Water Quality, Cyanobacteria, and Environmental Factors and Their Relations to Microcystin Concentrations for Use in Predictive Models at Ohio Lake Erie and Inland Lake Recreational Sites, 2013-14

USGS Publications Warehouse

Francy, Donna S.; Graham, Jennifer L.; Stelzer, Erin A.; Ecker, Christopher D.; Brady, Amie M. G.; Pam Struffolino,; Loftin, Keith A.

2015-11-06

The results of this study showed that water-quality and environmental variables are promising for use in site-specific daily or long-term predictive models. In order to develop more accurate models to predict toxin concentrations at freshwater lake sites, data need to be collected more frequently and for consecutive days in future studies.

Versatility of Cooperative Transcriptional Activation: A Thermodynamical Modeling Analysis for Greater-Than-Additive and Less-Than-Additive Effects

PubMed Central

Frank, Till D.; Carmody, Aimée M.; Kholodenko, Boris N.

2012-01-01

We derive a statistical model of transcriptional activation using equilibrium thermodynamics of chemical reactions. We examine to what extent this statistical model predicts synergy effects of cooperative activation of gene expression. We determine parameter domains in which greater-than-additive and less-than-additive effects are predicted for cooperative regulation by two activators. We show that the statistical approach can be used to identify different causes of synergistic greater-than-additive effects: nonlinearities of the thermostatistical transcriptional machinery and three-body interactions between RNA polymerase and two activators. In particular, our model-based analysis suggests that at low transcription factor concentrations cooperative activation cannot yield synergistic greater-than-additive effects, i.e., DNA transcription can only exhibit less-than-additive effects. Accordingly, transcriptional activity turns from synergistic greater-than-additive responses at relatively high transcription factor concentrations into less-than-additive responses at relatively low concentrations. In addition, two types of re-entrant phenomena are predicted. First, our analysis predicts that under particular circumstances transcriptional activity will feature a sequence of less-than-additive, greater-than-additive, and eventually less-than-additive effects when for fixed activator concentrations the regulatory impact of activators on the binding of RNA polymerase to the promoter increases from weak, to moderate, to strong. Second, for appropriate promoter conditions when activator concentrations are increased then the aforementioned re-entrant sequence of less-than-additive, greater-than-additive, and less-than-additive effects is predicted as well. Finally, our model-based analysis suggests that even for weak activators that individually induce only negligible increases in promoter activity, promoter activity can exhibit greater-than-additive responses when transcription factors and RNA polymerase interact by means of three-body interactions. Overall, we show that versatility of transcriptional activation is brought about by nonlinearities of transcriptional response functions and interactions between transcription factors, RNA polymerase and DNA. PMID:22506020

[Clinical and biological predictors of ketamine response in treatment-resistant major depression: Review].

PubMed

Romeo, B; Choucha, W; Fossati, P; Rotge, J-Y

2017-08-01

The aim of this review was to determine the clinical and biological predictors of the ketamine response. A systematic research on PubMed and PsycINFO database was performed without limits on year of publication. The main predictive factors of ketamine response, which were found in different studies, were (i) a family history of alcohol dependence, (ii) unipolar depressive disorder, and (iii) neurocognitive impairments, especially a slower processing speed. Many other predictive factors were identified, but not replicated, such as personal history of alcohol dependence, no antecedent of suicide attempt, anxiety symptoms. Some biological factors were also found such as markers of neural plasticity (slow wave activity, brain-derived neurotrophic factor Val66Met polymorphism, expression of Shank 3 protein), other neurologic factors (anterior cingulate activity, concentration of glutamine/glutamate), inflammatory factors (IL-6 concentration) or metabolic factors (concentration of B12 vitamin, D- and L-serine, alterations in the mitochondrial β-oxidation of fatty acids). This review had several limits: (i) patients had exclusively resistant major depressive episodes which represent a sub-type of depression and not all depression, (ii) response criteria were more frequently assessed than remission criteria, it was therefore difficult to conclude that these predictors were similar, and finally (iii) many studies used a very small number of patients. In conclusion, this review found that some predictors of ketamine response, like basal activity of anterior cingulate or vitamin B12 concentration, were identical to other therapeutics used in major depressive episode. These factors could be more specific to the major depressive episode and not to the ketamine response. Others, like family history of alcohol dependence, body mass index, or D- and L-serine were different from the other therapeutics. Neurocognitive impairments like slower speed processing or alterations in attention tests were also predictive to a good response. These predictive factors could be more specific to ketamine. With these different predictor factors (clinical and biological), it could be interesting to develop clinical strategies to personalize ketamine's administration. Copyright © 2016 L'Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.

Evaluation of MEGAN predicted biogenic isoprene emissions at urban locations in Southeast Texas

NASA Astrophysics Data System (ADS)

Kota, Sri Harsha; Schade, Gunnar; Estes, Mark; Boyer, Doug; Ying, Qi

2015-06-01

Summertime isoprene emissions in the Houston area predicted by the Model of Emissions of Gases and Aerosol from Nature (MEGAN) version 2.1 during the 2006 TexAQS study were evaluated using a source-oriented Community Multiscale Air Quality (CMAQ) Model. Predicted daytime isoprene concentrations at nine surface sites operated by the Texas Commission of Environmental Quality (TCEQ) were significantly higher than local observations when biogenic emissions dominate the total isoprene concentrations, with mean normalized bias (MNB) ranges from 2.0 to 7.7 and mean normalized error (MNE) ranges from 2.2 to 7.7. Predicted upper air isoprene and its first generation oxidation products of methacrolein (MACR) and methyl vinyl ketone (MVK) were also significantly higher (MNB = 8.6, MNE = 9.1) than observations made onboard of NOAA's WP-3 airplane, which flew over the urban area. Over-prediction of isoprene and its oxidation products both at the surface and the upper air strongly suggests that biogenic isoprene emissions in the Houston area are significantly overestimated. Reducing the emission rates by approximately 3/4 was necessary to reduce the error between predictions and observations. Comparison of gridded leaf area index (LAI), plant functional type (PFT) and gridded isoprene emission factor (EF) used in MEGAN modeling with estimates of the same factors from a field survey north of downtown Houston showed that the isoprene over-prediction is likely caused by the combined effects of a large overestimation of the gridded EF in urban Houston and an underestimation of urban LAI. Nevertheless, predicted ozone concentrations in this region were not significantly affected by the isoprene over-predictions, while predicted isoprene SOA and total SOA concentrations can be higher by as much as 50% and 13% using the higher isoprene emission rates, respectively.

Is the Factor-of-2 Rule Broadly Applicable for Evaluating the Prediction Accuracy of Metal-Toxicity Models?

PubMed

Meyer, Joseph S; Traudt, Elizabeth M; Ranville, James F

2018-01-01

In aquatic toxicology, a toxicity-prediction model is generally deemed acceptable if its predicted median lethal concentrations (LC50 values) or median effect concentrations (EC50 values) are within a factor of 2 of their paired, observed LC50 or EC50 values. However, that rule of thumb is based on results from only two studies: multiple LC50 values for the fathead minnow (Pimephales promelas) exposed to Cu in one type of exposure water, and multiple EC50 values for Daphnia magna exposed to Zn in another type of exposure water. We tested whether the factor-of-2 rule of thumb also is supported in a different dataset in which D. magna were exposed separately to Cd, Cu, Ni, or Zn. Overall, the factor-of-2 rule of thumb appeared to be a good guide to evaluating the acceptability of a toxicity model's underprediction or overprediction of observed LC50 or EC50 values in these acute toxicity tests.

Early pregnancy angiogenic markers and spontaneous abortion: an Odense Child Cohort study.

PubMed

Andersen, Louise B; Dechend, Ralf; Karumanchi, S Ananth; Nielsen, Jan; Joergensen, Jan S; Jensen, Tina K; Christesen, Henrik T

2016-11-01

Spontaneous abortion is the most commonly observed adverse pregnancy outcome. The angiogenic factors soluble Fms-like kinase 1 and placental growth factor are critical for normal pregnancy and may be associated to spontaneous abortion. We investigated the association between maternal serum concentrations of soluble Fms-like kinase 1 and placental growth factor, and subsequent spontaneous abortion. In the prospective observational Odense Child Cohort, 1676 pregnant women donated serum in early pregnancy, gestational week <22 (median 83 days of gestation, interquartile range 71-103). Concentrations of soluble Fms-like kinase 1 and placental growth factor were determined with novel automated assays. Spontaneous abortion was defined as complete or incomplete spontaneous abortion, missed abortion, or blighted ovum <22+0 gestational weeks, and the prevalence was 3.52% (59 cases). The time-dependent effect of maternal serum concentrations of soluble Fms-like kinase 1 and placental growth factor on subsequent late first-trimester or second-trimester spontaneous abortion (n = 59) was evaluated using a Cox proportional hazards regression model, adjusting for body mass index, parity, season of blood sampling, and age. Furthermore, receiver operating characteristics were employed to identify predictive values and optimal cut-off values. In the adjusted Cox regression analysis, increasing continuous concentrations of both soluble Fms-like kinase 1 and placental growth factor were significantly associated with a decreased hazard ratio for spontaneous abortion: soluble Fms-like kinase 1, 0.996 (95% confidence interval, 0.995-0.997), and placental growth factor, 0.89 (95% confidence interval, 0.86-0.93). When analyzed by receiver operating characteristic cut-offs, women with soluble Fms-like kinase 1 <742 pg/mL had an odds ratio for spontaneous abortion of 12.1 (95% confidence interval, 6.64-22.2), positive predictive value of 11.70%, negative predictive value of 98.90%, positive likelihood ratio of 3.64 (3.07-4.32), and negative likelihood ratio of 0.30 (0.19-0.48). For placental growth factor <19.7 pg/mL, odds ratio was 13.2 (7.09-24.4), positive predictive value was 11.80%, negative predictive value was 99.0%, positive likelihood ratio was 3.68 (3.12-4.34), and negative likelihood ratio was 0.28 (0.17-0.45). In the sensitivity analysis of 54 spontaneous abortions matched 1:4 to controls on gestational age at blood sampling, the highest area under the curve was seen for soluble Fms-like kinase 1 in prediction of first-trimester spontaneous abortion, 0.898 (0.834-0.962), and at the optimum cut-off of 725 pg/mL, negative predictive value was 51.4%, positive predictive value was 94.6%, positive likelihood ratio was 4.04 (2.57-6.35), and negative likelihood ratio was 0.22 (0.09-0.54). A strong, novel prospective association was identified between lower concentrations of soluble Fms-like kinase 1 and placental growth factor measured in early pregnancy and spontaneous abortion. A soluble Fms-like kinase 1 cut-off <742 pg/mL in maternal serum was optimal to stratify women at high vs low risk of spontaneous abortion. The cause and effect of angiogenic factor alterations in spontaneous abortions remain to be elucidated. Copyright © 2016 Elsevier Inc. All rights reserved.

Biological and behavioral factors modify urinary arsenic metabolic profiles in a U.S. population.

PubMed

Hudgens, Edward E; Drobna, Zuzana; He, Bin; Le, X C; Styblo, Miroslav; Rogers, John; Thomas, David J

2016-05-26

Because some adverse health effects associated with chronic arsenic exposure may be mediated by methylated arsenicals, interindividual variation in capacity to convert inorganic arsenic into mono- and di-methylated metabolites may be an important determinant of risk associated with exposure to this metalloid. Hence, identifying biological and behavioral factors that modify an individual's capacity to methylate inorganic arsenic could provide insights into critical dose-response relations underlying adverse health effects. A total of 904 older adults (≥45 years old) in Churchill County, Nevada, who chronically used home tap water supplies containing up to 1850 μg of arsenic per liter provided urine and toenail samples for determination of total and speciated arsenic levels. Effects of biological factors (gender, age, body mass index) and behavioral factors (smoking, recent fish or shellfish consumption) on patterns of arsenicals in urine were evaluated with bivariate analyses and multivariate regression models. Relative contributions of inorganic, mono-, and di-methylated arsenic to total speciated arsenic in urine were unchanged over the range of concentrations of arsenic in home tap water supplies used by study participants. Gender predicted both absolute and relative amounts of arsenicals in urine. Age predicted levels of inorganic arsenic in urine and body mass index predicted relative levels of mono- and di-methylated arsenic in urine. Smoking predicted both absolute and relative levels of arsenicals in urine. Multivariate regression models were developed for both absolute and relative levels of arsenicals in urine. Concentration of arsenic in home tap water and estimated water consumption were strongly predictive of levels of arsenicals in urine as were smoking, body mass index, and gender. Relative contributions of arsenicals to urinary arsenic were not consistently predicted by concentrations of arsenic in drinking water supplies but were more consistently predicted by gender, body mass index, age, and smoking. These findings suggest that analyses of dose-response relations in arsenic-exposed populations should account for biological and behavioral factors that modify levels of inorganic and methylated arsenicals in urine. Evidence of significant effects of these factors on arsenic metabolism may also support mode of action studies in appropriate experimental models.

Modeling the rheological behavior of thermosonic extracted guava, pomelo, and soursop juice concentrates at different concentration and temperature using a new combination model

PubMed Central

Abdullah, Norazlin; Yusof, Yus A.; Talib, Rosnita A.

2017-01-01

Abstract This study has modeled the rheological behavior of thermosonic extracted pink‐fleshed guava, pink‐fleshed pomelo, and soursop juice concentrates at different concentrations and temperatures. The effects of concentration on consistency coefficient (K) and flow behavior index (n) of the fruit juice concentrates was modeled using a master curve which utilized the concentration‐temperature shifting to allow a general prediction of rheological behaviors covering a wide concentration. For modeling the effects of temperature on K and n, the integration of two functions from the Arrhenius and logistic sigmoidal growth equations has provided a new model which gave better description of the properties. It also alleviated the problems of negative region when using the Arrhenius model alone. The fitted regression using this new model has improved coefficient of determination, R 2 values above 0.9792 as compared to using the Arrhenius and logistic sigmoidal models alone, which presented minimum R 2 of 0.6243 and 0.9440, respectively. Practical applications In general, juice concentrate is a better form of food for transportation, preservation, and ingredient. Models are necessary to predict the effects of processing factors such as concentration and temperature on the rheological behavior of juice concentrates. The modeling approach allows prediction of behaviors and determination of processing parameters. The master curve model introduced in this study simplifies and generalized rheological behavior of juice concentrates over a wide range of concentration when temperature factor is insignificant. The proposed new mathematical model from the combination of the Arrhenius and logistic sigmoidal growth models has improved and extended description of rheological properties of fruit juice concentrates. It also solved problems of negative values of consistency coefficient and flow behavior index prediction using existing model, the Arrhenius equation. These rheological data modeling provide good information for the juice processing and equipment manufacturing needs. PMID:29479123

Predictive blood plasma biomarkers for EGFR inhibitor-induced skin rash.

PubMed

Hichert, Vivien; Scholl, Catharina; Steffens, Michael; Paul, Tanusree; Schumann, Christian; Rüdiger, Stefan; Boeck, Stefan; Heinemann, Volker; Kächele, Volker; Seufferlein, Thomas; Stingl, Julia

2017-05-23

Epidermal growth factor receptor overexpression in human cancer can be effectively targeted by drugs acting as specific inhibitors of the receptor, like erlotinib, gefitinib, cetuximab and panitumumab. A common adverse effect is a typical papulopustular acneiform rash, whose occurrence and severity are positively correlated with overall survival in several cancer types. We studied molecules involved in epidermal growth factor receptor signaling which are quantifiable in plasma, with the aim of identifying biomarkers for the severity of rash. With a predictive value for the rash these biomarkers may also have a prognostic value for survival and disease outcome.The concentrations of amphiregulin, hepatocyte growth factor (HGF) and calcidiol were determined by specific enzyme-linked immunosorbent assays in plasma samples from 211 patients.We observed a significant inverse correlation between the plasma concentration of HGF and overall survival in patients with an inhibitor-induced rash (p-value = 0.0075; mean overall survival low HGF: 299 days, high HGF: 240 days) but not in patients without rash. The concentration of HGF was also significantly inversely correlated with severity of rash (p-value = 0.00124).High levels of HGF lead to increased signaling via its receptor MET, which can activate numerous pathways which are normally also activated by epidermal growth factor receptor. Increased HGF/MET signaling might compensate the inhibitory effect of epidermal growth factor receptor inhibitors in skin as well as tumor cells, leading to less severe skin rash and decreased efficacy of the anti-tumor therapy, rendering the plasma concentration of HGF a candidate for predictive biomarkers.

Femtosecond laser micromachining of compound parabolic concentrator fiber tipped glucose sensors.

PubMed

Hassan, Hafeez Ul; Lacraz, Amédée; Kalli, Kyriacos; Bang, Ole

2017-03-01

We report on highly accurate femtosecond (fs) laser micromachining of a compound parabolic concentrator (CPC) fiber tip on a polymer optical fiber (POF). The accuracy is reflected in an unprecedented correspondence between the numerically predicted and experimentally found improvement in fluorescence pickup efficiency of a Förster resonance energy transfer-based POF glucose sensor. A Zemax model of the CPC-tipped sensor predicts an optimal improvement of a factor of 3.96 compared to the sensor with a plane-cut fiber tip. The fs laser micromachined CPC tip showed an increase of a factor of 3.5, which is only 11.6% from the predicted value. Earlier state-of-the-art fabrication of the CPC-shaped tip by fiber tapering was of so poor quality that the actual improvement was 43% lower than the predicted improvement of the ideal CPC shape.

Femtosecond laser micromachining of compound parabolic concentrator fiber tipped glucose sensors

NASA Astrophysics Data System (ADS)

Hassan, Hafeez Ul; Lacraz, Amédée; Kalli, Kyriacos; Bang, Ole

2017-03-01

We report on highly accurate femtosecond (fs) laser micromachining of a compound parabolic concentrator (CPC) fiber tip on a polymer optical fiber (POF). The accuracy is reflected in an unprecedented correspondence between the numerically predicted and experimentally found improvement in fluorescence pickup efficiency of a Förster resonance energy transfer-based POF glucose sensor. A Zemax model of the CPC-tipped sensor predicts an optimal improvement of a factor of 3.96 compared to the sensor with a plane-cut fiber tip. The fs laser micromachined CPC tip showed an increase of a factor of 3.5, which is only 11.6% from the predicted value. Earlier state-of-the-art fabrication of the CPC-shaped tip by fiber tapering was of so poor quality that the actual improvement was 43% lower than the predicted improvement of the ideal CPC shape.

Use of a food web model to evaluate the factors responsible for high PCB fish concentrations in Lake Ellasjøen, a high arctic lake.

PubMed

Gewurtz, Sarah B; Gandhi, Nilima; Christensen, Guttorm N; Evenset, Anita; Gregor, Dennis; Diamond, Miriam L

2009-03-01

Lake Ellasjøen, located in the Norwegian high arctic, contains the highest concentrations of polychlorinated biphenyls (PCBs) ever recorded in fish and sediment from high arctic lakes, and concentrations are more than 10 times greater than in nearby Lake Øyangen. These elevated concentrations in Ellasjøen have been previously attributed, in part, to contaminant loadings from seabirds that use Ellasjøen, but not Øyangen, as a resting area. However, other factors, such as food web structure, organism growth rate, weight, lipid content, lake morphology, and nutrient inputs from the seabird guano, also differ between the two systems. The aim of this study is to evaluate the relative influence of these factors as explanatory variables for the higher PCB fish concentrations in Ellasjøen compared with Øyangen, using both a food web model and empirical data. The model is based on previously developed models but parameterized for Lakes Ellasjøen and Øyangen using measured data wherever possible. The model was applied to five representative PCB congeners (PCB 105, 118, 138, 153, and 180) using measured sediment and water concentrations as input data and evaluated with previously collected food web data. Modeled concentrations are within a factor of two of measured concentrations in 60% and 40% of the cases in Lakes Ellasjøen and Øyangen, respectively, and within a factor of 10 in 100% of the cases in both lakes. In many cases, this is comparable to the variability associated with the data as well as the efficacy of the predictions of other food web model applications. We next used the model to quantify the relative importance of five major differences between Ellasjøen and Øyangen by replacing variables representing each of these factors in the Ellasjøen model with those from Øyangen, in separate simulations. The model predicts that the elevated PCB concentrations in Ellasjøen water and sediment account for 49%-58% of differences in modeled fish PCB concentrations between lakes. These elevated sediment and, to a lesser extent, water concentrations in Ellasjøen are due to PCB loadings from seabird guano. However, sediment-water fugacity ratios of PCBs are consistently greater in Ellasjøen compared with Øyangen, which suggests that internal lake processes also contribute to differences in sediment and water concentrations. We hypothesize that the nutrients associated with guano influence sediment-water fugacity ratios of PCBs by increasing the stock of pelagic algae. As both these algae and the guano settle, their organic carbon content is degraded faster than PCBs, which causes an extra magnification step in Ellasjøen before these detrital particles are consumed by benthic organisms, which are in turn consumed by fish. The model predicts that the remaining approximately 50% of the differences in PCB concentrations observed between the fish of these lakes are due to other subtle differences in their food web structures. In conclusion, based on the results of a food web model, we found that the most dominant factors influencing the higher PCB fish concentrations in Lake Ellasjøen compared with Øyangen are the higher sediment and water concentrations in Ellasjøen, caused by seabird guano. Together, sediment and water are predicted to account for 49%-58% of differences in fish concentrations between lakes. Although seabird guano provides a source of nutrients to the lake, in addition to contaminants, empirical data and indirect model results suggest that nutrients are not leading to decreased bioaccumulation, in contrast to what has been observed in temperate, pelagic food webs. The results of this study emphasize the importance of considering even small differences in food web structure when comparing bioaccumulation in two lakes; although the food web structures of Ellasjøen and Øyangen differ only slightly, the model predicts that these differences account for most of the remaining approximately 50% of the differences in PCB fish concentrations between the two lakes. This study further demonstrates the utility of food web models as we were able to predict and tease apart the influence of various factors responsible for the elevated concentrations in the fish from Lake Ellasjøen, which would have been difficult using the field data alone.

Empirical evaluation of spatial and non-spatial European-scale multimedia fate models: results and implications for chemical risk assessment.

PubMed

Armitage, James M; Cousins, Ian T; Hauck, Mara; Harbers, Jasper V; Huijbregts, Mark A J

2007-06-01

Multimedia environmental fate models are commonly-applied tools for assessing the fate and distribution of contaminants in the environment. Owing to the large number of chemicals in use and the paucity of monitoring data, such models are often adopted as part of decision-support systems for chemical risk assessment. The purpose of this study was to evaluate the performance of three multimedia environmental fate models (spatially- and non-spatially-explicit) at a European scale. The assessment was conducted for four polycyclic aromatic hydrocarbons (PAHs) and hexachlorobenzene (HCB) and compared predicted and median observed concentrations using monitoring data collected for air, water, sediments and soils. Model performance in the air compartment was reasonable for all models included in the evaluation exercise as predicted concentrations were typically within a factor of 3 of the median observed concentrations. Furthermore, there was good correspondence between predictions and observations in regions that had elevated median observed concentrations for both spatially-explicit models. On the other hand, all three models consistently underestimated median observed concentrations in sediment and soil by 1-3 orders of magnitude. Although regions with elevated median observed concentrations in these environmental media were broadly identified by the spatially-explicit models, the magnitude of the discrepancy between predicted and median observed concentrations is of concern in the context of chemical risk assessment. These results were discussed in terms of factors influencing model performance such as the steady-state assumption, inaccuracies in emission estimates and the representativeness of monitoring data.

Predictors of response to a low-FODMAP diet in patients with functional gastrointestinal disorders and lactose or fructose intolerance.

PubMed

Wilder-Smith, C H; Olesen, S S; Materna, A; Drewes, A M

2017-04-01

Diets low in fermentable sugars (low-FODMAP diets) are increasingly adopted by patients with functional gastrointestinal disorders (FGID), but outcome predictors are unclear. To identify factors predictive of an efficacious response to a low-FODMAP diet in FGID patients with fructose or lactose intolerance thereby gaining insights into underlying mechanisms. Fructose and lactose breath tests were performed in FGID patients to determine intolerance (positive symptom score) and malabsorption (increased hydrogen or methane concentrations). Patients with fructose or lactose intolerance consumed a low-FODMAP diet and global adequate symptom relief was assessed after 6-8 weeks and correlated with pre-diet clinical symptoms and breath test results. A total of 81% of 584 patients completing the low-FODMAP diet achieved adequate relief, without significant differences between FGID subgroups or types of intolerance. Univariate analysis yielded predictive factors in fructose intolerance (chronic diarrhoea and pruritus, peak methane concentrations and fullness during breath tests) and lactose intolerance (peak hydrogen and methane concentrations and flatulence during breath tests). Using multivariate analysis, symptom relief was independently and positively predicted in fructose intolerance by chronic diarrhoea [odds ratio (95% confidence intervals): 2.62 (1.31-5.27), P = 0.007] and peak breath methane concentrations [1.53 (1.02-2.29), P = 0.042], and negatively predicted by chronic nausea [0.33 (0.16-0.67), P = 0.002]. No independent predictive factors emerged for lactose intolerance. Adequate global symptom relief was achieved with a low-FODMAP diet in a large majority of functional gastrointestinal disorders patients with fructose or lactose intolerance. Independent predictors of a satisfactory dietary outcome were only seen in fructose intolerant patients, and were indicative of changes in intestinal host or microbiome metabolism. © 2017 John Wiley & Sons Ltd.

Urinary Sodium Concentration Is an Independent Predictor of All-Cause and Cardiovascular Mortality in a Type 2 Diabetes Cohort Population

PubMed Central

Gand, Elise; Ragot, Stéphanie; Bankir, Lise; Piguel, Xavier; Fumeron, Frédéric; Halimi, Jean-Michel; Marechaud, Richard; Roussel, Ronan; Hadjadj, Samy; Study group, SURDIAGENE

2017-01-01

Objective. Sodium intake is associated with cardiovascular outcomes. However, no study has specifically reported an association between cardiovascular mortality and urinary sodium concentration (UNa). We examined the association of UNa with mortality in a cohort of type 2 diabetes (T2D) patients. Methods. Patients were followed for all-cause death and cardiovascular death. Baseline UNa was measured from second morning spot urinary sample. We used Cox proportional hazard models to identify independent predictors of mortality. Improvement in prediction of mortality by the addition of UNa to a model including known risk factors was assessed by the relative integrated discrimination improvement (rIDI) index. Results. Participants (n = 1,439) were followed for a median of 5.7 years, during which 254 cardiovascular deaths and 429 all-cause deaths were recorded. UNa independently predicted all-cause and cardiovascular mortality. An increase of one standard deviation of UNa was associated with a decrease of 21% of all-cause mortality and 22% of cardiovascular mortality. UNa improved all-cause and cardiovascular mortality prediction beyond identified risk factors (rIDI = 2.8%, P = 0.04 and rIDI = 4.6%, P = 0.02, resp.). Conclusions. In T2D, UNa was an independent predictor of mortality (low concentration is associated with increased risk) and improved modestly its prediction in addition to traditional risk factors. PMID:28255559

A primer on trace metal-sediment chemistry

USGS Publications Warehouse

Horowitz, Arthur J.

1985-01-01

In most aquatic systems, concentrations of trace metals in suspended sediment and the top few centimeters of bottom sediment are far greater than concentrations of trace metals dissolved in the water column. Consequently, the distribution, transport, and availability of these constituents can not be intelligently evaluated, nor can their environmental impact be determined or predicted solely through the sampling and analysis of dissolved phases. This Primer is designed to acquaint the reader with the basic principles that govern the concentration and distribution of trace metals associated with bottom and suspended sediments. The sampling and analysis of suspended and bottom sediments are very important for monitoring studies, not only because trace metal concentrations associated with them are orders of magnitude higher than in the dissolved phase, but also because of several other factors. Riverine transport of trace metals is dominated by sediment. In addition, bottom sediments serve as a source for suspended sediment and can provide a historical record of chemical conditions. This record will help establish area baseline metal levels against which existing conditions can be compared. Many physical and chemical factors affect a sediment's capacity to collect and concentrate trace metals. The physical factors include grain size, surface area, surface charge, cation exchange capacity, composition, and so forth. Increases in metal concentrations are strongly correlated with decreasing grain size and increasing surface area, surface charge, cation exchange capacity, and increasing concentrations of iron and manganese oxides, organic matter, and clay minerals. Chemical factors are equally important, especially for differentiating between samples having similar bulk chemistries and for inferring or predicting environmental availability. Chemical factors entail phase associations (with such sedimentary components as interstitial water, sulfides, carbonates, and organic matter) and ways in which the metals are entrained by the sediments (such as adsorption, complexation, and within mineral lattices).

Predictive factors for poor prognosis febrile neutropenia.

PubMed

Ahn, Shin; Lee, Yoon-Seon

2012-07-01

Most patients with chemotherapy-induced febrile neutropenia recover rapidly without serious complications. However, it still remains a life-threatening treatment-related toxicity, and is associated with dose reductions and delays of chemotherapeutic agents that may compromise treatment outcomes. Recent developments of risk stratification enabled early discharge with oral antibiotics for low-risk patients. However, even in low-risk patients, medical complications including bacteremia could happen. The authors reviewed recent literature to provide an update on research regarding predictive factors for poor prognosis in patients with febrile neutropenia. Various prognostic factors have been suggested with controversies. Hematological parameters, prophylactic measurements and patient-specific risk factors showed inconsistent results. MASCC risk-index score, which was originally developed to identify low-risk patients, in turn showed that the lower the MASCC score, the poorer the prognosis of febrile neutropenia, with very low levels (<15), the rate of complications was high. Patients with severe sepsis and septic shock commonly had procalcitonin concentration above 2.0 ng/ml, and this level should be considered at high risk of poor prognosis. Lower MASCC score and higher procalcitonin concentration can predict poor outcomes in febrile neutropenia. More research is required with regard to the other factors showing controversies.

Radionuclide concentration processes in marine organisms: A comprehensive review.

PubMed

Carvalho, Fernando P

2018-06-01

The first measurements made of artificial radionuclides released into the marine environment did reveal that radionuclides are concentrated by marine biological species. The need to report radionuclide accumulation in biota in different conditions and geographical areas prompted the use of concentration factors as a convenient way to describe the accumulation of radionuclides in biota relative to radionuclide concentrations in seawater. Later, concentration factors became a tool in modelling radionuclide distribution and transfer in aquatic environments and to predicting radioactivity in organisms. Many environmental parameters can modify the biokinetics of accumulation and elimination of radionuclides in marine biota, but concentration factors remained a convenient way to describe concentration processes of radioactive and stable isotopes in aquatic organisms. Revision of CF values is periodically undertaken by international organizations, such as the International Atomic Energy Agency (IAEA), to make updated information available to the international community. A brief commented review of radionuclide concentration processes and concentration factors in marine organisms is presented for key groups of radionuclides such as fission products, activation products, transuranium elements, and naturally-occurring radionuclides. Copyright © 2017 Elsevier Ltd. All rights reserved.

Predicting the Poaceae pollen season: six month-ahead forecasting and identification of relevant features

NASA Astrophysics Data System (ADS)

Navares, Ricardo; Aznarte, José Luis

2017-04-01

In this paper, we approach the problem of predicting the concentrations of Poaceae pollen which define the main pollination season in the city of Madrid. A classification-based approach, based on a computational intelligence model (random forests), is applied to forecast the dates in which risk concentration levels are to be observed. Unlike previous works, the proposal extends the range of forecasting horizons up to 6 months ahead. Furthermore, the proposed model allows to determine the most influential factors for each horizon, making no assumptions about the significance of the weather features. The performace of the proposed model proves it as a successful tool for allergy patients in preventing and minimizing the exposure to risky pollen concentrations and for researchers to gain a deeper insight on the factors driving the pollination season.

Predicting the Poaceae pollen season: six month-ahead forecasting and identification of relevant features.

PubMed

Navares, Ricardo; Aznarte, José Luis

2017-04-01

In this paper, we approach the problem of predicting the concentrations of Poaceae pollen which define the main pollination season in the city of Madrid. A classification-based approach, based on a computational intelligence model (random forests), is applied to forecast the dates in which risk concentration levels are to be observed. Unlike previous works, the proposal extends the range of forecasting horizons up to 6 months ahead. Furthermore, the proposed model allows to determine the most influential factors for each horizon, making no assumptions about the significance of the weather features. The performace of the proposed model proves it as a successful tool for allergy patients in preventing and minimizing the exposure to risky pollen concentrations and for researchers to gain a deeper insight on the factors driving the pollination season.

Estimating Time-Varying PCB Exposures Using Person-Specific Predictions to Supplement Measured Values: A Comparison of Observed and Predicted Values in Two Cohorts of Norwegian Women.

PubMed

Nøst, Therese Haugdahl; Breivik, Knut; Wania, Frank; Rylander, Charlotta; Odland, Jon Øyvind; Sandanger, Torkjel Manning

2016-03-01

Studies on the health effects of polychlorinated biphenyls (PCBs) call for an understanding of past and present human exposure. Time-resolved mechanistic models may supplement information on concentrations in individuals obtained from measurements and/or statistical approaches if they can be shown to reproduce empirical data. Here, we evaluated the capability of one such mechanistic model to reproduce measured PCB concentrations in individual Norwegian women. We also assessed individual life-course concentrations. Concentrations of four PCB congeners in pregnant (n = 310, sampled in 2007-2009) and postmenopausal (n = 244, 2005) women were compared with person-specific predictions obtained using CoZMoMAN, an emission-based environmental fate and human food-chain bioaccumulation model. Person-specific predictions were also made using statistical regression models including dietary and lifestyle variables and concentrations. CoZMoMAN accurately reproduced medians and ranges of measured concentrations in the two study groups. Furthermore, rank correlations between measurements and predictions from both CoZMoMAN and regression analyses were strong (Spearman's r > 0.67). Precision in quartile assignments from predictions was strong overall as evaluated by weighted Cohen's kappa (> 0.6). Simulations indicated large inter-individual differences in concentrations experienced in the past. The mechanistic model reproduced all measurements of PCB concentrations within a factor of 10, and subject ranking and quartile assignments were overall largely consistent, although they were weak within each study group. Contamination histories for individuals predicted by CoZMoMAN revealed variation between study subjects, particularly in the timing of peak concentrations. Mechanistic models can provide individual PCB exposure metrics that could serve as valuable supplements to measurements.

Prediction of sub-surface 37 Ar concentrations at locations in the Northwestern United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fritz, Bradley G.; Aalseth, Craig E.; Back, Henning O.

The Comprehensive Nuclear Test-Ban Treaty, which is intended to prevent nuclear weapon testing, includes a verification regime, which provides monitoring to identify potential nuclear testing. The presence of elevated 37Ar is one way to identify subsurface nuclear testing. However, the naturally occurring formation of 37Ar in the subsurface adds a complicating factor. Prediction of the naturally occurring concentration of 37Ar can help to determine if a measured 37Ar concentration is elevated. The naturally occurring 37Ar background concentration has been shown to vary between less than 1 mBq/m3 to greater than 100 mBq/m3 (Riedmann and Purtschert 2011). Here, we evaluate amore » model for predicting the average concentration of 37Ar at any depth under transient barometric pressures, and compare it with measurements. This model is shown to compare favorably with concentrations of 37Ar measured at multiple locations in the Northwestern United States.« less

Meteorological influence on predicting surface SO2 concentration from satellite remote sensing in Shanghai, China.

PubMed

Xue, Dan; Yin, Jingyuan

2014-05-01

In this study, we explored the potential applications of the Ozone Monitoring Instrument (OMI) satellite sensor in air pollution research. The OMI planetary boundary layer sulfur dioxide (SO2_PBL) column density and daily average surface SO2 concentration of Shanghai from 2004 to 2012 were analyzed. After several consecutive years of increase, the surface SO2 concentration finally declined in 2007. It was higher in winter than in other seasons. The coefficient between daily average surface SO2 concentration and SO2_PBL was only 0.316. But SO2_PBL was found to be a highly significant predictor of the surface SO2 concentration using the simple regression model. Five meteorological factors were considered in this study, among them, temperature, dew point, relative humidity, and wind speed were negatively correlated with surface SO2 concentration, while pressure was positively correlated. Furthermore, it was found that dew point was a more effective predictor than temperature. When these meteorological factors were used in multiple regression, the determination coefficient reached 0.379. The relationship of the surface SO2 concentration and meteorological factors was seasonally dependent. In summer and autumn, the regression model performed better than in spring and winter. The surface SO2 concentration predicting method proposed in this study can be easily adapted for other regions, especially most useful for those having no operational air pollution forecasting services or having sparse ground monitoring networks.

Learning and Study Strategies Inventory subtests and factors as predictors of National Board of Chiropractic Examiners Part 1 examination performance.

PubMed

Schutz, Christine M; Dalton, Leanne; Tepe, Rodger E

2013-01-01

This study was designed to extend research on the relationship between chiropractic students' learning and study strategies and national board examination performance. Sixty-nine first trimester chiropractic students self-administered the Learning and Study Strategies Inventory (LASSI). Linear trends tests (for continuous variables) and Mantel-Haenszel trend tests (for categorical variables) were utilized to determine if the 10 LASSI subtests and 3 factors predicted low, medium and high levels of National Board of Chiropractic Examiners (NBCE) Part 1 scores. Multiple regression was performed to predict overall mean NBCE examination scores using the 3 LASSI factors as predictor variables. Four LASSI subtests (Anxiety, Concentration, Selecting Main Ideas, Test Strategies) and one factor (Goal Orientation) were significantly associated with NBCE examination levels. One factor (Goal Orientation) was a significant predictor of overall mean NBCE examination performance. Learning and study strategies are predictive of NBCE Part 1 examination performance in chiropractic students. The current study found LASSI subtests Anxiety, Concentration, Selecting Main Ideas, and Test Strategies, and the Goal-Orientation factor to be significant predictors of NBCE scores. The LASSI may be useful to educators in preparing students for academic success. Further research is warranted to explore the effects of learning and study strategies training on GPA and NBCE performance.

Stability of colloidal gold and determination of the Hamaker constant

DOE Office of Scientific and Technical Information (OSTI.GOV)

Demirci, S.; Enuestuen, B.V.; Turkevich, J.

1978-12-14

Previous computation of stability factors of colloidal gold from coagulation data was found to be in systematic error due to an underestimation of the particle concentration by electron microscopy. A new experimental technique was developed for determination of this concentration. Stability factors were recalculated from the previous data using the correct concentration. While most of the previously reported conclusions remain unchanged, the absolute rate of fast coagulation is found to agree with that predicted by the theory. A value of the Hamaker constant was determined from the corrected data.

High serum uric acid concentration predicts poor survival in patients with breast cancer.

PubMed

Yue, Cai-Feng; Feng, Pin-Ning; Yao, Zhen-Rong; Yu, Xue-Gao; Lin, Wen-Bin; Qian, Yuan-Min; Guo, Yun-Miao; Li, Lai-Sheng; Liu, Min

2017-10-01

Uric acid is a product of purine metabolism. Recently, uric acid has gained much attraction in cancer. In this study, we aim to investigate the clinicopathological and prognostic significance of serum uric acid concentration in breast cancer patients. A total of 443 female patients with histopathologically diagnosed breast cancer were included. After a mean follow-up time of 56months, survival was analysed using the Kaplan-Meier method. To further evaluate the prognostic significance of uric acid concentrations, univariate and multivariate Cox regression analyses were applied. Of the clinicopathological parameters, uric acid concentration was associated with age, body mass index, ER status and PR status. Univariate analysis identified that patients with increased uric acid concentration had a significantly inferior overall survival (HR 2.13, 95% CI 1.15-3.94, p=0.016). In multivariate analysis, we found that high uric acid concentration is an independent prognostic factor predicting death, but insufficient to predict local relapse or distant metastasis. Kaplan-Meier analysis indicated that high uric acid concentration is related to the poor overall survival (p=0.013). High uric acid concentration predicts poor survival in patients with breast cancer, and might serve as a potential marker for appropriate management of breast cancer patients. Copyright © 2017 Elsevier B.V. All rights reserved.

Predicting glycogen concentration in the foot muscle of abalone using near infrared reflectance spectroscopy (NIRS).

PubMed

Fluckiger, Miriam; Brown, Malcolm R; Ward, Louise R; Moltschaniwskyj, Natalie A

2011-06-15

Near infrared reflectance spectroscopy (NIRS) was used to predict glycogen concentrations in the foot muscle of cultured abalone. NIR spectra of live, shucked and freeze-dried abalones were modelled against chemically measured glycogen data (range: 0.77-40.9% of dry weight (DW)) using partial least squares (PLS) regression. The calibration models were then used to predict glycogen concentrations of test abalone samples and model robustness was assessed from coefficient of determination of the validation (R2(val)) and standard error of prediction (SEP) values. The model for freeze-dried abalone gave the best prediction (R2(val) 0.97, SEP=1.71), making it suitable for quantifying glycogen. Models for live and shucked abalones had R2(val) of 0.86 and 0.90, and SEP of 3.46 and 3.07 respectively, making them suitable for producing estimations of glycogen concentration. As glycogen is a taste-active component associated with palatability in abalone, this study demonstrated the potential of NIRS as a rapid method to monitor the factors associated with abalone quality. Copyright © 2011 Elsevier Ltd. All rights reserved.

Characterization of air pollutant concentrations, fleet emission factors, and dispersion near a North Carolina interstate freeway across two seasons

NASA Astrophysics Data System (ADS)

Saha, Provat K.; Khlystov, Andrey; Snyder, Michelle G.; Grieshop, Andrew P.

2018-03-01

We present field measurement data and modeling of multiple traffic-related air pollutants during two seasons at a site adjoining Interstate 40, near Durham, North Carolina. We analyze spatial-temporal and seasonal trends and fleet-average pollutant emission factors and use our data to evaluate a line source dispersion model. Month-long measurement campaigns were performed in summer 2015 and winter 2016. Data were collected at a fixed near-road site located within 10 m from the highway edge, an upwind background site and, under favorable meteorological conditions, along downwind perpendicular transects. Measurements included the size distribution, chemical composition, and volatility of submicron particles, black carbon (BC), nitrogen oxides (NOx), meteorological conditions and traffic activity data. Results show strong seasonal and diurnal differences in spatial distribution of traffic sourced pollutants. A strong signature of vehicle emissions was observed within 100-150 m from the highway edge with significantly higher concentrations during morning. Substantially higher concentrations and less-sharp near-road gradients were observed in winter for many species. Season-specific fleet-average fuel-based emission factors for NO, NOx, BC, and particle number (PN) were derived based on up- and down-wind roadside measurements. The campaign-average NOx and PN emission factors were 20% and 300% higher in winter than summer, respectively. These results suggest that the combined effect of higher emissions and their slower downwind dispersion in winter dictate the observed higher downwind concentrations and wider highway influence zone in winter for several species. Finally, measurements of traffic data, emission factors, and pollutant concentrations were integrated to evaluate a line source dispersion model (R-LINE). The dispersion model captured the general trends in the spatial and temporal patterns in near-road concentrations. However, there was a tendency for the model to under-predict concentrations near the road in the mornings and over-predict concentrations in the evenings.

Development and evaluation of a semi-empirical two-zone dust exposure model for a dusty construction trade.

PubMed

Jones, Rachael M; Simmons, Catherine; Boelter, Fred

2011-06-01

Drywall finishing is a dusty construction activity. We describe a mathematical model that predicts the time-weighted average concentration of respirable and total dusts in the personal breathing zone of the sander, and in the area surrounding joint compound sanding activities. The model represents spatial variation in dust concentrations using two-zones, and temporal variation using an exponential function. Interzone flux and the relationships between respirable and total dusts are described using empirical factors. For model evaluation, we measured dust concentrations in two field studies, including three workers from a commercial contracting crew, and one unskilled worker. Data from the field studies confirm that the model assumptions and parameterization are reasonable and thus validate the modeling approach. Predicted dust C(twa) were in concordance with measured values for the contracting crew, but under estimated measured values for the unskilled worker. Further characterization of skill-related exposure factors is indicated.

Cytokine activation is predictive of mortality in Zambian patients with AIDS-related diarrhoea.

PubMed

Zulu, Isaac; Hassan, Ghaniah; Njobvu R N, Lungowe; Dhaliwal, Winnie; Sianongo, Sandie; Kelly, Paul

2008-11-13

Mortality in Zambian AIDS patients is high, especially in patients with diarrhoea, and there is still unacceptably high mortality in Zambian patients just starting anti-retroviral therapy. We set out to determine if high concentrations of serum cytokines correlate with mortality. Serum samples from 30 healthy controls (HIV seropositive and seronegative) and 50 patients with diarrhoea (20 of whom died within 6 weeks) were analysed. Concentrations of tumour necrosis factor receptor p55 (TNFR p55), macrophage migration inhibitory factor (MIF), interleukin (IL)-6, IL-12, interferon (IFN)-gamma and C-reactive protein (CRP) were measured by ELISA, and correlated with mortality after 6 weeks follow-up. Apart from IL-12, concentrations of all cytokines, TNFR p55 and CRP increased with worsening severity of disease, showing highly statistically significant trends. In a multivariable analysis high TNFR p55, IFN-gamma, CRP and low CD4 count (CD4 count <100) were predictive of mortality. Although nutritional status (assessed by body mass index, BMI) was predictive in univariate analysis, it was not an independent predictor in multivariate analysis. High serum concentrations of TNFR p55, IFN-gamma, CRP and low CD4 count correlated with disease severity and short-term mortality in HIV-infected Zambian adults with diarrhoea. These factors were better predictors of survival than BMI. Understanding the cause of TNFR p55, IFN-gamma and CRP elevation may be useful in development of interventions to reduce mortality in AIDS patients with chronic diarrhoea in Africa.

Concentration of folate in colorectal tissue biopsies predicts prevalence of adenomatous polyps

USDA-ARS?s Scientific Manuscript database

Background and aims: Folate has been implicated as a potential aetiological factor for colorectal cancer. Previous research has not adequately exploited concentrations of folate in normal colonic mucosal biopsies to examine the issue. Methods: Logistic regression models were used to estimate ORs ...

Neural network model for the prediction of PM10 daily concentrations in two sites in the Western Mediterranean.

PubMed

de Gennaro, Gianluigi; Trizio, Livia; Di Gilio, Alessia; Pey, Jorge; Pérez, Noemi; Cusack, Michael; Alastuey, Andrés; Querol, Xavier

2013-10-01

An artificial neural network (ANN) was developed and tested to forecast PM10 daily concentration in two contrasted environments in NE Spain, a regional background site (Montseny), and an urban background site (Barcelona-CSIC), which was highly influenced by vehicular emissions. In order to predict 24-h average PM10 concentrations, the artificial neural network previously developed by Caselli et al. (2009) was improved by using hourly PM concentrations and deterministic factors such as a Saharan dust alert. In particular, the model input data for prediction were the hourly PM10 concentrations 1-day in advance, local meteorological data and information about air masses origin. The forecasted performance indexes for both sites were calculated and they showed better results for the regional background site in Montseny (R(2)=0.86, SI=0.75) than for urban site in Barcelona (R(2)=0.73, SI=0.58), influenced by local and sometimes unexpected sources. Moreover, a sensitivity analysis conducted to understand the importance of the different variables included among the input data, showed that local meteorology and air masses origin are key factors in the model forecasts. This result explains the reason for the improvement of ANN's forecasting performance at the Montseny site with respect to the Barcelona site. Moreover, the artificial neural network developed in this work could prove useful to predict PM10 concentrations, especially, at regional background sites such as those on the Mediterranean Basin which are primarily affected by long-range transports. Hence, the artificial neural network presented here could be a powerful tool for obtaining real time information on air quality status and could aid stakeholders in their development of cost-effective control strategies. © 2013 Elsevier B.V. All rights reserved.

Prediction of sub-surface 37Ar concentrations at locations in the Northwestern United States.

PubMed

Fritz, Bradley G; Aalseth, Craig E; Back, Henning O; Hayes, James C; Humble, Paul H; Ivanusa, Pavlo; Mace, Emily K

2018-01-01

The Comprehensive Nuclear-Test-Ban Treaty, which is intended to prevent nuclear weapon test explosions and any other nuclear explosions, includes a verification regime, which provides monitoring to identify potential nuclear explosions. The presence of elevated 37 Ar is one way to identify subsurface nuclear explosive testing. However, the naturally occurring formation of 37 Ar in the subsurface adds a complicating factor. Prediction of the naturally occurring concentration of 37 Ar can help to determine if a measured 37 Ar concentration is elevated relative to background. The naturally occurring 37 Ar background concentration has been shown to vary between less than 1 mBq/m 3 to greater than 100 mBq/m 3 (Riedmann and Purtschert, 2011). The purpose of this work was to enhance the understanding of the naturally occurring background concentrations of 37 Ar, allowing for better interpretation of results. To that end, we present and evaluate a computationally efficient model for predicting the average concentration of 37 Ar at any depth under transient barometric pressures. Further, measurements of 37 Ar concentrations in samples collected at multiple locations are provided as validation of the concentration prediction model. The model is shown to compare favorably with concentrations of 37 Ar measured at multiple locations in the Northwestern United States. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluation of SimpleTreat 4.0: Simulations of pharmaceutical removal in wastewater treatment plant facilities.

PubMed

Lautz, L S; Struijs, J; Nolte, T M; Breure, A M; van der Grinten, E; van de Meent, D; van Zelm, R

2017-02-01

In this study, the removal of pharmaceuticals from wastewater as predicted by SimpleTreat 4.0 was evaluated. Field data obtained from literature of 43 pharmaceuticals, measured in 51 different activated sludge WWTPs were used. Based on reported influent concentrations, the effluent concentrations were calculated with SimpleTreat 4.0 and compared to measured effluent concentrations. The model predicts effluent concentrations mostly within a factor of 10, using the specific WWTP parameters as well as SimpleTreat default parameters, while it systematically underestimates concentrations in secondary sludge. This may be caused by unexpected sorption, resulting from variability in WWTP operating conditions, and/or QSAR applicability domain mismatch and background concentrations prior to measurements. Moreover, variability in detection techniques and sampling methods can cause uncertainty in measured concentration levels. To find possible structural improvements, we also evaluated SimpleTreat 4.0 using several specific datasets with different degrees of uncertainty and variability. This evaluation verified that the most influencing parameters for water effluent predictions were biodegradation and the hydraulic retention time. Results showed that model performance is highly dependent on the nature and quality, i.e. degree of uncertainty, of the data. The default values for reactor settings in SimpleTreat result in realistic predictions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Factors affecting paddy soil arsenic concentration in Bangladesh: prediction and uncertainty of geostatistical risk mapping.

PubMed

Ahmed, Zia U; Panaullah, Golam M; DeGloria, Stephen D; Duxbury, John M

2011-12-15

Knowledge of the spatial correlation of soil arsenic (As) concentrations with environmental variables is needed to assess the nature and extent of the risk of As contamination from irrigation water in Bangladesh. We analyzed 263 paired groundwater and paddy soil samples covering highland (HL) and medium highland-1 (MHL-1) land types for geostatistical mapping of soil As and delineation of As contaminated areas in Tala Upazilla, Satkhira district. We also collected 74 non-rice soil samples to assess the baseline concentration of soil As for this area. The mean soil As concentrations (mg/kg) for different land types under rice and non-rice crops were: rice-MHL-1 (21.2)>rice-HL (14.1)>non-rice-MHL-1 (11.9)>non-rice-HL (7.2). Multiple regression analyses showed that irrigation water As, Fe, land elevation and years of tubewell operation are the important factors affecting the concentrations of As in HL paddy soils. Only years of tubewell operation affected As concentration in the MHL-1 paddy soils. Quantitatively similar increases in soil As above the estimated baseline-As concentration were observed for rice soils on HL and MHL-1 after 6-8 years of groundwater irrigation, implying strong retention of As added in irrigation water in both land types. Application of single geostatistical methods with secondary variables such as regression kriging (RK) and ordinary co-kriging (OCK) gave little improvement in prediction of soil As over ordinary kriging (OK). Comparing single prediction methods, kriging within strata (KWS), the combination of RK for HL and OCK for MHL-1, gave more accurate soil As predictions and showed the lowest misclassification of declaring a location "contaminated" with respect to 14.8 mg As/kg, the highest value obtained for the baseline soil As concentration. Prediction of soil As buildup over time indicated that 75% or the soils cropped to rice would contain at least 30 mg/L As by the year 2020. Copyright © 2011 Elsevier B.V. All rights reserved.

Prediction of 222Rn in Danish dwellings using geology and house construction information from central databases.

PubMed

Andersen, Claus E; Raaschou-Nielsen, Ole; Andersen, Helle Primdal; Lind, Morten; Gravesen, Peter; Thomsen, Birthe L; Ulbak, Kaare

2007-01-01

A linear regression model has been developed for the prediction of indoor (222)Rn in Danish houses. The model provides proxy radon concentrations for about 21,000 houses in a Danish case-control study on the possible association between residential radon and childhood cancer (primarily leukaemia). The model was calibrated against radon measurements in 3116 houses. An independent dataset with 788 house measurements was used for model performance assessment. The model includes nine explanatory variables, of which the most important ones are house type and geology. All explanatory variables are available from central databases. The model was fitted to log-transformed radon concentrations and it has an R(2) of 40%. The uncertainty associated with individual predictions of (untransformed) radon concentrations is about a factor of 2.0 (one standard deviation). The comparison with the independent test data shows that the model makes sound predictions and that errors of radon predictions are only weakly correlated with the estimates themselves (R(2) = 10%).

An international model validation exercise on radionuclide transfer and doses to freshwater biota.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yankovich, T. L.; Vives i Batlle, J.; Vives-Lynch, S.

2010-06-09

Under the International Atomic Energy Agency (IAEA)'s EMRAS (Environmental Modelling for Radiation Safety) program, activity concentrations of {sup 60}Co, {sup 90}Sr, {sup 137}Cs and {sup 3}H in Perch Lake at Atomic Energy of Canada Limited's Chalk River Laboratories site were predicted, in freshwater primary producers, invertebrates, fishes, herpetofauna and mammals using eleven modelling approaches. Comparison of predicted radionuclide concentrations in the different species types with measured values highlighted a number of areas where additional work and understanding is required to improve the predictions of radionuclide transfer. For some species, the differences could be explained by ecological factors such as trophicmore » level or the influence of stable analogues. Model predictions were relatively poor for mammalian species and herpetofauna compared with measured values, partly due to a lack of relevant data. In addition, concentration ratios are sometimes under-predicted when derived from experiments performed under controlled laboratory conditions representative of conditions in other water bodies.« less

[Predictive factors of virological response in chronically HCV infected].

PubMed

Lapiński, Tadeusz Wojciech; Flisiak, Robert

2012-09-01

Research on new antivirals drugs applied in the treatment of chronically HCV infected indicate that even the most perfect therapeutic molecules do not guarantee 100% efficacy. Since the beginning of the history of HCV infection treatment clinicians looked for predictors of treatment efficacy. Numerous studies confirm the high probability of cure in patients who cleared HCVinfectional 4 and 12 weeks of therapy. However despite of viral factors, recent research demonstrated predictive role of some host dependent factors. The most important role seems to play genetic factors including polymorphism rs12979860, as well as chemokins including first of all CXCL10 (IP-10). Very interesting seems to be also results of studies on association between vitamine D concentration and treatment efficacy. However in the future the most important predictive factor remain probably early on-treatment viral response.

Sex specific differences in the predictive value of cholesterol homeostasis markers and 10-Year CVD event rate in Framingham Offspring Study participants

USDA-ARS?s Scientific Manuscript database

Available data are inconsistent on factors influencing plasma cholesterol homeostasis marker concentrations and their value in predicting subsequent cardiovascular disease (CVD) events. To address this issue the relationship between markers of cholesterol absorption (campesterol, sitosterol, cholest...

Predicting the concentration and specific gravity of biodiesel-diesel blends using near-infrared spectroscopy

USDA-ARS?s Scientific Manuscript database

Biodiesel made from different source materials usually have different physical and chemical properties and the concentration of biodiesel in biodiesel-diesel blends varies from pump to pump and from user to user; all these factors have significant effects on performance and efficiency of engines fue...

Endometrial cancer risk prediction including serum-based biomarkers: results from the EPIC cohort.

PubMed

Fortner, Renée T; Hüsing, Anika; Kühn, Tilman; Konar, Meric; Overvad, Kim; Tjønneland, Anne; Hansen, Louise; Boutron-Ruault, Marie-Christine; Severi, Gianluca; Fournier, Agnès; Boeing, Heiner; Trichopoulou, Antonia; Benetou, Vasiliki; Orfanos, Philippos; Masala, Giovanna; Agnoli, Claudia; Mattiello, Amalia; Tumino, Rosario; Sacerdote, Carlotta; Bueno-de-Mesquita, H B As; Peeters, Petra H M; Weiderpass, Elisabete; Gram, Inger T; Gavrilyuk, Oxana; Quirós, J Ramón; Maria Huerta, José; Ardanaz, Eva; Larrañaga, Nerea; Lujan-Barroso, Leila; Sánchez-Cantalejo, Emilio; Butt, Salma Tunå; Borgquist, Signe; Idahl, Annika; Lundin, Eva; Khaw, Kay-Tee; Allen, Naomi E; Rinaldi, Sabina; Dossus, Laure; Gunter, Marc; Merritt, Melissa A; Tzoulaki, Ioanna; Riboli, Elio; Kaaks, Rudolf

2017-03-15

Endometrial cancer risk prediction models including lifestyle, anthropometric and reproductive factors have limited discrimination. Adding biomarker data to these models may improve predictive capacity; to our knowledge, this has not been investigated for endometrial cancer. Using a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we investigated the improvement in discrimination gained by adding serum biomarker concentrations to risk estimates derived from an existing risk prediction model based on epidemiologic factors. Serum concentrations of sex steroid hormones, metabolic markers, growth factors, adipokines and cytokines were evaluated in a step-wise backward selection process; biomarkers were retained at p < 0.157 indicating improvement in the Akaike information criterion (AIC). Improvement in discrimination was assessed using the C-statistic for all biomarkers alone, and change in C-statistic from addition of biomarkers to preexisting absolute risk estimates. We used internal validation with bootstrapping (1000-fold) to adjust for over-fitting. Adiponectin, estrone, interleukin-1 receptor antagonist, tumor necrosis factor-alpha and triglycerides were selected into the model. After accounting for over-fitting, discrimination was improved by 2.0 percentage points when all evaluated biomarkers were included and 1.7 percentage points in the model including the selected biomarkers. Models including etiologic markers on independent pathways and genetic markers may further improve discrimination. © 2016 UICC.

Impact of source collinearity in simulated PM 2.5 data on the PMF receptor model solution

NASA Astrophysics Data System (ADS)

Habre, Rima; Coull, Brent; Koutrakis, Petros

2011-12-01

Positive Matrix Factorization (PMF) is a factor analytic model used to identify particle sources and to estimate their contributions to PM 2.5 concentrations observed at receptor sites. Collinearity in source contributions due to meteorological conditions introduces uncertainty in the PMF solution. We simulated datasets of speciated PM 2.5 concentrations associated with three ambient particle sources: "Motor Vehicle" (MV), "Sodium Chloride" (NaCl), and "Sulfur" (S), and we varied the correlation structure between their mass contributions to simulate collinearity. We analyzed the datasets in PMF using the ME-2 multilinear engine. The Pearson correlation coefficients between the simulated and PMF-predicted source contributions and profiles are denoted by " G correlation" and " F correlation", respectively. In sensitivity analyses, we examined how the means or variances of the source contributions affected the stability of the PMF solution with collinearity. The % errors in predicting the average source contributions were 23, 80 and 23% for MV, NaCl, and S, respectively. On average, the NaCl contribution was overestimated, while MV and S contributions were underestimated. The ability of PMF to predict the contributions and profiles of the three sources deteriorated significantly as collinearity in their contributions increased. When the mean of NaCl or variance of NaCl and MV source contributions was increased, the deterioration in G correlation with increasing collinearity became less significant, and the ability of PMF to predict the NaCl and MV loading profiles improved. When the three factor profiles were simulated to share more elements, the decrease in G and F correlations became non-significant. Our findings agree with previous simulation studies reporting that correlated sources are predicted with higher error and bias. Consequently, the power to detect significant concentration-response estimates in health effect analyses weakens.

Derivation of Soil Ecological Criteria for Copper in Chinese Soils.

PubMed

Wang, Xiaoqing; Wei, Dongpu; Ma, Yibing; McLaughlin, Mike J

2015-01-01

Considerable information on copper (Cu) ecotoxicity as affected by biological species and abiotic properties of soils has been collected from the last decade in the present study. The information on bioavailability/ecotoxicity, species sensitivity and differences in laboratory and field ecotoxicity of Cu in different soils was collated and integrated to derive soil ecological criteria for Cu in Chinese soils, which were expressed as predicted no effect concentrations (PNEC). First, all ecotoxicity data of Cu from bioassays based on Chinese soils were collected and screened with given criteria to compile a database. Second, the compiled data were corrected with leaching and aging factors to minimize the differences between laboratory and field conditions. Before Cu ecotoxicity data were entered into a species sensitivity distribution (SSD), they were normalized with Cu ecotoxicity predictive models to modify the effects of soil properties on Cu ecotoxicity. The PNEC value was set equal to the hazardous concentration for x% of the species (HCx), which could be calculated from the SSD curves, without an additional assessment factor. Finally, predictive models for HCx based on soil properties were developed. The soil properties had a significant effect on the magnitude of HCx, with HC5 varying from 13.1 mg/kg in acidic soils to 51.9 mg/kg in alkaline non-calcareous soils. The two-factor predictive models based on soil pH and cation exchange capacity could predict HCx with determination coefficients (R2) of 0.82-0.91. The three-factor predictive models--that took into account the effect of soil organic carbon--were more accurate than two-factor models, with R2 of 0.85-0.99. The predictive models obtained here could be used to calculate soil-specific criteria. All results obtained here could provide a scientific basis for revision of current Chinese soil environmental quality standards, and the approach adopted in this study could be used as a pragmatic framework for developing soil ecological criteria for other trace elements in soils.

Prediction of winter vitamin D status and requirements in the UK population based on 25(OH) vitamin D half-life and dietary intake data.

PubMed

Schoenmakers, Inez; Gousias, Petros; Jones, Kerry S; Prentice, Ann

2016-11-01

On a population basis, there is a gradual decline in vitamin D status (plasma 25(OH)D) throughout winter. We developed a mathematical model to predict the population winter plasma 25(OH)D concentration longitudinally, using age-specific values for 25(OH)D expenditure (25(OH)D 3 t 1/2 ), cross-sectional plasma 25(OH)D concentration and vitamin D intake (VDI) data from older (70+ years; n=492) and younger adults (18-69 years; n=448) participating in the UK National Diet and Nutrition Survey. From this model, the population VDI required to maintain the mean plasma 25(OH)D at a set concentration can be derived. As expected, both predicted and measured population 25(OH)D (mean (95%CI)) progressively declined from September to March (from 51 (40-61) to 38 (36-41)nmol/L (predicted) vs 38 (27-48)nmol/L (measured) in older people and from 59 (54-65) to 34 (31-37)nmol/L (predicted) vs 37 (31-44)nmol/L (measured) in younger people). The predicted and measured mean values closely matched. The predicted VDIs required to maintain mean winter plasma 25(OH)D at 50nmol/L at the population level were 10 (0-20) to 11 (9-14) and 11 (6-16) to 13(11-16)μg/d for older and younger adults, respectively dependent on the month. In conclusion, a prediction model accounting for 25(OH)D 3 t 1/2 , VDI and scaling factor for the 25(OH)D response to VDI, closely predicts measured population winter values. Refinements of this model may include specific scaling factors accounting for the 25(OH)D response at different VDIs and as influenced by body composition and specific values for 25(OH)D 3 t 1/2 dependent on host factors such as kidney function. This model may help to reduce the need for longitudinal measurements. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

The Relationships between PM2.5 and Meteorological Factors in China: Seasonal and Regional Variations

PubMed Central

Yang, Qianqian; Li, Tongwen; Shen, Huanfeng; Zhang, Liangpei

2017-01-01

The interactions between PM2.5 and meteorological factors play a crucial role in air pollution analysis. However, previous studies that have researched the relationships between PM2.5 concentration and meteorological conditions have been mainly confined to a certain city or district, and the correlation over the whole of China remains unclear. Whether spatial and seasonal variations exist deserves further research. In this study, the relationships between PM2.5 concentration and meteorological factors were investigated in 68 major cities in China for a continuous period of 22 months from February 2013 to November 2014, at season, year, city, and regional scales, and the spatial and seasonal variations were analyzed. The meteorological factors were relative humidity (RH), temperature (TEM), wind speed (WS), and surface pressure (PS). We found that spatial and seasonal variations of their relationships with PM2.5 exist. Spatially, RH is positively correlated with PM2.5 concentration in north China and Urumqi, but the relationship turns to negative in other areas of China. WS is negatively correlated with PM2.5 everywhere except for Hainan Island. PS has a strong positive relationship with PM2.5 concentration in northeast China and mid-south China, and in other areas the correlation is weak. Seasonally, the positive correlation between PM2.5 concentration and RH is stronger in winter and spring. TEM has a negative relationship with PM2.5 in autumn and the opposite in winter. PS is more positively correlated with PM2.5 in autumn than in other seasons. Our study investigated the relationships between PM2.5 and meteorological factors in terms of spatial and seasonal variations, and the conclusions about the relationships between PM2.5 and meteorological factors are more comprehensive and precise than before. We suggest that the variations could be considered in PM2.5 concentration prediction and haze control to improve the prediction accuracy and policy efficiency. PMID:29206181

A method for testing whether model predictions fall within a prescribed factor of true values, with an application to pesticide leaching

USGS Publications Warehouse

Parrish, Rudolph S.; Smith, Charles N.

1990-01-01

A quantitative method is described for testing whether model predictions fall within a specified factor of true values. The technique is based on classical theory for confidence regions on unknown population parameters and can be related to hypothesis testing in both univariate and multivariate situations. A capability index is defined that can be used as a measure of predictive capability of a model, and its properties are discussed. The testing approach and the capability index should facilitate model validation efforts and permit comparisons among competing models. An example is given for a pesticide leaching model that predicts chemical concentrations in the soil profile.

Application Study of Comprehensive Forecasting Model Based on Entropy Weighting Method on Trend of PM2.5 Concentration in Guangzhou, China

PubMed Central

Liu, Dong-jun; Li, Li

2015-01-01

For the issue of haze-fog, PM2.5 is the main influence factor of haze-fog pollution in China. The trend of PM2.5 concentration was analyzed from a qualitative point of view based on mathematical models and simulation in this study. The comprehensive forecasting model (CFM) was developed based on the combination forecasting ideas. Autoregressive Integrated Moving Average Model (ARIMA), Artificial Neural Networks (ANNs) model and Exponential Smoothing Method (ESM) were used to predict the time series data of PM2.5 concentration. The results of the comprehensive forecasting model were obtained by combining the results of three methods based on the weights from the Entropy Weighting Method. The trend of PM2.5 concentration in Guangzhou China was quantitatively forecasted based on the comprehensive forecasting model. The results were compared with those of three single models, and PM2.5 concentration values in the next ten days were predicted. The comprehensive forecasting model balanced the deviation of each single prediction method, and had better applicability. It broadens a new prediction method for the air quality forecasting field. PMID:26110332

Watershed regressions for pesticides (warp) models for predicting atrazine concentrations in Corn Belt streams

USGS Publications Warehouse

Stone, Wesley W.; Gilliom, Robert J.

2012-01-01

Watershed Regressions for Pesticides (WARP) models, previously developed for atrazine at the national scale, are improved for application to the United States (U.S.) Corn Belt region by developing region-specific models that include watershed characteristics that are influential in predicting atrazine concentration statistics within the Corn Belt. WARP models for the Corn Belt (WARP-CB) were developed for annual maximum moving-average (14-, 21-, 30-, 60-, and 90-day durations) and annual 95th-percentile atrazine concentrations in streams of the Corn Belt region. The WARP-CB models accounted for 53 to 62% of the variability in the various concentration statistics among the model-development sites. Model predictions were within a factor of 5 of the observed concentration statistic for over 90% of the model-development sites. The WARP-CB residuals and uncertainty are lower than those of the National WARP model for the same sites. Although atrazine-use intensity is the most important explanatory variable in the National WARP models, it is not a significant variable in the WARP-CB models. The WARP-CB models provide improved predictions for Corn Belt streams draining watersheds with atrazine-use intensities of 17 kg/km2 of watershed area or greater.

Application Study of Comprehensive Forecasting Model Based on Entropy Weighting Method on Trend of PM2.5 Concentration in Guangzhou, China.

PubMed

Liu, Dong-jun; Li, Li

2015-06-23

For the issue of haze-fog, PM2.5 is the main influence factor of haze-fog pollution in China. The trend of PM2.5 concentration was analyzed from a qualitative point of view based on mathematical models and simulation in this study. The comprehensive forecasting model (CFM) was developed based on the combination forecasting ideas. Autoregressive Integrated Moving Average Model (ARIMA), Artificial Neural Networks (ANNs) model and Exponential Smoothing Method (ESM) were used to predict the time series data of PM2.5 concentration. The results of the comprehensive forecasting model were obtained by combining the results of three methods based on the weights from the Entropy Weighting Method. The trend of PM2.5 concentration in Guangzhou China was quantitatively forecasted based on the comprehensive forecasting model. The results were compared with those of three single models, and PM2.5 concentration values in the next ten days were predicted. The comprehensive forecasting model balanced the deviation of each single prediction method, and had better applicability. It broadens a new prediction method for the air quality forecasting field.

Watershed Regressions for Pesticides (WARP) for Predicting Annual Maximum and Annual Maximum Moving-Average Concentrations of Atrazine in Streams

USGS Publications Warehouse

Stone, Wesley W.; Gilliom, Robert J.; Crawford, Charles G.

2008-01-01

Regression models were developed for predicting annual maximum and selected annual maximum moving-average concentrations of atrazine in streams using the Watershed Regressions for Pesticides (WARP) methodology developed by the National Water-Quality Assessment Program (NAWQA) of the U.S. Geological Survey (USGS). The current effort builds on the original WARP models, which were based on the annual mean and selected percentiles of the annual frequency distribution of atrazine concentrations. Estimates of annual maximum and annual maximum moving-average concentrations for selected durations are needed to characterize the levels of atrazine and other pesticides for comparison to specific water-quality benchmarks for evaluation of potential concerns regarding human health or aquatic life. Separate regression models were derived for the annual maximum and annual maximum 21-day, 60-day, and 90-day moving-average concentrations. Development of the regression models used the same explanatory variables, transformations, model development data, model validation data, and regression methods as those used in the original development of WARP. The models accounted for 72 to 75 percent of the variability in the concentration statistics among the 112 sampling sites used for model development. Predicted concentration statistics from the four models were within a factor of 10 of the observed concentration statistics for most of the model development and validation sites. Overall, performance of the models for the development and validation sites supports the application of the WARP models for predicting annual maximum and selected annual maximum moving-average atrazine concentration in streams and provides a framework to interpret the predictions in terms of uncertainty. For streams with inadequate direct measurements of atrazine concentrations, the WARP model predictions for the annual maximum and the annual maximum moving-average atrazine concentrations can be used to characterize the probable levels of atrazine for comparison to specific water-quality benchmarks. Sites with a high probability of exceeding a benchmark for human health or aquatic life can be prioritized for monitoring.

Estimating Time-Varying PCB Exposures Using Person-Specific Predictions to Supplement Measured Values: A Comparison of Observed and Predicted Values in Two Cohorts of Norwegian Women

PubMed Central

Nøst, Therese Haugdahl; Breivik, Knut; Wania, Frank; Rylander, Charlotta; Odland, Jon Øyvind; Sandanger, Torkjel Manning

2015-01-01

Background Studies on the health effects of polychlorinated biphenyls (PCBs) call for an understanding of past and present human exposure. Time-resolved mechanistic models may supplement information on concentrations in individuals obtained from measurements and/or statistical approaches if they can be shown to reproduce empirical data. Objectives Here, we evaluated the capability of one such mechanistic model to reproduce measured PCB concentrations in individual Norwegian women. We also assessed individual life-course concentrations. Methods Concentrations of four PCB congeners in pregnant (n = 310, sampled in 2007–2009) and postmenopausal (n = 244, 2005) women were compared with person-specific predictions obtained using CoZMoMAN, an emission-based environmental fate and human food-chain bioaccumulation model. Person-specific predictions were also made using statistical regression models including dietary and lifestyle variables and concentrations. Results CoZMoMAN accurately reproduced medians and ranges of measured concentrations in the two study groups. Furthermore, rank correlations between measurements and predictions from both CoZMoMAN and regression analyses were strong (Spearman’s r > 0.67). Precision in quartile assignments from predictions was strong overall as evaluated by weighted Cohen’s kappa (> 0.6). Simulations indicated large inter-individual differences in concentrations experienced in the past. Conclusions The mechanistic model reproduced all measurements of PCB concentrations within a factor of 10, and subject ranking and quartile assignments were overall largely consistent, although they were weak within each study group. Contamination histories for individuals predicted by CoZMoMAN revealed variation between study subjects, particularly in the timing of peak concentrations. Mechanistic models can provide individual PCB exposure metrics that could serve as valuable supplements to measurements. Citation Nøst TH, Breivik K, Wania F, Rylander C, Odland JØ, Sandanger TM. 2016. Estimating time-varying PCB exposures using person-specific predictions to supplement measured values: a comparison of observed and predicted values in two cohorts of Norwegian women. Environ Health Perspect 124:299–305; http://dx.doi.org/10.1289/ehp.1409191 PMID:26186800

Increase in the CO2 exchange rate of leaves of Ilex rotunda with elevated atmospheric CO2 concentration in an urban canyon

NASA Astrophysics Data System (ADS)

Takagi, M.; Gyokusen, Koichiro; Saito, Akira

It was found that the atmospheric carbon dioxide (CO2) concentration in an urban canyon in Fukuoka city, Japan during August 1997 was about 30 µmol mol-1 higher than that in the suburbs. When fully exposed to sunlight, in situ the rate of photosynthesis in single leaves of Ilex rotunda planted in the urban canyon was higher when the atmospheric CO2 concentration was elevated. A biochemically based model was able to predict the in situ rate of photosynthesis well. The model also predicted an increase in the daily CO2 exchange rate for leaves in the urban canyon with an increase in atmospheric CO2 concentration. However, in situ such an increase in the daily CO2 exchange rate may be offset by diminished sunlight, a higher air temperature and a lower relative humidity. Thus, the daily CO2 exchange rate predicted using the model based soleley on the environmental conditions prevailing in the urban canyon was lower than that predicted based only on environmental factors found in the suburbs.

Antepartal insulin-like growth factor 1 and insulin-like growth factor binding protein 2 concentrations are indicative of ketosis in dairy cows.

PubMed

Piechotta, M; Mysegades, W; Ligges, U; Lilienthal, J; Hoeflich, A; Miyamoto, A; Bollwein, H

2015-05-01

A study involving a small number of cows found that the concentrations of insulin-like growth hormone 1 (IGF1) may be a useful predictor of metabolic disease. Further, IGF1 may provide also a pathophysiological link to metabolic diseases such as ketosis. The objective of the current study was to test whether the low antepartal total IGF1 or IGF1 binding protein (IGFBP) concentrations might predict ketosis under field conditions. Clinical examinations and blood sampling were performed antepartum (262-270 d after artificial insemination) on 377 pluriparous pregnant Holstein Friesian cows. The presence of postpartum diseases were recorded (ketosis, fatty liver, displacement of the abomasum, hypocalcemia, mastitis, retention of fetal membranes, and clinical metritis or endometritis), and the concentrations of IGF1, IGFBP2, IGFBP3, and nonesterified fatty acids were measured. Cows with postpartum clinical ketosis had lower IGF1 concentrations antepartum than healthy cows. The sensitivity of antepartal IGF1 as a marker for postpartum ketosis was 0.87, and the specificity was 0.43; a positive predictive value of 0.91 and a negative predictive value of 0.35 were calculated. The cows with ketosis and retained fetal membranes had lower IGFBP2 concentrations compared with the healthy cows. It can be speculated that lower IGF1 production in the liver during late pregnancy may increase growth hormone secretions and lipolysis, thereby increasing the risk of ketosis. Lower IGFBP2 concentrations may reflect the suppression of IGFBP2 levels through higher growth hormone secretion. In conclusion, compared with nonesterified fatty acids as a predictive parameter, IGF1 and IGFBP2 may represent earlier biomarkers of inadequate metabolic adaptation to the high energy demand required postpartum. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Watershed Regressions for Pesticides (WARP) models for predicting stream concentrations of multiple pesticides

USGS Publications Warehouse

Stone, Wesley W.; Crawford, Charles G.; Gilliom, Robert J.

2013-01-01

Watershed Regressions for Pesticides for multiple pesticides (WARP-MP) are statistical models developed to predict concentration statistics for a wide range of pesticides in unmonitored streams. The WARP-MP models use the national atrazine WARP models in conjunction with an adjustment factor for each additional pesticide. The WARP-MP models perform best for pesticides with application timing and methods similar to those used with atrazine. For other pesticides, WARP-MP models tend to overpredict concentration statistics for the model development sites. For WARP and WARP-MP, the less-than-ideal sampling frequency for the model development sites leads to underestimation of the shorter-duration concentration; hence, the WARP models tend to underpredict 4- and 21-d maximum moving-average concentrations, with median errors ranging from 9 to 38% As a result of this sampling bias, pesticides that performed well with the model development sites are expected to have predictions that are biased low for these shorter-duration concentration statistics. The overprediction by WARP-MP apparent for some of the pesticides is variably offset by underestimation of the model development concentration statistics. Of the 112 pesticides used in the WARP-MP application to stream segments nationwide, 25 were predicted to have concentration statistics with a 50% or greater probability of exceeding one or more aquatic life benchmarks in one or more stream segments. Geographically, many of the modeled streams in the Corn Belt Region were predicted to have one or more pesticides that exceeded an aquatic life benchmark during 2009, indicating the potential vulnerability of streams in this region.

Optimization and modeling of laccase production by Trametes versicolor in a bioreactor using statistical experimental design.

PubMed

Tavares, A P M; Coelho, M A Z; Agapito, M S M; Coutinho, J A P; Xavier, A M R B

2006-09-01

Experimental design and response surface methodologies were applied to optimize laccase production by Trametes versicolor in a bioreactor. The effects of three factors, initial glucose concentration (0 and 9 g/L), agitation (100 and 180 rpm), and pH (3.0 and 5.0), were evaluated to identify the significant effects and its interactions in the laccase production. The pH of the medium was found to be the most important factor, followed by initial glucose concentration and the interaction of both factors. Agitation did not seem to play an important role in laccase production, nor did the interaction agitation x medium pH and agitation x initial glucose concentration. Response surface analysis showed that an initial glucose concentration of 11 g/L and pH controlled at 5.2 were the optimal conditions for laccase production by T. versicolor. Under these conditions, the predicted value for laccase activity was >10,000 U/L, which is in good agreement with the laccase activity obtained experimentally (11,403 U/L). In addition, a mathematical model for the bioprocess was developed. It is shown that it provides a good description of the experimental profile observed, and that it is capable of predicting biomass growth based on secondary process variables.

C-reactive protein (+1444C>T) polymorphism influences CRP response following a moderate inflammatory stimulus.

PubMed

D'Aiuto, Francesco; Casas, Juan P; Shah, Tina; Humphries, Steve E; Hingorani, Aroon D; Tonetti, Maurizio S

2005-04-01

Elevations in C-reactive protein (CRP) concentration are associated with an increased risk of future coronary events in prospective studies and it has been suggested that CRP could be used to aid risk prediction. A +1444C>T polymorphism in the CRP gene has been associated with differences in CRP concentration. We investigated the effect of this polymorphism on the CRP response to periodontal therapy, an intermediate inflammatory stimulus. Clinical parameters, CRP, and interleukin-6 (IL-6) concentrations were evaluated in 55 consecutive patients suffering from periodontitis at baseline, 1, 7 and 30 days after an intensive course of periodontal treatment. In a multivariate analysis individuals homozygous for the +1444T allele showed higher CRP concentrations (day 1, 21.10+/-4.81 mg/L and day 7, 4.89+/-0.74 mg/L) compared with C-allele carriers (day 1, 12.37+/-1.61 mg/L and day 7, 3.08+/-2.00 mg/L). This effect was independent of conventional cardiovascular risk factors and inflammatory factors known to affect CRP concentrations. CRP genotype may need to be considered when CRP values are used in coronary risk prediction.

Cytokine activation is predictive of mortality in Zambian patients with AIDS-related diarrhoea

PubMed Central

Zulu, Isaac; Hassan, Ghaniah; Njobvu RN, Lungowe; Dhaliwal, Winnie; Sianongo, Sandie; Kelly, Paul

2008-01-01

Background Mortality in Zambian AIDS patients is high, especially in patients with diarrhoea, and there is still unacceptably high mortality in Zambian patients just starting anti-retroviral therapy. We set out to determine if high concentrations of serum cytokines correlate with mortality. Methods Serum samples from 30 healthy controls (HIV seropositive and seronegative) and 50 patients with diarrhoea (20 of whom died within 6 weeks) were analysed. Concentrations of tumour necrosis factor receptor p55 (TNFR p55), macrophage migration inhibitory factor (MIF), interleukin (IL)-6, IL-12, interferon (IFN)-γ and C-reactive protein (CRP) were measured by ELISA, and correlated with mortality after 6 weeks follow-up. Results Apart from IL-12, concentrations of all cytokines, TNFR p55 and CRP increased with worsening severity of disease, showing highly statistically significant trends. In a multivariable analysis high TNFR p55, IFN-γ, CRP and low CD4 count (CD4 count <100) were predictive of mortality. Although nutritional status (assessed by body mass index, BMI) was predictive in univariate analysis, it was not an independent predictor in multivariate analysis. Conclusion High serum concentrations of TNFR p55, IFN-γ, CRP and low CD4 count correlated with disease severity and short-term mortality in HIV-infected Zambian adults with diarrhoea. These factors were better predictors of survival than BMI. Understanding the cause of TNFR p55, IFN-γ and CRP elevation may be useful in development of interventions to reduce mortality in AIDS patients with chronic diarrhoea in Africa. PMID:19014537

Prediction and analysis of near-road concentrations using a reduced-form emission/dispersion model

PubMed Central

2010-01-01

Background Near-road exposures of traffic-related air pollutants have been receiving increased attention due to evidence linking emissions from high-traffic roadways to adverse health outcomes. To date, most epidemiological and risk analyses have utilized simple but crude exposure indicators, most typically proximity measures, such as the distance between freeways and residences, to represent air quality impacts from traffic. This paper derives and analyzes a simplified microscale simulation model designed to predict short- (hourly) to long-term (annual average) pollutant concentrations near roads. Sensitivity analyses and case studies are used to highlight issues in predicting near-road exposures. Methods Process-based simulation models using a computationally efficient reduced-form response surface structure and a minimum number of inputs integrate the major determinants of air pollution exposures: traffic volume and vehicle emissions, meteorology, and receptor location. We identify the most influential variables and then derive a set of multiplicative submodels that match predictions from "parent" models MOBILE6.2 and CALINE4. The assembled model is applied to two case studies in the Detroit, Michigan area. The first predicts carbon monoxide (CO) concentrations at a monitoring site near a freeway. The second predicts CO and PM2.5 concentrations in a dense receptor grid over a 1 km2 area around the intersection of two major roads. We analyze the spatial and temporal patterns of pollutant concentration predictions. Results Predicted CO concentrations showed reasonable agreement with annual average and 24-hour measurements, e.g., 59% of the 24-hr predictions were within a factor of two of observations in the warmer months when CO emissions are more consistent. The highest concentrations of both CO and PM2.5 were predicted to occur near intersections and downwind of major roads during periods of unfavorable meteorology (e.g., low wind speeds) and high emissions (e.g., weekday rush hour). The spatial and temporal variation among predicted concentrations was significant, and resulted in unusual distributional and correlation characteristics, including strong negative correlation for receptors on opposite sides of a road and the highest short-term concentrations on the "upwind" side of the road. Conclusions The case study findings can likely be generalized to many other locations, and they have important implications for epidemiological and other studies. The reduced-form model is intended for exposure assessment, risk assessment, epidemiological, geographical information systems, and other applications. PMID:20579353

Concentration dependent refractive index of a binary mixture at high pressure.

PubMed

Croccolo, Fabrizio; Arnaud, Marc-Alexandre; Bégué, Didier; Bataller, Henri

2011-07-21

In the present work binary mixtures of varying concentrations of two miscible hydrocarbons, 1,2,3,4-tetrahydronaphtalene (THN) and n-dodecane (C12), are subjected to increasing pressure up to 50 MPa in order to investigate the dependence of the so-called concentration contrast factor (CF), i.e., (∂n/∂c)(p, T), on pressure level. The refractive index is measured by means of a Mach-Zehnder interferometer. The setup and experimental procedure are validated with different pure fluids in the same pressure range. The refractive index of the THN-C12 mixture is found to vary both over pressure and concentration, and the concentration CF is found to exponentially decrease as the pressure is increased. The measured values of the refractive index and the concentration CFs are compared with values obtained by two different theoretical predictions, the well-known Lorentz-Lorenz formula and an alternative one proposed by Looyenga. While the measured refractive indices agree very well with predictions given by Looyenga, the measured concentration CFs show deviations from the latter of the order of 6% and more than the double from the Lorentz-Lorenz predictions.

Comparison of predicted pesticide concentrations in groundwater from SCI-GROW and PRZM-GW models with historical monitoring data.

PubMed

Estes, Tammara L; Pai, Naresh; Winchell, Michael F

2016-06-01

A key factor in the human health risk assessment process for the registration of pesticides by the US Environmental Protection Agency (EPA) is an estimate of pesticide concentrations in groundwater used for drinking water. From 1997 to 2011, these estimates were obtained from the EPA empirical model SCI-GROW. Since 2012, these estimates have been obtained from the EPA deterministic model PRZM-GW, which has resulted in a significant increase in estimated groundwater concentrations for many pesticides. Historical groundwater monitoring data from the National Ambient Water Quality Assessment (NAWQA) Program (1991-2014) were compared with predicted groundwater concentrations from both SCI-GROW (v.2.3) and PRZM-GW (v.1.07) for 66 different pesticides of varying environmental fate properties. The pesticide environmental fate parameters associated with over- and underprediction of groundwater concentrations by the two models were evaluated. In general, SCI-GROW2.3 predicted groundwater concentrations were close to maximum historically observed groundwater concentrations. However, for pesticides with soil organic carbon content values below 1000 L kg(-1) and no simulated hydrolysis, PRZM-GW overpredicted, often by greater than 100 ppb. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

External evaluation of population pharmacokinetic models of vancomycin in neonates: the transferability of published models to different clinical settings

PubMed Central

Zhao, Wei; Kaguelidou, Florentia; Biran, Valérie; Zhang, Daolun; Allegaert, Karel; Capparelli, Edmund V; Holford, Nick; Kimura, Toshimi; Lo, Yoke-Lin; Peris, José-Esteban; Thomson, Alison; Anker, John N; Fakhoury, May; Jacqz-Aigrain, Evelyne

2013-01-01

Aims Vancomycin is one of the most evaluated antibiotics in neonates using modeling and simulation approaches. However no clear consensus on optimal dosing has been achieved. The objective of the present study was to perform an external evaluation of published models, in order to test their predictive performances in an independent dataset and to identify the possible study-related factors influencing the transferability of pharmacokinetic models to different clinical settings. Method Published neonatal vancomycin pharmacokinetic models were screened from the literature. The predictive performance of six models was evaluated using an independent dataset (112 concentrations from 78 neonates). The evaluation procedures used simulation-based diagnostics [visual predictive check (VPC) and normalized prediction distribution errors (NPDE)]. Results Differences in predictive performances of models for vancomycin pharmacokinetics in neonates were found. The mean of NPDE for six evaluated models were 1.35, −0.22, −0.36, 0.24, 0.66 and 0.48, respectively. These differences were explained, at least partly, by taking into account the method used to measure serum creatinine concentrations. The adult conversion factor of 1.3 (enzymatic to Jaffé) was tested with an improvement in the VPC and NPDE, but it still needs to be evaluated and validated in neonates. Differences were also identified between analytical methods for vancomycin. Conclusion The importance of analytical techniques for serum creatinine concentrations and vancomycin as predictors of vancomycin concentrations in neonates have been confirmed. Dosage individualization of vancomycin in neonates should consider not only patients' characteristics and clinical conditions, but also the methods used to measure serum creatinine and vancomycin. PMID:23148919

Variability of the soil-to-plant radiocaesium transfer factor for Japanese soils predicted with soil and plant properties.

PubMed

Uematsu, Shinichiro; Vandenhove, Hildegarde; Sweeck, Lieve; Van Hees, May; Wannijn, Jean; Smolders, Erik

2016-03-01

Food chain contamination with radiocaesium (RCs) in the aftermath of the Fukushima accident calls for an analysis of the specific factors that control the RCs transfer. Here, soil-to-plant transfer factors (TF) of RCs for grass were predicted from the potassium concentration in soil solution (mK) and the Radiocaesium Interception Potential (RIP) of the soil using existing mechanistic models. The mK and RIP were (a) either measured for 37 topsoils collected from the Fukushima accident affected area or (b) predicted from the soil clay content and the soil exchangeable potassium content using the models that had been calibrated for European soils. An average ammonium concentration was used throughout in the prediction. The measured RIP ranged 14-fold and measured mK varied 37-fold among the soils. The measured RIP was lower than the RIP predicted from the soil clay content likely due to the lower content of weathered micas in the clay fraction of Japanese soils. Also the measured mK was lower than that predicted. As a result, the predicted TFs relying on the measured RIP and mK were, on average, about 22-fold larger than the TFs predicted using the European calibrated models. The geometric mean of the measured TFs for grass in the affected area (N = 82) was in the middle of both. The TFs were poorly related to soil classification classes, likely because soil fertility (mK) was obscuring the effects of the soil classification related to the soil mineralogy (RIP). This study suggests that, on average, Japanese soils are more vulnerable than European soils at equal soil clay and exchangeable K content. The affected regions will be targeted for refined model validation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modeling individual exposures to ambient PM2.5 in the diabetes and the environment panel study (DEPS).

PubMed

Breen, Michael; Xu, Yadong; Schneider, Alexandra; Williams, Ronald; Devlin, Robert

2018-06-01

Air pollution epidemiology studies of ambient fine particulate matter (PM 2.5 ) often use outdoor concentrations as exposure surrogates, which can induce exposure error. The goal of this study was to improve ambient PM 2.5 exposure assessments for a repeated measurements study with 22 diabetic individuals in central North Carolina called the Diabetes and Environment Panel Study (DEPS) by applying the Exposure Model for Individuals (EMI), which predicts five tiers of individual-level exposure metrics for ambient PM 2.5 using outdoor concentrations, questionnaires, weather, and time-location information. Using EMI, we linked a mechanistic air exchange rate (AER) model to a mass-balance PM 2.5 infiltration model to predict residential AER (Tier 1), infiltration factors (F inf_home , Tier 2), indoor concentrations (C in , Tier 3), personal exposure factors (F pex , Tier 4), and personal exposures (E, Tier 5) for ambient PM 2.5 . We applied EMI to predict daily PM 2.5 exposure metrics (Tiers 1-5) for 174 participant-days across the 13 months of DEPS. Individual model predictions were compared to a subset of daily measurements of F pex and E (Tiers 4-5) from the DEPS participants. Model-predicted F pex and E corresponded well to daily measurements with a median difference of 14% and 23%; respectively. Daily model predictions for all 174 days showed considerable temporal and house-to-house variability of AER, F inf_home , and C in (Tiers 1-3), and person-to-person variability of F pex and E (Tiers 4-5). Our study demonstrates the capability of predicting individual-level ambient PM 2.5 exposure metrics for an epidemiological study, in support of improving risk estimation. Copyright © 2018. Published by Elsevier B.V.

Probabilistic determination of the ecological risk from OTNE in aquatic and terrestrial compartments based on US-wide monitoring data.

PubMed

McDonough, Kathleen; Casteel, Kenneth; Zoller, Ann; Wehmeyer, Kenneth; Hulzebos, Etje; Rila, Jean-Paul; Salvito, Daniel; Federle, Thomas

2017-01-01

OTNE [1-(1,2,3,4,5,6,7,8-octahydro-2,3,8,8-tetramethyl-2-naphthyl)ethan-1-one; trade name Iso E Super] is a fragrance ingredient commonly used in consumer products which are disposed down the drain. This research measured effluent and sludge concentrations of OTNE at 44 US wastewater treatment plants (WWTP). The mean effluent and sludge concentrations were 0.69 ± 0.65 μg/L and 20.6 ± 33.8 mg/kg dw respectively. Distribution of OTNE effluent concentrations and dilution factors were used to predict surface water and sediment concentrations and distributions of OTNE sludge concentrations and loading rates were used to predict terrestrial concentrations. The 90th percentile concentration of OTNE in US WWTP mixing zones was predicted to be 0.04 and 0.85 μg/L under mean and 7Q10 low flow (lowest river flow occurring over a 7 day period every 10 years) conditions respectively. The 90th percentile sediment concentrations under mean and 7Q10 low flow conditions were predicted to be 0.081 and 1.6 mg/kg dw respectively. Based on current US sludge application practices, the 90th percentile OTNE terrestrial concentration was 1.38 mg/kg dw. The probability of OTNE concentrations being below the predicted no effect concentration (PNEC) for the aquatic and sediment compartments was greater than 99%. For the terrestrial compartment, the probability of OTNE concentrations being lower than the PNEC was 97% for current US sludge application practices. Based on the results of this study, OTNE concentrations in US WWTP effluent and sludge do not pose an ecological risk to aquatic, sediment and terrestrial organisms. Copyright © 2016 Elsevier Ltd. All rights reserved.

Vulnerability of recently recharged groundwater in principal aquifers of the United States to nitrate contamination

USGS Publications Warehouse

Gurdak, Jason J.; Qi, Sharon L.

2012-01-01

Recently recharged water (defined here as <60 years old) is generally the most vulnerable part of a groundwater resource to nonpoint-source nitrate contamination. Understanding at the appropriate scale the interactions of natural and anthropogenic controlling factors that influence nitrate occurrence in recently recharged groundwater is critical to support best management and policy decisions that are often made at the aquifer to subaquifer scale. New logistic regression models were developed using data from the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) program and National Water Information System for 17 principal aquifers of the U.S. to identify important source, transport, and attenuation factors that control nonpoint source nitrate concentrations greater than relative background levels in recently recharged groundwater and were used to predict the probability of detecting elevated nitrate in areas beyond the sampling network. Results indicate that dissolved oxygen, crops and irrigated cropland, fertilizer application, seasonally high water table, and soil properties that affect infiltration and denitrification are among the most important factors in predicting elevated nitrate concentrations. Important differences in controlling factors and spatial predictions were identified in the principal aquifer and national-scale models and support the conclusion that similar spatial scales are needed between informed groundwater management and model development.

Environmental and genetic determinants of two vitamin D metabolites in healthy Australian children.

PubMed

Bima, Abdulhadi; Pezic, Angela; Sun, Cong; Cameron, Fergus J; Rodda, Christine; van der Mei, Ingrid; Chiaroni-Clarke, Rachel; Dwyer, Terence; Kemp, Andrew; Qu, Jun; Carlin, John; Ellis, Justine A; Ponsonby, Anne-Louise

2017-05-01

Vitamin D deficiency has been associated with adverse health outcomes. We examined genetic and environmental determinants of serum 25(OH)D3 and 1,25(OH)2D3 in childhood. The study sample consisted of 322 healthy Australian children (predominantly Caucasians) who provided a venous blood sample. A parental interview was conducted and skin phototype and anthropometry measures were assessed. Concentrations of 25(OH)D3 and 1,25(OH)2D3 were measured by selective solid-phase extraction-capillary liquid chromatography-tandem mass spectrometry. These concentrations were deseasonalised where relevant to remove the effect of month of sampling. Deseasonalised log 25(OH)D3 and 1,25(OH)2D3 concentrations were only moderately correlated (r=0.42, p<0.001). The following predicted both 25(OH)D3 and 1,25(OH)2D3: UVR 6 weeks before the interview, natural skin and eye colour, height and vitamin D allelic metabolism score. The following predicted 25(OH)D3 only: lifetime sunburns and vitamin D allelic synthesis score. Overall, 43.5% and 25.6% of variation in 25(OH)D3 and 1,25(OH)2D3 could be explained. After accounting for 25(OH)D3 concentrations, higher UVR 6 weeks before the interview and vitamin D allelic metabolism score further predicted 1,25(OH)2D3 concentrations. Environmental factors and genetic factors contributed to both vitamin D metabolite concentrations. The intriguing finding that the higher ambient UVR contributed to higher 1,25(OH)2D3 after accounting for 25(OH)D3 concentrations requires further evaluation.

A first European scale multimedia fate modelling of BDE-209 from 1970 to 2020.

PubMed

Earnshaw, Mark R; Jones, Kevin C; Sweetman, Andy J

2015-01-01

The European Variant Berkeley Trent (EVn-BETR) multimedia fugacity model is used to test the validity of previously derived emission estimates and predict environmental concentrations of the main decabromodiphenyl ether congener, BDE-209. The results are presented here and compared with measured environmental data from the literature. Future multimedia concentration trends are predicted using three emission scenarios (Low, Realistic and High) in the dynamic unsteady state mode covering the period 1970-2020. The spatial and temporal distributions of emissions are evaluated. It is predicted that BDE-209 atmospheric concentrations peaked in 2004 and will decline to negligible levels by 2025. Freshwater concentrations should have peaked in 2011, one year after the emissions peak with sediment concentrations peaking in 2013. Predicted atmospheric concentrations are in good agreement with measured data for the Realistic (best estimate of emissions) and High (worst case scenario) emission scenarios. The Low emission scenario consistently underestimates measured data. The German unilateral ban on the use of DecaBDE in the textile industry is simulated in an additional scenario, the effects of which are mainly observed within Germany with only a small effect on the surrounding areas. Overall, the EVn-BTER model predicts atmospheric concentrations reasonably well, within a factor of 5 and 1.2 for the Realistic and High emission scenarios respectively, providing partial validation for the original emission estimate. Total mean MEC:PEC shows the High emission scenario predicts the best fit between air, freshwater and sediment data. An alternative spatial distribution of emissions is tested, based on higher consumption in EBFRIP member states, resulting in improved agreement between MECs and PECs in comparison with the Uniform spatial distribution based on population density. Despite good agreement between modelled and measured point data, more long-term monitoring datasets are needed to compare predicted trends in concentration to determine the rate of change of POPs within the environment. Copyright © 2014 Elsevier Ltd. All rights reserved.

[Ecology suitability study of Chinese materia medica Gentianae Macrophyllae Radix].

PubMed

Lu, You-Yuan; Yang, Yan-Mei; Ma, Xiao-Hui; Zhang, Xiao-Bo; Zhu, Shou-Dong; Jin, Ling

2016-09-01

This paper is aimed to predict ecology suitability distribution of Gentianae Macrophyllae Radix and search the main ecological factors affecting the suitability distribution. The 313 distribution information about G. macrophylla, 186 distribution information about G. straminea, 343 distribution information about G. dauricaand 131 distribution information about G. crasicaulis were collected though investigation and network sharing platform data . The ecology suitable distribution factors for production Gentianae Macrophyllae Radix was analyzed respectively by the software of ArcGIS and MaxEnt with 55 environmental factors. The result of MaxEnt prediction was very well (AUC was above 0.9). The results of predominant factors analysis showed that precipitation and altitude were all the major factors impacting the ecology suitable of Getiana Macrophylla Radix production. G. macrophylla ecology suitable region was mainly concentrated in south of Gansu, Shanxi, central of Shaanxi and east of Qinghai provinces. G. straminea ecology suitable region was mainly concentrated in southwest of Gansu, east of Qinghai, north and northwest of Sichuan, east of Xizang province. G. daurica ecology suitable region was mainly concentrated in south and southwest of Gansu, east of Qinghai, Shanxi and north of Shaanxi province. G. crasicaulis ecology suitable region was mainly concentrated in Sichuan and north of Yunnan, east of Xizang, south of Gansu and east of Qinghai province. The ecological suitability distribution result of Gentianae Macrophyllae Radix was consistent with each species actual distribution. The study could provide reference for the collection and protection of wild resources, meanwhile, provide the basis for the selection of cultivation area of Gentiana Macrophylla Radix. Copyright© by the Chinese Pharmaceutical Association.

Environmental Factors Affecting Asthma and Allergies: Predicting and Simulating Downwind Exposure to Airborne Pollen

NASA Technical Reports Server (NTRS)

Luvall, Jeffrey; Estes, Sue; Sprigg, William A.; Nickovic, Slobodan; Huete, Alfredo; Solano, Ramon; Ratana, Piyachat; Jiang, Zhangyan; Flowers, Len; Zelicoff, Alan

2009-01-01

This slide presentation reviews the environmental factors that affect asthma and allergies and work to predict and simulate the downwind exposure to airborne pollen. Using a modification of Dust REgional Atmosphere Model (DREAM) that incorporates phenology (i.e. PREAM) the aim was to predict concentrations of pollen in time and space. The strategy for using the model to simulate downwind pollen dispersal, and evaluate the results. Using MODerate-resolution Imaging Spectroradiometer (MODIS), to get seasonal sampling of Juniper, the pollen chosen for the study, land cover on a near daily basis. The results of the model are reviewed.

A Physiologically Based Pharmacokinetic Model to Predict the Pharmacokinetics of Highly Protein-Bound Drugs and Impact of Errors in Plasma Protein Binding

PubMed Central

Ye, Min; Nagar, Swati; Korzekwa, Ken

2015-01-01

Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data was often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding, and blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for terminal elimination half-life (t1/2, 100% of drugs), peak plasma concentration (Cmax, 100%), area under the plasma concentration-time curve (AUC0–t, 95.4%), clearance (CLh, 95.4%), mean retention time (MRT, 95.4%), and steady state volume (Vss, 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. PMID:26531057

New particle formation and growth in biomass burning plumes: An important source of cloud condensation nuclei

NASA Astrophysics Data System (ADS)

Hennigan, Christopher J.; Westervelt, Daniel M.; Riipinen, Ilona; Engelhart, Gabriella J.; Lee, Taehyoung; Collett, Jeffrey L., Jr.; Pandis, Spyros N.; Adams, Peter J.; Robinson, Allen L.

2012-05-01

Experiments were performed in an environmental chamber to characterize the effects of photo-chemical aging on biomass burning emissions. Photo-oxidation of dilute exhaust from combustion of 12 different North American fuels induced significant new particle formation that increased the particle number concentration by a factor of four (median value). The production of secondary organic aerosol caused these new particles to grow rapidly, significantly enhancing cloud condensation nuclei (CCN) concentrations. Using inputs derived from these new data, global model simulations predict that nucleation in photo-chemically aging fire plumes produces dramatically higher CCN concentrations over widespread areas of the southern hemisphere during the dry, burning season (Sept.-Oct.), improving model predictions of surface CCN concentrations. The annual indirect forcing from CCN resulting from nucleation and growth in biomass burning plumes is predicted to be -0.2 W m-2, demonstrating that this effect has a significant impact on climate that has not been previously considered.

Accumulation of 2,3,7,8-tetrachlorodibenzo-p-dioxin by rainbow trout (Onchorhynchus mykiss) at environmentally relevant dietary concentrations

USGS Publications Warehouse

Jones, Paul D.; Kannan, Kurunthachalam; Newsted, John L.; Tillitt, Donald E.; Williams, Lisa L.; Giesy, John P.

2001-01-01

Rainbow trout were fed a diet containing 1.8, 18, or 90 pg/g 3H-2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) for up to 320 d. Concentrations of TCDD were determined in muscle, liver, and ovaries at 100, 150, 200, and 250 d. Concentrations of TCDD reached an apparent steady-state concentration in liver after 100 d of exposure, whereas concentrations in other tissues continued to increase until 150 d of exposure. The greatest portion of the total mass of TCDD was present in the muscle tissue with lesser proportions in other organs. As the ovaries developed before spawning, an increase occurred in the total mass of TCDD present in this tissue. The assimilation rate of TCDD during the initial 100 d of the exposure was determined to be between 10 and 30%. This is somewhat less than estimates derived based on both uptake and elimination constants determined during shorter exposures. Biomagnification factors (BMFs) were estimated for all tissues and exposure concentrations, and at all exposure periods. Lipid-normalized BMFs for muscle ranged from 0.38 to 1.51, which is consistent with the value of 1.0 predicted from fugacity theory. Uptake and depuration rate constants were determined and used to predict individual organ TCDD concentrations. Comparison with observed values indicated that the model could be used to predict tissue concentrations from the known concentrations of TCDD in food. This model will allow more refined risk assessments by predicting TCDD concentrations in sensitive tissues such as developing eggs.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hodgson, A.T.; Apte, M.G.; Shendell, D.G.

Detailed studies of a new manufactured house and four new industrialized relocatable school classrooms were conducted to determine the emission sources of formaldehyde and other VOCs and to identify and implement source reduction practices. Procedures were developed to generate VOC emission factors that allowed reasonably accurate predictions of indoor air VOC concentrations. Based on the identified sources of formaldehyde and other aldehydes, practices were developed to reduce the concentrations of these compounds in new house construction. An alternate ceiling panel reduced formaldehyde concentrations in the classrooms. Overall, the classrooms had relatively low VOC concentrations.

Groundwater nitrate contamination: Factors and indicators

PubMed Central

Wick, Katharina; Heumesser, Christine; Schmid, Erwin

2012-01-01

Identifying significant determinants of groundwater nitrate contamination is critical in order to define sensible agri-environmental indicators that support the design, enforcement, and monitoring of regulatory policies. We use data from approximately 1200 Austrian municipalities to provide a detailed statistical analysis of (1) the factors influencing groundwater nitrate contamination and (2) the predictive capacity of the Gross Nitrogen Balance, one of the most commonly used agri-environmental indicators. We find that the percentage of cropland in a given region correlates positively with nitrate concentration in groundwater. Additionally, environmental characteristics such as temperature and precipitation are important co-factors. Higher average temperatures result in lower nitrate contamination of groundwater, possibly due to increased evapotranspiration. Higher average precipitation dilutes nitrates in the soil, further reducing groundwater nitrate concentration. Finally, we assess whether the Gross Nitrogen Balance is a valid predictor of groundwater nitrate contamination. Our regression analysis reveals that the Gross Nitrogen Balance is a statistically significant predictor for nitrate contamination. We also show that its predictive power can be improved if we account for average regional precipitation. The Gross Nitrogen Balance predicts nitrate contamination in groundwater more precisely in regions with higher average precipitation. PMID:22906701

Predictors of 25-Hydroxyvitamin D Concentration Measured at Multiple Time Points in a Multiethnic Population.

PubMed

Knight, Julia A; Wong, Jody; Cole, David E C; Lee, Tim K; Parra, Esteban J

2017-11-15

The evidence for a relationship between serum vitamin D levels and nonskeletal health outcomes is inconsistent. The validity of single or predicted measurements of 25-hydroxyvitamin D (25(OH)D) concentration is unknown, as levels of this biomarker are highly seasonally variable. We compared models of 25(OH)D measured at baseline, at multiple time points throughout the year, and averaged over the year among 309 persons in Toronto, Ontario, Canada (43°N latitude) during 2009-2013. Information and blood samples were collected every 2 months. Baseline and average 25(OH)D concentrations were correlated (r = 0.88). Major factors associated with 25(OH)D level were similar across models and included race/ethnicity (concentrations in non-European groups were lower than those in Europeans), vitamin D supplement use of ≥1,000 IU/day (18.9 nmol/L (95% confidence interval (CI): 16.1, 21.8) vs. no supplement use in a full data set with all factors), and the presence of the group-specific component/vitamin D binding protein gene (GC/DBP) rs4588 functional polymorphism (AA vs. CC: -16.7 nmol/L (95% CI: -26.2, -7.1); CA vs. CC: -10.7 nmol/L (95% CI: -14.9, -6.5)). Most factors had similar associations in Europeans and non-Europeans. Genetic factors may play a greater role in average 25(OH)D concentrations. Prediction models for 25(OH)D are challenging and population-specific, but use of genetic factors along with a few common population-relevant, quantifiable nongenetic factors with strong associations may be the most feasible approach to vitamin D assessment over time. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The importance of expressing antimicrobial agents on water basis in growth/no growth interface models: a case study for Zygosaccharomyces bailii.

PubMed

Dang, T D T; Vermeulen, A; Mertens, L; Geeraerd, A H; Van Impe, J F; Devlieghere, F

2011-01-31

In a previous study on Zygosaccharomyces bailii, three growth/no growth models have been developed, predicting growth probability of the yeast at different conditions typical for acidified foods (Dang, T.D.T., Mertens, L., Vermeulen, A., Geeraerd, A.H., Van Impe, J.F., Debevere, J., Devlieghere, F., 2010. Modeling the growth/no growth boundary of Z. bailii in acidic conditions: A contribution to the alternative method to preserve foods without using chemical preservatives. International Journal of Food Microbiology 137, 1-12). In these broth-based models, the variables were pH, water activity and acetic acid, with acetic acid concentration expressed in volume % on the total culture medium (i.e., broth). To continue the previous study, validation experiments were performed for 15 selected combinations of intrinsic factors to assess the performance of the model at 22°C (60days) in a real food product (ketchup). Although the majority of experimental results were consistent, some remarkable deviations between prediction and validation were observed, e.g., Z. bailii growth occurred in conditions where almost no growth had been predicted. A thorough investigation revealed that the difference between two ways of expressing acetic acid concentration (i.e., on broth basis and on water basis) is rather significant, particularly for media containing high amounts of dry matter. Consequently, the use of broth-based concentrations in the models was not appropriate. Three models with acetic acid concentration expressed on water basis were established and it was observed that predictions by these models well matched the validation results; therefore a "systematic error" in broth-based models was recognized. In practice, quantities of antimicrobial agents are often calculated based on the water content of food products. Hence, to assure reliable predictions and facilitate the application of models (developed from lab media with high dry matter contents), it is important to express antimicrobial agents' concentrations on a common basis-the water content. Reviews over other published growth/no growth models in literature are carried out and expressions of the stress factors' concentrations (on broth basis) found in these models confirm this finding. Copyright © 2010 Elsevier B.V. All rights reserved.

Comparison of chlorine and ammonia concentration field trial data with calculated results from a Gaussian atmospheric transport and dispersion model.

PubMed

Bauer, Timothy J

2013-06-15

The Jack Rabbit Test Program was sponsored in April and May 2010 by the Department of Homeland Security Transportation Security Administration to generate source data for large releases of chlorine and ammonia from transport tanks. In addition to a variety of data types measured at the release location, concentration versus time data was measured using sensors at distances up to 500 m from the tank. Release data were used to create accurate representations of the vapor flux versus time for the ten releases. This study was conducted to determine the importance of source terms and meteorological conditions in predicting downwind concentrations and the accuracy that can be obtained in those predictions. Each source representation was entered into an atmospheric transport and dispersion model using simplifying assumptions regarding the source characterization and meteorological conditions, and statistics for cloud duration and concentration at the sensor locations were calculated. A detailed characterization for one of the chlorine releases predicted 37% of concentration values within a factor of two, but cannot be considered representative of all the trials. Predictions of toxic effects at 200 m are relevant to incidents involving 1-ton chlorine tanks commonly used in parts of the United States and internationally. Published by Elsevier B.V.

Core tungsten radiation diagnostic calibration by small shell pellet injection in the DIII-D tokamak

DOE PAGES

Hollmann, Eric M.; Commaux, Nicolas; Shiraki, Daisuke; ...

2017-10-04

Injection of small (OD = 0.8 mm) plastic pellets carrying embedded smaller (10 μg) tungsten grains is used to check calibrations of core tungsten line radiation diagnostics in support of the 2016 tungsten rings campaign in the DIII-D tokamak. The total (1 eV – 10 keV) and soft x-ray (1 keV – 10 keV) brightnesses we observed were found to be reasonably well (< factor 2) predicted using existing calibration factors and rate calculations. Individual core (EUV/SXR) tungsten line brightnesses appear to be somewhat less reliable (factor 2-4) for prediction of core tungsten concentration.

Core tungsten radiation diagnostic calibration by small shell pellet injection in the DIII-D tokamak

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hollmann, Eric M.; Commaux, Nicolas; Shiraki, Daisuke

Injection of small (OD = 0.8 mm) plastic pellets carrying embedded smaller (10 μg) tungsten grains is used to check calibrations of core tungsten line radiation diagnostics in support of the 2016 tungsten rings campaign in the DIII-D tokamak. The total (1 eV – 10 keV) and soft x-ray (1 keV – 10 keV) brightnesses we observed were found to be reasonably well (< factor 2) predicted using existing calibration factors and rate calculations. Individual core (EUV/SXR) tungsten line brightnesses appear to be somewhat less reliable (factor 2-4) for prediction of core tungsten concentration.

Size distribution and concentrations of heavy metals in atmospheric aerosols originating from industrial emissions as predicted by the HYSPLIT model

NASA Astrophysics Data System (ADS)

Chen, Bing; Stein, Ariel F.; Maldonado, Pabla Guerrero; Sanchez de la Campa, Ana M.; Gonzalez-Castanedo, Yolanda; Castell, Nuria; de la Rosa, Jesus D.

2013-06-01

This study presents a description of the emission, transport, dispersion, and deposition of heavy metals contained in atmospheric aerosols emitted from a large industrial complex in southern Spain using the HYSPLIT model coupled with high- (MM5) and low-resolution (GDAS) meteorological simulations. The dispersion model was configured to simulate eight size fractions (<0.33, 0.66, 1.3, 2.5, 5, 14, 17, and >17 μm) of metals based on direct measurements taken at the industrial emission stacks. Twelve stacks in four plants were studied and the stacks showed considerable differences for both emission fluxes and size ranges of metals. We model the dispersion of six major metals; Cr, Co, Ni, La, Zn, and Mo, which represent 77% of the total mass of the 43 measured elements. The prediction shows that the modeled industrial emissions produce an enrichment of heavy metals by a factor of 2-5 for local receptor sites when compared to urban and rural background areas in Spain. The HYSPLIT predictions based on the meteorological fields from MM5 show reasonable consistence with the temporal evolution of concentrations of Cr, Co, and Ni observed at three sites downwind of the industrial area. The magnitude of concentrations of metals at two receptors was underestimated for both MM5 (by a factor of 2-3) and GDAS (by a factor of 4-5) meteorological runs. The model prediction shows that heavy metal pollution from industrial emissions in this area is dominated by the ultra-fine (<0.66 μm) and fine (<2.5 μm) size fractions.

Fetal hemoglobin, α1-microglobulin and hemopexin are potential predictive first trimester biomarkers for preeclampsia.

PubMed

Anderson, Ulrik Dolberg; Gram, Magnus; Ranstam, Jonas; Thilaganathan, Basky; Kerström, Bo; Hansson, Stefan R

2016-04-01

Overproduction of cell-free fetal hemoglobin (HbF) in the preeclamptic placenta has been recently implicated as a new etiological factor of preeclampsia. In this study, maternal serum levels of HbF and the endogenous hemoglobin/heme scavenging systems were evaluated as predictive biomarkers for preeclampsia in combination with uterine artery Doppler ultrasound. Case-control study including 433 women in early pregnancy (mean 13.7weeks of gestation) of which 86 subsequently developed preeclampsia. The serum concentrations of HbF, total cell-free hemoglobin, hemopexin, haptoglobin and α1-microglobulin were measured in maternal serum. All patients were examined with uterine artery Doppler ultrasound. Logistic regression models were developed, which included the biomarkers, ultrasound indices, and maternal risk factors. There were significantly higher serum concentrations of HbF and α1-microglobulin and significantly lower serum concentrations of hemopexin in patients who later developed preeclampsia. The uterine artery Doppler ultrasound results showed significantly higher pulsatility index values in the preeclampsia group. The optimal prediction model was obtained by combining HbF, α1-microglobulin and hemopexin in combination with the maternal characteristics parity, diabetes and pre-pregnancy hypertension. The optimal sensitivity for all preeclampsia was 60% at 95% specificity. Overproduction of placentally derived HbF and depletion of hemoglobin/heme scavenging mechanisms are involved in the pathogenesis of preeclampsia. The combination of HbF and α1-microglobulin and/or hemopexin may serve as a prediction model for preeclampsia in combination with maternal risk factors and/or uterine artery Doppler ultrasound. Copyright © 2016 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. All rights reserved.

Model for breast cancer survival: relative prognostic roles of axillary nodal status, TNM stage, estrogen receptor concentration, and tumor necrosis.

PubMed

Shek, L L; Godolphin, W

1988-10-01

The independent prognostic effects of certain clinical and pathological variables measured at the time of primary diagnosis were assessed with Cox multivariate regression analysis. The 859 patients with primary breast cancer, on which the proportional hazards model was based, had a median follow-up of 60 months. Axillary nodal status (categorized as N0, N1-3 or N4+) was the most significant and independent factor in overall survival, but inclusion of TNM stage, estrogen receptor (ER) concentration and tumor necrosis significantly improved survival predictions. Predictions made with the model showed striking subset survival differences within stage: 5-year survival from 36% (N4+, loge[ER] = 0, marked necrosis) to 96% (N0, loge[ER] = 6, no necrosis) in TNM I, and from 0 to 70% for the same categories in TNM IV. Results of the model were used to classify patients into four distinct risk groups according to a derived hazard index. An 8-fold variation in survival was seen with the highest (greater than 3) to lowest index values (less than 1). Each hazard index level included patients with varied combinations of the above factors, but could be considered to denote the same degree of risk of breast cancer mortality. A model with ER concentration, nodal status, and tumor necrosis was found to best predict survival after disease recurrence in 369 patients, thus confirming the enduring biological significance of these factors.

Kinetic Model Facilitates Analysis of Fibrin Generation and Its Modulation by Clotting Factors: Implications for Hemostasis-Enhancing Therapies

DTIC Science & Technology

2014-01-01

facilitates analysis of fibrin generation and its modulation by clotting factors : implications for hemostasis-enhancing therapies† Alexander Y...investigate the ability of fibrinogen and a recently proposed prothrombin complex concentrate composition, PCC-AT (a combination of the clotting factors II...kinetics. Moreover, the model qualitatively predicted the impact of tissue factor and tPA/tenecteplase level variations on the fibrin output. In the

Modelling dimercaptosuccinic acid (DMSA) plasma kinetics in humans.

PubMed

van Eijkeren, Jan C H; Olie, J Daniël N; Bradberry, Sally M; Vale, J Allister; de Vries, Irma; Meulenbelt, Jan; Hunault, Claudine C

2016-11-01

No kinetic models presently exist which simulate the effect of chelation therapy on lead blood concentrations in lead poisoning. Our aim was to develop a kinetic model that describes the kinetics of dimercaptosuccinic acid (DMSA; succimer), a commonly used chelating agent, that could be used in developing a lead chelating model. This was a kinetic modelling study. We used a two-compartment model, with a non-systemic gastrointestinal compartment (gut lumen) and the whole body as one systemic compartment. The only data available from the literature were used to calibrate the unknown model parameters. The calibrated model was then validated by comparing its predictions with measured data from three different experimental human studies. The model predicted total DMSA plasma and urine concentrations measured in three healthy volunteers after ingestion of DMSA 10 mg/kg. The model was then validated by using data from three other published studies; it predicted concentrations within a factor of two, representing inter-human variability. A simple kinetic model simulating the kinetics of DMSA in humans has been developed and validated. The interest of this model lies in the future potential to use it to predict blood lead concentrations in lead-poisoned patients treated with DMSA.

Prediction models for transfer of arsenic from soil to corn grain (Zea mays L.).

PubMed

Yang, Hua; Li, Zhaojun; Long, Jian; Liang, Yongchao; Xue, Jianming; Davis, Murray; He, Wenxiang

2016-04-01

In this study, the transfer of arsenic (As) from soil to corn grain was investigated in 18 soils collected from throughout China. The soils were treated with three concentrations of As and the transfer characteristics were investigated in the corn grain cultivar Zhengdan 958 in a greenhouse experiment. Through stepwise multiple-linear regression analysis, prediction models were developed combining the As bioconcentration factor (BCF) of Zhengdan 958 and soil pH, organic matter (OM) content, and cation exchange capacity (CEC). The possibility of applying the Zhengdan 958 model to other cultivars was tested through a cross-cultivar extrapolation approach. The results showed that the As concentration in corn grain was positively correlated with soil pH. When the prediction model was applied to non-model cultivars, the ratio ranges between the predicted and measured BCF values were within a twofold interval between predicted and measured values. The ratios were close to a 1:1 relationship between predicted and measured values. It was also found that the prediction model (Log [BCF]=0.064 pH-2.297) could effectively reduce the measured BCF variability for all non-model corn cultivars. The novel model is firstly developed for As concentration in crop grain from soil, which will be very useful for understanding the As risk in soil environment.

Dietary Iodine Sufficiency and Moderate Insufficiency in the Lactating Mother and Nursing Infant: A Computational Perspective

PubMed Central

Fisher, W.; Wang, Jian; George, Nysia I.; Gearhart, Jeffery M.; McLanahan, Eva D.

2016-01-01

The Institute of Medicine recommends that lactating women ingest 290 μg iodide/d and a nursing infant, less than two years of age, 110 μg/d. The World Health Organization, United Nations Children’s Fund, and International Council for the Control of Iodine Deficiency Disorders recommend population maternal and infant urinary iodide concentrations ≥ 100 μg/L to ensure iodide sufficiency. For breast milk, researchers have proposed an iodide concentration range of 150–180 μg/L indicates iodide sufficiency for the mother and infant, however no national or international guidelines exist for breast milk iodine concentration. For the first time, a lactating woman and nursing infant biologically based model, from delivery to 90 days postpartum, was constructed to predict maternal and infant urinary iodide concentration, breast milk iodide concentration, the amount of iodide transferred in breast milk to the nursing infant each day and maternal and infant serum thyroid hormone kinetics. The maternal and infant models each consisted of three sub-models, iodide, thyroxine (T4), and triiodothyronine (T3). Using our model to simulate a maternal intake of 290 μg iodide/d, the average daily amount of iodide ingested by the nursing infant, after 4 days of life, gradually increased from 50 to 101 μg/day over 90 days postpartum. The predicted average lactating mother and infant urinary iodide concentrations were both in excess of 100 μg/L and the predicted average breast milk iodide concentration, 157 μg/L. The predicted serum thyroid hormones (T4, free T4 (fT4), and T3) in both the nursing infant and lactating mother were indicative of euthyroidism. The model was calibrated using serum thyroid hormone concentrations for lactating women from the United States and was successful in predicting serum T4 and fT4 levels (within a factor of two) for lactating women in other countries. T3 levels were adequately predicted. Infant serum thyroid hormone levels were adequately predicted for most data. For moderate iodide deficient conditions, where dietary iodide intake may range from 50 to 150 μg/d for the lactating mother, the model satisfactorily described the iodide measurements, although with some variation, in urine and breast milk. Predictions of serum thyroid hormones in moderately iodide deficient lactating women (50 μg/d) and nursing infants did not closely agree with mean reported serum thyroid hormone levels, however, predictions were usually within a factor of two. Excellent agreement between prediction and observation was obtained for a recent moderate iodide deficiency study in lactating women. Measurements included iodide levels in urine of infant and mother, iodide in breast milk, and serum thyroid hormone levels in infant and mother. A maternal iodide intake of 50 μg/d resulted in a predicted 29–32% reduction in serum T4 and fT4 in nursing infants, however the reduced serum levels of T4 and fT4 were within most of the published reference intervals for infant. This biologically based model is an important first step at integrating the rapid changes that occur in the thyroid system of the nursing newborn in order to predict adverse outcomes from exposure to thyroid acting chemicals, drugs, radioactive materials or iodine deficiency. PMID:26930410

Dietary Iodine Sufficiency and Moderate Insufficiency in the Lactating Mother and Nursing Infant: A Computational Perspective.

PubMed

Fisher, W; Wang, Jian; George, Nysia I; Gearhart, Jeffery M; McLanahan, Eva D

2016-01-01

The Institute of Medicine recommends that lactating women ingest 290 μg iodide/d and a nursing infant, less than two years of age, 110 μg/d. The World Health Organization, United Nations Children's Fund, and International Council for the Control of Iodine Deficiency Disorders recommend population maternal and infant urinary iodide concentrations ≥ 100 μg/L to ensure iodide sufficiency. For breast milk, researchers have proposed an iodide concentration range of 150-180 μg/L indicates iodide sufficiency for the mother and infant, however no national or international guidelines exist for breast milk iodine concentration. For the first time, a lactating woman and nursing infant biologically based model, from delivery to 90 days postpartum, was constructed to predict maternal and infant urinary iodide concentration, breast milk iodide concentration, the amount of iodide transferred in breast milk to the nursing infant each day and maternal and infant serum thyroid hormone kinetics. The maternal and infant models each consisted of three sub-models, iodide, thyroxine (T4), and triiodothyronine (T3). Using our model to simulate a maternal intake of 290 μg iodide/d, the average daily amount of iodide ingested by the nursing infant, after 4 days of life, gradually increased from 50 to 101 μg/day over 90 days postpartum. The predicted average lactating mother and infant urinary iodide concentrations were both in excess of 100 μg/L and the predicted average breast milk iodide concentration, 157 μg/L. The predicted serum thyroid hormones (T4, free T4 (fT4), and T3) in both the nursing infant and lactating mother were indicative of euthyroidism. The model was calibrated using serum thyroid hormone concentrations for lactating women from the United States and was successful in predicting serum T4 and fT4 levels (within a factor of two) for lactating women in other countries. T3 levels were adequately predicted. Infant serum thyroid hormone levels were adequately predicted for most data. For moderate iodide deficient conditions, where dietary iodide intake may range from 50 to 150 μg/d for the lactating mother, the model satisfactorily described the iodide measurements, although with some variation, in urine and breast milk. Predictions of serum thyroid hormones in moderately iodide deficient lactating women (50 μg/d) and nursing infants did not closely agree with mean reported serum thyroid hormone levels, however, predictions were usually within a factor of two. Excellent agreement between prediction and observation was obtained for a recent moderate iodide deficiency study in lactating women. Measurements included iodide levels in urine of infant and mother, iodide in breast milk, and serum thyroid hormone levels in infant and mother. A maternal iodide intake of 50 μg/d resulted in a predicted 29-32% reduction in serum T4 and fT4 in nursing infants, however the reduced serum levels of T4 and fT4 were within most of the published reference intervals for infant. This biologically based model is an important first step at integrating the rapid changes that occur in the thyroid system of the nursing newborn in order to predict adverse outcomes from exposure to thyroid acting chemicals, drugs, radioactive materials or iodine deficiency.

Derivation of Soil Ecological Criteria for Copper in Chinese Soils

PubMed Central

Wang, Xiaoqing; Wei, Dongpu; Ma, Yibing; McLaughlin, Mike J.

2015-01-01

Considerable information on copper (Cu) ecotoxicity as affected by biological species and abiotic properties of soils has been collected from the last decade in the present study. The information on bioavailability/ecotoxicity, species sensitivity and differences in laboratory and field ecotoxicity of Cu in different soils was collated and integrated to derive soil ecological criteria for Cu in Chinese soils, which were expressed as predicted no effect concentrations (PNEC). First, all ecotoxicity data of Cu from bioassays based on Chinese soils were collected and screened with given criteria to compile a database. Second, the compiled data were corrected with leaching and aging factors to minimize the differences between laboratory and field conditions. Before Cu ecotoxicity data were entered into a species sensitivity distribution (SSD), they were normalized with Cu ecotoxicity predictive models to modify the effects of soil properties on Cu ecotoxicity. The PNEC value was set equal to the hazardous concentration for x% of the species (HCx), which could be calculated from the SSD curves, without an additional assessment factor. Finally, predictive models for HCx based on soil properties were developed. The soil properties had a significant effect on the magnitude of HCx, with HC5 varying from 13.1 mg/kg in acidic soils to 51.9 mg/kg in alkaline non-calcareous soils. The two-factor predictive models based on soil pH and cation exchange capacity could predict HCx with determination coefficients (R2) of 0.82–0.91. The three-factor predictive models – that took into account the effect of soil organic carbon – were more accurate than two-factor models, with R2 of 0.85–0.99. The predictive models obtained here could be used to calculate soil-specific criteria. All results obtained here could provide a scientific basis for revision of current Chinese soil environmental quality standards, and the approach adopted in this study could be used as a pragmatic framework for developing soil ecological criteria for other trace elements in soils. PMID:26207783

Dynamic thermal analysis of a concentrated photovoltaic system

NASA Astrophysics Data System (ADS)

Avrett, John T., II; Cain, Stephen C.; Pochet, Michael

2012-02-01

Concentrated photovoltaic (PV) technology represents a growing market in the field of terrestrial solar energy production. As the demand for renewable energy technologies increases, further importance is placed upon the modeling, design, and simulation of these systems. Given the U.S. Air Force cultural shift towards energy awareness and conservation, several concentrated PV systems have been installed on Air Force installations across the country. However, there has been a dearth of research within the Air Force devoted to understanding these systems in order to possibly improve the existing technologies. This research presents a new model for a simple concentrated PV system. This model accurately determines the steady state operating temperature as a function of the concentration factor for the optical part of the concentrated PV system, in order to calculate the optimum concentration that maximizes power output and efficiency. The dynamic thermal model derived is validated experimentally using a commercial polysilicon solar cell, and is shown to accurately predict the steady state temperature and ideal concentration factor.

A physiologically based pharmacokinetic model to predict the pharmacokinetics of highly protein-bound drugs and the impact of errors in plasma protein binding.

PubMed

Ye, Min; Nagar, Swati; Korzekwa, Ken

2016-04-01

Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data were often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding and the blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate the model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for the terminal elimination half-life (t1/2 , 100% of drugs), peak plasma concentration (Cmax , 100%), area under the plasma concentration-time curve (AUC0-t , 95.4%), clearance (CLh , 95.4%), mean residence time (MRT, 95.4%) and steady state volume (Vss , 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Use of airborne hyperspectral imagery to map soil parameters in tilled agricultural fields

USGS Publications Warehouse

Hively, W. Dean; McCarty, Gregory W.; Reeves, James B.; Lang, Megan W.; Oesterling, Robert A.; Delwiche, Stephen R.

2011-01-01

Soil hyperspectral reflectance imagery was obtained for six tilled (soil) agricultural fields using an airborne imaging spectrometer (400–2450 nm, ~10 nm resolution, 2.5 m spatial resolution). Surface soil samples (n = 315) were analyzed for carbon content, particle size distribution, and 15 agronomically important elements (Mehlich-III extraction). When partial least squares (PLS) regression of imagery-derived reflectance spectra was used to predict analyte concentrations, 13 of the 19 analytes were predicted with R2 > 0.50, including carbon (0.65), aluminum (0.76), iron (0.75), and silt content (0.79). Comparison of 15 spectral math preprocessing treatments showed that a simple first derivative worked well for nearly all analytes. The resulting PLS factors were exported as a vector of coefficients and used to calculate predicted maps of soil properties for each field. Image smoothing with a 3 × 3 low-pass filter prior to spectral data extraction improved prediction accuracy. The resulting raster maps showed variation associated with topographic factors, indicating the effect of soil redistribution and moisture regime on in-field spatial variability. High-resolution maps of soil analyte concentrations can be used to improve precision environmental management of farmlands.

Interaction and influence of two creeks on Escherichia coli concentrations of nearby beaches: Exploration of predictability and mechanisms

USGS Publications Warehouse

Nevers, M.B.; Whitman, R.L.; Frick, W.E.; Ge, Z.

2007-01-01

The impact of river outfalls on beach water quality depends on numerous interacting factors. The delivery of contaminants by multiple creeks greatly complicates understanding of the source contributions, especially when pollution might originate up- or down-coast of beaches. We studied two beaches along Lake Michigan that are located between two creek outfalls to determine the hydrometeorologic factors influencing near-shore microbiologic water quality and the relative impact of the creeks. The creeks continuously delivered water with high concentrations of Escherichia coli to Lake Michigan, and the direction of transport of these bacteria was affected by current direction. Current direction reversals were associated with elevated E. coli concentrations at Central Avenue beach. Rainfall, barometric pressure, wave height, wave period, and creek specific conductance were significantly related to E. coli concentration at the beaches and were the parameters used in predictive models that best described E. coli variation at the two beaches. Multiple inputs to numerous beaches complicates the analysis and understanding of the relative relationship of sources but affords opportunities for showing how these complex creek inputs might interact to yield collective or individual effects on beach water quality.

Explicit solution of integrated 1 - exp equation for predicting accumulation and decline of concentrations for drugs obeying nonlinear saturation kinetics.

PubMed

Keller, Frieder; Hartmann, Bertram; Czock, David

2009-12-01

To describe nonlinear, saturable pharmacokinetics, the Michaelis-Menten equation is frequently used. However, the Michaelis-Menten equation has no integrated solution for concentrations but only for the time factor. Application of the Lambert W function was proposed recently to obtain an integrated solution of the Michaelis-Menten equation. As an alternative to the Michaelis-Menten equation, a 1 - exp equation has been used to describe saturable kinetics, with the advantage that the integrated 1 - exp equation has an explicit solution for concentrations. We used the integrated 1 - exp equation to predict the accumulation kinetics and the nonlinear concentration decline for a proposed fictive drug. In agreement with the recently proposed method, we found that for the integrated 1 - exp equation no steady state is obtained if the maximum rate of change in concentrations (Vmax) within interval (Tau) is less than the difference between peak and trough concentrations (Vmax x Tau < C peak - C trough).

Correlations of Maternal Buprenorphine Dose, Buprenorphine, and Metabolite Concentrations in Meconium with Neonatal Outcomes

PubMed Central

Kacinko, SL; Jones, HE; Johnson, RE; Choo, RE; Huestis, MA

2009-01-01

For the first time, relationships among maternal buprenorphine dose, meconium buprenorphine and metabolite concentrations, and neonatal outcomes are reported. Free and total buprenorphine and norbuprenorphine, nicotine, opiates, cocaine, benzodiazepines, and metabolites were quantified in meconium from 10 infants born to women who had received buprenorphine during pregnancy. Neither cumulative nor total third-trimester maternal buprenorphine dose predicted meconium concentrations or neonatal outcomes. Total buprenorphine meconium concentrations and buprenorphine/norbuprenorphine ratios were significantly related to neonatal abstinence syndrome (NAS ) scores >4. As free buprenorphine concentration and percentage free buprenorphine increased, head circumference decreased. Thrice-weekly urine tests for opiates, cocaine, and benzodiazepines and self-reported smoking data from the mother were compared with data from analysis of the meconium to estimate in utero exposure. Time of last drug use and frequency of use during the third trimester were important factors associated with drug-positive meconium specimens. The results suggest that buprenorphine and metabolite concentrations in the meconium may predict the onset and frequency of NAS. PMID:18701886

Effects of user puff topography, device voltage, and liquid nicotine concentration on electronic cigarette nicotine yield: measurements and model predictions.

PubMed

Talih, Soha; Balhas, Zainab; Eissenberg, Thomas; Salman, Rola; Karaoghlanian, Nareg; El Hellani, Ahmad; Baalbaki, Rima; Saliba, Najat; Shihadeh, Alan

2015-02-01

Some electronic cigarette (ECIG) users attain tobacco cigarette-like plasma nicotine concentrations while others do not. Understanding the factors that influence ECIG aerosol nicotine delivery is relevant to regulation, including product labeling and abuse liability. These factors may include user puff topography, ECIG liquid composition, and ECIG design features. This study addresses how these factors can influence ECIG nicotine yield. Aerosols were machine generated with 1 type of ECIG cartridge (V4L CoolCart) using 5 distinct puff profiles representing a tobacco cigarette smoker (2-s puff duration, 33-ml/s puff velocity), a slow average ECIG user (4 s, 17 ml/s), a fast average user (4 s, 33 ml/s), a slow extreme user (8 s, 17 ml/s), and a fast extreme user (8 s, 33 ml/s). Output voltage (3.3-5.2 V or 3.0-7.5 W) and e-liquid nicotine concentration (18-36 mg/ml labeled concentration) were varied. A theoretical model was also developed to simulate the ECIG aerosol production process and to provide insight into the empirical observations. Nicotine yields from 15 puffs varied by more than 50-fold across conditions. Experienced ECIG user profiles (longer puffs) resulted in higher nicotine yields relative to the tobacco smoker (shorter puffs). Puff velocity had no effect on nicotine yield. Higher nicotine concentration and higher voltages resulted in higher nicotine yields. These results were predicted well by the theoretical model (R (2) = 0.99). Depending on puff conditions and product features, 15 puffs from an ECIG can provide far less or far more nicotine than a single tobacco cigarette. ECIG emissions can be predicted using physical principles, with knowledge of puff topography and a few ECIG device design parameters. © The Author 2014. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Effects of User Puff Topography, Device Voltage, and Liquid Nicotine Concentration on Electronic Cigarette Nicotine Yield: Measurements and Model Predictions

PubMed Central

Talih, Soha; Balhas, Zainab; Eissenberg, Thomas; Salman, Rola; Karaoghlanian, Nareg; El Hellani, Ahmad; Baalbaki, Rima; Saliba, Najat

2015-01-01

Introduction: Some electronic cigarette (ECIG) users attain tobacco cigarette–like plasma nicotine concentrations while others do not. Understanding the factors that influence ECIG aerosol nicotine delivery is relevant to regulation, including product labeling and abuse liability. These factors may include user puff topography, ECIG liquid composition, and ECIG design features. This study addresses how these factors can influence ECIG nicotine yield. Methods: Aerosols were machine generated with 1 type of ECIG cartridge (V4L CoolCart) using 5 distinct puff profiles representing a tobacco cigarette smoker (2-s puff duration, 33-ml/s puff velocity), a slow average ECIG user (4 s, 17 ml/s), a fast average user (4 s, 33 ml/s), a slow extreme user (8 s, 17 ml/s), and a fast extreme user (8 s, 33 ml/s). Output voltage (3.3–5.2 V or 3.0–7.5 W) and e-liquid nicotine concentration (18–36 mg/ml labeled concentration) were varied. A theoretical model was also developed to simulate the ECIG aerosol production process and to provide insight into the empirical observations. Results: Nicotine yields from 15 puffs varied by more than 50-fold across conditions. Experienced ECIG user profiles (longer puffs) resulted in higher nicotine yields relative to the tobacco smoker (shorter puffs). Puff velocity had no effect on nicotine yield. Higher nicotine concentration and higher voltages resulted in higher nicotine yields. These results were predicted well by the theoretical model (R 2 = 0.99). Conclusions: Depending on puff conditions and product features, 15 puffs from an ECIG can provide far less or far more nicotine than a single tobacco cigarette. ECIG emissions can be predicted using physical principles, with knowledge of puff topography and a few ECIG device design parameters. PMID:25187061

A Comprehensive Review on the Predictive Performance of the Sheiner-Tozer and Derivative Equations for the Correction of Phenytoin Concentrations.

PubMed

Kiang, Tony K L; Ensom, Mary H H

2016-04-01

In settings where free phenytoin concentrations are not available, the Sheiner-Tozer equation-Corrected total phenytoin concentration = Observed total phenytoin concentration/[(0.2 × Albumin) + 0.1]; phenytoin in µg/mL, albumin in g/dL-and its derivative equations are commonly used to correct for altered phenytoin binding to albumin. The objective of this article was to provide a comprehensive and updated review on the predictive performance of these equations in various patient populations. A literature search of PubMed, EMBASE, and Google Scholar was conducted using combinations of the following terms: Sheiner-Tozer, Winter-Tozer, phenytoin, predictive equation, precision, bias, free fraction. All English-language articles up to November 2015 (excluding abstracts) were evaluated. This review shows the Sheiner-Tozer equation to be biased and imprecise in various critical care, head trauma, and general neurology patient populations. Factors contributing to bias and imprecision include the following: albumin concentration, free phenytoin assay temperature, experimental conditions (eg, timing of concentration sampling, steady-state dosing conditions), renal function, age, concomitant medications, and patient type. Although derivative equations using varying albumin coefficients have improved accuracy (without much improvement in precision) in intensive care and elderly patients, these equations still require further validation. Further experiments are also needed to yield derivative equations with good predictive performance in all populations as well as to validate the equations' impact on actual patient efficacy and toxicity outcomes. More complex, multivariate predictive equations may be required to capture all variables that can potentially affect phenytoin pharmacokinetics and clinical therapeutic outcomes. © The Author(s) 2016.

Concentrating phenolic acids from Lonicera japonica by nanofiltration technology

NASA Astrophysics Data System (ADS)

Li, Cunyu; Ma, Yun; Li, Hongyang; Peng, Guoping

2017-03-01

Response surface analysis methodology was used to optimize the concentrate process of phenolic acids from Lonicera japonica by nanofiltration technique. On the basis of the influences of pressure, temperature and circulating volume, the retention rate of neochlorogenic acid, chlorogenic acid and 4-dicaffeoylquinic acid were selected as index, molecular weight cut-off of nanofiltration membrane, concentration and pH were selected as influencing factors during concentrate process. The experiment mathematical model was arranged according to Box-Behnken central composite experiment design. The optimal concentrate conditions were as following: nanofiltration molecular weight cut-off, 150 Da; solutes concentration, 18.34 µg/mL; pH, 4.26. The predicted value of retention rate was 97.99% under the optimum conditions, and the experimental value was 98.03±0.24%, which was in accordance with the predicted value. These results demonstrate that the combination of Box-Behnken design and response surface analysis can well optimize the concentrate process of Lonicera japonica water-extraction by nanofiltration, and the results provide the basis for nanofiltration concentrate for heat-sensitive traditional Chinese medicine.

Near-roadway monitoring of vehicle emissions as a function of mode of operation for light-duty vehicles.

PubMed

Wen, Dongqi; Zhai, Wenjuan; Xiang, Sheng; Hu, Zhice; Wei, Tongchuan; Noll, Kenneth E

2017-11-01

Determination of the effect of vehicle emissions on air quality near roadways is important because vehicles are a major source of air pollution. A near-roadway monitoring program was undertaken in Chicago between August 4 and October 30, 2014, to measure ultrafine particles, carbon dioxide, carbon monoxide, traffic volume and speed, and wind direction and speed. The objective of this study was to develop a method to relate short-term changes in traffic mode of operation to air quality near roadways using data averaged over 5-min intervals to provide a better understanding of the processes controlling air pollution concentrations near roadways. Three different types of data analysis are provided to demonstrate the type of results that can be obtained from a near-roadway sampling program based on 5-min measurements: (1) development of vehicle emission factors (EFs) for ultrafine particles as a function of vehicle mode of operation, (2) comparison of measured and modeled CO 2 concentrations, and (3) application of dispersion models to determine concentrations near roadways. EFs for ultrafine particles are developed that are a function of traffic volume and mode of operation (free flow and congestion) for light-duty vehicles (LDVs) under real-world conditions. Two air quality models-CALINE4 (California Line Source Dispersion Model, version 4) and AERMOD (American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model)-are used to predict the ultrafine particulate concentrations near roadways for comparison with measured concentrations. When using CALINE4 to predict air quality levels in the mixing cell, changes in surface roughness and stability class have no effect on the predicted concentrations. However, when using AERMOD to predict air quality in the mixing cell, changes in surface roughness have a significant impact on the predicted concentrations. The paper provides emission factors (EFs) that are a function of traffic volume and mode of operation (free flow and congestion) for LDVs under real-world conditions. The good agreement between monitoring and modeling results indicates that high-resolution, simultaneous measurements of air quality and meteorological and traffic conditions can be used to determine real-world, fleet-wide vehicle EFs as a function of vehicle mode of operation under actual driving conditions.

Simulation of Tracer Concentration Data in the Brush Creek Drainage Flow Using an Integrated Puff Model.

NASA Astrophysics Data System (ADS)

Rao, K. Shankar; Eckman, Richard M.; Hosker, Rayford P., Jr.

1989-07-01

During the 1984 ASCOT field study in Brush Creek Valley, two perfluorocarbon tracers were released into the nocturnal drainage flow at two different heights. The resulting surface concentrations were sampled at 90 sites, and vertical concentration profiles at 11 sites. These detailed tracer measurements provide a valuable dataset for developing and testing models of pollutant transport and dispersion in valleys.In this paper, we present the results of Gaussian puff model simulations of the tracer releases in Brush Creek Valley. The model was modified to account for the restricted lateral dispersion in the valley, and for the gross elevation differences between the release site and the receptors. The variable wind fields needed to transport the puffs were obtained by interpolation between wind profiles measured using tethered balloons at five along-valley sites. Direct turbulence measurements were used to estimate diffusion. Subsidence in the valley flow was included for elevated releases.Two test simulations-covering different nights, tracers, and release heights-were performed. The predicted hourly concentrations were compared with observations at 51 ground-level locations. At most sites, the predicted and observed concentrations agree within a factor of 2 to 6. For the elevated release simulation, the observed mean concentration is 40 pL/L, the predicted mean is 21 pL/L, the correlation coefficient between the observed and predicted concentrations is 0.24, and the index of agreement is 0.46. For the surface release simulation, the observed mean is 85 pL/L, and the predicted mean is 73 pL/L. The correlation coefficient is 0.23, and the index of agreement is 0.42. The results suggest that this modified puff model can be used as a practical tool for simulating pollutant transport and dispersion in deep valleys.

Physiologically Based Pharmacokinetic Model for Terbinafine in Rats and Humans

PubMed Central

Hosseini-Yeganeh, Mahboubeh; McLachlan, Andrew J.

2002-01-01

The aim of this study was to develop a physiologically based pharmacokinetic (PB-PK) model capable of describing and predicting terbinafine concentrations in plasma and tissues in rats and humans. A PB-PK model consisting of 12 tissue and 2 blood compartments was developed using concentration-time data for tissues from rats (n = 33) after intravenous bolus administration of terbinafine (6 mg/kg of body weight). It was assumed that all tissues except skin and testis tissues were well-stirred compartments with perfusion rate limitations. The uptake of terbinafine into skin and testis tissues was described by a PB-PK model which incorporates a membrane permeability rate limitation. The concentration-time data for terbinafine in human plasma and tissues were predicted by use of a scaled-up PB-PK model, which took oral absorption into consideration. The predictions obtained from the global PB-PK model for the concentration-time profile of terbinafine in human plasma and tissues were in close agreement with the observed concentration data for rats. The scaled-up PB-PK model provided an excellent prediction of published terbinafine concentration-time data obtained after the administration of single and multiple oral doses in humans. The estimated volume of distribution at steady state (Vss) obtained from the PB-PK model agreed with the reported value of 11 liters/kg. The apparent volume of distribution of terbinafine in skin and adipose tissues accounted for 41 and 52%, respectively, of the Vss for humans, indicating that uptake into and redistribution from these tissues dominate the pharmacokinetic profile of terbinafine. The PB-PK model developed in this study was capable of accurately predicting the plasma and tissue terbinafine concentrations in both rats and humans and provides insight into the physiological factors that determine terbinafine disposition. PMID:12069977

Main controlling factors and forecasting models of lead accumulation in earthworms based on low-level lead-contaminated soils.

PubMed

Tang, Ronggui; Ding, Changfeng; Ma, Yibing; Wan, Mengxue; Zhang, Taolin; Wang, Xingxiang

2018-06-02

To explore the main controlling factors in soil and build a predictive model between the lead concentrations in earthworms (Pb earthworm ) and the soil physicochemical parameters, 13 soils with low level of lead contamination were used to conduct toxicity experiments using earthworms. The results indicated that a relatively high bioaccumulation factor appeared in the soils with low pH values. The lead concentrations between earthworms and soils after log transformation had a significantly positive correlation (R 2  = 0.46, P < 0.0001, n = 39). Stepwise multiple linear regression analysis derived a fitting empirical model between Pb earthworm and the soil physicochemical properties: log(Pb earthworm ) = 0.96log(Pb soil ) - 0.74log(OC) - 0.22pH + 0.95, (R 2  = 0.66, n = 39). Furthermore, path analysis confirmed that the Pb concentrations in the soil (Pb soil ), soil pH, and soil organic carbon (OC) were the primary controlling factors of Pb earthworm with high pathway parameters (0.71, - 0.51, and - 0.49, respectively). The predictive model based on Pb earthworm in a nationwide range of soils with low-level lead contamination could provide a reference for the establishment of safety thresholds in Pb-contaminated soils from the perspective of soil-animal systems.

Disruption of Pseudomonas putida by high pressure homogenization: a comparison of the predictive capacity of three process models for the efficient release of arginine deiminase.

PubMed

Patil, Mahesh D; Patel, Gopal; Surywanshi, Balaji; Shaikh, Naeem; Garg, Prabha; Chisti, Yusuf; Banerjee, Uttam Chand

2016-12-01

Disruption of Pseudomonas putida KT2440 by high-pressure homogenization in a French press is discussed for the release of arginine deiminase (ADI). The enzyme release response of the disruption process was modelled for the experimental factors of biomass concentration in the broth being disrupted, the homogenization pressure and the number of passes of the cell slurry through the homogenizer. For the same data, the response surface method (RSM), the artificial neural network (ANN) and the support vector machine (SVM) models were compared for their ability to predict the performance parameters of the cell disruption. The ANN model proved to be best for predicting the ADI release. The fractional disruption of the cells was best modelled by the RSM. The fraction of the cells disrupted depended mainly on the operating pressure of the homogenizer. The concentration of the biomass in the slurry was the most influential factor in determining the total protein release. Nearly 27 U/mL of ADI was released within a single pass from slurry with a biomass concentration of 260 g/L at an operating pressure of 510 bar. Using a biomass concentration of 100 g/L, the ADI release by French press was 2.7-fold greater than in a conventional high-speed bead mill. In the French press, the total protein release was 5.8-fold more than in the bead mill. The statistical analysis of the completely unseen data exhibited ANN and SVM modelling as proficient alternatives to RSM for the prediction and generalization of the cell disruption process in French press.

The Relationship between Elemental Carbon and Diesel Particulate Matter in Underground Metal/Nonmetal Mines in the United States and Coal Mines in Australia

PubMed Central

Noll, James; Gilles, Stewart; Wu, Hsin Wei; Rubinstein, Elaine

2015-01-01

In the United States, total carbon (TC) is used as a surrogate for determining diesel particulate matter (DPM) compliance exposures in underground metal/nonmetal mines. Since TC can be affected by interferences and elemental carbon (EC) is not, one method used to estimate the TC concentration is to multiply the EC concentration from the personal sample by a conversion factor to avoid the influence of potential interferences. Since there is no accepted single conversion factor for all metal/nonmetal mines, one is determined every time an exposure sample is taken by collecting an area sample that represents the TC/EC ratio in the miner's breathing zone and is away from potential interferences. As an alternative to this procedure, this article investigates the relationship between TC and EC from DPM samples to determine if a single conversion factor can be used for all metal/nonmetal mines. In addition, this article also investigates how well EC represents DPM concentrations in Australian coal mines since the recommended exposure limit for DPM in Australia is an EC value. When TC was predicted from EC values using a single conversion factor of 1.27 in 14 US metal/nonmetal mines, 95% of the predicted values were within 18% of the measured value, even at the permissible exposure limit (PEL) concentration of 160 μg/m3 TC. A strong correlation between TC and EC was also found in nine underground coal mines in Australia. PMID:25380085

Development of a modeling approach to estimate indoor-to-outdoor sulfur ratios and predict indoor PM2.5 and black carbon concentrations for Eastern Massachusetts households

PubMed Central

Tang, Chia Hsi; Garshick, Eric; Grady, Stephanie; Coull, Brent; Schwartz, Joel; Koutrakis, Petros

2018-01-01

The effects of indoor air pollution on human health have drawn increasing attention among the scientific community as individuals spend most of their time indoors. However, indoor air sampling is labor-intensive and costly, which limits the ability to study the adverse health effects related to indoor air pollutants. To overcome this challenge, many researchers have attempted to predict indoor exposures based on outdoor pollutant concentrations, home characteristics, and weather parameters. Typically, these models require knowledge of the infiltration factor, which indicates the fraction of ambient particles that penetrates indoors. For estimating indoor fine particulate matter (PM2.5) exposure, a common approach is to use the indoor-to-outdoor sulfur ratio (Sindoor/Soutdoor) as a proxy of the infiltration factor. The objective of this study was to develop a robust model that estimates Sindoor/Soutdoor for individual households that can be incorporated into models to predict indoor PM2.5 and black carbon (BC) concentrations. Overall, our model adequately estimated Sindoor/Soutdoor with an out-of-sample by home-season R2 of 0.89. Estimated Sindoor/Soutdoor reflected behaviors that influence particle infiltration, including window opening, use of forced air heating, and air purifier. Sulfur ratio-adjusted models predicted indoor PM2.5 and BC with high precision, with out-of-sample R2 values of 0.79 and 0.76, respectively. PMID:29064481

Study of indoor radon distribution using measurements and CFD modeling.

PubMed

Chauhan, Neetika; Chauhan, R P; Joshi, M; Agarwal, T K; Aggarwal, Praveen; Sahoo, B K

2014-10-01

Measurement and/or prediction of indoor radon ((222)Rn) concentration are important due to the impact of radon on indoor air quality and consequent inhalation hazard. In recent times, computational fluid dynamics (CFD) based modeling has become the cost effective replacement of experimental methods for the prediction and visualization of indoor pollutant distribution. The aim of this study is to implement CFD based modeling for studying indoor radon gas distribution. This study focuses on comparison of experimentally measured and CFD modeling predicted spatial distribution of radon concentration for a model test room. The key inputs for simulation viz. radon exhalation rate and ventilation rate were measured as a part of this study. Validation experiments were performed by measuring radon concentration at different locations of test room using active (continuous radon monitor) and passive (pin-hole dosimeters) techniques. Modeling predictions have been found to be reasonably matching with the measurement results. The validated model can be used to understand and study factors affecting indoor radon distribution for more realistic indoor environment. Copyright © 2014 Elsevier Ltd. All rights reserved.

Predictive Success Factors in Selective Upper Airway Stimulation.

PubMed

Heiser, Clemens; Hofauer, Benedikt

2017-01-01

Obstructive sleep apnea is one of the most common diseases in Western industrialized countries. A variety of conservative and surgical treatment options are available for its treatment. In recent years, selective upper airway stimulation (sUAS) has been shown to be effective and safe. Different biomarkers have been investigated as predictive clinical success factors in a number of clinical trials. Age does not matter in sUAS, as compared to its predictive role in other therapies. Weight seems to play a limited role, depending on drug-induced sleep endoscopy to rule out a complete concentric collapse with an increased body mass index. For surgical success and the related postoperative tongue motions, a nerve integrity monitoring methodology has been developed for predicting correct cuff placement. Postoperative sonography remains a promising method for the future assessment of predictive markers in sUAS. © 2017 S. Karger AG, Basel.

Modelling and analysis of ozone concentration by artificial intelligent techniques for estimating air quality

NASA Astrophysics Data System (ADS)

Taylan, Osman

2017-02-01

High ozone concentration is an important cause of air pollution mainly due to its role in the greenhouse gas emission. Ozone is produced by photochemical processes which contain nitrogen oxides and volatile organic compounds in the lower atmospheric level. Therefore, monitoring and controlling the quality of air in the urban environment is very important due to the public health care. However, air quality prediction is a highly complex and non-linear process; usually several attributes have to be considered. Artificial intelligent (AI) techniques can be employed to monitor and evaluate the ozone concentration level. The aim of this study is to develop an Adaptive Neuro-Fuzzy inference approach (ANFIS) to determine the influence of peripheral factors on air quality and pollution which is an arising problem due to ozone level in Jeddah city. The concentration of ozone level was considered as a factor to predict the Air Quality (AQ) under the atmospheric conditions. Using Air Quality Standards of Saudi Arabia, ozone concentration level was modelled by employing certain factors such as; nitrogen oxide (NOx), atmospheric pressure, temperature, and relative humidity. Hence, an ANFIS model was developed to observe the ozone concentration level and the model performance was assessed by testing data obtained from the monitoring stations established by the General Authority of Meteorology and Environment Protection of Kingdom of Saudi Arabia. The outcomes of ANFIS model were re-assessed by fuzzy quality charts using quality specification and control limits based on US-EPA air quality standards. The results of present study show that the ANFIS model is a comprehensive approach for the estimation and assessment of ozone level and is a reliable approach to produce more genuine outcomes.

Prediction of beef carcass and meat quality traits from factors characterising the rearing management system applied during the whole life of heifers.

PubMed

Soulat, J; Picard, B; Léger, S; Monteils, V

2018-06-01

In this study, four prediction models were developed by logistic regression using individual data from 96 heifers. Carcass and sensory rectus abdominis quality clusters were identified then predicted using the rearing factors data. The obtained models from rearing factors applied during the fattening period were compared to those characterising the heifers' whole life. The highest prediction power of carcass and meat quality clusters were obtained from the models considering the whole life, with success rates of 62.8% and 54.9%, respectively. Rearing factors applied during both pre-weaning and fattening periods influenced carcass and meat quality. According to models, carcass traits were improved when heifer's mother was older for first calving, calves ingested concentrates during pasture preceding weaning and heifers were slaughtered older. Meat traits were improved by the genetic of heifers' parents (i.e., calving ease and early muscularity) and when heifers were slaughtered older. A management of carcass and meat quality traits is possible at different periods of the heifers' life. Copyright © 2018 Elsevier Ltd. All rights reserved.

Polymer optical fiber compound parabolic concentrator tip for enhanced coupling efficiency for fluorescence based glucose sensors

PubMed Central

Hassan, Hafeez Ul; Nielsen, Kristian; Aasmul, Soren; Bang, Ole

2015-01-01

We demonstrate that the light excitation and capturing efficiency of fluorescence based fiber-optical sensors can be significantly increased by using a CPC (Compound Parabolic Concentrator) tip instead of the standard plane-cut tip. We use Zemax modelling to find the optimum CPC tip profile and fiber length of a polymer optical fiber diabetes sensor for continuous monitoring of glucose levels. We experimentally verify the improved performance of the CPC tipped sensor and the predicted production tolerances. Due to physical size requirements when the sensor has to be inserted into the body a non-optimal fiber length of 35 mm is chosen. For this length an average improvement in efficiency of a factor of 1.7 is experimentally demonstrated and critically compared to the predicted ideal factor of 3 in terms of parameters that should be improved through production optimization. PMID:26713213

Polymer optical fiber compound parabolic concentrator tip for enhanced coupling efficiency for fluorescence based glucose sensors.

PubMed

Hassan, Hafeez Ul; Nielsen, Kristian; Aasmul, Soren; Bang, Ole

2015-12-01

We demonstrate that the light excitation and capturing efficiency of fluorescence based fiber-optical sensors can be significantly increased by using a CPC (Compound Parabolic Concentrator) tip instead of the standard plane-cut tip. We use Zemax modelling to find the optimum CPC tip profile and fiber length of a polymer optical fiber diabetes sensor for continuous monitoring of glucose levels. We experimentally verify the improved performance of the CPC tipped sensor and the predicted production tolerances. Due to physical size requirements when the sensor has to be inserted into the body a non-optimal fiber length of 35 mm is chosen. For this length an average improvement in efficiency of a factor of 1.7 is experimentally demonstrated and critically compared to the predicted ideal factor of 3 in terms of parameters that should be improved through production optimization.

Environmental Conditions Associated with Elevated Vibrio parahaemolyticus Concentrations in Great Bay Estuary, New Hampshire.

PubMed

Urquhart, Erin A; Jones, Stephen H; Yu, Jong W; Schuster, Brian M; Marcinkiewicz, Ashley L; Whistler, Cheryl A; Cooper, Vaughn S

2016-01-01

Reports from state health departments and the Centers for Disease Control and Prevention indicate that the annual number of reported human vibriosis cases in New England has increased in the past decade. Concurrently, there has been a shift in both the spatial distribution and seasonal detection of Vibrio spp. throughout the region based on limited monitoring data. To determine environmental factors that may underlie these emerging conditions, this study focuses on a long-term database of Vibrio parahaemolyticus concentrations in oyster samples generated from data collected from the Great Bay Estuary, New Hampshire over a period of seven consecutive years. Oyster samples from two distinct sites were analyzed for V. parahaemolyticus abundance, noting significant relationships with various biotic and abiotic factors measured during the same period of study. We developed a predictive modeling tool capable of estimating the likelihood of V. parahaemolyticus presence in coastal New Hampshire oysters. Results show that the inclusion of chlorophyll a concentration to an empirical model otherwise employing only temperature and salinity variables, offers improved predictive capability for modeling the likelihood of V. parahaemolyticus in the Great Bay Estuary.

Pharmaceutical concentrations in screened municipal wastewaters in Victoria, British Columbia: A comparison with prescription rates and predicted concentrations.

PubMed

Saunders, Leslie J; Mazumder, Asit; Lowe, Christopher J

2016-04-01

Pharmaceuticals and personal care products (PPCPs) are emerging chemicals of concern detected in surface waters globally. Recent reviews advocate that PPCP occurrence, fate, and exposure need to be better predicted and characterized. The use of pharmaceutical prescription rates to estimate PPCP concentrations in the environment has been suggested. Concentrations of 7 pharmaceuticals (acetylsalicylic acid, diclofenac, fenoprofen, gemfibrozil, ibuprofen, ketoprofen, and naproxen) were measured in municipal wastewater using gas chromatography/ion trap-tandem mass spectroscopy (GC/IT-MS/MS). Subregional pharmaceutical prescription data were investigated to determine whether they could predict measured effluent concentrations (MECs) in wastewaters. Predicted effluent concentrations (PECs) for 5 of the 7 pharmaceuticals were within 2-fold agreement of the MECs when the fraction of parent pharmaceutical excreted was not considered. When the fraction of parent pharmaceutical excreted was considered, the respective PECs decreased, and most were within an order of magnitude of the MECs. Regression relationships of monthly PECs versus MECs were statistically significant (p < 0.05) but weak (R(2) = 0.18-0.56) for all pharmaceuticals except ketoprofen. This suggests high variability in the data and may be the result of factors influencing MECs such as the analytical methods used, wastewater sampling frequency, and methodology. The PECs were based solely on prescription rates and did not account for inputs of pharmaceuticals that had a significant over-the-counter component or were from other sources (e.g., hospitals). © 2015 SETAC.

Estimation of postfire nutrient loss in the Florida everglades.

PubMed

Qian, Y; Miao, S L; Gu, B; Li, Y C

2009-01-01

Postfire nutrient release into ecosystem via plant ash is critical to the understanding of fire impacts on the environment. Factors determining a postfire nutrient budget are prefire nutrient content in the combustible biomass, burn temperature, and the amount of combustible biomass. Our objective was to quantitatively describe the relationships between nutrient losses (or concentrations in ash) and burning temperature in laboratory controlled combustion and to further predict nutrient losses in field fire by applying predictive models established based on laboratory data. The percentage losses of total nitrogen (TN), total carbon (TC), and material mass showed a significant linear correlation with a slope close to 1, indicating that TN or TC loss occurred predominantly through volatilization during combustion. Data obtained in laboratory experiments suggest that the losses of TN, TC, as well as the ratio of ash total phosphorus (TP) concentration to leaf TP concentration have strong relationships with burning temperature and these relationships can be quantitatively described by nonlinear equations. The potential use of these nonlinear models relating nutrient loss (or concentration) to temperature in predicting nutrient concentrations in field ash appear to be promising. During a prescribed fire in the northern Everglades, 73.1% of TP was estimated to be retained in ash while 26.9% was lost to the atmosphere, agreeing well with the distribution of TP during previously reported wild fires. The use of predictive models would greatly reduce the cost associated with measuring field ash nutrient concentrations.

A hybrid machine learning model to predict and visualize nitrate concentration throughout the Central Valley aquifer, California, USA

USGS Publications Warehouse

Ransom, Katherine M.; Nolan, Bernard T.; Traum, Jonathan A.; Faunt, Claudia; Bell, Andrew M.; Gronberg, Jo Ann M.; Wheeler, David C.; Zamora, Celia; Jurgens, Bryant; Schwarz, Gregory E.; Belitz, Kenneth; Eberts, Sandra; Kourakos, George; Harter, Thomas

2017-01-01

Intense demand for water in the Central Valley of California and related increases in groundwater nitrate concentration threaten the sustainability of the groundwater resource. To assess contamination risk in the region, we developed a hybrid, non-linear, machine learning model within a statistical learning framework to predict nitrate contamination of groundwater to depths of approximately 500 m below ground surface. A database of 145 predictor variables representing well characteristics, historical and current field and landscape-scale nitrogen mass balances, historical and current land use, oxidation/reduction conditions, groundwater flow, climate, soil characteristics, depth to groundwater, and groundwater age were assigned to over 6000 private supply and public supply wells measured previously for nitrate and located throughout the study area. The boosted regression tree (BRT) method was used to screen and rank variables to predict nitrate concentration at the depths of domestic and public well supplies. The novel approach included as predictor variables outputs from existing physically based models of the Central Valley. The top five most important predictor variables included two oxidation/reduction variables (probability of manganese concentration to exceed 50 ppb and probability of dissolved oxygen concentration to be below 0.5 ppm), field-scale adjusted unsaturated zone nitrogen input for the 1975 time period, average difference between precipitation and evapotranspiration during the years 1971–2000, and 1992 total landscape nitrogen input. Twenty-five variables were selected for the final model for log-transformed nitrate. In general, increasing probability of anoxic conditions and increasing precipitation relative to potential evapotranspiration had a corresponding decrease in nitrate concentration predictions. Conversely, increasing 1975 unsaturated zone nitrogen leaching flux and 1992 total landscape nitrogen input had an increasing relative impact on nitrate predictions. Three-dimensional visualization indicates that nitrate predictions depend on the probability of anoxic conditions and other factors, and that nitrate predictions generally decreased with increasing groundwater age.

Evaluation of the Single Dilute (0.43 M) Nitric Acid Extraction to Determine Geochemically Reactive Elements in Soil

PubMed Central

2017-01-01

Recently a dilute nitric acid extraction (0.43 M) was adopted by ISO (ISO-17586:2016) as standard for extraction of geochemically reactive elements in soil and soil like materials. Here we evaluate the performance of this extraction for a wide range of elements by mechanistic geochemical modeling. Model predictions indicate that the extraction recovers the reactive concentration quantitatively (>90%). However, at low ratios of element to reactive surfaces the extraction underestimates reactive Cu, Cr, As, and Mo, that is, elements with a particularly high affinity for organic matter or oxides. The 0.43 M HNO3 together with more dilute and concentrated acid extractions were evaluated by comparing model-predicted and measured dissolved concentrations in CaCl2 soil extracts, using the different extractions as alternative model-input. Mean errors of the predictions based on 0.43 M HNO3 are generally within a factor three, while Mo is underestimated and Co, Ni and Zn in soils with pH > 6 are overestimated, for which possible causes are discussed. Model predictions using 0.43 M HNO3 are superior to those using 0.1 M HNO3 or Aqua Regia that under- and overestimate the reactive element contents, respectively. Low concentrations of oxyanions in our data set and structural underestimation of their reactive concentrations warrant further investigation. PMID:28164700

Quality control in the development of coagulation factor concentrates.

PubMed

Snape, T J

1987-01-01

Limitation of process change is a major factor contributing to assurance of quality in pharmaceutical manufacturing. This is particularly true in the manufacture of coagulation factor concentrates, for which presumptive testing for poorly defined product characteristics is an integral feature of finished product quality control. The development of new or modified preparations requires that this comfortable position be abandoned, and that the effect on finished product characteristics of changes to individual process steps (and components) be assessed. The degree of confidence in the safety and efficacy of the new product will be determined by, amongst other things, the complexity of the process alteration and the extent to which the results of finished product tests can be considered predictive. The introduction of a heat-treatment step for inactivation of potential viral contaminants in coagulation factor concentrates presents a significant challenge in both respects, quite independent of any consideration of assessment of the effectiveness of the viral inactivation step. These interactions are illustrated by some of the problems encountered with terminal dry heat-treatment (72 h. at 80 degrees C) of factor VIII and prothrombin complex concentrates manufactured by the Blood Products Laboratory.

A rapid and low energy consumption method to decolorize the high concentration triphenylmethane dye wastewater: operational parameters optimization for the ultrasonic-assisted ozone oxidation process.

PubMed

Zhou, Xian-Jiao; Guo, Wan-Qian; Yang, Shan-Shan; Ren, Nan-Qi

2012-02-01

This research set up an ultrasonic-assisted ozone oxidation process (UAOOP) to decolorize the triphenylmethane dyes wastewater. Five factors - temperature, initial pH, reaction time, ultrasonic power (low frequency 20 kHz), and ozone concentration - were investigated. Response surface methodology was used to find out the major factors influencing color removal rate and the interactions between these factors, and optimized the operating parameters as well. Under the experimental conditions: reaction temperature 39.81 °C, initial pH 5.29, ultrasonic power 60 W and ozone concentration 0.17 g/L, the highest color removals were achieved with 10 min reaction time and the initial concentration of the MG solution was 1000 mg/L. The optimal results indicated that the UAOOP was a rapid, efficient and low energy consumption technique to decolorize the high concentration MG wastewater. The predicted model was approximately in accordance with the experimental cases with correlation coefficients R(2) and R(adj)(2) of 0.9103 and 0.8386. Crown Copyright © 2011. Published by Elsevier Ltd. All rights reserved.

Identification of periparturient mare and foal associated predictors of post parturient immunoglobulin A concentrations in Thoroughbred foals.

PubMed

Jenvey, C; Caraguel, C; Howarth, G B; Riley, C B

2012-12-01

Prior to the start of endogenous production of immunoglobulins (Igs), absorption of maternal Igs is important to protect against pathogens in the early neonatal period. It is possible that mare- or foal-associated factors may influence neonatal IgA concentrations. The temporal relationships among serum and milk IgA concentrations in Thoroughbred mare-foal pairs were explored to determine if periparturient mare- and foal-associated factors contribute to the prediction of foal serum IgA concentrations. Blood and milk samples as well as complete veterinary records, were collected for 84 Thoroughbred mare-foal pairs from one month before to 2 months after parturition. Samples were tested using enzyme-linked immunosorbent assay (ELISA) for concentrations of IgA. Pairwise correlation coefficients were estimated (P < 0.01) and simple linear regression used to investigate unconditional associations between mare IgA levels, mare and foal risk factors and foal serum IgA concentration at 12 h. Backwards, stepwise elimination of nonsignificant factors was used to create a final model. There were significant temporal relationships among mare serum IgA and among colostrum and milk IgA concentrations within mares (P < 0.01). Mare serum IgA concentrations up to one month before parturition were associated with foal serum IgA concentrations at all time points and with colostrum and milk IgA concentrations. Mare serum IgA at -28 days and parity were associated with foal serum IgA concentration at 12 h (P < 0.001). Mare serum IgA concentrations up to 28 days before parturition, together with mare parity, are indicative of neonatal foal serum IgA concentrations. Mare serum and colostrum IgA concentrations may be useful peripartum predictors of neonatal mucosal immune status, enabling earlier intervention to prevent the consequences of mucosal infections.

Decay model for biocide treatment of unballasted vessels: application for the Laurentian Great Lakes.

PubMed

Sano, Larissa L; Bartell, Steven M; Landrum, Peter F

2005-10-01

A biocide decay model was developed to assess the potential efficacy and environmental impacts associated with using glutaraldehyde to treat unballasted overseas vessels trading on the Laurentian Great Lakes. The results of Monte Carlo simulations indicate that effective glutaraldehyde concentrations can be maintained for the duration of a vessel's oceanic transit (approximately 9-12 days): During this transit, glutaraldehyde concentrations were predicted to decrease by approximately 10% from initial treatment levels (e.g., 500 mgL(-1)). In terms of environmental impacts, mean glutaraldehyde concentrations released at Duluth-Superior Harbor, MN were predicted to be 100-fold lower than initial treatment concentrations, and ranged from 3.2 mgL(-1) (2 SD: 2.74) in April to 0.7 mgL(-1) (2 SD: 1.28) in August. Sensitivity analyses indicated that the re-ballasting dilution factor was the major variable governing final glutaraldehyde concentrations; however, lake surface temperatures became increasingly important during the warmer summer months.

AFIR: A Dimensionless Potency Metric for Characterizing the Activity of Monoclonal Antibodies

PubMed Central

Ramakrishna, R

2017-01-01

For monoclonal antibody (mAb) drugs, soluble targets may accumulate several thousand fold after binding to the drug. Time course data of mAb and total target is often collected and, although free target is more closely related to clinical effect, it is difficult to measure. Therefore, mathematical models of this data are used to predict target engagement. In this article, a “potency factor” is introduced as an approximation for the model‐predicted target inhibition. This potency factor is defined to be the time‐Averaged Free target concentration to Initial target concentration Ratio (AFIR), and it depends on three key quantities: the average drug concentration at steady state; the binding affinity; and the degree of target accumulation. AFIR provides the intuition for how changes in dosing regimen and binding affinity affect target capture and AFIR can be used to predict the druggability of new targets and the expected benefits of more potent, second‐generation mAbs. PMID:28375563

Complex Adaptive System Models and the Genetic Analysis of Plasma HDL-Cholesterol Concentration

PubMed Central

Rea, Thomas J.; Brown, Christine M.; Sing, Charles F.

2006-01-01

Despite remarkable advances in diagnosis and therapy, ischemic heart disease (IHD) remains a leading cause of morbidity and mortality in industrialized countries. Recent efforts to estimate the influence of genetic variation on IHD risk have focused on predicting individual plasma high-density lipoprotein cholesterol (HDL-C) concentration. Plasma HDL-C concentration (mg/dl), a quantitative risk factor for IHD, has a complex multifactorial etiology that involves the actions of many genes. Single gene variations may be necessary but are not individually sufficient to predict a statistically significant increase in risk of disease. The complexity of phenotype-genotype-environment relationships involved in determining plasma HDL-C concentration has challenged commonly held assumptions about genetic causation and has led to the question of which combination of variations, in which subset of genes, in which environmental strata of a particular population significantly improves our ability to predict high or low risk phenotypes. We document the limitations of inferences from genetic research based on commonly accepted biological models, consider how evidence for real-world dynamical interactions between HDL-C determinants challenges the simplifying assumptions implicit in traditional linear statistical genetic models, and conclude by considering research options for evaluating the utility of genetic information in predicting traits with complex etiologies. PMID:17146134

Changes in beta cell function during the proximate post-diagnosis period in persons with type 1 diabetes.

PubMed

DiMeglio, Linda A; Cheng, Peiyao; Beck, Roy W; Kollman, Craig; Ruedy, Katrina J; Slover, Robert; Aye, Tandy; Weinzimer, Stuart A; Bremer, Andrew A; Buckingham, Bruce

2016-06-01

Prior studies examining beta-cell preservation in type 1 diabetes have predominantly assessed stimulated C-peptide concentrations approximately 10 wk after diagnosis. We examined whether earlier assessments might aid in prediction of beta cell function over time. Using data from a multi-center randomized trial assessing the effect of intensive diabetes management initiated within 1 wk of diagnosis, we assessed which clinical factors predicted 90-min mixed-meal tolerance test (MMTT) stimulated C-peptide values obtained 2 and 6 wk after diagnosis. We also studied associations of these factors with C-peptide values at 1- and 2-year post-diagnosis. Data from intervention and control groups were pooled. Among 67 study participants (mean age 13.3 ± 5.7 yr, range 7.8-45.7 yr) in multivariable analyses, C-peptide increased from baseline to 2 wks and then 6 wk. C-peptide levels at these times were significantly correlated with 1- and 2-yr C-peptide concentrations (all p < 0.001), with the strongest observed associations between 6-wk C-peptide and the 1- and 2-yr values (r = 0.66 and r = 0.61, respectively). In multivariable analyses, greater baseline and 6-wk C-peptide, and older age independently predicted greater 1- and 2-yr C-peptide concentrations. C-peptide assessments close to diagnosis were predictive of subsequent C-peptide production. Our data demonstrate a clear increase in C-peptide over the initial 6 wk after diabetes diagnosis followed by a plateau. Our data do not suggest that MMTT assessments performed closer to diagnosis than 6 wk would improve prediction of subsequent residual beta cell function. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Evaluation of Four Methods for Predicting Carbon Stocks of Korean Pine Plantations in Heilongjiang Province, China

PubMed Central

Gao, Huilin; Dong, Lihu; Li, Fengri; Zhang, Lianjun

2015-01-01

A total of 89 trees of Korean pine (Pinus koraiensis) were destructively sampled from the plantations in Heilongjiang Province, P.R. China. The sample trees were measured and calculated for the biomass and carbon stocks of tree components (i.e., stem, branch, foliage and root). Both compatible biomass and carbon stock models were developed with the total biomass and total carbon stocks as the constraints, respectively. Four methods were used to evaluate the carbon stocks of tree components. The first method predicted carbon stocks directly by the compatible carbon stocks models (Method 1). The other three methods indirectly predicted the carbon stocks in two steps: (1) estimating the biomass by the compatible biomass models, and (2) multiplying the estimated biomass by three different carbon conversion factors (i.e., carbon conversion factor 0.5 (Method 2), average carbon concentration of the sample trees (Method 3), and average carbon concentration of each tree component (Method 4)). The prediction errors of estimating the carbon stocks were compared and tested for the differences between the four methods. The results showed that the compatible biomass and carbon models with tree diameter (D) as the sole independent variable performed well so that Method 1 was the best method for predicting the carbon stocks of tree components and total. There were significant differences among the four methods for the carbon stock of stem. Method 2 produced the largest error, especially for stem and total. Methods 3 and Method 4 were slightly worse than Method 1, but the differences were not statistically significant. In practice, the indirect method using the mean carbon concentration of individual trees was sufficient to obtain accurate carbon stocks estimation if carbon stocks models are not available. PMID:26659257

Association between osteopontin and human abdominal aortic aneurysm.

PubMed

Golledge, Jonathan; Muller, Juanita; Shephard, Neil; Clancy, Paula; Smallwood, Linda; Moran, Corey; Dear, Anthony E; Palmer, Lyle J; Norman, Paul E

2007-03-01

In vitro and animal studies have implicated osteopontin (OPN) in the pathogenesis of aortic aneurysm. The relationship between serum concentration of OPN and variants of the OPN gene with human abdominal aortic aneurysm (AAA) was investigated. OPN genotypes were examined in 4227 subjects in which aortic diameter and clinical risk factors were measured. Serum OPN was measured by ELISA in two cohorts of 665 subjects. The concentration of serum OPN was independently associated with the presence of AAA. Odds ratios (and 95% confidence intervals) for upper compared with lower OPN tertiles in predicting presence of AAA were 2.23 (1.29 to 3.85, P=0.004) for the population cohort and 4.08 (1.67 to 10.00, P=0.002) for the referral cohort after adjusting for other risk factors. In 198 patients with complete follow-up of aortic diameter at 3 years, initial serum OPN predicted AAA growth after adjustment for other risk factors (standardized coefficient 0.24, P=0.001). The concentration of OPN in the aortic wall was greater in patients with small AAAs (30 to 50 mm) than those with aortic occlusive disease alone. There was no association between five single nucleotide polymorphisms or haplotypes of the OPN gene and aortic diameter or AAA expansion. Serum and tissue concentrations of OPN are associated with human AAA. We found no relationship between variation of the OPN gene and AAA. OPN may be a useful biomarker for AAA presence and growth.

Cell density dependence of Microcystis aeruginosa responses to copper algaecide concentrations: Implications for microcystin-LR release.

PubMed

Kinley, Ciera M; Iwinski, Kyla J; Hendrikse, Maas; Geer, Tyler D; Rodgers, John H

2017-11-01

Along with mechanistic models, predictions of exposure-response relationships for copper are often derived from laboratory toxicity experiments with standardized experimental exposures and conditions. For predictions of copper toxicity to algae, cell density is a critical factor often overlooked. For pulse exposures of copper-based algaecides in aquatic systems, cell density can significantly influence copper sorbed by the algal population, and consequent responses. A cyanobacterium, Microcystis aeruginosa, was exposed to a copper-based algaecide over a range of cell densities to model the density-dependence of exposures, and effects on microcystin-LR (MC-LR) release. Copper exposure concentrations were arrayed to result in a gradient of MC-LR release, and masses of copper sorbed to algal populations were measured following exposures. While copper exposure concentrations eliciting comparable MC-LR release ranged an order of magnitude (24-h EC50s 0.03-0.3mg Cu/L) among cell densities of 10 6 through 10 7 cells/mL, copper doses (mg Cu/mg algae) were similar (24-h EC50s 0.005-0.006mg Cu/mg algae). Comparisons of MC-LR release as a function of copper exposure concentrations and doses provided a metric of the density dependence of algal responses in the context of copper-based algaecide applications. Combined with estimates of other site-specific factors (e.g. water characteristics) and fate processes (e.g. dilution and dispersion, sorption to organic matter and sediments), measuring exposure-response relationships for specific cell densities can refine predictions for in situ exposures and algal responses. These measurements can in turn decrease the likelihood of amending unnecessary copper concentrations to aquatic systems, and minimize risks for non-target aquatic organisms. Copyright © 2017 Elsevier Inc. All rights reserved.

Modeling pollen time series using seasonal-trend decomposition procedure based on LOESS smoothing

NASA Astrophysics Data System (ADS)

Rojo, Jesús; Rivero, Rosario; Romero-Morte, Jorge; Fernández-González, Federico; Pérez-Badia, Rosa

2017-02-01

Analysis of airborne pollen concentrations provides valuable information on plant phenology and is thus a useful tool in agriculture—for predicting harvests in crops such as the olive and for deciding when to apply phytosanitary treatments—as well as in medicine and the environmental sciences. Variations in airborne pollen concentrations, moreover, are indicators of changing plant life cycles. By modeling pollen time series, we can not only identify the variables influencing pollen levels but also predict future pollen concentrations. In this study, airborne pollen time series were modeled using a seasonal-trend decomposition procedure based on LOcally wEighted Scatterplot Smoothing (LOESS) smoothing (STL). The data series—daily Poaceae pollen concentrations over the period 2006-2014—was broken up into seasonal and residual (stochastic) components. The seasonal component was compared with data on Poaceae flowering phenology obtained by field sampling. Residuals were fitted to a model generated from daily temperature and rainfall values, and daily pollen concentrations, using partial least squares regression (PLSR). This method was then applied to predict daily pollen concentrations for 2014 (independent validation data) using results for the seasonal component of the time series and estimates of the residual component for the period 2006-2013. Correlation between predicted and observed values was r = 0.79 (correlation coefficient) for the pre-peak period (i.e., the period prior to the peak pollen concentration) and r = 0.63 for the post-peak period. Separate analysis of each of the components of the pollen data series enables the sources of variability to be identified more accurately than by analysis of the original non-decomposed data series, and for this reason, this procedure has proved to be a suitable technique for analyzing the main environmental factors influencing airborne pollen concentrations.

Modeling pollen time series using seasonal-trend decomposition procedure based on LOESS smoothing.

PubMed

Rojo, Jesús; Rivero, Rosario; Romero-Morte, Jorge; Fernández-González, Federico; Pérez-Badia, Rosa

2017-02-01

Analysis of airborne pollen concentrations provides valuable information on plant phenology and is thus a useful tool in agriculture-for predicting harvests in crops such as the olive and for deciding when to apply phytosanitary treatments-as well as in medicine and the environmental sciences. Variations in airborne pollen concentrations, moreover, are indicators of changing plant life cycles. By modeling pollen time series, we can not only identify the variables influencing pollen levels but also predict future pollen concentrations. In this study, airborne pollen time series were modeled using a seasonal-trend decomposition procedure based on LOcally wEighted Scatterplot Smoothing (LOESS) smoothing (STL). The data series-daily Poaceae pollen concentrations over the period 2006-2014-was broken up into seasonal and residual (stochastic) components. The seasonal component was compared with data on Poaceae flowering phenology obtained by field sampling. Residuals were fitted to a model generated from daily temperature and rainfall values, and daily pollen concentrations, using partial least squares regression (PLSR). This method was then applied to predict daily pollen concentrations for 2014 (independent validation data) using results for the seasonal component of the time series and estimates of the residual component for the period 2006-2013. Correlation between predicted and observed values was r = 0.79 (correlation coefficient) for the pre-peak period (i.e., the period prior to the peak pollen concentration) and r = 0.63 for the post-peak period. Separate analysis of each of the components of the pollen data series enables the sources of variability to be identified more accurately than by analysis of the original non-decomposed data series, and for this reason, this procedure has proved to be a suitable technique for analyzing the main environmental factors influencing airborne pollen concentrations.

Intrinsic Risk Factors of Lateral Ankle Sprain: A Systematic Review and Meta-analysis.

PubMed

Kobayashi, Takumi; Tanaka, Masashi; Shida, Masahiro

2016-01-01

Lateral ankle ligamentous sprain (LAS) is one of the most common injuries in recreational activities and competitive sports. Many studies have attempted to determine whether there are certain intrinsic factors that can predict LAS. However, no consensus has been reached on the predictive intrinsic factors. To identify the intrinsic risk factors of LAS by meta-analysis from data in randomized control trials and prospective cohort studies. A systematic computerized literature search of MEDLINE, CINAHL, ScienceDirect, SPORTDiscus, and Cochrane Register of Clinical Trials was performed. A computerized literature search from inception to January 2015 resulted in 1133 studies of the LAS intrinsic risk factors written in English. Systematic review. Level 4. The modified quality index was used to assess the quality of the design of the papers and the standardized mean difference was used as an index to pool included study outcomes. Eight articles were included in this systematic review. Meta-analysis results showed that body mass index, slow eccentric inversion strength, fast concentric plantar flexion strength, passive inversion joint position sense, and peroneus brevis reaction time correlated with LAS. Body mass index, slow eccentric inversion strength, fast concentric plantar flexion strength, passive inversion joint position sense, and the reaction time of the peroneus brevis were associated with significantly increased risk of LAS.

Source apportionment of trace metals in surface waters of a polluted stream using multivariate statistical analyses.

PubMed

Pekey, Hakan; Karakaş, Duran; Bakoğlu, Mithat

2004-11-01

Surface water samples were collected from ten previously selected sites of the polluted Dil Deresi stream, during two field surveys, December 2001 and April 2002. All samples were analyzed using ICP-AES, and the concentrations of trace metals (Al, As, Ba, Cd, Co, Cr, Cu, Fe, Pb, Sn and Zn) were determined. The results were compared with national and international water quality guidelines, as well as literature values reported for similar rivers. Factor analysis (FA) and a factor analysis-multiple regression (FA-MR) model were used for source apportionment and estimation of contributions from identified sources to the concentration of each parameter. By a varimax rotated factor analysis, four source types were identified as the paint industry; sewage, crustal and road traffic runoff for trace metals, explaining about 83% of the total variance. FA-MR results showed that predicted concentrations were calculated with uncertainties lower than 15%.

Understanding the retention and fate prediction of copper ions in single and competitive system in two soils: An experimental and numerical investigation.

PubMed

Buragohain, Poly; Garg, Ankit; Feng, Song; Lin, Peng; Sreedeep, S

2018-09-01

The concept of sponge city has become very popular with major thrust on design of waste containment systems such as biofilter and green roofs. Factors that may influence pollutant ions retention in these systems will be soil type and also their interactions. The study investigated single and competitive interaction of copper in two soils and its influence on the fate prediction. Freundlich and Langmuir nonlinear isotherms were selected to quantify the retention results. Series of numerical simulations were conducted to model 1 D advection-dispersion transport for the two soils and analyse the role of isotherms. The results indicated that contaminant fate prediction of copper-soil interaction based on the two non-linear isotherms was different for both single and that in competition. Retardation factor obtained from Freundlich (R F ) isotherm predicts more than Langmuir (R La ). This observation is more explicit at the higher range of equilibrium concentration. Fate prediction based on retardation value obtained from retention isotherms exhibited some anomalous trends contradicting the experimental findings due to inherent assumptions in governing equations. The necessity to have an approximate assessment of contaminant concentration in the field to effectively use contaminant retention results for accurate fate prediction is highlighted here. The study is important for modellers in design or analysis of biolfilter system (sponge city), where multiple ions tend to exist in waste water. Copyright © 2018 Elsevier B.V. All rights reserved.

Plant uptake of elements in soil and pore water: field observations versus model assumptions.

PubMed

Raguž, Veronika; Jarsjö, Jerker; Grolander, Sara; Lindborg, Regina; Avila, Rodolfo

2013-09-15

Contaminant concentrations in various edible plant parts transfer hazardous substances from polluted areas to animals and humans. Thus, the accurate prediction of plant uptake of elements is of significant importance. The processes involved contain many interacting factors and are, as such, complex. In contrast, the most common way to currently quantify element transfer from soils into plants is relatively simple, using an empirical soil-to-plant transfer factor (TF). This practice is based on theoretical assumptions that have been previously shown to not generally be valid. Using field data on concentrations of 61 basic elements in spring barley, soil and pore water at four agricultural sites in mid-eastern Sweden, we quantify element-specific TFs. Our aim is to investigate to which extent observed element-specific uptake is consistent with TF model assumptions and to which extent TF's can be used to predict observed differences in concentrations between different plant parts (root, stem and ear). Results show that for most elements, plant-ear concentrations are not linearly related to bulk soil concentrations, which is congruent with previous studies. This behaviour violates a basic TF model assumption of linearity. However, substantially better linear correlations are found when weighted average element concentrations in whole plants are used for TF estimation. The highest number of linearly-behaving elements was found when relating average plant concentrations to soil pore-water concentrations. In contrast to other elements, essential elements (micronutrients and macronutrients) exhibited relatively small differences in concentration between different plant parts. Generally, the TF model was shown to work reasonably well for micronutrients, whereas it did not for macronutrients. The results also suggest that plant uptake of elements from sources other than the soil compartment (e.g. from air) may be non-negligible. Copyright © 2013 Elsevier Ltd. All rights reserved.

Decolorization of the azo dye Acid Orange 51 by laccase produced in solid culture of a newly isolated Trametes trogii strain.

PubMed

Daâssi, Dalel; Zouari-Mechichi, Hela; Frikha, Fakher; Martinez, Maria Jesus; Nasri, Moncef; Mechichi, Tahar

2013-04-01

This study concerns the decolorization and detoxification of the azo dye Acid Orange 51 (AO51) by crude laccase from Trametes trogii produced in solid culture using sawdust as support media. A three-level Box-Behnken factorial design with four factors (enzyme concentration, 1-hydroxybenzotriazole (HBT) concentration, dye concentration and reaction time) combined with response surface methodology was applied to optimize AO51 decolorization. A mathematical model was developed showing the effect of each factor and their interactions on color removal. The model predicted that Acid Orange 51 decolorization above 87.87 ± 1.27 % could be obtained when enzyme concentration, HBT concentration, dye concentration and reaction time were set at 1 U/mL, 0.75 mM, 60 mg/L and 2 days, respectively. The experimental values were in good agreement with the predicted ones and the models were highly significant, the correlation coefficient (R 2 ) being 0.9. Then the desirability function was employed to determine the optimal decolorization condition for each dye and minimize the process cost simultaneously. In addition, germination index assay showed that laccase-treated dye was detoxified; however in the presence of HBT, the phytotoxicity of the treated dye was increased. By using cheap agro-industrial wastes, such as sawdust, a potential laccase was obtained. The low cost of laccase production may further broaden its application in textile wastewater treatment.

Air pollution dispersion models for human exposure predictions in London.

PubMed

Beevers, Sean D; Kitwiroon, Nutthida; Williams, Martin L; Kelly, Frank J; Ross Anderson, H; Carslaw, David C

2013-01-01

The London household survey has shown that people travel and are exposed to air pollutants differently. This argues for human exposure to be based upon space-time-activity data and spatio-temporal air quality predictions. For the latter, we have demonstrated the role that dispersion models can play by using two complimentary models, KCLurban, which gives source apportionment information, and Community Multi-scale Air Quality Model (CMAQ)-urban, which predicts hourly air quality. The KCLurban model is in close agreement with observations of NO(X), NO(2) and particulate matter (PM)(10/2.5), having a small normalised mean bias (-6% to 4%) and a large Index of Agreement (0.71-0.88). The temporal trends of NO(X) from the CMAQ-urban model are also in reasonable agreement with observations. Spatially, NO(2) predictions show that within 10's of metres of major roads, concentrations can range from approximately 10-20 p.p.b. up to 70 p.p.b. and that for PM(10/2.5) central London roadside concentrations are approximately double the suburban background concentrations. Exposure to different PM sources is important and we predict that brake wear-related PM(10) concentrations are approximately eight times greater near major roads than at suburban background locations. Temporally, we have shown that average NO(X) concentrations close to roads can range by a factor of approximately six between the early morning minimum and morning rush hour maximum periods. These results present strong arguments for the hybrid exposure model under development at King's and, in future, for in-building models and a model for the London Underground.

Integrative neural networks model for prediction of sediment rating curve parameters for ungauged basins

NASA Astrophysics Data System (ADS)

Atieh, M.; Mehltretter, S. L.; Gharabaghi, B.; Rudra, R.

2015-12-01

One of the most uncertain modeling tasks in hydrology is the prediction of ungauged stream sediment load and concentration statistics. This study presents integrated artificial neural networks (ANN) models for prediction of sediment rating curve parameters (rating curve coefficient α and rating curve exponent β) for ungauged basins. The ANN models integrate a comprehensive list of input parameters to improve the accuracy achieved; the input parameters used include: soil, land use, topographic, climatic, and hydrometric data sets. The ANN models were trained on the randomly selected 2/3 of the dataset of 94 gauged streams in Ontario, Canada and validated on the remaining 1/3. The developed models have high correlation coefficients of 0.92 and 0.86 for α and β, respectively. The ANN model for the rating coefficient α is directly proportional to rainfall erosivity factor, soil erodibility factor, and apportionment entropy disorder index, whereas it is inversely proportional to vegetation cover and mean annual snowfall. The ANN model for the rating exponent β is directly proportional to mean annual precipitation, the apportionment entropy disorder index, main channel slope, standard deviation of daily discharge, and inversely proportional to the fraction of basin area covered by wetlands and swamps. Sediment rating curves are essential tools for the calculation of sediment load, concentration-duration curve (CDC), and concentration-duration-frequency (CDF) analysis for more accurate assessment of water quality for ungauged basins.

Developing an in silico minimum inhibitory concentration panel test for Klebsiella pneumoniae

DOE PAGES

Nguyen, Marcus; Brettin, Thomas; Long, S. Wesley; ...

2018-01-11

Here, antimicrobial resistant infections are a serious public health threat worldwide. Whole genome sequencing approaches to rapidly identify pathogens and predict antibiotic resistance phenotypes are becoming more feasible and may offer a way to reduce clinical test turnaround times compared to conventional culture-based methods, and in turn, improve patient outcomes. In this study, we use whole genome sequence data from 1668 clinical isolates of Klebsiella pneumoniae to develop a XGBoost-based machine learning model that accurately predicts minimum inhibitory concentrations (MICs) for 20 antibiotics. The overall accuracy of the model, within ± 1 two-fold dilution factor, is 92%. Individual accuracies aremore » >= 90% for 15/20 antibiotics. We show that the MICs predicted by the model correlate with known antimicrobial resistance genes. Importantly, the genome-wide approach described in this study offers a way to predict MICs for isolates without knowledge of the underlying gene content. This study shows that machine learning can be used to build a complete in silico MIC prediction panel for K. pneumoniae and provides a framework for building MIC prediction models for other pathogenic bacteria.« less

Developing an in silico minimum inhibitory concentration panel test for Klebsiella pneumoniae

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nguyen, Marcus; Brettin, Thomas; Long, S. Wesley

Here, antimicrobial resistant infections are a serious public health threat worldwide. Whole genome sequencing approaches to rapidly identify pathogens and predict antibiotic resistance phenotypes are becoming more feasible and may offer a way to reduce clinical test turnaround times compared to conventional culture-based methods, and in turn, improve patient outcomes. In this study, we use whole genome sequence data from 1668 clinical isolates of Klebsiella pneumoniae to develop a XGBoost-based machine learning model that accurately predicts minimum inhibitory concentrations (MICs) for 20 antibiotics. The overall accuracy of the model, within ± 1 two-fold dilution factor, is 92%. Individual accuracies aremore » >= 90% for 15/20 antibiotics. We show that the MICs predicted by the model correlate with known antimicrobial resistance genes. Importantly, the genome-wide approach described in this study offers a way to predict MICs for isolates without knowledge of the underlying gene content. This study shows that machine learning can be used to build a complete in silico MIC prediction panel for K. pneumoniae and provides a framework for building MIC prediction models for other pathogenic bacteria.« less

Low Endogenous Fibroblast Growth Factor 2 Levels Are Associated With Heightened Conditioned Fear Expression in Rats and Humans.

PubMed

Graham, Bronwyn M; Zagic, Dino; Richardson, Rick

2017-10-15

Hippocampal concentrations of the neurotrophic factor fibroblast growth factor 2 (FGF2) are negatively associated with the expression of fear following conditioning in rats. Heightened conditioned fear expression may be a prospective risk factor for the development of human anxiety and trauma disorders. However, the relationship between conditioned fear expression and FGF2 is yet to be established in humans. Using a cross-species approach, we first investigated the relationship between serum concentrations of FGF2 and individual differences in conditioned fear expression in rats (n = 19). We then subjected 88 human participants, who were recruited from university and community advertisements, to a differential fear conditioning procedure and assessed the relationship between salivary concentrations of FGF2 and fear expression to a conditioned stimulus (CS) (a stimulus paired with a shock) and a CS that was never paired with shock. Rats with low serum levels of FGF2 exhibited significantly more freezing than rats with high serum levels of FGF2. Similarly, relative to those with high salivary FGF2, human participants with low salivary FGF2 exhibited significantly heightened skin conductance responses to the CS without shock during fear conditioning and to both the CS with shock and CS without shock during fear recall. These studies establish that peripheral markers of FGF2 concentrations are negatively associated with fear expression in both rats and humans. To the extent that conditioned fear expression predicts anxiety and trauma disorder vulnerability, FGF2 may be a clinically useful biomarker in the prediction and eventual prevention of these disorders. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Identifying constituent spectra sources in multispectral images to quantify and locate cervical neoplasia

NASA Astrophysics Data System (ADS)

Baker, Kevin C.; Bambot, Shabbir

2011-02-01

Optical spectroscopy has been shown to be an effective method for detecting neoplasia. Guided Therapeutics has developed LightTouch, a non invasive device that uses a combination of reflectance and fluorescence spectroscopy for identifying early cancer of the human cervix. The combination of the multispectral information from the two spectroscopic modalities has been shown to be an effective method to screen for cervical cancer. There has however been a relative paucity of work in identifying the individual spectral components that contribute to the measured fluorescence and reflectance spectra. This work aims to identify the constituent source spectra and their concentrations. We used non-negative matrix factorization (NNMF) numerical methods to decompose the mixed multispectral data into the constituent spectra and their corresponding concentrations. NNMF is an iterative approach that factorizes the measured data into non-negative factors. The factors are chosen to minimize the root-mean-squared residual error. NNMF has shown promise for feature extraction and identification in the fields of text mining and spectral data analysis. Since both the constituent source spectra and their corresponding concentrations are assumed to be non-negative by nature NNMF is a reasonable approach to deconvolve the measured multispectral data. Supervised learning methods were then used to determine which of the constituent spectra sources best predict the amount of neoplasia. The constituent spectra sources found to best predict neoplasia were then compared with spectra of known biological chromophores.

Soil and Water Assessment Tool model predictions of annual maximum pesticide concentrations in high vulnerability watersheds.

PubMed

Winchell, Michael F; Peranginangin, Natalia; Srinivasan, Raghavan; Chen, Wenlin

2018-05-01

Recent national regulatory assessments of potential pesticide exposure of threatened and endangered species in aquatic habitats have led to increased need for watershed-scale predictions of pesticide concentrations in flowing water bodies. This study was conducted to assess the ability of the uncalibrated Soil and Water Assessment Tool (SWAT) to predict annual maximum pesticide concentrations in the flowing water bodies of highly vulnerable small- to medium-sized watersheds. The SWAT was applied to 27 watersheds, largely within the midwest corn belt of the United States, ranging from 20 to 386 km 2 , and evaluated using consistent input data sets and an uncalibrated parameterization approach. The watersheds were selected from the Atrazine Ecological Exposure Monitoring Program and the Heidelberg Tributary Loading Program, both of which contain high temporal resolution atrazine sampling data from watersheds with exceptionally high vulnerability to atrazine exposure. The model performance was assessed based upon predictions of annual maximum atrazine concentrations in 1-d and 60-d durations, predictions critical in pesticide-threatened and endangered species risk assessments when evaluating potential acute and chronic exposure to aquatic organisms. The simulation results showed that for nearly half of the watersheds simulated, the uncalibrated SWAT model was able to predict annual maximum pesticide concentrations within a narrow range of uncertainty resulting from atrazine application timing patterns. An uncalibrated model's predictive performance is essential for the assessment of pesticide exposure in flowing water bodies, the majority of which have insufficient monitoring data for direct calibration, even in data-rich countries. In situations in which SWAT over- or underpredicted the annual maximum concentrations, the magnitude of the over- or underprediction was commonly less than a factor of 2, indicating that the model and uncalibrated parameterization approach provide a capable method for predicting the aquatic exposure required to support pesticide regulatory decision making. Integr Environ Assess Manag 2018;14:358-368. © 2017 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC). © 2017 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Optimization of chitin yield from shrimp shell waste by Bacillus subtilis and impact of gamma irradiation on production of low molecular weight chitosan.

PubMed

Gamal, Rawia F; El-Tayeb, Tarek S; Raffat, Enas I; Ibrahim, Haytham M M; Bashandy, A S

2016-10-01

Chitin and chitosan have been produced from the exoskeletons of crustacean shells such as shrimps. In this study, seventy bacterial isolates, isolated from soil, were tested for proteolytic enzymes production. The most efficient one, identified as Bacillus subtilis, was employed to extract chitin from shrimp shell waste (SSW). Following one-variable-at-a-time approach, the relevant factors affecting deproteinization (DP) and demineralization (DM) were sucrose concentration (10%, w/v), SSW concentration (5%, w/v), inoculum size (15%, v/v), and fermentation time (6days). These factors were optimized subsequently using Box-Behnken design and response surface methodology. Maximum DP (97.65%) and DM (82.94%) were predicted at sucrose concentration (5%), SSW concentration (12.5%), inoculum size (10%, containing 35×10(8) CFU/mL), and fermentation time (7days). The predicted optimum values were verified by additional experiment. The values of DP (96.0%) and DM (82.1%) obtained experimentally correlated to the predicted values which justify the authenticity of optimum points. Overall 1.3-fold increase in DP% and DM% was obtained compared with 75.27% and 63.50%, respectively, before optimization. Gamma-irradiation (35kGy) reduced deacetylation time of irradiated chitin by 4.5-fold compared with non-irradiated chitin. The molecular weight of chitosan was decreased from 1.9×10(6) (non-irradiated) to 3.7×10(4)g/mol (at 35kGy). Copyright © 2016 Elsevier B.V. All rights reserved.

Evaluating ammonia (NH3) predictions in the NOAA National Air Quality Forecast Capability (NAQFC) using in situ aircraft, ground-level, and satellite measurements from the DISCOVER-AQ Colorado campaign

NASA Astrophysics Data System (ADS)

Battye, William H.; Bray, Casey D.; Aneja, Viney P.; Tong, Daniel; Lee, Pius; Tang, Youhua

2016-09-01

The U.S. National Oceanic and Atmospheric Administration (NOAA) is responsible for forecasting elevated levels of air pollution within the National Air Quality Forecast Capability (NAQFC). The current research uses measurements gathered in the DISCOVER-AQ Colorado field campaign and the concurrent Front Range Air Pollution and Photochemistry Experiment (FRAPPE) to test performance of the NAQFC CMAQ modeling framework for predicting NH3. The DISCOVER-AQ and FRAPPE field campaigns were carried out in July and August 2014 in Northeast Colorado. Model predictions are compared with measurements of NH3 gas concentrations and the NH4+ component of fine particulate matter concentrations measured directly by the aircraft in flight. We also compare CMAQ predictions with NH3 measurements from ground-based monitors within the DISCOVER-AQ Colorado geographic domain, and from the Tropospheric Emission Spectrometer (TES) on the Aura satellite. In situ aircraft measurements carried out in July and August of 2014 suggest that the NAQFC CMAQ model underestimated the NH3 concentration in Northeastern Colorado by a factor of ∼2.7 (NMB = -63%). Ground-level monitors also produced a similar result. Average satellite-retrieved NH3 levels also exceeded model predictions by a factor of 1.5-4.2 (NMB = -33 to -76%). The underestimation of NH3 was not accompanied by an underestimation of particulate NH4+, which is further controlled by factors including acid availability, removal rate, and gas-particle partition. The average measured concentration of NH4+ was close to the average predication (NMB = +18%). Seasonal patterns measured at an AMoN site in the region suggest that the underestimation of NH3 is not due to the seasonal allocation of emissions, but to the overall annual emissions estimate. The underestimation of NH3 varied across the study domain, with the largest differences occurring in a region of intensive agriculture near Greeley, Colorado, and in the vicinity of Denver. The NAQFC modeling framework did not include a recently developed bidirectional flux algorithm for NH3, which has shown to considerably improve NH3 modeling in agricultural regions. The bidirectional flux algorithm, however, is not expected to obtain the magnitude of this increase sufficient to overcome the underestimation of NH3 found in this study. Our results suggest that further improvement of the emission inventories and modeling approaches are required to reduce the bias in NAQFC NH3 modeling predictions.

Computational Analysis of Intersubject Variability and Thrombin Generation in Dilutional Coagulopathy

DTIC Science & Technology

2012-11-01

proteins: Factor (F)II, FV, FVII , FVIII, F IX, and FX, as well as the anticoagulants antithrombin (AT) and TF pathway inhibi- tor (TFPI). The results...coagulation factors FII, FV, FVII , FVIIa, FVIII, F IX and FX, as well as the anticoagulants TFPI and AT and the throm- bin generation inducer TF. The model...scenario and tissue factor concentration. CONCLUSION: Dilutional effects on thrombin genera- tion in a human population can be predicted from trends

Spatiotemporal Patterns of Evapotranspiration in Response to Multiple Environmental Factors Simulated by the Community Land Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shi, Xiaoying; Mao, Jiafu; Thornton, P.

Spatiotemporal patterns of evapotranspiration (ET) over the period from 1982 to 2008 are investigated and attributed to multiple environmental factors using the Community Land Model version 4 (CLM4). Our results show that CLM4 captures the spatial distribution and interannual variability of ET well when compared to observation-based estimates. We find that climate dominates the predicted variability in ET. Elevated atmospheric CO2 concentration also plays an important role in modulating the trend of predicted ET over most land areas, and replaces climate to function as the dominant factor controlling ET changes over the North America, South America and Asia regions. Comparedmore » to the effect of climate and CO2 concentration, the roles of other factors such as nitrogen deposition, land use change and aerosol deposition are less pronounced and regionally dependent. The aerosol deposition contribution is the third most important factor for trends of ET over Europe, while it has the smallest impact over other regions. As ET is a dominant component of the terrestrial water cycle, our results suggest that environmental factors like elevated CO2, nitrogen and aerosol depositions, and land use change, in addition to climate, could have significant impact on future projections of water resources and water cycle dynamics at global and regional scales.« less

Diet and metabolic state are the main factors determining concentrations of perfluoroalkyl substances in female polar bears from Svalbard.

PubMed

Tartu, Sabrina; Bourgeon, Sophie; Aars, Jon; Andersen, Magnus; Lone, Karen; Jenssen, Bjørn Munro; Polder, Anuschka; Thiemann, Gregory W; Torget, Vidar; Welker, Jeffrey M; Routti, Heli

2017-10-01

Perfluoroalkyl substances (PFASs) have been detected in organisms worldwide, including Polar Regions. The polar bear (Ursus maritimus), the top predator of Arctic marine ecosystems, accumulates high concentrations of PFASs, which may be harmful to their health. The aim of this study was to investigate which factors (habitat quality, season, year, diet, metabolic state [i.e. feeding/fasting], breeding status and age) predict PFAS concentrations in female polar bears captured on Svalbard (Norway). We analysed two perfluoroalkyl sulfonates (PFSAs: PFHxS and PFOS) and C 8 -C 13 perfluoroalkyl carboxylates (PFCAs) in 112 plasma samples obtained in April and September 2012-2013. Nitrogen and carbon stable isotope ratios (δ 15 N, δ 13 C) in red blood cells and plasma, and fatty acid profiles in adipose tissue were used as proxies for diet. We determined habitat quality based on movement patterns, capture position and resource selection functions, which are models that predict the probability of use of a resource unit. Plasma urea to creatinine ratios were used as proxies for metabolic state (i.e. feeding or fasting state). Results were obtained from a conditional model averaging of 42 general linear mixed models. Diet was the most important predictor of PFAS concentrations. PFAS concentrations were positively related to trophic level and marine diet input. High PFAS concentrations in females feeding on the eastern part of Svalbard, where the habitat quality was higher than on the western coast, were likely related to diet and possibly to abiotic factors. Concentrations of PFSAs and C 8 -C 10 PFCAs were higher in fasting than in feeding polar bears and PFOS was higher in females with cubs of the year than in solitary females. Our findings suggest that female polar bears that are exposed to the highest levels of PFAS are those 1) feeding on high trophic level sea ice-associated prey, 2) fasting and 3) with small cubs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Application of data mining to the analysis of meteorological data for air quality prediction: A case study in Shenyang

NASA Astrophysics Data System (ADS)

Zhao, Chang; Song, Guojun

2017-08-01

Air pollution is one of the important reasons for restricting the current economic development. PM2.5 which is a vital factor in the measurement of air pollution is defined as a kind of suspended particulate matter with its equivalent diameter less than 25μm, which may enter the alveoli and therefore make a great impact on the human body. Meteorological factors are also one of the main factors affecting the production of PM2.5, therefore, it is essential to establish the model between meteorological factors and PM2.5 for the prediction. Data mining is a promising approach to model PM2.5 change, Shenyang which is one of the most important industrial city in Northeast China with severe air pollutions is set as the case city. Meteorological data (wind direction, wind speed, temperature, humidity, rainfall, etc.) from 2013 to 2015 and PM2.5 concentration data are used for this prediction. As to the requirements of the World Health Organization (WHO), three data mining models, whereby the predictions of PM2.5 are directly generated by the meteorological data. After assessment, the random forest model is appeared to offer better prediction performance than the other two. At last, the accuracy of the generated models are analysed.

Vulnerability of shallow groundwater and drinking-water wells to nitrate in the United States

USGS Publications Warehouse

Nolan, Bernard T.; Hitt, Kerie J.

2006-01-01

Two nonlinear models were developed at the national scale to (1) predict contamination of shallow ground water (typically < 5 m deep) by nitrate from nonpoint sources and (2) to predict ambient nitrate concentration in deeper supplies used for drinking. The new models have several advantages over previous national-scale approaches. First, they predict nitrate concentration (rather than probability of occurrence), which can be directly compared with water-quality criteria. Second, the models share a mechanistic structure that segregates nitrogen (N) sources and physical factors that enhance or restrict nitrate transport and accumulation in ground water. Finally, data were spatially averaged to minimize small-scale variability so that the large-scale influences of N loading, climate, and aquifer characteristics could more readily be identified. Results indicate that areas with high N application, high water input, well-drained soils, fractured rocks or those with high effective porosity, and lack of attenuation processes have the highest predicted nitrate concentration. The shallow groundwater model (mean square error or MSE = 2.96) yielded a coefficient of determination (R2) of 0.801, indicating that much of the variation in nitrate concentration is explained by the model. Moderate to severe nitrate contamination is predicted to occur in the High Plains, northern Midwest, and selected other areas. The drinking-water model performed comparably (MSE = 2.00, R2 = 0.767) and predicts that the number of users on private wells and residing in moderately contaminated areas (>5 to ≤10 mg/L nitrate) decreases by 12% when simulation depth increases from 10 to 50 m.

Vulnerability of shallow groundwater and drinking-water wells to nitrate in the United States.

PubMed

Nolan, Bernard T; Hitt, Kerie J

2006-12-15

Two nonlinear models were developed at the national scale to (1) predict contamination of shallow ground water (typically < 5 m deep) by nitrate from nonpoint sources and (2) to predict ambient nitrate concentration in deeper supplies used for drinking. The new models have several advantages over previous national-scale approaches. First, they predict nitrate concentration (rather than probability of occurrence), which can be directly compared with water-quality criteria. Second, the models share a mechanistic structure that segregates nitrogen (N) sources and physical factors that enhance or restrict nitrate transport and accumulation in ground water. Finally, data were spatially averaged to minimize small-scale variability so that the large-scale influences of N loading, climate, and aquifer characteristics could more readily be identified. Results indicate that areas with high N application, high water input, well-drained soils, fractured rocks or those with high effective porosity, and lack of attenuation processes have the highest predicted nitrate concentration. The shallow groundwater model (mean square error or MSE = 2.96) yielded a coefficient of determination (R(2)) of 0.801, indicating that much of the variation in nitrate concentration is explained by the model. Moderate to severe nitrate contamination is predicted to occur in the High Plains, northern Midwest, and selected other areas. The drinking-water model performed comparably (MSE = 2.00, R(2) = 0.767) and predicts that the number of users on private wells and residing in moderately contaminated areas (>5 to < or =10 mg/L nitrate) decreases by 12% when simulation depth increases from 10 to 50 m.

Investigation of Carbide Precipitation Process and Chromium Depletion during Thermal Treatment of Alloy 690

NASA Astrophysics Data System (ADS)

Jiao, S. Y.; Zhang, M. C.; Zheng, L.; Dong, J. X.

2010-01-01

For the purpose of studying the effect of heat treatment on carbide morphology and chromium concentration distribution, which are critical to the resistance of alloy 690 to stress corrosion cracking (SCC), a series of thermal treatments was performed. A model taking into account the intercorrelated dynamic process between the carbide precipitation and chemical diffusion of the chromium atom from matrix to grain boundary (GB) was constructed on the basis of classical nucleation theory, Kolmogorov-Johnson-Mehl-Avrami law, and diffusion theory. The validity of this model was evaluated by comparing the simulated results of the carbide average size and chromium concentration near the GB with the corresponding measured results. A discontinuous factor was introduced based on the relation linking the interdistance between the carbides and the carbide average size; thus, the carbide morphology and chromium concentration could be predicted by this model. According to the results of the experiments and simulations, a carbide discontinuous factor smaller than 2.2 together with the chromium concentration at the GB higher than a critical value (21 wt pct) were essential for the corrosion resistance ability of the alloy, and then some proper heat-treatment conditions were obtained through predicting the value of the two variables. In addition, the effects of the grain size and composition variation on the carbide discontinuous factor and chromium concentration profile were simulated. The results indicated that an intermediate grain size of approximately 31.8 to ~63.5 μm was beneficial for effectively improving the resistance of the alloy to SCC. Simultaneously, the carbon content should be adjusted near 0.02 pct, and the chromium content should be the highest possible in its chemical composition scale.

Gene expression analysis in zebrafish embryos: a potential approach to predict effect concentrations in the fish early life stage test.

PubMed

Weil, Mirco; Scholz, Stefan; Zimmer, Michaela; Sacher, Frank; Duis, Karen

2009-09-01

Based on the hypothesis that analysis of gene expression could be used to predict chronic fish toxicity, the zebrafish (Danio rerio) embryo test (DarT), developed as a replacement method for the acute fish test, was expanded to a gene expression D. rerio embryo test (Gene-DarT). The effects of 14 substances on lethal and sublethal endpoints of the DarT and on expression of potential marker genes were investigated: the aryl hydrocarbon receptor 2, cytochrome P450 1A (cypla), heat shock protein 70, fizzy-related protein 1, the transcription factors v-maf musculoaponeurotic fibrosarcoma oncogene family protein g (avian) 1 and NF-E2-p45-related factor, and heme oxygenase 1 (hmox1). After exposure of zebrafish embryos for 48 h, differential gene expression was evaluated using reverse transcriptase-polymerase chain reaction, gel electrophoresis, and densitometric analysis of the gels. All tested compounds significantly affected the expression of at least one potential marker gene, with cyp1a and hmox1 being most sensitive. Lowest-observed-effect concentrations (LOECs) for gene expression were below concentrations resulting in 10% lethal effects in the DarT. For 10 (3,4- and 3,5-dichloroaniline, 1,4-dichlorobenzene, 2,4-dinitrophenol, atrazine, parathion-ethyl, chlorotoluron, genistein, 4-nitroquinoline-1-oxide, and cadmium) out of the 14 tested substances, LOEC values derived with the Gene-DarT differ by a factor of less than 10 from LOEC values of fish early life stage tests with zebrafish. For pentachloroaniline and pentachlorobenzene, the Gene-DarT showed a 23- and 153-fold higher sensitivity, respectively, while for lindane, it showed a 13-fold lower sensitivity. For ivermectin, the Gene-DarT was by a factor of more than 1,000 less sensitive than the acute fish test. The results of the present study indicate that gene expression analysis in zebrafish embryos could principally be used to predict effect concentrations in the fish early life stage test.

Evaluation of NO2 predictions by the plume volume molar ratio method (PVMRM) and ozone limiting method (OLM) in AERMOD using new field observations.

PubMed

Hendrick, Elizabeth M; Tino, Vincent R; Hanna, Steven R; Egan, Bruce A

2013-07-01

The U.S. Environmental Protection Agency (EPA) plume volume molar ratio method (PVMRM) and the ozone limiting method (OLM) are in the AERMOD model to predict the 1-hr average NO2/NO(x) concentration ratio. These ratios are multiplied by the AERMOD predicted NO(x) concentration to predict the 1-hr average NO2 concentration. This paper first briefly reviews PVMRM and OLM and points out some scientific parameterizations that could be improved (such as specification of relative dispersion coefficients) and then discusses an evaluation of the PVMRM and OLM methods as implemented in AERMOD using a new data set. While AERMOD has undergone many model evaluation studies in its default mode, PVMRM and OLM are nondefault options, and to date only three NO2 field data sets have been used in their evaluations. Here AERMOD/PVMRM and AERMOD/OLM codes are evaluated with a new data set from a northern Alaskan village with a small power plant. Hourly pollutant concentrations (NO, NO2, ozone) as well as meteorological variables were measured at a single monitor 500 m from the plant. Power plant operating parameters and emissions were calculated based on hourly operator logs. Hourly observations covering 1 yr were considered, but the evaluations only used hours when the wind was in a 60 degrees sector including the monitor and when concentrations were above a threshold. PVMRM is found to have little bias in predictions of the C(NO2)/C(NO(x)) ratio, which mostly ranged from 0.2 to 0.4 at this site. OLM overpredicted the ratio. AERMOD overpredicts the maximum NO(x) concentration but has an underprediction bias for lower concentrations. AERMOD/PVMRM overpredicts the maximum C(NO2) by about 50%, while AERMOD/OLM overpredicts by a factor of 2. For 381 hours evaluated, there is a relative mean bias in C(NO2) predictions of near zero for AERMOD/PVMRM, while the relative mean bias reflects a factor of 2 overprediction for AERMOD/OLM. This study was initiated because the new stringent 1-hr NO2 NAAQS has prompted modelers to more widely use the PVMRM and OLM methods for conversion of NO(x) to NO2 in the AERMOD regulatory model. To date these methods have been evaluated with a limited number of data sets. This study identified a new data set of ambient pollutant and meteorological monitoring near an isolated power plant in Wainwright, Alaska. To supplement the existing evaluations, this new data were used to evaluate PVMRM and OLM. This new data set has been and will be made available to other scientists for future investigations.

Use of watershed factors to predict consumer surfactant risk, water quality, and habitat quality in the upper Trinity River, Texas.

PubMed

Atkinson, S F; Johnson, D R; Venables, B J; Slye, J L; Kennedy, J R; Dyer, S D; Price, B B; Ciarlo, M; Stanton, K; Sanderson, H; Nielsen, A

2009-06-15

Surfactants are high production volume chemicals that are used in a wide assortment of "down-the-drain" consumer products. Wastewater treatment plants (WWTPs) generally remove 85 to more than 99% of all surfactants from influents, but residual concentrations are discharged into receiving waters via wastewater treatment plant effluents. The Trinity River that flows through the Dallas-Fort Worth metropolitan area, Texas, is an ideal study site for surfactants due to the high ratio of wastewater treatment plant effluent to river flow (>95%) during late summer months, providing an interesting scenario for surfactant loading into the environment. The objective of this project was to determine whether surfactant concentrations, expressed as toxic units, in-stream water quality, and aquatic habitat in the upper Trinity River could be predicted based on easily accessible watershed characteristics. Surface water and pore water samples were collected in late summer 2005 at 11 sites on the Trinity River in and around the Dallas-Fort Worth metropolitan area. Effluents of 4 major waste water treatment plants that discharge effluents into the Trinity River were also sampled. General chemistries and individual surfactant concentrations were determined, and total surfactant toxic units were calculated. GIS models of geospatial, anthropogenic factors (e.g., population density) and natural factors (e.g., soil organic matter) were collected and analyzed according to subwatersheds. Multiple regression analyses using the stepwise maximum R(2) improvement method were performed to develop prediction models of surfactant risk, water quality, and aquatic habitat (dependent variables) using the geospatial parameters (independent variables) that characterized the upper Trinity River watershed. We show that GIS modeling has the potential to be a reliable and inexpensive method of predicting water and habitat quality in the upper Trinity River watershed and perhaps other highly urbanized watersheds in semi-arid regions.

Rating curve estimation of nutrient loads in Iowa rivers

USGS Publications Warehouse

Stenback, G.A.; Crumpton, W.G.; Schilling, K.E.; Helmers, M.J.

2011-01-01

Accurate estimation of nutrient loads in rivers and streams is critical for many applications including determination of sources of nutrient loads in watersheds, evaluating long-term trends in loads, and estimating loading to downstream waterbodies. Since in many cases nutrient concentrations are measured on a weekly or monthly frequency, there is a need to estimate concentration and loads during periods when no data is available. The objectives of this study were to: (i) document the performance of a multiple regression model to predict loads of nitrate and total phosphorus (TP) in Iowa rivers and streams; (ii) determine whether there is any systematic bias in the load prediction estimates for nitrate and TP; and (iii) evaluate streamflow and concentration factors that could affect the load prediction efficiency. A commonly cited rating curve regression is utilized to estimate riverine nitrate and TP loads for rivers in Iowa with watershed areas ranging from 17.4 to over 34,600km2. Forty-nine nitrate and 44 TP datasets each comprising 5-22years of approximately weekly to monthly concentrations were examined. Three nitrate data sets had sample collection frequencies averaging about three samples per week. The accuracy and precision of annual and long term riverine load prediction was assessed by direct comparison of rating curve load predictions with observed daily loads. Significant positive bias of annual and long term nitrate loads was detected. Long term rating curve nitrate load predictions exceeded observed loads by 25% or more at 33% of the 49 measurement sites. No bias was found for TP load prediction although 15% of the 44 cases either underestimated or overestimate observed long-term loads by more than 25%. The rating curve was found to poorly characterize nitrate and phosphorus variation in some rivers. ?? 2010 .

Short-time dynamics of lysozyme solutions with competing short-range attraction and long-range repulsion: Experiment and theory

NASA Astrophysics Data System (ADS)

Riest, Jonas; Nägele, Gerhard; Liu, Yun; Wagner, Norman J.; Godfrin, P. Douglas

2018-02-01

Recently, atypical static features of microstructural ordering in low-salinity lysozyme protein solutions have been extensively explored experimentally and explained theoretically based on a short-range attractive plus long-range repulsive (SALR) interaction potential. However, the protein dynamics and the relationship to the atypical SALR structure remain to be demonstrated. Here, the applicability of semi-analytic theoretical methods predicting diffusion properties and viscosity in isotropic particle suspensions to low-salinity lysozyme protein solutions is tested. Using the interaction potential parameters previously obtained from static structure factor measurements, our results of Monte Carlo simulations representing seven experimental lysoyzme samples indicate that they exist either in dispersed fluid or random percolated states. The self-consistent Zerah-Hansen scheme is used to describe the static structure factor, S(q), which is the input to our calculation schemes for the short-time hydrodynamic function, H(q), and the zero-frequency viscosity η. The schemes account for hydrodynamic interactions included on an approximate level. Theoretical predictions for H(q) as a function of the wavenumber q quantitatively agree with experimental results at small protein concentrations obtained using neutron spin echo measurements. At higher concentrations, qualitative agreement is preserved although the calculated hydrodynamic functions are overestimated. We attribute the differences for higher concentrations and lower temperatures to translational-rotational diffusion coupling induced by the shape and interaction anisotropy of particles and clusters, patchiness of the lysozyme particle surfaces, and the intra-cluster dynamics, features not included in our simple globular particle model. The theoretical results for the solution viscosity, η, are in qualitative agreement with our experimental data even at higher concentrations. We demonstrate that semi-quantitative predictions of diffusion properties and viscosity of solutions of globular proteins are possible given only the equilibrium structure factor of proteins. Furthermore, we explore the effects of changing the attraction strength on H(q) and η.

Use of linear regression models to determine influence factors on the concentration levels of radon in occupied houses

NASA Astrophysics Data System (ADS)

Buermeyer, Jonas; Gundlach, Matthias; Grund, Anna-Lisa; Grimm, Volker; Spizyn, Alexander; Breckow, Joachim

2016-09-01

This work is part of the analysis of the effects of constructional energy-saving measures to radon concentration levels in dwellings performed on behalf of the German Federal Office for Radiation Protection. In parallel to radon measurements for five buildings, both meteorological data outside the buildings and the indoor climate factors were recorded. In order to access effects of inhabited buildings, the amount of carbon dioxide (CO2) was measured. For a statistical linear regression model, the data of one object was chosen as an example. Three dummy variables were extracted from the process of the CO2 concentration to provide information on the usage and ventilation of the room. The analysis revealed a highly autoregressive model for the radon concentration with additional influence by the natural environmental factors. The autoregression implies a strong dependency on a radon source since it reflects a backward dependency in time. At this point of the investigation, it cannot be determined whether the influence by outside factors affects the source of radon or the habitant’s ventilation behavior resulting in variation of the occurring concentration levels. In any case, the regression analysis might provide further information that would help to distinguish these effects. In the next step, the influence factors will be weighted according to their impact on the concentration levels. This might lead to a model that enables the prediction of radon concentration levels based on the measurement of CO2 in combination with environmental parameters, as well as the development of advices for ventilation.

Natriuretic peptides and integrated risk assessment for cardiovascular disease: an individual-participant-data meta-analysis.

PubMed

Natriuretic Peptides Studies Collaboration; Willeit, Peter; Kaptoge, Stephen; Welsh, Paul; Butterworth, Adam; Chowdhury, Rajiv; Spackman, Sarah; Pennells, Lisa; Gao, Pei; Burgess, Stephen; Freitag, Daniel; Sweeting, Michael; Wood, Angela; Cook, Nancy; Judd, Suzanne; Trompet, Stella; Nambi, Vijay; Olsen, Michael; Everett, Brendan; Kee, Frank; Ärnlöv, Johan; Salomaa, Veikko; Levy, Daniel; Kauhanen, Jussi; Laukkanen, Jari; Kavousi, Maryam; Ninomiya, Toshiharu; Casas, Juan-Pablo; Daniels, Lori; Lind, Lars; Kistorp, Caroline; Rosenberg, Jens; Mueller, Thomas; Rubattu, Speranza; Panagiotakos, Demosthenes; Franco, Oscar; de Lemos, James; Luchner, Andreas; Kizer, Jorge; Kiechl, Stefan; Salonen, Jukka; Goya Wannamethee, S; de Boer, Rudolf; Nordestgaard, Børge; Andersson, Jonas; Jørgensen, Torben; Melander, Olle; Ballantyne, Christie; DeFilippi, Christopher; Ridker, Paul; Cushman, Mary; Rosamond, Wayne; Thompson, Simon; Gudnason, Vilmundur; Sattar, Naveed; Danesh, John; Di Angelantonio, Emanuele

2016-10-01

Guidelines for primary prevention of cardiovascular diseases focus on prediction of coronary heart disease and stroke. We assessed whether or not measurement of N-terminal-pro-B-type natriuretic peptide (NT-proBNP) concentration could enable a more integrated approach than at present by predicting heart failure and enhancing coronary heart disease and stroke risk assessment. In this individual-participant-data meta-analysis, we generated and harmonised individual-participant data from relevant prospective studies via both de-novo NT-proBNP concentration measurement of stored samples and collection of data from studies identified through a systematic search of the literature (PubMed, Scientific Citation Index Expanded, and Embase) for articles published up to Sept 4, 2014, using search terms related to natriuretic peptide family members and the primary outcomes, with no language restrictions. We calculated risk ratios and measures of risk discrimination and reclassification across predicted 10 year risk categories (ie, <5%, 5% to <7·5%, and ≥7·5%), adding assessment of NT-proBNP concentration to that of conventional risk factors (ie, age, sex, smoking status, systolic blood pressure, history of diabetes, and total and HDL cholesterol concentrations). Primary outcomes were the combination of coronary heart disease and stroke, and the combination of coronary heart disease, stroke, and heart failure. We recorded 5500 coronary heart disease, 4002 stroke, and 2212 heart failure outcomes among 95 617 participants without a history of cardiovascular disease in 40 prospective studies. Risk ratios (for a comparison of the top third vs bottom third of NT-proBNP concentrations, adjusted for conventional risk factors) were 1·76 (95% CI 1·56-1·98) for the combination of coronary heart disease and stroke and 2·00 (1·77-2·26) for the combination of coronary heart disease, stroke, and heart failure. Addition of information about NT-proBNP concentration to a model containing conventional risk factors was associated with a C-index increase of 0·012 (0·010-0·014) and a net reclassification improvement of 0·027 (0·019-0·036) for the combination of coronary heart disease and stroke and a C-index increase of 0·019 (0·016-0·022) and a net reclassification improvement of 0·028 (0·019-0·038) for the combination of coronary heart disease, stroke, and heart failure. In people without baseline cardiovascular disease, NT-proBNP concentration assessment strongly predicted first-onset heart failure and augmented coronary heart disease and stroke prediction, suggesting that NT-proBNP concentration assessment could be used to integrate heart failure into cardiovascular disease primary prevention. British Heart Foundation, Austrian Science Fund, UK Medical Research Council, National Institute for Health Research, European Research Council, and European Commission Framework Programme 7. Copyright © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY license. Published by Elsevier Ltd.. All rights reserved.

Towards a better prediction of peak concentration, volume of distribution and half-life after oral drug administration in man, using allometry.

PubMed

Sinha, Vikash K; Vaarties, Karin; De Buck, Stefan S; Fenu, Luca A; Nijsen, Marjoleen; Gilissen, Ron A H J; Sanderson, Wendy; Van Uytsel, Kelly; Hoeben, Eva; Van Peer, Achiel; Mackie, Claire E; Smit, Johan W

2011-05-01

It is imperative that new drugs demonstrate adequate pharmacokinetic properties, allowing an optimal safety margin and convenient dosing regimens in clinical practice, which then lead to better patient compliance. Such pharmacokinetic properties include suitable peak (maximum) plasma drug concentration (C(max)), area under the plasma concentration-time curve (AUC) and a suitable half-life (t(½)). The C(max) and t(½) following oral drug administration are functions of the oral clearance (CL/F) and apparent volume of distribution during the terminal phase by the oral route (V(z)/F), each of which may be predicted and combined to estimate C(max) and t(½). Allometric scaling is a widely used methodology in the pharmaceutical industry to predict human pharmacokinetic parameters such as clearance and volume of distribution. In our previous published work, we have evaluated the use of allometry for prediction of CL/F and AUC. In this paper we describe the evaluation of different allometric scaling approaches for the prediction of C(max), V(z)/F and t(½) after oral drug administration in man. Twenty-nine compounds developed at Janssen Research and Development (a division of Janssen Pharmaceutica NV), covering a wide range of physicochemical and pharmacokinetic properties, were selected. The C(max) following oral dosing of a compound was predicted using (i) simple allometry alone; (ii) simple allometry along with correction factors such as plasma protein binding (PPB), maximum life-span potential or brain weight (reverse rule of exponents, unbound C(max) approach); and (iii) an indirect approach using allometrically predicted CL/F and V(z)/F and absorption rate constant (k(a)). The k(a) was estimated from (i) in vivo pharmacokinetic experiments in preclinical species; and (ii) predicted effective permeability in man (P(eff)), using a Caco-2 permeability assay. The V(z)/F was predicted using allometric scaling with or without PPB correction. The t(½) was estimated from the allometrically predicted parameters CL/F and V(z)/F. Predictions were deemed adequate when errors were within a 2-fold range. C(max) and t(½) could be predicted within a 2-fold error range for 59% and 66% of the tested compounds, respectively, using allometrically predicted CL/F and V(z)/F. The best predictions for C(max) were obtained when k(a) values were calculated from the Caco-2 permeability assay. The V(z)/F was predicted within a 2-fold error range for 72% of compounds when PPB correction was applied as the correction factor for scaling. We conclude that (i) C(max) and t(½) are best predicted by indirect scaling approaches (using allometrically predicted CL/F and V(z)/F and accounting for k(a) derived from permeability assay); and (ii) the PPB is an important correction factor for the prediction of V(z)/F by using allometric scaling. Furthermore, additional work is warranted to understand the mechanisms governing the processes underlying determination of C(max) so that the empirical approaches can be fine-tuned further.

Association of Lipid Accumulation Product with Cardio-Metabolic Risk Factors in Postmenopausal Women.

PubMed

Namazi Shabestari, Alireza; Asadi, Mojgan; Jouyandeh, Zahra; Qorbani, Mostafa; Kelishadi, Roya

2016-06-01

The lipid accumulation product is a novel, safe and inexpensive index of central lipid over accumulation based on waist circumference and fasting concentration of circulating triglycerides. This study was designed to investigate the ability of lipid accumulation product to predict Cardio-metabolic risk factors in postmenopausal women. In this Cross-sectional study, 264 postmenopausal women by using convenience sampling method were selected from menopause clinic in Tehran. Cardio-metabolic risk factors were measured, and lipid accumulation product (waist-58×triglycerides [nmol/L]) was calculated. Optimal cut-off point of lipid accumulation product for predicting metabolic syndrome was estimated by ROC (Receiver-operating characteristic) curve analysis. Metabolic syndrome was diagnosed in 41.2% of subjects. Optimal cut-off point of lipid accumulation product for predicting metabolic syndrome was 47.63 (sensitivity:75%; specificity:77.9%). High lipid accumulation product increases risk of all Cardio-metabolic risk factors except overweight, high Total Cholesterol, high Low Density Lipoprotein Cholesterol and high Fasting Blood Sugar in postmenopausal women. Our findings show that lipid accumulation product is associated with metabolic syndrome and some Cardio-metabolic risk factors Also lipid accumulation product may have been a useful tool for predicting cardiovascular disease and metabolic syndrome risk in postmenopausal women.

Predicting bioconcentration of chemicals into vegetation from soil or air using the molecular connectivity index

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dowdy, D.L.; McKone, T.E.; Hsieh, D.P.H.

1995-12-31

Bioconcentration factors (BCFs) are the ratio of chemical concentration found in an exposed organism (in this case a plant) to the concentration in an air or soil exposure medium. The authors examine here the use of molecular connectivity indices (MCIs) as quantitative structure-activity relationships (QSARS) for predicting BCFs for organic chemicals between plants and air or soil. The authors compare the reliability of the octanol-air partition coefficient (K{sub oa}) to the MC based prediction method for predicting plant/air partition coefficients. The authors also compare the reliability of the octanol/water partition coefficient (K{sub ow}) to the MC based prediction method formore » predicting plant/soil partition coefficients. The results here indicate that, relative to the use of K{sub ow} or K{sub oa} as predictors of BCFs the MC can substantially increase the reliability with which BCFs can be estimated. The authors find that the MC provides a relatively precise and accurate method for predicting the potential biotransfer of a chemical from environmental media into plants. In addition, the MC is much faster and more cost effective than direct measurements.« less

Chronic beryllium disease and cancer risk estimates with uncertainty for beryllium released to the air from the Rocky Flats Plant.

PubMed Central

McGavran, P D; Rood, A S; Till, J E

1999-01-01

Beryllium was released into the air from routine operations and three accidental fires at the Rocky Flats Plant (RFP) in Colorado from 1958 to 1989. We evaluated environmental monitoring data and developed estimates of airborne concentrations and their uncertainties and calculated lifetime cancer risks and risks of chronic beryllium disease to hypothetical receptors. This article discusses exposure-response relationships for lung cancer and chronic beryllium disease. We assigned a distribution to cancer slope factor values based on the relative risk estimates from an occupational epidemiologic study used by the U.S. Environmental Protection Agency (EPA) to determine the slope factors. We used the regional atmospheric transport code for Hanford emission tracking atmospheric transport model for exposure calculations because it is particularly well suited for long-term annual-average dispersion estimates and it incorporates spatially varying meteorologic and environmental parameters. We accounted for model prediction uncertainty by using several multiplicative stochastic correction factors that accounted for uncertainty in the dispersion estimate, the meteorology, deposition, and plume depletion. We used Monte Carlo techniques to propagate model prediction uncertainty through to the final risk calculations. We developed nine exposure scenarios of hypothetical but typical residents of the RFP area to consider the lifestyle, time spent outdoors, location, age, and sex of people who may have been exposed. We determined geometric mean incremental lifetime cancer incidence risk estimates for beryllium inhalation for each scenario. The risk estimates were < 10(-6). Predicted air concentrations were well below the current reference concentration derived by the EPA for beryllium sensitization. Images Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 PMID:10464074

Influence of monitoring data selection for optimization of a steady state multimedia model on the magnitude and nature of the model prediction bias.

PubMed

Kim, Hee Seok; Lee, Dong Soo

2017-11-01

SimpleBox is an important multimedia model used to estimate the predicted environmental concentration for screening-level exposure assessment. The main objectives were (i) to quantitatively assess how the magnitude and nature of prediction bias of SimpleBox vary with the selection of observed concentration data set for optimization and (ii) to present the prediction performance of the optimized SimpleBox. The optimization was conducted using a total of 9604 observed multimedia data for 42 chemicals of four groups (i.e., polychlorinated dibenzo-p-dioxins/furans (PCDDs/Fs), polybrominated diphenyl ethers (PBDEs), phthalates, and polycyclic aromatic hydrocarbons (PAHs)). The model performance was assessed based on the magnitude and skewness of prediction bias. Monitoring data selection in terms of number of data and kind of chemicals plays a significant role in optimization of the model. The coverage of the physicochemical properties was found to be very important to reduce the prediction bias. This suggests that selection of observed data should be made such that the physicochemical property (such as vapor pressure, octanol-water partition coefficient, octanol-air partition coefficient, and Henry's law constant) range of the selected chemical groups be as wide as possible. With optimization, about 55%, 90%, and 98% of the total number of the observed concentration ratios were predicted within factors of three, 10, and 30, respectively, with negligible skewness. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparison of the predictions of two road dust emission models with the measurements of a mobile van

NASA Astrophysics Data System (ADS)

Kauhaniemi, M.; Stojiljkovic, A.; Pirjola, L.; Karppinen, A.; Härkönen, J.; Kupiainen, K.; Kangas, L.; Aarnio, M. A.; Omstedt, G.; Denby, B. R.; Kukkonen, J.

2014-02-01

The predictions of two road dust suspension emission models were compared with the on-site mobile measurements of suspension emission factors. Such a quantitative comparison has not previously been reported in the reviewed literature. The models used were the Nordic collaboration model NORTRIP (NOn-exhaust Road TRaffic Induced Particle emissions) and the Swedish-Finnish FORE model (Forecasting Of Road dust Emissions). These models describe particulate matter generated by the wear of road surface due to traction control methods and processes that control the suspension of road dust particles into the air. An experimental measurement campaign was conducted using a mobile laboratory called SNIFFER, along two selected road segments in central Helsinki in 2007 and 2008. The suspended PM10 concentration was measured behind the left rear tyre and the street background PM10 concentration in front of the van. Both models reproduced the measured seasonal variation of suspension emission factors fairly well during both years at both measurement sites. However, both models substantially under-predicted the measured emission values. The results indicate that road dust emission models can be directly compared with mobile measurements; however, more extensive and versatile measurement campaigns will be needed in the future.

Environmental Conditions Associated with Elevated Vibrio parahaemolyticus Concentrations in Great Bay Estuary, New Hampshire

PubMed Central

Urquhart, Erin A.; Jones, Stephen H.; Yu, Jong W.; Schuster, Brian M.; Marcinkiewicz, Ashley L.; Whistler, Cheryl A.; Cooper, Vaughn S.

2016-01-01

Reports from state health departments and the Centers for Disease Control and Prevention indicate that the annual number of reported human vibriosis cases in New England has increased in the past decade. Concurrently, there has been a shift in both the spatial distribution and seasonal detection of Vibrio spp. throughout the region based on limited monitoring data. To determine environmental factors that may underlie these emerging conditions, this study focuses on a long-term database of Vibrio parahaemolyticus concentrations in oyster samples generated from data collected from the Great Bay Estuary, New Hampshire over a period of seven consecutive years. Oyster samples from two distinct sites were analyzed for V. parahaemolyticus abundance, noting significant relationships with various biotic and abiotic factors measured during the same period of study. We developed a predictive modeling tool capable of estimating the likelihood of V. parahaemolyticus presence in coastal New Hampshire oysters. Results show that the inclusion of chlorophyll a concentration to an empirical model otherwise employing only temperature and salinity variables, offers improved predictive capability for modeling the likelihood of V. parahaemolyticus in the Great Bay Estuary. PMID:27144925

Modeling the probability of arsenic in groundwater in New England as a tool for exposure assessment.

PubMed

Ayotte, Joseph D; Nolan, Bernard T; Nuckols, John R; Cantor, Kenneth P; Robinson, Gilpin R; Baris, Dalsu; Hayes, Laura; Karagas, Margaret; Bress, William; Silverman, Debra T; Lubin, Jay H

2006-06-01

We developed a process-based model to predict the probability of arsenic exceeding 5 microg/L in drinking water wells in New England bedrock aquifers. The model is being used for exposure assessment in an epidemiologic study of bladder cancer. One important study hypothesis that may explain increased bladder cancer risk is elevated concentrations of inorganic arsenic in drinking water. In eastern New England, 20-30% of private wells exceed the arsenic drinking water standard of 10 micrograms per liter. Our predictive model significantly improves the understanding of factors associated with arsenic contamination in New England. Specific rock types, high arsenic concentrations in stream sediments, geochemical factors related to areas of Pleistocene marine inundation and proximity to intrusive granitic plutons, and hydrologic and landscape variables relating to groundwater residence time increase the probability of arsenic occurrence in groundwater. Previous studies suggest that arsenic in bedrock groundwater may be partly from past arsenical pesticide use. Variables representing historic agricultural inputs do not improve the model, indicating that this source does not significantly contribute to current arsenic concentrations. Due to the complexity of the fractured bedrock aquifers in the region, well depth and related variables also are not significant predictors.

Life extension of Structural Repairs – A statistical approach towards efficiency improvement

NASA Astrophysics Data System (ADS)

Deepashri, N. V.; Kalaiyappan, Mohan

2018-05-01

The life extension program of aircraft is taken up whenever aircraft’s intended life reaches close to its DSG (Design Service Goal). The Extended Service Goal (ESG) of an aircraft, in general, and structural repairs, in particular, is arrived at on the basis of F&DT (Fatigue & Damage Tolerance) analysis. Life extension program of aircraft consists of assessment of remaining life of all parts of the aircrafts including structural, mechanical, and electrical and avionics equipment and structural repairs. For life extension of stringer repair, as an example, it is required to re-assess the fatigue life of stringer in the presence of coupling under modified load spectrum. This is achieved by assessing the fatigue life of Web and Outer Flange (OF) part of stringers separately as per F&DT justification philosophy. Assessment of the fatigue life requires determination of stress concentration factor (Kt) for different combination of width, pitch, stringer thickness, coupling thickness and pad-up thickness of all stringer profiles available in different sections of fuselage. Determination of stress concentration factor for Web and Outer Flange of stringer profile covering entire ranges involves substantial number of Finite Element (FE) analysis. In order to optimise the number of FE runs, stress concentration factor is determined under worst repair factors combination (max. plate width; max. thickness; max. pitch; min. rivet dia.; and min. No. of rivets) resulting in conservative value. A parametric study of Web and Outer Flange data across stringer profiles were carried out and proven statistical techniques were used to find the optimal equation to predict stress concentration factor. This in turn reduced number of FE runs substantially for a given range of width, pitch, stringer thickness and so on. The use of optimal equation obtained through regression analysis is able to predict Kt within reasonable accuracy for a given range of inputs.

Estimate of uptake and translocation of emerging organic contaminants from irrigation water concentration in lettuce grown under controlled conditions.

PubMed

Hurtado, Carlos; Domínguez, Carmen; Pérez-Babace, Lorea; Cañameras, Núria; Comas, Jordi; Bayona, Josep M

2016-03-15

The widespread distribution of emerging organic contaminants (EOCs) in the water cycle can lead to their incorporation in irrigated crops, posing a potential risk for human consumption. To gain further insight into the processes controlling the uptake of organic microcontaminants, Batavia lettuce (Lactuca sativa) grown under controlled conditions was watered with EOCs (e.g., non-steroidal anti-inflammatories, sulfonamides, β-blockers, phenolic estrogens, anticonvulsants, stimulants, polycyclic musks, biocides) at different concentrations (0-40μgL(-1)). Linear correlations were obtained between the EOC concentrations in the roots and leaves and the watering concentrations for most of the contaminants investigated. However, large differences were found in the root concentration factors ( [Formula: see text] =0.27-733) and leaf translocation concentration factors ( [Formula: see text] =0-3) depending on the persistence of the target contaminants in the rhizosphere and the specific physicochemical properties of each one. With the obtained dataset, a simple predictive model based on a linear regression and the root bioconcentration and translocation factors can be used to estimate the concentration of the target EOCs in leaves based on the dose supplied in the irrigation water or the soil concentration. Finally, enantiomeric fractionation of racemic ibuprofen from the initial spiking mixture suggests that biodegradation mainly occurs in the rhizosphere. Copyright © 2015 Elsevier B.V. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, W.; Kleunen, A. van; Immerzeel, J.

The purpose of this study was to assess the suitability of applying equilibrium partitioning (EqP) theory to predict the bioaccumulation of polycyclic aromatic hydrocarbons (PAHs) by earthworms when these are exposed to contaminated soils in the field. Studies carried out in situ in various contaminated floodplain sites showed the presence of linear relationships with intercept zero between the lipid-normalized concentration of different PAHs in the earthworm, Lumbricus rubellus and the organic-matter-normalized concentration of the compounds in soil. The demonstration of such an isometric relationship is in agreement with the prediction of EqP theory that the biota-soil accumulation factor (BSAF) shouldmore » be independent of the octanol/water partition coefficient, log K{sub ow}. The average BSAF of PAH compounds in the sampled 20-cm top layer of soil was 0.10. The present study also investigated the route of uptake of PAHs for earthworms in soil. The bioconcentration factor of low-molecular-weight PAHs, such as phenanthrene, fluoranthene, and pyrene, was derived from bioconcentration kinetic modeling of water-only experiments and found to be of the same order of magnitude as the bioaccumulation factor in the field when the latter was normalized to calculated concentrations in soil pore water. The results indicated that the exposure of earthworms to PAHs in soil is mediated through direct contact of the worms with the dissolved interstitial soil-water phase, further supporting the applicability of EqP theory to PAHs. The experimental data on the biotransformation of PAHs suggest that earthworms possess some capacity of metabolization, although this does not seem to be a major factor in the total elimination of these compounds. Even though the EqP approach was found to be applicable to low-molecular-weight PAHs with respect to the prediction of bioaccumulation by earthworms in the field, the results were less conclusive for high-molecular-weight compounds, such as benzo[a]pyrene.« less

Prediction of urinary nitrogen and urinary urea nitrogen excretion by lactating dairy cattle in northwestern Europe and North America: a meta-analysis.

PubMed

Spek, J W; Dijkstra, J; van Duinkerken, G; Hendriks, W H; Bannink, A

2013-07-01

A meta-analysis was conducted on the effect of dietary and animal factors on the excretion of total urinary nitrogen (UN) and urinary urea nitrogen (UUN) in lactating dairy cattle in North America (NA) and northwestern Europe (EU). Mean treatment data were used from 47 trials carried out in NA and EU. Mixed model analysis was used with experiment included as a random effect and all other factors, consisting of dietary and animal characteristics, included as fixed effects. Fixed factors were nested within continent (EU or NA). A distinction was made between urinary excretions based on either urine spot samples or calculated assuming a zero N balance, and excretions that were determined by total collection of urine only. Moreover, with the subset of data based on total collection of urine, a new data set was created by calculating urinary N excretion assuming a zero N balance. Comparison with the original subset of data allowed for examining the effect of such an assumption on the relationship established between milk urea N (MUN) concentration and UN. Of all single dietary and animal factors evaluated to predict N excretion in urine, MUN and dietary crude protein (CP) concentration were by far the best predictors. Urinary N excretion was best predicted by the combination of MUN, CP, and dry matter intake, whereas UUN was best predicted by the combination of MUN and CP. All other factors did not improve or only marginally improved the prediction of UN or UUN. The relationship between UN and MUN differed between NA and EU, with higher estimated regression coefficients for MUN for the NA data set. Precision of UN and UUN prediction improved substantially when only UN or UUN data based on total collection of urine were used. The relationship between UN and MUN for the NA data set, but not for the EU data set, was substantially altered when UN was calculated assuming a zero N balance instead of being based on the total collection of urine. According to results of the present meta-analysis, UN and UUN are best predicted by the combination of MUN and CP and that, in regard to precision and accuracy, prediction equations for UN and UUN should be derived from the total collection of urine. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Compilation of selected marine radioecological data for the US Subseabed Program: Summaries of available radioecological concentration factors and biological half-lives

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gomez, L.S.; Marietta, M.G.; Jackson, D.W.

1987-04-01

The US Subseabed Disposal Program has compiled an extensive concentration factor and biological half-life data base from the international marine radioecological literature. A microcomputer-based data management system has been implemented to provide statistical and graphic summaries of these data. The data base is constructed in a manner which allows subsets to be sorted using a number of interstudy variables such as organism category, tissue/organ category, geographic location (for in situ studies), and several laboratory-related conditions (e.g., exposure time and exposure concentration). This report updates earlier reviews and provides summaries of the tabulated data. In addition to the concentration factor/biological half-lifemore » data base, we provide an outline of other published marine radioecological works. Our goal is to present these data in a form that enables those concerned with predictive assessment of radiation dose in the marine environment to make a more judicious selection of data for a given application. 555 refs., 19 figs., 7 tabs.« less

Indoor source apportionment in urban communities near industrial sites

NASA Astrophysics Data System (ADS)

Tunno, Brett J.; Dalton, Rebecca; Cambal, Leah; Holguin, Fernando; Lioy, Paul; Clougherty, Jane E.

2016-08-01

Because fine particulate matter (PM2.5) differs in chemical composition, source apportionment is frequently used for identification of relative contributions of multiple sources to outdoor concentrations. Indoor air pollution and source apportionment is often overlooked, though people in northern climates may spend up to 90% of their time inside. We selected 21 homes for a 1-week indoor sampling session during summer (July to September 2011), repeated in winter (January to March 2012). Elemental analysis was performed using inductively-coupled plasma mass spectrometry (ICP-MS), and factor analysis was used to determine constituent grouping. Multivariate modeling was run on factor scores to corroborate interpretations of source factors based on a literature review. For each season, a 5-factor solution explained 86-88% of variability in constituent concentrations. Indoor sources (i.e. cooking, smoking) explained greater variability than did outdoor sources in these industrial communities. A smoking factor was identified in each season, predicted by number of cigarettes smoked. Cooking factors were also identified in each season, explained by frequency of stove cooking and stovetop frying. Significant contributions from outdoor sources including coal and motor vehicles were also identified. Higher coal and secondary-related elemental concentrations were detected during summer than winter. Our findings suggest that source contributions to indoor concentrations can be identified and should be examined in relation to health effects.

LaSVM-based big data learning system for dynamic prediction of air pollution in Tehran.

PubMed

Ghaemi, Z; Alimohammadi, A; Farnaghi, M

2018-04-20

Due to critical impacts of air pollution, prediction and monitoring of air quality in urban areas are important tasks. However, because of the dynamic nature and high spatio-temporal variability, prediction of the air pollutant concentrations is a complex spatio-temporal problem. Distribution of pollutant concentration is influenced by various factors such as the historical pollution data and weather conditions. Conventional methods such as the support vector machine (SVM) or artificial neural networks (ANN) show some deficiencies when huge amount of streaming data have to be analyzed for urban air pollution prediction. In order to overcome the limitations of the conventional methods and improve the performance of urban air pollution prediction in Tehran, a spatio-temporal system is designed using a LaSVM-based online algorithm. Pollutant concentration and meteorological data along with geographical parameters are continually fed to the developed online forecasting system. Performance of the system is evaluated by comparing the prediction results of the Air Quality Index (AQI) with those of a traditional SVM algorithm. Results show an outstanding increase of speed by the online algorithm while preserving the accuracy of the SVM classifier. Comparison of the hourly predictions for next coming 24 h, with those of the measured pollution data in Tehran pollution monitoring stations shows an overall accuracy of 0.71, root mean square error of 0.54 and coefficient of determination of 0.81. These results are indicators of the practical usefulness of the online algorithm for real-time spatial and temporal prediction of the urban air quality.

Selenium deficiency risk predicted to increase under future climate change

PubMed Central

Jones, Gerrad D.; Droz, Boris; Greve, Peter; Gottschalk, Pia; Poffet, Deyan; McGrath, Steve P.; Seneviratne, Sonia I.; Smith, Pete; Winkel, Lenny H. E.

2017-01-01

Deficiencies of micronutrients, including essential trace elements, affect up to 3 billion people worldwide. The dietary availability of trace elements is determined largely by their soil concentrations. Until now, the mechanisms governing soil concentrations have been evaluated in small-scale studies, which identify soil physicochemical properties as governing variables. However, global concentrations of trace elements and the factors controlling their distributions are virtually unknown. We used 33,241 soil data points to model recent (1980–1999) global distributions of Selenium (Se), an essential trace element that is required for humans. Worldwide, up to one in seven people have been estimated to have low dietary Se intake. Contrary to small-scale studies, soil Se concentrations were dominated by climate–soil interactions. Using moderate climate-change scenarios for 2080–2099, we predicted that changes in climate and soil organic carbon content will lead to overall decreased soil Se concentrations, particularly in agricultural areas; these decreases could increase the prevalence of Se deficiency. The importance of climate–soil interactions to Se distributions suggests that other trace elements with similar retention mechanisms will be similarly affected by climate change. PMID:28223487

Effect of Ocean Acidification on Organic and Inorganic Speciation of Trace Metals.

PubMed

Stockdale, Anthony; Tipping, Edward; Lofts, Stephen; Mortimer, Robert J G

2016-02-16

Rising concentrations of atmospheric carbon dioxide are causing acidification of the oceans. This results in changes to the concentrations of key chemical species such as hydroxide, carbonate and bicarbonate ions. These changes will affect the distribution of different forms of trace metals. Using IPCC data for pCO2 and pH under four future emissions scenarios (to the year 2100) we use a chemical speciation model to predict changes in the distribution of organic and inorganic forms of trace metals. Under a scenario where emissions peak after the year 2100, predicted free ion Al, Fe, Cu, and Pb concentrations increase by factors of up to approximately 21, 2.4, 1.5, and 2.0 respectively. Concentrations of organically complexed metal typically have a lower sensitivity to ocean acidification induced changes. Concentrations of organically complexed Mn, Cu, Zn, and Cd fall by up to 10%, while those of organically complexed Fe, Co, and Ni rise by up to 14%. Although modest, these changes may have significance for the biological availability of metals given the close adaptation of marine microorganisms to their environment.

Selenium deficiency risk predicted to increase under future climate change.

PubMed

Jones, Gerrad D; Droz, Boris; Greve, Peter; Gottschalk, Pia; Poffet, Deyan; McGrath, Steve P; Seneviratne, Sonia I; Smith, Pete; Winkel, Lenny H E

2017-03-14

Deficiencies of micronutrients, including essential trace elements, affect up to 3 billion people worldwide. The dietary availability of trace elements is determined largely by their soil concentrations. Until now, the mechanisms governing soil concentrations have been evaluated in small-scale studies, which identify soil physicochemical properties as governing variables. However, global concentrations of trace elements and the factors controlling their distributions are virtually unknown. We used 33,241 soil data points to model recent (1980-1999) global distributions of Selenium (Se), an essential trace element that is required for humans. Worldwide, up to one in seven people have been estimated to have low dietary Se intake. Contrary to small-scale studies, soil Se concentrations were dominated by climate-soil interactions. Using moderate climate-change scenarios for 2080-2099, we predicted that changes in climate and soil organic carbon content will lead to overall decreased soil Se concentrations, particularly in agricultural areas; these decreases could increase the prevalence of Se deficiency. The importance of climate-soil interactions to Se distributions suggests that other trace elements with similar retention mechanisms will be similarly affected by climate change.

Evaluation of serum trace mineral, vitamin D, and sex steroid hormone concentration, and survey data in llamas and alpacas with metacarpophalangeal and metatarsophalangeal hyperextension.

PubMed

Semevolos, Stacy A; Reed, Shannon K; Schultz, Loren G

2013-01-01

To characterize serum trace mineral, sex steroid hormone, and vitamin D concentrations and identify factors associated with metacarpophalangeal and metatarsophalangeal hyperextension in llamas and alpacas. Serum samples from 79 llamas and 15 alpacas and owner survey data for 573 llamas and 399 alpacas. Serum samples were stored at -20°C until analysis and were evaluated for trace mineral, vitamin D, estradiol, progesterone, and testosterone concentrations. Information regarding age of onset, number of affected animals in herd, feed and supplements given, type of housing, and management practices was obtained in an owner survey. Higher serum zinc and iron concentrations were associated with metacarpophalangeal and metatarsophalangeal hyperextension in camelids, compared with controls. In summer and fall months, vitamin D concentrations were significantly higher in affected camelids than controls. Overall prevalence was 13.3% in llamas, compared with 0.7% in alpacas. No management factors were found to be predictive of this condition. No other factors examined were associated with metacarpophalangeal and metatarsophalangeal hyperextension. Despite similar supplementation practices and environmental conditions between affected and unaffected animals, an association of high serum zinc, iron, and vitamin D concentrations in affected camelids, compared with controls, may indicate differences of intake or absorption of dietary supplements.

Glycated hemoglobin measurement and prediction of cardiovascular disease.

PubMed

Di Angelantonio, Emanuele; Gao, Pei; Khan, Hassan; Butterworth, Adam S; Wormser, David; Kaptoge, Stephen; Kondapally Seshasai, Sreenivasa Rao; Thompson, Alex; Sarwar, Nadeem; Willeit, Peter; Ridker, Paul M; Barr, Elizabeth L M; Khaw, Kay-Tee; Psaty, Bruce M; Brenner, Hermann; Balkau, Beverley; Dekker, Jacqueline M; Lawlor, Debbie A; Daimon, Makoto; Willeit, Johann; Njølstad, Inger; Nissinen, Aulikki; Brunner, Eric J; Kuller, Lewis H; Price, Jackie F; Sundström, Johan; Knuiman, Matthew W; Feskens, Edith J M; Verschuren, W M M; Wald, Nicholas; Bakker, Stephan J L; Whincup, Peter H; Ford, Ian; Goldbourt, Uri; Gómez-de-la-Cámara, Agustín; Gallacher, John; Simons, Leon A; Rosengren, Annika; Sutherland, Susan E; Björkelund, Cecilia; Blazer, Dan G; Wassertheil-Smoller, Sylvia; Onat, Altan; Marín Ibañez, Alejandro; Casiglia, Edoardo; Jukema, J Wouter; Simpson, Lara M; Giampaoli, Simona; Nordestgaard, Børge G; Selmer, Randi; Wennberg, Patrik; Kauhanen, Jussi; Salonen, Jukka T; Dankner, Rachel; Barrett-Connor, Elizabeth; Kavousi, Maryam; Gudnason, Vilmundur; Evans, Denis; Wallace, Robert B; Cushman, Mary; D'Agostino, Ralph B; Umans, Jason G; Kiyohara, Yutaka; Nakagawa, Hidaeki; Sato, Shinichi; Gillum, Richard F; Folsom, Aaron R; van der Schouw, Yvonne T; Moons, Karel G; Griffin, Simon J; Sattar, Naveed; Wareham, Nicholas J; Selvin, Elizabeth; Thompson, Simon G; Danesh, John

2014-03-26

The value of measuring levels of glycated hemoglobin (HbA1c) for the prediction of first cardiovascular events is uncertain. To determine whether adding information on HbA1c values to conventional cardiovascular risk factors is associated with improvement in prediction of cardiovascular disease (CVD) risk. Analysis of individual-participant data available from 73 prospective studies involving 294,998 participants without a known history of diabetes mellitus or CVD at the baseline assessment. Measures of risk discrimination for CVD outcomes (eg, C-index) and reclassification (eg, net reclassification improvement) of participants across predicted 10-year risk categories of low (<5%), intermediate (5% to <7.5%), and high (≥ 7.5%) risk. During a median follow-up of 9.9 (interquartile range, 7.6-13.2) years, 20,840 incident fatal and nonfatal CVD outcomes (13,237 coronary heart disease and 7603 stroke outcomes) were recorded. In analyses adjusted for several conventional cardiovascular risk factors, there was an approximately J-shaped association between HbA1c values and CVD risk. The association between HbA1c values and CVD risk changed only slightly after adjustment for total cholesterol and triglyceride concentrations or estimated glomerular filtration rate, but this association attenuated somewhat after adjustment for concentrations of high-density lipoprotein cholesterol and C-reactive protein. The C-index for a CVD risk prediction model containing conventional cardiovascular risk factors alone was 0.7434 (95% CI, 0.7350 to 0.7517). The addition of information on HbA1c was associated with a C-index change of 0.0018 (0.0003 to 0.0033) and a net reclassification improvement of 0.42 (-0.63 to 1.48) for the categories of predicted 10-year CVD risk. The improvement provided by HbA1c assessment in prediction of CVD risk was equal to or better than estimated improvements for measurement of fasting, random, or postload plasma glucose levels. In a study of individuals without known CVD or diabetes, additional assessment of HbA1c values in the context of CVD risk assessment provided little incremental benefit for prediction of CVD risk.

A mathematical model of reservoir sediment quality prediction based on land-use and erosion processes in watershed

NASA Astrophysics Data System (ADS)

Junakova, N.; Balintova, M.; Junak, J.

2017-10-01

The aim of this paper is to propose a mathematical model for determining of total nitrogen (N) and phosphorus (P) content in eroded soil particles with emphasis on prediction of bottom sediment quality in reservoirs. The adsorbed nutrient concentrations are calculated using the Universal Soil Loss Equation (USLE) extended by the determination of the average soil nutrient concentration in top soils. The average annual vegetation and management factor is divided into five periods of the cropping cycle. For selected plants, the average plant nutrient uptake divided into five cropping periods is also proposed. The average nutrient concentrations in eroded soil particles in adsorbed form are modified by sediment enrichment ratio to obtain the total nutrient content in transported soil particles. The model was designed for the conditions of north-eastern Slovakia. The study was carried out in the agricultural basin of the small water reservoir Klusov.

Propylene glycol accumulation in critically ill patients receiving continuous intravenous lorazepam infusions.

PubMed

Horinek, Erica L; Kiser, Tyree H; Fish, Douglas N; MacLaren, Robert

2009-12-01

Lorazepam is recommended by the Society of Critical Care Medicine as the preferred agent for sedation of critically ill patients. Intravenous lorazepam contains propylene glycol, which has been associated with toxicity when high doses of lorazepam are administered. To evaluate the accumulation of propylene glycol in critically ill patients receiving lorazepam by continuous infusion and determine factors associated with propylene glycol concentration. A 6-month, retrospective, safety assessment was conducted of adults admitted to the medical intensive care unit who were receiving lorazepam by continuous infusion for 12 hours or more. Propylene glycol serum concentrations were obtained 24-48 hours after continuous-infusion lorazepam was initiated and every 3-5 days thereafter. Propylene glycol accumulation was defined as concentrations of 25 mg/dL or more. Groups with and without propylene glycol accumulation were compared and factors associated with propylene glycol concentration were determined using multivariate correlation regression analyses. Forty-eight propylene glycol serum samples were obtained from 33 patients. Fourteen (42%) patients had propylene glycol accumulation, representing 23 (48%) serum samples. Univariate analyses showed the following factors were related to propylene glycol accumulation: baseline renal dysfunction, presence of alcohol withdrawal, sex, age, Acute Physiology and Chronic Health Evaluation (APACHE II) score, rate of lorazepam continuous infusion, and 24-hour lorazepam dose. Multivariate linear regression modeling demonstrated that propylene glycol concentration was strongly associated with the continuous infusion rate and 24-hour dose (adjusted r(2) > or = 0.77; p < 0.001). Independent correlation analyses showed that these 2 variables were so strongly associated with propylene glycol concentration (r(2) > or = 0.71; p < 0.001) that they alone predicted propylene glycol concentration. Seven (21%) patients developed renal dysfunction after continuous-infusion lorazepam was initiated, but associated causes were indeterminable. Other possible propylene glycol-associated adverse effects were not observed. The continuous infusion rate and cumulative 24-hour lorazepam dose are strongly associated with and independently predict propylene glycol concentrations. Despite the absence of confirmed propylene glycol-associated adverse effects, clinicians should be aware that propylene glycol accumulation may occur with continuous-infusion lorazepam.

Ratio of mean platelet volume to platelet count is a potential surrogate marker predicting liver cirrhosis.

PubMed

Iida, Hiroya; Kaibori, Masaki; Matsui, Kosuke; Ishizaki, Morihiko; Kon, Masanori

2018-01-27

To provide a simple surrogate marker predictive of liver cirrhosis (LC). Specimens from 302 patients who underwent resection for hepatocellular carcinoma between January 2006 and December 2012 were retrospectively analyzed. Based on pathologic findings, patients were divided into groups based on whether or not they had LC. Parameters associated with hepatic functional reserve were compared in these two groups using Mann-Whitney U -test for univariate analysis. Factors differing significantly in univariate analyses were entered into multivariate logistic regression analysis. There were significant differences between the LC group ( n = 100) and non-LC group ( n = 202) in prothrombin activity, concentrations of alanine aminotransferase, aspartate aminotransferase, total bilirubin, albumin, cholinesterase, type IV collagen, hyaluronic acid, indocyanine green retention rate at 15 min, maximal removal rate of technitium-99m diethylene triamine penta-acetic acid-galactosyl human serum albumin and ratio of mean platelet volume to platelet count (MPV/PLT). Multivariate analysis showed that prothrombin activity, concentrations of alanine aminotransferase, aspartate aminotransferase, total bilirubin and hyaluronic acid, and MPV/PLT ratio were factors independently predictive of LC. The area under the curve value for MPV/PLT was 0.78, with a 0.8 cutoff value having a sensitivity of 65% and a specificity of 78%. The MPV/PLT ratio, which can be determined simply from the complete blood count, may be a simple surrogate marker predicting LC.

Hydrogen production by the hyperthermophilic bacterium Thermotoga maritima Part II: modeling and experimental approaches for hydrogen production.

PubMed

Auria, Richard; Boileau, Céline; Davidson, Sylvain; Casalot, Laurence; Christen, Pierre; Liebgott, Pierre Pol; Combet-Blanc, Yannick

2016-01-01

Thermotoga maritima is a hyperthermophilic bacterium known to produce hydrogen from a large variety of substrates. The aim of the present study is to propose a mathematical model incorporating kinetics of growth, consumption of substrates, product formations, and inhibition by hydrogen in order to predict hydrogen production depending on defined culture conditions. Our mathematical model, incorporating data concerning growth, substrates, and products, was developed to predict hydrogen production from batch fermentations of the hyperthermophilic bacterium, T. maritima . It includes the inhibition by hydrogen and the liquid-to-gas mass transfer of H 2 , CO 2 , and H 2 S. Most kinetic parameters of the model were obtained from batch experiments without any fitting. The mathematical model is adequate for glucose, yeast extract, and thiosulfate concentrations ranging from 2.5 to 20 mmol/L, 0.2-0.5 g/L, or 0.01-0.06 mmol/L, respectively, corresponding to one of these compounds being the growth-limiting factor of T. maritima . When glucose, yeast extract, and thiosulfate concentrations are all higher than these ranges, the model overestimates all the variables. In the window of the model validity, predictions of the model show that the combination of both variables (increase in limiting factor concentration and in inlet gas stream) leads up to a twofold increase of the maximum H 2 -specific productivity with the lowest inhibition. A mathematical model predicting H 2 production in T. maritima was successfully designed and confirmed in this study. However, it shows the limit of validity of such mathematical models. Their limit of applicability must take into account the range of validity in which the parameters were established.

Risk assessment of human exposure to Ra-226 in oil produced water from the Bakken Shale.

PubMed

Torres, Luisa; Yadav, Om Prakash; Khan, Eakalak

2018-06-01

Unconventional oil production in North Dakota (ND) and other states in the United States uses large amounts of water for hydraulic fracturing to stimulate oil flow. Most of the water used returns to the surface as produced water (PW) containing different constituents. Some of these contents are total dissolved solids and radionuclides. The most predominant radionuclide in PW is radium-226 (Ra-226) of which level depends on several factors including the content of certain cations. A multivariate regression model was developed to predict Ra-226 in PW from the Bakken Shale based on the levels of barium, strontium, and calcium. The simulated Ra-226 activity concentration in PW was 535 pCi/L supporting extremely limited actual data based on three PW samples from the Bakken (527, 816, and 1210 pCi/L). The simulated activity concentration was further analyzed by studying its impact in the event of a PW spill reaching a surface water body that provides drinking water, irrigation water for crops, and recreational fishing. Using food transfer factors found in the literature, the final annual effective dose rate for an adult in ND was estimated. The global average annual effective dose rate via food and drinking water is 0.30 mSv, while the predicted dose rate in this study was 0.49 mSv indicating that there is potential risk to human health in ND due to Ra-226 in PW spills. This predicted dose rate is considered the best case scenario as it is based on the simulated Ra-226 activity concentration in PW of 535 pCi/L which is close to the low end actual activity concentration of 527 pCi/L. Copyright © 2018 Elsevier B.V. All rights reserved.

Left Ventricular Structure and Risk of Cardiovascular Events: A Framingham Heart Study Cardiac Magnetic Resonance Study

PubMed Central

Tsao, Connie W; Gona, Philimon N; Salton, Carol J; Chuang, Michael L; Levy, Daniel; Manning, Warren J; O’Donnell, Christopher J

2015-01-01

Background Elevated left ventricular mass index (LVMI) and concentric left ventricular (LV) remodeling are related to adverse cardiovascular disease (CVD) events. The predictive utility of LV concentric remodeling and LV mass in the prediction of CVD events is not well characterized. Methods and Results Framingham Heart Study Offspring Cohort members without prevalent CVD (n=1715, 50% men, aged 65±9 years) underwent cardiovascular magnetic resonance for LVMI and geometry (2002–2006) and were prospectively followed for incident CVD (myocardial infarction, coronary insufficiency, heart failure, stroke) or CVD death. Over 13 808 person-years of follow-up (median 8.4, range 0.0 to 10.5 years), 85 CVD events occurred. In multivariable-adjusted proportional hazards regression models, each 10-g/m2 increment in LVMI and each 0.1 unit in relative wall thickness was associated with 33% and 59% increased risk for CVD, respectively (P=0.004 and P=0.009, respectively). The association between LV mass/LV end-diastolic volume and incident CVD was borderline significant (P=0.053). Multivariable-adjusted risk reclassification models showed a modest improvement in CVD risk prediction with the incorporation of cardiovascular magnetic resonance LVMI and measures of LV concentricity (C-statistic 0.71 [95% CI 0.65 to 0.78] for the model with traditional risk factors only, improved to 0.74 [95% CI 0.68 to 0.80] for the risk factor model additionally including LVMI and relative wall thickness). Conclusions Among adults free of prevalent CVD in the community, greater LVMI and LV concentric hypertrophy are associated with a marked increase in adverse incident CVD events. The potential benefit of aggressive primary prevention to modify LV mass and geometry in these adults requires further investigation. PMID:26374295

Magnetic Barkhausen noise indications of stress concentrations near pits of various depths

NASA Astrophysics Data System (ADS)

Mandal, K.; Loukas, M. E.; Corey, A.; Atherton, D. L.

1997-11-01

The presence of a defect in a material under stress, changes the local stress distribution around it. This local stress distributions around three circular pits in line pipe steel with depths of 30, 50 and 80% wall thickness were studied nondestructively by magnetic Barkhausen noise measurements and in the presence of different bending stresses. The results show stress concentration factors ˜ 1.5, 1.7 and 2.05, respectively, and are consistent with theoretical predictions.

Optimization and formulation design of gels of Diclofenac and Curcumin for transdermal drug delivery by Box-Behnken statistical design.

PubMed

Chaudhary, Hema; Kohli, Kanchan; Amin, Saima; Rathee, Permender; Kumar, Vikash

2011-02-01

The aim of this study was to develop and optimize a transdermal gel formulation for Diclofenac diethylamine (DDEA) and Curcumin (CRM). A 3-factor, 3-level Box-Behnken design was used to derive a second-order polynomial equation to construct contour plots for prediction of responses. Independent variables studied were the polymer concentration (X(1)), ethanol (X(2)) and propylene glycol (X(3)) and the levels of each factor were low, medium, and high. The dependent variables studied were the skin permeation rate of DDEA (Y(1)), skin permeation rate of CRM (Y(2)), and viscosity of the gels (Y(3)). Response surface plots were drawn, statistical validity of the polynomials was established to find the compositions of optimized formulation which was evaluated using the Franz-type diffusion cell. The permeation rate of DDEA increased proportionally with ethanol concentration but decreased with polymer concentration, whereas the permeation rate of CRM increased proportionally with polymer concentration. Gels showed a non-Fickian super case II (typical zero order) and non-Fickian diffusion release mechanism for DDEA and CRM, respectively. The design demonstrated the role of the derived polynomial equation and contour plots in predicting the values of dependent variables for the preparation and optimization of gel formulation for transdermal drug release. Copyright © 2010 Wiley-Liss, Inc.

Upstream factors affecting Tualatin River algae—Tracking the 2008 Anabaena algae bloom to Wapato Lake, Oregon

USGS Publications Warehouse

Rounds, Stewart A.; Carpenter, Kurt D.; Fesler, Kristel J.; Dorsey, Jessica L.

2015-12-17

The results and insights derived from this study can be used to enhance future monitoring and data collection strategies designed to improve water quality and plankton models and better predict dissolved-oxygen concentrations in the lower Tualatin River.

Runoff as a factor in USLE/RUSLE technology

NASA Astrophysics Data System (ADS)

Kinnell, Peter

2014-05-01

Modelling erosion for prediction purposes started with the development of the Universal Soil Loss Equation the focus of which was the prediction of long term (~20) average annul soil loss from field sized areas. That purpose has been maintained in the subsequent revision RUSLE, the most widely used erosion prediction model in the world. The lack of ability to predict short term soil loss saw the development of so-called process based models like WEPP and EUROSEM which focussed on predicting event erosion but failed to improve the prediction of long term erosion where the RUSLE worked well. One of the features of erosion recognised in the so-called process based modes is the fact that runoff is a primary factor in rainfall erosion and some modifications of USLE/RUSLE model have been proposed have included runoff as in independent factor in determining event erosivity. However, these models have ignored fundamental mathematical rules. The USLE-M which replaces the EI30 index by the product of the runoff ratio and EI30 was developed from the concept that soil loss is the product of runoff and sediment concentration and operates in a way that obeys the mathematical rules upon which the USLE/RUSLE model was based. In accounts for event soil loss better that the EI30 index where runoff values are known or predicted adequately. RUSLE2 now includes a capacity to model runoff driven erosion.

Identifying Environmental Risk Factors of Cholera in a Coastal Area with Geospatial Technologies

PubMed Central

Xu, Min; Cao, Chunxiang; Wang, Duochun; Kan, Biao

2014-01-01

Satellites contribute significantly to environmental quality and public health. Environmental factors are important indicators for the prediction of disease outbreaks. This study reveals the environmental factors associated with cholera in Zhejiang, a coastal province of China, using both Remote Sensing (RS) and Geographic information System (GIS). The analysis validated the correlation between the indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local cholera magnitude based on a ten-year monthly data from the year 1999 to 2008. Cholera magnitude has been strongly affected by the concurrent variables of SST and SSH, while OCC has a one-month time lag effect. A cholera prediction model has been established based on the sea environmental factors. The results of hot spot analysis showed the local cholera magnitude in counties significantly associated with the estuaries and rivers. PMID:25551518

Identifying environmental risk factors of cholera in a coastal area with geospatial technologies.

PubMed

Xu, Min; Cao, Chunxiang; Wang, Duochun; Kan, Biao

2014-12-29

Satellites contribute significantly to environmental quality and public health. Environmental factors are important indicators for the prediction of disease outbreaks. This study reveals the environmental factors associated with cholera in Zhejiang, a coastal province of China, using both Remote Sensing (RS) and Geographic information System (GIS). The analysis validated the correlation between the indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local cholera magnitude based on a ten-year monthly data from the year 1999 to 2008. Cholera magnitude has been strongly affected by the concurrent variables of SST and SSH, while OCC has a one-month time lag effect. A cholera prediction model has been established based on the sea environmental factors. The results of hot spot analysis showed the local cholera magnitude in counties significantly associated with the estuaries and rivers.

Spatiotemporal patterns of evapotranspiration in response to multiple environmental factors simulated by the Community Land Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shi, Xiaoying; Mao, Jiafu; Thornton, Peter E

In this study, spatial and temporal patterns of evapotranspiration (ET) over the period of 1982-2008 are investigated and attributed to multiple environmental factors using the Community Land Model version 4 (CLM4). Our results show that CLM4 captures the spatial distribution and interannual variability of ET well when compared to observation-based estimates derived from the FLUXNET network of eddy covariance towers using the model tree ensembles (MTE) approach. We find that climate trends and variability dominate predicted variability in ET. Elevated atmospheric CO2 concentration also plays an important role in modulating the trend of predicted ET over most land areas, andmore » functions as the dominant factor controlling ET changes over North America, South America and Asia regions. Compared to the effect of climate change and CO2 concentration, the roles of other factors such as nitrogen deposition, land use change and aerosol deposition are less pronounced and regionally dependent. For example, the aerosol deposition contribution is the third-most important factor for trends of ET over Europe, while it has the smallest impact on ET trend over other regions. As ET is a dominant component of the terrestrial water cycle, our results suggest that environmental factors like elevated CO2, nitrogen and aerosol depositions, and land use and land cover change, in addition to climate, could have significant impact on future projections of water resources and water cycle dynamics at global and regional scales.« less

Evaluation of the effect of temperature, NaOH concentration and time on solubilization of palm oil mill effluent (POME) using response surface methodology (RSM).

PubMed

Chou, K W; Norli, I; Anees, A

2010-11-01

In this study, palm oil mill effluent (POME) was solubilized by batch thermo-alkaline pre-treatments. A three-factor central composite design (CCD) was applied to identify the optimum COD solubilization condition. The individual and interactive effects of three factors, temperature, NaOH concentration and reaction time, on solubilization of POME were evaluated by employing response surface methodology (RSM). The experimental results showed that temperature, NaOH concentration and reaction time all had an individual significant effect on the solubilization of POME. But these three factors were independent, or there was insignificant interaction on the response. The maximum COD solubilization of 82.63% was estimated under the optimum condition at 32.5 degrees C, 8.83g/L of NaOH and 41.23h reaction time. The confirmation experiment of the predicted optimum conditions verified that the RSM with the central composite design was useful for optimizing the solubilization of POME.

Simulation of nitrate, sulfate, and ammonium aerosols over the United States

NASA Astrophysics Data System (ADS)

Walker, J. M.; Philip, S.; Martin, R. V.; Seinfeld, J. H.

2012-11-01

Atmospheric concentrations of inorganic gases and aerosols (nitrate, sulfate, and ammonium) are simulated for 2009 over the United States using the chemical transport model GEOS-Chem. Predicted aerosol concentrations are compared with surface-level measurement data from the Interagency Monitoring of Protected Visual Environments (IMPROVE), the Clean Air Status and Trends Network (CASTNET), and the California Air Resources Board (CARB). Sulfate predictions nationwide are in reasonably good agreement with observations, while nitrate and ammonium are over-predicted in the East and Midwest, but under-predicted in California, where observed concentrations are the highest in the country. Over-prediction of nitrate in the East and Midwest is consistent with results of recent studies, which suggest that nighttime nitric acid formation by heterogeneous hydrolysis of N2O5 is over-predicted based on current values of the N2O5 uptake coefficient, γ, onto aerosols. After reducing the value of γ by a factor of 10, predicted nitrate levels in the US Midwest and East still remain higher than those measured, and over-prediction of nitrate in this region remains unexplained. Comparison of model predictions with satellite measurements of ammonia from the Tropospheric Emissions Spectrometer (TES) indicates that ammonia emissions in GEOS-Chem are underestimated in California and that the nationwide seasonality applied to ammonia emissions in GEOS-Chem does not represent California very well, particularly underestimating winter emissions. An ammonia sensitivity study indicates that GEOS-Chem simulation of nitrate is ammonia-limited in southern California and much of the state, suggesting that an underestimate of ammonia emissions is likely the main cause for the under-prediction of nitrate aerosol in many areas of California. An approximate doubling of ammonia emissions is needed to reproduce observed nitrate concentrations in southern California and in other ammonia sensitive areas of California. However, even a tenfold increase in ammonia emissions yields predicted nitrate concentrations that are still biased low in the central valley of California. The under-prediction of nitrate aerosol in the central valley of California may arise in part from an under-prediction of both ammonia and nitric acid in this region. Since nitrate aerosols are particularly sensitive to mixed layer depths, owing to the gas-particle equilibrium, the nitrate under-prediction could also arise in part from a potential regional overestimate of GEOS-5 mixed layer depths in the central valley due to unresolved topography in this region.

Concentrations of antibiotics predicted to select for resistant bacteria: Proposed limits for environmental regulation.

PubMed

Bengtsson-Palme, Johan; Larsson, D G Joakim

2016-01-01

There are concerns that selection pressure from antibiotics in the environment may accelerate the evolution and dissemination of antibiotic-resistant pathogens. Nevertheless, there is currently no regulatory system that takes such risks into account. In part, this is due to limited knowledge of environmental concentrations that might exert selection for resistant bacteria. To experimentally determine minimal selective concentrations in complex microbial ecosystems for all antibiotics would involve considerable effort. In this work, our aim was to estimate upper boundaries for selective concentrations for all common antibiotics, based on the assumption that selective concentrations a priori need to be lower than those completely inhibiting growth. Data on Minimal Inhibitory Concentrations (MICs) were obtained for 111 antibiotics from the public EUCAST database. The 1% lowest observed MICs were identified, and to compensate for limited species coverage, predicted lowest MICs adjusted for the number of tested species were extrapolated through modeling. Predicted No Effect Concentrations (PNECs) for resistance selection were then assessed using an assessment factor of 10 to account for differences between MICs and minimal selective concentrations. The resulting PNECs ranged from 8 ng/L to 64 μg/L. Furthermore, the link between taxonomic similarity between species and lowest MIC was weak. This work provides estimated upper boundaries for selective concentrations (lowest MICs) and PNECs for resistance selection for all common antibiotics. In most cases, PNECs for selection of resistance were below available PNECs for ecotoxicological effects. The generated PNECs can guide implementation of compound-specific emission limits that take into account risks for resistance promotion. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Key Clinical Factors Predicting Adipokine and Oxidative Stress Marker Concentrations among Normal, Overweight and Obese Pregnant Women Using Artificial Neural Networks.

PubMed

Solis-Paredes, Mario; Estrada-Gutierrez, Guadalupe; Perichart-Perera, Otilia; Montoya-Estrada, Araceli; Guzmán-Huerta, Mario; Borboa-Olivares, Héctor; Bravo-Flores, Eyerahi; Cardona-Pérez, Arturo; Zaga-Clavellina, Veronica; Garcia-Latorre, Ethel; Gonzalez-Perez, Gabriela; Hernández-Pérez, José Alfredo; Irles, Claudine

2017-12-28

Maternal obesity has been related to adverse neonatal outcomes and fetal programming. Oxidative stress and adipokines are potential biomarkers in such pregnancies; thus, the measurement of these molecules has been considered critical. Therefore, we developed artificial neural network (ANN) models based on maternal weight status and clinical data to predict reliable maternal blood concentrations of these biomarkers at the end of pregnancy. Adipokines (adiponectin, leptin, and resistin), and DNA, lipid and protein oxidative markers (8-oxo-2'-deoxyguanosine, malondialdehyde and carbonylated proteins, respectively) were assessed in blood of normal weight, overweight and obese women in the third trimester of pregnancy. A Back-propagation algorithm was used to train ANN models with four input variables (age, pre-gestational body mass index (p-BMI), weight status and gestational age). ANN models were able to accurately predict all biomarkers with regression coefficients greater than R² = 0.945. P-BMI was the most significant variable for estimating adiponectin and carbonylated proteins concentrations (37%), while gestational age was the most relevant variable to predict resistin and malondialdehyde (34%). Age, gestational age and p-BMI had the same significance for leptin values. Finally, for 8-oxo-2'-deoxyguanosine prediction, the most significant variable was age (37%). These models become relevant to improve clinical and nutrition interventions in prenatal care.

Influence of physical and chemical properties of HTSXT-FTIR samples on the quality of prediction models developed to determine absolute concentrations of total proteins, carbohydrates and triglycerides: a preliminary study on the determination of their absolute concentrations in fresh microalgal biomass.

PubMed

Serrano León, Esteban; Coat, Rémy; Moutel, Benjamin; Pruvost, Jérémy; Legrand, Jack; Gonçalves, Olivier

2014-11-01

Absolute concentrations of total macromolecules (triglycerides, proteins and carbohydrates) in microorganisms can be rapidly measured by FTIR spectroscopy, but caution is needed to avoid non-specific experimental bias. Here, we assess the limits within which this approach can be used on model solutions of macromolecules of interest. We used the Bruker HTSXT-FTIR system. Our results show that the solid deposits obtained after the sampling procedure present physical and chemical properties that influence the quality of the absolute concentration prediction models (univariate and multivariate). The accuracy of the models was degraded by a factor of 2 or 3 outside the recommended concentration interval of 0.5-35 µg spot(-1). Change occurred notably in the sample hydrogen bond network, which could, however, be controlled using an internal probe (pseudohalide anion). We also demonstrate that for aqueous solutions, accurate prediction of total carbohydrate quantities (in glucose equivalent) could not be made unless a constant amount of protein was added to the model solution (BSA). The results of the prediction model for more complex solutions, here with two components: glucose and BSA, were very encouraging, suggesting that this FTIR approach could be used as a rapid quantification method for mixtures of molecules of interest, provided the limits of use of the HTSXT-FTIR method are precisely known and respected. This last finding opens the way to direct quantification of total molecules of interest in more complex matrices.

Cytochrome P450 and ABCB1 genetics: association with quetiapine and norquetiapine plasma and cerebrospinal fluid concentrations and with clinical response in patients suffering from schizophrenia. A pilot study.

PubMed

Nikisch, Georg; Baumann, Pierre; Oneda, Beatrice; Kiessling, Bernhard; Weisser, Heike; Mathé, Aleksander A; Yoshitake, Takashi; Kehr, Jan; Wiedemann, Georg; Eap, Chin B

2011-07-01

Variability in response to atypical antipsychotic drugs is due to genetic and environmental factors. Cytochrome P450 (CYP) isoforms are implicated in the metabolism of drugs, while the P-glycoprotein transporter (P-gp), encoded by the ABCB1 gene, may influence both the blood and brain drug concentrations. This study aimed to identify the possible associations of CYP and ABCB1 genetic polymorphisms with quetiapine and norquetiapine plasma and cerebrospinal fluid (CSF) concentrations and with response to treatment. Twenty-two patients with schizophrenia receiving 600 mg of quetiapine daily were genotyped for four CYP isoforms and ABCB1 polymorphisms. Quetiapine and norquetiapine peak plasma and CSF concentrations were measured after 4 weeks of treatment. Stepwise multiple regression analysis revealed that ABCB1 3435C > T (rs1045642), 2677G > T (rs2032582) and 1236C > T (rs1128503) polymorphisms predicted plasma quetiapine concentrations, explaining 41% of the variability (p = 0.001). Furthermore, the ABCB1 polymorphisms predicted 48% (p = 0.024) of the variability of the Δ PANSS total score, with the non-carriers of the 3435TT showing higher changes in the score. These results suggest that ABCB1 genetic polymorphisms may be a predictive marker of quetiapine treatment in schizophrenia.

Hazard Ranking Method for Populations Exposed to Arsenic in Private Water Supplies: Relation to Bedrock Geology.

PubMed

Crabbe, Helen; Fletcher, Tony; Close, Rebecca; Watts, Michael J; Ander, E Louise; Smedley, Pauline L; Verlander, Neville Q; Gregory, Martin; Middleton, Daniel R S; Polya, David A; Studden, Mike; Leonardi, Giovanni S

2017-12-01

Approximately one million people in the UK are served by private water supplies (PWS) where main municipal water supply system connection is not practical or where PWS is the preferred option. Chronic exposure to contaminants in PWS may have adverse effects on health. South West England is an area with elevated arsenic concentrations in groundwater and over 9000 domestic dwellings here are supplied by PWS. There remains uncertainty as to the extent of the population exposed to arsenic (As), and the factors predicting such exposure. We describe a hazard assessment model based on simplified geology with the potential to predict exposure to As in PWS. Households with a recorded PWS in Cornwall were recruited to take part in a water sampling programme from 2011 to 2013. Bedrock geologies were aggregated and classified into nine Simplified Bedrock Geological Categories (SBGC), plus a cross-cutting "mineralized" area. PWS were sampled by random selection within SBGCs and some 508 households volunteered for the study. Transformations of the data were explored to estimate the distribution of As concentrations for PWS by SBGC. Using the distribution per SBGC, we predict the proportion of dwellings that would be affected by high concentrations and rank the geologies according to hazard. Within most SBGCs, As concentrations were found to have log-normal distributions. Across these areas, the proportion of dwellings predicted to have drinking water over the prescribed concentration value (PCV) for As ranged from 0% to 20%. From these results, a pilot predictive model was developed calculating the proportion of PWS above the PCV for As and hazard ranking supports local decision making and prioritization. With further development and testing, this can help local authorities predict the number of dwellings that might fail the PCV for As, based on bedrock geology. The model presented here for Cornwall could be applied in areas with similar geologies. Application of the method requires independent validation and further groundwater-derived PWS sampling on other geological formations.

Bayesian Forecasting Tool to Predict the Need for Antidote in Acute Acetaminophen Overdose.

PubMed

Desrochers, Julie; Wojciechowski, Jessica; Klein-Schwartz, Wendy; Gobburu, Jogarao V S; Gopalakrishnan, Mathangi

2017-08-01

Acetaminophen (APAP) overdose is the leading cause of acute liver injury in the United States. Patients with elevated plasma acetaminophen concentrations (PACs) require hepatoprotective treatment with N-acetylcysteine (NAC). These patients have been primarily risk-stratified using the Rumack-Matthew nomogram. Previous studies of acute APAP overdoses found that the nomogram failed to accurately predict the need for the antidote. The objectives of this study were to develop a population pharmacokinetic (PK) model for APAP following acute overdose and evaluate the utility of population PK model-based Bayesian forecasting in NAC administration decisions. Limited APAP concentrations from a retrospective cohort of acute overdosed subjects from the Maryland Poison Center were used to develop the population PK model and to investigate the effect of type of APAP products and other prognostic factors. The externally validated population PK model was used a prior for Bayesian forecasting to predict the individual PK profile when one or two observed PACs were available. The utility of Bayesian forecasted APAP concentration-time profiles inferred from one (first) or two (first and second) PAC observations were also tested in their ability to predict the observed NAC decisions. A one-compartment model with first-order absorption and elimination adequately described the data with single activated charcoal and APAP products as significant covariates on absorption and bioavailability. The Bayesian forecasted individual concentration-time profiles had acceptable bias (6.2% and 9.8%) and accuracy (40.5% and 41.9%) when either one or two PACs were considered, respectively. The sensitivity and negative predictive value of the Bayesian forecasted NAC decisions using one PAC were 84% and 92.6%, respectively. The population PK analysis provided a platform for acceptably predicting an individual's concentration-time profile following acute APAP overdose with at least one PAC, and the individual's covariate profile, and can potentially be used for making early NAC administration decisions. © 2017 Pharmacotherapy Publications, Inc.

Genetic and epigenetic transgenerational implications related to omega-3 fatty acids. Part I: maternal FADS2 genotype and DNA methylation correlate with polyunsaturated fatty acid status in toddlers: an exploratory analysis.

PubMed

Lupu, Daniel S; Cheatham, Carol L; Corbin, Karen D; Niculescu, Mihai D

2015-11-01

Polyunsaturated fatty acid metabolism in toddlers is regulated by a complex network of interacting factors. The contribution of maternal genetic and epigenetic makeup to this milieu is not well understood. In a cohort of mothers and toddlers 16 months of age (n = 65 mother-child pairs), we investigated the association between maternal genetic and epigenetic fatty acid desaturase 2 (FADS2) profiles and toddlers' n-6 and n-3 fatty acid metabolism. FADS2 rs174575 variation and DNA methylation status were interrogated in mothers and toddlers, as well as food intake and plasma fatty acid concentrations in toddlers. A multivariate fit model indicated that maternal rs174575 genotype, combined with DNA methylation, can predict α-linolenic acid plasma concentration in all toddlers and arachidonic acid concentrations in boys. Arachidonic acid intake was predictive for its plasma concentration in girls, whereas intake of 3 major n-3 species (eicosapentaenoic, docosapentaenoic, and docosahexaenoic acids) were predictive for their plasma concentrations in boys. FADS2 genotype and DNA methylation in toddlers were not related to plasma concentrations or food intakes, except for CpG8 methylation. Maternal FADS2 methylation was a predictor for the boys' α-linolenic acid intakes. This exploratory study suggests that maternal FADS2 genetic and epigenetic status could be related to toddlers' polyunsaturated fatty acid metabolism. Copyright © 2015 Elsevier Inc. All rights reserved.

An evaluation of NASA's program in human factors research: Aircrew-vehicle system interaction

NASA Technical Reports Server (NTRS)

1982-01-01

Research in human factors in the aircraft cockpit and a proposed program augmentation were reviewed. The dramatic growth of microprocessor technology makes it entirely feasible to automate increasingly more functions in the aircraft cockpit; the promise of improved vehicle performance, efficiency, and safety through automation makes highly automated flight inevitable. An organized data base and validated methodology for predicting the effects of automation on human performance and thus on safety are lacking and without such a data base and validated methodology for analyzing human performance, increased automation may introduce new risks. Efforts should be concentrated on developing methods and techniques for analyzing man machine interactions, including human workload and prediction of performance.

High quality factor graphene varactors for wireless sensing applications

NASA Astrophysics Data System (ADS)

Koester, Steven J.

2011-10-01

A graphene wireless sensor concept is described. By utilizing thin gate dielectrics, the capacitance in a metal-insulator-graphene structure varies with charge concentration through the quantum capacitance effect. Simulations using realistic structural and transport parameters predict quality factors, Q, >60 at 1 GHz. When placed in series with an ideal inductor, a resonant frequency tuning ratio of 25% (54%) is predicted for sense charge densities ranging from 0.32 to 1.6 μC/cm2 at an equivalent oxide thickness of 2.0 nm (0.5 nm). The resonant frequency has a temperature sensitivity, df/dT, less than 0.025%/K for sense charge densities >0.32 μC/cm2.

Measuring Anti–Factor Xa Activity to Monitor Low-Molecular-Weight Heparin in Obesity: A Critical Review

PubMed Central

Egan, Gregory; Ensom, Mary H H

2015-01-01

Background: The choice of whether to monitor anti–factor Xa (anti-Xa) activity in patients who are obese and who are receiving low-molecular-weight heparin (LMWH) therapy is controversial. To the authors’ knowledge, no systematic review of monitoring of anti-Xa activity in such patients has been published to date. Objective: To systematically ascertain the utility of monitoring anti-Xa concentrations for LMWH therapy in obese patients. Data Sources: MEDLINE (1946 to September 2014), the Cochrane Database of Systematic Reviews, Embase (1974 to September 2014), PubMed (1947 to September 2014), International Pharmaceutical Abstracts (1970 to September 2014), and Scopus were searched using the terms obesity, morbid obesity, thrombosis, venous thrombosis, embolism, venous thromboembolism, pulmonary embolism, low-molecular weight heparin, enoxaparin, dalteparin, tinzaparin, anti-factor Xa, anti-factor Xa monitoring, anti-factor Xa activity, and anti-factor Xa assay. The reference lists of retrieved articles were also reviewed. Study Selection and Data Extraction: English-language studies describing obese patients treated with LMWH or reporting anti-Xa activity were reviewed using a 9-step decision-making algorithm to determine whether monitoring of LMWH therapy by means of anti-Xa activity in obesity is warranted. Studies published in abstract form were excluded. Data Synthesis: The analysis showed that anti-Xa concentrations are not strongly associated with thrombosis or hemorrhage. In clinical studies of LMWH for thromboprophylaxis in bariatric surgery, orthopedic surgery, general surgery, and medical patients, and for treatment of venous thrombo embolism and acute coronary syndrome, anti-Xa activity can be predicted from dose of LMWH and total body weight; no difference in clinical outcome was found between obese and non-obese participants. Conclusions: Routinely determining anti-Xa concentrations in obese patients to monitor the clinical effectiveness of LMWH is not warranted on the basis of the current evidence. Circumstances where measurement of anti-Xa concentration may help in clinical decision-making in either obese or non-obese patients would be cases where elimination of LMWH is impaired or there is an unexpected clinical response, as well as to confirm compliance with therapy or to identify deviation from predicted pharmacokinetics. PMID:25762818

Factors affecting Escherichia coli concentrations at Lake Erie public bathing beaches

USGS Publications Warehouse

Francy, Donna S.; Darner, Robert A.

1998-01-01

The environmental and water-quality factors that affect concentrations of Escherichia coli (E. coli) in water and sediment were investigated at three public bathing beachesEdgewater Park, Villa Angela, and Sims Parkin the Cleveland, Ohio metropolitan area. This study was done to aid in the determination of safe recreational use and to help water- resource managers assess more quickly and accurately the degradation of recreational water quality. Water and lake-bottom sediments were collected and ancillary environmental data were compiled for 41 days from May through September 1997. Water samples were analyzed for E. coli concentrations, suspended sediment concentrations, and turbidity. Lake- bottom sediment samples from the beach area were analyzed for E. coli concentrations and percent dry weight. Concentrations of E. coli were higher and more variable at Sims Park than at Villa Angela or Edgewater Park; concentrations were lowest at Edgewater Park. Time-series plots showed that short-term storage (less than one week) of E. coli in lake-bottom sediments may have occurred, although no evidence for long-term storage was found during the sampling period. E. coli concentrations in water were found to increase with increasing wave height, but the resuspension of E. coli from lake-bottom sediments by wave action could not be adequately assessed; higherwave heights were often associated with the discharge of sewage containing E. coli during or after a rainfall and wastewater-treatment plant overflow. Multiple linear regression (MLR) was used to develop models to predict recreational water quality at the in water. The related variables included turbidity, antecedent rainfall, antecedent weighted rainfall, volumes of wastewater-treatment plant overflows and metered outfalls (composed of storm-water runoff and combined-sewer overflows), a resuspension index, and wave heights. For the beaches in this study, wind speed, wind direction, water temperature, and the prswimmers were not included in the model because they were shown to be statistically unrelated to E. coli concentrations. From the several models developed, one model was chosen that accounted for 58 percent of the variability in E. coli concentrations. The chosen MLR model contained weighted categorical rainfall, beach-specific turbidity, wave height, and terms to correct for the different magnitudes of E. coli concentrations among the three beaches. For 1997, the MLR model predicted the recreational water quality as well as, and in some cases better than, antecedent E. coli concentrations (the current method). The MLR model improved the sensitivity of the prediction and the percentage of correct predictions over the current method; however, the MLR model predictions still erred to a similar degree as the current method with regard to false negatives. A false negative would allow swimming when, in fact, the bathing water standard was exceeded. More work needs to be done to validate the MLR model with data collected during other recreational seasons, especially during a season with a greater frequency and intensity of summer rains. Studies could focus on adding to the MLR model other environmental and water-quality variables that improve the predictive ability of the model. These variables might include concentrations of E. coli in deeper sediments outside the bathing area, the direction of lake currents, site-specific-rainfall amounts, time-of-day information on overflows and metered outfalls, concentrations of E. coli in treated wastewater-treatment plant effluents, and occurrences of sewage-line breaks. Rapid biological or chemical methods for determination of recreational water quality could also be used as variables in model refinements. Possible methods include the use of experimental rapid assay methods for determination of E. coli concentrations or other fecal indicators and the use of chemical tracers for fecal contamination, such as coprostanol (a degradation

KABAM Version 1.0 User's Guide and Technical Documentation - Appendix F -Description of Equations Used to Calculate the BCF, BAF, BMF, and BSAF Values

EPA Pesticide Factsheets

Describes equations for bioconcentration, bioaccumulation, biomagnification and biota-sediment accumulation factors used in KABAM V1.0. KABAM is a simulation model used to predict pesticide concentrations in aquatic regions for use in exposure assessments.

Using High Frequency Monitoring of Environmental Factors to Predict Microcystin Concentrations in a Multi-use, Inland Reservoir

EPA Science Inventory

Cyanobacteria, known as blue-green algae, are photosynthetic bacteria found naturally in marine, freshwater, and estuarine ecosystems. An increase in nutrient input and changes in the climate have contributed to the proliferation of cyanobacteria, forming harmful algal blooms, or...

Additive mixture effects of estrogenic chemicals in human cell-based assays can be influenced by inclusion of chemicals with differing effect profiles.

PubMed

Evans, Richard Mark; Scholze, Martin; Kortenkamp, Andreas

2012-01-01

A growing body of experimental evidence indicates that the in vitro effects of mixtures of estrogenic chemicals can be well predicted from the estrogenicity of their components by the concentration addition (CA) concept. However, some studies have observed small deviations from CA. Factors affecting the presence or observation of deviations could include: the type of chemical tested; number of mixture components; mixture design; and assay choice. We designed mixture experiments that address these factors, using mixtures with high numbers of components, chemicals from diverse chemical groups, assays with different in vitro endpoints and different mixture designs and ratios. Firstly, the effects of mixtures composed of up to 17 estrogenic chemicals were examined using estrogenicity assays with reporter-gene (ERLUX) and cell proliferation (ESCREEN) endpoints. Two mixture designs were used: 1) a 'balanced' design with components present in proportion to a common effect concentration (e.g. an EC(10)) and 2) a 'non-balanced' design with components in proportion to potential human tissue concentrations. Secondly, the individual and simultaneous ability of 16 potential modulator chemicals (each with minimal estrogenicity) to influence the assay outcome produced by a reference mixture of estrogenic chemicals was examined. Test chemicals included plasticizers, phthalates, metals, PCBs, phytoestrogens, PAHs, heterocyclic amines, antioxidants, UV filters, musks, PBDEs and parabens. In all the scenarios tested, the CA concept provided a good prediction of mixture effects. Modulation studies revealed that chemicals possessing minimal estrogenicity themselves could reduce (negatively modulate) the effect of a mixture of estrogenic chemicals. Whether the type of modulation we observed occurs in practice most likely depends on the chemical concentrations involved, and better information is required on likely human tissue concentrations of estrogens and of potential modulators. Successful prediction of the effects of diverse chemical combinations might be more likely if chemical profiling included consideration of effect modulation.

Additive Mixture Effects of Estrogenic Chemicals in Human Cell-Based Assays Can Be Influenced by Inclusion of Chemicals with Differing Effect Profiles

PubMed Central

Evans, Richard Mark; Scholze, Martin; Kortenkamp, Andreas

2012-01-01

A growing body of experimental evidence indicates that the in vitro effects of mixtures of estrogenic chemicals can be well predicted from the estrogenicity of their components by the concentration addition (CA) concept. However, some studies have observed small deviations from CA. Factors affecting the presence or observation of deviations could include: the type of chemical tested; number of mixture components; mixture design; and assay choice. We designed mixture experiments that address these factors, using mixtures with high numbers of components, chemicals from diverse chemical groups, assays with different in vitro endpoints and different mixture designs and ratios. Firstly, the effects of mixtures composed of up to 17 estrogenic chemicals were examined using estrogenicity assays with reporter-gene (ERLUX) and cell proliferation (ESCREEN) endpoints. Two mixture designs were used: 1) a ‘balanced’ design with components present in proportion to a common effect concentration (e.g. an EC10) and 2) a ‘non-balanced’ design with components in proportion to potential human tissue concentrations. Secondly, the individual and simultaneous ability of 16 potential modulator chemicals (each with minimal estrogenicity) to influence the assay outcome produced by a reference mixture of estrogenic chemicals was examined. Test chemicals included plasticizers, phthalates, metals, PCBs, phytoestrogens, PAHs, heterocyclic amines, antioxidants, UV filters, musks, PBDEs and parabens. In all the scenarios tested, the CA concept provided a good prediction of mixture effects. Modulation studies revealed that chemicals possessing minimal estrogenicity themselves could reduce (negatively modulate) the effect of a mixture of estrogenic chemicals. Whether the type of modulation we observed occurs in practice most likely depends on the chemical concentrations involved, and better information is required on likely human tissue concentrations of estrogens and of potential modulators. Successful prediction of the effects of diverse chemical combinations might be more likely if chemical profiling included consideration of effect modulation. PMID:22912892

Three-compartment model for contaminant accumulation by semipermeable membrane devices

USGS Publications Warehouse

Gale, Robert W.

1998-01-01

Passive sampling of dissolved hydrophobic contaminants with lipid (triolein)-containing semipermeable membrane devices (SPMDs) has been gaining acceptance for environmental monitoring. Understanding of the accumulation process has employed a simple polymer film-control model of uptake by the polymer-enclosed lipid, while aqueous film control has been only briefly discussed. A more complete three-compartment model incorporating both aqueous film (turbulent-diffusive) and polymer film (diffusive) mass transfer is developed here and is fit to data from accumulation studies conducted in constant-concentration, flow-through dilutors. This model predicts aqueous film control of the whole device for moderate to high Kow compounds, rather than polymer film control. Uptake rates for phenanthrene and 2,2‘,5,5‘-tetrachlorobiphenyl were about 4.8 and 4.2 L/day/standard SPMD, respectively. Maximum 28 day SPMD concentration factors of 30 000 are predicted for solutes with log Kow values of >5.5. Effects of varying aqueous and polymer film thicknesses and solute diffusivities in the polymer film are modeled, and overall accumulation by the whole device is predicted to remain under aqueous film control, although accumulation in the triolein may be subject to polymer film control. The predicted half-life and integrative response of SPMDs to pulsed concentration events is proportional to log KSPMD.

Modeling groundwater nitrate concentrations in private wells in Iowa

USGS Publications Warehouse

Wheeler, David C.; Nolan, Bernard T.; Flory, Abigail R.; DellaValle, Curt T.; Ward, Mary H.

2015-01-01

Contamination of drinking water by nitrate is a growing problem in many agricultural areas of the country. Ingested nitrate can lead to the endogenous formation of N-nitroso compounds, potent carcinogens. We developed a predictive model for nitrate concentrations in private wells in Iowa. Using 34,084 measurements of nitrate in private wells, we trained and tested random forest models to predict log nitrate levels by systematically assessing the predictive performance of 179 variables in 36 thematic groups (well depth, distance to sinkholes, location, land use, soil characteristics, nitrogen inputs, meteorology, and other factors). The final model contained 66 variables in 17 groups. Some of the most important variables were well depth, slope length within 1 km of the well, year of sample, and distance to nearest animal feeding operation. The correlation between observed and estimated nitrate concentrations was excellent in the training set (r-square = 0.77) and was acceptable in the testing set (r-square = 0.38). The random forest model had substantially better predictive performance than a traditional linear regression model or a regression tree. Our model will be used to investigate the association between nitrate levels in drinking water and cancer risk in the Iowa participants of the Agricultural Health Study cohort.

Modeling groundwater nitrate concentrations in private wells in Iowa.

PubMed

Wheeler, David C; Nolan, Bernard T; Flory, Abigail R; DellaValle, Curt T; Ward, Mary H

2015-12-01

Contamination of drinking water by nitrate is a growing problem in many agricultural areas of the country. Ingested nitrate can lead to the endogenous formation of N-nitroso compounds, potent carcinogens. We developed a predictive model for nitrate concentrations in private wells in Iowa. Using 34,084 measurements of nitrate in private wells, we trained and tested random forest models to predict log nitrate levels by systematically assessing the predictive performance of 179 variables in 36 thematic groups (well depth, distance to sinkholes, location, land use, soil characteristics, nitrogen inputs, meteorology, and other factors). The final model contained 66 variables in 17 groups. Some of the most important variables were well depth, slope length within 1 km of the well, year of sample, and distance to nearest animal feeding operation. The correlation between observed and estimated nitrate concentrations was excellent in the training set (r-square=0.77) and was acceptable in the testing set (r-square=0.38). The random forest model had substantially better predictive performance than a traditional linear regression model or a regression tree. Our model will be used to investigate the association between nitrate levels in drinking water and cancer risk in the Iowa participants of the Agricultural Health Study cohort. Copyright © 2015 Elsevier B.V. All rights reserved.

Release of Airborne Polychlorinated Biphenyls from New Bedford Harbor Results in Elevated Concentrations in the Surrounding Air.

PubMed

Martinez, Andres; Hadnott, Bailey N; Awad, Andrew M; Herkert, Nicholas J; Tomsho, Kathryn; Basra, Komal; Scammell, Madeleine K; Heiger-Bernays, Wendy; Hornbuckle, Keri C

2017-04-11

Qualitatively and quantitatively, we have demonstrated that airborne polychlorinated biphenyl (PCB) concentrations in the air surrounding New Bedford Harbor (NBH) are caused by its water PCB emissions. We measured airborne PCBs at 18 homes and businesses near NBH in 2015, with values ranging from 0.4 to 38 ng m -3 , with a very strong Aroclor 1242/1016 signal that is most pronounced closest to the harbor and reproducible over three sampling rounds. Using U.S. Environmental Protection Agency (U.S. EPA) water PCB data from 2015 and local meteorology, we predicted gas-phase fluxes of PCBs from 160 to 1200 μg m -2 day -1 . Fluxes were used as emissions for AERMOD, a widely applied U.S. EPA atmospheric dispersion model, to predict airborne PCB concentrations. The AERMOD predictions were within a factor of 2 of the field measurements. PCB emission from NBH (110 kg year -1 , average 2015) is the largest reported source of airborne PCBs from natural waters in North America, and the source of high ambient air PCB concentrations in locations close to NBH. It is likely that NBH has been an important source of airborne PCBs since it was contaminated with Aroclors more than 60 years ago.

Unhealthy Phenotype as Indicated by Salivary Biomarkers: Glucose, Insulin, VEGF-A, and IL-12p70 in Obese Kuwaiti Adolescents

PubMed Central

Hartman, Mor-Li; Goodson, J. Max; Shi, Ping; Vargas, Jorel; Yaskell, Tina; Stephens, Danielle; Cugini, Maryann; Hasturk, Hatice; Barake, Roula; Alsmadi, Osama; Al-Mutawa, Sabiha; Ariga, Jitendra; Soparkar, Pramod; Behbehani, Jawad; Behbehani, Kazem; Welty, Francine

2016-01-01

Objective. Here, we investigated the relationships between obesity and the salivary concentrations of insulin, glucose, and 20 metabolic biomarkers in Kuwaiti adolescents. Previously, we have shown that certain salivary metabolic markers can act as surrogates for blood concentrations. Methods. Salivary samples of whole saliva were collected from 8,317 adolescents. Salivary glucose concentration was measured by a high-sensitivity glucose oxidase method implemented on a robotic chemical analyzer. The concentration of salivary insulin and 20 other metabolic biomarkers was assayed in 744 randomly selected saliva samples by multiplexed bead-based immunoassay. Results. Obesity was seen in 26.5% of the adolescents. Salivary insulin predicting hyperinsulinemia occurred in 4.3% of normal-weight adolescents, 8.3% of overweight adolescents, and 25.7% of obese adolescents (p < 0.0001). Salivary glucose predicting hyperglycemia was found in only 3% of obese children and was not predictive (p = 0.89). Elevated salivary glucose and insulin occurring together was associated with elevated vascular endothelial growth factor and reduced salivary interleukin-12. Conclusion. Considering the surrogate nature of salivary insulin and glucose, this study suggests that elevated insulin may be a dominant sign of metabolic disease in adolescent populations. It also appears that a proangiogenic environment may accompany elevated glucose in obese adolescents. PMID:27069678

Climate and Physiography Predict Mercury Concentrations in Game Fish Species in Quebec Lakes Better than Anthropogenic Disturbances.

PubMed

Lucotte, Marc; Paquet, Serge; Moingt, Matthieu

2016-05-01

The fluctuations of mercury levels (Hg) in fish consumed by sport fishers in North-Eastern America depend upon a plethora of interrelated biological and abiological factors. To identify the dominant factors ultimately controlling fish Hg concentrations, we compiled mercury levels (Hg) during the 1976-2010 period in 90 large natural lakes in Quebec (Canada) for two major game species: northern pike (Esox lucius) and walleye (Sander vitreus). Our statistical analysis included 28 geographic information system variables and 15 climatic variables, including sulfate deposition. Higher winter temperatures explained 36% of the variability in higher walleye growth rates, in turn accounting for 54% of the variability in lower Hg concentrations. For northern pike, the dominance of a flat topography in the watershed explained 31% of the variability in lower Hg concentrations. Higher mean annual temperatures explained 27% of the variability in higher pike Hg concentrations. Pelagic versus littoral preferred habitats for walleye and pike respectively could explain the contrasted effect of temperature between the two species. Heavy logging could only explain 2% of the increase in walleye Hg concentrations. The influence of mining on fish Hg concentrations appeared to be masked by climatic effects.

Gender differences in predicting high-risk drinking among undergraduate students.

PubMed

Wilke, Dina J; Siebert, Darcy Clay; Delva, Jorge; Smith, Michael P; Howell, Richard L

2005-01-01

The purpose of this study was to examine gender differences in college students' high-risk drinking as measured by an estimated blood alcohol concentration (eBAC) based on gender, height, weight, self-reported number of drinks, and hours spent drinking. Using a developmental/contextual framework, high-risk drinking is conceptualized as a function of relevant individual characteristics, interpersonal factors, and contextual factors regularly mentioned in the college drinking literature. Individual characteristics include race, gender, and age; interpersonal characteristics include number of sexual partners and having experienced forced sexual contact. Finally, contextual factors include Greek membership, living off-campus, and perception of peer drinking behavior. This study is a secondary data analysis of 1,422 students at a large university in the Southeast. Data were gathered from a probability sample of students through a mail survey. A three-step hierarchical logistic regression analysis showed gender differences in the pathway for high-risk drinking. For men, high-risk drinking was predicted by a combination of individual characteristics and contextual factors. For women, interpersonal factors, along with individual characteristics and contextual factors, predicted high-risk drinking, highlighting the importance of understanding female sexual relationships and raising questions about women's risk-taking behavior. Implications for prevention and assessment are discussed.

Antipsychotic therapeutic drug monitoring: psychiatrists’ attitudes and factors predicting likely future use

PubMed Central

Law, Suzanne; Haddad, Peter M.; Chaudhry, Imran B.; Husain, Nusrat; Drake, Richard J.; Flanagan, Robert J.; David, Anthony S.

2015-01-01

Background: This study aimed to explore predictive factors for future use of therapeutic drug monitoring (TDM) and to further examine psychiatrists’ current prescribing practices and perspectives regarding antipsychotic TDM using plasma concentrations. Method: A cross-sectional study for consultant psychiatrists using a postal questionnaire was conducted in north-west England. Data were combined with those of a previous London-based study and principal axis factor analysis was conducted to identify predictors of future use of TDM. Results: Most of the 181 participants (82.9%, 95% confidence interval 76.7–87.7%) agreed that ‘if TDM for antipsychotics were readily available, I would use it’. Factor analysis identified five factors from the original 35 items regarding TDM. Four of the factors significantly predicted likely future use of antipsychotic TDM and together explained 40% of the variance in a multivariate linear regression model. Likely future use increased with positive attitudes and expectations, and decreased with potential barriers, negative attitudes and negative expectations. Scientific perspectives of TDM and psychiatrist characteristics were not significant predictors. Conclusion: Most senior psychiatrists indicated that they would use antipsychotic TDM if available. However, psychiatrists’ attitudes and expectations and the potential barriers need to be addressed, in addition to the scientific evidence, before widespread use of antipsychotic TDM is likely in clinical practice. PMID:26301077

Physics and chemistry of antimicrobial behavior of ion-exchanged silver in glass.

PubMed

Borrelli, N F; Senaratne, W; Wei, Y; Petzold, O

2015-02-04

The results of a comprehensive study involving the antimicrobial activity in a silver ion-exchanged glass are presented. The study includes the glass composition, the method of incorporating silver into the glass, the effective concentration of the silver available at the glass surface, and the effect of the ambient environment. A quantitative kinetic model that includes the above factors in predicting the antimicrobial activity is proposed. Finally, experimental data demonstrating antibacterial activity against Staphylococcus aureus with correlation to the predicted model is shown.

Changes in plasma thrombospondin-1 concentrations following acute intracerebral hemorrhage.

PubMed

Dong, Xiao-Qiao; Yu, Wen-Hua; Zhu, Qiang; Cheng, Zhen-Yu; Chen, Yi-Hua; Lin, Xiao-Feng; Ten, Xian-Lin; Tang, Xiao-Bing; Chen, Juan

2015-10-23

Angiogenesis is a fundamental process for brain development and repair. Thrombospondin-1 is the first identified endogenous angiogenesis inhibitor. Its expression in rat brain is upregulated after intracerebral hemorrhage (ICH). We determined whether plasma thrombospondin-1 concentrations are associated with injury severity and prognosis in ICH patients. This observational, prospective study recruited 110 patients and 110 age- and gender-matched healthy controls. Blood samples were collected from the patients at admission and from the healthy controls at study entry to measure plasma thrombospondin-1 concentrations. The endpoints included 1-week mortality, 6-month mortality, 6-month overall survival and 6-month unfavorable outcome (modified Rankin Scale score >2). Plasma thrombospondin-1 concentrations were markedly higher in patients than in healthy controls. Thrombospondin-1 was an independent predictive factor for all endpoints and plasma thrombospondin-1 concentrations were highly associated with injury severity reflected by hematoma volume and National Institutes of Health Stroke Scale score. Under receiver operating characteristic curves, plasma thrombospondin-1 concentrations had similar predictive values compared with hematoma volume and National Institutes of Health Stroke Scale score. Increased plasma thrombospondin-1 concentrations following ICH are independently associated with injury severity and short-term and long-term clinical outcomes. Copyright © 2015 Elsevier B.V. All rights reserved.

Predictors of blood trihalomethane concentrations in NHANES 1999-2006.

PubMed

Riederer, Anne M; Dhingra, Radhika; Blount, Benjamin C; Steenland, Kyle

2014-07-01

Trihalomethanes (THMs) are water disinfection by-products that have been associated with bladder cancer and adverse birth outcomes. Four THMs (bromoform, chloroform, bromodichloromethane, dibromochloromethane) were measured in blood and tap water of U.S. adults in the National Health and Nutrition Examination Survey (NHANES) 1999-2006. THMs are metabolized to potentially toxic/mutagenic intermediates by cytochrome p450 (CYP) 2D6 and CYP2E1 enzymes. We conducted exploratory analyses of blood THMs, including factors affecting CYP2D6 and CYP2E1 activity. We used weighted multivariable regressions to evaluate associations between blood THMs and water concentrations, survey year, and other factors potentially affecting THM exposure or metabolism (e.g., prescription medications, cruciferous vegetables, diabetes, fasting, pregnancy, swimming). From 1999 to 2006, geometric mean blood and water THM levels dropped in parallel, with decreases of 32%-76% in blood and 38%-52% in water, likely resulting, in part, from the lowering of the total THM drinking water standard in 2002-2004. The strongest predictors of blood THM levels were survey year and water concentration (n = 4,232 total THM; n = 4,080 bromoform; n = 4,582 chloroform; n = 4,374 bromodichloromethane; n = 4,464 dibromochloromethane). We detected statistically significant inverse associations with diabetes and eating cruciferous vegetables in all but the bromoform model. Medications did not consistently predict blood levels. Afternoon/evening blood samples had lower THM concentrations than morning samples. In a subsample (n = 230), air chloroform better predicted blood chloroform than water chloroform, suggesting showering/bathing was a more important source than drinking. We identified several factors associated with blood THMs that may affect their metabolism. The potential health implications require further study.

The Extent and Prediction of Heavy Metal Pollution in Soils of Shahrood and Damghan, Iran.

PubMed

Sakizadeh, Mohamad; Mirzaei, Rouhollah; Ghorbani, Hadi

2015-12-01

The levels of 12 heavy metals (Ag, Ba, Be, Cd, Co, Cr, Cu, Ni, Pb, Tl, V, Zn) were considered in 229 soil samples in Semnan Province, Iran. To discriminate between natural and anthropogenic inputs of heavy metals, factor analysis was used. Seven factors accounting for 90.5 % of the total variance were extracted. The mining and agricultural activities along with geogenic sources have been attributed as the main causes of the levels of heavy metals in the study area. The partial least squares regression was utilized to predict the level of soil pollution index (SPI) considering the concentrations of 12 heavy metals. The eigenvectors from the first three PLS represented more than 98 % of the overall variance. The correlation coefficient between the observed and predicted SPI was 0.99 indicating the high efficiency of this method. The resultant coefficient of determination for three PLS components was 0.984 confirming the predictive ability of this method.

Artificial neural networks identify the predictive values of risk factors on the conversion of amnestic mild cognitive impairment.

PubMed

Tabaton, Massimo; Odetti, Patrizio; Cammarata, Sergio; Borghi, Roberta; Monacelli, Fiammetta; Caltagirone, Carlo; Bossù, Paola; Buscema, Massimo; Grossi, Enzo

2010-01-01

The search for markers that are able to predict the conversion of amnestic mild cognitive impairment (aMCI) to Alzheimer's disease (AD) is crucial for early mechanistic therapies. Using artificial neural networks (ANNs), 22 variables that are known risk factors of AD were analyzed in 80 patients with aMCI, for a period spanning at least 2 years. The cases were chosen from 195 aMCI subjects recruited by four Italian Alzheimer's disease units. The parameters of glucose metabolism disorder, female gender, and apolipoprotein E epsilon3/epsilon4 genotype were found to be the biological variables with high relevance for predicting the conversion of aMCI. The scores of attention and short term memory tests also were predictors. Surprisingly, the plasma concentration of amyloid-beta (42) had a low predictive value. The results support the utility of ANN analysis as a new tool in the interpretation of data from heterogeneous and distinct sources.

Natural biogeochemical cycle of mercury in a global three-dimensional ocean tracer model

NASA Astrophysics Data System (ADS)

Zhang, Yanxu; Jaeglé, Lyatt; Thompson, LuAnne

2014-05-01

We implement mercury (Hg) biogeochemistry in the offline global 3-D ocean tracer model (OFFTRAC) to investigate the natural Hg cycle, prior to any anthropogenic input. The simulation includes three Hg tracers: dissolved elemental (Hg0aq), dissolved divalent (HgIIaq), and particle-bound mercury (HgPaq). Our Hg parameterization takes into account redox chemistry in ocean waters, air-sea exchange of Hg0, scavenging of HgIIaq onto sinking particles, and resupply of HgIIaq at depth by remineralization of sinking particles. Atmospheric boundary conditions are provided by a global simulation of the natural atmospheric Hg cycle in the GEOS-Chem model. In the surface ocean, the OFFTRAC model predicts global mean concentrations of 0.16 pM for total Hg, partitioned as 80% HgIIaq, 14% Hg0aq, and 6% HgPaq. Total Hg concentrations increase to 0.38 pM in the thermocline/intermediate waters (between the mixed layer and 1000 m depth) and 0.82 pM in deep waters (below 1000 m), reflecting removal of Hg from the surface to the subsurface ocean by particle sinking followed by remineralization at depth. Our model predicts that Hg concentrations in the deep North Pacific Ocean (>2000 m) are a factor of 2-3 higher than in the deep North Atlantic Ocean. This is the result of cumulative input of Hg from particle remineralization as deep waters transit from the North Atlantic to the North Pacific on their ~2000 year journey. The model is able to reproduce the relatively uniform concentrations of total Hg observed in the old deep waters of the North Pacific Ocean (observations: 1.2 ± 0.4 pM; model: 1.1 ± 0.04 pM) and Southern Ocean (observations: 1.1 ± 0.2 pM; model: 0.8 ± 0.02 pM). However, the modeled concentrations are factors of 5-6 too low compared to observed concentrations in the surface ocean and in the young water masses of the deep North Atlantic Ocean. This large underestimate for these regions implies a factor of 5-6 anthropogenic enhancement in Hg concentrations.

Multiple linear regression and regression with time series error models in forecasting PM10 concentrations in Peninsular Malaysia.

PubMed

Ng, Kar Yong; Awang, Norhashidah

2018-01-06

Frequent haze occurrences in Malaysia have made the management of PM 10 (particulate matter with aerodynamic less than 10 μm) pollution a critical task. This requires knowledge on factors associating with PM 10 variation and good forecast of PM 10 concentrations. Hence, this paper demonstrates the prediction of 1-day-ahead daily average PM 10 concentrations based on predictor variables including meteorological parameters and gaseous pollutants. Three different models were built. They were multiple linear regression (MLR) model with lagged predictor variables (MLR1), MLR model with lagged predictor variables and PM 10 concentrations (MLR2) and regression with time series error (RTSE) model. The findings revealed that humidity, temperature, wind speed, wind direction, carbon monoxide and ozone were the main factors explaining the PM 10 variation in Peninsular Malaysia. Comparison among the three models showed that MLR2 model was on a same level with RTSE model in terms of forecasting accuracy, while MLR1 model was the worst.

Contamination of estuarine water, biota, and sediment by halogenated organic compounds: A field study

USGS Publications Warehouse

Pereira, W.E.; Rostad, C.E.; Chiou, C.T.; Brinton, T.I.; Barber, L.B.; Demcheck, D.K.; Demas, C.R.

1988-01-01

Studies conducted in the vicinity of an industrial outfall in the Calcasieu River estuary, Louisiana, have shown that water, bottom and suspended sediment, and four different species of biota are contaminated with halogenated organic compounds (HOC) including haloarenes. A "salting-out" effect in the estuary moderately enhanced the partitioning tendency of the contaminants into biota and sediments. Contaminant concentrations in water, suspended sediments, and biota were found to be far below the values predicted on the basis of the assumption of phase equilibria with respect to concentrations in bottom sediment. Relative concentration factors of HOC between biota (catfish) and bottom sediment increased with increasing octanol/estuarine water partition coefficients (Kow*), maximizing at log Kow* of about 5, although these ratios were considerably less than equilibrium values. In contrast, contaminant concentrations in water, biota, and suspended sediments were much closer to equilibrium values. Bioconcentration factors of HOC determined on the basis of lipid content for four different biotic species correlated reasonably well with equilibrium triolein/water partition coefficients (Ktw).

[Predicting the probability of development and progression of primary open angle glaucoma by regression modeling].

PubMed

Likhvantseva, V G; Sokolov, V A; Levanova, O N; Kovelenova, I V

2018-01-01

Prediction of the clinical course of primary open-angle glaucoma (POAG) is one of the main directions in solving the problem of vision loss prevention and stabilization of the pathological process. Simple statistical methods of correlation analysis show the extent of each risk factor's impact, but do not indicate the total impact of these factors in personalized combinations. The relationships between the risk factors is subject to correlation and regression analysis. The regression equation represents the dependence of the mathematical expectation of the resulting sign on the combination of factor signs. To develop a technique for predicting the probability of development and progression of primary open-angle glaucoma based on a personalized combination of risk factors by linear multivariate regression analysis. The study included 66 patients (23 female and 43 male; 132 eyes) with newly diagnosed primary open-angle glaucoma. The control group consisted of 14 patients (8 male and 6 female). Standard ophthalmic examination was supplemented with biochemical study of lacrimal fluid. Concentration of matrix metalloproteinase MMP-2 and MMP-9 in tear fluid in both eyes was determined using 'sandwich' enzyme-linked immunosorbent assay (ELISA) method. The study resulted in the development of regression equations and step-by-step multivariate logistic models that can help calculate the risk of development and progression of POAG. Those models are based on expert evaluation of clinical and instrumental indicators of hydrodynamic disturbances (coefficient of outflow ease - C, volume of intraocular fluid secretion - F, fluctuation of intraocular pressure), as well as personalized morphometric parameters of the retina (central retinal thickness in the macular area) and concentration of MMP-2 and MMP-9 in the tear film. The newly developed regression equations are highly informative and can be a reliable tool for studying of the influence vector and assessment of pathogenic potential of the independent risk factors in specific personalized combinations.

Comparison of the predictions of two road dust emission models with the measurements of a mobile van

NASA Astrophysics Data System (ADS)

Kauhaniemi, M.; Stojiljkovic, A.; Pirjola, L.; Karppinen, A.; Härkönen, J.; Kupiainen, K.; Kangas, L.; Aarnio, M. A.; Omstedt, G.; Denby, B. R.; Kukkonen, J.

2014-09-01

The predictions of two road dust suspension emission models were compared with the on-site mobile measurements of suspension emission factors. Such a quantitative comparison has not previously been reported in the reviewed literature. The models used were the Nordic collaboration model NORTRIP (NOn-exhaust Road TRaffic Induced Particle emissions) and the Swedish-Finnish FORE model (Forecasting Of Road dust Emissions). These models describe particulate matter generated by the wear of road surface due to traction control methods and processes that control the suspension of road dust particles into the air. An experimental measurement campaign was conducted using a mobile laboratory called SNIFFER, along two selected road segments in central Helsinki in 2007 and 2008. The suspended PM10 concentration was measured behind the left rear tyre and the street background PM10 concentration in front of the van. Both models reproduced the measured seasonal variation of suspension emission factors fairly well during both years at both measurement sites. However, both models substantially under-predicted the measured emission values. The article illustrates the challenges in conducting road suspension measurements in densely trafficked urban conditions, and the numerous requirements for input data that are needed for accurately applying road suspension emission models.

Relation between different metal pollution criteria in sediments and its contribution on assessing toxicity.

PubMed

Alves, Cristina M; Ferreira, Carlos M H; Soares, Helena M V M

2018-05-14

Several tools have been developed and applied to evaluate the metal pollution status of sediments and predict their potential ecological risk assessment. To date, a comprehensive relationship between the information given by these sediment tools for predicting metal bioavailability and the effective toxicity observed is lacking. In this work, the possible inter-correlations between the data outcoming from using several qualitative evaluation tools of the sediment contamination (contamination factor, CF, the enrichment factor, EF, or the geoaccumulation index, Igeo), metal speciation on sediments (evaluated by the modified BCR sequential extraction procedure) and free metal concentrations in pore waters were studied. It was also our aim to evaluate if these assessment tools could be used for predicting the pore waters toxicity data as toxicity proxy. Principal component analysis and cluster analysis revealed that two quality indices used (CF and EF) were highly correlatable with the more labile fractions from BCR sediment speciation. However, neither of these parameters did correlate with the toxicity of pore waters measured by the chronic toxicity (72 h) in Pseudokirchneriella subcapitata. In contrast, the toxic effects of the given total metal load in sediments were better evaluated by using an additive metal approach using pore water free metal concentrations. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Influence of Individual Variability on Zooplankton Population Dynamics under Different Environmental Conditions

NASA Astrophysics Data System (ADS)

Bi, R.; Liu, H.

2016-02-01

Understanding how biological components respond to environmental changes could be insightful to predict ecosystem trajectories under different climate scenarios. Zooplankton are key components of marine ecosystems and changes in their dynamics could have major impact on ecosystem structure. We developed an individual-based model of a common coastal calanoid copepod Acartia tonsa to examine how environmental factors affect zooplankton population dynamics and explore the role of individual variability in sustaining population under various environmental conditions consisting of temperature, food concentration and salinity. Total abundance, egg production and proportion of survival were used to measure population success. Results suggested population benefits from high level of individual variability under extreme environmental conditions including unfavorable temperature, salinity, as well as low food concentration, and selection on fast-growers becomes stronger with increasing individual variability and increasing environmental stress. Multiple regression analysis showed that temperature, food concentration, salinity and individual variability have significant effects on survival of A. tonsa population. These results suggest that environmental factors have great influence on zooplankton population, and individual variability has important implications for population survivability under unfavorable conditions. Given that marine ecosystems are at risk from drastic environmental changes, understanding how individual variability sustains populations could increase our capability to predict population dynamics in a changing environment.

Modeling the probability of arsenic in groundwater in New England as a tool for exposure assessment

USGS Publications Warehouse

Ayotte, J.D.; Nolan, B.T.; Nuckols, J.R.; Cantor, K.P.; Robinson, G.R.; Baris, D.; Hayes, L.; Karagas, M.; Bress, W.; Silverman, D.T.; Lubin, J.H.

2006-01-01

We developed a process-based model to predict the probability of arsenic exceeding 5 ??g/L in drinking water wells in New England bedrock aquifers. The model is being used for exposure assessment in an epidemiologic study of bladder cancer. One important study hypothesis that may explain increased bladder cancer risk is elevated concentrations of inorganic arsenic in drinking water. In eastern New England, 20-30% of private wells exceed the arsenic drinking water standard of 10 micrograms per liter. Our predictive model significantly improves the understanding of factors associated with arsenic contamination in New England. Specific rock types, high arsenic concentrations in stream sediments, geochemical factors related to areas of Pleistocene marine inundation and proximity to intrusive granitic plutons, and hydrologic and landscape variables relating to groundwater residence time increase the probability of arsenic occurrence in groundwater. Previous studies suggest that arsenic in bedrock groundwater may be partly from past arsenical pesticide use. Variables representing historic agricultural inputs do not improve the model, indicating that this source does not significantly contribute to current arsenic concentrations. Due to the complexity of the fractured bedrock aquifers in the region, well depth and related variables also are not significant predictors. ?? 2006 American Chemical Society.

Metabolic health assessment of zoo elephants: Management factors predicting leptin levels and the glucose-to-insulin ratio and their associations with health parameters

PubMed Central

Brown, Janine L.

2017-01-01

Screening for metabolic-related health problems can enhance animal welfare, so the purpose of this study was to conduct the first metabolic health assessment of zoo elephants and use epidemiological methods to determine how factors in the captive environment were associated with metabolic hormone concentrations. In addition, we examined relationships between metabolic status and several fitness parameters: foot health, musculoskeletal health, reproductive cyclicity, and body condition. Two blood samples were collected 2 weeks apart from 87 Asian (Elephas maximus) and 105 African (Loxodonta africana) elephants managed by zoos accredited by the Association of Zoos and Aquariums for analysis of serum leptin, insulin, glucose and the glucose-to-insulin ratio (G:I). In females, mean (± SD) leptin concentrations and the G:I were lower (P<0.05) in Asian (3.93 ± 2.21 ng/ml and 110 ± 86 units) compared to African (4.37 ± 2.89 ng/ml and 208 ± 133 units) elephants, respectively. For males, mean leptin and the G:I were 4.99 ± 3.61 ng/ml and 253 ± 181 units for Asian, and 3.72 ± 2.00 ng/ml and 326 ± 231 units for African elephants, respectively, with no differences between species (P>0.05). As mean leptin concentration increased there was an increase in the odds of a female being non-cycling (P = 0.0083). The G:I was associated inversely with body condition (P = 0.0002); as the G:I increased there was a decreased risk of BCS = 4 or 5 as compared to the ideal, or BCS = 3. Neither leptin nor G:I were predictive of foot or musculoskeletal health scores. Factors related to walking and feeding practices were most influential in predicting metabolic status, whereas social and housing factors showed smaller, but significant effects. The metabolic health benefits of walking were detected if the time spent in staff-directed walking was 7 hours or more per week. The most protective feeding practices included implementing a random rather than predictable feeding schedule and limiting the number of methods presentation methods. Results indicate that leptin levels and G:I can be used as predictors of both ovarian cycle function and body condition, and are affected by zoo management in elephants. PMID:29186207

Metabolic health assessment of zoo elephants: Management factors predicting leptin levels and the glucose-to-insulin ratio and their associations with health parameters.

PubMed

Morfeld, Kari A; Brown, Janine L

2017-01-01

Screening for metabolic-related health problems can enhance animal welfare, so the purpose of this study was to conduct the first metabolic health assessment of zoo elephants and use epidemiological methods to determine how factors in the captive environment were associated with metabolic hormone concentrations. In addition, we examined relationships between metabolic status and several fitness parameters: foot health, musculoskeletal health, reproductive cyclicity, and body condition. Two blood samples were collected 2 weeks apart from 87 Asian (Elephas maximus) and 105 African (Loxodonta africana) elephants managed by zoos accredited by the Association of Zoos and Aquariums for analysis of serum leptin, insulin, glucose and the glucose-to-insulin ratio (G:I). In females, mean (± SD) leptin concentrations and the G:I were lower (P<0.05) in Asian (3.93 ± 2.21 ng/ml and 110 ± 86 units) compared to African (4.37 ± 2.89 ng/ml and 208 ± 133 units) elephants, respectively. For males, mean leptin and the G:I were 4.99 ± 3.61 ng/ml and 253 ± 181 units for Asian, and 3.72 ± 2.00 ng/ml and 326 ± 231 units for African elephants, respectively, with no differences between species (P>0.05). As mean leptin concentration increased there was an increase in the odds of a female being non-cycling (P = 0.0083). The G:I was associated inversely with body condition (P = 0.0002); as the G:I increased there was a decreased risk of BCS = 4 or 5 as compared to the ideal, or BCS = 3. Neither leptin nor G:I were predictive of foot or musculoskeletal health scores. Factors related to walking and feeding practices were most influential in predicting metabolic status, whereas social and housing factors showed smaller, but significant effects. The metabolic health benefits of walking were detected if the time spent in staff-directed walking was 7 hours or more per week. The most protective feeding practices included implementing a random rather than predictable feeding schedule and limiting the number of methods presentation methods. Results indicate that leptin levels and G:I can be used as predictors of both ovarian cycle function and body condition, and are affected by zoo management in elephants.

Structure of the Soot Growth Region of Laminar Premixer Methane/Oxygen Flames

NASA Technical Reports Server (NTRS)

Xu, F.; Faeth, G. M.

1999-01-01

Soot is a dominant feature of hydrocarbon/air flames, affecting their reaction mechanisms and structure. As a result, soot processes affect capabilities for computational combustion as well as predictions of flame radiation and pollution emissions. Motivated by these observations, the present investigation extended past work on soot growth in laminar premixed flames, seeking to evaluate model predictions of flame structure. Xu et al. report direct measurements of soot residence times, soot concentrations, soot structure, gas temperatures and gas compositions for premixed flames similar to those studied by Harris and Weiner and Ramer et al. respectively. It was found that predictions of major stable gas species concentrations based on mechanisms of Leung and Lindstedt and Frenklach and coworkers, were in good agreement with the measurements. The results were also used to evaluate the hydrogen-abstraction/carbon-addition (HACA) soot growth mechanisms of Frenklach and coworkers and Colket and Hall. It was found that these mechanisms were effective using quite reasonable correlations for the steric factors appearing in the theories. The successful evaluation of the HACA mechanism of soot growth in Refs. 1 and 2 is encouraging but one aspect of this evaluation is a concern. In particular, H-atom concentrations play a crucial role in the HACA mechanism and it was necessary to estimate these concentrations because they were not measured directly. These estimates were made assuming local thermodynamic equilibrium between H, and H based on measured temperatures and H2 concentrations and the equilibrium constant data of Kee et al.. This approach was justified by the flame structure predictions; nevertheless, direct evaluation of equilibrium estimates of H-atom concentrations in the soot growth regions of laminar premixed flames is needed to provide more convincing proof of this behavior. Thus, the objective of the present investigation was to complete new measurements of the structure of the soot growth region of laminar premixed flames and to use these results to evaluate whether H and H2 are in thermodynamic equilibrium and to extend the earlier evaluation of predictions of concentrations of major gas species.

On the competition among aerosol number, size and composition in predicting CCN variability: a multi-annual field study in an urbanized desert.

PubMed

Crosbie, E; Youn, J-S; Balch, B; Wonaschütz, A; Shingler, T; Wang, Z; Conant, W C; Betterton, E A; Sorooshian, A

2015-02-10

A 2-year data set of measured CCN (cloud condensation nuclei) concentrations at 0.2 % supersaturation is combined with aerosol size distribution and aerosol composition data to probe the effects of aerosol number concentrations, size distribution and composition on CCN patterns. Data were collected over a period of 2 years (2012-2014) in central Tucson, Arizona: a significant urban area surrounded by a sparsely populated desert. Average CCN concentrations are typically lowest in spring (233 cm -3 ), highest in winter (430 cm -3 ) and have a secondary peak during the North American monsoon season (July to September; 372 cm -3 ). There is significant variability outside of seasonal patterns, with extreme concentrations (1 and 99 % levels) ranging from 56 to 1945 cm -3 as measured during the winter, the season with highest variability. Modeled CCN concentrations based on fixed chemical composition achieve better closure in winter, with size and number alone able to predict 82% of the variance in CCN concentration. Changes in aerosol chemical composition are typically aligned with changes in size and aerosol number, such that hygroscopicity can be parameterized even though it is still variable. In summer, models based on fixed chemical composition explain at best only 41% (pre-monsoon) and 36% (monsoon) of the variance. This is attributed to the effects of secondary organic aerosol (SOA) production, the competition between new particle formation and condensational growth, the complex interaction of meteorology, regional and local emissions and multi-phase chemistry during the North American monsoon. Chemical composition is found to be an important factor for improving predictability in spring and on longer timescales in winter. Parameterized models typically exhibit improved predictive skill when there are strong relationships between CCN concentrations and the prevailing meteorology and dominant aerosol physicochemical processes, suggesting that similar findings could be possible in other locations with comparable climates and geography.

Factors Controlling the Properties of Multi-Phase Arctic Stratocumulus Clouds

NASA Technical Reports Server (NTRS)

Fridlind, Ann; Ackerman, Andrew; Menon, Surabi

2005-01-01

The 2004 Multi-Phase Arctic Cloud Experiment (M-PACE) IOP at the ARM NSA site focused on measuring the properties of autumn transition-season arctic stratus and the environmental conditions controlling them, including concentrations of heterogeneous ice nuclei. Our work aims to use a large-eddy simulation (LES) code with embedded size-resolved aerosol and cloud microphysics to identify factors controlling multi-phase arctic stratus. Our preliminary simulations of autumn transition-season clouds observed during the 1994 Beaufort and Arctic Seas Experiment (BASE) indicated that low concentrations of ice nuclei, which were not measured, may have significantly lowered liquid water content and thereby stabilized cloud evolution. However, cloud drop concentrations appeared to be virtually immune to changes in liquid water content, indicating an active Bergeron process with little effect of collection on drop number concentration. We will compare these results with preliminary simulations from October 8-13 during MPACE. The sensitivity of cloud properties to uncertainty in other factors, such as large-scale forcings and aerosol profiles, will also be investigated. Based on the LES simulations with M-PACE data, preliminary results from the NASA GlSS single-column model (SCM) will be used to examine the sensitivity of predicted cloud properties to changing cloud drop number concentrations for multi-phase arctic clouds. Present parametrizations assumed fixed cloud droplet number concentrations and these will be modified using M-PACE data.

Estimating the probability of elevated nitrate (NO2+NO3-N) concentrations in ground water in the Columbia Basin Ground Water Management Area, Washington

USGS Publications Warehouse

Frans, Lonna M.

2000-01-01

Logistic regression was used to relate anthropogenic (man-made) and natural factors to the occurrence of elevated concentrations of nitrite plus nitrate as nitrogen in ground water in the Columbia Basin Ground Water Management Area, eastern Washington. Variables that were analyzed included well depth, depth of well casing, ground-water recharge rates, presence of canals, fertilizer application amounts, soils, surficial geology, and land-use types. The variables that best explain the occurrence of nitrate concentrations above 3 milligrams per liter in wells were the amount of fertilizer applied annually within a 2-kilometer radius of a well and the depth of the well casing; the variables that best explain the occurrence of nitrate above 10 milligrams per liter included the amount of fertilizer applied annually within a 3-kilometer radius of a well, the depth of the well casing, and the mean soil hydrologic group, which is a measure of soil infiltration rate. Based on the relations between these variables and elevated nitrate concentrations, models were developed using logistic regression that predict the probability that ground water will exceed a nitrate concentration of either 3 milligrams per liter or 10 milligrams per liter. Maps were produced that illustrate the predicted probability that ground-water nitrate concentrations will exceed 3 milligrams per liter or 10 milligrams per liter for wells cased to 78 feet below land surface (median casing depth) and the predicted depth to which wells would need to be cased in order to have an 80-percent probability of drawing water with a nitrate concentration below either 3 milligrams per liter or 10 milligrams per liter. Maps showing the predicted probability for the occurrence of elevated nitrate concentrations indicate that the irrigated agricultural regions are most at risk. The predicted depths to which wells need to be cased in order to have an 80-percent chance of obtaining low nitrate ground water exceed 600 feet in the irrigated agricultural regions, whereas wells in dryland agricultural areas generally need a casing in excess of 400 feet. The predicted depth to which wells need to be cased to have at least an 80-percent chance to draw water with a nitrate concentration less than 10 milligrams per liter generally did not exceed 800 feet, with a 200-foot casing depth typical of the majority of the area.

Evaluation of relative response factor methodology for demonstrating attainment of ozone in Houston, Texas.

PubMed

Vizuete, William; Biton, Leiran; Jeffries, Harvey E; Couzo, Evan

2010-07-01

In 2007, the U.S. Environmental Protection Agency (EPA) released guidance on demonstrating attainment of the federal ozone (O3) standard. This guidance recommended a change in the use of air quality model (AQM) predictions from an absolute to a relative way. This was accomplished by using a ratio, and not the absolute difference of AQM O3 predictions from a historical year to an attainment year. This ratio of O3 concentrations, labeled the relative response factor (RRF), is multiplied by an average of observed concentrations at every monitor. In this analysis, whether the methodology used to calculate RRFs is severing the source-receptor relationship for a given monitor was investigated. Model predictions were generated with a regulatory AQM system used to support the 2004 Houston-Galveston-Brazoria State Implementation Plan. Following the procedures in the EPA guidance, an attainment demonstration was completed using regulatory AQM predictions and measurements from the Houston ground-monitoring network. Results show that the model predictions used for the RRF calculation were often based on model conditions that were geographically remote from observations and counter to wind flow. Many of the monitors used the same model predictions for an RRF, even if that O3 plume did not impact it. The RRF methodology resulted in severing the true source-receptor relationship for a monitor. This analysis also showed that model performance could influence RRF values, and values at monitoring sites appear to be sensitive to model bias. Results indicate an inverse linear correlation of RRFs with model bias at each monitor (R2 = 0.47), resulting in a change in future O3 design values up to 5 parts per billion (ppb). These results suggest that the application of RRF methodology in Houston, TX, should be changed from using all model predictions above 85 ppb to a method that removes any predictions that are not relevant to the observed source-receptor relationship.

[Factors affecting benzene diffusion from contaminated soils to the atmosphere and flux characteristics].

PubMed

Du, Ping; Wang, Shi-Jie; Zhao, Huan-Huan; Wu, Bin; Han, Chun-Mei; Fang, Ji-Dun; Li, Hui-Ying; Hosomi, Masaaki; Li, Fa-Sheng

2013-12-01

The influencing factors of benzene diffusion fluxes from sand and black soil to atmosphere were investigated using a flux chamber (30.0 cm x 17.5 cm x 29.0 cm). In this study, the benzene diffusion fluxes were estimated by measuring the benzene concentrations both in the headspace of the chamber and in the soils of different layers. The results indicated that the soil water content played an important role in benzene diffusion fluxes. The diffusion flux showed positive correlation with the initial benzene concentration and the benzene dissolution concentration for both soil types. The changes of air flow rate from 300 to 900 mL x min(-1) and temperature from 20 degrees C to 40 degrees C resulted in increases of the benzene diffusion flux. Our study of benzene diffusion fluxes from contaminated soils will be beneficial for the predicting model, and emergency management and precautions.

Modeling population exposures to outdoor sources of hazardous air pollutants.

PubMed

Ozkaynak, Halûk; Palma, Ted; Touma, Jawad S; Thurman, James

2008-01-01

Accurate assessment of human exposures is an important part of environmental health effects research. However, most air pollution epidemiology studies rely upon imperfect surrogates of personal exposures, such as information based on available central-site outdoor concentration monitoring or modeling data. In this paper, we examine the limitations of using outdoor concentration predictions instead of modeled personal exposures for over 30 gaseous and particulate hazardous air pollutants (HAPs) in the US. The analysis uses the results from an air quality dispersion model (the ASPEN or Assessment System for Population Exposure Nationwide model) and an inhalation exposure model (the HAPEM or Hazardous Air Pollutant Exposure Model, Version 5), applied by the US. Environmental protection Agency during the 1999 National Air Toxic Assessment (NATA) in the US. Our results show that the total predicted chronic exposure concentrations of outdoor HAPs from all sources are lower than the modeled ambient concentrations by about 20% on average for most gaseous HAPs and by about 60% on average for most particulate HAPs (mainly, due to the exclusion of indoor sources from our modeling analysis and lower infiltration of particles indoors). On the other hand, the HAPEM/ASPEN concentration ratio averages for onroad mobile source exposures were found to be greater than 1 (around 1.20) for most mobile-source related HAPs (e.g. 1, 3-butadiene, acetaldehyde, benzene, formaldehyde) reflecting the importance of near-roadway and commuting environments on personal exposures to HAPs. The distribution of the ratios of personal to ambient concentrations was found to be skewed for a number of the VOCs and reactive HAPs associated with major source emissions, indicating the importance of personal mobility factors. We conclude that the increase in personal exposures from the corresponding predicted ambient levels tends to occur near locations where there are either major emission sources of HAPs or when individuals are exposed to either on- or nonroad sources of HAPs during their daily activities. These findings underscore the importance of applying exposure-modeling methods, which incorporate information on time-activity, commuting, and exposure factors data, for the purposes of assigning exposures in air pollution health studies.

Predictors of Blood Trihalomethane Concentrations in NHANES 1999–2006

PubMed Central

Dhingra, Radhika; Blount, Benjamin C.; Steenland, Kyle

2014-01-01

Background: Trihalomethanes (THMs) are water disinfection by-products that have been associated with bladder cancer and adverse birth outcomes. Four THMs (bromoform, chloroform, bromodichloromethane, dibromochloromethane) were measured in blood and tap water of U.S. adults in the National Health and Nutrition Examination Survey (NHANES) 1999–2006. THMs are metabolized to potentially toxic/mutagenic intermediates by cytochrome p450 (CYP) 2D6 and CYP2E1 enzymes. Objectives: We conducted exploratory analyses of blood THMs, including factors affecting CYP2D6 and CYP2E1 activity. Methods: We used weighted multivariable regressions to evaluate associations between blood THMs and water concentrations, survey year, and other factors potentially affecting THM exposure or metabolism (e.g., prescription medications, cruciferous vegetables, diabetes, fasting, pregnancy, swimming). Results: From 1999 to 2006, geometric mean blood and water THM levels dropped in parallel, with decreases of 32%–76% in blood and 38%–52% in water, likely resulting, in part, from the lowering of the total THM drinking water standard in 2002–2004. The strongest predictors of blood THM levels were survey year and water concentration (n = 4,232 total THM; n = 4,080 bromoform; n = 4,582 chloroform; n = 4,374 bromodichloromethane; n = 4,464 dibromochloromethane). We detected statistically significant inverse associations with diabetes and eating cruciferous vegetables in all but the bromoform model. Medications did not consistently predict blood levels. Afternoon/evening blood samples had lower THM concentrations than morning samples. In a subsample (n = 230), air chloroform better predicted blood chloroform than water chloroform, suggesting showering/bathing was a more important source than drinking. Conclusions: We identified several factors associated with blood THMs that may affect their metabolism. The potential health implications require further study. Citation: Riederer AM, Dhingra R, Blount BC, Steenland K. 2014. Predictors of blood trihalomethane concentrations in NHANES 1999–2006. Environ Health Perspect 122:695–702; http://dx.doi.org/10.1289/ehp.1306499 PMID:24647036

Are Polar Field Magnetic Flux Concentrations Responsible for Missing Interplanetary Flux?

NASA Astrophysics Data System (ADS)

Linker, Jon A.; Downs, C.; Mikic, Z.; Riley, P.; Henney, C. J.; Arge, C. N.

2012-05-01

Magnetohydrodynamic (MHD) simulations are now routinely used to produce models of the solar corona and inner heliosphere for specific time periods. These models typically use magnetic maps of the photospheric magnetic field built up over a solar rotation, available from a number of ground-based and space-based solar observatories. The line-of-sight field at the Sun's poles is poorly observed, and the polar fields in these maps are filled with a variety of interpolation/extrapolation techniques. These models have been found to frequently underestimate the interplanetary magnetic flux (Riley et al., 2012, in press, Stevens et al., 2012, in press) near the minimum part of the cycle unless mitigating correction factors are applied. Hinode SOT observations indicate that strong concentrations of magnetic flux may be present at the poles (Tsuneta et al. 2008). The ADAPT flux evolution model (Arge et al. 2010) also predicts the appearance of such concentrations. In this paper, we explore the possibility that these flux concentrations may account for a significant amount of magnetic flux and alleviate discrepancies in interplanetary magnetic flux predictions. Research supported by AFOSR, NASA, and NSF.

Environmental Factors and Seasonality Affect the Concentration of Rotundone in Vitis vinifera L. cv. Shiraz Wine

PubMed Central

Zhang, Pangzhen; Howell, Kate; Krstic, Mark; Herderich, Markus; Barlow, Edward William R.; Fuentes, Sigfredo

2015-01-01

Rotundone is a sesquiterpene that gives grapes and wine a desirable ‘peppery’ aroma. Previous research has reported that growing grapevines in a cool climate is an important factor that drives rotundone accumulation in grape berries and wine. This study used historical data sets to investigate which weather parameters are mostly influencing rotundone concentration in grape berries and wine. For this purpose, wines produced from 15 vintages from the same Shiraz vineyard (The Old Block, Mount Langi Ghiran, Victoria, Australia) were analysed for rotundone concentration and compared to comprehensive weather data and minimal temperature information. Degree hours were obtained by interpolating available temperature information from the vineyard site using a simple piecewise cubic hermite interpolating polynomial method (PCHIP). Results showed that the highest concentrations of rotundone were consistently found in wines from cool and wet seasons. The Principal Component Analysis (PCA) showed that the concentration of rotundone in wine was negatively correlated with daily solar exposure and grape bunch zone temperature, and positively correlated with vineyard water balance. Finally, models were constructed based on the Gompertz function to describe the dynamics of rotundone concentration in berries through the ripening process according to phenological and thermal times. This characterisation is an important step forward to potentially predict the final quality of the resultant wines based on the evolution of specific compounds in berries according to critical environmental and micrometeorological variables. The modelling techniques described in this paper were able to describe the behaviour of rotundone concentration based on seasonal weather conditions and grapevine phenological stages, and could be potentially used to predict the final rotundone concentration early in future growing seasons. This could enable the adoption of precision irrigation and canopy management strategies to effectively mitigate adverse impacts related to climate change and microclimatic variability, such as heat waves, within a vineyard on wine quality. PMID:26176692

Circulating branched-chain amino acid concentrations are associated with obesity and future insulin resistance in children and adolescents.

PubMed

McCormack, S E; Shaham, O; McCarthy, M A; Deik, A A; Wang, T J; Gerszten, R E; Clish, C B; Mootha, V K; Grinspoon, S K; Fleischman, A

2013-02-01

What is already known about this subject Circulating concentrations of branched-chain amino acids (BCAAs) can affect carbohydrate metabolism in skeletal muscle, and therefore may alter insulin sensitivity. BCAAs are elevated in adults with diet-induced obesity, and are associated with their future risk of type 2 diabetes even after accounting for baseline clinical risk factors. What this study adds Increased concentrations of BCAAs are already present in young obese children and their metabolomic profiles are consistent with increased BCAA catabolism. Elevations in BCAAs in children are positively associated with insulin resistance measured 18 months later, independent of their initial body mass index. Branched-chain amino acid (BCAA) concentrations are elevated in response to overnutrition, and can affect both insulin sensitivity and secretion. Alterations in their metabolism may therefore play a role in the early pathogenesis of type 2 diabetes in overweight children. To determine whether paediatric obesity is associated with elevations in fasting circulating concentrations of BCAAs (isoleucine, leucine and valine), and whether these elevations predict future insulin resistance. Sixty-nine healthy subjects, ages 8-18 years, were enrolled as a cross-sectional cohort. A subset of subjects who were pre- or early-pubertal, ages 8-13 years, were enrolled in a prospective longitudinal cohort for 18 months (n = 17 with complete data). Elevations in the concentrations of BCAAs were significantly associated with body mass index (BMI) Z-score (Spearman's Rho 0.27, P = 0.03) in the cross-sectional cohort. In the subset of subjects that followed longitudinally, baseline BCAA concentrations were positively associated with homeostasis model assessment for insulin resistance measured 18 months later after controlling for baseline clinical factors including BMI Z-score, sex and pubertal stage (P = 0.046). Elevations in the concentrations of circulating BCAAs are significantly associated with obesity in children and adolescents, and may independently predict future insulin resistance. © 2012 The Authors. Pediatric Obesity © 2012 International Association for the Study of Obesity.

Cerebrospinal Nematodiasis in 20 Camelids.

PubMed

Bertin, F R; Taylor, S D

2016-07-01

Information about the clinical and clinicopathologic aspects of cerebrospinal nematodiasis (CN) in camelids is limited. Clinical and therapeutic variables will be identified as factors predictive of survival. Client-owned camelids suspected of having CN admitted to Purdue University between 1995 and 2015. A retrospective study was performed. A diagnosis of CN was based on cerebrospinal fluid (CSF) eosinophilic pleocytosis or postmortem findings. Eleven alpacas and 9 llamas met the inclusion criteria. Seventy-five percent of the camelids were male (27% castrated and 73% intact). Common clinical abnormalities included proprioceptive deficits (100% of animals), recumbency (55%), tachypnea (55%), and ataxia (40%). Among the 85% of treated animals, 100% received PO fenbendazole, and 88% received a nonsteroidal anti-inflammatory drug. The survival rate to discharge was 45%. Plasma fibrinogen concentration, creatine kinase activity, and serum creatinine concentration were significantly higher in nonsurvivors. Blood eosinophil count, platelet count, and total CO2 were significantly lower in nonsurvivors. Factors associated with survival were species, sex, absence of treatment with corticosteroids, and clinical improvement. There was no association between recumbency at admission and survival. A plasma fibrinogen concentration above >266 mg/dL was an excellent diagnostic test to predict survival in the presence of neurological signs or CSF eosinophilia. Although prognosis for CN in camelids is guarded, presence of recumbency at admission is not predictive of nonsurvival. Male camelids and llamas appear more likely to die from CN. Corticosteroid treatment is contraindicated in animals diagnosed with CN. Copyright © 2016 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals, Inc. on behalf of the American College of Veterinary Internal Medicine.

Strong ion calculator--a practical bedside application of modern quantitative acid-base physiology.

PubMed

Lloyd, P

2004-12-01

To review acid-base balance by considering the physical effects of ions in solution and describe the use of a calculator to derive the strong ion difference and Atot and strong ion gap. A review of articles reporting on the use of strong ion difference and Atot in the interpretation of acid base balance. Tremendous progress has been made in the last decade in our understanding of acid-base physiology. We now have a quantitative understanding of the mechanisms underlying the acidity of an aqueous solution. We can now predict the acidity given information about the concentration of the various ion-forming species within it. We can predict changes in acid-base status caused by disturbance of these factors, and finally, we can detect unmeasured anions with greater sensitivity than was previously possible with the anion gap, using either arterial or venous blood sampling. Acid-base interpretation has ceased to be an intuitive and arcane art. Much of it is now an exact computation that can be automated and incorporated into an online hospital laboratory information system. All diseases and all therapies can affect a patient's acid-base status only through the final common pathway of one or more of the three independent factors. With Constable's equations we can now accurately predict the acidity of plasma. When there is a discrepancy between the observed and predicted acidity we can deduce the net concentration of unmeasured ions to account for the difference.

For Whom the Mind Wanders, and When, Varies Across Laboratory and Daily-Life Settings.

PubMed

Kane, Michael J; Gross, Georgina M; Chun, Charlotte A; Smeekens, Bridget A; Meier, Matt E; Silvia, Paul J; Kwapil, Thomas R

2017-09-01

Undergraduates ( N = 274) participated in a weeklong daily-life experience-sampling study of mind wandering after being assessed in the lab for executive-control abilities (working memory capacity; attention-restraint ability; attention-constraint ability; and propensity for task-unrelated thoughts, or TUTs) and personality traits. Eight times a day, electronic devices prompted subjects to report on their current thoughts and context. Working memory capacity and attention abilities predicted subjects' TUT rates in the lab, but predicted the frequency of daily-life mind wandering only as a function of subjects' momentary attempts to concentrate. This pattern replicates prior daily-life findings but conflicts with laboratory findings. Results for personality factors also revealed different associations in the lab and daily life: Only neuroticism predicted TUT rate in the lab, but only openness predicted mind-wandering rate in daily life (both predicted the content of daily-life mind wandering). Cognitive and personality factors also predicted dimensions of everyday thought other than mind wandering, such as subjective judgments of controllability of thought. Mind wandering in people's daily environments and TUTs during controlled and artificial laboratory tasks have different correlates (and perhaps causes). Thus, mind-wandering theories based solely on lab phenomena may be incomplete.

Analysis of factors predicting speed of hematologic recovery after transplantation with 4-hydroperoxycyclophosphamide-purged autologous bone marrow grafts.

PubMed

Rowley, S D; Piantadosi, S; Marcellus, D C; Jones, R J; Davidson, N E; Davis, J M; Kennedy, J; Wiley, J M; Wingard, J R; Yeager, A M

1991-03-01

We previously described the predictive value of graft colony-forming units granulocyte macrophage (CFU-GM) content after 4-hydroperoxycyclophosphamide (4-HC) purging for the duration of aplasia after autologous bone marrow transplantation. Despite the uniform 4-HC concentration, we observed heterogeneity in CFU-GM survival and the kinetics of engraftment. We have now analysed patient and graft characteristics for 154 patients undergoing autologous transplantation with 4-HC purged grafts to further define this heterogeneity. Patients transplanted for the treatment of malignant lymphoma reached a peripheral blood granulocyte count of greater than 0.5 x 10(9)/l (median, 20 versus 40 days; p less than 0.001) and platelet transfusion independence (median, 30 versus 70 days; p less than 0.001) significantly faster than patients transplanted for acute non-lymphoblastic leukemia. Other diagnostic groups were intermediate. These differences were independent of graft CFU-GM content. Multiple other patient and graft factors including patient age, peripheral blood counts on day of harvest, and amounts of other hematopoietic progenitors also predicted the kinetics of engraftment in univariate and multivariate analysis. Cytomegalovirus infection during the aplastic period predicted a delay in granulocyte (p = 0.024) but not platelet recovery (p = 0.174). This analysis demonstrates that multiple patient, graft, and post-transplant factors predict the engraftment capacity of autografts, and the kinetics of engraftment with 4-HC purged grafts. The multiple predictive factors explain a significant portion of the variability in engraftment kinetics observed after transplantation with 4-HC purged autografts.

Combined effects of pharmaceuticals, personal care products, biocides and organic contaminants on the growth of Skeletonema pseudocostatum.

PubMed

Petersen, Karina; Heiaas, Harald Hasle; Tollefsen, Knut Erik

2014-05-01

Organisms in the environment are exposed to a number of pollutants from different compound groups. In addition to the classic pollutants like the polychlorinated biphenyls, polyaromatic hydrocarbons (PAHs), alkylphenols, biocides, etc. other compound groups of concern are constantly emerging. Pharmaceuticals and personal care products (PPCPs) can be expected to co-occur with other organic contaminants like biocides, PAHs and alkylphenols in areas affected by wastewater, industrial effluents and intensive recreational activity. In this study, representatives from these four different compound groups were tested individually and in mixtures in a growth inhibition assay with the marine algae Skeletonema pseudocostatum (formerly Skeletonema costatum) to determine whether the combined effects could be predicted by models for additive effects; the concentration addition (CA) and independent action (IA) prediction model. The eleven tested compounds reduced the growth of S. pseudocostatum in the microplate test in a concentration-dependent manner. The order of toxicity of these chemicals were irgarol>fluoxetine>diuron>benzo(a)pyrene>thioguanine>triclosan>propranolol>benzophenone 3>cetrimonium bromide>4-tert-octylphenol>endosulfan. Several binary mixtures and a mixture of eight compounds from the four different compound groups were tested. All tested mixtures were additive as model deviation ratios, the deviation between experimental and predicted effect concentrations, were within a factor of 2 from one or both prediction models (e.g. CA and IA). Interestingly, a concentration dependent shift from IA to CA, potentially due to activation of similar toxicity pathways at higher concentrations, was observed for the mixture of eight compounds. The combined effects of the multi-compound mixture were clearly additive and it should therefore be expected that PPCPs, biocides, PAHs and alkylphenols will collectively contribute to the risk in areas contaminated by such complex mixtures. Copyright © 2014 Elsevier B.V. All rights reserved.

Effects of exposure, diet, and thermoregulation on fecal glucocorticoid measures in wild bears.

PubMed

Stetz, Jeff; Hunt, Kathleen; Kendall, Katherine C; Wasser, Samuel K

2013-01-01

We examined fecal glucocorticoid (fGC) measures of nutrition and thermoregulatory demands on wild bears in Glacier National Park, Montana, and assessed how these measures changed in samples left in the field. Both ambient temperature and exposure can impact thermoregulation and sample degradation. Bear diets vary markedly with season, affecting body condition and thus fGC. We collected fecal samples during September and October, 2001, when ambient temperatures ranged from 30°C to -5°C. We collected half of each sample immediately and left the other half in its original location for 1-28 days. We used generalized linear models (GLM) to first predict fGC concentrations in fresh samples based on proxies of nutrition, ambient temperature, thermal exposure, and precipitation. These same covariates were then used to predict degradation-based differences in fGC concentrations between the paired sample halves. Variation in fGC was predicted by diet, Julian date, aspect, and the interaction between Julian date and aspect in both fresh and exposed samples. Cumulative precipitation was also a significant predictor of fGC concentrations in the exposed samples, independent of time, indicating that precipitation contributes to sample degradation but not enough to mask effects of other environmental factors on fGC concentrations. Differences between sample halves were only predicted by cumulative precipitation and exposure time; cumulative precipitation decreased, whereas exposure time increased, fGC concentrations in the exposed sample halves. Results indicate that fGC can provide reliable indices of nutrition and thermoregulatory demands in bears and that sample degradation impacts on these relations are minimal and can be virtually eliminated by controlling for cumulative precipitation over the estimated exposure times.

Effects of Exposure, Diet, and Thermoregulation on Fecal Glucocorticoid Measures in Wild Bears

PubMed Central

Stetz, Jeff; Hunt, Kathleen; Kendall, Katherine C.; Wasser, Samuel K.

2013-01-01

We examined fecal glucocorticoid (fGC) measures of nutrition and thermoregulatory demands on wild bears in Glacier National Park, Montana, and assessed how these measures changed in samples left in the field. Both ambient temperature and exposure can impact thermoregulation and sample degradation. Bear diets vary markedly with season, affecting body condition and thus fGC. We collected fecal samples during September and October, 2001, when ambient temperatures ranged from 30°C to −5°C. We collected half of each sample immediately and left the other half in its original location for 1–28 days. We used generalized linear models (GLM) to first predict fGC concentrations in fresh samples based on proxies of nutrition, ambient temperature, thermal exposure, and precipitation. These same covariates were then used to predict degradation-based differences in fGC concentrations between the paired sample halves. Variation in fGC was predicted by diet, Julian date, aspect, and the interaction between Julian date and aspect in both fresh and exposed samples. Cumulative precipitation was also a significant predictor of fGC concentrations in the exposed samples, independent of time, indicating that precipitation contributes to sample degradation but not enough to mask effects of other environmental factors on fGC concentrations. Differences between sample halves were only predicted by cumulative precipitation and exposure time; cumulative precipitation decreased, whereas exposure time increased, fGC concentrations in the exposed sample halves. Results indicate that fGC can provide reliable indices of nutrition and thermoregulatory demands in bears and that sample degradation impacts on these relations are minimal and can be virtually eliminated by controlling for cumulative precipitation over the estimated exposure times. PMID:23457488

Prediction of size-fractionated airborne particle-bound metals using MLR, BP-ANN and SVM analyses.

PubMed

Leng, Xiang'zi; Wang, Jinhua; Ji, Haibo; Wang, Qin'geng; Li, Huiming; Qian, Xin; Li, Fengying; Yang, Meng

2017-08-01

Size-fractionated heavy metal concentrations were observed in airborne particulate matter (PM) samples collected from 2014 to 2015 (spanning all four seasons) from suburban (Xianlin) and industrial (Pukou) areas in Nanjing, a megacity of southeast China. Rapid prediction models of size-fractionated metals were established based on multiple linear regression (MLR), back propagation artificial neural network (BP-ANN) and support vector machine (SVM) by using meteorological factors and PM concentrations as input parameters. About 38% and 77% of PM 2.5 concentrations in Xianlin and Pukou, respectively, were beyond the Chinese National Ambient Air Quality Standard limit of 75 μg/m 3 . Nearly all elements had higher concentrations in industrial areas, and in winter among the four seasons. Anthropogenic elements such as Pb, Zn, Cd and Cu showed larger percentages in the fine fraction (ø≤2.5 μm), whereas the crustal elements including Al, Ba, Fe, Ni, Sr and Ti showed larger percentages in the coarse fraction (ø > 2.5 μm). SVM showed a higher training correlation coefficient (R), and lower mean absolute error (MAE) as well as lower root mean square error (RMSE), than MLR and BP-ANN for most metals. All the three methods showed better prediction results for Ni, Al, V, Cd and As, whereas relatively poor for Cr and Fe. The daily airborne metal concentrations in 2015 were then predicted by the fully trained SVM models and the results showed the heaviest pollution of airborne heavy metals occurred in December and January, whereas the lightest pollution occurred in June and July. Copyright © 2017 Elsevier Ltd. All rights reserved.

Specification and prediction of nickel mobilization using artificial intelligence methods

NASA Astrophysics Data System (ADS)

Gholami, Raoof; Ziaii, Mansour; Ardejani, Faramarz Doulati; Maleki, Shahoo

2011-12-01

Groundwater and soil pollution from pyrite oxidation, acid mine drainage generation, and release and transport of toxic metals are common environmental problems associated with the mining industry. Nickel is one toxic metal considered to be a key pollutant in some mining setting; to date, its formation mechanism has not yet been fully evaluated. The goals of this study are 1) to describe the process of nickel mobilization in waste dumps by introducing a novel conceptual model, and 2) to predict nickel concentration using two algorithms, namely the support vector machine (SVM) and the general regression neural network (GRNN). The results obtained from this study have shown that considerable amount of nickel concentration can be arrived into the water flow system during the oxidation of pyrite and subsequent Acid Drainage (AMD) generation. It was concluded that pyrite, water, and oxygen are the most important factors for nickel pollution generation while pH condition, SO4, HCO3, TDS, EC, Mg, Fe, Zn, and Cu are measured quantities playing significant role in nickel mobilization. SVM and GRNN have predicted nickel concentration with a high degree of accuracy. Hence, SVM and GRNN can be considered as appropriate tools for environmental risk assessment.

Accuracy of travel time distribution (TTD) models as affected by TTD complexity, observation errors, and model and tracer selection

USGS Publications Warehouse

Green, Christopher T.; Zhang, Yong; Jurgens, Bryant C.; Starn, J. Jeffrey; Landon, Matthew K.

2014-01-01

Analytical models of the travel time distribution (TTD) from a source area to a sample location are often used to estimate groundwater ages and solute concentration trends. The accuracies of these models are not well known for geologically complex aquifers. In this study, synthetic datasets were used to quantify the accuracy of four analytical TTD models as affected by TTD complexity, observation errors, model selection, and tracer selection. Synthetic TTDs and tracer data were generated from existing numerical models with complex hydrofacies distributions for one public-supply well and 14 monitoring wells in the Central Valley, California. Analytical TTD models were calibrated to synthetic tracer data, and prediction errors were determined for estimates of TTDs and conservative tracer (NO3−) concentrations. Analytical models included a new, scale-dependent dispersivity model (SDM) for two-dimensional transport from the watertable to a well, and three other established analytical models. The relative influence of the error sources (TTD complexity, observation error, model selection, and tracer selection) depended on the type of prediction. Geological complexity gave rise to complex TTDs in monitoring wells that strongly affected errors of the estimated TTDs. However, prediction errors for NO3− and median age depended more on tracer concentration errors. The SDM tended to give the most accurate estimates of the vertical velocity and other predictions, although TTD model selection had minor effects overall. Adding tracers improved predictions if the new tracers had different input histories. Studies using TTD models should focus on the factors that most strongly affect the desired predictions.

Investigation and modeling of the residential infiltration of fine particulate matter in Beijing, China.

PubMed

Xu, Chunyu; Li, Na; Yang, Yibing; Li, Yunpu; Liu, Zhe; Wang, Qin; Zheng, Tongzhang; Civitarese, Anna; Xu, Dongqun

2017-06-01

The objective of this study was to estimate the residential infiltration factor (Finf) of fine particulate matter (PM 2.5 ) and to develop models to predict PM 2.5 Finf in Beijing. Eighty-eight paired indoor-outdoor PM 2.5 samples were collected by Teflon filters for seven consecutive days during both non-heating and heating seasons (from a total of 55 families between August, 2013 and February, 2014). The mass concentrations of PM 2.5 were measured by gravimetric method, and elemental concentrations of sulfur in filter deposits were determined by energy-dispersive x-ray fluorescence (ED-XRF) spectrometry. PM 2.5 Finf was estimated as the indoor/outdoor sulfur ratio. Multiple linear regression was used to construct Finf predicting models. The residential PM 2.5 Finf in non-heating season (0.70 ± 0.21, median = 0.78, n = 43) was significantly greater than in heating season (0.54 ± 0.18, median = 0.52, n = 45, p < 0.001). Outdoor temperature, window width, frequency of window opening, and air conditioner use were the most important predictors during non-heating season, which could explain 57% variations across residences, while the outdoor temperature was the only predictor identified in heating season, which could explain 18% variations across residences. The substantial variations of PM 2.5 Finf between seasons and among residences found in this study highlight the importance of incorporating Finf into exposure assessment in epidemiological studies of air pollution and human health in Beijing. The Finf predicting models developed in this study hold promise for incorporating PM 2.5 Finf into large epidemiology studies, thereby reducing exposure misclassification. Failure to consider the differences between indoor and outdoor PM 2.5 may contribute to exposure misclassification in epidemiological studies estimating exposure from a central site measurement. This study was conducted in Beijing to investigate residential PM 2.5 infiltration factor and to develop a localized predictive model in both nonheating and heating seasons. High variations of PM 2.5 infiltration factor between the two seasons and across homes within each season were found, highlighting the importance of including infiltration factor in the assessment of exposure to PM 2.5 of outdoor origin in epidemiological studies. Localized predictive models for PM 2.5 infiltration factor were also developed.

Optimization of extraction of chitin from procambarus clarkia shell by Box-Behnken design

NASA Astrophysics Data System (ADS)

Dong, Fang; Qiu, Hailong; Jia, Shaoqian; Dai, Cuiping; Kong, Qingxin; Xu, Changliang

2018-06-01

This paper investigated the optimizing extraction processing of chitin from procambarus clarkia shell by Box-Behnken design. Firstly, four independent variables were explored in single factor experiments, namely, concentration of hydrochloric acid, soaking time, concentration of sodium hydroxide and reaction time. Then, based on the results of the above experiments, four factors and three levels experiments were planned by Box-Behnken design. According to the experimental results, we harvested a second-order polynomial equation using multiple regression analysis. In addition, the optimum extraction process of chitin of the model was obtained: concentration of HCl solution 1.54mol/L, soaking time 19.87h, concentration of NaOH solution 2.9mol/L and reaction time 3.54h. For proving the accuracy of the model, we finished the verification experiment under the following conditions: concentration of hydrochloric acid 1.5mol/L, soaking time 20h, concentration of sodium hydroxide 3mol/L and reaction time 3.5h. The actual yield of chitin reached 18.76%, which was very close to the predicted yield (18.66%) of the model. The result indicated that the optimum extraction processing of chitin was feasible and practical.

Delayed neuropsychological sequelae after carbon monoxide poisoning: predictive risk factors in the Emergency Department. A retrospective study.

PubMed

Pepe, Giuseppe; Castelli, Matteo; Nazerian, Peiman; Vanni, Simone; Del Panta, Massimo; Gambassi, Francesco; Botti, Primo; Missanelli, Andrea; Grifoni, Stefano

2011-03-17

Delayed neuropsychological sequelae (DNS) commonly occur after recovery from acute carbon monoxide (CO) poisoning. The preventive role and the indications for hyperbaric oxygen therapy in the acute setting are still controversial. Early identification of patients at risk in the Emergency Department might permit an improvement in quality of care. We conducted a retrospective study to identify predictive risk factors for DNS development in the Emergency Department. We retrospectively considered all CO-poisoned patients admitted to the Emergency Department of Careggi University General Hospital (Florence, Italy) from 1992 to 2007. Patients were invited to participate in three follow-up visits at one, six and twelve months from hospital discharge. Clinical and biohumoral data were collected; univariate and multivariate analysis were performed to identify predictive risk factors for DNS. Three hundred forty seven patients were admitted to the Emergency Department for acute CO poisoning from 1992 to 2007; 141/347 patients participated in the follow-up visit at one month from hospital discharge. Thirty four/141 patients were diagnosed with DNS (24.1%). Five/34 patients previously diagnosed as having DNS presented to the follow-up visit at six months, reporting a complete recovery. The following variables (collected before or upon Emergency Department admission) were associated to DNS development at one month from hospital discharge in the univariate analysis: CO exposure duration >6 hours, a Glasgow Coma Scale (GCS) score <9, seizures, systolic blood pressure <90 mmHg, elevated creatine phosphokinase concentration and leukocytosis. There was no significant correlation with age, sex, voluntary exposure, headache, transient loss of consciousness, GCS between 14 and 9, arterial lactate and carboxyhemoglobin concentration. The multivariate analysis confirmed as independent prognostic factors GCS <9 (OR 7.15; CI 95%: 1.04-48.8) and leukocytosis (OR 3.31; CI 95%: 1.02-10.71). Our study identified several potential predictive risk factors for DNS. Treatment algorithms based on an appropriate risk-stratification of patients in the Emergency Department might reduce DNS incidence; however, more studies are needed. Adequate follow-up after hospital discharge, aimed at correct recognition of DNS, is also important.

Delayed neuropsychological sequelae after carbon monoxide poisoning: predictive risk factors in the Emergency Department. A retrospective study

PubMed Central

2011-01-01

Background Delayed neuropsychological sequelae (DNS) commonly occur after recovery from acute carbon monoxide (CO) poisoning. The preventive role and the indications for hyperbaric oxygen therapy in the acute setting are still controversial. Early identification of patients at risk in the Emergency Department might permit an improvement in quality of care. We conducted a retrospective study to identify predictive risk factors for DNS development in the Emergency Department. Methods We retrospectively considered all CO-poisoned patients admitted to the Emergency Department of Careggi University General Hospital (Florence, Italy) from 1992 to 2007. Patients were invited to participate in three follow-up visits at one, six and twelve months from hospital discharge. Clinical and biohumoral data were collected; univariate and multivariate analysis were performed to identify predictive risk factors for DNS. Results Three hundred forty seven patients were admitted to the Emergency Department for acute CO poisoning from 1992 to 2007; 141/347 patients participated in the follow-up visit at one month from hospital discharge. Thirty four/141 patients were diagnosed with DNS (24.1%). Five/34 patients previously diagnosed as having DNS presented to the follow-up visit at six months, reporting a complete recovery. The following variables (collected before or upon Emergency Department admission) were associated to DNS development at one month from hospital discharge in the univariate analysis: CO exposure duration >6 hours, a Glasgow Coma Scale (GCS) score <9, seizures, systolic blood pressure <90 mmHg, elevated creatine phosphokinase concentration and leukocytosis. There was no significant correlation with age, sex, voluntary exposure, headache, transient loss of consciousness, GCS between 14 and 9, arterial lactate and carboxyhemoglobin concentration. The multivariate analysis confirmed as independent prognostic factors GCS <9 (OR 7.15; CI 95%: 1.04-48.8) and leukocytosis (OR 3.31; CI 95%: 1.02-10.71). Conclusions Our study identified several potential predictive risk factors for DNS. Treatment algorithms based on an appropriate risk-stratification of patients in the Emergency Department might reduce DNS incidence; however, more studies are needed. Adequate follow-up after hospital discharge, aimed at correct recognition of DNS, is also important. PMID:21414211

Integrated combined effects of temperature, pH and sodium chloride concentration on biofilm formation by Salmonella enterica ser. Enteritidis and Typhimurium under low nutrient food-related conditions.

PubMed

Iliadis, Ioannis; Daskalopoulou, Aikaterini; Simões, Manuel; Giaouris, Efstathios

2018-05-01

Salmonella enterica is a major foodborne bacterial pathogen. This forms biofilms on surfaces and persists, depending on the strain and the environment. The integrative interaction of temperature (T; 13-39 °C), pH (5-8) and sodium chloride (NaCl) concentration (0.5-8.5%) on biofilm formation by two S. enterica strains (ser. Enteritidis and Typhimurium) was here evaluated under low nutrient conditions. This was achieved using response surface methodology to model the combined effect of each factor on the response, through mathematical quadratic fitting of the outcomes of a sequence of designed experiments. These last were executed by incubating stainless steel coupons carrying sessile bacteria, for 24 h, in 1:10 diluted tryptone soya broth, under 15 different combinations of three independent factors (T, pH and NaCl). For each strain, a second order polynomial model, describing the relationship between biofilm formation (log CFU/cm 2 ) and the factors (T, pH and NaCl), was developed using least square regression analysis. Both derived models predicted the combined influences of these factors on biofilm formation, with agreement between predictions and experimental observations (R 2  ≥ 0.96, P ≤ 0.0001). For both strains, the increase of NaCl content restricted their sessile growth, while under low salinity conditions (NaCl < 4%) biofilm formation was favored as pH increased, regardless of T. Interestingly, under low salt content, and depending on the strain, biofilm formation was either favored or hindered by increasing T. Thus, 34.5 and 13 °C were the T predicted to maximize biofilm formation by strains Enteritidis and Typhimurium, respectively, something which was also experimentally verified. To sum, these models can predict the interactive influences of crucial food-related factors on biofilm growth of a significant foodborne pathogen towards the efforts to limit its persistence in food industry. Copyright © 2018 Elsevier Ltd. All rights reserved.

Atmospheric chemistry of ethane and ethylene

NASA Technical Reports Server (NTRS)

Aikin, A. C.; Herman, J. R.; Maier, E. J.; Mcquillan, C. J.

1982-01-01

It is shown by a study of ethane and ethylene photochemistry that the loss of ethane is controlled by OH in the troposphere and Cl in the stratosphere. Ethane observations indicating free Cl concentrations below 30 km that are only 10% of the value predicted by the present model calculations cannot be explained by heterogeneous aerosol concentration processes, and contradict current stratospheric photochemistry. The chemical destruction of ethane and ethylene leads to the generation of such compounds as carbon monoxide and formaldehyde, and it is found that the tropospheric concentrations of the latter are enhanced by nearly a factor of three for an ethylene mixing ratio of 2 ppb.

Individualized pharmacokinetic risk assessment for development of diabetes in high risk population.

PubMed

Gupta, N; Al-Huniti, N H; Veng-Pedersen, P

2007-10-01

The objective of this study is to propose a non-parametric pharmacokinetic prediction model that addresses the individualized risk of developing type-2 diabetes in subjects with family history of type-2 diabetes. All selected 191 healthy subjects had both parents as type-2 diabetic. Glucose was administered intravenously (0.5 g/kg body weight) and 13 blood samples taken at specified times were analyzed for plasma insulin and glucose concentrations. All subjects were followed for an average of 13-14 years for diabetic or normal (non-diabetic) outcome. The new logistic regression model predicts the development of diabetes based on body mass index and only one blood sample at 90 min analyzed for insulin concentration. Our model correctly identified 4.5 times more subjects (54% versus 11.6%) predicted to develop diabetes and more than twice the subjects (99% versus 46.4%) predicted not to develop diabetes compared to current non-pharmacokinetic probability estimates for development of type-2 diabetes. Our model can be useful for individualized prediction of development of type-2 diabetes in subjects with family history of type-2 diabetes. This improved prediction may be an important mediating factor for better perception of risk and may result in an improved intervention.

Predicting Salt Permeability Coefficients in Highly Swollen, Highly Charged Ion Exchange Membranes.

PubMed

Kamcev, Jovan; Paul, Donald R; Manning, Gerald S; Freeman, Benny D

2017-02-01

This study presents a framework for predicting salt permeability coefficients in ion exchange membranes in contact with an aqueous salt solution. The model, based on the solution-diffusion mechanism, was tested using experimental salt permeability data for a series of commercial ion exchange membranes. Equilibrium salt partition coefficients were calculated using a thermodynamic framework (i.e., Donnan theory), incorporating Manning's counterion condensation theory to calculate ion activity coefficients in the membrane phase and the Pitzer model to calculate ion activity coefficients in the solution phase. The model predicted NaCl partition coefficients in a cation exchange membrane and two anion exchange membranes, as well as MgCl 2 partition coefficients in a cation exchange membrane, remarkably well at higher external salt concentrations (>0.1 M) and reasonably well at lower external salt concentrations (<0.1 M) with no adjustable parameters. Membrane ion diffusion coefficients were calculated using a combination of the Mackie and Meares model, which assumes ion diffusion in water-swollen polymers is affected by a tortuosity factor, and a model developed by Manning to account for electrostatic effects. Agreement between experimental and predicted salt diffusion coefficients was good with no adjustable parameters. Calculated salt partition and diffusion coefficients were combined within the framework of the solution-diffusion model to predict salt permeability coefficients. Agreement between model and experimental data was remarkably good. Additionally, a simplified version of the model was used to elucidate connections between membrane structure (e.g., fixed charge group concentration) and salt transport properties.

Rapid development of xylanase assay conditions using Taguchi methodology.

PubMed

Prasad Uday, Uma Shankar; Bandyopadhyay, Tarun Kanti; Bhunia, Biswanath

2016-11-01

The present investigation is mainly concerned with the rapid development of extracellular xylanase assay conditions by using Taguchi methodology. The extracellular xylanase was produced from Aspergillus niger (KP874102.1), a new strain isolated from a soil sample of the Baramura forest, Tripura West, India. Four physical parameters including temperature, pH, buffer concentration and incubation time were considered as key factors for xylanase activity and were optimized using Taguchi robust design methodology for enhanced xylanase activity. The main effect, interaction effects and optimal levels of the process factors were determined using signal-to-noise (S/N) ratio. The Taguchi method recommends the use of S/N ratio to measure quality characteristics. Based on analysis of the S/N ratio, optimal levels of the process factors were determined. Analysis of variance (ANOVA) was performed to evaluate statistically significant process factors. ANOVA results showed that temperature contributed the maximum impact (62.58%) on xylanase activity, followed by pH (22.69%), buffer concentration (9.55%) and incubation time (5.16%). Predicted results showed that enhanced xylanase activity (81.47%) can be achieved with pH 2, temperature 50°C, buffer concentration 50 Mm and incubation time 10 min.

Concentrations and fate of decamethylcyclopentasiloxane (D(5)) in the atmosphere.

PubMed

McLachlan, Michael S; Kierkegaard, Amelie; Hansen, Kaj M; van Egmond, Roger; Christensen, Jesper H; Skjøth, Carsten A

2010-07-15

Decamethylcyclopentasiloxane (D(5)) is a volatile compound used in personal care products that is released to the atmosphere in large quantities. Although D(5) is currently under consideration for regulation, there have been no field investigations of its atmospheric fate. We employed a recently developed, quality assured method to measure D(5) concentration in ambient air at a rural site in Sweden. The samples were collected with daily resolution between January and June 2009. The D(5) concentration ranged from 0.3 to 9 ng m(-3), which is 1-3 orders of magnitude lower than previous reports. The measured data were compared with D(5) concentrations predicted using an atmospheric circulation model that included both OH radical and D(5) chemistry. The model was parametrized using emissions estimates and physical chemical properties determined in laboratory experiments. There was good agreement between the measured and modeled D(5) concentrations. The results show that D(5) is clearly subject to long-range atmospheric transport, but that it is also effectively removed from the atmosphere via phototransformation. Atmospheric deposition has little influence on the atmospheric fate. The good agreement between the model predictions and the field observations indicates that there is a good understanding of the major factors governing D(5) concentrations in the atmosphere.

Application of artificial intelligent tools to modeling of glucosamine preparation from exoskeleton of shrimp.

PubMed

Valizadeh, Hadi; Pourmahmood, Mohammad; Mojarrad, Javid Shahbazi; Nemati, Mahboob; Zakeri-Milani, Parvin

2009-04-01

The objective of this study was to forecast and optimize the glucosamine production yield from chitin (obtained from Persian Gulf shrimp) by means of genetic algorithm (GA), particle swarm optimization (PSO), and artificial neural networks (ANNs) as tools of artificial intelligence methods. Three factors (acid concentration, acid solution to chitin ratio, and reaction time) were used as the input parameters of the models investigated. According to the obtained results, the production yield of glucosamine hydrochloride depends linearly on acid concentration, acid solution to solid ratio, and time and also the cross-product of acid concentration and time and the cross-product of solids to acid solution ratio and time. The production yield significantly increased with an increase of acid concentration, acid solution ratio, and reaction time. The production yield is inversely related to the cross-product of acid concentration and time. It means that at high acid concentrations, the longer reaction times give lower production yields. The results revealed that the average percent error (PE) for prediction of production yield by GA, PSO, and ANN are 6.84, 7.11, and 5.49%, respectively. Considering the low PE, it might be concluded that these models have a good predictive power in the studied range of variables and they have the ability of generalization to unknown cases.

Predicting the probability of elevated nitrate concentrations in the Puget Sound Basin: Implications for aquifer susceptibility and vulnerability

USGS Publications Warehouse

Tesoriero, A.J.; Voss, F.D.

1997-01-01

The occurrence and distribution of elevated nitrate concentrations (≥ 3 mg/l) in ground water in the Puget Sound Basin, Washington, were determined by examining existing data from more than 3000 wells. Models that estimate the probability that a well has an elevated nitrate concentration were constructed by relating the occurrence of elevated nitrate concentrations to both natural and anthropogenic variables using logistic regression. The variables that best explain the occurrence of elevated nitrate concentrations were well depth, surficial geology, and the percentage of urban and agricultural land within a radius of 3.2 kilometers of the well. From these relations, logistic regression models were developed to assess aquifer susceptibility (relative ease with which contaminants will reach aquifer) and ground-water vulnerability (relative ease with which contaminants will reach aquifer for a given set of land-use practices). Both models performed well at predicting the probability of elevated nitrate concentrations in an independent data set. This approach to assessing aquifer susceptibility and ground-water vulnerability has the advantages of having both model variables and coefficient values determined on the basis of existing water quality information and does not depend on the assignment of variables and weighting factors based on qualitative criteria.

Climate change and predicting soil loss from rainfall

NASA Astrophysics Data System (ADS)

Kinnell, Peter

2017-04-01

Conceptually, rainfall has a certain capacity to cause soil loss from an eroding area while soil surfaces have a certain resistance to being eroded by rainfall. The terms "rainfall erosivity' and "soil erodibility" are frequently used to encapsulate the concept and in the Revised Universal Soil Loss Equation (RUSLE), the most widely used soil loss prediction equation in the world, average annual values of the R "erosivity" factor and the K "erodibility" factor provide a basis for accounting for variation in rainfall erosion associated with geographic variations of climate and soils. In many applications of RUSLE, R and K are considered to be independent but in reality they are not. In RUSLE2, provision has been made to take account of the fact that K values determined using soil physical factors have to be adjusted for variations in climate because runoff is not directly included as a factor in determining R. Also, the USLE event erosivity index EI30 is better related to accounting for event sediment concentration than event soil loss. While the USLE-M, a modification of the USLE which includes runoff as a factor in determining the event erosivity index provides better estimates of event soil loss when event runoff is known, runoff prediction provides a challenge to modelling event soil loss as climate changes

Controls on accumulation and soil solution partitioning of heavy metals across upland sites in United Kingdom (UK).

PubMed

Zia, Afia; van den Berg, Leon; Ahmad, Muhammad Nauman; Riaz, Muhammad; Zia, Dania; Ashmore, Mike

2018-05-31

A significant body of knowledge suggests that soil solution pH and dissolved organic carbon (DOC) strongly influence metal concentrations and speciation in porewater, however, these effects vary between different metals. This study investigated the factors influencing soil and soil solution concentrations of copper (Cu), lead (Pb), nickel (Ni) and zinc (Zn) under field conditions in upland soils from UK having a wide range of pH, DOC and organic matter contents. The study primarily focussed on predicting soil and soil solution metal concentrations from the data on total soil metal concentrations (HNO 3 extracts) and soil and soil solution properties (pH, DOC and organic matter content). We tested the multiple regression models proposed by Tipping et al. (2003) to predict heavy metal concentrations in soil solutions and the results indicated a better fit (higher R 2 values) in both studies for Pb compared to the Zn and Cu concentrations. Both studies observed consistent negative relationships of metals with pH and loss on ignition (LOI) suggesting an increase in soil solution metal concentrations with increasing acidity. The positive relationship between Pb concentrations in porewater and HNO 3 extracts was similar for both studies, however, similar relationships were not found for the Zn and Cu concentrations because of the negative coefficients for these metals in our study. The results of this study conclude that the predictive equations of Tipping et al. (2003) may not be applicable to the field sites where the range of DOC and metal concentrations is much lower than their study. Our study also suggests that the extent to which metals are partitioned into soil solution is lower in soils with a higher organic matter contents due to binding of these metals to soil organic matter. Copyright © 2018 Elsevier Ltd. All rights reserved.

An application of the NCRP screening techniques to atmospheric radon releases from the former Feed Materials Production Center near Fernald, Ohio

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, C.W.

1999-11-01

The National Council on Radiation Protection and Measurements has published a series of screening models for releases of radionuclides to the environment. These models have been used to prioritize radionuclides being considered in environmental dose reconstructions. The NCRP atmospheric models are also accepted by the U.S. Nuclear Regulatory Commission for demonstrating compliance with the constraint on releases of airborne radioactive materials to the environment from licenses other than power reactors. This study tested the NCRP atmospheric techniques by comparing annual average predicted air concentrations of radon with measured radon concentrations at 14 locations 43 m to 598 m downwind ofmore » the former US Department of Energy Feed Materials Production Center (FMPC) near Fernald, Ohio, for the period 2 July 1985 to 2 July 1986. Predictions were made using five different sets of meteorological data as input: (1) NCRP default values; (2) composite FMPC site data; (3) data from the Greater Cincinnati Airport; (4) data from the Dayton, Ohio, airport; and (5) data collected at Miami University, located near Oxford, Ohio. Following are the respective medians and ranges of the ratio of the predicted to observed annual radon air concentrations for each of these sources of meterological data: (1) 5.2, 0.9--54; (2) 1.4, 0.1--8.2; (3) 0.7, 0.1--7.2; (4) 0.7, 0.1--8.4; and (5) 0.6, 0.1--10. The stated goal of the NCRP models is to predict doses that do not underpredict actual doses by greater than a factor of 10. In this comparison, all of the meteorological data produced air concentration predictions that meet this criteria. However, to ensure that final doses meet this criterion, one would need to carefully evaluate all assumptions used to calculate dose from each of these air concentrations.« less

Relevance analysis and short-term prediction of PM2.5 concentrations in Beijing based on multi-source data

NASA Astrophysics Data System (ADS)

Ni, X. Y.; Huang, H.; Du, W. P.

2017-02-01

The PM2.5 problem is proving to be a major public crisis and is of great public-concern requiring an urgent response. Information about, and prediction of PM2.5 from the perspective of atmospheric dynamic theory is still limited due to the complexity of the formation and development of PM2.5. In this paper, we attempted to realize the relevance analysis and short-term prediction of PM2.5 concentrations in Beijing, China, using multi-source data mining. A correlation analysis model of PM2.5 to physical data (meteorological data, including regional average rainfall, daily mean temperature, average relative humidity, average wind speed, maximum wind speed, and other pollutant concentration data, including CO, NO2, SO2, PM10) and social media data (microblog data) was proposed, based on the Multivariate Statistical Analysis method. The study found that during these factors, the value of average wind speed, the concentrations of CO, NO2, PM10, and the daily number of microblog entries with key words 'Beijing; Air pollution' show high mathematical correlation with PM2.5 concentrations. The correlation analysis was further studied based on a big data's machine learning model- Back Propagation Neural Network (hereinafter referred to as BPNN) model. It was found that the BPNN method performs better in correlation mining. Finally, an Autoregressive Integrated Moving Average (hereinafter referred to as ARIMA) Time Series model was applied in this paper to explore the prediction of PM2.5 in the short-term time series. The predicted results were in good agreement with the observed data. This study is useful for helping realize real-time monitoring, analysis and pre-warning of PM2.5 and it also helps to broaden the application of big data and the multi-source data mining methods.

An application of the NCRP screening techniques to atmospheric radon releases from the former feed materials production center near Fernald, Ohio. National Council on Radiation Protection and Measurements.

PubMed

Miller, C W

1999-11-01

The National Council on Radiation Protection and Measurements has published a series of screening models for releases of radionuclides to the environment. These models have been used to prioritize radionuclides being considered in environmental dose reconstructions. The NCRP atmospheric models are also accepted by the U.S. Nuclear Regulatory Commission for demonstrating compliance with the constraint on releases of airborne radioactive materials to the environment from licensees other than power reactors. This study tested the NCRP atmospheric techniques by comparing annual average predicted air concentrations of radon with measured radon concentrations at 14 locations 43 m to 598 m downwind of the former U.S. Department of Energy Feed Materials Production Center (FMPC) near Fernald, Ohio, for the period 2 July 1985 to 2 July 1986. Predictions were made using five different sets of meteorological data as input: (1) NCRP default values; (2) composite FMPC site data; (3) data from the Greater Cincinnati Airport; (4) data from the Dayton, Ohio, airport; and (5) data collected at Miami University, located near Oxford, Ohio. Following are the respective medians and ranges of the ratio of the predicted to observed annual radon air concentrations for each of these sources of meteorological data: (1) 5.2, 0.9-54; (2) 1.4, 0.1-8.2; (3) 0.7, 0.1-7.2; (4) 0.7, 0.1-8.4; and (5) 0.6, 0.1-10. The stated goal of the NCRP models is to predict doses that do not underpredict actual doses by greater than a factor of 10. In this comparison, all of the meteorological data produced air concentration predictions that meet this criteria. However, to ensure that final doses meet this criterion, one would need to carefully evaluate all assumptions used to calculate dose from each of these air concentrations.

Multiple factors impact the contents of heavy metals in vegetables in high natural background area of China.

PubMed

Gan, Yandong; Wang, Lihong; Yang, Guiqiang; Dai, Jiulan; Wang, Renqing; Wang, Wenxing

2017-10-01

A field survey was conducted to investigate the concentrations of chromium (Cr), nickel (Ni), copper (Cu), zinc (Zn), cadmium (Cd) and lead (Pb) in vegetables, corresponding cultivated soils and irrigation waters from 36 open sites in high natural background area of Wuzhou, South China. Redundancy analysis, Spearman's rho correlation analysis and multiple regression analysis were adopted to evaluate the contributions of impacting factors on metal contents in the edible parts of vegetables. This study concluded that leafy and root vegetables had relatively higher metal concentrations and adjusted transfer factor values compared to fruiting vegetables according to nonparametric tests. Plant species, total soil metal content and soil pH value were affirmed as three critical factors with the highest contribution rate among all the influencing factors. The bivariate curve equation models for heavy metals in the edible vegetable tissues were well fitted to predict the metal concentrations in vegetables. The results from this case study also suggested that it could be one of efficient strategies for clean agricultural production and food safety in high natural background area to breed vegetable varieties with low heavy metal accumulation and to enlarge planting scale of these varieties. Copyright © 2017 Elsevier Ltd. All rights reserved.

Proliferation kinetics and cyclic AMP as prognostic factors in adult acute leukemia.

PubMed

Paietta, E; Mittermayer, K; Schwarzmeier, J

1980-07-01

In 41 adult patients with acute leukemia (myeloblastic, lymphoblastic, and undifferentiated), proliferation kinetics (as determined by double-label autoradiography) and cyclic adenosine 3',5'-monophosphate (cAMP) concentration were studied for their significance in the prediction of responsiveness to cytostatic therapy. Patients with good clinical response had significantly shorter turnover times and higher labeling indices in the bone marrow than did those who failed to respond to treatment. Cases for which cell kinetics did not correlate with clinical response were explained by variance in the distribution of leukemic blasts between the proliferative cell cycle and the resting pool. Good clinical response was also found to be associated with low levels of cAMP in leukemic cells prior to therapy, whereas high cAMP contents predicted failure. Low cAMP concentrations, however, did not necessarily correlate with short turnover times and vice versa. This might be due to fluctuations of the cAMP concentrations during the cell cycle.

Improving emissions inventories in Mexico through systematic analysis of model performance along C-130 and DC-8 flight tracks during MILAGRO

NASA Astrophysics Data System (ADS)

Mena-Carrasco, M.; Carmichael, G. R.; Campbell, J. E.; Tang, Y.; Chai, T.

2007-05-01

During the MILAGRO campaign in March 2006 the University of Iowa provided regional air quality forecasting for scientific flight planning for the C-130 and DC-8. Model performance showed positive bias of ozone prediction (~15ppbv), associated to overpredictions in precursor concentrations (~2.15 ppbv NOy and ~1ppmv ARO1). Model bias showed a distinct geographical pattern in which the higher values were in and near Mexico City. Newer runs in which NOx and VOC emissions were decreased improved ozone prediction, decreasing bias and increasing model correlation, at the same time reducing regional bias over Mexico. This work will evaluate model performance using the newly published Mexico National Emissions Inventory, and the introduction of data assimilation to recover emissions scaling factors to optimize model performance. Finally the results of sensitivity runs showing the regional impact of Mexico City emissions on ozone concentrations will be shown, along with the influence of Mexico City aerosol concentrations on regional photochemistry.

Numerical modeling of field-assisted ion-exchanged channel waveguides by the explicit consideration of space-charge buildup.

PubMed

Mrozek, Piotr

2011-08-01

A numerical model explicitly considering the space-charge density evolved both under the mask and in the region of optical structure formation was used to predict the profiles of Ag concentration during field-assisted Ag(+)-Na(+) ion exchange channel waveguide fabrication. The influence of the unequal values of diffusion constants and mobilities of incoming and outgoing ions, the value of a correlation factor (Haven ratio), and particularly space-charge density induced during the ion exchange, on the resulting profiles of Ag concentration was analyzed and discussed. It was shown that the incorporation into the numerical model of a small quantity of highly mobile ions other than exclusively Ag(+) and Na(+) may considerably affect the range and shape of calculated Ag profiles in the multicomponent glass. The Poisson equation was used to predict the electric field spread evolution in the glass substrate. The results of the numerical analysis were verified by the experimental data of Ag concentration in a channel waveguide fabricated using a field-assisted process.

Evidence for the role of copper in the injury process of coliform bacteria in drinking water. [Escherichia coli

DOE Office of Scientific and Technical Information (OSTI.GOV)

Domek, M.J.; LeChevallier, M.W.; Cameron, S.C.

1984-08-01

Low levels of copper in chlorine-free distribution water caused injury of coliform populations. Monitoring of 44 drinking water samples indicated that 64% of the coliform population was injured. Physical and chemical parameters were measured, including three heavy metals (Cu, Cd, and Pb). Copper concentrations were important, ranging from 0.007 to 0.54 mg/liter. Statistical analyses of these factors were used to develop a model to predict coliform injury. The model predicted almost 90% injury with a copper concentration near the mean observed value (0.158 mg/liter) in distribution waters. Laboratory studies with copper concentrations of 0.025 and 0.050 mg/liter in an inorganicmore » carbon buffer under controlled conditions of temperature and pH caused over 90% injury within 6 and 2 days, respectively. Studies of the metabolism of injured Escherichia coli cells indicated that the respiratory chain is at least one site of damage in injured cells.« less

Glycated Hemoglobin Measurement and Prediction of Cardiovascular Disease

PubMed Central

Angelantonio, Emanuele Di; Gao, Pei; Khan, Hassan; Butterworth, Adam S.; Wormser, David; Kaptoge, Stephen; Kondapally Seshasai, Sreenivasa Rao; Thompson, Alex; Sarwar, Nadeem; Willeit, Peter; Ridker, Paul M; Barr, Elizabeth L.M.; Khaw, Kay-Tee; Psaty, Bruce M.; Brenner, Hermann; Balkau, Beverley; Dekker, Jacqueline M.; Lawlor, Debbie A.; Daimon, Makoto; Willeit, Johann; Njølstad, Inger; Nissinen, Aulikki; Brunner, Eric J.; Kuller, Lewis H.; Price, Jackie F.; Sundström, Johan; Knuiman, Matthew W.; Feskens, Edith J. M.; Verschuren, W. M. M.; Wald, Nicholas; Bakker, Stephan J. L.; Whincup, Peter H.; Ford, Ian; Goldbourt, Uri; Gómez-de-la-Cámara, Agustín; Gallacher, John; Simons, Leon A.; Rosengren, Annika; Sutherland, Susan E.; Björkelund, Cecilia; Blazer, Dan G.; Wassertheil-Smoller, Sylvia; Onat, Altan; Marín Ibañez, Alejandro; Casiglia, Edoardo; Jukema, J. Wouter; Simpson, Lara M.; Giampaoli, Simona; Nordestgaard, Børge G.; Selmer, Randi; Wennberg, Patrik; Kauhanen, Jussi; Salonen, Jukka T.; Dankner, Rachel; Barrett-Connor, Elizabeth; Kavousi, Maryam; Gudnason, Vilmundur; Evans, Denis; Wallace, Robert B.; Cushman, Mary; D’Agostino, Ralph B.; Umans, Jason G.; Kiyohara, Yutaka; Nakagawa, Hidaeki; Sato, Shinichi; Gillum, Richard F.; Folsom, Aaron R.; van der Schouw, Yvonne T.; Moons, Karel G.; Griffin, Simon J.; Sattar, Naveed; Wareham, Nicholas J.; Selvin, Elizabeth; Thompson, Simon G.; Danesh, John

2015-01-01

IMPORTANCE The value of measuring levels of glycated hemoglobin (HbA1c) for the prediction of first cardiovascular events is uncertain. OBJECTIVE To determine whether adding information on HbA1c values to conventional cardiovascular risk factors is associated with improvement in prediction of cardiovascular disease (CVD) risk. DESIGN, SETTING, AND PARTICIPANTS Analysis of individual-participant data available from 73 prospective studies involving 294 998 participants without a known history of diabetes mellitus or CVD at the baseline assessment. MAIN OUTCOMES AND MEASURES Measures of risk discrimination for CVD outcomes (eg, C-index) and reclassification (eg, net reclassification improvement) of participants across predicted 10-year risk categories of low (<5%), intermediate (5%to <7.5%), and high (≥7.5%) risk. RESULTS During a median follow-up of 9.9 (interquartile range, 7.6-13.2) years, 20 840 incident fatal and nonfatal CVD outcomes (13 237 coronary heart disease and 7603 stroke outcomes) were recorded. In analyses adjusted for several conventional cardiovascular risk factors, there was an approximately J-shaped association between HbA1c values and CVD risk. The association between HbA1c values and CVD risk changed only slightly after adjustment for total cholesterol and triglyceride concentrations or estimated glomerular filtration rate, but this association attenuated somewhat after adjustment for concentrations of high-density lipoprotein cholesterol and C-reactive protein. The C-index for a CVD risk prediction model containing conventional cardiovascular risk factors alone was 0.7434 (95% CI, 0.7350 to 0.7517). The addition of information on HbA1c was associated with a C-index change of 0.0018 (0.0003 to 0.0033) and a net reclassification improvement of 0.42 (−0.63 to 1.48) for the categories of predicted 10-year CVD risk. The improvement provided by HbA1c assessment in prediction of CVD risk was equal to or better than estimated improvements for measurement of fasting, random, or postload plasma glucose levels. CONCLUSIONS AND RELEVANCE In a study of individuals without known CVD or diabetes, additional assessment of HbA1c values in the context of CVD risk assessment provided little incremental benefit for prediction of CVD risk. PMID:24668104

Individual and community risk factors and sexually transmitted diseases among arrested youths: a two level analysis.

PubMed

Dembo, Richard; Belenko, Steven; Childs, Kristina; Wareham, Jennifer; Schmeidler, James

2009-08-01

High rates of infection for chlamydia and gonorrhea have been noted among youths involved in the juvenile justice system. Although both individual and community-level factors have been found to be associated with sexually transmitted disease (STD) risk, their relative importance has not been tested in this population. A two-level logistic regression analysis was completed to assess the influence of individual-level and community-level predictors on STD test results among arrested youths processed at a centralized intake facility. Results from weighted two level logistic regression analyses (n = 1,368) indicated individual-level factors of gender (being female), age, race (being African American), and criminal history predicted the youths' positive STD status. For the community-level predictors, concentrated disadvantage significantly and positively predicted the youths' STD status. Implications of these findings for future research and public health policy are discussed.

Space Shuttle ice nuclei

NASA Astrophysics Data System (ADS)

Turco, R. P.; Toon, O. B.; Whitten, R. C.; Cicerone, R. J.

1982-08-01

Estimates are made showing that, as a consequence of rocket activity in the earth's upper atmosphere in the Shuttle era, average ice nuclei concentrations in the upper atmosphere could increase by a factor of two, and that an aluminum dust layer weighing up to 1000 tons might eventually form in the lower atmosphere. The concentrations of Space Shuttle ice nuclei (SSIN) in the upper troposphere and lower stratosphere were estimated by taking into account the composition of the particles, the extent of surface poisoning, and the size of the particles. Calculated stratospheric size distributions at 20 km with Space Shuttle particulate injection, calculated SSIN concentrations at 10 and 20 km altitude corresponding to different water vapor/ice supersaturations, and predicted SSIN concentrations in the lower stratosphere and upper troposphere are shown.

Enhanced power factor of higher manganese silicide via melt spin synthesis method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shi, Xiaoya; Li, Qiang, E-mail: liqiang@bnl.gov; Shi, Xun

We report on the thermoelectric properties of the higher manganese silicide MnSi{sub 1.75} synthesized by means of a one-step non-equilibrium method. The ultrahigh cooling rate generated from the melt-spin technique is found to be effective in reducing second phases, which are inevitable during the traditional solid state diffusion processes. Aside from being detrimental to thermoelectric properties, second phases skew the revealing of the intrinsic properties of this class of materials, for example, the optimal level of carrier concentration. With this melt-spin sample, we are able to formulate a simple model based on a single parabolic band that can well describemore » the carrier concentration dependence of the Seebeck coefficient and power factor of the data reported in the literature. An optimal carrier concentration around 5 × 10{sup 20 }cm{sup −3} at 300 K is predicted according to this model. The phase-pure melt-spin sample shows the largest power factor at high temperature, resulting in the highest zT value among the three samples in this paper.« less

Quality factor of luminescent solar concentrators and practical concentration limits attainable with semiconductor quantum dots

DOE PAGES

Klimov, Victor I.; Baker, Thomas A.; Lim, Jaehoon; ...

2016-05-09

In this study, luminescent solar concentrators (LSCs) can be utilized as both large-area collectors of solar radiation supplementing traditional photovoltaic cells as well as semitransparent “solar windows” that provide a desired degree of shading and simultaneously serve as power-generation units. An important characteristic of an LSC is a concentration factor (C) that can be thought of as a coefficient of effective enlargement (or contraction) of the area of a solar cell when it is coupled to the LSC. Here we use analytical and numerical Monte Carlo modeling in addition to experimental studies of quantum-dot-based LSCs to analyze the factors thatmore » influence optical concentration in practical devices. Our theoretical model indicates that the maximum value of C achievable with a given fluorophore is directly linked to the LSC quality factor (Q LSC) defined as the ratio of absorption coefficients at the wavelengths of incident and reemitted light. In fact, we demonstrate that the ultimate concentration limit (C 0) realized in large-area devices scales linearly with the LSC quality factor and in the case of perfect emitters and devices without back reflectors is approximately equal to Q LSC. To test the predictions of this model, we conduct experimental studies of LSCs based on visible-light emitting II–VI core/shell quantum dots with two distinct LSC quality factors. We also investigate devices based on near-infrared emitting CuInSe xS 2–x quantum dots for which the large emission bandwidth allows us to assess the impact of varied Q LSC on the concentration factor by simply varying the detection wavelength. In all cases, we find an excellent agreement between the model and the experimental observations, suggesting that the developed formalism can be utilized for express evaluation of prospective LSC performance based on the optical spectra of LSC fluorophores, which should facilitate future efforts on the development of high-performance devices based on quantum dots as well as other types of emitters.« less

Quality factor of luminescent solar concentrators and practical concentration limits attainable with semiconductor quantum dots

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klimov, Victor I.; Baker, Thomas A.; Lim, Jaehoon

In this study, luminescent solar concentrators (LSCs) can be utilized as both large-area collectors of solar radiation supplementing traditional photovoltaic cells as well as semitransparent “solar windows” that provide a desired degree of shading and simultaneously serve as power-generation units. An important characteristic of an LSC is a concentration factor (C) that can be thought of as a coefficient of effective enlargement (or contraction) of the area of a solar cell when it is coupled to the LSC. Here we use analytical and numerical Monte Carlo modeling in addition to experimental studies of quantum-dot-based LSCs to analyze the factors thatmore » influence optical concentration in practical devices. Our theoretical model indicates that the maximum value of C achievable with a given fluorophore is directly linked to the LSC quality factor (Q LSC) defined as the ratio of absorption coefficients at the wavelengths of incident and reemitted light. In fact, we demonstrate that the ultimate concentration limit (C 0) realized in large-area devices scales linearly with the LSC quality factor and in the case of perfect emitters and devices without back reflectors is approximately equal to Q LSC. To test the predictions of this model, we conduct experimental studies of LSCs based on visible-light emitting II–VI core/shell quantum dots with two distinct LSC quality factors. We also investigate devices based on near-infrared emitting CuInSe xS 2–x quantum dots for which the large emission bandwidth allows us to assess the impact of varied Q LSC on the concentration factor by simply varying the detection wavelength. In all cases, we find an excellent agreement between the model and the experimental observations, suggesting that the developed formalism can be utilized for express evaluation of prospective LSC performance based on the optical spectra of LSC fluorophores, which should facilitate future efforts on the development of high-performance devices based on quantum dots as well as other types of emitters.« less

Usefulness of serum interleukin-18 in predicting cardiovascular mortality in patients with chronic kidney disease--systems and clinical approach.

PubMed

Formanowicz, Dorota; Wanic-Kossowska, Maria; Pawliczak, Elżbieta; Radom, Marcin; Formanowicz, Piotr

2015-12-16

The aim of this study was to check if serum interleukin-18 (IL-18) predicts 2-year cardiovascular mortality in patients at various stages of chronic kidney disease (CKD) and history of acute myocardial infarction (AMI) within the previous year. Diabetes mellitus was one of the key factors of exclusion. It was found that an increase in serum concentration of IL-18 above the cut-off point (1584.5 pg/mL) was characterized by 20.63-fold higher risk of cardiovascular deaths among studied patients. IL-18 serum concentration was found to be superior to the well-known cardiovascular risk parameters, like high sensitivity C-reactive protein (hsCRP), carotid intima media thickness (CIMT), glomerular filtration rate, albumins, ferritin, N-terminal prohormone of brain natriuretic peptide (NT-proBNP) in prognosis of cardiovascular mortality. The best predictive for IL-18 were 4 variables, such as CIMT, NT-proBNP, albumins and hsCRP, as they predicted its concentration at 89.5%. Concluding, IL-18 seems to be important indicator and predictor of cardiovascular death in two-year follow-up among non-diabetic patients suffering from CKD, with history of AMI in the previous year. The importance of IL-18 in the process of atherosclerotic plaque formation has been confirmed by systems analysis based on a formal model expressed in the language of Petri nets theory.

The Constraints, Construction, and Verification of a Strain-Specific Physiologically Based Pharmacokinetic Rat Model.

PubMed

Musther, Helen; Harwood, Matthew D; Yang, Jiansong; Turner, David B; Rostami-Hodjegan, Amin; Jamei, Masoud

2017-09-01

The use of in vitro-in vivo extrapolation (IVIVE) techniques, mechanistically incorporated within physiologically based pharmacokinetic (PBPK) models, can harness in vitro drug data and enhance understanding of in vivo pharmacokinetics. This study's objective was to develop a user-friendly rat (250 g, male Sprague-Dawley) IVIVE-linked PBPK model. A 13-compartment PBPK model including mechanistic absorption models was developed, with required system data (anatomical, physiological, and relevant IVIVE scaling factors) collated from literature and analyzed. Overall, 178 system parameter values for the model are provided. This study also highlights gaps in available system data required for strain-specific rat PBPK model development. The model's functionality and performance were assessed using previous literature-sourced in vitro properties for diazepam, metoprolol, and midazolam. The results of simulations were compared against observed pharmacokinetic rat data. Predicted and observed concentration profiles in 10 tissues for diazepam after a single intravenous (i.v.) dose making use of either observed i.v. clearance (CL iv ) or in vitro hepatocyte intrinsic clearance (CL int ) for simulations generally led to good predictions in various tissue compartments. Overall, all i.v. plasma concentration profiles were successfully predicted. However, there were challenges in predicting oral plasma concentration profiles for metoprolol and midazolam, and the potential reasons and according solutions are discussed. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Maps of estimated nitrate and arsenic concentrations in basin-fill aquifers of the southwestern United States

USGS Publications Warehouse

Beisner, Kimberly R.; Anning, David W.; Paul, Angela P.; McKinney, Tim S.; Huntington, Jena M.; Bexfield, Laura M.; Thiros, Susan A.

2012-01-01

Human-health concerns and economic considerations associated with meeting drinking-water standards motivated a study of the vulnerability of basin-fill aquifers to nitrate contamination and arsenic enrichment in the southwestern United States. Statistical models were developed by using the random forest classifier algorithm to predict concentrations of nitrate and arsenic across a model grid representing about 190,600 square miles of basin-fill aquifers in parts of Arizona, California, Colorado, Nevada, New Mexico, and Utah. The statistical models, referred to as classifiers, reflect natural and human-related factors that affect aquifer vulnerability to contamination and relate nitrate and arsenic concentrations to explanatory variables representing local- and basin-scale measures of source and aquifer susceptibility conditions. Geochemical variables were not used in concentration predictions because they were not available for the entire study area. The models were calibrated to assess model accuracy on the basis of measured values.Only 2 percent of the area underlain by basin-fill aquifers in the study area was predicted to equal or exceed the U.S. Environmental Protection Agency drinking-water standard for nitrate as N (10 milligrams per liter), whereas 43 percent of the area was predicted to equal or exceed the standard for arsenic (10 micrograms per liter). Areas predicted to equal or exceed the drinking-water standard for nitrate include basins in central Arizona near Phoenix; the San Joaquin Valley, the Santa Ana Inland, and San Jacinto Basins of California; and the San Luis Valley of Colorado. Much of the area predicted to equal or exceed the drinking-water standard for arsenic is within a belt of basins along the western portion of the Basin and Range Physiographic Province that includes almost all of Nevada and parts of California and Arizona. Predicted nitrate and arsenic concentrations are substantially lower than the drinking-water standards in much of the study area-about 93 percent of the area underlain by basin-fill aquifers was less than one-half the standard for nitrate as N (5.0 milligrams per liter), and 50 percent was less than one-half the standard for arsenic (5.0 micrograms per liter). The predicted concentrations and the improved understanding of the susceptibility and vulnerability of southwestern basin-fill aquifers to nitrate contamination and arsenic enrichment can be used by water managers as a qualitative tool to assess and protect the quality of groundwater resources in the Southwest.

Description of Aspergillus flavus growth under the influence of different factors (water activity, incubation temperature, protein and fat concentration, pH, and cinnamon essential oil concentration) by kinetic, probability of growth, and time-to-detection models.

PubMed

Kosegarten, Carlos E; Ramírez-Corona, Nelly; Mani-López, Emma; Palou, Enrique; López-Malo, Aurelio

2017-01-02

A Box-Behnken design was used to determine the effect of protein concentration (0, 5, or 10g of casein/100g), fat (0, 3, or 6g of corn oil/100g), a w (0.900, 0.945, or 0.990), pH (3.5, 5.0, or 6.5), concentration of cinnamon essential oil (CEO, 0, 200, or 400μL/kg) and incubation temperature (15, 25, or 35°C) on the growth of Aspergillus flavus during 50days of incubation. Mold response under the evaluated conditions was modeled by the modified Gompertz equation, logistic regression, and time-to-detection model. The obtained polynomial regression models allow the significant coefficients (p<0.05) for linear, quadratic and interaction effects for the Gompertz equation's parameters to be identified, which adequately described (R 2 >0.967) the studied mold responses. After 50days of incubation, every tested model system was classified according to the observed response as 1 (growth) or 0 (no growth), then a binary logistic regression was utilized to model A. flavus growth interface, allowing to predict the probability of mold growth under selected combinations of tested factors. The time-to-detection model was utilized to estimate the time at which A. flavus visible growth begins. Water activity, temperature, and CEO concentration were the most important factors affecting fungal growth. It was observed that there is a range of possible combinations that may induce growth, such that incubation conditions and the amount of essential oil necessary for fungal growth inhibition strongly depend on protein and fat concentrations as well as on the pH of studied model systems. The probabilistic model and the time-to-detection models constitute another option to determine appropriate storage/processing conditions and accurately predict the probability and/or the time at which A. flavus growth occurs. Copyright © 2016 Elsevier B.V. All rights reserved.

Hot flashes are not predictive for serum concentrations of tamoxifen and its metabolites

PubMed Central

2013-01-01

Background Tamoxifen has dramatically reduced the recurrence and mortality rate of estrogen receptor positive breast cancer. However, the efficacy of tamoxifen varies between individuals and 40% of patients will have a recurrence despite adjuvant tamoxifen treatment. Factors that predict tamoxifen efficacy would be helpful for optimizing treatment. Serum concentrations of the active metabolite, endoxifen, may be positively related to treatment outcome. In addition, hot flashes are suggested to be positively associated with tamoxifen treatment outcome. Methods We investigated in a series of 109 patients whether the frequency and severity of hot flashes were related to concentrations of tamoxifen and its metabolites. A serum sample of all patients was analyzed for the concentration of tamoxifen, N-desmethyltamoxifen, endoxifen and 4-hydroxytamoxifen, as well as for estradiol concentrations and several single nucleotide polymorphisms in CYP2D6. Additionally, these patients completed a questionnaire concerning biometric data and treatment side effects. Results We found no evidence supporting an association between concentrations of tamoxifen or metabolites and either the frequency or severity of hot flashes in the covariate unadjusted analyses. However, including interactions with menopausal status and pre-treatment hot flash (PTHF) history indicated that post-menopausal women with PTHF experienced an increasing frequency of hot flashes with increasing serum concentrations of tamoxifen and its metabolites. This finding was not altered when adjusting for potential confounding factors (duration of tamoxifen treatment, CYP2D6 phenotype, estradiol serum concentration, age and body mass index). In addition we observed a positive association between body mass index and both hot flash frequency (p = 0.04) and severity (p < 0.0001). We also observed that patients with lower estradiol levels reported more severe hot flashes (p = 0.02). Conclusions No univariate associations were observed between concentrations of active tamoxifen metabolites and either the frequency or severity of hot flashes during treatment. However, the frequency of hot flashes may be exacerbated by higher serum concentrations of tamoxifen and its metabolites in post-menopausal women with a history of hot flashes prior to tamoxifen treatment. PMID:24373320

Is a high serum copper concentration a risk factor for implantation failure?

PubMed

Matsubayashi, Hidehiko; Kitaya, Kotaro; Yamaguchi, Kohei; Nishiyama, Rie; Takaya, Yukiko; Ishikawa, Tomomoto

2017-08-10

Copper-containing contraceptive devices may deposit copper ions in the endometrium, resulting in implantation failure. The deposition of copper ions in many organs has been reported in patients with untreated Wilson's disease. Since these patients sometimes exhibit subfertility and/or early pregnancy loss, copper ions were also considered to accumulate in the uterine endometrium. Wilson's disease patients treated with zinc successfully delivered babies because zinc interfered with the absorption of copper from the gastrointestinal tract. These findings led to the hypothesis that infertile patients with high serum copper concentrations may have implantation failure due to the excess accumulation of copper ions. The relationship between implantation (pregnancy) rates and serum copper concentrations has not yet been examined. The Japanese government recently stated that actual copper intake was higher among Japanese than needed. Therefore, the aim of the present study was to investigate whether serum copper concentrations are related to the implantation (pregnancy) rates of human embryos in vivo. We included 269 patients (age <40 years old) who underwent vitrifying and warming single embryo transfer with a hormone replacement cycle using good blastocysts (3BB or more with Gardner's classification). Serum hCG, copper, and zinc concentrations were measured 16 days after the first date of progesterone replacement. We compared 96 women who were pregnant without miscarriage at 10 weeks of gestation (group P) and 173 women who were not pregnant (group NP). No significant differences were observed in age or BMI between the groups. Copper concentrations were significantly higher in group NP (average 193.2 μg/dL) than in group P (average 178.1 μg/dL). According to the area under the curve (AUC) on the receiver operating characteristic curve for the prediction of clinical pregnancy rates, the Cu/Zn ratio (AUC 0.64, 95% CI 0.54-0.71) was a better predictor than copper or zinc. When we set the cut-off as 1.59/1.60 for the Cu/Zn ratio, sensitivity, specificity, the positive predictive value, and negative predictive value were 0.98, 0.29, 0.71, and 0.88, respectively. Our single-center retrospective study suggests that high serum copper concentrations (high Cu/Zn ratio) are a risk factor for implantation failure.

Nowcasting recreational water quality

USGS Publications Warehouse

Boehm, Alexandria B.; Whitman, Richard L.; Nevers, Meredith; Hou, Deyi; Weisberg, Stephen B.

2007-01-01

Advances in molecular techniques may soon provide new opportunities to provide more timely information on whether recreational beaches are free from fecal contamination. However, an alternative approach is the use of predictive models. This chapter presents a summary of these developing efforts. First, we describe documented physical, chemical, and biological factors that have been demonstrated by researchers to affect bacterial concentrations at beaches and thus represent logical parameters for inclusion in a model. Then, we illustrate how various types of models can be applied to predict water quality at freshwater and marine beaches.

Lithium poisoning in the intensive care unit: predictive factors of severity and indications for extracorporeal toxin removal to improve outcome.

PubMed

Vodovar, Dominique; El Balkhi, Souleiman; Curis, Emmanuel; Deye, Nicolas; Mégarbane, Bruno

2016-09-01

Lithium is responsible for life-threatening poisoning, not consistently improved by extracorporeal toxin removal (ECTR). Our aim was to identify predictive factors on admission of poisoning severity and based on an evaluation of practice, report indications for ECTR susceptible to improve outcome Methods: We performed a retrospective cohort study including all lithium-poisoned patients admitted to the ICU in a university hospital. The usual clinical, biological and toxicological variables were collected. Poisoning severity was defined by seizures, catecholamine infusion, mechanical ventilation >48 h and/or fatality. Univariate followed by multiple logistic regression analyses were performed to identify prognosticators of poisoning severity and ECTR use. From 1992 to 2013, 128 lithium-poisoned patients including acutely (10%), acute-on-chronically (63%) and chronically poisoned patients (27%) were included. The presumed ingested dose of lithium was 17.0 g [8.0-24.5] (median [25th-75th percentiles]). Serum lithium concentrations were 2.6 mmol/l [1.5-4.6], 2.8 mmol/l [1.8-4.5] and 2.8 mmol/l [2.1-3.0] on admission, peaking at 3.6 mmol/l [2.6; 6.2], 4.3 mmol/l [2.4; 6.2] and 2.8 mmol/l [2.1; 3.1] in the three groups, respectively. Severe poisoning occurred in 48 patients (38%) including four fatalities. Using the regression analysis, predictive factors of poisoning severity were Glasgow coma score ≤10 (Odds ratio (OR), 11.1; 95% confidence interval (CI), [4.1-33.3], p < 0.0001) and lithium concentration ≥5.2 mmol/l (OR, 6.0; CI, [1.7-25.5], p = 0.005). Ninety-eight patients (77%) developed acute kidney injury according to KDIGO criteria and 22 (17%) were treated with ECTR. Peak lithium concentration ≥5.2 mmol/l (OR, 22.4; CI, [6.4-96.4]; p < 0.0001) and peak creatinine concentration ≥200 μmol/l (OR, 5.0; CI, [1.4-19.2]; p = 0.01) were associated with ECTR use. Only 21/46 patients who presented one of these two criteria were actually treated with ECTR. More significant neurological impairment persisted on discharge in patients not treated with ECTR (p = 0.0007) despite not significantly shorter length of ICU stay. Lithium poisoning is responsible for severe impairments but rare fatalities. Severity can be predicted on admission using Glasgow coma score and lithium concentration. Our results suggest that ECTR could be indicated if serum lithium ≥5.2 mmol/l or creatinine ≥200 μmol/l.

Adjustment of regional regression equations for urban storm-runoff quality using at-site data

USGS Publications Warehouse

Barks, C.S.

1996-01-01

Regional regression equations have been developed to estimate urban storm-runoff loads and mean concentrations using a national data base. Four statistical methods using at-site data to adjust the regional equation predictions were developed to provide better local estimates. The four adjustment procedures are a single-factor adjustment, a regression of the observed data against the predicted values, a regression of the observed values against the predicted values and additional local independent variables, and a weighted combination of a local regression with the regional prediction. Data collected at five representative storm-runoff sites during 22 storms in Little Rock, Arkansas, were used to verify, and, when appropriate, adjust the regional regression equation predictions. Comparison of observed values of stormrunoff loads and mean concentrations to the predicted values from the regional regression equations for nine constituents (chemical oxygen demand, suspended solids, total nitrogen as N, total ammonia plus organic nitrogen as N, total phosphorus as P, dissolved phosphorus as P, total recoverable copper, total recoverable lead, and total recoverable zinc) showed large prediction errors ranging from 63 percent to more than several thousand percent. Prediction errors for 6 of the 18 regional regression equations were less than 100 percent and could be considered reasonable for water-quality prediction equations. The regression adjustment procedure was used to adjust five of the regional equation predictions to improve the predictive accuracy. For seven of the regional equations the observed and the predicted values are not significantly correlated. Thus neither the unadjusted regional equations nor any of the adjustments were appropriate. The mean of the observed values was used as a simple estimator when the regional equation predictions and adjusted predictions were not appropriate.

Spatiotemporal estimation of historical PM2.5 concentrations using PM10, meteorological variables, and spatial effect

NASA Astrophysics Data System (ADS)

Li, Lianfa; Wu, Anna H.; Cheng, Iona; Chen, Jiu-Chiuan; Wu, Jun

2017-10-01

Monitoring of fine particulate matter with diameter <2.5 μm (PM2.5) started from 1999 in the US and even later in many other countries. The lack of historical PM2.5 data limits epidemiological studies of long-term exposure of PM2.5 and health outcomes such as cancer. In this study, we aimed to design a flexible approach to reliably estimate historical PM2.5 concentrations by incorporating spatial effect and the measurements of existing co-pollutants such as particulate matter with diameter <10 μm (PM10) and meteorological variables. Monitoring data of PM10, PM2.5, and meteorological variables covering the entire state of California were obtained from 1999 through 2013. We developed a spatiotemporal model that quantified non-linear associations between PM2.5 concentrations and the following predictor variables: spatiotemporal factors (PM10 and meteorological variables), spatial factors (land-use patterns, traffic, elevation, distance to shorelines, and spatial autocorrelation), and season. Our model accounted for regional-(county) scale spatial autocorrelation, using spatial weight matrix, and local-scale spatiotemporal variability, using local covariates in additive non-linear model. The spatiotemporal model was evaluated, using leaving-one-site-month-out cross validation. Our final daily model had an R2 of 0.81, with PM10, meteorological variables, and spatial autocorrelation, explaining 55%, 10%, and 10% of the variance in PM2.5 concentrations, respectively. The model had a cross-validation R2 of 0.83 for monthly PM2.5 concentrations (N = 8170) and 0.79 for daily PM2.5 concentrations (N = 51,421) with few extreme values in prediction. Further, the incorporation of spatial effects reduced bias in predictions. Our approach achieved a cross validation R2 of 0.61 for the daily model when PM10 was replaced by total suspended particulate. Our model can robustly estimate historical PM2.5 concentrations in California when PM2.5 measurements were not available.

Hazard Ranking Method for Populations Exposed to Arsenic in Private Water Supplies: Relation to Bedrock Geology

PubMed Central

Close, Rebecca; Watts, Michael J.; Ander, E. Louise; Smedley, Pauline L.; Verlander, Neville Q.; Gregory, Martin; Middleton, Daniel R. S.; Polya, David A.; Studden, Mike; Leonardi, Giovanni S.

2017-01-01

Approximately one million people in the UK are served by private water supplies (PWS) where main municipal water supply system connection is not practical or where PWS is the preferred option. Chronic exposure to contaminants in PWS may have adverse effects on health. South West England is an area with elevated arsenic concentrations in groundwater and over 9000 domestic dwellings here are supplied by PWS. There remains uncertainty as to the extent of the population exposed to arsenic (As), and the factors predicting such exposure. We describe a hazard assessment model based on simplified geology with the potential to predict exposure to As in PWS. Households with a recorded PWS in Cornwall were recruited to take part in a water sampling programme from 2011 to 2013. Bedrock geologies were aggregated and classified into nine Simplified Bedrock Geological Categories (SBGC), plus a cross-cutting “mineralized” area. PWS were sampled by random selection within SBGCs and some 508 households volunteered for the study. Transformations of the data were explored to estimate the distribution of As concentrations for PWS by SBGC. Using the distribution per SBGC, we predict the proportion of dwellings that would be affected by high concentrations and rank the geologies according to hazard. Within most SBGCs, As concentrations were found to have log-normal distributions. Across these areas, the proportion of dwellings predicted to have drinking water over the prescribed concentration value (PCV) for As ranged from 0% to 20%. From these results, a pilot predictive model was developed calculating the proportion of PWS above the PCV for As and hazard ranking supports local decision making and prioritization. With further development and testing, this can help local authorities predict the number of dwellings that might fail the PCV for As, based on bedrock geology. The model presented here for Cornwall could be applied in areas with similar geologies. Application of the method requires independent validation and further groundwater-derived PWS sampling on other geological formations. PMID:29194429

Modelling oxygen transfer using dynamic alpha factors.

PubMed

Jiang, Lu-Man; Garrido-Baserba, Manel; Nolasco, Daniel; Al-Omari, Ahmed; DeClippeleir, Haydee; Murthy, Sudhir; Rosso, Diego

2017-11-01

Due to the importance of wastewater aeration in meeting treatment requirements and due to its elevated energy intensity, it is important to describe the real nature of an aeration system to improve design and specification, performance prediction, energy consumption, and process sustainability. Because organic loadings drive aeration efficiency to its lowest value when the oxygen demand (energy) is the highest, the implications of considering their dynamic nature on energy costs are of utmost importance. A dynamic model aimed at identifying conservation opportunities is presented. The model developed describes the correlation between the COD concentration and the α factor in activated sludge. Using the proposed model, the aeration efficiency is calculated as a function of the organic loading (i.e. COD). This results in predictions of oxygen transfer values that are more realistic than the traditional method of assuming constant α values. The model was applied to two water resource recovery facilities, and was calibrated and validated with time-sensitive databases. Our improved aeration model structure increases the quality of prediction of field data through the recognition of the dynamic nature of the alpha factor (α) as a function of the applied oxygen demand. For the cases presented herein, the model prediction of airflow improved by 20-35% when dynamic α is used. The proposed model offers a quantitative tool for the prediction of energy demand and for minimizing aeration design uncertainty. Copyright © 2017 Elsevier Ltd. All rights reserved.

Advanced Multi-Moment Microphysics for Precipitation and Tropical Cyclone Forecast Improvement within COAMPS

DTIC Science & Technology

2010-09-30

of predicting up to three moments (total number concentration, mass, and the 6th-moment reflectivity factor) of hydrometeor hydrometeor particle size...R. Novak, F. E. Barthold, M. J. Bodner, J. J. Levit , C. B. Entwistle, T. Jensen, J. S. Kain, M. C. Coniglio, and R. S. Schneider, 2010: An overview

Prediction model of dissolved oxygen in ponds based on ELM neural network

NASA Astrophysics Data System (ADS)

Li, Xinfei; Ai, Jiaoyan; Lin, Chunhuan; Guan, Haibin

2018-02-01

Dissolved oxygen in ponds is affected by many factors, and its distribution is unbalanced. In this paper, in order to improve the imbalance of dissolved oxygen distribution more effectively, the dissolved oxygen prediction model of Extreme Learning Machine (ELM) intelligent algorithm is established, based on the method of improving dissolved oxygen distribution by artificial push flow. Select the Lake Jing of Guangxi University as the experimental area. Using the model to predict the dissolved oxygen concentration of different voltage pumps, the results show that the ELM prediction accuracy is higher than the BP algorithm, and its mean square error is MSEELM=0.0394, the correlation coefficient RELM=0.9823. The prediction results of the 24V voltage pump push flow show that the discrete prediction curve can approximate the measured values well. The model can provide the basis for the artificial improvement of the dissolved oxygen distribution decision.

Left Ventricular Structure and Risk of Cardiovascular Events: A Framingham Heart Study Cardiac Magnetic Resonance Study.

PubMed

Tsao, Connie W; Gona, Philimon N; Salton, Carol J; Chuang, Michael L; Levy, Daniel; Manning, Warren J; O'Donnell, Christopher J

2015-09-15

Elevated left ventricular mass index (LVMI) and concentric left ventricular (LV) remodeling are related to adverse cardiovascular disease (CVD) events. The predictive utility of LV concentric remodeling and LV mass in the prediction of CVD events is not well characterized. Framingham Heart Study Offspring Cohort members without prevalent CVD (n=1715, 50% men, aged 65±9 years) underwent cardiovascular magnetic resonance for LVMI and geometry (2002-2006) and were prospectively followed for incident CVD (myocardial infarction, coronary insufficiency, heart failure, stroke) or CVD death. Over 13 808 person-years of follow-up (median 8.4, range 0.0 to 10.5 years), 85 CVD events occurred. In multivariable-adjusted proportional hazards regression models, each 10-g/m(2) increment in LVMI and each 0.1 unit in relative wall thickness was associated with 33% and 59% increased risk for CVD, respectively (P=0.004 and P=0.009, respectively). The association between LV mass/LV end-diastolic volume and incident CVD was borderline significant (P=0.053). Multivariable-adjusted risk reclassification models showed a modest improvement in CVD risk prediction with the incorporation of cardiovascular magnetic resonance LVMI and measures of LV concentricity (C-statistic 0.71 [95% CI 0.65 to 0.78] for the model with traditional risk factors only, improved to 0.74 [95% CI 0.68 to 0.80] for the risk factor model additionally including LVMI and relative wall thickness). Among adults free of prevalent CVD in the community, greater LVMI and LV concentric hypertrophy are associated with a marked increase in adverse incident CVD events. The potential benefit of aggressive primary prevention to modify LV mass and geometry in these adults requires further investigation. © 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

On the Minimization of Fluctuations in the Response Times of Autoregulatory Gene Networks

PubMed Central

Murugan, Rajamanickam; Kreiman, Gabriel

2011-01-01

The temporal dynamics of the concentrations of several proteins are tightly regulated, particularly for critical nodes in biological networks such as transcription factors. An important mechanism to control transcription factor levels is through autoregulatory feedback loops where the protein can bind its own promoter. Here we use theoretical tools and computational simulations to further our understanding of transcription-factor autoregulatory loops. We show that the stochastic dynamics of feedback and mRNA synthesis can significantly influence the speed of response of autoregulatory genetic networks toward external stimuli. The fluctuations in the response-times associated with the accumulation of the transcription factor in the presence of negative or positive autoregulation can be minimized by confining the ratio of mRNA/protein lifetimes within 1:10. This predicted range of mRNA/protein lifetime agrees with ranges observed empirically in prokaryotes and eukaryotes. The theory can quantitatively and systematically account for the influence of regulatory element binding and unbinding dynamics on the transcription-factor concentration rise-times. The simulation results are robust against changes in several system parameters of the gene expression machinery. PMID:21943410

Predictive models for water sources with high susceptibility for bromine-containing disinfection by-product formation: implications for water treatment.

PubMed

Watson, Kalinda; Farré, Maria José; Birt, James; McGree, James; Knight, Nicole

2015-02-01

This study examines a matrix of synthetic water samples designed to include conditions that favour brominated disinfection by-product (Br-DBP) formation, in order to provide predictive models suitable for high Br-DBP forming waters such as salinity-impacted waters. Br-DBPs are known to be more toxic than their chlorinated analogues, in general, and their formation may be favoured by routine water treatment practices such as coagulation/flocculation under specific conditions; therefore, circumstances surrounding their formation must be understood. The chosen factors were bromide concentration, mineral alkalinity, bromide to dissolved organic carbon (Br/DOC) ratio and Suwannee River natural organic matter concentration. The relationships between these parameters and DBP formation were evaluated by response surface modelling of data generated using a face-centred central composite experimental design. Predictive models for ten brominated and/or chlorinated DBPs are presented, as well as models for total trihalomethanes (tTHMs) and total dihaloacetonitriles (tDHANs), and bromide substitution factors for the THMs and DHANs classes. The relationships described revealed that increasing alkalinity and increasing Br/DOC ratio were associated with increasing bromination of THMs and DHANs, suggesting that DOC lowering treatment methods that do not also remove bromide such as enhanced coagulation may create optimal conditions for Br-DBP formation in waters in which bromide is present.

Modelling Short-Term Maximum Individual Exposure from Airborne Hazardous Releases in Urban Environments. Part ΙI: Validation of a Deterministic Model with Wind Tunnel Experimental Data.

PubMed

Efthimiou, George C; Bartzis, John G; Berbekar, Eva; Hertwig, Denise; Harms, Frank; Leitl, Bernd

2015-06-26

The capability to predict short-term maximum individual exposure is very important for several applications including, for example, deliberate/accidental release of hazardous substances, odour fluctuations or material flammability level exceedance. Recently, authors have proposed a simple approach relating maximum individual exposure to parameters such as the fluctuation intensity and the concentration integral time scale. In the first part of this study (Part I), the methodology was validated against field measurements, which are governed by the natural variability of atmospheric boundary conditions. In Part II of this study, an in-depth validation of the approach is performed using reference data recorded under truly stationary and well documented flow conditions. For this reason, a boundary-layer wind-tunnel experiment was used. The experimental dataset includes 196 time-resolved concentration measurements which detect the dispersion from a continuous point source within an urban model of semi-idealized complexity. The data analysis allowed the improvement of an important model parameter. The model performed very well in predicting the maximum individual exposure, presenting a factor of two of observations equal to 95%. For large time intervals, an exponential correction term has been introduced in the model based on the experimental observations. The new model is capable of predicting all time intervals giving an overall factor of two of observations equal to 100%.

Predicting organic matter, nitrogen, and phosphorus concentrations in runoff from peat extraction sites using partial least squares regression

NASA Astrophysics Data System (ADS)

Tuukkanen, T.; Marttila, H.; Kløve, B.

2017-07-01

Organic matter and nutrient export from drained peatlands is affected by complex hydrological and biogeochemical interactions. Here partial least squares regression (PLSR) was used to relate various soil and catchment characteristics to variations in chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) concentrations in runoff. Peat core samples and water quality data were collected from 15 peat extraction sites in Finland. PLSR models constructed by cross-validation and variable selection routines predicted 92, 88, and 95% of the variation in mean COD, TN, and TP concentration in runoff, respectively. The results showed that variations in COD were mainly related to net production (temperature and water-extractable dissolved organic carbon (DOC)), hydrology (topographical relief), and solubility of dissolved organic matter (peat sulfur (S) and calcium (Ca) concentrations). Negative correlations for peat S and runoff COD indicated that acidity from oxidation of organic S stored in peat may be an important mechanism suppressing organic matter leaching. Moreover, runoff COD was associated with peat aluminum (Al), P, and sodium (Na) concentrations. Hydrological controls on TN and COD were similar (i.e., related to topography), whereas degree of humification, bulk density, and water-extractable COD and Al provided additional explanations for TN concentration. Variations in runoff TP concentration were attributed to erosion of particulate P, as indicated by a positive correlation with suspended sediment concentration (SSC), and factors associated with metal-humic complexation and P adsorption (peat Al, water-extractable P, and water-extractable iron (Fe)).

Implementation of an integrating sphere for the enhancement of noninvasive glucose detection using quantum cascade laser spectroscopy

NASA Astrophysics Data System (ADS)

Werth, Alexandra; Liakat, Sabbir; Dong, Anqi; Woods, Callie M.; Gmachl, Claire F.

2018-05-01

An integrating sphere is used to enhance the collection of backscattered light in a noninvasive glucose sensor based on quantum cascade laser spectroscopy. The sphere enhances signal stability by roughly an order of magnitude, allowing us to use a thermoelectrically (TE) cooled detector while maintaining comparable glucose prediction accuracy levels. Using a smaller TE-cooled detector reduces form factor, creating a mobile sensor. Principal component analysis has predicted principal components of spectra taken from human subjects that closely match the absorption peaks of glucose. These principal components are used as regressors in a linear regression algorithm to make glucose concentration predictions, over 75% of which are clinically accurate.

Insulin-Like Growth Factor 1 Predicts Post-Load Hypoglycemia following Bariatric Surgery: A Prospective Cohort Study

PubMed Central

Itariu, Bianca K.; Zeyda, Maximilian; Prager, Gerhard; Stulnig, Thomas M.

2014-01-01

Postprandial hypoglycemia is a complication following gastric bypass surgery, which frequently remains undetected. Severe hypoglycemic episodes, however, put patients at risk, e.g., for syncope. A major cause of hypoglycemia following gastric bypass is hyperinsulinemic nesidioblastosis. Since pancreatic islets in nesidioblastosis overexpress insulin-like growth factor 1 (IGF-1) receptor α and administration of recombinant IGF-1 provokes hypoglycemia, our main objective was to investigate the occurrence of post-load hypoglycemia one year after bariatric surgery and its relation to pre- and post-operative IGF-1 serum concentrations. We evaluated metabolic parameters including 2 h 75 g oral glucose tolerance test (OGTT) and measured IGF-1 serum concentration in thirty-six non-diabetic patients (29 f/7 m), aged 41.3±2.0 y with a median (IQR) BMI of 30.9 kg/m2 (27.5–34.3 kg/m2), who underwent elective bariatric surgery (predominantly gastric bypass, 83%) at our hospital. Post-load hypoglycemia as defined by a 2 h glucose concentration <60 mg/dl was detected in 50% of patients. Serum insulin and C-peptide concentration during the OGTT and HOMA-IR (homeostatic model assessment–insulin resistance) were similar in hypoglycemic and euglycemic patients. Strikingly, pre- and post-operative serum IGF-1 concentrations were significantly higher in hypoglycemic patients (p = 0.012 and p = 0.007 respectively). IGF-1 serum concentration before surgery negatively correlated with 2 h glucose concentration during the OGTT (rho = −0.58, p = 0.0003). Finally, IGF-1 serum concentrations before and after surgery significantly predicted post-load hypoglycemia with odds ratios of 1.28 (95%CI:1.03–1.55, p = 0.029) and 1.18 (95%CI:1.03–1.33, p = 0.015), respectively, for each 10 ng/ml increment. IGF-1 serum concentration could be a valuable biomarker to identify patients at risk for hypoglycemia following bariatric surgery independently of a diagnostic OGTT. Thus, IGF-1 testing could help to prevent a significant complication of gastric bypass surgery. PMID:24736741

Improved MEGAN predictions of biogenic isoprene in the contiguous United States

NASA Astrophysics Data System (ADS)

Wang, Peng; Schade, Gunnar; Estes, Mark; Ying, Qi

2017-01-01

Isoprene emitted from biogenic sources significantly contributes to ozone and secondary organic aerosol formation in the troposphere. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) has been widely used to estimate isoprene emissions from local to global scales. However, previous studies have shown that MEGAN significantly over-predicts isoprene emissions in the contiguous United States (US). In this study, ambient isoprene concentrations in the US were simulated by the Community Multiscale Air Quality (CMAQ) model (v5.0.1) using biogenic emissions estimated by MEGAN v2.10 with several different gridded isoprene emission factor (EF) fields. Best isoprene predictions were obtained with the EF field based on the Biogenic Emissions Landcover Database v4 (BELD4) from US EPA for its Biogenic Emission Inventory System (BEIS) model v3.61 (MEGAN-BEIS361). A seven-month simulation (April to October 2011) of isoprene emissions with MEGAN-BEIS361 and ambient concentrations using CMAQ shows that observed spatial and temporal variations (both diurnal and seasonal) of isoprene concentrations can be well predicted at most non-urban monitors using isoprene emission estimation from the MEGAN-BEIS361 without significant biases. The predicted monthly average vertical column density of formaldehyde (HCHO), a reactive volatile organic compound with significant contributions from isoprene oxidation, generally agree with the spatial distribution of HCHO column density derived using satellite data collected by the Ozone Monitoring Instrument (OMI), although summer month vertical column densities in the southeast US were overestimated, which suggests that isoprene emission might still be overestimated in that region. The agreement between observation and prediction may be further improved if more accurate PAR values, such as those derived from satellite-based observations, were used in modeling the biogenic emissions.

Rational and timely haemostatic interventions following cardiac surgery - coagulation factor concentrates or blood bank products.

PubMed

Tang, Mariann; Fenger-Eriksen, Christian; Wierup, Per; Greisen, Jacob; Ingerslev, Jørgen; Hjortdal, Vibeke; Sørensen, Benny

2017-06-01

Cardiac surgery may cause a serious coagulopathy leading to increased risk of bleeding and transfusion demands. Blood bank products are commonly first line haemostatic intervention, but has been associated with hazardous side effect. Coagulation factor concentrates may be a more efficient, predictable, and potentially a safer treatment, although prospective clinical trials are needed to further explore these hypotheses. This study investigated the haemostatic potential of ex vivo supplementation of coagulation factor concentrates versus blood bank products on blood samples drawn from patients undergoing cardiac surgery. 30 adults were prospectively enrolled (mean age=63.9, females=27%). Ex vivo haemostatic interventions (monotherapy or combinations) were performed in whole blood taken immediately after surgery and two hours postoperatively. Fresh-frozen plasma, platelets, cryoprecipitate, fibrinogen concentrate, prothrombin complex concentrate (PCC), and recombinant FVIIa (rFVIIa) were investigated. The haemostatic effect was evaluated using whole blood thromboelastometry parameters, as well as by thrombin generation. Immediately after surgery the compromised maximum clot firmness was corrected by monotherapy with fibrinogen or platelets or combination therapy with fibrinogen. At two hours postoperatively the coagulation profile was further deranged as illustrated by a prolonged clotting time, a reduced maximum velocity and further diminished maximum clot firmness. The thrombin lagtime was progressively prolonged and both peak thrombin and endogenous thrombin potential were compromised. No monotherapy effectively corrected all haemostatic abnormalities. The most effective combinations were: fibrinogen+rFVIIa or fibrinogen+PCC. Blood bank products were not as effective in the correction of the coagulopathy. Coagulation factor concentrates appear to provide a more optimal haemostasis profile following cardiac surgery compared to blood bank products. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estimation of Cadmium uptake by tobacco plants from laboratory leaching tests.

PubMed

Marković, Jelena P; Jović, Mihajlo D; Smičiklas, Ivana D; Šljivić-Ivanović, Marija Z; Smiljanić, Slavko N; Onjia, Antonije E; Popović, Aleksandar R

2018-03-21

The objective of the present study was to determine the impact of cadmium (Cd) concentration in the soil on its uptake by tobacco plants, and to compare the ability of diverse extraction procedures for determining Cd bioavailability and predicting soil-to-plant transfer and Cd plant concentrations. The pseudo-total digestion procedure, modified Tessier sequential extraction and six standard single-extraction tests for estimation of metal mobility and bioavailability were used for the leaching of Cd from a native soil, as well as samples artificially contaminated over a wide range of Cd concentrations. The results of various leaching tests were compared between each other, as well as with the amounts of Cd taken up by tobacco plants in pot experiments. In the native soil sample, most of the Cd was found in fractions not readily available under natural conditions, but with increasing pollution level, Cd amounts in readily available forms increased. With increasing concentrations of Cd in the soil, the quantity of pollutant taken up in tobacco also increased, while the transfer factor (TF) decreased. Linear and non-linear empirical models were developed for predicting the uptake of Cd by tobacco plants based on the results of selected leaching tests. The non-linear equations for ISO 14870 (diethylenetriaminepentaacetic acid extraction - DTPA), ISO/TS 21268-2 (CaCl 2 leaching procedure), US EPA 1311 (toxicity characteristic leaching procedure - TCLP) single step extractions, and the sum of the first two fractions of the sequential extraction, exhibited the best correlation with the experimentally determined concentrations of Cd in plants over the entire range of pollutant concentrations. This approach can improve and facilitate the assessment of human exposure to Cd by tobacco smoking, but may also have wider applicability in predicting soil-to-plant transfer.

[Determination of Chloride Salt Solution by NIR Spectroscopy].

PubMed

Zhang, Bin; Chen, Jian-hong; Jiao, Ming-xing

2015-07-01

Determination of chloride salt solution by near infrared spectrum plays a very important role in Biomedicine. The near infrared spectrum analysis of Sodium chloride, potassium chloride, calcium chloride aqueous solution shows that the concentration change of chloride salt can affect hydrogen bond, resulting in the variation of near infrared spectrum of water. The temperature influence on NIR spectrum has been decreased by choosing reasonable wavelength range and the wavelength where the temperature effects are zero (isosbestic point). Chlorine salt prediction model was established based on partial least squares method and used for predicting the concentration of the chlorine ion. The impact on near infrared spectrum of the cation ionic radius, the number of ionic charge, the complex effect of ionic in water has also discussed in this article and the reason of every factor are analysed. Experimental results show that the temperature and concentration will affect the near-infrared spectrum of the solution, It is found that the effect of temperature plays the dominant role at low concentrations of chlorine salt; rather, the ionic dominates at high concentration. Chloride complexes are formed in aqueous solution, It has an effect on hydrogen bond of water combining with the cations in chlorine salt solution, Comparing different chloride solutions at the same concentration, the destruction effects of chloride complexes and catnions on the hydrogen bond of water increases in the sequences: CaCl2 >NaCl>KC. The modeling result shows that the determination coefficients (R2) = 99.97%, the root mean square error of cross validation (RM- SECV) = 4.51, and the residual prediction deviation (RPD) = 62.7, it meets the daily requirements of biochemical detection accuracy.

Design of a breath analysis system for diabetes screening and blood glucose level prediction.

PubMed

Yan, Ke; Zhang, David; Wu, Darong; Wei, Hua; Lu, Guangming

2014-11-01

It has been reported that concentrations of several biomarkers in diabetics' breath show significant difference from those in healthy people's breath. Concentrations of some biomarkers are also correlated with the blood glucose levels (BGLs) of diabetics. Therefore, it is possible to screen for diabetes and predict BGLs by analyzing one's breath. In this paper, we describe the design of a novel breath analysis system for this purpose. The system uses carefully selected chemical sensors to detect biomarkers in breath. Common interferential factors, including humidity and the ratio of alveolar air in breath, are compensated or handled in the algorithm. Considering the intersubject variance of the components in breath, we build subject-specific prediction models to improve the accuracy of BGL prediction. A total of 295 breath samples from healthy subjects and 279 samples from diabetic subjects were collected to evaluate the performance of the system. The sensitivity and specificity of diabetes screening are 91.51% and 90.77%, respectively. The mean relative absolute error for BGL prediction is 21.7%. Experiments show that the system is effective and that the strategies adopted in the system can improve its accuracy. The system potentially provides a noninvasive and convenient method for diabetes screening and BGL monitoring as an adjunct to the standard criteria.

An operational system for the assimilation of the satellite information on wild-land fires for the needs of air quality modelling and forecasting

NASA Astrophysics Data System (ADS)

Sofiev, M.; Vankevich, R.; Lotjonen, M.; Prank, M.; Petukhov, V.; Ermakova, T.; Koskinen, J.; Kukkonen, J.

2009-09-01

This paper investigates a potential of two remotely sensed wild-land fire characteristics: 4-μm Brightness Temperature Anomaly (TA) and Fire Radiative Power (FRP) for the needs of operational chemical transport modelling and short-term forecasting of atmospheric composition and air quality. The treatments of the TA and FRP data are presented and a methodology for evaluating the emission fluxes of primary aerosols (PM2.5 and total PM) is described. The method does not include the complicated analysis of vegetation state, fuel load, burning efficiency and related factors, which are uncertain but inevitably involved in approaches based on burnt-area scars or similar products. The core of the current methodology is based on the empirical emission factors that are used to convert the observed temperature anomalies and fire radiative powers into emission fluxes. These factors have been derived from the analysis of several fire episodes in Europe (28.4-5.5.2006, 15.8-25.8.2006 and in August 2008). These episodes were characterised by: (i) well-identified FRP and TA values, and (ii) available ground-based observations of aerosol concentrations, and optical thickness for the regions where the contribution of the fire smoke to the concentrations of PM2.5 was dominant, in comparison with those of other pollution sources. The emission factors were determined separately for the forested and grassland areas; in case of mixed-type land use, an intermediate scaling was assumed. Despite significant differences between the TA and FRP methodologies, an accurate non-linear fitting was found between the predictions of these approaches. The agreement was comparatively weak only for small fires, for which the accuracy of both products is expected to be low. The applications of the Fire Assimilation System (FAS) in combination with the dispersion model SILAM showed that both the TA and FRP products are suitable for the evaluation of the emission fluxes from wild-land fires. The fire-originated concentrations of aerosols (PM2.5, PM10, sulphates and nitrates) and AOD, as predicted by the SILAM model were mainly within a factor of 2-3 compared with the observations. The main challenges of the FAS improvement include refining of the emission factors globally, determination of the types of fires (smouldering vs flaming), evaluation of the injection heights of the plumes, and predicting the temporal evolution of fires.

Aerial Application of Mancozeb and Urinary Ethylene Thiourea (ETU) Concentrations among Pregnant Women in Costa Rica: The Infants’ Environmental Health Study (ISA)

PubMed Central

Mora, Ana María; Córdoba, Leonel; Cano, Juan Camilo; Quesada, Rosario; Faniband, Moosa; Wesseling, Catharina; Ruepert, Clemens; Öberg, Mattias; Eskenazi, Brenda; Mergler, Donna; Lindh, Christian H.

2014-01-01

Background: Mancozeb and its main metabolite ethylene thiourea (ETU) may alter thyroid function; thyroid hormones are essential for fetal brain development. In Costa Rica, mancozeb is aerially sprayed at large-scale banana plantations on a weekly basis. Objectives: Our goals were to evaluate urinary ETU concentrations in pregnant women living near large-scale banana plantations, compare their estimated daily intake (EDI) with established reference doses (RfDs), and identify factors that predict their urinary ETU concentrations. Methods: We enrolled 451 pregnant women from Matina County, Costa Rica, which has large-scale banana production. We visited 445 women up to three times during pregnancy to obtain urine samples (n = 872) and information on factors that possibly influence exposure. We determined urinary ETU concentrations using liquid chromatography mass spectrometry. Results: Pregnant women’s median urinary ETU concentrations were more than five times higher than those reported for other general populations. Seventy-two percent of the women had EDIs above the RfD. Women who lived closest (1st quartile, < 48 m) to banana plantations on average had a 45% (95% CI: 23, 72%) higher urinary ETU compared with women who lived farthest away (4th quartile, ≥ 565 m). Compared with the other women, ETU was also higher in women who washed agricultural work clothes on the day before sampling (11%; 95% CI: 4.9, 17%), women who worked in agriculture during pregnancy (19%; 95% CI: 9.3, 29%), and immigrant women (6.2%; 95% CI: 1.0, 13%). Conclusions: The pregnant women’s urinary ETU concentrations are of concern, and the principal source of exposure is likely to be aerial spraying of mancozeb. The factors predicting ETU provide insight into possibilities for exposure reduction. Citation: van Wendel de Joode B, Mora AM, Córdoba L, Cano JC, Quesada R, Faniband M, Wesseling C, Ruepert C, Öberg M, Eskenazi B, Mergler D, Lindh CH. 2014. Aerial application of mancozeb and urinary ethylene thiourea (ETU) concentrations among pregnant women in Costa Rica: The Infants’ Environmental Health Study (ISA). Environ Health Perspect 122:1321–1328; http://dx.doi.org/10.1289/ehp.1307679 PMID:25198283

Storm loads of culturable and molecular fecal indicators in an inland urban stream.

PubMed

Liao, Hehuan; Krometis, Leigh-Anne H; Cully Hession, W; Benitez, Romina; Sawyer, Richard; Schaberg, Erin; von Wagoner, Emily; Badgley, Brian D

2015-10-15

Elevated concentrations of fecal indicator bacteria in receiving waters during wet-weather flows are a considerable public health concern that is likely to be exacerbated by future climate change and urbanization. Knowledge of factors driving the fate and transport of fecal indicator bacteria in stormwater is limited, and even less is known about molecular fecal indicators, which may eventually supplant traditional culturable indicators. In this study, concentrations and loading rates of both culturable and molecular fecal indicators were quantified throughout six storm events in an instrumented inland urban stream. While both concentrations and loading rates of each fecal indicator increased rapidly during the rising limb of the storm hydrographs, it is the loading rates rather than instantaneous concentrations that provide a better estimate of transport through the stream during the entire storm. Concentrations of general fecal indicators (both culturable and molecular) correlated most highly with each other during storm events but not with the human-associated HF183 Bacteroides marker. Event loads of general fecal indicators most strongly correlated with total runoff volume, maximum discharge, and maximum turbidity, while event loads of HF183 most strongly correlated with the time to peak flow in a hydrograph. These observations suggest that collection of multiple samples during a storm event is critical for accurate predictions of fecal indicator loading rates and total loads during wet-weather flows, which are required for effective watershed management. In addition, existing predictive models based on general fecal indicators may not be sufficient to predict source-specific genetic markers of fecal contamination. Copyright © 2015 Elsevier B.V. All rights reserved.

Arsenic concentrations, related environmental factors, and the predicted probability of elevated arsenic in groundwater in Pennsylvania

USGS Publications Warehouse

Gross, Eliza L.; Low, Dennis J.

2013-01-01

Logistic regression models were created to predict and map the probability of elevated arsenic concentrations in groundwater statewide in Pennsylvania and in three intrastate regions to further improve predictions for those three regions (glacial aquifer system, Gettysburg Basin, Newark Basin). Although the Pennsylvania and regional predictive models retained some different variables, they have common characteristics that can be grouped by (1) geologic and soils variables describing arsenic sources and mobilizers, (2) geochemical variables describing the geochemical environment of the groundwater, and (3) locally specific variables that are unique to each of the three regions studied and not applicable to statewide analysis. Maps of Pennsylvania and the three intrastate regions were produced that illustrate that areas most at risk are those with geology and soils capable of functioning as an arsenic source or mobilizer and geochemical groundwater conditions able to facilitate redox reactions. The models have limitations because they may not characterize areas that have localized controls on arsenic mobility. The probability maps associated with this report are intended for regional-scale use and may not be accurate for use at the field scale or when considering individual wells.

Environmental Risk Assessment of Pharmaceutical Mixtures: Demands, Gaps, and Possible Bridges.

PubMed

Backhaus, Thomas

2016-07-01

The ecotoxicological risk of pharmaceutical mixtures typically exceeds the risk of each individual compound, which calls specific attention to the fact that monitoring surveys routinely find complex pharmaceutical mixtures in various environmental compartments. However, although the body of evidence on the ecotoxicology of pharmaceutical mixtures is quite consistent, the current guidelines for the environmental risk assessment of pharmaceuticals often do not explicitly address mixture effects. Data availability and acceptable methods often limit such assessments. A tiered approach that begins with summing up individual risk quotients, i.e., the ratio between the predicted or measured environmental concentration and the predicted no effect concentration (PNEC) is therefore suggested in this paper, in order to improve the realism of the environmental risk assessment of pharmaceuticals. Additionally, the use of a mixture-specific assessment factor, as well as the classical mixture toxicity concepts of concentration addition and independent action is explored. Finally, specific attention is given to the exposure-based waiving of environmental risk assessments, as currently implemented in screening or pre-screening phases (tier 0 in Europe, categorical exclusion in the USA), since even low, individually non-toxic concentrations might combine to produce substantial mixture effects.

Optimization of physico-chemical properties of gelatin extracted from fish skin of rainbow trout (Onchorhynchus mykiss).

PubMed

Tabarestani, H Shahiri; Maghsoudlou, Y; Motamedzadegan, A; Mahoonak, A R Sadeghi

2010-08-01

Physico-chemical properties of gelatin extracted from rainbow trout (Onchorhynchus mykiss) skin were optimized using response surface methodology (RSM). Central rotatable composite design was applied to study the combined effects of NaOH concentration (0.01-0.21 N), acetic acid concentration (0.01-0.21 N) and pre-treatment time (1-3h) on yield, molecular weight distribution, gel strength, viscosity and melting point of gelatin. Regression models were developed to predict the variables. Predict values of multiple response at optimal condition were that yield=9.36%, alpha(1)/alpha(2) chain ratio=1.76, beta chain percent=32.81, gel strength=459 g, viscosity=3.2 mPa s and melting point=20.4 degrees C. The optimal condition was obtained using 0.19 N NaOH and 0.121 N acetic acid for 3h. The results showed that the concentration of H(+) during pre-treatment had significant effect on molecular weight distribution, melting point and gel strength. The concentration of OH(-) had significant effect on viscosity and for extraction yield, pretreatment time was the critical factor. (c) 2010 Elsevier Ltd. All rights reserved.

Mixture effects of benzene, toluene, ethylbenzene, and xylenes (BTEX) on lung carcinoma cells via a hanging drop air exposure system.

PubMed

Liu, Faye F; Escher, Beate I; Were, Stephen; Duffy, Lesley; Ng, Jack C

2014-06-16

A recently developed hanging drop air exposure system for toxicity studies of volatile chemicals was applied to evaluate the cell viability of lung carcinoma A549 cells after 1 and 24 h of exposure to benzene, toluene, ethylbenzene, and xylenes (BTEX) as individual compounds and as mixtures of four or six components. The cellular chemical concentrations causing 50% reduction of cell viability (EC50) were calculated using a mass balance model and came to 17, 12, 11, 9, 4, and 4 mmol/kg cell dry weight for benzene, toluene, ethylbenzene, m-xylene, o-xylene, and p-xylene, respectively, after 1 h of exposure. The EC50 decreased by a factor of 4 after 24 h of exposure. All mixture effects were best described by the mixture toxicity model of concentration addition, which is valid for chemicals with the same mode of action. Good agreement with the model predictions was found for benzene, toluene, ethylbenzene, and m-xylene at four different representative fixed concentration ratios after 1 h of exposure, but lower agreement with mixture prediction was obtained after 24 h of exposure. A recreated car exhaust mixture, which involved the contribution of the more toxic p-xylene and o-xylene, yielded an acceptable, but lower quality, prediction as well.

Assessment of the climate change impacts on fecal coliform contamination in a tidal estuarine system.

PubMed

Liu, Wen-Cheng; Chan, Wen-Ting

2015-12-01

Climate change is one of the key factors affecting the future microbiological water quality in rivers and tidal estuaries. A coupled 3D hydrodynamic and fecal coliform transport model was developed and applied to the Danshuei River estuarine system for predicting the influences of climate change on microbiological water quality. The hydrodynamic and fecal coliform model was validated using observational salinity and fecal coliform distributions. According to the analyses of the statistical error, predictions of the salinity and the fecal coliform concentration from the model simulation quantitatively agreed with the observed data. The validated model was then applied to predict the fecal coliform contamination as a result of climate change, including the change of freshwater discharge and the sea level rise. We found that the reduction of freshwater discharge under climate change scenarios resulted in an increase in the fecal coliform concentration. The sea level rise would decrease fecal coliform distributions because both the water level and the water volume increased. A reduction in freshwater discharge has a negative impact on the fecal coliform concentration, whereas a rising sea level has a positive influence on the fecal coliform contamination. An appropriate strategy for the effective microbiological management in tidal estuaries is required to reveal the persistent trends of climate in the future.

Inhalation exposure to cleaning products: application of a two-zone model.

PubMed

Earnest, C Matt; Corsi, Richard L

2013-01-01

In this study, modifications were made to previously applied two-zone models to address important factors that can affect exposures during cleaning tasks. Specifically, we expand on previous applications of the two-zone model by (1) introducing the source in discrete elements (source-cells) as opposed to a complete instantaneous release, (2) placing source cells in both the inner (near person) and outer zones concurrently, (3) treating each source cell as an independent mixture of multiple constituents, and (4) tracking the time-varying liquid concentration and emission rate of each constituent in each source cell. Three experiments were performed in an environmentally controlled chamber with a thermal mannequin and a simplified pure chemical source to simulate emissions from a cleaning product. Gas phase concentration measurements were taken in the bulk air and in the breathing zone of the mannequin to evaluate the model. The mean ratio of the integrated concentration in the mannequin's breathing zone to the concentration in the outer zone was 4.3 (standard deviation, σ = 1.6). The mean ratio of measured concentration in the breathing zone to predicted concentrations in the inner zone was 0.81 (σ = 0.16). Intake fractions ranged from 1.9 × 10(-3) to 2.7 × 10(-3). Model results reasonably predict those of previous exposure monitoring studies and indicate the inadequacy of well-mixed single-zone model applications for some but not all cleaning events.

Circulating Branched-chain Amino Acid Concentrations Are Associated with Obesity and Future Insulin Resistance in Children and Adolescents

PubMed Central

McCormack, Shana E.; Shaham, Oded; McCarthy, Meaghan A.; Deik, Amy A.; Wang, Thomas J.; Gerszten, Robert E.; Clish, Clary B.; Mootha, Vamsi K.; Grinspoon, Steven K.; Fleischman, Amy

2012-01-01

Background Branched-chain amino acid (BCAA) concentrations are elevated in response to overnutrition, and can affect both insulin sensitivity and secretion. Alterations in their metabolism may therefore play a role in the early pathogenesis of type 2 diabetes in overweight children. Objective To determine whether pediatric obesity is associated with elevations in fasting circulating concentrations of branched-chain amino acids (isoleucine, leucine, and valine), and whether these elevations predict future insulin resistance. Research Design and Methods Sixty-nine healthy subjects, ages 8 to18 years, were enrolled as a cross-sectional cohort. A subset who were pre- or early-pubertal, ages 8 to 13 years, were enrolled in a prospective longitudinal cohort for 18 months (n=17 with complete data). Results Elevations in the concentrations of BCAA’s were significantly associated with BMI Z-score (Spearman’s Rho 0.27, p=0.03) in the cross-sectional cohort. In the subset of subjects followed longitudinally, baseline BCAA concentrations were positively associated with HOMA-IR measured 18 months later after controlling for baseline clinical factors including BMI Z-score, sex, and pubertal stage (p=0.046). Conclusions Elevations in the concentrations of circulating branched-chain amino acids are significantly associated with obesity in children and adolescents, and may independently predict future insulin resistance. PMID:22961720

Can we predict uranium bioavailability based on soil parameters? Part 2: soil solution uranium concentration is not a good bioavailability index.

PubMed

Vandenhove, H; Van Hees, M; Wannijn, J; Wouters, K; Wang, L

2007-01-01

The present study aimed to quantify the influence of soil parameters on uranium uptake by ryegrass. Ryegrass was established on eighteen distinct soils, spiked with (238)U. Uranium soil-to-plant transfer factors (TF) ranged from 0.0003 to 0.0340kgkg(-1). There was no significant relation between the U soil-to-plant transfer (or total U uptake or flux) and the uranium concentration in the soil solution or any other soil factor measured, nor with the U recovered following selective soil extractions. Multiple linear regression analysis resulted in a significant though complex model explaining up to 99% of variation in TF. The influence of uranium speciation on uranium uptake observed was featured: UO(2)(+2), uranyl carbonate complexes and UO(2)PO(4)(-) seem the U species being preferentially taken up by the roots and transferred to the shoots. Improved correlations were obtained when relating the uranium TF with the summed soil solution concentrations of mentioned uranium species.

Study of dielectric properties of adulterated milk concentration and freshness

NASA Astrophysics Data System (ADS)

Jitendra Murthy, V.; Sai Kiranmai, N.; Kumar, Sanjeev

2017-08-01

The knowledge of dielectric properties may hold a potential to develop a new technique for quality evaluation of milk. The dielectric properties of water diluted cow’s milk with milk concentration from 70 percent to 100 percent stored during 36hour storage at 22°C and 144 hour at 5°C were measured at room temperature for frequencies ranging from 10 to 4500 MHz and at low, high & at microwave frequencies using X band bench and open-ended coaxial-line probe technology, along with electrical conductivity. The raw milk had the lowest dielectric constant (ɛ‧) when the frequency was higher than about 20M.Hz, and had the highest loss (ɛ″) or decepation factor tan (δ) at each frequency. The penetration depth (dp) increased with decreasing frequency, water content and storage time, which was large enough to detect dielectric properties changes in milk samples and provide large scale RF pasteurization processes. The loss factor can be an indicator in predicting milk concentration and freshness.

Measured and predicted environmental concentrations of carbamazepine, diclofenac, and metoprolol in small and medium rivers in northern Germany.

PubMed

Meyer, Wibke; Reich, Margrit; Beier, Silvio; Behrendt, Joachim; Gulyas, Holger; Otterpohl, Ralf

2016-08-01

This study evaluated the impact of secondary municipal effluent discharge on carbamazepine, diclofenac, and metoprolol concentrations in small and medium rivers in northern Germany and compared the measured environmental concentrations (MECs) to the predicted environmental concentrations (PECs) calculated with four well-established models. During a 1-year sampling period, secondary effluent grab samples were collected at four wastewater treatment plants (WWTPs) together with grab samples from the receiving waters upstream and downstream from the wastewater discharge points. The carbamazepine, diclofenac, and metoprolol concentrations were analyzed with high-performance liquid chromatography-tandem mass spectrometry (HPLC/MS-MS) after solid phase extraction. In the secondary effluents, 84-790 ng/L carbamazepine, 395-2100 ng/L diclofenac, and 745-5000 ng/L metoprolol were detected. The carbamazepine, diclofenac, and metoprolol concentrations analyzed in the rivers downstream from the secondary effluent discharge sites ranged from <5 to 68, 370, and 520 ng/L, respectively. Most of the downstream pharmaceutical concentrations were markedly higher than the corresponding upstream concentrations. The impact of wastewater discharge on the MECs in rivers downstream from the WWTPs was clearly demonstrated, but the correlations of the MECs with dilution factors were poor. The smallest rivers exhibited the largest maximum MECs and the widest ranges of MECs downstream from the wastewater discharge point. Three of the four tested models were conservative, as they showed higher PECs than the MECs in the rivers downstream from the WWTPs. However, the most detailed model underestimated the diclofenac concentrations.

Assessment of colour changes during storage of elderberry juice concentrate solutions using the optimization method.

PubMed

Walkowiak-Tomczak, Dorota; Czapski, Janusz; Młynarczyk, Karolina

2016-01-01

Elderberries are a source of dietary supplements and bioactive compounds, such as anthocyanins. These dyes are used in food technology. The aim of the study was to assess the changes in colour parameters, anthocyanin contents and sensory attributes in solutions of elderberry juice concentrates during storage in a model system and to determine predictability of sensory attributes of colour in solutions based on regression equations using the response surface methodology. The experiment was carried out according to the 3-level factorial design for three factors. Independent variables included pH, storage time and temperature. Dependent variables were assumed to be the components and colour parameters in the CIE L*a*b* system, pigment contents and sensory attributes. Changes in colour components X, Y, Z and colour parameters L*, a*, b*, C* and h* were most dependent on pH values. Colour lightness L* and tone h* increased with an increase in experimental factors, while the share of the red colour a* and colour saturation C* decreased. The greatest effect on the anthocyanin concentration was recorded for storage time. Sensory attributes deteriorated during storage. The highest correlation coefficients were found between the value of colour tone h* and anthocyanin contents in relation to the assessment of the naturalness and desirability of colour. A high goodness-of-fit of the model to data and high values of R2 for regression equations were obtained for all responses. The response surface method facilitates optimization of experimental factor values in order to obtain a specific attribute of the product, but not in all cases of the experiment. Within the tested range of factors, it is possible to predict changes in anthocyanin content and the sensory attributes of elderberry juice concentrate solutions as food dye, on the basis of the lack of a fit test. The highest stability of dyes and colour of elderberry solutions was found in the samples at pH 3.0, which confirms the advisability of using an anthocyanin preparation to shape the colour of high-acidity food products, such as fruit fillings, beverages,desserts.

Pharmacokinetic-based prediction of real-life dosing of extended half-life clotting factor concentrates on hemophilia

PubMed Central

Gherardini, Stefano

2018-01-01

The improvement of clotting factor concentrates (CFCs) has undergone an impressive boost during the last six years. Since 2010, several new recombinant factor (rF)VIII/IX concentrates entered phase I/II/III clinical trials. The improvements are related to the culture of human embryonic kidney (HEK) cells, post-translational glycosylation, PEGylation, and co-expression of the fragment crystallizable (Fc) region of immunoglobulin (Ig)G1 or albumin genes in the manufacturing procedures. The extended half-life (EHL) CFCs allow an increase of the interval between bolus administrations during prophylaxis, a very important advantage for patients with difficulties in venous access. Although the inhibitor risk has not been fully established, phase III studies have provided standard prophylaxis protocols, which, compared with on-demand treatment, have achieved very low annualized bleeding rates (ABRs). The key pharmacokinetics (PK) parameter to tailor patient therapy is clearance, which is more reliable than the half-life of CFCs; the clearance considers the decay rate of the drug concentration–time profile, while the half-life considers only the half concentration of the drug at a given time. To tailor the prophylaxis of hemophilia patients in real-life, we propose two formulae (expressed in terms of the clearance, trough and dose interval between prophylaxis), respectively based on the one- and two-compartmental models (CMs), for the prediction of the optimal single dose of EHL CFCs. Once the data from the time decay of the CFCs are fitted by the one- or two-CMs after an individual PK analysis, such formulae provide to the treater the optimal trade-off among trough and time-intervals between boluses. In this way, a sufficiently long time-interval between bolus administration could be guaranteed for a wider class of patients, with a preassigned level of the trough. Finally, a PK approach using repeated dosing is discussed, and some examples with new EHL CFCs are shown. PMID:29899890

AERMOD performance evaluation for three coal-fired electrical generating units in Southwest Indiana.

PubMed

Frost, Kali D

2014-03-01

An evaluation of the steady-state dispersion model AERMOD was conducted to determine its accuracy at predicting hourly ground-level concentrations of sulfur dioxide (SO2) by comparing model-predicted concentrations to a full year of monitored SO2 data. The two study sites are comprised of three coal-fired electrical generating units (EGUs) located in southwest Indiana. The sites are characterized by tall, buoyant stacks,flat terrain, multiple SO2 monitors, and relatively isolated locations. AERMOD v12060 and AERMOD v12345 with BETA options were evaluated at each study site. For the six monitor-receptor pairs evaluated, AERMOD showed generally good agreement with monitor values for the hourly 99th percentile SO2 design value, with design value ratios that ranged from 0.92 to 1.99. AERMOD was within acceptable performance limits for the Robust Highest Concentration (RHC) statistic (RHC ratios ranged from 0.54 to 1.71) at all six monitors. Analysis of the top 5% of hourly concentrations at the six monitor-receptor sites, paired in time and space, indicated poor model performance in the upper concentration range. The amount of hourly model predicted data that was within a factor of 2 of observations at these higher concentrations ranged from 14 to 43% over the six sites. Analysis of subsets of data showed consistent overprediction during low wind speed and unstable meteorological conditions, and underprediction during stable, low wind conditions. Hourly paired comparisons represent a stringent measure of model performance; however given the potential for application of hourly model predictions to the SO2 NAAQS design value, this may be appropriate. At these two sites, AERMOD v12345 BETA options do not improve model performance. A regulatory evaluation of AERMOD utilizing quantile-quantile (Q-Q) plots, the RHC statistic, and 99th percentile design value concentrations indicates that model performance is acceptable according to widely accepted regulatory performance limits. However, a scientific evaluation examining hourly paired monitor and model values at concentrations of interest indicates overprediction and underprediction bias that is outside of acceptable model performance measures. Overprediction of 1-hr SO2 concentrations by AERMOD presents major ramifications for state and local permitting authorities when establishing emission limits.

Hypocalcemia in dairy cows: meta-analysis and dietary cation anion difference theory revisited.

PubMed

Lean, I J; DeGaris, P J; McNeil, D M; Block, E

2006-02-01

Data from 137 published trials involving 2,545 calvings were analyzed using random effects normal logistic regression models to identify risk factors for clinical hypocalcemia in dairy cows. The aim of the study was to examine which form, if any, of the dietary cation anion difference (DCAD) equation provided the best estimate of milk fever risk and to clarify roles of calcium, magnesium, and phosphorus concentrations of prepartum diets in the pathogenesis of milk fever. Two statistically equivalent and biologically plausible models were developed that predict incidence of milk fever. These models were validated using data from 37 trials excluded from the original data used to generate the models; missing variables were replaced with mean values from the analyzed data. The preferred models differed slightly; Model 1 included prepartum DCAD, and Model 2 included prepartum dietary concentrations of potassium and sulfur alone, but not sodium and chloride. Other factors, included in both models were prepartum dietary concentrations of calcium, magnesium, phosphorus; days exposed to the prepartum diet; and breed. Jersey cows were at 2.25 times higher risk of milk fever than Holstein cows in Model 1. The results support the DCAD theory of greater risk of milk fever with higher prepartum dietary DCAD (odds ratio = 1.015). The only DCAD equation supported in statistical analyses was (Na(+) + K(+)) - (Cl(-) + S(2-)). This finding highlights the difference between developing equations to predict DCAD and those to predict milk fever. The results support a hypothesis of a quadratic role for Ca in the pathogenesis of milk fever (model 1, odds ratio = 0.131; Model 2, odds ratio = 0.115). Milk fever risk was highest with a prepartum dietary concentration of 1.35% calcium. Increasing prepartum dietary magnesium concentrations had the largest effect on decreasing incidence of milk fever in both Model 1 (odds ratio = 0.006) and Model 2 (odds ratio = 0.001). Increasing dietary phosphorus concentrations prepartum increased the risk of milk fever (Model 1, odds ratio = 6.376; Model 2, odds ratio = 9.872). The models presented provide the basis for the formulation of diets to reduce the risk of milk fever and strongly support the need to evaluate macro mineral nutrition apart from DCAD of the diet.

Study on two operating conditions of a full-scale oxidation ditch for optimization of energy consumption and effluent quality by using CFD model.

PubMed

Yang, Yin; Yang, Jiakuan; Zuo, Jiaolan; Li, Ye; He, Shu; Yang, Xiao; Zhang, Kai

2011-05-01

The operating condition of an oxidation ditch (OD) has significant impact on energy consumption and effluent quality of wastewater treatment plants (WWTPs). An experimentally validated numerical tool, based on computational fluid dynamics (CFD) model, was proposed to optimize the operating condition by considering two important factors: flow field and dissolved oxygen (DO) concentration profiles. The model is capable of predicting flow pattern and oxygen mass transfer characteristics in ODs equipped with surface aerators and submerged impellers. Performance demonstration and comparison of two operating conditions (existing and improved) were carried out in two full-scale Carrousel ODs at the Ping Dingshan WWTP in Henan, China. A moving wall model and a fan model were designed to simulate surface aerators and submerged impellers, respectively. Oxygen mass transfer in the ditch was predicted by using a unit analysis method. In aeration zones, the mass inlets representing the surface aerators were set as one source of DO. In the whole straight channel, the oxygen consumption was modeled by using modified BOD-DO model. The following results were obtained: (1) the CFD model characterized flow pattern and DO concentration profiles in the full-scale OD. The predicted flow field values were within 1.98 ± 4.28% difference from the actual measured values while the predicted DO concentration values were within -4.71 ± 4.15% of the measured ones, (2) a surface aerator should be relocated to around 15m from the curve bend entrance to reduce energy loss caused by fierce collisions at the wall of the curve bend, and (3) DO concentration gradients in the OD under the improved operating condition were more favorable for occurrence of simultaneous nitrification and denitrification (SND). Copyright © 2011 Elsevier Ltd. All rights reserved.

Operational Dust Prediction

NASA Technical Reports Server (NTRS)

Benedetti, Angela; Baldasano, Jose M.; Basart, Sara; Benincasa, Francesco; Boucher, Olivier; Brooks, Malcolm E.; Chen, Jen-Ping; Colarco, Peter R.; Gong, Sunlin; Huneeus, Nicolas;

Existing generating assets squeezed as new project starts slow

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, R.B.; Tiffany, E.D.

Most forecasting reports concentrate on political or regulatory events to predict future industry trends. Frequently overlooked are the more empirical performance trends of the principal power generation technologies. Solomon and Associates queried its many power plant performance databases and crunched some numbers to identify those trends. Areas of investigation included reliability, utilization (net output factor and net capacity factor) and cost (operating costs). An in-depth analysis for North America and Europe is presented in this article, by region and by regeneration technology. 4 figs., 2 tabs.

Direct Quantification of Cd2+ in the Presence of Cu2+ by a Combination of Anodic Stripping Voltammetry Using a Bi-Film-Modified Glassy Carbon Electrode and an Artificial Neural Network.

PubMed

Zhao, Guo; Wang, Hui; Liu, Gang

2017-07-03

Abstract : In this study, a novel method based on a Bi/glassy carbon electrode (Bi/GCE) for quantitatively and directly detecting Cd 2+ in the presence of Cu 2+ without further electrode modifications by combining square-wave anodic stripping voltammetry (SWASV) and a back-propagation artificial neural network (BP-ANN) has been proposed. The influence of the Cu 2+ concentration on the stripping response to Cd 2+ was studied. In addition, the effect of the ferrocyanide concentration on the SWASV detection of Cd 2+ in the presence of Cu 2+ was investigated. A BP-ANN with two inputs and one output was used to establish the nonlinear relationship between the concentration of Cd 2+ and the stripping peak currents of Cu 2+ and Cd 2+ . The factors affecting the SWASV detection of Cd 2+ and the key parameters of the BP-ANN were optimized. Moreover, the direct calibration model (i.e., adding 0.1 mM ferrocyanide before detection), the BP-ANN model and other prediction models were compared to verify the prediction performance of these models in terms of their mean absolute errors (MAEs), root mean square errors (RMSEs) and correlation coefficients. The BP-ANN model exhibited higher prediction accuracy than the direct calibration model and the other prediction models. Finally, the proposed method was used to detect Cd 2+ in soil samples with satisfactory results.

A physiologically based toxicokinetic model for lake trout (Salvelinus namaycush).

PubMed

Lien, G J; McKim, J M; Hoffman, A D; Jenson, C T

2001-01-01

A physiologically based toxicokinetic (PB-TK) model for fish, incorporating chemical exchange at the gill and accumulation in five tissue compartments, was parameterized and evaluated for lake trout (Salvelinus namaycush). Individual-based model parameterization was used to examine the effect of natural variability in physiological, morphological, and physico-chemical parameters on model predictions. The PB-TK model was used to predict uptake of organic chemicals across the gill and accumulation in blood and tissues in lake trout. To evaluate the accuracy of the model, a total of 13 adult lake trout were exposed to waterborne 1,1,2,2-tetrachloroethane (TCE), pentachloroethane (PCE), and hexachloroethane (HCE), concurrently, for periods of 6, 12, 24 or 48 h. The measured and predicted concentrations of TCE, PCE and HCE in expired water, dorsal aortic blood and tissues were generally within a factor of two, and in most instances much closer. Variability noted in model predictions, based on the individual-based model parameterization used in this study, reproduced variability observed in measured concentrations. The inference is made that parameters influencing variability in measured blood and tissue concentrations of xenobiotics are included and accurately represented in the model. This model contributes to a better understanding of the fundamental processes that regulate the uptake and disposition of xenobiotic chemicals in the lake trout. This information is crucial to developing a better understanding of the dynamic relationships between contaminant exposure and hazard to the lake trout.

Application of Physiologically Based Absorption Modeling to Characterize the Pharmacokinetic Profiles of Oral Extended Release Methylphenidate Products in Adults

PubMed Central

Yang, Xiaoxia; Duan, John; Fisher, Jeffrey

2016-01-01

A previously presented physiologically-based pharmacokinetic model for immediate release (IR) methylphenidate (MPH) was extended to characterize the pharmacokinetic behaviors of oral extended release (ER) MPH formulations in adults for the first time. Information on the anatomy and physiology of the gastrointestinal (GI) tract, together with the biopharmaceutical properties of MPH, was integrated into the original model, with model parameters representing hepatic metabolism and intestinal non-specific loss recalibrated against in vitro and in vivo kinetic data sets with IR MPH. A Weibull function was implemented to describe the dissolution of different ER formulations. A variety of mathematical functions can be utilized to account for the engineered release/dissolution technologies to achieve better model performance. The physiological absorption model tracked well the plasma concentration profiles in adults receiving a multilayer-release MPH formulation or Metadate CD, while some degree of discrepancy was observed between predicted and observed plasma concentration profiles for Ritalin LA and Medikinet Retard. A local sensitivity analysis demonstrated that model parameters associated with the GI tract significantly influenced model predicted plasma MPH concentrations, albeit to varying degrees, suggesting the importance of better understanding the GI tract physiology, along with the intestinal non-specific loss of MPH. The model provides a quantitative tool to predict the biphasic plasma time course data for ER MPH, helping elucidate factors responsible for the diverse plasma MPH concentration profiles following oral dosing of different ER formulations. PMID:27723791

Clinical and atopic parameters and airway inflammatory markers in childhood asthma: a factor analysis

PubMed Central

Leung, T; Wong, G; Ko, F; Lam, C; Fok, T

2005-01-01

Background: Recent studies have repeatedly shown weak correlations among lung function parameters, atopy, exhaled nitric oxide level (FeNO), and airway inflammatory markers, suggesting that they are non-overlapping characteristics of asthma in adults. A study was undertaken to determine, using factor analysis, whether the above features represent separate dimensions of childhood asthma. Methods: Clinically stable asthmatic patients aged 7–18 years underwent spirometric testing, methacholine bronchial challenge, blood sampling for atopy markers and chemokine levels (macrophage derived chemokine (MDC), thymus and activation regulated chemokine (TARC), and eotaxin), FeNO, and chemokines (MDC and eotaxin) and leukotriene B4 measurements in exhaled breath condensate (EBC). Results: The mean (SD) forced expiratory volume in 1 second (FEV1) and FeNO of 92 patients were 92.1 (15.9)% predicted and 87.3 (65.7) ppb, respectively. 59% of patients received inhaled corticosteroids. Factor analysis selected four different factors, explaining 55.5% of total variance. The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.587. Plasma total and specific IgE levels, peripheral blood eosinophil percentage, and FeNO loaded on factor 1; plasma TARC and MDC concentrations on factor 2; MDC, eotaxin and leukotriene B4 concentrations in EBC on factor 3; and plasma eotaxin concentration together with clinical indices including body mass index and disease severity score loaded on factor 4. Post hoc factor analyses revealed similar results when outliers were excluded. Conclusions: The results suggest that atopy related indices and airway inflammation are separate dimensions in the assessment of childhood asthma, and inflammatory markers in peripheral blood and EBC are non-overlapping factors of asthma. PMID:16055623

Biomarkers of exposure, sensitivity and disease

NASA Technical Reports Server (NTRS)

Brooks, A. L.

1999-01-01

PURPOSE: This review is to evaluate the use of biomarkers as an indication of past exposure to radiation or other environmental insults, individual sensitivity and risk for the development of late occurring disease. OVERVIEW: Biomarkers can be subdivided depending on their applications. Markers of exposure and dose can be used to reconstruct and predict past accidental or occupational exposures when limited or no physical measurements were available. Markers of risk or susceptibility can help identify sensitivity individuals that are at increased risk for development of spontaneous disease and may help predict the increased risk in sensitive individuals associated with environmental or therapeutic radiation exposures. Markers of disease represent the initial cellular or molecular changes that occur during disease development. Each of these types of biomarkers serves a unique purpose. OUTLINE: This paper concentrates on biomarkers of dose and exposure and provides a brief review of biomarkers of sensitivity and disease. The review of biomarkers of dose and exposure will demonstrate the usefulness of biomarkers in evaluation of physical factors associated with radiation exposure, such as LET, doserate and dose distribution. It will also evaluate the use of biomarkers to establish relationships that exist between exposure parameters such as energy deposition, environmental concentration of radioactive materials, alpha traversals and dose. In addition, the importance of biological factors on the magnitude of the biomarker response will be reviewed. Some of the factors evaluated will be the influence of species, tissue, cell types and genetic background. The review will demonstrate that markers of sensitivity and disease often have little usefulness in dose-reconstruction and, by the same token, many markers of dose or exposure may not be applicable for prediction of sensitivity or risk.

Use of an Artificial Neural Network to Construct a Model of Predicting Deep Fungal Infection in Lung Cancer Patients.

PubMed

Chen, Jian; Chen, Jie; Ding, Hong-Yan; Pan, Qin-Shi; Hong, Wan-Dong; Xu, Gang; Yu, Fang-You; Wang, Yu-Min

2015-01-01

The statistical methods to analyze and predict the related dangerous factors of deep fungal infection in lung cancer patients were several, such as logic regression analysis, meta-analysis, multivariate Cox proportional hazards model analysis, retrospective analysis, and so on, but the results are inconsistent. A total of 696 patients with lung cancer were enrolled. The factors were compared employing Student's t-test or the Mann-Whitney test or the Chi-square test and variables that were significantly related to the presence of deep fungal infection selected as candidates for input into the final artificial neural network analysis (ANN) model. The receiver operating characteristic (ROC) and area under curve (AUC) were used to evaluate the performance of the artificial neural network (ANN) model and logistic regression (LR) model. The prevalence of deep fungal infection from lung cancer in this entire study population was 32.04%(223/696), deep fungal infections occur in sputum specimens 44.05% (200/454). The ratio of candida albicans was 86.99% (194/223) in the total fungi. It was demonstrated that older (≥65 years), use of antibiotics, low serum albumin concentrations (≤37.18 g /L), radiotherapy, surgery, low hemoglobin hyperlipidemia (≤93.67 g /L), long time of hospitalization (≥14 days) were apt to deep fungal infection and the ANN model consisted of the seven factors. The AUC of ANN model (0.829±0.019) was higher than that of LR model (0.756±0.021). The artificial neural network model with variables consisting of age, use of antibiotics, serum albumin concentrations, received radiotherapy, received surgery, hemoglobin, time of hospitalization should be useful for predicting the deep fungal infection in lung cancer.

Soluble CD30 and Hepatocyte growth factor as predictive markers of antibody-mediated rejection of the kidney allograft.

PubMed

Pavlova, Yelena; Viklicky, Ondrej; Slatinska, Janka; Bürgelova, Marcela; Süsal, Caner; Skibova, Jelena; Honsová, Eva; Striz, Ilja; Kolesar, Libor; Slavcev, Antonij

2011-07-01

Our retrospective study was aimed to assess the relevance of pre- and post-transplant measurements of serum concentrations of the soluble CD30 molecule (soluble CD30, sCD30) and the cytokine Hepatocyte growth factor (HGF) for prediction of the risk for development of antibody-mediated rejection (AMR) in kidney transplant patients. Evaluation of sCD30, HGF levels and the presence of HLA-specific antibodies in a cohort of 205 patients was performed before, 2weeks and 6months after transplantation. Patients were followed up for kidney graft function and survival for two years. We found a tendency of higher incidence of AMR in retransplanted patients with elevated pre-transplant sCD30 (≥100U/ml) (p=0.051), however no such correlation was observed in first-transplant patients. Kidney recipients with simultaneously high sCD30 and HLA-specific antibodies (sCD30+/Ab+) before transplantation had significantly lower AMR-free survival compared to the other patient groups (p<0.001). HGF concentrations were not associated with the incidence of AMR at any time point of measurement, nevertheless, the combined analysis HGF and sCD30 showed increased incidence of AMR in recipients with elevated pretransplant sCD30 and low HGF levels. the predictive value of pretransplant sCD30 for the development of antibody-mediated rejection after transplantation is significantly potentiated by the co-presence of HLA specific antibodies. The role of HGF as a rejection-protective factor in patients with high pretransplant HGF levels would need further investigation. Copyright © 2011 Elsevier B.V. All rights reserved.

Combined effects of water temperature and copper ion concentration on catalase activity in Crassostrea ariakensis

NASA Astrophysics Data System (ADS)

Wang, Hui; Yang, Hongshuai; Liu, Jiahui; Li, Yanhong; Liu, Zhigang

2015-07-01

A central composite experimental design and response surface method were used to investigate the combined effects of water temperature (18-34°C) and copper ion concentration (0.1-1.5 mg/L) on the catalase (CAT) activity in the digestive gland of Crassostrea ariakensis. The results showed that the linear effects of temperature were significant ( P<0.01), the quadratic effects of temperature were significant ( P<0.05), the linear effects of copper ion concentration were not significant ( P>0.05), and the quadratic effects of copper ion concentration were significant ( P<0.05). Additionally, the synergistic effects of temperature and copper ion concentration were not significant ( P>0.05), and the effect of temperature was greater than that of copper ion concentration. A model equation of CAT enzyme activity in the digestive gland of C. ariakensis toward the two factors of interest was established, with R 2, Adj. R 2 and Pred. R 2 values as high as 0.943 7, 0.887 3 and 0.838 5, respectively. These findings suggested that the goodness of fit to experimental data and predictive capability of the model were satisfactory, and could be practically applied for prediction under the conditions of the study. Overall, the results suggest that the simultaneous variation of temperature and copper ion concentration alters the activity of the antioxidant enzyme CAT by modulating active oxygen species metabolism, which may be utilized as a biomarker to detect the effects of copper pollution.

Dissolved Organic Carbon Degradation in Response to Nutrient Amendments in Southwest Greenland Lakes

NASA Astrophysics Data System (ADS)

Burpee, B. T.; Northington, R.; Simon, K. S.; Saros, J. E.

2014-12-01

Aquatic ecosystems across the Arctic are currently experiencing rapid shifts in biotic, chemical, and physical factors in response to climate change. Preliminary data from multiple lakes in southwestern Greenland indicate decreasing dissolved organic carbon (DOC) concentrations over the past decade. Though several factors may be contributing to this phenomenon, this study attempts to elucidate the potential of heterotrophic bacteria to degrade DOC in the presence of increasing nutrient concentrations. In certain Arctic regions, nutrient subsidies have been released into lakes due to permafrost thaw. If this is occurring in southwestern Greenland, we hypothesized that increased nutrient concentrations will relieve nutrient limitation, thereby allowing heterotrophic bacteria to utilize DOC as an energy source. This prediction was tested using experimental DOC degradation assays from four sample lakes. Four nutrient amendment treatments (control, N, P, and N + P) were used to simulate in situ subsidies. Five time points were sampled during the incubation: days 0, 3, 6, 14, and 60. Total organic carbon (TOC) and parallel factor (PARAFAC) analysis were used to monitor the relative concentrations of different DOC fractions over time. In addition, samples for extracellular enzyme activity (EEA) analysis were collected at every time point. Early analysis of fulvic and humic pools of DOC do not indicate any significant change from days 0 to 14. This could be due to the fact that these DOC fractions are relatively recalcitrant. This study will be important in determining whether bacterial degradation could be a contributing factor to DOC decline in arctic lakes.

High risk of progression to NIDDM in South-African Indians with impaired glucose tolerance.

PubMed

Motala, A A; Omar, M A; Gouws, E

1993-04-01

A four-yr prospective study was undertaken to examine the natural history of IGT in 128 South-African Indians classified as such at year 0 of the study, based on WHO criteria. Subjects were reexamined at year 1 and year 4. Of the 113 subjects who completed the study, 50.4% progressed to NIDDM (rate of progression 12.6%/yr), 24.8% persisted with IGT, and 24.8%, reverted to NGT. The majority (72%) who progressed to NIDDM did so in year 1. At year 1, 47 subjects were still classified as IGT; of the 40 subjects completing the study, 16 subjects (40%) progressed to NIDDM, 17 subjects (42.5%) persisted with IGT, and 7 subjects (17.5%) reverted to NGT. Examination of risk factors predictive of subsequent progression to NIDDM was undertaken by analysis of baseline variables in two ways: When year 0 was used as baseline (in 113 IGT0 subjects), significant predictive risk factors were the FPG and 2-h plasma glucose concentrations. All subjects who at year 0 had 2-h plasma glucose > or = 10.2 and < 11.1 mM or FPG > or = 7.3 but < 7.8 mM, subsequently progressed to NIDDM. When year 1 was used as baseline (40 IGT1 subjects), 90-min plasma glucose concentration (midtest level) was found to be a significant risk factor for development of NIDDM. In conclusion, this study has demonstrated that in South-African Indians with IGT, the majority (50.4%) progress to NIDDM within 4 yr; significant predictors of subsequent diabetes are the baseline fasting and 2-h plasma glucose concentration.(ABSTRACT TRUNCATED AT 250 WORDS)

Effect of noise in principal component analysis with an application to ozone pollution

NASA Astrophysics Data System (ADS)

Tsakiri, Katerina G.

This thesis analyzes the effect of independent noise in principal components of k normally distributed random variables defined by a covariance matrix. We prove that the principal components as well as the canonical variate pairs determined from joint distribution of original sample affected by noise can be essentially different in comparison with those determined from the original sample. However when the differences between the eigenvalues of the original covariance matrix are sufficiently large compared to the level of the noise, the effect of noise in principal components and canonical variate pairs proved to be negligible. The theoretical results are supported by simulation study and examples. Moreover, we compare our results about the eigenvalues and eigenvectors in the two dimensional case with other models examined before. This theory can be applied in any field for the decomposition of the components in multivariate analysis. One application is the detection and prediction of the main atmospheric factor of ozone concentrations on the example of Albany, New York. Using daily ozone, solar radiation, temperature, wind speed and precipitation data, we determine the main atmospheric factor for the explanation and prediction of ozone concentrations. A methodology is described for the decomposition of the time series of ozone and other atmospheric variables into the global term component which describes the long term trend and the seasonal variations, and the synoptic scale component which describes the short term variations. By using the Canonical Correlation Analysis, we show that solar radiation is the only main factor between the atmospheric variables considered here for the explanation and prediction of the global and synoptic scale component of ozone. The global term components are modeled by a linear regression model, while the synoptic scale components by a vector autoregressive model and the Kalman filter. The coefficient of determination, R2, for the prediction of the synoptic scale ozone component was found to be the highest when we consider the synoptic scale component of the time series for solar radiation and temperature. KEY WORDS: multivariate analysis; principal component; canonical variate pairs; eigenvalue; eigenvector; ozone; solar radiation; spectral decomposition; Kalman filter; time series prediction

Testing prediction capabilities of an 131I terrestrial transport model by using measurements collected at the Hanford nuclear facility.

PubMed

Apostoaei, A Iulian

2005-05-01

A model describing transport of 131I in the environment was developed by SENES Oak Ridge, Inc., for assessment of radiation doses and excess lifetime risk from 131I atmospheric releases from Oak Ridge Reservation in Oak Ridge, Tennessee, and from Idaho National Engineering and Environmental Laboratory in southeast Idaho. This paper describes the results of an exercise designed to test the reliability of this model and to identify the main sources of uncertainty in doses and risks estimated by this model. The testing of the model was based on materials published by the International Atomic Energy Agency BIOMASS program, specifically environmental data collected after the release into atmosphere of 63 curies of 131I during 2-5 September 1963, after an accident at the Hanford PUREX Chemical Separations Plant, in Hanford, Washington. Measurements of activity in air, vegetation, and milk were collected in nine counties around Hanford during the first couple of months after the accident. The activity of 131I in the thyroid glands of two children was measured 47 d after the accident. The model developed by SENES Oak Ridge, Inc., was used to estimate concentrations of 131I in environmental media, thyroid doses for the general population, and the activity of 131I in thyroid glands of the two children. Predicted concentrations of 131I in pasture grass and milk and thyroid doses were compared with similar estimates produced by other modelers. The SENES model was also used to estimate excess lifetime risk of thyroid cancer due to the September 1963 releases of 131I from Hanford. The SENES model was first calibrated and then applied to all locations of interest around Hanford without fitting the model parameters to a given location. Predictions showed that the SENES model reproduces satisfactorily the time-dependent and the time-integrated measured concentrations in vegetation and milk, and provides reliable estimates of 131I activity in thyroids of children. SENES model generated concentrations of 131I closer to observed concentrations, as compared to the predictions produced with other models. The inter-model comparison showed that variation of thyroid doses among all participating models (SENES model included) was a factor of 3 for the general population, but a factor of 10 for the two studied children. As opposed to other models, SENES model allows a complete analysis of uncertainties in every predicted quantity, including estimated thyroid doses and risk of thyroid cancer. The uncertainties in the risk-per-unit-dose and the dose-per-unit-intake coefficients are major contributors to the uncertainty in the estimated lifetime risk and thyroid dose, respectively. The largest contributors to the uncertainty in the estimated concentration in milk are the feed-to-milk transfer factor (F(m)), the dry deposition velocity (V(d)), and the mass interception factor (r/Y)dry for the elemental form of iodine (I2). Exposure to the 1963 PUREX/Hanford accident produced low doses and risks for people living at the studied locations. The upper 97.5th percentile of the excess lifetime risk of thyroid cancer for the most extreme situations is about 10(-4). Measurements in pasture grass and milk at all locations around Hanford indicate a very low transfer of 131I from pasture to cow's milk (e.g., a feed-to-milk transfer coefficient, F(m), for commercial cows of about 0.0022 d L(-1)). These values are towards the low end of F(m) values measured elsewhere and they are low compared to the F(m) values used in other dose reconstruction studies, including the Hanford Environmental Dose Reconstruction.

Determination of the priority indexes for the oil refinery wastewater treatment process

NASA Astrophysics Data System (ADS)

Chesnokova, M. G.; Myshlyavtsev, A. V.; Kriga, A. S.; Shaporenko, A. P.; Markelov, V. V.

2017-08-01

The wastewater biological treatment intensity and effectiveness are influenced by many factors: temperature, pH, presence and concentration of toxic substances, the biomass concentration et al. Regulation of them allows controlling the biological treatment process. Using the Bayesian theorem the link between changes was determined and the wastewater indexes normative limits exceeding influence for activated sludge characteristics alteration probability was evaluated. The estimation of total, or aposterioric, priority index presence probability, which characterizes the wastewater treatment level, is an important way to use the Bayesian theorem in activated sludge swelling prediction at the oil refinery biological treatment unit.

Enhanced power factor of higher manganese silicide via melt spin synthesis method

DOE PAGES

Shi, Xiaoya; Shi, Xun; Li, Yulong; ...

2014-12-30

We report on the thermoelectric properties of the Higher Manganese Silicide MnSi₁.₇₅ (HMS) synthesized by means of a one-step non-equilibrium method. The ultrahigh cooling rate generated from the melt-spin technique is found to be effective in reducing second phases, which are inevitable during the traditional solid state diffusion processes. Aside from being detrimental to thermoelectric properties, second phases skew the revealing of the intrinsic properties of this class of materials, for example the optimal level of carrier concentration. With this melt-spin sample, we are able to formulate a simple model based on a single parabolic band that can well describemore » the carrier concentration dependence of the Seebeck coefficient and power factor of the data reported in the literature. An optimal carrier concentration around 5x10²⁰ cm⁻³ at 300 K is predicted according to this model. The phase-pure melt-spin sample shows the largest power factor at high temperature, resulting in the highest zT value among the three samples in this paper; the maximum value is superior to those reported in the literatures.« less

Population pharmacokinetics of transdermal fentanyl in patients with cancer-related pain.

PubMed

Kokubun, Hideya; Ebinuma, Keiichi; Matoba, Motohiro; Takayanagi, Risa; Yamada, Yasuhiko; Yago, Kazuo

2012-06-01

Determining the appropriate dose of transdermal fentanyl (TDF) for the alleviation of cancer pain requires determining the factors causing variations in serum fentanyl concentration after TDF treatment. The objective of this study was to identify these factors and incorporate them into a formula that can be used to predict serum fentanyl concentration after application of a TDF patch. Blood samples of cancer patients treated with a TDF patch for the alleviation of pain were collected at 24, 48, and 72 hours after application to evaluate population pharmacokinetics using the nonlinear mixed-effect model (NONMEM). Based upon this evaluation, Child-Pugh Score and use of a cytochrome P450 3A4 (CYP3A4) inducer were identified as the most significant factors in variations in serum fentanyl concentration and incorporated into the following Final Model formula: CL(fenta) (L/h) = 3.53 × (15 - Child-Pugh Score) × (1 + 1.38 × use or no use of CYP3A4 inducer). Bootstrap evaluation of the Final Model revealed a high convergence rate, suggesting that the model formula is a reliable and useful tool for determining TDF dose for the alleviation of cancer pain.

Enhanced power factor of higher manganese silicide via melt spin synthesis method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shi, Xiaoya; Shi, Xun; Li, Yulong

We report on the thermoelectric properties of the Higher Manganese Silicide MnSi₁.₇₅ (HMS) synthesized by means of a one-step non-equilibrium method. The ultrahigh cooling rate generated from the melt-spin technique is found to be effective in reducing second phases, which are inevitable during the traditional solid state diffusion processes. Aside from being detrimental to thermoelectric properties, second phases skew the revealing of the intrinsic properties of this class of materials, for example the optimal level of carrier concentration. With this melt-spin sample, we are able to formulate a simple model based on a single parabolic band that can well describemore » the carrier concentration dependence of the Seebeck coefficient and power factor of the data reported in the literature. An optimal carrier concentration around 5x10²⁰ cm⁻³ at 300 K is predicted according to this model. The phase-pure melt-spin sample shows the largest power factor at high temperature, resulting in the highest zT value among the three samples in this paper; the maximum value is superior to those reported in the literatures.« less

Prevalence, determinants and clinical correlates of vitamin D deficiency in patients with Chronic Obstructive Pulmonary Disease in London, UK.

PubMed

Jolliffe, David A; James, Wai Yee; Hooper, Richard L; Barnes, Neil C; Greiller, Claire L; Islam, Kamrul; Bhowmik, Angshu; Timms, Peter M; Rajakulasingam, Raj K; Choudhury, Aklak B; Simcock, David E; Hyppönen, Elina; Walton, Robert T; Corrigan, Christopher J; Griffiths, Christopher J; Martineau, Adrian R

2018-01-01

Vitamin D deficiency is common in patients with chronic obstructive pulmonary disease (COPD), yet a comprehensive analysis of environmental and genetic determinants of serum 25-hydroxyvitamin D (25[OH]D) concentration in patients with this condition is lacking. We conducted a multi-centre cross-sectional study in 278 COPD patients aged 41-92 years in London, UK. Details of potential environmental determinants of vitamin D status and COPD symptom control and severity were collected by questionnaire, and blood samples were taken for analysis of serum 25(OH)D concentration and DNA extraction. All participants performed spirometry and underwent measurement of weight and height. Quadriceps muscle strength (QS) was measured in 134 participants, and sputum induction with enumeration of lower airway eosinophil and neutrophil counts was performed for 44 participants. Thirty-seven single nucleotide polymorphisms (SNP) in 11 genes in the vitamin D pathway (DBP, DHCR7, CYP2R1, CYP27B1, CYP24A1, CYP27A1, CYP3A4, LRP2, CUBN, RXRA, and VDR) were typed using Taqman allelic discrimination assays. Linear regression was used to identify environmental and genetic factors independently associated with serum 25(OH)D concentration and to determine whether vitamin D status or genetic factors independently associated with % predicted forced expiratory volume in one second (FEV 1 ), % predicted forced vital capacity (FVC), the ratio of FEV 1 to FVC (FEV 1 :FVC), daily inhaled corticosteroid (ICS) dose, respiratory quality of life (QoL), QS, and the percentage of eosinophils and neutrophils in induced sputum. Mean serum 25(OH)D concentration was 45.4nmol/L (SD 25.3); 171/278 (61.5%) participants were vitamin D deficient (serum 25[OH]D concentration <50nmol/L). Lower vitamin D status was independently associated with higher body mass index (P=0.001), lower socio-economic position (P=0.037), lack of vitamin D supplement consumption (P<0.001), sampling in Winter or Spring (P for trend=0.006) and lack of a recent sunny holiday (P=0.002). Vitamin D deficiency associated with reduced % predicted FEV 1 (P for trend=0.060) and % predicted FVC (P for trend=0.003), but it did not associate with FEV 1 :FVC, ICS dose, QoL, QS, or the percentage of eosinophils or neutrophils in induced sputum. After correction for multiple comparisons testing, genetic variation in the vitamin D pathway was not found to associate with serum 25(OH)D concentration or clinical correlates of COPD severity. Vitamin D deficiency was common in this group of COPD patients in the UK, and it associated independently with reduced % predicted FEV1 and FVC. However, genetic variation in the vitamin D pathway was not associated with vitamin D status or severity of COPD. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluation of Liver Biomarkers as Prognostic Factors for Outcomes to Yttrium-90 Radioembolization of Primary and Secondary Liver Malignancies.

PubMed

Henrie, Adam M; Wittstrom, Kristina; Delu, Adam; Deming, Paulina

2015-09-01

The objective of this study was to examine indicators of liver function and inflammation for prognostic value in predicting outcomes to yttrium-90 radioembolization (RE). In a retrospective analysis, markers of liver function and inflammation, biomarkers required to stage liver function and inflammation, and data regarding survival, tumor response, and progression after RE were recorded. Univariate regression models were used to investigate the prognostic value of liver biomarkers in predicting outcome to RE as measured by survival, tumor progression, and radiographic and biochemical tumor response. Markers from all malignancy types were analyzed together. A subgroup analysis was performed on markers from patients with metastatic colorectal cancer. A total of 31 patients received RE from 2004 to 2014. Median survival after RE for all malignancies combined was 13.6 months (95% CI: 6.7-17.6 months). Results from an exploratory analysis of patient data suggest that liver biomarkers, including albumin concentrations, international normalized ratio, bilirubin concentrations, and the model for end-stage liver disease score, possess prognostic value in predicting outcomes to RE.

The second-language vocabulary trajectories of Turkish immigrant children in Norway from ages five to ten: the role of preschool talk exposure, maternal education, and co-ethnic concentration in the neighborhood.

PubMed

Rydland, Veslemøy; Grøver, Vibeke; Lawrence, Joshua

2014-03-01

Little research has explored how preschools can support children's second-language (L2) vocabulary development. This study keenly followed the progress of twemty-six Turkish immigrant children growing up in Norway from preschool (age five) to fifth grade (age ten). Four different measures of preschool talk exposure (amount and diversity of teacher-led group talk and amount and diversity of peer talk), as well as the demographic variables of maternal education and co-ethnic concentration in the neighborhood, were employed to predict the children's L2 vocabulary trajectories. The results of growth analyses revealed that maternal education was the only variable predicting children's vocabulary growth during the elementary years. However, teacher-led talk, peer talk, and neighborhood predicted children's L2 vocabulary skills at age five, and these differences were maintained up to age ten. This study underscores the importance of both preschool talk exposure (teacher-led talk and peer talk) and demographic factors on L2 learners' vocabulary development.

The relationship between uric acid and potassium in normal subjects.

PubMed Central

Kennedy, A C; Boddy, K; King, P C; Brennan, J; Anderson, J A; Buchanan, W W

1978-01-01

The serum uric acid concentration in normal healthy subjects has been studied in relation to sex, height, weight, lean body mass measured from total body potassium and predicted from the Hume-Weyers formula (1971), total body potassium, plasma potassium and urea, and packed cell volume. The strongest correlation was found with sex, but height, weight, total body potassium, lean body mass (measured and predicted) also correlated significantly with serum uric acid concentration. However, when the sex variable was removed, the other factors lost their significant correlation. Finally, total red blood cell and plasma volumes were predicted (Hume and Goldberg, 1964) and from these an estimate of total plasma uric acid, total plasma potassium, and total red blood cell potassium obtained. Measured total body potassium was found to correlate well with total plasma potassium and total red blood cell potassium independent of sex. Total plasma uric acid correlated well with measured total body potassium when both sexes were considered and when separated into male and female groups the males retained a significant correlation as did the female group. PMID:686865

Risk of nitrate in groundwaters of the United States - A national perspective

USGS Publications Warehouse

Nolan, B.T.; Ruddy, B.C.; Hitt, K.J.; Helsel, D.R.

1997-01-01

Nitrate contamination of groundwater occurs in predictable patterns, based on findings of the U.S. Geological Survey's (USGS) National Water Quality Assessment (NAWQA) Program. The NAWQA Program was begun in 1991 to describe the quality of the Nation's water resources, using nationally consistent methods. Variables affecting nitrate concentration in groundwater were grouped as 'input' factors (population density end the amount of nitrogen contributed by fertilizer, manure, and atmospheric sources) and 'aquifer vulnerability' factors (soil drainage characteristic and the ratio of woodland acres to cropland acres in agricultural areas) and compiled in a national map that shows patterns of risk for nitrate contamination of groundwater. Areas with high nitrogen input, well-drained soils, and low woodland to cropland ratio have the highest potential for contamination of shallow groundwater by nitrate. Groundwater nitrate data collected through 1992 from wells less than 100 ft deep generally verified the risk patterns shown on the national map. Median nitrate concentration was 0.2 mg/L in wells representing the low-risk group, and the maximum contaminant level (MCL) was exceeded in 3% of the wells. In contrast, median nitrate concentration was 4.8 mg/L in wells representing the high-risk group, and the MCL was exceeded in 25% of the wells.Nitrate contamination of groundwater occurs in predictable patterns, based on findings of the U.S. Geological Survey's (USGS) National Water Quality Assessment (NAWQA) Program. The NAWQA Program was begun in 1991 to describe the quality of the Nation's water resources, using nationally consistent methods. Variables affecting nitrate concentration in groundwater were grouped as `input' factors (population density and the amount of nitrogen contributed by fertilizer, manure, and atmospheric sources) and `aquifer vulnerability' factors (soil drainage characteristic and the ratio of woodland acres to cropland acres in agricultural areas) and compiled in a national map that shows patterns of risk for nitrate contamination of groundwater. Areas with high nitrogen input, well-drained soils, and low woodland to cropland ratio have the highest potential for contamination of shallow groundwater by nitrate. Groundwater nitrate data collected through 1992 from wells less than 100 ft deep generally verified the risk patterns shown on the national map. Median nitrate concentration was 0.2 mg/L in wells representing the low-risk group, and the maximum contaminant level (MCL) was exceeded in 3% of the wells. In contrast, median nitrate concentration was 4.8 mg/L in wells representing the high-risk group, and the MCL was exceeded in 25% of the wells.

Artificial Intelligence versus Statistical Modeling and Optimization of Cholesterol Oxidase Production by using Streptomyces Sp.

PubMed Central

Niwas, Ram; Osama, Khwaja; Khan, Saif; Haque, Shafiul; Tripathi, C. K. M.; Mishra, B. N.

2015-01-01

Cholesterol oxidase (COD) is a bi-functional FAD-containing oxidoreductase which catalyzes the oxidation of cholesterol into 4-cholesten-3-one. The wider biological functions and clinical applications of COD have urged the screening, isolation and characterization of newer microbes from diverse habitats as a source of COD and optimization and over-production of COD for various uses. The practicability of statistical/ artificial intelligence techniques, such as response surface methodology (RSM), artificial neural network (ANN) and genetic algorithm (GA) have been tested to optimize the medium composition for the production of COD from novel strain Streptomyces sp. NCIM 5500. All experiments were performed according to the five factor central composite design (CCD) and the generated data was analysed using RSM and ANN. GA was employed to optimize the models generated by RSM and ANN. Based upon the predicted COD concentration, the model developed with ANN was found to be superior to the model developed with RSM. The RSM-GA approach predicted maximum of 6.283 U/mL COD production, whereas the ANN-GA approach predicted a maximum of 9.93 U/mL COD concentration. The optimum concentrations of the medium variables predicted through ANN-GA approach were: 1.431 g/50 mL soybean, 1.389 g/50 mL maltose, 0.029 g/50 mL MgSO4, 0.45 g/50 mL NaCl and 2.235 ml/50 mL glycerol. The experimental COD concentration was concurrent with the GA predicted yield and led to 9.75 U/mL COD production, which was nearly two times higher than the yield (4.2 U/mL) obtained with the un-optimized medium. This is the very first time we are reporting the statistical versus artificial intelligence based modeling and optimization of COD production by Streptomyces sp. NCIM 5500. PMID:26368924

Artificial Intelligence versus Statistical Modeling and Optimization of Cholesterol Oxidase Production by using Streptomyces Sp.

PubMed

Pathak, Lakshmi; Singh, Vineeta; Niwas, Ram; Osama, Khwaja; Khan, Saif; Haque, Shafiul; Tripathi, C K M; Mishra, B N

2015-01-01

Cholesterol oxidase (COD) is a bi-functional FAD-containing oxidoreductase which catalyzes the oxidation of cholesterol into 4-cholesten-3-one. The wider biological functions and clinical applications of COD have urged the screening, isolation and characterization of newer microbes from diverse habitats as a source of COD and optimization and over-production of COD for various uses. The practicability of statistical/ artificial intelligence techniques, such as response surface methodology (RSM), artificial neural network (ANN) and genetic algorithm (GA) have been tested to optimize the medium composition for the production of COD from novel strain Streptomyces sp. NCIM 5500. All experiments were performed according to the five factor central composite design (CCD) and the generated data was analysed using RSM and ANN. GA was employed to optimize the models generated by RSM and ANN. Based upon the predicted COD concentration, the model developed with ANN was found to be superior to the model developed with RSM. The RSM-GA approach predicted maximum of 6.283 U/mL COD production, whereas the ANN-GA approach predicted a maximum of 9.93 U/mL COD concentration. The optimum concentrations of the medium variables predicted through ANN-GA approach were: 1.431 g/50 mL soybean, 1.389 g/50 mL maltose, 0.029 g/50 mL MgSO4, 0.45 g/50 mL NaCl and 2.235 ml/50 mL glycerol. The experimental COD concentration was concurrent with the GA predicted yield and led to 9.75 U/mL COD production, which was nearly two times higher than the yield (4.2 U/mL) obtained with the un-optimized medium. This is the very first time we are reporting the statistical versus artificial intelligence based modeling and optimization of COD production by Streptomyces sp. NCIM 5500.

Effects of 31 FDA approved small-molecule kinase inhibitors on isolated rat liver mitochondria.

PubMed

Zhang, Jun; Salminen, Alec; Yang, Xi; Luo, Yong; Wu, Qiangen; White, Matthew; Greenhaw, James; Ren, Lijun; Bryant, Matthew; Salminen, William; Papoian, Thomas; Mattes, William; Shi, Qiang

2017-08-01

The FDA has approved 31 small-molecule kinase inhibitors (KIs) for human use as of November 2016, with six having black box warnings for hepatotoxicity (BBW-H) in product labeling. The precise mechanisms and risk factors for KI-induced hepatotoxicity are poorly understood. Here, the 31 KIs were tested in isolated rat liver mitochondria, an in vitro system recently proposed to be a useful tool to predict drug-induced hepatotoxicity in humans. The KIs were incubated with mitochondria or submitochondrial particles at concentrations ranging from therapeutic maximal blood concentrations (Cmax) levels to 100-fold Cmax levels. Ten endpoints were measured, including oxygen consumption rate, inner membrane potential, cytochrome c release, swelling, reactive oxygen species, and individual respiratory chain complex (I-V) activities. Of the 31 KIs examined only three including sorafenib, regorafenib and pazopanib, all of which are hepatotoxic, caused significant mitochondrial toxicity at concentrations equal to the Cmax, indicating that mitochondrial toxicity likely contributes to the pathogenesis of hepatotoxicity associated with these KIs. At concentrations equal to 100-fold Cmax, 18 KIs were found to be toxic to mitochondria, and among six KIs with BBW-H, mitochondrial injury was induced by regorafenib, lapatinib, idelalisib, and pazopanib, but not ponatinib, or sunitinib. Mitochondrial liability at 100-fold Cmax had a positive predictive power (PPV) of 72% and negative predictive power (NPV) of 33% in predicting human KI hepatotoxicity as defined by product labeling, with the sensitivity and specificity being 62% and 44%, respectively. Similar predictive power was obtained using the criterion of Cmax ≥1.1 µM or daily dose ≥100 mg. Mitochondrial liability at 1-2.5-fold Cmax showed a 100% PPV and specificity, though the NPV and sensitivity were 32% and 14%, respectively. These data provide novel mechanistic insights into KI hepatotoxicity and indicate that mitochondrial toxicity at therapeutic levels can help identify hepatotoxic KIs.

Pharmaceuticals in water, fish and osprey nestlings in Delaware River and Bay

USGS Publications Warehouse

Bean, Thomas G.; Rattner, Barnett A.; Lazarus, Rebecca S.; Day, Daniel D.; Burket, S. Rebekah; Brooks, Bryan W.; Haddad, Samuel P.; Bowerman, William W.

2018-01-01

Exposure of wildlife to Active Pharmaceutical Ingredients (APIs) is likely to occur but studies of risk are limited. One exposure pathway that has received attention is trophic transfer of APIs in a water-fish-osprey food chain. Samples of water, fish plasma and osprey plasma were collected from Delaware River and Bay, and analyzed for 21 APIs. Only 2 of 21 analytes exceeded method detection limits in osprey plasma (acetaminophen and diclofenac) with plasma levels typically 2–3 orders of magnitude below human therapeutic concentrations (HTC). We built upon a screening level model used to predict osprey exposure to APIs in Chesapeake Bay and evaluated whether exposure levels could have been predicted in Delaware Bay had we just measured concentrations in water or fish. Use of surface water and BCFs did not predict API concentrations in fish well, likely due to fish movement patterns, and partitioning and bioaccumulation uncertainties associated with these ionizable chemicals. Input of highest measured API concentration in fish plasma combined with pharmacokinetic data accurately predicted that diclofenac and acetaminophen would be the APIs most likely detected in osprey plasma. For the majority of APIs modeled, levels were not predicted to exceed 1 ng/mL or method detection limits in osprey plasma. Based on the target analytes examined, there is little evidence that APIs represent a significant risk to ospreys nesting in Delaware Bay. If an API is present in fish orders of magnitude below HTC, sampling of fish-eating birds is unlikely to be necessary. However, several human pharmaceuticals accumulated in fish plasma within a recommended safety factor for HTC. It is now important to expand the scope of diet-based API exposure modeling to include alternative exposure pathways (e.g., uptake from landfills, dumps and wastewater treatment plants) and geographic locations (developing countries) where API contamination of the environment may represent greater risk.

Evaluating the spatial variation of total mercury in young-of-year yellow perch (Perca flavescens), surface water and upland soil for watershed-lake systems within the southern Boreal Shield.

PubMed

Gabriel, Mark C; Kolka, Randy; Wickman, Trent; Nater, Ed; Woodruff, Laurel

2009-06-15

The primary objective of this research is to investigate relationships between mercury in upland soil, lake water and fish tissue and explore the cause for the observed spatial variation of THg in age one yellow perch (Perca flavescens) for ten lakes within the Superior National Forest. Spatial relationships between yellow perch THg tissue concentration and a total of 45 watershed and water chemistry parameters were evaluated for two separate years: 2005 and 2006. Results show agreement with other studies where watershed area, lake water pH, nutrient levels (specifically dissolved NO(3)(-)-N) and dissolved iron are important factors controlling and/or predicting fish THg level. Exceeding all was the strong dependence of yellow perch THg level on soil A-horizon THg and, in particular, soil O-horizon THg concentrations (Spearman rho=0.81). Soil B-horizon THg concentration was significantly correlated (Pearson r=0.75) with lake water THg concentration. Lakes surrounded by a greater percentage of shrub wetlands (peatlands) had higher fish tissue THg levels, thus it is highly possible that these wetlands are main locations for mercury methylation. Stepwise regression was used to develop empirical models for the purpose of predicting the spatial variation in yellow perch THg over the studied region. The 2005 regression model demonstrates it is possible to obtain good prediction (up to 60% variance description) of resident yellow perch THg level using upland soil O-horizon THg as the only independent variable. The 2006 model shows even greater prediction (r(2)=0.73, with an overall 10 ng/g [tissue, wet weight] margin of error), using lake water dissolved iron and watershed area as the only model independent variables. The developed regression models in this study can help with interpreting THg concentrations in low trophic level fish species for untested lakes of the greater Superior National Forest and surrounding Boreal ecosystem.

Application of multi-factorial design of experiments to successfully optimize immunoassays for robust measurements of therapeutic proteins.

PubMed

Ray, Chad A; Patel, Vimal; Shih, Judy; Macaraeg, Chris; Wu, Yuling; Thway, Theingi; Ma, Mark; Lee, Jean W; Desilva, Binodh

2009-02-20

Developing a process that generates robust immunoassays that can be used to support studies with tight timelines is a common challenge for bioanalytical laboratories. Design of experiments (DOEs) is a tool that has been used by many industries for the purpose of optimizing processes. The approach is capable of identifying critical factors and their interactions with a minimal number of experiments. The challenge for implementing this tool in the bioanalytical laboratory is to develop a user-friendly approach that scientists can understand and apply. We have successfully addressed these challenges by eliminating the screening design, introducing automation, and applying a simple mathematical approach for the output parameter. A modified central composite design (CCD) was applied to three ligand binding assays. The intra-plate factors selected were coating, detection antibody concentration, and streptavidin-HRP concentrations. The inter-plate factors included incubation times for each step. The objective was to maximize the logS/B (S/B) of the low standard to the blank. The maximum desirable conditions were determined using JMP 7.0. To verify the validity of the predictions, the logS/B prediction was compared against the observed logS/B during pre-study validation experiments. The three assays were optimized using the multi-factorial DOE. The total error for all three methods was less than 20% which indicated method robustness. DOE identified interactions in one of the methods. The model predictions for logS/B were within 25% of the observed pre-study validation values for all methods tested. The comparison between the CCD and hybrid screening design yielded comparable parameter estimates. The user-friendly design enables effective application of multi-factorial DOE to optimize ligand binding assays for therapeutic proteins. The approach allows for identification of interactions between factors, consistency in optimal parameter determination, and reduced method development time.

Measurements of hydroxyl and hydroperoxy radicals during CalNex-LA: Model comparisons and radical budgets

NASA Astrophysics Data System (ADS)

Griffith, S. M.; Hansen, R. F.; Dusanter, S.; Michoud, V.; Gilman, J. B.; Kuster, W. C.; Veres, P. R.; Graus, M.; de Gouw, J. A.; Roberts, J.; Young, C.; Washenfelder, R.; Brown, S. S.; Thalman, R.; Waxman, E.; Volkamer, R.; Tsai, C.; Stutz, J.; Flynn, J. H.; Grossberg, N.; Lefer, B.; Alvarez, S. L.; Rappenglueck, B.; Mielke, L. H.; Osthoff, H. D.; Stevens, P. S.

2016-04-01

Measurements of hydroxyl (OH) and hydroperoxy (HO2*) radical concentrations were made at the Pasadena ground site during the CalNex-LA 2010 campaign using the laser-induced fluorescence-fluorescence assay by gas expansion technique. The measured concentrations of OH and HO2* exhibited a distinct weekend effect, with higher radical concentrations observed on the weekends corresponding to lower levels of nitrogen oxides (NOx). The radical measurements were compared to results from a zero-dimensional model using the Regional Atmospheric Chemical Mechanism-2 constrained by NOx and other measured trace gases. The chemical model overpredicted measured OH concentrations during the weekends by a factor of approximately 1.4 ± 0.3 (1σ), but the agreement was better during the weekdays (ratio of 1.0 ± 0.2). Model predicted HO2* concentrations underpredicted by a factor of 1.3 ± 0.2 on the weekends, while measured weekday concentrations were underpredicted by a factor of 3.0 ± 0.5. However, increasing the modeled OH reactivity to match the measured total OH reactivity improved the overall agreement for both OH and HO2* on all days. A radical budget analysis suggests that photolysis of carbonyls and formaldehyde together accounted for approximately 40% of radical initiation with photolysis of nitrous acid accounting for 30% at the measurement height and ozone photolysis contributing less than 20%. An analysis of the ozone production sensitivity reveals that during the week, ozone production was limited by volatile organic compounds throughout the day during the campaign but NOx limited during the afternoon on the weekends.

Critical Concentration Ratio for Solar Thermoelectric Generators

NASA Astrophysics Data System (ADS)

ur Rehman, Naveed; Siddiqui, Mubashir Ali

2016-10-01

A correlation for determining the critical concentration ratio (CCR) of solar concentrated thermoelectric generators (SCTEGs) has been established, and the significance of the contributing parameters is discussed in detail. For any SCTEG, higher concentration ratio leads to higher temperatures at the hot side of modules. However, the maximum value of this temperature for safe operation is limited by the material properties of the modules and should be considered as an important design constraint. Taking into account this limitation, the CCR can be defined as the maximum concentration ratio usable for a particular SCTEG. The established correlation is based on factors associated with the material and geometric properties of modules, thermal characteristics of the receiver, installation site attributes, and thermal and electrical operating conditions. To reduce the number of terms in the correlation, these factors are combined to form dimensionless groups by applying the Buckingham Pi theorem. A correlation model containing these groups is proposed and fit to a dataset obtained by simulating a thermodynamic (physical) model over sampled values acquired by applying the Latin hypercube sampling (LHS) technique over a realistic distribution of factors. The coefficient of determination and relative error are found to be 97% and ±20%, respectively. The correlation is validated by comparing the predicted results with literature values. In addition, the significance and effects of the Pi groups on the CCR are evaluated and thoroughly discussed. This study will lead to a wide range of opportunities regarding design and optimization of SCTEGs.

Factors determining antibody distribution in tumors.

PubMed

Thurber, Greg M; Schmidt, Michael M; Wittrup, K Dane

2008-02-01

The development of antibody therapies for cancer is increasing rapidly, primarily owing to their specificity. Antibody distribution in tumors is often extremely uneven, however, leading to some malignant cells being exposed to saturating concentrations of antibody, whereas others are completely untargeted. This is detrimental because large regions of cells escape therapy, whereas other regions might be exposed to suboptimal concentrations that promote a selection of resistant mutants. The distribution of antibody depends on a variety of factors, including dose, affinity, antigens per cell and molecular size. Because these parameters are often known or easily estimated, a quick calculation based on simple modeling considerations can predict the uniformity of targeting within a tumor. Such analyses should enable experimental researchers to identify in a straightforward way the limitations in achieving evenly distributed antibody, and design and test improved antibody therapeutics more rationally.

Factors determining antibody distribution in tumors

PubMed Central

Thurber, Greg M.; Schmidt, Michael M.; Wittrup, K. Dane

2009-01-01

The development of antibody therapies for cancer is increasing rapidly, primarily owing to their specificity. Antibody distribution in tumors is often extremely uneven, however, leading to some malignant cells being exposed to saturating concentrations of antibody, whereas others are completely untargeted. This is detrimental because large regions of cells escape therapy, whereas other regions might be exposed to suboptimal concentrations that promote a selection of resistant mutants. The distribution of antibody depends on a variety of factors, including dose, affinity, antigens per cell and molecular size. Because these parameters are often known or easily estimated, a quick calculation based on simple modeling considerations can predict the uniformity of targeting within a tumor. Such analyses should enable experimental researchers to identify in a straightforward way the limitations in achieving evenly distributed antibody, and design and test improved antibody therapeutics more rationally. PMID:18179828

Factorial analysis of trihalomethanes formation in drinking water.

PubMed

Chowdhury, Shakhawat; Champagne, Pascale; McLellan, P James

2010-06-01

Disinfection of drinking water reduces pathogenic infection, but may pose risks to human health through the formation of disinfection byproducts. The effects of different factors on the formation of trihalomethanes were investigated using a statistically designed experimental program, and a predictive model for trihalomethanes formation was developed. Synthetic water samples with different factor levels were produced, and trihalomethanes concentrations were measured. A replicated fractional factorial design with center points was performed, and significant factors were identified through statistical analysis. A second-order trihalomethanes formation model was developed from 92 experiments, and the statistical adequacy was assessed through appropriate diagnostics. This model was validated using additional data from the Drinking Water Surveillance Program database and was applied to the Smiths Falls water supply system in Ontario, Canada. The model predictions were correlated strongly to the measured trihalomethanes, with correlations of 0.95 and 0.91, respectively. The resulting model can assist in analyzing risk-cost tradeoffs in the design and operation of water supply systems.

Composition of water and suspended sediment in streams of urbanized subtropical watersheds in Hawaii

USGS Publications Warehouse

De Carlo, E. H.; Beltran, V.L.; Tomlinson, M.S.

2004-01-01

Urbanization on the small subtropical island of Oahu, Hawaii provides an opportunity to examine how anthropogenic activity affects the composition of material transferred from land to ocean by streams. This paper investigates the variability in concentrations of trace elements (Pb, Zn, Cu, Ba, Co, As, Ni, V and Cr) in streams of watersheds on Oahu, Hawaii. The focus is on water and suspended particulate matter collected from the Ala Wai Canal watershed in Honolulu and also the Kaneohe Stream watershed. As predicted, suspended particulate matter controls most trace element transport. Elements such as Pb, Zn, Cu, Ba and Co exhibit increased concentrations within urbanized portions of the watersheds. Particulate concentrations of these elements vary temporally during storms owing to input of road runoff containing elevated concentrations of elements associated with vehicular traffic and other anthropogenic activities. Enrichments of As in samples from predominantly conservation areas are interpreted as reflecting agricultural use of fertilizers at the boundaries of urban and conservation lands. Particulate Ni, V and Cr exhibit distributions during storm events that suggest a mineralogical control. Principal component analysis of particulate trace element concentrations establishes eigenvalues that account for nearly 80% of the total variance and separates trace elements into 3 factors. Factor 1 includes Pb, Zn, Cu, Ba and Co, interpreted to represent metals with an urban anthropogenic enrichment. Factor 2 includes Ni, V and Cr, elements whose concentrations do not appear to derive from anthropogenic activity and is interpreted to reflect mineralogical control. Another, albeit less significant, anthropogenic factor includes As, Cd and U and is thought to represent agricultural inputs. Samples collected during a storm derived from an offshore low-pressure system suggest that downstream transport of upper watershed material during tradewind-derived rains results in a 2-3-fold dilution of the particulate concentrations of Pb, Zn and Cu in the Ala Wai canal watershed. ?? 2004 Elsevier Ltd. All rights reserved.

[Optimization of dissolution process for superfine grinding technology on total saponins of Panax ginseng fibrous root by response surface methodology].

PubMed

Zhao, Ya; Lai, Xiao-Pin; Yao, Hai-Yan; Zhao, Ran; Wu, Yi-Na; Li, Geng

2014-03-01

To investigate the effects of superfine comminution extraction technology of ginseng total saponins from Panax ginseng fibrous root, and to make sure the optimal extraction condition. Optimal condition of ginseng total saponins from Panax ginseng fibrous root was based on single factor experiment to study the effects of crushing degree, extraction time, alcohol concentration and extraction temperature on extraction rate. Response surface method was used to investigate three main factors such as superfine comminution time, extraction time and alcohol concentration. The relationship between content of ginseng total saponins in Panax ginseng fibrous root and three factors fitted second degree polynomial models. The optimal extraction condition was 9 min of superfine comminution time, 70% of alcohol, 50 degrees C of extraction temperature and 70 min of extraction time. Under the optimal condition, ginseng total saponins from Panax ginseng fibrous root was average 94. 81%, which was consistent with the predicted value. The optimization of technology is rapid, efficient, simple and stable.

Concentration-dependent effect of hypocalcaemia on mortality of patients with critical bleeding requiring massive transfusion: a cohort study.

PubMed

Ho, K M; Leonard, A D

2011-01-01

Mortality of patients with critical bleeding requiring massive transfusion is high. Although hypothermia, acidosis and coagulopathy have been well described as important determinants of mortality in patients with critical bleeding requiring massive transfusion, the risk factors and outcome associated with hypocalcaemia in these patients remain uncertain. This cohort study assessed the relationship between the lowest ionised calcium concentration during the 24-hour period of critical bleeding and the hospital mortality of 352 consecutive patients, while adjusting for diagnosis, acidosis, coagulation results, transfusion requirements and use of recombinant factor VIIa. Hypocalcaemia was common (mean concentrations 0.77 mmol/l, SD 0.19) and had a linear; concentration-dependent relationship with mortality (odds ratio [OR] 1.25 per 0.1 mmol/l decrement, 95% confidence interval [CI]: 1.04 to 1.52; P = 0.02). Hypocalcaemia accounted for 12.5% of the variability and was more important than the lowest fibrinogen concentrations (10.8%), acidosis (7.9%) and lowest platelet counts (7.7%) in predicting hospital mortality. The amount of fresh frozen plasma transfused (OR 1.09 per unit, 95% CI: 1.02 to 1.17; P = 0.02) and acidosis (OR 1.45 per 0.1 decrement, 95% CI: 1.19 to 1.72; P = 0.01) were associated with the occurrence of severe hypocalcaemia (< 0.8 mmol/l). In conclusion, ionised calcium concentrations had an inverse concentration-dependent relationship with mortality of patients with critical bleeding requiring massive transfusion. Both acidosis and the amount of fresh frozen plasma transfused were the main risk factors for severe hypocalcaemia. Further research is needed to determine whether preventing ionised hypocalcaemia can reduce mortality of patients with critical bleeding requiring massive transfusion.

Iodine concentration: a new, important characteristic of the spot sign that predicts haematoma expansion.

PubMed

Fu, Fan; Sun, Shengjun; Liu, Liping; Li, Jianying; Su, Yaping; Li, Yingying

2018-04-19

The computed tomography angiography (CTA) spot sign is a validated predictor of haematoma expansion (HE) in spontaneous intracerebral haemorrhage (SICH). We investigated whether defining the iodine concentration (IC) inside the spot sign and the haematoma on Gemstone spectral imaging (GSI) would improve its sensitivity and specificity for predicting HE. From 2014 to 2016, we prospectively enrolled 65 SICH patients who underwent single-phase spectral CTA within 6 h. Logistic regression was performed to assess the risk factors for HE. The predictive performance of individual spot sign characteristics was examined via receiver operating characteristic (ROC) analysis. The spot sign was detected in 46.1% (30/65) of patients. ROC analysis indicated that IC inside the spot sign had the greatest area under the ROC curve for HE (0.858; 95% confidence interval, 0.727-0.989; p = 0.003). Multivariate analysis found that spot sign with higher IC (i.e. IC > 7.82 100 μg/ml) was an independent predictor of HE (odds ratio = 34.27; 95% confidence interval, 5.608-209.41; p < 0.001) with sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 0.81, 0.75, 0.90 and 0.60, respectively; while the spot sign showed sensitivity, specificity, PPV and NPV of 0.81, 0.79, 0.73 and 0.86. Logistic regression analysis indicated that the IC in haematomas was independently associated with HE (odds ratio = 1.525; 95% confidence interval, 1.041-2.235; p = 0.030). ICs in haematoma and in spot sign were all independently associated with HE. IC analysis in spectral imaging may help to identify SICH patients for targeted haemostatic therapy. • Iodine concentration in spot sign and haematoma can predict haematoma expansion • Spectral imaging could measure the IC inside the spot sign and haematoma • IC in spot sign improved the positive predictive value (PPV) cf. CTA.

Development of European NO2 Land Use Regression Model for present and future exposure assessment: Implications for policy analysis.

PubMed

Vizcaino, Pilar; Lavalle, Carlo

2018-05-04

A new Land Use Regression model was built to develop pan-European 100 m resolution maps of NO 2 concentrations. The model was built using NO 2 concentrations from routine monitoring stations available in the Airbase database as dependent variable. Predictor variables included land use, road traffic proxies, population density, climatic and topographical variables, and distance to sea. In order to capture international and inter regional disparities not accounted for with the mentioned predictor variables, additional proxies of NO 2 concentrations, like levels of activity intensity and NO x emissions for specific sectors, were also included. The model was built using Random Forest techniques. Model performance was relatively good given the EU-wide scale (R 2  = 0.53). Output predictions of annual average concentrations of NO 2 were in line with other existing models in terms of spatial distribution and values of concentration. The model was validated for year 2015, comparing model predictions derived from updated values of independent variables, with concentrations in monitoring stations for that year. The algorithm was then used to model future concentrations up to the year 2030, considering different emission scenarios as well as changes in land use, population distribution and economic factors assuming the most likely socio-economic trends. Levels of exposure were derived from maps of concentration. The model proved to be a useful tool for the ex-ante evaluation of specific air pollution mitigation measures, and more broadly, for impact assessment of EU policies on territorial development. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Vitamin B12 and folate concentrations during pregnancy and insulin resistance in the offspring: the Pune Maternal Nutrition Study

PubMed Central

Deshpande, S. S.; Jackson, A. A.; Refsum, H.; Rao, S.; Fisher, D. J.; Bhat, D. S.; Naik, S. S.; Coyaji, K. J.; Joglekar, C. V.; Joshi, N.; Lubree, H. G.; Deshpande, V. U.; Rege, S. S.; Fall, C. H. D.

2007-01-01

Aims/hypothesis Raised maternal plasma total homocysteine (tHcy) concentrations predict small size at birth, which is a risk factor for type 2 diabetes mellitus. We studied the association between maternal vitamin B12, folate and tHcy status during pregnancy, and offspring adiposity and insulin resistance at 6 years. Methods In the Pune Maternal Nutrition Study we studied 700 consecutive eligible pregnant women in six villages. We measured maternal nutritional intake and circulating concentrations of folate, vitamin B12, tHcy and methylmalonic acid (MMA) at 18 and 28 weeks of gestation. These were correlated with offspring anthropometry, body composition (dual-energy X-ray absorptiometry scan) and insulin resistance (homeostatic model assessment of insulin resistance [HOMA-R]) at 6 years. Results Two-thirds of mothers had low vitamin B12 (<150 pmol/l), 90% had high MMA (>0.26 μmol/l) and 30% had raised tHcy concentrations (>10 μmol/l); only one had a low erythrocyte folate concentration. Although short and thin (BMI), the 6-year-old children were relatively adipose compared with the UK standards (skinfold thicknesses). Higher maternal erythrocyte folate concentrations at 28 weeks predicted higher offspring adiposity and higher HOMA-R (both p < 0.01). Low maternal vitamin B12 (18 weeks; p = 0.03) predicted higher HOMA-R in the children. The offspring of mothers with a combination of high folate and low vitamin B12 concentrations were the most insulin resistant. Conclusions/interpretation Low maternal vitamin B12 and high folate status may contribute to the epidemic of adiposity and type 2 diabetes in India. Electronic supplementary material The online version of this article (doi:10.1007/s00125-007-0793-y) contains supplementary material, which is available to authorised users. PMID:17851649

Modeling indoor air pollution from cookstove emissions in developing countries using a Monte Carlo single-box model

NASA Astrophysics Data System (ADS)

Johnson, Michael; Lam, Nick; Brant, Simone; Gray, Christen; Pennise, David

2011-06-01

A simple Monte Carlo single-box model is presented as a first approach toward examining the relationship between emissions of pollutants from fuel/cookstove combinations and the resulting indoor air pollution (IAP) concentrations. The model combines stove emission rates with expected distributions of kitchen volumes and air exchange rates in the developing country context to produce a distribution of IAP concentration estimates. The resulting distribution can be used to predict the likelihood that IAP concentrations will meet air quality guidelines, including those recommended by the World Health Organization (WHO) for fine particulate matter (PM2.5) and carbon monoxide (CO). The model can also be used in reverse to estimate the probability that specific emission factors will result in meeting air quality guidelines. The modeled distributions of indoor PM2.5 concentration estimated that only 4% of homes using fuelwood in a rocket-style cookstove, even under idealized conditions, would meet the WHO Interim-1 annual PM2.5 guideline of 35 μg m-3. According to the model, the PM2.5 emissions that would be required for even 50% of homes to meet this guideline (0.055 g MJ-delivered-1) are lower than those for an advanced gasifier fan stove, while emissions levels similar to liquefied petroleum gas (0.018 g MJ-delivered-1) would be required for 90% of homes to meet the guideline. Although the predicted distribution of PM concentrations (median = 1320 μg m-3) from inputs for traditional wood stoves was within the range of reported values for India (108-3522 μg m-3), the model likely overestimates IAP concentrations. Direct comparison with simultaneously measured emissions rates and indoor concentrations of CO indicated the model overestimated IAP concentrations resulting from charcoal and kerosene emissions in Kenyan kitchens by 3 and 8 times respectively, although it underestimated the CO concentrations resulting from wood-burning cookstoves in India by approximately one half. The potential overestimation of IAP concentrations is thought to stem from the model's assumption that all stove emissions enter the room and are completely mixed. Future versions of the model may be improved by incorporating these factors into the model, as well as more comprehensive and representative data on stove emissions performance, daily cooking energy requirements, and kitchen characteristics.

Evaluation of concentrations of pharmaceuticals detected in sewage influents in Japan by using annual shipping and sales data.

PubMed

Azuma, Takashi; Nakada, Norihide; Yamashita, Naoyuki; Tanaka, Hiroaki

2015-11-01

A year-round monitoring survey of sewage flowing into sewage treatment plants located in urban Japan was conducted by targeting seven representative pharmaceutical components-atenolol (ATL), ciprofloxacin (CFX), clarithromycin (CTM), diclofenac (DCF), diltiazem (DTZ), disopyramide (DSP), and sulpiride (SPR)-detected in the river environment. For each of these components, two types of predicted concentration were estimated on the basis of two types of data (the shipping volume and sales volume of each component). The measured concentration of each component obtained through the survey and the two types of estimated predicted concentration of each component were then compared. The correspondence ratio between the predicted concentration estimated from the shipping volume of the component and the measured concentration (predicted concentration/measured concentration) was, for ATL, 3.1; CFX, 1.4; CTM, 1.4; DCF, 0.2; DTZ, 0.9; DSP, 11.6; and SPR, 1.1. The correspondence ratio between the predicted concentration estimated from the sales volume of the component and the measured concentration was, for ATL, 0.5; CFX, 1.1; CTM, 0.8; DCF, 0.1; DTZ, 0.2; DSP, 0.7; and SPR, 0.8. Although a generally corresponding trend was seen regardless of whether the prediction was based on shipping volume or sales volume, the predicted concentrations estimated from the shipping volumes of all components expect DSP were found, to our knowledge for the first time in Japan, to correspond better than those based on sales volumes to the measured concentrations. These findings should help to improve the prediction accuracy of concentrations of pharmaceutical components in river waters. Copyright © 2015 Elsevier Ltd. All rights reserved.

Red maple (Acer rubrum) leaf toxicosis in horses: a retrospective study of 32 cases.

PubMed

Alward, Ashley; Corriher, Candice A; Barton, Michelle H; Sellon, Debra C; Blikslager, Anthony T; Jones, Samuel L

2006-01-01

Ingestion of wilted red maple leaves by horses can result in severe hemolytic anemia and methemoglobinemia. Little is known about what factors influence the outcome of red maple leaf toxicosis in horses. Our hypothesis was that physical examination findings, clinicopathologic variables or therapeutic modalities may predict outcome in horses with red maple leaf toxicity. Horses with red maple leaf toxicosis presented to referral hospitals in the southeast region of the United States. A multi-institutional retrospective study was designed to identify factors that predict mortality in horses with red maple toxicosis. Thirty-two horses with red maple toxicosis were identified, 19 of which died. Twenty-nine horses presented with anemia and 24 had clinicopathologic evidence of systemic inflammation. Renal insufficiency was identified in 12/30 (41%) horses. Laminitis (9/28) and colic (13/30) also were identified in horses with red maple toxicosis, but development of these 2 conditions did not have a negative effect on short-term survival. Horses with red maple toxicosis that survived to discharge were likely to have developed pyrexia during hospitalization (P = .030). Horses that were treated with a corticosteroid had a significantly increased likelihood of death (P = .045). There was no significant relationship between initial serum hemoglobin concentration, methemoglobin concentration, or percentage methemoglobin and mortality in this horse series. This study suggests that information obtained on initial examination cannot be used to accurately predict survival in horses with red maple toxicosis, but horses that receive corticosteroids are unlikely to survive.

A Bayesian Network Model for Assessing Estrogen Fate and Transport in a Swine Waste Lagoon

PubMed Central

Lee, Boknam; Kullman, Seth W.; Yost, Erin; Meyer, Michael T.; Worley-Davis, Lynn; Reckhow, Kenneth H.

2017-01-01

Commercial swine waste lagoons are regarded as a major reservoir of natural estrogens, which have the potential to produce adverse physiological effects on exposed aquatic organisms and wildlife. However, there remains limited understanding of the complex mechanisms of physical, chemical, and biological processes that govern the fate and transport of natural estrogens within an anaerobic swine lagoon. To improve lagoon management and ultimately help control the offsite transport of these compounds from swine operations, a Bayesian network model was developed to predict estrogen fate and budget and compared against data collected from a commercial swine field site. In general, the model was able to predict the estrogen fate and budget in both the slurry and sludge stores within the swine lagoon. Sensitivity analysis within the model, demonstrated that the estrogen input loading from the associated barn facility was the most important factor in controlling estrogen concentrations within the lagoon slurry storage, while the settling rate was the most significant factor in the lagoon sludge storage. The degradation reactions were shown to be minor in both stores based on prediction of average total estrogen concentrations. Management scenario evaluations showed that the best possible management options to reduce estrogen levels in the lagoon are either to adjust the estrogen input loading from swine barn facilities or to effectively enhancing estrogen bonding with suspended solids through the use of organic polymers or inorganic coagulants. PMID:24798317

Comment on and reinterpretation of Gabriel et Al. (2014) 'fish mercury and surface water sulfate relationships in the everglades protection area'.

PubMed

Julian, Paul; Gu, Binhe; Redfield, Garth

2015-01-01

Mercury (Hg) methylation and bioaccumulation is a major environmental issue in the Everglades Protection Area (EvPA). Therefore, it is critical to improve our predictive understanding of Hg dynamics. This commentary critically reviews a recently published manuscript concerning the possible relationship between Hg in fish tissue and surface water sulfate within EvPA marshes. The commentary addresses fundamental issues with the authors' data analysis, results and interpretation as well as highlights inconsistencies with published literature and the lack of support for their suggested ecosystem management actions. A number of chemical, biological, and physical factors influence Hg methylation and bioaccumulation, and water sulfate is sometimes viewed as a keystone factor, Gabriel et al. (2014) conclude that Hg bioaccumulation is favored at elevated sulfate concentrations, and suggest mitigation strategies to reduce sulfate inputs to the EvPA. A careful review of their data and conclusions reveals major flaws and in fact, a more straightforward and defensible interpretation of their data would be that no predictable relationship exists between fish tissue Hg and surface water sulfate concentrations in south Florida. Given the complexity of Hg cycling and the influence of trophic and habitat characteristics on aquatic consumer Hg accumulation, expecting one parameter to predict Hg accumulation dynamics within fish species within a dynamic marsh environment is unrealistic. Furthermore, proposing any management guidance from this relationship with little to no quantitative statistical analysis is inappropriate and misleading.

Modeling the formation and aging of secondary organic aerosols in Los Angeles during CalNex 2010

DOE PAGES

Hayes, P. L.; Carlton, A. G.; Baker, K. R.; ...

2015-05-26

Four different literature parameterizations for the formation and evolution of urban secondary organic aerosol (SOA) frequently used in 3-D models are evaluated using a 0-D box model representing the Los Angeles metropolitan region during the California Research at the Nexus of Air Quality and Climate Change (CalNex) 2010 campaign. We constrain the model predictions with measurements from several platforms and compare predictions with particle- and gas-phase observations from the CalNex Pasadena ground site. That site provides a unique opportunity to study aerosol formation close to anthropogenic emission sources with limited recirculation. The model SOA that formed only from the oxidationmore » of VOCs (V-SOA) is insufficient to explain the observed SOA concentrations, even when using SOA parameterizations with multi-generation oxidation that produce much higher yields than have been observed in chamber experiments, or when increasing yields to their upper limit estimates accounting for recently reported losses of vapors to chamber walls. The Community Multiscale Air Quality (WRF-CMAQ) model (version 5.0.1) provides excellent predictions of secondary inorganic particle species but underestimates the observed SOA mass by a factor of 25 when an older VOC-only parameterization is used, which is consistent with many previous model–measurement comparisons for pre-2007 anthropogenic SOA modules in urban areas. Including SOA from primary semi-volatile and intermediate-volatility organic compounds (P-S/IVOCs) following the parameterizations of Robinson et al. (2007), Grieshop et al. (2009), or Pye and Seinfeld (2010) improves model–measurement agreement for mass concentration. The results from the three parameterizations show large differences (e.g., a factor of 3 in SOA mass) and are not well constrained, underscoring the current uncertainties in this area. Our results strongly suggest that other precursors besides VOCs, such as P-S/IVOCs, are needed to explain the observed SOA concentrations in Pasadena. All the recent parameterizations overpredict urban SOA formation at long photochemical ages (≈ 3 days) compared to observations from multiple sites, which can lead to problems in regional and especially global modeling. However, reducing IVOC emissions by one-half in the model to better match recent IVOC measurements improves SOA predictions at these long photochemical ages. Among the explicitly modeled VOCs, the precursor compounds that contribute the greatest SOA mass are methylbenzenes. Measured polycyclic aromatic hydrocarbons (naphthalenes) contribute 0.7% of the modeled SOA mass. The amounts of SOA mass from diesel vehicles, gasoline vehicles, and cooking emissions are estimated to be 16–27, 35–61, and 19–35%, respectively, depending on the parameterization used, which is consistent with the observed fossil fraction of urban SOA, 71(±3) %. The relative contribution of each source is uncertain by almost a factor of 2 depending on the parameterization used. In-basin biogenic VOCs are predicted to contribute only a few percent to SOA. A regional SOA background of approximately 2.1 μg m −3 is also present due to the long-distance transport of highly aged OA, likely with a substantial contribution from regional biogenic SOA. The percentage of SOA from diesel vehicle emissions is the same, within the estimated uncertainty, as reported in previous work that analyzed the weekly cycles in OA concentrations (Bahreini et al., 2012; Hayes et al., 2013). However, the modeling work presented here suggests a strong anthropogenic source of modern carbon in SOA, due to cooking emissions, which was not accounted for in those previous studies and which is higher on weekends. Lastly, this work adapts a simple two-parameter model to predict SOA concentration and O/C from urban emissions. This model successfully predicts SOA concentration, and the optimal parameter combination is very similar to that found for Mexico City. This approach provides a computationally inexpensive method for predicting urban SOA in global and climate models. We estimate pollution SOA to account for 26 Tg yr −1 of SOA globally, or 17% of global SOA, one-third of which is likely to be non-fossil.« less

Modeling the formation and aging of secondary organic aerosols in Los Angeles during CalNex 2010

NASA Astrophysics Data System (ADS)

Hayes, P. L.; Carlton, A. G.; Baker, K. R.; Ahmadov, R.; Washenfelder, R. A.; Alvarez, S.; Rappengluck, B.; Gilman, J. B.; Kuster, W. C.; de Gouw, J. A.; Zotter, P.; Prevot, A. S. H.; Szidat, S.; Kleindienst, T. E.; Offenberg, J. H.; Ma, P. K.; Jimenez, J. L.

2015-05-01

Four different literature parameterizations for the formation and evolution of urban secondary organic aerosol (SOA) frequently used in 3-D models are evaluated using a 0-D box model representing the Los Angeles metropolitan region during the California Research at the Nexus of Air Quality and Climate Change (CalNex) 2010 campaign. We constrain the model predictions with measurements from several platforms and compare predictions with particle- and gas-phase observations from the CalNex Pasadena ground site. That site provides a unique opportunity to study aerosol formation close to anthropogenic emission sources with limited recirculation. The model SOA that formed only from the oxidation of VOCs (V-SOA) is insufficient to explain the observed SOA concentrations, even when using SOA parameterizations with multi-generation oxidation that produce much higher yields than have been observed in chamber experiments, or when increasing yields to their upper limit estimates accounting for recently reported losses of vapors to chamber walls. The Community Multiscale Air Quality (WRF-CMAQ) model (version 5.0.1) provides excellent predictions of secondary inorganic particle species but underestimates the observed SOA mass by a factor of 25 when an older VOC-only parameterization is used, which is consistent with many previous model-measurement comparisons for pre-2007 anthropogenic SOA modules in urban areas. Including SOA from primary semi-volatile and intermediate-volatility organic compounds (P-S/IVOCs) following the parameterizations of Robinson et al. (2007), Grieshop et al. (2009), or Pye and Seinfeld (2010) improves model-measurement agreement for mass concentration. The results from the three parameterizations show large differences (e.g., a factor of 3 in SOA mass) and are not well constrained, underscoring the current uncertainties in this area. Our results strongly suggest that other precursors besides VOCs, such as P-S/IVOCs, are needed to explain the observed SOA concentrations in Pasadena. All the recent parameterizations overpredict urban SOA formation at long photochemical ages (~ 3 days) compared to observations from multiple sites, which can lead to problems in regional and especially global modeling. However, reducing IVOC emissions by one-half in the model to better match recent IVOC measurements improves SOA predictions at these long photochemical ages. Among the explicitly modeled VOCs, the precursor compounds that contribute the greatest SOA mass are methylbenzenes. Measured polycyclic aromatic hydrocarbons (naphthalenes) contribute 0.7% of the modeled SOA mass. The amounts of SOA mass from diesel vehicles, gasoline vehicles, and cooking emissions are estimated to be 16-27, 35-61, and 19-35%, respectively, depending on the parameterization used, which is consistent with the observed fossil fraction of urban SOA, 71(±3) %. The relative contribution of each source is uncertain by almost a factor of 2 depending on the parameterization used. In-basin biogenic VOCs are predicted to contribute only a few percent to SOA. A regional SOA background of approximately 2.1 μg m-3 is also present due to the long-distance transport of highly aged OA, likely with a substantial contribution from regional biogenic SOA. The percentage of SOA from diesel vehicle emissions is the same, within the estimated uncertainty, as reported in previous work that analyzed the weekly cycles in OA concentrations (Bahreini et al., 2012; Hayes et al., 2013). However, the modeling work presented here suggests a strong anthropogenic source of modern carbon in SOA, due to cooking emissions, which was not accounted for in those previous studies and which is higher on weekends. Lastly, this work adapts a simple two-parameter model to predict SOA concentration and O/C from urban emissions. This model successfully predicts SOA concentration, and the optimal parameter combination is very similar to that found for Mexico City. This approach provides a computationally inexpensive method for predicting urban SOA in global and climate models. We estimate pollution SOA to account for 26 Tg yr-1 of SOA globally, or 17% of global SOA, one-third of which is likely to be non-fossil.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hayes, P. L.; Carlton, A. G.; Baker, K. R.

Four different literature parameterizations for the formation and evolution of urban secondary organic aerosol (SOA) frequently used in 3-D models are evaluated using a 0-D box model representing the Los Angeles metropolitan region during the California Research at the Nexus of Air Quality and Climate Change (CalNex) 2010 campaign. We constrain the model predictions with measurements from several platforms and compare predictions with particle- and gas-phase observations from the CalNex Pasadena ground site. That site provides a unique opportunity to study aerosol formation close to anthropogenic emission sources with limited recirculation. The model SOA that formed only from the oxidationmore » of VOCs (V-SOA) is insufficient to explain the observed SOA concentrations, even when using SOA parameterizations with multi-generation oxidation that produce much higher yields than have been observed in chamber experiments, or when increasing yields to their upper limit estimates accounting for recently reported losses of vapors to chamber walls. The Community Multiscale Air Quality (WRF-CMAQ) model (version 5.0.1) provides excellent predictions of secondary inorganic particle species but underestimates the observed SOA mass by a factor of 25 when an older VOC-only parameterization is used, which is consistent with many previous model–measurement comparisons for pre-2007 anthropogenic SOA modules in urban areas. Including SOA from primary semi-volatile and intermediate-volatility organic compounds (P-S/IVOCs) following the parameterizations of Robinson et al. (2007), Grieshop et al. (2009), or Pye and Seinfeld (2010) improves model–measurement agreement for mass concentration. The results from the three parameterizations show large differences (e.g., a factor of 3 in SOA mass) and are not well constrained, underscoring the current uncertainties in this area. Our results strongly suggest that other precursors besides VOCs, such as P-S/IVOCs, are needed to explain the observed SOA concentrations in Pasadena. All the recent parameterizations overpredict urban SOA formation at long photochemical ages (≈ 3 days) compared to observations from multiple sites, which can lead to problems in regional and especially global modeling. However, reducing IVOC emissions by one-half in the model to better match recent IVOC measurements improves SOA predictions at these long photochemical ages. Among the explicitly modeled VOCs, the precursor compounds that contribute the greatest SOA mass are methylbenzenes. Measured polycyclic aromatic hydrocarbons (naphthalenes) contribute 0.7% of the modeled SOA mass. The amounts of SOA mass from diesel vehicles, gasoline vehicles, and cooking emissions are estimated to be 16–27, 35–61, and 19–35%, respectively, depending on the parameterization used, which is consistent with the observed fossil fraction of urban SOA, 71(±3) %. The relative contribution of each source is uncertain by almost a factor of 2 depending on the parameterization used. In-basin biogenic VOCs are predicted to contribute only a few percent to SOA. A regional SOA background of approximately 2.1 μg m −3 is also present due to the long-distance transport of highly aged OA, likely with a substantial contribution from regional biogenic SOA. The percentage of SOA from diesel vehicle emissions is the same, within the estimated uncertainty, as reported in previous work that analyzed the weekly cycles in OA concentrations (Bahreini et al., 2012; Hayes et al., 2013). However, the modeling work presented here suggests a strong anthropogenic source of modern carbon in SOA, due to cooking emissions, which was not accounted for in those previous studies and which is higher on weekends. Lastly, this work adapts a simple two-parameter model to predict SOA concentration and O/C from urban emissions. This model successfully predicts SOA concentration, and the optimal parameter combination is very similar to that found for Mexico City. This approach provides a computationally inexpensive method for predicting urban SOA in global and climate models. We estimate pollution SOA to account for 26 Tg yr −1 of SOA globally, or 17% of global SOA, one-third of which is likely to be non-fossil.« less

Pharmacokinetic/Pharmacodynamic Predictors of Clinical Potency for Hepatitis C Virus Nonnucleoside Polymerase and Protease Inhibitors

PubMed Central

Morcos, Peter N.; Le Pogam, Sophie; Ou, Ying; Frank, Karl; Lave, Thierry; Smith, Patrick

2012-01-01

This analysis was conducted to determine whether the hepatitis C virus (HCV) viral kinetics (VK) model can predict viral load (VL) decreases for nonnucleoside polymerase inhibitors (NNPolIs) and protease inhibitors (PIs) after 3-day monotherapy studies of patients infected with genotype 1 chronic HCV. This analysis includes data for 8 NNPolIs and 14 PIs, including VL decreases from 3-day monotherapy, total plasma trough concentrations on day 3 (Cmin), replicon data (50% effective concentration [EC50] and protein-shifted EC50 [EC50,PS]), and for PIs, liver-to-plasma ratios (LPRs) measured in vivo in preclinical species. VK model simulations suggested that achieving additional log10 VL decreases greater than one required 10-fold increases in the Cmin. NNPolI and PI data further supported this result. The VK model was successfully used to predict VL decreases in 3-day monotherapy for NNPolIs based on the EC50,PS and the day 3 Cmin. For PIs, however, predicting VL decreases using the same model and the EC50,PS and day 3 Cmin was not successful; a model including LPR values and the EC50 instead of the EC50,PS provided a better prediction of VL decrease. These results are useful for designing phase 1 monotherapy studies for NNPolIs and PIs by clarifying factors driving VL decreases, such as the day 3 Cmin and the EC50,PS for NNPolIs or the EC50 and LPR for PIs. This work provides a framework for understanding the pharmacokinetic/pharmacodynamic relationship for other HCV drug classes. The availability of mechanistic data on processes driving the target concentration, such as liver uptake transporters, should help to improve the predictive power of the approach. PMID:22470110

Evaluating the environmental fate of short-chain chlorinated paraffins (SCCPs) in the Nordic environment using a dynamic multimedia model.

PubMed

Krogseth, Ingjerd S; Breivik, Knut; Arnot, Jon A; Wania, Frank; Borgen, Anders R; Schlabach, Martin

2013-12-01

Short chain chlorinated paraffins (SCCPs) raise concerns due to their potential for persistence, bioaccumulation, long-range transport and adverse effects. An understanding of their environmental fate remains limited, partly due to the complexity of the mixture. The purpose of this study was to evaluate whether a mechanistic, integrated, dynamic environmental fate and bioaccumulation multimedia model (CoZMoMAN) can reconcile what is known about environmental emissions and human exposure of SCCPs in the Nordic environment. Realistic SCCP emission scenarios, resolved by formula group, were estimated and used to predict the composition and concentrations of SCCPs in the environment and the human food chain. Emissions at the upper end of the estimated range resulted in predicted total concentrations that were often within a factor of 6 of observations. Similar model performance for a complex group of organic contaminants as for the well-known polychlorinated biphenyls strengthens the confidence in the CoZMoMAN model and implies a relatively good mechanistic understanding of the environmental fate of SCCPs. However, the degree of chlorination predicted for SCCPs in sediments, fish, and humans was higher than observed and poorly established environmental half-lives and biotransformation rate constants contributed to the uncertainties in the predicted composition and ∑SCCP concentrations. Improving prediction of the SCCP composition will also require better constrained estimates of the composition of SCCP emissions. There is, however, also large uncertainty and lack of coherence in the existing observations, and better model-measurement agreement will require improved analytical methods and more strategic sampling. More measurements of SCCP levels and compositions in samples from background regions are particularly important.

Visibility from roads predict the distribution of invasive fishes in agricultural ponds.

PubMed

Kizuka, Toshikazu; Akasaka, Munemitsu; Kadoya, Taku; Takamura, Noriko

2014-01-01

Propagule pressure and habitat characteristics are important factors used to predict the distribution of invasive alien species. For species exhibiting strong propagule pressure because of human-mediated introduction of species, indicators of introduction potential must represent the behavioral characteristics of humans. This study examined 64 agricultural ponds to assess the visibility of ponds from surrounding roads and its value as a surrogate of propagule pressure to explain the presence and absence of two invasive fish species. A three-dimensional viewshed analysis using a geographic information system quantified the visual exposure of respective ponds to humans. Binary classification trees were developed as a function of their visibility from roads, as well as five environmental factors: river density, connectivity with upstream dam reservoirs, pond area, chlorophyll a concentration, and pond drainage. Traditional indicators of human-mediated introduction (road density and proportion of urban land-use area) were alternatively included for comparison instead of visual exposure. The presence of Bluegill (Lepomis macrochirus) was predicted by the ponds' higher visibility from roads and pond connection with upstream dam reservoirs. Results suggest that fish stocking into ponds and their dispersal from upstream sources facilitated species establishment. Largemouth bass (Micropterus salmoides) distribution was constrained by chlorophyll a concentration, suggesting their lower adaptability to various environments than that of Bluegill. Based on misclassifications from classification trees for Bluegill, pond visual exposure to roads showed greater predictive capability than traditional indicators of human-mediated introduction. Pond visibility is an effective predictor of invasive species distribution. Its wider use might improve management and mitigate further invasion. The visual exposure of recipient ecosystems to humans is important for many invasive species that spread with frequent instances of human-mediated introduction.

Early plasma monocyte chemoattractant protein 1 predicts the development of sepsis in trauma patients: A prospective observational study.

PubMed

Wang, Yuchang; Liu, Qinxin; Liu, Tao; Zheng, Qiang; Xu, Xi'e; Liu, Xinghua; Gao, Wei; Li, Zhanfei; Bai, Xiangjun

2018-04-01

Monocyte chemoattractant protein 1 (MCP-1) is an initiating cytokine of the inflammatory cascade. Extracellular MCP-1 exhibits pro-inflammatory characteristic and plays a central pathogenic role in critical illness. The purpose of the study was to identify the association between plasma MCP-1 levels and the development of sepsis after severe trauma.The plasma levels of MCP-1 in severe trauma patients were measured by a quantitative enzyme-linked immune sorbent assay and the dynamic release patterns were recorded at three time points during seven days post-trauma. The related factors of prognosis were compared between sepsis and non-sepsis groups and analyzed using multivariate logistic regression analysis. We also used receiver operating characteristic (ROC) curves to assess the values of different variables in predicting sepsis.A total of 72 patients who met criteria indicative of severe trauma (72.22% of male; mean age, 49.40 ± 14.29 years) were enrolled. Plasma MCP-1 concentrations significantly increased on post-trauma day 1 and that this increase was significantly correlated with the Injury Severity Score (ISS) and interleukin-6 (IL-6). Multivariate logistic regression analysis showed that early MCP-1, ISS, and IL-6 were independent risk factors for sepsis in severe trauma patients. Incorporation of the early MCP-1 into the ISS can increase the discriminative performance for predicting development of sepsis.Early plasma MCP-1 concentrations can be used to assess the severity of trauma and is correlated with the development of sepsis after severe trauma. The addition of the early MCP-1 levels to the ISS significantly improves its ability to predict development of sepsis.

Main predictors of periphyton species richness depend on adherence strategy and cell size

PubMed Central

Siqueira, Tadeu; Landeiro, Victor Lemes; Rodrigues, Liliana; Bonecker, Claudia Costa; Rodrigues, Luzia Cleide; Santana, Natália Fernanda; Thomaz, Sidinei Magela; Bini, Luis Mauricio

2017-01-01

Periphytic algae are important components of aquatic ecosystems. However, the factors driving periphyton species richness variation remain largely unexplored. Here, we used data from a subtropical floodplain (Upper Paraná River floodplain, Brazil) to quantify the influence of environmental variables (total suspended matter, temperature, conductivity, nutrient concentrations, hydrology, phytoplankton biomass, phytoplankton species richness, aquatic macrophyte species richness and zooplankton density) on overall periphytic algal species richness and on the richness of different algal groups defined by morphological traits (cell size and adherence strategy). We expected that the coefficients of determination of the models estimated for different trait-based groups would be higher than the model coefficient of determination of the entire algal community. We also expected that the relative importance of explanatory variables in predicting species richness would differ among algal groups. The coefficient of determination for the model used to predict overall periphytic algal species richness was higher than the ones obtained for models used to predict the species richness of the different groups. Thus, our first prediction was not supported. Species richness of aquatic macrophytes was the main predictor of periphyton species richness of the entire community and a significant predictor of the species richness of small mobile, large mobile and small-loosely attached algae. Abiotic variables, phytoplankton species richness, chlorophyll-a concentration, and hydrology were also significant predictors, depending on the group. These results suggest that habitat heterogeneity (as proxied by aquatic macrophytes richness) is important for maintaining periphyton species richness in floodplain environments. However, other factors played a role, suggesting that the analysis of species richness of different trait-based groups unveils relationships that were not detectable when the entire community was analysed together. PMID:28742122

Photodynamic therapy: computer modeling of diffusion and reaction phenomena

NASA Astrophysics Data System (ADS)

Hampton, James A.; Mahama, Patricia A.; Fournier, Ronald L.; Henning, Jeffery P.

1996-04-01

We have developed a transient, one-dimensional mathematical model for the reaction and diffusion phenomena that occurs during photodynamic therapy (PDT). This model is referred to as the PDTmodem program. The model is solved by the Crank-Nicholson finite difference technique and can be used to predict the fates of important molecular species within the intercapillary tissue undergoing PDT. The following factors govern molecular oxygen consumption and singlet oxygen generation within a tumor: (1) photosensitizer concentration; (2) fluence rate; and (3) intercapillary spacing. In an effort to maximize direct tumor cell killing, the model allows educated decisions to be made to insure the uniform generation and exposure of singlet oxygen to tumor cells across the intercapillary space. Based on predictions made by the model, we have determined that the singlet oxygen concentration profile within the intercapillary space is controlled by the product of the drug concentration, and light fluence rate. The model predicts that at high levels of this product, within seconds singlet oxygen generation is limited to a small core of cells immediately surrounding the capillary. The remainder of the tumor tissue in the intercapillary space is anoxic and protected from the generation and toxic effects of singlet oxygen. However, at lower values of this product, the PDT-induced anoxic regions are not observed. An important finding is that an optimal value of this product can be defined that maintains the singlet oxygen concentration throughout the intercapillary space at a near constant level. Direct tumor cell killing is therefore postulated to depend on the singlet oxygen exposure, defined as the product of the uniform singlet oxygen concentration and the time of exposure, and not on the total light dose.

Elevated Plasma CXCL12α Is Associated with a Poorer Prognosis in Pulmonary Arterial Hypertension

PubMed Central

Li, Lili; O’Connell, Caroline; Codd, Mary; Lawrie, Allan; Morton, Allison; Kiely, David G.; Condliffe, Robin; Elliot, Charles; McLoughlin, Paul; Gaine, Sean

2015-01-01

Rationale Recent work in preclinical models suggests that signalling via the pro-angiogenic and pro-inflammatory cytokine, CXCL12 (SDF-1), plays an important pathogenic role in pulmonary hypertension (PH). The objective of this study was to establish whether circulating concentrations of CXCL12α were elevated in patients with PAH and related to mortality. Methods Plasma samples were collected from patients with idiopathic pulmonary arterial hypertension (IPAH) and PAH associated with connective tissue diseases (CTD-PAH) attending two pulmonary hypertension referral centres (n = 95) and from age and gender matched healthy controls (n = 44). Patients were subsequently monitored throughout a period of five years. Results CXCL12α concentrations were elevated in PAH groups compared to controls (P<0.05) and receiver-operating-characteristic analysis showed that plasma CXCL12α concentrations discriminated patients from healthy controls (AUC 0.80, 95% confidence interval 0.73-0.88). Kaplan Meier analysis indicated that elevated plasma CXCL12α concentration was associated with reduced survival (P<0.01). Multivariate Cox proportional hazards model showed that elevated CXCL12α independently predicted (P<0.05) earlier death in PAH with a hazard ratio (95% confidence interval) of 2.25 (1.01-5.00). In the largest subset by WHO functional class (Class 3, 65% of patients) elevated CXCL12α independently predicted (P<0.05) earlier death, hazard ratio 2.27 (1.05-4.89). Conclusions Our data show that elevated concentrations of circulating CXCL12α in PAH predicted poorer survival. Furthermore, elevated circulating CXCL12α was an independent risk factor for death that could potentially be included in a prognostic model and guide therapy. PMID:25856504

Elevated plasma CXCL12α is associated with a poorer prognosis in pulmonary arterial hypertension.

PubMed

McCullagh, Brian N; Costello, Christine M; Li, Lili; O'Connell, Caroline; Codd, Mary; Lawrie, Allan; Morton, Allison; Kiely, David G; Condliffe, Robin; Elliot, Charles; McLoughlin, Paul; Gaine, Sean

2015-01-01

Recent work in preclinical models suggests that signalling via the pro-angiogenic and pro-inflammatory cytokine, CXCL12 (SDF-1), plays an important pathogenic role in pulmonary hypertension (PH). The objective of this study was to establish whether circulating concentrations of CXCL12α were elevated in patients with PAH and related to mortality. Plasma samples were collected from patients with idiopathic pulmonary arterial hypertension (IPAH) and PAH associated with connective tissue diseases (CTD-PAH) attending two pulmonary hypertension referral centres (n = 95) and from age and gender matched healthy controls (n = 44). Patients were subsequently monitored throughout a period of five years. CXCL12α concentrations were elevated in PAH groups compared to controls (P<0.05) and receiver-operating-characteristic analysis showed that plasma CXCL12α concentrations discriminated patients from healthy controls (AUC 0.80, 95% confidence interval 0.73-0.88). Kaplan Meier analysis indicated that elevated plasma CXCL12α concentration was associated with reduced survival (P<0.01). Multivariate Cox proportional hazards model showed that elevated CXCL12α independently predicted (P<0.05) earlier death in PAH with a hazard ratio (95% confidence interval) of 2.25 (1.01-5.00). In the largest subset by WHO functional class (Class 3, 65% of patients) elevated CXCL12α independently predicted (P<0.05) earlier death, hazard ratio 2.27 (1.05-4.89). Our data show that elevated concentrations of circulating CXCL12α in PAH predicted poorer survival. Furthermore, elevated circulating CXCL12α was an independent risk factor for death that could potentially be included in a prognostic model and guide therapy.

Clinical and clinicopathological factors associated with survival in 44 horses with equine neorickettsiosis (Potomac horse Fever).

PubMed

Bertin, F R; Reising, A; Slovis, N M; Constable, P D; Taylor, S D

2013-01-01

The epidemiology of equine neorickettsiosis (EN) has been extensively studied but limited clinical and clinicopathological data are available concerning naturally infected horses. Factors predictive of survival will be identified in horses diagnosed with EN. Convenience sample of 44 horses with EN admitted to 2 referral institutions. A retrospective study was performed. A diagnosis of EN was based on the presence of positive blood or fecal PCR. The most common clinical signs included diarrhea (66%), fever (50%), anorexia (45%), depression (39%), colic (39%), and lameness (18%). The median duration of hospitalization was 6 days and 73% of horses survived to discharge. Laminitis was present in 36% of horses, 88% of which were affected in all 4 feet. Serum creatinine and urea nitrogen concentrations, as well as RBC count, blood hemoglobin concentration, hematocrit, band neutrophils, serum AST activity, serum CK activity, and anion gap, were significantly (P < .05) higher in nonsurvivors. Serum chloride and sodium, concentrations as well as duration of hospitalization were significantly lower in nonsurvivors. The results of forward stepwise logistic regression indicated that blood hemoglobin concentration on admission and antimicrobial treatment with oxytetracycline were independent factors associated with survival. Severity of colitis as reflected by electrolyte loss, hemoconcentration, and prerenal azotemia were predictors of survival in horses diagnosed with EN. Treatment with oxytetracycline was associated with increased survival. Copyright © 2013 by the American College of Veterinary Internal Medicine.

An integrated, quality by design (QbD) approach for design, development and optimization of orally disintegrating tablet formulation of carbamazepine.

PubMed

Mishra, Saurabh M; Rohera, Bhagwan D

2017-11-01

The objective of the present study was to design and develop a formulation for orally disintegrating tablets (ODTs) of carbamazepine using quality by design principles. The target product profile (TPP) and quality target product profile (QTPP) of ODTs were identified. Risk assessment was carried out by leveraging prior knowledge and experience to define the criticality of factors based on their impact by Ishikawa fishbone diagram and preliminary hazard analysis tool. Box-Behnken response surface methodology was used to study the effect of critical factors on various attributes of ODTs. The independent factors selected were compression pressure (X 1 ), concentration of sublimating agent (volatile material) (X 2 ), disintegrant concentration (X 3 ) and the responses were tablet crushing strength, tablet porosity, disintegration time, water absorption time, tablet friability and drug dissolution. ANOVA and lack of fit test illustrated that selected independent variables had significant effect on the response variables, and excellent correlation was observed between actual and predicted values. Optimization by desirability function indicated that compression pressure, X 1 (1534 lbs), ammonium bicarbonate concentration, X 2 (7.68%) and Kollidon ® CL-SF concentration, X 3 (6%) were optimum to prepare ODT formulation of carbamazepine of desired attributes complying with QTPP. Thus, in the present study, a high level of assurance was established for ODT product quality and performance.

The development of a model to predict BW gain of growing cattle fed grass silage-based diets.

PubMed

Huuskonen, A; Huhtanen, P

2015-08-01

The objective of this meta-analysis was to develop and validate empirical equations predicting BW gain (BWG) and carcass traits of growing cattle from intake and diet composition variables. The modelling was based on treatment mean data from feeding trials in growing cattle, in which the nutrient supply was manipulated by wide ranges of forage and concentrate factors. The final dataset comprised 527 diets in 116 studies. The diets were mainly based on grass silage or grass silage partly or completely replaced by whole-crop silages, hay or straw. The concentrate feeds consisted of cereal grains, fibrous by-products and protein supplements. Mixed model regression analysis with a random study effect was used to develop prediction equations for BWG and carcass traits. The best-fit models included linear and quadratic effects of metabolisable energy (ME) intake per metabolic BW (BW0.75), linear effects of BW0.75, and dietary concentrations of NDF, fat and feed metabolisable protein (MP) as significant variables. Although diet variables had significant effects on BWG, their contribution to improve the model predictions compared with ME intake models was small. Feed MP rather than total MP was included in the final model, since it is less correlated to dietary ME concentration than total MP. None of the quadratic terms of feed variables was significant (P>0.10) when included in the final models. Further, additional feed variables (e.g. silage fermentation products, forage digestibility) did not have significant effects on BWG. For carcass traits, increased ME intake (ME/BW0.75) improved both dressing proportion (P0.10) effect on dressing proportion or carcass conformation score, but it increased (P<0.01) carcass fat score. The current study demonstrated that ME intake per BW0.75 was clearly the most important variable explaining the BWG response in growing cattle. The effect of increased ME supply displayed diminishing responses that could be associated with increased energy concentration of BWG, reduced diet metabolisability (proportion of ME of gross energy) and/or decreased efficiency of ME utilisation for growth with increased intake. Negative effects of increased dietary NDF concentration on BWG were smaller compared to responses that energy evaluation systems predict for energy retention. The present results showed only marginal effects of protein supply on BWG in growing cattle.

Physiological levels of blood coagulation factors IX and X control coagulation kinetics in an in vitro model of circulating tissue factor

NASA Astrophysics Data System (ADS)

Tormoen, Garth W.; Khader, Ayesha; Gruber, András; McCarty, Owen J. T.

2013-06-01

Thrombosis significantly contributes to cancer morbidity and mortality. The mechanism behind thrombosis in cancer may be circulating tissue factor (TF), as levels of circulating TF are associated with thrombosis. However, circulating TF antigen level alone has failed to predict thrombosis in patients with cancer. We hypothesize that coagulation factor levels regulate the kinetics of circulating TF-induced thrombosis. Coagulation kinetics were measured as a function of individual coagulation factor levels and TF particle concentration. Clotting times increased when pooled plasma was mixed at or above a ratio of 4:6 with PBS. Clotting times increased when pooled plasma was mixed at or above a ratio of 8:2 with factor VII-depleted plasma, 7:3 with factor IX- or factor X-depleted plasmas, or 2:8 with factor II-, V- or VIII-depleted plasmas. Addition of coagulation factors VII, X, IX, V and II to depleted plasmas shortened clotting and enzyme initiation times, and increased enzyme generation rates in a concentration-dependent manner. Only additions of factors IX and X from low-normal to high-normal levels shortened clotting times and increased enzyme generation rates. Our results demonstrate that coagulation kinetics for TF particles are controlled by factor IX and X levels within the normal physiological range. We hypothesize that individual patient factor IX and X levels may be prognostic for susceptibility to circulating TF-induced thrombosis.

Convergence in parameters and predictions using computational experimental design.

PubMed

Hagen, David R; White, Jacob K; Tidor, Bruce

2013-08-06

Typically, biological models fitted to experimental data suffer from significant parameter uncertainty, which can lead to inaccurate or uncertain predictions. One school of thought holds that accurate estimation of the true parameters of a biological system is inherently problematic. Recent work, however, suggests that optimal experimental design techniques can select sets of experiments whose members probe complementary aspects of a biochemical network that together can account for its full behaviour. Here, we implemented an experimental design approach for selecting sets of experiments that constrain parameter uncertainty. We demonstrated with a model of the epidermal growth factor-nerve growth factor pathway that, after synthetically performing a handful of optimal experiments, the uncertainty in all 48 parameters converged below 10 per cent. Furthermore, the fitted parameters converged to their true values with a small error consistent with the residual uncertainty. When untested experimental conditions were simulated with the fitted models, the predicted species concentrations converged to their true values with errors that were consistent with the residual uncertainty. This paper suggests that accurate parameter estimation is achievable with complementary experiments specifically designed for the task, and that the resulting parametrized models are capable of accurate predictions.

MLP based models to predict PM10, O3 concentrations, in Sines industrial area

NASA Astrophysics Data System (ADS)

Durao, R.; Pereira, M. J.

2012-04-01

Sines is an important Portuguese industrial area located southwest cost of Portugal with important nearby protected natural areas. The main economical activities are related with this industrial area, the deep-water port, petrochemical and thermo-electric industry. Nevertheless, tourism is also an important economic activity especially in summer time with potential to grow. The aim of this study is to develop prediction models of pollutant concentration categories (e.g. low concentration and high concentration) in order to provide early warnings to the competent authorities who are responsible for the air quality management. The knowledge in advanced of pollutant high concentrations occurrence will allow the implementation of mitigation actions and the release of precautionary alerts to population. The regional air quality monitoring network consists in three monitoring stations where a set of pollutants' concentrations are registered on a continuous basis. From this set stands out the tropospheric ozone (O3) and particulate matter (PM10) due to the high concentrations occurring in the region and their adverse effects on human health. Moreover, the major industrial plants of the region monitor SO2, NO2 and particles emitted flows at the principal chimneys (point sources), also on a continuous basis,. Therefore Artificial neuronal networks (ANN) were the applied methodology to predict next day pollutant concentrations; due to the ANNs structure they have the ability to capture the non-linear relationships between predictor variables. Hence the first step of this study was to apply multivariate exploratory techniques to select the best predictor variables. The classification trees methodology (CART) was revealed to be the most appropriate in this case.. Results shown that pollutants atmospheric concentrations are mainly dependent on industrial emissions and a complex combination of meteorological factors and the time of the year. In the second step, the Multi-layer perceptron (MLP) have shown to be able to learn the existent complex relationships using different combination of meteorological and emissions variables. Furthermore, MLP models identified what are the meteorological conditions that most affect O3 and PM10 concentrations in the region, namely wind speed and direction, boundary layer height, temperature, sunshine duration, relative humidity and the weather type. The developed MLP models showed good predictive success with model performances between 0.66 and 0.87, indicating a reasonable accuracy for models development and generalization capability. These performance values are obtained using cross entropy error functions. This error functions are only available for classification problems and ensure that the network outputs are true class membership probabilities, which is known to enhance the performance of classification neural networks.

The predictive value of plasma cytokines on gastroesophageal anastomotic leakage at an early stage in patients undergoing esophagectomy.

PubMed

Song, Jie-Qiong; He, Yi-Zhou; Fang, Yuan; Wu, Wei; Zhong, Ming

2017-08-01

It's difficult to diagnose gastroesophageal anastomotic leakage (GAL) at early postoperative stage. This study was conducted to evaluate the early predictive value of plasma cytokines levels on GAL in patients undergoing esophagectomy. Consecutive esophageal cancer patients who underwent esophagectomy and admitted to Surgical Intensive Care Unit (SICU) just after surgery were retrospectively analyzed. The baseline and postoperative 1 day plasma cytokine levels were collected and analyzed to evaluate the predictive value for clinically important anastomotic leakage. Area under receiver operating characteristic curve (AUROC) analysis was also performed. A total of 183 patients were included. Sixteen patients (8.74%) experienced GAL (GAL group) and the others did not (non-GAL group). The concentrations of tumor necrosis factor-alpha (TNF-α), interleukin (IL)-2R, IL-6, IL-8 and IL-10 in plasma on the first postoperative day significantly increased in the GAL group than in the non-GAL group (P<0.05). IL-6, IL-8 and IL-10 were fair predictors of GAL (AUROC >0.7) and the other two cytokines were poorly predictive (AUROC <0.7). The mean length of ICU and hospital stay were significantly longer in the GAL group than in the non-GAL group (P<0.05). Plasma concentrations of IL-6, IL-8 and IL-10 on the first postoperative day can predict clinically important GAL in patients undergoing esophagectomy.

Comprehensive probabilistic modelling of environmental emissions of engineered nanomaterials.

PubMed

Sun, Tian Yin; Gottschalk, Fadri; Hungerbühler, Konrad; Nowack, Bernd

2014-02-01

Concerns about the environmental risks of engineered nanomaterials (ENM) are growing, however, currently very little is known about their concentrations in the environment. Here, we calculate the concentrations of five ENM (nano-TiO2, nano-ZnO, nano-Ag, CNT and fullerenes) in environmental and technical compartments using probabilistic material-flow modelling. We apply the newest data on ENM production volumes, their allocation to and subsequent release from different product categories, and their flows into and within those compartments. Further, we compare newly predicted ENM concentrations to estimates from 2009 and to corresponding measured concentrations of their conventional materials, e.g. TiO2, Zn and Ag. We show that the production volume and the compounds' inertness are crucial factors determining final concentrations. ENM production estimates are generally higher than a few years ago. In most cases, the environmental concentrations of corresponding conventional materials are between one and seven orders of magnitude higher than those for ENM. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Comparison of Mathematical Models of Fish Mercury Concentration as a Function of Atmospheric Mercury Deposition Rate and Watershed Characteristics

NASA Astrophysics Data System (ADS)

Smith, R. A.; Moore, R. B.; Shanley, J. B.; Miller, E. K.; Kamman, N. C.; Nacci, D.

2009-12-01

Mercury (Hg) concentrations in fish and aquatic wildlife are complex functions of atmospheric Hg deposition rate, terrestrial and aquatic watershed characteristics that influence Hg methylation and export, and food chain characteristics determining Hg bioaccumulation. Because of the complexity and incomplete understanding of these processes, regional-scale models of fish tissue Hg concentration are necessarily empirical in nature, typically constructed through regression analysis of fish tissue Hg concentration data from many sampling locations on a set of potential explanatory variables. Unless the data sets are unusually long and show clear time trends, the empirical basis for model building must be based solely on spatial correlation. Predictive regional scale models are highly useful for improving understanding of the relevant biogeochemical processes, as well as for practical fish and wildlife management and human health protection. Mechanistically, the logical arrangement of explanatory variables is to multiply each of the individual Hg source terms (e.g. dry, wet, and gaseous deposition rates, and residual watershed Hg) for a given fish sampling location by source-specific terms pertaining to methylation, watershed transport, and biological uptake for that location (e.g. SO4 availability, hill slope, lake size). This mathematical form has the desirable property that predicted tissue concentration will approach zero as all individual source terms approach zero. One complication with this form, however, is that it is inconsistent with the standard linear multiple regression equation in which all terms (including those for sources and physical conditions) are additive. An important practical disadvantage of a model in which the Hg source terms are additive (rather than multiplicative) with their modifying factors is that predicted concentration is not zero when all sources are zero, making it unreliable for predicting the effects of large future reductions in Hg deposition. In this paper we compare the results of using several different linear and non-linear models in an analysis of watershed and fish Hg data for 450 New England lakes. The differences in model results pertain to both their utility in interpreting methylation and export processes as well as in fisheries management.

Modeling of glucose release from native and modified wheat starch gels during in vitro gastrointestinal digestion using artificial intelligence methods.

PubMed

Yousefi, A R; Razavi, Seyed M A

2017-04-01

Estimation of the amounts of glucose release (AGR) during gastrointestinal digestion can be useful to identify food of potential use in the diet of individuals with diabetes. In this work, adaptive neuro-fuzzy inference system (ANFIS), genetic algorithm-artificial neural network (GA-ANN) and group method of data handling (GMDH) models were applied to estimate the AGR from native (NWS), cross-linked (CLWS) and hydroxypropylated wheat starch (HPWS) gels during digestion under simulated gastrointestinal conditions. The GA-ANN and ANFIS were fed with 3 inputs of digestion time (1-120min), gel volume (7.5 and 15ml) and concentration (8 and 12%, w/w) for prediction of the AGR. The developed ANFIS predictions were close to the experimental data (r=0.977-0.996 and RMSE=0.225-0.619). The optimized GA-ANN, which included 6-7 hidden neurons, predicted the AGR with a good precision (r=0.984-0.993 and RMSE=0.338-0.588). Also, a three layers GMDH model with 3 neurons accurately predicted the AGR (r=0.979-0.986 and RMSE=0.339-0.443). Sensitivity analysis data demonstrated that the gel concentration was the most sensitive factor for prediction of the AGR. The results dedicated that the AGR will be accurately predictable through such soft computing methods providing less computational cost and time. Copyright © 2017 Elsevier B.V. All rights reserved.

Assessing element distribution and speciation in a stream at abandoned Pb-Zn mining site by combining classical, in-situ DGT and modelling approaches.

PubMed

Omanović, Dario; Pižeta, Ivanka; Vukosav, Petra; Kovács, Elza; Frančišković-Bilinski, Stanislav; Tamás, János

2015-04-01

The distribution and speciation of elements along a stream subjected to neutralised acid mine drainage (NAMD) effluent waters (Mátra Mountain, Hungary; Toka stream) were studied by a multi-methodological approach: dissolved and particulate fractions of elements were determined by HR-ICPMS, whereas speciation was carried out by DGT, supported by speciation modelling performed by Visual MINTEQ. Before the NAMD discharge, the Toka is considered as a pristine stream, with averages of dissolved concentrations of elements lower than world averages. A considerable increase of element concentrations caused by effluent water inflow is followed by a sharp or gradual concentration decrease. A large difference between total and dissolved concentrations was found for Fe, Al, Pb, Cu, Zn and As in effluent water and at the first downstream site, with high correlation factors between elements in particulate fraction, indicating their common behaviour, governed by the formation of ferri(hydr)oxides (co)precipitates. In-situ speciation by the DGT technique revealed that Zn, Cd, Ni, Co, Mn and U were predominantly present as a labile, potentially bioavailable fraction (>90%). The formation of strong complexes with dissolved organic matter (DOM) resulted in a relatively low DGT-labile concentration of Cu (42%), while low DGT-labile concentrations of Fe (5%) and Pb (12%) were presumably caused by their existence in colloidal (particulate) fraction which is not accessible to DGT. Except for Fe and Pb, a very good agreement between DGT-labile concentrations and those predicted by the applied speciation model was obtained, with an average correlation factor of 0.96. This study showed that the in-situ DGT technique in combination with model-predicted speciation and classical analysis of samples could provide a reasonable set of data for the assessment of the water quality status (WQS), as well as for the more general study of overall behaviour of the elements in natural waters subjected to high element loads. Copyright © 2014 Elsevier B.V. All rights reserved.

The hygroscopicity parameter (κ) of ambient organic aerosol at a field site subject to biogenic and anthropogenic influences: relationship to degree of aerosol oxidation

NASA Astrophysics Data System (ADS)

Chang, R. Y.-W.; Slowik, J. G.; Shantz, N. C.; Vlasenko, A.; Liggio, J.; Sjostedt, S. J.; Leaitch, W. R.; Abbatt, J. P. D.

2010-06-01

Cloud condensation nuclei (CCN) concentrations were measured at Egbert, a rural site in Ontario, Canada during the spring of 2007. The CCN concentrations were compared to values predicted from the aerosol chemical composition and size distribution using κ-Köhler theory, with the specific goal of this work being to determine the hygroscopic parameter (κ) of the oxygenated organic component of the aerosol, assuming that oxygenation drives the hygroscopicity for the entire organic fraction of the aerosol. The hygroscopicity of the oxygenated fraction of the organic component, as determined by an Aerodyne aerosol mass spectrometer (AMS), was characterised by two methods. First, positive matrix factorization (PMF) was used to separate oxygenated and unoxygenated organic aerosol factors. By assuming that the unoxygenated factor is completely non-hygroscopic and by varying κ of the oxygenated factor so that the predicted and measured CCN concentrations are internally consistent and in good agreement, κ of the oxygenated organic factor was found to be 0.22±0.04 for the suite of measurements made during this five-week campaign. In a second, equivalent approach, we continue to assume that the unoxygenated component of the aerosol, with a mole ratio of atomic oxygen to atomic carbon (O/C) ≈ 0, is completely non-hygroscopic, and we postulate a simple linear relationship between κorg and O/C. Under these assumptions, the κ of the entire organic component for bulk aerosols measured by the AMS can be parameterised as κorg=(0.29±0.05)·(O/C), for the range of O/C observed in this study (0.3 to 0.6). These results are averaged over our five-week study at one location using only the AMS for composition analysis. Empirically, our measurements are consistent with κorg generally increasing with increasing particle oxygenation, but high uncertainties preclude us from testing this hypothesis. Lastly, we examine select periods of different aerosol composition, corresponding to different air mass histories, to determine the generality of the campaign-wide findings described above.

[Serum PTH levels as a predictive factor of hypocalcaemia after total thyroidectomy].

PubMed

Díez Alonso, Manuel; Sánchez López, José Daniel; Sánchez-Seco Peña, María Isabel; Ratia Jiménez, Tomás; Arribas Gómez, Ignacio; Rodríguez Pascual, Angel; Martín-Duce, Antonio; Guadalix Hidalgo, Gregorio; Hernández Domínguez, Sara; Granell Vicent, Javier

2009-02-01

Postoperative parathyroid hormone (PTH) levels as a predictor of hypocalcaemia in patients subjected to total thyroidectomy is analyzed. Prospective study involving 67 patients who underwent total thyroidectomy due to a benign disease. Serum PTH and ionised calcium were measured 20 h after surgery. Sensitivity, specificity and predictive values of PTH and ionised calcium levels were calculated to predict clinical and analytical hypocalcaemia. A total of 42 (62.7%) patients developed hypocalcaemia (ionised calcium<0.95 mmol/l), but only 20 (29.9%) presented with symptoms. PTH concentration the day after surgery was significantly lower in the group that developed symptomatic hypocalcaemia (5.57+/-6.4 pg/ml) than in the asymptomatic (21.5+/-15.3 pg/ml) or normocalcaemic (26.8+/-24.9 pg/ml) groups (p=0.001). Taking the value of 13 pg/ml as a cut-off point of PTH levels, sensitivity, specificity, positive predictive value and negative predictive value were 54%, 72%, 76% and 48%, respectively. On the other hand, sensitivity for predicting symptomatic hypocalcaemia was 95% and specificity was 76%. The test showed a high incidence of false positives (11/30, 36%). Negative predictive value was 97% and positive predictive value was 65%. In multivariate analysis, PTH and ionised calcium were the only perioperative factors that showed an independent predictive value as risk indicators of symptomatic hypocalcaemia. Normal PTH levels 20 h after surgery practically rule out the subsequent appearance of hypocalcaemia symptoms. On the other hand, low PTH levels are not necessarily associated to symptomatic hypocalcaemia due to the high number of false positives.

Influence of Oil on Refrigerant Evaporator Performance

NASA Astrophysics Data System (ADS)

Kim, Jong-Soo; Nagata, Karsuya; Katsuta, Masafumi; Tomosugi, Hiroyuki; Kikuchi, Kouichiro; Horichi, Toshiaki

In vapor compression refrigeration system using oil-lubricated compressors, some amount of oil is always circulated through the system. Oil circulation can have a significant influence on the evaporator performance of automotive air conditioner which is especially required to cool quickly the car interior after a period standing in the sun. An experimental investigation was carried out an electrically heated horizontal tube to measure local heat transfer coefficients for various flow rates and heat fluxes during forced convection boiling of pure refrigerant R12 and refrigerant-oil mixtures (0-11% oil concentration by weight) and the results were compared with oil free performance. Local heat transfer coefficients increased at the region of low vapor quality by the addition of oil. On the other hand, because the oil-rich liquid film was formed on the heat transfer surface, heat transfer coefficients gradually decreased as the vapor quality became higher. Average heat transfer coefficient reached a maximum at about 4% oil concentration and this trend agreed well with the results of Green and Furse. Previous correlations, using the properties of the refrigerant-oil mixture, could not predict satisfactorily the local heat transfer coefficients data. New correlation modified by oil concentration factor was developed for predicting the corresponding heat transfer coefficient for refrigerant-oil mixture convection boiling. The maximum percent deviation between predicted and measured heat transfer coefficient was within ±30%.

Testing the coherence between occupational exposure limits for inhalation and their biological limit values with a generalized PBPK-model: the case of 2-propanol and acetone.

PubMed

Huizer, Daan; Huijbregts, Mark A J; van Rooij, Joost G M; Ragas, Ad M J

2014-08-01

The coherence between occupational exposure limits (OELs) and their corresponding biological limit values (BLVs) was evaluated for 2-propanol and acetone. A generic human PBPK model was used to predict internal concentrations after inhalation exposure at the level of the OEL. The fraction of workers with predicted internal concentrations lower than the BLV, i.e. the 'false negatives', was taken as a measure for incoherence. The impact of variability and uncertainty in input parameters was separated by means of nested Monte Carlo simulation. Depending on the exposure scenario considered, the median fraction of the population for which the limit values were incoherent ranged from 2% to 45%. Parameter importance analysis showed that body weight was the main factor contributing to interindividual variability in blood and urine concentrations and that the metabolic parameters Vmax and Km were the most important sources of uncertainty. This study demonstrates that the OELs and BLVs for 2-propanol and acetone are not fully coherent, i.e. enforcement of BLVs may result in OELs being violated. In order to assess the acceptability of this "incoherence", a maximum population fraction at risk of exceeding the OEL should be specified as well as a minimum level of certainty in predicting this fraction. Copyright © 2014 Elsevier Inc. All rights reserved.

A hybrid model for predicting carbon monoxide from vehicular exhausts in urban environments

NASA Astrophysics Data System (ADS)

Gokhale, Sharad; Khare, Mukesh

Several deterministic-based air quality models evaluate and predict the frequently occurring pollutant concentration well but, in general, are incapable of predicting the 'extreme' concentrations. In contrast, the statistical distribution models overcome the above limitation of the deterministic models and predict the 'extreme' concentrations. However, the environmental damages are caused by both extremes as well as by the sustained average concentration of pollutants. Hence, the model should predict not only 'extreme' ranges but also the 'middle' ranges of pollutant concentrations, i.e. the entire range. Hybrid modelling is one of the techniques that estimates/predicts the 'entire range' of the distribution of pollutant concentrations by combining the deterministic based models with suitable statistical distribution models ( Jakeman, et al., 1988). In the present paper, a hybrid model has been developed to predict the carbon monoxide (CO) concentration distributions at one of the traffic intersections, Income Tax Office (ITO), in the Delhi city, where the traffic is heterogeneous in nature and meteorology is 'tropical'. The model combines the general finite line source model (GFLSM) as its deterministic, and log logistic distribution (LLD) model, as its statistical components. The hybrid (GFLSM-LLD) model is then applied at the ITO intersection. The results show that the hybrid model predictions match with that of the observed CO concentration data within the 5-99 percentiles range. The model is further validated at different street location, i.e. Sirifort roadway. The validation results show that the model predicts CO concentrations fairly well ( d=0.91) in 10-95 percentiles range. The regulatory compliance is also developed to estimate the probability of exceedance of hourly CO concentration beyond the National Ambient Air Quality Standards (NAAQS) of India. It consists of light vehicles, heavy vehicles, three- wheelers (auto rickshaws) and two-wheelers (scooters, motorcycles, etc).

Improving risk prediction accuracy for new soldiers in the U.S. Army by adding self-report survey data to administrative data.

PubMed

Bernecker, Samantha L; Rosellini, Anthony J; Nock, Matthew K; Chiu, Wai Tat; Gutierrez, Peter M; Hwang, Irving; Joiner, Thomas E; Naifeh, James A; Sampson, Nancy A; Zaslavsky, Alan M; Stein, Murray B; Ursano, Robert J; Kessler, Ronald C

2018-04-03

High rates of mental disorders, suicidality, and interpersonal violence early in the military career have raised interest in implementing preventive interventions with high-risk new enlistees. The Army Study to Assess Risk and Resilience in Servicemembers (STARRS) developed risk-targeting systems for these outcomes based on machine learning methods using administrative data predictors. However, administrative data omit many risk factors, raising the question whether risk targeting could be improved by adding self-report survey data to prediction models. If so, the Army may gain from routinely administering surveys that assess additional risk factors. The STARRS New Soldier Survey was administered to 21,790 Regular Army soldiers who agreed to have survey data linked to administrative records. As reported previously, machine learning models using administrative data as predictors found that small proportions of high-risk soldiers accounted for high proportions of negative outcomes. Other machine learning models using self-report survey data as predictors were developed previously for three of these outcomes: major physical violence and sexual violence perpetration among men and sexual violence victimization among women. Here we examined the extent to which this survey information increases prediction accuracy, over models based solely on administrative data, for those three outcomes. We used discrete-time survival analysis to estimate a series of models predicting first occurrence, assessing how model fit improved and concentration of risk increased when adding the predicted risk score based on survey data to the predicted risk score based on administrative data. The addition of survey data improved prediction significantly for all outcomes. In the most extreme case, the percentage of reported sexual violence victimization among the 5% of female soldiers with highest predicted risk increased from 17.5% using only administrative predictors to 29.4% adding survey predictors, a 67.9% proportional increase in prediction accuracy. Other proportional increases in concentration of risk ranged from 4.8% to 49.5% (median = 26.0%). Data from an ongoing New Soldier Survey could substantially improve accuracy of risk models compared to models based exclusively on administrative predictors. Depending upon the characteristics of interventions used, the increase in targeting accuracy from survey data might offset survey administration costs.

Short communication: Use of genomic and metabolic information as well as milk performance records for prediction of subclinical ketosis risk via artificial neural networks.

PubMed

Ehret, A; Hochstuhl, D; Krattenmacher, N; Tetens, J; Klein, M S; Gronwald, W; Thaller, G

2015-01-01

Subclinical ketosis is one of the most prevalent metabolic disorders in high-producing dairy cows during early lactation. This renders its early detection and prevention important for both economical and animal-welfare reasons. Construction of reliable predictive models is challenging, because traits like ketosis are commonly affected by multiple factors. In this context, machine learning methods offer great advantages because of their universal learning ability and flexibility in integrating various sorts of data. Here, an artificial-neural-network approach was applied to investigate the utility of metabolic, genetic, and milk performance data for the prediction of milk levels of β-hydroxybutyrate within and across consecutive weeks postpartum. Data were collected from 218 dairy cows during their first 5wk in milk. All animals were genotyped with a 50,000 SNP panel, and weekly information on the concentrations of the milk metabolites glycerophosphocholine and phosphocholine as well as milk composition data (milk yield, fat and protein percentage) was available. The concentration of β-hydroxybutyric acid in milk was used as target variable in all prediction models. Average correlations between observed and predicted target values up to 0.643 could be obtained, if milk metabolite and routine milk recording data were combined for prediction at the same day within weeks. Predictive performance of metabolic as well as milk performance-based models was higher than that of models based on genetic information. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Chemodynamics of heavy metals in long-term contaminated soils: metal speciation in soil solution.

PubMed

Kim, Kwon-Rae; Owens, Gary

2009-01-01

The concentration and speciation of heavy metals in soil solution isolated from long-term contaminated soils were investigated. The soil solution was extracted at 70% maximum water holding capacity (MWHC) after equilibration for 24 h. The free metal concentrations (Cd2+, CU2+, Pb2+, and Zn2+) in soil solution were determined using the Donnan membrane technique (DMT). Initially the DMT was validated using artificial solutions where the percentage of free metal ions were significantly correlated with the percentages predicted using MINTEQA2. However, there was a significant difference between the absolute free ion concentrations predicted by MINTEQA2 and the values determined by the DMT. This was due to the significant metal adsorption onto the cation exchange membrane used in the DMT with 20%, 28%, 44%, and 8% mass loss of the initial total concentration of Cd, Cu, Pb, and Zn in solution, respectively. This could result in a significant error in the determination of free metal ions when using DMT if no allowance for membrane cation adsorption was made. Relative to the total soluble metal concentrations the amounts of free Cd2+ (3%-52%) and Zn2+ (11%-72%) in soil solutions were generally higher than those of Cu2+ (0.2%-30%) and Pb2+ (0.6%-10%). Among the key soil solution properties, dissolved heavy metal concentrations were the most significant factor governing free metal ion concentrations. Soil solution pH showed only a weak relationship with free metal ion partitioning coefficients (K(p)) and dissolved organic carbon did not show any significant influence on K(p).

Applying mixture toxicity modelling to predict bacterial bioluminescence inhibition by non-specifically acting pharmaceuticals and specifically acting antibiotics.

PubMed

Neale, Peta A; Leusch, Frederic D L; Escher, Beate I

2017-04-01

Pharmaceuticals and antibiotics co-occur in the aquatic environment but mixture studies to date have mainly focused on pharmaceuticals alone or antibiotics alone, although differences in mode of action may lead to different effects in mixtures. In this study we used the Bacterial Luminescence Toxicity Screen (BLT-Screen) after acute (0.5 h) and chronic (16 h) exposure to evaluate how non-specifically acting pharmaceuticals and specifically acting antibiotics act together in mixtures. Three models were applied to predict mixture toxicity including concentration addition, independent action and the two-step prediction (TSP) model, which groups similarly acting chemicals together using concentration addition, followed by independent action to combine the two groups. All non-antibiotic pharmaceuticals had similar EC 50 values at both 0.5 and 16 h, indicating together with a QSAR (Quantitative Structure-Activity Relationship) analysis that they act as baseline toxicants. In contrast, the antibiotics' EC 50 values decreased by up to three orders of magnitude after 16 h, which can be explained by their specific effect on bacteria. Equipotent mixtures of non-antibiotic pharmaceuticals only, antibiotics only and both non-antibiotic pharmaceuticals and antibiotics were prepared based on the single chemical results. The mixture toxicity models were all in close agreement with the experimental results, with predicted EC 50 values within a factor of two of the experimental results. This suggests that concentration addition can be applied to bacterial assays to model the mixture effects of environmental samples containing both specifically and non-specifically acting chemicals. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cytotoxic drugs in drinking water: a prediction and risk assessment exercise for the thames catchment in the United kingdom.

PubMed

Rowney, Nicole C; Johnson, Andrew C; Williams, Richard J

2009-12-01

Cytotoxic, also known as antineoplastic, drugs remain an important weapon in the fight against cancer. This study considers the water quality implications for the Thames catchment (United Kingdom) arising from the routine discharge of these drugs after use, down the drain and into the river. The review focuses on 13 different cytotoxic drugs from the alkylating agent, antimetabolite, and anthracycline antibiotic families. A geographic-information-system-based water quality model was used in the present study. The model was informed by literature values on consumption, excretion, and fate data to predict raw drinking water concentrations at the River Thames abstraction points at Farmoor, near Oxford, and Walton, in West London. To discover the highest plausible values, upper boundary values for consumption and excretion together with lower removal values for sewage treatment were used. The raw drinking water cytotoxic drug maximum concentrations at Walton (the higher of the two) representative of mean and low flow conditions were predicted to be 11 and 20 ng/L for the five combined alkylating agents, 2 and 4 ng/L for the three combined antimetabolites, and 0.05 and 0.10 ng/L the for two combined anthracycline antibiotics, respectively. If they were to escape into tap water, then the highest predicted concentrations would still be a factor of between 25 and 40 below the current recommended daily doses of concern. Although the risks may be negligible for healthy adults, more concern may be associated with special subgroup populations, such as pregnant women, their fetuses, and breast-feeding infants, due to their developmental vulnerability.

A simple physiologically based pharmacokinetic model evaluating the effect of anti-nicotine antibodies on nicotine disposition in the brains of rats and humans

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saylor, Kyle, E-mail: saylor@vt.edu; Zhang, Chenmi

Physiologically based pharmacokinetic (PBPK) modeling was applied to investigate the effects of anti-nicotine antibodies on nicotine disposition in the brains of rats and humans. Successful construction of both rat and human models was achieved by fitting model outputs to published nicotine concentration time course data in the blood and in the brain. Key parameters presumed to have the most effect on the ability of these antibodies to prevent nicotine from entering the brain were selected for investigation using the human model. These parameters, which included antibody affinity for nicotine, antibody cross-reactivity with cotinine, and antibody concentration, were broken down intomore » different, clinically-derived in silico treatment levels and fed into the human PBPK model. Model predictions suggested that all three parameters, in addition to smoking status, have a sizable impact on anti-nicotine antibodies' ability to prevent nicotine from entering the brain and that the antibodies elicited by current human vaccines do not have sufficient binding characteristics to reduce brain nicotine concentrations. If the antibody binding characteristics achieved in animal studies can similarly be achieved in human studies, however, nicotine vaccine efficacy in terms of brain nicotine concentration reduction is predicted to meet threshold values for alleviating nicotine dependence. - Highlights: • Modelling of nicotine disposition in the presence of anti-nicotine antibodies • Key vaccine efficacy factors are evaluated in silico in rats and in humans. • Model predicts insufficient antibody binding in past human nicotine vaccines. • Improving immunogenicity and antibody specificity may lead to vaccine success.« less

Elevated α-Hydroxybutyrate and Branched-Chain Amino Acid Levels Predict Deterioration of Glycemic Control in Adolescents.

PubMed

Tricò, Domenico; Prinsen, Hetty; Giannini, Cosimo; de Graaf, Robin; Juchem, Christoph; Li, Fangyong; Caprio, Sonia; Santoro, Nicola; Herzog, Raimund I

2017-07-01

Traditional risk factors for type 2 diabetes mellitus are weak predictors of changes in glucose tolerance and insulin sensitivity in youth. To identify early metabolic features of insulin resistance (IR) in youth and whether they predict deterioration of glycemic control. A cross-sectional and longitudinal study was conducted at the Yale Pediatric Obesity Clinic. Concentrations of α-hydroxybutyrate, β-hydroxybutyrate, lactate, and branched-chain amino acids (BCAAs) were measured by nuclear magnetic resonance spectroscopy in 78 nondiabetic adolescents during an oral glucose tolerance test (OGTT). Associations between baseline metabolic alterations and longitudinal changes in glucose control were tested in 16 subjects after a mean follow-up of 2.3 years. The relationship between metabolite levels, parameters of IR, and glycemic control, and their progression over time. Elevated fasting α-hydroxybutyrate levels were observed in adolescents with reduced insulin sensitivity after adjusting for age, sex, ethnicity, Tanner stage, and body mass index z-score (P = 0.014). Plasma α-hydroxybutyrate and BCAAs were increased throughout the course of the OGTT in this group (P < 0.03). Notably, borderline IR was associated with a progressive α-hydroxybutyrate decrease from elevated baseline concentrations to normal levels (P = 0.02). Increased baseline α-hydroxybutyrate concentrations were further associated with progressive worsening of glucose tolerance and disposition index. α-Hydroxybutyrate and BCAA concentrations during an OGTT characterize insulin-resistant youth and predict worsening of glycemic control. These findings provide potential biomarkers for risk assessment of type 2 diabetes and new insights into IR pathogenesis. Copyright © 2017 Endocrine Society

Polycyclic aromatic hydrocarbons bioavailability in industrial and agricultural soils: Linking SPME and Tenax extraction with bioassays.

PubMed

Guo, Meixia; Gong, Zongqiang; Li, Xiaojun; Allinson, Graeme; Rookes, James; Cahill, David

2017-06-01

The aims of this study were to evaluate the bioavailability of polycyclic aromatic hydrocarbons (PAHs) in industrial and agricultural soils using chemical methods and a bioassay, and to study the relationships between the methods. This was conducted by comparing the quantities of PAHs extracted from two manufactured gas plant (MGP) soils and an agricultural soil with low level contamination by solid-phase micro-extraction (SPME) and Tenax-TA extraction with the quantities taken up by the earthworm (Eisenia fetida). In addition, a biodegradation experiment was conducted on one MGP soil (MGP-A) to clarify the relationship between PAH removal by biodegradation and the variation in PAH concentrations in soil pore water. Results demonstrated that the earthworm bioassay could not be used to examine PAH bioavailability in the tested MGP soils; which was the case even in the diluted MGP-A soils after biodegradation. However, the bioassay was successfully applied to the agricultural soil. These results suggest that earthworms can only be used for bioassays in soils with low toxicity. In general, rapidly desorbing concentrations extracted by Tenax-TA could predict PAH concentrations accumulated in earthworms (R 2 =0.66), while SPME underestimated earthworm concentrations by a factor of 2.5. Both SPME and Tenax extraction can provide a useful tool to predict PAH bioavailability for earthworms, but Tenax-TA extraction was proven to be a more sensitive and precise method than SPME for the prediction of earthworm exposure in the agricultural soil. Copyright © 2017. Published by Elsevier Inc.

When will the TBT go away? Integrating monitoring and modelling to address TBT's delayed disappearance in the Drammensfjord, Norway.

PubMed

Arp, Hans Peter H; Eek, Espen; Nybakk, Anita Whitlock; Glette, Tormod; Møskeland, Thomas; Pettersen, Arne

2014-11-15

Despite a substantial decrease in the use and production of the marine antifouling agent tributyltin (TBT), its continuing presence in harbors remains a serious environmental concern. Herein a case study of TBT's persistence in the Drammensfjord, Norway, is presented. In 2005, severe TBT pollution was measured in the harbor of the Drammensfjord, with an average sediment concentration of 3387 μg kg(-1). To chart natural recovery in the Drammensfjord, an extensive sampling campaign was carried out over six years (2008-2013), quantifying TBT in water, settling particles and sediments. The monitoring campaign found a rapid decrease in sediment TBT concentration in the most contaminated areas, as well as a decrease in TBT entering the harbor via rivers and urban runoff. Changes observed in the more remote areas of the Drammensfjord, however, were less substantial. These data, along with measured and estimated geophysical properties, were used to parameterize and calibrate a coupled linear water-sediment model, referred to as the Drammensfjord model, to make prognosis on future TBT levels due to natural recovery. Unique to this type of model, the calibration was done using a Bayesian Monte Carlo (BMC) updating approach, which used monitoring data to calibrate predictions, as well as reduce the uncertainty of input parameters. To our knowledge, this is the first use of BMC updating to calibrate a model describing natural recovery in a lake/harbor type system. Prior to BMC updating, the non-calibrated model data agreed with monitoring data by a factor of 4.3. After BMC updating, the agreement was within a factor 3.2. The non-calibrated model predicted an average sediment concentration in the year 2025 of 2.5 μg kg(-1). The BMC calibrated model, however, predicted a higher concentration in the year 2025 of 16 μg kg(-1). This discrepancy was mainly due to the BMC calibration increasing the estimated riverine and runoff TBT emission levels relative to the initial input levels. Future monitoring campaigns can be used for further calibration of emission levels, and a clearer prognosis of when natural recovery will remove TBT pollution. Copyright © 2014 Elsevier Ltd. All rights reserved.

Use of a Generalized Additive Model to Investigate Key Abiotic Factors Affecting Microcystin Cellular Quotas in Heavy Bloom Areas of Lake Taihu

PubMed Central

Tao, Min; Xie, Ping; Chen, Jun; Qin, Boqiang; Zhang, Dawen; Niu, Yuan; Zhang, Meng; Wang, Qing; Wu, Laiyan

2012-01-01

Lake Taihu is the third largest freshwater lake in China and is suffering from serious cyanobacterial blooms with the associated drinking water contamination by microcystin (MC) for millions of citizens. So far, most studies on MCs have been limited to two small bays, while systematic research on the whole lake is lacking. To explain the variations in MC concentrations during cyanobacterial bloom, a large-scale survey at 30 sites across the lake was conducted monthly in 2008. The health risks of MC exposure were high, especially in the northern area. Both Microcystis abundance and MC cellular quotas presented positive correlations with MC concentration in the bloom seasons, suggesting that the toxic risks during Microcystis proliferations were affected by variations in both Microcystis density and MC production per Microcystis cell. Use of a powerful predictive modeling tool named generalized additive model (GAM) helped visualize significant effects of abiotic factors related to carbon fixation and proliferation of Microcystis (conductivity, dissolved inorganic carbon (DIC), water temperature and pH) on MC cellular quotas from recruitment period of Microcystis to the bloom seasons, suggesting the possible use of these factors, in addition to Microcystis abundance, as warning signs to predict toxic events in the future. The interesting relationship between macrophytes and MC cellular quotas of Microcystis (i.e., high MC cellular quotas in the presence of macrophytes) needs further investigation. PMID:22384128

Increased Trimethylamine N-oxide (TMAO) Portends High Mortality Risk Independent of Glycemic Control in Patients with Type 2 Diabetes Mellitus

PubMed Central

Wilson Tang, W. H.; Wang, Zeneng; Li, Xinmin S.; Fan, Yiying; Li, Daniel S.; Wu, Yuping; Hazen, Stanley L.

2017-01-01

Background Recent studies show a mechanistic link between intestinal microbial metabolism of dietary phosphatidylcholine and coronary artery disease pathogenesis. Concentrations of a pro-atherogenic gut microbe-generated metabolite, trimethylamine N-oxide (TMAO), predict increased incident cardiovascular disease risks in multiple cohorts. TMAO concentrations are increased in patients with type 2 diabetes mellitus (T2DM), but their prognostic value and relation to glycemic control are unclear. Methods We examined the relationship between fasting TMAO and two of its nutrient precursors, choline and betaine, versus 3-year major adverse cardiac events and 5-year mortality in 1,216 stable patients with T2DM who underwent elective diagnostic coronary angiography. Results TMAO (4.4 µmol/L [interquartile range 2.8–7.7µmol/L] vs. 3.6[2.3–5.7µmol/L]; P<0.001) and choline concentrations were higher in individuals with T2DM versus healthy controls. Within T2DM patients, higher plasma TMAO was associated with a significant 3.0-fold increased 3-year major adverse cardiac events risk (P<0.001) and a 3.6-fold increased 5-year mortality risk (P<0.001). Following adjustments for traditional risk factors and high sensitivity C-reactive protein, glycated hemoglobin and estimated glomerular filtration rate, increased TMAO concentrations remained predictive of both major adverse cardiac events and mortality risks in T2DM patients (e.g. Quartiles 4 vs. 1, hazard ratio 2.05[95%CI 1.31–3.20], P<0.001; and 2.07[95%CI 1.37–3.14], P<0.001, respectively). Conclusion Fasting plasma concentrations of the pro-atherogenic gut microbe-generated metabolite TMAO are higher in diabetic patients and portend higher major adverse cardiac events and mortality risks independent of traditional risk factors, renal function, and relationship to glycemic control. PMID:27864387

Increased Trimethylamine N-Oxide Portends High Mortality Risk Independent of Glycemic Control in Patients with Type 2 Diabetes Mellitus.

PubMed

Tang, W H Wilson; Wang, Zeneng; Li, Xinmin S; Fan, Yiying; Li, Daniel S; Wu, Yuping; Hazen, Stanley L

2017-01-01

Recent studies show a mechanistic link between intestinal microbial metabolism of dietary phosphatidylcholine and coronary artery disease pathogenesis. Concentrations of a proatherogenic gut microbe-generated metabolite, trimethylamine N-oxide (TMAO), predict increased incident cardiovascular disease risks in multiple cohorts. TMAO concentrations are increased in patients with type 2 diabetes mellitus (T2DM), but their prognostic value and relation to glycemic control are unclear. We examined the relationship between fasting TMAO and 2 of its nutrient precursors, choline and betaine, vs 3-year major adverse cardiac events and 5-year mortality in 1216 stable patients with T2DM who underwent elective diagnostic coronary angiography. TMAO [4.4 μmol/L (interquartile range 2.8-7.7 μmol/L) vs 3.6 (2.3-5.7 μmol/L); P < 0.001] and choline concentrations were higher in individuals with T2DM vs healthy controls. Within T2DM patients, higher plasma TMAO was associated with a significant 3.0-fold increased 3-year major adverse cardiac event risk (P < 0.001) and a 3.6-fold increased 5-year mortality risk (P < 0.001). Following adjustments for traditional risk factors and high-sensitivity C-reactive protein, glycohemoglobin, and estimated glomerular filtration rate, increased TMAO concentrations remained predictive of both major adverse cardiac events and mortality risks in T2DM patients [e.g., quartiles 4 vs 1, hazard ratio 2.05 (95% CI, 1.31-3.20), P < 0.001; and 2.07 (95% CI, 1.37-3.14), P < 0.001, respectively]. Fasting plasma concentrations of the proatherogenic gut microbe-generated metabolite TMAO are higher in diabetic patients and portend higher major adverse cardiac events and mortality risks independent of traditional risk factors, renal function, and relationship to glycemic control. © 2016 American Association for Clinical Chemistry.

Determinants of plasma PCB, brominated flame retardants, and organochlorine pesticides in pregnant women and 3 year old children in The Norwegian Mother and Child Cohort Study.

PubMed

Caspersen, Ida Henriette; Kvalem, Helen Engelstad; Haugen, Margaretha; Brantsæter, Anne Lise; Meltzer, Helle Margrete; Alexander, Jan; Thomsen, Cathrine; Frøshaug, May; Bremnes, Nanna Margrethe Bruun; Broadwell, Sharon Lynn; Granum, Berit; Kogevinas, Manolis; Knutsen, Helle Katrine

2016-04-01

Exposure to persistent organic pollutants (POPs) during prenatal and postnatal life has been extensively studied in relation to adverse health effects in children. The aim was to identify determinants of the concentrations of polychlorinated biphenyls (PCBs), brominated flame retardants (polybrominated diphenyl ethers, PBDEs; polybrominated biphenyl, PBB), and organochlorine pesticides (OCPs) in blood samples from pregnant women and children in The Norwegian Mother and Child Cohort Study (MoBa). Blood samples were collected from two independent subsamples within MoBa; a group of women (n=96) enrolled in mid-pregnancy during the years 2002-2008 and a group of 3 year old children (n=99) participating during 2010-2011. PCB congeners (74, 99, 138, 153, 180, 170, 194, 209, 105, 114, 118, 156, 157, 167, and 189), brominated flame retardants (PBDE-28, 47, 99, 100, 153, 154, and PBB-153), as well as the OCPs hexachlorobenzene (HCB), oxychlordane, 4,4'dichlorodiphenyltrichloroethane (DDT), and 4,4'dichlorodiphenyldichloroethylene (DDE) were measured in both pregnant women and children. Age, low parity, and low pre-pregnant BMI were the most important determinants of increased plasma concentrations of POPs in pregnant women. In 3 year old children, prolonged breastfeeding duration was a major determinant of increased POP concentrations. Estimated dietary exposure to PCBs during pregnancy was positively associated with plasma concentrations in 3 year old children, but not in pregnant women. Plasma concentrations were approximately 40% higher in children compared to pregnant women. Several factors associated with exposure and toxicokinetics, i.e. accumulation, excretion and transfer via breastmilk of POPs were the main predictors of POP levels in pregnant women and children. Diet, which is the main exposure source for these compounds in the general population, was found to predict PCB levels only among children. For the PBDEs, for which non-dietary sources are more important, toxicokinetic factors appeared to have less predictive impact. Copyright © 2015 Elsevier Inc. All rights reserved.

A New Merit Function for Evaluating the Flaw Tolerance of Composite Laminates. Pt. 2; Arbitrary Size Holes and Center Cracks

NASA Technical Reports Server (NTRS)

Mikulas, Martin M., Jr.; Sumpter, Rod

1999-01-01

In a previous paper, a new merit function for determining the strength performance of flawed composite laminates was presented. This previous analysis was restricted to circular hole flaws that were large enough that failure could be predicted using the laminate stress concentration factor. In this paper, the merit function is expanded to include the flaw cases of an arbitrary size circular hole or a center crack. Failure prediction for these cases is determined using the point stress criterion. An example application of the merit function is included for a wide range of graphite/epoxy laminates.

A New Merit Function for Evaluating the Flaw Tolerance of Composite Laminates. Part 2; Arbitrary Size Holes and Center Cracks

NASA Technical Reports Server (NTRS)

Martin, Mikulas M., Jr.; Sumpter, Rod

2000-01-01

In a previous paper, a new merit function for determining the strength performance of flawed composite laminates was presented. This previous analysis was restricted to circular hole flaws that were large enough that failure could be predicted using the laminate stress concentration factor. In this paper, the merit function is expanded to include the flaw cases of an arbitrary size circular hole or center crack. Failure prediction for these cases is determined using the point stress criterion. An example application of the merit function is included for a wide range of graphite/epoxy laminates.

A New Merit Function for Evaluating the Flaw Tolerance of Composite Laminates. Part 2; Arbitrary Size Holes and Center Cracks

NASA Technical Reports Server (NTRS)

Mikulas, Martin M., Jr.; Sumpter, Rod

1997-01-01

In a previous paper, a new merit function for determining the strength performance of flawed composite laminates was presented. This previous analysis was restricted to circular hole flaws that were large enough that failure could be predicted using the laminate stress concentration factor. In this paper, the merit function is expanded to include the flaw cases of an arbitrary size circular hole or a center crack. Failure prediction for these cases is determined using the point stress criterion. An example application of the merit function is included for a wide range of graphite/epoxy laminates.

Mathematical modeling of hydrolysate diffusion and utilization in cellulolytic biofilms of the extreme thermophile Caldicellulosiruptor obsidiansis.

PubMed

Wang, Zhi-Wu; Hamilton-Brehm, Scott D; Lochner, Adriane; Elkins, James G; Morrell-Falvey, Jennifer L

2011-02-01

In this study, a hydrolysate diffusion and utilization model was developed to examine factors influencing cellulolytic biofilm morphology. Model simulations using Caldicellulosiruptor obsidiansis revealed that the cellulolytic biofilm needs to generate more hydrolysate than it consumes to establish a higher than bulk solution intra-biofilm substrate concentration to support its growth. This produces a hydrolysate surplus that diffuses through the thin biofilm structure into the bulk solution, which gives rise to a uniform growth rate and hence the homogeneous morphology of the cellulolytic biofilm. Model predictions were tested against experimental data from a cellulose-fermenting bioreactor and the results were consistent with the model prediction and indicated that only a small fraction (10-12%) of the soluble hydrolysis products are utilized by the biofilm. The factors determining the rate-limiting step of cellulolytic biofilm growth are also analyzed and discussed. Copyright © 2010 Elsevier Ltd. All rights reserved.

Temporal modelling and forecasting of the airborne pollen of Cupressaceae on the southwestern Iberian Peninsula.

PubMed

Silva-Palacios, Inmaculada; Fernández-Rodríguez, Santiago; Durán-Barroso, Pablo; Tormo-Molina, Rafael; Maya-Manzano, José María; Gonzalo-Garijo, Ángela

2016-02-01

Cupressaceae includes species cultivated as ornamentals in the urban environment. This study aims to investigate airborne pollen data for Cupressaceae on the southwestern Iberian Peninsula over a 21-year period and to analyse the trends in these data and their relationship with meteorological parameters using time series analysis. Aerobiological sampling was conducted from 1993 to 2013 in Badajoz (SW Spain). The main pollen season for Cupressaceae lasted, on average, 58 days, ranging from 55 to 112 days, from 24 January to 22 March. Furthermore, a short-term forecasting model has been developed for daily pollen concentrations. The model proposed to forecast the airborne pollen concentration is described by one equation. This expression is composed of two terms: the first term represents the pollen concentration trend in the air according to the average concentration of the previous 10 days; the second term is obtained from considering the actual pollen concentration value, which is calculated based on the most representative meteorological parameters multiplied by a fitting coefficient. Temperature was the main meteorological factor by its influence over daily pollen forecast, being the rain the second most important factor. This model represents a good approach to a continuous balance model of Cupressaceae pollen concentration and is supported by a close agreement between the observed and predicted mean concentrations. The novelty of the proposed model is the analysis of meteorological parameters that are not frequently used in Aerobiology.

Observed and modeled seasonal trends in dissolved and particulate Cu, Fe, Mn, and Zn in a mining-impacted stream.

PubMed

Butler, Barbara A; Ranville, James F; Ross, Philippe E

2008-06-01

North Fork Clear Creek (NFCC) in Colorado, an acid-mine drainage (AMD) impacted stream, was chosen to examine the distribution of dissolved and particulate Cu, Fe, Mn, and Zn in the water column, with respect to seasonal hydrologic controls. NFCC is a high-gradient stream with discharge directly related to snowmelt and strong seasonal storms. Additionally, conditions in the stream cause rapid precipitation of large amounts of hydrous iron oxides (HFO) that sequester metals. Because AMD-impacted systems are complex, geochemical modeling may assist with predictions and/or confirmations of processes occurring in these environments. This research used Visual-MINTEQ to determine if field data collected over a two and one-half year study would be well represented by modeling with a currently existing model, while limiting the number of processes modeled and without modifications to the existing model's parameters. Observed distributions between dissolved and particulate phases in the water column varied greatly among the metals, with average dissolved fractions being >90% for Mn, approximately 75% for Zn, approximately 30% for Cu, and <10% for Fe. A strong seasonal trend was observed for the metals predominantly in the dissolved phase (Mn and Zn), with increasing concentrations during base-flow conditions and decreasing concentrations during spring-runoff. This trend was less obvious for Cu and Fe. Within hydrologic seasons, storm events significantly influenced in-stream metals concentrations. The most simplified modeling, using solely sorption to HFO, gave predicted percentage particulate Cu results for most samples to within a factor of two of the measured values, but modeling data were biased toward over-prediction. About one-half of the percentage particulate Zn data comparisons fell within a factor of two, with the remaining data being under-predicted. Slightly more complex modeling, which included dissolved organic carbon (DOC) as a solution phase ligand, significantly reduced the positive bias between observed and predicted percentage particulate Cu, while inclusion of hydrous manganese oxide (HMO) yielded model results more representative of the observed percentage particulate Zn. These results indicate that there is validity in the use of an existing model, without alteration and with typically collected water chemistry data, to describe complex natural systems, but that processes considered optimal for one metal might not be applicable for all metals in a given water sample.

A Computer Model for Analyzing Volatile Removal Assembly

NASA Technical Reports Server (NTRS)

Guo, Boyun

2010-01-01

A computer model simulates reactional gas/liquid two-phase flow processes in porous media. A typical process is the oxygen/wastewater flow in the Volatile Removal Assembly (VRA) in the Closed Environment Life Support System (CELSS) installed in the International Space Station (ISS). The volatile organics in the wastewater are combusted by oxygen gas to form clean water and carbon dioxide, which is solved in the water phase. The model predicts the oxygen gas concentration profile in the reactor, which is an indicator of reactor performance. In this innovation, a mathematical model is included in the computer model for calculating the mass transfer from the gas phase to the liquid phase. The amount of mass transfer depends on several factors, including gas-phase concentration, distribution, and reaction rate. For a given reactor dimension, these factors depend on pressure and temperature in the reactor and composition and flow rate of the influent.

Determination of Fracture Parameters for Multiple Cracks of Laminated Composite Finite Plate

NASA Astrophysics Data System (ADS)

Srivastava, Amit Kumar; Arora, P. K.; Srivastava, Sharad Chandra; Kumar, Harish; Lohumi, M. K.

2018-04-01

A predictive method for estimation of stress state at zone of crack tip and assessment of remaining component lifetime depend on the stress intensity factor (SIF). This paper discusses the numerical approach for prediction of first ply failure load (FL), progressive failure load, SIF and critical SIF for multiple cracks configurations of laminated composite finite plate using finite element method (FEM). The Hashin and Chang failure criterion are incorporated in ABAQUS using subroutine approach user defined field variables (USDFLD) for prediction of progressive fracture response of laminated composite finite plate, which is not directly available in the software. A tensile experiment on laminated composite finite plate with stress concentration is performed to validate the numerically predicted subroutine results, shows excellent agreement. The typical results are presented to examine effect of changing the crack tip distance (S), crack offset distance (H), and stacking fiber angle (θ) on FL, and SIF .

Regional accumulation characteristics of cadmium in vegetables: Influencing factors, transfer model and indication of soil threshold content.

PubMed

Yang, Yang; Chen, Weiping; Wang, Meie; Peng, Chi

2016-12-01

A regional investigation in the Youxian prefecture, southern China, was conducted to analyze the impact of environmental factors including soil properties and irrigation in conjunction with the use of fertilizers on the accumulation of Cd in vegetables. The Cd transfer potential from soil to vegetable was provided by the plant uptake factor (PUF), which varied by three orders of magnitude and was described by a Gaussian distribution model. The soil pH, content of soil organic matter (SOM), concentrations of Zn in the soil, pH of irrigation water and nitrogenous fertilizers contributed significantly to the PUF variations. A path model analysis, however, revealed the principal control of the PUF values resulted from the soil pH, soil Zn concentrations and SOM. Transfer functions were developed using the total soil Cd concentrations, soil pH, and SOM. They explained 56% of the variance for all samples irrespective of the vegetable genotypes. The transfer functions predicted the probability of exceeding China food safety standard concentrations for Cd in four major consumable vegetables under different soil conditions. Poor production practices in the study area involved usage of soil with pH values ≤ 5.5, especially for the cultivation of Raphanus sativus L., even with soil Cd concentrations below the China soil quality standard. We found the soil standard Cd concentrations for cultivating vegetables was not strict enough for strongly acidic (pH ≤ 5.5) and SOM-poor (SOM ≤ 10 g kg -1 ) soils present in southern China. It is thus necessary to address the effect of environmental variables to generate a suitable Cd threshold for cultivated soils. Copyright © 2016 Elsevier Ltd. All rights reserved.

Change in Growth Differentiation Factor 15, but Not C-Reactive Protein, Independently Predicts Major Cardiac Events in Patients with Non-ST Elevation Acute Coronary Syndrome

PubMed Central

Hernandez-Baldomero, Idaira F.; Bosa-Ojeda, Francisco

2014-01-01

Among the numerous emerging biomarkers, high-sensitivity C-reactive protein (hsCRP) and growth-differentiation factor-15 (GDF-15) have received widespread interest, with their potential role as predictors of cardiovascular risk. The concentrations of inflammatory biomarkers, however, are influenced, among others, by physiological variations, which are the natural, within-individual variation occurring over time. The aims of our study are: (a) to describe the changes in hsCRP and GDF-15 levels over a period of time and after an episode of non-ST-segment elevation acute coronary syndrome (NSTE-ACS) and (b) to examine whether the rate of change in hsCRP and GDF-15 after the acute event is associated with long-term major cardiovascular adverse events (MACE). Two hundred and Fifty five NSTE-ACS patients were included in the study. We measured hsCRP and GDF-15 concentrations, at admission and again 36 months after admission (end of the follow-up period). The present study shows that the change of hsCRP levels, measured after 36 months, does not predict MACE in NSTEACS-patients. However, the level of GDF-15 measured, after 36 months, was a stronger predictor of MACE, in comparison to the acute unstable phase. PMID:24839357

Estimation of Groundwater Radon in North Carolina Using Land Use Regression and Bayesian Maximum Entropy.

PubMed

Messier, Kyle P; Campbell, Ted; Bradley, Philip J; Serre, Marc L

2015-08-18

Radon ((222)Rn) is a naturally occurring chemically inert, colorless, and odorless radioactive gas produced from the decay of uranium ((238)U), which is ubiquitous in rocks and soils worldwide. Exposure to (222)Rn is likely the second leading cause of lung cancer after cigarette smoking via inhalation; however, exposure through untreated groundwater is also a contributing factor to both inhalation and ingestion routes. A land use regression (LUR) model for groundwater (222)Rn with anisotropic geological and (238)U based explanatory variables is developed, which helps elucidate the factors contributing to elevated (222)Rn across North Carolina. The LUR is also integrated into the Bayesian Maximum Entropy (BME) geostatistical framework to increase accuracy and produce a point-level LUR-BME model of groundwater (222)Rn across North Carolina including prediction uncertainty. The LUR-BME model of groundwater (222)Rn results in a leave-one out cross-validation r(2) of 0.46 (Pearson correlation coefficient = 0.68), effectively predicting within the spatial covariance range. Modeled results of (222)Rn concentrations show variability among intrusive felsic geological formations likely due to average bedrock (238)U defined on the basis of overlying stream-sediment (238)U concentrations that is a widely distributed consistently analyzed point-source data.

Optimization of fermentation medium for the production of atrazine degrading strain Acinetobacter sp. DNS(32) by statistical analysis system.

PubMed

Zhang, Ying; Wang, Yang; Wang, Zhi-Gang; Wang, Xi; Guo, Huo-Sheng; Meng, Dong-Fang; Wong, Po-Keung

2012-01-01

Statistical experimental designs provided by statistical analysis system (SAS) software were applied to optimize the fermentation medium composition for the production of atrazine-degrading Acinetobacter sp. DNS(32) in shake-flask cultures. A "Plackett-Burman Design" was employed to evaluate the effects of different components in the medium. The concentrations of corn flour, soybean flour, and K(2)HPO(4) were found to significantly influence Acinetobacter sp. DNS(32) production. The steepest ascent method was employed to determine the optimal regions of these three significant factors. Then, these three factors were optimized using central composite design of "response surface methodology." The optimized fermentation medium composition was composed as follows (g/L): corn flour 39.49, soybean flour 25.64, CaCO(3) 3, K(2)HPO(4) 3.27, MgSO(4)·7H(2)O 0.2, and NaCl 0.2. The predicted and verifiable values in the medium with optimized concentration of components in shake flasks experiments were 7.079 × 10(8) CFU/mL and 7.194 × 10(8) CFU/mL, respectively. The validated model can precisely predict the growth of atrazine-degraing bacterium, Acinetobacter sp. DNS(32).

Colligative thermoelectric transport properties in n-type filled CoSb{sub 3} determined by guest electrons in a host lattice

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lim, Young Soo, E-mail: yslim@pknu.ac.kr, E-mail: wsseo@kicet.re.kr, E-mail: pmoka@lgchem.com; Park, Kwan-Ho; Tak, Jang Yeul

2016-03-21

Among many kinds of thermoelectric materials, CoSb{sub 3} has received exceptional attention for automotive waste heat recovery. Its cage structure provides an ideal framework for the realization of phonon-glass electron-crystal strategy, and there have been numerous reports on the enhanced thermoelectric performance through the independent control of the thermal and electrical conductivity by introducing fillers into its cage sites. Herein, we report colligative thermoelectric transport properties in n-type CoSb{sub 3} from the viewpoint of “guest electrons in a host lattice.” Both the Seebeck coefficient and the charge transport properties are fundamentally determined by the concentration of the guest electrons, whichmore » are mostly donated by the fillers, in the conduction band of the host CoSb{sub 3}. Comparing this observation to our previous results, colligative relations for both the Seebeck coefficient and the mobility were deduced as functions of the carrier concentration, and thermoelectric transport constants were defined to predict the power factor in filled CoSb{sub 3}. This discovery not only increases the degree of freedom for choosing a filler but also provides the predictability of power factor in designing and engineering the n-type filled CoSb{sub 3} materials.« less

Water Quality in the Upper Anacostia River, Maryland: Continuous and Discrete Monitoring with Simulations to Estimate Concentrations and Yields, 2003-05

USGS Publications Warehouse

Miller, Cherie V.; Gutierrez-Magness, Angelica L.; Feit Majedi, Brenda L.; Foster, Gregory D.

2007-01-01

From 2003 through 2005, continuous and discrete waterquality data were collected at two stations on the Anacostia River in Maryland: Northeast Branch at Riverdale, Maryland (U.S. Geological Survey Station 01649500) and Northwest Branch near Hyattsville, Maryland (Station 01651000). Both stations are above the heads of tide for the river, and measurements approximately represent contributions of chemicals from the nontidal watersheds in the Anacostia River. This study was a cooperative effort between the U.S. Geological Survey, the Prince George's County Department of Environmental Resources, the Maryland Department of the Environment, the U.S. Environmental Protection Agency, and George Mason University. Samples were collected for suspended sediment, nutrients, and trace metals; data were used to calculate loads of selected chemical parameters, and to evaluate the sources and transport processes of contaminants. Enrichment factors were calculated for some trace metals and used to interpret patterns of occurrence over different flow regimes. Some metals, such as cadmium, lead, and zinc, were slightly enriched as compared to global averages for shales; overall, median values of enrichment factors for all metals were approximately 15 to 35. Stepwise linear regression models were developed on log-transformed concentrations to estimate the concentrations of suspended sediment, total nitrogen, and total phosphorus from continuous data of discharge and turbidity. The use of multiple explanatory variables improved the predictions over traditional rating curves that use only streamflow as the explanatory variable, because other variables such as turbidity measure the hysteretic effects of fine-grained suspended sediment over storm hydrographs. Estimates of the concentrations of suspended sediment from continuous discharge and turbidity showed coefficients of determination for the predictions (multiple R2) of 0.95 and biases of less than 4 percent. Models to estimate the concentrations of total phosphorus and total nitrogen had lower values of multiple R2 than suspended sediment, but the estimated bias for all the models was similar. The models for total nitrogen and total phosphorus tended to under-predict high concentrations and to over-predict low concentrations as compared to measured values. Annual yields (loads per square area in kilograms per year per square kilometer) were estimated for suspended sediment, total nitrogen, and total phosphorus using the U.S. Geological Survey models ESTIMATOR and LOADEST. The model LOADEST used hourly time steps and allowed the use of turbidity, which is strongly correlated to concentrations of suspended sediment, as a predictor variable. Annual yields for total nitrogen and total phosphorus were slightly higher but similar to previous estimates for other watersheds of the Chesapeake Bay, but annual yields for suspended sediment were higher by an order of magnitude for the two Anacostia River stations. Annual yields of suspended sediment at the two Anacostia River stations ranged from 131,000 to 248,000 kilograms per year per square kilometer for 2004 and 2005. LOADEST estimates were similar to those determined with ESTIMATOR, but had reduced errors associated with the estimates.

Trace metals in sediments of two estuarine lagoons from Puerto Rico.

PubMed

Acevedo-Figueroa, D; Jiménez, B D; Rodríguez-Sierra, C J

2006-05-01

Concentrations of As, Cd, Cu, Fe, Hg, Pb and Zn were evaluated in surface sediments of two estuaries from Puerto Rico, known as San José Lagoon (SJL) and Joyuda Lagoon. Significantly higher concentrations in microg/g dw of Cd (1.8 vs. 0.1), Cu (105 vs. 22), Hg (1.9 vs. 0.17), Pb (219 vs. 8), and Zn (531 vs. 52) were found in sediment samples from SJL when compared to Joyuda Lagoon. Average concentrations of Hg, Pb, and Zn in some sediment samples from SJL were above the effect range median (ERM) that predict toxic effects to aquatic organisms. Enrichments factors using Fe as a normalizer, and correlation matrices showed that metal pollution in SJL was the product of anthropogenic sources, while the metal content in Joyuda Lagoon was of natural origins. Sediment metal concentrations found in SJL were comparable to aquatic systems classified as contaminated from other regions of the world.

Combined effects of Corexit EC 9500A with secondary abiotic and biotic factors in the rotifer Brachionus plicatilis.

PubMed

Williams, Michael B; Powell, Mickie L; Watts, Stephen A

2016-10-01

We examined lethality and behavioral effects of Corexit EC 9500A (C-9500A) exposure on the model marine zooplankton Brachionus plicatilis singularly and in combination with abiotic and biotic factors. C-9500A exposure at standard husbandry conditions (17.5ppt, 24°C, 200 rotifer*mL(-1) density) identified the 24h median lethal concentration, by Probit analysis, to be 107ppm for cultured B. plicatilis. Rotifers surviving exposure to higher concentrations (100 and 150ppm) exhibited a decreased swimming velocity and a reduced net to gross movement ratio. Significant interaction between C-9500A exposure and temperature or salinity was observed. Upper thermal range was reduced and maximal salinity stress was seen as ca. 25ppt. Increased or decreased nutritional availability over the exposure period did not significantly alter mortality of B. plicatilis populations at the concentrations tested. Results from this study may be useful for predicting possible outcomes on marine zooplankton following dispersant application under diverse natural conditions. Copyright © 2016 Elsevier Inc. All rights reserved.

Refractive index investigation of poly(vinyl alcohol) films with TiO2 nanoparticle inclusions.

PubMed

Yovcheva, Temenuzhka; Vlaeva, Ivanka; Bodurov, Ivan; Dragostinova, Violeta; Sainov, Simeon

2012-11-10

The refractive index (RI) of polymer nanocomposite of poly(vinyl alcohol) films with TiO(2) nanoparticle inclusions with low concentration up to 1.2 wt. % was investigated. Accurate refractometric measurements, by a specially designed laser microrefractometer, were performed at wavelengths 532 and 632.8 nm. The influence of TiO(2) concentration on the RI dispersion curves was predicted based on the well-known Sellmeier model. The theoretical analysis, in a small filling factor approximation, was performed, and a relation between the effective RI of the nanocomposite and weight concentrations of the TiO(2) nanofiller was derived. The experimental values were approximated by two different functions (linear and a quadratic polynom). The polynomial approximation yields better result, where R(2)=0.90.

Predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwestern United States

USGS Publications Warehouse

Anning, David W.; Paul, Angela P.; McKinney, Tim S.; Huntington, Jena M.; Bexfield, Laura M.; Thiros, Susan A.

2012-01-01

The National Water-Quality Assessment (NAWQA) Program of the U.S. Geological Survey (USGS) is conducting a regional analysis of water quality in the principal aquifer systems across the United States. The Southwest Principal Aquifers (SWPA) study is building a better understanding of the susceptibility and vulnerability of basin-fill aquifers in the region to groundwater contamination by synthesizing baseline knowledge of groundwater-quality conditions in 16 basins previously studied by the NAWQA Program. The improved understanding of aquifer susceptibility and vulnerability to contamination is assisting in the development of tools that water managers can use to assess and protect the quality of groundwater resources.Human-health concerns and economic considerations associated with meeting drinking-water standards motivated a study of the vulnerability of basin-fill aquifers to nitrate con­tamination and arsenic enrichment in the southwestern United States. Statistical models were developed by using the random forest classifier algorithm to predict concentrations of nitrate and arsenic across a model grid that represents about 190,600 square miles of basin-fill aquifers in parts of Arizona, California, Colorado, Nevada, New Mexico, and Utah. The statistical models, referred to as classifiers, reflect natural and human-related factors that affect aquifer vulnerability to contamina­tion and relate nitrate and arsenic concentrations to explana­tory variables representing local- and basin-scale measures of source, aquifer susceptibility, and geochemical conditions. The classifiers were unbiased and fit the observed data well, and misclassifications were primarily due to statistical sampling error in the training datasets.The classifiers were designed to predict concentrations to be in one of six classes for nitrate, and one of seven classes for arsenic. Each classification scheme allowed for identification of areas with concentrations that were equal to or exceeding the U.S. Environmental Protection Agency drinking-water standard. Whereas 2.4 percent of the area underlain by basin-fill aquifers in the study area was predicted to equal or exceed this standard for nitrate (10 milligrams per liter as N; mg/L), 42.7 percent was predicted to equal or exceed the standard for arsenic (10 micrograms per liter; μg/L). Areas predicted to equal or exceed the drinking-water standard for nitrate include basins in central Arizona near Phoenix; the San Joaquin, Inland, and San Jacinto basins of California; and the San Luis Valley of Colorado. Much of the area predicted to equal or exceed the drinking-water standard for arsenic is within a belt of basins along the western portion of the Basin and Range Physiographic Province in Nevada, California, and Arizona. Predicted nitrate and arsenic concentrations are substantially lower than the drinking-water standards in much of the study area—about 93.0 percent of the area underlain by basin-fill aquifers was less than one-half the standard for nitrate (5.0 mg/L), and 50.2 percent was less than one-half the standard for arsenic (5.0 μg/L).

Simulation of nutrient and sediment concentrations and loads in the Delaware inland bays watershed: Extension of the hydrologic and water-quality model to ungaged segments

USGS Publications Warehouse

Gutierrez-Magness, Angelica L.

2006-01-01

Rapid population increases, agriculture, and industrial practices have been identified as important sources of excessive nutrients and sediments in the Delaware Inland Bays watershed. The amount and effect of excessive nutrients and sediments in the Inland Bays watershed have been well documented by the Delaware Geological Survey, the Delaware Department of Natural Resources and Environmental Control, the U.S. Environmental Protection Agency's National Estuary Program, the Delaware Center for Inland Bays, the University of Delaware, and other agencies. This documentation and data previously were used to develop a hydrologic and water-quality model of the Delaware Inland Bays watershed to simulate nutrients and sediment concentrations and loads, and to calibrate the model by comparing concentrations and streamflow data at six stations in the watershed over a limited period of time (October 1998 through April 2000). Although the model predictions of nutrient and sediment concentrations for the calibrated segments were fairly accurate, the predictions for the 28 ungaged segments located near tidal areas, where stream data were not available, were above the range of values measured in the area. The cooperative study established in 2000 by the Delaware Department of Natural Resources and Environmental Control, the Delaware Geological Survey, and the U.S. Geological Survey was extended to evaluate the model predictions in ungaged segments and to ensure that the model, developed as a planning and management tool, could accurately predict nutrient and sediment concentrations within the measured range of values in the area. The evaluation of the predictions was limited to the period of calibration (1999) of the 2003 model. To develop estimates on ungaged watersheds, parameter values from calibrated segments are transferred to the ungaged segments; however, accurate predictions are unlikely where parameter transference is subject to error. The unexpected nutrient and sediment concentrations simulated with the 2003 model were likely the result of inappropriate criteria for the transference of parameter values. From a model-simulation perspective, it is a common practice to transfer parameter values based on the similarity of soils or the similarity of land-use proportions between segments. For the Inland Bays model, the similarity of soils between segments was used as the basis to transfer parameter values. An alternative approach, which is documented in this report, is based on the similarity of the spatial distribution of the land use between segments and the similarity of land-use proportions, as these can be important factors for the transference of parameter values in lumped models. Previous work determined that the difference in the variation of runoff due to various spatial distributions of land use within a watershed can cause substantialloss of accuracy in the model predictions. The incorporation of the spatial distribution of land use to transfer parameter values from calibrated to uncalibrated segments provided more consistent and rational predictions of flow, especially during the summer, and consequently, predictions of lower nutrient concentrations during the same period. For the segments where the similarity of spatial distribution of land use was not clearly established with a calibrated segment, the similarity of the location of the most impervious areas was also used as a criterion for the transference of parameter values. The model predictions from the 28 ungaged segments were verified through comparison with measured in-stream concentrations from local and nearby streams provided by the Delaware Department of Natural Resources and Environmental Control. Model results indicated that the predicted edge-of-stream total suspended solids loads in the Inland Bays watershed were low in comparison to loads reported for the Eastern Shore of Maryland from the Chesapeake Bay watershed model. The flatness of the ter

A decrease in D-dimer concentration and an occurrence of skin rash as iatrogenic events and complementary predictors of survival in lung cancer patients treated with EGFR tyrosine kinase inhibitors.

PubMed

Zaborowska-Szmit, Magdalena; Kowalski, Dariusz M; Piórek, Aleksandra; Krzakowski, Maciej; Szmit, Sebastian

2016-12-01

Progression of lung cancer is associated with some abnormalities in coagulation. The aim of the study was to determine the predictive and prognostic value of changes in D-dimer concentration in non-small cell lung cancer (NSCLC) patients on anti-EGFR targeted therapy. The analysis included fifty two NSCLC patients treated with EGFR tyrosine kinase inhibitors (TKIs): erlotinib or gefitinib. All clinical data were collected before treatment and after 2 cycles (60days) of therapy and correlated with progression free and overall survival (PFS, OS). Two iatrogenic events were noted within the first 60days of anti-EGFR treatment: typical skin rash in 38 (73.1%) and a decrease in D-dimer concentration in 26 (50%) patients. Multivariate analysis revealed a decrease of D-dimer concentration as the strongest factor associated with longer PFS (HR=0.39; 95%CI: 0.16-0.91; p=0.029) and OS (HR=0.33; 95%CI: 0.13-0.82, p=0.017) independently of skin rash, baseline level of D-dimer and other clinical characteristics. Coexisting a decrease in D-dimer concentration with an occurrence of skin rash correlated significantly with the positive objective response after 60days of anti-EGFR therapy (p=0.0175) and indicated the longest PFS (HR=0.31; 95%CI: 0.16-0.60, p=0.0005) as well as OS (HR=0.30; 95%CI: 0.15-0.59, p=0.0005). Adverse events may predict the outcomes of cancer patients. Apart from skin rash, change in D-dimer concentration may be valuable parameter in creation of predictive and prognostic models in NSCLC patients receiving anti-EGFR targeted therapy. Copyright © 2016. Published by Elsevier Urban & Partner Sp. z o.o.

Vitamin D deficiency and insufficiency in HIV-infected children and young adults.

PubMed

Meyzer, Candice; Frange, Pierre; Chappuy, Hélène; Desse, Blandine; Veber, Florence; Le Clésiau, Hervé; Friedlander, Gérard; Blanche, Stéphane; Souberbielle, Jean-Claude; Tréluyer, Jean-Marc; Courbebaisse, Marie

2013-11-01

Vitamin D insufficiency and HIV infection are both risk factors for chronic disorders, so it is important to consider vitamin D status in HIV-infected patients. We prospectively investigated serum 25-hydroxyvitamin D (25(OH)D) concentrations, determined by radioimmunoassay, in 113 HIV-infected children (age≤24 years) and 54 healthy controls matched for age and phototype. We assessed the prevalence of vitamin D deficiency and insufficiency (VDD and VDI) defined as 25(OH)D titers of <10 ng/mL and between 10 and 30 ng/mL, respectively, and their predictive factors. The overall prevalence of VDD and VDI was 38.9% and 58.7%, respectively. Mean serum 25(OH)D concentrations were significantly higher in the HIV group than the control group (14.2±6.9 ng/mL vs. 10.4±5 ng/mL, P<0.001). Variables significantly associated with low serum 25(OH)D concentrations in HIV-infected children were dark phototype (P<0.001) and age (r=-0.19, P=0.03). Patients receiving efavirenz had a trend toward lower serum 25(OH)D concentrations (11.1±4.6 ng/mL vs. 14.6±7 ng/mL, P=0.1). Dark phototype was the only independent risk factor for VDD in HIV-infected children (odds ratio=14.6; 95% confidence interval: 2.4-89.9, P=0.004). VDD and VDI were common in both HIV-infected and control groups, and serum 25(OH)D concentrations were significantly lower in controls than in HIV-infected children.

Performance analysis of high-concentrated multi-junction solar cells in hot climate

NASA Astrophysics Data System (ADS)

Ghoneim, Adel A.; Kandil, Kandil M.; Alzanki, Talal H.; Alenezi, Mohammad R.

2018-03-01

Multi-junction concentrator solar cells are a promising technology as they can fulfill the increasing energy demand with renewable sources. Focusing sunlight upon the aperture of multi-junction photovoltaic (PV) cells can generate much greater power densities than conventional PV cells. So, concentrated PV multi-junction solar cells offer a promising way towards achieving minimum cost per kilowatt-hour. However, these cells have many aspects that must be fixed to be feasible for large-scale energy generation. In this work, a model is developed to analyze the impact of various atmospheric factors on concentrator PV performance. A single-diode equivalent circuit model is developed to examine multi-junction cells performance in hot weather conditions, considering the impacts of both temperature and concentration ratio. The impacts of spectral variations of irradiance on annual performance of various high-concentrated photovoltaic (HCPV) panels are examined, adapting spectra simulations using the SMARTS model. Also, the diode shunt resistance neglected in the existing models is considered in the present model. The present results are efficiently validated against measurements from published data to within 2% accuracy. Present predictions show that the single-diode model considering the shunt resistance gives accurate and reliable results. Also, aerosol optical depth (AOD) and air mass are most important atmospheric parameters having a significant impact on HCPV cell performance. In addition, the electrical efficiency (η) is noticed to increase with concentration to a certain concentration degree after which it decreases. Finally, based on the model predictions, let us conclude that the present model could be adapted properly to examine HCPV cells' performance over a broad range of operating conditions.

Toward a cumulative ecological risk model for the etiology of child maltreatment

PubMed Central

MacKenzie, Michael J.; Kotch, Jonathan B.; Lee, Li-Ching

2011-01-01

The purpose of the current study was to further the integration of cumulative risk models with empirical research on the etiology of child maltreatment. Despite the well-established literature supporting the importance of the accumulation of ecological risk, this perspective has had difficulty infiltrating empirical maltreatment research and its tendency to focus on more limited risk factors. Utilizing a sample of 842 mother-infant dyads, we compared the capacity of individual risk factors and a cumulative index to predict maltreatment reports in a prospective longitudinal investigation over the first sixteen years of life. The total load of risk in early infancy was found to be related to maternal cognitions surrounding her new role, measures of social support and well-being, and indicators of child cognitive functioning. After controlling for total level of cumulative risk, most single factors failed to predict later maltreatment reports and no single variable provided odd-ratios as powerful as the predictive power of a cumulative index. Continuing the shift away from simplistic causal models toward an appreciation for the cumulative nature of risk would be an important step forward in the way we conceptualize intervention and support programs, concentrating them squarely on alleviating the substantial risk facing so many of society’s families. PMID:24817777

Application of factor analysis of infrared spectra for quantitative determination of beta-tricalcium phosphate in calcium hydroxylapatite.

PubMed

Arsenyev, P A; Trezvov, V V; Saratovskaya, N V

1997-01-01

This work represents a method, which allows to determine phase composition of calcium hydroxylapatite basing on its infrared spectrum. The method uses factor analysis of the spectral data of calibration set of samples to determine minimal number of factors required to reproduce the spectra within experimental error. Multiple linear regression is applied to establish correlation between factor scores of calibration standards and their properties. The regression equations can be used to predict the property value of unknown sample. The regression model was built for determination of beta-tricalcium phosphate content in hydroxylapatite. Statistical estimation of quality of the model was carried out. Application of the factor analysis on spectral data allows to increase accuracy of beta-tricalcium phosphate determination and expand the range of determination towards its less concentration. Reproducibility of results is retained.

Physical self-concept and physical fitness in elderly individuals.

PubMed

Amesberger, G; Finkenzeller, T; Würth, S; Müller, E

2011-08-01

This investigation examined the relations between physical self-concept and physical fitness (endurance, balance, muscle strength, muscle power) for gaining knowledge about the interrelationship between subjective ratings and objective fitness scores in the elderly in three steps: (1) detecting correlations and changes in time, (2) clarifying the influence of gender, and (3) of a skiing intervention lasting 12 weeks. Physical self-concept was assessed using a modified version of the Physical Self-Concepts (PSK) scales (Stiller et al., 2004) reflecting three first-order factors (endurance, strength, general sportiness) and one second-order factor (global fitness). Objective fitness scores were obtained by VO(2 max), counter movement jump, concentric muscle strength, and static balance. The results reveal that elderly individuals' global physical self and general sportiness are mainly linked to VO(2 max) and concentric muscle strength. Global physical self is predicted by VO(2 max) in females and by physical strength (concentric muscle strength) in males, indicating gender differences. Over time, correlations between subjective ratings and objective fitness scores become stronger in the sense of convergent validity in the skiing intervention group, whereas convergent and divergent validity cannot be supported by data of the control group. In sum, physical self-concept is an important factor in the context of physical intervention programs in the elderly. © 2011 John Wiley & Sons A/S.

Preparation and optimization of self-assembled chondroitin sulfate-nisin nanogel based on quality by design concept.

PubMed

Mohtashamian, Shahab; Boddohi, Soheil; Hosseinkhani, Saman

2018-02-01

Self-assembled nanogel was prepared by electrostatic complexation of two oppositely charged biological macromolecules, which were cationic nisin and anionic chondroitin sulfate (ChS). The critical factors affected the physical properties of ChS-nisin nanogel was screened and optimized by Plackett-Burman design (PB) and central composite design (CCD). The independent factors selected were: concentration ratio of nisin to ChS, injection rate of nisin solution, buffer solvent type, magnetic stirring rate, pH of initial buffer solution, centrifuge-cooling temperature, and centrifuge rotation speed. Among these factors, concentration ratio changed the entrapment efficiency and loading capacity significantly. In addition, the hydrodynamic diameter and loading capacity were significantly influenced by injection rate and pH of initial buffer solution. The optimized nanogel structure was obtained by concentration ratio of 6.4mg/mL nisin to 1mg/mL ChS, pH of buffer solution at 4.6, and nisin solution injection rate of 0.2mL/min. The observed values of dependent responses were close to predicted values confirmed by model from response surface methodology. The results obviously showed that quality by design concept (QbD) could be effectively applied to optimize the developed ChS-nisin nanogel. Copyright © 2017 Elsevier B.V. All rights reserved.

Impacts of Changes of Indoor Air Pressure and Air Exchange Rate in Vapor Intrusion Scenarios

PubMed Central

Shen, Rui; Suuberg, Eric M.

2016-01-01

There has, in recent years, been increasing interest in understanding the transport processes of relevance in vapor intrusion of volatile organic compounds (VOCs) into buildings on contaminated sites. These studies have included fate and transport modeling. Most such models have simplified the prediction of indoor air contaminant vapor concentrations by employing a steady state assumption, which often results in difficulties in reconciling these results with field measurements. This paper focuses on two major factors that may be subject to significant transients in vapor intrusion situations, including the indoor air pressure and the air exchange rate in the subject building. A three-dimensional finite element model was employed with consideration of daily and seasonal variations in these factors. From the results, the variations of indoor air pressure and air exchange rate are seen to contribute to significant variations in indoor air contaminant vapor concentrations. Depending upon the assumptions regarding the variations in these parameters, the results are only sometimes consistent with the reports of several orders of magnitude in indoor air concentration variations from field studies. The results point to the need to examine more carefully the interplay of these factors in order to quantitatively understand the variations in potential indoor air exposures. PMID:28090133

Impacts of Changes of Indoor Air Pressure and Air Exchange Rate in Vapor Intrusion Scenarios.

PubMed

Shen, Rui; Suuberg, Eric M

2016-02-01

There has, in recent years, been increasing interest in understanding the transport processes of relevance in vapor intrusion of volatile organic compounds (VOCs) into buildings on contaminated sites. These studies have included fate and transport modeling. Most such models have simplified the prediction of indoor air contaminant vapor concentrations by employing a steady state assumption, which often results in difficulties in reconciling these results with field measurements. This paper focuses on two major factors that may be subject to significant transients in vapor intrusion situations, including the indoor air pressure and the air exchange rate in the subject building. A three-dimensional finite element model was employed with consideration of daily and seasonal variations in these factors. From the results, the variations of indoor air pressure and air exchange rate are seen to contribute to significant variations in indoor air contaminant vapor concentrations. Depending upon the assumptions regarding the variations in these parameters, the results are only sometimes consistent with the reports of several orders of magnitude in indoor air concentration variations from field studies. The results point to the need to examine more carefully the interplay of these factors in order to quantitatively understand the variations in potential indoor air exposures.

Evaluation of steady-state kinetic parameters for enzymes solubilized in water-in-oil microemulsion systems.

PubMed Central

Oldfield, C

1990-01-01

1. Equations are derived for the steady-state kinetics of substrate conversion by enzymes confined within the water-droplets of water-in-oil microemulsion systems. 2. Water-soluble substrates initially confined within droplets that do not contain enzyme are assumed to be converted into product only after they enter enzyme-containing droplets via the inter-droplet exchange process. 3. Hyperbolic (Michaelis-Menten) kinetics are predicted when the substrate concentration is varied in microemulsions of fixed composition. Both kcat. and Km are predicted to be dependent on the size and concentration of the water-droplets in the microemulsion. 4. The predicted behaviour is shown to be supported by published experimental data. A physical interpretation of the form of the rate equation is presented. 5. The rate equation for an oil-soluble substrate was derived assuming a pseudo-two-phase (oil & water) model for the microemulsion. Both kcat. and Km are shown to be independent of phi aq. Km is larger than the aqueous solution value by a factor approximately equal to the oil/water partition coefficient of the substrate. The validity of the rate equation is confirmed by published data. PMID:2264819

Occurrence and in-stream attenuation of wastewater-derived pharmaceuticals in Iberian rivers.

PubMed

Acuña, Vicenç; von Schiller, Daniel; García-Galán, Maria Jesús; Rodríguez-Mozaz, Sara; Corominas, Lluís; Petrovic, Mira; Poch, Manel; Barceló, Damià; Sabater, Sergi

2015-01-15

A multitude of pharmaceuticals enter surface waters via discharges of wastewater treatment plants (WWTPs), and many raise environmental and health concerns. Chemical fate models predict their concentrations using estimates of mass loading, dilution and in-stream attenuation. However, current comprehension of the attenuation rates remains a limiting factor for predictive models. We assessed in-stream attenuation of 75 pharmaceuticals in 4 river segments, aiming to characterize in-stream attenuation variability among different pharmaceutical compounds, as well as among river segments differing in environmental conditions. Our study revealed that in-stream attenuation was highly variable among pharmaceuticals and river segments and that none of the considered pharmaceutical physicochemical and molecular properties proved to be relevant in determining the mean attenuation rates. Instead, the octanol-water partition coefficient (Kow) influenced the variability of rates among river segments, likely due to its effect on sorption to sediments and suspended particles, and therefore influencing the balance between the different attenuation mechanisms (biotransformation, photolysis, sorption, and volatilization). The magnitude of the measured attenuation rates urges scientists to consider them as important as dilution when aiming to predict concentrations in freshwater ecosystems. Copyright © 2014 Elsevier B.V. All rights reserved.

Fate of ethanol during cooking of liquid foods prepared with alcoholic beverages: Theory and experimental studies.

PubMed

Snitkjær, Pia; Ryapushkina, Julia; Skovenborg, Erik; Astrup, Arne; Bech, Lene Mølskov; Jensen, Morten Georg; Risbo, Jens

2017-09-01

To obtain an understanding of the ethanol loss during cooking of liquid foods containing alcoholic beverages, ethanol concentration was measured as a function of time and remaining volume in meat stocks prepared with wine and beer. A mathematical model describing the decline in volatile compounds during heating of simple liquid foods was derived. The experimental results and the model show that concentration of ethanol at any given time is determined by the initial concentration and a power law function of the remaining volume fraction. The power law function is found to be independent of factors like pot dimensions and temperature. When using a lid to cover the pot during cooking, the model was still valid but the ethanol concentrations decreased more steeply, corresponding to a higher exponent. The results provide a theoretical and empirical guideline for predicting the ethanol concentration in cooked liquid foods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Contaminant transport in wetland flows with bulk degradation and bed absorption

NASA Astrophysics Data System (ADS)

Wang, Ping; Chen, G. Q.

2017-09-01

Ecological degradation and absorption are ubiquitous and exert considerable influence on the contaminant transport in natural and constructed wetland flows. It creates an increased demand on models to accurately characterize the spatial concentration distribution of the transport process. This work extends a method of spatial concentration moments by considering the non-uniform longitudinal solute displacements along the vertical direction, and analytically determines the spatial concentration distribution in the very initial stage since source release with effects of bulk degradation and bed absorption. The present method is demonstrated to bear a more accurate prediction especially in the initial stage through convergence analysis of Hermite polynomials. Results reveal that contaminant cloud shows to be more contracted and reformed by bed absorption with increasing damping factor of wetland flows. Tremendous vertical concentration variation especially in the downstream of the contaminant cloud remains great even at asymptotic large times. Spatial concentration evolution by the extended method other than the mean by previous studies is potential for various implements associated with contaminant transport with strict environmental standards.

A modeling and simulation approach to characterize methadone QT prolongation using pooled data from five clinical trials in MMT patients.

PubMed

Florian, J; Garnett, C E; Nallani, S C; Rappaport, B A; Throckmorton, D C

2012-04-01

Pharmacokinetic (PK)-pharmacodynamic modeling and simulation were used to establish a link between methadone dose, concentrations, and Fridericia rate-corrected QT (QTcF) interval prolongation, and to identify a dose that was associated with increased risk of developing torsade de pointes. A linear relationship between concentration and QTcF described the data from five clinical trials in patients on methadone maintenance treatment (MMT). A previously published population PK model adequately described the concentration-time data, and this model was used for simulation. QTcF was increased by a mean (90% confidence interval (CI)) of 17 (12, 22) ms per 1,000 ng/ml of methadone. Based on this model, doses >120 mg/day would increase the QTcF interval by >20 ms. The model predicts that 1-3% of patients would have ΔQTcF >60 ms, and 0.3-2.0% of patients would have QTcF >500 ms at doses of 160-200 mg/day. Our predictions are consistent with available observational data and support the need for electrocardiogram (ECG) monitoring and arrhythmia risk factor assessment in patients receiving methadone doses >120 mg/day.

Groundwater uranium and cancer incidence in South Carolina

PubMed Central

Wagner, Sara E.; Burch, James B.; Bottai, Matteo; Puett, Robin; Porter, Dwayne; Bolick-Aldrich, Susan; Temples, Tom; Wilkerson, Rebecca C.; Vena, John E.; Hébert, James R.

2012-01-01

Objective This ecologic study tested the hypothesis that census tracts with elevated groundwater uranium and more frequent groundwater use have increased cancer incidence. Methods Data sources included: incident total, leukemia, prostate, breast, colorectal, lung, kidney, and bladder cancers (1996–2005, SC Central Cancer Registry); demographic and groundwater use (1990 US Census); and groundwater uranium concentrations (n = 4,600, from existing federal and state databases). Kriging was used to predict average uranium concentrations within tracts. The relationship between uranium and standardized cancer incidence ratios was modeled among tracts with substantial groundwater use via linear or semiparametric regression, with and without stratification by the proportion of African Americans in each area. Results A total of 134,685 cancer cases were evaluated. Tracts with ≥50% groundwater use and uranium concentrations in the upper quartile had increased risks for colorectal, breast, kidney, prostate, and total cancer compared to referent tracts. Some of these relationships were more likely to be observed among tracts populated primarily by African Americans. Conclusion SC regions with elevated groundwater uranium and more groundwater use may have an increased incidence of certain cancers, although additional research is needed since the design precluded adjustment for race or other predictive factors at the individual level. PMID:21080052

Blood color is influenced by inflammation and independently predicts survival in hemodialysis patients: quantitative evaluation of blood color.

PubMed

Shibata, Masanori; Nagai, Kojiro; Doi, Toshio; Tawada, Hideo; Taniguchi, Shinkichi

2012-11-01

Blood color of dialysis patients can be seen routinely. Darkened blood color is often observed in critically ill patients generally because of decreased oxygen saturation, but little is known about the other factors responsible for the color intensity. In addition, quantitative blood color examination has not been performed yet. Therefore, no one has evaluated the predictive power of blood color. The aim of this study was to evaluate if blood color darkness reflects some medical problems and is associated with survival disadvantage. Study design is a prospective cohort study. One hundred sixty-seven patients were enrolled in this study. Quantification of blood color was done using a reflected light colorimeter. Demographic and clinical data were collected to find out the factors that can be related to blood color. Follow-ups were performed for 2 years to analyze the risk factors for their survival. Regression analysis showed that C-reactive protein and white blood cell count were negatively correlated with blood color. In addition, blood color was positively correlated with mean corpuscular hemoglobin concentration and serum sodium concentration as well as blood oxygen saturation. During a follow-up, 34 (20.4%) patients died. Cox regression analysis revealed that darkened blood color was an independent significant risk factor of mortality in hemodialysis patients as well as low albumin and low Kt/V. These results suggest that inflammation independently affects blood color and quantification of blood color is useful to estimate prognosis in patients undergoing hemodialysis. It is possible that early detection of blood color worsening can improve patients' survival. © 2012, Copyright the Authors. Artificial Organs © 2012, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Stress concentration factors at saddle and crown positions on the central brace of two-planar welded CHS DKT-connections

NASA Astrophysics Data System (ADS)

Ahmadi, Hamid; Lotfollahi-Yaghin, Mohammad Ali; Aminfar, Mohammad H.

2012-03-01

A set of parametric stress analyses was carried out for two-planar tubular DKT-joints under different axial loading conditions. The analysis results were used to present general remarks on the effects of the geometrical parameters on stress concentration factors (SCFs) at the inner saddle, outer saddle, and crown positions on the central brace. Based on results of finite element (FE) analysis and through nonlinear regression analysis, a new set of SCF parametric equations was established for fatigue design purposes. An assessment study of equations was conducted against the experimental data and original SCF database. The satisfaction of acceptance criteria proposed by the UK Department of Energy (UK DoE) was also checked. Results of parametric study showed that highly remarkable differences exist between the SCF values in a multi-planar DKT-joint and the corresponding SCFs in an equivalent uni-planar KT-joint having the same geometrical properties. It can be clearly concluded from this observation that using the equations proposed for uni-planar KT-connections to compute the SCFs in multi-planar DKT-joints will lead to either considerably under-predicting or over-predicting results. Hence, it is necessary to develop SCF formulae specially designed for multi-planar DKT-joints. Good results of equation assessment according to UK DoE acceptance criteria, high values of correlation coefficients, and the satisfactory agreement between the predictions of the proposed equations and the experimental data guarantee the accuracy of the equations. Therefore, the developed equations can be reliably used for fatigue design of offshore structures.

Application of XGBoost algorithm in hourly PM2.5 concentration prediction

NASA Astrophysics Data System (ADS)

Pan, Bingyue

2018-02-01

In view of prediction techniques of hourly PM2.5 concentration in China, this paper applied the XGBoost(Extreme Gradient Boosting) algorithm to predict hourly PM2.5 concentration. The monitoring data of air quality in Tianjin city was analyzed by using XGBoost algorithm. The prediction performance of the XGBoost method is evaluated by comparing observed and predicted PM2.5 concentration using three measures of forecast accuracy. The XGBoost method is also compared with the random forest algorithm, multiple linear regression, decision tree regression and support vector machines for regression models using computational results. The results demonstrate that the XGBoost algorithm outperforms other data mining methods.

Modeling Immunization To Infliximab in Children With Crohn's Disease Using Population Pharmacokinetics: A Pilot Study.

PubMed

Petitcollin, Antoine; Leuret, Oriane; Tron, Camille; Lemaitre, Florian; Verdier, Marie-Clémence; Paintaud, Gilles; Bouguen, Guillaume; Willot, Stéphanie; Bellissant, Eric; Ternant, David

2018-05-18

Antidrug antibodies (ADAs) dramatically increase infliximab clearance and are responsible for underexposure to the drug, leading to treatment failure. This pilot study aimed at developing a population pharmacokinetic model to detect and describe an early increase in infliximab clearance due to ADA. Twenty children with Crohn's disease (CD) were followed for 1 year or until treatment failure. Infliximab trough concentration, ADA, C-reactive protein (CRP), and Paediatric Crohn's Disease Activity Index (PCDAI) were recorded at each visit. A time-varying clearance population pharmacokinetic model was built to detect and describe an increase in infliximab clearance, independent from ADA testing. Factors associated with clearance variation and the relationships between infliximab concentrations, clearance variation, and clinical response were investigated. The model detected important increases in clearance in 4 patients. These patients had suboptimal early response, with higher mean PCDAI (P = 0.0086) and CRP (P = 0.028) compared with other patients. Two of them had detectable ADA. Clearance increase as described by the model and lower infliximab trough concentration at week 2 were associated with poorer outcomes in a multivariate Cox model (P = 0.001 and P = 0.0048, respectively). Being able to detect an increase in infliximab clearance, this model could allow the early detection of immunization to infliximab and therefore could help with dose adjustment in patients with CD. Moreover, the results suggest that clearance variations could be used as a predictive marker of clinical response. These findings need to be confirmed in a larger cohort, however, and predictive factors of clearance increase have to be investigated.

Uric acid as one of the important factors in multifactorial disorders – facts and controversies

PubMed Central

Pasalic, Daria; Marinkovic, Natalija; Feher-Turkovic, Lana

2012-01-01

With considering serum concentration of the uric acid in humans we are observing hyperuricemia and possible gout development. Many epidemiological studies have shown the relationship between the uric acid and different disorders such are obesity, metabolic syndrome, hypertension and coronary artery disease. Clinicians and investigators recognized serum uric acid concentration as very important diagnostic and prognostic factor of many multifactorial disorders. This review presented few clinical conditions which are not directly related to uric acid, but the concentrations of uric acid might have a great impact in observing, monitoring, prognosis and therapy of such disorders. Uric acid is recognized as a marker of oxidative stress. Production of the uric acid includes enzyme xanthine oxidase which is involved in producing of radical-oxigen species (ROS). As by-products ROS have a significant role in the increased vascular oxidative stress and might be involved in atherogenesis. Uric acid may inhibit endothelial function by inhibition of nitric oxide-function under conditions of oxidative stress. Down regulation of nitric oxide and induction of endothelial dysfunction might also be involved in pathogenesis of hypertension. The most important and well evidenced is possible predictive role of uric acid in predicting short-term outcome (mortality) in acute myocardial infarction (AMI) patients and stroke. Nephrolithiasis of uric acid origin is significantly more common among patients with the metabolic syndrome and obesity. On contrary to this, uric acid also acts is an “antioxidant”, a free radical scavenger and a chelator of transitional metal ions which are converted to poorly reactive forms. PMID:22384520

Uric acid as one of the important factors in multifactorial disorders--facts and controversies.

PubMed

Pasalic, Daria; Marinkovic, Natalija; Feher-Turkovic, Lana

2012-01-01

With considering serum concentration of the uric acid in humans we are observing hyperuricemia and possible gout development. Many epidemiological studies have shown the relationship between the uric acid and different disorders such are obesity, metabolic syndrome, hypertension and coronary artery disease. Clinicians and investigators recognized serum uric acid concentration as very important diagnostic and prognostic factor of many multifactorial disorders. This review presented few clinical conditions which are not directly related to uric acid, but the concentrations of uric acid might have a great impact in observing, monitoring, prognosis and therapy of such disorders. Uric acid is recognized as a marker of oxidative stress. Production of the uric acid includes enzyme xanthine oxidase which is involved in producing of radical-oxigen species (ROS). As by-products ROS have a significant role in the increased vascular oxidative stress and might be involved in atherogenesis. Uric acid may inhibit endothelial function by inhibition of nitric oxide-function under conditions of oxidative stress. Down regulation of nitric oxide and induction of endothelial dysfunction might also be involved in pathogenesis of hypertension. The most important and well evidenced is possible predictive role of uric acid in predicting short-term outcome (mortality) in acute myocardial infarction (AMI) patients and stroke. Nephrolithiasis of uric acid origin is significantly more common among patients with the metabolic syndrome and obesity. On contrary to this, uric acid also acts is an "antioxidant", a free radical scavenger and a chelator of transitional metal ions which are converted to poorly reactive forms.

Modifiable pathways in Alzheimer's disease: Mendelian randomisation analysis.

PubMed

Larsson, Susanna C; Traylor, Matthew; Malik, Rainer; Dichgans, Martin; Burgess, Stephen; Markus, Hugh S

2017-12-06

To determine which potentially modifiable risk factors, including socioeconomic, lifestyle/dietary, cardiometabolic, and inflammatory factors, are associated with Alzheimer's disease. Mendelian randomisation study using genetic variants associated with the modifiable risk factors as instrumental variables. International Genomics of Alzheimer's Project. 17 008 cases of Alzheimer's disease and 37 154 controls. Odds ratio of Alzheimer's per genetically predicted increase in each modifiable risk factor estimated with Mendelian randomisation analysis. This study included analyses of 24 potentially modifiable risk factors. A Bonferroni corrected threshold of P=0.002 was considered to be significant, and P<0.05 was considered suggestive of evidence for a potential association. Genetically predicted educational attainment was significantly associated with Alzheimer's. The odds ratios were 0.89 (95% confidence interval 0.84 to 0.93; P=2.4×10 -6 ) per year of education completed and 0.74 (0.63 to 0.86; P=8.0×10 -5 ) per unit increase in log odds of having completed college/university. The correlated trait intelligence had a suggestive association with Alzheimer's (per genetically predicted 1 SD higher intelligence: 0.73, 0.57 to 0.93; P=0.01). There was suggestive evidence for potential associations between genetically predicted higher quantity of smoking (per 10 cigarettes a day: 0.69, 0.49 to 0.99; P=0.04) and 25-hydroxyvitamin D concentrations (per 20% higher levels: 0.92, 0.85 to 0.98; P=0.01) and lower odds of Alzheimer's and between higher coffee consumption (per one cup a day: 1.26, 1.05 to 1.51; P=0.01) and higher odds of Alzheimer's. Genetically predicted alcohol consumption, serum folate, serum vitamin B 12 , homocysteine, cardiometabolic factors, and C reactive protein were not associated with Alzheimer's disease. These results provide support that higher educational attainment is associated with a reduced risk of Alzheimer's disease. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Predicting arsenic concentrations in groundwater of San Luis Valley, Colorado: implications for individual-level lifetime exposure assessment.

PubMed

James, Katherine A; Meliker, Jaymie R; Buttenfield, Barbara E; Byers, Tim; Zerbe, Gary O; Hokanson, John E; Marshall, Julie A

2014-08-01

Consumption of inorganic arsenic in drinking water at high levels has been associated with chronic diseases. Risk is less clear at lower levels of arsenic, in part due to difficulties in estimating exposure. Herein we characterize spatial and temporal variability of arsenic concentrations and develop models for predicting aquifer arsenic concentrations in the San Luis Valley, Colorado, an area of moderately elevated arsenic in groundwater. This study included historical water samples with total arsenic concentrations from 595 unique well locations. A longitudinal analysis established temporal stability in arsenic levels in individual wells. The mean arsenic levels for a random sample of 535 wells were incorporated into five kriging models to predict groundwater arsenic concentrations at any point in time. A separate validation dataset (n = 60 wells) was used to identify the model with strongest predictability. Findings indicate that arsenic concentrations are temporally stable (r = 0.88; 95 % CI 0.83-0.92 for samples collected from the same well 15-25 years apart) and the spatial model created using ordinary kriging best predicted arsenic concentrations (ρ = 0.72 between predicted and observed validation data). These findings illustrate the value of geostatistical modeling of arsenic and suggest the San Luis Valley is a good region for conducting epidemiologic studies of groundwater metals because of the ability to accurately predict variation in groundwater arsenic concentrations.

Prediction of Particle Concentration using Traffic Emission Model

NASA Astrophysics Data System (ADS)

He, Hong-di; Lu, Jane Wei-zhen

2010-05-01

Vehicle emission is regarded as one of major sources of air pollution in urban area. Much attention has been addressed on it especially at traffic intersection. At intersection, vehicles frequently stop with idling engine during the red time and speed-up rapidly in the green time, which result in a high velocity fluctuation and produce extra pollutants to the surrounding air. To deeply understand such process, a semi-empirical model for predicting the changing effect of traffic flow patterns on particulate concentrations is proposed. The performance of the model is evaluated using the correlation coefficient and other parameters. From the results, the correlation coefficients in morning and afternoon data were found to be 0.86 an 0.73 respectively, which implies that the semi-empirical model for morning and afternoon data are 86% and 73% error free. Due to less affected by possible factors such as traffic volume and movement of pedestrian, the dispersion of the particulate matter in the morning is smaller and then contributes to higher performance than that in the afternoon.

Spatial representation of organic carbon and active-layer thickness of high latitude soils in CMIP5 earth system models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mishra, Umakant; Drewniak, Beth; Jastrow, Julie D.

Soil properties such as soil organic carbon (SOC) stocks and active-layer thickness are used in earth system models (F.SMs) to predict anthropogenic and climatic impacts on soil carbon dynamics, future changes in atmospheric greenhouse gas concentrations, and associated climate changes in the permafrost regions. Accurate representation of spatial and vertical distribution of these soil properties in ESMs is a prerequisite for redudng existing uncertainty in predicting carbon-climate feedbacks. We compared the spatial representation of SOC stocks and active-layer thicknesses predicted by the coupled Modellntercomparison Project Phase 5 { CMIP5) ESMs with those predicted from geospatial predictions, based on observation datamore » for the state of Alaska, USA. For the geospatial modeling. we used soil profile observations {585 for SOC stocks and 153 for active-layer thickness) and environmental variables (climate, topography, land cover, and surficial geology types) and generated fine-resolution (50-m spatial resolution) predictions of SOC stocks (to 1-m depth) and active-layer thickness across Alaska. We found large inter-quartile range (2.5-5.5 m) in predicted active-layer thickness of CMIP5 modeled results and small inter-quartile range (11.5-22 kg m-2) in predicted SOC stocks. The spatial coefficient of variability of active-layer thickness and SOC stocks were lower in CMIP5 predictions compared to our geospatial estimates when gridded at similar spatial resolutions (24.7 compared to 30% and 29 compared to 38%, respectively). However, prediction errors. when calculated for independent validation sites, were several times larger in ESM predictions compared to geospatial predictions. Primaly factors leading to observed differences were ( 1) lack of spatial heterogeneity in ESM predictions, (2) differences in assumptions concerning environmental controls, and (3) the absence of pedogenic processes in ESM model structures. Our results suggest that efforts to incorporate these factors in F.SMs should reduce current uncertainties associated with ESM predictions of carbon-climate feedbacks.« less

Serum Brain-Derived Neurotrophic Factor is Related to Platelet Reactivity but not to Genetic Polymorphisms within BDNF Encoding Gene in Patients with Type 2 Diabetes.

PubMed

Eyileten, Ceren; Zaremba, Małgorzata; Janicki, Piotr K; Rosiak, Marek; Cudna, Agnieszka; Kapłon-Cieślicka, Agnieszka; Opolski, Grzegorz; Filipiak, Krzysztof J; Kosior, Dariusz A; Mirowska-Guzel, Dagmara; Postula, Marek

2016-01-07

The aim of this study was to investigate the association between serum concentrations of the brain-derived neurotrophic factor (BDNF), platelet reactivity and inflammatory markers, as well as its association with BDNF encoding gene variants in type 2 diabetic patients (T2DM) during acetylsalicylic acid (ASA) therapy. This retrospective, open-label study enrolled 91 patients. Serum BDNF, genotype variants, hematological, biochemical, and inflammatory markers were measured. Blood samples were taken in the morning 2-3 h after the last ASA dose. The BDNF genotypes for selected variants were analyzed by use of the iPLEX Sequenom assay. In multivariate linear regression analysis, CADP-CT >74 sec (p<0.001) and sP-selectin concentration (p=0.03) were predictive of high serum BDNF. In multivariate logistic regression analysis, CADP-CT >74 sec (p=0.02) and IL-6 concentration (p=0.03) were risk factors for serum BDNF above the median. Non-significant differences were observed between intronic SNP rs925946, missense SNP rs6265, and intronic SNP rs4923463 allelic groups and BDNF concentrations in the investigated cohort. Chronic inflammatory condition and enhanced immune system are associated with the production of BDNF, which may be why the serum BDNF level in T2DM patients with high platelet reactivity was higher compared to subjects with normal platelet reactivity in this study.

Toxicity and bioaccumulation of a mixture of heavy metals in Chironomus tentans (Diptera: Chironomidae) in synthetic sediment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harrahy, E.A.; Clements, W.H.

1997-02-01

This research investigated toxicity and bioaccumulation of a mixture of Cd, Cu, Pb, and Zn in Chironomus tentans in synthetic sediment, and compared predicted to measured steady-state bioaccumulation factors (BAFs). In a toxicity test, C. tentans were exposed to various dilutions of a base concentration (1.0 X) of a mixture of the four metals (5 {micro}g/g Cd. 10 {micro}g/g Cu. 70 {micro}g/g Pb, and 300 {micro}g/g Zn) in synthetic sediment. Mortality ranged from 17 to 100%. To measure bioaccumulation of the metals, C. tentans were exposed to 0.35 X the base concentration for a period of up to 14 dmore » in two uptake tests. Bioaccumulation of all four metals increased over the 14-d uptake phases. Concentrations of metals in chironomids were significantly correlated with exposure time in the uptake phases. Only concentrations of copper approached background levels after 7 d depuration. Uptake rate coefficients and elimination rate constants were determined for each metal. Bioaccumulation factors were highest for Cd and lowest for Pb. With the exception of Pb, steady-state BAFs were within a factor of about two of those calculated using the first-order kinetic model. The high BAFs calculated may indicate greater bioavailability in synthetic sediment. Studies comparing toxicity and bioaccumulation of natural and synthetic sediments are necessary before the use of synthetic sediments is widely adopted.« less

Pretransplant soluble CD30 serum concentration does not affect kidney graft outcomes 3 years after transplantation.

PubMed

Kovač, J; Arnol, M; Vidan Jeras, B; Bren, A F; Kandus, A

2010-12-01

An elevated serum concentration of soluble the form of CD30 (sCD30), an activation marker of mainly T(H)2-type cytokines producing T lymphocytes, has been reported as a predictive factor for acute cellular rejection episodes and poor graft outcomes in kidney transplantation. This historic cohort study investigated the association of a pretransplant sCD30 serum concentrations with kidney graft function and graft survival 3 years posttransplantation in adult recipients of deceased donor kidney grafts, treated with monoclonal anti-CD25 antibodies as an induction treatment combined with a cyclosporine (CsA)-based maintenance triple therapy. The pretransplant sera of 296 recipients were tested for sCD30 content using a microsphere flow-cytometry assay. The estimated glomerular filtration rate (eGFR) was determined by the 4-variable Modification of Diet in Renal Disease equation. The incidences of graft loss were calculated with the use of Kaplan-Meier survival analysis and compared using the log-rank test. According to the distribution of the pretransplant sCD30 levels concentration ≥2700 pg/mL was defined as high (n = 146) and concentration <2700 pg/mL as low (n = 150). Three years posttransplantation, the eGFR was not significantly different in the recipients in high and low sCD30 groups (65 ± 24 vs 67 ± 21 mL/min/1.73 m(2); P = .43); there was no association between the eGFR 3 years after transplantation and the pretransplant sCD30 levels (r(2) = 0.002; P = .49). Graft survival 3 years after transplantation was also not different in the recipients in high and low sCD30 groups (P = .52). In our adult deceased-donor kidney graft recipients, the pretransplant sCD30 serum concentration was not a predictive factor of immunologic risk associated with the kidney graft function 3 years posttransplantation; neither did it affect graft survival 3 years after transplantation. The immunosuppression with anti-CD25 antibodies as an induction treatment combined with the CsA-based maintenance triple therapy could possibly be decisive for our findings. Copyright © 2010 Elsevier Inc. All rights reserved.

Multimethod prediction of child abuse risk in an at-risk sample of male intimate partner violence offenders.

PubMed

Rodriguez, Christina M; Gracia, Enrique; Lila, Marisol

2016-10-01

The vast majority of research on child abuse potential has concentrated on women demonstrating varying levels of risk of perpetrating physical child abuse. In contrast, the current study considered factors predictive of physical child abuse potential in a group of 70 male intimate partner violence offenders, a group that would represent a likely high risk group. Elements of Social Information Processing theory were evaluated, including pre-existing schemas of empathy, anger, and attitudes approving of parent-child aggression considered as potential moderators of negative attributions of child behavior. To lend methodological rigor, the study also utilized multiple measures and multiple methods, including analog tasks, to predict child abuse risk. Contrary to expectations, findings did not support the role of anger independently predicting child abuse risk in this sample of men. However, preexisting beliefs approving of parent-child aggression, lower empathy, and more negative child behavior attributions independently predicted abuse potential; in addition, greater anger, poorer empathy, and more favorable attitudes toward parent-child aggression also exacerbated men's negative child attributions to further elevate their child abuse risk. Future work is encouraged to consider how factors commonly considered in women parallel or diverge from those observed to elevate child abuse risk in men of varying levels of risk. Copyright © 2016 Elsevier Ltd. All rights reserved.

Predicting the influence of liposomal lipid composition on liposome size, zeta potential and liposome-induced dendritic cell maturation using a design of experiments approach.

PubMed

Soema, Peter C; Willems, Geert-Jan; Jiskoot, Wim; Amorij, Jean-Pierre; Kersten, Gideon F

2015-08-01

In this study, the effect of liposomal lipid composition on the physicochemical characteristics and adjuvanticity of liposomes was investigated. Using a design of experiments (DoE) approach, peptide-containing liposomes containing various lipids (EPC, DOPE, DOTAP and DC-Chol) and peptide concentrations were formulated. Liposome size and zeta potential were determined for each formulation. Moreover, the adjuvanticity of the liposomes was assessed in an in vitro dendritic cell (DC) model, by quantifying the expression of DC maturation markers CD40, CD80, CD83 and CD86. The acquired data of these liposome characteristics were successfully fitted with regression models, and response contour plots were generated for each response factor. These models were applied to predict a lipid composition that resulted in a liposome with a target zeta potential. Subsequently, the expression of the DC maturation factors for this lipid composition was predicted and tested in vitro; the acquired maturation responses corresponded well with the predicted ones. These results show that a DoE approach can be used to screen various lipids and lipid compositions, and to predict their impact on liposome size, charge and adjuvanticity. Using such an approach may accelerate the formulation development of liposomal vaccine adjuvants. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Genetics and risk factors for basal cell carcinoma.

PubMed

Madan, V; Hoban, P; Strange, R C; Fryer, A A; Lear, J T

2006-05-01

Nonmelanoma skin cancer (NMSC) is the commonest cancer in whites and its incidence is increasing worldwide. The prevalence of this cancer is predicted to equal that of all others combined and it was estimated that there were over 2 million cases diagnosed in the U.S.A. in 2004. Patients exhibit marked differences in clinical phenotype with variations in tumour numbers, rate of tumour accrual, site and histological subtype. Furthermore, patients are at increased risk of other cutaneous and noncutaneous cancers. The factors accounting for this variation are complex and still not completely understood. Clearly, ultraviolet light (UV) exposure is a major influence but its relationship to clinical phenotype is not yet clear. In addition, immunosuppression is a significant risk factor. Our group has identified high-risk groups for the development of further basal cell carcinoma (BCC), namely patients with truncal BCC and those presenting with tumour clusters. This presentation will concentrate on these clinical subgroups as well as immunosuppressed patients. These groups represent significant management challenges and are areas where novel, nonsurgical treatment options may make a significant clinical impact in patient care. The risk factors predisposing to these clinical phenotypes will be discussed, including genetic factors and UV exposure. Potential clinical applications, including predictive indices, will be considered.

A simple phenomenological model for grain clustering in turbulence

NASA Astrophysics Data System (ADS)

Hopkins, Philip F.

2016-01-01

We propose a simple model for density fluctuations of aerodynamic grains, embedded in a turbulent, gravitating gas disc. The model combines a calculation for the behaviour of a group of grains encountering a single turbulent eddy, with a hierarchical approximation of the eddy statistics. This makes analytic predictions for a range of quantities including: distributions of grain densities, power spectra and correlation functions of fluctuations, and maximum grain densities reached. We predict how these scale as a function of grain drag time ts, spatial scale, grain-to-gas mass ratio tilde{ρ }, strength of turbulence α, and detailed disc properties. We test these against numerical simulations with various turbulence-driving mechanisms. The simulations agree well with the predictions, spanning ts Ω ˜ 10-4-10, tilde{ρ }˜ 0{-}3, α ˜ 10-10-10-2. Results from `turbulent concentration' simulations and laboratory experiments are also predicted as a special case. Vortices on a wide range of scales disperse and concentrate grains hierarchically. For small grains this is most efficient in eddies with turnover time comparable to the stopping time, but fluctuations are also damped by local gas-grain drift. For large grains, shear and gravity lead to a much broader range of eddy scales driving fluctuations, with most power on the largest scales. The grain density distribution has a log-Poisson shape, with fluctuations for large grains up to factors ≳1000. We provide simple analytic expressions for the predictions, and discuss implications for planetesimal formation, grain growth, and the structure of turbulence.

Ratio of urine and blood urea nitrogen concentration predicts the response of tolvaptan in congestive heart failure.

PubMed

Shimizu, Keisuke; Doi, Kent; Imamura, Teruhiko; Noiri, Eisei; Yahagi, Naoki; Nangaku, Masaomi; Kinugawa, Koichiro

2015-06-01

This study was conducted to evaluate the performance of the ratio of urine and blood urea nitrogen concentration (UUN/BUN) as a new predictive factor for the response of an arginine vasopressin receptor 2 antagonist tolvaptan (TLV) in decompensated heart failure patients. This study enrolled 70 decompensated heart failure patients who were administered TLV at University of Tokyo Hospital. We collected the data of clinical parameters including UUN/BUN before administering TLV. Two different outcomes were defined as follows: having over 300 mL increase in urine volume on the first day (immediate urine output response) and having any decrease in body weight within one week after starting TLV treatment (subsequent clinical response). Among the 70 enrolled patients, 37 patients (52.9%) showed immediate urine output response; 51 patients (72.9%) showed a subsequent clinical response of body weight decrease. Receiver operating characteristics (ROC) analysis showed good prediction by UUN/BUN for the immediate response (AUC-ROC 0.86 [0.75-0.93]) and a significantly better prediction by UUN/BUN for the subsequent clinical response compared with urinary osmolality (AUC-ROC 0.78 [0.63-0.88] vs. 0.68 [0.52-0.80], P < 0.05). We demonstrated that a clinical parameter of UUN/BUN can predict the response of TLV even when measured before TLV administration. UUN/BUN might enable identification of good responders for this new drug. © 2015 Asian Pacific Society of Nephrology.

Predicting the toxicity of sediment-associated trace metals with simultaneously extracted trace metal: Acid-volatile sulfide concentrations and dry weight-normalized concentrations: A critical comparison

USGS Publications Warehouse

Long, E.R.; MacDonald, D.D.; Cubbage, J.C.; Ingersoll, C.G.

1998-01-01

The relative abilities of sediment concentrations of simultaneously extracted trace metal: acid-volatile sulfide (SEM: AVS) and dry weight-normalized trace metals to correctly predict both toxicity and nontoxicity were compared by analysis of 77 field-collected samples. Relative to the SEM:AVS concentrations, sediment guidelines based upon dry weight-normalized concentrations were equally or slightly more accurate in predicting both nontoxic and toxic results in laboratory tests.

Response surface optimization of the critical medium components for pullulan production by Aureobasidium pullulans FB-1.

PubMed

Singh, Ram Sarup; Singh, Harpreet; Saini, Gaganpreet Kaur

2009-01-01

Culture conditions for pullulan production by Aureobasidium pullulans were optimized using response surface methodology at shake flask level without pH control. In the present investigation, a five-level with five-factor central composite rotatable design of experiments was employed to optimize the levels of five factors significantly affecting the pullulan production, biomass production, and sugar utilization in submerged cultivation. The selected factors included concentration of sucrose, ammonium sulphate, yeast extract, dipotassium hydrogen phosphate, and sodium chloride. Using this methodology, the optimal values for concentration of sucrose, ammonium sulphate, yeast extract, dipotassium hydrogen phosphate, and sodium chloride were 5.31%, 0.11%, 0.07%, 0.05%, and 0.15% (w/v), respectively. This optimized medium has projected a theoretically production of pullulan of 4.44%, biomass yield of 1.03%, and sugar utilization of 97.12%. The multiple correlation coefficient 'R' was 0.9976, 0.9761 and 0.9919 for pullulan production, biomass production, and sugar utilization, respectively. The value of R being very close to one justifies an excellent correlation between the predicted and the experimental data.

Groundwater Vulnerability Assessment of the Pingtung Plain in Southern Taiwan.

PubMed

Liang, Ching-Ping; Jang, Cheng-Shin; Liang, Cheng-Wei; Chen, Jui-Sheng

2016-11-23

In the Pingtung Plain of southern Taiwan, elevated levels of NO₃ - -N in groundwater have been reported. Therefore, efforts for assessing groundwater vulnerability are required as part of the critical steps to prevent and control groundwater pollution. This study makes a groundwater vulnerability assessment for the Pingtung Plain using an improved overlay and index-based DRASTIC model. The improvement of the DRASTIC model is achieved by reassigning the weighting coefficients of the factors in this model with the help of a discriminant analysis statistical method. The analytical results obtained from the improved DRASTIC model provide a reliable prediction for use in groundwater vulnerability assessment to nitrate pollution and can correctly identify the groundwater protection zones in the Pingtung Plain. Moreover, the results of the sensitivity analysis conducted for the seven parameters in the improved DRASTIC model demonstrate that the aquifer media (A) is the most sensitive factor when the nitrate-N concentration is below 2.5 mg/L. For the cases where the nitrate-N concentration is above 2.5 mg/L, the aquifer media (A) and net recharge (R) are the two most important factors.

Modeling of rotating disc contactor (RDC) column

NASA Astrophysics Data System (ADS)

Ismail, Wan Nurul Aiffah; Zakaria, Siti Aisyah; Noor, Nor Fashihah Mohd; Sulong, Ibrahim; Arshad, Khairil Anuar

2014-12-01

Liquid-liquid extraction is one of the most important separation processes. Different kinds of liquid-liquid extractor such as Rotating Disc Contactor (RDC) Column being used in industries. The study of liquid-liquid extraction in an RDC column has become a very important subject to be discussed not just among chemical engineers but mathematician as well. In this research, the modeling of small diameter RDC column using the chemical system involving cumene/isobutryric asid/water are analyzed by the method of Artificial Neural Network (ANN). In the previous research, we begin the process of analyzed the data using methods of design of the experiments (DOE) to identify which factor and their interaction factor are significant and to determine the percentage of contribution of the variance for each factor. From the result obtained, we continue the research by discussed the development and validation of an artificial neural network model in estimating the concentration of continuous and concentration of dispersed outlet for an RDC column. It is expected that an efficient and reliable model will be formed to predict RDC column performance as an alternative to speed up the simulation process.

Positive matrix factorization and trajectory modelling for source identification: A new look at Indian Ocean Experiment ship observations

NASA Astrophysics Data System (ADS)

Bhanuprasad, S. G.; Venkataraman, Chandra; Bhushan, Mani

The sources of aerosols on a regional scale over India have only recently received attention in studies using back trajectory analysis and chemical transport modelling. Receptor modelling approaches such as positive matrix factorization (PMF) and the potential source contribution function (PSCF) are effective tools in source identification of urban and regional-scale pollution. In this work, PMF and PSCF analysis is applied to identify categories and locations of sources that influenced surface concentrations of aerosols in the Indian Ocean Experiment (INDOEX) domain measured on-board the research vessel Ron Brown [Quinn, P.K., Coffman, D.J., Bates, T.S., Miller, T.L., Johnson, J.E., Welton, E.J., et al., 2002. Aerosol optical properties during INDOEX 1999: means, variability, and controlling factors. Journal of Geophysical Research 107, 8020, doi:10.1029/2000JD000037]. Emissions inventory information is used to identify sources co-located with probable source regions from PSCF. PMF analysis identified six factors influencing PM concentrations during the INDOEX cruise of the Ron Brown including a biomass combustion factor (35-40%), three industrial emissions factors (35-40%), primarily secondary sulphate-nitrate, balance trace elements and Zn, and two dust factors (20-30%) of Si- and Ca-dust. The identified factors effectively predict the measured submicron PM concentrations (slope of regression line=0.90±0.20; R2=0.76). Probable source regions shifted based on changes in surface and elevated flows during different times in the ship cruise. They were in India in the early part of the cruise, but in west Asia, south-east Asia and Africa, during later parts of the cruise. Co-located sources include coal-fired electric utilities, cement, metals and petroleum production in India and west Asia, biofuel combustion for energy and crop residue burning in India, woodland/forest burning in north sub-Saharan Africa and forest burning in south-east Asia. Significant findings are equivalent contributions of biomass combustion and industrial emissions to the measured aerosol surface concentrations, the origin of carbonaceous aerosols largely from biomass combustion and the identification of probable source regions in Africa, west Asia, the Arabian peninsula and south-east Asia, in addition to India, which affected particulate matter concentrations over parts of the INDOEX domain covered by the Ron Brown cruise.

A COMPARISON OF WINTER SHORT-TERM AND ANNUAL AVERAGE RADON MEASUREMENTS IN BASEMENTS OF A RADON-PRONE REGION AND EVALUATION OF FURTHER RADON TESTING INDICATORS

PubMed Central

Barros, Nirmalla G.; Steck, Daniel J.; Field, R. William

2014-01-01

The primary objective of this study was to investigate the temporal variability between basement winter short-term (7 to 10 days) and basement annual radon measurements. Other objectives were to test the short-term measurement’s diagnostic performance at two reference levels and to evaluate its ability to predict annual average basement radon concentrations. Electret ion chamber (short-term) and alpha track (annual) radon measurements were obtained by trained personnel in Iowa residences. Overall, the geometric mean of the short-term radon concentrations (199 Bq m−3) was slightly greater than the geometric mean of the annual radon concentrations (181 Bq m−3). Short-term tests incorrectly predicted that the basement annual radon concentrations would be below 148 Bq m−3 12% of the time and 2% of the time at 74 Bq m−3. The short-term and annual radon concentrations were strongly correlated (r=0.87, p<0.0001). The foundation wall material of the basement was the only significant factor to have an impact on the absolute difference between the short-term and annual measurements. The findings from this study provide evidence of a substantially lower likelihood of obtaining a false negative result from a single short-term test in a region with high indoor radon potential when the reference level is lowered to 74 Bq m−3. PMID:24670901

Moss bags as sentinels for human safety in mercury-polluted groundwaters.

PubMed

Cesa, Mattia; Nimis, Pier Luigi; Buora, Clara; Lorenzonetto, Alberta; Pozzobon, Alessandro; Raris, Marina; Rosa, Maria; Salvadori, Michela

2014-05-01

An equation to estimate Hg concentrations of <4 μg/L in groundwaters of a polluted area in NE Italy was set out by using transplants of the aquatic moss Rhynchostegium riparioides as trace element bioaccumulators. The equation is derived from a previous mathematical model which was implemented under laboratory conditions. The work aimed at (1) checking the compliance of the uptake kinetics with the model, (2) improving/adapting the model for groundwater monitoring, (3) comparing the performances of two populations of moss collected from different sites, and (4) assessing the environmental impact of Hg contamination on a small river. The main factors affecting Hg uptake in the field were-as expected-water concentration and time of exposure, even though the uptake kinetics in the field were slightly different from those which were previously observed in the lab, since the redox environmental conditions influence the solubility of cationic Fe, which is a negative competitor of Hg(2+). The equation was improved by including the variable 'dissolved oxygen concentration'. A numerical parameter depending on the moss collection site was also provided, since the differences in uptake efficiency were observed between the two populations tested. Predicted Hg concentrations well fitted the values measured in situ (approximately ±50%), while a notable underestimation was observed when the equation was used to predict Hg concentration in a neighbouring river (-96%), probably due to the organic pollution which hampers metal uptake by mosses.

Body map of regional vs. whole body sweating rate and sweat electrolyte concentrations in men and women during moderate exercise-heat stress.

PubMed

Baker, Lindsay B; Ungaro, Corey T; Sopeña, Bridget C; Nuccio, Ryan P; Reimel, Adam J; Carter, James M; Stofan, John R; Barnes, Kelly A

2018-05-01

This study determined the relations between regional (REG) and whole body (WB) sweating rate (RSR and WBSR, respectively) as well as REG and WB sweat Na + concentration ([Na + ]) during exercise. Twenty-six recreational athletes (17 men, 9 women) cycled for 90 min while WB sweat [Na + ] was measured using the washdown technique. RSR and REG sweat [Na + ] were measured from nine regions using absorbent patches. RSR and REG sweat [Na + ] from all regions were significantly ( P < 0.05) correlated with WBSR ( r = 0.58-0.83) and WB sweat [Na + ] ( r = 0.74-0.88), respectively. However, the slope and y-intercept of the regression lines for most models were significantly different than 1 and 0, respectively. The coefficients of determination ( r 2 ) were 0.44-0.69 for RSR predicting WBSR [best predictors: dorsal forearm ( r 2  = 0.62) and triceps ( r 2  = 0.69)] and 0.55-0.77 for REG predicting WB sweat [Na + ] [best predictors: ventral forearm ( r 2  = 0.73) and thigh ( r 2  = 0.77)]. There was a significant ( P < 0.05) effect of day-to-day variability on the regression model predicting WBSR from RSR at most regions but no effect on predictions of WB sweat [Na + ] from REG. Results suggest that REG cannot be used as a direct surrogate for WB sweating responses. Nonetheless, the use of regression equations to predict WB sweat [Na + ] from REG can provide an estimation of WB sweat [Na + ] with an acceptable level of accuracy, especially using the forearm or thigh. However, the best practice for measuring WBSR remains conventional WB mass balance calculations since prediction of WBSR from RSR using absorbent patches does not meet the accuracy or reliability required to inform fluid intake recommendations. NEW & NOTEWORTHY This study developed a body map of regional sweating rate and regional (REG) sweat electrolyte concentrations and determined the effect of within-subject (bilateral and day-to-day) and between-subject (sex) factors on the relations between REG and the whole body (WB). Regression equations can be used to predict WB sweat Na + concentration from REG, especially using the forearm or thigh. However, prediction of WB sweating rate from REG sweating rate using absorbent patches does not reach the accuracy or reliability required to inform fluid intake recommendations.

Predicting the Activity Coefficients of Free-Solvent for Concentrated Globular Protein Solutions Using Independently Determined Physical Parameters

PubMed Central

McBride, Devin W.; Rodgers, Victor G. J.

2013-01-01

The activity coefficient is largely considered an empirical parameter that was traditionally introduced to correct the non-ideality observed in thermodynamic systems such as osmotic pressure. Here, the activity coefficient of free-solvent is related to physically realistic parameters and a mathematical expression is developed to directly predict the activity coefficients of free-solvent, for aqueous protein solutions up to near-saturation concentrations. The model is based on the free-solvent model, which has previously been shown to provide excellent prediction of the osmotic pressure of concentrated and crowded globular proteins in aqueous solutions up to near-saturation concentrations. Thus, this model uses only the independently determined, physically realizable quantities: mole fraction, solvent accessible surface area, and ion binding, in its prediction. Predictions are presented for the activity coefficients of free-solvent for near-saturated protein solutions containing either bovine serum albumin or hemoglobin. As a verification step, the predictability of the model for the activity coefficient of sucrose solutions was evaluated. The predicted activity coefficients of free-solvent are compared to the calculated activity coefficients of free-solvent based on osmotic pressure data. It is observed that the predicted activity coefficients are increasingly dependent on the solute-solvent parameters as the protein concentration increases to near-saturation concentrations. PMID:24324733

Evaluating the spatial variation of total mercury in young-of-year yellow perch (Perca flavescens), surface water and upland soil for watershed-lake systems within the southern Boreal Shield

USGS Publications Warehouse

Gabriel, M.C.; Kolka, R.; Wickman, T.; Nater, E.; Woodruff, Laurel G.

2009-01-01

The primary objective of this research is to investigate relationships between mercury in upland soil, lake water and fish tissue and explore the cause for the observed spatial variation of THg in age one yellow perch (Perca flavescens) for ten lakes within the Superior National Forest. Spatial relationships between yellow perch THg tissue concentration and a total of 45 watershed and water chemistry parameters were evaluated for two separate years: 2005 and 2006. Results show agreement with other studies where watershed area, lake water pH, nutrient levels (specifically dissolved NO3−-N) and dissolved iron are important factors controlling and/or predicting fish THg level. Exceeding all was the strong dependence of yellow perch THg level on soil A-horizon THg and, in particular, soil O-horizon THg concentrations (Spearman ρ = 0.81). Soil B-horizon THg concentration was significantly correlated (Pearson r = 0.75) with lake water THg concentration. Lakes surrounded by a greater percentage of shrub wetlands (peatlands) had higher fish tissue THg levels, thus it is highly possible that these wetlands are main locations for mercury methylation. Stepwise regression was used to develop empirical models for the purpose of predicting the spatial variation in yellow perch THg over the studied region. The 2005 regression model demonstrates it is possible to obtain good prediction (up to 60% variance description) of resident yellow perch THg level using upland soil O-horizon THg as the only independent variable. The 2006 model shows even greater prediction (r2 = 0.73, with an overall 10 ng/g [tissue, wet weight] margin of error), using lake water dissolved iron and watershed area as the only model independent variables. The developed regression models in this study can help with interpreting THg concentrations in low trophic level fish species for untested lakes of the greater Superior National Forest and surrounding Boreal ecosystem.

Structural and Predictive Properties of the Emotional Quotient Inventory Youth Version-Short Form (EQ-i:YV[S]).

PubMed

Davis, Sarah K; Wigelsworth, Michael

2018-01-01

Emotional intelligence (EI) is a popular construct with concentrated areas of application in education and health contexts. There is a need for reliable and valid measurement of EI in young people, with brief yet sensitive measures of the construct preferable for use in time-limited settings. However, the proliferation of EI measures has often outpaced rigorous psychometric evaluation (Gignac, 2009 ). Using data from 849 adolescents (407 females, 422 males) aged 11 to 16 years (M age 13.4, SD = 1.2 years), this article systematically examines the structural and predictive properties of a frequently employed measure of adolescent trait EI-the Emotional Quotient Inventory Youth Version-Short Form (EQ-i:YV[S]); Bar-On & Parker, 2000 ). Although the intended multidimensional factor structure was recovered through confirmatory factor analysis, the statistical and conceptual coherency of the underlying model was inadequate. Using a multitrait-multimethod approach, the EQ-i:YV(S) was found to converge with other measures of EI; however, evidence for divergent validity (Big Five personality dimensions) was less robust. Predictive utility for adolescent mental health outcomes (depression, disruptive behavior) was also limited. Findings suggest that use of the EQ-i:YV(S) for predictive or evaluative purposes should be avoided until refinements to the scale are made.

Effect of diet composition and incubation time on feed indigestible neutral detergent fiber concentration in dairy cows.

PubMed

Krizsan, S J; Huhtanen, P

2013-03-01

Indigestible neutral detergent fiber (NDF) predicts forage digestibility accurately and precisely when determined by a 288-h ruminal in situ incubation, and it is an important parameter in mechanistic rumen models. The long incubation time required is a disadvantage. Further, intrinsic cell wall characteristics of feeds should be determined under ideal conditions for fiber digestion. The objective of this study was to determine the effects of diet composition and rumen incubation time on the concentrations of indigestible NDF (iNDF) for a wide range of feeds in dairy cows. Additionally, predicted concentrations of unavailable NDF generated using the National Research Council (NRC) model and the Cornell Net Carbohydrate and Protein System (CNCPS) were evaluated. Indigestible NDF was evaluated in 18 feeds using 4 cows in a split-split plot design. Treatments were in a 3 × 3 factorial arrangement, consisting of different diets and incubation times. Diet composition was primarily varied by changing the level of concentrate supplementation between 190 (low), 421 (medium), and 625 (high)g/kg of diet dry matter (DM). Grass silage was used as the basal forage for all cows. The feeds were incubated for 144, 216, and 288 h. Indigestible NDF was determined from 2-g samples weighed into polyester bags with a pore size of 12 µm and a pore area equal to 6% of the total surface area, giving a sample size to surface ratio of 10mg/cm(2). Across all feeds, the measured iNDF concentrations ranged from 6 to 516 g/kg of DM. The feed iNDF concentration was not affected by the cow used, but diet composition had a significant effect. The mean measured iNDF concentrations for cows consuming low-, medium-, and high-concentrate diets were 178, 186, and 197 g/kg of DM, respectively. The incubation time also affected the feed iNDF concentrations, which averaged 199, 185, and 177 g/kg of DM for 144-, 216-, and 288-h incubations, respectively. We also observed significant interactions between incubation time and feed, and between diet composition and feed, with fiber-rich feeds being most sensitive to these factors. The evaluation of model predictions of unavailable NDF indicated poor precision with prediction errors of 56 (NRC) and 84 (CNCPS)g/kg of DM. Indigestible NDF should be determined based on 288-h ruminal in situ incubations in cows consuming diets with a low proportion of concentrate to represent the feed fraction that is unavailable to the animal. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Predictive model for convective flows induced by surface reactivity contrast

NASA Astrophysics Data System (ADS)

Davidson, Scott M.; Lammertink, Rob G. H.; Mani, Ali

2018-05-01

Concentration gradients in a fluid adjacent to a reactive surface due to contrast in surface reactivity generate convective flows. These flows result from contributions by electro- and diffusio-osmotic phenomena. In this study, we have analyzed reactive patterns that release and consume protons, analogous to bimetallic catalytic conversion of peroxide. Similar systems have typically been studied using either scaling analysis to predict trends or costly numerical simulation. Here, we present a simple analytical model, bridging the gap in quantitative understanding between scaling relations and simulations, to predict the induced potentials and consequent velocities in such systems without the use of any fitting parameters. Our model is tested against direct numerical solutions to the coupled Poisson, Nernst-Planck, and Stokes equations. Predicted slip velocities from the model and simulations agree to within a factor of ≈2 over a multiple order-of-magnitude change in the input parameters. Our analysis can be used to predict enhancement of mass transport and the resulting impact on overall catalytic conversion, and is also applicable to predicting the speed of catalytic nanomotors.

Selenium and sulfur relationships in alfalfa and soil under field conditions, San Joaquin Valley, California

USGS Publications Warehouse

Severson, R.C.; Gough, L.P.

1992-01-01

Relationships between total Se and S or soluble SeO4 and SO4 in soils and tissue concentrations in alfalfa (Medicago sativa L.), under field conditions in the San Joaquin Valley of California, suggest that the rate of accumulation of Se in alfalfa may be reduced in areas where high Se and S concentrations in soils were measured. These data suggest that the balance between carbonate and sulfate minerals in soil may have a greater influence on uptake of Se by alfalfa than does the balance of SeO4 and SO4 in soil solution. Soil and alfalfa were sampled from areas representing a wide range in soil Se and S concentrations. Specific sampling locations were selected based on a previous study of Se, S, and other elements where 721 soil samples were collected to map landscape variability and distribution of elements. Six multiple-linear regression equations were developed between total and/or soluble soil chemical constituents and tissue concentrations of Se in alfalfa. We chose a regression model that accounted for 72% of the variability in alfalfa Se concentrations based on an association of elements in soil (total C, S, Se, and Sr) determined by factor analysis. To prepare a map showing the spatial distribution of estimated alfalfa Se concentrations, the model was applied to the data from the previously collected 721 soil samples. Estimated alfalfa Se concentrations in most of the study area were within a range that is predicted to produce alfalfa with neither Se deficiency nor toxicity when consumed by livestock. A few small areas are predicted to produce alfalfa that potentially would not meet minimum dietary needs of livestock.

Planetesimal Formation in the Protoplanetary Nebula

NASA Technical Reports Server (NTRS)

Cuzzi, Jeffrey N.; Mrad, Susan (Technical Monitor)

1998-01-01

In this talk we will address two distinct phases of planetesimal formation, each of which is fundamentally dependent upon the coupled interactions of particles and turbulent nebula gas. It has been shown both numerically and experimentally that 3-D (three dimensional) turbulence concentrates aerodynamically size-selected particles by orders of magnitude. In a previous review chapter we illustrated the initial predictions of Turbulent Concentration (TC) as applied to the solar nebula. We predicted the particle size which will be most effectively concentrated by turbulence; it is the particle which has a gas drag stopping time equal to the overturn time of the smallest (Kolmogorov scale) eddy. The primary uncertainty is the level of nebula turbulence, or Reynolds number Re, which can be expressed in terms of the standard nebula eddy viscosity parameter alpha = Rev(sub m)/cH, where v(sub m) is molecular viscosity, c is sound speed, and H is vertical scale height. Several studies, and observed lifetimes of circumstellar disks, have suggested that the level of nebula turbulence can be described by alpha = 10(exp -2) - 10(exp -4). There is some recent concern about how energy is provided to maintain this turbulence, but the issue remains open. We adopt a canonical minimum mass nebula with a range of alpha is greater than 0. We originally showed that chondrule-sized particles are selected for concentration in the terrestrial planet region if alpha = 10(exp -3) - 10(exp -4). In addition, Paque and Cuzzi found that the size distribution of chondrules is an excellent match for theoretical predictions. One then asks by what concentration factor C these particles can be concentrated; our early numerical results indicated an increase of C with alpha, and were supported by simple scaling arguments, but the extrapolation range was quite large and the predictions (C is approximately equal to 10(exp 5) - 10(exp 6) not unlikely) uncertain. The work presented here, which makes use of our recent demonstration that the particle density field is a multifractal with flow-independent properties provides a far more secure ground for such predictions. We also indicate how fine-grained dust rims on chondrules might enter into constraining the situation. Once large particles (meter-size mass equivalent) reach the midplane, perhaps in the form of dense aggregates of the sort formed in 3D turbulence, they remain stable against gravitational instability but might grow rapidly by accretion of their drifting neighbors, depending on the level of global turbulence.

Characterizing the Indoor-Outdoor Relationship of Fine Particulate Matter in Non-Heating Season for Urban Residences in Beijing

PubMed Central

Huang, Lihui; Pu, Zhongnan; Li, Mu; Sundell, Jan

2015-01-01

Objective Ambient fine particulate matter (PM2.5) pollution is currently a major public health concern in Chinese urban areas. However, PM2.5 exposure primarily occurs indoors. Given such, we conducted this study to characterize the indoor-outdoor relationship of PM2.5 mass concentrations for urban residences in Beijing. Methods In this study, 24-h real-time indoor and ambient PM2.5 mass concentrations were concurrently collected for 41 urban residences in the non-heating season. The diurnal variation of pollutant concentrations was characterized. Pearson correlation analysis was used to examine the correlation between indoor and ambient PM2.5 mass concentrations. Regression analysis with ordinary least square was employed to characterize the influences of a variety of factors on PM2.5 mass concentration. Results Hourly ambient PM2.5 mass concentrations were 3–280 μg/m3 with a median of 58 μg/m3, and hourly indoor counterpart were 4–193 μg/m3 with a median of 34 μg/m3. The median indoor/ambient ratio of PM2.5 mass concentration was 0.62. The diurnal variation of residential indoor and ambient PM2.5 mass concentrations tracked with each other well. Strong correlation was found between indoor and ambient PM2.5 mass concentrations on the community basis (coefficients: r≥0.90, p<0.0001), and the ambient data explained ≥84% variance of the indoor data. Regression analysis suggested that the variables, such as traffic conditions, indoor smoking activities, indoor cleaning activities, indoor plants and number of occupants, had significant influences on the indoor PM2.5 mass concentrations. Conclusions PM2.5 of ambient origin made dominant contribution to residential indoor PM2.5 exposure in the non-heating season under the high ambient fine particle pollution condition. Nonetheless, the large inter-residence variability of infiltration factor of ambient PM2.5 raised the concern of exposure misclassification when using ambient PM2.5 mass concentrations as exposure surrogates. PM2.5 of indoor origin still had minor influence on indoor PM2.5 mass concentrations, particularly at 11:00–13:00 and 22:00–0:00. The predictive models suggested that particles from traffic emission, secondary aerosols, particles from indoor smoking, resuspended particles due to indoor cleaning and particles related to indoor plants contributed to indoor PM2.5 mass concentrations in this study. Real-time ventilation measurements and improvement of questionnaire design to involve more variables subject to built environment were recommended to enhance the performance of the predictive models. PMID:26397734

Fate and bioaccumulation of isoproturon in outdoor aquatic microcosms.

PubMed

Merlin, Gerard; Vuillod, Maryline; Lissolo, Thierry; Clement, Bernard

2002-06-01

To gain information concerning the ecotoxicity of isoproturon (IPU) on aquatic ecosystems, six experimental ponds of 5 m3 each were studied. All the experiments were conducted during the summer over two years. Three different types of ecosystems were tested in 1994 and one type of ecosystem was selected and repeated in 1995 with three replicates. In each case, the initial concentration of IPU contamination was set at 10 microg/L. The IPU concentration was determined in the water column and in different species (mainly plants) of the microcosms. A first-order kinetic decrease in IPU concentration was observed in 1994, with half-life ranging from 15 to 35 d, depending on the microcosms. This relatively fast decrease was also confirmed in 1995, but it reached a constant value after two months. A high variability of the IPU concentration was observed in exposed plants, with bioconcentration factors ranging from 100 to 1,200 with large coefficients of variation. The observed plant bioconcentration factors are higher than those predicted by usual numerical models, probably due to the specific binding of IPU on one protein of the photosynthetic apparatus. Our data show that bioconcentration does not occur in mollusks but is important in photosynthetic organisms. Plant bioconcentration and microbial biodegradation are the main processes involved in the IPU decay in our outdoor aquatic microcosms.

Combined evaluation of the Glasgow prognostic score and carcinoembryonic antigen concentration prior to hepatectomy predicts postoperative outcomes in patients with liver metastasis from colorectal cancer.

PubMed

Kobayashi, Takashi; Kawakamil, Masayo; Hara, Yoshiaki; Shioiri, Sadaaki; Yasuno, Masamichi; Teruya, Masanori; Kaminishi, Michio

2014-01-01

Little is known about the ability of the inflammation-based Glasgow prognostic score (GPS). 106 patients who underwent curative resection for colorectal liver metastasis (CRLM) were analyzed. Patients with an elevated Creactive protein concentration (>10 mg/L) and hypoalbuminemia (<35 g/L) at admission were assigned a GPS 2, those with only 1 of these biochemical abnormalities were assigned a GPS 1, and those without either abnormality were assigned a GPS 0. Multivariate analysis showed that 2 variables, carcinoembryonic antigen (CEA) concentration > 30 ng/mL and a GPS 1 or 2, were independently prognostic of survival. Patients were classified into 3 groups on the basis of these 2 variables. Patients with GPS 1 or 2 and CEA concentration > 30 ng/mL were assigned a new score of 2, those with either 1 factor were assigned a new score of 1, and those with neither factors were assigned a new score of 0. The 5-year overall survival rates of new scores of 0, 1, 2 were 71.5%, 31.6%, and 0%, respectively (P < 0.0001). This simple staging system may be able to identify a subgroup of patients who are eligible for curative resection but show poor prognosis.

Effect of Wind Flow on Convective Heat Losses from Scheffler Solar Concentrator Receivers

NASA Astrophysics Data System (ADS)

Nene, Anita Arvind; Ramachandran, S.; Suyambazhahan, S.

2018-05-01

Receiver is an important element of solar concentrator system. In a Scheffler concentrator, solar rays get concentrated at focus of parabolic dish. While radiation losses are more predictable and calculable since strongly related to receiver temperature, convective looses are difficult to estimate in view of additional factors such as wind flow direction, speed, receiver geometry, prior to current work. Experimental investigation was carried out on two geometries of receiver namely cylindrical and conical with 2.7 m2 Scheffler to find optimum condition of tilt to provide best efficiency. Experimental results showed that as compared to cylindrical receiver, conical receiver gave maximum efficiency at 45° tilt angle. However effect of additional factors like wind speed, wind direction on especially convective losses could not be separately seen. The current work was undertaken to investigate further the same two geometries using computation fluid dynamics using FLUENT to compute convective losses considering all variables such at tilt angle of receiver, wind velocity and wind direction. For cylindrical receiver, directional heat transfer coefficient (HTC) is remarkably high to tilt condition meaning this geometry is critical to tilt leading to higher convective heat losses. For conical receiver, directional average HTC is remarkably less to tilt condition leading to lower convective heat loss.

A novel approach combining self-organizing map and parallel factor analysis for monitoring water quality of watersheds under non-point source pollution

PubMed Central

Zhang, Yixiang; Liang, Xinqiang; Wang, Zhibo; Xu, Lixian

2015-01-01

High content of organic matter in the downstream of watersheds underscored the severity of non-point source (NPS) pollution. The major objectives of this study were to characterize and quantify dissolved organic matter (DOM) in watersheds affected by NPS pollution, and to apply self-organizing map (SOM) and parallel factor analysis (PARAFAC) to assess fluorescence properties as proxy indicators for NPS pollution and labor-intensive routine water quality indicators. Water from upstreams and downstreams was sampled to measure dissolved organic carbon (DOC) concentrations and excitation-emission matrix (EEM). Five fluorescence components were modeled with PARAFAC. The regression analysis between PARAFAC intensities (Fmax) and raw EEM measurements indicated that several raw fluorescence measurements at target excitation-emission wavelength region could provide similar DOM information to massive EEM measurements combined with PARAFAC. Regression analysis between DOC concentration and raw EEM measurements suggested that some regions in raw EEM could be used as surrogates for labor-intensive routine indicators. SOM can be used to visualize the occurrence of pollution. Relationship between DOC concentration and PARAFAC components analyzed with SOM suggested that PARAFAC component 2 might be the major part of bulk DOC and could be recognized as a proxy indicator to predict the DOC concentration. PMID:26526140

Environmental factors associated with long-term changes in chlorophyll concentration in the Sacramento-San Joaquin delta and Suisun Bay, California

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lehman, P.W.

Long-term changes in chlorophyll concentration were predicted from environmental variables using Box-Jenkins transfer function models for the Sacramento and San Joaquin rivers and Suisun Bay. The indication that oceanic phytoplankton biomass for the California regions is associated with climatic phenomena produced by El Nino and the Southern Oscillation (ENSO) was one of several factors used to standardize the dataset. Data used for the analyses were collected continuously on a semimonthly or monthly basis over the 17-yr period between 1971 and 1987. Groups of highly correlated environmental variables were summarized along three environmental axes using principal component analysis. The first environmentalmore » axis summarized river flow and specific conductance. The second environmental axis summarized water transparency and the third environmental axis summarized air and water temperature. Chlorophyll concentration was significantly cross-correlated with environmental axes and individual environmental variables. Transfer function models developed to describe changes in chlorophyll concentration over time were characterized by lag responses and described between 41% and 51% of the data variation. Significant cross-correlations between environmental axes and the California climate index (CA SLP) were used to develop a conceptual model of the link between regional climate and estuarine production. 50 refs., 5 figs.« less