Predicting Transition from Laminar to Turbulent Flow over a Surface

NASA Technical Reports Server (NTRS)

Sturdza, Peter (Inventor); Rajnarayan, Dev (Inventor)

2013-01-01

A prediction of whether a point on a computer-generated surface is adjacent to laminar or turbulent flow is made using a transition prediction technique. A plurality of boundary-layer properties at the point are obtained from a steady-state solution of a fluid flow in a region adjacent to the point. A plurality of instability modes are obtained, each defined by one or more mode parameters. A vector of regressor weights is obtained for the known instability growth rates in a training dataset. For each instability mode in the plurality of instability modes, a covariance vector is determined, which is the covariance of a predicted local growth rate with the known instability growth rates. Each covariance vector is used with the vector of regressor weights to determine a predicted local growth rate at the point. Based on the predicted local growth rates, an n-factor envelope at the point is determined.

Local environmental quality positively predicts breastfeeding in the UK’s Millennium Cohort Study

PubMed Central

Sear, Rebecca

2017-01-01

ABSTRACT Background and Objectives: Breastfeeding is an important form of parental investment with clear health benefits. Despite this, rates remain low in the UK; understanding variation can therefore help improve interventions. Life history theory suggests that environmental quality may pattern maternal investment, including breastfeeding. We analyse a nationally representative dataset to test two predictions: (i) higher local environmental quality predicts higher likelihood of breastfeeding initiation and longer duration; (ii) higher socioeconomic status (SES) provides a buffer against the adverse influences of low local environmental quality. Methodology: We ran factor analysis on a wide range of local-level environmental variables. Two summary measures of local environmental quality were generated by this analysis—one ‘objective’ (based on an independent assessor’s neighbourhood scores) and one ‘subjective’ (based on respondent’s scores). We used mixed-effects regression techniques to test our hypotheses. Results: Higher objective, but not subjective, local environmental quality predicts higher likelihood of starting and maintaining breastfeeding over and above individual SES and area-level measures of environmental quality. Higher individual SES is protective, with women from high-income households having relatively high breastfeeding initiation rates and those with high status jobs being more likely to maintain breastfeeding, even in poor environmental conditions. Conclusions and Implications: Environmental quality is often vaguely measured; here we present a thorough investigation of environmental quality at the local level, controlling for individual- and area-level measures. Our findings support a shift in focus away from individual factors and towards altering the landscape of women’s decision making contexts when considering behaviours relevant to public health. PMID:29354262

Local environmental quality positively predicts breastfeeding in the UK's Millennium Cohort Study.

PubMed

Brown, Laura J; Sear, Rebecca

2017-01-01

Background and Objectives: Breastfeeding is an important form of parental investment with clear health benefits. Despite this, rates remain low in the UK; understanding variation can therefore help improve interventions. Life history theory suggests that environmental quality may pattern maternal investment, including breastfeeding. We analyse a nationally representative dataset to test two predictions: (i) higher local environmental quality predicts higher likelihood of breastfeeding initiation and longer duration; (ii) higher socioeconomic status (SES) provides a buffer against the adverse influences of low local environmental quality. Methodology: We ran factor analysis on a wide range of local-level environmental variables. Two summary measures of local environmental quality were generated by this analysis-one 'objective' (based on an independent assessor's neighbourhood scores) and one 'subjective' (based on respondent's scores). We used mixed-effects regression techniques to test our hypotheses. Results: Higher objective, but not subjective, local environmental quality predicts higher likelihood of starting and maintaining breastfeeding over and above individual SES and area-level measures of environmental quality. Higher individual SES is protective, with women from high-income households having relatively high breastfeeding initiation rates and those with high status jobs being more likely to maintain breastfeeding, even in poor environmental conditions. Conclusions and Implications: Environmental quality is often vaguely measured; here we present a thorough investigation of environmental quality at the local level, controlling for individual- and area-level measures. Our findings support a shift in focus away from individual factors and towards altering the landscape of women's decision making contexts when considering behaviours relevant to public health.

Inter-kingdom prediction certainty evaluation of protein subcellular localization tools: microbial pathogenesis approach for deciphering host microbe interaction.

PubMed

Khan, Abdul Arif; Khan, Zakir; Kalam, Mohd Abul; Khan, Azmat Ali

2018-01-01

Microbial pathogenesis involves several aspects of host-pathogen interactions, including microbial proteins targeting host subcellular compartments and subsequent effects on host physiology. Such studies are supported by experimental data, but recent detection of bacterial proteins localization through computational eukaryotic subcellular protein targeting prediction tools has also come into practice. We evaluated inter-kingdom prediction certainty of these tools. The bacterial proteins experimentally known to target host subcellular compartments were predicted with eukaryotic subcellular targeting prediction tools, and prediction certainty was assessed. The results indicate that these tools alone are not sufficient for inter-kingdom protein targeting prediction. The correct prediction of pathogen's protein subcellular targeting depends on several factors, including presence of localization signal, transmembrane domain and molecular weight, etc., in addition to approach for subcellular targeting prediction. The detection of protein targeting in endomembrane system is comparatively difficult, as the proteins in this location are channelized to different compartments. In addition, the high specificity of training data set also creates low inter-kingdom prediction accuracy. Current data can help to suggest strategy for correct prediction of bacterial protein's subcellular localization in host cell. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Psychological Factors Predict Local and Referred Experimental Muscle Pain: A Cluster Analysis in Healthy Adults

PubMed Central

Lee, Jennifer E.; Watson, David; Frey-Law, Laura A.

2012-01-01

Background Recent studies suggest an underlying three- or four-factor structure explains the conceptual overlap and distinctiveness of several negative emotionality and pain-related constructs. However, the validity of these latent factors for predicting pain has not been examined. Methods A cohort of 189 (99F; 90M) healthy volunteers completed eight self-report negative emotionality and pain-related measures (Eysenck Personality Questionnaire-Revised; Positive and Negative Affect Schedule; State-Trait Anxiety Inventory; Pain Catastrophizing Scale; Fear of Pain Questionnaire; Somatosensory Amplification Scale; Anxiety Sensitivity Index; Whiteley Index). Using principal axis factoring, three primary latent factors were extracted: General Distress; Catastrophic Thinking; and Pain-Related Fear. Using these factors, individuals clustered into three subgroups of high, moderate, and low negative emotionality responses. Experimental pain was induced via intramuscular acidic infusion into the anterior tibialis muscle, producing local (infusion site) and/or referred (anterior ankle) pain and hyperalgesia. Results Pain outcomes differed between clusters (multivariate analysis of variance and multinomial regression), with individuals in the highest negative emotionality cluster reporting the greatest local pain (p = 0.05), mechanical hyperalgesia (pressure pain thresholds; p = 0.009) and greater odds (2.21 OR) of experiencing referred pain compared to the lowest negative emotionality cluster. Conclusion Our results provide support for three latent psychological factors explaining the majority of the variance between several pain-related psychological measures, and that individuals in the high negative emotionality subgroup are at increased risk for (1) acute local muscle pain; (2) local hyperalgesia; and (3) referred pain using a standardized nociceptive input. PMID:23165778

Predicting Transition from Laminar to Turbulent Flow over a Surface

NASA Technical Reports Server (NTRS)

Rajnarayan, Dev (Inventor); Sturdza, Peter (Inventor)

2016-01-01

A prediction of whether a point on a computer-generated surface is adjacent to laminar or turbulent flow is made using a transition prediction technique. A plurality of instability modes are obtained, each defined by one or more mode parameters. A vector of regressor weights is obtained for the known instability growth rates in a training dataset. For an instability mode in the plurality of instability modes, a covariance vector is determined. A predicted local instability growth rate at the point is determined using the covariance vector and the vector of regressor weights. Based on the predicted local instability growth rate, an n-factor envelope at the point is determined.

Analysis of uncertainties in turbine metal temperature predictions

NASA Technical Reports Server (NTRS)

Stepka, F. S.

1980-01-01

An analysis was conducted to examine the extent to which various factors influence the accuracy of analytically predicting turbine blade metal temperatures and to determine the uncertainties in these predictions for several accuracies of the influence factors. The advanced turbofan engine gas conditions of 1700 K and 40 atmospheres were considered along with those of a highly instrumented high temperature turbine test rig and a low temperature turbine rig that simulated the engine conditions. The analysis showed that the uncertainty in analytically predicting local blade temperature was as much as 98 K, or 7.6 percent of the metal absolute temperature, with current knowledge of the influence factors. The expected reductions in uncertainties in the influence factors with additional knowledge and tests should reduce the uncertainty in predicting blade metal temperature to 28 K, or 2.1 percent of the metal absolute temperature.

Relationship of number of seizures recorded on video-EEG to surgical outcome in refractory medial temporal lobe epilepsy

PubMed Central

Sainju, Rup Kamal; Wolf, Bethany Jacobs; Bonilha, Leonardo; Martz, Gabriel

2014-01-01

Introduction Surgical planning for refractory medial temporal lobe epilepsy (rMTLE) relies on seizure localization by ictal electroencephalography (EEG). Multiple factors impact the number of seizures recorded. We evaluated whether seizure freedom correlated to the number of seizures recorded, and the related factors. Methods We collected data for 32 patients with rMTLE who underwent anterior temporal lobectomy. Primary analysis evaluated number of seizures captured as a predictor of surgical outcome. Subsequent analyses explored factors that may seizure number. Results Number of seizures recorded did not predict seizure freedom. More seizures were recorded with more days of seizure occurrence (p<0.001), seizure clusters (p≤0.011) and poorly localized seizures (PLSz) (p=0.004). Regression modeling showed a trend for subjects with fewer recorded poorly localized seizures to have better surgical outcome (p=0.052). Conclusions Total number of recorded seizures does not predict surgical outcome. Patients with more PLSz may have worse outcome. PMID:22990726

Climate and local abundance in freshwater fishes

PubMed Central

Knouft, Jason H.; Anthony, Melissa M.

2016-01-01

Identifying factors regulating variation in numbers of individuals among populations across a species' distribution is a fundamental goal in ecology. A common prediction, often referred to as the abundant-centre hypothesis, suggests that abundance is highest near the centre of a species' range. However, because of the primary focus on the geographical position of a population, this framework provides little insight into the environmental factors regulating local abundance. While range-wide variation in population abundance associated with environmental conditions has been investigated in terrestrial species, the relationship between climate and local abundance in freshwater taxa across species' distributions is not well understood. We used GIS-based temperature and precipitation data to determine the relationships between climatic conditions and range-wide variation in local abundance for 19 species of North American freshwater fishes. Climate predicted a portion of the variation in local abundance among populations for 18 species. In addition, the relationship between climatic conditions and local abundance varied among species, which is expected as lineages partition the environment across geographical space. The influence of local habitat quality on species persistence is well documented; however, our results also indicate the importance of climate in regulating population sizes across a species geographical range, even in aquatic taxa. PMID:27429769

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.

Comorbidity, Use of Common Medications, and Risk of Early Death in Patients with Localized or Locally Advanced Prostate Cancer

PubMed Central

Nieder, Carsten; Dalhaug, Astrid; Pawinski, Adam; Aandahl, Gro; Norum, Jan

2011-01-01

In this paper, we analyze predictive factors for early death from comorbidity (defined as death within 3 years from diagnosis and unrelated to prostate cancer) in patients with localized or locally advanced prostate cancer. Such information may guide individually tailored treatment or observation strategies, and help to avoid overtreatment. We retrospectively analyzed baseline parameters including information on comorbidity and medication use among 177 patients (median age at diagnosis 70 years). Actuarial survival analyses were performed. During the first 3 years, two patients (1.1%) died from progressive prostate cancer after they had developed distant metastases. The risk of dying from other causes (3.4%) was numerically higher, although not to a statistically significant degree. Six patients who died from other causes had age-adjusted Charlson comorbidity index (CCI) scores ≥5 (CCI is a sum score where each comorbid condition is assigned with a score depending on the risk of dying associated with this condition). The main comorbidity was cardiovascular disease. The two statistically significant predictive factors were medication use and age-adjusted CCI score ≥5 (univariate analysis). However, medication use was not an independent factor as all patients with age-adjusted CCI score ≥5 also used at least one class of medication. Median survival was 30 months in patients with age-adjusted CCI score ≥5. Prediction of non-prostate cancer death may be important to prevent overtreatment in patients who are more threatened by comorbidity. Our data suggest that simple parameters such as use of medications vs. none, or presence of serious cardiac disease vs. none, are not sufficient, and that age-adjusted CCI scores outperform the other factors included in our analysis. PMID:21666987

Local connectome phenotypes predict social, health, and cognitive factors

PubMed Central

Powell, Michael A.; Garcia, Javier O.; Yeh, Fang-Cheng; Vettel, Jean M.

2018-01-01

The unique architecture of the human connectome is defined initially by genetics and subsequently sculpted over time with experience. Thus, similarities in predisposition and experience that lead to similarities in social, biological, and cognitive attributes should also be reflected in the local architecture of white matter fascicles. Here we employ a method known as local connectome fingerprinting that uses diffusion MRI to measure the fiber-wise characteristics of macroscopic white matter pathways throughout the brain. This fingerprinting approach was applied to a large sample (N = 841) of subjects from the Human Connectome Project, revealing a reliable degree of between-subject correlation in the local connectome fingerprints, with a relatively complex, low-dimensional substructure. Using a cross-validated, high-dimensional regression analysis approach, we derived local connectome phenotype (LCP) maps that could reliably predict a subset of subject attributes measured, including demographic, health, and cognitive measures. These LCP maps were highly specific to the attribute being predicted but also sensitive to correlations between attributes. Collectively, these results indicate that the local architecture of white matter fascicles reflects a meaningful portion of the variability shared between subjects along several dimensions. PMID:29911679

Local connectome phenotypes predict social, health, and cognitive factors.

PubMed

Powell, Michael A; Garcia, Javier O; Yeh, Fang-Cheng; Vettel, Jean M; Verstynen, Timothy

2018-01-01

The unique architecture of the human connectome is defined initially by genetics and subsequently sculpted over time with experience. Thus, similarities in predisposition and experience that lead to similarities in social, biological, and cognitive attributes should also be reflected in the local architecture of white matter fascicles. Here we employ a method known as local connectome fingerprinting that uses diffusion MRI to measure the fiber-wise characteristics of macroscopic white matter pathways throughout the brain. This fingerprinting approach was applied to a large sample ( N = 841) of subjects from the Human Connectome Project, revealing a reliable degree of between-subject correlation in the local connectome fingerprints, with a relatively complex, low-dimensional substructure. Using a cross-validated, high-dimensional regression analysis approach, we derived local connectome phenotype (LCP) maps that could reliably predict a subset of subject attributes measured, including demographic, health, and cognitive measures. These LCP maps were highly specific to the attribute being predicted but also sensitive to correlations between attributes. Collectively, these results indicate that the local architecture of white matter fascicles reflects a meaningful portion of the variability shared between subjects along several dimensions.

Estimation and prediction under local volatility jump-diffusion model

NASA Astrophysics Data System (ADS)

Kim, Namhyoung; Lee, Younhee

2018-02-01

Volatility is an important factor in operating a company and managing risk. In the portfolio optimization and risk hedging using the option, the value of the option is evaluated using the volatility model. Various attempts have been made to predict option value. Recent studies have shown that stochastic volatility models and jump-diffusion models reflect stock price movements accurately. However, these models have practical limitations. Combining them with the local volatility model, which is widely used among practitioners, may lead to better performance. In this study, we propose a more effective and efficient method of estimating option prices by combining the local volatility model with the jump-diffusion model and apply it using both artificial and actual market data to evaluate its performance. The calibration process for estimating the jump parameters and local volatility surfaces is divided into three stages. We apply the local volatility model, stochastic volatility model, and local volatility jump-diffusion model estimated by the proposed method to KOSPI 200 index option pricing. The proposed method displays good estimation and prediction performance.

[Locally advanced head and neck cancers: recommendations of an expert panel and perspectives for the use of TPF regimen (docetaxel, cisplatin and fluoro-uracil) as induction therapy].

PubMed

Bardet, E; Bourhis, J; Cals, L; Fayette, J; Guigay, J; Hans, S; Saint-Guily, J Lacau; Lagarde, F; Lallemant, B; Milano, G; Rolland, F; Lefebvre, J-L

2009-10-01

The purpose of the present article was to evaluate indications, regimens, treatment modalities, and predictive factors of response to treatment in locally advanced squamous cell carcinoma of the head and neck (SCCHN). An expert panel including otolaryngology and head and neck surgery specialists, oncologists, radiotherapists and biologists analyzed the literature providing a synthesis and giving some recommendations. Findings from the main randomized phase III trials highlight that the TPF regimen (docetaxel, cisplatin, fluorouracil) represent a preferential option when induction chemotherapy is indicated in either operable or non-operable patients. Given the potential fragility of patients presenting with SCCHN, treatment modalities in routine use require applying preventive measures and tailored follow-up according to each patient's profile. As regards predictive factors of response to TPF regimen, no factor is currently validated, but ongoing trials should provide better knowledge. Progresses in induction chemotherapy have allowed improving the prognosis of patients with locally advanced SCCHN. The TPF regimen represents a major improvement in this indication, and ongoing strategic clinical trials should refine its indications.

A Bayesian network approach for modeling local failure in lung cancer

NASA Astrophysics Data System (ADS)

Oh, Jung Hun; Craft, Jeffrey; Lozi, Rawan Al; Vaidya, Manushka; Meng, Yifan; Deasy, Joseph O.; Bradley, Jeffrey D.; El Naqa, Issam

2011-03-01

Locally advanced non-small cell lung cancer (NSCLC) patients suffer from a high local failure rate following radiotherapy. Despite many efforts to develop new dose-volume models for early detection of tumor local failure, there was no reported significant improvement in their application prospectively. Based on recent studies of biomarker proteins' role in hypoxia and inflammation in predicting tumor response to radiotherapy, we hypothesize that combining physical and biological factors with a suitable framework could improve the overall prediction. To test this hypothesis, we propose a graphical Bayesian network framework for predicting local failure in lung cancer. The proposed approach was tested using two different datasets of locally advanced NSCLC patients treated with radiotherapy. The first dataset was collected retrospectively, which comprises clinical and dosimetric variables only. The second dataset was collected prospectively in which in addition to clinical and dosimetric information, blood was drawn from the patients at various time points to extract candidate biomarkers as well. Our preliminary results show that the proposed method can be used as an efficient method to develop predictive models of local failure in these patients and to interpret relationships among the different variables in the models. We also demonstrate the potential use of heterogeneous physical and biological variables to improve the model prediction. With the first dataset, we achieved better performance compared with competing Bayesian-based classifiers. With the second dataset, the combined model had a slightly higher performance compared to individual physical and biological models, with the biological variables making the largest contribution. Our preliminary results highlight the potential of the proposed integrated approach for predicting post-radiotherapy local failure in NSCLC patients.

The Importance of Biotic vs. Abiotic Drivers of Local Plant Community Composition Along Regional Bioclimatic Gradients

PubMed Central

Klanderud, Kari; Vandvik, Vigdis; Goldberg, Deborah

2015-01-01

We assessed if the relative importance of biotic and abiotic factors for plant community composition differs along environmental gradients and between functional groups, and asked which implications this may have in a warmer and wetter future. The study location is a unique grid of sites spanning regional-scale temperature and precipitation gradients in boreal and alpine grasslands in southern Norway. Within each site we sampled vegetation and associated biotic and abiotic factors, and combined broad- and fine-scale ordination analyses to assess the relative explanatory power of these factors for species composition. Although the community responses to biotic and abiotic factors did not consistently change as predicted along the bioclimatic gradients, abiotic variables tended to explain a larger proportion of the variation in species composition towards colder sites, whereas biotic variables explained more towards warmer sites, supporting the stress gradient hypothesis. Significant interactions with precipitation suggest that biotic variables explained more towards wetter climates in the sub alpine and boreal sites, but more towards drier climates in the colder alpine. Thus, we predict that biotic interactions may become more important in alpine and boreal grasslands in a warmer future, although more winter precipitation may counteract this trend in oceanic alpine climates. Our results show that both local and regional scales analyses are needed to disentangle the local vegetation-environment relationships and their regional-scale drivers, and biotic interactions and precipitation must be included when predicting future species assemblages. PMID:26091266

The Importance of Biotic vs. Abiotic Drivers of Local Plant Community Composition Along Regional Bioclimatic Gradients.

PubMed

Klanderud, Kari; Vandvik, Vigdis; Goldberg, Deborah

2015-01-01

We assessed if the relative importance of biotic and abiotic factors for plant community composition differs along environmental gradients and between functional groups, and asked which implications this may have in a warmer and wetter future. The study location is a unique grid of sites spanning regional-scale temperature and precipitation gradients in boreal and alpine grasslands in southern Norway. Within each site we sampled vegetation and associated biotic and abiotic factors, and combined broad- and fine-scale ordination analyses to assess the relative explanatory power of these factors for species composition. Although the community responses to biotic and abiotic factors did not consistently change as predicted along the bioclimatic gradients, abiotic variables tended to explain a larger proportion of the variation in species composition towards colder sites, whereas biotic variables explained more towards warmer sites, supporting the stress gradient hypothesis. Significant interactions with precipitation suggest that biotic variables explained more towards wetter climates in the sub alpine and boreal sites, but more towards drier climates in the colder alpine. Thus, we predict that biotic interactions may become more important in alpine and boreal grasslands in a warmer future, although more winter precipitation may counteract this trend in oceanic alpine climates. Our results show that both local and regional scales analyses are needed to disentangle the local vegetation-environment relationships and their regional-scale drivers, and biotic interactions and precipitation must be included when predicting future species assemblages.

Strong expectations cancel locality effects: evidence from Hindi.

PubMed

Husain, Samar; Vasishth, Shravan; Srinivasan, Narayanan

2014-01-01

Expectation-driven facilitation (Hale, 2001; Levy, 2008) and locality-driven retrieval difficulty (Gibson, 1998, 2000; Lewis & Vasishth, 2005) are widely recognized to be two critical factors in incremental sentence processing; there is accumulating evidence that both can influence processing difficulty. However, it is unclear whether and how expectations and memory interact. We first confirm a key prediction of the expectation account: a Hindi self-paced reading study shows that when an expectation for an upcoming part of speech is dashed, building a rarer structure consumes more processing time than building a less rare structure. This is a strong validation of the expectation-based account. In a second study, we show that when expectation is strong, i.e., when a particular verb is predicted, strong facilitation effects are seen when the appearance of the verb is delayed; however, when expectation is weak, i.e., when only the part of speech "verb" is predicted but a particular verb is not predicted, the facilitation disappears and a tendency towards a locality effect is seen. The interaction seen between expectation strength and distance shows that strong expectations cancel locality effects, and that weak expectations allow locality effects to emerge.

Strong Expectations Cancel Locality Effects: Evidence from Hindi

PubMed Central

Husain, Samar; Vasishth, Shravan; Srinivasan, Narayanan

2014-01-01

Expectation-driven facilitation (Hale, 2001; Levy, 2008) and locality-driven retrieval difficulty (Gibson, 1998, 2000; Lewis & Vasishth, 2005) are widely recognized to be two critical factors in incremental sentence processing; there is accumulating evidence that both can influence processing difficulty. However, it is unclear whether and how expectations and memory interact. We first confirm a key prediction of the expectation account: a Hindi self-paced reading study shows that when an expectation for an upcoming part of speech is dashed, building a rarer structure consumes more processing time than building a less rare structure. This is a strong validation of the expectation-based account. In a second study, we show that when expectation is strong, i.e., when a particular verb is predicted, strong facilitation effects are seen when the appearance of the verb is delayed; however, when expectation is weak, i.e., when only the part of speech “verb” is predicted but a particular verb is not predicted, the facilitation disappears and a tendency towards a locality effect is seen. The interaction seen between expectation strength and distance shows that strong expectations cancel locality effects, and that weak expectations allow locality effects to emerge. PMID:25010700

Expression, fermentation and purification of a predicted intrinsically disordered region of the transcription factor, NFAT5.

PubMed

DuMond, Jenna F; He, Yi; Burg, Maurice B; Ferraris, Joan D

2015-11-01

Hypertonicity stimulates Nuclear Factor of Activated T-cells 5 (NFAT5) nuclear localization and transactivating activity. Many transcription factors are known to contain intrinsically disordered regions (IDRs) which become more structured with local environmental changes such as osmolality, temperature and tonicity. The transactivating domain of NFAT5 is predicted to be intrinsically disordered under normal tonicity, and under high NaCl, the activity of this domain is increased. To study the binding of co-regulatory proteins at IDRs a cDNA construct expressing the NFAT5 TAD was created and transformed into Escherichia coli cells. Transformed E. coli cells were mass produced by fermentation and extracted by cell lysis to release the NFAT5 TAD. The NFAT5 TAD was subsequently purified using a His-tag column, cation exchange chromatography as well as hydrophobic interaction chromatography and then characterized by mass spectrometry (MS). Published by Elsevier Inc.

Effects of different dispersal patterns on the presence-absence of multiple species

NASA Astrophysics Data System (ADS)

Mohd, Mohd Hafiz; Murray, Rua; Plank, Michael J.; Godsoe, William

2018-03-01

Predicting which species will be present (or absent) across a geographical region remains one of the key problems in ecology. Numerous studies have suggested several ecological factors that can determine species presence-absence: environmental factors (i.e. abiotic environments), interactions among species (i.e. biotic interactions) and dispersal process. While various ecological factors have been considered, less attention has been given to the problem of understanding how different dispersal patterns, in interaction with other factors, shape community assembly in the presence of priority effects (i.e. where relative initial abundances determine the long-term presence-absence of each species). By employing both local and non-local dispersal models, we investigate the consequences of different dispersal patterns on the occurrence of priority effects and coexistence in multi-species communities. In the case of non-local, but short-range dispersal, we observe agreement with the predictions of local models for weak and medium dispersal strength, but disagreement for relatively strong dispersal levels. Our analysis shows the existence of a threshold value in dispersal strength (i.e. saddle-node bifurcation) above which priority effects disappear. These results also reveal a co-dimension 2 point, corresponding to a degenerate transcritical bifurcation: at this point, the transcritical bifurcation changes from subcritical to supercritical with corresponding creation of a saddle-node bifurcation curve. We observe further contrasting effects of non-local dispersal as dispersal distance changes: while very long-range dispersal can lead to species extinctions, intermediate-range dispersal can permit more outcomes with multi-species coexistence than short-range dispersal (or purely local dispersal). Overall, our results show that priority effects are more pronounced in the non-local dispersal models than in the local dispersal models. Taken together, our findings highlight the profound delicacy in the mediation of priority effects by dispersal processes: ;big steps; can have more influence than many ;small steps;.

Application and analysis of debris-flow early warning system in Wenchuan earthquake-affected area

NASA Astrophysics Data System (ADS)

Liu, D. L.; Zhang, S. J.; Yang, H. J.; Zhao, L. Q.; Jiang, Y. H.; Tang, D.; Leng, X. P.

2016-02-01

The activities of debris flow (DF) in the Wenchuan earthquake-affected area significantly increased after the earthquake on 12 May 2008. The safety of the lives and property of local people is threatened by DFs. A physics-based early warning system (EWS) for DF forecasting was developed and applied in this earthquake area. This paper introduces an application of the system in the Wenchuan earthquake-affected area and analyzes the prediction results via a comparison to the DF events triggered by the strong rainfall events reported by the local government. The prediction accuracy and efficiency was first compared with a contribution-factor-based system currently used by the weather bureau of Sichuan province. The storm on 17 August 2012 was used as a case study for this comparison. The comparison shows that the false negative rate and false positive rate of the new system is, respectively, 19 and 21 % lower than the system based on the contribution factors. Consequently, the prediction accuracy is obviously higher than the system based on the contribution factors with a higher operational efficiency. On the invitation of the weather bureau of Sichuan province, the authors upgraded their prediction system of DF by using this new system before the monsoon of Wenchuan earthquake-affected area in 2013. Two prediction cases on 9 July 2013 and 10 July 2014 were chosen to further demonstrate that the new EWS has high stability, efficiency, and prediction accuracy.

[Predictive factors of mortality of the burnt persons: study on 221 adults hospitalized between 2004 and 2009].

PubMed

Elkafssaoui, S; Hami, H; Mrabet, M; Bouaiti, E; Tourabi, K; Quyou, A; Soulaymani, A; Ihrai, H

2014-06-01

The objective of the present study is the evaluation of the predictive factors of mortality to a troop of Moroccan grown-up serious burnt persons. Variables analyzed in the study are: the age, the sex, the localization of the burn, the degree of burn, indicates Total Body Surface Area (TBSA), indicate Unit of Standard Burn (UBS) and the indication of leases, sepsis and the medical histories (tobacco, diabetes). Factors associated significantly to a mortality raised at the burned patients were the female genital organ, the localization of the burn at the level of the head, the sepsis, one TBSA greater or equal to 20%, an UBS greater or equal to 200 and an indication of leases greater or equal to 75. Other factors such as the age, the degree of burn and the histories did not show a significant difference. An evaluation and a good knowledge of factors associated to a high risk of death allow an adequate coverage of this category of patients. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

Mathematical modeling analysis of intratumoral disposition of anticancer agents and drug delivery systems.

PubMed

Popilski, Hen; Stepensky, David

2015-05-01

Solid tumors are characterized by complex morphology. Numerous factors relating to the composition of the cells and tumor stroma, vascularization and drainage of fluids affect the local microenvironment within a specific location inside the tumor. As a result, the intratumoral drug/drug delivery system (DDS) disposition following systemic or local administration is non-homogeneous and its complexity reflects the differences in the local microenvironment. Mathematical models can be used to analyze the intratumoral drug/DDS disposition and pharmacological effects and to assist in choice of optimal anticancer treatment strategies. The mathematical models that have been applied by different research groups to describe the intratumoral disposition of anticancer drugs/DDSs are summarized in this article. The properties of these models and of their suitability for prediction of the drug/DDS intratumoral disposition and pharmacological effects are reviewed. Currently available mathematical models appear to neglect some of the major factors that govern the drug/DDS intratumoral disposition, and apparently possess limited prediction capabilities. More sophisticated and detailed mathematical models and their extensive validation are needed for reliable prediction of different treatment scenarios and for optimization of drug treatment in the individual cancer patients.

Prostate cancer: predicting high-risk prostate cancer-a novel stratification tool.

PubMed

Buck, Jessica; Chughtai, Bilal

2014-05-01

Currently, numerous systems exist for the identification of high-risk prostate cancer, but few of these systems can guide treatment strategies. A new stratification tool that uses common diagnostic factors can help to predict outcomes after radical prostatectomy. The tool aids physicians in the identification of appropriate candidates for aggressive, local treatment.

Predicting Efficiency of Travel in Young, Visually Impaired Children from Their Other Spatial Skills.

ERIC Educational Resources Information Center

Hill, Anita; And Others

1985-01-01

To test ways of predicting how efficiently visually impaired children learn travel skills, a criteria checklist of spatial skills was developed for close-body space, local space, and geographical/travel space. Comparison was made between predictors of efficient learning including subjective ratings of teachers, personal qualities and factors of…

High-grade extremity soft tissue sarcomas: factors predictive of local recurrence and its effect on morbidity and mortality.

PubMed

Eilber, Fritz C; Rosen, Gerald; Nelson, Scott D; Selch, Michael; Dorey, Frederick; Eckardt, Jeffery; Eilber, Frederick R

2003-02-01

To identify patient characteristics associated with the development of local recurrence and the effect of local recurrence on subsequent morbidity and mortality in patients with intermediate- to high-grade extremity soft tissue sarcomas. Numerous studies on extremity soft tissue sarcomas have consistently shown that presentation with locally recurrent disease is associated with the development of subsequent local recurrences and that large tumor size and high histologic grade are significant factors associated with decreased survival. However, the effect of local recurrence on patient survival remains unclear. From 1975 to 1997, 753 patients with intermediate- to high-grade extremity soft tissue sarcomas were treated at UCLA. Treatment outcomes and patient characteristics were analyzed to identify factors associated with both local recurrence and survival. Patients with locally recurrent disease were at a significantly increased risk of developing a subsequent local recurrence. Local recurrence was a morbid event requiring amputation in 38% of the cases. The development of a local recurrence was the most significant factor associated with decreased survival. Once a patient developed a local recurrence, he or she was about three times more likely to die of disease compared to similar patients who had not developed a local recurrence. Local recurrence in patients with intermediate- to high-grade extremity soft tissue sarcomas is associated with the development of subsequent local recurrences, a morbid event decreasing functional outcomes and the most significant factor associated with decreased survival. Although 85% to 90% of patients with high-grade extremity soft tissue sarcomas are treatable with a limb salvage approach, patients who develop a local recurrence need aggressive treatment and should be considered for trials of adjuvant systemic therapy.

Linking genetic and environmental factors in amphibian disease risk

PubMed Central

Savage, Anna E; Becker, Carlos G; Zamudio, Kelly R

2015-01-01

A central question in evolutionary biology is how interactions between organisms and the environment shape genetic differentiation. The pathogen Batrachochytrium dendrobatidis (Bd) has caused variable population declines in the lowland leopard frog (Lithobates yavapaiensis); thus, disease has potentially shaped, or been shaped by, host genetic diversity. Environmental factors can also influence both amphibian immunity and Bd virulence, confounding our ability to assess the genetic effects on disease dynamics. Here, we used genetics, pathogen dynamics, and environmental data to characterize L. yavapaiensis populations, estimate migration, and determine relative contributions of genetic and environmental factors in predicting Bd dynamics. We found that the two uninfected populations belonged to a single genetic deme, whereas each infected population was genetically unique. We detected an outlier locus that deviated from neutral expectations and was significantly correlated with mortality within populations. Across populations, only environmental variables predicted infection intensity, whereas environment and genetics predicted infection prevalence, and genetic diversity alone predicted mortality. At one locality with geothermally elevated water temperatures, migration estimates revealed source–sink dynamics that have likely prevented local adaptation. We conclude that integrating genetic and environmental variation among populations provides a better understanding of Bd spatial epidemiology, generating more effective conservation management strategies for mitigating amphibian declines. PMID:26136822

Accurate Prediction of Inducible Transcription Factor Binding Intensities In Vivo

PubMed Central

Siepel, Adam; Lis, John T.

2012-01-01

DNA sequence and local chromatin landscape act jointly to determine transcription factor (TF) binding intensity profiles. To disentangle these influences, we developed an experimental approach, called protein/DNA binding followed by high-throughput sequencing (PB–seq), that allows the binding energy landscape to be characterized genome-wide in the absence of chromatin. We applied our methods to the Drosophila Heat Shock Factor (HSF), which inducibly binds a target DNA sequence element (HSE) following heat shock stress. PB–seq involves incubating sheared naked genomic DNA with recombinant HSF, partitioning the HSF–bound and HSF–free DNA, and then detecting HSF–bound DNA by high-throughput sequencing. We compared PB–seq binding profiles with ones observed in vivo by ChIP–seq and developed statistical models to predict the observed departures from idealized binding patterns based on covariates describing the local chromatin environment. We found that DNase I hypersensitivity and tetra-acetylation of H4 were the most influential covariates in predicting changes in HSF binding affinity. We also investigated the extent to which DNA accessibility, as measured by digital DNase I footprinting data, could be predicted from MNase–seq data and the ChIP–chip profiles for many histone modifications and TFs, and found GAGA element associated factor (GAF), tetra-acetylation of H4, and H4K16 acetylation to be the most predictive covariates. Lastly, we generated an unbiased model of HSF binding sequences, which revealed distinct biophysical properties of the HSF/HSE interaction and a previously unrecognized substructure within the HSE. These findings provide new insights into the interplay between the genomic sequence and the chromatin landscape in determining transcription factor binding intensity. PMID:22479205

[The importance of local and general factors in development of inflammatory periodontal diseases in children and adolescents].

PubMed

Shishinashvili, T E; Tsagareli, Z G; Khimshiashvili, N B

2012-10-01

The aim of the study was to investigate the influence of local and general adverse risk factors and their role in the development of inflammatory periodontal diseases in children and adolescents. The study of the dental status among 618 school children, 9 to 15 years of age has been performed. The obtained results revealed an ambiguous influence of general and local risk factors on the development of inflammatory periodontal diseases. Namely, among the general risk factors the main role is given to hormonal functioning state of juvenile age (26.5%) - (arhythmia formation of hormonal activity). Among the local risk factors inducing inflammatory periodontal diseases at young age, the most significant are tooth-jaw anomalies (32.2%), especially - dental occlusion pathology, lips' bridle attachment anomalies, absence of interdental contacts, small vestibule of the mouth and so on. Poor oral hygiene, however, is also a significant factor in all age groups. Definition of the role and importance of general and local risk factors, taking into consideration patient's age, is of great importance in organization of early prevention, giving the possibility to predict disease possible development, choose most appropriate way to treat the specific situation, reduce the need of complex treatment and improve treatment outcomes.

Preoperative staging of rectal cancer.

PubMed

Yeung, Justin Mc; Ferris, Nicholas J; Lynch, A Craig; Heriot, Alexander G

2009-10-01

Preoperative staging is now an essential factor in the multidisciplinary management of rectal cancer because tumor stage is the strongest predictive factor for recurrence. Preoperative staging of rectal cancer can be divided into either local or distant staging. Local staging incorporates the assessment of mural wall invasion, circumferential resection margin involvement, as well as the nodal status for metastasis. Distant staging assesses for evidence of metastatic disease. The aim of this review is to consider the indications and limitations of the current preoperative imaging modalities for rectal cancer staging including clinical examination, endorectal ultrasound, magnetic resonance imaging, computed tomography and positron emission tomography-computed tomography, with respect to local and distant disease.

The status of perineural invasion predicts the outcomes of postoperative radiotherapy in locally advanced esophageal squamous cell carcinoma.

PubMed

Ning, Zhong-Hua; Zhao, Wei; Li, Xiao-Dong; Chen, Lu-Jun; Xu, Bin; Gu, Wen-Dong; Shao, Ying-Jie; Xu, Yun; Huang, Jin; Pei, Hong-Lei; Jiang, Jing-Ting

2015-01-01

Prognosis of locally advanced esophageal squamous cell carcinoma (ESCC) remains dismal even after curative resection and adjuvant radiotherapy. New biomarkers for predicting prognosis and treatment outcomes are needed for improved treatment stratification of patients with locally advanced ESCC. The prognostic and treatment predictive significance of perineural invasion (PNI) in the locally advanced ESCC remains unclear. This study aimed to examine the effect of PNI on the outcomes of locally advanced ESCC patients after curative resection with or without postoperative radiotherapy (PORT). We retrospectively reviewed 262 consecutive locally advanced ESCC patients who underwent curative resection. Tumors sections were re-evaluated for PNI by an independent pathologist blinded to the patients' outcomes. Overall survival (OS) and disease-free survival (DFS) were determined using the Kaplan-Meier method; univariate log-rank test and multivariate Cox proportional hazard model were used to evaluate the prognostic value of PNI. Finally, 243 patients were analyzed and enrolled into this study, of which 132 received PORT. PNI was identified in 22.2% (54/243) of the pathologic sections. The 5-year DFS was favorable for PNI-negative patients versus PNI-positive patients (21.3% vs. 36.7%, respectively; P = 0.005). The 5-year OS was 40.3% for PNI-negative patients versus 21.7% for PNI-positive patients (P < 0.001). On multivariate analysis, PNI was an independent prognostic factor. In a subset analysis for patients received PORT, PNI was evaluated as a prognostic predictor as well (P < 0.05). In contrast to patients without PORT, PORT couldn't improve the disease recurrence and survival in locally advanced ESCC patients with PNI-positive (P > 0.05). PNI could serve as an independent prognostic factor and prognosticate treatment outcomes in locally advanced ESCC patients. The PNI status should be considered when stratifying high-risk locally advanced ESCC patients for adjuvant radiotherapy. Future prospective study is warranted to confirm our results.

Consideration of some factors affecting low-frequency fuselage noise transmission for propeller aircraft

NASA Technical Reports Server (NTRS)

Mixson, J. S.; Roussos, L. A.

1986-01-01

Possible reasons for disagreement between measured and predicted trends of sidewall noise transmission at low frequency are investigated using simplified analysis methods. An analytical model combining incident plane acoustic waves with an infinite flat panel is used to study the effects of sound incidence angle, plate structural properties, frequency, absorption, and the difference between noise reduction and transmission loss. Analysis shows that these factors have significant effects on noise transmission but they do not account for the differences between measured and predicted trends at low frequencies. An analytical model combining an infinite flat plate with a normally incident acoustic wave having exponentially decaying magnitude along one coordinate is used to study the effect of a localized source distribution such as is associated with propeller noise. Results show that the localization brings the predicted low-frequency trend of noise transmission into better agreement with measured propeller results. This effect is independent of low-frequency stiffness effects that have been previously reported to be associated with boundary conditions.

Evaluation of non-negative matrix factorization of grey matter in age prediction.

PubMed

Varikuti, Deepthi P; Genon, Sarah; Sotiras, Aristeidis; Schwender, Holger; Hoffstaedter, Felix; Patil, Kaustubh R; Jockwitz, Christiane; Caspers, Svenja; Moebus, Susanne; Amunts, Katrin; Davatzikos, Christos; Eickhoff, Simon B

2018-06-01

The relationship between grey matter volume (GMV) patterns and age can be captured by multivariate pattern analysis, allowing prediction of individuals' age based on structural imaging. Raw data, voxel-wise GMV and non-sparse factorization (with Principal Component Analysis, PCA) show good performance but do not promote relatively localized brain components for post-hoc examinations. Here we evaluated a non-negative matrix factorization (NNMF) approach to provide a reduced, but also interpretable representation of GMV data in age prediction frameworks in healthy and clinical populations. This examination was performed using three datasets: a multi-site cohort of life-span healthy adults, a single site cohort of older adults and clinical samples from the ADNI dataset with healthy subjects, participants with Mild Cognitive Impairment and patients with Alzheimer's disease (AD) subsamples. T1-weighted images were preprocessed with VBM8 standard settings to compute GMV values after normalization, segmentation and modulation for non-linear transformations only. Non-negative matrix factorization was computed on the GM voxel-wise values for a range of granularities (50-690 components) and LASSO (Least Absolute Shrinkage and Selection Operator) regression were used for age prediction. First, we compared the performance of our data compression procedure (i.e., NNMF) to various other approaches (i.e., uncompressed VBM data, PCA-based factorization and parcellation-based compression). We then investigated the impact of the granularity on the accuracy of age prediction, as well as the transferability of the factorization and model generalization across datasets. We finally validated our framework by examining age prediction in ADNI samples. Our results showed that our framework favorably compares with other approaches. They also demonstrated that the NNMF based factorization derived from one dataset could be efficiently applied to compress VBM data of another dataset and that granularities between 300 and 500 components give an optimal representation for age prediction. In addition to the good performance in healthy subjects our framework provided relatively localized brain regions as the features contributing to the prediction, thereby offering further insights into structural changes due to brain aging. Finally, our validation in clinical populations showed that our framework is sensitive to deviance from normal structural variations in pathological aging. Copyright © 2018 Elsevier Inc. All rights reserved.

Assessing impacts of climate change on species range shifts and extirpation on the local scale through Late Pleistocene fossils of Sequoia sempervirens in the Los Angeles Basin.

NASA Astrophysics Data System (ADS)

George, J.; MacDonald, G. M.

2017-12-01

As the effects of climate change become more apparent, increased importance must be placed on species' response to changing environments for ecosystem management and threat mitigation. While many studies have focused on the response of ecosystem types, few venture to the species level, as true limiting factors of species can be difficult to discern. Paleoproxies provide a valuable resource for predicting responses to future change through observation of similar responses in the past. This study uses plant paleorecords of Sequoia sempervirens to more closely examine the relationship of local climate change and species response in the Los Angeles Basin during the Late Pleistocene. The modern distribution of S. sempervirens has a southern extent, today, reaching the south end of Monterey County, California. Fossilized material from the La Brea Tar Pits extends that range to the farthest known point south, 200 miles from the southernmost modern stands, and has previously not been dated. A coupled analysis of 8 S. sempervirens specimens preserved in asphalt using Accelerator Mass Spectrometry (AMS) dates paired with δC13 values will help to illuminate patterns of changing climate on a local scale, as well as provide valuable data on primary environmental factors in plant community change. Understanding the intricacies of species' range shifts and factors behind local extirpation on a local scale is necessary to interpret species response in the past as well as predicting response in the future.

A general framework for predicting delayed responses of ecological communities to habitat loss.

PubMed

Chen, Youhua; Shen, Tsung-Jen

2017-04-20

Although biodiversity crisis at different spatial scales has been well recognised, the phenomena of extinction debt and immigration credit at a crossing-scale context are, at best, unclear. Based on two community patterns, regional species abundance distribution (SAD) and spatial abundance distribution (SAAD), Kitzes and Harte (2015) presented a macroecological framework for predicting post-disturbance delayed extinction patterns in the entire ecological community. In this study, we further expand this basic framework to predict diverse time-lagged effects of habitat destruction on local communities. Specifically, our generalisation of KH's model could address the questions that could not be answered previously: (1) How many species are subjected to delayed extinction in a local community when habitat is destructed in other areas? (2) How do rare or endemic species contribute to extinction debt or immigration credit of the local community? (3) How will species differ between two local areas? From the demonstrations using two SAD models (single-parameter lognormal and logseries), the predicted patterns of the debt, credit, and change in the fraction of unique species can vary, but with consistencies and depending on several factors. The general framework deepens the understanding of the theoretical effects of habitat loss on community dynamic patterns in local samples.

Improved prediction of residue flexibility by embedding optimized amino acid grouping into RSA-based linear models.

PubMed

Zhang, Hua; Kurgan, Lukasz

2014-12-01

Knowledge of protein flexibility is vital for deciphering the corresponding functional mechanisms. This knowledge would help, for instance, in improving computational drug design and refinement in homology-based modeling. We propose a new predictor of the residue flexibility, which is expressed by B-factors, from protein chains that use local (in the chain) predicted (or native) relative solvent accessibility (RSA) and custom-derived amino acid (AA) alphabets. Our predictor is implemented as a two-stage linear regression model that uses RSA-based space in a local sequence window in the first stage and a reduced AA pair-based space in the second stage as the inputs. This method is easy to comprehend explicit linear form in both stages. Particle swarm optimization was used to find an optimal reduced AA alphabet to simplify the input space and improve the prediction performance. The average correlation coefficients between the native and predicted B-factors measured on a large benchmark dataset are improved from 0.65 to 0.67 when using the native RSA values and from 0.55 to 0.57 when using the predicted RSA values. Blind tests that were performed on two independent datasets show consistent improvements in the average correlation coefficients by a modest value of 0.02 for both native and predicted RSA-based predictions.

Patterns and multi-scale drivers of phytoplankton species richness in temperate peri-urban lakes.

PubMed

Catherine, Arnaud; Selma, Maloufi; Mouillot, David; Troussellier, Marc; Bernard, Cécile

2016-07-15

Local species richness (SR) is a key characteristic affecting ecosystem functioning. Yet, the mechanisms regulating phytoplankton diversity in freshwater ecosystems are not fully understood, especially in peri-urban environments where anthropogenic pressures strongly impact the quality of aquatic ecosystems. To address this issue, we sampled the phytoplankton communities of 50 lakes in the Paris area (France) characterized by a large gradient of physico-chemical and catchment-scale characteristics. We used large phytoplankton datasets to describe phytoplankton diversity patterns and applied a machine-learning algorithm to test the degree to which species richness patterns are potentially controlled by environmental factors. Selected environmental factors were studied at two scales: the lake-scale (e.g. nutrients concentrations, water temperature, lake depth) and the catchment-scale (e.g. catchment, landscape and climate variables). Then, we used a variance partitioning approach to evaluate the interaction between lake-scale and catchment-scale variables in explaining local species richness. Finally, we analysed the residuals of predictive models to identify potential vectors of improvement of phytoplankton species richness predictive models. Lake-scale and catchment-scale drivers provided similar predictive accuracy of local species richness (R(2)=0.458 and 0.424, respectively). Both models suggested that seasonal temperature variations and nutrient supply strongly modulate local species richness. Integrating lake- and catchment-scale predictors in a single predictive model did not provide increased predictive accuracy; therefore suggesting that the catchment-scale model probably explains observed species richness variations through the impact of catchment-scale variables on in-lake water quality characteristics. Models based on catchment characteristics, which include simple and easy to obtain variables, provide a meaningful way of predicting phytoplankton species richness in temperate lakes. This approach may prove useful and cost-effective for the management and conservation of aquatic ecosystems. Copyright © 2016 Elsevier B.V. All rights reserved.

Predicting residue-wise contact orders in proteins by support vector regression.

PubMed

Song, Jiangning; Burrage, Kevin

2006-10-03

The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

Can Image-Defined Risk Factors Predict Surgical Complications in Localized Neuroblastoma?

PubMed

Yoneda, Akihiro; Nishikawa, Masanori; Uehara, Shuichiro; Oue, Takaharu; Usui, Noriaki; Inoue, Masami; Fukuzawa, Masahiro; Okuyama, Hiroomi

2016-02-01

Image-defined risk factors (IDRFs) have been propounded for predicting the surgical risks associated with localized neuroblastoma (NB) since 2009. In 2011, a new guideline (NG) for assessing IDRFs was published. According to the NG, the situation in which "the tumor is only in contact with renal vessels," should be considered to be "IDRF-present." Previously, this situation was diagnosed as "IDRF absent." In this study, we evaluated the IDRFs in localized NB patients to clarify the predictive capability of IDRFs for surgical complications, as well as the usefulness of the NG. Materials and A total of 107 localized patients with NB were included in this study. The enhanced computed tomography and magnetic resonance images from the time of their diagnoses were evaluated by a single radiologist. We also analyzed the association of clinical factors, including the IDRFs (before and after applying the NG), with surgical complications. Of the 107 patients, 33 and 74 patients were diagnosed as IDRF-present (OP group), and IDRF-absent (ON group) before the NG, respectively. According to the NG, there were 76 and 31 patients who were classified as IDRF-present (NP group) and IDRF absent (NN group), respectively. Thus, 43 (40%) patients in the ON group were reassigned to the NP group after the NG. Surgical complications were observed in 17 of 82 patients who underwent surgical resection. Of the patients who underwent secondary operations, surgical complication rates were 55% in the OP group and 44% in the NP group. According to a univariate analysis, non-INSS 1, IDRFs before and after the NG and secondary operations were significantly associated with surgical complications. In a multivariate analysis, non-INSS 1 status and IDRFs after the NG were significantly associated with surgical complications. Georg Thieme Verlag KG Stuttgart · New York.

Dengue Vector Dynamics (Aedes aegypti) Influenced by Climate and Social Factors in Ecuador: Implications for Targeted Control

PubMed Central

Stewart Ibarra, Anna M.; Ryan, Sadie J.; Beltrán, Efrain; Mejía, Raúl; Silva, Mercy; Muñoz, Ángel

2013-01-01

Background Dengue fever, a mosquito-borne viral disease, is now the fastest spreading tropical disease globally. Previous studies indicate that climate and human behavior interact to influence dengue virus and vector (Aedes aegypti) population dynamics; however, the relative effects of these variables depends on local ecology and social context. We investigated the roles of climate and socio-ecological factors on Ae. aegypti population dynamics in Machala, a city in southern coastal Ecuador where dengue is hyper-endemic. Methods/Principal findings We studied two proximate urban localities where we monitored weekly Ae. aegypti oviposition activity (Nov. 2010-June 2011), conducted seasonal pupal surveys, and surveyed household to identify dengue risk factors. The results of this study provide evidence that Ae. aegypti population dynamics are influenced by social risk factors that vary by season and lagged climate variables that vary by locality. Best-fit models to predict the presence of Ae. aegypti pupae included parameters for household water storage practices, access to piped water, the number of households per property, condition of the house and patio, and knowledge and perceptions of dengue. Rainfall and minimum temperature were significant predictors of oviposition activity, although the effect of rainfall varied by locality due to differences in types of water storage containers. Conclusions These results indicate the potential to reduce the burden of dengue in this region by conducting focused vector control interventions that target high-risk households and containers in each season and by developing predictive models using climate and non-climate information. These findings provide the region's public health sector with key information for conducting time and location-specific vector control campaigns, and highlight the importance of local socio-ecological studies to understand dengue dynamics. See Text S1 for an executive summary in Spanish. PMID:24324542

Spatial ecological processes and local factors predict the distribution and abundance of spawning by steelhead (Oncorhynchus mykiss) across a complex riverscape

Treesearch

Jeffrey A. Falke; Jason B. Dunham; Christopher E. Jordan; Kristina M. McNyset; Gordon H. Reeves

2013-01-01

Processes that influence habitat selection in landscapes involve the interaction of habitat composition and configuration and are particularly important for species with complex life cycles. We assessed the relative influence of landscape spatial processes and local habitat characteristics on patterns in the distribution and abundance of spawning steelhead (...

Localized delivery of growth factors for periodontal tissue regeneration: role, strategies, and perspectives.

PubMed

Chen, Fa-Ming; Shelton, Richard M; Jin, Yan; Chapple, Iain L C

2009-05-01

Difficulties associated with achieving predictable periodontal regeneration, means that novel techniques need to be developed in order to regenerate the extensive soft and hard tissue destruction that results from periodontitis. Localized delivery of growth factors to the periodontium is an emerging and versatile therapeutic approach, with the potential to become a powerful tool in future regenerative periodontal therapy. Optimized delivery regimes and well-defined release kinetics appear to be logical prerequisites for safe and efficacious clinical application of growth factors and to avoid unwanted side effects and toxicity. While adequate concentrations of growth factor(s) need to be appropriately localized, delivery vehicles are also expected to possess properties such as protein protection, precision in controlled release, biocompatibility and biodegradability, self-regulated therapeutic activity, potential for multiple delivery, and good cell/tissue penetration. Here, current knowledge, recent advances, and future possibilities of growth factor delivery strategies are outlined for periodontal regeneration. First, the role of those growth factors that have been implicated in the periodontal healing/regeneration process, general requirements for their delivery, and the different material types available are described. A detailed discussion follows of current strategies for the selection of devices for localized growth factor delivery, with particular emphasis placed upon their advantages and disadvantages and future prospects for ongoing studies in reconstructing the tooth supporting apparatus.

Prognostic Significance of Human Apurinic/Apyrimidinic Endonuclease (APE/Ref-1) Expression in Rectal Cancer Treated With Preoperative Radiochemotherapy

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

Kim, Jun-Sang, E-mail: k423j@cnu.ac.kr; Cancer Research Institute, Chungnam National University, Daejeon; Kim, Jin-Man

Purpose: Human apurinic endonuclease/redox factor 1 (APE/Ref-1) mediates repair of radiation-induced DNA lesions and regulates transcription via redox-based activation. We investigated the predictive and prognostic significance of APE/Ref-1 expression in pretreatment biopsy specimens in locally advanced rectal cancer (LARC) (cT3-T4 or N+). Methods and Materials: APE/Ref-1 expression was analyzed by immunohistochemistry in pretreatment biopsy specimens obtained from 83 patients with LARC. Patients received preoperative radiotherapy of 50.4 Gy in 28 fractions, combined with oral capecitabine and leucovorin chemotherapy, followed by curative surgery. The prognostic significance of various clinicopathologic characteristics, including APE/Ref-1 protein expression, was evaluated. Results: APE/Ref-1 was expressed inmore » 97% of patient samples. Exclusive APE/Ref-1 nuclear staining was observed in 49 of 83 samples (59%), and mixed nuclear and cytoplasmic staining was observed in 31 samples (37%). APE/Ref-1 nuclear expression levels were low in 49 patients (59%) and high in 34 patients (41%). The level of APE/Ref-1 nuclear expression was not a prognostic factor for overall and disease-free survival. Cytoplasmic expression of APE/Ref-1 was a borderline-significant predictive factor for pathologic tumor response (p = 0.08) and a significant prognostic factor for disease-free survival, as shown by univariate analysis (p = 0.037). Multivariate analysis confirmed that cytoplasmic localization of APE/Ref-1 is a significant predictor of disease-free survival (hazard ratio, 0.45; p = 0.046). Conclusions: APE/Ref-1 was expressed in a majority of pretreatment biopsy specimens from patients with LARC. The level of APE/Ref-1 nuclear expression was not a significant predictive and prognostic factor; however, cytoplasmic localization of the protein was negatively associated with disease-free survival. These results indicate that cytoplasmic expression of APE/Ref-1 represents an adverse prognostic factor for LARC patients who receive preoperative radiochemotherapy.« less

Percutaneous Lung Thermal Ablation of Non-surgical Clinical N0 Non-small Cell Lung Cancer: Results of Eight Years’ Experience in 87 Patients from Two Centers

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

Palussiere, Jean, E-mail: J.Palussiere@bordeaux.unicancer.fr; Lagarde, Philippe, E-mail: P.Lagarde@bordeaux.unicancer.fr; Aupérin, Anne, E-mail: auperin@igr.fr

2015-02-15

PurposeTo evaluate the survival outcomes of percutaneous thermal ablation (RFA + microwaves) for patients presenting N0 non-small-cell lung cancer (NSCLC) ineligible for surgery.Materials and MethodsEighty-seven patients from two comprehensive cancer centers were included. Eighty-two patients were treated with RFA electrodes and five with microwave antenna. Overall survival (OS) and disease-free survival (DFS) were estimated and predictive factors of local tumor progression, OS and DFS identified and compared by univariate and multivariate analysesResultsMedian follow-up was 30.5 months (interquartile range 16.7–51) and tumor size was 21 mm (range 10–54 mm). Treatment was incomplete for 14 patients with a local tumor progression of 11.5, 18.3, and 21.1 % atmore » 1, 2, and 3 years, respectively. Two patients presented with neurological (grade III or IV) complications, and one died of respiratory and multivisceral failure as a result of the procedure at 29 days. In univariate analysis, increasing tumor size (P = 0.003) was the only predictive factor related to risk of local tumor progression. 5-year OS and DFS were 58.1 and 27.9 %, respectively. Sex (P = 0.044), pathology (P = 0.032), and tumor size >2 cm (P = 0.046) were prognostic factors for DFS. In multivariate analysis, pathology (P = 0.033) and tumor size >2 cm (P = 0.032) were independent prognostic factors for DFS.ConclusionsOversized and overlapping ablation of N0 NSCLC was well tolerated, effective, with few local tumor progressions, even over long-term follow-up. Increasing tumor size was the main prognostic factor linked to OS, DFS, and local tumor progression.« less

Whose Disease Will Recur After Mastectomy for Early Stage, Node-Negative Breast Cancer? A Systematic Review.

PubMed

Kent, Collin; Horton, Janet; Blitzblau, Rachel; Koontz, Bridget F

2015-12-01

Effective local control is associated with improved overall survival, particularly for women with early-stage cancers. No other local therapy is typically offered to women with T1-2 N0 breast cancer after mastectomy, although in select women the 5-year local recurrence rate can be as high as 20%. Therefore, accurately predicting the women who are at highest risk for recurrence after mastectomy will identify those who might benefit from more aggressive adjuvant treatment. A systematic search was conducted identifying risk factors associated with locoregional recurrence, including age, menopausal status, receptor status, lymphovascular invasion (LVI), margin status, use of systemic therapy, size, grade, and genomic classifer score. Although associations varied among studies, the risk factors most consistently identified were age ≤ 40 years, LVI, positive/close margin, and larger tumor size. In women with multiple high risk factors, risk of local recurrence was as high as 20% at 10 years. Additional multicenter studies are needed to investigate risk factors for locoregional recurrence after mastectomy without radiotherapy in T1-2N0 breast cancer. Consideration of additional adjuvant local therapy might be warranted in a subset of women at high risk of local recurrence. Copyright © 2015 Elsevier Inc. All rights reserved.

Redox Protein Expression Predicts Radiotherapeutic Response in Early-Stage Invasive Breast Cancer Patients

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

Woolston, Caroline M.; Al-Attar, Ahmad; Storr, Sarah J.

2011-04-01

Purpose: Early-stage invasive breast cancer patients have commonly undergone breast-conserving surgery and radiotherapy. In a large majority of these patients, the treatment is effective; however, a proportion will develop local recurrence. Deregulated redox systems provide cancer cells protection from increased oxidative stress, such as that induced by ionizing radiation. Therefore, the expression of redox proteins was examined in tumor specimens from this defined cohort to determine whether such expression could predict response. Methods and Materials: The nuclear and cytoplasmic expression of nine redox proteins (glutathione, glutathione reductase, glutaredoxin, glutathione peroxidase 1, 3, and 4, and glutathione S-transferase-{theta}, -{pi}, and -{alpha})more » was assessed using conventional immunohistochemistry on a tissue microarray of 224 tumors. Results: A high cytoplasmic expression of glutathione S-transferase-{theta} significantly correlated with a greater risk of local recurrence (p = .008) and, when combined with a low nuclear expression (p = .009), became an independent predictive factor (p = .002) for local recurrence. High cytoplasmic expression of glutathione S-transferase-{theta} also correlated with a worse overall survival (p = .009). Low nuclear and cytoplasmic expression of glutathione peroxidase 3 (p = .002) correlated with a greater risk of local recurrence and was an independent predictive factor (p = .005). These proteins did not correlate with tumor grade, suggesting their function might be specific to the regulation of oxidative stress rather than alterations of tumor phenotype. Only nuclear (p = .005) and cytoplasmic (p = .001) expression of glutathione peroxidase 4 correlated with the tumor grade. Conclusions: Our results support the use of redox protein expression, namely glutathione S-transferase-{theta} and glutathione peroxidase 3, to predict the response to radiotherapy in early-stage breast cancer patients. If incorporated into routine diagnostic tests, they have the potential to aid clinicians in their stratification of patients into more tailored treatment regimens. Future targeted therapies to these systems might improve the efficacy of reactive oxygen species-inducing therapies, such as radiotherapy.« less

Towards the prediction of essential genes by integration of network topology, cellular localization and biological process information

PubMed Central

2009-01-01

Background The identification of essential genes is important for the understanding of the minimal requirements for cellular life and for practical purposes, such as drug design. However, the experimental techniques for essential genes discovery are labor-intensive and time-consuming. Considering these experimental constraints, a computational approach capable of accurately predicting essential genes would be of great value. We therefore present here a machine learning-based computational approach relying on network topological features, cellular localization and biological process information for prediction of essential genes. Results We constructed a decision tree-based meta-classifier and trained it on datasets with individual and grouped attributes-network topological features, cellular compartments and biological processes-to generate various predictors of essential genes. We showed that the predictors with better performances are those generated by datasets with integrated attributes. Using the predictor with all attributes, i.e., network topological features, cellular compartments and biological processes, we obtained the best predictor of essential genes that was then used to classify yeast genes with unknown essentiality status. Finally, we generated decision trees by training the J48 algorithm on datasets with all network topological features, cellular localization and biological process information to discover cellular rules for essentiality. We found that the number of protein physical interactions, the nuclear localization of proteins and the number of regulating transcription factors are the most important factors determining gene essentiality. Conclusion We were able to demonstrate that network topological features, cellular localization and biological process information are reliable predictors of essential genes. Moreover, by constructing decision trees based on these data, we could discover cellular rules governing essentiality. PMID:19758426

Impacts of West Nile Virus on wildlife

USGS Publications Warehouse

Saito, E.K.; Wild, M.A.

2004-01-01

The recent epidemic of West Nile virus in the United States proved to be unexpectedly active and was the largest epidemic of the virus ever recorded. Much remains to be discovered about the ecology and epidemiology of West Nile virus in the United States, including which species are important in maintaining the virus in nature, why some species are more susceptible to lethal infection, and what environmental factors are important in predicting future epidemics. These factors will likely vary regionally, depending on local ecological characteristics. Until scientists better understand the virus and factors influencing its activity, predicting its effects for future seasons is impossible. However, experts are certain about one thing: West Nile virus is here to stay.

Predictors of response to intra-articular steroid injections in patients with osteoarthritis of the knee joint.

PubMed

Fatimah, Nibah; Salim, Babur; Raja, Ejaz-Ul-Haq; Nasim, Amjad

2016-10-01

This study aimed to determine the factors associated with response to intra-articular steroid injection (IASI) in patients with knee joint osteoarthritis. One hundred seventy-four female patients, age ranging from 30 to 80 years, diagnosed to have osteoarthritis of the knee joint, were given IASI. Response to IASI was assessed by using WOMAC and VAS at 2 weeks, 4 weeks and 3 months. At 3 months, the subjects were categorized as responders, partial responders and non-responders to treatment by IASI. Various factors were narrowed down to see their effect on response, namely age, BMI, smoking habits, comorbidities, presence of clinical effusion, radiographic score, local knee tenderness, range of movement and socioeconomic status. One hundred twenty-four patients completed the study. 16.1 % showed 50 % or more improvement in WOMAC score at 3 months post IASI therapy, whereas 38.7 % of OA patients had more than 50 % improvement in VAS score. Out of all factors, range of movement, local knee tenderness and radiographic score of the affected joint are the three parameters which can predict the improvement in WOMAC score after 3 months of IASI therapy (P = 0.013, P = 0.045 and P = 0.000, respectively). Age of the patient can predict improvement in VAS at 3 months post IASI (P = 0.027). We conclude that age, range of movement, local knee tenderness and radiographic score of the affected joint can predict response to IASI after 3 months of IASI therapy.

Recursion equations in predicting band width under gradient elution.

PubMed

Liang, Heng; Liu, Ying

2004-06-18

The evolution of solute zone under gradient elution is a typical problem of non-linear continuity equation since the local diffusion coefficient and local migration velocity of the mass cells of solute zones are the functions of position and time due to space- and time-variable mobile phase composition. In this paper, based on the mesoscopic approaches (Lagrangian description, the continuity theory and the local equilibrium assumption), the evolution of solute zones in space- and time-dependent fields is described by the iterative addition of local probability density of the mass cells of solute zones. Furthermore, on macroscopic levels, the recursion equations have been proposed to simulate zone migration and spreading in reversed-phase high-performance liquid chromatography (RP-HPLC) through directly relating local retention factor and local diffusion coefficient to local mobile phase concentration. This new approach differs entirely from the traditional theories on plate concept with Eulerian description, since band width recursion equation is actually the accumulation of local diffusion coefficients of solute zones to discrete-time slices. Recursion equations and literature equations were used in dealing with same experimental data in RP-HPLC, and the comparison results show that the recursion equations can accurately predict band width under gradient elution.

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.

Subjective Social Status and Well-Being: The Role of Referent Abstraction.

PubMed

Haught, Heather M; Rose, Jason; Geers, Andrew; Brown, Jill A

2015-01-01

Subjective social status (SSS) has been shown to predict well-being and mental health, above and beyond objective social status (OSS). However, little is known about the factors that moderate this relationship. Two studies explored whether the link between SSS and well-being varied depending upon the referent used for comparison in SSS judgments. Participants judged their well-being and SSS in comparison to referents that varied in abstraction. A confirmatory factor analysis on SSS judgments yielded two factors: (a) SSS perceptions toward global referents and (b) SSS perceptions toward local referents. SSS relative to a global referent was a better predictor of depression (Studies 1 and 2), life satisfaction (Studies 1 and 2), and self-esteem (Study 2) than SSS relative to a local referent. These findings have theoretical implications for understanding how people differentiate between local vs. global referents and practical implications for status-related health disparities.

Predictability and context determine differences in conflict monitoring between adolescence and adulthood.

PubMed

Chmielewski, Witold X; Roessner, Veit; Beste, Christian

2015-10-01

The ability to link contextual information to actions is an important aspect of conflict monitoring and response selection. These mechanisms depend on medial prefrontal networks. Although these areas undergo a protracted development from adolescence to adulthood, it has remained elusive how the influence of contextual information on conflict monitoring is modulated between adolescence and adulthood. Using event-related potentials (ERPs) and source localization techniques we show that the ability to link contextual information to actions is altered and that the predictability of upcoming events is an important factor to consider in this context. In adolescents, conflict monitoring functions are not as much modulated by predictability factors as in adults. It seems that adults exhibit a stronger anticipation of upcoming events than adolescents. This results in disadvantages for adults when the upcoming context is not predictable. In adolescents, problems to predict upcoming events therefore turn out to be beneficial. Two cognitive-neurophysiological factors are important for this: The first factor is related to altered conflict monitoring functions associated with modulations of neural activity in the medial frontal cortex. The second factor is related to altered perceptual processing of target stimuli associated with modulations of neural activity in parieto-occipital areas. Copyright © 2015 Elsevier B.V. All rights reserved.

Climate fails to predict wood decomposition at regional scales

NASA Astrophysics Data System (ADS)

Bradford, Mark A.; Warren, Robert J., II; Baldrian, Petr; Crowther, Thomas W.; Maynard, Daniel S.; Oldfield, Emily E.; Wieder, William R.; Wood, Stephen A.; King, Joshua R.

2014-07-01

Decomposition of organic matter strongly influences ecosystem carbon storage. In Earth-system models, climate is a predominant control on the decomposition rates of organic matter. This assumption is based on the mean response of decomposition to climate, yet there is a growing appreciation in other areas of global change science that projections based on mean responses can be irrelevant and misleading. We test whether climate controls on the decomposition rate of dead wood--a carbon stock estimated to represent 73 +/- 6 Pg carbon globally--are sensitive to the spatial scale from which they are inferred. We show that the common assumption that climate is a predominant control on decomposition is supported only when local-scale variation is aggregated into mean values. Disaggregated data instead reveal that local-scale factors explain 73% of the variation in wood decomposition, and climate only 28%. Further, the temperature sensitivity of decomposition estimated from local versus mean analyses is 1.3-times greater. Fundamental issues with mean correlations were highlighted decades ago, yet mean climate-decomposition relationships are used to generate simulations that inform management and adaptation under environmental change. Our results suggest that to predict accurately how decomposition will respond to climate change, models must account for local-scale factors that control regional dynamics.

Geo-environmental model for the prediction of potential transmission risk of Dirofilaria in an area with dry climate and extensive irrigated crops. The case of Spain.

PubMed

Simón, Luis; Afonin, Alexandr; López-Díez, Lucía Isabel; González-Miguel, Javier; Morchón, Rodrigo; Carretón, Elena; Montoya-Alonso, José Alberto; Kartashev, Vladimir; Simón, Fernando

2014-03-01

Zoonotic filarioses caused by Dirofilaria immitis and Dirofilaria repens are transmitted by culicid mosquitoes. Therefore Dirofilaria transmission depends on climatic factors like temperature and humidity. In spite of the dry climate of most of the Spanish territory, there are extensive irrigated crops areas providing moist habitats favourable for mosquito breeding. A GIS model to predict the risk of Dirofilaria transmission in Spain, based on temperatures and rainfall data as well as in the distribution of irrigated crops areas, is constructed. The model predicts that potential risk of Dirofilaria transmission exists in all the Spanish territory. Highest transmission risk exists in several areas of Andalucía, Extremadura, Castilla-La Mancha, Murcia, Valencia, Aragón and Cataluña, where moderate/high temperatures coincide with extensive irrigated crops. High risk in Balearic Islands and in some points of Canary Islands, is also predicted. The lowest risk is predicted in Northern cold and scarcely or non-irrigated dry Southeastern areas. The existence of irrigations locally increases transmission risk in low rainfall areas of the Spanish territory. The model can contribute to implement rational preventive therapy guidelines in accordance with the transmission characteristics of each local area. Moreover, the use of humidity-related factors could be of interest in future predictions to be performed in countries with similar environmental characteristics. Copyright © 2014 Elsevier B.V. All rights reserved.

Comparison of Methods for Estimating Prevalence of Chronic Diseases and Health Behaviors for Small Geographic Areas: Boston Validation Study, 2013

PubMed Central

Holt, James B.; Zhang, Xingyou; Lu, Hua; Shah, Snehal N.; Dooley, Daniel P.; Matthews, Kevin A.; Croft, Janet B.

2017-01-01

Introduction Local health authorities need small-area estimates for prevalence of chronic diseases and health behaviors for multiple purposes. We generated city-level and census-tract–level prevalence estimates of 27 measures for the 500 largest US cities. Methods To validate the methodology, we constructed multilevel logistic regressions to predict 10 selected health indicators among adults aged 18 years or older by using 2013 Behavioral Risk Factor Surveillance System (BRFSS) data; we applied their predicted probabilities to census population data to generate city-level, neighborhood-level, and zip-code–level estimates for the city of Boston, Massachusetts. Results By comparing the predicted estimates with their corresponding direct estimates from a locally administered survey (Boston BRFSS 2010 and 2013), we found that our model-based estimates for most of the selected health indicators at the city level were close to the direct estimates from the local survey. We also found strong correlation between the model-based estimates and direct survey estimates at neighborhood and zip code levels for most indicators. Conclusion Findings suggest that our model-based estimates are reliable and valid at the city level for certain health outcomes. Local health authorities can use the neighborhood-level estimates if high quality local health survey data are not otherwise available. PMID:29049020

Development of local calibration factors and design criteria values for mechanistic-empirical pavement design.

DOT National Transportation Integrated Search

2015-08-01

A mechanistic-empirical (ME) pavement design procedure allows for analyzing and selecting pavement structures based : on predicted distress progression resulting from stresses and strains within the pavement over its design life. The Virginia : Depar...

The Complexity of Vesicle Transport Factors in Plants Examined by Orthology Search

PubMed Central

Mirus, Oliver; Scharf, Klaus-Dieter; Fragkostefanakis, Sotirios; Schleiff, Enrico

2014-01-01

Vesicle transport is a central process to ensure protein and lipid distribution in eukaryotic cells. The current knowledge on the molecular components and mechanisms of this process is majorly based on studies in Saccharomyces cerevisiae and Arabidopsis thaliana, which revealed 240 different proteinaceous factors either experimentally proven or predicted to be involved in vesicle transport. In here, we performed an orthologue search using two different algorithms to identify the components of the secretory pathway in yeast and 14 plant genomes by using the ‘core-set’ of 240 factors as bait. We identified 4021 orthologues and (co-)orthologues in the discussed plant species accounting for components of COP-II, COP-I, Clathrin Coated Vesicles, Retromers and ESCRTs, Rab GTPases, Tethering factors and SNAREs. In plants, we observed a significantly higher number of (co-)orthologues than yeast, while only 8 tethering factors from yeast seem to be absent in the analyzed plant genomes. To link the identified (co-)orthologues to vesicle transport, the domain architecture of the proteins from yeast, genetic model plant A. thaliana and agriculturally relevant crop Solanum lycopersicum has been inspected. For the orthologous groups containing (co-)orthologues from yeast, A. thaliana and S. lycopersicum, we observed the same domain architecture for 79% (416/527) of the (co-)orthologues, which documents a very high conservation of this process. Further, publically available tissue-specific expression profiles for a subset of (co-)orthologues found in A. thaliana and S. lycopersicum suggest that some (co-)orthologues are involved in tissue-specific functions. Inspection of localization of the (co-)orthologues based on available proteome data or localization predictions lead to the assignment of plastid- as well as mitochondrial localized (co-)orthologues of vesicle transport factors and the relevance of this is discussed. PMID:24844592

A Dynamical Model Reveals Gene Co-Localizations in Nucleus

PubMed Central

Yao, Ye; Lin, Wei; Hennessy, Conor; Fraser, Peter; Feng, Jianfeng

2011-01-01

Co-localization of networks of genes in the nucleus is thought to play an important role in determining gene expression patterns. Based upon experimental data, we built a dynamical model to test whether pure diffusion could account for the observed co-localization of genes within a defined subnuclear region. A simple standard Brownian motion model in two and three dimensions shows that preferential co-localization is possible for co-regulated genes without any direct interaction, and suggests the occurrence may be due to a limitation in the number of available transcription factors. Experimental data of chromatin movements demonstrates that fractional rather than standard Brownian motion is more appropriate to model gene mobilizations, and we tested our dynamical model against recent static experimental data, using a sub-diffusion process by which the genes tend to colocalize more easily. Moreover, in order to compare our model with recently obtained experimental data, we studied the association level between genes and factors, and presented data supporting the validation of this dynamic model. As further applications of our model, we applied it to test against more biological observations. We found that increasing transcription factor number, rather than factory number and nucleus size, might be the reason for decreasing gene co-localization. In the scenario of frequency- or amplitude-modulation of transcription factors, our model predicted that frequency-modulation may increase the co-localization between its targeted genes. PMID:21760760

Influence of phenotype at diagnosis and of other potential prognostic factors on the course of inflammatory bowel disease.

PubMed

Romberg-Camps, M J L; Dagnelie, P C; Kester, A D M; Hesselink-van de Kruijs, M A M; Cilissen, M; Engels, L G J B; Van Deursen, C; Hameeteman, W H A; Wolters, F L; Russel, M G V M; Stockbrügger, R W

2009-02-01

Disease course in inflammatory bowel disease (IBD) is variable and difficult to predict. To optimize prognosis, it is of interest to identify phenotypic characteristics at disease onset and other prognostic factors that predict disease course. The aim of this study was to evaluate such factors in a population-based IBD group. IBD patients diagnosed between 1 January 1991 and 1 January 2003 were included. A follow-up questionnaire was developed and medical records were reviewed. Patients were classified according to phenotype at diagnosis and risk factors were registered. Disease severity, cumulative medication use, and "surgical" and "nonsurgical" recurrence rates were calculated as outcome parameters. In total, 476 Crohn's disease (CD), 630 ulcerative colitis (UC), and 81 indeterminate colitis (IC) patients were diagnosed. In CD (mean follow-up 7.6 years), 50% had undergone resective surgery. In UC (mean follow-up 7 years), colectomy rate was 8.3%. First year cumulative recurrence rates per 100 patient-years for CD, UC, and IC were 53, 44, and 42%, respectively. In CD, small bowel localization and stricturing disease were negative prognostic factors for surgery, as was young age. Overall recurrence rate was increased by young age and current smoking. In UC, extensive colitis increased surgical risk. In UC, older age at diagnosis initially increased recurrence risk but was subsequently protective. This population-based IBD study showed high recurrence rates in the first year. In CD, small bowel localization, stricturing disease, and young age were predictive for disease recurrence. In UC, extensive colitis and older age at diagnosis were negative prognostic predictors.

Utterance rate and linguistic properties as determinants of lexical dysfluencies in children who stutter

PubMed Central

Howell, Peter; Au-Yeung, James; Pilgrim, Lesley

2007-01-01

Two important determinants of variation in stuttering frequency are utterance rate and the linguistic properties of the words being spoken. Little is known how these determinants interrelate. It is hypothesized that those linguistic factors that lead to change in word duration, alter utterance rate locally within an utterance that then gives rise to an increase in stuttering frequency. According to the hypothesis, utterance rate variation should occur locally within the linguistic segments in an utterance that is known to increase the likelihood of stuttering. The hypothesis is tested using length of tone unit as the linguistic factor. Three predictions are confirmed: Utterance rate varies locally within the tone units and this local variation affects stuttering frequency; stuttering frequency is positively related to the length of tone units; variations in utterance rate are correlated with tone unit length. Alternative theoretical formulations of these findings are considered. PMID:9921672

Development of regionalized SPFs for two-lane rural roads in Pennsylvania.

PubMed

Li, Lingyu; Gayah, Vikash V; Donnell, Eric T

2017-11-01

The American Association of State Highway and Transportation Officials' Highway Safety Manual (HSM) contains safety performance functions (SPFs) to predict annual crash frequencies for several roadway types. When applying these SPFs in a jurisdiction whose data were not used to develop the SPF, a calibration factor can be applied to adjust the expected crash frequency estimate to statewide or local conditions. Alternatively, the HSM suggests that transportation agencies may develop their own SPFs in lieu of applying the calibration factor to the HSM SPFs. However, the HSM does not provide guidance on the appropriate level of regionalization that should be adopted for either method, even though safety performance may vary considerably within a state. In light of this, the present study considers the development of local or regionalized SPFs for two-lane rural highways within the Commonwealth of Pennsylvania. Three regionalization levels were considered: statewide, engineering district and individual counties. The expected crash frequency for each level of regionalization was compared to the reported crash frequency over an eight-year analysis period. The results indicate that district-level SPFs with county-level adjustment factors provide better predictive accuracy than the development of a statewide SPF or application of the HSM-calibrated SPF. The findings suggest that there are significant differences in safety performance across engineering districts within Pennsylvania. As such, other state transportation agencies developing SPFs or using calibration factors may also consider how variations across jurisdictions will affect predicted crash frequencies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Low thrombospondin 2 expression is predictive of low tumor regression after neoadjuvant chemoradiotherapy in rectal cancer.

PubMed

Lin, Cheng-Yi; Lin, Ching-Yih; Chang, I-Wei; Sheu, Ming-Jen; Li, Chien-Feng; Lee, Sung-Wei; Lin, Li-Ching; Lee, Ying-En; He, Hong-Lin

2015-01-01

Neoadjuvant concurrent chemoradiotherapy (CCRT) followed by surgery is the mainstay of treatment for locally advanced rectal cancer. Several heparin-binding associated proteins have been reported to play a critical role in cancer progression. However, the clinical relevancies of such proteins and their associations with CCRT response in rectal cancer have not yet to be fully elucidated. The analysis of a public transcriptome of rectal cancer indicated that thrombospondin 2 (THBS2) is a predictive factor for CCRT response. Immunohistochemical analyses were conducted to evaluate the expression of THBS2 in pretreatment biopsy specimens from rectal cancer patients without distant metastasis. Furthermore, the relationships between THBS2 expression and various clinicopathological factors or survival were analyzed. Low expression of THBS2 was significantly associated with advanced pretreatment tumor (P<0.001) and nodal status (P=0.004), post-treatment tumor (P<0.001) and nodal status (P<0.001), increased vascular invasion (P=0.003), increased perineural invasion (P=0.023) and inferior tumor regression grade (P=0.015). In univariate analysis, low THBS2 expression predicted worse outcomes for disease-free survival, local recurrence-free survival and metastasis-free survival (all P<0.001). In multivariate analysis, low expression of THBS2 still served as a negative prognostic factor for disease-free survival (Hazard ratio=3.057, P=0.002) and metastasis-free survival (Hazard ratio=3.362, P=0.012). Low THBS2 expression was correlated with advanced disease status and low tumor regression after preoperative CCRT and that it acted as an independent negative prognostic factor in rectal cancer. THBS2 may represent a predictive biomarker for CCRT response in rectal cancer.

Relationship of Th17/Treg Cells and Radiation Pneumonia in Locally Advanced Esophageal Carcinoma.

PubMed

Wang, Yan; Xu, Gang; Wang, Jie; Li, Xin-Hua; Sun, Ping; Zhang, Wei; Li, Jun-Xia; Wu, Chao-Yang

2017-08-01

Radiation pneumonia is a main side-effect that has limited the clinical usage of radiotherapy in locally advanced esophageal carcinoma. T helper cells 17 (Th 17) and T regulatory cells (Tregs) play an important role in inflammatory diseases. The balance between Treg and Th17 cells is a key factor in the progression of many inflammatory and autoimmune diseases. Whether Tregs and Th17 cells are predictive factors of radiation pneumonia has not yet been reported. In this study, we investigated the relationships of Treg/Th17 cells and radiation pneumonia in patients with locally advanced esophageal cancer who received radiotherapy. One hundred and forty-eight patients with locally advanced esophageal cancer who received radical and palliative radiotherapy were enrolled. The levels of Th17 and Treg cells in the blood of patients were detected using flow cytometry at the time point of pre-radiotherapy, 1st, 2nd, 3rd, 4th, 5th and 6th week from the start of radiation and 4 weeks after completion of radiotherapy. Radiation pneumonia was evaluated according to Radiation Therapy Oncology Group's acute radiation pneumonia standards, with the endpoint being grade 2 or above radiation pneumonia. There were 24 cases of radiation pneumonia in 148 cases of locally advanced esophageal cancer patients who underwent radiotherapy. Th17 cells increased and, in contrast, Treg cells decreased in the radiation pneumonia group. The change in the ratio of Th17/Treg was more pronounced and the difference was statistically significant from the 5th week after irradiation compared to patients with no radiation pneumonia (p<0.05). There was no significant difference in dosimetric parameters, including V5, V20, V30 and mean lung dose (MLD) and clinical factors, such as gender, age, smoking history, history of surgery and chemotherapy. The ratio of Th17/Treg cells may be an effective predictive factor of radiation pneumonia. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Farm Management, Environment, and Weather Factors Jointly Affect the Probability of Spinach Contamination by Generic Escherichia coli at the Preharvest Stage

PubMed Central

Navratil, Sarah; Gregory, Ashley; Bauer, Arin; Srinath, Indumathi; Szonyi, Barbara; Nightingale, Kendra; Anciso, Juan; Jun, Mikyoung; Han, Daikwon; Lawhon, Sara; Ivanek, Renata

2014-01-01

The National Resources Information (NRI) databases provide underutilized information on the local farm conditions that may predict microbial contamination of leafy greens at preharvest. Our objective was to identify NRI weather and landscape factors affecting spinach contamination with generic Escherichia coli individually and jointly with farm management and environmental factors. For each of the 955 georeferenced spinach samples (including 63 positive samples) collected between 2010 and 2012 on 12 farms in Colorado and Texas, we extracted variables describing the local weather (ambient temperature, precipitation, and wind speed) and landscape (soil characteristics and proximity to roads and water bodies) from NRI databases. Variables describing farm management and environment were obtained from a survey of the enrolled farms. The variables were evaluated using a mixed-effect logistic regression model with random effects for farm and date. The model identified precipitation as a single NRI predictor of spinach contamination with generic E. coli, indicating that the contamination probability increases with an increasing mean amount of rain (mm) in the past 29 days (odds ratio [OR] = 3.5). The model also identified the farm's hygiene practices as a protective factor (OR = 0.06) and manure application (OR = 52.2) and state (OR = 108.1) as risk factors. In cross-validation, the model showed a solid predictive performance, with an area under the receiver operating characteristic (ROC) curve of 81%. Overall, the findings highlighted the utility of NRI precipitation data in predicting contamination and demonstrated that farm management, environment, and weather factors should be considered jointly in development of good agricultural practices and measures to reduce produce contamination. PMID:24509926

Procedures for adjusting regional regression models of urban-runoff quality using local data

USGS Publications Warehouse

Hoos, A.B.; Sisolak, J.K.

1993-01-01

Statistical operations termed model-adjustment procedures (MAP?s) can be used to incorporate local data into existing regression models to improve the prediction of urban-runoff quality. Each MAP is a form of regression analysis in which the local data base is used as a calibration data set. Regression coefficients are determined from the local data base, and the resulting `adjusted? regression models can then be used to predict storm-runoff quality at unmonitored sites. The response variable in the regression analyses is the observed load or mean concentration of a constituent in storm runoff for a single storm. The set of explanatory variables used in the regression analyses is different for each MAP, but always includes the predicted value of load or mean concentration from a regional regression model. The four MAP?s examined in this study were: single-factor regression against the regional model prediction, P, (termed MAP-lF-P), regression against P,, (termed MAP-R-P), regression against P, and additional local variables (termed MAP-R-P+nV), and a weighted combination of P, and a local-regression prediction (termed MAP-W). The procedures were tested by means of split-sample analysis, using data from three cities included in the Nationwide Urban Runoff Program: Denver, Colorado; Bellevue, Washington; and Knoxville, Tennessee. The MAP that provided the greatest predictive accuracy for the verification data set differed among the three test data bases and among model types (MAP-W for Denver and Knoxville, MAP-lF-P and MAP-R-P for Bellevue load models, and MAP-R-P+nV for Bellevue concentration models) and, in many cases, was not clearly indicated by the values of standard error of estimate for the calibration data set. A scheme to guide MAP selection, based on exploratory data analysis of the calibration data set, is presented and tested. The MAP?s were tested for sensitivity to the size of a calibration data set. As expected, predictive accuracy of all MAP?s for the verification data set decreased as the calibration data-set size decreased, but predictive accuracy was not as sensitive for the MAP?s as it was for the local regression models.

Olive flowering phenology variation between different cultivars in Spain and Italy: modeling analysis

NASA Astrophysics Data System (ADS)

Garcia-Mozo, H.; Orlandi, F.; Galan, C.; Fornaciari, M.; Romano, B.; Ruiz, L.; Diaz de La Guardia, C.; Trigo, M. M.; Chuine, I.

2009-03-01

Phenology data are sensitive data to identify how plants are adapted to local climate and how they respond to climatic changes. Modeling flowering phenology allows us to identify the meteorological variables determining the reproductive cycle. Phenology of temperate of woody plants is assumed to be locally adapted to climate. Nevertheless, recent research shows that local adaptation may not be an important constraint in predicting phenological responses. We analyzed variations in flowering dates of Olea europaea L. at different sites of Spain and Italy, testing for a genetic differentiation of flowering phenology among olive varieties to estimate whether local modeling is necessary for olive or not. We build models for the onset and peak dates flowering in different sites of Andalusia and Puglia. Process-based phenological models using temperature as input variable and photoperiod as the threshold date to start temperature accumulation were developed to predict both dates. Our results confirm and update previous results that indicated an advance in olive onset dates. The results indicate that both internal and external validity were higher in the models that used the photoperiod as an indicator to start to cumulate temperature. The use of the unified model for modeling the start and peak dates in the different localities provides standardized results for the comparative study. The use of regional models grouping localities by varieties and climate similarities indicate that local adaptation would not be an important factor in predicting olive phenological responses face to the global temperature increase.

Factors associated with self-reported health: implications for screening level community-based health and environmental studies

EPA Science Inventory

BACKGROUND: Advocates for environmental justice, local, state, and national public health officials, exposure scientists, need broad-based heath indices to identify vulnerable communities. Longitudinal studies show that perception of current health status predicts subsequent mort...

Improving spatial prediction of Schistosoma haematobium prevalence in southern Ghana through new remote sensors and local water access profiles.

PubMed

Kulinkina, Alexandra V; Walz, Yvonne; Koch, Magaly; Biritwum, Nana-Kwadwo; Utzinger, Jürg; Naumova, Elena N

2018-06-04

Schistosomiasis is a water-related neglected tropical disease. In many endemic low- and middle-income countries, insufficient surveillance and reporting lead to poor characterization of the demographic and geographic distribution of schistosomiasis cases. Hence, modeling is relied upon to predict areas of high transmission and to inform control strategies. We hypothesized that utilizing remotely sensed (RS) environmental data in combination with water, sanitation, and hygiene (WASH) variables could improve on the current predictive modeling approaches. Schistosoma haematobium prevalence data, collected from 73 rural Ghanaian schools, were used in a random forest model to investigate the predictive capacity of 15 environmental variables derived from RS data (Landsat 8, Sentinel-2, and Global Digital Elevation Model) with fine spatial resolution (10-30 m). Five methods of variable extraction were tested to determine the spatial linkage between school-based prevalence and the environmental conditions of potential transmission sites, including applying the models to known human water contact locations. Lastly, measures of local water access and groundwater quality were incorporated into RS-based models to assess the relative importance of environmental and WASH variables. Predictive models based on environmental characterization of specific locations where people contact surface water bodies offered some improvement as compared to the traditional approach based on environmental characterization of locations where prevalence is measured. A water index (MNDWI) and topographic variables (elevation and slope) were important environmental risk factors, while overall, groundwater iron concentration predominated in the combined model that included WASH variables. The study helps to understand localized drivers of schistosomiasis transmission. Specifically, unsatisfactory water quality in boreholes perpetuates reliance of surface water bodies, indirectly increasing schistosomiasis risk and resulting in rapid reinfection (up to 40% prevalence six months following preventive chemotherapy). Considering WASH-related risk factors in schistosomiasis prediction can help shift the focus of control strategies from treating symptoms to reducing exposure.

Management of health care expenditure by soft computing methodology

NASA Astrophysics Data System (ADS)

Maksimović, Goran; Jović, Srđan; Jovanović, Radomir; Aničić, Obrad

2017-01-01

In this study was managed the health care expenditure by soft computing methodology. The main goal was to predict the gross domestic product (GDP) according to several factors of health care expenditure. Soft computing methodologies were applied since GDP prediction is very complex task. The performances of the proposed predictors were confirmed with the simulation results. According to the results, support vector regression (SVR) has better prediction accuracy compared to other soft computing methodologies. The soft computing methods benefit from the soft computing capabilities of global optimization in order to avoid local minimum issues.

Ecological and evolutionary drivers of the elevational gradient of diversity.

PubMed

Laiolo, Paola; Pato, Joaquina; Obeso, José Ramón

2018-05-02

Ecological, evolutionary, spatial and neutral theories make distinct predictions and provide distinct explanations for the mechanisms that control the relationship between diversity and the environment. Here, we test predictions of the elevational diversity gradient focusing on Iberian bumblebees, grasshoppers and birds. Processes mediated by local abundance and regional diversity concur in explaining local diversity patterns along elevation. Effects expressed through variation in abundance were similar among taxa and point to the overriding role of a physical factor, temperature. This determines how energy is distributed among individuals and ultimately how the resulting pattern of abundance affects species incidence. Effects expressed through variation in regional species pools depended instead on taxon-specific evolutionary history, and lead to diverging responses under similar environmental pressures. Local filters and regional variation also explain functional diversity gradients, in line with results from species richness that indicate an (local) ecological and (regional) historical unfolding of diversity-elevation relationships. © 2018 John Wiley & Sons Ltd/CNRS.

Germination behaviour of annual plants under changing climatic conditions: separating local and regional environmental effects.

PubMed

Petrů, Martina; Tielbörger, Katja

2008-04-01

The role of local adaptation and factors other than climate in determining extinction probabilities of species under climate change has not been yet explicitly studied. Here we performed a field experiment with annual plants growing along a steep climatic gradient in Israel to isolate climatic effects for local trait expression. The focus trait was seed dormancy, for which many theoretical predictions exist regarding climate-driven optimal germination behaviour. We evaluated how germination is consistent with theory, indicating local adaptation to current and changing climatic conditions, and how it varies among species and between natural and standardised soil conditions. We reciprocally sowed seeds from three or four origins for each of three annual species, Biscutella didyma, Bromus fasciculatus and Hymenocarpos circinnatus, in their home and neighbouring sowing locations along an aridity gradient. Our predictions were: lower germination fraction for seeds from more arid origins, and higher germination at wetter sowing locations for all seed origins. By sowing seeds in both local and standard soil, we separated climatic effects from local conditions. At the arid sowing location, two species supported the prediction of low germination of drier seed origins, but differences between seed origins at the other sites were not substantial. There were no clear rainfall effects on germination. Germination fractions were consistently lower on local soil than on standard soil, indicating the important role of soil type and neighbour conditions for trait expression. Local environmental conditions may override effects of climate and so should be carefully addressed in future studies testing for the potential of species to adapt or plastically respond to climate change.

Lack of congruence in species diversity indices and community structures of planktonic groups based on local environmental factors.

PubMed

Doi, Hideyuki; Chang, Kwang-Hyeon; Nishibe, Yuichiro; Imai, Hiroyuki; Nakano, Shin-ichi

2013-01-01

The importance of analyzing the determinants of biodiversity and community composition by using multiple trophic levels is well recognized; however, relevant data are lacking. In the present study, we investigated variations in species diversity indices and community structures of the plankton taxonomic groups-zooplankton, rotifers, ciliates, and phytoplankton-under a range of local environmental factors in pond ecosystems. For each planktonic group, we estimated the species diversity index by using linear models and analyzed the community structure by using canonical correspondence analysis. We showed that the species diversity indices and community structures varied among the planktonic groups and according to local environmental factors. The observed lack of congruence among the planktonic groups may have been caused by niche competition between groups with similar trophic guilds or by weak trophic interactions. Our findings highlight the difficulty of predicting total biodiversity within a system, based upon a single taxonomic group. Thus, to conserve the biodiversity of an ecosystem, it is crucial to consider variations in species diversity indices and community structures of different taxonomic groups, under a range of local conditions.

Evaluation of backscatter dose from internal lead shielding in clinical electron beams using EGSnrc Monte Carlo simulations.

PubMed

De Vries, Rowen J; Marsh, Steven

2015-11-08

Internal lead shielding is utilized during superficial electron beam treatments of the head and neck, such as lip carcinoma. Methods for predicting backscattered dose include the use of empirical equations or performing physical measurements. The accuracy of these empirical equations required verification for the local electron beams. In this study, a Monte Carlo model of a Siemens Artiste linac was developed for 6, 9, 12, and 15 MeV electron beams using the EGSnrc MC package. The model was verified against physical measurements to an accuracy of better than 2% and 2mm. Multiple MC simulations of lead interfaces at different depths, corresponding to mean electron energies in the range of 0.2-14 MeV at the interfaces, were performed to calculate electron backscatter values. The simulated electron backscatter was compared with current empirical equations to ascertain their accuracy. The major finding was that the current set of backscatter equations does not accurately predict electron backscatter, particularly in the lower energies region. A new equation was derived which enables estimation of electron backscatter factor at any depth upstream from the interface for the local treatment machines. The derived equation agreed to within 1.5% of the MC simulated electron backscatter at the lead interface and upstream positions. Verification of the equation was performed by comparing to measurements of the electron backscatter factor using Gafchromic EBT2 film. These results show a mean value of 0.997 ± 0.022 to 1σ of the predicted values of electron backscatter. The new empirical equation presented can accurately estimate electron backscatter factor from lead shielding in the range of 0.2 to 14 MeV for the local linacs.

Evaluation of backscatter dose from internal lead shielding in clinical electron beams using EGSnrc Monte Carlo simulations

PubMed Central

Marsh, Steven

2015-01-01

Internal lead shielding is utilized during superficial electron beam treatments of the head and neck, such as lip carcinoma. Methods for predicting backscattered dose include the use of empirical equations or performing physical measurements. The accuracy of these empirical equations required verification for the local electron beams. In this study, a Monte Carlo model of a Siemens Artiste linac was developed for 6, 9, 12, and 15 MeV electron beams using the EGSnrc MC package. The model was verified against physical measurements to an accuracy of better than 2% and 2 mm. Multiple MC simulations of lead interfaces at different depths, corresponding to mean electron energies in the range of 0.2–14 MeV at the interfaces, were performed to calculate electron backscatter values. The simulated electron backscatter was compared with current empirical equations to ascertain their accuracy. The major finding was that the current set of backscatter equations does not accurately predict electron backscatter, particularly in the lower energies region. A new equation was derived which enables estimation of electron backscatter factor at any depth upstream from the interface for the local treatment machines. The derived equation agreed to within 1.5% of the MC simulated electron backscatter at the lead interface and upstream positions. Verification of the equation was performed by comparing to measurements of the electron backscatter factor using Gafchromic EBT2 film. These results show a mean value of 0.997±0.022 to 1σ of the predicted values of electron backscatter. The new empirical equation presented can accurately estimate electron backscatter factor from lead shielding in the range of 0.2 to 14 MeV for the local linacs. PACS numbers: 87.53.Bn, 87.55.K‐, 87.56.bd PMID:26699566

Cross-scale assessment of potential habitat shifts in a rapidly changing climate

USGS Publications Warehouse

Jarnevich, Catherine S.; Holcombe, Tracy R.; Bella, Elizabeth S.; Carlson, Matthew L.; Graziano, Gino; Lamb, Melinda; Seefeldt, Steven S.; Morisette, Jeffrey T.

2014-01-01

We assessed the ability of climatic, environmental, and anthropogenic variables to predict areas of high-risk for plant invasion and consider the relative importance and contribution of these predictor variables by considering two spatial scales in a region of rapidly changing climate. We created predictive distribution models, using Maxent, for three highly invasive plant species (Canada thistle, white sweetclover, and reed canarygrass) in Alaska at both a regional scale and a local scale. Regional scale models encompassed southern coastal Alaska and were developed from topographic and climatic data at a 2 km (1.2 mi) spatial resolution. Models were applied to future climate (2030). Local scale models were spatially nested within the regional area; these models incorporated physiographic and anthropogenic variables at a 30 m (98.4 ft) resolution. Regional and local models performed well (AUC values > 0.7), with the exception of one species at each spatial scale. Regional models predict an increase in area of suitable habitat for all species by 2030 with a general shift to higher elevation areas; however, the distribution of each species was driven by different climate and topographical variables. In contrast local models indicate that distance to right-of-ways and elevation are associated with habitat suitability for all three species at this spatial level. Combining results from regional models, capturing long-term distribution, and local models, capturing near-term establishment and distribution, offers a new and effective tool for highlighting at-risk areas and provides insight on how variables acting at different scales contribute to suitability predictions. The combinations also provides easy comparison, highlighting agreement between the two scales, where long-term distribution factors predict suitability while near-term do not and vice versa.

A Superior Kirchhoff Method for Aeroacoustic Noise Prediction: The Ffowcs Williams-Hawkings Equation

NASA Technical Reports Server (NTRS)

Brentner, Kenneth S.

1997-01-01

The prediction of aeroacoustic noise is important; all new aircraft must meet noise certification requirements. Local noise standards can be even more stringent. The NASA noise reduction goal is to reduce perceived noise levels by a factor of two in 10 years. The objective of this viewgraph presentation is to demonstrate the superiority of the FW-H approach over the Kirchoff method for aeroacoustics, both analytically and numerically.

Lifestyle and Genetic Predictors of Stiffness Index in Community-dwelling Elderly Korean Men and Women.

PubMed

Park, Kyung-Ae; Park, Yeon-Hwan; Suh, Min-Hee; Choi-Kwon, Smi

2015-09-01

Differing lifestyle, nutritional, and genetic factors may lead to a differing stiffness index (SI) determined by quantitative ultrasound in elderly men and women. The purpose of this study was to determine SI and the gender-specific factors associated with low SI in a Korean elderly cohort. This was a cross-sectional descriptive study identifying the gender-specific factors related to SI in 252 men and women aged 65 years and greater from local senior centers in Seoul, Korea between January and February 2009. The mean SI of elderly men was significantly higher than that of the women's. A multiple regression analysis reveals that age, nutritional status, and physical activity were predictive factors of lower SI in men, whereas age, alcohol consumption, educational level, and genetic polymorphism were predictive factors for elderly women. Low SI was common in both elderly men and women. We found gender differences in factors linked to low SI. In multiple regression analysis, nutritional status and physical activity were more important factors in men, whereas alcohol consumption, educational level, and genetic polymorphism were significant factors predicting low SI in women. Gender-specific modifiable risk factors associated with low SI should be considered when developing osteoporosis prevention programs for the elderly. Copyright © 2015. Published by Elsevier B.V.

Predictors of responses to corticosteroids for anorexia in advanced cancer patients: a multicenter prospective observational study.

PubMed

Matsuo, Naoki; Morita, Tatsuya; Matsuda, Yoshinobu; Okamoto, Kenichiro; Matsumoto, Yoshihisa; Kaneishi, Keisuke; Odagiri, Takuya; Sakurai, Hiroki; Katayama, Hideki; Mori, Ichiro; Yamada, Hirohide; Watanabe, Hiroaki; Yokoyama, Taro; Yamaguchi, Takashi; Nishi, Tomohiro; Shirado, Akemi; Hiramoto, Shuji; Watanabe, Toshio; Kohara, Hiroyuki; Shimoyama, Satofumi; Aruga, Etsuko; Baba, Mika; Sumita, Koki; Iwase, Satoru

2017-01-01

Although corticosteroids are widely used to relieve anorexia, information regarding the factors predicting responses to corticosteroids remains limited. The purpose of the study is to identify potential factors predicting responses to corticosteroids for anorexia in advanced cancer patients. Inclusion criteria for this multicenter prospective observational study were patients who had metastatic or locally advanced cancer and had an anorexia intensity score of 4 or more on a 0-10 Numerical Rating Scale (NRS). Univariate and multivariate analyses were conducted to identify the factors predicting ≥2-point reduction in NRS on day 3. Among 180 patients who received corticosteroids, 99 (55 %; 95 % confidence interval [CI], 47-62 %) had a response with ≥2-point reduction. Factors that significantly predicted responses were Palliative Performance Scale (PPS) > 40 and absence of drowsiness. In addition, factors that tended to be associated with ≥2-point reduction in NRS included PS 0-3, absence of diabetes mellitus, absence of peripheral edema, presence of lung metastasis, absence of peritoneal metastasis, baseline anorexia NRS of >6, presence of pain, and presence of constipation. A multivariate analysis showed that the independent factors predicting responses were PPS of >40 (odds ratio = 2.7 [95 % CI = 1.4-5.2]), absence of drowsiness (2.6 [1.3-5.0]), and baseline NRS of >6 (2.4 [1.1-4.8]). Treatment responses to corticosteroids for anorexia may be predicted by PPS, drowsiness, and baseline symptom intensity. Larger prospective studies are needed to confirm these results.

Damping in Space Constructions

NASA Astrophysics Data System (ADS)

de Vreugd, Jan; de Lange, Dorus; Winters, Jasper; Human, Jet; Kamphues, Fred; Tabak, Erik

2014-06-01

Monolithic structures are often used in optomechanical designs for space applications to achieve high dimensional stability and to prevent possible backlash and friction phenomena. The capacity of monolithic structures to dissipate mechanical energy is however limited due to the high Q-factor, which might result in high stresses during dynamic launch loads like random vibration, sine sweeps and shock. To reduce the Q-factor in space applications, the effect of constrained layer damping (CLD) is investigated in this work. To predict the damping increase, the CLD effect is implemented locally at the supporting struts in an existing FE model of an optical instrument. Numerical simulations show that the effect of local damping treatment in this instrument could reduce the vibrational stresses with 30-50%. Validation experiments on a simple structure showed good agreement between measured and predicted damping properties. This paper presents material characterization, material modeling, numerical implementation of damping models in finite element code, numerical results on space hardware and the results of validation experiments.

Do traditional risk factors predict whether men who have sex with men engage in unprotected anal intercourse? The need for locally based research to guide interventions.

PubMed

Berg, Rigmor C; Grimes, Richard

2011-09-01

A great deal of research effort has been expended in an effort to identify the variables which most influence men who have sex with men's (MSM) unsafe sexual behaviors.While a set of predictor variables has emerged, these predict the unsafe behaviors of MSM in some locations but not in others, suggesting the need to investigate the predictive ability of these variables among MSM in previously understudied populations. Therefore, this study examined the ability of previously identified factors to predict unsafe sexual behaviors among MSM in Houston, Texas. Data were collected through a short self-report survey completed by MSM attending the Houston pride festival. The multiethnic participants (N = 109) represented a range of age, educational, and income backgrounds. Fifty-seven percent of the survey respondents had been drunk and/or high in sexual contexts, 19 percent evidenced alcohol dependency, 26 percent reported finding sex partners online and sex with serodiscordant or unknown serostatus partners was common. Compared to men who did not report unprotected anal intercourse (UAI) in the preceding two months, MSM who engaged in UAI were younger and more likely to use alcohol in sexual contexts, meet men online for offline sex, and perceive lower safer sex norms in their community. Although these results were statistically significant, the strength of the relationships was too small to have any practical value. The lack of useful explanatory power underscores the importance of accelerated HIV research that identifies the unique, local factors associated with unsafe sex in other previously understudied populations.

Linking extinction-colonization dynamics to genetic structure in a salamander metapopulation.

PubMed

Cosentino, Bradley J; Phillips, Christopher A; Schooley, Robert L; Lowe, Winsor H; Douglas, Marlis R

2012-04-22

Theory predicts that founder effects have a primary role in determining metapopulation genetic structure. However, ecological factors that affect extinction-colonization dynamics may also create spatial variation in the strength of genetic drift and migration. We tested the hypothesis that ecological factors underlying extinction-colonization dynamics influenced the genetic structure of a tiger salamander (Ambystoma tigrinum) metapopulation. We used empirical data on metapopulation dynamics to make a priori predictions about the effects of population age and ecological factors on genetic diversity and divergence among 41 populations. Metapopulation dynamics of A. tigrinum depended on wetland area, connectivity and presence of predatory fish. We found that newly colonized populations were more genetically differentiated than established populations, suggesting that founder effects influenced genetic structure. However, ecological drivers of metapopulation dynamics were more important than age in predicting genetic structure. Consistent with demographic predictions from metapopulation theory, genetic diversity and divergence depended on wetland area and connectivity. Divergence was greatest in small, isolated wetlands where genetic diversity was low. Our results show that ecological factors underlying metapopulation dynamics can be key determinants of spatial genetic structure, and that habitat area and isolation may mediate the contributions of drift and migration to divergence and evolution in local populations.

Inference of Expanded Lrp-Like Feast/Famine Transcription Factor Targets in a Non-Model Organism Using Protein Structure-Based Prediction

PubMed Central

Ashworth, Justin; Plaisier, Christopher L.; Lo, Fang Yin; Reiss, David J.; Baliga, Nitin S.

2014-01-01

Widespread microbial genome sequencing presents an opportunity to understand the gene regulatory networks of non-model organisms. This requires knowledge of the binding sites for transcription factors whose DNA-binding properties are unknown or difficult to infer. We adapted a protein structure-based method to predict the specificities and putative regulons of homologous transcription factors across diverse species. As a proof-of-concept we predicted the specificities and transcriptional target genes of divergent archaeal feast/famine regulatory proteins, several of which are encoded in the genome of Halobacterium salinarum. This was validated by comparison to experimentally determined specificities for transcription factors in distantly related extremophiles, chromatin immunoprecipitation experiments, and cis-regulatory sequence conservation across eighteen related species of halobacteria. Through this analysis we were able to infer that Halobacterium salinarum employs a divergent local trans-regulatory strategy to regulate genes (carA and carB) involved in arginine and pyrimidine metabolism, whereas Escherichia coli employs an operon. The prediction of gene regulatory binding sites using structure-based methods is useful for the inference of gene regulatory relationships in new species that are otherwise difficult to infer. PMID:25255272

Inference of expanded Lrp-like feast/famine transcription factor targets in a non-model organism using protein structure-based prediction.

PubMed

Ashworth, Justin; Plaisier, Christopher L; Lo, Fang Yin; Reiss, David J; Baliga, Nitin S

2014-01-01

Widespread microbial genome sequencing presents an opportunity to understand the gene regulatory networks of non-model organisms. This requires knowledge of the binding sites for transcription factors whose DNA-binding properties are unknown or difficult to infer. We adapted a protein structure-based method to predict the specificities and putative regulons of homologous transcription factors across diverse species. As a proof-of-concept we predicted the specificities and transcriptional target genes of divergent archaeal feast/famine regulatory proteins, several of which are encoded in the genome of Halobacterium salinarum. This was validated by comparison to experimentally determined specificities for transcription factors in distantly related extremophiles, chromatin immunoprecipitation experiments, and cis-regulatory sequence conservation across eighteen related species of halobacteria. Through this analysis we were able to infer that Halobacterium salinarum employs a divergent local trans-regulatory strategy to regulate genes (carA and carB) involved in arginine and pyrimidine metabolism, whereas Escherichia coli employs an operon. The prediction of gene regulatory binding sites using structure-based methods is useful for the inference of gene regulatory relationships in new species that are otherwise difficult to infer.

Human impacts and changes in the coastal waters of south China.

PubMed

Wang, Linlin; Li, Qiang; Bi, Hongsheng; Mao, Xian-Zhong

2016-08-15

Human impact on the environment remains at the center of the debate on global environmental change. Using the Hong Kong-Shenzhen corridor in south China as an example, we present evidence that rapid urbanization and economic development in coastal areas were the dominant factors causing rapid changes in coastal waters. From 1990 to 2012, coastal seawater temperature increased ~0.060°C per year, sea level rose 4.4mm per year and pH decreased from 8.2 to 7.7, much faster than global averages. In the same period, there were exponential increases in the local population, gross domestic product and land fill area. Empirical analyses suggest that the large increase in the population affected local temperature, and economic development had a major impact on local pH. Results also show that pH and temperature were significantly correlated with local sea level rise, but pH had more predictive power, suggesting it could be considered a predictor for changes in local sea level. We conclude that human activities could significantly exacerbate local environmental changes which should be considered in predictive models and future development plans in coastal areas. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Local and Regional Determinants of an Uncommon Functional Group in Freshwater Lakes and Ponds

PubMed Central

McCann, Michael James

2015-01-01

A combination of local and regional factors and stochastic forces is expected to determine the occurrence of species and the structure of communities. However, in most cases, our understanding is incomplete, with large amounts of unexplained variation. Using functional groups rather than individual species may help explain the relationship between community composition and conditions. In this study, I used survey data from freshwater lakes and ponds to understand factors that determine the presence of the floating plant functional group in the northeast United States. Of the 176 water bodies surveyed, 104 (59.1%) did not contain any floating plant species. The occurrence of this functional group was largely determined by local abiotic conditions, which were spatially autocorrelated across the region. A model predicting the presence of the floating plant functional group performed similarly to the best species-specific models. Using a permutation test, I also found that the observed prevalence of floating plants is no different than expected by random assembly from a species pool of its size. These results suggest that the size of the species pool interacts with local conditions in determining the presence of a functional group. Nevertheless, a large amount of unexplained variation remains, attributable to either stochastic species occurrence or incomplete predictive models. The simple permutation approach in this study can be extended to test alternative models of community assembly. PMID:26121636

A Comparative Analysis of Factors Related to a Candidate's Success or Failure in the 1975 and 1977 Community School Board Elections in New York City.

ERIC Educational Resources Information Center

Levine, Jonathan; Clawar, Harry J.

In 1960, the New York City Public School System was decentralized into 32 school districts with limited authority over elementary and junior high schools. Locally elected district community school boards were provided for by State legislation. In this study factors relevant to predicting a candidate's success or failure in the 1975 and 1977 school…

Localized mRNA translation and protein association

NASA Astrophysics Data System (ADS)

Zhdanov, Vladimir P.

2014-08-01

Recent direct observations of localization of mRNAs and proteins both in prokaryotic and eukaryotic cells can be related to slowdown of diffusion of these species due to macromolecular crowding and their ability to aggregate and form immobile or slowly mobile complexes. Here, a generic kinetic model describing both these factors is presented and comprehensively analyzed. Although the model is non-linear, an accurate self-consistent analytical solution of the corresponding reaction-diffusion equation has been constructed, the types of localized protein distributions have been explicitly shown, and the predicted kinetic regimes of gene expression have been classified.

Size versus electronic factors in transition metal carbide and TCP phase stability

NASA Astrophysics Data System (ADS)

Pettifor, D. G.; Seiser, B.; Margine, E. R.; Kolmogorov, A. N.; Drautz, R.

2013-09-01

The contributions of atomic size and electronic factors to the structural stability of transition metal carbides and topologically close-packed (TCP) phases are investigated. The hard-sphere model that has been used by Cottrell to rationalize the occurrence of the octahedral and trigonal local coordination polyhedra within the transition metal carbides is shown to have limitations in TiC since density functional theory (DFT) predicts that the second most metastable phase closest to the B1 (NaCl) ground state takes the B? (BN) structure type with 5-atom local coordination polyhedra with very short Ti-C bond lengths. The importance of electronic factors in the TCP phases is demonstrated by DFT predictions that the A15, ? and ? phases are stabilized between groups VI and VII of the elemental transition metals, whereas the ? and Laves phases are destabilized. The origin of this difference is related to the bimodal shape parameter of the electronic density of states by using the bond-order potential expansion of the structural energy within a canonical tight-binding model. The importance of the size factor in the TCP phases is illustrated by the DFT heats of formation for the binary systems Mo-Re, Mo-Ru, Nb-Re and Nb-Ru which show that the ? and Laves phases become more and more stable compared to A15, ? and ? as the size factor increases from Mo-Re through to Nb-Ru.

Prognostic factors in breast phyllodes tumors: a nomogram based on a retrospective cohort study of 404 patients.

PubMed

Zhou, Zhi-Rui; Wang, Chen-Chen; Sun, Xiang-Jie; Yang, Zhao-Zhi; Chen, Xing-Xing; Shao, Zhi-Ming; Yu, Xiao-Li; Guo, Xiao-Mao

2018-04-01

The aim of this study was to explore the independent prognostic factors related to postoperative recurrence-free survival (RFS) in patients with breast phyllodes tumors (PTBs). A retrospective analysis was conducted in Fudan University Shanghai Cancer Center. According to histological type, patients with benign PTBs were classified as a low-risk group, while borderline and malignant PTBs were classified as a high-risk group. The Cox regression model was adopted to identify factors affecting postoperative RFS in the two groups, and a nomogram was generated to predict recurrence-free survival at 1, 3, and 5 years. Among the 404 patients, 168 (41.6%) patients had benign PTB, 184 (45.5%) had borderline PTB, and 52 (12.9%) had malignant PTB. Fifty-five patients experienced postoperative local recurrence, including six benign cases, 26 borderline cases, and 22 malignant cases; the three histological types of PTB had local recurrence rates of 3.6%, 14.1%, and 42.3%, respectively. Stromal cell atypia was an independent prognostic factor for RFS in the low-risk group, while the surgical approach and tumor border were independent prognostic factors for RFS in the high-risk group, and patients receiving simple excision with an infiltrative tumor border had a higher recurrence rate. A nomogram developed based on clinicopathologic features and surgical approaches could predict recurrence-free survival at 1, 3, and 5 years. For high-risk patients, this predictive nomogram based on tumor border, tumor residue, mitotic activity, degree of stromal cell hyperplasia, and atypia can be applied for patient counseling and clinical management. The efficacy of adjuvant radiotherapy remains uncertain. © 2018 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

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.

Validation of a nomogram in the prediction of local recurrence risks after conserving surgery for Asian women with ductal carcinoma in situ of the breast.

PubMed

Wang, F; Li, H; Tan, P H; Chua, E T; Yeo, R M C; Lim, F L W T; Kim, S W; Tan, D Y H; Wong, F Y

2014-11-01

At our centre, ductal carcinoma in situ (DCIS) was commonly treated with breast-conservation therapy (BCT). Local recurrence after BCT is a major concern. The aims of our study were to review the outcomes of DCIS treatment in our patients and to evaluate a nomogram from Memorial Sloan Kettering Cancer Centre (MSKCC) for predicting ipsilateral breast tumour recurrence (IBTR) in our Asian population. Chart reviews of 716 patients with pure DCIS treated from 1992 to 2011 were carried out. Univariable Cox regression analyses were used to evaluate the effects of the 10 prognostic factors of the MSKCC nomogram on IBTR. We constructed a separate National Cancer Centre Singapore (NCCS) nomogram based on multivariable Cox regression via reduced model selection by applying the stopping rule of Akaike's information criterion to predict IBTR-free survival. The abilities of the NCCS nomogram and the MSKCC nomogram to predict IBTR of individual patients were evaluated with bootstrapping of 200 sets of resamples and the NCCS dataset, respectively. Harrell's c-index was calculated for each nomogram to evaluate the concordance between predicted and observed responses of individual subjects. Study patients were followed up for a median of 70 months. Over 95% of patients received adjuvant radiotherapy. The 5 and 10 year actuarial IBTR-free survival rates for the cohort were 95.5 and 92.6%, respectively. In the multivariate analysis, independent prognostic factors for IBTR included use of adjuvant endocrine therapy, presence of comedonecrosis and younger age at diagnosis. These factors formed the basis of the NCCS nomogram, which had a similar c-index (NCCS: 0.696; MSKCC: 0.673) compared with the MSKCC nomogram. The MSKCC nomogram was validated in an Asian population. A simpler NCCS nomogram using a different combination of fewer prognostic factors may be sufficient for the prediction of IBTR in Asians, but requires external validation to compare for relative performance. Copyright © 2014 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

A variable structure fuzzy neural network model of squamous dysplasia and esophageal squamous cell carcinoma based on a global chaotic optimization algorithm.

PubMed

Moghtadaei, Motahareh; Hashemi Golpayegani, Mohammad Reza; Malekzadeh, Reza

2013-02-07

Identification of squamous dysplasia and esophageal squamous cell carcinoma (ESCC) is of great importance in prevention of cancer incidence. Computer aided algorithms can be very useful for identification of people with higher risks of squamous dysplasia, and ESCC. Such method can limit the clinical screenings to people with higher risks. Different regression methods have been used to predict ESCC and dysplasia. In this paper, a Fuzzy Neural Network (FNN) model is selected for ESCC and dysplasia prediction. The inputs to the classifier are the risk factors. Since the relation between risk factors in the tumor system has a complex nonlinear behavior, in comparison to most of ordinary data, the cost function of its model can have more local optimums. Thus the need for global optimization methods is more highlighted. The proposed method in this paper is a Chaotic Optimization Algorithm (COA) proceeding by the common Error Back Propagation (EBP) local method. Since the model has many parameters, we use a strategy to reduce the dependency among parameters caused by the chaotic series generator. This dependency was not considered in the previous COA methods. The algorithm is compared with logistic regression model as the latest successful methods of ESCC and dysplasia prediction. The results represent a more precise prediction with less mean and variance of error. Copyright © 2012 Elsevier Ltd. All rights reserved.

A review on the factors affecting mite growth in stored grain commodities.

PubMed

Collins, D A

2012-03-01

A thorough review of the literature has identified the key factors and interactions that affect the growth of mite pests on stored grain commodities. Although many factors influence mite growth, the change and combinations of the physical conditions (temperature, relative humidity and/or moisture content) during the storage period are likely to have the greatest impact, with biological factors (e.g. predators and commodity) playing an important role. There is limited information on the effects of climate change, light, species interactions, local density dependant factors, spread of mycotoxins and action thresholds for mites. A greater understanding of these factors may identify alternative control techniques. The ability to predict mite population dynamics over a range of environmental conditions, both physical and biological, is essential in providing an early warning of mite infestations, advising when appropriate control measures are required and for evaluating control measures. This information may provide a useful aid in predicting and preventing mite population development as part of a risk based decision support system.

Failure analysis of thick composite cylinders under external pressure

NASA Technical Reports Server (NTRS)

Caiazzo, A.; Rosen, B. W.

1992-01-01

Failure of thick section composites due to local compression strength and overall structural instability is treated. Effects of material nonlinearity, imperfect fiber architecture, and structural imperfections upon anticipated failure stresses are determined. Comparisons with experimental data for a series of test cylinders are described. Predicting the failure strength of composite structures requires consideration of stability and material strength modes of failure using linear and nonlinear analysis techniques. Material strength prediction requires the accurate definition of the local multiaxial stress state in the material. An elasticity solution for the linear static analysis of thick anisotropic cylinders and rings is used herein to predict the axisymmetric stress state in the cylinders. Asymmetric nonlinear behavior due to initial cylinder out of roundness and the effects of end closure structure are treated using finite element methods. It is assumed that local fiber or ply waviness is an important factor in the initiation of material failure. An analytical model for the prediction of compression failure of fiber composites, which includes the effects of fiber misalignments, matrix inelasticity, and multiaxial applied stresses is used for material strength calculations. Analytical results are compared to experimental data for a series of glass and carbon fiber reinforced epoxy cylinders subjected to external pressure. Recommendations for pretest characterization and other experimental issues are presented. Implications for material and structural design are discussed.

National Business Cycles and Community Competition for Jobs.

ERIC Educational Resources Information Center

Kasarda, John D.; Irwin, Michael D.

1991-01-01

Analysis of employment change data for 3,101 counties during recent national recession and recovery periods found that factors derived from human ecological theory (density, infrastructure age, unionization, labor force education, and crime rate) best predicted local competitive dynamics across all business-cycle phases. Contains 60 references.…

Local and Landscape Drivers of Parasitoid Abundance, Richness, and Composition in Urban Gardens.

PubMed

Burks, Julia M; Philpott, Stacy M

2017-04-01

Urbanization negatively affects biodiversity, yet some urban habitat features can support diversity. Parasitoid wasps, an abundant and highly diverse group of arthropods, can inhabit urban areas and do well in areas with higher host abundance, floral resources, or local or landscape complexity. Parasitoids provide biological control services in many agricultural habitats, yet few studies have examined diversity and abundance of parasitoids in urban agroecosystems to understand how to promote conservation and function. We examined the local habitat and landscape drivers of parasitoid abundance, superfamily and family richness, and parasitoid composition in urban gardens in the California central coast. Local factors included garden size, ground cover type, herbaceous plant species, and number of trees and shrubs. Landscape characteristics included land cover and landscape diversity around gardens. We found that garden size, mulch cover, and urban cover within 500 m of gardens predicted increases in parasitoid abundance within gardens. The height of herbaceous vegetation and tree and shrub richness predicted increases in superfamily and family richness whereas increases in urban cover resulted in declines in parasitoid richness. Abundance of individual superfamilies and families responded to a wide array of local and landscape factors, sometimes in opposite ways. Composition of parasitoid communities responded to changes in garden size, herbaceous plant cover, and number of flowers. Thus, both local scale management and landscape planning may impact the abundance, diversity, and community composition of parasitoids in urban gardens, and may result in differences in the effectiveness of parasitoids in biological control. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Stereotactic radiotherapy following surgery for brain metastasis: Predictive factors for local control and radionecrosis.

PubMed

Doré, M; Martin, S; Delpon, G; Clément, K; Campion, L; Thillays, F

2017-02-01

To evaluate local control and adverse effects after postoperative hypofractionated stereotactic radiosurgery in patients with brain metastasis. We reviewed patients who had hypofractionated stereotactic radiosurgery (7.7Gy×3 prescribed to the 70% isodose line, with 2mm planning target volume margin) following resection from March 2008 to January 2014. The primary endpoint was local failure defined as recurrence within the surgical cavity. Secondary endpoints were distant failure rates and the occurrence of radionecrosis. Out of 95 patients, 39.2% had metastatic lesions from a non-small cell lung cancer primary tumour. The median Graded Prognostic Assessment score was 3 (48% of patients). One-year local control rates were 84%. Factors associated with improved local control were no cavity enhancement on pre-radiation MRI (P<0.00001), planning target volume less than 12cm 3 (P=0.005), Graded Prognostic Assessment score 2 or above (P=0.009). One-year distant cerebral control rates were 56%. Thirty-three percent of patients received whole brain radiation therapy. Histologically proven radionecrosis of brain tissue occurred in 7.2% of cases. The size of the preoperative lesion and the volume of healthy brain tissue receiving 21Gy (V 21 ) were both predictive of the incidence of radionecrosis (P=0.010 and 0.036, respectively). Adjuvant hypofractionated stereotactic radiosurgery to the postoperative cavity in patients with brain metastases results in excellent local control in selected patients, helps delay the use of whole brain radiation, and is associated with a relatively low risk of radionecrosis. Copyright © 2016 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

Improved geometric variables for predicting disturbed flow at the normal carotid bifurcation

NASA Astrophysics Data System (ADS)

Bijari, Payam B.; Antiga, Luca; Steinman, David A.

2011-03-01

Recent work from our group has shown the primacy of the bifurcation area ratio and tortuosity in determining the amount of disturbed flow at the carotid bifurcation, believed to be a local risk factor for the carotid atherosclerosis. We have also presented fast and reliable methods of extraction of geometry from routine 3D contrast-enhanced magnetic resonance angiography, as the necessary step along the way for large-scale trials of such local risk factors. In the present study, we refine our original geometric variables to better reflect the underlying fluid mechanical principles. Flaring of the bifurcation, leading to flow separation, is defined by the maximum relative expansion of the common carotid artery (CCA), proximal to the bifurcation apex. The beneficial effect of curvature on flow inertia, via its suppression of flow separation, is now characterized by the tortuosity of CCA as it enters the flare region. Based on data from 50 normal carotid bifurcations, multiple linear regressions of these new independent geometric predictors against the dependent disturbed flow burden reveals adjusted R2 values approaching 0.5, better than the values closer to 0.3 achieved using the original variables. The excellent scan-rescan reproducibility demonstrated for our earlier geometric variables is shown to be preserved for the new definitions. Improved prediction of disturbed flow by robust and reproducible vascular geometry offers a practical pathway to large-scale studies of local risk factors in atherosclerosis.

A statistical model to estimate the local vulnerability to severe weather

NASA Astrophysics Data System (ADS)

Pardowitz, Tobias

2018-06-01

We present a spatial analysis of weather-related fire brigade operations in Berlin. By comparing operation occurrences to insured losses for a set of severe weather events we demonstrate the representativeness and usefulness of such data in the analysis of weather impacts on local scales. We investigate factors influencing the local rate of operation occurrence. While depending on multiple factors - which are often not available - we focus on publicly available quantities. These include topographic features, land use information based on satellite data and information on urban structure based on data from the OpenStreetMap project. After identifying suitable predictors such as housing coverage or local density of the road network we set up a statistical model to be able to predict the average occurrence frequency of local fire brigade operations. Such model can be used to determine potential hotspots for weather impacts even in areas or cities where no systematic records are available and can thus serve as a basis for a broad range of tools or applications in emergency management and planning.

A prospective evaluation of preoperative localization by technetium-99m sestamibi scintigraphy and ultrasonography in primary hyperparathyroidism.

PubMed

Lo, Chung-Yau; Lang, Brian H; Chan, W F; Kung, Annie W C; Lam, Karen S L

2007-02-01

Ultrasonography (USG) and technetium-99m sestamibi (MIBI) scintigraphy are commonly used imaging modalities in the era of minimally invasive parathyroidectomy (MIP) for primary hyperparathyroidism (pHPT). However, their relative importance and actual contribution to MIP have not been prospectively assessed. A total of 100 consecutive pHPT patients planning for MIP were recruited. Both USG and MIBI findings were correlated with intraoperative findings and postoperative outcome. Clinicopathologic factors were examined for potential association with a correct localizing result. Thirty men and 70 women (age range 13 to 93 years [median 55.5]) were included in the study. The final pathology included 98 patients with solitary adenoma and 2 patients with multiglandular disease. The sensitivities, accuracies, and positive predicted values for USG and MIBI alone were 57% vs 89%, 56% vs 85%, and 97% vs 94%, respectively. Correctly localized adenomas were significantly heavier than incorrectly localized ones. MIBI is preferred over USG in pHPT patients planning for MIP. Weight of adenoma appeared to be the only clinicopathologic factor determining localization accuracy.

A spectroscopic approach toward depression diagnosis: local metabolism meets functional connectivity.

PubMed

Demenescu, Liliana Ramona; Colic, Lejla; Li, Meng; Safron, Adam; Biswal, B; Metzger, Coraline Danielle; Li, Shijia; Walter, Martin

2017-03-01

Abnormal anterior insula (AI) response and functional connectivity (FC) is associated with depression. In addition to clinical features, such as severity, AI FC and its metabolism further predicted therapeutic response. Abnormal FC between anterior cingulate and AI covaried with reduced glutamate level within cingulate cortex. Recently, deficient glial glutamate conversion was found in AI in major depression disorder (MDD). We therefore postulate a local glutamatergic mechanism in insula cortex of depressive patients, which is correlated with symptoms severity and itself influences AI's network connectivity in MDD. Twenty-five MDD patients and 25 healthy controls (HC) matched on age and sex underwent resting state functional magnetic resonance imaging and magnetic resonance spectroscopy scans. To determine the role of local glutamate-glutamine complex (Glx) ratio on whole brain AI FC, we conducted regression analysis with Glx relative to creatine (Cr) ratio as factor of interest and age, sex, and voxel tissue composition as nuisance factors. We found that in MDD, but not in HC, AI Glx/Cr ratio correlated positively with AI FC to right supramarginal gyrus and negatively with AI FC toward left occipital cortex (p < 0.05 family wise error). AI Glx/Cr level was negatively correlated with HAMD score (p < 0.05) in MDD patients. We showed that the local AI ratio of glutamatergic-creatine metabolism is an underlying candidate subserving functional network disintegration of insula toward low level and supramodal integration areas, in MDD. While causality cannot directly be inferred from such correlation, our finding helps to define a multilevel network of response-predicting regions based on local metabolism and connectivity strength.

The predictive factors for lymph node metastasis in early gastric cancer: A clinical study.

PubMed

Wang, Yinzhong

2015-01-01

To detect the clinicopathological factors associated with lymph node metastases in early gastric cancer. We retrospectively evaluated the distribution of metastatic nodes in 198 patients with early gastric cancer treated in our hospital between May 2008 and January 2015, the clinicopathological factors including age, gender, tumor location, tumor size, macroscopic type, depth of invasion, histological type and venous invasion were studied, and the relationship between various parameters and lymph node metastases was analyzed. In this study, one hundred and ninety-eight patients with early gastric cancer were included, and lymph node metastasis was detected in 28 patients. Univariate analysis revealed a close relationship between tumor size, depth of invasion, histological type, venous invasion, local ulceration and lymph node metastases. Multivariate analysis revealed that the five factors were independent risk factors for lymph node metastases. The clinicopathological parameters including tumor size, depth of invasion, local ulceration, histological type and venous invasion are closely correlated with lymph node metastases, should be paid high attention in early gastric cancer patients.

Local temperatures predict breeding phenology but do not result in breeding synchrony among a community of resident cavity-nesting birds.

PubMed

Drake, Anna; Martin, Kathy

2018-02-09

Weather and ecological factors are known to influence breeding phenology and thus individual fitness. We predicted concordance between weather conditions and annual variation in phenology within a community of eight resident, cavity-nesting bird species over a 17-year period. We show that, although clutch initiation dates for six of our eight species are correlated with local daily maximum temperatures, this common driver does not produce a high degree of breeding synchrony due to species-specific responses to conditions during different periods of the preceding winter or spring. These "critical temperature periods" were positively associated with average lay date for each species, although the interval between critical periods and clutch initiation varied from 4-78 days. The ecological factors we examined (cavity availability and a food pulse) had an additional influence on timing in only one of our eight focal species. Our results have strong implications for understanding heterogeneous wildlife responses to climate change: divergent responses would be expected within communities where species respond to local conditions within different temporal windows, due to differing warming trends between winter and spring. Our system therefore indicates that climate change could alter relative breeding phenology among sympatric species in temperate ecosystems.

Environmental Monitoring of Endemic Cholera

NASA Astrophysics Data System (ADS)

ElNemr, W.; Jutla, A. S.; Constantin de Magny, G.; Hasan, N. A.; Islam, M.; Sack, R.; Huq, A.; Hashem, F.; Colwell, R.

2012-12-01

Cholera remains a major public health threat. Since Vibrio cholerae, the causative agent of the disease, is autochthonous to riverine, estuarine, and coastal waters, it is unlikely the bacteria can be eradicated from its natural habitat. Prediction of disease, in conjunction with preventive vaccination can reduce the prevalence rate of a disease. Understanding the influence of environmental parameters on growth and proliferation of bacteria is an essential first step in developing prediction methods for outbreaks. Large scale geophysical variables, such as SST and coastal chlorophyll, are often associated with conditions favoring growth of V. cholerae. However, local environmental factors, meaning biological activity in ponds from where the bulk of populations in endemic regions derive water for daily usage, are either neglected or oversimplified. Using data collected from several sites in two geographically distinct locations in South Asia, we have identified critical local environmental factors associated with cholera outbreak. Of 18 environmental variables monitored for water sources in Mathbaria (a coastal site near the Bay of Bengal) and Bakergonj (an inland site) of Bangladesh, water depth and chlorophyll were found to be important factors associated with initiation of cholera outbreaks. Cholera in coastal regions appears to be related to intrusion. However, monsoonal flooding creates conditions for cholera epidemics in inland regions. This may be one of the first attempts to relate in-situ environmental observations with cholera. We anticipate that it will be useful for further development of prediction models in the resource constrained regions.

Testing the Sensory Drive Hypothesis: Geographic variation in echolocation frequencies of Geoffroy's horseshoe bat (Rhinolophidae: Rhinolophus clivosus)

PubMed Central

Catto, Sarah; Mutumi, Gregory L.; Finger, Nikita; Webala, Paul W.

2017-01-01

Geographic variation in sensory traits is usually influenced by adaptive processes because these traits are involved in crucial life-history aspects including orientation, communication, lineage recognition and mate choice. Studying this variation can therefore provide insights into lineage diversification. According to the Sensory Drive Hypothesis, lineage diversification may be driven by adaptation of sensory systems to local environments. It predicts that acoustic signals vary in association with local climatic conditions so that atmospheric attenuation is minimized and transmission of the signals maximized. To test this prediction, we investigated the influence of climatic factors (specifically relative humidity and temperature) on geographic variation in the resting frequencies of the echolocation pulses of Geoffroy’s horseshoe bat, Rhinolophus clivosus. If the evolution of phenotypic variation in this lineage tracks climate variation, human induced climate change may lead to decreases in detection volumes and a reduction in foraging efficiency. A complex non-linear interaction between relative humidity and temperature affects atmospheric attenuation of sound and principal components composed of these correlated variables were, therefore, used in a linear mixed effects model to assess their contribution to observed variation in resting frequencies. A principal component composed predominantly of mean annual temperature (factor loading of -0.8455) significantly explained a proportion of the variation in resting frequency across sites (P < 0.05). Specifically, at higher relative humidity (around 60%) prevalent across the distribution of R. clivosus, increasing temperature had a strong negative effect on resting frequency. Climatic factors thus strongly influence acoustic signal divergence in this lineage, supporting the prediction of the Sensory Drive Hypothesis. The predicted future increase in temperature due to climate change is likely to decrease the detection volume in echolocating bats and adversely impact their foraging efficiency. PMID:29186147

Testing the Sensory Drive Hypothesis: Geographic variation in echolocation frequencies of Geoffroy's horseshoe bat (Rhinolophidae: Rhinolophus clivosus).

PubMed

Jacobs, David S; Catto, Sarah; Mutumi, Gregory L; Finger, Nikita; Webala, Paul W

2017-01-01

Geographic variation in sensory traits is usually influenced by adaptive processes because these traits are involved in crucial life-history aspects including orientation, communication, lineage recognition and mate choice. Studying this variation can therefore provide insights into lineage diversification. According to the Sensory Drive Hypothesis, lineage diversification may be driven by adaptation of sensory systems to local environments. It predicts that acoustic signals vary in association with local climatic conditions so that atmospheric attenuation is minimized and transmission of the signals maximized. To test this prediction, we investigated the influence of climatic factors (specifically relative humidity and temperature) on geographic variation in the resting frequencies of the echolocation pulses of Geoffroy's horseshoe bat, Rhinolophus clivosus. If the evolution of phenotypic variation in this lineage tracks climate variation, human induced climate change may lead to decreases in detection volumes and a reduction in foraging efficiency. A complex non-linear interaction between relative humidity and temperature affects atmospheric attenuation of sound and principal components composed of these correlated variables were, therefore, used in a linear mixed effects model to assess their contribution to observed variation in resting frequencies. A principal component composed predominantly of mean annual temperature (factor loading of -0.8455) significantly explained a proportion of the variation in resting frequency across sites (P < 0.05). Specifically, at higher relative humidity (around 60%) prevalent across the distribution of R. clivosus, increasing temperature had a strong negative effect on resting frequency. Climatic factors thus strongly influence acoustic signal divergence in this lineage, supporting the prediction of the Sensory Drive Hypothesis. The predicted future increase in temperature due to climate change is likely to decrease the detection volume in echolocating bats and adversely impact their foraging efficiency.

Ecological Trait Composition of Freshwater Fish Across Gradients of Environmental Variability in North-Eastern Australia

NASA Astrophysics Data System (ADS)

Kennard, M. J.; Pusey, B. J.; Arthington, A. H.

2005-05-01

North-eastern Australia encompasses 18o of latitude, monsoonal/tropical to sub-tropical/temperate climates, geomorphologically diverse rivers, and flow regimes with markedly varied seasonality, constancy and predictability. Fish assemblages in the region vary in relation to the predictability of aquatic habitat availability and other topographic, climatic and/or biogeographic factors. This paper examines how environmental, biogeographic and phylogenetic factors may constrain ecological trait composition at local and regional scales. We derived 17 categories of ecological traits to describe the morphology, behaviour, habitat, life history and trophic characteristics of 114 fish species from 64 river basins. Trait composition varied substantially across the region. The number of riffle dwelling species, maximum size and longevity of fishes was greater in the hydrologically predictable and constant rivers of the Wet Tropics region than in more unpredictable or seasonal environments. The importance of herbivory was also greater in the tropics. Historical biogeographic and phylogenetic factors may confound our ability to understand the role of environmental factors in determining spatial variation in ecological trait composition. Understanding the functional linkages between environmental drivers of fish species distributions via their ecological characteristics should provide a foundation for predicting future impacts of environmental change in a region of Australia subject to increasing human pressures.

Nowcasting the spread of chikungunya virus in the Americas.

PubMed

Johansson, Michael A; Powers, Ann M; Pesik, Nicki; Cohen, Nicole J; Staples, J Erin

2014-01-01

In December 2013, the first locally-acquired chikungunya virus (CHIKV) infections in the Americas were reported in the Caribbean. As of May 16, 55,992 cases had been reported and the outbreak was still spreading. Identification of newly affected locations is paramount to intervention activities, but challenging due to limitations of current data on the outbreak and on CHIKV transmission. We developed models to make probabilistic predictions of spread based on current data considering these limitations. Branching process models capturing travel patterns, local infection prevalence, climate dependent transmission factors, and associated uncertainty estimates were developed to predict probable locations for the arrival of CHIKV-infected travelers and for the initiation of local transmission. Many international cities and areas close to where transmission has already occurred were likely to have received infected travelers. Of the ten locations predicted to be the most likely locations for introduced CHIKV transmission in the first four months of the outbreak, eight had reported local cases by the end of April. Eight additional locations were likely to have had introduction leading to local transmission in April, but with substantial uncertainty. Branching process models can characterize the risk of CHIKV introduction and spread during the ongoing outbreak. Local transmission of CHIKV is currently likely in several Caribbean locations and possible, though uncertain, for other locations in the continental United States, Central America, and South America. This modeling framework may also be useful for other outbreaks where the risk of pathogen spread over heterogeneous transportation networks must be rapidly assessed on the basis of limited information.

Rapid evolution of cis-regulatory sequences via local point mutations

NASA Technical Reports Server (NTRS)

Stone, J. R.; Wray, G. A.

2001-01-01

Although the evolution of protein-coding sequences within genomes is well understood, the same cannot be said of the cis-regulatory regions that control transcription. Yet, changes in gene expression are likely to constitute an important component of phenotypic evolution. We simulated the evolution of new transcription factor binding sites via local point mutations. The results indicate that new binding sites appear and become fixed within populations on microevolutionary timescales under an assumption of neutral evolution. Even combinations of two new binding sites evolve very quickly. We predict that local point mutations continually generate considerable genetic variation that is capable of altering gene expression.

When High-Capacity Readers Slow Down and Low-Capacity Readers Speed Up: Working Memory and Locality Effects.

PubMed

Nicenboim, Bruno; Logačev, Pavel; Gattei, Carolina; Vasishth, Shravan

2016-01-01

We examined the effects of argument-head distance in SVO and SOV languages (Spanish and German), while taking into account readers' working memory capacity and controlling for expectation (Levy, 2008) and other factors. We predicted only locality effects, that is, a slowdown produced by increased dependency distance (Gibson, 2000; Lewis and Vasishth, 2005). Furthermore, we expected stronger locality effects for readers with low working memory capacity. Contrary to our predictions, low-capacity readers showed faster reading with increased distance, while high-capacity readers showed locality effects. We suggest that while the locality effects are compatible with memory-based explanations, the speedup of low-capacity readers can be explained by an increased probability of retrieval failure. We present a computational model based on ACT-R built under the previous assumptions, which is able to give a qualitative account for the present data and can be tested in future research. Our results suggest that in some cases, interpreting longer RTs as indexing increased processing difficulty and shorter RTs as facilitation may be too simplistic: The same increase in processing difficulty may lead to slowdowns in high-capacity readers and speedups in low-capacity ones. Ignoring individual level capacity differences when investigating locality effects may lead to misleading conclusions.

When High-Capacity Readers Slow Down and Low-Capacity Readers Speed Up: Working Memory and Locality Effects

PubMed Central

Nicenboim, Bruno; Logačev, Pavel; Gattei, Carolina; Vasishth, Shravan

2016-01-01

We examined the effects of argument-head distance in SVO and SOV languages (Spanish and German), while taking into account readers' working memory capacity and controlling for expectation (Levy, 2008) and other factors. We predicted only locality effects, that is, a slowdown produced by increased dependency distance (Gibson, 2000; Lewis and Vasishth, 2005). Furthermore, we expected stronger locality effects for readers with low working memory capacity. Contrary to our predictions, low-capacity readers showed faster reading with increased distance, while high-capacity readers showed locality effects. We suggest that while the locality effects are compatible with memory-based explanations, the speedup of low-capacity readers can be explained by an increased probability of retrieval failure. We present a computational model based on ACT-R built under the previous assumptions, which is able to give a qualitative account for the present data and can be tested in future research. Our results suggest that in some cases, interpreting longer RTs as indexing increased processing difficulty and shorter RTs as facilitation may be too simplistic: The same increase in processing difficulty may lead to slowdowns in high-capacity readers and speedups in low-capacity ones. Ignoring individual level capacity differences when investigating locality effects may lead to misleading conclusions. PMID:27014113

Predictive factors for survival and correlation to toxicity in advanced Stage III non-small cell lung cancer patients with concurrent chemoradiation.

PubMed

Kim, Yong-Hyub; Ahn, Sung-Ja; Kim, Young-Chul; Kim, Kyu-Sik; Oh, In-Jae; Ban, Hee-Jung; Chung, Woong-Ki; Nam, Taek-Keun; Yoon, Mee Sun; Jeong, Jae-Uk; Song, Ju-Young

2016-02-01

Concurrent chemoradiotherapy is the standard treatment for locally advanced Stage III non-small cell lung cancer in patients with a good performance status and minimal weight loss. This study aimed to define subgroups with different survival outcomes and identify correlations with the radiation-related toxicities. We retrospectively reviewed 381 locally advanced Stage III non-small cell lung cancer patients with a good performance status or weight loss of <10% who received concurrent chemoradiotherapy between 2004 and 2011. Three-dimensional conformal radiotherapy was administered once daily, combined with weekly chemotherapy. The Kaplan-Meier method was used for survival comparison and Cox regression for multivariate analysis. Multivariate analysis was performed using all variables with P values <0.1 from the univariate analysis. Median survival of all patients was 24 months. Age > 75 years, the diffusion lung capacity for carbon monoxide ≤80%, gross tumor volume ≥100 cm(3) and subcarinal nodal involvement were the statistically significant predictive factors for poor overall survival both in univariate and multivariate analyses. Patients were classified into four groups according to these four predictive factors. The median survival times were 36, 29, 18 and 14 months in Groups I, II, III and IV, respectively (P < 0.001). Rates of esophageal or lung toxicity ≥Grade 3 were 5.9, 14.1, 12.5 and 22.2%, respectively. The radiotherapy interruption rate differed significantly between the prognostic subgroups; 8.8, 15.4, 22.7 and 30.6%, respectively (P = 0.017). Severe toxicity and interruption of radiotherapy were more frequent in patients with multiple adverse predictive factors. To maintain the survival benefit in patients with concurrent chemoradiotherapy, strategies to reduce treatment-related toxicities need to be deeply considered. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Molecular markers to complement sentinel node status in predicting survival in patients with high-risk locally invasive melanoma.

PubMed

Rowe, Casey J; Tang, Fiona; Hughes, Maria Celia B; Rodero, Mathieu P; Malt, Maryrose; Lambie, Duncan; Barbour, Andrew; Hayward, Nicholas K; Smithers, B Mark; Green, Adele C; Khosrotehrani, Kiarash

2016-08-01

Sentinel lymph node status is a major prognostic marker in locally invasive cutaneous melanoma. However, this procedure is not always feasible, requires advanced logistics and carries rare but significant morbidity. Previous studies have linked markers of tumour biology to patient survival. In this study, we aimed to combine the predictive value of established biomarkers in addition to clinical parameters as indicators of survival in addition to or instead of sentinel node biopsy in a cohort of high-risk melanoma patients. Patients with locally invasive melanomas undergoing sentinel lymph node biopsy were ascertained and prospectively followed. Information on mortality was validated through the National Death Index. Immunohistochemistry was used to analyse proteins previously reported to be associated with melanoma survival, namely Ki67, p16 and CD163. Evaluation and multivariate analyses according to REMARK criteria were used to generate models to predict disease-free and melanoma-specific survival. A total of 189 patients with available archival material of their primary tumour were analysed. Our study sample was representative of the entire cohort (N = 559). Average Breslow thickness was 2.5 mm. Thirty-two (17%) patients in the study sample died from melanoma during the follow-up period. A prognostic score was developed and was strongly predictive of survival, independent of sentinel node status. The score allowed classification of risk of melanoma death in sentinel node-negative patients. Combining clinicopathological factors and established biomarkers allows prediction of outcome in locally invasive melanoma and might be implemented in addition to or in cases when sentinel node biopsy cannot be performed. © 2016 UICC.

LOCALIZER: subcellular localization prediction of both plant and effector proteins in the plant cell

PubMed Central

Sperschneider, Jana; Catanzariti, Ann-Maree; DeBoer, Kathleen; Petre, Benjamin; Gardiner, Donald M.; Singh, Karam B.; Dodds, Peter N.; Taylor, Jennifer M.

2017-01-01

Pathogens secrete effector proteins and many operate inside plant cells to enable infection. Some effectors have been found to enter subcellular compartments by mimicking host targeting sequences. Although many computational methods exist to predict plant protein subcellular localization, they perform poorly for effectors. We introduce LOCALIZER for predicting plant and effector protein localization to chloroplasts, mitochondria, and nuclei. LOCALIZER shows greater prediction accuracy for chloroplast and mitochondrial targeting compared to other methods for 652 plant proteins. For 107 eukaryotic effectors, LOCALIZER outperforms other methods and predicts a previously unrecognized chloroplast transit peptide for the ToxA effector, which we show translocates into tobacco chloroplasts. Secretome-wide predictions and confocal microscopy reveal that rust fungi might have evolved multiple effectors that target chloroplasts or nuclei. LOCALIZER is the first method for predicting effector localisation in plants and is a valuable tool for prioritizing effector candidates for functional investigations. LOCALIZER is available at http://localizer.csiro.au/. PMID:28300209

Are Culturally Specific Measures of Trauma-Related Anxiety and Depression Needed? The Case of Sri Lanka

ERIC Educational Resources Information Center

Jayawickreme, Nuwan; Jayawickreme, Eranda; Atanasov, Pavel; Goonasekera, Michelle A.; Foa, Edna B.

2012-01-01

The hypothesis that psychometric instruments incorporating local idioms of distress predict functional impairment in a non-Western, war-affected population above and beyond translations of already established instruments was tested. Exploratory factor analysis was conducted on the War-Related Psychological and Behavioral Problems section of the…

Effect of soil conditions on predicted ground motion: Case study from Western Anatolia, Turkey

NASA Astrophysics Data System (ADS)

Gok, Elcin; Chávez-García, Francisco J.; Polat, Orhan

2014-04-01

We present a site effect study for the city of Izmir, Western Anatolia, Turkey. Local amplification was evaluated using state-of-practice tools. Ten earthquakes recorded at 16 sites were analysed using spectral ratios relative to a reference site, horizontal-to-vertical spectral ratios, and an inversion scheme of the Fourier amplitude spectra of the recorded S-waves. Seismic noise records were also used to estimate site effects. The different estimates are in good agreement among them, although a basic uncertainty of a factor of 2 seems difficult to decrease. We used our site effect estimates to predict ground motion in Izmir for a possible M6.5 earthquake close to the city using stochastic modelling. Site effects have a large impact on PSV (pseudospectral velocity), where local amplification increases amplitudes by almost a factor of 9 at 1 Hz relative to the firm ground condition. Our results allow identifying the neighbourhoods of Izmir where hazard mitigation measurements are a priority task and will also be useful for planning urban development.

High-resolution modeling of thermal thresholds and environmental influences on coral bleaching for local and regional reef management.

PubMed

Kumagai, Naoki H; Yamano, Hiroya

2018-01-01

Coral reefs are one of the world's most threatened ecosystems, with global and local stressors contributing to their decline. Excessive sea-surface temperatures (SSTs) can cause coral bleaching, resulting in coral death and decreases in coral cover. A SST threshold of 1 °C over the climatological maximum is widely used to predict coral bleaching. In this study, we refined thermal indices predicting coral bleaching at high-spatial resolution (1 km) by statistically optimizing thermal thresholds, as well as considering other environmental influences on bleaching such as ultraviolet (UV) radiation, water turbidity, and cooling effects. We used a coral bleaching dataset derived from the web-based monitoring system Sango Map Project, at scales appropriate for the local and regional conservation of Japanese coral reefs. We recorded coral bleaching events in the years 2004-2016 in Japan. We revealed the influence of multiple factors on the ability to predict coral bleaching, including selection of thermal indices, statistical optimization of thermal thresholds, quantification of multiple environmental influences, and use of multiple modeling methods (generalized linear models and random forests). After optimization, differences in predictive ability among thermal indices were negligible. Thermal index, UV radiation, water turbidity, and cooling effects were important predictors of the occurrence of coral bleaching. Predictions based on the best model revealed that coral reefs in Japan have experienced recent and widespread bleaching. A practical method to reduce bleaching frequency by screening UV radiation was also demonstrated in this paper.

High-resolution modeling of thermal thresholds and environmental influences on coral bleaching for local and regional reef management

PubMed Central

Yamano, Hiroya

2018-01-01

Coral reefs are one of the world’s most threatened ecosystems, with global and local stressors contributing to their decline. Excessive sea-surface temperatures (SSTs) can cause coral bleaching, resulting in coral death and decreases in coral cover. A SST threshold of 1 °C over the climatological maximum is widely used to predict coral bleaching. In this study, we refined thermal indices predicting coral bleaching at high-spatial resolution (1 km) by statistically optimizing thermal thresholds, as well as considering other environmental influences on bleaching such as ultraviolet (UV) radiation, water turbidity, and cooling effects. We used a coral bleaching dataset derived from the web-based monitoring system Sango Map Project, at scales appropriate for the local and regional conservation of Japanese coral reefs. We recorded coral bleaching events in the years 2004–2016 in Japan. We revealed the influence of multiple factors on the ability to predict coral bleaching, including selection of thermal indices, statistical optimization of thermal thresholds, quantification of multiple environmental influences, and use of multiple modeling methods (generalized linear models and random forests). After optimization, differences in predictive ability among thermal indices were negligible. Thermal index, UV radiation, water turbidity, and cooling effects were important predictors of the occurrence of coral bleaching. Predictions based on the best model revealed that coral reefs in Japan have experienced recent and widespread bleaching. A practical method to reduce bleaching frequency by screening UV radiation was also demonstrated in this paper. PMID:29473007

Social ecology of child soldiers: child, family, and community determinants of mental health, psychosocial well-being, and reintegration in Nepal.

PubMed

Kohrt, Brandon A; Jordans, Mark J D; Tol, Wietse A; Perera, Em; Karki, Rohit; Koirala, Suraj; Upadhaya, Nawaraj

2010-11-01

This study employed a social ecology framework to evaluate psychosocial well-being in a cross-sectional sample of 142 former child soldiers in Nepal. Outcome measures included the Depression Self Rating Scale (DSRS), Child Posttraumatic Stress Disorder Symptom Scale (CPSS), and locally developed measures of functional impairment and reintegration. Hierarchical linear modeling was used to examine the contribution of factors at multiple levels. At the child level, traumatic exposures, especially torture, predicted poor outcomes, while education improved outcomes. At the family level, conflict-related death of a relative, physical abuse in the household, and loss of wealth during the conflict predicted poor outcomes. At the community level, living in high caste Hindu communities predicted lack of reintegration supports. Ultimately, social ecology is well suited to identify intervention foci across ecological levels based on community differences in vulnerability and protective factors.

Biomarkers for Response to Neoadjuvant Chemoradiation for Rectal Cancer

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

Kuremsky, Jeffrey G.; UNC Doris Duke Clinical Research Fellowship Program, Chapel Hill, NC; Tepper, Joel E.

2009-07-01

Locally advanced rectal cancer (LARC) is currently treated with neoadjuvant chemoradiation. Although approximately 45% of patients respond to neoadjuvant therapy with T-level downstaging, there is no effective method of predicting which patients will respond. Molecular biomarkers have been investigated for their ability to predict outcome in LARC treated with neoadjuvant chemotherapy and radiation. A literature search using PubMed resulted in the initial assessment of 1,204 articles. Articles addressing the ability of a biomarker to predict outcome for LARC treated with neoadjuvant chemotherapy and radiation were included. Six biomarkers met the criteria for review: p53, epidermal growth factor receptor (EGFR), thymidylatemore » synthase, Ki-67, p21, and bcl-2/bax. On the basis of composite data, p53 is unlikely to have utility as a predictor of response. Epidermal growth factor receptor has shown promise as a predictor when quantitatively evaluated in pretreatment biopsies or when EGFR polymorphisms are evaluated in germline DNA. Thymidylate synthase, when evaluated for polymorphisms in germline DNA, is promising as a predictive biomarker. Ki-67 and bcl-2 are not useful in predicting outcome. p21 needs to be further evaluated to determine its usefulness in predicting outcome. Bax requires more investigation to determine its usefulness. Epidermal growth factor receptor, thymidylate synthase, and p21 should be evaluated in larger prospective clinical trials for their ability to guide preoperative therapy choices in LARC.« less

Coupling of the Models of Human Physiology and Thermal Comfort

NASA Astrophysics Data System (ADS)

Pokorny, J.; Jicha, M.

2013-04-01

A coupled model of human physiology and thermal comfort was developed in Dymola/Modelica. A coupling combines a modified Tanabe model of human physiology and thermal comfort model developed by Zhang. The Coupled model allows predicting the thermal sensation and comfort of both local and overall from local boundary conditions representing ambient and personal factors. The aim of this study was to compare prediction of the Coupled model with the Fiala model prediction and experimental data. Validation data were taken from the literature, mainly from the validation manual of software Theseus-FE [1]. In the paper validation of the model for very light physical activities (1 met) indoor environment with temperatures from 12 °C up to 48 °C is presented. The Coupled model predicts mean skin temperature for cold, neutral and warm environment well. However prediction of core temperature in cold environment is inaccurate and very affected by ambient temperature. Evaluation of thermal comfort in warm environment is supplemented by skin wettedness prediction. The Coupled model is designed for non-uniform and transient environmental conditions; it is also suitable simulation of thermal comfort in vehicles cabins. The usage of the model is limited for very light physical activities up to 1.2 met only.

Using Chou's pseudo amino acid composition based on approximate entropy and an ensemble of AdaBoost classifiers to predict protein subnuclear location.

PubMed

Jiang, Xiaoying; Wei, Rong; Zhao, Yanjun; Zhang, Tongliang

2008-05-01

The knowledge of subnuclear localization in eukaryotic cells is essential for understanding the life function of nucleus. Developing prediction methods and tools for proteins subnuclear localization become important research fields in protein science for special characteristics in cell nuclear. In this study, a novel approach has been proposed to predict protein subnuclear localization. Sample of protein is represented by Pseudo Amino Acid (PseAA) composition based on approximate entropy (ApEn) concept, which reflects the complexity of time series. A novel ensemble classifier is designed incorporating three AdaBoost classifiers. The base classifier algorithms in three AdaBoost are decision stumps, fuzzy K nearest neighbors classifier, and radial basis-support vector machines, respectively. Different PseAA compositions are used as input data of different AdaBoost classifier in ensemble. Genetic algorithm is used to optimize the dimension and weight factor of PseAA composition. Two datasets often used in published works are used to validate the performance of the proposed approach. The obtained results of Jackknife cross-validation test are higher and more balance than them of other methods on same datasets. The promising results indicate that the proposed approach is effective and practical. It might become a useful tool in protein subnuclear localization. The software in Matlab and supplementary materials are available freely by contacting the corresponding author.

Computer simulation of the linear and nonlinear optical susceptibilities of p-nitroaniline in cyclohexane, 1,4-dioxane, and tetrahydrofuran in quadrupolar approximation. II. Local field effects and optical susceptibilitities.

PubMed

Reis, H; Papadopoulos, M G; Grzybowski, A

2006-09-21

This is the second part of a study to elucidate the local field effects on the nonlinear optical properties of p-nitroaniline (pNA) in three solvents of different multipolar character, that is, cyclohexane (CH), 1,4-dioxane (DI), and tetrahydrofuran (THF), employing a discrete description of the solutions. By the use of liquid structure information from molecular dynamics simulations and molecular properties computed by high-level ab initio methods, the local field and local field gradients on p-nitroaniline and the solvent molecules are computed in quadrupolar approximation. To validate the simulations and the induction model, static and dynamic (non)linear properties of the pure solvents are also computed. With the exception of the static dielectric constant of pure THF, a good agreement between computed and experimental refractive indices, dielectric constants, and third harmonic generation signals is obtained for the solvents. For the solutions, it is found that multipole moments up to two orders higher than quadrupole have a negligible influence on the local fields on pNA, if a simple distribution model is employed for the electric properties of pNA. Quadrupole effects are found to be nonnegligible in all three solvents but are especially pronounced in the 1,4-dioxane solvent, in which the local fields are similar to those in THF, although the dielectric constant of DI is 2.2 and that of the simulated THF is 5.4. The electric-field-induced second harmonic generation (EFISH) signal and the hyper-Rayleigh scattering signal of pNA in the solutions computed with the local field are in good to fair agreement with available experimental results. This confirms the effect of the "dioxane anomaly" also on nonlinear optical properties. Predictions based on an ellipsoidal Onsager model as applied by experimentalists are in very good agreement with the discrete model predictions. This is in contrast to a recent discrete reaction field calculation of pNA in 1,4-dioxane, which found that the predicted first hyperpolarizability of pNA deviated strongly from the predictions obtained using Onsager-Lorentz local field factors.

Planning Target Volume D95 and Mean Dose Should Be Considered for Optimal Local Control for Stereotactic Ablative Radiation Therapy

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

Zhao, Lina; Zhou, Shouhao; Balter, Peter

Purpose: To identify the optimal dose parameters predictive for local/lobar control after stereotactic ablative radiation therapy (SABR) in early-stage non-small cell lung cancer (NSCLC). Methods and Materials: This study encompassed a total of 1092 patients (1200 lesions) with NSCLC of clinical stage T1-T2 N0M0 who were treated with SABR of 50 Gy in 4 fractions or 70 Gy in 10 fractions, depending on tumor location/size, using computed tomography-based heterogeneity corrections and a convolution superposition calculation algorithm. Patients were monitored by chest CT or positron emission tomography/CT and/or biopsy after SABR. Factors predicting local/lobar recurrence (LR) were determined by competing risk multivariate analysis.more » Continuous variables were divided into 2 subgroups at cutoff values identified by receiver operating characteristic curves. Results: At a median follow-up time of 31.7 months (interquartile range, 14.8-51.3 months), the 5-year time to local recurrence within the same lobe and overall survival rates were 93.8% and 44.8%, respectively. Total cumulative number of patients experiencing LR was 40 (3.7%), occurring at a median time of 14.4 months (range, 4.8-46 months). Using multivariate competing risk analysis, independent predictive factors for LR after SABR were minimum biologically effective dose (BED{sub 10}) to 95% of planning target volume (PTVD95 BED{sub 10}) ≤86 Gy (corresponding to PTV D95 physics dose of 42 Gy in 4 fractions or 55 Gy in 10 fractions) and gross tumor volume ≥8.3 cm{sup 3}. The PTVmean BED{sub 10} was highly correlated with PTVD95 BED{sub 10.} In univariate analysis, a cutoff of 130 Gy for PTVmean BED{sub 10} (corresponding to PTVmean physics dose of 55 Gy in 4 fractions or 75 Gy in 10 fractions) was also significantly associated with LR. Conclusions: In addition to gross tumor volume, higher radiation dose delivered to the PTV predicts for better local/lobar control. We recommend that both PTVD95 BED{sub 10} >86 Gy and PTVmean BED{sub 10} >130 Gy should be considered for SABR plan optimization.« less

Microclimate variables of the ambient environment deliver the actual estimates of the extrinsic incubation period of Plasmodium vivax and Plasmodium falciparum: a study from a malaria-endemic urban setting, Chennai in India.

PubMed

Thomas, Shalu; Ravishankaran, Sangamithra; Justin, N A Johnson Amala; Asokan, Aswin; Kalsingh, T Maria Jusler; Mathai, Manu Thomas; Valecha, Neena; Montgomery, Jacqui; Thomas, Matthew B; Eapen, Alex

2018-05-16

Environmental factors such as temperature, relative humidity and their daily variation influence a range of mosquito life history traits and hence, malaria transmission. The standard way of characterizing environmental factors with meteorological station data need not be the actual microclimates experienced by mosquitoes within local transmission settings. A year-long study was conducted in Chennai, India to characterize local temperature and relative humidity (RH). Data loggers (Hobos) were placed in a range of probable indoor and outdoor resting sites of Anopheles stephensi. Recordings were taken hourly to estimate mean temperature and RH, together with daily temperature range (DTR) and daily relative humidity range. The temperature data were used to explore the predicted variation in extrinsic incubation period (EIP) of Plasmodium falciparum and Plasmodium vivax between microhabitats and across the year. Mean daily temperatures within the indoor settings were significantly warmer than those recorded outdoors. DTR in indoor environments was observed to be modest and ranged from 2 to 6 °C. Differences in EIP between microhabitats were most notable during the hottest summer months of April-June, with parasite development predicted to be impaired for tiled houses and overhead tanks. Overall, the prevailing warm and stable conditions suggest rapid parasite development rate regardless of where mosquitoes might rest. Taking account of seasonal and local environmental variation, the predicted EIP of P. falciparum varied from a minimum of 9.1 days to a maximum of 15.3 days, while the EIP of P. vivax varied from 8.0 to 24.3 days. This study provides a detailed picture of the actual microclimates experienced by mosquitoes in an urban slum malaria setting. The data indicate differences between microhabitats that could impact mosquito and parasite life history traits. The predicted effects for EIP are often relatively subtle, but variation between minimum and maximum EIPs can play a role in disease transmission, depending on the time of year and where mosquitoes rest. Appropriate characterization of the local microclimate conditions would be the key to fully understand the effects of environment on local transmission ecology.

3D-QSAR based on quantum-chemical molecular fields: toward an improved description of halogen interactions.

PubMed

Güssregen, Stefan; Matter, Hans; Hessler, Gerhard; Müller, Marco; Schmidt, Friedemann; Clark, Timothy

2012-09-24

Current 3D-QSAR methods such as CoMFA or CoMSIA make use of classical force-field approaches for calculating molecular fields. Thus, they can not adequately account for noncovalent interactions involving halogen atoms like halogen bonds or halogen-π interactions. These deficiencies in the underlying force fields result from the lack of treatment of the anisotropy of the electron density distribution of those atoms, known as the "σ-hole", although recent developments have begun to take specific interactions such as halogen bonding into account. We have now replaced classical force field derived molecular fields by local properties such as the local ionization energy, local electron affinity, or local polarizability, calculated using quantum-mechanical (QM) techniques that do not suffer from the above limitation for 3D-QSAR. We first investigate the characteristics of QM-based local property fields to show that they are suitable for statistical analyses after suitable pretreatment. We then analyze these property fields with partial least-squares (PLS) regression to predict biological affinities of two data sets comprising factor Xa and GABA-A/benzodiazepine receptor ligands. While the resulting models perform equally well or even slightly better in terms of consistency and predictivity than the classical CoMFA fields, the most important aspect of these augmented field-types is that the chemical interpretation of resulting QM-based property field models reveals unique SAR trends driven by electrostatic and polarizability effects, which cannot be extracted directly from CoMFA electrostatic maps. Within the factor Xa set, the interaction of chlorine and bromine atoms with a tyrosine side chain in the protease S1 pocket are correctly predicted. Within the GABA-A/benzodiazepine ligand data set, PLS models of high predictivity resulted for our QM-based property fields, providing novel insights into key features of the SAR for two receptor subtypes and cross-receptor selectivity of the ligands. The detailed interpretation of regression models derived using improved QM-derived property fields thus provides a significant advantage by revealing chemically meaningful correlations with biological activity and helps in understanding novel structure-activity relationship features. This will allow such knowledge to be used to design novel molecules on the basis of interactions additional to steric and hydrogen-bonding features.

Development of a hierarchical model for predicting microbiological contamination of private groundwater supplies in a geologically heterogeneous region.

PubMed

O'Dwyer, Jean; Hynds, Paul D; Byrne, Kenneth A; Ryan, Michael P; Adley, Catherine C

2018-06-01

Private groundwater sources in the Republic of Ireland provide drinking water to an estimated 750,000 people or 16% of the national population. Consumers of untreated groundwater are at increased risk of infection from pathogenic microorganisms. However, given the volume of private wells in operation, remediation or even quantification of public risk is both costly and time consuming. In this study, a hierarchical logistic regression model was developed to 'predict' contamination with E. coli based on the results of groundwater quality analyses of private wells (n = 132) during the period of September 2011 to November 2012. Assessment of potential microbial contamination risk factors were categorised into three groups: Intrinsic (environmental factors), Specific (local features) and Infrastructural (groundwater source characteristics) which included a total of 15 variables. Overall, 51.4% of wells tested positive for E. coli during the study period with univariate analysis indicating that 11 of the 15 assessed risk factors, including local bedrock type, local subsoil type, septic tank reliance, 5 day antecedent precipitation and temperature, along with well type and depth, were all significantly associated with E. coli presence (p < 0.05). Hierarchical logistic regression was used to develop a private well susceptibility model with the final model containing 8 of the 11 associated variables. The model was shown to be highly efficient; correctly classifying the presence of E. coli in 94.2% of cases, and the absence of E. coli in 84.7% of cases. Model validation was performed using an external data set (n = 32) and it was shown that the model has promising accuracy with 90% of positive E. coli cases correctly predicted. The developed model represents a risk assessment and management tool that may be used to develop effective water-quality management strategies to minimize public health risks both in Ireland and abroad. Copyright © 2018 Elsevier Ltd. All rights reserved.

Nomograms Predicting Progression-Free Survival, Overall Survival, and Pelvic Recurrence in Locally Advanced Cervical Cancer Developed From an Analysis of Identifiable Prognostic Factors in Patients From NRG Oncology/Gynecologic Oncology Group Randomized Trials of Chemoradiotherapy

PubMed Central

Rose, Peter G.; Java, James; Whitney, Charles W.; Stehman, Frederick B.; Lanciano, Rachelle; Thomas, Gillian M.; DiSilvestro, Paul A.

2015-01-01

Purpose To evaluate the prognostic factors in locally advanced cervical cancer limited to the pelvis and develop nomograms for 2-year progression-free survival (PFS), 5-year overall survival (OS), and pelvic recurrence. Patients and Methods We retrospectively reviewed 2,042 patients with locally advanced cervical carcinoma enrolled onto Gynecologic Oncology Group clinical trials of concurrent cisplatin-based chemotherapy and radiotherapy. Nomograms for 2-year PFS, five-year OS, and pelvic recurrence were created as visualizations of Cox proportional hazards regression models. The models were validated by bootstrap-corrected, relatively unbiased estimates of discrimination and calibration. Results Multivariable analysis identified prognostic factors including histology, race/ethnicity, performance status, tumor size, International Federation of Gynecology and Obstetrics stage, tumor grade, pelvic node status, and treatment with concurrent cisplatin-based chemotherapy. PFS, OS, and pelvic recurrence nomograms had bootstrap-corrected concordance indices of 0.62, 0.64, and 0.73, respectively, and were well calibrated. Conclusion Prognostic factors were used to develop nomograms for 2-year PFS, 5-year OS, and pelvic recurrence for locally advanced cervical cancer clinically limited to the pelvis treated with concurrent cisplatin-based chemotherapy and radiotherapy. These nomograms can be used to better estimate individual and collective outcomes. PMID:25732170

Support Vector Machine-Based Prediction of Local Tumor Control After Stereotactic Body Radiation Therapy for Early-Stage Non-Small Cell Lung Cancer

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

Klement, Rainer J., E-mail: rainer_klement@gmx.de; Department of Radiotherapy and Radiation Oncology, Leopoldina Hospital, Schweinfurt; Allgäuer, Michael

2014-03-01

Background: Several prognostic factors for local tumor control probability (TCP) after stereotactic body radiation therapy (SBRT) for early stage non-small cell lung cancer (NSCLC) have been described, but no attempts have been undertaken to explore whether a nonlinear combination of potential factors might synergistically improve the prediction of local control. Methods and Materials: We investigated a support vector machine (SVM) for predicting TCP in a cohort of 399 patients treated at 13 German and Austrian institutions. Among 7 potential input features for the SVM we selected those most important on the basis of forward feature selection, thereby evaluating classifier performancemore » by using 10-fold cross-validation and computing the area under the ROC curve (AUC). The final SVM classifier was built by repeating the feature selection 10 times with different splitting of the data for cross-validation and finally choosing only those features that were selected at least 5 out of 10 times. It was compared with a multivariate logistic model that was built by forward feature selection. Results: Local failure occurred in 12% of patients. Biologically effective dose (BED) at the isocenter (BED{sub ISO}) was the strongest predictor of TCP in the logistic model and also the most frequently selected input feature for the SVM. A bivariate logistic function of BED{sub ISO} and the pulmonary function indicator forced expiratory volume in 1 second (FEV1) yielded the best description of the data but resulted in a significantly smaller AUC than the final SVM classifier with the input features BED{sub ISO}, age, baseline Karnofsky index, and FEV1 (0.696 ± 0.040 vs 0.789 ± 0.001, P<.03). The final SVM resulted in sensitivity and specificity of 67.0% ± 0.5% and 78.7% ± 0.3%, respectively. Conclusions: These results confirm that machine learning techniques like SVMs can be successfully applied to predict treatment outcome after SBRT. Improvements over traditional TCP modeling are expected through a nonlinear combination of multiple features, eventually helping in the task of personalized treatment planning.« less

Support vector machine-based prediction of local tumor control after stereotactic body radiation therapy for early-stage non-small cell lung cancer.

PubMed

Klement, Rainer J; Allgäuer, Michael; Appold, Steffen; Dieckmann, Karin; Ernst, Iris; Ganswindt, Ute; Holy, Richard; Nestle, Ursula; Nevinny-Stickel, Meinhard; Semrau, Sabine; Sterzing, Florian; Wittig, Andrea; Andratschke, Nicolaus; Guckenberger, Matthias

2014-03-01

Several prognostic factors for local tumor control probability (TCP) after stereotactic body radiation therapy (SBRT) for early stage non-small cell lung cancer (NSCLC) have been described, but no attempts have been undertaken to explore whether a nonlinear combination of potential factors might synergistically improve the prediction of local control. We investigated a support vector machine (SVM) for predicting TCP in a cohort of 399 patients treated at 13 German and Austrian institutions. Among 7 potential input features for the SVM we selected those most important on the basis of forward feature selection, thereby evaluating classifier performance by using 10-fold cross-validation and computing the area under the ROC curve (AUC). The final SVM classifier was built by repeating the feature selection 10 times with different splitting of the data for cross-validation and finally choosing only those features that were selected at least 5 out of 10 times. It was compared with a multivariate logistic model that was built by forward feature selection. Local failure occurred in 12% of patients. Biologically effective dose (BED) at the isocenter (BED(ISO)) was the strongest predictor of TCP in the logistic model and also the most frequently selected input feature for the SVM. A bivariate logistic function of BED(ISO) and the pulmonary function indicator forced expiratory volume in 1 second (FEV1) yielded the best description of the data but resulted in a significantly smaller AUC than the final SVM classifier with the input features BED(ISO), age, baseline Karnofsky index, and FEV1 (0.696 ± 0.040 vs 0.789 ± 0.001, P<.03). The final SVM resulted in sensitivity and specificity of 67.0% ± 0.5% and 78.7% ± 0.3%, respectively. These results confirm that machine learning techniques like SVMs can be successfully applied to predict treatment outcome after SBRT. Improvements over traditional TCP modeling are expected through a nonlinear combination of multiple features, eventually helping in the task of personalized treatment planning. Copyright © 2014 Elsevier Inc. All rights reserved.

Parameterizing sorption isotherms using a hybrid global-local fitting procedure.

PubMed

Matott, L Shawn; Singh, Anshuman; Rabideau, Alan J

2017-05-01

Predictive modeling of the transport and remediation of groundwater contaminants requires an accurate description of the sorption process, which is usually provided by fitting an isotherm model to site-specific laboratory data. Commonly used calibration procedures, listed in order of increasing sophistication, include: trial-and-error, linearization, non-linear regression, global search, and hybrid global-local search. Given the considerable variability in fitting procedures applied in published isotherm studies, we investigated the importance of algorithm selection through a series of numerical experiments involving 13 previously published sorption datasets. These datasets, considered representative of state-of-the-art for isotherm experiments, had been previously analyzed using trial-and-error, linearization, or non-linear regression methods. The isotherm expressions were re-fit using a 3-stage hybrid global-local search procedure (i.e. global search using particle swarm optimization followed by Powell's derivative free local search method and Gauss-Marquardt-Levenberg non-linear regression). The re-fitted expressions were then compared to previously published fits in terms of the optimized weighted sum of squared residuals (WSSR) fitness function, the final estimated parameters, and the influence on contaminant transport predictions - where easily computed concentration-dependent contaminant retardation factors served as a surrogate measure of likely transport behavior. Results suggest that many of the previously published calibrated isotherm parameter sets were local minima. In some cases, the updated hybrid global-local search yielded order-of-magnitude reductions in the fitness function. In particular, of the candidate isotherms, the Polanyi-type models were most likely to benefit from the use of the hybrid fitting procedure. In some cases, improvements in fitness function were associated with slight (<10%) changes in parameter values, but in other cases significant (>50%) changes in parameter values were noted. Despite these differences, the influence of isotherm misspecification on contaminant transport predictions was quite variable and difficult to predict from inspection of the isotherms. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Adaptation Method for Overall and Local Performances of Gas Turbine Engine Model

NASA Astrophysics Data System (ADS)

Kim, Sangjo; Kim, Kuisoon; Son, Changmin

2018-04-01

An adaptation method was proposed to improve the modeling accuracy of overall and local performances of gas turbine engine. The adaptation method was divided into two steps. First, the overall performance parameters such as engine thrust, thermal efficiency, and pressure ratio were adapted by calibrating compressor maps, and second, the local performance parameters such as temperature of component intersection and shaft speed were adjusted by additional adaptation factors. An optimization technique was used to find the correlation equation of adaptation factors for compressor performance maps. The multi-island genetic algorithm (MIGA) was employed in the present optimization. The correlations of local adaptation factors were generated based on the difference between the first adapted engine model and performance test data. The proposed adaptation method applied to a low-bypass ratio turbofan engine of 12,000 lb thrust. The gas turbine engine model was generated and validated based on the performance test data in the sea-level static condition. In flight condition at 20,000 ft and 0.9 Mach number, the result of adapted engine model showed improved prediction in engine thrust (overall performance parameter) by reducing the difference from 14.5 to 3.3%. Moreover, there was further improvement in the comparison of low-pressure turbine exit temperature (local performance parameter) as the difference is reduced from 3.2 to 0.4%.

On Bi-Grid Local Mode Analysis of Solution Techniques for 3-D Euler and Navier-Stokes Equations

NASA Technical Reports Server (NTRS)

Ibraheem, S. O.; Demuren, A. O.

1994-01-01

A procedure is presented for utilizing a bi-grid stability analysis as a practical tool for predicting multigrid performance in a range of numerical methods for solving Euler and Navier-Stokes equations. Model problems based on the convection, diffusion and Burger's equation are used to illustrate the superiority of the bi-grid analysis as a predictive tool for multigrid performance in comparison to the smoothing factor derived from conventional von Neumann analysis. For the Euler equations, bi-grid analysis is presented for three upwind difference based factorizations, namely Spatial, Eigenvalue and Combination splits, and two central difference based factorizations, namely LU and ADI methods. In the former, both the Steger-Warming and van Leer flux-vector splitting methods are considered. For the Navier-Stokes equations, only the Beam-Warming (ADI) central difference scheme is considered. In each case, estimates of multigrid convergence rates from the bi-grid analysis are compared to smoothing factors obtained from single-grid stability analysis. Effects of grid aspect ratio and flow skewness are examined. Both predictions are compared with practical multigrid convergence rates for 2-D Euler and Navier-Stokes solutions based on the Beam-Warming central scheme.

Machine-Learning Algorithms Predict Graft Failure After Liver Transplantation.

PubMed

Lau, Lawrence; Kankanige, Yamuna; Rubinstein, Benjamin; Jones, Robert; Christophi, Christopher; Muralidharan, Vijayaragavan; Bailey, James

2017-04-01

The ability to predict graft failure or primary nonfunction at liver transplant decision time assists utilization of scarce resource of donor livers, while ensuring that patients who are urgently requiring a liver transplant are prioritized. An index that is derived to predict graft failure using donor and recipient factors, based on local data sets, will be more beneficial in the Australian context. Liver transplant data from the Austin Hospital, Melbourne, Australia, from 2010 to 2013 has been included in the study. The top 15 donor, recipient, and transplant factors influencing the outcome of graft failure within 30 days were selected using a machine learning methodology. An algorithm predicting the outcome of interest was developed using those factors. Donor Risk Index predicts the outcome with an area under the receiver operating characteristic curve (AUC-ROC) value of 0.680 (95% confidence interval [CI], 0.669-0.690). The combination of the factors used in Donor Risk Index with the model for end-stage liver disease score yields an AUC-ROC of 0.764 (95% CI, 0.756-0.771), whereas survival outcomes after liver transplantation score obtains an AUC-ROC of 0.638 (95% CI, 0.632-0.645). The top 15 donor and recipient characteristics within random forests results in an AUC-ROC of 0.818 (95% CI, 0.812-0.824). Using donor, transplant, and recipient characteristics known at the decision time of a transplant, high accuracy in matching donors and recipients can be achieved, potentially providing assistance with clinical decision making.

Seasonal Drought Prediction: Advances, Challenges, and Future Prospects

NASA Astrophysics Data System (ADS)

Hao, Zengchao; Singh, Vijay P.; Xia, Youlong

2018-03-01

Drought prediction is of critical importance to early warning for drought managements. This review provides a synthesis of drought prediction based on statistical, dynamical, and hybrid methods. Statistical drought prediction is achieved by modeling the relationship between drought indices of interest and a suite of potential predictors, including large-scale climate indices, local climate variables, and land initial conditions. Dynamical meteorological drought prediction relies on seasonal climate forecast from general circulation models (GCMs), which can be employed to drive hydrological models for agricultural and hydrological drought prediction with the predictability determined by both climate forcings and initial conditions. Challenges still exist in drought prediction at long lead time and under a changing environment resulting from natural and anthropogenic factors. Future research prospects to improve drought prediction include, but are not limited to, high-quality data assimilation, improved model development with key processes related to drought occurrence, optimal ensemble forecast to select or weight ensembles, and hybrid drought prediction to merge statistical and dynamical forecasts.

[Studying the association between genetic polymorphism of growth factors and the development of primary open-angle glaucoma].

PubMed

Kirilenko, M Yu; Tikunova, E V; Sirotina, S S; Polonikov, A V; Bushueva, O Yu; Churnosov, M I

Primary open-angle glaucoma (POAG) is a multifactorial disease, etiopathogenesis of which largely depends on growth factors. Possessing a variety of medical and biological effects, these cytokines may influence the development and progression of POAG. to reveal the role of genetic polymorphisms of growth factors in predisposition to developing POAG that is refractory to local hypotensive therapy. The object of the study were 162 patients with stage II-III POAG, in whom local hypotensive therapy was inefficient, 90 patients with stage II-III POAG well controlled on local hypotensive therapy, and 191 controls. The material for the study was venous blood taken from the cubital vein of a proband. Isolation of genomic DNA was performed by phenol-chloroform extraction. Analysis of genetic polymorphisms of growth factors was performed through allelic discrimination. For that, synthesis of DNA was carried out via polymerase chain reaction (PCR). It is found that the T IGFR-1 genetic variant (OR=1.34) and a combination of the C VEGF-A and T IGFR-1 genetic variants (OR=1.90) are risk factors of developing POAG that is refractory to local hypotensive therapy. A statistical model for predicting such a risk has been proposed that includes: VEGF-A с.-958C>T genetic marker (rs 833,061), age, concomitant non-inflammatory ocular diseases, microvascular changes in the conjunctiva, the degree of pigmentation of the angle of the anterior chamber, and pseudoexfoliative syndrome. Recognition accuracy of the model is 90.42%. The T IGFR-1 genetic variant and a combination of the C VEGF-A and T IGFR-1 genetic variants increase the risk of developing POAG that is refractory to local hypotensive therapy.

The number counts and infrared backgrounds from infrared-bright galaxies

NASA Technical Reports Server (NTRS)

Hacking, P. B.; Soifer, B. T.

1991-01-01

Extragalactic number counts and diffuse backgrounds at 25, 60, and 100 microns are predicted using new luminosity functions and improved spectral-energy distribution density functions derived from IRAS observations of nearby galaxies. Galaxies at redshifts z less than 3 that are like those in the local universe should produce a minimum diffuse background of 0.0085, 0.038, and 0.13 MJy/sr at 25, 60, and 100 microns, respectively. Models with significant luminosity evolution predict backgrounds about a factor of 4 greater than this minimum.

Review of image defined risk factors in localized neuroblastoma patients: Results of the GPOH NB97 trial.

PubMed

Simon, Thorsten; Hero, Barbara; Benz-Bohm, Gabriele; von Schweinitz, Dietrich; Berthold, Frank

2008-05-01

Recently, an international expert group proposed revision of the International Neuroblastoma Staging System (INSS). Localized disease can be classified as L1 without and as L2 with image defined risk factors (IDRF published in JCO 2005; 23:8483-8489). Our aim was to evaluate IDRF for the prediction of resectability, complications, and outcome. Records of 520 localized neuroblastoma patients of the NB97 trial were reviewed. Patients were retrospectively classified as having IDRF or not. A total of 366 evaluable patients were then analyzed for extent and complications of surgery and the prognostic value of IDRF. Any IDRF was present in 26/160 of stage 1, 49/113 of stage 2, and 64/93 of stage 3 patients. Complete primary resection was achieved in 156/227 patients without IDRF and 43/139 patients with IDRF (P < 0.001). The frequency of complications was higher if any IDRF was present: 37/139 versus 33/227 (P = 0.006). Lack of IDRF was associated with better event free survival (3-year-EFS 86 +/- 2% vs. 75 +/- 4%, P = 0.010), whereas overall survival was similar (3-year-OS 98 +/- 1% vs. 96 +/- 2%, P = 0.462). EFS clearly depended on INSS stage (3-year-EFS 93 +/- 2% in stage 1, 78 +/- 4% in stage 2, and 69 +/- 5% in stage 3, P < 0.001). OS was not different (3-year-OS 98 +/- 1% vs. 99 +/- 1% vs. 94 +/- 2%, P = 0.056). Multivariate analysis demonstrated an impact of INSS stage on EFS only. IDRF were not shown to be significant for predicting EFS or OS. IDRF were useful in predicting risk and completeness of operation. IDRF failed as independent risk predictors in localized neuroblastoma. INSS more precisely identified patients with poor prognosis. (c) 2008 Wiley-Liss, Inc.

Characterization of Residual Stress Effects on Fatigue Crack Growth of a Friction Stir Welded Aluminum Alloy

NASA Technical Reports Server (NTRS)

Newman, John A.; Smith, Stephen W.; Seshadri, Banavara R.; James, Mark A.; Brazill, Richard L.; Schultz, Robert W.; Donald, J. Keith; Blair, Amy

2015-01-01

An on-line compliance-based method to account for residual stress effects in stress-intensity factor and fatigue crack growth property determinations has been evaluated. Residual stress intensity factor results determined from specimens containing friction stir weld induced residual stresses are presented, and the on-line method results were found to be in excellent agreement with residual stress-intensity factor data obtained using the cut compliance method. Variable stress-intensity factor tests were designed to demonstrate that a simple superposition model, summing the applied stress-intensity factor with the residual stress-intensity factor, can be used to determine the total crack-tip stress-intensity factor. Finite element, VCCT (virtual crack closure technique), and J-integral analysis methods have been used to characterize weld-induced residual stress using thermal expansion/contraction in the form of an equivalent delta T (change in local temperature during welding) to simulate the welding process. This equivalent delta T was established and applied to analyze different specimen configurations to predict residual stress distributions and associated residual stress-intensity factor values. The predictions were found to agree well with experimental results obtained using the crack- and cut-compliance methods.

Non-native species impacts on pond occupancy by an anuran

USGS Publications Warehouse

Adams, Michael J.; Pearl, Christopher A.; Galvan, Stephanie; McCreary, Brome

2011-01-01

Non-native fish and bullfrogs (Lithobates catesbeianus; Rana catesbeiana) are frequently cited as factors contributing to the decline of ranid frogs in the western United States (Bradford 2005). This hypothesis is supported by studies showing competition with or predation by these introduced species (Kupferberg 1997, Kiesecker and Blaustein 1998, Lawler et al. 1999, Knapp et al. 2001) and studies suggesting a deficit of native frogs at sites occupied by bullfrogs or game fish (Hammerson 1982, Schwalbe and Rosen 1988, Fisher and Shaffer 1996, Adams 1999). Conversely, other studies failed to find a negative association between native ranids and bullfrogs and point out that presence of non-native species correlates with habitat alterations that could also contribute to declines of native species (Hayes and Jennings 1986; Adams 1999, 2000; Pearl et al. 2005). A criticism of these studies is that they may not detect an effect of non-native species if the process of displacement is at an early stage. We are not aware of any studies that have monitored a set of native frog populations to determine if non-native species predict population losses. Our objective was to study site occupancy trends in relation to non-native species for northern red-legged frogs (Rana aurora) on federal lands in the southern Willamette Valley, Oregon. We conducted a 5-yr monitoring study to answer the following questions about the status and trends of the northern red-legged frog: 1) What is the rate of local extinction (how often is a site that is occupied in year t unoccupied in year t+1) and what factors predict variation in local extinction? and 2) What is the rate of colonization (how often is a site that is unoccupied in year t occupied in year t+1) and what factors predict variation in colonization? The factors we hypothesized for local extinction were: 1) bullfrog presence, 2) bullfrogs mediated by wetland vegetation, 3) non-native fish (Centrarchidae), 4) non-native fish mediated by wetland vegetation, 5) extent of emergent vegetation, 6) extent of riparian forest, and 7) a combined effect of bullfrogs and fish. The factors that we hypothesized for colonization were: 1) the extent of human influence in the surrounding landscape, 2) riparian forest, and 3) wetland size.

Voting on Vouchers: A Socio-Political Analysis of California Proposition 38, Fall 2000.

ERIC Educational Resources Information Center

Catterall, James S.; Chapleau, Richard

2003-01-01

Describes the construction and results of a predictive model that could help identify what factors seemed to influence voter choices on a school voucher constitutional amendment in California. Precinct voting outcome data from the County of Los Angeles were linked to voter demographics along with measures of local school quality and existing…

Opting out of the Bill: Voluntary Adequacy Funding in Maryland

ERIC Educational Resources Information Center

Finch, Maida A.; Goff, Peter; Houck, Eric

2016-01-01

The key to anticipating local response to state finance policy is to bridge knowledge of the state context with the specifications of the individual reform. Yet it is precisely this unique blend of social, political, and economic factors in any given state that makes the impact of school finance reforms difficult to predict, especially as these…

Oncologic outcome after local recurrence of chondrosarcoma: Analysis of prognostic factors.

PubMed

Kim, Han-Soo; Bindiganavile, Srimanth S; Han, Ilkyu

2015-06-01

Literature on outcome after local recurrence (LR) in chondrosarcoma is scarce and better appreciation of prognostic factors is needed. (1) To evaluate post-LR oncologic outcomes of disease-specific survival and subsequent LR and (2) to identify prognostic factors for post-LR oncologic outcomes. Review of 28 patients with locally recurrent chondrosarcoma from the original cohort of 150 patients, who were treated surgically with or without adjuvants between 1982 and 2011, was performed. Mean age was 46 years (range, 21-73) which included 20 males and 8 females with mean follow up of 8.4 ± 7.5 years (range, 1.2-31.0). Post-LR survival at 5 years was 58.6 ± 10.3%. Age greater than 50 years (P = 0.011) and LR occurring within 1 year of primary surgery (P = 0.011) independently predicted poor survival. Seven patients suffered subsequent LR, which was significantly affected by surgical margin for LR (P = 0.038). Long-term survival of locally recurrent chondrosarcoma is achievable in a substantial number of patients. Older age at onset of LR and shorter interval from primary surgery to LR identifies high risk patients for poor post-LR survival while, wide surgical margins at LR surgery reduces the risk of subsequent LR. © 2015 Wiley Periodicals, Inc.

The Selection of Children from Low-Income Families into Preschool

PubMed Central

Crosnoe, Robert; Purtell, Kelly M.; Davis-Kean, Pamela; Ansari, Arya; Benner, Aprile D.

2016-01-01

Because children from low-income families benefit from preschool but are less likely than other children to enroll, identifying factors that promote their enrollment can support research and policy aiming to reduce socioeconomic disparities in education. In this study, we tested an accommodations model with data on 6,250 children in the Early Childhood Longitudinal Study-Birth Cohort. In general, parental necessity (e.g., maternal employment) and human capital considerations (e.g., maternal education) most consistently predicted preschool enrollment among children from low-income families. Supply side factors (e.g., local child care options) and more necessity and human capital factors (e.g., having fewer children, desiring preparation for school) selected such children into preschool over parental care or other care arrangements, and several necessity factors (e.g., being less concerned about costs) selected them into non-Head Start preschools over Head Start programs. Systemic connections and child elicitation did not consistently predict preschool enrollment in this population. PMID:26890917

Biomechanics of Atherosclerotic Coronary Plaque: Site, Stability and In Vivo Elasticity Modeling

PubMed Central

Ohayon, Jacques; Finet, Gérard; Le Floc’h, Simon; Cloutier, Guy; Gharib, Ahmed M.; Heroux, Julie; Pettigrew, Roderic I.

2016-01-01

Coronary atheroma develop in local sites that are widely variable among patients and are considerably variable in their vulnerability for rupture. This article summarizes studies conducted by our collaborative laboratories on predictive biomechanical modeling of coronary plaques. It aims to give insights into the role of biomechanics in the development and localization of atherosclerosis, the morphologic features that determine vulnerable plaque stability, and emerging in vivo imaging techniques that may detect and characterize vulnerable plaque. Composite biomechanical and hemodynamic factors that influence the actual site of development of plaques have been studied. Plaque vulnerability, in vivo, is more challenging to assess. Important steps have been made in defining the biomechanical factors that are predictive of plaque rupture and the likelihood of this occurring if characteristic features are known. A critical key in defining plaque vulnerability is the accurate quantification of both the morphology and the mechanical properties of the diseased arteries. Recently, an early IVUS based palpography technique developed to assess local strain, elasticity and mechanical instabilities has been successfully revisited and improved to account for complex plaque geometries. This is based on an initial best estimation of the plaque components’ contours, allowing subsequent iteration for elastic modulus assessment as a basis for plaque stability determination. The improved method has also been preliminarily evaluated in patients with successful histologic correlation. Further clinical evaluation and refinement are on the horizon. PMID:24043605

BLIMPK/Streamline Surface Catalytic Heating Predictions on the Space Shuttle Orbiter

NASA Technical Reports Server (NTRS)

Marichalar, Jeremiah J.; Rochelle, William C.; Kirk, Benjamin S.; Campbell, Charles H.

2006-01-01

This paper describes the results of an analysis of localized catalytic heating effects to the U.S. Space Shuttle Orbiter Thermal Protection System (TPS). The analysis applies to the High-temperature Reusable Surface Insulation (HRSI) on the lower fuselage and wing acreage, as well as the critical Reinforced Carbon-Carbon on the nose cap, chin panel and the wing leading edge. The object of the analysis was to use a modified two-layer approach to predict the catalytic heating effects on the Orbiter windward HRSI tile acreage, nose cap, and wing leading edge assuming localized highly catalytic or fully catalytic surfaces. The method incorporated the Boundary Layer Integral Matrix Procedure Kinetic (BLIMPK) code with streamline inputs from viscous Navier-Stokes solutions to produce heating rates for localized fully catalytic and highly catalytic surfaces as well as for nominal partially catalytic surfaces (either Reinforced Carbon-Carbon or Reaction Cured Glass) with temperature-dependent recombination coefficients. The highly catalytic heating results showed very good correlation with Orbiter Experiments STS-2, -3, and -5 centerline and STS-5 wing flight data for the HRSI tiles. Recommended catalytic heating factors were generated for use in future Shuttle missions in the event of quick-time analysis of damaged or repaired TPS areas during atmospheric reentry. The catalytic factors are presented along the streamlines as well as a function of stagnation enthalpy so they can be used for arbitrary trajectories.

Predictive relevance of PD-L1 expression combined with CD8+ TIL density in stage III non-small cell lung cancer patients receiving concurrent chemoradiotherapy.

PubMed

Tokito, Takaaki; Azuma, Koichi; Kawahara, Akihiko; Ishii, Hidenobu; Yamada, Kazuhiko; Matsuo, Norikazu; Kinoshita, Takashi; Mizukami, Naohisa; Ono, Hirofumi; Kage, Masayoshi; Hoshino, Tomoaki

2016-03-01

Expression of programmed cell death-ligand 1 (PD-L1) is known to be a mechanism whereby cancer can escape immune surveillance, but little is known about factors predictive of efficacy in patients with locally advanced non-small cell lung cancer (NSCLC). We investigated the predictive relevance of PD-L1 expression and CD8+ tumour-infiltrating lymphocytes (TILs) density in patients with locally advanced NSCLC receiving concurrent chemoradiotherapy (CCRT). We retrospectively reviewed 74 consecutive patients with stage III NSCLC who had received CCRT. PD-L1 expression and CD8+ TIL density were evaluated by immunohistochemical analysis. Univariate and multivariate analyses demonstrated that CD8+ TIL density was an independent and significant predictive factor for progression-free survival (PFS) and OS, whereas PD-L1 expression was not correlated with PFS and OS. Sub-analysis revealed that the PD-L1+/CD8 low group had the shortest PFS (8.6 months, p = 0.02) and OS (13.9 months, p = 0.11), and that the PD-L1-/CD8 high group had the longest prognosis (median PFS and OS were not reached) by Kaplan-Meier curves of the four sub-groups. Among stage III NSCLC patients who received CCRT, there was a trend for poor survival in those who expressed PD-L1. Our analysis indicated that a combination of lack of PD-L1 expression and CD8+ TIL density was significantly associated with favourable survival in these patients. It is proposed that PD-L1 expression in combination with CD8+ TIL density could be a useful predictive biomarker in patients with stage III NSCLC. Copyright © 2015 Elsevier Ltd. All rights reserved.

Combination of Pre-Treatment DWI-Signal Intensity and S-1 Treatment: A Predictor of Survival in Patients with Locally Advanced Pancreatic Cancer Receiving Stereotactic Body Radiation Therapy and Sequential S-1.

PubMed

Zhang, Yu; Zhu, Xiaofei; Liu, Ri; Wang, Xianglian; Sun, Gaofeng; Song, Jiaqi; Lu, Jianping; Zhang, Huojun

2018-04-01

To identify whether the combination of pre-treatment radiological and clinical factors can predict the overall survival (OS) in patients with locally advanced pancreatic cancer (LAPC) treated with stereotactic body radiation and sequential S-1 (a prodrug of 5-FU combined with two modulators) therapy with improved accuracy compared with that of established clinical and radiologic risk models. Patients admitted with LAPC underwent diffusion weighted imaging (DWI) scan at 3.0-T (b = 600 s/mm 2 ). The mean signal intensity (SI b = 600) of region-of-interest (ROI) was measured. The Log-rank test was done for tumor location, biliary stent, S-1, and other treatments and the Cox regression analysis was done to identify independent prognostic factors for OS. Prediction error curves (PEC) were used to assess potential errors in prediction of survival. The accuracy of prediction was evaluated by Integrated Brier Score (IBS) and C index. 41 patients were included in this study. The median OS was 11.7 months (2.8-23.23 months). The 1-year OS was 46%. Multivariate analysis showed that pre-treatment SI b = 600 value and administration of S-1 were independent predictors for OS. The performance of pre-treatment SI b = 600 and S-1 treatment in combination was better than that of SI b = 600 or S-1 treatment alone. The combination of pre-treatment SI b = 600 and S-1 treatment could predict the OS in patients with LAPC undergoing SBRT and sequential S-1 therapy with improved accuracy compared with that of established clinical and radiologic risk models. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Identifying Clinical Factors Which Predict for Early Failure Patterns Following Resection for Pancreatic Adenocarcinoma in Patients Who Received Adjuvant Chemotherapy Without Chemoradiation.

PubMed

Walston, Steve; Salloum, Joseph; Grieco, Carmine; Wuthrick, Evan; Diaz, Dayssy A; Barney, Christian; Manilchuk, Andrei; Schmidt, Carl; Dillhoff, Mary; Pawlik, Timothy M; Williams, Terence M

2018-05-04

The role of radiation therapy (RT) in resected pancreatic cancer (PC) remains incompletely defined. We sought to determine clinical variables which predict for local-regional recurrence (LRR) to help select patients for adjuvant RT. We identified 73 patients with PC who underwent resection and adjuvant gemcitabine-based chemotherapy alone. We performed detailed radiologic analysis of first patterns of failure. LRR was defined as recurrence of PC within standard postoperative radiation volumes. Univariate analyses (UVA) were conducted using the Kaplan-Meier method and multivariate analyses (MVA) utilized the Cox proportional hazard ratio model. Factors significant on UVA were used for MVA. At median follow-up of 20 months, rates of local-regional recurrence only (LRRO) were 24.7%, LRR as a component of any failure 68.5%, metastatic recurrence (MR) as a component of any failure 65.8%, and overall disease recurrence (OR) 90.5%. On UVA, elevated postoperative CA 19-9 (>90 U/mL), pathologic lymph node positive (pLN+) disease, and higher tumor grade were associated with increased LRR, MR, and OR. On MVA, elevated postoperative CA 19-9 and pLN+ were associated with increased MR and OR. In addition, positive resection margin was associated with increased LRRO on both UVA and MVA. About 25% of patients with PC treated without adjuvant RT develop LRRO as initial failure. The only independent predictor of LRRO was positive margin, while elevated postoperative CA 19-9 and pLN+ were associated with predicting MR and overall survival. These data may help determine which patients benefit from intensification of local therapy with radiation.

Environmental Predictors of US County Mortality Patterns on a National Basis.

PubMed

Chan, Melissa P L; Weinhold, Robert S; Thomas, Reuben; Gohlke, Julia M; Portier, Christopher J

2015-01-01

A growing body of evidence has found that mortality rates are positively correlated with social inequalities, air pollution, elevated ambient temperature, availability of medical care and other factors. This study develops a model to predict the mortality rates for different diseases by county across the US. The model is applied to predict changes in mortality caused by changing environmental factors. A total of 3,110 counties in the US, excluding Alaska and Hawaii, were studied. A subset of 519 counties from the 3,110 counties was chosen by using systematic random sampling and these samples were used to validate the model. Step-wise and linear regression analyses were used to estimate the ability of environmental pollutants, socio-economic factors and other factors to explain variations in county-specific mortality rates for cardiovascular diseases, cancers, chronic obstructive pulmonary disease (COPD), all causes combined and lifespan across five population density groups. The estimated models fit adequately for all mortality outcomes for all population density groups and, adequately predicted risks for the 519 validation counties. This study suggests that, at local county levels, average ozone (0.07 ppm) is the most important environmental predictor of mortality. The analysis also illustrates the complex inter-relationships of multiple factors that influence mortality and lifespan, and suggests the need for a better understanding of the pathways through which these factors, mortality, and lifespan are related at the community level.

Environmental Predictors of US County Mortality Patterns on a National Basis

PubMed Central

Thomas, Reuben; Gohlke, Julia M.; Portier, Christopher J.

2015-01-01

A growing body of evidence has found that mortality rates are positively correlated with social inequalities, air pollution, elevated ambient temperature, availability of medical care and other factors. This study develops a model to predict the mortality rates for different diseases by county across the US. The model is applied to predict changes in mortality caused by changing environmental factors. A total of 3,110 counties in the US, excluding Alaska and Hawaii, were studied. A subset of 519 counties from the 3,110 counties was chosen by using systematic random sampling and these samples were used to validate the model. Step-wise and linear regression analyses were used to estimate the ability of environmental pollutants, socio-economic factors and other factors to explain variations in county-specific mortality rates for cardiovascular diseases, cancers, chronic obstructive pulmonary disease (COPD), all causes combined and lifespan across five population density groups. The estimated models fit adequately for all mortality outcomes for all population density groups and, adequately predicted risks for the 519 validation counties. This study suggests that, at local county levels, average ozone (0.07 ppm) is the most important environmental predictor of mortality. The analysis also illustrates the complex inter-relationships of multiple factors that influence mortality and lifespan, and suggests the need for a better understanding of the pathways through which these factors, mortality, and lifespan are related at the community level. PMID:26629706

Parafoveal Target Detectability Reversal Predicted by Local Luminance and Contrast Gain Control

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.; Beard, Bettina L.; Null, Cynthia H. (Technical Monitor)

1996-01-01

This project is part of a program to develop image discrimination models for the prediction of the detectability of objects in a range of backgrounds. We wanted to see if the models could predict parafoveal object detection as well as they predict detection in foveal vision. We also wanted to make our simplified models more general by local computation of luminance and contrast gain control. A signal image (0.78 x 0.17 deg) was made by subtracting a simulated airport runway scene background image (2.7 deg square) from the same scene containing an obstructing aircraft. Signal visibility contrast thresholds were measured in a fully crossed factorial design with three factors: eccentricity (0 deg or 4 deg), background (uniform or runway scene background), and fixed-pattern white noise contrast (0%, 5%, or 10%). Three experienced observers responded to three repetitions of 60 2IFC trials in each condition and thresholds were estimated by maximum likelihood probit analysis. In the fovea the average detection contrast threshold was 4 dB lower for the runway background than for the uniform background, but in the parafovea, the average threshold was 6 dB higher for the runway background than for the uniform background. This interaction was similar across the different noise levels and for all three observers. A likely reason for the runway background giving a lower threshold in the fovea is the low luminance near the signal in that scene. In our model, the local luminance computation is controlled by a spatial spread parameter. When this parameter and a corresponding parameter for the spatial spread of contrast gain were increased for the parafoveal predictions, the model predicts the interaction of background with eccentricity.

A Novel Risk Stratification to Predict Local-Regional Failures in Urothelial Carcinoma of the Bladder After Radical Cystectomy

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

Baumann, Brian C.; Guzzo, Thomas J.; He Jiwei

2013-01-01

Purpose: Local-regional failures (LF) following radical cystectomy (RC) plus pelvic lymph node dissection (PLND) with or without chemotherapy for invasive urothelial bladder carcinoma are more common than previously reported. Adjuvant radiation therapy (RT) could reduce LF but currently has no defined role because of previously reported morbidity. Modern techniques with improved normal tissue sparing have rekindled interest in RT. We assessed the risk of LF and determined those factors that predict recurrence to facilitate patient selection for future adjuvant RT trials. Methods and Materials: From 1990-2008, 442 patients with urothelial bladder carcinoma at University of Pennsylvania were prospectively followed aftermore » RC plus PLND with or without chemotherapy with routine pelvic computed tomography (CT) or magnetic resonance imaging (MRI). One hundred thirty (29%) patients received chemotherapy. LF was any pelvic failure detected before or within 3 months of distant failure. Competing risk analyses identified factors predicting increased LF risk. Results: On univariate analysis, pathologic stage {>=}pT3, <10 nodes removed, positive margins, positive nodes, hydronephrosis, lymphovascular invasion, and mixed histology significantly predicted LF; node density was marginally predictive, but use of chemotherapy, number of positive nodes, type of surgical diversion, age, gender, race, smoking history, and body mass index were not. On multivariate analysis, only stage {>=}pT3 and <10 nodes removed were significant independent LF predictors with hazard ratios of 3.17 and 2.37, respectively (P<.01). Analysis identified 3 patient subgroups with significantly different LF risks: low-risk ({<=}pT2), intermediate-risk ({>=}pT3 and {>=}10 nodes removed), and high-risk ({>=}pT3 and <10 nodes) with 5-year LF rates of 8%, 23%, and 42%, respectively (P<.01). Conclusions: This series using routine CT and MRI surveillance to detect LF confirms that such failures are relatively common in cases of locally advanced disease and provides a rubric based on pathological stage and number of nodes removed that stratifies patients into 3 groups with significantly different LF risks to simplify patient selection for future adjuvant radiation therapy trials.« less

Diesel engine emissions and combustion predictions using advanced mixing models applicable to fuel sprays

NASA Astrophysics Data System (ADS)

Abani, Neerav; Reitz, Rolf D.

2010-09-01

An advanced mixing model was applied to study engine emissions and combustion with different injection strategies ranging from multiple injections, early injection and grouped-hole nozzle injection in light and heavy duty diesel engines. The model was implemented in the KIVA-CHEMKIN engine combustion code and simulations were conducted at different mesh resolutions. The model was compared with the standard KIVA spray model that uses the Lagrangian-Drop and Eulerian-Fluid (LDEF) approach, and a Gas Jet spray model that improves predictions of liquid sprays. A Vapor Particle Method (VPM) is introduced that accounts for sub-grid scale mixing of fuel vapor and more accurately and predicts the mixing of fuel-vapor over a range of mesh resolutions. The fuel vapor is transported as particles until a certain distance from nozzle is reached where the local jet half-width is adequately resolved by the local mesh scale. Within this distance the vapor particle is transported while releasing fuel vapor locally, as determined by a weighting factor. The VPM model more accurately predicts fuel-vapor penetrations for early cycle injections and flame lift-off lengths for late cycle injections. Engine combustion computations show that as compared to the standard KIVA and Gas Jet spray models, the VPM spray model improves predictions of in-cylinder pressure, heat released rate and engine emissions of NOx, CO and soot with coarse mesh resolutions. The VPM spray model is thus a good tool for efficiently investigating diesel engine combustion with practical mesh resolutions, thereby saving computer time.

One-hour glucose value as a long-term predictor of cardiovascular morbidity and mortality: the Malmö Preventive Project.

PubMed

Nielsen, Mette L; Pareek, Manan; Leósdóttir, Margrét; Eriksson, Karl-Fredrik; Nilsson, Peter M; Olsen, Michael H

2018-03-01

To examine the predictive capability of a 1-h vs 2-h postload glucose value for cardiovascular morbidity and mortality. Prospective, population-based cohort study (Malmö Preventive Project) with subject inclusion 1974-1992. 4934 men without known diabetes and cardiovascular disease, who had blood glucose (BG) measured at 0, 20, 40, 60, 90 and 120 min during an OGTT (30 g glucose per m 2 body surface area), were followed for 27 years. Data on cardiovascular events and death were obtained through national and local registries. Predictive capabilities of fasting BG (FBG) and glucose values obtained during OGTT alone and added to a clinical prediction model comprising traditional cardiovascular risk factors were assessed using Harrell's concordance index (C-index) and integrated discrimination improvement (IDI). Median age was 48 (25th-75th percentile: 48-49) years and mean FBG 4.6 ± 0.6 mmol/L. FBG and 2-h postload BG did not independently predict cardiovascular events or death. Conversely, 1-h postload BG predicted cardiovascular morbidity and mortality and remained an independent predictor of cardiovascular death (HR: 1.09, 95% CI: 1.01-1.17, P  = 0.02) and all-cause mortality (HR: 1.10, 95% CI: 1.05-1.16, P  < 0.0001) after adjusting for various traditional risk factors. Clinical risk factors with added 1-h postload BG performed better than clinical risk factors alone, in predicting cardiovascular death (likelihood-ratio test, P  = 0.02) and all-cause mortality (likelihood-ratio test, P  = 0.0001; significant IDI, P  = 0.0003). Among men without known diabetes, addition of 1-h BG, but not FBG or 2-h BG, to clinical risk factors provided incremental prognostic yield for prediction of cardiovascular death and all-cause mortality. © 2018 European Society of Endocrinology.

Family history does not predict angiographic localization or severity of coronary artery disease.

PubMed

Banerjee, Amitava; Lim, Chris C S; Silver, Louise E; Heneghan, Carl; Welch, Sarah J V; Mehta, Ziyah; Banning, Adrian P; Rothwell, Peter M

2012-04-01

Family history of MI is an established risk factor for coronary artery disease and subclinical atherosclerosis. Maternal MI and maternal stroke are more common in females than males presenting with acute coronary syndromes (ACS), suggesting sex-specific heritability, but the effects of family history on location and extent of coronary artery disease are unknown. In a prospective, population-based study (Oxford Vascular Study) of all patients with ACS, family history data for stroke and MI were analysed by sex of proband and affected first degree relatives (FDRs), and coronary angiograms were reviewed, where available. Of 835 probands with one or more ACS, 623 (420 males) had incident events and complete family history data. 351 patients with incident events (56.3%; 266 males) underwent coronary angiography. Neither angiographic disease localization nor severity were associated with sex-of-parent/sex-of-offspring in men or women. Sex-specific family history data do not predict angiographic localization of coronary disease in patients presenting with ACS. Maternal stroke and maternal MI probably affect ACS in females by a mechanism unrelated to atherosclerosis or coronary anatomy. However, family history data may still be useful in risk prediction and prognosis of ACS. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

The zebrafish dorsal axis is apparent at the four-cell stage.

PubMed

Gore, Aniket V; Maegawa, Shingo; Cheong, Albert; Gilligan, Patrick C; Weinberg, Eric S; Sampath, Karuna

2005-12-15

A central question in the development of multicellular organisms pertains to the timing and mechanisms of specification of the embryonic axes. In many organisms, specification of the dorsoventral axis requires signalling by proteins of the Transforming growth factor-beta and Wnt families. Here we show that maternal transcripts of the zebrafish Nodal-related morphogen, Squint (Sqt), can localize to two blastomeres at the four-cell stage and predict the dorsal axis. Removal of cells containing sqt transcripts from four-to-eight-cell embryos or injection of antisense morpholino oligonucleotides targeting sqt into oocytes can cause a loss of dorsal structures. Localization of sqt transcripts is independent of maternal Wnt pathway function and requires a highly conserved sequence in the 3' untranslated region. Thus, the dorsoventral axis is apparent by early cleavage stages and may require the maternally encoded morphogen Sqt and its associated factors. Because the 3' untranslated region of the human nodal gene can also localize exogenous sequences to dorsal cells, this mechanism may be evolutionarily conserved.

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.

[Constitutional factors of resistance to the effects of local vibration].

PubMed

Shalaurov, A V; Shchedrina, A G

1989-01-01

The study directed at the improvement of vibration disease prevention shows that not only functional, but also constitutional and somatotypologic body characteristics should be taken into account in predicting resistance to the impact of local occupational vibration. Such approach is specified by the fact that the relation of the main body components affects the amount of the zone of tissues and organs involved into vibration process. The study of 300 assemblerriveters and metal workers engaged in mechanical assembly shows that workers with elevated content of fat tissue and relatively small amount of osteal and muscular tissue, i.e., representatives of the abdominal somatype, are most resistant to local vibration. When the content of osteal and muscular components increases and that of the fat one decreases (thoracic somatotype), resistance to local vibration experiences a significant decline. The dimensions of skin and fat folds of upper extremities are greatly correlated to local vibration resistance.

Prediction of transmittance spectra for transparent composite electrodes with ultra-thin metal layers

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

Zhao, Zhao; Alford, T. L., E-mail: TA@asu.edu; Khorasani, Arash Elhami

2015-11-28

Recent interest in indium-free transparent composite-electrodes (TCEs) has motivated theoretical and experimental efforts to better understand and enhance their electrical and optical properties. Various tools have been developed to calculate the optical transmittance of multilayer thin-film structures based on the transfer-matrix method. However, the factors that affect the accuracy of these calculations have not been investigated very much. In this study, two sets of TCEs, TiO{sub 2}/Au/TiO{sub 2} and TiO{sub 2}/Ag/TiO{sub 2}, were fabricated to study the factors that affect the accuracy of transmittance predictions. We found that the predicted transmittance can deviate significantly from measured transmittance for TCEs thatmore » have ultra-thin plasmonic metal layers. The ultrathin metal layer in the TCE is typically discontinuous. When light interacts with the metallic islands in this discontinuous layer, localized surface plasmons are generated. This causes extra light absorption, which then leads to the actual transmittance being lower than the predicted transmittance.« less

Predictors of outcomes in patients with primary retroperitoneal dedifferentiated liposarcoma undergoing surgery.

PubMed

Keung, Emily Z; Hornick, Jason L; Bertagnolli, Monica M; Baldini, Elizabeth H; Raut, Chandrajit P

2014-02-01

Although sarcoma histology is recognized as a prognostic factor, most studies of retroperitoneal sarcomas report results combining multiple histologies and are inadequately powered to identify prognostic factors specific to a particular histology. We reviewed our experience with retroperitoneal dedifferentiated liposarcoma (RP DDLPS) to identify factors predictive of outcomes. All patients with RP DDLPS treated at our institution between 1998 and 2008 were reviewed. Multivariable Cox regression analyses were performed to identify factors predictive of progression-free survival (PFS), local recurrence-free survival (LRFS), distant recurrence-free survival (DRFS), and overall survival (OS). We identified 119 patients with primary DDLPS. Median tumor size was 20.5 cm; 21% were multifocal. French Federation of Cancer Centers Sarcoma Group tumor grades were intermediate in 53% of patients and high in 28% (unknown 19%). Resections were complete (R0/R1) in 80% of patients and incomplete (R2) in 11% (unknown 9%). Tumors were removed intact in 72% of patients and fragmented in 16% (unknown 12%). Median follow-up was 74.1 months. One hundred patients (84%) experienced recurrence or progression, with 92% occurring in the retroperitoneum. Median PFS, LRFS, DRFS, and OS were 21.1, 21.5, 45.8, and 59.0 months, respectively, and were significantly worse with R2 resection. On multivariate analysis, tumor integrity (intact vs fragmented) was predictive of PFS, multifocality predicted LRFS, and extent of resection (R0/R1 vs R2), grade, and tumor integrity predicted OS. In this cohort of primary RP DDLPS, factors under surgeon control (tumor integrity, extent of resection) and reflective of tumor biology (grade, multifocality) impact patient outcomes. Copyright © 2014 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

ACUTE PANCREATITIS GRAVITY PREDICTIVE FACTORS: WHICH AND WHEN TO USE THEM?

PubMed Central

FERREIRA, Alexandre de Figueiredo; BARTELEGA, Janaina Alves; URBANO, Hugo Corrêa de Andrade; de SOUZA, Iure Kalinine Ferraz

2015-01-01

Introduction: Acute pancreatitis has as its main causes lithiasic biliary disease and alcohol abuse. Most of the time, the disease shows a self-limiting course, with a rapid recovery, only with supportive treatment. However, in a significant percentage of cases, it runs with important local and systemic complications associated with high mortality rates. Aim: To present the current state of the use of these prognostic factors (predictive scores) of gravity, as the time of application, complexity and specificity. Method: A non-systematic literature review through 28 papers, with emphasis on 13 articles published in indexed journals between 2008 and 2013 using Lilacs, Medline, Pubmed. Results: Several clinical, laboratory analysis, molecular and image variables can predict the development of severe acute pancreatitis. Some of them by themselves can be determinant to the progression of the disease to a more severe form, such as obesity, hematocrit, age and smoking. Hematocrit with a value lower than 44% and serum urea lower than 20 mg/dl, both at admission, appear as risk factors for pancreatic necrosis. But the PCR differentiates mild cases of serious ones in the first 24 h. Multifactorial scores measured on admission and during the first 48 h of hospitalization have been used in intensive care units, being the most ones used: Ranson, Apache II, Glasgow, Iget and Saps II. Conclusion: Acute pancreatitis is a disease in which several prognostic factors are employed being useful in predicting mortality and on the development of the severe form. It is suggested that the association of a multifactorial score, especially the Saps II associated with Iget, may increase the prognosis accuracy. However, the professional's preferences, the experience on the service as well as the available tools, are factors that have determined the choice of the most suitable predictive score. PMID:26537149

A model to predict the risk of lethal nasopharyngeal necrosis after re-irradiation with intensity-modulated radiotherapy in nasopharyngeal carcinoma patients.

PubMed

Yu, Ya-Hui; Xia, Wei-Xiong; Shi, Jun-Li; Ma, Wen-Juan; Li, Yong; Ye, Yan-Fang; Liang, Hu; Ke, Liang-Ru; Lv, Xing; Yang, Jing; Xiang, Yan-Qun; Guo, Xiang

2016-06-29

For patients with nasopharyngeal carcinoma (NPC) who undergo re-irradiation with intensity-modulated radiotherapy (IMRT), lethal nasopharyngeal necrosis (LNN) is a severe late adverse event. The purpose of this study was to identify risk factors for LNN and develop a model to predict LNN after radical re-irradiation with IMRT in patients with recurrent NPC. Patients who underwent radical re-irradiation with IMRT for locally recurrent NPC between March 2001 and December 2011 and who had no evidence of distant metastasis were included in this study. Clinical characteristics, including recurrent carcinoma conditions and dosimetric features, were evaluated as candidate risk factors for LNN. Logistic regression analysis was used to identify independent risk factors and construct the predictive scoring model. Among 228 patients enrolled in this study, 204 were at risk of developing LNN based on risk analysis. Of the 204 patients treated, 31 (15.2%) developed LNN. Logistic regression analysis showed that female sex (P = 0.008), necrosis before re-irradiation (P = 0.008), accumulated total prescription dose to the gross tumor volume (GTV) ≥145.5 Gy (P = 0.043), and recurrent tumor volume ≥25.38 cm(3) (P = 0.009) were independent risk factors for LNN. A model to predict LNN was then constructed that included these four independent risk factors. A model that includes sex, necrosis before re-irradiation, accumulated total prescription dose to GTV, and recurrent tumor volume can effectively predict the risk of developing LNN in NPC patients who undergo radical re-irradiation with IMRT.

The global obesity pandemic: shaped by global drivers and local environments.

PubMed

Swinburn, Boyd A; Sacks, Gary; Hall, Kevin D; McPherson, Klim; Finegood, Diane T; Moodie, Marjory L; Gortmaker, Steven L

2011-08-27

The simultaneous increases in obesity in almost all countries seem to be driven mainly by changes in the global food system, which is producing more processed, affordable, and effectively marketed food than ever before. This passive overconsumption of energy leading to obesity is a predictable outcome of market economies predicated on consumption-based growth. The global food system drivers interact with local environmental factors to create a wide variation in obesity prevalence between populations. Within populations, the interactions between environmental and individual factors, including genetic makeup, explain variability in body size between individuals. However, even with this individual variation, the epidemic has predictable patterns in subpopulations. In low-income countries, obesity mostly affects middle-aged adults (especially women) from wealthy, urban environments; whereas in high-income countries it affects both sexes and all ages, but is disproportionately greater in disadvantaged groups. Unlike other major causes of preventable death and disability, such as tobacco use, injuries, and infectious diseases, there are no exemplar populations in which the obesity epidemic has been reversed by public health measures. This absence increases the urgency for evidence-creating policy action, with a priority on reduction of the supply-side drivers. Copyright © 2011 Elsevier Ltd. All rights reserved.

Computational prediction of strain-dependent diffusion of transcription factors through the cell nucleus.

PubMed

Nava, Michele M; Fedele, Roberto; Raimondi, Manuela T

2016-08-01

Nuclear spreading plays a crucial role in stem cell fate determination. In previous works, we reported evidence of multipotency maintenance for mesenchymal stromal cells cultured on three-dimensional engineered niche substrates, fabricated via two-photon laser polymerization. We correlated maintenance of multipotency to a more roundish morphology of these cells with respect to those cultured on conventional flat substrates. To interpret these findings, here we present a multiphysics model coupling nuclear strains induced by cell adhesion to passive diffusion across the cell nucleus. Fully three-dimensional reconstructions of cultured cells were developed on the basis of confocal images: in particular, the level of nuclear spreading resulted significantly dependent on the cell localization within the niche architecture. We assumed that the cell diffusivity varies as a function of the local volumetric strain. The model predictions indicate that the higher the level of spreading of the cell, the higher the flux across the nucleus of small solutes such as transcription factors. Our results point toward nuclear spreading as a primary mechanism by which the stem cell translates its shape into a fate decision, i.e., by amplifying the diffusive flow of transcriptional activators into the nucleus.

Scaling local species-habitat relations to the larger landscape with a hierarchical spatial count model

USGS Publications Warehouse

Thogmartin, W.E.; Knutson, M.G.

2007-01-01

Much of what is known about avian species-habitat relations has been derived from studies of birds at local scales. It is entirely unclear whether the relations observed at these scales translate to the larger landscape in a predictable linear fashion. We derived habitat models and mapped predicted abundances for three forest bird species of eastern North America using bird counts, environmental variables, and hierarchical models applied at three spatial scales. Our purpose was to understand habitat associations at multiple spatial scales and create predictive abundance maps for purposes of conservation planning at a landscape scale given the constraint that the variables used in this exercise were derived from local-level studies. Our models indicated a substantial influence of landscape context for all species, many of which were counter to reported associations at finer spatial extents. We found land cover composition provided the greatest contribution to the relative explained variance in counts for all three species; spatial structure was second in importance. No single spatial scale dominated any model, indicating that these species are responding to factors at multiple spatial scales. For purposes of conservation planning, areas of predicted high abundance should be investigated to evaluate the conservation potential of the landscape in their general vicinity. In addition, the models and spatial patterns of abundance among species suggest locations where conservation actions may benefit more than one species. ?? 2006 Springer Science+Business Media B.V.

Modified vs. standard D2 lymphadenectomy in distal subtotal gastrectomy for locally advanced gastric cancer patients under 70 years of age.

PubMed

Zhang, Chun-Dong; Zong, Liang; Ning, Fei-Long; Zeng, Xian-Tao; Dai, Dong-Qiu

2018-01-01

The present study was conducted to investigate the prognosis and survival of patients with locally advanced gastric cancer who underwent distal subtotal gastrectomy with modified D2 (D1+) and D2 lymphadenectomy, under 70 years of age. The five-year overall survival rates of 390 patients were compared between those receiving D1+ and D2 lymphadenectomy. Univariate and multivariate analyses were used to identify factors that correlated with prognosis and lymph node metastasis. Tumor size (P=0.039), pT stage (P=0.011), pN stage (P<0.001), and lymphadenectomy (P=0.004) were identified as independent prognostic factors. Furthermore, tumor size (P=0.022), pT stage (P=0.012), and lymphadenectomy (P=0.028) were proven as independent factors predicting lymph node metastasis. In conclusion, cancers of larger size, higher pT stage, and with D1+ lymphadenectomy had a higher risk of lymph node metastasis. Standard D2 lymphadenectomy removes sufficient lymph nodes to improve staging accuracy and survival. Therefore, D2 lymphanectomy is recommended in distal subtotal gastrectomy for locally advanced gastric cancer, especially for cancers of larger size and higher pT stage.

Multi-level multi-task learning for modeling cross-scale interactions in nested geospatial data

USGS Publications Warehouse

Yuan, Shuai; Zhou, Jiayu; Tan, Pang-Ning; Fergus, Emi; Wagner, Tyler; Sorrano, Patricia

2017-01-01

Predictive modeling of nested geospatial data is a challenging problem as the models must take into account potential interactions among variables defined at different spatial scales. These cross-scale interactions, as they are commonly known, are particularly important to understand relationships among ecological properties at macroscales. In this paper, we present a novel, multi-level multi-task learning framework for modeling nested geospatial data in the lake ecology domain. Specifically, we consider region-specific models to predict lake water quality from multi-scaled factors. Our framework enables distinct models to be developed for each region using both its local and regional information. The framework also allows information to be shared among the region-specific models through their common set of latent factors. Such information sharing helps to create more robust models especially for regions with limited or no training data. In addition, the framework can automatically determine cross-scale interactions between the regional variables and the local variables that are nested within them. Our experimental results show that the proposed framework outperforms all the baseline methods in at least 64% of the regions for 3 out of 4 lake water quality datasets evaluated in this study. Furthermore, the latent factors can be clustered to obtain a new set of regions that is more aligned with the response variables than the original regions that were defined a priori from the ecology domain.

The local lymph node assay compared with the human maximization test as an indicator of allergic potency in humans using patch test clinic populations.

PubMed

Zaghi, Danny; Maibach, Howard I

2009-01-01

The human maximization test (HMT) is a method to evaluate potency in humans, while the local lymph node assay (LLNA) is a test method that allows for the measuring of the allergic potency of a substance in a rodent. It has been proposed that an EC3 value (the value obtained by the LLNA test, ie, the concentration of an allergen leading to a 3-fold increase of baseline proliferation rate) would be a reliable indicator for a compound's allergic potency in humans. This paper compares the correlation between the EC3 value of a compound and its allergic occurrence in the general population with the correlation between the HMT of the compound and its allergic occurrence in the general population, to determine the relationship to potency. The correlation values when outliers were removed from the sample were -0.56 and -0.71 for LLNA and HMT, respectively, suggesting that there is a possible 20% error margin in LLNA's ability to predict potency. The data also suggest that other factors (such as exposure) could play up to a 30% role in the determination of allergic occurrence in the general population. The potency assays might be made more clinically relevant for predicting allergic frequencies by including a frequency factor and other factors in its dermatotoxicological interpretation.

Polish Version of the Neighbourhood Environment Walkability Scale (NEWS-Poland).

PubMed

Jaśkiewicz, Michał; Besta, Tomasz

2016-11-04

The characteristics of built environments are the subject of intense consideration in the search for solutions to promote wellbeing and a higher quality of life among the inhabitants of cities. Walkability, defined as the extent to which the built environment is friendly to living and fulfilling the needs of the area, has become an important concept in sustainable urban design, public health and environmental psychology. This study systematically adapted the Neighbourhood Environment Walkability Scale (NEWS) for Poland, and evaluated the construct validity aspects of the adapted version among Polish adults. A total sample of 783 participants from a TriCity (Trójmiasto) agglomeration completed the adapted version of the NEWS. Smaller extracted samples of the participants also completed wellbeing related scales, including self-efficacy, local identity and distance to city centre measures. It was expected that various districts of Gdańsk would differ in terms of walkability. The confirmatory factor analysis showed satisfactory goodness-of-fit statistics and factor loadings corresponding to the proposed original factor structure. According to the predictions, the NEWS subscales correlated with the self-efficacy, local identity and wellbeing related measures. In addition, the comparisons between the neighbourhoods of Gdańsk also showed a predictable pattern of results. Overall, the NEWS demonstrated satisfactory measurement properties, and may be useful in the evaluation of the built environment in Poland.

Reliability of vascular geometry factors derived from clinical MRA

NASA Astrophysics Data System (ADS)

Bijari, Payam B.; Antiga, Luca; Steinman, David A.

2009-02-01

Recent work from our group has demonstrated that the amount of disturbed flow at the carotid bifurcation, believed to be a local risk factor for carotid atherosclerosis, can be predicted from luminal geometric factors. The next step along the way to a large-scale retrospective or prospective imaging study of such local risk factors for atherosclerosis is to investigate whether these geometric features are reproducible and accurate from routine 3D contrast-enhanced magnetic resonance angiography (CEMRA) using a fast and practical method of extraction. Motivated by this fact, we examined the reproducibility of multiple geometric features that are believed important in atherosclerosis risk assessment. We reconstructed three-dimensional carotid bifurcations from 15 clinical study participants who had previously undergone baseline and repeat CEMRA acquisitions. Certain geometric factors were extracted and compared between the baseline and the repeat scan. As the spatial resolution of the CEMRA data was noticeably coarse and anisotropic, we also investigated whether this might affect the measurement of the same geometric risk factors by simulating the CEMRA acquisition for 15 normal carotid bifurcations previously acquired at high resolution. Our results show that the extracted geometric factors are reproducible and faithful, with intra-subject uncertainties well below inter-subject variabilities. More importantly, these geometric risk factors can be extracted consistently and quickly for potential use as disturbed flow predictors.

Tumour size is the only predictive factor of distant recurrence after pathological complete response to neoadjuvant chemotherapy in patients with large operable or locally advanced breast cancers: a sub-study of EORTC 10994/BIG 1-00 phase III trial.

PubMed

Fei, F; Messina, C; Slaets, L; Chakiba, C; Cameron, D; Bogaerts, J; Bonnefoi, H

2015-02-01

Although achieving a pathological complete response (pCR) after neoadjuvant chemotherapy (NACT) in breast cancer predicts a better outcome, some patients still relapse. The objectives of this study were to describe the types of events in this group of patients and to identify predictive factors for relapse. Patients with large operable or locally advanced breast cancers (T4d tumours were excluded) were randomised to receive either six cycles of anthracycline-based chemotherapy or three cycles of docetaxel followed by three cycles of eprirubicin/docetaxel. pCR was defined as no evidence of residual invasive cancer (or very few scattered tumour cells) in the primary tumour and axillary lymph nodes at surgery. Two Cox regression analyses were performed to identify predictive factors of relapse: one for recurrence-free interval (RFI) and one for distant recurrence-free interval (DRFI). Out of 283 eligible patients who achieved a pCR, 40 (14.1%) and 28 (9.9%) presented an event of interest for the RFI and DRFI analyses, respectively. Five-year RFI, DRFI and overall survival (OS) were 85.3% (95% confidence interval (CI), 80.1-89.3), 89.6% (95% CI, 85.0-92.9) and 91.9% (95% CI, 87.2-94.9), respectively. No predictors for RFI after pCR were identified. For DRFI, tumour size was the only predictor: Hazard ratio (HR) T3 versus T1-2=3.62 (95% CI, 1.66-7.89); HR T4 versus T1-2: HR, 2.80 (95% CI, 0.62-12.64) p=0.0048. In this study, clinical tumour size emerged as the only predictor for DRFI after pCR, with T3 and T4 tumours having an increased risk for distant recurrence compared to T1-2 tumours. Copyright © 2014 Elsevier Ltd. All rights reserved.

Prediction of chemotherapeutic response of colorectal liver metastases with dynamic gadolinium-DTPA-enhanced MRI and localized 19F MRS pharmacokinetic studies of 5-fluorouracil.

PubMed

van Laarhoven, H W M; Klomp, D W J; Rijpkema, M; Kamm, Y L M; Wagener, D J Th; Barentsz, J O; Punt, C J A; Heerschap, A

2007-04-01

Systemic chemotherapy is effective in only a subset of patients with metastasized colorectal cancer. Therefore, early selection of patients who are most likely to benefit from chemotherapy is desirable. Response to treatment may be determined by the delivery of the drug to the tumor, retention of the drug in the tumor and by the amount of intracellular uptake, metabolic activation and catabolism, as well as other factors. The first aim of this study was to investigate the predictive value of DCE-MRI with the contrast agent Gd-DTPA for tumor response to first-line chemotherapy in patients with liver metastases of colorectal cancer. The second aim was to investigate the predictive value of 5-fluorouracil (FU) uptake, retention and catabolism as measured by localized (19)F MRS for tumor response to FU therapy. Since FU uptake, retention and metabolism may depend on tumor vascularization, the relationship between (19)F MRS and the DCE-MRI parameters k(ep), K(trans) and v(e) was also examined (1). In this study, 37 patients were included. The kinetic parameters of DCE-MRI, k(ep), K(trans) and v(e), before start of treatment did not predict tumor response after 2 months, suggesting that the delivery of chemotherapy by tumor vasculature is not a major factor determining response in first-line treatment. No evident correlations between (19)F MRS parameters and tumor response were found. This suggests that in liver metastases that are not selected on the basis of their tumor diameter, FU uptake and catabolism are not limiting factors for response. The transfer constant K(trans), as measured by DCE-MRI before start of treatment, was negatively correlated with FU half-life in the liver metastases, which suggests that, in metastases with a larger tumor blood flow or permeability surface area product, FU is rapidly washed out from the tumor. c 2006 John Wiley & Sons, Ltd.

Effect of water flow and chemical environment on microbiota growth and composition in the human colon.

PubMed

Cremer, Jonas; Arnoldini, Markus; Hwa, Terence

2017-06-20

The human gut harbors a dynamic microbial community whose composition bears great importance for the health of the host. Here, we investigate how colonic physiology impacts bacterial growth, which ultimately dictates microbiota composition. Combining measurements of bacterial physiology with analysis of published data on human physiology into a quantitative, comprehensive modeling framework, we show how water flow in the colon, in concert with other physiological factors, determine the abundances of the major bacterial phyla. Mechanistically, our model shows that local pH values in the lumen, which differentially affect the growth of different bacteria, drive changes in microbiota composition. It identifies key factors influencing the delicate regulation of colonic pH, including epithelial water absorption, nutrient inflow, and luminal buffering capacity, and generates testable predictions on their effects. Our findings show that a predictive and mechanistic understanding of microbial ecology in the gut is possible. Such predictive understanding is needed for the rational design of intervention strategies to actively control the microbiota.

Effect of water flow and chemical environment on microbiota growth and composition in the human colon

PubMed Central

Cremer, Jonas; Arnoldini, Markus; Hwa, Terence

2017-01-01

The human gut harbors a dynamic microbial community whose composition bears great importance for the health of the host. Here, we investigate how colonic physiology impacts bacterial growth, which ultimately dictates microbiota composition. Combining measurements of bacterial physiology with analysis of published data on human physiology into a quantitative, comprehensive modeling framework, we show how water flow in the colon, in concert with other physiological factors, determine the abundances of the major bacterial phyla. Mechanistically, our model shows that local pH values in the lumen, which differentially affect the growth of different bacteria, drive changes in microbiota composition. It identifies key factors influencing the delicate regulation of colonic pH, including epithelial water absorption, nutrient inflow, and luminal buffering capacity, and generates testable predictions on their effects. Our findings show that a predictive and mechanistic understanding of microbial ecology in the gut is possible. Such predictive understanding is needed for the rational design of intervention strategies to actively control the microbiota. PMID:28588144

Vertical ridge augmentation using an equine bone and collagen block infused with recombinant human platelet-derived growth factor-BB: a randomized single-masked histologic study in non-human primates.

PubMed

Nevins, Myron; Al Hezaimi, Khalid; Schupbach, Peter; Karimbux, Nadeem; Kim, David M

2012-07-01

This study tests the effectiveness of hydroxyapatite and collagen bone blocks of equine origin (eHAC), infused with recombinant human platelet-derived growth factor-BB (rhPDGF-BB), to augment localized posterior mandibular defects in non-human primates (Papio hamadryas). Bilateral critical-sized defects simulating severe atrophy were created at the time of the posterior teeth extraction. Test and control blocks (without growth factor) were randomly grafted into the respective sites in each non-human primate. All sites exhibited vertical ridge augmentation, with physiologic hard- and soft-tissue integration of the blocks when clinical and histologic examinations were done at 4 months after the vertical ridge augmentation procedure. There was a clear, although non-significant, tendency to increased regeneration in the test sites. As in the first two preclinical studies in this series using canines, experimental eHAC blocks infused with rhPDGF-BB proved to be a predictable and technically viable method to predictably regenerate bone and soft tissue in critical-sized defects. This investigation supplies additional evidence that eHAC blocks infused with rhPDGF-BB growth factor is a predictable and technically feasible option for vertical augmentation of severely resorbed ridges.

Effects of human dynamics on epidemic spreading in Côte d'Ivoire

NASA Astrophysics Data System (ADS)

Li, Ruiqi; Wang, Wenxu; Di, Zengru

2017-02-01

Understanding and predicting outbreaks of contagious diseases are crucial to the development of society and public health, especially for underdeveloped countries. However, challenging problems are encountered because of complex epidemic spreading dynamics influenced by spatial structure and human dynamics (including both human mobility and human interaction intensity). We propose a systematical model to depict nationwide epidemic spreading in Côte d'Ivoire, which integrates multiple factors, such as human mobility, human interaction intensity, and demographic features. We provide insights to aid in modeling and predicting the epidemic spreading process by data-driven simulation and theoretical analysis, which is otherwise beyond the scope of local evaluation and geometrical views. We show that the requirement that the average local basic reproductive number to be greater than unity is not necessary for outbreaks of epidemics. The observed spreading phenomenon can be roughly explained as a heterogeneous diffusion-reaction process by redefining mobility distance according to the human mobility volume between nodes, which is beyond the geometrical viewpoint. However, the heterogeneity of human dynamics still poses challenges to precise prediction.

Potential Theory for Directed Networks

PubMed Central

Zhang, Qian-Ming; Lü, Linyuan; Wang, Wen-Qiang; Zhou, Tao

2013-01-01

Uncovering factors underlying the network formation is a long-standing challenge for data mining and network analysis. In particular, the microscopic organizing principles of directed networks are less understood than those of undirected networks. This article proposes a hypothesis named potential theory, which assumes that every directed link corresponds to a decrease of a unit potential and subgraphs with definable potential values for all nodes are preferred. Combining the potential theory with the clustering and homophily mechanisms, it is deduced that the Bi-fan structure consisting of 4 nodes and 4 directed links is the most favored local structure in directed networks. Our hypothesis receives strongly positive supports from extensive experiments on 15 directed networks drawn from disparate fields, as indicated by the most accurate and robust performance of Bi-fan predictor within the link prediction framework. In summary, our main contribution is twofold: (i) We propose a new mechanism for the local organization of directed networks; (ii) We design the corresponding link prediction algorithm, which can not only testify our hypothesis, but also find out direct applications in missing link prediction and friendship recommendation. PMID:23408979

Life prediction and constitutive behavior

NASA Technical Reports Server (NTRS)

Halford, G. R.

1983-01-01

One of the primary drivers that prompted the initiation of the hot section technology (HOST) program was the recognized need for improved cyclic durability of costly hot section components. All too frequently, fatigue in one form or another was directly responsible for the less than desired durability, and prospects for the future weren't going to improve unless a significant effort was mounted to increase our knowledge and understanding of the elements governing cyclic crack initiation and propagation lifetime. Certainly one of the important factors is the ability to perform accurate structural stress-strain analyses on a routine basis to determine the magnitudes of the localized stresses and strains since it is these localized conditions that govern the initiation and crack growth processes. Developing the ability to more accurately predict crack initiation lifetimes and cyclic crack growth rates for the complex loading conditions found in turbine engine hot sections is of course the ultimate goal of the life prediction research efforts. It has been found convenient to divide the research efforts into those dealing with nominally isotropic and anisotropic alloys; the latter for application to directionally solidified and single crystal turbine blades.

Baseline nutritional status is predictive of response to treatment and survival in patients treated by definitive chemoradiotherapy for a locally advanced esophageal cancer.

PubMed

Di Fiore, Frédéric; Lecleire, Stéphane; Pop, Daniela; Rigal, Olivier; Hamidou, Hadji; Paillot, Bernard; Ducrotté, Philippe; Lerebours, Eric; Michel, Pierre

2007-11-01

To assess the impact of baseline nutritional status on treatment response and survival in nonmetastatic patients with a locally advanced esophageal cancer (LAEC) treated with definitive chemoradiotherapy (CRT). One hundred five patients with LAEC treated by definitive CRT were retrospectively included. The CRT regimen was based on an external radiotherapy (RT) delivered concomitantly to a cisplatin-based chemotherapy (CT). Patients were considered to have a complete response (CR) to CRT when no residual tumor was detected on CT scan and esophagoscopy performed 2 months after the end of CRT. Multivariate analysis of predictive factors of response to CRT and survival were performed using a logistic regression and a Cox model, respectively. Mean value of baseline nutritional parameters was significantly different between nonresponder (N = 42) and responder (N = 63) patients to CRT (weight loss 10%vs 5.8%, P= 0.0047; serum albumin level 35 g/L vs 38.7 g/L, P= 0.0004; BMI 22.8 kg/m2vs 25.2 kg/m2, P= 0.01). In multivariate analysis, serum albumin level > 35 g/L was the only independent predictive factor of CR to CRT (P= 0.009). Independent prognostic factors of survival were BMI > 18 kg/m2 (P= 0.003), dysphagia Atkinson score <2 (P= 0.008), dose of RT > 50 Grays (Gy) (P < 0.0001) and CR to CRT (P < 0.0001). Survival was influenced by baseline nutritional status as well as dysphagia, dose of RT, and CR to CRT. Despite the retrospective design of the study, our results may provide the concept basis for performing a prospective nutritional intervention study in patients treated by definitive CRT for an esophageal cancer.

The 'bioscience problem' for nursing students: an integrative review of published evaluations of Year 1 bioscience, and proposed directions for curriculum development.

PubMed

McVicar, Andrew; Andrew, Sharon; Kemble, Ross

2015-03-01

The difficulties that nursing students have in learning human biosciences have given cause for concern for over 20 years but the problem remains. To conduct an integrative review of published primary research into the 'bioscience problem', evaluate their outcomes, and provide a contemporary analysis of potential directions for curriculum planners. A systematic search of electronic databases CINAHL, Medline, British Nursing Index and Google Scholar was conducted for empirical research studies, published between 1990 and 2013, designed to either predict performance of students in bioscience assessments in Year 1 of their studies or identify in-course curriculum delivery issues. The search generated nineteen papers that met inclusion criteria. Twelve papers involved predictive factors for bioscience attainment and seven surveyed student views on curriculum issues. Four others that surveyed reflections of later-year students or qualified nurses on Year 1 outcomes were also retained for additional context. Prediction based on pre-admission academic achievement was not reliable. Student factors including age at entry, self-efficacy in science, and having appropriate study skills in particular appear to be confounding factors. In-course influences such as teaching strategy or lecturer skills are also inconsistent and likely to represent confounders operating at local, institutional level. The integrative review approach enabled analysis of incongruencies between studies that have been a barrier to curriculum development. Sound admissions criteria based on pre-university academic performance show promise in resolving the 'bioscience problem' but will likely be contingent on innovative support early in Year 1 for study skills and the fundamentals of human bioscience, plus attention to local quality assurance for curriculum delivery. Copyright © 2014 Elsevier Ltd. All rights reserved.

Predictive factors of esophageal stenosis associated with tumor regression in radiation therapy for locally advanced esophageal cancer.

PubMed

Atsumi, Kazushige; Shioyama, Yoshiyuki; Nakamura, Katsumasa; Nomoto, Satoshi; Ohga, Saiji; Yoshitake, Tadamasa; Nonoshita, Takeshi; Ueda, Masanobu; Hirata, Hideki; Honda, Hiroshi

2010-01-01

The purpose of this retrospective study was to clarify the predictive factors correlated with esophageal stenosis within three months after radiation therapy for locally advanced esophageal cancer. We enrolled 47 patients with advanced esophageal cancer with T2-4 and stage II-III who were treated with definitive radiation therapy and achieving complete response of primary lesion at Kyushu University Hospital between January 1998 and December 2005. Esophagography was performed for all patients before treatment and within three months after completion of the radiation therapy, the esophageal stenotic ratio was evaluated. The stenotic ratio was used to define four levels of stenosis: stenosis level 1, stenotic ratio of 0-25%; 2, 25-50%; 3,50-75%; 4,75-100%. We then estimated the correlation between the esophageal stenosis level after radiation therapy and each of numerous factors. The numbers and total percentages of patients at each stenosis level were as follows: level 1: n = 14 (30%); level 2: 8 (17%); level 3: 14 (30%); and level 4: 11 (23%). Esophageal stenosis in the case of full circumference involvement tended to be more severe and more frequent. Increases in wall thickness tended to be associated with increases in esophageal stenosis severity and frequency. The extent of involved circumference and wall thickness of tumor region were significantly correlated with esophageal stenosis associated with tumor regression in radiation therapy (p = 0.0006, p = 0.005). For predicting the possibility of esophageal stenosis with tumor regression within three months in radiation therapy, the extent of involved circumference and esophageal wall thickness of the tumor region may be useful.

Nonlinear analysis of aortic flow in living dogs.

NASA Technical Reports Server (NTRS)

Ling, S. C.; Atabek, H. B.; Letzing, W. G.; Patel, D. J.

1973-01-01

A nonlinear theory which considered the convective accelerations of blood and the nonlinear elastic behavior and taper angle of the vascular wall was used to study the nature of blood flow in the descending thoracic aorta of living dogs under a wide range of pressures and flows. Velocity profiles, wall friction, and discharge waves were predicted from locally measured input data about the pressure-gradient wave and arterial distention. The results indicated that a major part of the mean pressure gradient was balanced by convective accelerations; the theory, which took this factor into account, predicted the correct velocity distributions and flow waves.

Local politics and retail cannabis markets: the case of the Dutch coffeeshops.

PubMed

Wouters, Marije; Benschop, Annemieke; Korf, Dirk J

2010-07-01

Cannabis coffeeshops are concentrated in specific areas in the Netherlands; close to 80% of Dutch municipalities have no coffeeshops. We investigated why such wide local differences exist. Regression analyses were carried out on data regarding the number of coffeeshops per municipality, local council seat distribution and area demographic characteristics. A contrast analysis of municipalities with no/few vs. many coffeeshops was also performed. Whether a town has one or more coffeeshops can be predicted in part by its population size, but more strongly by political composition of the local council. The larger the percentage of progressive councillors, the greater the probability that coffeeshops are allowed. The number of coffeeshops in a town depends primarily on the demand for cannabis (reflected in factors like local population size); it generally has little to do with national-level party political preferences about drug policy. Both the demand for coffeeshops and local political preference influence coffeeshop policy in the Netherlands. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Irregular vascular pattern by contrast-enhanced ultrasonography and high serum Lens culinaris agglutinin-reactive fraction of alpha-fetoprotein level predict poor outcome after successful radiofrequency ablation in patients with early-stage hepatocellular carcinoma.

PubMed

Takada, Hitomi; Tsuchiya, Kaoru; Yasui, Yutaka; Nakakuki, Natsuko; Tamaki, Nobuharu; Suzuki, Shoko; Nakanishi, Hiroyuki; Itakura, Jun; Takahashi, Yuka; Kurosaki, Masayuki; Asahina, Yasuhiro; Enomoto, Nobuyuki; Izumi, Namiki

2016-11-01

Radiofrequency ablation (RFA) is considered the most effective treatment for early-stage hepatocellular carcinoma (HCC) patients unsuitable for resection. However, poor outcome after RFA has occasionally been reported worldwide. To predict such an outcome, we investigated imaging findings using contrast-enhanced ultrasonography (CEUS) with Sonazoid and serum tumor markers before RFA. This study included 176 early-stage HCC patients who had initially achieved successful RFA. Patients were examined using CEUS; their levels of alpha-fetoprotein (AFP), Lens culinaris agglutinin-reactive fraction of AFP (AFP-L3), and des-gamma-carboxy prothrombin before RFA were measured. Sonazoid provided parenchyma-specific contrast imaging and facilitated tumor vascular architecture imaging through maximum intensity projection (MIP). Kaplan-Meier analysis examined cumulative rates of local tumor progression, intrasubsegmental recurrence, and survival; factors associated with these were determined with Cox proportional hazards analysis. Local tumor progression (n = 15), intrasubsegmental recurrence (n = 46), and death (n = 18) were observed. Irregular pattern in MIP classification and serum AFP-L3 level (>10%) before RFA were identified as independent risk factors for local tumor progression and intrasubsegmental recurrence. These two factors were independently associated with poor survival after RFA (irregular pattern in MIP: hazard ratio, (HR) = 8.26; 95% confidence interval, (CI) = 2.24-30.3; P = 0.002 and AFP-L3 > 10%: HR = 2.94; 95% CI = 1.09-7.94; P = 0.033). Irregular MIP pattern by CEUS and high level of serum AFP-L3 were independent risk factors for poor outcome after successful RFA. The Patients with these findings should be considered as special high-risk group in early-stage HCC. © 2016 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Hotspots of Community Change: Temporal Dynamics Are Spatially Variable in Understory Plant Composition of a California Oak Woodland

PubMed Central

Spotswood, Erica N.; Bartolome, James W.; Allen-Diaz, Barbara

2015-01-01

Community response to external drivers such climate and disturbance can lead to fluctuations in community composition, or to directional change. Temporal dynamics can be influenced by a combination of drivers operating at multiple spatial scales, including external landscape scale drivers, local abiotic conditions, and local species pools. We hypothesized that spatial variation in these factors can create heterogeneity in temporal dynamics within landscapes. We used understory plant species composition from an 11 year dataset from a California oak woodland to compare plots where disturbance was experimentally manipulated with the removal of livestock grazing and a prescribed burn. We quantified three properties of temporal variation: compositional change (reflecting the appearance and disappearance of species), temporal fluctuation, and directional change. Directional change was related most strongly to disturbance type, and was highest at plots where grazing was removed during the study. Temporal fluctuations, compositional change, and directional change were all related to intrinsic abiotic factors, suggesting that some locations are more responsive to external drivers than others. Temporal fluctuations and compositional change were linked to local functional composition, indicating that environmental filters can create subsets of the local species pool that do not respond in the same way to external drivers. Temporal dynamics are often assumed to be relatively static at the landscape scale, provided disturbance and climate are continuous. This study shows that local and landscape scale factors jointly influence temporal dynamics creating hotspots that are particularly responsive to climate and disturbance. Thus, adequate predictions of response to disturbance or to changing climate will only be achieved by considering how factors at multiple spatial scales influence community resilience and recovery. PMID:26222069

Hotspots of Community Change: Temporal Dynamics Are Spatially Variable in Understory Plant Composition of a California Oak Woodland.

PubMed

Spotswood, Erica N; Bartolome, James W; Allen-Diaz, Barbara

2015-01-01

Community response to external drivers such climate and disturbance can lead to fluctuations in community composition, or to directional change. Temporal dynamics can be influenced by a combination of drivers operating at multiple spatial scales, including external landscape scale drivers, local abiotic conditions, and local species pools. We hypothesized that spatial variation in these factors can create heterogeneity in temporal dynamics within landscapes. We used understory plant species composition from an 11 year dataset from a California oak woodland to compare plots where disturbance was experimentally manipulated with the removal of livestock grazing and a prescribed burn. We quantified three properties of temporal variation: compositional change (reflecting the appearance and disappearance of species), temporal fluctuation, and directional change. Directional change was related most strongly to disturbance type, and was highest at plots where grazing was removed during the study. Temporal fluctuations, compositional change, and directional change were all related to intrinsic abiotic factors, suggesting that some locations are more responsive to external drivers than others. Temporal fluctuations and compositional change were linked to local functional composition, indicating that environmental filters can create subsets of the local species pool that do not respond in the same way to external drivers. Temporal dynamics are often assumed to be relatively static at the landscape scale, provided disturbance and climate are continuous. This study shows that local and landscape scale factors jointly influence temporal dynamics creating hotspots that are particularly responsive to climate and disturbance. Thus, adequate predictions of response to disturbance or to changing climate will only be achieved by considering how factors at multiple spatial scales influence community resilience and recovery.

Regional lymph node metastases are a strong risk factor for venous thromboembolism: results from the Vienna Cancer and Thrombosis Study

PubMed Central

Dickmann, Boris; Ahlbrecht, Jonas; Ay, Cihan; Dunkler, Daniela; Thaler, Johannes; Scheithauer, Werner; Quehenberger, Peter; Zielinski, Christoph; Pabinger, Ingrid

2013-01-01

Advanced cancer is a risk factor for venous thromboembolism. However, lymph node metastases are usually not considered an established risk factor. In the framework of the prospective, observational Vienna Cancer and Thrombosis Study we investigated the association between local (N0), regional (N1–3), and distant (M1) cancer stages and the occurrence of venous thromboembolism. Furthermore, we were specifically interested in the relationship between stage and biomarkers that have been reported to be associated with venous thromboembolism. We followed 832 patients with solid tumors for a median of 527 days. The study end-point was symptomatic venous thromboembolism. At study inclusion, 241 patients had local, 138 regional, and 453 distant stage cancer. The cumulative probability of venous thromboembolism after 6 months in patients with local, regional and distant stage cancer was 2.1%, 6.5% and 6.0%, respectively (P=0.002). Compared to patients with local stage disease, patients with regional and distant stage disease had a significantly higher risk of venous thromboembolism in multivariable Cox-regression analysis including age, newly diagnosed cancer (versus progression of disease), surgery, radiotherapy, and chemotherapy (regional: HR=3.7, 95% CI: 1.5–9.6; distant: HR=5.4, 95% CI: 2.3–12.9). Furthermore, patients with regional or distant stage disease had significantly higher levels of D-dimer, factor VIII, and platelets, and lower hemoglobin levels than those with local stage disease. These results demonstrate an increased risk of venous thromboembolism in patients with regional disease. Elevated levels of predictive biomarkers in patients with regional disease underpin the results and are in line with the activation of the hemostatic system in the early phase of metastatic dissemination. PMID:23585523

Validation of a multifactorial risk factor model used for predicting future caries risk with Nevada adolescents.

PubMed

Ditmyer, Marcia M; Dounis, Georgia; Howard, Katherine M; Mobley, Connie; Cappelli, David

2011-05-20

The objective of this study was to measure the validity and reliability of a multifactorial Risk Factor Model developed for use in predicting future caries risk in Nevada adolescents in a public health setting. This study examined retrospective data from an oral health surveillance initiative that screened over 51,000 students 13-18 years of age, attending public/private schools in Nevada across six academic years (2002/2003-2007/2008). The Risk Factor Model included ten demographic variables: exposure to fluoridation in the municipal water supply, environmental smoke exposure, race, age, locale (metropolitan vs. rural), tobacco use, Body Mass Index, insurance status, sex, and sealant application. Multiple regression was used in a previous study to establish which significantly contributed to caries risk. Follow-up logistic regression ascertained the weight of contribution and odds ratios of the ten variables. Researchers in this study computed sensitivity, specificity, positive predictive value (PVP), negative predictive value (PVN), and prevalence across all six years of screening to assess the validity of the Risk Factor Model. Subjects' overall mean caries prevalence across all six years was 66%. Average sensitivity across all six years was 79%; average specificity was 81%; average PVP was 89% and average PVN was 67%. Overall, the Risk Factor Model provided a relatively constant, valid measure of caries that could be used in conjunction with a comprehensive risk assessment in population-based screenings by school nurses/nurse practitioners, health educators, and physicians to guide them in assessing potential future caries risk for use in prevention and referral practices.

Study on predictive role of AR and EGFR family genes with response to neoadjuvant chemotherapy in locally advanced breast cancer in Indian women.

PubMed

Singh, L C; Chakraborty, Anurupa; Mishra, Ashwani K; Devi, Thoudam Regina; Sugandhi, Nidhi; Chintamani, Chintamani; Bhatnagar, Dinesh; Kapur, Sujala; Saxena, Sunita

2012-06-01

Locally advanced breast cancer (LABC) remains a clinical challenge as the majority of patients with this diagnosis develop distant metastases despite appropriate therapy. We analyzed expression of steroid and growth hormone receptor genes as well as gene associated with metabolism of chemotherapeutic drugs in locally advanced breast cancer before and after neoadjuvant chemotherapy (NACT) to study whether there is a change in gene expression induced by chemotherapy and whether such changes are associated with tumor response or non-response. Fifty patients were included with locally advanced breast cancer treated with cyclophosphamide, adriamycin, 5-fluorouracil (CAF)-based neoadjuvant chemotherapy before surgery. Total RNA was extracted from 50 match samples of pre- and post-NACT tumor tissues. RNA expression levels of epidermal growth factor receptor family genes including EGFR, ERBB2, ERBB3, androgen receptor (AR), and multidrug-resistance gene 1 (MDR1) were determined by quantitative real-time reverse transcriptase-polymerase chain reaction. Responders show significantly high levels of pre-NACT AR gene expression (P = 0.016), which reduces following NACT (P = 0.008), and hence can serve as a useful tool for the prediction of the success of neoadjuvant chemotherapy in individual cancer patients with locally advanced breast carcinoma. Moreover, a significant post-therapeutic increase in the expression levels of EGFR and MDR1 gene in responders (P = 0.026 and P < 0.001) as well as in non-responders (P = 0.055, P = 0.001) suggests that expression of these genes changes during therapy but they do not have any impact on tumor response, whereas a post-therapeutic reduction was observed in AR in responders. This indicates an independent predictive role of AR with response to NACT.

ILS Localizer Performance Prediction of an Alford 1B Array Near a Limited Access Road at the New Orleans Airport.

DOT National Transportation Integrated Search

1974-08-01

The Transportation Systems Center (TSC) ILS Localizer Performance Prediction Model was used to predict the derogation to an Alford 1B Localizer caused by vehicular traffic traveling on a roadway to be located in front of the localizer. Several differ...

Comparison of different models for ground-level atmospheric turbulence strength (C(n)(2)) prediction with a new model according to local weather data for FSO applications.

PubMed

Arockia Bazil Raj, A; Arputha Vijaya Selvi, J; Durairaj, S

2015-02-01

Atmospheric parameters strongly affect the performance of free-space optical communication (FSOC) systems when the optical wave is propagating through the inhomogeneous turbulence transmission medium. Developing a model to get an accurate prediction of the atmospheric turbulence strength (C(n)(2)) according to meteorological parameters (weather data) becomes significant to understand the behavior of the FSOC channel during different seasons. The construction of a dedicated free-space optical link for the range of 0.5 km at an altitude of 15.25 m built at Thanjavur (Tamil Nadu) is described in this paper. The power level and beam centroid information of the received signal are measured continuously with weather data at the same time using an optoelectronic assembly and the developed weather station, respectively, and are recorded in a data-logging computer. Existing models that exhibit relatively fewer prediction errors are briefed and are selected for comparative analysis. Measured weather data (as input factors) and C(n)(2) (as a response factor) of size [177,147×4] are used for linear regression analysis and to design mathematical models more suitable in the test field. Along with the model formulation methodologies, we have presented the contributions of the input factors' individual and combined effects on the response surface and the coefficient of determination (R(2)) estimated using analysis of variance tools. An R(2) value of 98.93% is obtained using the new model, model equation V, from a confirmatory test conducted with a testing data set of size [2000×4]. In addition, the prediction accuracies of the selected and the new models are investigated during different seasons in a one-year period using the statistics of day, week-averaged, month-averaged, and seasonal-averaged diurnal Cn2 profiles, and are verified in terms of the sum of absolute error (SAE). A Cn2 prediction maximum average SAE of 2.3×10(-13)  m(-2/3) is achieved using the new model in a longer range of dynamic meteorological parameters during the different local seasons.

Assessing local resilience to typhoon disasters: A case study in Nansha, Guangzhou.

PubMed

Song, Jinglu; Huang, Bo; Li, Rongrong

2018-01-01

Building communities' resilience to natural weather hazards requires the appropriate assessment of such capabilities. The resilience of a community is affected not only by social, economic, and infrastructural factors but also by natural factors (including both site characteristics and the intensity and frequency of events). To date, studies of natural factors have tended to draw on annual censuses and to use aggregated data, thus allowing only a limited understanding of site-specific hot or cold spots of resilience. To improve this situation, we carried out a comprehensive assessment of resilience to typhoon disasters in Nansha district, Guangzhou, China. We measured disaster resilience on 1×1-km grid units with respect to socioeconomic and infrastructural dimensions using a set of variables and also estimated natural factors in a detailed manner with a meteorological modeling tool, the Weather Research and Forecast model. We selected typhoon samples over the past 10 years, simulated the maximum typhoon-borne strong winds and precipitation of each sample, and predicted the wind speed and precipitation volume at the 100-year return-level on the basis of extreme value analysis. As a result, a composite resilience index was devised by combining factors in different domains using factor analysis coupled with the analytic hierarchy process. Resilience mapping using this composite resilience index allows local governments and planners to identify potential hot or cold spots of resilience and the dominant factors in particular locations, thereby assisting them in making more rational site-specific measures to improve local resilience to future typhoon disasters.

Assessing local resilience to typhoon disasters: A case study in Nansha, Guangzhou

PubMed Central

Huang, Bo; Li, Rongrong

2018-01-01

Building communities’ resilience to natural weather hazards requires the appropriate assessment of such capabilities. The resilience of a community is affected not only by social, economic, and infrastructural factors but also by natural factors (including both site characteristics and the intensity and frequency of events). To date, studies of natural factors have tended to draw on annual censuses and to use aggregated data, thus allowing only a limited understanding of site-specific hot or cold spots of resilience. To improve this situation, we carried out a comprehensive assessment of resilience to typhoon disasters in Nansha district, Guangzhou, China. We measured disaster resilience on 1×1-km grid units with respect to socioeconomic and infrastructural dimensions using a set of variables and also estimated natural factors in a detailed manner with a meteorological modeling tool, the Weather Research and Forecast model. We selected typhoon samples over the past 10 years, simulated the maximum typhoon-borne strong winds and precipitation of each sample, and predicted the wind speed and precipitation volume at the 100-year return-level on the basis of extreme value analysis. As a result, a composite resilience index was devised by combining factors in different domains using factor analysis coupled with the analytic hierarchy process. Resilience mapping using this composite resilience index allows local governments and planners to identify potential hot or cold spots of resilience and the dominant factors in particular locations, thereby assisting them in making more rational site-specific measures to improve local resilience to future typhoon disasters. PMID:29522526

Animal movement in the absence of predation: environmental drivers of movement strategies in a partial migration system

USGS Publications Warehouse

Bastille-Rousseau, Guillaume; Gibbs, James P.; Yackulic, Charles B.; Frair, Jacqueline L.; Cabrera, Fredy; Rousseau, Louis-Philippe

2016-01-01

Animal movement strategies including migration, dispersal, nomadism, and residency are shaped by broad-scale spatial-temporal structuring of the environment, including factors such as the degrees of spatial variation, seasonality and inter-annual predictability. Animal movement strategies, in turn, interact with the characteristics of individuals and the local distribution of resources to determine local patterns of resource selection with complex and poorly understood implications for animal fitness. Here we present a multi-scale investigation of animal movement strategies and resource selection. We consider the degree to which spatial variation, seasonality, and inter-annual predictability in resources drive migration patterns among different taxa and how movement strategies in turn shape local resource selection patterns. We focus on adult Galapagos giant tortoises Chelonoidis spp. as a model system since they display many movement strategies and evolved in the absence of predators of adults. Specifically, our analysis is based on 63 individuals among four taxa tracked on three islands over six years and almost 106 tortoise re-locations. Tortoises displayed a continuum of movement strategies from migration to sedentarism that were linked to the spatio-temporal scale and predictability of resource distributions. Movement strategies shaped patterns of resource selection. Specifically, migratory individuals displayed stronger selection toward areas where resources were more predictable among years than did non-migratory individuals, which indicates a selective advantage for migrants in seasonally structured, more predictable environments. Our analytical framework combines large-scale predictions for movement strategies, based on environmental structuring, with finer-scale analysis of space-use. Integrating different organizational levels of analysis provides a deeper understanding of the eco-evolutionary dynamics at play in the emergence and maintenance of migration and the critical role of resource predictability. Our results highlight that assessing the potential benefits of differential behavioral responses first requires an understanding of the interactions among movement strategies, resource selection and individual characteristics.

Factors predictive of locoregional recurrence following neoadjuvant chemotherapy in patients with large operable or locally advanced breast cancer: An analysis of the EORTC 10994/BIG 1-00 study.

PubMed

Gillon, Pauline; Touati, Nathan; Breton-Callu, Christel; Slaets, Leen; Cameron, David; Bonnefoi, Hervé

2017-07-01

Identification of clinicopathological factors predicting for a locoregional recurrence (LRR) after neoadjuvant chemotherapy (NAC) could help to decide on the optimal locoregional radiotherapy. The objective of this trial is to identify those factors in the context of a phase III trial (European Organisation for Research and Treatment of Cancer 10994). Patients received NAC followed by surgery with or without radiotherapy. Radiotherapy was administered according to pre-specified guidelines. Patients with hormone receptor positive tumours received adjuvant hormonal therapy. A proportion of patients with human epidermal growth factor receptor 2 (HER2) positive cancer received adjuvant trastuzumab. The predictive factors for LRR were identified by multivariate analysis with time to LRR as first event as the primary end-point. The median follow-up was 4.4 years. In 1553 eligible patients, there were 76 LRRs with a 5-year cumulative incidence of 4.9% (95% confidence interval, CI [3.76-6.04]). In multivariate analysis, breast cancer subtype was a significant predictor of LRR (p < 0.0001): hazard ratio (HR) 6.44 (95% CI [2.83-14.69]) for triple negative, 6.26 (95% CI [2.81-13.93]) for HER2+ without trastuzumab (T) and 3.37 (95% CI [1.10-10.34]) for HER2+ with T cancers, all compared to luminal A patients. Lack of pathological response was also associated with significantly higher LRR risk in case of ≥4 pathologically positive nodes, HR 2.43 (95% CI [1.34-4.40], p < 0.0001). Breast cancer subtype and lack of pathological response are predictive factors for high LRR after NAC. Copyright © 2017 Elsevier Ltd. All rights reserved.

Predicting groundwater recharge for varying land cover and climate conditions - a global meta-study

NASA Astrophysics Data System (ADS)

Mohan, Chinchu; Western, Andrew W.; Wei, Yongping; Saft, Margarita

2018-05-01

Groundwater recharge is one of the important factors determining the groundwater development potential of an area. Even though recharge plays a key role in controlling groundwater system dynamics, much uncertainty remains regarding the relationships between groundwater recharge and its governing factors at a large scale. Therefore, this study aims to identify the most influential factors of groundwater recharge, and to develop an empirical model to estimate diffuse rainfall recharge at a global scale. Recharge estimates reported in the literature from various parts of the world (715 sites) were compiled and used in model building and testing exercises. Unlike conventional recharge estimates from water balance, this study used a multimodel inference approach and information theory to explain the relationship between groundwater recharge and influential factors, and to predict groundwater recharge at 0.5° resolution. The results show that meteorological factors (precipitation and potential evapotranspiration) and vegetation factors (land use and land cover) had the most predictive power for recharge. According to the model, long-term global average annual recharge (1981-2014) was 134 mm yr-1 with a prediction error ranging from -8 to 10 mm yr-1 for 97.2 % of cases. The recharge estimates presented in this study are unique and more reliable than the existing global groundwater recharge estimates because of the extensive validation carried out using both independent local estimates collated from the literature and national statistics from the Food and Agriculture Organization (FAO). In a water-scarce future driven by increased anthropogenic development, the results from this study will aid in making informed decisions about groundwater potential at a large scale.

Mode localization in the cooperative dynamics of protein recognition

NASA Astrophysics Data System (ADS)

Copperman, J.; Guenza, M. G.

2016-07-01

The biological function of proteins is encoded in their structure and expressed through the mediation of their dynamics. This paper presents a study on the correlation between local fluctuations, binding, and biological function for two sample proteins, starting from the Langevin Equation for Protein Dynamics (LE4PD). The LE4PD is a microscopic and residue-specific coarse-grained approach to protein dynamics, which starts from the static structural ensemble of a protein and predicts the dynamics analytically. It has been shown to be accurate in its prediction of NMR relaxation experiments and Debye-Waller factors. The LE4PD is solved in a set of diffusive modes which span a vast range of time scales of the protein dynamics, and provides a detailed picture of the mode-dependent localization of the fluctuation as a function of the primary structure of the protein. To investigate the dynamics of protein complexes, the theory is implemented here to treat the coarse-grained dynamics of interacting macromolecules. As an example, calculations of the dynamics of monomeric and dimerized HIV protease and the free Insulin Growth Factor II Receptor (IGF2R) domain 11 and its IGF2R:IGF2 complex are presented. Either simulation-derived or experimentally measured NMR conformers are used as input structural ensembles to the theory. The picture that emerges suggests a dynamical heterogeneous protein where biologically active regions provide energetically comparable conformational states that are trapped by a reacting partner in agreement with the conformation-selection mechanism of binding.

Predictors of Responses to Corticosteroids for Cancer-Related Fatigue in Advanced Cancer Patients: A Multicenter, Prospective, Observational Study.

PubMed

Matsuo, Naoki; Morita, Tatsuya; Matsuda, Yoshinobu; Okamoto, Kenichiro; Matsumoto, Yoshihisa; Kaneishi, Keisuke; Odagiri, Takuya; Sakurai, Hiroki; Katayama, Hideki; Mori, Ichiro; Yamada, Hirohide; Watanabe, Hiroaki; Yokoyama, Taro; Yamaguchi, Takashi; Nishi, Tomohiro; Shirado, Akemi; Hiramoto, Shuji; Watanabe, Toshio; Kohara, Hiroyuki; Shimoyama, Satofumi; Aruga, Etsuko; Baba, Mika; Sumita, Koki; Iwase, Satoru

2016-07-01

Although corticosteroids are widely used to relieve cancer-related fatigue (CRF), information regarding the factors predicting responses to corticosteroids remains limited. The aim of this study was to identify potential factors predicting responses to corticosteroids for CRF in advanced cancer patients. Inclusion criteria for this multicenter, prospective, observational study were patients who had metastatic or locally advanced cancer and had a fatigue intensity score of 4 or more on a 0-10 Numerical Rating Scale (NRS). Univariate and multivariate analyses were conducted to identify the factors predicting two-point reduction or more in NRS on day 3. Among 179 patients who received corticosteroids, 86 (48%; 95% CI 41%-56%) had a response with two-point reduction or more. Factors that significantly predicted responses were performance status score of 3 or more, Palliative Performance Scale score more than 40, absence of ascites, absence of drowsiness, absence of depression, serum albumin level greater than 3 mg/dL, serum sodium level greater than 135 mEq/L, and baseline NRS score greater than 5. A multivariate analysis showed that the independent factors predicting responses were baseline NRS score greater than 5 (odds ratio [OR] 6.6, 95% CI 2.8-15.4), Palliative Performance Scale score more than 40 (OR 4.4, 95% CI 2.1-9.3), absence of drowsiness (OR 3.4, 95% CI 1.7-6.9), absence of ascites (OR 2.3, 95% CI 1.1-4.7), and absence of pleural effusion (OR 2.2, 95% CI 1.0-5.0). Treatment responses to corticosteroids for CRF may be predicted by baseline symptom intensity, performance status, drowsiness, and severity of fluid retention symptoms. Larger prospective studies are needed to confirm these results. Copyright © 2016 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Predictors of Longitudinal Quality of Life in Juvenile Localized Scleroderma.

PubMed

Ardalan, Kaveh; Zigler, Christina K; Torok, Kathryn S

2017-07-01

Localized scleroderma can negatively affect children's quality of life (QoL), but predictors of impact have not been well described. We sought to identify predictors of QoL impact in juvenile localized scleroderma patients. We analyzed longitudinal data from a single-center cohort of juvenile localized scleroderma patients, using hierarchical generalized linear modeling (HGLM) to identify predictors of QoL impact. HGLM is useful for nested data and allows for evaluation of both time-variant and time-invariant predictors. The number of extracutaneous manifestations (ECMs; e.g., joint contracture and hemifacial atrophy) and female sex predicted negative QoL impact, defined as a Children's Dermatology Life Quality Index score >1 (P = 0.019 for ECMs and P = 0.002 for female sex). As the time since the initial visit increased, the odds of reporting a negative QoL impact decreased (P < 0.001). Our results suggest that ECMs, sex, and time since initial visit are more predictive of QoL impact in localized scleroderma than cutaneous features. Further study is required to determine which ECMs have the most impact on QoL, which factors underlie sex differences in QoL in localized scleroderma, and why increasing the time since the initial visit appears to be protective. An improved understanding of predictors of QoL impact may allow for the identification of patients at risk of poorer outcomes and for the tailoring of treatment and psychosocial support. © 2016, American College of Rheumatology.

Does the academic performance of psychiatrists influence success in the NHS Clinical Excellence Award Scheme?

PubMed Central

Mitchell, Alex J; Crowfoot, Daniel; Leaver, James; Hughes, Samantha

2011-01-01

Objectives Given the uncertainty about factors that influence receipt of Clinical Excellence Awards (CEA) and recent availability of advanced research metrics, we examined the factors that predict CEA success using a convenience sample of English psychiatrists. Design Observational study examining region, subspecialty, H-index, M-index, number of publications, years since registration and years in specialty. Setting ACCEA Nominal Roll, cross-referenced with data from the GMC's list of registered medical practitioners and Thompson's Web of Science database. Participants A total of 494 psychiatrists including 245 with national levels awards and a random sample with local level awards. Main outcome measures Receipt of local or national CEA awards in 2008 and 2009. Results Of those with national awards, 126 had university contracts and 119 NHS contracts. Across all staff, years since qualification in medicine and H-index were the dominant influences. For local awards we found that years worked in the specialty was the main predictor of a CEA award with a smaller contribution from H-index. For national awards to university staff (academics) years on the medical register and publication rate were significant predictors. For national awards to NHS staff (non-academics) H-index and total cites were predictive, but these were themselves related to age. Conclusions Progression in CEAs among psychiatrists is strongly influenced by age (years spent in specialty and years on the medical register) with an additional contribution from research productivity. Currently, research impact is crudely assessed in the CEA process. We suggest that CEA committees formally assess the impact of NHS-related research using standardized research metrics which are openly available. We also suggest that supporting organizations and local trusts adhere to the rules mandated by the ACCEA. PMID:21541089

Local-regional recurrence after surgery without postoperative irradiation for carcinomas of the major salivary glands: Implications for adjuvant therapy

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

Chen, Allen M.; Granchi, Phillip J.; Garcia, Joaquin

2007-03-15

Purpose: To determine factors predictive of local-regional recurrence (LRR) after surgery alone for carcinomas of the major salivary glands in an attempt to evaluate the potential role of postoperative radiation therapy. Methods and Materials: Between 1960 and 2004, 207 patients with carcinomas of the major salivary glands were treated with definitive surgery without postoperative radiation therapy. Histology was: 67 mucoepidermoid (32%), 50 adenoid cystic (24%), 34 acinic cell (16%), 23 malignant mixed (11%), 16 adenocarcinoma (8%), 6 oncocytic (3%), 6 myoepithelial (3%), and 5 other (2%). Distribution of pathologic T-stage was: 54 T1 (26%), 83 T2 (40%), 46 T3 (22%),more » and 24 T4 (12%). Sixty patients (29%) had microscopically positive margins. Median follow-up was 6.1 years (range, 0.5-18.7 years). Results: The 5-year and 10-year estimates of local-regional control were 86% and 74%, respectively. A Cox proportional hazard model identified pathologic lymph node metastasis (hazard ratio [HR], 4.8; p = 0.001), high histologic grade (HR, 4.2; p = 0.003), positive margins (HR, 2.6; p = 0.03), and T3-4 disease (HR, 2.0; p = 0.04) as independent predictors of LRR. The presence of any one of these factors was associated with 10-year local-regional control rates of 37% to 63%. Conclusion: Lymph node metastasis, high tumor grade, positive margins, and T3-4 stage predict for significant rates of LRR after surgery for carcinomas of the major salivary glands. Postoperative radiation therapy should be considered for patients with these disease characteristics.« less

Pathological response of locally advanced rectal cancer to preoperative chemotherapy without pelvic irradiation.

PubMed

Bensignor, T; Brouquet, A; Dariane, C; Thirot-Bidault, A; Lazure, T; Julié, C; Nordlinger, B; Penna, C; Benoist, S

2015-06-01

Pathological response to chemotherapy without pelvic irradiation is not well defined in rectal cancer. This study aimed to evaluate the objective pathological response to preoperative chemotherapy without pelvic irradiation in middle or low locally advanced rectal cancer (LARC). Between 2008 and 2013, 22 patients with middle or low LARC (T3/4 and/or N+ and circumferential resection margin < 2 mm) and synchronous metastatic disease or a contraindication to pelvic irradiation underwent rectal resection after preoperative chemotherapy. The pathological response of rectal tumour was analysed according to the Rödel tumour regression grading (TRG) system. Predictive factors of objective pathological response (TRG 2-4) were analysed. All patients underwent rectal surgery after a median of six cycles of preoperative chemotherapy. Of these, 20 (91%) had sphincter saving surgery and an R0 resection. Twelve (55%) patients had an objective pathological response (TRG 2-4), including one complete response. Poor response (TRG 0-1) to chemotherapy was noted in 10 (45%) patients. In univariate analyses, none of the factors examined was found to be predictive of an objective pathological response to chemotherapy. At a median follow-up of 37.2 months, none of the 22 patients experienced local recurrence. Of the 19 patients with Stage IV rectal cancer, 15 (79%) had liver surgery with curative intent. Preoperative chemotherapy without pelvic irradiation is associated with objective pathological response and adequate local control in selected patients with LARC. Further prospective controlled studies will address the question of whether it can be used as a valuable alternative to radiochemotherapy in LARC. Colorectal Disease © 2014 The Association of Coloproctology of Great Britain and Ireland.

Modelling malaria incidence with environmental dependency in a locality of Sudanese savannah area, Mali

PubMed Central

Gaudart, Jean; Touré, Ousmane; Dessay, Nadine; Dicko, A lassane; Ranque, Stéphane; Forest, Loic; Demongeot, Jacques; Doumbo, Ogobara K

2009-01-01

Background The risk of Plasmodium falciparum infection is variable over space and time and this variability is related to environmental variability. Environmental factors affect the biological cycle of both vector and parasite. Despite this strong relationship, environmental effects have rarely been included in malaria transmission models. Remote sensing data on environment were incorporated into a temporal model of the transmission, to forecast the evolution of malaria epidemiology, in a locality of Sudanese savannah area. Methods A dynamic cohort was constituted in June 1996 and followed up until June 2001 in the locality of Bancoumana, Mali. The 15-day composite vegetation index (NDVI), issued from satellite imagery series (NOAA) from July 1981 to December 2006, was used as remote sensing data. The statistical relationship between NDVI and incidence of P. falciparum infection was assessed by ARIMA analysis. ROC analysis provided an NDVI value for the prediction of an increase in incidence of parasitaemia. Malaria transmission was modelled using an SIRS-type model, adapted to Bancoumana's data. Environmental factors influenced vector mortality and aggressiveness, as well as length of the gonotrophic cycle. NDVI observations from 1981 to 2001 were used for the simulation of the extrinsic variable of a hidden Markov chain model. Observations from 2002 to 2006 served as external validation. Results The seasonal pattern of P. falciparum incidence was significantly explained by NDVI, with a delay of 15 days (p = 0.001). An NDVI threshold of 0.361 (p = 0.007) provided a Diagnostic Odd Ratio (DOR) of 2.64 (CI95% [1.26;5.52]). The deterministic transmission model, with stochastic environmental factor, predicted an endemo-epidemic pattern of malaria infection. The incidences of parasitaemia were adequately modelled, using the observed NDVI as well as the NDVI simulations. Transmission pattern have been modelled and observed values were adequately predicted. The error parameters have shown the smallest values for a monthly model of environmental changes. Conclusion Remote-sensed data were coupled with field study data in order to drive a malaria transmission model. Several studies have shown that the NDVI presents significant correlations with climate variables, such as precipitations particularly in Sudanese savannah environments. Non-linear model combining environmental variables, predisposition factors and transmission pattern can be used for community level risk evaluation. PMID:19361335

Modelling malaria incidence with environmental dependency in a locality of Sudanese savannah area, Mali.

PubMed

Gaudart, Jean; Touré, Ousmane; Dessay, Nadine; Dicko, A Lassane; Ranque, Stéphane; Forest, Loic; Demongeot, Jacques; Doumbo, Ogobara K

2009-04-10

The risk of Plasmodium falciparum infection is variable over space and time and this variability is related to environmental variability. Environmental factors affect the biological cycle of both vector and parasite. Despite this strong relationship, environmental effects have rarely been included in malaria transmission models.Remote sensing data on environment were incorporated into a temporal model of the transmission, to forecast the evolution of malaria epidemiology, in a locality of Sudanese savannah area. A dynamic cohort was constituted in June 1996 and followed up until June 2001 in the locality of Bancoumana, Mali. The 15-day composite vegetation index (NDVI), issued from satellite imagery series (NOAA) from July 1981 to December 2006, was used as remote sensing data.The statistical relationship between NDVI and incidence of P. falciparum infection was assessed by ARIMA analysis. ROC analysis provided an NDVI value for the prediction of an increase in incidence of parasitaemia.Malaria transmission was modelled using an SIRS-type model, adapted to Bancoumana's data. Environmental factors influenced vector mortality and aggressiveness, as well as length of the gonotrophic cycle. NDVI observations from 1981 to 2001 were used for the simulation of the extrinsic variable of a hidden Markov chain model. Observations from 2002 to 2006 served as external validation. The seasonal pattern of P. falciparum incidence was significantly explained by NDVI, with a delay of 15 days (p = 0.001). An NDVI threshold of 0.361 (p = 0.007) provided a Diagnostic Odd Ratio (DOR) of 2.64 (CI95% [1.26;5.52]).The deterministic transmission model, with stochastic environmental factor, predicted an endemo-epidemic pattern of malaria infection. The incidences of parasitaemia were adequately modelled, using the observed NDVI as well as the NDVI simulations. Transmission pattern have been modelled and observed values were adequately predicted. The error parameters have shown the smallest values for a monthly model of environmental changes. Remote-sensed data were coupled with field study data in order to drive a malaria transmission model. Several studies have shown that the NDVI presents significant correlations with climate variables, such as precipitations particularly in Sudanese savannah environments. Non-linear model combining environmental variables, predisposition factors and transmission pattern can be used for community level risk evaluation.

Effects of Climate Change and Fisheries Bycatch on Shy Albatross (Thalassarche cauta) in Southern Australia

PubMed Central

2015-01-01

The impacts of climate change on marine species are often compounded by other stressors that make direct attribution and prediction difficult. Shy albatrosses (Thalassarche cauta) breeding on Albatross Island, Tasmania, show an unusually restricted foraging range, allowing easier discrimination between the influence of non-climate stressors (fisheries bycatch) and environmental variation. Local environmental conditions (rainfall, air temperature, and sea-surface height, an indicator of upwelling) during the vulnerable chick-rearing stage, have been correlated with breeding success of shy albatrosses. We use an age-, stage- and sex-structured population model to explore potential relationships between local environmental factors and albatross breeding success while accounting for fisheries bycatch by trawl and longline fisheries. The model uses time-series of observed breeding population counts, breeding success, adult and juvenile survival rates and a bycatch mortality observation for trawl fishing to estimate fisheries catchability, environmental influence, natural mortality rate, density dependence, and productivity. Observed at-sea distributions for adult and juvenile birds were coupled with reported fishing effort to estimate vulnerability to incidental bycatch. The inclusion of rainfall, temperature and sea-surface height as explanatory variables for annual chick mortality rate was statistically significant. Global climate models predict little change in future local average rainfall, however, increases are forecast in both temperatures and upwelling, which are predicted to have detrimental and beneficial effects, respectively, on breeding success. The model shows that mitigation of at least 50% of present bycatch is required to offset losses due to future temperature changes, even if upwelling increases substantially. Our results highlight the benefits of using an integrated modeling approach, which uses available demographic as well as environmental data within a single estimation framework, to provide future predictions. Such predictions inform the development of management options in the face of climate change. PMID:26057739

Effects of Climate Change and Fisheries Bycatch on Shy Albatross (Thalassarche cauta) in Southern Australia.

PubMed

Thomson, Robin B; Alderman, Rachael L; Tuck, Geoffrey N; Hobday, Alistair J

2015-01-01

The impacts of climate change on marine species are often compounded by other stressors that make direct attribution and prediction difficult. Shy albatrosses (Thalassarche cauta) breeding on Albatross Island, Tasmania, show an unusually restricted foraging range, allowing easier discrimination between the influence of non-climate stressors (fisheries bycatch) and environmental variation. Local environmental conditions (rainfall, air temperature, and sea-surface height, an indicator of upwelling) during the vulnerable chick-rearing stage, have been correlated with breeding success of shy albatrosses. We use an age-, stage- and sex-structured population model to explore potential relationships between local environmental factors and albatross breeding success while accounting for fisheries bycatch by trawl and longline fisheries. The model uses time-series of observed breeding population counts, breeding success, adult and juvenile survival rates and a bycatch mortality observation for trawl fishing to estimate fisheries catchability, environmental influence, natural mortality rate, density dependence, and productivity. Observed at-sea distributions for adult and juvenile birds were coupled with reported fishing effort to estimate vulnerability to incidental bycatch. The inclusion of rainfall, temperature and sea-surface height as explanatory variables for annual chick mortality rate was statistically significant. Global climate models predict little change in future local average rainfall, however, increases are forecast in both temperatures and upwelling, which are predicted to have detrimental and beneficial effects, respectively, on breeding success. The model shows that mitigation of at least 50% of present bycatch is required to offset losses due to future temperature changes, even if upwelling increases substantially. Our results highlight the benefits of using an integrated modeling approach, which uses available demographic as well as environmental data within a single estimation framework, to provide future predictions. Such predictions inform the development of management options in the face of climate change.

Associations between disability prevalence and local-area characteristics in a general community-living population.

PubMed

Philibert, M D; Pampalon, R; Hamel, D; Daniel, M

2013-10-01

Disability is understood to arise from person-environment interactions. Hence, heterogeneity in local-area characteristics should be associated with local-area variation in disability prevalence. This study evaluated the associations of disability prevalence with local-area socioeconomic status and contextual features. Disability prevalence was obtained from the Canada census of 2001 for the entire province of Québec at the level of dissemination areas (617 individuals on average) based on responses from 20% of the population. Data on local-area characteristics were urban-rural denomination, social and material deprivation, active and collective commuting, residential stability, and housing quality. Associations between local-area characteristics and disability prevalence were assessed using multilevel logistic regressions. Disability was associated with local-area socioeconomic status and contextual characteristics, and heterogeneity in these factors accounted for urban-rural differences in disability prevalence. Associations between contextual features and disability prevalence were confounded by local-area socioeconomic status. Some associations between local-area socioeconomic status and disability prevalence were moderated by contextual characteristics. The importance of this effect modification is greater when expressed in terms of the absolute magnitude of disability than in the relative likelihood of disability. Explanation of rural-urban differences by the contribution of other local-area characteristics is consistent with the conceptualization of urban-rural categories as the reflection of spatially varying ensembles of compositional and contextual factors. Although local-area socioeconomic status explains most variability in disability prevalence, this study shows that contextual characteristics are relevant to analyses of the spatial patterning of disability as they predict spatial variations of disability, sometimes in interaction with socioeconomic status. This study demonstrates that absolute and relative perspectives on effect modification may lead to differing conclusions. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Shuttle sonic boom - Technology and predictions. [environmental impact

NASA Technical Reports Server (NTRS)

Holloway, P. F.; Wilhold, G. A.; Jones, J. H.; Garcia, F., Jr.; Hicks, R. M.

1973-01-01

Because the shuttle differs significantly in both geometric and operational characteristics from conventional supersonic aircraft, estimation of sonic boom characteristics required a new technology base. The prediction procedures thus developed are reviewed. Flight measurements obtained for both the ascent and entry phases of the Apollo 15 and 16 and for the ascent phase only of the Apollo 17 missions are presented which verify the techniques established for application to shuttle. Results of extensive analysis of the sonic boom overpressure characteristics completed to date are presented which indicate that this factor of the shuttle's environmental impact is predictable, localized, of short duration and acceptable. Efforts are continuing to define the shuttle sonic boom characteristics to a fine level of detail based on the final system design.

Statistical short-term earthquake prediction.

PubMed

Kagan, Y Y; Knopoff, L

1987-06-19

A statistical procedure, derived from a theoretical model of fracture growth, is used to identify a foreshock sequence while it is in progress. As a predictor, the procedure reduces the average uncertainty in the rate of occurrence for a future strong earthquake by a factor of more than 1000 when compared with the Poisson rate of occurrence. About one-third of all main shocks with local magnitude greater than or equal to 4.0 in central California can be predicted in this way, starting from a 7-year database that has a lower magnitude cut off of 1.5. The time scale of such predictions is of the order of a few hours to a few days for foreshocks in the magnitude range from 2.0 to 5.0.

PlantTFDB: a comprehensive plant transcription factor database

PubMed Central

Guo, An-Yuan; Chen, Xin; Gao, Ge; Zhang, He; Zhu, Qi-Hui; Liu, Xiao-Chuan; Zhong, Ying-Fu; Gu, Xiaocheng; He, Kun; Luo, Jingchu

2008-01-01

Transcription factors (TFs) play key roles in controlling gene expression. Systematic identification and annotation of TFs, followed by construction of TF databases may serve as useful resources for studying the function and evolution of transcription factors. We developed a comprehensive plant transcription factor database PlantTFDB (http://planttfdb.cbi.pku.edu.cn), which contains 26 402 TFs predicted from 22 species, including five model organisms with available whole genome sequence and 17 plants with available EST sequences. To provide comprehensive information for those putative TFs, we made extensive annotation at both family and gene levels. A brief introduction and key references were presented for each family. Functional domain information and cross-references to various well-known public databases were available for each identified TF. In addition, we predicted putative orthologs of those TFs among the 22 species. PlantTFDB has a simple interface to allow users to search the database by IDs or free texts, to make sequence similarity search against TFs of all or individual species, and to download TF sequences for local analysis. PMID:17933783

Predicting intensity of white-tailed deer herbivory in the Central Appalachian Mountains

USGS Publications Warehouse

Kniowski, Andrew B.; Ford, W. Mark

2018-01-01

In eastern North America, white-tailed deer (Odocoileus virginianus) can have profound influences on forest biodiversity and forest successional processes. Moderate to high deer populations in the central Appalachians have resulted in lower forest biodiversity. Legacy effects in some areas persist even following deer population reductions or declines. This has prompted managers to consider deer population management goals in light of policies designed to support conservation of biodiversity and forest regeneration while continuing to support ample recreational hunting opportunities. However, despite known relationships between herbivory intensity and biodiversity impact, little information exists on the predictability of herbivory intensity across the varied and spatially diverse habitat conditions of the central Appalachians. We examined the predictability of browsing rates across central Appalachian landscapes at four environmental scales: vegetative community characteristics, physical environment, habitat configuration, and local human and deer population demographics. In an information-theoretic approach, we found that a model fitting the number of stems browsed relative to local vegetation characteristics received most (62%) of the overall support of all tested models assessing herbivory impact. Our data suggest that deer herbivory responded most predictably to differences in vegetation quantity and type. No other spatial factors or demographic factors consistently affected browsing intensity. Because herbivory, vegetation communities, and productivity vary spatially, we suggest that effective broad-scale herbivory impact assessment should include spatially-balanced vegetation monitoring that accounts for regional differences in deer forage preference. Effective monitoring is necessary to avoid biodiversity impacts and deleterious changes in vegetation community composition that are difficult to reverse and/or may not be detected using traditional deer-density based management goals.

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%.

Predicting Esophagitis After Chemoradiation Therapy for Non-Small Cell Lung Cancer: An Individual Patient Data Meta-Analysis

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

Palma, David A., E-mail: david.palma@uwo.ca; Senan, Suresh; Oberije, Cary

Purpose: Concurrent chemoradiation therapy (CCRT) improves survival compared with sequential treatment for locally advanced non-small cell lung cancer, but it increases toxicity, particularly radiation esophagitis (RE). Validated predictors of RE for clinical use are lacking. We performed an individual-patient-data meta-analysis to determine factors predictive of clinically significant RE. Methods and Materials: After a systematic review of the literature, data were obtained on 1082 patients who underwent CCRT, including patients from Europe, North America, Asia, and Australia. Patients were randomly divided into training and validation sets (2/3 vs 1/3 of patients). Factors predictive of RE (grade ≥2 and grade ≥3) weremore » assessed using logistic modeling, with the concordance statistic (c statistic) used to evaluate the performance of each model. Results: The median radiation therapy dose delivered was 65 Gy, and the median follow-up time was 2.1 years. Most patients (91%) received platinum-containing CCRT regimens. The development of RE was common, scored as grade 2 in 348 patients (32.2%), grade 3 in 185 (17.1%), and grade 4 in 10 (0.9%). There were no RE-related deaths. On univariable analysis using the training set, several baseline factors were statistically predictive of RE (P<.05), but only dosimetric factors had good discrimination scores (c > .60). On multivariable analysis, the esophageal volume receiving ≥60 Gy (V60) alone emerged as the best predictor of grade ≥2 and grade ≥3 RE, with good calibration and discrimination. Recursive partitioning identified 3 risk groups: low (V60 <0.07%), intermediate (V60 0.07% to 16.99%), and high (V60 ≥17%). With use of the validation set, the predictive model performed inferiorly for the grade ≥2 endpoint (c = .58) but performed well for the grade ≥3 endpoint (c = .66). Conclusions: Clinically significant RE is common, but life-threatening complications occur in <1% of patients. Although several factors are statistically predictive of RE, the V60 alone provides the best predictive ability. Efforts to reduce the V60 should be prioritized, with further research needed to identify and validate new predictive factors.« less

Vascular endothelial growth factor (VEGF) expression in locally advanced prostate cancer: secondary analysis of radiation therapy oncology group (RTOG) 8610.

PubMed

Pan, Larry; Baek, Seunghee; Edmonds, Pamela R; Roach, Mack; Wolkov, Harvey; Shah, Satish; Pollack, Alan; Hammond, M Elizabeth; Dicker, Adam P

2013-04-25

Angiogenesis is a key element in solid-tumor growth, invasion, and metastasis. VEGF is among the most potent angiogenic factor thus far detected. The aim of the present study is to explore the potential of VEGF (also known as VEGF-A) as a prognostic and predictive biomarker among men with locally advanced prostate cancer. The analysis was performed using patients enrolled on RTOG 8610, a phase III randomized control trial of radiation therapy alone (Arm 1) versus short-term neoadjuvant and concurrent androgen deprivation and radiation therapy (Arm 2) in men with locally advanced prostate carcinoma. Tissue samples were obtained from the RTOG tissue repository. Hematoxylin and eosin slides were reviewed, and paraffin blocks were immunohistochemically stained for VEGF expression and graded by Intensity score (0-3). Cox or Fine and Gray's proportional hazards models were used. Sufficient pathologic material was available from 103 (23%) of the 456 analyzable patients enrolled in the RTOG 8610 study. There were no statistically significant differences in the pre-treatment characteristics between the patient groups with and without VEGF intensity data. Median follow-up for all surviving patients with VEGF intensity data is 12.2 years. Univariate and multivariate analyses demonstrated no statistically significant correlation between the intensity of VEGF expression and overall survival, distant metastasis, local progression, disease-free survival, or biochemical failure. VEGF expression was also not statistically significantly associated with any of the endpoints when analyzed by treatment arm. This study revealed no statistically significant prognostic or predictive value of VEGF expression for locally advanced prostate cancer. This analysis is among one of the largest sample bases with long-term follow-up in a well-characterized patient population. There is an urgent need to establish multidisciplinary initiatives for coordinating further research in the area of human prostate cancer biomarkers.

Factors affecting summer distributions of Bering Sea forage fish species: Assessing competing hypotheses

NASA Astrophysics Data System (ADS)

Parker-Stetter, Sandra; Urmy, Samuel; Horne, John; Eisner, Lisa; Farley, Edward

2016-12-01

Hypotheses on the factors affecting forage fish species distributions are often proposed but rarely evaluated using a comprehensive suite of indices. Using 24 predictor indices, we compared competing hypotheses and calculated average models for the distributions of capelin, age-0 Pacific cod, and age-0 pollock in the eastern Bering Sea from 2006 to 2010. Distribution was described using a two stage modeling approach: probability of occurrence ("presence") and density when fish were present. Both local (varying by location and year) and annual (uniform in space but varying by year) indices were evaluated, the latter accounting for the possibility that distributions were random but that overall presence or densities changed with annual conditions. One regional index, distance to the location of preflexion larvae earlier in the year, was evaluated for age-0 pollock. Capelin distributions were best predicted by local indices such as bottom depth, temperature, and salinity. Annual climate (May sea surface temperature (SST), sea ice extent anomaly) and wind (June wind speed cubed) indices were often important for age-0 Pacific cod in addition to local indices (temperature and depth). Surface, midwater, and water column age-0 pollock distributions were best described by a combination of local (depth, temperature, salinity, zooplankton) and annual (May SST, sea ice anomaly, June wind speed cubed) indices. Our results corroborated some of those in previous distribution studies, but suggested that presence and density may also be influenced by other factors. Even though there were common environmental factors that influenced all species' distributions, it is not possible to generalize conditions for forage fish as a group.

Instrumental record of debris flow initiation during natural rainfall: Implications for modeling slope stability

USGS Publications Warehouse

Montgomery, D.R.; Schmidt, K.M.; Dietrich, W.E.; McKean, J.

2009-01-01

The middle of a hillslope hollow in the Oregon Coast Range failed and mobilized as a debris flow during heavy rainfall in November 1996. Automated pressure transducers recorded high spatial variability of pore water pressure within the area that mobilized as a debris flow, which initiated where local upward flow from bedrock developed into overlying colluvium. Postfailure observations of the bedrock surface exposed in the debris flow scar reveal a strong spatial correspondence between elevated piezometric response and water discharging from bedrock fractures. Measurements of apparent root cohesion on the basal (Cb) and lateral (Cl) scarp demonstrate substantial local variability, with areally weighted values of Cb = 0.1 and Cl = 4.6 kPa. Using measured soil properties and basal root strength, the widely used infinite slope model, employed assuming slope parallel groundwater flow, provides a poor prediction of hydrologie conditions at failure. In contrast, a model including lateral root strength (but neglecting lateral frictional strength) gave a predicted critical value of relative soil saturation that fell within the range defined by the arithmetic and geometric mean values at the time of failure. The 3-D slope stability model CLARA-W, used with locally observed pore water pressure, predicted small areas with lower factors of safety within the overall slide mass at sites consistent with field observations of where the failure initiated. This highly variable and localized nature of small areas of high pore pressure that can trigger slope failure means, however, that substantial uncertainty appears inevitable for estimating hydrologie conditions within incipient debris flows under natural conditions. Copyright 2009 by the American Geophysical Union.

A mRNA and cognate microRNAs localize in the nucleolus.

PubMed

Reyes-Gutierrez, Pablo; Ritland Politz, Joan C; Pederson, Thoru

2014-01-01

We previously discovered that a set of 5 microRNAs are concentrated in the nucleolus of rat myoblasts. We now report that several mRNAs are also localized in the nucleoli of these cells as determined by microarray analysis of RNA from purified nucleoli. Among the most abundant of these nucleolus-localized mRNAs is that encoding insulin-like growth factor 2 (IGF2), a regulator of myoblast proliferation and differentiation. The presence of IGF2 mRNA in nucleoli was confirmed by fluorescence in situ hybridization, and RT-PCR experiments demonstrated that these nucleolar transcripts are spliced, thus arriving from the nucleoplasm. Bioinformatics analysis predicted canonically structured, highly thermodynamically stable interactions between IGF2 mRNA and all 5 of the nucleolus-localized microRNAs. These results raise the possibility that the nucleolus is a staging site for setting up particular mRNA-microRNA interactions prior to export to the cytoplasm.

Auxiliary field diffusion Monte Carlo calculations of light and medium-mass nuclei with local chiral interactions

NASA Astrophysics Data System (ADS)

Lonardoni, D.; Gandolfi, S.; Lynn, J. E.; Petrie, C.; Carlson, J.; Schmidt, K. E.; Schwenk, A.

2018-04-01

Quantum Monte Carlo methods have recently been employed to study properties of nuclei and infinite matter using local chiral effective-field-theory interactions. In this work, we present a detailed description of the auxiliary field diffusion Monte Carlo algorithm for nuclei in combination with local chiral two- and three-nucleon interactions up to next-to-next-to-leading order. We show results for the binding energy, charge radius, charge form factor, and Coulomb sum rule in nuclei with 3 ≤A ≤16 . Particular attention is devoted to the effect of different operator structures in the three-body force for different cutoffs. The outcomes suggest that local chiral interactions fit to few-body observables give a very good description of the ground-state properties of nuclei up to 16O, with the exception of one fit for the softer cutoff which predicts overbinding in larger nuclei.

Determining Coastal Hazards Risk Perception to Enhance Local Mitigation Planning through a Participatory Mapping Approach

NASA Astrophysics Data System (ADS)

Bethel, M.; Braud, D.; Lambeth, T.; Biber, P.; Wu, W.

2017-12-01

Coastal community leaders, government officials, and natural resource managers must be able to accurately assess and predict a given coastal landscape's sustainability and/or vulnerability as coastal habitat continues to undergo rapid and dramatic changes associated with natural and anthropogenic activities such as accelerated relative sea level rise (SLR). To help address this information need, a multi-disciplinary project team conducted Sea Grant sponsored research in Louisiana and Mississippi with traditional ecosystem users and natural resource managers to determine a method for producing localized vulnerability and sustainability maps for projected SLR and storm surge impacts, and determine how and whether the results of such an approach can provide more useful information to enhance hazard mitigation planning. The goals of the project are to develop and refine SLR visualization tools for local implementation in areas experiencing subsidence and erosion, and discover the different ways stakeholder groups evaluate risk and plan mitigation strategies associated with projected SLR and storm surge. Results from physical information derived from data and modeling of subsidence, erosion, engineered restoration and coastal protection features, historical land loss, and future land projections under SLR are integrated with complimentary traditional ecological knowledge (TEK) offered by the collaborating local ecosystem users for these assessments. The data analysis involves interviewing stakeholders, coding the interviews for themes, and then converting the themes into vulnerability and sustainability factors. Each factor is weighted according to emphasis by the TEK experts and number of experts who mention it to determine which factors are the highest priority. The priority factors are then mapped with emphasis on the perception of contributing to local community vulnerability or sustainability to SLR and storm surge. The maps are used by the collaborators to benefit local hazard mitigation and adaptation planning. The results to date in achieving the project objectives will be presented that include: analyses of scientific field data collected related to marsh vegetation biomass characteristics, analyses of TEK data collected, and mapping products developed.

Are the Stress Drops of Small Earthquakes Good Predictors of the Stress Drops of Larger Earthquakes?

NASA Astrophysics Data System (ADS)

Hardebeck, J.

2017-12-01

Uncertainty in PSHA could be reduced through better estimates of stress drop for possible future large earthquakes. Studies of small earthquakes find spatial variability in stress drop; if large earthquakes have similar spatial patterns, their stress drops may be better predicted using the stress drops of small local events. This regionalization implies the variance with respect to the local mean stress drop may be smaller than the variance with respect to the global mean. I test this idea using the Shearer et al. (2006) stress drop catalog for M1.5-3.1 events in southern California. I apply quality control (Hauksson, 2015) and remove near-field aftershocks (Wooddell & Abrahamson, 2014). The standard deviation of the distribution of the log10 stress drop is reduced from 0.45 (factor of 3) to 0.31 (factor of 2) by normalizing each event's stress drop by the local mean. I explore whether a similar variance reduction is possible when using the Shearer catalog to predict stress drops of larger southern California events. For catalogs of moderate-sized events (e.g. Kanamori, 1993; Mayeda & Walter, 1996; Boyd, 2017), normalizing by the Shearer catalog's local mean stress drop does not reduce the standard deviation compared to the unmodified stress drops. I compile stress drops of larger events from the literature, and identify 15 M5.5-7.5 earthquakes with at least three estimates. Because of the wide range of stress drop estimates for each event, and the different techniques and assumptions, it is difficult to assign a single stress drop value to each event. Instead, I compare the distributions of stress drop estimates for pairs of events, and test whether the means of the distributions are statistically significantly different. The events divide into 3 categories: low, medium, and high stress drop, with significant differences in mean stress drop between events in the low and the high stress drop categories. I test whether the spatial patterns of the Shearer catalog stress drops can predict the categories of the 15 events. I find that they cannot, rather the large event stress drops are uncorrelated with the local mean stress drop from the Shearer catalog. These results imply that the regionalization of stress drops of small events does not extend to the larger events, at least with current standard techniques of stress drop estimation.

Regional variations in the diversity and predicted metabolic potential of benthic prokaryotes in coastal northern Zhejiang, East China Sea

PubMed Central

Wang, Kai; Ye, Xiansen; Zhang, Huajun; Chen, Heping; Zhang, Demin; Liu, Lian

2016-01-01

Knowledge about the drivers of benthic prokaryotic diversity and metabolic potential in interconnected coastal sediments at regional scales is limited. We collected surface sediments across six zones covering ~200 km in coastal northern Zhejiang, East China Sea and combined 16 S rRNA gene sequencing, community-level metabolic prediction, and sediment physicochemical measurements to investigate variations in prokaryotic diversity and metabolic gene composition with geographic distance and under local environmental conditions. Geographic distance was the most influential factor in prokaryotic β-diversity compared with major environmental drivers, including temperature, sediment texture, acid-volatile sulfide, and water depth, but a large unexplained variation in community composition suggested the potential effects of unmeasured abiotic/biotic factors and stochastic processes. Moreover, prokaryotic assemblages showed a biogeographic provincialism across the zones. The predicted metabolic gene composition similarly shifted as taxonomic composition did. Acid-volatile sulfide was strongly correlated with variation in metabolic gene composition. The enrichments in the relative abundance of sulfate-reducing bacteria and genes relevant with dissimilatory sulfate reduction were observed and predicted, respectively, in the Yushan area. These results provide insights into the relative importance of geographic distance and environmental condition in driving benthic prokaryotic diversity in coastal areas and predict specific biogeochemically-relevant genes for future studies. PMID:27917954

The time frame of Epstein-Barr virus latent membrane protein-1 gene to disappear in nasopharyngeal swabs after initiation of primary radiotherapy is an independently significant prognostic factor predicting local control for patients with nasopharyngeal carcinoma

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

Lin, S.-Y.; Chang, K.-P.; Graduate Institute of Clinical Medical Sciences, Chang Gung University, Linkou, Taiwan

Purpose: The presence of Epstein-Barr virus latent membrane protein-1 (LMP-1) gene in nasopharyngeal swabs indicates the presence of nasopharyngeal carcinoma (NPC) mucosal tumor cells. This study was undertaken to investigate whether the time taken for LMP-1 to disappear after initiation of primary radiotherapy (RT) was inversely associated with NPC local control. Methods and Materials: During July 1999 and October 2002, there were 127 nondisseminated NPC patients receiving serial examinations of nasopharyngeal swabbing with detection of LMP-1 during the RT course. The time for LMP-1 regression was defined as the number of days after initiation of RT for LMP-1 results tomore » turn negative. The primary outcome was local control, which was represented by freedom from local recurrence. Results: The time for LMP-1 regression showed a statistically significant influence on NPC local control both univariately (p < 0.0001) and multivariately (p = 0.004). In multivariate analysis, the administration of chemotherapy conferred a significantly more favorable local control (p = 0.03). Advanced T status ({>=} T2b), overall treatment time of external photon radiotherapy longer than 55 days, and older age showed trends toward being poor prognosticators. The time for LMP-1 regression was very heterogeneous. According to the quartiles of the time for LMP-1 regression, we defined the pattern of LMP-1 regression as late regression if it required 40 days or more. Kaplan-Meier plots indicated that the patients with late regression had a significantly worse local control than those with intermediate or early regression (p 0.0129). Conclusion: Among the potential prognostic factors examined in this study, the time for LMP-1 regression was the most independently significant factor that was inversely associated with NPC local control.« less

Examining the relationship between local extinction risk and position in range.

PubMed

Boakes, Elizabeth H; Isaac, Nicholas J B; Fuller, Richard A; Mace, Georgina M; McGowan, Philip J K

2018-02-01

Over half of globally threatened animal species have experienced rapid geographic range loss. Identifying the parts of species' distributions most vulnerable to local extinction would benefit conservation planning. However, previous studies give little consensus on whether ranges decline to the core or edge. We built on previous work by using empirical data to examine the position of recent local extinctions within species' geographic ranges, address range position as a continuum, and explore the influence of environmental factors. We aggregated point-locality data for 125 Galliform species from across the Palearctic and Indo-Malaya into equal-area half-degree grid cells and used a multispecies dynamic Bayesian occupancy model to estimate rates of local extinctions. Our model provides a novel approach to identify loss of populations from within species ranges. We investigated the relationship between extinction rates and distance from range edge by examining whether patterns were consistent across biogeographic realm and different categories of land use. In the Palearctic, local extinctions occurred closer to the range edge than range core in both unconverted and human-dominated landscapes. In Indo-Malaya, no pattern was found for unconverted landscapes, but in human-dominated landscapes extinctions tended to occur closer to the core than the edge. Our results suggest that local and regional factors override general spatial patterns of recent local extinction within species' ranges and highlight the difficulty of predicting the parts of a species' distribution most vulnerable to threat. © 2017 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Diffusion in the presence of a local attracting factor: Theory and interdisciplinary applications.

PubMed

Veermäe, Hardi; Patriarca, Marco

2017-06-01

In many complex diffusion processes the drift of random walkers is not caused by an external force, as in the case of Brownian motion, but by local variations of fitness perceived by the random walkers. In this paper, a simple but general framework is presented that describes such a type of random motion and may be of relevance in different problems, such as opinion dynamics, cultural spreading, and animal movement. To this aim, we study the problem of a random walker in d dimensions moving in the presence of a local heterogeneous attracting factor expressed in terms of an assigned position-dependent "attractiveness function." At variance with standard Brownian motion, the attractiveness function introduced here regulates both the advection and diffusion of the random walker, thus providing testable predictions for a specific form of fluctuation-relations. We discuss the relation between the drift-diffusion equation based on the attractiveness function and that describing standard Brownian motion, and we provide some explicit examples illustrating its relevance in different fields, such as animal movement, chemotactic diffusion, and social dynamics.

Protein Sub-Nuclear Localization Based on Effective Fusion Representations and Dimension Reduction Algorithm LDA.

PubMed

Wang, Shunfang; Liu, Shuhui

2015-12-19

An effective representation of a protein sequence plays a crucial role in protein sub-nuclear localization. The existing representations, such as dipeptide composition (DipC), pseudo-amino acid composition (PseAAC) and position specific scoring matrix (PSSM), are insufficient to represent protein sequence due to their single perspectives. Thus, this paper proposes two fusion feature representations of DipPSSM and PseAAPSSM to integrate PSSM with DipC and PseAAC, respectively. When constructing each fusion representation, we introduce the balance factors to value the importance of its components. The optimal values of the balance factors are sought by genetic algorithm. Due to the high dimensionality of the proposed representations, linear discriminant analysis (LDA) is used to find its important low dimensional structure, which is essential for classification and location prediction. The numerical experiments on two public datasets with KNN classifier and cross-validation tests showed that in terms of the common indexes of sensitivity, specificity, accuracy and MCC, the proposed fusing representations outperform the traditional representations in protein sub-nuclear localization, and the representation treated by LDA outperforms the untreated one.

Diffusion in the presence of a local attracting factor: Theory and interdisciplinary applications

NASA Astrophysics Data System (ADS)

Veermäe, Hardi; Patriarca, Marco

2017-06-01

In many complex diffusion processes the drift of random walkers is not caused by an external force, as in the case of Brownian motion, but by local variations of fitness perceived by the random walkers. In this paper, a simple but general framework is presented that describes such a type of random motion and may be of relevance in different problems, such as opinion dynamics, cultural spreading, and animal movement. To this aim, we study the problem of a random walker in d dimensions moving in the presence of a local heterogeneous attracting factor expressed in terms of an assigned position-dependent "attractiveness function." At variance with standard Brownian motion, the attractiveness function introduced here regulates both the advection and diffusion of the random walker, thus providing testable predictions for a specific form of fluctuation-relations. We discuss the relation between the drift-diffusion equation based on the attractiveness function and that describing standard Brownian motion, and we provide some explicit examples illustrating its relevance in different fields, such as animal movement, chemotactic diffusion, and social dynamics.

Protein Sub-Nuclear Localization Based on Effective Fusion Representations and Dimension Reduction Algorithm LDA

PubMed Central

Wang, Shunfang; Liu, Shuhui

2015-01-01

An effective representation of a protein sequence plays a crucial role in protein sub-nuclear localization. The existing representations, such as dipeptide composition (DipC), pseudo-amino acid composition (PseAAC) and position specific scoring matrix (PSSM), are insufficient to represent protein sequence due to their single perspectives. Thus, this paper proposes two fusion feature representations of DipPSSM and PseAAPSSM to integrate PSSM with DipC and PseAAC, respectively. When constructing each fusion representation, we introduce the balance factors to value the importance of its components. The optimal values of the balance factors are sought by genetic algorithm. Due to the high dimensionality of the proposed representations, linear discriminant analysis (LDA) is used to find its important low dimensional structure, which is essential for classification and location prediction. The numerical experiments on two public datasets with KNN classifier and cross-validation tests showed that in terms of the common indexes of sensitivity, specificity, accuracy and MCC, the proposed fusing representations outperform the traditional representations in protein sub-nuclear localization, and the representation treated by LDA outperforms the untreated one. PMID:26703574

Evaluation of quantitative precipitation forecasts by TIGGE ensembles for south China during the presummer rainy season

NASA Astrophysics Data System (ADS)

Huang, Ling; Luo, Yali

2017-08-01

Based on The Observing System Research and Predictability Experiment Interactive Grand Global Ensemble (TIGGE) data set, this study evaluates the ability of global ensemble prediction systems (EPSs) from the European Centre for Medium-Range Weather Forecasts (ECMWF), U.S. National Centers for Environmental Prediction, Japan Meteorological Agency (JMA), Korean Meteorological Administration, and China Meteorological Administration (CMA) to predict presummer rainy season (April-June) precipitation in south China. Evaluation of 5 day forecasts in three seasons (2013-2015) demonstrates the higher skill of probability matching forecasts compared to simple ensemble mean forecasts and shows that the deterministic forecast is a close second. The EPSs overestimate light-to-heavy rainfall (0.1 to 30 mm/12 h) and underestimate heavier rainfall (>30 mm/12 h), with JMA being the worst. By analyzing the synoptic situations predicted by the identified more skillful (ECMWF) and less skillful (JMA and CMA) EPSs and the ensemble sensitivity for four representative cases of torrential rainfall, the transport of warm-moist air into south China by the low-level southwesterly flow, upstream of the torrential rainfall regions, is found to be a key synoptic factor that controls the quantitative precipitation forecast. The results also suggest that prediction of locally produced torrential rainfall is more challenging than prediction of more extensively distributed torrential rainfall. A slight improvement in the performance is obtained by shortening the forecast lead time from 30-36 h to 18-24 h to 6-12 h for the cases with large-scale forcing, but not for the locally produced cases.

Readmission prediction via deep contextual embedding of clinical concepts.

PubMed

Xiao, Cao; Ma, Tengfei; Dieng, Adji B; Blei, David M; Wang, Fei

2018-01-01

Hospital readmission costs a lot of money every year. Many hospital readmissions are avoidable, and excessive hospital readmissions could also be harmful to the patients. Accurate prediction of hospital readmission can effectively help reduce the readmission risk. However, the complex relationship between readmission and potential risk factors makes readmission prediction a difficult task. The main goal of this paper is to explore deep learning models to distill such complex relationships and make accurate predictions. We propose CONTENT, a deep model that predicts hospital readmissions via learning interpretable patient representations by capturing both local and global contexts from patient Electronic Health Records (EHR) through a hybrid Topic Recurrent Neural Network (TopicRNN) model. The experiment was conducted using the EHR of a real world Congestive Heart Failure (CHF) cohort of 5,393 patients. The proposed model outperforms state-of-the-art methods in readmission prediction (e.g. 0.6103 ± 0.0130 vs. second best 0.5998 ± 0.0124 in terms of ROC-AUC). The derived patient representations were further utilized for patient phenotyping. The learned phenotypes provide more precise understanding of readmission risks. Embedding both local and global context in patient representation not only improves prediction performance, but also brings interpretable insights of understanding readmission risks for heterogeneous chronic clinical conditions. This is the first of its kind model that integrates the power of both conventional deep neural network and the probabilistic generative models for highly interpretable deep patient representation learning. Experimental results and case studies demonstrate the improved performance and interpretability of the model.

Local house prices and mental health.

PubMed

Joshi, Nayan Krishna

2016-03-01

This paper examines the impact of local (county-level) house prices on individual self-reported mental health using individual level data from the United States Behavioral Risk Factor Surveillance System between 2005 and 2011. Exploiting a fixed-effects model that relies on within-county variations, relative to the corresponding changes in other counties, I find that while individuals are likely to experience worse self-reported mental health when local house prices decline, this association is most pronounced for individuals who are least likely to be homeowners. This finding is not consistent with a prediction from a pure wealth mechanism but rather with the hypothesis that house prices act as an economic barometer. I also demonstrate that the association between self-reported mental health and local house prices is not driven by unemployment or foreclosure. The primary result-that lower local house prices have adverse impact on self-reported mental health of homeowners and renters-is consistent with studies using data from the United Kingdom.

Prognostic Significance of Carbohydrate Antigen 19-9 in Unresectable Locally Advanced Pancreatic Cancer Treated With Dose-Escalated Intensity Modulated Radiation Therapy and Concurrent Full-Dose Gemcitabine: Analysis of a Prospective Phase 1/2 Dose Escalation Study

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

Vainshtein, Jeffrey M., E-mail: jvainsh@med.umich.edu; Schipper, Matthew; Zalupski, Mark M.

2013-05-01

Purpose: Although established in the postresection setting, the prognostic value of carbohydrate antigen 19-9 (CA19-9) in unresectable locally advanced pancreatic cancer (LAPC) is less clear. We examined the prognostic utility of CA19-9 in patients with unresectable LAPC treated on a prospective trial of intensity modulated radiation therapy (IMRT) dose escalation with concurrent gemcitabine. Methods and Materials: Forty-six patients with unresectable LAPC were treated at the University of Michigan on a phase 1/2 trial of IMRT dose escalation with concurrent gemcitabine. CA19-9 was obtained at baseline and during routine follow-up. Cox models were used to assess the effect of baseline factorsmore » on freedom from local progression (FFLP), distant progression (FFDP), progression-free survival (PFS), and overall survival (OS). Stepwise forward regression was used to build multivariate predictive models for each endpoint. Results: Thirty-eight patients were eligible for the present analysis. On univariate analysis, baseline CA19-9 and age predicted OS, CA19-9 at baseline and 3 months predicted PFS, gross tumor volume (GTV) and black race predicted FFLP, and CA19-9 at 3 months predicted FFDP. On stepwise multivariate regression modeling, baseline CA19-9, age, and female sex predicted OS; baseline CA19-9 and female sex predicted both PFS and FFDP; and GTV predicted FFLP. Patients with baseline CA19-9 ≤90 U/mL had improved OS (median 23.0 vs 11.1 months, HR 2.88, P<.01) and PFS (14.4 vs 7.0 months, HR 3.61, P=.001). CA19-9 progression over 90 U/mL was prognostic for both OS (HR 3.65, P=.001) and PFS (HR 3.04, P=.001), and it was a stronger predictor of death than either local progression (HR 1.46, P=.42) or distant progression (HR 3.31, P=.004). Conclusions: In patients with unresectable LAPC undergoing definitive chemoradiation therapy, baseline CA19-9 was independently prognostic even after established prognostic factors were controlled for, whereas CA19-9 progression strongly predicted disease progression and death. Future trials should stratify by baseline CA19-9 and incorporate CA19-9 progression as a criterion for progressive disease.« less

Habitat availability and gene flow influence diverging local population trajectories under scenarios of climate change: a place-based approach.

PubMed

Schwalm, Donelle; Epps, Clinton W; Rodhouse, Thomas J; Monahan, William B; Castillo, Jessica A; Ray, Chris; Jeffress, Mackenzie R

2016-04-01

Ecological niche theory holds that species distributions are shaped by a large and complex suite of interacting factors. Species distribution models (SDMs) are increasingly used to describe species' niches and predict the effects of future environmental change, including climate change. Currently, SDMs often fail to capture the complexity of species' niches, resulting in predictions that are generally limited to climate-occupancy interactions. Here, we explore the potential impact of climate change on the American pika using a replicated place-based approach that incorporates climate, gene flow, habitat configuration, and microhabitat complexity into SDMs. Using contemporary presence-absence data from occupancy surveys, genetic data to infer connectivity between habitat patches, and 21 environmental niche variables, we built separate SDMs for pika populations inhabiting eight US National Park Service units representing the habitat and climatic breadth of the species across the western United States. We then predicted occurrence probability under current (1981-2010) and three future time periods (out to 2100). Occurrence probabilities and the relative importance of predictor variables varied widely among study areas, revealing important local-scale differences in the realized niche of the American pika. This variation resulted in diverse and - in some cases - highly divergent future potential occupancy patterns for pikas, ranging from complete extirpation in some study areas to stable occupancy patterns in others. Habitat composition and connectivity, which are rarely incorporated in SDM projections, were influential in predicting pika occupancy in all study areas and frequently outranked climate variables. Our findings illustrate the importance of a place-based approach to species distribution modeling that includes fine-scale factors when assessing current and future climate impacts on species' distributions, especially when predictions are intended to manage and conserve species of concern within individual protected areas. © 2015 John Wiley & Sons Ltd.

Prediction of forest fires occurrences with area-level Poisson mixed models.

PubMed

Boubeta, Miguel; Lombardía, María José; Marey-Pérez, Manuel Francisco; Morales, Domingo

2015-05-01

The number of fires in forest areas of Galicia (north-west of Spain) during the summer period is quite high. Local authorities are interested in analyzing the factors that explain this phenomenon. Poisson regression models are good tools for describing and predicting the number of fires per forest areas. This work employs area-level Poisson mixed models for treating real data about fires in forest areas. A parametric bootstrap method is applied for estimating the mean squared errors of fires predictors. The developed methodology and software are applied to a real data set of fires in forest areas of Galicia. Copyright © 2015 Elsevier Ltd. All rights reserved.

Factors Predictive of Sentinel Lymph Node Involvement in Primary Breast Cancer.

PubMed

Malter, Wolfram; Hellmich, Martin; Badian, Mayhar; Kirn, Verena; Mallmann, Peter; Krämer, Stefan

2018-06-01

Sentinel lymph node biopsy (SLNB) has replaced axillary lymph node dissection (ALND) for axillary staging in patients with early-stage breast cancer. The need for therapeutic ALND is the subject of ongoing debate especially after the publication of the ACOSOG Z0011 trial. In a retrospective trial with univariate and multivariate analyses, factors predictive of sentinel lymph node involvement should be analyzed in order to define tumor characteristics of breast cancer patients, where SLNB should not be spared to receive important indicators for adjuvant treatment decisions (e.g. thoracic wall irradiation after mastectomy with or without reconstruction). Between 2006 and 2010, 1,360 patients with primary breast cancer underwent SLNB with/without ALND with evaluation of tumor localization, multicentricity and multifocality, histological subtype, tumor size, grading, lymphovascular invasion (LVI), and estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status. These characteristics were retrospectively analyzed in univariate and multivariate logistic regression models to define significant predictive factors for sentinel lymph node involvement. The multivariate analysis demonstrated that tumor size and LVI (p<0.001) were independent predictive factors for metastatic sentinel lymph node involvement in patients with early-stage breast cancer. Because of the increased risk for metastatic involvement of axillary sentinel nodes in cases with larger breast cancer or diagnosis of LVI, patients with these breast cancer characteristics should not be spared from SLNB in a clinically node-negative situation in order to avoid false-negative results with a high potential for wrong indication of primary breast reconstruction or wrong non-indication of necessary post-mastectomy radiation therapy. The prognostic impact of avoidance of axillary staging with SLNB is analyzed in the ongoing prospective INSEMA trial. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

A comparison between index of entropy and catastrophe theory methods for mapping groundwater potential in an arid region.

PubMed

Al-Abadi, Alaa M; Shahid, Shamsuddin

2015-09-01

In this study, index of entropy and catastrophe theory methods were used for demarcating groundwater potential in an arid region using weighted linear combination techniques in geographical information system (GIS) environment. A case study from Badra area in the eastern part of central of Iraq was analyzed and discussed. Six factors believed to have influence on groundwater occurrence namely elevation, slope, aquifer transmissivity and storativity, soil, and distance to fault were prepared as raster thematic layers to facility integration into GIS environment. The factors were chosen based on the availability of data and local conditions of the study area. Both techniques were used for computing weights and assigning ranks vital for applying weighted linear combination approach. The results of application of both modes indicated that the most influential groundwater occurrence factors were slope and elevation. The other factors have relatively smaller values of weights implying that these factors have a minor role in groundwater occurrence conditions. The groundwater potential index (GPI) values for both models were classified using natural break classification scheme into five categories: very low, low, moderate, high, and very high. For validation of generated GPI, the relative operating characteristic (ROC) curves were used. According to the obtained area under the curve, the catastrophe model with 78 % prediction accuracy was found to perform better than entropy model with 77 % prediction accuracy. The overall results indicated that both models have good capability for predicting groundwater potential zones.

GP workforce participation in Tasmania.

PubMed

Gartlan, Jan; Male, Sarah; Donaldson, Lawrence; Nelson, Mark; Winzenberg, Tania

2007-05-01

Predicting future general practitioner workforce requires information about how demographic factors affect GP workforce participation. Regional differences might not be accounted for in national studies. The authors aimed to determine GP characteristics associated with workforce participation in Tasmania. A self administered census of Tasmanian GPs measured GP demographics and the number of 3.5 hour sessions worked in 1 week in 2005. Four hundred and three GPs responded (76% response rate). Six percent of GPs were on leave at the time of the census. Age, gender and graduation outside of Australia, the United Kingdom or Ireland were associated with workforce participation, but rurality had no effect. The effect of age was modified by gender with women aged over 55 years being more likely to work full time (p=0.03). Factors affecting workforce participation may vary across regions. Predictions based on national models may need to be interpreted in the context of local circumstances.

Accurate Computation of Electric Field Enhancement Factors for Metallic Nanoparticles Using the Discrete Dipole Approximation

PubMed Central

2010-01-01

We model the response of nanoscale Ag prolate spheroids to an external uniform static electric field using simulations based on the discrete dipole approximation, in which the spheroid is represented as a collection of polarizable subunits. We compare the results of simulations that employ subunit polarizabilities derived from the Clausius–Mossotti relation with those of simulations that employ polarizabilities that include a local environmental correction for subunits near the spheroid’s surface [Rahmani et al. Opt Lett 27: 2118 (2002)]. The simulations that employ corrected polarizabilities give predictions in very good agreement with exact results obtained by solving Laplace’s equation. In contrast, simulations that employ uncorrected Clausius–Mossotti polarizabilities substantially underestimate the extent of the electric field “hot spot” near the spheroid’s sharp tip, and give predictions for the field enhancement factor near the tip that are 30 to 50% too small. PMID:20672062

PubMed Central

Taran, Florin-Andrei; Schneeweiss, Andreas; Lux, Michael P.; Janni, Wolfgang; Hartkopf, Andreas D.; Nabieva, Naiba; Overkamp, Friedrich; Kolberg, Hans-Christian; Hadji, Peyman; Tesch, Hans; Wöckel, Achim; Ettl, Johannes; Lüftner, Diana; Wallwiener, Markus; Müller, Volkmar; Beckmann, Matthias W.; Belleville, Erik; Wallwiener, Diethelm; Brucker, Sara Y.; Fasching, Peter A.; Fehm, Tanja N.; Schütz, Florian

2018-01-01

This summary provides an overview of how new therapies or new aspects of established therapies relate to the latest findings. Neoadjuvant therapy, local therapy, new aspects of systemic therapy, and prognostic and predictive factors are presented. In the neoadjuvant setting, the association between pathological complete response (pCR) and prognosis is still of interest as is the identification of new molecular predictors for new therapies such as CDK4/6 inhibitors. As regards surgical treatment, the target is still to reduce the aggressiveness of surgery. To achieve this, a better understanding particularly of ductal carcinoma in situ is required. With regard to systemic therapy, more data on the best combinations and therapy sequences for existing therapies is available. Finally, the use of prognostic and predictive factors may help to avoid overtreatment and ensure that patients only receive therapies which have been shown to be effective for their specific condition and have fewer side effects. PMID:29576629

Predictive factors in the evaluation of treatment response to neoadjuvant chemoradiotherapy in patients with advanced esophageal squamous cell cancer

PubMed Central

Wong, Claudia

2017-01-01

Neoadjuvant therapy before esophagectomy is evidence-based, and is a standard-of-care for locally advanced and operable esophageal cancer. However response to such treatment varies in individual patients, from no clinical response to pathological complete response. It has been consistently shown that a good pathological responses is of prognostic value, but perhaps in the expense of those who do not. It is important to identify suitable predictive factors for response, so that patients are not exposed to potentially harmful chemotherapy and/or radiotherapy without benefits. Alternative management strategies can be devised. Various clinical, radiological, serological and potential molecular markers have been studied. None has been shown to be sufficiently reliable to be used in daily practice. Certainly more understanding of the molecular basis for response to chemotherapy/radiotherapy is needed, so that patient treatment can be tailored and individualized. PMID:28815073

MRI evaluation following partial HIFU therapy for localized prostate cancer: A single-center study.

PubMed

Hoquetis, L; Malavaud, B; Game, X; Beauval, J B; Portalez, D; Soulie, M; Rischmann, P

2016-09-01

To evaluate the value of MRI for surveillance of primary hemi-HIFU therapy for localized PCa in a single-center. Patients with localized prostate cancer were treated with hemi-HIFU from October 2009 to March 2014. All patients performed MRI before focal therapy, the reader was blinded to the treatment. Oncological failure was defined as positive biopsy or biochemical recurrence (Phoenix). Twenty-five patients were treated with hemi-HIFU in one center. The median nadir PSA was 1.45±1.4ng/mL. Prostate volume decreased from 45 cc to 25 cc on MRI findings. At 20 months, none of the patients had histological recurrence. Biochemical-free survival rate was 88%. MRI evaluation had a negative predictive value of 100% on the treated area and 81% on the untreated area. PSAd≥0.1ng/mL(2) was a predictive factor for cancer on untreated area (P=0.042). MRI control at 6 months is a potentially effective evaluation of treated area after hemi-HIFU and may replace randomized biopsies if PSAd<0.1ng/mL(2) during follow-up. 4. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Predicting Local Dengue Transmission in Guangzhou, China, through the Influence of Imported Cases, Mosquito Density and Climate Variability

PubMed Central

Sang, Shaowei; Yin, Wenwu; Bi, Peng; Zhang, Honglong; Wang, Chenggang; Liu, Xiaobo; Chen, Bin; Yang, Weizhong; Liu, Qiyong

2014-01-01

Introduction Each year there are approximately 390 million dengue infections worldwide. Weather variables have a significant impact on the transmission of Dengue Fever (DF), a mosquito borne viral disease. DF in mainland China is characterized as an imported disease. Hence it is necessary to explore the roles of imported cases, mosquito density and climate variability in dengue transmission in China. The study was to identify the relationship between dengue occurrence and possible risk factors and to develop a predicting model for dengue’s control and prevention purpose. Methodology and Principal Findings Three traditional suburbs and one district with an international airport in Guangzhou city were selected as the study areas. Autocorrelation and cross-correlation analysis were used to perform univariate analysis to identify possible risk factors, with relevant lagged effects, associated with local dengue cases. Principal component analysis (PCA) was applied to extract principal components and PCA score was used to represent the original variables to reduce multi-collinearity. Combining the univariate analysis and prior knowledge, time-series Poisson regression analysis was conducted to quantify the relationship between weather variables, Breteau Index, imported DF cases and the local dengue transmission in Guangzhou, China. The goodness-of-fit of the constructed model was determined by pseudo-R2, Akaike information criterion (AIC) and residual test. There were a total of 707 notified local DF cases from March 2006 to December 2012, with a seasonal distribution from August to November. There were a total of 65 notified imported DF cases from 20 countries, with forty-six cases (70.8%) imported from Southeast Asia. The model showed that local DF cases were positively associated with mosquito density, imported cases, temperature, precipitation, vapour pressure and minimum relative humidity, whilst being negatively associated with air pressure, with different time lags. Conclusions Imported DF cases and mosquito density play a critical role in local DF transmission, together with weather variables. The establishment of an early warning system, using existing surveillance datasets will help to control and prevent dengue in Guangzhou, China. PMID:25019967

Predicting local dengue transmission in Guangzhou, China, through the influence of imported cases, mosquito density and climate variability.

PubMed

Sang, Shaowei; Yin, Wenwu; Bi, Peng; Zhang, Honglong; Wang, Chenggang; Liu, Xiaobo; Chen, Bin; Yang, Weizhong; Liu, Qiyong

2014-01-01

Each year there are approximately 390 million dengue infections worldwide. Weather variables have a significant impact on the transmission of Dengue Fever (DF), a mosquito borne viral disease. DF in mainland China is characterized as an imported disease. Hence it is necessary to explore the roles of imported cases, mosquito density and climate variability in dengue transmission in China. The study was to identify the relationship between dengue occurrence and possible risk factors and to develop a predicting model for dengue's control and prevention purpose. Three traditional suburbs and one district with an international airport in Guangzhou city were selected as the study areas. Autocorrelation and cross-correlation analysis were used to perform univariate analysis to identify possible risk factors, with relevant lagged effects, associated with local dengue cases. Principal component analysis (PCA) was applied to extract principal components and PCA score was used to represent the original variables to reduce multi-collinearity. Combining the univariate analysis and prior knowledge, time-series Poisson regression analysis was conducted to quantify the relationship between weather variables, Breteau Index, imported DF cases and the local dengue transmission in Guangzhou, China. The goodness-of-fit of the constructed model was determined by pseudo-R2, Akaike information criterion (AIC) and residual test. There were a total of 707 notified local DF cases from March 2006 to December 2012, with a seasonal distribution from August to November. There were a total of 65 notified imported DF cases from 20 countries, with forty-six cases (70.8%) imported from Southeast Asia. The model showed that local DF cases were positively associated with mosquito density, imported cases, temperature, precipitation, vapour pressure and minimum relative humidity, whilst being negatively associated with air pressure, with different time lags. Imported DF cases and mosquito density play a critical role in local DF transmission, together with weather variables. The establishment of an early warning system, using existing surveillance datasets will help to control and prevent dengue in Guangzhou, China.

Social Ecology of Child Soldiers: Child, Family, and Community Determinants of Mental Health, Psychosocial Wellbeing, and Reintegration in Nepal

PubMed Central

Kohrt, Brandon A.; Jordans, Mark J.D.; Tol, Wietse A.; Perera, Em; Karki, Rohit; Koirala, Suraj; Upadhaya, Nawaraj

2013-01-01

This study employs social ecology to evaluate psychosocial wellbeing in a cross-sectional sample of 142 former child soldiers in Nepal. Outcome measures included the Depression Self Rating Scale (DSRS), Child Posttraumatic Stress Scale (CPSS), and locally developed measures of function impairment and reintegration. At the child level, traumatic exposures, especially torture, predicted poor outcomes, while education improved outcomes. At the family level, conflict-related death of a relative, physical abuse in the household, and loss of wealth during the conflict predicted poor outcomes. At the community level, living in high caste Hindu communities predicted fewer reintegration supports. Ultimately, social ecology is well-suited to identify intervention foci across ecological levels, based on community differences in vulnerability and protective factors. PMID:21088102

Empirical Model for Evaluating PM10 Concentration Caused by River Dust Episodes

PubMed Central

Lin, Chao-Yuan; Chiang, Mon-Ling; Lin, Cheng-Yu

2016-01-01

Around the estuary of the Zhuo-Shui River in Taiwan, the waters recede during the winter, causing an increase in bare land area and exposing a large amount of fine earth and sand particles that were deposited on the riverbed. Observations at the site revealed that when northeastern monsoons blow over bare land without vegetation or water cover, the fine particles are readily lifted by the wind, forming river dust, which greatly endangers the health of nearby residents. Therefore, determining which factors affect river dust and constructing a model to predict river dust concentration are extremely important in the research and development of a prototype warning system for areas at risk of river dust emissions. In this study, the region around the estuary of the Zhuo-Shui River (from the Zi-Qiang Bridge to the Xi-Bin Bridge) was selected as the research area. Data from a nearby air quality monitoring station were used to screen for days with river dust episodes. The relationships between PM10 concentration and meteorological factors or bare land area were analyzed at different temporal scales to explore the factors that affect river dust emissions. Study results showed that no single factor alone had adequate power to explain daily average or daily maximum PM10 concentration. Stepwise regression analysis of multiple factors showed that the model could not effectively predict daily average PM10 concentration, but daily maximum PM10 concentration could be predicted by a combination of wind velocity, temperature, and bare land area; the coefficient of determination for this model was 0.67. It was inferred that river dust episodes are caused by the combined effect of multiple factors. In addition, research data also showed a time lag effect between meteorological factors and hourly PM10 concentration. This characteristic was applied to the construction of a prediction model, and can be used in an early warning system for local residents. PMID:27271642

Empirical Model for Evaluating PM10 Concentration Caused by River Dust Episodes.

PubMed

Lin, Chao-Yuan; Chiang, Mon-Ling; Lin, Cheng-Yu

2016-06-02

Around the estuary of the Zhuo-Shui River in Taiwan, the waters recede during the winter, causing an increase in bare land area and exposing a large amount of fine earth and sand particles that were deposited on the riverbed. Observations at the site revealed that when northeastern monsoons blow over bare land without vegetation or water cover, the fine particles are readily lifted by the wind, forming river dust, which greatly endangers the health of nearby residents. Therefore, determining which factors affect river dust and constructing a model to predict river dust concentration are extremely important in the research and development of a prototype warning system for areas at risk of river dust emissions. In this study, the region around the estuary of the Zhuo-Shui River (from the Zi-Qiang Bridge to the Xi-Bin Bridge) was selected as the research area. Data from a nearby air quality monitoring station were used to screen for days with river dust episodes. The relationships between PM10 concentration and meteorological factors or bare land area were analyzed at different temporal scales to explore the factors that affect river dust emissions. Study results showed that no single factor alone had adequate power to explain daily average or daily maximum PM10 concentration. Stepwise regression analysis of multiple factors showed that the model could not effectively predict daily average PM10 concentration, but daily maximum PM10 concentration could be predicted by a combination of wind velocity, temperature, and bare land area; the coefficient of determination for this model was 0.67. It was inferred that river dust episodes are caused by the combined effect of multiple factors. In addition, research data also showed a time lag effect between meteorological factors and hourly PM10 concentration. This characteristic was applied to the construction of a prediction model, and can be used in an early warning system for local residents.

Primary assembly of soil communities: disentangling the effect of dispersal and local environment.

PubMed

Ingimarsdóttir, María; Caruso, Tancredi; Ripa, Jörgen; Magnúsdóttir, Olöf Birna; Migliorini, Massimo; Hedlund, Katarina

2012-11-01

It has long been recognised that dispersal abilities and environmental factors are important in shaping invertebrate communities, but their relative importance for primary soil community assembly has not yet been disentangled. By studying soil communities along chronosequences on four recently emerged nunataks (ice-free land in glacial areas) in Iceland, we replicated environmental conditions spatially at various geographical distances. This allowed us to determine the underlying factors of primary community assembly with the help of metacommunity theories that predict different levels of dispersal constraints and effects of the local environment. Comparing community assembly of the nunataks with that of non-isolated deglaciated areas indicated that isolation of a few kilometres did not affect the colonisation of the soil invertebrates. When accounting for effects of geographical distances, soil age and plant richness explained a significant part of the variance observed in the distribution of the oribatid mites and collembola communities, respectively. Furthermore, null model analyses revealed less co-occurrence than expected by chance and also convergence in the body size ratio of co-occurring oribatids, which is consistent with species sorting. Geographical distances influenced species composition, indicating that the community is also assembled by dispersal, e.g. mass effect. When all the results are linked together, they demonstrate that local environmental factors are important in structuring the soil community assembly, but are accompanied with effects of dispersal that may "override" the visible effect of the local environment.

Non-Gaussian bias: insights from discrete density peaks

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

Desjacques, Vincent; Riotto, Antonio; Gong, Jinn-Ouk, E-mail: Vincent.Desjacques@unige.ch, E-mail: jinn-ouk.gong@apctp.org, E-mail: Antonio.Riotto@unige.ch

2013-09-01

Corrections induced by primordial non-Gaussianity to the linear halo bias can be computed from a peak-background split or the widespread local bias model. However, numerical simulations clearly support the prediction of the former, in which the non-Gaussian amplitude is proportional to the linear halo bias. To understand better the reasons behind the failure of standard Lagrangian local bias, in which the halo overdensity is a function of the local mass overdensity only, we explore the effect of a primordial bispectrum on the 2-point correlation of discrete density peaks. We show that the effective local bias expansion to peak clustering vastlymore » simplifies the calculation. We generalize this approach to excursion set peaks and demonstrate that the resulting non-Gaussian amplitude, which is a weighted sum of quadratic bias factors, precisely agrees with the peak-background split expectation, which is a logarithmic derivative of the halo mass function with respect to the normalisation amplitude. We point out that statistics of thresholded regions can be computed using the same formalism. Our results suggest that halo clustering statistics can be modelled consistently (in the sense that the Gaussian and non-Gaussian bias factors agree with peak-background split expectations) from a Lagrangian bias relation only if the latter is specified as a set of constraints imposed on the linear density field. This is clearly not the case of standard Lagrangian local bias. Therefore, one is led to consider additional variables beyond the local mass overdensity.« less

Addressing potential local adaptation in species distribution models: implications for conservation under climate change

USGS Publications Warehouse

Hällfors, Maria Helena; Liao, Jishan; Dzurisin, Jason D. K.; Grundel, Ralph; Hyvärinen, Marko; Towle, Kevin; Wu, Grace C.; Hellmann, Jessica J.

2016-01-01

Species distribution models (SDMs) have been criticized for involving assumptions that ignore or categorize many ecologically relevant factors such as dispersal ability and biotic interactions. Another potential source of model error is the assumption that species are ecologically uniform in their climatic tolerances across their range. Typically, SDMs to treat a species as a single entity, although populations of many species differ due to local adaptation or other genetic differentiation. Not taking local adaptation into account, may lead to incorrect range prediction and therefore misplaced conservation efforts. A constraint is that we often do not know the degree to which populations are locally adapted, however. Lacking experimental evidence, we still can evaluate niche differentiation within a species' range to promote better conservation decisions. We explore possible conservation implications of making type I or type II errors in this context. For each of two species, we construct three separate MaxEnt models, one considering the species as a single population and two of disjunct populations. PCA analyses and response curves indicate different climate characteristics in the current environments of the populations. Model projections into future climates indicate minimal overlap between areas predicted to be climatically suitable by the whole species versus population-based models. We present a workflow for addressing uncertainty surrounding local adaptation in SDM application and illustrate the value of conducting population-based models to compare with whole-species models. These comparisons might result in more cautious management actions when alternative range outcomes are considered.

Beyond the standard two-film theory: Computational fluid dynamics simulations for carbon dioxide capture in a wetted wall column

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

Wang, Chao; Xu, Zhijie; Lai, Canhai

The standard two-film theory (STFT) is a diffusion-based mechanism that can be used to describe gas mass transfer across liquid film. Fundamental assumptions of the STFT impose serious limitations on its ability to predict mass transfer coefficients. To better understand gas absorption across liquid film in practical situations, a multiphase computational fluid dynamics (CFD) model fully equipped with mass transport and chemistry capabilities has been developed for solvent-based carbon dioxide (CO 2) capture to predict the CO 2 mass transfer coefficient in a wetted wall column. The hydrodynamics is modeled using a volume of fluid method, and the diffusive andmore » reactive mass transfer between the two phases is modeled by adopting a one-fluid formulation. We demonstrate that the proposed CFD model can naturally account for the influence of many important factors on the overall mass transfer that cannot be quantitatively explained by the STFT, such as the local variation in fluid velocities and properties, flow instabilities, and complex geometries. The CFD model also can predict the local mass transfer coefficient variation along the column height, which the STFT typically does not consider.« less

Beyond the standard two-film theory: Computational fluid dynamics simulations for carbon dioxide capture in a wetted wall column

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

Wang, Chao; Xu, Zhijie; Lai, Canhai

The standard two-film theory (STFT) is a diffusion-based mechanism that can be used to describe gas mass transfer across liquid film. Fundamental assumptions of the STFT impose serious limitations on its ability to predict mass transfer coefficients. To better understand gas absorption across liquid film in practical situations, a multiphase computational fluid dynamics (CFD) model fully equipped with mass transport and chemistry capabilities has been developed for solvent-based carbon dioxide (CO2) capture to predict the CO2 mass transfer coefficient in a wetted wall column. The hydrodynamics is modeled using a volume of fluid method, and the diffusive and reactive massmore » transfer between the two phases is modeled by adopting a one-fluid formulation. We demonstrate that the proposed CFD model can naturally account for the influence of many important factors on the overall mass transfer that cannot be quantitatively explained by the STFT, such as the local variation in fluid velocities and properties, flow instabilities, and complex geometries. The CFD model also can predict the local mass transfer coefficient variation along the column height, which the STFT typically does not consider.« less

Beyond the standard two-film theory: Computational fluid dynamics simulations for carbon dioxide capture in a wetted wall column

DOE PAGES

Wang, Chao; Xu, Zhijie; Lai, Canhai; ...

2018-03-27

The standard two-film theory (STFT) is a diffusion-based mechanism that can be used to describe gas mass transfer across liquid film. Fundamental assumptions of the STFT impose serious limitations on its ability to predict mass transfer coefficients. To better understand gas absorption across liquid film in practical situations, a multiphase computational fluid dynamics (CFD) model fully equipped with mass transport and chemistry capabilities has been developed for solvent-based carbon dioxide (CO 2) capture to predict the CO 2 mass transfer coefficient in a wetted wall column. The hydrodynamics is modeled using a volume of fluid method, and the diffusive andmore » reactive mass transfer between the two phases is modeled by adopting a one-fluid formulation. We demonstrate that the proposed CFD model can naturally account for the influence of many important factors on the overall mass transfer that cannot be quantitatively explained by the STFT, such as the local variation in fluid velocities and properties, flow instabilities, and complex geometries. The CFD model also can predict the local mass transfer coefficient variation along the column height, which the STFT typically does not consider.« less

The parsec-scale relationship between ICO and AV in local molecular clouds

NASA Astrophysics Data System (ADS)

Lee, Cheoljong; Leroy, Adam K.; Bolatto, Alberto D.; Glover, Simon C. O.; Indebetouw, Remy; Sandstrom, Karin; Schruba, Andreas

2018-03-01

We measure the parsec-scale relationship between integrated CO intensity (ICO) and visual extinction (AV) in 24 local molecular clouds using maps of CO emission and dust optical depth from Planck. This relationship informs our understanding of CO emission across environments, but clean Milky Way measurements remain scarce. We find uniform ICO for a given AV, with the results bracketed by previous studies of the Pipe and Perseus clouds. Our measured ICO-AV relation broadly agrees with the standard Galactic CO-to-H2 conversion factor, the relation found for the Magellanic clouds at coarser resolution, and numerical simulations by Glover & Clark (2016). This supports the idea that CO emission primarily depends on shielding, which protects molecules from dissociating radiation. Evidence for CO saturation at high AV and a threshold for CO emission at low AV varies remains uncertain due to insufficient resolution and ambiguities in background subtraction. Resolution of order 0.1 pc may be required to measure these features. We use this ICO-AV relation to predict how the CO-to-H2 conversion factor (XCO) would change if the Solar Neighbourhood clouds had different dust-to-gas ratio (metallicity). The calculations highlight the need for improved observations of the CO emission threshold and H I shielding layer depth. They are also sensitive to the shape of the column density distribution. Because local clouds collectively show a self-similar distribution, we predict a shallow metallicity dependence for XCO down to a few tenths of solar metallicity. However, our calculations also imply dramatic variations in cloud-to-cloud XCO at subsolar metallicity.

Transarterial chemoembolization for early stage hepatocellular carcinoma decrease local tumor control and overall survival compared to radiofrequency ablation

PubMed Central

Hocquelet, Arnaud; Seror, Olivier; Blanc, Jean-Frédéric; Frulio, Nora; Salut, Cécile; Nault, Jean-Charles; Hervé Trillaud

2017-01-01

Background & Aims To compare treatment failure and survival associated with ultrasound-guided radiofrequency ablation (RFA) and trans-arterial chemoembolization (TACE) for early-stage HCC in Child-Pugh A cirrhosis patients. Methods 122 cirrhotic patients (RFA: 61; TACE: 61) were well matched according to cirrhosis severity; tumor size and serum alpha-fetoprotein. TACE was performed in case of inconspicuous nodule on US or nodule with “at risk location”. Treatment failure was defined as local tumor progression (LTP) and primary treatment failure (failing to obtain complete response after two treatment session). Treatment failure and overall survival (OS) were compared after coarsened exact matching. Cox proportional model to assess independent predictive factors was performed. Results No significant difference was seen for baseline characteristics between the two groups. Mean tumor size was 3cm in both group with 41% HCC>3cm. Treatment failure rates after TACE was 42.6% (14 primary treatment failures and 12 LTP) and 9.8% after RFA (no primary treatment failure and 6 LTP) P < 0.001. TACE was the only predictive factor of treatment failure (Hazard ratio: 5.573). The 4-years OS after RFA and TACE were 54.1% and 31.5% (P = 0.042), respectively. Conclusion For Child-Pugh A patients with early-stage HCC, alternative treatment as supra-selective TACE to RFA regarded as too challenging using common US guidance decrease significantly the local tumor control and overall survival. Efforts to improve feasibility of RFA especially for inconspicuous target have to be made. PMID:27793027

Prospective study of neoadjuvant chemoradiotherapy using intensity-modulated radiotherapy and 5 fluorouracil for locally advanced rectal cancer - toxicities and response assessment.

PubMed

Simson, David K; Mitra, Swarupa; Ahlawat, Parveen; Saxena, Upasna; Sharma, Manoj Kumar; Rawat, Sheh; Singh, Harpreet; Bansal, Babita; Sripathi, Lalitha Kameshwari; Tanwar, Aditi

2018-01-01

The past 2 decades witnessed the strengthening of evidence favoring the role of neoadjuvant chemoradiation (CHRT) in the treatment of locally advanced rectal cancer. The study aims to evaluate the response and acute toxicities to neoadjuvant CHRT using intensity-modulated radiotherapy (IMRT) in the treatment of rectal cancer. Predictive factors to achieve pathological complete response (pCR) were analyzed, as a secondary endpoint. All consecutive patients who underwent IMRT as part of neoadjuvant CHRT in the treatment of rectal cancer between August 2014 and December 2016 at a tertiary cancer care center were accrued for the study. The cohort underwent CHRT with IMRT technique at a dose of 50.4 Gy in 28 fractions concurrent with continuous infusion of 5 fluorouracil during the first and the last 4 days of CHRT. Surgery was performed 6 weeks later and the pathological response to CHRT was noted. Forty-three subjects were accrued for the study. Radiation dermatitis and diarrhea were the only observed grade ≥3 acute toxicities. Sphincter preservation rate (SPR) was 43.3%. pCR was observed in 32.6%. Univariate and multivariate logistic regression showed that carcinoembryonic antigen was the only independent predictive factor to achieve pCR. IMRT as part of neoadjuvant CHRT in the treatment of locally advanced rectal cancer is well tolerated and gives comparable results with respect to earlier studies in terms of pathological response and SPR. Further randomized controlled studies are needed to firmly state that IMRT is superior to 3-dimensional conformal radiotherapy.

Climate Controls AM Fungal Distributions from Global to Local Scales

NASA Astrophysics Data System (ADS)

Kivlin, S. N.; Hawkes, C.; Muscarella, R.; Treseder, K. K.; Kazenel, M.; Lynn, J.; Rudgers, J.

2016-12-01

Arbuscular mycorrhizal (AM) fungi have key functions in terrestrial biogeochemical processes; thus, determining the relative importance of climate, edaphic factors, and plant community composition on their geographic distributions can improve predictions of their sensitivity to global change. Local adaptation by AM fungi to plant hosts, soil nutrients, and climate suggests that all of these factors may control fungal geographic distributions, but their relative importance is unknown. We created species distribution models for 142 AM fungal taxa at the global scale with data from GenBank. We compared climate variables (BioClim and soil moisture), edaphic variables (phosphorus, carbon, pH, and clay content), and plant variables using model selection on models with (1) all variables, (2) climatic variables only (including soil moisture) and (3) resource-related variables only (all other soil parameters and NPP) using the MaxEnt algorithm evaluated with ENMEval. We also evaluated whether drivers of AM fungal distributions were phylogenetically conserved. To test whether global correlates of AM fungal distributions were reflected at local scales, we then surveyed AM fungi in nine plant hosts along three elevation gradients in the Upper Gunnison Basin, Colorado, USA. At the global scale, the distributions of 55% of AM fungal taxa were affected by both climate and soil resources, whereas 16% were only affected by climate and 29% were only affected by soil resources. Even for AM fungi that were affected by both climate and resources, the effects of climatic variables nearly always outweighed those of resources. Soil moisture and isothermality were the main climatic and NPP and soil carbon the main resource related factors influencing AM fungal distributions. Distributions of closely related AM fungal taxa were similarly affected by climate, but not by resources. Local scale surveys of AM fungi across elevations confirmed that climate was a key driver of AM fungal composition and root colonization, with weaker influences of plant identity and soil nutrients. These two studies across scales suggest prevailing effects of climate on AM fungal distributions. Thus, incorporating climate when forecasting future ranges of AM fungi will enhance predictions of AM fungal abundance and associated ecosystem functions.

Stability of radiomic features in CT perfusion maps

NASA Astrophysics Data System (ADS)

Bogowicz, M.; Riesterer, O.; Bundschuh, R. A.; Veit-Haibach, P.; Hüllner, M.; Studer, G.; Stieb, S.; Glatz, S.; Pruschy, M.; Guckenberger, M.; Tanadini-Lang, S.

2016-12-01

This study aimed to identify a set of stable radiomic parameters in CT perfusion (CTP) maps with respect to CTP calculation factors and image discretization, as an input for future prognostic models for local tumor response to chemo-radiotherapy. Pre-treatment CTP images of eleven patients with oropharyngeal carcinoma and eleven patients with non-small cell lung cancer (NSCLC) were analyzed. 315 radiomic parameters were studied per perfusion map (blood volume, blood flow and mean transit time). Radiomics robustness was investigated regarding the potentially standardizable (image discretization method, Hounsfield unit (HU) threshold, voxel size and temporal resolution) and non-standardizable (artery contouring and noise threshold) perfusion calculation factors using the intraclass correlation (ICC). To gain added value for our model radiomic parameters correlated with tumor volume, a well-known predictive factor for local tumor response to chemo-radiotherapy, were excluded from the analysis. The remaining stable radiomic parameters were grouped according to inter-parameter Spearman correlations and for each group the parameter with the highest ICC was included in the final set. The acceptance level was 0.9 and 0.7 for the ICC and correlation, respectively. The image discretization method using fixed number of bins or fixed intervals gave a similar number of stable radiomic parameters (around 40%). The potentially standardizable factors introduced more variability into radiomic parameters than the non-standardizable ones with 56-98% and 43-58% instability rates, respectively. The highest variability was observed for voxel size (instability rate  >97% for both patient cohorts). Without standardization of CTP calculation factors none of the studied radiomic parameters were stable. After standardization with respect to non-standardizable factors ten radiomic parameters were stable for both patient cohorts after correction for inter-parameter correlations. Voxel size, image discretization, HU threshold and temporal resolution have to be standardized to build a reliable predictive model based on CTP radiomics analysis.

Intra- and Interseasonal Autoregressive Prediction of Dengue Outbreaks Using Local Weather and Regional Climate for a Tropical Environment in Colombia

PubMed Central

Eastin, Matthew D.; Delmelle, Eric; Casas, Irene; Wexler, Joshua; Self, Cameron

2014-01-01

Dengue fever transmission results from complex interactions between the virus, human hosts, and mosquito vectors—all of which are influenced by environmental factors. Predictive models of dengue incidence rate, based on local weather and regional climate parameters, could benefit disease mitigation efforts. Time series of epidemiological and meteorological data for the urban environment of Cali, Colombia are analyzed from January of 2000 to December of 2011. Significant dengue outbreaks generally occur during warm-dry periods with extreme daily temperatures confined between 18°C and 32°C—the optimal range for mosquito survival and viral transmission. Two environment-based, multivariate, autoregressive forecast models are developed that allow dengue outbreaks to be anticipated from 2 weeks to 6 months in advance. These models have the potential to enhance existing dengue early warning systems, ultimately supporting public health decisions on the timing and scale of vector control efforts. PMID:24957546

Computational fluid dynamics tools can be used to predict the progression of coronary artery disease

NASA Astrophysics Data System (ADS)

Coşkun, A. Ümit; Chen, Caixia; Stone, Peter H.; Feldman, Charles L.

2006-03-01

Atherosclerosis is focal and individual plaques evolve in an independent manner. The endothelium regulates arterial behavior by responding to its local shear stress. In vitro studies indicate that low endothelial shear stress (ESS) upregulates the genetic and molecular responses leading to the initiation and progression of atherosclerosis and promotes inflammation and formation of other features characteristic of vulnerable plaque. Physiologic ESS is vasculoprotective and fosters quiescence of the endothelium and vascular wall. High ESS promotes platelet aggregation. ESS and vascular wall morphology along the course of human coronary arteries can now be characterized in vivo, and may predict the focal areas in which atherosclerosis progression occurs. Rapidly evolving methodologies are able to characterize the arterial wall and the local hemodynamic factors likely responsible for progression of coronary disease in man. These new diagnostic modalities allow for identification of plaque progression. Accurate identification of arterial segments at high-risk for progression may permit pre-emptive intervention strategies to avoid adverse coronary events.

A Simplified Model of Local Structure in Aqueous Proline Amino Acid Revealed by First-Principles Molecular Dynamics Simulations

PubMed Central

Troitzsch, Raphael Z.; Tulip, Paul R.; Crain, Jason; Martyna, Glenn J.

2008-01-01

Aqueous proline solutions are deceptively simple as they can take on complex roles such as protein chaperones, cryoprotectants, and hydrotropic agents in biological processes. Here, a molecular level picture of proline/water mixtures is developed. Car-Parrinello ab initio molecular dynamics (CPAIMD) simulations of aqueous proline amino acid at the B-LYP level of theory, performed using IBM's Blue Gene/L supercomputer and massively parallel software, reveal hydrogen-bonding propensities that are at odds with the predictions of the CHARMM22 empirical force field but are in better agreement with results of recent neutron diffraction experiments. In general, the CPAIMD (B-LYP) simulations predict a simplified structural model of proline/water mixtures consisting of fewer distinct local motifs. Comparisons of simulation results to experiment are made by direct evaluation of the neutron static structure factor S(Q) from CPAIMD (B-LYP) trajectories as well as to the results of the empirical potential structure refinement reverse Monte Carlo procedure applied to the neutron data. PMID:18790850

Users guide for the hydroacoustic coverage assessment model (HydroCAM)

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

Farrell, T., LLNL

1997-12-01

A model for predicting the detection and localization performance of hydroacoustic monitoring networks has been developed. The model accounts for major factors affecting global-scale acoustic propagation in the ocean. including horizontal refraction, travel time variability due to spatial and temporal fluctuations in the ocean, and detailed characteristics of the source. Graphical user interfaces are provided to setup the models and visualize the results. The model produces maps of network detection coverage and localization area of uncertainty, as well as intermediate results such as predicted path amplitudes, travel time and travel time variance. This Users Guide for the model is organizedmore » into three sections. First a summary of functionality available in the model is presented, including example output products. The second section provides detailed descriptions of each of models contained in the system. The last section describes how to run the model, including a summary of each data input form in the user interface.« less

A simplified model of local structure in aqueous proline amino acid revealed by first-principles molecular dynamics simulations.

PubMed

Troitzsch, Raphael Z; Tulip, Paul R; Crain, Jason; Martyna, Glenn J

2008-12-01

Aqueous proline solutions are deceptively simple as they can take on complex roles such as protein chaperones, cryoprotectants, and hydrotropic agents in biological processes. Here, a molecular level picture of proline/water mixtures is developed. Car-Parrinello ab initio molecular dynamics (CPAIMD) simulations of aqueous proline amino acid at the B-LYP level of theory, performed using IBM's Blue Gene/L supercomputer and massively parallel software, reveal hydrogen-bonding propensities that are at odds with the predictions of the CHARMM22 empirical force field but are in better agreement with results of recent neutron diffraction experiments. In general, the CPAIMD (B-LYP) simulations predict a simplified structural model of proline/water mixtures consisting of fewer distinct local motifs. Comparisons of simulation results to experiment are made by direct evaluation of the neutron static structure factor S(Q) from CPAIMD (B-LYP) trajectories as well as to the results of the empirical potential structure refinement reverse Monte Carlo procedure applied to the neutron data.

Evaluating the influence of gully erosion on landslide hazard analysis triggered by heavy rainfall

NASA Astrophysics Data System (ADS)

Ruljigaljig, Tjuku; Tsai, Ching-Jun; Peng, Wen-Fei; Yu, Teng-To

2017-04-01

During the rainstorm period such as typhoon or heavy rain, the development of gully will induce a large-scale landslide. The purpose of this study is to assess and quantify the existence and development of gully for the purpose of triggering landslides by analyzing the landslides hazard. Firstly, based on multi-scale DEM data, this study uses wavelet transform to construct an automatic algorithm. The 1-meter DEM is used to evaluate the location and type of gully, and to establish an evaluation model for predicting erosion development.In this study, routes in the Chai-Yi were studied to clarify the damage potential of roadways from local gully. The local of gully is regarded as a parameter to reduce the strength parameter. The distribution of factor of safe (F.S.) is compared with the landslide inventory map. The result of this research could be used to increase the prediction accuracy of landslide hazard analysis due to heavy rainfalls.

Finite Element Creep Damage Analyses and Life Prediction of P91 Pipe Containing Local Wall Thinning Defect

NASA Astrophysics Data System (ADS)

Xue, Jilin; Zhou, Changyu

2016-03-01

Creep continuum damage finite element (FE) analyses were performed for P91 steel pipe containing local wall thinning (LWT) defect subjected to monotonic internal pressure, monotonic bending moment and combined internal pressure and bending moment by orthogonal experimental design method. The creep damage lives of pipe containing LWT defect under different load conditions were obtained. Then, the creep damage life formulas were regressed based on the creep damage life results from FE method. At the same time a skeletal point rupture stress was found and used for life prediction which was compared with creep damage lives obtained by continuum damage analyses. From the results, the failure lives of pipe containing LWT defect can be obtained accurately by using skeletal point rupture stress method. Finally, the influence of LWT defect geometry was analysed, which indicated that relative defect depth was the most significant factor for creep damage lives of pipe containing LWT defect.

Derogation of Localizer Course Due to Proposed Water Tower Peterson Field, Colorado

DOT National Transportation Integrated Search

1974-10-01

The additional derogation to the localizer front and back courses caused by a water tower placed near the localizer site is predicted. This prediction is made with the Transportation Systems Center (TSC) localizer model. This additional derogation to...

Stereotactic body radiation therapy for liver oligometastases: predictive factors of local response by 18F-FDG-PET/CT.

PubMed

Mazzola, Rosario; Fersino, Sergio; Alongi, Pierpaolo; Di Paola, Gioacchino; Gregucci, Fabiana; Aiello, Dario; Tebano, Umberto; Pasetto, Stefano; Ruggieri, Ruggero; Salgarello, Matteo; Alongi, Filippo

2018-05-23

To investigate metabolic parameters as predictive of local response after stereotactic body radiation therapy (SBRT) for liver-oligometastases. Inclusion criteria of the present retrospective study were: (a) liver oligometastases with controlled primary tumor; (b) absence of progressive disease ≥6 months; (c) metastases ≤ 3; (d) evaluation of SBRT-response by means of 18-fludeoxyglucose-PET/CT for at least two subsequent evaluations; (e) Karnofsky performance status >80; (f) life-expectancy >6 months. The following metabolic parameters were defined semi-quantitatively for each metastases: (1) standardized uptake value (SUVmax; (2) SUV-mean; (3) metabolic tumor volume (MTV), tumor volume with a SUV ≥3, threshold 40%; (4) total lesion glycolysis (TLG), i.e. the product of SUV-mean and MTV. Local control was defined as absence of recurrence in the field of irradiation. 41 liver metastases were analyzed. Pre-SBRT, median SUV-max was 8.7 (range, 4.5-23.59), median SUV-mean was 4.6 (range, 3-7.5), median MTV was 5.7 cc (range, 0.9-80.6) and median total lesion glycolysis was 24.1 (range, 3.6-601.5). At statistical analysis, metastases with SUV-mean >5 (p 0.04; odds ratio 4.75, sensitivity = 50%, specificity = 82.6%, area under the curve 0.66) and SUV-max >12 (p 0.02; odds ratio 5.03, sensitivity = 69%, specificity = 70%, area under the curve = 0.69) showed higher rates of infield-failure compared to the remaining lesions. According to current findings, pre-SBRT SUV-max and SUV-mean could be predictable of local response in liver oligometastases. Advances in knowledge: Present findings could support the hypothesis that fludeoxyglucose-PET/CT may be a powerful tool to predict tumor control. Specifically, current results might be helpful for clinicians in the decision-making process regarding liver oligometastatic patient selection as well as the individual therapy stratification distinguishing between slowly local progressing patients and rapidly progressing patients.

Predictive factors of head and neck squamous cell carcinoma patient tolerance to high-dose cisplatin in concurrent chemoradiotherapy

PubMed Central

NAKANO, KENJI; SATO, YASUYOSHI; TOSHIYASU, TAKASHI; SATO, YUKIKO; INAGAKI, LINA; TOMOMATSU, JUNICHI; SASAKI, TORU; SHIMBASHI, WATARU; FUKUSHIMA, HIROFUMI; YONEKAWA, HIROYUKI; MITANI, HIROKI; KAWABATA, KAZUYOSHI; TAKAHASHI, SHUNJI

2016-01-01

Although high-dose cisplatin is the standard regimen of concurrent chemoradiotherapy (CCRT) for locally advanced head and neck squamous cell carcinoma (HNSCC), varying levels of patient tolerance towards cisplatin have been reported, and the predictive factors of cisplatin tolerance remain to be elucidated. The present study retrospectively reviewed newly diagnosed HNSCC patients who received CCRT. Cisplatin (80 mg/m2) was administered every 3 weeks. The proportion of high-dose cisplatin-tolerant patients (cumulative cisplatin dose, ≥200 mg/m2) was determined, and the predictive factors of cisplatin tolerance were analyzed in a logistic regression analysis. Between June 2006 and March 2013, a total of 159 patients were treated with CCRT. The median follow-up time was 36.7 months. A total of 73 patients (46%) tolerated a cumulative cisplatin dose ≥200 mg/m2; male gender [odds ratio (OR), 25.00; P=0.005] and high body surface area (BSA) (>1.80 m2; OR, 2.21; P=0.032) were significantly predictive of high-dose cisplatin tolerance. The high-dose cisplatin-tolerant patients had a significantly higher complete response (CR) rate (82 vs. 67%, P=0.045); however, there were no significant between-group differences in the 3-year OS (79.5 vs. 81.2%, P=0.59) or PFS (70.4 vs. 44.6%, P=0.076) by cisplatin tolerance. In clinical practice, approximately one-half of the patients tolerated high-dose cisplatin in CCRT. Male gender and high BSA could be predictive of cisplatin tolerance. PMID:26893880

Racial Differences in the Effects of Neighborhood Disadvantage on Residential Mobility in Later Life

PubMed Central

Riley, Alicia; Cagney, Kathleen A.

2016-01-01

Objectives: Past research on the residential mobility of older adults has focused on individual-level factors and life course events. Less attention has been paid to the role of the residential environment in explaining residential mobility in older adults. We sought to understand whether neighborhood disadvantage had predictive utility in explaining residential relocation patterns, and whether associations differed between Whites and non-Whites. Method: Data are from the National Social Life, Health and Aging Project, a nationally representative sample of community-dwelling older adults. Neighborhoods were defined at the census tract level. Local movers (different census tract, same county) and distant movers (different county) were compared with stayers. Results: After adjusting for individual-level factors, neighborhood disadvantage increased the likelihood of a local move, regardless of race/ethnicity. For non-Whites, higher neighborhood disadvantage decreased the likelihood of a distant move. Among local movers, Blacks and Latinos were less likely to improve neighborhood quality than Whites. Discussion: Neighborhood disadvantage may promote local mobility by undermining person–environment fit. Racial differences in access to better neighborhoods persist in later life. Future research should explore how older adults optimize person–environment fit in the face of neighborhood disadvantage when the possibility of relocation to a better neighborhood may be restricted. PMID:27257227

Fatigue crack growth behaviour of semi-elliptical surface cracks for an API 5L X65 gas pipeline under tension

NASA Astrophysics Data System (ADS)

Shaari, M. S.; Akramin, M. R. M.; Ariffin, A. K.; Abdullah, S.; Kikuchi, M.

2018-02-01

The paper is presenting the fatigue crack growth (FCG) behavior of semi-elliptical surface cracks for API X65 gas pipeline using S-version FEM. A method known as global-local overlay technique was used in this study to predict the fatigue behavior that involve of two separate meshes each specifically for global (geometry) and local (crack). The pre-post program was used to model the global geometry (coarser mesh) known as FAST including the material and boundary conditions. Hence, the local crack (finer mesh) will be defined the exact location and the mesh control accordingly. The local mesh was overlaid along with the global before the numerical computation taken place to solve the engineering problem. The stress intensity factors were computed using the virtual crack closure-integral method (VCCM). The most important results is the behavior of the fatigue crack growth, which contains the crack depth (a), crack length (c) and stress intensity factors (SIF). The correlation between the fatigue crack growth and the SIF shows a good growth for the crack depth (a) and dissimilar for the crack length (c) where stunned behavior was resulted. The S-version FEM will benefiting the user due to the overlay technique where it will shorten the computation process.

Self-organizing map analysis using multivariate data from theophylline powders predicted by a thin-plate spline interpolation.

PubMed

Yasuda, Akihito; Onuki, Yoshinori; Kikuchi, Shingo; Takayama, Kozo

2010-11-01

The quality by design concept in pharmaceutical formulation development requires establishment of a science-based rationale and a design space. We integrated thin-plate spline (TPS) interpolation and Kohonen's self-organizing map (SOM) to visualize the latent structure underlying causal factors and pharmaceutical responses. As a model pharmaceutical product, theophylline powders were prepared based on the standard formulation. The angle of repose, compressibility, cohesion, and dispersibility were measured as the response variables. These responses were predicted quantitatively on the basis of a nonlinear TPS. A large amount of data on these powders was generated and classified into several clusters using an SOM. The experimental values of the responses were predicted with high accuracy, and the data generated for the powders could be classified into several distinctive clusters. The SOM feature map allowed us to analyze the global and local correlations between causal factors and powder characteristics. For instance, the quantities of microcrystalline cellulose (MCC) and magnesium stearate (Mg-St) were classified distinctly into each cluster, indicating that the quantities of MCC and Mg-St were crucial for determining the powder characteristics. This technique provides a better understanding of the relationships between causal factors and pharmaceutical responses in theophylline powder formulations. © 2010 Wiley-Liss, Inc. and the American Pharmacists Association

Implementation of fuzzy logic to determining selling price of products in a local corporate chain store

NASA Astrophysics Data System (ADS)

Kristiana, S. P. D.

2017-12-01

Corporate chain store is one type of retail industries companies that are developing growing rapidly in Indonesia. The competition between retail companies is very tight, so retailer companies should evaluate its performance continuously in order to survive. The selling price of products is one of the essential attributes and gets attention of many consumers where it’s used to evaluate the performance of the industry. This research aimed to determine optimal selling price of product with considering cost factors, namely purchase price of the product from supplier, holding costs, and transportation costs. Fuzzy logic approach is used in data processing with MATLAB software. Fuzzy logic is selected to solve the problem because this method can consider complexities factors. The result is a model of determination of the optimal selling price by considering three cost factors as inputs in the model. Calculating MAPE and model prediction ability for some products are used as validation and verification where the average value is 0.0525 for MAPE and 94.75% for prediction ability. The conclusion is this model can predict the selling price of up to 94.75%, so it can be used as tools for the corporate chain store in particular to determine the optimal selling price for its products.

Watchful waiting and factors predictive of secondary treatment of localized prostate cancer.

PubMed

Wu, Hongyan; Sun, Leon; Moul, Judd W; Wu, Hong Yu; McLeod, David G; Amling, Christopher; Lance, Raymond; Kusuda, Leo; Donahue, Timothy; Foley, John; Chung, Andrew; Sexton, Wade; Soderdahl, Douglas

2004-03-01

Watchful waiting remains an important treatment option for some patients with localized prostate cancer. We defined the demographic, clinical and outcome features of men selecting watchful waiting as an initial treatment strategy, and determined factors predictive of eventual progression to secondary treatment. Of 8390 patients diagnosed with prostate cancer from 1990 to 2001 in the Department of Defense Center for Prostate Disease Research Database, 1158 patients chose watchful waiting as initial treatment. The demographic and clinical differences between patients on watchful waiting and those choosing other initial treatments were compared using the chi-square test. Secondary treatment-free survival according to various prognostic factors was plotted using the Kaplan-Meier method and differences were tested using the log rank test. A multivariate Cox proportional hazards regression analysis was performed to determine which factors were independent predictors of secondary treatment. Compared to other patients, those selecting watchful waiting were older, had lower prostate specific antigen (PSA) at diagnosis, and were more likely to have lower stage (cT1) and lower grade (Gleason sum 7 or less) cancers. Age, PSA and clinical stage were all significant and independent predictors of secondary treatment. The relative risk of secondary treatment can be expressed as EXP (-0.034 x age at diagnosis + 0.284 x LOG (diagnostic PSA) + 0.271 x clinical stage T2 + 0.264 x clinical stage T3). Men who elect watchful waiting as initial management for prostate cancer are older with lower Gleason sums and serum PSA. In these men, age at diagnosis, serum PSA and clinical stage are the most significant predictors of requiring or selecting secondary treatment.

Primary Gleason Grade 4 Impact on Biochemical Recurrence After Permanent Interstitial Brachytherapy in Japanese Patients With Low- or Intermediate-Risk Prostate Cancer

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

Uesugi, Tatsuya; Saika, Takashi, E-mail: saika@cc.okayama-u.ac.jp; Edamura, Kohei

2012-02-01

Purpose: To reveal a predictive factor for biochemical recurrence (BCR) after permanent prostate brachytherapy (PPB) using iodine-125 seed implantation in patients with localized prostate cancer classified as low or intermediate risk based on National Comprehensive Cancer Network (NCCN) guidelines. Methods and Materials: From January 2004 to December 2009, 414 consecutive Japanese patients with clinically localized prostate cancer classified as low or intermediate risk based on the NCCN guidelines were treated with PPB. The clinical factors including pathological data reviewed by a central pathologist and follow-up data were prospectively collected. Kaplan-Meier and Cox regression analyses were used to assess the factorsmore » associated with BCR. Results: Median follow-up was 36.5 months. The 2-, 3-, 4-, and 5-year BCR-free rates using the Phoenix definition were 98.3%, 96.0%, 91.6%, and 87.0%, respectively. On univariate analysis, the Gleason score, especially primary Gleason grade 4 in biopsy specimens, was a strong predicting factor (p < 0.0001), while age, initial prostate-specific antigen (PSA) level, T stage, and minimal dose delivered to 90% of the prostate volume (D90) were insignificant. Multivariate analysis indicated that a primary Gleason grade 4 was the most powerful prognostic factor associated with BCR (hazard ratio = 6.576, 95% confidence interval, 2.597-16.468, p < 0.0001). Conclusions: A primary Gleason grade 4 carried a worse BCR prognosis than the primary grade 3 in patients treated with PPB. Therefore, the indication for PPB in patients with a Gleason sum of 4 + 3 deserves careful and thoughtful consideration.« less

Localized lymphedema (elephantiasis): a case series and review of the literature.

PubMed

Lu, Song; Tran, Tien Anh; Jones, David M; Meyer, Dale R; Ross, Jeffrey S; Fisher, Hugh A; Carlson, John Andrew

2009-01-01

Lymphedema typically affects a whole limb. Rarely, lymphedema can present as a circumscribed plaque or an isolated skin tumor. To describe the clinical and pathologic characteristics and etiologic factors of localized lymphedema. Case-control study of skin biopsy and excision specimens histologically diagnosed with lymphedema and presenting as a localized skin tumor identified during a 4-year period. We identified 24 cases of localized lymphedema presenting as solitary large polyps (11), solid or papillomatous plaques (7), pendulous swellings (4), or tumors mimicking sarcoma (2). Patients were 18 females and 6 males with a mean age of 41 years (range 16-74). Anogenital involvement was most frequent (75%)--mostly vulva (58%), followed by eyelid (13%), thigh (8%) and breast (4%). Causative factors included injury due to trauma, surgery or childbirth (54%), chronic inflammatory disease (rosacea, Crohn's disease) (8%), and bacterial cellulitis (12%). Eighty-five percent of these patients were either overweight (50%) or obese (35%). Compared with a series of 80 patients with diffuse lymphedema, localized lymphedema patients were significantly younger (41 vs. 62 years old, p = 0.0001), had no history of cancer treatment (0% vs. 18%, p = 0.03), and had an injury to the affected site (54% vs. 6%, p = 0.0001). Histologically, all cases exhibited dermal edema, fibroplasia, dilated lymphatic vessels, uniformly distributed stromal cells and varying degrees of papillated epidermal hyperplasia, inflammatory infiltrates and hyperkeratosis. Tumor size significantly and positively correlated with history of cellulitis, obesity, dense inflammatory infiltrates containing abundant plasma cells, and lymphoid follicles (p < 0.05). A history of cellulitis, morbid obesity, lymphoid follicles and follicular cysts predicted recurrent or progressive swelling despite excision (p < 0.05). Localized lymphedema should be considered in the etiology of skin tumors when assessing a polyp, plaque, swelling or mass showing dermal edema, fibrosis and dilated lymphatics on biopsy. A combination of lymph stasis promoting factors (trauma, obesity, infection and/or inflammatory disorders) produces localized elephantiasis.

Complete surgical resection improves outcome in INRG high-risk patients with localized neuroblastoma older than 18 months.

PubMed

Fischer, Janina; Pohl, Alexandra; Volland, Ruth; Hero, Barbara; Dübbers, Martin; Cernaianu, Grigore; Berthold, Frank; von Schweinitz, Dietrich; Simon, Thorsten

2017-08-04

Although several studies have been conducted on the role of surgery in localized neuroblastoma, the impact of surgical timing and extent of primary tumor resection on outcome in high-risk patients remains controversial. Patients from the German neuroblastoma trial NB97 with localized neuroblastoma INSS stage 1-3 age > 18 months were included for retrospective analysis. Imaging reports were reviewed by two independent physicians for Image Defined Risk Factors (IDRF). Operation notes and corresponding imaging reports were analyzed for surgical radicality. The extent of tumor resection was classified as complete resection (95-100%), gross total resection (90-95%), incomplete resection (50-90%), and biopsy (<50%) and correlated with local control rate and outcome. Patients were stratified according to the International Neuroblastoma Risk Group (INRG) staging system. Survival curves were estimated according to the method of Kaplan and Meier and compared by the log-rank test. A total of 179 patients were included in this study. 77 patients underwent more than one primary tumor operation. After best surgery, 68.7% of patients achieved complete resection of the primary tumor, 16.8% gross total resection, 14.0% incomplete surgery, and 0.5% biopsy only. The cumulative complication rate was 20.3% and the surgery associated mortality rate was 1.1%. Image defined risk factors (IDRF) predicted the extent of resection. Patients with complete resection had a better local-progression-free survival (LPFS), event-free survival (EFS) and OS (overall survival) than the other groups. Subgroup analyses showed better EFS, LPFS and OS for patients with complete resection in INRG high-risk patients. Multivariable analyses revealed resection (complete vs. other), and MYCN (non-amplified vs. amplified) as independent prognostic factors for EFS, LPFS and OS. In patients with localized neuroblastoma age 18 months or older, especially in INRG high-risk patients harboring MYCN amplification, extended surgery of the primary tumor site improved local control rate and survival with an acceptable risk of complications.

A Preliminary Study of Temperament Among Malnourished Mayan Children.

PubMed

Galler, J R; Cervera, M D; Harrison, R H

1998-01-01

Temperament ratings using a modified Carey Infant Temperament Questionnaire were assessed in marginally malnourished and healthy comparison infants aged 7-13 months. The children were selected from a total of 81 children in this age range living in a rural region of southern Yucatan, Mexico. Eleven marginally malnourished infants whose weights fell between one-half and two standard deviations below local means and 14 comparison children whose weights fell one-half to two standard deviations above the local means were included in the study. Lengths did not differ between index and comparison groups. Related temperament categories were statistically grouped into two factors. Factor 1 (Difficult Child), which included approach, mood, threshold, adaptability and rhythmicity, showed a significant nutrition × sex interaction; Factor 2 (Activity) did not distinguish the groups. Comparison boys were viewed as significantly easier than marginally malnourished boys, and they were more adaptable to change and predictable in biological functions. Girls were similar regardless of nutritional status, and their scores were intermediate between those of malnourished and well-nourished boys. These findings were not significantly associated with environmental conditions in the home.

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.

A Bayesian network to predict coastal vulnerability to sea level rise

USGS Publications Warehouse

Gutierrez, B.T.; Plant, N.G.; Thieler, E.R.

2011-01-01

Sea level rise during the 21st century will have a wide range of effects on coastal environments, human development, and infrastructure in coastal areas. The broad range of complex factors influencing coastal systems contributes to large uncertainties in predicting long-term sea level rise impacts. Here we explore and demonstrate the capabilities of a Bayesian network (BN) to predict long-term shoreline change associated with sea level rise and make quantitative assessments of prediction uncertainty. A BN is used to define relationships between driving forces, geologic constraints, and coastal response for the U.S. Atlantic coast that include observations of local rates of relative sea level rise, wave height, tide range, geomorphic classification, coastal slope, and shoreline change rate. The BN is used to make probabilistic predictions of shoreline retreat in response to different future sea level rise rates. Results demonstrate that the probability of shoreline retreat increases with higher rates of sea level rise. Where more specific information is included, the probability of shoreline change increases in a number of cases, indicating more confident predictions. A hindcast evaluation of the BN indicates that the network correctly predicts 71% of the cases. Evaluation of the results using Brier skill and log likelihood ratio scores indicates that the network provides shoreline change predictions that are better than the prior probability. Shoreline change outcomes indicating stability (-1 1 m/yr) was not well predicted. We find that BNs can assimilate important factors contributing to coastal change in response to sea level rise and can make quantitative, probabilistic predictions that can be applied to coastal management decisions. Copyright ?? 2011 by the American Geophysical Union.

Local tumour control and eye preservation after gamma-knife radiosurgery of choroidal melanomas.

PubMed

Wackernagel, Werner; Holl, Etienne; Tarmann, Lisa; Mayer, Christoph; Avian, Alexander; Schneider, Mona; Kapp, Karin S; Langmann, Gerald

2014-02-01

To report on local tumour control and eye preservation after gamma knife radiosurgery (GK-RS) to treat choroidal melanomas. A total of 189 patients with choroidal melanoma were treated with GK-RS, with treatment doses between 25 and 80 Grays. The main outcome measures of our retrospective analysis were local tumour control, time to recurrence, eye retention rate and the reason for and time to secondary enucleation. Patient-associated, tumour-associated and treatment-associated parameters were evaluated as potential risk factors. Local tumour control was achieved in 94.4% of patients. The estimated tumour control rates were 97.6% at 1 year, 94.2% at 5 years and 92.4% at 10 years after treatment. Recurrence was observed between 3.1 months and 60.7 months post-treatment (median: 13.5 months). Advanced tumour stage (Tumour, Node, Metastasis (TNM) 3-4) was the most important risk factor for recurrence (Fine-Gray model; subhazard ratio, SHR: 3.3; p=0.079). The treatment dose was not related to tumour recurrence. The eye preservation rate was 81.6% at 5 years after treatment, remaining stable thereafter. Twenty-five eyes (14.1%) had to be enucleated at between 17 days and 68.0 months (median: 13.9 months) after GK-RS, and advanced tumour stage (Cox model; p=0.005), treatment dose (p=0.048), pretreatment visual acuity (p=0.016), and retinal detachment (p=0.027) were risk factors for requiring enucleation. GK-RS achieved a high tumour control rate, comparable to linear accelerator-based radiotherapy. Advanced TNM stage was a predictive risk factor for tumour recurrence and for secondary enucleation after GK-RS. Lower treatment doses were unrelated to tumour recurrence, although they were associated with an improved eye retention rate.

Development of a fine scale smoke dispersion modeling system. Part II: Case study of a prescribed burn in the New Jersey Pine Barrens

Treesearch

Michael T. Kiefer; Warren E. Heilman; Shiyuan Zhong; Joseph J. Charney; X. Bian; Ryan P. Shadbolt; John Hom; Kenneth Clark; Nicholas Skowronski; Michael Gallagher; Matthew Patterson

2011-01-01

Smoke dispersion from wildland fires is a critical health and safety issue, impacting air quality and visibility across a broad range of space and time scales. Predicting the dispersion of smoke from low-intensity fires is particularly challenging due to the fact that it is highly sensitive to factors such as near-surface meteorological conditions, local topography,...

Study of short-haul aircraft operating economics. Phase 2: An analysis of the impact of jet modernization on local service airline operating costs

NASA Technical Reports Server (NTRS)

Andrastek, D. A.

1976-01-01

The objectives of this phase of the study were (1) to assess the 10 year operating cost trends of the local service airlines operating in the 1965 through 1974 period, (2) to glean from these trends the technological and operational parameters which were impacted most significantly by the transition to newer pure jet, short haul transports, and effected by changing fuel prices and cost of living indices, and (3) to develop, construct, and evaluate an operating cost forecasting model which would incorporate those factors which best predicted airline total operating cost behavior over that 10-year period.

Multiscale processing of loss of metal: a machine learning approach

NASA Astrophysics Data System (ADS)

De Masi, G.; Gentile, M.; Vichi, R.; Bruschi, R.; Gabetta, G.

2017-07-01

Corrosion is one of the principal causes of degradation to failure of marine structures. In practice, localized corrosion is the most dangerous mode of attack and can result in serious failures, in particular in marine flowlines and inter-field lines, arousing serious concerns relatively to environmental impact. The progress in time of internal corrosion, the location along the route and across the pipe section, the development pattern and the depth of the loss of metal are a very complex issue: the most important factors are products characteristics, transport conditions over the operating lifespan, process fluid-dynamics, and pipeline geometrical configuration. Understanding which factors among them play the most important role is a key step to develop a model able to predict with enough accuracy the sections more exposed to risk of failure. Some factors play a crucial role at certain spatial scales while other factors at other scales. The Mutual Information Theory, intimately related to the concept of Shannon Entropy in Information theory, has been applied to detect the most important variables at each scale. Finally, the variables emerged from this analysis at each scale have been integrated in a predicting data driven model sensibly improving its performance.

Uncertainties of isoprene emissions in the MEGAN model estimated for a coniferous and broad-leaved mixed forest in Southern China

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

Situ, S.; Wang, Xuemei; Guenther, Alex B.

2014-12-01

Using local observed emission factor, meteorological data, vegetation 5 information and dynamic MODIS LAI, MEGANv2.1 was constrained to predict the isoprene emission from Dinghushan forest in the Pearl River Delta region during a field campaign in November 2008, and the uncertainties in isoprene emission estimates were quantified by the Monte Carlo approach. The results indicate that MEGAN can predict the isoprene emission reasonably during the campaign, and the mean value of isoprene emission is 2.35 mg m-2 h-1 in daytime. There are high uncertainties associated with the MEGAN inputs and calculated parameters, and the relative error can be as highmore » as -89 to 111% for a 95% confidence interval. The emission factor of broadleaf trees and the activity factor accounting for light and temperature dependence are the most important contributors to the uncertainties in isoprene emission estimated for the Dinghushan forest during the campaign. The results also emphasize the importance of accurate observed PAR and temperature to reduce the uncertainties in isoprene emission estimated by model, because the MEGAN model activity factor accounting for light and temperature dependence is highly sensitive to PAR and temperature.« less

Changes in Gene Expression Predicting Local Control in Cervical Cancer: Results from Radiation Therapy Oncology Group 0128

PubMed Central

Weidhaas, Joanne B.; Li, Shu-Xia; Winter, Kathryn; Ryu, Janice; Jhingran, Anuja; Miller, Bridgette; Dicker, Adam P.; Gaffney, David

2009-01-01

Purpose To evaluate the potential of gene expression signatures to predict response to treatment in locally advanced cervical cancer treated with definitive chemotherapy and radiation. Experimental Design Tissue biopsies were collected from patients participating in Radiation Therapy Oncology Group (RTOG) 0128, a phase II trial evaluating the benefit of celecoxib in addition to cisplatin chemotherapy and radiation for locally advanced cervical cancer. Gene expression profiling was done and signatures of pretreatment, mid-treatment (before the first implant), and “changed” gene expression patterns between pre- and mid-treatment samples were determined. The ability of the gene signatures to predict local control versus local failure was evaluated. Two-group t test was done to identify the initial gene set separating these end points. Supervised classification methods were used to enrich the gene sets. The results were further validated by leave-one-out and 2-fold cross-validation. Results Twenty-two patients had suitable material from pretreatment samples for analysis, and 13 paired pre- and mid-treatment samples were obtained. The changed gene expression signatures between the pre- and mid-treatment biopsies predicted response to treatment, separating patients with local failures from those who achieved local control with a seven-gene signature. The in-sample prediction rate, leave-one-out prediction rate, and 2-fold prediction rate are 100% for this seven-gene signature. This signature was enriched for cell cycle genes. Conclusions Changed gene expression signatures during therapy in cervical cancer can predict outcome as measured by local control. After further validation, such findings could be applied to direct additional therapy for cervical cancer patients treated with chemotherapy and radiation. PMID:19509178

Atmospheric Aerosol Source-Receptor Relationships: The Role of Coal-Fired Power Plants

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

Allen L. Robinson; Spyros N. Pandis; Cliff I. Davidson

2005-12-01

This report describes the technical progress made on the Pittsburgh Air Quality Study (PAQS) during the period of March 2005 through August 2005. Significant progress was made this project period on the source characterization, source apportionment, and deterministic modeling activities. This report highlights new data on road dust, vegetative detritus and motor vehicle emissions. For example, the results show significant differences in the composition in urban and rural road dust. A comparison of the organic of the fine particulate matter in the tunnel with the ambient provides clear evidence of the significant contribution of vehicle emissions to ambient PM. Themore » source profiles developed from this work are being used by the source-receptor modeling activities. The report presents results on the spatial distribution of PMF-factors. The results can be grouped into three different categories: regional sources, local sources, or potentially both regional and local sources. Examples of the regional sources are the sulfate and selenium PMF-factors which most likely-represent coal fired power plants. Examples of local sources are the specialty steel and lead factors. There is reasonable correspondence between these apportionments and data from the EPA TRI and AIRS emission inventories. Detailed comparisons between PMCAMx predictions and measurements by the STN and IMPROVE measurements in the Eastern US are presented. Comparisons were made for the major aerosol components and PM{sub 2.5} mass in July 2001, October 2001, January 2002, and April 2002. The results are encouraging with average fraction biases for most species less than 0.25. The improvement of the model performance during the last two years was mainly due to the comparison of the model predictions with the continuous measurements in the Pittsburgh Supersite. Major improvements have included the descriptions: of ammonia emissions (CMU inventory), night time nitrate chemistry, EC emissions and their diurnal variation, and nitric acid dry removal.« less

Predicting Rib Fracture Risk With Whole-Body Finite Element Models: Development and Preliminary Evaluation of a Probabilistic Analytical Framework

PubMed Central

Forman, Jason L.; Kent, Richard W.; Mroz, Krystoffer; Pipkorn, Bengt; Bostrom, Ola; Segui-Gomez, Maria

2012-01-01

This study sought to develop a strain-based probabilistic method to predict rib fracture risk with whole-body finite element (FE) models, and to describe a method to combine the results with collision exposure information to predict injury risk and potential intervention effectiveness in the field. An age-adjusted ultimate strain distribution was used to estimate local rib fracture probabilities within an FE model. These local probabilities were combined to predict injury risk and severity within the whole ribcage. The ultimate strain distribution was developed from a literature dataset of 133 tests. Frontal collision simulations were performed with the THUMS (Total HUman Model for Safety) model with four levels of delta-V and two restraints: a standard 3-point belt and a progressive 3.5–7 kN force-limited, pretensioned (FL+PT) belt. The results of three simulations (29 km/h standard, 48 km/h standard, and 48 km/h FL+PT) were compared to matched cadaver sled tests. The numbers of fractures predicted for the comparison cases were consistent with those observed experimentally. Combining these results with field exposure informantion (ΔV, NASS-CDS 1992–2002) suggests a 8.9% probability of incurring AIS3+ rib fractures for a 60 year-old restrained by a standard belt in a tow-away frontal collision with this restraint, vehicle, and occupant configuration, compared to 4.6% for the FL+PT belt. This is the first study to describe a probabilistic framework to predict rib fracture risk based on strains observed in human-body FE models. Using this analytical framework, future efforts may incorporate additional subject or collision factors for multi-variable probabilistic injury prediction. PMID:23169122

Developing a local least-squares support vector machines-based neuro-fuzzy model for nonlinear and chaotic time series prediction.

PubMed

Miranian, A; Abdollahzade, M

2013-02-01

Local modeling approaches, owing to their ability to model different operating regimes of nonlinear systems and processes by independent local models, seem appealing for modeling, identification, and prediction applications. In this paper, we propose a local neuro-fuzzy (LNF) approach based on the least-squares support vector machines (LSSVMs). The proposed LNF approach employs LSSVMs, which are powerful in modeling and predicting time series, as local models and uses hierarchical binary tree (HBT) learning algorithm for fast and efficient estimation of its parameters. The HBT algorithm heuristically partitions the input space into smaller subdomains by axis-orthogonal splits. In each partitioning, the validity functions automatically form a unity partition and therefore normalization side effects, e.g., reactivation, are prevented. Integration of LSSVMs into the LNF network as local models, along with the HBT learning algorithm, yield a high-performance approach for modeling and prediction of complex nonlinear time series. The proposed approach is applied to modeling and predictions of different nonlinear and chaotic real-world and hand-designed systems and time series. Analysis of the prediction results and comparisons with recent and old studies demonstrate the promising performance of the proposed LNF approach with the HBT learning algorithm for modeling and prediction of nonlinear and chaotic systems and time series.

Estimating gene function with least squares nonnegative matrix factorization.

PubMed

Wang, Guoli; Ochs, Michael F

2007-01-01

Nonnegative matrix factorization is a machine learning algorithm that has extracted information from data in a number of fields, including imaging and spectral analysis, text mining, and microarray data analysis. One limitation with the method for linking genes through microarray data in order to estimate gene function is the high variance observed in transcription levels between different genes. Least squares nonnegative matrix factorization uses estimates of the uncertainties on the mRNA levels for each gene in each condition, to guide the algorithm to a local minimum in normalized chi2, rather than a Euclidean distance or divergence between the reconstructed data and the data itself. Herein, application of this method to microarray data is demonstrated in order to predict gene function.

Bypass Flow Resistance in Prismatic Gas-Cooled Nuclear Reactors

DOE PAGES

McEligot, Donald M.; Johnson, Richard W.

2016-12-20

Available computational fluid dynamics (CFD) predictions of pressure distributions in the vertical bypass flow between blocks in a prismatic gas-cooled reactor (GCR) have been analyzed to deduce apparent friction factors and loss coefficients for systems and network codes. We performed calculations for vertical gap spacings "s" of 2, 6 and 10 mm, horizontal gaps between the blocks of two mm and two flow rates, giving a range of gap Reynolds numbers Re Dh of about 40 to 5300. Laminar predictions of the fully-developed friction factor f fd were about three to ten per cent lower than the classical infinitely-wide channelmore » In the entry region, the local apparent friction factor was slightly higher than the classic idealized case but the hydraulic entry length L hy was approximately the same. The per cent reduction in flow resistance was greater than the per cent increase in flow area at the vertical corners of the blocks. The standard k-ϵ model was employed for flows expected to be turbulent. Its predictions of f fd and flow resistance were significantly higher than direct numerical simulations for the classic case; the value of L hy was about thirty gap spacings. Initial quantitative information for entry coefficients and loss coefficients for the expansion-contraction junctions between blocks is also presented. Our study demonstrates how CFD predictions can be employed to provide integral quantities needed in systems and network codes.« less

Bypass Flow Resistance in Prismatic Gas-Cooled Nuclear Reactors

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

McEligot, Donald M.; Johnson, Richard W.

Available computational fluid dynamics (CFD) predictions of pressure distributions in the vertical bypass flow between blocks in a prismatic gas-cooled reactor (GCR) have been analyzed to deduce apparent friction factors and loss coefficients for systems and network codes. We performed calculations for vertical gap spacings "s" of 2, 6 and 10 mm, horizontal gaps between the blocks of two mm and two flow rates, giving a range of gap Reynolds numbers Re Dh of about 40 to 5300. Laminar predictions of the fully-developed friction factor f fd were about three to ten per cent lower than the classical infinitely-wide channelmore » In the entry region, the local apparent friction factor was slightly higher than the classic idealized case but the hydraulic entry length L hy was approximately the same. The per cent reduction in flow resistance was greater than the per cent increase in flow area at the vertical corners of the blocks. The standard k-ϵ model was employed for flows expected to be turbulent. Its predictions of f fd and flow resistance were significantly higher than direct numerical simulations for the classic case; the value of L hy was about thirty gap spacings. Initial quantitative information for entry coefficients and loss coefficients for the expansion-contraction junctions between blocks is also presented. Our study demonstrates how CFD predictions can be employed to provide integral quantities needed in systems and network codes.« less

Dengue Baidu Search Index data can improve the prediction of local dengue epidemic: A case study in Guangzhou, China

PubMed Central

Liu, Tao; Zhu, Guanghu; Lin, Hualiang; Zhang, Yonghui; He, Jianfeng; Deng, Aiping; Peng, Zhiqiang; Xiao, Jianpeng; Rutherford, Shannon; Xie, Runsheng; Zeng, Weilin; Li, Xing; Ma, Wenjun

2017-01-01

Background Dengue fever (DF) in Guangzhou, Guangdong province in China is an important public health issue. The problem was highlighted in 2014 by a large, unprecedented outbreak. In order to respond in a more timely manner and hence better control such potential outbreaks in the future, this study develops an early warning model that integrates internet-based query data into traditional surveillance data. Methodology and principal findings A Dengue Baidu Search Index (DBSI) was collected from the Baidu website for developing a predictive model of dengue fever in combination with meteorological and demographic factors. Generalized additive models (GAM) with or without DBSI were established. The generalized cross validation (GCV) score and deviance explained indexes, intraclass correlation coefficient (ICC) and root mean squared error (RMSE), were respectively applied to measure the fitness and the prediction capability of the models. Our results show that the DBSI with one-week lag has a positive linear relationship with the local DF occurrence, and the model with DBSI (ICC:0.94 and RMSE:59.86) has a better prediction capability than the model without DBSI (ICC:0.72 and RMSE:203.29). Conclusions Our study suggests that a DSBI combined with traditional disease surveillance and meteorological data can improve the dengue early warning system in Guangzhou. PMID:28263988

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

Bilbao, Cristina, E-mail: cbilbao@dbbf.ulpgc.e; Department of Radiation Oncology, Hospital Universitario de Gran Canaria Dr. Negrin, Las Palmas de Gran Canaria, Canary Islands; Lara, Pedro Carlos

Purpose: To elucidate whether microsatellite instability (MSI) predicts clinical outcome in radiation-treated endometrioid endometrial cancer (EEC). Methods and Materials: A consecutive series of 93 patients with EEC treated with extrafascial hysterectomy and postoperative radiotherapy was studied. The median clinical follow-up of patients was 138 months, with a maximum of 232 months. Five quasimonomorphic mononucleotide markers (BAT-25, BAT-26, NR21, NR24, and NR27) were used for MSI classification. Results: Twenty-five patients (22%) were classified as MSI. Both in the whole series and in early stages (I and II), univariate analysis showed a significant association between MSI and poorer 10-year local disease-free survival,more » disease-free survival, and cancer-specific survival. In multivariate analysis, MSI was excluded from the final regression model in the whole series, but in early stages MSI provided additional significant predictive information independent of traditional prognostic and predictive factors (age, stage, grade, and vascular invasion) for disease-free survival (hazard ratio [HR] 3.25, 95% confidence interval [CI] 1.01-10.49; p = 0.048) and cancer-specific survival (HR 4.20, 95% CI 1.23-14.35; p = 0.022) and was marginally significant for local disease-free survival (HR 3.54, 95% CI 0.93-13.46; p = 0.064). Conclusions: These results suggest that MSI may predict radiotherapy response in early-stage EEC.« less

Cancer Research Participation Beliefs and Behaviors of a Southern Black Population: A Quantitative Analysis of the Role of Structural Factors in Cancer Research Participation.

PubMed

Farr, Deeonna E; Brandt, Heather M; Comer, Kimberly D; Jackson, Dawnyéa D; Pandya, Kinjal; Friedman, Daniela B; Ureda, John R; Williams, Deloris G; Scott, Dolores B; Green, Wanda; Hébert, James R

2015-09-01

Increasing the participation of Blacks in cancer research is a vital component of a strategy to reduce racial inequities in cancer burden. Community-based participatory research (CBPR) is especially well-suited to advancing our knowledge of factors that influence research participation to ultimately address cancer-related health inequities. A paucity of literature focuses on the role of structural factors limiting participation in cancer research. As part of a larger CBPR project, we used survey data from a statewide cancer needs assessment of a Black faith community to examine the influence of structural factors on attitudes toward research and the contributions of both structural and attitudinal factors on whether individuals participate in research. Regression analyses and non-parametric statistics were conducted on data from 727 adult survey respondents. Structural factors, such as having health insurance coverage, experiencing discrimination during health care encounters, and locale, predicted belief in the benefits, but not the risks, of research participation. Positive attitudes toward research predicted intention to participate in cancer research. Significant differences in structural and attitudinal factors were found between cancer research participants and non-participants; however, directionality is confounded by the cross-sectional survey design and causality cannot be determined. This study points to complex interplay of structural and attitudinal factors on research participation as well as need for additional quantitative examinations of the various types of factors that influence research participation in Black communities.

Urban heat island effect on cicada densities in metropolitan Seoul.

PubMed

Nguyen, Hoa Q; Andersen, Desiree K; Kim, Yuseob; Jang, Yikweon

2018-01-01

Urban heat island (UHI) effect, the ubiquitous consequence of urbanization, is considered to play a major role in population expansion of numerous insects. Cryptotympana atrata and Hyalessa fuscata are the most abundant cicada species in the Korean Peninsula, where their population densities are higher in urban than in rural areas. We predicted a positive relationship between the UHI intensities and population densities of these two cicada species in metropolitan Seoul. To test this prediction, enumeration surveys of cicada exuviae densities were conducted in 36 localities located within and in the vicinity of metropolitan Seoul. Samples were collected in two consecutive periods from July to August 2015. The abundance of each species was estimated by two resource-weighted densities, one based on the total geographic area, and the other on the total number of trees. Multiple linear regression analyses were performed to identify factors critical for the prevalence of cicada species in the urban habitat. C. atrata and H. fuscata were major constituents of cicada species composition collected across all localities. Minimum temperature and sampling period were significant factors contributing to the variation in densities of both species, whereas other environmental factors related to urbanization were not significant. More cicada exuviae were collected in the second rather than in the first samplings, which matched the phenological pattern of cicadas in metropolitan Seoul. Cicada population densities increased measurably with the increase in temperature. Age of residential complex also exhibited a significantly positive correlation to H. fuscata densities, but not to C. atrata densities. Effects of temperature on cicada densities have been discerned from other environmental factors, as cicada densities increased measurably in tandem with elevated temperature. Several mechanisms may contribute to the abundance of cicadas in urban environments, such as higher fecundity of females, lower mortality rate of instars, decline in host plant quality, and local adaptation of organisms, but none of them were tested in the current study. In sum, results of the enumeration surveys of cicada exuviae support the hypothesis that the UHI effect underlies the population expansion of cicadas in metropolitan Seoul. Nevertheless, the underlying mechanisms for this remain untested.

Local participation in biodiversity conservation initiatives: a comparative analysis of different models in South East Mexico.

PubMed

Méndez-López, María Elena; García-Frapolli, Eduardo; Pritchard, Diana J; Sánchez González, María Consuelo; Ruiz-Mallén, Isabel; Porter-Bolland, Luciana; Reyes-Garcia, Victoria

2014-12-01

In Mexico, biodiversity conservation is primarily implemented through three schemes: 1) protected areas, 2) payment-based schemes for environmental services, and 3) community-based conservation, officially recognized in some cases as Indigenous and Community Conserved Areas. In this paper we compare levels of local participation across conservation schemes. Through a survey applied to 670 households across six communities in Southeast Mexico, we document local participation during the creation, design, and implementation of the management plan of different conservation schemes. To analyze the data, we first calculated the frequency of participation at the three different stages mentioned, then created a participation index that characterizes the presence and relative intensity of local participation for each conservation scheme. Results showed that there is a low level of local participation across all the conservation schemes explored in this study. Nonetheless, the payment for environmental services had the highest local participation while the protected areas had the least. Our findings suggest that local participation in biodiversity conservation schemes is not a predictable outcome of a specific (community-based) model, thus implying that other factors might be important in determining local participation. This has implications on future strategies that seek to encourage local involvement in conservation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Numerical calculation of listener-specific head-related transfer functions and sound localization: Microphone model and mesh discretization

PubMed Central

Ziegelwanger, Harald; Majdak, Piotr; Kreuzer, Wolfgang

2015-01-01

Head-related transfer functions (HRTFs) can be numerically calculated by applying the boundary element method on the geometry of a listener’s head and pinnae. The calculation results are defined by geometrical, numerical, and acoustical parameters like the microphone used in acoustic measurements. The scope of this study was to estimate requirements on the size and position of the microphone model and on the discretization of the boundary geometry as triangular polygon mesh for accurate sound localization. The evaluation involved the analysis of localization errors predicted by a sagittal-plane localization model, the comparison of equivalent head radii estimated by a time-of-arrival model, and the analysis of actual localization errors obtained in a sound-localization experiment. While the average edge length (AEL) of the mesh had a negligible effect on localization performance in the lateral dimension, the localization performance in sagittal planes, however, degraded for larger AELs with the geometrical error as dominant factor. A microphone position at an arbitrary position at the entrance of the ear canal, a microphone size of 1 mm radius, and a mesh with 1 mm AEL yielded a localization performance similar to or better than observed with acoustically measured HRTFs. PMID:26233020

Long-term local control rates of patients with adenoid cystic carcinoma of the head and neck managed by surgery and postoperative radiation.

PubMed

Ali, Safina; Palmer, Frank L; Katabi, Nora; Lee, Nancy; Shah, Jatin P; Patel, Snehal G; Ganly, Ian

2017-10-01

To report long-term local control in patients with adenoid cystic cancer (ACC) of the head and neck managed by surgery and identify factors predictive for local failure. Single-institution retrospective cohort study. Eighty-seven patients who had surgery for ACC between 1985 and 2009 were identified. Patient, tumor, and treatment characteristics were recorded. Local recurrence-free survival (LRFS) was recorded by the Kaplan-Meier method. Predictors of local control were identified. The median age was 54 years. Seventy-two (83%) patients had perineural invasion, 61 (70%) had close/positive margins, and 58 (67%) had pT 1T2. Fifty-nine (68%) patients had postoperative radiation therapy (PORT). With a median follow-up of 85 months, the 10-year LRFS was 78.7%. There were 14 local recurrences. On multivariable analysis, pathological tumor (T)3T4 stage and no PORT were independent predictors for local failure. Patients with no PORT had a 13-fold increased risk of local failure compared to patients treated with PORT (P = 0.003) after adjusting for stage. After adjusting for T stage, patients who do not get PORT are more likely to have local recurrence. 4. Laryngoscope, 127:2265-2269, 2017. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.

Mutual diffusion of binary liquid mixtures containing methanol, ethanol, acetone, benzene, cyclohexane, toluene, and carbon tetrachloride

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

Guevara-Carrion, Gabriela; Janzen, Tatjana; Muñoz-Muñoz, Y. Mauricio

Mutual diffusion coefficients of all 20 binary liquid mixtures that can be formed out of methanol, ethanol, acetone, benzene, cyclohexane, toluene, and carbon tetrachloride without a miscibility gap are studied at ambient conditions of temperature and pressure in the entire composition range. The considered mixtures show a varying mixing behavior from almost ideal to strongly non-ideal. Predictive molecular dynamics simulations employing the Green-Kubo formalism are carried out. Radial distribution functions are analyzed to gain an understanding of the liquid structure influencing the diffusion processes. It is shown that cluster formation in mixtures containing one alcoholic component has a significant impactmore » on the diffusion process. The estimation of the thermodynamic factor from experimental vapor-liquid equilibrium data is investigated, considering three excess Gibbs energy models, i.e., Wilson, NRTL, and UNIQUAC. It is found that the Wilson model yields the thermodynamic factor that best suits the simulation results for the prediction of the Fick diffusion coefficient. Four semi-empirical methods for the prediction of the self-diffusion coefficients and nine predictive equations for the Fick diffusion coefficient are assessed and it is found that methods based on local composition models are more reliable. Finally, the shear viscosity and thermal conductivity are predicted and in most cases favorably compared with experimental literature values.« less

Multinomial Logistic Regression Predicted Probability Map To Visualize The Influence Of Socio-Economic Factors On Breast Cancer Occurrence in Southern Karnataka

NASA Astrophysics Data System (ADS)

Madhu, B.; Ashok, N. C.; Balasubramanian, S.

2014-11-01

Multinomial logistic regression analysis was used to develop statistical model that can predict the probability of breast cancer in Southern Karnataka using the breast cancer occurrence data during 2007-2011. Independent socio-economic variables describing the breast cancer occurrence like age, education, occupation, parity, type of family, health insurance coverage, residential locality and socioeconomic status of each case was obtained. The models were developed as follows: i) Spatial visualization of the Urban- rural distribution of breast cancer cases that were obtained from the Bharat Hospital and Institute of Oncology. ii) Socio-economic risk factors describing the breast cancer occurrences were complied for each case. These data were then analysed using multinomial logistic regression analysis in a SPSS statistical software and relations between the occurrence of breast cancer across the socio-economic status and the influence of other socio-economic variables were evaluated and multinomial logistic regression models were constructed. iii) the model that best predicted the occurrence of breast cancer were identified. This multivariate logistic regression model has been entered into a geographic information system and maps showing the predicted probability of breast cancer occurrence in Southern Karnataka was created. This study demonstrates that Multinomial logistic regression is a valuable tool for developing models that predict the probability of breast cancer Occurrence in Southern Karnataka.

The influence of acoustical and non-acoustical factors on short-term annoyance due to aircraft noise in the field - The COSMA study.

PubMed

Bartels, Susanne; Márki, Ferenc; Müller, Uwe

2015-12-15

Air traffic has increased for the past decades and is forecasted to continue to grow. Noise due to current airport operations can impair the physical and psychological well-being of airport residents. The field study investigated aircraft noise-induced short-term (i.e., within hourly intervals) annoyance in local residents near a busy airport. We aimed at examining the contribution of acoustical and non-acoustical factors to the annoyance rating. Across four days from getting up till going to bed, 55 residents near Cologne/Bonn Airport (M=46years, SD=14years, 34 female) rated their annoyance due to aircraft noise at hourly intervals. For each participant and each hour, 26 noise metrics from outdoor measurements and further 6 individualized metrics that took into account the sound attenuation due to each person's whereabouts in and around their homes were obtained. Non-acoustical variables were differentiated into situational factors (time of day, performed activity during past hour, day of the week) and personal factors (e.g., sensitivity to noise, attitudes, domestic noise insulation). Generalized Estimation Equations were applied for the development of a prediction model for annoyance. Acoustical factors explained only a small proportion (13.7%) of the variance in the annoyance ratings. The number of fly-overs predicted annoyance better than did equivalent and maximum sound pressure levels. The proportion of explained variance in annoyance rose considerably (to 27.6%) when individualized noise metrics as well as situational and personal variables were included in the prediction model. Consideration of noise metrics related to the number of fly-overs and individual adjustment of noise metrics can improve the prediction of short-term annoyance compared to models using equivalent outdoor levels only. Non-acoustical factors have remarkable impact not only on long-term annoyance as shown before but also on short-term annoyance judged in the home environment. Copyright © 2015 Elsevier B.V. All rights reserved.

Pioneer factors, genetic competence, and inductive signaling: programming liver and pancreas progenitors from the endoderm.

PubMed

Zaret, K S; Watts, J; Xu, J; Wandzioch, E; Smale, S T; Sekiya, T

2008-01-01

The endoderm is a multipotent progenitor cell population in the embryo that gives rise to the liver, pancreas, and other cell types and provides paradigms for understanding cell-type specification. Studies of isolated embryo tissue cells and genetic approaches in vivo have defined fibroblast growth factor/mitogen-activated protein kinase (FGF/MAPK) and bone morphogenetic protein (BMP) signaling pathways that induce liver and pancreatic fates in the endoderm. In undifferentiated endoderm cells, the FoxA and GATA transcription factors are among the first to engage silent genes, helping to endow competence for cell-type specification. FoxA proteins can bind their target sites in highly compacted chromatin and open up the local region for other factors to bind; hence, they have been termed "pioneer factors." We recently found that FoxA proteins remain bound to chromatin in mitosis, as an epigenetic mark. In embryonic stem cells, which lack FoxA, FoxA target sites can be occupied by FoxD3, which in turn helps to maintain a local demethylation of chromatin. By these means, a cascade of Fox factors helps to endow progenitor cells with the competence to activate genes in response to tissue-inductive signals. Understanding such epigenetic mechanisms for transcriptional competence coupled with knowledge of the relevant signals for cell-type specification should greatly facilitate efforts to predictably differentiate stem cells to liver and pancreatic fates.

PLPD: reliable protein localization prediction from imbalanced and overlapped datasets

PubMed Central

Lee, KiYoung; Kim, Dae-Won; Na, DoKyun; Lee, Kwang H.; Lee, Doheon

2006-01-01

Subcellular localization is one of the key functional characteristics of proteins. An automatic and efficient prediction method for the protein subcellular localization is highly required owing to the need for large-scale genome analysis. From a machine learning point of view, a dataset of protein localization has several characteristics: the dataset has too many classes (there are more than 10 localizations in a cell), it is a multi-label dataset (a protein may occur in several different subcellular locations), and it is too imbalanced (the number of proteins in each localization is remarkably different). Even though many previous works have been done for the prediction of protein subcellular localization, none of them tackles effectively these characteristics at the same time. Thus, a new computational method for protein localization is eventually needed for more reliable outcomes. To address the issue, we present a protein localization predictor based on D-SVDD (PLPD) for the prediction of protein localization, which can find the likelihood of a specific localization of a protein more easily and more correctly. Moreover, we introduce three measurements for the more precise evaluation of a protein localization predictor. As the results of various datasets which are made from the experiments of Huh et al. (2003), the proposed PLPD method represents a different approach that might play a complimentary role to the existing methods, such as Nearest Neighbor method and discriminate covariant method. Finally, after finding a good boundary for each localization using the 5184 classified proteins as training data, we predicted 138 proteins whose subcellular localizations could not be clearly observed by the experiments of Huh et al. (2003). PMID:16966337

Modelling and measurement of crack closure and crack growth following overloads and underloads

NASA Technical Reports Server (NTRS)

Dexter, R. J.; Hudak, S. J.; Davidson, D. L.

1989-01-01

Ignoring crack growth retardation following overloads can result in overly conservative life predictions in structures subjected to variable amplitude fatigue loading. Crack closure is believed to contribute to the crack growth retardation, although the specific closure mechanism is dabatable. The delay period and corresponding crack growth rate transients following overload and overload/underload cycles were systematically measured as a function of load ratio and overload magnitude. These responses are correlated in terms of the local 'driving force' for crack growth, i.e. the effective stress intensity factor range. Experimental results are compared with the predictions of a Dugdale-type (1960) crack closure model, and improvements in the model are suggested.

Protein subcellular localization prediction using artificial intelligence technology.

PubMed

Nair, Rajesh; Rost, Burkhard

2008-01-01

Proteins perform many important tasks in living organisms, such as catalysis of biochemical reactions, transport of nutrients, and recognition and transmission of signals. The plethora of aspects of the role of any particular protein is referred to as its "function." One aspect of protein function that has been the target of intensive research by computational biologists is its subcellular localization. Proteins must be localized in the same subcellular compartment to cooperate toward a common physiological function. Aberrant subcellular localization of proteins can result in several diseases, including kidney stones, cancer, and Alzheimer's disease. To date, sequence homology remains the most widely used method for inferring the function of a protein. However, the application of advanced artificial intelligence (AI)-based techniques in recent years has resulted in significant improvements in our ability to predict the subcellular localization of a protein. The prediction accuracy has risen steadily over the years, in large part due to the application of AI-based methods such as hidden Markov models (HMMs), neural networks (NNs), and support vector machines (SVMs), although the availability of larger experimental datasets has also played a role. Automatic methods that mine textual information from the biological literature and molecular biology databases have considerably sped up the process of annotation for proteins for which some information regarding function is available in the literature. State-of-the-art methods based on NNs and HMMs can predict the presence of N-terminal sorting signals extremely accurately. Ab initio methods that predict subcellular localization for any protein sequence using only the native amino acid sequence and features predicted from the native sequence have shown the most remarkable improvements. The prediction accuracy of these methods has increased by over 30% in the past decade. The accuracy of these methods is now on par with high-throughput methods for predicting localization, and they are beginning to play an important role in directing experimental research. In this chapter, we review some of the most important methods for the prediction of subcellular localization.

Optimization of formulation variables of benzocaine liposomes using experimental design.

PubMed

Mura, Paola; Capasso, Gaetano; Maestrelli, Francesca; Furlanetto, Sandra

2008-01-01

This study aimed to optimize, by means of an experimental design multivariate strategy, a liposomal formulation for topical delivery of the local anaesthetic agent benzocaine. The formulation variables for the vesicle lipid phase uses potassium glycyrrhizinate (KG) as an alternative to cholesterol and the addition of a cationic (stearylamine) or anionic (dicethylphosphate) surfactant (qualitative factors); the percents of ethanol and the total volume of the hydration phase (quantitative factors) were the variables for the hydrophilic phase. The combined influence of these factors on the considered responses (encapsulation efficiency (EE%) and percent drug permeated at 180 min (P%)) was evaluated by means of a D-optimal design strategy. Graphic analysis of the effects indicated that maximization of the selected responses requested opposite levels of the considered factors: For example, KG and stearylamine were better for increasing EE%, and cholesterol and dicethylphosphate for increasing P%. In the second step, the Doehlert design, applied for the response-surface study of the quantitative factors, pointed out a negative interaction between percent ethanol and volume of the hydration phase and allowed prediction of the best formulation for maximizing drug permeation rate. Experimental P% data of the optimized formulation were inside the confidence interval (P < 0.05) calculated around the predicted value of the response. This proved the suitability of the proposed approach for optimizing the composition of liposomal formulations and predicting the effects of formulation variables on the considered experimental response. Moreover, the optimized formulation enabled a significant improvement (P < 0.05) of the drug anaesthetic effect with respect to the starting reference liposomal formulation, thus demonstrating its actually better therapeutic effectiveness.

Do the conventional clinicopathologic parameters predict for response and survival in head and neck cancer patients undergoing neoadjuvant chemotherapy?

PubMed

Fonseca, E; Cruz, J J; Dueñas, A; Gómez, A; Sánchez, P; Martín, G; Nieto, A; Soria, P; Muñoz, A; Gómez, J L; Pardal, J L

1996-01-01

Neoadjuvant chemotherapy for head and neck carcinoma is still an important treatment modality. The prognostic value of patient and tumor parameters has been extensively evaluated in several trials, yielding mixed results. We report the prognostic factors emerging from a group of patients undergoing neoadjuvant chemotherapy. From April 1986 to June 1992, 149 consecutive patients received cisplatin-5-fluorouracil-based neoadjuvant chemotherapy. After four courses of chemotherapy, patients underwent local-regional treatment with surgery, radiation or both. A variety of patient and tumor characteristics were evaluated as predictors for response to chemotherapy and survival. The complete response, partial response and no response rates to NAC were 52%, 33% and 15%, respectively. No parameters predicted response to chemotherapy. At a maximum follow-up of 87 months, overall survival was 39% and disease-free survival was 49%. Variables shown to be predictors of survival in univariate analyses were age, performance status, histology, site, T, N, stage, and response to chemotherapy. Using the Cox regression analysis, only complete response to induction chemotherapy (P = 0.0006), performance status (P = 0.03), stage (P = 0.01), age (P = 0.03) and primary tumor site (P = 0.04) emerged as independent prognostic factors for survival. Complete response to chemotherapy was confirmed as the strongest prognostic factor influencing survival. However, conventional clinicopathologic factors did not predict response, hence, potential prognostic biologic and molecular factors for response must be sought. At present, much effort must be made for the improvement of the complete response rate, which seems to be a requisite to prolong survival.

Auxiliary field diffusion Monte Carlo calculations of light and medium-mass nuclei with local chiral interactions

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

Lonardoni, D.; Gandolfi, S.; Lynn, J. E.

Quantum Monte Carlo methods have recently been employed to study properties of nuclei and infinite matter using local chiral effective-field-theory interactions. In this paper, we present a detailed description of the auxiliary field diffusion Monte Carlo algorithm for nuclei in combination with local chiral two- and three-nucleon interactions up to next-to-next-to-leading order. We show results for the binding energy, charge radius, charge form factor, and Coulomb sum rule in nuclei withmore » $$3{\\le}A{\\le}16$$. Particular attention is devoted to the effect of different operator structures in the three-body force for different cutoffs. Finally, the outcomes suggest that local chiral interactions fit to few-body observables give a very good description of the ground-state properties of nuclei up to $$^{16}\\mathrm{O}$$, with the exception of one fit for the softer cutoff which predicts overbinding in larger nuclei.« less

Auxiliary field diffusion Monte Carlo calculations of light and medium-mass nuclei with local chiral interactions

DOE PAGES

Lonardoni, D.; Gandolfi, S.; Lynn, J. E.; ...

2018-04-24

Quantum Monte Carlo methods have recently been employed to study properties of nuclei and infinite matter using local chiral effective-field-theory interactions. In this paper, we present a detailed description of the auxiliary field diffusion Monte Carlo algorithm for nuclei in combination with local chiral two- and three-nucleon interactions up to next-to-next-to-leading order. We show results for the binding energy, charge radius, charge form factor, and Coulomb sum rule in nuclei withmore » $$3{\\le}A{\\le}16$$. Particular attention is devoted to the effect of different operator structures in the three-body force for different cutoffs. Finally, the outcomes suggest that local chiral interactions fit to few-body observables give a very good description of the ground-state properties of nuclei up to $$^{16}\\mathrm{O}$$, with the exception of one fit for the softer cutoff which predicts overbinding in larger nuclei.« less

[Application of ARIMA model on prediction of malaria incidence].

PubMed

Jing, Xia; Hua-Xun, Zhang; Wen, Lin; Su-Jian, Pei; Ling-Cong, Sun; Xiao-Rong, Dong; Mu-Min, Cao; Dong-Ni, Wu; Shunxiang, Cai

2016-01-29

To predict the incidence of local malaria of Hubei Province applying the Autoregressive Integrated Moving Average model (ARIMA). SPSS 13.0 software was applied to construct the ARIMA model based on the monthly local malaria incidence in Hubei Province from 2004 to 2009. The local malaria incidence data of 2010 were used for model validation and evaluation. The model of ARIMA (1, 1, 1) (1, 1, 0) 12 was tested as relatively the best optimal with the AIC of 76.085 and SBC of 84.395. All the actual incidence data were in the range of 95% CI of predicted value of the model. The prediction effect of the model was acceptable. The ARIMA model could effectively fit and predict the incidence of local malaria of Hubei Province.

Non-Friedmann cosmology for the Local Universe, significance of the universal Hubble constant, and short-distance indicators of dark energy

NASA Astrophysics Data System (ADS)

Chernin, A. D.; Teerikorpi, P.; Baryshev, Yu. V.

2006-09-01

Based on the increasing evidence of the cosmological relevance of the local Hubble flow, we consider a simple analytical cosmological model for the Local Universe. This is a non-Friedmann model with a non-uniform static space-time. The major dynamical factor controlling the local expansion is the antigravity produced by the omnipresent and permanent dark energy of the cosmic vacuum (or the cosmological constant). The antigravity dominates at larger distances than 1-2 Mpc from the center of the Local group. The model gives a natural explanation of the two key quantitative characteristics of the local expansion flow, which are the local Hubble constant and the velocity dispersion of the flow. The observed kinematical similarity of the local and global flows of expansion is clarified by the model. We analytically demonstrate the efficiency of the vacuum cooling mechanism that allows one to see the Hubble law this close to the Local group. The "universal Hubble constant" HV (≈60 km s-1 Mpc-1), depending only on the vacuum density, has special significance locally and globally. The model makes a number of verifiable predictions. It also unexpectedly shows that the dwarf galaxies of the local flow with the shortest distances and lowest redshifts may be the most sensitive indicators of dark energy in our neighborhood.

Score of liver ultrasonography predicts treatment-related severe neutropenia and neutropenic fever in induction chemotherapy with docetaxel for locally advanced head and neck cancer patients with normal serum transamines.

PubMed

Wang, Ting-Yao; Chen, Wei-Ming; Yang, Lan-Yan; Chen, Chao-Yu; Chou, Wen-Chi; Chen, Yi-Yang; Chen, Chih-Cheng; Lee, Kuan-Der; Lu, Chang-Hsien

2016-11-01

Induction chemotherapy with docetaxel improved outcome in advanced head and neck squamous cell carcinoma (HNSCC) patients, but docetaxel was not recommended in liver dysfunction patients for treatment toxicities. Severe neutropenic events (SNE) including severe neutropenia (SN) and febrile neutropenia (FN) still developed in these patients with normal serum transaminases. Ultrasonography (US) fibrotic score represented degree of hepatic parenchymal damage and showed good correlation to fibrotic changes histologically. This study aims to evaluate the association of US fibrotic score with docetaxel treatment-related SNE in advanced HNSCC patients with normal serum transaminases. Between 1 January 2011 and 31 December 2013, a total of 47 advanced HNSCC patients treated with induction docetaxel were enrolled. The clinical features were collected to assess predictive factors for SNE. The patients were divided into two groups by the US fibrotic score with a cutoff value of 7. The Mann-Whitney U test and logistic regression method were used for the risk factor analysis. The background, treatment, and response were similar in both groups except for lower lymphocyte and platelet count in patients with higher US score. Twenty-seven patients (51 %) developed grade 3/4 neutropenia, and more SNE developed in patients with US score ≧7. In multivariate analysis, only US score ≥7 was independent predictive factor for developing SN (hazard ratio 7.71, p = 0.043) and FN (hazard ratio 20.95, p = 0.008). US score ≥7 is an independent risk factor for SNE in advanced HNSCC patients treated with induction docetaxel. US score could be used for risk prediction of docetaxel-related SNE.

Accurate prediction of subcellular location of apoptosis proteins combining Chou's PseAAC and PsePSSM based on wavelet denoising.

PubMed

Yu, Bin; Li, Shan; Qiu, Wen-Ying; Chen, Cheng; Chen, Rui-Xin; Wang, Lei; Wang, Ming-Hui; Zhang, Yan

2017-12-08

Apoptosis proteins subcellular localization information are very important for understanding the mechanism of programmed cell death and the development of drugs. The prediction of subcellular localization of an apoptosis protein is still a challenging task because the prediction of apoptosis proteins subcellular localization can help to understand their function and the role of metabolic processes. In this paper, we propose a novel method for protein subcellular localization prediction. Firstly, the features of the protein sequence are extracted by combining Chou's pseudo amino acid composition (PseAAC) and pseudo-position specific scoring matrix (PsePSSM), then the feature information of the extracted is denoised by two-dimensional (2-D) wavelet denoising. Finally, the optimal feature vectors are input to the SVM classifier to predict subcellular location of apoptosis proteins. Quite promising predictions are obtained using the jackknife test on three widely used datasets and compared with other state-of-the-art methods. The results indicate that the method proposed in this paper can remarkably improve the prediction accuracy of apoptosis protein subcellular localization, which will be a supplementary tool for future proteomics research.

Accurate prediction of subcellular location of apoptosis proteins combining Chou’s PseAAC and PsePSSM based on wavelet denoising

PubMed Central

Chen, Cheng; Chen, Rui-Xin; Wang, Lei; Wang, Ming-Hui; Zhang, Yan

2017-01-01

Apoptosis proteins subcellular localization information are very important for understanding the mechanism of programmed cell death and the development of drugs. The prediction of subcellular localization of an apoptosis protein is still a challenging task because the prediction of apoptosis proteins subcellular localization can help to understand their function and the role of metabolic processes. In this paper, we propose a novel method for protein subcellular localization prediction. Firstly, the features of the protein sequence are extracted by combining Chou's pseudo amino acid composition (PseAAC) and pseudo-position specific scoring matrix (PsePSSM), then the feature information of the extracted is denoised by two-dimensional (2-D) wavelet denoising. Finally, the optimal feature vectors are input to the SVM classifier to predict subcellular location of apoptosis proteins. Quite promising predictions are obtained using the jackknife test on three widely used datasets and compared with other state-of-the-art methods. The results indicate that the method proposed in this paper can remarkably improve the prediction accuracy of apoptosis protein subcellular localization, which will be a supplementary tool for future proteomics research. PMID:29296195

New and Accurate Predictive Model for the Efficacy of Extracorporeal Shock Wave Therapy in Managing Patients With Chronic Plantar Fasciitis.

PubMed

Yin, Mengchen; Chen, Ni; Huang, Quan; Marla, Anastasia Sulindro; Ma, Junming; Ye, Jie; Mo, Wen

2017-12-01

To identify factors for the outcome of a minimum clinically successful therapy and to establish a predictive model of extracorporeal shock wave therapy (ESWT) in managing patients with chronic plantar fasciitis. Randomized, controlled, prospective study. Outpatient of local medical center settings. Patients treated for symptomatic chronic plantar fasciitis between 2014 and 2016 (N=278). ESWT was performed by the principal authors to treat chronic plantar fasciitis. ESWT was administered in 3 sessions, with an interval of 2 weeks (±4d). In the low-, moderate-, and high-intensity groups, 2400 impulses total of ESWT with an energy flux density of 0.2, 0.4, and 0.6mJ/mm 2 , respectively (a rate of 8 impulses per second), were applied. The independent variables were patient age, sex, body mass index, affected side, duration of symptoms, Roles and Maudsley score, visual analog scale (VAS) score when taking first steps in the morning, edema, bone spurs, and intensity grade of ESWT. A minimal reduction of 50% in the VAS score was considered as minimum clinically successful therapy. The correlations between the achievement of minimum clinically successful therapy and independent variables were analyzed. The statistically significant factors identified were further analyzed by multivariate logistic regression, and the predictive model was established. The success rate of ESWT was 66.9%. Univariate analysis found that VAS score when taking first steps in the morning, edema, and the presence of heel spur in radiograph significantly affected the outcome of the treatment. Logistic regression drew the equation: minimum clinically successful therapy=(1+e [.011+42.807×heel spur+.109×edema+5.395×VAS score] ) -1 .The sensitivity of the predictive factors was 96.77%, 87.63%, and 86.02%, respectively. The specificity of the predictive factors was 45.65%, 42.39%, and 85.87%, respectively. The area under the curve of the predictive factors was .751, .650, and .859, respectively. The Youden index was .4243, .3003, and .7189, respectively. The Hosmer-Lemeshow test showed a good fitting of the predictive model, with an overall accuracy of 89.6%. This study establishes a new and accurate predictive model for the efficacy of ESWT in managing patients with chronic plantar fasciitis. The use of these parameters, in the form of a predictive model for ESWT efficacy, has the potential to improve decision-making in the application of ESWT. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

A 17-molecule set as a predictor of complete response to neoadjuvant chemotherapy with docetaxel, cisplatin, and 5-fluorouracil in esophageal cancer

PubMed Central

Fumoto, Shoichi; Shibata, Tomotaka; Nishiki, Kohei; Tsukamoto, Yoshiyuki; Etoh, Tsuyoshi; Moriyama, Masatsugu; Shiraishi, Norio; Inomata, Masafumi

2017-01-01

Background Recently, neoadjuvant chemotherapy with docetaxel/cisplatin/5-fluorouracil (NAC-DCF) was identified as a novel strong regimen with a high rate of pathological complete response (pCR) in advanced esophageal cancer in Japan. Predicting pCR will contribute to the therapeutic strategy and the prevention of surgical invasion. However, a predictor of pCR after NAC-DCF has not yet been developed. The aim of this study was to identify a novel predictor of pCR in locally advanced esophageal cancer treated with NAC-DCF. Patients and methods A total of 32 patients who received NAC-DCF followed by esophagectomy between June 2013 and March 2016 were enrolled in this study. We divided the patients into the following 2 groups: pCR group (9 cases) and non-pCR group (23 cases), and compared gene expressions between these groups using DNA microarray data and KeyMolnet. Subsequently, a validation study of candidate molecular expression was performed in 7 additional cases. Results Seventeen molecules, including transcription factor E2F, T-cell-specific transcription factor, Src (known as “proto-oncogene tyrosine-protein kinase of sarcoma”), interferon regulatory factor 1, thymidylate synthase, cyclin B, cyclin-dependent kinase (CDK) 4, CDK, caspase-1, vitamin D receptor, histone deacetylase, MAPK/ERK kinase, bcl-2-associated X protein, runt-related transcription factor 1, PR domain zinc finger protein 1, platelet-derived growth factor receptor, and interleukin 1, were identified as candidate molecules. The molecules were mainly associated with pathways, such as transcriptional regulation by SMAD, RB/E2F, and STAT. The validation study indicated that 12 of the 17 molecules (71%) matched the trends of molecular expression. Conclusions A 17-molecule set that predicts pCR after NAC-DCF for locally advanced esophageal cancer was identified. PMID:29136005

Developing and implementing the use of predictive models for estimating water quality at Great Lakes beaches

USGS Publications Warehouse

Francy, Donna S.; Brady, Amie M.G.; Carvin, Rebecca B.; Corsi, Steven R.; Fuller, Lori M.; Harrison, John H.; Hayhurst, Brett A.; Lant, Jeremiah; Nevers, Meredith B.; Terrio, Paul J.; Zimmerman, Tammy M.

2013-01-01

Predictive models have been used at beaches to improve the timeliness and accuracy of recreational water-quality assessments over the most common current approach to water-quality monitoring, which relies on culturing fecal-indicator bacteria such as Escherichia coli (E. coli.). Beach-specific predictive models use environmental and water-quality variables that are easily and quickly measured as surrogates to estimate concentrations of fecal-indicator bacteria or to provide the probability that a State recreational water-quality standard will be exceeded. When predictive models are used for beach closure or advisory decisions, they are referred to as “nowcasts.” During the recreational seasons of 2010-12, the U.S. Geological Survey (USGS), in cooperation with 23 local and State agencies, worked to improve existing nowcasts at 4 beaches, validate predictive models at another 38 beaches, and collect data for predictive-model development at 7 beaches throughout the Great Lakes. This report summarizes efforts to collect data and develop predictive models by multiple agencies and to compile existing information on the beaches and beach-monitoring programs into one comprehensive report. Local agencies measured E. coli concentrations and variables expected to affect E. coli concentrations such as wave height, turbidity, water temperature, and numbers of birds at the time of sampling. In addition to these field measurements, equipment was installed by the USGS or local agencies at or near several beaches to collect water-quality and metrological measurements in near real time, including nearshore buoys, weather stations, and tributary staff gages and monitors. The USGS worked with local agencies to retrieve data from existing sources either manually or by use of tools designed specifically to compile and process data for predictive-model development. Predictive models were developed by use of linear regression and (or) partial least squares techniques for 42 beaches that had at least 2 years of data (2010-11 and sometimes earlier) and for 1 beach that had 1 year of data. For most models, software designed for model development by the U.S. Environmental Protection Agency (Virtual Beach) was used. The selected model for each beach was based on a combination of explanatory variables including, most commonly, turbidity, day of the year, change in lake level over 24 hours, wave height, wind direction and speed, and antecedent rainfall for various time periods. Forty-two predictive models were validated against data collected during an independent year (2012) and compared to the current method for assessing recreational water quality-using the previous day’s E. coli concentration (persistence model). Goals for good predictive-model performance were responses that were at least 5 percent greater than the persistence model and overall correct responses greater than or equal to 80 percent, sensitivities (percentage of exceedances of the bathing-water standard that were correctly predicted by the model) greater than or equal to 50 percent, and specificities (percentage of nonexceedances correctly predicted by the model) greater than or equal to 85 percent. Out of 42 predictive models, 24 models yielded over-all correct responses that were at least 5 percent greater than the use of the persistence model. Predictive-model responses met the performance goals more often than the persistence-model responses in terms of overall correctness (28 versus 17 models, respectively), sensitivity (17 versus 4 models), and specificity (34 versus 25 models). Gaining knowledge of each beach and the factors that affect E. coli concentrations is important for developing good predictive models. Collection of additional years of data with a wide range of environmental conditions may also help to improve future model performance. The USGS will continue to work with local agencies in 2013 and beyond to develop and validate predictive models at beaches and improve existing nowcasts, restructuring monitoring activities to accommodate future uncertainties in funding and resources.

Fine-scale natal homing and localized movement as shaped by sex and spawning habitat in chinook salmon

USGS Publications Warehouse

Neville, Helen; Isaak, Daniel; Dunham, J.B.; Thurow, Russel; Rieman, B.

2006-01-01

Natal homing is a hallmark of the life history of salmonid fishes, but the spatial scale of homing within local, naturally reproducing salmon populations is still poorly understood. Accurate homing (paired with restricted movement) should lead to the existence of fine-scale genetic structuring due to the spatial clustering of related individuals on spawning grounds. Thus, we explored the spatial resolution of natal homing using genetic associations among individual Chinook salmon (Oncorhynchus tshawytscha) in an interconnected stream network. We also investigated the relationship between genetic patterns and two factors hypothesized to influence natal homing and localized movements at finer scales in this species, localized patterns in the distribution of spawning gravels and sex. Spatial autocorrelation analyses showed that spawning locations in both sub-basins of our study site were spatially clumped, but the upper sub-basin generally had a larger spatial extent and continuity of redd locations than the lower sub-basin, where the distribution of redds and associated habitat conditions were more patchy. Male genotypes were not autocorrelated at any spatial scale in either sub-basin. Female genotypes showed significant spatial autocorrelation and genetic patterns for females varied in the direction predicted between the two sub-basins, with much stronger autocorrelation in the sub-basin with less continuity in spawning gravels. The patterns observed here support predictions about differential constraints and breeding tactics between the two sexes and the potential for fine-scale habitat structure to influence the precision of natal homing and localized movements of individual Chinook salmon on their breeding grounds.

WE-AB-207B-02: A Bayesian Network Approach for Joint Prediction of Tumor Control and Radiation Pneumonitis (RP) in Non-Small-Cell Lung Cancer (NSCLC)

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

Luo, Y; McShan, D; Matuszak, M

Purpose: NSCLC radiotherapy treatment is a trade-off between controlling the tumor while limiting radiation-induced toxicities. Here we identify hierarchical biophysical relationships that could simultaneously influence both local control (LC) and RP by using an integrated Bayesian Networks (BN) approach. Methods: We studied 79 NSCLC patients treated on prospective protocol with 56 cases of LC and 21 events of RP. Beyond dosimetric information, each patient had 193 features including 12 clinical factors, 60 circulating blood cytokines before and during radiotherapy, 62 microRNAs, and 59 single-nucleotide polymorphisms (SNPs). The most relevant biophysical predictors for both LC and RP were identified using amore » Markov blanket local discovery algorithm and the corresponding BN was constructed using a score-learning algorithm. The area under the free-response receiver operating characteristics (AU-FROC) was used for performance evaluation. Cross-validation was employed to guard against overfitting pitfalls. Results: A BN revealing the biophysical interrelationships jointly in terms of LC and RP was developed and evaluated. The integrated BN included two SNPs, one microRNA, one clinical factor, three pre-treatment cytokines, relative changes of two cytokines between pre and during-treatment, and gEUDs of the GTV (a=-20) and lung (a=1). On cross-validation, the AUC prediction of independent LC was 0.85 (95% CI: 0.75–0.95) and RP was 0.83 (0.73–0.92). The AU-FROC of the integrated BN to predict both LC/RP was 0.81 (0.71–0.90) based on 2000 stratified bootstrap, indicating minimal loss in joint prediction power. Conclusions: We developed a new approach for multiple outcome utility application in radiotherapy based on integrated BN techniques. The BN developed from large-scale retrospective data is able to simultaneously predict LC and RP in NSCLC treatments based on individual patient characteristics. The joint prediction is only slightly compromised compared to independent predictions. Our approach shows promise for use in clinical decision support system for personalized radiotherapy subject to multiple endpoints. These studies were supported by a grant from the NCI/NIH P01-CA59827.« less

The unrestricted local properties: application in nanoelectronics and for predicting radicals reactivity.

PubMed

Dral, Pavlo O

2014-03-01

The local electron affinity (EA(L)) and the local ionization energy (IE(L)) are successfully used for predicting properties of closed-shell species for drug design and for nanoelectronics. Here the respective unrestricted Hartree-Fock variants of EA(L) and IE(L), i.e., the unrestricted local electron affinity (UHF-EA(L)) and ionization energy (UHF-IE(L)), have been shown to be useful for predicting properties of open-shell species. UHF-EA(L) and UHF-IE(L) have been applied for explaining unique electronic properties of an exemplary nanomaterial carbon peapod. It is also demonstrated that UHF-EA(L) is useful for predicting and better understanding reactivity of radicals related to alkanes activation.

Outcomes of multiple wire localization for larger breast cancers: when can mastectomy be avoided?

PubMed

Kirstein, Laurie J; Rafferty, Elizabeth; Specht, Michelle C; Moore, Richard H; Taghian, Alphonse G; Hughes, Kevin S; Gadd, Michele A; Smith, Barbara L

2008-09-01

Mastectomy is often recommended when mammography shows a breast cancer with extensive calcifications. We wished to determine whether the use of multiple localizing wires to guide lumpectomy in this setting was associated with increased rates of breast conservation. We also wanted to identify factors that predicted a poor chance of successful lumpectomy, to avoid multiple lumpectomy attempts in a patient who would ultimately require mastectomy. Records of 153 women with breast cancer who underwent lumpectomy for larger lesions that required multiple wire localization and 196 controls who required only single wire localization were reviewed retrospectively. The number of localizing wires, specimen volume, largest specimen dimension, number of surgical procedures, and rates of breast conservation were scored. Seventy-seven percent of patients requiring multiple wire localization had successful breast conservation, compared with 90% of those needing only single wire localization. Only 28% of multiple wire patients required more than 1 excision to achieve clear margins, compared with 36% of single wire patients (p < 0.01). Breast conservation is possible in the great majority of breast cancer patients whose mammographic lesions require multiple localizing wires for excision. The use of multiple wires can decrease the number of procedures required to obtain clear lumpectomy margins.

Effects of local and global mechanical distortions to hypervelocity boundary layers

NASA Astrophysics Data System (ADS)

Flaherty, William P.

The response of hypervelocity boundary layers to global mechanical distortions due to concave surface curvature is examined. Surface heat transfer, visual boundary layer thickness, and pressure sensitive paint (PSP) data are obtained for a suite of models with different concave surface geometries. Results are compared to predictions using existing approximate methods. Near the leading edge, good agreement is observed, but at larger pressure gradients, predictions diverge significantly from the experimental data. Up to a factor of five underprediction is reported in regions with greatest distortion. Curve fits to the experimental data are compared with surface equations. It is demonstrated that reasonable estimates of the laminar heat flux augmentation may be obtained as a function of the local turning angle for all model geometries, even at the conditions of greatest distortion. As a means of introducing additional local distortions, vortex generators are used to impose streamwise structures into the boundary layer. The response of the large scale vortical structures to an adverse pressure gradient is investigated. For a flat plate baseline case, heat transfer augmentation at similar levels to turbulent flow is measured. For the concave geometries, increases in heat transfer by factors up to 2.6 are measured over the laminar values, though for higher turning angle cases, a relaxation to below undisturbed values is reported at turning angles between 10 and 15 degrees. The scaling of heat transfer with turning angle that is identified for the laminar boundary layer response is found to be robust even in the presence of the imposed vortex structures. PSP measurements indicated that natural streaks form over concave models even when imposed vorticity is present. Correlations found between the heat transfer and natural streak formation are discussed and indicate possible vortex interactions.

Prediction of response to chemoradiation in rectal cancer by a gene polymorphism in the epidermal growth factor receptor promoter region

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

Spindler, Karen-Lise Garm; Nielsen, Jens Nederby; Lindebjerg, Jan

2006-10-01

Purpose: Epidermal growth factor receptor (EGFR) has been associated with radioresistance in solid tumors. Recently a polymorphism in the Sp1 recognition site of the EGFR promoter region was identified. The present study investigated the predictive value of this polymorphism for the outcome of chemoradiation in locally advanced rectal cancer. Methods and Materials: The study included 77 patients with locally advanced T3 rectal tumors. Treatment consisted of preoperative radiation therapy at a total tumor dose of 65 Gy and concomitant chemotherapy with Uftoral. Blood samples from 63 patients were evaluated for Sp1 -216 G/T polymorphism by polymerase chain reaction analysis. Forty-eightmore » primary tumor biopsies were available for EGFR immunostaining. Patients underwent surgery 8 weeks after treatment. Pathologic response evaluation was performed according to the tumor regression grade (TRG) system. Results: Forty-nine percent had major response (TRG1-2) and 51% moderate response (TRG 3-4) to chemoradiation. The rates of major response were 34% (10/29) in GG homozygote patients compared with 65% (22/34) in patients with T containing variants (p = 0.023). Fifty-eight percent of biopsies were positive for EGFR expression (28/48). The major response rates with regard to EGFR immunostaining were not significantly different. EGFR-positive tumors were found in 83% of the GG homozygote patients compared with 38% of patients with TT or GT variants (p = 0.008). Conclusions: There was a significant correlation between EGFR Sp1 -216 G/T polymorphism and treatment response to chemoradiation in locally advanced rectal cancer. Further investigations of a second set of patient and other treatment schedules are warranted.« less

Status and future transition of rapid urbanizing landscape in central Western Ghats - CA based approach

NASA Astrophysics Data System (ADS)

Bharath, S..; Rajan, K. S.; Ramachandra, T. V.

2014-11-01

The land use changes in forested landscape are highly complex and dynamic, affected by the natural, socio-economic, cultural, political and other factors. The remote sensing (RS) and geographical information system (GIS) techniques coupled with multi-criteria evaluation functions such as Markov-cellular automata (CA-Markov) model helps in analysing intensity, extent and future forecasting of human activities affecting the terrestrial biosphere. Karwar taluk of Central Western Ghats in Karnataka state, India has seen rapid transitions in its forest cover due to various anthropogenic activities, primarily driven by major industrial activities. A study based on Landsat and IRS derived data along with CA-Markov method has helped in characterizing the patterns and trends of land use changes over a period of 2004-2013, expected transitions was predicted for a set of scenarios through 2013-2022. The analysis reveals the loss of pristine forest cover from 75.51% to 67.36% (1973 to 2013) and increase in agriculture land as well as built-up area of 8.65% (2013), causing impact on local flora and fauna. The other factors driving these changes are the aggregated level of demand for land, local and regional effects of land use activities such as deforestation, improper practices in expansion of agriculture and infrastructure development, deteriorating natural resources availability. The spatio temporal models helped in visualizing on-going changes apart from prediction of likely changes. The CA-Markov based analysis provides us insights into the localized changes impacting these regions and can be useful in developing appropriate mitigation management approaches based on the modelled future impacts. This necessitates immediate measures for minimizing the future impacts.

Prospective study of neoadjuvant chemoradiotherapy using intensity-modulated radiotherapy and 5 fluorouracil for locally advanced rectal cancer – toxicities and response assessment

PubMed Central

Simson, David K; Mitra, Swarupa; Ahlawat, Parveen; Saxena, Upasna; Sharma, Manoj Kumar; Rawat, Sheh; Singh, Harpreet; Bansal, Babita; Sripathi, Lalitha Kameshwari; Tanwar, Aditi

2018-01-01

Aims and objectives The past 2 decades witnessed the strengthening of evidence favoring the role of neoadjuvant chemoradiation (CHRT) in the treatment of locally advanced rectal cancer. The study aims to evaluate the response and acute toxicities to neoadjuvant CHRT using intensity-modulated radiotherapy (IMRT) in the treatment of rectal cancer. Predictive factors to achieve pathological complete response (pCR) were analyzed, as a secondary endpoint. Materials and methods All consecutive patients who underwent IMRT as part of neoadjuvant CHRT in the treatment of rectal cancer between August 2014 and December 2016 at a tertiary cancer care center were accrued for the study. The cohort underwent CHRT with IMRT technique at a dose of 50.4 Gy in 28 fractions concurrent with continuous infusion of 5 fluorouracil during the first and the last 4 days of CHRT. Surgery was performed 6 weeks later and the pathological response to CHRT was noted. Results Forty-three subjects were accrued for the study. Radiation dermatitis and diarrhea were the only observed grade ≥3 acute toxicities. Sphincter preservation rate (SPR) was 43.3%. pCR was observed in 32.6%. Univariate and multivariate logistic regression showed that carcinoembryonic antigen was the only independent predictive factor to achieve pCR. Conclusion IMRT as part of neoadjuvant CHRT in the treatment of locally advanced rectal cancer is well tolerated and gives comparable results with respect to earlier studies in terms of pathological response and SPR. Further randomized controlled studies are needed to firmly state that IMRT is superior to 3-dimensional conformal radiotherapy. PMID:29593430

Exact states in waveguides with periodically modulated nonlinearity

NASA Astrophysics Data System (ADS)

Ding, E.; Chan, H. N.; Chow, K. W.; Nakkeeran, K.; Malomed, B. A.

2017-09-01

We introduce a one-dimensional model based on the nonlinear Schrödinger/Gross-Pitaevskii equation where the local nonlinearity is subject to spatially periodic modulation in terms of the Jacobi {dn} function, with three free parameters including the period, amplitude, and internal form-factor. An exact periodic solution is found for each set of parameters and, which is more important for physical realizations, we solve the inverse problem and predict the period and amplitude of the modulation that yields a particular exact spatially periodic state. A numerical stability analysis demonstrates that the periodic states become modulationally unstable for large periods, and regain stability in the limit of an infinite period, which corresponds to a bright soliton pinned to a localized nonlinearity-modulation pattern. The exact dark-bright soliton complex in a coupled system with a localized modulation structure is also briefly considered. The system can be realized in planar optical waveguides and cigar-shaped atomic Bose-Einstein condensates.

Local–global overlap in diversity informs mechanisms of bacterial biogeography

PubMed Central

Livermore, Joshua A; Jones, Stuart E

2015-01-01

Spatial variation in environmental conditions and barriers to organism movement are thought to be important factors for generating endemic species, thus enhancing global diversity. Recent microbial ecology research suggested that the entire diversity of bacteria in the global oceans could be recovered at a single site, thus inferring a lack of bacterial endemism. We argue this is not the case in the global ocean, but might be in other bacterial ecosystems with higher dispersal rates and lower global diversity, like the human gut. We quantified the degree to which local and global bacterial diversity overlap in a diverse set of ecosystems. Upon comparison of observed local–global diversity overlap with predictions from a neutral biogeography model, human-associated microbiomes (gut, skin, mouth) behaved much closer to neutral expectations whereas soil, lake and marine communities deviated strongly from the neutral expectations. This is likely a result of differences in dispersal rate among ‘patches', global diversity of these systems, and local densities of bacterial cells. It appears that overlap of local and global bacterial diversity is surprisingly large (but likely not one-hundred percent), and most importantly this overlap appears to be predictable based upon traditional biogeographic parameters like community size, global diversity, inter-patch environmental heterogeneity and patch connectivity. PMID:25848869

Importance of adequate local spatiotemporal transmission measures in malaria cohort studies: application to the relation between placental malaria and first malaria infection in infants.

PubMed

Le Port, Agnès; Cottrell, Gilles; Chandre, Fabrice; Cot, Michel; Massougbodji, Achille; Garcia, André

2013-07-01

According to several studies, infants whose mothers had a malaria-infected placenta (MIP) at delivery are at increased risk of a first malaria infection. Immune tolerance caused by intrauterine contact with the parasite could explain this phenomenon, but it is also known that infants who are highly exposed to Anopheles mosquitoes infected with Plasmodium are at greater risk of contracting malaria. Consequently, local malaria transmission must be taken into account to demonstrate the immune tolerance hypothesis. From data collected between 2007 and 2010 on 545 infants followed from birth to age 18 months in southern Benin, we compared estimates of the effect of MIP on time to first malaria infection obtained through different Cox models. In these models, MIP was adjusted for either 1) "village-like" time-independent exposure variables or 2) spatiotemporal exposure prediction derived from local climatic, environmental, and behavioral factors. Only the use of exposure prediction improved the model's goodness of fit (Bayesian Information Criterion) and led to clear conclusions regarding the effect of placental infection, whereas the models using the village-like variables were less successful than the univariate model. This demonstrated clearly the benefit of adequately taking transmission into account in cohort studies of malaria.

Uptake and localization mechanisms of fluorescent and colored lipid probes. Part 2. QSAR models that predict localization of fluorescent probes used to identify ("specifically stain") various biomembranes and membranous organelles.

PubMed

Horobin, R W; Stockert, J C; Rashid-Doubell, F

2015-05-01

We discuss a variety of biological targets including generic biomembranes and the membranes of the endoplasmic reticulum, endosomes/lysosomes, Golgi body, mitochondria (outer and inner membranes) and the plasma membrane of usual fluidity. For each target, we discuss the access of probes to the target membrane, probe uptake into the membrane and the mechanism of selectivity of the probe uptake. A statement of the QSAR decision rule that describes the required physicochemical features of probes that enable selective staining also is provided, followed by comments on exceptions and limits. Examples of probes typically used to demonstrate each target structure are noted and decision rule tabulations are provided for probes that localize in particular targets; these tabulations show distribution of probes in the conceptual space defined by the relevant structure parameters ("parameter space"). Some general implications and limitations of the QSAR models for probe targeting are discussed including the roles of certain cell and protocol factors that play significant roles in lipid staining. A case example illustrates the predictive ability of QSAR models. Key limiting values of the head group hydrophilicity parameter associated with membrane-probe interactions are discussed in an appendix.

Modeling the risk of transmission of schistosomiasis in Akure North Local Government Area of Ondo State, Nigeria using satellite derived environmental data.

PubMed

Ajakaye, Oluwaremilekun G; Adedeji, Oluwatola I; Ajayi, Paul O

2017-07-01

Schistosomiasis is a parasitic disease and its distribution, in space and time, can be influenced by environmental factors such as rivers, elevation, slope, land surface temperature, land use/cover and rainfall. The aim of this study is to identify the areas with suitable conditions for schistosomiasis transmission on the basis of physical and environmental factors derived from satellite imagery and spatial analysis for Akure North Local Government Area (LGA) of Ondo State. Nigeria. This was done through methodology multicriteria evaluation (MCE) using Saaty's analytical hierarchy process (AHP). AHP is a multi-criteria decision method that uses hierarchical structures to represent a problem and makes decisions based on priority scales. In this research AHP was used to obtain the mapping weight or importance of each individual schistosomiasis risk factor. For the purpose of identifying areas of schistosomiasis risk, this study focused on temperature, drainage, elevation, rainfall, slope and land use/land cover as the factors controlling schistosomiasis incidence in the study area. It is by reclassifying and overlaying these factors that areas vulnerable to schistosomiasis were identified. The weighted overlay analysis was done after each factor was given the appropriate weight derived through the analytical hierarchical process. The prevalence of urinary schistosomiasis in the study area was also determined by parasitological analysis of urine samples collected through random sampling. The results showed varying risk of schistosomiasis with a larger portion of the area (82%) falling under the high and very high risk category. The study also showed that one community (Oba Ile) had the lowest risk of schistosomiasis while the risk increased in the four remaining communities (Iju, Igoba, Ita Ogbolu and Ogbese). The predictions made by the model correlated strongly with observations from field study. The high risk zones corresponded to known endemic communities. This study revealed that environmental factors can be used in identifying and predicting the transmission of schistosomiasis as well as effective monitoring of disease risk in newly established rural and agricultural communities.

Treatment default amongst patients with tuberculosis in urban Morocco: predicting and explaining default and post-default sputum smear and drug susceptibility results.

PubMed

Cherkaoui, Imad; Sabouni, Radia; Ghali, Iraqi; Kizub, Darya; Billioux, Alexander C; Bennani, Kenza; Bourkadi, Jamal Eddine; Benmamoun, Abderrahmane; Lahlou, Ouafae; Aouad, Rajae El; Dooley, Kelly E

2014-01-01

Public tuberculosis (TB) clinics in urban Morocco. Explore risk factors for TB treatment default and develop a prediction tool. Assess consequences of default, specifically risk for transmission or development of drug resistance. Case-control study comparing patients who defaulted from TB treatment and patients who completed it using quantitative methods and open-ended questions. Results were interpreted in light of health professionals' perspectives from a parallel study. A predictive model and simple tool to identify patients at high risk of default were developed. Sputum from cases with pulmonary TB was collected for smear and drug susceptibility testing. 91 cases and 186 controls enrolled. Independent risk factors for default included current smoking, retreatment, work interference with adherence, daily directly observed therapy, side effects, quick symptom resolution, and not knowing one's treatment duration. Age >50 years, never smoking, and having friends who knew one's diagnosis were protective. A simple scoring tool incorporating these factors was 82.4% sensitive and 87.6% specific for predicting default in this population. Clinicians and patients described additional contributors to default and suggested locally-relevant intervention targets. Among 89 cases with pulmonary TB, 71% had sputum that was smear positive for TB. Drug resistance was rare. The causes of default from TB treatment were explored through synthesis of qualitative and quantitative data from patients and health professionals. A scoring tool with high sensitivity and specificity to predict default was developed. Prospective evaluation of this tool coupled with targeted interventions based on our findings is warranted. Of note, the risk of TB transmission from patients who default treatment to others is likely to be high. The commonly-feared risk of drug resistance, though, may be low; a larger study is required to confirm these findings.

Leptospirosis in American Samoa – Estimating and Mapping Risk Using Environmental Data

PubMed Central

Lau, Colleen L.; Clements, Archie C. A.; Skelly, Chris; Dobson, Annette J.; Smythe, Lee D.; Weinstein, Philip

2012-01-01

Background The recent emergence of leptospirosis has been linked to many environmental drivers of disease transmission. Accurate epidemiological data are lacking because of under-diagnosis, poor laboratory capacity, and inadequate surveillance. Predictive risk maps have been produced for many diseases to identify high-risk areas for infection and guide allocation of public health resources, and are particularly useful where disease surveillance is poor. To date, no predictive risk maps have been produced for leptospirosis. The objectives of this study were to estimate leptospirosis seroprevalence at geographic locations based on environmental factors, produce a predictive disease risk map for American Samoa, and assess the accuracy of the maps in predicting infection risk. Methodology and Principal Findings Data on seroprevalence and risk factors were obtained from a recent study of leptospirosis in American Samoa. Data on environmental variables were obtained from local sources, and included rainfall, altitude, vegetation, soil type, and location of backyard piggeries. Multivariable logistic regression was performed to investigate associations between seropositivity and risk factors. Using the multivariable models, seroprevalence at geographic locations was predicted based on environmental variables. Goodness of fit of models was measured using area under the curve of the receiver operating characteristic, and the percentage of cases correctly classified as seropositive. Environmental predictors of seroprevalence included living below median altitude of a village, in agricultural areas, on clay soil, and higher density of piggeries above the house. Models had acceptable goodness of fit, and correctly classified ∼84% of cases. Conclusions and Significance Environmental variables could be used to identify high-risk areas for leptospirosis. Environmental monitoring could potentially be a valuable strategy for leptospirosis control, and allow us to move from disease surveillance to environmental health hazard surveillance as a more cost-effective tool for directing public health interventions. PMID:22666516

Similarity indices based on link weight assignment for link prediction of unweighted complex networks

NASA Astrophysics Data System (ADS)

Liu, Shuxin; Ji, Xinsheng; Liu, Caixia; Bai, Yi

2017-01-01

Many link prediction methods have been proposed for predicting the likelihood that a link exists between two nodes in complex networks. Among these methods, similarity indices are receiving close attention. Most similarity-based methods assume that the contribution of links with different topological structures is the same in the similarity calculations. This paper proposes a local weighted method, which weights the strength of connection between each pair of nodes. Based on the local weighted method, six local weighted similarity indices extended from unweighted similarity indices (including Common Neighbor (CN), Adamic-Adar (AA), Resource Allocation (RA), Salton, Jaccard and Local Path (LP) index) are proposed. Empirical study has shown that the local weighted method can significantly improve the prediction accuracy of these unweighted similarity indices and that in sparse and weakly clustered networks, the indices perform even better.

Predictors of cultural capital on science academic achievement at the 8th grade level

NASA Astrophysics Data System (ADS)

Misner, Johnathan Scott

The purpose of the study was to determine if students' cultural capital is a significant predictor of 8th grade science achievement test scores in urban locales. Cultural capital refers to the knowledge used and gained by the dominant class, which allows social and economic mobility. Cultural capital variables include magazines at home and parental education level. Other variables analyzed include socioeconomic status (SES), gender, and English language learners (ELL). This non-experimental study analyzed the results of the 2011 Eighth Grade Science National Assessment of Educational Progress (NAEP). The researcher analyzed the data using a multivariate stepwise regression analysis. The researcher concluded that the addition of cultural capital factors significantly increased the predictive power of the model where magazines in home, gender, student classified as ELL, parental education level, and SES were the independent variables and science achievement was the dependent variable. For alpha=0.05, the overall test for the model produced a R2 value of 0.232; therefore the model predicted 23.2% of variance in science achievement results. Other major findings include: higher measures of home resources predicted higher 2011 NAEP eighth grade science achievement; males were predicted to have higher 2011 NAEP 8 th grade science achievement; classified ELL students were predicted to score lower on the NAEP eight grade science achievement; higher parent education predicted higher NAEP eighth grade science achievement; lower measures of SES predicted lower 2011 NAEP eighth grade science achievement. This study contributed to the research in this field by identifying cultural capital factors that have been found to have statistical significance on predicting eighth grade science achievement results, which can lead to strategies to help improve science academic achievement among underserved populations.

Developing robust arsenic awareness prediction models using machine learning algorithms.

PubMed

Singh, Sushant K; Taylor, Robert W; Rahman, Mohammad Mahmudur; Pradhan, Biswajeet

2018-04-01

Arsenic awareness plays a vital role in ensuring the sustainability of arsenic mitigation technologies. Thus far, however, few studies have dealt with the sustainability of such technologies and its associated socioeconomic dimensions. As a result, arsenic awareness prediction has not yet been fully conceptualized. Accordingly, this study evaluated arsenic awareness among arsenic-affected communities in rural India, using a structured questionnaire to record socioeconomic, demographic, and other sociobehavioral factors with an eye to assessing their association with and influence on arsenic awareness. First a logistic regression model was applied and its results compared with those produced by six state-of-the-art machine-learning algorithms (Support Vector Machine [SVM], Kernel-SVM, Decision Tree [DT], k-Nearest Neighbor [k-NN], Naïve Bayes [NB], and Random Forests [RF]) as measured by their accuracy at predicting arsenic awareness. Most (63%) of the surveyed population was found to be arsenic-aware. Significant arsenic awareness predictors were divided into three types: (1) socioeconomic factors: caste, education level, and occupation; (2) water and sanitation behavior factors: number of family members involved in water collection, distance traveled and time spent for water collection, places for defecation, and materials used for handwashing after defecation; and (3) social capital and trust factors: presence of anganwadi and people's trust in other community members, NGOs, and private agencies. Moreover, individuals' having higher social network positively contributed to arsenic awareness in the communities. Results indicated that both the SVM and the RF algorithms outperformed at overall prediction of arsenic awareness-a nonlinear classification problem. Lower-caste, less educated, and unemployed members of the population were found to be the most vulnerable, requiring immediate arsenic mitigation. To this end, local social institutions and NGOs could play a crucial role in arsenic awareness and outreach programs. Use of SVM or RF or a combination of the two, together with use of a larger sample size, could enhance the accuracy of arsenic awareness prediction. Copyright © 2018 Elsevier Ltd. All rights reserved.

Multivariable Time Series Prediction for the Icing Process on Overhead Power Transmission Line

PubMed Central

Li, Peng; Zhao, Na; Zhou, Donghua; Cao, Min; Li, Jingjie; Shi, Xinling

2014-01-01

The design of monitoring and predictive alarm systems is necessary for successful overhead power transmission line icing. Given the characteristics of complexity, nonlinearity, and fitfulness in the line icing process, a model based on a multivariable time series is presented here to predict the icing load of a transmission line. In this model, the time effects of micrometeorology parameters for the icing process have been analyzed. The phase-space reconstruction theory and machine learning method were then applied to establish the prediction model, which fully utilized the history of multivariable time series data in local monitoring systems to represent the mapping relationship between icing load and micrometeorology factors. Relevant to the characteristic of fitfulness in line icing, the simulations were carried out during the same icing process or different process to test the model's prediction precision and robustness. According to the simulation results for the Tao-Luo-Xiong Transmission Line, this model demonstrates a good accuracy of prediction in different process, if the prediction length is less than two hours, and would be helpful for power grid departments when deciding to take action in advance to address potential icing disasters. PMID:25136653

Prognostic factors for seizure outcome in patients with MRI-negative temporal lobe epilepsy: A meta-analysis and systematic review.

PubMed

Wang, Xiu; Zhang, Chao; Wang, Yao; Hu, Wenhan; Shao, Xiaoqiu; Zhang, Jian-Guo; Zhang, Kai

2016-05-01

To perform a systematic review and meta-analysis to identify predictors of postoperative seizure freedom in patients with magnetic resonance imaging (MRI)-negative temporal lobe epilepsy. Publications were screened from electronic databases (MEDLINE, EMBASE), epilepsy archives, and bibliographies of relevant articles that were written in English. We recorded all possible risk factors that might predict seizure outcome after surgery. We calculated odds ratio (OR) with corresponding 95% confidence intervals (95% CI) of predictors for postoperative seizure freedom. Heterogeneity was assessed with I(2). All meta-analyses were performed using Review Manager. Epilepsy duration (OR=2.57, 95% CI=1.21-5.47, p<0.05, I(2)=1%) and ictal or interictal electroencephalographic anomalies precisely localized in the ipsilateral temporal lobe (OR=3.89, 95% CI=1.66-9.08, p<0.01, I(2)=0 and OR=3.38, 95% CI=1.57-7.25, p<0.05, I(2)=0, respectively) were significantly associated with a higher rate of seizure freedom after surgery. However, the positron emission tomography (PET) results were not predictive of postoperative seizure freedom (OR=2.11, 95% CI=0.95-4.65, p=0.06, I(2)=0). No significant difference in seizure freedom was observed between the positive and negative pathology groups (OR=1.36, 95% CI=0.70-2.63, p=0.36, I(2)=0). A shorter epilepsy duration and scalp electroencephalogram (EEG) signals localized precisely in the temporal lobe predicted a better seizure outcome in patients with MRI-negative temporal lobe epilepsy. Copyright © 2016 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Mechanics Model for Simulating RC Hinges under Reversed Cyclic Loading

PubMed Central

Shukri, Ahmad Azim; Visintin, Phillip; Oehlers, Deric J.; Jumaat, Mohd Zamin

2016-01-01

Describing the moment rotation (M/θ) behavior of reinforced concrete (RC) hinges is essential in predicting the behavior of RC structures under severe loadings, such as under cyclic earthquake motions and blast loading. The behavior of RC hinges is defined by localized slip or partial interaction (PI) behaviors in both the tension and compression region. In the tension region, slip between the reinforcement and the concrete defines crack spacing, crack opening and closing, and tension stiffening. While in the compression region, slip along concrete to concrete interfaces defines the formation and failure of concrete softening wedges. Being strain-based, commonly-applied analysis techniques, such as the moment curvature approach, cannot directly simulate these PI behaviors because they are localized and displacement based. Therefore, strain-based approaches must resort to empirical factors to define behaviors, such as tension stiffening and concrete softening hinge lengths. In this paper, a displacement-based segmental moment rotation approach, which directly simulates the partial interaction behaviors in both compression and tension, is developed for predicting the M/θ response of an RC beam hinge under cyclic loading. Significantly, in order to develop the segmental approach, a partial interaction model to predict the tension stiffening load slip relationship between the reinforcement and the concrete is developed. PMID:28773430

Mechanics Model for Simulating RC Hinges under Reversed Cyclic Loading.

PubMed

Shukri, Ahmad Azim; Visintin, Phillip; Oehlers, Deric J; Jumaat, Mohd Zamin

2016-04-22

Describing the moment rotation (M/θ) behavior of reinforced concrete (RC) hinges is essential in predicting the behavior of RC structures under severe loadings, such as under cyclic earthquake motions and blast loading. The behavior of RC hinges is defined by localized slip or partial interaction (PI) behaviors in both the tension and compression region. In the tension region, slip between the reinforcement and the concrete defines crack spacing, crack opening and closing, and tension stiffening. While in the compression region, slip along concrete to concrete interfaces defines the formation and failure of concrete softening wedges. Being strain-based, commonly-applied analysis techniques, such as the moment curvature approach, cannot directly simulate these PI behaviors because they are localized and displacement based. Therefore, strain-based approaches must resort to empirical factors to define behaviors, such as tension stiffening and concrete softening hinge lengths. In this paper, a displacement-based segmental moment rotation approach, which directly simulates the partial interaction behaviors in both compression and tension, is developed for predicting the M/θ response of an RC beam hinge under cyclic loading. Significantly, in order to develop the segmental approach, a partial interaction model to predict the tension stiffening load slip relationship between the reinforcement and the concrete is developed.

Gex-Model Using Local Area Fraction for Binary Electrolyte Systems

NASA Astrophysics Data System (ADS)

Haghtalab, Ali; Joda, Marzieh

2007-06-01

The correlation and prediction of phase equilibria of electrolyte systems are essential in the design and operation of many industrial processes such as downstream processing in biotechnology, desalination, hydrometallurgy, etc. In this research, the local composition non-random two liquid-nonrandom factor (NRTL-NRF) model of Haghtalab and Vera was extended for uni-univalent aqueous electrolyte solutions. Based on the assumptions of the NRTL-NRF model, excess Gibbs free energy ( g E) functions were derived for binary electrolyte systems. In this work, the local area fraction was applied and the modified model of NRTL-NRF was developed with either an equal or unequal surface area of an anion to the surface area of a cation. The modified NRTL-NRF models consist of two contributions, one due to long-range forces represented by the Debye-Hückel theory, and the other due to short-range forces, represented by local area fractions of species through nonrandom factors. Each model contains only two adjustable parameters per electrolyte. In addition, the model with unequal surface area of ionic species gives better results in comparison with the second new model with equal surface area of ions. The results for the mean activity coefficients for aqueous solutions of uni-univalent electrolytes at 298.15 K showed that the present model is more accurate than the original NRTL-NRF model.

Kin competition and the evolution of cooperation

PubMed Central

Platt, Thomas G.; Bever, James D.

2017-01-01

Kin and multilevel selection theories predict that genetic structure is required for the evolution of cooperation. However, local competition among relatives can limit cooperative benefits, antagonizing the evolution of cooperation. We show that several ecological factors determine the extent to which kin competition constrains cooperative benefits. In addition, we argue that cooperative acts that expand local carrying capacity are less constrained by kin competition than other cooperative traits, and are therefore more likely to evolve. These arguments are particularly relevant to microbial cooperation, which often involves the production of public goods that promote population expansion. The challenge now is to understand how an organism’s ecology influences how much cooperative groups contribute to future generations and thereby the evolution of cooperation. PMID:19409651

The effect of spending cuts on teen pregnancy.

PubMed

Paton, David; Wright, Liam

2017-07-01

In recent years, English local authorities have been forced to make significant cuts to devolved expenditure. In this paper, we examine the impact of reductions in local expenditure on one particular public health target: reducing rates of teen pregnancy. Contrary to predictions made at the time of the cuts, panel data estimates provide no evidence that areas which reduced expenditure the most have experienced relative increases in teenage pregnancy rates. Rather, expenditure cuts are associated with small reductions in teen pregnancy rates, a result which is robust to a number of alternative specifications and tests for causality. Underlying socio-economic factors such as education outcomes and alcohol consumption are found to be significant predictors of teen pregnancy. Copyright © 2017 Elsevier B.V. All rights reserved.

Dynamic motif occupancy (DynaMO) analysis identifies transcription factors and their binding sites driving dynamic biological processes

PubMed Central

Kuang, Zheng; Ji, Zhicheng

2018-01-01

Abstract Biological processes are usually associated with genome-wide remodeling of transcription driven by transcription factors (TFs). Identifying key TFs and their spatiotemporal binding patterns are indispensable to understanding how dynamic processes are programmed. However, most methods are designed to predict TF binding sites only. We present a computational method, dynamic motif occupancy analysis (DynaMO), to infer important TFs and their spatiotemporal binding activities in dynamic biological processes using chromatin profiling data from multiple biological conditions such as time-course histone modification ChIP-seq data. In the first step, DynaMO predicts TF binding sites with a random forests approach. Next and uniquely, DynaMO infers dynamic TF binding activities at predicted binding sites using their local chromatin profiles from multiple biological conditions. Another landmark of DynaMO is to identify key TFs in a dynamic process using a clustering and enrichment analysis of dynamic TF binding patterns. Application of DynaMO to the yeast ultradian cycle, mouse circadian clock and human neural differentiation exhibits its accuracy and versatility. We anticipate DynaMO will be generally useful for elucidating transcriptional programs in dynamic processes. PMID:29325176

Self-organizing map analysis using multivariate data from theophylline tablets predicted by a thin-plate spline interpolation.

PubMed

Yasuda, Akihito; Onuki, Yoshinori; Obata, Yasuko; Yamamoto, Rie; Takayama, Kozo

2013-01-01

The "quality by design" concept in pharmaceutical formulation development requires the establishment of a science-based rationale and a design space. We integrated thin-plate spline (TPS) interpolation and Kohonen's self-organizing map (SOM) to visualize the latent structure underlying causal factors and pharmaceutical responses. As a model pharmaceutical product, theophylline tablets were prepared based on a standard formulation. The tensile strength, disintegration time, and stability of these variables were measured as response variables. These responses were predicted quantitatively based on nonlinear TPS. A large amount of data on these tablets was generated and classified into several clusters using an SOM. The experimental values of the responses were predicted with high accuracy, and the data generated for the tablets were classified into several distinct clusters. The SOM feature map allowed us to analyze the global and local correlations between causal factors and tablet characteristics. The results of this study suggest that increasing the proportion of microcrystalline cellulose (MCC) improved the tensile strength and the stability of tensile strength of these theophylline tablets. In addition, the proportion of MCC has an optimum value for disintegration time and stability of disintegration. Increasing the proportion of magnesium stearate extended disintegration time. Increasing the compression force improved tensile strength, but degraded the stability of disintegration. This technique provides a better understanding of the relationships between causal factors and pharmaceutical responses in theophylline tablet formulations.

Regional Assessment of Storm-triggered Shall Landslide Risks using the SLIDE (SLope-Infiltration-Distributed Equilibrium) Model

NASA Astrophysics Data System (ADS)

Hong, Y.; Kirschbaum, D. B.; Fukuoka, H.

2011-12-01

The key to advancing the predictability of rainfall-triggered landslides is to use physically based slope-stability models that simulate the dynamical response of the subsurface moisture to spatiotemporal variability of rainfall in complex terrains. An early warning system applying such physical models has been developed to predict rainfall-induced shallow landslides over Java Island in Indonesia and Honduras. The prototyped early warning system integrates three major components: (1) a susceptibility mapping or hotspot identification component based on a land surface geospatial database (topographical information, maps of soil properties, and local landslide inventory etc.); (2) a satellite-based precipitation monitoring system (http://trmm.gsfc.nasa.gov) and a precipitation forecasting model (i.e. Weather Research Forecast); and (3) a physically-based, rainfall-induced landslide prediction model SLIDE (SLope-Infiltration-Distributed Equilibrium). The system utilizes the modified physical model to calculate a Factor of Safety (FS) that accounts for the contribution of rainfall infiltration and partial saturation to the shear strength of the soil in topographically complex terrains. The system's prediction performance has been evaluated using a local landslide inventory. In Java Island, Indonesia, evaluation of SLIDE modeling results by local news reports shows that the system successfully predicted landslides in correspondence to the time of occurrence of the real landslide events. Further study of SLIDE is implemented in Honduras where Hurricane Mitch triggered widespread landslides in 1998. Results shows within the approximately 1,200 square kilometers study areas, the values of hit rates reached as high as 78% and 75%, while the error indices were 35% and 49%. Despite positive model performance, the SLIDE model is limited in the early warning system by several assumptions including, using general parameter calibration rather than in situ tests and neglecting geologic information. Advantages and limitations of this model will be discussed with respect to future applications of landslide assessment and prediction over large scales. In conclusion, integration of spatially distributed remote sensing precipitation products and in-situ datasets and physical models in this prototype system enable us to further develop a regional early warning tool in the future for forecasting storm-induced landslides.

Boundary-Layer Receptivity and Integrated Transition Prediction

NASA Technical Reports Server (NTRS)

Chang, Chau-Lyan; Choudhari, Meelan

2005-01-01

The adjoint parabold stability equations (PSE) formulation is used to calculate the boundary layer receptivity to localized surface roughness and suction for compressible boundary layers. Receptivity efficiency functions predicted by the adjoint PSE approach agree well with results based on other nonparallel methods including linearized Navier-Stokes equations for both Tollmien-Schlichting waves and crossflow instability in swept wing boundary layers. The receptivity efficiency function can be regarded as the Green's function to the disturbance amplitude evolution in a nonparallel (growing) boundary layer. Given the Fourier transformed geometry factor distribution along the chordwise direction, the linear disturbance amplitude evolution for a finite size, distributed nonuniformity can be computed by evaluating the integral effects of both disturbance generation and linear amplification. The synergistic approach via the linear adjoint PSE for receptivity and nonlinear PSE for disturbance evolution downstream of the leading edge forms the basis for an integrated transition prediction tool. Eventually, such physics-based, high fidelity prediction methods could simulate the transition process from the disturbance generation through the nonlinear breakdown in a holistic manner.

Influence of lake surface area and total phosphorus on annual bluegill growth in small impoundments of central Georgia

USGS Publications Warehouse

Jennings, Cecil A.; Sundmark, Aaron P.

2017-01-01

The relationships between environmental variables and the growth rates of fishes are important and rapidly expanding topics in fisheries ecology. We used an informationtheoretic approach to evaluate the influence of lake surface area and total phosphorus on the age-specific growth rates of Lepomis macrochirus (Bluegill) in 6 small impoundments in central Georgia. We used model averaging to create composite models and determine the relative importance of the variables within each model. Results indicated that surface area was the most important factor in the models predicting growth of Bluegills aged 1–4 years; total phosphorus was also an important predictor for the same age-classes. These results suggest that managers can use water quality and lake morphometry variables to create predictive models specific to their waterbody or region to help develop lake-specific management plans that select for and optimize local-level habitat factors for enhancing Bluegill growth.

Predictors of short-term and long-term incontinence after robot-assisted radical prostatectomy.

PubMed

Shao, I-Hung; Chang, Ying-Hsu; Hou, Chun-Ming; Lin, Zheng-Feng; Wu, Chun-Te

2018-01-01

Purpose To determine retrospectively the prognostic factors for urinary incontinence following robot-assisted radical prostatectomy (RARP). Methods Altogether, 180 patients with localized prostate cancer underwent RARP (same surgeon). Preoperative physical status, disease characteristics, laboratory findings, and surgical technique were recorded and the patients checked 1, 6, 12, and 24 months after RARP regarding their contribution to predicting post-prostatectomy urinary incontinence (PPI). Results Overall, 114 (63.3%) patients had PPI 1 month after RARP and 19 patients (16.0%) at 24 months. Univariate analysis showed that age was a significant factor for predicting PPI at 1 month. PPI predictors at 24 months were age, body mass index, preoperative serum albumin level, previous transurethral resection of the prostate, total operative time, and bladder neck sparing. Multivariate analysis indicated that age and total operative time were significant predictors. Conclusion Older age and longer operative time were highly relevant to short- and long-term PPI occurrence after RARP.

A literature review of the cardiovascular risk-assessment tools: applicability among Asian population.

PubMed

Liau, Siow Yen; Mohamed Izham, M I; Hassali, M A; Shafie, A A

2010-01-01

Cardiovascular diseases, the main causes of hospitalisations and death globally, have put an enormous economic burden on the healthcare system. Several risk factors are associated with the occurrence of cardiovascular events. At the heart of efficient prevention of cardiovascular disease is the concept of risk assessment. This paper aims to review the available cardiovascular risk-assessment tools and its applicability in predicting cardiovascular risk among Asian populations. A systematic search was performed using keywords as MeSH and Boolean terms. A total of 25 risk-assessment tools were identified. Of these, only two risk-assessment tools (8%) were derived from an Asian population. These risk-assessment tools differ in various ways, including characteristics of the derivation sample, type of study, time frame of follow-up, end points, statistical analysis and risk factors included. Very few cardiovascular risk-assessment tools were developed in Asian populations. In order to accurately predict the cardiovascular risk of our population, there is a need to develop a risk-assessment tool based on local epidemiological data.

Climate and Non-Climate Drivers of Dengue Epidemics in Southern Coastal Ecuador

PubMed Central

Stewart-Ibarra, Anna M.; Lowe, Rachel

2013-01-01

We report a statistical mixed model for assessing the importance of climate and non-climate drivers of interannual variability in dengue fever in southern coastal Ecuador. Local climate data and Pacific sea surface temperatures (Oceanic Niño Index [ONI]) were used to predict dengue standardized morbidity ratios (SMRs; 1995–2010). Unobserved confounding factors were accounted for using non-structured yearly random effects. We found that ONI, rainfall, and minimum temperature were positively associated with dengue, with more cases of dengue during El Niño events. We assessed the influence of non-climatic factors on dengue SMR using a subset of data (2001–2010) and found that the percent of households with Aedes aegypti immatures was also a significant predictor. Our results indicate that monitoring the climate and non-climate drivers identified in this study could provide some predictive lead for forecasting dengue epidemics, showing the potential to develop a dengue early-warning system in this region. PMID:23478584

LocTree2 predicts localization for all domains of life

PubMed Central

Goldberg, Tatyana; Hamp, Tobias; Rost, Burkhard

2012-01-01

Motivation: Subcellular localization is one aspect of protein function. Despite advances in high-throughput imaging, localization maps remain incomplete. Several methods accurately predict localization, but many challenges remain to be tackled. Results: In this study, we introduced a framework to predict localization in life's three domains, including globular and membrane proteins (3 classes for archaea; 6 for bacteria and 18 for eukaryota). The resulting method, LocTree2, works well even for protein fragments. It uses a hierarchical system of support vector machines that imitates the cascading mechanism of cellular sorting. The method reaches high levels of sustained performance (eukaryota: Q18=65%, bacteria: Q6=84%). LocTree2 also accurately distinguishes membrane and non-membrane proteins. In our hands, it compared favorably with top methods when tested on new data. Availability: Online through PredictProtein (predictprotein.org); as standalone version at http://www.rostlab.org/services/loctree2. Contact: localization@rostlab.org Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:22962467

Groundwater source contamination mechanisms: Physicochemical profile clustering, risk factor analysis and multivariate modelling

NASA Astrophysics Data System (ADS)

Hynds, Paul; Misstear, Bruce D.; Gill, Laurence W.; Murphy, Heather M.

2014-04-01

An integrated domestic well sampling and "susceptibility assessment" programme was undertaken in the Republic of Ireland from April 2008 to November 2010. Overall, 211 domestic wells were sampled, assessed and collated with local climate data. Based upon groundwater physicochemical profile, three clusters have been identified and characterised by source type (borehole or hand-dug well) and local geological setting. Statistical analysis indicates that cluster membership is significantly associated with the prevalence of bacteria (p = 0.001), with mean Escherichia coli presence within clusters ranging from 15.4% (Cluster-1) to 47.6% (Cluster-3). Bivariate risk factor analysis shows that on-site septic tank presence was the only risk factor significantly associated (p < 0.05) with bacterial presence within all clusters. Point agriculture adjacency was significantly associated with both borehole-related clusters. Well design criteria were associated with hand-dug wells and boreholes in areas characterised by high permeability subsoils, while local geological setting was significant for hand-dug wells and boreholes in areas dominated by low/moderate permeability subsoils. Multivariate susceptibility models were developed for all clusters, with predictive accuracies of 84% (Cluster-1) to 91% (Cluster-2) achieved. Septic tank setback was a common variable within all multivariate models, while agricultural sources were also significant, albeit to a lesser degree. Furthermore, well liner clearance was a significant factor in all models, indicating that direct surface ingress is a significant well contamination mechanism. Identification and elucidation of cluster-specific contamination mechanisms may be used to develop improved overall risk management and wellhead protection strategies, while also informing future remediation and maintenance efforts.

Predicting local field potentials with recurrent neural networks.

PubMed

Kim, Louis; Harer, Jacob; Rangamani, Akshay; Moran, James; Parks, Philip D; Widge, Alik; Eskandar, Emad; Dougherty, Darin; Chin, Sang Peter

2016-08-01

We present a Recurrent Neural Network using LSTM (Long Short Term Memory) that is capable of modeling and predicting Local Field Potentials. We train and test the network on real data recorded from epilepsy patients. We construct networks that predict multi-channel LFPs for 1, 10, and 100 milliseconds forward in time. Our results show that prediction using LSTM outperforms regression when predicting 10 and 100 millisecond forward in time.

High-powered microwave ablation of larger hepatocellular carcinoma: evaluation of recurrence rate and factors related to recurrence.

PubMed

Zhang, N N; Lu, W; Cheng, X J; Liu, J Y; Zhou, Y H; Li, F

2015-11-01

To evaluate the safety and efficacy of high-powered (80-100 W) percutaneous microwave ablation (MWA) at a frequency of 2450±10 MHz for treating larger hepatocellular carcinoma (HCC) and to predict the risk factors of local recurrence after high-powered MWA. The study was approved by the Institutional Review Board, and informed consent was waived because of the retrospective study design. Forty-five patients with a total of 60 lesions received high-power (80-100 W) MWA at a frequency of 2450±10 MHz through a percutaneous approach that was guided by ultrasound. Of the 60 lesions with a maximum tumour measuring 3-8 cm, 46 lesions were 3-5 cm and 14 were 5-8 cm. The complete ablation rates, local recurrence rates, complications, and short-term survival were analysed. Ten possible risk factors for local recurrence were analysed. The complete ablation rates were 82.61% for the first ablation and 100% for the second ablation for 3-5 cm lesions. The complete ablation rates were 64.29% (82.61% versus 64.29%, p=0.037) for the first ablation and 85.71% (100% versus 85.71%, p=0.055) for the second ablation for 5-8 cm lesions. Local recurrence was observed in 11 out of the 45 (24.44%) successfully treated patients. The 1-year and 2-year survival rates were 95.56% (43/45) and 86.67% (39/45), respectively. No procedure-related mortality was observed and no major bleeding, liver rupture, or liver abscesses occurred. Univariate analysis showed that a positive correlation existed between the number of lesions (p=0.022), proximity to the risk area (p=0.001), pre-ablation alpha-fetoprotein (AFP) levels (p=0.025), hepatitis B virus (HBV)-DNA replication (p=0.027) and local recurrence. Multivariate analysis identified HBV-DNA (p=0.031) and proximity to the risk area (p=0.039) as the independent prognosis factors causing postoperative HCC local recurrence. High-powered MWA of larger hepatocellular carcinomas appears to be a safe and effective treatment. HBV-DNA and proximity to the risk area appear to be independent predictors of local tumour recurrence. Copyright © 2015 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Semi-supervised protein subcellular localization.

PubMed

Xu, Qian; Hu, Derek Hao; Xue, Hong; Yu, Weichuan; Yang, Qiang

2009-01-30

Protein subcellular localization is concerned with predicting the location of a protein within a cell using computational method. The location information can indicate key functionalities of proteins. Accurate predictions of subcellular localizations of protein can aid the prediction of protein function and genome annotation, as well as the identification of drug targets. Computational methods based on machine learning, such as support vector machine approaches, have already been widely used in the prediction of protein subcellular localization. However, a major drawback of these machine learning-based approaches is that a large amount of data should be labeled in order to let the prediction system learn a classifier of good generalization ability. However, in real world cases, it is laborious, expensive and time-consuming to experimentally determine the subcellular localization of a protein and prepare instances of labeled data. In this paper, we present an approach based on a new learning framework, semi-supervised learning, which can use much fewer labeled instances to construct a high quality prediction model. We construct an initial classifier using a small set of labeled examples first, and then use unlabeled instances to refine the classifier for future predictions. Experimental results show that our methods can effectively reduce the workload for labeling data using the unlabeled data. Our method is shown to enhance the state-of-the-art prediction results of SVM classifiers by more than 10%.

Quark-hadron duality and parity violating asymmetry of electroweak reactions in the {delta} region

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

Matsui, K.; Sato, T.; Lee, T.-S.H.

2005-08-01

A dynamical model [T. Sato and T.-S. H. Lee, Phys. Rev. C 54, 2660 (1996); 63, 055201 (2001); T. Sato, D. Uno, and T.-S. H. Lee, ibid. 67, 065201 (2003)] of electroweak pion production reactions in the {delta}(1232) region has been extended to include the neutral current contributions for examining the local quark-hadron duality in neutrino-induced reactions and for investigating how the axial N-{delta} form factor can be determined by the parity violating asymmetry of N(e{sup {yields}},e{sup '}) reactions. We first show that the recent data of (e,e{sup '}) structure functions F{sub 1} and F{sub 2}, which exhibit the quark-hadronmore » duality, are in good agreement with our predictions. For possible future experimental tests, we then predict that the structure functions F{sub 1},F{sub 2}, and F{sub 3} for ({nu},e) and ({nu},{nu}{sup '}) processes also show the similar quark-hadron duality. The spin-dependent structure functions g{sub 1} and g{sub 2} of (e,e{sup '}) have also been calculated from our model. It is found that the local quark-hadron duality is not seen in the calculated g{sub 1} and g{sub 2}, while our results for g{sub 1} and some polarization observables associated with the exclusive p(e{sup {yields}},e{sup '}{pi}) and p{sup {yields}}(e{sup {yields}},e{sup '}{pi}) reactions are in reasonably good agreement with the recent data. In the study of parity violating asymmetry A of N(e{sup {yields}},e{sup '}) reactions, the relative importance between the nonresonant mechanisms and the {delta} excitation is investigated by taking into account the unitarity condition. Predictions are made for using the data of A to test the axial N-{delta} form factors determined previously in the studies of N({nu}{sub {mu}},{mu}{sup -}{pi}) reactions. The predicted asymmetry A are also compared with the parton model predictions for future experimental investigations of quark-hadron duality.« less

Protein subcellular localization prediction using multiple kernel learning based support vector machine.

PubMed

Hasan, Md Al Mehedi; Ahmad, Shamim; Molla, Md Khademul Islam

2017-03-28

Predicting the subcellular locations of proteins can provide useful hints that reveal their functions, increase our understanding of the mechanisms of some diseases, and finally aid in the development of novel drugs. As the number of newly discovered proteins has been growing exponentially, which in turns, makes the subcellular localization prediction by purely laboratory tests prohibitively laborious and expensive. In this context, to tackle the challenges, computational methods are being developed as an alternative choice to aid biologists in selecting target proteins and designing related experiments. However, the success of protein subcellular localization prediction is still a complicated and challenging issue, particularly, when query proteins have multi-label characteristics, i.e., if they exist simultaneously in more than one subcellular location or if they move between two or more different subcellular locations. To date, to address this problem, several types of subcellular localization prediction methods with different levels of accuracy have been proposed. The support vector machine (SVM) has been employed to provide potential solutions to the protein subcellular localization prediction problem. However, the practicability of an SVM is affected by the challenges of selecting an appropriate kernel and selecting the parameters of the selected kernel. To address this difficulty, in this study, we aimed to develop an efficient multi-label protein subcellular localization prediction system, named as MKLoc, by introducing multiple kernel learning (MKL) based SVM. We evaluated MKLoc using a combined dataset containing 5447 single-localized proteins (originally published as part of the Höglund dataset) and 3056 multi-localized proteins (originally published as part of the DBMLoc set). Note that this dataset was used by Briesemeister et al. in their extensive comparison of multi-localization prediction systems. Finally, our experimental results indicate that MKLoc not only achieves higher accuracy than a single kernel based SVM system but also shows significantly better results than those obtained from other top systems (MDLoc, BNCs, YLoc+). Moreover, MKLoc requires less computation time to tune and train the system than that required for BNCs and single kernel based SVM.

Local thermal sensation modeling-a review on the necessity and availability of local clothing properties and local metabolic heat production.

PubMed

Veselá, S; Kingma, B R M; Frijns, A J H

2017-03-01

Local thermal sensation modeling gained importance due to developments in personalized and locally applied heating and cooling systems in office environments. The accuracy of these models depends on skin temperature prediction by thermophysiological models, which in turn rely on accurate environmental and personal input data. Environmental parameters are measured or prescribed, but personal factors such as clothing properties and metabolic rates have to be estimated. Data for estimating the overall values of clothing properties and metabolic rates are available in several papers and standards. However, local values are more difficult to retrieve. For local clothing, this study revealed that full and consistent data sets are not available in the published literature for typical office clothing sets. Furthermore, the values for local heat production were not verified for characteristic office activities, but were adapted empirically. Further analyses showed that variations in input parameters can lead to local skin temperature differences (∆T skin,loc  = 0.4-4.4°C). These differences can affect the local sensation output, where ∆T skin,loc  = 1°C is approximately one step on a 9-point thermal sensation scale. In conclusion, future research should include a systematic study of local clothing properties and the development of feasible methods for measuring and validating local heat production. © 2016 The Authors. Indoor Air published by John Wiley & Sons Ltd.

Streamflow Prediction based on Chaos Theory

NASA Astrophysics Data System (ADS)

Li, X.; Wang, X.; Babovic, V. M.

2015-12-01

Chaos theory is a popular method in hydrologic time series prediction. Local model (LM) based on this theory utilizes time-delay embedding to reconstruct the phase-space diagram. For this method, its efficacy is dependent on the embedding parameters, i.e. embedding dimension, time lag, and nearest neighbor number. The optimal estimation of these parameters is thus critical to the application of Local model. However, these embedding parameters are conventionally estimated using Average Mutual Information (AMI) and False Nearest Neighbors (FNN) separately. This may leads to local optimization and thus has limitation to its prediction accuracy. Considering about these limitation, this paper applies a local model combined with simulated annealing (SA) to find the global optimization of embedding parameters. It is also compared with another global optimization approach of Genetic Algorithm (GA). These proposed hybrid methods are applied in daily and monthly streamflow time series for examination. The results show that global optimization can contribute to the local model to provide more accurate prediction results compared with local optimization. The LM combined with SA shows more advantages in terms of its computational efficiency. The proposed scheme here can also be applied to other fields such as prediction of hydro-climatic time series, error correction, etc.

Real-time prediction of respiratory motion based on a local dynamic model in an augmented space

NASA Astrophysics Data System (ADS)

Hong, S.-M.; Jung, B.-H.; Ruan, D.

2011-03-01

Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively low observation rate. Sensitivity analysis indicates its robustness toward the choice of parameters. Its simplicity, robustness and low computation cost makes the proposed local dynamic model an attractive tool for real-time prediction with system latencies below 0.4 s.

Real-time prediction of respiratory motion based on a local dynamic model in an augmented space.

PubMed

Hong, S-M; Jung, B-H; Ruan, D

2011-03-21

Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively low observation rate. Sensitivity analysis indicates its robustness toward the choice of parameters. Its simplicity, robustness and low computation cost makes the proposed local dynamic model an attractive tool for real-time prediction with system latencies below 0.4 s.

Wind power prediction based on genetic neural network

NASA Astrophysics Data System (ADS)

Zhang, Suhan

2017-04-01

The scale of grid connected wind farms keeps increasing. To ensure the stability of power system operation, make a reasonable scheduling scheme and improve the competitiveness of wind farm in the electricity generation market, it's important to accurately forecast the short-term wind power. To reduce the influence of the nonlinear relationship between the disturbance factor and the wind power, the improved prediction model based on genetic algorithm and neural network method is established. To overcome the shortcomings of long training time of BP neural network and easy to fall into local minimum and improve the accuracy of the neural network, genetic algorithm is adopted to optimize the parameters and topology of neural network. The historical data is used as input to predict short-term wind power. The effectiveness and feasibility of the method is verified by the actual data of a certain wind farm as an example.

Analysis of SEER Adenosquamous Carcinoma Data to Identify Cause Specific Survival Predictors and Socioeconomic Disparities.

PubMed

Cheung, Rex

2016-01-01

This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) adenosquamous carcinoma data to identify predictive models and potential disparities in outcome. This study analyzed socio-economic, staging and treatment factors available in the SEER database for adenosquamous carcinoma. For the risk modeling, each factor was fitted by a generalized linear model to predict the cause specific survival. An area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. A total of 20,712 patients diagnosed from 1973 to 2009 were included in this study. The mean follow up time (S.D.) was 54.2 (78.4) months. Some 2/3 of the patients were female. The mean (S.D.) age was 63 (13.8) years. SEER stage was the most predictive factor of outcome (ROC area of 0.71). 13.9% of the patients were un-staged and had risk of cause specific death of 61.3% that was higher than the 45.3% risk for the regional disease and lower than the 70.3% for metastatic disease. Sex, site, radiotherapy, and surgery had ROC areas of about 0.55-0.65. Rural residence and race contributed to socioeconomic disparity for treatment outcome. Radiotherapy was underused even with localized and regional stages when the intent was curative. This under use was most pronounced in older patients. Anatomic stage was predictive and useful in treatment selection. Under-staging may have contributed to poor outcome.

Use the predictive models to explore the key factors affecting phytoplankton succession in Lake Erhai, China.

PubMed

Zhu, Rong; Wang, Huan; Chen, Jun; Shen, Hong; Deng, Xuwei

2018-01-01

Increasing algae in Lake Erhai has resulted in frequent blooms that have not only led to water ecosystem degeneration but also seriously influenced the quality of the water supply and caused extensive damage to the local people, as the lake is a water resource for Dali City. Exploring the key factors affecting phytoplankton succession and developing predictive models with easily detectable parameters for phytoplankton have been proven to be practical ways to improve water quality. To this end, a systematic survey focused on phytoplankton succession was conducted over 2 years in Lake Erhai. The data from the first study year were used to develop predictive models, and the data from the second year were used for model verification. The seasonal succession of phytoplankton in Lake Erhai was obvious. The dominant groups were Cyanobacteria in the summer, Chlorophyta in the autumn and Bacillariophyta in the winter. The developments and verification of predictive models indicated that compared to phytoplankton biomass, phytoplankton density is more effective for estimating phytoplankton variation in Lake Erhai. CCA (canonical correlation analysis) indicated that TN (total nitrogen), TP (total phosphorus), DO (dissolved oxygen), SD (Secchi depth), Cond (conductivity), T (water temperature), and ORP (oxidation reduction potential) had significant influences (p < 0.05) on the phytoplankton community. The CCA of the dominant species found that Microcystis was significantly influenced by T. The dominant Chlorophyta, Psephonema aenigmaticum and Mougeotia, were significantly influenced by TN. All results indicated that TN and T were the two key factors driving phytoplankton succession in Lake Erhai.

Prospective study of the evolution of blood lymphoid immune parameters during dacarbazine chemotherapy in metastatic and locally advanced melanoma patients.

PubMed

Mignot, Grégoire; Hervieu, Alice; Vabres, Pierre; Dalac, Sophie; Jeudy, Geraldine; Bel, Blandine; Apetoh, Lionel; Ghiringhelli, François

2014-01-01

The importance of immune responses in the control of melanoma growth is well known. However, the implication of these antitumor immune responses in the efficacy of dacarbazine, a cytotoxic drug classically used in the treatment of melanoma, remains poorly understood in humans. In this prospective observational study, we performed an immunomonitoring of eleven metastatic or locally advanced patients treated with dacarbazine as a first line of treatment. We assessed by flow cytometry lymphoid populations and their activation state; we also isolated NK cells to perform in vitro cytotoxicity tests. We found that chemotherapy induces lymphopenia and that a significantly higher numbers of naïve CD4+ T cells and lower proportion of Treg before chemotherapy are associated with disease control after dacarbazine treatment. Interestingly, NK cell cytotoxicity against dacarbazine-pretreated melanoma cells is only observed in NK cells from patients who achieved disease control. Together, our data pinpoint that some immune factors could help to predict the response of melanoma patients to dacarbazine. Future larger scale studies are warranted to test their validity as prediction markers.

Pics d'accélération du mouvement sismique observés lors du séisme de Chichi à Taiwan : application à l'estimation de l'aléa sismiqueAnalysis of peak ground accelerations during the Chichi earthquake, Taiwan: application to seismic hazard evaluation

NASA Astrophysics Data System (ADS)

Chang, Tsui-Yu; Cotton, Fabrice; Angelier, Jacques; Shin, Tzay-Chyn

2001-07-01

Attenuation laws are widely used in order to estimate the peak ground acceleration that may occur at a given locality during an earthquake, for hazard evaluation purposes. However, these simplified laws should be regarded acceptable only in the first approximation, because numerous significant parameters at the local and regional scales are often ignored. We examined the relationship between distance and peak acceleration based on examples from the dense accelerometric network of Taiwan, specifically for the Chichi destructive earthquake. We thus observed significant discrepancies between the predicted and observed accelerations, resulting from (1) near-field saturation, (2) amplification in sedimentary basins, and (3) hanging wall effect. We mapped the residual accelerations (difference between observed and predicted peak ground accelerations). This highlights the role of the regional structure, independently revealed by the geological analysis, as a significant factor that controls the transmission of the seismic accelerations.

Earthquake Shaking - Finding the "Hot Spots"

USGS Publications Warehouse

Field, Edward; Jones, Lucile; Jordan, Tom; Benthien, Mark; Wald, Lisa

2001-01-01

A new Southern California Earthquake Center study has quantified how local geologic conditions affect the shaking experienced in an earthquake. The important geologic factors at a site are softness of the rock or soil near the surface and thickness of the sediments above hard bedrock. Even when these 'site effects' are taken into account, however, each earthquake exhibits unique 'hotspots' of anomalously strong shaking. Better predictions of strong ground shaking will therefore require additional geologic data and more comprehensive computer simulations of individual earthquakes.

Predictability of weather and climate in a coupled ocean-atmosphere model: A dynamical systems approach. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Nese, Jon M.

1989-01-01

A dynamical systems approach is used to quantify the instantaneous and time-averaged predictability of a low-order moist general circulation model. Specifically, the effects on predictability of incorporating an active ocean circulation, implementing annual solar forcing, and asynchronously coupling the ocean and atmosphere are evaluated. The predictability and structure of the model attractors is compared using the Lyapunov exponents, the local divergence rates, and the correlation, fractal, and Lyapunov dimensions. The Lyapunov exponents measure the average rate of growth of small perturbations on an attractor, while the local divergence rates quantify phase-spatial variations of predictability. These local rates are exploited to efficiently identify and distinguish subtle differences in predictability among attractors. In addition, the predictability of monthly averaged and yearly averaged states is investigated by using attractor reconstruction techniques.

Machine learning prediction for classification of outcomes in local minimisation

NASA Astrophysics Data System (ADS)

Das, Ritankar; Wales, David J.

2017-01-01

Machine learning schemes are employed to predict which local minimum will result from local energy minimisation of random starting configurations for a triatomic cluster. The input data consists of structural information at one or more of the configurations in optimisation sequences that converge to one of four distinct local minima. The ability to make reliable predictions, in terms of the energy or other properties of interest, could save significant computational resources in sampling procedures that involve systematic geometry optimisation. Results are compared for two energy minimisation schemes, and for neural network and quadratic functions of the inputs.

Link prediction based on local community properties

NASA Astrophysics Data System (ADS)

Yang, Xu-Hua; Zhang, Hai-Feng; Ling, Fei; Cheng, Zhi; Weng, Guo-Qing; Huang, Yu-Jiao

2016-09-01

The link prediction algorithm is one of the key technologies to reveal the inherent rule of network evolution. This paper proposes a novel link prediction algorithm based on the properties of the local community, which is composed of the common neighbor nodes of any two nodes in the network and the links between these nodes. By referring to the node degree and the condition of assortativity or disassortativity in a network, we comprehensively consider the effect of the shortest path and edge clustering coefficient within the local community on node similarity. We numerically show the proposed method provide good link prediction results.

Performance predictions for a parabolic localizer antenna on Runway 28R - San Francisco Airport.

DOT National Transportation Integrated Search

1973-06-01

The TSC ILS localizer model is used to predict the performance of the Texas Instruments "wide aperture" parabolic antenna as a localizer system for runway 28R at San Francisco Airport. Course derogation caused by the new American Airlines hangar is c...

Predictors of Satisfaction With Doctor and Nurse Communication: A National Study.

PubMed

McFarland, Daniel C; Johnson Shen, Megan; Holcombe, Randall F

2017-10-01

Prior research indicates that effective communication between medical providers and patients is associated with a number of positive patient outcomes, yet little research has examined how ecological factors (e.g., hospital size, local demographics) influence patients' reported satisfaction with doctor and nurse communication. Given the current emphasis on improving patient satisfaction in hospitals across the United States, understanding these factors is critical to interpreting patient satisfaction and improving patient-centered communication, particularly in diverse and dense populations. As such, this study examined county-level data including population density, population diversity, and hospital structural factors as predictors of patient satisfaction with doctor and nurse communication. Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS), U.S. Census data, and number of hospital beds were obtained from publicly available Hospital Compare, U.S. Census, and American Hospital Directory websites, respectively. Multivariate regression modeling was performed for the individual dimensions of HCAHPS scores assessing doctor and nurse communication. Standardized partial regression coefficients were used to assess strengths of county-level predictors. County-level factors accounted for 30% and 16% of variability in patient satisfaction with doctor and nurse communication, respectively. College education (β = 0.45) and White ethnicity (β = 0.25) most strongly predicted a favorable rating of doctor and nurse communication, respectively. Primary language (non-English speaking; β = -0.50) most strongly predicted an unfavorable rating of doctor communication, while number of hospital beds (β = -0.16) and foreign-born (β = -0.16) most strongly predicted an unfavorable rating of nurse communication. County-level predictors should be considered when interpreting patient satisfaction with doctor and nurse communication and designing multilevel patient-centered communication improvement strategies. Discordant findings with individual-level factors should be explored further.

Prognostic Impact of Indocyanine Green Plasma Disappearance Rate in Hepatocellular Carcinoma Patients after Radiofrequency Ablation: A Prognostic Nomogram Study

PubMed Central

Azumi, Motoi; Suda, Takeshi; Terai, Shuji; Akazawa, Kouhei

2017-01-01

Objective Radiofrequency ablation has been used widely for the local ablation of hepatocellular carcinoma, particularly in its early stages. The study aim was to identify significant prognostic factors and develop a predictive nomogram for patients with hepatocellular carcinoma who have undergone radiofrequency ablation. We also developed the formula to predict the probability of 3- and 5-year overall survival based on clinical variables. Methods We retrospectively studied 96 consecutive patients with hepatocellular carcinoma who had undergone radiofrequency ablation as a first-line treatment. Independent and significant factors affecting the overall survival were selected using a Cox proportional hazards model, and a prognostic nomogram was developed based on these factors. The predictive accuracy of the nomogram was determined by Harrell's concordance index and compared with the Cancer of the Liver Italian Program score and Japan Integrated Staging score. Results A multivariate analysis revealed that age, indocyanine green plasma disappearance rate, and log(des-gamma-carboxy prothrombin) level were independent and significant factors influencing the overall survival. The nomogram was based on these three factors. The mean concordance index of the nomogram was 0.74±0.08, which was significantly better than that of conventional staging systems using the Cancer of the Liver Italian Program score (0.54±0.03) and Japan Integrated Staging score (0.59±0.07). Conclusion This study suggested that the indocyanine green plasma disappearance rate and age at radiofrequency ablation (RFA) and des-gamma-carboxy-prothrombin (DCP) are good predictors of the prognosis in hepatocellular carcinoma patients after radiofrequency ablation. We successfully developed a nomogram using obtainable variables before treatment. PMID:28458303

Prognostic Impact of Indocyanine Green Plasma Disappearance Rate in Hepatocellular Carcinoma Patients after Radiofrequency Ablation: A Prognostic Nomogram Study.

PubMed

Azumi, Motoi; Suda, Takeshi; Terai, Shuji; Akazawa, Kouhei

2017-01-01

Objective Radiofrequency ablation has been used widely for the local ablation of hepatocellular carcinoma, particularly in its early stages. The study aim was to identify significant prognostic factors and develop a predictive nomogram for patients with hepatocellular carcinoma who have undergone radiofrequency ablation. We also developed the formula to predict the probability of 3- and 5-year overall survival based on clinical variables. Methods We retrospectively studied 96 consecutive patients with hepatocellular carcinoma who had undergone radiofrequency ablation as a first-line treatment. Independent and significant factors affecting the overall survival were selected using a Cox proportional hazards model, and a prognostic nomogram was developed based on these factors. The predictive accuracy of the nomogram was determined by Harrell's concordance index and compared with the Cancer of the Liver Italian Program score and Japan Integrated Staging score. Results A multivariate analysis revealed that age, indocyanine green plasma disappearance rate, and log (des-gamma-carboxy prothrombin) level were independent and significant factors influencing the overall survival. The nomogram was based on these three factors. The mean concordance index of the nomogram was 0.74±0.08, which was significantly better than that of conventional staging systems using the Cancer of the Liver Italian Program score (0.54±0.03) and Japan Integrated Staging score (0.59±0.07). Conclusion This study suggested that the indocyanine green plasma disappearance rate and age at radiofrequency ablation (RFA) and des-gamma-carboxy-prothrombin (DCP) are good predictors of the prognosis in hepatocellular carcinoma patients after radiofrequency ablation. We successfully developed a nomogram using obtainable variables before treatment.

Evaluation of Vascular Endothelial Growth Factor as a Prognostic Marker for Local Relapse in Early-Stage Breast Cancer Patients Treated With Breast-Conserving Therapy

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

Moran, Meena S., E-mail: meena.moran@yale.edu; Yang Qifeng; Department of Breast Surgery, Qilu Hospital, Shandong University, Jinan, People's Republic of China

2011-12-01

Purpose: Vascular endothelial growth factor (VEGF) is an important protein involved in the process of angiogenesis that has been found to correlate with relapse-free and overall survival in breast cancer, predominantly in locally advanced and metastatic disease. A paucity of data is available on the prognostic implications of VEGF in early-stage breast cancer; specifically, its prognostic value for local relapse after breast-conserving therapy (BCT) is largely unknown. The purpose of our study was to assess VEGF expression in a cohort of early-stage breast cancer patients treated with BCT and to correlate the clinical and pathologic features and outcomes with overexpressionmore » of VEGF. Methods and Materials: After obtaining institutional review board approval, the paraffin specimens of 368 patients with early-stage breast cancer treated with BCT between 1975 and 2005 were constructed into tissue microarrays with twofold redundancy. The tissue microarrays were stained for VEGF and read by a trained pathologist, who was unaware of the clinical details, as positive or negative according the standard guidelines. The clinical and pathologic data, long-term outcomes, and results of VEGF staining were analyzed. Results: The median follow-up for the entire cohort was 6.5 years. VEGF expression was positive in 56 (15%) of the 368 patients. Although VEGF expression did not correlate with age at diagnosis, tumor size, nodal status, histologic type, family history, estrogen receptor/progesterone receptor status, or HER-2 status, a trend was seen toward increased VEGF expression in the black cohort (26% black vs. 13% white, p = .068). Within the margin-negative cohort, VEGF did not predict for local relapse-free survival (RFS) (96% vs. 95%), nodal RFS (100% vs. 100%), distant metastasis-free survival (91% vs. 92%), overall survival (92% vs. 97%), respectively (all p >.05). Subset analysis revealed that VEGF was highly predictive of local RFS in node-positive, margin-negative patients (86% vs. 100%, p = .029) on univariate analysis, but it did not retain its significance on multivariate analysis (hazard ratio, 2.52; 95% confidence interval, 0.804-7.920, p = .113). No other subgroups were identified in which a correlation was found between VEGF expression and local relapse. Conclusion: To our knowledge, our study is the first to assess the prognostic value of VEGF with the endpoint of local relapse in early-stage breast cancer treated with BCT, an important question given the recent increased use of targeted antiangiogenic agents in early-stage breast cancer. Our study results suggest that VEGF is not an independent predictor of local RFS after BCT, but additional, larger studies specifically analyzing the endpoint of VEGF and local relapse are warranted.« less

Spatial, seasonal, and source variability in the stable oxygen and hydrogen isotopic composition of tap waters throughout the USA

USGS Publications Warehouse

Landwehr, Jurate M.; Coplen, Tyler B.; Stewart, David W.

2013-01-01

To assess spatial, seasonal, and source variability in stable isotopic composition of human drinking waters throughout the entire USA, we have constructed a database of δ18O and δ2H of US tap waters. An additional purpose was to create a publicly available dataset useful for evaluating the forensic applicability of these isotopes for human tissue source geolocation. Samples were obtained at 349 sites, from diverse population centres, grouped by surface hydrologic units for regional comparisons. Samples were taken concurrently during two contrasting seasons, summer and winter. Source supply (surface, groundwater, mixed, and cistern) and system (public and private) types were noted. The isotopic composition of tap waters exhibits large spatial and regional variation within each season as well as significant at-site differences between seasons at many locations, consistent with patterns found in environmental (river and precipitation) waters deriving from hydrologic processes influenced by geographic factors. However, anthropogenic factors, such as the population of a tap’s surrounding community and local availability from diverse sources, also influence the isotopic composition of tap waters. Even within a locale as small as a single metropolitan area, tap waters with greatly differing isotopic compositions can be found, so that tap water within a region may not exhibit the spatial or temporal coherence predicted for environmental water. Such heterogeneities can be confounding factors when attempting forensic inference of source water location, and they underscore the necessity of measurements, not just predictions, with which to characterize the isotopic composition of regional tap waters. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.

Spatial epidemiological techniques in cholera mapping and analysis towards a local scale predictive modelling

NASA Astrophysics Data System (ADS)

Rasam, A. R. A.; Ghazali, R.; Noor, A. M. M.; Mohd, W. M. N. W.; Hamid, J. R. A.; Bazlan, M. J.; Ahmad, N.

2014-02-01

Cholera spatial epidemiology is the study of the spread and control of the disease spatial pattern and epidemics. Previous studies have shown that multi-factorial causation such as human behaviour, ecology and other infectious risk factors influence the disease outbreaks. Thus, understanding spatial pattern and possible interrelationship factors of the outbreaks are crucial to be explored an in-depth study. This study focuses on the integration of geographical information system (GIS) and epidemiological techniques in exploratory analyzing the cholera spatial pattern and distribution in the selected district of Sabah. Spatial Statistic and Pattern tools in ArcGIS and Microsoft Excel software were utilized to map and analyze the reported cholera cases and other data used. Meanwhile, cohort study in epidemiological technique was applied to investigate multiple outcomes of the disease exposure. The general spatial pattern of cholera was highly clustered showed the disease spread easily at a place or person to others especially 1500 meters from the infected person and locations. Although the cholera outbreaks in the districts are not critical, it could be endemic at the crowded areas, unhygienic environment, and close to contaminated water. It was also strongly believed that the coastal water of the study areas has possible relationship with the cholera transmission and phytoplankton bloom since the areas recorded higher cases. GIS demonstrates a vital spatial epidemiological technique in determining the distribution pattern and elucidating the hypotheses generating of the disease. The next research would be applying some advanced geo-analysis methods and other disease risk factors for producing a significant a local scale predictive risk model of the disease in Malaysia.

Predicting the performance of a strategic alliance: an analysis of the Community Clinical Oncology Program.

PubMed

Kaluzny, A D; Lacey, L M; Warnecke, R; Hynes, D M; Morrissey, J; Ford, L; Sondik, E

1993-06-01

This study is designed to examine the effects of environment and structure of the Community Clinical Oncology Program (CCOP) on performance as measured by patient accrual to National Cancer Institute (NCI)-approved treatment protocols. Data and analysis are part of a larger evaluation of the NCI Community Clinical Oncology Program during its second funding cycle, June 1987-May 1990. Data, taken from primary and secondary sources, included a survey of selected informants in CCOPs and research bases, CCOP grant applications, CCOP annual progress reports, and site visits to a subsample of CCOPs (N = 20) and research bases (N = 5). Accrual data were obtained from NCI records. Analysis involved three complementary sets of factors: the local health care resources environment available to the CCOP, the larger policy environment as reflected by the relationship of the CCOP to selected research bases and the NCI, and the operational structure of the CCOP itself. A hierarchical model examined the separate and cumulative effects of local and policy environment and structure on performance. Other things equal, the primary predictors of treatment accrual were: (1) the larger policy environment, as measured by the attendance of nurses at research base meetings; and (2) operational structure, as measured by the number and character of components within participating CCOPs and the number of hours per week worked by data managers. These factors explained 73 percent of the total variance in accrual performance. Findings suggest criteria for selecting the types of organizations to participate in the alliance, as well as for establishing guidelines for managing such alliances. A future challenge is to determine the extent to which factors predicting accrual to cancer treatment clinical trials are equally important as predictors of accrual to cancer prevention and control trials.

Localized primary gastrointestinal diffuse large B cell lymphoma received a surgical approach: an analysis of prognostic factors and comparison of staging systems in 101 patients from a single institution.

PubMed

Zhang, Shengting; Wang, Li; Yu, Dong; Shen, Yang; Cheng, Shu; Zhang, Li; Qian, Ying; Shen, Zhixiang; Li, Qinyu; Zhao, Weili

2015-08-15

Diffuse large B cell lymphoma (DLBCL) represents the most common histological subtype of primary gastrointestinal lymphoma and is a heterogeneous group of disease. Prognostic characterization of individual patients is an essential prerequisite for a proper risk-based therapeutic choice. Clinical and pathological prognostic factors were identified, and predictive value of four previously described prognostic systems were assessed in 101 primary gastrointestinal DLBCL (PG-DLBCL) patients with localized disease, including Ann Arbor staging with Musshoff modification, International Prognostic Index (IPI), Lugano classification, and Paris staging system. Univariate factors correlated with inferior survival time were clinical parameters [age>60 years old, multiple extranodal/gastrointestinal involvement, elevated serum lactate dehydrogenase and β2-microglobulin, and decreased serum albumin], as well as pathological parameters (invasion depth beyond serosa, involvement of regional lymph node or adjacent tissue, Ki-67 index, and Bcl-2 expression). Major independent variables of adverse outcome indicated by multivariate analysis were multiple gastrointestinal involvement. In patients unfit for Rituximab but received surgery, radical surgery significantly prolonged the survival time, comparing with alleviative surgery. Addition of Rituximab could overcome the negative prognostic effect of alleviative surgery. Among the four prognostic systems, IPI and Lugano classification clearly separated patients into different risk groups. IPI was able to further stratify the early-stage patients of Lugano classification into groups with distinct prognosis. Radical surgery might be proposed for the patients unfit for Rituximab treatment, and a combination of clinical and pathological staging systems was more helpful to predict the disease outcome of PG-DLBCL patients.

Modeling Efficacy of Bevacizumab Treatment for Metastatic Colon Cancer

PubMed Central

Islam, Rezwan; Chyou, Po-Huang; Burmester, James K

2013-01-01

Purpose: Bevacizumab, an FDA-approved adjuvant treatment for metastatic colon cancer, has extended survival for many patients. However, factors predicting response to treatment remain undefined. Patients and Methods: Relevant clinical and environmental data were abstracted from medical records of 149 evaluable patients treated with bevacizumab for metastatic colon cancer at a multi-specialty clinic. Tumor response was calculated from radiologic reports using Response Evaluation Criteria in Solid Tumors (RECIST) criteria and verified by oncologist review. Patients with at least one occurrence of complete or partial response or stable disease were classified as responders; those exhibiting progressive disease were classified as non-responders. Results: Univariate analysis demonstrated that blood in stool (P<0.05), unexplained weight loss (P<0.05), primary colon cancer site (P<0.05), chemotherapy treatment of primary tumor site (P<0.05), and adenocarcinoma versus adenoma subtype (P<0.05) was associated with tumor responsiveness. Factors remaining statistically significant following multivariate modeling included adenocarcinoma as tumor cell type versus other adenocarcinoma subtypes (OR=6.35, 95% CI: 1.08-37.18), chemotherapy treatment applied to primary tumor (OR= 0.07, 95% CI: 0.0-0.76,), tumor localization to cecal/ascending colon (OR=0.061, 95% CI: 0.006-0.588,), and unexplained weight loss (OR=0.1, 95% CI: 0.02-0.56,). Chemotherapy treatment of primary tumor, unexplained weight loss, and cecal/ascending localization of the tumor were associated with poorer outcomes. Adenocarcinoma as cell type compared to other adenocarcinoma subtypes was associated with better response to bevacizumab treatment. Conclusion: Results suggest that response to bevacizumab therapy may be predicted by modeling clinical factors including symptomology on presentation, tumor location and type, and initial response to chemotherapy. PMID:23678369

Proposed framework for thermomechanical life modeling of metal matrix composites

NASA Technical Reports Server (NTRS)

Halford, Gary R.; Lerch, Bradley A.; Saltsman, James F.

1993-01-01

The framework of a mechanics of materials model is proposed for thermomechanical fatigue (TMF) life prediction of unidirectional, continuous-fiber metal matrix composites (MMC's). Axially loaded MMC test samples are analyzed as structural components whose fatigue lives are governed by local stress-strain conditions resulting from combined interactions of the matrix, interfacial layer, and fiber constituents. The metallic matrix is identified as the vehicle for tracking fatigue crack initiation and propagation. The proposed framework has three major elements. First, TMF flow and failure characteristics of in situ matrix material are approximated from tests of unreinforced matrix material, and matrix TMF life prediction equations are numerically calibrated. The macrocrack initiation fatigue life of the matrix material is divided into microcrack initiation and microcrack propagation phases. Second, the influencing factors created by the presence of fibers and interfaces are analyzed, characterized, and documented in equation form. Some of the influences act on the microcrack initiation portion of the matrix fatigue life, others on the microcrack propagation life, while some affect both. Influencing factors include coefficient of thermal expansion mismatch strains, residual (mean) stresses, multiaxial stress states, off-axis fibers, internal stress concentrations, multiple initiation sites, nonuniform fiber spacing, fiber debonding, interfacial layers and cracking, fractured fibers, fiber deflections of crack fronts, fiber bridging of matrix cracks, and internal oxidation along internal interfaces. Equations exist for some, but not all, of the currently identified influencing factors. The third element is the inclusion of overriding influences such as maximum tensile strain limits of brittle fibers that could cause local fractures and ensuing catastrophic failure of surrounding matrix material. Some experimental data exist for assessing the plausibility of the proposed framework.

Estimation of Hydrogen-Exchange Protection Factors from MD Simulation Based on Amide Hydrogen Bonding Analysis.

PubMed

Park, In-Hee; Venable, John D; Steckler, Caitlin; Cellitti, Susan E; Lesley, Scott A; Spraggon, Glen; Brock, Ansgar

2015-09-28

Hydrogen exchange (HX) studies have provided critical insight into our understanding of protein folding, structure, and dynamics. More recently, hydrogen exchange mass spectrometry (HX-MS) has become a widely applicable tool for HX studies. The interpretation of the wealth of data generated by HX-MS experiments as well as other HX methods would greatly benefit from the availability of exchange predictions derived from structures or models for comparison with experiment. Most reported computational HX modeling studies have employed solvent-accessible-surface-area based metrics in attempts to interpret HX data on the basis of structures or models. In this study, a computational HX-MS prediction method based on classification of the amide hydrogen bonding modes mimicking the local unfolding model is demonstrated. Analysis of the NH bonding configurations from molecular dynamics (MD) simulation snapshots is used to determine partitioning over bonded and nonbonded NH states and is directly mapped into a protection factor (PF) using a logistics growth function. Predicted PFs are then used for calculating deuteration values of peptides and compared with experimental data. Hydrogen exchange MS data for fatty acid synthase thioesterase (FAS-TE) collected for a range of pHs and temperatures was used for detailed evaluation of the approach. High correlation between prediction and experiment for observable fragment peptides is observed in the FAS-TE and additional benchmarking systems that included various apo/holo proteins for which literature data were available. In addition, it is shown that HX modeling can improve experimental resolution through decomposition of in-exchange curves into rate classes, which correlate with prediction from MD. Successful rate class decompositions provide further evidence that the presented approach captures the underlying physical processes correctly at the single residue level. This assessment is further strengthened in a comparison of residue resolved protection factor predictions for staphylococcal nuclease with NMR data, which was also used to compare prediction performance with other algorithms described in the literature. The demonstrated transferable and scalable MD based HX prediction approach adds significantly to the available tools for HX-MS data interpretation based on available structures and models.

Estimation of Hydrogen-Exchange Protection Factors from MD Simulation Based on Amide Hydrogen Bonding Analysis

PubMed Central

Park, In-Hee; Venable, John D.; Steckler, Caitlin; Cellitti, Susan E.; Lesley, Scott A.; Spraggon, Glen; Brock, Ansgar

2015-01-01

Hydrogen exchange (HX) studies have provided critical insight into our understanding of protein folding, structure and dynamics. More recently, Hydrogen Exchange Mass Spectrometry (HX-MS) has become a widely applicable tool for HX studies. The interpretation of the wealth of data generated by HX-MS experiments as well as other HX methods would greatly benefit from the availability of exchange predictions derived from structures or models for comparison with experiment. Most reported computational HX modeling studies have employed solvent-accessible-surface-area based metrics in attempts to interpret HX data on the basis of structures or models. In this study, a computational HX-MS prediction method based on classification of the amide hydrogen bonding modes mimicking the local unfolding model is demonstrated. Analysis of the NH bonding configurations from Molecular Dynamics (MD) simulation snapshots is used to determine partitioning over bonded and non-bonded NH states and is directly mapped into a protection factor (PF) using a logistics growth function. Predicted PFs are then used for calculating deuteration values of peptides and compared with experimental data. Hydrogen exchange MS data for Fatty acid synthase thioesterase (FAS-TE) collected for a range of pHs and temperatures was used for detailed evaluation of the approach. High correlation between prediction and experiment for observable fragment peptides is observed in the FAS-TE and additional benchmarking systems that included various apo/holo proteins for which literature data were available. In addition, it is shown that HX modeling can improve experimental resolution through decomposition of in-exchange curves into rate classes, which correlate with prediction from MD. Successful rate class decompositions provide further evidence that the presented approach captures the underlying physical processes correctly at the single residue level. This assessment is further strengthened in a comparison of residue resolved protection factor predictions for staphylococcal nuclease with NMR data, which was also used to compare prediction performance with other algorithms described in the literature. The demonstrated transferable and scalable MD based HX prediction approach adds significantly to the available tools for HX-MS data interpretation based on available structures and models. PMID:26241692

Identification of Transcription Factors ZmMYB111 and ZmMYB148 Involved in Phenylpropanoid Metabolism.

PubMed

Zhang, Junjie; Zhang, Shuangshuang; Li, Hui; Du, Hai; Huang, Huanhuan; Li, Yangping; Hu, Yufeng; Liu, Hanmei; Liu, Yinghong; Yu, Guowu; Huang, Yubi

2016-01-01

Maize is the leading crop worldwide in terms of both planting area and total yields, but environmental stresses cause significant losses in productivity. Phenylpropanoid compounds play an important role in plant stress resistance; however, the mechanism of their synthesis is not fully understood, especially in regard to the expression and regulation of key genes. Phenylalanine ammonia-lyase (PAL) is the first key enzyme involved in phenylpropanoid metabolism, and it has a significant effect on the synthesis of important phenylpropanoid compounds. According to the results of sequence alignments and functional prediction, we selected two conserved R2R3-MYB transcription factors as candidate genes for the regulation of phenylpropanoid metabolism. The two candidate R2R3-MYB genes, which we named ZmMYB111 and ZmMYB148, were cloned, and then their structural characteristics and phylogenetic placement were predicted and analyzed. In addition, a series of evaluations were performed, including expression profiles, subcellular localization, transcription activation, protein-DNA interaction, and transient expression in maize endosperm. Our results indicated that both ZmMYB111 and ZmMYB148 are indeed R2R3-MYB transcription factors and that they may play a regulatory role in PAL gene expression.

Localized-itinerant dichotomy and unconventional magnetism in SrRu2O6

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

Okamoto, Satoshi; Ochi, Masayuki; Arita, Ryotaro

Electron correlations tend to generate local magnetic moments that usually order if the lattices are not too frustrated. The hexagonal compound SrRumore » $$_2$$O$$_6$$ has a relatively high N{\\'e}el temperature but small local moments, which seem to be at odds with the nominal valence of Ru$$^{5+}$$ in the $$t_{2g}^3$$ configuration. Here, we investigate the electronic and magnetic properties of SrRu$$_2$$O$$_6$$ using density functional theory (DFT) combined with dynamical mean field theory (DMFT). We find that the strong hybridization between Ru $d$ and O $p$ states results in a Ru valence that is closer to $+4$, leading to the small ordered moment, consistent with a DFT prediction. While the agreement with DFT might indicate that SrRu$$_2$$O$$_6$$ is in the weak coupling regime, our DMFT studies provide evidence from the mass enhancement and local moment formation that indicate correlation effects play a significant role. The local moment per Ru site is about a factor 2 larger than the ordered moment at low temperatures and remains finite in the whole temperature range investigated. Our theoretical N{\\'e}el temperature $$\\sim 700$$~K is in reasonable agreement with experimental observations. Due to a small lattice distortion, the degenerate $$t_{2g}$$ manifold is split and the quasiparticle weight is renormalized significantly in the $$a_{1g}$$ state, while correlation effects in $$e_g'$$ states are about a factor of 2--3 weaker. SrRu$$_2$$O$$_6$$ is a unique system in which localized and itinerant electrons coexist with the proximity to an orbitally-selective Mott transition within the $$t_{2g}$$ sector.« less

Perceived threat and corroboration: key factors that improve a predictive model of trust in internet-based health information and advice.

PubMed

Harris, Peter R; Sillence, Elizabeth; Briggs, Pam

2011-07-27

How do people decide which sites to use when seeking health advice online? We can assume, from related work in e-commerce, that general design factors known to affect trust in the site are important, but in this paper we also address the impact of factors specific to the health domain. The current study aimed to (1) assess the factorial structure of a general measure of Web trust, (2) model how the resultant factors predicted trust in, and readiness to act on, the advice found on health-related websites, and (3) test whether adding variables from social cognition models to capture elements of the response to threatening, online health-risk information enhanced the prediction of these outcomes. Participants were asked to recall a site they had used to search for health-related information and to think of that site when answering an online questionnaire. The questionnaire consisted of a general Web trust questionnaire plus items assessing appraisals of the site, including threat appraisals, information checking, and corroboration. It was promoted on the hungersite.com website. The URL was distributed via Yahoo and local print media. We assessed the factorial structure of the measures using principal components analysis and modeled how well they predicted the outcome measures using structural equation modeling (SEM) with EQS software. We report an analysis of the responses of participants who searched for health advice for themselves (N = 561). Analysis of the general Web trust questionnaire revealed 4 factors: information quality, personalization, impartiality, and credible design. In the final SEM model, information quality and impartiality were direct predictors of trust. However, variables specific to eHealth (perceived threat, coping, and corroboration) added substantially to the ability of the model to predict variance in trust and readiness to act on advice on the site. The final model achieved a satisfactory fit: χ(2) (5) = 10.8 (P = .21), comparative fit index = .99, root mean square error of approximation = .052. The model accounted for 66% of the variance in trust and 49% of the variance in readiness to act on the advice. Adding variables specific to eHealth enhanced the ability of a model of trust to predict trust and readiness to act on advice.

Perceived Threat and Corroboration: Key Factors That Improve a Predictive Model of Trust in Internet-based Health Information and Advice

PubMed Central

Harris, Peter R; Briggs, Pam

2011-01-01

Background How do people decide which sites to use when seeking health advice online? We can assume, from related work in e-commerce, that general design factors known to affect trust in the site are important, but in this paper we also address the impact of factors specific to the health domain. Objective The current study aimed to (1) assess the factorial structure of a general measure of Web trust, (2) model how the resultant factors predicted trust in, and readiness to act on, the advice found on health-related websites, and (3) test whether adding variables from social cognition models to capture elements of the response to threatening, online health-risk information enhanced the prediction of these outcomes. Methods Participants were asked to recall a site they had used to search for health-related information and to think of that site when answering an online questionnaire. The questionnaire consisted of a general Web trust questionnaire plus items assessing appraisals of the site, including threat appraisals, information checking, and corroboration. It was promoted on the hungersite.com website. The URL was distributed via Yahoo and local print media. We assessed the factorial structure of the measures using principal components analysis and modeled how well they predicted the outcome measures using structural equation modeling (SEM) with EQS software. Results We report an analysis of the responses of participants who searched for health advice for themselves (N = 561). Analysis of the general Web trust questionnaire revealed 4 factors: information quality, personalization, impartiality, and credible design. In the final SEM model, information quality and impartiality were direct predictors of trust. However, variables specific to eHealth (perceived threat, coping, and corroboration) added substantially to the ability of the model to predict variance in trust and readiness to act on advice on the site. The final model achieved a satisfactory fit: χ2 5 = 10.8 (P = .21), comparative fit index = .99, root mean square error of approximation = .052. The model accounted for 66% of the variance in trust and 49% of the variance in readiness to act on the advice. Conclusions Adding variables specific to eHealth enhanced the ability of a model of trust to predict trust and readiness to act on advice. PMID:21795237

Primary radical ablative surgery and fibula free-flap reconstruction for T4 oral cavity squamous cell carcinoma with mandibular invasion: oncologic and functional results and their predictive factors.

PubMed

Camuzard, Olivier; Dassonville, Olivier; Ettaiche, Marc; Chamorey, Emmanuel; Poissonnet, Gilles; Berguiga, Riadh; Leysalle, Axel; Benezery, Karen; Peyrade, Frédéric; Saada, Esma; Hechema, Raphael; Sudaka, Anne; Haudebourg, Juliette; Demard, François; Santini, José; Bozec, Alexandre

2017-01-01

The aims of this study were to evaluate clinical outcomes and to determine their predictive factors in patients with oral cavity squamous cell carcinoma (OCSCC) invading the mandibular bone (T4) who underwent primary radical surgery and fibula free-flap reconstruction. Between 2001 and 2013, all patients who underwent primary surgery and mandibular fibula free-flap reconstruction for OCSCC were enrolled in this retrospective study. Predictive factors of oncologic and functional outcomes were assessed in univariate and multivariate analysis. 77 patients (55 men and 22 women, mean age 62 ± 10.6 years) were enrolled in this study. Free-flap failure and local and general complication rates were 9, 31, and 22 %, respectively. In multivariate analysis, ASA score (p = 0.002), pathologic N-stage (p = 0.01), and close surgical margins (p = 0.03) were independent predictors of overall survival. Six months after therapy, oral diet, speech intelligibility, and mouth opening functions were normal or slightly impaired in, respectively, 79, 88, and 83 % of patients. 6.5 % of patients remaining dependent on enteral nutrition 6 months after therapy. With acceptable postoperative outcomes and satisfactory oncologic and functional results, segmental mandibulectomy with fibula free-flap reconstruction should be considered the gold standard primary treatment for patients with OCSCC invading mandible bone. Oncologic outcomes are dependent on three main factors: ASA score, pathologic N-stage, and surgical margin status.

Biological Factors Contributing to the Response to Cognitive Training in Mild Cognitive Impairment.

PubMed

Peter, Jessica; Schumacher, Lena V; Landerer, Verena; Abdulkadir, Ahmed; Kaller, Christoph P; Lahr, Jacob; Klöppel, Stefan

2018-01-01

In mild cognitive impairment (MCI), small benefits from cognitive training were observed for memory functions but there appears to be great variability in the response to treatment. Our study aimed to improve the characterization and selection of those participants who will benefit from cognitive intervention. We evaluated the predictive value of disease-specific biological factors for the outcome after cognitive training in MCI (n = 25) and also considered motivation of the participants. We compared the results of the cognitive intervention group with two independent control groups of MCI patients (local memory clinic, n = 20; ADNI cohort, n = 302). The primary outcome measure was episodic memory as measured by verbal delayed recall of a 10-word list. Episodic memory remained stable after treatment and slightly increased 6 months after the intervention. In contrast, in MCI patients who did not receive an intervention, episodic memory significantly decreased during the same time interval. A larger left entorhinal cortex predicted more improvement in episodic memory after treatment and so did higher levels of motivation. Adding disease-specific biological factors significantly improved the prediction of training-related change compared to a model based simply on age and baseline performance. Bootstrapping with resampling (n = 1000) verified the stability of our finding. Cognitive training might be particularly helpful in individuals with a bigger left entorhinal cortex as individuals who did not benefit from intervention showed 17% less volume in this area. When extended to alternative treatment options, stratification based on disease-specific biological factors is a useful step towards individualized medicine.

Improvement of Advanced Storm-scale Analysis and Prediction System (ASAPS) on Seoul Metropolitan Area, Korea

NASA Astrophysics Data System (ADS)

Park, Jeong-Gyun; Jee, Joon-Bum

2017-04-01

Dangerous weather such as severe rain, heavy snow, drought and heat wave caused by climate change make more damage in the urban area that dense populated and industry areas. Urban areas, unlike the rural area, have big population and transportation, dense the buildings and fuel consumption. Anthropogenic factors such as road energy balance, the flow of air in the urban is unique meteorological phenomena. However several researches are in process about prediction of urban meteorology. ASAPS (Advanced Storm-scale Analysis and Prediction System) predicts a severe weather with very short range (prediction with 6 hour) and high resolution (every hour with time and 1 km with space) on Seoul metropolitan area based on KLAPS (Korea Local Analysis and Prediction System) from KMA (Korea Meteorological Administration). This system configured three parts that make a background field (SUF5), analysis field (SU01) with observation and forecast field with high resolution (SUF1). In this study, we improve a high-resolution ASAPS model and perform a sensitivity test for the rainfall case. The improvement of ASAPS include model domain configuration, high resolution topographic data and data assimilation with WISE observation data.

Protein (multi-)location prediction: using location inter-dependencies in a probabilistic framework

PubMed Central

2014-01-01

Motivation Knowing the location of a protein within the cell is important for understanding its function, role in biological processes, and potential use as a drug target. Much progress has been made in developing computational methods that predict single locations for proteins. Most such methods are based on the over-simplifying assumption that proteins localize to a single location. However, it has been shown that proteins localize to multiple locations. While a few recent systems attempt to predict multiple locations of proteins, their performance leaves much room for improvement. Moreover, they typically treat locations as independent and do not attempt to utilize possible inter-dependencies among locations. Our hypothesis is that directly incorporating inter-dependencies among locations into both the classifier-learning and the prediction process can improve location prediction performance. Results We present a new method and a preliminary system we have developed that directly incorporates inter-dependencies among locations into the location-prediction process of multiply-localized proteins. Our method is based on a collection of Bayesian network classifiers, where each classifier is used to predict a single location. Learning the structure of each Bayesian network classifier takes into account inter-dependencies among locations, and the prediction process uses estimates involving multiple locations. We evaluate our system on a dataset of single- and multi-localized proteins (the most comprehensive protein multi-localization dataset currently available, derived from the DBMLoc dataset). Our results, obtained by incorporating inter-dependencies, are significantly higher than those obtained by classifiers that do not use inter-dependencies. The performance of our system on multi-localized proteins is comparable to a top performing system (YLoc+), without being restricted only to location-combinations present in the training set. PMID:24646119

Protein (multi-)location prediction: using location inter-dependencies in a probabilistic framework.

PubMed

Simha, Ramanuja; Shatkay, Hagit

2014-03-19

Knowing the location of a protein within the cell is important for understanding its function, role in biological processes, and potential use as a drug target. Much progress has been made in developing computational methods that predict single locations for proteins. Most such methods are based on the over-simplifying assumption that proteins localize to a single location. However, it has been shown that proteins localize to multiple locations. While a few recent systems attempt to predict multiple locations of proteins, their performance leaves much room for improvement. Moreover, they typically treat locations as independent and do not attempt to utilize possible inter-dependencies among locations. Our hypothesis is that directly incorporating inter-dependencies among locations into both the classifier-learning and the prediction process can improve location prediction performance. We present a new method and a preliminary system we have developed that directly incorporates inter-dependencies among locations into the location-prediction process of multiply-localized proteins. Our method is based on a collection of Bayesian network classifiers, where each classifier is used to predict a single location. Learning the structure of each Bayesian network classifier takes into account inter-dependencies among locations, and the prediction process uses estimates involving multiple locations. We evaluate our system on a dataset of single- and multi-localized proteins (the most comprehensive protein multi-localization dataset currently available, derived from the DBMLoc dataset). Our results, obtained by incorporating inter-dependencies, are significantly higher than those obtained by classifiers that do not use inter-dependencies. The performance of our system on multi-localized proteins is comparable to a top performing system (YLoc+), without being restricted only to location-combinations present in the training set.

c-Met Expression Is a Marker of Poor Prognosis in Patients With Locally Advanced Head and Neck Squamous Cell Carcinoma Treated With Chemoradiation

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

Baschnagel, Andrew M.; Williams, Lindsay; Hanna, Alaa

2014-03-01

Purpose: To examine the prognostic significance of c-Met expression in relation to p16 and epidermal growth factor receptor (EGFR) in patients with locally advanced head and neck squamous cell carcinoma (HNSCC) treated with definitive concurrent chemoradiation. Methods and Materials: Archival tissue from 107 HNSCC patients treated with chemoradiation was retrieved, and a tissue microarray was assembled. Immunohistochemical staining of c-Met, p16, and EGFR was performed. c-Met expression was correlated with p16, EGFR, clinical characteristics, and clinical endpoints including locoregional control (LRC), distant metastasis (DM), disease-free survival (DFS), and overall survival (OS). Results: Fifty-one percent of patients were positive for p16,more » and 53% were positive for EGFR. Both p16-negative (P≤.001) and EGFR-positive (P=.019) status predicted for worse DFS. Ninety-three percent of patients stained positive for c-Met. Patients were divided into low (0, 1, or 2+ intensity) or high (3+ intensity) c-Met expression. On univariate analysis, high c-Met expression predicted for worse LRC (hazard ratio [HR] 2.27; 95% CI, 1.08-4.77; P=.031), DM (HR 4.41; 95% CI, 1.56-12.45; P=.005), DFS (HR 3.00; 95% CI, 1.68-5.38; P<.001), and OS (HR 4.35; 95% CI, 2.13-8.88; P<.001). On multivariate analysis, after adjustment for site, T stage, smoking history, and EGFR status, only high c-Met expression (P=.011) and negative p16 status (P=.003) predicted for worse DFS. High c-Met expression was predictive of worse DFS in both EGFR-positive (P=.032) and -negative (P=.008) patients. In the p16-negative patients, those with high c-Met expression had worse DFS (P=.036) than did those with low c-Met expression. c-Met expression was not associated with any outcome in the p16-positive patients. Conclusions: c-Met is expressed in the majority of locally advanced HNSCC cases, and high c-Met expression predicts for worse clinical outcomes. High c-Met expression predicted for worse DFS in p16-negative patients but not in p16-positive patients. c-Met predicted for worse outcome regardless of EGFR status.« less

A multilevel perspective to explain recycling behaviour in communities.

PubMed

Tabernero, Carmen; Hernández, Bernardo; Cuadrado, Esther; Luque, Bárbara; Pereira, Cícero R

2015-08-15

Previous research on the motivation for environmentally responsible behaviour has focused mainly on individual variables, rather than organizational or collective variables. Therefore, the results of those studies are hardly applicable to environmental management. This study considers individual, collective, and organizational variables together that contribute to the management of environmental waste. The main aim is to identify, through the development of a multilevel model, those predictive variables of recycling behaviour that help organizations to increase the recycling rates in their communities. Individual (age, gender, educational level, self-efficacy with respect to residential recycling, individual recycling behaviour), organizational (satisfaction with the quality of the service provided by a recycling company), and collective (community recycling rates, number of inhabitants, community efficacy beliefs) motivational factors relevant to recycling behaviour were analysed. A sample of 1501 residents from 55 localities was surveyed. The results of multilevel analyses indicated that there was significant variability within and between localities. Interactions between variables at the level of the individual (e.g. satisfaction with service quality) and variables at the level of the collective (e.g. community efficacy) predicted recycling behaviour in localities with low and high community recycling rates and large and small populations. The interactions showed that the relationship between self-efficacy and recycling is stronger in localities with weak community efficacy beliefs than in communities with strong beliefs. The findings show that the relationship between satisfaction with service quality and recycling behaviour is stronger in localities with strong community efficacy beliefs than in communities with weaker beliefs and a smaller population. The results are discussed accordingly in relation to theory and possible contribution to waste management. Those findings may be incorporated in national and international environmental policies in order to promote environmentally responsible behaviour in citizenship. Copyright © 2015 Elsevier Ltd. All rights reserved.

Rapid recovery of genetic diversity of dogwhelk (Nucella lapillus L.) populations after local extinction and recolonization contradicts predictions from life-history characteristics.

PubMed

Colson, I; Hughes, R N

2004-08-01

The dogwhelk Nucella lapillus is a predatory marine gastropod populating North Atlantic rocky shores. As with many other gastropod species, N. lapillus was affected by tributyltin (TBT) pollution during the 1970s and 1980s, when local populations became extinct. After a partial ban on TBT in the United Kingdom in 1987, vacant sites have been recolonized. N. lapillus lacks a planktonic larval stage and is therefore expected to have limited dispersal ability. Relatively fast recolonization of some sites, however, contradicts this assumption. We compared levels of genetic diversity and genetic structuring between recolonized sites and sites that showed continuous population at three localities across the British Isles. No significant genetic effects of extinction/recolonization events were observed in SW Scotland and NE England. In SW England we observed a decrease in genetic diversity and an increase in genetic structure in recolonized populations. This last result could be an artefact, however, due to the superposition of other local factors influencing the genetic structuring of dogwhelk populations. We conclude that recolonization of vacant sites was accomplished by a relatively high number of individuals originating from several source populations (the 'migrant-pool' model of recolonization), implying that movements are more widespread than expected on the basis of development mode alone. Comparison with published data on genetic structure of marine organisms with contrasted larval dispersal supports this hypothesis. Our results also stress the importance of local factors (geographical or ecological) in determining genetic structure of dogwhelk populations. Copyright 2004 Blackwell Publishing Ltd

Fast and anisotropic flexibility-rigidity index for protein flexibility and fluctuation analysis

NASA Astrophysics Data System (ADS)

Opron, Kristopher; Xia, Kelin; Wei, Guo-Wei

2014-06-01

Protein structural fluctuation, typically measured by Debye-Waller factors, or B-factors, is a manifestation of protein flexibility, which strongly correlates to protein function. The flexibility-rigidity index (FRI) is a newly proposed method for the construction of atomic rigidity functions required in the theory of continuum elasticity with atomic rigidity, which is a new multiscale formalism for describing excessively large biomolecular systems. The FRI method analyzes protein rigidity and flexibility and is capable of predicting protein B-factors without resorting to matrix diagonalization. A fundamental assumption used in the FRI is that protein structures are uniquely determined by various internal and external interactions, while the protein functions, such as stability and flexibility, are solely determined by the structure. As such, one can predict protein flexibility without resorting to the protein interaction Hamiltonian. Consequently, bypassing the matrix diagonalization, the original FRI has a computational complexity of O(N^2). This work introduces a fast FRI (fFRI) algorithm for the flexibility analysis of large macromolecules. The proposed fFRI further reduces the computational complexity to O(N). Additionally, we propose anisotropic FRI (aFRI) algorithms for the analysis of protein collective dynamics. The aFRI algorithms permit adaptive Hessian matrices, from a completely global 3N × 3N matrix to completely local 3 × 3 matrices. These 3 × 3 matrices, despite being calculated locally, also contain non-local correlation information. Eigenvectors obtained from the proposed aFRI algorithms are able to demonstrate collective motions. Moreover, we investigate the performance of FRI by employing four families of radial basis correlation functions. Both parameter optimized and parameter-free FRI methods are explored. Furthermore, we compare the accuracy and efficiency of FRI with some established approaches to flexibility analysis, namely, normal mode analysis and Gaussian network model (GNM). The accuracy of the FRI method is tested using four sets of proteins, three sets of relatively small-, medium-, and large-sized structures and an extended set of 365 proteins. A fifth set of proteins is used to compare the efficiency of the FRI, fFRI, aFRI, and GNM methods. Intensive validation and comparison indicate that the FRI, particularly the fFRI, is orders of magnitude more efficient and about 10% more accurate overall than some of the most popular methods in the field. The proposed fFRI is able to predict B-factors for α-carbons of the HIV virus capsid (313 236 residues) in less than 30 seconds on a single processor using only one core. Finally, we demonstrate the application of FRI and aFRI to protein domain analysis.

Fast and anisotropic flexibility-rigidity index for protein flexibility and fluctuation analysis

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

Opron, Kristopher; Xia, Kelin; Wei, Guo-Wei, E-mail: wei@math.msu.edu

Protein structural fluctuation, typically measured by Debye-Waller factors, or B-factors, is a manifestation of protein flexibility, which strongly correlates to protein function. The flexibility-rigidity index (FRI) is a newly proposed method for the construction of atomic rigidity functions required in the theory of continuum elasticity with atomic rigidity, which is a new multiscale formalism for describing excessively large biomolecular systems. The FRI method analyzes protein rigidity and flexibility and is capable of predicting protein B-factors without resorting to matrix diagonalization. A fundamental assumption used in the FRI is that protein structures are uniquely determined by various internal and external interactions,more » while the protein functions, such as stability and flexibility, are solely determined by the structure. As such, one can predict protein flexibility without resorting to the protein interaction Hamiltonian. Consequently, bypassing the matrix diagonalization, the original FRI has a computational complexity of O(N{sup 2}). This work introduces a fast FRI (fFRI) algorithm for the flexibility analysis of large macromolecules. The proposed fFRI further reduces the computational complexity to O(N). Additionally, we propose anisotropic FRI (aFRI) algorithms for the analysis of protein collective dynamics. The aFRI algorithms permit adaptive Hessian matrices, from a completely global 3N × 3N matrix to completely local 3 × 3 matrices. These 3 × 3 matrices, despite being calculated locally, also contain non-local correlation information. Eigenvectors obtained from the proposed aFRI algorithms are able to demonstrate collective motions. Moreover, we investigate the performance of FRI by employing four families of radial basis correlation functions. Both parameter optimized and parameter-free FRI methods are explored. Furthermore, we compare the accuracy and efficiency of FRI with some established approaches to flexibility analysis, namely, normal mode analysis and Gaussian network model (GNM). The accuracy of the FRI method is tested using four sets of proteins, three sets of relatively small-, medium-, and large-sized structures and an extended set of 365 proteins. A fifth set of proteins is used to compare the efficiency of the FRI, fFRI, aFRI, and GNM methods. Intensive validation and comparison indicate that the FRI, particularly the fFRI, is orders of magnitude more efficient and about 10% more accurate overall than some of the most popular methods in the field. The proposed fFRI is able to predict B-factors for α-carbons of the HIV virus capsid (313 236 residues) in less than 30 seconds on a single processor using only one core. Finally, we demonstrate the application of FRI and aFRI to protein domain analysis.« less

The value of nodal information in predicting lung cancer relapse using 4DPET/4DCT

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

Li, Heyse, E-mail: heyse.li@mail.utoronto.ca; Becker, Nathan; Raman, Srinivas

2015-08-15

Purpose: There is evidence that computed tomography (CT) and positron emission tomography (PET) imaging metrics are prognostic and predictive in nonsmall cell lung cancer (NSCLC) treatment outcomes. However, few studies have explored the use of standardized uptake value (SUV)-based image features of nodal regions as predictive features. The authors investigated and compared the use of tumor and node image features extracted from the radiotherapy target volumes to predict relapse in a cohort of NSCLC patients undergoing chemoradiation treatment. Methods: A prospective cohort of 25 patients with locally advanced NSCLC underwent 4DPET/4DCT imaging for radiation planning. Thirty-seven image features were derivedmore » from the CT-defined volumes and SUVs of the PET image from both the tumor and nodal target regions. The machine learning methods of logistic regression and repeated stratified five-fold cross-validation (CV) were used to predict local and overall relapses in 2 yr. The authors used well-known feature selection methods (Spearman’s rank correlation, recursive feature elimination) within each fold of CV. Classifiers were ranked on their Matthew’s correlation coefficient (MCC) after CV. Area under the curve, sensitivity, and specificity values are also presented. Results: For predicting local relapse, the best classifier found had a mean MCC of 0.07 and was composed of eight tumor features. For predicting overall relapse, the best classifier found had a mean MCC of 0.29 and was composed of a single feature: the volume greater than 0.5 times the maximum SUV (N). Conclusions: The best classifier for predicting local relapse had only tumor features. In contrast, the best classifier for predicting overall relapse included a node feature. Overall, the methods showed that nodes add value in predicting overall relapse but not local relapse.« less

Shaping up the protein folding funnel by local interaction: lesson from a structure prediction study.

PubMed

Chikenji, George; Fujitsuka, Yoshimi; Takada, Shoji

2006-02-28

Predicting protein tertiary structure by folding-like simulations is one of the most stringent tests of how much we understand the principle of protein folding. Currently, the most successful method for folding-based structure prediction is the fragment assembly (FA) method. Here, we address why the FA method is so successful and its lesson for the folding problem. To do so, using the FA method, we designed a structure prediction test of "chimera proteins." In the chimera proteins, local structural preference is specific to the target sequences, whereas nonlocal interactions are only sequence-independent compaction forces. We find that these chimera proteins can find the native folds of the intact sequences with high probability indicating dominant roles of the local interactions. We further explore roles of local structural preference by exact calculation of the HP lattice model of proteins. From these results, we suggest principles of protein folding: For small proteins, compact structures that are fully compatible with local structural preference are few, one of which is the native fold. These local biases shape up the funnel-like energy landscape.

Shaping up the protein folding funnel by local interaction: Lesson from a structure prediction study

PubMed Central

Chikenji, George; Fujitsuka, Yoshimi; Takada, Shoji

2006-01-01

Predicting protein tertiary structure by folding-like simulations is one of the most stringent tests of how much we understand the principle of protein folding. Currently, the most successful method for folding-based structure prediction is the fragment assembly (FA) method. Here, we address why the FA method is so successful and its lesson for the folding problem. To do so, using the FA method, we designed a structure prediction test of “chimera proteins.” In the chimera proteins, local structural preference is specific to the target sequences, whereas nonlocal interactions are only sequence-independent compaction forces. We find that these chimera proteins can find the native folds of the intact sequences with high probability indicating dominant roles of the local interactions. We further explore roles of local structural preference by exact calculation of the HP lattice model of proteins. From these results, we suggest principles of protein folding: For small proteins, compact structures that are fully compatible with local structural preference are few, one of which is the native fold. These local biases shape up the funnel-like energy landscape. PMID:16488978

Local mechanical properties of LFT injection molded parts: Numerical simulations versus experiments

NASA Astrophysics Data System (ADS)

Desplentere, F.; Soete, K.; Bonte, H.; Debrabandere, E.

2014-05-01

In predictive engineering for polymer processes, the proper prediction of material microstructure from known processing conditions and constituent material properties is a critical step forward properly predicting bulk properties in the finished composite. Operating within the context of long-fiber thermoplastics (LFT, length < 15mm) this investigation concentrates on the prediction of the local mechanical properties of an injection molded part. To realize this, the Autodesk Simulation Moldflow Insight 2014 software has been used. In this software, a fiber breakage algorithm for the polymer flow inside the mold is available. Using well known micro mechanic formulas allow to combine the local fiber length with the local orientation into local mechanical properties. Different experiments were performed using a commercially available glass fiber filled compound to compare the measured data with the numerical simulation results. In this investigation, tensile tests and 3 point bending tests are considered. To characterize the fiber length distribution of the polymer melt entering the mold (necessary for the numerical simulations), air shots were performed. For those air shots, similar homogenization conditions were used as during the injection molding tests. The fiber length distribution is characterized using automated optical method on samples for which the matrix material is burned away. Using the appropriate settings for the different experiments, good predictions of the local mechanical properties are obtained.

Meteorological factors associated with abundance of airborne fungal spores over natural vegetation

NASA Astrophysics Data System (ADS)

Crandall, Sharifa G.; Gilbert, Gregory S.

2017-08-01

The abundance of airborne fungal spores in agricultural and urban settings increases with greater air temperature, relative humidity, or precipitation. The same meteorological factors that affect temporal patterns in spore abundance in managed environments also vary spatially across natural habitats in association with differences in vegetation structure. Here we investigated how temporal and spatial variation in aerial spore abundance is affected by abiotic (weather) and biotic (vegetation) factors as a foundation for predicting how fungi may respond to changes in weather and land-use patterns. We measured the phenology of airborne fungal spores across a mosaic of naturally occurring vegetation types at different time scales to describe (1) how spore abundance changes over time, (2) which local meteorological variables are good predictors for airborne spore density, and (3) whether spore abundance differs across vegetation types. Using an air volumetric vacuum sampler, we collected spore samples at 3-h intervals over a 120-h period in a mixed-evergreen forest and coastal prairie to measure diurnal, nocturnal, and total airborne spore abundance across vegetation types. Spore samples were also collected at weekly and monthly intervals in mixed-evergreen forest, redwood forest, and maritime chaparral vegetation types from 12 field sites across two years. We found greater airborne spore densities during the wetter winter months compared to the drier summer months. Mean total spore abundance in the mixed-evergreen forest was twice than in the coastal prairie, but there were no significant differences in total airborne spore abundance among mixed-evergreen forest, redwood forest, and maritime chaparral vegetation types. Weekly and monthly peaks in airborne spore abundance corresponded with rain events and peaks in soil moisture. Overall, temporal patterns in meteorological factors were much more important in determining airborne fungal spore abundance than the vegetation type. This suggests that overall patterns of fungal spore dynamics may be predictable across heterogeneous landscapes based on local weather patterns.

Quantifying Uncertainty in Daily Temporal Variations of Atmospheric NH3 Emissions Following Application of Chemical Fertilizers

NASA Astrophysics Data System (ADS)

Balasubramanian, S.; Koloutsou-Vakakis, S.; Rood, M. J.

2014-12-01

Improving modeling predictions of atmospheric particulate matter and deposition of reactive nitrogen requires representative emission inventories of precursor species, such as ammonia (NH3). Anthropogenic NH3 is primarily emitted to the atmosphere from agricultural sources (80-90%) with dominant contributions (56%) from chemical fertilizer usage (CFU) in regions like Midwest USA. Local crop management practices vary spatially and temporally, which influence regional air quality. To model the impact of CFU, NH3 emission inputs to chemical transport models are obtained from the National Emission Inventory (NEI). NH3 emissions from CFU are typically estimated by combining annual fertilizer sales data with emission factors. The Sparse Matrix Operator Kernel Emissions (SMOKE) model is used to disaggregate annual emissions to hourly scale using temporal factors. These factors are estimated by apportioning emissions within each crop season in proportion to the nitrogen applied and time-averaged to the hourly scale. Such approach does not reflect influence of CFU for different crops and local weather and soil conditions. This study provides an alternate approach for estimating temporal factors for NH3 emissions. The DeNitrification DeComposition (DNDC) model was used to estimate daily variations in NH3 emissions from CFU at 14 Central Illinois locations for 2002-2011. Weather, crop and soil data were provided as inputs. A method was developed to estimate site level CFU by combining planting and harvesting dates, nitrogen management and fertilizer sales data. DNDC results indicated that annual NH3 emissions were within ±15% of SMOKE estimates. Daily modeled emissions across 10 years followed similar distributions but varied in magnitudes within ±20%. Individual emission peaks on days after CFU were 2.5-8 times greater as compared to existing estimates from SMOKE. By identifying the episodic nature of NH3 emissions from CFU, this study is expected to provide improvements in predicting atmospheric particulate matter concentrations and deposition of reactive nitrogen.

Strain localization and elastic-plastic coupling during deformation of porous sandstone

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

Dewers, Thomas A.; Issen, Kathleen A.; Holcomb, David J.

Results of axisymmetric compression tests on weak, porous Castlegate Sandstone (Cretaceous, Utah, USA), covering a range of dilational and compactional behaviors, are examined for localization behavior. Assuming isotropy, bulk and shear moduli evolve as increasing functions of mean stress and Mises equivalent shear stress respectively, and as decreasing functions of work-conjugate plastic strains. Acoustic emissions events located during testing show onset of localization and permit calculation of observed shear and low-angle compaction localization zones, or bands, as localization commences. Total strain measured experimentally partitions into: A) elastic strain with constant moduli, B) elastic strain due to stress dependence of moduli,more » C) elastic strain due to moduli degradation with increasing plastic strain, and D) plastic strain. The third term is the elastic-plastic coupling strain, and though often ignored, contributes significantly to pre-failure total strain for brittle and transitional tests. Constitutive parameters and localization predictions derived from experiments are compared to theoretical predictions. In the brittle regime, predictions of band angles (angle between band normal and maximum compression) demonstrate good agreement with observed shear band angles. Compaction localization was observed in the transitional regime in between shear localization and spatially pervasive compaction, over a small range of mean stresses. In contrast with predictions however, detailed acoustic emissions analyses in this regime show low angle, compaction-dominated but shear-enhanced, localization.« less

Single-Nucleotide Polymorphisms Reveal Spatial Diversity Among Clones of Yersinia pestis During Plague Outbreaks in Colorado and the Western United States.

PubMed

Lowell, Jennifer L; Antolin, Michael F; Andersen, Gary L; Hu, Ping; Stokowski, Renee P; Gage, Kenneth L

2015-05-01

In western North America, plague epizootics caused by Yersinia pestis appear to sweep across landscapes, primarily infecting and killing rodents, especially ground squirrels and prairie dogs. During these epizootics, the risk of Y. pestis transmission to humans is highest. While empirical models that include climatic conditions and densities of rodent hosts and fleas can predict when epizootics are triggered, bacterial transmission patterns across landscapes, and the scale at which Y. pestis is maintained in nature during inter-epizootic periods, are poorly defined. Elucidating the spatial extent of Y. pestis clones during epizootics can determine whether bacteria are propagated across landscapes or arise independently from local inter-epizootic maintenance reservoirs. We used DNA microarray technology to identify single-nucleotide polymorphisms (SNPs) in 34 Y. pestis isolates collected in the western United States from 1980 to 2006, 21 of which were collected during plague epizootics in Colorado. Phylogenetic comparisons were used to elucidate the hypothesized spread of Y. pestis between the mountainous Front Range and the eastern plains of northern Colorado during epizootics. Isolates collected from across the western United States were included for regional comparisons. By identifying SNPs that mark individual clones, our results strongly suggest that Y. pestis is maintained locally and that widespread epizootic activity is caused by multiple clones arising independently at small geographic scales. This is in contrast to propagation of individual clones being transported widely across landscapes. Regionally, our data are consistent with the notion that Y. pestis diversifies at relatively local scales following long-range translocation events. We recommend that surveillance and prediction by public health and wildlife management professionals focus more on models of local or regional weather patterns and ecological factors that may increase risk of widespread epizootics, rather than predicting or attempting to explain epizootics on the basis of movement of host species that may transport plague.

Collaborative Completion of Transcription Factor Binding Profiles via Local Sensitive Unified Embedding.

PubMed

Zhu, Lin; Guo, Wei-Li; Lu, Canyi; Huang, De-Shuang

2016-12-01

Although the newly available ChIP-seq data provides immense opportunities for comparative study of regulatory activities across different biological conditions, due to cost, time or sample material availability, it is not always possible for researchers to obtain binding profiles for every protein in every sample of interest, which considerably limits the power of integrative studies. Recently, by leveraging related information from measured data, Ernst et al. proposed ChromImpute for predicting additional ChIP-seq and other types of datasets, it is demonstrated that the imputed signal tracks accurately approximate the experimentally measured signals, and thereby could potentially enhance the power of integrative analysis. Despite the success of ChromImpute, in this paper, we reexamine its learning process, and show that its performance may degrade substantially and sometimes may even fail to output a prediction when the available data is scarce. This limitation could hurt its applicability to important predictive tasks, such as the imputation of TF binding data. To alleviate this problem, we propose a novel method called Local Sensitive Unified Embedding (LSUE) for imputing new ChIP-seq datasets. In LSUE, the ChIP-seq data compendium are fused together by mapping proteins, samples, and genomic positions simultaneously into the Euclidean space, thereby making their underling associations directly evaluable using simple calculations. In contrast to ChromImpute which mainly makes use of the local correlations between available datasets, LSUE can better estimate the overall data structure by formulating the representation learning of all involved entities as a single unified optimization problem. Meanwhile, a novel form of local sensitive low rank regularization is also proposed to further improve the performance of LSUE. Experimental evaluations on the ENCODE TF ChIP-seq data illustrate the performance of the proposed model. The code of LSUE is available at https://github.com/ekffar/LSUE.

Local plant adaptation across a subarctic elevational gradient

PubMed Central

Kardol, Paul; De Long, Jonathan R.; Wardle, David A.

2014-01-01

Predicting how plants will respond to global warming necessitates understanding of local plant adaptation to temperature. Temperature may exert selective effects on plants directly, and also indirectly through environmental factors that covary with temperature, notably soil properties. However, studies on the interactive effects of temperature and soil properties on plant adaptation are rare, and the role of abiotic versus biotic soil properties in plant adaptation to temperature remains untested. We performed two growth chamber experiments using soils and Bistorta vivipara bulbil ecotypes from a subarctic elevational gradient (temperature range: ±3°C) in northern Sweden to disentangle effects of local ecotype, temperature, and biotic and abiotic properties of soil origin on plant growth. We found partial evidence for local adaption to temperature. Although soil origin affected plant growth, we did not find support for local adaptation to either abiotic or biotic soil properties, and there were no interactive effects of soil origin with ecotype or temperature. Our results indicate that ecotypic variation can be an important driver of plant responses to the direct effects of increasing temperature, while responses to covariation in soil properties are of a phenotypic, rather than adaptive, nature. PMID:26064553

Contextual cost: when a visual-search target is not where it should be.

PubMed

Makovski, Tal; Jiang, Yuhong V

2010-02-01

Visual search is often facilitated when the search display occasionally repeats, revealing a contextual-cueing effect. According to the associative-learning account, contextual cueing arises from associating the display configuration with the target location. However, recent findings emphasizing the importance of local context near the target have given rise to the possibility that low-level repetition priming may account for the contextual-cueing effect. This study distinguishes associative learning from local repetition priming by testing whether search is directed toward a target's expected location, even when the target is relocated. After participants searched for a T among Ls in displays that repeated 24 times, they completed a transfer session where the target was relocated locally to a previously blank location (Experiment 1) or to an adjacent distractor location (Experiment 2). Results revealed that contextual cueing decreased as the target appeared farther away from its expected location, ultimately resulting in a contextual cost when the target swapped locations with a local distractor. We conclude that target predictability is a key factor in contextual cueing.

Investigation on the real-time prediction of ground motions using seismic records observed in deep boreholes

NASA Astrophysics Data System (ADS)

Miyakoshi, H.; Tsuno, S.

2013-12-01

The present method of the EEW system installed in the railway field of Japan predicts seismic ground motions based on the estimated earthquake information about epicentral distances and magnitudes using initial P-waves observed on the surface. In the case of local earthquakes beneath the Tokyo Metropolitan Area, however, a method to directly predict seismic ground motions using P-waves observed in deep boreholes could issue EEWs more simply and surely. Besides, a method to predict seismic ground motions, using S-waves observed in deep boreholes and S-wave velocity structures beneath seismic stations, could show planar distributions of ground motions for train operation control areas in the aftermath of earthquakes. This information is available to decide areas in which the emergency inspection of railway structures should be performed. To develop those two methods, we investigated relationships between peak amplitudes on the surface and those in deep boreholes, using seismic records of KiK-net stations in the Kanto Basin. In this study, we used earthquake accelerograms observed in boreholes whose depths are deeper than the top face of Pre-Neogene basement and those on the surface at 12 seismic stations of KiK-net. We selected 243 local earthquakes whose epicenters are located around the Kanto Region. Those JMA magnitudes are in the range from 4.5 to 7.0. We picked the on-set of P-waves and S-waves using a vertical component and two horizontal components, respectively. Peak amplitudes of P-waves and S-waves were obtained using vertical components and vector sums of two horizontal components, respectively. We estimated parameters which represent site amplification factors beneath seismic stations, using peak amplitudes of S-waves observed in the deep borehole and those on the surface, to minimize the residuals between calculations by the theoretical equation and observations. Correlation coefficients between calculations and observations are high values in the range from 0.8 to 0.9. This result suggests that we could predict ground motions with the high accuracy using peak amplitudes of S-waves in deep boreholes and site amplification factors based on S-wave velocity structures. Also, we estimated parameters which represent radiation coefficients and the P/S velocity ratios around hypocentral regions, using peak amplitudes of P-waves and S-waves observed in deep boreholes, to minimize the residuals between calculations and observations. Correlation coefficients between calculations and observations are slightly lower values in the range from 0.7 to 0.9 than those for site amplification factors. This result suggests that the variability of radiation patterns for individual earthquakes affects the accuracy to predict ground motions using P-waves in deep boreholes.

Experimental test of quantum nonlocality in three-photon Greenberger-Horne-Zeilinger entanglement

PubMed

Pan; Bouwmeester; Daniell; Weinfurter; Zeilinger

2000-02-03

Bell's theorem states that certain statistical correlations predicted by quantum physics for measurements on two-particle systems cannot be understood within a realistic picture based on local properties of each individual particle-even if the two particles are separated by large distances. Einstein, Podolsky and Rosen first recognized the fundamental significance of these quantum correlations (termed 'entanglement' by Schrodinger) and the two-particle quantum predictions have found ever-increasing experimental support. A more striking conflict between quantum mechanical and local realistic predictions (for perfect correlations) has been discovered; but experimental verification has been difficult, as it requires entanglement between at least three particles. Here we report experimental confirmation of this conflict, using our recently developed method to observe three-photon entanglement, or 'Greenberger-Horne-Zeilinger' (GHZ) states. The results of three specific experiments, involving measurements of polarization correlations between three photons, lead to predictions for a fourth experiment; quantum physical predictions are mutually contradictory with expectations based on local realism. We find the results of the fourth experiment to be in agreement with the quantum prediction and in striking conflict with local realism.

IE1 and hr facilitate the localization of Bombyx mori nucleopolyhedrovirus ORF8 to specific nuclear sites.

PubMed

Kang, WonKyung; Imai, Noriko; Kawasaki, Yu; Nagamine, Toshihiro; Matsumoto, Shogo

2005-11-01

The Bombyx mori nucleopolyhedrovirus (BmNPV) ORF8 protein has previously been reported to colocalize with IE1 to specific nuclear sites during infection. Transient expression of green fluorescent protein (GFP)-fused ORF8 showed the protein to have cytoplasmic localization, but following BmNPV infection the protein formed foci, suggesting that ORF8 requires some other viral factor(s) for this. Therefore, interacting factors were looked for using the yeast two-hybrid system and IE1 was identified. We mapped the interacting region of ORF8 using a yeast two-hybrid assay. An N-terminal region (residues 1-110) containing a predicted coiled-coil domain interacted with IE1, while a truncated N-terminal region (residues 1-78) that lacks this domain did not. In addition, a protein with a complete deletion of the N-terminal region failed to interact with IE1. These results suggest that the ORF8 N-terminal region containing the coiled-coil domain is required for the interaction with IE1. Next, whether IE1 plays a role in ORF8 localization was investigated. In the presence of IE1, GFP-ORF8 localized to the nucleus. In addition, cotransfection with a plasmid expressing IE1 and a plasmid containing the hr3 element resulted in nuclear foci formation. A GFP-fused ORF8 mutant protein containing the coiled-coil domain, previously shown to interact with IE1, also formed nuclear foci in the presence of IE1 and hr3. However, ORF8 mutant proteins that did not interact with IE1 failed to form nuclear foci. In contrast to wild-type IE1, focus formation was not observed for an IE1 mutant protein that was deficient in hr binding. These results suggest that IE1 and hr facilitate the localization of BmNPV ORF8 to specific nuclear sites.

Li-ion Battery Separators, Mechanical Integrity and Failure Mechanisms Leading to Soft and Hard Internal Shorts

PubMed Central

Zhang, Xiaowei; Sahraei, Elham; Wang, Kai

2016-01-01

Separator integrity is an important factor in preventing internal short circuit in lithium-ion batteries. Local penetration tests (nail or conical punch) often produce presumably sporadic results, where in exactly similar cell and test set-ups one cell goes to thermal runaway while the other shows minimal reactions. We conducted an experimental study of the separators under mechanical loading, and discovered two distinct deformation and failure mechanisms, which could explain the difference in short circuit characteristics of otherwise similar tests. Additionally, by investigation of failure modes, we provided a hypothesis about the process of formation of local “soft short circuits” in cells with undetectable failure. Finally, we proposed a criterion for predicting onset of soft short from experimental data. PMID:27581185

Prediction of household and commercial BMW generation according to socio-economic and other factors for the Dublin region.

PubMed

Purcell, M; Magette, W L

2009-04-01

Both planning and design of integrated municipal solid waste management systems require accurate prediction of waste generation. This research predicted the quantity and distribution of biodegradable municipal waste (BMW) generation within a diverse 'landscape' of residential areas, as well as from a variety of commercial establishments (restaurants, hotels, hospitals, etc.) in the Dublin (Ireland) region. Socio-economic variables, housing types, and the sizes and main activities of commercial establishments were hypothesized as the key determinants contributing to the spatial variability of BMW generation. A geographical information system (GIS) 'model' of BMW generation was created using ArcMap, a component of ArcGIS 9. Statistical data including socio-economic status and household size were mapped on an electoral district basis. Historical research and data from scientific literature were used to assign BMW generation rates to residential and commercial establishments. These predictions were combined to give overall BMW estimates for the region, which can aid waste planning and policy decisions. This technique will also aid the design of future waste management strategies, leading to policy and practice alterations as a function of demographic changes and development. The household prediction technique gave a more accurate overall estimate of household waste generation than did the social class technique. Both techniques produced estimates that differed from the reported local authority data; however, given that local authority reported figures for the region are below the national average, with some of the waste generated from apartment complexes being reported as commercial waste, predictions arising from this research are believed to be closer to actual waste generation than a comparison to reported data would suggest. By changing the input data, this estimation tool can be adapted for use in other locations. Although focusing on waste in the Dublin region, this method of waste prediction can have significant potential benefits if a universal method can be found to apply it effectively.

Testing for local adaptation and evolutionary potential along altitudinal gradients in rainforest Drosophila: beyond laboratory estimates.

PubMed

O'Brien, Eleanor K; Higgie, Megan; Reynolds, Alan; Hoffmann, Ary A; Bridle, Jon R

2017-05-01

Predicting how species will respond to the rapid climatic changes predicted this century is an urgent task. Species distribution models (SDMs) use the current relationship between environmental variation and species' abundances to predict the effect of future environmental change on their distributions. However, two common assumptions of SDMs are likely to be violated in many cases: (i) that the relationship of environment with abundance or fitness is constant throughout a species' range and will remain so in future and (ii) that abiotic factors (e.g. temperature, humidity) determine species' distributions. We test these assumptions by relating field abundance of the rainforest fruit fly Drosophila birchii to ecological change across gradients that include its low and high altitudinal limits. We then test how such ecological variation affects the fitness of 35 D. birchii families transplanted in 591 cages to sites along two altitudinal gradients, to determine whether genetic variation in fitness responses could facilitate future adaptation to environmental change. Overall, field abundance was highest at cooler, high-altitude sites, and declined towards warmer, low-altitude sites. By contrast, cage fitness (productivity) increased towards warmer, lower-altitude sites, suggesting that biotic interactions (absent from cages) drive ecological limits at warmer margins. In addition, the relationship between environmental variation and abundance varied significantly among gradients, indicating divergence in ecological niche across the species' range. However, there was no evidence for local adaptation within gradients, despite greater productivity of high-altitude than low-altitude populations when families were reared under laboratory conditions. Families also responded similarly to transplantation along gradients, providing no evidence for fitness trade-offs that would favour local adaptation. These findings highlight the importance of (i) measuring genetic variation in key traits under ecologically relevant conditions, and (ii) considering the effect of biotic interactions when predicting species' responses to environmental change. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Comparison of National Operative Mortality in Gastroenterological Surgery Using Web-based Prospective Data Entry Systems.

PubMed

Anazawa, Takayuki; Paruch, Jennifer L; Miyata, Hiroaki; Gotoh, Mitsukazu; Ko, Clifford Y; Cohen, Mark E; Hirahara, Norimichi; Zhou, Lynn; Konno, Hiroyuki; Wakabayashi, Go; Sugihara, Kenichi; Mori, Masaki

2015-12-01

International collaboration is important in healthcare quality evaluation; however, few international comparisons of general surgery outcomes have been accomplished. Furthermore, predictive model application for risk stratification has not been internationally evaluated. The National Clinical Database (NCD) in Japan was developed in collaboration with the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP), with a goal of creating a standardized surgery database for quality improvement. The study aimed to compare the consistency and impact of risk factors of 3 major gastroenterological surgical procedures in Japan and the United States (US) using web-based prospective data entry systems: right hemicolectomy (RH), low anterior resection (LAR), and pancreaticoduodenectomy (PD).Data from NCD and ACS-NSQIP, collected over 2 years, were examined. Logistic regression models were used for predicting 30-day mortality for both countries. Models were exchanged and evaluated to determine whether the models built for one population were accurate for the other population.We obtained data for 113,980 patients; 50,501 (Japan: 34,638; US: 15,863), 42,770 (Japan: 35,445; US: 7325), and 20,709 (Japan: 15,527; US: 5182) underwent RH, LAR, and, PD, respectively. Thirty-day mortality rates for RH were 0.76% (Japan) and 1.88% (US); rates for LAR were 0.43% versus 1.08%; and rates for PD were 1.35% versus 2.57%. Patient background, comorbidities, and practice style were different between Japan and the US. In the models, the odds ratio for each variable was similar between NCD and ACS-NSQIP. Local risk models could predict mortality using local data, but could not accurately predict mortality using data from other countries.We demonstrated the feasibility and efficacy of the international collaborative research between Japan and the US, but found that local risk models remain essential for quality improvement.

Job embeddedness and nurse retention.

PubMed

Reitz, O Ed; Anderson, Mary Ann; Hill, Pamela D

2010-01-01

Nurse retention is a different way of conceptualizing the employer-employee relationship when compared with turnover. Job embeddedness (JE), a construct based on retention, represents the sum of reasons why employees remain at their jobs. However, JE has not been investigated in relation to locale (urban or rural) or exclusively with a sample of registered nurses (RNs). The purpose of this study was to determine what factors (JE, age, gender, locale, and income) help predict nurse retention. A cross-sectional mailed survey design was used with RNs in different locales (urban or rural). Job embeddedness was measured by the score on the composite, standardized instrument. Nurse retention was measured by self-report items concerning intent to stay. A response rate of 49.3% was obtained. The typical respondent was female (96.1%), white, non-Hispanic (87.4%), and married (74.9%). Age and JE were predictive of nurse retention and accounted for 26% of the explained variance in intent to stay. Although age was a significant predictor of intent to stay, it accounted for only 1.4% of the variance while JE accounted for 24.6% of the variance of nurse retention (as measured by intent to stay). Older, more "embedded" nurses are more likely to remain employed in their current organization. Based on these findings, JE may form the basis for the development of an effective nurse retention program.

Prediction of the Seizure Suppression Effect by Electrical Stimulation via a Computational Modeling Approach.

PubMed

Ahn, Sora; Jo, Sumin; Jun, Sang Beom; Lee, Hyang Woon; Lee, Seungjun

2017-01-01

In this paper, we identified factors that can affect seizure suppression via electrical stimulation by an integrative study based on experimental and computational approach. Preferentially, we analyzed the characteristics of seizure-like events (SLEs) using our previous in vitro experimental data. The results were analyzed in two groups classified according to the size of the effective region, in which the SLE was able to be completely suppressed by local stimulation. However, no significant differences were found between these two groups in terms of signal features or propagation characteristics (i.e., propagation delays, frequency spectrum, and phase synchrony). Thus, we further investigated important factors using a computational model that was capable of evaluating specific influences on effective region size. In the proposed model, signal transmission between neurons was based on two different mechanisms: synaptic transmission and the electrical field effect. We were able to induce SLEs having similar characteristics with differentially weighted adjustments for the two transmission methods in various noise environments. Although the SLEs had similar characteristics, their suppression effects differed. First of all, the suppression effect occurred only locally where directly received the stimulation effect in the high noise environment, but it occurred in the entire network in the low noise environment. Interestingly, in the same noise environment, the suppression effect was different depending on SLE propagation mechanism; only a local suppression effect was observed when the influence of the electrical field transmission was very weak, whereas a global effect was observed with a stronger electrical field effect. These results indicate that neuronal activities synchronized by a strong electrical field effect respond more sensitively to partial changes in the entire network. In addition, the proposed model was able to predict that stimulation of a seizure focus region is more effective for suppression. In conclusion, we confirmed the possibility of a computational model as a simulation tool to analyze the efficacy of deep brain stimulation (DBS) and investigated the key factors that determine the size of an effective region in seizure suppression via electrical stimulation.

PreCisIon: PREdiction of CIS-regulatory elements improved by gene's positION.

PubMed

Elati, Mohamed; Nicolle, Rémy; Junier, Ivan; Fernández, David; Fekih, Rim; Font, Julio; Képès, François

2013-02-01

Conventional approaches to predict transcriptional regulatory interactions usually rely on the definition of a shared motif sequence on the target genes of a transcription factor (TF). These efforts have been frustrated by the limited availability and accuracy of TF binding site motifs, usually represented as position-specific scoring matrices, which may match large numbers of sites and produce an unreliable list of target genes. To improve the prediction of binding sites, we propose to additionally use the unrelated knowledge of the genome layout. Indeed, it has been shown that co-regulated genes tend to be either neighbors or periodically spaced along the whole chromosome. This study demonstrates that respective gene positioning carries significant information. This novel type of information is combined with traditional sequence information by a machine learning algorithm called PreCisIon. To optimize this combination, PreCisIon builds a strong gene target classifier by adaptively combining weak classifiers based on either local binding sequence or global gene position. This strategy generically paves the way to the optimized incorporation of any future advances in gene target prediction based on local sequence, genome layout or on novel criteria. With the current state of the art, PreCisIon consistently improves methods based on sequence information only. This is shown by implementing a cross-validation analysis of the 20 major TFs from two phylogenetically remote model organisms. For Bacillus subtilis and Escherichia coli, respectively, PreCisIon achieves on average an area under the receiver operating characteristic curve of 70 and 60%, a sensitivity of 80 and 70% and a specificity of 60 and 56%. The newly predicted gene targets are demonstrated to be functionally consistent with previously known targets, as assessed by analysis of Gene Ontology enrichment or of the relevant literature and databases.

Evaluation of procedures for prediction of unconventional gas in the presence of geologic trends

USGS Publications Warehouse

Attanasi, E.D.; Coburn, T.C.

2009-01-01

This study extends the application of local spatial nonparametric prediction models to the estimation of recoverable gas volumes in continuous-type gas plays to regimes where there is a single geologic trend. A transformation is presented, originally proposed by Tomczak, that offsets the distortions caused by the trend. This article reports on numerical experiments that compare predictive and classification performance of the local nonparametric prediction models based on the transformation with models based on Euclidean distance. The transformation offers improvement in average root mean square error when the trend is not severely misspecified. Because of the local nature of the models, even those based on Euclidean distance in the presence of trends are reasonably robust. The tests based on other model performance metrics such as prediction error associated with the high-grade tracts and the ability of the models to identify sites with the largest gas volumes also demonstrate the robustness of both local modeling approaches. ?? International Association for Mathematical Geology 2009.

The effect of using genealogy-based haplotypes for genomic prediction

PubMed Central

2013-01-01

Background Genomic prediction uses two sources of information: linkage disequilibrium between markers and quantitative trait loci, and additive genetic relationships between individuals. One way to increase the accuracy of genomic prediction is to capture more linkage disequilibrium by regression on haplotypes instead of regression on individual markers. The aim of this study was to investigate the accuracy of genomic prediction using haplotypes based on local genealogy information. Methods A total of 4429 Danish Holstein bulls were genotyped with the 50K SNP chip. Haplotypes were constructed using local genealogical trees. Effects of haplotype covariates were estimated with two types of prediction models: (1) assuming that effects had the same distribution for all haplotype covariates, i.e. the GBLUP method and (2) assuming that a large proportion (π) of the haplotype covariates had zero effect, i.e. a Bayesian mixture method. Results About 7.5 times more covariate effects were estimated when fitting haplotypes based on local genealogical trees compared to fitting individuals markers. Genealogy-based haplotype clustering slightly increased the accuracy of genomic prediction and, in some cases, decreased the bias of prediction. With the Bayesian method, accuracy of prediction was less sensitive to parameter π when fitting haplotypes compared to fitting markers. Conclusions Use of haplotypes based on genealogy can slightly increase the accuracy of genomic prediction. Improved methods to cluster the haplotypes constructed from local genealogy could lead to additional gains in accuracy. PMID:23496971

The effect of using genealogy-based haplotypes for genomic prediction.

PubMed

Edriss, Vahid; Fernando, Rohan L; Su, Guosheng; Lund, Mogens S; Guldbrandtsen, Bernt

2013-03-06

Genomic prediction uses two sources of information: linkage disequilibrium between markers and quantitative trait loci, and additive genetic relationships between individuals. One way to increase the accuracy of genomic prediction is to capture more linkage disequilibrium by regression on haplotypes instead of regression on individual markers. The aim of this study was to investigate the accuracy of genomic prediction using haplotypes based on local genealogy information. A total of 4429 Danish Holstein bulls were genotyped with the 50K SNP chip. Haplotypes were constructed using local genealogical trees. Effects of haplotype covariates were estimated with two types of prediction models: (1) assuming that effects had the same distribution for all haplotype covariates, i.e. the GBLUP method and (2) assuming that a large proportion (π) of the haplotype covariates had zero effect, i.e. a Bayesian mixture method. About 7.5 times more covariate effects were estimated when fitting haplotypes based on local genealogical trees compared to fitting individuals markers. Genealogy-based haplotype clustering slightly increased the accuracy of genomic prediction and, in some cases, decreased the bias of prediction. With the Bayesian method, accuracy of prediction was less sensitive to parameter π when fitting haplotypes compared to fitting markers. Use of haplotypes based on genealogy can slightly increase the accuracy of genomic prediction. Improved methods to cluster the haplotypes constructed from local genealogy could lead to additional gains in accuracy.

A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China

PubMed Central

Yu, Xianyu; Wang, Yi; Niu, Ruiqing; Hu, Youjian

2016-01-01

In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR) technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM) classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO) algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%–19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides. PMID:27187430

A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China.

PubMed

Yu, Xianyu; Wang, Yi; Niu, Ruiqing; Hu, Youjian

2016-05-11

In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR) technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM) classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO) algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%-19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides.

A genetic polymorphism repurposes the G-protein coupled and membrane-associated estrogen receptor GPER to a transcription factor-like molecule promoting paracrine signaling between stroma and breast carcinoma cells

PubMed Central

Pupo, Marco; Bodmer, Alexandre; Berto, Melissa; Maggiolini, Marcello; Dietrich, Pierre-Yves; Picard, Didier

2017-01-01

GPER is a membrane-associated estrogen receptor of the family of G-protein coupled receptors. For breast cancer, the contribution of GPER to promoting the proliferation and migration of both carcinoma cells and cancer-associated fibroblasts (CAFs) in response to estrogen and other agonists has extensively been investigated. Intriguingly, GPER was previously found to be localized to the nucleus in one isolate of breast CAFs. Moreover, this nuclear GPER was shown to bind regulatory sequences of cancer-relevant target genes and to induce their expression. We decided to find out what induces the nuclear localization of GPER, how general this phenomenon is, and what its functional significance is. We discovered that interfering with N-linked glycosylation of GPER, either by mutation of the predicted glycosylation sites or pharmacologically with tunicamycin, drives GPER into the nucleus. Surveying a small set of CAFs from breast cancer biopsies, we found that a relatively common single nucleotide polymorphism, which results in the expression of a GPER variant with the amino acid substitution P16L, is associated with the nuclear localization of GPER. GPER with P16L fails to be glycosylated, presumably because of a conformational effect on the nearby glycosylation sites. GPER P16L is defective for membrane-associated signaling, but instead acts like an estrogen-stimulated transcription factor. In CAFs, it induces the secretion of paracrine factors that promote the migration of carcinoma cells. This raises the possibility that the GPER P16L polymorphism could be a risk factor for breast cancer. PMID:28596490

A genetic polymorphism repurposes the G-protein coupled and membrane-associated estrogen receptor GPER to a transcription factor-like molecule promoting paracrine signaling between stroma and breast carcinoma cells.

PubMed

Pupo, Marco; Bodmer, Alexandre; Berto, Melissa; Maggiolini, Marcello; Dietrich, Pierre-Yves; Picard, Didier

2017-07-18

GPER is a membrane-associated estrogen receptor of the family of G-protein coupled receptors. For breast cancer, the contribution of GPER to promoting the proliferation and migration of both carcinoma cells and cancer-associated fibroblasts (CAFs) in response to estrogen and other agonists has extensively been investigated. Intriguingly, GPER was previously found to be localized to the nucleus in one isolate of breast CAFs. Moreover, this nuclear GPER was shown to bind regulatory sequences of cancer-relevant target genes and to induce their expression. We decided to find out what induces the nuclear localization of GPER, how general this phenomenon is, and what its functional significance is. We discovered that interfering with N-linked glycosylation of GPER, either by mutation of the predicted glycosylation sites or pharmacologically with tunicamycin, drives GPER into the nucleus. Surveying a small set of CAFs from breast cancer biopsies, we found that a relatively common single nucleotide polymorphism, which results in the expression of a GPER variant with the amino acid substitution P16L, is associated with the nuclear localization of GPER. GPER with P16L fails to be glycosylated, presumably because of a conformational effect on the nearby glycosylation sites. GPER P16L is defective for membrane-associated signaling, but instead acts like an estrogen-stimulated transcription factor. In CAFs, it induces the secretion of paracrine factors that promote the migration of carcinoma cells. This raises the possibility that the GPER P16L polymorphism could be a risk factor for breast cancer.

Type of Resection (Whipple vs. Distal) Does Not Affect the National Failure to Provide Post-resection Adjuvant Chemotherapy in Localized Pancreatic Cancer.

PubMed

Bergquist, John R; Ivanics, Tommy; Shubert, Christopher R; Habermann, Elizabeth B; Smoot, Rory L; Kendrick, Michael L; Nagorney, David M; Farnell, Michael B; Truty, Mark J

2017-06-01

Adjuvant chemotherapy improves survival after curative intent resection for localized pancreatic adenocarcinoma (PDAC). Given the differences in perioperative morbidity, we hypothesized that patients undergoing distal partial pancreatectomy (DPP) would receive adjuvant therapy more often those undergoing pancreatoduodenectomy (PD). The National Cancer Data Base (2004-2012) identified patients with localized PDAC undergoing DPP and PD, excluding neoadjuvant cases, and factors associated with receipt of adjuvant therapy were identified. Overall survival (OS) was analyzed using multivariable Cox proportional hazards regression. Overall, 13,501 patients were included (DPP, n = 1933; PD, n = 11,568). Prognostic characteristics were similar, except DPP patients had fewer N1 lesions, less often positive margins, more minimally invasive resections, and shorter hospital stay. The proportion of patients not receiving adjuvant chemotherapy was equivalent (DPP 33.7%, PD 32.0%; p = 0.148). The type of procedure was not independently associated with adjuvant chemotherapy (hazard ratio 0.96, 95% confidence interval 0.90-1.02; p = 0.150), and patients receiving adjuvant chemotherapy had improved unadjusted and adjusted OS compared with surgery alone. The type of resection did not predict adjusted mortality (p = 0.870). Receipt of adjuvant chemotherapy did not vary by type of resection but improved survival independent of procedure performed. Factors other than type of resection appear to be driving the nationwide rates of post-resection adjuvant chemotherapy in localized PDAC.

Leukocytosis and neutrophilia predict outcome in locally advanced esophageal cancer treated with definitive chemoradiation

PubMed Central

Schernberg, Antoine; Moureau-Zabotto, Laurence; Del Campo, Eleonor Rivin; Escande, Alexandre; Ducreux, Michel; Nguyen, France; Goere, Diane; Chargari, Cyrus; Deutsch, Eric

2017-01-01

Purpose To investigate the prognostic value of leukocyte and neutrophil count as biomarkers in patients with locally advanced esophageal squamous cell carcinoma (SCC) undergoing exclusive chemoradiation. Results A total of 126 patients were identified. Respectively, 33% and 35% displayed baseline leukocytosis and neutrophilia. Estimated 3-year OS and PFS from chemoradiation completion were 31% and 25%, respectively. In univariate analysis, both leukocytosis and neutrophilia were associated with worse OS, PFS, and LRC (p < 0.01). In multivariate analysis, leukocytosis remained an independent risk factor associated with poorer OS, PFS and LRC (p < 0.05), independently from tumor stage and length, with higher prognostic value for OS compared with patients’ performance status (PS). Materials and Methods Bi-institutional clinical records from consecutive non-operable patients treated between 2003 and 2015 with definitive chemoradiation for locally advanced esophageal carcinoma were reviewed. Leukocytosis and neutrophilia were defined as a leukocyte or neutrophil count over 10 G/L and 7 G/L, respectively. These parameters were studied for their potential correlation with overall survival (OS), progression free survival (PFS), locoregional control (LRC) and distant metastases control (DMC). Conclusions Leukocytosis and neutrophilia were independent prognostic factors of poor OS, PFS, and LRC in this bi-institutional series of locally advanced esophageal SCC treated with definitive chemoradiation. Although prospective confirmation is warranted, it is suggested that the leukocyte and neutrophil count parameters might be clinically relevant biomarkers to be considered for further clinical investigations. PMID:28086222

On the stability analysis of approximate factorization methods for 3D Euler and Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Demuren, A. O.; Ibraheem, S. O.

1993-01-01

The convergence characteristics of various approximate factorizations for the 3D Euler and Navier-Stokes equations are examined using the von-Neumann stability analysis method. Three upwind-difference based factorizations and several central-difference based factorizations are considered for the Euler equations. In the upwind factorizations both the flux-vector splitting methods of Steger and Warming and van Leer are considered. Analysis of the Navier-Stokes equations is performed only on the Beam and Warming central-difference scheme. The range of CFL numbers over which each factorization is stable is presented for one-, two-, and three-dimensional flow. Also presented for each factorization is the CFL number at which the maximum eigenvalue is minimized, for all Fourier components, as well as for the high frequency range only. The latter is useful for predicting the effectiveness of multigrid procedures with these schemes as smoothers. Further, local mode analysis is performed to test the suitability of using a uniform flow field in the stability analysis. Some inconsistencies in the results from previous analyses are resolved.

Mapping Arid Vegetation Species Distributions in the White Mountains, Eastern California, Using AVIRIS, Topography, and Geology

NASA Technical Reports Server (NTRS)

VandeVen, C.; Weiss, S. B.

2001-01-01

Our challenge is to model plant species distributions in complex montane environments using disparate sources of data, including topography, geology, and hyperspectral data. From an ecologist's point of view, species distributions are determined by local environment and disturbance history, while spectral data are 'ancillary.' However, a remote sensor's perspective says that spectral data provide picture of what vegetation is there, topographic and geologic data are ancillary. In order to bridge the gap, all available data should be used to get the best possible prediction of species distributions using complex multivariate techniques implemented on a GIS. Vegetation reflects local climatic and nutrient conditions, both of which can be modeled, allowing predictive mapping of vegetation distributions. Geologic substrate strongly affects chemical, thermal, and physical properties of soils, while climatic conditions are determined by local topography. As elevation increases, precipitation increases and temperature decreases. Aspect, slope, and surrounding topography determine potential insolation, so that south-facing slopes are warmer and north-facing slopes cooler at a given elevation. Topographic position (ridge, slope, canyon, or meadow) and slope angle affect sediment accumulation and soil depth. These factors combine as complex environmental gradients, and underlie many features of plant distributions. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data, digital elevation models, digitized geologic maps, and 378 ground control points were used to predictively map species distributions in the central and southern White Mountains, along the western boundary of the Basin and Range province. Minimum Noise Fraction (MNF) bands were calculated from the visible and near-infrared AVIRIS bands, and combined with digitized geologic maps and topographic variables using Canonical Correspondence Analysis (CCA). CCA allows for modeling species 'envelopes' in multidimensional environmental space, which can then be projected across entire landscapes.

PSORTb 3.0: improved protein subcellular localization prediction with refined localization subcategories and predictive capabilities for all prokaryotes.

PubMed

Yu, Nancy Y; Wagner, James R; Laird, Matthew R; Melli, Gabor; Rey, Sébastien; Lo, Raymond; Dao, Phuong; Sahinalp, S Cenk; Ester, Martin; Foster, Leonard J; Brinkman, Fiona S L

2010-07-01

PSORTb has remained the most precise bacterial protein subcellular localization (SCL) predictor since it was first made available in 2003. However, the recall needs to be improved and no accurate SCL predictors yet make predictions for archaea, nor differentiate important localization subcategories, such as proteins targeted to a host cell or bacterial hyperstructures/organelles. Such improvements should preferably be encompassed in a freely available web-based predictor that can also be used as a standalone program. We developed PSORTb version 3.0 with improved recall, higher proteome-scale prediction coverage, and new refined localization subcategories. It is the first SCL predictor specifically geared for all prokaryotes, including archaea and bacteria with atypical membrane/cell wall topologies. It features an improved standalone program, with a new batch results delivery system complementing its web interface. We evaluated the most accurate SCL predictors using 5-fold cross validation plus we performed an independent proteomics analysis, showing that PSORTb 3.0 is the most accurate but can benefit from being complemented by Proteome Analyst predictions. http://www.psort.org/psortb (download open source software or use the web interface). psort-mail@sfu.ca Supplementary data are available at Bioinformatics online.

Postoperative re-irradiation using stereotactic body radiotherapy for metastatic epidural spinal cord compression.

PubMed

Ito, Kei; Nihei, Keiji; Shimizuguchi, Takuya; Ogawa, Hiroaki; Furuya, Tomohisa; Sugita, Shurei; Hozumi, Takahiro; Keisuke Sasai; Karasawa, Katsuyuki

2018-06-15

OBJECTIVE This study aimed to clarify the outcomes of postoperative re-irradiation using stereotactic body radiotherapy (SBRT) for metastatic epidural spinal cord compression (MESCC) in the authors' institution and to identify factors correlated with local control. METHODS Cases in which patients with previously irradiated MESCC underwent decompression surgery followed by spine SBRT as re-irradiation between April 2013 and May 2017 were retrospectively reviewed. The surgical procedures were mainly performed by the posterior approach and included decompression and fixation. The prescribed dose for spine SBRT was 24 Gy in 2 fractions. The primary outcome was local control, which was defined as elimination, shrinkage, or no change of the tumor on CT or MRI obtained approximately every 3 months after SBRT. In addition, various patient-, treatment-, and tumor-specific factors were evaluated to determine their predictive value for local control. RESULTS Twenty-eight cases were identified in the authors' institutional databases as meeting the inclusion criteria. The histology of the primary disease was thyroid cancer in 7 cases, lung cancer in 6, renal cancer in 3, colorectal cancer in 3, and other cancers in 9. The most common previous radiation dose was 30 Gy in 10 fractions (15 cases). The mean interval since the most recent irradiation was 16 months (range 5-132 months). The median duration of follow-up after SBRT was 13 months (range 4-38 months). The 1-year local control rate was 70%. In the analysis of factors related to local control, Bilsky grade, number of vertebral levels in the treatment target, the interval between the latest radiotherapy and SBRT, recursive partitioning analysis (RPA), the prognostic index for spinal metastases (PRISM), and the revised Tokuhashi score were not significantly correlated with local control. The favorable group classified by the Rades prognostic score achieved a significantly higher 1-year local control rate than the unfavorable group (1-year local control rate: 100% vs 33%; p < 0.01). Radiation-induced myelopathy and vertebral compression fracture were observed in 1 and 3 patients, respectively. No other grade 3 or greater toxicities were encountered. CONCLUSIONS The results indicate that spine SBRT as postoperative re-irradiation was effective, and it was especially useful for patients classified as having a good survival prognosis according to the Rades score.

Factors which predict violence victimization in Nigeria

PubMed Central

Fry, Lincoln J.

2014-01-01

Background: Violence is a major public health issue, globally as well as in the African continent. This paper looks at Nigeria and begins the process of identifying the factors that predict interpersonal violence in that country. The purpose is to interpret the implications of the results presented here for violence prevention programmes in Nigeria. Materials and Methods: The study is based on the responses of 2324 Nigerians included in Round Four of the Afrobarometer surveys. The study concentrates on 579 respondents who reported either they or someone else in their family had been the victim of violence, defined as being physically attacked, in the past year. Results: A logistical regression analysis revealed five significant factors that predicted interpersonal violence: being the victim of a property crime, the fear of crime, the respondents faith, whethera police station was in the local area and poverty. The findings revealed that 43.7% of the sample had been victimised within the past year and 18.8% had been the victim of both violent and property crimes. One surprising findingwas the number of respondents who were re-victimised; 75% of violence victims also had been property crime victims. Conclusions: These findings suggest that target hardening should be the basis to plan, implement and evaluate violence prevention programmes in Nigeria. Prevention personnel and/or law enforcement need to respond to reported incidents of property and/or violence victimisation and attempt to prepare victims to protect both their premises and their persons in the future. PMID:24970968

Prediction of CT Substitutes from MR Images Based on Local Diffeomorphic Mapping for Brain PET Attenuation Correction.

PubMed

Wu, Yao; Yang, Wei; Lu, Lijun; Lu, Zhentai; Zhong, Liming; Huang, Meiyan; Feng, Yanqiu; Feng, Qianjin; Chen, Wufan

2016-10-01

Attenuation correction is important for PET reconstruction. In PET/MR, MR intensities are not directly related to attenuation coefficients that are needed in PET imaging. The attenuation coefficient map can be derived from CT images. Therefore, prediction of CT substitutes from MR images is desired for attenuation correction in PET/MR. This study presents a patch-based method for CT prediction from MR images, generating attenuation maps for PET reconstruction. Because no global relation exists between MR and CT intensities, we propose local diffeomorphic mapping (LDM) for CT prediction. In LDM, we assume that MR and CT patches are located on 2 nonlinear manifolds, and the mapping from the MR manifold to the CT manifold approximates a diffeomorphism under a local constraint. Locality is important in LDM and is constrained by the following techniques. The first is local dictionary construction, wherein, for each patch in the testing MR image, a local search window is used to extract patches from training MR/CT pairs to construct MR and CT dictionaries. The k-nearest neighbors and an outlier detection strategy are then used to constrain the locality in MR and CT dictionaries. Second is local linear representation, wherein, local anchor embedding is used to solve MR dictionary coefficients when representing the MR testing sample. Under these local constraints, dictionary coefficients are linearly transferred from the MR manifold to the CT manifold and used to combine CT training samples to generate CT predictions. Our dataset contains 13 healthy subjects, each with T1- and T2-weighted MR and CT brain images. This method provides CT predictions with a mean absolute error of 110.1 Hounsfield units, Pearson linear correlation of 0.82, peak signal-to-noise ratio of 24.81 dB, and Dice in bone regions of 0.84 as compared with real CTs. CT substitute-based PET reconstruction has a regression slope of 1.0084 and R 2 of 0.9903 compared with real CT-based PET. In this method, no image segmentation or accurate registration is required. Our method demonstrates superior performance in CT prediction and PET reconstruction compared with competing methods. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Rate and extent of protein localization is controlled by peptide-binding domain association kinetics and morphology.

PubMed

Mills, Evan; Truong, Kevin

2009-06-01

Protein localization is an important regulatory mechanism in many cell signaling pathways such as cytoskeletal organization and genetic regulation. The specific mechanism of protein localization determines the kinetics and morphological constraints of protein translocation, and thus affects the rate and extent of localization. To investigate the affect of localization kinetics and morphology on protein localization, we designed a protein localization system based on Ca(2+)-calmodulin and Src homology 3 domain binding peptides that can translocate between specific localizations in response to a Ca(2+) signal. We used a stochastic biomolecular simulator to predict that such a protein localization system will exhibit slower and less complete translocations when the association kinetics of a binding domain and peptide are reduced. As well, we predicted that increasing the diffusion resistance by manipulating the morphology of the system would similarly impair translocation speed and completeness. We then constructed a network of synthetic fusion proteins and showed that these predictions could be qualitatively confirmed in vitro. This work provides a basis for explaining the different characteristics (rate and extent) of protein transport and localization in cells as a consequence of the kinetics and morphology of the transport mechanism.

A Multifactorial Analysis of Melanoma: Prognostic Histopathological Features Comparing Clark's and Breslow's Staging Methods

PubMed Central

Balch, Charles M.; Murad, Tariq M.; Soong, Seng-Jaw; Ingalls, Anna Lee; Halpern, Norman B.; Maddox, William A.

1978-01-01

A multifactorial analysis was used to identify the dominant prognostic variables affecting survival from a computerized data base of 339 melanoma patients treated at this institution during the past 17 years. Five of the 13 parameters examined simultaneously were found to independently influence five year survival rates: 1) pathological stage (I vs II, p = 0.0014), 2) lesion ulceration (present vs absent, p = 0.006), 3) surgical treatment (wide excision vs wide excision plus lymphadenectomy, p = 0.024), 4) melanoma thickness (p = 0.032), and 5) location (upper extremity vs lower extremity vs trunk vs head and neck, p = 0.038). Additional factors considered that had either indirect or no influence on survival rates were clinical stage of disease, age, sex, level of invasion, pigmentation, lymphocyte infiltration, growth pattern, and regression. Most of these latter variables derived their prognostic value from correlation with melanoma thickness, except sex which correlated with location (extremity lesions were more frequent on females, trunk lesions on males). This statistical analysis enabled us to derive a mathematical equation for predicting an individual patient's probability of five year survival. Three categories of risk were delineated by measuring tumor thickness (Breslow microstaging) in Stage I patients: 1) thin melanomas (<0.76 mm) were associated with localized disease and a 100% cure rate: 2) intermediate thickness melanomas (0.76-4.00 mm) had an increasing risk (up to 80%) of harboring regional and/or distant metastases and 3) thick melanomas (≥4.00 mm) had a 80% risk of occult distant metastases at the time of initial presentation. The level of invasion (Clark's microstaging) correlated with survival, but was less predictive than measuring tumor thickness. Within each of Clark's Level II, III and IV groups, there were gradations of thickness with statistically different survival rates. Both microstaging methods (Breslow and Clark) were less predictive factors in patients with lymph node or distant metastases. Clinical trials evaluating alternative surgical treatments or adjunctive therapy modalities for melanoma patients should incorporate these parameters into their assessment, especially in Stage I (localized) disease where tumor thickness and the anatomical site of the primary melanoma are dominant prognostic factors. PMID:736651

Quantifying predictability variations in a low-order ocean-atmosphere model - A dynamical systems approach

NASA Technical Reports Server (NTRS)

Nese, Jon M.; Dutton, John A.

1993-01-01

The predictability of the weather and climatic states of a low-order moist general circulation model is quantified using a dynamic systems approach, and the effect of incorporating a simple oceanic circulation on predictability is evaluated. The predictability and the structure of the model attractors are compared using Liapunov exponents, local divergence rates, and the correlation and Liapunov dimensions. It was found that the activation of oceanic circulation increases the average error doubling time of the atmosphere and the coupled ocean-atmosphere system by 10 percent and decreases the variance of the largest local divergence rate by 20 percent. When an oceanic circulation develops, the average predictability of annually averaged states is improved by 25 percent and the variance of the largest local divergence rate decreases by 25 percent.

Micro Finite Element models of the vertebral body: Validation of local displacement predictions.

PubMed

Costa, Maria Cristiana; Tozzi, Gianluca; Cristofolini, Luca; Danesi, Valentina; Viceconti, Marco; Dall'Ara, Enrico

2017-01-01

The estimation of local and structural mechanical properties of bones with micro Finite Element (microFE) models based on Micro Computed Tomography images depends on the quality bone geometry is captured, reconstructed and modelled. The aim of this study was to validate microFE models predictions of local displacements for vertebral bodies and to evaluate the effect of the elastic tissue modulus on model's predictions of axial forces. Four porcine thoracic vertebrae were axially compressed in situ, in a step-wise fashion and scanned at approximately 39μm resolution in preloaded and loaded conditions. A global digital volume correlation (DVC) approach was used to compute the full-field displacements. Homogeneous, isotropic and linear elastic microFE models were generated with boundary conditions assigned from the interpolated displacement field measured from the DVC. Measured and predicted local displacements were compared for the cortical and trabecular compartments in the middle of the specimens. Models were run with two different tissue moduli defined from microindentation data (12.0GPa) and a back-calculation procedure (4.6GPa). The predicted sum of axial reaction forces was compared to the experimental values for each specimen. MicroFE models predicted more than 87% of the variation in the displacement measurements (R2 = 0.87-0.99). However, model predictions of axial forces were largely overestimated (80-369%) for a tissue modulus of 12.0GPa, whereas differences in the range 10-80% were found for a back-calculated tissue modulus. The specimen with the lowest density showed a large number of elements strained beyond yield and the highest predictive errors. This study shows that the simplest microFE models can accurately predict quantitatively the local displacements and qualitatively the strain distribution within the vertebral body, independently from the considered bone types.

Common neighbours and the local-community-paradigm for topological link prediction in bipartite networks

NASA Astrophysics Data System (ADS)

Daminelli, Simone; Thomas, Josephine Maria; Durán, Claudio; Vittorio Cannistraci, Carlo

2015-11-01

Bipartite networks are powerful descriptions of complex systems characterized by two different classes of nodes and connections allowed only across but not within the two classes. Unveiling physical principles, building theories and suggesting physical models to predict bipartite links such as product-consumer connections in recommendation systems or drug-target interactions in molecular networks can provide priceless information to improve e-commerce or to accelerate pharmaceutical research. The prediction of nonobserved connections starting from those already present in the topology of a network is known as the link-prediction problem. It represents an important subject both in many-body interaction theory in physics and in new algorithms for applied tools in computer science. The rationale is that the existing connectivity structure of a network can suggest where new connections can appear with higher likelihood in an evolving network, or where nonobserved connections are missing in a partially known network. Surprisingly, current complex network theory presents a theoretical bottle-neck: a general framework for local-based link prediction directly in the bipartite domain is missing. Here, we overcome this theoretical obstacle and present a formal definition of common neighbour index and local-community-paradigm (LCP) for bipartite networks. As a consequence, we are able to introduce the first node-neighbourhood-based and LCP-based models for topological link prediction that utilize the bipartite domain. We performed link prediction evaluations in several networks of different size and of disparate origin, including technological, social and biological systems. Our models significantly improve topological prediction in many bipartite networks because they exploit local physical driving-forces that participate in the formation and organization of many real-world bipartite networks. Furthermore, we present a local-based formalism that allows to intuitively implement neighbourhood-based link prediction entirely in the bipartite domain.

DeepLoc: prediction of protein subcellular localization using deep learning.

PubMed

Almagro Armenteros, José Juan; Sønderby, Casper Kaae; Sønderby, Søren Kaae; Nielsen, Henrik; Winther, Ole

2017-11-01

The prediction of eukaryotic protein subcellular localization is a well-studied topic in bioinformatics due to its relevance in proteomics research. Many machine learning methods have been successfully applied in this task, but in most of them, predictions rely on annotation of homologues from knowledge databases. For novel proteins where no annotated homologues exist, and for predicting the effects of sequence variants, it is desirable to have methods for predicting protein properties from sequence information only. Here, we present a prediction algorithm using deep neural networks to predict protein subcellular localization relying only on sequence information. At its core, the prediction model uses a recurrent neural network that processes the entire protein sequence and an attention mechanism identifying protein regions important for the subcellular localization. The model was trained and tested on a protein dataset extracted from one of the latest UniProt releases, in which experimentally annotated proteins follow more stringent criteria than previously. We demonstrate that our model achieves a good accuracy (78% for 10 categories; 92% for membrane-bound or soluble), outperforming current state-of-the-art algorithms, including those relying on homology information. The method is available as a web server at http://www.cbs.dtu.dk/services/DeepLoc. Example code is available at https://github.com/JJAlmagro/subcellular_localization. The dataset is available at http://www.cbs.dtu.dk/services/DeepLoc/data.php. jjalma@dtu.dk. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Ageing, exposure to pollution, and interactions between climate change and local seasons as oxidant conditions predicting incident hematologic malignancy at KINSHASA University clinics, Democratic Republic of CONGO (DRC).

PubMed

Nkanga, Mireille Solange Nganga; Longo-Mbenza, Benjamin; Adeniyi, Oladele Vincent; Ngwidiwo, Jacques Bikaula; Katawandja, Antoine Lufimbo; Kazadi, Paul Roger Beia; Nzonzila, Alain Nganga

2017-08-23

The global burden of hematologic malignancy (HM) is rapidly rising with aging, exposure to polluted environments, and global and local climate variability all being well-established conditions of oxidative stress. However, there is currently no information on the extent and predictors of HM at Kinshasa University Clinics (KUC), DR Congo (DRC). This study evaluated the impact of bio-clinical factors, exposure to polluted environments, and interactions between global climate changes (EL Nino and La Nina) and local climate (dry and rainy seasons) on the incidence of HM. This hospital-based prospective cohort study was conducted at Kinshasa University Clinics in DR Congo. A total of 105 black African adult patients with anaemia between 2009 and 2016 were included. HM was confirmed by morphological typing according to the French-American-British (FAB) Classification System. Gender, age, exposure to traffic pollution and garages/stations, global climate variability (El Nino and La Nina), and local climate (dry and rainy seasons) were potential independent variables to predict incident HM using Cox regression analysis and Kaplan Meier curves. Out of the total 105 patients, 63 experienced incident HM, with an incidence rate of 60%. After adjusting for gender, HIV/AIDS, and other bio-clinical factors, the most significant independent predictors of HM were age ≥ 55 years (HR = 2.4; 95% CI 1.4-4.3; P = 0.003), exposure to pollution and garages or stations (HR = 4.9; 95% CI 2-12.1; P < 0.001), combined local dry season + La Nina (HR = 4.6; 95%CI 1.8-11.8; P < 0.001), and combined local dry season + El Nino (HR = 4; 95% CI 1.6-9.7; P = 0.004). HM types included acute myeloid leukaemia (28.6% n = 18), multiple myeloma (22.2% n = 14), myelodysplastic syndromes (15.9% n = 10), chronic myeloid leukaemia (15.9% n = 10), chronic lymphoid leukaemia (9.5% n = 6), and acute lymphoid leukaemia (7.9% n = 5). After adjusting for confounders using Cox regression analysis, age ≥ 55 years, exposure to pollution, combined local dry season + La Nina and combined local dry season + El Nino were the most significant predictors of incident hematologic malignancy. These findings highlight the importance of aging, pollution, the dry season, El Nino and La Nina as related to global warming as determinants of hematologic malignancies among African patients from Kinshasa, DR Congo. Cancer registries in DRC and other African countries will provide more robust database for future researches on haematological malignancies in the region.

TEMPLE: analysing population genetic variation at transcription factor binding sites.

PubMed

Litovchenko, Maria; Laurent, Stefan

2016-11-01

Genetic variation occurring at the level of regulatory sequences can affect phenotypes and fitness in natural populations. This variation can be analysed in a population genetic framework to study how genetic drift and selection affect the evolution of these functional elements. However, doing this requires a good understanding of the location and nature of regulatory regions and has long been a major hurdle. The current proliferation of genomewide profiling experiments of transcription factor occupancies greatly improves our ability to identify genomic regions involved in specific DNA-protein interactions. Although software exists for predicting transcription factor binding sites (TFBS), and the effects of genetic variants on TFBS specificity, there are no tools currently available for inferring this information jointly with the genetic variation at TFBS in natural populations. We developed the software Transcription Elements Mapping at the Population LEvel (TEMPLE), which predicts TFBS, evaluates the effects of genetic variants on TFBS specificity and summarizes the genetic variation occurring at TFBS in intraspecific sequence alignments. We demonstrate that TEMPLE's TFBS prediction algorithms gives identical results to PATSER, a software distribution commonly used in the field. We also illustrate the unique features of TEMPLE by analysing TFBS diversity for the TF Senseless (SENS) in one ancestral and one cosmopolitan population of the fruit fly Drosophila melanogaster. TEMPLE can be used to localize TFBS that are characterized by strong genetic differentiation across natural populations. This will be particularly useful for studies aiming to identify adaptive mutations. TEMPLE is a java-based cross-platform software that easily maps the genetic diversity at predicted TFBSs using a graphical interface, or from the Unix command line. © 2016 John Wiley & Sons Ltd.

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.

Restrictive Factors and Output Forecast of Green Development of Agricultural Industry Based on Gray System

NASA Astrophysics Data System (ADS)

Sun, Fengru

2018-01-01

This paper analyzes the characteristics of agricultural products from the perspective of agricultural production, farmers’ income, adjustment of agricultural structure and environmental improvement, and analyzes the characteristics of agricultural products in LanZhou area. Through data mining and empirical analysis, the regional agriculture (1) forecasting model of gray system with dynamic data processing, combined with the output data of lily in 2004-2003, the yield prediction is predicted and the fitting state is good and the error is small. Finally, combined with the relevant characteristics of the local characteristics of the agricultural industry to make reference, by changing the characteristics of agricultural production as the center of the mindset, and agricultural industrialization and organic combination, take the characteristics of efficient industrialization of agricultural products.

Intermittent dynamics in complex systems driven to depletion.

PubMed

Escobar, Juan V; Pérez Castillo, Isaac

2018-03-19

When complex systems are driven to depletion by some external factor, their non-stationary dynamics can present an intermittent behaviour between relative tranquility and burst of activity whose consequences are often catastrophic. To understand and ultimately be able to predict such dynamics, we propose an underlying mechanism based on sharp thresholds of a local generalized energy density that naturally leads to negative feedback. We find a transition from a continuous regime to an intermittent one, in which avalanches can be predicted despite the stochastic nature of the process. This model may have applications in many natural and social complex systems where a rapid depletion of resources or generalized energy drives the dynamics. In particular, we show how this model accurately describes the time evolution and avalanches present in a real social system.

A Particle Swarm Optimization-Based Approach with Local Search for Predicting Protein Folding.

PubMed

Yang, Cheng-Hong; Lin, Yu-Shiun; Chuang, Li-Yeh; Chang, Hsueh-Wei

2017-10-01

The hydrophobic-polar (HP) model is commonly used for predicting protein folding structures and hydrophobic interactions. This study developed a particle swarm optimization (PSO)-based algorithm combined with local search algorithms; specifically, the high exploration PSO (HEPSO) algorithm (which can execute global search processes) was combined with three local search algorithms (hill-climbing algorithm, greedy algorithm, and Tabu table), yielding the proposed HE-L-PSO algorithm. By using 20 known protein structures, we evaluated the performance of the HE-L-PSO algorithm in predicting protein folding in the HP model. The proposed HE-L-PSO algorithm exhibited favorable performance in predicting both short and long amino acid sequences with high reproducibility and stability, compared with seven reported algorithms. The HE-L-PSO algorithm yielded optimal solutions for all predicted protein folding structures. All HE-L-PSO-predicted protein folding structures possessed a hydrophobic core that is similar to normal protein folding.

CNNH_PSS: protein 8-class secondary structure prediction by convolutional neural network with highway.

PubMed

Zhou, Jiyun; Wang, Hongpeng; Zhao, Zhishan; Xu, Ruifeng; Lu, Qin

2018-05-08

Protein secondary structure is the three dimensional form of local segments of proteins and its prediction is an important problem in protein tertiary structure prediction. Developing computational approaches for protein secondary structure prediction is becoming increasingly urgent. We present a novel deep learning based model, referred to as CNNH_PSS, by using multi-scale CNN with highway. In CNNH_PSS, any two neighbor convolutional layers have a highway to deliver information from current layer to the output of the next one to keep local contexts. As lower layers extract local context while higher layers extract long-range interdependencies, the highways between neighbor layers allow CNNH_PSS to have ability to extract both local contexts and long-range interdependencies. We evaluate CNNH_PSS on two commonly used datasets: CB6133 and CB513. CNNH_PSS outperforms the multi-scale CNN without highway by at least 0.010 Q8 accuracy and also performs better than CNF, DeepCNF and SSpro8, which cannot extract long-range interdependencies, by at least 0.020 Q8 accuracy, demonstrating that both local contexts and long-range interdependencies are indeed useful for prediction. Furthermore, CNNH_PSS also performs better than GSM and DCRNN which need extra complex model to extract long-range interdependencies. It demonstrates that CNNH_PSS not only cost less computer resource, but also achieves better predicting performance. CNNH_PSS have ability to extracts both local contexts and long-range interdependencies by combing multi-scale CNN and highway network. The evaluations on common datasets and comparisons with state-of-the-art methods indicate that CNNH_PSS is an useful and efficient tool for protein secondary structure prediction.

Predicting Posttraumatic Stress Symptom Prevalence and Local Distribution after an Earthquake with Scarce Data.

PubMed

Dussaillant, Francisca; Apablaza, Mauricio

2017-08-01

After a major earthquake, the assignment of scarce mental health emergency personnel to different geographic areas is crucial to the effective management of the crisis. The scarce information that is available in the aftermath of a disaster may be valuable in helping predict where are the populations that are in most need. The objectives of this study were to derive algorithms to predict posttraumatic stress (PTS) symptom prevalence and local distribution after an earthquake and to test whether there are algorithms that require few input data and are still reasonably predictive. A rich database of PTS symptoms, informed after Chile's 2010 earthquake and tsunami, was used. Several model specifications for the mean and centiles of the distribution of PTS symptoms, together with posttraumatic stress disorder (PTSD) prevalence, were estimated via linear and quantile regressions. The models varied in the set of covariates included. Adjusted R2 for the most liberal specifications (in terms of numbers of covariates included) ranged from 0.62 to 0.74, depending on the outcome. When only including peak ground acceleration (PGA), poverty rate, and household damage in linear and quadratic form, predictive capacity was still good (adjusted R2 from 0.59 to 0.67 were obtained). Information about local poverty, household damage, and PGA can be used as an aid to predict PTS symptom prevalence and local distribution after an earthquake. This can be of help to improve the assignment of mental health personnel to the affected localities. Dussaillant F , Apablaza M . Predicting posttraumatic stress symptom prevalence and local distribution after an earthquake with scarce data. Prehosp Disaster Med. 2017;32(4):357-367.

The fluctuating resource hypothesis explains invasibility, but not exotic advantage following disturbance.

PubMed

Pearson, Dean E; Ortega, Yvette K; Villarreal, Diego; Lekberg, Ylva; Cock, Marina C; Eren, Özkan; Hierro, José L

2018-06-01

Invasibility is a key indicator of community susceptibility to changes in structure and function. The fluctuating resource hypothesis (FRH) postulates that invasibility is an emergent community property, a manifestation of multiple processes that cannot be reliably predicted by individual community attributes like diversity or productivity. Yet, research has emphasized the role of these individual attributes, with the expectation that diversity should deter invasibility and productivity enhance it. In an effort to explore how these and other factors may influence invasibility, we evaluated the relationship between invasibility and species richness, productivity, resource availability, and resilience in experiments crossing disturbance with exotic seed addition in 1-m 2 plots replicated over large expanses of grasslands in Montana, USA and La Pampa, Argentina. Disturbance increased invasibility as predicted by FRH, but grasslands were more invasible in Montana than La Pampa whether disturbed or not, despite Montana's higher species richness and lower productivity. Moreover, invasibility correlated positively with nitrogen availability and negatively with native plant cover. These patterns suggested that resource availability and the ability of the community to recover from disturbance (resilience) better predicted invasibility than either species richness or productivity, consistent with predictions from FRH. However, in ambient, unseeded plots in Montana, disturbance reduced native cover by >50% while increasing exotic cover >200%. This provenance bias could not be explained by FRH, which predicts that colonization processes act on species' traits independent of origins. The high invasibility of Montana grasslands following disturbance was associated with a strong shift from perennial to annual species, as predicted by succession theory. However, this shift was driven primarily by exotic annuals, which were more strongly represented than perennials in local exotic vs. native species pools. We attribute this provenance bias to extrinsic biogeographic factors such as disparate evolutionary histories and/or introduction filters selecting for traits that favor exotics following disturbance. Our results suggest that (1) invasibility is an emergent property best explained by a community's efficiency in utilizing resources, as predicted by FRH but (2) understanding provenance biases in biological invasions requires moving beyond FRH to incorporate extrinsic biogeographic factors that may favor exotics in community assembly. © 2018 by the Ecological Society of America.

Predictors of human rotation.

PubMed

Stochl, Jan; Croudace, Tim

2013-01-01

Why some humans prefer to rotate clockwise rather than anticlockwise is not well understood. This study aims to identify the predictors of the preferred rotation direction in humans. The variables hypothesised to influence rotation preference include handedness, footedness, sex, brain hemisphere lateralisation, and the Coriolis effect (which results from geospatial location on the Earth). An online questionnaire allowed us to analyse data from 1526 respondents in 97 countries. Factor analysis showed that the direction of rotation should be studied separately for local and global movements. Handedness, footedness, and the item hypothesised to measure brain hemisphere lateralisation are predictors of rotation direction for both global and local movements. Sex is a predictor of the direction of global rotation movements but not local ones, and both sexes tend to rotate clockwise. Geospatial location does not predict the preferred direction of rotation. Our study confirms previous findings concerning the influence of handedness, footedness, and sex on human rotation; our study also provides new insight into the underlying structure of human rotation movements and excludes the Coriolis effect as a predictor of rotation.

Local and regional factors affecting atmospheric mercury speciation at a remote location

USGS Publications Warehouse

Manolopoulos, H.; Schauer, J.J.; Purcell, M.D.; Rudolph, T.M.; Olson, M.L.; Rodger, B.; Krabbenhoft, D.P.

2007-01-01

Atmospheric concentrations of elemental (Hg0), reactive gaseous (RGM), and particulate (PHg) mercury were measured at two remote sites in the midwestern United States. Concurrent measurements of Hg0, PHg, and RGM obtained at Devil's Lake and Mt. Horeb, located approximately 65 km apart, showed that Hg0 and PHg concentrations were affected by regional, as well as local sources, while RGM was mainly impacted by local sources. Plumes reaching the Devil's Lake site from a nearby coal-fired power plant significantly impacted SO2 and RGM concentrations at Devil's Lake, but had little impact on Hg0. Our findings suggest that traditional modeling approaches to assess sources of mercury deposited that utilize source emissions and large-scale grids may not be sufficient to predict mercury deposition at sensitive locations due to the importance of small-scale sources and processes. We suggest the use of a receptor-based monitoring to better understand mercury source-receptor relationships. ?? 2007 NRC Canada.

Dynamic motif occupancy (DynaMO) analysis identifies transcription factors and their binding sites driving dynamic biological processes.

PubMed

Kuang, Zheng; Ji, Zhicheng; Boeke, Jef D; Ji, Hongkai

2018-01-09

Biological processes are usually associated with genome-wide remodeling of transcription driven by transcription factors (TFs). Identifying key TFs and their spatiotemporal binding patterns are indispensable to understanding how dynamic processes are programmed. However, most methods are designed to predict TF binding sites only. We present a computational method, dynamic motif occupancy analysis (DynaMO), to infer important TFs and their spatiotemporal binding activities in dynamic biological processes using chromatin profiling data from multiple biological conditions such as time-course histone modification ChIP-seq data. In the first step, DynaMO predicts TF binding sites with a random forests approach. Next and uniquely, DynaMO infers dynamic TF binding activities at predicted binding sites using their local chromatin profiles from multiple biological conditions. Another landmark of DynaMO is to identify key TFs in a dynamic process using a clustering and enrichment analysis of dynamic TF binding patterns. Application of DynaMO to the yeast ultradian cycle, mouse circadian clock and human neural differentiation exhibits its accuracy and versatility. We anticipate DynaMO will be generally useful for elucidating transcriptional programs in dynamic processes. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Control of the spontaneous emission from a single quantum dash using a slow-light mode in a two-dimensional photonic crystal on a Bragg reflector

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

Chauvin, N.; Fiore, A.; Nedel, P.

2009-07-15

We demonstrate the coupling of a single InAs/InP quantum, emitting around 1.55 {mu}m, to a slow-light mode in a two-dimensional photonic crystal on Bragg reflector. These surface addressable 2.5D photonic crystal band-edge modes present the advantages of a vertical emission and the mode area and localization may be controlled, leading to a less critical spatial alignment with the emitter. An increase in the spontaneous emission rate by a factor of 1.5-2 is measured at low temperature and is compared to the Purcell factor predicted by three-dimensional time-domain electromagnetic simulations.

Predicted 25(OH)D score and colorectal cancer risk according to vitamin D receptor expression.

PubMed

Jung, Seungyoun; Qian, Zhi Rong; Yamauchi, Mai; Bertrand, Kimberly A; Fitzgerald, Kathryn C; Inamura, Kentaro; Kim, Sun A; Mima, Kosuke; Sukawa, Yasutaka; Zhang, Xuehong; Wang, Molin; Smith-Warner, Stephanie A; Wu, Kana; Fuchs, Charles S; Chan, Andrew T; Giovannucci, Edward L; Ng, Kimmie; Cho, Eunyoung; Ogino, Shuji; Nishihara, Reiko

2014-08-01

Despite accumulating evidence for the preventive effect of vitamin D on colorectal carcinogenesis, its precise mechanisms remain unclear. We hypothesized that vitamin D was associated with a lower risk of colorectal cancer with high-level vitamin D receptor (VDR) expression, but not with risk of tumor with low-level VDR expression. Among 140,418 participants followed from 1986 through 2008 in the Nurses' Health Study and the Health Professionals' Follow-up Study, we identified 1,059 incident colorectal cancer cases with tumor molecular data. The predicted 25-hydroxyvitamin D [25(OH)D] score was developed using the known determinants of plasma 25(OH)D. We estimated the HR for cancer subtypes using the duplication method Cox proportional hazards model. A higher predicted 25(OH)D score was associated with a lower risk of colorectal cancer irrespective of VDR expression level (P(heterogeneity) for subtypes = 0.75). Multivariate HRs (95% confidence intervals) comparing the highest with the lowest quintile of predicted 25(OH)D scores were 0.48 (0.30-0.78) for VDR-negative tumor and 0.56 (0.42-0.75) for VDR-positive tumor. Similarly, the significant inverse associations of the predicted 25(OH)D score with colorectal cancer risk did not significantly differ by KRAS, BRAF, or PIK3CA status (P(heterogeneity) for subtypes ≥ 0.22). A higher predicted vitamin D score was significantly associated with a lower colorectal cancer risk, regardless of VDR status and other molecular features examined. The preventive effect of vitamin D on colorectal carcinogenesis may not totally depend on tumor factors. Host factors (such as local and systemic immunity) may need to be considered. ©2014 American Association for Cancer Research.

An evidential link prediction method and link predictability based on Shannon entropy

NASA Astrophysics Data System (ADS)

Yin, Likang; Zheng, Haoyang; Bian, Tian; Deng, Yong

2017-09-01

Predicting missing links is of both theoretical value and practical interest in network science. In this paper, we empirically investigate a new link prediction method base on similarity and compare nine well-known local similarity measures on nine real networks. Most of the previous studies focus on the accuracy, however, it is crucial to consider the link predictability as an initial property of networks itself. Hence, this paper has proposed a new link prediction approach called evidential measure (EM) based on Dempster-Shafer theory. Moreover, this paper proposed a new method to measure link predictability via local information and Shannon entropy.

Effect of scale on trait predictors of species responses to agriculture.

PubMed

Gilroy, James J; Medina Uribe, Claudia A; Haugaasen, Torbjørn; Edwards, David P

2015-04-01

Species persistence in human-altered landscapes can depend on factors operating at multiple spatial scales. To understand anthropogenic impacts on biodiversity, it is useful to examine relationships between species traits and their responses to land-use change. A key knowledge gap concerns whether these relationships vary depending on the scale of response under consideration. We examined how local- and large-scale habitat variables influence the occupancy dynamics of a bird community in cloud forest zones in the Colombian Chocó-Andes. Using data collected across a continuum of forest and agriculture, we examined which traits best predict species responses to local variation in farmland and which traits best predict species responses to isolation from contiguous forest. Global range size was a strong predictor of species responses to agriculture at both scales; widespread species were less likely to decline as local habitat cover decreased and as distance from forest increased. Habitat specialization was a strong predictor of species responses only at the local scale. Open-habitat species were particularly likely to increase as pasture increased, but they were relatively insensitive to variation in distance to forest. Foraging plasticity and flocking behavior were strong predictors of species responses to distance from forest, but not their responses to local habitat. Species with lower plasticity in foraging behaviors and obligate flock-following species were more likely to decline as distance from contiguous forest increased. For species exhibiting these latter traits, persistence in tropical landscapes may depend on the protection of larger contiguous blocks of forest, rather than the integration of smaller-scale woodland areas within farmland. Species listed as threatened or near threatened on the International Union for Conservation of Nature Red List were also more likely to decline in response to both local habitat quality and isolation from forest relative to least-concern species, underlining the importance of contiguous forests for threatened taxa. © 2014 Society for Conservation Biology.

Frailty Index Predicts All-Cause Mortality for Middle-Aged and Older Taiwanese: Implications for Active-Aging Programs.

PubMed

Lin, Shu-Yu; Lee, Wei-Ju; Chou, Ming-Yueh; Peng, Li-Ning; Chiou, Shu-Ti; Chen, Liang-Kung

2016-01-01

Frailty Index, defined as an individual's accumulated proportion of listed health-related deficits, is a well-established metric used to assess the health status of old adults; however, it has not yet been developed in Taiwan, and its local related structure factors remain unclear. The objectives were to construct a Taiwan Frailty Index to predict mortality risk, and to explore the structure of its factors. Analytic data on 1,284 participants aged 53 and older were excerpted from the Social Environment and Biomarkers of Aging Study (2006), in Taiwan. A consensus workgroup of geriatricians selected 159 items according to the standard procedure for creating a Frailty Index. Cox proportional hazard modeling was used to explore the association between the Taiwan Frailty Index and mortality. Exploratory factor analysis was used to identify structure factors and produce a shorter version-the Taiwan Frailty Index Short-Form. During an average follow-up of 4.3 ± 0.8 years, 140 (11%) subjects died. Compared to those in the lowest Taiwan Frailty Index tertile (< 0.18), those in the uppermost tertile (> 0.23) had significantly higher risk of death (Hazard ratio: 3.2; 95% CI 1.9-5.4). Thirty-five items of five structure factors identified by exploratory factor analysis, included: physical activities, life satisfaction and financial status, health status, cognitive function, and stresses. Area under the receiver operating characteristic curves (C-statistics) of the Taiwan Frailty Index and its Short-Form were 0.80 and 0.78, respectively, with no statistically significant difference between them. Although both the Taiwan Frailty Index and Short-Form were associated with mortality, the Short-Form, which had similar accuracy in predicting mortality as the full Taiwan Frailty Index, would be more expedient in clinical practice and community settings to target frailty screening and intervention.

Immunohistochemistry predictive markers for primary colorectal cancer tumors: where are we and where are we going?

PubMed

Bărbălan, Alexandru; Nicolaescu, Andrei Cristian; Măgăran, Antoanela Valentina; Mercuţ, Răzvan; Bălăşoiu, Maria; Băncescu, Gabriela; Şerbănescu, Mircea Sebastian; Lazăr, Octavian Fulger; Săftoiu, Adrian

2018-01-01

The aim of our study is to highlight and organize the recently published immunohistochemistry (IHC) predictive biomarkers of primary colorectal cancers (CRCs) that could lead to practical implementation. We reviewed articles that examined CRC samples with significant statistic correlation between the IHC marker expression and disease progression over time, relationships with the available clinical features and those who detect the prognosis of drug effects. Our analysis showed that nine markers could correlate with medical treatment response of CRCs in different stages. When using better overall survival (OS) and better disease-free survival (DFS) as a grouping factor, there were 14 markers that could be used in assessing CRC prognosis. By using poor prognostic for the OS and the DFS as a grouping factor, we found 43 markers. Subgroup analysis was also performed based on the 32 markers recently confirmed to predict metastasis evolution or the recurrence risks. Venous invasion could be predictable for tumors, statistically significant metastasis susceptibility was observed for markers and also the capacity to evaluate recurrence. CRCs integrate a variety of localizations and there are proofs that distinguish the sites of tumors. The studies reporting data specifically for rectal cancer separating it from colon cancer contained seven IHC markers. In order to be able to implement a predictive biomarker in clinical practice, it must comply with certain criteria as clinical value and analytical proof. Unique biological signature of CRC can be distinguished by identifying biomarkers expression. Several markers have shown potential, but the majority still need to render clinical utility.

The influence of local spring temperature variance on temperature sensitivity of spring phenology.

PubMed

Wang, Tao; Ottlé, Catherine; Peng, Shushi; Janssens, Ivan A; Lin, Xin; Poulter, Benjamin; Yue, Chao; Ciais, Philippe

2014-05-01

The impact of climate warming on the advancement of plant spring phenology has been heavily investigated over the last decade and there exists great variability among plants in their phenological sensitivity to temperature. However, few studies have explicitly linked phenological sensitivity to local climate variance. Here, we set out to test the hypothesis that the strength of phenological sensitivity declines with increased local spring temperature variance, by synthesizing results across ground observations. We assemble ground-based long-term (20-50 years) spring phenology database (PEP725 database) and the corresponding climate dataset. We find a prevalent decline in the strength of phenological sensitivity with increasing local spring temperature variance at the species level from ground observations. It suggests that plants might be less likely to track climatic warming at locations with larger local spring temperature variance. This might be related to the possibility that the frost risk could be higher in a larger local spring temperature variance and plants adapt to avoid this risk by relying more on other cues (e.g., high chill requirements, photoperiod) for spring phenology, thus suppressing phenological responses to spring warming. This study illuminates that local spring temperature variance is an understudied source in the study of phenological sensitivity and highlight the necessity of incorporating this factor to improve the predictability of plant responses to anthropogenic climate change in future studies. © 2013 John Wiley & Sons Ltd.

Binding ligand prediction for proteins using partial matching of local surface patches.

PubMed

Sael, Lee; Kihara, Daisuke

2010-01-01

Functional elucidation of uncharacterized protein structures is an important task in bioinformatics. We report our new approach for structure-based function prediction which captures local surface features of ligand binding pockets. Function of proteins, specifically, binding ligands of proteins, can be predicted by finding similar local surface regions of known proteins. To enable partial comparison of binding sites in proteins, a weighted bipartite matching algorithm is used to match pairs of surface patches. The surface patches are encoded with the 3D Zernike descriptors. Unlike the existing methods which compare global characteristics of the protein fold or the global pocket shape, the local surface patch method can find functional similarity between non-homologous proteins and binding pockets for flexible ligand molecules. The proposed method improves prediction results over global pocket shape-based method which was previously developed by our group.

Binding Ligand Prediction for Proteins Using Partial Matching of Local Surface Patches

PubMed Central

Sael, Lee; Kihara, Daisuke

2010-01-01

Functional elucidation of uncharacterized protein structures is an important task in bioinformatics. We report our new approach for structure-based function prediction which captures local surface features of ligand binding pockets. Function of proteins, specifically, binding ligands of proteins, can be predicted by finding similar local surface regions of known proteins. To enable partial comparison of binding sites in proteins, a weighted bipartite matching algorithm is used to match pairs of surface patches. The surface patches are encoded with the 3D Zernike descriptors. Unlike the existing methods which compare global characteristics of the protein fold or the global pocket shape, the local surface patch method can find functional similarity between non-homologous proteins and binding pockets for flexible ligand molecules. The proposed method improves prediction results over global pocket shape-based method which was previously developed by our group. PMID:21614188

SubCellProt: predicting protein subcellular localization using machine learning approaches.

PubMed

Garg, Prabha; Sharma, Virag; Chaudhari, Pradeep; Roy, Nilanjan

2009-01-01

High-throughput genome sequencing projects continue to churn out enormous amounts of raw sequence data. However, most of this raw sequence data is unannotated and, hence, not very useful. Among the various approaches to decipher the function of a protein, one is to determine its localization. Experimental approaches for proteome annotation including determination of a protein's subcellular localizations are very costly and labor intensive. Besides the available experimental methods, in silico methods present alternative approaches to accomplish this task. Here, we present two machine learning approaches for prediction of the subcellular localization of a protein from the primary sequence information. Two machine learning algorithms, k Nearest Neighbor (k-NN) and Probabilistic Neural Network (PNN) were used to classify an unknown protein into one of the 11 subcellular localizations. The final prediction is made on the basis of a consensus of the predictions made by two algorithms and a probability is assigned to it. The results indicate that the primary sequence derived features like amino acid composition, sequence order and physicochemical properties can be used to assign subcellular localization with a fair degree of accuracy. Moreover, with the enhanced accuracy of our approach and the definition of a prediction domain, this method can be used for proteome annotation in a high throughput manner. SubCellProt is available at www.databases.niper.ac.in/SubCellProt.

Prognostic Value of Plasma Epstein-Barr Virus DNA for Local and Regionally Advanced Nasopharyngeal Carcinoma Treated With Cisplatin-Based Concurrent Chemoradiotherapy in Intensity-Modulated Radiotherapy Era.

PubMed

Chen, Wen-Hui; Tang, Lin-Quan; Guo, Shan-Shan; Chen, Qiu-Yan; Zhang, Lu; Liu, Li-Ting; Qian, Chao-Nan; Guo, Xiang; Xie, Dan; Zeng, Mu-Sheng; Mai, Hai-Qiang

2016-02-01

This study aimed to evaluate the prognostic value of plasma Epstein-Barr Virus DNA (EBV DNA) for local and regionally advanced nasopharyngeal carcinoma (NPC) patients treated with concurrent chemoradiotherapy in intensity-modulated radiotherapy (IMRT) era.In this observational study, 404 nonmetastatic local and regionally advanced NPC patients treated with IMRT and cisplatin-based concurrent chemotherapy were recruited. Blood samples were collected before treatment for examination of plasma EBV DNA levels. We evaluated the association of pretreatment plasma EBV DNA levels with progression-free survival rate (PFS), distant metastasis-free survival rate (DMFS), and overall survival rate (OS).Compared to patients with an EBV DNA level < 4000  copies/mL, patients with an EBV DNA ≥ 4000  copies/mL had a lower rate of 3-year PFS (76%, 95% CI [68-84]) versus (93%, 95% CI [90-96], P < 0.001), DMFS (83%, 95% CI [76-89]) versus (97%, 95% CI [94-99], P < 0.001), and OS (85%, 95% CI [78-92]) versus (98%, 95% CI [95-100], P < 0.001). Multivariate analysis showed that pretreatment EBV DNA levels (HR = 3.324, 95% CI, 1.80-6.138, P < 0.001) and clinical stage (HR = 1.878, 95% CI, 1.036-3.404, P = 0.038) were the only independent factor associated with PFS, pretreatment EBV DNA level was the only significant factor to predict DMFS (HR = 6.292, 95% CI, 2.647-14.956, P < 0.001), and pretreatment EBV DNA levels (HR = 3.753, 95% CI, 1.701-8.284, P < 0.001) and clinical stage (HR = 2.577, 95% CI, 1.252-5.050, P = 0.010) were significantly associated with OS. In subgroup analysis, higher plasma EBV DNA levels still predicted a worse PFS, DMFS, and OS for the patients stage III or stage IVa-b, compared with those with low EBV DNA levels.Elevated plasma EBV DNA was still effective prognostic biomarker for local and regionally advanced NPC patients treated with IMRT and cisplatin-based concurrent chemotherapy. Future ramdomized clinical trials are needed to further evaluate whether plasma EBV DNA levels could be applied to guide concurrent chemotherapy regimen for local and regionally advanced NPC patients.

Quantifying drivers of wild pig movement across multiple spatial and temporal scales.

PubMed

Kay, Shannon L; Fischer, Justin W; Monaghan, Andrew J; Beasley, James C; Boughton, Raoul; Campbell, Tyler A; Cooper, Susan M; Ditchkoff, Stephen S; Hartley, Steve B; Kilgo, John C; Wisely, Samantha M; Wyckoff, A Christy; VerCauteren, Kurt C; Pepin, Kim M

2017-01-01

The movement behavior of an animal is determined by extrinsic and intrinsic factors that operate at multiple spatio-temporal scales, yet much of our knowledge of animal movement comes from studies that examine only one or two scales concurrently. Understanding the drivers of animal movement across multiple scales is crucial for understanding the fundamentals of movement ecology, predicting changes in distribution, describing disease dynamics, and identifying efficient methods of wildlife conservation and management. We obtained over 400,000 GPS locations of wild pigs from 13 different studies spanning six states in southern U.S.A., and quantified movement rates and home range size within a single analytical framework. We used a generalized additive mixed model framework to quantify the effects of five broad predictor categories on movement: individual-level attributes, geographic factors, landscape attributes, meteorological conditions, and temporal variables. We examined effects of predictors across three temporal scales: daily, monthly, and using all data during the study period. We considered both local environmental factors such as daily weather data and distance to various resources on the landscape, as well as factors acting at a broader spatial scale such as ecoregion and season. We found meteorological variables (temperature and pressure), landscape features (distance to water sources), a broad-scale geographic factor (ecoregion), and individual-level characteristics (sex-age class), drove wild pig movement across all scales, but both the magnitude and shape of covariate relationships to movement differed across temporal scales. The analytical framework we present can be used to assess movement patterns arising from multiple data sources for a range of species while accounting for spatio-temporal correlations. Our analyses show the magnitude by which reaction norms can change based on the temporal scale of response data, illustrating the importance of appropriately defining temporal scales of both the movement response and covariates depending on the intended implications of research (e.g., predicting effects of movement due to climate change versus planning local-scale management). We argue that consideration of multiple spatial scales within the same framework (rather than comparing across separate studies post-hoc ) gives a more accurate quantification of cross-scale spatial effects by appropriately accounting for error correlation.

Similarity-based Regularized Latent Feature Model for Link Prediction in Bipartite Networks.

PubMed

Wang, Wenjun; Chen, Xue; Jiao, Pengfei; Jin, Di

2017-12-05

Link prediction is an attractive research topic in the field of data mining and has significant applications in improving performance of recommendation system and exploring evolving mechanisms of the complex networks. A variety of complex systems in real world should be abstractly represented as bipartite networks, in which there are two types of nodes and no links connect nodes of the same type. In this paper, we propose a framework for link prediction in bipartite networks by combining the similarity based structure and the latent feature model from a new perspective. The framework is called Similarity Regularized Nonnegative Matrix Factorization (SRNMF), which explicitly takes the local characteristics into consideration and encodes the geometrical information of the networks by constructing a similarity based matrix. We also develop an iterative scheme to solve the objective function based on gradient descent. Extensive experiments on a variety of real world bipartite networks show that the proposed framework of link prediction has a more competitive, preferable and stable performance in comparison with the state-of-art methods.

Factors predicting change in hospital safety climate and capability in a multi-site patient safety collaborative: a longitudinal survey study.

PubMed

Benn, Jonathan; Burnett, Susan; Parand, Anam; Pinto, Anna; Vincent, Charles

2012-07-01

The study had two specific objectives: (1) To analyse change in a survey measure of organisational patient safety climate and capability (SCC) resulting from participation in the UK Safer Patients Initiative and (2) To investigate the role of a range of programme and contextual factors in predicting change in SCC scores. Single group longitudinal design with repeated measurement at 12-month follow-up. Multiple service areas within NHS hospital sites across England, Wales, Scotland and Northern Ireland. Stratified sample of 284 respondents representing programme teams at 19 hospital sites. A complex intervention comprising a multi-component quality improvement collaborative focused upon patient safety and designed to impact upon hospital leadership, communication, organisation and safety climate. A survey including a 31-item SCC scale was administered at two time-points. Modest but significant positive movement in SCC score was observed between the study time-points. Individual programme responsibility, availability of early adopters, multi-professional collaboration and extent of process measurement were significant predictors of change in SCC. Hospital type and size, along with a range of programme preconditions, were not found to be significant. A range of social, cultural and organisational factors may be sensitive to this type of intervention but the measurable effect is small. Supporting critical local programme implementation factors may be an effective strategy in achieving development in organisational patient SCC, regardless of contextual factors and organisational preconditions.

Local adaptation in migrated interior Douglas-fir seedlings is mediated by ectomycorrhizas and other soil factors.

PubMed

Pickles, Brian J; Twieg, Brendan D; O'Neill, Gregory A; Mohn, William W; Simard, Suzanne W

2015-08-01

Separating edaphic impacts on tree distributions from those of climate and geography is notoriously difficult. Aboveground and belowground factors play important roles, and determining their relative contribution to tree success will greatly assist in refining predictive models and forestry strategies in a changing climate. In a common glasshouse, seedlings of interior Douglas-fir (Pseudotsuga menziesii var. glauca) from multiple populations were grown in multiple forest soils. Fungicide was applied to half of the seedlings to separate soil fungal and nonfungal impacts on seedling performance. Soils of varying geographic and climatic distance from seed origin were compared, using a transfer function approach. Seedling height and biomass were optimized following seed transfer into drier soils, whereas survival was optimized when elevation transfer was minimised. Fungicide application reduced ectomycorrhizal root colonization by c. 50%, with treated seedlings exhibiting greater survival but reduced biomass. Local adaptation of Douglas-fir populations to soils was mediated by soil fungi to some extent in 56% of soil origin by response variable combinations. Mediation by edaphic factors in general occurred in 81% of combinations. Soil biota, hitherto unaccounted for in climate models, interacts with biogeography to influence plant ranges in a changing climate. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Using fire-weather forecasts and local weather observations in predicting burning index for individual fire-danger stations.

Treesearch

Owen P. Cramer

1958-01-01

Any agency engaged in forest-fire control needs accurate weather forecasts and systematic procedures for making the best use of predicted and reported weather information. This study explores the practicability of using several tabular and graphical aids for converting area forecasts and local observations of relative humidity and wind speed into predicted values for...

Factors That Predict Financial Sustainability of Community Coalitions: Five Years of Findings from the PROSPER Partnership Project

PubMed Central

Greenberg, Mark T.; Feinberg, Mark E.; Johnson, Lesley E.; Perkins, Daniel F.; Welsh, Janet A.; Spoth, Richard L.

2014-01-01

This study is a longitudinal investigation of the PROSPER partnership model designed to evaluate the level of sustainability funding by community prevention teams, including which factors impact teams’ generation of sustainable funding. Community teams were responsible for choosing, implementing with quality, and sustaining evidence-based programs (EBPs) intended to reduce substance misuse and promote positive youth and family development. Fourteen US rural communities and small towns were studied. Data were collected from PROSPER community team members (N=164) and Prevention Coordinators (N=10), over a 5-year period. Global and specific aspects of team functioning were assessed over 6 waves. Outcome measures were the total funds (cash and in-kind) raised to implement prevention programs. All 14 community teams were sustained for the first five years. However, there was substantial variability in the amount of funds raised and these differences were predicted by earlier and concurrent team functioning and by team sustainability planning. Given the sufficient infrastructure and ongoing technical assistance provided by the PROSPER partnership model, local sustainability of EBPs is achievable. PMID:24706195

Selection criteria for preoperative endoscopic retrograde cholangiopancreatography before laparoscopic cholecystectomy and endoscopic treatment of bile duct stones: Results of a retrospective, single center study between 1996-2002

PubMed Central

Lakatos, Laszlo; Mester, Gabor; Reti, Gyorgy; Nagy, Attila; Lakatos, Peter Laszlo

2004-01-01

AIM: The optimal treatment for bile duct stones (in terms of cost, complications and accuracy) is unclear. The aim of our study was to determine the predictive factors for preoperative endoscopic retrograde cholangiopancreatography (ERCP). METHODS: Patients undergoing preoperative ERCP ( ≤ 90 d before laparoscopic cholecystectomy) were evaluated in this retrospective study from the 1st of January 1996 to the 31st of December 2002. The indications for ERCP were elevated serum bilirubin, elevated liver function tests (LFT), dilated bile duct ( ≥ 8 mm) and/or stone at US examination, coexisting acute pancreatitis and/or acute pancreatitis or jaundice in patient’s history. Suspected prognostic factors and the combination of factors were compared to the result of ERCP. RESULTS: Two hundred and six preoperative ERCPs were performed during the observed period. The rate of successful cannulation for ERC was (97.1%). Bile duct stones were detected in 81 patients (39.3%), and successfully removed in 79 (97.5%). The number of prognostic factors correlated with the presence of bile duct stones. The positive predictive value for one prognostic factor was 1.2%, for two 43%, for three 72.5%, for four or more 91.4%. CONCLUSION: Based on our data preoperative ERCP is highly recommended in patients with three or more positive factors (high risk patients). In contrast, ERCP is not indicated in patients with zero or one factor (low risk patients). Preoperative ERCP should be offered to patients with two positive factors (moderate risk patients), however the practice should also be based on the local conditions (e.g. skill of the endoscopist, other diagnostic tools). PMID:15526372

Prevalence and predictive factors for the detection of carcinoma in cavity margin performed at the time of breast lumpectomy.

PubMed

Tengher-Barna, Iulia; Hequet, Delphine; Reboul-Marty, Jeanne; Frassati-Biaggi, Annonciade; Seince, Nathalie; Rodrigues-Faure, Anabela; Uzan, Michèle; Ziol, Marianne

2009-02-01

Margin resection status is a major risk factor for the development of local recurrence in breast conservation therapy for carcinoma. Tumor bed excision sent as separate orientated cavity margins represents a tool to verify the completeness of the carcinoma resection. We aimed to (1) determine the prevalence of positive cavity margin and its influence on subsequent surgical treatment and (2) identify potential predictive factors for positive cavity margins. From 2003 to 2006, 107 (57 years; 30-88) consecutive patients who underwent a lumpectomy for carcinoma with four orientated cavity margins for carcinoma were selected. Preoperative clinical, radiological and histological data, perioperative macroscopic characteristics and definitive histological analysis results were recorded. Lumpectomy or cavity margins were considered as positive when the distance from carcinoma to the margin was less than or equal to 3 mm. Histological examination of cavity margins showed carcinoma in 38 patients (35%), therefore modifying subsequent surgical therapy in 33 cases. Examination of the cavity margins led (1) to avoiding surgical re-excision in 20 cases (lumpectomy margins were positive and the cavity margins negative), (2) to performing a mastectomy or a re-excision in 13 cases (carcinoma was detected in the cavity margins although the lumpectomy margins were negative or tumor size was superior to 3 cm). Between preoperative and perioperative parameters, US scan and macroscopic size of the tumor were predictive factors for positive cavity margins whereas characteristics of the carcinoma determined on biopsy samples and macroscopic status of the lumpectomy margins were not. Our study confirms that the systematic practice of cavity margin resection avoids surgical re-excision and reduces the likelihood of underestimating the extent of the tumor.

Treatment Default amongst Patients with Tuberculosis in Urban Morocco: Predicting and Explaining Default and Post-Default Sputum Smear and Drug Susceptibility Results

PubMed Central

Ghali, Iraqi; Kizub, Darya; Billioux, Alexander C.; Bennani, Kenza; Bourkadi, Jamal Eddine; Benmamoun, Abderrahmane; Lahlou, Ouafae; Aouad, Rajae El; Dooley, Kelly E.

2014-01-01

Setting Public tuberculosis (TB) clinics in urban Morocco. Objective Explore risk factors for TB treatment default and develop a prediction tool. Assess consequences of default, specifically risk for transmission or development of drug resistance. Design Case-control study comparing patients who defaulted from TB treatment and patients who completed it using quantitative methods and open-ended questions. Results were interpreted in light of health professionals’ perspectives from a parallel study. A predictive model and simple tool to identify patients at high risk of default were developed. Sputum from cases with pulmonary TB was collected for smear and drug susceptibility testing. Results 91 cases and 186 controls enrolled. Independent risk factors for default included current smoking, retreatment, work interference with adherence, daily directly observed therapy, side effects, quick symptom resolution, and not knowing one’s treatment duration. Age >50 years, never smoking, and having friends who knew one’s diagnosis were protective. A simple scoring tool incorporating these factors was 82.4% sensitive and 87.6% specific for predicting default in this population. Clinicians and patients described additional contributors to default and suggested locally-relevant intervention targets. Among 89 cases with pulmonary TB, 71% had sputum that was smear positive for TB. Drug resistance was rare. Conclusion The causes of default from TB treatment were explored through synthesis of qualitative and quantitative data from patients and health professionals. A scoring tool with high sensitivity and specificity to predict default was developed. Prospective evaluation of this tool coupled with targeted interventions based on our findings is warranted. Of note, the risk of TB transmission from patients who default treatment to others is likely to be high. The commonly-feared risk of drug resistance, though, may be low; a larger study is required to confirm these findings. PMID:24699682

Predicting Ground Illuminance

NASA Astrophysics Data System (ADS)

Lesniak, Michael V.; Tregoning, Brett D.; Hitchens, Alexandra E.

2015-01-01

Our Sun outputs 3.85 x 1026 W of radiation, of which roughly 37% is in the visible band. It is directly responsible for nearly all natural illuminance experienced on Earth's surface, either in the form of direct/refracted sunlight or in reflected light bouncing off the surfaces and/or atmospheres of our Moon and the visible planets. Ground illuminance, defined as the amount of visible light intercepting a unit area of surface (from all incident angles), varies over 7 orders of magnitude from day to night. It is highly dependent on well-modeled factors such as the relative positions of the Sun, Earth, and Moon. It is also dependent on less predictable factors such as local atmospheric conditions and weather.Several models have been proposed to predict ground illuminance, including Brown (1952) and Shapiro (1982, 1987). The Brown model is a set of empirical data collected from observation points around the world that has been reduced to a smooth fit of illuminance against a single variable, solar altitude. It provides limited applicability to the Moon and for cloudy conditions via multiplicative reduction factors. The Shapiro model is a theoretical model that treats the atmosphere as a three layer system of light reflectance and transmittance. It has different sets of reflectance and transmittance coefficients for various cloud types.In this paper we compare the models' predictions to ground illuminance data from an observing run at the White Sands missile range (data was obtained from the United Kingdom's Meteorology Office). Continuous illuminance readings were recorded under various cloud conditions, during both daytime and nighttime hours. We find that under clear skies, the Shapiro model tends to better fit the observations during daytime hours with typical discrepancies under 10%. Under cloudy skies, both models tend to poorly predict ground illuminance. However, the Shapiro model, with typical average daytime discrepancies of 25% or less in many cases, performed somewhat better than the Brown model during daytime hours. During nighttime hours under cloudy skies, both models produced erratic results.

Interface-induced localization in AlSb/InAs heterostructures

NASA Astrophysics Data System (ADS)

Shaw, M. J.; Briddon, P. R.; Jaros, M.

1995-12-01

The existence of localized states at perfect InSb-like interfaces in AlSb/InAs superlattices is predicted from ab initio pseudopotential calculations. Localized states are predicted in both the valence and conduction bands, the former being identifiable with the interface states proposed by Kroemer, Nguyen, and Brar [J. Vac. Sci. Technol. 10, 1769 (1990)]. The existence of these interface localized states is invoked to explain the reported experimental dependence of the band gap upon interface types in such superlattices.

Shear buckling analysis of a hat-stiffened panel

NASA Technical Reports Server (NTRS)

Ko, William L.; Jackson, Raymond H.

1994-01-01

A buckling analysis was performed on a hat-stiffened panel subjected to shear loading. Both local buckling and global buckling were analyzed. The global shear buckling load was found to be several times higher than the local shear buckling load. The classical shear buckling theory for a flat plate was found to be useful in predicting the local shear buckling load of the hat-stiffened panel, and the predicted local shear buckling loads thus obtained compare favorably with the results of finite element analysis.

Prospective Study of the Evolution of Blood Lymphoid Immune Parameters during Dacarbazine Chemotherapy in Metastatic and Locally Advanced Melanoma Patients

PubMed Central

Vabres, Pierre; Dalac, Sophie; Jeudy, Geraldine; Bel, Blandine; Apetoh, Lionel; Ghiringhelli, François

2014-01-01

Background The importance of immune responses in the control of melanoma growth is well known. However, the implication of these antitumor immune responses in the efficacy of dacarbazine, a cytotoxic drug classically used in the treatment of melanoma, remains poorly understood in humans. Methods In this prospective observational study, we performed an immunomonitoring of eleven metastatic or locally advanced patients treated with dacarbazine as a first line of treatment. We assessed by flow cytometry lymphoid populations and their activation state; we also isolated NK cells to perform in vitro cytotoxicity tests. Results We found that chemotherapy induces lymphopenia and that a significantly higher numbers of naïve CD4+ T cells and lower proportion of Treg before chemotherapy are associated with disease control after dacarbazine treatment. Interestingly, NK cell cytotoxicity against dacarbazine-pretreated melanoma cells is only observed in NK cells from patients who achieved disease control. Conclusion Together, our data pinpoint that some immune factors could help to predict the response of melanoma patients to dacarbazine. Future larger scale studies are warranted to test their validity as prediction markers. PMID:25170840