Correlation between experimental human and murine skin sensitization induction thresholds.

PubMed

Api, Anne Marie; Basketter, David; Lalko, Jon

2015-01-01

Quantitative risk assessment for skin sensitization is directed towards the determination of levels of exposure to known sensitizing substances that will avoid the induction of contact allergy in humans. A key component of this work is the predictive identification of relative skin sensitizing potency, achieved normally by the measurement of the threshold (the "EC3" value) in the local lymph node assay (LLNA). In an extended series of studies, the accuracy of this murine induction threshold as the predictor of the absence of a sensitizing effect has been verified by conduct of a human repeated insult patch test (HRIPT). Murine and human thresholds for a diverse set of 57 fragrance chemicals spanning approximately four orders of magnitude variation in potency have been compared. The results confirm that there is a useful correlation, with the LLNA EC3 value helping particularly to identify stronger sensitizers. Good correlation (with half an order of magnitude) was seen with three-quarters of the dataset. The analysis also helps to identify potential outlier types of (fragrance) chemistry, exemplified by hexyl and benzyl salicylates (an over-prediction) and trans-2-hexenal (an under-prediction).

Quantitative power Doppler ultrasound measures of peripheral joint synovitis in poor prognosis early rheumatoid arthritis predict radiographic progression.

PubMed

Sreerangaiah, Dee; Grayer, Michael; Fisher, Benjamin A; Ho, Meilien; Abraham, Sonya; Taylor, Peter C

2016-01-01

To assess the value of quantitative vascular imaging by power Doppler US (PDUS) as a tool that can be used to stratify patient risk of joint damage in early seropositive RA while still biologic naive but on synthetic DMARD treatment. Eighty-five patients with seropositive RA of <3 years duration had clinical, laboratory and imaging assessments at 0 and 12 months. Imaging assessments consisted of radiographs of the hands and feet, two-dimensional (2D) high-frequency and PDUS imaging of 10 MCP joints that were scored for erosions and vascularity and three-dimensional (3D) PDUS of MCP joints and wrists that were scored for vascularity. Severe deterioration on radiographs and ultrasonography was seen in 45 and 28% of patients, respectively. The 3D power Doppler volume and 2D vascularity scores were the most useful US predictors of deterioration. These variables were modelled in two equations that estimate structural damage over 12 months. The equations had a sensitivity of 63.2% and specificity of 80.9% for predicting radiographic structural damage and a sensitivity of 54.2% and specificity of 96.7% for predicting structural damage on ultrasonography. In seropositive early RA, quantitative vascular imaging by PDUS has clinical utility in predicting which patients will derive benefit from early use of biologic therapy. © The Author 2015. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Fear-avoidance beliefs and temporal summation of evoked thermal pain influence self-report of disability in patients with chronic low back pain.

PubMed

George, Steven Z; Wittmer, Virgil T; Fillingim, Roger B; Robinson, Michael E

2006-03-01

Quantitative sensory testing has demonstrated a promising link between experimentally determined pain sensitivity and clinical pain. However, previous studies of quantitative sensory testing have not routinely considered the important influence of psychological factors on clinical pain. This study investigated whether measures of thermal pain sensitivity (temporal summation, first pulse response, and tolerance) contributed to clinical pain reports for patients with chronic low back pain, after controlling for depression or fear-avoidance beliefs about work. Consecutive patients (n=27) with chronic low back pain were recruited from an interdisciplinary pain rehabilitation program in Jacksonville, FL. Patients completed validated self-report questionnaires for depression, fear-avoidance beliefs, clinical pain intensity, and clinical pain related disability. Patients also underwent quantitative sensory testing from previously described protocols to determine thermal pain sensitivity (temporal summation, first pulse response, and tolerance). Hierarchical regression models investigated the contribution of depression and thermal pain sensitivity to clinical pain intensity, and fear-avoidance beliefs and thermal pain sensitivity to clinical pain related disability. None of the measures of thermal pain sensitivity contributed to clinical pain intensity after controlling for depression. Temporal summation of evoked thermal pain significantly contributed to clinical pain disability after controlling for fear-avoidance beliefs about work. Measures of thermal pain sensitivity did not contribute to pain intensity, after controlling for depression. Fear-avoidance beliefs about work and temporal summation of evoked thermal pain significantly influenced pain related disability. These factors should be considered as potential outcome predictors for patients with work-related low back pain. This study supported the neuromatrix theory of pain for patients with CLBP, as cognitive-evaluative factor contributed to pain perception, and cognitive-evaluative and sensory-discriminative factors uniquely contributed to an action program in response to chronic pain. Future research will determine if a predictive model consisting of fear-avoidance beliefs and temporal summation of evoked thermal pain has predictive validity for determining clinical outcome in rehabilitation or vocational settings.

Usefulness of gram staining of blood collected from total parenteral nutrition catheter for rapid diagnosis of catheter-related sepsis.

PubMed Central

Moonens, F; el Alami, S; Van Gossum, A; Struelens, M J; Serruys, E

1994-01-01

The accuracy of Gram staining of blood drawn from catheters used to administer total parenteral nutrition was compared with paired quantitative blood cultures for the diagnosis of catheter-related sepsis. Gram staining was positive in 11 of 18 episodes of catheter-related sepsis documented by quantitative culture (sensitivity, 61%) but in none of the 5 episodes of fever unrelated to catheter infection. Thus, this procedure enabled the rapid presumptive diagnosis and guidance of antimicrobial therapy for total parenteral nutrition catheter sepsis, with a positive predictive value of 100% and a negative predictive value of 42%. PMID:7521359

A score model for predicting post-liver transplantation survival in HBV cirrhosis-related hepatocellular carcinoma recipients: a single center 5-year experience.

PubMed

Wang, Li-Ying; Zheng, Shu-Sen; Xu, Xiao; Wang, Wei-Lin; Wu, Jian; Zhang, Min; Shen, Yan; Yan, Sheng; Xie, Hai-Yang; Chen, Xin-Hua; Jiang, Tian-An; Chen, Fen

2015-02-01

The prognostic prediction of liver transplantation (LT) guides the donor organ allocation. However, there is currently no satisfactory model to predict the recipients' outcome, especially for the patients with HBV cirrhosis-related hepatocellular carcinoma (HCC). The present study was to develop a quantitative assessment model for predicting the post-LT survival in HBV-related HCC patients. Two hundred and thirty-eight LT recipients at the Liver Transplant Center, First Affiliated Hospital, Zhejiang University School of Medicine between 2008 and 2013 were included in this study. Their post-LT prognosis was recorded and multiple risk factors were analyzed using univariate and multivariate analyses in Cox regression. The score model was as follows: 0.114X(Child-Pugh score)-0.002X(positive HBV DNA detection time)+0.647X(number of tumor nodules)+0.055X(max diameter of tumor nodules)+0.231XlnAFP+0.437X(tumor differentiation grade). The receiver operating characteristic curve analysis showed that the area under the curve of the scoring model for predicting the post-LT survival was 0.887. The cut-off value was 1.27, which was associated with a sensitivity of 72.5% and a specificity of 90.7%, respectively. The quantitative score model for predicting post-LT survival proved to be sensitive and specific.

MethylMeter(®): bisulfite-free quantitative and sensitive DNA methylation profiling and mutation detection in FFPE samples.

PubMed

McCarthy, David; Pulverer, Walter; Weinhaeusel, Andreas; Diago, Oscar R; Hogan, Daniel J; Ostertag, Derek; Hanna, Michelle M

2016-06-01

Development of a sensitive method for DNA methylation profiling and associated mutation detection in clinical samples. Formalin-fixed and paraffin-embedded tumors received by clinical laboratories often contain insufficient DNA for analysis with bisulfite or methylation sensitive restriction enzymes-based methods. To increase sensitivity, methyl-CpG DNA capture and Coupled Abscription PCR Signaling detection were combined in a new assay, MethylMeter(®). Gliomas were analyzed for MGMT methylation, glioma CpG island methylator phenotype and IDH1 R132H. MethylMeter had 100% assay success rate measuring all five biomarkers in formalin-fixed and paraffin-embedded tissue. MGMT methylation results were supported by survival and mRNA expression data. MethylMeter is a sensitive and quantitative method for multitarget DNA methylation profiling and associated mutation detection. The MethylMeter-based GliomaSTRAT assay measures methylation of four targets and one mutation to simultaneously grade gliomas and predict their response to temozolomide. This information is clinically valuable in management of gliomas.

Post-anoxic quantitative MRI changes may predict emergence from coma and functional outcomes at discharge.

PubMed

Reynolds, Alexandra S; Guo, Xiaotao; Matthews, Elizabeth; Brodie, Daniel; Rabbani, Leroy E; Roh, David J; Park, Soojin; Claassen, Jan; Elkind, Mitchell S V; Zhao, Binsheng; Agarwal, Sachin

2017-08-01

Traditional predictors of neurological prognosis after cardiac arrest are unreliable after targeted temperature management. Absence of pupillary reflexes remains a reliable predictor of poor outcome. Diffusion-weighted imaging has emerged as a potential predictor of recovery, and here we compare imaging characteristics to pupillary exam. We identified 69 patients who had MRIs within seven days of arrest and used a semi-automated algorithm to perform quantitative volumetric analysis of apparent diffusion coefficient (ADC) sequences at various thresholds. Area under receiver operating characteristic curves (ROC-AUC) were estimated to compare predictive values of quantitative MRI with pupillary exam at days 3, 5 and 7 post-arrest, for persistence of coma and functional outcomes at discharge. Cerebral Performance Category scores of 3-4 were considered poor outcome. Excluding patients where life support was withdrawn, ≥2.8% diffusion restriction of the entire brain at an ADC of ≤650×10 -6 m 2 /s was 100% specific and 68% sensitive for failure to wake up from coma before discharge. The ROC-AUC of ADC changes at ≤450×10 -6 mm 2 /s and ≤650×10 -6 mm 2 /s were significantly superior in predicting failure to wake up from coma compared to bilateral absence of pupillary reflexes. Among survivors, >0.01% of diffusion restriction of the entire brain at an ADC ≤450×10 -6 m 2 /s was 100% specific and 46% sensitive for poor functional outcome at discharge. The ROC curve predicting poor functional outcome at ADC ≤450×10 -6 mm 2 /s had an AUC of 0.737 (0.574-0.899, p=0.04). Post-anoxic diffusion changes using quantitative brain MRI may aid in predicting persistent coma and poor functional outcomes at hospital discharge. Copyright © 2017 Elsevier B.V. All rights reserved.

[Comparison of two quantitative methods of endobronchial ultrasound real-time elastography for evaluating intrathoracic lymph nodes].

PubMed

Mao, X W; Yang, J Y; Zheng, X X; Wang, L; Zhu, L; Li, Y; Xiong, H K; Sun, J Y

2017-06-12

Objective: To compare the clinical value of two quantitative methods in analyzing endobronchial ultrasound real-time elastography (EBUS-RTE) images for evaluating intrathoracic lymph nodes. Methods: From January 2014 to April 2014, EBUS-RTE examination was performed in patients who received EBUS-TBNA examination in Shanghai Chest Hospital. Each intrathoracic lymph node had a selected EBUS-RTE image. Stiff area ratio and mean hue value of region of interest (ROI) in each image were calculated respectively. The final diagnosis of lymph node was based on the pathologic/microbiologic results of EBUS-TBNA, pathologic/microbiologic results of other examinations and clinical following-up. The sensitivity, specificity, positive predictive value, negative predictive value and accuracy were evaluated for distinguishing malignant and benign lesions. Results: Fifty-six patients and 68 lymph nodes were enrolled in this study, of which 35 lymph nodes were malignant and 33 lymph nodes were benign. The stiff area ratio and mean hue value of benign and malignant lesions were 0.32±0.29, 0.62±0.20 and 109.99±28.13, 141.62±17.52, respectively, and statistical differences were found in both of those two methods ( t =-5.14, P <0.01; t =-5.53, P <0.01). The area under curves was 0.813, 0.814 in stiff area ratio and mean hue value, respectively. The optimal diagnostic cut-off value of stiff area ratio was 0.48, and the sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 82.86%, 81.82%, 82.86%, 81.82% and 82.35%, respectively. The optimal diagnostic cut-off value of mean hue value was 126.28, and the sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 85.71%, 75.76%, 78.95%, 83.33% and 80.88%, respectively. Conclusion: Both the stiff area ratio and mean hue value methods can be used for analyzing EBUS-RTE images quantitatively, having the value of differentiating benign and malignant intrathoracic lymph nodes, and the stiff area ratio is better than the mean hue value between the two methods.

TS mRNA levels can predict pemetrexed and raltitrexed sensitivity in colorectal cancer.

PubMed

Zhang, Qun; Shen, Jie; Wang, Hao; Hu, Jing; Yu, Lixia; Xie, Li; Wei, Jia; Liu, Baorui; Guan, Wenxian; Qian, Xiaoping

2014-02-01

The purpose of the study is to analyze the relationship between tumor thymidylate synthase (TS) mRNA expression levels and raltitrexed/pemetrexed/5-FU sensitivity. We collected freshly removed colorectal tumor specimens from 50 patients. Chemosensitivities to anticancer drugs were evaluated by histoculture drug response assay. We adopted quantitative reverse transcription polymerase chain reaction for TS mRNA detection and immunohistochemical staining for assessing TS expression in tumor tissues. There is a significant relationship between TS mRNA expression levels and in vitro chemosensitivity of freshly removed colorectal tumor specimens to pemetrexed (P < 0.001)/raltitrexed (P = 0.004)/5-FU (P = 0.007). TS mRNA expression levels can predict pemetrexed and raltitrexed sensitivity in colorectal cancer.

Quantitation of cytokine mRNA expression as an endpoint for prediction and diagnosis of xenobiotic-induced hypersensitivity reactions.

PubMed

Gaspard, I; Kerdine, S; Pallardy, M; Lebrec, H

1999-09-01

Xenobiotic-induced hypersensitivity reactions are immune-mediated effects that involve specific antibodies and/or effector and regulatory T lymphocytes. Cytokines are key mediators of such responses and must be considered as possible endpoints for predicting sensitizing potency of drugs and chemicals, as well as for helping diagnosis of allergy. Detecting cytokine production at the protein level has been shown to not be always sensitive enough. This paper describes three examples of the utilization of semiquantitative or competitive reverse transcription polymerase chain reaction analysis of interleukin-4, interferon gamma, and interleukin-1beta mRNAs as endpoints for assessing T-cell or dendritic cell responses to sensitizing drugs (beta-lactam antibiotics) or chemicals (dinitrochlorobenzene). Copyright 1999 Academic Press.

Technical and financial evaluation of assays for progesterone in canine practice in the UK.

PubMed

Moxon, R; Copley, D; England, G C W

2010-10-02

The concentration of progesterone was measured in 60 plasma samples from bitches at various stages of the oestrous cycle, using commercially available quantitative and semi-quantitative ELISA test kits, as well as by two commercial laboratories undertaking radioimmunoassay (RIA). The RIA, which was assumed to be the 'gold standard' in terms of reliability and accuracy, was the most expensive method when analysing more than one sample per week, and had the longest delay in obtaining results, but had minimal requirements for practice staff time. When compared with the RIA, the quantitative ELISA had a strong positive correlation (r=0.97, P<0.05) and a sensitivity and specificity of 70.6 per cent and 100.0 per cent, respectively, and positive and negative predictive values of 100.0 per cent and 71.0 per cent, respectively, with an overall accuracy of 90.0 per cent. This method was the least expensive when analysing five or more samples per week, but had longer turnaround times than that of the semi-quantitative ELISA and required more staff time. When compared with the RIA, the semi-quantitative ELISA had a sensitivity and specificity of 100.0 per cent and 95.5 per cent, respectively, and positive and negative predictive values of 73.9 per cent and 77.8 per cent, respectively, with an overall accuracy of 89.2 per cent. This method was more expensive than the quantitative ELISA when analysing five or more samples per week, but had the shortest turnaround time and low requirements in terms of staff time.

A mechano-acoustic model of the effect of superior canal dehiscence on hearing in chinchilla

PubMed Central

Songer, Jocelyn E.; Rosowski, John J.

2008-01-01

Superior canal dehiscence (SCD) is a pathological condition of the ear that can cause a conductive hearing loss. The effect of SCD (a hole in the bony wall of the superior semicircular canal) on chinchilla middle- and inner-ear mechanics is analyzed with a circuit model of the dehiscence. The model is used to predict the effect of dehiscence on auditory sensitivity and mechanics. These predictions are compared to previously published measurements of dehiscence related changes in chinchilla cochlear potential, middle-ear input admittance and stapes velocity. The comparisons show that the model predictions are both qualitatively and quantitatively similar to the physiological results for frequencies where physiologic data are available. The similarity supports the third-window hypothesis of the effect of superior canal dehiscence on auditory sensitivity and mechanics and provides the groundwork for the development of a model that predicts the effect of superior canal dehiscence syndrome on auditory sensitivity and mechanics in humans. PMID:17672643

A Crowdsourcing Approach to Developing and Assessing Prediction Algorithms for AML Prognosis

PubMed Central

Noren, David P.; Long, Byron L.; Norel, Raquel; Rrhissorrakrai, Kahn; Hess, Kenneth; Hu, Chenyue Wendy; Bisberg, Alex J.; Schultz, Andre; Engquist, Erik; Liu, Li; Lin, Xihui; Chen, Gregory M.; Xie, Honglei; Hunter, Geoffrey A. M.; Norman, Thea; Friend, Stephen H.; Stolovitzky, Gustavo; Kornblau, Steven; Qutub, Amina A.

2016-01-01

Acute Myeloid Leukemia (AML) is a fatal hematological cancer. The genetic abnormalities underlying AML are extremely heterogeneous among patients, making prognosis and treatment selection very difficult. While clinical proteomics data has the potential to improve prognosis accuracy, thus far, the quantitative means to do so have yet to be developed. Here we report the results and insights gained from the DREAM 9 Acute Myeloid Prediction Outcome Prediction Challenge (AML-OPC), a crowdsourcing effort designed to promote the development of quantitative methods for AML prognosis prediction. We identify the most accurate and robust models in predicting patient response to therapy, remission duration, and overall survival. We further investigate patient response to therapy, a clinically actionable prediction, and find that patients that are classified as resistant to therapy are harder to predict than responsive patients across the 31 models submitted to the challenge. The top two performing models, which held a high sensitivity to these patients, substantially utilized the proteomics data to make predictions. Using these models, we also identify which signaling proteins were useful in predicting patient therapeutic response. PMID:27351836

Utility of DWI with quantitative ADC values in ovarian tumors: a meta-analysis of diagnostic test performance.

PubMed

Pi, Shan; Cao, Rong; Qiang, Jin Wei; Guo, Yan Hui

2018-01-01

Background Diffusion-weighted imaging (DWI) and quantitative apparent diffusion coefficient (ADC) values are widely used in the differential diagnosis of ovarian tumors. Purpose To assess the diagnostic performance of quantitative ADC values in ovarian tumors. Material and Methods PubMed, Embase, the Cochrane Library, and local databases were searched for studies assessing ovarian tumors using quantitative ADC values. We quantitatively analyzed the diagnostic performances for two clinical problems: benign vs. malignant tumors and borderline vs. malignant tumors. We evaluated diagnostic performances by the pooled sensitivity and specificity values and by summary receiver operating characteristic (SROC) curves. Subgroup analyses were used to analyze study heterogeneity. Results From the 742 studies identified in the search results, 16 studies met our inclusion criteria. A total of ten studies evaluated malignant vs. benign ovarian tumors and six studies assessed malignant vs. borderline ovarian tumors. Regarding the diagnostic accuracy of quantitative ADC values for distinguishing between malignant and benign ovarian tumors, the pooled sensitivity and specificity values were 0.91 and 0.91, respectively. The area under the SROC curve (AUC) was 0.96. For differentiating borderline from malignant tumors, the pooled sensitivity and specificity values were 0.89 and 0.79, and the AUC was 0.91. The methodological quality of the included studies was moderate. Conclusion Quantitative ADC values could serve as useful preoperative markers for predicting the nature of ovarian tumors. Nevertheless, prospective trials focused on standardized imaging parameters are needed to evaluate the clinical value of quantitative ADC values in ovarian tumors.

Quantitation of MRI sensitivity to quasi-monodisperse microbubble contrast agents for spatially resolved manometry.

PubMed

Bencsik, Martin; Al-Rwaili, Amgad; Morris, Robert; Fairhurst, David J; Mundell, Victoria; Cave, Gareth; McKendry, Jonathan; Evans, Stephen

2013-11-01

The direct in-vivo measurement of fluid pressure cannot be achieved with MRI unless it is done with the contribution of a contrast agent. No such contrast agents are currently available commercially, whilst those demonstrated previously only produced qualitative results due to their broad size distribution. Our aim is to quantitate then model the MR sensitivity to the presence of quasi-monodisperse microbubble populations. Lipid stabilised microbubble populations with mean radius 1.2 ± 0.8 μm have been produced by mechanical agitation. Contrast agents with increasing volume fraction of bubbles up to 4% were formed and the contribution the bubbles bring to the relaxation rate was quantitated. A periodic pressure change was also continuously applied to the same contrast agent, until MR signal changes were only due to bubble radius change and not due to a change in bubble density. The MR data compared favourably with the prediction of an improved numerical simulation. An excellent MR sensitivity of 23 % bar(-1) has been demonstrated. This work opens up the possibility of generating microbubble preparations tailored to specific applications with optimised MR sensitivity, in particular MRI based in-vivo manometry. Copyright © 2012 Wiley Periodicals, Inc.

Quantitative prediction of oral cancer risk in patients with oral leukoplakia.

PubMed

Liu, Yao; Li, Yicheng; Fu, Yue; Liu, Tong; Liu, Xiaoyong; Zhang, Xinyan; Fu, Jie; Guan, Xiaobing; Chen, Tong; Chen, Xiaoxin; Sun, Zheng

2017-07-11

Exfoliative cytology has been widely used for early diagnosis of oral squamous cell carcinoma. We have developed an oral cancer risk index using DNA index value to quantitatively assess cancer risk in patients with oral leukoplakia, but with limited success. In order to improve the performance of the risk index, we collected exfoliative cytology, histopathology, and clinical follow-up data from two independent cohorts of normal, leukoplakia and cancer subjects (training set and validation set). Peaks were defined on the basis of first derivatives with positives, and modern machine learning techniques were utilized to build statistical prediction models on the reconstructed data. Random forest was found to be the best model with high sensitivity (100%) and specificity (99.2%). Using the Peaks-Random Forest model, we constructed an index (OCRI2) as a quantitative measurement of cancer risk. Among 11 leukoplakia patients with an OCRI2 over 0.5, 4 (36.4%) developed cancer during follow-up (23 ± 20 months), whereas 3 (5.3%) of 57 leukoplakia patients with an OCRI2 less than 0.5 developed cancer (32 ± 31 months). OCRI2 is better than other methods in predicting oral squamous cell carcinoma during follow-up. In conclusion, we have developed an exfoliative cytology-based method for quantitative prediction of cancer risk in patients with oral leukoplakia.

Diagnostic accuracy of quantitative real-time PCR assay versus clinical and Gram stain identification of bacterial vaginosis.

PubMed

Menard, J-P; Mazouni, C; Fenollar, F; Raoult, D; Boubli, L; Bretelle, F

2010-12-01

The purpose of this investigation was to determine the diagnostic accuracy of quantitative real-time polymerase chain reaction (PCR) assay in diagnosing bacterial vaginosis versus the standard methods, the Amsel criteria and the Nugent score. The Amsel criteria, the Nugent score, and results from the molecular tool were obtained independently from vaginal samples of 163 pregnant women who reported abnormal vaginal symptoms before 20 weeks gestation. To determine the performance of the molecular tool, we calculated the kappa value, sensitivity, specificity, and positive and negative predictive values. Either or both of the Amsel criteria (≥3 criteria) and the Nugent score (score ≥7) indicated that 25 women (15%) had bacterial vaginosis, and the remaining 138 women did not. DNA levels of Gardnerella vaginalis or Atopobium vaginae exceeded 10(9) copies/mL or 10(8) copies/mL, respectively, in 34 (21%) of the 163 samples. Complete agreement between both reference methods and high concentrations of G. vaginalis and A. vaginae was found in 94.5% of women (154/163 samples, kappa value = 0.81, 95% confidence interval 0.70-0.81). The nine samples with discordant results were categorized as intermediate flora by the Nugent score. The molecular tool predicted bacterial vaginosis with a sensitivity of 100%, a specificity of 93%, a positive predictive value of 73%, and a negative predictive value of 100%. The quantitative real-time PCR assay shows excellent agreement with the results of both reference methods for the diagnosis of bacterial vaginosis.

Multi-scale modeling of microstructure dependent intergranular brittle fracture using a quantitative phase-field based method

DOE PAGES

Chakraborty, Pritam; Zhang, Yongfeng; Tonks, Michael R.

2015-12-07

In this study, the fracture behavior of brittle materials is strongly influenced by their underlying microstructure that needs explicit consideration for accurate prediction of fracture properties and the associated scatter. In this work, a hierarchical multi-scale approach is pursued to model microstructure sensitive brittle fracture. A quantitative phase-field based fracture model is utilized to capture the complex crack growth behavior in the microstructure and the related parameters are calibrated from lower length scale atomistic simulations instead of engineering scale experimental data. The workability of this approach is demonstrated by performing porosity dependent intergranular fracture simulations in UO 2 and comparingmore » the predictions with experiments.« less

Multi-scale modeling of microstructure dependent intergranular brittle fracture using a quantitative phase-field based method

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

Chakraborty, Pritam; Zhang, Yongfeng; Tonks, Michael R.

In this study, the fracture behavior of brittle materials is strongly influenced by their underlying microstructure that needs explicit consideration for accurate prediction of fracture properties and the associated scatter. In this work, a hierarchical multi-scale approach is pursued to model microstructure sensitive brittle fracture. A quantitative phase-field based fracture model is utilized to capture the complex crack growth behavior in the microstructure and the related parameters are calibrated from lower length scale atomistic simulations instead of engineering scale experimental data. The workability of this approach is demonstrated by performing porosity dependent intergranular fracture simulations in UO 2 and comparingmore » the predictions with experiments.« less

Enhanced analytical sensitivity of a quantitative PCR for CMV using a modified nucleic-acid extraction procedure.

PubMed

Ferreira-Gonzalez, A; Yanovich, S; Langley, M R; Weymouth, L A; Wilkinson, D S; Garrett, C T

2000-01-01

Accurate and rapid diagnosis of CMV disease in immunocompromised individuals remains a challenge. Quantitative polymerase chain reaction (QPCR) methods for detection of CMV in peripheral blood mononuclear cells (PBMC) have improved the positive and negative predictive value of PCR for diagnosis of CMV disease. However, detection of CMV in plasma has demonstrated a lower negative predictive value for plasma as compared with PBMC. To enhance the sensitivity of the QPCR assay for plasma specimens, plasma samples were centrifuged before nucleic-acid extraction and the extracted DNA resolubilized in reduced volume. Optimization of the nucleic-acid extraction focused on decreasing or eliminating the presence of inhibitors in the pelleted plasma. Quantitation was achieved by co-amplifying an internal quantitative standard (IS) with the same primer sequences as CMV. PCR products were detected by hybridization in a 96-well microtiter plate coated with a CMV or IS specific probe. The precision of the QPCR assay for samples prepared from untreated and from pelleted plasma was then assessed. The coefficient of variation for both types of samples was almost identical and the magnitude of the coefficient of variations was reduced by a factor of ten if the data were log transformed. Linearity of the QPCR assay extended over a 3.3-log range for both types of samples but the range of linearity for pelleted plasma was 20 to 40,000 viral copies/ml (vc/ml) in contrast to 300 to 400,000 vc/ml for plasma. Thus, centrifugation of plasma before nucleic-acid extraction and resuspension of extracted CMV DNA in reduced volume enhanced the analytical sensitivity approximately tenfold over the dynamic range of the assay. Copyright 2000 Wiley-Liss, Inc.

A systematic review of quantitative burn wound microbiology in the management of burns patients.

PubMed

Halstead, Fenella D; Lee, Kwang Chear; Kwei, Johnny; Dretzke, Janine; Oppenheim, Beryl A; Moiemen, Naiem S

2018-02-01

The early diagnosis of infection or sepsis in burns are important for patient care. Globally, a large number of burn centres advocate quantitative cultures of wound biopsies for patient management, since there is assumed to be a direct link between the bioburden of a burn wound and the risk of microbial invasion. Given the conflicting study findings in this area, a systematic review was warranted. Bibliographic databases were searched with no language restrictions to August 2015. Study selection, data extraction and risk of bias assessment were performed in duplicate using pre-defined criteria. Substantial heterogeneity precluded quantitative synthesis, and findings were described narratively, sub-grouped by clinical question. Twenty six laboratory and/or clinical studies were included. Substantial heterogeneity hampered comparisons across studies and interpretation of findings. Limited evidence suggests that (i) more than one quantitative microbiology sample is required to obtain reliable estimates of bacterial load; (ii) biopsies are more sensitive than swabs in diagnosing or predicting sepsis; (iii) high bacterial loads may predict worse clinical outcomes, and (iv) both quantitative and semi-quantitative culture reports need to be interpreted with caution and in the context of other clinical risk factors. The evidence base for the utility and reliability of quantitative microbiology for diagnosing or predicting clinical outcomes in burns patients is limited and often poorly reported. Consequently future research is warranted. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Non-animal assessment of skin sensitization hazard: Is an integrated testing strategy needed, and if so what should be integrated?

PubMed

Roberts, David W; Patlewicz, Grace

2018-01-01

There is an expectation that to meet regulatory requirements, and avoid or minimize animal testing, integrated approaches to testing and assessment will be needed that rely on assays representing key events (KEs) in the skin sensitization adverse outcome pathway. Three non-animal assays have been formally validated and regulatory adopted: the direct peptide reactivity assay (DPRA), the KeratinoSens™ assay and the human cell line activation test (h-CLAT). There have been many efforts to develop integrated approaches to testing and assessment with the "two out of three" approach attracting much attention. Here a set of 271 chemicals with mouse, human and non-animal sensitization test data was evaluated to compare the predictive performances of the three individual non-animal assays, their binary combinations and the "two out of three" approach in predicting skin sensitization potential. The most predictive approach was to use both the DPRA and h-CLAT as follows: (1) perform DPRA - if positive, classify as sensitizing, and (2) if negative, perform h-CLAT - a positive outcome denotes a sensitizer, a negative, a non-sensitizer. With this approach, 85% (local lymph node assay) and 93% (human) of non-sensitizer predictions were correct, whereas the "two out of three" approach had 69% (local lymph node assay) and 79% (human) of non-sensitizer predictions correct. The findings are consistent with the argument, supported by published quantitative mechanistic models that only the first KE needs to be modeled. All three assays model this KE to an extent. The value of using more than one assay depends on how the different assays compensate for each other's technical limitations. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Decision-making, sensitivity to reward, and attrition in weight-management

PubMed Central

Koritzky, Gilly; Dieterle, Camille; Rice, Chantelle; Jordan, Katie; Bechara, Antoine

2014-01-01

Objective Attrition is a common problem in weight-management. Understanding the risk factors for attrition should enhance professionals’ ability to increase completion rates and improve health outcomes for more individuals. We propose a model that draws upon neuropsychological knowledge on reward-sensitivity in obesity and overeating to predict attrition. Design & Methods 52 participants in a weight-management program completed a complex decision-making task.Decision-making characteristics – including sensitivity to reward – were further estimated using a quantitative model. Impulsivity and risk-taking measures were also administered. Results Consistent with the hypothesis that sensitivity to reward predicted attrition, program dropouts had higher sensitivity to reward than completers (p < 0.03). No differences were observed between completers and dropouts in initial BMI, age, employment status, or the number of prior weight-loss attempts (p ≥ 0.07). Completers had a slightly higher education level than dropouts, but its inclusion in the model did not increase predictive power. Impulsivity, delay of gratification, and risk-taking did not predict attrition, either. Conclusions Findings link attrition in weight-management to the neural mechanisms associated with reward-seeking and related influences on decision-making. Individual differences in the magnitude of response elicited by rewards may account for the relative difficulty experienced by dieters in adhering to treatment. PMID:24771588

Gram staining of protected pulmonary specimens in the early diagnosis of ventilator-associated pneumonia.

PubMed

Mimoz, O; Karim, A; Mazoit, J X; Edouard, A; Leprince, S; Nordmann, P

2000-11-01

We evaluated prospectively the use of Gram staining of protected pulmonary specimens to allow the early diagnosis of ventilator-associated pneumonia (VAP), compared with the use of 60 bronchoscopic protected specimen brushes (PSB) and 126 blinded plugged telescopic catheters (PTC) obtained from 134 patients. Gram stains were from Cytospin slides; they were studied for the presence of microorganisms in 10 and 50 fields by two independent observers and classified according to their Gram stain morphology. Quantitative cultures were performed after serial dilution and plating on appropriate culture medium. A final diagnosis of VAP, based on a culture of > or = 10(3) c.f.u. ml-1, was established after 81 (44%) samplings. When 10 fields were analysed, a strong relationship was found between the presence of bacteria on Gram staining and the final diagnosis of VAP (for PSB and PTC respectively: sensitivity 74 and 81%, specificity 94 and 100%, positive predictive value 91 and 100%, negative predictive value 82 and 88%). The correlation was less when we compared the morphology of microorganisms observed on Gram staining with those of bacteria obtained from quantitative cultures (for PSB and PTC respectively: sensitivity 54 and 69%, specificity 86 and 89%, positive predictive value 72 and 78%, negative predictive value 74 and 84%). Increasing the number of fields read to 50 was associated with a slight decrease in specificity and positive predictive value of Gram staining, but with a small increase in its sensitivity and negative predictive value. The results obtained by the two observers were similar to each other for both numbers of fields analysed. Gram staining of protected pulmonary specimens performed on 10 fields predicted the presence of VAP and partially identified (using Gram stain morphology) the microorganisms growing at significant concentrations, and could help in the early choice of the treatment of VAP. Increasing the number of fields read or having the Gram stain analysed by two independent individuals did not improve the results.

MethylMeter®: bisulfite-free quantitative and sensitive DNA methylation profiling and mutation detection in FFPE samples

PubMed Central

McCarthy, David; Pulverer, Walter; Weinhaeusel, Andreas; Diago, Oscar R; Hogan, Daniel J; Ostertag, Derek; Hanna, Michelle M

2016-01-01

Aim: Development of a sensitive method for DNA methylation profiling and associated mutation detection in clinical samples. Materials & methods: Formalin-fixed and paraffin-embedded tumors received by clinical laboratories often contain insufficient DNA for analysis with bisulfite or methylation sensitive restriction enzymes-based methods. To increase sensitivity, methyl-CpG DNA capture and Coupled Abscription PCR Signaling detection were combined in a new assay, MethylMeter®. Gliomas were analyzed for MGMT methylation, glioma CpG island methylator phenotype and IDH1 R132H. Results: MethylMeter had 100% assay success rate measuring all five biomarkers in formalin-fixed and paraffin-embedded tissue. MGMT methylation results were supported by survival and mRNA expression data. Conclusion: MethylMeter is a sensitive and quantitative method for multitarget DNA methylation profiling and associated mutation detection. The MethylMeter-based GliomaSTRAT assay measures methylation of four targets and one mutation to simultaneously grade gliomas and predict their response to temozolomide. This information is clinically valuable in management of gliomas. PMID:27337298

Use of Artificial Intelligence and Machine Learning Algorithms with Gene Expression Profiling to Predict Recurrent Nonmuscle Invasive Urothelial Carcinoma of the Bladder.

PubMed

Bartsch, Georg; Mitra, Anirban P; Mitra, Sheetal A; Almal, Arpit A; Steven, Kenneth E; Skinner, Donald G; Fry, David W; Lenehan, Peter F; Worzel, William P; Cote, Richard J

2016-02-01

Due to the high recurrence risk of nonmuscle invasive urothelial carcinoma it is crucial to distinguish patients at high risk from those with indolent disease. In this study we used a machine learning algorithm to identify the genes in patients with nonmuscle invasive urothelial carcinoma at initial presentation that were most predictive of recurrence. We used the genes in a molecular signature to predict recurrence risk within 5 years after transurethral resection of bladder tumor. Whole genome profiling was performed on 112 frozen nonmuscle invasive urothelial carcinoma specimens obtained at first presentation on Human WG-6 BeadChips (Illumina®). A genetic programming algorithm was applied to evolve classifier mathematical models for outcome prediction. Cross-validation based resampling and gene use frequencies were used to identify the most prognostic genes, which were combined into rules used in a voting algorithm to predict the sample target class. Key genes were validated by quantitative polymerase chain reaction. The classifier set included 21 genes that predicted recurrence. Quantitative polymerase chain reaction was done for these genes in a subset of 100 patients. A 5-gene combined rule incorporating a voting algorithm yielded 77% sensitivity and 85% specificity to predict recurrence in the training set, and 69% and 62%, respectively, in the test set. A singular 3-gene rule was constructed that predicted recurrence with 80% sensitivity and 90% specificity in the training set, and 71% and 67%, respectively, in the test set. Using primary nonmuscle invasive urothelial carcinoma from initial occurrences genetic programming identified transcripts in reproducible fashion, which were predictive of recurrence. These findings could potentially impact nonmuscle invasive urothelial carcinoma management. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Added value of semi-quantitative breast-specific gamma imaging in the work-up of suspicious breast lesions compared to mammography, ultrasound and 3-T MRI

PubMed Central

Seymer, A; Keinrath, P; Holzmannhofer, J; Pirich, C; Hergan, K; Meissnitzer, M W

2015-01-01

Objective: To prospectively analyse the diagnostic value of semi-quantitative breast-specific gamma imaging (BSGI) in the work-up of suspicious breast lesions compared with that of mammography (MG), breast ultrasound and MRI of the breast. Methods: Within a 15-month period, 67 patients with 92 breast lesions rated as Category IV or V according to the breast imaging reporting and data system detected with MG and/or ultrasound were included into the study. After the injection of 740–1110 MBq of Technetium-99m (99mTc) SestaMIBI intravenously, scintigrams were obtained in two projections comparable to MG. The BSGI was analysed visually and semi-quantitatively by calculating a relative uptake factor (X). With the exception of two patients with cardiac pacemakers, all patients underwent 3-T breast MRI. Biopsy results were obtained as the reference standard in all patients. Sensitivity, specificity, positive- and negative-predictive values, accuracy and area under the curve were calculated for each modality. Results: Among the 92 lesions, 67 (72.8%) were malignant. 60 of the 67 cancers of any size were detected by BSGI with an overall sensitivity of 90%, only exceeded by ultrasound with a sensitivity of 99%. The sensitivity of BSGI for lesions <1 cm declined significantly to 60%. Overall specificity of ultrasound was only 20%. Specificity, accuracy and positive-predictive value were the highest for BSGI (56%, 80% and 85%, respectively). X was significantly higher for malignant lesions (mean, 4.27) and differed significantly between ductal types (mean, 4.53) and the other histopathological entities (mean, 3.12). Conclusion: Semi-quantitative BSGI with calculation of the relative uptake factor (X) can help to characterize breast lesions. BSGI negativity may obviate the need for biopsy of breast lesions >1 cm with low or intermediate prevalence for malignancy. Advances in knowledge: Compared with morphological imaging modalities, specificity, positive-predictive value for malignancy and accuracy were the highest for BSGI in our study. BSGI negativity may support the decision not to biopsy in selected lesions with a low or low-to-moderate pre-test probability for malignancy. PMID:25882690

Quantitative Sensory Testing Predicts Pregabalin Efficacy in Painful Chronic Pancreatitis

PubMed Central

Olesen, Søren S.; Graversen, Carina; Bouwense, Stefan A. W.; van Goor, Harry; Wilder-Smith, Oliver H. G.; Drewes, Asbjørn M.

2013-01-01

Background A major problem in pain medicine is the lack of knowledge about which treatment suits a specific patient. We tested the ability of quantitative sensory testing to predict the analgesic effect of pregabalin and placebo in patients with chronic pancreatitis. Methods Sixty-four patients with painful chronic pancreatitis received pregabalin (150–300 mg BID) or matching placebo for three consecutive weeks. Analgesic effect was documented in a pain diary based on a visual analogue scale. Responders were defined as patients with a reduction in clinical pain score of 30% or more after three weeks of study treatment compared to baseline recordings. Prior to study medication, pain thresholds to electric skin and pressure stimulation were measured in dermatomes T10 (pancreatic area) and C5 (control area). To eliminate inter-subject differences in absolute pain thresholds an index of sensitivity between stimulation areas was determined (ratio of pain detection thresholds in pancreatic versus control area, ePDT ratio). Pain modulation was recorded by a conditioned pain modulation paradigm. A support vector machine was used to screen sensory parameters for their predictive power of pregabalin efficacy. Results The pregabalin responders group was hypersensitive to electric tetanic stimulation of the pancreatic area (ePDT ratio 1.2 (0.9–1.3)) compared to non-responders group (ePDT ratio: 1.6 (1.5–2.0)) (P = 0.001). The electrical pain detection ratio was predictive for pregabalin effect with a classification accuracy of 83.9% (P = 0.007). The corresponding sensitivity was 87.5% and specificity was 80.0%. No other parameters were predictive of pregabalin or placebo efficacy. Conclusions The present study provides first evidence that quantitative sensory testing predicts the analgesic effect of pregabalin in patients with painful chronic pancreatitis. The method can be used to tailor pain medication based on patient’s individual sensory profile and thus comprises a significant step towards personalized pain medicine. PMID:23469256

Determination of IgE antibodies to the benzylpenicilloyl determinant: a comparison of the sensitivity and specificity of three radio allergo sorbent test methods.

PubMed

Garcia, J J; Blanca, M; Moreno, F; Vega, J M; Mayorga, C; Fernandez, J; Juarez, C; Romano, A; de Ramon, E

1997-01-01

The quantitation of in vitro IgE antibodies to the benzylpenicilloyl determinant (BPO) is a useful tool for evaluating suspected penicillin allergic subjects. Although many different methods have been employed, few studies have compared their diagnostic specificity and sensitivity. In this study, the sensitivity and specificity of three different radio allergo sorbent test (RAST) methods for quantitating specific IgE antibodies to the BPO determinant were compared. Thirty positive control sera (serum samples from penicillin allergic subjects with a positive clinical history and a positive penicillin skin test) and 30 negative control sera (sera from subjects with no history of penicillin allergy and negative skin tests) were tested for BPO-specific IgE antibodies by RAST using three different conjugates coupled to the solid phase: benzylpenicillin conjugated to polylysine (BPO-PLL), benzylpenicillin conjugated to human serum albumin (BPO-HSA), and benzylpenicillin conjugated to an aminospacer (BPO-SP). Receiver operator control curves (ROC analysis) were carried out by determining different cut-off points between positive and negative values. Contingence tables were constructed and sensitivity, specificity, negative predictive values (PV-), and positive predictive values (PV+) were calculated. Pearson correlation coefficients (r) and intraclass correlation coefficients (ICC) were determined and the differences between methods were compared by chi 2 analysis. Analysis of the areas defined by the ROC curves showed statistical differences among the three methods. When cut-off points for optimal sensitivity and specificity were chosen, the BPO-HSA assay was less sensitive and less specific and had a lower PV- and PV+ than the BPO-PLL and BPO-SP assays. Assessment of r and ICC indicated that the correlation was very high, but the concordance between the PLL and SP methods was higher than between the PLL and HSA or SP and HSA methods. We conclude that for quantitating IgE antibodies by RAST to the BPO determinant, BPO-SP or BPO-PLL conjugates offer advantages in sensitivity and specificity compared with BPO-HSA. These results support and extend previous in vitro studies by our group and highlight the importance of the carrier for RAST assays.

Impact of implementation choices on quantitative predictions of cell-based computational models

NASA Astrophysics Data System (ADS)

Kursawe, Jochen; Baker, Ruth E.; Fletcher, Alexander G.

2017-09-01

'Cell-based' models provide a powerful computational tool for studying the mechanisms underlying the growth and dynamics of biological tissues in health and disease. An increasing amount of quantitative data with cellular resolution has paved the way for the quantitative parameterisation and validation of such models. However, the numerical implementation of cell-based models remains challenging, and little work has been done to understand to what extent implementation choices may influence model predictions. Here, we consider the numerical implementation of a popular class of cell-based models called vertex models, which are often used to study epithelial tissues. In two-dimensional vertex models, a tissue is approximated as a tessellation of polygons and the vertices of these polygons move due to mechanical forces originating from the cells. Such models have been used extensively to study the mechanical regulation of tissue topology in the literature. Here, we analyse how the model predictions may be affected by numerical parameters, such as the size of the time step, and non-physical model parameters, such as length thresholds for cell rearrangement. We find that vertex positions and summary statistics are sensitive to several of these implementation parameters. For example, the predicted tissue size decreases with decreasing cell cycle durations, and cell rearrangement may be suppressed by large time steps. These findings are counter-intuitive and illustrate that model predictions need to be thoroughly analysed and implementation details carefully considered when applying cell-based computational models in a quantitative setting.

A Quantitative Study of Oxygen as a Metabolic Regulator

NASA Technical Reports Server (NTRS)

Radhakrishnan, Krishnan; LaManna, Joseph C.; Cabrera, Marco E.

1999-01-01

An acute reduction in oxygen (O2) delivery to a tissue is generally associated with a decrease in phosphocreatine, increases in ADP, NADH/NAD, and inorganic phosphate, increased rates of glycolysis and lactate production, and reduced rates of pyruvate and fatty acid oxidation. However, given the complexity of the human bioenergetic system and its components, it is difficult to determine quantitatively how cellular metabolic processes interact to maintain ATP homeostasis during stress (e.g., hypoxia, ischemia, and exercise). Of special interest is the determination of mechanisms relating tissue oxygenation to observed metabolic responses at the tissue, organ, and whole body levels and the quantification of how changes in tissue O2 availability affect the pathways of ATP synthesis and the metabolites that control these pathways. In this study, we extend a previously developed mathematical model of human bioenergetics to provide a physicochemical framework that permits quantitative understanding of O2 as a metabolic regulator. Specifically, the enhancement permits studying the effects of variations in tissue oxygenation and in parameters controlling the rate of cellular respiration on glycolysis, lactate production, and pyruvate oxidation. The whole body is described as a bioenergetic system consisting of metabolically distinct tissue/organ subsystems that exchange materials with the blood. In order to study the dynamic response of each subsystem to stimuli, we solve the ordinary differential equations describing the temporal evolution of metabolite levels, given the initial concentrations. The solver used in the present study is the packaged code LSODE, as implemented in the NASA Lewis kinetics and sensitivity analysis code, LSENS. A major advantage of LSENS is the efficient procedures supporting systematic sensitivity analysis, which provides the basic methods for studying parameter sensitivities (i.e., changes in model behavior due to parameter variation). Sensitivity analysis establishes relationships between model predictions and problem parameters (i.e., initial concentrations, rate coefficients, etc). It helps determine the effects of uncertainties or changes in these input parameters on the predictions, which ultimately are compared with experimental observations in order to validate the model. Sensitivity analysis can identify parameters that must be determined accurately because of their large effect on the model predictions and parameters that need not be known with great precision because they have little or no effect on the solution. This capability may prove to be important in optimizing the design of experiments, thereby reducing the use of animals. This approach can be applied to study the metabolic effects of reduced oxygen delivery to cardiac muscle due to local myocardial ischemia and the effects of acute hypoxia on brain metabolism. Other important applications of sensitivity analysis include identification of quantitatively relevant pathways and biochemical species within an overall mechanism, when examining the effects of a genetic anomaly or pathological state on energetic system components and whole system behavior.

Quantitative Acoustic Model for Adhesion Evaluation of Pmma/silicon Film Structures

NASA Astrophysics Data System (ADS)

Ju, H. S.; Tittmann, B. R.

2010-02-01

A Poly-methyl-methacrylate (PMMA) film on a silicon substrate is a main structure for photolithography in semiconductor manufacturing processes. This paper presents a potential of scanning acoustic microscopy (SAM) for nondestructive evaluation of the PMMA/Si film structure, whose adhesion failure is commonly encountered during the fabrication and post-fabrication processes. A physical model employing a partial discontinuity in displacement is developed for rigorously quantitative evaluation of the interfacial weakness. The model is implanted to the matrix method for the surface acoustic wave (SAW) propagation in anisotropic media. Our results show that variations in the SAW velocity and reflectance are predicted to show their sensitivity to the adhesion condition. Experimental results by the v(z) technique and SAW velocity reconstruction verify the prediction.

Benefit of hepatitis C virus core antigen assay in prediction of therapeutic response to interferon and ribavirin combination therapy.

PubMed

Takahashi, Masahiko; Saito, Hidetsugu; Higashimoto, Makiko; Atsukawa, Kazuhiro; Ishii, Hiromasa

2005-01-01

A highly sensitive second-generation hepatitis C virus (HCV) core antigen assay has recently been developed. We compared viral disappearance and first-phase kinetics between commercially available core antigen (Ag) assays, Lumipulse Ortho HCV Ag (Lumipulse-Ag), and a quantitative HCV RNA PCR assay, Cobas Amplicor HCV Monitor test, version 2 (Amplicor M), to estimate the predictive benefit of a sustained viral response (SVR) and non-SVR in 44 genotype 1b patients treated with interferon (IFN) and ribavirin. HCV core Ag negativity could predict SVR on day 1 (sensitivity = 100%, specificity = 85.0%, accuracy = 86.4%), whereas RNA negativity could predict SVR on day 7 (sensitivity = 100%, specificity = 87.2%, accuracy = 88.6%). None of the patients who had detectable serum core Ag or RNA on day 14 achieved SVR (specificity = 100%). The predictive accuracy on day 14 was higher by RNA negativity (93.2%) than that by core Ag negativity (75.0%). The combined predictive criterion of both viral load decline during the first 24 h and basal viral load was also predictive for SVR; the sensitivities of Lumipulse-Ag and Amplicor-M were 45.5 and 47.6%, respectively, and the specificity was 100%. Amplicor-M had better predictive accuracy than Lumipulse-Ag in 2-week disappearance tests because it had better sensitivity. On the other hand, estimates of kinetic parameters were similar regardless of the detection method. Although the correlations between Lumipulse-Ag and Amplicor-M were good both before and 24 h after IFN administration, HCV core Ag seemed to be relatively lower 24 h after IFN administration than before administration. Lumipulse-Ag seems to be useful for detecting the HCV concentration during IFN therapy; however, we still need to understand the characteristics of the assay.

Diagnostic value of highly-sensitive chimerism analysis after allogeneic stem cell transplantation.

PubMed

Sellmann, Lea; Rabe, Kim; Bünting, Ivonne; Dammann, Elke; Göhring, Gudrun; Ganser, Arnold; Stadler, Michael; Weissinger, Eva M; Hambach, Lothar

2018-05-02

Conventional analysis of host chimerism (HC) frequently fails to detect relapse before its clinical manifestation in patients with hematological malignancies after allogeneic stem cell transplantation (allo-SCT). Quantitative PCR (qPCR)-based highly-sensitive chimerism analysis extends the detection limit of conventional (short tandem repeats-based) chimerism analysis from 1 to 0.01% host cells in whole blood. To date, the diagnostic value of highly-sensitive chimerism analysis is hardly defined. Here, we applied qPCR-based chimerism analysis to 901 blood samples of 71 out-patients with hematological malignancies after allo-SCT. Receiver operating characteristics (ROC) curves were calculated for absolute HC values and for the increments of HC before relapse. Using the best cut-offs, relapse was detected with sensitivities of 74 or 85% and specificities of 69 or 75%, respectively. Positive predictive values (PPVs) were only 12 or 18%, but the respective negative predictive values were 98 or 99%. Relapse was detected median 38 or 45 days prior to clinical diagnosis, respectively. Considering also durations of steadily increasing HC of more than 28 days improved PPVs to more than 28 or 59%, respectively. Overall, highly-sensitive chimerism analysis excludes relapses with high certainty and predicts relapses with high sensitivity and specificity more than a month prior to clinical diagnosis.

Sensitivity study on durability variables of marine concrete structures

NASA Astrophysics Data System (ADS)

Zhou, Xin'gang; Li, Kefei

2013-06-01

In order to study the influence of parameters on durability of marine concrete structures, the parameter's sensitivity analysis was studied in this paper. With the Fick's 2nd law of diffusion and the deterministic sensitivity analysis method (DSA), the sensitivity factors of apparent surface chloride content, apparent chloride diffusion coefficient and its time dependent attenuation factor were analyzed. The results of the analysis show that the impact of design variables on concrete durability was different. The values of sensitivity factor of chloride diffusion coefficient and its time dependent attenuation factor were higher than others. Relative less error in chloride diffusion coefficient and its time dependent attenuation coefficient induces a bigger error in concrete durability design and life prediction. According to probability sensitivity analysis (PSA), the influence of mean value and variance of concrete durability design variables on the durability failure probability was studied. The results of the study provide quantitative measures of the importance of concrete durability design and life prediction variables. It was concluded that the chloride diffusion coefficient and its time dependent attenuation factor have more influence on the reliability of marine concrete structural durability. In durability design and life prediction of marine concrete structures, it was very important to reduce the measure and statistic error of durability design variables.

Machine learning for predicting the response of breast cancer to neoadjuvant chemotherapy

PubMed Central

Mani, Subramani; Chen, Yukun; Li, Xia; Arlinghaus, Lori; Chakravarthy, A Bapsi; Abramson, Vandana; Bhave, Sandeep R; Levy, Mia A; Xu, Hua; Yankeelov, Thomas E

2013-01-01

Objective To employ machine learning methods to predict the eventual therapeutic response of breast cancer patients after a single cycle of neoadjuvant chemotherapy (NAC). Materials and methods Quantitative dynamic contrast-enhanced MRI and diffusion-weighted MRI data were acquired on 28 patients before and after one cycle of NAC. A total of 118 semiquantitative and quantitative parameters were derived from these data and combined with 11 clinical variables. We used Bayesian logistic regression in combination with feature selection using a machine learning framework for predictive model building. Results The best predictive models using feature selection obtained an area under the curve of 0.86 and an accuracy of 0.86, with a sensitivity of 0.88 and a specificity of 0.82. Discussion With the numerous options for NAC available, development of a method to predict response early in the course of therapy is needed. Unfortunately, by the time most patients are found not to be responding, their disease may no longer be surgically resectable, and this situation could be avoided by the development of techniques to assess response earlier in the treatment regimen. The method outlined here is one possible solution to this important clinical problem. Conclusions Predictive modeling approaches based on machine learning using readily available clinical and quantitative MRI data show promise in distinguishing breast cancer responders from non-responders after the first cycle of NAC. PMID:23616206

Quantitative Ultrasound for Measuring Obstructive Severity in Children with Hydronephrosis.

PubMed

Cerrolaza, Juan J; Peters, Craig A; Martin, Aaron D; Myers, Emmarie; Safdar, Nabile; Linguraru, Marius George

2016-04-01

We define sonographic biomarkers for hydronephrotic renal units that can predict the necessity of diuretic nuclear renography. We selected a cohort of 50 consecutive patients with hydronephrosis of varying severity in whom 2-dimensional sonography and diuretic mercaptoacetyltriglycine renography had been performed. A total of 131 morphological parameters were computed using quantitative image analysis algorithms. Machine learning techniques were then applied to identify ultrasound based safety thresholds that agreed with the t½ for washout. A best fit model was then derived for each threshold level of t½ that would be clinically relevant at 20, 30 and 40 minutes. Receiver operating characteristic curve analysis was performed. Sensitivity, specificity and area under the receiver operating characteristic curve were determined. Improvement obtained by the quantitative imaging method compared to the Society for Fetal Urology grading system and the hydronephrosis index was statistically verified. For the 3 thresholds considered and at 100% sensitivity the specificities of the quantitative imaging method were 94%, 70% and 74%, respectively. Corresponding area under the receiver operating characteristic curve values were 0.98, 0.94 and 0.94, respectively. Improvement obtained by the quantitative imaging method over the Society for Fetal Urology grade and hydronephrosis index was statistically significant (p <0.05 in all cases). Quantitative imaging analysis of renal sonograms in children with hydronephrosis can identify thresholds of clinically significant washout times with 100% sensitivity to decrease the number of diuretic renograms in up to 62% of children. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

The local lymph node assay in 2014.

PubMed

Basketter, David A; Gerberick, G Frank; Kimber, Ian

2014-01-01

Toxicology endeavors to predict the potential of materials to cause adverse health (and environmental) effects and to assess the risk(s) associated with exposure. For skin sensitizers, the local lymph node assay was the first method to be fully and independently validated, as well as the first to offer an objective end point with a quantitative measure of sensitizing potency (in addition to hazard identification). Fifteen years later, it serves as the primary standard for the development of in vitro/in chemico/in silico alternatives.

Tumor invasiveness defined by IASLC/ATS/ERS classification of ground-glass nodules can be predicted by quantitative CT parameters.

PubMed

Zhou, Qian-Jun; Zheng, Zhi-Chun; Zhu, Yong-Qiao; Lu, Pei-Ji; Huang, Jia; Ye, Jian-Ding; Zhang, Jie; Lu, Shun; Luo, Qing-Quan

2017-05-01

To investigate the potential value of CT parameters to differentiate ground-glass nodules between noninvasive adenocarcinoma and invasive pulmonary adenocarcinoma (IPA) as defined by IASLC/ATS/ERS classification. We retrospectively reviewed 211 patients with pathologically proved stage 0-IA lung adenocarcinoma which appeared as subsolid nodules, from January 2012 to January 2013 including 137 pure ground glass nodules (pGGNs) and 74 part-solid nodules (PSNs). Pathological data was classified under the 2011 IASLC/ATS/ERS classification. Both quantitative and qualitative CT parameters were used to determine the tumor invasiveness between noninvasive adenocarcinomas and IPAs. There were 154 noninvasive adenocarcinomas and 57 IPAs. In pGGNs, CT size and area, one-dimensional mean CT value and bubble lucency were significantly different between noninvasive adenocarcinomas and IPAs on univariate analysis. Multivariate regression and ROC analysis revealed that CT size and one-dimensional mean CT value were predictive of noninvasive adenocarcinomas compared to IPAs. Optimal cutoff value was 13.60 mm (sensitivity, 75.0%; specificity, 99.6%), and -583.60 HU (sensitivity, 68.8%; specificity, 66.9%). In PSNs, there were significant differences in CT size and area, solid component area, solid proportion, one-dimensional mean and maximum CT value, three-dimensional (3D) mean CT value between noninvasive adenocarcinomas and IPAs on univariate analysis. Multivariate and ROC analysis showed that CT size and 3D mean CT value were significantly differentiators. Optimal cutoff value was 19.64 mm (sensitivity, 53.7%; specificity, 93.9%), -571.63 HU (sensitivity, 85.4%; specificity, 75.8%). For pGGNs, CT size and one-dimensional mean CT value are determinants for tumor invasiveness. For PSNs, tumor invasiveness can be predicted by CT size and 3D mean CT value.

Quantitative molecular analysis in mantle cell lymphoma.

PubMed

Brízová, H; Hilská, I; Mrhalová, M; Kodet, R

2011-07-01

A molecular analysis has three major roles in modern oncopathology--as an aid in the differential diagnosis, in molecular monitoring of diseases, and in estimation of the potential prognosis. In this report we review the application of the molecular analysis in a group of patients with mantle cell lymphoma (MCL). We demonstrate that detection of the cyclin D1 mRNA level is a molecular marker in 98% of patients with MCL. Cyclin D1 quantitative monitoring is specific and sensitive for the differential diagnosis and for the molecular monitoring of the disease in the bone marrow. Moreover, the dynamics of cyclin D1 in bone marrow reflects the disease development and it predicts the clinical course. We employed the molecular analysis for a precise quantitative detection of proliferation markers, Ki-67, topoisomerase IIalpha, and TPX2, that are described as effective prognostic factors. Using the molecular approach it is possible to measure the proliferation rate in a reproducible, standard way which is an essential prerequisite for using the proliferation activity as a routine clinical tool. Comparing with immunophenotyping we may conclude that the quantitative PCR-based analysis is a useful, reliable, rapid, reproducible, sensitive and specific method broadening our diagnostic tools in hematopathology. In comparison to interphase FISH in paraffin sections quantitative PCR is less technically demanding and less time-consuming and furthermore it is more sensitive in detecting small changes in the mRNA level. Moreover, quantitative PCR is the only technology which provides precise and reproducible quantitative information about the expression level. Therefore it may be used to demonstrate the decrease or increase of a tumor-specific marker in bone marrow in comparison with a previously aspirated specimen. Thus, it has a powerful potential to monitor the course of the disease in correlation with clinical data.

A quantitative microscopic approach to predict local recurrence based on in vivo intraoperative imaging of sarcoma tumor margins

PubMed Central

Mueller, Jenna L.; Fu, Henry L.; Mito, Jeffrey K.; Whitley, Melodi J.; Chitalia, Rhea; Erkanli, Alaattin; Dodd, Leslie; Cardona, Diana M.; Geradts, Joseph; Willett, Rebecca M.; Kirsch, David G.; Ramanujam, Nimmi

2015-01-01

The goal of resection of soft tissue sarcomas located in the extremity is to preserve limb function while completely excising the tumor with a margin of normal tissue. With surgery alone, one-third of patients with soft tissue sarcoma of the extremity will have local recurrence due to microscopic residual disease in the tumor bed. Currently, a limited number of intraoperative pathology-based techniques are used to assess margin status; however, few have been widely adopted due to sampling error and time constraints. To aid in intraoperative diagnosis, we developed a quantitative optical microscopy toolbox, which includes acriflavine staining, fluorescence microscopy, and analytic techniques called sparse component analysis and circle transform to yield quantitative diagnosis of tumor margins. A series of variables were quantified from images of resected primary sarcomas and used to optimize a multivariate model. The sensitivity and specificity for differentiating positive from negative ex vivo resected tumor margins was 82% and 75%. The utility of this approach was tested by imaging the in vivo tumor cavities from 34 mice after resection of a sarcoma with local recurrence as a bench mark. When applied prospectively to images from the tumor cavity, the sensitivity and specificity for differentiating local recurrence was 78% and 82%. For comparison, if pathology was used to predict local recurrence in this data set, it would achieve a sensitivity of 29% and a specificity of 71%. These results indicate a robust approach for detecting microscopic residual disease, which is an effective predictor of local recurrence. PMID:25994353

Use of the MagNA Pure LC Automated Nucleic Acid Extraction System followed by Real-Time Reverse Transcription-PCR for Ultrasensitive Quantitation of Hepatitis C Virus RNA

PubMed Central

Cook, Linda; Ng, Ka-Wing; Bagabag, Arthur; Corey, Lawrence; Jerome, Keith R.

2004-01-01

Hepatitis C virus (HCV) infection is an increasing health problem worldwide. Quantitative assays for HCV viral load are valuable in predicting response to therapy and for following treatment efficacy. Unfortunately, most quantitative tests for HCV RNA are limited by poor sensitivity. We have developed a convenient, highly sensitive real-time reverse transcription-PCR assay for HCV RNA. The assay amplifies a portion of the 5′ untranslated region of HCV, which is then quantitated using the TaqMan 7700 detection system. Extraction of viral RNA for our assay is fully automated with the MagNA Pure LC extraction system (Roche). Our assay has a 100% detection rate for samples containing 50 IU of HCV RNA/ml and is linear up to viral loads of at least 109 IU/ml. The assay detects genotypes 1a, 2a, and 3a with equal efficiency. Quantitative results by our assay correlate well with HCV viral load as determined by the Bayer VERSANT HCV RNA 3.0 bDNA assay. In clinical use, our assay is highly reproducible, with high and low control specimens showing a coefficient of variation for the logarithmic result of 2.8 and 7.0%, respectively. The combination of reproducibility, extreme sensitivity, and ease of performance makes this assay an attractive option for routine HCV viral load testing. PMID:15365000

Characterizing crown fuel distribution for conifers in the interior western United States

Treesearch

Seth Ex; Frederick W. Smith; Tara Keyser

2015-01-01

Canopy fire hazard evaluation is essential for prioritizing fuel treatments and for assessing potential risk to firefighters during suppression activities. Fire hazard is usually expressed as predicted potential fire behavior, which is sensitive to the methodology used to quantitatively describe fuel profiles: methodologies that assume that fuel is distributed...

Nervous System Sensitization as a Predictor of Outcome in the Treatment of Peripheral Musculoskeletal Conditions: A Systematic Review.

PubMed

O'Leary, Helen; Smart, Keith M; Moloney, Niamh A; Doody, Catherine M

2017-02-01

Research suggests that peripheral and central nervous system sensitization can contribute to the overall pain experience in peripheral musculoskeletal (MSK) conditions. It is unclear, however, whether sensitization of the nervous system results in poorer outcomes following the treatment. This systematic review investigated whether nervous system sensitization in peripheral MSK conditions predicts poorer clinical outcomes in response to a surgical or conservative intervention. Four electronic databases were searched to identify the relevant studies. Eligible studies had a prospective design, with a follow-up assessing the outcome in terms of pain or disability. Studies that used baseline indices of nervous system sensitization were included, such as quantitative sensory testing (QST) or questionnaires that measured centrally mediated symptoms. Thirteen studies met the inclusion criteria, of which six were at a high risk of bias. The peripheral MSK conditions investigated were knee and hip osteoarthritis, shoulder pain, and elbow tendinopathy. QST parameters indicative of sensitization (lower electrical pain thresholds, cold hyperalgesia, enhanced temporal summation, lower punctate sharpness thresholds) were associated with negative outcome (more pain or disability) in 5 small exploratory studies. Larger studies that accounted for multiple confounders in design and analysis did not support a predictive relationship between QST parameters and outcome. Two studies used self-report measures to capture comorbid centrally mediated symptoms, and found higher questionnaire scores were independently predictive of more persistent pain following a total joint arthroplasty. This systematic review found insufficient evidence to support an independent predictive relationship between QST measures of nervous system sensitization and treatment outcome. Self-report measures demonstrated better predictive ability. Further high-quality prognostic research is warranted. © 2016 World Institute of Pain.

Comparison of Urine Albumin-to-Creatinine Ratio (ACR) Between ACR Strip Test and Quantitative Test in Prediabetes and Diabetes

PubMed Central

Cho, Seon; Kim, Suyoung; Cho, Han-Ik

2017-01-01

Background Albuminuria is generally known as a sensitive marker of renal and cardiovascular dysfunction. It can be used to help predict the occurrence of nephropathy and cardiovascular disorders in diabetes. Individuals with prediabetes have a tendency to develop macrovascular and microvascular pathology, resulting in an increased risk of retinopathy, cardiovascular diseases, and chronic renal diseases. We evaluated the clinical value of a strip test for measuring the urinary albumin-to-creatinine ratio (ACR) in prediabetes and diabetes. Methods Spot urine samples were obtained from 226 prediabetic and 275 diabetic subjects during regular health checkups. Urinary ACR was measured by using strip and laboratory quantitative tests. Results The positive rates of albuminuria measured by using the ACR strip test were 15.5% (microalbuminuria, 14.6%; macroalbuminuria, 0.9%) and 30.5% (microalbuminuria, 25.1%; macroalbuminuria, 5.5%) in prediabetes and diabetes, respectively. In the prediabetic population, the sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy of the ACR strip method were 92.0%, 94.0%, 65.7%, 99.0%, and 93.8%, respectively; the corresponding values in the diabetic population were 80.0%, 91.6%, 81.0%, 91.1%, and 88.0%, respectively. The median [interquartile range] ACR values in the strip tests for measurement ranges of <30, 30-300, and >300 mg/g were 9.4 [6.3-15.4], 46.9 [26.5-87.7], and 368.8 [296.2-575.2] mg/g, respectively, using the laboratory method. Conclusions The ACR strip test showed high sensitivity, specificity, and negative predictive value, suggesting that the test can be used to screen for albuminuria in cases of prediabetes and diabetes. PMID:27834062

A quantitative ELISA procedure for the measurement of membrane-bound platelet-associated IgG (PAIgG).

PubMed

Lynch, D M; Lynch, J M; Howe, S E

1985-03-01

A quantitative ELISA assay for the measurement of in vivo bound platelet-associated IgG (PAIgG) using intact patient platelets is presented. The assay requires quantitation and standardization of the number of platelets bound to microtiter plate wells and an absorbance curve using quantitated IgG standards. Platelet-bound IgG was measured using an F(ab')2 peroxidase labeled anti-human IgG and o-phenylenediamine dihydrochloride (OPD) as the substrate. Using this assay, PAIgG for normal individuals was 2.8 +/- 1.6 fg/platelet (mean +/- 1 SD; n = 30). Increased levels were found in 28 of 30 patients with clinical autoimmune thrombocytopenia (ATP) with a range of 7.0-80 fg/platelet. Normal PAIgG levels were found in 26 of 30 patients with nonimmune thrombocytopenia. In the sample population studied, the PAIgG assay showed a sensitivity of 93%, specificity of 90%, a positive predictive value of 0.90, and a negative predictive value of 0.93. The procedure is highly reproducible (CV = 6.8%) and useful in evaluating patients with suspected immune mediated thrombocytopenia.

Young children's core symbolic and nonsymbolic quantitative knowledge in the prediction of later mathematics achievement.

PubMed

Geary, David C; vanMarle, Kristy

2016-12-01

At the beginning of preschool (M = 46 months of age), 197 (94 boys) children were administered tasks that assessed a suite of nonsymbolic and symbolic quantitative competencies as well as their executive functions, verbal and nonverbal intelligence, preliteracy skills, and their parents' education level. The children's mathematics achievement was assessed at the end of preschool (M = 64 months). We used a series of Bayesian and standard regression analyses to winnow this broad set of competencies down to the core subset of quantitative skills that predict later mathematics achievement, controlling other factors. This knowledge included children's fluency in reciting the counting string, their understanding of the cardinal value of number words, and recognition of Arabic numerals, as well as their sensitivity to the relative quantity of 2 collections of objects. The results inform theoretical models of the foundations of children's early quantitative development and have practical implications for the design of early interventions for children at risk for poor long-term mathematics achievement. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Mechanistic applicability domain classification of a local lymph node assay dataset for skin sensitization.

PubMed

Roberts, David W; Patlewicz, Grace; Kern, Petra S; Gerberick, Frank; Kimber, Ian; Dearman, Rebecca J; Ryan, Cindy A; Basketter, David A; Aptula, Aynur O

2007-07-01

The goal of eliminating animal testing in the predictive identification of chemicals with the intrinsic ability to cause skin sensitization is an important target, the attainment of which has recently been brought into even sharper relief by the EU Cosmetics Directive and the requirements of the REACH legislation. Development of alternative methods requires that the chemicals used to evaluate and validate novel approaches comprise not only confirmed skin sensitizers and non-sensitizers but also substances that span the full chemical mechanistic spectrum associated with skin sensitization. To this end, a recently published database of more than 200 chemicals tested in the mouse local lymph node assay (LLNA) has been examined in relation to various chemical reaction mechanistic domains known to be associated with sensitization. It is demonstrated here that the dataset does cover the main reaction mechanistic domains. In addition, it is shown that assignment to a reaction mechanistic domain is a critical first step in a strategic approach to understanding, ultimately on a quantitative basis, how chemical properties influence the potency of skin sensitizing chemicals. This understanding is necessary if reliable non-animal approaches, including (quantitative) structure-activity relationships (Q)SARs, read-across, and experimental chemistry based models, are to be developed.

Intermittent Turbulence in the Stable Boundary Layer over Land. Part III: A Classification for Observations during CASES-99.

NASA Astrophysics Data System (ADS)

van de Wiel, B. J. H.; Moene, A. F.; Hartogensis, O. K.; de Bruin, H. A. R.; Holtslag, A. A. M.

2003-10-01

In this paper a classification of stable boundary layer regimes is presented based on observations of near-surface turbulence during the Cooperative Atmosphere-Surface Exchange Study-1999 (CASES-99). It is found that the different nights can be divided into three subclasses: a turbulent regime, an intermittent regime, and a radiative regime, which confirms the findings of two companion papers that use a simplified theoretical model (it is noted that its simpliflied structure limits the model generality to near-surface flows). The papers predict the occurrence of stable boundary layer regimes in terms of external forcing parameters such as the (effective) pressure gradient and radiative forcing. The classification in the present work supports these predictions and shows that the predictions are robust in a qualitative sense. As such, it is, for example, shown that intermittent turbulence is most likely to occur in clear-sky conditions with a moderately weak effective pressure gradient. The quantitative features of the theoretical classification are, however, rather sensitive to (often uncertain) local parameter estimations, such as the bulk heat conductance of the vegetation layer. This sensitivity limits the current applicability of the theoretical classification in a strict quantitative sense, apart from its conceptual value.

Highly sensitive image-derived indices of water-stressed plants using hyperspectral imaging in SWIR and histogram analysis

PubMed Central

Kim, David M.; Zhang, Hairong; Zhou, Haiying; Du, Tommy; Wu, Qian; Mockler, Todd C.; Berezin, Mikhail Y.

2015-01-01

The optical signature of leaves is an important monitoring and predictive parameter for a variety of biotic and abiotic stresses, including drought. Such signatures derived from spectroscopic measurements provide vegetation indices – a quantitative method for assessing plant health. However, the commonly used metrics suffer from low sensitivity. Relatively small changes in water content in moderately stressed plants demand high-contrast imaging to distinguish affected plants. We present a new approach in deriving sensitive indices using hyperspectral imaging in a short-wave infrared range from 800 nm to 1600 nm. Our method, based on high spectral resolution (1.56 nm) instrumentation and image processing algorithms (quantitative histogram analysis), enables us to distinguish a moderate water stress equivalent of 20% relative water content (RWC). The identified image-derived indices 15XX nm/14XX nm (i.e. 1529 nm/1416 nm) were superior to common vegetation indices, such as WBI, MSI, and NDWI, with significantly better sensitivity, enabling early diagnostics of plant health. PMID:26531782

In silico designing of power conversion efficient organic lead dyes for solar cells using todays innovative approaches to assure renewable energy for future

NASA Astrophysics Data System (ADS)

Kar, Supratik; Roy, Juganta K.; Leszczynski, Jerzy

2017-06-01

Advances in solar cell technology require designing of new organic dye sensitizers for dye-sensitized solar cells with high power conversion efficiency to circumvent the disadvantages of silicon-based solar cells. In silico studies including quantitative structure-property relationship analysis combined with quantum chemical analysis were employed to understand the primary electron transfer mechanism and photo-physical properties of 273 arylamine organic dyes from 11 diverse chemical families explicit to iodine electrolyte. The direct quantitative structure-property relationship models enable identification of the essential electronic and structural attributes necessary for quantifying the molecular prerequisites of 11 classes of arylamine organic dyes, responsible for high power conversion efficiency of dye-sensitized solar cells. Tetrahydroquinoline, N,N'-dialkylaniline and indoline have been least explored classes under arylamine organic dyes for dye-sensitized solar cells. Therefore, the identified properties from the corresponding quantitative structure-property relationship models of the mentioned classes were employed in designing of "lead dyes". Followed by, a series of electrochemical and photo-physical parameters were computed for designed dyes to check the required variables for electron flow of dye-sensitized solar cells. The combined computational techniques yielded seven promising lead dyes each for all three chemical classes considered. Significant (130, 183, and 46%) increment in predicted %power conversion efficiency was observed comparing with the existing dye with highest experimental %power conversion efficiency value for tetrahydroquinoline, N,N'-dialkylaniline and indoline, respectively maintaining required electrochemical parameters.

Evaluation of dried blood spot as an alternative sample collection method for hepatitis C virus RNA quantitation and genotyping using a commercial system.

PubMed

Mahajan, Supriya; Choudhary, Manish Chandra; Kumar, Guresh; Gupta, Ekta

2018-06-01

Dried blood spot (DBS) is a minimally invasive sampling method suitable for sample collection, storage and transportation in resource limited areas. Aim of this study was to compare the diagnostic utility of DBS with plasma sample for HCV RNA quantitation and genotyping using commercial systems. Plasma and DBS card spotted samples were collected from 95 HCV seropositive patients. Both types of samples were subjected to HCV RNA by real-time PCR (Abbott m2000rt, USA). Genotyping was performed using Abbott HCV genotype II kit (Abbott diagnostics, USA) in samples with viral load > 3 log 10  IU/ml. In both plasma and DBS, 14 (14.7%) samples were negative and 81 (85.3%) were positive for HCV RNA. Median viral load in plasma (3.78; range 0-7.43) log 10  IU/ml was comparable to DBS (3.93; range 0-7.24) log 10  IU/ml. DBS demonstrated sensitivity and specificity of 97.5 and 85.7% respectively, with positive predictive value (PPV) of 97.5% and negative predictive value (NPV) of 85.7%. DBS showed good correlation (r 2  = 0.866) and agreement (93.5%) with plasma. Genotyping in 20 patients showed 100% concordance between DBS and plasma samples. DBS showed good sensitivity and specificity as a sampling method for HCV RNA quantitation and genotyping.

A Quantitative Chemotherapy Genetic Interaction Map Reveals Factors Associated with PARP Inhibitor Resistance.

PubMed

Hu, Hsien-Ming; Zhao, Xin; Kaushik, Swati; Robillard, Lilliane; Barthelet, Antoine; Lin, Kevin K; Shah, Khyati N; Simmons, Andy D; Raponi, Mitch; Harding, Thomas C; Bandyopadhyay, Sourav

2018-04-17

Chemotherapy is used to treat most cancer patients, yet our understanding of factors that dictate response and resistance to such drugs remains limited. We report the generation of a quantitative chemical-genetic interaction map in human mammary epithelial cells charting the impact of the knockdown of 625 genes related to cancer and DNA repair on sensitivity to 29 drugs, covering all classes of chemotherapy. This quantitative map is predictive of interactions maintained in other cell lines, identifies DNA-repair factors, predicts cancer cell line responses to therapy, and prioritizes synergistic drug combinations. We identify that ARID1A loss confers resistance to PARP inhibitors in cells and ovarian cancer patients and that loss of GPBP1 causes resistance to cisplatin and PARP inhibitors through the regulation of genes involved in homologous recombination. This map helps navigate patient genomic data and optimize chemotherapeutic regimens by delineating factors involved in the response to specific types of DNA damage. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Role of serum hepatitis B virus marker quantitation to differentiate natural history phases of HBV infection.

PubMed

Wang, Li; Zou, Zhi-Qiang; Wang, Kai; Yu, Ji-Guang; Liu, Xiang-Zhong

2016-01-01

The purpose of this study was to characterize roles of serum hepatitis B virus marker quantitation in differentiation of natural phases of HBV infection. A total of 184 chronic hepatitis B (CHB) patients were analyzed retrospectively. Patients were classified into four categories: immune tolerant phase (IT, n = 36), immune clearance phase (IC, n = 81), low-replicative phase (LR, n = 31), and HBeAg-negative hepatitis phase (ENH, n = 36), based on clinical, biochemical, serological, HBV DNA level and histological data. Hepatitis B surface antigen (HBsAg) quantitation in four phases were 4.7 ± 0.2, 3.8 ± 0.5, 2.5 ± 1.2 and 3.4 ± 0.4 log10 IU/mL, respectively. There were significant differences between IT and IC (p < 0.001) and between LR and ENH phases (p < 0.001). Quantitation of hepatitis B e antigen (HBeAg) in IT and IC phases are 1317.9 ± 332.9 and 673.4 ± 562.1 S/CO, respectively (p < 0.001). Hepatitis B core antibody (HBcAb) quantitation in the four groups were 9.48 ± 3.3, 11.7 ± 2.8, 11.2 ± 2.6 and 13.2 ± 2.9 S/CO, respectively. Area under receiver operating characteristic curve (AUCs) of HBsAg and HBeAg at cutoff values of 4.41 log10 IU/mL and 1118.96 S/CO for differentiation of IT and IC phases are 0.984 and 0.828, with sensitivity 94.4 and 85.2 %, specificity 98.7 and 75 %, respectively. AUCs of HBsAg and HBcAb at cutoff values of 3.4 log10 IU/mL and 10.5 S/CO for differentiation of LR and ENT phases are 0.796 and 0.705, with sensitivity 58.1 and 85.7 %, and specificity 94.4 and 46.2 %, respectively. HBsAg quantitation has high predictive value and HBeAg quantitation has moderate predictive value for discriminating IT and IC phase. HBsAg and HBcAb quantitations have moderate predictive values for differentiation of LR and ENH phase.

Quantitative somatosensory testing of the penis: optimizing the clinical neurological examination.

PubMed

Bleustein, Clifford B; Eckholdt, Haftan; Arezzo, Joseph C; Melman, Arnold

2003-06-01

Quantitative somatosensory testing, including vibration, pressure, spatial perception and thermal thresholds of the penis, has demonstrated neuropathy in patients with a history of erectile dysfunction of all etiologies. We evaluated which measurement of neurological function of the penis was best at predicting erectile dysfunction and examined the impact of location on the penis for quantitative somatosensory testing measurements. A total of 107 patients were evaluated. All patients were required to complete the erectile function domain of the International Index of Erectile Function (IIEF) questionnaire, of whom 24 had no complaints of erectile dysfunction and scored within the "normal" range on the IIEF. Patients were subsequently tested on ventral middle penile shaft, proximal dorsal midline penile shaft and glans penis (with foreskin retracted) for vibration, pressure, spatial perception, and warm and cold thermal thresholds. Mixed models repeated measures analysis of variance controlling for age, diabetes and hypertension revealed that method of measurement (quantitative somatosensory testing) was predictive of IIEF score (F = 209, df = 4,1315, p <0.001), while site of measurement on the penis was not. To determine the best method of measurement, we used hierarchical regression, which revealed that warm temperature was the best predictor of erectile dysfunction with pseudo R(2) = 0.19, p <0.0007. There was no significant improvement in predicting erectile dysfunction when another test was added. Using 37C and greater as the warm thermal threshold yielded a sensitivity of 88.5%, specificity 70.0% and positive predictive value 85.5%. Quantitative somatosensory testing using warm thermal threshold measurements taken at the glans penis can be used alone to assess the neurological status of the penis. Warm thermal thresholds alone offer a quick, noninvasive accurate method of evaluating penile neuropathy in an office setting.

Preoperative Cerebral Oxygen Extraction Fraction Imaging Generated from 7T MR Quantitative Susceptibility Mapping Predicts Development of Cerebral Hyperperfusion following Carotid Endarterectomy.

PubMed

Nomura, J-I; Uwano, I; Sasaki, M; Kudo, K; Yamashita, F; Ito, K; Fujiwara, S; Kobayashi, M; Ogasawara, K

2017-12-01

Preoperative hemodynamic impairment in the affected cerebral hemisphere is associated with the development of cerebral hyperperfusion following carotid endarterectomy. Cerebral oxygen extraction fraction images generated from 7T MR quantitative susceptibility mapping correlate with oxygen extraction fraction images on positron-emission tomography. The present study aimed to determine whether preoperative oxygen extraction fraction imaging generated from 7T MR quantitative susceptibility mapping could identify patients at risk for cerebral hyperperfusion following carotid endarterectomy. Seventy-seven patients with unilateral internal carotid artery stenosis (≥70%) underwent preoperative 3D T2*-weighted imaging using a multiple dipole-inversion algorithm with a 7T MR imager. Quantitative susceptibility mapping images were then obtained, and oxygen extraction fraction maps were generated. Quantitative brain perfusion single-photon emission CT was also performed before and immediately after carotid endarterectomy. ROIs were automatically placed in the bilateral middle cerebral artery territories in all images using a 3D stereotactic ROI template, and affected-to-contralateral ratios in the ROIs were calculated on quantitative susceptibility mapping-oxygen extraction fraction images. Ten patients (13%) showed post-carotid endarterectomy hyperperfusion (cerebral blood flow increases of ≥100% compared with preoperative values in the ROIs on brain perfusion SPECT). Multivariate analysis showed that a high quantitative susceptibility mapping-oxygen extraction fraction ratio was significantly associated with the development of post-carotid endarterectomy hyperperfusion (95% confidence interval, 33.5-249.7; P = .002). Sensitivity, specificity, and positive- and negative-predictive values of the quantitative susceptibility mapping-oxygen extraction fraction ratio for the prediction of the development of post-carotid endarterectomy hyperperfusion were 90%, 84%, 45%, and 98%, respectively. Preoperative oxygen extraction fraction imaging generated from 7T MR quantitative susceptibility mapping identifies patients at risk for cerebral hyperperfusion following carotid endarterectomy. © 2017 by American Journal of Neuroradiology.

Diagnostic accuracy of shear wave elastography for prediction of breast malignancy in patients with pathological nipple discharge

PubMed Central

Guo, Xiaobo; Liu, Ying; Li, Wanhu

2016-01-01

Objectives Pathological nipple discharge (PND) may indicate malignant breast lesions. As the role of shear wave elastography (SWE) in predicting these malignant lesions has not yet been evaluated, we aim to evaluate the diagnostic value of SWE for this condition. Design Prospective diagnostic accuracy study comparing a combination of qualitative and quantitative measurements of SWE (index test) to a ductoscopy and microdochectomy for histological diagnosis (reference test). Setting Fuzhou General Hospital of Nanjing military command. Participants A total of 379 patients with PND were finally included from January, 2011 to March 2014, after we screened 1084 possible candidates. All participants were evaluated through SWE, with qualitative parameters generated by Virtual Touch tissue imaging (VTI) and quantitative parameters generated by Virtual Touch tissue quantification (VTQ). All the patients were consented to receive a ductoscopy and microdochectomy for histological diagnosis, and the results were set as a reference test. Outcome measures Sensitivity and specificity of the combined VTI and VTQ of the SWE for detection of malignancy in patients with PND. Results The 379 participants presented with 404 lesions. The results of pathological examination showed that 326 (80.7%) of the 404 lesions were benign and the other 78 (19.3%) were malignant. An area under the curve of elasticity score, VTQm and VTQc, were 0.872, 0.825 and 0.857, respectively, with the corresponding cut-off point as 2.50, 2.860 m/s and 3.015 m/s, respectively. After a combination of these measurements, the sensitivity, specificity, and positive and negative predictive value (PPV and NPV), were 89.7%, 72.1%, 43.5% and 96.7%, respectively. The sensitivity analysis showed 82% of the sensitivity and 96.8% of the specificity, in which patients with no pathological findings in ductoscopy were excluded. Conclusions Ultrasonographic elastography is sensitive for patients with PND and could be used as a triage test before ductoscopy examination. Studies for further improvement of diagnostic sensitivity are warranted. PMID:26801462

Validation of simple indexes to assess insulin sensitivity during pregnancy in Wistar and Sprague-Dawley rats.

PubMed

Cacho, J; Sevillano, J; de Castro, J; Herrera, E; Ramos, M P

2008-11-01

Insulin resistance plays a role in the pathogenesis of diabetes, including gestational diabetes. The glucose clamp is considered the gold standard for determining in vivo insulin sensitivity, both in human and in animal models. However, the clamp is laborious, time consuming and, in animals, requires anesthesia and collection of multiple blood samples. In human studies, a number of simple indexes, derived from fasting glucose and insulin levels, have been obtained and validated against the glucose clamp. However, these indexes have not been validated in rats and their accuracy in predicting altered insulin sensitivity remains to be established. In the present study, we have evaluated whether indirect estimates based on fasting glucose and insulin levels are valid predictors of insulin sensitivity in nonpregnant and 20-day-pregnant Wistar and Sprague-Dawley rats. We have analyzed the homeostasis model assessment of insulin resistance (HOMA-IR), the quantitative insulin sensitivity check index (QUICKI), and the fasting glucose-to-insulin ratio (FGIR) by comparing them with the insulin sensitivity (SI(Clamp)) values obtained during the hyperinsulinemic-isoglycemic clamp. We have performed a calibration analysis to evaluate the ability of these indexes to accurately predict insulin sensitivity as determined by the reference glucose clamp. Finally, to assess the reliability of these indexes for the identification of animals with impaired insulin sensitivity, performance of the indexes was analyzed by receiver operating characteristic (ROC) curves in Wistar and Sprague-Dawley rats. We found that HOMA-IR, QUICKI, and FGIR correlated significantly with SI(Clamp), exhibited good sensitivity and specificity, accurately predicted SI(Clamp), and yielded lower insulin sensitivity in pregnant than in nonpregnant rats. Together, our data demonstrate that these indexes provide an easy and accurate measure of insulin sensitivity during pregnancy in the rat.

Quantitative risk assessment for skin sensitization: Success or failure?

PubMed

Kimber, Ian; Gerberick, G Frank; Basketter, David A

2017-02-01

Skin sensitization is unique in the world of toxicology. There is a combination of reliable, validated predictive test methods for identification of skin sensitizing chemicals, a clearly documented and transparent approach to risk assessment, and effective feedback from dermatology clinics around the world delivering evidence of the success or failure of the hazard identification/risk assessment/management process. Recent epidemics of contact allergy, particularly to preservatives, have raised questions of whether the safety/risk assessment process is working in an optimal manner (or indeed is working at all!). This review has as its focus skin sensitization quantitative risk assessment (QRA). The core toxicological principles of QRA are reviewed, and evidence of use and misuse examined. What becomes clear is that skin sensitization QRA will only function adequately if two essential criteria are met. The first is that QRA is applied rigourously, and the second is that potential exposure to the sensitizing substance is assessed adequately. This conclusion will come as no surprise to any toxicologist who appreciates the basic premise that "risk = hazard x exposure". Accordingly, use of skin sensitization QRA is encouraged, not least because the essential feedback from dermatology clinics can be used as a tool to refine QRA in situations where this risk assessment tool has not been properly used. Copyright © 2016 Elsevier Inc. All rights reserved.

Benefit of Hepatitis C Virus Core Antigen Assay in Prediction of Therapeutic Response to Interferon and Ribavirin Combination Therapy

PubMed Central

Takahashi, Masahiko; Saito, Hidetsugu; Higashimoto, Makiko; Atsukawa, Kazuhiro; Ishii, Hiromasa

2005-01-01

A highly sensitive second-generation hepatitis C virus (HCV) core antigen assay has recently been developed. We compared viral disappearance and first-phase kinetics between commercially available core antigen (Ag) assays, Lumipulse Ortho HCV Ag (Lumipulse-Ag), and a quantitative HCV RNA PCR assay, Cobas Amplicor HCV Monitor test, version 2 (Amplicor M), to estimate the predictive benefit of a sustained viral response (SVR) and non-SVR in 44 genotype 1b patients treated with interferon (IFN) and ribavirin. HCV core Ag negativity could predict SVR on day 1 (sensitivity = 100%, specificity = 85.0%, accuracy = 86.4%), whereas RNA negativity could predict SVR on day 7 (sensitivity = 100%, specificity = 87.2%, accuracy = 88.6%). None of the patients who had detectable serum core Ag or RNA on day 14 achieved SVR (specificity = 100%). The predictive accuracy on day 14 was higher by RNA negativity (93.2%) than that by core Ag negativity (75.0%). The combined predictive criterion of both viral load decline during the first 24 h and basal viral load was also predictive for SVR; the sensitivities of Lumipulse-Ag and Amplicor-M were 45.5 and 47.6%, respectively, and the specificity was 100%. Amplicor-M had better predictive accuracy than Lumipulse-Ag in 2-week disappearance tests because it had better sensitivity. On the other hand, estimates of kinetic parameters were similar regardless of the detection method. Although the correlations between Lumipulse-Ag and Amplicor-M were good both before and 24 h after IFN administration, HCV core Ag seemed to be relatively lower 24 h after IFN administration than before administration. Lumipulse-Ag seems to be useful for detecting the HCV concentration during IFN therapy; however, we still need to understand the characteristics of the assay. PMID:15634970

Ga-67 uptake in the lung in sarcoidosis

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

Johnson, D.G.; Johnson, S.M.; Harris, C.C.

1984-02-01

Images were obtained with Ga-67 and bronchopulmonary lavage performed in 21 patients with sarcoidosis (31 studies). The Ga-67 index, a semiquantitative criterion, was compared to a quantitative computer index based on lung:liver activity ratios; accuracy in predicting active alveolitis (defined by lavage lymphocyte counts) was assessed and differences between 24- and 48-hour studies examined. Computer activity ratios correlated well with the Ga-67 index, which had a sensitivity of 64%, specificity of 71%, 82%, and 77%, respectively, for the computer scores. Scores at 24 and 48 hours were similar. These results suggest that (a) Ga-67 scanning is useful in staging activitymore » in pulmonary sarcoidosis, (b) quantitative computer scores are accurate in predicting disease activity, and (c) scanning can be performed 24 or 48 hours after injection.« less

Diagnostic effectiveness of quantitative [18F]flutemetamol PET imaging for detection of fibrillar amyloid β using cortical biopsy histopathology as the standard of truth in subjects with idiopathic normal pressure hydrocephalus

PubMed Central

2014-01-01

Introduction PET imaging of amyloid-β (Aβ) in vivo holds promise for aiding in earlier diagnosis and intervention in Alzheimer’s disease (AD) and mild cognitive impairment. AD-like Aβ pathology is a common comorbidity in patients with idiopathic normal pressure hydrocephalus (iNPH). Fifty patients with iNPH needing ventriculo-peritoneal shunting or intracranial pressure monitoring underwent [18F]flutemetamol PET before (N = 28) or after (N = 22) surgery. Cortical uptake of [18F]flutemetamol was assessed visually by blinded reviewers, and also quantitatively via standard uptake value ratio (SUVR) in specific neocortical regions in relation to either cerebellum or pons reference region: the cerebral cortex of (prospective studies) or surrounding (retrospective studies) the biopsy site, the contralateral homolog, and a calculated composite brain measure. Aβ pathology in the biopsy specimen (standard of truth [SoT]) was measured using Bielschowsky silver and thioflavin S plaque scores, percentage area of grey matter positive for monoclonal antibody to Aβ (4G8), and overall pathology impression. We set out to find (1) which pair(s) of PET SUVR and pathology SoT endpoints matched best, (2) whether quantitative measures of [18F]flutemetamol PET were better for predicting the pathology outcome than blinded image examination (BIE), and (3) whether there was a better match between PET image findings in retrospective vs. prospective studies. Results Of the 24 possible endpoint/SoT combinations, the one with composite-cerebellum SUVR and SoT based on overall pathology had the highest Youden index (1.000), receiver operating characteristic area under the curve (1.000), sensitivity (1.000), specificity (1.000), and sum of sensitivity and specificity for the pooled data as well as for the retrospective and prospective studies separately (2.00, for all 3). The BIE sum of sensitivity and specificity, comparable to that for quantitation, was highest using Bielschowsky silver as SoT for all SUVRs (ipsilateral, contralateral, and composite, for both reference regions). The composite SUVR had a 100% positive predictive value (both reference regions) for the overall pathology diagnosis. All SUVRs had a 100% negative predictive value for the Bielschowsky silver result. Conclusion Bielschowsky silver stain and overall pathology judgment showed the strongest associations with imaging results. PMID:24755237

Comparison between Surrogate Indexes of Insulin Sensitivity/Resistance and Hyperinsulinemic Euglycemic Glucose Clamps in Rhesus Monkeys

PubMed Central

Lee, Ho-Won; Muniyappa, Ranganath; Yan, Xu; Yue, Lilly Q.; Linden, Ellen H.; Chen, Hui; Hansen, Barbara C.

2011-01-01

The euglycemic glucose clamp is the reference method for assessing insulin sensitivity in humans and animals. However, clamps are ill-suited for large studies because of extensive requirements for cost, time, labor, and technical expertise. Simple surrogate indexes of insulin sensitivity/resistance including quantitative insulin-sensitivity check index (QUICKI) and homeostasis model assessment (HOMA) have been developed and validated in humans. However, validation studies of QUICKI and HOMA in both rats and mice suggest that differences in metabolic physiology between rodents and humans limit their value in rodents. Rhesus monkeys are a species more similar to humans than rodents. Therefore, in the present study, we evaluated data from 199 glucose clamp studies obtained from a large cohort of 86 monkeys with a broad range of insulin sensitivity. Data were used to evaluate simple surrogate indexes of insulin sensitivity/resistance (QUICKI, HOMA, Log HOMA, 1/HOMA, and 1/Fasting insulin) with respect to linear regression, predictive accuracy using a calibration model, and diagnostic performance using receiver operating characteristic. Most surrogates had modest linear correlations with SIClamp (r ≈ 0.4–0.64) with comparable correlation coefficients. Predictive accuracy determined by calibration model analysis demonstrated better predictive accuracy of QUICKI than HOMA and Log HOMA. Receiver operating characteristic analysis showed equivalent sensitivity and specificity of most surrogate indexes to detect insulin resistance. Thus, unlike in rodents but similar to humans, surrogate indexes of insulin sensitivity/resistance including QUICKI and log HOMA may be reasonable to use in large studies of rhesus monkeys where it may be impractical to conduct glucose clamp studies. PMID:21209021

Predicting Response to Neoadjuvant Chemotherapy with PET Imaging Using Convolutional Neural Networks

PubMed Central

Ypsilantis, Petros-Pavlos; Siddique, Musib; Sohn, Hyon-Mok; Davies, Andrew; Cook, Gary; Goh, Vicky; Montana, Giovanni

2015-01-01

Imaging of cancer with 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) has become a standard component of diagnosis and staging in oncology, and is becoming more important as a quantitative monitor of individual response to therapy. In this article we investigate the challenging problem of predicting a patient’s response to neoadjuvant chemotherapy from a single 18F-FDG PET scan taken prior to treatment. We take a “radiomics” approach whereby a large amount of quantitative features is automatically extracted from pretherapy PET images in order to build a comprehensive quantification of the tumor phenotype. While the dominant methodology relies on hand-crafted texture features, we explore the potential of automatically learning low- to high-level features directly from PET scans. We report on a study that compares the performance of two competing radiomics strategies: an approach based on state-of-the-art statistical classifiers using over 100 quantitative imaging descriptors, including texture features as well as standardized uptake values, and a convolutional neural network, 3S-CNN, trained directly from PET scans by taking sets of adjacent intra-tumor slices. Our experimental results, based on a sample of 107 patients with esophageal cancer, provide initial evidence that convolutional neural networks have the potential to extract PET imaging representations that are highly predictive of response to therapy. On this dataset, 3S-CNN achieves an average 80.7% sensitivity and 81.6% specificity in predicting non-responders, and outperforms other competing predictive models. PMID:26355298

Prediction of gestational diabetes mellitus in the first trimester: comparison of C-reactive protein, fasting plasma glucose, insulin and insulin sensitivity indices.

PubMed

Ozgu-Erdinc, A Seval; Yilmaz, Saynur; Yeral, M Ilkin; Seckin, K Doga; Erkaya, Salim; Danisman, A Nuri

2015-11-01

To develop a predictive index based on high sensitivity C-reactive protein (hs-CRP), fasting plasma glucose (FPG) and fasting plasma insulin (FPI) measurements for early diagnosis of gestational diabetes mellitus (GDM). Healthy pregnant women who were screened for GDM during their first antenatal visit were included in this retrospective cohort study. FPG, FPI and serum hs-CRP concentrations were measured between weeks 11 and 14. A two-step glucose challenge test was carried out between gestational weeks 24 and 28. Fasting glucose/insulin ratio (FIGR), Homeostatic Model Assessment Insulin Resistance (HOMA-IR), HOMA-β indices and Quantitative Insulin Sensitivity Check Index (QUICKI) were used to estimate insulin sensitivity and β-cell function. Of the 450 women who were eligible for the study, 49 (11.2%) were diagnosed with GDM at weeks 24-28. The median FPG and hs-CRP levels were higher in the GDM diagnosed women compared to the others. Comparison of accuracy measures resulted in the highest specificity (87.2%; 95% CI 83.5-90.1) and diagnostic odds ratio (3.9; 95% CI 2.1-7.6) for hs-CRP. FPG and hs-CRP in the first trimester are correlated with later development of GDM in the pregnancy. In our study, FPG provided a better sensitivity while hs-CRP exhibited a better specificity for prediction of GDM.

The Quantitative Science of Evaluating Imaging Evidence.

PubMed

Genders, Tessa S S; Ferket, Bart S; Hunink, M G Myriam

2017-03-01

Cardiovascular diagnostic imaging tests are increasingly used in everyday clinical practice, but are often imperfect, just like any other diagnostic test. The performance of a cardiovascular diagnostic imaging test is usually expressed in terms of sensitivity and specificity compared with the reference standard (gold standard) for diagnosing the disease. However, evidence-based application of a diagnostic test also requires knowledge about the pre-test probability of disease, the benefit of making a correct diagnosis, the harm caused by false-positive imaging test results, and potential adverse effects of performing the test itself. To assist in clinical decision making regarding appropriate use of cardiovascular diagnostic imaging tests, we reviewed quantitative concepts related to diagnostic performance (e.g., sensitivity, specificity, predictive values, likelihood ratios), as well as possible biases and solutions in diagnostic performance studies, Bayesian principles, and the threshold approach to decision making. Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Novel Uses of In Vitro Data to Develop Quantitative Biological Activity Relationship Models for in Vivo Carcinogenicity Prediction.

PubMed

Pradeep, Prachi; Povinelli, Richard J; Merrill, Stephen J; Bozdag, Serdar; Sem, Daniel S

2015-04-01

The availability of large in vitro datasets enables better insight into the mode of action of chemicals and better identification of potential mechanism(s) of toxicity. Several studies have shown that not all in vitro assays can contribute as equal predictors of in vivo carcinogenicity for development of hybrid Quantitative Structure Activity Relationship (QSAR) models. We propose two novel approaches for the use of mechanistically relevant in vitro assay data in the identification of relevant biological descriptors and development of Quantitative Biological Activity Relationship (QBAR) models for carcinogenicity prediction. We demonstrate that in vitro assay data can be used to develop QBAR models for in vivo carcinogenicity prediction via two case studies corroborated with firm scientific rationale. The case studies demonstrate the similarities between QBAR and QSAR modeling in: (i) the selection of relevant descriptors to be used in the machine learning algorithm, and (ii) the development of a computational model that maps chemical or biological descriptors to a toxic endpoint. The results of both the case studies show: (i) improved accuracy and sensitivity which is especially desirable under regulatory requirements, and (ii) overall adherence with the OECD/REACH guidelines. Such mechanism based models can be used along with QSAR models for prediction of mechanistically complex toxic endpoints. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Novel images extraction model using improved delay vector variance feature extraction and multi-kernel neural network for EEG detection and prediction.

PubMed

Ge, Jing; Zhang, Guoping

2015-01-01

Advanced intelligent methodologies could help detect and predict diseases from the EEG signals in cases the manual analysis is inefficient available, for instance, the epileptic seizures detection and prediction. This is because the diversity and the evolution of the epileptic seizures make it very difficult in detecting and identifying the undergoing disease. Fortunately, the determinism and nonlinearity in a time series could characterize the state changes. Literature review indicates that the Delay Vector Variance (DVV) could examine the nonlinearity to gain insight into the EEG signals but very limited work has been done to address the quantitative DVV approach. Hence, the outcomes of the quantitative DVV should be evaluated to detect the epileptic seizures. To develop a new epileptic seizure detection method based on quantitative DVV. This new epileptic seizure detection method employed an improved delay vector variance (IDVV) to extract the nonlinearity value as a distinct feature. Then a multi-kernel functions strategy was proposed in the extreme learning machine (ELM) network to provide precise disease detection and prediction. The nonlinearity is more sensitive than the energy and entropy. 87.5% overall accuracy of recognition and 75.0% overall accuracy of forecasting were achieved. The proposed IDVV and multi-kernel ELM based method was feasible and effective for epileptic EEG detection. Hence, the newly proposed method has importance for practical applications.

Development of a quantitative intracranial vascular features extraction tool on 3D MRA using semiautomated open-curve active contour vessel tracing.

PubMed

Chen, Li; Mossa-Basha, Mahmud; Balu, Niranjan; Canton, Gador; Sun, Jie; Pimentel, Kristi; Hatsukami, Thomas S; Hwang, Jenq-Neng; Yuan, Chun

2018-06-01

To develop a quantitative intracranial artery measurement technique to extract comprehensive artery features from time-of-flight MR angiography (MRA). By semiautomatically tracing arteries based on an open-curve active contour model in a graphical user interface, 12 basic morphometric features and 16 basic intensity features for each artery were identified. Arteries were then classified as one of 24 types using prediction from a probability model. Based on the anatomical structures, features were integrated within 34 vascular groups for regional features of vascular trees. Eight 3D MRA acquisitions with intracranial atherosclerosis were assessed to validate this technique. Arterial tracings were validated by an experienced neuroradiologist who checked agreement at bifurcation and stenosis locations. This technique achieved 94% sensitivity and 85% positive predictive values (PPV) for bifurcations, and 85% sensitivity and PPV for stenosis. Up to 1,456 features, such as length, volume, and averaged signal intensity for each artery, as well as vascular group in each of the MRA images, could be extracted to comprehensively reflect characteristics, distribution, and connectivity of arteries. Length for the M1 segment of the middle cerebral artery extracted by this technique was compared with reviewer-measured results, and the intraclass correlation coefficient was 0.97. A semiautomated quantitative method to trace, label, and measure intracranial arteries from 3D-MRA was developed and validated. This technique can be used to facilitate quantitative intracranial vascular research, such as studying cerebrovascular adaptation to aging and disease conditions. Magn Reson Med 79:3229-3238, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

The value of assessing pulmonary venous flow velocity for predicting severity of mitral regurgitation: A quantitative assessment integrating left ventricular function

NASA Technical Reports Server (NTRS)

Pu, M.; Griffin, B. P.; Vandervoort, P. M.; Stewart, W. J.; Fan, X.; Cosgrove, D. M.; Thomas, J. D.

1999-01-01

Although alteration in pulmonary venous flow has been reported to relate to mitral regurgitant severity, it is also known to vary with left ventricular (LV) systolic and diastolic dysfunction. There are few data relating pulmonary venous flow to quantitative indexes of mitral regurgitation (MR). The object of this study was to assess quantitatively the accuracy of pulmonary venous flow for predicting MR severity by using transesophageal echocardiographic measurement in patients with variable LV dysfunction. This study consisted of 73 patients undergoing heart surgery with mild to severe MR. Regurgitant orifice area (ROA), regurgitant stroke volume (RSV), and regurgitant fraction (RF) were obtained by quantitative transesophageal echocardiography and proximal isovelocity surface area. Both left and right upper pulmonary venous flow velocities were recorded and their patterns classified by the ratio of systolic to diastolic velocity: normal (>/=1), blunted (<1), and systolic reversal (<0). Twenty-three percent of patients had discordant patterns between the left and right veins. When the most abnormal patterns either in the left or right vein were used for analysis, the ratio of peak systolic to diastolic flow velocity was negatively correlated with ROA (r = -0.74, P <.001), RSV (r = -0.70, P <.001), and RF (r = -0.66, P <.001) calculated by the Doppler thermodilution method; values were r = -0.70, r = -0.67, and r = -0.57, respectively (all P <.001), for indexes calculated by the proximal isovelocity surface area method. The sensitivity, specificity, and predictive values of the reversed pulmonary venous flow pattern for detecting a large ROA (>0.3 cm(2)) were 69%, 98%, and 97%, respectively. The sensitivity, specificity, and predictive values of the normal pulmonary venous flow pattern for detecting a small ROA (<0.3 cm(2)) were 60%, 96%, and 94%, respectively. However, the blunted pattern had low sensitivity (22%), specificity (61%), and predictive values (30%) for detecting ROA of greater than 0.3 cm(2) with significant overlap with the reversed and normal patterns. Among patients with the blunted pattern, the correlation between the systolic to diastolic velocity ratio was worse in those with LV dysfunction (ejection fraction <50%, r = 0.23, P >.05) than in those with normal LV function (r = -0.57, P <.05). Stepwise linear regression analysis showed that the peak systolic to diastolic velocity ratio was independently correlated with RF (P <.001) and effective stroke volume (P <.01), with a multiple correlation coefficient of 0.71 (P <.001). In conclusion, reversed pulmonary venous flow in systole is a highly specific and reliable marker of moderately severe or severe MR with an ROA greater than 0.3 cm(2), whereas the normal pattern accurately predicts mild to moderate MR. Blunted pulmonary venous flow can be seen in all grades of MR with low predictive value for severity of MR, especially in the presence of LV dysfunction. The blunted pulmonary venous flow pattern must therefore be interpreted cautiously in clinical practice as a marker for severity of MR.

Comparison of quantitative and qualitative tests for glucose-6-phosphate dehydrogenase deficiency in the neonatal period.

PubMed

Keihanian, F; Basirjafari, S; Darbandi, B; Saeidinia, A; Jafroodi, M; Sharafi, R; Shakiba, M

2017-06-01

Considering the high prevalence of glucose-6-phosphate dehydrogenase (G6PD) deficiency among newborns, different screening methods have been established in various countries. In this study, we aimed to assess the prevalence of G6PD deficiency among newborns in Rasht, Iran, and compare G6PD activity in cord blood samples, using quantitative and qualitative tests. This cross-sectional, prospective study was performed at five largest hospitals in Rasht, Guilan Province, Iran. The screening tests were performed for all the newborns, referred to these hospitals. Specimens were characterized in terms of G6PD activity under ultraviolet light, using the kinetic method and the qualitative fluorescent spot test (FST). We also determined the sensitivity, specificity, negative predictive value, and positive predictive value of the qualitative assay. Blood samples were collected from 1474 newborns. Overall, 757 (51.4%) subjects were male. As the findings revealed, 1376 (93.4%) newborns showed normal G6PD activity, while 98 (6.6%) had G6PD deficiency. There was a significant difference in the mean G6PD level between males and females (P = 0.0001). Also, a significant relationship was detected between FST results and the mean values obtained in the quantitative test (P < 0.0001). According to the present study, FST showed acceptable sensitivity and specificity for G6PD activity, although it appeared inefficient for diagnostic purposes in some cases. © 2017 John Wiley & Sons Ltd.

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.

The combination of indocyanine green clearance test and model for end-stage liver disease score predicts early graft outcome after liver transplantation.

PubMed

Yunhua, Tang; Weiqiang, Ju; Maogen, Chen; Sai, Yang; Zhiheng, Zhang; Dongping, Wang; Zhiyong, Guo; Xiaoshun, He

2018-06-01

Early allograft dysfunction (EAD) and early postoperative complications are two important clinical endpoints when evaluating clinical outcomes of liver transplantation (LT). We developed and validated two ICGR15-MELD models in 87 liver transplant recipients for predicting EAD and early postoperative complications after LT by incorporating the quantitative liver function tests (ICGR15) into the MELD score. Eighty seven consecutive patients who underwent LT were collected and divided into a training cohort (n = 61) and an internal validation cohort (n = 26). For predicting EAD after LT, the area under curve (AUC) for ICGR15-MELD score was 0.876, with a sensitivity of 92.0% and a specificity of 75.0%, which is better than MELD score or ICGR15 alone. The recipients with a ICGR15-MELD score ≥0.243 have a higher incidence of EAD than those with a ICGR15-MELD score <0.243 (P <0.001). For predicting early postoperative complications, the AUC of ICGR15-MELD score was 0.832, with a sensitivity of 90.9% and a specificity of 71.0%. Those recipients with an ICGR15-MELD score ≥0.098 have a higher incidence of early postoperative complications than those with an ICGR15-MELD score <0.098 (P < 0.001). Finally, application of the two ICGR15-MELD models in the validation cohort still gave good accuracy (AUC, 0.835 and 0.826, respectively) in predicting EAD and early postoperative complications after LT. The combination of quantitative liver function tests (ICGR15) and the preoperative MELD score is a reliable and effective predictor of EAD and early postoperative complications after LT, which is better than MELD score or ICGR15 alone.

Pred-Skin: A Fast and Reliable Web Application to Assess Skin Sensitization Effect of Chemicals.

PubMed

Braga, Rodolpho C; Alves, Vinicius M; Muratov, Eugene N; Strickland, Judy; Kleinstreuer, Nicole; Trospsha, Alexander; Andrade, Carolina Horta

2017-05-22

Chemically induced skin sensitization is a complex immunological disease with a profound impact on quality of life and working ability. Despite some progress in developing alternative methods for assessing the skin sensitization potential of chemical substances, there is no in vitro test that correlates well with human data. Computational QSAR models provide a rapid screening approach and contribute valuable information for the assessment of chemical toxicity. We describe the development of a freely accessible web-based and mobile application for the identification of potential skin sensitizers. The application is based on previously developed binary QSAR models of skin sensitization potential from human (109 compounds) and murine local lymph node assay (LLNA, 515 compounds) data with good external correct classification rate (0.70-0.81 and 0.72-0.84, respectively). We also included a multiclass skin sensitization potency model based on LLNA data (accuracy ranging between 0.73 and 0.76). When a user evaluates a compound in the web app, the outputs are (i) binary predictions of human and murine skin sensitization potential; (ii) multiclass prediction of murine skin sensitization; and (iii) probability maps illustrating the predicted contribution of chemical fragments. The app is the first tool available that incorporates quantitative structure-activity relationship (QSAR) models based on human data as well as multiclass models for LLNA. The Pred-Skin web app version 1.0 is freely available for the web, iOS, and Android (in development) at the LabMol web portal ( http://labmol.com.br/predskin/ ), in the Apple Store, and on Google Play, respectively. We will continuously update the app as new skin sensitization data and respective models become available.

Sensitivity of the Boundary Plasma to the Plasma-Material Interface

DOE PAGES

Canik, John M.; Tang, X. -Z.

2017-01-01

While the sensitivity of the scrape-off layer and divertor plasma to the highly uncertain cross-field transport assumptions is widely recognized, the plasma is also sensitive to the details of the plasma-material interface (PMI) models used as part of comprehensive predictive simulations. Here in this paper, these PMI sensitivities are studied by varying the relevant sub-models within the SOLPS plasma transport code. Two aspects are explored: the sheath model used as a boundary condition in SOLPS, and fast particle reflection rates for ions impinging on a material surface. Both of these have been the study of recent high-fidelity simulation efforts aimedmore » at improving the understanding and prediction of these phenomena. It is found that in both cases quantitative changes to the plasma solution result from modification of the PMI model, with a larger impact in the case of the reflection coefficient variation. Finally, this indicates the necessity to better quantify the uncertainties within the PMI models themselves, and perform thorough sensitivity analysis to propagate these throughout the boundary model; this is especially important for validation against experiment, where the error in the simulation is a critical and less-studied piece of the code-experiment comparison.« less

Prediction of genotoxic potential of cosmetic ingredients by an in silico battery system consisting of a combination of an expert rule-based system and a statistics-based system.

PubMed

Aiba née Kaneko, Maki; Hirota, Morihiko; Kouzuki, Hirokazu; Mori, Masaaki

2015-02-01

Genotoxicity is the most commonly used endpoint to predict the carcinogenicity of chemicals. The International Conference on Harmonization (ICH) M7 Guideline on Assessment and Control of DNA Reactive (Mutagenic) Impurities in Pharmaceuticals to Limit Potential Carcinogenic Risk offers guidance on (quantitative) structure-activity relationship ((Q)SAR) methodologies that predict the outcome of bacterial mutagenicity assay for actual and potential impurities. We examined the effectiveness of the (Q)SAR approach with the combination of DEREK NEXUS as an expert rule-based system and ADMEWorks as a statistics-based system for the prediction of not only mutagenic potential in the Ames test, but also genotoxic potential in mutagenicity and clastogenicity tests, using a data set of 342 chemicals extracted from the literature. The prediction of mutagenic potential or genotoxic potential by DEREK NEXUS or ADMEWorks showed high values of sensitivity and concordance, while prediction by the combination of DEREK NEXUS and ADMEWorks (battery system) showed the highest values of sensitivity and concordance among the three methods, but the lowest value of specificity. The number of false negatives was reduced with the battery system. We also separately predicted the mutagenic potential and genotoxic potential of 41 cosmetic ingredients listed in the International Nomenclature of Cosmetic Ingredients (INCI) among the 342 chemicals. Although specificity was low with the battery system, sensitivity and concordance were high. These results suggest that the battery system consisting of DEREK NEXUS and ADMEWorks is useful for prediction of genotoxic potential of chemicals, including cosmetic ingredients.

Evaluation of serological and molecular tests used to identify Toxoplasma gondii infection in pregnant women attended in a public health service in São Paulo state, Brazil.

PubMed

Murata, Fernando Henrique Antunes; Ferreira, Marina Neves; Pereira-Chioccola, Vera Lucia; Spegiorin, Lígia Cosentino Junqueira Franco; Meira-Strejevitch, Cristina da Silva; Gava, Ricardo; Silveira-Carvalho, Aparecida Perpétuo; de Mattos, Luiz Carlos; Brandão de Mattos, Cinara Cássia

2017-09-01

Toxoplasmosis during pregnancy can have severe consequences. The use of sensitive and specific serological and molecular methods is extremely important for the correct diagnosis of the disease. We compared the ELISA and ELFA serological methods, conventional PCR (cPCR), Nested PCR and quantitative PCR (qPCR) in the diagnosis of Toxoplasma gondii infection in pregnant women without clinical suspicion of toxoplasmosis (G1=94) and with clinical suspicion of toxoplasmosis (G2=53). The results were compared using the Kappa index, and the sensitivity, specificity, positive predictive value and negative predictive value were calculated. The results of the serological methods showed concordance between the ELISA and ELFA methods even though ELFA identified more positive cases than ELISA. Molecular methods were discrepant with cPCR using B22/23 primers having greater sensitivity and lower specificity compared to the other molecular methods. Copyright © 2017 Elsevier Inc. All rights reserved.

Quantitative assessment of hematopoietic chimerism by quantitative real-time polymerase chain reaction of sequence polymorphism systems after hematopoietic stem cell transplantation.

PubMed

Qin, Xiao-ying; Li, Guo-xuan; Qin, Ya-zhen; Wang, Yu; Wang, Feng-rong; Liu, Dai-hong; Xu, Lan-ping; Chen, Huan; Han, Wei; Wang, Jing-zhi; Zhang, Xiao-hui; Li, Jin-lan; Li, Ling-di; Liu, Kai-yan; Huang, Xiao-jun

2011-08-01

Analysis of changes in recipient and donor hematopoietic cell origin is extremely useful to monitor the effect of hematopoietic stem cell transplantation (HSCT) and sequential adoptive immunotherapy by donor lymphocyte infusions. We developed a sensitive, reliable and rapid real-time PCR method based on sequence polymorphism systems to quantitatively assess the hematopoietic chimerism after HSCT. A panel of 29 selected sequence polymorphism (SP) markers was screened by real-time PCR in 101 HSCT patients with leukemia and other hematological diseases. The chimerism kinetics of bone marrow samples of 8 HSCT patients in remission and relapse situations were followed longitudinally. Recipient genotype discrimination was possible in 97.0% (98 of 101) with a mean number of 2.5 (1-7) informative markers per recipient/donor pair. Using serial dilutions of plasmids containing specific SP markers, the linear correlation (r) of 0.99, the slope between -3.2 and -3.7 and the sensitivity of 0.1% were proved reproducible. By this method, it was possible to very accurately detect autologous signals in the range from 0.1% to 30%. The accuracy of the method in the very important range of autologous signals below 5% was extraordinarily high (standard deviation <1.85%), which might significantly improve detection accuracy of changes in autologous signals early in the post-transplantation course of follow-up. The main advantage of the real-time PCR method over short tandem repeat PCR chimerism assays is the absence of PCR competition and plateau biases, with demonstrated greater sensitivity and linearity. Finally, we prospectively analyzed bone marrow samples of 8 patients who received allografts and presented the chimerism kinetics of remission and relapse situations that illustrated the sensitivity level and the promising clinical application of this method. This SP-based real-time PCR assay provides a rapid, sensitive, and accurate quantitative assessment of mixed chimerism that can be useful in predicting graft rejection and early relapse.

Parametric studies with an atmospheric diffusion model that assesses toxic fuel hazards due to the ground clouds generated by rocket launches

NASA Technical Reports Server (NTRS)

Stewart, R. B.; Grose, W. L.

1975-01-01

Parametric studies were made with a multilayer atmospheric diffusion model to place quantitative limits on the uncertainty of predicting ground-level toxic rocket-fuel concentrations. Exhaust distributions in the ground cloud, cloud stabilized geometry, atmospheric coefficients, the effects of exhaust plume afterburning of carbon monoxide CO, assumed surface mixing-layer division in the model, and model sensitivity to different meteorological regimes were studied. Large-scale differences in ground-level predictions are quantitatively described. Cloud alongwind growth for several meteorological conditions is shown to be in error because of incorrect application of previous diffusion theory. In addition, rocket-plume calculations indicate that almost all of the rocket-motor carbon monoxide is afterburned to carbon dioxide CO2, thus reducing toxic hazards due to CO. The afterburning is also shown to have a significant effect on cloud stabilization height and on ground-level concentrations of exhaust products.

Inductive reasoning about causally transmitted properties.

PubMed

Shafto, Patrick; Kemp, Charles; Bonawitz, Elizabeth Baraff; Coley, John D; Tenenbaum, Joshua B

2008-11-01

Different intuitive theories constrain and guide inferences in different contexts. Formalizing simple intuitive theories as probabilistic processes operating over structured representations, we present a new computational model of category-based induction about causally transmitted properties. A first experiment demonstrates undergraduates' context-sensitive use of taxonomic and food web knowledge to guide reasoning about causal transmission and shows good qualitative agreement between model predictions and human inferences. A second experiment demonstrates strong quantitative and qualitative fits to inferences about a more complex artificial food web. A third experiment investigates human reasoning about complex novel food webs where species have known taxonomic relations. Results demonstrate a double-dissociation between the predictions of our causal model and a related taxonomic model [Kemp, C., & Tenenbaum, J. B. (2003). Learning domain structures. In Proceedings of the 25th annual conference of the cognitive science society]: the causal model predicts human inferences about diseases but not genes, while the taxonomic model predicts human inferences about genes but not diseases. We contrast our framework with previous models of category-based induction and previous formal instantiations of intuitive theories, and outline challenges in developing a complete model of context-sensitive reasoning.

Longer-Term Investigation of the Value of 18F-FDG-PET and Magnetic Resonance Imaging for Predicting the Conversion of Mild Cognitive Impairment to Alzheimer's Disease: A Multicenter Study.

PubMed

Inui, Yoshitaka; Ito, Kengo; Kato, Takashi

2017-01-01

The value of fluorine-18-fluorodeoxyglucose positron emission tomography (18F-FDG-PET) and magnetic resonance imaging (MRI) for predicting conversion of mild cognitive impairment (MCI) to Alzheimer's disease (AD) in longer-term is unclear. To evaluate longer-term prediction of MCI to AD conversion using 18F-FDG-PET and MRI in a multicenter study. One-hundred and fourteen patients with MCI were followed for 5 years. They underwent clinical and neuropsychological examinations, 18F-FDG-PET, and MRI at baseline. PET images were visually classified into predefined dementia patterns. PET scores were calculated as a semi quantitative index. For structural MRI, z-scores in medial temporal area were calculated by automated volume-based morphometry (VBM). Overall, 72% patients with amnestic MCI progressed to AD during the 5-year follow-up. The diagnostic accuracy of PET scores over 5 years was 60% with 53% sensitivity and 84% specificity. Visual interpretation of PET images predicted conversion to AD with an overall 82% diagnostic accuracy, 94% sensitivity, and 53% specificity. The accuracy of VBM analysis presented little fluctuation through 5 years and it was highest (73%) at the 5-year follow-up, with 79% sensitivity and 63% specificity. The best performance (87.9% diagnostic accuracy, 89.8% sensitivity, and 82.4% specificity) was with a combination identified using multivariate logistic regression analysis that included PET visual interpretation, educational level, and neuropsychological tests as predictors. 18F-FDG-PET visual assessment showed high performance for predicting conversion to AD from MCI, particularly in combination with neuropsychological tests. PET scores showed high diagnostic specificity. Structural MRI focused on the medial temporal area showed stable predictive value throughout the 5-year course.

Establishing optimal quantitative-polymerase chain reaction assays for routine diagnosis and tracking of minimal residual disease in JAK2-V617F-associated myeloproliferative neoplasms: a joint European LeukemiaNet/MPN&MPNr-EuroNet (COST action BM0902) study.

PubMed

Jovanovic, J V; Ivey, A; Vannucchi, A M; Lippert, E; Oppliger Leibundgut, E; Cassinat, B; Pallisgaard, N; Maroc, N; Hermouet, S; Nickless, G; Guglielmelli, P; van der Reijden, B A; Jansen, J H; Alpermann, T; Schnittger, S; Bench, A; Tobal, K; Wilkins, B; Cuthill, K; McLornan, D; Yeoman, K; Akiki, S; Bryon, J; Jeffries, S; Jones, A; Percy, M J; Schwemmers, S; Gruender, A; Kelley, T W; Reading, S; Pancrazzi, A; McMullin, M F; Pahl, H L; Cross, N C P; Harrison, C N; Prchal, J T; Chomienne, C; Kiladjian, J J; Barbui, T; Grimwade, D

2013-10-01

Reliable detection of JAK2-V617F is critical for accurate diagnosis of myeloproliferative neoplasms (MPNs); in addition, sensitive mutation-specific assays can be applied to monitor disease response. However, there has been no consistent approach to JAK2-V617F detection, with assays varying markedly in performance, affecting clinical utility. Therefore, we established a network of 12 laboratories from seven countries to systematically evaluate nine different DNA-based quantitative PCR (qPCR) assays, including those in widespread clinical use. Seven quality control rounds involving over 21,500 qPCR reactions were undertaken using centrally distributed cell line dilutions and plasmid controls. The two best-performing assays were tested on normal blood samples (n=100) to evaluate assay specificity, followed by analysis of serial samples from 28 patients transplanted for JAK2-V617F-positive disease. The most sensitive assay, which performed consistently across a range of qPCR platforms, predicted outcome following transplant, with the mutant allele detected a median of 22 weeks (range 6-85 weeks) before relapse. Four of seven patients achieved molecular remission following donor lymphocyte infusion, indicative of a graft vs MPN effect. This study has established a robust, reliable assay for sensitive JAK2-V617F detection, suitable for assessing response in clinical trials, predicting outcome and guiding management of patients undergoing allogeneic transplant.

Electroencephalography reactivity for prognostication of post-anoxic coma after cardiopulmonary resuscitation: A comparison of quantitative analysis and visual analysis.

PubMed

Liu, Gang; Su, Yingying; Jiang, Mengdi; Chen, Weibi; Zhang, Yan; Zhang, Yunzhou; Gao, Daiquan

2016-07-28

Electroencephalogram reactivity (EEG-R) is a positive predictive factor for assessing outcomes in comatose patients. Most studies assess the prognostic value of EEG-R utilizing visual analysis; however, this method is prone to subjectivity. We sought to categorize EEG-R with a quantitative approach. We retrospectively studied consecutive comatose patients who had an EEG-R recording performed 1-3 days after cardiopulmonary resuscitation (CPR) or during normothermia after therapeutic hypothermia. EEG-R was assessed via visual analysis and quantitative analysis separately. Clinical outcomes were followed-up at 3-month and dichotomized as recovery of awareness or no recovery of awareness. A total of 96 patients met the inclusion criteria, and 38 (40%) patients recovered awareness at 3-month followed-up. Of 27 patients with EEG-R measured with visual analysis, 22 patients recovered awareness; and of the 69 patients who did not demonstrated EEG-R, 16 patients recovered awareness. The sensitivity and specificity of visually measured EEG-R were 58% and 91%, respectively. The area under the receiver operating characteristic curve for the quantitative analysis was 0.92 (95% confidence interval, 0.87-0.97), with the best cut-off value of 0.10. EEG-R through quantitative analysis might be a good method in predicting the recovery of awareness in patients with post-anoxic coma after CPR. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

An ensemble model of QSAR tools for regulatory risk assessment.

PubMed

Pradeep, Prachi; Povinelli, Richard J; White, Shannon; Merrill, Stephen J

2016-01-01

Quantitative structure activity relationships (QSARs) are theoretical models that relate a quantitative measure of chemical structure to a physical property or a biological effect. QSAR predictions can be used for chemical risk assessment for protection of human and environmental health, which makes them interesting to regulators, especially in the absence of experimental data. For compatibility with regulatory use, QSAR models should be transparent, reproducible and optimized to minimize the number of false negatives. In silico QSAR tools are gaining wide acceptance as a faster alternative to otherwise time-consuming clinical and animal testing methods. However, different QSAR tools often make conflicting predictions for a given chemical and may also vary in their predictive performance across different chemical datasets. In a regulatory context, conflicting predictions raise interpretation, validation and adequacy concerns. To address these concerns, ensemble learning techniques in the machine learning paradigm can be used to integrate predictions from multiple tools. By leveraging various underlying QSAR algorithms and training datasets, the resulting consensus prediction should yield better overall predictive ability. We present a novel ensemble QSAR model using Bayesian classification. The model allows for varying a cut-off parameter that allows for a selection in the desirable trade-off between model sensitivity and specificity. The predictive performance of the ensemble model is compared with four in silico tools (Toxtree, Lazar, OECD Toolbox, and Danish QSAR) to predict carcinogenicity for a dataset of air toxins (332 chemicals) and a subset of the gold carcinogenic potency database (480 chemicals). Leave-one-out cross validation results show that the ensemble model achieves the best trade-off between sensitivity and specificity (accuracy: 83.8 % and 80.4 %, and balanced accuracy: 80.6 % and 80.8 %) and highest inter-rater agreement [kappa ( κ ): 0.63 and 0.62] for both the datasets. The ROC curves demonstrate the utility of the cut-off feature in the predictive ability of the ensemble model. This feature provides an additional control to the regulators in grading a chemical based on the severity of the toxic endpoint under study.

An ensemble model of QSAR tools for regulatory risk assessment

DOE PAGES

Pradeep, Prachi; Povinelli, Richard J.; White, Shannon; ...

2016-09-22

Quantitative structure activity relationships (QSARs) are theoretical models that relate a quantitative measure of chemical structure to a physical property or a biological effect. QSAR predictions can be used for chemical risk assessment for protection of human and environmental health, which makes them interesting to regulators, especially in the absence of experimental data. For compatibility with regulatory use, QSAR models should be transparent, reproducible and optimized to minimize the number of false negatives. In silico QSAR tools are gaining wide acceptance as a faster alternative to otherwise time-consuming clinical and animal testing methods. However, different QSAR tools often make conflictingmore » predictions for a given chemical and may also vary in their predictive performance across different chemical datasets. In a regulatory context, conflicting predictions raise interpretation, validation and adequacy concerns. To address these concerns, ensemble learning techniques in the machine learning paradigm can be used to integrate predictions from multiple tools. By leveraging various underlying QSAR algorithms and training datasets, the resulting consensus prediction should yield better overall predictive ability. We present a novel ensemble QSAR model using Bayesian classification. The model allows for varying a cut-off parameter that allows for a selection in the desirable trade-off between model sensitivity and specificity. The predictive performance of the ensemble model is compared with four in silico tools (Toxtree, Lazar, OECD Toolbox, and Danish QSAR) to predict carcinogenicity for a dataset of air toxins (332 chemicals) and a subset of the gold carcinogenic potency database (480 chemicals). Leave-one-out cross validation results show that the ensemble model achieves the best trade-off between sensitivity and specificity (accuracy: 83.8 % and 80.4 %, and balanced accuracy: 80.6 % and 80.8 %) and highest inter-rater agreement [kappa (κ): 0.63 and 0.62] for both the datasets. The ROC curves demonstrate the utility of the cut-off feature in the predictive ability of the ensemble model. In conclusion, this feature provides an additional control to the regulators in grading a chemical based on the severity of the toxic endpoint under study.« less

Ultrasound hepatic/renal ratio and hepatic attenuation rate for quantifying liver fat content.

PubMed

Zhang, Bo; Ding, Fang; Chen, Tian; Xia, Liang-Hua; Qian, Juan; Lv, Guo-Yi

2014-12-21

To establish and validate a simple quantitative assessment method for nonalcoholic fatty liver disease (NAFLD) based on a combination of the ultrasound hepatic/renal ratio and hepatic attenuation rate. A total of 170 subjects were enrolled in this study. All subjects were examined by ultrasound and (1)H-magnetic resonance spectroscopy ((1)H-MRS) on the same day. The ultrasound hepatic/renal echo-intensity ratio and ultrasound hepatic echo-intensity attenuation rate were obtained from ordinary ultrasound images using the MATLAB program. Correlation analysis revealed that the ultrasound hepatic/renal ratio and hepatic echo-intensity attenuation rate were significantly correlated with (1)H-MRS liver fat content (ultrasound hepatic/renal ratio: r = 0.952, P = 0.000; hepatic echo-intensity attenuation r = 0.850, P = 0.000). The equation for predicting liver fat content by ultrasound (quantitative ultrasound model) is: liver fat content (%) = 61.519 × ultrasound hepatic/renal ratio + 167.701 × hepatic echo-intensity attenuation rate -26.736. Spearman correlation analysis revealed that the liver fat content ratio of the quantitative ultrasound model was positively correlated with serum alanine aminotransferase, aspartate aminotransferase, and triglyceride, but negatively correlated with high density lipoprotein cholesterol. Receiver operating characteristic curve analysis revealed that the optimal point for diagnosing fatty liver was 9.15% in the quantitative ultrasound model. Furthermore, in the quantitative ultrasound model, fatty liver diagnostic sensitivity and specificity were 94.7% and 100.0%, respectively, showing that the quantitative ultrasound model was better than conventional ultrasound methods or the combined ultrasound hepatic/renal ratio and hepatic echo-intensity attenuation rate. If the (1)H-MRS liver fat content had a value < 15%, the sensitivity and specificity of the ultrasound quantitative model would be 81.4% and 100%, which still shows that using the model is better than the other methods. The quantitative ultrasound model is a simple, low-cost, and sensitive tool that can accurately assess hepatic fat content in clinical practice. It provides an easy and effective parameter for the early diagnosis of mild hepatic steatosis and evaluation of the efficacy of NAFLD treatment.

Using demography and movement behavior to predict range expansion of the southern sea otter.

USGS Publications Warehouse

Tinker, M.T.; Doak, D.F.; Estes, J.A.

2008-01-01

In addition to forecasting population growth, basic demographic data combined with movement data provide a means for predicting rates of range expansion. Quantitative models of range expansion have rarely been applied to large vertebrates, although such tools could be useful for restoration and management of many threatened but recovering populations. Using the southern sea otter (Enhydra lutris nereis) as a case study, we utilized integro-difference equations in combination with a stage-structured projection matrix that incorporated spatial variation in dispersal and demography to make forecasts of population recovery and range recolonization. In addition to these basic predictions, we emphasize how to make these modeling predictions useful in a management context through the inclusion of parameter uncertainty and sensitivity analysis. Our models resulted in hind-cast (1989–2003) predictions of net population growth and range expansion that closely matched observed patterns. We next made projections of future range expansion and population growth, incorporating uncertainty in all model parameters, and explored the sensitivity of model predictions to variation in spatially explicit survival and dispersal rates. The predicted rate of southward range expansion (median = 5.2 km/yr) was sensitive to both dispersal and survival rates; elasticity analysis indicated that changes in adult survival would have the greatest potential effect on the rate of range expansion, while perturbation analysis showed that variation in subadult dispersal contributed most to variance in model predictions. Variation in survival and dispersal of females at the south end of the range contributed most of the variance in predicted southward range expansion. Our approach provides guidance for the acquisition of further data and a means of forecasting the consequence of specific management actions. Similar methods could aid in the management of other recovering populations.

Vesicular stomatitis forecasting based on Google Trends

PubMed Central

Lu, Yi; Zhou, GuangYa; Chen, Qin

2018-01-01

Background Vesicular stomatitis (VS) is an important viral disease of livestock. The main feature of VS is irregular blisters that occur on the lips, tongue, oral mucosa, hoof crown and nipple. Humans can also be infected with vesicular stomatitis and develop meningitis. This study analyses 2014 American VS outbreaks in order to accurately predict vesicular stomatitis outbreak trends. Methods American VS outbreaks data were collected from OIE. The data for VS keywords were obtained by inputting 24 disease-related keywords into Google Trends. After calculating the Pearson and Spearman correlation coefficients, it was found that there was a relationship between outbreaks and keywords derived from Google Trends. Finally, the predicted model was constructed based on qualitative classification and quantitative regression. Results For the regression model, the Pearson correlation coefficients between the predicted outbreaks and actual outbreaks are 0.953 and 0.948, respectively. For the qualitative classification model, we constructed five classification predictive models and chose the best classification predictive model as the result. The results showed, SN (sensitivity), SP (specificity) and ACC (prediction accuracy) values of the best classification predictive model are 78.52%,72.5% and 77.14%, respectively. Conclusion This study applied Google search data to construct a qualitative classification model and a quantitative regression model. The results show that the method is effective and that these two models obtain more accurate forecast. PMID:29385198

Divisional role of quantitative HER2 testing in breast cancer.

PubMed

Yamamoto-Ibusuki, Mutsuko; Yamamoto, Yutaka; Fu, Peifen; Yamamoto, Satoko; Fujiwara, Saori; Honda, Yumi; Iyama, Ken-ichi; Iwase, Hirotaka

2015-03-01

Human epidermal growth factor receptor 2 (HER2) is amplified in human breast cancers in which therapy targeted to HER2 significantly improves patient outcome. We re-visited the use of real-time quantitative polymerase chain reaction (qPCR)-based assays using formalin-fixed paraffin-embedded (FFPE) tissues as alternative methods and investigated their particular clinical relevance. DNA and RNA were isolated from FFPE specimens and HER2 status was assessed by qPCR in 249 consecutive patients with primary breast cancer. Concordance with results forg immunohistochemistry (IHC) and in situ hybridization (ISH), clinical characteristics and survival was assessed. HER2 gene copy number had a stronger correlation with clinicopathological characteristics and excellent concordance with IHC/ISH results (Sensitivity: 96.7 %; concordance: 99.2 %). HER2 gene expression showed inadequate sensitivity, rendering it unsuitable to determine HER2 status (Sensitivity: 46.7 %; concordance: 92.1 %), but lower HER2 gene expression, leading to the classification of many cases as "false negative", contributed to a prediction of better prognosis within the HER2-amplified subpopulation. Quantitative HER2 assessments are suggested to have evolved their accuracy in this decade, which can be a potential alternative for HER2 diagnosis in line with the in situ method, while HER2 gene expression levels could provide additional information regarding prognosis or therapeutic strategy within a HER2-amplified subpopulation.

Determination of subthalamic nucleus location by quantitative analysis of despiked background neural activity from microelectrode recordings obtained during deep brain stimulation surgery.

PubMed

Danish, Shabbar F; Baltuch, Gordon H; Jaggi, Jurg L; Wong, Stephen

2008-04-01

Microelectrode recording during deep brain stimulation surgery is a useful adjunct for subthalamic nucleus (STN) localization. We hypothesize that information in the nonspike background activity can help identify STN boundaries. We present results from a novel quantitative analysis that accomplishes this goal. Thirteen consecutive microelectrode recordings were retrospectively analyzed. Spikes were removed from the recordings with an automated algorithm. The remaining "despiked" signals were converted via root mean square amplitude and curve length calculations into "feature profile" time series. Subthalamic nucleus boundaries determined by inspection, based on sustained deviations from baseline for each feature profile, were compared against those determined intraoperatively by the clinical neurophysiologist. Feature profile activity within STN exhibited a sustained rise in 10 of 13 tracks (77%). The sensitivity of STN entry was 60% and 90% for curve length and root mean square amplitude, respectively, when agreement within 0.5 mm of the neurophysiologist's prediction was used. Sensitivities were 70% and 100% for 1 mm accuracy. Exit point sensitivities were 80% and 90% for both features within 0.5 mm and 1.0 mm, respectively. Reproducible activity patterns in deep brain stimulation microelectrode recordings can allow accurate identification of STN boundaries. Quantitative analyses of this type may provide useful adjunctive information for electrode placement in deep brain stimulation surgery.

Quantitative targeted proteomic analysis of potential markers of tyrosine kinase inhibitor (TKI) sensitivity in EGFR mutated lung adenocarcinoma.

PubMed

Awasthi, Shivangi; Maity, Tapan; Oyler, Benjamin L; Qi, Yue; Zhang, Xu; Goodlett, David R; Guha, Udayan

2018-04-13

Lung cancer causes the highest mortality among all cancers. Patients harboring kinase domain mutations in the epidermal growth factor receptor (EGFR) respond to EGFR tyrosine kinase inhibitors (TKIs), however, acquired resistance always develops. Moreover, 30-40% of patients with EGFR mutations exhibit primary resistance. Hence, there is an unmet need for additional biomarkers of TKI sensitivity that complement EGFR mutation testing and predict treatment response. We previously identified phosphopeptides whose phosphorylation is inhibited upon treatment with EGFR TKIs, erlotinib and afatinib in TKI sensitive cells, but not in resistant cells. These phosphosites are potential biomarkers of TKI sensitivity. Here, we sought to develop modified immuno-multiple reaction monitoring (immuno-MRM)-based quantitation assays for select phosphosites including EGFR-pY1197, pY1172, pY998, AHNAK-pY160, pY715, DAPP1-pY139, CAV1-pY14, INPPL1-pY1135, NEDD9-pY164, NF1-pY2579, and STAT5A-pY694. These sites were significantly hypophosphorylated by erlotinib and a 3rd generation EGFR TKI, osimertinib, in TKI-sensitive H3255 cells, which harbor the TKI-sensitizing EGFR L858R mutation. However, in H1975 cells, which harbor the TKI-resistant EGFR L858R/T790M mutant, osimertinib, but not erlotinib, could significantly inhibit phosphorylation of EGFR-pY-1197, STAT5A-pY694 and CAV1-pY14, suggesting these sites also predict response in TKI-resistant cells. We could further validate EGFR-pY-1197 as a biomarker of TKI sensitivity by developing a calibration curve-based modified immuno-MRM assay. In this report, we have shown the development and optimization of MRM assays coupled with global phosphotyrosine enrichment (modified immuno-MRM) for a list of 11 phosphotyrosine peptides. Our optimized assays identified the targets reproducibly in biological samples with good selectivity. We also developed and characterized quantitation methods to determine endogenous abundance of these targets and correlated the results of the relative quantification with amounts estimated from the calibration curves. This approach represents a way to validate and verify biomarker candidates discovered from large-scale global phospho-proteomics analysis. The application of these modified immuno-MRM assays in lung adenocarcinoma cells provides proof-of concept for the feasibility of clinical applications. These assays may be used in prospective clinical studies of EGFR TKI treatment of EGFR mutant lung cancer to correlate treatment response and other clinical endpoints. Copyright © 2018. Published by Elsevier B.V.

Local sensitivity of per-recruit fishing mortality reference points.

PubMed

Cadigan, N G; Wang, S

2016-12-01

We study the sensitivity of fishery management per-recruit harvest rates which may be part of a quantitative harvest strategy designed to achieve some objective for catch or population size. We use a local influence sensitivity analysis to derive equations that describe how these reference harvest rates are affected by perturbations to productivity processes. These equations give a basic theoretical understanding of sensitivity that can be used to predict what the likely impacts of future changes in productivity will be. Our results indicate that per-recruit reference harvest rates are more sensitive to perturbations when the equilibrium catch or population size per recruit, as functions of the harvest rate, have less curvature near the reference point. Overall our results suggest that per recruit reference points will, with some exceptions, usually increase if (1) growth rates increase, (2) natural mortality rates increase, or (3) fishery selectivity increases to an older age.

Sensitivity analysis, calibration, and testing of a distributed hydrological model using error‐based weighting and one objective function

USGS Publications Warehouse

Foglia, L.; Hill, Mary C.; Mehl, Steffen W.; Burlando, P.

2009-01-01

We evaluate the utility of three interrelated means of using data to calibrate the fully distributed rainfall‐runoff model TOPKAPI as applied to the Maggia Valley drainage area in Switzerland. The use of error‐based weighting of observation and prior information data, local sensitivity analysis, and single‐objective function nonlinear regression provides quantitative evaluation of sensitivity of the 35 model parameters to the data, identification of data types most important to the calibration, and identification of correlations among parameters that contribute to nonuniqueness. Sensitivity analysis required only 71 model runs, and regression required about 50 model runs. The approach presented appears to be ideal for evaluation of models with long run times or as a preliminary step to more computationally demanding methods. The statistics used include composite scaled sensitivities, parameter correlation coefficients, leverage, Cook's D, and DFBETAS. Tests suggest predictive ability of the calibrated model typical of hydrologic models.

Error sensitivity analysis in 10-30-day extended range forecasting by using a nonlinear cross-prediction error model

NASA Astrophysics Data System (ADS)

Xia, Zhiye; Xu, Lisheng; Chen, Hongbin; Wang, Yongqian; Liu, Jinbao; Feng, Wenlan

2017-06-01

Extended range forecasting of 10-30 days, which lies between medium-term and climate prediction in terms of timescale, plays a significant role in decision-making processes for the prevention and mitigation of disastrous meteorological events. The sensitivity of initial error, model parameter error, and random error in a nonlinear crossprediction error (NCPE) model, and their stability in the prediction validity period in 10-30-day extended range forecasting, are analyzed quantitatively. The associated sensitivity of precipitable water, temperature, and geopotential height during cases of heavy rain and hurricane is also discussed. The results are summarized as follows. First, the initial error and random error interact. When the ratio of random error to initial error is small (10-6-10-2), minor variation in random error cannot significantly change the dynamic features of a chaotic system, and therefore random error has minimal effect on the prediction. When the ratio is in the range of 10-1-2 (i.e., random error dominates), attention should be paid to the random error instead of only the initial error. When the ratio is around 10-2-10-1, both influences must be considered. Their mutual effects may bring considerable uncertainty to extended range forecasting, and de-noising is therefore necessary. Second, in terms of model parameter error, the embedding dimension m should be determined by the factual nonlinear time series. The dynamic features of a chaotic system cannot be depicted because of the incomplete structure of the attractor when m is small. When m is large, prediction indicators can vanish because of the scarcity of phase points in phase space. A method for overcoming the cut-off effect ( m > 4) is proposed. Third, for heavy rains, precipitable water is more sensitive to the prediction validity period than temperature or geopotential height; however, for hurricanes, geopotential height is most sensitive, followed by precipitable water.

Predictive value of EEG in postanoxic encephalopathy: A quantitative model-based approach.

PubMed

Efthymiou, Evdokia; Renzel, Roland; Baumann, Christian R; Poryazova, Rositsa; Imbach, Lukas L

2017-10-01

The majority of comatose patients after cardiac arrest do not regain consciousness due to severe postanoxic encephalopathy. Early and accurate outcome prediction is therefore essential in determining further therapeutic interventions. The electroencephalogram is a standardized and commonly available tool used to estimate prognosis in postanoxic patients. The identification of pathological EEG patterns with poor prognosis relies however primarily on visual EEG scoring by experts. We introduced a model-based approach of EEG analysis (state space model) that allows for an objective and quantitative description of spectral EEG variability. We retrospectively analyzed standard EEG recordings in 83 comatose patients after cardiac arrest between 2005 and 2013 in the intensive care unit of the University Hospital Zürich. Neurological outcome was assessed one month after cardiac arrest using the Cerebral Performance Category. For a dynamic and quantitative EEG analysis, we implemented a model-based approach (state space analysis) to quantify EEG background variability independent from visual scoring of EEG epochs. Spectral variability was compared between groups and correlated with clinical outcome parameters and visual EEG patterns. Quantitative assessment of spectral EEG variability (state space velocity) revealed significant differences between patients with poor and good outcome after cardiac arrest: Lower mean velocity in temporal electrodes (T4 and T5) was significantly associated with poor prognostic outcome (p<0.005) and correlated with independently identified visual EEG patterns such as generalized periodic discharges (p<0.02). Receiver operating characteristic (ROC) analysis confirmed the predictive value of lower state space velocity for poor clinical outcome after cardiac arrest (AUC 80.8, 70% sensitivity, 15% false positive rate). Model-based quantitative EEG analysis (state space analysis) provides a novel, complementary marker for prognosis in postanoxic encephalopathy. Copyright © 2017 Elsevier B.V. All rights reserved.

Predicting drug hydrolysis based on moisture uptake in various packaging designs.

PubMed

Naversnik, Klemen; Bohanec, Simona

2008-12-18

An attempt was made to predict the stability of a moisture sensitive drug product based on the knowledge of the dependence of the degradation rate on tablet moisture. The moisture increase inside a HDPE bottle with the drug formulation was simulated with the sorption-desorption moisture transfer model, which, in turn, allowed an accurate prediction of the drug degradation kinetics. The stability prediction, obtained by computer simulation, was made in a considerably shorter time frame and required little resources compared to a conventional stability study. The prediction was finally upgraded to a stochastic Monte Carlo simulation, which allowed quantitative incorporation of uncertainty, stemming from various sources. The resulting distribution of the outcome of interest (amount of degradation product at expiry) is a comprehensive way of communicating the result along with its uncertainty, superior to single-value results or confidence intervals.

4D-Fingerprint Categorical QSAR Models for Skin Sensitization Based on Classification Local Lymph Node Assay Measures

PubMed Central

Li, Yi; Tseng, Yufeng J.; Pan, Dahua; Liu, Jianzhong; Kern, Petra S.; Gerberick, G. Frank; Hopfinger, Anton J.

2008-01-01

Currently, the only validated methods to identify skin sensitization effects are in vivo models, such as the Local Lymph Node Assay (LLNA) and guinea pig studies. There is a tremendous need, in particular due to novel legislation, to develop animal alternatives, eg. Quantitative Structure-Activity Relationship (QSAR) models. Here, QSAR models for skin sensitization using LLNA data have been constructed. The descriptors used to generate these models are derived from the 4D-molecular similarity paradigm and are referred to as universal 4D-fingerprints. A training set of 132 structurally diverse compounds and a test set of 15 structurally diverse compounds were used in this study. The statistical methodologies used to build the models are logistic regression (LR), and partial least square coupled logistic regression (PLS-LR), which prove to be effective tools for studying skin sensitization measures expressed in the two categorical terms of sensitizer and non-sensitizer. QSAR models with low values of the Hosmer-Lemeshow goodness-of-fit statistic, χHL2, are significant and predictive. For the training set, the cross-validated prediction accuracy of the logistic regression models ranges from 77.3% to 78.0%, while that of PLS-logistic regression models ranges from 87.1% to 89.4%. For the test set, the prediction accuracy of logistic regression models ranges from 80.0%-86.7%, while that of PLS-logistic regression models ranges from 73.3%-80.0%. The QSAR models are made up of 4D-fingerprints related to aromatic atoms, hydrogen bond acceptors and negatively partially charged atoms. PMID:17226934

High positive predictive value of Gram stain on catheter-drawn blood samples for the diagnosis of catheter-related bloodstream infection in intensive care neonates.

PubMed

Deleers, M; Dodémont, M; Van Overmeire, B; Hennequin, Y; Vermeylen, D; Roisin, S; Denis, O

2016-04-01

Catheter-related bloodstream infections (CRBSIs) remain a leading cause of healthcare-associated infections in preterm infants. Rapid and accurate methods for the diagnosis of CRBSIs are needed in order to implement timely and appropriate treatment. A retrospective study was conducted during a 7-year period (2005-2012) in the neonatal intensive care unit of the University Hospital Erasme to assess the value of Gram stain on catheter-drawn blood samples (CDBS) to predict CRBSIs. Both peripheral samples and CDBS were obtained from neonates with clinically suspected CRBSI. Gram stain, automated culture and quantitative cultures on blood agar plates were performed for each sample. The paired quantitative blood culture was used as the standard to define CRBSI. Out of 397 episodes of suspected CRBSIs, 35 were confirmed by a positive ratio of quantitative culture (>5) or a colony count of CDBS culture >100 colony-forming units (CFU)/mL. All but two of the 30 patients who had a CDBS with a positive Gram stain were confirmed as having a CRBSI. Seven patients who had a CDBS with a negative Gram stain were diagnosed as CRBSI. The sensitivity, specificity, positive predictive value and negative predictive value of Gram stain on CDBS were 80, 99.4, 93.3 and 98.1 %, respectively. Gram staining on CDBS is a viable method for rapidly (<1 h) detecting CRBSI without catheter withdrawal.

Identification of line-specific strategies for improving carotenoid production in synthetic maize through data-driven mathematical modeling.

PubMed

Comas, Jorge; Benfeitas, Rui; Vilaprinyo, Ester; Sorribas, Albert; Solsona, Francesc; Farré, Gemma; Berman, Judit; Zorrilla, Uxue; Capell, Teresa; Sandmann, Gerhard; Zhu, Changfu; Christou, Paul; Alves, Rui

2016-09-01

Plant synthetic biology is still in its infancy. However, synthetic biology approaches have been used to manipulate and improve the nutritional and health value of staple food crops such as rice, potato and maize. With current technologies, production yields of the synthetic nutrients are a result of trial and error, and systematic rational strategies to optimize those yields are still lacking. Here, we present a workflow that combines gene expression and quantitative metabolomics with mathematical modeling to identify strategies for increasing production yields of nutritionally important carotenoids in the seed endosperm synthesized through alternative biosynthetic pathways in synthetic lines of white maize, which is normally devoid of carotenoids. Quantitative metabolomics and gene expression data are used to create and fit parameters of mathematical models that are specific to four independent maize lines. Sensitivity analysis and simulation of each model is used to predict which gene activities should be further engineered in order to increase production yields for carotenoid accumulation in each line. Some of these predictions (e.g. increasing Zmlycb/Gllycb will increase accumulated β-carotenes) are valid across the four maize lines and consistent with experimental observations in other systems. Other predictions are line specific. The workflow is adaptable to any other biological system for which appropriate quantitative information is available. Furthermore, we validate some of the predictions using experimental data from additional synthetic maize lines for which no models were developed. © 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd.

Comparative Ecology of H2 Cycling in Organotrophic and Phototrophic Ecosystems

NASA Technical Reports Server (NTRS)

Hoehler, Tori M.; Alperin, Marc J.; Albert, Daniel B.; Bebout, Brad M.; Martens, Christopher S.; DesMarais, David J.; DeVincenzi, Don (Technical Monitor)

2001-01-01

The simple biochemistry of H2 is critical to a large number of microbial processes, affecting the interaction of organisms with each other and with the environment. The sensitivity of these many processes to H2 can be described quantitatively, at a basic thermodynamic level. This shared dependence on H2 may provide a means for interpreting the ecology and system-level biogeochemistry of widely variant microbial ecosystems on a common (and quantitative) level. Understanding the factors that control H2 itself is a critical prerequisite. Here, we examine two ecosystems that vary widely with respect to H2 cycling. In anoxic, 'organotrophic' sediments from Cape Lookout Bight (North Carolina, USA), H2 partial pressures are strictly maintained at low, steady-state levels by H2-consuming organisms, in a fashion that can be quantitatively predicted by simple thermodynamic calculations. In phototrophic microbial mats from Baja, Mexico, H2 partial pressures are instead controlled by the activity of light-sensitive H2-producing organisms. In consequence, H2 partial pressures within the system fluctuate by orders of magnitude on hour-long time scales. The differences in H2 cycling subsequently impact H2-sensitive microbial processes, such as methanogenesis. For example, the presence of sulfate in the organotrophic system always yielded low levels of H2 that were inhibitory to methanogenesis; however, the elevated levels of H2 in the phototrophic system favored methane production at significant levels, even in the presence of high sulfate concentrations. The myriad of other H2-sensitive microbial processes are expected to exhibit similar behavior.

Procalcitonin as a biomarker for severe Plasmodium falciparum disease: a critical appraisal of a semi-quantitative point-of-care test in a cohort of travellers with imported malaria.

PubMed

Hesselink, Dennis A; Burgerhart, Jan-Steven; Bosmans-Timmerarends, Hanna; Petit, Pieter; van Genderen, Perry J J

2009-09-01

Imported malaria occurs as a relatively rare event in developed countries. As a consequence, most clinicians have little experience in making clinical assessments of disease severity and decisions regarding the need for parenteral therapy or high-level monitoring. In this study, the diagnostic accuracy of procalcitonin (PCT) for severe Plasmodium falciparum disease was assessed in a cohort of 100 consecutive travellers with various species of imported malaria. In all patients, PCT was measured on admission with a semi-quantitative 'point-of-care' test. Patients with severe P. falciparum malaria had significantly higher median PCT levels on admission as compared with patients with uncomplicated P. falciparum disease. In addition, PCT levels in patients with non-falciparum malaria were also higher compared with patients with non-severe falciparum malaria but lower compared with severe P. falciparum malaria. At a cut-off point of 10 ng/mL, PCT had a sensitivity of 0,67 and a specificity of 0,94 for severe falciparum disease. However, at lower cut-off points the specificity and positive predictive value were rather poor although the sensitivity and negative predictive value remained high. Potential drawbacks in the interpretation of elevated PCT levels on admission may be caused by infections with non-falciparum species and by concomitant bacterial infections. Semi-quantitative determination of PCT on admission is of limited use in the initial clinical assessment of disease severity in travellers with imported malaria, especially in settings with limited experience with the treatment of malaria.

A cascaded QSAR model for efficient prediction of overall power conversion efficiency of all-organic dye-sensitized solar cells.

PubMed

Li, Hongzhi; Zhong, Ziyan; Li, Lin; Gao, Rui; Cui, Jingxia; Gao, Ting; Hu, Li Hong; Lu, Yinghua; Su, Zhong-Min; Li, Hui

2015-05-30

A cascaded model is proposed to establish the quantitative structure-activity relationship (QSAR) between the overall power conversion efficiency (PCE) and quantum chemical molecular descriptors of all-organic dye sensitizers. The cascaded model is a two-level network in which the outputs of the first level (JSC, VOC, and FF) are the inputs of the second level, and the ultimate end-point is the overall PCE of dye-sensitized solar cells (DSSCs). The model combines quantum chemical methods and machine learning methods, further including quantum chemical calculations, data division, feature selection, regression, and validation steps. To improve the efficiency of the model and reduce the redundancy and noise of the molecular descriptors, six feature selection methods (multiple linear regression, genetic algorithms, mean impact value, forward selection, backward elimination, and +n-m algorithm) are used with the support vector machine. The best established cascaded model predicts the PCE values of DSSCs with a MAE of 0.57 (%), which is about 10% of the mean value PCE (5.62%). The validation parameters according to the OECD principles are R(2) (0.75), Q(2) (0.77), and Qcv2 (0.76), which demonstrate the great goodness-of-fit, predictivity, and robustness of the model. Additionally, the applicability domain of the cascaded QSAR model is defined for further application. This study demonstrates that the established cascaded model is able to effectively predict the PCE for organic dye sensitizers with very low cost and relatively high accuracy, providing a useful tool for the design of dye sensitizers with high PCE. © 2015 Wiley Periodicals, Inc.

Evaluation of an ensemble of genetic models for prediction of a quantitative trait.

PubMed

Milton, Jacqueline N; Steinberg, Martin H; Sebastiani, Paola

2014-01-01

Many genetic markers have been shown to be associated with common quantitative traits in genome-wide association studies. Typically these associated genetic markers have small to modest effect sizes and individually they explain only a small amount of the variability of the phenotype. In order to build a genetic prediction model without fitting a multiple linear regression model with possibly hundreds of genetic markers as predictors, researchers often summarize the joint effect of risk alleles into a genetic score that is used as a covariate in the genetic prediction model. However, the prediction accuracy can be highly variable and selecting the optimal number of markers to be included in the genetic score is challenging. In this manuscript we present a strategy to build an ensemble of genetic prediction models from data and we show that the ensemble-based method makes the challenge of choosing the number of genetic markers more amenable. Using simulated data with varying heritability and number of genetic markers, we compare the predictive accuracy and inclusion of true positive and false positive markers of a single genetic prediction model and our proposed ensemble method. The results show that the ensemble of genetic models tends to include a larger number of genetic variants than a single genetic model and it is more likely to include all of the true genetic markers. This increased sensitivity is obtained at the price of a lower specificity that appears to minimally affect the predictive accuracy of the ensemble.

Quantification of photoacoustic microscopy images for ovarian cancer detection

NASA Astrophysics Data System (ADS)

Wang, Tianheng; Yang, Yi; Alqasemi, Umar; Kumavor, Patrick D.; Wang, Xiaohong; Sanders, Melinda; Brewer, Molly; Zhu, Quing

2014-03-01

In this paper, human ovarian tissues with malignant and benign features were imaged ex vivo by using an opticalresolution photoacoustic microscopy (OR-PAM) system. Several features were quantitatively extracted from PAM images to describe photoacoustic signal distributions and fluctuations. 106 PAM images from 18 human ovaries were classified by applying those extracted features to a logistic prediction model. 57 images from 9 ovaries were used as a training set to train the logistic model, and 49 images from another 9 ovaries were used to test our prediction model. We assumed that if one image from one malignant ovary was classified as malignant, it is sufficient to classify this ovary as malignant. For the training set, we achieved 100% sensitivity and 83.3% specificity; for testing set, we achieved 100% sensitivity and 66.7% specificity. These preliminary results demonstrate that PAM could be extremely valuable in assisting and guiding surgeons for in vivo evaluation of ovarian tissue.

Comparison of routine urinalysis and urine Gram stain for detection of bacteriuria in dogs.

PubMed

Way, Leilani Ireland; Sullivan, Lauren A; Johnson, Valerie; Morley, Paul S

2013-01-01

To determine the utility of performing urine Gram stain for detection of bacteriuria compared to routine urine sediment examination and bacterial aerobic urine culture. Prospective, observational study. University teaching hospital. Urine samples acquired via cystocentesis through convenience sampling from 103 dogs presenting to a tertiary referral institution. All samples underwent routine urinalysis, including sediment examination, as well as urine Gram stain and quantitative bacterial aerobic urine culture. The urine Gram stain demonstrated improved sensitivity (96% versus 76%), specificity (100% versus 77%), positive predictive value (100% versus 83%), and negative predictive value (93% versus 69%) when identifying bacteriuria, compared to routine urine sediment examination. The urine Gram stain is highly sensitive and specific when detecting the presence of bacteria in canine urine samples. Gram staining should be considered when bacteriuria is highly suspected and requires rapid identification while bacterial culture is pending. © Veterinary Emergency and Critical Care Society 2013.

The Bragg Reflection Polarimeter On the Gravity and Extreme Magnetism Small Explorer Mission

NASA Astrophysics Data System (ADS)

Allured, Ryan; Griffiths, S.; Daly, R.; Prieskorn, Z.; Marlowe, H.; Kaaret, P.; GEMS Team

2011-09-01

The strong gravity associated with black holes warps the spacetime outside of the event horizon, and it is predicted that this will leave characteristic signatures on the polarization of X-ray emission originating in the accretion disk. The Gravity and Extreme Magnetism Small Explorer (GEMS) mission will be the first observatory with the capability to make polarization measurements with enough sensitivity to quantitatively test this prediction. Students at the University of Iowa are currently working on the development of the Bragg Reflection Polarimeter (BRP), a soft X-ray polarimeter sensitive at 500 eV, that is the student experiment on GEMS. The BRP will complement the main experiment by making a polarization measurement from accreting black holes below the main energy band (2-10 keV). This measurement will constrain the inclination of the accretion disk and tighten measurements of black hole spin.

Numerical simulation of damage and progressive failures in composite laminates using the layerwise plate theory

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

Reddy, Y.S.

1992-01-01

The failure behavior of composite laminates is modeled numerically using the Generalized Layerwise Plate Theory (GLPT) of Reddy and a progressive failure algorithm. The Layerwise Theory of Reddy assumes a piecewise continuous displacement field through the thickness of the laminate and therefore has the ability to capture the interlaminar stress fields near the free edges and cut outs more accurately. The progressive failure algorithm is based on the assumption that the material behaves like a stable progressively fracturing solid. A three-dimensional stiffness reduction scheme is developed and implemented to study progressive failures in composite laminates. The effect of various parametersmore » such as out-of-plane material properties, boundary conditions, and stiffness reduction methods on the failure stresses and strains of a quasi-isotropic composite laminate with free edges subjected to tensile loading is studied. The ultimate stresses and strains predicted by the Generalized Layerwise Plate Theory (GLPT) and the more widely used First Order Shear Deformation Theory (FSDT) are compared with experimental results. The predictions of the GLPT are found to be in good agreement with the experimental results both qualitatively and quantitatively, while the predictions of FSDT are found to be different from experimental results both qualitatively and quantitatively. The predictive ability of various phenomenological failure criteria is evaluated with reference to the experimental results available in the literature. The effect of geometry of the test specimen and the displacement boundary conditions at the grips on the ultimate stresses and strains of a composite laminate under compressive loading is studied. The ultimate stresses and strains are found to be quite sensitive to the geometry of the test specimen and the displacement boundary conditions at the grips. The degree of sensitivity is observed to depend strongly on the lamination sequence.« less

Anti-signal recognition particle autoantibody ELISA validation and clinical associations.

PubMed

Aggarwal, Rohit; Oddis, Chester V; Goudeau, Danielle; Fertig, Noreen; Metes, Ilinca; Stephens, Chad; Qi, Zengbiao; Koontz, Diane; Levesque, Marc C

2015-07-01

The aim of this study was to develop and validate a quantitative anti-signal recognition particle (SRP) autoantibody serum ELISA in patients with myositis and longitudinal association with myositis disease activity. We developed a serum ELISA using recombinant purified full-length human SRP coated on ELISA plates and a secondary antibody that bound human IgG to detect anti-SRP binding. Protein immunoprecipitation was used as the gold standard for the presence of anti-SRP. Serum samples from three groups were analysed: SRP(+) myositis subjects by immunoprecipitation, SRP(-) myositis subjects by immunoprecipitation and non-myositis controls. The ELISA's sensitivity, specificity, positive predictive value and negative predictive value were evaluated. Percentage agreement and test-retest reliability were assessed. Serial samples from seven SRP immunoprecipitation-positive subjects were also tested, along with serum muscle enzymes and manual muscle testing. Using immunoprecipitation, we identified 26 SRP(+) myositis patients and 77 SRP(-) controls (including 38 patients with necrotizing myopathy). Non-myositis control patients included SLE (n = 4) and SSc (n = 7) patients. Anti-SRP positivity by ELISA showed strong agreement (97.1%) with immunoprecipitation (κ = 0.94). The sensitivity, specificity, positive predictive value, and negative predictive value of the anti-SRP ELISA were 88, 100, 100 and 96, respectively. The area under the curve was 0.94, and test-retest reliability was strong (r = 0.91, P < 0.001). Serial samples showed that anti-SRP levels paralleled changes in muscle enzymes and manual muscle testing. We developed a quantitative ELISA for detecting serum anti-SRP autoantibodies and validated the assay in myositis. Longitudinal assessment of SRP levels by ELISA may be a useful biomarker for disease activity. © The Author 2014. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Analysis of bacterial migration. 2: Studies with multiple attractant gradients

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

Strauss, I.; Frymier, P.D.; Hahn, C.M.

1995-02-01

Many motile bacteria exhibit chemotaxis, the ability to bias their random motion toward or away from increasing concentrations of chemical substances which benefit or inhibit their survival, respectively. Since bacteria encounter numerous chemical concentration gradients simultaneously in natural surroundings, it is necessary to know quantitatively how a bacterial population responds in the presence of more than one chemical stimulus to develop predictive mathematical models describing bacterial migration in natural systems. This work evaluates three hypothetical models describing the integration of chemical signals from multiple stimuli: high sensitivity, maximum signal, and simple additivity. An expression for the tumbling probability for individualmore » stimuli is modified according to the proposed models and incorporated into the cell balance equation for a 1-D attractant gradient. Random motility and chemotactic sensitivity coefficients, required input parameters for the model, are measured for single stimulus responses. Theoretical predictions with the three signal integration models are compared to the net chemotactic response of Escherichia coli to co- and antidirectional gradients of D-fucose and [alpha]-methylaspartate in the stopped-flow diffusion chamber assay. Results eliminate the high-sensitivity model and favor the simple additivity over the maximum signal. None of the simple models, however, accurately predict the observed behavior, suggesting a more complex model with more steps in the signal processing mechanism is required to predict responses to multiple stimuli.« less

Validation of automatic wheeze detection in patients with obstructed airways and in healthy subjects.

PubMed

Guntupalli, Kalpalatha K; Alapat, Philip M; Bandi, Venkata D; Kushnir, Igal

2008-12-01

Computerized lung-sound analysis is a sensitive and quantitative method to identify wheezing by its typical pattern on spectral analysis. We evaluated the accuracy of the VRI, a multi-sensor, computer-based device with an automated technique of wheeze detection. The method was validated in 100 sound files from seven subjects with asthma or chronic obstructive pulmonary disease and seven healthy subjects by comparison of auscultation findings, examination of audio files, and computer detection of wheezes. Three blinded physicians identified 40 sound files with wheezes and 60 sound files without wheezes. Sensitivity and specificity were 83% and 85%, respectively. Negative predictive value and positive predictive value were 89% and 79%, respectively. Overall inter-rater agreement was 84%. False positive cases were found to contain sounds that simulate wheezes, such as background noises with high frequencies or strong noises from the throat that could be heard and identified without a stethoscope. The present findings demonstrate that the wheeze detection algorithm has good accuracy, sensitivity, specificity, negative predictive value and positive predictive value for wheeze detection in regional analyses with a single sensor and multiple sensors. Results are similar to those reported in the literature. The device is user-friendly, requires minimal patient effort, and, distinct from other devices, it provides a dynamic image of breath sound distribution with wheeze detection output in less than 1 minute.

The Value of Diffusion-Weighted Imaging in Combination With Conventional Magnetic Resonance Imaging for Improving Tumor Detection for Early Cervical Carcinoma Treated With Fertility-Sparing Surgery.

PubMed

Li, Xiulei; Wang, Ling; Li, Yong; Song, Peiji

2017-10-01

This study aimed to investigate the value of diffusion-weighted imaging (DWI) in combination with conventional magnetic resonance imaging (MRI) for improving tumor detection in young patients treated with fertility-sparing surgery because of early cervical carcinoma. Fifty-four patients with stage Ia or Ib1 cervical carcinoma were enrolled into this study. Magnetic resonance examinations were performed for these patients using conventional MRI (including T1-weighted imaging, T2-weighted imaging, and dynamic contrast-enhanced MRI) and DWI. The apparent diffusion coefficient (ADC) values of cervical carcinoma were analyzed quantitatively and compared with that of adjacent epithelium. Sensitivity, positive predictive value, and accuracy of 2 sets of MRI sequences were calculated on the basis of histologic results, and the diagnostic ability of conventional MRI/DWI combinations was compared with that of conventional MRI. The mean ADC value from cervical carcinoma (mean, 786 × 10 mm/s ± 100) was significantly lower than that from adjacent epithelium (mean, 1352 × 10 mm/s ± 147) (P = 0.01). When the threshold ADC value set as 1010 × 10 mm/s, the sensitivity and specificity for differentiating cervical carcinoma from nontumor epithelium were 78.2% and 67.2%, respectively. The sensitivity and accuracy of conventional MRI for tumor detection were 76.0% and 70.4%, whereas the sensitivity and accuracy of conventional MRI/DWI combinations were 91.7% and 90.7%, respectively. Conventional MRI/DWI combinations revealed a positive predictive value of 97.8% and only 4 false-negative findings. The addition of DWI to conventional MRI considerably improves the sensitivity and accuracy of tumor detection in young patients treated with fertility-sparing surgery, which supports the inclusion quantitative analysis of ADC value in routine MRI protocol before fertility-sparing surgery.

Generalized Polynomial Chaos Based Uncertainty Quantification for Planning MRgLITT Procedures

PubMed Central

Fahrenholtz, S.; Stafford, R. J.; Maier, F.; Hazle, J. D.; Fuentes, D.

2014-01-01

Purpose A generalized polynomial chaos (gPC) method is used to incorporate constitutive parameter uncertainties within the Pennes representation of bioheat transfer phenomena. The stochastic temperature predictions of the mathematical model are critically evaluated against MR thermometry data for planning MR-guided Laser Induced Thermal Therapies (MRgLITT). Methods Pennes bioheat transfer model coupled with a diffusion theory approximation of laser tissue interaction was implemented as the underlying deterministic kernel. A probabilistic sensitivity study was used to identify parameters that provide the most variance in temperature output. Confidence intervals of the temperature predictions are compared to MR temperature imaging (MRTI) obtained during phantom and in vivo canine (n=4) MRgLITT experiments. The gPC predictions were quantitatively compared to MRTI data using probabilistic linear and temporal profiles as well as 2-D 60 °C isotherms. Results Within the range of physically meaningful constitutive values relevant to the ablative temperature regime of MRgLITT, the sensitivity study indicated that the optical parameters, particularly the anisotropy factor, created the most variance in the stochastic model's output temperature prediction. Further, within the statistical sense considered, a nonlinear model of the temperature and damage dependent perfusion, absorption, and scattering is captured within the confidence intervals of the linear gPC method. Multivariate stochastic model predictions using parameters with the dominant sensitivities show good agreement with experimental MRTI data. Conclusions Given parameter uncertainties and mathematical modeling approximations of the Pennes bioheat model, the statistical framework demonstrates conservative estimates of the therapeutic heating and has potential for use as a computational prediction tool for thermal therapy planning. PMID:23692295

Development of a quantitative diagnostic method of estrogen receptor expression levels by immunohistochemistry using organic fluorescent material-assembled nanoparticles

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

Gonda, Kohsuke, E-mail: gonda@med.tohoku.ac.jp; Miyashita, Minoru; Watanabe, Mika

2012-09-28

Highlights: Black-Right-Pointing-Pointer Organic fluorescent material-assembled nanoparticles for IHC were prepared. Black-Right-Pointing-Pointer New nanoparticle fluorescent intensity was 10.2-fold greater than Qdot655. Black-Right-Pointing-Pointer Nanoparticle staining analyzed a wide range of ER expression levels in tissue. Black-Right-Pointing-Pointer Nanoparticle staining enhanced the quantitative sensitivity for ER diagnosis. -- Abstract: The detection of estrogen receptors (ERs) by immunohistochemistry (IHC) using 3,3 Prime -diaminobenzidine (DAB) is slightly weak as a prognostic marker, but it is essential to the application of endocrine therapy, such as antiestrogen tamoxifen-based therapy. IHC using DAB is a poor quantitative method because horseradish peroxidase (HRP) activity depends on reaction time, temperature andmore » substrate concentration. However, IHC using fluorescent material provides an effective method to quantitatively use IHC because the signal intensity is proportional to the intensity of the photon excitation energy. However, the high level of autofluorescence has impeded the development of quantitative IHC using fluorescence. We developed organic fluorescent material (tetramethylrhodamine)-assembled nanoparticles for IHC. Tissue autofluorescence is comparable to the fluorescence intensity of quantum dots, which are the most representative fluorescent nanoparticles. The fluorescent intensity of our novel nanoparticles was 10.2-fold greater than quantum dots, and they did not bind non-specifically to breast cancer tissues due to the polyethylene glycol chain that coated their surfaces. Therefore, the fluorescent intensity of our nanoparticles significantly exceeded autofluorescence, which produced a significantly higher signal-to-noise ratio on IHC-imaged cancer tissues than previous methods. Moreover, immunostaining data from our nanoparticle fluorescent IHC and IHC with DAB were compared in the same region of adjacent tissues sections to quantitatively examine the two methods. The results demonstrated that our nanoparticle staining analyzed a wide range of ER expression levels with higher accuracy and quantitative sensitivity than DAB staining. This enhancement in the diagnostic accuracy and sensitivity for ERs using our immunostaining method will improve the prediction of responses to therapies that target ERs and progesterone receptors that are induced by a downstream ER signal.« less

Prediction of rodent carcinogenic potential of naturally occurring chemicals in the human diet using high-throughput QSAR predictive modeling

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

Valerio, Luis G.; Arvidson, Kirk B.; Chanderbhan, Ronald F.

2007-07-01

Consistent with the U.S. Food and Drug Administration (FDA) Critical Path Initiative, predictive toxicology software programs employing quantitative structure-activity relationship (QSAR) models are currently under evaluation for regulatory risk assessment and scientific decision support for highly sensitive endpoints such as carcinogenicity, mutagenicity and reproductive toxicity. At the FDA's Center for Food Safety and Applied Nutrition's Office of Food Additive Safety and the Center for Drug Evaluation and Research's Informatics and Computational Safety Analysis Staff (ICSAS), the use of computational SAR tools for both qualitative and quantitative risk assessment applications are being developed and evaluated. One tool of current interest ismore » MDL-QSAR predictive discriminant analysis modeling of rodent carcinogenicity, which has been previously evaluated for pharmaceutical applications by the FDA ICSAS. The study described in this paper aims to evaluate the utility of this software to estimate the carcinogenic potential of small, organic, naturally occurring chemicals found in the human diet. In addition, a group of 19 known synthetic dietary constituents that were positive in rodent carcinogenicity studies served as a control group. In the test group of naturally occurring chemicals, 101 were found to be suitable for predictive modeling using this software's discriminant analysis modeling approach. Predictions performed on these compounds were compared to published experimental evidence of each compound's carcinogenic potential. Experimental evidence included relevant toxicological studies such as rodent cancer bioassays, rodent anti-carcinogenicity studies, genotoxic studies, and the presence of chemical structural alerts. Statistical indices of predictive performance were calculated to assess the utility of the predictive modeling method. Results revealed good predictive performance using this software's rodent carcinogenicity module of over 1200 chemicals, comprised primarily of pharmaceutical, industrial and some natural products developed under an FDA-MDL cooperative research and development agreement (CRADA). The predictive performance for this group of dietary natural products and the control group was 97% sensitivity and 80% concordance. Specificity was marginal at 53%. This study finds that the in silico QSAR analysis employing this software's rodent carcinogenicity database is capable of identifying the rodent carcinogenic potential of naturally occurring organic molecules found in the human diet with a high degree of sensitivity. It is the first study to demonstrate successful QSAR predictive modeling of naturally occurring carcinogens found in the human diet using an external validation test. Further test validation of this software and expansion of the training data set for dietary chemicals will help to support the future use of such QSAR methods for screening and prioritizing the risk of dietary chemicals when actual animal data are inadequate, equivocal, or absent.« less

Diagnostic value of "dysphagia limit" for neurogenic dysphagia: 17 years of experience in 1278 adults.

PubMed

Aydogdu, Ibrahim; Kiylioglu, Nefati; Tarlaci, Sultan; Tanriverdi, Zeynep; Alpaydin, Sezin; Acarer, Ahmet; Baysal, Leyla; Arpaci, Esra; Yuceyar, Nur; Secil, Yaprak; Ozdemirkiran, Tolga; Ertekin, Cumhur

2015-03-01

Neurogenic dysphagia (ND) is a prevalent condition that accounts for significant mortality and morbidity worldwide. Screening and follow-up are critical for early diagnosis and management which can mitigate its complications and be cost-saving. The aims of this study are to provide a comprehensive investigation of the dysphagia limit (DL) in a large diverse cohort and to provide a longitudinal assessment of dysphagia in a subset of subjects. We developed a quantitative and noninvasive method for objective assessment of dysphagia by using laryngeal sensor and submental electromyography. DL is the volume at which second or more swallows become necessary to swallow the whole amount of bolus. This study represents 17 years experience with the DL approach in assessing ND in a cohort of 1278 adult subjects consisting of 292 healthy controls, 784 patients with dysphagia, and 202 patients without dysphagia. A total of 192 of all patients were also reevaluated longitudinally over a period of 1-19 months. DL has 92% sensitivity, 91% specificity, 94% positive predictive value, and 88% negative predictive value with an accuracy of 0.92. Patients with ALS, stroke, and movement disorders have the highest sensitivity (85-97%) and positive predictive value (90-99%). The clinical severity of dysphagia has significant negative correlation with DL (r=-0.67, p<0.0001). We propose the DL as a reliable, quick, noninvasive, quantitative test to detect and follow both clinical and subclinical dysphagia and it can be performed in an EMG laboratory. Our study provides specific quantitative features of DL test that can be readily utilized by the neurologic community and nominates DL as an objective and robust method to evaluate dysphagia in a wide range of neurologic conditions. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Modeling ready biodegradability of fragrance materials.

PubMed

Ceriani, Lidia; Papa, Ester; Kovarich, Simona; Boethling, Robert; Gramatica, Paola

2015-06-01

In the present study, quantitative structure activity relationships were developed for predicting ready biodegradability of approximately 200 heterogeneous fragrance materials. Two classification methods, classification and regression tree (CART) and k-nearest neighbors (kNN), were applied to perform the modeling. The models were validated with multiple external prediction sets, and the structural applicability domain was verified by the leverage approach. The best models had good sensitivity (internal ≥80%; external ≥68%), specificity (internal ≥80%; external 73%), and overall accuracy (≥75%). Results from the comparison with BIOWIN global models, based on group contribution method, show that specific models developed in the present study perform better in prediction than BIOWIN6, in particular for the correct classification of not readily biodegradable fragrance materials. © 2015 SETAC.

Universally Sloppy Parameter Sensitivities in Systems Biology Models

PubMed Central

Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P

2007-01-01

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a “sloppy” spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters. PMID:17922568

Universally sloppy parameter sensitivities in systems biology models.

PubMed

Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P

2007-10-01

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

Emission Computed Tomography: A New Technique for the Quantitative Physiologic Study of Brain and Heart in Vivo

DOE R&D Accomplishments Database

Phelps, M. E.; Hoffman, E. J.; Huang, S. C.; Schelbert, H. R.; Kuhl, D. E.

1978-01-01

Emission computed tomography can provide a quantitative in vivo measurement of regional tissue radionuclide tracer concentrations. This facility when combined with physiologic models and radioactively labeled physiologic tracers that behave in a predictable manner allow measurement of a wide variety of physiologic variables. This integrated technique has been referred to as Physiologic Tomography (PT). PT requires labeled compounds which trace physiologic processes in a known and predictable manner, and physiologic models which are appropriately formulated and validated to derive physiologic variables from ECT data. In order to effectively achieve this goal, PT requires an ECT system that is capable of performing truly quantitative or analytical measurements of tissue tracer concentrations and which has been well characterized in terms of spatial resolution, sensitivity and signal to noise ratios in the tomographic image. This paper illustrates the capabilities of emission computed tomography and provides examples of physiologic tomography for the regional measurement of cerebral and myocardial metabolic rate for glucose, regional measurement of cerebral blood volume, gated cardiac blood pools and capillary perfusion in brain and heart. Studies on patients with stroke and myocardial ischemia are also presented.

Issues in Quantitative Analysis of Ultraviolet Imager (UV) Data: Airglow

NASA Technical Reports Server (NTRS)

Germany, G. A.; Richards, P. G.; Spann, J. F.; Brittnacher, M. J.; Parks, G. K.

1999-01-01

The GGS Ultraviolet Imager (UVI) has proven to be especially valuable in correlative substorm, auroral morphology, and extended statistical studies of the auroral regions. Such studies are based on knowledge of the location, spatial, and temporal behavior of auroral emissions. More quantitative studies, based on absolute radiometric intensities from UVI images, require a more intimate knowledge of the instrument behavior and data processing requirements and are inherently more difficult than studies based on relative knowledge of the oval location. In this study, UVI airglow observations are analyzed and compared with model predictions to illustrate issues that arise in quantitative analysis of UVI images. These issues include instrument calibration, long term changes in sensitivity, and imager flat field response as well as proper background correction. Airglow emissions are chosen for this study because of their relatively straightforward modeling requirements and because of their implications for thermospheric compositional studies. The analysis issues discussed here, however, are identical to those faced in quantitative auroral studies.

Skin prick testing predicts peanut challenge outcome in previously allergic or sensitized children with low serum peanut-specific IgE antibody concentration.

PubMed

Nolan, Richard C; Richmond, Peter; Prescott, Susan L; Mallon, Dominic F; Gong, Grace; Franzmann, Annkathrin M; Naidoo, Rama; Loh, Richard K S

2007-05-01

Peanut allergy is transient in some children but it is not clear whether quantitating peanut-specific IgE by Skin Prick Test (SPT) adds additional information to fluorescent-enzyme immunoassay (FEIA) in discriminating between allergic and tolerant children. To investigate whether SPT with a commercial extract or fresh foods adds additional predictive information for peanut challenge in children with a low FEIA (<10 k UA/L) who were previously sensitized, or allergic to peanuts. Children from a hospital-based allergy service who were previously sensitized or allergic to peanuts were invited to undergo a peanut challenge unless they had a serum peanut-specific IgE>10 k UA/L, a previous severe reaction, or a recent reaction to peanuts (within two years). SPT with a commercial extract, raw and roasted saline soaked peanuts was performed immediately prior to open challenge in hospital with increasing quantity of peanuts until total of 26.7 g of peanut was consumed. A positive challenge consisted of an objective IgE mediated reaction occurring during the observation period. 54 children (median age of 6.3 years) were admitted for a challenge. Nineteen challenges were positive, 27 negative, five were indeterminate and three did not proceed after SPT. Commercial and fresh food extracts provided similar diagnostic information. A wheal diameter of >or=7 mm of the commercial extract predicted an allergic outcome with specificity 97%, positive predictive value 93% and sensitivity 83%. There was a tendency for an increase in SPT wheal since initial diagnosis in children who remained allergic to peanuts while it decreased in those with a negative challenge. The outcome of a peanut challenge in peanut sensitized or previously allergic children with a low FEIA can be predicted by SPT. In this cohort, not challenging children with a SPT wheal of >or=7 mm would have avoided 15 of 18 positive challenges and denied a challenge to one out of 27 tolerant children.

Current V3 genotyping algorithms are inadequate for predicting X4 co-receptor usage in clinical isolates.

PubMed

Low, Andrew J; Dong, Winnie; Chan, Dennison; Sing, Tobias; Swanstrom, Ronald; Jensen, Mark; Pillai, Satish; Good, Benjamin; Harrigan, P Richard

2007-09-12

Integrating CCR5 antagonists into clinical practice would benefit from accurate assays of co-receptor usage (CCR5 versus CXCR4) with fast turnaround and low cost. Published HIV V3-loop based predictors of co-receptor usage were compared with actual phenotypic tropism results in a large cohort of antiretroviral naive individuals to determine accuracy on clinical samples and identify areas for improvement. Aligned HIV envelope V3 loop sequences (n = 977), derived by bulk sequencing were analyzed by six methods: the 11/25 rule; a neural network (NN), two support vector machines, and two subtype-B position specific scoring matrices (PSSM). Co-receptor phenotype results (Trofile Co-receptor Phenotype Assay; Monogram Biosciences) were stratified by CXCR4 relative light unit (RLU) readout and CD4 cell count. Co-receptor phenotype was available for 920 clinical samples with V3 genotypes having fewer than seven amino acid mixtures (n = 769 R5; n = 151 X4-capable). Sensitivity and specificity for predicting X4 capacity were evaluated for the 11/25 rule (30% sensitivity/93% specificity), NN (44%/88%), PSSM(sinsi) (34%/96%), PSSM(x4r5) (24%/97%), SVMgenomiac (22%/90%) and SVMgeno2pheno (50%/89%). Quantitative increases in sensitivity could be obtained by optimizing the cut-off for methods with continuous output (PSSM methods), and/or integrating clinical data (CD4%). Sensitivity was directly proportional to strength of X4 signal in the phenotype assay (P < 0.05). Current default implementations of co-receptor prediction algorithms are inadequate for predicting HIV X4 co-receptor usage in clinical samples, particularly those X4 phenotypes with low CXCR4 RLU signals. Significant improvements can be made to genotypic predictors, including training on clinical samples, using additional data to improve predictions and optimizing cutoffs and increasing genotype sensitivity.

Smaller = Denser, and the Brain Knows It: Natural Statistics of Object Density Shape Weight Expectations

PubMed Central

Peters, Megan A. K.; Balzer, Jonathan; Shams, Ladan

2015-01-01

If one nondescript object’s volume is twice that of another, is it necessarily twice as heavy? As larger objects are typically heavier than smaller ones, one might assume humans use such heuristics in preparing to lift novel objects if other informative cues (e.g., material, previous lifts) are unavailable. However, it is also known that humans are sensitive to statistical properties of our environments, and that such sensitivity can bias perception. Here we asked whether statistical regularities in properties of liftable, everyday objects would bias human observers’ predictions about objects’ weight relationships. We developed state-of-the-art computer vision techniques to precisely measure the volume of everyday objects, and also measured their weight. We discovered that for liftable man-made objects, “twice as large” doesn’t mean “twice as heavy”: Smaller objects are typically denser, following a power function of volume. Interestingly, this “smaller is denser” relationship does not hold for natural or unliftable objects, suggesting some ideal density range for objects designed to be lifted. We then asked human observers to predict weight relationships between novel objects without lifting them; crucially, these weight predictions quantitatively match typical weight relationships shown by similarly-sized objects in everyday environments. These results indicate that the human brain represents the statistics of everyday objects and that this representation can be quantitatively abstracted and applied to novel objects. Finally, that the brain possesses and can use precise knowledge of the nonlinear association between size and weight carries important implications for implementation of forward models of motor control in artificial systems. PMID:25768977

The guinea-pig skin sensitization test revisited: an evaluation formula to predict possible sensitization levels for eight chemicals used in household products.

PubMed

Momma, J; Kitajima, S; Inoue, T

1998-02-20

In predicting human skin sensitization due to possible risky chemicals, it is not sufficient to evaluate solely the minimum induction dose (MID) or the standard challenge dose (SCD) in the Guinea Pig Maximization Test (GPMT). Nakamura et al. (1994) (Nakamura, A., Momma, J., Sekiguchi, H., Noda, T., Yamano, T., Kaniwa, M., Kojima, S., Tsuda, M., Kurokawa, Y., 1994. A new protocol and criteria for quantitative determination of sensitization potencies of chemicals by guinea pig maximization test. Contact Dermatitis 31, 72-85) previously measured the residual dose of chemicals in the products implicated in human allergic accidents, and stated that '... the level of chemical in the products (direct exposure-dose = DED) was similar to or higher than value of sensitization potency.' However, several of the chemicals listed in their article, show an even lower value of sensitization potency than the DED, although a potential correlation between results of the GPMT and the DED was seemed to be evident; a key question about the essential rule of those parameters therefore remains open. Using the data of Nakamura et al. (1994), we analyzed the functional rules of the three independent parameters, the MID, the SCD, and the DED on which the GPMT is based. Calculations of the degree of allergic reactions elicited in humans provided a range of discrimination constants (D) using the formula; D = DED/(MID*SCD). Possible human allergic accidents may be predicted when the dose of a candidate chemical in a chemical product (equal to DED) exceeds the value; D*(MID*SCD), following the correct evaluation of the MID as well as the SCD.

Micellar modification of drug stability: analysis of the effect of hexadecyltrimethylammonium halides on the rate of degradation of cephaclor.

PubMed

Oliveira, A G; Cuccovia, I M; Chaimovich, H

1990-01-01

The intra- and intermolecular rates of degradation of cephaclor were determined with and without hexadecyltrimethylammonium bromide (CTABr). Micellar-derived spectral shifts were used to measure the association of the ionic forms as well as to determine the effect of CTABr on the apparent acid dissociation constant of the antibiotic. The rate of degradation of cephaclor increased with detergent and was salt sensitive. Micellar effects were analyzed quantitatively within the framework of the pseudophase ion exchange model. All experimental data were fitted to this model which was used to predict the combined effects of pH and detergent concentration. Micelles increased the rate of OH- attack on cephaclor; most of the effect was due to the concentration of reagents in the micellar pseudophase. The intramolecular degradation was catalyzed 25-fold by micelles, and a working hypothesis to rationalize this effect is proposed. The results demonstrate that quantitative analysis can be utilized to assess and predict effects of detergents on drug stability.

Importance of Multimodal MRI in Characterizing Brain Tissue and Its Potential Application for Individual Age Prediction.

PubMed

Cherubini, Andrea; Caligiuri, Maria Eugenia; Peran, Patrice; Sabatini, Umberto; Cosentino, Carlo; Amato, Francesco

2016-09-01

This study presents a voxel-based multiple regression analysis of different magnetic resonance image modalities, including anatomical T1-weighted, T2(*) relaxometry, and diffusion tensor imaging. Quantitative parameters sensitive to complementary brain tissue alterations, including morphometric atrophy, mineralization, microstructural damage, and anisotropy loss, were compared in a linear physiological aging model in 140 healthy subjects (range 20-74 years). The performance of different predictors and the identification of the best biomarker of age-induced structural variation were compared without a priori anatomical knowledge. The best quantitative predictors in several brain regions were iron deposition and microstructural damage, rather than macroscopic tissue atrophy. Age variations were best resolved with a combination of markers, suggesting that multiple predictors better capture age-induced tissue alterations. The results of the linear model were used to predict apparent age in different regions of individual brain. This approach pointed to a number of novel applications that could potentially help highlighting areas particularly vulnerable to disease.

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

Digital PCR quantification of MGMT methylation refines prediction of clinical benefit from alkylating agents in glioblastoma and metastatic colorectal cancer.

PubMed

Barault, L; Amatu, A; Bleeker, F E; Moutinho, C; Falcomatà, C; Fiano, V; Cassingena, A; Siravegna, G; Milione, M; Cassoni, P; De Braud, F; Rudà, R; Soffietti, R; Venesio, T; Bardelli, A; Wesseling, P; de Witt Hamer, P; Pietrantonio, F; Siena, S; Esteller, M; Sartore-Bianchi, A; Di Nicolantonio, F

2015-09-01

O(6)-methyl-guanine-methyl-transferase (MGMT) silencing by promoter methylation may identify cancer patients responding to the alkylating agents dacarbazine or temozolomide. We evaluated the prognostic and predictive value of MGMT methylation testing both in tumor and cell-free circulating DNA (cfDNA) from plasma samples using an ultra-sensitive two-step digital PCR technique (methyl-BEAMing). Results were compared with two established techniques, methylation-specific PCR (MSP) and Bs-pyrosequencing. Thresholds for MGMT methylated status for each technique were established in a training set of 98 glioblastoma (GBM) patients. The prognostic and the predictive value of MGMT methylated status was validated in a second cohort of 66 GBM patients treated with temozolomide in which methyl-BEAMing displayed a better specificity than the other techniques. Cutoff values of MGMT methylation specific for metastatic colorectal cancer (mCRC) tissue samples were established in a cohort of 60 patients treated with dacarbazine. In mCRC, both quantitative assays methyl-BEAMing and Bs-pyrosequencing outperformed MSP, providing better prediction of treatment response and improvement in progression-free survival (PFS) (P < 0.001). Ability of methyl-BEAMing to identify responding patients was validated in a cohort of 23 mCRC patients treated with temozolomide and preselected for MGMT methylated status according to MSP. In mCRC patients treated with dacarbazine, exploratory analysis of cfDNA by methyl-BEAMing showed that MGMT methylation was associated with better response and improved median PFS (P = 0.008). Methyl-BEAMing showed high reproducibility, specificity and sensitivity and was applicable to formalin-fixed paraffin-embedded tissues and cfDNA. This study supports the quantitative assessment of MGMT methylation for clinical purposes since it could refine prediction of response to alkylating agents. © The Author 2015. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Rising CO2 Levels Will Intensify Phytoplankton Blooms in Eutrophic and Hypertrophic Lakes

PubMed Central

Verspagen, Jolanda M. H.; Van de Waal, Dedmer B.; Finke, Jan F.; Visser, Petra M.; Van Donk, Ellen; Huisman, Jef

2014-01-01

Harmful algal blooms threaten the water quality of many eutrophic and hypertrophic lakes and cause severe ecological and economic damage worldwide. Dense blooms often deplete the dissolved CO2 concentration and raise pH. Yet, quantitative prediction of the feedbacks between phytoplankton growth, CO2 drawdown and the inorganic carbon chemistry of aquatic ecosystems has received surprisingly little attention. Here, we develop a mathematical model to predict dynamic changes in dissolved inorganic carbon (DIC), pH and alkalinity during phytoplankton bloom development. We tested the model in chemostat experiments with the freshwater cyanobacterium Microcystis aeruginosa at different CO2 levels. The experiments showed that dense blooms sequestered large amounts of atmospheric CO2, not only by their own biomass production but also by inducing a high pH and alkalinity that enhanced the capacity for DIC storage in the system. We used the model to explore how phytoplankton blooms of eutrophic waters will respond to rising CO2 levels. The model predicts that (1) dense phytoplankton blooms in low- and moderately alkaline waters can deplete the dissolved CO2 concentration to limiting levels and raise the pH over a relatively wide range of atmospheric CO2 conditions, (2) rising atmospheric CO2 levels will enhance phytoplankton blooms in low- and moderately alkaline waters with high nutrient loads, and (3) above some threshold, rising atmospheric CO2 will alleviate phytoplankton blooms from carbon limitation, resulting in less intense CO2 depletion and a lesser increase in pH. Sensitivity analysis indicated that the model predictions were qualitatively robust. Quantitatively, the predictions were sensitive to variation in lake depth, DIC input and CO2 gas transfer across the air-water interface, but relatively robust to variation in the carbon uptake mechanisms of phytoplankton. In total, these findings warn that rising CO2 levels may result in a marked intensification of phytoplankton blooms in eutrophic and hypertrophic waters. PMID:25119996

Quantitative structural MRI for early detection of Alzheimer’s disease

PubMed Central

McEvoy, Linda K; Brewer, James B

2011-01-01

Alzheimer’s disease (AD) is a common progressive neurodegenerative disorder that is not currently diagnosed until a patient reaches the stage of dementia. There is a pressing need to identify AD at an earlier stage, so that treatment, when available, can begin early. Quantitative structural MRI is sensitive to the neurodegeneration that occurs in mild and preclinical AD, and is predictive of decline to dementia in individuals with mild cognitive impairment. Objective evidence of ongoing brain atrophy will be critical for risk/benefit decisions once potentially aggressive, disease-modifying treatments become available. Recent advances have paved the way for the use of quantitative structural MRI in clinical practice, and initial clinical use has been promising. However, further experience with these measures in the relatively unselected patient populations seen in clinical practice is needed to complete translation of the recent enormous advances in scientific knowledge of AD into the clinical realm. PMID:20977326

PCR Inhibition of a Quantitative PCR for Detection of Mycobacterium avium Subspecies Paratuberculosis DNA in Feces: Diagnostic Implications and Potential Solutions

PubMed Central

Acharya, Kamal R.; Dhand, Navneet K.; Whittington, Richard J.; Plain, Karren M.

2017-01-01

Molecular tests such as polymerase chain reaction (PCR) are increasingly being applied for the diagnosis of Johne’s disease, a chronic intestinal infection of ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP). Feces, as the primary test sample, presents challenges in terms of effective DNA isolation, with potential for PCR inhibition and ultimately for reduced analytical and diagnostic sensitivity. However, limited evidence is available regarding the magnitude and diagnostic implications of PCR inhibition for the detection of MAP in feces. This study aimed to investigate the presence and diagnostic implications of PCR inhibition in a quantitative PCR assay for MAP (High-throughput Johne’s test) to investigate the characteristics of samples prone to inhibition and to identify measures that can be taken to overcome this. In a study of fecal samples derived from a high prevalence, endemically infected cattle herd, 19.94% of fecal DNA extracts showed some evidence of inhibition. Relief of inhibition by a five-fold dilution of the DNA extract led to an average increase in quantification of DNA by 3.3-fold that consequently increased test sensitivity of the qPCR from 55 to 80% compared to fecal culture. DNA extracts with higher DNA and protein content had 19.33 and 10.94 times higher odds of showing inhibition, respectively. The results suggest that the current test protocol is sensitive for herd level diagnosis of Johne’s disease but that test sensitivity and individual level diagnosis could be enhanced by relief of PCR inhibition, achieved by five-fold dilution of the DNA extract. Furthermore, qualitative and quantitative parameters derived from absorbance measures of DNA extracts could be useful for prediction of inhibitory fecal samples. PMID:28210245

Quantitative prediction of drug side effects based on drug-related features.

PubMed

Niu, Yanqing; Zhang, Wen

2017-09-01

Unexpected side effects of drugs are great concern in the drug development, and the identification of side effects is an important task. Recently, machine learning methods are proposed to predict the presence or absence of interested side effects for drugs, but it is difficult to make the accurate prediction for all of them. In this paper, we transform side effect profiles of drugs as their quantitative scores, by summing up their side effects with weights. The quantitative scores may measure the dangers of drugs, and thus help to compare the risk of different drugs. Here, we attempt to predict quantitative scores of drugs, namely the quantitative prediction. Specifically, we explore a variety of drug-related features and evaluate their discriminative powers for the quantitative prediction. Then, we consider several feature combination strategies (direct combination, average scoring ensemble combination) to integrate three informative features: chemical substructures, targets, and treatment indications. Finally, the average scoring ensemble model which produces the better performances is used as the final quantitative prediction model. Since weights for side effects are empirical values, we randomly generate different weights in the simulation experiments. The experimental results show that the quantitative method is robust to different weights, and produces satisfying results. Although other state-of-the-art methods cannot make the quantitative prediction directly, the prediction results can be transformed as the quantitative scores. By indirect comparison, the proposed method produces much better results than benchmark methods in the quantitative prediction. In conclusion, the proposed method is promising for the quantitative prediction of side effects, which may work cooperatively with existing state-of-the-art methods to reveal dangers of drugs.

Factors influencing protein tyrosine nitration – structure-based predictive models

PubMed Central

Bayden, Alexander S.; Yakovlev, Vasily A.; Graves, Paul R.; Mikkelsen, Ross B.; Kellogg, Glen E.

2010-01-01

Models for exploring tyrosine nitration in proteins have been created based on 3D structural features of 20 proteins for which high resolution X-ray crystallographic or NMR data are available and for which nitration of 35 total tyrosines has been experimentally proven under oxidative stress. Factors suggested in previous work to enhance nitration were examined with quantitative structural descriptors. The role of neighboring acidic and basic residues is complex: for the majority of tyrosines that are nitrated the distance to the heteroatom of the closest charged sidechain corresponds to the distance needed for suspected nitrating species to form hydrogen bond bridges between the tyrosine and that charged amino acid. This suggests that such bridges play a very important role in tyrosine nitration. Nitration is generally hindered for tyrosines that are buried and for those tyrosines where there is insufficient space for the nitro group. For in vitro nitration, closed environments with nearby heteroatoms or unsaturated centers that can stabilize radicals are somewhat favored. Four quantitative structure-based models, depending on the conditions of nitration, have been developed for predicting site-specific tyrosine nitration. The best model, relevant for both in vitro and in vivo cases predicts 30 of 35 tyrosine nitrations (positive predictive value) and has a sensitivity of 60/71 (11 false positives). PMID:21172423

Impact of Hydrogeological Uncertainty on Estimation of Environmental Risks Posed by Hydrocarbon Transportation Networks

NASA Astrophysics Data System (ADS)

Ciriello, V.; Lauriola, I.; Bonvicini, S.; Cozzani, V.; Di Federico, V.; Tartakovsky, Daniel M.

2017-11-01

Ubiquitous hydrogeological uncertainty undermines the veracity of quantitative predictions of soil and groundwater contamination due to accidental hydrocarbon spills from onshore pipelines. Such predictions, therefore, must be accompanied by quantification of predictive uncertainty, especially when they are used for environmental risk assessment. We quantify the impact of parametric uncertainty on quantitative forecasting of temporal evolution of two key risk indices, volumes of unsaturated and saturated soil contaminated by a surface spill of light nonaqueous-phase liquids. This is accomplished by treating the relevant uncertain parameters as random variables and deploying two alternative probabilistic models to estimate their effect on predictive uncertainty. A physics-based model is solved with a stochastic collocation method and is supplemented by a global sensitivity analysis. A second model represents the quantities of interest as polynomials of random inputs and has a virtually negligible computational cost, which enables one to explore any number of risk-related contamination scenarios. For a typical oil-spill scenario, our method can be used to identify key flow and transport parameters affecting the risk indices, to elucidate texture-dependent behavior of different soils, and to evaluate, with a degree of confidence specified by the decision-maker, the extent of contamination and the correspondent remediation costs.

Implementation of a polling protocol for predicting celiac disease in videocapsule analysis.

PubMed

Ciaccio, Edward J; Tennyson, Christina A; Bhagat, Govind; Lewis, Suzanne K; Green, Peter H

2013-07-16

To investigate the presence of small intestinal villous atrophy in celiac disease patients from quantitative analysis of videocapsule image sequences. Nine celiac patient data with biopsy-proven villous atrophy and seven control patient data lacking villous atrophy were used for analysis. Celiacs had biopsy-proven disease with scores of Marsh II-IIIC except in the case of one hemophiliac patient. At four small intestinal levels (duodenal bulb, distal duodenum, jejunum, and ileum), video clips of length 200 frames (100 s) were analyzed. Twenty-four measurements were used for image characterization. These measurements were determined by quantitatively processing the videocapsule images via techniques for texture analysis, motility estimation, volumetric reconstruction using shape-from-shading principles, and image transformation. Each automated measurement method, or automaton, was polled as to whether or not villous atrophy was present in the small intestine, indicating celiac disease. Each automaton's vote was determined based upon an optimized parameter threshold level, with the threshold levels being determined from prior data. A prediction of villous atrophy was made if it received the majority of votes (≥ 13), while no prediction was made for tie votes (12-12). Thus each set of images was classified as being from either a celiac disease patient or from a control patient. Separated by intestinal level, the overall sensitivity of automata polling for predicting villous atrophy and hence celiac disease was 83.9%, while the specificity was 92.9%, and the overall accuracy of automata-based polling was 88.1%. The method of image transformation yielded the highest sensitivity at 93.8%, while the method of texture analysis using subbands had the highest specificity at 76.0%. Similar results of prediction were observed at all four small intestinal locations, but there were more tie votes at location 4 (ileum). Incorrect prediction which reduced sensitivity occurred for two celiac patients with Marsh type II pattern, which is characterized by crypt hyperplasia, but normal villous architecture. Pooled from all levels, there was a mean of 14.31 ± 3.28 automaton votes for celiac vs 9.67 ± 3.31 automaton votes for control when celiac patient data was analyzed (P < 0.001). Pooled from all levels, there was a mean of 9.71 ± 2.8128 automaton votes for celiac vs 14.32 ± 2.7931 automaton votes for control when control patient data was analyzed (P < 0.001). Automata-based polling may be useful to indicate presence of mucosal atrophy, indicative of celiac disease, across the entire small bowel, though this must be confirmed in a larger patient set. Since the method is quantitative and automated, it can potentially eliminate observer bias and enable the detection of subtle abnormality in patients lacking a clear diagnosis. Our paradigm was found to be more efficacious at proximal small intestinal locations, which may suggest a greater presence and severity of villous atrophy at proximal as compared with distal locations.

Implementation of a polling protocol for predicting celiac disease in videocapsule analysis

PubMed Central

Ciaccio, Edward J; Tennyson, Christina A; Bhagat, Govind; Lewis, Suzanne K; Green, Peter H

2013-01-01

AIM: To investigate the presence of small intestinal villous atrophy in celiac disease patients from quantitative analysis of videocapsule image sequences. METHODS: Nine celiac patient data with biopsy-proven villous atrophy and seven control patient data lacking villous atrophy were used for analysis. Celiacs had biopsy-proven disease with scores of Marsh II-IIIC except in the case of one hemophiliac patient. At four small intestinal levels (duodenal bulb, distal duodenum, jejunum, and ileum), video clips of length 200 frames (100 s) were analyzed. Twenty-four measurements were used for image characterization. These measurements were determined by quantitatively processing the videocapsule images via techniques for texture analysis, motility estimation, volumetric reconstruction using shape-from-shading principles, and image transformation. Each automated measurement method, or automaton, was polled as to whether or not villous atrophy was present in the small intestine, indicating celiac disease. Each automaton’s vote was determined based upon an optimized parameter threshold level, with the threshold levels being determined from prior data. A prediction of villous atrophy was made if it received the majority of votes (≥ 13), while no prediction was made for tie votes (12-12). Thus each set of images was classified as being from either a celiac disease patient or from a control patient. RESULTS: Separated by intestinal level, the overall sensitivity of automata polling for predicting villous atrophy and hence celiac disease was 83.9%, while the specificity was 92.9%, and the overall accuracy of automata-based polling was 88.1%. The method of image transformation yielded the highest sensitivity at 93.8%, while the method of texture analysis using subbands had the highest specificity at 76.0%. Similar results of prediction were observed at all four small intestinal locations, but there were more tie votes at location 4 (ileum). Incorrect prediction which reduced sensitivity occurred for two celiac patients with Marsh type II pattern, which is characterized by crypt hyperplasia, but normal villous architecture. Pooled from all levels, there was a mean of 14.31 ± 3.28 automaton votes for celiac vs 9.67 ± 3.31 automaton votes for control when celiac patient data was analyzed (P < 0.001). Pooled from all levels, there was a mean of 9.71 ± 2.8128 automaton votes for celiac vs 14.32 ± 2.7931 automaton votes for control when control patient data was analyzed (P < 0.001). CONCLUSION: Automata-based polling may be useful to indicate presence of mucosal atrophy, indicative of celiac disease, across the entire small bowel, though this must be confirmed in a larger patient set. Since the method is quantitative and automated, it can potentially eliminate observer bias and enable the detection of subtle abnormality in patients lacking a clear diagnosis. Our paradigm was found to be more efficacious at proximal small intestinal locations, which may suggest a greater presence and severity of villous atrophy at proximal as compared with distal locations. PMID:23858375

Field-sensitivity To Rheological Parameters

NASA Astrophysics Data System (ADS)

Freund, Jonathan; Ewoldt, Randy

2017-11-01

We ask this question: where in a flow is a quantity of interest Q quantitatively sensitive to the model parameters θ-> describing the rheology of the fluid? This field sensitivity is computed via the numerical solution of the adjoint flow equations, as developed to expose the target sensitivity δQ / δθ-> (x) via the constraint of satisfying the flow equations. Our primary example is a sphere settling in Carbopol, for which we have experimental data. For this Carreau-model configuration, we simultaneously calculate how much a local change in the fluid intrinsic time-scale λ, limit-viscosities ηo and η∞, and exponent n would affect the drag D. Such field sensitivities can show where different fluid physics in the model (time scales, elastic versus viscous components, etc.) are important for the target observable and generally guide model refinement based on predictive goals. In this case, the computational cost of solving the local sensitivity problem is negligible relative to the flow. The Carreau-fluid/sphere example is illustrative; the utility of field sensitivity is in the design and analysis of less intuitive flows, for which we provide some additional examples.

NMR-based metabolomic urinalysis: a rapid screening test for urinary tract infection.

PubMed

Lam, Ching-Wan; Law, Chun-Yiu; To, Kelvin Kai-Wang; Cheung, Stanley Kwok-Kuen; Lee, Kim-Chung; Sze, Kong-Hung; Leung, Ka-Fai; Yuen, Kwok-Yung

2014-09-25

Urinary tract infection (UTI) is one of the most common bacterial infections in humans; however, there is no accurate and fast quantitative test to detect UTI. Dipstick urinalysis is semi-quantitative with a limited diagnostic accuracy, while urine culture is accurate but takes time. We described a quantitative biochemical method for the diagnosis of bacteriuria using a single marker. We compared the urine metabolomes from 88 patients with bacterial UTI and 61 controls using (1)H NMR spectroscopy followed by principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA). The biomarker identified was subsequently validated using independent samples. The urine acetic acid/creatinine (mmol/mmol) level was determined to be the most discriminatory marker for bacterial UTI with an area-under-receiver operating characteristic curve=0.97, sensitivity=91% and specificity=95% at the optimal cutoff 0.03 mmol/mmol. For validation, 60 samples were recruited prospectively. Using the optimal cutoff for acetic acid/creatinine, this method showed sensitivity=96%, specificity=94%, positive predictive value=92%, negative predictive value=97% and an overall accuracy=95%. The diagnostic performance was superior to dipstick urinalysis or microscopy. In addition, we also observed an increase of urinary trimethylamine (TMA) in patients with Escherichia coli-associated UTI. TMA is a mammalian-microbial co-metabolite and the high level of TMA generated is related to the bacterial enzyme, trimethylamine N-oxide (TMAO) reductase which reduces TMAO to TMA. Urine acetic acid is a neglected metabolite that can be used for rapid diagnosis of UTI and TMA can be used for etiologic diagnosis of UTI. With the introduction of NMR-based clinical analyzers to clinical laboratories, NMR-based urinalysis can be translated for clinical use. Copyright © 2014 Elsevier B.V. All rights reserved.

Solar Cycle Predictions

NASA Technical Reports Server (NTRS)

Pesnell, William Dean

2012-01-01

Solar cycle predictions are needed to plan long-term space missions; just like weather predictions are needed to plan the launch. Fleets of satellites circle the Earth collecting many types of science data, protecting astronauts, and relaying information. All of these satellites are sensitive at some level to solar cycle effects. Predictions of drag on LEO spacecraft are one of the most important. Launching a satellite with less propellant can mean a higher orbit, but unanticipated solar activity and increased drag can make that a Pyrrhic victory as you consume the reduced propellant load more rapidly. Energetic events at the Sun can produce crippling radiation storms that endanger all assets in space. Solar cycle predictions also anticipate the shortwave emissions that cause degradation of solar panels. Testing solar dynamo theories by quantitative predictions of what will happen in 5-20 years is the next arena for solar cycle predictions. A summary and analysis of 75 predictions of the amplitude of the upcoming Solar Cycle 24 is presented. The current state of solar cycle predictions and some anticipations how those predictions could be made more accurate in the future will be discussed.

When Health Information Meets Social Media: Exploring Virality on Sina Weibo.

PubMed

Liu, Xinchuan; Lu, Jia; Wang, Haiyan

2017-10-01

This study explored the impacts social media bring about on health communication. The impacts involved four factors: authority, privacy, evidence, and incentive appeals. They were adopted to predict virality of health messages on Sina Weibo in terms of retweeting, endorsing, and replying. A quantitative content analysis was conducted with a two-stage probability sample of 1,261 messages from 34 accounts. The results illustrated two modes Weibo users employed to process health information. The heuristic mode was used for retweeting that was sensitive to public messages, negative appeals, and nonprofessional authority. The systematic mode was used for endorsing and replying that were sensitive to private messages, positive appeals, and both professional and nonprofessional authorities.

Adult attachment status predicts the developmental trajectory of maternal sensitivity in new motherhood among Chinese mothers.

PubMed

Liang, X; Wang, Z-Y; Liu, H-Y; Lin, Q; Wang, Z; Liu, Y

2015-01-01

to investigate adult attachment status in first-time mothers, and stability and/or changes in maternal sensitivity during infancy. longitudinal study using quantitative and qualitative methods, and statistical modelling. Three home visits were undertaken when the infant was approximately six, nine and 14 months old. The Adult-to-Parental Attachment Experience Survey was used, and scores for three dimensions were obtained: secure-autonomous, preoccupied and dismissive. Maternal sensitivity was assessed at each time point using the Maternal Behaviour Q-Sort by observing interaction between the mother and infant at home. homes and community settings in greater metropolitan Beijing, North China. 83 mothers and infants born in 2010 enrolled in this study. Data were missing for one or more time points in 20 cases. the mean score for maternal sensitivity tended to increase from six to 14 months. Post-hoc analyses of one-way repeated-measures analysis of variance revealed that maternal sensitivity was significantly higher at 14 months than at six or nine months. An unconditional latent growth model (LGM) of maternal sensitivity, estimated using the Bayesian approach, provided a good fit for the data. Using three attachment-related variables as predictors in the conditional LGM, the model fitting indices were found to be sufficient, and the results suggested that the secure score positively predicted the intercept of the growth model, and the dismissive score negatively predicted both the intercept and slope of the growth model. maternal sensitivity increased over time during infancy. Furthermore, individual differences existed in the developmental trajectory, which was influenced by maternal attachment status. knowledge about attachment-related differences in the trajectory of first-time mothers' sensitivity to infants may help midwives and doctors to provide individualised information and support, with special attention given to mothers with a dismissive attachment status. Copyright © 2014 Elsevier Ltd. All rights reserved.

A facile, branched DNA assay to quantitatively measure glucocorticoid receptor auto-regulation in T-cell acute lymphoblastic leukemia

PubMed Central

Schwartz, Jason R.; Sarvaiya, Purvaba J.; Leiva, Lily E.; Velez, Maria C.; Singleton, Tammuella C.; Yu, Lolie C.; Vedeckis, Wayne V.

2012-01-01

Glucocorticoid (GC) steroid hormones are used to treat acute lymphoblastic leukemia (ALL) because of their pro-apoptotic effects in hematopoietic cells. However, not all leukemia cells are sensitive to GC, and no assay to stratify patients is available. In the GC-sensitive T-cell ALL cell line CEM-C7, auto-up-regulation of RNA transcripts for the glucocorticoid receptor (GR) correlates with increased apoptotic response. This study aimed to determine if a facile assay of GR transcript levels might be promising for stratifying ALL patients into hormone-sensitive and hormone-resistant populations. The GR transcript profiles of various lymphoid cell lines and 4 bone marrow samples from patients with T-cell ALL were analyzed using both an optimized branched DNA (bDNA) assay and a real-time quantitative reverse transcription-polymerase chain reaction assay. There were significant correlations between both assay platforms when measuring total GR (exon 5/6) transcripts in various cell lines and patient samples, but not for a probe set that detects a specific, low abundance GR transcript (exon 1A3). Our results suggest that the bDNA platform is reproducible and precise when measuring total GR transcripts and, with further development, may ultimately offer a simple clinical assay to aid in the prediction of GC-sensitivity in ALL patients. PMID:22739263

Lyme Borreliosis--the Utility of Improved Real-Time PCR Assay in the Detection of Borrelia burgdorferi Infections.

PubMed

Bil-Lula, Iwona; Matuszek, Patryk; Pfeiffer, Thomas; Woźniak, Mieczysław

2015-01-01

Infections of Borrelia burgdorferi sensu lato reveal clinical manifestations affecting numerous organs and tissues. The standard diagnostic procedure of these infections is quite simple if a positive history of tick exposure or typical erythema migrans appears. Lack of unequivocal clinical symptoms creates the necessity for further evaluation with laboratory tests. This study discusses the utility of a novel, improved, well-optimized, sensitive and highly specific quantitative real-time PCR assay for the diagnostics of infections caused by Borrelia burgdorferi sensu lato. We designed an improved, specific, highly sensitive real-time quantitative polymerase chain reaction (RQ-PCR) assay for the detection and quantification of all Borrelia burgdorferi genotypes. A wide validation effort was undertaken to ensure confidence in the highly sensitive and specific detection of B. burgdorferi. Due to high sensitivity and great specificity, as low as 1.6×10² copies of Borrelia per mL of whole blood could be detected. As much as 12 (3%) negative ELISA IgM results, 14 (2.8%) negative results of Line blot IgM, 11 (3.1%) and 7 (2.7%) of negative ELISA IgG and Line blot IgG results, respectively, were positive in real-time PCR. The data in this study confirms the high positive predictive value of real-time PCR test in the detection of Borrelia infections.

Arsenate (As V) in water: quantitative sensitivity relationships among biomarker, ecotoxicity and genotoxicity endpoints.

PubMed

Silva, Valéria C; Almeida, Sônia M; Resgalla, Charrid; Masfaraud, Jean-François; Cotelle, Sylvie; Radetski, Claudemir M

2013-06-01

It is useful to test ecotoxicity and genotoxicity endpoints in the environmental impact assessment. Here, we compare and discuss ecotoxicity and genotoxicity effects in organisms in response to exposure to arsenate (As V) in solution. Eco(geno)toxicity responses in Aliivibrio fischeri, Lytechinus variegatus, Daphnia magna, Skeletonema costatum and Vicia faba were analyzed by assessing different endpoints: biomass growth, peroxidase activity, mitotic index, micronucleus frequency, and lethality in accordance with the international protocols. Quantitative sensitivity relationships (QSR) between these endpoints were established in order to rank endpoint sensitivity. The results for the QSR values based on the lowest observed effect concentration (LOEC) ratios varied from 2 (for ratio of root peroxidase activity to leaf peroxidase activity) to 2286 (for ratio of higher plant biomass growth to root peroxidase activity). The QSR values allowed the following sensitivity ranking to be established: higher plant enzymatic activity>daphnids≈echinoderms>bacteria≈algae>higher plant biomass growth. The LOEC values for the mitotic index and micronucleus frequency (LOEC=0.25mgAsL(-1)) were similar to the lowest LOEC values observed in aquatic organisms. This approach to the QSR of different endpoints could form the basis for monitoring and predicting early effects of pollutants before they give rise to significant changes in natural community structures. Copyright © 2013 Elsevier Inc. All rights reserved.

Cost Models for MMC Manufacturing Processes

NASA Technical Reports Server (NTRS)

Elzey, Dana M.; Wadley, Haydn N. G.

1996-01-01

Processes for the manufacture of advanced metal matrix composites are rapidly approaching maturity in the research laboratory and there is growing interest in their transition to industrial production. However, research conducted to date has almost exclusively focused on overcoming the technical barriers to producing high-quality material and little attention has been given to the economical feasibility of these laboratory approaches and process cost issues. A quantitative cost modeling (QCM) approach was developed to address these issues. QCM are cost analysis tools based on predictive process models relating process conditions to the attributes of the final product. An important attribute, of the QCM approach is the ability to predict the sensitivity of material production costs to product quality and to quantitatively explore trade-offs between cost and quality. Applications of the cost models allow more efficient direction of future MMC process technology development and a more accurate assessment of MMC market potential. Cost models were developed for two state-of-the art metal matrix composite (MMC) manufacturing processes: tape casting and plasma spray deposition. Quality and Cost models are presented for both processes and the resulting predicted quality-cost curves are presented and discussed.

Interpretation of Negative Molecular Test Results in Patients With Suspected or Confirmed Ebola Virus Disease: Report of Two Cases.

PubMed

Edwards, Jeffrey K; Kleine, Christian; Munster, Vincent; Giuliani, Ruggero; Massaquoi, Moses; Sprecher, Armand; Chertow, Daniel S

2015-12-01

Quantitative reverse-transcription polymerase chain reaction (qRT-PCR) is the most sensitive quantitative diagnostic assay for detection of Ebola virus in multiple body fluids. Despite the strengths of this assay, we present 2 cases of Ebola virus disease (EVD) and highlight the potential for false-negative results during the early and late stages of EVD. The first case emphasizes the low negative-predictive value of qRT-PCR during incubation and the early febrile stage of EVD, and the second case emphasizes the potential for false-negative results during recovery and late neurologic complications of EVD. Careful interpretation of test results are needed to guide difficult admission and discharge decisions in suspected or confirmed EVD.

Hybrid optimal descriptors as a tool to predict skin sensitization in accordance to OECD principles.

PubMed

Toropova, Alla P; Toropov, Andrey A

2017-06-05

Skin sensitization (allergic contact dermatitis) is a widespread problem arising from the contact of chemicals with the skin. The detection of molecular features with undesired effect for skin is complex task owing to unclear biochemical mechanisms and unclearness of conditions of action of chemicals to skin. The development of computational methods for estimation of this endpoint in order to reduce animal testing is recommended (Cosmetics Directive EC regulation 1907/2006; EU Regulation, Regulation, 1223/2009). The CORAL software (http://www.insilico.eu/coral) gives good predictive models for the skin sensitization. Simplified molecular input-line entry system (SMILES) together with molecular graph are used to represent the molecular structure for these models. So-called hybrid optimal descriptors are used to establish quantitative structure-activity relationships (QSARs). The aim of this study is the estimation of the predictive potential of the hybrid descriptors. Three different distributions into the training (≈70%), calibration (≈15%), and validation (≈15%) sets are studied. QSAR for these three distributions are built up with using the Monte Carlo technique. The statistical characteristics of these models for external validation set are used as a measure of predictive potential of these models. The best model, according to the above criterion, is characterized by n validation =29, r 2 validation =0.8596, RMSE validation =0.489. Mechanistic interpretation and domain of applicability for these models are defined. Copyright © 2017 Elsevier B.V. All rights reserved.

A ratiometric threshold for determining presence of cancer during fluorescence-guided surgery.

PubMed

Warram, Jason M; de Boer, Esther; Moore, Lindsay S; Schmalbach, Cecelia E; Withrow, Kirk P; Carroll, William R; Richman, Joshua S; Morlandt, Anthony B; Brandwein-Gensler, Margaret; Rosenthal, Eben L

2015-07-01

Fluorescence-guided imaging to assist in identification of malignant margins has the potential to dramatically improve oncologic surgery. However, a standardized method for quantitative assessment of disease-specific fluorescence has not been investigated. Introduced here is a ratiometric threshold derived from mean fluorescent tissue intensity that can be used to semi-quantitatively delineate tumor from normal tissue. Open-field and a closed-field imaging devices were used to quantify fluorescence in punch biopsy tissues sampled from primary tumors collected during a phase 1 trial evaluating the safety of cetuximab-IRDye800 in patients (n = 11) undergoing surgical intervention for head and neck cancer. Fluorescence ratios were calculated using mean fluorescence intensity (MFI) from punch biopsy normalized by MFI of patient-matched tissues. Ratios were compared to pathological assessment and a ratiometric threshold was established to predict presence of cancer. During open-field imaging using an intraoperative device, the threshold for muscle normalized tumor fluorescence was found to be 2.7, which produced a sensitivity of 90.5% and specificity of 78.6% for delineating disease tissue. The skin-normalized threshold generated greater sensitivity (92.9%) and specificity (81.0%). Successful implementation of a semi-quantitative threshold can provide a scientific methodology for delineating disease from normal tissue during fluorescence-guided resection of cancer. © 2015 Wiley Periodicals, Inc.

A randomized and blinded comparison of qPCR and NGS-based detection of aneuploidy in a cell line mixture model of blastocyst biopsy mosaicism.

PubMed

Goodrich, David; Tao, Xin; Bohrer, Chelsea; Lonczak, Agnieszka; Xing, Tongji; Zimmerman, Rebekah; Zhan, Yiping; Scott, Richard T; Treff, Nathan R

2016-11-01

A subset of preimplantation stage embryos may possess mosaicism of chromosomal constitution, representing a possible limitation to the clinical predictive value of comprehensive chromosome screening (CCS) from a single biopsy. However, contemporary methods of CCS may be capable of predicting mosaicism in the blastocyst by detecting intermediate levels of aneuploidy within a trophectoderm biopsy. This study evaluates the sensitivity and specificity of aneuploidy detection by two CCS platforms using a cell line mixture model of a mosaic trophectoderm biopsy. Four cell lines with known karyotypes were obtained and mixed together at specific ratios of six total cells (0:6, 1:5, 2:4, 3:3, 4:2, 5:1, and 6:0). A female euploid and a male trisomy 18 cell line were used for one set, and a male trisomy 13 and a male trisomy 15 cell line were used for another. Replicates of each mixture were prepared, randomized, and blinded for analysis by one of two CCS platforms (quantitative polymerase chain reaction (qPCR) or VeriSeq next-generation sequencing (NGS)). Sensitivity and specificity of aneuploidy detection at each level of mosaicism was determined and compared between platforms. With the default settings for each platform, the sensitivity of qPCR and NGS were not statistically different, and 100 % specificity was observed (no false positives) at all levels of mosaicism. However, the use of previously published custom criteria for NGS increased sensitivity but also significantly decreased specificity (33 % false-positive prediction of aneuploidy). By demonstrating increased false-positive diagnoses when reducing the stringency of predicting an abnormality, these data illustrate the importance of preclinical evaluation of new testing paradigms before clinical implementation.

New approach to predict photoallergic potentials of chemicals based on murine local lymph node assay.

PubMed

Maeda, Yosuke; Hirosaki, Haruka; Yamanaka, Hidenori; Takeyoshi, Masahiro

2018-05-23

Photoallergic dermatitis, caused by pharmaceuticals and other consumer products, is a very important issue in human health. However, S10 guidelines of the International Conference on Harmonization do not recommend the existing prediction methods for photoallergy because of their low predictability in human cases. We applied local lymph node assay (LLNA), a reliable, quantitative skin sensitization prediction test, to develop a new photoallergy prediction method. This method involves a three-step approach: (1) ultraviolet (UV) absorption analysis; (2) determination of no observed adverse effect level for skin phototoxicity based on LLNA; and (3) photoallergy evaluation based on LLNA. Photoallergic potential of chemicals was evaluated by comparing lymph node cell proliferation among groups treated with chemicals with minimal effect levels of skin sensitization and skin phototoxicity under UV irradiation (UV+) or non-UV irradiation (UV-). A case showing significant difference (P < .05) in lymph node cell proliferation rates between UV- and UV+ groups was considered positive for photoallergic reaction. After testing 13 chemicals, seven human photoallergens tested positive and the other six, with no evidence of causing photoallergic dermatitis or UV absorption, tested negative. Among these chemicals, both doxycycline hydrochloride and minocycline hydrochloride were tetracycline antibiotics with different photoallergic properties, and the new method clearly distinguished between the photoallergic properties of these chemicals. These findings suggested high predictability of our method; therefore, it is promising and effective in predicting human photoallergens. Copyright © 2018 John Wiley & Sons, Ltd.

Serial semi-quantitative measurement of fecal calprotectin in patients with ulcerative colitis in remission.

PubMed

Garcia-Planella, Esther; Mañosa, Míriam; Chaparro, María; Beltrán, Belén; Barreiro-de-Acosta, Manuel; Gordillo, Jordi; Ricart, Elena; Bermejo, Fernando; García-Sánchez, Valle; Piqueras, Marta; Llaó, Jordina; Gisbert, Javier P; Cabré, Eduard; Domènech, Eugeni

2018-02-01

Fecal calprotectin (FC) correlates with clinical and endoscopic activity in ulcerative colitis (UC), and it is a good predictor of relapse. However, its use in clinical practice is constrained by the need for the patient to deliver stool samples, and for their handling and processing in the laboratory. The availability of hand held devices might spread the use of FC in clinical practice. To evaluate the usefulness of a rapid semi-quantitative test of FC in predicting relapse in patients with UC in remission. Prospective, multicenter study that included UC patients in clinical remission for ≥6 months on maintenance treatment with mesalamine. Patients were evaluated clinically and semi-quantitative FC was measured using a monoclonal immunochromatography rapid test at baseline and every three months until relapse or 12 months of follow-up. One hundred and ninety-one patients had at least one determination of FC. At the end of follow-up, 33 patients (17%) experienced clinical relapse. Endoscopic activity at baseline (p = .043) and having had at least one FC > 60 μg/g during the study period (p = .03) were associated with a higher risk of relapse during follow-up. We obtained a total of 636 semi-quantitative FC determinations matched with a three-month follow-up clinical assessment. Having undetectable FC was inversely associated with early relapse (within three months), with a negative predictive value of 98.6% and a sensitivity of 93.9%. Serial, rapid semi-quantitative measurement of FC may be a useful, easy and cheap monitoring tool for patients with UC in remission.

Novel approach for classifying chemicals according to skin sensitizing potency by non-radioisotopic modification of the local lymph node assay.

PubMed

Takeyoshi, Masahiro; Iida, Kenji; Shiraishi, Keiji; Hoshuyama, Satsuki

2005-01-01

The murine local lymph node assay (LLNA) is currently recognized as a stand-alone sensitization test for determining the sensitizing potential of chemicals, and it has the advantage of yielding a quantitative endpoint that can be used to predict the sensitization potency of chemicals. The EC3 has been proposed as a parameter for classifying chemicals according to the sensitization potency. We previously developed a non-radioisotopic endpoint for the LLNA based on 5-bromo-2'-deoxyuridine (BrdU) incorporation (non-RI LLNA), and we are proposing a new procedure to predict the sensitization potency of chemicals based on comparisons with known human contact allergens. Nine chemicals (i.e. diphencyclopropenone, p-phenylenediamine, glutaraldehyde, cinnamicaldehyde, citral, eugenol, isopropyl myristate, propyleneglycol and hexane) categorized as human contact allergen classes 1-5 were tested by the non-RI LLNA with the following reference allergens: 2,4-dinitrochlorobenzene (DNCB) as a class 1 human contact allergen, isoeugenol as a class 2 human contact allergen and alpha-hexylcinnamic aldehyde (HCA) as a class 3 human contact allergen. Consequently, nine test chemicals were almost assigned to their correct allergen class. The results suggested that the new procedure for non-RI LLNA can provide correct sensitization potency data. Sensitization potency data are useful for evaluating the sensitization risk to humans of exposure to new chemical products. Accordingly, this approach would be an effective modification of LLNA with regard to its experimental design. Moreover, this procedure can be applied also to the standard LLNA with radioisotopes and to other modifications of the LLNA. Copyright 2005 John Wiley & Sons, Ltd.

Fasting insulin sensitivity indices are not better than routine clinical variables at predicting insulin sensitivity among Black Africans: a clamp study in sub-Saharan Africans

PubMed Central

2014-01-01

Background We aimed to evaluate the predictive utility of common fasting insulin sensitivity indices, and non-laboratory surrogates [BMI, waist circumference (WC) and waist-to-height ratio (WHtR)] in sub-Saharan Africans without diabetes. Methods We measured fasting glucose and insulin, and glucose uptake during 80/mU/m2/min euglycemic clamp in 87 Cameroonians (51 men) aged (SD) 34.6 (11.4) years. We derived insulin sensitivity indices including HOMA-IR, quantitative insulin sensitivity check index (QUICKI), fasting insulin resistance index (FIRI) and glucose-to-insulin ratio (GIR). Indices and clinical predictors were compared to clamp using correlation tests, robust linear regressions and agreement of classification by sex-specific thirds. Results The mean insulin sensitivity was M = 10.5 ± 3.2 mg/kg/min. Classification across thirds of insulin sensitivity by clamp matched with non-laboratory surrogates in 30-48% of participants, and with fasting indices in 27-51%, with kappa statistics ranging from −0.10 to 0.26. Fasting indices correlated significantly with clamp (/r/=0.23-0.30), with GIR performing less well than fasting insulin and HOMA-IR (both p < 0.02). BMI, WC and WHtR were equal or superior to fasting indices (/r/=0.38-0.43). Combinations of fasting indices and clinical predictors explained 25-27% of variation in clamp values. Conclusion Fasting insulin sensitivity indices are modest predictors of insulin sensitivity measured by euglycemic clamp, and do not perform better than clinical surrogates in this population. PMID:25106496

Sensitivity of subject-specific models to Hill muscle-tendon model parameters in simulations of gait.

PubMed

Carbone, V; van der Krogt, M M; Koopman, H F J M; Verdonschot, N

2016-06-14

Subject-specific musculoskeletal (MS) models of the lower extremity are essential for applications such as predicting the effects of orthopedic surgery. We performed an extensive sensitivity analysis to assess the effects of potential errors in Hill muscle-tendon (MT) model parameters for each of the 56 MT parts contained in a state-of-the-art MS model. We used two metrics, namely a Local Sensitivity Index (LSI) and an Overall Sensitivity Index (OSI), to distinguish the effect of the perturbation on the predicted force produced by the perturbed MT parts and by all the remaining MT parts, respectively, during a simulated gait cycle. Results indicated that sensitivity of the model depended on the specific role of each MT part during gait, and not merely on its size and length. Tendon slack length was the most sensitive parameter, followed by maximal isometric muscle force and optimal muscle fiber length, while nominal pennation angle showed very low sensitivity. The highest sensitivity values were found for the MT parts that act as prime movers of gait (Soleus: average OSI=5.27%, Rectus Femoris: average OSI=4.47%, Gastrocnemius: average OSI=3.77%, Vastus Lateralis: average OSI=1.36%, Biceps Femoris Caput Longum: average OSI=1.06%) and hip stabilizers (Gluteus Medius: average OSI=3.10%, Obturator Internus: average OSI=1.96%, Gluteus Minimus: average OSI=1.40%, Piriformis: average OSI=0.98%), followed by the Peroneal muscles (average OSI=2.20%) and Tibialis Anterior (average OSI=1.78%) some of which were not included in previous sensitivity studies. Finally, the proposed priority list provides quantitative information to indicate which MT parts and which MT parameters should be estimated most accurately to create detailed and reliable subject-specific MS models. Copyright © 2016 Elsevier Ltd. All rights reserved.

Atomic bonding effects in annular dark field scanning transmission electron microscopy. II. Experiments

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

Odlyzko, Michael L.; Held, Jacob T.; Mkhoyan, K. Andre, E-mail: mkhoyan@umn.edu

2016-07-15

Quantitatively calibrated annular dark field scanning transmission electron microscopy (ADF-STEM) imaging experiments were compared to frozen phonon multislice simulations adapted to include chemical bonding effects. Having carefully matched simulation parameters to experimental conditions, a depth-dependent bonding effect was observed for high-angle ADF-STEM imaging of aluminum nitride. This result is explained by computational predictions, systematically examined in the preceding portion of this study, showing the propagation of the converged STEM beam to be highly sensitive to net interatomic charge transfer. Thus, although uncertainties in experimental conditions and simulation accuracy remain, the computationally predicted experimental bonding effect withstands the experimental testing reportedmore » here.« less

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.

Testing a lepton quarticity flavor theory of neutrino oscillations with the DUNE experiment

NASA Astrophysics Data System (ADS)

Srivastava, Rahul; Ternes, Christoph A.; Tórtola, Mariam; Valle, José W. F.

2018-03-01

Oscillation studies play a central role in elucidating at least some aspects of the flavor problem. Here we examine the status of the predictions of a lepton quarticity flavor theory of neutrino oscillations against the existing global sample of oscillation data. By performing quantitative simulations we also determine the potential of the upcoming DUNE experiment in narrowing down the currently ill-measured oscillation parameters θ23 and δCP. We present the expected improved sensitivity on these parameters for different assumptions.

Comparative ecology of H2 cycling in sedimentary and phototrophic ecosystems

NASA Technical Reports Server (NTRS)

Hoehler, Tori M.; Albert, Daniel B.; Alperin, Marc J.; Bebout, Brad M.; Martens, Christopher S.; Des Marais, David J.

2002-01-01

The simple biochemistry of H2 is critical to a large number of microbial processes, affecting the interaction of organisms with each other and with the environment. The sensitivity of each of these processes to H2 can be described collectively, through the quantitative language of thermodynamics. A necessary prerequisite is to understand the factors that, in turn, control H2 partial pressures. These factors are assessed for two distinctly different ecosystems. In anoxic sediments from Cape Lookout Bight (North Carolina, USA), H2 partial pressures are strictly maintained at low, steady-state levels by H2-consuming organisms, in a fashion that can be quantitatively predicted by simple thermodynamic calculations. In phototrophic microbial mats from Baja California (Mexico), H2 partial pressures are controlled by the activity of light-sensitive H2-producing organisms, and consequently fluctuate over orders of magnitude on a daily basis. The differences in H2 cycling can subsequently impact any of the H2-sensitive microbial processes in these systems. In one example, methanogenesis in Cape Lookout Bight sediments is completely suppressed through the efficient consumption of H2 by sulfate-reducing bacteria; in contrast, elevated levels of H2 prevail in the producer-controlled phototrophic system, and methanogenesis occurs readily in the presence of 40 mM sulfate.

[Quantitative surface analysis of Pt-Co, Cu-Au and Cu-Ag alloy films by XPS and AES].

PubMed

Li, Lian-Zhong; Zhuo, Shang-Jun; Shen, Ru-Xiang; Qian, Rong; Gao, Jie

2013-11-01

In order to improve the quantitative analysis accuracy of AES, We associated XPS with AES and studied the method to reduce the error of AES quantitative analysis, selected Pt-Co, Cu-Au and Cu-Ag binary alloy thin-films as the samples, used XPS to correct AES quantitative analysis results by changing the auger sensitivity factors to make their quantitative analysis results more similar. Then we verified the accuracy of the quantitative analysis of AES when using the revised sensitivity factors by other samples with different composition ratio, and the results showed that the corrected relative sensitivity factors can reduce the error in quantitative analysis of AES to less than 10%. Peak defining is difficult in the form of the integral spectrum of AES analysis since choosing the starting point and ending point when determining the characteristic auger peak intensity area with great uncertainty, and to make analysis easier, we also processed data in the form of the differential spectrum, made quantitative analysis on the basis of peak to peak height instead of peak area, corrected the relative sensitivity factors, and verified the accuracy of quantitative analysis by the other samples with different composition ratio. The result showed that the analytical error in quantitative analysis of AES reduced to less than 9%. It showed that the accuracy of AES quantitative analysis can be highly improved by the way of associating XPS with AES to correct the auger sensitivity factors since the matrix effects are taken into account. Good consistency was presented, proving the feasibility of this method.

Social cognition and neural substrates of face perception: implications for neurodevelopmental and neuropsychiatric disorders.

PubMed

Lazar, Steven M; Evans, David W; Myers, Scott M; Moreno-De Luca, Andres; Moore, Gregory J

2014-04-15

Social cognition is an important aspect of social behavior in humans. Social cognitive deficits are associated with neurodevelopmental and neuropsychiatric disorders. In this study we examine the neural substrates of social cognition and face processing in a group of healthy young adults to examine the neural substrates of social cognition. Fifty-seven undergraduates completed a battery of social cognition tasks and were assessed with electroencephalography (EEG) during a face-perception task. A subset (N=22) were administered a face-perception task during functional magnetic resonance imaging. Variance in the N170 EEG was predicted by social attribution performance and by a quantitative measure of empathy. Neurally, face processing was more bilateral in females than in males. Variance in fMRI voxel count in the face-sensitive fusiform gyrus was predicted by quantitative measures of social behavior, including the Social Responsiveness Scale (SRS) and the Empathizing Quotient. When measured as a quantitative trait, social behaviors in typical and pathological populations share common neural pathways. The results highlight the importance of viewing neurodevelopmental and neuropsychiatric disorders as spectrum phenomena that may be informed by studies of the normal distribution of relevant traits in the general population. Copyright © 2014 Elsevier B.V. All rights reserved.

Predicting refeeding hypophosphataemia: insulin growth factor 1 (IGF-1) as a diagnostic biochemical marker for clinical practice.

PubMed

Goyale, Atul; Ashley, Sarah L; Taylor, David R; Elnenaei, Manal O; Alaghband-Zadeh, Jamshid; Sherwood, Roy A; le Roux, Carel W; Vincent, Royce P

2015-01-01

Refeeding syndrome (RS) is a potentially fatal condition that can occur following the re-introduction of nutrition after a period of starvation. Hypophosphataemia following the reintroduction of nutrition is often the only reliable biochemical marker of RS. Refeeding index (RI) generated from baseline insulin-like growth factor-1 (IGF-1) and leptin has been proposed as a useful biochemical marker for the identification of patients at risk of developing refeeding hypophosphataemia (RH). A prospective study included 52 patients referred for parenteral nutrition (PN). The sensitivity and specificity of IGF-1 measured using a sensitive assay was compared to the RI in predicting the development of RH (a ≥ 30% drop in PO4 during the first 36-h of PN administration). Leptin and IGF-1 were analysed on baseline samples using a quantitative enzyme-linked immunoassay. Daily blood samples were collected from all patients for routine biochemistry for the full duration of PN administration. High sensitivity IGF-1 measurement alone was comparable with the RI, using receiver-operating characteristic (ROC) curve analysis, with areas under the curve being 0.79 and 0.80, respectively, and superior to leptin alone (0.72) for predicting ≥ 30% drop in PO4. The cut-off value for IGF-1 that gave best sensitivity (91% [95% CI 75-98%]) and specificity (65% [95% CI 41-85%]) was 63.7 µg/L, with a likelihood ratio of 2.59. Baseline IGF-1 is an objective, sensitive and specific biochemical marker in identifying patients who are at high risk of developing RH prior to PN administration and therefore may have a role in clinical practice. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Comparison between three quantitative assays in patients with chronic hepatitis C and their relevance in the prediction of response to therapy.

PubMed

Pradat, P; Chossegros, P; Bailly, F; Pontisso, P; Saracco, G; Sauleda, S; Thursz, M; Tillmann, H; Vlassopoulou, H; Alberti, A; Braconier, J H; Esteban, J I; Hadziyannis, S; Manns, M; Rizzetto, M; Thomas, H C; Trépo, C

2000-05-01

To compare three quantitative assays measuring viral load in patients with chronic hepatitis C and to determine their value in predicting response to interferon (IFN) therapy, we analysed serum from 896 patients from eight European Centres using QUANTIPLEXtrade mark bDNA, MONITOR AMPLICORtrade mark and SUPERQUANTtrade mark assays. Analyses were performed on the same sample. Viral genotype was assessed using INNO-LiPA HCV II kits. Intercentre variations were observed that were related to the handling of specimens not processed and stored within 6 h of blood sampling. Among sera with optimal handling, a stronger correlation was observed between bDNA and SUPERQUANT (0.806) than between bDNA and MONITOR (0.677) and between MONITOR and SUPERQUANT (0.632). These discrepancies were greatest with genotype 2 (bDNA/SUPERQUANT= 0.772; bDNA/MONITOR=0. 456; SUPERQUANT/MONITOR= 0.299). This correlation was influenced by viraemia level and was better at lower viral loads. The proportion of sera with undetectable viral load was 15% with bDNA, 9.7% with MONITOR and 7.7% with SUPERQUANT. For the three measurements, the best cut-offs of sustained response to IFN treatment were located at their detection threshold. Among patients with viral load below the detection level, a sustained response was observed in 35% tested with bDNA, 38% with MONITOR and 80% with SUPERQUANT. Hence a stronger correlation was observed between bDNA and SUPERQUANT than between either of these assays and MONITOR. SUPERQUANT was the most sensitive assay and this greater sensitivity was associated with a better predictive value of treatment response.

T2* Mapping Provides Information That Is Statistically Comparable to an Arthroscopic Evaluation of Acetabular Cartilage.

PubMed

Morgan, Patrick; Nissi, Mikko J; Hughes, John; Mortazavi, Shabnam; Ellerman, Jutta

2017-07-01

Objectives The purpose of this study was to validate T2* mapping as an objective, noninvasive method for the prediction of acetabular cartilage damage. Methods This is the second step in the validation of T2*. In a previous study, we established a quantitative predictive model for identifying and grading acetabular cartilage damage. In this study, the model was applied to a second cohort of 27 consecutive hips to validate the model. A clinical 3.0-T imaging protocol with T2* mapping was used. Acetabular regions of interest (ROI) were identified on magnetic resonance and graded using the previously established model. Each ROI was then graded in a blinded fashion by arthroscopy. Accurate surgical location of ROIs was facilitated with a 2-dimensional map projection of the acetabulum. A total of 459 ROIs were studied. Results When T2* mapping and arthroscopic assessment were compared, 82% of ROIs were within 1 Beck group (of a total 6 possible) and 32% of ROIs were classified identically. Disease prediction based on receiver operating characteristic curve analysis demonstrated a sensitivity of 0.713 and a specificity of 0.804. Model stability evaluation required no significant changes to the predictive model produced in the initial study. Conclusions These results validate that T2* mapping provides statistically comparable information regarding acetabular cartilage when compared to arthroscopy. In contrast to arthroscopy, T2* mapping is quantitative, noninvasive, and can be used in follow-up. Unlike research quantitative magnetic resonance protocols, T2* takes little time and does not require a contrast agent. This may facilitate its use in the clinical sphere.

The current preference for the immuno-analytical ELISA method for quantitation of steroid hormones (endocrine disruptor compounds) in wastewater in South Africa.

PubMed

Manickum, Thavrin; John, Wilson

2015-07-01

The availability of national test centers to offer a routine service for analysis and quantitation of some selected steroid hormones [natural estrogens (17-β-estradiol, E2; estrone, E1; estriol, E3), synthetic estrogen (17-α-ethinylestradiol, EE2), androgen (testosterone), and progestogen (progesterone)] in wastewater matrix was investigated; corresponding internationally used chemical- and immuno-analytical test methods were reviewed. The enzyme-linked immunosorbent assay (ELISA) (immuno-analytical technique) was also assessed for its suitability as a routine test method to quantitate the levels of these hormones at a sewage/wastewater treatment plant (WTP) (Darvill, Pietermaritzburg, South Africa), over a 2-year period. The method performance and other relevant characteristics of the immuno-analytical ELISA method were compared to the conventional chemical-analytical methodology, like gas/liquid chromatography-mass spectrometry (GC/LC-MS), and GC-LC/tandem mass spectrometry (MSMS), for quantitation of the steroid hormones in wastewater and environmental waters. The national immuno-analytical ELISA technique was found to be sensitive (LOQ 5 ng/L, LOD 0.2-5 ng/L), accurate (mean recovery 96%), precise (RSD 7-10%), and cost-effective for screening and quantitation of these steroid hormones in wastewater and environmental water matrix. A survey of the most current international literature indicates a fairly equal use of the LC-MS/MS, GC-MS/MS (chemical-analytical), and ELISA (immuno-analytical) test methods for screening and quantitation of the target steroid hormones in both water and wastewater matrix. Internationally, the observed sensitivity, based on LOQ (ng/L), for the steroid estrogens E1, E2, EE2, is, in decreasing order: LC-MSMS (0.08-9.54) > GC-MS (1) > ELISA (5) (chemical-analytical > immuno-analytical). At the national level, the routine, unoptimized chemical-analytical LC-MSMS method was found to lack the required sensitivity for meeting environmental requirements for steroid hormone quantitation. Further optimization of the sensitivity of the chemical-analytical LC-tandem mass spectrometry methods, especially for wastewater screening, in South Africa is required. Risk assessment studies showed that it was not practical to propose standards or allowable limits for the steroid estrogens E1, E2, EE2, and E3; the use of predicted-no-effect concentration values of the steroid estrogens appears to be appropriate for use in their risk assessment in relation to aquatic organisms. For raw water sources, drinking water, raw and treated wastewater, the use of bioassays, with trigger values, is a useful screening tool option to decide whether further examination of specific endocrine activity may be warranted, or whether concentrations of such activity are of low priority, with respect to health concerns in the human population. The achievement of improved quantitation limits for immuno-analytical methods, like ELISA, used for compound quantitation, and standardization of the method for measuring E2 equivalents (EEQs) used for biological activity (endocrine: e.g., estrogenic) are some areas for future EDC research.

Polymer coated quartz crystal microbalance sensors for detection of volatile organic compounds in gas mixtures.

PubMed

Si, Pengchao; Mortensen, John; Komolov, Alexei; Denborg, Jens; Møller, Preben Juul

2007-08-06

By coating different conducting polymers of thiophene and its derivatives on quartz crystal microbalance (QCM) sensor surfaces, new novel QCM gas sensors have been produced in two simple ways, which could classify testing gas samples of volatile organic compounds (VOCs) gases. Principle components analysis (PCA) has been performed based on the QCM measurement results, which shows that our QCM sensors array has very good utilizing potential on sensing both polar and low-polar/nonpolar VOC gases. The sensitivity, selectivity, reproducibility and detection limit of QCM sensors have also been discussed. Quantitative variation of sensitivity response with the increasing concentration has been studied. (PLS) analysis and prediction of concentrations of single gas in mixtures have been carried out.

Serum oestradiol and beta-HCG measurements after day 3 or 5 embryo transfers in interpreting pregnancy outcome.

PubMed

Kumbak, Banu; Oral, Engin; Karlikaya, Guvenc; Lacin, Selman; Kahraman, Semra

2006-10-01

The aim of this study was to assess the clinical value of serum oestradiol concentration 8 days after embryo transfer (D8E2) and beta-human chorionic gonadotrophin (HCG-beta) concentration 12 days after embryo transfer (D12HCG-beta) in the prediction of pregnancy and the outcome of pregnancy following assisted reproduction, taking into account the day of transfer, which was either day 3 (D3) or day 5 (D5). The objective was to improve patient counselling by giving quantitative and reliable predictive information instead of non-specific uncertainties. A total of 2035 embryo transfer cycles performed between January 2003 and June 2005 were analysed retrospectively. Biochemical pregnancy, ectopic pregnancy and first-trimester abortions were classified as non-viable pregnancies; pregnancies beyond 12 weeks gestation were classified as ongoing pregnancies (OP). Significantly higher D8E2 and D12HCG-beta were obtained in D5 transfers compared with D3 transfers with regard to pregnancy and OP (P

Vitamin D, Race, and Experimental Pain Sensitivity in Older Adults with Knee Osteoarthritis

PubMed Central

Glover, T.L.; Goodin, B.R.; Horgas, A.L.; Kindler, L.L.; King, C.D.; Sibille, K.T.; Peloquin, C.A.; Riley, J.L.; Staud, R.; Bradley, L.A.; Fillingim, R.B.

2012-01-01

Objective Low levels of serum circulating 25-hydroxyvitamin D have been correlated with many health conditions, including chronic pain. Recent clinical practice guidelines define vitamin D levels < 20 ng/mL as deficient and values of 21–29 ng/mL as insufficient. Vitamin D insufficiency, including the most severe levels of deficiency, is more prevalent in black Americans. Ethnic and race group differences have been reported in both clinical and experimental pain, with black Americans reporting increased pain. The purpose of this study was to examine whether variation in vitamin D levels contribute to race differences in knee osteoarthritic pain. Methods The sample consisted of 94 participants (75% female), including 45 blacks and 49 whites with symptomatic knee osteoarthritis. Average age was 55.8 years (range 45–71 years). Participants completed a questionnaire on knee osteoarthritic symptoms and underwent quantitative sensory testing, including measures of heat and mechanical pain sensitivity. Results Blacks had significantly lower levels of vitamin D compared to whites, demonstrated greater clinical pain, and showed greater sensitivity to mechanical and heat pain. Low levels of vitamin D predicted increased experimental pain sensitivity, but did not predict self-reported clinical pain. Group differences in vitamin D significantly predicted group differences in heat pain and pressure pain thresholds on the index knee and ipsilateral forearm. Conclusion These data demonstrate race differences in experimental pain are mediated by differences in vitamin D level. Vitamin D deficiency may be a risk factor for increased knee osteoarthritic pain in black Americans. PMID:23135697

Natural speech algorithm applied to baseline interview data can predict which patients will respond to psilocybin for treatment-resistant depression.

PubMed

Carrillo, Facundo; Sigman, Mariano; Fernández Slezak, Diego; Ashton, Philip; Fitzgerald, Lily; Stroud, Jack; Nutt, David J; Carhart-Harris, Robin L

2018-04-01

Natural speech analytics has seen some improvements over recent years, and this has opened a window for objective and quantitative diagnosis in psychiatry. Here, we used a machine learning algorithm applied to natural speech to ask whether language properties measured before psilocybin for treatment-resistant can predict for which patients it will be effective and for which it will not. A baseline autobiographical memory interview was conducted and transcribed. Patients with treatment-resistant depression received 2 doses of psilocybin, 10 mg and 25 mg, 7 days apart. Psychological support was provided before, during and after all dosing sessions. Quantitative speech measures were applied to the interview data from 17 patients and 18 untreated age-matched healthy control subjects. A machine learning algorithm was used to classify between controls and patients and predict treatment response. Speech analytics and machine learning successfully differentiated depressed patients from healthy controls and identified treatment responders from non-responders with a significant level of 85% of accuracy (75% precision). Automatic natural language analysis was used to predict effective response to treatment with psilocybin, suggesting that these tools offer a highly cost-effective facility for screening individuals for treatment suitability and sensitivity. The sample size was small and replication is required to strengthen inferences on these results. Copyright © 2018 Elsevier B.V. All rights reserved.

Factors influencing protein tyrosine nitration--structure-based predictive models.

PubMed

Bayden, Alexander S; Yakovlev, Vasily A; Graves, Paul R; Mikkelsen, Ross B; Kellogg, Glen E

2011-03-15

Models for exploring tyrosine nitration in proteins have been created based on 3D structural features of 20 proteins for which high-resolution X-ray crystallographic or NMR data are available and for which nitration of 35 total tyrosines has been experimentally proven under oxidative stress. Factors suggested in previous work to enhance nitration were examined with quantitative structural descriptors. The role of neighboring acidic and basic residues is complex: for the majority of tyrosines that are nitrated the distance to the heteroatom of the closest charged side chain corresponds to the distance needed for suspected nitrating species to form hydrogen bond bridges between the tyrosine and that charged amino acid. This suggests that such bridges play a very important role in tyrosine nitration. Nitration is generally hindered for tyrosines that are buried and for those tyrosines for which there is insufficient space for the nitro group. For in vitro nitration, closed environments with nearby heteroatoms or unsaturated centers that can stabilize radicals are somewhat favored. Four quantitative structure-based models, depending on the conditions of nitration, have been developed for predicting site-specific tyrosine nitration. The best model, relevant for both in vitro and in vivo cases, predicts 30 of 35 tyrosine nitrations (positive predictive value) and has a sensitivity of 60/71 (11 false positives). Copyright © 2010 Elsevier Inc. All rights reserved.

Amplitude-modulation detection by gerbils in reverberant sound fields.

PubMed

Lingner, Andrea; Kugler, Kathrin; Grothe, Benedikt; Wiegrebe, Lutz

2013-08-01

Reverberation can dramatically reduce the depth of amplitude modulations which are critical for speech intelligibility. Psychophysical experiments indicate that humans' sensitivity to amplitude modulation in reverberation is better than predicted from the acoustic modulation depth at the receiver position. Electrophysiological studies on reverberation in rabbits highlight the contribution of neurons sensitive to interaural correlation. Here, we use a prepulse-inhibition paradigm to quantify the gerbils' amplitude modulation threshold in both anechoic and reverberant virtual environments. Data show that prepulse inhibition provides a reliable method for determining the gerbils' AM sensitivity. However, we find no evidence for perceptual restoration of amplitude modulation in reverberation. Instead, the deterioration of AM sensitivity in reverberant conditions can be quantitatively explained by the reduced modulation depth at the receiver position. We suggest that the lack of perceptual restoration is related to physical properties of the gerbil's ear input signals and inner-ear processing as opposed to shortcomings of their binaural neural processing. Copyright © 2013 Elsevier B.V. All rights reserved.

Local Patterns to Global Architectures: Influences of Network Topology on Human Learning.

PubMed

Karuza, Elisabeth A; Thompson-Schill, Sharon L; Bassett, Danielle S

2016-08-01

A core question in cognitive science concerns how humans acquire and represent knowledge about their environments. To this end, quantitative theories of learning processes have been formalized in an attempt to explain and predict changes in brain and behavior. We connect here statistical learning approaches in cognitive science, which are rooted in the sensitivity of learners to local distributional regularities, and network science approaches to characterizing global patterns and their emergent properties. We focus on innovative work that describes how learning is influenced by the topological properties underlying sensory input. The confluence of these theoretical approaches and this recent empirical evidence motivate the importance of scaling-up quantitative approaches to learning at both the behavioral and neural levels. Copyright © 2016 Elsevier Ltd. All rights reserved.

The agar diffusion scratch assay - A novel method to assess the bioactive and cytotoxic potential of new materials and compounds

PubMed Central

Pusnik, Mascha; Imeri, Minire; Deppierraz, Grégoire; Bruinink, Arie; Zinn, Manfred

2016-01-01

A profound in vitro evaluation not only of the cytotoxic but also of bioactive potential of a given compound or material is crucial for predicting potential effects in the in vivo situation. However, most of the current methods have weaknesses in either the quantitative or qualitative assessment of cytotoxicity and/or bioactivity of the test compound. Here we describe a novel assay combining the ISO 10993-5 agar diffusion test and the scratch also termed wound healing assay. In contrast to these original tests this assay is able to detect and distinguish between cytotoxic, cell migration modifying and cytotoxic plus cell migration modifying compounds, and this at higher sensitivity and in a quantitative way. PMID:26861591

Quantitative Kα line spectroscopy for energy transport in ultra-intense laser plasma interaction

NASA Astrophysics Data System (ADS)

Zhang, Z.; Nishimura, H.; Namimoto, T.; Fujioka, S.; Arikawa, Y.; Nakai, M.; Koga, M.; Shiraga, H.; Kojima, S.; Azechi, H.; Ozaki, T.; Chen, H.; Pakr, J.; Williams, G. J.; Nishikino, M.; Kawachi, T.; Sagisaka, A.; Orimo, S.; Ogura, K.; Pirozhkov, A.; Yogo, A.; Kiriyama, H.; Kondo, K.; Okano, Y.

2012-10-01

X-ray line spectra ranging from 17 to 77 keV were quantitatively measured with a Laue spectrometer, composed of a cylindrically curved crystal and a detector. The absolute sensitivity of the spectrometer system was calibrated using pre-characterized laser-produced x-ray sources and radioisotopes, for the detectors and crystal respectively. The integrated reflectivity for the crystal is in good agreement with predictions by an open code for x-ray diffraction. The energy transfer efficiency from incident laser beams to hot electrons, as the energy transfer agency for Au Kα x-ray line emissions, is derived as a consequence of this work. By considering the hot electron temperature, the transfer efficiency from LFEX laser to Au plate target is about 8% to 10%.

A standardized model for predicting flap failure using indocyanine green dye

NASA Astrophysics Data System (ADS)

Zimmermann, Terence M.; Moore, Lindsay S.; Warram, Jason M.; Greene, Benjamin J.; Nakhmani, Arie; Korb, Melissa L.; Rosenthal, Eben L.

2016-03-01

Techniques that provide a non-invasive method for evaluation of intraoperative skin flap perfusion are currently available but underutilized. We hypothesize that intraoperative vascular imaging can be used to reliably assess skin flap perfusion and elucidate areas of future necrosis by means of a standardized critical perfusion threshold. Five animal groups (negative controls, n=4; positive controls, n=5; chemotherapy group, n=5; radiation group, n=5; chemoradiation group, n=5) underwent pre-flap treatments two weeks prior to undergoing random pattern dorsal fasciocutaneous flaps with a length to width ratio of 2:1 (3 x 1.5 cm). Flap perfusion was assessed via laser-assisted indocyanine green dye angiography and compared to standard clinical assessment for predictive accuracy of flap necrosis. For estimating flap-failure, clinical prediction achieved a sensitivity of 79.3% and a specificity of 90.5%. When average flap perfusion was more than three standard deviations below the average flap perfusion for the negative control group at the time of the flap procedure (144.3+/-17.05 absolute perfusion units), laser-assisted indocyanine green dye angiography achieved a sensitivity of 81.1% and a specificity of 97.3%. When absolute perfusion units were seven standard deviations below the average flap perfusion for the negative control group, specificity of necrosis prediction was 100%. Quantitative absolute perfusion units can improve specificity for intraoperative prediction of viable tissue. Using this strategy, a positive predictive threshold of flap failure can be standardized for clinical use.

[Diagnostic value of quantitative pharmacokinetic parameters and relative quantitative pharmacokinetic parameters in breast lesions with dynamic contrast-enhanced MRI].

PubMed

Sun, T T; Liu, W H; Zhang, Y Q; Li, L H; Wang, R; Ye, Y Y

2017-08-01

Objective: To explore the differential between the value of dynamic contrast-enhanced MRI quantitative pharmacokinetic parameters and relative pharmacokinetic quantitative parameters in breast lesions. Methods: Retrospective analysis of 255 patients(262 breast lesions) who was obtained by clinical palpation , ultrasound or full-field digital mammography , and then all lessions were pathologically confirmed in Zhongda Hospital, Southeast University from May 2012 to May 2016. A 3.0 T MRI scanner was used to obtain the quantitative MR pharmacokinetic parameters: volume transfer constant (K(trans)), exchange rate constant (k(ep))and extravascular extracellular volume fraction (V(e)). And measured the quantitative pharmacokinetic parameters of normal glands tissues which on the same side of the same level of the lesions; and then calculated the value of relative pharmacokinetic parameters: rK(rans)、rk(ep) and rV(e).To explore the diagnostic value of two pharmacokinetic parameters in differential diagnosis of benign and malignant breast lesions using receiver operating curves and model of logistic regression. Results: (1)There were significant differences between benign lesions and malignant lesions in K(trans) and k(ep) ( t =15.489, 15.022, respectively, P <0.05), there were no significant differences between benign lesions and malignant lesions in V(e)( t =-2.346, P >0.05). The areas under the ROC curve(AUC)of K(trans), k(ep) and V(e) between malignant and benign lesions were 0.933, 0.948 and 0.387, the sensitivity of K(trans), k(ep) and V(e) were 77.1%, 85.0%, 51.0% , and the specificity of K(trans), k(ep) and V(e) were 96.3%, 93.6%, 60.8% for the differential diagnosis of breast lesions if taken the maximum Youden's index as cut-off. (2)There were significant differences between benign lesions and malignant lesions in rK(trans), rk(ep) and rV(e) ( t =14.177, 11.726, 2.477, respectively, P <0.05). The AUC of rK(trans), rk(ep) and rV(e) between malignant and benign lesions were 0.963, 0.903 and 0.575, the sensitivity of rK(trans), rk(ep) and rV(e) were 85.6%, 71.9%, 52.9% , and the specificity of rK(trans), rk(ep) and rV(e) were 94.5%, 92.7%, 60.6% for the differential diagnosis of breast lesions.(3)There was no significant difference in the area under the ROC curve between the predictive probability of quantitative pharmacokinetic parameters and the prediction probability of relative quantitative pharmacokinetic parameters( Z =0.867, P =0.195). Conclusion: There was no significant difference between the quantitative parameter values (K(trans,) k(ep)) and the relative quantitative parameter values (rK(trans,) rk(ep)) in diagnosis of breast lesions, which were important parameters in differential diagnosis of benign and malignant breast lesions.

Virus Sensitivity Index of UV disinfection.

PubMed

Tang, Walter Z; Sillanpää, Mika

2015-01-01

A new concept of Virus Sensitivity Index (VSI) is defined as the ratio between the first-order inactivation rate constant of a virus, ki, and that of MS2-phage during UV disinfection, kr. MS2-phage is chosen as the reference virus because it is recommended as a virus indicator during UV reactor design and validation by the US Environmental Protection Agency. VSI has wide applications in research, design, and validation of UV disinfection systems. For example, it can be used to rank the UV disinfection sensitivity of viruses in reference to MS2-phage. There are four major steps in deriving the equation between Hi/Hr and 1/VSI. First, the first-order inactivation rate constants are determined by regression analysis between Log I and fluence required. Second, the inactivation rate constants of MS2-phage are statistically analysed at 3, 4, 5, and 6 Log I levels. Third, different VSI values are obtained from the ki of different viruses dividing by the kr of MS2-phage. Fourth, correlation between Hi/Hr and 1/VSI is analysed by using linear, quadratic, and cubic models. As expected from the theoretical analysis, a linear relationship adequately correlates Hi/Hr and 1/VSI without an intercept. VSI is used to quantitatively predict the UV fluence required for any virus at any log inactivation (Log I). Four equations were developed at 3, 4, 5, and 6 Log I. These equations have been validated using external data which are not used for the virus development. At Log I less than 3, the equation tends to under-predict the required fluence at both low Log I such as 1 and 2 Log I. At Log I greater than 3 Log I, the equation tends to over-predict the fluence required. The reasons for these may very likely be due to the shoulder at the beginning and the tailing at the end of the collimated beam test experiments. At 3 Log I, the error percentage is less than 6%. The VSI is also used to predict inactivation rate constants under two different UV disinfection scenarios such as under sunlight and different virus aggregates. The correlation analysis shows that viruses will be about 40% more sensitive to sunlight than to UV254. On the other hand, virus size of 500 nm will reduce their VSI by 10%. This is the first attempt to use VSI to predict the required fluence at any given Log I. The equation can be used to quantitatively evaluate other parameters influencing UV disinfection. These factors include environmental species, antibiotic-resistant bacteria or genes, photo and dark repair, water quality such as suspended solids, and UV transmittance.

Preparing systems engineering and computing science students in disciplined methods, quantitative, and advanced statistical techniques to improve process performance

NASA Astrophysics Data System (ADS)

McCray, Wilmon Wil L., Jr.

The research was prompted by a need to conduct a study that assesses process improvement, quality management and analytical techniques taught to students in U.S. colleges and universities undergraduate and graduate systems engineering and the computing science discipline (e.g., software engineering, computer science, and information technology) degree programs during their academic training that can be applied to quantitatively manage processes for performance. Everyone involved in executing repeatable processes in the software and systems development lifecycle processes needs to become familiar with the concepts of quantitative management, statistical thinking, process improvement methods and how they relate to process-performance. Organizations are starting to embrace the de facto Software Engineering Institute (SEI) Capability Maturity Model Integration (CMMI RTM) Models as process improvement frameworks to improve business processes performance. High maturity process areas in the CMMI model imply the use of analytical, statistical, quantitative management techniques, and process performance modeling to identify and eliminate sources of variation, continually improve process-performance; reduce cost and predict future outcomes. The research study identifies and provides a detail discussion of the gap analysis findings of process improvement and quantitative analysis techniques taught in U.S. universities systems engineering and computing science degree programs, gaps that exist in the literature, and a comparison analysis which identifies the gaps that exist between the SEI's "healthy ingredients " of a process performance model and courses taught in U.S. universities degree program. The research also heightens awareness that academicians have conducted little research on applicable statistics and quantitative techniques that can be used to demonstrate high maturity as implied in the CMMI models. The research also includes a Monte Carlo simulation optimization model and dashboard that demonstrates the use of statistical methods, statistical process control, sensitivity analysis, quantitative and optimization techniques to establish a baseline and predict future customer satisfaction index scores (outcomes). The American Customer Satisfaction Index (ACSI) model and industry benchmarks were used as a framework for the simulation model.

Comparison of quantitative and qualitative tests for glucose-6-phosphate dehydrogenase deficiency.

PubMed

LaRue, Nicole; Kahn, Maria; Murray, Marjorie; Leader, Brandon T; Bansil, Pooja; McGray, Sarah; Kalnoky, Michael; Zhang, Hao; Huang, Huiqiang; Jiang, Hui; Domingo, Gonzalo J

2014-10-01

A barrier to eliminating Plasmodium vivax malaria is inadequate treatment of infected patients. 8-Aminoquinoline-based drugs clear the parasite; however, people with glucose-6-phosphate dehydrogenase (G6PD) deficiency are at risk for hemolysis from these drugs. Understanding the performance of G6PD deficiency tests is critical for patient safety. Two quantitative assays and two qualitative tests were evaluated. The comparison of quantitative assays gave a Pearson correlation coefficient of 0.7585 with significant difference in mean G6PD activity, highlighting the need to adhere to a single reference assay. Both qualitative tests had high sensitivity and negative predictive value at a cutoff G6PD value of 40% of normal activity if interpreted conservatively and performed under laboratory conditions. The performance of both tests dropped at a cutoff level of 45%. Cytochemical staining of specimens confirmed that heterozygous females with > 50% G6PD-deficient cells can seem normal by phenotypic tests. © The American Society of Tropical Medicine and Hygiene.

Comparisons of Robustness and Sensitivity between Cancer and Normal Cells by Microarray Data

PubMed Central

Chu, Liang-Hui; Chen, Bor-Sen

2008-01-01

Robustness is defined as the ability to uphold performance in face of perturbations and uncertainties, and sensitivity is a measure of the system deviations generated by perturbations to the system. While cancer appears as a robust but fragile system, few computational and quantitative evidences demonstrate robustness tradeoffs in cancer. Microarrays have been widely applied to decipher gene expression signatures in human cancer research, and quantification of global gene expression profiles facilitates precise prediction and modeling of cancer in systems biology. We provide several efficient computational methods based on system and control theory to compare robustness and sensitivity between cancer and normal cells by microarray data. Measurement of robustness and sensitivity by linear stochastic model is introduced in this study, which shows oscillations in feedback loops of p53 and demonstrates robustness tradeoffs that cancer is a robust system with some extreme fragilities. In addition, we measure sensitivity of gene expression to perturbations in other gene expression and kinetic parameters, discuss nonlinear effects in feedback loops of p53 and extend our method to robustness-based cancer drug design. PMID:19259409

A Ratiometric Threshold for Determining Presence of Cancer During Fluorescence-guided Surgery

PubMed Central

Warram, Jason M; de Boer, Esther; Moore, Lindsay S.; Schmalbach, Cecelia E; Withrow, Kirk P; Carroll, William R; Richman, Joshua S; Morlandt, Anthony B; Brandwein-Gensler, Margaret; Rosenthal, Eben L

2015-01-01

Background&Objective Fluorescence-guided imaging to assist in identification of malignant margins has the potential to dramatically improve oncologic surgery. However a standardized method for quantitative assessment of disease-specific fluorescence has not been investigated. Introduced here is a ratiometric threshold derived from mean fluorescent tissue intensity that can be used to semi-quantitatively delineate tumor from normal tissue. Methods Open-field and a closed-field imaging devices were used to quantify fluorescence in punch biopsy tissues sampled from primary tumors collected during a phase 1 trial evaluating the safety of cetuximab-IRDye800 in patients (n=11) undergoing surgical intervention for head and neck cancer. Fluorescence ratios were calculated using mean fluorescence intensity (MFI) from punch biopsy normalized by MFI of patient-matched tissues. Ratios were compared to pathological assessment and a ratiometric threshold was established to predict presence of cancer. Results During open-field imaging using an intraoperative device, the threshold for muscle normalized tumor fluorescence was found to be 2.7, which produced a sensitivity of 90.5% and specificity of 78.6% for delineating disease tissue. The skin-normalized threshold generated greater sensitivity (92.9%) and specificity (81.0%). Conclusion Successful implementation of a semi-quantitative threshold can provide a scientific methodology for delineating disease from normal tissue during fluorescence-guided resection of cancer. PMID:26074273

Proteome-wide Light/Dark Modulation of Thiol Oxidation in Cyanobacteria Revealed by Quantitative Site-specific Redox Proteomics*

PubMed Central

Guo, Jia; Nguyen, Amelia Y.; Dai, Ziyu; Su, Dian; Gaffrey, Matthew J.; Moore, Ronald J.; Jacobs, Jon M.; Monroe, Matthew E.; Smith, Richard D.; Koppenaal, David W.; Pakrasi, Himadri B.; Qian, Wei-Jun

2014-01-01

Reversible protein thiol oxidation is an essential regulatory mechanism of photosynthesis, metabolism, and gene expression in photosynthetic organisms. Herein, we present proteome-wide quantitative and site-specific profiling of in vivo thiol oxidation modulated by light/dark in the cyanobacterium Synechocystis sp. PCC 6803, an oxygenic photosynthetic prokaryote, using a resin-assisted thiol enrichment approach. Our proteomic approach integrates resin-assisted enrichment with isobaric tandem mass tag labeling to enable site-specific and quantitative measurements of reversibly oxidized thiols. The redox dynamics of ∼2,100 Cys-sites from 1,060 proteins under light, dark, and 3-(3,4-dichlorophenyl)-1,1-dimethylurea (a photosystem II inhibitor) conditions were quantified. In addition to relative quantification, the stoichiometry or percentage of oxidation (reversibly oxidized/total thiols) for ∼1,350 Cys-sites was also quantified. The overall results revealed broad changes in thiol oxidation in many key biological processes, including photosynthetic electron transport, carbon fixation, and glycolysis. Moreover, the redox sensitivity along with the stoichiometric data enabled prediction of potential functional Cys-sites for proteins of interest. The functional significance of redox-sensitive Cys-sites in NADP-dependent glyceraldehyde-3-phosphate dehydrogenase, peroxiredoxin (AhpC/TSA family protein Sll1621), and glucose 6-phosphate dehydrogenase was further confirmed with site-specific mutagenesis and biochemical studies. Together, our findings provide significant insights into the broad redox regulation of photosynthetic organisms. PMID:25118246

Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model

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

Urrego-Blanco, Jorge Rolando; Urban, Nathan Mark; Hunke, Elizabeth Clare

Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual modelmore » parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. Lastly, it is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.« less

Sensitivity of subject-specific models to errors in musculo-skeletal geometry.

PubMed

Carbone, V; van der Krogt, M M; Koopman, H F J M; Verdonschot, N

2012-09-21

Subject-specific musculo-skeletal models of the lower extremity are an important tool for investigating various biomechanical problems, for instance the results of surgery such as joint replacements and tendon transfers. The aim of this study was to assess the potential effects of errors in musculo-skeletal geometry on subject-specific model results. We performed an extensive sensitivity analysis to quantify the effect of the perturbation of origin, insertion and via points of each of the 56 musculo-tendon parts contained in the model. We used two metrics, namely a Local Sensitivity Index (LSI) and an Overall Sensitivity Index (OSI), to distinguish the effect of the perturbation on the predicted force produced by only the perturbed musculo-tendon parts and by all the remaining musculo-tendon parts, respectively, during a simulated gait cycle. Results indicated that, for each musculo-tendon part, only two points show a significant sensitivity: its origin, or pseudo-origin, point and its insertion, or pseudo-insertion, point. The most sensitive points belong to those musculo-tendon parts that act as prime movers in the walking movement (insertion point of the Achilles Tendon: LSI=15.56%, OSI=7.17%; origin points of the Rectus Femoris: LSI=13.89%, OSI=2.44%) and as hip stabilizers (insertion points of the Gluteus Medius Anterior: LSI=17.92%, OSI=2.79%; insertion point of the Gluteus Minimus: LSI=21.71%, OSI=2.41%). The proposed priority list provides quantitative information to improve the predictive accuracy of subject-specific musculo-skeletal models. Copyright © 2012 Elsevier Ltd. All rights reserved.

Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model

DOE PAGES

Urrego-Blanco, Jorge Rolando; Urban, Nathan Mark; Hunke, Elizabeth Clare; ...

2016-04-01

Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual modelmore » parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. Lastly, it is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.« less

Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model

NASA Astrophysics Data System (ADS)

Urrego-Blanco, Jorge R.; Urban, Nathan M.; Hunke, Elizabeth C.; Turner, Adrian K.; Jeffery, Nicole

2016-04-01

Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual model parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. It is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.

A quantitative measure for degree of automation and its relation to system performance and mental load.

PubMed

Wei, Z G; Macwan, A P; Wieringa, P A

1998-06-01

In this paper we quantitatively model degree of automation (DofA) in supervisory control as a function of the number and nature of tasks to be performed by the operator and automation. This model uses a task weighting scheme in which weighting factors are obtained from task demand load, task mental load, and task effect on system performance. The computation of DofA is demonstrated using an experimental system. Based on controlled experiments using operators, analyses of the task effect on system performance, the prediction and assessment of task demand load, and the prediction of mental load were performed. Each experiment had a different DofA. The effect of a change in DofA on system performance and mental load was investigated. It was found that system performance became less sensitive to changes in DofA at higher levels of DofA. The experimental data showed that when the operator controlled a partly automated system, perceived mental load could be predicted from the task mental load for each task component, as calculated by analyzing a situation in which all tasks were manually controlled. Actual or potential applications of this research include a methodology to balance and optimize the automation of complex industrial systems.

Prediction of revascularization after myocardial perfusion SPECT by machine learning in a large population.

PubMed

Arsanjani, Reza; Dey, Damini; Khachatryan, Tigran; Shalev, Aryeh; Hayes, Sean W; Fish, Mathews; Nakanishi, Rine; Germano, Guido; Berman, Daniel S; Slomka, Piotr

2015-10-01

We aimed to investigate if early revascularization in patients with suspected coronary artery disease can be effectively predicted by integrating clinical data and quantitative image features derived from perfusion SPECT (MPS) by machine learning (ML) approach. 713 rest (201)Thallium/stress (99m)Technetium MPS studies with correlating invasive angiography with 372 revascularization events (275 PCI/97 CABG) within 90 days after MPS (91% within 30 days) were considered. Transient ischemic dilation, stress combined supine/prone total perfusion deficit (TPD), supine rest and stress TPD, exercise ejection fraction, and end-systolic volume, along with clinical parameters including patient gender, history of hypertension and diabetes mellitus, ST-depression on baseline ECG, ECG and clinical response during stress, and post-ECG probability by boosted ensemble ML algorithm (LogitBoost) to predict revascularization events. These features were selected using an automated feature selection algorithm from all available clinical and quantitative data (33 parameters). Tenfold cross-validation was utilized to train and test the prediction model. The prediction of revascularization by ML algorithm was compared to standalone measures of perfusion and visual analysis by two experienced readers utilizing all imaging, quantitative, and clinical data. The sensitivity of machine learning (ML) (73.6% ± 4.3%) for prediction of revascularization was similar to one reader (73.9% ± 4.6%) and standalone measures of perfusion (75.5% ± 4.5%). The specificity of ML (74.7% ± 4.2%) was also better than both expert readers (67.2% ± 4.9% and 66.0% ± 5.0%, P < .05), but was similar to ischemic TPD (68.3% ± 4.9%, P < .05). The receiver operator characteristics areas under curve for ML (0.81 ± 0.02) was similar to reader 1 (0.81 ± 0.02) but superior to reader 2 (0.72 ± 0.02, P < .01) and standalone measure of perfusion (0.77 ± 0.02, P < .01). ML approach is comparable or better than experienced readers in prediction of the early revascularization after MPS, and is significantly better than standalone measures of perfusion derived from MPS.

Quantitative Investigation of the Role of Intra-/Intercellular Dynamics in Bacterial Quorum Sensing.

PubMed

Leaman, Eric J; Geuther, Brian Q; Behkam, Bahareh

2018-04-20

Bacteria utilize diffusible signals to regulate population density-dependent coordinated gene expression in a process called quorum sensing (QS). While the intracellular regulatory mechanisms of QS are well-understood, the effect of spatiotemporal changes in the population configuration on the sensitivity and robustness of the QS response remains largely unexplored. Using a microfluidic device, we quantitatively characterized the emergent behavior of a population of swimming E. coli bacteria engineered with the lux QS system and a GFP reporter. We show that the QS activation time follows a power law with respect to bacterial population density, but this trend is disrupted significantly by microscale variations in population configuration and genetic circuit noise. We then developed a computational model that integrates population dynamics with genetic circuit dynamics to enable accurate (less than 7% error) quantitation of the bacterial QS activation time. Through modeling and experimental analyses, we show that changes in spatial configuration of swimming bacteria can drastically alter the QS activation time, by up to 22%. The integrative model developed herein also enables examination of the performance robustness of synthetic circuits with respect to growth rate, circuit sensitivity, and the population's initial size and spatial structure. Our framework facilitates quantitative tuning of microbial systems performance through rational engineering of synthetic ribosomal binding sites. We have demonstrated this through modulation of QS activation time over an order of magnitude. Altogether, we conclude that predictive engineering of QS-based bacterial systems requires not only the precise temporal modulation of gene expression (intracellular dynamics) but also accounting for the spatiotemporal changes in population configuration (intercellular dynamics).

FDG-PET Response Prediction in Pediatric Hodgkin's Lymphoma: Impact of Metabolically Defined Tumor Volumes and Individualized SUV Measurements on the Positive Predictive Value.

PubMed

Hussien, Amr Elsayed M; Furth, Christian; Schönberger, Stefan; Hundsdoerfer, Patrick; Steffen, Ingo G; Amthauer, Holger; Müller, Hans-Wilhelm; Hautzel, Hubertus

2015-01-28

In pediatric Hodgkin's lymphoma (pHL) early response-to-therapy prediction is metabolically assessed by (18)F-FDG PET carrying an excellent negative predictive value (NPV) but an impaired positive predictive value (PPV). Aim of this study was to improve the PPV while keeping the optimal NPV. A comparison of different PET data analyses was performed applying individualized standardized uptake values (SUV), PET-derived metabolic tumor volume (MTV) and the product of both parameters, termed total lesion glycolysis (TLG); One-hundred-eight PET datasets (PET1, n = 54; PET2, n = 54) of 54 children were analysed by visual and semi-quantitative means. SUVmax, SUVmean, MTV and TLG were obtained the results of both PETs and the relative change from PET1 to PET2 (Δ in %) were compared for their capability of identifying responders and non-responders using receiver operating characteristics (ROC)-curves. In consideration of individual variations in noise and contrasts levels all parameters were additionally obtained after threshold correction to lean body mass and background; All semi-quantitative SUV estimates obtained at PET2 were significantly superior to the visual PET2 analysis. However, ΔSUVmax revealed the best results (area under the curve, 0.92; p < 0.001; sensitivity 100%; specificity 85.4%; PPV 46.2%; NPV 100%; accuracy, 87.0%) but was not significantly superior to SUVmax-estimation at PET2 and ΔTLGmax. Likewise, the lean body mass and background individualization of the datasets did not impove the results of the ROC analyses; Sophisticated semi-quantitative PET measures in early response assessment of pHL patients do not perform significantly better than the previously proposed ΔSUVmax. All analytical strategies failed to improve the impaired PPV to a clinically acceptable level while preserving the excellent NPV.

HBeAg and hepatitis B virus DNA as outcome predictors during therapy with peginterferon alfa-2a for HBeAg-positive chronic hepatitis B.

PubMed

Fried, Michael W; Piratvisuth, Teerha; Lau, George K K; Marcellin, Patrick; Chow, Wan-Cheng; Cooksley, Graham; Luo, Kang-Xian; Paik, Seung Woon; Liaw, Yun-Fan; Button, Peter; Popescu, Matei

2008-02-01

The aims of this study were to evaluate the usefulness of quantitative hepatitis B e antigen (HBeAg) values for predicting HBeAg seroconversion in patients treated with peginterferon alfa-2a and to assess the dynamic changes in quantitative HBeAg during therapy, compared with conventional measures of serum hepatitis B virus DNA. Data were analyzed from a large, randomized, multinational phase III registration trial involving 271 HBV-infected HBeAg-positive patients who received peginterferon alfa-2a plus oral placebo for 48 weeks. HBeAg levels were measured serially during therapy using a microparticle enzyme immunoassay validated with in-house reference standards obtained from the Paul Ehrlich Institute (PEIU/mL). In patients who achieved HBeAg seroconversion, levels of HBeAg consistently decreased during treatment and remained at their lowest level during the 24 weeks of posttreatment follow-up. After 24 weeks of treatment, 4% of patients with the highest levels of HBeAg (>or=100 PEIU/mL) achieved HBeAg seroconversion, yielding a negative predictive value of 96%, which was greater than that obtained for levels of HBV DNA (86%). Late responders to peginterferon alfa-2a could also be differentiated from nonresponders by continued decrease in HBeAg values, which were not evident by changes in HBV DNA. These analyses suggest quantitative HBeAg is a useful adjunctive measurement for predicting HBeAg seroconversion in patients treated with peginterferon when considering both sensitivity and specificity compared with serum HBV DNA.

Evaluation of a rapid quantitative determination method of PSA concentration with gold immunochromatographic strips.

PubMed

Wu, Cheng-Ching; Lin, Hung-Yu; Wang, Chao-Ping; Lu, Li-Fen; Yu, Teng-Hung; Hung, Wei-Chin; Houng, Jer-Yiing; Chung, Fu-Mei; Lee, Yau-Jiunn; Hu, Jin-Jia

2015-11-03

Prostate cancer remains the most common cancer in men. Qualitative or semi-quantitative immunochromatographic measurements of prostate specific antigen (PSA) have been shown to be simple, noninvasive and feasible. The aim of this study was to evaluate an optimized gold immunochromatographic strip device for the detection of PSA, in which the results can be analysed using a Chromogenic Rapid Test Reader to quantitatively assess the test results. This reader measures the reflectance of the signal line via a charge-coupled device camera. For quantitative analysis, PSA concentration was computed via a calibration equation. Capillary blood samples from 305 men were evaluated, and two independent observers interpreted the test results after 12 min. Blood samples were also collected and tested with a conventional quantitative assay. Sensitivity, specificity, positive and negative predictive values, and accuracy of the PSA rapid quantitative test system were 100, 96.6, 89.5, 100, and 97.4 %, respectively. Reproducibility of the test was 99.2, and interobserver variation was 8 % with a false positive rate of 3.4 %. The correlation coefficient between the ordinary quantitative assay and the rapid quantitative test was 0.960. The PSA rapid quantitative test system provided results quickly and was easy to use, so that tests using this system can be easily performed at outpatient clinics or elsewhere. This system may also be useful for initial cancer screening and for point-of-care testing, because results can be obtained within 12 min and at a cost lower than that of conventional quantitative assays.

Evaluation of New Quantitative Assays for Diagnosis and Monitoring of Cytomegalovirus Disease in Human Immunodeficiency Virus-Positive Patients

PubMed Central

Pellegrin, Isabelle; Garrigue, Isabelle; Binquet, Christine; Chene, Genevieve; Neau, Didier; Bonot, Pascal; Bonnet, Fabrice; Fleury, Herve; Pellegrin, Jean-Luc

1999-01-01

Cobas Amplicor CMV Monitor (CMM) and Quantiplex CMV bDNA 2.0 (CMV bDNA 2.0), two new standardized and quantitative assays for the detection of cytomegalovirus (CMV) DNA in plasma and peripheral blood leukocytes (PBLs), respectively, were compared to the CMV viremia assay, pp65 antigenemia assay, and the Amplicor CMV test (P-AMP). The CMV loads were measured in 384 samples from 58 human immunodeficiency virus (HIV) type 1-infected, CMV-seropositive subjects, including 13 with symptomatic CMV disease. The assays were highly concordant (agreement, 0.88 to 0.97) except when the CMV load was low. Quantitative results for plasma and PBLs were significantly correlated (Spearman ρ = 0.92). For PBLs, positive results were obtained 125 days before symptomatic CMV disease by CMV bDNA 2.0 and 124 days by pp65 antigenemia assay, whereas they were obtained 46 days before symptomatic CMV disease by CMM and P-AMP. At the time of CMV disease diagnosis, the sensitivity, specificity, and positive and negative predictive values of CMV bDNA 2.0 were 92.3, 97.8, 92.3, and 97.8%, respectively, whereas they were 92.3, 93.3, 80, and 97.8%, respectively, for the pp65 antigenemia assay; 84.6, 100, 100, and 95.7%, respectively, for CMM; and 76.9, 100, 100, and 93.8%, respectively, for P-AMP. Considering the entire follow-up, the sensitivity, specificity, and positive and negative predictive values of CMV bDNA 2.0 were 92.3, 73.3, 52.1, and 97.1%, respectively, whereas they were 100, 55.5, 39.4, and 100%, respectively, for the pp65 antigenemia assay; 92.3, 86.7, 66.7, and 97.5%, respectively, for CMM; and 84.6, 91.1, 73.3, and 95.3%, respectively, for P-AMP. Detection of CMV in plasma is technically easy and, despite its later positivity (i.e., later than in PBLs), can provide enough information sufficiently early so that HIV-infected patients can be effectively treated. In addition, these standardized quantitative assays accurately monitor the efficacy of anti-CMV treatment. PMID:10488165

Culturally Sensitive Parent Education: A Critical Review of Quantitative Research.

ERIC Educational Resources Information Center

Gorman, Jean Cheng; Balter, Lawrence

1997-01-01

Critically reviews the quantitative literature on culturally sensitive parent education programs, discussing issues of research methodology and program efficacy in producing change among ethnic minority parents and their children. Culturally sensitive programs for African American and Hispanic families are described in detail. Methodological flaws…

Beyond equilibrium climate sensitivity

NASA Astrophysics Data System (ADS)

Knutti, Reto; Rugenstein, Maria A. A.; Hegerl, Gabriele C.

2017-10-01

Equilibrium climate sensitivity characterizes the Earth's long-term global temperature response to increased atmospheric CO2 concentration. It has reached almost iconic status as the single number that describes how severe climate change will be. The consensus on the 'likely' range for climate sensitivity of 1.5 °C to 4.5 °C today is the same as given by Jule Charney in 1979, but now it is based on quantitative evidence from across the climate system and throughout climate history. The quest to constrain climate sensitivity has revealed important insights into the timescales of the climate system response, natural variability and limitations in observations and climate models, but also concerns about the simple concepts underlying climate sensitivity and radiative forcing, which opens avenues to better understand and constrain the climate response to forcing. Estimates of the transient climate response are better constrained by observed warming and are more relevant for predicting warming over the next decades. Newer metrics relating global warming directly to the total emitted CO2 show that in order to keep warming to within 2 °C, future CO2 emissions have to remain strongly limited, irrespective of climate sensitivity being at the high or low end.

An integrative formal model of motivation and decision making: The MGPM*.

PubMed

Ballard, Timothy; Yeo, Gillian; Loft, Shayne; Vancouver, Jeffrey B; Neal, Andrew

2016-09-01

We develop and test an integrative formal model of motivation and decision making. The model, referred to as the extended multiple-goal pursuit model (MGPM*), is an integration of the multiple-goal pursuit model (Vancouver, Weinhardt, & Schmidt, 2010) and decision field theory (Busemeyer & Townsend, 1993). Simulations of the model generated predictions regarding the effects of goal type (approach vs. avoidance), risk, and time sensitivity on prioritization. We tested these predictions in an experiment in which participants pursued different combinations of approach and avoidance goals under different levels of risk. The empirical results were consistent with the predictions of the MGPM*. Specifically, participants pursuing 1 approach and 1 avoidance goal shifted priority from the approach to the avoidance goal over time. Among participants pursuing 2 approach goals, those with low time sensitivity prioritized the goal with the larger discrepancy, whereas those with high time sensitivity prioritized the goal with the smaller discrepancy. Participants pursuing 2 avoidance goals generally prioritized the goal with the smaller discrepancy. Finally, all of these effects became weaker as the level of risk increased. We used quantitative model comparison to show that the MGPM* explained the data better than the original multiple-goal pursuit model, and that the major extensions from the original model were justified. The MGPM* represents a step forward in the development of a general theory of decision making during multiple-goal pursuit. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

68Ga-PSMA-617 PET/CT: a promising new technique for predicting risk stratification and metastatic risk of prostate cancer patients.

PubMed

Liu, Chen; Liu, Teli; Zhang, Ning; Liu, Yiqiang; Li, Nan; Du, Peng; Yang, Yong; Liu, Ming; Gong, Kan; Yang, Xing; Zhu, Hua; Yan, Kun; Yang, Zhi

2018-05-02

The purpose of this study was to investigate the performance of 68 Ga-PSMA-617 PET/CT in predicting risk stratification and metastatic risk of prostate cancer. Fifty newly diagnosed patients with prostate cancer as confirmed by needle biopsy were continuously included, 40 in a train set and ten in a test set. 68 Ga-PSMA-617 PET/CT and clinical data of all patients were retrospectively analyzed. Semi-quantitative analysis of PET images provided maximum standardized uptake (SUVmax) of primary prostate cancer and volumetric parameters including intraprostatic PSMA-derived tumor volume (iPSMA-TV) and intraprostatic total lesion PSMA (iTL-PSMA). According to prostate cancer risk stratification criteria of the NCCN Guideline, all patients were simplified into a low-intermediate risk group or a high-risk group. The semi-quantitative parameters of 68 Ga-PSMA-617 PET/CT were used to establish a univariate logistic regression model for high-risk prostate cancer and its metastatic risk, and to evaluate the diagnostic efficacy of the predictive model. In the train set, 30/40 (75%) patients had high-risk prostate cancer and 10/40 (25%) patients had low-to-moderate-risk prostate cancer; in the test set, 8/10 (80%) patients had high-risk prostate cancer while 2/10 (20%) had low-intermediate risk prostate cancer. The univariate logistic regression model established with SUVmax, iPSMA-TV and iTL-PSMA could all effectively predict high-risk prostate cancer; the AUC of ROC were 0.843, 0.802 and 0.900, respectively. Based on the test set, the sensitivity and specificity of each model were 87.5% and 50% for SUVmax, 62.5% and 100% for iPSMA-TV, and 87.5% and 100% for iTL-PSMA, respectively. The iPSMA-TV and iTL-PSMA-based predictive model could predict the metastatic risk of prostate cancer, the AUC of ROC was 0.863 and 0.848, respectively, but the SUVmax-based prediction model could not predict metastatic risk. Semi-quantitative analysis indexes of 68 Ga-PSMA-617 PET/CT imaging can be used as "imaging biomarkers" to predict risk stratification and metastatic risk of prostate cancer.

Detection of Independent Associations of Plasma Lipidomic Parameters with Insulin Sensitivity Indices Using Data Mining Methodology.

PubMed

Kopprasch, Steffi; Dheban, Srirangan; Schuhmann, Kai; Xu, Aimin; Schulte, Klaus-Martin; Simeonovic, Charmaine J; Schwarz, Peter E H; Bornstein, Stefan R; Shevchenko, Andrej; Graessler, Juergen

2016-01-01

Glucolipotoxicity is a major pathophysiological mechanism in the development of insulin resistance and type 2 diabetes mellitus (T2D). We aimed to detect subtle changes in the circulating lipid profile by shotgun lipidomics analyses and to associate them with four different insulin sensitivity indices. The cross-sectional study comprised 90 men with a broad range of insulin sensitivity including normal glucose tolerance (NGT, n = 33), impaired glucose tolerance (IGT, n = 32) and newly detected T2D (n = 25). Prior to oral glucose challenge plasma was obtained and quantitatively analyzed for 198 lipid molecular species from 13 different lipid classes including triacylglycerls (TAGs), phosphatidylcholine plasmalogen/ether (PC O-s), sphingomyelins (SMs), and lysophosphatidylcholines (LPCs). To identify a lipidomic signature of individual insulin sensitivity we applied three data mining approaches, namely least absolute shrinkage and selection operator (LASSO), Support Vector Regression (SVR) and Random Forests (RF) for the following insulin sensitivity indices: homeostasis model of insulin resistance (HOMA-IR), glucose insulin sensitivity index (GSI), insulin sensitivity index (ISI), and disposition index (DI). The LASSO procedure offers a high prediction accuracy and and an easier interpretability than SVR and RF. After LASSO selection, the plasma lipidome explained 3% (DI) to maximal 53% (HOMA-IR) variability of the sensitivity indexes. Among the lipid species with the highest positive LASSO regression coefficient were TAG 54:2 (HOMA-IR), PC O- 32:0 (GSI), and SM 40:3:1 (ISI). The highest negative regression coefficient was obtained for LPC 22:5 (HOMA-IR), TAG 51:1 (GSI), and TAG 58:6 (ISI). Although a substantial part of lipid molecular species showed a significant correlation with insulin sensitivity indices we were able to identify a limited number of lipid metabolites of particular importance based on the LASSO approach. These few selected lipids with the closest connection to sensitivity indices may help to further improve disease risk prediction and disease and therapy monitoring.

The use of copula functions for predictive analysis of correlations between extreme storm tides

NASA Astrophysics Data System (ADS)

Domino, Krzysztof; Błachowicz, Tomasz; Ciupak, Maurycy

2014-11-01

In this paper we present a method used in quantitative description of weakly predictable hydrological, extreme events at inland sea. Investigations for correlations between variations of individual measuring points, employing combined statistical methods, were carried out. As a main tool for this analysis we used a two-dimensional copula function sensitive for correlated extreme effects. Additionally, a new proposed methodology, based on Detrended Fluctuations Analysis (DFA) and Anomalous Diffusion (AD), was used for the prediction of negative and positive auto-correlations and associated optimum choice of copula functions. As a practical example we analysed maximum storm tides data recorded at five spatially separated places at the Baltic Sea. For the analysis we used Gumbel, Clayton, and Frank copula functions and introduced the reversed Clayton copula. The application of our research model is associated with modelling the risk of high storm tides and possible storm flooding.

An indigenously developed nitrite kit to aid in the diagnosis of urinary tract infection.

PubMed

Sood, S; Upadhyaya, P; Kapil, A; Lodha, R; Jain, Y; Bagga, A

1999-09-01

To evaluate the utility of an indigenously developed nitrite kit for the rapid diagnosis of urinary tract infection (UTI) METHODS: 1018 urine specimens were collected from all cases where there was clinical suspicion of UTI. Samples were cultured as per standard microbiological protocol. Presence of nitrites was indicated by the development of purple color on addition of color developing solution and compared with the set of graded positive and negative controls also provided in the Kit. The results of the nitrite kit were compared with the semi-quantitative urine culture as the gold standard. The sensitivity, specificity, positive predictive and negative predictive values were 47%, 87%, 31% and 93%, respectively. Nitrite kit as a screening test can decrease the work load in the clinical bacteriology laboratory. More importantly in a field set up that is devoid of culture facilities, it can be used to correctly predict the absence of UTI.

Diffusion rate limitations in actin-based propulsion of hard and deformable particles.

PubMed

Dickinson, Richard B; Purich, Daniel L

2006-08-15

The mechanism by which actin polymerization propels intracellular vesicles and invasive microorganisms remains an open question. Several recent quantitative studies have examined propulsion of biomimetic particles such as polystyrene microspheres, phospholipid vesicles, and oil droplets. In addition to allowing quantitative measurement of parameters such as the dependence of particle speed on its size, these systems have also revealed characteristic behaviors such a saltatory motion of hard particles and oscillatory deformation of soft particles. Such measurements and observations provide tests for proposed mechanisms of actin-based motility. In the actoclampin filament end-tracking motor model, particle-surface-bound filament end-tracking proteins are involved in load-insensitive processive insertion of actin subunits onto elongating filament plus-ends that are persistently tethered to the surface. In contrast, the tethered-ratchet model assumes working filaments are untethered and the free-ended filaments grow as thermal ratchets in a load-sensitive manner. This article presents a model for the diffusion and consumption of actin monomers during actin-based particle propulsion to predict the monomer concentration field around motile particles. The results suggest that the various behaviors of biomimetic particles, including dynamic saltatory motion of hard particles and oscillatory vesicle deformations, can be quantitatively and self-consistently explained by load-insensitive, diffusion-limited elongation of (+)-end-tethered actin filaments, consistent with predictions of the actoclampin filament-end tracking mechanism.

Assessing treatment response in triple-negative breast cancer from quantitative image analysis in perfusion magnetic resonance imaging.

PubMed

Banerjee, Imon; Malladi, Sadhika; Lee, Daniela; Depeursinge, Adrien; Telli, Melinda; Lipson, Jafi; Golden, Daniel; Rubin, Daniel L

2018-01-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is sensitive but not specific to determining treatment response in early stage triple-negative breast cancer (TNBC) patients. We propose an efficient computerized technique for assessing treatment response, specifically the residual tumor (RT) status and pathological complete response (pCR), in response to neoadjuvant chemotherapy. The proposed approach is based on Riesz wavelet analysis of pharmacokinetic maps derived from noninvasive DCE-MRI scans, obtained before and after treatment. We compared the performance of Riesz features with the traditional gray level co-occurrence matrices and a comprehensive characterization of the lesion that includes a wide range of quantitative features (e.g., shape and boundary). We investigated a set of predictive models ([Formula: see text]) incorporating distinct combinations of quantitative characterizations and statistical models at different time points of the treatment and some area under the receiver operating characteristic curve (AUC) values we reported are above 0.8. The most efficient models are based on first-order statistics and Riesz wavelets, which predicted RT with an AUC value of 0.85 and pCR with an AUC value of 0.83, improving results reported in a previous study by [Formula: see text]. Our findings suggest that Riesz texture analysis of TNBC lesions can be considered a potential framework for optimizing TNBC patient care.

Error-growth dynamics and predictability of surface thermally induced atmospheric flow

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

Zeng, X.; Pielke, R.A.

1993-09-01

Using the CSU Regional Atmospheric Modeling System (RAMS) in its nonhydrostatic and compressible configuration, over 200 two-dimensional simulations with [Delta]x = 2 km and [Delta]x = 100 m are performed to study in detail the initial adjustment process and the error-growth dynamics of surface thermally induced circulation including the sensitivity to initial conditions, boundary conditions, and model parameters, and to study the predictability as a function of the size of surface heat patches under a calm mean wind. It is found that the error growth is not sensitive to the characterisitics of the initial perturbations. The numerical smoothing has amore » strong impact on the initial adjustment process and on the error-growth dynamics. The predictability and flow structures, it is found that the vertical velocity field is strongly affected by the mean wind, and the flow structures are quite sensitive to the initial soil water content. The transition from organized flow to the situation in which fluxes are dominated by noncoherent turbulent eddies under a calm mean wind is quantitatively evaluated and this transition is different for different variables. The relationship between the predictability of a realization and of an ensemble average is discussed. The predictability and the coherent circulations modulated by the surface inhomogeneities are also studied by computing the autocorrelations and the power spectra. The three-dimensional mesoscale and large-eddy simulations are performed to verify the above results. It is found that the two-dimensional mesoscale (or fine resolution) simulation yields very close or similar results regarding the predictability as those from the three-dimensional mesoscale (or large eddy) simulation. The horizontally averaged quantities based on two-dimensional fine-resolution simulations are insensitive to initial perturbations and agree with those based on three-dimensional large-eddy simulations. 87 refs., 25 figs.« less

Measurement Uncertainty Budget of the PMV Thermal Comfort Equation

NASA Astrophysics Data System (ADS)

Ekici, Can

2016-05-01

Fanger's predicted mean vote (PMV) equation is the result of the combined quantitative effects of the air temperature, mean radiant temperature, air velocity, humidity activity level and clothing thermal resistance. PMV is a mathematical model of thermal comfort which was developed by Fanger. The uncertainty budget of the PMV equation was developed according to GUM in this study. An example is given for the uncertainty model of PMV in the exemplification section of the study. Sensitivity coefficients were derived from the PMV equation. Uncertainty budgets can be seen in the tables. A mathematical model of the sensitivity coefficients of Ta, hc, T_{mrt}, T_{cl}, and Pa is given in this study. And the uncertainty budgets for hc, T_{cl}, and Pa are given in this study.

Model of Silicon Refining During Tapping: Removal of Ca, Al, and Other Selected Element Groups

NASA Astrophysics Data System (ADS)

Olsen, Jan Erik; Kero, Ida T.; Engh, Thorvald A.; Tranell, Gabriella

2017-04-01

A mathematical model for industrial refining of silicon alloys has been developed for the so-called oxidative ladle refining process. It is a lumped (zero-dimensional) model, based on the mass balances of metal, slag, and gas in the ladle, developed to operate with relatively short computational times for the sake of industrial relevance. The model accounts for a semi-continuous process which includes both the tapping and post-tapping refining stages. It predicts the concentrations of Ca, Al, and trace elements, most notably the alkaline metals, alkaline earth metal, and rare earth metals. The predictive power of the model depends on the quality of the model coefficients, the kinetic coefficient, τ, and the equilibrium partition coefficient, L for a given element. A sensitivity analysis indicates that the model results are most sensitive to L. The model has been compared to industrial measurement data and found to be able to qualitatively, and to some extent quantitatively, predict the data. The model is very well suited for alkaline and alkaline earth metals which respond relatively fast to the refining process. The model is less well suited for elements such as the lanthanides and Al, which are refined more slowly. A major challenge for the prediction of the behavior of the rare earth metals is that reliable thermodynamic data for true equilibrium conditions relevant to the industrial process is not typically available in literature.

Novel benzanthrone probes for membrane and protein studies

NASA Astrophysics Data System (ADS)

Ryzhova, Olga; Vus, Kateryna; Trusova, Valeriya; Kirilova, Elena; Kirilov, Georgiy; Gorbenko, Galyna; Kinnunen, Paavo

2016-09-01

The applicability of a series of novel benzanthrone dyes to monitoring the changes in physicochemical properties of lipid bilayer and to differentiating between the native and aggregated protein states has been evaluated. Based on the quantitative parameters of the dye-membrane and dye-protein binding derived from the fluorimetric titration data, the most prospective membrane probes and amyloid tracers have been selected from the group of examined compounds. Analysis of the red edge excitation shifts of the membrane- and amyloid-bound dyes provided information on the properties of benzanthrone binding sites within the lipid and protein matrixes. To understand how amyloid specificity of benzanthrones correlates with their structure, quantitative structure activity relationship (QSAR) analysis was performed involving a range of quantum chemical molecular descriptors. A statistically significant model was obtained for predicting the sensitivity of novel benzanthrone dyes to amyloid fibrils.

Development of an in Silico Model of DPPH• Free Radical Scavenging Capacity: Prediction of Antioxidant Activity of Coumarin Type Compounds.

PubMed

Goya Jorge, Elizabeth; Rayar, Anita Maria; Barigye, Stephen J; Jorge Rodríguez, María Elisa; Sylla-Iyarreta Veitía, Maité

2016-06-07

A quantitative structure-activity relationship (QSAR) study of the 2,2-diphenyl-l-picrylhydrazyl (DPPH•) radical scavenging ability of 1373 chemical compounds, using DRAGON molecular descriptors (MD) and the neural network technique, a technique based on the multilayer multilayer perceptron (MLP), was developed. The built model demonstrated a satisfactory performance for the training ( R 2 = 0.713 ) and test set ( Q ext 2 = 0.654 ) , respectively. To gain greater insight on the relevance of the MD contained in the MLP model, sensitivity and principal component analyses were performed. Moreover, structural and mechanistic interpretation was carried out to comprehend the relationship of the variables in the model with the modeled property. The constructed MLP model was employed to predict the radical scavenging ability for a group of coumarin-type compounds. Finally, in order to validate the model's predictions, an in vitro assay for one of the compounds (4-hydroxycoumarin) was performed, showing a satisfactory proximity between the experimental and predicted pIC50 values.

Composition of the Vaginal Microbiota in Women of Reproductive Age – Sensitive and Specific Molecular Diagnosis of Bacterial Vaginosis Is Possible?

PubMed Central

Shipitsyna, Elena; Roos, Annika; Datcu, Raluca; Hallén, Anders; Fredlund, Hans; Jensen, Jørgen S.; Engstrand, Lars; Unemo, Magnus

2013-01-01

Background and Objective Bacterial vaginosis (BV) is the most common vaginal disorder, characterized by depletion of the normal lactobacillus-dominant microbiota and overgrowth of commensal anaerobic bacteria. This study aimed to investigate the composition of the vaginal microbiota in women of reproductive age (healthy women and women with BV), with the view of developing molecular criteria for BV diagnosis. Materials and Methods Vaginal samples from 163 women (79 control, 73 BV and 11 intermediate (Lactobacillary grade II flora) cases) were analyzed using 454 pyrosequencing of the hypervariable regions V3–V4 of the 16S rRNA gene and 16 quantitative bacterial species/genus-specific real-time PCR assays. Sensitivities and specificities of potential BV markers were computed using the Amsel criteria as reference standard for BV. The use of quantitative thresholds for prediction of BV, determined for both relative abundance measured with 454 pyrosequencing and bacterial load measured with qPCR, was evaluated. Results Relative to the healthy women, the BV patients had in their vaginal microbiota significantly higher prevalence, loads and relative abundances of the majority of BV associated bacteria. However, only Gardnerella vaginalis, Atopobium vaginae, Eggerthella, Prevotella, BVAB2 and Megasphaera type 1 detected at or above optimal thresholds were highly predictable for BV, with the best diagnostic accuracy shown for A. vaginae. The depletion of Lactobacillus species combined with the presence of either G. vaginalis or A. vaginae at diagnostic levels was a highly accurate BV predictor. Conclusions Quantitative determination of the presence of G. vaginalis, A. vaginae, Eggerthella, Prevotella, BVAB2 and Megasphaera type 1 as well as the depletion of Lactobacillus was highly accurate for BV diagnosis. Measurements of abundance of normal and BV microbiota relative to total bacteria in vaginal fluid may provide more accurate BV diagnosis, and be used for test-of-cure, rather than qualitative detection or absolute counts of BV related microorganisms. PMID:23585843

The Impact of Quantitative Data Provided by a Multi-spectral Digital Skin Lesion Analysis Device on Dermatologists'Decisions to Biopsy Pigmented Lesions.

PubMed

Farberg, Aaron S; Winkelmann, Richard R; Tucker, Natalie; White, Richard; Rigel, Darrell S

2017-09-01

BACKGROUND: Early diagnosis of melanoma is critical to survival. New technologies, such as a multi-spectral digital skin lesion analysis (MSDSLA) device [MelaFind, STRATA Skin Sciences, Horsham, Pennsylvania] may be useful to enhance clinician evaluation of concerning pigmented skin lesions. Previous studies evaluated the effect of only the binary output. OBJECTIVE: The objective of this study was to determine how decisions dermatologists make regarding pigmented lesion biopsies are impacted by providing both the underlying classifier score (CS) and associated probability risk provided by multi-spectral digital skin lesion analysis. This outcome was also compared against the improvement reported with the provision of only the binary output. METHODS: Dermatologists attending an educational conference evaluated 50 pigmented lesions (25 melanomas and 25 benign lesions). Participants were asked if they would biopsy the lesion based on clinical images, and were asked this question again after being shown multi-spectral digital skin lesion analysis data that included the probability graphs and classifier score. RESULTS: Data were analyzed from a total of 160 United States board-certified dermatologists. Biopsy sensitivity for melanoma improved from 76 percent following clinical evaluation to 92 percent after quantitative multi-spectral digital skin lesion analysis information was provided ( p <0.0001). Specificity improved from 52 percent to 79 percent ( p <0.0001). The positive predictive value increased from 61 percent to 81 percent ( p <0.01) when the quantitative data were provided. Negative predictive value also increased (68% vs. 91%, p<0.01), and overall biopsy accuracy was greater with multi-spectral digital skin lesion analysis (64% vs. 86%, p <0.001). Interrater reliability improved (intraclass correlation 0.466 before, 0.559 after). CONCLUSION: Incorporating the classifier score and probability data into physician evaluation of pigmented lesions led to both increased sensitivity and specificity, thereby resulting in more accurate biopsy decisions.

A novel Alu-based real-time PCR method for the quantitative detection of plasma circulating cell-free DNA: Sensitivity and specificity for the diagnosis of myocardial infarction

PubMed Central

LOU, XIAOLI; HOU, YANQIANG; LIANG, DONGYU; PENG, LIANG; CHEN, HONGWEI; MA, SHANYUAN; ZHANG, LURONG

2015-01-01

In the present study, we aimed to develop and validate a rapid and sensitive, Alu-based real-time PCR method for the detection of circulating cell-free DNA (cfDNA). This method targeted repetitive elements of the Alu reduplicative elements in the human genome, followed by signal amplification using fluorescence quantification. Standard Alu-puc57 vectors were constructed and 5 pairs of specific primers were designed. Valuation was conducted concerning linearity, variation and recovery. We found 5 linear responses (R1–5=0.998–0.999). The average intra- and inter-assay coefficients of variance were 12.98 and 10.75%, respectively. The recovery was 82.33–114.01%, with a mean recovery index of 101.26%. This Alu-based assay was reliable, accurate and sensitive for the quantitative detection of cfDNA. Plasma from normal controls and patients with myocardial infarction (MI) were analyzed, and the baseline levels of cfDNA were higher in the MI group. The area under the receiver operating characteristic (ROC) curve for Alu1, Alu2, Alu3, Alu4, Alu5 and Alu (Alu1 + Alu2 + Alu3 + Alu4 + Alu5) was 0.887, 0.758, 0.857, 0.940, 0.968 and 0.933, respectively. The optimal cut-off value for Alu1, Alu2, Alu3, Alu4, Alu5 and Alu to predict MI was 3.71, 1.93, 0.22, 3.73, 6.13 and 6.40 log copies/ml. We demonstrate that this new method is a reliable, accurate and sensitive method for the quantitative detection of cfDNA and that it is useful for studying the regulation of cfDNA in certain pathological conditions. Alu4, Alu5 and Alu showed better sensitivity and specificity for the diagnosis of MI compared with cardiac troponin I (cTnI), creatine kinase MB (CK-MB) isoenzyme and lactate dehydrogenase (LDH). Alu5 had the best prognostic ability. PMID:25374065

A novel multi-walled carbon nanotube-based antibody conjugate for quantitative and semi-quantitative lateral flow assays.

PubMed

Sun, Wenjuan; Hu, Xiaolong; Liu, Jia; Zhang, Yurong; Lu, Jianzhong; Zeng, Libo

2017-10-01

In this study, the multi-walled carbon nanotubes (MWCNTs) were applied in lateral flow strips (LFS) for semi-quantitative and quantitative assays. Firstly, the solubility of MWCNTs was improved using various surfactants to enhance their biocompatibility for practical application. The dispersed MWCNTs were conjugated with the methamphetamine (MET) antibody in a non-covalent manner and then manufactured into the LFS for the quantitative detection of MET. The MWCNTs-based lateral flow assay (MWCNTs-LFA) exhibited an excellent linear relationship between the values of test line and MET when its concentration ranges from 62.5 to 1500 ng/mL. The sensitivity of the LFS was evaluated by conjugating MWCNTs with HCG antibody and the MWCNTs conjugated method is 10 times more sensitive than the one conjugated with classical colloidal gold nanoparticles. Taken together, our data demonstrate that MWCNTs-LFA is a more sensitive and reliable assay for semi-quantitative and quantitative detection which can be used in forensic analysis.

The application of IS6110-baced loop-mediated isothermal amplification (LAMP) in the early diagnosis of tuberculous meningitis.

PubMed

Sun, Wen-Wen; Sun, Qin; Yan, Li-Ping; Zhang, Qing

2017-08-22

Here, we evaluated the potential activity of rapid Mycobacterium tuberculosis detection with loop-mediated isothermal amplification (LAMP), for the early diagnosis of tuberculous meningitis (TBM). Patients with suspected TBM from January 2014 to December 2015 were reviewed retrospectively. The cerebrospinalfluid(CSF) was collected. Acid-fast bacillus (AFB) staining, MGIT 960 culture, real-time fluorescent quantitative polymerase chain reaction (RTFQ PCR) and LAMP were performed. A total of 200 patients were included in the study. Of which, 172 of them were diagnosed with TBM (86.00%). The sensitivities of AFB staining, MGIT 960 culture, LAMP and RTFQ PCR for TBM diagnosis were 2.91% (5/172), 12.79% (22/172), 43.02% (74/172), and 34.30% (59/172), respectively. The sensitivity of LAMP for TBM was significantly higher than those of AFB staining and MGIT960 culture ( χ2 = 75.11, P < 0.001; χ2 = 43.88, P = 0.002). LAMP's sensitivity was however comparable to RTFQ PCR assay ( χ2 = 2.08, P = 0.130). The specificity, positive predictive value and negative predictive value of LAMP in the diagnosis of TBM were 92.86% (26/28), 97.37% (74/76) and 20.97 % (26/124), respectively. The overall consistency between LAMP and RTFQ PCR in the diagnosis of TBM was 88.5% (177/200), with Kappa value of 0.870. The consistency between LAMP and MGIT960 culture was 71% (142/200), with Kappa value of 0.730. Among all the methods, LAMP had high sensitivity, specificity and positive predictive value, showing high consistency with MGIT960 culture and RTFQ PCR.

Analysis of a quantitative PCR assay for CMV infection in liver transplant recipients: an intent to find the optimal cut-off value.

PubMed

Martín-Dávila, P; Fortún, J; Gutiérrez, C; Martí-Belda, P; Candelas, A; Honrubia, A; Barcena, R; Martínez, A; Puente, A; de Vicente, E; Moreno, S

2005-06-01

Preemptive therapy required highly predictive tests for CMV disease. CMV antigenemia assay (pp65 Ag) has been commonly used for rapid diagnosis of CMV infection. Amplification methods for early detection of CMV DNA are under analysis. To compare two diagnostic methods for CMV infection and disease in this population: quantitative PCR (qPCR) performed in two different samples, plasma and leukocytes (PMNs) and using a commercial diagnostic test (COBAS Amplicor Monitor Test) versus pp65 Ag. Prospective study conducted in liver transplant recipients from February 2000 to February 2001. Analyses were performed on 164 samples collected weekly during early post-transplant period from 33 patients. Agreements higher than 78% were observed between the three assays. Optimal qPCR cut-off values were calculated using ROC curves for two specific antigenemia values. For antigenemia >or=10 positive cells, the optimal cut-off value for qPCR in plasma was 1330 copies/ml, with a sensitivity (S) of 58% and a specificity (E) of 98% and the optimal cut-off value for qPCR-cells was 713 copies/5x10(6) cells (S:91.7% and E:86%). Using a threshold of antigenemia >or=20 positive cells, the optimal cut-off values were 1330 copies/ml for qPCR-plasma (S 87%; E 98%) and 4755 copies/5x10(6) cells for qPCR-cells (S 87.5%; E 98%). Prediction values for the three assays were calculated in patients with CMV disease (9 pts; 27%). Considering the assays in a qualitative way, the most sensitive was CMV PCR in cells (S: 100%, E: 54%, PPV: 40%; NPV: 100%). Using specific cut-off values for disease detection the sensitivity, specificity, PPV and NPV for antigenemia >or=10 positive cells were: 89%; 83%; 67%; 95%, respectively. For qPCR-cells >or=713 copies/5x10(6) cells: 100%; 54%; 33% and 100% and for plasma-qPCR>or=1330 copies/ml: 78%, 77%, 47%, 89% respectively. Optimal cut-off for viral load performed in plasma and cells can be obtained for the breakpoint antigenemia value recommended for initiating preemptive therapy with high specificities and sensitivities. Diagnostic assays like CMV pp65 Ag and quantitative PCR for CMV have similar efficiency and could be recommended as methods of choice for diagnosis and monitoring of active CMV infection after transplantation.

Utility of Clinical Parameters and Multiparametric MRI as Predictive Factors for Differentiating Uterine Sarcoma From Atypical Leiomyoma.

PubMed

Bi, Qiu; Xiao, Zhibo; Lv, Fajin; Liu, Yao; Zou, Chunxia; Shen, Yiqing

2018-02-05

The objective of this study was to find clinical parameters and qualitative and quantitative magnetic resonance imaging (MRI) features for differentiating uterine sarcoma from atypical leiomyoma (ALM) preoperatively and to calculate predictive values for uterine sarcoma. Data from 60 patients with uterine sarcoma and 88 patients with ALM confirmed by surgery and pathology were collected. Clinical parameters, qualitative MRI features, diffusion-weighted imaging with apparent diffusion coefficient values, and quantitative parameters of dynamic contrast-enhanced MRI of these two tumor types were compared. Predictive values for uterine sarcoma were calculated using multivariable logistic regression. Patient clinical manifestations, tumor locations, margins, T2-weighted imaging signals, mean apparent diffusion coefficient values, minimum apparent diffusion coefficient values, and time-signal intensity curves of solid tumor components were obvious significant parameters for distinguishing between uterine sarcoma and ALM (all P <.001). Abnormal vaginal bleeding, tumors located mainly in the uterine cavity, ill-defined tumor margins, and mean apparent diffusion coefficient values of <1.272 × 10 -3  mm 2 /s were significant preoperative predictors of uterine sarcoma. When the overall scores of these four predictors were greater than or equal to 7 points, the sensitivity, the specificity, the accuracy, and the positive and negative predictive values were 88.9%, 99.9%, 95.7%, 97.0%, and 95.1%, respectively. The use of clinical parameters and multiparametric MRI as predictive factors was beneficial for diagnosing uterine sarcoma preoperatively. These findings could be helpful for guiding treatment decisions. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Combined visual and semi-quantitative assessment of 123I-FP-CIT SPECT for the diagnosis of dopaminergic neurodegenerative diseases.

PubMed

Ueda, Jun; Yoshimura, Hajime; Shimizu, Keiji; Hino, Megumu; Kohara, Nobuo

2017-07-01

Visual and semi-quantitative assessments of 123 I-FP-CIT single-photon emission computed tomography (SPECT) are useful for the diagnosis of dopaminergic neurodegenerative diseases (dNDD), including Parkinson's disease, dementia with Lewy bodies, progressive supranuclear palsy, multiple system atrophy, and corticobasal degeneration. However, the diagnostic value of combined visual and semi-quantitative assessment in dNDD remains unclear. Among 239 consecutive patients with a newly diagnosed possible parkinsonian syndrome who underwent 123 I-FP-CIT SPECT in our medical center, 114 patients with a disease duration less than 7 years were diagnosed as dNDD with the established criteria or as non-dNDD according to clinical judgment. We retrospectively examined their clinical characteristics and visual and semi-quantitative assessments of 123 I-FP-CIT SPECT. The striatal binding ratio (SBR) was used as a semi-quantitative measure of 123 I-FP-CIT SPECT. We calculated the sensitivity and specificity of visual assessment alone, semi-quantitative assessment alone, and combined visual and semi-quantitative assessment for the diagnosis of dNDD. SBR was correlated with visual assessment. Some dNDD patients with a normal visual assessment had an abnormal SBR, and vice versa. There was no statistically significant difference between sensitivity of the diagnosis with visual assessment alone and semi-quantitative assessment alone (91.2 vs. 86.8%, respectively, p = 0.29). Combined visual and semi-quantitative assessment demonstrated superior sensitivity (96.7%) to visual assessment (p = 0.03) or semi-quantitative assessment (p = 0.003) alone with equal specificity. Visual and semi-quantitative assessments of 123 I-FP-CIT SPECT are helpful for the diagnosis of dNDD, and combined visual and semi-quantitative assessment shows superior sensitivity with equal specificity.

Building predictive in vitro pulmonary toxicity assays using high-throughput imaging and artificial intelligence.

PubMed

Lee, Jia-Ying Joey; Miller, James Alastair; Basu, Sreetama; Kee, Ting-Zhen Vanessa; Loo, Lit-Hsin

2018-06-01

Human lungs are susceptible to the toxicity induced by soluble xenobiotics. However, the direct cellular effects of many pulmonotoxic chemicals are not always clear, and thus, a general in vitro assay for testing pulmonotoxicity applicable to a wide variety of chemicals is not currently available. Here, we report a study that uses high-throughput imaging and artificial intelligence to build an in vitro pulmonotoxicity assay by automatically comparing and selecting human lung-cell lines and their associated quantitative phenotypic features most predictive of in vivo pulmonotoxicity. This approach is called "High-throughput In vitro Phenotypic Profiling for Toxicity Prediction" (HIPPTox). We found that the resulting assay based on two phenotypic features of a human bronchial epithelial cell line, BEAS-2B, can accurately classify 33 reference chemicals with human pulmonotoxicity information (88.8% balance accuracy, 84.6% sensitivity, and 93.0% specificity). In comparison, the predictivity of a standard cell-viability assay on the same set of chemicals is much lower (77.1% balanced accuracy, 84.6% sensitivity, and 69.5% specificity). We also used the assay to evaluate 17 additional test chemicals with unknown/unclear human pulmonotoxicity, and experimentally confirmed that many of the pulmonotoxic reference and predicted-positive test chemicals induce DNA strand breaks and/or activation of the DNA-damage response (DDR) pathway. Therefore, HIPPTox helps us to uncover these common modes-of-action of pulmonotoxic chemicals. HIPPTox may also be applied to other cell types or models, and accelerate the development of predictive in vitro assays for other cell-type- or organ-specific toxicities.

Deriving field-based species sensitivity distributions (f-SSDs) from stacked species distribution models (S-SDMs).

PubMed

Schipper, Aafke M; Posthuma, Leo; de Zwart, Dick; Huijbregts, Mark A J

2014-12-16

Quantitative relationships between species richness and single environmental factors, also called species sensitivity distributions (SSDs), are helpful to understand and predict biodiversity patterns, identify environmental management options and set environmental quality standards. However, species richness is typically dependent on a variety of environmental factors, implying that it is not straightforward to quantify SSDs from field monitoring data. Here, we present a novel and flexible approach to solve this, based on the method of stacked species distribution modeling. First, a species distribution model (SDM) is established for each species, describing its probability of occurrence in relation to multiple environmental factors. Next, the predictions of the SDMs are stacked along the gradient of each environmental factor with the remaining environmental factors at fixed levels. By varying those fixed levels, our approach can be used to investigate how field-based SSDs for a given environmental factor change in relation to changing confounding influences, including for example optimal, typical, or extreme environmental conditions. This provides an asset in the evaluation of potential management measures to reach good ecological status.

Musculoskeletal ultrasound and other imaging modalities in rheumatoid arthritis.

PubMed

Ohrndorf, Sarah; Werner, Stephanie G; Finzel, Stephanie; Backhaus, Marina

2013-05-01

This review refers to the use of musculoskeletal ultrasound in patients with rheumatoid arthritis (RA) both in clinical practice and research. Furthermore, other novel sensitive imaging modalities (high resolution peripheral quantitative computed tomography and fluorescence optical imaging) are introduced in this article. Recently published ultrasound studies presented power Doppler activity by ultrasound highly predictive for later radiographic erosions in patients with RA. Another study presented synovitis detected by ultrasound being predictive of subsequent structural radiographic destruction irrespective of the ultrasound modality (grayscale ultrasound/power Doppler ultrasound). Further studies are currently under way which prove ultrasound findings as imaging biomarkers in the destructive process of RA. Other introduced novel imaging modalities are in the validation process to prove their impact and significance in inflammatory joint diseases. The introduced imaging modalities show different sensitivities and specificities as well as strength and weakness belonging to the assessment of inflammation, differentiation of the involved structures and radiological progression. The review tries to give an answer regarding how to best integrate them into daily clinical practice with the aim to improve the diagnostic algorithms, the daily patient care and, furthermore, the disease's outcome.

Supercritical water oxidation of quinazoline: Reaction kinetics and modeling.

PubMed

Gong, Yanmeng; Guo, Yang; Wang, Shuzhong; Song, Wenhan; Xu, Donghai

2017-03-01

This paper presents a first quantitative kinetic model for supercritical water oxidation (SCWO) of quinazoline that describes the formation and interconversion of intermediates and final products at 673-873 K. The set of 11 reaction pathways for phenol, pyrimidine, naphthalene, NH 3 , etc, involved in the simplified reaction network proved sufficient for fitting the experimental results satisfactorily. We validated the model prediction ability on CO 2 yields at initial quinazoline loading not used in the parameter estimation. Reaction rate analysis and sensitivity analysis indicate that nearly all reactions reach their thermodynamic equilibrium within 300 s. The pyrimidine yielding from quinazoline is the dominant ring-opening pathway and provides a significant contribution to CO 2 formation. Low sensitivity of NH 3 decomposition rate to concentration confirms its refractory nature in SCWO. Nitrogen content in liquid products decreases whereas that in gaseous phase increases as reaction time prolonged. The nitrogen predicted by the model in gaseous phase combined with the experimental nitrogen in liquid products gives an accurate nitrogen balance of conversion process. Copyright © 2016 Elsevier Ltd. All rights reserved.

Duration comparison: relative stimulus differences stimulus age, and stimulus predictiveness.

PubMed Central

Stubbs, D A; Dreyfus, L R; Fetterman, J G; Boynton, D M; Locklin, N; Smith, L D

1994-01-01

Under a psychophysical trials procedure, pigeons were presented with a red light of one duration followed by a green light of a second duration. Eight geometrically spaced base durations were paired with one of four shorter and four longer durations as the alternate member of a duration pair, with different pairs randomly intermixed. One choice was reinforced if red had lasted longer than green, and a second choice was reinforced if green had lasted longer. Performance was compared when all the base durations and their pair members were included (entire-range condition) or when only the four longest base durations and their comparison durations (restricted-range condition) were used. Discrimination sensitivity decreased for longer duration pairs under both conditions, supporting a memory-based account. Sensitivity was lower under the restricted-range condition. Under both conditions, a bias to report "green as longer" increased as the second green duration increased. Bias changed as a matching function of the green-duration predictiveness of the correct choice. The results are related to a quantitative model of timing and remembering proposed by Staddon. PMID:8064211

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

Pavlickova, Katarina; Vyskupova, Monika, E-mail: vyskupova@fns.uniba.sk

Cumulative environmental impact assessment deals with the occasional use in practical application of environmental impact assessment process. The main reasons are the difficulty of cumulative impact identification caused by lack of data, inability to measure the intensity and spatial effect of all types of impacts and the uncertainty of their future evolution. This work presents a method proposal to predict cumulative impacts on the basis of landscape vulnerability evaluation. For this purpose, qualitative assessment of landscape ecological stability is conducted and major vulnerability indicators of environmental and socio-economic receptors are specified and valuated. Potential cumulative impacts and the overall impactmore » significance are predicted quantitatively in modified Argonne multiple matrixes while considering the vulnerability of affected landscape receptors and the significance of impacts identified individually. The method was employed in the concrete environmental impact assessment process conducted in Slovakia. The results obtained in this case study reflect that this methodology is simple to apply, valid for all types of impacts and projects, inexpensive and not time-consuming. The objectivity of the partial methods used in this procedure is improved by quantitative landscape ecological stability evaluation, assignment of weights to vulnerability indicators based on the detailed characteristics of affected factors, and grading impact significance. - Highlights: • This paper suggests a method proposal for cumulative impact prediction. • The method includes landscape vulnerability evaluation. • The vulnerability of affected receptors is determined by their sensitivity. • This method can increase the objectivity of impact prediction in the EIA process.« less

Modeling the Afferent Dynamics of the Baroreflex Control System

PubMed Central

Mahdi, Adam; Sturdy, Jacob; Ottesen, Johnny T.; Olufsen, Mette S.

2013-01-01

In this study we develop a modeling framework for predicting baroreceptor firing rate as a function of blood pressure. We test models within this framework both quantitatively and qualitatively using data from rats. The models describe three components: arterial wall deformation, stimulation of mechanoreceptors located in the BR nerve-endings, and modulation of the action potential frequency. The three sub-systems are modeled individually following well-established biological principles. The first submodel, predicting arterial wall deformation, uses blood pressure as an input and outputs circumferential strain. The mechanoreceptor stimulation model, uses circumferential strain as an input, predicting receptor deformation as an output. Finally, the neural model takes receptor deformation as an input predicting the BR firing rate as an output. Our results show that nonlinear dependence of firing rate on pressure can be accounted for by taking into account the nonlinear elastic properties of the artery wall. This was observed when testing the models using multiple experiments with a single set of parameters. We find that to model the response to a square pressure stimulus, giving rise to post-excitatory depression, it is necessary to include an integrate-and-fire model, which allows the firing rate to cease when the stimulus falls below a given threshold. We show that our modeling framework in combination with sensitivity analysis and parameter estimation can be used to test and compare models. Finally, we demonstrate that our preferred model can exhibit all known dynamics and that it is advantageous to combine qualitative and quantitative analysis methods. PMID:24348231

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

PubMed

Lloyd, P

2004-12-01

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

[Quantitative analysis of diffusion-weighted magnetic resonance images during chemoradiation therapy for cancer of the cervix uteri: Prognostic role of pretreatment diffusion coefficient values].

PubMed

Kharuzhyk, S A

2015-01-01

to carry out a quantitative analysis of diffusion-weighted magnetic resonance images (DWI) in cancer of the cervix uteri (CCU) and to estimate the possibility of using pretreatment measured diffusion coefficient (MDC) to predict chemoradiation therapy (CRT). The investigation prospectively enrolled 46 women with morphologically verified Stages IB-IVB CCU. All the women underwent diffusion-weighted magnetic resonance imaging of pelvic organs before and after treatment. A semiautomatic method was used to determine tumor signal intensity (SI) on DWI at b 1000 s/mm2 (SI b1000) and tumor MDC. The reproducibility of MDC measurements was assessed in 16 randomly selected women. The investigators compared the pretreatment quantitative DWI measures in complete and incomplete regression (CR and IR) groups and the presence and absence of tumor progression during a follow-up. An association of MDC with progression-free and overall survivals (PFS and OS) was determined in the patients. A semiautomatic tumor segmentation framework could determine the pretreatment quantitative DMI measures with minimal time spent and high reproducibility. The mean tumor MDC was 0.82 +/- 0.14 x 10(-3) mm2/s. CR and IR were established in 28 and 18 women, respectively. The MDC < or = 0.83 x 10(-3) mm2/s predicted CR with a sensitivity of 64.3% and a specificity of 77.8% (p=0.007). The median follow-up was 47 months (range, 3-82 months). With the MDC < or = 0.86 x 10(-3) mm2/s, 5-year PFS was 74.1% versus 42.1% with a higher MDC (p=0.023) and 5-year OS was 70.4 and 40.6%, respectively (p=0.021). The survival difference was insignificant in relation to the degree of tumor regression. The pretreatment IS at b1000 was of no prognostic value. The pretreatment tumor MDC may serve as a biomarker for predicting the efficiency of CRT for CCU.

Fire frequency in the Interior Columbia River Basin: Building regional models from fire history data

USGS Publications Warehouse

McKenzie, D.; Peterson, D.L.; Agee, James K.

2000-01-01

Fire frequency affects vegetation composition and successional pathways; thus it is essential to understand fire regimes in order to manage natural resources at broad spatial scales. Fire history data are lacking for many regions for which fire management decisions are being made, so models are needed to estimate past fire frequency where local data are not yet available. We developed multiple regression models and tree-based (classification and regression tree, or CART) models to predict fire return intervals across the interior Columbia River basin at 1-km resolution, using georeferenced fire history, potential vegetation, cover type, and precipitation databases. The models combined semiqualitative methods and rigorous statistics. The fire history data are of uneven quality; some estimates are based on only one tree, and many are not cross-dated. Therefore, we weighted the models based on data quality and performed a sensitivity analysis of the effects on the models of estimation errors that are due to lack of cross-dating. The regression models predict fire return intervals from 1 to 375 yr for forested areas, whereas the tree-based models predict a range of 8 to 150 yr. Both types of models predict latitudinal and elevational gradients of increasing fire return intervals. Examination of regional-scale output suggests that, although the tree-based models explain more of the variation in the original data, the regression models are less likely to produce extrapolation errors. Thus, the models serve complementary purposes in elucidating the relationships among fire frequency, the predictor variables, and spatial scale. The models can provide local managers with quantitative information and provide data to initialize coarse-scale fire-effects models, although predictions for individual sites should be treated with caution because of the varying quality and uneven spatial coverage of the fire history database. The models also demonstrate the integration of qualitative and quantitative methods when requisite data for fully quantitative models are unavailable. They can be tested by comparing new, independent fire history reconstructions against their predictions and can be continually updated, as better fire history data become available.

Modelling pollination services across agricultural landscapes

PubMed Central

Lonsdorf, Eric; Kremen, Claire; Ricketts, Taylor; Winfree, Rachael; Williams, Neal; Greenleaf, Sarah

2009-01-01

Background and Aims Crop pollination by bees and other animals is an essential ecosystem service. Ensuring the maintenance of the service requires a full understanding of the contributions of landscape elements to pollinator populations and crop pollination. Here, the first quantitative model that predicts pollinator abundance on a landscape is described and tested. Methods Using information on pollinator nesting resources, floral resources and foraging distances, the model predicts the relative abundance of pollinators within nesting habitats. From these nesting areas, it then predicts relative abundances of pollinators on the farms requiring pollination services. Model outputs are compared with data from coffee in Costa Rica, watermelon and sunflower in California and watermelon in New Jersey–Pennsylvania (NJPA). Key Results Results from Costa Rica and California, comparing field estimates of pollinator abundance, richness or services with model estimates, are encouraging, explaining up to 80 % of variance among farms. However, the model did not predict observed pollinator abundances on NJPA, so continued model improvement and testing are necessary. The inability of the model to predict pollinator abundances in the NJPA landscape may be due to not accounting for fine-scale floral and nesting resources within the landscapes surrounding farms, rather than the logic of our model. Conclusions The importance of fine-scale resources for pollinator service delivery was supported by sensitivity analyses indicating that the model's predictions depend largely on estimates of nesting and floral resources within crops. Despite the need for more research at the finer-scale, the approach fills an important gap by providing quantitative and mechanistic model from which to evaluate policy decisions and develop land-use plans that promote pollination conservation and service delivery. PMID:19324897

Prediction of Skin Sensitization with a Particle Swarm Optimized Support Vector Machine

PubMed Central

Yuan, Hua; Huang, Jianping; Cao, Chenzhong

2009-01-01

Skin sensitization is the most commonly reported occupational illness, causing much suffering to a wide range of people. Identification and labeling of environmental allergens is urgently required to protect people from skin sensitization. The guinea pig maximization test (GPMT) and murine local lymph node assay (LLNA) are the two most important in vivo models for identification of skin sensitizers. In order to reduce the number of animal tests, quantitative structure-activity relationships (QSARs) are strongly encouraged in the assessment of skin sensitization of chemicals. This paper has investigated the skin sensitization potential of 162 compounds with LLNA results and 92 compounds with GPMT results using a support vector machine. A particle swarm optimization algorithm was implemented for feature selection from a large number of molecular descriptors calculated by Dragon. For the LLNA data set, the classification accuracies are 95.37% and 88.89% for the training and the test sets, respectively. For the GPMT data set, the classification accuracies are 91.80% and 90.32% for the training and the test sets, respectively. The classification performances were greatly improved compared to those reported in the literature, indicating that the support vector machine optimized by particle swarm in this paper is competent for the identification of skin sensitizers. PMID:19742136

Asymmetric bagging and feature selection for activities prediction of drug molecules.

PubMed

Li, Guo-Zheng; Meng, Hao-Hua; Lu, Wen-Cong; Yang, Jack Y; Yang, Mary Qu

2008-05-28

Activities of drug molecules can be predicted by QSAR (quantitative structure activity relationship) models, which overcomes the disadvantages of high cost and long cycle by employing the traditional experimental method. With the fact that the number of drug molecules with positive activity is rather fewer than that of negatives, it is important to predict molecular activities considering such an unbalanced situation. Here, asymmetric bagging and feature selection are introduced into the problem and asymmetric bagging of support vector machines (asBagging) is proposed on predicting drug activities to treat the unbalanced problem. At the same time, the features extracted from the structures of drug molecules affect prediction accuracy of QSAR models. Therefore, a novel algorithm named PRIFEAB is proposed, which applies an embedded feature selection method to remove redundant and irrelevant features for asBagging. Numerical experimental results on a data set of molecular activities show that asBagging improve the AUC and sensitivity values of molecular activities and PRIFEAB with feature selection further helps to improve the prediction ability. Asymmetric bagging can help to improve prediction accuracy of activities of drug molecules, which can be furthermore improved by performing feature selection to select relevant features from the drug molecules data sets.

Paramagnetic fluorinated nanoemulsions for sensitive cellular fluorine-19 magnetic resonance imaging

PubMed Central

Kislukhin, Alexander A.; Xu, Hongyan; Adams, Stephen R.; Narsinh, Kazim H.; Tsien, Roger Y.; Ahrens, Eric T.

2016-01-01

Fluorine-19 magnetic resonance imaging (19F MRI) probes enable quantitative in vivo detection of cell therapies and inflammatory cells. Here, we describe the formulation of perfluorocarbon-based nanoemulsions with improved sensitivity for cellular MRI. Reduction of the 19F spin-lattice relaxation time (T1) enables rapid imaging and an improved signal-to-noise ratio, thereby improving cell detection sensitivity. We synthesized metal-binding β-diketones conjugated to linear perfluoropolyether (PFPE), formulated these fluorinated ligands as aqueous nanoemulsions, and then metalated them with various transition and lanthanide ions in the fluorous phase. Iron(III) tris-β-diketonate ('FETRIS') nanoemulsions with PFPE have low cytotoxicity (<20%) and superior MRI properties. Moreover, the 19F T1 can readily be reduced by an order of magnitude and tuned by stoichiometric modulation of the iron concentration. The resulting 19F MRI detection sensitivity is enhanced by 3-to-5 fold over previously used tracers at 11.7 T, and is predicted to increase by at least 8-fold at clinical field strength of 3 T. PMID:26974409

An automated quantitative DNA image cytometry system detects abnormal cells in cervical cytology with high sensitivity.

PubMed

Wong, O G; Ho, M W; Tsun, O K; Ng, A K; Tsui, E Y; Chow, J N; Ip, P P; Cheung, A N

2018-03-26

To evaluate the performance of an automated DNA-image-cytometry system as a tool to detect cervical carcinoma. Of 384 liquid-based cervical cytology samples with available biopsy follow-up were analyzed by both the Imager System and a high-risk HPV test (Cobas). The sensitivity and specificity of Imager System for detecting biopsy proven high-grade squamous intraepithelial lesion (HSIL, cervical intraepithelial neoplasia [CIN]2-3) and carcinoma were 89.58% and 56.25%, respectively, compared to 97.22% and 23.33% of HPV test but additional HPV 16/18 genotyping increased the specificity to 69.58%. The sensitivity and specificity of the Imager System for predicting HSIL+ (CIN2-3+) lesions among atypical squamous cells of undetermined significance samples were 80.00% and 70.53%, respectively, compared to 100% and 11.58% of HPV test whilst the HPV 16/18 genotyping increased the specificity to 77.89%. Among atypical squamous cells-cannot exclude HSIL, the sensitivity and specificity of Imager System for predicting HSIL+ (CIN2-3+) lesions upon follow up were 82.86% and 33.33%%, respectively, compared to 97.14% and 4.76% of HPV test and the HPV 16/18 genotyping increased the specificity to 19.05%. Among low-grade squamous intraepithelial lesion cases, the sensitivity and specificity of the Imager System for predicting HSIL+ (CIN2-3+) lesions were 66.67% and 35.71%%, respectively, compared to 66.67% and 29.76% of HPV test while HPV 16/18 genotyping increased the specificity to 79.76%. The overall results of imager and high-risk HPV test agreed in 69.43% (268) of all samples. The automated imager system and HPV 16/18 genotyping can enhance the specificity of detecting HSIL+ (CIN2-3+) lesions. © 2018 John Wiley & Sons Ltd.

Detection of nucleophosmin 1 mutations by quantitative real-time polymerase chain reaction versus capillary electrophoresis: a comparative study.

PubMed

Barakat, Fareed H; Luthra, Rajyalakshmi; Yin, C Cameron; Barkoh, Bedia A; Hai, Seema; Jamil, Waqar; Bhakta, Yaminiben I; Chen, Su; Medeiros, L Jeffrey; Zuo, Zhuang

2011-08-01

Nucleophosmin 1 (NPM1) is the most commonly mutated gene in acute myeloid leukemia. Detection of NPM1 mutations is useful for stratifying patients for therapy, predicting prognosis, and assessing for minimal residual disease. Several methods have been developed to rapidly detect NPM1 mutations in genomic DNA and/or messenger RNA specimens. To directly compare a quantitative real-time polymerase chain reaction (qPCR) assay with a widely used capillary electrophoresis assay for detecting NPM1 mutations. We adopted and modified a qPCR assay designed to detect the 6 most common NPM1 mutations and performed the assay in parallel with capillary electrophoresis assay in 207 bone marrow aspirate or peripheral blood samples from patients with a range of hematolymphoid neoplasms. The qPCR assay demonstrated a higher analytical sensitivity than the capillary electrophoresis 1/1000 versus 1/40, respectively. The capillary electrophoresis assay generated 10 equivocal results that needed to be repeated, whereas the qPCR assay generated only 1 equivocal result. After test conditions were optimized, the qPCR and capillary electrophoresis methods produced 100% concordant results, 85 positive and 122 negative. Given the higher analytical sensitivity and specificity of the qPCR assay, that assay is less likely to generate equivocal results than the capillary electrophoresis assay. Moreover, the qPCR assay is quantitative, faster, cheaper, less prone to contamination, and well suited for monitoring minimal residual disease.

Breast cancer Ki67 expression preoperative discrimination by DCE-MRI radiomics features

NASA Astrophysics Data System (ADS)

Ma, Wenjuan; Ji, Yu; Qin, Zhuanping; Guo, Xinpeng; Jian, Xiqi; Liu, Peifang

2018-02-01

To investigate whether quantitative radiomics features extracted from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) are associated with Ki67 expression of breast cancer. In this institutional review board approved retrospective study, we collected 377 cases Chinese women who were diagnosed with invasive breast cancer in 2015. This cohort included 53 low-Ki67 expression (Ki67 proliferation index less than 14%) and 324 cases with high-Ki67 expression (Ki67 proliferation index more than 14%). A binary-classification of low- vs. high- Ki67 expression was performed. A set of 52 quantitative radiomics features, including morphological, gray scale statistic, and texture features, were extracted from the segmented lesion area. Three most common machine learning classification methods, including Naive Bayes, k-Nearest Neighbor and support vector machine with Gaussian kernel, were employed for the classification and the least absolute shrink age and selection operator (LASSO) method was used to select most predictive features set for the classifiers. Classification performance was evaluated by the area under receiver operating characteristic curve (AUC), accuracy, sensitivity and specificity. The model that used Naive Bayes classification method achieved the best performance than the other two methods, yielding 0.773 AUC value, 0.757 accuracy, 0.777 sensitivity and 0.769 specificity. Our study showed that quantitative radiomics imaging features of breast tumor extracted from DCE-MRI are associated with breast cancer Ki67 expression. Future larger studies are needed in order to further evaluate the findings.

Stepped MS(All) Relied Transition (SMART): An approach to rapidly determine optimal multiple reaction monitoring mass spectrometry parameters for small molecules.

PubMed

Ye, Hui; Zhu, Lin; Wang, Lin; Liu, Huiying; Zhang, Jun; Wu, Mengqiu; Wang, Guangji; Hao, Haiping

2016-02-11

Multiple reaction monitoring (MRM) is a universal approach for quantitative analysis because of its high specificity and sensitivity. Nevertheless, optimization of MRM parameters remains as a time and labor-intensive task particularly in multiplexed quantitative analysis of small molecules in complex mixtures. In this study, we have developed an approach named Stepped MS(All) Relied Transition (SMART) to predict the optimal MRM parameters of small molecules. SMART requires firstly a rapid and high-throughput analysis of samples using a Stepped MS(All) technique (sMS(All)) on a Q-TOF, which consists of serial MS(All) events acquired from low CE to gradually stepped-up CE values in a cycle. The optimal CE values can then be determined by comparing the extracted ion chromatograms for the ion pairs of interest among serial scans. The SMART-predicted parameters were found to agree well with the parameters optimized on a triple quadrupole from the same vendor using a mixture of standards. The parameters optimized on a triple quadrupole from a different vendor was also employed for comparison, and found to be linearly correlated with the SMART-predicted parameters, suggesting the potential applications of the SMART approach among different instrumental platforms. This approach was further validated by applying to simultaneous quantification of 31 herbal components in the plasma of rats treated with a herbal prescription. Because the sMS(All) acquisition can be accomplished in a single run for multiple components independent of standards, the SMART approach are expected to find its wide application in the multiplexed quantitative analysis of complex mixtures. Copyright © 2015 Elsevier B.V. All rights reserved.

Quantitative measures of meniscus extrusion predict incident radiographic knee osteoarthritis – data from the Osteoarthritis Initiative

PubMed Central

Emmanuel, K.; Quinn, E.; Niu, J.; Guermazi, A.; Roemer, F.; Wirth, W.; Eckstein, F.; Felson, D.

2017-01-01

SUMMARY Objective To test the hypothesis that quantitative measures of meniscus extrusion predict incident radiographic knee osteoarthritis (KOA), prior to the advent of radiographic disease. Methods 206 knees with incident radiographic KOA (Kellgren Lawrence Grade (KLG) 0 or 1 at baseline, developing KLG 2 or greater with a definite osteophyte and joint space narrowing (JSN) grade ≥1 by year 4) were matched to 232 control knees not developing incident KOA. Manual segmentation of the central five slices of the medial and lateral meniscus was performed on coronal 3T DESS MRI and quantitative meniscus position was determined. Cases and controls were compared using conditional logistic regression adjusting for age, sex, BMI, race and clinical site. Sensitivity analyses of early (year [Y] 1/2) and late (Y3/4) incidence was performed. Results Mean medial extrusion distance was significantly greater for incident compared to non-incident knees (1.56 mean ± 1.12 mm SD vs 1.29 ± 0.99 mm; +21%, P < 0.01), so was the percent extrusion area of the medial meniscus (25.8 ± 15.8% vs 22.0 ± 13.5%; +17%, P < 0.05). This finding was consistent for knees restricted to medial incidence. No significant differences were observed for the lateral meniscus in incident medial KOA, or for the tibial plateau coverage between incident and non-incident knees. Restricting the analysis to medial incident KOA at Y1/2 differences were attenuated, but reached significance for extrusion distance, whereas no significant differences were observed at incident KOA in Y3/4. Conclusion Greater medial meniscus extrusion predicts incident radiographic KOA. Early onset KOA showed greater differences for meniscus position between incident and non-incident knees than late onset KOA. PMID:26318658

Two-dimensional time dependent hurricane overwash and erosion modeling at Santa Rosa Island

USGS Publications Warehouse

McCall, R.T.; Van Theil de Vries, J. S. M.; Plant, N.G.; Van Dongeren, A. R.; Roelvink, J.A.; Thompson, D.M.; Reniers, A.J.H.M.

2010-01-01

A 2DH numerical, model which is capable of computing nearshore circulation and morphodynamics, including dune erosion, breaching and overwash, is used to simulate overwash caused by Hurricane Ivan (2004) on a barrier island. The model is forced using parametric wave and surge time series based on field data and large-scale numerical model results. The model predicted beach face and dune erosion reasonably well as well as the development of washover fans. Furthermore, the model demonstrated considerable quantitative skill (upwards of 66% of variance explained, maximum bias - 0.21 m) in hindcasting the post-storm shape and elevation of the subaerial barrier island when a sheet flow sediment transport limiter was applied. The prediction skill ranged between 0.66 and 0.77 in a series of sensitivity tests in which several hydraulic forcing parameters were varied. The sensitivity studies showed that the variations in the incident wave height and wave period affected the entire simulated island morphology while variations in the surge level gradient between the ocean and back barrier bay affected the amount of deposition on the back barrier and in the back barrier bay. The model sensitivity to the sheet flow sediment transport limiter, which served as a proxy for unknown factors controlling the resistance to erosion, was significantly greater than the sensitivity to the hydraulic forcing parameters. If no limiter was applied the simulated morphological response of the barrier island was an order of magnitude greater than the measured morphological response.

Sensitive and affordable diagnostic assay for the quantitative detection of anaplastic lymphoma kinase (ALK) alterations in patients with non-small cell lung cancer.

PubMed

Dama, Elisa; Tillhon, Micol; Bertalot, Giovanni; de Santis, Francesca; Troglio, Flavia; Pessina, Simona; Passaro, Antonio; Pece, Salvatore; de Marinis, Filippo; Dell'Orto, Patrizia; Viale, Giuseppe; Spaggiari, Lorenzo; Di Fiore, Pier Paolo; Bianchi, Fabrizio; Barberis, Massimo; Vecchi, Manuela

2016-06-14

Accurate detection of altered anaplastic lymphoma kinase (ALK) expression is critical for the selection of lung cancer patients eligible for ALK-targeted therapies. To overcome intrinsic limitations and discrepancies of currently available companion diagnostics for ALK, we developed a simple, affordable and objective PCR-based predictive model for the quantitative measurement of any ALK fusion as well as wild-type ALK upregulation. This method, optimized for low-quantity/-quality RNA from FFPE samples, combines cDNA pre-amplification with ad hoc generated calibration curves. All the models we derived yielded concordant predictions when applied to a cohort of 51 lung tumors, and correctly identified all 17 ALK FISH-positive and 33 of the 34 ALK FISH-negative samples. The one discrepant case was confirmed as positive by IHC, thus raising the accuracy of our test to 100%. Importantly, our method was accurate when using low amounts of input RNA (10 ng), also in FFPE samples with limited tumor cellularity (5-10%) and in FFPE cytology specimens. Thus, our test is an easily implementable diagnostic tool for the rapid, efficacious and cost-effective screening of ALK status in patients with lung cancer.

An enzyme-linked immunosorbent assay for the quantification of serum platelet-bindable IgG.

PubMed

Howe, S E; Lynch, D M; Lynch, J M

1984-01-01

An enzyme-linked immunosorbent assay (ELISA) using F(ab')2 peroxidase-labeled antihuman immunoglobulin and o-phenylenediamine dihydrochloride (OPD) as a substrate was developed to measure serum platelet bindable IgG (S-PBIgG). The assay was made quantitative by standardizing the number of normal "target" platelets bound to microtiter plate wells, and by incorporating quantitated IgG standards with each microtiter plate tested to prepare a standard calibration curve. By this method, S-PBIgG for normal individuals was 3.4 +/- 1.6 fg per platelet (mean +/- 1 SD; n = 40). Increased S-PBIgG levels were detected in 36 of 40 patients with clinical autoimmune thrombocytopenia (ATP), ranging from 7.0 to 85 fg per platelet. Normal S-PBIgG levels were found in 34 of 40 patients with nonimmune thrombocytopenia. This method showed a sensitivity of 90 percent, specificity of 85 percent, and in the sample population studied, a positive predictive value of 0.86 and a negative predictive value of 0.90. This assay is highly reproducible (coefficient of variation was 6.8%) and appears useful in the evaluation of patients with suspected immune-mediated thrombocytopenia.

Quantitative structure-property relationship modeling of Grätzel solar cell dyes.

PubMed

Venkatraman, Vishwesh; Åstrand, Per-Olof; Alsberg, Bjørn Kåre

2014-01-30

With fossil fuel reserves on the decline, there is increasing focus on the design and development of low-cost organic photovoltaic devices, in particular, dye-sensitized solar cells (DSSCs). The power conversion efficiency (PCE) of a DSSC is heavily influenced by the chemical structure of the dye. However, as far as we know, no predictive quantitative structure-property relationship models for DSSCs with PCE as one of the response variables have been reported. Thus, we report for the first time the successful application of comparative molecular field analysis (CoMFA) and vibrational frequency-based eigenvalue (EVA) descriptors to model molecular structure-photovoltaic performance relationships for a set of 40 coumarin derivatives. The results show that the models obtained provide statistically robust predictions of important photovoltaic parameters such as PCE, the open-circuit voltage (V(OC)), short-circuit current (J(SC)) and the peak absorption wavelength λ(max). Some of our findings based on the analysis of the models are in accordance with those reported in the literature. These structure-property relationships can be applied to the rational structural design and evaluation of new photovoltaic materials. Copyright © 2013 Wiley Periodicals, Inc.

Microdose clinical trial: quantitative determination of nicardipine and prediction of metabolites in human plasma.

PubMed

Yamane, Naoe; Takami, Tomonori; Tozuka, Zenzaburo; Sugiyama, Yuichi; Yamazaki, Akira; Kumagai, Yuji

2009-01-01

A sample treatment procedure and high-sensitive liquid chromatography/tandem mass spectrometry (LC/MS/MS) method for quantitative determination of nicardipine in human plasma were developed for a microdose clinical trial with nicardipine, a non-radioisotope labeled drug. The calibration curve was linear in the range of 1-500 pg/mL using 1 mL of plasma. Analytical method validation for the clinical dose, for which the calibration curve was linear in the range of 0.2-100 ng/mL using 20 microL of plasma, was also conducted. Each method was successfully applied to making determinations in plasma using LC/MS/MS after administration of a microdose (100 microg) and clinical dose (20 mg) to each of six healthy volunteers. We tested new approaches in the search for metabolites in plasma after microdosing. In vitro metabolites of nicardipine were characterized using linear ion trap-fourier transform ion cyclotron resonance mass spectrometry (LIT-FTICRMS) and the nine metabolites predicted to be in plasma were analyzed using LC/MS/MS. There is a strong possibility that analysis of metabolites by LC/MS/MS may advance to utilization in microdose clinical trials with non-radioisotope labeled drugs.

Diffusion MRI in early cancer therapeutic response assessment

PubMed Central

Galbán, C. J.; Hoff, B. A.; Chenevert, T. L.; Ross, B. D.

2016-01-01

Imaging biomarkers for the predictive assessment of treatment response in patients with cancer earlier than standard tumor volumetric metrics would provide new opportunities to individualize therapy. Diffusion-weighted MRI (DW-MRI), highly sensitive to microenvironmental alterations at the cellular level, has been evaluated extensively as a technique for the generation of quantitative and early imaging biomarkers of therapeutic response and clinical outcome. First demonstrated in a rodent tumor model, subsequent studies have shown that DW-MRI can be applied to many different solid tumors for the detection of changes in cellularity as measured indirectly by an increase in the apparent diffusion coefficient (ADC) of water molecules within the lesion. The introduction of quantitative DW-MRI into the treatment management of patients with cancer may aid physicians to individualize therapy, thereby minimizing unnecessary systemic toxicity associated with ineffective therapies, saving valuable time, reducing patient care costs and ultimately improving clinical outcome. This review covers the theoretical basis behind the application of DW-MRI to monitor therapeutic response in cancer, the analytical techniques used and the results obtained from various clinical studies that have demonstrated the efficacy of DW-MRI for the prediction of cancer treatment response. PMID:26773848

Modeling and simulation of deformation of hydrogels responding to electric stimulus.

PubMed

Li, Hua; Luo, Rongmo; Lam, K Y

2007-01-01

A model for simulation of pH-sensitive hydrogels is refined in this paper to extend its application to electric-sensitive hydrogels, termed the refined multi-effect-coupling electric-stimulus (rMECe) model. By reformulation of the fixed-charge density and consideration of finite deformation, the rMECe model is able to predict the responsive deformations of the hydrogels when they are immersed in a bath solution subject to externally applied electric field. The rMECe model consists of nonlinear partial differential governing equations with chemo-electro-mechanical coupling effects and the fixed-charge density with electric-field effect. By comparison between simulation and experiment extracted from literature, the model is verified to be accurate and stable. The rMECe model performs quantitatively for deformation analysis of the electric-sensitive hydrogels. The influences of several physical parameters, including the externally applied electric voltage, initial fixed-charge density, hydrogel strip thickness, ionic strength and valence of surrounding solution, are discussed in detail on the displacement and average curvature of the hydrogels.

Comparing theories of reference-dependent choice.

PubMed

Bhatia, Sudeep

2017-09-01

Preferences are influenced by the presence or absence of salient choice options, known as reference points. This behavioral tendency is traditionally attributed to the loss aversion and diminishing sensitivity assumptions of prospect theory. In contrast, some psychological research suggests that reference dependence is caused by attentional biases that increase the subjective weighting of the reference point's primary attributes. Although both theories are able to successfully account for behavioral findings involving reference dependence, this article shows that these theories make diverging choice predictions when available options are inferior to the reference point. It presents the results of 2 studies that use settings with inferior choice options to compare these 2 theories. The analysis involves quantitative fits to participant-level choice data, and the results indicate that most participants are better described by models with attentional bias than they are by models with loss aversion and diminishing sensitivity. These differences appear to be caused by violations of loss aversion and diminishing sensitivity in losses. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

New MYC IHC Classifier Integrating Quantitative Architecture Parameters to Predict MYC Gene Translocation in Diffuse Large B-Cell Lymphoma

PubMed Central

Dong, Wei-Feng; Canil, Sarah; Lai, Raymond; Morel, Didier; Swanson, Paul E.; Izevbaye, Iyare

2018-01-01

A new automated MYC IHC classifier based on bivariate logistic regression is presented. The predictor relies on image analysis developed with the open-source ImageJ platform. From a histologic section immunostained for MYC protein, 2 dimensionless quantitative variables are extracted: (a) relative distance between nuclei positive for MYC IHC based on euclidean minimum spanning tree graph and (b) coefficient of variation of the MYC IHC stain intensity among MYC IHC-positive nuclei. Distance between positive nuclei is suggested to inversely correlate MYC gene rearrangement status, whereas coefficient of variation is suggested to inversely correlate physiological regulation of MYC protein expression. The bivariate classifier was compared with 2 other MYC IHC classifiers (based on percentage of MYC IHC positive nuclei), all tested on 113 lymphomas including mostly diffuse large B-cell lymphomas with known MYC fluorescent in situ hybridization (FISH) status. The bivariate classifier strongly outperformed the “percentage of MYC IHC-positive nuclei” methods to predict MYC+ FISH status with 100% sensitivity (95% confidence interval, 94-100) associated with 80% specificity. The test is rapidly performed and might at a minimum provide primary IHC screening for MYC gene rearrangement status in diffuse large B-cell lymphomas. Furthermore, as this bivariate classifier actually predicts “permanent overexpressed MYC protein status,” it might identify nontranslocation-related chromosomal anomalies missed by FISH. PMID:27093450

Shot noise-limited Cramér-Rao bound and algorithmic sensitivity for wavelength shifting interferometry

NASA Astrophysics Data System (ADS)

Chen, Shichao; Zhu, Yizheng

2017-02-01

Sensitivity is a critical index to measure the temporal fluctuation of the retrieved optical pathlength in quantitative phase imaging system. However, an accurate and comprehensive analysis for sensitivity evaluation is still lacking in current literature. In particular, previous theoretical studies for fundamental sensitivity based on Gaussian noise models are not applicable to modern cameras and detectors, which are dominated by shot noise. In this paper, we derive two shot noiselimited theoretical sensitivities, Cramér-Rao bound and algorithmic sensitivity for wavelength shifting interferometry, which is a major category of on-axis interferometry techniques in quantitative phase imaging. Based on the derivations, we show that the shot noise-limited model permits accurate estimation of theoretical sensitivities directly from measured data. These results can provide important insights into fundamental constraints in system performance and can be used to guide system design and optimization. The same concepts can be generalized to other quantitative phase imaging techniques as well.

Combination of methylated-DNA precipitation and methylation-sensitive restriction enzymes (COMPARE-MS) for the rapid, sensitive and quantitative detection of DNA methylation.

PubMed

Yegnasubramanian, Srinivasan; Lin, Xiaohui; Haffner, Michael C; DeMarzo, Angelo M; Nelson, William G

2006-02-09

Hypermethylation of CpG island (CGI) sequences is a nearly universal somatic genome alteration in cancer. Rapid and sensitive detection of DNA hypermethylation would aid in cancer diagnosis and risk stratification. We present a novel technique, called COMPARE-MS, that can rapidly and quantitatively detect CGI hypermethylation with high sensitivity and specificity in hundreds of samples simultaneously. To quantitate CGI hypermethylation, COMPARE-MS uses real-time PCR of DNA that was first digested by methylation-sensitive restriction enzymes and then precipitated by methyl-binding domain polypeptides immobilized on a magnetic solid matrix. We show that COMPARE-MS could detect five genome equivalents of methylated CGIs in a 1000- to 10,000-fold excess of unmethylated DNA. COMPARE-MS was used to rapidly quantitate hypermethylation at multiple CGIs in >155 prostate tissues, including benign and malignant prostate specimens, and prostate cell lines. This analysis showed that GSTP1, MDR1 and PTGS2 CGI hypermethylation as determined by COMPARE-MS could differentiate between malignant and benign prostate with sensitivities >95% and specificities approaching 100%. This novel technology could significantly improve our ability to detect CGI hypermethylation.

Diffusion-weighted imaging of the prostate: should we use quantitative metrics to better characterize focal lesions originating in the peripheral zone?

PubMed

Pierre, Thibaut; Cornud, Francois; Colléter, Loïc; Beuvon, Frédéric; Foissac, Frantz; Delongchamps, Nicolas B; Legmann, Paul

2018-05-01

To compare inter-reader concordance and accuracy of qualitative diffusion-weighted (DW) PIRADSv2.0 score with those of quantitative DW-MRI for the diagnosis of peripheral zone prostate cancer. Two radiologists independently assigned a DW-MRI-PIRADS score to 92 PZ-foci, in 74 patients (64.3±5.6 years old; median PSA level: 8 ng/ml, normal DRE in 70 men). A standardised ADCmean and nine ADC-derived parameters were measured, including ADCratios with the whole-prostate (WP-ADCratio) or the mirror-PZ (mirror-ADCratio) as reference areas. Surgical histology and MRI-TRUS fusion-biopsy were the reference for tumours and benign foci, respectively. Inter-reader agreement was assessed by the Cohen-kappa-coefficient and the intraclass correlation coefficient (ICC). Univariate-multivariate regressions determined the most predictive factor for cancer. Fifty lesions were malignant. Inter-reader concordance was fair for qualitative assessment, but excellent for quantitative assessment for all quantitative variables. At univariate analysis, ADCmean, WP-ADCratio and WL-ADCmean performed equally, but significantly better than the mirror-ADCratio (p<0.001). At multivariate analysis, the only independent variable significantly associated with malignancy was the whole-prostate-ADCratio. At a cut-off value of 0.68, sensitivity was 94-90 % and specificity was 60-38 % for readers 1 and 2, respectively. The whole-prostate-ADCratio improved the qualitative inter-reader concordance and characterisation of focal PZ-lesions. • Inter-reader concordance of DW PI-RADSv2.0 score for PZ lesions was only fair. • Using a standardised ADCmean measurement and derived DW-quantitative parameters, concordance was excellent. • The whole-prostate ADCratio performed significantly better than the mirror-ADCratio for cancer detection. • At a cut-off of 0.68, sensitivity values of WP-ADCratio were 94-90 %. • The whole-prostate ADCratio may circumvent variations of ADC metrics across centres.

Prediction of neonatal respiratory morbidity by quantitative ultrasound lung texture analysis: a multicenter study.

PubMed

Palacio, Montse; Bonet-Carne, Elisenda; Cobo, Teresa; Perez-Moreno, Alvaro; Sabrià, Joan; Richter, Jute; Kacerovsky, Marian; Jacobsson, Bo; García-Posada, Raúl A; Bugatto, Fernando; Santisteve, Ramon; Vives, Àngels; Parra-Cordero, Mauro; Hernandez-Andrade, Edgar; Bartha, José Luis; Carretero-Lucena, Pilar; Tan, Kai Lit; Cruz-Martínez, Rogelio; Burke, Minke; Vavilala, Suseela; Iruretagoyena, Igor; Delgado, Juan Luis; Schenone, Mauro; Vilanova, Josep; Botet, Francesc; Yeo, George S H; Hyett, Jon; Deprest, Jan; Romero, Roberto; Gratacos, Eduard

2017-08-01

Prediction of neonatal respiratory morbidity may be useful to plan delivery in complicated pregnancies. The limited predictive performance of the current diagnostic tests together with the risks of an invasive procedure restricts the use of fetal lung maturity assessment. The objective of the study was to evaluate the performance of quantitative ultrasound texture analysis of the fetal lung (quantusFLM) to predict neonatal respiratory morbidity in preterm and early-term (<39.0 weeks) deliveries. This was a prospective multicenter study conducted in 20 centers worldwide. Fetal lung ultrasound images were obtained at 25.0-38.6 weeks of gestation within 48 hours of delivery, stored in Digital Imaging and Communication in Medicine format, and analyzed with quantusFLM. Physicians were blinded to the analysis. At delivery, perinatal outcomes and the occurrence of neonatal respiratory morbidity, defined as either respiratory distress syndrome or transient tachypnea of the newborn, were registered. The performance of the ultrasound texture analysis test to predict neonatal respiratory morbidity was evaluated. A total of 883 images were collected, but 17.3% were discarded because of poor image quality or exclusion criteria, leaving 730 observations for the final analysis. The prevalence of neonatal respiratory morbidity was 13.8% (101 of 730). The quantusFLM predicted neonatal respiratory morbidity with a sensitivity, specificity, positive and negative predictive values of 74.3% (75 of 101), 88.6% (557 of 629), 51.0% (75 of 147), and 95.5% (557 of 583), respectively. Accuracy was 86.5% (632 of 730) and positive and negative likelihood ratios were 6.5 and 0.3, respectively. The quantusFLM predicted neonatal respiratory morbidity with an accuracy similar to that previously reported for other tests with the advantage of being a noninvasive technique. Copyright © 2017. Published by Elsevier Inc.

A quantitative systems physiology model of renal function and blood pressure regulation: Model description.

PubMed

Hallow, K M; Gebremichael, Y

2017-06-01

Renal function plays a central role in cardiovascular, kidney, and multiple other diseases, and many existing and novel therapies act through renal mechanisms. Even with decades of accumulated knowledge of renal physiology, pathophysiology, and pharmacology, the dynamics of renal function remain difficult to understand and predict, often resulting in unexpected or counterintuitive therapy responses. Quantitative systems pharmacology modeling of renal function integrates this accumulated knowledge into a quantitative framework, allowing evaluation of competing hypotheses, identification of knowledge gaps, and generation of new experimentally testable hypotheses. Here we present a model of renal physiology and control mechanisms involved in maintaining sodium and water homeostasis. This model represents the core renal physiological processes involved in many research questions in drug development. The model runs in R and the code is made available. In a companion article, we present a case study using the model to explore mechanisms and pharmacology of salt-sensitive hypertension. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Affordable, automatic quantitative fall risk assessment based on clinical balance scales and Kinect data.

PubMed

Colagiorgio, P; Romano, F; Sardi, F; Moraschini, M; Sozzi, A; Bejor, M; Ricevuti, G; Buizza, A; Ramat, S

2014-01-01

The problem of a correct fall risk assessment is becoming more and more critical with the ageing of the population. In spite of the available approaches allowing a quantitative analysis of the human movement control system's performance, the clinical assessment and diagnostic approach to fall risk assessment still relies mostly on non-quantitative exams, such as clinical scales. This work documents our current effort to develop a novel method to assess balance control abilities through a system implementing an automatic evaluation of exercises drawn from balance assessment scales. Our aim is to overcome the classical limits characterizing these scales i.e. limited granularity and inter-/intra-examiner reliability, to obtain objective scores and more detailed information allowing to predict fall risk. We used Microsoft Kinect to record subjects' movements while performing challenging exercises drawn from clinical balance scales. We then computed a set of parameters quantifying the execution of the exercises and fed them to a supervised classifier to perform a classification based on the clinical score. We obtained a good accuracy (~82%) and especially a high sensitivity (~83%).

Development of an Analytical Method for the Determination of Amoxicillin in Commercial Drugs and Wastewater Samples, and Assessing its Stability in Simulated Gastric Digestion.

PubMed

Unutkan, Tugçe; Bakirdere, Sezgin; Keyf, Seyfullah

2018-01-01

A highly sensitive analytical HPLC-UV method was developed for the determination of amoxicillin in drugs and wastewater samples at a single wavelength (230 nm). In order to substantially predict the in vivo behavior of amoxicillin, drug samples were subjected to simulated gastric conditions. The calibration plot of the method was linear from 0.050 to 500 mg L-1 with a correlation coefficient of 0.9999. The limit of detection and limit of quantitation were found to be 16 and 54 μg L-1, respectively. The percentage recovery of amoxicillin in wastewater was found to be 97.0 ± 1.6%. The method was successfully applied for the qualitative and quantitative determination of amoxicillin in drug samples including tablets and suspensions. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Evaluation of a Parental Questionnaire to Identify Atopic Dermatitis in Infants and Preschool Children

PubMed Central

von Kobyletzki, Laura B.; Janson, Staffan; Hasselgren, Mikael; Bornehag, Carl-Gustaf; Svensson, Åke

2012-01-01

Aim. To develop and validate a questionnaire for detecting atopic dermatitis in infants and small children from the age of 2 months. Methods. Parents to 60 children answered a written questionnaire prior to a physical examination and individual semistructured interview. Qualitative and quantitative analyses of validity, sensitivity, specificity, and predictive values of the questionnaire were performed. Results. A total of 27 girls and 33 boys, aged 2 to 71 months, 35 with and 25 without physician-diagnosed eczema, participated. Validation of the questionnaire by comparisons with physicians' diagnoses showed a sensitivity of 0.91 (95% CI 0.77–0.98) and a specificity of 1 (95% CI 0.86–1). Conclusions. Three questions in a parental questionnaire were sufficient for diagnosing eczema in infants and small children. PMID:22500189

Measurement of the neutral composition of the lower thermosphere above Fort Churchill by rocket-borne mass spectrometer.

NASA Technical Reports Server (NTRS)

Hickman, D. R.; Nier, A. O.

1972-01-01

Measurement of the neutral atmospheric composition above Fort Churchill, Canada (59 N, 94 W), by mass spectrometers in two rocket flights at 0835 CST on Feb. 4 and 6, 1969. A quantitative measure for the extent of agreement with static diffusive equilibrium is introduced, and substantial agreement with profiles predicted when static diffusive equilibrium was assumed is found for all constituents including helium. A sensitive search for atomic nitrogen yielded upper limits of a few per cent for one flight and of 0.2% for the other.

Atmospheric Effects of Subsonic Aircraft: Interim Assessment Report of the Advanced Subsonic Technology Program

NASA Technical Reports Server (NTRS)

Friedl, Randall R. (Editor)

1997-01-01

This first interim assessment of the subsonic assessment (SASS) project attempts to summarize concisely the status of our knowledge concerning the impacts of present and future subsonic aircraft fleets. It also highlights the major areas of scientific uncertainty, through review of existing data bases and model-based sensitivity studies. In view of the need for substantial improvements in both model formulations and experimental databases, this interim assessment cannot provide confident numerical predictions of aviation impacts. However, a number of quantitative estimates are presented, which provide some guidance to policy makers.

Diagnostic performance of procalcitonin for hospitalised children with acute pyelonephritis presenting to the paediatric emergency department.

PubMed

Chen, Shan-Ming; Chang, Hung-Ming; Hung, Tung-Wei; Chao, Yu-Hua; Tsai, Jeng-Dau; Lue, Ko-Huang; Sheu, Ji-Nan

2013-05-01

Urinary tract infection (UTI) is a common bacterial infection in children that can result in permanent renal damage. This study prospectively assessed the diagnostic performance of procalcitonin (PCT) for predicting acute pyelonephritis (APN) among children with febrile UTI presenting to the paediatric emergency department (ED). Children aged ≤10 years with febrile UTI admitted to hospital from the paediatric ED were prospectively studied. Blood PCT, C reactive protein (CRP) and white blood cell (WBC) count were measured in the ED. Sensitivity, specificity, predictive values, multilevel likelihood ratios, receiver operating characteristic (ROC) curve analysis and multivariate logistic regression were used to assess quantitative variables for diagnosing APN. The 136 enrolled patients (56 boys and 80 girls; age range 1 month to 10 years) were divided into APN (n=87) and lower UTI (n=49) groups according to (99m)Tc-dimercaptosuccinic acid scan results. The cut-off value for maximum diagnostic performance of PCT was 1.3 ng/ml (sensitivity 86.2%, specificity 89.8%). By multivariate regression analysis, only PCT and CRP were retained as significant predictors of APN. Comparing ROC curves, PCT had a significantly greater area under the curve than CRP, WBC count and fever for differentiating between APN and lower UTI. PCT has better sensitivity and specificity than CRP and WBC count for distinguishing between APN and lower UTI. PCT is a valuable marker for predicting APN in children with febrile UTI. It may be considered in the initial investigation and therapeutic strategies for children presenting to the ED.

Temporal Expression-based Analysis of Metabolism

PubMed Central

Segrè, Daniel

2012-01-01

Metabolic flux is frequently rerouted through cellular metabolism in response to dynamic changes in the intra- and extra-cellular environment. Capturing the mechanisms underlying these metabolic transitions in quantitative and predictive models is a prominent challenge in systems biology. Progress in this regard has been made by integrating high-throughput gene expression data into genome-scale stoichiometric models of metabolism. Here, we extend previous approaches to perform a Temporal Expression-based Analysis of Metabolism (TEAM). We apply TEAM to understanding the complex metabolic dynamics of the respiratorily versatile bacterium Shewanella oneidensis grown under aerobic, lactate-limited conditions. TEAM predicts temporal metabolic flux distributions using time-series gene expression data. Increased predictive power is achieved by supplementing these data with a large reference compendium of gene expression, which allows us to take into account the unique character of the distribution of expression of each individual gene. We further propose a straightforward method for studying the sensitivity of TEAM to changes in its fundamental free threshold parameter θ, and reveal that discrete zones of distinct metabolic behavior arise as this parameter is changed. By comparing the qualitative characteristics of these zones to additional experimental data, we are able to constrain the range of θ to a small, well-defined interval. In parallel, the sensitivity analysis reveals the inherently difficult nature of dynamic metabolic flux modeling: small errors early in the simulation propagate to relatively large changes later in the simulation. We expect that handling such “history-dependent” sensitivities will be a major challenge in the future development of dynamic metabolic-modeling techniques. PMID:23209390

Quantitative imaging features: extension of the oncology medical image database

NASA Astrophysics Data System (ADS)

Patel, M. N.; Looney, P. T.; Young, K. C.; Halling-Brown, M. D.

2015-03-01

Radiological imaging is fundamental within the healthcare industry and has become routinely adopted for diagnosis, disease monitoring and treatment planning. With the advent of digital imaging modalities and the rapid growth in both diagnostic and therapeutic imaging, the ability to be able to harness this large influx of data is of paramount importance. The Oncology Medical Image Database (OMI-DB) was created to provide a centralized, fully annotated dataset for research. The database contains both processed and unprocessed images, associated data, and annotations and where applicable expert determined ground truths describing features of interest. Medical imaging provides the ability to detect and localize many changes that are important to determine whether a disease is present or a therapy is effective by depicting alterations in anatomic, physiologic, biochemical or molecular processes. Quantitative imaging features are sensitive, specific, accurate and reproducible imaging measures of these changes. Here, we describe an extension to the OMI-DB whereby a range of imaging features and descriptors are pre-calculated using a high throughput approach. The ability to calculate multiple imaging features and data from the acquired images would be valuable and facilitate further research applications investigating detection, prognosis, and classification. The resultant data store contains more than 10 million quantitative features as well as features derived from CAD predictions. Theses data can be used to build predictive models to aid image classification, treatment response assessment as well as to identify prognostic imaging biomarkers.

Comment on Hall et al. (2017), "How to Choose Between Measures of Tinnitus Loudness for Clinical Research? A Report on the Reliability and Validity of an Investigator-Administered Test and a Patient-Reported Measure Using Baseline Data Collected in a Phase IIa Drug Trial".

PubMed

Sabour, Siamak

2018-03-08

The purpose of this letter, in response to Hall, Mehta, and Fackrell (2017), is to provide important knowledge about methodology and statistical issues in assessing the reliability and validity of an audiologist-administered tinnitus loudness matching test and a patient-reported tinnitus loudness rating. The author uses reference textbooks and published articles regarding scientific assessment of the validity and reliability of a clinical test to discuss the statistical test and the methodological approach in assessing validity and reliability in clinical research. Depending on the type of the variable (qualitative or quantitative), well-known statistical tests can be applied to assess reliability and validity. The qualitative variables of sensitivity, specificity, positive predictive value, negative predictive value, false positive and false negative rates, likelihood ratio positive and likelihood ratio negative, as well as odds ratio (i.e., ratio of true to false results), are the most appropriate estimates to evaluate validity of a test compared to a gold standard. In the case of quantitative variables, depending on distribution of the variable, Pearson r or Spearman rho can be applied. Diagnostic accuracy (validity) and diagnostic precision (reliability or agreement) are two completely different methodological issues. Depending on the type of the variable (qualitative or quantitative), well-known statistical tests can be applied to assess validity.

Rapid and accurate prediction of degradant formation rates in pharmaceutical formulations using high-performance liquid chromatography-mass spectrometry.

PubMed

Darrington, Richard T; Jiao, Jim

2004-04-01

Rapid and accurate stability prediction is essential to pharmaceutical formulation development. Commonly used stability prediction methods include monitoring parent drug loss at intended storage conditions or initial rate determination of degradants under accelerated conditions. Monitoring parent drug loss at the intended storage condition does not provide a rapid and accurate stability assessment because often <0.5% drug loss is all that can be observed in a realistic time frame, while the accelerated initial rate method in conjunction with extrapolation of rate constants using the Arrhenius or Eyring equations often introduces large errors in shelf-life prediction. In this study, the shelf life prediction of a model pharmaceutical preparation utilizing sensitive high-performance liquid chromatography-mass spectrometry (LC/MS) to directly quantitate degradant formation rates at the intended storage condition is proposed. This method was compared to traditional shelf life prediction approaches in terms of time required to predict shelf life and associated error in shelf life estimation. Results demonstrated that the proposed LC/MS method using initial rates analysis provided significantly improved confidence intervals for the predicted shelf life and required less overall time and effort to obtain the stability estimation compared to the other methods evaluated. Copyright 2004 Wiley-Liss, Inc. and the American Pharmacists Association.

Comparison of fecal indicators with pathogenic bacteria and rotavirus in groundwater.

PubMed

Ferguson, Andrew S; Layton, Alice C; Mailloux, Brian J; Culligan, Patricia J; Williams, Daniel E; Smartt, Abby E; Sayler, Gary S; Feighery, John; McKay, Larry D; Knappett, Peter S K; Alexandrova, Ekaterina; Arbit, Talia; Emch, Michael; Escamilla, Veronica; Ahmed, Kazi Matin; Alam, Md Jahangir; Streatfield, P Kim; Yunus, Mohammad; van Geen, Alexander

2012-08-01

Groundwater is routinely analyzed for fecal indicators but direct comparisons of fecal indicators to the presence of bacterial and viral pathogens are rare. This study was conducted in rural Bangladesh where the human population density is high, sanitation is poor, and groundwater pumped from shallow tubewells is often contaminated with fecal bacteria. Five indicator microorganisms (E. coli, total coliform, F+RNA coliphage, Bacteroides and human-associated Bacteroides) and various environmental parameters were compared to the direct detection of waterborne pathogens by quantitative PCR in groundwater pumped from 50 tubewells. Rotavirus was detected in groundwater filtrate from the largest proportion of tubewells (40%), followed by Shigella (10%), Vibrio (10%), and pathogenic E. coli (8%). Spearman rank correlations and sensitivity-specificity calculations indicate that some, but not all, combinations of indicators and environmental parameters can predict the presence of pathogens. Culture-dependent fecal indicator bacteria measured on a single date did not predict total bacterial pathogens, but annually averaged monthly measurements of culturable E. coli did improve prediction for total bacterial pathogens. A qPCR-based E. coli assay was the best indicator for the bacterial pathogens. F+RNA coliphage were neither correlated nor sufficiently sensitive towards rotavirus, but were predictive of bacterial pathogens. Since groundwater cannot be excluded as a significant source of diarrheal disease in Bangladesh and neighboring countries with similar characteristics, the need to develop more effective methods for screening tubewells with respect to microbial contamination is necessary. Copyright © 2012 Elsevier B.V. All rights reserved.

Comparison of fecal indicators with pathogenic bacteria and rotavirus in groundwater

PubMed Central

Ferguson, Andrew S.; Layton, Alice C.; Mailloux, Brian J; Culligan, Patricia J.; Williams, Daniel E.; Smartt, Abby E.; Sayler, Gary S.; Feighery, John; McKay, Larry; Knappett, Peter S.K.; Alexandrova, Ekaterina; Arbit, Talia; Emch, Michael; Escamilla, Veronica; Ahmed, Kazi Matin; Alam, Md. Jahangir; Streatfield, P. Kim; Yunus, Mohammad; van Geen, Alexander

2012-01-01

Groundwater is routinely analyzed for fecal indicators but direct comparisons of fecal indicators to the presence of bacterial and viral pathogens are rare. This study was conducted in rural Bangladesh where the human population density is high, sanitation is poor, and groundwater pumped from shallow tubewells is often contaminated with fecal bacteria. Five indicator microorganisms (E. coli, total coliform, F+RNA coliphage, Bacteroides and human-associated Bacteroides) and various environmental parameters were compared to the direct detection of waterborne pathogens by quantitative PCR in groundwater pumped from 50 tubewells. Rotavirus was detected in groundwater filtrate from the largest proportion of tubewells (40%), followed by Shigella (10%), Vibrio (10%), and pathogenic E. coli (8%). Spearman rank correlations and sensitivity-specificity calculations indicate that some, but not all, combinations of indicators and environmental parameters can predict the presence of pathogens. Culture-dependent fecal indicator bacteria measured on a single date did not predict total bacterial pathogens, but annually averaged monthly measurements of culturable E. coli did improve prediction for total bacterial pathogens. A qPCR-based E. coli assay was the best indicator for the bacterial pathogens. F+RNA coliphage were neither correlated nor sufficiently sensitive towards rotavirus, but were predictive of bacterial pathogens. Since groundwater cannot be excluded as a significant source of diarrheal disease in Bangladesh and neighboring countries with similar characteristics, the need to develop more effective methods for screening tubewells with respect to microbial contamination is necessary. PMID:22705866

Norcocaine in human hair as a biomarker of heavy cocaine use in a high risk population.

PubMed

Poon, S; Gareri, J; Walasek, P; Koren, G

2014-08-01

In hair analysis, cocaine (COC) and its metabolites have been studied relatively extensively with a consistent focus of distinguishing active drug use and excluding external contamination. Although quantitative cut-offs using major metabolite, benzolecgonine (BE), in hair have been proposed to distinguish likely active use from passive exposure, exogenously formed BE may result in false positive tests. Hence, the presence of less commonly detected COC metabolite, norcocaine (NCOC), may be useful in increasing certainty of illicit COC use and evaluating likelihood of environmental contamination. The objective of the present study was to observe the pattern of NCOC detection in a clinical population of suspected users and evaluate the possible role of NCOC in distinguishing systemic exposure from external contamination to COC and assessing intensity of cocaine use. Hair samples collected between January 2011 and May 2013 from the Motherisk Laboratory were analyzed by GC-MS for the presence of COC, BE, and NCOC. NCOC positivity rates (%) for various COC concentration ranges as well as sensitivity, specificity, positive predictive value, and negative predictive values of NCOC as a biomarker of different COC use profiles was calculated. The rate of NCOC positivity (%) within COC concentration ranges (ng/mg) 0.13-0.4 (above LOD, below LOQ), 0.4-3, 3-6, 6-10, 10-14, >14 were 0.26, 4.15, 29.63, 55.85, 80.37, and 94.02, respectively; p<0.0001 for all positivity comparisons between ranges. These results were used to determine a COC cut-off concentration for differing levels of COC use. The presence of NCOC above the LOD of 0.13 ng/mg predicted COC concentrations exceeding 14.00 ng/mg, with sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 94.0%, 87.9%, 41.5%, and 99.4%, respectively. The presence NCOC above the LOD of 0.13 ng/mg predicted COC concentrations exceeding the 75th percentile, with sensitivity, specificity, PPV, and NPV of 76.6%, 94.7%, 74.7%, and 95.2%, respectively. Despite an inability to definitively rule out external contamination, the presence of NCOC in hair is strongly associated with elevated COC levels and performs as a highly specific surrogate marker for frequent/intensive cocaine use and highly sensitive marker for intensive/daily use of cocaine. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Quantitative cultures of endotracheal aspirates for the diagnosis of ventilator-associated pneumonia.

PubMed

el-Ebiary, M; Torres, A; González, J; de la Bellacasa, J P; García, C; Jiménez de Anta, M T; Ferrer, M; Rodriguez-Roisin, R

1993-12-01

Bronchoalveolar lavage (BAL) and protected specimen brushing (PSB) are the most commonly used methods for diagnosing ventilator-associated (VA) pneumonia although they require bronchoscopy. Endotracheal aspiration (EA) is a simple and less costly technique than PSB or BAL. The purpose of our study was to investigate the diagnostic value of EA quantitative cultures and to compare the results obtained using EA with those obtained using PSB and BAL in mechanically ventilated patients with or without pneumonia. We prospectively studied 102 intubated patients divided into three diagnostic categories: Group I (definite pneumonia, n = 26), Group II (uncertain status, n = 48), and Group III (control group, n = 28). All patients received prior antibiotic treatment. EA, PSB, and BAL were obtained sequentially in all patients. When comparing Group I with Group III and using 10(5) cfu/ml as a threshold, we found that EA quantitative cultures represented a relatively sensitive (70%) and relatively specific (72%) method to diagnose VA pneumonia. The specificity of BAL and PSB (87% and 93%, respectively) was better than that of EA. The negative predictive value of EA cultures was higher (72%) when compared with that obtained using PSB (34%) (p < 0.05). EA quantitative cultures correlated with PSB and BAL quantitative cultures in patients with definite pneumonia. Although EA quantitative cultures are less specific than PSB and BAL for diagnosing VA pneumonia, our results suggest that the former approach may be used to treat these patients when bronchoscopic procedures are not available.

Conventional liquid chromatography/triple quadrupole mass spectrometer-based metabolite identification and semi-quantitative estimation approach in the investigation of dabigatran etexilate in vitro metabolism

PubMed Central

Hu, Zhe-Yi; Parker, Robert B.; Herring, Vanessa L.; Laizure, S. Casey

2012-01-01

Dabigatran etexilate (DABE) is an oral prodrug that is rapidly converted by esterases to dabigatran (DAB), a direct inhibitor of thrombin. To elucidate the esterase-mediated metabolic pathway of DABE, a high-performance liquid chromatography/mass spectrometer (LC-MS/MS)-based metabolite identification and semi-quantitative estimation approach was developed. To overcome the poor full-scan sensitivity of conventional triple quadrupole mass spectrometry, precursor-product ion pairs were predicted, to search for the potential in vitro metabolites. The detected metabolites were confirmed by the product ion scan. A dilution method was introduced to evaluate the matrix effects of tentatively identified metabolites without chemical standards. Quantitative information on detected metabolites was obtained using ‘metabolite standards’ generated from incubation samples that contain a high concentration of metabolite in combination with a correction factor for mass spectrometry response. Two in vitro metabolites of DABE (M1 and M2) were identified, and quantified by the semi-quantitative estimation approach. It is noteworthy that CES1 convert DABE to M1 while CES2 mediates the conversion of DABE to M2. M1 (or M2) was further metabolized to DAB by CES2 (or CES1). The approach presented here provides a solution to a bioanalytical need for fast identification and semi-quantitative estimation of CES metabolites in preclinical samples. PMID:23239178

Insights into multimodal imaging classification of ADHD

PubMed Central

Colby, John B.; Rudie, Jeffrey D.; Brown, Jesse A.; Douglas, Pamela K.; Cohen, Mark S.; Shehzad, Zarrar

2012-01-01

Attention deficit hyperactivity disorder (ADHD) currently is diagnosed in children by clinicians via subjective ADHD-specific behavioral instruments and by reports from the parents and teachers. Considering its high prevalence and large economic and societal costs, a quantitative tool that aids in diagnosis by characterizing underlying neurobiology would be extremely valuable. This provided motivation for the ADHD-200 machine learning (ML) competition, a multisite collaborative effort to investigate imaging classifiers for ADHD. Here we present our ML approach, which used structural and functional magnetic resonance imaging data, combined with demographic information, to predict diagnostic status of individuals with ADHD from typically developing (TD) children across eight different research sites. Structural features included quantitative metrics from 113 cortical and non-cortical regions. Functional features included Pearson correlation functional connectivity matrices, nodal and global graph theoretical measures, nodal power spectra, voxelwise global connectivity, and voxelwise regional homogeneity. We performed feature ranking for each site and modality using the multiple support vector machine recursive feature elimination (SVM-RFE) algorithm, and feature subset selection by optimizing the expected generalization performance of a radial basis function kernel SVM (RBF-SVM) trained across a range of the top features. Site-specific RBF-SVMs using these optimal feature sets from each imaging modality were used to predict the class labels of an independent hold-out test set. A voting approach was used to combine these multiple predictions and assign final class labels. With this methodology we were able to predict diagnosis of ADHD with 55% accuracy (versus a 39% chance level in this sample), 33% sensitivity, and 80% specificity. This approach also allowed us to evaluate predictive structural and functional features giving insight into abnormal brain circuitry in ADHD. PMID:22912605

Scoring severity in trauma: comparison of prehospital scoring systems in trauma ICU patients.

PubMed

Llompart-Pou, J A; Chico-Fernández, M; Sánchez-Casado, M; Salaberria-Udabe, R; Carbayo-Górriz, C; Guerrero-López, F; González-Robledo, J; Ballesteros-Sanz, M Á; Herrán-Monge, R; Servià-Goixart, L; León-López, R; Val-Jordán, E

2017-06-01

We evaluated the predictive ability of mechanism, Glasgow coma scale, age and arterial pressure (MGAP), Glasgow coma scale, age and systolic blood pressure (GAP), and triage-revised trauma Score (T-RTS) scores in patients from the Spanish trauma ICU registry using the trauma and injury severity score (TRISS) as a reference standard. Patients admitted for traumatic disease in the participating ICU were included. Quantitative data were reported as median [interquartile range (IQR), categorical data as number (percentage)]. Comparisons between groups with quantitative variables and categorical variables were performed using Student's T Test and Chi Square Test, respectively. We performed receiving operating curves (ROC) and evaluated the area under the curve (AUC) with its 95 % confidence interval (CI). Sensitivity, specificity, positive predictive and negative predictive values and accuracy were evaluated in all the scores. A value of p < 0.05 was considered significant. The final sample included 1361 trauma ICU patients. Median age was 45 (30-61) years. 1092 patients (80.3 %) were male. Median ISS was 18 (13-26) and median T-RTS was 11 (10-12). Median GAP was 20 (15-22) and median MGAP 24 (20-27). Observed mortality was 17.7 % whilst predicted mortality using TRISS was 16.9 %. The AUC in the scores evaluated was: TRISS 0.897 (95 % CI 0.876-0.918), MGAP 0.860 (95 % CI 0.835-0.886), GAP 0.849 (95 % CI 0.823-0.876) and T-RTS 0.796 (95 % CI 0.762-0.830). Both MGAP and GAP scores performed better than the T-RTS in the prediction of hospital mortality in Spanish trauma ICU patients. Since these are easy-to-perform scores, they should be incorporated in clinical practice as a triaging tool.

ADMET Evaluation in Drug Discovery. 18. Reliable Prediction of Chemical-Induced Urinary Tract Toxicity by Boosting Machine Learning Approaches.

PubMed

Lei, Tailong; Sun, Huiyong; Kang, Yu; Zhu, Feng; Liu, Hui; Zhou, Wenfang; Wang, Zhe; Li, Dan; Li, Youyong; Hou, Tingjun

2017-11-06

Xenobiotic chemicals and their metabolites are mainly excreted out of our bodies by the urinary tract through the urine. Chemical-induced urinary tract toxicity is one of the main reasons that cause failure during drug development, and it is a common adverse event for medications, natural supplements, and environmental chemicals. Despite its importance, there are only a few in silico models for assessing urinary tract toxicity for a large number of compounds with diverse chemical structures. Here, we developed a series of qualitative and quantitative structure-activity relationship (QSAR) models for predicting urinary tract toxicity. In our study, the recursive feature elimination method incorporated with random forests (RFE-RF) was used for dimension reduction, and then eight machine learning approaches were used for QSAR modeling, i.e., relevance vector machine (RVM), support vector machine (SVM), regularized random forest (RRF), C5.0 trees, eXtreme gradient boosting (XGBoost), AdaBoost.M1, SVM boosting (SVMBoost), and RVM boosting (RVMBoost). For building classification models, the synthetic minority oversampling technique was used to handle the imbalance data set problem. Among all the machine learning approaches, SVMBoost based on the RBF kernel achieves both the best quantitative (q ext 2 = 0.845) and qualitative predictions for the test set (MCC of 0.787, AUC of 0.893, sensitivity of 89.6%, specificity of 94.1%, and global accuracy of 90.8%). The application domains were then analyzed, and all of the tested chemicals fall within the application domain coverage. We also examined the structure features of the chemicals with large prediction errors. In brief, both the regression and classification models developed by the SVMBoost approach have reliable prediction capability for assessing chemical-induced urinary tract toxicity.

Predicting animal δ18O: Accounting for diet and physiological adaptation

NASA Astrophysics Data System (ADS)

Kohn, Matthew J.

1996-12-01

Theoretical predictions and measured isotope variations indicate that diet and physiological adaptation have a significant impact on animals δ18O and cannot be ignored. A generalized model is therefore developed for the prediction of animal body water and phosphate δ18O to incorporate these factors quantitatively. Application of the model reproduces most published compositions and compositional trends for mammals and birds. A moderate dependence of animal δ18O on humidity is predicted for drought-tolerant animals, and the correlation between humidity and North American deer bone composition as corrected for local meteoric water is predicted within the scatter of the data. In contrast to an observed strong correlation between kangaroo δ18O and humidity (Δδ18O/Δh ∼ 2.5± 0.4‰/10%r.h.), the predicted humidity dependence is only 1.3 - 1.7‰/10% r.h., and it is inferred that drinking water in hot dry areas of Australia is enriched in 18O over rainwater. Differences in physiology and water turnover readily explain the observed differences in δ18O for several herbivore genera in East Africa, excepting antelopes. Antelope models are more sensitive to biological fractionations, and adjustments to the flux of transcutaneous water vapor within experimentally measured ranges allows their δ18O values to be matched. Models of the seasonal changes of forage composition for two regions with dissimilar climates show that significant seasonal variations in animal isotope composition are expected, and that animals with different physiologies and diets track climate differently. Analysis of different genera with disparate sensitivities to surface water and humidity will allow the most accurate quantification of past climate changes.

Finding the bottom and using it

PubMed Central

Sandoval, Ruben M.; Wang, Exing; Molitoris, Bruce A.

2014-01-01

Maximizing 2-photon parameters used in acquiring images for quantitative intravital microscopy, especially when high sensitivity is required, remains an open area of investigation. Here we present data on correctly setting the black level of the photomultiplier tube amplifier by adjusting the offset to allow for accurate quantitation of low intensity processes. When the black level is set too high some low intensity pixel values become zero and a nonlinear degradation in sensitivity occurs rendering otherwise quantifiable low intensity values virtually undetectable. Initial studies using a series of increasing offsets for a sequence of concentrations of fluorescent albumin in vitro revealed a loss of sensitivity for higher offsets at lower albumin concentrations. A similar decrease in sensitivity, and therefore the ability to correctly determine the glomerular permeability coefficient of albumin, occurred in vivo at higher offset. Finding the offset that yields accurate and linear data are essential for quantitative analysis when high sensitivity is required. PMID:25313346

Evaluation of a New Molecular Entity as a Victim of Metabolic Drug-Drug Interactions-an Industry Perspective.

PubMed

Bohnert, Tonika; Patel, Aarti; Templeton, Ian; Chen, Yuan; Lu, Chuang; Lai, George; Leung, Louis; Tse, Susanna; Einolf, Heidi J; Wang, Ying-Hong; Sinz, Michael; Stearns, Ralph; Walsky, Robert; Geng, Wanping; Sudsakorn, Sirimas; Moore, David; He, Ling; Wahlstrom, Jan; Keirns, Jim; Narayanan, Rangaraj; Lang, Dieter; Yang, Xiaoqing

2016-08-01

Under the guidance of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ), scientists from 20 pharmaceutical companies formed a Victim Drug-Drug Interactions Working Group. This working group has conducted a review of the literature and the practices of each company on the approaches to clearance pathway identification (fCL), estimation of fractional contribution of metabolizing enzyme toward metabolism (fm), along with modeling and simulation-aided strategy in predicting the victim drug-drug interaction (DDI) liability due to modulation of drug metabolizing enzymes. Presented in this perspective are the recommendations from this working group on: 1) strategic and experimental approaches to identify fCL and fm, 2) whether those assessments may be quantitative for certain enzymes (e.g., cytochrome P450, P450, and limited uridine diphosphoglucuronosyltransferase, UGT enzymes) or qualitative (for most of other drug metabolism enzymes), and the impact due to the lack of quantitative information on the latter. Multiple decision trees are presented with stepwise approaches to identify specific enzymes that are involved in the metabolism of a given drug and to aid the prediction and risk assessment of drug as a victim in DDI. Modeling and simulation approaches are also discussed to better predict DDI risk in humans. Variability and parameter sensitivity analysis were emphasized when applying modeling and simulation to capture the differences within the population used and to characterize the parameters that have the most influence on the prediction outcome. Copyright © 2016 by The American Society for Pharmacology and Experimental Therapeutics.

The Accuracy of Serum Matrix Metalloproteinase-9 for Predicting Hemorrhagic Transformation After Acute Ischemic Stroke: A Systematic Review and Meta-Analysis.

PubMed

Wang, Lu; Wei, Chenchen; Deng, Linghui; Wang, Ziqiong; Song, Mengyuan; Xiong, Yao; Liu, Ming

2018-06-01

Hemorrhagic transformation is a serious complication of acute ischemic stroke, which may cause detrimental outcomes and the delayed use of anticoagulation therapy. Early predicting and identifying the patients at high risk of hemorrhagic transformation before clinical deterioration occurrence become a research priority. To study the value of plasma matrix metalloproteinase-9 predicting hemorrhagic transformation after ischemic stroke. We searched PubMed, Ovid, Cochrane Library, and other 2 Chinese databases to identify literatures published up to September 2017 and performed meta-analysis by STATA (version 12.0, StataCorp LP, College Station, TX). Twelve studies incorporating 1492 participants were included and 7 studies were included in the quantitative statistical analysis. The pooled sensitivity was 85% (95% confidence interval [CI]: 75%, 91%) and the pooled specificity was 79% (95% CI: 67%, 87%). The area under the receiver operating characteristic curve was .89 (95% CI .86, .91). Significant heterogeneity for all estimates value existed (all the P value < .05 and I 2  > 50%). There is no threshold effect with P value greater than .05 of the correlation coefficient. Meta-regression and subgroup analysis showed cut-off value and hemorrhagic subtype contributed to heterogeneity. Deeks' funnel plot indicated no significant publication bias for 7 quantitative analysis studies. Matrix metalloproteinase-9 has high predictive value for hemorrhagic transformation after acute ischemic stroke. It may be useful to test matrix metalloproteinase-9 to exclude patients at low risk of hemorrhage for precise treatment in the future clinical work. Copyright © 2018 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Quantitative mass spectrometry methods for pharmaceutical analysis

PubMed Central

Loos, Glenn; Van Schepdael, Ann

2016-01-01

Quantitative pharmaceutical analysis is nowadays frequently executed using mass spectrometry. Electrospray ionization coupled to a (hybrid) triple quadrupole mass spectrometer is generally used in combination with solid-phase extraction and liquid chromatography. Furthermore, isotopically labelled standards are often used to correct for ion suppression. The challenges in producing sensitive but reliable quantitative data depend on the instrumentation, sample preparation and hyphenated techniques. In this contribution, different approaches to enhance the ionization efficiencies using modified source geometries and improved ion guidance are provided. Furthermore, possibilities to minimize, assess and correct for matrix interferences caused by co-eluting substances are described. With the focus on pharmaceuticals in the environment and bioanalysis, different separation techniques, trends in liquid chromatography and sample preparation methods to minimize matrix effects and increase sensitivity are discussed. Although highly sensitive methods are generally aimed for to provide automated multi-residue analysis, (less sensitive) miniaturized set-ups have a great potential due to their ability for in-field usage. This article is part of the themed issue ‘Quantitative mass spectrometry’. PMID:27644982

Use of Direct LAMP Screening of Broiler Fecal Samples for Campylobacter jejuni and Campylobacter coli in the Positive Flock Identification Strategy.

PubMed

Sabike, Islam I; Uemura, Ryoko; Kirino, Yumi; Mekata, Hirohisa; Sekiguchi, Satoshi; Okabayashi, Tamaki; Goto, Yoshitaka; Yamazaki, Wataru

2016-01-01

Rapid identification of Campylobacter -positive flocks before slaughter, following freezing and heat treatment for the Campylobacter -positive carcasses at the slaughterhouses is an effective control strategy against foodborne campylobacteriosis. We evaluated a loop-mediated isothermal amplification (LAMP) assay for the direct screening of naturally contaminated chicken cloacal swabs for C. jejuni / C. coli to compare this assay with conventional quantitative culture methods. In a comparison study of 165 broilers, the LAMP assay showed 82.8% (48/58 by conventional culture) sensitivity, 100% (107/107) specificity, 100% (48/48) positive predictive value (PPV), and 91.5% (107/117) negative predictive value (NPV). In a comparison of 55 flocks, LAMP showed 90.5% (19/21) sensitivity, 100% (34/34) specificity, 100% (19/19) PPV, and 94.4% (34/36) NPV. In the cumulative total of 28 farm-level comparisons, LAMP showed 100% (12/12) sensitivity, 100% (16/16) specificity, 100% (12/12) PPV, and 100% (16/16) NPV. The LAMP assay required less than 90 min from the arrival of the fecal samples to final results in the laboratory. This suggests that the LAMP assay will facilitate the identification of C. jejuni / C. coli -positive broiler flocks at the farm level or in slaughterhouses before slaughtering, which would make it an effective tool in preventing the spread of Campylobacter contamination.

Evaluating Rapid Models for High-Throughput Exposure Forecasting (SOT)

EPA Science Inventory

High throughput exposure screening models can provide quantitative predictions for thousands of chemicals; however these predictions must be systematically evaluated for predictive ability. Without the capability to make quantitative, albeit uncertain, forecasts of exposure, the ...

Use of Cell Viability Assay Data Improves the Prediction Accuracy of Conventional Quantitative Structure–Activity Relationship Models of Animal Carcinogenicity

PubMed Central

Zhu, Hao; Rusyn, Ivan; Richard, Ann; Tropsha, Alexander

2008-01-01

Background To develop efficient approaches for rapid evaluation of chemical toxicity and human health risk of environmental compounds, the National Toxicology Program (NTP) in collaboration with the National Center for Chemical Genomics has initiated a project on high-throughput screening (HTS) of environmental chemicals. The first HTS results for a set of 1,408 compounds tested for their effects on cell viability in six different cell lines have recently become available via PubChem. Objectives We have explored these data in terms of their utility for predicting adverse health effects of the environmental agents. Methods and results Initially, the classification k nearest neighbor (kNN) quantitative structure–activity relationship (QSAR) modeling method was applied to the HTS data only, for a curated data set of 384 compounds. The resulting models had prediction accuracies for training, test (containing 275 compounds together), and external validation (109 compounds) sets as high as 89%, 71%, and 74%, respectively. We then asked if HTS results could be of value in predicting rodent carcinogenicity. We identified 383 compounds for which data were available from both the Berkeley Carcinogenic Potency Database and NTP–HTS studies. We found that compounds classified by HTS as “actives” in at least one cell line were likely to be rodent carcinogens (sensitivity 77%); however, HTS “inactives” were far less informative (specificity 46%). Using chemical descriptors only, kNN QSAR modeling resulted in 62.3% prediction accuracy for rodent carcinogenicity applied to this data set. Importantly, the prediction accuracy of the model was significantly improved (72.7%) when chemical descriptors were augmented by HTS data, which were regarded as biological descriptors. Conclusions Our studies suggest that combining NTP–HTS profiles with conventional chemical descriptors could considerably improve the predictive power of computational approaches in toxicology. PMID:18414635

Real time endoscopic ultrasound elastography and strain ratio in the diagnosis of solid pancreatic lesions.

PubMed

Okasha, Hussein; Elkholy, Shaimaa; El-Sayed, Ramy; Wifi, Mohamed-Naguib; El-Nady, Mohamed; El-Nabawi, Walid; El-Dayem, Waleed A; Radwan, Mohamed I; Farag, Ali; El-Sherif, Yahya; Al-Gemeie, Emad; Salman, Ahmed; El-Sherbiny, Mohamed; El-Mazny, Ahmed; Mahdy, Reem E

2017-08-28

To evaluate the accuracy of the elastography score combined to the strain ratio in the diagnosis of solid pancreatic lesions (SPL). A total of 172 patients with SPL identified by endoscopic ultrasound were enrolled in the study to evaluate the efficacy of elastography and strain ratio in differentiating malignant from benign lesions. The semi quantitative score of elastography was represented by the strain ratio method. Two areas were selected, area (A) representing the region of interest and area (B) representing the normal area. Area (B) was then divided by area (A). Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated by comparing diagnoses made by elastography, strain ratio and final diagnoses. SPL were shown to be benign in 49 patients and malignant in 123 patients. Elastography alone had a sensitivity of 99%, a specificity of 63%, and an accuracy of 88%, a PPV of 87% and an NPV of 96%. The best cut-off level of strain ratio to obtain the maximal area under the curve was 7.8 with a sensitivity of 92%, specificity of 77%, PPV of 91%, NPV of 80% and an accuracy of 88%. Another estimated cut off strain ratio level of 3.8 had a higher sensitivity of 99% and NPV of 96%, but with less specificity, PPV and accuracy 53%, 84% and 86%, respectively. Adding both elastography to strain ratio resulted in a sensitivity of 98%, specificity of 77%, PPV of 91%, NPV of 95% and accuracy of 92% for the diagnosis of SPL. Combining elastography to strain ratio increases the accuracy of the differentiation of benign from malignant SPL.

Real time endoscopic ultrasound elastography and strain ratio in the diagnosis of solid pancreatic lesions

PubMed Central

Okasha, Hussein; Elkholy, Shaimaa; El-Sayed, Ramy; Wifi, Mohamed-Naguib; El-Nady, Mohamed; El-Nabawi, Walid; El-Dayem, Waleed A; Radwan, Mohamed I; Farag, Ali; El-sherif, Yahya; Al-Gemeie, Emad; Salman, Ahmed; El-Sherbiny, Mohamed; El-Mazny, Ahmed; Mahdy, Reem E

2017-01-01

AIM To evaluate the accuracy of the elastography score combined to the strain ratio in the diagnosis of solid pancreatic lesions (SPL). METHODS A total of 172 patients with SPL identified by endoscopic ultrasound were enrolled in the study to evaluate the efficacy of elastography and strain ratio in differentiating malignant from benign lesions. The semi quantitative score of elastography was represented by the strain ratio method. Two areas were selected, area (A) representing the region of interest and area (B) representing the normal area. Area (B) was then divided by area (A). Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated by comparing diagnoses made by elastography, strain ratio and final diagnoses. RESULTS SPL were shown to be benign in 49 patients and malignant in 123 patients. Elastography alone had a sensitivity of 99%, a specificity of 63%, and an accuracy of 88%, a PPV of 87% and an NPV of 96%. The best cut-off level of strain ratio to obtain the maximal area under the curve was 7.8 with a sensitivity of 92%, specificity of 77%, PPV of 91%, NPV of 80% and an accuracy of 88%. Another estimated cut off strain ratio level of 3.8 had a higher sensitivity of 99% and NPV of 96%, but with less specificity, PPV and accuracy 53%, 84% and 86%, respectively. Adding both elastography to strain ratio resulted in a sensitivity of 98%, specificity of 77%, PPV of 91%, NPV of 95% and accuracy of 92% for the diagnosis of SPL. CONCLUSION Combining elastography to strain ratio increases the accuracy of the differentiation of benign from malignant SPL. PMID:28932088

Elastographic techniques of thyroid gland: current status.

PubMed

Andrioli, Massimiliano; Persani, Luca

2014-08-01

Thyroid nodules are very common with malignancies accounting for about 5 %. Fine-needle biopsy is the most accurate test for thyroid cancer diagnosis. Elastography, a new technology directly evaluating the elastic property of the tissue, has been recently added to the diagnostic armamentarium of the endocrinologists as noninvasive predictor of thyroid malignancy. In this paper, we critically reviewed characteristics and applications of elastographic methods in thyroid gland. Elastographic techniques can be classified on the basis of the following: source-of-tissue compression (free-hand, carotid vibration, ultrasound pulses), processing time (real-time, off-line), stiffness expression (qualitative, semi-quantitative, or quantitative). Acoustic radiation force impulse and aixplorer shear wave are the newest and most promising quantitative elastographic methods. Primary application of elastography is the detection of nodular lesions suspicious for malignancy. Published data show a high sensitivity and negative predictive value of the technique. Insufficient data are available on the possible application of elastography in the differential diagnosis of indeterminate lesions and in thyroiditis. Elastography represents a noninvasive tool able to increase the performance of ultrasound in the selection of thyroid nodules at higher risk of malignancy. Some technical improvements and definition of more robust quantitative diagnostic criteria are required for assigning a definite role in the management of thyroid nodules and thyroiditis to elastography.

Mini-Column Ion-Exchange Separation and Atomic Absorption Quantitation of Nickel, Cobalt, and Iron: An Undergraduate Quantitative Analysis Experiment.

ERIC Educational Resources Information Center

Anderson, James L.; And Others

1980-01-01

Presents an undergraduate quantitative analysis experiment, describing an atomic absorption quantitation scheme that is fast, sensitive and comparatively simple relative to other titration experiments. (CS)

A quantitative systems pharmacology model of blood coagulation network describes in vivo biomarker changes in non-bleeding subjects.

PubMed

Lee, D; Nayak, S; Martin, S W; Heatherington, A C; Vicini, P; Hua, F

2016-12-01

Essentials Baseline coagulation activity can be detected in non-bleeding state by in vivo biomarker levels. A detailed mathematical model of coagulation was developed to describe the non-bleeding state. Optimized model described in vivo biomarkers with recombinant activated factor VII treatment. Sensitivity analysis predicted prothrombin fragment 1 + 2 and D-dimer are regulated differently. Background Prothrombin fragment 1 + 2 (F 1 + 2 ), thrombin-antithrombin III complex (TAT) and D-dimer can be detected in plasma from non-bleeding hemostatically normal subjects or hemophilic patients. They are often used as safety or pharmacodynamic biomarkers for hemostatis-modulating therapies in the clinic, and provide insights into in vivo coagulation activity. Objectives To develop a quantitative systems pharmacology (QSP) model of the blood coagulation network to describe in vivo biomarkers, including F 1 + 2 , TAT, and D-dimer, under non-bleeding conditions. Methods The QSP model included intrinsic and extrinsic coagulation pathways, platelet activation state-dependent kinetics, and a two-compartment pharmacokinetics model for recombinant activated factor VII (rFVIIa). Literature data on F 1 + 2 and D-dimer at baseline and changes with rFVIIa treatment were used for parameter optimization. Multiparametric sensitivity analysis (MPSA) was used to understand key proteins that regulate F 1 + 2 , TAT and D-dimer levels. Results The model was able to describe tissue factor (TF)-dependent baseline levels of F 1 + 2 , TAT and D-dimer in a non-bleeding state, and their increases in hemostatically normal subjects and hemophilic patients treated with different doses of rFVIIa. The amount of TF required is predicted to be very low in a non-bleeding state. The model also predicts that these biomarker levels will be similar in hemostatically normal subjects and hemophilic patients. MPSA revealed that F 1 + 2 and TAT levels are highly correlated, and that D-dimer is more sensitive to the perturbation of coagulation protein concentrations. Conclusions A QSP model for non-bleeding baseline coagulation activity was established with data from clinically relevant in vivo biomarkers at baseline and changes in response to rFVIIa treatment. This model will provide future mechanistic insights into this system. © 2016 International Society on Thrombosis and Haemostasis.

Identification of the soluble form of tyrosine kinase receptor Axl as a potential biomarker for intracranial aneurysm rupture.

PubMed

Xu, Jing; Ma, Feiqiang; Yan, Wei; Qiao, Sen; Xu, Shengquan; Li, Yi; Luo, Jianhong; Zhang, Jianmin; Jin, Jinghua

2015-03-05

Subarachnoid hemorrhage caused by a ruptured intracranial aneurysm (RIA) is a devastating condition with significant morbidity and mortality. Despite the fact that RIAs can be prevented by microsurgical clipping or endovascular coiling, there are no reliable means of effectively predicting IA patients at risk for rupture. The purpose of our study was to discover differentially-expressed glycoproteins in IAs with or without rupture as potential biomarkers to predict rupture. Forty age/gender-matched patients with RIA, unruptured IA (UIA), healthy controls (HCs) and disease controls (DCs) (discovery cohort, n = 10 per group) were recruited and a multiplex quantitative proteomic method, iTRAQ (isobaric Tagging for Relative and Absolute protein Quantification), was used to quantify relative changes in the lectin-purified glycoproteins in CSF from RIAs and UIAs compared to HCs and DCs. Then we verified the proteomic results in an independent set of samples (validation cohort, n = 20 per group) by enzyme-linked immunosorbent assay. Finally, we evaluated the specificity and sensitivity of the candidate marker with receiver operating characteristic (ROC) curve methods. The proteomic findings identified 294 proteins, 40 of which displayed quantitative changes unique to RIA, 13 to UIA, and 20 to IA. One of these proteins, receptor tyrosine kinase Axl, was significantly increased in RIA, as confirmed in CSF from the discovery cohort as well as in CSF and plasma from the validation cohort (p <0.05). Spearman's correlation analysis revealed that the CSF and plasma Axl levels were strongly correlated (r = 0.93, p <0.0001). The ROC curve indicated an optimal CSF Axl threshold of 0.12 nM for discriminating RIA from UIA with corresponding sensitivity/specificity of 73.33%/90% and an area under the curve (AUC) of 0.89 (95% CI: 0.80-0.97, p < 0.0001). The optimal threshold for plasma Axl was 1.7 nM with corresponding sensitivity/specificity of 50%/80% and an AUC of 0.71 (95% CI: 0.54-0.87, p = 0.027). Both CSF and plasma Axl levels are significantly elevated in RIA patients. Axl might serve as a promising biomarker to predict the rupture of IA.

Magnetic Resonance Imaging of Intracranial Hypotension: Diagnostic Value of Combined Qualitative Signs and Quantitative Metrics.

PubMed

Aslan, Kerim; Gunbey, Hediye Pinar; Tomak, Leman; Ozmen, Zafer; Incesu, Lutfi

The aim of this study was to investigate whether the use of combination quantitative metrics (mamillopontine distance [MPD], pontomesencephalic angle, and mesencephalon anterior-posterior/medial-lateral diameter ratios) with qualitative signs (dural enhancement, subdural collections/hematoma, venous engorgement, pituitary gland enlargements, and tonsillar herniations) provides a more accurate diagnosis of intracranial hypotension (IH). The quantitative metrics and qualitative signs of 34 patients and 34 control subjects were assessed by 2 independent observers. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of quantitative metrics and qualitative signs, and for the diagnosis of IH, optimum cutoff values of quantitative metrics were found with ROC analysis. Combined ROC curve was measured for the quantitative metrics, and qualitative signs combinations in determining diagnostic accuracy and sensitivity, specificity, and positive and negative predictive values were found, and the best model combination was formed. Whereas MPD and pontomesencephalic angle were significantly lower in patients with IH when compared with the control group (P < 0.001), mesencephalon anterior-posterior/medial-lateral diameter ratio was significantly higher (P < 0.001). For qualitative signs, the highest individual distinctive power was dural enhancement with area under the ROC curve (AUC) of 0.838. For quantitative metrics, the highest individual distinctive power was MPD with AUC of 0.947. The best accuracy in the diagnosis of IH was obtained by combination of dural enhancement, venous engorgement, and MPD with an AUC of 1.00. This study showed that the combined use of dural enhancement, venous engorgement, and MPD had diagnostic accuracy of 100 % for the diagnosis of IH. Therefore, a more accurate IH diagnosis can be provided with combination of quantitative metrics with qualitative signs.

Evolution of flowering strategies in Oenothera glazioviana: an integral projection model approach.

PubMed Central

Rees, Mark; Rose, Karen E

2002-01-01

The timing of reproduction is a key determinant of fitness. Here, we develop parameterized integral projection models of size-related flowering for the monocarpic perennial Oenothera glazioviana and use these to predict the evolutionarily stable strategy (ESS) for flowering. For the most part there is excellent agreement between the model predictions and the results of quantitative field studies. However, the model predicts a much steeper relationship between plant size and the probability of flowering than observed in the field, indicating selection for a 'threshold size' flowering function. Elasticity and sensitivity analysis of population growth rate lambda and net reproductive rate R(0) are used to identify the critical traits that determine fitness and control the ESS for flowering. Using the fitted model we calculate the fitness landscape for invading genotypes and show that this is characterized by a ridge of approximately equal fitness. The implications of these results for the maintenance of genetic variation are discussed. PMID:12137582

Evolution of flowering strategies in Oenothera glazioviana: an integral projection model approach.

PubMed

Rees, Mark; Rose, Karen E

2002-07-22

The timing of reproduction is a key determinant of fitness. Here, we develop parameterized integral projection models of size-related flowering for the monocarpic perennial Oenothera glazioviana and use these to predict the evolutionarily stable strategy (ESS) for flowering. For the most part there is excellent agreement between the model predictions and the results of quantitative field studies. However, the model predicts a much steeper relationship between plant size and the probability of flowering than observed in the field, indicating selection for a 'threshold size' flowering function. Elasticity and sensitivity analysis of population growth rate lambda and net reproductive rate R(0) are used to identify the critical traits that determine fitness and control the ESS for flowering. Using the fitted model we calculate the fitness landscape for invading genotypes and show that this is characterized by a ridge of approximately equal fitness. The implications of these results for the maintenance of genetic variation are discussed.

Coupling model of aerobic waste degradation considering temperature, initial moisture content and air injection volume.

PubMed

Ma, Jun; Liu, Lei; Ge, Sai; Xue, Qiang; Li, Jiangshan; Wan, Yong; Hui, Xinminnan

2018-03-01

A quantitative description of aerobic waste degradation is important in evaluating landfill waste stability and economic management. This research aimed to develop a coupling model to predict the degree of aerobic waste degradation. On the basis of the first-order kinetic equation and the law of conservation of mass, we first developed the coupling model of aerobic waste degradation that considered temperature, initial moisture content and air injection volume to simulate and predict the chemical oxygen demand in the leachate. Three different laboratory experiments on aerobic waste degradation were simulated to test the model applicability. Parameter sensitivity analyses were conducted to evaluate the reliability of parameters. The coupling model can simulate aerobic waste degradation, and the obtained simulation agreed with the corresponding results of the experiment. Comparison of the experiment and simulation demonstrated that the coupling model is a new approach to predict aerobic waste degradation and can be considered as the basis for selecting the economic air injection volume and appropriate management in the future.

Analysis of transient fission gas behaviour in oxide fuel using BISON and TRANSURANUS

NASA Astrophysics Data System (ADS)

Barani, T.; Bruschi, E.; Pizzocri, D.; Pastore, G.; Van Uffelen, P.; Williamson, R. L.; Luzzi, L.

2017-04-01

The modelling of fission gas behaviour is a crucial aspect of nuclear fuel performance analysis in view of the related effects on the thermo-mechanical performance of the fuel rod, which can be particularly significant during transients. In particular, experimental observations indicate that substantial fission gas release (FGR) can occur on a small time scale during transients (burst release). To accurately reproduce the rapid kinetics of the burst release process in fuel performance calculations, a model that accounts for non-diffusional mechanisms such as fuel micro-cracking is needed. In this work, we present and assess a model for transient fission gas behaviour in oxide fuel, which is applied as an extension of conventional diffusion-based models to introduce the burst release effect. The concept and governing equations of the model are presented, and the sensitivity of results to the newly introduced parameters is evaluated through an analytic sensitivity analysis. The model is assessed for application to integral fuel rod analysis by implementation in two structurally different fuel performance codes: BISON (multi-dimensional finite element code) and TRANSURANUS (1.5D code). Model assessment is based on the analysis of 19 light water reactor fuel rod irradiation experiments from the OECD/NEA IFPE (International Fuel Performance Experiments) database, all of which are simulated with both codes. The results point out an improvement in both the quantitative predictions of integral fuel rod FGR and the qualitative representation of the FGR kinetics with the transient model relative to the canonical, purely diffusion-based models of the codes. The overall quantitative improvement of the integral FGR predictions in the two codes is comparable. Moreover, calculated radial profiles of xenon concentration after irradiation are investigated and compared to experimental data, illustrating the underlying representation of the physical mechanisms of burst release.

Sweat conductivity and coulometric quantitative test in neonatal cystic fibrosis screening.

PubMed

Domingos, Mouseline Torquato; Magdalena, Neiva Isabel Rodrigues; Cat, Mônica Nunes Lima; Watanabe, Alexandra Mitiru; Rosário Filho, Nelson Augusto

2015-01-01

To compare the results obtained with the sweat test using the conductivity method and coulometric measurement of sweat chloride in newborns (NBs) with suspected cystic fibrosis (CF) in the neonatal screening program. The sweat test was performed simultaneously by both methods in children with and without CF. The cutoff values to confirm CF were >50 mmol/L in the conductivity and >60 mmol/L in the coulometric test. There were 444 infants without CF (185 males, 234 females, and 24 unreported) submitted to the sweat test through conductivity and coulometric measurement simultaneously, obtaining median results of 32 mmol/L and 12 mmol/L, respectively. For 90 infants with CF, the median values of conductivity and coulometric measurement were 108 mmol/L and 97 mmol/L, respectively. The false positive rate for conductivity was 16.7%, and was higher than 50 mmol/L in all patients with CF, which gives this method a sensitivity of 100% (95% CI: 93.8-97.8), specificity of 96.2% (95% CI: 93.8-97.8), positive predictive value of 83.3% (95% CI: 74.4-91.1), negative predictive value of 100% (95% CI: 90.5-109.4), and 9.8% accuracy. The correlation between the methods was r=0.97 (p>0.001). The best suggested cutoff value was 69.0 mmol/L, with a kappa coefficient=0.89. The conductivity test showed excellent correlation with the quantitative coulometric test, high sensitivity and specificity, and can be used in the diagnosis of CF in children detected through newborn screening. Copyright © 2015 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

Pneumocystis jirovecii (Pj) quantitative PCR to differentiate Pj pneumonia from Pj colonization in immunocompromised patients.

PubMed

Maillet, M; Maubon, D; Brion, J P; François, P; Molina, L; Stahl, J P; Epaulard, O; Bosseray, A; Pavese, P

2014-03-01

Conventional polymerase chain reaction (PCR) in respiratory samples does not differentiate between Pneumocystis pneumonia (PCP) and Pneumocystis jirovecii (Pj) colonization. We used Pj real-time quantitative PCR (qPCR) with the objective to discriminate PCP from Pj colonization in immunocompromised patients. All positive Pj qPCR [targeting the major surface glycoprotein (MSG) gene] obtained in respiratory samples from immunocompromised patients presenting pneumonia at the Grenoble University Hospital, France, were collected between August 2009 and April 2011. Diagnoses were retrospectively determined by a multidisciplinary group of experts blinded to the Pj qPCR results. Thirty-one bronchoalveolar lavages and four broncho aspirations positive for the Pj qPCR were obtained from 35 immunocompromised patients. Diagnoses of definite, probable, and possible PCP, and pneumonia from another etiology were retrospectively made for 7, 4, 5, and 19 patients, respectively. Copy numbers were significantly higher in the "definite group" (median 465,000 copies/ml) than in the "probable group" (median 38,600 copies/ml), the "possible group" (median 1,032 copies/ml), and the "other diagnosis group" (median 390 copies/ml). With the value of 3,160 copies/ml, the sensitivity and specificity of qPCR for the diagnosis of PCP were 100 % and 70 %, respectively. With the value of 31,600 copies/ml, the sensitivity and specificity were 80 % and 100 %, respectively. The positive predictive value was 100 % for results with more than 31,600 copies/ml and the negative predictive value was 100 % for results with fewer than 3,160 copies/ml. qPCR targeting the MSG gene can be helpful to discriminate PCP from Pj colonization in immunocompromised patients, using two cut-off values, with a gray zone between them.

Use of the ciliated protozoan Tetrahymena pyriformis for the assessment of toxicity and quantitative structure--activity relationships of xenobiotics: comparison with the Microtox test.

PubMed

Bogaerts, P; Bohatier, J; Bonnemoy, F

2001-07-01

Cytotoxicity and quantitative structure-activity relationships of 13 inorganic and 21 organic substances were determined using three bioassays performed on the ciliated protozoan Tetrahymena pyriformis and the luminescent bacterium Vibrio fischeri. The best concordance of toxicity results was observed between the T. pyriformis FDA--esterase activity and population growth inhibition tests for the organic compounds. The sensitivity of these two assays is compared with that of the Microtox test. The T. pyriformis FDA test showed a high sensitivity is most cases. The aim of the current research was to determine whether the relative toxicity of metal ions and organic molecules, with these three bioassays, was predictable using three ion characteristics and hydrophobicity, respectively. For metal ions, the variable that best modeled the toxicity data obtained with the two T. pyriformis tests was the softness index [sigma(p), i.e., (coordinate bond energy of the metal fluoride--coordinate bond energy of the metal iodide)/(coordinate bond energy of the metal fluoride)]. No correlation was found with the Microtox test. For organic compounds, a significant correlation was observed between the hydrophobicity coefficient and the toxicity data. This correlation is closer with the two tests using Tetrahymena. Copyright 2001 Academic Press.

[Development of a diagnostic test system for early non-invasive detection of prostate cancer based on PCA3 mRNA levels in urine sediment using quantitative reverse tanscription polymerase chain reaction (qRT-PCR)].

PubMed

Pavlov, K A; Shkoporov, A N; Khokhlova, E V; Korchagina, A A; Sidorenkov, A V; Grigor'ev, M É; Pushkar', D Iu; Chekhonin, V P

2013-01-01

The wide introduction of prostatic specific antigen (PSA) determination into clinical practice has resulted in a larger number of prostate biopsies, while the lower age threshold for PSA has led to a larger number of unnecessary prostate biopsies. Hence, there is a need for new biomarkers that can detect prostate cancer. PCA3 is a noncoding messenger ribonucleic acid (mRNA) that is expressed exclusively in prostate cells. The aim of the study has been to develop a diagnostic test system for early non-invasive detection of prostate cancer based on PCA3 mRNA levels in urine sediment using quantitative reverse transcription polymerase chain reaction (qRT-PCR). As part of the study, a laboratory diagnostic test system prototype has been designed, an application methodology has been developed and specificity and sensitivity data of the method has been assessed. The diagnostic system has demonstrated its ability to detect significantly elevated levels of PCA 3/KLK 3 in samples from prostate cancer (PCa) patients compared with those from healthy men. The findings have shown relatively high diagnostic sensitivity, specificity and negative-predictive values for an early non-invasive screening of prostate cancer

X-Ray and UV Photoelectron Spectroscopy | Materials Science | NREL

Science.gov Websites

backsheet material, showing excellent quantitative agreement between measured and predicted peak area ratios quantitative agreement between measured and predicted peak area ratios. Subtle differences in polymer functionality are assessed by deviations from stoichiometry. Elemental Analysis Uses quantitative identification

Weather Prediction Center (WPC) Home Page

Science.gov Websites

grids, quantitative precipitation, and winter weather outlook probabilities can be found at: http Short Range Products » More Medium Range Products Quantitative Precipitation Forecasts Legacy Page Discussion (Day 1-3) Quantitative Precipitation Forecast Discussion NWS Weather Prediction Center College

Characterization and Comparison of Galactomannan Enzyme Immunoassay and Quantitative Real-Time PCR Assay for Detection of Aspergillus fumigatus in Bronchoalveolar Lavage Fluid from Experimental Invasive Pulmonary Aspergillosis

PubMed Central

Francesconi, Andrea; Kasai, Miki; Petraitiene, Ruta; Petraitis, Vidmantas; Kelaher, Amy M.; Schaufele, Robert; Hope, William W.; Shea, Yvonne R.; Bacher, John; Walsh, Thomas J.

2006-01-01

Bronchoalveolar lavage (BAL) is widely used for evaluation of patients with suspected invasive pulmonary aspergillosis (IPA). However, the diagnostic yield of BAL for detection of IPA by culture and direct examination is limited. Earlier diagnosis may be facilitated by assays that can detect Aspergillus galactomannan antigen or DNA in BAL fluid. We therefore characterized and compared the diagnostic yields of a galactomannan enzyme immunoassay (GM EIA), quantitative real-time PCR (qPCR), and quantitative cultures in experiments using BAL fluid from neutropenic rabbits with experimentally induced IPA defined as microbiologically and histologically evident invasion. The qPCR assay targeted the rRNA gene complex of Aspergillus fumigatus. The GM EIA and qPCR assay were characterized by receiver operator curve analysis. With an optimal cutoff of 0.75, the GM EIA had a sensitivity and specificity of 100% in untreated controls. A decline in sensitivity (92%) was observed when antifungal therapy (AFT) was administered. The optimal cutoff for qPCR was a crossover of 36 cycles, with sensitivity and specificity of 80% and 100%, respectively. The sensitivity of qPCR also decreased with AFT to 50%. Quantitative culture of BAL had a sensitivity of 46% and a specificity of 100%. The sensitivity of quantitative culture decreased with AFT to 16%. The GM EIA and qPCR assay had greater sensitivity than culture in detection of A. fumigatus in BAL fluid in experimentally induced IPA (P ± 0.04). Use of the GM EIA and qPCR assay in conjunction with culture-based diagnostic methods applied to BAL fluid could facilitate accurate diagnosis and more-timely initiation of specific therapy. PMID:16825367

Odor Landscapes in Turbulent Environments

NASA Astrophysics Data System (ADS)

Celani, Antonio; Villermaux, Emmanuel; Vergassola, Massimo

2014-10-01

The olfactory system of male moths is exquisitely sensitive to pheromones emitted by females and transported in the environment by atmospheric turbulence. Moths respond to minute amounts of pheromones, and their behavior is sensitive to the fine-scale structure of turbulent plumes where pheromone concentration is detectible. The signal of pheromone whiffs is qualitatively known to be intermittent, yet quantitative characterization of its statistical properties is lacking. This challenging fluid dynamics problem is also relevant for entomology, neurobiology, and the technological design of olfactory stimulators aimed at reproducing physiological odor signals in well-controlled laboratory conditions. Here, we develop a Lagrangian approach to the transport of pheromones by turbulent flows and exploit it to predict the statistics of odor detection during olfactory searches. The theory yields explicit probability distributions for the intensity and the duration of pheromone detections, as well as their spacing in time. Predictions are favorably tested by using numerical simulations, laboratory experiments, and field data for the atmospheric surface layer. The resulting signal of odor detections lends itself to implementation with state-of-the-art technologies and quantifies the amount and the type of information that male moths can exploit during olfactory searches.

A comparative analysis of numerical approaches to the mechanics of elastic sheets

NASA Astrophysics Data System (ADS)

Taylor, Michael; Davidovitch, Benny; Qiu, Zhanlong; Bertoldi, Katia

2015-06-01

Numerically simulating deformations in thin elastic sheets is a challenging problem in computational mechanics due to destabilizing compressive stresses that result in wrinkling. Determining the location, structure, and evolution of wrinkles in these problems has important implications in design and is an area of increasing interest in the fields of physics and engineering. In this work, several numerical approaches previously proposed to model equilibrium deformations in thin elastic sheets are compared. These include standard finite element-based static post-buckling approaches as well as a recently proposed method based on dynamic relaxation, which are applied to the problem of an annular sheet with opposed tractions where wrinkling is a key feature. Numerical solutions are compared to analytic predictions of the ground state, enabling a quantitative evaluation of the predictive power of the various methods. Results indicate that static finite element approaches produce local minima that are highly sensitive to initial imperfections, relying on a priori knowledge of the equilibrium wrinkling pattern to generate optimal results. In contrast, dynamic relaxation is much less sensitive to initial imperfections and can generate low-energy solutions for a wide variety of loading conditions without requiring knowledge of the equilibrium solution beforehand.

Three year evaluation of Xpert MTB/RIF in a low prevalence tuberculosis setting: A Scottish perspective.

PubMed

Parcell, Benjamin J; Jarchow-MacDonald, Anna A; Seagar, Amie-Louise; Laurenson, Ian F; Prescott, Gordon J; Lockhart, Michael

2017-05-01

Xpert MTB/RIF (Cepheid) is a rapid molecular assay shown to be sensitive and specific for pulmonary tuberculosis (TB) diagnosis in highly endemic countries. We evaluated its diagnostic performance in a low TB prevalence setting, examined rifampicin resistance detection and quantitative capabilities predicting graded auramine microscopy and time to positivity (TTP) of culture. Xpert MTB/RIF was used to test respiratory samples over a 3 year period. Samples underwent graded auramine microscopy, solid/liquid culture, in-house IS6110 real-time PCR, and GenoType MTBDRplus (HAIN Lifescience) to determine rifampicin and/or isoniazid resistance. A total of 2103 Xpert MTB/RIF tests were performed. Compared to culture sensitivity was 95.8%, specificity 99.5%, positive predictive value (PPV) 82.1%, and negative predictive value (NPV) 99.9%. A positive correlation was found between auramine microscopy grade and Xpert MTB/RIF assay load. We found a clear reduction in the median TTP as Xpert MTB/RIF assay load increased. Rifampicin resistance was detected. Xpert MTB/RIF was rapid and accurate in diagnosing pulmonary TB in a low prevalence area. Rapid results will influence infection prevention and control and treatment measures. The excellent NPV obtained suggests further work should be carried out to assess its role in replacing microscopy. Copyright © 2017 The British Infection Association. Published by Elsevier Ltd. All rights reserved.

Accuracy of MSCT Coronary Angiography with 64 Row CT Scanner—Facing the Facts

PubMed Central

Wehrschuetz, M.; Wehrschuetz, E.; Schuchlenz, H.; Schaffler, G.

2010-01-01

Improvements in multislice computed tomography (MSCT) angiography of the coronary vessels have enabled the minimally invasive detection of coronary artery stenoses, while quantitative coronary angiography (QCA) is the accepted reference standard for evaluation thereof. Sixteen-slice MSCT showed promising diagnostic accuracy in detecting coronary artery stenoses haemodynamically and the subsequent introduction of 64-slice scanners promised excellent and fast results for coronary artery studies. This prompted us to evaluate the diagnostic accuracy, sensitivity, specificity, and the negative und positive predictive value of 64-slice MSCT in the detection of haemodynamically significant coronary artery stenoses. Thirty-seven consecutive subjects with suspected coronary artery disease were evaluated with MSCT angiography and the results compared with QCA. All vessels were considered for the assessment of significant coronary artery stenosis (diameter reduction ≥ 50%). Thirteen patients (35%) were identified as having significant coronary artery stenoses on QCA with 6.3% (35/555) affected segments. None of the coronary segments were excluded from analysis. Overall sensitivity for classifying stenoses of 64-slice MSCT was 69%, specificity was 92%, positive predictive value was 38% and negative predictive value was 98%. The interobserver variability for detection of significant lesions had a k-value of 0.43. Sixty-four-slice MSCT offers the diagnostic potential to detect coronary artery disease, to quantify haemodynamically significant coronary artery stenoses and to avoid unnecessary invasive coronary artery examinations. PMID:20567636

A versatile quantitation platform based on platinum nanoparticles incorporated volumetric bar-chart chip for highly sensitive assays.

PubMed

Wang, Yuzhen; Zhu, Guixian; Qi, Wenjin; Li, Ying; Song, Yujun

2016-11-15

Platinum nanoparticles incorporated volumetric bar-chart chip (PtNPs-V-Chip) is able to be used for point-of-care tests by providing quantitative and visualized readout without any assistance from instruments, data processing, or graphic plotting. To improve the sensitivity of PtNPs-V-Chip, hybridization chain reaction was employed in this quantitation platform for highly sensitive assays that can detect as low as 16 pM Ebola Virus DNA, 0.01ng/mL carcinoembryonic antigen (CEA), and the 10 HER2-expressing cancer cells. Based on this amplified strategy, a 100-fold decrease of detection limit was achieved for DNA by improving the number of platinum nanoparticle catalyst for the captured analyte. This quantitation platform can also distinguish single base mismatch of DNA hybridization and observe the concentration threshold of CEA. The new strategy lays the foundation for this quantitation platform to be applied in forensic analysis, biothreat detection, clinical diagnostics and drug screening. Copyright © 2016 Elsevier B.V. All rights reserved.

Urinary Squamous Epithelial Cells Do Not Accurately Predict Urine Culture Contamination, but May Predict Urinalysis Performance in Predicting Bacteriuria.

PubMed

Mohr, Nicholas M; Harland, Karisa K; Crabb, Victoria; Mutnick, Rachel; Baumgartner, David; Spinosi, Stephanie; Haarstad, Michael; Ahmed, Azeemuddin; Schweizer, Marin; Faine, Brett

2016-03-01

The presence of squamous epithelial cells (SECs) has been advocated to identify urinary contamination despite a paucity of evidence supporting this practice. We sought to determine the value of using quantitative SECs as a predictor of urinalysis contamination. Retrospective cross-sectional study of adults (≥18 years old) presenting to a tertiary academic medical center who had urinalysis with microscopy and urine culture performed. Patients with missing or implausible demographic data were excluded (2.5% of total sample). The primary analysis aimed to determine an SEC threshold that predicted urine culture contamination using receiver operating characteristics (ROC) curve analysis. The a priori secondary analysis explored how demographic variables (age, sex, body mass index) may modify the SEC test performance and whether SECs impacted traditional urinalysis indicators of bacteriuria. A total of 19,328 records were included. ROC curve analysis demonstrated that SEC count was a poor predictor of urine culture contamination (area under the ROC curve = 0.680, 95% confidence interval [CI] = 0.671 to 0.689). In secondary analysis, the positive likelihood ratio (LR+) of predicting bacteriuria via urinalysis among noncontaminated specimens was 4.98 (95% CI = 4.59 to 5.40) in the absence of SECs, but the LR+ fell to 2.35 (95% CI = 2.17 to 2.54) for samples with more than 8 SECs/low-powered field (lpf). In an independent validation cohort, urinalysis samples with fewer than 8 SECs/lpf predicted bacteriuria better (sensitivity = 75%, specificity = 84%) than samples with more than 8 SECs/lpf (sensitivity = 86%, specificity = 70%; diagnostic odds ratio = 17.5 [14.9 to 20.7] vs. 8.7 [7.3 to 10.5]). Squamous epithelial cells are a poor predictor of urine culture contamination, but may predict poor predictive performance of traditional urinalysis measures. © 2016 by the Society for Academic Emergency Medicine.

Magnetic resonance imaging of the preterm infant brain.

PubMed

Doria, Valentina; Arichi, Tomoki; Edwards, David A

2014-01-01

Despite improvements in neonatal care, survivors of preterm birth are still at a significantly increased risk of developing life-long neurological difficulties including cerebral palsy and cognitive difficulties. Cranial ultrasound is routinely used in neonatal practice, but has a low sensitivity for identifying later neurodevelopmental difficulties. Magnetic Resonance Imaging (MRI) can be used to identify intracranial abnormalities with greater diagnostic accuracy in preterm infants, and theoretically might improve the planning and targeting of long-term neurodevelopmental care; reducing parental stress and unplanned healthcare utilisation; and ultimately may improve healthcare cost effectiveness. Furthermore, MR imaging offers the advantage of allowing the quantitative assessment of the integrity, growth and function of intracranial structures, thereby providing the means to develop sensitive biomarkers which may be predictive of later neurological impairment. However further work is needed to define the accuracy and value of diagnosis by MR and the techniques's precise role in care pathways for preterm infants.

Classification and virtual screening of androgen receptor antagonists.

PubMed

Li, Jiazhong; Gramatica, Paola

2010-05-24

Computational tools, such as quantitative structure-activity relationship (QSAR), are highly useful as screening support for prioritization of substances of very high concern (SVHC). From the practical point of view, QSAR models should be effective to pick out more active rather than inactive compounds, expressed as sensitivity in classification works. This research investigates the classification of a big data set of endocrine-disrupting chemicals (EDCs)-androgen receptor (AR) antagonists, mainly aiming to improve the external sensitivity and to screen for potential AR binders. The kNN, lazy IB1, and ADTree methods and the consensus approach were used to build different models, which improve the sensitivity on external chemicals from 57.1% (literature) to 76.4%. Additionally, the models' predictive abilities were further validated on a blind collected data set (sensitivity: 85.7%). Then the proposed classifiers were used: (i) to distinguish a set of AR binders into antagonists and agonists; (ii) to screen a combined estrogen receptor binder database to find out possible chemicals that can bind to both AR and ER; and (iii) to virtually screen our in-house environmental chemical database. The in silico screening results suggest: (i) that some compounds can affect the normal endocrine system through a complex mechanism binding both to ER and AR; (ii) new EDCs, which are nonER binders, but can in silico bind to AR, are recognized; and (iii) about 20% of compounds in a big data set of environmental chemicals are predicted as new AR antagonists. The priority should be given to them to experimentally test the binding activities with AR.

A behavioral economic measure of demand for alcohol predicts brief intervention outcomes.

PubMed

MacKillop, James; Murphy, James G

2007-07-10

Considerable basic and clinical research supports a behavioral economic conceptualization of alcohol and drug dependence. One behavioral economic approach to assess motivation for a drug is the use of demand curves, or quantitative representations of drug consumption and drug-reinforced responding across a range of prices. This study used a hypothetical alcohol purchase task to generate demand curves, and examined whether the resulting demand curve parameters predicted drinking outcomes following a brief intervention. Participants were 51 college student drinkers (67% female; 94% Caucasian; drinks/week: M=24.57, S.D.=8.77) who completed a brief alcohol intervention. Consistent with predictions, a number of demand curve indices significantly predicted post-intervention alcohol use and frequency of heavy drinking episodes, even after controlling for baseline drinking and other pertinent covariates. Most prominently, O(max) (i.e., maximum alcohol expenditure) and breakpoint (i.e., sensitivity of consumption to increasing price) predicted greater drinking at 6-month post-intervention follow-up. These results indicate that a behavioral economic measure of alcohol demand may have utility in characterizing the malleability of alcohol consumption. Moreover, these results support the utility of translating experimental assays of reinforcement into clinical research.

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.

Quantitative fetal fibronectin and cervical length to predict preterm birth in asymptomatic women with previous cervical surgery.

PubMed

Vandermolen, Brooke I; Hezelgrave, Natasha L; Smout, Elizabeth M; Abbott, Danielle S; Seed, Paul T; Shennan, Andrew H

2016-10-01

Quantitative fetal fibronectin testing has demonstrated accuracy for prediction of spontaneous preterm birth in asymptomatic women with a history of preterm birth. Predictive accuracy in women with previous cervical surgery (a potentially different risk mechanism) is not known. We sought to compare the predictive accuracy of cervicovaginal fluid quantitative fetal fibronectin and cervical length testing in asymptomatic women with previous cervical surgery to that in women with 1 previous preterm birth. We conducted a prospective blinded secondary analysis of a larger observational study of cervicovaginal fluid quantitative fetal fibronectin concentration in asymptomatic women measured with a Hologic 10Q system (Hologic, Marlborough, MA). Prediction of spontaneous preterm birth (<30, <34, and <37 weeks) with cervicovaginal fluid quantitative fetal fibronectin concentration in primiparous women who had undergone at least 1 invasive cervical procedure (n = 473) was compared with prediction in women who had previous spontaneous preterm birth, preterm prelabor rupture of membranes, or late miscarriage (n = 821). Relationship with cervical length was explored. The rate of spontaneous preterm birth <34 weeks in the cervical surgery group was 3% compared with 9% in previous spontaneous preterm birth group. Receiver operating characteristic curves comparing quantitative fetal fibronectin for prediction at all 3 gestational end points were comparable between the cervical surgery and previous spontaneous preterm birth groups (34 weeks: area under the curve, 0.78 [95% confidence interval 0.64-0.93] vs 0.71 [95% confidence interval 0.64-0.78]; P = .39). Prediction of spontaneous preterm birth using cervical length compared with quantitative fetal fibronectin for prediction of preterm birth <34 weeks of gestation offered similar prediction (area under the curve, 0.88 [95% confidence interval 0.79-0.96] vs 0.77 [95% confidence interval 0.62-0.92], P = .12 in the cervical surgery group; and 0.77 [95% confidence interval 0.70-0.84] vs 0.74 [95% confidence interval 0.67-0.81], P = .32 in the previous spontaneous preterm birth group). Prediction of spontaneous preterm birth using cervicovaginal fluid quantitative fetal fibronectin in asymptomatic women with cervical surgery is valid, and has comparative accuracy to that in women with a history of spontaneous preterm birth. Copyright © 2016 Elsevier Inc. All rights reserved.

Does enhanced insulin sensitivity improve sleep measures in patients with obstructive sleep apnea: A randomized, placebo-controlled pilot study

PubMed Central

Liu, Alice; Kim, Sun H.; Ariel, Danit; Abbasi, Fahim; Lamendola, Cindy; Cardell, James; Xu, Shiming; Patel, Shailja; Tomasso, Vanessa; Mojaddidi, Hafasa; Grove, Kaylene; Tsao, Philip S.; Kushida, Clete A.; Reaven, Gerald M.

2016-01-01

Background High fasting insulin levels have been reported to predict development of observed apneas, suggesting that insulin resistance may contribute to the pathogenesis of obstructive sleep apnea (OSA). The study aim was to determine whether enhancing insulin sensitivity in individuals with OSA would improve sleep measures. Patients/Methods Insulin-resistant, nondiabetic individuals with untreated OSA were randomized (2:1) to pioglitazone (45mg/day) or placebo for 8 weeks in this single-blind study. All individuals had repeat measurements pertaining to sleep (overnight polysomnography and Functional Outcomes of Sleep Questionnaire) and insulin action (insulin suppression test). Results Forty-five overweight/obese men and women with moderate/severe OSA were randomized to pioglitazone (n=30) or placebo (n=15). Although insulin sensitivity increased 31% among pioglitazone-treated as compared to no change among individuals receiving placebo ((p<0.001 for between-group difference), no improvements in quantitative or qualitative sleep measurements were observed. Conclusions Pioglitazone administration increased insulin sensitivity in otherwise untreated individuals with OSA, without any change in polysomnographic sleep measures over an 8-week period. These findings do not support a causal role for insulin resistance in the pathogenesis of OSA. PMID:27544837

Sensitivity regularization of the Cramér-Rao lower bound to minimize B1 nonuniformity effects in quantitative magnetization transfer imaging.

PubMed

Boudreau, Mathieu; Pike, G Bruce

2018-05-07

To develop and validate a regularization approach of optimizing B 1 insensitivity of the quantitative magnetization transfer (qMT) pool-size ratio (F). An expression describing the impact of B 1 inaccuracies on qMT fitting parameters was derived using a sensitivity analysis. To simultaneously optimize for robustness against noise and B 1 inaccuracies, the optimization condition was defined as the Cramér-Rao lower bound (CRLB) regularized by the B 1 -sensitivity expression for the parameter of interest (F). The qMT protocols were iteratively optimized from an initial search space, with and without B 1 regularization. Three 10-point qMT protocols (Uniform, CRLB, CRLB+B 1 regularization) were compared using Monte Carlo simulations for a wide range of conditions (e.g., SNR, B 1 inaccuracies, tissues). The B 1 -regularized CRLB optimization protocol resulted in the best robustness of F against B 1 errors, for a wide range of SNR and for both white matter and gray matter tissues. For SNR = 100, this protocol resulted in errors of less than 1% in mean F values for B 1 errors ranging between -10 and 20%, the range of B 1 values typically observed in vivo in the human head at field strengths of 3 T and less. Both CRLB-optimized protocols resulted in the lowest σ F values for all SNRs and did not increase in the presence of B 1 inaccuracies. This work demonstrates a regularized optimization approach for improving the robustness of auxiliary measurements (e.g., B 1 ) sensitivity of qMT parameters, particularly the pool-size ratio (F). Predicting substantially less B 1 sensitivity using protocols optimized with this method, B 1 mapping could even be omitted for qMT studies primarily interested in F. © 2018 International Society for Magnetic Resonance in Medicine.

Noninvasive Diagnosis of Nonalcoholic Fatty Liver Disease and Quantification of Liver Fat Using a New Quantitative Ultrasound Technique.

PubMed

Lin, Steven C; Heba, Elhamy; Wolfson, Tanya; Ang, Brandon; Gamst, Anthony; Han, Aiguo; Erdman, John W; O'Brien, William D; Andre, Michael P; Sirlin, Claude B; Loomba, Rohit

2015-07-01

Liver biopsy analysis is the standard method used to diagnose nonalcoholic fatty liver disease (NAFLD). Advanced magnetic resonance imaging is a noninvasive procedure that can accurately diagnose and quantify steatosis, but is expensive. Conventional ultrasound is more accessible but identifies steatosis with low levels of sensitivity, specificity, and quantitative accuracy, and results vary among technicians. A new quantitative ultrasound (QUS) technique can identify steatosis in animal models. We assessed the accuracy of QUS in the diagnosis and quantification of hepatic steatosis, comparing findings with those from magnetic resonance imaging proton density fat fraction (MRI-PDFF) analysis as a reference. We performed a prospective, cross-sectional analysis of a cohort of adults (N = 204) with NAFLD (MRI-PDFF, ≥5%) and without NAFLD (controls). Subjects underwent MRI-PDFF and QUS analyses of the liver on the same day at the University of California, San Diego, from February 2012 through March 2014. QUS parameters and backscatter coefficient (BSC) values were calculated. Patients were assigned randomly to training (n = 102; mean age, 51 ± 17 y; mean body mass index, 31 ± 7 kg/m(2)) and validation (n = 102; mean age, 49 ± 17 y; body mass index, 30 ± 6 kg/m(2)) groups; 69% of patients in each group had NAFLD. BSC (range, 0.00005-0.25 1/cm-sr) correlated with MRI-PDFF (Spearman ρ = 0.80; P < .0001). In the training group, the BSC analysis identified patients with NAFLD with an area under the curve value of 0.98 (95% confidence interval, 0.95-1.00; P < .0001). The optimal BSC cut-off value identified patients with NAFLD in the training and validation groups with 93% and 87% sensitivity, 97% and 91% specificity, 86% and 76% negative predictive values, and 99% and 95% positive predictive values, respectively. QUS measurements of BSC can accurately diagnose and quantify hepatic steatosis, based on a cross-sectional analysis that used MRI-PDFF as the reference. With further validation, QUS could be an inexpensive, widely available method to screen the general or at-risk population for NAFLD. Copyright © 2015 AGA Institute. Published by Elsevier Inc. All rights reserved.

A mechanics approach to the study of pressure sensitive adhesives and human skin for transdermal drug delivery applications

NASA Astrophysics Data System (ADS)

Taub, Marc Barry

Transdermal drug delivery is an alternative approach to the systemic delivery of pharmaceuticals where drugs are administered through the skin and absorbed percutaneously. This method of delivery offers several advantages over more traditional routes; most notably, the avoidance of the fast-pass metabolism of the liver and gut, the ability to offer controlled release rates, and the possibility for novel devices. Pressure sensitive adhesives (PSAs) are used to bond transdermal drug delivery devices to the skin because of their good initial and long-term adhesion, clean removability, and skin and drug compatibility. However, an understanding of the mechanics of adhesion to the dermal layer, together with quantitative and reproducible test methods for measuring adhesion, have been lacking. This study utilizes a mechanics-based approach to quantify the interfacial adhesion of PSAs bonded to selected substrates, including human dermal tissue. The delamination of PSA layers is associated with cavitation in the PSA followed by the formation of an extensive cohesive zone behind the debond tip. A quantitative metrology was developed to assess the adhesion and delamination of PSAs, such that it could be possible to easily distinguish between the adhesive characteristics of different PSA compositions and to provide a quantitative basis from which the reliability of adhesive layers bonded to substrates could be studied. A mechanics-based model was also developed to predict debonding in terms of the relevant energy dissipation mechanisms active during this process. As failure of transdermal devices may occur cohesively within the PSA layer, adhesively at the interface between the PSA and the skin, or cohesively between the corneocytes that comprise the outermost layer of the skin, it was also necessary to explore the mechanical and fracture properties of human skin. The out-of-plane delamination of corneocytes was studied by determining the strain energy release rate during debonding of cantilever-beam specimens containing thin layers of human dermal tissue at their midline. Finally, the interfacial adhesion of PSAs bonded to human skin was studied and the mechanics model that was developed for PSA failure was extended to provide the capability for in vivo reliability predictions for transdermal systems bonded to human skin.

Quantitative and Sensitive Detection of Chloramphenicol by Surface-Enhanced Raman Scattering

PubMed Central

Ding, Yufeng; Yin, Hongjun; Meng, Qingyun; Zhao, Yongmei; Liu, Luo; Wu, Zhenglong; Xu, Haijun

2017-01-01

We used surface-enhanced Raman scattering (SERS) for the quantitative and sensitive detection of chloramphenicol (CAP). Using 30 nm colloidal Au nanoparticles (NPs), a low detection limit for CAP of 10−8 M was obtained. The characteristic Raman peak of CAP centered at 1344 cm−1 was used for the rapid quantitative detection of CAP in three different types of CAP eye drops, and the accuracy of the measurement result was verified by high-performance liquid chromatography (HPLC). The experimental results reveal that the SERS technique based on colloidal Au NPs is accurate and sensitive, and can be used for the rapid detection of various antibiotics. PMID:29261161

Assessment of In-Stent Restenosis Using 64-MDCT: Analysis of the CORE-64 Multicenter International Trial

PubMed Central

Wykrzykowska, Joanna J.; Arbab-Zadeh, Armin; Godoy, Gustavo; Miller, Julie M.; Lin, Shezhang; Vavere, Andrea; Paul, Narinder; Niinuma, Hiroyuki; Hoe, John; Brinker, Jeffrey; Khosa, Faisal; Sarwar, Sheryar; Lima, Joao; Clouse, Melvin E.

2012-01-01

OBJECTIVE Evaluations of stents by MDCT from studies performed at single centers have yielded variable results with a high proportion of unassessable stents. The purpose of this study was to evaluate the accuracy of 64-MDCT angiography (MDCTA) in identifying in-stent restenosis in a multicenter trial. MATERIALS AND METHODS The Coronary Evaluation Using Multidetector Spiral Computed Tomography Angiography Using 64 Detectors (CORE-64) Multicenter Trial and Registry evaluated the accuracy of 64-MDCTA in assessing 405 patients referred for coronary angiography. A total of 75 stents in 52 patients were assessed: 48 of 75 stents (64%) in 36 of 52 patients (69%) could be evaluated. The prevalence of in-stent restenosis by quantitative coronary angiography (QCA) in this subgroup was 23% (17/75). Eighty percent of the stents were ≤ 3.0 mm in diameter. RESULTS The overall sensitivity, specificity, positive predictive value, and negative predictive value to detect 50% in-stent stenosis visually using MDCT compared with QCA was 33.3%, 91.7%, 57.1%, and 80.5%, respectively, with an overall accuracy of 77.1% for the 48 assessable stents. The ability to evaluate stents on MDCTA varied by stent type: Thick-strut stents such as Bx Velocity were assessable in 50% of the cases; Cypher, 62.5% of the cases; and thinner-strut stents such as Taxus, 75% of the cases. We performed quantitative assessment of in-stent contrast attenuation in Hounsfield units and correlated that value with the quantitative percentage of stenosis by QCA. The correlation coefficient between the average attenuation decrease and ≥ 50% stenosis by QCA was 0.25 (p = 0.073). Quantitative assessment failed to improve the accuracy of MDCT over qualitative assessment. CONCLUSION The results of our study showed that 64-MDCT has poor ability to detect in-stent restenosis in small-diameter stents. Evaluability and negative predictive value were better in large-diameter stents. Thus, 64-MDCT may be appropriate for stent assessment in only selected patients. PMID:20028909

MJO prediction skill of the subseasonal-to-seasonal (S2S) prediction models

NASA Astrophysics Data System (ADS)

Son, S. W.; Lim, Y.; Kim, D.

2017-12-01

The Madden-Julian Oscillation (MJO), the dominant mode of tropical intraseasonal variability, provides the primary source of tropical and extratropical predictability on subseasonal to seasonal timescales. To better understand its predictability, this study conducts quantitative evaluation of MJO prediction skill in the state-of-the-art operational models participating in the subseasonal-to-seasonal (S2S) prediction project. Based on bivariate correlation coefficient of 0.5, the S2S models exhibit MJO prediction skill ranging from 12 to 36 days. These prediction skills are affected by both the MJO amplitude and phase errors, the latter becoming more important with forecast lead times. Consistent with previous studies, the MJO events with stronger initial amplitude are typically better predicted. However, essentially no sensitivity to the initial MJO phase is observed. Overall MJO prediction skill and its inter-model spread are further related with the model mean biases in moisture fields and longwave cloud-radiation feedbacks. In most models, a dry bias quickly builds up in the deep tropics, especially across the Maritime Continent, weakening horizontal moisture gradient. This likely dampens the organization and propagation of MJO. Most S2S models also underestimate the longwave cloud-radiation feedbacks in the tropics, which may affect the maintenance of the MJO convective envelop. In general, the models with a smaller bias in horizontal moisture gradient and longwave cloud-radiation feedbacks show a higher MJO prediction skill, suggesting that improving those processes would enhance MJO prediction skill.

Investigation of the Sensitivity of Transmission Raman Spectroscopy for Polymorph Detection in Pharmaceutical Tablets.

PubMed

Feng, Hanzhou; Bondi, Robert W; Anderson, Carl A; Drennen, James K; Igne, Benoît

2017-08-01

Polymorph detection is critical for ensuring pharmaceutical product quality in drug substances exhibiting polymorphism. Conventional analytical techniques such as X-ray powder diffraction and solid-state nuclear magnetic resonance are utilized primarily for characterizing the presence and identity of specific polymorphs in a sample. These techniques have encountered challenges in analyzing the constitution of polymorphs in the presence of other components commonly found in pharmaceutical dosage forms. Laborious sample preparation procedures are usually required to achieve satisfactory data interpretability. There is a need for alternative techniques capable of probing pharmaceutical dosage forms rapidly and nondestructively, which is dictated by the practical requirements of applications such as quality monitoring on production lines or when quantifying product shelf lifetime. The sensitivity of transmission Raman spectroscopy for detecting polymorphs in final tablet cores was investigated in this work. Carbamazepine was chosen as a model drug, polymorph form III is the commercial form, whereas form I is an undesired polymorph that requires effective detection. The concentration of form I in a direct compression tablet formulation containing 20% w/w of carbamazepine, 74.00% w/w of fillers (mannitol and microcrystalline cellulose), and 6% w/w of croscarmellose sodium, silicon dioxide, and magnesium stearate was estimated using transmission Raman spectroscopy. Quantitative models were generated and optimized using multivariate regression and data preprocessing. Prediction uncertainty was estimated for each validation sample by accounting for all the main variables contributing to the prediction. Multivariate detection limits were calculated based on statistical hypothesis testing. The transmission Raman spectroscopic model had an absolute prediction error of 0.241% w/w for the independent validation set. The method detection limit was estimated at 1.31% w/w. The results demonstrated that transmission Raman spectroscopy is a sensitive tool for polymorphs detection in pharmaceutical tablets.

Identifying sensitive windows for prenatal particulate air pollution exposure and mitochondrial DNA content in cord blood.

PubMed

Rosa, Maria José; Just, Allan C; Guerra, Marco Sánchez; Kloog, Itai; Hsu, Hsiao-Hsien Leon; Brennan, Kasey J; García, Adriana Mercado; Coull, Brent; Wright, Rosalind J; Téllez Rojo, Martha María; Baccarelli, Andrea A; Wright, Robert O

2017-01-01

Changes in mitochondrial DNA (mtDNA) can serve as a marker of cumulative oxidative stress (OS) due to the mitochondria's unique genome and relative lack of repair systems. In utero particulate matter ≤2.5μm (PM 2.5 ) exposure can enhance oxidative stress. Our objective was to identify sensitive windows to predict mtDNA damage experienced in the prenatal period due to PM 2.5 exposure using mtDNA content measured in cord blood. Women affiliated with the Mexican social security system were recruited during pregnancy in the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) study. Mothers with cord blood collected at delivery and complete covariate data were included (n=456). Mothers' prenatal daily exposure to PM 2.5 was estimated using a satellite-based spatio-temporally resolved prediction model and place of residence during pregnancy. DNA was extracted from umbilical cord leukocytes. Quantitative real-time polymerase chain reaction (qPCR) was used to determine mtDNA content. A distributive lag regression model (DLM) incorporating weekly averages of daily PM 2.5 predictions was constructed to plot the association between exposure and OS over the length of pregnancy. In models that included child's sex, mother's age at delivery, prenatal environmental tobacco smoke exposure, birth year, maternal education, and assay batch, we found significant associations between higher PM 2.5 exposure during late pregnancy (35-40weeks) and lower mtDNA content in cord blood. Increased PM 2.5 during a specific prenatal window in the third trimester was associated with decreased mtDNA content suggesting heightened sensitivity to PM-induced OS during this life stage. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dynamic Pain Phenotypes are Associated with Spinal Cord Stimulation-Induced Reduction in Pain: A Repeated Measures Observational Pilot Study.

PubMed

Campbell, Claudia M; Buenaver, Luis F; Raja, Srinivasa N; Kiley, Kasey B; Swedberg, Lauren J; Wacnik, Paul W; Cohen, Steven P; Erdek, Michael A; Williams, Kayode A; Christo, Paul J

2015-07-01

Spinal cord stimulation (SCS) has become a widely used treatment option for a variety of pain conditions. Substantial variability exists in the degree of benefit obtained from SCS and patient selection is a topic of expanding interest and importance. However, few studies have examined the potential benefits of dynamic quantitative sensory testing (QST) to develop objective measures of SCS outcomes or as a predictive tool to help patient selection. Psychological characteristics have been shown to play an important role in shaping individual differences in the pain experience and may aid in predicting responses to SCS. Static laboratory pain-induction measures have also been examined in their capacity for predicting SCS outcomes. The current study evaluated clinical, psychological and laboratory pain measures at baseline, during trial SCS lead placement, as well as 1 month and 3 months following permanent SCS implantation in chronic pain patients who received SCS treatment. Several QST measures were conducted, with specific focus on examination of dynamic models (central sensitization and conditioned pain modulation [CPM]) and their association with pain outcomes 3 months post SCS implantation. Results suggest few changes in QST over time. However, central sensitization and CPM at baseline were significantly associated with clinical pain at 3 months following SCS implantation, controlling for psycho/behavioral factors and pain at baseline. Specifically, enhanced central sensitization and reduced CPM were associated with less self-reported pain 3 months following SCS implantation. These findings suggest a potentially important role for dynamic pain assessment in individuals undergoing SCS, and hint at potential mechanisms through which SCS may impart its benefit. Wiley Periodicals, Inc.

Quantitative self-assembly prediction yields targeted nanomedicines

NASA Astrophysics Data System (ADS)

Shamay, Yosi; Shah, Janki; Işık, Mehtap; Mizrachi, Aviram; Leibold, Josef; Tschaharganeh, Darjus F.; Roxbury, Daniel; Budhathoki-Uprety, Januka; Nawaly, Karla; Sugarman, James L.; Baut, Emily; Neiman, Michelle R.; Dacek, Megan; Ganesh, Kripa S.; Johnson, Darren C.; Sridharan, Ramya; Chu, Karen L.; Rajasekhar, Vinagolu K.; Lowe, Scott W.; Chodera, John D.; Heller, Daniel A.

2018-02-01

Development of targeted nanoparticle drug carriers often requires complex synthetic schemes involving both supramolecular self-assembly and chemical modification. These processes are generally difficult to predict, execute, and control. We describe herein a targeted drug delivery system that is accurately and quantitatively predicted to self-assemble into nanoparticles based on the molecular structures of precursor molecules, which are the drugs themselves. The drugs assemble with the aid of sulfated indocyanines into particles with ultrahigh drug loadings of up to 90%. We devised quantitative structure-nanoparticle assembly prediction (QSNAP) models to identify and validate electrotopological molecular descriptors as highly predictive indicators of nano-assembly and nanoparticle size. The resulting nanoparticles selectively targeted kinase inhibitors to caveolin-1-expressing human colon cancer and autochthonous liver cancer models to yield striking therapeutic effects while avoiding pERK inhibition in healthy skin. This finding enables the computational design of nanomedicines based on quantitative models for drug payload selection.

Diagnostic accuracy of uriSed automated urine microscopic sediment analyzer and dipstick parameters in predicting urine culture test results.

PubMed

Huysal, Kağan; Budak, Yasemin U; Karaca, Ayse Ulusoy; Aydos, Murat; Kahvecioğlu, Serdar; Bulut, Mehtap; Polat, Murat

2013-01-01

Urinary tract infection (UTI) is one of the most common types of infection. Currently, diagnosis is primarily based on microbiologic culture, which is time- and labor-consuming. The aim of this study was to assess the diagnostic accuracy of urinalysis results from UriSed (77 Electronica, Budapest, Hungary), an automated microscopic image-based sediment analyzer, in predicting positive urine cultures. We examined a total of 384 urine specimens from hospitalized patients and outpatients attending our hospital on the same day for urinalysis, dipstick tests and semi-quantitative urine culture. The urinalysis results were compared with those of conventional semiquantitative urine culture. Of 384 urinary specimens, 68 were positive for bacteriuria by culture, and were thus considered true positives. Comparison of these results with those obtained from the UriSed analyzer indicated that the analyzer had a specificity of 91.1%, a sensitivity of 47.0%, a positive predictive value (PPV) of 53.3% (95% confidence interval (CI) = 40.8-65.3), and a negative predictive value (NPV) of 88.8% (95% CI = 85.0-91.8%). The accuracy was 83.3% when the urine leukocyte parameter was used, 76.8% when bacteriuria analysis of urinary sediment was used, and 85.1% when the bacteriuria and leukocyturia parameters were combined. The presence of nitrite was the best indicator of culture positivity (99.3% specificity) but had a negative likelihood ratio of 0.7, indicating that it was not a reliable clinical test. Although the specificity of the UriSed analyzer was within acceptable limits, the sensitivity value was low. Thus, UriSed urinalysis resuIts do not accurately predict the outcome of culture.

An Extended Structure–Activity Relationship of Nondioxin-Like PCBs Evaluates and Supports Modeling Predictions and Identifies Picomolar Potency of PCB 202 Towards Ryanodine Receptors

PubMed Central

Feng, Wei; Zheng, Jing; Dong, Yao; Li, Xueshu; Lehmler, Hans-Joachim; Pessah, Isaac N.

2017-01-01

Nondioxin-like polychlorinated biphenyls (NDL PCBs) activate ryanodine-sensitive Ca2+ channels (RyRs) and this activation has been associated with neurotoxicity in exposed animals. RyR-active congeners follow a distinct structure–activity relationship and a quantitative structure–activity relationship (QSAR) predicts that a large number of PCBs likely activate the receptor, which requires validation. Additionally, previous structural based conclusions have been established using receptor ligand binding assays but the impact of varying PCB structures on ion channel gating behavior is not understood. We used [3H]Ryanodine ([3H]Ry) binding to assess the RyR-activity of 14 previously untested PCB congeners evaluating the predictability of the QSAR. Congeners determined to display widely varying potency were then assayed with single channel voltage clamp analysis to assess direct influences on channel gating kinetics. The RyR-activity of individual PCBs assessed in in vitro assays followed the general pattern predicted by the QSAR but binding and lipid bilayer experiments demonstrated higher potency than predicted. Of the 49 congeners tested to date, tetra-ortho PCB 202 was found to be the most potent RyR-active congener increasing channel open probability at 200 pM. Shifting meta-substitutions to the para-position resulted in a > 100-fold reduction in potency as seen with PCB 197. Non-ortho PCB 11 was found to lack activity at the receptor supporting a minimum mono-ortho substitution for PCB RyR activity. These findings expand and support previous SAR assessments; where out of the 49 congeners tested to date 42 activate the receptor demonstrating that the RyR is a sensitive and common target of PCBs. PMID:27655348

Diagnostic techniques in deflagration and detonation studies.

PubMed

Proud, William G; Williamson, David M; Field, John E; Walley, Stephen M

2015-12-01

Advances in experimental, high-speed techniques can be used to explore the processes occurring within energetic materials. This review describes techniques used to study a wide range of processes: hot-spot formation, ignition thresholds, deflagration, sensitivity and finally the detonation process. As this is a wide field the focus will be on small-scale experiments and quantitative studies. It is important that such studies are linked to predictive models, which inform the experimental design process. The stimuli range includes, thermal ignition, drop-weight, Hopkinson Bar and Plate Impact studies. Studies made with inert simulants are also included as these are important in differentiating between reactive response and purely mechanical behaviour.

Analysis of Particulate Contamination During Launch of MMS Mission

NASA Technical Reports Server (NTRS)

Brieda, Lubos; Barrie, Alexander; Hughes, David; Errigo, Therese

2010-01-01

NASA's Magnetospheric MultiScale (MMS) is an unmanned constellation of four identical spacecraft designed to investigate magnetic reconnection by obtaining detailed measurements of plasma properties in Earth's magnetopause and magnetotail. Each of the four identical satellites carries a suite of instruments which characterize the ambient ion and electron energy spectrum and composition. Some of these instruments utilize microchannel plates and are sensitive to particulate contamination. In this paper, we analyze the transport of particulates during pre-launch, launch and ascent events, and use the analysis to obtain quantitative predictions of contamination impact on the instruments. Viewfactor calculation is performed by considering the gravitational and aerodynamic forces acting on the particles.

Computer-oriented synthesis of wide-band non-uniform negative resistance amplifiers

NASA Technical Reports Server (NTRS)

Branner, G. R.; Chan, S.-P.

1975-01-01

This paper presents a synthesis procedure which provides design values for broad-band amplifiers using non-uniform negative resistance devices. Employing a weighted least squares optimization scheme, the technique, based on an extension of procedures for uniform negative resistance devices, is capable of providing designs for a variety of matching network topologies. It also provides, for the first time, quantitative results for predicting the effects of parameter element variations on overall amplifier performance. The technique is also unique in that it employs exact partial derivatives for optimization and sensitivity computation. In comparison with conventional procedures, significantly improved broad-band designs are shown to result.

Fracture modes in off-axis fiber composites

NASA Technical Reports Server (NTRS)

Sinclair, J. H.; Chamis, C. C.

1978-01-01

Criteria were developed for identifying, characterizing, and quantifying fracture modes in high-modulus graphite-fiber/resin unidirectional composites subjected to off-axis tensile loading. Procedures are described which use sensitivity analyses and off-axis data to determine the uniaxial strength of fiber composites. It was found that off-axis composites fail by three fracture modes which produce unique fracture surface characteristics. The stress that dominates each fracture mode and the load angle range of its dominance can be identified. Linear composite mechanics is adequate to describe quantitatively the mechanical behavior of off-axis composites. The uniaxial strengths predicted from off-axis data are comparable to these measured in uniaxial tests.

Sensitive and affordable diagnostic assay for the quantitative detection of anaplastic lymphoma kinase (ALK) alterations in patients with non-small cell lung cancer

PubMed Central

Dama, Elisa; Tillhon, Micol; Bertalot, Giovanni; de Santis, Francesca; Troglio, Flavia; Pessina, Simona; Passaro, Antonio; Pece, Salvatore; de Marinis, Filippo; Dell'Orto, Patrizia; Viale, Giuseppe; Spaggiari, Lorenzo; Di Fiore, Pier Paolo; Bianchi, Fabrizio; Barberis, Massimo; Vecchi, Manuela

2016-01-01

Accurate detection of altered anaplastic lymphoma kinase (ALK) expression is critical for the selection of lung cancer patients eligible for ALK-targeted therapies. To overcome intrinsic limitations and discrepancies of currently available companion diagnostics for ALK, we developed a simple, affordable and objective PCR-based predictive model for the quantitative measurement of any ALK fusion as well as wild-type ALK upregulation. This method, optimized for low-quantity/−quality RNA from FFPE samples, combines cDNA pre-amplification with ad hoc generated calibration curves. All the models we derived yielded concordant predictions when applied to a cohort of 51 lung tumors, and correctly identified all 17 ALK FISH-positive and 33 of the 34 ALK FISH-negative samples. The one discrepant case was confirmed as positive by IHC, thus raising the accuracy of our test to 100%. Importantly, our method was accurate when using low amounts of input RNA (10 ng), also in FFPE samples with limited tumor cellularity (5–10%) and in FFPE cytology specimens. Thus, our test is an easily implementable diagnostic tool for the rapid, efficacious and cost-effective screening of ALK status in patients with lung cancer. PMID:27206799

Discussion of skill improvement in marine ecosystem dynamic models based on parameter optimization and skill assessment

NASA Astrophysics Data System (ADS)

Shen, Chengcheng; Shi, Honghua; Liu, Yongzhi; Li, Fen; Ding, Dewen

2016-07-01

Marine ecosystem dynamic models (MEDMs) are important tools for the simulation and prediction of marine ecosystems. This article summarizes the methods and strategies used for the improvement and assessment of MEDM skill, and it attempts to establish a technical framework to inspire further ideas concerning MEDM skill improvement. The skill of MEDMs can be improved by parameter optimization (PO), which is an important step in model calibration. An efficient approach to solve the problem of PO constrained by MEDMs is the global treatment of both sensitivity analysis and PO. Model validation is an essential step following PO, which validates the efficiency of model calibration by analyzing and estimating the goodness-of-fit of the optimized model. Additionally, by focusing on the degree of impact of various factors on model skill, model uncertainty analysis can supply model users with a quantitative assessment of model confidence. Research on MEDMs is ongoing; however, improvement in model skill still lacks global treatments and its assessment is not integrated. Thus, the predictive performance of MEDMs is not strong and model uncertainties lack quantitative descriptions, limiting their application. Therefore, a large number of case studies concerning model skill should be performed to promote the development of a scientific and normative technical framework for the improvement of MEDM skill.

Meeting the Sustainable Development Goals leads to lower world population growth

PubMed Central

Abel, Guy J.; Barakat, Bilal; KC, Samir; Lutz, Wolfgang

2016-01-01

Here we show the extent to which the expected world population growth could be lowered by successfully implementing the recently agreed-upon Sustainable Development Goals (SDGs). The SDGs include specific quantitative targets on mortality, reproductive health, and education for all girls by 2030, measures that will directly and indirectly affect future demographic trends. Based on a multidimensional model of population dynamics that stratifies national populations by age, sex, and level of education with educational fertility and mortality differentials, we translate these goals into SDG population scenarios, resulting in population sizes between 8.2 and 8.7 billion in 2100. Because these results lie outside the 95% prediction range given by the 2015 United Nations probabilistic population projections, we complement the study with sensitivity analyses of these projections that suggest that those prediction intervals are too narrow because of uncertainty in baseline data, conservative assumptions on correlations, and the possibility of new policies influencing these trends. Although the analysis presented here rests on several assumptions about the implementation of the SDGs and the persistence of educational, fertility, and mortality differentials, it quantitatively illustrates the view that demography is not destiny and that policies can make a decisive difference. In particular, advances in female education and reproductive health can contribute greatly to reducing world population growth. PMID:27911797

Development of a quantitative NS1-capture enzyme-linked immunosorbent assay for early detection of yellow fever virus infection.

PubMed

Ricciardi-Jorge, Taissa; Bordignon, Juliano; Koishi, Andrea; Zanluca, Camila; Mosimann, Ana Luiza; Duarte Dos Santos, Claudia Nunes

2017-11-24

Yellow fever is an arboviral disease that causes thousands of deaths every year in Africa and the Americas. However, few commercial diagnostic kits are available. Non-structural protein 1 (NS1) is an early marker of several flavivirus infections and is widely used to diagnose dengue virus (DENV) infection. Nonetheless, little is known about the dynamics of Yellow fever virus (YFV) NS1 expression and secretion, to encourage its use in diagnosis. To tackle this issue, we developed a quantitative NS1-capture ELISA specific for YFV using a monoclonal antibody and recombinant NS1 protein. This test was used to quantify NS1 in mosquito and human cell line cultures infected with vaccine and wild YFV strains. Our results showed that NS1 was detectable in the culture supernatants of both cell lines; however, a higher concentration was maintained as cell-associated rather than secreted into the extracellular milieu. A panel of 73 human samples was used to demonstrate the suitability of YFV NS1 as a diagnostic tool, resulting in 80% sensitivity, 100% specificity, a 100% positive predictive value and a 95.5% negative predictive value compared with RT-PCR. Overall, the developed NS1-capture ELISA showed potential as a promising assay for the detection of early YF infection.

Meeting the Sustainable Development Goals leads to lower world population growth.

PubMed

Abel, Guy J; Barakat, Bilal; Kc, Samir; Lutz, Wolfgang

2016-12-13

Here we show the extent to which the expected world population growth could be lowered by successfully implementing the recently agreed-upon Sustainable Development Goals (SDGs). The SDGs include specific quantitative targets on mortality, reproductive health, and education for all girls by 2030, measures that will directly and indirectly affect future demographic trends. Based on a multidimensional model of population dynamics that stratifies national populations by age, sex, and level of education with educational fertility and mortality differentials, we translate these goals into SDG population scenarios, resulting in population sizes between 8.2 and 8.7 billion in 2100. Because these results lie outside the 95% prediction range given by the 2015 United Nations probabilistic population projections, we complement the study with sensitivity analyses of these projections that suggest that those prediction intervals are too narrow because of uncertainty in baseline data, conservative assumptions on correlations, and the possibility of new policies influencing these trends. Although the analysis presented here rests on several assumptions about the implementation of the SDGs and the persistence of educational, fertility, and mortality differentials, it quantitatively illustrates the view that demography is not destiny and that policies can make a decisive difference. In particular, advances in female education and reproductive health can contribute greatly to reducing world population growth.

Time-Resolved Fluorescent Immunochromatography of Aflatoxin B1 in Soybean Sauce: A Rapid and Sensitive Quantitative Analysis.

PubMed

Wang, Du; Zhang, Zhaowei; Li, Peiwu; Zhang, Qi; Zhang, Wen

2016-07-14

Rapid and quantitative sensing of aflatoxin B1 with high sensitivity and specificity has drawn increased attention of studies investigating soybean sauce. A sensitive and rapid quantitative immunochromatographic sensing method was developed for the detection of aflatoxin B1 based on time-resolved fluorescence. It combines the advantages of time-resolved fluorescent sensing and immunochromatography. The dynamic range of a competitive and portable immunoassay was 0.3-10.0 µg·kg(-1), with a limit of detection (LOD) of 0.1 µg·kg(-1) and recoveries of 87.2%-114.3%, within 10 min. The results showed good correlation (R² > 0.99) between time-resolved fluorescent immunochromatographic strip test and high performance liquid chromatography (HPLC). Soybean sauce samples analyzed using time-resolved fluorescent immunochromatographic strip test revealed that 64.2% of samples contained aflatoxin B1 at levels ranging from 0.31 to 12.5 µg·kg(-1). The strip test is a rapid, sensitive, quantitative, and cost-effective on-site screening technique in food safety analysis.

Critical factors determining the quantification capability of matrix-assisted laser desorption/ionization– time-of-flight mass spectrometry

PubMed Central

Wang, Chia-Chen; Lai, Yin-Hung; Ou, Yu-Meng; Chang, Huan-Tsung; Wang, Yi-Sheng

2016-01-01

Quantitative analysis with mass spectrometry (MS) is important but challenging. Matrix-assisted laser desorption/ionization (MALDI) coupled with time-of-flight (TOF) MS offers superior sensitivity, resolution and speed, but such techniques have numerous disadvantages that hinder quantitative analyses. This review summarizes essential obstacles to analyte quantification with MALDI-TOF MS, including the complex ionization mechanism of MALDI, sensitive characteristics of the applied electric fields and the mass-dependent detection efficiency of ion detectors. General quantitative ionization and desorption interpretations of ion production are described. Important instrument parameters and available methods of MALDI-TOF MS used for quantitative analysis are also reviewed. This article is part of the themed issue ‘Quantitative mass spectrometry’. PMID:27644968

Advanced 2-dimensional quantitative coronary angiographic analysis for prediction of fractional flow reserve in intermediate coronary stenoses.

PubMed

Opolski, Maksymilian P; Pregowski, Jerzy; Kruk, Mariusz; Kepka, Cezary; Staruch, Adam D; Witkowski, Adam

2014-07-01

The widespread clinical application of coronary computed tomography angiography (CCTA) has resulted in increased referral patterns of patients with intermediate coronary stenoses to invasive coronary angiography. We evaluated the application of advanced quantitative coronary angiography (A-QCA) for predicting fractional flow reserve (FFR) in intermediate coronary lesions detected on CCTA. Fifty-six patients with 66 single intermediate coronary lesions (≥ 50% to 80% stenosis) on CCTA prospectively underwent coronary angiography and FFR. A-QCA including calculation of the Poiseuille-based index defined as the ratio of lesion length to the fourth power of the minimal lumen diameter (MLD) was performed. Significant stenosis was defined as FFR ≤ 0.80. The mean FFR was 0.86 ± 0.09, and 18 lesions (27%) were functionally significant. FFR correlated with lesion length (R=-0.303, P=0.013), MLD (R=0.527, P<0.001), diameter stenosis (R=-0.404, P=0.001), minimum lumen area (MLA) (R=0.530, P<0.001), lumen stenosis (R=-0.400, P=0.001), and Poiseuille-based index (R=-0.602, P<0.001). The optimal cutoff values for MLD, MLA, diameter stenosis, and lumen stenosis were ≤ 1.3 mm, ≤ 1.5 mm, >44%, and >69%, respectively (maximum negative predictive value of 94% for MLA, maximum positive predictive value of 58% for diameter stenosis). The Poiseuille-based index was the most accurate (C statistic 0.86, sensitivity 100%, specificity 71%, positive predictive value 56%, and negative predictive value 100%) predictor of FFR ≤ 0.80, but showed the lowest interobserver agreement (intraclass correlation coefficient 0.37). A-QCA might be used to rule out significant ischemia in intermediate stenoses detected by CCTA. The diagnostic application of the Poiseuille-based angiographic index is precluded by its high interobserver variability.

Improved cancer risk stratification and diagnosis via quantitative phase microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Liu, Yang; Uttam, Shikhar; Pham, Hoa V.; Hartman, Douglas J.

2017-02-01

Pathology remains the gold standard for cancer diagnosis and in some cases prognosis, in which trained pathologists examine abnormality in tissue architecture and cell morphology characteristic of cancer cells with a bright-field microscope. The limited resolution of conventional microscope can result in intra-observer variation, missed early-stage cancers, and indeterminate cases that often result in unnecessary invasive procedures in the absence of cancer. Assessment of nanoscale structural characteristics via quantitative phase represents a promising strategy for identifying pre-cancerous or cancerous cells, due to its nanoscale sensitivity to optical path length, simple sample preparation (i.e., label-free) and low cost. I will present the development of quantitative phase microscopy system in transmission and reflection configuration to detect the structural changes in nuclear architecture, not be easily identifiable by conventional pathology. Specifically, we will present the use of transmission-mode quantitative phase imaging to improve diagnostic accuracy of urine cytology and the nuclear dry mass is progressively correlate with negative, atypical, suspicious and positive cytological diagnosis. In a second application, we will present the use of reflection-mode quantitative phase microscopy for depth-resolved nanoscale nuclear architecture mapping (nanoNAM) of clinically prepared formalin-fixed, paraffin-embedded tissue sections. We demonstrated that the quantitative phase microscopy system detects a gradual increase in the density alteration of nuclear architecture during malignant transformation in animal models of colon carcinogenesis and in human patients with ulcerative colitis, even in tissue that appears histologically normal according to pathologists. We evaluated the ability of nanoNAM to predict "future" cancer progression in patients with ulcerative colitis.

Designing novel nano-immunoassays: antibody orientation versus sensitivity

NASA Astrophysics Data System (ADS)

Puertas, S.; Moros, M.; Fernández-Pacheco, R.; Ibarra, M. R.; Grazú, V.; de la Fuente, J. M.

2010-12-01

There is a growing interest in the use of magnetic nanoparticles (MNPs) for their application in quantitative and highly sensitive biosensors. Their use as labels of biological recognition events and their detection by means of some magnetic method constitute a very promising strategy for quantitative high-sensitive lateral-flow assays. In this paper, we report the importance of nanoparticle functionalization for the improvement of sensitivity for a lateral-flow immunoassay. More precisely, we have found that immobilization of IgG anti-hCG through its polysaccharide moieties on MNPs allows more successful recognition of the hCG hormone. Although we have used the detection of hCG as a model in this work, the strategy of binding antibodies to MNPs through its sugar chains reported here is applicable to other antibodies. It has huge potential as it will be very useful for the development of quantitative and high-sensitive lateral-flow assays for its use on human and veterinary, medicine, food and beverage manufacturing, pharmaceutical, medical biologics and personal care product production, environmental remediation, etc.

Concomitant semi-quantitative and visual analysis improves the predictive value on treatment outcome of interim 18F-fluorodeoxyglucose / Positron Emission Tomography in advanced Hodgkin lymphoma.

PubMed

Biggi, Alberto; Bergesio, Fabrizio; Chauvie, Stephane; Bianchi, Andrea; Menga, Massimo; Fallanca, Federico; Hutchings, Martin; Gregianin, Michele; Meignan, Michel; Gallamini, Andrea

2017-07-27

Qualitative assessment using the Deauville five-point scale (DS) is the gold standard for interim and end-of treatment PET interpretation in lymphoma. In the present study we assessed the reliability and the prognostic value of different semi- quantitative (SQ) parameters in comparison with DS for interim PET (iPET) interpretation in Hodgkin lymphoma (HL). A cohort of 82 out of 260 patients with advanced stage HL enrolled in the International Validation Study (IVS), scored as 3 to 5 by the expert panel was included in the present report. Two nuclear medicine physicians blinded to patient history, clinical data and treatment outcome reviewed independently the iPET using the following parameters: DS, SUVMax, SUVPeak of the most active lesion, QMax (ratio of SUVMax of the lesion to liver SUVMax) and QRes (ratio of SUVPeak of the lesion to liver SUVMean). The optimal sensitivity, specificity, positive and negative predictive value to predict treatment outcome was calculated for all the above parameters with the Receiver Operator Characteristics analysis. The prognostic value of all parameters were similar, the best cut-off value being 4 for DS (Area Under the Curve, AUC, 0.81 CI95%: 0.72-0.90), 3.81 for SUVMax (AUC 0.82 CI95%: 0.73-0.91), 3.20 for SUVPeak (AUC 0.86 CI95%: 0.77-0.94), 1.07 for QMax (AUC 0.84 CI95%: 0.75-0.93) and 1.38 for QRes (AUC 0.84 CI95%: 0.75-0.93). The reproducibility of different parameters was similar as the inter-observer variability measured with Cohen's kappa were 0.93 (95% CI 0.84-1.01) for the DS, 0.88 (0.77-0.98) for SUVMax, 0.82 (0.70-0.95) for SUVPeak, 0.85 (0.74-0.97) for QRes and 0.78 (0.65-0.92) for QMax. Due to the high specificity of SUVPeak (0.87) and to the good sensitivity of DS (0.86), upon the use of both parameters the positive predictive value increased from 0.65 of the DS alone to 0.79. When both parameters were positive in iPET, 3-years Failure-Free Survival (FFS) was significantly lower compared to patients whose iPET was interpreted with qualitative parameters only (DS 4 or 5): 21% vs 35%. On the other hand, the FFS of patients with negative results was not significantly different (88% vs 86%). In this study we demonstrated that, combining semi-quantitative parameters with SUVPeak to a pure qualitative interpretation key with DS, it is possible to increase the positive predictive value of iPET and to identify with higher precision the patients subset with a very dismal prognosis. However, these retrospective findings should be confirmed prospectively in a larger patient cohort.

A new approach for rapid detection and typing of serum monoclonal components.

PubMed

Cacoub, P; Camproux, A C; Thiolières, J M; Assogba, U; Hausfater, P; Mallet, A; Foglietti, M J; Piette, J C; Bernard, M

2000-12-01

When used independently, none of the routine methods to explore serum monoclonal components (MC), including: serum protein electrophoresis (SPE), immunoelectrophoresis (IEP), kappa to lambda ratio (KLR) and immunofixation (IFE), provides a comprehensive quantitative and qualitative identification of the MC. In the past few years the concept of 'protein profile', based on immunonephelometric quantifications of serum proteins, has become widely used. It consists of a qualitative and quantitative graphic representation of numerous serum proteins including immunoglobulins. Aim of study was to develop a multidimensional model based exclusively on protein profiles labeled the protein profile prediction method (PPPM) to improve routine MC detection and typing. Serum samples from 127 hospitalized patients and 99 healthy blood donors were submitted to all of the following: SPE, IFE, KLR and a protein profile (which included IgM, IgA, IgG, kappa and lambda chain detections and quantification). The presence of a MC using IFE was chosen as the gold standard. Healthy donors and patients were randomly divided into two groups defined as testing and validation groups. A logistic model was designed based on the protein profiles of the testing group leading to the determination of a threshold value (called Z(r)) for MC detection. It was then tested to detect MC in the validation group. Using IFE, 73 MC were found in the 127 hospitalized patients. Using the threshold value for MC detection of Z(r)=1.86, the PPPM showed greater sensitivity (94.6%) in detecting a MC compared to either SPE (64.8%) or KLR (89.2%). This result was obtained without diminished specificity (80.8%). The association of SPE or KLR to PPPM did not significantly increase the sensitivity of the PPPM. In the validation group, for samples which had a high predictive probability of a MC using PPPM, the correct MC typing was identified in up to 77% of sera using PPPM only. These results may be interesting in helping to determine when supplementary IFE analysis is required to qualitatively analyze a MC. PPPM allows MC detection with great sensitivity. The immune protein profile dramatically increases the sensitivity of either SPE and/or KLR in detecting MC and may also allow heavy and light chain typing.

Quantitative Glycomics Strategies*

PubMed Central

Mechref, Yehia; Hu, Yunli; Desantos-Garcia, Janie L.; Hussein, Ahmed; Tang, Haixu

2013-01-01

The correlations between protein glycosylation and many biological processes and diseases are increasing the demand for quantitative glycomics strategies enabling sensitive monitoring of changes in the abundance and structure of glycans. This is currently attained through multiple strategies employing several analytical techniques such as capillary electrophoresis, liquid chromatography, and mass spectrometry. The detection and quantification of glycans often involve labeling with ionic and/or hydrophobic reagents. This step is needed in order to enhance detection in spectroscopic and mass spectrometric measurements. Recently, labeling with stable isotopic reagents has also been presented as a very viable strategy enabling relative quantitation. The different strategies available for reliable and sensitive quantitative glycomics are herein described and discussed. PMID:23325767

A Quantitative Study of Oxygen as a Metabolic Regulator

NASA Technical Reports Server (NTRS)

Radhakrishnan, Krishnan; LaManna, Joseph C.; Cabera, Marco E.

2000-01-01

An acute reduction in oxygen delivery to a tissue is associated with metabolic changes aimed at maintaining ATP homeostasis. However, given the complexity of the human bio-energetic system, it is difficult to determine quantitatively how cellular metabolic processes interact to maintain ATP homeostasis during stress (e.g., hypoxia, ischemia, and exercise). In particular, we are interested in determining mechanisms relating cellular oxygen concentration to observed metabolic responses at the cellular, tissue, organ, and whole body levels and in quantifying how changes in tissue oxygen availability affect the pathways of ATP synthesis and the metabolites that control these pathways. In this study; we extend a previously developed mathematical model of human bioenergetics, to provide a physicochemical framework that permits quantitative understanding of oxygen as a metabolic regulator. Specifically, the enhancement - sensitivity analysis - permits studying the effects of variations in tissue oxygenation and parameters controlling cellular respiration on glycolysis, lactate production, and pyruvate oxidation. The analysis can distinguish between parameters that must be determined accurately and those that require less precision, based on their effects on model predictions. This capability may prove to be important in optimizing experimental design, thus reducing use of animals.

Three-dimensional shear wave elastography for differentiation of breast lesions: An initial study with quantitative analysis using three orthogonal planes.

PubMed

Wang, Qiao

2018-05-25

To prospectively evaluate the diagnostic performance of three-dimensional (3D) shear wave elastography (SWE) for breast lesions with quantitative stiffness information from transverse, sagittal and coronal planes. Conventional ultrasound (US), two-dimensional (2D)-SWE and 3D-SWE were performed for 122 consecutive patients with 122 breast lesions before biopsy or surgical excision. Maximum elasticity values of Young's modulus (Emax) were recorded on 2D-SWE and three planes of 3D-SWE. Area under the receiver operating characteristic curve (AUC), sensitivity and specificity of US, 2D-SWE and 3D-SWE were evaluated. Two combined sets (i.e., BI-RADS and 2D-SWE; BI-RADS and 3D-SWE) were compared in AUC. Observer consistency was also evaluated. On 3D-SWE, the AUC and sensitivity of sagittal plane were significantly higher than those of transverse and coronal planes (both P < 0.05). Compared with BI-RADS alone, both combined sets had significantly (P < 0.05) higher AUCs and specificities, whereas, the two combined sets showed no significant difference in AUC (P > 0.05). However, the combined set of BI-RADS and sagittal plane of 3D-SWE had significantly higher sensitivity than the combined set of BI-RADS and 2D-SWE. The sagittal plane shows the best diagnostic performance among 3D-SWE. The combination of BI-RADS and 3D-SWE is a useful tool for predicting breast malignant lesions in comparison with BI-RADS alone.

Sequencing sit-to-stand and upright posture for mobility limitation assessment: determination of the timing of the task phases from force platform data.

PubMed

Mazzà, Claudia; Zok, Mounir; Della Croce, Ugo

2005-06-01

The identification of quantitative tools to assess an individual's mobility limitation is a complex and challenging task. Several motor tasks have been designated as potential indicators of mobility limitation. In this study, a multiple motor task obtained by sequencing sit-to-stand and upright posture was used. Algorithms based on data obtained exclusively from a single force platform were developed to detect the timing of the motor task phases (sit-to-stand, preparation to the upright posture and upright posture). To test these algorithms, an experimental protocol inducing predictable changes in the acquired signals was designed. Twenty-two young, able-bodied subjects performed the task in four different conditions: self-selected natural and high speed with feet kept together, and self-selected natural and high speed with feet pelvis-width apart. The proposed algorithms effectively detected the timing of the task phases, the duration of which was sensitive to the four different experimental conditions. As expected, the duration of the sit-to-stand was sensitive to the speed of the task and not to the foot position, while the duration of the preparation to the upright posture was sensitive to foot position but not to speed. In addition to providing a simple and effective description of the execution of the motor task, the correct timing of the studied multiple task could facilitate the accurate determination of variables descriptive of the single isolated phases, allowing for a more thorough description of the motor task and therefore could contribute to the development of effective quantitative functional evaluation tests.

Applying a simple water-energy balance framework to predict the climate sensitivity of streamflow over the continental United States

NASA Astrophysics Data System (ADS)

Renner, M.; Bernhofer, C.

2011-12-01

The prediction of climate effects on terrestrial ecosystems and water resources is one of the major research questions in hydrology. Conceptual water-energy balance models can be used to gain a first order estimate of how long-term average streamflow is changing with a change in water and energy supply. A common framework for investigation of this question is based on the Budyko hypothesis, which links hydrological response to aridity. Recently, Renner et al. (2011) introduced the CCUW hypothesis, which is based on the assumption that the total efficiency of the catchment ecosystem to use the available water and energy for actual evapotranspiration remains constant even under climate changes. Here, we confront the climate sensitivity approaches (including several versions of Budyko's approach and the CCUW) with data of more than 400 basins distributed over the continental United States. We first map an estimate of the sensitivity of streamflow to changes in precipitation using long-term average data of the period 1949-2003. This provides a hydro-climatic status of the respective basins as well as their expected proportional effect on changes in climate. Next, by splitting the data in two periods, we (i) analyse the long-term average changes in hydro-climatolgy, we (ii) use the different climate sensitivity methods to predict the change in streamflow given the observed changes in water and energy supply and (iii) we apply a quantitative approach to separate the impacts of changes in the long-term average climate from basin characteristics change on streamflow. This allows us to evaluate the observed changes in streamflow as well as to evaluate the impact of basin changes on the validity of climate sensitivity approaches. The apparent increase of streamflow in the majority of basins in the US is dominated by a climate trend towards increased humidity. It is further evident that impacts of changes in basin characteristics appear in parallel with climate changes. There are coherent spatial patterns with basins of increasing catchment efficiency being dominant in the western and central parts of the US. A hot spot of decreasing efficiency is found within the US Midwest. The impact of basin changes on the prediction is large and can be twice as the observed change signal. However, we find that both, the CCUW hypothesis and the approaches using the Budyko hypothesis, show minimal deviations between observed and predicted changes in streamflow for basins where a dominance of climatic changes and low influences of basin changes have been found. Thus, climate sensitivity methods can be regarded as valid tools if we expect climate changes only and neglect any direct anthropogenic influences.

Scaling behavior of columnar structure during physical vapor deposition

NASA Astrophysics Data System (ADS)

Meese, W. J.; Lu, T.-M.

2018-02-01

The statistical effects of different conditions in physical vapor deposition, such as sputter deposition, have on thin film morphology has long been the subject of interest. One notable effect is that of column development due to differential chamber pressure in the well-known empirical model called the Thornton's Structure Zone Model. The model is qualitative in nature and theoretical understanding with quantitative predictions of the morphology is still lacking due, in part, to the absence of a quantitative description of the incident flux distribution on the growth front. In this work, we propose an incident Gaussian flux model developed from a series of binary hard-sphere collisions and simulate its effects using Monte Carlo methods and a solid-on-solid growth scheme. We also propose an approximate cosine-power distribution for faster Monte Carlo sampling. With this model, it is observed that higher chamber pressures widen the average deposition angle, and similarly increase the growth of column diameters (or lateral correlation length) and the column-to-column separation (film surface wavelength). We treat both the column diameter and the surface wavelength as power laws. It is seen that both the column diameter exponent and the wavelength exponent are very sensitive to changes in pressure for low pressures (0.13 Pa to 0.80 Pa); meanwhile, both exponents saturate for higher pressures (0.80 Pa to 6.7 Pa) around a value of 0.6. These predictions will serve as guides to future experiments for quantitative description of the film morphology under a wide range of vapor pressure.

Detection of dysregulated protein-association networks by high-throughput proteomics predicts cancer vulnerabilities.

PubMed

Lapek, John D; Greninger, Patricia; Morris, Robert; Amzallag, Arnaud; Pruteanu-Malinici, Iulian; Benes, Cyril H; Haas, Wilhelm

2017-10-01

The formation of protein complexes and the co-regulation of the cellular concentrations of proteins are essential mechanisms for cellular signaling and for maintaining homeostasis. Here we use isobaric-labeling multiplexed proteomics to analyze protein co-regulation and show that this allows the identification of protein-protein associations with high accuracy. We apply this 'interactome mapping by high-throughput quantitative proteome analysis' (IMAHP) method to a panel of 41 breast cancer cell lines and show that deviations of the observed protein co-regulations in specific cell lines from the consensus network affects cellular fitness. Furthermore, these aberrant interactions serve as biomarkers that predict the drug sensitivity of cell lines in screens across 195 drugs. We expect that IMAHP can be broadly used to gain insight into how changing landscapes of protein-protein associations affect the phenotype of biological systems.

Aquatic effects assessment: needs and tools.

PubMed

Marchini, Silvia

2002-01-01

In the assessment of the adverse effects pollutants can produce on exposed ecosystems, different approaches can be followed depending on the quality and quantity of information available, whose advantages and limits are discussed with reference to the aquatic compartment. When experimental data are lacking, a predictive approach can be pursued by making use of validated quantitative structure-activity relationships (QSARs), which provide reliable ecotoxicity estimates only if appropriate models are applied. The experimental approach is central to any environmental hazard assessment procedure, although many uncertainties underlying the extrapolation from a limited set of single species laboratory data to the complexity of the ecosystem (e.g., the limitations of common summary statistics, the variability of species sensitivity, the need to consider alterations at higher level of integration) make the task difficult. When adequate toxicity information are available, the statistical extrapolation approach can be used to predict environmental compatible concentrations.

Experimental and Numerical Analysis of Microstructures and Stress States of Shot-Peened GH4169 Superalloys

NASA Astrophysics Data System (ADS)

Hu, Dianyin; Gao, Ye; Meng, Fanchao; Song, Jun; Wang, Rongqiao

2018-04-01

Combining experiments and finite element analysis (FEA), a systematic study was performed to analyze the microstructural evolution and stress states of shot-peened GH4169 superalloy over a variety of peening intensities and coverages. A dislocation density evolution model was integrated into the representative volume FEA model to quantitatively predict microstructural evolution in the surface layers and compared with experimental results. It was found that surface roughness and through-depth residual stress profile are more sensitive to shot-peening intensity compared to coverage due to the high kinetic energy involved. Moreover, a surface nanocrystallization layer was discovered in the top surface region of GH4169 for all shot-peening conditions. However, the grain refinement was more intensified under high shot-peening coverage, under which enough time was permitted for grain refinement. The grain size gradient predicted by the numerical framework showed good agreement with experimental observations.

WPC Quantitative Precipitation Forecasts - Day 1

Science.gov Websites

to all federal, state, and local government web resources and services. Quantitative Precipitation Prediction Center 5830 University Research Court College Park, Maryland 20740 Weather Prediction Center Web

Prediction of Scar Size in Rats Six Months after Burns Based on Early Post-injury Polarization-Sensitive Optical Frequency Domain Imaging

PubMed Central

Kravez, Eli; Villiger, Martin; Bouma, Brett; Yarmush, Martin; Yakhini, Zohar; Golberg, Alexander

2017-01-01

Hypertrophic scars remain a major clinical problem in the rehabilitation of burn survivors and lead to physical, aesthetic, functional, psychological, and social stresses. Prediction of healing outcome and scar formation is critical for deciding on the best treatment plan. Both subjective and objective scales have been devised to assess scar severity. Whereas scales of the first type preclude cross-comparison between observers, those of the second type are based on imaging modalities that either lack the ability to image individual layers of the scar or only provide very limited fields of view. To overcome these deficiencies, this work aimed at developing a predictive model of scar formation based on polarization sensitive optical frequency domain imaging (PS-OFDI), which offers comprehensive subsurface imaging. We report on a linear regression model that predicts the size of a scar 6 months after third-degree burn injuries in rats based on early post-injury PS-OFDI and measurements of scar area. When predicting the scar area at month 6 based on the homogeneity and the degree of polarization (DOP), which are signatures derived from the PS-OFDI signal, together with the scar area measured at months 2 and 3, we achieved predictions with a Pearson coefficient of 0.57 (p < 10−4) and a Spearman coefficient of 0.66 (p < 10−5), which were significant in comparison to prediction models trained on randomly shuffled data. As the model in this study was developed on the rat burn model, the methodology can be used in larger studies that are more relevant to humans; however, the actual model inferred herein is not translatable. Nevertheless, our analysis and modeling methodology can be extended to perform larger wound healing studies in different contexts. This study opens new possibilities for quantitative and objective assessment of scar severity that could help to determine the optimal course of therapy. PMID:29249978

SU-F-R-46: Predicting Distant Failure in Lung SBRT Using Multi-Objective Radiomics Model

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

Zhou, Z; Folkert, M; Iyengar, P

2016-06-15

Purpose: To predict distant failure in lung stereotactic body radiation therapy (SBRT) in early stage non-small cell lung cancer (NSCLC) by using a new multi-objective radiomics model. Methods: Currently, most available radiomics models use the overall accuracy as the objective function. However, due to data imbalance, a single object may not reflect the performance of a predictive model. Therefore, we developed a multi-objective radiomics model which considers both sensitivity and specificity as the objective functions simultaneously. The new model is used to predict distant failure in lung SBRT using 52 patients treated at our institute. Quantitative imaging features of PETmore » and CT as well as clinical parameters are utilized to build the predictive model. Image features include intensity features (9), textural features (12) and geometric features (8). Clinical parameters for each patient include demographic parameters (4), tumor characteristics (8), treatment faction schemes (4) and pretreatment medicines (6). The modelling procedure consists of two steps: extracting features from segmented tumors in PET and CT; and selecting features and training model parameters based on multi-objective. Support Vector Machine (SVM) is used as the predictive model, while a nondominated sorting-based multi-objective evolutionary computation algorithm II (NSGA-II) is used for solving the multi-objective optimization. Results: The accuracy for PET, clinical, CT, PET+clinical, PET+CT, CT+clinical, PET+CT+clinical are 71.15%, 84.62%, 84.62%, 85.54%, 82.69%, 84.62%, 86.54%, respectively. The sensitivities for the above seven combinations are 41.76%, 58.33%, 50.00%, 50.00%, 41.67%, 41.67%, 58.33%, while the specificities are 80.00%, 92.50%, 90.00%, 97.50%, 92.50%, 97.50%, 97.50%. Conclusion: A new multi-objective radiomics model for predicting distant failure in NSCLC treated with SBRT was developed. The experimental results show that the best performance can be obtained by combining all features.« less

Empirical Observations on the Sensitivity of Hot Cathode Ionization Type Vacuum Gages

NASA Technical Reports Server (NTRS)

Summers, R. L.

1969-01-01

A study of empirical methods of predicting tile relative sensitivities of hot cathode ionization gages is presented. Using previously published gage sensitivities, several rules for predicting relative sensitivity are tested. The relative sensitivity to different gases is shown to be invariant with gage type, in the linear range of gage operation. The total ionization cross section, molecular and molar polarizability, and refractive index are demonstrated to be useful parameters for predicting relative gage sensitivity. Using data from the literature, the probable error of predictions of relative gage sensitivity based on these molecular properties is found to be about 10 percent. A comprehensive table of predicted relative sensitivities, based on empirical methods, is presented.

Flow cytometric immunobead assay for quantitative detection of platelet autoantibodies in immune thrombocytopenia patients.

PubMed

Zhai, Juping; Ding, Mengyuan; Yang, Tianjie; Zuo, Bin; Weng, Zhen; Zhao, Yunxiao; He, Jun; Wu, Qingyu; Ruan, Changgeng; He, Yang

2017-10-23

Platelet autoantibody detection is critical for immune thrombocytopenia (ITP) diagnosis and prognosis. Therefore, we aimed to establish a quantitative flow cytometric immunobead assay (FCIA) for ITP platelet autoantibodies evaluation. Capture microbeads coupled with anti-GPIX, -GPIb, -GPIIb, -GPIIIa and P-selectin antibodies were used to bind the platelet-bound autoantibodies complex generated from plasma samples of 250 ITP patients, 163 non-ITP patients and 243 healthy controls, a fluorescein isothiocyanate (FITC)-conjugated secondary antibody was the detector reagent and mean fluorescence intensity (MFI) signals were recorded by flow cytometry. Intra- and inter-assay variations of the quantitative FCIA assay were assessed. Comparisons of the specificity, sensitivity and accuracy between quantitative and qualitative FCIA or monoclonal antibody immobilization of platelet antigen (MAIPA) assay were performed. Finally, treatment process was monitored by our quantitative FCIA in 8 newly diagnosed ITPs. The coefficient of variations (CV) of the quantitative FCIA assay were respectively 9.4, 3.8, 5.4, 5.1 and 5.8% for anti-GPIX, -GPIb, -GPIIIa, -GPIIb and -P-selectin autoantibodies. Elevated levels of autoantibodies against platelet glycoproteins GPIX, GPIb, GPIIIa, GPIIb and P-selectin were detected by our quantitative FCIA in ITP patients compared to non-ITP patients or healthy controls. The sensitivity, specificity and accuracy of our quantitative assay were respectively 73.13, 81.98 and 78.65% when combining all 5 autoantibodies, while the sensitivity, specificity and accuracy of MAIPA assay were respectively 41.46, 90.41 and 72.81%. A quantitative FCIA assay was established. Reduced levels of platelet autoantibodies could be confirmed by our quantitative FCIA in ITP patients after corticosteroid treatment. Our quantitative assay is not only good for ITP diagnosis but also for ITP treatment monitoring.

Pain Sensitization Associated with Non-Response Following Physiotherapy in People with Knee Osteoarthritis.

PubMed

O'Leary, Helen; Smart, Keith M; Moloney, Niamh A; Blake, Catherine; Doody, Catherine M

2018-05-22

In knee osteoarthritis (OA) pain sensitization has been linked to a more severe symptomatology, but the prognostic implications of pain sensitivity in people undergoing conservative treatment such as physiotherapy are not established. This study aimed to prospectively investigate the association between features of pain sensitization and clinical outcome (non-response) following guideline-based physiotherapy in people with knee OA. Participants (n=156) with moderate/severe knee OA were recruited from secondary care. All participants completed self-administered questionnaires and underwent quantitative sensory testing (QST) at baseline, thereby establishing subjective and objective measures of pain sensitization. Participants (n=134) were later classified following a physiotherapy intervention, using treatment responder criteria (responder/non-responder). QST data was reduced to a core set of latent variables using principal component analysis. A hierarchical logistic regression model was constructed to investigate if features related to pain sensitization predicted non-response after controlling for other known predictors of poor outcome in knee OA. Higher temporal summation (TS) (OR 2.00, 95% CI 1.23 to 3.27) and lower pressure pain thresholds (PPT) (OR 0.48, 95% CI 0.29 to 0.81) emerged as robust predictors of non-response following physiotherapy, along with a higher comorbidity score. The model demonstrated high sensitivity (87.8%) but modest specificity (52.3%). The independent relationship between pain sensitization and non-response may indicate an underlying explanatory association between neuroplastic changes in nociceptive processing and the maintenance of on-going pain and disability in knee OA pain. These preliminary results suggest interventions targeting pain sensitization may warrant future investigation in this population.

The Impact of Microphysics and Planetary Boundary Layer Physics on Model Simulation of U.S. Deep South Summer Convection

NASA Technical Reports Server (NTRS)

McCaul, Eugene W., Jr.; Case, Jonathan L.; Zavodsky, Bradley T.; Srikishen, Jayanthi; Medlin, Jeffrey M.; Wood, Lance

2014-01-01

Inspection of output from various configurations of high-resolution, explicit convection forecast models such as the Weather Research and Forecasting (WRF) model indicates significant sensitivity to the choices of model physics pararneterizations employed. Some of the largest apparent sensitivities are related to the specifications of the cloud microphysics and planetary boundary layer physics packages. In addition, these sensitivities appear to be especially pronounced for the weakly-sheared, multicell modes of deep convection characteristic of the Deep South of the United States during the boreal summer. Possible ocean-land sensitivities also argue for further examination of the impacts of using unique ocean-land surface initialization datasets provided by the NASA Short-term Prediction Research and Transition (SPoRn Center to select NOAAlNWS weather forecast offices. To obtain better quantitative understanding of these sensitivities and also to determine the utility of the ocean-land initialization data, we have executed matrices of regional WRF forecasts for selected convective events near Mobile, AL (MOB), and Houston, TX (HGX). The matrices consist of identically initialized WRF 24-h forecasts using any of eight microphysics choices and any of three planetary boWldary layer choices. The resulting 24 simulations performed for each event within either the MOB or HGX regions are then compared to identify the sensitivities of various convective storm metrics to the physics choices. Particular emphasis is placed on sensitivities of precipitation timing, intensity, and coverage, as well as amount and coverage oflightuing activity diagnosed from storm kinematics and graupel in the mixed phase layer. The results confirm impressions gleaned from study of the behavior of variously configured WRF runs contained in the ensembles produced each spring at the Center for the Analysis and Prediction of Storms, but with the benefit of more straightforward control of the physics package choices. The design of the experiments thus allows for more direct interpretation of the sensitivities to each possible physics combination. The results should assist forecasters in their efforts to anticipate and correct for possible biases in simulated WRF convection patterns, and help the modeling community refine their model parameterizations.

The Impacts of Microphysics and Planetary Boundary Layer Physics on Model Simulations of U. S. Deep South Summer Convection

NASA Technical Reports Server (NTRS)

McCaul, E. W., Jr.; Case, J. L.; Zavodsky, B. T.; Srikishen, J.; Medlin, J. M.; Wood, L.

2014-01-01

Inspection of output from various configurations of high-resolution, explicit convection forecast models such as the Weather Research and Forecasting (WRF) model indicates significant sensitivity to the choices of model physics parameterizations employed. Some of the largest apparent sensitivities are related to the specifications of the cloud microphysics and planetary boundary layer physics packages. In addition, these sensitivities appear to be especially pronounced for the weakly-sheared, multicell modes of deep convection characteristic of the Deep South of the United States during the boreal summer. Possible ocean-land sensitivities also argue for further examination of the impacts of using unique ocean-land surface initialization datasets provided by the NASA Short-term Prediction Research and Transition (SPoRT Center to select NOAA/NWS weather forecast offices. To obtain better quantitative understanding of these sensitivities and also to determine the utility of the ocean-land initialization data, we have executed matrices of regional WRF forecasts for selected convective events near Mobile, AL (MOB), and Houston, TX (HGX). The matrices consist of identically initialized WRF 24-h forecasts using any of eight microphysics choices and any of three planetary boundary layer choices. The resulting 24 simulations performed for each event within either the MOB or HGX regions are then compared to identify the sensitivities of various convective storm metrics to the physics choices. Particular emphasis is placed on sensitivities of precipitation timing, intensity, and coverage, as well as amount and coverage of lightning activity diagnosed from storm kinematics and graupel in the mixed phase layer. The results confirm impressions gleaned from study of the behavior of variously configured WRF runs contained in the ensembles produced each spring at the Center for the Analysis and Prediction of Storms, but with the benefit of more straightforward control of the physics package choices. The design of the experiments thus allows for more direct interpretation of the sensitivities to each possible physics combination. The results should assist forecasters in their efforts to anticipate and correct for possible biases in simulated WRF convection patterns, and help the modeling community refine their model parameterizations.

Quantitative intact specimen magnetic resonance microscopy at 3.0 T.

PubMed

Bath, Kevin G; Voss, Henning U; Jing, Deqiang; Anderson, Stewart; Hempstead, Barbara; Lee, Francis S; Dyke, Jonathan P; Ballon, Douglas J

2009-06-01

In this report, we discuss the application of a methodology for high-contrast, high-resolution magnetic resonance microscopy (MRM) of murine tissue using a 3.0-T imaging system. We employed a threefold strategy that included customized specimen preparation to maximize image contrast, three-dimensional data acquisition to minimize scan time and custom radiofrequency resonator design to maximize signal sensitivity. Images had a resolution of 100 x 78 x 78 microm(3) with a signal-to-noise ratio per voxel greater than 25:1 and excellent contrast-to-noise ratios over a 30-min acquisition. We quantitatively validated the methods through comparisons of neuroanatomy across two lines of genetically engineered mice. Specifically, we were able to detect volumetric differences of as little as 9% between genetically engineered mouse strains in multiple brain regions that were predictive of underlying impairments in brain development. The overall methodology was straightforward to implement and provides ready access to basic MRM at field strengths that are widely available in both the laboratory and the clinic.

Surface temperature/heat transfer measurement using a quantitative phosphor thermography system

NASA Technical Reports Server (NTRS)

Buck, G. M.

1991-01-01

A relative-intensity phosphor thermography technique developed for surface heating studies in hypersonic wind tunnels is described. A direct relationship between relative emission intensity and phosphor temperature is used for quantitative surface temperature measurements in time. The technique provides global surface temperature-time histories using a 3-CCD (Charge Coupled Device) video camera and digital recording system. A current history of technique development at Langley is discussed. Latest developments include a phosphor mixture for a greater range of temperature sensitivity and use of castable ceramics for inexpensive test models. A method of calculating surface heat-transfer from thermal image data in blowdown wind tunnels is included in an appendix, with an analysis of material thermal heat-transfer properties. Results from tests in the Langley 31-Inch Mach 10 Tunnel are presented for a ceramic orbiter configuration and a four-inch diameter hemisphere model. Data include windward heating for bow-shock/wing-shock interactions on the orbiter wing surface, and a comparison with prediction for hemisphere heating distribution.

Dynamic absorption coefficients of chemically amplified resists and nonchemically amplified resists at extreme ultraviolet

NASA Astrophysics Data System (ADS)

Fallica, Roberto; Stowers, Jason K.; Grenville, Andrew; Frommhold, Andreas; Robinson, Alex P. G.; Ekinci, Yasin

2016-07-01

The dynamic absorption coefficients of several chemically amplified resists (CAR) and non-CAR extreme ultraviolet (EUV) photoresists are measured experimentally using a specifically developed setup in transmission mode at the x-ray interference lithography beamline of the Swiss Light Source. The absorption coefficient α and the Dill parameters ABC were measured with unprecedented accuracy. In general, the α of resists match very closely with the theoretical value calculated from elemental densities and absorption coefficients, whereas exceptions are observed. In addition, through the direct measurements of the absorption coefficients and dose-to-clear values, we introduce a new figure of merit called chemical sensitivity to account for all the postabsorption chemical reaction ongoing in the resist, which also predicts a quantitative clearing volume and clearing radius, due to the photon absorption in the resist. These parameters may help provide deeper insight into the underlying mechanisms of the EUV concepts of clearing volume and clearing radius, which are then defined and quantitatively calculated.

Assessment of the U937 cell line for the detection of contact allergens

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

Python, Francois; Goebel, Carsten; Aeby, Pierre

2007-04-15

The human myeloid cell line U937 was evaluated as an in vitro test system to identify contact sensitizers in order to develop alternatives to animal tests for the cosmetic industry. Specific culture conditions (i.e., presence of interleukin-4, IL-4) were applied to obtain a dendritic cell-like phenotype. In the described test protocol, these cells were exposed to test chemicals and then analyzed by flow cytometry for CD86 expression and by quantitative real-time reverse transcriptase-polymerase chain reaction for IL-1{beta} and IL-8 gene expressions. Eight sensitizers, three non-sensitizers and five oxidative hair dye precursors were examined after 24-, 48- and 72-h exposure times.more » Test item-specific modulations of the chosen activation markers (CD86, IL-1{beta} and IL-8) suggest that this U937 activation test could discriminate test items classified as contact sensitizers or non-sensitizers in the local lymph node assay in mice (LLNA). More specifically, a test item can be considered as a potential sensitizer when it significantly induced the upregulation of the expression of at least two markers. Using this approach, we could correctly evaluate the dendritic cell (DC) activation potential for 15 out of 16 tested chemicals. We conclude that the U937 activation test may represent an useful tool in a future in vitro test battery for predicting sensitizing properties of chemicals.« less

The use of hippocampal volumetric measurements to improve diagnostic accuracy in pediatric patients with mesial temporal sclerosis.

PubMed

Guzmán Pérez-Carrillo, Gloria J; Owen, Christopher; Schwetye, Katherine E; McFarlane, Spencer; Vellimana, Ananth K; Mar, Soe; Miller-Thomas, Michelle M; Shimony, Joshua S; Smyth, Matthew D; Benzinger, Tammie L S

2017-06-01

OBJECTIVE Many patients with medically intractable epilepsy have mesial temporal sclerosis (MTS), which significantly affects their quality of life. The surgical excision of MTS lesions can result in marked improvement or even complete resolution of the epileptic episodes. Reliable radiological diagnosis of MTS is a clinical challenge. The purpose of this study was to evaluate the utility of volumetric mapping of the hippocampi for the identification of MTS in a case-controlled series of pediatric patients who underwent resection for medically refractory epilepsy, using pathology as a gold standard. METHODS A cohort of 57 pediatric patients who underwent resection for medically intractable epilepsy between 2005 and 2015 was evaluated. On pathological investigation, this group included 24 patients with MTS and 33 patients with non-MTS findings. Retrospective quantitative volumetric measurements of the hippocampi were acquired for 37 of these 57 patients. Two neuroradiologists with more than 10 years of experience who were blinded to the patients' MTS status performed the retrospective review of MR images. To produce the volumetric data, MR scans were parcellated and segmented using the FreeSurfer software suite. Hippocampal regions of interest were compared against an age-weighted local regression curve generated with data from the pediatric normal cohort. Standard deviations and percentiles of specific subjects were calculated. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were determined for the original clinical read and the expert readers. Receiver operating characteristic curves were generated for the methods of classification to compare results from the readers with the authors' results, and an optimal threshold was determined. From that threshold the sensitivity, specificity, PPV, and NPV were calculated for the volumetric analysis. RESULTS With the use of quantitative volumetry, a sensitivity of 72%, a specificity of 95%, a PPV of 93%, an NPV of 78%, and an area under the curve of 0.84 were obtained using a percentage difference of normalized hippocampal volume. The resulting specificity (95%) and PPV (93%) are superior to the original clinical read and to Reader A and Reader B's findings (range for specificity 74%-86% and for PPV 64%-71%). The sensitivity (72%) and NPV (78%) are comparable to Reader A's findings (73% and 81%, respectively) and are better than those of the original clinical read and of Reader B (sensitivity 45% and 63% and NPV 71% and 70%, respectively). CONCLUSIONS Volumetric measurement of the hippocampi outperforms expert readers in specificity and PPV, and it demonstrates comparable to superior sensitivity and NPV. Volumetric measurements can complement anatomical imaging for the identification of MTS, much like a computer-aided detection tool would. The implementation of this approach in the daily clinical workflow could significantly improve diagnostic accuracy.

Measuring changes in transmission of neglected tropical diseases, malaria, and enteric pathogens from quantitative antibody levels.

PubMed

Arnold, Benjamin F; van der Laan, Mark J; Hubbard, Alan E; Steel, Cathy; Kubofcik, Joseph; Hamlin, Katy L; Moss, Delynn M; Nutman, Thomas B; Priest, Jeffrey W; Lammie, Patrick J

2017-05-01

Serological antibody levels are a sensitive marker of pathogen exposure, and advances in multiplex assays have created enormous potential for large-scale, integrated infectious disease surveillance. Most methods to analyze antibody measurements reduce quantitative antibody levels to seropositive and seronegative groups, but this can be difficult for many pathogens and may provide lower resolution information than quantitative levels. Analysis methods have predominantly maintained a single disease focus, yet integrated surveillance platforms would benefit from methodologies that work across diverse pathogens included in multiplex assays. We developed an approach to measure changes in transmission from quantitative antibody levels that can be applied to diverse pathogens of global importance. We compared age-dependent immunoglobulin G curves in repeated cross-sectional surveys between populations with differences in transmission for multiple pathogens, including: lymphatic filariasis (Wuchereria bancrofti) measured before and after mass drug administration on Mauke, Cook Islands, malaria (Plasmodium falciparum) before and after a combined insecticide and mass drug administration intervention in the Garki project, Nigeria, and enteric protozoans (Cryptosporidium parvum, Giardia intestinalis, Entamoeba histolytica), bacteria (enterotoxigenic Escherichia coli, Salmonella spp.), and viruses (norovirus groups I and II) in children living in Haiti and the USA. Age-dependent antibody curves fit with ensemble machine learning followed a characteristic shape across pathogens that aligned with predictions from basic mechanisms of humoral immunity. Differences in pathogen transmission led to shifts in fitted antibody curves that were remarkably consistent across pathogens, assays, and populations. Mean antibody levels correlated strongly with traditional measures of transmission intensity, such as the entomological inoculation rate for P. falciparum (Spearman's rho = 0.75). In both high- and low transmission settings, mean antibody curves revealed changes in population mean antibody levels that were masked by seroprevalence measures because changes took place above or below the seropositivity cutoff. Age-dependent antibody curves and summary means provided a robust and sensitive measure of changes in transmission, with greatest sensitivity among young children. The method generalizes to pathogens that can be measured in high-throughput, multiplex serological assays, and scales to surveillance activities that require high spatiotemporal resolution. Our results suggest quantitative antibody levels will be particularly useful to measure differences in exposure for pathogens that elicit a transient antibody response or for monitoring populations with very high- or very low transmission, when seroprevalence is less informative. The approach represents a new opportunity to conduct integrated serological surveillance for neglected tropical diseases, malaria, and other infectious diseases with well-defined antigen targets.

Measuring changes in transmission of neglected tropical diseases, malaria, and enteric pathogens from quantitative antibody levels

PubMed Central

van der Laan, Mark J.; Hubbard, Alan E.; Steel, Cathy; Kubofcik, Joseph; Hamlin, Katy L.; Moss, Delynn M.; Nutman, Thomas B.; Priest, Jeffrey W.; Lammie, Patrick J.

2017-01-01

Background Serological antibody levels are a sensitive marker of pathogen exposure, and advances in multiplex assays have created enormous potential for large-scale, integrated infectious disease surveillance. Most methods to analyze antibody measurements reduce quantitative antibody levels to seropositive and seronegative groups, but this can be difficult for many pathogens and may provide lower resolution information than quantitative levels. Analysis methods have predominantly maintained a single disease focus, yet integrated surveillance platforms would benefit from methodologies that work across diverse pathogens included in multiplex assays. Methods/Principal findings We developed an approach to measure changes in transmission from quantitative antibody levels that can be applied to diverse pathogens of global importance. We compared age-dependent immunoglobulin G curves in repeated cross-sectional surveys between populations with differences in transmission for multiple pathogens, including: lymphatic filariasis (Wuchereria bancrofti) measured before and after mass drug administration on Mauke, Cook Islands, malaria (Plasmodium falciparum) before and after a combined insecticide and mass drug administration intervention in the Garki project, Nigeria, and enteric protozoans (Cryptosporidium parvum, Giardia intestinalis, Entamoeba histolytica), bacteria (enterotoxigenic Escherichia coli, Salmonella spp.), and viruses (norovirus groups I and II) in children living in Haiti and the USA. Age-dependent antibody curves fit with ensemble machine learning followed a characteristic shape across pathogens that aligned with predictions from basic mechanisms of humoral immunity. Differences in pathogen transmission led to shifts in fitted antibody curves that were remarkably consistent across pathogens, assays, and populations. Mean antibody levels correlated strongly with traditional measures of transmission intensity, such as the entomological inoculation rate for P. falciparum (Spearman’s rho = 0.75). In both high- and low transmission settings, mean antibody curves revealed changes in population mean antibody levels that were masked by seroprevalence measures because changes took place above or below the seropositivity cutoff. Conclusions/Significance Age-dependent antibody curves and summary means provided a robust and sensitive measure of changes in transmission, with greatest sensitivity among young children. The method generalizes to pathogens that can be measured in high-throughput, multiplex serological assays, and scales to surveillance activities that require high spatiotemporal resolution. Our results suggest quantitative antibody levels will be particularly useful to measure differences in exposure for pathogens that elicit a transient antibody response or for monitoring populations with very high- or very low transmission, when seroprevalence is less informative. The approach represents a new opportunity to conduct integrated serological surveillance for neglected tropical diseases, malaria, and other infectious diseases with well-defined antigen targets. PMID:28542223

Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

PubMed

Davatzikos, Christos; Rathore, Saima; Bakas, Spyridon; Pati, Sarthak; Bergman, Mark; Kalarot, Ratheesh; Sridharan, Patmaa; Gastounioti, Aimilia; Jahani, Nariman; Cohen, Eric; Akbari, Hamed; Tunc, Birkan; Doshi, Jimit; Parker, Drew; Hsieh, Michael; Sotiras, Aristeidis; Li, Hongming; Ou, Yangming; Doot, Robert K; Bilello, Michel; Fan, Yong; Shinohara, Russell T; Yushkevich, Paul; Verma, Ragini; Kontos, Despina

2018-01-01

The growth of multiparametric imaging protocols has paved the way for quantitative imaging phenotypes that predict treatment response and clinical outcome, reflect underlying cancer molecular characteristics and spatiotemporal heterogeneity, and can guide personalized treatment planning. This growth has underlined the need for efficient quantitative analytics to derive high-dimensional imaging signatures of diagnostic and predictive value in this emerging era of integrated precision diagnostics. This paper presents cancer imaging phenomics toolkit (CaPTk), a new and dynamically growing software platform for analysis of radiographic images of cancer, currently focusing on brain, breast, and lung cancer. CaPTk leverages the value of quantitative imaging analytics along with machine learning to derive phenotypic imaging signatures, based on two-level functionality. First, image analysis algorithms are used to extract comprehensive panels of diverse and complementary features, such as multiparametric intensity histogram distributions, texture, shape, kinetics, connectomics, and spatial patterns. At the second level, these quantitative imaging signatures are fed into multivariate machine learning models to produce diagnostic, prognostic, and predictive biomarkers. Results from clinical studies in three areas are shown: (i) computational neuro-oncology of brain gliomas for precision diagnostics, prediction of outcome, and treatment planning; (ii) prediction of treatment response for breast and lung cancer, and (iii) risk assessment for breast cancer.

Quantitative measures of meniscus extrusion predict incident radiographic knee osteoarthritis--data from the Osteoarthritis Initiative.

PubMed

Emmanuel, K; Quinn, E; Niu, J; Guermazi, A; Roemer, F; Wirth, W; Eckstein, F; Felson, D

2016-02-01

To test the hypothesis that quantitative measures of meniscus extrusion predict incident radiographic knee osteoarthritis (KOA), prior to the advent of radiographic disease. 206 knees with incident radiographic KOA (Kellgren Lawrence Grade (KLG) 0 or 1 at baseline, developing KLG 2 or greater with a definite osteophyte and joint space narrowing (JSN) grade ≥1 by year 4) were matched to 232 control knees not developing incident KOA. Manual segmentation of the central five slices of the medial and lateral meniscus was performed on coronal 3T DESS MRI and quantitative meniscus position was determined. Cases and controls were compared using conditional logistic regression adjusting for age, sex, BMI, race and clinical site. Sensitivity analyses of early (year [Y] 1/2) and late (Y3/4) incidence was performed. Mean medial extrusion distance was significantly greater for incident compared to non-incident knees (1.56 mean ± 1.12 mm SD vs 1.29 ± 0.99 mm; +21%, P < 0.01), so was the percent extrusion area of the medial meniscus (25.8 ± 15.8% vs 22.0 ± 13.5%; +17%, P < 0.05). This finding was consistent for knees restricted to medial incidence. No significant differences were observed for the lateral meniscus in incident medial KOA, or for the tibial plateau coverage between incident and non-incident knees. Restricting the analysis to medial incident KOA at Y1/2 differences were attenuated, but reached significance for extrusion distance, whereas no significant differences were observed at incident KOA in Y3/4. Greater medial meniscus extrusion predicts incident radiographic KOA. Early onset KOA showed greater differences for meniscus position between incident and non-incident knees than late onset KOA. Copyright © 2015 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

A simulation of orientation dependent, global changes in camera sensitivity in ECT

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

Bieszk, J.A.; Hawman, E.G.; Malmin, R.E.

1984-01-01

ECT promises the abilities to: 1) observe radioisotope distributions in a patient without the summation of overlying activity to reduce contrast, and 2) measure quantitatively these distributions to further and more accurately assess organ function. Ideally, camera-based ECT systems should have a performance that is independent of camera orientation or gantry angle. This study is concerned with ECT quantitation errors that can arise from angle-dependent variations of camera sensitivity. Using simulated phantoms representative of heart and liver sections, the effects of sensitivity changes on reconstructed images were assessed both visually and quantitatively based on ROI sums. The sinogram for eachmore » test image was simulated with 128 linear digitization and 180 angular views. The global orientation-dependent sensitivity was modelled by applying an angular sensitivity dependence to the sinograms of the test images. Four sensitivity variations were studied. Amplitudes of 0% (as a reference), 5%, 10%, and 25% with a costheta dependence were studied as well as a cos2theta dependence with a 5% amplitude. Simulations were done with and without Poisson noise to: 1) determine trends in the quantitative effects as a function of the magnitude of the variation, and 2) to see how these effects are manifested in studies having statistics comparable to clinical cases. For the most realistic sensitivity variation (costheta, 5% ampl.), the ROIs chosen in the present work indicated changes of <0.5% in the noiseless case and <5% for the case with Poisson noise. The effects of statistics appear to dominate any effects due to global, sinusoidal, orientation-dependent sensitivity changes in the cases studied.« less

Challenges and perspectives in quantitative NMR.

PubMed

Giraudeau, Patrick

2017-01-01

This perspective article summarizes, from the author's point of view at the beginning of 2016, the major challenges and perspectives in the field of quantitative NMR. The key concepts in quantitative NMR are first summarized; then, the most recent evolutions in terms of resolution and sensitivity are discussed, as well as some potential future research directions in this field. A particular focus is made on methodologies capable of boosting the resolution and sensitivity of quantitative NMR, which could open application perspectives in fields where the sample complexity and the analyte concentrations are particularly challenging. These include multi-dimensional quantitative NMR and hyperpolarization techniques such as para-hydrogen-induced polarization or dynamic nuclear polarization. Because quantitative NMR cannot be dissociated from the key concepts of analytical chemistry, i.e. trueness and precision, the methodological developments are systematically described together with their level of analytical performance. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Quantitative metal magnetic memory reliability modeling for welded joints

NASA Astrophysics Data System (ADS)

Xing, Haiyan; Dang, Yongbin; Wang, Ben; Leng, Jiancheng

2016-03-01

Metal magnetic memory(MMM) testing has been widely used to detect welded joints. However, load levels, environmental magnetic field, and measurement noises make the MMM data dispersive and bring difficulty to quantitative evaluation. In order to promote the development of quantitative MMM reliability assessment, a new MMM model is presented for welded joints. Steel Q235 welded specimens are tested along the longitudinal and horizontal lines by TSC-2M-8 instrument in the tensile fatigue experiments. The X-ray testing is carried out synchronously to verify the MMM results. It is found that MMM testing can detect the hidden crack earlier than X-ray testing. Moreover, the MMM gradient vector sum K vs is sensitive to the damage degree, especially at early and hidden damage stages. Considering the dispersion of MMM data, the K vs statistical law is investigated, which shows that K vs obeys Gaussian distribution. So K vs is the suitable MMM parameter to establish reliability model of welded joints. At last, the original quantitative MMM reliability model is first presented based on the improved stress strength interference theory. It is shown that the reliability degree R gradually decreases with the decreasing of the residual life ratio T, and the maximal error between prediction reliability degree R 1 and verification reliability degree R 2 is 9.15%. This presented method provides a novel tool of reliability testing and evaluating in practical engineering for welded joints.

Molecular Modeling of Thermodynamic and Transport Properties for CO 2 and Aqueous Brines

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

Jiang, Hao; Economou, Ioannis G.; Panagiotopoulos, Athanassios Z.

Molecular simulation techniques using classical force-fields occupy the space between ab initio quantum mechanical methods and phenomenological correlations. In particular, Monte Carlo and molecular dynamics algorithms can be used to provide quantitative predictions of thermodynamic and transport properties of fluids relevant for geologic carbon sequestration at conditions for which experimental data are uncertain or not available. These methods can cover time and length scales far exceeding those of quantum chemical methods, while maintaining transferability and predictive power lacking from phenomenological correlations. The accuracy of predictions depends sensitively on the quality of the molecular models used. Many existing fixed-point-charge models formore » water and aqueous mixtures fail to represent accurately these fluid properties, especially when descriptions covering broad ranges of thermodynamic conditions are needed. Recent work on development of accurate models for water, CO 2, and dissolved salts, as well as their mixtures, is summarized in this Account. Polarizable models that can respond to the different dielectric environments in aqueous versus nonaqueous phases are necessary for predictions of properties over extended ranges of temperatures and pressures. Phase compositions and densities, activity coefficients of the dissolved salts, interfacial tensions, viscosities and diffusivities can be obtained in near-quantitative agreement to available experimental data, using relatively modest computational resources. In some cases, for example, for the composition of the CO 2-rich phase in coexistence with an aqueous phase, recent results from molecular simulations have helped discriminate among conflicting experimental data sets. The sensitivity of properties on the quality of the intermolecular interaction model varies significantly. Properties such as the phase compositions or electrolyte activity coefficients are much more sensitive than phase densities, viscosities, or component diffusivities. Strong confinement effects on physical properties in nanoscale media can also be directly obtained from molecular simulations. Future work on molecular modeling for CO 2 and aqueous brines is likely to be focused on more systematic generation of interaction models by utilizing quantum chemical as well as direct experimental measurements. New ion models need to be developed for use with the current generation of polarizable water models, including ion–ion interactions that will allow for accurate description of dense, mixed brines. Methods will need to be devised that go beyond the use of effective potentials for incorporation of quantum effects known to be important for water, and reactive force fields developed that can handle bond creation and breaking in systems with carbonate and silicate minerals. Lastly, another area of potential future work is the integration of molecular simulation methods in multiscale models for the chemical reactions leading to mineral dissolution and flow within the porous media in underground formations.« less

Molecular Modeling of Thermodynamic and Transport Properties for CO2 and Aqueous Brines.

PubMed

Jiang, Hao; Economou, Ioannis G; Panagiotopoulos, Athanassios Z

2017-04-18

Molecular simulation techniques using classical force-fields occupy the space between ab initio quantum mechanical methods and phenomenological correlations. In particular, Monte Carlo and molecular dynamics algorithms can be used to provide quantitative predictions of thermodynamic and transport properties of fluids relevant for geologic carbon sequestration at conditions for which experimental data are uncertain or not available. These methods can cover time and length scales far exceeding those of quantum chemical methods, while maintaining transferability and predictive power lacking from phenomenological correlations. The accuracy of predictions depends sensitively on the quality of the molecular models used. Many existing fixed-point-charge models for water and aqueous mixtures fail to represent accurately these fluid properties, especially when descriptions covering broad ranges of thermodynamic conditions are needed. Recent work on development of accurate models for water, CO 2 , and dissolved salts, as well as their mixtures, is summarized in this Account. Polarizable models that can respond to the different dielectric environments in aqueous versus nonaqueous phases are necessary for predictions of properties over extended ranges of temperatures and pressures. Phase compositions and densities, activity coefficients of the dissolved salts, interfacial tensions, viscosities and diffusivities can be obtained in near-quantitative agreement to available experimental data, using relatively modest computational resources. In some cases, for example, for the composition of the CO 2 -rich phase in coexistence with an aqueous phase, recent results from molecular simulations have helped discriminate among conflicting experimental data sets. The sensitivity of properties on the quality of the intermolecular interaction model varies significantly. Properties such as the phase compositions or electrolyte activity coefficients are much more sensitive than phase densities, viscosities, or component diffusivities. Strong confinement effects on physical properties in nanoscale media can also be directly obtained from molecular simulations. Future work on molecular modeling for CO 2 and aqueous brines is likely to be focused on more systematic generation of interaction models by utilizing quantum chemical as well as direct experimental measurements. New ion models need to be developed for use with the current generation of polarizable water models, including ion-ion interactions that will allow for accurate description of dense, mixed brines. Methods will need to be devised that go beyond the use of effective potentials for incorporation of quantum effects known to be important for water, and reactive force fields developed that can handle bond creation and breaking in systems with carbonate and silicate minerals. Another area of potential future work is the integration of molecular simulation methods in multiscale models for the chemical reactions leading to mineral dissolution and flow within the porous media in underground formations.

Molecular Modeling of Thermodynamic and Transport Properties for CO 2 and Aqueous Brines

DOE PAGES

Jiang, Hao; Economou, Ioannis G.; Panagiotopoulos, Athanassios Z.

2017-02-24

Molecular simulation techniques using classical force-fields occupy the space between ab initio quantum mechanical methods and phenomenological correlations. In particular, Monte Carlo and molecular dynamics algorithms can be used to provide quantitative predictions of thermodynamic and transport properties of fluids relevant for geologic carbon sequestration at conditions for which experimental data are uncertain or not available. These methods can cover time and length scales far exceeding those of quantum chemical methods, while maintaining transferability and predictive power lacking from phenomenological correlations. The accuracy of predictions depends sensitively on the quality of the molecular models used. Many existing fixed-point-charge models formore » water and aqueous mixtures fail to represent accurately these fluid properties, especially when descriptions covering broad ranges of thermodynamic conditions are needed. Recent work on development of accurate models for water, CO 2, and dissolved salts, as well as their mixtures, is summarized in this Account. Polarizable models that can respond to the different dielectric environments in aqueous versus nonaqueous phases are necessary for predictions of properties over extended ranges of temperatures and pressures. Phase compositions and densities, activity coefficients of the dissolved salts, interfacial tensions, viscosities and diffusivities can be obtained in near-quantitative agreement to available experimental data, using relatively modest computational resources. In some cases, for example, for the composition of the CO 2-rich phase in coexistence with an aqueous phase, recent results from molecular simulations have helped discriminate among conflicting experimental data sets. The sensitivity of properties on the quality of the intermolecular interaction model varies significantly. Properties such as the phase compositions or electrolyte activity coefficients are much more sensitive than phase densities, viscosities, or component diffusivities. Strong confinement effects on physical properties in nanoscale media can also be directly obtained from molecular simulations. Future work on molecular modeling for CO 2 and aqueous brines is likely to be focused on more systematic generation of interaction models by utilizing quantum chemical as well as direct experimental measurements. New ion models need to be developed for use with the current generation of polarizable water models, including ion–ion interactions that will allow for accurate description of dense, mixed brines. Methods will need to be devised that go beyond the use of effective potentials for incorporation of quantum effects known to be important for water, and reactive force fields developed that can handle bond creation and breaking in systems with carbonate and silicate minerals. Lastly, another area of potential future work is the integration of molecular simulation methods in multiscale models for the chemical reactions leading to mineral dissolution and flow within the porous media in underground formations.« less

Arterial spin labelling MRI for detecting pseudocapsule defects and predicting renal capsule invasion in renal cell carcinoma.

PubMed

Zhang, H; Wu, Y; Xue, W; Zuo, P; Oesingmann, N; Gan, Q; Huang, Z; Wu, M; Hu, F; Kuang, M; Song, B

2017-11-01

To evaluate prospectively the performance of combining morphological and arterial spin labelling (ASL) magnetic resonance imaging (MRI) for detecting pseudocapsule defects in renal cell carcinoma (RCC), and to predict renal capsule invasion confirmed histopathologically. Twenty consecutive patients with suspicious renal tumours underwent MRI. Renal ASL imaging was performed and renal blood flow was measured quantitatively. The diagnostic performance of T2-weighted images alone, and a combination of T2-weighted and ASL images for predicting renal capsule invasion were assessed. Twenty renal lesions were evaluated in 20 patients. All lesions were clear cell RCCs (ccRCCs) confirmed at post-surgical histopathology. Fifteen ccRCCs showed pseudocapsule defects on T2-weighted images, of which 12 cases showed existing blood flow in defect areas on perfusion images. To predict renal capsule invasion, the sensitivity, specificity, positive predictive value, and negative predictive value were 100%, 71.4%, 86.7%, 100%, respectively, for T2-weighted images alone, and 92.3%, 100%, 100%, 87.5%, respectively, for the combination of T2-weighted and ASL images. ASL images can reflect the perfusion of pseudocapsule defects and as such, the combination of T2-weighted and ASL images produces promising diagnostic accuracy for predicting renal capsule invasion. Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

The FAQUIRE Approach: FAst, QUantitative, hIghly Resolved and sEnsitivity Enhanced 1H, 13C Data.

PubMed

Farjon, Jonathan; Milande, Clément; Martineau, Estelle; Akoka, Serge; Giraudeau, Patrick

2018-02-06

The targeted analysis of metabolites in complex mixtures is a challenging issue. NMR is one of the major tools in this field, but there is a strong need for more sensitive, better-resolved, and faster quantitative methods. In this framework, we introduce the concept of FAst, QUantitative, hIghly Resolved and sEnsitivity enhanced (FAQUIRE) NMR to push forward the limits of metabolite NMR analysis. 2D 1 H, 13 C 2D quantitative maps are promising alternatives for enhancing the spectral resolution but are highly time-consuming because of (i) the intrinsic nature of 2D, (ii) the longer recycling times required for quantitative conditions, and (iii) the higher number of scans needed to reduce the level of detection/quantification to access low concentrated metabolites. To reach this aim, speeding up the recently developed QUantItative Perfected and pUre shifted HSQC (QUIPU HSQC) is an interesting attempt to develop the FAQUIRE concept. Thanks to the combination of spectral aliasing, nonuniform sampling, and variable repetition time, the acquisition time of 2D quantitative maps is reduced by a factor 6 to 9, while conserving a high spectral resolution thanks to a pure shift approach. The analytical potential of the new Quick QUIPU HSQC (Q QUIPU HSQC) is evaluated on a model metabolite sample, and its potential is shown on breast-cell extracts embedding metabolites at millimolar to submillimolar concentrations.

Monitoring dominant strictures in primary sclerosing cholangitis with brush cytology and FDG-PET.

PubMed

Sangfelt, Per; Sundin, Anders; Wanders, Alkwin; Rasmussen, Ib; Karlson, Britt-Marie; Bergquist, Annika; Rorsman, Fredrik

2014-12-01

Despite a high risk of cholangiocellular adenocarcinoma (CCA) it is unclear how surveillance of patients with primary sclerosing cholangitis (PSC) should be performed. We evaluated a follow-up algorithm of brush cytology and positron emission tomography/computed tomography with [(18)F] fluorodeoxyglucose ([(18)F]FDG-PET/CT), measured as maximum standardized uptake values, normalized to the liver background (SUVmax/liver) at 180 min, in PSC patients with dominant bile duct strictures. Brush cytology with high grade dysplasia (HGD) was detected in 12/70 patients (17%), yielding a diagnostic sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 56%, 89%, 75%, and 88%, respectively. Preemptive liver transplantations due to repeated HGD before manifest CCA were performed in six patients. Receiver operating characteristic (ROC) analysis of [(18)F]FDG uptake showed that a SUVmax/liver quotient of 3.3 was able to discriminate between CCA and non-malignant disease with a sensitivity, specificity, PPV and NPV for CCA of 89%, 92%, 62%, 98%, respectively. A SUVmax/liver >3.3 detected CCA in 8/9 patients whereas a quotient <2.4 excluded CCA. Combining brush cytology and quantitative [(18)F]FDG-PET/CT yielded a sensitivity for HGD and/or CCA of 100% and a specificity of 88%. Early detection of HGD before manifest CCA is feasible with repeated brush cytology and may allow for preemptive liver transplantation. [(18)F]FDG-PET/CT has a high sensitivity for manifest CCA and a negative scan indicates a non-malignant state of the disease. Brush cytology and [(18)F]FDG-PET/CT are complementary in monitoring and managing PSC patients with dominant strictures. Copyright © 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Electrophysiological characteristics and pharmacological sensitivity of two lines of human induced pluripotent stem cell derived cardiomyocytes coming from two different suppliers.

PubMed

Goineau, Sonia; Castagné, Vincent

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are increasingly used as preclinical tool for predicting drug-induced QT prolongation and arrhythmias. This study was conducted to assess the electrophysiological characteristics and the pharmacological sensitivity of two commercialized hiPSC-CMs. The baseline electrophysiological characteristics measured with a multi-electrode array (MEA) technology differ between Cor.4U and iCell 2 : higher beat rate (+32bpm) and shorter field potential duration (FPD, -201ms) for Cor.4U. The FPD lengthening after cisapride (100nM: +65% versus +18%), quinidine (10μM: +65% versus +31%), sotalol (30μM: +90% versus +47%) or flecainide (3μM: +76% versus +22%) application appeared earlier in iCell 2 as compared to Cor.4U. Arrhythmia occurrence also appeared earlier in iCell 2 as compared to Cor.4U for the 3 substances mentioned above. The FPD shortening recorded after verapamil or nifedipine application was similar in both hiPSC-CMs. In conclusion, Cor.4U and iCell 2 hiPSC-CMs are both sensitive enough to detect drug-induced delayed or shortened repolarization and arrhythmia and can provide useful predictive cardiac electrophysiology data. Arrhythmias occurred at concentrations higher than clinical free maximum plasma concentrations with an overestimation of the risk with cisapride. However, quantitative differences of baseline electrophysiological characteristics or pharmacological sensitivity of both cell types have to be considered with caution during the interpretation of data. The new chemical entities included within a given drug development program should be evaluated in hiPSC-CMs coming from a single supplier. Copyright © 2017 Elsevier Inc. All rights reserved.

Predicting gestational diabetes mellitus during the first trimester using anthropometric measurements and HOMA-IR.

PubMed

Alptekin, Hüsnü; Çizmecioğlu, Ahmet; Işık, Hatice; Cengiz, Türkan; Yildiz, Murat; Iyisoy, Mehmet Sinan

2016-05-01

To determine the predictability of gestational diabetes mellitus (GDM) during the first trimester using the degree of insulin resistance and anthropometric measurements and to assign the risk of developing GDM by weight gained during pregnancy (WGDP). A total of 250 singleton pregnancies at 7-12 gestational weeks were studied. Body mass index (BMI), waist/hip ratio (WHR), quantitative insulin sensitivity check index (QUICKI), homeostasis model assessment-insulin resistance (HOMA-IR) scores and WGDP were determined. The backward stepwise method was applied to estimate possible associations with GDM. Cutoff points were estimated using receiver operating characteristic curve analysis. GDM was found in 20 of 227 singleton pregnancies (8.8 %). The calculated HOMA-IR, QUICKI, BMI, WHR, WGDP, and parity were significantly associated with GDM. Logistic regression analyses showed that three covariates (HOMA-IR, BMI, WGDP) remained independently associated with GDM. It was calculated as OR 1.254 (95 % CI 1.006-1.563), AUC 0.809, sensitivity 90 %, specificity 61 % with cutoff = 2.08 for HOMA-IR; OR 1.157 (CI 1.045-1.281), AUC 0.723, sensitivity 80 %, specificity 58 % with cutoff = 25.95 for BMI; OR 1.221, (CI 1.085-1.374), AUC 0.654, sensitivity 80 %, specificity 46 % with cutoff = 4.7 for WGDP. Despite a HOMA-IR score of >3.1 in pregnant women, GDM was detected in only three of 29 patients (10.3 %) if WGDP was <4.7 kg at weeks 24-28. First trimester screening for GDM can be achieved based on maternal anthropometric measurements and HOMA-IR. In particular, if BMI is >25.95 kg/m(2) and the HOMA-IR score >2.08, controlling weight gain may protect against GDM.

MiR-129-5p Sensitizes the Response of Her-2 Positive Breast Cancer to Trastuzumab by Reducing Rps6.

PubMed

Lu, Xiangdong; Ma, Jingjing; Chu, Jiahui; Shao, Qing; Zhang, Yao; Lu, Guangping; Li, Jun; Huang, Xiang; Li, Wei; Li, Yongfei; Ling, Yang; Zhao, Tao

2017-01-01

Trastuzumab is an important treatment used for patients with Her-2-positive breast cancer, but an increasing incidence of trastuzumab resistance has been observed clinically during the past decade. Aberrant microRNA (miR) expression levels are correlated with prognosis and response to trastuzumab in breast cancer. MiR-129-5p is downregulated in trastuzumab-resistant human breast cancer cells (JIMT-1), but its potential function and underlying mechanism remain unclear. Quantitative RT-PCR (qRT-PCR) was used to determine the expression levels of miR-129-5p and its potential target genes. The effects of miR-129-5p on cell responses to trastuzumab were analyzed by CCK-8 and flow cytometry assays in Her-2-positive breast cancer cells (SKBR-3 and JIMT-1). Bio-informatics analyses were performed to predict target genes of miR-129-5p, and luciferase assays were carried out to confirm the binding of miR-129-5p and rpS6. MiR-129-5p, which was downregulated and predicted to target rpS6 in trastuzumab-resistant breast cancer cells, enhanced the sensitivity of breast cancer cells to trastuzumab by reducing the expression of rpS6. Moreover, the overexpression of rpS6 reversed the sensitivity of cells to trastuzumab induced by miR-129-5p. MiR-129-5p sensitized Her-2-positive breast cancer to trastuzumab by downregulating rpS6. These findings provide novel insights into the common role of rpS6 and its related molecular mechanisms in mediating trastuzumab-resistance in Her-2-positive breast cancers. © 2017 The Author(s). Published by S. Karger AG, Basel.

[Clinical benefit of HCV core antigen assay in patients receiving interferon and ribavirin combination therapy].

PubMed

Higashimoto, Makiko; Takahashi, Masahiko; Jokyu, Ritsuko; Saito, Hidetsugu

2006-02-01

A highly sensitive second generation HCV core antigen assay has recently been developed. We compared viral disappearance and kinetics data between commercially available core antigen assays, Lumipulse Ortho HCV Ag, and a quantitative HCV RNA PCR assay, Cobas Amplicor HCV Monitor Test, Version 2 to estimate the predictive benefit of sustained viral response (SVR) and non-SVR in 59 patients treated with interferon and ribavirin combination therapy. We found a good correlation between HCV core Ag and HCV RNA level regardless of genotype. Although the sensitivity of the core antigen assay was lower than PCR, the dynamic range was broader than that of the PCR assay, so that we did not need to dilute the samples in 59 patients. We detected serial decline of core Ag levels in 24 hrs, 7 days and 14 days after interferon combination therapy. The decline of core antigen levels was significant in SVR patients compared to non-SVR as well as in genotype 2a, 2b patients compared to 1b. Core antigen-negative on day 1 could predict all 10 SVR patients (PPV = 100%), whereas RNA-negative could predict 22 SVR out of 25 on day 14 (PPV = 88.0%). None of the patients who had detectable serum core antigen on day 14 became SVR(NPV = 100%), although NPV was 91.2% on RNA negativity. An easy, simple, low cost new HCV core antigen detecting system seems to be useful for assessing and monitoring IFN treatment for HCV.

Sensitive determination of dopamine levels via surface-enhanced Raman scattering of Ag nanoparticle dimers.

PubMed

Yu, Xiantong; He, XiaoXiao; Yang, Taiqun; Zhao, Litao; Chen, Qichen; Zhang, Sanjun; Chen, Jinquan; Xu, Jianhua

2018-01-01

Dopamine (DA) is an important neurotransmitter in the hypothalamus and pituitary gland, which can produce a direct influence on mammals' emotions in midbrain. Additionally, the level of DA is highly related with some important neurologic diseases such as schizophrenia, Parkinson, and Huntington's diseases, etc. In light of the important roles that DA plays in the disease modulation, it is of considerable significance to develop a sensitive and reproducible approach for monitoring DA. The objective of this study was to develop an efficient approach to quantitatively monitor the level of DA using Ag nanoparticle (NP) dimers and enhanced Raman spectroscopy. Ag NP dimers were synthesized for the sensitive detection of DA via surface-enhanced Raman scattering (SERS). Citrate was used as both the capping agent of NPs and sensing agent to DA, which is self-assembled on the surface of Ag NP dimers by reacting with the surface carboxyl group to form a stable amide bond. To improve accuracy and precision, the multiplicative effects model for surface-enhanced Raman spectroscopy was utilized to analyze the SERS assays. A low limits of detection (LOD) of 20 pM and a wide linear response range from 30 pM to 300 nM were obtained for DA quantitative detection. The SERS enhancement factor was theoretically valued at approximately 10 7 by discrete dipole approximation. DA was self-assembled on the citrate capped surface of Ag NPs dimers through the amide bond. The adsorption energy was estimated to be 256 KJ/mol using the Langmuir isotherm model. The density functional theory was used to simulate the spectral characteristics of SERS during the adsorption of DA on the surface of the Ag dimers. Furthermore, to improve the accuracy and precision of quantitative analysis of SERS assays with a multiplicative effects model for surface-enhanced Raman spectroscopy. A LOD of 20 pM DA-level was obtained, and the linear response ranged from 30 pM to 300 nM for quantitative DA detection. The absolute relative percentage error was 4.22% between the real and predicted DA concentrations. This detection scheme is expected to have good applications in the prevention and diagnosis of certain diseases caused by disorders in the DA level.

Sensitive determination of dopamine levels via surface-enhanced Raman scattering of Ag nanoparticle dimers

PubMed Central

Yu, Xiantong; He, XiaoXiao; Yang, Taiqun; Zhao, Litao; Chen, Qichen; Zhang, Sanjun; Chen, Jinquan; Xu, Jianhua

2018-01-01

Background Dopamine (DA) is an important neurotransmitter in the hypothalamus and pituitary gland, which can produce a direct influence on mammals’ emotions in midbrain. Additionally, the level of DA is highly related with some important neurologic diseases such as schizophrenia, Parkinson, and Huntington’s diseases, etc. In light of the important roles that DA plays in the disease modulation, it is of considerable significance to develop a sensitive and reproducible approach for monitoring DA. Purpose The objective of this study was to develop an efficient approach to quantitatively monitor the level of DA using Ag nanoparticle (NP) dimers and enhanced Raman spectroscopy. Methods Ag NP dimers were synthesized for the sensitive detection of DA via surface-enhanced Raman scattering (SERS). Citrate was used as both the capping agent of NPs and sensing agent to DA, which is self-assembled on the surface of Ag NP dimers by reacting with the surface carboxyl group to form a stable amide bond. To improve accuracy and precision, the multiplicative effects model for surface-enhanced Raman spectroscopy was utilized to analyze the SERS assays. Results A low limits of detection (LOD) of 20 pM and a wide linear response range from 30 pM to 300 nM were obtained for DA quantitative detection. The SERS enhancement factor was theoretically valued at approximately 107 by discrete dipole approximation. DA was self-assembled on the citrate capped surface of Ag NPs dimers through the amide bond. The adsorption energy was estimated to be 256 KJ/mol using the Langmuir isotherm model. The density functional theory was used to simulate the spectral characteristics of SERS during the adsorption of DA on the surface of the Ag dimers. Furthermore, to improve the accuracy and precision of quantitative analysis of SERS assays with a multiplicative effects model for surface-enhanced Raman spectroscopy. Conclusion A LOD of 20 pM DA-level was obtained, and the linear response ranged from 30 pM to 300 nM for quantitative DA detection. The absolute relative percentage error was 4.22% between the real and predicted DA concentrations. This detection scheme is expected to have good applications in the prevention and diagnosis of certain diseases caused by disorders in the DA level. PMID:29713165

A PBPK Model to Predict Disposition of CYP3A-Metabolized Drugs in Pregnant Women: Verification and Discerning the Site of CYP3A Induction

PubMed Central

Ke, A B; Nallani, S C; Zhao, P; Rostami-Hodjegan, A; Unadkat, J D

2012-01-01

Besides logistical and ethical concerns, evaluation of safety and efficacy of medications in pregnant women is complicated by marked changes in pharmacokinetics (PK) of drugs. For example, CYP3A activity is induced during the third trimester (T3). We explored whether a previously published physiologically based pharmacokinetic (PBPK) model could quantitatively predict PK profiles of CYP3A-metabolized drugs during T3, and discern the site of CYP3A induction (i.e., liver, intestine, or both). The model accounted for gestational age-dependent changes in maternal physiological function and hepatic CYP3A activity. For model verification, mean plasma area under the curve (AUC), peak plasma concentration (Cmax), and trough plasma concentration (Cmin) of midazolam (MDZ), nifedipine (NIF), and indinavir (IDV) were predicted and compared with published studies. The PBPK model successfully predicted MDZ, NIF, and IDV disposition during T3. A sensitivity analysis suggested that CYP3A induction in T3 is most likely hepatic and not intestinal. Our PBPK model is a useful tool to evaluate different dosing regimens during T3 for drugs cleared primarily via CYP3A metabolism. PMID:23835883

Sensitivity, accuracy, and precision issues in opto-electronic holography based on fiber optics and high-spatial- and high-digitial-resolution cameras

NASA Astrophysics Data System (ADS)

Furlong, Cosme; Yokum, Jeffrey S.; Pryputniewicz, Ryszard J.

2002-06-01

Sensitivity, accuracy, and precision characteristics in quantitative optical metrology techniques, and specifically in optoelectronic holography based on fiber optics and high-spatial and high-digital resolution cameras, are discussed in this paper. It is shown that sensitivity, accuracy, and precision dependent on both, the effective determination of optical phase and the effective characterization of the illumination-observation conditions. Sensitivity, accuracy, and precision are investigated with the aid of National Institute of Standards and Technology (NIST) traceable gages, demonstrating the applicability of quantitative optical metrology techniques to satisfy constantly increasing needs for the study and development of emerging technologies.

Evaluation of trypan blue stain in a haemocytometer for rapid detection of cerebrospinal fluid sterility in HIV patients with cryptococcal meningitis.

PubMed

Kwizera, Richard; Akampurira, Andrew; Kandole, Tadeo K; Nielsen, Kirsten; Kambugu, Andrew; Meya, David B; Boulware, David R; Rhein, Joshua

2017-08-22

Quantitative culture is the most common method to determine the fungal burden and sterility of cerebrospinal fluid (CSF) among persons with cryptococcal meningitis. A major drawback of cultures is a long turnaround-time. Recent evidence demonstrates that live and dead Cryptococcus yeasts can be distinguished using trypan blue staining. We hypothesized that trypan blue staining combined with haemocytometer counting may provide a rapid estimation of quantitative culture count and detection of CSF sterility. To test this, we evaluated 194 CSF specimens from 96 HIV-infected participants with cryptococcal meningitis in Kampala, Uganda. Cryptococcal meningitis was diagnosed by CSF cryptococcal antigen (CRAG). We stained CSF with trypan blue and quantified yeasts using a haemocytometer. We compared the haemocytometer readings versus quantitative Cryptococcus CSF cultures. Haemocytometer counting with trypan blue staining had a sensitivity of 98% (64/65), while CSF cultures had a sensitivity of 95% (62/65) with reference to CSF CRAG for diagnostic CSF specimens. For samples that were positive in both tests, the haemocytometer had higher readings compared to culture. For diagnostic specimens, the median of log 10 transformed counts were 5.59 (n = 64, IQR = 5.09 to 6.05) for haemocytometer and 4.98 (n = 62, IQR = 3.75 to 5.79) for culture; while the overall median counts were 5.35 (n = 189, IQR = 4.78-5.84) for haemocytometer and 3.99 (n = 151, IQR = 2.59-5.14) for cultures. The percentage agreement with culture sterility was 2.4% (1/42). Counts among non-sterile follow-up specimens had a median of 5.38 (n = 86, IQR = 4.74 to 6.03) for haemocytometer and 2.89 (n = 89, IQR = 2.11 to 4.38) for culture. At diagnosis, CSF quantitative cultures correlated with haemocytometer counts (R 2  = 0.59, P < 0.001). At 7-14 days, quantitative cultures did not correlate with haemocytometer counts (R 2  = 0.43, P = 0.4). Despite a positive correlation, the haemocytometer counts with trypan blue staining did not predict the outcome of quantitative cultures in patients receiving antifungal therapy.

KRAS Mutation Is a Predictor of Oxaliplatin Sensitivity in Colon Cancer Cells

PubMed Central

Lin, Yu-Lin; Ou, Da-Liang; Lin, Liang-In; Tseng, Li-Hui; Chang, Yih-Leong; Yeh, Kun-Huei; Cheng, Ann-Lii

2012-01-01

Molecular biomarkers to determine the effectiveness of targeted therapies in cancer treatment have been widely adopted in colorectal cancer (CRC), but those to predict chemotherapy sensitivity remain poorly defined. We tested our hypothesis that KRAS mutation may be a predictor of oxaliplatin sensitivity in CRC. KRAS was knocked-down in KRAS-mutant CRC cells (DLD-1G13D and SW480G12V) by small interfering RNAs (siRNA) and overexpressed in KRAS-wild-type CRC cells (COLO320DM) by KRAS-mutant vectors to generate paired CRC cells. These paired CRC cells were tested by oxaliplatin, irinotecan and 5FU to determine the change in drug sensitivity by MTT assay and flow cytometry. Reasons for sensitivity alteration were further determined by western blot and real-time quantitative reverse transcriptase polymerase chain reaction (qRT -PCR). In KRAS-wild-type CRC cells (COLO320DM), KRAS overexpression by mutant vectors caused excision repair cross-complementation group 1 (ERCC1) downregulation in protein and mRNA levels, and enhanced oxaliplatin sensitivity. In contrast, in KRAS-mutant CRC cells (DLD-1G13D and SW480G12V), KRAS knocked-down by KRAS-siRNA led to ERCC1 upregulation and increased oxaliplatin resistance. The sensitivity of irinotecan and 5FU had not changed in the paired CRC cells. To validate ERCC1 as a predictor of sensitivity for oxaliplatin, ERCC1 was knocked-down by siRNA in KRAS-wild-type CRC cells, which restored oxaliplatin sensitivity. In contrast, ERCC1 was overexpressed by ERCC1-expressing vectors in KRAS-mutant CRC cells, and caused oxaliplatin resistance. Overall, our findings suggest that KRAS mutation is a predictor of oxaliplatin sensitivity in colon cancer cells by the mechanism of ERCC1 downregulation. PMID:23209813

Comparison between culture and a multiplex quantitative real-time polymerase chain reaction assay detecting Ureaplasma urealyticum and U. parvum.

PubMed

Frølund, Maria; Björnelius, Eva; Lidbrink, Peter; Ahrens, Peter; Jensen, Jørgen Skov

2014-01-01

A novel multiplex quantitative real-time polymerase chain reaction (qPCR) for simultaneous detection of U. urealyticum and U. parvum was developed and compared with quantitative culture in Shepard's 10 C medium for ureaplasmas in urethral swabs from 129 men and 66 women, and cervical swabs from 61 women. Using culture as the gold standard, the sensitivity of the qPCR was 96% and 95% for female urethral and cervical swabs, respectively. In male urethral swabs the sensitivity was 89%. The corresponding specificities were 100%, 87% and 99%. The qPCR showed a linear increasing DNA copy number with increasing colour-changing units. Although slightly less sensitive than culture, this multiplex qPCR assay detecting U. urealyticum and U. parvum constitutes a simple and fast alternative to the traditional methods for identification of ureaplasmas and allows simultaneous species differentiation and quantitation in clinical samples. Furthermore, specimens overgrown by other bacteria using the culture method can be evaluated in the qPCR.

Detection of Organophosphorus Pesticides with Colorimetry and Computer Image Analysis.

PubMed

Li, Yanjie; Hou, Changjun; Lei, Jincan; Deng, Bo; Huang, Jing; Yang, Mei

2016-01-01

Organophosphorus pesticides (OPs) represent a very important class of pesticides that are widely used in agriculture because of their relatively high-performance and moderate environmental persistence, hence the sensitive and specific detection of OPs is highly significant. Based on the inhibitory effect of acetylcholinesterase (AChE) induced by inhibitors, including OPs and carbamates, a colorimetric analysis was used for detection of OPs with computer image analysis of color density in CMYK (cyan, magenta, yellow and black) color space and non-linear modeling. The results showed that there was a gradually weakened trend of yellow intensity with the increase of the concentration of dichlorvos. The quantitative analysis of dichlorvos was achieved by Artificial Neural Network (ANN) modeling, and the results showed that the established model had a good predictive ability between training sets and predictive sets. Real cabbage samples containing dichlorvos were detected by colorimetry and gas chromatography (GC), respectively. The results showed that there was no significant difference between colorimetry and GC (P > 0.05). The experiments of accuracy, precision and repeatability revealed good performance for detection of OPs. AChE can also be inhibited by carbamates, and therefore this method has potential applications in real samples for OPs and carbamates because of high selectivity and sensitivity.

Near-infrared Raman spectroscopy to detect anti-Toxoplasma gondii antibody in blood sera of domestic cats: quantitative analysis based on partial least-squares multivariate statistics

NASA Astrophysics Data System (ADS)

Duarte, Janaína; Pacheco, Marcos T. T.; Villaverde, Antonio Balbin; Machado, Rosangela Z.; Zângaro, Renato A.; Silveira, Landulfo

2010-07-01

Toxoplasmosis is an important zoonosis in public health because domestic cats are the main agents responsible for the transmission of this disease in Brazil. We investigate a method for diagnosing toxoplasmosis based on Raman spectroscopy. Dispersive near-infrared Raman spectra are used to quantify anti-Toxoplasma gondii (IgG) antibodies in blood sera from domestic cats. An 830-nm laser is used for sample excitation, and a dispersive spectrometer is used to detect the Raman scattering. A serological test is performed in all serum samples by the enzyme-linked immunosorbent assay (ELISA) for validation. Raman spectra are taken from 59 blood serum samples and a quantification model is implemented based on partial least squares (PLS) to quantify the sample's serology by Raman spectra compared to the results provided by the ELISA test. Based on the serological values provided by the Raman/PLS model, diagnostic parameters such as sensitivity, specificity, accuracy, positive prediction values, and negative prediction values are calculated to discriminate negative from positive samples, obtaining 100, 80, 90, 83.3, and 100%, respectively. Raman spectroscopy, associated with the PLS, is promising as a serological assay for toxoplasmosis, enabling fast and sensitive diagnosis.

Cross-Sectional Analysis of the Utility of Pulmonary Function Tests in Predicting Emphysema in Ever-Smokers

PubMed Central

Hesselbacher, Sean E.; Ross, Robert; Schabath, Matthew B.; Smith, E. O’Brian; Perusich, Sarah; Barrow, Nadia; Smithwick, Pamela; Mammen, Manoj J.; Coxson, Harvey; Krowchuk, Natasha; Corry, David B.; Kheradmand, Farrah

2011-01-01

Emphysema is largely an under-diagnosed medical condition that can exist in smokers in the absence of airway obstruction. We aimed to determine the sensitivity and specificity of pulmonary function tests (PFTs) in assessing emphysema using quantitative CT scans as the reference standard. We enrolled 224 ever-smokers (current or former) over the age of 40. CT of thorax was used to quantify the low attenuation area (% emphysema), and to measure the standardized airway wall thickness. PFTs were used individually and in combination to predict their ability to discriminate radiographic emphysema. Significant emphysema (>7%) was detected in 122 (54%) subjects. Twenty six (21%) emphysema subjects had no evidence of airflow obstruction (FEV1/FVC ratio <70%), while all subjects with >23% emphysema showed airflow obstruction. The sensitivity and specificity of spirometry for detecting radiographic emphysema were 79% and 75%, respectively. Standardized airway wall thickness was increased in subjects with airflow obstruction, but did not correlate with emphysema severity. In this cohort of lifetime ever-smokers, PFTs alone were inadequate for diagnosing emphysema. Airway wall thickness quantified by CT morphometry was associated with airflow limitation, but not with emphysema indicating that the heterogeneous nature of lung disease in smokers may represent distinct phenotypes. PMID:21655122

An rK28-Based Immunoenzymatic Assay for the Diagnosis of Canine Visceral Leishmaniasis in Latin America

PubMed Central

Lauricella, Marta Alicia; Maidana, Cristina Graciela; Frias, Victoria Fragueiro; Romagosa, Carlo M.; Negri, Vanesa; Benedetti, Ruben; Sinagra, Angel J.; Luna, Concepcion; Tartaglino, Lilian; Laucella, Susana; Reed, Steven G.; Riarte, Adelina R.

2016-01-01

Direct observation of Leishmania parasites in tissue aspirates has shown low sensitivity for the detection of canine visceral leishmaniasis (VL). Therefore in the last quarter century immunoenzymatic tests have been developed to improve diagnosis. The purpose of this study was to develop a fast recombinant K28 antigen, naked-eye qualitative enzyme-linked immunosorbent assay (VL Ql-ELISA) and a quantitative version (VL Qt-ELISA), and to display it in a kit format, whose cutoff value (0.156) was selected as the most adequate one to differentiate reactive from nonreactive samples. Considering 167 cases and 300 controls, sensitivity was 91% for both assays and specificity was 100% and 98.7% in Ql-ELISA and Qt-ELISA, respectively. Positive predictive values were 100% and 97.4% for Ql-ELISA and Qt-ELISA, respectively, and negative predictive values were 95.2% for both ELISAs. Reagent stability, reliability studies, including periodic repetitions and retest of samples, cutoff selection, and comparison of rK28 ELISAs with rK39 immunochromatographic test, were the international criteria that supported the quality in both kits. The performance of both ELISA kits in this work confirmed their validity and emphasized their usefulness for low-to-medium complexity laboratories. PMID:27162270

Biogenic organic emissions, air quality and climate

NASA Astrophysics Data System (ADS)

Guenther, A. B.

2015-12-01

Living organisms produce copious amounts of a diverse array of metabolites including many volatile organic compounds that are released into the atmosphere. These compounds participate in numerous chemical reactions that influence the atmospheric abundance of important air pollutants and short-lived climate forcers including organic aerosol, ozone and methane. The production and release of these organics are strongly influenced by environmental conditions including air pollution, temperature, solar radiation, and water availability and they are highly sensitive to stress and extreme events. As a result, releases of biogenic organics to the atmosphere have an impact on, and are sensitive to, air quality and climate leading to potential feedback couplings. Their role in linking air quality and climate is conceptually clear but an accurate quantitative representation is needed for predictive models. Progress towards this goal will be presented including numerical model development and assessments of the predictive capability of the Model of Emission of Gases and Aerosols from Nature (MEGAN). Recent studies of processes controlling the magnitude and variations in biogenic organic emissions will be described and observations of their impact on atmospheric composition will be shown. Recent advances and priorities for future research will be discussed including laboratory process studies, long-term measurements, multi-scale regional studies, global satellite observations, and the development of a next generation model for simulating land-atmosphere chemical exchange.

Improving statistical inference on pathogen densities estimated by quantitative molecular methods: malaria gametocytaemia as a case study.

PubMed

Walker, Martin; Basáñez, María-Gloria; Ouédraogo, André Lin; Hermsen, Cornelus; Bousema, Teun; Churcher, Thomas S

2015-01-16

Quantitative molecular methods (QMMs) such as quantitative real-time polymerase chain reaction (q-PCR), reverse-transcriptase PCR (qRT-PCR) and quantitative nucleic acid sequence-based amplification (QT-NASBA) are increasingly used to estimate pathogen density in a variety of clinical and epidemiological contexts. These methods are often classified as semi-quantitative, yet estimates of reliability or sensitivity are seldom reported. Here, a statistical framework is developed for assessing the reliability (uncertainty) of pathogen densities estimated using QMMs and the associated diagnostic sensitivity. The method is illustrated with quantification of Plasmodium falciparum gametocytaemia by QT-NASBA. The reliability of pathogen (e.g. gametocyte) densities, and the accompanying diagnostic sensitivity, estimated by two contrasting statistical calibration techniques, are compared; a traditional method and a mixed model Bayesian approach. The latter accounts for statistical dependence of QMM assays run under identical laboratory protocols and permits structural modelling of experimental measurements, allowing precision to vary with pathogen density. Traditional calibration cannot account for inter-assay variability arising from imperfect QMMs and generates estimates of pathogen density that have poor reliability, are variable among assays and inaccurately reflect diagnostic sensitivity. The Bayesian mixed model approach assimilates information from replica QMM assays, improving reliability and inter-assay homogeneity, providing an accurate appraisal of quantitative and diagnostic performance. Bayesian mixed model statistical calibration supersedes traditional techniques in the context of QMM-derived estimates of pathogen density, offering the potential to improve substantially the depth and quality of clinical and epidemiological inference for a wide variety of pathogens.

Methods and Applications of the Audibility Index in Hearing Aid Selection and Fitting

PubMed Central

Amlani, Amyn M.; Punch, Jerry L.; Ching, Teresa Y. C.

2002-01-01

During the first half of the 20th century, communications engineers at Bell Telephone Laboratories developed the articulation model for predicting speech intelligibility transmitted through different telecommunication devices under varying electroacoustic conditions. The profession of audiology adopted this model and its quantitative aspects, known as the Articulation Index and Speech Intelligibility Index, and applied these indices to the prediction of unaided and aided speech intelligibility in hearing-impaired listeners. Over time, the calculation methods of these indices—referred to collectively in this paper as the Audibility Index—have been continually refined and simplified for clinical use. This article provides (1) an overview of the basic principles and the calculation methods of the Audibility Index, the Speech Transmission Index and related indices, as well as the Speech Recognition Sensitivity Model, (2) a review of the literature on using the Audibility Index to predict speech intelligibility of hearing-impaired listeners, (3) a review of the literature on the applicability of the Audibility Index to the selection and fitting of hearing aids, and (4) a discussion of future scientific needs and clinical applications of the Audibility Index. PMID:25425917

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

Hudson, W.G.

Scapteriscus vicinus is the most important pest of turf and pasture grasses in Florida. This study develops a method of correlating sample results with true population density and provides the first quantitative information on spatial distribution and movement patterns of mole crickets. Three basic techniques for sampling mole crickets were compared: soil flushes, soil corer, and pitfall trapping. No statistical difference was found between the soil corer and soil flushing. Soil flushing was shown to be more sensitive to changes in population density than pitfall trapping. No technique was effective for sampling adults. Regression analysis provided a means of adjustingmore » for the effects of soil moisture and showed soil temperature to be unimportant in predicting efficiency of flush sampling. Cesium-137 was used to label females for subsequent location underground. Comparison of mean distance to nearest neighbor with the distance predicted by a random distribution model showed that the observed distance in the spring was significantly greater than hypothesized (Student's T-test, p < 0.05). Fall adult nearest neighbor distance was not different than predicted by the random distribution hypothesis.« less

Predicting the synergy of multiple stress effects

NASA Astrophysics Data System (ADS)

Liess, Matthias; Foit, Kaarina; Knillmann, Saskia; Schäfer, Ralf B.; Liess, Hans-Dieter

2016-09-01

Toxicants and other, non-chemical environmental stressors contribute to the global biodiversity crisis. Examples include the loss of bees and the reduction of aquatic biodiversity. Although non-compliance with regulations might be contributing, the widespread existence of these impacts suggests that for example the current approach of pesticide risk assessment fails to protect biodiversity when multiple stressors concurrently affect organisms. To quantify such multiple stress effects, we analysed all applicable aquatic studies and found that the presence of environmental stressors increases individual sensitivity to toxicants (pesticides, trace metals) by a factor of up to 100. To predict this dependence, we developed the “Stress Addition Model” (SAM). With the SAM, we assume that each individual has a general stress capacity towards all types of specific stress that should not be exhausted. Experimental stress levels are transferred into general stress levels of the SAM using the stress-related mortality as a common link. These general stress levels of independent stressors are additive, with the sum determining the total stress exerted on a population. With this approach, we provide a tool that quantitatively predicts the highly synergistic direct effects of independent stressor combinations.

Raised D-dimer levels in acute sickle cell crisis and their correlation with chest X-ray abnormalities

PubMed Central

Dar, Javeed; Mughal, Inam; Hassan, Hilali; Al Mekki, Taj E.; Chapunduka, Zivani; Hassan, Imad S. A.

2010-01-01

Objective: Quantitation of D-dimer level during a sickling crisis and its correlation with other clinical abnormalities. Design: Prospective longitudinal study. Setting: Armed Forces Hospital, Southern Region, Kingdom of Saudi Arabia. Patients: Adult patients (12 years and older) admitted acutely with a sickle cell crisis who consent to taking part in the study. Candidates may re-participate if they are readmitted with a further acute painful crisis. Results: 36 patients with homozygous sickle cell disease consented to take part in the study. D-dimer levels were raised in 31 (68.9%) of 45 episodes of painful crisis of whom 13 had an abnormal chest X-ray. Of those with a normal chest X-ray only one patient had a raised D-dimer level: sensitivity of 92.3%, specificity 40.6%, positive predictive value 38.7% and negative predictive value of 92.9% for an abnormal chest X-ray. Conclusion: D-dimer levels are frequently raised during an acute painful crisis. A normal level has a high negative predictive value for an abnormal chest X-ray. PMID:21063468

Raised D-dimer levels in acute sickle cell crisis and their correlation with chest X-ray abnormalities.

PubMed

Dar, Javeed; Mughal, Inam; Hassan, Hilali; Al Mekki, Taj E; Chapunduka, Zivani; Hassan, Imad S A

2010-10-08

Quantitation of D-dimer level during a sickling crisis and its correlation with other clinical abnormalities. Prospective longitudinal study. Armed Forces Hospital, Southern Region, Kingdom of Saudi Arabia. Adult patients (12 years and older) admitted acutely with a sickle cell crisis who consent to taking part in the study. Candidates may re-participate if they are readmitted with a further acute painful crisis. 36 patients with homozygous sickle cell disease consented to take part in the study. D-dimer levels were raised in 31 (68.9%) of 45 episodes of painful crisis of whom 13 had an abnormal chest X-ray. Of those with a normal chest X-ray only one patient had a raised D-dimer level: sensitivity of 92.3%, specificity 40.6%, positive predictive value 38.7% and negative predictive value of 92.9% for an abnormal chest X-ray. D-dimer levels are frequently raised during an acute painful crisis. A normal level has a high negative predictive value for an abnormal chest X-ray.

PredPsych: A toolbox for predictive machine learning-based approach in experimental psychology research.

PubMed

Koul, Atesh; Becchio, Cristina; Cavallo, Andrea

2017-12-12

Recent years have seen an increased interest in machine learning-based predictive methods for analyzing quantitative behavioral data in experimental psychology. While these methods can achieve relatively greater sensitivity compared to conventional univariate techniques, they still lack an established and accessible implementation. The aim of current work was to build an open-source R toolbox - "PredPsych" - that could make these methods readily available to all psychologists. PredPsych is a user-friendly, R toolbox based on machine-learning predictive algorithms. In this paper, we present the framework of PredPsych via the analysis of a recently published multiple-subject motion capture dataset. In addition, we discuss examples of possible research questions that can be addressed with the machine-learning algorithms implemented in PredPsych and cannot be easily addressed with univariate statistical analysis. We anticipate that PredPsych will be of use to researchers with limited programming experience not only in the field of psychology, but also in that of clinical neuroscience, enabling computational assessment of putative bio-behavioral markers for both prognosis and diagnosis.

A Kinetic Model for Calcium Dynamics in RAW 264.7 Cells: 2. Knockdown Response and Long-Term Response

PubMed Central

Maurya, Mano Ram; Subramaniam, Shankar

2007-01-01

This article addresses how quantitative models such as the one proposed in the companion article can be used to study cellular network perturbations such as knockdowns and pharmacological perturbations in a predictive manner. Using the kinetic model for cytosolic calcium dynamics in RAW 264.7 cells developed in the companion article, the calcium response to complement 5a (C5a) for the knockdown of seven proteins (C5a receptor; G-β-2; G-α,i-2,3; regulator of G-protein signaling-10; G-protein coupled receptor kinase-2; phospholipase C β-3; arrestin) is predicted and validated against the data from the Alliance for Cellular Signaling. The knockdown responses provide insights into how altered expressions of important proteins in disease states result in intermediate measurable phenotypes. Long-term response and long-term dose response have also been predicted, providing insights into how the receptor desensitization, internalization, and recycle result in tolerance. Sensitivity analysis of long-term response shows that the mechanisms and parameters in the receptor recycle path are important for long-term calcium dynamics. PMID:17483189

Analytical validation of quantitative immunohistochemical assays of tumor infiltrating lymphocyte biomarkers.

PubMed

Singh, U; Cui, Y; Dimaano, N; Mehta, S; Pruitt, S K; Yearley, J; Laterza, O F; Juco, J W; Dogdas, B

2018-06-04

Tumor infiltrating lymphocytes (TIL), especially T-cells, have both prognostic and therapeutic applications. The presence of CD8+ effector T-cells and the ratio of CD8+ cells to FOXP3+ regulatory T-cells have been used as biomarkers of disease prognosis to predict response to various immunotherapies. Blocking the interaction between inhibitory receptors on T-cells and their ligands with therapeutic antibodies including atezolizumab, nivolumab, pembrolizumab and tremelimumab increases the immune response against cancer cells and has shown significant improvement in clinical benefits and survival in several different tumor types. The improved clinical outcome is presumed to be associated with a higher tumor infiltration; therefore, it is thought that more accurate methods for measuring the amount of TIL could assist prognosis and predict treatment response. We have developed and validated quantitative immunohistochemistry (IHC) assays for CD3, CD8 and FOXP3 for immunophenotyping T-lymphocytes in tumor tissue. Various types of formalin fixed, paraffin embedded (FFPE) tumor tissues were immunolabeled with anti-CD3, anti-CD8 and anti-FOXP3 antibodies using an IHC autostainer. The tumor area of stained tissues, including the invasive margin of the tumor, was scored by a pathologist (visual scoring) and by computer-based quantitative image analysis. Two image analysis scores were obtained for the staining of each biomarker: the percent positive cells in the tumor area and positive cells/mm 2 tumor area. Comparison of visual vs. image analysis scoring methods using regression analysis showed high correlation and indicated that quantitative image analysis can be used to score the number of positive cells in IHC stained slides. To demonstrate that the IHC assays produce consistent results in normal daily testing, we evaluated the specificity, sensitivity and reproducibility of the IHC assays using both visual and image analysis scoring methods. We found that CD3, CD8 and FOXP3 IHC assays met the fit-for-purpose analytical acceptance validation criteria and that they can be used to support clinical studies.

QSAR classification models for the prediction of endocrine disrupting activity of brominated flame retardants.

PubMed

Kovarich, Simona; Papa, Ester; Gramatica, Paola

2011-06-15

The identification of potential endocrine disrupting (ED) chemicals is an important task for the scientific community due to their diffusion in the environment; the production and use of such compounds will be strictly regulated through the authorization process of the REACH regulation. To overcome the problem of insufficient experimental data, the quantitative structure-activity relationship (QSAR) approach is applied to predict the ED activity of new chemicals. In the present study QSAR classification models are developed, according to the OECD principles, to predict the ED potency for a class of emerging ubiquitary pollutants, viz. brominated flame retardants (BFRs). Different endpoints related to ED activity (i.e. aryl hydrocarbon receptor agonism and antagonism, estrogen receptor agonism and antagonism, androgen and progesterone receptor antagonism, T4-TTR competition, E2SULT inhibition) are modeled using the k-NN classification method. The best models are selected by maximizing the sensitivity and external predictive ability. We propose simple QSARs (based on few descriptors) characterized by internal stability, good predictive power and with a verified applicability domain. These models are simple tools that are applicable to screen BFRs in relation to their ED activity, and also to design safer alternatives, in agreement with the requirements of REACH regulation at the authorization step. Copyright © 2011 Elsevier B.V. All rights reserved.

Comparative Analysis of Soft Computing Models in Prediction of Bending Rigidity of Cotton Woven Fabrics

NASA Astrophysics Data System (ADS)

Guruprasad, R.; Behera, B. K.

2015-10-01

Quantitative prediction of fabric mechanical properties is an essential requirement for design engineering of textile and apparel products. In this work, the possibility of prediction of bending rigidity of cotton woven fabrics has been explored with the application of Artificial Neural Network (ANN) and two hybrid methodologies, namely Neuro-genetic modeling and Adaptive Neuro-Fuzzy Inference System (ANFIS) modeling. For this purpose, a set of cotton woven grey fabrics was desized, scoured and relaxed. The fabrics were then conditioned and tested for bending properties. With the database thus created, a neural network model was first developed using back propagation as the learning algorithm. The second model was developed by applying a hybrid learning strategy, in which genetic algorithm was first used as a learning algorithm to optimize the number of neurons and connection weights of the neural network. The Genetic algorithm optimized network structure was further allowed to learn using back propagation algorithm. In the third model, an ANFIS modeling approach was attempted to map the input-output data. The prediction performances of the models were compared and a sensitivity analysis was reported. The results show that the prediction by neuro-genetic and ANFIS models were better in comparison with that of back propagation neural network model.

Early prediction of cerebral palsy by computer-based video analysis of general movements: a feasibility study.

PubMed

Adde, Lars; Helbostad, Jorunn L; Jensenius, Alexander R; Taraldsen, Gunnar; Grunewaldt, Kristine H; Støen, Ragnhild

2010-08-01

The aim of this study was to investigate the predictive value of a computer-based video analysis of the development of cerebral palsy (CP) in young infants. A prospective study of general movements used recordings from 30 high-risk infants (13 males, 17 females; mean gestational age 31wks, SD 6wks; range 23-42wks) between 10 and 15 weeks post term when fidgety movements should be present. Recordings were analysed using computer vision software. Movement variables, derived from differences between subsequent video frames, were used for quantitative analyses. CP status was reported at 5 years. Thirteen infants developed CP (eight hemiparetic, four quadriparetic, one dyskinetic; seven ambulatory, three non-ambulatory, and three unknown function), of whom one had fidgety movements. Variability of the centroid of motion had a sensitivity of 85% and a specificity of 71% in identifying CP. By combining this with variables reflecting the amount of motion, specificity increased to 88%. Nine out of 10 children with CP, and for whom information about functional level was available, were correctly predicted with regard to ambulatory and non-ambulatory function. Prediction of CP can be provided by computer-based video analysis in young infants. The method may serve as an objective and feasible tool for early prediction of CP in high-risk infants.

Bispectral index, entropy, and quantitative electroencephalogram during single-agent xenon anesthesia.

PubMed

Laitio, Ruut M; Kaskinoro, Kimmo; Särkelä, Mika O K; Kaisti, Kaike K; Salmi, Elina; Maksimow, Anu; Långsjö, Jaakko W; Aantaa, Riku; Kangas, Katja; Jääskeläinen, Satu; Scheinin, Harry

2008-01-01

The aim was to evaluate the performance of anesthesia depth monitors, Bispectral Index (BIS) and Entropy, during single-agent xenon anesthesia in 17 healthy subjects. After mask induction with xenon and intubation, anesthesia was continued with xenon only. BIS, State Entropy and Response Entropy, and electroencephalogram were monitored throughout induction, steady-state anesthesia, and emergence. The performance of BIS, State Entropy, and Response Entropy were evaluated with prediction probability, sensitivity, and specificity analyses. The power spectrum of the raw electroencephalogram signal was calculated. The mean (SD) xenon concentration during anesthesia was 66.4% (2.4%). BIS, State Entropy, and Response Entropy demonstrated low prediction probability values at loss of response (0.455, 0.656, and 0.619) but 1 min after that the values were high (0.804, 0.941, and 0.929). Thereafter, equally good performance was demonstrated for all indices. At emergence, the prediction probability values to distinguish between steady-state anesthesia and return of response for BIS, State Entropy, and Response Entropy were 0.988, 0.892, and 0.992. No statistical differences between the performances of the monitors were observed. Quantitative electroencephalogram analyses showed generalized increase in total power (P < 0.001), delta (P < 0.001) and theta activity (P < 0.001), and increased alpha activity (P = 0.003) in the frontal brain regions. Electroencephalogram-derived depth of sedation indices BIS and Entropy showed a delay to detect loss of response during induction of xenon anesthesia. Both monitors performed well in distinguishing between conscious and unconscious states during steady-state anesthesia. Xenon-induced changes in electroencephalogram closely resemble those induced by propofol.

Accelerated discovery of metallic glasses through iteration of machine learning and high-throughput experiments

PubMed Central

Wolverton, Christopher; Hattrick-Simpers, Jason; Mehta, Apurva

2018-01-01

With more than a hundred elements in the periodic table, a large number of potential new materials exist to address the technological and societal challenges we face today; however, without some guidance, searching through this vast combinatorial space is frustratingly slow and expensive, especially for materials strongly influenced by processing. We train a machine learning (ML) model on previously reported observations, parameters from physiochemical theories, and make it synthesis method–dependent to guide high-throughput (HiTp) experiments to find a new system of metallic glasses in the Co-V-Zr ternary. Experimental observations are in good agreement with the predictions of the model, but there are quantitative discrepancies in the precise compositions predicted. We use these discrepancies to retrain the ML model. The refined model has significantly improved accuracy not only for the Co-V-Zr system but also across all other available validation data. We then use the refined model to guide the discovery of metallic glasses in two additional previously unreported ternaries. Although our approach of iterative use of ML and HiTp experiments has guided us to rapid discovery of three new glass-forming systems, it has also provided us with a quantitatively accurate, synthesis method–sensitive predictor for metallic glasses that improves performance with use and thus promises to greatly accelerate discovery of many new metallic glasses. We believe that this discovery paradigm is applicable to a wider range of materials and should prove equally powerful for other materials and properties that are synthesis path–dependent and that current physiochemical theories find challenging to predict. PMID:29662953

Accelerated discovery of metallic glasses through iteration of machine learning and high-throughput experiments

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

Ren, Fang; Ward, Logan; Williams, Travis

With more than a hundred elements in the periodic table, a large number of potential new materials exist to address the technological and societal challenges we face today; however, without some guidance, searching through this vast combinatorial space is frustratingly slow and expensive, especially for materials strongly influenced by processing. We train a machine learning (ML) model on previously reported observations, parameters from physiochemical theories, and make it synthesis method–dependent to guide high-throughput (HiTp) experiments to find a new system of metallic glasses in the Co-V-Zr ternary. Experimental observations are in good agreement with the predictions of the model, butmore » there are quantitative discrepancies in the precise compositions predicted. We use these discrepancies to retrain the ML model. The refined model has significantly improved accuracy not only for the Co-V-Zr system but also across all other available validation data. We then use the refined model to guide the discovery of metallic glasses in two additional previously unreported ternaries. Although our approach of iterative use of ML and HiTp experiments has guided us to rapid discovery of three new glass-forming systems, it has also provided us with a quantitatively accurate, synthesis method–sensitive predictor for metallic glasses that improves performance with use and thus promises to greatly accelerate discovery of many new metallic glasses. We believe that this discovery paradigm is applicable to a wider range of materials and should prove equally powerful for other materials and properties that are synthesis path–dependent and that current physiochemical theories find challenging to predict.« less

An orientation sensitive approach in biomolecule interaction quantitative structure-activity relationship modeling and its application in ion-exchange chromatography.

PubMed

Kittelmann, Jörg; Lang, Katharina M H; Ottens, Marcel; Hubbuch, Jürgen

2017-01-27

Quantitative structure-activity relationship (QSAR) modeling for prediction of biomolecule parameters has become an established technique in chromatographic purification process design. Unfortunately available descriptor sets fail to describe the orientation of biomolecules and the effects of ionic strength in the mobile phase on the interaction with the stationary phase. The literature describes several special descriptors used for chromatographic retention modeling, all of these do not describe the screening of electrostatic potential by the mobile phase in use. In this work we introduce two new approaches of descriptor calculations, namely surface patches and plane projection, which capture an oriented binding to charged surfaces and steric hindrance of the interaction with chromatographic ligands with regard to electrostatic potential screening by mobile phase ions. We present the use of the developed descriptor sets for predictive modeling of Langmuir isotherms for proteins at different pH values between pH 5 and 10 and varying ionic strength in the range of 10-100mM. The resulting model has a high correlation of calculated descriptors and experimental results, with a coefficient of determination of 0.82 and a predictive coefficient of determination of 0.92 for unknown molecular structures and conditions. The agreement of calculated molecular interaction orientations with both, experimental results as well as molecular dynamic simulations from literature is shown. The developed descriptors provide the means for improved QSAR models of chromatographic processes, as they reflect the complex interactions of biomolecules with chromatographic phases. Copyright © 2016 Elsevier B.V. All rights reserved.

Quantitative Microbial Risk Assessment for Escherichia coli O157:H7 in Fresh-Cut Lettuce.

PubMed

Pang, Hao; Lambertini, Elisabetta; Buchanan, Robert L; Schaffner, Donald W; Pradhan, Abani K

2017-02-01

Leafy green vegetables, including lettuce, are recognized as potential vehicles for foodborne pathogens such as Escherichia coli O157:H7. Fresh-cut lettuce is potentially at high risk of causing foodborne illnesses, as it is generally consumed without cooking. Quantitative microbial risk assessments (QMRAs) are gaining more attention as an effective tool to assess and control potential risks associated with foodborne pathogens. This study developed a QMRA model for E. coli O157:H7 in fresh-cut lettuce and evaluated the effects of different potential intervention strategies on the reduction of public health risks. The fresh-cut lettuce production and supply chain was modeled from field production, with both irrigation water and soil as initial contamination sources, to consumption at home. The baseline model (with no interventions) predicted a mean probability of 1 illness per 10 million servings and a mean of 2,160 illness cases per year in the United States. All intervention strategies evaluated (chlorine, ultrasound and organic acid, irradiation, bacteriophage, and consumer washing) significantly reduced the estimated mean number of illness cases when compared with the baseline model prediction (from 11.4- to 17.9-fold reduction). Sensitivity analyses indicated that retail and home storage temperature were the most important factors affecting the predicted number of illness cases. The developed QMRA model provided a framework for estimating risk associated with consumption of E. coli O157:H7-contaminated fresh-cut lettuce and can guide the evaluation and development of intervention strategies aimed at reducing such risk.

Accelerated discovery of metallic glasses through iteration of machine learning and high-throughput experiments

DOE PAGES

Ren, Fang; Ward, Logan; Williams, Travis; ...

2018-04-01

With more than a hundred elements in the periodic table, a large number of potential new materials exist to address the technological and societal challenges we face today; however, without some guidance, searching through this vast combinatorial space is frustratingly slow and expensive, especially for materials strongly influenced by processing. We train a machine learning (ML) model on previously reported observations, parameters from physiochemical theories, and make it synthesis method–dependent to guide high-throughput (HiTp) experiments to find a new system of metallic glasses in the Co-V-Zr ternary. Experimental observations are in good agreement with the predictions of the model, butmore » there are quantitative discrepancies in the precise compositions predicted. We use these discrepancies to retrain the ML model. The refined model has significantly improved accuracy not only for the Co-V-Zr system but also across all other available validation data. We then use the refined model to guide the discovery of metallic glasses in two additional previously unreported ternaries. Although our approach of iterative use of ML and HiTp experiments has guided us to rapid discovery of three new glass-forming systems, it has also provided us with a quantitatively accurate, synthesis method–sensitive predictor for metallic glasses that improves performance with use and thus promises to greatly accelerate discovery of many new metallic glasses. We believe that this discovery paradigm is applicable to a wider range of materials and should prove equally powerful for other materials and properties that are synthesis path–dependent and that current physiochemical theories find challenging to predict.« less

Non-animal sensitization testing: state-of-the-art.

PubMed

Vandebriel, Rob J; van Loveren, Henk

2010-05-01

Predictive tests to identify the sensitizing properties of chemicals are carried out using animals. In the European Union timelines for phasing out many standard animal tests were established for cosmetics. Following this policy, the new European Chemicals Legislation (REACH) favors alternative methods, if validated and appropriate. In this review the authors aim to provide a state-of-the art overview of alternative methods (in silico, in chemico, and in vitro) to identify contact and respiratory sensitizing capacity and in some occasions give a measure of potency. The past few years have seen major advances in QSAR (quantitative structure-activity relationship) models where especially mechanism-based models have great potential, peptide reactivity assays where multiple parameters can be measured simultaneously, providing a more complete reactivity profile, and cell-based assays. Several cell-based assays are in development, not only using different cell types, but also several specifically developed assays such as three-dimenionally (3D)-reconstituted skin models, an antioxidant response reporter assay, determination of signaling pathways, and gene profiling. Some of these assays show relatively high sensitivity and specificity for a large number of sensitizers and should enter validation (or are indeed entering this process). Integrating multiple assays in a decision tree or integrated testing system is a next step, but has yet to be developed. Adequate risk assessment, however, is likely to require significantly more time and efforts.

SU-F-J-207: Non-Small Cell Lung Cancer Patient Survival Prediction with Quantitative Tumor Textures Analysis in Baseline CT

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

Wu, Y; Zou, J; Murillo, P

Purpose: Chemo-radiation therapy (CRT) is widely used in treating patients with locally advanced non-small cell lung cancer (NSCLC). Determination of the likelihood of patient response to treatment and optimization of treatment regime is of clinical significance. Up to date, no imaging biomarker has reliably correlated to NSCLC patient survival rate. This pilot study is to extract CT texture information from tumor regions for patient survival prediction. Methods: Thirteen patients with stage II-III NSCLC were treated using CRT with a median dose of 6210 cGy. Non-contrast-enhanced CT images were acquired for treatment planning and retrospectively collected for this study. Texture analysismore » was applied in segmented tumor regions using the Local Binary Pattern method (LBP). By comparing its HU with neighboring voxels, the LBPs of a voxel were measured in multiple scales with different group radiuses and numbers of neighbors. The LBP histograms formed a multi-dimensional texture vector for each patient, which was then used to establish and test a Support Vector Machine (SVM) model to predict patients’ one year survival. The leave-one-out cross validation strategy was used recursively to enlarge the training set and derive a reliable predictor. The predictions were compared with the true clinical outcomes. Results: A 10-dimensional LBP histogram was extracted from 3D segmented tumor region for each of the 13 patients. Using the SVM model with the leave-one-out strategy, only 1 out of 13 patients was misclassified. The experiments showed an accuracy of 93%, sensitivity of 100%, and specificity of 86%. Conclusion: Within the framework of a Support Vector Machine based model, the Local Binary Pattern method is able to extract a quantitative imaging biomarker in the prediction of NSCLC patient survival. More patients are to be included in the study.« less

The discovery and development of proteomic safety biomarkers for the detection of drug-induced liver toxicity.

PubMed

Amacher, David E

2010-05-15

Biomarkers are biometric measurements that provide critical quantitative information about the biological condition of the animal or individual being tested. In drug safety studies, established toxicity biomarkers are used along with other conventional study data to determine dose-limiting organ toxicity, and to define species sensitivity for new chemical entities intended for possible use as human medicines. A continuing goal of drug safety scientists in the pharmaceutical industry is to discover and develop better trans-species biomarkers that can be used to determine target organ toxicities for preclinical species in short-term studies at dose levels that are some multiple of the intended human dose and again later in full development for monitoring clinical trials at lower therapeutic doses. Of particular value are early, predictive, noninvasive biomarkers that have in vitro, in vivo, and clinical transferability. Such translational biomarkers bridge animal testing used in preclinical science and human studies that are part of subsequent clinical testing. Although suitable for in vivo preclinical regulatory studies, conventional hepatic safety biomarkers are basically confirmatory markers because they signal organ toxicity after some pathological damage has occurred, and are therefore not well-suited for short-term, predictive screening assays early in the discovery-to-development progression of new chemical entities (NCEs) available in limited quantities. Efforts between regulatory agencies and the pharmaceutical industry are underway for the coordinated discovery, qualification, verification and validation of early predictive toxicity biomarkers. Early predictive safety biomarkers are those that are detectable and quantifiable prior to the onset of irreversible tissue injury and which are associated with a mechanism of action relevant to a specific type of potential hepatic injury. Potential drug toxicity biomarkers are typically endogenous macromolecules in biological fluids with varying immunoreactivity which can present bioanalytical challenges when first discovered. The potential success of these efforts is greatly enhanced by recent advances in two closely linked technologies, toxicoproteomics and targeted, quantitative mass spectrometry. This review focuses on the examination of the current status of these technologies as they relate to the discovery and development of novel preclinical biomarkers of hepatotoxicity. A critical assessment of the current literature reveals two distinct lines of safety biomarker investigation, (1) peripheral fluid biomarkers of organ toxicity and (2) tissue or cell-based toxicity signatures. Improved peripheral fluid biomarkers should allow the sensitive detection of potential organ toxicity prior to the onset of overt organ pathology. Advancements in tissue or cell-based toxicity biomarkers will provide sensitive in vitro or ex vivo screening systems based on toxicity pathway markers. An examination of the current practices in clinical pathology and the critical evaluation of some recently proposed biomarker candidates in comparison to the desired characteristics of an ideal toxicity biomarker lead this author to conclude that a combination of selected biomarkers will be more informative if not predictive of potential animal organ toxicity than any single biomarker, new or old. For the practical assessment of combinations of conventional and/or novel toxicity biomarkers in rodent and large animal preclinical species, mass spectrometry has emerged as the premier analytical tool compared to specific immunoassays or functional assays. Selected and multiple reaction monitoring mass spectrometry applications make it possible for this same basic technology to be used in the progressive stages of biomarker discovery, development, and more importantly, routine study applications without the use of specific antibody reagents. This technology combined with other "omics" technologies can provide added selectivity and sensitivity in preclinical drug safety testing.

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

Amacher, David E.

Biomarkers are biometric measurements that provide critical quantitative information about the biological condition of the animal or individual being tested. In drug safety studies, established toxicity biomarkers are used along with other conventional study data to determine dose-limiting organ toxicity, and to define species sensitivity for new chemical entities intended for possible use as human medicines. A continuing goal of drug safety scientists in the pharmaceutical industry is to discover and develop better trans-species biomarkers that can be used to determine target organ toxicities for preclinical species in short-term studies at dose levels that are some multiple of the intendedmore » human dose and again later in full development for monitoring clinical trials at lower therapeutic doses. Of particular value are early, predictive, noninvasive biomarkers that have in vitro, in vivo, and clinical transferability. Such translational biomarkers bridge animal testing used in preclinical science and human studies that are part of subsequent clinical testing. Although suitable for in vivo preclinical regulatory studies, conventional hepatic safety biomarkers are basically confirmatory markers because they signal organ toxicity after some pathological damage has occurred, and are therefore not well-suited for short-term, predictive screening assays early in the discovery-to-development progression of new chemical entities (NCEs) available in limited quantities. Efforts between regulatory agencies and the pharmaceutical industry are underway for the coordinated discovery, qualification, verification and validation of early predictive toxicity biomarkers. Early predictive safety biomarkers are those that are detectable and quantifiable prior to the onset of irreversible tissue injury and which are associated with a mechanism of action relevant to a specific type of potential hepatic injury. Potential drug toxicity biomarkers are typically endogenous macromolecules in biological fluids with varying immunoreactivity which can present bioanalytical challenges when first discovered. The potential success of these efforts is greatly enhanced by recent advances in two closely linked technologies, toxicoproteomics and targeted, quantitative mass spectrometry. This review focuses on the examination of the current status of these technologies as they relate to the discovery and development of novel preclinical biomarkers of hepatotoxicity. A critical assessment of the current literature reveals two distinct lines of safety biomarker investigation, (1) peripheral fluid biomarkers of organ toxicity and (2) tissue or cell-based toxicity signatures. Improved peripheral fluid biomarkers should allow the sensitive detection of potential organ toxicity prior to the onset of overt organ pathology. Advancements in tissue or cell-based toxicity biomarkers will provide sensitive in vitro or ex vivo screening systems based on toxicity pathway markers. An examination of the current practices in clinical pathology and the critical evaluation of some recently proposed biomarker candidates in comparison to the desired characteristics of an ideal toxicity biomarker lead this author to conclude that a combination of selected biomarkers will be more informative if not predictive of potential animal organ toxicity than any single biomarker, new or old. For the practical assessment of combinations of conventional and/or novel toxicity biomarkers in rodent and large animal preclinical species, mass spectrometry has emerged as the premier analytical tool compared to specific immunoassays or functional assays. Selected and multiple reaction monitoring mass spectrometry applications make it possible for this same basic technology to be used in the progressive stages of biomarker discovery, development, and more importantly, routine study applications without the use of specific antibody reagents. This technology combined with other 'omics' technologies can provide added selectivity and sensitivity in preclinical drug safety testing.« less

Theory and Application of Magnetic Flux Leakage Pipeline Detection.

PubMed

Shi, Yan; Zhang, Chao; Li, Rui; Cai, Maolin; Jia, Guanwei

2015-12-10

Magnetic flux leakage (MFL) detection is one of the most popular methods of pipeline inspection. It is a nondestructive testing technique which uses magnetic sensitive sensors to detect the magnetic leakage field of defects on both the internal and external surfaces of pipelines. This paper introduces the main principles, measurement and processing of MFL data. As the key point of a quantitative analysis of MFL detection, the identification of the leakage magnetic signal is also discussed. In addition, the advantages and disadvantages of different identification methods are analyzed. Then the paper briefly introduces the expert systems used. At the end of this paper, future developments in pipeline MFL detection are predicted.

Theory and Application of Magnetic Flux Leakage Pipeline Detection

PubMed Central

Shi, Yan; Zhang, Chao; Li, Rui; Cai, Maolin; Jia, Guanwei

2015-01-01

Magnetic flux leakage (MFL) detection is one of the most popular methods of pipeline inspection. It is a nondestructive testing technique which uses magnetic sensitive sensors to detect the magnetic leakage field of defects on both the internal and external surfaces of pipelines. This paper introduces the main principles, measurement and processing of MFL data. As the key point of a quantitative analysis of MFL detection, the identification of the leakage magnetic signal is also discussed. In addition, the advantages and disadvantages of different identification methods are analyzed. Then the paper briefly introduces the expert systems used. At the end of this paper, future developments in pipeline MFL detection are predicted. PMID:26690435

Reproducible surface-enhanced Raman quantification of biomarkers in multicomponent mixtures.

PubMed

De Luca, Anna Chiara; Reader-Harris, Peter; Mazilu, Michael; Mariggiò, Stefania; Corda, Daniela; Di Falco, Andrea

2014-03-25

Direct and quantitative detection of unlabeled glycerophosphoinositol (GroPIns), an abundant cytosolic phosphoinositide derivative, would allow rapid evaluation of several malignant cell transformations. Here we report label-free analysis of GroPIns via surface-enhanced Raman spectroscopy (SERS) with a sensitivity of 200 nM, well below its apparent concentration in cells. Crucially, our SERS substrates, based on lithographically defined gold nanofeatures, can be used to predict accurately the GroPIns concentration even in multicomponent mixtures, avoiding the preliminary separation of individual compounds. Our results represent a critical step toward the creation of SERS-based biosensor for rapid, label-free, and reproducible detection of specific molecules, overcoming limits of current experimental methods.

Altering wettability to recover more oil from tight formations

DOE PAGES

Brady, Patrick V.; Bryan, Charles R.; Thyne, Geoffrey; ...

2016-06-03

We describe here a method for chemically modifying fracturing fluids and overflushes to chemically increase oil recovery from tight formations. Oil wetting of tight formations is usually controlled by adhesion to illite, kerogen, or both; adhesion to carbonate minerals may also play a role. Oil-illite adhesion is sensitive to salinity, dissolved divalent cation content, and pH. We measure oil-rock adhesion with middle Bakken formation oil and core to verify a surface complexation model of reservoir wettability. The agreement between the model and experiments suggests that wettability trends in tight formations can be quantitatively predicted and that fracturing fluid and overflushmore » compositions can be individually tailored to increase oil recovery.« less

Altering wettability to recover more oil from tight formations

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

Brady, Patrick V.; Bryan, Charles R.; Thyne, Geoffrey

We describe here a method for chemically modifying fracturing fluids and overflushes to chemically increase oil recovery from tight formations. Oil wetting of tight formations is usually controlled by adhesion to illite, kerogen, or both; adhesion to carbonate minerals may also play a role. Oil-illite adhesion is sensitive to salinity, dissolved divalent cation content, and pH. We measure oil-rock adhesion with middle Bakken formation oil and core to verify a surface complexation model of reservoir wettability. The agreement between the model and experiments suggests that wettability trends in tight formations can be quantitatively predicted and that fracturing fluid and overflushmore » compositions can be individually tailored to increase oil recovery.« less

The Impacts of Microphysics and Planetary Boundary Layer Physics on Model Simulations of U.S. Deep South Summer Convection

NASA Technical Reports Server (NTRS)

McCaul, Eugene W., Jr.; Case, Jonathan L.; Zavodsky, Bradley; Srikishen, Jayanthi; Medlin, Jeffrey; Wood, Lance

2014-01-01

Convection-allowing numerical weather simula- tions have often been shown to produce convective storms that have significant sensitivity to choices of model physical parameterizations. Among the most important of these sensitivities are those related to cloud microphysics, but planetary boundary layer parameterizations also have a significant impact on the evolution of the convection. Aspects of the simulated convection that display sensitivity to these physics schemes include updraft size and intensity, simulated radar reflectivity, timing and placement of storm initi- ation and decay, total storm rainfall, and other storm features derived from storm structure and hydrometeor fields, such as predicted lightning flash rates. In addition to the basic parameters listed above, the simulated storms may also exhibit sensitivity to im- posed initial conditions, such as the fields of soil temper- ature and moisture, vegetation cover and health, and sea and lake water surface temperatures. Some of these sensitivities may rival those of the basic physics sensi- tivities mentioned earlier. These sensitivities have the potential to disrupt the accuracy of short-term forecast simulations of convective storms, and thereby pose sig- nificant difficulties for weather forecasters. To make a systematic study of the quantitative impacts of each of these sensitivities, a matrix of simulations has been performed using all combinations of eight separate microphysics schemes, three boundary layer schemes, and two sets of initial conditions. The first version of initial conditions consists of the default data from large-scale operational model fields, while the second features specialized higher- resolution soil conditions, vegetation conditions and water surface temperatures derived from datasets created at NASA's Short-term Prediction and Operational Research Tran- sition (SPoRT) Center at the National Space Science and Technology Center (NSSTC) in Huntsville, AL. Simulations as outlined above, each 48 in number, were conducted for five midsummer weakly sheared coastal convective events each at two sites, Mobile, AL (MOB) and Houston, TX (HGX). Of special interest to operational forecasters at MOB and HGX were accuracy of timing and placement of convective storm initiation, reflectivity magnitudes and coverage, rainfall and inferred lightning threat.

Sensitivity to synchronicity of biological motion in normal and amblyopic vision

PubMed Central

Luu, Jennifer Y.; Levi, Dennis M.

2017-01-01

Amblyopia is a developmental disorder of spatial vision that results from abnormal early visual experience usually due to the presence of strabismus, anisometropia, or both strabismus and anisometropia. Amblyopia results in a range of visual deficits that cannot be corrected by optics because the deficits reflect neural abnormalities. Biological motion refers to the motion patterns of living organisms, and is normally displayed as points of lights positioned at the major joints of the body. In this experiment, our goal was twofold. We wished to examine whether the human visual system in people with amblyopia retained the higher-level processing capabilities to extract visual information from the synchronized actions of others, therefore retaining the ability to detect biological motion. Specifically, we wanted to determine if the synchronized interaction of two agents performing a dancing routine allowed the amblyopic observer to use the actions of one agent to predict the expected actions of a second agent. We also wished to establish whether synchronicity sensitivity (detection of synchronized versus desynchronized interactions) is impaired in amblyopic observers relative to normal observers. The two aims are differentiated in that the first aim looks at whether synchronized actions result in improved expected action predictions while the second aim quantitatively compares synchronicity sensitivity, or the ratio of desynchronized to synchronized detection sensitivities, to determine if there is a difference between normal and amblyopic observers. Our results show that the ability to detect biological motion requires more samples in both eyes of amblyopes than in normal control observers. The increased sample threshold is not the result of low-level losses but may reflect losses in feature integration due to undersampling in the amblyopic visual system. However, like normal observers, amblyopes are more sensitive to synchronized versus desynchronized interactions, indicating that higher-level processing of biological motion remains intact. We also found no impairment in synchronicity sensitivity in the amblyopic visual system relative to the normal visual system. Since there is no impairment in synchronicity sensitivity in either the nonamblyopic or amblyopic eye of amblyopes, our results suggest that the higher order processing of biological motion is intact. PMID:23474301

Essential Set of Molecular Descriptors for ADME Prediction in Drug and Environmental Chemical Space

EPA Science Inventory

Historically, the disciplines of pharmacology and toxicology have embraced quantitative structure-activity relationships (QSAR) and quantitative structure-property relationships (QSPR) to predict ADME properties or biological activities of untested chemicals. The question arises ...

Quantitative Contrast-Enhanced Ultrasound Parameters in Crohn Disease: Their Role in Disease Activity Determination With Ultrasound.

PubMed

Medellin-Kowalewski, Alexandra; Wilkens, Rune; Wilson, Alexandra; Ruan, Ji; Wilson, Stephanie R

2016-01-01

The primary objective of our study was to examine the association between contrast-enhanced ultrasound (CEUS) parameters and established gray-scale ultrasound with color Doppler imaging (CDI) for the determination of disease activity in patients with Crohn disease. Our secondary objective was to develop quantitative time-signal intensity curve thresholds for disease activity. One hundred twenty-seven patients with Crohn disease underwent ultrasound with CDI and CEUS. Reviewers graded wall thickness, inflammatory fat, and mural blood flow as showing remission or inflammation (mild, moderate, or severe). If both gray-scale ultrasound and CDI predicted equal levels of disease activity, the studies were considered concordant. If ultrasound images suggested active disease not supported by CDI findings, the ultrasound results for disease activity were indeterminate. Time-signal intensity curves from CEUS were acquired with calculation of peak enhancement (PE), and AUCs. Interobserver variation and associations between PE and ultrasound parameters were examined. Multiclass ROC analysis was used to develop CEUS thresholds for activity. Ninety-six (76%) studies were concordant, 19 of which showed severe disease, and 31 (24%) studies were indeterminate. Kappa analyses revealed good interobserver agreement on grades for CDI (κ = 0.76) and ultrasound (κ = 0.80) assessments. PE values on CEUS and wall thickness showed good association with the Spearman rank correlation coefficient for the entire population (ρ = 0.62, p < 0.01) and for the concordant group (ρ = 0.70, p < 0.01). Multiclass ROC analyses of the concordant group using wall thickness alone as the reference standard showed cutoff points of 18.2 dB for differentiating mild versus moderate activity (sensitivity, 89.0% and specificity, 87.0%) and 23.0 dB for differentiating moderate versus severe (sensitivity, 90% and specificity, 86.8%). Almost identical cutoff points were observed when using ultrasound global assessment as the reference standard: using 18.2 dB to differentiate mild versus moderate activity yielded sensitivity of 89.2% and specificity of 90.9% and using 22.9 dB to differentiate moderate versus severe activity yielded sensitivity of 89.5% and specificity of 83.1%. Quantitative CEUS parameters integrated into inflammatory assessments with ultrasound reduce indeterminate results and improve disease activity level determinations.

A New Diagnostic system for Ultra Sensitive and Specific Detection and Quantitation of “Candidatus Liberibacter asiaticus”, the Bacterium Associated with Citrus Huanglongbing

USDA-ARS?s Scientific Manuscript database

In this study, an ultra sensitive and quantitative diagnostic system for “Candidatus Liberibacter asiaticus” was developed. This system adapts a nested PCR and Taq-Man PCR in a single closed tube. The procedure involves two steps of PCR using the species specific outer and inner primer pairs. Differ...

Temperature sensitivity of soil microbial communities: An application of macromolecular rate theory to microbial respiration

NASA Astrophysics Data System (ADS)

Alster, Charlotte J.; Koyama, Akihiro; Johnson, Nels G.; Wallenstein, Matthew D.; von Fischer, Joseph C.

2016-06-01

There is compelling evidence that microbial communities vary widely in their temperature sensitivity and may adapt to warming through time. To date, this sensitivity has been largely characterized using a range of models relying on versions of the Arrhenius equation, which predicts an exponential increase in reaction rate with temperature. However, there is growing evidence from laboratory and field studies that observe nonmonotonic responses of reaction rates to variation in temperature, indicating that Arrhenius is not an appropriate model for quantitatively characterizing temperature sensitivity. Recently, Hobbs et al. (2013) developed macromolecular rate theory (MMRT), which incorporates thermodynamic temperature optima as arising from heat capacity differences between isoenzymes. We applied MMRT to measurements of respiration from soils incubated at different temperatures. These soils were collected from three grassland sites across the U.S. Great Plains and reciprocally transplanted, allowing us to isolate the effects of microbial community type from edaphic factors. We found that microbial community type explained roughly 30% of the variation in the CO2 production rate from the labile C pool but that temperature and soil type were most important in explaining variation in labile and recalcitrant C pool size. For six out of the nine soil × inoculum combinations, MMRT was superior to Arrhenius. The MMRT analysis revealed that microbial communities have distinct heat capacity values and temperature sensitivities sometimes independent of soil type. These results challenge the current paradigm for modeling temperature sensitivity of soil C pools and understanding of microbial enzyme dynamics.

Determination of hemispheric language dominance using functional magnetic resonance imaging and the Shiritori (Japanese word chain) task in patients with epilepsy: Comparison with the Wada test.

PubMed

Kashida, Yumi; Otsubo, Toshiaki; Hanaya, Ryosuke; Kodabashi, Atsushi; Tsumagari, Noriko; Sugata, Sei; Hosoyama, Hiroshi; Iida, Koji; Nakamura, Katsumi; Tokimura, Hiroshi; Fujimoto, Toshiro; Arita, Kazunori

2016-08-01

The Wada test has been the gold standard for determining hemispheric language dominance (HLD) in the presurgical evaluation of patients scheduled for neurosurgical procedures. As it poses inherent risks associated with intra-arterial catheter techniques and as it occasionally fails to indicate language dominance, an alternative reliable test is needed. We quantitatively assessed the results of functional magnetic resonance imaging (fMRI) using the Shiritori task, a Japanese word chain, to identify the threshold for correctly predicting HLD. The subjects were 28 patients with intractable epilepsy scheduled to undergo the Wada test and focus resection. We set the region of interest (ROI) on the bilateral Brodmann areas 44 and 45 (BA 44 and 45). To compare the functional activity at both ROIs we calculated the language laterality index (LI) using the formula: [VL-VR]/[VL+VR]×100, where VL and VR indicated the number of activated voxels in the left and right ROIs, respectively. As 2 patients were excluded due to the lack of activation in either ROI, the final study population consisted of 26 patients. By the Wada test, HLD was left in 20, right in 3, and equivocal in 3. At a cut-off of LI+50, the predictive sensitivity and specificity for left HLD were 85% (17/20) and 100%; right HLD was predicted in a single patient (sensitivity 33.3%, specificity 100%). The fMRI using the Shiritori task showed good activation in ROI of BA 44 and 45. At a cut-off of LI+50, LI of BA 44 and 45 predicted HLD identified by the Wada test with high specificity. Copyright © 2016 Elsevier B.V. All rights reserved.

Real-time shear wave elastography may predict autoimmune thyroid disease.

PubMed

Vlad, Mihaela; Golu, Ioana; Bota, Simona; Vlad, Adrian; Timar, Bogdan; Timar, Romulus; Sporea, Ioan

2015-05-01

To evaluate and compare the values of the elasticity index as measured by shear wave elastography in healthy subjects and in patients with autoimmune thyroid disease, in order to establish if this investigation can predict the occurrence of autoimmune thyroid disease. A total of 104 cases were included in the study group: 91 women (87.5%), out of which 52 (50%) with autoimmune thyroid disease diagnosed by specific tests and 52 (50%) healthy volunteers, matched for age and gender. For all the subjects, three measurements were performed on each thyroid lobe and a mean value was calculated. The data were expressed in kPa. The investigation was performed with an Aixplorer system (SuperSonic Imagine, France), using a linear high-resolution 15-4 MHz transducer. The mean value for the elasticity index was similar in the right and the left thyroid lobes, both in normal subjects and in patients with autoimmune thyroid disease: 19.6 ± 6.6 vs. 19.5 ± 6.8 kPa, p = 0.92, and 26.6 ± 10.0 vs. 25.8 ± 11.7 kPa, p = 0.71, respectively. This parameter was significantly higher in patients with autoimmune thyroid disease than in controls (p < 0.001). For a cut-off value of 22.3 kPa, which resulted in the highest sum of sensitivity and specificity, the elasticity index assessed by shear wave elastography had a sensitivity of 59.6% and a specificity of 76.9% (AUROC = 0.71; p < 0.001) for predicting the presence of autoimmune thyroid disease. Quantitative elasticity index measured by shear wave elastography was significantly higher in autoimmune thyroid disease than in normal thyroid parenchyma and may predict the presence of autoimmune thyroid disease.

Defining age- and lactocrine-sensitive elements of the neonatal porcine uterine microRNA–mRNA interactome†,‡

PubMed Central

George, Ashley F.; Rahman, Kathleen M.; Camp, Meredith E.; Prasad, Nripesh; Bartol, Frank F.; Bagnell, Carol A.

2017-01-01

Abstract Factors delivered to offspring in colostrum within 2 days of birth support neonatal porcine uterine development. The uterine mRNA transcriptome is affected by age and nursing during this period. Whether uterine microRNA (miRNA) expression is affected similarly is unknown. Objectives were to (1) determine effects of age and nursing on porcine uterine miRNA expression between birth and postnatal day (PND) 2 using miRNA sequencing (miRNAseq) and; (2) define affected miRNA–mRNA interactions and associated biological processes using integrated target prediction analysis. At birth (PND 0), gilts were euthanized, nursed ad libitum, or gavage-fed milk replacer for 48 h. Uteri were collected at birth or 50 h postnatal. MicroRNAseq data were validated using quantitative real-time PCR. Targets were predicted using an established mRNA database generated from the same tissues. For PND 2 versus PND 0 comparisons, 31 differentially expressed (DE) miRNAs were identified for nursed, and 42 DE miRNAs were identified for replacer-fed gilts. Six DE miRNAs were identified for nursed versus replacer-fed gilts on PND 2. Target prediction for inversely correlated DE miRNA–mRNA pairings indicated 20 miRNAs targeting 251 mRNAs in nursed, versus 29 miRNAs targeting 585 mRNAs in replacer-fed gilts for PND 2 versus PND 0 comparisons, and 5 miRNAs targeting 81 mRNAs for nursed versus replacer-fed gilts on PND 2. Biological processes predicted to be affected by age and nursing included cell-to-cell signaling, cell morphology, and tissue morphology. Results indicate novel age- and lactocrine-sensitive miRNA–mRNA relationships associated with porcine neonatal uterine development between birth and PND 2. PMID:28203709

Probabilistic prediction of barrier-island response to hurricanes

USGS Publications Warehouse

Plant, Nathaniel G.; Stockdon, Hilary F.

2012-01-01

Prediction of barrier-island response to hurricane attack is important for assessing the vulnerability of communities, infrastructure, habitat, and recreational assets to the impacts of storm surge, waves, and erosion. We have demonstrated that a conceptual model intended to make qualitative predictions of the type of beach response to storms (e.g., beach erosion, dune erosion, dune overwash, inundation) can be reformulated in a Bayesian network to make quantitative predictions of the morphologic response. In an application of this approach at Santa Rosa Island, FL, predicted dune-crest elevation changes in response to Hurricane Ivan explained about 20% to 30% of the observed variance. An extended Bayesian network based on the original conceptual model, which included dune elevations, storm surge, and swash, but with the addition of beach and dune widths as input variables, showed improved skill compared to the original model, explaining 70% of dune elevation change variance and about 60% of dune and shoreline position change variance. This probabilistic approach accurately represented prediction uncertainty (measured with the log likelihood ratio), and it outperformed the baseline prediction (i.e., the prior distribution based on the observations). Finally, sensitivity studies demonstrated that degrading the resolution of the Bayesian network or removing data from the calibration process reduced the skill of the predictions by 30% to 40%. The reduction in skill did not change conclusions regarding the relative importance of the input variables, and the extended model's skill always outperformed the original model.

Detection and Analysis of Enamel Cracks by Quantitative Light-induced Fluorescence Technology.

PubMed

Jun, Mi-Kyoung; Ku, Hye-Min; Kim, Euiseong; Kim, Hee-Eun; Kwon, Ho-Keun; Kim, Baek-Il

2016-03-01

The ability to accurately detect tooth cracks and quantify their depth would allow the prediction of crack progression and treatment success. The aim of this in vitro study was to determine the capabilities of quantitative light-induced fluorescence (QLF) technology in the detection of enamel cracks. Ninety-six extracted human teeth were selected for examining naturally existing or suspected cracked teeth surfaces using a photocuring unit. QLF performed with a digital camera (QLF-D) images were used to assess the ability to detect enamel cracks based on the maximum fluorescence loss value (ΔFmax, %), which was then analyzed using the QLF-D software. A histologic evaluation was then performed in which the samples were sectioned and observed with the aid of a polarized light microscope. The relationship between ΔFmax and the histology findings was assessed based on the Spearman rank correlation. The sensitivity and specificity were calculated to evaluate the validity of using QLF-D to analyze enamel inner-half cracks and cracks extending to the dentin-enamel junction. There was a strong correlation between the results of histologic evaluations of enamel cracks and the ΔFmax value, with a correlation coefficient of 0.84. The diagnostic accuracy of QLF-D had a sensitivity of 0.87 and a specificity of 0.98 for enamel inner-half cracks and a sensitivity of 0.90 and a specificity of 1.0 for cracks extending to the dentin-enamel junction. These results indicate that QLF technology would be a useful clinical tool for diagnosing enamel cracks, especially given that this is a nondestructive method. Copyright © 2016 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Development of Conventional and Real-Time Quantitative PCR Assays for Diagnosis and Monitoring of Scabies

PubMed Central

Wong, Samson S. Y.; Poon, Rosana W. S.; Chau, Sandy; Wong, Sally C. Y.; To, Kelvin K. W.; Cheng, Vincent C. C.; Fung, Kitty S. C.

2015-01-01

Scabies remains the most prevalent, endemic, and neglected ectoparasitic infestation globally and can cause institutional outbreaks. The sensitivity of routine microscopy for demonstration of Sarcoptes scabiei mites or eggs in skin scrapings is only about 50%. Except for three studies using conventional or two-tube nested PCR on a small number of cases, no systematic study has been performed to improve the laboratory diagnosis of this important infection. We developed a conventional and a real-time quantitative PCR (qPCR) assay based on the mitochondrial cytochrome c oxidase subunit 1 (cox1) gene of S. scabiei. The cox1 gene is relatively well conserved, with its sequence having no high levels of similarity to the sequences of other human skin mites, pathogenic zoonotic mites, or common house dust mite species. This mitochondrial gene is also present in large quantities in arthropod cells, potentially improving the sensitivity of a PCR-based assay. In our study, both assays were specific and were more sensitive than microscopy in diagnosing scabies, with positive and negative predictive values of 100%. The S. scabiei DNA copy number in the microscopy-positive specimens was significantly higher than that in the microscopy-negative specimens (median S. scabiei DNA copy number, 3.604 versus 2.457 log10 copies per reaction; P = 0.0213). In the patient with crusted scabies, the qPCR assay performed on lesional skin swabs instead of scrapings revealed that the parasite DNA load took about 2 weeks to become negative after treatment. The utility of using lesional skin swabs as an alternative sample for diagnosis of scabies by PCR should be further evaluated. PMID:25903566

Development of Conventional and Real-Time Quantitative PCR Assays for Diagnosis and Monitoring of Scabies.

PubMed

Wong, Samson S Y; Poon, Rosana W S; Chau, Sandy; Wong, Sally C Y; To, Kelvin K W; Cheng, Vincent C C; Fung, Kitty S C; Yuen, K Y

2015-07-01

Scabies remains the most prevalent, endemic, and neglected ectoparasitic infestation globally and can cause institutional outbreaks. The sensitivity of routine microscopy for demonstration of Sarcoptes scabiei mites or eggs in skin scrapings is only about 50%. Except for three studies using conventional or two-tube nested PCR on a small number of cases, no systematic study has been performed to improve the laboratory diagnosis of this important infection. We developed a conventional and a real-time quantitative PCR (qPCR) assay based on the mitochondrial cytochrome c oxidase subunit 1 (cox1) gene of S. scabiei. The cox1 gene is relatively well conserved, with its sequence having no high levels of similarity to the sequences of other human skin mites, pathogenic zoonotic mites, or common house dust mite species. This mitochondrial gene is also present in large quantities in arthropod cells, potentially improving the sensitivity of a PCR-based assay. In our study, both assays were specific and were more sensitive than microscopy in diagnosing scabies, with positive and negative predictive values of 100%. The S. scabiei DNA copy number in the microscopy-positive specimens was significantly higher than that in the microscopy-negative specimens (median S. scabiei DNA copy number, 3.604 versus 2.457 log10 copies per reaction; P = 0.0213). In the patient with crusted scabies, the qPCR assay performed on lesional skin swabs instead of scrapings revealed that the parasite DNA load took about 2 weeks to become negative after treatment. The utility of using lesional skin swabs as an alternative sample for diagnosis of scabies by PCR should be further evaluated. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Third-Kind Encounters in Biomedicine: Immunology Meets Mathematics and Informatics to Become Quantitative and Predictive.

PubMed

Eberhardt, Martin; Lai, Xin; Tomar, Namrata; Gupta, Shailendra; Schmeck, Bernd; Steinkasserer, Alexander; Schuler, Gerold; Vera, Julio

2016-01-01

The understanding of the immune response is right now at the center of biomedical research. There are growing expectations that immune-based interventions will in the midterm provide new, personalized, and targeted therapeutic options for many severe and highly prevalent diseases, from aggressive cancers to infectious and autoimmune diseases. To this end, immunology should surpass its current descriptive and phenomenological nature, and become quantitative, and thereby predictive.Immunology is an ideal field for deploying the tools, methodologies, and philosophy of systems biology, an approach that combines quantitative experimental data, computational biology, and mathematical modeling. This is because, from an organism-wide perspective, the immunity is a biological system of systems, a paradigmatic instance of a multi-scale system. At the molecular scale, the critical phenotypic responses of immune cells are governed by large biochemical networks, enriched in nested regulatory motifs such as feedback and feedforward loops. This network complexity confers them the ability of highly nonlinear behavior, including remarkable examples of homeostasis, ultra-sensitivity, hysteresis, and bistability. Moving from the cellular level, different immune cell populations communicate with each other by direct physical contact or receiving and secreting signaling molecules such as cytokines. Moreover, the interaction of the immune system with its potential targets (e.g., pathogens or tumor cells) is far from simple, as it involves a number of attack and counterattack mechanisms that ultimately constitute a tightly regulated multi-feedback loop system. From a more practical perspective, this leads to the consequence that today's immunologists are facing an ever-increasing challenge of integrating massive quantities from multi-platforms.In this chapter, we support the idea that the analysis of the immune system demands the use of systems-level approaches to ensure the success in the search for more effective and personalized immune-based therapies.

Quantitative analysis of transverse bacterial migration induced by chemotaxis in a packed column with structured physical heterogeneity.

PubMed

Wang, Meng; Ford, Roseanne M

2010-01-15

A two-dimensional mathematical model was developed to simulate transport phenomena of chemotactic bacteria in a sand-packed column designed with structured physical heterogeneity in the presence of a localized chemical source. In contrast to mathematical models in previous research work, in which bacteria were typically treated as immobile colloids, this model incorporated a convective-like chemotaxis term to represent chemotactic migration. Consistency between experimental observation and model prediction supported the assertions that (1) dispersion-induced microbial transfer between adjacent conductive zones occurred at the interface and had little influence on bacterial transport in the bulk flow of the permeable layers and (2) the enhanced transverse bacterial migration in chemotactic experiments relative to nonchemotactic controls was mainly due to directed migration toward the chemical source zone. On the basis of parameter sensitivity analysis, chemotactic parameters determined in bulk aqueous fluid were adequate to predict the microbial transport in our intermediate-scale porous media system. Additionally, the analysis of adsorption coefficient values supported the observation of a previous study that microbial deposition to the surface of porous media might be decreased under the effect of chemoattractant gradients. By quantitatively describing bacterial transport and distribution in a heterogeneous system, this mathematical model serves to advance our understanding of chemotaxis and motility effects in granular media systems and provides insights for modeling microbial transport in in situ microbial processes.

Quantifying the Risk of Human Toxoplasma gondii Infection Due to Consumption of Domestically Produced Lamb in the United States.

PubMed

Guo, Miao; Mishra, Abhinav; Buchanan, Robert L; Dubey, Jitender P; Hill, Dolores E; Gamble, H Ray; Pradhan, Abani K

2016-07-01

Toxoplasma gondii is a prevalent protozoan parasite worldwide. Human toxoplasmosis is responsible for considerable morbidity and mortality in the United States, and meat products have been identified as an important source of T. gondii infections in humans. The goal of this study was to develop a farm-to-table quantitative microbial risk assessment model to predict the public health burden in the United States associated with consumption of U.S. domestically produced lamb. T. gondii prevalence in market lambs was pooled from the 2011 National Animal Health Monitoring System survey, and the concentration of the infectious life stage (bradyzoites) was calculated in the developed model. A log-linear regression and an exponential doseresponse model were used to model the reduction of T. gondii during home cooking and to predict the probability of infection, respectively. The mean probability of infection per serving of lamb was estimated to be 1.5 cases per 100,000 servings, corresponding to ∼6,300 new infections per year in the U.S. Based on the sensitivity analysis, we identified cooking as the most effective method to influence human health risk. This study provided a quantitative microbial risk assessment framework for T. gondii infection through consumption of lamb and quantified the infection risk and public health burden associated with lamb consumption.

PREDICTING TOXICOLOGICAL ENDPOINTS OF CHEMICALS USING QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS (QSARS)

EPA Science Inventory

Quantitative structure-activity relationships (QSARs) are being developed to predict the toxicological endpoints for untested chemicals similar in structure to chemicals that have known experimental toxicological data. Based on a very large number of predetermined descriptors, a...

Large-scale exploration and analysis of drug combinations.

PubMed

Li, Peng; Huang, Chao; Fu, Yingxue; Wang, Jinan; Wu, Ziyin; Ru, Jinlong; Zheng, Chunli; Guo, Zihu; Chen, Xuetong; Zhou, Wei; Zhang, Wenjuan; Li, Yan; Chen, Jianxin; Lu, Aiping; Wang, Yonghua

2015-06-15

Drug combinations are a promising strategy for combating complex diseases by improving the efficacy and reducing corresponding side effects. Currently, a widely studied problem in pharmacology is to predict effective drug combinations, either through empirically screening in clinic or pure experimental trials. However, the large-scale prediction of drug combination by a systems method is rarely considered. We report a systems pharmacology framework to predict drug combinations (PreDCs) on a computational model, termed probability ensemble approach (PEA), for analysis of both the efficacy and adverse effects of drug combinations. First, a Bayesian network integrating with a similarity algorithm is developed to model the combinations from drug molecular and pharmacological phenotypes, and the predictions are then assessed with both clinical efficacy and adverse effects. It is illustrated that PEA can predict the combination efficacy of drugs spanning different therapeutic classes with high specificity and sensitivity (AUC = 0.90), which was further validated by independent data or new experimental assays. PEA also evaluates the adverse effects (AUC = 0.95) quantitatively and detects the therapeutic indications for drug combinations. Finally, the PreDC database includes 1571 known and 3269 predicted optimal combinations as well as their potential side effects and therapeutic indications. The PreDC database is available at http://sm.nwsuaf.edu.cn/lsp/predc.php. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

ADC as a useful diagnostic tool for differentiating benign and malignant vertebral bone marrow lesions and compression fractures: a systematic review and meta-analysis.

PubMed

Suh, Chong Hyun; Yun, Seong Jong; Jin, Wook; Lee, Sun Hwa; Park, So Young; Ryu, Chang-Woo

2018-07-01

To assess the sensitivity and specificity of quantitative assessment of the apparent diffusion coefficient (ADC) for differentiating benign and malignant vertebral bone marrow lesions (BMLs) and compression fractures (CFs) METHODS: An electronic literature search of MEDLINE and EMBASE was conducted. Bivariate modelling and hierarchical summary receiver operating characteristic modelling were performed to evaluate the diagnostic performance of ADC for differentiating vertebral BMLs. Subgroup analysis was performed for differentiating benign and malignant vertebral CFs. Meta-regression analyses according to subject, study and diffusion-weighted imaging (DWI) characteristics were performed. Twelve eligible studies (748 lesions, 661 patients) were included. The ADC exhibited a pooled sensitivity of 0.89 (95% confidence interval [CI] 0.80-0.94) and a pooled specificity of 0.87 (95% CI 0.78-0.93) for differentiating benign and malignant vertebral BMLs. In addition, the pooled sensitivity and specificity for differentiating benign and malignant CFs were 0.92 (95% CI 0.82-0.97) and 0.91 (95% CI 0.87-0.94), respectively. In the meta-regression analysis, the DWI slice thickness was a significant factor affecting heterogeneity (p < 0.01); thinner slice thickness (< 5 mm) showed higher specificity (95%) than thicker slice thickness (81%). Quantitative assessment of ADC is a useful diagnostic tool for differentiating benign and malignant vertebral BMLs and CFs. • Quantitative assessment of ADC is useful in differentiating vertebral BMLs. • Quantitative ADC assessment for BMLs had sensitivity of 89%, specificity of 87%. • Quantitative ADC assessment for CFs had sensitivity of 92%, specificity of 91%. • The specificity is highest (95%) with thinner (< 5 mm) DWI slice thickness.

Targeted Quantitation of Proteins by Mass Spectrometry

PubMed Central

2013-01-01

Quantitative measurement of proteins is one of the most fundamental analytical tasks in a biochemistry laboratory, but widely used immunochemical methods often have limited specificity and high measurement variation. In this review, we discuss applications of multiple-reaction monitoring (MRM) mass spectrometry, which allows sensitive, precise quantitative analyses of peptides and the proteins from which they are derived. Systematic development of MRM assays is permitted by databases of peptide mass spectra and sequences, software tools for analysis design and data analysis, and rapid evolution of tandem mass spectrometer technology. Key advantages of MRM assays are the ability to target specific peptide sequences, including variants and modified forms, and the capacity for multiplexing that allows analysis of dozens to hundreds of peptides. Different quantitative standardization methods provide options that balance precision, sensitivity, and assay cost. Targeted protein quantitation by MRM and related mass spectrometry methods can advance biochemistry by transforming approaches to protein measurement. PMID:23517332

Targeted quantitation of proteins by mass spectrometry.

PubMed

Liebler, Daniel C; Zimmerman, Lisa J

2013-06-04

Quantitative measurement of proteins is one of the most fundamental analytical tasks in a biochemistry laboratory, but widely used immunochemical methods often have limited specificity and high measurement variation. In this review, we discuss applications of multiple-reaction monitoring (MRM) mass spectrometry, which allows sensitive, precise quantitative analyses of peptides and the proteins from which they are derived. Systematic development of MRM assays is permitted by databases of peptide mass spectra and sequences, software tools for analysis design and data analysis, and rapid evolution of tandem mass spectrometer technology. Key advantages of MRM assays are the ability to target specific peptide sequences, including variants and modified forms, and the capacity for multiplexing that allows analysis of dozens to hundreds of peptides. Different quantitative standardization methods provide options that balance precision, sensitivity, and assay cost. Targeted protein quantitation by MRM and related mass spectrometry methods can advance biochemistry by transforming approaches to protein measurement.

Quantitative Real-Time Legionella PCR for Environmental Water Samples: Data Interpretation

PubMed Central

Joly, Philippe; Falconnet, Pierre-Alain; André, Janine; Weill, Nicole; Reyrolle, Monique; Vandenesch, François; Maurin, Max; Etienne, Jerome; Jarraud, Sophie

2006-01-01

Quantitative Legionella PCRs targeting the 16S rRNA gene (specific for the genus Legionella) and the mip gene (specific for the species Legionella pneumophila) were applied to a total of 223 hot water system samples (131 in one laboratory and 92 in another laboratory) and 37 cooling tower samples (all in the same laboratory). The PCR results were compared with those of conventional culture. 16S rRNA gene PCR results were nonquantifiable for 2.8% of cooling tower samples and up to 39.1% of hot water system samples, and this was highly predictive of Legionella CFU counts below 250/liter. PCR cutoff values for identifying hot water system samples containing >103 CFU/liter legionellae were determined separately in each laboratory. The cutoffs differed widely between the laboratories and had sensitivities from 87.7 to 92.9% and specificities from 77.3 to 96.5%. The best specificity was obtained with mip PCR. PCR cutoffs could not be determined for cooling tower samples, as the results were highly variable and often high for culture-negative samples. Thus, quantitative Legionella PCR appears to be applicable to samples from hot water systems, but the positivity cutoff has to be determined in each laboratory. PMID:16597985

Phenotypic characterization of glioblastoma identified through shape descriptors

NASA Astrophysics Data System (ADS)

Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

2016-03-01

This paper proposes quantitatively describing the shape of glioblastoma (GBM) tissue phenotypes as a set of shape features derived from segmentations, for the purposes of discriminating between GBM phenotypes and monitoring tumor progression. GBM patients were identified from the Cancer Genome Atlas, and quantitative MR imaging data were obtained from the Cancer Imaging Archive. Three GBM tissue phenotypes are considered including necrosis, active tumor and edema/invasion. Volumetric tissue segmentations are obtained from registered T1˗weighted (T1˗WI) postcontrast and fluid-attenuated inversion recovery (FLAIR) MRI modalities. Shape features are computed from respective tissue phenotype segmentations, and a Kruskal-Wallis test was employed to select features capable of classification with a significance level of p < 0.05. Several classifier models are employed to distinguish phenotypes, where a leave-one-out cross-validation was performed. Eight features were found statistically significant for classifying GBM phenotypes with p <0.05, orientation is uninformative. Quantitative evaluations show the SVM results in the highest classification accuracy of 87.50%, sensitivity of 94.59% and specificity of 92.77%. In summary, the shape descriptors proposed in this work show high performance in predicting GBM tissue phenotypes. They are thus closely linked to morphological characteristics of GBM phenotypes and could potentially be used in a computer assisted labeling system.

Sensitivity to envelope-based interaural delays at high frequencies: center frequency affects the envelope rate-limitation.

PubMed

Bernstein, Leslie R; Trahiotis, Constantine

2014-02-01

Sensitivity to ongoing interaural temporal disparities (ITDs) was measured using bandpass-filtered pulse trains centered at 4600, 6500, or 9200 Hz. Save for minor differences in the exact center frequencies, those target stimuli were those employed by Majdak and Laback [J. Acoust. Soc. Am. 125, 3903-3913 (2009)]. At each center frequency, threshold ITD was measured for pulse repetition rates ranging from 64 to 609 Hz. The results and quantitative predictions by a cross-correlation-based model indicated that (1) at most pulse repetition rates, threshold ITD increased with center frequency, (2) the cutoff frequency of the putative envelope low-pass filter that determines sensitivity to ITD at high envelope rates appears to be inversely related to center frequency, and (3) both outcomes were accounted for by assuming that, independent of the center frequency, the listeners' decision variable was a constant criterion change in interaural correlation of the stimuli as processed internally. The finding of an inverse relation between center frequency and the envelope rate limitation, while consistent with much prior literature, runs counter to the conclusion reached by Majdak and Laback.

Deriving a no expected sensitization induction level for fragrance ingredients without animal testing: An integrated approach applied to specific case studies.

PubMed

Natsch, Andreas; Emter, Roger; Haupt, Tina; Ellis, Graham

2018-06-01

Cosmetic regulations prohibit animal testing for the purpose of safety assessment and recent REACH guidance states that the local lymph node assay (LLNA) in mice shall only be conducted if in vitro data cannot give sufficient information for classification and labelling. However, Quantitative Risk Assessment (QRA) for fragrance ingredients requires a NESIL, a dose not expected to cause induction of skin sensitization in humans. In absence of human data, this is derived from the LLNA and it remains a key challenge for risk assessors to derive this value from non-animal data. Here we present a workflow using structural information, reactivity data and KeratinoSens results to predict a LLNA result as a point of departure. Specific additional tests (metabolic activation, complementary reactivity tests) are applied in selected cases depending on the chemical domain of a molecule. Finally, in vitro and in vivo data on close analogues are used to estimate uncertainty of the prediction in the specific chemical domain. This approach was applied to three molecules which were subsequently tested in the LLNA and 22 molecules with available and sometimes discordant human and LLNA data. Four additional case studies illustrate how this approach is being applied to recently developed molecules in the absence of animal data. Estimation of uncertainty and how this can be applied to determine a final NESIL for risk assessment is discussed. We conclude that, in the data-rich domain of fragrance ingredients, sensitization risk assessment without animal testing is possible in most cases by this integrated approach.

Diagnostic accuracy of semi-quantitative and quantitative culture techniques for the diagnosis of catheter-related infections in newborns and molecular typing of isolated microorganisms.

PubMed

Riboli, Danilo Flávio Moraes; Lyra, João César; Silva, Eliane Pessoa; Valadão, Luisa Leite; Bentlin, Maria Regina; Corrente, José Eduardo; Rugolo, Ligia Maria Suppo de Souza; da Cunha, Maria de Lourdes Ribeiro de Souza

2014-05-22

Catheter-related bloodstream infections (CR-BSIs) have become the most common cause of healthcare-associated bloodstream infections in neonatal intensive care units (ICUs). Microbiological evidence implicating catheters as the source of bloodstream infection is necessary to establish the diagnosis of CR-BSIs. Semi-quantitative culture is used to determine the presence of microorganisms on the external catheter surface, whereas quantitative culture also isolates microorganisms present inside the catheter. The main objective of this study was to determine the sensitivity and specificity of these two techniques for the diagnosis of CR-BSIs in newborns from a neonatal ICU. In addition, PFGE was used for similarity analysis of the microorganisms isolated from catheters and blood cultures. Semi-quantitative and quantitative methods were used for the culture of catheter tips obtained from newborns. Strains isolated from catheter tips and blood cultures which exhibited the same antimicrobial susceptibility profile were included in the study as positive cases of CR-BSI. PFGE of the microorganisms isolated from catheters and blood cultures was performed for similarity analysis and detection of clones in the ICU. A total of 584 catheter tips from 399 patients seen between November 2005 and June 2012 were analyzed. Twenty-nine cases of CR-BSI were confirmed. Coagulase-negative staphylococci (CoNS) were the most frequently isolated microorganisms, including S. epidermidis as the most prevalent species (65.5%), followed by S. haemolyticus (10.3%), yeasts (10.3%), K. pneumoniae (6.9%), S. aureus (3.4%), and E. coli (3.4%). The sensitivity of the semi-quantitative and quantitative techniques was 72.7% and 59.3%, respectively, and specificity was 95.7% and 94.4%. The diagnosis of CR-BSIs based on PFGE analysis of similarity between strains isolated from catheter tips and blood cultures showed 82.6% sensitivity and 100% specificity. The semi-quantitative culture method showed higher sensitivity and specificity for the diagnosis of CR-BSIs in newborns when compared to the quantitative technique. In addition, this method is easier to perform and shows better agreement with the gold standard, and should therefore be recommended for routine clinical laboratory use. PFGE may contribute to the control of CR-BSIs by identifying clusters of microorganisms in neonatal ICUs, providing a means of determining potential cross-infection between patients.

National Centers for Environmental Prediction

Science.gov Websites

ENSEMBLE PRODUCTS & DATA SOURCES Probabilistic Forecasts of Quantitative Precipitation from the NCEP Predictability Research with Indian Monsoon Examples - PDF - 28 Mar 2005 North American Ensemble Forecast System QUANTITATIVE PRECIPITATION *PQPF* In these charts, the probability that 24-hour precipitation amounts over a

Uncertainty and sensitivity assessments of an agricultural-hydrological model (RZWQM2) using the GLUE method

NASA Astrophysics Data System (ADS)

Sun, Mei; Zhang, Xiaolin; Huo, Zailin; Feng, Shaoyuan; Huang, Guanhua; Mao, Xiaomin

2016-03-01

Quantitatively ascertaining and analyzing the effects of model uncertainty on model reliability is a focal point for agricultural-hydrological models due to more uncertainties of inputs and processes. In this study, the generalized likelihood uncertainty estimation (GLUE) method with Latin hypercube sampling (LHS) was used to evaluate the uncertainty of the RZWQM-DSSAT (RZWQM2) model outputs responses and the sensitivity of 25 parameters related to soil properties, nutrient transport and crop genetics. To avoid the one-sided risk of model prediction caused by using a single calibration criterion, the combined likelihood (CL) function integrated information concerning water, nitrogen, and crop production was introduced in GLUE analysis for the predictions of the following four model output responses: the total amount of water content (T-SWC) and the nitrate nitrogen (T-NIT) within the 1-m soil profile, the seed yields of waxy maize (Y-Maize) and winter wheat (Y-Wheat). In the process of evaluating RZWQM2, measurements and meteorological data were obtained from a field experiment that involved a winter wheat and waxy maize crop rotation system conducted from 2003 to 2004 in southern Beijing. The calibration and validation results indicated that RZWQM2 model can be used to simulate the crop growth and water-nitrogen migration and transformation in wheat-maize crop rotation planting system. The results of uncertainty analysis using of GLUE method showed T-NIT was sensitive to parameters relative to nitrification coefficient, maize growth characteristics on seedling period, wheat vernalization period, and wheat photoperiod. Parameters on soil saturated hydraulic conductivity, nitrogen nitrification and denitrification, and urea hydrolysis played an important role in crop yield component. The prediction errors for RZWQM2 outputs with CL function were relatively lower and uniform compared with other likelihood functions composed of individual calibration criterion. This new and successful application of the GLUE method for determining the uncertainty and sensitivity of the RZWQM2 could provide a reference for the optimization of model parameters with different emphases according to research interests.

Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

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

Alves, Vinicius M.; Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599; Muratov, Eugene

Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putativemore » sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using Random Forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers was 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR Toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the Scorecard database of possible skin or sense organ toxicants as primary candidates for experimental validation. - Highlights: • It was compiled the largest publicly-available skin sensitization dataset. • Predictive QSAR models were developed for skin sensitization. • Developed models have higher prediction accuracy than OECD QSAR Toolbox. • Putative chemical hazards in the Scorecard database were found using our models.« less

Quantitative optical metrology with CMOS cameras

NASA Astrophysics Data System (ADS)

Furlong, Cosme; Kolenovic, Ervin; Ferguson, Curtis F.

2004-08-01

Recent advances in laser technology, optical sensing, and computer processing of data, have lead to the development of advanced quantitative optical metrology techniques for high accuracy measurements of absolute shapes and deformations of objects. These techniques provide noninvasive, remote, and full field of view information about the objects of interest. The information obtained relates to changes in shape and/or size of the objects, characterizes anomalies, and provides tools to enhance fabrication processes. Factors that influence selection and applicability of an optical technique include the required sensitivity, accuracy, and precision that are necessary for a particular application. In this paper, sensitivity, accuracy, and precision characteristics in quantitative optical metrology techniques, and specifically in optoelectronic holography (OEH) based on CMOS cameras, are discussed. Sensitivity, accuracy, and precision are investigated with the aid of National Institute of Standards and Technology (NIST) traceable gauges, demonstrating the applicability of CMOS cameras in quantitative optical metrology techniques. It is shown that the advanced nature of CMOS technology can be applied to challenging engineering applications, including the study of rapidly evolving phenomena occurring in MEMS and micromechatronics.

Is ozone model bias driven by errors in cloud predictions? A quantitative assessment using satellite cloud retrievals in WRF-Chem

NASA Astrophysics Data System (ADS)

Ryu, Y. H.; Hodzic, A.; Barré, J.; Descombes, G.; Minnis, P.

2017-12-01

Clouds play a key role in radiation and hence O3 photochemistry by modulating photolysis rates and light-dependent emissions of biogenic volatile organic compounds (BVOCs). It is not well known, however, how much of the bias in O3 predictions is caused by inaccurate cloud predictions. This study quantifies the errors in surface O3 predictions associated with clouds in summertime over CONUS using the Weather Research and Forecasting with Chemistry (WRF-Chem) model. Cloud fields used for photochemistry are corrected based on satellite cloud retrievals in sensitivity simulations. It is found that the WRF-Chem model is able to detect about 60% of clouds in the right locations and generally underpredicts cloud optical depths. The errors in hourly O3 due to the errors in cloud predictions can be up to 60 ppb. On average in summertime over CONUS, the errors in 8-h average O3 of 1-6 ppb are found to be attributable to those in cloud predictions under cloudy sky conditions. The contribution of changes in photolysis rates due to clouds is found to be larger ( 80 % on average) than that of light-dependent BVOC emissions. The effects of cloud corrections on O­3 are about 2 times larger in VOC-limited than NOx-limited regimes, suggesting that the benefits of accurate cloud predictions would be greater in VOC-limited than NOx-limited regimes.

A practical approach to the sensitivity analysis for kinetic Monte Carlo simulation of heterogeneous catalysis

DOE PAGES

Hoffmann, Max J.; Engelmann, Felix; Matera, Sebastian

2017-01-31

Lattice kinetic Monte Carlo simulations have become a vital tool for predictive quality atomistic understanding of complex surface chemical reaction kinetics over a wide range of reaction conditions. In order to expand their practical value in terms of giving guidelines for atomic level design of catalytic systems, it is very desirable to readily evaluate a sensitivity analysis for a given model. The result of such a sensitivity analysis quantitatively expresses the dependency of the turnover frequency, being the main output variable, on the rate constants entering the model. In the past the application of sensitivity analysis, such as Degree ofmore » Rate Control, has been hampered by its exuberant computational effort required to accurately sample numerical derivatives of a property that is obtained from a stochastic simulation method. Here in this study we present an efficient and robust three stage approach that is capable of reliably evaluating the sensitivity measures for stiff microkinetic models as we demonstrate using CO oxidation on RuO 2(110) as a prototypical reaction. In a first step, we utilize the Fisher Information Matrix for filtering out elementary processes which only yield negligible sensitivity. Then we employ an estimator based on linear response theory for calculating the sensitivity measure for non-critical conditions which covers the majority of cases. Finally we adopt a method for sampling coupled finite differences for evaluating the sensitivity measure of lattice based models. This allows efficient evaluation even in critical regions near a second order phase transition that are hitherto difficult to control. The combined approach leads to significant computational savings over straightforward numerical derivatives and should aid in accelerating the nano scale design of heterogeneous catalysts.« less

A practical approach to the sensitivity analysis for kinetic Monte Carlo simulation of heterogeneous catalysis.

PubMed

Hoffmann, Max J; Engelmann, Felix; Matera, Sebastian

2017-01-28

Lattice kinetic Monte Carlo simulations have become a vital tool for predictive quality atomistic understanding of complex surface chemical reaction kinetics over a wide range of reaction conditions. In order to expand their practical value in terms of giving guidelines for the atomic level design of catalytic systems, it is very desirable to readily evaluate a sensitivity analysis for a given model. The result of such a sensitivity analysis quantitatively expresses the dependency of the turnover frequency, being the main output variable, on the rate constants entering the model. In the past, the application of sensitivity analysis, such as degree of rate control, has been hampered by its exuberant computational effort required to accurately sample numerical derivatives of a property that is obtained from a stochastic simulation method. In this study, we present an efficient and robust three-stage approach that is capable of reliably evaluating the sensitivity measures for stiff microkinetic models as we demonstrate using the CO oxidation on RuO 2 (110) as a prototypical reaction. In the first step, we utilize the Fisher information matrix for filtering out elementary processes which only yield negligible sensitivity. Then we employ an estimator based on the linear response theory for calculating the sensitivity measure for non-critical conditions which covers the majority of cases. Finally, we adapt a method for sampling coupled finite differences for evaluating the sensitivity measure for lattice based models. This allows for an efficient evaluation even in critical regions near a second order phase transition that are hitherto difficult to control. The combined approach leads to significant computational savings over straightforward numerical derivatives and should aid in accelerating the nano-scale design of heterogeneous catalysts.

A practical approach to the sensitivity analysis for kinetic Monte Carlo simulation of heterogeneous catalysis

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

Hoffmann, Max J.; Engelmann, Felix; Matera, Sebastian

Lattice kinetic Monte Carlo simulations have become a vital tool for predictive quality atomistic understanding of complex surface chemical reaction kinetics over a wide range of reaction conditions. In order to expand their practical value in terms of giving guidelines for atomic level design of catalytic systems, it is very desirable to readily evaluate a sensitivity analysis for a given model. The result of such a sensitivity analysis quantitatively expresses the dependency of the turnover frequency, being the main output variable, on the rate constants entering the model. In the past the application of sensitivity analysis, such as Degree ofmore » Rate Control, has been hampered by its exuberant computational effort required to accurately sample numerical derivatives of a property that is obtained from a stochastic simulation method. Here in this study we present an efficient and robust three stage approach that is capable of reliably evaluating the sensitivity measures for stiff microkinetic models as we demonstrate using CO oxidation on RuO 2(110) as a prototypical reaction. In a first step, we utilize the Fisher Information Matrix for filtering out elementary processes which only yield negligible sensitivity. Then we employ an estimator based on linear response theory for calculating the sensitivity measure for non-critical conditions which covers the majority of cases. Finally we adopt a method for sampling coupled finite differences for evaluating the sensitivity measure of lattice based models. This allows efficient evaluation even in critical regions near a second order phase transition that are hitherto difficult to control. The combined approach leads to significant computational savings over straightforward numerical derivatives and should aid in accelerating the nano scale design of heterogeneous catalysts.« less

A practical approach to the sensitivity analysis for kinetic Monte Carlo simulation of heterogeneous catalysis

NASA Astrophysics Data System (ADS)

Hoffmann, Max J.; Engelmann, Felix; Matera, Sebastian

2017-01-01

Lattice kinetic Monte Carlo simulations have become a vital tool for predictive quality atomistic understanding of complex surface chemical reaction kinetics over a wide range of reaction conditions. In order to expand their practical value in terms of giving guidelines for the atomic level design of catalytic systems, it is very desirable to readily evaluate a sensitivity analysis for a given model. The result of such a sensitivity analysis quantitatively expresses the dependency of the turnover frequency, being the main output variable, on the rate constants entering the model. In the past, the application of sensitivity analysis, such as degree of rate control, has been hampered by its exuberant computational effort required to accurately sample numerical derivatives of a property that is obtained from a stochastic simulation method. In this study, we present an efficient and robust three-stage approach that is capable of reliably evaluating the sensitivity measures for stiff microkinetic models as we demonstrate using the CO oxidation on RuO2(110) as a prototypical reaction. In the first step, we utilize the Fisher information matrix for filtering out elementary processes which only yield negligible sensitivity. Then we employ an estimator based on the linear response theory for calculating the sensitivity measure for non-critical conditions which covers the majority of cases. Finally, we adapt a method for sampling coupled finite differences for evaluating the sensitivity measure for lattice based models. This allows for an efficient evaluation even in critical regions near a second order phase transition that are hitherto difficult to control. The combined approach leads to significant computational savings over straightforward numerical derivatives and should aid in accelerating the nano-scale design of heterogeneous catalysts.

Heterochronic opsin expression due to early light deprivation results in drastically shifted visual sensitivity in a cichlid fish: Possible role of thyroid hormone signaling.

PubMed

Karagic, Nidal; Härer, Andreas; Meyer, Axel; Torres-Dowdall, Julián

2018-06-14

During early ontogeny, visual opsin gene expression in cichlids is influenced by prevailing light regimen. Red light, for example, leads to an early switch from the expression of short-wavelength sensitive to long-wavelength sensitive opsins. Here, we address the influence of light deprivation on opsin expression. Individuals reared in constant darkness during the first 14 days post-hatching (dph) showed a general developmental delay compared with fish reared under a 12:12 hr light-dark cycle (control group). Several characters including pigmentation patterns and eye development, appeared later in dark-reared individuals. Quantitative real-time PCR and fluorescent in situ hybridization at six time points during the 14 days period revealed that fish from the control group expressed opsin genes from 5 dph on and maintained a short-wavelength sensitive phenotype (sws1, rh2b, and rh2a). Onset of opsin expression in dark-reared Midas cichlids was delayed by 4 days and visual sensitivity rapidly progressed toward a long-wavelength sensitive phenotype (sws2b, rh2a, and lws). Shifts in visual sensitivities toward longer wavelengths are mediated by thyroid hormone (TH) in many vertebrates. Compared to control fish, dark-reared individuals showed elevated dio3 expression levels - a validated proxy for TH concentration - suggesting higher circulating TH levels. Despite decelerated overall development, ontogeny of opsin gene expression was accelerated, resulting in retinae with long-wavelength shifted predicted sensitivities compared to light-reared individuals. Indirect evidence suggests that this was due to altered TH metabolism. © 2018 Wiley Periodicals, Inc.

Quantifying the influence of sediment source area sampling on detrital thermochronometer data

NASA Astrophysics Data System (ADS)

Whipp, D. M., Jr.; Ehlers, T. A.; Coutand, I.; Bookhagen, B.

2014-12-01

Detrital thermochronology offers a unique advantage over traditional bedrock thermochronology because of its sensitivity to sediment production and transportation to sample sites. In mountainous regions, modern fluvial sediment is often collected and dated to determine the past (105 to >107 year) exhumation history of the upstream drainage area. Though potentially powerful, the interpretation of detrital thermochronometer data derived from modern fluvial sediment is challenging because of spatial and temporal variations in sediment production and transport, and target mineral concentrations. Thermochronometer age prediction models provide a quantitative basis for data interpretation, but it can be difficult to separate variations in catchment bedrock ages from the effects of variable basin denudation and sediment transport. We present two examples of quantitative data interpretation using detrital thermochronometer data from the Himalaya, focusing on the influence of spatial and temporal variations in basin denudation on predicted age distributions. We combine age predictions from the 3D thermokinematic numerical model Pecube with simple models for sediment sampling in the upstream drainage basin area to assess the influence of variations in sediment production by different geomorphic processes or scaled by topographic metrics. We first consider a small catchment from the central Himalaya where bedrock landsliding appears to have affected the observed muscovite 40Ar/39Ar age distributions. Using a simple model of random landsliding with a power-law landslide frequency-area relationship we find that the sediment residence time in the catchment has a major influence on predicted age distributions. In the second case, we compare observed detrital apatite fission-track age distributions from 16 catchments in the Bhutan Himalaya to ages predicted using Pecube and scaled by various topographic metrics. Preliminary results suggest that predicted age distributions scaled by the rock uplift rate in Pecube are statistically equivalent to the observed age distributions for ~75% of the catchments, but may improve when scaled by local relief or specific stream power weighted by satellite-derived precipitation. Ongoing work is exploring the effect of scaling by other topographic metrics.

Quantitative imaging features of pretreatment CT predict volumetric response to chemotherapy in patients with colorectal liver metastases.

PubMed

Creasy, John M; Midya, Abhishek; Chakraborty, Jayasree; Adams, Lauryn B; Gomes, Camilla; Gonen, Mithat; Seastedt, Kenneth P; Sutton, Elizabeth J; Cercek, Andrea; Kemeny, Nancy E; Shia, Jinru; Balachandran, Vinod P; Kingham, T Peter; Allen, Peter J; DeMatteo, Ronald P; Jarnagin, William R; D'Angelica, Michael I; Do, Richard K G; Simpson, Amber L

2018-06-19

This study investigates whether quantitative image analysis of pretreatment CT scans can predict volumetric response to chemotherapy for patients with colorectal liver metastases (CRLM). Patients treated with chemotherapy for CRLM (hepatic artery infusion (HAI) combined with systemic or systemic alone) were included in the study. Patients were imaged at baseline and approximately 8 weeks after treatment. Response was measured as the percentage change in tumour volume from baseline. Quantitative imaging features were derived from the index hepatic tumour on pretreatment CT, and features statistically significant on univariate analysis were included in a linear regression model to predict volumetric response. The regression model was constructed from 70% of data, while 30% were reserved for testing. Test data were input into the trained model. Model performance was evaluated with mean absolute prediction error (MAPE) and R 2 . Clinicopatholologic factors were assessed for correlation with response. 157 patients were included, split into training (n = 110) and validation (n = 47) sets. MAPE from the multivariate linear regression model was 16.5% (R 2 = 0.774) and 21.5% in the training and validation sets, respectively. Stratified by HAI utilisation, MAPE in the validation set was 19.6% for HAI and 25.1% for systemic chemotherapy alone. Clinical factors associated with differences in median tumour response were treatment strategy, systemic chemotherapy regimen, age and KRAS mutation status (p < 0.05). Quantitative imaging features extracted from pretreatment CT are promising predictors of volumetric response to chemotherapy in patients with CRLM. Pretreatment predictors of response have the potential to better select patients for specific therapies. • Colorectal liver metastases (CRLM) are downsized with chemotherapy but predicting the patients that will respond to chemotherapy is currently not possible. • Heterogeneity and enhancement patterns of CRLM can be measured with quantitative imaging. • Prediction model constructed that predicts volumetric response with 20% error suggesting that quantitative imaging holds promise to better select patients for specific treatments.

Quantitative assessment of post-concussion syndrome following mild traumatic brain injury using robotic technology.

PubMed

Subbian, Vignesh; Meunier, Jason M; Korfhagen, Joseph J; Ratcliff, Jonathan J; Shaw, George J; Beyette, Fred R

2014-01-01

Post-Concussion Syndrome (PCS) is a common sequelae of mild Traumatic Brain Injury (mTBI). Currently, there is no reliable test to determine which patients will develop PCS following an mTBI. As a result, clinicians are challenged to identify patients at high risk for subsequent PCS. Hence, there is a need to develop an objective test that can guide clinical risk stratification and predict the likelihood of PCS at the initial point of care in an Emergency Department (ED). This paper presents the results of robotic-assisted neurologic testing completed on mTBI patients in the ED and its ability to predict PCS at 3 weeks post-injury. Preliminary results show that abnormal proprioception, as measured using robotic testing is associated with higher risk of developing PCS following mTBI. In this pilot study, proprioceptive measures obtained through robotic testing had a 77% specificity (95CI: 46%-94%) and a 64% sensitivity (95CI: 41%-82%).

Contamination of packaged food by substances migrating from a direct-contact plastic layer: Assessment using a generic quantitative household scale methodology.

PubMed

Vitrac, Olivier; Challe, Blandine; Leblanc, Jean-Charles; Feigenbaum, Alexandre

2007-01-01

The contamination risk in 12 packaged foods by substances released from the plastic contact layer has been evaluated using a novel modeling technique, which predicts the migration that accounts for (i) possible variations in the time of contact between foodstuffs and packaging and (ii) uncertainty in physico-chemical parameters used to predict migration. Contamination data, which are subject to variability and uncertainty, are derived through a stochastic resolution of transport equations, which control the migration into food. Distributions of contact times between packaging materials and foodstuffs were reconstructed from the volumes and frequencies of purchases of a given panel of 6422 households, making assumptions about household storage behaviour. The risk of contamination of the packaged foods was estimated for styrene (a monomer found in polystyrene yogurt pots) and 2,6-di-tert-butyl-4-hydroxytoluene (a representative of the widely used phenolic antioxidants). The results are analysed and discussed regarding sensitivity of the model to the set parameters and chosen assumptions.

The Effect of Molecular Orientation to Solid-Solid and Melting Transitions

NASA Astrophysics Data System (ADS)

Yazici, Mustafa; Özgan, Şükrü

The thermodynamics of solid-solid and solid-liquid transitions are investigated with an account of the number of molecular orientation. The variations of the positional and orientational orders with the reduced temperature are studied. It is found out that orientational order parameter is very sensitive to the number of allowed orientation. The reduced transition temperatures, volume changes and entropy changes of the phase transitions and theoretical phase diagrams are obtained. The entropy changes of melting transitions for different numbers of allowed orientation of the present model are compared with the theoretical results and some experimental data. The quantitative predictions of the model are compared with experimental results for plastic crystals and agreement between predictions of the model and the experimental results are approximately good. Also, different numbers of allowed orientation D correspond to different experimental results HI, HBr, H2S for D = 2; HBr, CCl4, HI for D = 4; C2H12 for D = 6; CH4, PH3 for D = 20.

Modeling Liver-Related Adverse Effects of Drugs Using kNN QSAR Method

PubMed Central

Rodgers, Amie D.; Zhu, Hao; Fourches, Dennis; Rusyn, Ivan; Tropsha, Alexander

2010-01-01

Adverse effects of drugs (AEDs) continue to be a major cause of drug withdrawals both in development and post-marketing. While liver-related AEDs are a major concern for drug safety, there are few in silico models for predicting human liver toxicity for drug candidates. We have applied the Quantitative Structure Activity Relationship (QSAR) approach to model liver AEDs. In this study, we aimed to construct a QSAR model capable of binary classification (active vs. inactive) of drugs for liver AEDs based on chemical structure. To build QSAR models, we have employed an FDA spontaneous reporting database of human liver AEDs (elevations in activity of serum liver enzymes), which contains data on approximately 500 approved drugs. Approximately 200 compounds with wide clinical data coverage, structural similarity and balanced (40/60) active/inactive ratio were selected for modeling and divided into multiple training/test and external validation sets. QSAR models were developed using the k nearest neighbor method and validated using external datasets. Models with high sensitivity (>73%) and specificity (>94%) for prediction of liver AEDs in external validation sets were developed. To test applicability of the models, three chemical databases (World Drug Index, Prestwick Chemical Library, and Biowisdom Liver Intelligence Module) were screened in silico and the validity of predictions was determined, where possible, by comparing model-based classification with assertions in publicly available literature. Validated QSAR models of liver AEDs based on the data from the FDA spontaneous reporting system can be employed as sensitive and specific predictors of AEDs in pre-clinical screening of drug candidates for potential hepatotoxicity in humans. PMID:20192250

Deep Learning for Prediction of Obstructive Disease From Fast Myocardial Perfusion SPECT: A Multicenter Study.

PubMed

Betancur, Julian; Commandeur, Frederic; Motlagh, Mahsaw; Sharir, Tali; Einstein, Andrew J; Bokhari, Sabahat; Fish, Mathews B; Ruddy, Terrence D; Kaufmann, Philipp; Sinusas, Albert J; Miller, Edward J; Bateman, Timothy M; Dorbala, Sharmila; Di Carli, Marcelo; Germano, Guido; Otaki, Yuka; Tamarappoo, Balaji K; Dey, Damini; Berman, Daniel S; Slomka, Piotr J

2018-03-12

The study evaluated the automatic prediction of obstructive disease from myocardial perfusion imaging (MPI) by deep learning as compared with total perfusion deficit (TPD). Deep convolutional neural networks trained with a large multicenter population may provide improved prediction of per-patient and per-vessel coronary artery disease from single-photon emission computed tomography MPI. A total of 1,638 patients (67% men) without known coronary artery disease, undergoing stress 99m Tc-sestamibi or tetrofosmin MPI with new generation solid-state scanners in 9 different sites, with invasive coronary angiography performed within 6 months of MPI, were studied. Obstructive disease was defined as ≥70% narrowing of coronary arteries (≥50% for left main artery). Left ventricular myocardium was segmented using clinical nuclear cardiology software and verified by an expert reader. Stress TPD was computed using sex- and camera-specific normal limits. Deep learning was trained using raw and quantitative polar maps and evaluated for prediction of obstructive stenosis in a stratified 10-fold cross-validation procedure. A total of 1,018 (62%) patients and 1,797 of 4,914 (37%) arteries had obstructive disease. Area under the receiver-operating characteristic curve for disease prediction by deep learning was higher than for TPD (per patient: 0.80 vs. 0.78; per vessel: 0.76 vs. 0.73: p < 0.01). With deep learning threshold set to the same specificity as TPD, per-patient sensitivity improved from 79.8% (TPD) to 82.3% (deep learning) (p < 0.05), and per-vessel sensitivity improved from 64.4% (TPD) to 69.8% (deep learning) (p < 0.01). Deep learning has the potential to improve automatic interpretation of MPI as compared with current clinical methods. Copyright © 2018 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

The fecal hemoglobin concentration, age and sex test score: Development and external validation of a simple prediction tool for colorectal cancer detection in symptomatic patients.

PubMed

Cubiella, Joaquín; Digby, Jayne; Rodríguez-Alonso, Lorena; Vega, Pablo; Salve, María; Díaz-Ondina, Marta; Strachan, Judith A; Mowat, Craig; McDonald, Paula J; Carey, Francis A; Godber, Ian M; Younes, Hakim Ben; Rodriguez-Moranta, Francisco; Quintero, Enrique; Álvarez-Sánchez, Victoria; Fernández-Bañares, Fernando; Boadas, Jaume; Campo, Rafel; Bujanda, Luis; Garayoa, Ana; Ferrandez, Ángel; Piñol, Virginia; Rodríguez-Alcalde, Daniel; Guardiola, Jordi; Steele, Robert J C; Fraser, Callum G

2017-05-15

Prediction models for colorectal cancer (CRC) detection in symptomatic patients, based on easily obtainable variables such as fecal haemoglobin concentration (f-Hb), age and sex, may simplify CRC diagnosis. We developed, and then externally validated, a multivariable prediction model, the FAST Score, with data from five diagnostic test accuracy studies that evaluated quantitative fecal immunochemical tests in symptomatic patients referred for colonoscopy. The diagnostic accuracy of the Score in derivation and validation cohorts was compared statistically with the area under the curve (AUC) and the Chi-square test. 1,572 and 3,976 patients were examined in these cohorts, respectively. For CRC, the odds ratio (OR) of the variables included in the Score were: age (years): 1.03 (95% confidence intervals (CI): 1.02-1.05), male sex: 1.6 (95% CI: 1.1-2.3) and f-Hb (0-<20 µg Hb/g feces): 2.0 (95% CI: 0.7-5.5), (20-<200 µg Hb/g): 16.8 (95% CI: 6.6-42.0), ≥200 µg Hb/g: 65.7 (95% CI: 26.3-164.1). The AUC for CRC detection was 0.88 (95% CI: 0.85-0.90) in the derivation and 0.91 (95% CI: 0.90-093; p = 0.005) in the validation cohort. At the two Score thresholds with 90% (4.50) and 99% (2.12) sensitivity for CRC, the Score had equivalent sensitivity, although the specificity was higher in the validation cohort (p < 0.001). Accordingly, the validation cohort was divided into three groups: high (21.4% of the cohort, positive predictive value-PPV: 21.7%), intermediate (59.8%, PPV: 0.9%) and low (18.8%, PPV: 0.0%) risk for CRC. The FAST Score is an easy to calculate prediction tool, highly accurate for CRC detection in symptomatic patients. © 2017 UICC.

An Extended Structure-Activity Relationship of Nondioxin-Like PCBs Evaluates and Supports Modeling Predictions and Identifies Picomolar Potency of PCB 202 Towards Ryanodine Receptors.

PubMed

Holland, Erika B; Feng, Wei; Zheng, Jing; Dong, Yao; Li, Xueshu; Lehmler, Hans-Joachim; Pessah, Isaac N

2017-01-01

Nondioxin-like polychlorinated biphenyls (NDL PCBs) activate ryanodine-sensitive Ca 2+  channels (RyRs) and this activation has been associated with neurotoxicity in exposed animals. RyR-active congeners follow a distinct structure-activity relationship and a quantitative structure-activity relationship (QSAR) predicts that a large number of PCBs likely activate the receptor, which requires validation. Additionally, previous structural based conclusions have been established using receptor ligand binding assays but the impact of varying PCB structures on ion channel gating behavior is not understood. We used [ 3 H]Ryanodine ([ 3 H]Ry) binding to assess the RyR-activity of 14 previously untested PCB congeners evaluating the predictability of the QSAR. Congeners determined to display widely varying potency were then assayed with single channel voltage clamp analysis to assess direct influences on channel gating kinetics. The RyR-activity of individual PCBs assessed in in vitro assays followed the general pattern predicted by the QSAR but binding and lipid bilayer experiments demonstrated higher potency than predicted. Of the 49 congeners tested to date, tetra-ortho PCB 202 was found to be the most potent RyR-active congener increasing channel open probability at 200 pM. Shifting meta-substitutions to the para-position resulted in a > 100-fold reduction in potency as seen with PCB 197. Non-ortho PCB 11 was found to lack activity at the receptor supporting a minimum mono-ortho substitution for PCB RyR activity. These findings expand and support previous SAR assessments; where out of the 49 congeners tested to date 42 activate the receptor demonstrating that the RyR is a sensitive and common target of PCBs. © The Author 2016. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Systems engineering and integration: Cost estimation and benefits analysis

NASA Technical Reports Server (NTRS)

Dean, ED; Fridge, Ernie; Hamaker, Joe

1990-01-01

Space Transportation Avionics hardware and software cost has traditionally been estimated in Phase A and B using cost techniques which predict cost as a function of various cost predictive variables such as weight, lines of code, functions to be performed, quantities of test hardware, quantities of flight hardware, design and development heritage, complexity, etc. The output of such analyses has been life cycle costs, economic benefits and related data. The major objectives of Cost Estimation and Benefits analysis are twofold: (1) to play a role in the evaluation of potential new space transportation avionics technologies, and (2) to benefit from emerging technological innovations. Both aspects of cost estimation and technology are discussed here. The role of cost analysis in the evaluation of potential technologies should be one of offering additional quantitative and qualitative information to aid decision-making. The cost analyses process needs to be fully integrated into the design process in such a way that cost trades, optimizations and sensitivities are understood. Current hardware cost models tend to primarily use weights, functional specifications, quantities, design heritage and complexity as metrics to predict cost. Software models mostly use functionality, volume of code, heritage and complexity as cost descriptive variables. Basic research needs to be initiated to develop metrics more responsive to the trades which are required for future launch vehicle avionics systems. These would include cost estimating capabilities that are sensitive to technological innovations such as improved materials and fabrication processes, computer aided design and manufacturing, self checkout and many others. In addition to basic cost estimating improvements, the process must be sensitive to the fact that no cost estimate can be quoted without also quoting a confidence associated with the estimate. In order to achieve this, better cost risk evaluation techniques are needed as well as improved usage of risk data by decision-makers. More and better ways to display and communicate cost and cost risk to management are required.

Histogram analysis of diffusion kurtosis imaging of nasopharyngeal carcinoma: Correlation between quantitative parameters and clinical stage.

PubMed

Xu, Xiao-Quan; Ma, Gao; Wang, Yan-Jun; Hu, Hao; Su, Guo-Yi; Shi, Hai-Bin; Wu, Fei-Yun

2017-07-18

To evaluate the correlation between histogram parameters derived from diffusion-kurtosis (DK) imaging and the clinical stage of nasopharyngeal carcinoma (NPC). High T-stage (T3/4) NPC showed significantly higher Kapp-mean (P = 0.018), Kapp-median (P = 0.029) and Kapp-90th (P = 0.003) than low T-stage (T1/2) NPC. High N-stage NPC (N2/3) showed significantly lower Dapp-mean (P = 0.002), Dapp-median (P = 0.002) and Dapp-10th (P < 0.001) than low N-stage NPC (N0/1). High AJCC-stage NPC (III/IV) showed significantly lower Dapp-10th (P = 0.038) than low AJCC-stage NPC (I/II). ROC analyses indicated that Kapp-90th was optimal for predicting high T-stage (AUC, 0.759; sensitivity, 0.842; specificity, 0.607), while Dapp-10th was best for predicting high N- and AJCC-stage (N-stage, AUC, 0.841; sensitivity, 0.875; specificity, 0.807; AJCC-stage, AUC, 0.671; sensitivity, 0.800; specificity, 0.588). DK imaging data of forty-seven consecutive NPC patients were retrospectively analyzed. Apparent diffusion for Gaussian distribution (Dapp) and apparent kurtosis coefficient (Kapp) were generated using diffusion-kurtosis model. Histogram parameters, including mean, median, 10th, 90th percentiles, skewness and kurtosis of Dapp and Kapp were calculated. Patients were divided into low and high T, N and clinical stage based on American Joint Committee on Cancer (AJCC) staging system. Differences of histogram parameters between low and high T, N and AJCC stages were compared using t test. Multiple receiver operating characteristic (ROC) curves were used to determine and compare the value of significant parameters in predicting high T, N and AJCC stage, respectively. DK imaging-derived parameters correlated well with clinical stage of NPC, therefore could serve as an adjunctive imaging technique for evaluating NPC.

"An integrative formal model of motivation and decision making: The MGPM*": Correction to Ballard et al. (2016).

PubMed

2017-02-01

Reports an error in "An integrative formal model of motivation and decision making: The MGPM*" by Timothy Ballard, Gillian Yeo, Shayne Loft, Jeffrey B. Vancouver and Andrew Neal ( Journal of Applied Psychology , 2016[Sep], Vol 101[9], 1240-1265). Equation A3 contained an error. This correct equation is provided in the erratum. (The following abstract of the original article appeared in record 2016-28692-001.) We develop and test an integrative formal model of motivation and decision making. The model, referred to as the extended multiple-goal pursuit model (MGPM*), is an integration of the multiple-goal pursuit model (Vancouver, Weinhardt, & Schmidt, 2010) and decision field theory (Busemeyer & Townsend, 1993). Simulations of the model generated predictions regarding the effects of goal type (approach vs. avoidance), risk, and time sensitivity on prioritization. We tested these predictions in an experiment in which participants pursued different combinations of approach and avoidance goals under different levels of risk. The empirical results were consistent with the predictions of the MGPM*. Specifically, participants pursuing 1 approach and 1 avoidance goal shifted priority from the approach to the avoidance goal over time. Among participants pursuing 2 approach goals, those with low time sensitivity prioritized the goal with the larger discrepancy, whereas those with high time sensitivity prioritized the goal with the smaller discrepancy. Participants pursuing 2 avoidance goals generally prioritized the goal with the smaller discrepancy. Finally, all of these effects became weaker as the level of risk increased. We used quantitative model comparison to show that the MGPM* explained the data better than the original multiple-goal pursuit model, and that the major extensions from the original model were justified. The MGPM* represents a step forward in the development of a general theory of decision making during multiple-goal pursuit. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Searching for an Accurate Marker-Based Prediction of an Individual Quantitative Trait in Molecular Plant Breeding

PubMed Central

Fu, Yong-Bi; Yang, Mo-Hua; Zeng, Fangqin; Biligetu, Bill

2017-01-01

Molecular plant breeding with the aid of molecular markers has played an important role in modern plant breeding over the last two decades. Many marker-based predictions for quantitative traits have been made to enhance parental selection, but the trait prediction accuracy remains generally low, even with the aid of dense, genome-wide SNP markers. To search for more accurate trait-specific prediction with informative SNP markers, we conducted a literature review on the prediction issues in molecular plant breeding and on the applicability of an RNA-Seq technique for developing function-associated specific trait (FAST) SNP markers. To understand whether and how FAST SNP markers could enhance trait prediction, we also performed a theoretical reasoning on the effectiveness of these markers in a trait-specific prediction, and verified the reasoning through computer simulation. To the end, the search yielded an alternative to regular genomic selection with FAST SNP markers that could be explored to achieve more accurate trait-specific prediction. Continuous search for better alternatives is encouraged to enhance marker-based predictions for an individual quantitative trait in molecular plant breeding. PMID:28729875

Prediction of redox-sensitive cysteines using sequential distance and other sequence-based features.

PubMed

Sun, Ming-An; Zhang, Qing; Wang, Yejun; Ge, Wei; Guo, Dianjing

2016-08-24

Reactive oxygen species can modify the structure and function of proteins and may also act as important signaling molecules in various cellular processes. Cysteine thiol groups of proteins are particularly susceptible to oxidation. Meanwhile, their reversible oxidation is of critical roles for redox regulation and signaling. Recently, several computational tools have been developed for predicting redox-sensitive cysteines; however, those methods either only focus on catalytic redox-sensitive cysteines in thiol oxidoreductases, or heavily depend on protein structural data, thus cannot be widely used. In this study, we analyzed various sequence-based features potentially related to cysteine redox-sensitivity, and identified three types of features for efficient computational prediction of redox-sensitive cysteines. These features are: sequential distance to the nearby cysteines, PSSM profile and predicted secondary structure of flanking residues. After further feature selection using SVM-RFE, we developed Redox-Sensitive Cysteine Predictor (RSCP), a SVM based classifier for redox-sensitive cysteine prediction using primary sequence only. Using 10-fold cross-validation on RSC758 dataset, the accuracy, sensitivity, specificity, MCC and AUC were estimated as 0.679, 0.602, 0.756, 0.362 and 0.727, respectively. When evaluated using 10-fold cross-validation with BALOSCTdb dataset which has structure information, the model achieved performance comparable to current structure-based method. Further validation using an independent dataset indicates it is robust and of relatively better accuracy for predicting redox-sensitive cysteines from non-enzyme proteins. In this study, we developed a sequence-based classifier for predicting redox-sensitive cysteines. The major advantage of this method is that it does not rely on protein structure data, which ensures more extensive application compared to other current implementations. Accurate prediction of redox-sensitive cysteines not only enhances our understanding about the redox sensitivity of cysteine, it may also complement the proteomics approach and facilitate further experimental investigation of important redox-sensitive cysteines.

Quantitative prediction of phase transformations in silicon during nanoindentation

NASA Astrophysics Data System (ADS)

Zhang, Liangchi; Basak, Animesh

2013-08-01

This paper establishes the first quantitative relationship between the phases transformed in silicon and the shape characteristics of nanoindentation curves. Based on an integrated analysis using TEM and unit cell properties of phases, the volumes of the phases emerged in a nanoindentation are formulated as a function of pop-out size and depth of nanoindentation impression. This simple formula enables a fast, accurate and quantitative prediction of the phases in a nanoindentation cycle, which has been impossible before.

DW MRI at 3.0 T versus FDG PET/CT for detection of malignant pulmonary tumors.

PubMed

Zhang, Jian; Cui, Long-Biao; Tang, Xing; Ren, Xin-Ling; Shi, Jie-Ran; Yang, Hai-Nan; Zhang, Yan; Li, Zhi-Kui; Wu, Chang-Gui; Jian, Wen; Zhao, Feng; Ti, Xin-Yu; Yin, Hong

2014-02-01

Emerging evidence suggests that diffusion-weighted magnetic resonance imaging (DW MRI) could be useful for tumor detection with N and M staging of lung cancer in place of fluorine 18 fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT). DW MRI at 3.0 T and FDG PET/CT were performed before therapy in 113 patients with pulmonary nodules. Mean apparent diffusion coefficient (ADC), maximal standardized uptake value (SUVmax ) and Ki-67 scores were assessed. Quantitatively, specificity and accuracy of ADC (91.7 and 92.9%, respectively) were significantly higher than those of SUVmax (66.7 and 77.9% respectively, p < 0.05), although sensitivity was not significantly different between them (93.5 and 83.1%, p > 0.05). Qualitatively, sensitivity, specificity and accuracy of DW MRI (96.1, 83.3 and 92.0%, respectively) were also not significantly different from that of FDG PET/CT (88.3, 83.3 and 86.7%, respectively, p > 0.05). Significant negative correlation was found between Ki-67 score and ADC (r = -0.66, p < 0.05), ADC and SUVmax (r = -0.37, p < 0.05), but not between Ki-67 score and SUVmax (r = -0.11, p > 0.05). In conclusion, quantitative and qualitative assessments for detection of malignant pulmonary tumors with DW MRI at 3.0 T are superior to those with FDG PET/CT. Furthermore, ADC could predict the malignancy of lung cancer. © 2013 UICC.

Quantitative modeling of the dynamics and intracellular trafficking of far-red light-activatable prodrugs: implications in stimuli-responsive drug delivery system.

PubMed

Li, Mengjie; Thapa, Pritam; Rajaputra, Pallavi; Bio, Moses; Peer, Cody J; Figg, William D; You, Youngjae; Woo, Sukyung

2017-12-01

The combination of photodynamic therapy (PDT) with anti-tumor agents is a complimentary strategy to treat local cancers. We developed a unique photosensitizer (PS)-conjugated paclitaxel (PTX) prodrug in which a PS is excited by near-infrared wavelength light to site-specifically release PTX while generating singlet oxygen (SO) to effectively kill cancer cells with both PTX and SO. The aim of the present study was to identify the determinants influencing the combined efficacy of this light-activatable prodrug, especially the bystander killing effects from released PTX. Using PS-conjugated PTX as a model system, we developed a quantitative mathematical model describing the intracellular trafficking. Dynamics of the prodrug and the model predictions were verified with experimental data using human cancer cells in vitro. The sensitivity analysis suggested that parameters related to extracellular concentration of released PTX, prodrug uptake, target engagement, and target abundance are critical in determining the combined killing efficacy of the prodrug. We found that released PTX cytotoxicity was most sensitive to the retention time of the drug in extracellular space. Modulating drug internalization and conjugating the agents targeted to abundant receptors may provide a new strategy for maximizing the killing capacity of the far-red light-activatable prodrug system. These results provide guidance for the design of the PDT combination study in vivo and have implications for other stimuli-responsive drug delivery systems.

Ranking and validation of spallation models for isotopic production cross sections of heavy residua

NASA Astrophysics Data System (ADS)

Sharma, Sushil K.; Kamys, Bogusław; Goldenbaum, Frank; Filges, Detlef

2017-07-01

The production cross sections of isotopically identified residual nuclei of spallation reactions induced by 136Xe projectiles at 500AMeV on hydrogen target were analyzed in a two-step model. The first stage of the reaction was described by the INCL4.6 model of an intranuclear cascade of nucleon-nucleon and pion-nucleon collisions whereas the second stage was analyzed by means of four different models; ABLA07, GEM2, GEMINI++ and SMM. The quality of the data description was judged quantitatively using two statistical deviation factors; the H-factor and the M-factor. It was found that the present analysis leads to a different ranking of models as compared to that obtained from the qualitative inspection of the data reproduction. The disagreement was caused by sensitivity of the deviation factors to large statistical errors present in some of the data. A new deviation factor, the A factor, was proposed, that is not sensitive to the statistical errors of the cross sections. The quantitative ranking of models performed using the A-factor agreed well with the qualitative analysis of the data. It was concluded that using the deviation factors weighted by statistical errors may lead to erroneous conclusions in the case when the data cover a large range of values. The quality of data reproduction by the theoretical models is discussed. Some systematic deviations of the theoretical predictions from the experimental results are observed.

A novel quantitative reverse-transcription PCR (qRT-PCR) for the enumeration of total bacteria, using meat micro-flora as a model.

PubMed

Dolan, Anthony; Burgess, Catherine M; Barry, Thomas B; Fanning, Seamus; Duffy, Geraldine

2009-04-01

A sensitive quantitative reverse-transcription PCR (qRT-PCR) method was developed for enumeration of total bacteria. Using two sets of primers separately to target the ribonuclease-P (RNase P) RNA transcripts of gram positive and gram negative bacteria. Standard curves were generated using SYBR Green I kits for the LightCycler 2.0 instrument (Roche Diagnostics) to allow quantification of mixed microflora in liquid media. RNA standards were used and extracted from known cell equivalents and subsequently converted to cDNA for the construction of standard curves. The number of mixed bacteria in culture was determined by qRT-PCR, and the results correlated (r(2)=0.88, rsd=0.466) with the total viable count over the range from approx. Log(10) 3 to approx. Log(10) 7 CFU ml(-1). The rapid nature of this assay (8 h) and its potential as an alternative method to the standard plate count method to predict total viable counts and shelf life are discussed.

Ultrasound Assessment of Human Meniscus.

PubMed

Viren, Tuomas; Honkanen, Juuso T; Danso, Elvis K; Rieppo, Lassi; Korhonen, Rami K; Töyräs, Juha

2017-09-01

The aim of the present study was to evaluate the applicability of ultrasound imaging to quantitative assessment of human meniscus in vitro. Meniscus samples (n = 26) were harvested from 13 knee joints of non-arthritic human cadavers. Subsequently, three locations (anterior, center and posterior) from each meniscus were imaged with two ultrasound transducers (frequencies 9 and 40 MHz), and quantitative ultrasound parameters were determined. Furthermore, partial-least-squares regression analysis was applied for ultrasound signal to determine the relations between ultrasound scattering and meniscus integrity. Significant correlations between measured and predicted meniscus compositions and mechanical properties were obtained (R 2  = 0.38-0.69, p < 0.05). The relationship between conventional ultrasound parameters and integrity of the meniscus was weaker. To conclude, ultrasound imaging exhibited a potential for evaluation of meniscus integrity. Higher ultrasound frequency combined with multivariate analysis of ultrasound backscattering was found to be the most sensitive for evaluation of meniscus integrity. Copyright © 2017 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Quantitative interpretation of heavy ion effects: Comparison of different systems and endpoints

NASA Astrophysics Data System (ADS)

Kiefer, J.

For a quantitative interpretation of biological heavy ion action the following parameters have to be taken into account: variations of energy depositions in microscopical sites, the dependence of primary lesion formation on local energy density and changes in repairability. They can be studied in objects of different size and with different sensitivities. Results on survival and mutation induction in yeast and in mammalian cells will be compared with theoretical predictions. It is shown that shouldered survival curves of diploid yeast can be adequately described if the final slope is adjusted according to the varying production of primary lesions. This is not the case for mammalian cells where the experiments show a rapid loss of the shoulder with LET, contrary to theoretical expectations. This behaviour is interpreted to mean that the repairability of heavy ion lesions is different in the two systems. Mutation induction is theoretically expected to decrease with higher LET. This is found in yeast but not in mammalian cells where it actually increases. These results suggest a higher rate of misrepair in mammalian cells.

Dynamic Redox Regulation of IL-4 Signaling.

PubMed

Dwivedi, Gaurav; Gran, Margaret A; Bagchi, Pritha; Kemp, Melissa L

2015-11-01

Quantifying the magnitude and dynamics of protein oxidation during cell signaling is technically challenging. Computational modeling provides tractable, quantitative methods to test hypotheses of redox mechanisms that may be simultaneously operative during signal transduction. The interleukin-4 (IL-4) pathway, which has previously been reported to induce reactive oxygen species and oxidation of PTP1B, may be controlled by several other putative mechanisms of redox regulation; widespread proteomic thiol oxidation observed via 2D redox differential gel electrophoresis upon IL-4 treatment suggests more than one redox-sensitive protein implicated in this pathway. Through computational modeling and a model selection strategy that relied on characteristic STAT6 phosphorylation dynamics of IL-4 signaling, we identified reversible protein tyrosine phosphatase (PTP) oxidation as the primary redox regulatory mechanism in the pathway. A systems-level model of IL-4 signaling was developed that integrates synchronous pan-PTP oxidation with ROS-independent mechanisms. The model quantitatively predicts the dynamics of IL-4 signaling over a broad range of new redox conditions, offers novel hypotheses about regulation of JAK/STAT signaling, and provides a framework for interrogating putative mechanisms involving receptor-initiated oxidation.

Dynamic Redox Regulation of IL-4 Signaling

PubMed Central

Dwivedi, Gaurav; Gran, Margaret A.; Bagchi, Pritha; Kemp, Melissa L.

2015-01-01

Quantifying the magnitude and dynamics of protein oxidation during cell signaling is technically challenging. Computational modeling provides tractable, quantitative methods to test hypotheses of redox mechanisms that may be simultaneously operative during signal transduction. The interleukin-4 (IL-4) pathway, which has previously been reported to induce reactive oxygen species and oxidation of PTP1B, may be controlled by several other putative mechanisms of redox regulation; widespread proteomic thiol oxidation observed via 2D redox differential gel electrophoresis upon IL-4 treatment suggests more than one redox-sensitive protein implicated in this pathway. Through computational modeling and a model selection strategy that relied on characteristic STAT6 phosphorylation dynamics of IL-4 signaling, we identified reversible protein tyrosine phosphatase (PTP) oxidation as the primary redox regulatory mechanism in the pathway. A systems-level model of IL-4 signaling was developed that integrates synchronous pan-PTP oxidation with ROS-independent mechanisms. The model quantitatively predicts the dynamics of IL-4 signaling over a broad range of new redox conditions, offers novel hypotheses about regulation of JAK/STAT signaling, and provides a framework for interrogating putative mechanisms involving receptor-initiated oxidation. PMID:26562652

Rejection sensitivity prospectively predicts increased rumination.

PubMed

Pearson, Katherine A; Watkins, Edward R; Mullan, Eugene G

2011-10-01

Converging research findings indicate that rumination is correlated with a specific maladaptive interpersonal style encapsulating submissive (overly-accommodating, non-assertive and self-sacrificing) behaviours, and an attachment orientation characterised by rejection sensitivity. This study examined the prospective longitudinal relationship between rumination, the submissive interpersonal style, and rejection sensitivity by comparing two alternative hypotheses: (a) the submissive interpersonal style and rejection sensitivity prospectively predict increased rumination; (b) rumination prospectively predicts the submissive interpersonal style and rejection sensitivity. Currently depressed (n = 22), previously depressed (n = 42) and never depressed (n = 28) individuals completed self-report measures assessing depressive rumination and key psychosocial measures of interpersonal style and behaviours, at baseline and again six months later. Baseline rejection sensitivity prospectively predicted increased rumination six months later, after statistically controlling for baseline rumination, gender and depression. Baseline rumination did not predict the submissive interpersonal style or rejection sensitivity. The results provide a first step towards delineating a potential casual relationship between rejection sensitivity and rumination, and suggest the potential value of clinical assessment and intervention for both rejection sensitivity and rumination in individuals who present with either difficulty. Copyright © 2011 Elsevier Ltd. All rights reserved.

Quantitative AOP-based predictions for two aromatase inhibitors evaluating the influence of bioaccumulation on prediction accuracy

EPA Science Inventory

The adverse outcome pathway (AOP) framework can be used to support the use of mechanistic toxicology data as a basis for risk assessment. For certain risk contexts this includes defining, quantitative linkages between the molecular initiating event (MIE) and subsequent key events...

Studying Biology to Understand Risk: Dosimetry Models and Quantitative Adverse Outcome Pathways

EPA Science Inventory

Confidence in the quantitative prediction of risk is increased when the prediction is based to as great an extent as possible on the relevant biological factors that constitute the pathway from exposure to adverse outcome. With the first examples now over 40 years old, physiologi...

DOSIMETRY MODELING OF INHALED FORMALDEHYDE: BINNING NASAL FLUX PREDICTIONS FOR QUANTITATIVE RISK ASSESSMENT

EPA Science Inventory

Dosimetry Modeling of Inhaled Formaldehyde: Binning Nasal Flux Predictions for Quantitative Risk Assessment. Kimbell, J.S., Overton, J.H., Subramaniam, R.P., Schlosser, P.M., Morgan, K.T., Conolly, R.B., and Miller, F.J. (2001). Toxicol. Sci. 000, 000:000.

Interspecies e...

Toxicity challenges in environmental chemicals: Prediction of human plasma protein binding through quantitative structure-activity relationship (QSAR) models

EPA Science Inventory

The present study explores the merit of utilizing available pharmaceutical data to construct a quantitative structure-activity relationship (QSAR) for prediction of the fraction of a chemical unbound to plasma protein (Fub) in environmentally relevant compounds. Independent model...

Parameterizing the Logistic Model of Tumor Growth by DW-MRI and DCE-MRI Data to Predict Treatment Response and Changes in Breast Cancer Cellularity during Neoadjuvant Chemotherapy1

PubMed Central

Atuegwu, Nkiruka C; Arlinghaus, Lori R; Li, Xia; Chakravarthy, A Bapsi; Abramson, Vandana G; Sanders, Melinda E; Yankeelov, Thomas E

2013-01-01

Diffusion-weighted and dynamic contrast-enhanced magnetic resonance imaging (MRI) data of 28 patients were obtained pretreatment, after one cycle, and after completion of all cycles of neoadjuvant chemotherapy (NAC). For each patient at each time point, the tumor cell number was estimated using the apparent diffusion coefficient and the extravascular extracellular (ve) and plasma volume (vp) fractions. The proliferation/death rate was obtained using the number of tumor cells from the first two time points in conjunction with the logistic model of tumor growth, which was then used to predict tumor cellularity at the conclusion of NAC. The Pearson correlation coefficient between the predicted and the experimental number of tumor cells measured at the end of NAC was 0.81 (P = .0043). The proliferation rate estimated after the first cycle of therapy was able to separate patients who went on to achieve pathologic complete response from those who did not (P = .021) with a sensitivity and specificity of 82.4% and 72.7%, respectively. These data provide preliminary results indicating that incorporating readily available quantitative MRI data into a simple model of tumor growth can lead to potentially clinically relevant information for predicting an individual patient's response to NAC. PMID:23730404

Causal Genetic Variation Underlying Metabolome Differences.

PubMed

Swain-Lenz, Devjanee; Nikolskiy, Igor; Cheng, Jiye; Sudarsanam, Priya; Nayler, Darcy; Staller, Max V; Cohen, Barak A

2017-08-01

An ongoing challenge in biology is to predict the phenotypes of individuals from their genotypes. Genetic variants that cause disease often change an individual's total metabolite profile, or metabolome. In light of our extensive knowledge of metabolic pathways, genetic variants that alter the metabolome may help predict novel phenotypes. To link genetic variants to changes in the metabolome, we studied natural variation in the yeast Saccharomyces cerevisiae We used an untargeted mass spectrometry method to identify dozens of metabolite Quantitative Trait Loci (mQTL), genomic regions containing genetic variation that control differences in metabolite levels between individuals. We mapped differences in urea cycle metabolites to genetic variation in specific genes known to regulate amino acid biosynthesis. Our functional assays reveal that genetic variation in two genes, AUA1 and ARG81 , cause the differences in the abundance of several urea cycle metabolites. Based on knowledge of the urea cycle, we predicted and then validated a new phenotype: sensitivity to a particular class of amino acid isomers. Our results are a proof-of-concept that untargeted mass spectrometry can reveal links between natural genetic variants and metabolome diversity. The interpretability of our results demonstrates the promise of using genetic variants underlying natural differences in the metabolome to predict novel phenotypes from genotype. Copyright © 2017 by the Genetics Society of America.

Role of serum miRNAs in the prediction of ovarian hyperstimulation syndrome in polycystic ovarian syndrome patients.

PubMed

Zhao, Chun; Liu, Xiaoguang; Shi, Zhonghua; Zhang, Jing; Zhang, Junqiang; Jia, Xuemei; Ling, Xiufeng

2015-01-01

Polycystic ovarian syndrome (PCOS) causes a significantly increased risk of ovarian hyperstimulation syndrome (OHSS). Here, we focused on the altered expression of serum miRNAs and their predictive value for OHSS in PCOS patients. We used the TaqMan low density array followed by individual quantitative reverse transcription-polymerase chain reaction to identify and validate the expression of serum miRNAs in PCOS patients likely to develop severe OHSS. The miR-16 and miR-223 expression levels were significantly reduced in the patients who were likely to develop severe OHSS than in the control subjects who were likely to develop mild or no OHSS. The sensitivity and specificity of the basal LH, basal LH/FSH, and body mass index (BMI) as OHSS predictors were also evaluated. miR-16 was the most efficient for OHSS prediction as it yielded the highest AUC. Logistic binary regression analyses revealed a positive association of miR-223 and BMI. Serum miRNAs are differentially expressed in PCOS patients likely to suffer from severe OHSS. We identified and validated two serum miRNAs that have potential for use as novel noninvasive biomarkers to accurately predict OHSS before controlled ovarian hyperstimulation (COH) for PCOS patients. © 2015 S. Karger AG, Basel.

Computational predictive models for P-glycoprotein inhibition of in-house chalcone derivatives and drug-bank compounds.

PubMed

Ngo, Trieu-Du; Tran, Thanh-Dao; Le, Minh-Tri; Thai, Khac-Minh

2016-11-01

The human P-glycoprotein (P-gp) efflux pump is of great interest for medicinal chemists because of its important role in multidrug resistance (MDR). Because of the high polyspecificity as well as the unavailability of high-resolution X-ray crystal structures of this transmembrane protein, ligand-based, and structure-based approaches which were machine learning, homology modeling, and molecular docking were combined for this study. In ligand-based approach, individual two-dimensional quantitative structure-activity relationship models were developed using different machine learning algorithms and subsequently combined into the Ensemble model which showed good performance on both the diverse training set and the validation sets. The applicability domain and the prediction quality of the developed models were also judged using the state-of-the-art methods and tools. In our structure-based approach, the P-gp structure and its binding region were predicted for a docking study to determine possible interactions between the ligands and the receptor. Based on these in silico tools, hit compounds for reversing MDR were discovered from the in-house and DrugBank databases through virtual screening using prediction models and molecular docking in an attempt to restore cancer cell sensitivity to cytotoxic drugs.

Identification of fidgety movements and prediction of CP by the use of computer-based video analysis is more accurate when based on two video recordings.

PubMed

Adde, Lars; Helbostad, Jorunn; Jensenius, Alexander R; Langaas, Mette; Støen, Ragnhild

2013-08-01

This study evaluates the role of postterm age at assessment and the use of one or two video recordings for the detection of fidgety movements (FMs) and prediction of cerebral palsy (CP) using computer vision software. Recordings between 9 and 17 weeks postterm age from 52 preterm and term infants (24 boys, 28 girls; 26 born preterm) were used. Recordings were analyzed using computer vision software. Movement variables, derived from differences between subsequent video frames, were used for quantitative analysis. Sensitivities, specificities, and area under curve were estimated for the first and second recording, or a mean of both. FMs were classified based on the Prechtl approach of general movement assessment. CP status was reported at 2 years. Nine children developed CP of whom all recordings had absent FMs. The mean variability of the centroid of motion (CSD) from two recordings was more accurate than using only one recording, and identified all children who were diagnosed with CP at 2 years. Age at assessment did not influence the detection of FMs or prediction of CP. The accuracy of computer vision techniques in identifying FMs and predicting CP based on two recordings should be confirmed in future studies.

Genomic prediction of piglet response to infection with one of two porcine reproductive and respiratory syndrome virus isolates.

PubMed

Waide, Emily H; Tuggle, Christopher K; Serão, Nick V L; Schroyen, Martine; Hess, Andrew; Rowland, Raymond R R; Lunney, Joan K; Plastow, Graham; Dekkers, Jack C M

2018-02-01

Genomic prediction of the pig's response to the porcine reproductive and respiratory syndrome (PRRS) virus (PRRSV) would be a useful tool in the swine industry. This study investigated the accuracy of genomic prediction based on porcine SNP60 Beadchip data using training and validation datasets from populations with different genetic backgrounds that were challenged with different PRRSV isolates. Genomic prediction accuracy averaged 0.34 for viral load (VL) and 0.23 for weight gain (WG) following experimental PRRSV challenge, which demonstrates that genomic selection could be used to improve response to PRRSV infection. Training on WG data during infection with a less virulent PRRSV, KS06, resulted in poor accuracy of prediction for WG during infection with a more virulent PRRSV, NVSL. Inclusion of single nucleotide polymorphisms (SNPs) that are in linkage disequilibrium with a major quantitative trait locus (QTL) on chromosome 4 was vital for accurate prediction of VL. Overall, SNPs that were significantly associated with either trait in single SNP genome-wide association analysis were unable to predict the phenotypes with an accuracy as high as that obtained by using all genotyped SNPs across the genome. Inclusion of data from close relatives into the training population increased whole genome prediction accuracy by 33% for VL and by 37% for WG but did not affect the accuracy of prediction when using only SNPs in the major QTL region. Results show that genomic prediction of response to PRRSV infection is moderately accurate and, when using all SNPs on the porcine SNP60 Beadchip, is not very sensitive to differences in virulence of the PRRSV in training and validation populations. Including close relatives in the training population increased prediction accuracy when using the whole genome or SNPs other than those near a major QTL.