Meta-analysis of the relative sensitivity of semi-natural vegetation species to ozone.
Hayes, F; Jones, M L M; Mills, G; Ashmore, M
2007-04-01
This study identified 83 species from existing publications suitable for inclusion in a database of sensitivity of species to ozone (OZOVEG database). An index, the relative sensitivity to ozone, was calculated for each species based on changes in biomass in order to test for species traits associated with ozone sensitivity. Meta-analysis of the ozone sensitivity data showed a wide inter-specific range in response to ozone. Some relationships in comparison to plant physiological and ecological characteristics were identified. Plants of the therophyte lifeform were particularly sensitive to ozone. Species with higher mature leaf N concentration were more sensitive to ozone than those with lower leaf N concentration. Some relationships between relative sensitivity to ozone and Ellenberg habitat requirements were also identified. In contrast, no relationships between relative sensitivity to ozone and mature leaf P concentration, Grime's CSR strategy, leaf longevity, flowering season, stomatal density and maximum altitude were found. The relative sensitivity of species and relationships with plant characteristics identified in this study could be used to predict sensitivity to ozone of untested species and communities.
Maternal sensitivity: a concept analysis.
Shin, Hyunjeong; Park, Young-Joo; Ryu, Hosihn; Seomun, Gyeong-Ae
2008-11-01
The aim of this paper is to report a concept analysis of maternal sensitivity. Maternal sensitivity is a broad concept encompassing a variety of interrelated affective and behavioural caregiving attributes. It is used interchangeably with the terms maternal responsiveness or maternal competency, with no consistency of use. There is a need to clarify the concept of maternal sensitivity for research and practice. A search was performed on the CINAHL and Ovid MEDLINE databases using 'maternal sensitivity', 'maternal responsiveness' and 'sensitive mothering' as key words. The searches yielded 54 records for the years 1981-2007. Rodgers' method of evolutionary concept analysis was used to analyse the material. Four critical attributes of maternal sensitivity were identified: (a) dynamic process involving maternal abilities; (b) reciprocal give-and-take with the infant; (c) contingency on the infant's behaviour and (d) quality of maternal behaviours. Maternal identity and infant's needs and cues are antecedents for these attributes. The consequences are infant's comfort, mother-infant attachment and infant development. In addition, three positive affecting factors (social support, maternal-foetal attachment and high self-esteem) and three negative affecting factors (maternal depression, maternal stress and maternal anxiety) were identified. A clear understanding of the concept of maternal sensitivity could be useful for developing ways to enhance maternal sensitivity and to maximize the developmental potential of infants. Knowledge of the attributes of maternal sensitivity identified in this concept analysis may be helpful for constructing measuring items or dimensions.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, S.; Toll, J.; Cothern, K.
1995-12-31
The authors have performed robust sensitivity studies of the physico-chemical Hudson River PCB model PCHEPM to identify the parameters and process uncertainties contributing the most to uncertainty in predictions of water column and sediment PCB concentrations, over the time period 1977--1991 in one segment of the lower Hudson River. The term ``robust sensitivity studies`` refers to the use of several sensitivity analysis techniques to obtain a more accurate depiction of the relative importance of different sources of uncertainty. Local sensitivity analysis provided data on the sensitivity of PCB concentration estimates to small perturbations in nominal parameter values. Range sensitivity analysismore » provided information about the magnitude of prediction uncertainty associated with each input uncertainty. Rank correlation analysis indicated which parameters had the most dominant influence on model predictions. Factorial analysis identified important interactions among model parameters. Finally, term analysis looked at the aggregate influence of combinations of parameters representing physico-chemical processes. The authors scored the results of the local and range sensitivity and rank correlation analyses. The authors considered parameters that scored high on two of the three analyses to be important contributors to PCB concentration prediction uncertainty, and treated them probabilistically in simulations. They also treated probabilistically parameters identified in the factorial analysis as interacting with important parameters. The authors used the term analysis to better understand how uncertain parameters were influencing the PCB concentration predictions. The importance analysis allowed us to reduce the number of parameters to be modeled probabilistically from 16 to 5. This reduced the computational complexity of Monte Carlo simulations, and more importantly, provided a more lucid depiction of prediction uncertainty and its causes.« less
NASA Astrophysics Data System (ADS)
Ye, M.; Chen, Z.; Shi, L.; Zhu, Y.; Yang, J.
2017-12-01
Nitrogen reactive transport modeling is subject to uncertainty in model parameters, structures, and scenarios. While global sensitivity analysis is a vital tool for identifying the parameters important to nitrogen reactive transport, conventional global sensitivity analysis only considers parametric uncertainty. This may result in inaccurate selection of important parameters, because parameter importance may vary under different models and modeling scenarios. By using a recently developed variance-based global sensitivity analysis method, this paper identifies important parameters with simultaneous consideration of parametric uncertainty, model uncertainty, and scenario uncertainty. In a numerical example of nitrogen reactive transport modeling, a combination of three scenarios of soil temperature and two scenarios of soil moisture leads to a total of six scenarios. Four alternative models are used to evaluate reduction functions used for calculating actual rates of nitrification and denitrification. The model uncertainty is tangled with scenario uncertainty, as the reduction functions depend on soil temperature and moisture content. The results of sensitivity analysis show that parameter importance varies substantially between different models and modeling scenarios, which may lead to inaccurate selection of important parameters if model and scenario uncertainties are not considered. This problem is avoided by using the new method of sensitivity analysis in the context of model averaging and scenario averaging. The new method of sensitivity analysis can be applied to other problems of contaminant transport modeling when model uncertainty and/or scenario uncertainty are present.
Global sensitivity analysis of DRAINMOD-FOREST, an integrated forest ecosystem model
Shiying Tian; Mohamed A. Youssef; Devendra M. Amatya; Eric D. Vance
2014-01-01
Global sensitivity analysis is a useful tool to understand process-based ecosystem models by identifying key parameters and processes controlling model predictions. This study reported a comprehensive global sensitivity analysis for DRAINMOD-FOREST, an integrated model for simulating water, carbon (C), and nitrogen (N) cycles and plant growth in lowland forests. The...
Byers, Helen; Wallis, Yvonne; van Veen, Elke M; Lalloo, Fiona; Reay, Kim; Smith, Philip; Wallace, Andrew J; Bowers, Naomi; Newman, William G; Evans, D Gareth
2016-11-01
The sensitivity of testing BRCA1 and BRCA2 remains unresolved as the frequency of deep intronic splicing variants has not been defined in high-risk familial breast/ovarian cancer families. This variant category is reported at significant frequency in other tumour predisposition genes, including NF1 and MSH2. We carried out comprehensive whole gene RNA analysis on 45 high-risk breast/ovary and male breast cancer families with no identified pathogenic variant on exonic sequencing and copy number analysis of BRCA1/2. In addition, we undertook variant screening of a 10-gene high/moderate risk breast/ovarian cancer panel by next-generation sequencing. DNA testing identified the causative variant in 50/56 (89%) breast/ovarian/male breast cancer families with Manchester scores of ≥50 with two variants being confirmed to affect splicing on RNA analysis. RNA sequencing of BRCA1/BRCA2 on 45 individuals from high-risk families identified no deep intronic variants and did not suggest loss of RNA expression as a cause of lost sensitivity. Panel testing in 42 samples identified a known RAD51D variant, a high-risk ATM variant in another breast ovary family and a truncating CHEK2 mutation. Current exonic sequencing and copy number analysis variant detection methods of BRCA1/2 have high sensitivity in high-risk breast/ovarian cancer families. Sequence analysis of RNA does not identify any variants undetected by current analysis of BRCA1/2. However, RNA analysis clarified the pathogenicity of variants of unknown significance detected by current methods. The low diagnostic uplift achieved through sequence analysis of the other known breast/ovarian cancer susceptibility genes indicates that further high-risk genes remain to be identified.
Global Sensitivity Analysis for Process Identification under Model Uncertainty
NASA Astrophysics Data System (ADS)
Ye, M.; Dai, H.; Walker, A. P.; Shi, L.; Yang, J.
2015-12-01
The environmental system consists of various physical, chemical, and biological processes, and environmental models are always built to simulate these processes and their interactions. For model building, improvement, and validation, it is necessary to identify important processes so that limited resources can be used to better characterize the processes. While global sensitivity analysis has been widely used to identify important processes, the process identification is always based on deterministic process conceptualization that uses a single model for representing a process. However, environmental systems are complex, and it happens often that a single process may be simulated by multiple alternative models. Ignoring the model uncertainty in process identification may lead to biased identification in that identified important processes may not be so in the real world. This study addresses this problem by developing a new method of global sensitivity analysis for process identification. The new method is based on the concept of Sobol sensitivity analysis and model averaging. Similar to the Sobol sensitivity analysis to identify important parameters, our new method evaluates variance change when a process is fixed at its different conceptualizations. The variance considers both parametric and model uncertainty using the method of model averaging. The method is demonstrated using a synthetic study of groundwater modeling that considers recharge process and parameterization process. Each process has two alternative models. Important processes of groundwater flow and transport are evaluated using our new method. The method is mathematically general, and can be applied to a wide range of environmental problems.
Mokhtari, Amirhossein; Christopher Frey, H; Zheng, Junyu
2006-11-01
Sensitivity analyses of exposure or risk models can help identify the most significant factors to aid in risk management or to prioritize additional research to reduce uncertainty in the estimates. However, sensitivity analysis is challenged by non-linearity, interactions between inputs, and multiple days or time scales. Selected sensitivity analysis methods are evaluated with respect to their applicability to human exposure models with such features using a testbed. The testbed is a simplified version of a US Environmental Protection Agency's Stochastic Human Exposure and Dose Simulation (SHEDS) model. The methods evaluated include the Pearson and Spearman correlation, sample and rank regression, analysis of variance, Fourier amplitude sensitivity test (FAST), and Sobol's method. The first five methods are known as "sampling-based" techniques, wheras the latter two methods are known as "variance-based" techniques. The main objective of the test cases was to identify the main and total contributions of individual inputs to the output variance. Sobol's method and FAST directly quantified these measures of sensitivity. Results show that sensitivity of an input typically changed when evaluated under different time scales (e.g., daily versus monthly). All methods provided similar insights regarding less important inputs; however, Sobol's method and FAST provided more robust insights with respect to sensitivity of important inputs compared to the sampling-based techniques. Thus, the sampling-based methods can be used in a screening step to identify unimportant inputs, followed by application of more computationally intensive refined methods to a smaller set of inputs. The implications of time variation in sensitivity results for risk management are briefly discussed.
Local sensitivity analysis for inverse problems solved by singular value decomposition
Hill, M.C.; Nolan, B.T.
2010-01-01
Local sensitivity analysis provides computationally frugal ways to evaluate models commonly used for resource management, risk assessment, and so on. This includes diagnosing inverse model convergence problems caused by parameter insensitivity and(or) parameter interdependence (correlation), understanding what aspects of the model and data contribute to measures of uncertainty, and identifying new data likely to reduce model uncertainty. Here, we consider sensitivity statistics relevant to models in which the process model parameters are transformed using singular value decomposition (SVD) to create SVD parameters for model calibration. The statistics considered include the PEST identifiability statistic, and combined use of the process-model parameter statistics composite scaled sensitivities and parameter correlation coefficients (CSS and PCC). The statistics are complimentary in that the identifiability statistic integrates the effects of parameter sensitivity and interdependence, while CSS and PCC provide individual measures of sensitivity and interdependence. PCC quantifies correlations between pairs or larger sets of parameters; when a set of parameters is intercorrelated, the absolute value of PCC is close to 1.00 for all pairs in the set. The number of singular vectors to include in the calculation of the identifiability statistic is somewhat subjective and influences the statistic. To demonstrate the statistics, we use the USDA’s Root Zone Water Quality Model to simulate nitrogen fate and transport in the unsaturated zone of the Merced River Basin, CA. There are 16 log-transformed process-model parameters, including water content at field capacity (WFC) and bulk density (BD) for each of five soil layers. Calibration data consisted of 1,670 observations comprising soil moisture, soil water tension, aqueous nitrate and bromide concentrations, soil nitrate concentration, and organic matter content. All 16 of the SVD parameters could be estimated by regression based on the range of singular values. Identifiability statistic results varied based on the number of SVD parameters included. Identifiability statistics calculated for four SVD parameters indicate the same three most important process-model parameters as CSS/PCC (WFC1, WFC2, and BD2), but the order differed. Additionally, the identifiability statistic showed that BD1 was almost as dominant as WFC1. The CSS/PCC analysis showed that this results from its high correlation with WCF1 (-0.94), and not its individual sensitivity. Such distinctions, combined with analysis of how high correlations and(or) sensitivities result from the constructed model, can produce important insights into, for example, the use of sensitivity analysis to design monitoring networks. In conclusion, the statistics considered identified similar important parameters. They differ because (1) with CSS/PCC can be more awkward because sensitivity and interdependence are considered separately and (2) identifiability requires consideration of how many SVD parameters to include. A continuing challenge is to understand how these computationally efficient methods compare with computationally demanding global methods like Markov-Chain Monte Carlo given common nonlinear processes and the often even more nonlinear models.
Chon, Hye Sook; Marchion, Douglas C; Xiong, Yin; Chen, Ning; Bicaku, Elona; Stickles, Xiaomang Ba; Bou Zgheib, Nadim; Judson, Patricia L; Hakam, Ardeshir; Gonzalez-Bosquet, Jesus; Wenham, Robert M; Apte, Sachin M; Lancaster, Johnathan M
2012-01-01
To identify pathways that influence endometrial cancer (EC) cell sensitivity to cisplatin and to characterize the BCL2 antagonist of cell death (BAD) pathway as a therapeutic target to increase cisplatin sensitivity. Eight EC cell lines (Ishikawa, MFE296, RL 95-2, AN3CA, KLE, MFE280, MFE319, HEC-1-A) were subjected to Affymetrix Human U133A GeneChip expression analysis of approximately 22,000 probe sets. In parallel, endometrial cell line sensitivity to cisplatin was quantified by MTS assay, and IC(50) values were calculated. Pearson's correlation test was used to identify genes associated with response to cisplatin. Genes associated with cisplatin responsiveness were subjected to pathway analysis. The BAD pathway was identified and subjected to targeted modulation, and the effect on cisplatin sensitivity was evaluated. Pearson's correlation analysis identified 1443 genes associated with cisplatin resistance (P<0.05), which included representation of the BAD-apoptosis pathway. Small interfering RNA (siRNA) knockdown of BAD pathway protein phosphatase PP2C expression was associated with increased phosphorylated BAD (serine-155) levels and a parallel increase in cisplatin resistance in Ishikawa (P=0.004) and HEC-1-A (P=0.02) cell lines. In contrast, siRNA knockdown of protein kinase A expression increased cisplatin sensitivity in the Ishikawa (P=0.02) cell line. The BAD pathway influences EC cell sensitivity to cisplatin, likely via modulation of the phosphorylation status of the BAD protein. The BAD pathway represents an appealing therapeutic target to increase EC cell sensitivity to cisplatin. Copyright © 2011 Elsevier Inc. All rights reserved.
Hickinson, D Mark; Marshall, Gayle B; Beran, Garry J; Varella-Garcia, Marileila; Mills, Elizabeth A; South, Marie C; Cassidy, Andrew M; Acheson, Kerry L; McWalter, Gael; McCormack, Rose M; Bunn, Paul A; French, Tim; Graham, Alex; Holloway, Brian R; Hirsch, Fred R; Speake, Georgina
2009-06-01
Potential biomarkers were identified for in vitro sensitivity to the epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor gefitinib in head and neck cancer. Gefitinib sensitivity was determined in cell lines, followed by transcript profiling coupled with a novel pathway analysis approach. Eleven cell lines were highly sensitive to gefitinib (inhibitor concentration required to give 50% growth inhibition [GI(50)] < 1 microM), three had intermediate sensitivity (GI(50) 1-7 microM), and six were resistant (GI(50) > 7 microM); an exploratory principal component analysis revealed a separation between the genomic profiles of sensitive and resistant cell lines. Subsequently, a hypothesis-driven analysis of Affymetrix data (Affymetrix, Inc., Santa Clara, CA, USA) revealed higher mRNA levels for E-cadherin (CDH1); transforming growth factor, alpha (TGF-alpha); amphiregulin (AREG); FLJ22662; EGFR; p21-activated kinase 6 (PAK6); glutathione S-transferase Pi (GSTP1); and ATP-binding cassette, subfamily C, member 5 (ABCC5) in sensitive versus resistant cell lines. A hypothesis-free analysis identified 46 gene transcripts that were strongly differentiated, seven of which had a known association with EGFR and head and neck cancer (human EGF receptor 3 [HER3], TGF-alpha, CDH1, EGFR, keratin 16 [KRT16], fibroblast growth factor 2 [FGF2], and cortactin [CTTN]). Polymerase chain reaction (PCR) and enzyme-linked immunoabsorbant assay analysis confirmed Affymetrix data, and EGFR gene mutation, amplification, and genomic gain correlated strongly with gefitinib sensitivity. We identified biomarkers that predict for in vitro responsiveness to gefitinib, seven of which have known association with EGFR and head and neck cancer. These in vitro predictive biomarkers may have potential utility in the clinic and warrant further investigation.
Material and morphology parameter sensitivity analysis in particulate composite materials
NASA Astrophysics Data System (ADS)
Zhang, Xiaoyu; Oskay, Caglar
2017-12-01
This manuscript presents a novel parameter sensitivity analysis framework for damage and failure modeling of particulate composite materials subjected to dynamic loading. The proposed framework employs global sensitivity analysis to study the variance in the failure response as a function of model parameters. In view of the computational complexity of performing thousands of detailed microstructural simulations to characterize sensitivities, Gaussian process (GP) surrogate modeling is incorporated into the framework. In order to capture the discontinuity in response surfaces, the GP models are integrated with a support vector machine classification algorithm that identifies the discontinuities within response surfaces. The proposed framework is employed to quantify variability and sensitivities in the failure response of polymer bonded particulate energetic materials under dynamic loads to material properties and morphological parameters that define the material microstructure. Particular emphasis is placed on the identification of sensitivity to interfaces between the polymer binder and the energetic particles. The proposed framework has been demonstrated to identify the most consequential material and morphological parameters under vibrational and impact loads.
Loomba, Rohit S; Shah, Parinda H; Nijhawan, Karan; Aggarwal, Saurabh; Arora, Rohit
2015-03-01
Increased cardiothoracic ratio noted on chest radiographs often prompts concern and further evaluation with additional imaging. This study pools available data assessing the utility of cardiothoracic ratio in predicting left ventricular dilation. A systematic review of the literature was conducted to identify studies comparing cardiothoracic ratio by chest x-ray to left ventricular dilation by echocardiography. Electronic databases were used to identify studies which were then assessed for quality and bias, with those with adequate quality and minimal bias ultimately being included in the pooled analysis. The pooled data were used to determine the sensitivity, specificity, positive predictive value and negative predictive value of cardiomegaly in predicting left ventricular dilation. A total of six studies consisting of 466 patients were included in this analysis. Cardiothoracic ratio had 83.3% sensitivity, 45.4% specificity, 43.5% positive predictive value and 82.7% negative predictive value. When a secondary analysis was conducted with a pediatric study excluded, a total of five studies consisting of 371 patients were included. Cardiothoracic ratio had 86.2% sensitivity, 25.2% specificity, 42.5% positive predictive value and 74.0% negative predictive value. Cardiothoracic ratio as determined by chest radiograph is sensitive but not specific for identifying left ventricular dilation. Cardiothoracic ratio also has a strong negative predictive value for identifying left ventricular dilation.
NASA Astrophysics Data System (ADS)
Dai, H.; Chen, X.; Ye, M.; Song, X.; Zachara, J. M.
2016-12-01
Sensitivity analysis has been an important tool in groundwater modeling to identify the influential parameters. Among various sensitivity analysis methods, the variance-based global sensitivity analysis has gained popularity for its model independence characteristic and capability of providing accurate sensitivity measurements. However, the conventional variance-based method only considers uncertainty contribution of single model parameters. In this research, we extended the variance-based method to consider more uncertainty sources and developed a new framework to allow flexible combinations of different uncertainty components. We decompose the uncertainty sources into a hierarchical three-layer structure: scenario, model and parametric. Furthermore, each layer of uncertainty source is capable of containing multiple components. An uncertainty and sensitivity analysis framework was then constructed following this three-layer structure using Bayesian network. Different uncertainty components are represented as uncertain nodes in this network. Through the framework, variance-based sensitivity analysis can be implemented with great flexibility of using different grouping strategies for uncertainty components. The variance-based sensitivity analysis thus is improved to be able to investigate the importance of an extended range of uncertainty sources: scenario, model, and other different combinations of uncertainty components which can represent certain key model system processes (e.g., groundwater recharge process, flow reactive transport process). For test and demonstration purposes, the developed methodology was implemented into a test case of real-world groundwater reactive transport modeling with various uncertainty sources. The results demonstrate that the new sensitivity analysis method is able to estimate accurate importance measurements for any uncertainty sources which were formed by different combinations of uncertainty components. The new methodology can provide useful information for environmental management and decision-makers to formulate policies and strategies.
Dorfman, David M; LaPlante, Charlotte D; Pozdnyakova, Olga; Li, Betty
2015-11-01
In our high-sensitivity flow cytometric approach for systemic mastocytosis (SM), we identified mast cell event clustering as a new diagnostic criterion for the disease. To objectively characterize mast cell gated event distributions, we performed cluster analysis using FLOCK, a computational approach to identify cell subsets in multidimensional flow cytometry data in an unbiased, automated fashion. FLOCK identified discrete mast cell populations in most cases of SM (56/75 [75%]) but only a minority of non-SM cases (17/124 [14%]). FLOCK-identified mast cell populations accounted for 2.46% of total cells on average in SM cases and 0.09% of total cells on average in non-SM cases (P < .0001) and were predictive of SM, with a sensitivity of 75%, a specificity of 86%, a positive predictive value of 76%, and a negative predictive value of 85%. FLOCK analysis provides useful diagnostic information for evaluating patients with suspected SM, and may be useful for the analysis of other hematopoietic neoplasms. Copyright© by the American Society for Clinical Pathology.
Mendoza, Maria C.B.; Burns, Trudy L.; Jones, Michael P.
2009-01-01
Objectives Case-deletion diagnostic methods are tools that allow identification of influential observations that may affect parameter estimates and model fitting conclusions. The goal of this paper was to develop two case-deletion diagnostics, the exact case deletion (ECD) and the empirical influence function (EIF), for detecting outliers that can affect results of sib-pair maximum likelihood quantitative trait locus (QTL) linkage analysis. Methods Subroutines to compute the ECD and EIF were incorporated into the maximum likelihood QTL variance estimation components of the linkage analysis program MAPMAKER/SIBS. Performance of the diagnostics was compared in simulation studies that evaluated the proportion of outliers correctly identified (sensitivity), and the proportion of non-outliers correctly identified (specificity). Results Simulations involving nuclear family data sets with one outlier showed EIF sensitivities approximated ECD sensitivities well for outlier-affected parameters. Sensitivities were high, indicating the outlier was identified a high proportion of the time. Simulations also showed the enormous computational time advantage of the EIF. Diagnostics applied to body mass index in nuclear families detected observations influential on the lod score and model parameter estimates. Conclusions The EIF is a practical diagnostic tool that has the advantages of high sensitivity and quick computation. PMID:19172086
The application of sensitivity analysis to models of large scale physiological systems
NASA Technical Reports Server (NTRS)
Leonard, J. I.
1974-01-01
A survey of the literature of sensitivity analysis as it applies to biological systems is reported as well as a brief development of sensitivity theory. A simple population model and a more complex thermoregulatory model illustrate the investigatory techniques and interpretation of parameter sensitivity analysis. The role of sensitivity analysis in validating and verifying models, and in identifying relative parameter influence in estimating errors in model behavior due to uncertainty in input data is presented. This analysis is valuable to the simulationist and the experimentalist in allocating resources for data collection. A method for reducing highly complex, nonlinear models to simple linear algebraic models that could be useful for making rapid, first order calculations of system behavior is presented.
Pseudotargeted MS Method for the Sensitive Analysis of Protein Phosphorylation in Protein Complexes.
Lyu, Jiawen; Wang, Yan; Mao, Jiawei; Yao, Yating; Wang, Shujuan; Zheng, Yong; Ye, Mingliang
2018-05-15
In this study, we presented an enrichment-free approach for the sensitive analysis of protein phosphorylation in minute amounts of samples, such as purified protein complexes. This method takes advantage of the high sensitivity of parallel reaction monitoring (PRM). Specifically, low confident phosphopeptides identified from the data-dependent acquisition (DDA) data set were used to build a pseudotargeted list for PRM analysis to allow the identification of additional phosphopeptides with high confidence. The development of this targeted approach is very easy as the same sample and the same LC-system were used for the discovery and the targeted analysis phases. No sample fractionation or enrichment was required for the discovery phase which allowed this method to analyze minute amount of sample. We applied this pseudotargeted MS method to quantitatively examine phosphopeptides in affinity purified endogenous Shc1 protein complexes at four temporal stages of EGF signaling and identified 82 phospho-sites. To our knowledge, this is the highest number of phospho-sites identified from the protein complexes. This pseudotargeted MS method is highly sensitive in the identification of low abundance phosphopeptides and could be a powerful tool to study phosphorylation-regulated assembly of protein complex.
NASA Astrophysics Data System (ADS)
Safaei, S.; Haghnegahdar, A.; Razavi, S.
2016-12-01
Complex environmental models are now the primary tool to inform decision makers for the current or future management of environmental resources under the climate and environmental changes. These complex models often contain a large number of parameters that need to be determined by a computationally intensive calibration procedure. Sensitivity analysis (SA) is a very useful tool that not only allows for understanding the model behavior, but also helps in reducing the number of calibration parameters by identifying unimportant ones. The issue is that most global sensitivity techniques are highly computationally demanding themselves for generating robust and stable sensitivity metrics over the entire model response surface. Recently, a novel global sensitivity analysis method, Variogram Analysis of Response Surfaces (VARS), is introduced that can efficiently provide a comprehensive assessment of global sensitivity using the Variogram concept. In this work, we aim to evaluate the effectiveness of this highly efficient GSA method in saving computational burden, when applied to systems with extra-large number of input factors ( 100). We use a test function and a hydrological modelling case study to demonstrate the capability of VARS method in reducing problem dimensionality by identifying important vs unimportant input factors.
Sensitivity and Uncertainty Analysis of the GFR MOX Fuel Subassembly
NASA Astrophysics Data System (ADS)
Lüley, J.; Vrban, B.; Čerba, Š.; Haščík, J.; Nečas, V.; Pelloni, S.
2014-04-01
We performed sensitivity and uncertainty analysis as well as benchmark similarity assessment of the MOX fuel subassembly designed for the Gas-Cooled Fast Reactor (GFR) as a representative material of the core. Material composition was defined for each assembly ring separately allowing us to decompose the sensitivities not only for isotopes and reactions but also for spatial regions. This approach was confirmed by direct perturbation calculations for chosen materials and isotopes. Similarity assessment identified only ten partly comparable benchmark experiments that can be utilized in the field of GFR development. Based on the determined uncertainties, we also identified main contributors to the calculation bias.
Comparative Sensitivity Analysis of Muscle Activation Dynamics
Günther, Michael; Götz, Thomas
2015-01-01
We mathematically compared two models of mammalian striated muscle activation dynamics proposed by Hatze and Zajac. Both models are representative for a broad variety of biomechanical models formulated as ordinary differential equations (ODEs). These models incorporate parameters that directly represent known physiological properties. Other parameters have been introduced to reproduce empirical observations. We used sensitivity analysis to investigate the influence of model parameters on the ODE solutions. In addition, we expanded an existing approach to treating initial conditions as parameters and to calculating second-order sensitivities. Furthermore, we used a global sensitivity analysis approach to include finite ranges of parameter values. Hence, a theoretician striving for model reduction could use the method for identifying particularly low sensitivities to detect superfluous parameters. An experimenter could use it for identifying particularly high sensitivities to improve parameter estimation. Hatze's nonlinear model incorporates some parameters to which activation dynamics is clearly more sensitive than to any parameter in Zajac's linear model. Other than Zajac's model, Hatze's model can, however, reproduce measured shifts in optimal muscle length with varied muscle activity. Accordingly we extracted a specific parameter set for Hatze's model that combines best with a particular muscle force-length relation. PMID:26417379
Co-acting gene networks predict TRAIL responsiveness of tumour cells with high accuracy.
O'Reilly, Paul; Ortutay, Csaba; Gernon, Grainne; O'Connell, Enda; Seoighe, Cathal; Boyce, Susan; Serrano, Luis; Szegezdi, Eva
2014-12-19
Identification of differentially expressed genes from transcriptomic studies is one of the most common mechanisms to identify tumor biomarkers. This approach however is not well suited to identify interaction between genes whose protein products potentially influence each other, which limits its power to identify molecular wiring of tumour cells dictating response to a drug. Due to the fact that signal transduction pathways are not linear and highly interlinked, the biological response they drive may be better described by the relative amount of their components and their functional relationships than by their individual, absolute expression. Gene expression microarray data for 109 tumor cell lines with known sensitivity to the death ligand cytokine tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) was used to identify genes with potential functional relationships determining responsiveness to TRAIL-induced apoptosis. The machine learning technique Random Forest in the statistical environment "R" with backward elimination was used to identify the key predictors of TRAIL sensitivity and differentially expressed genes were identified using the software GeneSpring. Gene co-regulation and statistical interaction was assessed with q-order partial correlation analysis and non-rejection rate. Biological (functional) interactions amongst the co-acting genes were studied with Ingenuity network analysis. Prediction accuracy was assessed by calculating the area under the receiver operator curve using an independent dataset. We show that the gene panel identified could predict TRAIL-sensitivity with a very high degree of sensitivity and specificity (AUC=0·84). The genes in the panel are co-regulated and at least 40% of them functionally interact in signal transduction pathways that regulate cell death and cell survival, cellular differentiation and morphogenesis. Importantly, only 12% of the TRAIL-predictor genes were differentially expressed highlighting the importance of functional interactions in predicting the biological response. The advantage of co-acting gene clusters is that this analysis does not depend on differential expression and is able to incorporate direct- and indirect gene interactions as well as tissue- and cell-specific characteristics. This approach (1) identified a descriptor of TRAIL sensitivity which performs significantly better as a predictor of TRAIL sensitivity than any previously reported gene signatures, (2) identified potential novel regulators of TRAIL-responsiveness and (3) provided a systematic view highlighting fundamental differences between the molecular wiring of sensitive and resistant cell types.
2014-01-01
Background Due to the recent European legislations posing a ban of animal tests for safety assessment within the cosmetic industry, development of in vitro alternatives for assessment of skin sensitization is highly prioritized. To date, proposed in vitro assays are mainly based on single biomarkers, which so far have not been able to classify and stratify chemicals into subgroups, related to risk or potency. Methods Recently, we presented the Genomic Allergen Rapid Detection (GARD) assay for assessment of chemical sensitizers. In this paper, we show how the genome wide readout of GARD can be expanded and used to identify differentially regulated pathways relating to individual chemical sensitizers. In this study, we investigated the mechanisms of action of a range of skin sensitizers through pathway identification, pathway classification and transcription factor analysis and related this to the reactive mechanisms and potency of the sensitizing agents. Results By transcriptional profiling of chemically stimulated MUTZ-3 cells, 33 canonical pathways intimately involved in sensitization to chemical substances were identified. The results showed that metabolic processes, cell cycling and oxidative stress responses are the key events activated during skin sensitization, and that these functions are engaged differently depending on the reactivity mechanisms of the sensitizing agent. Furthermore, the results indicate that the chemical reactivity groups seem to gradually engage more pathways and more molecules in each pathway with increasing sensitizing potency of the chemical used for stimulation. Also, a switch in gene regulation from up to down regulation, with increasing potency, was seen both in genes involved in metabolic functions and cell cycling. These observed pathway patterns were clearly reflected in the regulatory elements identified to drive these processes, where 33 regulatory elements have been proposed for further analysis. Conclusions This study demonstrates that functional analysis of biomarkers identified from our genomics study of human MUTZ-3 cells can be used to assess sensitizing potency of chemicals in vitro, by the identification of key cellular events, such as metabolic and cell cycling pathways. PMID:24517095
Young, Ewa; Zimerson, Erik; Bruze, Magnus; Svedman, Cecilia
2016-02-01
The results from a previous study indicated the presence of several possible sensitizers formed during oxidation of the potent sensitizer p-phenylenediamine (PPD) to which PPD-sensitized patients might react, in various patterns. To extract and analyse a yellow spot from a thin-layer chromatogram with oxidized PPD, to which 6 of 14 (43%) PPD-positive patients had reacted in a previous study, in order to identify potential sensitizer(s) and to patch test this/these substance(s) in the 14 PPD-positive patients. The yellow spot was extracted from a thin-layer chromatogram of oxidized PPD, and two substances, suspected to be allergens, were identified by analysis with gas chromatography mass spectrometry (GCMS). The 14 PPD-positive patients, who had been previously tested with the thin-layer chromatogram of oxidized PPD, participated in the investigation, and were tested with dilutions of the two substances. GCMS analysis identified 4-nitroaniline and 4,4'-azodianiline in the yellow spot. Of the 14 PPD-positive test patients, 5 (36%) reacted to 4-nitroaniline and 9 (64%) reacted to 4,4'-azodianiline. The results show that 4-nitroaniline and 4,4'-azodianiline, formed during oxidation of PPD, are potent sensitizers. PPD-sensitized patients react to a high extent to concentrations equimolar to PPD of 4-nitroaniline and 4,4'-azodianiline. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Postoperative complications following colectomy for ulcerative colitis: A validation study
2012-01-01
Background Ulcerative colitis (UC) patients failing medical management require colectomy. This study compares risk estimates for predictors of postoperative complication derived from administrative data against that of chart review and evaluates the accuracy of administrative coding for this population. Methods Hospital administrative databases were used to identify adults with UC undergoing colectomy from 1996–2007. Medical charts were reviewed and regression analyses comparing chart versus administrative data were performed to assess the effect of age, emergent operation, and Charlson comorbidities on the occurrence of postoperative complications. Sensitivity, specificity, and positive/negative predictive values of administrative coding for identifying the study population, Charlson comorbidities, and postoperative complications were assessed. Results Compared to chart review, administrative data estimated a higher magnitude of effect for emergent admission (OR 2.52 [95% CI: 1.80–3.52] versus 1.49 [1.06–2.09]) and Charlson comorbidities (OR 2.91 [1.86–4.56] versus 1.50 [1.05–2.15]) as predictors of postoperative complications. Administrative data correctly identified UC and colectomy in 85.9% of cases. The administrative database was 37% sensitive in identifying patients with ≥ 1Charlson comorbidity. Restricting analysis to active comorbidities increased the sensitivity to 63%. The sensitivity of identifying patients with at least one postoperative complication was 68%; restricting analysis to more severe complications improved the sensitivity to 84%. Conclusions Administrative data identified the same risk factors for postoperative complications as chart review, but overestimated the magnitude of risk. This discrepancy may be explained by coding inaccuracies that selectively identifying the most serious complications and comorbidities. PMID:22943760
Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models
Rakovec, O.; Hill, Mary C.; Clark, M.P.; Weerts, A. H.; Teuling, A. J.; Uijlenhoet, R.
2014-01-01
This paper presents a hybrid local-global sensitivity analysis method termed the Distributed Evaluation of Local Sensitivity Analysis (DELSA), which is used here to identify important and unimportant parameters and evaluate how model parameter importance changes as parameter values change. DELSA uses derivative-based “local” methods to obtain the distribution of parameter sensitivity across the parameter space, which promotes consideration of sensitivity analysis results in the context of simulated dynamics. This work presents DELSA, discusses how it relates to existing methods, and uses two hydrologic test cases to compare its performance with the popular global, variance-based Sobol' method. The first test case is a simple nonlinear reservoir model with two parameters. The second test case involves five alternative “bucket-style” hydrologic models with up to 14 parameters applied to a medium-sized catchment (200 km2) in the Belgian Ardennes. Results show that in both examples, Sobol' and DELSA identify similar important and unimportant parameters, with DELSA enabling more detailed insight at much lower computational cost. For example, in the real-world problem the time delay in runoff is the most important parameter in all models, but DELSA shows that for about 20% of parameter sets it is not important at all and alternative mechanisms and parameters dominate. Moreover, the time delay was identified as important in regions producing poor model fits, whereas other parameters were identified as more important in regions of the parameter space producing better model fits. The ability to understand how parameter importance varies through parameter space is critical to inform decisions about, for example, additional data collection and model development. The ability to perform such analyses with modest computational requirements provides exciting opportunities to evaluate complicated models as well as many alternative models.
Are quantitative sensitivity analysis methods always reliable?
NASA Astrophysics Data System (ADS)
Huang, X.
2016-12-01
Physical parameterizations developed to represent subgrid-scale physical processes include various uncertain parameters, leading to large uncertainties in today's Earth System Models (ESMs). Sensitivity Analysis (SA) is an efficient approach to quantitatively determine how the uncertainty of the evaluation metric can be apportioned to each parameter. Also, SA can identify the most influential parameters, as a result to reduce the high dimensional parametric space. In previous studies, some SA-based approaches, such as Sobol' and Fourier amplitude sensitivity testing (FAST), divide the parameters into sensitive and insensitive groups respectively. The first one is reserved but the other is eliminated for certain scientific study. However, these approaches ignore the disappearance of the interactive effects between the reserved parameters and the eliminated ones, which are also part of the total sensitive indices. Therefore, the wrong sensitive parameters might be identified by these traditional SA approaches and tools. In this study, we propose a dynamic global sensitivity analysis method (DGSAM), which iteratively removes the least important parameter until there are only two parameters left. We use the CLM-CASA, a global terrestrial model, as an example to verify our findings with different sample sizes ranging from 7000 to 280000. The result shows DGSAM has abilities to identify more influential parameters, which is confirmed by parameter calibration experiments using four popular optimization methods. For example, optimization using Top3 parameters filtered by DGSAM could achieve substantial improvement against Sobol' by 10%. Furthermore, the current computational cost for calibration has been reduced to 1/6 of the original one. In future, it is necessary to explore alternative SA methods emphasizing parameter interactions.
NASA Technical Reports Server (NTRS)
Gaebler, John A.; Tolson, Robert H.
2010-01-01
In the study of entry, descent, and landing, Monte Carlo sampling methods are often employed to study the uncertainty in the designed trajectory. The large number of uncertain inputs and outputs, coupled with complicated non-linear models, can make interpretation of the results difficult. Three methods that provide statistical insights are applied to an entry, descent, and landing simulation. The advantages and disadvantages of each method are discussed in terms of the insights gained versus the computational cost. The first method investigated was failure domain bounding which aims to reduce the computational cost of assessing the failure probability. Next a variance-based sensitivity analysis was studied for the ability to identify which input variable uncertainty has the greatest impact on the uncertainty of an output. Finally, probabilistic sensitivity analysis is used to calculate certain sensitivities at a reduced computational cost. These methods produce valuable information that identifies critical mission parameters and needs for new technology, but generally at a significant computational cost.
NASA Technical Reports Server (NTRS)
Sankararaman, Shankar
2016-01-01
This paper presents a computational framework for uncertainty characterization and propagation, and sensitivity analysis under the presence of aleatory and epistemic un- certainty, and develops a rigorous methodology for efficient refinement of epistemic un- certainty by identifying important epistemic variables that significantly affect the overall performance of an engineering system. The proposed methodology is illustrated using the NASA Langley Uncertainty Quantification Challenge (NASA-LUQC) problem that deals with uncertainty analysis of a generic transport model (GTM). First, Bayesian inference is used to infer subsystem-level epistemic quantities using the subsystem-level model and corresponding data. Second, tools of variance-based global sensitivity analysis are used to identify four important epistemic variables (this limitation specified in the NASA-LUQC is reflective of practical engineering situations where not all epistemic variables can be refined due to time/budget constraints) that significantly affect system-level performance. The most significant contribution of this paper is the development of the sequential refine- ment methodology, where epistemic variables for refinement are not identified all-at-once. Instead, only one variable is first identified, and then, Bayesian inference and global sensi- tivity calculations are repeated to identify the next important variable. This procedure is continued until all 4 variables are identified and the refinement in the system-level perfor- mance is computed. The advantages of the proposed sequential refinement methodology over the all-at-once uncertainty refinement approach are explained, and then applied to the NASA Langley Uncertainty Quantification Challenge problem.
Nelson, S D; Nelson, R E; Cannon, G W; Lawrence, P; Battistone, M J; Grotzke, M; Rosenblum, Y; LaFleur, J
2014-12-01
This is a cost-effectiveness analysis of training rural providers to identify and treat osteoporosis. Results showed a slight cost savings, increase in life years, increase in treatment rates, and decrease in fracture incidence. However, the results were sensitive to small differences in effectiveness, being cost-effective in 70 % of simulations during probabilistic sensitivity analysis. We evaluated the cost-effectiveness of training rural providers to identify and treat veterans at risk for fragility fractures relative to referring these patients to an urban medical center for specialist care. The model evaluated the impact of training on patient life years, quality-adjusted life years (QALYs), treatment rates, fracture incidence, and costs from the perspective of the Department of Veterans Affairs. We constructed a Markov microsimulation model to compare costs and outcomes of a hypothetical cohort of veterans seen by rural providers. Parameter estimates were derived from previously published studies, and we conducted one-way and probabilistic sensitivity analyses on the parameter inputs. Base-case analysis showed that training resulted in no additional costs and an extra 0.083 life years (0.054 QALYs). Our model projected that as a result of training, more patients with osteoporosis would receive treatment (81.3 vs. 12.2 %), and all patients would have a lower incidence of fractures per 1,000 patient years (hip, 1.628 vs. 1.913; clinical vertebral, 0.566 vs. 1.037) when seen by a trained provider compared to an untrained provider. Results remained consistent in one-way sensitivity analysis and in probabilistic sensitivity analyses, training rural providers was cost-effective (less than $50,000/QALY) in 70 % of the simulations. Training rural providers to identify and treat veterans at risk for fragility fractures has a potential to be cost-effective, but the results are sensitive to small differences in effectiveness. It appears that provider education alone is not enough to make a significant difference in fragility fracture rates among veterans.
Sensitivity to Landscape Features: A Spatial Analysis of Field Geoscientists on the Move
ERIC Educational Resources Information Center
Baker, Kathleen M.; Petcovic, L. Heather
2016-01-01
Intelligent behavior in everyday contexts may depend on both ability and an individual's disposition toward using that ability. Research into patterns of thinking has identified three logically distinct components necessary for dispositional behavior: ability, inclination, and sensitivity. Surprisingly, sensitivity appears to be the most common…
NASA Astrophysics Data System (ADS)
Hameed, M.; Demirel, M. C.; Moradkhani, H.
2015-12-01
Global Sensitivity Analysis (GSA) approach helps identify the effectiveness of model parameters or inputs and thus provides essential information about the model performance. In this study, the effects of the Sacramento Soil Moisture Accounting (SAC-SMA) model parameters, forcing data, and initial conditions are analysed by using two GSA methods: Sobol' and Fourier Amplitude Sensitivity Test (FAST). The simulations are carried out over five sub-basins within the Columbia River Basin (CRB) for three different periods: one-year, four-year, and seven-year. Four factors are considered and evaluated by using the two sensitivity analysis methods: the simulation length, parameter range, model initial conditions, and the reliability of the global sensitivity analysis methods. The reliability of the sensitivity analysis results is compared based on 1) the agreement between the two sensitivity analysis methods (Sobol' and FAST) in terms of highlighting the same parameters or input as the most influential parameters or input and 2) how the methods are cohered in ranking these sensitive parameters under the same conditions (sub-basins and simulation length). The results show the coherence between the Sobol' and FAST sensitivity analysis methods. Additionally, it is found that FAST method is sufficient to evaluate the main effects of the model parameters and inputs. Another conclusion of this study is that the smaller parameter or initial condition ranges, the more consistency and coherence between the sensitivity analysis methods results.
Bialosky, Joel E.; Robinson, Michael E.
2014-01-01
Background Cluster analysis can be used to identify individuals similar in profile based on response to multiple pain sensitivity measures. There are limited investigations into how empirically derived pain sensitivity subgroups influence clinical outcomes for individuals with spine pain. Objective The purposes of this study were: (1) to investigate empirically derived subgroups based on pressure and thermal pain sensitivity in individuals with spine pain and (2) to examine subgroup influence on 2-week clinical pain intensity and disability outcomes. Design A secondary analysis of data from 2 randomized trials was conducted. Methods Baseline and 2-week outcome data from 157 participants with low back pain (n=110) and neck pain (n=47) were examined. Participants completed demographic, psychological, and clinical information and were assessed using pain sensitivity protocols, including pressure (suprathreshold pressure pain) and thermal pain sensitivity (thermal heat threshold and tolerance, suprathreshold heat pain, temporal summation). A hierarchical agglomerative cluster analysis was used to create subgroups based on pain sensitivity responses. Differences in data for baseline variables, clinical pain intensity, and disability were examined. Results Three pain sensitivity cluster groups were derived: low pain sensitivity, high thermal static sensitivity, and high pressure and thermal dynamic sensitivity. There were differences in the proportion of individuals meeting a 30% change in pain intensity, where fewer individuals within the high pressure and thermal dynamic sensitivity group (adjusted odds ratio=0.3; 95% confidence interval=0.1, 0.8) achieved successful outcomes. Limitations Only 2-week outcomes are reported. Conclusions Distinct pain sensitivity cluster groups for individuals with spine pain were identified, with the high pressure and thermal dynamic sensitivity group showing worse clinical outcome for pain intensity. Future studies should aim to confirm these findings. PMID:24764070
Horita, Nobuyuki; Miyazawa, Naoki; Kojima, Ryota; Kimura, Naoko; Inoue, Miyo; Ishigatsubo, Yoshiaki; Kaneko, Takeshi
2013-11-01
Studies on the sensitivity and specificity of the Binax Now Streptococcus pneumonia urinary antigen test (index test) show considerable variance of results. Those written in English provided sufficient original data to evaluate the sensitivity and specificity of the index test using unconcentrated urine to identify S. pneumoniae infection in adults with pneumonia. Reference tests were conducted with at least one culture and/or smear. We estimated sensitivity and two specificities. One was the specificity evaluated using only patients with pneumonia of identified other aetiologies ('specificity (other)'). The other was the specificity evaluated based on both patients with pneumonia of unknown aetiology and those with pneumonia of other aetiologies ('specificity (unknown and other)') using a fixed model for meta-analysis. We found 10 articles involving 2315 patients. The analysis of 10 studies involving 399 patients yielded a pooled sensitivity of 0.75 (95% confidence interval: 0.71-0.79) without heterogeneity or publication bias. The analysis of six studies involving 258 patients yielded a pooled specificity (other) of 0.95 (95% confidence interval: 0.92-0.98) without no heterogeneity or publication bias. We attempted to conduct a meta-analysis with the 10 studies involving 1916 patients to estimate specificity (unknown and other), but it remained unclear due to moderate heterogeneity and possible publication bias. In our meta-analysis, sensitivity of the index test was moderate and specificity (other) was high; however, the specificity (unknown and other) remained unclear. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.
NASA Technical Reports Server (NTRS)
Winters, J. M.; Stark, L.
1984-01-01
Original results for a newly developed eight-order nonlinear limb antagonistic muscle model of elbow flexion and extension are presented. A wider variety of sensitivity analysis techniques are used and a systematic protocol is established that shows how the different methods can be used efficiently to complement one another for maximum insight into model sensitivity. It is explicitly shown how the sensitivity of output behaviors to model parameters is a function of the controller input sequence, i.e., of the movement task. When the task is changed (for instance, from an input sequence that results in the usual fast movement task to a slower movement that may also involve external loading, etc.) the set of parameters with high sensitivity will in general also change. Such task-specific use of sensitivity analysis techniques identifies the set of parameters most important for a given task, and even suggests task-specific model reduction possibilities.
Sweetapple, Christine; Fu, Guangtao; Butler, David
2013-09-01
This study investigates sources of uncertainty in the modelling of greenhouse gas emissions from wastewater treatment, through the use of local and global sensitivity analysis tools, and contributes to an in-depth understanding of wastewater treatment modelling by revealing critical parameters and parameter interactions. One-factor-at-a-time sensitivity analysis is used to screen model parameters and identify those with significant individual effects on three performance indicators: total greenhouse gas emissions, effluent quality and operational cost. Sobol's method enables identification of parameters with significant higher order effects and of particular parameter pairs to which model outputs are sensitive. Use of a variance-based global sensitivity analysis tool to investigate parameter interactions enables identification of important parameters not revealed in one-factor-at-a-time sensitivity analysis. These interaction effects have not been considered in previous studies and thus provide a better understanding wastewater treatment plant model characterisation. It was found that uncertainty in modelled nitrous oxide emissions is the primary contributor to uncertainty in total greenhouse gas emissions, due largely to the interaction effects of three nitrogen conversion modelling parameters. The higher order effects of these parameters are also shown to be a key source of uncertainty in effluent quality. Copyright © 2013 Elsevier Ltd. All rights reserved.
Metabolomic analysis of insulin resistance across different mouse strains and diets.
Stöckli, Jacqueline; Fisher-Wellman, Kelsey H; Chaudhuri, Rima; Zeng, Xiao-Yi; Fazakerley, Daniel J; Meoli, Christopher C; Thomas, Kristen C; Hoffman, Nolan J; Mangiafico, Salvatore P; Xirouchaki, Chrysovalantou E; Yang, Chieh-Hsin; Ilkayeva, Olga; Wong, Kari; Cooney, Gregory J; Andrikopoulos, Sofianos; Muoio, Deborah M; James, David E
2017-11-24
Insulin resistance is a major risk factor for many diseases. However, its underlying mechanism remains unclear in part because it is triggered by a complex relationship between multiple factors, including genes and the environment. Here, we used metabolomics combined with computational methods to identify factors that classified insulin resistance across individual mice derived from three different mouse strains fed two different diets. Three inbred ILSXISS strains were fed high-fat or chow diets and subjected to metabolic phenotyping and metabolomics analysis of skeletal muscle. There was significant metabolic heterogeneity between strains, diets, and individual animals. Distinct metabolites were changed with insulin resistance, diet, and between strains. Computational analysis revealed 113 metabolites that were correlated with metabolic phenotypes. Using these 113 metabolites, combined with machine learning to segregate mice based on insulin sensitivity, we identified C22:1-CoA, C2-carnitine, and C16-ceramide as the best classifiers. Strikingly, when these three metabolites were combined into one signature, they classified mice based on insulin sensitivity more accurately than each metabolite on its own or other published metabolic signatures. Furthermore, C22:1-CoA was 2.3-fold higher in insulin-resistant mice and correlated significantly with insulin resistance. We have identified a metabolomic signature composed of three functionally unrelated metabolites that accurately predicts whole-body insulin sensitivity across three mouse strains. These data indicate the power of simultaneous analysis of individual, genetic, and environmental variance in mice for identifying novel factors that accurately predict metabolic phenotypes like whole-body insulin sensitivity. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.
Robles, A; Ruano, M V; Ribes, J; Seco, A; Ferrer, J
2014-04-01
The results of a global sensitivity analysis of a filtration model for submerged anaerobic MBRs (AnMBRs) are assessed in this paper. This study aimed to (1) identify the less- (or non-) influential factors of the model in order to facilitate model calibration and (2) validate the modelling approach (i.e. to determine the need for each of the proposed factors to be included in the model). The sensitivity analysis was conducted using a revised version of the Morris screening method. The dynamic simulations were conducted using long-term data obtained from an AnMBR plant fitted with industrial-scale hollow-fibre membranes. Of the 14 factors in the model, six were identified as influential, i.e. those calibrated using off-line protocols. A dynamic calibration (based on optimisation algorithms) of these influential factors was conducted. The resulting estimated model factors accurately predicted membrane performance. Copyright © 2014 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Núñez, M.; Robie, T.; Vlachos, D. G.
2017-10-01
Kinetic Monte Carlo (KMC) simulation provides insights into catalytic reactions unobtainable with either experiments or mean-field microkinetic models. Sensitivity analysis of KMC models assesses the robustness of the predictions to parametric perturbations and identifies rate determining steps in a chemical reaction network. Stiffness in the chemical reaction network, a ubiquitous feature, demands lengthy run times for KMC models and renders efficient sensitivity analysis based on the likelihood ratio method unusable. We address the challenge of efficiently conducting KMC simulations and performing accurate sensitivity analysis in systems with unknown time scales by employing two acceleration techniques: rate constant rescaling and parallel processing. We develop statistical criteria that ensure sufficient sampling of non-equilibrium steady state conditions. Our approach provides the twofold benefit of accelerating the simulation itself and enabling likelihood ratio sensitivity analysis, which provides further speedup relative to finite difference sensitivity analysis. As a result, the likelihood ratio method can be applied to real chemistry. We apply our methodology to the water-gas shift reaction on Pt(111).
Dai, Heng; Ye, Ming; Walker, Anthony P.; ...
2017-03-28
A hydrological model consists of multiple process level submodels, and each submodel represents a process key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this study develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods withmore » variance-based global sensitivity analysis. A process sensitivity index is derived as a single summary measure of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and their parameters. Here, for demonstration, the new index is used to assign importance to the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that convert precipitation to recharge, and the geology process is simulated by two models of hydraulic conductivity. Each process model has its own random parameters. Finally, the new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dai, Heng; Ye, Ming; Walker, Anthony P.
A hydrological model consists of multiple process level submodels, and each submodel represents a process key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this study develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods withmore » variance-based global sensitivity analysis. A process sensitivity index is derived as a single summary measure of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and their parameters. Here, for demonstration, the new index is used to assign importance to the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that convert precipitation to recharge, and the geology process is simulated by two models of hydraulic conductivity. Each process model has its own random parameters. Finally, the new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less
Fukutomi, Yuma; Kawakami, Yuji; Taniguchi, Masami; Saito, Akemi; Fukuda, Azumi; Yasueda, Hiroshi; Nakazawa, Takuya; Hasegawa, Maki; Nakamura, Hiroyuki; Akiyama, Kazuo
2012-01-01
Booklice (Liposcelis bostrichophila) are a common household insect pest distributed worldwide. Particularly in Japan, they infest 'tatami' mats and are the most frequently detected insect among all detectable insects, present at a frequency of about 90% in dust samples. Although it has been hypothesized that they are an important indoor allergen, studies on their allergenicity have been limited. To clarify the allergenicity of booklice and the cross-reactivity of this insect allergen with allergens of other insects, patients sensitized to booklice were identified from 185 Japanese adults with allergic asthma using skin tests and IgE-ELISA. IgE-inhibition analysis, immunoblotting and immunoblotting-inhibition analysis were performed using sera from these patients. Allergenic proteins contributing to specific sensitization to booklice were identified by two-dimensional electrophoresis and two-dimensional immunoblotting. The booklouse-specific IgE antibody was detected in sera from 41 patients (22% of studied patients). IgE inhibition analysis revealed that IgE reactivity to the booklouse allergen in the sera from one third of booklouse-sensitized patients was not inhibited by preincubation with extracts from any other environmental insects in this study. Immunoblotting identified a 26-kD protein from booklouse extract as the allergenic protein contributing to specific sensitization to booklice. The amino acid sequence of peptide fragments of this protein showed no homology to those of previously described allergenic proteins, indicating that this protein is a new allergen. Sensitization to booklice was relatively common and specific sensitization to this insect not related to insect panallergy was indicated in this population. Copyright © 2011 S. Karger AG, Basel.
Adkins, Daniel E.; McClay, Joseph L.; Vunck, Sarah A.; Batman, Angela M.; Vann, Robert E.; Clark, Shaunna L.; Souza, Renan P.; Crowley, James J.; Sullivan, Patrick F.; van den Oord, Edwin J.C.G.; Beardsley, Patrick M.
2014-01-01
Behavioral sensitization has been widely studied in animal models and is theorized to reflect neural modifications associated with human psychostimulant addiction. While the mesolimbic dopaminergic pathway is known to play a role, the neurochemical mechanisms underlying behavioral sensitization remain incompletely understood. In the present study, we conducted the first metabolomics analysis to globally characterize neurochemical differences associated with behavioral sensitization. Methamphetamine-induced sensitization measures were generated by statistically modeling longitudinal activity data for eight inbred strains of mice. Subsequent to behavioral testing, nontargeted liquid and gas chromatography-mass spectrometry profiling was performed on 48 brain samples, yielding 301 metabolite levels per sample after quality control. Association testing between metabolite levels and three primary dimensions of behavioral sensitization (total distance, stereotypy and margin time) showed four robust, significant associations at a stringent metabolome-wide significance threshold (false discovery rate < 0.05). Results implicated homocarnosine, a dipeptide of GABA and histidine, in total distance sensitization, GABA metabolite 4-guanidinobutanoate and pantothenate in stereotypy sensitization, and myo-inositol in margin time sensitization. Secondary analyses indicated that these associations were independent of concurrent methamphetamine levels and, with the exception of the myo-inositol association, suggest a mechanism whereby strain-based genetic variation produces specific baseline neurochemical differences that substantially influence the magnitude of MA-induced sensitization. These findings demonstrate the utility of mouse metabolomics for identifying novel biomarkers, and developing more comprehensive neurochemical models, of psychostimulant sensitization. PMID:24034544
Spatiotemporal sensitivity analysis of vertical transport of pesticides in soil
Environmental fate and transport processes are influenced by many factors. Simulation models that mimic these processes often have complex implementations, which can lead to over-parameterization. Sensitivity analyses are subsequently used to identify critical parameters whose un...
Sensitivity analysis of infectious disease models: methods, advances and their application
Wu, Jianyong; Dhingra, Radhika; Gambhir, Manoj; Remais, Justin V.
2013-01-01
Sensitivity analysis (SA) can aid in identifying influential model parameters and optimizing model structure, yet infectious disease modelling has yet to adopt advanced SA techniques that are capable of providing considerable insights over traditional methods. We investigate five global SA methods—scatter plots, the Morris and Sobol’ methods, Latin hypercube sampling-partial rank correlation coefficient and the sensitivity heat map method—and detail their relative merits and pitfalls when applied to a microparasite (cholera) and macroparasite (schistosomaisis) transmission model. The methods investigated yielded similar results with respect to identifying influential parameters, but offered specific insights that vary by method. The classical methods differed in their ability to provide information on the quantitative relationship between parameters and model output, particularly over time. The heat map approach provides information about the group sensitivity of all model state variables, and the parameter sensitivity spectrum obtained using this method reveals the sensitivity of all state variables to each parameter over the course of the simulation period, especially valuable for expressing the dynamic sensitivity of a microparasite epidemic model to its parameters. A summary comparison is presented to aid infectious disease modellers in selecting appropriate methods, with the goal of improving model performance and design. PMID:23864497
Applying geologic sensitivity analysis to environmental risk management: The financial implications
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rogers, D.T.
The financial risks associated with environmental contamination can be staggering and are often difficult to identify and accurately assess. Geologic sensitivity analysis is gaining recognition as a significant and useful tool that can empower the user with crucial information concerning environmental risk management and brownfield redevelopment. It is particularly useful when (1) evaluating the potential risks associated with redevelopment of historical industrial facilities (brownfields) and (2) planning for future development, especially in areas of rapid development because the number of potential contaminating sources often increases with an increase in economic development. An examination of the financial implications relating to geologicmore » sensitivity analysis in southeastern Michigan from numerous case studies indicate that the environmental cost of contamination may be 100 to 1,000 times greater at a geologically sensitive location compared to the least sensitive location. Geologic sensitivity analysis has demonstrated that near-surface geology may influence the environmental impact of a contaminated site to a greater extent than the amount and type of industrial development.« less
Ethical sensitivity in professional practice: concept analysis.
Weaver, Kathryn; Morse, Janice; Mitcham, Carl
2008-06-01
This paper is a report of a concept analysis of ethical sensitivity. Ethical sensitivity enables nurses and other professionals to respond morally to the suffering and vulnerability of those receiving professional care and services. Because of its significance to nursing and other professional practices, ethical sensitivity deserves more focused analysis. A criteria-based method oriented toward pragmatic utility guided the analysis of 200 papers and books from the fields of nursing, medicine, psychology, dentistry, clinical ethics, theology, education, law, accounting or business, journalism, philosophy, political and social sciences and women's studies. This literature spanned 1970 to 2006 and was sorted by discipline and concept dimensions and examined for concept structure and use across various contexts. The analysis was completed in September 2007. Ethical sensitivity in professional practice develops in contexts of uncertainty, client suffering and vulnerability, and through relationships characterized by receptivity, responsiveness and courage on the part of professionals. Essential attributes of ethical sensitivity are identified as moral perception, affectivity and dividing loyalties. Outcomes include integrity preserving decision-making, comfort and well-being, learning and professional transcendence. Our findings promote ethical sensitivity as a type of practical wisdom that pursues client comfort and professional satisfaction with care delivery. The analysis and resulting model offers an inclusive view of ethical sensitivity that addresses some of the limitations with prior conceptualizations.
Daikoku, Tohru; Oyama, Yukari; Yajima, Misako; Sekizuka, Tsuyoshi; Kuroda, Makoto; Shimada, Yuka; Takehara, Kazuhiko; Miwa, Naoko; Okuda, Tomoko; Sata, Tetsutaro; Shiraki, Kimiyasu
2015-06-01
Herpes simplex virus 2 caused a genital ulcer, and a secondary herpetic whitlow appeared during acyclovir therapy. The secondary and recurrent whitlow isolates were acyclovir-resistant and temperature-sensitive in contrast to a genital isolate. We identified the ribonucleotide reductase mutation responsible for temperature-sensitivity by deep-sequencing analysis.
Glaubitz, Ulrike; Li, Xia; Schaedel, Sandra; Erban, Alexander; Sulpice, Ronan; Kopka, Joachim; Hincha, Dirk K; Zuther, Ellen
2017-01-01
Transcript and metabolite profiling were performed on leaves from six rice cultivars under high night temperature (HNT) condition. Six genes were identified as central for HNT response encoding proteins involved in transcription regulation, signal transduction, protein-protein interactions, jasmonate response and the biosynthesis of secondary metabolites. Sensitive cultivars showed specific changes in transcript abundance including abiotic stress responses, changes of cell wall-related genes, of ABA signaling and secondary metabolism. Additionally, metabolite profiles revealed a highly activated TCA cycle under HNT and concomitantly increased levels in pathways branching off that could be corroborated by enzyme activity measurements. Integrated data analysis using clustering based on one-dimensional self-organizing maps identified two profiles highly correlated with HNT sensitivity. The sensitivity profile included genes of the functional bins abiotic stress, hormone metabolism, cell wall, signaling, redox state, transcription factors, secondary metabolites and defence genes. In the tolerance profile, similar bins were affected with slight differences in hormone metabolism and transcription factor responses. Metabolites of the two profiles revealed involvement of GABA signaling, thus providing a link to the TCA cycle status in sensitive cultivars and of myo-inositol as precursor for inositol phosphates linking jasmonate signaling to the HNT response specifically in tolerant cultivars. © 2016 John Wiley & Sons Ltd.
Identifying significant environmental features using feature recognition.
DOT National Transportation Integrated Search
2015-10-01
The Department of Environmental Analysis at the Kentucky Transportation Cabinet has expressed an interest in feature-recognition capability because it may help analysts identify environmentally sensitive features in the landscape, : including those r...
Analysis of Publically Available Skin Sensitization Data from REACH Registrations 2008–2014
Luechtefeld, Thomas; Maertens, Alexandra; Russo, Daniel P.; Rovida, Costanza; Zhu, Hao; Hartung, Thomas
2017-01-01
Summary The public data on skin sensitization from REACH registrations already included 19,111 studies on skin sensitization in December 2014, making it the largest repository of such data so far (1,470 substances with mouse LLNA, 2,787 with GPMT, 762 with both in vivo and in vitro and 139 with only in vitro data). 21% were classified as sensitizers. The extracted skin sensitization data was analyzed to identify relationships in skin sensitization guidelines, visualize structural relationships of sensitizers, and build models to predict sensitization. A chemical with molecular weight > 500 Da is generally considered non-sensitizing owing to low bioavailability, but 49 sensitizing chemicals with a molecular weight > 500 Da were found. A chemical similarity map was produced using PubChem’s 2D Tanimoto similarity metric and Gephi force layout visualization. Nine clusters of chemicals were identified by Blondel’s module recognition algorithm revealing wide module-dependent variation. Approximately 31% of mapped chemicals are Michael’s acceptors but alone this does not imply skin sensitization. A simple sensitization model using molecular weight and five ToxTree structural alerts showed a balanced accuracy of 65.8% (specificity 80.4%, sensitivity 51.4%), demonstrating that structural alerts have information value. A simple variant of k-nearest neighbors outperformed the ToxTree approach even at 75% similarity threshold (82% balanced accuracy at 0.95 threshold). At higher thresholds, the balanced accuracy increased. Lower similarity thresholds decrease sensitivity faster than specificity. This analysis scopes the landscape of chemical skin sensitization, demonstrating the value of large public datasets for health hazard prediction. PMID:26863411
2012-04-24
compliance (Figure 3). This sensitivity analysis shows that public compliance is likely the most important consideration in saving lives. If the... public complies, medication effectiveness and POD throughput are the next two most important factors. Figure 3. Sensitivity Analysis ...government decision makers to the public . The number of gaps identified in this analysis is overwhelming, and improving the outcomes of the end-to
Global Sensitivity Analysis of Environmental Models: Convergence, Robustness and Validation
NASA Astrophysics Data System (ADS)
Sarrazin, Fanny; Pianosi, Francesca; Khorashadi Zadeh, Farkhondeh; Van Griensven, Ann; Wagener, Thorsten
2015-04-01
Global Sensitivity Analysis aims to characterize the impact that variations in model input factors (e.g. the parameters) have on the model output (e.g. simulated streamflow). In sampling-based Global Sensitivity Analysis, the sample size has to be chosen carefully in order to obtain reliable sensitivity estimates while spending computational resources efficiently. Furthermore, insensitive parameters are typically identified through the definition of a screening threshold: the theoretical value of their sensitivity index is zero but in a sampling-base framework they regularly take non-zero values. There is little guidance available for these two steps in environmental modelling though. The objective of the present study is to support modellers in making appropriate choices, regarding both sample size and screening threshold, so that a robust sensitivity analysis can be implemented. We performed sensitivity analysis for the parameters of three hydrological models with increasing level of complexity (Hymod, HBV and SWAT), and tested three widely used sensitivity analysis methods (Elementary Effect Test or method of Morris, Regional Sensitivity Analysis, and Variance-Based Sensitivity Analysis). We defined criteria based on a bootstrap approach to assess three different types of convergence: the convergence of the value of the sensitivity indices, of the ranking (the ordering among the parameters) and of the screening (the identification of the insensitive parameters). We investigated the screening threshold through the definition of a validation procedure. The results showed that full convergence of the value of the sensitivity indices is not necessarily needed to rank or to screen the model input factors. Furthermore, typical values of the sample sizes that are reported in the literature can be well below the sample sizes that actually ensure convergence of ranking and screening.
NASA Technical Reports Server (NTRS)
Benek, John A.; Luckring, James M.
2017-01-01
A NATO symposium held in 2008 identified many promising sensitivity analysis and un-certainty quantification technologies, but the maturity and suitability of these methods for realistic applications was not known. The STO Task Group AVT-191 was established to evaluate the maturity and suitability of various sensitivity analysis and uncertainty quantification methods for application to realistic problems of interest to NATO. The program ran from 2011 to 2015, and the work was organized into four discipline-centric teams: external aerodynamics, internal aerodynamics, aeroelasticity, and hydrodynamics. This paper presents an overview of the AVT-191 program content.
NASA Technical Reports Server (NTRS)
Benek, John A.; Luckring, James M.
2017-01-01
A NATO symposium held in Greece in 2008 identified many promising sensitivity analysis and uncertainty quantification technologies, but the maturity and suitability of these methods for realistic applications was not clear. The NATO Science and Technology Organization, Task Group AVT-191 was established to evaluate the maturity and suitability of various sensitivity analysis and uncertainty quantification methods for application to realistic vehicle development problems. The program ran from 2011 to 2015, and the work was organized into four discipline-centric teams: external aerodynamics, internal aerodynamics, aeroelasticity, and hydrodynamics. This paper summarizes findings and lessons learned from the task group.
NASA Astrophysics Data System (ADS)
Wang, Xu; Bi, Fengrong; Du, Haiping
2018-05-01
This paper aims to develop an 5-degree-of-freedom driver and seating system model for optimal vibration control. A new method for identification of the driver seating system parameters from experimental vibration measurement has been developed. The parameter sensitivity analysis has been conducted considering the random excitation frequency and system parameter uncertainty. The most and least sensitive system parameters for the transmissibility ratio have been identified. The optimised PID controllers have been developed to reduce the driver's body vibration.
NASA Astrophysics Data System (ADS)
Khorashadi Zadeh, Farkhondeh; Nossent, Jiri; van Griensven, Ann; Bauwens, Willy
2017-04-01
Parameter estimation is a major concern in hydrological modeling, which may limit the use of complex simulators with a large number of parameters. To support the selection of parameters to include in or exclude from the calibration process, Global Sensitivity Analysis (GSA) is widely applied in modeling practices. Based on the results of GSA, the influential and the non-influential parameters are identified (i.e. parameters screening). Nevertheless, the choice of the screening threshold below which parameters are considered non-influential is a critical issue, which has recently received more attention in GSA literature. In theory, the sensitivity index of a non-influential parameter has a value of zero. However, since numerical approximations, rather than analytical solutions, are utilized in GSA methods to calculate the sensitivity indices, small but non-zero indices may be obtained for the indices of non-influential parameters. In order to assess the threshold that identifies non-influential parameters in GSA methods, we propose to calculate the sensitivity index of a "dummy parameter". This dummy parameter has no influence on the model output, but will have a non-zero sensitivity index, representing the error due to the numerical approximation. Hence, the parameters whose indices are above the sensitivity index of the dummy parameter can be classified as influential, whereas the parameters whose indices are below this index are within the range of the numerical error and should be considered as non-influential. To demonstrated the effectiveness of the proposed "dummy parameter approach", 26 parameters of a Soil and Water Assessment Tool (SWAT) model are selected to be analyzed and screened, using the variance-based Sobol' and moment-independent PAWN methods. The sensitivity index of the dummy parameter is calculated from sampled data, without changing the model equations. Moreover, the calculation does not even require additional model evaluations for the Sobol' method. A formal statistical test validates these parameter screening results. Based on the dummy parameter screening, 11 model parameters are identified as influential. Therefore, it can be denoted that the "dummy parameter approach" can facilitate the parameter screening process and provide guidance for GSA users to define a screening-threshold, with only limited additional resources. Key words: Parameter screening, Global sensitivity analysis, Dummy parameter, Variance-based method, Moment-independent method
NASA Astrophysics Data System (ADS)
Razavi, Saman; Gupta, Hoshin V.
2015-05-01
Sensitivity analysis is an essential paradigm in Earth and Environmental Systems modeling. However, the term "sensitivity" has a clear definition, based in partial derivatives, only when specified locally around a particular point (e.g., optimal solution) in the problem space. Accordingly, no unique definition exists for "global sensitivity" across the problem space, when considering one or more model responses to different factors such as model parameters or forcings. A variety of approaches have been proposed for global sensitivity analysis, based on different philosophies and theories, and each of these formally characterizes a different "intuitive" understanding of sensitivity. These approaches focus on different properties of the model response at a fundamental level and may therefore lead to different (even conflicting) conclusions about the underlying sensitivities. Here we revisit the theoretical basis for sensitivity analysis, summarize and critically evaluate existing approaches in the literature, and demonstrate their flaws and shortcomings through conceptual examples. We also demonstrate the difficulty involved in interpreting "global" interaction effects, which may undermine the value of existing interpretive approaches. With this background, we identify several important properties of response surfaces that are associated with the understanding and interpretation of sensitivities in the context of Earth and Environmental System models. Finally, we highlight the need for a new, comprehensive framework for sensitivity analysis that effectively characterizes all of the important sensitivity-related properties of model response surfaces.
Park, Ji Hyun; Kim, Hyeon-Young; Lee, Hanna; Yun, Eun Kyoung
2015-12-01
This study compares the performance of the logistic regression and decision tree analysis methods for assessing the risk factors for infection in cancer patients undergoing chemotherapy. The subjects were 732 cancer patients who were receiving chemotherapy at K university hospital in Seoul, Korea. The data were collected between March 2011 and February 2013 and were processed for descriptive analysis, logistic regression and decision tree analysis using the IBM SPSS Statistics 19 and Modeler 15.1 programs. The most common risk factors for infection in cancer patients receiving chemotherapy were identified as alkylating agents, vinca alkaloid and underlying diabetes mellitus. The logistic regression explained 66.7% of the variation in the data in terms of sensitivity and 88.9% in terms of specificity. The decision tree analysis accounted for 55.0% of the variation in the data in terms of sensitivity and 89.0% in terms of specificity. As for the overall classification accuracy, the logistic regression explained 88.0% and the decision tree analysis explained 87.2%. The logistic regression analysis showed a higher degree of sensitivity and classification accuracy. Therefore, logistic regression analysis is concluded to be the more effective and useful method for establishing an infection prediction model for patients undergoing chemotherapy. Copyright © 2015 Elsevier Ltd. All rights reserved.
Chen, Lin; Zhu, Zhe; Gao, Wei; Jiang, Qixin; Yu, Jiangming; Fu, Chuangang
2017-09-05
Insulin-like growth factor 1 receptor (IGF-1R) is proved to contribute the development of many types of cancers. But, little is known about its roles in radio-resistance of colorectal cancer (CRC). Here, we demonstrated that low IGF-1R expression value was associated with the better radiotherapy sensitivity of CRC. Besides, through Quantitative Real-time PCR (qRT-PCR), the elevated expression value of epidermal growth factor receptor (EGFR) was observed in CRC cell lines (HT29, RKO) with high radio-sensitivity compared with those with low sensitivity (SW480, LOVO). The irradiation induced apoptosis rates of wild type and EGFR agonist (EGF) or IGF-1R inhibitor (NVP-ADW742) treated HT29 and SW480 cells were quantified by flow cytometry. As a result, the apoptosis rate of EGF and NVP-ADW742 treated HT29 cells was significantly higher than that of those wild type ones, which indicated that high EGFR and low IGF-1R expression level in CRC was associated with the high sensitivity to radiotherapy. We next conducted systemic bioinformatics analysis of genome-wide expression profiles of CRC samples from the Cancer Genome Atlas (TCGA). Differential expression analysis between IGF-1R and EGFR abnormal CRC samples, i.e. CRC samples with higher IGF-1R and lower EGFR expression levels based on their median expression values, and the rest of CRC samples identified potential genes contribute to radiotherapy sensitivity. Functional enrichment of analysis of those differential expression genes (DEGs) in the Database for Annotation, Visualization and Integrated Discovery (DAVID) indicated PPAR signaling pathway as an important pathway for the radio-resistance of CRC. Our study identified the potential biomarkers for the rational selection of radiotherapy for CRC patients. Copyright © 2017 Elsevier B.V. All rights reserved.
Song, Sang-Hoon; Lee, Naeun; Kim, Dong-Joon; Lee, Sooyeun; Jeong, Chul-Ho
2017-01-01
Molecular and metabolic alterations in cancer cells are one of the leading causes of acquired resistance to chemotherapeutics. In this study, we explored an experimental strategy to identify which of these alterations can induce erlotinib resistance in human pancreatic cancer. Using genetically matched erlotinib-sensitive (BxPC-3) and erlotinib-resistant (BxPC-3ER) pancreatic cancer cells, we conducted a multi-omics analysis of metabolomes and transcriptomes in these cells. Untargeted and targeted metabolomic analyses revealed significant changes in metabolic pathways involved in the regulation of polyamines, amino acids, and fatty acids. Further transcriptomic analysis identified that ornithine decarboxylase (ODC) and its major metabolite, putrescine, contribute to the acquisition of erlotinib resistance in BxPC-3ER cells. Notably, either pharmacological or genetic blockage of ODC was able to restore erlotinib sensitivity, and this could be rescued by treatment with exogenous putrescine in erlotinib-resistant BxPC-3ER cells. Moreover, using a panel of cancer cells we demonstrated that ODC expression levels in cancer cells are inversely correlated with sensitivity to chemotherapeutics. Taken together, our findings will begin to uncover mechanisms of acquired drug resistance and ultimately help to identify potential therapeutic markers in cancer. PMID:29190951
Vinnakota, Kalyan C; Beard, Daniel A; Dash, Ranjan K
2009-01-01
Identification of a complex biochemical system model requires appropriate experimental data. Models constructed on the basis of data from the literature often contain parameters that are not identifiable with high sensitivity and therefore require additional experimental data to identify those parameters. Here we report the application of a local sensitivity analysis to design experiments that will improve the identifiability of previously unidentifiable model parameters in a model of mitochondrial oxidative phosphorylation and tricaboxylic acid cycle. Experiments were designed based on measurable biochemical reactants in a dilute suspension of purified cardiac mitochondria with experimentally feasible perturbations to this system. Experimental perturbations and variables yielding the most number of parameters above a 5% sensitivity level are presented and discussed.
Analyzing reflective narratives to assess the ethical reasoning of pediatric residents.
Moon, Margaret; Taylor, Holly A; McDonald, Erin L; Hughes, Mark T; Beach, Mary Catherine; Carrese, Joseph A
2013-01-01
A limiting factor in ethics education in medical training has been difficulty in assessing competence in ethics. This study was conducted to test the concept that content analysis of pediatric residents' personal reflections about ethics experiences can identify changes in ethical sensitivity and reasoning over time. Analysis of written narratives focused on two of our ethics curriculum's goals: 1) To raise sensitivity to ethical issues in everyday clinical practice and 2) to enhance critical reflection on personal and professional values as they affect patient care. Content analysis of written reflections was guided by a tool developed to identify and assess the level of ethical reasoning in eight domains determined to be important aspects of ethical competence. Based on the assessment of narratives written at two times (12 to 16 months/apart) during their training, residents showed significant progress in two specific domains: use of professional values, and use of personal values. Residents did not show decline in ethical reasoning in any domain. This study demonstrates that content analysis of personal narratives may provide a useful method for assessment of developing ethical sensitivity and reasoning.
Voils, Corrine I.; Olsen, Maren K.; Williams, John W.; for the IMPACT Study Investigators
2008-01-01
Objective: To determine whether a subset of depressive symptoms could be identified to facilitate diagnosis of depression in older adults in primary care. Method: Secondary analysis was conducted on 898 participants aged 60 years or older with major depressive disorder and/or dysthymic disorder (according to DSM-IV criteria) who participated in the Improving Mood–Promoting Access to Collaborative Treatment (IMPACT) study, a multisite, randomized trial of collaborative care for depression (recruitment from July 1999 to August 2001). Linear regression was used to identify a core subset of depressive symptoms associated with decreased social, physical, and mental functioning. The sensitivity and specificity, adjusting for selection bias, were evaluated for these symptoms. The sensitivity and specificity of a second subset of 4 depressive symptoms previously validated in a midlife sample was also evaluated. Results: Psychomotor changes, fatigue, and suicidal ideation were associated with decreased functioning and served as the core set of symptoms. Adjusting for selection bias, the sensitivity of these 3 symptoms was 0.012 and specificity 0.994. The sensitivity of the 4 symptoms previously validated in a midlife sample was 0.019 and specificity was 0.997. Conclusion: We identified 3 depression symptoms that were highly specific for major depressive disorder in older adults. However, these symptoms and a previously identified subset were too insensitive for accurate diagnosis. Therefore, we recommend a full assessment of DSM-IV depression criteria for accurate diagnosis. PMID:18311416
Smith, P A; Son, P S; Callaghan, P M; Jederberg, W W; Kuhlmann, K; Still, K R
1996-07-17
Components of colophony (rosin) resin acids are sensitizers through dermal and pulmonary exposure to heated and unheated material. Significant work in the literature identifies specific resin acids and their oxidation products as sensitizers. Pulmonary exposure to colophony sensitizers has been estimated indirectly through formaldehyde exposure. To assess pulmonary sensitization from airborne resin acids, direct measurement is desired, as the degree to which aldehyde exposure correlates with that of resin acids during colophony heating is undefined. Any analytical method proposed should be applicable to a range of compounds and should also identify specific compounds present in a breathing zone sample. This work adapts OSHA Sampling and Analytical Method 58, which is designed to provide airborne concentration data for coal tar pitch volatile solids by air filtration through a glass fiber filter, solvent extraction of the filter, and gravimetric analysis of the non-volatile extract residue. In addition to data regarding total soluble material captured, a portion of the extract may be subjected to compound-specific analysis. Levels of soluble solids found during personal breathing zone sampling during electronics soldering in a Naval Aviation Depot ranged from below the "reliable quantitation limit" reported in the method to 7.98 mg/m3. Colophony-spiked filters analyzed in accordance with the method (modified) produced a limit of detection for total solvent-soluble colophony solids of 10 micrograms/filter. High performance liquid chromatography was used to identify abietic acid present in a breathing zone sample.
Sensitivity analysis of add-on price estimate for select silicon wafering technologies
NASA Technical Reports Server (NTRS)
Mokashi, A. R.
1982-01-01
The cost of producing wafers from silicon ingots is a major component of the add-on price of silicon sheet. Economic analyses of the add-on price estimates and their sensitivity internal-diameter (ID) sawing, multiblade slurry (MBS) sawing and fixed-abrasive slicing technique (FAST) are presented. Interim price estimation guidelines (IPEG) are used for estimating a process add-on price. Sensitivity analysis of price is performed with respect to cost parameters such as equipment, space, direct labor, materials (blade life) and utilities, and the production parameters such as slicing rate, slices per centimeter and process yield, using a computer program specifically developed to do sensitivity analysis with IPEG. The results aid in identifying the important cost parameters and assist in deciding the direction of technology development efforts.
Probabilistic sensitivity analysis for NICE technology assessment: not an optional extra.
Claxton, Karl; Sculpher, Mark; McCabe, Chris; Briggs, Andrew; Akehurst, Ron; Buxton, Martin; Brazier, John; O'Hagan, Tony
2005-04-01
Recently the National Institute for Clinical Excellence (NICE) updated its methods guidance for technology assessment. One aspect of the new guidance is to require the use of probabilistic sensitivity analysis with all cost-effectiveness models submitted to the Institute. The purpose of this paper is to place the NICE guidance on dealing with uncertainty into a broader context of the requirements for decision making; to explain the general approach that was taken in its development; and to address each of the issues which have been raised in the debate about the role of probabilistic sensitivity analysis in general. The most appropriate starting point for developing guidance is to establish what is required for decision making. On the basis of these requirements, the methods and framework of analysis which can best meet these needs can then be identified. It will be argued that the guidance on dealing with uncertainty and, in particular, the requirement for probabilistic sensitivity analysis, is justified by the requirements of the type of decisions that NICE is asked to make. Given this foundation, the main issues and criticisms raised during and after the consultation process are reviewed. Finally, some of the methodological challenges posed by the need fully to characterise decision uncertainty and to inform the research agenda will be identified and discussed. Copyright (c) 2005 John Wiley & Sons, Ltd.
Hill, Ryan M; Oosterhoff, Benjamin; Kaplow, Julie B
2017-07-01
Although a large number of risk markers for suicide ideation have been identified, little guidance has been provided to prospectively identify adolescents at risk for suicide ideation within community settings. The current study addressed this gap in the literature by utilizing classification tree analysis (CTA) to provide a decision-making model for screening adolescents at risk for suicide ideation. Participants were N = 4,799 youth (Mage = 16.15 years, SD = 1.63) who completed both Waves 1 and 2 of the National Longitudinal Study of Adolescent to Adult Health. CTA was used to generate a series of decision rules for identifying adolescents at risk for reporting suicide ideation at Wave 2. Findings revealed 3 distinct solutions with varying sensitivity and specificity for identifying adolescents who reported suicide ideation. Sensitivity of the classification trees ranged from 44.6% to 77.6%. The tree with greatest specificity and lowest sensitivity was based on a history of suicide ideation. The tree with moderate sensitivity and high specificity was based on depressive symptoms, suicide attempts or suicide among family and friends, and social support. The most sensitive but least specific tree utilized these factors and gender, ethnicity, hours of sleep, school-related factors, and future orientation. These classification trees offer community organizations options for instituting large-scale screenings for suicide ideation risk depending on the available resources and modality of services to be provided. This study provides a theoretically and empirically driven model for prospectively identifying adolescents at risk for suicide ideation and has implications for preventive interventions among at-risk youth. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Testing alternative ground water models using cross-validation and other methods
Foglia, L.; Mehl, S.W.; Hill, M.C.; Perona, P.; Burlando, P.
2007-01-01
Many methods can be used to test alternative ground water models. Of concern in this work are methods able to (1) rank alternative models (also called model discrimination) and (2) identify observations important to parameter estimates and predictions (equivalent to the purpose served by some types of sensitivity analysis). Some of the measures investigated are computationally efficient; others are computationally demanding. The latter are generally needed to account for model nonlinearity. The efficient model discrimination methods investigated include the information criteria: the corrected Akaike information criterion, Bayesian information criterion, and generalized cross-validation. The efficient sensitivity analysis measures used are dimensionless scaled sensitivity (DSS), composite scaled sensitivity, and parameter correlation coefficient (PCC); the other statistics are DFBETAS, Cook's D, and observation-prediction statistic. Acronyms are explained in the introduction. Cross-validation (CV) is a computationally intensive nonlinear method that is used for both model discrimination and sensitivity analysis. The methods are tested using up to five alternative parsimoniously constructed models of the ground water system of the Maggia Valley in southern Switzerland. The alternative models differ in their representation of hydraulic conductivity. A new method for graphically representing CV and sensitivity analysis results for complex models is presented and used to evaluate the utility of the efficient statistics. The results indicate that for model selection, the information criteria produce similar results at much smaller computational cost than CV. For identifying important observations, the only obviously inferior linear measure is DSS; the poor performance was expected because DSS does not include the effects of parameter correlation and PCC reveals large parameter correlations. ?? 2007 National Ground Water Association.
Genetics and clinical response to warfarin and edoxaban in patients with venous thromboembolism
Vandell, Alexander G; Walker, Joseph; Brown, Karen S; Zhang, George; Lin, Min; Grosso, Michael A; Mercuri, Michele F
2017-01-01
Objective The aim of this study was to investigate whether genetic variants can identify patients with venous thromboembolism (VTE) at an increased risk of bleeding with warfarin. Methods Hokusai-venous thromboembolism (Hokusai VTE), a randomised, multinational, double-blind, non-inferiority trial, evaluated the safety and efficacy of edoxaban versus warfarin in patients with VTE initially treated with heparin. In this subanalysis of Hokusai VTE, patients genotyped for variants in CYP2C9 and VKORC1 genes were divided into three warfarin sensitivity types (normal, sensitive and highly sensitive) based on their genotypes. An exploratory analysis was also conducted comparing normal responders to pooled sensitive responders (ie, sensitive and highly sensitive responders). Results The analysis included 47.7% (3956/8292) of the patients in Hokusai VTE. Among 1978 patients randomised to warfarin, 63.0% (1247) were normal responders, 34.1% (675) were sensitive responders and 2.8% (56) were highly sensitive responders. Compared with normal responders, sensitive and highly sensitive responders had heparin therapy discontinued earlier (p<0.001), had a decreased final weekly warfarin dose (p<0.001), spent more time overanticoagulated (p<0.001) and had an increased bleeding risk with warfarin (sensitive responders HR 1.38 [95% CI 1.11 to 1.71], p=0.0035; highly sensitive responders 1.79 [1.09 to 2.99]; p=0.0252). Conclusion In this study, CYP2C9 and VKORC1 genotypes identified patients with VTE at increased bleeding risk with warfarin. Trial registration number NCT00986154. PMID:28689179
Maebe, Kevin; Meeus, Ivan; De Riek, Jan; Smagghe, Guy
2015-01-01
Bumblebees such as Bombus terrestris are essential pollinators in natural and managed ecosystems. In addition, this species is intensively used in agriculture for its pollination services, for instance in tomato and pepper greenhouses. Here we performed a quantitative trait loci (QTL) analysis on B. terrestris using 136 microsatellite DNA markers to identify genes linked with 20 traits including light sensitivity, body size and mass, and eye and hind leg measures. By composite interval mapping (IM), we found 83 and 34 suggestive QTLs for 19 of the 20 traits at the linkage group wide significance levels of p = 0.05 and 0.01, respectively. Furthermore, we also found five significant QTLs at the genome wide significant level of p = 0.05. Individual QTLs accounted for 7.5-53.3% of the phenotypic variation. For 15 traits, at least one QTL was confirmed with multiple QTL model mapping. Multivariate principal components analysis confirmed 11 univariate suggestive QTLs but revealed three suggestive QTLs not identified by the individual traits. We also identified several candidate genes linked with light sensitivity, in particular the Phosrestin-1-like gene is a primary candidate for its phototransduction function. In conclusion, we believe that the suggestive and significant QTLs, and markers identified here, can be of use in marker-assisted breeding to improve selection towards light sensitive bumblebees, and thus also the pollination service of bumblebees.
NASA Astrophysics Data System (ADS)
Dai, Heng; Chen, Xingyuan; Ye, Ming; Song, Xuehang; Zachara, John M.
2017-05-01
Sensitivity analysis is an important tool for development and improvement of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study, we developed a new sensitivity analysis method that integrates the concept of variance-based method with a hierarchical uncertainty quantification framework. Different uncertain inputs are grouped and organized into a multilayer framework based on their characteristics and dependency relationships to reduce the dimensionality of the sensitivity analysis. A set of new sensitivity indices are defined for the grouped inputs using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially distributed input variables.
NASA Astrophysics Data System (ADS)
Dai, H.; Chen, X.; Ye, M.; Song, X.; Zachara, J. M.
2017-12-01
Sensitivity analysis is an important tool for development and improvement of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study we developed a new sensitivity analysis method that integrates the concept of variance-based method with a hierarchical uncertainty quantification framework. Different uncertain inputs are grouped and organized into a multi-layer framework based on their characteristics and dependency relationships to reduce the dimensionality of the sensitivity analysis. A set of new sensitivity indices are defined for the grouped inputs using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially-distributed input variables.
Sobol' sensitivity analysis for stressor impacts on honeybee ...
We employ Monte Carlo simulation and nonlinear sensitivity analysis techniques to describe the dynamics of a bee exposure model, VarroaPop. Daily simulations are performed of hive population trajectories, taking into account queen strength, foraging success, mite impacts, weather, colony resources, population structure, and other important variables. This allows us to test the effects of defined pesticide exposure scenarios versus controlled simulations that lack pesticide exposure. The daily resolution of the model also allows us to conditionally identify sensitivity metrics. We use the variancebased global decomposition sensitivity analysis method, Sobol’, to assess firstand secondorder parameter sensitivities within VarroaPop, allowing us to determine how variance in the output is attributed to each of the input variables across different exposure scenarios. Simulations with VarroaPop indicate queen strength, forager life span and pesticide toxicity parameters are consistent, critical inputs for colony dynamics. Further analysis also reveals that the relative importance of these parameters fluctuates throughout the simulation period according to the status of other inputs. Our preliminary results show that model variability is conditional and can be attributed to different parameters depending on different timescales. By using sensitivity analysis to assess model output and variability, calibrations of simulation models can be better informed to yield more
Evaluation of Microbial Load in Oropharyngeal Mucosa from Tannery Workers
Castellanos-Arévalo, Diana C.; Castellanos-Arévalo, Andrea P.; Camarena-Pozos, David A.; Colli-Mull, Juan G.; Maldonado-Vega, María
2014-01-01
Background Animal skin provides an ideal medium for the propagation of microorganisms and it is used like raw material in the tannery and footware industry. The aim of this study was to evaluate and identify the microbial load in oropharyngeal mucosa of tannery employees. Methods The health risk was estimated based on the identification of microorganisms found in the oropharyngeal mucosa samples. The study was conducted in a tanners group and a control group. Samples were taken from oropharyngeal mucosa and inoculated on plates with selective medium. In the samples, bacteria were identified by 16S ribosomal DNA analysis and the yeasts through a presumptive method. In addition, the sensitivity of these microorganisms to antibiotics/antifungals was evaluated. Results The identified bacteria belonged to the families Enterobacteriaceae, Pseudomonadaceae, Neisseriaceae, Alcaligenaceae, Moraxellaceae, and Xanthomonadaceae, of which some species are considered as pathogenic or opportunistic microorganisms; these bacteria were not present in the control group. Forty-two percent of bacteria identified in the tanners group are correlated with respiratory diseases. Yeasts were also identified, including the following species: Candida glabrata, Candida tropicalis, Candida albicans, and Candida krusei. Regarding the sensitivity test of bacteria identified in the tanners group, 90% showed sensitivity to piperacillin/tazobactam, 87% showed sensitivity to ticarcillin/clavulanic acid, 74% showed sensitivity to ampicillin/sulbactam, and 58% showed sensitivity to amoxicillin/clavulanic acid. Conclusion Several of the bacteria and yeast identified in the oropharyngeal mucosa of tanners have been correlated with infections in humans and have already been reported as airborne microorganisms in this working environment, representing a health risk for workers. PMID:25830072
System parameter identification from projection of inverse analysis
NASA Astrophysics Data System (ADS)
Liu, K.; Law, S. S.; Zhu, X. Q.
2017-05-01
The output of a system due to a change of its parameters is often approximated with the sensitivity matrix from the first order Taylor series. The system output can be measured in practice, but the perturbation in the system parameters is usually not available. Inverse sensitivity analysis can be adopted to estimate the unknown system parameter perturbation from the difference between the observation output data and corresponding analytical output data calculated from the original system model. The inverse sensitivity analysis is re-visited in this paper with improvements based on the Principal Component Analysis on the analytical data calculated from the known system model. The identification equation is projected into a subspace of principal components of the system output, and the sensitivity of the inverse analysis is improved with an iterative model updating procedure. The proposed method is numerical validated with a planar truss structure and dynamic experiments with a seven-storey planar steel frame. Results show that it is robust to measurement noise, and the location and extent of stiffness perturbation can be identified with better accuracy compared with the conventional response sensitivity-based method.
Sum, Simon Siu-Man; Marcus, Andrea F; Blair, Debra; Olejnik, Laura A; Cao, Joyce; Parrott, J Scott; Peters, Emily N; Hand, Rosa K; Byham-Gray, Laura D
2017-09-01
To compare the 7-point subjective global assessment (SGA) and the protein energy wasting (PEW) score with nutrition evaluations conducted by registered dietitian nutritionists in identifying PEW risk in stage 5 chronic kidney disease patients on maintenance hemodialysis. This study is a secondary analysis of a cross-sectional study entitled "Development and Validation of a Predictive energy Equation in Hemodialysis". PEW risk identified by the 7-point SGA and the PEW score was compared against the nutrition evaluations conducted by registered dietitian nutritionists through data examination from the original study (reference standard). A total of 133 patients were included for the analysis. The sensitivity, specificity, positive and negative predictive value (PPV and NPV), positive and negative likelihood ratio (PLR and NLR) of both scoring tools were calculated when compared against the reference standard. The patients were predominately African American (n = 112, 84.2%), non-Hispanic (n = 101, 75.9%), and male (n = 80, 60.2%). Both the 7-point SGA (sensitivity = 78.6%, specificity = 59.1%, PPV = 33.9%, NPV = 91.2%, PLR = 1.9, and NLR = 0.4) and the PEW score (sensitivity = 100%, specificity = 28.6%, PPV = 27.2%, NPV = 100%, PLR = 1.4, and NLR = 0) were more sensitive than specific in identifying PEW risk. The 7-point SGA may miss 21.4% patients having PEW and falsely identify 40.9% of patients who do not have PEW. The PEW score can identify PEW risk in all patients, but 71.4% of patients identified may not have PEW risk. Both the 7-point SGA and the PEW score could identify PEW risk. The 7-point SGA was more specific, and the PEW score was more sensitive. Both scoring tools were found to be clinically confident in identifying patients who were actually not at PEW risk. Copyright © 2017 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.
Sensitivity analysis of automatic flight control systems using singular value concepts
NASA Technical Reports Server (NTRS)
Herrera-Vaillard, A.; Paduano, J.; Downing, D.
1985-01-01
A sensitivity analysis is presented that can be used to judge the impact of vehicle dynamic model variations on the relative stability of multivariable continuous closed-loop control systems. The sensitivity analysis uses and extends the singular-value concept by developing expressions for the gradients of the singular value with respect to variations in the vehicle dynamic model and the controller design. Combined with a priori estimates of the accuracy of the model, the gradients are used to identify the elements in the vehicle dynamic model and controller that could severely impact the system's relative stability. The technique is demonstrated for a yaw/roll damper stability augmentation designed for a business jet.
Mutel, Christopher L; de Baan, Laura; Hellweg, Stefanie
2013-06-04
Comprehensive sensitivity analysis is a significant tool to interpret and improve life cycle assessment (LCA) models, but is rarely performed. Sensitivity analysis will increase in importance as inventory databases become regionalized, increasing the number of system parameters, and parametrized, adding complexity through variables and nonlinear formulas. We propose and implement a new two-step approach to sensitivity analysis. First, we identify parameters with high global sensitivities for further examination and analysis with a screening step, the method of elementary effects. Second, the more computationally intensive contribution to variance test is used to quantify the relative importance of these parameters. The two-step sensitivity test is illustrated on a regionalized, nonlinear case study of the biodiversity impacts from land use of cocoa production, including a worldwide cocoa products trade model. Our simplified trade model can be used for transformable commodities where one is assessing market shares that vary over time. In the case study, the highly uncertain characterization factors for the Ivory Coast and Ghana contributed more than 50% of variance for almost all countries and years examined. The two-step sensitivity test allows for the interpretation, understanding, and improvement of large, complex, and nonlinear LCA systems.
USDA-ARS?s Scientific Manuscript database
This paper assesses the impact of different likelihood functions in identifying sensitive parameters of the highly parameterized, spatially distributed Soil and Water Assessment Tool (SWAT) watershed model for multiple variables at multiple sites. The global one-factor-at-a-time (OAT) method of Morr...
NASA Astrophysics Data System (ADS)
Vanrolleghem, Peter A.; Mannina, Giorgio; Cosenza, Alida; Neumann, Marc B.
2015-03-01
Sensitivity analysis represents an important step in improving the understanding and use of environmental models. Indeed, by means of global sensitivity analysis (GSA), modellers may identify both important (factor prioritisation) and non-influential (factor fixing) model factors. No general rule has yet been defined for verifying the convergence of the GSA methods. In order to fill this gap this paper presents a convergence analysis of three widely used GSA methods (SRC, Extended FAST and Morris screening) for an urban drainage stormwater quality-quantity model. After the convergence was achieved the results of each method were compared. In particular, a discussion on peculiarities, applicability, and reliability of the three methods is presented. Moreover, a graphical Venn diagram based classification scheme and a precise terminology for better identifying important, interacting and non-influential factors for each method is proposed. In terms of convergence, it was shown that sensitivity indices related to factors of the quantity model achieve convergence faster. Results for the Morris screening method deviated considerably from the other methods. Factors related to the quality model require a much higher number of simulations than the number suggested in literature for achieving convergence with this method. In fact, the results have shown that the term "screening" is improperly used as the method may exclude important factors from further analysis. Moreover, for the presented application the convergence analysis shows more stable sensitivity coefficients for the Extended-FAST method compared to SRC and Morris screening. Substantial agreement in terms of factor fixing was found between the Morris screening and Extended FAST methods. In general, the water quality related factors exhibited more important interactions than factors related to water quantity. Furthermore, in contrast to water quantity model outputs, water quality model outputs were found to be characterised by high non-linearity.
Sensitivity-Based Guided Model Calibration
NASA Astrophysics Data System (ADS)
Semnani, M.; Asadzadeh, M.
2017-12-01
A common practice in automatic calibration of hydrologic models is applying the sensitivity analysis prior to the global optimization to reduce the number of decision variables (DVs) by identifying the most sensitive ones. This two-stage process aims to improve the optimization efficiency. However, Parameter sensitivity information can be used to enhance the ability of the optimization algorithms to find good quality solutions in a fewer number of solution evaluations. This improvement can be achieved by increasing the focus of optimization on sampling from the most sensitive parameters in each iteration. In this study, the selection process of the dynamically dimensioned search (DDS) optimization algorithm is enhanced by utilizing a sensitivity analysis method to put more emphasis on the most sensitive decision variables for perturbation. The performance of DDS with the sensitivity information is compared to the original version of DDS for different mathematical test functions and a model calibration case study. Overall, the results show that DDS with sensitivity information finds nearly the same solutions as original DDS, however, in a significantly fewer number of solution evaluations.
Tian, Yuan; Hassmiller Lich, Kristen; Osgood, Nathaniel D; Eom, Kirsten; Matchar, David B
2016-11-01
As health services researchers and decision makers tackle more difficult problems using simulation models, the number of parameters and the corresponding degree of uncertainty have increased. This often results in reduced confidence in such complex models to guide decision making. To demonstrate a systematic approach of linked sensitivity analysis, calibration, and uncertainty analysis to improve confidence in complex models. Four techniques were integrated and applied to a System Dynamics stroke model of US veterans, which was developed to inform systemwide intervention and research planning: Morris method (sensitivity analysis), multistart Powell hill-climbing algorithm and generalized likelihood uncertainty estimation (calibration), and Monte Carlo simulation (uncertainty analysis). Of 60 uncertain parameters, sensitivity analysis identified 29 needing calibration, 7 that did not need calibration but significantly influenced key stroke outcomes, and 24 not influential to calibration or stroke outcomes that were fixed at their best guess values. One thousand alternative well-calibrated baselines were obtained to reflect calibration uncertainty and brought into uncertainty analysis. The initial stroke incidence rate among veterans was identified as the most influential uncertain parameter, for which further data should be collected. That said, accounting for current uncertainty, the analysis of 15 distinct prevention and treatment interventions provided a robust conclusion that hypertension control for all veterans would yield the largest gain in quality-adjusted life years. For complex health care models, a mixed approach was applied to examine the uncertainty surrounding key stroke outcomes and the robustness of conclusions. We demonstrate that this rigorous approach can be practical and advocate for such analysis to promote understanding of the limits of certainty in applying models to current decisions and to guide future data collection. © The Author(s) 2016.
Search Strategy to Identify Dental Survival Analysis Articles Indexed in MEDLINE.
Layton, Danielle M; Clarke, Michael
2016-01-01
Articles reporting survival outcomes (time-to-event outcomes) in patients over time are challenging to identify in the literature. Research shows the words authors use to describe their dental survival analyses vary, and that allocation of medical subject headings by MEDLINE indexers is inconsistent. Together, this undermines accurate article identification. The present study aims to develop and validate a search strategy to identify dental survival analyses indexed in MEDLINE (Ovid). A gold standard cohort of articles was identified to derive the search terms, and an independent gold standard cohort of articles was identified to test and validate the proposed search strategies. The first cohort included all 6,955 articles published in the 50 dental journals with the highest impact factors in 2008, of which 95 articles were dental survival articles. The second cohort included all 6,514 articles published in the 50 dental journals with the highest impact factors for 2012, of which 148 were dental survival articles. Each cohort was identified by a systematic hand search. Performance parameters of sensitivity, precision, and number needed to read (NNR) for the search strategies were calculated. Sensitive, precise, and optimized search strategies were developed and validated. The performances of the search strategy maximizing sensitivity were 92% sensitivity, 14% precision, and 7.11 NNR; the performances of the strategy maximizing precision were 93% precision, 10% sensitivity, and 1.07 NNR; and the performances of the strategy optimizing the balance between sensitivity and precision were 83% sensitivity, 24% precision, and 4.13 NNR. The methods used to identify search terms were objective, not subjective. The search strategies were validated in an independent group of articles that included different journals and different publication years. Across the three search strategies, dental survival articles can be identified with sensitivity up to 92%, precision up to 93%, and NNR of less than two articles to identify relevant records. This research has highlighted the impact that variation in reporting and indexing has on article identification and has improved researchers' ability to identify dental survival articles.
Towards simplification of hydrologic modeling: Identification of dominant processes
Markstrom, Steven; Hay, Lauren E.; Clark, Martyn P.
2016-01-01
The Precipitation–Runoff Modeling System (PRMS), a distributed-parameter hydrologic model, has been applied to the conterminous US (CONUS). Parameter sensitivity analysis was used to identify: (1) the sensitive input parameters and (2) particular model output variables that could be associated with the dominant hydrologic process(es). Sensitivity values of 35 PRMS calibration parameters were computed using the Fourier amplitude sensitivity test procedure on 110 000 independent hydrologically based spatial modeling units covering the CONUS and then summarized to process (snowmelt, surface runoff, infiltration, soil moisture, evapotranspiration, interflow, baseflow, and runoff) and model performance statistic (mean, coefficient of variation, and autoregressive lag 1). Identified parameters and processes provide insight into model performance at the location of each unit and allow the modeler to identify the most dominant process on the basis of which processes are associated with the most sensitive parameters. The results of this study indicate that: (1) the choice of performance statistic and output variables has a strong influence on parameter sensitivity, (2) the apparent model complexity to the modeler can be reduced by focusing on those processes that are associated with sensitive parameters and disregarding those that are not, (3) different processes require different numbers of parameters for simulation, and (4) some sensitive parameters influence only one hydrologic process, while others may influence many
ON IDENTIFIABILITY OF NONLINEAR ODE MODELS AND APPLICATIONS IN VIRAL DYNAMICS
MIAO, HONGYU; XIA, XIAOHUA; PERELSON, ALAN S.; WU, HULIN
2011-01-01
Ordinary differential equations (ODE) are a powerful tool for modeling dynamic processes with wide applications in a variety of scientific fields. Over the last 2 decades, ODEs have also emerged as a prevailing tool in various biomedical research fields, especially in infectious disease modeling. In practice, it is important and necessary to determine unknown parameters in ODE models based on experimental data. Identifiability analysis is the first step in determing unknown parameters in ODE models and such analysis techniques for nonlinear ODE models are still under development. In this article, we review identifiability analysis methodologies for nonlinear ODE models developed in the past one to two decades, including structural identifiability analysis, practical identifiability analysis and sensitivity-based identifiability analysis. Some advanced topics and ongoing research are also briefly reviewed. Finally, some examples from modeling viral dynamics of HIV, influenza and hepatitis viruses are given to illustrate how to apply these identifiability analysis methods in practice. PMID:21785515
A comparison of analysis methods to estimate contingency strength.
Lloyd, Blair P; Staubitz, Johanna L; Tapp, Jon T
2018-05-09
To date, several data analysis methods have been used to estimate contingency strength, yet few studies have compared these methods directly. To compare the relative precision and sensitivity of four analysis methods (i.e., exhaustive event-based, nonexhaustive event-based, concurrent interval, concurrent+lag interval), we applied all methods to a simulated data set in which several response-dependent and response-independent schedules of reinforcement were programmed. We evaluated the degree to which contingency strength estimates produced from each method (a) corresponded with expected values for response-dependent schedules and (b) showed sensitivity to parametric manipulations of response-independent reinforcement. Results indicated both event-based methods produced contingency strength estimates that aligned with expected values for response-dependent schedules, but differed in sensitivity to response-independent reinforcement. The precision of interval-based methods varied by analysis method (concurrent vs. concurrent+lag) and schedule type (continuous vs. partial), and showed similar sensitivities to response-independent reinforcement. Recommendations and considerations for measuring contingencies are identified. © 2018 Society for the Experimental Analysis of Behavior.
Computational methods for efficient structural reliability and reliability sensitivity analysis
NASA Technical Reports Server (NTRS)
Wu, Y.-T.
1993-01-01
This paper presents recent developments in efficient structural reliability analysis methods. The paper proposes an efficient, adaptive importance sampling (AIS) method that can be used to compute reliability and reliability sensitivities. The AIS approach uses a sampling density that is proportional to the joint PDF of the random variables. Starting from an initial approximate failure domain, sampling proceeds adaptively and incrementally with the goal of reaching a sampling domain that is slightly greater than the failure domain to minimize over-sampling in the safe region. Several reliability sensitivity coefficients are proposed that can be computed directly and easily from the above AIS-based failure points. These probability sensitivities can be used for identifying key random variables and for adjusting design to achieve reliability-based objectives. The proposed AIS methodology is demonstrated using a turbine blade reliability analysis problem.
Iverieli, M V; Abashidze, N O; Gogishvili, Kh B
2009-04-01
The aim of the research was to study sensitivity of specific microorganisms from the periodontal pockets of patients with rapidly progressive periodontal disease to Taromentine. 95 patients aged 21 to 35 years (50 women (52,6+/-33,62) and 45 men (47,36+/-3,62)) with rapidly progressive form of periodontal desease were observed. Porphiromonas gingivalis was identifide in 83 out of 95 patients (87,36+/-2,06). Prevotella intermedia - in 31 patients (32,6+/-2,750); Actinobacillus actinomycetemcomitans - in 23 patients (24,2+/-2,050); Bacteroides forsythus - in 19 patients (20,0+/-2,360); Treponema denticola - in 16 patients (16,84+/-2,190); Candida - in 11 patients (11,57+/-1,80). The sensitivity of all cultures to Taromentine was investigated: 134 (77,9+/-1,89) out of 183 identified markers demonstrated sensitivity to Taromentine. Demostrated sensitivity to Taromentine: 64 (37,2+/-1,06) out of 83 identified cultures of Porphiromonas gingivalis, 24 (13,95+/-1,85) out of 31 identified cultures of Prevotela intermedia, 18 (10,47+/-1,05) out of 23 identified cultures of Actinobacillus actinomycetemcomitans, 15 (8,7+/-1,86) out of 19 identified cultures of Bacteroides forsythus, and 13 (7,84+/-1,09) out of 16 identified cultures of Treponema denticola. Totally 38 (22,1+/-1,59) out of 172 identified periodontal markers demonstrated resistence to Taromentine. The results of analysis showed that Taromentine could be recommended in complex treatment of periodontal diseases.
Silva, M M; Lemos, J M; Coito, A; Costa, B A; Wigren, T; Mendonça, T
2014-01-01
This paper addresses the local identifiability and sensitivity properties of two classes of Wiener models for the neuromuscular blockade and depth of hypnosis, when drug dose profiles like the ones commonly administered in the clinical practice are used as model inputs. The local parameter identifiability was assessed based on the singular value decomposition of the normalized sensitivity matrix. For the given input signal excitation, the results show an over-parameterization of the standard pharmacokinetic/pharmacodynamic models. The same identifiability assessment was performed on recently proposed minimally parameterized parsimonious models for both the neuromuscular blockade and the depth of hypnosis. The results show that the majority of the model parameters are identifiable from the available input-output data. This indicates that any identification strategy based on the minimally parameterized parsimonious Wiener models for the neuromuscular blockade and for the depth of hypnosis is likely to be more successful than if standard models are used. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Single-molecule detection: applications to ultrasensitive biochemical analysis
NASA Astrophysics Data System (ADS)
Castro, Alonso; Shera, E. Brooks
1995-06-01
Recent developments in laser-based detection of fluorescent molecules have made possible the implementation of very sensitive techniques for biochemical analysis. We present and discuss our experiments on the applications of our recently developed technique of single-molecule detection to the analysis of molecules of biological interest. These newly developed methods are capable of detecting and identifying biomolecules at the single-molecule level of sensitivity. In one case, identification is based on measuring fluorescence brightness from single molecules. In another, molecules are classified by determining their electrophoretic velocities.
How often do sensitivity analyses for economic parameters change cost-utility analysis conclusions?
Schackman, Bruce R; Gold, Heather Taffet; Stone, Patricia W; Neumann, Peter J
2004-01-01
There is limited evidence about the extent to which sensitivity analysis has been used in the cost-effectiveness literature. Sensitivity analyses for health-related QOL (HR-QOL), cost and discount rate economic parameters are of particular interest because they measure the effects of methodological and estimation uncertainties. To investigate the use of sensitivity analyses in the pharmaceutical cost-utility literature in order to test whether a change in economic parameters could result in a different conclusion regarding the cost effectiveness of the intervention analysed. Cost-utility analyses of pharmaceuticals identified in a prior comprehensive audit (70 articles) were reviewed and further audited. For each base case for which sensitivity analyses were reported (n = 122), up to two sensitivity analyses for HR-QOL (n = 133), cost (n = 99), and discount rate (n = 128) were examined. Article mentions of thresholds for acceptable cost-utility ratios were recorded (total 36). Cost-utility ratios were denominated in US dollars for the year reported in each of the original articles in order to determine whether a different conclusion would have been indicated at the time the article was published. Quality ratings from the original audit for articles where sensitivity analysis results crossed the cost-utility ratio threshold above the base-case result were compared with those that did not. The most frequently mentioned cost-utility thresholds were $US20,000/QALY, $US50,000/QALY, and $US100,000/QALY. The proportions of sensitivity analyses reporting quantitative results that crossed the threshold above the base-case results (or where the sensitivity analysis result was dominated) were 31% for HR-QOL sensitivity analyses, 20% for cost-sensitivity analyses, and 15% for discount-rate sensitivity analyses. Almost half of the discount-rate sensitivity analyses did not report quantitative results. Articles that reported sensitivity analyses where results crossed the cost-utility threshold above the base-case results (n = 25) were of somewhat higher quality, and were more likely to justify their sensitivity analysis parameters, than those that did not (n = 45), but the overall quality rating was only moderate. Sensitivity analyses for economic parameters are widely reported and often identify whether choosing different assumptions leads to a different conclusion regarding cost effectiveness. Changes in HR-QOL and cost parameters should be used to test alternative guideline recommendations when there is uncertainty regarding these parameters. Changes in discount rates less frequently produce results that would change the conclusion about cost effectiveness. Improving the overall quality of published studies and describing the justifications for parameter ranges would allow more meaningful conclusions to be drawn from sensitivity analyses.
Genetics and clinical response to warfarin and edoxaban in patients with venous thromboembolism.
Vandell, Alexander G; Walker, Joseph; Brown, Karen S; Zhang, George; Lin, Min; Grosso, Michael A; Mercuri, Michele F
2017-11-01
The aim of this study was to investigate whether genetic variants can identify patients with venous thromboembolism (VTE) at an increased risk of bleeding with warfarin. Hokusai-venous thromboembolism (Hokusai VTE), a randomised, multinational, double-blind, non-inferiority trial, evaluated the safety and efficacy of edoxaban versus warfarin in patients with VTE initially treated with heparin. In this subanalysis of Hokusai VTE, patients genotyped for variants in CYP2C9 and VKORC1 genes were divided into three warfarin sensitivity types (normal, sensitive and highly sensitive) based on their genotypes. An exploratory analysis was also conducted comparing normal responders to pooled sensitive responders (ie, sensitive and highly sensitive responders). The analysis included 47.7% (3956/8292) of the patients in Hokusai VTE. Among 1978 patients randomised to warfarin, 63.0% (1247) were normal responders, 34.1% (675) were sensitive responders and 2.8% (56) were highly sensitive responders. Compared with normal responders, sensitive and highly sensitive responders had heparin therapy discontinued earlier (p<0.001), had a decreased final weekly warfarin dose (p<0.001), spent more time overanticoagulated (p<0.001) and had an increased bleeding risk with warfarin (sensitive responders HR 1.38 [95% CI 1.11 to 1.71], p=0.0035; highly sensitive responders 1.79 [1.09 to 2.99]; p=0.0252). In this study, CYP2C9 and VKORC1 genotypes identified patients with VTE at increased bleeding risk with warfarin. NCT00986154. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Development and application of optimum sensitivity analysis of structures
NASA Technical Reports Server (NTRS)
Barthelemy, J. F. M.; Hallauer, W. L., Jr.
1984-01-01
The research focused on developing an algorithm applying optimum sensitivity analysis for multilevel optimization. The research efforts have been devoted to assisting NASA Langley's Interdisciplinary Research Office (IRO) in the development of a mature methodology for a multilevel approach to the design of complex (large and multidisciplinary) engineering systems. An effort was undertaken to identify promising multilevel optimization algorithms. In the current reporting period, the computer program generating baseline single level solutions was completed and tested out.
Sensitivity and Specificity of Polysomnographic Criteria for Defining Insomnia
Edinger, Jack D.; Ulmer, Christi S.; Means, Melanie K.
2013-01-01
Study Objectives: In recent years, polysomnography-based eligibility criteria have been increasingly used to identify candidates for insomnia research, and this has been particularly true of studies evaluating pharmacologic therapy for primary insomnia. However, the sensitivity and specificity of PSG for identifying individuals with insomnia is unknown, and there is no consensus on the criteria sets which should be used for participant selection. In the current study, an archival data set was used to test the sensitivity and specificity of PSG measures for identifying individuals with primary insomnia in both home and lab settings. We then evaluated the sensitivity and specificity of the eligibility criteria employed in a number of recent insomnia trials for identifying primary insomnia sufferers in our sample. Design: Archival data analysis. Settings: Study participants' homes and a clinical sleep laboratory. Participants: Adults: 76 with primary insomnia and 78 non-complaining normal sleepers. Measurements and Results: ROC and cross-tabs analyses were used to evaluate the sensitivity and specificity of PSG-derived total sleep time, latency to persistent sleep, wake after sleep onset, and sleep efficiency for discriminating adults with primary insomnia from normal sleepers. None of the individual criteria accurately discriminated PI from normal sleepers, and none of the criteria sets used in recent trials demonstrated acceptable sensitivity and specificity for identifying primary insomnia. Conclusions: The use of quantitative PSG-based selection criteria in insomnia research may exclude many who meet current diagnostic criteria for an insomnia disorder. Citation: Edinger JD; Ulmer CS; Means MK. Sensitivity and specificity of polysomnographic criteria for defining insomnia. J Clin Sleep Med 2013;9(5):481-491. PMID:23674940
Tiffin, Nicki; Meintjes, Ayton; Ramesar, Rajkumar; Bajic, Vladimir B.; Rayner, Brian
2010-01-01
Multiple factors underlie susceptibility to essential hypertension, including a significant genetic and ethnic component, and environmental effects. Blood pressure response of hypertensive individuals to salt is heterogeneous, but salt sensitivity appears more prevalent in people of indigenous African origin. The underlying genetics of salt-sensitive hypertension, however, are poorly understood. In this study, computational methods including text- and data-mining have been used to select and prioritize candidate aetiological genes for salt-sensitive hypertension. Additionally, we have compared allele frequencies and copy number variation for single nucleotide polymorphisms in candidate genes between indigenous Southern African and Caucasian populations, with the aim of identifying candidate genes with significant variability between the population groups: identifying genetic variability between population groups can exploit ethnic differences in disease prevalence to aid with prioritisation of good candidate genes. Our top-ranking candidate genes include parathyroid hormone precursor (PTH) and type-1angiotensin II receptor (AGTR1). We propose that the candidate genes identified in this study warrant further investigation as potential aetiological genes for salt-sensitive hypertension. PMID:20886000
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dai, Heng; Chen, Xingyuan; Ye, Ming
Sensitivity analysis is an important tool for quantifying uncertainty in the outputs of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study we developed a hierarchical sensitivity analysis method that (1) constructs an uncertainty hierarchy by analyzing the input uncertainty sources, and (2) accounts for the spatial correlation among parameters at each level ofmore » the hierarchy using geostatistical tools. The contribution of uncertainty source at each hierarchy level is measured by sensitivity indices calculated using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport in model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally as driven by the dynamic interaction between groundwater and river water at the site. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially-distributed parameters.« less
Gasse, Barbara; Prasad, Megana; Delgado, Sidney; Huckert, Mathilde; Kawczynski, Marzena; Garret-Bernardin, Annelyse; Lopez-Cazaux, Serena; Bailleul-Forestier, Isabelle; Manière, Marie-Cécile; Stoetzel, Corinne; Bloch-Zupan, Agnès; Sire, Jean-Yves
2017-01-01
Amelogenesis imperfecta (AI) designates a group of genetic diseases characterized by a large range of enamel disorders causing important social and health problems. These defects can result from mutations in enamel matrix proteins or protease encoding genes. A range of mutations in the enamel cleavage enzyme matrix metalloproteinase-20 gene (MMP20) produce enamel defects of varying severity. To address how various alterations produce a range of AI phenotypes, we performed a targeted analysis to find MMP20 mutations in French patients diagnosed with non-syndromic AI. Genomic DNA was isolated from saliva and MMP20 exons and exon-intron boundaries sequenced. We identified several homozygous or heterozygous mutations, putatively involved in the AI phenotypes. To validate missense mutations and predict sensitive positions in the MMP20 sequence, we evolutionarily compared 75 sequences extracted from the public databases using the Datamonkey webserver. These sequences were representative of mammalian lineages, covering more than 150 million years of evolution. This analysis allowed us to find 324 sensitive positions (out of the 483 MMP20 residues), pinpoint functionally important domains, and build an evolutionary chart of important conserved MMP20 regions. This is an efficient tool to identify new- and previously-identified mutations. We thus identified six functional MMP20 mutations in unrelated families, finding two novel mutated sites. The genotypes and phenotypes of these six mutations are described and compared. To date, 13 MMP20 mutations causing AI have been reported, making these genotypes and associated hypomature enamel phenotypes the most frequent in AI. PMID:28659819
Gasse, Barbara; Prasad, Megana; Delgado, Sidney; Huckert, Mathilde; Kawczynski, Marzena; Garret-Bernardin, Annelyse; Lopez-Cazaux, Serena; Bailleul-Forestier, Isabelle; Manière, Marie-Cécile; Stoetzel, Corinne; Bloch-Zupan, Agnès; Sire, Jean-Yves
2017-01-01
Amelogenesis imperfecta (AI) designates a group of genetic diseases characterized by a large range of enamel disorders causing important social and health problems. These defects can result from mutations in enamel matrix proteins or protease encoding genes. A range of mutations in the enamel cleavage enzyme matrix metalloproteinase-20 gene ( MMP20 ) produce enamel defects of varying severity. To address how various alterations produce a range of AI phenotypes, we performed a targeted analysis to find MMP20 mutations in French patients diagnosed with non-syndromic AI. Genomic DNA was isolated from saliva and MMP20 exons and exon-intron boundaries sequenced. We identified several homozygous or heterozygous mutations, putatively involved in the AI phenotypes. To validate missense mutations and predict sensitive positions in the MMP20 sequence, we evolutionarily compared 75 sequences extracted from the public databases using the Datamonkey webserver. These sequences were representative of mammalian lineages, covering more than 150 million years of evolution. This analysis allowed us to find 324 sensitive positions (out of the 483 MMP20 residues), pinpoint functionally important domains, and build an evolutionary chart of important conserved MMP20 regions. This is an efficient tool to identify new- and previously-identified mutations. We thus identified six functional MMP20 mutations in unrelated families, finding two novel mutated sites. The genotypes and phenotypes of these six mutations are described and compared. To date, 13 MMP20 mutations causing AI have been reported, making these genotypes and associated hypomature enamel phenotypes the most frequent in AI.
NASA Astrophysics Data System (ADS)
Haghnegahdar, Amin; Elshamy, Mohamed; Yassin, Fuad; Razavi, Saman; Wheater, Howard; Pietroniro, Al
2017-04-01
Complex physically-based environmental models are being increasingly used as the primary tool for watershed planning and management due to advances in computation power and data acquisition. Model sensitivity analysis plays a crucial role in understanding the behavior of these complex models and improving their performance. Due to the non-linearity and interactions within these complex models, Global sensitivity analysis (GSA) techniques should be adopted to provide a comprehensive understanding of model behavior and identify its dominant controls. In this study we adopt a multi-basin multi-criteria GSA approach to systematically assess the behavior of the Modélisation Environmentale-Surface et Hydrologie (MESH) across various hydroclimatic conditions in Canada including areas in the Great Lakes Basin, Mackenzie River Basin, and South Saskatchewan River Basin. MESH is a semi-distributed physically-based coupled land surface-hydrology modelling system developed by Environment and Climate Change Canada (ECCC) for various water resources management purposes in Canada. We use a novel method, called Variogram Analysis of Response Surfaces (VARS), to perform sensitivity analysis. VARS is a variogram-based GSA technique that can efficiently provide a spectrum of sensitivity information across a range of scales within the parameter space. We use multiple metrics to identify dominant controls of model response (e.g. streamflow) to model parameters under various conditions such as high flows, low flows, and flow volume. We also investigate the influence of initial conditions on model behavior as part of this study. Our preliminary results suggest that this type of GSA can significantly help with estimating model parameters, decreasing calibration computational burden, and reducing prediction uncertainty.
Kinase Pathway Dependence in Primary Human Leukemias Determined by Rapid Inhibitor Screening
Tyner, Jeffrey W.; Yang, Wayne F.; Bankhead, Armand; Fan, Guang; Fletcher, Luke B.; Bryant, Jade; Glover, Jason M.; Chang, Bill H.; Spurgeon, Stephen E.; Fleming, William H.; Kovacsovics, Tibor; Gotlib, Jason R.; Oh, Stephen T.; Deininger, Michael W.; Zwaan, C. Michel; Den Boer, Monique L.; van den Heuvel-Eibrink, Marry M.; O’Hare, Thomas; Druker, Brian J.; Loriaux, Marc M.
2012-01-01
Kinases are dysregulated in most cancer but the frequency of specific kinase mutations is low, indicating a complex etiology in kinase dysregulation. Here we report a strategy to rapidly identify functionally important kinase targets, irrespective of the etiology of kinase pathway dysregulation, ultimately enabling a correlation of patient genetic profiles to clinically effective kinase inhibitors. Our methodology assessed the sensitivity of primary leukemia patient samples to a panel of 66 small-molecule kinase inhibitors over 3 days. Screening of 151 leukemia patient samples revealed a wide diversity of drug sensitivities, with 70% of the clinical specimens exhibiting hypersensitivity to one or more drugs. From this data set, we developed an algorithm to predict kinase pathway dependence based on analysis of inhibitor sensitivity patterns. Applying this algorithm correctly identified pathway dependence in proof-of-principle specimens with known oncogenes, including a rare FLT3 mutation outside regions covered by standard molecular diagnostic tests. Interrogation of all 151 patient specimens with this algorithm identified a diversity of gene targets and signaling pathways that could aid prioritization of deep sequencing data sets, permitting a cumulative analysis to understand kinase pathway dependence within leukemia subsets. In a proof-of-principle case, we showed that in vitro drug sensitivity could predict both a clinical response and the development of drug resistance. Taken together, our results suggested that drug target scores derived from a comprehensive kinase inhibitor panel could predict pathway dependence in cancer cells while simultaneously identifying potential therapeutic options. PMID:23087056
D'Angelo, Heather; Fleischhacker, Sheila; Rose, Shyanika W; Ribisl, Kurt M
2014-07-01
Identifying tobacco retail outlets for U.S. FDA compliance checks or calculating tobacco outlet density is difficult in the 13 States without tobacco retail licensing or where licensing lists are unavailable for research. This study uses primary data collection to identify tobacco outlets in three counties in a non-licensing state and validate two commercial secondary data sources. We calculated sensitivity and positive predictive values (PPV) to examine the evidence of validity for two secondary data sources, and conducted a geospatial analysis to determine correct allocation to census tract. ReferenceUSA had almost perfect sensitivity (0.82) while Dun & Bradstreet (D&B) had substantial sensitivity (0.69) for identifying tobacco outlets; combined, sensitivity improved to 0.89. D&B identified fewer "false positives" with a PPV of 0.82 compared to 0.71 for ReferenceUSA. More than 90% of the outlets identified by ReferenceUSA were geocoded to the correct census tract. Combining two commercial data sources resulted in enumeration of nearly 90% of tobacco outlets in a three county area. Commercial databases appear to provide a reasonably accurate way to identify tobacco outlets for enforcement operations and density estimation. Copyright © 2014 Elsevier Ltd. All rights reserved.
Designing novel cellulase systems through agent-based modeling and global sensitivity analysis.
Apte, Advait A; Senger, Ryan S; Fong, Stephen S
2014-01-01
Experimental techniques allow engineering of biological systems to modify functionality; however, there still remains a need to develop tools to prioritize targets for modification. In this study, agent-based modeling (ABM) was used to build stochastic models of complexed and non-complexed cellulose hydrolysis, including enzymatic mechanisms for endoglucanase, exoglucanase, and β-glucosidase activity. Modeling results were consistent with experimental observations of higher efficiency in complexed systems than non-complexed systems and established relationships between specific cellulolytic mechanisms and overall efficiency. Global sensitivity analysis (GSA) of model results identified key parameters for improving overall cellulose hydrolysis efficiency including: (1) the cellulase half-life, (2) the exoglucanase activity, and (3) the cellulase composition. Overall, the following parameters were found to significantly influence cellulose consumption in a consolidated bioprocess (CBP): (1) the glucose uptake rate of the culture, (2) the bacterial cell concentration, and (3) the nature of the cellulase enzyme system (complexed or non-complexed). Broadly, these results demonstrate the utility of combining modeling and sensitivity analysis to identify key parameters and/or targets for experimental improvement.
Designing novel cellulase systems through agent-based modeling and global sensitivity analysis
Apte, Advait A; Senger, Ryan S; Fong, Stephen S
2014-01-01
Experimental techniques allow engineering of biological systems to modify functionality; however, there still remains a need to develop tools to prioritize targets for modification. In this study, agent-based modeling (ABM) was used to build stochastic models of complexed and non-complexed cellulose hydrolysis, including enzymatic mechanisms for endoglucanase, exoglucanase, and β-glucosidase activity. Modeling results were consistent with experimental observations of higher efficiency in complexed systems than non-complexed systems and established relationships between specific cellulolytic mechanisms and overall efficiency. Global sensitivity analysis (GSA) of model results identified key parameters for improving overall cellulose hydrolysis efficiency including: (1) the cellulase half-life, (2) the exoglucanase activity, and (3) the cellulase composition. Overall, the following parameters were found to significantly influence cellulose consumption in a consolidated bioprocess (CBP): (1) the glucose uptake rate of the culture, (2) the bacterial cell concentration, and (3) the nature of the cellulase enzyme system (complexed or non-complexed). Broadly, these results demonstrate the utility of combining modeling and sensitivity analysis to identify key parameters and/or targets for experimental improvement. PMID:24830736
NASA Astrophysics Data System (ADS)
Razavi, Saman; Gupta, Hoshin; Haghnegahdar, Amin
2016-04-01
Global sensitivity analysis (GSA) is a systems theoretic approach to characterizing the overall (average) sensitivity of one or more model responses across the factor space, by attributing the variability of those responses to different controlling (but uncertain) factors (e.g., model parameters, forcings, and boundary and initial conditions). GSA can be very helpful to improve the credibility and utility of Earth and Environmental System Models (EESMs), as these models are continually growing in complexity and dimensionality with continuous advances in understanding and computing power. However, conventional approaches to GSA suffer from (1) an ambiguous characterization of sensitivity, and (2) poor computational efficiency, particularly as the problem dimension grows. Here, we identify several important sensitivity-related characteristics of response surfaces that must be considered when investigating and interpreting the ''global sensitivity'' of a model response (e.g., a metric of model performance) to its parameters/factors. Accordingly, we present a new and general sensitivity and uncertainty analysis framework, Variogram Analysis of Response Surfaces (VARS), based on an analogy to 'variogram analysis', that characterizes a comprehensive spectrum of information on sensitivity. We prove, theoretically, that Morris (derivative-based) and Sobol (variance-based) methods and their extensions are special cases of VARS, and that their SA indices are contained within the VARS framework. We also present a practical strategy for the application of VARS to real-world problems, called STAR-VARS, including a new sampling strategy, called "star-based sampling". Our results across several case studies show the STAR-VARS approach to provide reliable and stable assessments of "global" sensitivity, while being at least 1-2 orders of magnitude more efficient than the benchmark Morris and Sobol approaches.
Hou, Wen-Hsuan; Kang, Chun-Mei; Ho, Mu-Hsing; Kuo, Jessie Ming-Chuan; Chen, Hsiao-Lien; Chang, Wen-Yin
2017-03-01
To evaluate the accuracy of the inpatient fall risk screening tool and to identify the most critical fall risk factors in inpatients. Variations exist in several screening tools applied in acute care hospitals for examining risk factors for falls and identifying high-risk inpatients. Secondary data analysis. A subset of inpatient data for the period from June 2011-June 2014 was extracted from the nursing information system and adverse event reporting system of an 818-bed teaching medical centre in Taipei. Data were analysed using descriptive statistics, receiver operating characteristic curve analysis and logistic regression analysis. During the study period, 205 fallers and 37,232 nonfallers were identified. The results revealed that the inpatient fall risk screening tool (cut-off point of ≥3) had a low sensitivity level (60%), satisfactory specificity (87%), a positive predictive value of 2·0% and a negative predictive value of 99%. The receiver operating characteristic curve analysis revealed an area under the curve of 0·805 (sensitivity, 71·8%; specificity, 78%). To increase the sensitivity values, the Youden index suggests at least 1·5 points to be the most suitable cut-off point for the inpatient fall risk screening tool. Multivariate logistic regression analysis revealed a considerably increased fall risk in patients with impaired balance and impaired elimination. The fall risk factor was also significantly associated with days of hospital stay and with admission to surgical wards. The findings can raise awareness about the two most critical risk factors for falls among future clinical nurses and other healthcare professionals and thus facilitate the development of fall prevention interventions. This study highlights the needs for redefining the cut-off points of the inpatient fall risk screening tool to effectively identify inpatients at a high risk of falls. Furthermore, inpatients with impaired balance and impaired elimination should be closely monitored by nurses to prevent falling during hospitalisations. © 2016 John Wiley & Sons Ltd.
Specialized Binary Analysis for Vetting Android APPS Using GUI Logic
2016-04-01
the use of high- level reasoning based on the GUI design logic of an app to enable a security analyst to diagnose and triage the potentially sensitive...execution paths of an app. Levels of Inconsistency We have identified three- levels of logical inconsistencies: Event- level inconsistency A sensitive...operation (e.g., taking a picture) is not trigged by user action on a GUI component. Layout- level inconsistency A sensitive operation is triggered by
Harnessing Connectivity in a Large-Scale Small-Molecule Sensitivity Dataset.
Seashore-Ludlow, Brinton; Rees, Matthew G; Cheah, Jaime H; Cokol, Murat; Price, Edmund V; Coletti, Matthew E; Jones, Victor; Bodycombe, Nicole E; Soule, Christian K; Gould, Joshua; Alexander, Benjamin; Li, Ava; Montgomery, Philip; Wawer, Mathias J; Kuru, Nurdan; Kotz, Joanne D; Hon, C Suk-Yee; Munoz, Benito; Liefeld, Ted; Dančík, Vlado; Bittker, Joshua A; Palmer, Michelle; Bradner, James E; Shamji, Alykhan F; Clemons, Paul A; Schreiber, Stuart L
2015-11-01
Identifying genetic alterations that prime a cancer cell to respond to a particular therapeutic agent can facilitate the development of precision cancer medicines. Cancer cell-line (CCL) profiling of small-molecule sensitivity has emerged as an unbiased method to assess the relationships between genetic or cellular features of CCLs and small-molecule response. Here, we developed annotated cluster multidimensional enrichment analysis to explore the associations between groups of small molecules and groups of CCLs in a new, quantitative sensitivity dataset. This analysis reveals insights into small-molecule mechanisms of action, and genomic features that associate with CCL response to small-molecule treatment. We are able to recapitulate known relationships between FDA-approved therapies and cancer dependencies and to uncover new relationships, including for KRAS-mutant cancers and neuroblastoma. To enable the cancer community to explore these data, and to generate novel hypotheses, we created an updated version of the Cancer Therapeutic Response Portal (CTRP v2). We present the largest CCL sensitivity dataset yet available, and an analysis method integrating information from multiple CCLs and multiple small molecules to identify CCL response predictors robustly. We updated the CTRP to enable the cancer research community to leverage these data and analyses. ©2015 American Association for Cancer Research.
Wang, W; Zhang, M; Chen, H D; Cai, X X; Xu, M L; Lei, K Y; Niu, J H; Deng, L; Liu, J; Ge, Z J; Yu, S X; Wang, B H
2016-10-06
In this study, a methylation-sensitive amplification polymorphism analysis system was used to analyze DNA methylation level in three cotton accessions. Two disease-sensitive near-isogenic lines, PD94042 and IL41, and one disease-resistant Gossypium mustelinum accession were exposed to Verticillium wilt, to investigate molecular disease resistance mechanisms in cotton. We observed multiple different DNA methylation types across the three accessions following Verticillium wilt exposure. These included hypomethylation, hypermethylation, and other patterns. In general, the global DNA methylation level was significantly increased in the disease-resistant accession G. mustelinum following disease exposure. In contrast, there was no significant difference in the disease-sensitive accession PD94042, and a significant decrease was observed in IL41. Our results suggest that disease-resistant cotton might employ a mechanism to increase methylation level in response to disease stress. The differing methylation patterns, together with the increase in global DNA methylation level, might play important roles in tolerance to Verticillium wilt in cotton. Through cloning and analysis of differently methylated DNA sequences, we were also able to identify several genes that may contribute to disease resistance in cotton. Our results revealed the effect of DNA methylation on cotton disease resistance, and also identified genes that played important roles, which may shed light on the future cotton disease-resistant molecular breeding.
2015-10-28
techniques such as regression analysis, correlation, and multicollinearity assessment to identify the change and error on the input to the model...between many of the independent or predictor variables, the issue of multicollinearity may arise [18]. VII. SUMMARY Accurate decisions concerning
Jiang, Sha-Yi; Yang, Jing-Wei; Shao, Jing-Bo; Liao, Xue-Lian; Lu, Zheng-Hua; Jiang, Hui
2016-05-01
In this meta-analysis, we evaluated the diagnostic role of Epstein-Barr virus deoxyribonucleic acid detection and quantitation in the serum of pediatric and young adult patients with infectious mononucleosis. The primary outcome of this meta-analysis was the sensitivity and specificity of Epstein-Barr virus (EBV) deoxyribonucleic acid (DNA) detection and quantitation using polymerase chain reaction (PCR). A systematic review and meta-analysis was performed by searching for articles that were published through September 24, 2014 in the following databases: Medline, Cochrane, EMBASE, and Google Scholar. The following keywords were used for the search: "Epstein-Barr virus," "infectious mononucleosis," "children/young adults/infant/pediatric," and "polymerase chain reaction or PCR." Three were included in this analysis. We found that for detection by PCR, the pooled sensitivity for detecting EBV DNA was 77% (95%CI, 66-86%) and the pooled specificity for was 98% (95%CI, 93-100%). Our findings indicate that this PCR-based assay has high specificity and good sensitivity for detecting of EBV DNA, indicating it may useful for identifying patients with infectious mononucleosis. This assay may also be helpful to identify young athletic patients or highly physically active pediatric patients who are at risk for a splenic rupture due to acute infectious mononucleosis. © 2015 Wiley Periodicals, Inc.
Scale/TSUNAMI Sensitivity Data for ICSBEP Evaluations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rearden, Bradley T; Reed, Davis Allan; Lefebvre, Robert A
2011-01-01
The Tools for Sensitivity and Uncertainty Analysis Methodology Implementation (TSUNAMI) software developed at Oak Ridge National Laboratory (ORNL) as part of the Scale code system provide unique methods for code validation, gap analysis, and experiment design. For TSUNAMI analysis, sensitivity data are generated for each application and each existing or proposed experiment used in the assessment. The validation of diverse sets of applications requires potentially thousands of data files to be maintained and organized by the user, and a growing number of these files are available through the International Handbook of Evaluated Criticality Safety Benchmark Experiments (IHECSBE) distributed through themore » International Criticality Safety Benchmark Evaluation Program (ICSBEP). To facilitate the use of the IHECSBE benchmarks in rigorous TSUNAMI validation and gap analysis techniques, ORNL generated SCALE/TSUNAMI sensitivity data files (SDFs) for several hundred benchmarks for distribution with the IHECSBE. For the 2010 edition of IHECSBE, the sensitivity data were generated using 238-group cross-section data based on ENDF/B-VII.0 for 494 benchmark experiments. Additionally, ORNL has developed a quality assurance procedure to guide the generation of Scale inputs and sensitivity data, as well as a graphical user interface to facilitate the use of sensitivity data in identifying experiments and applying them in validation studies.« less
Disclosure of sensitive behaviors across self-administered survey modes: a meta-analysis.
Gnambs, Timo; Kaspar, Kai
2015-12-01
In surveys, individuals tend to misreport behaviors that are in contrast to prevalent social norms or regulations. Several design features of the survey procedure have been suggested to counteract this problem; particularly, computerized surveys are supposed to elicit more truthful responding. This assumption was tested in a meta-analysis of survey experiments reporting 460 effect sizes (total N =125,672). Self-reported prevalence rates of several sensitive behaviors for which motivated misreporting has been frequently observed were compared across self-administered paper-and-pencil versus computerized surveys. The results revealed that computerized surveys led to significantly more reporting of socially undesirable behaviors than comparable surveys administered on paper. This effect was strongest for highly sensitive behaviors and surveys administered individually to respondents. Moderator analyses did not identify interviewer effects or benefits of audio-enhanced computer surveys. The meta-analysis highlighted the advantages of computerized survey modes for the assessment of sensitive topics.
Validation of ICD-9 Codes for Stable Miscarriage in the Emergency Department.
Quinley, Kelly E; Falck, Ailsa; Kallan, Michael J; Datner, Elizabeth M; Carr, Brendan G; Schreiber, Courtney A
2015-07-01
International Classification of Disease, Ninth Revision (ICD-9) diagnosis codes have not been validated for identifying cases of missed abortion where a pregnancy is no longer viable but the cervical os remains closed. Our goal was to assess whether ICD-9 code "632" for missed abortion has high sensitivity and positive predictive value (PPV) in identifying patients in the emergency department (ED) with cases of stable early pregnancy failure (EPF). We studied females ages 13-50 years presenting to the ED of an urban academic medical center. We approached our analysis from two perspectives, evaluating both the sensitivity and PPV of ICD-9 code "632" in identifying patients with stable EPF. All patients with chief complaints "pregnant and bleeding" or "pregnant and cramping" over a 12-month period were identified. We randomly reviewed two months of patient visits and calculated the sensitivity of ICD-9 code "632" for true cases of stable miscarriage. To establish the PPV of ICD-9 code "632" for capturing missed abortions, we identified patients whose visits from the same time period were assigned ICD-9 code "632," and identified those with actual cases of stable EPF. We reviewed 310 patient records (17.6% of 1,762 sampled). Thirteen of 31 patient records assigned ICD-9 code for missed abortion correctly identified cases of stable EPF (sensitivity=41.9%), and 140 of the 142 patients without EPF were not assigned the ICD-9 code "632"(specificity=98.6%). Of the 52 eligible patients identified by ICD-9 code "632," 39 cases met the criteria for stable EPF (PPV=75.0%). ICD-9 code "632" has low sensitivity for identifying stable EPF, but its high specificity and moderately high PPV are valuable for studying cases of stable EPF in epidemiologic studies using administrative data.
NASA Astrophysics Data System (ADS)
da Silva, Ricardo Siqueira; Kumar, Lalit; Shabani, Farzin; Picanço, Marcelo Coutinho
2018-04-01
A sensitivity analysis can categorize levels of parameter influence on a model's output. Identifying parameters having the most influence facilitates establishing the best values for parameters of models, providing useful implications in species modelling of crops and associated insect pests. The aim of this study was to quantify the response of species models through a CLIMEX sensitivity analysis. Using open-field Solanum lycopersicum and Neoleucinodes elegantalis distribution records, and 17 fitting parameters, including growth and stress parameters, comparisons were made in model performance by altering one parameter value at a time, in comparison to the best-fit parameter values. Parameters that were found to have a greater effect on the model results are termed "sensitive". Through the use of two species, we show that even when the Ecoclimatic Index has a major change through upward or downward parameter value alterations, the effect on the species is dependent on the selection of suitability categories and regions of modelling. Two parameters were shown to have the greatest sensitivity, dependent on the suitability categories of each species in the study. Results enhance user understanding of which climatic factors had a greater impact on both species distributions in our model, in terms of suitability categories and areas, when parameter values were perturbed by higher or lower values, compared to the best-fit parameter values. Thus, the sensitivity analyses have the potential to provide additional information for end users, in terms of improving management, by identifying the climatic variables that are most sensitive.
Analytic uncertainty and sensitivity analysis of models with input correlations
NASA Astrophysics Data System (ADS)
Zhu, Yueying; Wang, Qiuping A.; Li, Wei; Cai, Xu
2018-03-01
Probabilistic uncertainty analysis is a common means of evaluating mathematical models. In mathematical modeling, the uncertainty in input variables is specified through distribution laws. Its contribution to the uncertainty in model response is usually analyzed by assuming that input variables are independent of each other. However, correlated parameters are often happened in practical applications. In the present paper, an analytic method is built for the uncertainty and sensitivity analysis of models in the presence of input correlations. With the method, it is straightforward to identify the importance of the independence and correlations of input variables in determining the model response. This allows one to decide whether or not the input correlations should be considered in practice. Numerical examples suggest the effectiveness and validation of our analytic method in the analysis of general models. A practical application of the method is also proposed to the uncertainty and sensitivity analysis of a deterministic HIV model.
Sensitivity analysis of a ground-water-flow model
Torak, Lynn J.; ,
1991-01-01
A sensitivity analysis was performed on 18 hydrological factors affecting steady-state groundwater flow in the Upper Floridan aquifer near Albany, southwestern Georgia. Computations were based on a calibrated, two-dimensional, finite-element digital model of the stream-aquifer system and the corresponding data inputs. Flow-system sensitivity was analyzed by computing water-level residuals obtained from simulations involving individual changes to each hydrological factor. Hydrological factors to which computed water levels were most sensitive were those that produced the largest change in the sum-of-squares of residuals for the smallest change in factor value. Plots of the sum-of-squares of residuals against multiplier or additive values that effect change in the hydrological factors are used to evaluate the influence of each factor on the simulated flow system. The shapes of these 'sensitivity curves' indicate the importance of each hydrological factor to the flow system. Because the sensitivity analysis can be performed during the preliminary phase of a water-resource investigation, it can be used to identify the types of hydrological data required to accurately characterize the flow system prior to collecting additional data or making management decisions.
Bell, L T O; Gandhi, S
2018-06-01
To directly compare the accuracy and speed of analysis of two commercially available computer-assisted detection (CAD) programs in detecting colorectal polyps. In this retrospective single-centre study, patients who had colorectal polyps identified on computed tomography colonography (CTC) and subsequent lower gastrointestinal endoscopy, were analysed using two commercially available CAD programs (CAD1 and CAD2). Results were compared against endoscopy to ascertain sensitivity and positive predictive value (PPV) for colorectal polyps. Time taken for CAD analysis was also calculated. CAD1 demonstrated a sensitivity of 89.8%, PPV of 17.6% and mean analysis time of 125.8 seconds. CAD2 demonstrated a sensitivity of 75.5%, PPV of 44.0% and mean analysis time of 84.6 seconds. The sensitivity and PPV for colorectal polyps and CAD analysis times can vary widely between current commercially available CAD programs. There is still room for improvement. Generally, there is a trade-off between sensitivity and PPV, and so further developments should aim to optimise both. Information on these factors should be made routinely available, so that an informed choice on their use can be made. This information could also potentially influence the radiologist's use of CAD results. Copyright © 2018 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
Brekelmans, Marjolein P; Fens, Niki; Brinkman, Paul; Bos, Lieuwe D; Sterk, Peter J; Tak, Paul P; Gerlag, Daniëlle M
2016-01-01
To investigate whether exhaled breath analysis using an electronic nose can identify differences between inflammatory joint diseases and healthy controls. In a cross-sectional study, the exhaled breath of 21 rheumatoid arthritis (RA) and 18 psoriatic arthritis (PsA) patients with active disease was compared to 21 healthy controls using an electronic nose (Cyranose 320; Smiths Detection, Pasadena, CA, USA). Breathprints were analyzed with principal component analysis, discriminant analysis, and area under curve (AUC) of receiver operating characteristics (ROC) curves. Volatile organic compounds (VOCs) were identified by gas chromatography and mass spectrometry (GC-MS), and relationships between breathprints and markers of disease activity were explored. Breathprints of RA patients could be distinguished from controls with an accuracy of 71% (AUC 0.75, 95% CI 0.60-0.90, sensitivity 76%, specificity 67%). Breathprints from PsA patients were separated from controls with 69% accuracy (AUC 0.77, 95% CI 0.61-0.92, sensitivity 72%, specificity 71%). Distinction between exhaled breath of RA and PsA patients exhibited an accuracy of 69% (AUC 0.72, 95% CI 0.55-0.89, sensitivity 71%, specificity 72%). There was a positive correlation in RA patients of exhaled breathprints with disease activity score (DAS28) and number of painful joints. GC-MS identified seven key VOCs that significantly differed between the groups. Exhaled breath analysis by an electronic nose may play a role in differential diagnosis of inflammatory joint diseases. Data from this study warrant external validation.
Verhaegh, Pauline; Bavalia, Roisin; Winkens, Bjorn; Masclee, Ad; Jonkers, Daisy; Koek, Ger
2018-06-01
Nonalcoholic fatty liver disease is a rapidly increasing health problem. Liver biopsy analysis is the most sensitive test to differentiate between nonalcoholic steatohepatitis (NASH) and simple steatosis (SS), but noninvasive methods are needed. We performed a systematic review and meta-analysis of noninvasive tests for differentiating NASH from SS, focusing on blood markers. We performed a systematic search of the PubMed, Medline and Embase (1990-2016) databases using defined keywords, limited to full-text papers in English and human adults, and identified 2608 articles. Two independent reviewers screened the articles and identified 122 eligible articles that used liver biopsy as reference standard. If at least 2 studies were available, pooled sensitivity (sens p ) and specificity (spec p ) values were determined using the Meta-Analysis Package for R (metafor). In the 122 studies analyzed, 219 different blood markers (107 single markers and 112 scoring systems) were identified to differentiate NASH from simple steatosis, and 22 other diagnostic tests were studied. Markers identified related to several pathophysiological mechanisms. The markers analyzed in the largest proportions of studies were alanine aminotransferase (sens p , 63.5% and spec p , 74.4%) within routine biochemical tests, adiponectin (sensp, 72.0% and spec p , 75.7%) within inflammatory markers, CK18-M30 (sens p , 68.4% and spec p , 74.2%) within markers of cell death or proliferation and homeostatic model assessment of insulin resistance (sens p , 69.0% and spec p , 72.7%) within the metabolic markers. Two scoring systems could also be pooled: the NASH test (differentiated NASH from borderline NASH plus simple steatosis with 22.9% sens p and 95.3% spec p ) and the GlycoNASH test (67.1% sens p and 63.8% spec p ). In the meta-analysis, we found no test to differentiate NASH from SS with a high level of pooled sensitivity and specificity (≥80%). However, some blood markers, when included in scoring systems in single studies, identified patients with NASH with ≥80% sensitivity and specificity. Replication studies and more standardized study designs are urgently needed. At present, no marker or scoring system can be recommended for use in clinical practice to differentiate NASH from simple steatosis. Copyright © 2018 AGA Institute. Published by Elsevier Inc. All rights reserved.
Vitrectomy for the diagnosis and management of uveitis of unknown cause.
Margolis, Ron; Brasil, Oswaldo F M; Lowder, Careen Y; Singh, Rishi P; Kaiser, Peter K; Smith, Scott D; Perez, Victor L; Sonnie, Christine; Sears, Jonathan E
2007-10-01
To determine the diagnostic yield of tests commonly used for vitreous fluid analysis in eyes with suspected intraocular infection or malignancy. Noncomparative interventional case series. Forty-four consecutive patients (45 eyes) treated from 1998 through 2006 with posterior segment inflammation who underwent pars plana vitrectomy for diagnostic purposes. Vitreous specimens obtained via pars plana vitrectomy were analyzed by microbiologic culture, cytologic analysis, and flow cytometry. Diagnostic yield and sensitivity of each test performed on vitreous specimens and visual outcomes of eyes that underwent diagnostic vitrectomy (DVx). Preoperative diagnoses were infection in 15 eyes and malignancy in 30 eyes. Overall, vitreous analysis identified a specific cause in 9 (20%) of 45 eyes. The overall sensitivity of DVx was 63.6%. The sensitivities of individual tests were: culture, 50%; cytologic analysis, 66.7%; and flow cytometry, 83.3%. The yields of diagnostic tests were: culture, 5.7%; cytologic analysis, 14.3%; and flow cytometry, 20.6%. Final diagnoses were infection in 6 eyes, malignancy in 9 eyes, and idiopathic in 30 eyes. Mean visual acuity improved significantly in the first 6 months after DVx. Visual acuity improved in 60% of eyes, with 37.8% of eyes improving by 3 lines or more. Analysis of vitreous fluid by widely available tests is useful in identifying intraocular infection or malignancy. Most patients experienced a substantial improvement in vision.
A subset of walnut allergic adults is sensitized to walnut 11S globulin Jug r 4.
Blankestijn, Mark A; den Hartog Jager, Constance F; Blom, W Marty; Otten, Henny G; de Jong, G Aard H; Gaspari, Marco; Houben, Geert F; Knulst, André C; Verhoeckx, Kitty C M
2018-06-15
The role of sensitization to commercially available allergens of English walnut (Juglans regia) Jug r 1, 2 and 3 in walnut allergy has been previously investigated in walnut allergic adults and was unable to explain allcases of walnut allergy. Identify recognized walnut allergens, other than the ones previously investigated (Jug r 1-3), in walnut allergic adults and determine the sensitization frequency and diagnostic value. Three different in-house walnut extracts were prepared and analysed on SDS-PAGE blots to identify allergenic walnut proteins. Immunoblots and immunoprecipitation, followed by LC-MS analysis, were performed to screen for, and confirm, IgE binding to walnut allergens in selected walnut allergic adults. In a cohort of 55 walnut challenged adults, including 33 allergic and 22 tolerant, sensitization to native and recombinant walnut allergen Jug r 4 was assessed using immunoblotting and immuno-line blot (EUROLINE), respectively. Screening of sera of eight walnut allergic adults identified Jug r 4 as an allergen in our population. In the total cohort of 55 subjects, five were positive for Jug r 4 on immunoblot and 10 on EUROLINE. All but one EUROLINE positive subject had a positive food challenge (sensitivity 27%, specificity 95%, PPV 90%, NPV 47%). All five subjects positive on immunoblot were also positive on EUROLINE. LC-MS analysis showed a lack of Jug r 4 in the ImmunoCAP extract. Co-sensitization to other 11S albumins (e.g. hazelnut Cor a 9) was common in Jug r 4 sensitized subjects, potentially due to cross-reactivity. Walnut 11S globulin Jug r 4 is a relevant minor allergen, recognized by 27% of walnut allergic adults. It has a high positive predictive value of 90% for walnut allergy. Specific IgE against Jug r 4 occurred mostly with concomitant sensitization to other walnut components, mainly Jug r 1. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
Fragment-based prediction of skin sensitization using recursive partitioning
NASA Astrophysics Data System (ADS)
Lu, Jing; Zheng, Mingyue; Wang, Yong; Shen, Qiancheng; Luo, Xiaomin; Jiang, Hualiang; Chen, Kaixian
2011-09-01
Skin sensitization is an important toxic endpoint in the risk assessment of chemicals. In this paper, structure-activity relationships analysis was performed on the skin sensitization potential of 357 compounds with local lymph node assay data. Structural fragments were extracted by GASTON (GrAph/Sequence/Tree extractiON) from the training set. Eight fragments with accuracy significantly higher than 0.73 ( p < 0.1) were retained to make up an indicator descriptor fragment. The fragment descriptor and eight other physicochemical descriptors closely related to the endpoint were calculated to construct the recursive partitioning tree (RP tree) for classification. The balanced accuracy of the training set, test set I, and test set II in the leave-one-out model were 0.846, 0.800, and 0.809, respectively. The results highlight that fragment-based RP tree is a preferable method for identifying skin sensitizers. Moreover, the selected fragments provide useful structural information for exploring sensitization mechanisms, and RP tree creates a graphic tree to identify the most important properties associated with skin sensitization. They can provide some guidance for designing of drugs with lower sensitization level.
Wright, Robin; Parrish, Mark L; Cadera, Emily; Larson, Lynnelle; Matson, Clinton K; Garrett-Engele, Philip; Armour, Chris; Lum, Pek Yee; Shoemaker, Daniel D
2003-07-30
Increased levels of HMG-CoA reductase induce cell type- and isozyme-specific proliferation of the endoplasmic reticulum. In yeast, the ER proliferations induced by Hmg1p consist of nuclear-associated stacks of smooth ER membranes known as karmellae. To identify genes required for karmellae assembly, we compared the composition of populations of homozygous diploid S. cerevisiae deletion mutants following 20 generations of growth with and without karmellae. Using an initial population of 1,557 deletion mutants, 120 potential mutants were identified as a result of three independent experiments. Each experiment produced a largely non-overlapping set of potential mutants, suggesting that differences in specific growth conditions could be used to maximize the comprehensiveness of similar parallel analysis screens. Only two genes, UBC7 and YAL011W, were identified in all three experiments. Subsequent analysis of individual mutant strains confirmed that each experiment was identifying valid mutations, based on the mutant's sensitivity to elevated HMG-CoA reductase and inability to assemble normal karmellae. The largest class of HMG-CoA reductase-sensitive mutations was a subset of genes that are involved in chromatin structure and transcriptional regulation, suggesting that karmellae assembly requires changes in transcription or that the presence of karmellae may interfere with normal transcriptional regulation. Copyright 2003 John Wiley & Sons, Ltd.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dai, Heng; Ye, Ming; Walker, Anthony P.
Hydrological models are always composed of multiple components that represent processes key to intended model applications. When a process can be simulated by multiple conceptual-mathematical models (process models), model uncertainty in representing the process arises. While global sensitivity analysis methods have been widely used for identifying important processes in hydrologic modeling, the existing methods consider only parametric uncertainty but ignore the model uncertainty for process representation. To address this problem, this study develops a new method to probe multimodel process sensitivity by integrating the model averaging methods into the framework of variance-based global sensitivity analysis, given that the model averagingmore » methods quantify both parametric and model uncertainty. A new process sensitivity index is derived as a metric of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and model parameters. For demonstration, the new index is used to evaluate the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that converting precipitation to recharge, and the geology process is also simulated by two models of different parameterizations of hydraulic conductivity; each process model has its own random parameters. The new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less
Edwards, D. L.; Saleh, A. A.; Greenspan, S. L.
2015-01-01
Summary We performed a systematic review and meta-analysis of the performance of clinical risk assessment instruments for screening for DXA-determined osteoporosis or low bone density. Commonly evaluated risk instruments showed high sensitivity approaching or exceeding 90 % at particular thresholds within various populations but low specificity at thresholds required for high sensitivity. Simpler instruments, such as OST, generally performed as well as or better than more complex instruments. Introduction The purpose of the study is to systematically review the performance of clinical risk assessment instruments for screening for dual-energy X-ray absorptiometry (DXA)-determined osteoporosis or low bone density. Methods Systematic review and meta-analysis were performed. Multiple literature sources were searched, and data extracted and analyzed from included references. Results One hundred eight references met inclusion criteria. Studies assessed many instruments in 34 countries, most commonly the Osteoporosis Self-Assessment Tool (OST), the Simple Calculated Osteoporosis Risk Estimation (SCORE) instrument, the Osteoporosis Self-Assessment Tool for Asians (OSTA), the Osteoporosis Risk Assessment Instrument (ORAI), and body weight criteria. Meta-analyses of studies evaluating OST using a cutoff threshold of <1 to identify US postmenopausal women with osteoporosis at the femoral neck provided summary sensitivity and specificity estimates of 89 % (95%CI 82–96 %) and 41 % (95%CI 23–59 %), respectively. Meta-analyses of studies evaluating OST using a cutoff threshold of 3 to identify US men with osteoporosis at the femoral neck, total hip, or lumbar spine provided summary sensitivity and specificity estimates of 88 % (95%CI 79–97 %) and 55 % (95%CI 42–68 %), respectively. Frequently evaluated instruments each had thresholds and populations for which sensitivity for osteoporosis or low bone mass detection approached or exceeded 90 % but always with a trade-off of relatively low specificity. Conclusions Commonly evaluated clinical risk assessment instruments each showed high sensitivity approaching or exceeding 90 % for identifying individuals with DXA-determined osteoporosis or low BMD at certain thresholds in different populations but low specificity at thresholds required for high sensitivity. Simpler instruments, such as OST, generally performed as well as or better than more complex instruments. PMID:25644147
2014-01-01
Background The Timed Up and Go test (TUG) is a commonly used screening tool to assist clinicians to identify patients at risk of falling. The purpose of this systematic review and meta-analysis is to determine the overall predictive value of the TUG in community-dwelling older adults. Methods A literature search was performed to identify all studies that validated the TUG test. The methodological quality of the selected studies was assessed using the QUADAS-2 tool, a validated tool for the quality assessment of diagnostic accuracy studies. A TUG score of ≥13.5 seconds was used to identify individuals at higher risk of falling. All included studies were combined using a bivariate random effects model to generate pooled estimates of sensitivity and specificity at ≥13.5 seconds. Heterogeneity was assessed using the variance of logit transformed sensitivity and specificity. Results Twenty-five studies were included in the systematic review and 10 studies were included in meta-analysis. The TUG test was found to be more useful at ruling in rather than ruling out falls in individuals classified as high risk (>13.5 sec), with a higher pooled specificity (0.74, 95% CI 0.52-0.88) than sensitivity (0.31, 95% CI 0.13-0.57). Logistic regression analysis indicated that the TUG score is not a significant predictor of falls (OR = 1.01, 95% CI 1.00-1.02, p = 0.05). Conclusion The Timed Up and Go test has limited ability to predict falls in community dwelling elderly and should not be used in isolation to identify individuals at high risk of falls in this setting. PMID:24484314
NASA Astrophysics Data System (ADS)
Sarris, Theo S.; Close, Murray; Abraham, Phillip
2018-03-01
A test using Rhodamine WT and heat as tracers, conducted over a 78 day period in a strongly heterogeneous alluvial aquifer, was used to evaluate the utility of the combined observation dataset for aquifer characterization. A highly parameterized model was inverted, with concentration and temperature time-series as calibration targets. Groundwater heads recorded during the experiment were boundary dependent and were ignored during the inversion process. The inverted model produced a high resolution depiction of the hydraulic conductivity and porosity fields. Statistical properties of these fields are in very good agreement with estimates from previous studies at the site. Spatially distributed sensitivity analysis suggests that both solute and heat transport were most sensitive to the hydraulic conductivity and porosity fields and less sensitive to dispersivity and thermal distribution factor, with sensitivity to porosity greatly reducing outside the monitored area. The issues of model over-parameterization and non-uniqueness are addressed through identifiability analysis. Longitudinal dispersivity and thermal distribution factor are highly identifiable, however spatially distributed parameters are only identifiable near the injection point. Temperature related density effects became observable for both heat and solute, as the temperature anomaly increased above 12 degrees centigrade, and affected down gradient propagation. Finally we demonstrate that high frequency and spatially dense temperature data cannot inform a dual porosity model in the absence of frequent solute concentration measurements.
Faghri, Jamshid; Zandi, Alireza; Peiman, Alireza; Fazeli, Hossein; Esfahani, Bahram Nasr; Safaei, Hajieh Ghasemian; Hosseini, Nafiseh Sadat; Mobasherizadeh, Sina; Sedighi, Mansour; Burbur, Samaneh; Oryan, Golfam
2016-03-01
To study on antibiotic susceptibility and identify coagulase-negative Staphylococcus (CoNS) species based on tuf gene sequencing from keratitis followed by using soft contact lenses in Isfahan, Iran, 2013. This study examined 77 keratitis cases. The samples were cultured and the isolation of CoNS was done by phenotypic tests, and in vitro sensitivity testing was done by Kirby-Bauer disk diffusion susceptibility method. Thirty-eight of isolates were conveniently identified as CoNS. In this study, 27 (71.1%), 21 (55.3%), and 16 (42.1%) were resistant to penicillin, erythromycin, and tetracycline, respectively. One hundred percent of isolates were sensitive to gentamicin, and 36 (94.7%) and 33 (86.8%) of isolates were sensitive to chloramphenicol and ciprofloxacin, respectively. Also, resistances to cefoxitin were 7 (18.4%). Analysis of tuf gene proved to be discriminative and sensitive in which all the isolates were identified with 99.0% similarity to reference strains, and Staphylococcus epidermidis had the highest prevalence among other species. Results of this study showed that CoNS are the most common agents causing contact lens-associated microbial keratitis, and the tuf gene sequencing analysis is a reliable method for distinguishing CoNS species. Also gentamycin, chloramphenicol, and ciprofloxacin are more effective than the other antibacterial agents against these types of bacteria.
Who is More Affected by Ozone Pollution? A Systematic Review and Meta-Analysis
Bell, Michelle L.; Zanobetti, Antonella; Dominici, Francesca
2014-01-01
Ozone is associated with adverse health; however, less is known about vulnerable/sensitive populations, which we refer to as sensitive populations. We systematically reviewed epidemiologic evidence (1988–2013) regarding sensitivity to mortality or hospital admission from short-term ozone exposure. We performed meta-analysis for overall associations by age and sex; assessed publication bias; and qualitatively assessed sensitivity to socioeconomic indicators, race/ethnicity, and air conditioning. The search identified 2,091 unique papers, with 167 meeting inclusion criteria (73 on mortality and 96 on hospitalizations and emergency department visits, including 2 examining both mortality and hospitalizations). The strongest evidence for ozone sensitivity was for age. Per 10-parts per billion increase in daily 8-hour ozone concentration, mortality risk for younger persons, at 0.60% (95% confidence interval (CI): 0.40, 0.80), was statistically lower than that for older persons, at 1.27% (95% CI: 0.76, 1.78). Findings adjusted for publication bias were similar. Limited/suggestive evidence was found for higher associations among women; mortality risks were 0.39% (95% CI: −0.22, 1.00) higher than those for men. We identified strong evidence for higher associations with unemployment or lower occupational status and weak evidence of sensitivity for racial/ethnic minorities and persons with low education, in poverty, or without central air conditioning. Findings show that some populations, especially the elderly, are particularly sensitive to short-term ozone exposure. PMID:24872350
Spatial Analysis for Monitoring Forest Health
Francis A. Roesch
1994-01-01
A plan for the spatial analysis for the sample design for the detection monitoring phase in the joint USDA Forest Service/EPA Forest Health Monitoring Program (FHM) in the United States is discussed. The spatial analysis procedure is intended to more quickly identify changes in forest health by providing increased sensitivity to localized changes. The procedure is...
Seizure semiology identifies patients with bilateral temporal lobe epilepsy.
Loesch, Anna Mira; Feddersen, Berend; Tezer, F Irsel; Hartl, Elisabeth; Rémi, Jan; Vollmar, Christian; Noachtar, Soheyl
2015-01-01
Laterality in temporal lobe epilepsy is usually defined by EEG and imaging results. We investigated whether the analysis of seizure semiology including lateralizing seizure phenomena identifies bilateral independent temporal lobe seizure onset. We investigated the seizure semiology in 17 patients in whom invasive EEG-video-monitoring documented bilateral temporal seizure onset. The results were compared to 20 left and 20 right consecutive temporal lobe epilepsy (TLE) patients who were seizure free after anterior temporal lobe resection. The seizure semiology was analyzed using the semiological seizure classification with particular emphasis on the sequence of seizure phenomena over time and lateralizing seizure phenomena. Statistical analysis included chi-square test or Fisher's exact test. Bitemporal lobe epilepsy patients had more frequently different seizure semiology (100% vs. 40%; p<0.001) and significantly more often lateralizing seizure phenomena pointing to bilateral seizure onset compared to patients with unilateral TLE (67% vs. 11%; p<0.001). The sensitivity of identical vs. different seizure semiology for the identification of bilateral TLE was high (100%) with a specificity of 60%. Lateralizing seizure phenomena had a low sensitivity (59%) but a high specificity (89%). The combination of lateralizing seizure phenomena and different seizure semiology showed a high specificity (94%) but a low sensitivity (59%). The analysis of seizure semiology including lateralizing seizure phenomena adds important clinical information to identify patients with bilateral TLE. Copyright © 2014 Elsevier B.V. All rights reserved.
Mendes, Paula; Nunes, Luis Miguel; Teixeira, Margarida Ribau
2014-09-01
This article demonstrates how decision-makers can be guided in the process of defining performance target values in the balanced scorecard system. We apply a method based on sensitivity analysis with Monte Carlo simulation to the municipal solid waste management system in Loulé Municipality (Portugal). The method includes two steps: sensitivity analysis of performance indicators to identify those performance indicators with the highest impact on the balanced scorecard model outcomes; and sensitivity analysis of the target values for the previously identified performance indicators. Sensitivity analysis shows that four strategic objectives (IPP1: Comply with the national waste strategy; IPP4: Reduce nonrenewable resources and greenhouse gases; IPP5: Optimize the life-cycle of waste; and FP1: Meet and optimize the budget) alone contribute 99.7% of the variability in overall balanced scorecard value. Thus, these strategic objectives had a much stronger impact on the estimated balanced scorecard outcome than did others, with the IPP1 and the IPP4 accounting for over 55% and 22% of the variance in overall balanced scorecard value, respectively. The remaining performance indicators contribute only marginally. In addition, a change in the value of a single indicator's target value made the overall balanced scorecard value change by as much as 18%. This may lead to involuntarily biased decisions by organizations regarding performance target-setting, if not prevented with the help of methods such as that proposed and applied in this study. © The Author(s) 2014.
NASA Astrophysics Data System (ADS)
Demaria, Eleonora M.; Nijssen, Bart; Wagener, Thorsten
2007-06-01
Current land surface models use increasingly complex descriptions of the processes that they represent. Increase in complexity is accompanied by an increase in the number of model parameters, many of which cannot be measured directly at large spatial scales. A Monte Carlo framework was used to evaluate the sensitivity and identifiability of ten parameters controlling surface and subsurface runoff generation in the Variable Infiltration Capacity model (VIC). Using the Monte Carlo Analysis Toolbox (MCAT), parameter sensitivities were studied for four U.S. watersheds along a hydroclimatic gradient, based on a 20-year data set developed for the Model Parameter Estimation Experiment (MOPEX). Results showed that simulated streamflows are sensitive to three parameters when evaluated with different objective functions. Sensitivity of the infiltration parameter (b) and the drainage parameter (exp) were strongly related to the hydroclimatic gradient. The placement of vegetation roots played an important role in the sensitivity of model simulations to the thickness of the second soil layer (thick2). Overparameterization was found in the base flow formulation indicating that a simplified version could be implemented. Parameter sensitivity was more strongly dictated by climatic gradients than by changes in soil properties. Results showed how a complex model can be reduced to a more parsimonious form, leading to a more identifiable model with an increased chance of successful regionalization to ungauged basins. Although parameter sensitivities are strictly valid for VIC, this model is representative of a wider class of macroscale hydrological models. Consequently, the results and methodology will have applicability to other hydrological models.
Patlewicz, Grace; Casati, Silvia; Basketter, David A; Asturiol, David; Roberts, David W; Lepoittevin, Jean-Pierre; Worth, Andrew P; Aschberger, Karin
2016-12-01
Predictive testing to characterize substances for their skin sensitization potential has historically been based on animal tests such as the Local Lymph Node Assay (LLNA). In recent years, regulations in the cosmetics and chemicals sectors have provided strong impetus to develop non-animal alternatives. Three test methods have undergone OECD validation: the direct peptide reactivity assay (DPRA), the KeratinoSens™ and the human Cell Line Activation Test (h-CLAT). Whilst these methods perform relatively well in predicting LLNA results, a concern raised is their ability to predict chemicals that need activation to be sensitizing (pre- or pro-haptens). This current study reviewed an EURL ECVAM dataset of 127 substances for which information was available in the LLNA and three non-animal test methods. Twenty eight of the sensitizers needed to be activated, with the majority being pre-haptens. These were correctly identified by 1 or more of the test methods. Six substances were categorized exclusively as pro-haptens, but were correctly identified by at least one of the cell-based assays. The analysis here showed that skin metabolism was not likely to be a major consideration for assessing sensitization potential and that sensitizers requiring activation could be identified correctly using one or more of the current non-animal methods. Published by Elsevier Inc.
Li, Liang; Wang, Yiying; Xu, Jiting; Flora, Joseph R V; Hoque, Shamia; Berge, Nicole D
2018-08-01
Hydrothermal carbonization (HTC) is a wet, low temperature thermal conversion process that continues to gain attention for the generation of hydrochar. The importance of specific process conditions and feedstock properties on hydrochar characteristics is not well understood. To evaluate this, linear and non-linear models were developed to describe hydrochar characteristics based on data collected from HTC-related literature. A Sobol analysis was subsequently conducted to identify parameters that most influence hydrochar characteristics. Results from this analysis indicate that for each investigated hydrochar property, the model fit and predictive capability associated with the random forest models is superior to both the linear and regression tree models. Based on results from the Sobol analysis, the feedstock properties and process conditions most influential on hydrochar yield, carbon content, and energy content were identified. In addition, a variational process parameter sensitivity analysis was conducted to determine how feedstock property importance changes with process conditions. Copyright © 2018 Elsevier Ltd. All rights reserved.
Measuring Road Network Vulnerability with Sensitivity Analysis
Jun-qiang, Leng; Long-hai, Yang; Liu, Wei-yi; Zhao, Lin
2017-01-01
This paper focuses on the development of a method for road network vulnerability analysis, from the perspective of capacity degradation, which seeks to identify the critical infrastructures in the road network and the operational performance of the whole traffic system. This research involves defining the traffic utility index and modeling vulnerability of road segment, route, OD (Origin Destination) pair and road network. Meanwhile, sensitivity analysis method is utilized to calculate the change of traffic utility index due to capacity degradation. This method, compared to traditional traffic assignment, can improve calculation efficiency and make the application of vulnerability analysis to large actual road network possible. Finally, all the above models and calculation method is applied to actual road network evaluation to verify its efficiency and utility. This approach can be used as a decision-supporting tool for evaluating the performance of road network and identifying critical infrastructures in transportation planning and management, especially in the resource allocation for mitigation and recovery. PMID:28125706
Motif-based analysis of large nucleotide data sets using MEME-ChIP
Ma, Wenxiu; Noble, William S; Bailey, Timothy L
2014-01-01
MEME-ChIP is a web-based tool for analyzing motifs in large DNA or RNA data sets. It can analyze peak regions identified by ChIP-seq, cross-linking sites identified by cLIP-seq and related assays, as well as sets of genomic regions selected using other criteria. MEME-ChIP performs de novo motif discovery, motif enrichment analysis, motif location analysis and motif clustering, providing a comprehensive picture of the DNA or RNA motifs that are enriched in the input sequences. MEME-ChIP performs two complementary types of de novo motif discovery: weight matrix–based discovery for high accuracy; and word-based discovery for high sensitivity. Motif enrichment analysis using DNA or RNA motifs from human, mouse, worm, fly and other model organisms provides even greater sensitivity. MEME-ChIP’s interactive HTML output groups and aligns significant motifs to ease interpretation. this protocol takes less than 3 h, and it provides motif discovery approaches that are distinct and complementary to other online methods. PMID:24853928
Graves, Gabrielle S; Adam, Murtaza K; Stepien, Kimberly E; Han, Dennis P
2014-08-01
To evaluate sensitivity, specificity and reproducibility of colour difference plot analysis (CDPA) of 103 hexagon multifocal electroretinogram (mfERG) in detecting established hydroxychloroquine (HCQ) retinal toxicity. Twenty-three patients taking HCQ were divided into those with and without retinal toxicity and were compared with a control group without retinal disease and not taking HCQ. CDPA with two masked examiners was performed using age-corrected mfERG responses in the central ring (Rc ; 0-5.5 degrees from fixation) and paracentral ring (Rp ; 5.5-11 degrees from fixation). An abnormal ring was defined as containing any hexagons with a difference in two or more standard deviations from normal (colour blue or black). Categorical analysis (ring involvement or not) showed Rc had 83% sensitivity and 93% specificity. Rp had 89% sensitivity and 82% specificity. Requiring abnormal hexagons in both Rc and Rp yielded sensitivity and specificity of 83% and 95%, respectively. If required in only one ring, they were 89% and 80%, respectively. In this population, there was complete agreement in identifying toxicity when comparing CDPA using Rp with ring ratio analysis using R5/R4 P1 ring responses (89% sensitivity and 95% specificity). Continuous analysis of CDPA with receiver operating characteristic analysis showed optimized detection (83% sensitivity and 96% specificity) when ≥4 abnormal hexagons were present anywhere within the Rp ring outline. Intergrader agreement and reproducibility were good. Colour difference plot analysis had sensitivity and specificity that approached that of ring ratio analysis of R5/R4 P₁ responses. Ease of implementation and reproducibility are notable advantages of CDPA. © 2014 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.
Source apportionment and sensitivity analysis: two methodologies with two different purposes
NASA Astrophysics Data System (ADS)
Clappier, Alain; Belis, Claudio A.; Pernigotti, Denise; Thunis, Philippe
2017-11-01
This work reviews the existing methodologies for source apportionment and sensitivity analysis to identify key differences and stress their implicit limitations. The emphasis is laid on the differences between source impacts
(sensitivity analysis) and contributions
(source apportionment) obtained by using four different methodologies: brute-force top-down, brute-force bottom-up, tagged species and decoupled direct method (DDM). A simple theoretical example to compare these approaches is used highlighting differences and potential implications for policy. When the relationships between concentration and emissions are linear, impacts and contributions are equivalent concepts. In this case, source apportionment and sensitivity analysis may be used indifferently for both air quality planning purposes and quantifying source contributions. However, this study demonstrates that when the relationship between emissions and concentrations is nonlinear, sensitivity approaches are not suitable to retrieve source contributions and source apportionment methods are not appropriate to evaluate the impact of abatement strategies. A quantification of the potential nonlinearities should therefore be the first step prior to source apportionment or planning applications, to prevent any limitations in their use. When nonlinearity is mild, these limitations may, however, be acceptable in the context of the other uncertainties inherent to complex models. Moreover, when using sensitivity analysis for planning, it is important to note that, under nonlinear circumstances, the calculated impacts will only provide information for the exact conditions (e.g. emission reduction share) that are simulated.
Biomarkers of gluten sensitivity in patients with non-affective psychosis: a meta-analysis.
Lachance, Laura R; McKenzie, Kwame
2014-02-01
Dohan first proposed that there may be an association between gluten sensitivity and schizophrenia in the 1950s. Since then, this association has been measured using several different serum biomarkers of gluten sensitivity. At this point, it is unclear which serum biomarkers of gluten sensitivity are elevated in patients with schizophrenia. However, evidence suggests that the immune response in this group is different from the immune response to gluten found in patients with Celiac disease. A systematic literature review was performed to identify all original articles that measured biomarkers of gluten sensitivity in patients with schizophrenia and non-affective psychoses compared to a control group. Three databases were used: Ovid MEDLINE, Psych INFO, and Embase, dating back to 1946. Forward tracking and backward tracking were undertaken on retrieved papers. A meta-analysis was performed of specific biomarkers and reported according to MOOSE guidelines. 17 relevant original articles were identified, and 12 met criteria for the meta-analysis. Five biomarkers of gluten sensitivity were found to be significantly elevated in patients with non-affective psychoses compared to controls. The pooled odds ratio and 95% confidence intervals were Anti-Gliadin IgG OR=2.31 [1.16, 4.58], Anti-Gliadin IgA OR=2.57 [1.13, 5.82], Anti-TTG2 IgA OR=5.86 [2.88, 11.95], Anti-Gliadin (unspecified isotype) OR=7.68 [2.07, 28.42], and Anti-Wheat OR=2.74 [1.06, 7.08]. Four biomarkers for gluten sensitivity, Anti-EMA IgA, Anti-TTG2 IgG, Anti-DGP IgG, and Anti-Gluten were not found to be associated with schizophrenia. Not all serum biomarkers of gluten sensitivity are elevated in patients with schizophrenia. However, the specific immune response to gluten in this population differs from that found in patients with Celiac disease. Copyright © 2013 Elsevier B.V. All rights reserved.
Identifying genetic alterations that prime a cancer cell to respond to a particular therapeutic agent can facilitate the development of precision cancer medicines. Cancer cell-line (CCL) profiling of small-molecule sensitivity has emerged as an unbiased method to assess the relationships between genetic or cellular features of CCLs and small-molecule response. Here, we developed annotated cluster multidimensional enrichment analysis to explore the associations between groups of small molecules and groups of CCLs in a new, quantitative sensitivity dataset.
Sandstedt, Mikael; Jonsson, Marianne; Asp, Julia; Dellgren, Göran; Lindahl, Anders; Jeppsson, Anders; Sandstedt, Joakim
2015-12-01
Flow cytometry (FCM) has become a well-established method for analysis of both intracellular and cell-surface proteins, while quantitative RT-PCR (RT-qPCR) is used to determine gene expression with high sensitivity and specificity. Combining these two methods would be of great value. The effects of intracellular staining on RNA integrity and RT-qPCR sensitivity and quality have not, however, been fully examined. We, therefore, intended to assess these effects further. Cells from the human lung cancer cell line A549 were fixed, permeabilized and sorted by FCM. Sorted cells were analyzed using RT-qPCR. RNA integrity was determined by RNA quality indicator analysis. A549 cells were then mixed with cells of the mouse cardiomyocyte cell line HL-1. A549 cells were identified by the cell surface marker ABCG2, while HL-1 cells were identified by intracellular cTnT. Cells were sorted and analyzed by RT-qPCR. Finally, cell cultures from human atrial biopsies were used to evaluate the effects of fixation and permeabilization on RT-qPCR analysis of nonimmortalized cells stored prior to analysis by FCM. A large amount of RNA could be extracted even when cells had been fixed and permeabilized. Permeabilization resulted in increased RNA degradation and a moderate decrease in RT-qPCR sensitivity. Gene expression levels were also affected to a moderate extent. Sorted populations from the mixed A549 and HL-1 cell samples showed gene expression patterns that corresponded to FCM data. When samples were stored before FCM sorting, the RT-qPCR analysis could still be performed with high sensitivity and quality. In summary, our results show that intracellular FCM may be performed with only minor impairment of the RT-qPCR sensitivity and quality when analyzing sorted cells; however, these effects should be considered when comparing RT-qPCR data of not fixed samples with those of fixed and permeabilized samples. © 2015 International Society for Advancement of Cytometry.
Fafin-Lefevre, Mélanie; Morlais, Fabrice; Guittet, Lydia; Clin, Bénédicte; Launoy, Guy; Galateau-Sallé, Françoise; Plancoulaine, Benoît; Herlin, Paulette; Letourneux, Marc
2011-08-01
To identify which morphologic or densitometric parameters are modified in cell nuclei from bronchopulmonary cancer based on 18 parameters involving shape, intensity, chromatin, texture, and DNA content and develop a bronchopulmonary cancer screening method relying on analysis of sputum sample cell nuclei. A total of 25 sputum samples from controls and 22 bronchial aspiration samples from patients presenting with bronchopulmonary cancer who were professionally exposed to cancer were used. After Feulgen staining, 18 morphologic and DNA content parameters were measured on cell nuclei, via image cytom- etry. A method was developed for analyzing distribution quantiles, compared with simply interpreting mean values, to characterize morphologic modifications in cell nuclei. Distribution analysis of parameters enabled us to distinguish 13 of 18 parameters that demonstrated significant differences between controls and cancer cases. These parameters, used alone, enabled us to distinguish two population types, with both sensitivity and specificity > 70%. Three parameters offered 100% sensitivity and specificity. When mean values offered high sensitivity and specificity, comparable or higher sensitivity and specificity values were observed for at least one of the corresponding quantiles. Analysis of modification in morphologic parameters via distribution analysis proved promising for screening bronchopulmonary cancer from sputum.
A new framework for comprehensive, robust, and efficient global sensitivity analysis: 1. Theory
NASA Astrophysics Data System (ADS)
Razavi, Saman; Gupta, Hoshin V.
2016-01-01
Computer simulation models are continually growing in complexity with increasingly more factors to be identified. Sensitivity Analysis (SA) provides an essential means for understanding the role and importance of these factors in producing model responses. However, conventional approaches to SA suffer from (1) an ambiguous characterization of sensitivity, and (2) poor computational efficiency, particularly as the problem dimension grows. Here, we present a new and general sensitivity analysis framework (called VARS), based on an analogy to "variogram analysis," that provides an intuitive and comprehensive characterization of sensitivity across the full spectrum of scales in the factor space. We prove, theoretically, that Morris (derivative-based) and Sobol (variance-based) methods and their extensions are special cases of VARS, and that their SA indices can be computed as by-products of the VARS framework. Synthetic functions that resemble actual model response surfaces are used to illustrate the concepts, and show VARS to be as much as two orders of magnitude more computationally efficient than the state-of-the-art Sobol approach. In a companion paper, we propose a practical implementation strategy, and demonstrate the effectiveness, efficiency, and reliability (robustness) of the VARS framework on real-data case studies.
2018-01-01
Effect-directed analysis (EDA) is a commonly used approach for effect-based identification of endocrine disruptive chemicals in complex (environmental) mixtures. However, for routine toxicity assessment of, for example, water samples, current EDA approaches are considered time-consuming and laborious. We achieved faster EDA and identification by downscaling of sensitive cell-based hormone reporter gene assays and increasing fractionation resolution to allow testing of smaller fractions with reduced complexity. The high-resolution EDA approach is demonstrated by analysis of four environmental passive sampler extracts. Downscaling of the assays to a 384-well format allowed analysis of 64 fractions in triplicate (or 192 fractions without technical replicates) without affecting sensitivity compared to the standard 96-well format. Through a parallel exposure method, agonistic and antagonistic androgen and estrogen receptor activity could be measured in a single experiment following a single fractionation. From 16 selected candidate compounds, identified through nontargeted analysis, 13 could be confirmed chemically and 10 were found to be biologically active, of which the most potent nonsteroidal estrogens were identified as oxybenzone and piperine. The increased fractionation resolution and the higher throughput that downscaling provides allow for future application in routine high-resolution screening of large numbers of samples in order to accelerate identification of (emerging) endocrine disruptors. PMID:29547277
Moghtaderi, Mozhgan; Hosseini Teshnizi, Saeed; Farjadian, Shirin
2017-01-01
Various allergens are implicated in the pathogenesis of allergic diseases in different regions. This study attempted to identify the most common allergens among patients with allergies based on the results of skin prick tests in different parts of Iran. Relevant studies conducted from 2000 to 2016 were identified from the MEDLINE database. Six common groups of allergen types, including animal, cockroach, food, fungus, house dust mite, and pollen were considered. Subgroup analysis was performed to determine the prevalence of each type of allergen. The Egger test was used to assess publication bias. We included 44 studies in this meta-analysis. The overall prevalence of positive skin test results for at least one allergen was estimated to be 59% in patients with allergies in various parts of Iran. The number of patients was 11,646 (56% male and 44% female), with a mean age of 17.46±11.12 years. The most common allergen sources were pollen (47.0%), mites (35.2%), and food (15.3%). The prevalence of sensitization to food and cockroach allergens among children was greater than among adults. Pollen is the most common allergen sensitization in cities of Iran with a warm and dry climate; however, sensitization to house dust mites is predominant in northern and southern coastal areas of Iran.
Farjadian, Shirin
2017-01-01
Various allergens are implicated in the pathogenesis of allergic diseases in different regions. This study attempted to identify the most common allergens among patients with allergies based on the results of skin prick tests in different parts of Iran. Relevant studies conducted from 2000 to 2016 were identified from the MEDLINE database. Six common groups of allergen types, including animal, cockroach, food, fungus, house dust mite, and pollen were considered. Subgroup analysis was performed to determine the prevalence of each type of allergen. The Egger test was used to assess publication bias. We included 44 studies in this meta-analysis. The overall prevalence of positive skin test results for at least one allergen was estimated to be 59% in patients with allergies in various parts of Iran. The number of patients was 11,646 (56% male and 44% female), with a mean age of 17.46±11.12 years. The most common allergen sources were pollen (47.0%), mites (35.2%), and food (15.3%). The prevalence of sensitization to food and cockroach allergens among children was greater than among adults. Pollen is the most common allergen sensitization in cities of Iran with a warm and dry climate; however, sensitization to house dust mites is predominant in northern and southern coastal areas of Iran. PMID:28171712
Pain sensitivity profiles in patients with advanced knee osteoarthritis
Frey-Law, Laura A.; Bohr, Nicole L.; Sluka, Kathleen A.; Herr, Keela; Clark, Charles R.; Noiseux, Nicolas O.; Callaghan, John J; Zimmerman, M Bridget; Rakel, Barbara A.
2016-01-01
The development of patient profiles to subgroup individuals on a variety of variables has gained attention as a potential means to better inform clinical decision-making. Patterns of pain sensitivity response specific to quantitative sensory testing (QST) modality have been demonstrated in healthy subjects. It has not been determined if these patterns persist in a knee osteoarthritis population. In a sample of 218 participants, 19 QST measures along with pain, psychological factors, self-reported function, and quality of life were assessed prior to total knee arthroplasty. Component analysis was used to identify commonalities across the 19 QST assessments to produce standardized pain sensitivity factors. Cluster analysis then grouped individuals that exhibited similar patterns of standardized pain sensitivity component scores. The QST resulted in four pain sensitivity components: heat, punctate, temporal summation, and pressure. Cluster analysis resulted in five pain sensitivity profiles: a “low pressure pain” group, an “average pain” group, and three “high pain” sensitivity groups who were sensitive to different modalities (punctate, heat, and temporal summation). Pain and function differed between pain sensitivity profiles, along with sex distribution; however no differences in OA grade, medication use, or psychological traits were found. Residualizing QST data by age and sex resulted in similar components and pain sensitivity profiles. Further, these profiles are surprisingly similar to those reported in healthy populations suggesting that individual differences in pain sensitivity are a robust finding even in an older population with significant disease. PMID:27152688
Differential metabolome analysis of field-grown maize kernels in response to drought stress
USDA-ARS?s Scientific Manuscript database
Drought stress constrains maize kernel development and can exacerbate aflatoxin contamination. In order to identify drought responsive metabolites and explore pathways involved in kernel responses, a metabolomics analysis was conducted on kernels from a drought tolerant line, Lo964, and a sensitive ...
Uncertainty and Sensitivity Analysis of Afterbody Radiative Heating Predictions for Earth Entry
NASA Technical Reports Server (NTRS)
West, Thomas K., IV; Johnston, Christopher O.; Hosder, Serhat
2016-01-01
The objective of this work was to perform sensitivity analysis and uncertainty quantification for afterbody radiative heating predictions of Stardust capsule during Earth entry at peak afterbody radiation conditions. The radiation environment in the afterbody region poses significant challenges for accurate uncertainty quantification and sensitivity analysis due to the complexity of the flow physics, computational cost, and large number of un-certain variables. In this study, first a sparse collocation non-intrusive polynomial chaos approach along with global non-linear sensitivity analysis was used to identify the most significant uncertain variables and reduce the dimensions of the stochastic problem. Then, a total order stochastic expansion was constructed over only the important parameters for an efficient and accurate estimate of the uncertainty in radiation. Based on previous work, 388 uncertain parameters were considered in the radiation model, which came from the thermodynamics, flow field chemistry, and radiation modeling. The sensitivity analysis showed that only four of these variables contributed significantly to afterbody radiation uncertainty, accounting for almost 95% of the uncertainty. These included the electronic- impact excitation rate for N between level 2 and level 5 and rates of three chemical reactions in uencing N, N(+), O, and O(+) number densities in the flow field.
General methods for sensitivity analysis of equilibrium dynamics in patch occupancy models
Miller, David A.W.
2012-01-01
Sensitivity analysis is a useful tool for the study of ecological models that has many potential applications for patch occupancy modeling. Drawing from the rich foundation of existing methods for Markov chain models, I demonstrate new methods for sensitivity analysis of the equilibrium state dynamics of occupancy models. Estimates from three previous studies are used to illustrate the utility of the sensitivity calculations: a joint occupancy model for a prey species, its predators, and habitat used by both; occurrence dynamics from a well-known metapopulation study of three butterfly species; and Golden Eagle occupancy and reproductive dynamics. I show how to deal efficiently with multistate models and how to calculate sensitivities involving derived state variables and lower-level parameters. In addition, I extend methods to incorporate environmental variation by allowing for spatial and temporal variability in transition probabilities. The approach used here is concise and general and can fully account for environmental variability in transition parameters. The methods can be used to improve inferences in occupancy studies by quantifying the effects of underlying parameters, aiding prediction of future system states, and identifying priorities for sampling effort.
Convergence Estimates for Multidisciplinary Analysis and Optimization
NASA Technical Reports Server (NTRS)
Arian, Eyal
1997-01-01
A quantitative analysis of coupling between systems of equations is introduced. This analysis is then applied to problems in multidisciplinary analysis, sensitivity, and optimization. For the sensitivity and optimization problems both multidisciplinary and single discipline feasibility schemes are considered. In all these cases a "convergence factor" is estimated in terms of the Jacobians and Hessians of the system, thus it can also be approximated by existing disciplinary analysis and optimization codes. The convergence factor is identified with the measure for the "coupling" between the disciplines in the system. Applications to algorithm development are discussed. Demonstration of the convergence estimates and numerical results are given for a system composed of two non-linear algebraic equations, and for a system composed of two PDEs modeling aeroelasticity.
Correlation between experimental human and murine skin sensitization induction thresholds.
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).
Ely, D. Matthew
2006-01-01
Recharge is a vital component of the ground-water budget and methods for estimating it range from extremely complex to relatively simple. The most commonly used techniques, however, are limited by the scale of application. One method that can be used to estimate ground-water recharge includes process-based models that compute distributed water budgets on a watershed scale. These models should be evaluated to determine which model parameters are the dominant controls in determining ground-water recharge. Seven existing watershed models from different humid regions of the United States were chosen to analyze the sensitivity of simulated recharge to model parameters. Parameter sensitivities were determined using a nonlinear regression computer program to generate a suite of diagnostic statistics. The statistics identify model parameters that have the greatest effect on simulated ground-water recharge and that compare and contrast the hydrologic system responses to those parameters. Simulated recharge in the Lost River and Big Creek watersheds in Washington State was sensitive to small changes in air temperature. The Hamden watershed model in west-central Minnesota was developed to investigate the relations that wetlands and other landscape features have with runoff processes. Excess soil moisture in the Hamden watershed simulation was preferentially routed to wetlands, instead of to the ground-water system, resulting in little sensitivity of any parameters to recharge. Simulated recharge in the North Fork Pheasant Branch watershed, Wisconsin, demonstrated the greatest sensitivity to parameters related to evapotranspiration. Three watersheds were simulated as part of the Model Parameter Estimation Experiment (MOPEX). Parameter sensitivities for the MOPEX watersheds, Amite River, Louisiana and Mississippi, English River, Iowa, and South Branch Potomac River, West Virginia, were similar and most sensitive to small changes in air temperature and a user-defined flow routing parameter. Although the primary objective of this study was to identify, by geographic region, the importance of the parameter value to the simulation of ground-water recharge, the secondary objectives proved valuable for future modeling efforts. The value of a rigorous sensitivity analysis can (1) make the calibration process more efficient, (2) guide additional data collection, (3) identify model limitations, and (4) explain simulated results.
Which Industries Are Sensitive to Business Cycles?
ERIC Educational Resources Information Center
Berman, Jay; Pfleeger, Janet
1997-01-01
An analysis of the 1994-2005 Bureau of Labor Statistics employment projections can be used to identify industries that are projected to move differently with business cycles in the future than with those of the past, and can be used to identify the industries and occupations that are most prone to business cycle swings. (Author)
Makdissi, Michael; Davis, Gavin
2016-10-01
The objective of this study was to determine the reliability and validity of identifying clinical signs of concussion using video analysis in Australian football. Prospective cohort study. All impacts and collisions potentially resulting in a concussion were identified during 2012 and 2013 Australian Football League seasons. Consensus definitions were developed for clinical signs associated with concussion. For intra- and inter-rater reliability analysis, two experienced clinicians independently assessed 102 randomly selected videos on two occasions. Sensitivity, specificity, positive and negative predictive values were calculated based on the diagnosis provided by team medical staff. 212 incidents resulting in possible concussion were identified in 414 Australian Football League games. The intra-rater reliability of the video-based identification of signs associated with concussion was good to excellent. Inter-rater reliability was good to excellent for impact seizure, slow to get up, motor incoordination, ragdoll appearance (2 of 4 analyses), clutching at head and facial injury. Inter-rater reliability for loss of responsiveness and blank and vacant look was only fair and did not reach statistical significance. The feature with the highest sensitivity was slow to get up (87%), but this sign had a low specificity (19%). Other video signs had a high specificity but low sensitivity. Blank and vacant look (100%) and motor incoordination (81%) had the highest positive predictive value. Video analysis may be a useful adjunct to the side-line assessment of a possible concussion. Video analysis however should not replace the need for a thorough multimodal clinical assessment. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Harshan, S.; Roth, M.; Velasco, E.
2014-12-01
Forecasting of the urban weather and climate is of great importance as our cities become more populated and considering the combined effects of global warming and local land use changes which make urban inhabitants more vulnerable to e.g. heat waves and flash floods. In meso/global scale models, urban parameterization schemes are used to represent the urban effects. However, these schemes require a large set of input parameters related to urban morphological and thermal properties. Obtaining all these parameters through direct measurements are usually not feasible. A number of studies have reported on parameter estimation and sensitivity analysis to adjust and determine the most influential parameters for land surface schemes in non-urban areas. Similar work for urban areas is scarce, in particular studies on urban parameterization schemes in tropical cities have so far not been reported. In order to address above issues, the town energy balance (TEB) urban parameterization scheme (part of the SURFEX land surface modeling system) was subjected to a sensitivity and optimization/parameter estimation experiment at a suburban site in, tropical Singapore. The sensitivity analysis was carried out as a screening test to identify the most sensitive or influential parameters. Thereafter, an optimization/parameter estimation experiment was performed to calibrate the input parameter. The sensitivity experiment was based on the "improved Sobol's global variance decomposition method" . The analysis showed that parameters related to road, roof and soil moisture have significant influence on the performance of the model. The optimization/parameter estimation experiment was performed using the AMALGM (a multi-algorithm genetically adaptive multi-objective method) evolutionary algorithm. The experiment showed a remarkable improvement compared to the simulations using the default parameter set. The calibrated parameters from this optimization experiment can be used for further model validation studies to identify inherent deficiencies in model physics.
2014-09-01
previous report [6, 7], Ptenpc-/- tumors are sensitive to ADT (Fig 1A). A significant amount of normal epithelium was identified in castrated...histopathological analysis by H & E staining (Fig 1A) and MRI analysis (data not shown). There is no noticeable normal epithelium in the castrated Ptenpc...indicated that while tumor cells are enriched for pathways involving cell adhesion molecules and tight junction (consistent with their epithelial
NASA Astrophysics Data System (ADS)
Samper, J.; Dewonck, S.; Zheng, L.; Yang, Q.; Naves, A.
Diffusion of inert and reactive tracers (DIR) is an experimental program performed by ANDRA at Bure underground research laboratory in Meuse/Haute Marne (France) to characterize diffusion and retention of radionuclides in Callovo-Oxfordian (C-Ox) argillite. In situ diffusion experiments were performed in vertical boreholes to determine diffusion and retention parameters of selected radionuclides. C-Ox clay exhibits a mild diffusion anisotropy due to stratification. Interpretation of in situ diffusion experiments is complicated by several non-ideal effects caused by the presence of a sintered filter, a gap between the filter and borehole wall and an excavation disturbed zone (EdZ). The relevance of such non-ideal effects and their impact on estimated clay parameters have been evaluated with numerical sensitivity analyses and synthetic experiments having similar parameters and geometric characteristics as real DIR experiments. Normalized dimensionless sensitivities of tracer concentrations at the test interval have been computed numerically. Tracer concentrations are found to be sensitive to all key parameters. Sensitivities are tracer dependent and vary with time. These sensitivities are useful to identify which are the parameters that can be estimated with less uncertainty and find the times at which tracer concentrations begin to be sensitive to each parameter. Synthetic experiments generated with prescribed known parameters have been interpreted automatically with INVERSE-CORE 2D and used to evaluate the relevance of non-ideal effects and ascertain parameter identifiability in the presence of random measurement errors. Identifiability analysis of synthetic experiments reveals that data noise makes difficult the estimation of clay parameters. Parameters of clay and EdZ cannot be estimated simultaneously from noisy data. Models without an EdZ fail to reproduce synthetic data. Proper interpretation of in situ diffusion experiments requires accounting for filter, gap and EdZ. Estimates of the effective diffusion coefficient and the porosity of clay are highly correlated, indicating that these parameters cannot be estimated simultaneously. Accurate estimation of De and porosities of clay and EdZ is only possible when the standard deviation of random noise is less than 0.01. Small errors in the volume of the circulation system do not affect clay parameter estimates. Normalized sensitivities as well as the identifiability analysis of synthetic experiments provide additional insight on inverse estimation of in situ diffusion experiments and will be of great benefit for the interpretation of real DIR in situ diffusion experiments.
Famoso, Adam N.; Zhao, Keyan; Clark, Randy T.; Tung, Chih-Wei; Wright, Mark H.; Bustamante, Carlos; Kochian, Leon V.; McCouch, Susan R.
2011-01-01
Aluminum (Al) toxicity is a primary limitation to crop productivity on acid soils, and rice has been demonstrated to be significantly more Al tolerant than other cereal crops. However, the mechanisms of rice Al tolerance are largely unknown, and no genes underlying natural variation have been reported. We screened 383 diverse rice accessions, conducted a genome-wide association (GWA) study, and conducted QTL mapping in two bi-parental populations using three estimates of Al tolerance based on root growth. Subpopulation structure explained 57% of the phenotypic variation, and the mean Al tolerance in Japonica was twice that of Indica. Forty-eight regions associated with Al tolerance were identified by GWA analysis, most of which were subpopulation-specific. Four of these regions co-localized with a priori candidate genes, and two highly significant regions co-localized with previously identified QTLs. Three regions corresponding to induced Al-sensitive rice mutants (ART1, STAR2, Nrat1) were identified through bi-parental QTL mapping or GWA to be involved in natural variation for Al tolerance. Haplotype analysis around the Nrat1 gene identified susceptible and tolerant haplotypes explaining 40% of the Al tolerance variation within the aus subpopulation, and sequence analysis of Nrat1 identified a trio of non-synonymous mutations predictive of Al sensitivity in our diversity panel. GWA analysis discovered more phenotype–genotype associations and provided higher resolution, but QTL mapping identified critical rare and/or subpopulation-specific alleles not detected by GWA analysis. Mapping using Indica/Japonica populations identified QTLs associated with transgressive variation where alleles from a susceptible aus or indica parent enhanced Al tolerance in a tolerant Japonica background. This work supports the hypothesis that selectively introgressing alleles across subpopulations is an efficient approach for trait enhancement in plant breeding programs and demonstrates the fundamental importance of subpopulation in interpreting and manipulating the genetics of complex traits in rice. PMID:21829395
Skeletal Mechanism Generation of Surrogate Jet Fuels for Aeropropulsion Modeling
NASA Astrophysics Data System (ADS)
Sung, Chih-Jen; Niemeyer, Kyle E.
2010-05-01
A novel implementation for the skeletal reduction of large detailed reaction mechanisms using the directed relation graph with error propagation and sensitivity analysis (DRGEPSA) is developed and presented with skeletal reductions of two important hydrocarbon components, n-heptane and n-decane, relevant to surrogate jet fuel development. DRGEPSA integrates two previously developed methods, directed relation graph-aided sensitivity analysis (DRGASA) and directed relation graph with error propagation (DRGEP), by first applying DRGEP to efficiently remove many unimportant species prior to sensitivity analysis to further remove unimportant species, producing an optimally small skeletal mechanism for a given error limit. It is illustrated that the combination of the DRGEP and DRGASA methods allows the DRGEPSA approach to overcome the weaknesses of each previous method, specifically that DRGEP cannot identify all unimportant species and that DRGASA shields unimportant species from removal.
Legler, Juliette; Fletcher, Tony; Govarts, Eva; Porta, Miquel; Blumberg, Bruce; Heindel, Jerrold J; Trasande, Leonardo
2015-04-01
Obesity and diabetes are epidemic in the European Union (EU). Exposure to endocrine-disrupting chemicals (EDCs) is increasingly recognized as a contributor, independent of diet and physical activity. The objective was to estimate obesity, diabetes, and associated costs that can be reasonably attributed to EDC exposures in the EU. An expert panel evaluated evidence for probability of causation using weight-of-evidence characterization adapted from that applied by the Intergovernmental Panel on Climate Change. Exposure-response relationships and reference levels were evaluated for relevant EDCs, and biomarker data were organized from peer-reviewed studies to represent European exposure and burden of disease. Cost estimation as of 2010 utilized published cost estimates for childhood obesity, adult obesity, and adult diabetes. Setting, Patients and Participants, and Intervention: Cost estimation was performed from the societal perspective. The panel identified a 40% to 69% probability of dichlorodiphenyldichloroethylene causing 1555 cases of overweight at age 10 (sensitivity analysis: 1555-5463) in 2010 with associated costs of €24.6 million (sensitivity analysis: €24.6-86.4 million). A 20% to 39% probability was identified for dichlorodiphenyldichloroethylene causing 28 200 cases of adult diabetes (sensitivity analysis: 28 200-56 400) with associated costs of €835 million (sensitivity analysis: €835 million-16.6 billion). The panel also identified a 40% to 69% probability of phthalate exposure causing 53 900 cases of obesity in older women and €15.6 billion in associated costs. Phthalate exposure was also found to have a 40% to 69% probability of causing 20 500 new-onset cases of diabetes in older women with €607 million in associated costs. Prenatal bisphenol A exposure was identified to have a 20% to 69% probability of causing 42 400 cases of childhood obesity, with associated lifetime costs of €1.54 billion. EDC exposures in the EU contribute substantially to obesity and diabetes, with a moderate probability of >€18 billion costs per year. This is a conservative estimate; the results emphasize the need to control EDC exposures.
Legler, Juliette; Fletcher, Tony; Govarts, Eva; Porta, Miquel; Blumberg, Bruce; Heindel, Jerrold J.
2015-01-01
Context: Obesity and diabetes are epidemic in the European Union (EU). Exposure to endocrine-disrupting chemicals (EDCs) is increasingly recognized as a contributor, independent of diet and physical activity. Objective: The objective was to estimate obesity, diabetes, and associated costs that can be reasonably attributed to EDC exposures in the EU. Design: An expert panel evaluated evidence for probability of causation using weight-of-evidence characterization adapted from that applied by the Intergovernmental Panel on Climate Change. Exposure-response relationships and reference levels were evaluated for relevant EDCs, and biomarker data were organized from peer-reviewed studies to represent European exposure and burden of disease. Cost estimation as of 2010 utilized published cost estimates for childhood obesity, adult obesity, and adult diabetes. Setting, Patients and Participants, and Intervention: Cost estimation was performed from the societal perspective. Results: The panel identified a 40% to 69% probability of dichlorodiphenyldichloroethylene causing 1555 cases of overweight at age 10 (sensitivity analysis: 1555–5463) in 2010 with associated costs of €24.6 million (sensitivity analysis: €24.6–86.4 million). A 20% to 39% probability was identified for dichlorodiphenyldichloroethylene causing 28 200 cases of adult diabetes (sensitivity analysis: 28 200–56 400) with associated costs of €835 million (sensitivity analysis: €835 million–16.6 billion). The panel also identified a 40% to 69% probability of phthalate exposure causing 53 900 cases of obesity in older women and €15.6 billion in associated costs. Phthalate exposure was also found to have a 40% to 69% probability of causing 20 500 new-onset cases of diabetes in older women with €607 million in associated costs. Prenatal bisphenol A exposure was identified to have a 20% to 69% probability of causing 42 400 cases of childhood obesity, with associated lifetime costs of €1.54 billion. Conclusions: EDC exposures in the EU contribute substantially to obesity and diabetes, with a moderate probability of >€18 billion costs per year. This is a conservative estimate; the results emphasize the need to control EDC exposures. PMID:25742518
Sensitivity Analysis of the Land Surface Model NOAH-MP for Different Model Fluxes
NASA Astrophysics Data System (ADS)
Mai, Juliane; Thober, Stephan; Samaniego, Luis; Branch, Oliver; Wulfmeyer, Volker; Clark, Martyn; Attinger, Sabine; Kumar, Rohini; Cuntz, Matthias
2015-04-01
Land Surface Models (LSMs) use a plenitude of process descriptions to represent the carbon, energy and water cycles. They are highly complex and computationally expensive. Practitioners, however, are often only interested in specific outputs of the model such as latent heat or surface runoff. In model applications like parameter estimation, the most important parameters are then chosen by experience or expert knowledge. Hydrologists interested in surface runoff therefore chose mostly soil parameters while biogeochemists interested in carbon fluxes focus on vegetation parameters. However, this might lead to the omission of parameters that are important, for example, through strong interactions with the parameters chosen. It also happens during model development that some process descriptions contain fixed values, which are supposedly unimportant parameters. However, these hidden parameters remain normally undetected although they might be highly relevant during model calibration. Sensitivity analyses are used to identify informative model parameters for a specific model output. Standard methods for sensitivity analysis such as Sobol indexes require large amounts of model evaluations, specifically in case of many model parameters. We hence propose to first use a recently developed inexpensive sequential screening method based on Elementary Effects that has proven to identify the relevant informative parameters. This reduces the number parameters and therefore model evaluations for subsequent analyses such as sensitivity analysis or model calibration. In this study, we quantify parametric sensitivities of the land surface model NOAH-MP that is a state-of-the-art LSM and used at regional scale as the land surface scheme of the atmospheric Weather Research and Forecasting Model (WRF). NOAH-MP contains multiple process parameterizations yielding a considerable amount of parameters (˜ 100). Sensitivities for the three model outputs (a) surface runoff, (b) soil drainage and (c) latent heat are calculated on twelve Model Parameter Estimation Experiment (MOPEX) catchments ranging in size from 1020 to 4421 km2. This allows investigation of parametric sensitivities for distinct hydro-climatic characteristics, emphasizing different land-surface processes. The sequential screening identifies the most informative parameters of NOAH-MP for different model output variables. The number of parameters is reduced substantially for all of the three model outputs to approximately 25. The subsequent Sobol method quantifies the sensitivities of these informative parameters. The study demonstrates the existence of sensitive, important parameters in almost all parts of the model irrespective of the considered output. Soil parameters, e.g., are informative for all three output variables whereas plant parameters are not only informative for latent heat but also for soil drainage because soil drainage is strongly coupled to transpiration through the soil water balance. These results contrast to the choice of only soil parameters in hydrological studies and only plant parameters in biogeochemical ones. The sequential screening identified several important hidden parameters that carry large sensitivities and have hence to be included during model calibration.
Bermudo, R; Abia, D; Mozos, A; García-Cruz, E; Alcaraz, A; Ortiz, Á R; Thomson, T M; Fernández, P L
2011-01-01
Introduction: Currently, final diagnosis of prostate cancer (PCa) is based on histopathological analysis of needle biopsies, but this process often bears uncertainties due to small sample size, tumour focality and pathologist's subjective assessment. Methods: Prostate cancer diagnostic signatures were generated by applying linear discriminant analysis to microarray and real-time RT–PCR (qRT–PCR) data from normal and tumoural prostate tissue samples. Additionally, after removal of biopsy tissues, material washed off from transrectal biopsy needles was used for molecular profiling and discriminant analysis. Results: Linear discriminant analysis applied to microarray data for a set of 318 genes differentially expressed between non-tumoural and tumoural prostate samples produced 26 gene signatures, which classified the 84 samples used with 100% accuracy. To identify signatures potentially useful for the diagnosis of prostate biopsies, surplus material washed off from routine biopsy needles from 53 patients was used to generate qRT–PCR data for a subset of 11 genes. This analysis identified a six-gene signature that correctly assigned the biopsies as benign or tumoural in 92.6% of the cases, with 88.8% sensitivity and 96.1% specificity. Conclusion: Surplus material from prostate needle biopsies can be used for minimal-size gene signature analysis for sensitive and accurate discrimination between non-tumoural and tumoural prostates, without interference with current diagnostic procedures. This approach could be a useful adjunct to current procedures in PCa diagnosis. PMID:22009027
USDA-ARS?s Scientific Manuscript database
Drought tolerance is a complex trait that is governed by multiple genes. To identify the potential candidate genes, comparative analysis of drought stress-responsive transcriptome between drought-tolerant (Triticum aestivum Cv. C306) and drought-sensitive (Triticum aestivum Cv. WL711) genotypes was ...
While sensitivity of model species to common toxicants has been addressed, a systematic analysis of inter-species variability for different test types, modes of action and species is as yet lacking. Hence, the aim of the present study was to identify similarities and differences ...
Yang, Ze-Hui; Zheng, Rui; Gao, Yuan; Zhang, Qiang
2016-09-01
With the widespread application of high-throughput technology, numerous meta-analysis methods have been proposed for differential expression profiling across multiple studies. We identified the suitable differentially expressed (DE) genes that contributed to lung adenocarcinoma (ADC) clustering based on seven popular multiple meta-analysis methods. Seven microarray expression profiles of ADC and normal controls were extracted from the ArrayExpress database. The Bioconductor was used to perform the data preliminary preprocessing. Then, DE genes across multiple studies were identified. Hierarchical clustering was applied to compare the classification performance for microarray data samples. The classification efficiency was compared based on accuracy, sensitivity and specificity. Across seven datasets, 573 ADC cases and 222 normal controls were collected. After filtering out unexpressed and noninformative genes, 3688 genes were remained for further analysis. The classification efficiency analysis showed that DE genes identified by sum of ranks method separated ADC from normal controls with the best accuracy, sensitivity and specificity of 0.953, 0.969 and 0.932, respectively. The gene set with the highest classification accuracy mainly participated in the regulation of response to external stimulus (P = 7.97E-04), cyclic nucleotide-mediated signaling (P = 0.01), regulation of cell morphogenesis (P = 0.01) and regulation of cell proliferation (P = 0.01). Evaluation of DE genes identified by different meta-analysis methods in classification efficiency provided a new perspective to the choice of the suitable method in a given application. Varying meta-analysis methods always present varying abilities, so synthetic consideration should be taken when providing meta-analysis methods for particular research. © 2015 John Wiley & Sons Ltd.
Optimal Hemoglobin A1c Levels for Screening of Diabetes and Prediabetes in the Japanese Population.
Shimodaira, Masanori; Okaniwa, Shinji; Hanyu, Norinao; Nakayama, Tomohiro
2015-01-01
The aim of this study was to evaluate the utility of hemoglobin A1c (HbA1c) to identify individuals with diabetes and prediabetes in the Japanese population. A total of 1372 individuals without known diabetes were selected for this study. A 75 g oral glucose tolerance test (OGTT) was used to diagnose diabetes and prediabetes. The ability of HbA1c to detect diabetes and prediabetes was investigated using receiver operating characteristic (ROC) analysis. The kappa (κ) coefficient was used to test the agreement between HbA1c categorization and OGTT-based diagnosis. ROC analysis demonstrated that HbA1c was a good test to identify diabetes and prediabetes, with areas under the curve of 0.918 and 0.714, respectively. Optimal HbA1c cutoffs for diagnosing diabetes and prediabetes were 6.0% (sensitivity 83.7%, specificity 87.6%) and 5.7% (sensitivity 60.6%, specificity 72.1%), respectively, although the cutoff for prediabetes showed low accuracy (67.6%) and a high false-negative rate (39.4%). Agreement between HbA1c categorization and OGTT-based diagnosis was low in diabetes (κ = 0.399) and prediabetes (κ = 0.324). In Japanese subjects, the HbA1c cutoff of 6.0% had appropriate sensitivity and specificity for diabetes screening, whereas the cutoff of 5.7% had modest sensitivity and specificity in identifying prediabetes. Thus, HbA1c may be inadequate as a screening tool for prediabetes.
Alkylation sensitivity screens reveal a conserved cross-species functionome
Svilar, David; Dyavaiah, Madhu; Brown, Ashley R.; Tang, Jiang-bo; Li, Jianfeng; McDonald, Peter R.; Shun, Tong Ying; Braganza, Andrea; Wang, Xiao-hong; Maniar, Salony; St Croix, Claudette M.; Lazo, John S.; Pollack, Ian F.; Begley, Thomas J.; Sobol, Robert W.
2013-01-01
To identify genes that contribute to chemotherapy resistance in glioblastoma, we conducted a synthetic lethal screen in a chemotherapy-resistant glioblastoma derived cell line with the clinical alkylator temozolomide (TMZ) and an siRNA library tailored towards “druggable” targets. Select DNA repair genes in the screen were validated independently, confirming the DNA glycosylases UNG and MYH as well as MPG to be involved in the response to high dose TMZ. The involvement of UNG and MYH is likely the result of a TMZ-induced burst of reactive oxygen species. We then compared the human TMZ sensitizing genes identified in our screen with those previously identified from alkylator screens conducted in E. coli and S. cerevisiae. The conserved biological processes across all three species composes an Alkylation Functionome that includes many novel proteins not previously thought to impact alkylator resistance. This high-throughput screen, validation and cross-species analysis was then followed by a mechanistic analysis of two essential nodes: base excision repair (BER) DNA glycosylases (UNG, human and mag1, S. cerevisiae) and protein modification systems, including UBE3B and ICMT in human cells or pby1, lip22, stp22 and aim22 in S. cerevisiae. The conserved processes of BER and protein modification were dual targeted and yielded additive sensitization to alkylators in S. cerevisiae. In contrast, dual targeting of BER and protein modification genes in human cells did not increase sensitivity, suggesting an epistatic relationship. Importantly, these studies provide potential new targets to overcome alkylating agent resistance. PMID:23038810
Yoshida, Kanako; Kuramitsu, Yasuhiro; Murakami, Kohei; Ryozawa, Shomei; Taba, Kumiko; Kaino, Seiji; Zhang, Xiulian; Sakaida, Isao; Nakamura, Kazuyuki
2011-06-01
TS-1 is an oral anticancer agent containing two biochemical modulators for 5-fluorouracil (5-FU) and tegafur (FT), a metabolically activated prodrug of 5-FU. TS-1 has been recognized as an effective anticancer drug using standard therapies for patients with advanced pancreatic cancer along with gemcitabine. However, a high level of inherent and acquired tumor resistance to TS-1 induces difficulty in the treatment. To identify proteins linked to the TS-1-resistance of pancreatic cancer, we profiled protein expression levels in samples of TS-1-resistant and -sensitive pancreatic cancer cell lines by using two-dimensional gel electrophoresis (2-DE) and liquid chromatography-tandem mass spectrometry (LC-MS/MS). The cytotoxicity of a 5-FU/5-chloro-2,4-dihydroxypyridine (CDHP) combination towards pancreatic cancer cell lines was evaluated by MTS assay. Panc-1, BxPC-3, MiaPaCa-2 and PK59 showed high sensitivity to the 5-FU/CDHP combination (TS-1-sensitive), whereas PK45p and KLM-1 were much less sensitive (TS-1-resistant). Proteomic analysis showed that eleven spots, including T-complex protein 1 subunit beta, ribonuclease inhibitor, elongation factor 1-delta, peroxiredoxin-2 and superoxide dismutase (Cu-Zn), appeared to be down-regulated, and 29 spots, including hypoxia up-regulated protein 1, lamin-A/C, endoplasmin, fascin and annexin A1, appeared to be up-regulated in TS-1-resistant cells compared with -sensitive cells. These results suggest that the identified proteins showing different expression between TS-1-sensitive and -resistant pancreatic cancer cells possibly relate to TS-1-sensitivity. These findings could be useful to overcome the TS-1-resistance of pancreatic cancer cells.
Gan, Yanjun; Duan, Qingyun; Gong, Wei; ...
2014-01-01
Sensitivity analysis (SA) is a commonly used approach for identifying important parameters that dominate model behaviors. We use a newly developed software package, a Problem Solving environment for Uncertainty Analysis and Design Exploration (PSUADE), to evaluate the effectiveness and efficiency of ten widely used SA methods, including seven qualitative and three quantitative ones. All SA methods are tested using a variety of sampling techniques to screen out the most sensitive (i.e., important) parameters from the insensitive ones. The Sacramento Soil Moisture Accounting (SAC-SMA) model, which has thirteen tunable parameters, is used for illustration. The South Branch Potomac River basin nearmore » Springfield, West Virginia in the U.S. is chosen as the study area. The key findings from this study are: (1) For qualitative SA methods, Correlation Analysis (CA), Regression Analysis (RA), and Gaussian Process (GP) screening methods are shown to be not effective in this example. Morris One-At-a-Time (MOAT) screening is the most efficient, needing only 280 samples to identify the most important parameters, but it is the least robust method. Multivariate Adaptive Regression Splines (MARS), Delta Test (DT) and Sum-Of-Trees (SOT) screening methods need about 400–600 samples for the same purpose. Monte Carlo (MC), Orthogonal Array (OA) and Orthogonal Array based Latin Hypercube (OALH) are appropriate sampling techniques for them; (2) For quantitative SA methods, at least 2777 samples are needed for Fourier Amplitude Sensitivity Test (FAST) to identity parameter main effect. McKay method needs about 360 samples to evaluate the main effect, more than 1000 samples to assess the two-way interaction effect. OALH and LPτ (LPTAU) sampling techniques are more appropriate for McKay method. For the Sobol' method, the minimum samples needed are 1050 to compute the first-order and total sensitivity indices correctly. These comparisons show that qualitative SA methods are more efficient but less accurate and robust than quantitative ones.« less
Ma, Chunming; Liu, Yue; Lu, Qiang; Lu, Na; Liu, Xiaoli; Tian, Yiming; Wang, Rui; Yin, Fuzai
2016-02-01
The blood pressure-to-height ratio (BPHR) has been shown to be an accurate index for screening hypertension in children and adolescents. The aim of the present study was to perform a meta-analysis to assess the performance of BPHR for the assessment of hypertension. Electronic and manual searches were performed to identify studies of the BPHR. After methodological quality assessment and data extraction, pooled estimates of the sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, area under the receiver operating characteristic curve and summary receiver operating characteristics were assessed systematically. The extent of heterogeneity for it was assessed. Six studies were identified for analysis. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio values of BPHR, for assessment of hypertension, were 96% [95% confidence interval (CI)=0.95-0.97], 90% (95% CI=0.90-0.91), 10.68 (95% CI=8.03-14.21), 0.04 (95% CI=0.03-0.07) and 247.82 (95% CI=114.50-536.34), respectively. The area under the receiver operating characteristic curve was 0.9472. The BPHR had higher diagnostic accuracies for identifying hypertension in children and adolescents.
Page, Robert B; Monaghan, James R; Samuels, Amy K; Smith, Jeramiah J; Beachy, Christopher K; Voss, S Randal
2007-02-01
Ambystomatid salamanders offer several advantages for endocrine disruption research, including genomic and bioinformatics resources, an accessible laboratory model (Ambystoma mexicanum), and natural lineages that are broadly distributed among North American habitats. We used microarray analysis to measure the relative abundance of transcripts isolated from A. mexicanum epidermis (skin) after exogenous application of thyroid hormone (TH). Only one gene had a >2-fold change in transcript abundance after 2 days of TH treatment. However, hundreds of genes showed significantly different transcript levels at days 12 and 28 in comparison to day 0. A list of 123 TH-responsive genes was identified using statistical, BLAST, and fold level criteria. Cluster analysis identified two groups of genes with similar transcription patterns: up-regulated versus down-regulated. Most notably, several keratins exhibited dramatic (1000 fold) increases or decreases in transcript abundance. Keratin gene expression changes coincided with morphological remodeling of epithelial tissues. This suggests that keratin loci can be developed as sensitive biomarkers to assay temporal disruptions of larval-to-adult gene expression programs. Our study has identified the first collection of loci that are regulated during TH-induced metamorphosis in a salamander, thus setting the stage for future investigations of TH disruption in the Mexican axolotl and other salamanders of the genus Ambystoma.
Imaging modalities for characterising focal pancreatic lesions.
Best, Lawrence Mj; Rawji, Vishal; Pereira, Stephen P; Davidson, Brian R; Gurusamy, Kurinchi Selvan
2017-04-17
Increasing numbers of incidental pancreatic lesions are being detected each year. Accurate characterisation of pancreatic lesions into benign, precancerous, and cancer masses is crucial in deciding whether to use treatment or surveillance. Distinguishing benign lesions from precancerous and cancerous lesions can prevent patients from undergoing unnecessary major surgery. Despite the importance of accurately classifying pancreatic lesions, there is no clear algorithm for management of focal pancreatic lesions. To determine and compare the diagnostic accuracy of various imaging modalities in detecting cancerous and precancerous lesions in people with focal pancreatic lesions. We searched the CENTRAL, MEDLINE, Embase, and Science Citation Index until 19 July 2016. We searched the references of included studies to identify further studies. We did not restrict studies based on language or publication status, or whether data were collected prospectively or retrospectively. We planned to include studies reporting cross-sectional information on the index test (CT (computed tomography), MRI (magnetic resonance imaging), PET (positron emission tomography), EUS (endoscopic ultrasound), EUS elastography, and EUS-guided biopsy or FNA (fine-needle aspiration)) and reference standard (confirmation of the nature of the lesion was obtained by histopathological examination of the entire lesion by surgical excision, or histopathological examination for confirmation of precancer or cancer by biopsy and clinical follow-up of at least six months in people with negative index tests) in people with pancreatic lesions irrespective of language or publication status or whether the data were collected prospectively or retrospectively. Two review authors independently searched the references to identify relevant studies and extracted the data. We planned to use the bivariate analysis to calculate the summary sensitivity and specificity with their 95% confidence intervals and the hierarchical summary receiver operating characteristic (HSROC) to compare the tests and assess heterogeneity, but used simpler models (such as univariate random-effects model and univariate fixed-effect model) for combining studies when appropriate because of the sparse data. We were unable to compare the diagnostic performance of the tests using formal statistical methods because of sparse data. We included 54 studies involving a total of 3,196 participants evaluating the diagnostic accuracy of various index tests. In these 54 studies, eight different target conditions were identified with different final diagnoses constituting benign, precancerous, and cancerous lesions. None of the studies was of high methodological quality. None of the comparisons in which single studies were included was of sufficiently high methodological quality to warrant highlighting of the results. For differentiation of cancerous lesions from benign or precancerous lesions, we identified only one study per index test. The second analysis, of studies differentiating cancerous versus benign lesions, provided three tests in which meta-analysis could be performed. The sensitivities and specificities for diagnosing cancer were: EUS-FNA: sensitivity 0.79 (95% confidence interval (CI) 0.07 to 1.00), specificity 1.00 (95% CI 0.91 to 1.00); EUS: sensitivity 0.95 (95% CI 0.84 to 0.99), specificity 0.53 (95% CI 0.31 to 0.74); PET: sensitivity 0.92 (95% CI 0.80 to 0.97), specificity 0.65 (95% CI 0.39 to 0.84). The third analysis, of studies differentiating precancerous or cancerous lesions from benign lesions, only provided one test (EUS-FNA) in which meta-analysis was performed. EUS-FNA had moderate sensitivity for diagnosing precancerous or cancerous lesions (sensitivity 0.73 (95% CI 0.01 to 1.00) and high specificity 0.94 (95% CI 0.15 to 1.00), the extremely wide confidence intervals reflecting the heterogeneity between the studies). The fourth analysis, of studies differentiating cancerous (invasive carcinoma) from precancerous (dysplasia) provided three tests in which meta-analysis was performed. The sensitivities and specificities for diagnosing invasive carcinoma were: CT: sensitivity 0.72 (95% CI 0.50 to 0.87), specificity 0.92 (95% CI 0.81 to 0.97); EUS: sensitivity 0.78 (95% CI 0.44 to 0.94), specificity 0.91 (95% CI 0.61 to 0.98); EUS-FNA: sensitivity 0.66 (95% CI 0.03 to 0.99), specificity 0.92 (95% CI 0.73 to 0.98). The fifth analysis, of studies differentiating cancerous (high-grade dysplasia or invasive carcinoma) versus precancerous (low- or intermediate-grade dysplasia) provided six tests in which meta-analysis was performed. The sensitivities and specificities for diagnosing cancer (high-grade dysplasia or invasive carcinoma) were: CT: sensitivity 0.87 (95% CI 0.00 to 1.00), specificity 0.96 (95% CI 0.00 to 1.00); EUS: sensitivity 0.86 (95% CI 0.74 to 0.92), specificity 0.91 (95% CI 0.83 to 0.96); EUS-FNA: sensitivity 0.47 (95% CI 0.24 to 0.70), specificity 0.91 (95% CI 0.32 to 1.00); EUS-FNA carcinoembryonic antigen 200 ng/mL: sensitivity 0.58 (95% CI 0.28 to 0.83), specificity 0.51 (95% CI 0.19 to 0.81); MRI: sensitivity 0.69 (95% CI 0.44 to 0.86), specificity 0.93 (95% CI 0.43 to 1.00); PET: sensitivity 0.90 (95% CI 0.79 to 0.96), specificity 0.94 (95% CI 0.81 to 0.99). The sixth analysis, of studies differentiating cancerous (invasive carcinoma) from precancerous (low-grade dysplasia) provided no tests in which meta-analysis was performed. The seventh analysis, of studies differentiating precancerous or cancerous (intermediate- or high-grade dysplasia or invasive carcinoma) from precancerous (low-grade dysplasia) provided two tests in which meta-analysis was performed. The sensitivity and specificity for diagnosing cancer were: CT: sensitivity 0.83 (95% CI 0.68 to 0.92), specificity 0.83 (95% CI 0.64 to 0.93) and MRI: sensitivity 0.80 (95% CI 0.58 to 0.92), specificity 0.81 (95% CI 0.53 to 0.95), respectively. The eighth analysis, of studies differentiating precancerous or cancerous (intermediate- or high-grade dysplasia or invasive carcinoma) from precancerous (low-grade dysplasia) or benign lesions provided no test in which meta-analysis was performed.There were no major alterations in the subgroup analysis of cystic pancreatic focal lesions (42 studies; 2086 participants). None of the included studies evaluated EUS elastography or sequential testing. We were unable to arrive at any firm conclusions because of the differences in the way that study authors classified focal pancreatic lesions into cancerous, precancerous, and benign lesions; the inclusion of few studies with wide confidence intervals for each comparison; poor methodological quality in the studies; and heterogeneity in the estimates within comparisons.
NASA Astrophysics Data System (ADS)
Razavi, S.; Gupta, H. V.
2014-12-01
Sensitivity analysis (SA) is an important paradigm in the context of Earth System model development and application, and provides a powerful tool that serves several essential functions in modelling practice, including 1) Uncertainty Apportionment - attribution of total uncertainty to different uncertainty sources, 2) Assessment of Similarity - diagnostic testing and evaluation of similarities between the functioning of the model and the real system, 3) Factor and Model Reduction - identification of non-influential factors and/or insensitive components of model structure, and 4) Factor Interdependence - investigation of the nature and strength of interactions between the factors, and the degree to which factors intensify, cancel, or compensate for the effects of each other. A variety of sensitivity analysis approaches have been proposed, each of which formally characterizes a different "intuitive" understanding of what is meant by the "sensitivity" of one or more model responses to its dependent factors (such as model parameters or forcings). These approaches are based on different philosophies and theoretical definitions of sensitivity, and range from simple local derivatives and one-factor-at-a-time procedures to rigorous variance-based (Sobol-type) approaches. In general, each approach focuses on, and identifies, different features and properties of the model response and may therefore lead to different (even conflicting) conclusions about the underlying sensitivity. This presentation revisits the theoretical basis for sensitivity analysis, and critically evaluates existing approaches so as to demonstrate their flaws and shortcomings. With this background, we discuss several important properties of response surfaces that are associated with the understanding and interpretation of sensitivity. Finally, a new approach towards global sensitivity assessment is developed that is consistent with important properties of Earth System model response surfaces.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Chao Yang; Luo, Gang; Jiang, Fangming
2010-05-01
Current computational models for proton exchange membrane fuel cells (PEMFCs) include a large number of parameters such as boundary conditions, material properties, and numerous parameters used in sub-models for membrane transport, two-phase flow and electrochemistry. In order to successfully use a computational PEMFC model in design and optimization, it is important to identify critical parameters under a wide variety of operating conditions, such as relative humidity, current load, temperature, etc. Moreover, when experimental data is available in the form of polarization curves or local distribution of current and reactant/product species (e.g., O2, H2O concentrations), critical parameters can be estimated inmore » order to enable the model to better fit the data. Sensitivity analysis and parameter estimation are typically performed using manual adjustment of parameters, which is also common in parameter studies. We present work to demonstrate a systematic approach based on using a widely available toolkit developed at Sandia called DAKOTA that supports many kinds of design studies, such as sensitivity analysis as well as optimization and uncertainty quantification. In the present work, we couple a multidimensional PEMFC model (which is being developed, tested and later validated in a joint effort by a team from Penn State Univ. and Sandia National Laboratories) with DAKOTA through the mapping of model parameters to system responses. Using this interface, we demonstrate the efficiency of performing simple parameter studies as well as identifying critical parameters using sensitivity analysis. Finally, we show examples of optimization and parameter estimation using the automated capability in DAKOTA.« less
Choi, William; Tong, Xiuli; Cain, Kate
2016-08-01
This 1-year longitudinal study examined the role of Cantonese lexical tone sensitivity in predicting English reading comprehension and the pathways underlying their relation. Multiple measures of Cantonese lexical tone sensitivity, English lexical stress sensitivity, Cantonese segmental phonological awareness, general auditory sensitivity, English word reading, and English reading comprehension were administered to 133 Cantonese-English unbalanced bilingual second graders. Structural equation modeling analysis identified transfer of Cantonese lexical tone sensitivity to English reading comprehension. This transfer was realized through a direct pathway via English stress sensitivity and also an indirect pathway via English word reading. These results suggest that prosodic sensitivity is an important factor influencing English reading comprehension and that it needs to be incorporated into theoretical accounts of reading comprehension across languages. Copyright © 2016 Elsevier Inc. All rights reserved.
Hwyneeds : a sensitivity analysis
DOT National Transportation Integrated Search
2000-01-01
County highway needs identified in Iowa's Quadrennial Needs Study are used to determine the amount of funding allocated to each Iowa county for secondary highway improvements. The Iowa Department of Transportation uses a computer algorithm called HWY...
Fathiazar, Elham; Anemuller, Jorn; Kretzberg, Jutta
2016-08-01
Voltage-Sensitive Dye (VSD) imaging is an optical imaging method that allows measuring the graded voltage changes of multiple neurons simultaneously. In neuroscience, this method is used to reveal networks of neurons involved in certain tasks. However, the recorded relative dye fluorescence changes are usually low and signals are superimposed by noise and artifacts. Therefore, establishing a reliable method to identify which cells are activated by specific stimulus conditions is the first step to identify functional networks. In this paper, we present a statistical method to identify stimulus-activated network nodes as cells, whose activities during sensory network stimulation differ significantly from the un-stimulated control condition. This method is demonstrated based on voltage-sensitive dye recordings from up to 100 neurons in a ganglion of the medicinal leech responding to tactile skin stimulation. Without relying on any prior physiological knowledge, the network nodes identified by our statistical analysis were found to match well with published cell types involved in tactile stimulus processing and to be consistent across stimulus conditions and preparations.
Patient safety and systematic reviews: finding papers indexed in MEDLINE, EMBASE and CINAHL.
Tanon, A A; Champagne, F; Contandriopoulos, A-P; Pomey, M-P; Vadeboncoeur, A; Nguyen, H
2010-10-01
To develop search strategies for identifying papers on patient safety in MEDLINE, EMBASE and CINAHL. Six journals were electronically searched for papers on patient safety published between 2000 and 2006. Identified papers were divided into two gold standards: one to build and the other to validate the search strategies. Candidate terms for strategy construction were identified using a word frequency analysis of titles, abstracts and keywords used to index the papers in the databases. Searches were run for each one of the selected terms independently in every database. Sensitivity, precision and specificity were calculated for each candidate term. Terms with sensitivity greater than 10% were combined to form the final strategies. The search strategies developed were run against the validation gold standard to assess their performance. A final step in the validation process was to compare the performance of each strategy to those of other strategies found in the literature. We developed strategies for all three databases that were highly sensitive (range 95%-100%), precise (range 40%-60%) and balanced (the product of sensitivity and precision being in the range of 30%-40%). The strategies were very specific and outperformed those found in the literature. The strategies we developed can meet the needs of users aiming to maximise either sensitivity or precision, or seeking a reasonable compromise between sensitivity and precision, when searching for papers on patient safety in MEDLINE, EMBASE or CINAHL.
2010-01-01
Background Alzheimer's Disease (AD) affects a growing proportion of the population each year. Novel therapies on the horizon may slow the progress of AD symptoms and avoid cases altogether. Initiating treatment for the underlying pathology of AD would ideally be based on biomarker screening tools identifying pre-symptomatic individuals. Early-stage modeling provides estimates of potential outcomes and informs policy development. Methods A time-to-event (TTE) simulation provided estimates of screening asymptomatic patients in the general population age ≥55 and treatment impact on the number of patients reaching AD. Patients were followed from AD screen until all-cause death. Baseline sensitivity and specificity were 0.87 and 0.78, with treatment on positive screen. Treatment slowed progression by 50%. Events were scheduled using literature-based age-dependent incidences of AD and death. Results The base case results indicated increased AD free years (AD-FYs) through delays in onset and a reduction of 20 AD cases per 1000 screened individuals. Patients completely avoiding AD accounted for 61% of the incremental AD-FYs gained. Total years of treatment per 1000 screened patients was 2,611. The number-needed-to-screen was 51 and the number-needed-to-treat was 12 to avoid one case of AD. One-way sensitivity analysis indicated that duration of screening sensitivity and rescreen interval impact AD-FYs the most. A two-way sensitivity analysis found that for a test with an extended duration of sensitivity (15 years) the number of AD cases avoided was 6,000-7,000 cases for a test with higher sensitivity and specificity (0.90,0.90). Conclusions This study yielded valuable parameter range estimates at an early stage in the study of screening for AD. Analysis identified duration of screening sensitivity as a key variable that may be unavailable from clinical trials. PMID:20433705
Furiak, Nicolas M; Klein, Robert W; Kahle-Wrobleski, Kristin; Siemers, Eric R; Sarpong, Eric; Klein, Timothy M
2010-04-30
Alzheimer's Disease (AD) affects a growing proportion of the population each year. Novel therapies on the horizon may slow the progress of AD symptoms and avoid cases altogether. Initiating treatment for the underlying pathology of AD would ideally be based on biomarker screening tools identifying pre-symptomatic individuals. Early-stage modeling provides estimates of potential outcomes and informs policy development. A time-to-event (TTE) simulation provided estimates of screening asymptomatic patients in the general population age > or =55 and treatment impact on the number of patients reaching AD. Patients were followed from AD screen until all-cause death. Baseline sensitivity and specificity were 0.87 and 0.78, with treatment on positive screen. Treatment slowed progression by 50%. Events were scheduled using literature-based age-dependent incidences of AD and death. The base case results indicated increased AD free years (AD-FYs) through delays in onset and a reduction of 20 AD cases per 1000 screened individuals. Patients completely avoiding AD accounted for 61% of the incremental AD-FYs gained. Total years of treatment per 1000 screened patients was 2,611. The number-needed-to-screen was 51 and the number-needed-to-treat was 12 to avoid one case of AD. One-way sensitivity analysis indicated that duration of screening sensitivity and rescreen interval impact AD-FYs the most. A two-way sensitivity analysis found that for a test with an extended duration of sensitivity (15 years) the number of AD cases avoided was 6,000-7,000 cases for a test with higher sensitivity and specificity (0.90,0.90). This study yielded valuable parameter range estimates at an early stage in the study of screening for AD. Analysis identified duration of screening sensitivity as a key variable that may be unavailable from clinical trials.
Phase 1 of the automated array assembly task of the low cost silicon solar array project
NASA Technical Reports Server (NTRS)
Pryor, R. A.; Grenon, L. A.; Coleman, M. G.
1978-01-01
The results of a study of process variables and solar cell variables are presented. Interactions between variables and their effects upon control ranges of the variables are identified. The results of a cost analysis for manufacturing solar cells are discussed. The cost analysis includes a sensitivity analysis of a number of cost factors.
NASA Astrophysics Data System (ADS)
Razavi, S.; Gupta, H. V.
2015-12-01
Earth and environmental systems models (EESMs) are continually growing in complexity and dimensionality with continuous advances in understanding and computing power. Complexity and dimensionality are manifested by introducing many different factors in EESMs (i.e., model parameters, forcings, boundary conditions, etc.) to be identified. Sensitivity Analysis (SA) provides an essential means for characterizing the role and importance of such factors in producing the model responses. However, conventional approaches to SA suffer from (1) an ambiguous characterization of sensitivity, and (2) poor computational efficiency, particularly as the problem dimension grows. Here, we present a new and general sensitivity analysis framework (called VARS), based on an analogy to 'variogram analysis', that provides an intuitive and comprehensive characterization of sensitivity across the full spectrum of scales in the factor space. We prove, theoretically, that Morris (derivative-based) and Sobol (variance-based) methods and their extensions are limiting cases of VARS, and that their SA indices can be computed as by-products of the VARS framework. We also present a practical strategy for the application of VARS to real-world problems, called STAR-VARS, including a new sampling strategy, called "star-based sampling". Our results across several case studies show the STAR-VARS approach to provide reliable and stable assessments of "global" sensitivity across the full range of scales in the factor space, while being at least 1-2 orders of magnitude more efficient than the benchmark Morris and Sobol approaches.
Zhang, Jun-Feng; Xu, Yong-Qing; Dong, Jia-Min; Peng, Li-Na; Feng, Xu; Wang, Xu; Li, Fei; Miao, Yu; Yao, Shu-Kuan; Zhao, Qiao-Qin; Feng, Shan-Shan; Hu, Bao-Zhong
2018-01-01
Plant expansins are proteins involved in cell wall loosening, plant growth, and development, as well as in response to plant diseases and other stresses. In this study, we identified 128 expansin coding sequences from the wheat (Triticum aestivum) genome. These sequences belong to 45 homoeologous copies of TaEXPs, including 26 TaEXPAs, 15 TaEXPBs and four TaEXLAs. No TaEXLB was identified. Gene expression and sub-expression profiles revealed that most of the TaEXPs were expressed either only in root tissues or in multiple organs. Real-time qPCR analysis showed that many TaEXPs were differentially expressed in four different tissues of the two wheat cultivars—the cold-sensitive ‘Chinese Spring (CS)’ and the cold-tolerant ‘Dongnongdongmai 1 (D1)’ cultivars. Our results suggest that the differential expression of TaEXPs could be related to low-temperature tolerance or sensitivity of different wheat cultivars. Our study expands our knowledge on wheat expansins and sheds new light on the functions of expansins in plant development and stress response. PMID:29596529
Sensitivity of drainage efficiency of cranberry fields to edaphic conditions
NASA Astrophysics Data System (ADS)
Periard, Yann; José Gumiere, Silvio; Rousseau, Alain N.; Caron, Jean; Hallema, Dennis W.
2014-05-01
Water management on a cranberry farm requires intelligent irrigation and drainage strategies to sustain strong productivity and minimize environmental impact. For example, to avoid propagation of disease and meet evapotranspiration demand, it is imperative to maintain optimal moisture conditions in the root zone, which depends on an efficient drainage system. However, several drainage problems have been identified in cranberry fields. Most of these drainage problems are due to the presence of a restrictive layer in the soil profile (Gumiere et al., 2014). The objective of this work is to evaluate the effects of a restrictive layer on the drainage efficiency by the bias of a multi-local sensitivity analysis. We have tested the sensitivity of the drainage efficiency to different input parameters set of soil hydraulic properties, geometrical parameters and climatic conditions. Soil water flux dynamic for every input parameters set was simulated with finite element model Hydrus 1D (Simanek et al., 2008). Multi-local sensitivity was calculated with the Gâteaux directional derivatives with the procedure described by Cheviron et al. (2010). Results indicate that drainage efficiency is more sensitive to soil hydraulic properties than geometrical parameters and climatic conditions. Then, the geometrical parameters of the depth are more sensitive than the thickness. The drainage efficiency was very insensitive to the climatic conditions. Understanding the sensitivity of drainage efficiency according to soil hydraulic properties, geometrical and climatic conditions are essential for diagnosis drainage problems. However, it becomes important to identify the mechanisms involved in the genesis of anthropogenic soils cranberry to identify conditions that may lead to the formation of a restrictive layer. References: Cheviron, B., S.J. Gumiere, Y. Le Bissonnais, R. Moussa and D. Raclot. 2010. Sensitivity analysis of distributed erosion models: Framework. Water Resources Research 46: W08508. doi:10.1029/2009WR007950. Gumiere, S.J., J. Lafond, D. W. Hallema, Y. Périard, J. Caron et J. Gallichand. 2014. Mapping soil hydraulic conductivity and matric potential for water management of cranberry: Characterization and spatial interpolation methods. Biosystems Engineering.
Identification of stochastic interactions in nonlinear models of structural mechanics
NASA Astrophysics Data System (ADS)
Kala, Zdeněk
2017-07-01
In the paper, the polynomial approximation is presented by which the Sobol sensitivity analysis can be evaluated with all sensitivity indices. The nonlinear FEM model is approximated. The input area is mapped using simulations runs of Latin Hypercube Sampling method. The domain of the approximation polynomial is chosen so that it were possible to apply large number of simulation runs of Latin Hypercube Sampling method. The method presented also makes possible to evaluate higher-order sensitivity indices, which could not be identified in case of nonlinear FEM.
Uncertainty Analysis of the Grazing Flow Impedance Tube
NASA Technical Reports Server (NTRS)
Brown, Martha C.; Jones, Michael G.; Watson, Willie R.
2012-01-01
This paper outlines a methodology to identify the measurement uncertainty of NASA Langley s Grazing Flow Impedance Tube (GFIT) over its operating range, and to identify the parameters that most significantly contribute to the acoustic impedance prediction. Two acoustic liners are used for this study. The first is a single-layer, perforate-over-honeycomb liner that is nonlinear with respect to sound pressure level. The second consists of a wire-mesh facesheet and a honeycomb core, and is linear with respect to sound pressure level. These liners allow for evaluation of the effects of measurement uncertainty on impedances educed with linear and nonlinear liners. In general, the measurement uncertainty is observed to be larger for the nonlinear liners, with the largest uncertainty occurring near anti-resonance. A sensitivity analysis of the aerodynamic parameters (Mach number, static temperature, and static pressure) used in the impedance eduction process is also conducted using a Monte-Carlo approach. This sensitivity analysis demonstrates that the impedance eduction process is virtually insensitive to each of these parameters.
Sumner, T; Shephard, E; Bogle, I D L
2012-09-07
One of the main challenges in the development of mathematical and computational models of biological systems is the precise estimation of parameter values. Understanding the effects of uncertainties in parameter values on model behaviour is crucial to the successful use of these models. Global sensitivity analysis (SA) can be used to quantify the variability in model predictions resulting from the uncertainty in multiple parameters and to shed light on the biological mechanisms driving system behaviour. We present a new methodology for global SA in systems biology which is computationally efficient and can be used to identify the key parameters and their interactions which drive the dynamic behaviour of a complex biological model. The approach combines functional principal component analysis with established global SA techniques. The methodology is applied to a model of the insulin signalling pathway, defects of which are a major cause of type 2 diabetes and a number of key features of the system are identified.
Ohad, Shoshanit; Ben-Dor, Shifra; Prilusky, Jaime; Kravitz, Valeria; Dassa, Bareket; Chalifa-Caspi, Vered; Kashi, Yechezkel; Rorman, Efrat
2016-01-01
The emerging microbial source tracking (MST) methodologies aim to identify fecal contamination originating from domestic and wild animals, and from humans. Avian MST is especially challenging, primarily because the Aves class includes both domesticated and wild species with highly diverse habitats and dietary characteristics. The quest for specific fecal bacterial MST markers can be difficult with respect to attaining sufficient assay sensitivity and specificity. The present study utilizes high throughput sequencing (HTS) to screen bacterial 16S rRNA genes from fecal samples collected from both domestic and wild avian species. Operational taxonomic unit (OTU) analysis was then performed, from which sequences were retained for downstream quantitative polymerase chain reaction (qPCR) marker development. Identification of unique avian host DNA sequences, absent in non-avian hosts, was then carried out using a dedicated database of bacterial 16S rRNA gene taken from the Ribosomal Database Project. Six qPCR assays were developed targeting the 16S rRNA gene of Lactobacillus, Gallibacterium, Firmicutes, Fusobacteriaceae, and other bacteria. Two assays (Av4143 and Av163) identified most of the avian fecal samples and demonstrated sensitivity values of 91 and 70%, respectively. The Av43 assay only identified droppings from battery hens and poultry, whereas each of the other three assays (Av24, Av13, and Av216) identified waterfowl species with lower sensitivities values. The development of an MST assay-panel, which includes both domestic and wild avian species, expands the currently known MST analysis capabilities for decoding fecal contamination.
Stability and sensitivity of ABR flow control protocols
NASA Astrophysics Data System (ADS)
Tsai, Wie K.; Kim, Yuseok; Chiussi, Fabio; Toh, Chai-Keong
1998-10-01
This tutorial paper surveys the important issues in stability and sensitivity analysis of ABR flow control of ATM networks. THe stability and sensitivity issues are formulated in a systematic framework. Four main cause of instability in ABR flow control are identified: unstable control laws, temporal variations of available bandwidth with delayed feedback control, misbehaving components, and interactions between higher layer protocols and ABR flow control. Popular rate-based ABR flow control protocols are evaluated. Stability and sensitivity is shown to be the fundamental issues when the network has dynamically-varying bandwidth. Simulation result confirming the theoretical studies are provided. Open research problems are discussed.
Bouguerra, R; Alberti, H; Smida, H; Salem, L B; Rayana, C B; El Atti, J; Achour, A; Gaigi, S; Slama, C B; Zouari, B; Alberti, K G M M
2007-11-01
Waist circumference (WC) is a convenient measure of abdominal adipose tissue. It itself is a cardiovascular disease (CVD) and diabetes-risk factor and is strongly linked to other CVD risk factors. There are, however, ethnic differences in the relationship of WC to the other risk factors. The aim of this study was to determine the optimal cut-off points of WC and body mass index (BMI) at which cardiovascular risk factors can be identified with maximum sensitivity and specificity in a representative sample of the Tunisian adult population and to investigate any correlation between WC and BMI. We used a sample of the Tunisian National Nutrition Survey, a cross-sectional population-based survey, conducted in 1996 on a large nationally representative sample, which included 3435 adults (1244 men and 2191 women) of 20 years or older. WC, BMI, blood pressure and fasting blood measurements (plasma glucose, total cholesterol, triglycerides) were recorded. Receiver operating characteristic (ROC) curve analysis was used to identify optimal cut-off values of WC and BMI to identify with maximum sensitivity and specificity the detection of high blood pressure, hyperglycaemia, high blood cholesterol and hypertriglyceridaemia. ROC curve analysis suggested WC cut-off points of 85 cm in men and 85 cm in women for the optimum detection of high blood pressure, diabetes and dyslipidaemia. The optimum BMI cut-off points for predicting cardiovascular risk factors were 24 kg/m(2) in men and 27 kg/m(2) in women. The cut-off points recommended for the Caucasian population differ from those appropriate for the Tunisian population. The data show a continuous increase in odds ratios of each cardiovascular risk factor, with increasing level of WC and BMI. WC exceeding 85 cm in men and 79 cm in women correctly identified subjects with a BMI of >/=25 kg/m(2), sensitivity of >90% and specificity of >83%. Based on the ROC analysis, we suggest a WC of 85 cm for both men and women as appropriate cut-off points to identify central obesity for the purposes of CVD and diabetes-risk detection among Tunisians. WCs of 85 cm in men and 79 cm in women were the most sensitive and specific to identify most subjects with a BMI >/=25 kg/m(2).
Sensitivity analysis and nonlinearity assessment of steam cracking furnace process
NASA Astrophysics Data System (ADS)
Rosli, M. N.; Sudibyo, Aziz, N.
2017-11-01
In this paper, sensitivity analysis and nonlinearity assessment of cracking furnace process are presented. For the sensitivity analysis, the fractional factorial design method is employed as a method to analyze the effect of input parameters, which consist of four manipulated variables and two disturbance variables, to the output variables and to identify the interaction between each parameter. The result of the factorial design method is used as a screening method to reduce the number of parameters, and subsequently, reducing the complexity of the model. It shows that out of six input parameters, four parameters are significant. After the screening is completed, step test is performed on the significant input parameters to assess the degree of nonlinearity of the system. The result shows that the system is highly nonlinear with respect to changes in an air-to-fuel ratio (AFR) and feed composition.
Public Involvement Processes and Methodologies: An Analysis
Ernst Valfer; Stephen Laner; Daina Dravnieks
1977-01-01
This report explor'es some sensitive or critical areas in public involvement.. A 1972 RF&D workshop on public involvement identified a series of issues requiring research and analysis. A subsequent PNW study "Public Involvement and the Forest Service", (Hendee 1973) addressed many of these issues. This study assignment by the Chief's Office was...
Petrillo, Antonella; Fusco, Roberta; Petrillo, Mario; Granata, Vincenza; Delrio, Paolo; Bianco, Francesco; Pecori, Biagio; Botti, Gerardo; Tatangelo, Fabiana; Caracò, Corradina; Aloj, Luigi; Avallone, Antonio; Lastoria, Secondo
2017-01-01
Purpose To investigate dynamic contrast enhanced-MRI (DCE-MRI) in the preoperative chemo-radiotherapy (CRT) assessment for locally advanced rectal cancer (LARC) compared to18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT). Methods 75 consecutive patients with LARC were enrolled in a prospective study. DCE-MRI analysis was performed measuring SIS: linear combination of percentage change (Δ) of maximum signal difference (MSD) and wash-out slope (WOS). 18F-FDG PET/CT analysis was performed using SUV maximum (SUVmax). Tumor regression grade (TRG) were estimated after surgery. Non-parametric tests, receiver operating characteristic were evaluated. Results 55 patients (TRG1-2) were classified as responders while 20 subjects as non responders. ΔSIS reached sensitivity of 93%, specificity of 80% and accuracy of 89% (cut-off 6%) to differentiate responders by non responders, sensitivity of 93%, specificity of 69% and accuracy of 79% (cut-off 30%) to identify pathological complete response (pCR). Therapy assessment via ΔSUVmax reached sensitivity of 67%, specificity of 75% and accuracy of 70% (cut-off 60%) to differentiate responders by non responders and sensitivity of 80%, specificity of 31% and accuracy of 51% (cut-off 44%) to identify pCR. Conclusions CRT response assessment by DCE-MRI analysis shows a higher predictive ability than 18F-FDG PET/CT in LARC patients allowing to better discriminate significant and pCR. PMID:28042958
Petrillo, Antonella; Fusco, Roberta; Petrillo, Mario; Granata, Vincenza; Delrio, Paolo; Bianco, Francesco; Pecori, Biagio; Botti, Gerardo; Tatangelo, Fabiana; Caracò, Corradina; Aloj, Luigi; Avallone, Antonio; Lastoria, Secondo
2017-01-31
To investigate dynamic contrast enhanced-MRI (DCE-MRI) in the preoperative chemo-radiotherapy (CRT) assessment for locally advanced rectal cancer (LARC) compared to18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT). 75 consecutive patients with LARC were enrolled in a prospective study. DCE-MRI analysis was performed measuring SIS: linear combination of percentage change (Δ) of maximum signal difference (MSD) and wash-out slope (WOS). 18F-FDG PET/CT analysis was performed using SUV maximum (SUVmax). Tumor regression grade (TRG) were estimated after surgery. Non-parametric tests, receiver operating characteristic were evaluated. 55 patients (TRG1-2) were classified as responders while 20 subjects as non responders. ΔSIS reached sensitivity of 93%, specificity of 80% and accuracy of 89% (cut-off 6%) to differentiate responders by non responders, sensitivity of 93%, specificity of 69% and accuracy of 79% (cut-off 30%) to identify pathological complete response (pCR). Therapy assessment via ΔSUVmax reached sensitivity of 67%, specificity of 75% and accuracy of 70% (cut-off 60%) to differentiate responders by non responders and sensitivity of 80%, specificity of 31% and accuracy of 51% (cut-off 44%) to identify pCR. CRT response assessment by DCE-MRI analysis shows a higher predictive ability than 18F-FDG PET/CT in LARC patients allowing to better discriminate significant and pCR.
Yari, Shamsi; Hadizadeh Tasbiti, Alireza; Ghanei, Mostafa; Shokrgozar, Mohammad Ali; Fateh, Abolfazl; Mahdian, Reza; Yari, Fatemeh; Bahrmand, Ahmadreza
2017-01-01
Multidrug-resistant tuberculosis (MDR-TB) is a form of TB caused by Mycobacterium tuberculosis (M. tuberculosis) that do not respond to, at least, isoniazid and rifampicin, the two most powerful, first-line (or standard) anti-TB drugs. Novel intervention strategies for eliminating this disease were based on finding proteins that can be used for designing new drugs or new and reliable kits for diagnosis. The aim of this study was to compare the protein profiles of MDR-TB with sensitive isolates. Proteomic analysis of M. tuberculosis MDR-TB and sensitive isolates was obtained with ion exchange chromatography coupled with MALDI-TOF-TOF (matrix-assisted laser desorption/ionization) in order to identify individual proteins that have different expression in MDR-TB to be used as a drug target or diagnostic marker for designing valuable TB vaccines or TB rapid tests. We identified eight proteins in MDR-TB isolates, and analyses showed that these proteins are absent in M. tuberculosis-sensitive isolates: (Rv2140c, Rv0009, Rv1932, Rv0251c, Rv2558, Rv1284, Rv3699 and MMP major membrane proteins). These data will provide valuable clues in further investigation for suitable TB rapid tests or drug targets against drug-resistant and sensitive M. tuberculosis isolates.
Sensitivity and specificity of dosing alerts for dosing errors among hospitalized pediatric patients
Stultz, Jeremy S; Porter, Kyle; Nahata, Milap C
2014-01-01
Objectives To determine the sensitivity and specificity of a dosing alert system for dosing errors and to compare the sensitivity of a proprietary system with and without institutional customization at a pediatric hospital. Methods A retrospective analysis of medication orders, orders causing dosing alerts, reported adverse drug events, and dosing errors during July, 2011 was conducted. Dosing errors with and without alerts were identified and the sensitivity of the system with and without customization was compared. Results There were 47 181 inpatient pediatric orders during the studied period; 257 dosing errors were identified (0.54%). The sensitivity of the system for identifying dosing errors was 54.1% (95% CI 47.8% to 60.3%) if customization had not occurred and increased to 60.3% (CI 54.0% to 66.3%) with customization (p=0.02). The sensitivity of the system for underdoses was 49.6% without customization and 60.3% with customization (p=0.01). Specificity of the customized system for dosing errors was 96.2% (CI 96.0% to 96.3%) with a positive predictive value of 8.0% (CI 6.8% to 9.3). All dosing errors had an alert over-ridden by the prescriber and 40.6% of dosing errors with alerts were administered to the patient. The lack of indication-specific dose ranges was the most common reason why an alert did not occur for a dosing error. Discussion Advances in dosing alert systems should aim to improve the sensitivity and positive predictive value of the system for dosing errors. Conclusions The dosing alert system had a low sensitivity and positive predictive value for dosing errors, but might have prevented dosing errors from reaching patients. Customization increased the sensitivity of the system for dosing errors. PMID:24496386
A metabolomics approach to the identification of biomarkers of sugar-sweetened beverage intake.
Gibbons, Helena; McNulty, Breige A; Nugent, Anne P; Walton, Janette; Flynn, Albert; Gibney, Michael J; Brennan, Lorraine
2015-03-01
The association between sugar-sweetened beverages (SSBs) and health risks remains controversial. To clarify proposed links, reliable and accurate dietary assessment methods of food intakes are essential. The aim of this present work was to use a metabolomics approach to identify a panel of urinary biomarkers indicative of SSB consumption from a national food consumption survey and subsequently validate this panel in an acute intervention study. Heat map analysis was performed to identify correlations between ¹H nuclear magnetic resonance (NMR) spectral regions and SSB intakes in participants of the National Adult Nutrition Survey (n = 565). Metabolites were identified and receiver operating characteristic (ROC) analysis was performed to assess sensitivity and specificity of biomarkers. The panel of biomarkers was validated in an acute study (n = 10). A fasting first-void urine sample and postprandial samples (2, 4, 6 h) were collected after SSB consumption. After NMR spectroscopic profiling of the urine samples, multivariate data analysis was applied. A panel of 4 biomarkers-formate, citrulline, taurine, and isocitrate-were identified as markers of SSB intake. This panel of biomarkers had an area under the curve of 0.8 for ROC analysis and a sensitivity and specificity of 0.7 and 0.8, respectively. All 4 biomarkers were identified in the SSB sample. After acute consumption of an SSB drink, all 4 metabolites increased in the urine. The present metabolomics-based strategy proved to be successful in the identification of SSB biomarkers. Future work will ascertain how to translate this panel of markers for use in nutrition epidemiology. © 2015 American Society for Nutrition.
Monoallelic mutation analysis (MAMA) for identifying germline mutations.
Papadopoulos, N; Leach, F S; Kinzler, K W; Vogelstein, B
1995-09-01
Dissection of germline mutations in a sensitive and specific manner presents a continuing challenge. In dominantly inherited diseases, mutations occur in only one allele and are often masked by the normal allele. Here we report the development of a sensitive and specific diagnostic strategy based on somatic cell hybridization termed MAMA (monoallelic mutation analysis). We have demonstrated the utility of this strategy in two different hereditary colorectal cancer syndromes, one caused by a defective tumour suppressor gene on chromosome 5 (familial adenomatous polyposis, FAP) and the other caused by a defective mismatch repair gene on chromosome 2 (hereditary non-polyposis colorectal cancer, HNPCC).
Trame, MN; Lesko, LJ
2015-01-01
A systems pharmacology model typically integrates pharmacokinetic, biochemical network, and systems biology concepts into a unifying approach. It typically consists of a large number of parameters and reaction species that are interlinked based upon the underlying (patho)physiology and the mechanism of drug action. The more complex these models are, the greater the challenge of reliably identifying and estimating respective model parameters. Global sensitivity analysis provides an innovative tool that can meet this challenge. CPT Pharmacometrics Syst. Pharmacol. (2015) 4, 69–79; doi:10.1002/psp4.6; published online 25 February 2015 PMID:27548289
Biomarkers identified by urinary metabonomics for noninvasive diagnosis of nutritional rickets.
Wang, Maoqing; Yang, Xue; Ren, Lihong; Li, Songtao; He, Xuan; Wu, Xiaoyan; Liu, Tingting; Lin, Liqun; Li, Ying; Sun, Changhao
2014-09-05
Nutritional rickets is a worldwide public health problem; however, the current diagnostic methods retain shortcomings for accurate diagnosis of nutritional rickets. To identify urinary biomarkers associated with nutritional rickets and establish a noninvasive diagnosis method, urinary metabonomics analysis by ultra-performance liquid chromatography/quadrupole time-of-flight tandem mass spectrometry and multivariate statistical analysis were employed to investigate the metabolic alterations associated with nutritional rickets in 200 children with or without nutritional rickets. The pathophysiological changes and pathogenesis of nutritional rickets were illustrated by the identified biomarkers. By urinary metabolic profiling, 31 biomarkers of nutritional rickets were identified and five candidate biomarkers for clinical diagnosis were screened and identified by quantitative analysis and receiver operating curve analysis. Urinary levels of five candidate biomarkers were measured using mass spectrometry or commercial kits. In the validation step, the combination of phosphate and sebacic acid was able to give a noninvasive and accurate diagnostic with high sensitivity (94.0%) and specificity (71.2%). Furthermore, on the basis of the pathway analysis of biomarkers, our urinary metabonomics analysis gives new insight into the pathogenesis and pathophysiology of nutritional rickets.
Loewenthal, Kate Miriam; Rogers, Marian Brooke
2004-09-01
There is political and scientific goodwill towards the provision of culture-sensitive support, but as yet little knowledge about how such support works and what are its strengths and difficulties in practice. To study groups offering culture-sensitive psychological and other support to the strictly orthodox Jewish community in London. Semi-structured interviews with service providers, potential and actual users from the community, and professionals serving the community. Interviews asked about the aims, functioning and achievements of 10 support groups. Thematic analysis identified seven important themes: admiration for the work of the groups; appreciation of the benefits of culture-sensitive services; concerns over confidentiality and stigma; concerns over finance and fund-raising; concerns about professionalism; the importance of liaison with rabbinic authorities; need for better dissemination of information. The strengths and difficulties of providing culture-sensitive services in one community were identified. Areas for attention include vigilance regarding confidentiality, improvements in disseminating information, improvements in the reliability of funding and attention to systematic needs assessment, and to the examination of efficacy of these forms of service provision.
Implementation Strategies for Gender-Sensitive Public Health Practice: A European Workshop.
Oertelt-Prigione, Sabine; Dalibert, Lucie; Verdonk, Petra; Stutz, Elisabeth Zemp; Klinge, Ineke
2017-11-01
Providing a robust scientific background for the focus on gender-sensitive public health and a systematic approach to its implementation. Within the FP7-EUGenMed project ( http://eugenmed.eu ) a workshop on sex and gender in public health was convened on February 2-3, 2015. The experts participated in moderated discussion rounds to (1) assemble available knowledge and (2) identify structural influences on practice implementation. The findings were summarized and analyzed in iterative rounds to define overarching strategies and principles. The participants discussed the rationale for implementing gender-sensitive public health and identified priorities and key stakeholders to engage in the process. Communication strategies and specific promotion strategies with distinct stakeholders were defined. A comprehensive list of gender-sensitive practices was established using the recently published taxonomy of the Expert Recommendations for Implementing Change (ERIC) project as a blueprint. A clearly defined implementation strategy should be mandated for all new projects in the field of gender-sensitive public health. Our tool can support researchers and practitioners with the analysis of current and past research as well as with the planning of new projects.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sung, Yixing; Adams, Brian M.; Secker, Jeffrey R.
2011-12-01
The CASL Level 1 Milestone CASL.P4.01, successfully completed in December 2011, aimed to 'conduct, using methodologies integrated into VERA, a detailed sensitivity analysis and uncertainty quantification of a crud-relevant problem with baseline VERA capabilities (ANC/VIPRE-W/BOA).' The VUQ focus area led this effort, in partnership with AMA, and with support from VRI. DAKOTA was coupled to existing VIPRE-W thermal-hydraulics and BOA crud/boron deposit simulations representing a pressurized water reactor (PWR) that previously experienced crud-induced power shift (CIPS). This work supports understanding of CIPS by exploring the sensitivity and uncertainty in BOA outputs with respect to uncertain operating and model parameters. Thismore » report summarizes work coupling the software tools, characterizing uncertainties, and analyzing the results of iterative sensitivity and uncertainty studies. These studies focused on sensitivity and uncertainty of CIPS indicators calculated by the current version of the BOA code used in the industry. Challenges with this kind of analysis are identified to inform follow-on research goals and VERA development targeting crud-related challenge problems.« less
Aiba, Toshiki; Saito, Toshiyuki; Hayashi, Akiko; Sato, Shinji; Yunokawa, Harunobu; Maruyama, Toru; Fujibuchi, Wataru; Kurita, Hisaka; Tohyama, Chiharu; Ohsako, Seiichiroh
2017-03-09
It has been pointed out that environmental factors or chemicals can cause diseases that are developmental in origin. To detect abnormal epigenetic alterations in DNA methylation, convenient and cost-effective methods are required for such research, in which multiple samples are processed simultaneously. We here present methylated site display (MSD), a unique technique for the preparation of DNA libraries. By combining it with amplified fragment length polymorphism (AFLP) analysis, we developed a new method, MSD-AFLP. Methylated site display libraries consist of only DNAs derived from DNA fragments that are CpG methylated at the 5' end in the original genomic DNA sample. To test the effectiveness of this method, CpG methylation levels in liver, kidney, and hippocampal tissues of mice were compared to examine if MSD-AFLP can detect subtle differences in the levels of tissue-specific differentially methylated CpGs. As a result, many CpG sites suspected to be tissue-specific differentially methylated were detected. Nucleotide sequences adjacent to these methyl-CpG sites were identified and we determined the methylation level by methylation-sensitive restriction endonuclease (MSRE)-PCR analysis to confirm the accuracy of AFLP analysis. The differences of the methylation level among tissues were almost identical among these methods. By MSD-AFLP analysis, we detected many CpGs showing less than 5% statistically significant tissue-specific difference and less than 10% degree of variability. Additionally, MSD-AFLP analysis could be used to identify CpG methylation sites in other organisms including humans. MSD-AFLP analysis can potentially be used to measure slight changes in CpG methylation level. Regarding the remarkable precision, sensitivity, and throughput of MSD-AFLP analysis studies, this method will be advantageous in a variety of epigenetics-based research.
Verkest, K R; Fleeman, L M; Morton, J M; Ishioka, K; Rand, J S
2011-07-01
The hormonal mediators of obesity-induced insulin resistance and compensatory hyperinsulinemia in dogs have not been identified. Plasma samples were obtained after a 24-h fast from 104 client-owned lean, overweight, and obese dogs. Plasma glucose and insulin concentrations were used to calculate insulin sensitivity and β-cell function with the use of the homeostasis model assessment (HOMA(insulin sensitivity) and HOMA(β-cell function), respectively). Path analysis with multivariable linear regression was used to identify whether fasting plasma leptin, adiponectin, or glucagon-like peptide-1 concentrations were associated with adiposity, insulin sensitivity, and basal insulin secretion. None of the dogs were hyperglycemic. In the final path model, adiposity was positively associated with leptin (P < 0.01) and glucagon-like peptide-1 (P = 0.04) concentrations. No significant total effect of adiposity on adiponectin in dogs (P = 0.24) was observed. If there is a direct effect of leptin on adiponectin, then our results indicate that this is a positive relationship, which at least partly counters a negative direct relationship between adiposity and adiponectin. Fasting plasma leptin concentration was directly negatively associated with fasting insulin sensitivity (P = 0.01) and positively associated with β-cell function (P < 0.01), but no direct association was observed between adiponectin concentration and either insulin sensitivity or β-cell function (P = 0.42 and 0.11, respectively). We conclude that dogs compensate effectively for obesity-induced insulin resistance. Fasting plasma leptin concentrations appear to be associated with obesity-associated changes in insulin sensitivity and compensatory hyperinsulinemia in naturally occurring obese dogs. Adiponectin does not appear to be involved in the pathophysiology of obesity-associated changes in insulin sensitivity. Copyright © 2011 Elsevier Inc. All rights reserved.
Kuwano, Noriko; Fukuda, Hiromi; Murashima, Sachiyo
2016-11-01
The study aimed to analyze the professional autonomy of Japanese nurses when caring for non-Japanese patients and to identify its contributing factors. A descriptive cross-sectional design was used. Participants included 238 clinical nurses working at 27 hospitals in Japan. The Intercultural Sensitivity Scale (Chen and Starosta), and the Scale for Professional Autonomy in Nursing (Kikuchi and Harada) were used to measure intercultural sensitivity and professional autonomy. Stepwise multiple regression analysis was used to identify the most significant factors affecting professional autonomy. Professional autonomy of Japanese nurses caring for non-Japanese patients was significantly lower than when caring for Japanese patients (142.84 vs. 172.85; p < .001). Contributing factors were intercultural sensitivity (p < .001), length of nurse experience (p < .05), and availability of interpretation service (p < .05). Incorporating transcultural nursing content into training programs in schools and hospitals could enhance professional autonomy of Japanese nurses by promoting intercultural sensitivity. © The Author(s) 2015.
Ocular findings associated with a Cys39Arg mutation in the Norrie disease gene.
Joos, K M; Kimura, A E; Vandenburgh, K; Bartley, J A; Stone, E M
1994-12-01
To diagnose the carriers and noncarriers in a family affected with Norrie disease based on molecular analysis. Family members from three generations, including one affected patient, two obligate carriers, one carrier identified with linkage analysis, one noncarrier identified with linkage analysis, and one female family member with indeterminate carrier status, were examined clinically and electrophysiologically. Linkage analysis had previously failed to determine the carrier status of one female family member in the third generation. Blood samples were screened for mutations in the Norrie disease gene with single-strand conformation polymorphism analysis. The mutation was characterized by dideoxy-termination sequencing. Ophthalmoscopy and electroretinographic examination failed to detect the carrier state. The affected individuals and carriers in this family were found to have a transition from thymidine to cytosine in the first nucleotide of codon 39 of the Norrie disease gene, causing a cysteine-to-arginine mutation. Single-strand conformation polymorphism analysis identified a patient of indeterminate status (by linkage) to be a noncarrier of Norrie disease. Ophthalmoscopy and electroretinography could not identify carriers of this Norrie disease mutation. Single-strand conformation polymorphism analysis was more sensitive and specific than linkage analysis in identifying carriers in this family.
Rastogi, S C; Lepoittevin, J P; Johansen, J D; Frosch, P J; Menné, T; Bruze, M; Dreier, B; Andersen, K E; White, I R
1998-12-01
Deodorants are one of the most frequently-used types of cosmetics and are a source of allergic contact dermatitis. Therefore, a gas chromatography - mass spectrometric analysis of 71 deodorants was performed for identification of fragrance and non-fragrance materials present in marketed deodorants. Futhermore, the sensitizing potential of these molecules was evaluated using structure activity relationships (SARs) analysis. This was based on the presence of 1 or more chemically reactive site(s), in the chemical structure, associated with sensitizing potential. Among the many different substances used to formulate cosmetic products (over 3500), 226 chemicals were identified in a sample of 71 deodorants. 84 molecules were found to contain at least 1 structural alert, and 70 to belong to, or be susceptible to being metabolized into, the chemical group of aldehydes, ketones and alpha,beta-unsaturated aldehydes, ketone or esters. The combination of GC-MS and SARs analysis could be helpful in the selection of substances for supplementary investigations regarding sensitizing properties. Thus, it may be a valuable tool in the management of contact allergy to deodorants and for producing new deodorants with decreased propensity to cause contact allergy.
An easily implemented static condensation method for structural sensitivity analysis
NASA Technical Reports Server (NTRS)
Gangadharan, S. N.; Haftka, R. T.; Nikolaidis, E.
1990-01-01
A black-box approach to static condensation for sensitivity analysis is presented with illustrative examples of a cube and a car structure. The sensitivity of the structural response with respect to joint stiffness parameter is calculated using the direct method, forward-difference, and central-difference schemes. The efficiency of the various methods for identifying joint stiffness parameters from measured static deflections of these structures is compared. The results indicate that the use of static condensation can reduce computation times significantly and the black-box approach is only slightly less efficient than the standard implementation of static condensation. The ease of implementation of the black-box approach recommends it for use with general-purpose finite element codes that do not have a built-in facility for static condensation.
Oshone, Rediet; Ngom, Mariama; Chu, Feixia; Mansour, Samira; Sy, Mame Ourèye; Champion, Antony; Tisa, Louis S
2017-08-18
Soil salinization is a worldwide problem that is intensifying because of the effects of climate change. An effective method for the reclamation of salt-affected soils involves initiating plant succession using fast growing, nitrogen fixing actinorhizal trees such as the Casuarina. The salt tolerance of Casuarina is enhanced by the nitrogen-fixing symbiosis that they form with the actinobacterium Frankia. Identification and molecular characterization of salt-tolerant Casuarina species and associated Frankia is imperative for the successful utilization of Casuarina trees in saline soil reclamation efforts. In this study, salt-tolerant and salt-sensitive Casuarina associated Frankia strains were identified and comparative genomics, transcriptome profiling, and proteomics were employed to elucidate the molecular mechanisms of salt and osmotic stress tolerance. Salt-tolerant Frankia strains (CcI6 and Allo2) that could withstand up to 1000 mM NaCl and a salt-sensitive Frankia strain (CcI3) which could withstand only up to 475 mM NaCl were identified. The remaining isolates had intermediate levels of salt tolerance with MIC values ranging from 650 mM to 750 mM. Comparative genomic analysis showed that all of the Frankia isolates from Casuarina belonged to the same species (Frankia casuarinae). Pangenome analysis revealed a high abundance of singletons among all Casuarina isolates. The two salt-tolerant strains contained 153 shared single copy genes (most of which code for hypothetical proteins) that were not found in the salt-sensitive(CcI3) and moderately salt-tolerant (CeD) strains. RNA-seq analysis of one of the two salt-tolerant strains (Frankia sp. strain CcI6) revealed hundreds of genes differentially expressed under salt and/or osmotic stress. Among the 153 genes, 7 and 7 were responsive to salt and osmotic stress, respectively. Proteomic profiling confirmed the transcriptome results and identified 19 and 8 salt and/or osmotic stress-responsive proteins in the salt-tolerant (CcI6) and the salt-sensitive (CcI3) strains, respectively. Genetic differences between salt-tolerant and salt-sensitive Frankia strains isolated from Casuarina were identified. Transcriptome and proteome profiling of a salt-tolerant strain was used to determine molecular differences correlated with differential salt-tolerance and several candidate genes were identified. Mechanisms involving transcriptional and translational regulation, cell envelop remodeling, and previously uncharacterized proteins appear to be important for salt tolerance. Physiological and mutational analyses will further shed light on the molecular mechanism of salt tolerance in Casuarina associated Frankia isolates.
The Objective Identification and Quantification of Interstitial Lung Abnormalities in Smokers.
Ash, Samuel Y; Harmouche, Rola; Ross, James C; Diaz, Alejandro A; Hunninghake, Gary M; Putman, Rachel K; Onieva, Jorge; Martinez, Fernando J; Choi, Augustine M; Lynch, David A; Hatabu, Hiroto; Rosas, Ivan O; Estepar, Raul San Jose; Washko, George R
2017-08-01
Previous investigation suggests that visually detected interstitial changes in the lung parenchyma of smokers are highly clinically relevant and predict outcomes, including death. Visual subjective analysis to detect these changes is time-consuming, insensitive to subtle changes, and requires training to enhance reproducibility. Objective detection of such changes could provide a method of disease identification without these limitations. The goal of this study was to develop and test a fully automated image processing tool to objectively identify radiographic features associated with interstitial abnormalities in the computed tomography scans of a large cohort of smokers. An automated tool that uses local histogram analysis combined with distance from the pleural surface was used to detect radiographic features consistent with interstitial lung abnormalities in computed tomography scans from 2257 individuals from the Genetic Epidemiology of COPD study, a longitudinal observational study of smokers. The sensitivity and specificity of this tool was determined based on its ability to detect the visually identified presence of these abnormalities. The tool had a sensitivity of 87.8% and a specificity of 57.5% for the detection of interstitial lung abnormalities, with a c-statistic of 0.82, and was 100% sensitive and 56.7% specific for the detection of the visual subtype of interstitial abnormalities called fibrotic parenchymal abnormalities, with a c-statistic of 0.89. In smokers, a fully automated image processing tool is able to identify those individuals who have interstitial lung abnormalities with moderate sensitivity and specificity. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
El Allaki, Farouk; Harrington, Noel; Howden, Krista
2016-11-01
The objectives of this study were (1) to estimate the annual sensitivity of Canada's bTB surveillance system and its three system components (slaughter surveillance, export testing and disease investigation) using a scenario tree modelling approach, and (2) to identify key model parameters that influence the estimates of the surveillance system sensitivity (SSSe). To achieve these objectives, we designed stochastic scenario tree models for three surveillance system components included in the analysis. Demographic data, slaughter data, export testing data, and disease investigation data from 2009 to 2013 were extracted for input into the scenario trees. Sensitivity analysis was conducted to identify key influential parameters on SSSe estimates. The median annual SSSe estimates generated from the study were very high, ranging from 0.95 (95% probability interval [PI]: 0.88-0.98) to 0.97 (95% PI: 0.93-0.99). Median annual sensitivity estimates for the slaughter surveillance component ranged from 0.95 (95% PI: 0.88-0.98) to 0.97 (95% PI: 0.93-0.99). This shows that slaughter surveillance to be the major contributor to overall surveillance system sensitivity with a high probability to detect M. bovis infection if present at a prevalence of 0.00028% or greater during the study period. The export testing and disease investigation components had extremely low component sensitivity estimates-the maximum median sensitivity estimates were 0.02 (95% PI: 0.014-0.023) and 0.0061 (95% PI: 0.0056-0.0066) respectively. The three most influential input parameters on the model's output (SSSe) were the probability of a granuloma being detected at slaughter inspection, the probability of a granuloma being present in older animals (≥12 months of age), and the probability of a granuloma sample being submitted to the laboratory. Additional studies are required to reduce the levels of uncertainty and variability associated with these three parameters influencing the surveillance system sensitivity. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.
Gray, Ewan; Donten, Anna; Karssemeijer, Nico; van Gils, Carla; Evans, D Gareth; Astley, Sue; Payne, Katherine
2017-09-01
To identify the incremental costs and consequences of stratified national breast screening programs (stratified NBSPs) and drivers of relative cost-effectiveness. A decision-analytic model (discrete event simulation) was conceptualized to represent four stratified NBSPs (risk 1, risk 2, masking [supplemental screening for women with higher breast density], and masking and risk 1) compared with the current UK NBSP and no screening. The model assumed a lifetime horizon, the health service perspective to identify costs (£, 2015), and measured consequences in quality-adjusted life-years (QALYs). Multiple data sources were used: systematic reviews of effectiveness and utility, published studies reporting costs, and cohort studies embedded in existing NBSPs. Model parameter uncertainty was assessed using probabilistic sensitivity analysis and one-way sensitivity analysis. The base-case analysis, supported by probabilistic sensitivity analysis, suggested that the risk stratified NBSPs (risk 1 and risk-2) were relatively cost-effective when compared with the current UK NBSP, with incremental cost-effectiveness ratios of £16,689 per QALY and £23,924 per QALY, respectively. Stratified NBSP including masking approaches (supplemental screening for women with higher breast density) was not a cost-effective alternative, with incremental cost-effectiveness ratios of £212,947 per QALY (masking) and £75,254 per QALY (risk 1 and masking). When compared with no screening, all stratified NBSPs could be considered cost-effective. Key drivers of cost-effectiveness were discount rate, natural history model parameters, mammographic sensitivity, and biopsy rates for recalled cases. A key assumption was that the risk model used in the stratification process was perfectly calibrated to the population. This early model-based cost-effectiveness analysis provides indicative evidence for decision makers to understand the key drivers of costs and QALYs for exemplar stratified NBSP. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Miao, Jing-Kun; Chen, Qi-Xiong; Bao, Li-Ming; Huang, Yi; Zhang, Juan; Wan, Ke-Xing; Yi, Jing; Wang, Shi-Yi; Zou, Lin; Li, Ting-Yu
2013-09-23
Conventional screening tests to assess G6PD deficiency use a low cutoff value of 2.10 U/gHb which may not be adequate for detecting females with heterozygous deficiency. The aim of present study was to determine an appropriate cutoff value with increased sensitivity in identifying G6PD-deficient heterozygous females. G6PD activity analysis was performed on 51,747 neonates using semi-quantitative fluorescent spot test. Neonates suspected with G6PD deficiency were further analyzed using quantitatively enzymatic assay and for common G6PD mutations. The cutoff values of G6PD activity were estimated using the receiver operating characteristic curve. Our results demonstrated that using 2.10 U/g Hb as a cutoff, the sensitivity of the assay to detect female neonates with G6PD heterozygous deficiency was 83.3%, as compared with 97.6% using 2.55 U/g Hb as a cutoff. The high cutoff identified 21% (8/38) of the female neonates with partial G6PD deficiency which were not detected with 2.10 U/g Hb. Our study found that high cutoffs, 2.35 and 2.55 U/g Hb, would increase assay's sensitivity to identify male and female G6PD deficiency neonates, respectively. We established a reliable cutoff value of G6PD activity with increased sensitivity in identifying female newborns with partial G6PD deficiency. Copyright © 2013 Elsevier B.V. All rights reserved.
Fong, Zhi Ven; Loehrer, Andrew P; Castillo, Carlos Fernández-del; Bababekov, Yanik J; Jin, Ginger; Ferrone, Cristina R; Warshaw, Andrew L; Traeger, Lara N; Hutter, Matthew M; Lillemoe, Keith D; Chang, David C
2018-01-01
Background A minimum-volume policy restricting hospitals not meeting the threshold from performing complex surgery may increase travel burden and decrease spatial access to surgery. We aim to identify vulnerable populations that would be sensitive to an added travel burden. Methods We performed a retrospective analysis of the California Office of Statewide Health Planning and Development database for patients undergoing pancreatectomy from 2005 to 2014. Number of hospitals bypassed was used as a metric for travel. Patients bypassing fewer hospitals were deemed to be more sensitive to an added travel burden. Results There were 13,374 patients who underwent a pancreatectomy, of which 2,368 (17.7%) were non-bypassers. On unadjusted analysis, patients >80 year old travelled less than their younger counterparts, bypassing a mean of 10.9 ± 9.5 hospitals compared to 14.2 ± 21.3 hospitals bypassed by the 35–49 year old age group (p<0.001). Racial minorities travelled less when compared to Non-Hispanic Whites (p<0.001). Patients identifying their payer status as self-pay (8.9 ± 15.6 hospitals bypassed) and Medicaid (10.1 ± 17.2 hospitals bypassed) also travelled less when compared to patients with private insurance (13.8 ± 20.4 hospitals bypassed, p<0.001). On multivariate analysis, advanced age, racial minority and patients with self-pay or Medicaid payer status were independently associated with increased sensitivity to an added travel burden. Conclusion In patients undergoing pancreatectomy, the elderly, racial minorities and patients with self-pay or Medicaid payer status were associated with an increased sensitivity to an added travel burden. This vulnerable cohort may be disproportionately affected by a minimum-volume policy. PMID:28504112
Sensitivity Analysis of the Integrated Medical Model for ISS Programs
NASA Technical Reports Server (NTRS)
Goodenow, D. A.; Myers, J. G.; Arellano, J.; Boley, L.; Garcia, Y.; Saile, L.; Walton, M.; Kerstman, E.; Reyes, D.; Young, M.
2016-01-01
Sensitivity analysis estimates the relative contribution of the uncertainty in input values to the uncertainty of model outputs. Partial Rank Correlation Coefficient (PRCC) and Standardized Rank Regression Coefficient (SRRC) are methods of conducting sensitivity analysis on nonlinear simulation models like the Integrated Medical Model (IMM). The PRCC method estimates the sensitivity using partial correlation of the ranks of the generated input values to each generated output value. The partial part is so named because adjustments are made for the linear effects of all the other input values in the calculation of correlation between a particular input and each output. In SRRC, standardized regression-based coefficients measure the sensitivity of each input, adjusted for all the other inputs, on each output. Because the relative ranking of each of the inputs and outputs is used, as opposed to the values themselves, both methods accommodate the nonlinear relationship of the underlying model. As part of the IMM v4.0 validation study, simulations are available that predict 33 person-missions on ISS and 111 person-missions on STS. These simulated data predictions feed the sensitivity analysis procedures. The inputs to the sensitivity procedures include the number occurrences of each of the one hundred IMM medical conditions generated over the simulations and the associated IMM outputs: total quality time lost (QTL), number of evacuations (EVAC), and number of loss of crew lives (LOCL). The IMM team will report the results of using PRCC and SRRC on IMM v4.0 predictions of the ISS and STS missions created as part of the external validation study. Tornado plots will assist in the visualization of the condition-related input sensitivities to each of the main outcomes. The outcomes of this sensitivity analysis will drive review focus by identifying conditions where changes in uncertainty could drive changes in overall model output uncertainty. These efforts are an integral part of the overall verification, validation, and credibility review of IMM v4.0.
Kang, Jung Julie; Reiter, Robert; Steinberg, Michael; King, Christopher R.
2015-01-01
PURPOSE Integrating ultra-sensitive PSA (uPSA) into surveillance of high-risk patients following radical prostatectomy (RP) potentially optimizes management by correctly identifying actual recurrences, promoting an early salvage strategy and minimizing overtreatment. The power of uPSA following surgery to identify eventual biochemical failures is tested. PATIENTS AND METHODS From 1991–2013, 247 high-risk patients with a median follow-up was 44 months after RP were identified (extraprostatic extension and/or positive margin). Surgical technique, initial PSA (iPSA), pathology and post-op PSA were analyzed. The uPSA assay threshold was 0.01 ng/mL. Conventional biochemical relapse (cBCR) was defined as PSA ≥0.2 ng/mL. Kaplan Meier and Cox multivariate analyses (MVA) compared uPSA recurrence vs. cBCR rates. RESULTS Sensitivity analysis identified uPSA ≥0.03 as the optimal threshold identifying recurrence. First post-op uPSA ≥0.03, Gleason grade, T-stage, iPSA, and margin status predicted cBCR. On MVA, only first post-op uPSA ≥0.03, Gleason grade, and T-stage independently predicted cBCR. First post-op uPSA ≥0.03 conferred the highest risk (HR 8.5, p<0.0001) and discerned cBCR with greater sensitivity than undetectable first conventional PSA (70% vs. 46%). Any post-op PSA ≥0.03 captured all failures missed by first post-op value (100% sensitivity) with accuracy (96% specificity). Defining failure at uPSA ≥0.03 yielded a median lead-time advantage of 18 months (mean 24 months) over the conventional PSA ≥0.2 definition. CONCLUSION uPSA ≥0.03 is an independent factor, identifies BCR more accurately than any traditional risk factors, and confers a significant lead-time advantage. uPSA enables critical decisions regarding timing and indication for post-op RT among high-risk patients following RP. PMID:25463990
Wong, Vanessa K; Baker, Stephen; Pickard, Derek J; Parkhill, Julian; Page, Andrew J; Feasey, Nicholas A; Kingsley, Robert A; Thomson, Nicholas R; Keane, Jacqueline A; Weill, François-Xavier; Edwards, David J; Hawkey, Jane; Harris, Simon R; Mather, Alison E; Cain, Amy K; Hadfield, James; Hart, Peter J; Thieu, Nga Tran Vu; Klemm, Elizabeth J; Glinos, Dafni A; Breiman, Robert F; Watson, Conall H; Kariuki, Samuel; Gordon, Melita A; Heyderman, Robert S; Okoro, Chinyere; Jacobs, Jan; Lunguya, Octavie; Edmunds, W John; Msefula, Chisomo; Chabalgoity, Jose A; Kama, Mike; Jenkins, Kylie; Dutta, Shanta; Marks, Florian; Campos, Josefina; Thompson, Corinne; Obaro, Stephen; MacLennan, Calman A; Dolecek, Christiane; Keddy, Karen H; Smith, Anthony M; Parry, Christopher M; Karkey, Abhilasha; Mulholland, E Kim; Campbell, James I; Dongol, Sabina; Basnyat, Buddha; Dufour, Muriel; Bandaranayake, Don; Naseri, Take Toleafoa; Singh, Shalini Pravin; Hatta, Mochammad; Newton, Paul; Onsare, Robert S; Isaia, Lupeoletalalei; Dance, David; Davong, Viengmon; Thwaites, Guy; Wijedoru, Lalith; Crump, John A; De Pinna, Elizabeth; Nair, Satheesh; Nilles, Eric J; Thanh, Duy Pham; Turner, Paul; Soeng, Sona; Valcanis, Mary; Powling, Joan; Dimovski, Karolina; Hogg, Geoff; Farrar, Jeremy; Holt, Kathryn E; Dougan, Gordon
2015-06-01
The emergence of multidrug-resistant (MDR) typhoid is a major global health threat affecting many countries where the disease is endemic. Here whole-genome sequence analysis of 1,832 Salmonella enterica serovar Typhi (S. Typhi) identifies a single dominant MDR lineage, H58, that has emerged and spread throughout Asia and Africa over the last 30 years. Our analysis identifies numerous transmissions of H58, including multiple transfers from Asia to Africa and an ongoing, unrecognized MDR epidemic within Africa itself. Notably, our analysis indicates that H58 lineages are displacing antibiotic-sensitive isolates, transforming the global population structure of this pathogen. H58 isolates can harbor a complex MDR element residing either on transmissible IncHI1 plasmids or within multiple chromosomal integration sites. We also identify new mutations that define the H58 lineage. This phylogeographical analysis provides a framework to facilitate global management of MDR typhoid and is applicable to similar MDR lineages emerging in other bacterial species.
Wong, Vanessa K; Baker, Stephen; Pickard, Derek J; Parkhill, Julian; Page, Andrew J; Feasey, Nicholas A; Kingsley, Robert A; Thomson, Nicholas R; Keane, Jacqueline A; Weill, François-Xavier; Edwards, David J; Hawkey, Jane; Harris, Simon R; Mather, Alison E; Cain, Amy K; Hadfield, James; Hart, Peter J; Thieu, Nga Tran Vu; Klemm, Elizabeth J; Glinos, Dafni A; Breiman, Robert F; Watson, Conall H; Kariuki, Samuel; Gordon, Melita A; Heyderman, Robert S; Okoro, Chinyere; Jacobs, Jan; Lunguya, Octavie; Edmunds, W John; Msefula, Chisomo; Chabalgoity, Jose A; Kama, Mike; Jenkins, Kylie; Dutta, Shanta; Marks, Florian; Campos, Josefina; Thompson, Corinne; Obaro, Stephen; MacLennan, Calman A; Dolecek, Christiane; Keddy, Karen H; Smith, Anthony M; Parry, Christopher M; Karkey, Abhilasha; Mulholland, E Kim; Campbell, James I; Dongol, Sabina; Basnyat, Buddha; Dufour, Muriel; Bandaranayake, Don; Naseri, Take Toleafoa; Singh, Shalini Pravin; Hatta, Mochammad; Newton, Paul; Onsare, Robert S; Isaia, Lupeoletalalei; Dance, David; Davong, Viengmon; Thwaites, Guy; Wijedoru, Lalith; Crump, John A; De Pinna, Elizabeth; Nair, Satheesh; Nilles, Eric J; Thanh, Duy Pham; Turner, Paul; Soeng, Sona; Valcanis, Mary; Powling, Joan; Dimovski, Karolina; Hogg, Geoff; Farrar, Jeremy; Holt, Kathryn E; Dougan, Gordon
2016-01-01
The emergence of multidrug-resistant (MDR) typhoid is a major global health threat affecting many countries where the disease is endemic. Here whole-genome sequence analysis of 1,832 Salmonella enterica serovar Typhi (S. Typhi) identifies a single dominant MDR lineage, H58, that has emerged and spread throughout Asia and Africa over the last 30 years. Our analysis identifies numerous transmissions of H58, including multiple transfers from Asia to Africa and an ongoing, unrecognized MDR epidemic within Africa itself. Notably, our analysis indicates that H58 lineages are displacing antibiotic-sensitive isolates, transforming the global population structure of this pathogen. H58 isolates can harbor a complex MDR element residing either on transmissible IncHI1 plasmids or within multiple chromosomal integration sites. We also identify new mutations that define the H58 lineage. This phylogeographical analysis provides a framework to facilitate global management of MDR typhoid and is applicable to similar MDR lineages emerging in other bacterial species. PMID:25961941
Schlattmann, Peter; Verba, Maryna; Dewey, Marc; Walther, Mario
2015-01-01
Bivariate linear and generalized linear random effects are frequently used to perform a diagnostic meta-analysis. The objective of this article was to apply a finite mixture model of bivariate normal distributions that can be used for the construction of componentwise summary receiver operating characteristic (sROC) curves. Bivariate linear random effects and a bivariate finite mixture model are used. The latter model is developed as an extension of a univariate finite mixture model. Two examples, computed tomography (CT) angiography for ruling out coronary artery disease and procalcitonin as a diagnostic marker for sepsis, are used to estimate mean sensitivity and mean specificity and to construct sROC curves. The suggested approach of a bivariate finite mixture model identifies two latent classes of diagnostic accuracy for the CT angiography example. Both classes show high sensitivity but mainly two different levels of specificity. For the procalcitonin example, this approach identifies three latent classes of diagnostic accuracy. Here, sensitivities and specificities are quite different as such that sensitivity increases with decreasing specificity. Additionally, the model is used to construct componentwise sROC curves and to classify individual studies. The proposed method offers an alternative approach to model between-study heterogeneity in a diagnostic meta-analysis. Furthermore, it is possible to construct sROC curves even if a positive correlation between sensitivity and specificity is present. Copyright © 2015 Elsevier Inc. All rights reserved.
Evaluation and construction of diagnostic criteria for inclusion body myositis
Mammen, Andrew L.; Amato, Anthony A.; Weiss, Michael D.; Needham, Merrilee
2014-01-01
Objective: To use patient data to evaluate and construct diagnostic criteria for inclusion body myositis (IBM), a progressive disease of skeletal muscle. Methods: The literature was reviewed to identify all previously proposed IBM diagnostic criteria. These criteria were applied through medical records review to 200 patients diagnosed as having IBM and 171 patients diagnosed as having a muscle disease other than IBM by neuromuscular specialists at 2 institutions, and to a validating set of 66 additional patients with IBM from 2 other institutions. Machine learning techniques were used for unbiased construction of diagnostic criteria. Results: Twenty-four previously proposed IBM diagnostic categories were identified. Twelve categories all performed with high (≥97%) specificity but varied substantially in their sensitivities (11%–84%). The best performing category was European Neuromuscular Centre 2013 probable (sensitivity of 84%). Specialized pathologic features and newly introduced strength criteria (comparative knee extension/hip flexion strength) performed poorly. Unbiased data-directed analysis of 20 features in 371 patients resulted in construction of higher-performing data-derived diagnostic criteria (90% sensitivity and 96% specificity). Conclusions: Published expert consensus–derived IBM diagnostic categories have uniformly high specificity but wide-ranging sensitivities. High-performing IBM diagnostic category criteria can be developed directly from principled unbiased analysis of patient data. Classification of evidence: This study provides Class II evidence that published expert consensus–derived IBM diagnostic categories accurately distinguish IBM from other muscle disease with high specificity but wide-ranging sensitivities. PMID:24975859
Luo, Mingxu; Song, Hongmei; Liu, Gang; Lin, Yikai; Luo, Lintao; Zhou, Xin; Chen, Bo
2017-10-13
The diagnostic values of diffusion weighted imaging (DWI) and 18 F-fluorodeoxyglucose positron emission tomography/computed tomography ( 18 F-FDG PET/CT) for N-staging of gastric cancer (GC) were identified and compared. After a systematic search to identify relevant articles, meta-analysis was used to summarize the sensitivities, specificities, and areas under curves (AUCs) for DWI and PET/CT. To better understand the diagnostic utility of DWI and PET/CT for N-staging, the performance of multi-detector computed tomography (MDCT) was used as a reference. Fifteen studies were analyzed. The pooled sensitivity, specificity, and AUC with 95% confidence intervals of DWI were 0.79 (0.73-0.85), 0.69 (0.61-0.77), and 0.81 (0.77-0.84), respectively. For PET/CT, the corresponding values were 0.52 (0.39-0.64), 0.88 (0.61-0.97), and 0.66 (0.62-0.70), respectively. Comparison of the two techniques revealed DWI had higher sensitivity and AUC, but no difference in specificity. DWI exhibited higher sensitivity but lower specificity than MDCT, and 18 F-FDG PET/CT had lower sensitivity and equivalent specificity. Overall, DWI performed better than 18 F-FDG PET/CT for preoperative N-staging in GC. When the efficacy of MDCT was taken as a reference, DWI represented a complementary imaging technique, while 18 F-FDG PET/CT had limited utility for preoperative N-staging.
De Souza, Aglecio Luiz; Batista, Gisele Almeida; Alegre, Sarah Monte
2017-01-01
We compare spectral analysis of photoplethysmography (PTG) with insulin resistance measured by the hyperinsulinemic euglycemic clamp (HEC) technique. A total of 100 nondiabetic subjects, 43 men and 57 women aged 20-63years, 30 lean, 42 overweight and 28 obese were enrolled in the study. These patients underwent an examination with HEC, and an examination with the PTG spectral analysis and calculation of the PTG Total Power (PTG-TP). Receiver-operating characteristic (ROC) curves were constructed to determine the specificity and sensitivity of PTG-TP in the assessment of insulin resistance. There is a moderate correlation between insulin sensitivity (M-value) and PTG-TP (r=- 0.64, p<0.0001). The ROC curves showed that the most relevant cutoff to the whole study group was a PTG-TP>406.2. This cut-off had a sensitivity=95.7%, specificity =84,4% and the area under the ROC curve (AUC)=0.929 for identifying insulin resistance. All AUC ROC curve analysis were significant (p<0.0001). The use of the PTG-TP marker measured from the PTG spectral analysis is a useful tool in screening and follow up of IR, especially in large-scale studies. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Visualizing Confidence in Cluster-Based Ensemble Weather Forecast Analyses.
Kumpf, Alexander; Tost, Bianca; Baumgart, Marlene; Riemer, Michael; Westermann, Rudiger; Rautenhaus, Marc
2018-01-01
In meteorology, cluster analysis is frequently used to determine representative trends in ensemble weather predictions in a selected spatio-temporal region, e.g., to reduce a set of ensemble members to simplify and improve their analysis. Identified clusters (i.e., groups of similar members), however, can be very sensitive to small changes of the selected region, so that clustering results can be misleading and bias subsequent analyses. In this article, we - a team of visualization scientists and meteorologists-deliver visual analytics solutions to analyze the sensitivity of clustering results with respect to changes of a selected region. We propose an interactive visual interface that enables simultaneous visualization of a) the variation in composition of identified clusters (i.e., their robustness), b) the variability in cluster membership for individual ensemble members, and c) the uncertainty in the spatial locations of identified trends. We demonstrate that our solution shows meteorologists how representative a clustering result is, and with respect to which changes in the selected region it becomes unstable. Furthermore, our solution helps to identify those ensemble members which stably belong to a given cluster and can thus be considered similar. In a real-world application case we show how our approach is used to analyze the clustering behavior of different regions in a forecast of "Tropical Cyclone Karl", guiding the user towards the cluster robustness information required for subsequent ensemble analysis.
Chawade, Aakash; Lindlöf, Angelica; Olsson, Björn; Olsson, Olof
2013-01-01
Low temperature is a key factor that limits growth and productivity of many important agronomical crops worldwide. Rice (Oryza sativa L.) is negatively affected already at temperatures below +10°C and is therefore denoted as chilling sensitive. However, chilling tolerant rice cultivars exist and can be commercially cultivated at altitudes up to 3,050 meters with temperatures reaching as low as +4°C. In this work, the global transcriptional response to cold stress (+4°C) was studied in the Nepalese highland variety Jumli Marshi (spp. japonica) and 4,636 genes were identified as significantly differentially expressed within 24 hours of cold stress. Comparison with previously published microarray data from one chilling tolerant and two sensitive rice cultivars identified 182 genes differentially expressed (DE) upon cold stress in all four rice cultivars and 511 genes DE only in the chilling tolerant rice. Promoter analysis of the 182 genes suggests a complex cross-talk between ABRE and CBF regulons. Promoter analysis of the 511 genes identified over-represented ABRE motifs but not DRE motifs, suggesting a role for ABA signaling in cold tolerance. Moreover, 2,101 genes were DE in Jumli Marshi alone. By chromosomal localization analysis, 473 of these cold responsive genes were located within 13 different QTLs previously identified as cold associated. PMID:24349120
Acoustic resonance of outer-rotor brushless dc motor for air-conditioner fan
NASA Astrophysics Data System (ADS)
Lee, Hong-Joo; Chung, Shi-Uk; Hwang, Sang-Moon
2008-04-01
Generation of acoustic noise in electric motor is an interacting combination of mechanical and electromagnetic sources. In this paper, a brushless dc motor for air-conditioner fan is analyzed by finite element method to identify noise source, and the analysis results are verified by experiments, and sensitivity analysis is performed by design of experiments.
2015-03-12
26 Table 3: Optometry Clinic Frequency Count... Optometry Clinic Frequency Count.................................................................. 86 Table 22: Probability Distribution Summary Table...Clinic, the Audiology Clinic, and the Optometry Clinic. Methodology Overview The overarching research goal is to identify feasible solutions to
Identifying Talent in Youth Sport: A Novel Methodology Using Higher-Dimensional Analysis.
Till, Kevin; Jones, Ben L; Cobley, Stephen; Morley, David; O'Hara, John; Chapman, Chris; Cooke, Carlton; Beggs, Clive B
2016-01-01
Prediction of adult performance from early age talent identification in sport remains difficult. Talent identification research has generally been performed using univariate analysis, which ignores multivariate relationships. To address this issue, this study used a novel higher-dimensional model to orthogonalize multivariate anthropometric and fitness data from junior rugby league players, with the aim of differentiating future career attainment. Anthropometric and fitness data from 257 Under-15 rugby league players was collected. Players were grouped retrospectively according to their future career attainment (i.e., amateur, academy, professional). Players were blindly and randomly divided into an exploratory (n = 165) and validation dataset (n = 92). The exploratory dataset was used to develop and optimize a novel higher-dimensional model, which combined singular value decomposition (SVD) with receiver operating characteristic analysis. Once optimized, the model was tested using the validation dataset. SVD analysis revealed 60 m sprint and agility 505 performance were the most influential characteristics in distinguishing future professional players from amateur and academy players. The exploratory dataset model was able to distinguish between future amateur and professional players with a high degree of accuracy (sensitivity = 85.7%, specificity = 71.1%; p<0.001), although it could not distinguish between future professional and academy players. The validation dataset model was able to distinguish future professionals from the rest with reasonable accuracy (sensitivity = 83.3%, specificity = 63.8%; p = 0.003). Through the use of SVD analysis it was possible to objectively identify criteria to distinguish future career attainment with a sensitivity over 80% using anthropometric and fitness data alone. As such, this suggests that SVD analysis may be a useful analysis tool for research and practice within talent identification.
Identifying Talent in Youth Sport: A Novel Methodology Using Higher-Dimensional Analysis
Till, Kevin; Jones, Ben L.; Cobley, Stephen; Morley, David; O'Hara, John; Chapman, Chris; Cooke, Carlton; Beggs, Clive B.
2016-01-01
Prediction of adult performance from early age talent identification in sport remains difficult. Talent identification research has generally been performed using univariate analysis, which ignores multivariate relationships. To address this issue, this study used a novel higher-dimensional model to orthogonalize multivariate anthropometric and fitness data from junior rugby league players, with the aim of differentiating future career attainment. Anthropometric and fitness data from 257 Under-15 rugby league players was collected. Players were grouped retrospectively according to their future career attainment (i.e., amateur, academy, professional). Players were blindly and randomly divided into an exploratory (n = 165) and validation dataset (n = 92). The exploratory dataset was used to develop and optimize a novel higher-dimensional model, which combined singular value decomposition (SVD) with receiver operating characteristic analysis. Once optimized, the model was tested using the validation dataset. SVD analysis revealed 60 m sprint and agility 505 performance were the most influential characteristics in distinguishing future professional players from amateur and academy players. The exploratory dataset model was able to distinguish between future amateur and professional players with a high degree of accuracy (sensitivity = 85.7%, specificity = 71.1%; p<0.001), although it could not distinguish between future professional and academy players. The validation dataset model was able to distinguish future professionals from the rest with reasonable accuracy (sensitivity = 83.3%, specificity = 63.8%; p = 0.003). Through the use of SVD analysis it was possible to objectively identify criteria to distinguish future career attainment with a sensitivity over 80% using anthropometric and fitness data alone. As such, this suggests that SVD analysis may be a useful analysis tool for research and practice within talent identification. PMID:27224653
Vrana, Julie A.; Theis, Jason D.; Dasari, Surendra; Mereuta, Oana M.; Dispenzieri, Angela; Zeldenrust, Steven R.; Gertz, Morie A.; Kurtin, Paul J.; Grogg, Karen L.; Dogan, Ahmet
2014-01-01
Examination of abdominal subcutaneous fat aspirates is a practical, sensitive and specific method for the diagnosis of systemic amyloidosis. Here we describe the development and implementation of a clinical assay using mass spectrometry-based proteomics to type amyloidosis in subcutaneous fat aspirates. First, we validated the assay comparing amyloid-positive (n=43) and -negative (n=26) subcutaneous fat aspirates. The assay classified amyloidosis with 88% sensitivity and 96% specificity. We then implemented the assay as a clinical test, and analyzed 366 amyloid-positive subcutaneous fat aspirates in a 4-year period as part of routine clinical care. The assay had a sensitivity of 90%, and diverse amyloid types, including immunoglobulin light chain (74%), transthyretin (13%), serum amyloid A (%1), gelsolin (1%), and lysozyme (1%), were identified. Using bioinformatics, we identified a universal amyloid proteome signature, which has high sensitivity and specificity for amyloidosis similar to that of Congo red staining. We curated proteome databases which included variant proteins associated with systemic amyloidosis, and identified clonotypic immunoglobulin variable gene usage in immunoglobulin light chain amyloidosis, and the variant peptides in hereditary transthyretin amyloidosis. In conclusion, mass spectrometry-based proteomic analysis of subcutaneous fat aspirates offers a powerful tool for the diagnosis and typing of systemic amyloidosis. The assay reveals the underlying pathogenesis by identifying variable gene usage in immunoglobulin light chains and the variant peptides in hereditary amyloidosis. PMID:24747948
Asao, Keiko; McEwen, Laura N.; Lee, Joyce M.; Herman, William H.
2015-01-01
Aims To estimate and evaluate the sensitivity and specificity of providers’ diagnosis codes and medication lists to identify outpatient visits by patients with diabetes. Methods We used data from the 2006 to 2010 National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey. We assessed the sensitivity and specificity of providers’ diagnoses and medication lists to identify patients with diabetes, using the checkbox for diabetes as the gold standard. We then examined differences in sensitivity by patients’ characteristics using multivariate logistic regression models. Results The checkbox identified 12,647 outpatient visits by adults with diabetes among the 70,352 visits used for this analysis. The sensitivity and specificity of providers’ diagnoses or listed diabetes medications were 72.3% (95% CI: 70.8% to 73.8%) and 99.2% (99.1% to 99.4%), respectively. Diabetic patients ≥75 years pf age, women, non-Hispanics, and those with private insurance or Medicare were more likely to be missed by providers’ diagnoses and medication lists. Diabetic patients who had more diagnosis codes and medications recorded, had glucose or hemoglobin A1c measured, or made office- rather than hospital-outpatient visits were less likely to be missed. Conclusions Providers’ diagnosis codes and medication lists fail to identify approximately one quarter of outpatient visits by patients with diabetes. PMID:25891975
A Sensitivity Analysis of fMRI Balloon Model.
Zayane, Chadia; Laleg-Kirati, Taous Meriem
2015-01-01
Functional magnetic resonance imaging (fMRI) allows the mapping of the brain activation through measurements of the Blood Oxygenation Level Dependent (BOLD) contrast. The characterization of the pathway from the input stimulus to the output BOLD signal requires the selection of an adequate hemodynamic model and the satisfaction of some specific conditions while conducting the experiment and calibrating the model. This paper, focuses on the identifiability of the Balloon hemodynamic model. By identifiability, we mean the ability to estimate accurately the model parameters given the input and the output measurement. Previous studies of the Balloon model have somehow added knowledge either by choosing prior distributions for the parameters, freezing some of them, or looking for the solution as a projection on a natural basis of some vector space. In these studies, the identification was generally assessed using event-related paradigms. This paper justifies the reasons behind the need of adding knowledge, choosing certain paradigms, and completing the few existing identifiability studies through a global sensitivity analysis of the Balloon model in the case of blocked design experiment.
Identifying hearing loss by means of iridology.
Stearn, Natalie; Swanepoel, De Wet
2006-11-13
Isolated reports of hearing loss presenting as markings on the iris exist, but to date the effectiveness of iridology to identify hearing loss has not been investigated. This study therefore aimed to determine the efficacy of iridological analysis in the identification of moderate to profound sensorineural hearing loss in adolescents. A controlled trial was conducted with an iridologist, blind to the actual hearing status of participants, analyzing the irises of participants with and without hearing loss. Fifty hearing impaired and fifty normal hearing subjects, between the ages of 15 and 19 years, controlled for gender, participated in the study. An experienced iridologist analyzed the randomised set of participants' irises. A 70% correct identification of hearing status was obtained by iridological analyses with a false negative rate of 41% compared to a 19% false positive rate. The respective sensitivity and specificity rates therefore came to 59% and 81%. Iridological analysis of hearing status indicated a statistically significant relationship to actual hearing status (P < 0.05). Although statistically significant sensitivity and specificity rates for identifying hearing loss by iridology were not comparable to those of traditional audiological screening procedures.
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.
Maintaining gender sensitivity in the family practice: facilitators and barriers.
Celik, Halime; Lagro-Janssen, Toine; Klinge, Ineke; van der Weijden, Trudy; Widdershoven, Guy
2009-12-01
This study aims to identify the facilitators and barriers perceived by General Practitioners (GPs) to maintain a gender perspective in family practice. Nine semi-structured interviews were conducted among nine pairs of GPs. The data were analysed by means of deductive content analysis using theory-based methods to generate facilitators and barriers to gender sensitivity. Gender sensitivity in family practice can be influenced by several factors which ultimately determine the extent to which a gender sensitive approach is satisfactorily practiced by GPs in the doctor-patient relationship. Gender awareness, repetition and reminders, motivation triggers and professional guidelines were found to facilitate gender sensitivity. On the other hand, lacking skills and routines, scepticism, heavy workload and the timing of implementation were found to be barriers to gender sensitivity. While the potential effect of each factor affecting gender sensitivity in family practice has been elucidated, the effects of the interplay between these factors still need to be determined.
Wilson, Kate E; Marouga, Rita; Prime, John E; Pashby, D Paul; Orange, Paul R; Crosier, Steven; Keith, Alexander B; Lathe, Richard; Mullins, John; Estibeiro, Peter; Bergling, Helene; Hawkins, Edward; Morris, Christopher M
2005-10-01
Comparative proteomic methods are rapidly being applied to many different biological systems including complex tissues. One pitfall of these methods is that in some cases, such as oncology and neuroscience, tissue complexity requires isolation of specific cell types and sample is limited. Laser microdissection (LMD) is commonly used for obtaining such samples for proteomic studies. We have combined LMD with sensitive thiol-reactive saturation dye labelling of protein samples and 2-D DIGE to identify protein changes in a test system, the isolated CA1 pyramidal neurone layer of a transgenic (Tg) rat carrying a human amyloid precursor protein transgene. Saturation dye labelling proved to be extremely sensitive with a spot map of over 5,000 proteins being readily produced from 5 mug total protein, with over 100 proteins being significantly altered at p < 0.0005. Of the proteins identified, all showed coherent changes associated with transgene expression. It was, however, difficult to identify significantly different proteins using PMF and MALDI-TOF on gels containing less than 500 mug total protein. The use of saturation dye labelling of limiting samples will therefore require the use of highly sensitive MS techniques to identify the significantly altered proteins isolated using methods such as LMD.
McCormick, Natalie; Lacaille, Diane; Bhole, Vidula; Avina-Zubieta, J. Antonio
2014-01-01
Objective Heart failure (HF) is an important covariate and outcome in studies of elderly populations and cardiovascular disease cohorts, among others. Administrative data is increasingly being used for long-term clinical research in these populations. We aimed to conduct the first systematic review and meta-analysis of studies reporting on the validity of diagnostic codes for identifying HF in administrative data. Methods MEDLINE and EMBASE were searched (inception to November 2010) for studies: (a) Using administrative data to identify HF; or (b) Evaluating the validity of HF codes in administrative data; and (c) Reporting validation statistics (sensitivity, specificity, positive predictive value [PPV], negative predictive value, or Kappa scores) for HF, or data sufficient for their calculation. Additional articles were located by hand search (up to February 2011) of original papers. Data were extracted by two independent reviewers; article quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool. Using a random-effects model, pooled sensitivity and specificity values were produced, along with estimates of the positive (LR+) and negative (LR−) likelihood ratios, and diagnostic odds ratios (DOR = LR+/LR−) of HF codes. Results Nineteen studies published from1999–2009 were included in the qualitative review. Specificity was ≥95% in all studies and PPV was ≥87% in the majority, but sensitivity was lower (≥69% in ≥50% of studies). In a meta-analysis of the 11 studies reporting sensitivity and specificity values, the pooled sensitivity was 75.3% (95% CI: 74.7–75.9) and specificity was 96.8% (95% CI: 96.8–96.9). The pooled LR+ was 51.9 (20.5–131.6), the LR− was 0.27 (0.20–0.37), and the DOR was 186.5 (96.8–359.2). Conclusions While most HF diagnoses in administrative databases do correspond to true HF cases, about one-quarter of HF cases are not captured. The use of broader search parameters, along with laboratory and prescription medication data, may help identify more cases. PMID:25126761
Sensitivity of surface meteorological analyses to observation networks
NASA Astrophysics Data System (ADS)
Tyndall, Daniel Paul
A computationally efficient variational analysis system for two-dimensional meteorological fields is developed and described. This analysis approach is most efficient when the number of analysis grid points is much larger than the number of available observations, such as for large domain mesoscale analyses. The analysis system is developed using MATLAB software and can take advantage of multiple processors or processor cores. A version of the analysis system has been exported as a platform independent application (i.e., can be run on Windows, Linux, or Macintosh OS X desktop computers without a MATLAB license) with input/output operations handled by commonly available internet software combined with data archives at the University of Utah. The impact of observation networks on the meteorological analyses is assessed by utilizing a percentile ranking of individual observation sensitivity and impact, which is computed by using the adjoint of the variational surface assimilation system. This methodology is demonstrated using a case study of the analysis from 1400 UTC 27 October 2010 over the entire contiguous United States domain. The sensitivity of this approach to the dependence of the background error covariance on observation density is examined. Observation sensitivity and impact provide insight on the influence of observations from heterogeneous observing networks as well as serve as objective metrics for quality control procedures that may help to identify stations with significant siting, reporting, or representativeness issues.
NASA Astrophysics Data System (ADS)
Buckland, Catherine; Bailey, Richard; Thomas, David
2017-04-01
Two billion people living in drylands are affected by land degradation. Sediment erosion by wind and water removes fertile soil and destabilises landscapes. Vegetation disturbance is a key driver of dryland erosion caused by both natural and human forcings: drought, fire, land use, grazing pressure. A quantified understanding of vegetation cover sensitivities and resultant surface change to forcing factors is needed if the vegetation and landscape response to future climate change and human pressure are to be better predicted. Using quartz luminescence dating and statistical changepoint analysis (Killick & Eckley, 2014) this study demonstrates the ability to identify step-changes in depositional age of near-surface sediments. Lx/Tx luminescence profiles coupled with statistical analysis show the use of near-surface sediments in providing a high-resolution record of recent system response and aeolian system thresholds. This research determines how the environment has recorded and retained sedimentary evidence of drought response and land use disturbances over the last two hundred years across both individual landforms and the wider Nebraska Sandhills. Identifying surface deposition and comparing with records of climate, fire and land use changes allows us to assess the sensitivity and stability of the surface sediment to a range of forcing factors. Killick, R and Eckley, IA. (2014) "changepoint: An R Package for Changepoint Analysis." Journal of Statistical Software, (58) 1-19.
Alam, Maksudul; Deng, Xinwei; Philipson, Casandra; Bassaganya-Riera, Josep; Bisset, Keith; Carbo, Adria; Eubank, Stephen; Hontecillas, Raquel; Hoops, Stefan; Mei, Yongguo; Abedi, Vida; Marathe, Madhav
2015-01-01
Agent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system. The interaction of components and the behavior of individual objects is described procedurally as a function of the internal states and the local interactions, which are often stochastic in nature. Such models typically have complex structures and consist of a large number of modeling parameters. Determining the key modeling parameters which govern the outcomes of the system is very challenging. Sensitivity analysis plays a vital role in quantifying the impact of modeling parameters in massively interacting systems, including large complex ABM. The high computational cost of executing simulations impedes running experiments with exhaustive parameter settings. Existing techniques of analyzing such a complex system typically focus on local sensitivity analysis, i.e. one parameter at a time, or a close “neighborhood” of particular parameter settings. However, such methods are not adequate to measure the uncertainty and sensitivity of parameters accurately because they overlook the global impacts of parameters on the system. In this article, we develop novel experimental design and analysis techniques to perform both global and local sensitivity analysis of large-scale ABMs. The proposed method can efficiently identify the most significant parameters and quantify their contributions to outcomes of the system. We demonstrate the proposed methodology for ENteric Immune SImulator (ENISI), a large-scale ABM environment, using a computational model of immune responses to Helicobacter pylori colonization of the gastric mucosa. PMID:26327290
Alam, Maksudul; Deng, Xinwei; Philipson, Casandra; Bassaganya-Riera, Josep; Bisset, Keith; Carbo, Adria; Eubank, Stephen; Hontecillas, Raquel; Hoops, Stefan; Mei, Yongguo; Abedi, Vida; Marathe, Madhav
2015-01-01
Agent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system. The interaction of components and the behavior of individual objects is described procedurally as a function of the internal states and the local interactions, which are often stochastic in nature. Such models typically have complex structures and consist of a large number of modeling parameters. Determining the key modeling parameters which govern the outcomes of the system is very challenging. Sensitivity analysis plays a vital role in quantifying the impact of modeling parameters in massively interacting systems, including large complex ABM. The high computational cost of executing simulations impedes running experiments with exhaustive parameter settings. Existing techniques of analyzing such a complex system typically focus on local sensitivity analysis, i.e. one parameter at a time, or a close "neighborhood" of particular parameter settings. However, such methods are not adequate to measure the uncertainty and sensitivity of parameters accurately because they overlook the global impacts of parameters on the system. In this article, we develop novel experimental design and analysis techniques to perform both global and local sensitivity analysis of large-scale ABMs. The proposed method can efficiently identify the most significant parameters and quantify their contributions to outcomes of the system. We demonstrate the proposed methodology for ENteric Immune SImulator (ENISI), a large-scale ABM environment, using a computational model of immune responses to Helicobacter pylori colonization of the gastric mucosa.
Nakabayashi, Ryo; Tsugawa, Hiroshi; Kitajima, Mariko; Takayama, Hiromitsu; Saito, Kazuki
2015-01-01
In metabolomics, the analysis of product ions in tandem mass spectrometry (MS/MS) is noteworthy to chemically assign structural information. However, the development of relevant analytical methods are less advanced. Here, we developed a method to boost sensitivity in liquid chromatography–Fourier transform ion cyclotron resonance–tandem mass spectrometry analysis (MS/MS boost analysis). To verify the MS/MS boost analysis, both quercetin and uniformly labeled 13C quercetin were analyzed, revealing that the origin of the product ions is not the instrument, but the analyzed compounds resulting in sensitive product ions. Next, we applied this method to the analysis of monoterpene indole alkaloids (MIAs). The comparative analyses of MIAs having indole basic skeleton (ajmalicine, catharanthine, hirsuteine, and hirsutine) and oxindole skeleton (formosanine, isoformosanine, pteropodine, isopteropodine, rhynchophylline, isorhynchophylline, and mitraphylline) identified 86 and 73 common monoisotopic ions, respectively. The comparative analyses of the three pairs of stereoisomers showed more than 170 common monoisotopic ions in each pair. This method was also applied to the targeted analysis of MIAs in Catharanthus roseus and Uncaria rhynchophylla to profile indole and oxindole compounds using the product ions. This analysis is suitable for chemically assigning features of the metabolite groups, which contributes to targeted metabolome analysis. PMID:26734034
Gui, Xuwei; Xiao, Heping
2014-01-01
This systematic review and meta-analysis was performed to determine accuracy and usefulness of adenosine deaminase (ADA) in diagnosis of tuberculosis pleurisy. Medline, Google scholar and Web of Science databases were searched to identify related studies until 2014. Two reviewers independently assessed quality of studies included according to standard Quality Assessment of Diagnosis Accuracy Studies (QUADAS) criteria. The sensitivity, specificity, diagnostic odds ratio and other parameters of ADA in diagnosis of tuberculosis pleurisy were analyzed with Meta-DiSC1.4 software, and pooled using the random effects model. Twelve studies including 865 tuberculosis pleurisy patients and 1379 non-tuberculosis pleurisy subjects were identified from 110 studies for this meta-analysis. The sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR) and diagnosis odds ratio (DOR) of ADA in the diagnosis of tuberculosis pleurisy were 45.25 (95% CI 27.63-74.08), 0.86 (95% CI 0.84-0.88), 0.88 (95% CI 0.86-0.90), 6.32 (95% CI 4.83-8.26) and 0.15 (95% 0.11-0.22), respectively. The area under the summary receiver operating characteristic curve (SROC) was 0.9340. Our results demonstrate that the sensitivity and specificity of ADA are high in the diagnosis of tuberculosis pleurisy especially when ADA≥50 (U/L). Thus, ADA is a relatively sensitive and specific marker for tuberculosis pleurisy diagnosis. However, it is cautious to apply these results due to the heterogeneity in study design of these studies. Further studies are required to confirm the optimal cut-off value of ADA.
Sensitivity and Specificity of Eustachian Tube Function Tests in Adults
Doyle, William J.; Swarts, J. Douglas; Banks, Julianne; Casselbrant, Margaretha L; Mandel, Ellen M; Alper, Cuneyt M.
2013-01-01
Objective Determine if Eustachian Tube (ET) function (ETF) tests can identify ears with physician-diagnosed ET dysfunction (ETD) in a mixed population at high sensitivity and specificity and define the inter-relatedness of ETF test parameters. Methods ETF was evaluated using the Forced-Response, Inflation-Deflation, Valsalva and Sniffing tests in 15 control ears of adult subjects after unilateral myringotomy (Group I) and in 23 ears of 19 adult subjects with ventilation tubes inserted for ETD (Group II). Data were analyzed using logistic regression including each parameter independently and then a step-down Discriminant Analysis including all ETF test parameters to predict group assignment. Factor Analysis operating over all parameters was used to explore relatedness. Results The Discriminant Analysis identified 4 ETF test parameters (Valsalva, ET opening pressure, dilatory efficiency and % positive pressure equilibrated) that together correctly assigned ears to Group II at a sensitivity of 95% and a specificity of 83%. Individual parameters representing the efficiency of ET opening during swallowing showed moderately accurate assignments of ears to their respective groups. Three factors captured approximately 98% of the variance among parameters, the first had negative loadings of the ETF structural parameters, the second had positive loadings of the muscle-assisted ET opening parameters and the third had negative loadings of the muscle-assisted ET opening parameters and positive loadings of the structural parameters. Discussion These results show that ETF tests can correctly assign individual ears to physician-diagnosed ETD with high sensitivity and specificity and that ETF test parameters can be grouped into structural-functional categories. PMID:23868429
Probabilistic Structural Evaluation of Uncertainties in Radiator Sandwich Panel Design
NASA Technical Reports Server (NTRS)
Kuguoglu, Latife; Ludwiczak, Damian
2006-01-01
The Jupiter Icy Moons Orbiter (JIMO) Space System is part of the NASA's Prometheus Program. As part of the JIMO engineering team at NASA Glenn Research Center, the structural design of the JIMO Heat Rejection Subsystem (HRS) is evaluated. An initial goal of this study was to perform sensitivity analyses to determine the relative importance of the input variables on the structural responses of the radiator panel. The desire was to let the sensitivity analysis information identify the important parameters. The probabilistic analysis methods illustrated here support this objective. The probabilistic structural performance evaluation of a HRS radiator sandwich panel was performed. The radiator panel structural performance was assessed in the presence of uncertainties in the loading, fabrication process variables, and material properties. The stress and displacement contours of the deterministic structural analysis at mean probability was performed and results presented. It is followed by a probabilistic evaluation to determine the effect of the primitive variables on the radiator panel structural performance. Based on uncertainties in material properties, structural geometry and loading, the results of the displacement and stress analysis are used as an input file for the probabilistic analysis of the panel. The sensitivity of the structural responses, such as maximum displacement and maximum tensile and compressive stresses of the facesheet in x and y directions and maximum VonMises stresses of the tube, to the loading and design variables is determined under the boundary condition where all edges of the radiator panel are pinned. Based on this study, design critical material and geometric parameters of the considered sandwich panel are identified.
Sensitivity and Nonlinearity of Thermoacoustic Oscillations
NASA Astrophysics Data System (ADS)
Juniper, Matthew P.; Sujith, R. I.
2018-01-01
Nine decades of rocket engine and gas turbine development have shown that thermoacoustic oscillations are difficult to predict but can usually be eliminated with relatively small ad hoc design changes. These changes can, however, be ruinously expensive to devise. This review explains why linear and nonlinear thermoacoustic behavior is so sensitive to parameters such as operating point, fuel composition, and injector geometry. It shows how nonperiodic behavior arises in experiments and simulations and discusses how fluctuations in thermoacoustic systems with turbulent reacting flow, which are usually filtered or averaged out as noise, can reveal useful information. Finally, it proposes tools to exploit this sensitivity in the future: adjoint-based sensitivity analysis to optimize passive control designs and complex systems theory to warn of impending thermoacoustic oscillations and to identify the most sensitive elements of a thermoacoustic system.
Hoffman, Jessica M; Soltow, Quinlyn A; Li, Shuzhao; Sidik, Alfire; Jones, Dean P; Promislow, Daniel E L
2014-01-01
Researchers have used whole-genome sequencing and gene expression profiling to identify genes associated with age, in the hope of understanding the underlying mechanisms of senescence. But there is a substantial gap from variation in gene sequences and expression levels to variation in age or life expectancy. In an attempt to bridge this gap, here we describe the effects of age, sex, genotype, and their interactions on high-sensitivity metabolomic profiles in the fruit fly, Drosophila melanogaster. Among the 6800 features analyzed, we found that over one-quarter of all metabolites were significantly associated with age, sex, genotype, or their interactions, and multivariate analysis shows that individual metabolomic profiles are highly predictive of these traits. Using a metabolomic equivalent of gene set enrichment analysis, we identified numerous metabolic pathways that were enriched among metabolites associated with age, sex, and genotype, including pathways involving sugar and glycerophospholipid metabolism, neurotransmitters, amino acids, and the carnitine shuttle. Our results suggest that high-sensitivity metabolomic studies have excellent potential not only to reveal mechanisms that lead to senescence, but also to help us understand differences in patterns of aging among genotypes and between males and females. PMID:24636523
Functional analysis of inappropriate social interactions in students with Asperger's syndrome.
Roantree, Christina F; Kennedy, Craig H
2012-01-01
We analyzed the inappropriate social interactions of 3 students with Asperger's syndrome whose behavior was maintained by social positive reinforcement. We tested whether inappropriate social behavior was sensitive to social positive reinforcement contingencies and whether such contingencies could be reversed to increase the probability of socially appropriate responding. Our results show that social positive reinforcers can be identified for inappropriate social interactions and that appropriate social behaviors can be sensitive to reinforcement contingency reversals.
NASA Astrophysics Data System (ADS)
Marquet, P.; Rothenfusser, K.; Rappaz, B.; Depeursinge, C.; Jourdain, P.; Magistretti, P. J.
2016-03-01
Quantitative phase microscopy (QPM) has recently emerged as a powerful label-free technique in the field of living cell imaging allowing to non-invasively measure with a nanometric axial sensitivity cell structure and dynamics. Since the phase retardation of a light wave when transmitted through the observed cells, namely the quantitative phase signal (QPS), is sensitive to both cellular thickness and intracellular refractive index related to the cellular content, its accurate analysis allows to derive various cell parameters and monitor specific cell processes, which are very likely to identify new cell biomarkers. Specifically, quantitative phase-digital holographic microscopy (QP-DHM), thanks to its numerical flexibility facilitating parallelization and automation processes, represents an appealing imaging modality to both identify original cellular biomarkers of diseases as well to explore the underlying pathophysiological processes.
Wu, Yiping; Liu, Shuguang; Huang, Zhihong; Yan, Wende
2014-01-01
Ecosystem models are useful tools for understanding ecological processes and for sustainable management of resources. In biogeochemical field, numerical models have been widely used for investigating carbon dynamics under global changes from site to regional and global scales. However, it is still challenging to optimize parameters and estimate parameterization uncertainty for complex process-based models such as the Erosion Deposition Carbon Model (EDCM), a modified version of CENTURY, that consider carbon, water, and nutrient cycles of ecosystems. This study was designed to conduct the parameter identifiability, optimization, sensitivity, and uncertainty analysis of EDCM using our developed EDCM-Auto, which incorporated a comprehensive R package—Flexible Modeling Framework (FME) and the Shuffled Complex Evolution (SCE) algorithm. Using a forest flux tower site as a case study, we implemented a comprehensive modeling analysis involving nine parameters and four target variables (carbon and water fluxes) with their corresponding measurements based on the eddy covariance technique. The local sensitivity analysis shows that the plant production-related parameters (e.g., PPDF1 and PRDX) are most sensitive to the model cost function. Both SCE and FME are comparable and performed well in deriving the optimal parameter set with satisfactory simulations of target variables. Global sensitivity and uncertainty analysis indicate that the parameter uncertainty and the resulting output uncertainty can be quantified, and that the magnitude of parameter-uncertainty effects depends on variables and seasons. This study also demonstrates that using the cutting-edge R functions such as FME can be feasible and attractive for conducting comprehensive parameter analysis for ecosystem modeling.
Knowledge-guided gene prioritization reveals new insights into the mechanisms of chemoresistance.
Emad, Amin; Cairns, Junmei; Kalari, Krishna R; Wang, Liewei; Sinha, Saurabh
2017-08-11
Identification of genes whose basal mRNA expression predicts the sensitivity of tumor cells to cytotoxic treatments can play an important role in individualized cancer medicine. It enables detailed characterization of the mechanism of action of drugs. Furthermore, screening the expression of these genes in the tumor tissue may suggest the best course of chemotherapy or a combination of drugs to overcome drug resistance. We developed a computational method called ProGENI to identify genes most associated with the variation of drug response across different individuals, based on gene expression data. In contrast to existing methods, ProGENI also utilizes prior knowledge of protein-protein and genetic interactions, using random walk techniques. Analysis of two relatively new and large datasets including gene expression data on hundreds of cell lines and their cytotoxic responses to a large compendium of drugs reveals a significant improvement in prediction of drug sensitivity using genes identified by ProGENI compared to other methods. Our siRNA knockdown experiments on ProGENI-identified genes confirmed the role of many new genes in sensitivity to three chemotherapy drugs: cisplatin, docetaxel, and doxorubicin. Based on such experiments and extensive literature survey, we demonstrate that about 73% of our top predicted genes modulate drug response in selected cancer cell lines. In addition, global analysis of genes associated with groups of drugs uncovered pathways of cytotoxic response shared by each group. Our results suggest that knowledge-guided prioritization of genes using ProGENI gives new insight into mechanisms of drug resistance and identifies genes that may be targeted to overcome this phenomenon.
Sensitivity analysis of periodic errors in heterodyne interferometry
NASA Astrophysics Data System (ADS)
Ganguly, Vasishta; Kim, Nam Ho; Kim, Hyo Soo; Schmitz, Tony
2011-03-01
Periodic errors in heterodyne displacement measuring interferometry occur due to frequency mixing in the interferometer. These nonlinearities are typically characterized as first- and second-order periodic errors which cause a cyclical (non-cumulative) variation in the reported displacement about the true value. This study implements an existing analytical periodic error model in order to identify sensitivities of the first- and second-order periodic errors to the input parameters, including rotational misalignments of the polarizing beam splitter and mixing polarizer, non-orthogonality of the two laser frequencies, ellipticity in the polarizations of the two laser beams, and different transmission coefficients in the polarizing beam splitter. A local sensitivity analysis is first conducted to examine the sensitivities of the periodic errors with respect to each input parameter about the nominal input values. Next, a variance-based approach is used to study the global sensitivities of the periodic errors by calculating the Sobol' sensitivity indices using Monte Carlo simulation. The effect of variation in the input uncertainty on the computed sensitivity indices is examined. It is seen that the first-order periodic error is highly sensitive to non-orthogonality of the two linearly polarized laser frequencies, while the second-order error is most sensitive to the rotational misalignment between the laser beams and the polarizing beam splitter. A particle swarm optimization technique is finally used to predict the possible setup imperfections based on experimentally generated values for periodic errors.
Prevalence of potent skin sensitizers in oxidative hair dye products in Korea.
Kim, Hyunji; Kim, Kisok
2016-09-01
The objective of the present study was to elucidate the prevalence of potent skin sensitizers in oxidative hair dye products manufactured by Korean domestic companies. A database on hair dye products made by domestic companies and selling in the Korean market in 2013 was used to obtain information on company name, brand name, quantity of production, and ingredients. The prevalence of substances categorized as potent skin sensitizers was calculated using the hair dye ingredient database, and the pattern of concomitant presence of hair dye ingredients was analyzed using network analysis software. A total of 19 potent skin sensitizers were identified from a database that included 99 hair dye products manufactured by Korean domestic companies. Among 19 potent skin sensitizers, the four most frequent were resorcinol, m-aminophenol, p-phenylenediamine (PPD), and p-aminophenol; these four skin-sensitizing ingredients were found in more than 50% of the products studied. Network analysis showed that resorcinol, m-aminophenol, and PPD existed together in many hair dye products. In 99 products examined, the average product contained 4.4 potent sensitizers, and 82% of the products contained four or more skin sensitizers. The present results demonstrate that oxidative hair dye products made by Korean domestic manufacturers contain various numbers and types of potent skin sensitizers. Furthermore, these results suggest that some hair dye products should be used with caution to prevent adverse effects on the skin, including allergic contact dermatitis.
Duran, Ibrahim; Schulze, Josefa; Martakis, KyriakoS; Stark, Christina; Schoenau, Eckhard
2018-03-07
To assess the diagnostic performance of body mass index (BMI) cut-off values according to recommendations of the World Health Organization (WHO), the World Obesity Federation (WOF), and the German Society for Adiposity (DAG) to identify excess body fat in children with cerebral palsy (CP). The present study was a monocentric retrospective analysis of prospectively collected data among children and adolescents with CP participating in a rehabilitation programme. Excess body fat was defined as a body fat percentage above the 85th centile assessed by dual-energy X-ray absorptiometry. In total, 329 children (181 males, 148 females) with CP were eligible for analysis. The mean age was 12 years 4 months (standard deviation 2y 9mo). The BMI cut-off values for 'overweight' according to the WHO, WOF, and DAG showed the following sensitivities and specificities for the prediction of excess body fat in our population: WHO: sensitivity 0.768 (95% confidence interval [CI] 0.636-0.870), specificity 0.894 (95% CI 0.851-0.928); WOF: sensitivity 0.696 (95% CI 0.559-0.812), specificity 0.934 (95% CI 0.898-0.960); DAG: sensitivity 0.411 (95% CI 0.281-0.550), specificity 0.993 (95% CI 0.974-0.999). Body mass index showed high specificity, but low sensitivity in children with CP. Thus, 'normal-weight obese' children with CP were overlooked, when assessing excess body fat only using BMI. Excess body fat in children with cerebral palsy (CP) is less common than previously reported. Body mass index (BMI) had high specificity but low sensitivity in detecting excess body fat in children with CP. BMI evaluation criteria of the German Society for Adiposity could be improved in children with CP. © 2018 Mac Keith Press.
The diagnostic value of narrow-band imaging for early and invasive lung cancer: a meta-analysis.
Zhu, Juanjuan; Li, Wei; Zhou, Jihong; Chen, Yuqing; Zhao, Chenling; Zhang, Ting; Peng, Wenjia; Wang, Xiaojing
2017-07-01
This study aimed to compare the ability of narrow-band imaging to detect early and invasive lung cancer with that of conventional pathological analysis and white-light bronchoscopy. We searched the PubMed, EMBASE, Sinomed, and China National Knowledge Infrastructure databases for relevant studies. Meta-disc software was used to perform data analysis, meta-regression analysis, sensitivity analysis, and heterogeneity testing, and STATA software was used to determine if publication bias was present, as well as to calculate the relative risks for the sensitivity and specificity of narrow-band imaging vs those of white-light bronchoscopy for the detection of early and invasive lung cancer. A random-effects model was used to assess the diagnostic efficacy of the above modalities in cases in which a high degree of between-study heterogeneity was noted with respect to their diagnostic efficacies. The database search identified six studies including 578 patients. The pooled sensitivity and specificity of narrow-band imaging were 86% (95% confidence interval: 83-88%) and 81% (95% confidence interval: 77-84%), respectively, and the pooled sensitivity and specificity of white-light bronchoscopy were 70% (95% confidence interval: 66-74%) and 66% (95% confidence interval: 62-70%), respectively. The pooled relative risks for the sensitivity and specificity of narrow-band imaging vs the sensitivity and specificity of white-light bronchoscopy for the detection of early and invasive lung cancer were 1.33 (95% confidence interval: 1.07-1.67) and 1.09 (95% confidence interval: 0.84-1.42), respectively, and sensitivity analysis showed that narrow-band imaging exhibited good diagnostic efficacy with respect to detecting early and invasive lung cancer and that the results of the study were stable. Narrow-band imaging was superior to white light bronchoscopy with respect to detecting early and invasive lung cancer; however, the specificities of the two modalities did not differ significantly.
Giustacchini, Alice; Thongjuea, Supat; Barkas, Nikolaos; Woll, Petter S; Povinelli, Benjamin J; Booth, Christopher A G; Sopp, Paul; Norfo, Ruggiero; Rodriguez-Meira, Alba; Ashley, Neil; Jamieson, Lauren; Vyas, Paresh; Anderson, Kristina; Segerstolpe, Åsa; Qian, Hong; Olsson-Strömberg, Ulla; Mustjoki, Satu; Sandberg, Rickard; Jacobsen, Sten Eirik W; Mead, Adam J
2017-06-01
Recent advances in single-cell transcriptomics are ideally placed to unravel intratumoral heterogeneity and selective resistance of cancer stem cell (SC) subpopulations to molecularly targeted cancer therapies. However, current single-cell RNA-sequencing approaches lack the sensitivity required to reliably detect somatic mutations. We developed a method that combines high-sensitivity mutation detection with whole-transcriptome analysis of the same single cell. We applied this technique to analyze more than 2,000 SCs from patients with chronic myeloid leukemia (CML) throughout the disease course, revealing heterogeneity of CML-SCs, including the identification of a subgroup of CML-SCs with a distinct molecular signature that selectively persisted during prolonged therapy. Analysis of nonleukemic SCs from patients with CML also provided new insights into cell-extrinsic disruption of hematopoiesis in CML associated with clinical outcome. Furthermore, we used this single-cell approach to identify a blast-crisis-specific SC population, which was also present in a subclone of CML-SCs during the chronic phase in a patient who subsequently developed blast crisis. This approach, which might be broadly applied to any malignancy, illustrates how single-cell analysis can identify subpopulations of therapy-resistant SCs that are not apparent through cell-population analysis.
Sensitivity Analysis of Digital I&C Modules in Protection and Safety Systems
NASA Astrophysics Data System (ADS)
Khalil Ur, Rahman; Zubair, M.; Heo, G.
2013-12-01
This research is performed to examine the sensitivity of digital Instrumentation and Control (I&C) components and modules used in regulating and protection systems architectures of nuclear industry. Fault Tree Analysis (FTA) was performed for four configurations of RPS channel architecture. The channel unavailability has been calculated by using AIMS-PSA, which comes out 4.517E-03, 2.551E-03, 2.246E-03 and 2.7613-04 for architecture configuration I, II, III and IV respectively. It is observed that unavailability decreases by 43.5 % & 50.4% by inserting partial redundancy whereas maximum reduction of 93.9 % in unavailability happens when double redundancy is inserted in architecture. Coincidence module output failure and bi-stable output failures are identified as sensitive failures by Risk Reduction Worth (RRW) and Fussell-Vesely (FV) importance. RRW highlights that risk from coincidence processor output failure can reduced by 48.83 folds and FV indicates that BP output is sensitive by 0.9796 (on a scale of 1).
PASTA: splice junction identification from RNA-Sequencing data
2013-01-01
Background Next generation transcriptome sequencing (RNA-Seq) is emerging as a powerful experimental tool for the study of alternative splicing and its regulation, but requires ad-hoc analysis methods and tools. PASTA (Patterned Alignments for Splicing and Transcriptome Analysis) is a splice junction detection algorithm specifically designed for RNA-Seq data, relying on a highly accurate alignment strategy and on a combination of heuristic and statistical methods to identify exon-intron junctions with high accuracy. Results Comparisons against TopHat and other splice junction prediction software on real and simulated datasets show that PASTA exhibits high specificity and sensitivity, especially at lower coverage levels. Moreover, PASTA is highly configurable and flexible, and can therefore be applied in a wide range of analysis scenarios: it is able to handle both single-end and paired-end reads, it does not rely on the presence of canonical splicing signals, and it uses organism-specific regression models to accurately identify junctions. Conclusions PASTA is a highly efficient and sensitive tool to identify splicing junctions from RNA-Seq data. Compared to similar programs, it has the ability to identify a higher number of real splicing junctions, and provides highly annotated output files containing detailed information about their location and characteristics. Accurate junction data in turn facilitates the reconstruction of the splicing isoforms and the analysis of their expression levels, which will be performed by the remaining modules of the PASTA pipeline, still under development. Use of PASTA can therefore enable the large-scale investigation of transcription and alternative splicing. PMID:23557086
Bashir, Mustafa R; Merkle, Elmar M; Smith, Alastair D; Boll, Daniel T
2012-02-01
To assess whether in vivo dual-ratio Dixon discrimination can improve detection of diffuse liver disease, specifically steatosis, iron deposition and combined disease over traditional single-ratio in/opposed phase analysis. Seventy-one patients with biopsy-proven (17.7 ± 17.0 days) hepatic steatosis (n = 16), iron deposition (n = 11), combined deposition (n = 3) and neither disease (n = 41) underwent MR examinations. Dual-echo in/opposed-phase MR with Dixon water/fat reconstructions were acquired. Analysis consisted of: (a) single-ratio hepatic region-of-interest (ROI)-based assessment of in/opposed ratios; (b) dual-ratio hepatic ROI assessment of in/opposed and fat/water ratios; (c) computer-aided dual-ratio assessment evaluating all hepatic voxels. Disease-specific thresholds were determined; statistical analyses assessed disease-dependent voxel ratios, based on single-ratio (a) and dual-ratio (b and c) techniques. Single-ratio discrimination succeeded in identifying iron deposition (I/O(Ironthreshold)<0.88) and steatosis (I/O(Fatthreshold>1.15)) from normal parenchyma, sensitivity 70.0%; it failed to detect combined disease. Dual-ratio discrimination succeeded in identifying abnormal hepatic parenchyma (F/W(Normalthreshold)>0.05), sensitivity 96.7%; logarithmic functions for iron deposition (I/O(Irondiscriminator)
Cost analysis of school-based intermittent screening and treatment of malaria in Kenya
2011-01-01
Background The control of malaria in schools is receiving increasing attention, but there remains currently no consensus as to the optimal intervention strategy. This paper analyses the costs of intermittent screening and treatment (IST) of malaria in schools, implemented as part of a cluster-randomized controlled trial on the Kenyan coast. Methods Financial and economic costs were estimated using an ingredients approach whereby all resources required in the delivery of IST are quantified and valued. Sensitivity analysis was conducted to investigate how programme variation affects costs and to identify potential cost savings in the future implementation of IST. Results The estimated financial cost of IST per child screened is US$ 6.61 (economic cost US$ 6.24). Key contributors to cost were salary costs (36%) and malaria rapid diagnostic tests (RDT) (22%). Almost half (47%) of the intervention cost comprises redeployment of existing resources including health worker time and use of hospital vehicles. Sensitivity analysis identified changes to intervention delivery that can reduce programme costs by 40%, including use of alternative RDTs and removal of supervised treatment. Cost-effectiveness is also likely to be highly sensitive to the proportion of children found to be RDT-positive. Conclusion In the current context, school-based IST is a relatively expensive malaria intervention, but reducing the complexity of delivery can result in considerable savings in the cost of intervention. (Costs are reported in US$ 2010). PMID:21933376
Accommodative Lag by Autorefraction and Two Dynamic Retinoscopy Methods
2008-01-01
Purpose To evaluate two clinical procedures, MEM and Nott retinoscopy, for detecting accommodative lags 1.00 diopter (D) or greater in children as identified by an open-field autorefractor. Methods 168 children 8 to <12 years old with low myopia, normal visual acuity, and no strabismus participated as part of an ancillary study within the screening process for a randomized trial. Accommodative response to a 3.00 D demand was first assessed by MEM and Nott retinoscopy, viewing binocularly with spherocylindrical refractive error corrected, with testing order randomized and each performed by a different masked examiner. The response was then determined viewing monocularly with spherical equivalent refractive error corrected, using an open-field autorefractor, which was the gold standard used for eligibility for the clinical trial. Sensitivity and specificity for accommodative lags of 1.00 D or more were calculated for each retinoscopy method compared to the autorefractor. Results 116 (69%) of the 168 children had accommodative lag of 1.00 D or more by autorefraction. MEM identified 66 children identified by autorefraction for a sensitivity of 57% (95% CI = 47% to 66%) and a specificity of 63% (95% CI = 49% to 76%). Nott retinoscopy identified 35 children for a sensitivity of 30% (95% CI = 22% to 39%) and a specificity of 81% (95% CI = 67% to 90%). Analysis of receiver operating characteristic (ROC) curves constructed for MEM and for Nott retinoscopy failed to reveal alternate cut points that would improve the combination of sensitivity and specificity for identifying accommodative lag ≥ 1.00 D as defined by autorefraction. Conclusions Neither MEM nor Nott retinoscopy provided adequate sensitivity and specificity to identify myopic children with accommodative lag ≥ 1.00 D as determined by autorefraction. A variety of methodological differences between the techniques may contribute to the modest to poor agreement. PMID:19214130
Rapid and sensitive detection of mink circovirus by recombinase polymerase amplification.
Ge, Junwei; Shi, Yunjia; Cui, Xingyang; Gu, Shanshan; Zhao, Lili; Chen, Hongyan
2018-06-01
To date, the pathogenic role of mink circovirus (MiCV) remains unclear, and its prevalence and economic importance are unknown. Therefore, a rapid and sensitive molecular diagnosis is necessary for disease management and epidemiological surveillance. However, only PCR methods can identify MiCV infection at present. In this study, we developed a nested PCR and established a novel recombinase polymerase amplification (RPA) assay for MiCV detection. Sensitivity analysis showed that the detection limit of nested PCR and RPA assay was 10 1 copies/reaction, and these methods were more sensitive than conventional PCR, which has a detection limit of 10 5 copies/reaction. The RPA assay had no cross-reactivity with other related viral pathogens, and amplification was completed in less than 20 min with a simple device. Further assessment of clinical samples showed that the two assays were accurate in identifying positive and negative conventional PCR samples. The detection rate of MiCV by the RPA assay in clinical samples was 38.09%, which was 97% consistent with that by the nested PCR. The developed nested PCR is a highly sensitive tool for practical use, and the RPA assay is a simple, sensitive, and potential alternative method for rapid and accurate MiCV diagnosis. Copyright © 2018 Elsevier B.V. All rights reserved.
von Bargen, Christoph; Dojahn, Jörg; Waidelich, Dietmar; Humpf, Hans-Ulrich; Brockmeyer, Jens
2013-12-11
The accidental or fraudulent blending of meat from different species is a highly relevant aspect for food product quality control, especially for consumers with ethical concerns against species, such as horse or pork. In this study, we present a sensitive mass spectrometrical approach for the detection of trace contaminations of horse meat and pork and demonstrate the specificity of the identified biomarker peptides against chicken, lamb, and beef. Biomarker peptides were identified by a shotgun proteomic approach using tryptic digests of protein extracts and were verified by the analysis of 21 different meat samples from the 5 species included in this study. For the most sensitive peptides, a multiple reaction monitoring (MRM) method was developed that allows for the detection of 0.55% horse or pork in a beef matrix. To enhance sensitivity, we applied MRM(3) experiments and were able to detect down to 0.13% pork contamination in beef. To the best of our knowledge, we present here the first rapid and sensitive mass spectrometrical method for the detection of horse and pork by use of MRM and MRM(3).
Ramasamy, Adaikalavan; Curjuric, Ivan; Coin, Lachlan J; Kumar, Ashish; McArdle, Wendy L; Imboden, Medea; Leynaert, Benedicte; Kogevinas, Manolis; Schmid-Grendelmeier, Peter; Pekkanen, Juha; Wjst, Matthias; Bircher, Andreas J; Sovio, Ulla; Rochat, Thierry; Hartikainen, Anna-Liisa; Balding, David J; Jarvelin, Marjo-Riitta; Probst-Hensch, Nicole; Strachan, David P; Jarvis, Deborah L
2011-11-01
Hay fever or seasonal allergic rhinitis (AR) is a chronic disorder associated with IgE sensitization to grass. The underlying genetic variants have not been studied comprehensively. There is overwhelming evidence that those who have older siblings have less AR, although the mechanism for this remains unclear. We sought to identify common genetic variant associations with prevalent AR and grass sensitization using existing genome-wide association study (GWAS) data and to determine whether genetic variants modify the protective effect of older siblings. Approximately 2.2 million genotyped or imputed single nucleotide polymorphisms were investigated in 4 large European adult cohorts for AR (3,933 self-reported cases vs 8,965 control subjects) and grass sensitization (2,315 cases vs 10,032 control subjects). Three loci reached genome-wide significance for either phenotype. The HLA variant rs7775228, which cis-regulates HLA-DRB4, was strongly associated with grass sensitization and weakly with AR (P(grass) = 1.6 × 10(-9); P(AR) = 8.0 × 10(-3)). Variants in a locus near chromosome 11 open reading frame 30 (C11orf30) and leucine-rich repeat containing 32 (LRRC32), which was previously associated with atopic dermatitis and eczema, were also strongly associated with both phenotypes (rs2155219; P(grass) = 9.4 × 10(-9); P(AR) = 3.8 × 10(-8)). The third genome-wide significant variant was rs17513503 (P(grass) = 1.2 × 10(-8); PAR = 7.4 × 10(-7)) which was located near transmembrane protein 232 (TMEM232) and solute carrier family 25, member 46 (SLC25A46). Twelve further loci with suggestive associations were also identified. Using a candidate gene approach, where we considered variants within 164 genes previously thought to be important, we found variants in 3 further genes that may be of interest: thymic stromal lymphopoietin (TSLP), Toll-like receptor 6 (TLR6) and nucleotide-binding oligomerization domain containing 1 (NOD1/CARD4). We found no evidence for variants that modified the effect of birth order on either phenotype. This relatively large meta-analysis of GWASs identified few loci associated with AR and grass sensitization. No birth order interaction was identified in the current analyses. Copyright © 2011 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.
Martino, Rosemary; Maki, Ellen; Diamant, Nicholas
2014-06-01
Dysphagia screening often includes administration of water. This study assessed the accuracy in identifying dysphagia with each additional teaspoon of water. The original research of the TOR-BSST(©) permitted this assessment. Trained nurses from acute and rehabilitation facilities prospectively administered the TOR-BSST(©) to 311 eligible stroke inpatients. A sensitivity analysis was conducted for the water item using 10 teaspoons plus a sip as the standard. The proportion of positive screenings was 59.2% in acute and 38.5% in rehabilitation. Of all four items that form the TOR-BSST(©), the water swallow item contributed to the identification of dysphagia in 42.7% in acute and 29.0% in rehabilitation patients. Across all patients, dysphagia accuracy was that five teaspoons resulted in a sensitivity of 79% (95% confidence interval [CI] = 70-86), eight a sensitivity of 92% (95% CI = 85-96) and 10 a sensitivity of 96% (95% CI = 90-99). Although a primary contributor, the water swallow item alone does not identify all patients with dysphagia. For a water swallow to accurately identify dysphagia, it is critical to administer 10 teaspoons. The TOR-BSST(©) water swallow item contributes largely to the total TOR-BSST(©)'s screening score and in making the test highly accurate and reliable.
Quatman, Carmen E; Hettrich, Carolyn M; Schmitt, Laura C; Spindler, Kurt P
2011-07-01
Current diagnostic strategies for detection of structural articular cartilage abnormalities, the earliest structural signs of osteoarthritis, often do not capture the condition until it is too far advanced for the most potential benefit of noninvasive interventions. To systematically review the literature relative to the following questions: (1) Is magnetic resonance imaging (MRI) a valid, sensitive, specific, accurate, and reliable instrument to identify knee articular cartilage abnormalities compared with arthroscopy? (2) Is MRI a sensitive tool that can be utilized to identify early cartilage degeneration? Systematic review. A systematic search was performed in November 2010 using PubMed MEDLINE (from 1966), CINAHL (from 1982), SPORTDiscus (from 1985), SCOPUS (from 1996), and EMBASE (from 1974) databases. Fourteen level I and 13 level II studies were identified that met inclusion criteria and provided information related to diagnostic performance of MRI compared with arthroscopic evaluation. The diagnostic performance of MRI demonstrated a large range of sensitivities, specificities, and accuracies. The sensitivity for identifying articular cartilage abnormalities in the knee joint was reported between 26% and 96%. Specificity and accuracy were reported between 50% and 100% and between 49% and 94%, respectively. The sensitivity, specificity, and accuracy for identifying early osteoarthritis were reported between 0% and 86%, 48% and 95%, and 5% and 94%, respectively. As a result of inconsistencies between imaging techniques and methodological shortcomings of many of the studies, a meta-analysis was not performed, and it was difficult to fully synthesize the information to state firm conclusions about the diagnostic performance of MRI. There is evidence in some MRI protocols that MRI is a relatively valid, sensitive, specific, accurate, and reliable clinical tool for identifying articular cartilage degeneration. Because of heterogeneity of MRI sequences, it is not possible to make definitive conclusions regarding its global clinical utility for guiding diagnosis and treatment strategies. Traumatic sports injuries to the knee may be significant precursor events to early onset of posttraumatic osteoarthritis. Magnetic resonance imaging may aid in early identification of structural injuries to articular cartilage as evidenced by articular cartilage degeneration grading.
Quatman, Carmen E.; Hettrich, Carolyn M.; Schmitt, Laura C.; Spindler, Kurt P.
2013-01-01
Background Current diagnostic strategies for detection of structural articular cartilage abnormalities, the earliest structural signs of osteoarthritis, often do not capture the condition until it is too far advanced for the most potential benefit of non-invasive interventions. Purpose Systematically review the literature relative to the following questions: (1) Is MRI a valid, sensitive, specific, accurate and reliable instrument to identify knee articular cartilage abnormalities compared to arthroscopy? (2) Is MRI a sensitive tool that can be utilized to identify early cartilage degeneration? Study Design Systematic Review Methods A systematic search was performed in November 2010 using PubMed MEDLINE (from 1966), CINAHL (from 1982), SPORTDiscus (from 1985), and SCOPUS (from 1996) databases. Results Fourteen level I and 13 level II studies were identified that met inclusion criteria and provided information related to diagnostic performance of MRI compared to arthroscopic evaluation. The diagnostic performance of MRI demonstrated a large range of sensitivities, specificities, and accuracies. The sensitivity for identifying articular cartilage abnormalities in the knee joint was reported between 26–96%. Specificity and accuracy was reported between 50–100% and 49–94%, respectively. The sensitivity, specificity, and accuracy for identifying early osteoarthritis were reported between 0–86%, 48–95%, and 5–94%, respectively. As a result of inconsistencies between imaging techniques and methodological shortcomings of many of the studies, a meta-analysis was not performed and it was difficult to fully synthesize the information to state firm conclusions about the diagnostic performance of MRI. Conclusions There is evidence in some MRI protocols that MRI is a relatively valid, sensitive, specific, accurate, and reliable clinical tool for identifying articular cartilage degeneration. Due to heterogeneity of MRI sequences it is not possible to make definitive conclusions regarding its global clinical utility for guiding diagnosis and treatment strategies. Clinical Relevance Traumatic sports injuries to the knee may be significant precursor events to early onset of posttraumatic osteoarthritis. MRI may aid in early identification of structural injuries to articular cartilage as evidenced by articular cartilage degeneration grading. PMID:21730207
A global sensitivity analysis approach for morphogenesis models.
Boas, Sonja E M; Navarro Jimenez, Maria I; Merks, Roeland M H; Blom, Joke G
2015-11-21
Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such 'black-box' models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of in silico sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all 'black-box' models, including high-throughput in vitro models in which output measures are affected by a set of experimental perturbations.
Gao, Yong; Zhu, Weimo
2011-05-01
The purpose of this study was to identify subgroup-sensitive physical activities (PA) using differential item functioning (DIF) analysis. A sub-unweighted sample of 1857 (men=923 and women=934) from the 2003-2004 National Health and Nutrition Examination Survey PA questionnaire data was used for the analyses. Using the Mantel-Haenszel, the simultaneous item bias test, and the ANOVA DIF methods, 33 specific leisure-time moderate and/or vigorous PA (MVPA) items were analyzed for DIF across race/ethnicity, gender, education, income, and age groups. Many leisure-time MVPA items were identified as large DIF items. When participating in the same amount of leisure-time MVPA, non-Hispanic blacks were more likely to participate in basketball and dance activities than non-Hispanic whites (NHW); NHW were more likely to participated in golf and hiking than non-Hispanic blacks; Hispanics were more likely to participate in dancing, hiking, and soccer than NHW, whereas NHW were more likely to engage in bicycling, golf, swimming, and walking than Hispanics; women were more likely to participate in aerobics, dancing, stretching, and walking than men, whereas men were more likely to engage in basketball, fishing, golf, running, soccer, weightlifting, and hunting than women; educated persons were more likely to participate in jogging and treadmill exercise than less educated persons; persons with higher incomes were more likely to engage in golf than those with lower incomes; and adults (20-59 yr) were more likely to participate in basketball, dancing, jogging, running, and weightlifting than older adults (60+ yr), whereas older adults were more likely to participate in walking and golf than younger adults. DIF methods are able to identify subgroup-sensitive PA and thus provide useful information to help design group-sensitive, targeted interventions for disadvantaged PA subgroups. © 2011 by the American College of Sports Medicine
Use of multi-criteria decision analysis to identify potentially dangerous glacial lakes.
Kougkoulos, Ioannis; Cook, Simon J; Jomelli, Vincent; Clarke, Leon; Symeonakis, Elias; Dortch, Jason M; Edwards, Laura A; Merad, Myriam
2018-04-15
Glacial Lake Outburst Floods (GLOFs) represent a significant threat in deglaciating environments, necessitating the development of GLOF hazard and risk assessment procedures. Here, we outline a Multi-Criteria Decision Analysis (MCDA) approach that can be used to rapidly identify potentially dangerous lakes in regions without existing tailored GLOF risk assessments, where a range of glacial lake types exist, and where field data are sparse or non-existent. Our MCDA model (1) is desk-based and uses freely and widely available data inputs and software, and (2) allows the relative risk posed by a range of glacial lake types to be assessed simultaneously within any region. A review of the factors that influence GLOF risk, combined with the strict rules of criteria selection inherent to MCDA, has allowed us to identify 13 exhaustive, non-redundant, and consistent risk criteria. We use our MCDA model to assess the risk of 16 extant glacial lakes and 6 lakes that have already generated GLOFs, and found that our results agree well with previous studies. For the first time in GLOF risk assessment, we employed sensitivity analyses to test the strength of our model results and assumptions, and to identify lakes that are sensitive to the criteria and risk thresholds used. A key benefit of the MCDA method is that sensitivity analyses are readily undertaken. Overall, these sensitivity analyses lend support to our model, although we suggest that further work is required to determine the relative importance of assessment criteria, and the thresholds that determine the level of risk for each criterion. As a case study, the tested method was then applied to 25 potentially dangerous lakes in the Bolivian Andes, where GLOF risk is poorly understood; 3 lakes are found to pose 'medium' or 'high' risk, and require further detailed investigation. Copyright © 2017 Elsevier B.V. All rights reserved.
Validation of a Low-Cost Paper-Based Screening Test for Sickle Cell Anemia
Piety, Nathaniel Z.; Yang, Xiaoxi; Kanter, Julie; Vignes, Seth M.; George, Alex; Shevkoplyas, Sergey S.
2016-01-01
Background The high childhood mortality and life-long complications associated with sickle cell anemia (SCA) in developing countries could be significantly reduced with effective prophylaxis and education if SCA is diagnosed early in life. However, conventional laboratory methods used for diagnosing SCA remain prohibitively expensive and impractical in this setting. This study describes the clinical validation of a low-cost paper-based test for SCA that can accurately identify sickle trait carriers (HbAS) and individuals with SCA (HbSS) among adults and children over 1 year of age. Methods and Findings In a population of healthy volunteers and SCA patients in the United States (n = 55) the test identified individuals whose blood contained any HbS (HbAS and HbSS) with 100% sensitivity and 100% specificity for both visual evaluation and automated analysis, and detected SCA (HbSS) with 93% sensitivity and 94% specificity for visual evaluation and 100% sensitivity and 97% specificity for automated analysis. In a population of post-partum women (with a previously unknown SCA status) at a primary obstetric hospital in Cabinda, Angola (n = 226) the test identified sickle cell trait carriers with 94% sensitivity and 97% specificity using visual evaluation (none of the women had SCA). Notably, our test permits instrument- and electricity-free visual diagnostics, requires minimal training to be performed, can be completed within 30 minutes, and costs about $0.07 in test-specific consumable materials. Conclusions Our results validate the paper-based SCA test as a useful low-cost tool for screening adults and children for sickle trait and disease and demonstrate its practicality in resource-limited clinical settings. PMID:26735691
Yokooji, Tomoharu; Kurihara, Saki; Murakami, Tomoko; Chinuki, Yuko; Takahashi, Hitoshi; Morita, Eishin; Harada, Susumu; Ishii, Kaori; Hiragun, Makiko; Hide, Michihiro; Matsuo, Hiroaki
2013-12-01
In Japan, hydrolyzed wheat proteins (HWP) have been reported to cause wheat-dependent exercise-induced anaphylaxis (WDEIA) by transcutaneous sensitization using HWP-containing soap. Patients develop allergic reactions not only with soap use, but also with exercise after the intake of wheat protein (WP). ω5-Gliadin and HMW-glutenin were identified as major allergens in conventional WP-WDEIA patients. However, the allergens in HWP-WDEIA have yet to be elucidated. Sera were obtained from 22 patients with HWP-sensitized WDEIA. The allergenic activities of HWP and six recombinant wheat gluten proteins, including α/β-, γ-, ω1,2- and ω5-gliadin and low- and high molecular weight (HMW)-glutenins, were characterized by immunoblot analysis and histamine releasing test. IgE-binding epitopes were identified using arrays of overlapping peptides synthesized on SPOTs membrane. Immunoblot analysis showed that IgE antibodies (Abs) from HWP-WDEIA bound to α/β-, γ- and ω1,2-gliadin. Recombinant γ-gliadin induced significant histamine release from basophils in eight of 11 patients with HWP-WDEIA. An IgE-binding epitope "QPQQPFPQ" was identified within the primary sequence of γ-gliadin, and the deamidated peptide containing the "PEEPFP" sequence bound with IgE Abs more strongly compared to the native epitope-peptide. The epitope-peptide inhibited IgE-binding to HWP, indicating that the specific IgE to HWP cross-reacts with γ-gliadin. HWP-WDEIA patients could be sensitized to HWP containing a PEEPFP sequence, and WDEIA symptoms after WP ingestion could partly be induced by γ-gliadin. These findings could be useful to help develop tools for diagnosis and desensitization therapy for HWP-WDEIA.
Edwards, Sian E; Grobman, William A; Lappen, Justin R; Winter, Cathy; Fox, Robert; Lenguerrand, Erik; Draycott, Timothy
2015-04-01
We sought to compare the predictive power of published modified obstetric early warning scoring systems (MOEWS) for the development of severe sepsis in women with chorioamnionitis. This was a retrospective cohort study using prospectively collected clinical observations at a single tertiary unit (Chicago, IL). Hospital databases and patient records were searched to identify and verify cases with clinically diagnosed chorioamnionitis during the study period (June 2006 through November 2007). Vital sign data (heart rate, respiratory rate, blood pressure, temperature, mental state) for these cases were extracted from an electronic database and the single worst composite recording was identified for analysis. Global literature databases were searched (2014) to identify examples of MOEWS. Scores for each identified MOEWS were derived from each set of vital sign recordings during the presentation with chorioamnionitis. The performance of these MOEWS (the primary outcome) was then analyzed and compared using their sensitivity, specificity, positive and negative predictive values, and receiver-operating characteristic curve for severe sepsis. Six MOEWS were identified. There was wide variation in design and pathophysiological thresholds used for clinical alerts. In all, 913 women with chorioamnionitis were identified from the clinical database. In all, 364 cases with complete data for all physiological indicators were included in analysis. Five women developed severe sepsis, including 1 woman who died. The sensitivities of the MOEWS in predicting the severe deterioration ranged from 40-100% and the specificities varied even more ranging from 4-97%. The positive predictive values were low for all MOEWS ranging from <2-15%. The MOEWS with simpler designs tended to be more sensitive, whereas the more complex MOEWS were more specific, but failed to identify some of the women who developed severe sepsis. Currently used MOEWS vary widely in terms of alert thresholds, format, and accuracy. Most MOEWS have not been validated. The MOEWS generally performed poorly in predicting severe sepsis in obstetric patients; in general severe sepsis was overdetected. Simple MOEWS with high sensitivity followed with more specific secondary testing is likely to be the best way forward. Further research is required to develop early warning systems for use in this setting. Copyright © 2015 Elsevier Inc. All rights reserved.
Dulai, Parambir S; Boland, Brigid S; Singh, Siddharth; Chaudrey, Khadija; Koliani-Pace, Jenna L; Kochhar, Gursimran; Parikh, Malav P; Shmidt, Eugenia; Hartke, Justin; Chilukuri, Prianka; Meserve, Joseph; Whitehead, Diana; Hirten, Robert; Winters, Adam C; Katta, Leah G; Peerani, Farhad; Narula, Neeraj; Sultan, Keith; Swaminath, Arun; Bohm, Matthew; Lukin, Dana; Hudesman, David; Chang, John T; Rivera-Nieves, Jesus; Jairath, Vipul; Zou, G Y; Feagan, Brian G; Shen, Bo; Siegel, Corey A; Loftus, Edward V; Kane, Sunanda; Sands, Bruce E; Colombel, Jean-Frederic; Sandborn, William J; Lasch, Karen; Cao, Charlie
2018-05-29
As more treatment options for inflammatory bowel diseases become available, it is important to identify patients most likely to respond to different therapies. We created and validated a scoring system to identify patients with Crohn's disease (CD) who respond to vedolizumab. We collected data from GEMINI 2 phase 3 trial of patients with active CD treated with vedolizumab for 26 weeks (n=814) and performed logistic regression analysis to identify factors associated with clinical, steroid-free, and durable remission (derivation set). We used these data to develop a clinical decision support tool, which we validated using data from 366 participants in a separate clinical practice observational cohort of patients with active CD treated with vedolizumab for 26 weeks (the VICTORY cohort). We evaluated the ability of this tool to identify patients in clinical remission or corticosteroid-free remission, or those with mucosal healing (MH), clinical remission with MH, or corticosteroid-free remission with MH after vedolizumab therapy using receiver operating characteristic area under the curve (AUC) analyses. The primary outcome was to develop and validate a list of factors associated with achieving remission by vedolizumab in patients with active CD. In the derivation analysis, we identified absence of previous treatment with a tumor necrosis factor antagonist (+3 points), absence of prior bowel surgery (+2 points), absence of prior fistulizing disease (+2 points), baseline level of albumin (+0.4 points per g/L), and baseline concentration of C-reactive protein (reduction of 0.5 points for values between 3.0-10.0 mg/L and 3.0 points for values > 10.0 mg/L) as factors associated with remission. In the validation set, our model identified patients in clinical remission with an AUC of 0.67, patients in corticosteroid-free remission with an AUC of 0.66, patients with MH with an AUC of 0.72, patients in clinical remission with MH with an AUC of 0.73, and patients in corticosteroid-free clinical remission with MH with an AUC of 0.75. A cut-off value of 13 points identified patients in clinical remission after vedolizumab therapy with 92% sensitivity, patients in corticosteroid-free remission with 94% sensitivity, patients with MH with 98% sensitivity, patients in deep remission with 100% sensitivity, and patients with corticosteroid-free clinical remission with MH with 100% sensitivity. We developed and validated a scoring system to identify patients with CD most likely to respond to 26 weeks of vedolizumab therapy. Further studies are needed to optimize its accuracy in select populations and determine its cost effectiveness. Copyright © 2018 AGA Institute. Published by Elsevier Inc. All rights reserved.
Applying causal mediation analysis to personality disorder research.
Walters, Glenn D
2018-01-01
This article is designed to address fundamental issues in the application of causal mediation analysis to research on personality disorders. Causal mediation analysis is used to identify mechanisms of effect by testing variables as putative links between the independent and dependent variables. As such, it would appear to have relevance to personality disorder research. It is argued that proper implementation of causal mediation analysis requires that investigators take several factors into account. These factors are discussed under 5 headings: variable selection, model specification, significance evaluation, effect size estimation, and sensitivity testing. First, care must be taken when selecting the independent, dependent, mediator, and control variables for a mediation analysis. Some variables make better mediators than others and all variables should be based on reasonably reliable indicators. Second, the mediation model needs to be properly specified. This requires that the data for the analysis be prospectively or historically ordered and possess proper causal direction. Third, it is imperative that the significance of the identified pathways be established, preferably with a nonparametric bootstrap resampling approach. Fourth, effect size estimates should be computed or competing pathways compared. Finally, investigators employing the mediation method are advised to perform a sensitivity analysis. Additional topics covered in this article include parallel and serial multiple mediation designs, moderation, and the relationship between mediation and moderation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Sensitivity analysis and approximation methods for general eigenvalue problems
NASA Technical Reports Server (NTRS)
Murthy, D. V.; Haftka, R. T.
1986-01-01
Optimization of dynamic systems involving complex non-hermitian matrices is often computationally expensive. Major contributors to the computational expense are the sensitivity analysis and reanalysis of a modified design. The present work seeks to alleviate this computational burden by identifying efficient sensitivity analysis and approximate reanalysis methods. For the algebraic eigenvalue problem involving non-hermitian matrices, algorithms for sensitivity analysis and approximate reanalysis are classified, compared and evaluated for efficiency and accuracy. Proper eigenvector normalization is discussed. An improved method for calculating derivatives of eigenvectors is proposed based on a more rational normalization condition and taking advantage of matrix sparsity. Important numerical aspects of this method are also discussed. To alleviate the problem of reanalysis, various approximation methods for eigenvalues are proposed and evaluated. Linear and quadratic approximations are based directly on the Taylor series. Several approximation methods are developed based on the generalized Rayleigh quotient for the eigenvalue problem. Approximation methods based on trace theorem give high accuracy without needing any derivatives. Operation counts for the computation of the approximations are given. General recommendations are made for the selection of appropriate approximation technique as a function of the matrix size, number of design variables, number of eigenvalues of interest and the number of design points at which approximation is sought.
POSSIBLE ROLE OF INDOOR RADON REDUCTION SYSTEMS IN BACK-DRAFTING RESIDENTIAL COMBUSTION APPLIANCES
The article gives results of a computational sensitivity analysis conducted to identify conditions under which residential active soil depressurization (ASD) systems for indoor radon reduction might contribute to or create back-drafting of natural draft combustion appliances. Par...
Pavement thickness design for local roads in Iowa : tech brief.
DOT National Transportation Integrated Search
2010-01-01
The main objectives of this research are to: 1) identify the most critical design input parameters, 2) determine the minimum pavement thickness, and 3) develop new pavement design and sensitivity analysis (PD&SA) software which can provide the most a...
Barratt, M D; Langowski, J J
1999-01-01
The DEREK knowledge-based computer system contains a subset of approximately 50 rules describing chemical substructures (toxophores) responsible for skin sensitization. This rulebase, based originally on Unilever historical in-house guinea pig maximization test data, has been subject to extensive validation and is undergoing refinement as the next stage of its development. As part of an ongoing program of validation and testing, the predictive ability of the sensitization rule set has been assessed by processing the structures of the 84 chemical substances in the list of contact allergens issued by the BgVV (German Federal Institute for Health Protection of Consumers). This list of chemicals is important because the biological data for each of the chemicals have been carefully scrutinized and peer reviewed, a key consideration in an area of toxicology in which much unreliable and potentially misleading data have been published. The existing DEREK rulebase for skin sensitization identified toxophores for skin sensitization in the structures of 71 out of the 84 chemicals (85%). The exercise highlighted areas of chemistry where further development of the rulebase was required, either by extension of the scope of existing rules or by generation of new rules where a sound mechanistic rationale for the biological activity could be established. Chemicals likely to be acting as photoallergens were identified, and new rules for photoallergenicity have subsequently been written. At the end of the exercise, the refined rulebase was able to identify toxophores for skin sensitization for 82 of the 84 chemicals in the BgVV list.
Macera, Annalisa; Lario, Chiara; Petracchini, Massimo; Gallo, Teresa; Regge, Daniele; Floriani, Irene; Ribero, Dario; Capussotti, Lorenzo; Cirillo, Stefano
2013-03-01
To compare the diagnostic accuracy and sensitivity of Gd-EOB-DTPA MRI and diffusion-weighted (DWI) imaging alone and in combination for detecting colorectal liver metastases in patients who had undergone preoperative chemotherapy. Thirty-two consecutive patients with a total of 166 liver lesions were retrospectively enrolled. Of the lesions, 144 (86.8 %) were metastatic at pathology. Three image sets (1, Gd-EOB-DTPA; 2, DWI; 3, combined Gd-EOB-DTPA and DWI) were independently reviewed by two observers. Statistical analysis was performed on a per-lesion basis. Evaluation of image set 1 correctly identified 127/166 lesions (accuracy 76.5 %; 95 % CI 69.3-82.7) and 106/144 metastases (sensitivity 73.6 %, 95 % CI 65.6-80.6). Evaluation of image set 2 correctly identified 108/166 (accuracy 65.1 %, 95 % CI 57.3-72.3) and 87/144 metastases (sensitivity of 60.4 %, 95 % CI 51.9-68.5). Evaluation of image set 3 correctly identified 148/166 (accuracy 89.2 %, 95 % CI 83.4-93.4) and 131/144 metastases (sensitivity 91 %, 95 % CI 85.1-95.1). Differences were statistically significant (P < 0.001). Notably, similar results were obtained analysing only small lesions (<1 cm). The combination of DWI with Gd-EOB-DTPA-enhanced MRI imaging significantly increases the diagnostic accuracy and sensitivity in patients with colorectal liver metastases treated with preoperative chemotherapy, and it is particularly effective in the detection of small lesions.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hagos, Samson M.; Leung, Lai-Yung R.; Gustafson, William I.
2014-02-28
A multi-scale moisture budget analysis is used to identify the mechanisms responsible for the sensitivity of the water cycle to spatial resolution using idealized regional aquaplanet simulations. In the higher resolution simulations, moisture transport by eddies fluxes dry the boundary layer enhancing evaporation and precipitation. This effect of eddies, which is underestimated by the physics parameterizations in the low-resolution simulations, is found to be responsible for the sensitivity of the water cycle both directly, and through its upscale effect, on the mean circulation. Correlations among moisture transport by eddies at adjacent ranges of scales provides the potential for reducing thismore » sensitivity by representing the unresolved eddies by their marginally resolved counterparts.« less
Luo, Mingxu; Song, Hongmei; Liu, Gang; Lin, Yikai; Luo, Lintao; Zhou, Xin; Chen, Bo
2017-01-01
The diagnostic values of diffusion weighted imaging (DWI) and 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) for N-staging of gastric cancer (GC) were identified and compared. After a systematic search to identify relevant articles, meta-analysis was used to summarize the sensitivities, specificities, and areas under curves (AUCs) for DWI and PET/CT. To better understand the diagnostic utility of DWI and PET/CT for N-staging, the performance of multi-detector computed tomography (MDCT) was used as a reference. Fifteen studies were analyzed. The pooled sensitivity, specificity, and AUC with 95% confidence intervals of DWI were 0.79 (0.73–0.85), 0.69 (0.61–0.77), and 0.81 (0.77–0.84), respectively. For PET/CT, the corresponding values were 0.52 (0.39–0.64), 0.88 (0.61–0.97), and 0.66 (0.62–0.70), respectively. Comparison of the two techniques revealed DWI had higher sensitivity and AUC, but no difference in specificity. DWI exhibited higher sensitivity but lower specificity than MDCT, and 18F-FDG PET/CT had lower sensitivity and equivalent specificity. Overall, DWI performed better than 18F-FDG PET/CT for preoperative N-staging in GC. When the efficacy of MDCT was taken as a reference, DWI represented a complementary imaging technique, while 18F-FDG PET/CT had limited utility for preoperative N-staging. PMID:29137440
Yoo, Doo Han; Lee, Jae Shin
2016-07-01
[Purpose] This study examined the clinical usefulness of the clock drawing test applying Rasch analysis for predicting the level of cognitive impairment. [Subjects and Methods] A total of 187 stroke patients with cognitive impairment were enrolled in this study. The 187 patients were evaluated by the clock drawing test developed through Rasch analysis along with the mini-mental state examination of cognitive evaluation tool. An analysis of the variance was performed to examine the significance of the mini-mental state examination and the clock drawing test according to the general characteristics of the subjects. Receiver operating characteristic analysis was performed to determine the cutoff point for cognitive impairment and to calculate the sensitivity and specificity values. [Results] The results of comparison of the clock drawing test with the mini-mental state showed significant differences in according to gender, age, education, and affected side. A total CDT of 10.5, which was selected as the cutoff point to identify cognitive impairement, showed a sensitivity, specificity, Youden index, positive predictive, and negative predicive values of 86.4%, 91.5%, 0.8, 95%, and 88.2%. [Conclusion] The clock drawing test is believed to be useful in assessments and interventions based on its excellent ability to identify cognitive disorders.
Zhu, Zhou; Ihle, Nathan T; Rejto, Paul A; Zarrinkar, Patrick P
2016-06-13
Genome-scale functional genomic screens across large cell line panels provide a rich resource for discovering tumor vulnerabilities that can lead to the next generation of targeted therapies. Their data analysis typically has focused on identifying genes whose knockdown enhances response in various pre-defined genetic contexts, which are limited by biological complexities as well as the incompleteness of our knowledge. We thus introduce a complementary data mining strategy to identify genes with exceptional sensitivity in subsets, or outlier groups, of cell lines, allowing an unbiased analysis without any a priori assumption about the underlying biology of dependency. Genes with outlier features are strongly and specifically enriched with those known to be associated with cancer and relevant biological processes, despite no a priori knowledge being used to drive the analysis. Identification of exceptional responders (outliers) may not lead only to new candidates for therapeutic intervention, but also tumor indications and response biomarkers for companion precision medicine strategies. Several tumor suppressors have an outlier sensitivity pattern, supporting and generalizing the notion that tumor suppressors can play context-dependent oncogenic roles. The novel application of outlier analysis described here demonstrates a systematic and data-driven analytical strategy to decipher large-scale functional genomic data for oncology target and precision medicine discoveries.
Sensitivity of quantitative EEG for seizure identification in the intensive care unit.
Haider, Hiba A; Esteller, Rosana; Hahn, Cecil D; Westover, M Brandon; Halford, Jonathan J; Lee, Jong W; Shafi, Mouhsin M; Gaspard, Nicolas; Herman, Susan T; Gerard, Elizabeth E; Hirsch, Lawrence J; Ehrenberg, Joshua A; LaRoche, Suzette M
2016-08-30
To evaluate the sensitivity of quantitative EEG (QEEG) for electrographic seizure identification in the intensive care unit (ICU). Six-hour EEG epochs chosen from 15 patients underwent transformation into QEEG displays. Each epoch was reviewed in 3 formats: raw EEG, QEEG + raw, and QEEG-only. Epochs were also analyzed by a proprietary seizure detection algorithm. Nine neurophysiologists reviewed raw EEGs to identify seizures to serve as the gold standard. Nine other neurophysiologists with experience in QEEG evaluated the epochs in QEEG formats, with and without concomitant raw EEG. Sensitivity and false-positive rates (FPRs) for seizure identification were calculated and median review time assessed. Mean sensitivity for seizure identification ranged from 51% to 67% for QEEG-only and 63%-68% for QEEG + raw. FPRs averaged 1/h for QEEG-only and 0.5/h for QEEG + raw. Mean sensitivity of seizure probability software was 26.2%-26.7%, with FPR of 0.07/h. Epochs with the highest sensitivities contained frequent, intermittent seizures. Lower sensitivities were seen with slow-frequency, low-amplitude seizures and epochs with rhythmic or periodic patterns. Median review times were shorter for QEEG (6 minutes) and QEEG + raw analysis (14.5 minutes) vs raw EEG (19 minutes; p = 0.00003). A panel of QEEG trends can be used by experts to shorten EEG review time for seizure identification with reasonable sensitivity and low FPRs. The prevalence of false detections confirms that raw EEG review must be used in conjunction with QEEG. Studies are needed to identify optimal QEEG trend configurations and the utility of QEEG as a screening tool for non-EEG personnel. This study provides Class II evidence that QEEG + raw interpreted by experts identifies seizures in patients in the ICU with a sensitivity of 63%-68% and FPR of 0.5 seizures per hour. © 2016 American Academy of Neurology.
Silvester, Jocelyn A; Kurada, Satya; Szwajcer, Andrea; Kelly, Ciarán P; Leffler, Daniel A; Duerksen, Donald R
2017-09-01
Tests to measure serum endomysial antibodies (EMA) and antibodies to tissue transglutaminase (tTG) were developed to screen for celiac disease in patients consuming gluten. However, they are commonly used to monitor patients on a gluten-free diet (GFD). We conducted a meta-analysis to assess the sensitivity and specificity of tTG IgA and EMA IgA assays in identifying patients with celiac disease who have persistent villous atrophy despite a GFD. We searched PUBMED, EMBASE, BIOSIS, SCOPUS, clinicaltrials.gov, Science Citation Index, and Cochrane Library databases through November 2016. Inclusion criteria were studies of subjects with biopsy-confirmed celiac disease, follow-up biopsies, and measurement of serum antibodies on a GFD, biopsy performed on subjects regardless of symptoms, or antibody test results. Our analysis excluded subjects with refractory celiac disease, undergoing gluten challenge, or consuming a prescribed oats-containing GFD. Tests were considered to have positive or negative findings based on manufacturer cut-off values. Villous atrophy was defined as a Marsh 3 lesion or villous height:crypt depth ratio below 3.0. We constructed forest plots to determine the sensitivity and specificity of detection for individual studies. For the meta-analysis, a bivariate random effects model was used to jointly model sensitivity and specificity. Our search identified 5408 unique citations. Following review of abstracts, 442 articles were reviewed in detail. Only 26 studies (6 of tTG assays, 15 of EMA assays, and 5 of tTG and EMA assays) met our inclusion criteria. The most common reason studies were excluded from our analysis was inability to cross-tabulate histologic and serologic findings. The serum assays identified patients with persistent villous atrophy with high levels of specificity: 0.83 for the tTG IgA assay (95% CI, 0.79-0.87) and 0.91 for the EMA IgA assay (95% CI, 0.87-0.94). However, they detected villous atrophy with low levels of sensitivity: 0.50 for the tTG IgA assay (95% CI, 0.41-0.60) and 0.45 for the EMA IgA assay (95% CI, 0.34-0.57). The tests had similar levels of performance in pediatric and adult patients. In a meta-analysis of patients with biopsy-confirmed celiac disease undergoing follow-up biopsy on a GFD, we found that tests for serum tTG IgA and EMA IgA levels had low sensitivity (below 50%) in detection of persistent villous atrophy. We need more-accurate non-invasive markers of mucosal damage in children and adults with celiac disease who are following a GFD. Copyright © 2017 AGA Institute. Published by Elsevier Inc. All rights reserved.
Hill, Mary C.
2010-01-01
Doherty and Hunt (2009) present important ideas for first-order-second moment sensitivity analysis, but five issues are discussed in this comment. First, considering the composite-scaled sensitivity (CSS) jointly with parameter correlation coefficients (PCC) in a CSS/PCC analysis addresses the difficulties with CSS mentioned in the introduction. Second, their new parameter identifiability statistic actually is likely to do a poor job of parameter identifiability in common situations. The statistic instead performs the very useful role of showing how model parameters are included in the estimated singular value decomposition (SVD) parameters. Its close relation to CSS is shown. Third, the idea from p. 125 that a suitable truncation point for SVD parameters can be identified using the prediction variance is challenged using results from Moore and Doherty (2005). Fourth, the relative error reduction statistic of Doherty and Hunt is shown to belong to an emerging set of statistics here named perturbed calculated variance statistics. Finally, the perturbed calculated variance statistics OPR and PPR mentioned on p. 121 are shown to explicitly include the parameter null-space component of uncertainty. Indeed, OPR and PPR results that account for null-space uncertainty have appeared in the literature since 2000.
Richardson, Rodney T.; Lin, Chia-Hua; Sponsler, Douglas B.; Quijia, Juan O.; Goodell, Karen; Johnson, Reed M.
2015-01-01
• Premise of the study: Melissopalynology, the identification of bee-collected pollen, provides insight into the flowers exploited by foraging bees. Information provided by melissopalynology could guide floral enrichment efforts aimed at supporting pollinators, but it has rarely been used because traditional methods of pollen identification are laborious and require expert knowledge. We approach melissopalynology in a novel way, employing a molecular method to study the pollen foraging of honey bees (Apis mellifera) in a landscape dominated by field crops, and compare these results to those obtained by microscopic melissopalynology. • Methods: Pollen was collected from honey bee colonies in Madison County, Ohio, USA, during a two-week period in midspring and identified using microscopic methods and ITS2 metabarcoding. • Results: Metabarcoding identified 19 plant families and exhibited sensitivity for identifying the taxa present in large and diverse pollen samples relative to microscopy, which identified eight families. The bulk of pollen collected by honey bees was from trees (Sapindaceae, Oleaceae, and Rosaceae), although dandelion (Taraxacum officinale) and mustard (Brassicaceae) pollen were also abundant. • Discussion: For quantitative analysis of pollen, using both metabarcoding and microscopic identification is superior to either individual method. For qualitative analysis, ITS2 metabarcoding is superior, providing heightened sensitivity and genus-level resolution. PMID:25606352
Richardson, Rodney T; Lin, Chia-Hua; Sponsler, Douglas B; Quijia, Juan O; Goodell, Karen; Johnson, Reed M
2015-01-01
Melissopalynology, the identification of bee-collected pollen, provides insight into the flowers exploited by foraging bees. Information provided by melissopalynology could guide floral enrichment efforts aimed at supporting pollinators, but it has rarely been used because traditional methods of pollen identification are laborious and require expert knowledge. We approach melissopalynology in a novel way, employing a molecular method to study the pollen foraging of honey bees (Apis mellifera) in a landscape dominated by field crops, and compare these results to those obtained by microscopic melissopalynology. • Pollen was collected from honey bee colonies in Madison County, Ohio, USA, during a two-week period in midspring and identified using microscopic methods and ITS2 metabarcoding. • Metabarcoding identified 19 plant families and exhibited sensitivity for identifying the taxa present in large and diverse pollen samples relative to microscopy, which identified eight families. The bulk of pollen collected by honey bees was from trees (Sapindaceae, Oleaceae, and Rosaceae), although dandelion (Taraxacum officinale) and mustard (Brassicaceae) pollen were also abundant. • For quantitative analysis of pollen, using both metabarcoding and microscopic identification is superior to either individual method. For qualitative analysis, ITS2 metabarcoding is superior, providing heightened sensitivity and genus-level resolution.
Taly, Valerie; Pekin, Deniz; Benhaim, Leonor; Kotsopoulos, Steve K; Le Corre, Delphine; Li, Xinyu; Atochin, Ivan; Link, Darren R; Griffiths, Andrew D; Pallier, Karine; Blons, Hélène; Bouché, Olivier; Landi, Bruno; Hutchison, J Brian; Laurent-Puig, Pierre
2013-12-01
Multiplex digital PCR (dPCR) enables noninvasive and sensitive detection of circulating tumor DNA with performance unachievable by current molecular-detection approaches. Furthermore, picodroplet dPCR facilitates simultaneous screening for multiple mutations from the same sample. We investigated the utility of multiplex dPCR to screen for the 7 most common mutations in codons 12 and 13 of the KRAS (Kirsten rat sarcoma viral oncogene homolog) oncogene from plasma samples of patients with metastatic colorectal cancer. Fifty plasma samples were tested from patients for whom the primary tumor biopsy tissue DNA had been characterized by quantitative PCR. Tumor characterization revealed that 19 patient tumors had KRAS mutations. Multiplex dPCR analysis of the plasma DNA prepared from these samples identified 14 samples that matched the mutation identified in the tumor, 1 sample contained a different KRAS mutation, and 4 samples had no detectable mutation. Among the tumor samples that were wild type for KRAS, 2 KRAS mutations were identified in the corresponding plasma samples. Duplex dPCR (i.e., wild-type and single-mutation assay) was also used to analyze plasma samples from patients with KRAS-mutated tumors and 5 samples expected to contain the BRAF (v-raf murine sarcoma viral oncogene homolog B) V600E mutation. The results for the duplex analysis matched those for the multiplex analysis for KRAS-mutated samples and, owing to its higher sensitivity, enabled detection of 2 additional samples with low levels of KRAS-mutated DNA. All 5 samples with BRAF mutations were detected. This work demonstrates the clinical utility of multiplex dPCR to screen for multiple mutations simultaneously with a sensitivity sufficient to detect mutations in circulating DNA obtained by noninvasive blood collection.
Zhan, Xianquan; Yang, Haiyan; Peng, Fang; Li, Jianglin; Mu, Yun; Long, Ying; Cheng, Tingting; Huang, Yuda; Li, Zhao; Lu, Miaolong; Li, Na; Li, Maoyu; Liu, Jianping; Jungblut, Peter R
2018-04-01
Two-dimensional gel electrophoresis (2DE) in proteomics is traditionally assumed to contain only one or two proteins in each 2DE spot. However, 2DE resolution is being complemented by the rapid development of high sensitivity mass spectrometers. Here we compared MALDI-MS, LC-Q-TOF MS and LC-Orbitrap Velos MS for the identification of proteins within one spot. With LC-Orbitrap Velos MS each Coomassie Blue-stained 2DE spot contained an average of at least 42 and 63 proteins/spot in an analysis of a human glioblastoma proteome and a human pituitary adenoma proteome, respectively, if a single gel spot was analyzed. If a pool of three matched gel spots was analyzed this number further increased up to an average of 230 and 118 proteins/spot for glioblastoma and pituitary adenoma proteome, respectively. Multiple proteins per spot confirm the necessity of isotopic labeling in large-scale quantification of different protein species in a proteome. Furthermore, a protein abundance analysis revealed that most of the identified proteins in each analyzed 2DE spot were low-abundance proteins. Many proteins were present in several of the analyzed spots showing the ability of 2DE-MS to separate at the protein species level. Therefore, 2DE coupled with high-sensitivity LC-MS has a clearly higher sensitivity as expected until now to detect, identify and quantify low abundance proteins in a complex human proteome with an estimated resolution of about 500 000 protein species. This clearly exceeds the resolution power of bottom-up LC-MS investigations. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Probabilistic structural analysis of a truss typical for space station
NASA Technical Reports Server (NTRS)
Pai, Shantaram S.
1990-01-01
A three-bay, space, cantilever truss is probabilistically evaluated using the computer code NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) to identify and quantify the uncertainties and respective sensitivities associated with corresponding uncertainties in the primitive variables (structural, material, and loads parameters) that defines the truss. The distribution of each of these primitive variables is described in terms of one of several available distributions such as the Weibull, exponential, normal, log-normal, etc. The cumulative distribution function (CDF's) for the response functions considered and sensitivities associated with the primitive variables for given response are investigated. These sensitivities help in determining the dominating primitive variables for that response.
Utility of salivary biomarkers for demonstrating acute myocardial infarction.
Miller, C S; Foley, J D; Floriano, P N; Christodoulides, N; Ebersole, J L; Campbell, C L; Bailey, A L; Rose, B G; Kinane, D F; Novak, M J; McDevitt, J T; Ding, X; Kryscio, R J
2014-07-01
The comparative utility of serum and saliva as diagnostic fluids for identifying biomarkers of acute myocardial infarction (AMI) was investigated. The goal was to determine if salivary biomarkers could facilitate a screening diagnosis of AMI, especially in cases of non-ST elevation MI (NSTEMI), since these cases are not readily identified by electrocardiogram (ECG). Serum and unstimulated whole saliva (UWS) collected from 92 AMI patients within 48 hours of chest pain onset and 105 asymptomatic healthy control individuals were assayed for 13 proteins relevant to cardiovascular disease, by Beadlyte technology (Luminex(®)) and enzyme immunoassays. Data were analyzed with concentration cut-points, ECG findings, logistic regression (LR) (adjusted for matching for age, gender, race, smoking, number of teeth, and oral health status), and classification and regression tree (CART) analysis. A sensitivity analysis was conducted by repetition of the CART analysis in 58 cases and 58 controls, each matched by age and gender. Serum biomarkers demonstrated AMI sensitivity and specificity superior to that of saliva, as determined by LR and CART. The predominant discriminators in serum by LR were troponin I (TnI), B-type natriuretic peptide (BNP), and creatine kinase-MB (CK-MB), and TnI and BNP by CART. In saliva, LR identified C-reactive protein (CRP) as the biomarker most predictive of AMI. A combination of smoking tobacco, UWS CRP, CK-MB, sCD40 ligand, gender, and number of teeth identified AMI in the CART decision trees. When ECG findings, salivary biomarkers, and confounders were included, AMI was predicted with 80.0% sensitivity and 100% specificity. These analyses support the potential utility of salivary biomarker measurements used with ECG for the identification of AMI. Thus, saliva-based tests may provide additional diagnostic screening information in the clinical course for patients suspected of having an AMI. © International & American Associations for Dental Research.
Fyn-Dependent Gene Networks in Acute Ethanol Sensitivity
Farris, Sean P.; Miles, Michael F.
2013-01-01
Studies in humans and animal models document that acute behavioral responses to ethanol are predisposing factor for the risk of long-term drinking behavior. Prior microarray data from our laboratory document strain- and brain region-specific variation in gene expression profile responses to acute ethanol that may be underlying regulators of ethanol behavioral phenotypes. The non-receptor tyrosine kinase Fyn has previously been mechanistically implicated in the sedative-hypnotic response to acute ethanol. To further understand how Fyn may modulate ethanol behaviors, we used whole-genome expression profiling. We characterized basal and acute ethanol-evoked (3 g/kg) gene expression patterns in nucleus accumbens (NAC), prefrontal cortex (PFC), and ventral midbrain (VMB) of control and Fyn knockout mice. Bioinformatics analysis identified a set of Fyn-related gene networks differently regulated by acute ethanol across the three brain regions. In particular, our analysis suggested a coordinate basal decrease in myelin-associated gene expression within NAC and PFC as an underlying factor in sensitivity of Fyn null animals to ethanol sedation. An in silico analysis across the BXD recombinant inbred (RI) strains of mice identified a significant correlation between Fyn expression and a previously published ethanol loss-of-righting-reflex (LORR) phenotype. By combining PFC gene expression correlates to Fyn and LORR across multiple genomic datasets, we identified robust Fyn-centric gene networks related to LORR. Our results thus suggest that multiple system-wide changes exist within specific brain regions of Fyn knockout mice, and that distinct Fyn-dependent expression networks within PFC may be important determinates of the LORR due to acute ethanol. These results add to the interpretation of acute ethanol behavioral sensitivity in Fyn kinase null animals, and identify Fyn-centric gene networks influencing variance in ethanol LORR. Such networks may also inform future design of pharmacotherapies for the treatment and prevention of alcohol use disorders. PMID:24312422
Greenspan, Joel D.; Slade, Gary D.; Bair, Eric; Dubner, Ronald; Fillingim, Roger B.; Ohrbach, Richard; Knott, Charlie; Mulkey, Flora; Rothwell, Rebecca; Maixner, William
2011-01-01
Many studies report that people with temporomandibular disorders (TMD) are more sensitive to experimental pain stimuli than TMD-free controls. Such differences in sensitivity are observed in remote body sites as well as in the orofacial region, suggesting a generalized upregulation of nociceptive processing in TMD cases. This large case-control study of 185 adults with TMD and 1,633 TMD-free controls measured sensitivity to painful pressure, mechanical cutaneous, and heat stimuli, using multiple testing protocols. Based on an unprecedented 36 experimental pain measures, 28 showed statistically significantly greater pain sensitivity in TMD cases than controls. The largest effects were seen for pressure pain thresholds at multiple body sites and cutaneous mechanical pain threshold. The other mechanical cutaneous pain measures and many of the heat pain measures showed significant differences, but with lesser effect sizes. Principal component analysis (PCA) of the pain measures derived from 1,633 controls identified five components labeled: (1) heat pain ratings, (2) heat pain aftersensations and tolerance, (3) mechanical cutaneous pain sensitivity, (4) pressure pain thresholds, and (5) heat pain temporal summation. These results demonstrate that, compared to TMD-free controls, chronic TMD cases are more sensitive to many experimental noxious stimuli at extra-cranial body sites, and provides for the first time the ability to directly compare the case-control effect sizes of a wide range of pain sensitivity measures. PMID:22074753
Relevant Feature Set Estimation with a Knock-out Strategy and Random Forests
Ganz, Melanie; Greve, Douglas N.; Fischl, Bruce; Konukoglu, Ender
2015-01-01
Group analysis of neuroimaging data is a vital tool for identifying anatomical and functional variations related to diseases as well as normal biological processes. The analyses are often performed on a large number of highly correlated measurements using a relatively smaller number of samples. Despite the correlation structure, the most widely used approach is to analyze the data using univariate methods followed by post-hoc corrections that try to account for the data’s multivariate nature. Although widely used, this approach may fail to recover from the adverse effects of the initial analysis when local effects are not strong. Multivariate pattern analysis (MVPA) is a powerful alternative to the univariate approach for identifying relevant variations. Jointly analyzing all the measures, MVPA techniques can detect global effects even when individual local effects are too weak to detect with univariate analysis. Current approaches are successful in identifying variations that yield highly predictive and compact models. However, they suffer from lessened sensitivity and instabilities in identification of relevant variations. Furthermore, current methods’ user-defined parameters are often unintuitive and difficult to determine. In this article, we propose a novel MVPA method for group analysis of high-dimensional data that overcomes the drawbacks of the current techniques. Our approach explicitly aims to identify all relevant variations using a “knock-out” strategy and the Random Forest algorithm. In evaluations with synthetic datasets the proposed method achieved substantially higher sensitivity and accuracy than the state-of-the-art MVPA methods, and outperformed the univariate approach when the effect size is low. In experiments with real datasets the proposed method identified regions beyond the univariate approach, while other MVPA methods failed to replicate the univariate results. More importantly, in a reproducibility study with the well-known ADNI dataset the proposed method yielded higher stability and power than the univariate approach. PMID:26272728
Pietrowska, M; Marczak, L; Polanska, J; Nowicka, E; Behrent, K; Tarnawski, R; Stobiecki, M; Polanski, A; Widlak, P
2010-01-01
Mass spectrometry-based analysis of the serum proteome allows identifying multi-peptide patterns/signatures specific for blood of cancer patients, thus having high potential value for cancer diagnostics. However, because of problems with optimization and standardization of experimental and computational design, none of identified proteome patterns/signatures was approved for diagnostics in clinical practice as yet. Here we compared two methods of serum sample preparation for mass spectrometry-based proteome pattern analysis aimed to identify biomarkers that could be used in early detection of breast cancer patients. Blood samples were collected in a group of 92 patients diagnosed at early (I and II) stages of the disease before the start of therapy, and in a group of age-matched healthy controls (104 women). Serum specimens were purified and analyzed using MALDI-ToF spectrometry, either directly or after membrane filtration (50 kDa cut-off) to remove albumin and other large serum proteins. Mass spectra of the low-molecular-weight fraction (2-10 kDa) of the serum proteome were resolved using the Gaussian mixture decomposition, and identified spectral components were used to build classifiers that differentiated samples from breast cancer patients and healthy persons. Mass spectra of complete serum and membrane-filtered albumin-depleted samples have apparently different structure and peaks specific for both types of samples could be identified. The optimal classifier built for the complete serum specimens consisted of 8 spectral components, and had 81% specificity and 72% sensitivity, while that built for the membrane-filtered samples consisted of 4 components, and had 80% specificity and 81% sensitivity. We concluded that pre-processing of samples to remove albumin might be recommended before MALDI-ToF mass spectrometric analysis of the low-molecular-weight components of human serum Keywords: albumin removal; breast cancer; clinical proteomics; mass spectrometry; pattern analysis; serum proteome.
Grisham, Rachel N.; Sylvester, Brooke E.; Won, Helen; McDermott, Gregory; DeLair, Deborah; Ramirez, Ricardo; Yao, Zhan; Shen, Ronglai; Dao, Fanny; Bogomolniy, Faina; Makker, Vicky; Sala, Evis; Soumerai, Tara E.; Hyman, David M.; Socci, Nicholas D.; Viale, Agnes; Gershenson, David M.; Farley, John; Levine, Douglas A.; Rosen, Neal; Berger, Michael F.; Spriggs, David R.; Aghajanian, Carol A.; Solit, David B.; Iyer, Gopa
2015-01-01
Purpose No effective systemic therapy exists for patients with metastatic low-grade serous (LGS) ovarian cancers. BRAF and KRAS mutations are common in serous borderline (SB) and LGS ovarian cancers, and MEK inhibition has been shown to induce tumor regression in a minority of patients; however, no correlation has been observed between mutation status and clinical response. With the goal of identifying biomarkers of sensitivity to MEK inhibitor treatment, we performed an outlier analysis of a patient who experienced a complete, durable, and ongoing (> 5 years) response to selumetinib, a non-ATP competitive MEK inhibitor. Patients and Methods Next-generation sequencing was used to analyze this patient's tumor as well as an additional 28 SB/LGS tumors. Functional characterization of an identified novel alteration of interest was performed. Results Analysis of the extraordinary responder's tumor identified a 15-nucleotide deletion in the negative regulatory helix of the MAP2K1 gene encoding for MEK1. Functional characterization demonstrated that this mutant induced extracellular signal-regulated kinase pathway activation, promoted anchorage-independent growth and tumor formation in mice, and retained sensitivity to selumetinib. Analysis of additional LGS/SB tumors identified mutations predicted to induce extracellular signal-regulated kinase pathway activation in 82% (23 of 28), including two patients with BRAF fusions, one of whom achieved an ongoing complete response to MEK inhibitor–based combination therapy. Conclusion Alterations affecting the mitogen-activated protein kinase pathway are present in the majority of patients with LGS ovarian cancer. Next-generation sequencing analysis revealed deletions and fusions that are not detected by older sequencing approaches. These findings, coupled with the observation that a subset of patients with recurrent LGS ovarian cancer experienced dramatic and durable responses to MEK inhibitor therapy, support additional clinical studies of MEK inhibitors in this disease. PMID:26324360
NASA Astrophysics Data System (ADS)
Camilo, Ana E. F.; Grégio, André; Santos, Rafael D. C.
2016-05-01
Malware detection may be accomplished through the analysis of their infection behavior. To do so, dynamic analysis systems run malware samples and extract their operating system activities and network traffic. This traffic may represent malware accessing external systems, either to steal sensitive data from victims or to fetch other malicious artifacts (configuration files, additional modules, commands). In this work, we propose the use of visualization as a tool to identify compromised systems based on correlating malware communications in the form of graphs and finding isomorphisms between them. We produced graphs from over 6 thousand distinct network traffic files captured during malware execution and analyzed the existing relationships among malware samples and IP addresses.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Knogler, Thomas; El-Rabadi, Karem; Weber, Michael
2014-12-15
Purpose: To determine the diagnostic performance of three-dimensional (3D) texture analysis (TA) of contrast-enhanced computed tomography (CE-CT) images for treatment response assessment in patients with Hodgkin lymphoma (HL), compared with F-18-fludeoxyglucose (FDG) positron emission tomography/CT. Methods: 3D TA of 48 lymph nodes in 29 patients was performed on venous-phase CE-CT images before and after chemotherapy. All lymph nodes showed pathologically elevated FDG uptake at baseline. A stepwise logistic regression with forward selection was performed to identify classic CT parameters and texture features (TF) that enable the separation of complete response (CR) and persistent disease. Results: The TF fraction of imagemore » in runs, calculated for the 45° direction, was able to correctly identify CR with an accuracy of 75%, a sensitivity of 79.3%, and a specificity of 68.4%. Classical CT features achieved an accuracy of 75%, a sensitivity of 86.2%, and a specificity of 57.9%, whereas the combination of TF and CT imaging achieved an accuracy of 83.3%, a sensitivity of 86.2%, and a specificity of 78.9%. Conclusions: 3D TA of CE-CT images is potentially useful to identify nodal residual disease in HL, with a performance comparable to that of classical CT parameters. Best results are achieved when TA and classical CT features are combined.« less
Psychometric properties of the postpartum depression screening scale beyond the postpartum period.
Vogeli, Jo M; Hooker, Stephanie A; Everhart, Kevin D; Kaplan, Peter S
2018-04-01
Accurate postpartum depression screening measures are needed to identify mothers with depressive symptoms both in the postpartum period and beyond. Because it had not been tested beyond the immediate postpartum period, the reliability and validity of the Postpartum Depression Screening Scale (PDSS) and its sensitivity, specificity, and predictive value for diagnoses of major depressive disorder (MDD) were assessed in a diverse community sample of 238 mothers of 4- to 15-month-old infants. Mothers (N = 238; M age = 30.2, SD = 5.3) attended a lab session and completed the PDSS, the Beck Depression Inventory-II (BDI-II), and a structured clinical interview (SCID) to diagnose MDD. The reliability, validity, specificity, sensitivity, and predictive value of the PDSS to identify maternal depression were assessed. Confirmatory factor analysis supported the construct validity of five but not seven content subscales. The PDSS total and subscale scores demonstrated acceptable to high reliability (α = 0.68-0.95). Discriminant function analysis showed the scale correctly provided diagnostic classification at a rate higher than chance alone. Sensitivity and specificity for major depressive disorder (MDD) diagnosis were good and comparable to those of the BDI-II. Even in mothers who were somewhat more diverse and had older infants than those in the original normative study, the PDSS appears to be a psychometrically sound screener for identifying depressed mothers in the 15 months after childbirth. © 2018 Wiley Periodicals, Inc.
Pérez, Teresa; Makrestsov, Nikita; Garatt, John; Torlakovic, Emina; Gilks, C Blake; Mallett, Susan
The Canadian Immunohistochemistry Quality Control program monitors clinical laboratory performance for estrogen receptor and progesterone receptor tests used in breast cancer treatment management in Canada. Current methods assess sensitivity and specificity at each time point, compared with a reference standard. We investigate alternative performance analysis methods to enhance the quality assessment. We used 3 methods of analysis: meta-analysis of sensitivity and specificity of each laboratory across all time points; sensitivity and specificity at each time point for each laboratory; and fitting models for repeated measurements to examine differences between laboratories adjusted by test and time point. Results show 88 laboratories participated in quality control at up to 13 time points using typically 37 to 54 histology samples. In meta-analysis across all time points no laboratories have sensitivity or specificity below 80%. Current methods, presenting sensitivity and specificity separately for each run, result in wide 95% confidence intervals, typically spanning 15% to 30%. Models of a single diagnostic outcome demonstrated that 82% to 100% of laboratories had no difference to reference standard for estrogen receptor and 75% to 100% for progesterone receptor, with the exception of 1 progesterone receptor run. Laboratories with significant differences to reference standard identified with Generalized Estimating Equation modeling also have reduced performance by meta-analysis across all time points. The Canadian Immunohistochemistry Quality Control program has a good design, and with this modeling approach has sufficient precision to measure performance at each time point and allow laboratories with a significantly lower performance to be targeted for advice.
Sovero, Merly; Garcia, Josefina; Laguna-Torres, V. Alberto; Gomez, Jorge; Aleman, Washington; Chicaiza, Wilson; Barrantes, Melvin; Sanchez, Felix; Jimenez, Mirna; Comach, Guillermo; de Rivera, Ivette Lorenzana; Barboza, Alma; Aguayo, Nicolas; Kochel, Tadeusz
2010-01-01
Since the first detection of swine origin virus (SOIV) on March 28, 2009, the virus has spread worldwide and oseltamivir-resistant strains have already been identified in the past months. Here, we show the phylogenetic analysis of 63 SOIV isolates from eight countries in Central and South America, and their sensitivity to oseltamivir. PMID:20810843
Identification of Proteus mirabilis Mutants with Increased Sensitivity to Antimicrobial Peptides
McCoy, Andrea J.; Liu, Hongjian; Falla, Timothy J.; Gunn, John S.
2001-01-01
Antimicrobial peptides (APs) are important components of the innate defenses of animals, plants, and microorganisms. However, some bacterial pathogens are resistant to the action of APs. For example, Proteus mirabilis is highly resistant to the action of APs, such as polymyxin B (PM), protegrin, and the synthetic protegrin analog IB-367. To better understand this resistance, a transposon mutagenesis approach was used to generate P. mirabilis mutants sensitive to APs. Four unique PM-sensitive mutants of P. mirabilis were identified (these mutants were >2 to >128 times more sensitive than the wild type). Two of these mutants were also sensitive to IB-367 (16 and 128 times more sensitive than the wild type). Lipopolysaccharide (LPS) profiles of the PM- and protegrin-sensitive mutants demonstrated marked differences in both the lipid A and O-antigen regions, while the PM-sensitive mutants appeared to have alterations of either lipid A or O antigen. Matrix-assisted laser desorption ionization–time of flight mass spectrometry analysis of the wild-type and PM-sensitive mutant lipid A showed species with one or two aminoarabinose groups, while lipid A from the PM- and protegrin-sensitive mutants was devoid of aminoarabinose. When the mutants were streaked on an agar-containing medium, the swarming motility of the PM- and protegrin-sensitive mutants was completely inhibited and the swarming motility of the mutants sensitive to only PM was markedly decreased. DNA sequence analysis of the mutagenized loci revealed similarities to an O-acetyltransferase (PM and protegrin sensitive) and ATP synthase and sap loci (PM sensitive). These data further support the role of LPS modifications as an elaborate mechanism in the resistance of certain bacterial species to APs and suggest that LPS surface charge alterations may play a role in P. mirabilis swarming motility. PMID:11408219
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lambrechts, Nathalie; Verstraelen, Sandra; Lodewyckx, Hanne
2009-04-15
Early detection of the sensitizing potential of chemicals is an emerging issue for chemical, pharmaceutical and cosmetic industries. In our institute, an in vitro classification model for prediction of chemical-induced skin sensitization based on gene expression signatures in human CD34{sup +} progenitor-derived dendritic cells (DC) has been developed. This primary cell model is able to closely mimic the induction phase of sensitization by Langerhans cells in the skin, but it has drawbacks, such as the availability of cord blood. The aim of this study was to investigate whether human in vitro cultured THP-1 monocytes or macrophages display a similar expressionmore » profile for 13 predictive gene markers previously identified in DC and whether they also possess a discriminating capacity towards skin sensitizers and non-sensitizers based on these marker genes. To this end, the cell models were exposed to 5 skin sensitizers (ammonium hexachloroplatinate IV, 1-chloro-2,4-dinitrobenzene, eugenol, para-phenylenediamine, and tetramethylthiuram disulfide) and 5 non-sensitizers (L-glutamic acid, methyl salicylate, sodium dodecyl sulfate, tributyltin chloride, and zinc sulfate) for 6, 10, and 24 h, and mRNA expression of the 13 genes was analyzed using real-time RT-PCR. The transcriptional response of 7 out of 13 genes in THP-1 monocytes was significantly correlated with DC, whereas only 2 out of 13 genes in THP-1 macrophages. After a cross-validation of a discriminant analysis of the gene expression profiles in the THP-1 monocytes, this cell model demonstrated to also have a capacity to distinguish skin sensitizers from non-sensitizers. However, the DC model was superior to the monocyte model for discrimination of (non-)sensitizing chemicals.« less
Identifying Mother-Child Interaction Styles Using a Person-Centered Approach.
Nelson, Jackie A; O'Brien, Marion; Grimm, Kevin J; Leerkes, Esther M
2014-05-01
Parent-child conflict in the context of a supportive relationship has been discussed as a potentially constructive interaction pattern; the current study is the first to test this using a holistic analytic approach. Interaction styles, defined as mother-child conflict in the context of maternal sensitivity, were identified and described with demographic and stress-related characteristics of families. Longitudinal associations were tested between interaction styles and children's later social competence. Participants included 814 partnered mothers with a first-grade child. Latent profile analysis identified agreeable , dynamic , and disconnected interaction styles. Mothers' intimacy with a partner, depressive symptoms, and authoritarian childrearing beliefs, along with children's later conflict with a best friend and externalizing problems, were associated with group membership. Notably, the dynamic style, characterized by high sensitivity and high conflict, included families who experienced psychological and relational stressors. Findings are discussed with regard to how family stressors shape parent-child interaction patterns.
Identifying Mother-Child Interaction Styles Using a Person-Centered Approach
Nelson, Jackie A.; O’Brien, Marion; Grimm, Kevin J.; Leerkes, Esther M.
2016-01-01
Parent-child conflict in the context of a supportive relationship has been discussed as a potentially constructive interaction pattern; the current study is the first to test this using a holistic analytic approach. Interaction styles, defined as mother-child conflict in the context of maternal sensitivity, were identified and described with demographic and stress-related characteristics of families. Longitudinal associations were tested between interaction styles and children’s later social competence. Participants included 814 partnered mothers with a first-grade child. Latent profile analysis identified agreeable, dynamic, and disconnected interaction styles. Mothers’ intimacy with a partner, depressive symptoms, and authoritarian childrearing beliefs, along with children’s later conflict with a best friend and externalizing problems, were associated with group membership. Notably, the dynamic style, characterized by high sensitivity and high conflict, included families who experienced psychological and relational stressors. Findings are discussed with regard to how family stressors shape parent-child interaction patterns. PMID:28751818
Hunting for Active Galactic Nuclei in JWST/MIRI Imaging
NASA Astrophysics Data System (ADS)
Lin, Kenneth W.; Pope, Alexandra; Kirkpatrick, Allison
2018-01-01
The mid-infrared is uniquely sensitive to both star formation and active galactic nuclei (AGN) activity in galaxies. While spectra in this range can unambiguously identify these two processes, imaging data from the Spitzer Space Telescope found that the mid-infrared colors are also able to separate AGN from star forming galaxies. With the launch of the James Webb Space Telescope, our access to mid-infrared will be renewed; specifically, MIRI will provide imaging in 9 bands from 5.6-25.5 microns. While predictions show that color diagnostics will be useful with JWST/MIRI, this does not exploit the full dataset of MIRI imaging. In this poster, we discuss a Principal Component Analysis to identify the JWST filters that are most sensitive to the AGN contribution and demonstrate how to use it to identify large samples of AGN from planned MIRI imaging surveys.
2017-01-01
Objective To compare swallowing function between healthy subjects and patients with pharyngeal dysphagia using high resolution manometry (HRM) and to evaluate the usefulness of HRM for detecting pharyngeal dysphagia. Methods Seventy-five patients with dysphagia and 28 healthy subjects were included in this study. Diagnosis of dysphagia was confirmed by a videofluoroscopy. HRM was performed to measure pressure and timing information at the velopharynx (VP), tongue base (TB), and upper esophageal sphincter (UES). HRM parameters were compared between dysphagia and healthy groups. Optimal threshold values of significant HRM parameters for dysphagia were determined. Results VP maximal pressure, TB maximal pressure, UES relaxation duration, and UES resting pressure were lower in the dysphagia group than those in healthy group. UES minimal pressure was higher in dysphagia group than in the healthy group. Receiver operating characteristic (ROC) analyses were conducted to validate optimal threshold values for significant HRM parameters to identify patients with pharyngeal dysphagia. With maximal VP pressure at a threshold value of 144.0 mmHg, dysphagia was identified with 96.4% sensitivity and 74.7% specificity. With maximal TB pressure at a threshold value of 158.0 mmHg, dysphagia was identified with 96.4% sensitivity and 77.3% specificity. At a threshold value of 2.0 mmHg for UES minimal pressure, dysphagia was diagnosed at 74.7% sensitivity and 60.7% specificity. Lastly, UES relaxation duration of <0.58 seconds had 85.7% sensitivity and 65.3% specificity, and UES resting pressure of <75.0 mmHg had 89.3% sensitivity and 90.7% specificity for identifying dysphagia. Conclusion We present evidence that HRM could be a useful evaluation tool for detecting pharyngeal dysphagia. PMID:29201816
Spector, Logan G; Menk, Jeremiah S; Vinocur, Jeffrey M; Oster, Matthew E; Harvey, Brian A; St Louis, James D; Moller, James; Kochilas, Lazaros K
2016-08-09
The long-term outcomes of patients undergoing interventions for congenital heart disease (CHD) remain largely unknown. We linked the Pediatric Cardiac Care Consortium (PCCC) with the National Death Index (NDI) and the United Network for Organ Sharing Dataset (UNOS) registries to study mortality and transplant occurring up to 32 years postintervention. The objective of the current analysis was to determine the sensitivity of this linkage in identifying patients who are known to have died or undergone heart transplant. We used direct identifiers from 59 324 subjects registered in the PCCC between 1982 and 2003 to test for completeness of case ascertainment of subjects with known vital and heart transplant status by linkage with the NDI and UNOS registries. Of the 4612 in-hospital deaths, 3873 were identified by the NDI as "true" matches for a sensitivity of 84.0% (95% CI, 82.9-85.0). There was no difference in sensitivity across 25 congenital cardiovascular conditions after adjustment for age, sex, race, presence of first name, death year, and residence at death. Of 455 known heart transplants in the PCCC, there were 408 matches in the UNOS registry, for a sensitivity of 89.7% (95% CI, 86.9-92.3). An additional 4851 deaths and 363 transplants that occurred outside the PCCC were identified through 2014. The linkage of the PCCC with the NDI and UNOS national registries is feasible with a satisfactory sensitivity. This linkage provides a conservative estimate of the long-term death and heart transplant events in this cohort. © 2016 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.
Park, Chul-Hyun; Kim, Don-Kyu; Lee, Yong-Taek; Yi, Youbin; Lee, Jung-Sang; Kim, Kunwoo; Park, Jung Ho; Yoon, Kyung Jae
2017-10-01
To compare swallowing function between healthy subjects and patients with pharyngeal dysphagia using high resolution manometry (HRM) and to evaluate the usefulness of HRM for detecting pharyngeal dysphagia. Seventy-five patients with dysphagia and 28 healthy subjects were included in this study. Diagnosis of dysphagia was confirmed by a videofluoroscopy. HRM was performed to measure pressure and timing information at the velopharynx (VP), tongue base (TB), and upper esophageal sphincter (UES). HRM parameters were compared between dysphagia and healthy groups. Optimal threshold values of significant HRM parameters for dysphagia were determined. VP maximal pressure, TB maximal pressure, UES relaxation duration, and UES resting pressure were lower in the dysphagia group than those in healthy group. UES minimal pressure was higher in dysphagia group than in the healthy group. Receiver operating characteristic (ROC) analyses were conducted to validate optimal threshold values for significant HRM parameters to identify patients with pharyngeal dysphagia. With maximal VP pressure at a threshold value of 144.0 mmHg, dysphagia was identified with 96.4% sensitivity and 74.7% specificity. With maximal TB pressure at a threshold value of 158.0 mmHg, dysphagia was identified with 96.4% sensitivity and 77.3% specificity. At a threshold value of 2.0 mmHg for UES minimal pressure, dysphagia was diagnosed at 74.7% sensitivity and 60.7% specificity. Lastly, UES relaxation duration of <0.58 seconds had 85.7% sensitivity and 65.3% specificity, and UES resting pressure of <75.0 mmHg had 89.3% sensitivity and 90.7% specificity for identifying dysphagia. We present evidence that HRM could be a useful evaluation tool for detecting pharyngeal dysphagia.
The Newborn Screening Paradox: Sensitivity vs. Overdiagnosis in VLCAD Deficiency.
Diekman, Eugene; de Sain-van der Velden, Monique; Waterham, Hans; Kluijtmans, Leo; Schielen, Peter; van Veen, Evert Ben; Ferdinandusse, Sacha; Wijburg, Frits; Visser, Gepke
2016-01-01
To improve the efficacy of newborn screening (NBS) for very long chain acyl-CoA dehydrogenase deficiency (VLCADD). Data on all dried blood spots collected by the Dutch NBS from October 2007 to 2010 (742.728) were included. Based solely on the C14:1 levels (cutoff ≥0.8 μmol/L), six newborns with VLCADD had been identified through NBS during this period. The ratio of C14:1 over C2 was calculated. DNA of all blood spots with a C14:1/C2 ratio of ≥0.020 was isolated and sequenced. Children homozygous or compound heterozygous for mutations in the ACADVL gene were traced back and invited for detailed clinical, biochemical, and genetic evaluation. Retrospective analysis based on the C14:1/C2 ratio with a cutoff of ≥0.020 identified an additional five children with known ACADVL mutations and low enzymatic activity. All were still asymptomatic at the time of diagnosis (age 2-5 years). Increasing the cutoff to ≥0.023 resulted in a sensitivity of 93% and a positive predictive value of 37%. The sensitivity of the previously used screening approach (C14:1 ≥0.8) was 50%. This study shows that the ratio C14:1/C2 is a more sensitive marker than C14:1 for identifying VLCADD patients in NBS. However, as these patients were all asymptomatic at the time of diagnosis, this suggests that a more sensitive screening approach may also identify individuals who may never develop clinical disease. Long-term follow-up studies are needed to establish the risk of these VLCADD-deficient individuals for developing clinical signs and symptoms.
Xu, Weijia; Ozer, Stuart; Gutell, Robin R
2009-01-01
With an increasingly large amount of sequences properly aligned, comparative sequence analysis can accurately identify not only common structures formed by standard base pairing but also new types of structural elements and constraints. However, traditional methods are too computationally expensive to perform well on large scale alignment and less effective with the sequences from diversified phylogenetic classifications. We propose a new approach that utilizes coevolutional rates among pairs of nucleotide positions using phylogenetic and evolutionary relationships of the organisms of aligned sequences. With a novel data schema to manage relevant information within a relational database, our method, implemented with a Microsoft SQL Server 2005, showed 90% sensitivity in identifying base pair interactions among 16S ribosomal RNA sequences from Bacteria, at a scale 40 times bigger and 50% better sensitivity than a previous study. The results also indicated covariation signals for a few sets of cross-strand base stacking pairs in secondary structure helices, and other subtle constraints in the RNA structure.
Xu, Weijia; Ozer, Stuart; Gutell, Robin R.
2010-01-01
With an increasingly large amount of sequences properly aligned, comparative sequence analysis can accurately identify not only common structures formed by standard base pairing but also new types of structural elements and constraints. However, traditional methods are too computationally expensive to perform well on large scale alignment and less effective with the sequences from diversified phylogenetic classifications. We propose a new approach that utilizes coevolutional rates among pairs of nucleotide positions using phylogenetic and evolutionary relationships of the organisms of aligned sequences. With a novel data schema to manage relevant information within a relational database, our method, implemented with a Microsoft SQL Server 2005, showed 90% sensitivity in identifying base pair interactions among 16S ribosomal RNA sequences from Bacteria, at a scale 40 times bigger and 50% better sensitivity than a previous study. The results also indicated covariation signals for a few sets of cross-strand base stacking pairs in secondary structure helices, and other subtle constraints in the RNA structure. PMID:20502534
STRUCTURE OF THE UNIVERSITY PERSONALITY INVENTORY FOR CHINESE COLLEGE STUDENTS.
Zhang, Jieting; Lanza, Stephanie; Zhang, Minqiang; Su, Binyuan
2015-06-01
The University Personality Inventory, a mental health instrument for college students, is frequently used for screening in China. However, its unidimensionality has been questioned. This study examined its dimensions to provide more information about the specific mental problems for students at risk. Four subsamples were randomly created from a sample (N = 6,110; M age = 19.1 yr.) of students at a university in China. Principal component analysis with Promax rotation was applied on the first two subsamples to explore dimension of the inventory. Confirmatory factor analysis was conducted on the third subsample to verify the exploratory dimensions. Finally, the identified factors were compared to the Symptom Checklist-90 (SCL-90) to support validity, and sex differences were examined, based on the fourth subsample. Five factors were identified: Physical Symptoms, Cognitive Symptoms, Emotional Vulnerability, Social Avoidance, and Interpersonal Sensitivity, accounting for 60.3% of the variance. All the five factors were significantly correlated with the SCL-90. Women scored significantly higher than men on Cognitive Symptoms and Interpersonal Sensitivity.
Bellanger, Martine; Demeneix, Barbara; Grandjean, Philippe; Zoeller, R Thomas; Trasande, Leonardo
2015-04-01
Epidemiological studies and animal models demonstrate that endocrine-disrupting chemicals (EDCs) contribute to cognitive deficits and neurodevelopmental disabilities. The objective was to estimate neurodevelopmental disability and associated costs that can be reasonably attributed to EDC exposure in the European Union. An expert panel applied a weight-of-evidence characterization adapted from the Intergovernmental Panel on Climate Change. Exposure-response relationships and reference levels were evaluated for relevant EDCs, and biomarker data were organized from peer-reviewed studies to represent European exposure and approximate burden of disease. Cost estimation as of 2010 utilized lifetime economic productivity estimates, lifetime cost estimates for autism spectrum disorder, and annual costs for attention-deficit hyperactivity disorder. Setting, Patients and Participants, and Intervention: Cost estimation was carried out from a societal perspective, ie, including direct costs (eg, treatment costs) and indirect costs such as productivity loss. The panel identified a 70-100% probability that polybrominated diphenyl ether and organophosphate exposures contribute to IQ loss in the European population. Polybrominated diphenyl ether exposures were associated with 873,000 (sensitivity analysis, 148,000 to 2.02 million) lost IQ points and 3290 (sensitivity analysis, 3290 to 8080) cases of intellectual disability, at costs of €9.59 billion (sensitivity analysis, €1.58 billion to €22.4 billion). Organophosphate exposures were associated with 13.0 million (sensitivity analysis, 4.24 million to 17.1 million) lost IQ points and 59 300 (sensitivity analysis, 16,500 to 84,400) cases of intellectual disability, at costs of €146 billion (sensitivity analysis, €46.8 billion to €194 billion). Autism spectrum disorder causation by multiple EDCs was assigned a 20-39% probability, with 316 (sensitivity analysis, 126-631) attributable cases at a cost of €199 million (sensitivity analysis, €79.7 million to €399 million). Attention-deficit hyperactivity disorder causation by multiple EDCs was assigned a 20-69% probability, with 19 300 to 31 200 attributable cases at a cost of €1.21 billion to €2.86 billion. EDC exposures in Europe contribute substantially to neurobehavioral deficits and disease, with a high probability of >€150 billion costs/year. These results emphasize the advantages of controlling EDC exposure.
Sensitivity analysis for axis rotation diagrid structural systems according to brace angle changes
NASA Astrophysics Data System (ADS)
Yang, Jae-Kwang; Li, Long-Yang; Park, Sung-Soo
2017-10-01
General regular shaped diagrid structures can express diverse shapes because braces are installed along the exterior faces of the structures and the structures have no columns. However, since irregular shaped structures have diverse variables, studies to assess behaviors resulting from various variables are continuously required to supplement the imperfections related to such variables. In the present study, materials elastic modulus and yield strength were selected as variables for strength that would be applied to diagrid structural systems in the form of Twisters among the irregular shaped buildings classified by Vollers and that affect the structural design of these structural systems. The purpose of this study is to conduct sensitivity analysis for axial rotation diagrid structural systems according to changes in brace angles in order to identify the design variables that have relatively larger effects and the tendencies of the sensitivity of the structures according to changes in brace angles and axial rotation angles.
Chu, Haitao; Nie, Lei; Cole, Stephen R; Poole, Charles
2009-08-15
In a meta-analysis of diagnostic accuracy studies, the sensitivities and specificities of a diagnostic test may depend on the disease prevalence since the severity and definition of disease may differ from study to study due to the design and the population considered. In this paper, we extend the bivariate nonlinear random effects model on sensitivities and specificities to jointly model the disease prevalence, sensitivities and specificities using trivariate nonlinear random-effects models. Furthermore, as an alternative parameterization, we also propose jointly modeling the test prevalence and the predictive values, which reflect the clinical utility of a diagnostic test. These models allow investigators to study the complex relationship among the disease prevalence, sensitivities and specificities; or among test prevalence and the predictive values, which can reveal hidden information about test performance. We illustrate the proposed two approaches by reanalyzing the data from a meta-analysis of radiological evaluation of lymph node metastases in patients with cervical cancer and a simulation study. The latter illustrates the importance of carefully choosing an appropriate normality assumption for the disease prevalence, sensitivities and specificities, or the test prevalence and the predictive values. In practice, it is recommended to use model selection techniques to identify a best-fitting model for making statistical inference. In summary, the proposed trivariate random effects models are novel and can be very useful in practice for meta-analysis of diagnostic accuracy studies. Copyright 2009 John Wiley & Sons, Ltd.
NASA Astrophysics Data System (ADS)
Dasgupta, Sambarta
Transient stability and sensitivity analysis of power systems are problems of enormous academic and practical interest. These classical problems have received renewed interest, because of the advancement in sensor technology in the form of phasor measurement units (PMUs). The advancement in sensor technology has provided unique opportunity for the development of real-time stability monitoring and sensitivity analysis tools. Transient stability problem in power system is inherently a problem of stability analysis of the non-equilibrium dynamics, because for a short time period following a fault or disturbance the system trajectory moves away from the equilibrium point. The real-time stability decision has to be made over this short time period. However, the existing stability definitions and hence analysis tools for transient stability are asymptotic in nature. In this thesis, we discover theoretical foundations for the short-term transient stability analysis of power systems, based on the theory of normally hyperbolic invariant manifolds and finite time Lyapunov exponents, adopted from geometric theory of dynamical systems. The theory of normally hyperbolic surfaces allows us to characterize the rate of expansion and contraction of co-dimension one material surfaces in the phase space. The expansion and contraction rates of these material surfaces can be computed in finite time. We prove that the expansion and contraction rates can be used as finite time transient stability certificates. Furthermore, material surfaces with maximum expansion and contraction rate are identified with the stability boundaries. These stability boundaries are used for computation of stability margin. We have used the theoretical framework for the development of model-based and model-free real-time stability monitoring methods. Both the model-based and model-free approaches rely on the availability of high resolution time series data from the PMUs for stability prediction. The problem of sensitivity analysis of power system, subjected to changes or uncertainty in load parameters and network topology, is also studied using the theory of normally hyperbolic manifolds. The sensitivity analysis is used for the identification and rank ordering of the critical interactions and parameters in the power network. The sensitivity analysis is carried out both in finite time and in asymptotic. One of the distinguishing features of the asymptotic sensitivity analysis is that the asymptotic dynamics of the system is assumed to be a periodic orbit. For asymptotic sensitivity analysis we employ combination of tools from ergodic theory and geometric theory of dynamical systems.
Lo Re, Vincent; Haynes, Kevin; Forde, Kimberly A; Goldberg, David S; Lewis, James D; Carbonari, Dena M; Leidl, Kimberly B F; Reddy, K Rajender; Nezamzadeh, Melissa S; Roy, Jason; Sha, Daohang; Marks, Amy R; De Boer, Jolanda; Schneider, Jennifer L; Strom, Brian L; Corley, Douglas A
2015-12-01
Few studies have evaluated the ability of laboratory tests to predict risk of acute liver failure (ALF) among patients with drug-induced liver injury (DILI). We aimed to develop a highly sensitive model to identify DILI patients at increased risk of ALF. We compared its performance with that of Hy's Law, which predicts severity of DILI based on levels of alanine aminotransferase or aspartate aminotransferase and total bilirubin, and validated the model in a separate sample. We conducted a retrospective cohort study of 15,353 Kaiser Permanente Northern California members diagnosed with DILI from 2004 through 2010, liver aminotransferase levels above the upper limit of normal, and no pre-existing liver disease. Thirty ALF events were confirmed by medical record review. Logistic regression was used to develop prognostic models for ALF based on laboratory results measured at DILI diagnosis. External validation was performed in a sample of 76 patients with DILI at the University of Pennsylvania. Hy's Law identified patients that developed ALF with a high level of specificity (0.92) and negative predictive value (0.99), but low level of sensitivity (0.68) and positive predictive value (0.02). The model we developed, comprising data on platelet count and total bilirubin level, identified patients with ALF with a C statistic of 0.87 (95% confidence interval [CI], 0.76-0.96) and enabled calculation of a risk score (Drug-Induced Liver Toxicity ALF Score). We found a cut-off score that identified patients at high risk patients for ALF with a sensitivity value of 0.91 (95% CI, 0.71-0.99) and a specificity value of 0.76 (95% CI, 0.75-0.77). This cut-off score identified patients at high risk for ALF with a high level of sensitivity (0.89; 95% CI, 0.52-1.00) in the validation analysis. Hy's Law identifies patients with DILI at high risk for ALF with low sensitivity but high specificity. We developed a model (the Drug-Induced Liver Toxicity ALF Score) based on platelet count and total bilirubin level that identifies patients at increased risk for ALF with high sensitivity. Copyright © 2015 AGA Institute. Published by Elsevier Inc. All rights reserved.
Connolly, Keith P; Schwartzberg, Randy S; Reuss, Bryan; Crumbie, David; Homan, Brad M
2013-02-20
Magnetic resonance imaging (MRI) has been suggested to be of high accuracy at academic institutions in the identification of superior labral tears; however, many Type-II superior labral anterior-posterior (SLAP) lesions encountered during arthroscopy have not been previously diagnosed with noncontrast images. This study evaluated the accuracy of diagnosing Type-II SLAP lesions in a community setting with use of noncontrast MRI and analyzed the effect that radiologist training and the scanner type or magnet strength had on sensitivity and specificity. One hundred and forty-four patients requiring repair of an arthroscopically confirmed Type-II SLAP lesion who had a noncontrast MRI examination performed within twelve months before the procedure were included in the sensitivity analysis. An additional 100 patients with arthroscopically confirmed, normal superior labral anatomy were identified for specificity analysis. The transcribed interpretations of the images by the radiologists were used to document the diagnosis of a SLAP lesion and were compared with the operative report. The magnet strength, type of MRI system (open or closed), and whether the radiologist had completed a musculoskeletal fellowship were also recorded. Noncontrast MRI identified SLAP lesions in fifty-four of 144 shoulders, yielding an overall sensitivity of 38% (95% confidence interval [CI] = 30%, 46%). Specificity was 94% (95% CI = 87%, 98%), with six SLAP lesions diagnosed in 100 shoulders that did not contain the lesion. Musculoskeletal fellowship-trained radiologists performed with higher sensitivity than those who had not completed the fellowship (46% versus 19%; p = 0.009). Our results demonstrate a low sensitivity and high specificity in the diagnosis of Type-II SLAP lesions with noncontrast MRI in this community setting. Musculoskeletal fellowship-trained radiologists had significantly higher sensitivities in accurately diagnosing the lesion than did radiologists without such training. Noncontrast MRI is not a reliable diagnostic tool for Type-II SLAP lesions in a community setting.
Liu, Ting; He, Xiang-ge
2006-05-01
To evaluate the overall diagnostic capabilities of frequency-doubling technology (FDT) in patients of primary glaucoma, with standard automated perimetry (SAP) and/or optic disc appearance as the gold standard. A comprehensive electric search in MEDLINE, EMBASE, Cochrane Library, BIOSIS, Previews, HMIC, IPA, OVID, CNKI, CBMdisc, VIP information, CMCC, CCPD, SSreader and 21dmedia and a manual search in related textbooks, journals, congress articles and their references were performed to identify relevant English and Chinese language articles. Criteria for adaptability were established according to validity criteria for diagnostic research published by the Cochrane Methods Group on Screening and Diagnostic Tests. Quality of the included articles was assessed and relevant materials were extracted for studying. Statistical analysis was performed with Meta Test version 0.6 software. Heterogeneity of the included articles was tested, which was used to select appropriate effect model to calculate pooled weighted sensitivity and specificity. Summary Receiver Operating Characteristic (SROC) curve was established and the area under the curve (AUC) was calculated. Finally, sensitivity analysis was performed. Fifteen English articles (21 studies) of 206 retrieved articles were included in the present study, with a total of 3172 patients. The reported sensitivity of FDT ranged from 0.51 to 1.00, and specificity from 0.58 to 1.00. The pooled weighted sensitivity and specificity for FDT with 95% confidence intervals (95% CI) after correction for standard error were 0.86 (0.80 - 0.90), 0.87 (0.81 - 0.91), respectively. The AUC of SROC was 93.01%. Sensitivity analysis demonstrated no disproportionate influences of individual study. The included articles are of good quality and FDT can be a highly efficient diagnostic test for primary glaucoma based on Meta-analysis. However, a high quality perspective study is still required for further analysis.
Morozova, Tatiana V; Anholt, Robert RH; Mackay, Trudy FC
2007-01-01
Background Alcoholism is a complex disorder determined by interactions between genetic and environmental risk factors. Drosophila represents a powerful model system to dissect the genetic architecture of alcohol sensitivity, as large numbers of flies can readily be reared in defined genetic backgrounds and under controlled environmental conditions. Furthermore, flies exposed to ethanol undergo physiological and behavioral changes that resemble human alcohol intoxication, including loss of postural control, sedation, and development of tolerance. Results We performed artificial selection for alcohol sensitivity for 35 generations and created duplicate selection lines that are either highly sensitive or resistant to ethanol exposure along with unselected control lines. We used whole genome expression analysis to identify 1,678 probe sets with different expression levels between the divergent lines, pooled across replicates, at a false discovery rate of q < 0.001. We assessed to what extent genes with altered transcriptional regulation might be causally associated with ethanol sensitivity by measuring alcohol sensitivity of 37 co-isogenic P-element insertional mutations in 35 candidate genes, and found that 32 of these mutants differed in sensitivity to ethanol exposure from their co-isogenic controls. Furthermore, 23 of these novel genes have human orthologues. Conclusion Combining whole genome expression profiling with selection for genetically divergent lines is an effective approach for identifying candidate genes that affect complex traits, such as alcohol sensitivity. Because of evolutionary conservation of function, it is likely that human orthologues of genes affecting alcohol sensitivity in Drosophila may contribute to alcohol-associated phenotypes in humans. PMID:17973985
Zhang, Peige; Zhang, Li; Zheng, Shaoping; Yu, Cheng; Xie, Mingxing; Lv, Qing
2016-01-01
To evaluate the overall performance of acoustic radiation force impulse imaging (ARFI) in differentiating between benign and malignant lymph nodes (LNs) by conducting a meta-analysis. PubMed, Embase, Web of Science, the Cochrane Library and the China National Knowledge Infrastructure were comprehensively searched for potential studies through August 13th, 2016. Studies that investigated the diagnostic power of ARFI for the differential diagnosis of benign and malignant LNs by using virtual touch tissue quantification (VTQ) or virtual touch tissue imaging quantification (VTIQ) were collected. The included articles were published in English or Chinese. Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) was used to evaluate the methodological quality. The pooled sensitivity, specificity, and the area under the summary receiver operating characteristic (SROC) curve (AUC) were calculated by means of a bivariate mixed-effects regression model. Meta-regression analysis was performed to identify the potential sources of between study heterogeneity. Fagan plot analysis was used to explore the clinical utilities. Publication bias was assessed using Deek's funnel plot. Nine studies involving 1084 LNs from 929 patients were identified to analyze in the meta-analysis. The summary sensitivity and specificity of ARFI in detecting malignant LNs were 0.87 (95% confidence interval [CI], 0.83-0.91) and 0.88 (95% CI, 0.82-0.92), respectively. The AUC was 0.93 (95% CI, 0.90-0.95). The pooled DOR was 49.59 (95% CI, 26.11-94.15). Deek's funnel plot revealed no significant publication bias. ARFI is a promising tool for the differentiation of benign and malignant LNs with high sensitivity and specificity.
Yu, Cheng; Xie, Mingxing; Lv, Qing
2016-01-01
Objective To evaluate the overall performance of acoustic radiation force impulse imaging (ARFI) in differentiating between benign and malignant lymph nodes (LNs) by conducting a meta-analysis. Methods PubMed, Embase, Web of Science, the Cochrane Library and the China National Knowledge Infrastructure were comprehensively searched for potential studies through August 13th, 2016. Studies that investigated the diagnostic power of ARFI for the differential diagnosis of benign and malignant LNs by using virtual touch tissue quantification (VTQ) or virtual touch tissue imaging quantification (VTIQ) were collected. The included articles were published in English or Chinese. Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) was used to evaluate the methodological quality. The pooled sensitivity, specificity, and the area under the summary receiver operating characteristic (SROC) curve (AUC) were calculated by means of a bivariate mixed-effects regression model. Meta-regression analysis was performed to identify the potential sources of between study heterogeneity. Fagan plot analysis was used to explore the clinical utilities. Publication bias was assessed using Deek’s funnel plot. Results Nine studies involving 1084 LNs from 929 patients were identified to analyze in the meta-analysis. The summary sensitivity and specificity of ARFI in detecting malignant LNs were 0.87 (95% confidence interval [CI], 0.83–0.91) and 0.88 (95% CI, 0.82–0.92), respectively. The AUC was 0.93 (95% CI, 0.90–0.95). The pooled DOR was 49.59 (95% CI, 26.11–94.15). Deek’s funnel plot revealed no significant publication bias. Conclusion ARFI is a promising tool for the differentiation of benign and malignant LNs with high sensitivity and specificity. PMID:27855188
Granata, A; Nicoletti, R; Tinaglia, V; De Cecco, L; Pisanu, M E; Ricci, A; Podo, F; Canevari, S; Iorio, E; Bagnoli, M; Mezzanzanica, D
2014-01-21
Aberrant choline metabolism has been proposed as a novel cancer hallmark. We recently showed that epithelial ovarian cancer (EOC) possesses an altered MRS-choline profile, characterised by increased phosphocholine (PCho) content to which mainly contribute over-expression and activation of choline kinase-alpha (ChoK-alpha). To assess its biological relevance, ChoK-alpha expression was downmodulated by transient RNA interference in EOC in vitro models. Gene expression profiling by microarray analysis and functional analysis was performed to identify the pathway/functions perturbed in ChoK-alpha-silenced cells, then validated by in vitro experiments. In silenced cells, compared with control, we observed: (I) a significant reduction of both CHKA transcript and ChoK-alpha protein expression; (II) a dramatic, proportional drop in PCho content ranging from 60 to 71%, as revealed by (1)H-magnetic spectroscopy analysis; (III) a 35-36% of cell growth inhibition, with no evidences of apoptosis or modification of the main cellular survival signalling pathways; (IV) 476 differentially expressed genes, including genes related to lipid metabolism. Ingenuity pathway analysis identified cellular functions related to cell death and cellular proliferation and movement as the most perturbed. Accordingly, CHKA-silenced cells displayed a significant delay in wound repair, a reduced migration and invasion capability were also observed. Furthermore, although CHKA silencing did not directly induce cell death, a significant increase of sensitivity to platinum, paclitaxel and doxorubicin was observed even in a drug-resistant context. We showed for the first time in EOC that CHKA downregulation significantly decreased the aggressive EOC cell behaviour also affecting cells' sensitivity to drug treatment. These observations open the way to further analysis for ChoK-alpha validation as a new EOC therapeutic target to be used alone or in combination with conventional drugs.
Bao, Jie; Hou, Zhangshuan; Huang, Maoyi; ...
2015-12-04
Here, effective sensitivity analysis approaches are needed to identify important parameters or factors and their uncertainties in complex Earth system models composed of multi-phase multi-component phenomena and multiple biogeophysical-biogeochemical processes. In this study, the impacts of 10 hydrologic parameters in the Community Land Model on simulations of runoff and latent heat flux are evaluated using data from a watershed. Different metrics, including residual statistics, the Nash-Sutcliffe coefficient, and log mean square error, are used as alternative measures of the deviations between the simulated and field observed values. Four sensitivity analysis (SA) approaches, including analysis of variance based on the generalizedmore » linear model, generalized cross validation based on the multivariate adaptive regression splines model, standardized regression coefficients based on a linear regression model, and analysis of variance based on support vector machine, are investigated. Results suggest that these approaches show consistent measurement of the impacts of major hydrologic parameters on response variables, but with differences in the relative contributions, particularly for the secondary parameters. The convergence behaviors of the SA with respect to the number of sampling points are also examined with different combinations of input parameter sets and output response variables and their alternative metrics. This study helps identify the optimal SA approach, provides guidance for the calibration of the Community Land Model parameters to improve the model simulations of land surface fluxes, and approximates the magnitudes to be adjusted in the parameter values during parametric model optimization.« less
Foley, Elaine; Rippon, Gina; Thai, Ngoc Jade; Longe, Olivia; Senior, Carl
2012-02-01
Very little is known about the neural structures involved in the perception of realistic dynamic facial expressions. In the present study, a unique set of naturalistic dynamic facial emotional expressions was created. Through fMRI and connectivity analysis, a dynamic face perception network was identified, which is demonstrated to extend Haxby et al.'s [Haxby, J. V., Hoffman, E. A., & Gobbini, M. I. The distributed human neural system for face perception. Trends in Cognitive Science, 4, 223-233, 2000] distributed neural system for face perception. This network includes early visual regions, such as the inferior occipital gyrus, which is identified as insensitive to motion or affect but sensitive to the visual stimulus, the STS, identified as specifically sensitive to motion, and the amygdala, recruited to process affect. Measures of effective connectivity between these regions revealed that dynamic facial stimuli were associated with specific increases in connectivity between early visual regions, such as the inferior occipital gyrus and the STS, along with coupling between the STS and the amygdala, as well as the inferior frontal gyrus. These findings support the presence of a distributed network of cortical regions that mediate the perception of different dynamic facial expressions.
Willis, Sarah R; Ahmed, Hashim U; Moore, Caroline M; Donaldson, Ian; Emberton, Mark; Miners, Alec H; van der Meulen, Jan
2014-01-01
Objective To compare the diagnostic outcomes of the current approach of transrectal ultrasound (TRUS)-guided biopsy in men with suspected prostate cancer to an alternative approach using multiparametric MRI (mpMRI), followed by MRI-targeted biopsy if positive. Design Clinical decision analysis was used to synthesise data from recently emerging evidence in a format that is relevant for clinical decision making. Population A hypothetical cohort of 1000 men with suspected prostate cancer. Interventions mpMRI and, if positive, MRI-targeted biopsy compared with TRUS-guided biopsy in all men. Outcome measures We report the number of men expected to undergo a biopsy as well as the numbers of correctly identified patients with or without prostate cancer. A probabilistic sensitivity analysis was carried out using Monte Carlo simulation to explore the impact of statistical uncertainty in the diagnostic parameters. Results In 1000 men, mpMRI followed by MRI-targeted biopsy ‘clinically dominates’ TRUS-guided biopsy as it results in fewer expected biopsies (600 vs 1000), more men being correctly identified as having clinically significant cancer (320 vs 250), and fewer men being falsely identified (20 vs 50). The mpMRI-based strategy dominated TRUS-guided biopsy in 86% of the simulations in the probabilistic sensitivity analysis. Conclusions Our analysis suggests that mpMRI followed by MRI-targeted biopsy is likely to result in fewer and better biopsies than TRUS-guided biopsy. Future research in prostate cancer should focus on providing precise estimates of key diagnostic parameters. PMID:24934207
Randomized Trial of Plaque-Identifying Toothpaste: Decreasing Plaque and Inflammation.
Fasula, Kim; Evans, Carla A; Boyd, Linda; Giblin, Lori; Belavsky, Benjamin Z; Hetzel, Scott; McBride, Patrick; DeMets, David L; Hennekens, Charles H
2017-06-01
Randomized data are sparse about whether a plaque-identifying toothpaste reduces dental plaque and nonexistent for inflammation. Inflammation is intimately involved in the pathogenesis of atherosclerosis and is accurately measured by high-sensitivity C-reactive protein (hs-CRP), a sensitive marker for cardiovascular disease. The hypotheses that Plaque HD (TJA Health LLC, Joliet, Ill), a plaque-identifying toothpaste, produces statistically significant reductions in dental plaque and hs-CRP were tested in this randomized trial. Sixty-one apparently healthy subjects aged 19 to 44 years were assigned at random to this plaque-identifying (n = 31) or placebo toothpaste (n = 30) for 60 days. Changes from baseline to follow-up in dental plaque and hs-CRP were assessed. In an intention-to-treat analysis, the plaque-identifying toothpaste reduced mean plaque score by 49%, compared with a 24% reduction in placebo (P = .001). In a prespecified subgroup analysis of 38 subjects with baseline levels >0.5 mg/L, the plaque-identifying toothpaste reduced hs-CRP by 29%, compared with a 25% increase in placebo toothpaste (P = .041). This plaque-identifying toothpaste produced statistically significant reductions in dental plaque and hs-CRP. The observed reduction in dental plaque confirms and extends a previous observation. The observed reduction in inflammation supports the hypothesis of a reduction in risks of cardiovascular disease. The direct test of this hypothesis requires a large-scale randomized trial of sufficient size and duration designed a priori to do so. Such a finding would have major clinical and public health implications. Copyright © 2017 Elsevier Inc. All rights reserved.
Fast computation of derivative based sensitivities of PSHA models via algorithmic differentiation
NASA Astrophysics Data System (ADS)
Leövey, Hernan; Molkenthin, Christian; Scherbaum, Frank; Griewank, Andreas; Kuehn, Nicolas; Stafford, Peter
2015-04-01
Probabilistic seismic hazard analysis (PSHA) is the preferred tool for estimation of potential ground-shaking hazard due to future earthquakes at a site of interest. A modern PSHA represents a complex framework which combines different models with possible many inputs. Sensitivity analysis is a valuable tool for quantifying changes of a model output as inputs are perturbed, identifying critical input parameters and obtaining insight in the model behavior. Differential sensitivity analysis relies on calculating first-order partial derivatives of the model output with respect to its inputs. Moreover, derivative based global sensitivity measures (Sobol' & Kucherenko '09) can be practically used to detect non-essential inputs of the models, thus restricting the focus of attention to a possible much smaller set of inputs. Nevertheless, obtaining first-order partial derivatives of complex models with traditional approaches can be very challenging, and usually increases the computation complexity linearly with the number of inputs appearing in the models. In this study we show how Algorithmic Differentiation (AD) tools can be used in a complex framework such as PSHA to successfully estimate derivative based sensitivities, as is the case in various other domains such as meteorology or aerodynamics, without no significant increase in the computation complexity required for the original computations. First we demonstrate the feasibility of the AD methodology by comparing AD derived sensitivities to analytically derived sensitivities for a basic case of PSHA using a simple ground-motion prediction equation. In a second step, we derive sensitivities via AD for a more complex PSHA study using a ground motion attenuation relation based on a stochastic method to simulate strong motion. The presented approach is general enough to accommodate more advanced PSHA studies of higher complexity.
Interval analysis of interictal EEG: pathology of the alpha rhythm in focal epilepsy
NASA Astrophysics Data System (ADS)
Pyrzowski, Jan; Siemiński, Mariusz; Sarnowska, Anna; Jedrzejczak, Joanna; Nyka, Walenty M.
2015-11-01
The contemporary use of interictal scalp electroencephalography (EEG) in the context of focal epilepsy workup relies on the visual identification of interictal epileptiform discharges. The high-specificity performance of this marker comes, however, at a cost of only moderate sensitivity. Zero-crossing interval analysis is an alternative to Fourier analysis for the assessment of the rhythmic component of EEG signals. We applied this method to standard EEG recordings of 78 patients divided into 4 subgroups: temporal lobe epilepsy (TLE), frontal lobe epilepsy (FLE), psychogenic nonepileptic seizures (PNES) and nonepileptic patients with headache. Interval-analysis based markers were capable of effectively discriminating patients with epilepsy from those in control subgroups (AUC~0.8) with diagnostic sensitivity potentially exceeding that of visual analysis. The identified putative epilepsy-specific markers were sensitive to the properties of the alpha rhythm and displayed weak or non-significant dependences on the number of antiepileptic drugs (AEDs) taken by the patients. Significant AED-related effects were concentrated in the theta interval range and an associated marker allowed for identification of patients on AED polytherapy (AUC~0.9). Interval analysis may thus, in perspective, increase the diagnostic yield of interictal scalp EEG. Our findings point to the possible existence of alpha rhythm abnormalities in patients with epilepsy.
DOE Office of Scientific and Technical Information (OSTI.GOV)
López C, Diana C.; Wozny, Günter; Flores-Tlacuahuac, Antonio
2016-03-23
The lack of informative experimental data and the complexity of first-principles battery models make the recovery of kinetic, transport, and thermodynamic parameters complicated. We present a computational framework that combines sensitivity, singular value, and Monte Carlo analysis to explore how different sources of experimental data affect parameter structural ill conditioning and identifiability. Our study is conducted on a modified version of the Doyle-Fuller-Newman model. We demonstrate that the use of voltage discharge curves only enables the identification of a small parameter subset, regardless of the number of experiments considered. Furthermore, we show that the inclusion of a single electrolyte concentrationmore » measurement significantly aids identifiability and mitigates ill-conditioning.« less
The genomic landscape of rapid repeated evolutionary adaptation to toxic pollution in wild fish
Atlantic killifish populations have rapidly adapted to normally lethal levels of pollution in four urban estuaries. Through analysis of 384 whole killifish genome sequences and comparative transcriptomics in four pairs of sensitive and tolerant populations, we identify the aryl h...
Efficiency of the Bethesda System for Thyroid Cytopathology.
Mora-Guzmán, Ismael; Muñoz de Nova, José Luis; Marín-Campos, Cristina; Jiménez-Heffernan, José Antonio; Cuesta Pérez, Juan Julián; Lahera Vargas, Marcos; Torres Mínguez, Emma; Martín-Pérez, Elena
2018-03-28
Fine-needle aspiration biopsies are a key tool for preoperative assessment of thyroid nodules, and the Bethesda system is the preferred method to report cytological analysis. The purpose of this study is to assess the efficiency of the Bethesda system to identify the malignancy risk of thyroid nodules. Patients who underwent thyroid surgery between June 2010 and June 2017 were included. Samples were classified into 6categories according to rates of malignancy associated with each diagnostic category. In order to investigate the correlation between categories, a statistical analysis compared the categories with pathology reports. Diagnostic indicators were calculated as a screening test (categories IV, V, VI as true-positive) and as a method to identify malignancy (V, VI as true-positive). In a series of 522 patients, we found 184 (35.2%) malignant tumours, papillary carcinoma being the most prevalent with 155 cases (84.2%). Malignant rates for diagnostic categories were: I, 0%; II, 1.5%; III, 6.4%; IV, 31%; V, 86.5%; VI, 100%. A robust correlation was identified between categories on statistical analysis. For the «screening test» analysis, sensitivity was 98.9%, specificity 84.4%, positive predictive value 69.6%, negative predictive value 99.5%, and diagnostic accuracy 88.2%. Analysing the accuracy to detect malignancy, values were: sensitivity 98.6%, specificity 97.6%, positive predictive value 93.5%, negative predictive value 99.5%, diagnostic accuracy 97.9%. The Bethesda system is a clear and reliable approach to report thyroid cytology and therefore is an effective tool to identify malignancy risk and guide clinical management. Copyright © 2018 AEC. Publicado por Elsevier España, S.L.U. All rights reserved.
Xiao, Jinshu; Wang, La; Liu, Taihang; Wu, Yunfei; Dong, Feifan; Jiang, Yaming; Pan, Minhui; Zhang, Youhong; Lu, Cheng
2017-01-01
Thermotolerance is important particularly for poikilotherms such as insects. Understanding the mechanisms by which insects respond to high temperatures can provide insights into their adaptation to the environment. Therefore, in this study, we performed a transcriptome analysis of two silkworm strains with significantly different resistance to heat as well as humidity; the thermo-resistant strain 7532 and the thermos-sensitive strain Knobbed. We identified in total 4,944 differentially expressed genes (DEGs) using RNA-Seq. Among these, 4,390 were annotated and 554 were novel. Gene Ontology (GO) analysis of 747 DEGs identified between RT_48h (Resistant strain with high-temperature Treatment for 48 hours) and ST_48h (Sensitive strain with high-temperature Treatment for 48 hours) showed significant enrichment of 12 GO terms including metabolic process, extracellular region and serine-type peptidase activity. Moreover, we discovered 12 DEGs that may contribute to the heat-humidity stress response in the silkworm. Our data clearly showed that 48h post-exposure may be a critical time point for silkworm to respond to high temperature and humidity. These results provide insights into the genes and biological processes involved in high temperature and humidity tolerance in the silkworm, and advance our understanding of thermal tolerance in insects. PMID:28542312
Xiao, Wenfu; Chen, Peng; Xiao, Jinshu; Wang, La; Liu, Taihang; Wu, Yunfei; Dong, Feifan; Jiang, Yaming; Pan, Minhui; Zhang, Youhong; Lu, Cheng
2017-01-01
Thermotolerance is important particularly for poikilotherms such as insects. Understanding the mechanisms by which insects respond to high temperatures can provide insights into their adaptation to the environment. Therefore, in this study, we performed a transcriptome analysis of two silkworm strains with significantly different resistance to heat as well as humidity; the thermo-resistant strain 7532 and the thermos-sensitive strain Knobbed. We identified in total 4,944 differentially expressed genes (DEGs) using RNA-Seq. Among these, 4,390 were annotated and 554 were novel. Gene Ontology (GO) analysis of 747 DEGs identified between RT_48h (Resistant strain with high-temperature Treatment for 48 hours) and ST_48h (Sensitive strain with high-temperature Treatment for 48 hours) showed significant enrichment of 12 GO terms including metabolic process, extracellular region and serine-type peptidase activity. Moreover, we discovered 12 DEGs that may contribute to the heat-humidity stress response in the silkworm. Our data clearly showed that 48h post-exposure may be a critical time point for silkworm to respond to high temperature and humidity. These results provide insights into the genes and biological processes involved in high temperature and humidity tolerance in the silkworm, and advance our understanding of thermal tolerance in insects.
Raman exfoliative cytology for oral precancer diagnosis
NASA Astrophysics Data System (ADS)
Sahu, Aditi; Gera, Poonam; Pai, Venkatesh; Dubey, Abhishek; Tyagi, Gunjan; Waghmare, Mandavi; Pagare, Sandeep; Mahimkar, Manoj; Murali Krishna, C.
2017-11-01
Oral premalignant lesions (OPLs) such as leukoplakia, erythroplakia, and oral submucous fibrosis, often precede oral cancer. Screening and management of these premalignant conditions can improve prognosis. Raman spectroscopy has previously demonstrated potential in the diagnosis of oral premalignant conditions (in vivo), detected viral infection, and identified cancer in both oral and cervical exfoliated cells (ex vivo). The potential of Raman exfoliative cytology (REC) in identifying premalignant conditions was investigated. Oral exfoliated samples were collected from healthy volunteers (n=20), healthy volunteers with tobacco habits (n=20), and oral premalignant conditions (n=27, OPL) using Cytobrush. Spectra were acquired using Raman microprobe. Spectral acquisition parameters were: λex: 785 nm, laser power: 40 mW, acquisition time: 15 s, and average: 3. Postspectral acquisition, cell pellet was subjected to Pap staining. Multivariate analysis was carried out using principal component analysis and principal component-linear discriminant analysis using both spectra- and patient-wise approaches in three- and two-group models. OPLs could be identified with ˜77% (spectra-wise) and ˜70% (patient-wise) sensitivity in the three-group model while with 86% (spectra-wise) and 83% (patient-wise) in the two-group model. Use of histopathologically confirmed premalignant cases and better sampling devices may help in development of improved standard models and also enhance the sensitivity of the method. Future longitudinal studies can help validate potential of REC in screening and monitoring high-risk populations and prognosis prediction of premalignant lesions.
King, Carly J.; Woodward, Josha; Schwartzman, Jacob; Coleman, Daniel J.; Lisac, Robert; Wang, Nicholas J.; Van Hook, Kathryn; Gao, Lina; Urrutia, Joshua; Dane, Mark A.; Heiser, Laura M.; Alumkal, Joshi J.
2017-01-01
Recent work demonstrates that castration-resistant prostate cancer (CRPC) tumors harbor countless genomic aberrations that control many hallmarks of cancer. While some specific mutations in CRPC may be actionable, many others are not. We hypothesized that genomic aberrations in cancer may operate in concert to promote drug resistance and tumor progression, and that organization of these genomic aberrations into therapeutically targetable pathways may improve our ability to treat CRPC. To identify the molecular underpinnings of enzalutamide-resistant CRPC, we performed transcriptional and copy number profiling studies using paired enzalutamide-sensitive and resistant LNCaP prostate cancer cell lines. Gene networks associated with enzalutamide resistance were revealed by performing an integrative genomic analysis with the PAthway Representation and Analysis by Direct Reference on Graphical Models (PARADIGM) tool. Amongst the pathways enriched in the enzalutamide-resistant cells were those associated with MEK, EGFR, RAS, and NFKB. Functional validation studies of 64 genes identified 10 candidate genes whose suppression led to greater effects on cell viability in enzalutamide-resistant cells as compared to sensitive parental cells. Examination of a patient cohort demonstrated that several of our functionally-validated gene hits are deregulated in metastatic CRPC tumor samples, suggesting that they may be clinically relevant therapeutic targets for patients with enzalutamide-resistant CRPC. Altogether, our approach demonstrates the potential of integrative genomic analyses to clarify determinants of drug resistance and rational co-targeting strategies to overcome resistance. PMID:29340039
Liu, Wei; Xu, Libin; Lamberson, Connor; Haas, Dorothea; Korade, Zeljka; Porter, Ned A.
2014-01-01
We describe a highly sensitive method for the detection of 7-dehydrocholesterol (7-DHC), the biosynthetic precursor of cholesterol, based on its reactivity with 4-phenyl-1,2,4-triazoline-3,5-dione (PTAD) in a Diels-Alder cycloaddition reaction. Samples of biological tissues and fluids with added deuterium-labeled internal standards were derivatized with PTAD and analyzed by LC-MS. This protocol permits fast processing of samples, short chromatography times, and high sensitivity. We applied this method to the analysis of cells, blood, and tissues from several sources, including human plasma. Another innovative aspect of this study is that it provides a reliable and highly reproducible measurement of 7-DHC in 7-dehydrocholesterol reductase (Dhcr7)-HET mouse (a model for Smith-Lemli-Opitz syndrome) samples, showing regional differences in the brain tissue. We found that the levels of 7-DHC are consistently higher in Dhcr7-HET mice than in controls, with the spinal cord and peripheral nerve showing the biggest differences. In addition to 7-DHC, sensitive analysis of desmosterol in tissues and blood was also accomplished with this PTAD method by assaying adducts formed from the PTAD “ene” reaction. The method reported here may provide a highly sensitive and high throughput way to identify at-risk populations having errors in cholesterol biosynthesis. PMID:24259532
NASA Astrophysics Data System (ADS)
Liu, Haixing; Savić, Dragan; Kapelan, Zoran; Zhao, Ming; Yuan, Yixing; Zhao, Hongbin
2014-07-01
Flow entropy is a measure of uniformity of pipe flows in water distribution systems. By maximizing flow entropy one can identify reliable layouts or connectivity in networks. In order to overcome the disadvantage of the common definition of flow entropy that does not consider the impact of pipe diameter on reliability, an extended definition of flow entropy, termed as diameter-sensitive flow entropy, is proposed. This new methodology is then assessed by using other reliability methods, including Monte Carlo Simulation, a pipe failure probability model, and a surrogate measure (resilience index) integrated with water demand and pipe failure uncertainty. The reliability assessment is based on a sample of WDS designs derived from an optimization process for each of the two benchmark networks. Correlation analysis is used to evaluate quantitatively the relationship between entropy and reliability. To ensure reliability, a comparative analysis between the flow entropy and the new method is conducted. The results demonstrate that the diameter-sensitive flow entropy shows consistently much stronger correlation with the three reliability measures than simple flow entropy. Therefore, the new flow entropy method can be taken as a better surrogate measure for reliability and could be potentially integrated into the optimal design problem of WDSs. Sensitivity analysis results show that the velocity parameters used in the new flow entropy has no significant impact on the relationship between diameter-sensitive flow entropy and reliability.
Dong, Hengjin; Buxton, Martin
2006-01-01
The objective of this study is to apply a Markov model to compare cost-effectiveness of total knee replacement (TKR) using computer-assisted surgery (CAS) with that of TKR using a conventional manual method in the absence of formal clinical trial evidence. A structured search was carried out to identify evidence relating to the clinical outcome, cost, and effectiveness of TKR. Nine Markov states were identified based on the progress of the disease after TKR. Effectiveness was expressed by quality-adjusted life years (QALYs). The simulation was carried out initially for 120 cycles of a month each, starting with 1,000 TKRs. A discount rate of 3.5 percent was used for both cost and effectiveness in the incremental cost-effectiveness analysis. Then, a probabilistic sensitivity analysis was carried out using a Monte Carlo approach with 10,000 iterations. Computer-assisted TKR was a long-term cost-effective technology, but the QALYs gained were small. After the first 2 years, the incremental cost per QALY of computer-assisted TKR was dominant because of cheaper and more QALYs. The incremental cost-effectiveness ratio (ICER) was sensitive to the "effect of CAS," to the CAS extra cost, and to the utility of the state "Normal health after primary TKR," but it was not sensitive to utilities of other Markov states. Both probabilistic and deterministic analyses produced similar cumulative serious or minor complication rates and complex or simple revision rates. They also produced similar ICERs. Compared with conventional TKR, computer-assisted TKR is a cost-saving technology in the long-term and may offer small additional QALYs. The "effect of CAS" is to reduce revision rates and complications through more accurate and precise alignment, and although the conclusions from the model, even when allowing for a full probabilistic analysis of uncertainty, are clear, the "effect of CAS" on the rate of revisions awaits long-term clinical evidence.
Thornton, C G; Cranfield, M R; MacLellan, K M; Brink, T L; Strandberg, J D; Carlin, E A; Torrelles, J B; Maslow, J N; Hasson, J L; Heyl, D M; Sarro, S J; Chatterjee, D; Passen, S
1999-03-01
Mycobacterium avium is the causative agent of the avian mycobacteriosis commonly known as avian tuberculosis (ATB). This infection causes disseminated disease, is difficult to diagnose, and is of serious concern because it causes significant mortality in birds. A new method was developed for processing specimens for an antemortem screening test for ATB. This novel method uses the zwitterionic detergent C18-carboxypropylbetaine (CB-18). Blood, bone marrow, bursa, and fecal specimens from 28 ducks and swabs of 20 lesions were processed with CB-18 for analysis by smear, culture, and polymerase chain reaction (PCR). Postmortem examination confirmed nine of these birds as either positive or highly suspect for disseminated disease. The sensitivities of smear, culture, and PCR, relative to postmortem analysis and independent of specimen type, were 44.4%, 88.9%, and 100%, respectively, and the specificities were 84.2%, 57.9%, and 15.8%, respectively. Reductions in specificity were due primarily to results among fecal specimens. However, these results were clustered among a subset of birds, suggesting that these tests actually identified birds in early stages of the disease. Restriction fragment length polymorphism mapping identified one strain of M. avium (serotype 1) that was isolated from lesions, bursa, bone marrow, blood, and feces of all but three of the culture-positive birds. In birds with confirmed disease, blood had the lowest sensitivity and the highest specificity by all diagnostic methods. Swabs of lesions provided the highest sensitivity by smear and culture (33.3% and 77.8%, respectively), whereas fecal specimens had the highest sensitivity by PCR (77.8%). The results of this study indicate that processing fecal specimens with CB-18, followed by PCR analysis, may provide a valuable first step for monitoring the presence of ATB in birds.
Huang, Yao-Ting; Chen, Jia-Min; Ho, Bing-Ching; Wu, Zong-Yen; Kuo, Rita C; Liu, Po-Yu
2018-01-01
Stenotrophomonas acidaminiphila is an aerobic, glucose non-fermentative, Gram-negative bacterium that been isolated from various environmental sources, particularly aquatic ecosystems. Although resistance to multiple antimicrobial agents has been reported in S. acidaminiphila , the mechanisms are largely unknown. Here, for the first time, we report the complete genome and antimicrobial resistome analysis of a clinical isolate S. acidaminiphila SUNEO which is resistant to sulfamethoxazole. Comparative analysis among closely related strains identified common and strain-specific genes. In particular, comparison with a sulfamethoxazole-sensitive strain identified a mutation within the sulfonamide-binding site of folP in SUNEO, which may reduce the binding affinity of sulfamethoxazole. Selection pressure analysis indicated folP in SUNEO is under purifying selection, which may be owing to long-term administration of sulfonamide against Stenotrophomonas .
Influential input classification in probabilistic multimedia models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Maddalena, Randy L.; McKone, Thomas E.; Hsieh, Dennis P.H.
1999-05-01
Monte Carlo analysis is a statistical simulation method that is often used to assess and quantify the outcome variance in complex environmental fate and effects models. Total outcome variance of these models is a function of (1) the uncertainty and/or variability associated with each model input and (2) the sensitivity of the model outcome to changes in the inputs. To propagate variance through a model using Monte Carlo techniques, each variable must be assigned a probability distribution. The validity of these distributions directly influences the accuracy and reliability of the model outcome. To efficiently allocate resources for constructing distributions onemore » should first identify the most influential set of variables in the model. Although existing sensitivity and uncertainty analysis methods can provide a relative ranking of the importance of model inputs, they fail to identify the minimum set of stochastic inputs necessary to sufficiently characterize the outcome variance. In this paper, we describe and demonstrate a novel sensitivity/uncertainty analysis method for assessing the importance of each variable in a multimedia environmental fate model. Our analyses show that for a given scenario, a relatively small number of input variables influence the central tendency of the model and an even smaller set determines the shape of the outcome distribution. For each input, the level of influence depends on the scenario under consideration. This information is useful for developing site specific models and improving our understanding of the processes that have the greatest influence on the variance in outcomes from multimedia models.« less
Puziss, J W; Hardy, T A; Johnson, R B; Roach, P J; Hieter, P
1994-01-01
The yeast gene MCK1 encodes a serine/threonine protein kinase that is thought to function in regulating kinetochore activity and entry into meiosis. Disruption of MCK1 confers a cold-sensitive phenotype, a temperature-sensitive phenotype, and sensitivity to the microtubule-destabilizing drug benomyl and leads to loss of chromosomes during growth on benomyl. A dosage suppression selection was used to identify genes that, when present at high copy number, could suppress the cold-sensitive phenotype of mck1::HIS3 mutant cells. Several unique classes of clones were identified, and one of these, designated MDS1, has been characterized in some detail. Nucleotide sequence data reveal that MDS1 encodes a serine/threonine protein kinase that is highly homologous to the shaggy/zw3 kinase in Drosophila melanogaster and its functional homolog, glycogen synthase kinase 3, in rats. The presence of MDS1 in high copy number rescues both the cold-sensitive and the temperature-sensitive phenotypes, but not the benomyl-sensitive phenotype, associated with the disruption of MCK1. Analysis of strains harboring an mds1 null mutation demonstrates that MDS1 is not essential during normal vegetative growth but appears to be required for meiosis. Finally, in vitro experiments indicate that the proteins encoded by both MCK1 and MDS1 possess protein kinase activity with substrate specificity similar to that of mammalian glycogen synthase kinase 3. Images PMID:8264650
NASA Astrophysics Data System (ADS)
Kastanos, Evdokia; Hadjigeorgiou, Katerina; Kyriakides, Alexandros; Pitris, Costas
2011-03-01
Urinary tract infection (UTI) diagnosis requires an overnight culture to identify a sample as positive or negative for a UTI. Additional cultures are required to identify the pathogen responsible for the infection and to test its sensitivity to antibiotics. A rise in ineffective treatments, chronic infections, rising health care costs and antibiotic resistance are some of the consequences of this prolonged waiting period of UTI diagnosis. In this work, Surface Enhanced Raman Spectroscopy (SERS) is used for classifying bacterial samples as positive or negative for UTI. SERS spectra of serial dilutions of E.coli bacteria, isolated from a urine culture, were classified as positive (105-108 cells/ml) or negative (103-104 cells/ml) for UTI after mixing samples with gold nanoparticles. A leave-one-out cross validation was performed using the first two principal components resulting in the correct classification of 82% of all samples. Sensitivity of classification was 88% and specificity was 67%. Antibiotic sensitivity testing was also done using SERS spectra of various species of gram negative bacteria collected 4 hours after exposure to antibiotics. Spectral analysis revealed clear separation between the spectra of samples exposed to ciprofloxacin (sensitive) and amoxicillin (resistant). This study can become the basis for identifying urine samples as positive or negative for a UTI and determining their antibiogram without requiring an overnight culture.
Isolation of temperature-sensitive mutants of 16 S rRNA in Escherichia coli.
Triman, K; Becker, E; Dammel, C; Katz, J; Mori, H; Douthwaite, S; Yapijakis, C; Yoast, S; Noller, H F
1989-10-20
Temperature-sensitive mutants have been isolated following hydroxylamine mutagenesis of a plasmid containing Escherichia coli rRNA genes carrying selectable markers for spectinomycin resistance (U1192 in 16 S rRNA) and erythromycin resistance (G2058 in 23 S rRNA). These antibiotic resistance alleles, originally identified by Morgan and co-workers, enable us to follow expression of cloned rRNA genes in vivo. Recessive mutations causing the loss of expression of the cloned 16 S rRNA gene were identified by the loss of the ability of cells to survive on media containing spectinomycin. The mutations were localized by in vitro restriction fragment replacement followed by in vivo marker rescue and were identified by DNA sequence analysis. We report here seven single-base alterations in 16 S rRNA (A146, U153, A350, A359, A538, A1292 and U1293), five of which produce temperature-sensitive spectinomycin resistance and two that produce unconditional loss of resistance. In each case, loss of ribosomal function can be accounted for by disruption of base-pairing in the secondary structure of 16 S rRNA. For the temperature-sensitive mutants, there is a lag period of about two generations between a shift to the restrictive temperature and cessation of growth, implying that the structural defects cause impairment of ribosome assembly.
Bedside diagnosis of dysphagia: a systematic review.
O'Horo, John C; Rogus-Pulia, Nicole; Garcia-Arguello, Lisbeth; Robbins, JoAnne; Safdar, Nasia
2015-04-01
Dysphagia is associated with aspiration, pneumonia, and malnutrition, but remains challenging to identify at the bedside. A variety of exam protocols and maneuvers are commonly used, but the efficacy of these maneuvers is highly variable. We conducted a comprehensive search of 7 databases, including MEDLINE, Embase, and Scopus, from each database's earliest inception through June 9, 2014. Studies reporting diagnostic performance of a bedside examination maneuver compared to a reference gold standard (videofluoroscopic swallow study or flexible endoscopic evaluation of swallowing with sensory testing) were included for analysis. From each study, data were abstracted based on the type of diagnostic method and reference standard study population and inclusion/exclusion characteristics, design, and prediction of aspiration. The search strategy identified 38 articles meeting inclusion criteria. Overall, most bedside examinations lacked sufficient sensitivity to be used for screening purposes across all patient populations examined. Individual studies found dysphonia assessments, abnormal pharyngeal sensation assessments, dual axis accelerometry, and 1 description of water swallow testing to be sensitive tools, but none were reported as consistently sensitive. A preponderance of identified studies was in poststroke adults, limiting the generalizability of results. No bedside screening protocol has been shown to provide adequate predictive value for presence of aspiration. Several individual exam maneuvers demonstrated reasonable sensitivity, but reproducibility and consistency of these protocols was not established. More research is needed to design an optimal protocol for dysphagia detection. © 2015 Society of Hospital Medicine.
Lunny, Carole; McKenzie, Joanne E; McDonald, Steve
2016-06-01
Locating overviews of systematic reviews is difficult because of an absence of appropriate indexing terms and inconsistent terminology used to describe overviews. Our objective was to develop a validated search strategy to retrieve overviews in MEDLINE. We derived a test set of overviews from the references of two method articles on overviews. Two population sets were used to identify discriminating terms, that is, terms that appear frequently in the test set but infrequently in two population sets of references found in MEDLINE. We used text mining to conduct a frequency analysis of terms appearing in the titles and abstracts. Candidate terms were combined and tested in MEDLINE in various permutations, and the performance of strategies measured using sensitivity and precision. Two search strategies were developed: a sensitivity-maximizing strategy, achieving 93% sensitivity (95% confidence interval [CI]: 87, 96) and 7% precision (95% CI: 6, 8), and a sensitivity-and-precision-maximizing strategy, achieving 66% sensitivity (95% CI: 58, 74) and 21% precision (95% CI: 17, 25). The developed search strategies enable users to more efficiently identify overviews of reviews compared to current strategies. Consistent language in describing overviews would aid in their identification, as would a specific MEDLINE Publication Type. Copyright © 2015 Elsevier Inc. All rights reserved.
Age Dependent Variability in Gene Expression in Fischer 344 ...
Recent evidence suggests older adults may be a sensitive population with regard to environmental exposure to toxic compounds. One source of this sensitivity could be an enhanced variability in response. Studies on phenotypic differences have suggested that variation in response does increase with age. However, few reports address the question of variation in gene expression as an underlying cause for increased variability of phenotypic response in the aged. In this study, we utilized global analysis to compare variation in constitutive gene expression in the retinae of young (4 mos), middle-aged (11 mos) and aged (23 mos) Fischer 344 rats. Three hundred and forty transcripts were identified in which variance in expression increased from 4 to 23 mos of age, while only twelve transcripts were found for which it decreased. Functional roles for identified genes were clustered in basic biological categories including cell communication, function, metabolism and response to stimuli. Our data suggest that population stochastically-induced variability should be considered in assessing sensitivity due to old age. Recent evidence suggests older adults may be a sensitive population with regard to environmental exposure to toxic compounds. One source of this sensitivity could be an enhanced variability in response. Studies on phenotypic differences have suggested that variation in response does increase with age. However, few reports address the question of variation in
IgE sensitization in relation to preschool eczema and filaggrin mutation.
Johansson, Emma Kristin; Bergström, Anna; Kull, Inger; Lind, Tomas; Söderhäll, Cilla; van Hage, Marianne; Wickman, Magnus; Ballardini, Natalia; Wahlgren, Carl-Fredrik
2017-12-01
Eczema (atopic dermatitis) is associated with an increased risk of having IgE antibodies. IgE sensitization can occur through an impaired skin barrier. Filaggrin gene (FLG) mutation is associated with eczema and possibly also with IgE sensitization. We sought to explore the longitudinal relation between preschool eczema (PSE), FLG mutation, or both and IgE sensitization in childhood. A total of 3201 children from the BAMSE (Children Allergy Milieu Stockholm Epidemiology) birth cohort recruited from the general population were included. Regular parental questionnaires identified children with eczema. Blood samples were collected at 4, 8, and 16 years of age for analysis of specific IgE. FLG mutation analysis was performed on 1890 of the children. PSE was associated with IgE sensitization to both food allergens and aeroallergens up to age 16 years (overall adjusted odds ratio, 2.30; 95% CI, 2.00-2.66). This association was even stronger among children with persistent PSE. FLG mutation was associated with IgE sensitization to peanut at age 4 years (adjusted odds ratio, 1.88; 95% CI, 1.03-3.44) but not to other allergens up to age 16 years. FLG mutation and PSE were not effect modifiers for the association between IgE sensitization and PSE or FLG mutation, respectively. Sensitized children with PSE were characterized by means of polysensitization, but no other specific IgE sensitization patterns were found. PSE is associated with IgE sensitization to both food allergens and aeroallergens up to 16 years of age. FLG mutation is associated with IgE sensitization to peanut but not to other allergens. Sensitized children with preceding PSE are more often polysensitized. Copyright © 2017 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.
Commercial test kits for detection of Lyme borreliosis: a meta-analysis of test accuracy
Cook, Michael J; Puri, Basant K
2016-01-01
The clinical diagnosis of Lyme borreliosis can be supported by various test methodologies; test kits are available from many manufacturers. Literature searches were carried out to identify studies that reported characteristics of the test kits. Of 50 searched studies, 18 were included where the tests were commercially available and samples were proven to be positive using serology testing, evidence of an erythema migrans rash, and/or culture. Additional requirements were a test specificity of ≥85% and publication in the last 20 years. The weighted mean sensitivity for all tests and for all samples was 59.5%. Individual study means varied from 30.6% to 86.2%. Sensitivity for each test technology varied from 62.4% for Western blot kits, and 62.3% for enzyme-linked immunosorbent assay tests, to 53.9% for synthetic C6 peptide ELISA tests and 53.7% when the two-tier methodology was used. Test sensitivity increased as dissemination of the pathogen affected different organs; however, the absence of data on the time from infection to serological testing and the lack of standard definitions for “early” and “late” disease prevented analysis of test sensitivity versus time of infection. The lack of standardization of the definitions of disease stage and the possibility of retrospective selection bias prevented clear evaluation of test sensitivity by “stage”. The sensitivity for samples classified as acute disease was 35.4%, with a corresponding sensitivity of 64.5% for samples from patients defined as convalescent. Regression analysis demonstrated an improvement of 4% in test sensitivity over the 20-year study period. The studies did not provide data to indicate the sensitivity of tests used in a clinical setting since the effect of recent use of antibiotics or steroids or other factors affecting antibody response was not factored in. The tests were developed for only specific Borrelia species; sensitivities for other species could not be calculated. PMID:27920571
1981-04-01
LIFE CYCLE COST (LCC) LCC SENSITIVITY ANALYSIS LCC MODE , REPAIR LEVEL ANALYSIS (RLA) 20 ABSTRACT (Cnn tlnue on reverse side It necessary and Identify... level analysis capability. Next it provides values for Air Force input parameters and instructions for contractor inputs, general operating...Maintenance Manhour Requirements 39 5.1.4 Calculation of Repair Level Fractions 43 5.2 Cost Element Equations 47 5.2.1 Production Cost Element 47
Mori, Yoshikazu; Ogawa, Kazuo; Warabi, Eiji; Yamamoto, Masahiro; Hirokawa, Takatsugu
2016-01-01
Transient receptor potential vanilloid type 1 (TRPV1) is a non-selective cation channel and a multimodal sensor protein. Since the precise structure of TRPV1 was obtained by electron cryo-microscopy, the binding mode of representative agonists such as capsaicin and resiniferatoxin (RTX) has been extensively characterized; however, detailed information on the binding mode of other vanilloids remains lacking. In this study, mutational analysis of human TRPV1 was performed, and four agonists (capsaicin, RTX, [6]-shogaol and [6]-gingerol) were used to identify amino acid residues involved in ligand binding and/or modulation of proton sensitivity. The detailed binding mode of each ligand was then simulated by computational analysis. As a result, three amino acids (L518, F591 and L670) were newly identified as being involved in ligand binding and/or modulation of proton sensitivity. In addition, in silico docking simulation and a subsequent mutational study suggested that [6]-gingerol might bind to and activate TRPV1 in a unique manner. These results provide novel insights into the binding mode of various vanilloids to the channel and will be helpful in developing a TRPV1 modulator. PMID:27606946
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
From web search to healthcare utilization: privacy-sensitive studies from mobile data.
White, Ryen; Horvitz, Eric
2013-01-01
We explore relationships between health information seeking activities and engagement with healthcare professionals via a privacy-sensitive analysis of geo-tagged data from mobile devices. We analyze logs of mobile interaction data stripped of individually identifiable information and location data. The data analyzed consist of time-stamped search queries and distances to medical care centers. We examine search activity that precedes the observation of salient evidence of healthcare utilization (EHU) (ie, data suggesting that the searcher is using healthcare resources), in our case taken as queries occurring at or near medical facilities. We show that the time between symptom searches and observation of salient evidence of seeking healthcare utilization depends on the acuity of symptoms. We construct statistical models that make predictions of forthcoming EHU based on observations about the current search session, prior medical search activities, and prior EHU. The predictive accuracy of the models varies (65%-90%) depending on the features used and the timeframe of the analysis, which we explore via a sensitivity analysis. We provide a privacy-sensitive analysis that can be used to generate insights about the pursuit of health information and healthcare. The findings demonstrate how large-scale studies of mobile devices can provide insights on how concerns about symptomatology lead to the pursuit of professional care. We present new methods for the analysis of mobile logs and describe a study that provides evidence about how people transition from mobile searches on symptoms and diseases to the pursuit of healthcare in the world.
The Effects of Phonetic Similarity and List Length on Children's Sound Categorization Performance.
ERIC Educational Resources Information Center
Snowling, Margaret J.; And Others
1994-01-01
Examined the phonological analysis and verbal working memory components of the sound categorization task and their relationships to reading skill differences. Children were tested on sound categorization by having them identify odd words in sequences. Sound categorization performance was sensitive to individual differences in speech perception…
USDA-ARS?s Scientific Manuscript database
A nondestructive and sensitive method was developed to detect the presence of mixed pesticides of acetamiprid, chlorpyrifos and carbendazim on apples by surface-enhanced Raman spectroscopy (SERS). Self-modeling mixture analysis (SMA) was used to extract and identify the Raman spectra of individual p...
Federal Register 2010, 2011, 2012, 2013, 2014
2010-01-13
... number. Comments also should not include any sensitive health information, such as medical records or other individually identifiable health information. In addition, comments should not include any ``[t... fertilizers: nitrogen, phosphate, and potash, as well as control release fertilizers and micronutrients...
Theodore, M Jordan; Anderson, Raydel D; Wang, Xin; Katz, Lee S; Vuong, Jeni T; Bell, Melissa E; Juni, Billie A; Lowther, Sara A; Lynfield, Ruth; MacNeil, Jessica R; Mayer, Leonard W
2012-04-01
PCR detecting the protein D (hpd) and fuculose kinase (fucK) genes showed high sensitivity and specificity for identifying Haemophilus influenzae and differentiating it from H. haemolyticus. Phylogenetic analysis using the 16S rRNA gene demonstrated two distinct groups for H. influenzae and H. haemolyticus.
Mass Spectrometry contamination from Tinuvin 770, a common additive in laboratory plastics
USDA-ARS?s Scientific Manuscript database
The superior sensitivity of current mass spectrometers makes them prone to contamination issues which can have deleterious effects on sample analysis. Here, Bis(2,2,6,6-tetramethyl-4-piperidyl) sebacate (marketed under the name Tinuvin 770) is identified as a major contaminant in applications utiliz...
False-Positive Tangible Outcomes of Functional Analyses
ERIC Educational Resources Information Center
Rooker, Griffin W.; Iwata, Brian A.; Harper, Jill M.; Fahmie, Tara A.; Camp, Erin M.
2011-01-01
Functional analysis (FA) methodology is the most precise method for identifying variables that maintain problem behavior. Occasionally, however, results of an FA may be influenced by idiosyncratic sensitivity to aspects of the assessment conditions. For example, data from several studies suggest that inclusion of a tangible condition during an FA…
USDA-ARS?s Scientific Manuscript database
Hydrologic models are used to simulate the responses of agricultural systems to different inputs and management strategies to identify alternative management practices to cope up with future climate and/or geophysical changes. The Agricultural Policy/Environmental eXtender (APEX) is a model develope...
DIAGNOSTIC STUDY ON FINE PARTICULATE MATTER PREDICTIONS OF CMAQ IN THE SOUTHEASTERN U.S.
In this study, the authors use the process analysis tool embedded in CMAQ to examine major processes that govern the fate of key pollutants, identify the most influential processes that contribute to model errors, and guide the diagnostic and sensitivity studies aimed at improvin...
Initial Factor Analysis and Cross-Validation of the Multicultural Teaching Competencies Inventory
ERIC Educational Resources Information Center
Prieto, Loreto R.
2012-01-01
The Multicultural Teaching Competencies Inventory (MTCI) contains items based on the tri-parte model of cultural competencies established by Sue and associates (Sue et al., 1992, 1982, 2003) that identify multicultural Awareness, Knowledge, and Skill as central characteristics of a culturally sensitive professional. The development and validation…
Development of Water Quality Index for the United States: A Sensitivity Analysis
Background: Water quality is quantified using several measures, available from various data sources, which can be combined to create a single index of overall water quality. It is necessary to identify appropriate variables to include in an index which could be used for health re...
NASA Technical Reports Server (NTRS)
Smathers, J. B.; Kuykendall, W. E., Jr.; Wright, R. E., Jr.; Marshall, J. R.
1973-01-01
Radioisotope measurement techniques and neutron activation analysis are evaluated for use in identifying and locating contamination sources in space environment simulation chambers. The alpha range method allows the determination of total contaminant concentration in vapor state and condensate state. A Cf-252 neutron activation analysis system for detecting oils and greases tagged with stable elements is described. While neutron activation analysis of tagged contaminants offers specificity, an on-site system is extremely costly to implement and provides only marginal detection sensitivity under even the most favorable conditions.
Proteomic profiling for plasma biomarkers of tuberculosis progression.
Liu, Qiuyue; Pan, Liping; Han, Fen; Luo, Baojian; Jia, Hongyan; Xing, Aiying; Li, Qi; Zhang, Zongde
2018-06-05
Severe pulmonary tuberculosis (STB) is a life‑threatening condition with high economic and social burden. The present study aimed to screen for distinct proteins in different stages of TB and identify biomarkers for a better understanding of TB progression and pathogenesis. Blood samples were obtained from 81 patients with STB, 80 with mild TB (MTB) and 50 healthy controls. Differentially expressed proteins were identified using liquid chromatography‑tandem mass spectrometry‑based label‑free quantitative proteomic analysis. Functional and pathway enrichment analyses were performed for the identified proteins. The expression of potential biomarkers was further validated by western blot analysis and enzyme‑linked immunosorbent assays. The accuracy, sensitivity and specificity for selected protein biomarkers in diagnosing STB were also evaluated. A total of 1,011 proteins were identified in all three groups, and 153 differentially expressed proteins were identified in patients with STB. These proteins were involved in 'cellular process', 'response to stimulus', 'apoptotic process', 'immune system process' and 'select metabolic process'. Significant differences in protein expression were detected in α‑1‑acid glycoprotein 2 (ORM2), interleukin‑36α (IL‑36α), S100 calcium binding protein A9 (S100‑A9), superoxide dismutase (SOD)1 in the STB group, compared with the MTB and control groups. The combination of plasma ORM2, IL‑36α, S100A9 and SOD1 levels achieved 90.00% sensitivity and 92.16% specificity to discriminate between patients with STB and MTB, and 89.66% sensitivity and 98.9% specificity to discriminate between patients with STB and healthy controls. ORM2, S100A9, IL‑36α and SOD1 were associated with the development of TB, and have the potential to distinguish between different stages of TB. Differential protein expression during disease progression may improve the current understanding of STB pathogenesis.
Review of nutritional screening and assessment tools and clinical outcomes in heart failure.
Lin, Hong; Zhang, Haifeng; Lin, Zheng; Li, Xinli; Kong, Xiangqin; Sun, Gouzhen
2016-09-01
Recent studies have suggested that undernutrition as defined using multidimensional nutritional evaluation tools may affect clinical outcomes in heart failure (HF). The evidence supporting this correlation is unclear. Therefore, we conducted this systematic review to critically appraise the use of multidimensional evaluation tools in the prediction of clinical outcomes in HF. We performed descriptive analyses of all identified articles involving qualitative analyses. We used STATA to conduct meta-analyses when at least three studies that tested the same type of nutritional assessment or screening tools and used the same outcome were identified. Sensitivity analyses were conducted to validate our positive results. We identified 17 articles with qualitative analyses and 11 with quantitative analysis after comprehensive literature searching and screening. We determined that the prevalence of malnutrition is high in HF (range 16-90 %), particularly in advanced and acute decompensated HF (approximate range 75-90 %). Undernutrition as identified by multidimensional evaluation tools may be significantly associated with hospitalization, length of stay and complications and is particularly strongly associated with high mortality. The meta-analysis revealed that compared with other tools, Mini Nutritional Assessment (MNA) scores were the strongest predictors of mortality in HF [HR (4.32, 95 % CI 2.30-8.11)]. Our results remained reliable after conducting sensitivity analyses. The prevalence of malnutrition is high in HF, particularly in advanced and acute decompensated HF. Moreover, undernutrition as identified by multidimensional evaluation tools is significantly associated with unfavourable prognoses and high mortality in HF.
CHD7 Expression Predicts Survival Outcomes in Patients with Resected Pancreatic Cancer
Colbert, Lauren E.; Petrova, Aleksandra V.; Fisher, Sarah B.; Pantazides, Brooke G.; Madden, Matthew Z.; Hardy, Claire W.; Warren, Matthew D.; Pan, Yunfeng; Nagaraju, Ganji P.; Liu, Elaine A.; Saka, Burcu; Hall, William A.; Shelton, Joseph W.; Gandhi, Khanjan; Pauly, Rini; Kowalski, Jeanne; Kooby, David A.; El-Rayes, Bassel F.; Staley, Charles A.; Adsay, N. Volkan; Curran, Walter J.; Landry, Jerome C.; Maithel, Shishir K.; Yu, David S.
2014-01-01
Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with poor outcomes with current therapies. Gemcitabine is the primary adjuvant drug used clinically, but its effectiveness is limited. In this study, our objective was to utilize a rationale-driven approach to identify novel biomarkers for outcome in patients with early-stage resected PDAC treated with adjuvant gemcitabine. Using a synthetic lethal screen in human PDAC cells, we identified 93 genes including 55 genes linked to DNA damage responses (DDR) that demonstrated gemcitabine sensitization when silenced, including CHD7 which functions in chromatin remodeling. CHD7 depletion sensitized PDAC cells to gemcitabine and delayed their growth in tumor xenografts. Moreover, CHD7 silencing impaired ATR-dependent phosphorylation of CHK1 and increased DNA damage induced by gemcitabine. CHD7 was dysregulated, ranking above the 90th percentile in differential expression in a panel of PDAC clinical specimens, highlighting its potential as a biomarker. Immunohistochemical analysis of specimens from 59 resected PDAC patients receiving adjuvant gemcitabine revealed that low CHD7 expression was associated with increased recurrence-free survival (RFS) and overall survival (OS), in univariate and multivariate analyses. Notably, CHD7 expression was not associated with RFS or OS for patients not receiving gemcitabine. Thus, low CHD7 expression was correlated selectively with gemcitabine sensitivity in this patient population. These results supported our rationale-driven strategy to exploit dysregulated DDR pathways in PDAC to identify genetic determinants of gemcitabine sensitivity, identifying CHD7 as a novel biomarker candidate to evaluate further for individualizing PDAC treatment. PMID:24626090
Chen, Song; Duan, Hongtao; Kong, Jiahui; Li, Zedong
2015-01-01
Objectives To date, the relationship between C-reactive protein (CRP) level and diabetic retinopathy (DR) remains controversial. Therefore, a systematic review and meta-analysis was used to reveal the potential relationship between CRP level and DR. Methods A systematic search of PubMed, Embase.com, and Web of Science was performed to identify all comparative studies that compared the CRP level of two groups (case group and control group). We defined that diabetic patients without retinopathy and /or matched healthy persons constituted the control group, and patients with DR were the case group. Results Two cross sectional studies and twenty case control studies including a total of 3679 participants were identified. After pooling the data from all 22 studies, obvious heterogeneity existed between the studies, so a subgroup analysis and sensitivity analysis were performed. Removing the sensitivity studies, the blood CRP levels in the case group were observed to be higher than those in the control group [SMD = 0.22, 95% confidence interval (CI), 0.11–0.34], and the blood CRP levels in the proliferative diabetic retinopathy (PDR) group were also higher than those in the non-proliferative diabetic retinopathy (NPDR) group [SMD = 0.50, 95% CI, 0.30–0.70]. Conclusions The results from this current meta-analysis indicate that the CRP level might be used as a biomarker to determine the severity of DR. PMID:26636823
Du, Yushen; Wu, Nicholas C.; Jiang, Lin; Zhang, Tianhao; Gong, Danyang; Shu, Sara; Wu, Ting-Ting
2016-01-01
ABSTRACT Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp), we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available. PMID:27803181
Folded concave penalized learning in identifying multimodal MRI marker for Parkinson’s disease
Liu, Hongcheng; Du, Guangwei; Zhang, Lijun; Lewis, Mechelle M.; Wang, Xue; Yao, Tao; Li, Runze; Huang, Xuemei
2016-01-01
Background Brain MRI holds promise to gauge different aspects of Parkinson’s disease (PD)-related pathological changes. Its analysis, however, is hindered by the high-dimensional nature of the data. New method This study introduces folded concave penalized (FCP) sparse logistic regression to identify biomarkers for PD from a large number of potential factors. The proposed statistical procedures target the challenges of high-dimensionality with limited data samples acquired. The maximization problem associated with the sparse logistic regression model is solved by local linear approximation. The proposed procedures then are applied to the empirical analysis of multimodal MRI data. Results From 45 features, the proposed approach identified 15 MRI markers and the UPSIT, which are known to be clinically relevant to PD. By combining the MRI and clinical markers, we can enhance substantially the specificity and sensitivity of the model, as indicated by the ROC curves. Comparison to existing methods We compare the folded concave penalized learning scheme with both the Lasso penalized scheme and the principle component analysis-based feature selection (PCA) in the Parkinson’s biomarker identification problem that takes into account both the clinical features and MRI markers. The folded concave penalty method demonstrates a substantially better clinical potential than both the Lasso and PCA in terms of specificity and sensitivity. Conclusions For the first time, we applied the FCP learning method to MRI biomarker discovery in PD. The proposed approach successfully identified MRI markers that are clinically relevant. Combining these biomarkers with clinical features can substantially enhance performance. PMID:27102045
NASA Astrophysics Data System (ADS)
Rohmer, Jeremy
2016-04-01
Predicting the temporal evolution of landslides is typically supported by numerical modelling. Dynamic sensitivity analysis aims at assessing the influence of the landslide properties on the time-dependent predictions (e.g., time series of landslide displacements). Yet two major difficulties arise: 1. Global sensitivity analysis require running the landslide model a high number of times (> 1000), which may become impracticable when the landslide model has a high computation time cost (> several hours); 2. Landslide model outputs are not scalar, but function of time, i.e. they are n-dimensional vectors with n usually ranging from 100 to 1000. In this article, I explore the use of a basis set expansion, such as principal component analysis, to reduce the output dimensionality to a few components, each of them being interpreted as a dominant mode of variation in the overall structure of the temporal evolution. The computationally intensive calculation of the Sobol' indices for each of these components are then achieved through meta-modelling, i.e. by replacing the landslide model by a "costless-to-evaluate" approximation (e.g., a projection pursuit regression model). The methodology combining "basis set expansion - meta-model - Sobol' indices" is then applied to the La Frasse landslide to investigate the dynamic sensitivity analysis of the surface horizontal displacements to the slip surface properties during the pore pressure changes. I show how to extract information on the sensitivity of each main modes of temporal behaviour using a limited number (a few tens) of long running simulations. In particular, I identify the parameters, which trigger the occurrence of a turning point marking a shift between a regime of low values of landslide displacements and one of high values.
The countermovement jump to monitor neuromuscular status: A meta-analysis.
Claudino, João Gustavo; Cronin, John; Mezêncio, Bruno; McMaster, Daniel Travis; McGuigan, Michael; Tricoli, Valmor; Amadio, Alberto Carlos; Serrão, Julio Cerca
2017-04-01
The primary objective of this meta-analysis was to compare countermovement jump (CMJ) performance in studies that reported the highest value as opposed to average value for the purposes of monitoring neuromuscular status (i.e., fatigue and supercompensation). The secondary aim was to determine the sensitivity of the dependent variables. Systematic review with meta-analysis. The meta-analysis was conducted on the highest or average of a number of CMJ variables. Multiple literature searches were undertaken in Pubmed, Scopus, and Web of Science to identify articles utilizing CMJ to monitor training status. Effect sizes (ES) with 95% confidence interval (95% CI) were calculated using the mean and standard deviation of the pre- and post-testing data. The coefficient of variation (CV) with 95% CI was also calculated to assess the level of instability of each variable. Heterogeneity was assessed using a random-effects model. 151 articles were included providing a total of 531 ESs for the meta-analyses; 85.4% of articles used highest CMJ height, 13.2% used average and 1.3% used both when reporting changes in CMJ performance. Based on the meta-analysis, average CMJ height was more sensitive than highest CMJ height in detecting CMJ fatigue and supercompensation. Furthermore, other CMJ variables such as peak power, mean power, peak velocity, peak force, mean impulse, and power were sensitive in tracking the supercompensation effects of training. The average CMJ height was more sensitive than highest CMJ height in monitoring neuromuscular status; however, further investigation is needed to determine the sensitivity of other CMJ performance variables. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
Uncertainty Quantification Techniques of SCALE/TSUNAMI
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rearden, Bradley T; Mueller, Don
2011-01-01
The Standardized Computer Analysis for Licensing Evaluation (SCALE) code system developed at Oak Ridge National Laboratory (ORNL) includes Tools for Sensitivity and Uncertainty Analysis Methodology Implementation (TSUNAMI). The TSUNAMI code suite can quantify the predicted change in system responses, such as k{sub eff}, reactivity differences, or ratios of fluxes or reaction rates, due to changes in the energy-dependent, nuclide-reaction-specific cross-section data. Where uncertainties in the neutron cross-section data are available, the sensitivity of the system to the cross-section data can be applied to propagate the uncertainties in the cross-section data to an uncertainty in the system response. Uncertainty quantification ismore » useful for identifying potential sources of computational biases and highlighting parameters important to code validation. Traditional validation techniques often examine one or more average physical parameters to characterize a system and identify applicable benchmark experiments. However, with TSUNAMI correlation coefficients are developed by propagating the uncertainties in neutron cross-section data to uncertainties in the computed responses for experiments and safety applications through sensitivity coefficients. The bias in the experiments, as a function of their correlation coefficient with the intended application, is extrapolated to predict the bias and bias uncertainty in the application through trending analysis or generalized linear least squares techniques, often referred to as 'data adjustment.' Even with advanced tools to identify benchmark experiments, analysts occasionally find that the application models include some feature or material for which adequately similar benchmark experiments do not exist to support validation. For example, a criticality safety analyst may want to take credit for the presence of fission products in spent nuclear fuel. In such cases, analysts sometimes rely on 'expert judgment' to select an additional administrative margin to account for gap in the validation data or to conclude that the impact on the calculated bias and bias uncertainty is negligible. As a result of advances in computer programs and the evolution of cross-section covariance data, analysts can use the sensitivity and uncertainty analysis tools in the TSUNAMI codes to estimate the potential impact on the application-specific bias and bias uncertainty resulting from nuclides not represented in available benchmark experiments. This paper presents the application of methods described in a companion paper.« less
NASA Technical Reports Server (NTRS)
Bueno, R. A.
1977-01-01
Results of the generalized likelihood ratio (GLR) technique for the detection of failures in aircraft application are presented, and its relationship to the properties of the Kalman-Bucy filter is examined. Under the assumption that the system is perfectly modeled, the detectability and distinguishability of four failure types are investigated by means of analysis and simulations. Detection of failures is found satisfactory, but problems in identifying correctly the mode of a failure may arise. These issues are closely examined as well as the sensitivity of GLR to modeling errors. The advantages and disadvantages of this technique are discussed, and various modifications are suggested to reduce its limitations in performance and computational complexity.
Chapter 5: Modulation Excitation Spectroscopy with Phase-Sensitive Detection for Surface Analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shulda, Sarah; Richards, Ryan M.
Advancements in in situ spectroscopic techniques have led to significant progress being made in elucidating heterogeneous reaction mechanisms. The potential of these progressive methods is often limited only by the complexity of the system and noise in the data. Short-lived intermediates can be challenging, if not impossible, to identify with conventional spectra analysis means. Often equally difficult is separating signals that arise from active and inactive species. Modulation excitation spectroscopy combined with phase-sensitive detection analysis is a powerful tool for removing noise from the data while simultaneously revealing the underlying kinetics of the reaction. A stimulus is applied at amore » constant frequency to the reaction system, for example, a reactant cycled with an inert phase. Through mathematical manipulation of the data, any signal contributing to the overall spectra but not oscillating with the same frequency as the stimulus will be dampened or removed. With phase-sensitive detection, signals oscillating with the stimulus frequency but with various lag times are amplified providing valuable kinetic information. In this chapter, some examples are provided from the literature that have successfully used modulation excitation spectroscopy with phase-sensitive detection to uncover previously unobserved reaction intermediates and kinetics. Examples from a broad range of spectroscopic methods are included to provide perspective to the reader.« less
Norman, Sonya B; Allard, Carolyn B; Trim, Ryan S; Thorp, Steven R; Behrooznia, Michelle; Masino, Tonya T; Stein, Murray B
2013-04-01
Many women have unidentified anxiety or trauma histories that can impact their health and medical treatment-seeking behavior. This study examined the sensitivity, specificity, efficiency, and sensitivity to change of the Overall Anxiety Severity and Impairment Scale (OASIS) for identifying an anxiety disorder in a female sample with and without trauma history related to intimate partner violence (IPV). Forty-three women with full or partial PTSD from IPV and 41 women without PTSD completed the OASIS. All participants with trauma history completed the Clinician Administered PTSD Scale. This report is a secondary analysis of a study on the neurobiology of psychological trauma in survivors of IPV recruited from the community. A cut-score of 5 best discriminated those with PTSD from those without, successfully classifying 91% of the sample with 93% sensitivity and 90% specificity. The measure showed strong sensitivity to change in a subsample of 20 participants who completed PTSD treatment and strong convergent and divergent validity in the full sample. This study suggests that the OASIS can identify the presence of an anxiety disorder among a female sample of IPV survivors when PTSD is present.
Autoantibody recognition mechanisms of p53 epitopes
NASA Astrophysics Data System (ADS)
Phillips, J. C.
2016-06-01
There is an urgent need for economical blood based, noninvasive molecular biomarkers to assist in the detection and diagnosis of cancers in a cost-effective manner at an early stage, when curative interventions are still possible. Serum autoantibodies are attractive biomarkers for early cancer detection, but their development has been hindered by the punctuated genetic nature of the ten million known cancer mutations. A landmark study of 50,000 patients (Pedersen et al., 2013) showed that a few p53 15-mer epitopes are much more sensitive colon cancer biomarkers than p53, which in turn is a more sensitive cancer biomarker than any other protein. The function of p53 as a nearly universal ;tumor suppressor; is well established, because of its strong immunogenicity in terms of not only antibody recruitment, but also stimulation of autoantibodies. Here we examine dimensionally compressed bioinformatic fractal scaling analysis for identifying the few sensitive epitopes from the p53 amino acid sequence, and show how it could be used for early cancer detection (ECD). We trim 15-mers to 7-mers, and identify specific 7-mers from other species that could be more sensitive to aggressive human cancers, such as liver cancer. Our results could provide a roadmap for ECD.
2012-01-01
Background The aspartate aminotransferase-to-platelet ratio index (APRI), a tool with limited expense and widespread availability, is a promising noninvasive alternative to liver biopsy for detecting hepatic fibrosis. The objective of this study was to systematically review the performance of the APRI in predicting significant fibrosis and cirrhosis in hepatitis B-related fibrosis. Methods Areas under summary receiver operating characteristic curves (AUROC), sensitivity and specificity were used to examine the accuracy of the APRI for the diagnosis of hepatitis B-related significant fibrosis and cirrhosis. Heterogeneity was explored using meta-regression. Results Nine studies were included in this meta-analysis (n = 1,798). Prevalence of significant fibrosis and cirrhosis were 53.1% and 13.5%, respectively. The summary AUCs of the APRI for significant fibrosis and cirrhosis were 0.79 and 0.75, respectively. For significant fibrosis, an APRI threshold of 0.5 was 84% sensitive and 41% specific. At the cutoff of 1.5, the summary sensitivity and specificity were 49% and 84%, respectively. For cirrhosis, an APRI threshold of 1.0-1.5 was 54% sensitive and 78% specific. At the cutoff of 2.0, the summary sensitivity and specificity were 28% and 87%, respectively. Meta-regression analysis indicated that the APRI accuracy for both significant fibrosis and cirrhosis was affected by histological classification systems, but not influenced by the interval between Biopsy & APRI or blind biopsy. Conclusion Our meta-analysis suggests that APRI show limited value in identifying hepatitis B-related significant fibrosis and cirrhosis. PMID:22333407
Algorithm sensitivity analysis and parameter tuning for tissue image segmentation pipelines
Kurç, Tahsin M.; Taveira, Luís F. R.; Melo, Alba C. M. A.; Gao, Yi; Kong, Jun; Saltz, Joel H.
2017-01-01
Abstract Motivation: Sensitivity analysis and parameter tuning are important processes in large-scale image analysis. They are very costly because the image analysis workflows are required to be executed several times to systematically correlate output variations with parameter changes or to tune parameters. An integrated solution with minimum user interaction that uses effective methodologies and high performance computing is required to scale these studies to large imaging datasets and expensive analysis workflows. Results: The experiments with two segmentation workflows show that the proposed approach can (i) quickly identify and prune parameters that are non-influential; (ii) search a small fraction (about 100 points) of the parameter search space with billions to trillions of points and improve the quality of segmentation results (Dice and Jaccard metrics) by as much as 1.42× compared to the results from the default parameters; (iii) attain good scalability on a high performance cluster with several effective optimizations. Conclusions: Our work demonstrates the feasibility of performing sensitivity analyses, parameter studies and auto-tuning with large datasets. The proposed framework can enable the quantification of error estimations and output variations in image segmentation pipelines. Availability and Implementation: Source code: https://github.com/SBU-BMI/region-templates/. Contact: teodoro@unb.br Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28062445
Algorithm sensitivity analysis and parameter tuning for tissue image segmentation pipelines.
Teodoro, George; Kurç, Tahsin M; Taveira, Luís F R; Melo, Alba C M A; Gao, Yi; Kong, Jun; Saltz, Joel H
2017-04-01
Sensitivity analysis and parameter tuning are important processes in large-scale image analysis. They are very costly because the image analysis workflows are required to be executed several times to systematically correlate output variations with parameter changes or to tune parameters. An integrated solution with minimum user interaction that uses effective methodologies and high performance computing is required to scale these studies to large imaging datasets and expensive analysis workflows. The experiments with two segmentation workflows show that the proposed approach can (i) quickly identify and prune parameters that are non-influential; (ii) search a small fraction (about 100 points) of the parameter search space with billions to trillions of points and improve the quality of segmentation results (Dice and Jaccard metrics) by as much as 1.42× compared to the results from the default parameters; (iii) attain good scalability on a high performance cluster with several effective optimizations. Our work demonstrates the feasibility of performing sensitivity analyses, parameter studies and auto-tuning with large datasets. The proposed framework can enable the quantification of error estimations and output variations in image segmentation pipelines. Source code: https://github.com/SBU-BMI/region-templates/ . teodoro@unb.br. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.
NASA Astrophysics Data System (ADS)
Muldoon, Timothy J.; Thekkek, Nadhi; Roblyer, Darren; Maru, Dipen; Harpaz, Noam; Potack, Jonathan; Anandasabapathy, Sharmila; Richards-Kortum, Rebecca
2010-03-01
Early detection of neoplasia in patients with Barrett's esophagus is essential to improve outcomes. The aim of this ex vivo study was to evaluate the ability of high-resolution microendoscopic imaging and quantitative image analysis to identify neoplastic lesions in patients with Barrett's esophagus. Nine patients with pathologically confirmed Barrett's esophagus underwent endoscopic examination with biopsies or endoscopic mucosal resection. Resected fresh tissue was imaged with fiber bundle microendoscopy; images were analyzed by visual interpretation or by quantitative image analysis to predict whether the imaged sites were non-neoplastic or neoplastic. The best performing pair of quantitative features were chosen based on their ability to correctly classify the data into the two groups. Predictions were compared to the gold standard of histopathology. Subjective analysis of the images by expert clinicians achieved average sensitivity and specificity of 87% and 61%, respectively. The best performing quantitative classification algorithm relied on two image textural features and achieved a sensitivity and specificity of 87% and 85%, respectively. This ex vivo pilot trial demonstrates that quantitative analysis of images obtained with a simple microendoscope system can distinguish neoplasia in Barrett's esophagus with good sensitivity and specificity when compared to histopathology and to subjective image interpretation.
Kittelson, Andrew J.; Stevens-Lapsley, Jennifer E.; Schmiege, Sarah J.
2017-01-01
Objective Knee osteoarthritis (OA) is a broadly applied diagnosis that may encompass multiple subtypes of pain. The purpose of this study was to identify phenotypes of knee OA, using measures from the following pain-related domains: 1) knee OA pathology, 2) psychological distress, and 3) altered pain neurophysiology. Methods Data were selected from a total of 3494 participants at Visit #6 of the Osteoarthritis Initiative (OAI) study. Latent Class Analysis was applied to the following variables: radiographic OA severity, quadriceps strength, Body Mass Index (BMI), Charlson Comorbidity Index (CCI), Center for Epidemiologic Studies Depression subscale (CES-D), Coping Strategies Questionnaire-Catastrophizing subscale (CSQ-Cat), number of bodily pain sites, and knee joint tenderness at 4 sites. Resulting classes were compared on the following demographic and clinical factors: age, sex, pain severity, disability, walking speed, and use of arthritis-related healthcare. Results A four-class model was identified. Class 1 (4% of the study population) had higher CCI scores. Class 2 (24%) had higher knee joint sensitivity. Class 3 (10%) had greater psychological distress. Class 4 (62%) had lesser radiographic OA, little psychological involvement, greater strength, and less pain sensitivity. Additionally, Class 1 was the oldest, on average. Class 4 was the youngest, had the lowest disability, and least pain. Class 3 had the worst disability and most pain. Conclusions Four distinct pain phenotypes of knee OA were identified. Psychological factors, comorbidity status, and joint sensitivity appear to be important in defining phenotypes of knee OA-related pain. PMID:26414884
Kittelson, Andrew J; Stevens-Lapsley, Jennifer E; Schmiege, Sarah J
2016-05-01
Knee osteoarthritis (OA) is a broadly applied diagnosis that may describe multiple subtypes of pain. The purpose of this study was to identify phenotypes of knee OA, using measures from the following pain-related domains: 1) knee OA pathology, 2) psychological distress, and 3) altered pain neurophysiology. Data were selected from a total of 3,494 participants at visit 6 of the Osteoarthritis Initiative study. Latent class analysis was applied to the following variables: radiographic OA severity, quadriceps strength, body mass index, the Charlson Comorbidity Index (CCI), the Center for Epidemiologic Studies Depression Scale, the Coping Strategies Questionnaire-Catastrophizing subscale, number of bodily pain sites, and knee joint tenderness at 4 sites. The resulting classes were compared on the following demographic and clinical factors: age, sex, pain severity, disability, walking speed, and use of arthritis-related health care. A 4-class model was identified. Class 1 (4% of the study population) had higher CCI scores. Class 2 (24%) had higher knee joint sensitivity. Class 3 (10%) had greater psychological distress. Class 4 (62%) had lesser radiographic OA, little psychological involvement, greater strength, and less pain sensitivity. Additionally, class 1 was the oldest, on average. Class 4 was the youngest, had the lowest disability, and least pain. Class 3 had the worst disability and most pain. Four distinct pain phenotypes of knee OA were identified. Psychological factors, comorbidity status, and joint sensitivity appear to be important in defining phenotypes of knee OA-related pain. © 2016, American College of Rheumatology.
Spectral negentropy based sidebands and demodulation analysis for planet bearing fault diagnosis
NASA Astrophysics Data System (ADS)
Feng, Zhipeng; Ma, Haoqun; Zuo, Ming J.
2017-12-01
Planet bearing vibration signals are highly complex due to intricate kinematics (involving both revolution and spinning) and strong multiple modulations (including not only the fault induced amplitude modulation and frequency modulation, but also additional amplitude modulations due to load zone passing, time-varying vibration transfer path, and time-varying angle between the gear pair mesh lines of action and fault impact force vector), leading to difficulty in fault feature extraction. Rolling element bearing fault diagnosis essentially relies on detection of fault induced repetitive impulses carried by resonance vibration, but they are usually contaminated by noise and therefor are hard to be detected. This further adds complexity to planet bearing diagnostics. Spectral negentropy is able to reveal the frequency distribution of repetitive transients, thus providing an approach to identify the optimal frequency band of a filter for separating repetitive impulses. In this paper, we find the informative frequency band (including the center frequency and bandwidth) of bearing fault induced repetitive impulses using the spectral negentropy based infogram. In Fourier spectrum, we identify planet bearing faults according to sideband characteristics around the center frequency. For demodulation analysis, we filter out the sensitive component based on the informative frequency band revealed by the infogram. In amplitude demodulated spectrum (squared envelope spectrum) of the sensitive component, we diagnose planet bearing faults by matching the present peaks with the theoretical fault characteristic frequencies. We further decompose the sensitive component into mono-component intrinsic mode functions (IMFs) to estimate their instantaneous frequencies, and select a sensitive IMF with an instantaneous frequency fluctuating around the center frequency for frequency demodulation analysis. In the frequency demodulated spectrum (Fourier spectrum of instantaneous frequency) of selected IMF, we discern planet bearing fault reasons according to the present peaks. The proposed spectral negentropy infogram based spectrum and demodulation analysis method is illustrated via a numerical simulated signal analysis. Considering the unique load bearing feature of planet bearings, experimental validations under both no-load and loading conditions are done to verify the derived fault symptoms and the proposed method. The localized faults on outer race, rolling element and inner race are successfully diagnosed.
McPhail, Mark J W; Farne, Hugo; Senvar, Naz; Wendon, Julia A; Bernal, William
2016-04-01
Several prognostic factors are used to identify patients with acute liver failure (ALF) who require emergency liver transplantation. We performed a meta-analysis to determine the accuracy of King's College criteria (KCC) versus the model for end-stage liver disease (MELD) scores in predicting hospital mortality among patients with ALF. We performed a systematic search of the literature for articles published from 2001 through 2015 that compared the accuracy of the KCC with MELD scores in predicting hospital mortality in patients with ALF. We identified 23 studies (comprising 2153 patients) and assessed the quality of data, and then performed a meta-analysis of pooled sensitivity and specificity values, diagnostic odds ratios (DORs), and summary receiver operating characteristic curves. Subgroups analyzed included study quality, era, location (Europe vs non-Europe), and size; ALF etiology (acetaminophen-associated ALF [AALF] vs nonassociated [NAALF]); and whether or not the study included patients who underwent liver transplantation and if the study center was also a transplant center. The DOR for the KCC was 5.3 (95% confidence interval [CI], 3.7-7.6; 57% heterogeneity) and the DOR for MELD score was 7.0 (95% CI, 5.1-9.7; 48% heterogeneity), so the MELD score and KCC are comparable in overall accuracy. The summary area under the receiver operating characteristic curve values was 0.76 for the KCC and 0.78 for MELD scores. The KCC identified patients with AALF who died with 58% sensitivity (95% CI, 51%-65%) and 89% specificity (95% CI, 85%-93%), whereas MELD scores identified patients with AALF who died with 80% sensitivity (95% CI, 74%-86%) and 53% specificity (95% CI, 47%-59%). The KCC predicted hospital mortality in patients with NAALF with 58% sensitivity (95% CI, 54%-63%) and 74% specificity (95% CI, 69%-78%), whereas MELD scores predicted hospital mortality in patients with NAALF with 76% sensitivity (95% CI, 72%-80%) and 73% specificity (95% CI, 69%-78%). In patients with AALF, the KCC's DOR was 10.4 (95% CI, 4.9-22.1) and the MELD score's DOR was 6.6 (95% CI, 2.1-20.2). In patients with NAALF, the KCC's DOR was 4.16 (95% CI, 2.34-7.40) and the MELD score's DOR was 8.42 (95% CI, 5.98-11.88). Based on a meta-analysis of studies, the KCC more accurately predicts hospital mortality among patients with AALF, whereas MELD scores more accurately predict mortality among patients with NAALF. However, there is significant heterogeneity among studies and neither system is optimal for all patients. Given the importance of specificity in decision making for listing for emergency liver transplantation, MELD scores should not replace the KCC in predicting hospital mortality of patients with AALF, but could have a role for NAALF. Copyright © 2016 AGA Institute. Published by Elsevier Inc. All rights reserved.
Staton, Catherine A; De Silva, Vijitha; Krebs, Elizabeth; Andrade, Luciano; Rulisa, Stephen; Mallawaarachchi, Badra Chandanie; Jin, Kezhi; RicardoVissoci, Joao; Østbye, Truls
2016-01-20
Road traffic crashes (RTCs) are a leading cause of death. In low and middle income countries (LMIC) data to conduct hotspot analyses and safety audits are usually incomplete, poor quality, and not computerized. Police data are often limited, but there are no alternative gold standards. This project evaluates high road utilizer surveys as an alternative to police data to identify RTC hotspots. Retrospective police RTC data was compared to prospective data from high road utilizer surveys regarding dangerous road locations. Spatial analysis using geographic information systems was used to map dangerous locations and identify RTC hotspots. We assessed agreement (Cohen's Kappa), sensitivity/specificity, and cost differences. In Rwanda police data identified 1866 RTC locations from 2589 records while surveys identified 1264 locations from 602 surveys. In Sri Lanka, police data identified 721 RTC locations from 752 records while survey data found 3000 locations from 300 surveys. There was high agreement (97 %, 83 %) and kappa (0.60, 0.60) for Rwanda and Sri Lanka respectively. Sensitivity and specificity are 92 % and 95 % for Rwanda and 74 % and 93 % for Sri Lanka. The cost per crash location identified was $2.88 for police and $2.75 for survey data in Rwanda and $2.75 for police and $1.21 for survey data in Sri Lanka. Surveys to locate RTC hotspots have high sensitivity and specificity compared to police data. Therefore, surveys can be a viable, inexpensive, and rapid alternative to the use of police data in LMIC.
Sensitivity Analysis Tailored to Constrain 21st Century Terrestrial Carbon-Uptake
NASA Astrophysics Data System (ADS)
Muller, S. J.; Gerber, S.
2013-12-01
The long-term fate of terrestrial carbon (C) in response to climate change remains a dominant source of uncertainty in Earth-system model projections. Increasing atmospheric CO2 could be mitigated by long-term net uptake of C, through processes such as increased plant productivity due to "CO2-fertilization". Conversely, atmospheric conditions could be exacerbated by long-term net release of C, through processes such as increased decomposition due to higher temperatures. This balance is an important area of study, and a major source of uncertainty in long-term (>year 2050) projections of planetary response to climate change. We present results from an innovative application of sensitivity analysis to LM3V, a dynamic global vegetation model (DGVM), intended to identify observed/observable variables that are useful for constraining long-term projections of C-uptake. We analyzed the sensitivity of cumulative C-uptake by 2100, as modeled by LM3V in response to IPCC AR4 scenario climate data (1860-2100), to perturbations in over 50 model parameters. We concurrently analyzed the sensitivity of over 100 observable model variables, during the extant record period (1970-2010), to the same parameter changes. By correlating the sensitivities of observable variables with the sensitivity of long-term C-uptake we identified model calibration variables that would also constrain long-term C-uptake projections. LM3V employs a coupled carbon-nitrogen cycle to account for N-limitation, and we find that N-related variables have an important role to play in constraining long-term C-uptake. This work has implications for prioritizing field campaigns to collect global data that can help reduce uncertainties in the long-term land-atmosphere C-balance. Though results of this study are specific to LM3V, the processes that characterize this model are not completely divorced from other DGVMs (or reality), and our approach provides valuable insights into how data can be leveraged to be better constrain projections for the land carbon sink.
Xuan, Min; Zhou, Fengsheng; Ding, Yan; Zhu, Qiaoying; Dong, Ji; Zhou, Hao; Cheng, Jun; Jiang, Xiao; Wu, Pengxi
2018-04-01
To review the diagnostic accuracy of contrast-enhanced ultrasound (CEUS) used to detect residual or recurrent liver tumors after radiofrequency ablation (RFA). This technique uses contrast-enhanced computer tomography or/and contrast-enhanced magnetic resonance imaging as the gold standard of investigation. MEDLINE, EMBASE, and COCHRANE were systematically searched for all potentially eligible studies comparing CEUS with the reference standard that follows RFA. Risk of bias and applicability concerns were addressed by adopting the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Pooled point estimates for sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratios (DOR) with 95% CI were computed before plotting the sROC (summary receiver operating characteristic) curve. Meta-regression and subgroup analysis were used to identify the source of the heterogeneity that was detected. Publication bias was evaluated using Deeks' funnel plot asymmetry test. Ten eligible studies on 1162 lesions that occurred between 2001 and 2016 were included in the final analysis. The quality of the included studies assessed by the QUADAS-2 tool was considered reasonable. The pooled sensitivity and specificity of CEUS in detecting residual or recurrent liver tumors had the following values: 0.90 (95% CI 0.85-0.94) and 1.00 (95% CI 0.99-1.00), respectively. Overall DOR was 420.10 (95% CI 142.30-1240.20). The sources of heterogeneity could not be precisely identified by meta-regression or subgroup analysis. No evidence of publication bias was found. This study confirmed that CEUS exhibits high sensitivity and specificity in assessing therapeutic responses to RFA for liver tumors.
Tian, Bao-Guo; Si, Ji-Tao; Zhao, Yan; Wang, Hong-Tao; Hao, Ji-Ming
2007-01-01
This paper deals with the procedure and methodology which can be used to select the optimal treatment and disposal technology of municipal solid waste (MSW), and to provide practical and effective technical support to policy-making, on the basis of study on solid waste management status and development trend in China and abroad. Focusing on various treatment and disposal technologies and processes of MSW, this study established a Monte-Carlo mathematical model of cost minimization for MSW handling subjected to environmental constraints. A new method of element stream (such as C, H, O, N, S) analysis in combination with economic stream analysis of MSW was developed. By following the streams of different treatment processes consisting of various techniques from generation, separation, transfer, transport, treatment, recycling and disposal of the wastes, the element constitution as well as its economic distribution in terms of possibility functions was identified. Every technique step was evaluated economically. The Mont-Carlo method was then conducted for model calibration. Sensitivity analysis was also carried out to identify the most sensitive factors. Model calibration indicated that landfill with power generation of landfill gas was economically the optimal technology at the present stage under the condition of more than 58% of C, H, O, N, S going to landfill. Whether or not to generate electricity was the most sensitive factor. If landfilling cost increases, MSW separation treatment was recommended by screening first followed with incinerating partially and composting partially with residue landfilling. The possibility of incineration model selection as the optimal technology was affected by the city scale. For big cities and metropolitans with large MSW generation, possibility for constructing large-scale incineration facilities increases, whereas, for middle and small cities, the effectiveness of incinerating waste decreases.
Banal, F; Dougados, M; Combescure, C; Gossec, L
2009-07-01
To evaluate the ability of the widely used ACR set of criteria (both list and tree format) to diagnose RA compared with expert opinion according to disease duration. A systematic literature review was conducted in PubMed and Embase databases. All articles reporting the prevalence of RA according to ACR criteria and expert opinion in cohorts of early (<1 year duration) or established (>1 year) arthritis were analysed to calculate the sensitivity and specificity of ACR 1987 criteria against the "gold standard" (expert opinion). A meta-analysis using a summary receiver operating characteristic (SROC) curve was performed and pooled sensitivity and specificity were calculated with confidence intervals. Of 138 publications initially identified, 19 were analysable (total 7438 patients, 3883 RA). In early arthritis, pooled sensitivity and specificity of the ACR set of criteria were 77% (68% to 84%) and 77% (68% to 84%) in the list format versus 80% (72% to 88%) and 33% (24% to 43%) in the tree format. In established arthritis, sensitivity and specificity were respectively 79% (71% to 85%) and 90% (84% to 94%) versus 80% (71% to 85%) and 93% (86% to 97%). The SROC meta-analysis confirmed the statistically significant differences, suggesting that diagnostic performances of ACR list criteria are better in established arthritis. The specificity of ACR 1987 criteria in early RA is low, and these criteria should not be used as diagnostic tools. Sensitivity and specificity in established RA are higher, which reflects their use as classification criteria gold standard.
Christner, Martin; Dressler, Dirk; Andrian, Mark; Reule, Claudia; Petrini, Orlando
2017-01-01
The fast and reliable characterization of bacterial and fungal pathogens plays an important role in infectious disease control and tracking of outbreak agents. DNA based methods are the gold standard for epidemiological investigations, but they are still comparatively expensive and time-consuming. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a fast, reliable and cost-effective technique now routinely used to identify clinically relevant human pathogens. It has been used for subspecies differentiation and typing, but its use for epidemiological tasks, e. g. for outbreak investigations, is often hampered by the complexity of data analysis. We have analysed publicly available MALDI-TOF mass spectra from a large outbreak of Shiga-Toxigenic Escherichia coli in northern Germany using a general purpose software tool for the analysis of complex biological data. The software was challenged with depauperate spectra and reduced learning group sizes to mimic poor spectrum quality and scarcity of reference spectra at the onset of an outbreak. With high quality formic acid extraction spectra, the software's built in classifier accurately identified outbreak related strains using as few as 10 reference spectra (99.8% sensitivity, 98.0% specificity). Selective variation of processing parameters showed impaired marker peak detection and reduced classification accuracy in samples with high background noise or artificially reduced peak counts. However, the software consistently identified mass signals suitable for a highly reliable marker peak based classification approach (100% sensitivity, 99.5% specificity) even from low quality direct deposition spectra. The study demonstrates that general purpose data analysis tools can effectively be used for the analysis of bacterial mass spectra.
Ray, Partha; Rialon-Guevara, Kristy L.; Veras, Emanuela; Sullenger, Bruce A.; White, Rebekah R.
2012-01-01
Most cases of pancreatic cancer are not diagnosed until they are no longer curable with surgery. Therefore, it is critical to develop a sensitive, preferably noninvasive, method for detecting the disease at an earlier stage. In order to identify biomarkers for pancreatic cancer, we devised an in vitro positive/negative selection strategy to identify RNA ligands (aptamers) that could detect structural differences between the secretomes of pancreatic cancer and non-cancerous cells. Using this molecular recognition approach, we identified an aptamer (M9-5) that differentially bound conditioned media from cancerous and non-cancerous human pancreatic cell lines. This aptamer further discriminated between the sera of pancreatic cancer patients and healthy volunteers with high sensitivity and specificity. We utilized biochemical purification methods and mass-spectrometric analysis to identify the M9-5 target as cyclophilin B (CypB). This molecular recognition–based strategy simultaneously identified CypB as a serum biomarker and generated a new reagent to recognize it in body fluids. Moreover, this approach should be generalizable to other diseases and complementary to traditional approaches that focus on differences in expression level between samples. Finally, we suggest that the aptamer we identified has the potential to serve as a tool for the early detection of pancreatic cancer. PMID:22484812
Ray, Partha; Rialon-Guevara, Kristy L; Veras, Emanuela; Sullenger, Bruce A; White, Rebekah R
2012-05-01
Most cases of pancreatic cancer are not diagnosed until they are no longer curable with surgery. Therefore, it is critical to develop a sensitive, preferably noninvasive, method for detecting the disease at an earlier stage. In order to identify biomarkers for pancreatic cancer, we devised an in vitro positive/negative selection strategy to identify RNA ligands (aptamers) that could detect structural differences between the secretomes of pancreatic cancer and non-cancerous cells. Using this molecular recognition approach, we identified an aptamer (M9-5) that differentially bound conditioned media from cancerous and non-cancerous human pancreatic cell lines. This aptamer further discriminated between the sera of pancreatic cancer patients and healthy volunteers with high sensitivity and specificity. We utilized biochemical purification methods and mass-spectrometric analysis to identify the M9-5 target as cyclophilin B (CypB). This molecular recognition-based strategy simultaneously identified CypB as a serum biomarker and generated a new reagent to recognize it in body fluids. Moreover, this approach should be generalizable to other diseases and complementary to traditional approaches that focus on differences in expression level between samples. Finally, we suggest that the aptamer we identified has the potential to serve as a tool for the early detection of pancreatic cancer.
Sinha, Pallavi; Singh, Vikas K.; Suryanarayana, V.; Krishnamurthy, L.; Saxena, Rachit K.; Varshney, Rajeev K.
2015-01-01
Gene expression analysis using quantitative real-time PCR (qRT-PCR) is a very sensitive technique and its sensitivity depends on the stable performance of reference gene(s) used in the study. A number of housekeeping genes have been used in various expression studies in many crops however, their expression were found to be inconsistent under different stress conditions. As a result, species specific housekeeping genes have been recommended for different expression studies in several crop species. However, such specific housekeeping genes have not been reported in the case of pigeonpea (Cajanus cajan) despite the fact that genome sequence has become available for the crop. To identify the stable housekeeping genes in pigeonpea for expression analysis under drought stress conditions, the relative expression variations of 10 commonly used housekeeping genes (EF1α, UBQ10, GAPDH, 18SrRNA, 25SrRNA, TUB6, ACT1, IF4α, UBC and HSP90) were studied on root, stem and leaves tissues of Asha (ICPL 87119). Three statistical algorithms geNorm, NormFinder and BestKeeper were used to define the stability of candidate genes. geNorm analysis identified IF4α and TUB6 as the most stable housekeeping genes however, NormFinder analysis determined IF4α and HSP90 as the most stable housekeeping genes under drought stress conditions. Subsequently validation of the identified candidate genes was undertaken in qRT-PCR based gene expression analysis of uspA gene which plays an important role for drought stress conditions in pigeonpea. The relative quantification of the uspA gene varied according to the internal controls (stable and least stable genes), thus highlighting the importance of the choice of as well as validation of internal controls in such experiments. The identified stable and validated housekeeping genes will facilitate gene expression studies in pigeonpea especially under drought stress conditions. PMID:25849964
Sinha, Pallavi; Singh, Vikas K; Suryanarayana, V; Krishnamurthy, L; Saxena, Rachit K; Varshney, Rajeev K
2015-01-01
Gene expression analysis using quantitative real-time PCR (qRT-PCR) is a very sensitive technique and its sensitivity depends on the stable performance of reference gene(s) used in the study. A number of housekeeping genes have been used in various expression studies in many crops however, their expression were found to be inconsistent under different stress conditions. As a result, species specific housekeeping genes have been recommended for different expression studies in several crop species. However, such specific housekeeping genes have not been reported in the case of pigeonpea (Cajanus cajan) despite the fact that genome sequence has become available for the crop. To identify the stable housekeeping genes in pigeonpea for expression analysis under drought stress conditions, the relative expression variations of 10 commonly used housekeeping genes (EF1α, UBQ10, GAPDH, 18SrRNA, 25SrRNA, TUB6, ACT1, IF4α, UBC and HSP90) were studied on root, stem and leaves tissues of Asha (ICPL 87119). Three statistical algorithms geNorm, NormFinder and BestKeeper were used to define the stability of candidate genes. geNorm analysis identified IF4α and TUB6 as the most stable housekeeping genes however, NormFinder analysis determined IF4α and HSP90 as the most stable housekeeping genes under drought stress conditions. Subsequently validation of the identified candidate genes was undertaken in qRT-PCR based gene expression analysis of uspA gene which plays an important role for drought stress conditions in pigeonpea. The relative quantification of the uspA gene varied according to the internal controls (stable and least stable genes), thus highlighting the importance of the choice of as well as validation of internal controls in such experiments. The identified stable and validated housekeeping genes will facilitate gene expression studies in pigeonpea especially under drought stress conditions.
Sensitivity analysis of navy aviation readiness based sparing model
2017-09-01
variability. (See Figure 4.) Figure 4. Research design flowchart 18 Figure 4 lays out the four steps of the methodology , starting in the upper left-hand...as a function of changes in key inputs. We develop NAVARM Experimental Designs (NED), a computational tool created by applying a state-of-the-art...experimental design to the NAVARM model. Statistical analysis of the resulting data identifies the most influential cost factors. Those are, in order of
Voigt, Jeffrey; Carpenter, Linda; Leuchter, Andrew
2017-01-01
Repetitive Transcranial Magnetic Stimulation (rTMS) commonly is used for the treatment of Major Depressive Disorder (MDD) after patients have failed to benefit from trials of multiple antidepressant medications. No analysis to date has examined the cost-effectiveness of rTMS used earlier in the course of treatment and over a patients' lifetime. We used lifetime Markov simulation modeling to compare the direct costs and quality adjusted life years (QALYs) of rTMS and medication therapy in patients with newly diagnosed MDD (ages 20-59) who had failed to benefit from one pharmacotherapy trial. Patients' life expectancies, rates of response and remission, and quality of life outcomes were derived from the literature, and treatment costs were based upon published Medicare reimbursement data. Baseline costs, aggregate per year quality of life assessments (QALYs), Monte Carlo simulation, tornado analysis, assessment of dominance, and one way sensitivity analysis were also performed. The discount rate applied was 3%. Lifetime direct treatment costs, and QALYs identified rTMS as the dominant therapy compared to antidepressant medications (i.e., lower costs with better outcomes) in all age ranges, with costs/improved QALYs ranging from $2,952/0.32 (older patients) to $11,140/0.43 (younger patients). One-way sensitivity analysis demonstrated that the model was most sensitive to the input variables of cost per rTMS session, monthly prescription drug cost, and the number of rTMS sessions per year. rTMS was identified as the dominant therapy compared to antidepressant medication trials over the life of the patient across the lifespan of adults with MDD, given current costs of treatment. These models support the use of rTMS after a single failed antidepressant medication trial versus further attempts at medication treatment in adults with MDD.
2017-01-01
Objective Repetitive Transcranial Magnetic Stimulation (rTMS) commonly is used for the treatment of Major Depressive Disorder (MDD) after patients have failed to benefit from trials of multiple antidepressant medications. No analysis to date has examined the cost-effectiveness of rTMS used earlier in the course of treatment and over a patients’ lifetime. Methods We used lifetime Markov simulation modeling to compare the direct costs and quality adjusted life years (QALYs) of rTMS and medication therapy in patients with newly diagnosed MDD (ages 20–59) who had failed to benefit from one pharmacotherapy trial. Patients’ life expectancies, rates of response and remission, and quality of life outcomes were derived from the literature, and treatment costs were based upon published Medicare reimbursement data. Baseline costs, aggregate per year quality of life assessments (QALYs), Monte Carlo simulation, tornado analysis, assessment of dominance, and one way sensitivity analysis were also performed. The discount rate applied was 3%. Results Lifetime direct treatment costs, and QALYs identified rTMS as the dominant therapy compared to antidepressant medications (i.e., lower costs with better outcomes) in all age ranges, with costs/improved QALYs ranging from $2,952/0.32 (older patients) to $11,140/0.43 (younger patients). One-way sensitivity analysis demonstrated that the model was most sensitive to the input variables of cost per rTMS session, monthly prescription drug cost, and the number of rTMS sessions per year. Conclusion rTMS was identified as the dominant therapy compared to antidepressant medication trials over the life of the patient across the lifespan of adults with MDD, given current costs of treatment. These models support the use of rTMS after a single failed antidepressant medication trial versus further attempts at medication treatment in adults with MDD. PMID:29073256
Sharma, P; Bhargava, M; Sukhachev, D; Datta, S; Wattal, C
2014-02-01
Tropical febrile illnesses such as malaria and dengue are challenging to differentiate clinically. Automated cellular indices from hematology analyzers may afford a preliminary rapid distinction. Blood count and VCS parameters from 114 malaria patients, 105 dengue patients, and 105 febrile controls without dengue or malaria were analyzed. Statistical discriminant functions were generated, and their diagnostic performances were assessed by ROC curve analysis. Three statistical functions were generated: (i) malaria-vs.-controls factor incorporating platelet count and standard deviations of lymphocyte volume and conductivity that identified malaria with 90.4% sensitivity, 88.6% specificity; (ii) dengue-vs.-controls factor incorporating platelet count, lymphocyte percentage and standard deviation of lymphocyte conductivity that identified dengue with 81.0% sensitivity and 77.1% specificity; and (iii) febrile-controls-vs.-malaria/dengue factor incorporating mean corpuscular hemoglobin concentration, neutrophil percentage, mean lymphocyte and monocyte volumes, and standard deviation of monocyte volume that distinguished malaria and dengue from other febrile illnesses with 85.1% sensitivity and 91.4% specificity. Leukocyte abnormalities quantitated by automated analyzers successfully identified malaria and dengue and distinguished them from other fevers. These economic discriminant functions can be rapidly calculated by analyzer software programs to generate electronic flags to trigger-specific testing. They could potentially transform diagnostic approaches to tropical febrile illnesses in cost-constrained settings. © 2013 John Wiley & Sons Ltd.
Neurolysin Knockout Mice Generation and Initial Phenotype Characterization*
Cavalcanti, Diogo M. L. P.; Castro, Leandro M.; Rosa Neto, José C.; Seelaender, Marilia; Neves, Rodrigo X.; Oliveira, Vitor; Forti, Fábio L.; Iwai, Leo K.; Gozzo, Fabio C.; Todiras, Mihail; Schadock, Ines; Barros, Carlos C.; Bader, Michael; Ferro, Emer S.
2014-01-01
The oligopeptidase neurolysin (EC 3.4.24.16; Nln) was first identified in rat brain synaptic membranes and shown to ubiquitously participate in the catabolism of bioactive peptides such as neurotensin and bradykinin. Recently, it was suggested that Nln reduction could improve insulin sensitivity. Here, we have shown that Nln KO mice have increased glucose tolerance, insulin sensitivity, and gluconeogenesis. KO mice have increased liver mRNA for several genes related to gluconeogenesis. Isotopic label semiquantitative peptidomic analysis suggests an increase in specific intracellular peptides in gastrocnemius and epididymal adipose tissue, which likely is involved with the increased glucose tolerance and insulin sensitivity in the KO mice. These results suggest the exciting new possibility that Nln is a key enzyme for energy metabolism and could be a novel therapeutic target to improve glucose uptake and insulin sensitivity. PMID:24719317
Mehta, Milap; Tserentsoodol, Nomingerel; Postlethwait, John H.; Rebrik, Tatiana I.
2013-01-01
The ligand sensitivity of cGMP-gated (CNG) ion channels in cone photoreceptors is modulated by CNG-modulin, a Ca2+-binding protein. We investigated the functional role of CNG-modulin in phototransduction in vivo in morpholino-mediated gene knockdown zebrafish. Through comparative genomic analysis, we identified the orthologue gene of CNG-modulin in zebrafish, eml1, an ancient gene present in the genome of all vertebrates sequenced to date. We compare the photoresponses of wild-type cones with those of cones that do not express the EML1 protein. In the absence of EML1, dark-adapted cones are ∼5.3-fold more light sensitive than wild-type cones. Previous qualitative studies in several nonmammalian species have shown that immediately after the onset of continuous illumination, cones are less light sensitive than in darkness, but sensitivity then recovers over the following 15–20 s. We characterize light sensitivity recovery in continuously illuminated wild-type zebrafish cones and demonstrate that sensitivity recovery does not occur in the absence of EML1. PMID:24198367
Korenbrot, Juan I; Mehta, Milap; Tserentsoodol, Nomingerel; Postlethwait, John H; Rebrik, Tatiana I
2013-11-06
The ligand sensitivity of cGMP-gated (CNG) ion channels in cone photoreceptors is modulated by CNG-modulin, a Ca(2+)-binding protein. We investigated the functional role of CNG-modulin in phototransduction in vivo in morpholino-mediated gene knockdown zebrafish. Through comparative genomic analysis, we identified the orthologue gene of CNG-modulin in zebrafish, eml1, an ancient gene present in the genome of all vertebrates sequenced to date. We compare the photoresponses of wild-type cones with those of cones that do not express the EML1 protein. In the absence of EML1, dark-adapted cones are ∼5.3-fold more light sensitive than wild-type cones. Previous qualitative studies in several nonmammalian species have shown that immediately after the onset of continuous illumination, cones are less light sensitive than in darkness, but sensitivity then recovers over the following 15-20 s. We characterize light sensitivity recovery in continuously illuminated wild-type zebrafish cones and demonstrate that sensitivity recovery does not occur in the absence of EML1.
Ji, Ling Yun; Xu, Dong Lei; Yin, Shu Peng; Liu, Hai Can; Li, Gui Lian; Jiang, Yi; Wei, Jian Hao; Zeng, Hao; Lou, Yong Liang; Lyu, Jian Xin; Wan, Kang Lin
2017-07-01
In this study, milk from a cow with mastitis was analyzed to determine the presence of mycobacterial infection. Milk quality and security problems pertaining to the safe consumption of dairy products were also discussed in this study. Milk was preprocessed with 4% NaOH. Then, mycobacteria were isolated from the milk sample on L-J medium. The isolate was identified using multiple loci Polymerase Chain Reaction (PCR) and multi-locus sequence analysis with 16S rRNA, sodA, hsp65, and ITS genes. The drug sensitivity of the isolate to 27 antibiotics was tested through alamar blue assay. Smooth, moist, pale yellow colonies appeared on the L-J medium within a week after inoculation. Based on the results of multiple loci PCR analysis, the isolate was preliminarily identified as non-tuberculous mycobacteria. The 16S rRNA, SodA, hsp65, and ITS gene sequences of the isolate exhibited 99%, 99%, 99%, and 100% similarities, respectively, with those of the published reference strains of Mycobacterium elephantis (M. elephantis). The drug sensitivity results showed that the strain is resistant to isoniazid, p-aminosalicylic acid, and trimesulf but is sensitive to ofloxacin, rifampicin, amikacin, capreomycin, moxifloxacin, kanamycin, levofloxacin, cycloserine, ethambutol, streptomycin, tobramycin, rifabutin, ciprofloxacin, linezolid, cefoxitin, clarithromycin, and minocycline. To the best of our knowledge, this study is initially to report the isolation of M. elephantis from the milk of a cow with mastitis in China. Copyright © 2017 The Editorial Board of Biomedical and Environmental Sciences. Published by China CDC. All rights reserved.
Thethi, Tina K; Katalenich, Bonnie; Nagireddy, Prathima; Chabbra, Pankdeep; Kuhadiya, Nitesh; Fonseca, Vivian
2015-06-01
Polycystic ovarian syndrome (PCOS) is associated with an increase in cardiovascular (CV) risk factors such as insulin resistance, with accompanying hyperinsulinemia and hyperlipidemia, which are predisposing factors for type 2 diabetes mellitus and CV disease. The aim of this meta-analysis is to examine the effect of insulin sensitizers on clinical and biochemical features of PCOS and risk factors for CV disease. A systematic literature review was conducted, and randomized controlled clinical trials were identified by a search of bibliographic databases: Medline database (from 1966 forward), EMBASE (January 1985 forward), and Cochrane Central Register of Controlled Trials. Reviews of reference lists further identified candidate trials. Data was independently abstracted in duplicate by 2 investigators using a standardized data-collection form. Articles without a comparison group and randomization allocation were excluded. Reviewers worked independently and in duplicate to determine the methodological quality of trials, then collected data on patient characteristics, interventions, and outcomes. Of 455 studies, 44 trials were eligible. A random effects model was used. Significant unadjusted results favoring treatment with insulin sensitizers were obtained for body mass index (BMI) (effect size [ES] of 0.58), waist to hip ratio (WHR) (ES of 0.02), low-density-lipoprotein cholesterol (LDL-C) (ES of 0.11), fasting insulin (ES of 2.82), fasting glucose (ES of 0.10), free testosterone (ES of 1.88), and androstenedione level (ES of 0.76). Treatment with insulin sensitizers in women with PCOS results in improvement in CV factors such as BMI, WHR, LDL-C, fasting insulin, glucose, free testosterone, and androstenedione.
Kim, Hae Young; Park, Ji Hoon; Lee, Yoon Jin; Lee, Sung Soo; Jeon, Jong-June; Lee, Kyoung Ho
2018-04-01
Purpose To perform a systematic review and meta-analysis to identify computed tomographic (CT) features for differentiating complicated appendicitis in patients suspected of having appendicitis and to summarize their diagnostic accuracy. Materials and Methods Studies on diagnostic accuracy of CT features for differentiating complicated appendicitis (perforated or gangrenous appendicitis) in patients suspected of having appendicitis were searched in Ovid-MEDLINE, EMBASE, and the Cochrane Library. Overlapping descriptors used in different studies to denote the same image finding were subsumed under a single CT feature. Pooled diagnostic accuracy of the CT features was calculated by using a bivariate random effects model. CT features with pooled diagnostic odds ratios with 95% confidence intervals not including 1 were considered as informative. Results Twenty-three studies were included, and 184 overlapping descriptors for various CT findings were subsumed under 14 features. Of these, 10 features were informative for complicated appendicitis. There was a general tendency for these features to show relatively high specificity but low sensitivity. Extraluminal appendicolith, abscess, appendiceal wall enhancement defect, extraluminal air, ileus, periappendiceal fluid collection, ascites, intraluminal air, and intraluminal appendicolith showed pooled specificity greater than 70% (range, 74%-100%), but sensitivity was limited (range, 14%-59%). Periappendiceal fat stranding was the only feature that showed high sensitivity (94%; 95% confidence interval: 86%, 98%) but low specificity (40%; 95% confidence interval, 23%, 60%). Conclusion Ten informative CT features for differentiating complicated appendicitis were identified in this study, nine of which showed high specificity, but low sensitivity. © RSNA, 2017 Online supplemental material is available for this article.
Mallett, Susan; Halligan, Steve; Collins, Gary S.; Altman, Doug G.
2014-01-01
Background Different methods of evaluating diagnostic performance when comparing diagnostic tests may lead to different results. We compared two such approaches, sensitivity and specificity with area under the Receiver Operating Characteristic Curve (ROC AUC) for the evaluation of CT colonography for the detection of polyps, either with or without computer assisted detection. Methods In a multireader multicase study of 10 readers and 107 cases we compared sensitivity and specificity, using radiological reporting of the presence or absence of polyps, to ROC AUC calculated from confidence scores concerning the presence of polyps. Both methods were assessed against a reference standard. Here we focus on five readers, selected to illustrate issues in design and analysis. We compared diagnostic measures within readers, showing that differences in results are due to statistical methods. Results Reader performance varied widely depending on whether sensitivity and specificity or ROC AUC was used. There were problems using confidence scores; in assigning scores to all cases; in use of zero scores when no polyps were identified; the bimodal non-normal distribution of scores; fitting ROC curves due to extrapolation beyond the study data; and the undue influence of a few false positive results. Variation due to use of different ROC methods exceeded differences between test results for ROC AUC. Conclusions The confidence scores recorded in our study violated many assumptions of ROC AUC methods, rendering these methods inappropriate. The problems we identified will apply to other detection studies using confidence scores. We found sensitivity and specificity were a more reliable and clinically appropriate method to compare diagnostic tests. PMID:25353643
Mallett, Susan; Halligan, Steve; Collins, Gary S; Altman, Doug G
2014-01-01
Different methods of evaluating diagnostic performance when comparing diagnostic tests may lead to different results. We compared two such approaches, sensitivity and specificity with area under the Receiver Operating Characteristic Curve (ROC AUC) for the evaluation of CT colonography for the detection of polyps, either with or without computer assisted detection. In a multireader multicase study of 10 readers and 107 cases we compared sensitivity and specificity, using radiological reporting of the presence or absence of polyps, to ROC AUC calculated from confidence scores concerning the presence of polyps. Both methods were assessed against a reference standard. Here we focus on five readers, selected to illustrate issues in design and analysis. We compared diagnostic measures within readers, showing that differences in results are due to statistical methods. Reader performance varied widely depending on whether sensitivity and specificity or ROC AUC was used. There were problems using confidence scores; in assigning scores to all cases; in use of zero scores when no polyps were identified; the bimodal non-normal distribution of scores; fitting ROC curves due to extrapolation beyond the study data; and the undue influence of a few false positive results. Variation due to use of different ROC methods exceeded differences between test results for ROC AUC. The confidence scores recorded in our study violated many assumptions of ROC AUC methods, rendering these methods inappropriate. The problems we identified will apply to other detection studies using confidence scores. We found sensitivity and specificity were a more reliable and clinically appropriate method to compare diagnostic tests.
The clinical relevance of birch pollen profilin cross-reactivity in sensitized patients.
Wölbing, F; Kunz, J; Kempf, W E; Grimmel, C; Fischer, J; Biedermann, T
2017-04-01
Overlapping seasons and cross-reactivity, especially to grass pollen profilin, can hamper the diagnosis of birch pollen allergy. To identify the primary sensitizing allergen and the clinical relevance of cross-sensitization, we correlated sensitization profiles with in vitro and in vivo tests, symptom scores, and pollen counts. A total of 433 patients with positive skin prick test (SPT) to birch pollen were analyzed regarding IgE to major birch and grass pollen allergens Bet v 1 and Phl p 1/p 5 and the profilins Bet v 2 and Phl p 12. Subgroups were analyzed by basophil activation test (BAT) and CAP-FEIA-based cross- and self-inhibition tests. A total of 349 patients were sensitized to Bet v 1, 44 patients to both Bet v 1 and Bet v 2, and 15 patients to Bet v 2 only. From Bet v 2-sensitized patients, 40 were also sensitized to Phl p 12. Ex vivo, Bet v 2 and Phl p 12 induced dose-dependent activation in basophils of these patients. Cross- and self-inhibition tests with both allergens confirmed cross-reactivity. However, semiquantitative analysis of SPTs demonstrated markedly increased reactivity to grass compared to birch pollen extract in Bet v 2 only sensitized patients. Accordingly, in most of those patients, clinical symptoms precisely correlated with grass pollen counts. Identification of the clinically relevant and sensitizing allergen needs correlation of actual pollen counts with clinical symptoms and sensitization status to major allergens. Semiquantitative analysis of SPT or BAT and determining profilin-specific IgE can contribute to making the diagnosis. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Dinsmore, P K; Klaenhammer, T R
1997-05-01
A spontaneous mutant of the lactococcal phage phi31 that is insensitive to the phage defense mechanism AbiA was characterized in an effort to identify the phage factor(s) involved in sensitivity of phi31 to AbiA. A point mutation was localized in the genome of the AbiA-insensitive phage (phi31A) by heteroduplex analysis of a 9-kb region. The mutation (G to T) was within a 738-bp open reading frame (ORF245) and resulted in an arginine-to-leucine change in the predicted amino acid sequence of the protein. The mutant phi31A-ORF245 reduced the sensitivity of phi31 to AbiA when present in trans, indicating that the mutation in ORF245 is responsible for the AbiA insensitivity of phi31A. Transcription of ORF245 occurs early in the phage infection cycles of phi31 and phi31A and is unaffected by AbiA. Expansion of the phi31 sequence revealed ORF169 (immediately upstream of ORF245) and ORF71 (which ends 84 bp upstream of ORF169). Two inverted repeats lie within the 84-bp region between ORF71 and ORF169. Sequence analysis of an independently isolated AbiA-insensitive phage, phi31B, identified a mutation (G to A) in one of the inverted repeats. A 118-bp fragment from phi31, encompassing the 84-bp region between ORF71 and ORF169, eliminates AbiA activity against phi31 when present in trans, establishing a relationship between AbiA and this fragment. The study of this region of phage phi31 has identified an open reading frame (ORF245) and a 118-bp DNA fragment that interact with AbiA and are likely to be involved in the sensitivity of this phage to AbiA.
Ausderau, Karla K; Furlong, Melissa; Sideris, John; Bulluck, John; Little, Lauren M; Watson, Linda R; Boyd, Brian A; Belger, Aysenil; Dickie, Virginia A; Baranek, Grace T
2014-08-01
Sensory features are highly prevalent and heterogeneous among children with ASD. There is a need to identify homogenous groups of children with ASD based on sensory features (i.e., sensory subtypes) to inform research and treatment. Sensory subtypes and their stability over 1 year were identified through latent profile transition analysis (LPTA) among a national sample of children with ASD. Data were collected from caregivers of children with ASD ages 2-12 years at two time points (Time 1 N = 1294; Time 2 N = 884). Four sensory subtypes (Mild; Sensitive-Distressed; Attenuated-Preoccupied; Extreme-Mixed) were identified, which were supported by fit indices from the LPTA as well as current theoretical models that inform clinical practice. The Mild and Extreme-Mixed subtypes reflected quantitatively different sensory profiles, while the Sensitive-Distressed and Attenuated-Preoccupied subtypes reflected qualitatively different profiles. Further, subtypes reflected differential child (i.e., gender, developmental age, chronological age, autism severity) and family (i.e., income, mother's education) characteristics. Ninety-one percent of participants remained stable in their subtypes over 1 year. Characterizing the nature of homogenous sensory subtypes may facilitate assessment and intervention, as well as potentially inform biological mechanisms. © 2014 The Authors. Journal of Child Psychology and Psychiatry. © 2014 Association for Child and Adolescent Mental Health.
Diagnostic potential of Raman spectroscopy in Barrett's esophagus
NASA Astrophysics Data System (ADS)
Wong Kee Song, Louis-Michel; Molckovsky, Andrea; Wang, Kenneth K.; Burgart, Lawrence J.; Dolenko, Brion; Somorjai, Rajmund L.; Wilson, Brian C.
2005-04-01
Patients with Barrett's esophagus (BE) undergo periodic endoscopic surveillance with random biopsies in an effort to detect dysplastic or early cancerous lesions. Surveillance may be enhanced by near-infrared Raman spectroscopy (NIRS), which has the potential to identify endoscopically-occult dysplastic lesions within the Barrett's segment and allow for targeted biopsies. The aim of this study was to assess the diagnostic performance of NIRS for identifying dysplastic lesions in BE in vivo. Raman spectra (Pexc=70 mW; t=5 s) were collected from Barrett's mucosa at endoscopy using a custom-built NIRS system (λexc=785 nm) equipped with a filtered fiber-optic probe. Each probed site was biopsied for matching histological diagnosis as assessed by an expert pathologist. Diagnostic algorithms were developed using genetic algorithm-based feature selection and linear discriminant analysis, and classification was performed on all spectra with a bootstrap-based cross-validation scheme. The analysis comprised 192 samples (112 non-dysplastic, 54 low-grade dysplasia and 26 high-grade dysplasia/early adenocarcinoma) from 65 patients. Compared with histology, NIRS differentiated dysplastic from non-dysplastic Barrett's samples with 86% sensitivity, 88% specificity and 87% accuracy. NIRS identified 'high-risk' lesions (high-grade dysplasia/early adenocarcinoma) with 88% sensitivity, 89% specificity and 89% accuracy. In the present study, NIRS classified Barrett's epithelia with high and clinically-useful diagnostic accuracy.
Engineering applications of heuristic multilevel optimization methods
NASA Technical Reports Server (NTRS)
Barthelemy, Jean-Francois M.
1988-01-01
Some engineering applications of heuristic multilevel optimization methods are presented and the discussion focuses on the dependency matrix that indicates the relationship between problem functions and variables. Coordination of the subproblem optimizations is shown to be typically achieved through the use of exact or approximate sensitivity analysis. Areas for further development are identified.
Engineering applications of heuristic multilevel optimization methods
NASA Technical Reports Server (NTRS)
Barthelemy, Jean-Francois M.
1989-01-01
Some engineering applications of heuristic multilevel optimization methods are presented and the discussion focuses on the dependency matrix that indicates the relationship between problem functions and variables. Coordination of the subproblem optimizations is shown to be typically achieved through the use of exact or approximate sensitivity analysis. Areas for further development are identified.
USDA-ARS?s Scientific Manuscript database
Sugarbeet is being considered as one of the most viable feedstock alternatives to corn for biofuel production since herbicide resistant energy beets were deregulated by USDA in 2012. Growing sugarbeets for biofuel production may have significant impacts on soil health and water quality in the north-...
Anderson, Raydel D.; Wang, Xin; Katz, Lee S.; Vuong, Jeni T.; Bell, Melissa E.; Juni, Billie A.; Lowther, Sara A.; Lynfield, Ruth; MacNeil, Jessica R.; Mayer, Leonard W.
2012-01-01
PCR detecting the protein D (hpd) and fuculose kinase (fucK) genes showed high sensitivity and specificity for identifying Haemophilus influenzae and differentiating it from H. haemolyticus. Phylogenetic analysis using the 16S rRNA gene demonstrated two distinct groups for H. influenzae and H. haemolyticus. PMID:22301020
Probabilistic Cues to Grammatical Category in English Orthography and Their Influence during Reading
ERIC Educational Resources Information Center
Arciuli, Joanne; Monaghan, Padraic
2009-01-01
We investigated probabilistic cues to grammatical category (noun vs. verb) in English orthography. These cues are located in both the beginnings and endings of words--as identified in our large-scale corpus analysis. Experiment 1 tested participants' sensitivity to beginning and ending cues while making speeded grammatical classifications.…
Amarasinghe, Nirmalie Champika; De AlwisSenevirathne, Rohini
2016-10-17
Musculoskeletal disorders (MSDs) have been identified as a predisposing factor for lesser productivity, but no validated tool has been developed to assess them in the Sri- Lankan context. To develop a validated tool to assess the neck and upper limb MSDs. It comprises three components: item selections, item reduction using principal component analysis, and validation. A tentative self-administrated questionnaire was developed, translated, and pre-tested. Four important domains - neck, shoulder, elbow and wrist - were identified through principal component analysis. Prevalence of any MSDs was 38.1% and prevalence of neck, shoulder, elbow and wrist MSDs are 12.85%, 13.71%, 12%, 13.71% respectively. Content and criterion validity of the tool was assessed. Separate ROC curves were produced and sensitivity and specificity of neck (83.1%, 71.7%), shoulder (97.6%, 91.9%), elbow (98.2%, 87.2%), and wrist (97.6%, 94.9%) was determined. Cronbach's Alpha and correlation coefficient was above 0.7. The tool has high sensitivity, specificity, internal consistency, and test re-test reliability.
STRUCTURE OF THE UNIVERSITY PERSONALITY INVENTORY FOR CHINESE COLLEGE STUDENTS1,2
ZHANG, JIETING; LANZA, STEPHANIE; ZHANG, MINQIANG; SU, BINYUAN
2016-01-01
Summary The University Personality Inventory, a mental health instrument for college students, is frequently used for screening in China. However, its unidimensionality has been questioned. This study examined its dimensions to provide more information about the specific mental problems for students at risk. Four subsamples were randomly created from a sample (N = 6,110; M age = 19.1 yr.) of students at a university in China. Principal component analysis with Promax rotation was applied on the first two subsamples to explore dimension of the inventory. Confirmatory factor analysis was conducted on the third subsample to verify the exploratory dimensions. Finally, the identified factors were compared to the Sympton Checklist–90 (SCL–90) to support validity, and sex differences were examined, based on the fourth subsample. Five factors were identified: Physical Symptoms, Cognitive Symptoms, Emotional Vulnerability, Social Avoidance, and Interpersonal Sensitivity, accounting for 60.3% of the variance. All the five factors were significantly correlated with the SCL–90. Women significantly scored higher than men on Cognitive Symptoms and Interpersonal Sensitivity. PMID:25933045
Takahashi, Yuji; Shomura, Ayahiko; Sasaki, Takuji; Yano, Masahiro
2001-01-01
Hd6 is a quantitative trait locus involved in rice photoperiod sensitivity. It was detected in backcross progeny derived from a cross between the japonica variety Nipponbare and the indica variety Kasalath. To isolate a gene at Hd6, we used a large segregating population for the high-resolution and fine-scale mapping of Hd6 and constructed genomic clone contigs around the Hd6 region. Linkage analysis with P1-derived artificial chromosome clone-derived DNA markers delimited Hd6 to a 26.4-kb genomic region. We identified a gene encoding the α subunit of protein kinase CK2 (CK2α) in this region. The Nipponbare allele of CK2α contains a premature stop codon, and the resulting truncated product is undoubtedly nonfunctional. Genetic complementation analysis revealed that the Kasalath allele of CK2α increases days-to-heading. Map-based cloning with advanced backcross progeny enabled us to identify a gene underlying a quantitative trait locus even though it exhibited a relatively small effect on the phenotype. PMID:11416158
DOE Office of Scientific and Technical Information (OSTI.GOV)
Reents, W.D. Jr.
Particles present in the environment have significant affects in many areas from personal health due to atmospheric particles to various industrial processes that can be ruined due to particulate contamination such as semiconductor device manufacture and manufacture of sterile health products. The ability to detect deleterious contamination requires appropriate instrumentation to detect these particles. To prevent such contamination, the particle source must be identified by determining the composition of the offending particles. In a controlled environment, particle contamination often occurs in transients. In order to identify unknown particles, a technique must obtain compositional and size information regardless of particle identity,more » and perform this analysis in real-time so as to separate {open_quotes}background{close_quotes} particles from those produced in the transient event. Since processes are sensitive to certain particle size regimes and possibly, compositions, the instrumentation must be designed with these needs in mind. The authors have developed an instrument, the Ultra-Sensitive Particle Analysis System (USPAS) for situations where ultrafine particles, down to 0.002 micron, are of concern, such as the semiconductor manufacturing industry and the ambient environment.« less
Sensitivity Analysis in Sequential Decision Models.
Chen, Qiushi; Ayer, Turgay; Chhatwal, Jagpreet
2017-02-01
Sequential decision problems are frequently encountered in medical decision making, which are commonly solved using Markov decision processes (MDPs). Modeling guidelines recommend conducting sensitivity analyses in decision-analytic models to assess the robustness of the model results against the uncertainty in model parameters. However, standard methods of conducting sensitivity analyses cannot be directly applied to sequential decision problems because this would require evaluating all possible decision sequences, typically in the order of trillions, which is not practically feasible. As a result, most MDP-based modeling studies do not examine confidence in their recommended policies. In this study, we provide an approach to estimate uncertainty and confidence in the results of sequential decision models. First, we provide a probabilistic univariate method to identify the most sensitive parameters in MDPs. Second, we present a probabilistic multivariate approach to estimate the overall confidence in the recommended optimal policy considering joint uncertainty in the model parameters. We provide a graphical representation, which we call a policy acceptability curve, to summarize the confidence in the optimal policy by incorporating stakeholders' willingness to accept the base case policy. For a cost-effectiveness analysis, we provide an approach to construct a cost-effectiveness acceptability frontier, which shows the most cost-effective policy as well as the confidence in that for a given willingness to pay threshold. We demonstrate our approach using a simple MDP case study. We developed a method to conduct sensitivity analysis in sequential decision models, which could increase the credibility of these models among stakeholders.
Comparison of Four Saliva Detection Methods to Identify Expectorated Blood Spatter.
Park, Hee-Yeon; Son, Bu-Nam; Seo, Young-Il; Lim, Si-Keun
2015-11-01
Blood spatter analysis is an important step for crime scene reconstruction. The presence of saliva in blood spatter could indicate expectorated blood which is difficult to distinguish from impact spatter. In this study, four saliva test methods (SALIgAE(®) , Phadebas(®) sheet, RSID(™) -Saliva kit, and starch gel diffusion) were compared to identify the best method for detecting expectorated blood spatter. The RSID(™) -Saliva kit showed the highest sensitivity even when saliva was mixed with blood, and was not inhibited by the presence of blood. The SALIgAE(®) test provided easy and rapid results, but the yellow color of a positive reaction was overwhelmed by the red color of the blood. The starch gel diffusion method and the Phadebas(®) sheet exhibited relatively low sensitivity and the assay took a long time. When using the RSID(™) -Saliva kit for identifying saliva in blood, results should be read within 10 min. © 2015 American Academy of Forensic Sciences.
Kim, Hyun Seok; Mendiratta, Saurabh; Kim, Jiyeon; Pecot, Chad Victor; Larsen, Jill E.; Zubovych, Iryna; Seo, Bo Yeun; Kim, Jimi; Eskiocak, Banu; Chung, Hannah; McMillan, Elizabeth; Wu, Sherry; De Brabander, Jef; Komurov, Kakajan; Toombs, Jason E.; Wei, Shuguang; Peyton, Michael; Williams, Noelle; Gazdar, Adi F.; Posner, Bruce A.; Brekken, Rolf; Sood, Anil K.; Deberardinis, Ralph J.; Roth, Michael G.; Minna, John D.; White, Michael A.
2013-01-01
SUMMARY Context-specific molecular vulnerabilities that arise during tumor evolution represent an attractive intervention target class. However, the frequency and diversity of somatic lesions detected among lung tumors can confound efforts to identify these targets. To confront this challenge, we have applied parallel screening of chemical and genetic perturbations within a panel of molecularly annotated NSCLC lines to identify intervention opportunities tightly linked to molecular response indicators predictive of target sensitivity. Anchoring this analysis on a matched tumor/normal cell model from a lung adenocarcinoma patient identified three distinct target/response-indicator pairings that are represented with significant frequencies (6–16%) in the patient population. These include NLRP3 mutation/inflammasome activation-dependent FLIP addiction, co-occuring KRAS and LKB1 mutation-driven COPI addiction, and selective sensitivity to a synthetic indolotriazine that is specified by a 7-gene expression signature. Target efficacies were validated in vivo, and mechanism of action studies uncovered new cancer cell biology. PMID:24243015
Kim, Hyun Seok; Mendiratta, Saurabh; Kim, Jiyeon; Pecot, Chad Victor; Larsen, Jill E; Zubovych, Iryna; Seo, Bo Yeun; Kim, Jimi; Eskiocak, Banu; Chung, Hannah; McMillan, Elizabeth; Wu, Sherry; De Brabander, Jef; Komurov, Kakajan; Toombs, Jason E; Wei, Shuguang; Peyton, Michael; Williams, Noelle; Gazdar, Adi F; Posner, Bruce A; Brekken, Rolf A; Sood, Anil K; Deberardinis, Ralph J; Roth, Michael G; Minna, John D; White, Michael A
2013-10-24
Context-specific molecular vulnerabilities that arise during tumor evolution represent an attractive intervention target class. However, the frequency and diversity of somatic lesions detected among lung tumors can confound efforts to identify these targets. To confront this challenge, we have applied parallel screening of chemical and genetic perturbations within a panel of molecularly annotated NSCLC lines to identify intervention opportunities tightly linked to molecular response indicators predictive of target sensitivity. Anchoring this analysis on a matched tumor/normal cell model from a lung adenocarcinoma patient identified three distinct target/response-indicator pairings that are represented with significant frequencies (6%-16%) in the patient population. These include NLRP3 mutation/inflammasome activation-dependent FLIP addiction, co-occurring KRAS and LKB1 mutation-driven COPI addiction, and selective sensitivity to a synthetic indolotriazine that is specified by a seven-gene expression signature. Target efficacies were validated in vivo, and mechanism-of-action studies informed generalizable principles underpinning cancer cell biology. Copyright © 2013 Elsevier Inc. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Golbus, Jessica R.; Puckelwartz, Megan J.; Dellefave-Castillo, Lisa
Background—Cardiomyopathy is highly heritable but genetically diverse. At present, genetic testing for cardiomyopathy uses targeted sequencing to simultaneously assess the coding regions of more than 50 genes. New genes are routinely added to panels to improve the diagnostic yield. With the anticipated $1000 genome, it is expected that genetic testing will shift towards comprehensive genome sequencing accompanied by targeted gene analysis. Therefore, we assessed the reliability of whole genome sequencing and targeted analysis to identify cardiomyopathy variants in 11 subjects with cardiomyopathy. Methods and Results—Whole genome sequencing with an average of 37× coverage was combined with targeted analysis focused onmore » 204 genes linked to cardiomyopathy. Genetic variants were scored using multiple prediction algorithms combined with frequency data from public databases. This pipeline yielded 1-14 potentially pathogenic variants per individual. Variants were further analyzed using clinical criteria and/or segregation analysis. Three of three previously identified primary mutations were detected by this analysis. In six subjects for whom the primary mutation was previously unknown, we identified mutations that segregated with disease, had clinical correlates, and/or had additional pathological correlation to provide evidence for causality. For two subjects with previously known primary mutations, we identified additional variants that may act as modifiers of disease severity. In total, we identified the likely pathological mutation in 9 of 11 (82%) subjects. We conclude that these pilot data demonstrate that ~30-40× coverage whole genome sequencing combined with targeted analysis is feasible and sensitive to identify rare variants in cardiomyopathy-associated genes.« less
Quantitative methods to direct exploration based on hydrogeologic information
Graettinger, A.J.; Lee, J.; Reeves, H.W.; Dethan, D.
2006-01-01
Quantitatively Directed Exploration (QDE) approaches based on information such as model sensitivity, input data covariance and model output covariance are presented. Seven approaches for directing exploration are developed, applied, and evaluated on a synthetic hydrogeologic site. The QDE approaches evaluate input information uncertainty, subsurface model sensitivity and, most importantly, output covariance to identify the next location to sample. Spatial input parameter values and covariances are calculated with the multivariate conditional probability calculation from a limited number of samples. A variogram structure is used during data extrapolation to describe the spatial continuity, or correlation, of subsurface information. Model sensitivity can be determined by perturbing input data and evaluating output response or, as in this work, sensitivities can be programmed directly into an analysis model. Output covariance is calculated by the First-Order Second Moment (FOSM) method, which combines the covariance of input information with model sensitivity. A groundwater flow example, modeled in MODFLOW-2000, is chosen to demonstrate the seven QDE approaches. MODFLOW-2000 is used to obtain the piezometric head and the model sensitivity simultaneously. The seven QDE approaches are evaluated based on the accuracy of the modeled piezometric head after information from a QDE sample is added. For the synthetic site used in this study, the QDE approach that identifies the location of hydraulic conductivity that contributes the most to the overall piezometric head variance proved to be the best method to quantitatively direct exploration. ?? IWA Publishing 2006.
Urban Principle of Water Sensitive Design in Kampung Kamboja at Pontianak City
NASA Astrophysics Data System (ADS)
Hasriyanti, N.; Ryanti, E.
2017-07-01
This study will define the design principles of settlement area banks of the Kapuas Pontianak to approach the concept of water sensitive urban design (WSUD) in densely populated residential areas. Using a case study of a region densely located on the banks of the river with engineering literature to formulate the aspects taken into consideration and the components are arranged in the design, analysis descriptive paradigm rationalistic to identify the characteristics of residential areas riverbank with consideration of elements WSUD and formulate design principles residential area that is sensitive to water. This research is important to do because of problems related to the water management system in the settlement bank of the river in the city of Pontianak do not maximize. So that the primacy of this study contains several objectives to be achieved is to identify the characteristics of the settlement area riverbanks under consideration aspects areas design that is sensitive to water and principle areas design that will formulate the structure of the existing problems related to the needs of the community infrastructure facilities infrastructure neighborhoods and formulate and create guidelines for appropriate technology for integrated water management systems in the residential area of the riverbank and engineering design for the settlements are sensitive to water (WSUD). The final aim of the study is expected to achieve water management systems in residential areas by utilizing the abundant rainwater availability by using LID (Low Impact Development) through the concept of urban design that sensitive water
Calabrese, Emma; Maaser, Christian; Zorzi, Francesca; Kannengiesser, Klaus; Hanauer, Stephen B; Bruining, David H; Iacucci, Marietta; Maconi, Giovanni; Novak, Kerri L; Panaccione, Remo; Strobel, Deike; Wilson, Stephanie R; Watanabe, Mamoru; Pallone, Francesco; Ghosh, Subrata
2016-05-01
Bowel ultrasonography (US) is considered a useful technique for assessing mural inflammation and complications in Crohn's disease (CD). The aim of this review is to appraise the evidence on the accuracy of bowel US for CD. In addition, we aim to provide recommendations for its optimal use. Publications were identified by literature search from 1992 to 2014 and selected based on predefined criteria: 15 or more patients; bowel US for diagnosing CD, complications, postoperative recurrence, activity; adequate reference standards; prospective study design; data reported to allow calculation of sensitivity, specificity, agreement, or correlation values; articles published in English. The search yielded 655 articles, of which 63 were found to be eligible and retrieved as full-text articles for analysis. Bowel US showed 79.7% sensitivity and 96.7% specificity for the diagnosis of suspected CD, and 89% sensitivity and 94.3% specificity for initial assessment in established patients with CD. Bowel US identified ileal CD with 92.7% sensitivity, 88.2% specificity, and colon CD with 81.8% sensitivity, 95.3% specificity, with lower accuracy for detecting proximal lesions. The oral contrast agent improves the sensitivity and specificity in determining CD lesions and in assessing sites and extent. Bowel US is a tool for evaluation of CD lesions in terms of complications, postoperative recurrence, and monitoring response to medical therapy; it reliably detects postoperative recurrence and complications, as well as offers the possibility of monitoring disease progression.
Sensitivity of global terrestrial ecosystems to climate variability.
Seddon, Alistair W R; Macias-Fauria, Marc; Long, Peter R; Benz, David; Willis, Kathy J
2016-03-10
The identification of properties that contribute to the persistence and resilience of ecosystems despite climate change constitutes a research priority of global relevance. Here we present a novel, empirical approach to assess the relative sensitivity of ecosystems to climate variability, one property of resilience that builds on theoretical modelling work recognizing that systems closer to critical thresholds respond more sensitively to external perturbations. We develop a new metric, the vegetation sensitivity index, that identifies areas sensitive to climate variability over the past 14 years. The metric uses time series data derived from the moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index, and three climatic variables that drive vegetation productivity (air temperature, water availability and cloud cover). Underlying the analysis is an autoregressive modelling approach used to identify climate drivers of vegetation productivity on monthly timescales, in addition to regions with memory effects and reduced response rates to external forcing. We find ecologically sensitive regions with amplified responses to climate variability in the Arctic tundra, parts of the boreal forest belt, the tropical rainforest, alpine regions worldwide, steppe and prairie regions of central Asia and North and South America, the Caatinga deciduous forest in eastern South America, and eastern areas of Australia. Our study provides a quantitative methodology for assessing the relative response rate of ecosystems--be they natural or with a strong anthropogenic signature--to environmental variability, which is the first step towards addressing why some regions appear to be more sensitive than others, and what impact this has on the resilience of ecosystem service provision and human well-being.
Sensitivity of global terrestrial ecosystems to climate variability
NASA Astrophysics Data System (ADS)
Seddon, Alistair W. R.; Macias-Fauria, Marc; Long, Peter R.; Benz, David; Willis, Kathy J.
2016-03-01
The identification of properties that contribute to the persistence and resilience of ecosystems despite climate change constitutes a research priority of global relevance. Here we present a novel, empirical approach to assess the relative sensitivity of ecosystems to climate variability, one property of resilience that builds on theoretical modelling work recognizing that systems closer to critical thresholds respond more sensitively to external perturbations. We develop a new metric, the vegetation sensitivity index, that identifies areas sensitive to climate variability over the past 14 years. The metric uses time series data derived from the moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index, and three climatic variables that drive vegetation productivity (air temperature, water availability and cloud cover). Underlying the analysis is an autoregressive modelling approach used to identify climate drivers of vegetation productivity on monthly timescales, in addition to regions with memory effects and reduced response rates to external forcing. We find ecologically sensitive regions with amplified responses to climate variability in the Arctic tundra, parts of the boreal forest belt, the tropical rainforest, alpine regions worldwide, steppe and prairie regions of central Asia and North and South America, the Caatinga deciduous forest in eastern South America, and eastern areas of Australia. Our study provides a quantitative methodology for assessing the relative response rate of ecosystems—be they natural or with a strong anthropogenic signature—to environmental variability, which is the first step towards addressing why some regions appear to be more sensitive than others, and what impact this has on the resilience of ecosystem service provision and human well-being.
A Monte Carlo Sensitivity Analysis of CF2 and CF Radical Densities in a c-C4F8 Plasma
NASA Technical Reports Server (NTRS)
Bose, Deepak; Rauf, Shahid; Hash, D. B.; Govindan, T. R.; Meyyappan, M.
2004-01-01
A Monte Carlo sensitivity analysis is used to build a plasma chemistry model for octacyclofluorobutane (c-C4F8) which is commonly used in dielectric etch. Experimental data are used both quantitatively and quantitatively to analyze the gas phase and gas surface reactions for neutral radical chemistry. The sensitivity data of the resulting model identifies a few critical gas phase and surface aided reactions that account for most of the uncertainty in the CF2 and CF radical densities. Electron impact dissociation of small radicals (CF2 and CF) and their surface recombination reactions are found to be the rate-limiting steps in the neutral radical chemistry. The relative rates for these electron impact dissociation and surface recombination reactions are also suggested. The resulting mechanism is able to explain the measurements of CF2 and CF densities available in the literature and also their hollow spatial density profiles.
Vialet-Chabrand, Silvere; Griffiths, Howard
2017-01-01
The physical requirement for charge to balance across biological membranes means that the transmembrane transport of each ionic species is interrelated, and manipulating solute flux through any one transporter will affect other transporters at the same membrane, often with unforeseen consequences. The OnGuard systems modeling platform has helped to resolve the mechanics of stomatal movements, uncovering previously unexpected behaviors of stomata. To date, however, the manual approach to exploring model parameter space has captured little formal information about the emergent connections between parameters that define the most interesting properties of the system as a whole. Here, we introduce global sensitivity analysis to identify interacting parameters affecting a number of outputs commonly accessed in experiments in Arabidopsis (Arabidopsis thaliana). The analysis highlights synergies between transporters affecting the balance between Ca2+ sequestration and Ca2+ release pathways, notably those associated with internal Ca2+ stores and their turnover. Other, unexpected synergies appear, including with the plasma membrane anion channels and H+-ATPase and with the tonoplast TPK K+ channel. These emergent synergies, and the core hubs of interaction that they define, identify subsets of transporters associated with free cytosolic Ca2+ concentration that represent key targets to enhance plant performance in the future. They also highlight the importance of interactions between the voltage regulation of the plasma membrane and tonoplast in coordinating transport between the different cellular compartments. PMID:28432256
Zhou, Zhiran; Zhang, Huitian; Lei, Yunxia
2016-10-01
To evaluate the diagnostic value of secreted frizzled-related protein 2 (SFRP2) gene promoter hypermethylation in stool for colorectal cancer (CRC). Open published diagnostic study of SFRP2 gene promoter hypermethylation in stool for CRC detection was electronic searched in the databases of PubMed, EMBASE, Cochrane Library, Web of Science, and China National Knowledge Infrastructure. The data of true positive, false positive false negative, and true negative identified by stool SFRP2 gene hypermethylation was extracted and pooled for diagnostic sensitivity, specificity, and summary receiver operating characteristic (SROC) curve. According to the inclusion and exclusion criteria, we finally included nine publications with 792 cases in the meta-analysis. Thus, the diagnostic sensitivity was aggregated through random effect model. The pooled sensitivity was 0.82 with the corresponding 95% confidence interval (95% CI) of 0.79-0.85; the pooled specificity and its corresponding 95% CI were 0.47 and 0.40-0.53 by the random effect model; we pooled the SROC curve by sensitivity versus specificity according to data published in the nine studies. The area under the SROC curve was 0.70 (95% CI: 0.65-0.73). SFRP2 gene promoter hypermethylation in stool can was a potential biomarker for CRC diagnosis with relative high sensitivity.
Comparative peptidomics analysis of neural adaptations in rats repeatedly exposed to amphetamine.
Romanova, Elena V; Lee, Ji Eun; Kelleher, Neil L; Sweedler, Jonathan V; Gulley, Joshua M
2012-10-01
Repeated exposure to amphetamine (AMPH) induces long-lasting behavioral changes, referred to as sensitization, that are accompanied by various neuroadaptations in the brain. To investigate the chemical changes that occur during behavioral sensitization, we applied a comparative proteomics approach to screen for neuropeptide changes in a rodent model of AMPH-induced sensitization. By measuring peptide profiles with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and comparing signal intensities using principal component analysis and variance statistics, subsets of peptides are found with significant differences in the dorsal striatum, nucleus accumbens, and medial prefrontal cortex of AMPH-sensitized male Sprague-Dawley rats. These biomarker peptides, identified in follow-up analyses using liquid chromatography and tandem mass spectrometry, suggest that behavioral sensitization to AMPH is associated with complex chemical adaptations that regulate energy/metabolism, neurotransmission, apoptosis, neuroprotection, and neuritogenesis, as well as cytoskeleton integrity and neuronal morphology. Our data contribute to a growing number of reports showing that in addition to the mesolimbic dopamine system, which is the best known signaling pathway involved with reinforcing the effect of psychostimulants, concomitant chemical changes in other pathways and in neuronal organization may play a part in the overall effect of chronic AMPH exposure on behavior. © 2012 The Authors Journal of Neurochemistry © 2012 International Society for Neurochemistry.
High frequency QRS ECG predicts ischemic defects during myocardial perfusion imaging
NASA Technical Reports Server (NTRS)
2004-01-01
Changes in high frequency QRS components of the electrocardiogram (HF QRS ECG) (150-250 Hz) are more sensitive than changes in conventional ST segments for detecting myocardial ischemia. We investigated the accuracy of 12-lead HF QRS ECG in detecting ischemia during adenosine tetrofosmin myocardial perfusion imaging (MPI). 12-lead HF QRS ECG recordings were obtained from 45 patients before and during adenosine technetium-99 tetrofosmin MPI tests. Before the adenosine infusions, recordings of HF QRS were analyzed according to a morphological score that incorporated the number, type and location of reduced amplitude zones (RAZs) present in the 12 leads. During the adenosine infusions, recordings of HF QRS were analyzed according to the maximum percentage changes (in both the positive and negative directions) that occurred in root mean square (RMS) voltage amplitudes within the 12 leads. The best set of prospective HF QRS criteria had a sensitivity of 94% and a specificity of 83% for correctly identifying the MPI result. The sensitivity of simultaneous ST segment changes (18%) was significantly lower than that of any individual HF QRS criterion (P less than 0.00l). Analysis of 12-lead HF QRS ECG is highly sensitive and specific for detecting ischemic perfusion defects during adenosine MPI stress tests and significantly more sensitive than analysis of conventional ST segments.
High frequency QRS ECG predicts ischemic defects during myocardial perfusion imaging
NASA Technical Reports Server (NTRS)
Rahman, Atiar
2006-01-01
Background: Changes in high frequency QRS components of the electrocardiogram (HF QRS ECG) (150-250 Hz) are more sensitive than changes in conventional ST segments for detecting myocardial ischemia. We investigated the accuracy of 12-lead HF QRS ECG in detecting ischemia during adenosine tetrofosmin myocardial perfusion imaging (MPI). Methods and Results: 12-lead HF QRS ECG recordings were obtained from 45 patients before and during adenosine technetium-99 tetrofosmin MPI tests. Before the adenosine infusions, recordings of HF QRS were analyzed according to a morphological score that incorporated the number, type and location of reduced amplitude zones (RAZs) present in the 12 leads. During the adenosine infusions, recordings of HF QRS were analyzed according to the maximum percentage changes (in both the positive and negative directions) that occurred in root mean square (RMS) voltage amplitudes within the 12 leads. The best set of prospective HF QRS criteria had a sensitivity of 94% and a specificity of 83% for correctly identifying the MPI result. The sensitivity of simultaneous ST segment changes (18%) was significantly lower than that of any individual HF QRS criterion (P<0.001). Conclusions: Analysis of 12-lead HF QRS ECG is highly sensitive and specific for detecting ischemic perfusion defects during adenosine MPI stress tests and significantly more sensitive than analysis of conventional ST segments.
NASA Astrophysics Data System (ADS)
Hwang, Joonki; Lee, Sangyeop; Choo, Jaebum
2016-06-01
A novel surface-enhanced Raman scattering (SERS)-based lateral flow immunoassay (LFA) biosensor was developed to resolve problems associated with conventional LFA strips (e.g., limits in quantitative analysis and low sensitivity). In our SERS-based biosensor, Raman reporter-labeled hollow gold nanospheres (HGNs) were used as SERS detection probes instead of gold nanoparticles. With the proposed SERS-based LFA strip, the presence of a target antigen can be identified through a colour change in the test zone. Furthermore, highly sensitive quantitative evaluation is possible by measuring SERS signals from the test zone. To verify the feasibility of the SERS-based LFA strip platform, an immunoassay of staphylococcal enterotoxin B (SEB) was performed as a model reaction. The limit of detection (LOD) for SEB, as determined with the SERS-based LFA strip, was estimated to be 0.001 ng mL-1. This value is approximately three orders of magnitude more sensitive than that achieved with the corresponding ELISA-based method. The proposed SERS-based LFA strip sensor shows significant potential for the rapid and sensitive detection of target markers in a simplified manner.A novel surface-enhanced Raman scattering (SERS)-based lateral flow immunoassay (LFA) biosensor was developed to resolve problems associated with conventional LFA strips (e.g., limits in quantitative analysis and low sensitivity). In our SERS-based biosensor, Raman reporter-labeled hollow gold nanospheres (HGNs) were used as SERS detection probes instead of gold nanoparticles. With the proposed SERS-based LFA strip, the presence of a target antigen can be identified through a colour change in the test zone. Furthermore, highly sensitive quantitative evaluation is possible by measuring SERS signals from the test zone. To verify the feasibility of the SERS-based LFA strip platform, an immunoassay of staphylococcal enterotoxin B (SEB) was performed as a model reaction. The limit of detection (LOD) for SEB, as determined with the SERS-based LFA strip, was estimated to be 0.001 ng mL-1. This value is approximately three orders of magnitude more sensitive than that achieved with the corresponding ELISA-based method. The proposed SERS-based LFA strip sensor shows significant potential for the rapid and sensitive detection of target markers in a simplified manner. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr07243c
Quantitative Ultrasound for Measuring Obstructive Severity in Children with Hydronephrosis.
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.
Panas, Michael W.; Mao, Rong; Delanoy, Michelle; Flanagan, John J.; Binder, Steven R.; Rebman, Alison W.; Montoya, Jose G.; Soloski, Mark J.; Steere, Allen C.; Dattwyler, Raymond J.; Arnaboldi, Paul M.; Aucott, John N.
2015-01-01
The current standard for laboratory diagnosis of Lyme disease in the United States is serologic detection of antibodies against Borrelia burgdorferi. The Centers for Disease Control and Prevention recommends a two-tiered testing algorithm; however, this scheme has limited sensitivity for detecting early Lyme disease. Thus, there is a need to improve diagnostics for Lyme disease at the early stage, when antibiotic treatment is highly efficacious. We examined novel and established antigen markers to develop a multiplex panel that identifies early infection using the combined sensitivity of multiple markers while simultaneously maintaining high specificity by requiring positive results for two markers to designate a positive test. Ten markers were selected from our initial analysis of 62 B. burgdorferi surface proteins and synthetic peptides by assessing binding of IgG and IgM to each in a training set of Lyme disease patient samples and controls. In a validation set, this 10-antigen panel identified a higher proportion of early-Lyme-disease patients as positive at the baseline or posttreatment visit than two-tiered testing (87.5% and 67.5%, respectively; P < 0.05). Equivalent specificities of 100% were observed in 26 healthy controls. Upon further analysis, positivity on the novel 10-antigen panel was associated with longer illness duration and multiple erythema migrans. The improved sensitivity and comparable specificity of our 10-antigen panel compared to two-tiered testing in detecting early B. burgdorferi infection indicates that multiplex analysis, featuring the next generation of markers, could advance diagnostic technology to better aid clinicians in diagnosing and treating early Lyme disease. PMID:26447113
Bedside Diagnosis of Dysphagia: A Systematic Review
O’Horo, John C.; Rogus-Pulia, Nicole; Garcia-Arguello, Lisbeth; Robbins, JoAnne; Safdar, Nasia
2015-01-01
Background Dysphagia is associated with aspiration, pneumonia and malnutrition, but remains challenging to identify at the bedside. A variety of exam protocols and maneuvers are commonly used, but the efficacy of these maneuvers is highly variable. Methods We conducted a comprehensive search of seven databases, including MEDLINE, EMBASE and Scopus, from each database’s earliest inception through June 5th, 2013. Studies reporting diagnostic performance of a bedside examination maneuver compared to a reference gold standard (videofluoroscopic swallow study [VFSS] or flexible endoscopic evaluation of swallowing with sensory testing [FEEST]) were included for analysis. From each study, data were abstracted based on the type of diagnostic method and reference standard study population and inclusion/exclusion characteristics, design and prediction of aspiration. Results The search strategy identified 38 articles meeting inclusion criteria. Overall, most bedside examinations lacked sufficient sensitivity to be used for screening purposes across all patient populations examined. Individual studies found dysphonia assessments, abnormal pharyngeal sensation assessments, dual axis accelerometry, and one description of water swallow testing to be sensitive tools, but none were reported as consistently sensitive. A preponderance of identified studies was in post-stroke adults, limiting the generalizability of results. Conclusions No bedside screening protocol has been shown to provide adequate predictive value for presence of aspiration. Several individual exam maneuvers demonstrated reasonable sensitivity, but reproducibility and consistency of these protocols was not established. More research is needed to design an optimal protocol for dysphagia detection. PMID:25581840
Characterization of Cannabis sativa allergens.
Nayak, Ajay P; Green, Brett J; Sussman, Gordon; Berlin, Noam; Lata, Hemant; Chandra, Suman; ElSohly, Mahmoud A; Hettick, Justin M; Beezhold, Donald H
2013-07-01
Allergic sensitization to Cannabis sativa is rarely reported, but the increasing consumption of marijuana has resulted in an increase in the number of individuals who become sensitized. To date, little is known about the causal allergens associated with C sativa. To characterize marijuana allergens in different components of the C sativa plant using serum IgE from marijuana sensitized patients. Serum samples from 23 patients with a positive skin prick test result to a crude C sativa extract were evaluated. IgE reactivity was variable between patients and C sativa extracts. IgE reactivity to C sativa proteins in Western blots was heterogeneous and ranged from 10 to 70 kDa. Putative allergens derived from 2-dimensional gels were identified. Prominent IgE reactive bands included a 23-kDa oxygen-evolving enhancer protein 2 and a 50-kDa protein identified to be the photosynthetic enzyme ribulose-1,5-bisphosphate carboxylase/oxygenase. Additional proteins were identified in the proteomic analysis, including those from adenosine triphosphate synthase, glyceraldehyde-3-phosphate dehydrogenase, phosphoglycerate kinase, and luminal binding protein (heat shock protein 70), suggesting these proteins are potential allergens. Deglycosylation studies helped refine protein allergen identification and demonstrated significant IgE antibodies against plant oligosaccharides that could help explain cross-reactivity. Identification and characterization of allergens from C sativa may be helpful in further understanding allergic sensitization to this plant species. Copyright © 2013 American College of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.
Guo, B Z; Xu, G; Cao, Y G; Holbrook, C C; Lynch, R E
2006-02-01
Preharvest aflatoxin contamination has been identified by the peanut industry as a serious issue in food safety and human health because of the carcinogenic toxicity. Drought stress is the most important environmental factor exacerbating Aspergillus infection and aflatoxin contamination in peanut. The development of drought-tolerant peanut cultivars could reduce aflatoxin contamination and would represent a major advance in the peanut industry. In this study, we identified a novel PLD gene in peanut (Arachis hypogaea), encoding a putative phospholipase D (PLD, EC 3.1.4.4). The completed cDNA sequence was obtained by using the consensus-degenerated hybrid oligonucleotide primer strategy. The deduced amino acid sequence shows high identity with known PLDs, and has similar conserved domains. The PLD gene expression under drought stress has been studied using four peanut lines: Tifton 8 and A13 (both drought tolerant) and Georgia Green (moderate) and PI 196754 (drought sensitive). Northern analysis showed that PLD gene expression was induced faster by drought stress in the drought-sensitive lines than the drought tolerance lines. Southern analysis showed that cultivated peanut has multiple copies (3 to 5 copies) of the PLD gene. These results suggest that peanut PLD may be involved in drought sensitivity and tolerance responses. Peanut PLD gene expression may be useful as a tool in germplasm screening for drought tolerance.
Hu, Fang; Rishishwar, Lavanya; Sivadas, Ambily; Mitchell, Gabriel J; Jordan, I King; Murphy, Timothy F; Gilsdorf, Janet R; Mayer, Leonard W; Wang, Xin
2016-12-01
Haemophilus haemolyticus has been recently discovered to have the potential to cause invasive disease. It is closely related to nontypeable Haemophilus influenzae (NT H. influenzae). NT H. influenzae and H. haemolyticus are often misidentified because none of the existing tests targeting the known phenotypes of H. haemolyticus are able to specifically identify H. haemolyticus Through comparative genomic analysis of H. haemolyticus and NT H. influenzae, we identified genes unique to H. haemolyticus that can be used as targets for the identification of H. haemolyticus A real-time PCR targeting purT (encoding phosphoribosylglycinamide formyltransferase 2 in the purine synthesis pathway) was developed and evaluated. The lower limit of detection was 40 genomes/PCR; the sensitivity and specificity in detecting H. haemolyticus were 98.9% and 97%, respectively. To improve the discrimination of H. haemolyticus and NT H. influenzae, a testing scheme combining two targets (H. haemolyticus purT and H. influenzae hpd, encoding protein D lipoprotein) was also evaluated and showed 96.7% sensitivity and 98.2% specificity for the identification of H. haemolyticus and 92.8% sensitivity and 100% specificity for the identification of H. influenzae, respectively. The dual-target testing scheme can be used for the diagnosis and surveillance of infection and disease caused by H. haemolyticus and NT H. influenzae. Copyright © 2016, American Society for Microbiology. All Rights Reserved.
Hu, Fang; Rishishwar, Lavanya; Sivadas, Ambily; Mitchell, Gabriel J.; Jordan, I. King; Murphy, Timothy F.; Gilsdorf, Janet R.; Mayer, Leonard W.
2016-01-01
Haemophilus haemolyticus has been recently discovered to have the potential to cause invasive disease. It is closely related to nontypeable Haemophilus influenzae (NT H. influenzae). NT H. influenzae and H. haemolyticus are often misidentified because none of the existing tests targeting the known phenotypes of H. haemolyticus are able to specifically identify H. haemolyticus. Through comparative genomic analysis of H. haemolyticus and NT H. influenzae, we identified genes unique to H. haemolyticus that can be used as targets for the identification of H. haemolyticus. A real-time PCR targeting purT (encoding phosphoribosylglycinamide formyltransferase 2 in the purine synthesis pathway) was developed and evaluated. The lower limit of detection was 40 genomes/PCR; the sensitivity and specificity in detecting H. haemolyticus were 98.9% and 97%, respectively. To improve the discrimination of H. haemolyticus and NT H. influenzae, a testing scheme combining two targets (H. haemolyticus purT and H. influenzae hpd, encoding protein D lipoprotein) was also evaluated and showed 96.7% sensitivity and 98.2% specificity for the identification of H. haemolyticus and 92.8% sensitivity and 100% specificity for the identification of H. influenzae, respectively. The dual-target testing scheme can be used for the diagnosis and surveillance of infection and disease caused by H. haemolyticus and NT H. influenzae. PMID:27707939
Arnau, E G; Andersen, K E; Bruze, M; Frosch, P J; Johansen, J D; Menné, T; Rastogi, S C; White, I R; Lepoittevin, J P
2000-12-01
Fragrance materials are among the most common causes of allergic contact dermatitis. The aim of this study was to identify in a perfume fragrance allergens not included in the fragrance mix, by use of bioassay-guided chemical fractionation and chemical analysis/structure-activity relationships (SARs). The basis for the investigation was a 45-year-old woman allergic to her own perfume. She had a negative patch test to the fragrance mix and agreed to participate in the study. Chemical fractionation of the perfume concentrate was used for repeated patch testing and/or repeated open application test on the pre-sensitized patient. The chemical composition of the fractions giving a positive patch-test response and repeated open application test reactions was obtained by gas chromatography-mass spectrometry. From the compounds identified, those that contained a "structural alert" in their chemical structure, indicating an ability to modify skin proteins and thus behave as a skin sensitizer, were tested on the patient. The patient reacted positively to the synthetic fragrance p-t-butyl-alpha-methylhydrocinnamic aldehyde (Lilial), a widely used fragrance compound not present in the fragrance mix. The combination of bioassay-guided chemical fractionation and chemical analysis/structure-activity relationships seems to be a valuable tool for the investigation of contact allergy to fragrance materials.
Walmsley, Christopher W; McCurry, Matthew R; Clausen, Phillip D; McHenry, Colin R
2013-01-01
Finite element analysis (FEA) is a computational technique of growing popularity in the field of comparative biomechanics, and is an easily accessible platform for form-function analyses of biological structures. However, its rapid evolution in recent years from a novel approach to common practice demands some scrutiny in regards to the validity of results and the appropriateness of assumptions inherent in setting up simulations. Both validation and sensitivity analyses remain unexplored in many comparative analyses, and assumptions considered to be 'reasonable' are often assumed to have little influence on the results and their interpretation. HERE WE REPORT AN EXTENSIVE SENSITIVITY ANALYSIS WHERE HIGH RESOLUTION FINITE ELEMENT (FE) MODELS OF MANDIBLES FROM SEVEN SPECIES OF CROCODILE WERE ANALYSED UNDER LOADS TYPICAL FOR COMPARATIVE ANALYSIS: biting, shaking, and twisting. Simulations explored the effect on both the absolute response and the interspecies pattern of results to variations in commonly used input parameters. Our sensitivity analysis focuses on assumptions relating to the selection of material properties (heterogeneous or homogeneous), scaling (standardising volume, surface area, or length), tooth position (front, mid, or back tooth engagement), and linear load case (type of loading for each feeding type). Our findings show that in a comparative context, FE models are far less sensitive to the selection of material property values and scaling to either volume or surface area than they are to those assumptions relating to the functional aspects of the simulation, such as tooth position and linear load case. Results show a complex interaction between simulation assumptions, depending on the combination of assumptions and the overall shape of each specimen. Keeping assumptions consistent between models in an analysis does not ensure that results can be generalised beyond the specific set of assumptions used. Logically, different comparative datasets would also be sensitive to identical simulation assumptions; hence, modelling assumptions should undergo rigorous selection. The accuracy of input data is paramount, and simulations should focus on taking biological context into account. Ideally, validation of simulations should be addressed; however, where validation is impossible or unfeasible, sensitivity analyses should be performed to identify which assumptions have the greatest influence upon the results.
NASA Astrophysics Data System (ADS)
Meliga, Philippe
2017-07-01
We provide in-depth scrutiny of two methods making use of adjoint-based gradients to compute the sensitivity of drag in the two-dimensional, periodic flow past a circular cylinder (Re≲189 ): first, the time-stepping analysis used in Meliga et al. [Phys. Fluids 26, 104101 (2014), 10.1063/1.4896941] that relies on classical Navier-Stokes modeling and determines the sensitivity to any generic control force from time-dependent adjoint equations marched backwards in time; and, second, a self-consistent approach building on the model of Mantič-Lugo et al. [Phys. Rev. Lett. 113, 084501 (2014), 10.1103/PhysRevLett.113.084501] to compute semilinear approximations of the sensitivity to the mean and fluctuating components of the force. Both approaches are applied to open-loop control by a small secondary cylinder and allow identifying the sensitive regions without knowledge of the controlled states. The theoretical predictions obtained by time-stepping analysis reproduce well the results obtained by direct numerical simulation of the two-cylinder system. So do the predictions obtained by self-consistent analysis, which corroborates the relevance of the approach as a guideline for efficient and systematic control design in the attempt to reduce drag, even though the Reynolds number is not close to the instability threshold and the oscillation amplitude is not small. This is because, unlike simpler approaches relying on linear stability analysis to predict the main features of the flow unsteadiness, the semilinear framework encompasses rigorously the effect of the control on the mean flow, as well as on the finite-amplitude fluctuation that feeds back nonlinearly onto the mean flow via the formation of Reynolds stresses. Such results are especially promising as the self-consistent approach determines the sensitivity from time-independent equations that can be solved iteratively, which makes it generally less computationally demanding. We ultimately discuss the extent to which relevant information can be gained from a hybrid modeling computing self-consistent sensitivities from the postprocessing of DNS data. Application to alternative control objectives such as increasing the lift and alleviating the fluctuating drag and lift is also discussed.
McCurry, Matthew R.; Clausen, Phillip D.; McHenry, Colin R.
2013-01-01
Finite element analysis (FEA) is a computational technique of growing popularity in the field of comparative biomechanics, and is an easily accessible platform for form-function analyses of biological structures. However, its rapid evolution in recent years from a novel approach to common practice demands some scrutiny in regards to the validity of results and the appropriateness of assumptions inherent in setting up simulations. Both validation and sensitivity analyses remain unexplored in many comparative analyses, and assumptions considered to be ‘reasonable’ are often assumed to have little influence on the results and their interpretation. Here we report an extensive sensitivity analysis where high resolution finite element (FE) models of mandibles from seven species of crocodile were analysed under loads typical for comparative analysis: biting, shaking, and twisting. Simulations explored the effect on both the absolute response and the interspecies pattern of results to variations in commonly used input parameters. Our sensitivity analysis focuses on assumptions relating to the selection of material properties (heterogeneous or homogeneous), scaling (standardising volume, surface area, or length), tooth position (front, mid, or back tooth engagement), and linear load case (type of loading for each feeding type). Our findings show that in a comparative context, FE models are far less sensitive to the selection of material property values and scaling to either volume or surface area than they are to those assumptions relating to the functional aspects of the simulation, such as tooth position and linear load case. Results show a complex interaction between simulation assumptions, depending on the combination of assumptions and the overall shape of each specimen. Keeping assumptions consistent between models in an analysis does not ensure that results can be generalised beyond the specific set of assumptions used. Logically, different comparative datasets would also be sensitive to identical simulation assumptions; hence, modelling assumptions should undergo rigorous selection. The accuracy of input data is paramount, and simulations should focus on taking biological context into account. Ideally, validation of simulations should be addressed; however, where validation is impossible or unfeasible, sensitivity analyses should be performed to identify which assumptions have the greatest influence upon the results. PMID:24255817
Reduction and Uncertainty Analysis of Chemical Mechanisms Based on Local and Global Sensitivities
NASA Astrophysics Data System (ADS)
Esposito, Gaetano
Numerical simulations of critical reacting flow phenomena in hypersonic propulsion devices require accurate representation of finite-rate chemical kinetics. The chemical kinetic models available for hydrocarbon fuel combustion are rather large, involving hundreds of species and thousands of reactions. As a consequence, they cannot be used in multi-dimensional computational fluid dynamic calculations in the foreseeable future due to the prohibitive computational cost. In addition to the computational difficulties, it is also known that some fundamental chemical kinetic parameters of detailed models have significant level of uncertainty due to limited experimental data available and to poor understanding of interactions among kinetic parameters. In the present investigation, local and global sensitivity analysis techniques are employed to develop a systematic approach of reducing and analyzing detailed chemical kinetic models. Unlike previous studies in which skeletal model reduction was based on the separate analysis of simple cases, in this work a novel strategy based on Principal Component Analysis of local sensitivity values is presented. This new approach is capable of simultaneously taking into account all the relevant canonical combustion configurations over different composition, temperature and pressure conditions. Moreover, the procedure developed in this work represents the first documented inclusion of non-premixed extinction phenomena, which is of great relevance in hypersonic combustors, in an automated reduction algorithm. The application of the skeletal reduction to a detailed kinetic model consisting of 111 species in 784 reactions is demonstrated. The resulting reduced skeletal model of 37--38 species showed that the global ignition/propagation/extinction phenomena of ethylene-air mixtures can be predicted within an accuracy of 2% of the full detailed model. The problems of both understanding non-linear interactions between kinetic parameters and identifying sources of uncertainty affecting relevant reaction pathways are usually addressed by resorting to Global Sensitivity Analysis (GSA) techniques. In particular, the most sensitive reactions controlling combustion phenomena are first identified using the Morris Method and then analyzed under the Random Sampling -- High Dimensional Model Representation (RS-HDMR) framework. The HDMR decomposition shows that 10% of the variance seen in the extinction strain rate of non-premixed flames is due to second-order effects between parameters, whereas the maximum concentration of acetylene, a key soot precursor, is affected by mostly only first-order contributions. Moreover, the analysis of the global sensitivity indices demonstrates that improving the accuracy of the reaction rates including the vinyl radical, C2H3, can drastically reduce the uncertainty of predicting targeted flame properties. Finally, the back-propagation of the experimental uncertainty of the extinction strain rate to the parameter space is also performed. This exercise, achieved by recycling the numerical solutions of the RS-HDMR, shows that some regions of the parameter space have a high probability of reproducing the experimental value of the extinction strain rate between its own uncertainty bounds. Therefore this study demonstrates that the uncertainty analysis of bulk flame properties can effectively provide information on relevant chemical reactions.
He, Ye; Lin, Huazhen; Tu, Dongsheng
2018-06-04
In this paper, we introduce a single-index threshold Cox proportional hazard model to select and combine biomarkers to identify patients who may be sensitive to a specific treatment. A penalized smoothed partial likelihood is proposed to estimate the parameters in the model. A simple, efficient, and unified algorithm is presented to maximize this likelihood function. The estimators based on this likelihood function are shown to be consistent and asymptotically normal. Under mild conditions, the proposed estimators also achieve the oracle property. The proposed approach is evaluated through simulation analyses and application to the analysis of data from two clinical trials, one involving patients with locally advanced or metastatic pancreatic cancer and one involving patients with resectable lung cancer. Copyright © 2018 John Wiley & Sons, Ltd.
Recognizing patterns of visual field loss using unsupervised machine learning
NASA Astrophysics Data System (ADS)
Yousefi, Siamak; Goldbaum, Michael H.; Zangwill, Linda M.; Medeiros, Felipe A.; Bowd, Christopher
2014-03-01
Glaucoma is a potentially blinding optic neuropathy that results in a decrease in visual sensitivity. Visual field abnormalities (decreased visual sensitivity on psychophysical tests) are the primary means of glaucoma diagnosis. One form of visual field testing is Frequency Doubling Technology (FDT) that tests sensitivity at 52 points within the visual field. Like other psychophysical tests used in clinical practice, FDT results yield specific patterns of defect indicative of the disease. We used Gaussian Mixture Model with Expectation Maximization (GEM), (EM is used to estimate the model parameters) to automatically separate FDT data into clusters of normal and abnormal eyes. Principal component analysis (PCA) was used to decompose each cluster into different axes (patterns). FDT measurements were obtained from 1,190 eyes with normal FDT results and 786 eyes with abnormal (i.e., glaucomatous) FDT results, recruited from a university-based, longitudinal, multi-center, clinical study on glaucoma. The GEM input was the 52-point FDT threshold sensitivities for all eyes. The optimal GEM model separated the FDT fields into 3 clusters. Cluster 1 contained 94% normal fields (94% specificity) and clusters 2 and 3 combined, contained 77% abnormal fields (77% sensitivity). For clusters 1, 2 and 3 the optimal number of PCA-identified axes were 2, 2 and 5, respectively. GEM with PCA successfully separated FDT fields from healthy and glaucoma eyes and identified familiar glaucomatous patterns of loss.
Velmurugan, K R; Varghese, R T; Fonville, N C; Garner, H R
2017-01-01
There remains a large discrepancy between the known genetic contributions to cancer and that which can be explained by genomic variants, both inherited and somatic. Recently, understudied repetitive DNA regions called microsatellites have been identified as genetic risk markers for a number of diseases including various cancers (breast, ovarian and brain). In this study, we demonstrate an integrated process for identifying and further evaluating microsatellite-based risk markers for lung cancer using data from the cancer genome atlas and the 1000 genomes project. Comparing whole-exome germline sequencing data from 488 TCGA lung cancer samples to germline exome data from 390 control samples from the 1000 genomes project, we identified 119 potentially informative microsatellite loci. These loci were found to be able to distinguish between cancer and control samples with sensitivity and specificity ratios over 0.8. Then these loci, supplemented with additional loci from other cancers and controls, were evaluated using a target enrichment kit and sample-multiplexed nextgen sequencing. Thirteen of the 119 risk markers were found to be informative in a well powered study (>0.99 for a 0.95 confidence interval) using high-depth (579x±315) nextgen sequencing of 30 lung cancer and 89 control samples, resulting in sensitivity and specificity ratios of 0.90 and 0.94, respectively. When 8 loci harvested from the bioinformatic analysis of other cancers are added to the classifier, then the sensitivity and specificity rise to 0.93 and 0.97, respectively. Analysis of the genes harboring these loci revealed two genes (ARID1B and REL) and two significantly enriched pathways (chromatin organization and cellular stress response) suggesting that the process of lung carcinogenesis is linked to chromatin remodeling, inflammation, and tumor microenvironment restructuring. We illustrate that high-depth sequencing enables a high-precision microsatellite-based risk classifier analysis approach. This microsatellite-based platform confirms the potential to create clinically actionable diagnostics for lung cancer. PMID:28759038
Velmurugan, K R; Varghese, R T; Fonville, N C; Garner, H R
2017-11-16
There remains a large discrepancy between the known genetic contributions to cancer and that which can be explained by genomic variants, both inherited and somatic. Recently, understudied repetitive DNA regions called microsatellites have been identified as genetic risk markers for a number of diseases including various cancers (breast, ovarian and brain). In this study, we demonstrate an integrated process for identifying and further evaluating microsatellite-based risk markers for lung cancer using data from the cancer genome atlas and the 1000 genomes project. Comparing whole-exome germline sequencing data from 488 TCGA lung cancer samples to germline exome data from 390 control samples from the 1000 genomes project, we identified 119 potentially informative microsatellite loci. These loci were found to be able to distinguish between cancer and control samples with sensitivity and specificity ratios over 0.8. Then these loci, supplemented with additional loci from other cancers and controls, were evaluated using a target enrichment kit and sample-multiplexed nextgen sequencing. Thirteen of the 119 risk markers were found to be informative in a well powered study (>0.99 for a 0.95 confidence interval) using high-depth (579x±315) nextgen sequencing of 30 lung cancer and 89 control samples, resulting in sensitivity and specificity ratios of 0.90 and 0.94, respectively. When 8 loci harvested from the bioinformatic analysis of other cancers are added to the classifier, then the sensitivity and specificity rise to 0.93 and 0.97, respectively. Analysis of the genes harboring these loci revealed two genes (ARID1B and REL) and two significantly enriched pathways (chromatin organization and cellular stress response) suggesting that the process of lung carcinogenesis is linked to chromatin remodeling, inflammation, and tumor microenvironment restructuring. We illustrate that high-depth sequencing enables a high-precision microsatellite-based risk classifier analysis approach. This microsatellite-based platform confirms the potential to create clinically actionable diagnostics for lung cancer.
Dehghan-Nayeri, Nasrin; Eshghi, Peyman; Pour, Kourosh Goudarzi; Rezaei-Tavirani, Mostafa; Omrani, Mir Davood; Gharehbaghian, Ahmad
2017-07-01
Dexamethasone is considered as a direct chemotherapeutic agent in the treatment of pediatric acute lymphoblastic leukemia (ALL). Beside the advantages of the drug, some problems arising from the dose-related side effects are challenging issues during the treatment. Accordingly, the classification of patients to dexamethasone sensitive and resistance groups can help to select optimizing the therapeutic dose with the lowest adverse effects particularly in sensitive cases. For this purpose, we investigated inhibited proliferation and induced cytotoxicity in NALM-6 cells, as sensitive cells, after dexamethasone treatment. In addition, comparative protein expression analysis using the 2DE-MALDI-TOF MS technique was performed to identify the specific altered proteins. In addition, we evaluated mRNA expression levels of the identified proteins in bone-marrow samples from pediatric ALL patients using the real-time q-PCR method. Eventually, proteomic analysis revealed a combination of biomarkers, including capping proteins (CAPZA1 and CAPZB), chloride channel (CLIC1), purine nucleoside phosphorylase (PNP), and proteasome activator (PSME1), in response to the dexamethasone treatment. In addition, our results indicated low expression of identified proteins at both the mRNA and protein expression levels after drug treatment. Moreover, quantitative real-time PCR data analysis indicated that independent of the molecular subtypes of the leukemia, CAPZA1, CAPZB, CLIC1, and PNP expression levels were lower in ALL samples than normal samples, although PSME1 expression level was higher in ALL samples than normal samples. Furthermore, the expression level of all proteins (except PSME1) was different between high-risk and standard-risk patients that suggesting the prognostic value of them. In conclusion, our study suggests a panel of biomarkers comprising CAPZA1, CAPZB, CLIC1, PNP, and PSME1 as early diagnosis and treatment evaluation markers that may differentiate cancer cells which are presumably to benefit from dexamethasone-based chemotherapy and may facilitate the prediction of clinical outcome.
Parametric sensitivity analysis of an agro-economic model of management of irrigation water
NASA Astrophysics Data System (ADS)
El Ouadi, Ihssan; Ouazar, Driss; El Menyari, Younesse
2015-04-01
The current work aims to build an analysis and decision support tool for policy options concerning the optimal allocation of water resources, while allowing a better reflection on the issue of valuation of water by the agricultural sector in particular. Thus, a model disaggregated by farm type was developed for the rural town of Ait Ben Yacoub located in the east Morocco. This model integrates economic, agronomic and hydraulic data and simulates agricultural gross margin across in this area taking into consideration changes in public policy and climatic conditions, taking into account the competition for collective resources. To identify the model input parameters that influence over the results of the model, a parametric sensitivity analysis is performed by the "One-Factor-At-A-Time" approach within the "Screening Designs" method. Preliminary results of this analysis show that among the 10 parameters analyzed, 6 parameters affect significantly the objective function of the model, it is in order of influence: i) Coefficient of crop yield response to water, ii) Average daily gain in weight of livestock, iii) Exchange of livestock reproduction, iv) maximum yield of crops, v) Supply of irrigation water and vi) precipitation. These 6 parameters register sensitivity indexes ranging between 0.22 and 1.28. Those results show high uncertainties on these parameters that can dramatically skew the results of the model or the need to pay particular attention to their estimates. Keywords: water, agriculture, modeling, optimal allocation, parametric sensitivity analysis, Screening Designs, One-Factor-At-A-Time, agricultural policy, climate change.
From web search to healthcare utilization: privacy-sensitive studies from mobile data
Horvitz, Eric
2013-01-01
Objective We explore relationships between health information seeking activities and engagement with healthcare professionals via a privacy-sensitive analysis of geo-tagged data from mobile devices. Materials and methods We analyze logs of mobile interaction data stripped of individually identifiable information and location data. The data analyzed consist of time-stamped search queries and distances to medical care centers. We examine search activity that precedes the observation of salient evidence of healthcare utilization (EHU) (ie, data suggesting that the searcher is using healthcare resources), in our case taken as queries occurring at or near medical facilities. Results We show that the time between symptom searches and observation of salient evidence of seeking healthcare utilization depends on the acuity of symptoms. We construct statistical models that make predictions of forthcoming EHU based on observations about the current search session, prior medical search activities, and prior EHU. The predictive accuracy of the models varies (65%–90%) depending on the features used and the timeframe of the analysis, which we explore via a sensitivity analysis. Discussion We provide a privacy-sensitive analysis that can be used to generate insights about the pursuit of health information and healthcare. The findings demonstrate how large-scale studies of mobile devices can provide insights on how concerns about symptomatology lead to the pursuit of professional care. Conclusion We present new methods for the analysis of mobile logs and describe a study that provides evidence about how people transition from mobile searches on symptoms and diseases to the pursuit of healthcare in the world. PMID:22661560
Koenig, Helen C; Finkel, Barbara B; Khalsa, Satjeet S; Lanken, Paul N; Prasad, Meeta; Urbani, Richard; Fuchs, Barry D
2011-01-01
Lung protective ventilation reduces mortality in patients with acute lung injury, but underrecognition of acute lung injury has limited its use. We recently validated an automated electronic acute lung injury surveillance system in patients with major trauma in a single intensive care unit. In this study, we assessed the system's performance as a prospective acute lung injury screening tool in a diverse population of intensive care unit patients. Patients were screened prospectively for acute lung injury over 21 wks by the automated system and by an experienced research coordinator who manually screened subjects for enrollment in Acute Respiratory Distress Syndrome Clinical Trials Network (ARDSNet) trials. Performance of the automated system was assessed by comparing its results with the manual screening process. Discordant results were adjudicated blindly by two physician reviewers. In addition, a sensitivity analysis using a range of assumptions was conducted to better estimate the system's performance. The Hospital of the University of Pennsylvania, an academic medical center and ARDSNet center (1994-2006). Intubated patients in medical and surgical intensive care units. None. Of 1270 patients screened, 84 were identified with acute lung injury (incidence of 6.6%). The automated screening system had a sensitivity of 97.6% (95% confidence interval, 96.8-98.4%) and a specificity of 97.6% (95% confidence interval, 96.8-98.4%). The manual screening algorithm had a sensitivity of 57.1% (95% confidence interval, 54.5-59.8%) and a specificity of 99.7% (95% confidence interval, 99.4-100%). Sensitivity analysis demonstrated a range for sensitivity of 75.0-97.6% of the automated system under varying assumptions. Under all assumptions, the automated system demonstrated higher sensitivity than and comparable specificity to the manual screening method. An automated electronic system identified patients with acute lung injury with high sensitivity and specificity in diverse intensive care units of a large academic medical center. Further studies are needed to evaluate the effect of automated prompts that such a system can initiate on the use of lung protective ventilation in patients with acute lung injury.
Yang, Shaoyu; Chen, Xueqin; Pan, Yuelong; Yu, Jiekai; Li, Xin; Ma, Shenglin
2016-11-01
The present study aimed to identify potential serum biomarkers for predicting the clinical outcomes of patients with advanced non-small cell lung cancer (NSCLC) treated with epidermal growth factor receptor tyrosine kinase inhibitors (EGFR‑TKIs). A total of 61 samples were collected and analyzed using the integrated approach of magnetic bead‑based weak cation exchange chromatography and matrix‑assisted laser desorption/ionization‑time of flight‑mass spectrometry. The Zhejiang University Protein Chip Data Analysis system was used to identify the protein spectra of patients that are resistant and sensitive to EGFR‑TKIs. Furthermore, a support vector machine was used to construct a predictive model with high accuracy. The model was trained using 46 samples and tested with the remaining 15 samples. In addition, the ExPASy Bioinformatics Resource Portal was used to search potential candidate proteins for peaks in the predictive model. Seven mass/charge (m/z) peaks at 3,264, 9,156, 9,172, 3,964, 9,451, 4,295 and 3,983 Da, were identified as significantly different peaks between the EGFR‑TKIs sensitive and resistant groups. A predictive model was generated with three protein peaks at 3,264, 9,451 and 4,295 Da (m/z). This three‑peak model was capable of distinguishing EGFR‑TKIs resistant patients from sensitive patients with a specificity of 80% and a sensitivity of 80.77%. Furthermore, in a blind test, this model exhibited a high specificity (80%) and a high sensitivity (90%). Apelin, TYRO protein tyrosine kinase‑binding protein and big endothelin‑1 may be potential candidates for the proteins identified with an m/z of 3,264, 9,451 and 4,295 Da, respectively. The predictive model used in the present study may provide an improved understanding of the pathogenesis of NSCLC, and may provide insights for the development of TKI treatment plans tailored to specific patients.
NASA Astrophysics Data System (ADS)
Setou, M.; Hayasaka, T.; Shimma, S.; Sugiura, Y.; Matsumoto, M.
2008-12-01
Molecular identification using high-sensitivity tandem mass spectrometry is essential for protein analysis on the tissue surface. Here we report an improved digestion protocol for protein identification directly on the tissue surface using mass spectrometry. By denaturation process and the use of detergent-supplemented trypsin solution, we could successfully detect and identify many molecules such as tubulin, neurofilament, and synaptosomal-associated 25 kDa protein directly from a mouse cerebellum section.
Albrekt, Ann-Sofie; Borrebaeck, Carl A. K.; Lindstedt, Malin
2015-01-01
Background Repeated exposure to certain low molecular weight (LMW) chemical compounds may result in development of allergic reactions in the skin or in the respiratory tract. In most cases, a certain LMW compound selectively sensitize the skin, giving rise to allergic contact dermatitis (ACD), or the respiratory tract, giving rise to occupational asthma (OA). To limit occurrence of allergic diseases, efforts are currently being made to develop predictive assays that accurately identify chemicals capable of inducing such reactions. However, while a few promising methods for prediction of skin sensitization have been described, to date no validated method, in vitro or in vivo, exists that is able to accurately classify chemicals as respiratory sensitizers. Results Recently, we presented the in vitro based Genomic Allergen Rapid Detection (GARD) assay as a novel testing strategy for classification of skin sensitizing chemicals based on measurement of a genomic biomarker signature. We have expanded the applicability domain of the GARD assay to classify also respiratory sensitizers by identifying a separate biomarker signature containing 389 differentially regulated genes for respiratory sensitizers in comparison to non-respiratory sensitizers. By using an independent data set in combination with supervised machine learning, we validated the assay, showing that the identified genomic biomarker is able to accurately classify respiratory sensitizers. Conclusions We have identified a genomic biomarker signature for classification of respiratory sensitizers. Combining this newly identified biomarker signature with our previously identified biomarker signature for classification of skin sensitizers, we have developed a novel in vitro testing strategy with a potent ability to predict both skin and respiratory sensitization in the same sample. PMID:25760038
Qiu, Yajuan; Zhou, Zhiyuan; Li, Zhaoming; Lu, Lisha; Li, Ling; Li, Xin; Wang, Xinhua; Zhang, Mingzhi
2017-03-01
The aim of the present study was to identify the potential relevant biomarkers to predict the therapeutic response of advanced extranodal natural killer/T cell lymphoma(ENKTL) treated with asparaginase-based treatment. Proteomic technology is used to identify differentially expressed proteins between chemotherapy-resistant and chemotherapy-sensitive patients. Then enzyme-linked immunosorbent assay is used to validate the predictive value of selective biomarkers. A total of 61 upregulated and 22 downregulated proteins are identified in chemotherapy-resistant patients compared with chemotherapy-sensitive patients. Furthermore, they validated that pretreatment high level 14-3-3 epsilon(ε)(≥61.95 ng/mL, 84.0 and 95.2% for sensitivity and specificity, respectively) is associated with poor 2-year overall survival (OS) (5.3 vs 68.8%, p<0.0001) and PFS (4.5 vs 76.9%, p<0.0001). In multivariate survival analysis, pretreatment high level 14-3-3 epsilon significantly is correlated with both inferior OS (p = 0.033) and PFS (p = 0.005). These findings indicate that pretreatment high level 14-3-3 epsilon is an independent predictor of chemotherapy-resistance and poor prognosis for patients with advanced ENKTL in the era of asparaginase. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Effects of metric change on safety in the workplace for selected occupations
NASA Astrophysics Data System (ADS)
Lefande, J. M.; Pokorney, J. L.
1982-04-01
The study assesses the potential safety issues of metric conversion in the workplace. A purposive sample of 35 occupations based on injury and illnesses indexes were assessed. After an analysis of workforce population, hazard analysis and measurement sensitivity of the occupations, jobs were analyzed to identify potential safety hazards by industrial hygienists, safety engineers and academia. The study's major findings were as follows: No metric hazard experience was identified. An increased exposure might occur when particular jobs and their job tasks are going the transition from customary measurement to metric measurement. Well planned metric change programs reduce hazard potential. Metric safety issues are unresolved in the aviation industry.
MIDAS: Software for the detection and analysis of lunar impact flashes
NASA Astrophysics Data System (ADS)
Madiedo, José M.; Ortiz, José L.; Morales, Nicolás; Cabrera-Caño, Jesús
2015-06-01
Since 2009 we are running a project to identify flashes produced by the impact of meteoroids on the surface of the Moon. For this purpose we are employing small telescopes and high-sensitivity CCD video cameras. To automatically identify these events a software package called MIDAS was developed and tested. This package can also perform the photometric analysis of these flashes and estimate the value of the luminous efficiency. Besides, we have implemented in MIDAS a new method to establish which is the likely source of the meteoroids (known meteoroid stream or sporadic background). The main features of this computer program are analyzed here, and some examples of lunar impact events are presented.
Targeted Analysis of Whole Genome Sequence Data to Diagnose Genetic Cardiomyopathy
Golbus, Jessica R.; Puckelwartz, Megan J.; Dellefave-Castillo, Lisa; ...
2014-09-01
Background—Cardiomyopathy is highly heritable but genetically diverse. At present, genetic testing for cardiomyopathy uses targeted sequencing to simultaneously assess the coding regions of more than 50 genes. New genes are routinely added to panels to improve the diagnostic yield. With the anticipated $1000 genome, it is expected that genetic testing will shift towards comprehensive genome sequencing accompanied by targeted gene analysis. Therefore, we assessed the reliability of whole genome sequencing and targeted analysis to identify cardiomyopathy variants in 11 subjects with cardiomyopathy. Methods and Results—Whole genome sequencing with an average of 37× coverage was combined with targeted analysis focused onmore » 204 genes linked to cardiomyopathy. Genetic variants were scored using multiple prediction algorithms combined with frequency data from public databases. This pipeline yielded 1-14 potentially pathogenic variants per individual. Variants were further analyzed using clinical criteria and/or segregation analysis. Three of three previously identified primary mutations were detected by this analysis. In six subjects for whom the primary mutation was previously unknown, we identified mutations that segregated with disease, had clinical correlates, and/or had additional pathological correlation to provide evidence for causality. For two subjects with previously known primary mutations, we identified additional variants that may act as modifiers of disease severity. In total, we identified the likely pathological mutation in 9 of 11 (82%) subjects. We conclude that these pilot data demonstrate that ~30-40× coverage whole genome sequencing combined with targeted analysis is feasible and sensitive to identify rare variants in cardiomyopathy-associated genes.« less
Sada, Yvonne; Hou, Jason; Richardson, Peter; El-Serag, Hashem; Davila, Jessica
2013-01-01
Background Accurate identification of hepatocellular cancer (HCC) cases from automated data is needed for efficient and valid quality improvement initiatives and research. We validated HCC ICD-9 codes, and evaluated whether natural language processing (NLP) by the Automated Retrieval Console (ARC) for document classification improves HCC identification. Methods We identified a cohort of patients with ICD-9 codes for HCC during 2005–2010 from Veterans Affairs administrative data. Pathology and radiology reports were reviewed to confirm HCC. The positive predictive value (PPV), sensitivity, and specificity of ICD-9 codes were calculated. A split validation study of pathology and radiology reports was performed to develop and validate ARC algorithms. Reports were manually classified as diagnostic of HCC or not. ARC generated document classification algorithms using the Clinical Text Analysis and Knowledge Extraction System. ARC performance was compared to manual classification. PPV, sensitivity, and specificity of ARC were calculated. Results 1138 patients with HCC were identified by ICD-9 codes. Based on manual review, 773 had HCC. The HCC ICD-9 code algorithm had a PPV of 0.67, sensitivity of 0.95, and specificity of 0.93. For a random subset of 619 patients, we identified 471 pathology reports for 323 patients and 943 radiology reports for 557 patients. The pathology ARC algorithm had PPV of 0.96, sensitivity of 0.96, and specificity of 0.97. The radiology ARC algorithm had PPV of 0.75, sensitivity of 0.94, and specificity of 0.68. Conclusion A combined approach of ICD-9 codes and NLP of pathology and radiology reports improves HCC case identification in automated data. PMID:23929403
Sada, Yvonne; Hou, Jason; Richardson, Peter; El-Serag, Hashem; Davila, Jessica
2016-02-01
Accurate identification of hepatocellular cancer (HCC) cases from automated data is needed for efficient and valid quality improvement initiatives and research. We validated HCC International Classification of Diseases, 9th Revision (ICD-9) codes, and evaluated whether natural language processing by the Automated Retrieval Console (ARC) for document classification improves HCC identification. We identified a cohort of patients with ICD-9 codes for HCC during 2005-2010 from Veterans Affairs administrative data. Pathology and radiology reports were reviewed to confirm HCC. The positive predictive value (PPV), sensitivity, and specificity of ICD-9 codes were calculated. A split validation study of pathology and radiology reports was performed to develop and validate ARC algorithms. Reports were manually classified as diagnostic of HCC or not. ARC generated document classification algorithms using the Clinical Text Analysis and Knowledge Extraction System. ARC performance was compared with manual classification. PPV, sensitivity, and specificity of ARC were calculated. A total of 1138 patients with HCC were identified by ICD-9 codes. On the basis of manual review, 773 had HCC. The HCC ICD-9 code algorithm had a PPV of 0.67, sensitivity of 0.95, and specificity of 0.93. For a random subset of 619 patients, we identified 471 pathology reports for 323 patients and 943 radiology reports for 557 patients. The pathology ARC algorithm had PPV of 0.96, sensitivity of 0.96, and specificity of 0.97. The radiology ARC algorithm had PPV of 0.75, sensitivity of 0.94, and specificity of 0.68. A combined approach of ICD-9 codes and natural language processing of pathology and radiology reports improves HCC case identification in automated data.
Assessment of algorithms to identify patients with thrombophilia following venous thromboembolism.
Delate, Thomas; Hsiao, Wendy; Kim, Benjamin; Witt, Daniel M; Meyer, Melissa R; Go, Alan S; Fang, Margaret C
2016-01-01
Routine testing for thrombophilia following venous thromboembolism (VTE) is controversial. The use of large datasets to study the clinical impact of thrombophilia testing on patterns of care and patient outcomes may enable more efficient analysis of this practice in a wide range of settings. We set out to examine how accurately algorithms using International Classification of Diseases 9th Revision (ICD-9) codes and/or pharmacy data reflect laboratory-confirmed thrombophilia diagnoses. A random sample of adult Kaiser Permanente Colorado patients diagnosed with unprovoked VTE between 1/2004 and 12/2010 underwent medical record abstraction of thrombophilia test results. Algorithms using "ICD-9" (positive if a thrombophilia ICD-9 code was present), "Extended anticoagulation (AC)" (positive if AC therapy duration was >6 months), and "ICD-9 & Extended AC" (positive for both) criteria to identify possible thrombophilia cases were tested. Using positive thrombophilia laboratory results as the gold standard, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value of each algorithm were calculated, along with 95% confidence intervals (CIs). In our cohort of 636 patients, sensitivities were low (<50%) for each algorithm. "ICD-9" yielded the highest PPV (41.5%, 95% CI 26.3-57.9%) and a high specificity (95.9%, 95% CI 94.0-97.4%). "Extended AC" had the highest sensitivity but lowest specificity, and "ICD-9 & Extended AC" had the highest specificity but lowest sensitivity. ICD-9 codes for thrombophilia are highly specific for laboratory-confirmed cases, but all algorithms had low sensitivities. Further development of methods to identify thrombophilia patients in large datasets is warranted. Copyright © 2015 Elsevier Ltd. All rights reserved.
Sánchez-Manubens, Judith; Antón, Jordi; Bou, Rosa; Iglesias, Estíbaliz; Calzada-Hernandez, Joan; Borlan, Sergi; Gimenez-Roca, Clara; Rivera, Josefa
2016-07-01
Kawasaki disease is an acute self-limited systemic vasculitis common in childhood. Intravenous immunoglobulin (IVIG) is an effective treatment, and it reduces the incidence of cardiac complications. Egami score has been validated to identify IVIG non-responder patients in Japanese population, and it has shown high sensitivity and specificity to identify these non-responder patients. Although its effectiveness in Japan, Egami score has shown to be ineffective in non-Japanese populations. The aim of this study was to apply the Egami score in a Western Mediterranean population in Catalonia (Spain). Observational population-based study that includes patients from all Pediatric Units in 33 Catalan hospitals, both public and private management, between January 2004 and March 2014. Sensitivity and specificity for the Egami score was calculated, and a logistic regression analysis of predictors of overall response to IVIG was also developed. Predicting IVIG resistance with a cutoff for Egami score ≥3 obtained 26 % sensitivity and 82 % specificity. Negative predictive value was 85 % and positive predictive value 22 %. This low sensitivity implies that three out of four non-responders will not be identified by the Egami score. Besides, logistic regression models did not found significance for the use of the Egami score to predict IVIG resistance in Catalan population although having an area under the ROC curve of 0.618 (IC 95 % 0.538-0.698, p < 0.001). Although regression models found an area under the ROC curve >0.5 to predict IVIG resistance, the low sensitivity excludes the Egami score as a useful tool to predict IVIG resistance in Catalan population.
Ganglion Cell Loss and Age-Related Visual Loss: A Cortical Pooling Analysis
SCHMIDT, LAURA A.; LY-SCHROEDER, EMILY; SWANSON, WILLIAM H.
2006-01-01
Purpose To evaluate the ability of the cortical pooling model to predict the effects of random, mild ganglion cell loss, we compared the predictions of the model with the age-related loss and variability in achromatic and chromatic contrast sensitivity. Methods The relative sensitivity to small (0.5°) and large (3.0°) stimuli was compared in older (mean = 67 years, n = 27) and younger (mean = 23 years, n = 32) adults. Contrast sensitivity for modulations along the luminance, equiluminant L-cone, and equiluminant S-cone axes was assessed at the fovea and at four peripheral locations (12°). Results When the stimuli were large, threshold measurements obtained from all participants were reliable and well within the range of modulations along the chromatic axes that could be produced by the phosphors of the CRT. For the large stimuli, neither long- nor short-term variability increased as a function of age. Increasing the size of the stimulus did not decrease the magnitude of the age-related losses when the stimulus was chromatic, and visual losses observed with large chromatic stimuli were not different from those obtained with small achromatic stimuli. Moreover, chromatic contrast sensitivity assessments identified significant visual losses in four individuals who were not identified by achromatic contrast sensitivity assessments and only missed identifying one individual with significant losses in achromatic contrast sensitivity. Conclusions The declines in achromatic and chromatic sensitivity as a function of age (0.4 – 0.7 dB per decade) were similar to those obtained in previous studies of achromatic and chromatic perimetry and are consistent with the loss of retinal ganglion cells reported in histologic studies. The results of this study are consistent with the predictions the cortical pooling model makes for both variability and contrast sensitivity. These findings emphasize that selective visual impairments do not necessarily reflect preferential damage to a single ganglion cell class and that it is important to include the influence of higher cortical processing when quantifying the relation between ganglion cells and visual function. PMID:16840870
DOE Office of Scientific and Technical Information (OSTI.GOV)
Welch, B. T., E-mail: Welch.brian@mayo.edu; Eiken, P. W.; Atwell, T. D.
PurposeMesothelioma has been considered a difficult pathologic diagnosis to achieve via image-guided core needle biopsy. The purpose of this study was to assess the diagnostic sensitivity of percutaneous image-guided biopsy for diagnosis of pleural mesothelioma.Materials and MethodsRetrospective review was performed to identify patients with a confirmed diagnosis of pleural mesothelioma and who underwent image-guided needle biopsy between January 1, 2002, and January 1, 2016. Thirty-two patients with pleural mesothelioma were identified and included for analysis in 33 image-guided biopsy procedures. Patient, procedural, and pathologic characteristics were recorded. Complications were characterized via standardized nomenclature [Common Terminology for Clinically Adverse Events (CTCAE)].ResultsPercutaneousmore » image-guided biopsy was associated with an overall sensitivity of 81%. No CTCAE clinically significant complications were observed. No image-guided procedures were complicated by pneumothorax or necessitated chest tube placement. No patients had tumor seeding of the biopsy tract.ConclusionPercutaneous image-guided biopsy can achieve high sensitivity for pathologic diagnosis of pleural mesothelioma with a low procedural complication rate, potentially obviating need for surgical biopsy.« less
CORSSTOL: Cylinder Optimization of Rings, Skin, and Stringers with Tolerance sensitivity
NASA Technical Reports Server (NTRS)
Finckenor, J.; Bevill, M.
1995-01-01
Cylinder Optimization of Rings, Skin, and Stringers with Tolerance (CORSSTOL) sensitivity is a design optimization program incorporating a method to examine the effects of user-provided manufacturing tolerances on weight and failure. CORSSTOL gives designers a tool to determine tolerances based on need. This is a decisive way to choose the best design among several manufacturing methods with differing capabilities and costs. CORSSTOL initially optimizes a stringer-stiffened cylinder for weight without tolerances. The skin and stringer geometry are varied, subject to stress and buckling constraints. Then the same analysis and optimization routines are used to minimize the maximum material condition weight subject to the least favorable combination of tolerances. The adjusted optimum dimensions are provided with the weight and constraint sensitivities of each design variable. The designer can immediately identify critical tolerances. The safety of parts made out of tolerance can also be determined. During design and development of weight-critical systems, design/analysis tools that provide product-oriented results are of vital significance. The development of this program and methodology provides designers with an effective cost- and weight-saving design tool. The tolerance sensitivity method can be applied to any system defined by a set of deterministic equations.
Ackerman, L K; Noonan, G O; Begley, T H
2009-12-01
The ambient ionization technique direct analysis in real time (DART) was characterized and evaluated for the screening of food packaging for the presence of packaging additives using a benchtop mass spectrometer (MS). Approximate optimum conditions were determined for 13 common food-packaging additives, including plasticizers, anti-oxidants, colorants, grease-proofers, and ultraviolet light stabilizers. Method sensitivity and linearity were evaluated using solutions and characterized polymer samples. Additionally, the response of a model additive (di-ethyl-hexyl-phthalate) was examined across a range of sample positions, DART, and MS conditions (temperature, voltage and helium flow). Under optimal conditions, molecular ion (M+H+) was the major ion for most additives. Additive responses were highly sensitive to sample and DART source orientation, as well as to DART flow rates, temperatures, and MS inlet voltages, respectively. DART-MS response was neither consistently linear nor quantitative in this setting, and sensitivity varied by additive. All additives studied were rapidly identified in multiple food-packaging materials by DART-MS/MS, suggesting this technique can be used to screen food packaging rapidly. However, method sensitivity and quantitation requires further study and improvement.
Silvano, Amy; Guyer, Craig; Steury, Todd; Grand, James B.
2017-01-01
Most imperiled species are rare or elusive and difficult to detect, which makes gathering data to estimate their response to habitat restoration a challenge. We used a repeatable, systematic method for selecting focal species using relative sensitivities derived from occupancy analysis. Our objective was to select suites of focal species that would be useful as surrogates when predicting effects of restoration of habitat characteristics preferred by imperiled species. We developed 27 habitat profiles that represent general habitat relationships for 118 imperiled species. We identified 23 regularly encountered species that were sensitive to important aspects of those profiles. We validated our approach by examining the correlation between estimated probabilities of occupancy for species of concern and focal species selected using our method. Occupancy rates of focal species were more related to occupancy rates of imperiled species when they were sensitive to more of the parameters appearing in profiles of imperiled species. We suggest that this approach can be an effective means of predicting responses by imperiled species to proposed management actions. However, adequate monitoring will be required to determine the effectiveness of using focal species to guide management actions.
NASA Astrophysics Data System (ADS)
Stelzle, Florian; Zam, Azhar; Adler, Werner; Douplik, Alexandre; Tangermann-Gerk, Katja; Nkenke, Emeka; Neukam, Friedrich Wilhelm; Schmidt, Michael
Objective: Laser surgery has many advantages. However, due to a lack of haptic feedback it is accompanied by the risk of iatrogenic nerve damage. The aim of this study was to evaluate the possibilities of optical nerve identification by diffuse reflectance spectroscopy to set the base for a feedback control system to enhance nerve preservation in oral and maxillofacial laser surgery. Materials and Methods: Diffuse reflectance spectra of nerve tissue, skin, mucosa, fat tissue, muscle, cartilage and bone (15120 spectra) of ex vivo pig heads were acquired in the wavelength range of 350-650 nm. Tissue differentiation was performed by principal components analysis (PCA) followed by linear discriminant analysis (LDA). Specificity and sensitivity were calculated by receiver operating characteristic (ROC) analysis and the area under curve (AUC). Results: Nerve tissue could correctly be identified and differed from skin, mucosa, fat tissue, muscle, cartilage and bone in more than 90% of the cases (AUC results) with a specificity of over 78% and a sensitivity of more than 86%. Conclusion: Nerve tissue can be identified by diffuse reflectance spectroscopy with high precision and reliability. The results may set the base for a feedback system to prevent iatrogenic nerve damage performing oral and maxillofacial laser surgery.
Hatem, S M; Hu, L; Ragé, M; Gierasimowicz, A; Plaghki, L; Bouhassira, D; Attal, N; Iannetti, G D; Mouraux, A
2012-12-01
To assess the clinical usefulness of an automated analysis of event-related potentials (ERPs). Nociceptive laser-evoked potentials (LEPs) and non-nociceptive somatosensory electrically-evoked potentials (SEPs) were recorded in 37 patients with syringomyelia and 21 controls. LEP and SEP peak amplitudes and latencies were estimated using a single-trial automated approach based on time-frequency wavelet filtering and multiple linear regression, as well as a conventional approach based on visual inspection. The amplitudes and latencies of normal and abnormal LEP and SEP peaks were identified reliably using both approaches, with similar sensitivity and specificity. Because the automated approach provided an unbiased solution to account for average waveforms where no ERP could be identified visually, it revealed significant differences between patients and controls that were not revealed using the visual approach. The automated analysis of ERPs characterized reliably and objectively LEP and SEP waveforms in patients. The automated single-trial analysis can be used to characterize normal and abnormal ERPs with a similar sensitivity and specificity as visual inspection. While this does not justify its use in a routine clinical setting, the technique could be useful to avoid observer-dependent biases in clinical research. Copyright © 2012 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Hamelin, Elizabeth I.; Blake, Thomas A.; Perez, Jonas W.; Crow, Brian S.; Shaner, Rebecca L.; Coleman, Rebecca M.; Johnson, Rudolph C.
2016-05-01
Public health response to large scale chemical emergencies presents logistical challenges for sample collection, transport, and analysis. Diagnostic methods used to identify and determine exposure to chemical warfare agents, toxins, and poisons traditionally involve blood collection by phlebotomists, cold transport of biomedical samples, and costly sample preparation techniques. Use of dried blood spots, which consist of dried blood on an FDA-approved substrate, can increase analyte stability, decrease infection hazard for those handling samples, greatly reduce the cost of shipping/storing samples by removing the need for refrigeration and cold chain transportation, and be self-prepared by potentially exposed individuals using a simple finger prick and blood spot compatible paper. Our laboratory has developed clinical assays to detect human exposures to nerve agents through the analysis of specific protein adducts and metabolites, for which a simple extraction from a dried blood spot is sufficient for removing matrix interferents and attaining sensitivities on par with traditional sampling methods. The use of dried blood spots can bridge the gap between the laboratory and the field allowing for large scale sample collection with minimal impact on hospital resources while maintaining sensitivity, specificity, traceability, and quality requirements for both clinical and forensic applications.
Rosén, Karl G; Norén, Håkan; Carlsson, Ann
2018-04-18
Recent developments have produced new CTG classification systems and the question is to what extent these may affect the model of FHR + ST interpretation? The two new systems (FIGO2015 and SSOG2017) classify FHR + ST events differently from the current CTG classification system used in the STAN interpretation algorithm (STAN2007). Identify the predominant FHR patterns in connection with ST events in cases of cord artery metabolic acidosis missed by the different CTG classification systems. Indicate to what extent STAN clinical guidelines could be modified enhancing the sensitivity. Provide a pathophysiological rationale. Forty-four cases with umbilical cord artery metabolic acidosis were retrieved from a European multicenter database. Significant FHR + ST events were evaluated post hoc in consensus by an expert panel. Eighteen cases were not identified as in need of intervention and regarded as negative in the sensitivity analysis. In 12 cases, ST changes occurred but the CTG was regarded as reassuring. Visual analysis of the FHR + ST tracings revealed specific FHR patterns: Conclusion: These findings indicate FHR + ST analysis may be undertaken regardless of CTG classification system provided there is a more physiologically oriented approach to FHR assessment in connection with an ST event.
Increased incidence of head and neck cancer in liver transplant recipients: a meta-analysis.
Liu, Qian; Yan, Lifeng; Xu, Cheng; Gu, Aihua; Zhao, Peng; Jiang, Zhao-Yan
2014-10-22
It is unclear whether liver transplantation is associated with an increased incidence of post-transplant head and neck cancer. This comprehensive meta-analysis evaluated the association between liver transplantation and the risk of head and neck cancer using data from all available studies. PubMed and Web of Science were systematically searched to identify all relevant publications up to March 2014. Standardized incidence ratio (SIR) and 95% confidence intervals (CIs) for risk of head and neck cancer in liver transplant recipients were calculated. Tests for heterogeneity, sensitivity, and publishing bias were also performed. Of the 964 identified articles, 10 were deemed eligible. These studies included data on 56,507 patients with a total follow-up of 129,448.9 patient-years. SIR for head and neck cancer was 3.836-fold higher (95% CI 2.754-4.918, P = 0.000) in liver transplant recipients than in the general population. No heterogeneity or publication bias was observed. Sensitivity analysis indicated that omission of any of the studies resulted in an SIR for head and neck cancer between 3.488 (95% CI: 2.379-4.598) and 4.306 (95% CI: 3.020-5.592). Liver transplant recipients are at higher risk of developing head and neck cancer than the general population.
Yang, Zemao; Dai, Zhigang; Lu, Ruike; Wu, Bibo; Tang, Qing; Xu, Ying; Cheng, Chaohua; Su, Jianguang
2017-11-29
Drought stress results in significant crop yield losses. Comparative transcriptome analysis between tolerant and sensitive species can provide insights into drought tolerance mechanisms in jute. We present a comprehensive study on drought tolerance in two jute species-a drought tolerant species (Corchorus olitorius L., GF) and a drought sensitive species (Corchorus capsularis L., YY). In total, 45,831 non-redundant unigenes with average sequence length of 1421 bp were identified. Higher numbers of differentially expressed genes (DEGs) were discovered in YY (794) than in GF (39), implying that YY was relatively more vulnerable or hyper-responsive to drought stress at the molecular level; the two main pathways, phenylpropanoid biosynthesis and peroxisome pathway, significantly involved in scavenging of reactive oxygen species (ROS) and 14 unigenes in the two pathways presented a significant differential expression in response to increase of superoxide. Our classification analysis showed that 1769 transcription factors can be grouped into 81 families and 948 protein kinases (PKs) into 122 families. In YY, we identified 34 TF DEGs from and 23 PK DEGs, including 19 receptor-like kinases (RLKs). Most of these RLKs were downregulated during drought stress, implying their role as negative regulators of the drought tolerance mechanism in jute.
A cadmium-sensitive, glutathione-deficient mutant of Arabidopsis thaliana.
Howden, R; Andersen, C R; Goldsbrough, P B; Cobbett, C S
1995-01-01
The roots of the cadmium-sensitive mutant of Arabidopsis thaliana, cad1-1, become brown in the presence of cadmium. A new cadmium-sensitive mutant affected at a second locus, cad2, has been identified using this phenotype. Genetic analysis has grown that the sensitive phenotype is recessive to the wild type and segregates as a single Mendelian locus. Assays of cadmium accumulation by intact plants indicated that the mutant is deficient in its ability to sequester cadmium. Undifferentiated callus tissue was also cadmium sensitive, suggesting that the mutant phenotype is expressed at the cellular level. The level of cadmium-binding complexes formed in vivo was decreased compared with the wild type and accumulation of phytochelatins was about 10% of that in the wild type. The level of glutathione, the substrate for phytochelatin biosynthesis, in tissues of the mutant was decreased to about 15 to 30% of that in the wild type. Thus, the deficiency in phytochelatin biosynthesis can be explained by a deficiency in glutathione. PMID:7770518
Yabu, Julie M.; Siebert, Janet C.; Maecker, Holden T.
2016-01-01
Background Kidney transplantation is the most effective treatment for end-stage kidney disease. Sensitization, the formation of human leukocyte antigen (HLA) antibodies, remains a major barrier to successful kidney transplantation. Despite the implementation of desensitization strategies, many candidates fail to respond. Current progress is hindered by the lack of biomarkers to predict response and to guide therapy. Our objective was to determine whether differences in immune and gene profiles may help identify which candidates will respond to desensitization therapy. Methods and Findings Single-cell mass cytometry by time-of-flight (CyTOF) phenotyping, gene arrays, and phosphoepitope flow cytometry were performed in a study of 20 highly sensitized kidney transplant candidates undergoing desensitization therapy. Responders to desensitization therapy were defined as 5% or greater decrease in cumulative calculated panel reactive antibody (cPRA) levels, and non-responders had 0% decrease in cPRA. Using a decision tree analysis, we found that a combination of transitional B cell and regulatory T cell (Treg) frequencies at baseline before initiation of desensitization therapy could distinguish responders from non-responders. Using a support vector machine (SVM) and longitudinal data, TRAF3IP3 transcripts and HLA-DR-CD38+CD4+ T cells could also distinguish responders from non-responders. Combining all assays in a multivariate analysis and elastic net regression model with 72 analytes, we identified seven that were highly interrelated and eleven that predicted response to desensitization therapy. Conclusions Measuring baseline and longitudinal immune and gene profiles could provide a useful strategy to distinguish responders from non-responders to desensitization therapy. This study presents the integration of novel translational studies including CyTOF immunophenotyping in a multivariate analysis model that has potential applications to predict response to desensitization, select candidates, and personalize medicine to ultimately improve overall outcomes in highly sensitized kidney transplant candidates. PMID:27078882
Yabu, Julie M; Siebert, Janet C; Maecker, Holden T
2016-01-01
Kidney transplantation is the most effective treatment for end-stage kidney disease. Sensitization, the formation of human leukocyte antigen (HLA) antibodies, remains a major barrier to successful kidney transplantation. Despite the implementation of desensitization strategies, many candidates fail to respond. Current progress is hindered by the lack of biomarkers to predict response and to guide therapy. Our objective was to determine whether differences in immune and gene profiles may help identify which candidates will respond to desensitization therapy. Single-cell mass cytometry by time-of-flight (CyTOF) phenotyping, gene arrays, and phosphoepitope flow cytometry were performed in a study of 20 highly sensitized kidney transplant candidates undergoing desensitization therapy. Responders to desensitization therapy were defined as 5% or greater decrease in cumulative calculated panel reactive antibody (cPRA) levels, and non-responders had 0% decrease in cPRA. Using a decision tree analysis, we found that a combination of transitional B cell and regulatory T cell (Treg) frequencies at baseline before initiation of desensitization therapy could distinguish responders from non-responders. Using a support vector machine (SVM) and longitudinal data, TRAF3IP3 transcripts and HLA-DR-CD38+CD4+ T cells could also distinguish responders from non-responders. Combining all assays in a multivariate analysis and elastic net regression model with 72 analytes, we identified seven that were highly interrelated and eleven that predicted response to desensitization therapy. Measuring baseline and longitudinal immune and gene profiles could provide a useful strategy to distinguish responders from non-responders to desensitization therapy. This study presents the integration of novel translational studies including CyTOF immunophenotyping in a multivariate analysis model that has potential applications to predict response to desensitization, select candidates, and personalize medicine to ultimately improve overall outcomes in highly sensitized kidney transplant candidates.
Sensitivity and specificity of eustachian tube function tests in adults.
Doyle, William J; Swarts, J Douglas; Banks, Julianne; Casselbrant, Margaretha L; Mandel, Ellen M; Alper, Cuneyt M
2013-07-01
The study demonstrates the utility of eustachian tube (ET) function (ETF) test results for accurately assigning ears to disease state. To determine if ETF tests can identify ears with physician-diagnosed ET dysfunction (ETD) in a mixed population at high sensitivity and specificity and to define the interrelatedness of ETF test parameters. Through use of the forced-response, inflation-deflation, Valsalva, and sniffing tests, ETF was evaluated in 15 control ears of adult subjects after unilateral myringotomy (group 1) and in 23 ears of 19 adult subjects with ventilation tubes inserted for ETD (group 2). Data were analyzed using logistic regression including each parameter independently and then a step-down discriminant analysis including all ETF test parameters to predict group assignment. Factor analysis operating over all parameters was used to explore relatedness. ETF testing. ETF parameters for the forced response, inflation-deflation, Valsalva, and sniffing tests measured in 15 control ears of adult subjects after unilateral myringotomy (group 1) and in 23 ears of 19 adult subjects with ventilation tubes inserted for ETD (group 2). The discriminant analysis identified 4 ETF test parameters (Valsalva, ET opening pressure, dilatory efficiency, and percentage of positive pressure equilibrated) that together correctly assigned ears to group 2 at a sensitivity of 95% and a specificity of 83%. Individual parameters representing the efficiency of ET opening during swallowing showed moderately accurate assignments of ears to their respective groups. Three factors captured approximately 98% of the variance among parameters: the first had negative loadings of the ETF structural parameters; the second had positive loadings of the muscle-assisted ET opening parameters; and the third had negative loadings of the muscle-assisted ET opening parameters and positive loadings of the structural parameters. These results show that ETF tests can correctly assign individual ears to physician-diagnosed ETD with high sensitivity and specificity and that ETF test parameters can be grouped into structural-functional categories.
Neutrophil/lymphocyte ratio and platelet/lymphocyte ratio in mood disorders: A meta-analysis.
Mazza, Mario Gennaro; Lucchi, Sara; Tringali, Agnese Grazia Maria; Rossetti, Aurora; Botti, Eugenia Rossana; Clerici, Massimo
2018-06-08
The immune and inflammatory system is involved in the etiology of mood disorders. Neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR) and monocyte/lymphocyte ratio (MLR) are inexpensive and reproducible biomarkers of inflammation. This is the first meta-analysis exploring the role of NLR and PLR in mood disorder. We identified 11 studies according to our inclusion criteria from the main Electronic Databases. Meta-analyses were carried out generating pooled standardized mean differences (SMDs) between index and healthy controls (HC). Heterogeneity was estimated. Relevant sensitivity and meta-regression analyses were conducted. Subjects with bipolar disorder (BD) had higher NLR and PLR as compared with HC (respectively SMD = 0.672; p < 0.001; I 2 = 82.4% and SMD = 0.425; p = 0.048; I 2 = 86.53%). Heterogeneity-based sensitivity analyses confirmed these findings. Subgroup analysis evidenced an influence of bipolar phase on the overall estimate whit studies including subjects in manic and any bipolar phase showing a significantly higher NLR and PLR as compared with HC whereas the effect was not significant among studies including only euthymic bipolar subjects. Meta-regression showed that age and sex influenced the relationship between BD and NLR but not the relationship between BD and PLR. Meta-analysis was not carried out for MLR because our search identified only one study when comparing BD to HC, and only one study when comparing MDD to HC. Subjects with major depressive disorder (MDD) had higher NLR as compared with HC (SMD = 0.670; p = 0.028; I 2 = 89.931%). Heterogeneity-based sensitivity analyses and meta-regression confirmed these findings. Our meta-analysis supports the hypothesis that an inflammatory activation occurs in mood disorders and NLR and PLR may be useful to detect this activation. More researches including comparison of NLR, PLR and MLR between different bipolar phases and between BD and MDD are needed. Copyright © 2018 Elsevier Inc. All rights reserved.
Rice, Simon M; Ogrodniczuk, John S; Kealy, David; Seidler, Zac E; Dhillon, Haryana M; Oliffe, John L
2017-12-22
Clinical practice and literature has supported the existence of a phenotypic sub-type of depression in men. While a number of self-report rating scales have been developed in order to empirically test the male depression construct, psychometric validation of these scales is limited. To confirm the psychometric properties of the multidimensional Male Depression Risk Scale (MDRS-22) and to develop clinical cut-off scores for the MDRS-22. Data were obtained from an online sample of 1000 Canadian men (median age (M) = 49.63, standard deviation (SD) = 14.60). Confirmatory factor analysis (CFA) was used to replicate the established six-factor model of the MDRS-22. Psychometric values of the MDRS subscales were comparable to the widely used Patient Health Questionnaire-9. CFA model fit indices indicated adequate model fit for the six-factor MDRS-22 model. ROC curve analysis indicated the MDRS-22 was effective for identifying those with a recent (previous four-weeks) suicide attempt (area under curve (AUC) values = 0.837). The MDRS-22 cut-off identified proportionally more (84.62%) cases of recent suicide attempt relative to the PHQ-9 moderate range (53.85%). The MDRS-22 is the first male-sensitive depression scale to be psychometrically validated using CFA techniques in independent and cross-nation samples. Additional studies should identify differential item functioning and evaluate cross-cultural effects.
Gomes, Ciro Martins; Mazin, Suleimy Cristina; dos Santos, Elisa Raphael; Cesetti, Mariana Vicente; Bächtold, Guilherme Albergaria Brízida; Cordeiro, João Henrique de Freitas; Theodoro, Fabrício Claudino Estrela Terra; Damasco, Fabiana dos Santos; Carranza, Sebastián Andrés Vernal; Santos, Adriana de Oliveira; Roselino, Ana Maria; Sampaio, Raimunda Nonata Ribeiro
2015-01-01
The diagnosis of mucocutaneous leishmaniasis (MCL) is hampered by the absence of a gold standard. An accurate diagnosis is essential because of the high toxicity of the medications for the disease. This study aimed to assess the ability of polymerase chain reaction (PCR) to identify MCL and to compare these results with clinical research recently published by the authors. A systematic literature review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA Statement was performed using comprehensive search criteria and communication with the authors. A meta-analysis considering the estimates of the univariate and bivariate models was performed. Specificity near 100% was common among the papers. The primary reason for accuracy differences was sensitivity. The meta-analysis, which was only possible for PCR samples of lesion fragments, revealed a sensitivity of 71% [95% confidence interval (CI) = 0.59; 0.81] and a specificity of 93% (95% CI = 0.83; 0.98) in the bivariate model. The search for measures that could increase the sensitivity of PCR should be encouraged. The quality of the collected material and the optimisation of the amplification of genetic material should be prioritised. PMID:25946238
Nishijima, Daniel Kiden; Gaona, Samuel D; Waechter, Trent; Maloney, Ric; Blitz, Adam; Elms, Andrew R; Farrales, Roel D; Montoya, James; Bair, Troy; Howard, Calvin; Gilbert, Megan; Trajano, Renee; Hatchel, Kaela; Faul, Mark; Bell, Jeneita M; Coronado, Victor; Vinson, David R; Ballard, Dustin W; Tancredi, Daniel J; Garzon, Hernando; Mackey, Kevin E; Shahlaie, Kiarash; Holmes, James F
2017-11-06
Field triage guidelines recommend transport of head-injured patients on anticoagulants or antiplatelets to a higher-level trauma center based on studies suggesting a high incidence of traumatic intracranial hemorrhage (tICH). We compared the incidence of tICH in older adults transported by EMS with and without anticoagulation or antiplatelet use and evaluated the accuracies of different sets of field triage criteria to identify tICH. This was a prospective, observational study at 5 EMS agencies and 11 hospitals. Older adults (≥55 years) with head trauma and transported by EMS from Aug 2015 to Sept 2016 were eligible. EMS providers completed standardized data forms and patients were followed through ED or hospital discharge. We enrolled 1,304 patients; 1147 (88%) received a cranial CT scan and were eligible for analysis. 434 (33%) patients had anticoagulant or antiplatelet use and 112 (10%) had tICH. The incidence of tICH in patients with (11%, 95%CI 8-14%) and without (9%, 95%CI 7-11%) anticoagulant or antiplatelet use was similar. Anticoagulant or antiplatelet use was not predictive of tICH on adjusted analysis. Steps 1-3 criteria alone were not sensitive in identifying tICH (27%) while the addition of anticoagulant or antiplatelet criterion improved sensitivity (63%). Other derived sets of triage criteria were highly sensitive (>98%) but poorly specific (<11%). The incidence of tICH was similar between patients with and without anticoagulant or antiplatelet use. Use of anticoagulant or antiplatelet medications was not a risk factor for tICH. We were unable to identify a set of triage criteria that was accurate for trauma center need.
Prenatal Sonographic Predictors of Neonatal Coarctation of the Aorta.
Anuwutnavin, Sanitra; Satou, Gary; Chang, Ruey-Kang; DeVore, Greggory R; Abuel, Ashley; Sklansky, Mark
2016-11-01
To identify practical prenatal sonographic markers for the postnatal diagnosis of coarctation of the aorta. We reviewed the fetal echocardiograms and postnatal outcomes of fetal cases of suspected coarctation of the aorta seen at a single institution between 2010 and 2014. True- and false-positive cases were compared. Logistic regression analysis was used to determine echocardiographic predictors of coarctation of the aorta. Optimal cutoffs for these markers and a multivariable threshold scoring system were derived to discriminate fetuses with coarctation of the aorta from those without coarctation of the aorta. Among 35 patients with prenatal suspicion of coarctation of the aorta, the diagnosis was confirmed postnatally in 9 neonates (25.7% true-positive rate). Significant predictors identified from multivariate analysis were as follows: Z score for the ascending aorta diameter of -2 or less (P = < .001), Z score for the mitral valve annulus of -2 or less (P= .033), Zscore for the transverse aortic arch diameter of -2 or less (P= .028), and abnormal aortic valve morphologic features (P= .026). Among all variables studied, the ascending aortic Z score had the highest sensitivity (78%) and specificity (92%) for detection of coarctation of the aorta. A multivariable threshold scoring system identified fetuses with coarctation of the aorta with still greater sensitivity (89%) and only mildly decreased specificity (88%). The finding of a diminutive ascending aorta represents a powerful and practical prenatal predictor of neonatal coarctation of the aorta. A multivariable scoring system, including dimensions of the ascending and transverse aortas, mitral valve annulus, and morphologic features of the aortic valve, provides excellent sensitivity and specificity. The use of these practical sonographic markers may improve prenatal detection of coarctation of the aorta. © 2016 by the American Institute of Ultrasound in Medicine.
Ablordeppey, Enyo A; Drewry, Anne M; Beyer, Alexander B; Theodoro, Daniel L; Fowler, Susan A; Fuller, Brian M; Carpenter, Christopher R
2017-04-01
We performed a systematic review and meta-analysis to examine the accuracy of bedside ultrasound for confirmation of central venous catheter position and exclusion of pneumothorax compared with chest radiography. PubMed, Embase, Cochrane Central Register of Controlled Trials, reference lists, conference proceedings and ClinicalTrials.gov. Articles and abstracts describing the diagnostic accuracy of bedside ultrasound compared with chest radiography for confirmation of central venous catheters in sufficient detail to reconstruct 2 × 2 contingency tables were reviewed. Primary outcomes included the accuracy of confirming catheter positioning and detecting a pneumothorax. Secondary outcomes included feasibility, interrater reliability, and efficiency to complete bedside ultrasound confirmation of central venous catheter position. Investigators abstracted study details including research design and sonographic imaging technique to detect catheter malposition and procedure-related pneumothorax. Diagnostic accuracy measures included pooled sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio. Fifteen studies with 1,553 central venous catheter placements were identified with a pooled sensitivity and specificity of catheter malposition by ultrasound of 0.82 (0.77-0.86) and 0.98 (0.97-0.99), respectively. The pooled positive and negative likelihood ratios of catheter malposition by ultrasound were 31.12 (14.72-65.78) and 0.25 (0.13-0.47). The sensitivity and specificity of ultrasound for pneumothorax detection was nearly 100% in the participating studies. Bedside ultrasound reduced mean central venous catheter confirmation time by 58.3 minutes. Risk of bias and clinical heterogeneity in the studies were high. Bedside ultrasound is faster than radiography at identifying pneumothorax after central venous catheter insertion. When a central venous catheter malposition exists, bedside ultrasound will identify four out of every five earlier than chest radiography.
Optimizing human activity patterns using global sensitivity analysis.
Fairchild, Geoffrey; Hickmann, Kyle S; Mniszewski, Susan M; Del Valle, Sara Y; Hyman, James M
2014-12-01
Implementing realistic activity patterns for a population is crucial for modeling, for example, disease spread, supply and demand, and disaster response. Using the dynamic activity simulation engine, DASim, we generate schedules for a population that capture regular (e.g., working, eating, and sleeping) and irregular activities (e.g., shopping or going to the doctor). We use the sample entropy (SampEn) statistic to quantify a schedule's regularity for a population. We show how to tune an activity's regularity by adjusting SampEn, thereby making it possible to realistically design activities when creating a schedule. The tuning process sets up a computationally intractable high-dimensional optimization problem. To reduce the computational demand, we use Bayesian Gaussian process regression to compute global sensitivity indices and identify the parameters that have the greatest effect on the variance of SampEn. We use the harmony search (HS) global optimization algorithm to locate global optima. Our results show that HS combined with global sensitivity analysis can efficiently tune the SampEn statistic with few search iterations. We demonstrate how global sensitivity analysis can guide statistical emulation and global optimization algorithms to efficiently tune activities and generate realistic activity patterns. Though our tuning methods are applied to dynamic activity schedule generation, they are general and represent a significant step in the direction of automated tuning and optimization of high-dimensional computer simulations.
Optimizing human activity patterns using global sensitivity analysis
Hickmann, Kyle S.; Mniszewski, Susan M.; Del Valle, Sara Y.; Hyman, James M.
2014-01-01
Implementing realistic activity patterns for a population is crucial for modeling, for example, disease spread, supply and demand, and disaster response. Using the dynamic activity simulation engine, DASim, we generate schedules for a population that capture regular (e.g., working, eating, and sleeping) and irregular activities (e.g., shopping or going to the doctor). We use the sample entropy (SampEn) statistic to quantify a schedule’s regularity for a population. We show how to tune an activity’s regularity by adjusting SampEn, thereby making it possible to realistically design activities when creating a schedule. The tuning process sets up a computationally intractable high-dimensional optimization problem. To reduce the computational demand, we use Bayesian Gaussian process regression to compute global sensitivity indices and identify the parameters that have the greatest effect on the variance of SampEn. We use the harmony search (HS) global optimization algorithm to locate global optima. Our results show that HS combined with global sensitivity analysis can efficiently tune the SampEn statistic with few search iterations. We demonstrate how global sensitivity analysis can guide statistical emulation and global optimization algorithms to efficiently tune activities and generate realistic activity patterns. Though our tuning methods are applied to dynamic activity schedule generation, they are general and represent a significant step in the direction of automated tuning and optimization of high-dimensional computer simulations. PMID:25580080
A 3-Year Study of Predictive Factors for Positive and Negative Appendicectomies.
Chang, Dwayne T S; Maluda, Melissa; Lee, Lisa; Premaratne, Chandrasiri; Khamhing, Srisongham
2018-03-06
Early and accurate identification or exclusion of acute appendicitis is the key to avoid the morbidity of delayed treatment for true appendicitis or unnecessary appendicectomy, respectively. We aim (i) to identify potential predictive factors for positive and negative appendicectomies; and (ii) to analyse the use of ultrasound scans (US) and computed tomography (CT) scans for acute appendicitis. All appendicectomies that took place at our hospital from the 1st of January 2013 to the 31st of December 2015 were retrospectively recorded. Test results of potential predictive factors of acute appendicitis were recorded. Statistical analysis was performed using Fisher exact test, logistic regression analysis, sensitivity, specificity, and positive and negative predictive values calculation. 208 patients were included in this study. 184 patients had histologically proven acute appendicitis. The other 24 patients had either nonappendicitis pathology or normal appendix. Logistic regression analysis showed statistically significant associations between appendicitis and white cell count, neutrophil count, C-reactive protein, and bilirubin. Neutrophil count was the test with the highest sensitivity and negative predictive values, whereas bilirubin was the test with the highest specificity and positive predictive values (PPV). US and CT scans had high sensitivity and PPV for diagnosing appendicitis. No single test was sufficient to diagnose or exclude acute appendicitis by itself. Combining tests with high sensitivity (abnormal neutrophil count, and US and CT scans) and high specificity (raised bilirubin) may predict acute appendicitis more accurately.