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Russell S. Thomas

Bio: Russell S. Thomas is an academic researcher from United States Environmental Protection Agency. The author has contributed to research in topics: Aryl hydrocarbon receptor & Gene expression. The author has an hindex of 56, co-authored 182 publications receiving 10457 citations. Previous affiliations of Russell S. Thomas include Research Triangle Park & University of Wisconsin-Madison.


Papers
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Journal ArticleDOI
TL;DR: A newly developed probabilistic model, the Creme RIFM model, is used to estimate aggregate exposure to fragrance ingredients using the example of 2-phenylethanol (PEA) to demonstrate the utility of the model in determining systemic and dermal exposure to fragrances from individual products, and aggregate exposure.

1,108 citations

Journal ArticleDOI
Leming Shi1, Gregory Campbell1, Wendell D. Jones, Fabien Campagne2  +198 moreInstitutions (55)
TL;DR: P predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans are generated.
Abstract: Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.

753 citations

Journal ArticleDOI
TL;DR: The ToxCast chemical library is demonstrated to provide comprehensive coverage of the knowledge domains and target inventories of potential interest to EPA, and the varied representations and approaches presented here define local chemistry domains potentially worthy of further investigation.
Abstract: The U.S. Environmental Protection Agency’s (EPA) ToxCast program is testing a large library of Agency-relevant chemicals using in vitro high-throughput screening (HTS) approaches to support the development of improved toxicity prediction models. Launched in 2007, Phase I of the program screened 310 chemicals, mostly pesticides, across hundreds of ToxCast assay end points. In Phase II, the ToxCast library was expanded to 1878 chemicals, culminating in the public release of screening data at the end of 2013. Subsequent expansion in Phase III has resulted in more than 3800 chemicals actively undergoing ToxCast screening, 96% of which are also being screened in the multi-Agency Tox21 project. The chemical library unpinning these efforts plays a central role in defining the scope and potential application of ToxCast HTS results. The history of the phased construction of EPA’s ToxCast library is reviewed, followed by a survey of the library contents from several different vantage points. CAS Registry Numbers ar...

455 citations

Journal ArticleDOI
TL;DR: Upon investigating the liver phenotype, it was found that the decrease in liver size is directly related to a reduction in hepatocyte size and the result of massive portosystemic shunting in null animals.
Abstract: A physiological examination of mice harboring a null allele at the aryl hydrocarbon (Ah) locus revealed that the encoded aryl hydrocarbon receptor plays a role in the resolution of fetal vascular structures during development. Although the aryl hydrocarbon receptor is more commonly studied for its role in regulating xenobiotic metabolism and dioxin toxicity, a developmental role of this protein is supported by the observation that Ah null mice display smaller livers, reduced fecundity, and decreased body weights. Upon investigating the liver phenotype, we found that the decrease in liver size is directly related to a reduction in hepatocyte size. We also found that smaller hepatocyte size is the result of massive portosystemic shunting in null animals. Colloidal carbon uptake and microsphere perfusion studies indicated that 56% of portal blood flow bypasses the liver sinusoids. Latex corrosion casts and angiography demonstrated that shunting is consistent with the existence of a patent ductus venosus in adult animals. Importantly, fetal vascular structures were also observed at other sites. Intravital microscopy demonstrated an immature sinusoidal architecture in the liver and persistent hyaloid arteries in the eyes of adult Ah null mice, whereas corrosion casting experiments described aberrations in kidney vascular patterns.

388 citations

Journal ArticleDOI
TL;DR: The incorporation of dosimetry and exposure provide necessary context for interpretation of in vitro toxicity screening data and are important considerations in determining chemical testing priorities.

351 citations


Cited by
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28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Journal ArticleDOI
TL;DR: In this paper, high-density oligonucleotide arrays offer the opportunity to examine patterns of gene expression on a genome scale, and the authors have designed custom arrays that interrogate the expression of the vast majority of proteinencoding human and mouse genes and have used them to profile a panel of 79 human and 61 mouse tissues.
Abstract: The tissue-specific pattern of mRNA expression can indicate important clues about gene function. High-density oligonucleotide arrays offer the opportunity to examine patterns of gene expression on a genome scale. Toward this end, we have designed custom arrays that interrogate the expression of the vast majority of protein-encoding human and mouse genes and have used them to profile a panel of 79 human and 61 mouse tissues. The resulting data set provides the expression patterns for thousands of predicted genes, as well as known and poorly characterized genes, from mice and humans. We have explored this data set for global trends in gene expression, evaluated commonly used lines of evidence in gene prediction methodologies, and investigated patterns indicative of chromosomal organization of transcription. We describe hundreds of regions of correlated transcription and show that some are subject to both tissue and parental allele-specific expression, suggesting a link between spatial expression and imprinting.

3,513 citations

Journal Article
TL;DR: A case study explores the background of the digitization project, the practices implemented, and the critiques of the project, which aims to provide access to a plethora of information to EPA employees, scientists, and researchers.
Abstract: The Environmental Protection Agency (EPA) provides access to information on a variety of topics related to the environment and strives to inform citizens of health risks. The EPA also has an extensive library network that consists of 26 libraries throughout the United States, which provide access to a plethora of information to EPA employees, scientists, and researchers. The EPA implemented a reorganization project to digitize their materials so they would be more accessible to a wider range of users, but this plan was drastically accelerated when the EPA was threatened with a budget cut. It chose to close and reduce the hours and services of some of their libraries. As a result, the agency was accused of denying users the “right to know” by making information unavailable, not providing an adequate strategic plan, and discarding vital materials. This case study explores the background of the digitization project, the practices implemented, and the critiques of the project.

2,588 citations

Journal ArticleDOI
TL;DR: This article shows how MCC produces a more informative and truthful score in evaluating binary classifications than accuracy and F1 score, by first explaining the mathematical properties, and then the asset of MCC in six synthetic use cases and in a real genomics scenario.
Abstract: To evaluate binary classifications and their confusion matrices, scientific researchers can employ several statistical rates, accordingly to the goal of the experiment they are investigating. Despite being a crucial issue in machine learning, no widespread consensus has been reached on a unified elective chosen measure yet. Accuracy and F1 score computed on confusion matrices have been (and still are) among the most popular adopted metrics in binary classification tasks. However, these statistical measures can dangerously show overoptimistic inflated results, especially on imbalanced datasets. The Matthews correlation coefficient (MCC), instead, is a more reliable statistical rate which produces a high score only if the prediction obtained good results in all of the four confusion matrix categories (true positives, false negatives, true negatives, and false positives), proportionally both to the size of positive elements and the size of negative elements in the dataset. In this article, we show how MCC produces a more informative and truthful score in evaluating binary classifications than accuracy and F1 score, by first explaining the mathematical properties, and then the asset of MCC in six synthetic use cases and in a real genomics scenario. We believe that the Matthews correlation coefficient should be preferred to accuracy and F1 score in evaluating binary classification tasks by all scientific communities.

2,358 citations

Journal ArticleDOI
21 Apr 2016-Cell
TL;DR: It is concluded that transcript levels by themselves are not sufficient to predict protein levels in many scenarios and to thus explain genotype-phenotype relationships and that high-quality data quantifying different levels of gene expression are indispensable for the complete understanding of biological processes.

1,996 citations