Dataset Information

A New Stochastic Kriging Method for Modeling Multi-Source Exposure-Response Data in Toxicology Studies.

ABSTRACT: One of the most fundamental steps in risk assessment is to quantify the exposure-response relationship for the material/chemical of interest. This work develops a new statistical method, referred to as SKQ (stochastic kriging with qualitative factors), to synergistically model exposure-response data, which often arise from multiple sources (e.g., laboratories, animal providers, and shapes of nanomaterials) in toxicology studies. Compared to the existing methods, SKQ has several distinct features. First, SKQ integrates data across multiple sources and allows for the derivation of more accurate information from limited data. Second, SKQ is highly flexible and able to model practically any continuous response surfaces (e.g., dose-time-response surface). Third, SKQ is able to accommodate variance heterogeneity across experimental conditions and to provide valid statistical inference (i.e., quantify uncertainties of the model estimates). Through empirical studies, we have demonstrated SKQ's ability to efficiently model exposure-response surfaces by pooling information across multiple data sources. SKQ fits into the mosaic of efficient decision-making methods for assessing the risk of a tremendously large variety of nanomaterials and helps to alleviate safety concerns regarding the enormous amount of new nanomaterials.

SUBMITTER: Wang K

PROVIDER: S-EPMC4105196 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature

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A New Stochastic Kriging Method for Modeling Multi-Source Exposure-Response Data in Toxicology Studies.

Wang Kai K Chen Xi X Yang Feng F Porter Dale W DW Wu Nianqiang N

ACS sustainable chemistry & engineering 20140520 7

One of the most fundamental steps in risk assessment is to quantify the exposure-response relationship for the material/chemical of interest. This work develops a new statistical method, referred to as SKQ (stochastic kriging with qualitative factors), to synergistically model exposure-response data, which often arise from multiple sources (e.g., laboratories, animal providers, and shapes of nanomaterials) in toxicology studies. Compared to the existing methods, SKQ has several distinct features ...[more]

PMID: 25068094

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Project description:Droughts are the most expensive natural disasters on the planet. As a result of climate change and human activities, the incidence and impact of drought have grown in China. Timely and effective monitoring of drought is crucial for water resource management, drought mitigation, and national food security. In this study, we constructed a comprehensive drought index (YCDI) suitable for the Yellow River Basin using principal component analysis and the entropy weight-AHP method, which integrated a standardized precipitation evapotranspiration index (SPEI), self-calibrating Palmer drought severity index (scPDSI), vegetation condition index (VCI), and standardized water storage index (SWSI). SWSI is calculated by the terrestrial water storage anomaly (TWSA), which can more comprehensively reflect the impact of surface water resources on drought (as compared with soil moisture-based indexes). The study results showed that: (1) compared with single drought index, YCDI has stronger ability to monitor drought process. In terms of time scale and drought degree, the monitoring results based on YCDI were similar with data presented in the China Flood and Drought Bulletin and Meteorological Drought Yearbook, reaching ~87% and ~69%, respectively. The correlation between drought intensity and crop harvest area was 0.56. (2) By the combined analysis of the Mann-Kendall test and Moving T test, it was found that the abrupt change of YCDI index at the time of 2009, mainly due to the precipitation in 2009 reached the lowest value in the past 30 years in northern China and extreme high temperature weather. (3) The YCDI of Henan and Shandong provinces in the middle and lower reaches of the basin decreased more significantly, with the maximum value reaching 0.097/yr, while the index in the upper reaches showed an increasing trend with the maximum rate of 0.096/yr. (4) The frequency of mild drought, moderate drought, severe drought and extreme drought in the Yellow River basin during the study period was 15.84%, 12.52%, 4.03% and 0.97%, respectively. Among them, the highest frequency of droughts occurred in Ningxia, Inner Mongolia and central Shaanxi provinces. Drought causation in the Yellow River basin is more influenced by human activities than climate change in the middle and lower reaches, while climate change is the main factor in the upper reaches. Overall, YCDI is a reliable indicator for monitoring the spatial and temporal evolution of drought in the Yellow River basin, and it can be used for monitoring soil moisture changes and vegetation dynamics, which can provide scientific guidance for regional drought governance.

Project description:BackgroundDiethyl phthalate (DEP) is widely used in many commercially available products including plastics and personal care products. DEP has generally not been found to share the antiandrogenic mode of action that is common among other types of phthalates, but there is emerging evidence that DEP may be associated with other types of health effects.ObjectiveTo inform chemical risk assessment, we performed a systematic review to identify and characterize outcomes within six broad hazard categories (male reproductive, female reproductive, developmental, liver, kidney, and cancer) following exposure of nonhuman mammalian animals to DEP or its primary metabolite, monoethyl phthalate (MEP).MethodsA literature search was conducted in online scientific databases (PubMed, Web of Science, Toxline, Toxcenter) and Toxic Substances Control Act Submissions, augmented by review of online regulatory sources as well as forward and backward searches. Studies were selected for inclusion using PECO (Population, Exposure, Comparator, Outcome) criteria. Studies were evaluated using criteria defined a priori for reporting quality, risk of bias, and sensitivity using a domain-based approach. Evidence was synthesized by outcome and life stage of exposure, and strength of evidence was summarized into categories of robust, moderate, slight, indeterminate, or compelling evidence of no effect, using a structured framework.ResultsThirty-four experimental studies in animals were included in this analysis. Although no effects on androgen-dependent male reproductive development were observed following gestational exposure to DEP, there was evidence including effects on sperm following peripubertal and adult exposures, and the overall evidence for male reproductive effects was considered moderate. There was moderate evidence that DEP exposure can lead to developmental effects, with the major effect being reduced postnatal growth following gestational or early postnatal exposure; this generally occurred at doses associated with maternal effects, consistent with the observation that DEP is not a potent developmental toxicant. The evidence for liver effects was considered moderate based on consistent changes in relative liver weight at higher dose levels; histopathological and biochemical changes indicative of hepatic effects were also observed, but primarily in studies that had significant concerns for risk of bias and sensitivity. The evidence for female reproductive effects was considered slight based on few reports of statistically significant effects on maternal body weight gain, organ weight changes, and pregnancy outcomes. Evidence for cancer and effects on kidney were judged to be indeterminate based on limited evidence (i.e., a single two-year cancer bioassay) and inconsistent findings, respectively.ConclusionsThese results suggest that DEP exposure may induce androgen-independent male reproductive toxicity (i.e., sperm effects) as well as developmental toxicity and hepatic effects, with some evidence of female reproductive toxicity. More research is warranted to fully evaluate these outcomes and strengthen confidence in this database.

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A New Stochastic Kriging Method for Modeling Multi-Source Exposure-Response Data in Toxicology Studies.

Publications

A New Stochastic Kriging Method for Modeling Multi-Source Exposure-Response Data in Toxicology Studies.

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