An approach for prioritizing "down-the-drain" chemicals used in the household.
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ABSTRACT:
SUBMITTER: Rotsidou M
PROVIDER: S-EPMC4344670 | biostudies-literature | 2015 Jan
REPOSITORIES: biostudies-literature
Publications
An approach for prioritizing "down-the-drain" chemicals used in the household.
Rotsidou Marina M Scrimshaw Mark D MD
International journal of environmental research and public health 20150126 2
Many chemicals are present in cleaning and personal care products, which after use are washed down the drain and find their way into water bodies, where they may impact the environment. This study surveyed individuals to determine what products were used most in the home, in an attempt to prioritize which compounds may be of most concern. The survey resulted in the identification of 14 categories of products consisting of 315 specific brands. The survey estimated that individuals each discharge ...[more]
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Project description:BackgroundDiabetes and obesity are major threats to public health in the United States and abroad. Understanding the role that chemicals in our environment play in the development of these conditions is an emerging issue in environmental health, although identifying and prioritizing chemicals for testing beyond those already implicated in the literature is challenging. This review is intended to help researchers generate hypotheses about chemicals that may contribute to diabetes and to obesity-related health outcomes by summarizing relevant findings from the U.S. Environmental Protection Agency (EPA) ToxCast™ high-throughput screening (HTS) program.ObjectivesOur aim was to develop new hypotheses around environmental chemicals of potential interest for diabetes- or obesity-related outcomes using high-throughput screening data.MethodsWe identified ToxCast™ assay targets relevant to several biological processes related to diabetes and obesity (insulin sensitivity in peripheral tissue, pancreatic islet and ? cell function, adipocyte differentiation, and feeding behavior) and presented chemical screening data against those assay targets to identify chemicals of potential interest.DiscussionThe results of this screening-level analysis suggest that the spectrum of environmental chemicals to consider in research related to diabetes and obesity is much broader than indicated by research papers and reviews published in the peer-reviewed literature. Testing hypotheses based on ToxCast™ data will also help assess the predictive utility of this HTS platform.ConclusionsMore research is required to put these screening-level analyses into context, but the information presented in this review should facilitate the development of new hypotheses.CitationAuerbach S, Filer D, Reif D, Walker V, Holloway AC, Schlezinger J, Srinivasan S, Svoboda D, Judson R, Bucher JR, Thayer KA. 2016. Prioritizing environmental chemicals for obesity and diabetes outcomes research: a screening approach using ToxCast™ high-throughput data. Environ Health Perspect 124:1141-1154;?http://dx.doi.org/10.1289/ehp.1510456.
| S-EPMC4977057 | biostudies-literature
Project description:The current multistep carcinogenesis models of colon cancer do not fully capture the genetic heterogeneity of the disease, which is additionally complicated by the presence of passenger and driver genetic alterations. The aim of the present study was to select in the context of this significant heterogeneity additional genes functionally related to colon cancer development. Methods: High-throughput copy number and gene expression data of 36 microsatellite stable sporadic colon cancers resected from patients of a single Institution characterized for mutations in APC, KRAS, TP53 and loss of 18q were analyzed. Genes whose expression correlated with the underlying copy number pattern were selected and their association with the above listed mutations and overall survival was evaluated. Results: Gain of 20q was strongly associated with TP53 mutation, and overall survival with alterations on 7p, 8p, 13q, 18q and 20q. An association with 18q loss and gain of 8q24 was also observed. New candidate genes with a potential role in colon cancer are PLCG1 on 20q, DBC1 on 8q21 and NDGR1 on 8p24. In addition an unexpected pattern of loss and mutability was found in the region upstream of KRAS gene. Conclusions: By integrating copy number alterations with gene expression and mutations in colon cancer associated genes we have developed a strategy that identifies previously known molecular features and additional players in the molecular landscape of colon cancer.
2009-08-27 | GSE16125 | GEO
Project description:Pesticides have been reported in treated wastewater effluent at concentrations that exceed aquatic toxicity thresholds, indicating that treatment may be insufficient to adequately address potential pesticide impacts on aquatic life. Gaining a better understanding of the relative contribution from specific use patterns, transport pathways, and flow characteristics is an essential first step to informing source control measures. The results of this study are the first of their kind, reporting pesticide concentrations at sub-sewershed sites within a single sewer catchment to provide information on the relative contribution from various urban sources. Seven monitoring events were collected from influent, effluent, and seven sub-sewershed sites to capture seasonal variability. In addition, samples were collected from sites with the potential for relatively large mass fluxes of pesticides (pet grooming operations, pest control operators, and laundromats). Fipronil and imidacloprid were detected in most samples (>70%). Pyrethroids were detected in >50% of all influent and lateral samples. There were significant removals of pyrethroids from the aqueous process stream within the facility to below reporting limits. Imidacloprid and fiproles were the only pesticides that were detected above reporting limits in effluent, highlighting the importance of source identification and control for the more hydrophilic compounds. Single source monitoring revealed large contributions of fipronil, imidacloprid, and permethrin originating from a pet groomer, with elevated levels of cypermethrin at a commercial laundry location. The results provide important information needed to prioritize future monitoring efforts, calibrate down-the-drain models, and identify potential mitigation strategies at the site of pesticide use to prevent introduction to sewersheds.
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Project description:BackgroundScientists and regulatory agencies strive to identify chemicals that may cause harmful effects to humans and the environment; however, prioritization is challenging because of the large number of chemicals requiring evaluation and limited data and resources.ObjectivesWe aimed to prioritize chemicals for exposure and exposure potential and obtain a quantitative perspective on research needs to better address uncertainty in screening assessments.MethodsWe used a multimedia mass balance model to prioritize > 12,000 organic chemicals using four far-field human exposure metrics. The propagation of variance (uncertainty) in key chemical information used as model input for calculating exposure metrics was quantified.ResultsModeled human concentrations and intake rates span approximately 17 and 15 orders of magnitude, respectively. Estimates of exposure potential using human concentrations and a unit emission rate span approximately 13 orders of magnitude, and intake fractions span 7 orders of magnitude. The actual chemical emission rate contributes the greatest variance (uncertainty) in exposure estimates. The human biotransformation half-life is the second greatest source of uncertainty in estimated concentrations. In general, biotransformation and biodegradation half-lives are greater sources of uncertainty in modeled exposure and exposure potential than chemical partition coefficients.ConclusionsMechanistic exposure modeling is suitable for screening and prioritizing large numbers of chemicals. By including uncertainty analysis and uncertainty in chemical information in the exposure estimates, these methods can help identify and address the important sources of uncertainty in human exposure and risk assessment in a systematic manner.
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Project description:Background:Industries such as electroplating, mining and battery production are major sources of heavy metal-rich waste entering nearby water bodies. Irrigation with heavy metal contaminated water can deteriorate soil quality as well as agricultural produce and have further toxic effects on human health. Objectives:The objective of the present study was to estimate the concentration of hazardous heavy metals such as chromium (Cr), cadmium (Cd), copper (Cu), nickel (Ni), zinc (Zn) and lead (Pb), as well as physico-chemical variables (pH, electrical conductivity, total dissolved solids, chemical oxygen demand and dissolved oxygen) at sampling locations along the Najafgarh and Loha mandi drains in Delhi, National Capital Region, India. Methods:The present study evaluated the quality of wastewater from the Najafgarh and Loha mandi drains, which are used for irrigational purposes in the Delhi region. Drain water quality was monitored for a period of 2 years for physico-chemical variables (pH, chemical oxygen demand, electrical conductivity and dissolved oxygen) as well as heavy metal concentrations (Cr, Cu, Cd, Zn, Ni and Pb). The two-year monitoring period (July 2012-March 2014) was chosen to represent three seasons: pre-monsoon, monsoon, and post-monsoon. Results:Varied concentrations of multiple heavy metals were found due to the extensive discharge of untreated industrial effluents into the drain water. Punjabi Bagh of Najafgarh drain was the most contaminated sampling site with the maximum concentration of Zn (12.040 ± 0.361 mg L-1), followed by Cr (2.436 ± 0.073mg L-1) and Cu (2.617 ± 0.078 mg L-1). Conclusions:Consumption of heavy metal-contaminated agricultural products can cause deleterious human health effects, leading to further health problems. The presence of multi-heavy metal ions above the Food and Agriculture Organization of the United Nations (FAO) permissible limits indicated that drain water was not suitable for irrigational purposes, and adequate measures are required to remove the heavy metal load from drain water. Competing Interests:The authors declare no competing financial interests.
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Project description:The current multistep carcinogenesis models of colon cancer do not fully capture the genetic heterogeneity of the disease, which is additionally complicated by the presence of passenger and driver genetic alterations. The aim of the present study was to select in the context of this significant heterogeneity additional genes functionally related to colon cancer development. Methods: High-throughput copy number and gene expression data of 36 microsatellite stable sporadic colon cancers resected from patients of a single Institution characterized for mutations in APC, KRAS, TP53 and loss of 18q were analyzed. Genes whose expression correlated with the underlying copy number pattern were selected and their association with the above listed mutations and overall survival was evaluated. Results: Gain of 20q was strongly associated with TP53 mutation, and overall survival with alterations on 7p, 8p, 13q, 18q and 20q. An association with 18q loss and gain of 8q24 was also observed. New candidate genes with a potential role in colon cancer are PLCG1 on 20q, DBC1 on 8q21 and NDGR1 on 8p24. In addition an unexpected pattern of loss and mutability was found in the region upstream of KRAS gene. Conclusions: By integrating copy number alterations with gene expression and mutations in colon cancer associated genes we have developed a strategy that identifies previously known molecular features and additional players in the molecular landscape of colon cancer. A total of 48 sporadic colon cancer samples were analyzed by Affymetrix Mapping 250K Nsp SNP Arrays and 36 of them were also analyzed by Affymetrix Human Exon 1.0 ST Array [transcript (gene) version]. Short summary: Expression data was correlated to copy number data to identify genes whose expression was induced by copy number changes. Gene dosage candidates were then evaluated for their association with gene mutation status of APC, KRAS and TP53, loss of heterozigosity of 18q and overall survival. Long summary: Raw intensity .CEL files of the SNP arrays were processed with Chromosome Copy Number Analysis Tool (v.1.5.6 Affymetrix, Santa Clara, CA) to identify chromosomal gains and losses. Forty eight normal samples from the HapMap project supplied by Affymetrix were used as an un-paired reference set [http://www.affymetrix.com/support/technical/sample_data/500k_data.affx]. All genomic coordinates of the SNP array probes were mapped to the Human Mar. 2006 assembly the UCSC genome browser. Raw intensity .CEL files of the exon arrays were processed with the Robust Multi-Array implementation of Affymetrix Power Tools (v.1.8.6) using the core set of features (22011 probesets). All plots and analysis steps following this processing were done using the R programming language version 2.9.0Bioconductor packages. The identification of statistically significant segments of aberration in the copy number data was performed using the default parameters of the KC-SMART algorithm and 1000 permutations (KCsmart v.2.2.0). The identification and annotation of genes within each aberrant segment was performed using biomaRt v.2.0.0. The list of genes was further annotated by using the cancerGenes resource, Cancer Gene Census and the list of breast and colon CAN genes listed in Wood et al. The genomic landscapes of human breast and colorectal cancers. Science 2007;318:1108-1113. Gene dosage effects across 36 samples for which gene expression and copy number data was available was assessed by evaluating the Spearman correlation of the raw continuous copy number (log-ratios) expression (log-intensity) for each genomic region surrounding each gene falling within the segments identified by KC-SMART. Prior to performing this task, to reduce the total number of correlation tests to perform, we filtered the gene expression dataset by removing all entries having no Gene Symbol annotation 17291 probesets and half the remaining dataset exhibiting the lowest variance resulting in 8645 probesets. Category package version 2.10.0 was used to apply a linear model-based test to detect enrichment of systematic high correlation in specific chromosomal bands taking into consideration the hierarchical structure of the bands. Gene expression class comparisons and survival analysis of the selected gene dosage candidates were performed using two sample t-tests and Cox proportional hazards regression. P-value adjustment of the correlation tests and the gene expression associations was performed using the step-up false discovery rate (FDR) controlling procedure of Benjamini and Hochberg. Raw data, supplementary methods and figures supplied as reproducible documentation (Sweave file) available from http://pierotti.group.ifom-ieo-campus.it/suppl/crc.html.
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Project description:BackgroundIdentifying cancer hazards is the first step towards cancer prevention. The International Agency for Research on Cancer (IARC) Monographs Programme, which has evaluated nearly 1,000 agents for their carcinogenic potential since 1971, typically selects agents for hazard identification on the basis of public nominations, expert advice, published data on carcinogenicity, and public health importance.ObjectivesHere, we present a novel and complementary strategy for identifying agents for hazard evaluation using chemoinformatics, database integration, and automated text mining.DiscussionTo inform selection among a broad range of pesticides nominated for evaluation, we identified and screened nearly 6,000 relevant chemical structures, after which we systematically compiled information on 980 pesticides, creating network maps that allowed cluster visualization by chemical similarity, pesticide class, and publicly available information concerning cancer epidemiology, cancer bioassays, and carcinogenic mechanisms. For the IARC Monograph meetings that took place in March and June 2015, this approach supported high-priority evaluation of glyphosate, malathion, parathion, tetrachlorvinphos, diazinon, p,p'-dichlorodiphenyltrichloroethane (DDT), lindane, and 2,4-dichlorophenoxyacetic acid (2,4-D).ConclusionsThis systematic approach, accounting for chemical similarity and overlaying multiple data sources, can be used by risk assessors as well as by researchers to systematize, inform, and increase efficiency in selecting and prioritizing agents for hazard identification, risk assessment, regulation, or further investigation. This approach could be extended to an array of outcomes and agents, including occupational carcinogens, drugs, and foods. Citation: Guha N, Guyton KZ, Loomis D, Barupal DK. 2016. Prioritizing chemicals for risk assessment using chemoinformatics: examples from the IARC Monographs on Pesticides. Environ Health Perspect 124:1823-1829;?http://dx.doi.org/10.1289/EHP186.
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Project description:Predicting the contribution of media components to bacterial growth was first initiated by introducing machine learning to high-throughput growth assays. A total of 1336 temporal growth records corresponding to 225 different media, which were composed of 13 chemical components, were generated. The growth rate and saturated density of each growth curve were automatically calculated with the newly developed data processing program. To identify the decision making factors related to growth among the 13 chemicals, big datasets linking the growth parameters to the chemical combinations were subjected to decision tree learning. The results showed that the only carbon source, glucose, determined bacterial growth, but it was not the first priority. Instead, the top decision making chemicals in relation to the growth rate and saturated density were ammonium and ferric ions, respectively. Three chemical components (NH4+, Mg2+ and glucose) commonly appeared in the decision trees of the growth rate and saturated density, but they exhibited different mechanisms. The concentration ranges for fast growth and high density were overlapped for glucose but distinguished for NH4+ and Mg2+. The results suggested that these chemicals were crucial in determining the growth speed and growth maximum in either a universal use or a trade-off manner. This differentiation might reflect the diversity in the resource allocation mechanisms for growth priority depending on the environmental restrictions. This study provides a representative example for clarifying the contribution of the environment to population dynamics through an innovative viewpoint of employing modern data science within traditional microbiology to obtain novel findings.
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Project description:We assessed the genotoxicity of 30 food-flavoring chemicals used in Japan that have not been investigated before. These 30 food-flavoring chemicals have representative chemical structures belonging to 18 chemical classes. The Ames and chromosomal aberration (CA) tests (in vitro tests) were first conducted in accordance with the "Food Additive Risk Assessment Guidelines" of the Japan Food Safety Commission. If the in vitro test yielded a positive result, an in vivo micronucleus test or a transgenic mouse gene mutation assay was performed to verify the in vitro test results. Of the 30 food-flavoring chemicals, 3 yielded a positive result in both Ames and CA tests. Another 11 chemicals yielded positive results in the CA test. However, none of the chemicals yielding positive in vitro test results yielded positive results in the in vivo tests. These findings indicate no genotoxicity concerns of the food-flavoring chemicals belonging to the abovementioned 18 chemical classes used in Japan unless there are other structural modifications.
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