Raw data for each glucocorticoid ligand mixtures experiment. This dataset is associated with the following publication: MedlockKakaley, E., M. Cardon, E. Gray, P. Hartig, and V. Wilson. Generalized concentration addition model predicts glucocorticoid activity bioassay responses to environmentally detected receptor-ligand mixtures. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 252-263, (2019).

This data release includes datasets provided by the Woolnough Laboratory at Central Michigan University. These data were collected as a part of a laboratory exposure experiment, conducted in 2018, examining the effects of agricultural and urban contaminant mixtures on two life stages (larval and juvenile) of the freshwater mussel, plain pocketbook (Lampsilis cardium), using largemouth bass (Micropterus salmoides) as the host fish. Contaminant mixtures were representative of contaminants frequently detected in agricultural and urban settings. Agricultural contaminant mixtures consisted of bromacil, estrone, metolachlor, tri(butoxyethyl) phosphate, 4-nonylphenol, atrazine, N,N-diethyl-meta-toluamide (DEET), and bisphenol A. Urban contaminant mixtures consisted of metformin, sulfamethoxazole, desvenlafazine, and 5-methyl-1H-benzotriazole. Lampsilis cardium and M. salmoides were exposed to either an agricultural or urban contaminant mixture, control water treatment, or control ethanol treatment for 40 or 100 days. Throughout the exposure periods, water samples were collected from the contaminant mixture holding tanks for verification of concentration dosing. Gravid adult female L. cardium and M. salmoides were exposed to a specified treatment for 13 or 60 days. During this exposure period, prematurely released glochidia (L. cardium larvae) were enumerated. After the initial exposure period, glochidia were stripped from gravid female L. cardium, enumerated, and inoculated into M. salmoides tanks of the corresponding treatment for infestation and encystment. After infestation, parasitic glochidia and M. salmoides host fish were exposed for 27 or 40 more days (40- and 100-day total exposure durations, respectively). During this exposure period, glochidia that dropped off the host fish were enumerated and observations of their metamorphose state (partially or fully metamorphosed) were documented. The data contained in this data release were analyzed and discussed in the primary publication titled “Reduced freshwater mussel juvenile production as a result of agricultural and urban contaminant mixture exposures” (https://doi.org/xxxxxx).

GC/MS metabolomic data from livers of amphibians exposed to pesticides. This dataset is associated with the following publication: Glinski, D., T. Purucker, R. Van Meter, M. Black, and M. Henderson. Endogenous and exogenous biomarker analysis in terrestrial phase amphibians (Lithobates sphenocephala) following dermal exposure to pesticide mixtures. ENVIRONMENTAL CHEMISTRY. CSIRO Publishing, Collingwood Victoria, AUSTRALIA, 16(1): 55-67, (2019).

GC/MS data from the metabolomic profiling of green frog livers after exposure to pesticides and their mixtures. This dataset is associated with the following publication: Van Meter, R., D. Glinski, T. Purucker, and M. Henderson. Influence of exposure to pesticide mixtures on the metabolomic profile in post-metamorphic green frogs (Lithobates clamitans). SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 624: 1348-1359, (2018).

Publicly available dataset containing chemical exposure data. This dataset is associated with the following publication: Lin, Y., V. Morozov, A. Kadry, J. Caffrey , and W. Chou. Reconstructing population exposures to acrylamide from human monitoring data using a pharmacokinetic framework. CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 331: 138798, (2023).

Data from study assessing the utility of knowledgebase-leveraging of comprehensive environmental-contaminant-exposure datasets by comparing biological effects predicted on the basis of target chemical analyses with measured biological effects in corresponding split water samples.

The dataset contains the metadata associated with the figures in the manuscript. This dataset is associated with the following publication: Corteselli, E., E. Gibbs-Flournoy, S. Simmons, P. Bromberg, A. Gold, and J.M. Samet. Long Chain Lipid Hydroperoxides Increase the Glutathione Redox Potential Through Glutathione Peroxidase 4. Biochimica et Biophysica Acta. Elsevier Science Ltd, New York, NY, USA, 1863(5): 950-959, (2019).

RLWrankedLists.tar.gz:These lists linked to various chemical treatment conditions serve as the target collection of Cmap. Probes of the entire microarray are sorted based on their log fold changes over control conditions. RLWsignatures2015.tar.gz: These signatures linked to various chemical treatment conditions serve as queries in Cmap. This dataset is not publicly accessible because: too big in size. It can be accessed through the following means: located in the High Performance Computing archive /asm/FISHTOX/TAR_BALLs/fishCmap.tar.gz. Format: Fish connectivity mapping involves working with a large amount of data. Of primary interest to other researchers and general public are probably the rank-ordered gene lists and gene signatures. The former acts as a database-like target while the latter as queries. Along with fish Cmap outputs, they are contained in the file fishCmap.tar.gz as RLWrankedLists.tar.gz and RLWsignatures2015.tar.gz. This dataset is associated with the following publication: Wang , R., A. Biales , N. Garcia-Reyero, E. Perkins, D. Villeneuve, G. Ankley, and D. Bencic. Fish Connectivity Mapping: Linking Chemical Stressors by Their MOA-Driven Transcriptomic Profiles. BMC Genomics. BioMed Central Ltd, London, UK, 17(84): 1-20, (2016).

This subproduct is a database of multiagency data, funded as part of the Great Lakes Restoration Initiative (GLRI), to monitor and assess potential exposure and effects of chemicals of emerging concern (CECs) on aquatic and other wildlife in the Great Lakes. This database includes environmental contaminant occurrence data and biological indicator data from Army Corps of Engineers, NOAA, US EPA, US FWS, and USGS.