individual values for liver detoxification for each human sample and for each chemical. This dataset is associated with the following publication: Moser, G., and S. Padilla. Esterase detoxification of acetylcholinesterase inhibitors using human liver samples in vitro. TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 11-20, (2016).

This dataset was prepared from the US Environmental Protection Agency's (EPA) Toxicity Reference Database (ToxRefDB) that contains information for 1,142 chemicals and 5,960 studies. Curations include information regarding the study design, chemical identity, dosing, treatment group parameters, treatment-related (significantly different from control) and critical (adverse) effects for all dose treatment groups, as well as endpoint testing status according to guideline specifications. ToxRefDB data was examined for all subchronic (SUB) studies with complete curations, which included registrant-submitted toxicity studies from the US EPA’s Office of Pesticide Programs (OPP) and guideline studies sourced from the National Toxicology Program (NTP). Statistically significant differences between treatment and control group data at p<0.05 within the source documents was extracted and denoted with a “treatment-related” Boolean indicator “true”. Across the studies with absolute liver weights and relative-to-body (RLW) liver weights, the treatment-related mean effect values at the lowest effect (LE) dose levels as well as mean control liver weights were determined for all chemical-study-sex-species-exposure route groupings. The LE-ALW and LE-RLW changes were quantified as effect size differences from control using the following equation: Effect_size = 100 x (LE Effect_value – Control Effect_Value) / Control Effect_Value Any microscopic liver pathology effects occurring at the corresponding LE dose level of weight change were also identified and listed in the dataset. Histopathology terms were presented as they appeared in ToxRefDB without harmonizing different hierarchical levels and aggregating multiple terms used to depict the same lesions. The final dataset that includes chemical stressor information, study source identifiers, study type, sex, species, strain, administration route, administration method, dose level, mg/kg/day value, qualitative and quantitative effect information, effect size from control, and pathology effects if present. The dataset includes data from 389 subchronic studies on 273 chemicals. This dataset is associated with the following publication: Mezencev, R., M. Feshuk, L. Kolaczkowski, G. Peterson, Q. Zhao, S. Watford, and J. Weaver. The association between histopathologic effects and liver weight changes induced in mice and rats by chemical exposures: an analysis of the data from Toxicity Reference Database (ToxRefDB). TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 200(2): 404-413, (2024).

These are the raw data files for TOXSCI manuscript 19-0578 entitled, “Respirometric Screening and Characterization of Mitochondrial Toxicants Within the ToxCast Phase I and II Chemical Libraries”: Description from readme.txt file: 1) sc_seahorse.lvl0.merged.data.csv- contains all mapped raw OCR data from tier 1 single-concentration RSA screening of 1,042 Toxcast Phase I and II chemicals 2) mc_seahorse.lvl0.merged.data.csv- contains all mapped raw OCR data from tier 2 multi-concentration RSA screening of 249 actives from tier 1 3) EFA.lvl0.merged.data.csv- contains all mapped raw OCR data from tier 3 EFA screening of 149 putative electron transport chain inhibitors 4) mc5_mc6_ncct_mito_nov2019.csv- level 5 and 6 outputs from ToxCast pipeline (tcpl) analysis 5) RawMC3_ToxCast_by_aeid.csv- level 3 tcpl outputs for all mitochondrial ToxCast assays 6) RawMC5_ToxCast_by_aeid.csv- level 5 tcpl outputs for all mitochondrial ToxCast assays 7) ref.set.chems.csv- sixty reference chemicals used to compared assay performance 8) study_code.R- R script used to analyze data and generate figures and tables. This dataset is associated with the following publication: Hallinger, D., H. Lindsay, K. Friedman, D. Suarez, and S. Simmons. Respirometric Screening and Characterization of Mitochondrial Toxicants Within the ToxCast Phase I and II Chemical Libraries. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 176(1): 175-192, (2020).

These are the raw data files for TOXSCI manuscript 19-0578 entitled, “Respirometric Screening and Characterization of Mitochondrial Toxicants Within the ToxCast Phase I and II Chemical Libraries”: Description from readme.txt file: 1) sc_seahorse.lvl0.merged.data.csv- contains all mapped raw OCR data from tier 1 single-concentration RSA screening of 1,042 Toxcast Phase I and II chemicals 2) mc_seahorse.lvl0.merged.data.csv- contains all mapped raw OCR data from tier 2 multi-concentration RSA screening of 249 actives from tier 1 3) EFA.lvl0.merged.data.csv- contains all mapped raw OCR data from tier 3 EFA screening of 149 putative electron transport chain inhibitors 4) mc5_mc6_ncct_mito_nov2019.csv- level 5 and 6 outputs from ToxCast pipeline (tcpl) analysis 5) RawMC3_ToxCast_by_aeid.csv- level 3 tcpl outputs for all mitochondrial ToxCast assays 6) RawMC5_ToxCast_by_aeid.csv- level 5 tcpl outputs for all mitochondrial ToxCast assays 7) ref.set.chems.csv- sixty reference chemicals used to compared assay performance 8) study_code.R- R script used to analyze data and generate figures and tables. This dataset is associated with the following publication: Hallinger, D., H. Lindsay, K. Friedman, D. Suarez, and S. Simmons. Respirometric Screening and Characterization of Mitochondrial Toxicants Within the ToxCast Phase I and II Chemical Libraries. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 176(1): 175-192, (2020).

Research interested in oxidative stress markers following exposure to VOCs. This dataset is associated with the following publication: Kodavanti , P., J. Royland , D.A. Moore-Smith, J. Beas, J. Richards , T. Beasley , P. Evansky , and P.J. Bushnell. Acute and Subchronic Toxicity of Inhaled Toluene in Male Long-Evans Rats: Oxidative Stress Markers in Brain. NEUROTOXICOLOGY. Elsevier B.V., Amsterdam, NETHERLANDS, 51: 10-19, (2015).

Research interested in oxidative stress markers following exposure to VOCs. This dataset is associated with the following publication: Kodavanti , P., J. Royland , D.A. Moore-Smith, J. Beas, J. Richards , T. Beasley , P. Evansky , and P.J. Bushnell. Acute and Subchronic Toxicity of Inhaled Toluene in Male Long-Evans Rats: Oxidative Stress Markers in Brain. NEUROTOXICOLOGY. Elsevier B.V., Amsterdam, NETHERLANDS, 51: 10-19, (2015).

Supplemental data for "Schaupp CM, Maloney EM, Mattingly K, Olker JH, Villeneuve DL. Comparison of in silico, in vitro, and in vivo toxicity benchmarks suggests a role for ToxCast data in ecological hazard assessment. Toxicol Sci. 2023 Jul 25:kfad072. doi: 10.1093/toxsci/kfad072. Epub ahead of print. PMID: 37490521.". This dataset is associated with the following publication: Schaupp, C., E. Maloney, K. Mattingly, J. Olker, and D. Villeneuve. Comparison of in silico, in vitro, and in vivo toxicity benchmarks suggests a role for ToxCast data in ecological hazard assessment.. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 195(2): 145-154, (2023).

Bioactivity data for p,p'-DDD and analogues from ToxCast assays conducted in liver cells were sourced from the EPA’s CompTox Chemistry Dashboard. The links also provide access to the ToxCast assay information and annotation data user guide. This dataset is associated with the following publication: Lizarraga, L., J. Dean, J. Kaiser, S. Wesselkamper, J. Lambert, and J. Zhao. A Case Study on the Application of An Expert-driven Read-Across Approach in Support of Quantitative Risk Assessment of p,p’-Dichlorodiphenyldichloroethane. REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, USA, 103: 301-313, (2019).

Bioactivity data for p,p'-DDD and analogues from ToxCast assays conducted in liver cells were sourced from the EPA’s CompTox Chemistry Dashboard. The links also provide access to the ToxCast assay information and annotation data user guide. This dataset is associated with the following publication: Lizarraga, L., J. Dean, J. Kaiser, S. Wesselkamper, J. Lambert, and J. Zhao. A Case Study on the Application of An Expert-driven Read-Across Approach in Support of Quantitative Risk Assessment of p,p’-Dichlorodiphenyldichloroethane. REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, USA, 103: 301-313, (2019).