These data are the individual parameter and well-level data that were support the conclusions in Brown et al. Note: the parameters CVtime and CVnetwork were not used. This dataset is associated with the following publication: Brown, J., D. Hall, C. Frank, K. Wallace, W. Mundy, and T. Shafer. Editor's highlight: Evaluation of a Microelectrode Array-based Assay for Neural Network Ontogeny using Training Set Chemicals. TOXICOLOGICAL SCIENCES. Society of Toxicology, 154(1): 126-139, (2016).

PubMed was searched for the terms microRNA and biomarker in addition to blood (blue), urine (orange), saliva (grey), or cerebrospinal fluid (yellow). The graph in the paper displays the number of total annual publications over the past 16 years and the actual numbers used generate this graph are in incuded in the attached spreadsheet. A near annual doubling of publications occurred from the years 2009 until 2015, whereas only a mere 4% increase in annual publications from 2015 until 2018 was noted. While a number of factors can contribute to these publication trends, this indicates an overall cooling of research interest in biofluid-based microRNA biomarker development. This dataset is associated with the following publication: Chorley, B., E. Atabakhsh, G. Doran, J. Gautier, H. Ellinger-Ziegelbauer, D. Jackson, T. Sharapova, P. Yuen, R. Church, P. Couttet, R. Froetschl, J. McDuffie, V. Martine, P. Pande, L. Peel, C. Rafferty, F. Simutis, and A. Harrill. Methodological considerations for measuring biofluid-based microRNA biomarkers. CRITICAL REVIEWS IN TOXICOLOGY. Taylor & Francis Group, London, UK, 51(3): 264-282, (2021).

We used data from the National Birth Defects Prevention Study to identify infants born in North Carolina with available new born blood spots. We processed dried blood spots to characterize DNA methylation patterns and evaluated differences in DNA methylation patterns by birth defect status (no birth defect, diagnosed with Tetralogy of Fallot) and by exposure to air pollution. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Access to the data can be requested from CDC. Format: The data set is from CDC's National Birth Defect Prevention Study (NBDPS). The data include date of birth and residential address history, as well as other individual-level variables.

This dataset contains the data, code and associated files for the manuscript Authored by Marable et al. This dataset is associated with the following publication: Marable, C., C. Frank, R. Seim, S. Hester, M. Henderson, B. Chorley, and T. Shafer. Integrated Omic Analyses Identify Pathways and Transcriptomic Regulators Associated with Chemical Alterations of in vitro Neural Network Formation. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 186(1): 118-133, (2022).

Biomonitoring provides a measure of internal doses of environmental chemicals or agents and allows for a more accurate measure of human health risk from these exposures. In these Alberta Biomonitoring Program datasets, information was collected as part of 3 province-wide studies investigating the serum levels of environmental chemicals (both natural and synthetic) in pregnant women in northern, central and southern Alberta (Phase 1), in children in southern Alberta (Phase 2), and maternal and umbilical cord blood samples from 7 Alberta cities (Phase 3). The goals of the program are to create a benchmark against which to track future exposures, provide a starting point for assessing health risks, indicate possible exposure sources and prioritize research efforts. Chemicals targeted for monitoring were selected using expert guidance and review of similar studies. For Phases 1 and 2, results for each chemical are presented in a single column, as either whole serum or lipid-adjusted concentrations. Each row provides the mean concentration and standard error of measurement for the replicate pools in the Age+Region group. Supplementary rows include the Limit of Detection/Limit of Quantification (LOD/LOQ) and Comments (for report status; results are only reported if ≥25% of pooled samples had detectable concentrations of a chemical). For Phase 3, results for each chemical are presented in up to 8 columns (age-weighted and age-and-geography-weighted means in whole serum and lipid-adjusted serum, and their 95% confidence intervals (CIs)). Each row provides the mean concentration and 95% CI for the replicate pools in the Age+Region group. Supplementary rows include the LOD/LOQ, Report Status (Yes: ≥25% of pooled samples had detectable concentrations; No: <25% had detectable concentrations) and Comments. For more information, please consult the Phase 1 and 2 reports (https://open.alberta.ca/publications/9780778566953; https://open.alberta.ca/publications/9780778582786).

The attached zip file contains all of the source data, intermediate outputs and R-scripts used to calculate the tipping points reported in the Frank et al manuscript. This dataset is associated with the following publication: Christopher, F., J. Brown, K. Wallace, J. Wambaugh, I. Shah, and T. Shafer. Defining toxicological tipping points in neuronal network development. TOXICOLOGY AND APPLIED PHARMACOLOGY. Academic Press Incorporated, Orlando, FL, USA, 354: 81-93, (2018).

Data in each figure of the publication are provided in different tabs of the excel spreadsheet. There were multiple concentrations tested, which are listed in the rows of the sheet. Each column is a different replicate. This dataset is associated with the following publication: Saavedra, L., K. Wallace, T. Freudenrich, M. Mall, W. Mundy, J. Davila, T. Shafer, M. Wernig, and D. Haag. Comparison of Acute Effects of Neurotoxic Compounds on Network Activity in Human and Rodent Neural Cultures. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 180(2): 295-312, (2021).

Code for analysis of NHANES data. This dataset is associated with the following publication: Wells, E., L. Kopylev, R. Nachman, E. Radke-Farabaugh, and D. Segal. Seafood, wine, rice, vegetables, and other food items associated with mercury biomarkers among seafood and non-seafood consumers: NHANES 2011–2012. Journal of Exposure Science and Environmental Epidemiology. Nature Publishing Group, London, UK, 1-11, (2020).

Biocrates metabolomics data for cerebrospinal fluid, serum, plasma, and urine from rats dosed with trimethyl tin at 2, 6, 10, or 14 days after treatmetn. This dataset is associated with the following publication: Imam, S., Z. He, E. Cuevas, H. Rosas-Hernandez, S. Lantz, S. Sarkar, J. Raymick, B. Robinson, J. Hanig, D. Herr, D. MacMillan, A. Smith, S. Liachenko, S. Ferguson, J. O'Callaghan, D. Miller, C. Somps, I. Pardo, W. Slikker, J. Pierson, R. Roberts, B. Gong, W. Tong, M. Aschner, M.J. Kallman, D. Calligaro, and M. Paule. Changes in the metabolome and microRNA levels in biological fluids might represent biomarkers of neurotoxicity: A trimethyltin study. Experimental Biology and Medicine. SAGE Publications, THOUSAND OAKS, CA, USA, 243(3): 228-236, (2018).

This is STATA software code for analysis on publicly available NHANES data