To determine nephron specificity of microRNA expression that may be associated as toxicity biomarker seen in the urine, laser-capture microdissection (LCM) was performed on the 4 major segment of the nephron in control rat samples. These samples were sent to Bayer for candidate digital drop PCR measurements, NIEHS for smallRNA-seq measurements, and Abcam for FirePlex measurements. smallRNA-seq measurements were used as global assessment of miRNA expression in these segments. FirePlex and ddPCR were used as medium to low number candidate assessments, respectively, of miRNA candidates, based on seq and urine data. "Data associated with Fig 4" summarizes the ddPCR findings. "Data Associated with Figure 5" and "Data Associated with Figure 6" summarize the smallRNA-seq findings. "Data Associated with Figure 7" summarize the FirePlex findings. "Data associated with Figure 8_9" summarize the correlations of these measurements. The cumlmination of these data determine nephron-specific and enriched expression of miRNAs, that are potential candidates of toxicity markers that could leak into the urine upon chemical exposure. This dataset is associated with the following publication: Chorley, B., H. Ellinger-Ziegelbauer, M. Tackett, F. Simutis, A. Harrill, J. McDuffie, E. Atabakhsh, R. Nassirpour, L. Whiteley, J. Léonard, G. Carswell, E. Harpur, C. Chen, and J. Gautier. Urinary miRNA Biomarkers of Drug-Induced Kidney Injury and Their Site Specificity Within the Nephron. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 180(1): 1-16, (2021).

Urine samples were derived from a variety of archived industry-led studies, outlined in the dataset. The purpose was to measure a targeted set of miRNA targets that were represented in the Thermo Fisher TLDA A and TLDA B card sets in Figure 2. These case studies were selected due to probable nephrotoxicity, associated with published or internal records. These clinical markers and histopath evidence was included in Table 1 associated dataset. Given specific nephron toxicity, this experiment would determine miRNA candidates that may be specific toxicity biomarkers. This analysis set up the Venn Analysis in Figure 3, which specified candidates for nephron-specific analyses. This dataset is associated with the following publication: Chorley, B., H. Ellinger-Ziegelbauer, M. Tackett, F. Simutis, A. Harrill, J. McDuffie, E. Atabakhsh, R. Nassirpour, L. Whiteley, J. Léonard, G. Carswell, E. Harpur, C. Chen, and J. Gautier. Urinary miRNA Biomarkers of Drug-Induced Kidney Injury and Their Site Specificity Within the Nephron. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 180(1): 1-16, (2021).

Urine samples were derived from a variety of archived industry-led studies, outlined in the dataset. The purpose was to measure a targeted set of miRNA targets that were represented in the Thermo Fisher TLDA A and TLDA B card sets in Figure 2. These case studies were selected due to probable nephrotoxicity, associated with published or internal records. These clinical markers and histopath evidence was included in Table 1 associated dataset. Given specific nephron toxicity, this experiment would determine miRNA candidates that may be specific toxicity biomarkers. This analysis set up the Venn Analysis in Figure 3, which specified candidates for nephron-specific analyses. This dataset is associated with the following publication: Chorley, B., H. Ellinger-Ziegelbauer, M. Tackett, F. Simutis, A. Harrill, J. McDuffie, E. Atabakhsh, R. Nassirpour, L. Whiteley, J. Léonard, G. Carswell, E. Harpur, C. Chen, and J. Gautier. Urinary miRNA Biomarkers of Drug-Induced Kidney Injury and Their Site Specificity Within the Nephron. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 180(1): 1-16, (2021).

For this study, EPA analyzed the miRNA PCR data that were used for Figures 4 and 5 of the data. The raw PCR data itself, which were not generated by EPA, are included as zipped RDML files. These data include amplification data for all miRNA targets and samples measured. Version 2 of these datasets have been updated to include new analyses (Mann Whitney U Test to include a non-parametric stat in response to reviews).

NASA s Rodent Research (RR) project is playing a critical role in advancing biomedical research on the physiological effects of space environments. Due to the limited resources for conducting biological experiments aboard the International Space Station (ISS) it is imperative to use crew time efficiently while maximizing high-quality science return. NASA s GeneLab project has as its primary objectives to 1) further increase the value of these experiments using a multi-omics systems biology-based approach and 2) disseminate these data without restrictions to the scientific community. The current investigation assessed viability of RNA DNA and protein extracted from archived RR-1 tissue samples for epigenomic transcriptomic and proteomic assays. During the first RR spaceflight experiment a variety of tissue types were harvested from subjects snap-frozen or RNAlater-preserved and then stored at least a year at -80C after return to Earth. They were then prioritized for this investigation based on likelihood of significant scientific value for spaceflight research. All tissues were made available to GeneLab through the bio-specimen sharing program managed by the Ames Life Science Data Archive and included mouse adrenal glands quadriceps gastrocnemius tibialis anterior extensor digitorum longus soleus eye and kidney. We report here protocols for and results of these tissue extractions and thus the feasibility and value of these kinds of omics analyses. In addition to providing additional opportunities for investigation of spaceflight effects on the mouse transcriptome and proteome in new kinds of tissues our results may also be of value to program managers for the prioritization of ISS crew time for rodent research activities.

This dataset contains the files, scripts and data that were used to run the simulations and data analyses for the manuscript. This dataset is associated with the following publication: Ball, K., C. Grant, W. Mundy, and T. Shafer. A multivariate extension of mutual information for growing neural networks.. Neural Networks. Elsevier B.V., Amsterdam, NETHERLANDS, 95: 29-43, (2017).

This dataset contains the files, scripts and data that were used to run the simulations and data analyses for the manuscript. This dataset is associated with the following publication: Ball, K., C. Grant, W. Mundy, and T. Shafer. A multivariate extension of mutual information for growing neural networks.. Neural Networks. Elsevier B.V., Amsterdam, NETHERLANDS, 95: 29-43, (2017).

This dataset is a project file generated by BMDExpress 2.2 SW (Sciome, Research Triangle Park, NC). It contains gene expression data for livers of rats exposed to 4 chemicals (crude MCHM, neat MCHM, DMPT, p-toluidine) and kidneys of rats exposed to PPH. The project file includes normalized expression data (GeneChip Rat 230 2.0 Array) using 7 different pre-processing methods (RMA, GCRMA, MAS5.0, MAS5.0_noA calls, PLIER, PLIER16, and PLIER16_noA calls); differentially expressed probe-sets detected by William's method (p<0.05, and minimum fold change of 1.5); probeset-level and pathway-level BMD and BMDL values from transcriptomic dose-response modeling. This dataset is associated with the following publication: Mezencev, R., and S. Auerbach. The sensitivity of transcriptomics BMD modeling to the methods used for microarray data normalization. PLOS ONE. Public Library of Science, San Francisco, CA, USA, 15(5): e0232955, (2020).