Liquid-chromatography-mass spectrometry (LC-MS) raw data sets from various instruments delivered in their native instrument format. 31 files in all. 7.5 GB data.

The experimental metabolomics data generated during the current study are available in the MetaboLights repository under the identifier MTBLS8274. Portions of this dataset are inaccessible because: L:\Priv\Metabolomics. They can be accessed through the following means: L:\Priv\Metabolomics. Format: L:\Priv\Metabolomics. This dataset is associated with the following publication: Viant, M., E. Amstalden, T. Athersuch, M. Bouhifd, S. Camuzeaux, D. Crizer, P. Driemert, T. Ebbels, D. Ekman, B. Flick, V. Giri, M. G?mez-Romero, V. Haake, M. Herold, A. Kende, F. Lai, P. Leonards, P. Lim, G. Lloyd, J. Mosley, C. Namini, J. Rice, S. Romano, C. Sands, M. Smith, T. Sobansky, A. Southam, L. Swindale, B. van Ravenzwaay, T. Walk, R. Weber, F. Zickgraf, and H. Kamp. Demonstrating the reliability of in vivo metabolomics based chemical grouping: towards best practice. Archives of Toxicology. Springer, New York, NY, USA, 98: 1111-1123, (2024).

GC-MS chromatograms from chamber and field studies were generated in this study. This dataset is associated with the following publication: Jaoui, M., R. Szmigielski, K. Nestorowicz, A. Kolodziejczyk, K. Sarang, K.J. Rudzinski, A. Konopka, T. Kleindienst, E. Bulska, and M. Lewandowski. Organic Hydroxy Acids as Highly Oxygenated Molecular (HOM) Tracers for Aged Isoprene Aerosol. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 53(24): 14516-14527, (2019).

GC-MS chromatograms from chamber and field studies were generated in this study. This dataset is associated with the following publication: Jaoui, M., R. Szmigielski, K. Nestorowicz, A. Kolodziejczyk, K. Sarang, K.J. Rudzinski, A. Konopka, T. Kleindienst, E. Bulska, and M. Lewandowski. Organic Hydroxy Acids as Highly Oxygenated Molecular (HOM) Tracers for Aged Isoprene Aerosol. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 53(24): 14516-14527, (2019).

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).

The file contains three files in comma separated values (.csv) format. “Reyes_EHP_Phthalates_US_metabolites.csv” contains information about the National Health and Nutrition Examination Survey (NHANES) metabolite code names along with Tolerable Daily Intake (TDI), molecular weight of the parent phthalate, molecular weight of the metabolite, and names and abbreviations of the corresponding metabolites and phthalates. “Reyes_EHP_Phthalates_US_MCR.csv” contains the following information: • Data on the surveyed individuals from the original NHANES data files that includes • Identifying information for individual; • Demographic information used in defining the creatinine levels and in investigating sub populations based on age, gender, ethnicity; • Concentration of phthalate metabolites and creatinine in urine. • Calculated values for each individual; • Daily intake of each of the six phthalate; • Hazard Quotients associated with each phthalate’s daily intake; • Values of Hazard Index and the Maximum Cumulative Ratio. “Reyes_EHP_Phthalates_US_MCR_definitions.csv” and the definitions and units of the fields in “Reyes_EHP_Phthalates_US_MCR.csv”. This dataset is associated with the following publication: Reyes, J., and P. Price. An analysis of cumulative risks based on biomonitoring data for six phthalates using the Maximum Cumulative Ratio. ENVIRONMENT INTERNATIONAL. Elsevier B.V., Amsterdam, NETHERLANDS, 112: 77-84, (2018).

The file contains three files in comma separated values (.csv) format. “Reyes_EHP_Phthalates_US_metabolites.csv” contains information about the National Health and Nutrition Examination Survey (NHANES) metabolite code names along with Tolerable Daily Intake (TDI), molecular weight of the parent phthalate, molecular weight of the metabolite, and names and abbreviations of the corresponding metabolites and phthalates. “Reyes_EHP_Phthalates_US_MCR.csv” contains the following information: • Data on the surveyed individuals from the original NHANES data files that includes • Identifying information for individual; • Demographic information used in defining the creatinine levels and in investigating sub populations based on age, gender, ethnicity; • Concentration of phthalate metabolites and creatinine in urine. • Calculated values for each individual; • Daily intake of each of the six phthalate; • Hazard Quotients associated with each phthalate’s daily intake; • Values of Hazard Index and the Maximum Cumulative Ratio. “Reyes_EHP_Phthalates_US_MCR_definitions.csv” and the definitions and units of the fields in “Reyes_EHP_Phthalates_US_MCR.csv”. This dataset is associated with the following publication: Reyes, J., and P. Price. An analysis of cumulative risks based on biomonitoring data for six phthalates using the Maximum Cumulative Ratio. ENVIRONMENT INTERNATIONAL. Elsevier B.V., Amsterdam, NETHERLANDS, 112: 77-84, (2018).

Dataset consists of 2 main files as follows: 1. All main and Supplemental MS final figures used for manuscript preparation for better viewing (pdf file). Figures are copies of raw or analyzed data directly from the mass spectrometers experimental files generated during research. Explanation of figures is provided in manuscript's text 2. Xcel file (Mass calculator CPK metabolites original), containing a significant amount of MS raw data obtained during the research for parent chemicals and metabolites. Emphasis was provided to the analyses of CPK metabolites. The file contains an Index page stating the content of each sheet. Because CPK metabolites were labelled differently as the research progressed, a Legend with the different labeling of each metabolite is presented on each sheet. This dataset is associated with the following publication: Kolanczyk, R., J. Serrano, M. Tapper, and P. Schmieder. A comparison of fish pesticide metabolic pathways with those of the rat and goat. REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, USA, 94: 124-143, (2018).

Dataset consists of 2 main files as follows: 1. All main and Supplemental MS final figures used for manuscript preparation for better viewing (pdf file). Figures are copies of raw or analyzed data directly from the mass spectrometers experimental files generated during research. Explanation of figures is provided in manuscript's text 2. Xcel file (Mass calculator CPK metabolites original), containing a significant amount of MS raw data obtained during the research for parent chemicals and metabolites. Emphasis was provided to the analyses of CPK metabolites. The file contains an Index page stating the content of each sheet. Because CPK metabolites were labelled differently as the research progressed, a Legend with the different labeling of each metabolite is presented on each sheet. This dataset is associated with the following publication: Kolanczyk, R., J. Serrano, M. Tapper, and P. Schmieder. A comparison of fish pesticide metabolic pathways with those of the rat and goat. REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, USA, 94: 124-143, (2018).

The data, source code and scripts included in this dataset are used to generate the results presented in the manuscript "The min-max test: an objective method for discriminating mass spectra" by Moorthy and Sisco. The manuscript explores a new method for objectively discriminating electron ionization mass spectra, a task that is commonplace when compounds are closely eluting in gas chromatography mass spectrometry. The C++ source codes and R analysis scripts can be extended for other application areas.