MetaMap is a highly configurable application developed by the Lister Hill National Center for Biomedical Communications at the National Library of Medicine (NLM) to map biomedical text to the UMLS Metathesaurus or, equivalently, to identify Metathesaurus concepts referred to in English text. MetaMap employs a knowledge-intensive approach, natural-language processing (NLP), and computational-linguistic techniques, and is used worldwide in industry and academia. At NLM, MetaMap is one of the foundations of NLM's Medical Text Indexer (MTI), which is applied to both semiautomatic and fully automatic indexing of biomedical literature. Technical documentation at http://metamap.nlm.nih.gov/#Downloads

The Github Repository, https://github.com/jodhernandezbe/TRI4PLADS/tree/v1.0.0,, is publicly available and referenced in supplementary information. This GitHub repository describes the computational framework overview, software requirements, model use, model output, and disclaimer. This repository presents a multi-scale framework that combines data engineering with process systems engineering (PSE) to enhance the precision of chemical flow analysis (CFA) at the end-of-life (EoL) stage. The focus is on chemicals used in plastic manufacturing, tracing their flows through the supply chain and EoL pathways. Additionally, this study examines potential discharges from material recovery facilities to publicly owned treatment works (POTW) facilities, recognizing their relevance to human and environmental health. Tracking these discharges is critical, as industrial EoL material transfers to POTWs can interfere with biological treatment processes, leading to unintended environmental chemical releases. By integrating data-driven methodologies with mechanistic modeling, this framework supports the identification, quantification, and regulatory assessment of chemical discharges, providing a science-based foundation for industrial and policy decision-making in sustainable material and water management. The attached file CoU - Metadata File.xlsx contains the datasets to build Figure 3 and describe a qualitative flow diagram of methyl methacrylate from manufacturing to potential consumer products generated from the Chemical Conditions of Use Locator methodology (https://doi.org/10.1111/jiec.13626). The attached file "MMA POTW Dataset.xlsx" contains the datasets needed to run the Chemical Tracker and Exposure Assessor in Publicly Owned Treatment Works Model (ChemTEAPOTW) as described in the Github Repository https://github.com/gruizmer/ChemTEAPOTW. The attached file "Plastic Data-Calculations-Assumptions.docx" contains all calculations and assumption to estimate the methyl methacrylate (MMA) releases from plastic recycling. Finally, users can generate Figures 4 and 5 after following the step-by-step process described in main Github repository for the MMA case study. This dataset is associated with the following publication: Hernandez-Betancur, J.D., J.D. Chea, D. Perez, and G.J. Ruiz-Mercado. Integrating data engineering and process systems engineering for end-of-life chemical flow analysis. COMPUTERS AND CHEMICAL ENGINEERING. Elsevier Science Ltd, New York, NY, USA, 204: 109414, (2026).

Dataset includes the SRA accessions of the sequencing data used to benchmark the MetaCompare 2.0 pipeline as well as tables of bacterial taxa and antibiotic resistance genes used to perform the risk assessments. A link to the GitHub page where the pipeline source code can be found is also provided. This dataset is associated with the following publication: Rumi, M., M. Oh, B. Davis, C. Brown, J. Adeesh, P. Vikesland, A. Pruden, and L. Zhang. MetaCompare 2.0: Differential ranking of ecological and human health resistome risks. FEMS Microbiology Ecology. Oxford University Press, OXFORD, UK, 100(12): fiae155, (2024).

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