Publications by authors named "Todd Martin"

The rapid increase of publicly available chemical structures and associated experimental data presents a valuable opportunity to build robust QSAR models for applications in different fields. However, the common concern is the quality of both the chemical structure information and associated experimental data. This is especially true when those data are collected from multiple sources as chemical substance mappings can contain many duplicate structures and molecular inconsistencies.

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One type of firefighting foam, referred to as aqueous filmforming foams (AFFF), is known to contain per- and polyfluoroalkyl substances (PFAS). The concerns raised with PFAS, and their potential environmental and health impacts, have led to a surge in research on fluorine-free alternatives both in the United States and globally. Particularly, in January 2023, a new military specification (MIL-PRF-32725) for fluorine-free foam was released in accordance with Congressional requirements for the U.

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The need for careful assembly, training, and validation of quantitative structure-activity/property models (QSAR/QSPR) is more significant than ever as data sets become larger and sophisticated machine learning tools become increasingly ubiquitous and accessible to the scientific community. Regulatory agencies such as the United States Environmental Protection Agency must carefully scrutinize each aspect of a resulting QSAR/QSPR model to determine its potential use in environmental exposure and hazard assessment. Herein, we revisit the goals of the Organisation for Economic Cooperation and Development (OECD) in our application and discuss the validation principles for structure-activity models.

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A solvent has many different types of impact on the environment. This article describes a method that combines several different types of impacts together into one environmental index so that similar solvents may be compared by their cumulative impact to the environment. The software tool PARIS III (Program for Assisting the Replacement of Industrial Solvents III) initially finds thousands of solvents mixtures with behaviors as close as possible to those of the original solvent entered.

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The release of persistent per- and polyfluoroalkyl substances (PFAS) into the environment is a major concern for the United States Environmental Protection Agency (U.S. EPA).

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"Green" pyrotechnics seek to remove known environmental pollutants and health hazards from their formulations. This chemical engineering approach often focuses on maintaining performance effects upon replacement of objectionable ingredients, yet neglects the chemical products formed by the exothermic reaction. In this work, milligram quantities of a lab-scale pyrotechnic red smoke composition were functioned within a thermal probe for product identification by pyrolysis-gas chromatography-mass spectrometry.

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Regulatory agencies world-wide face the challenge of performing risk-based prioritization of thousands of substances in commerce. In this study, a major effort was undertaken to compile a large genotoxicity dataset (54,805 records for 9299 substances) from several public sources (e.g.

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Background: Humans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk management. However, it is cost- and time-prohibitive to evaluate all new and existing chemicals using traditional rodent acute toxicity tests.

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Comparative chemical hazard assessment, which compares hazards for several endpoints across several chemicals, can be used for a variety of purposes including alternatives assessment and the prioritization of chemicals for further assessment. A new framework was developed to compile and integrate chemical hazard data for several human health and ecotoxicity endpoints from public online sources including hazardous chemical lists, Globally Harmonized System hazard codes (H-codes) or hazard categories from government health agencies, experimental quantitative toxicity values, and predicted values using Quantitative Structure-Activity Relationship (QSAR) models. QSAR model predictions were obtained using EPA's Toxicity Estimation Software Tool.

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PARIS III (Program for Assisting the Replacement of Industrial Solvents III, Version 1.4.0) is a pollution prevention solvent substitution software tool used to find mixtures of solvents that are less harmful to the environment than the industrial solvents to be replaced.

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Background: Endocrine disrupting chemicals (EDCs) are xenobiotics that mimic the interaction of natural hormones and alter synthesis, transport, or metabolic pathways. The prospect of EDCs causing adverse health effects in humans and wildlife has led to the development of scientific and regulatory approaches for evaluating bioactivity. This need is being addressed using high-throughput screening (HTS) approaches and computational modeling.

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Groundwater in sub-Saharan Africa supports livelihoods and poverty alleviation, maintains vital ecosystems, and strongly influences terrestrial water and energy budgets. Yet the hydrological processes that govern groundwater recharge and sustainability-and their sensitivity to climatic variability-are poorly constrained. Given the absence of firm observational constraints, it remains to be seen whether model-based projections of decreased water resources in dry parts of the region are justified.

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Multiple mode of action (MOA) frameworks have been developed in aquatic ecotoxicology, mainly based on fish toxicity. These frameworks provide information on a key determinant of chemical toxicity, but the MOA categories and level of specificity remain unique to each of the classification schemes. The present study aimed to develop a consensus MOA assignment within EnviroTox, a curated in vivo aquatic toxicity database, based on the following MOA classification schemes: Verhaar (modified) framework, Assessment Tool for Evaluating Risk, Toxicity Estimation Software Tool, and OASIS.

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The evaluation of potential alternatives for chemicals of concern (CoC) requires an understanding of their potential human health and environmental impacts during the manufacture, use, recycle and disposal life stages. During the manufacturing phase, the processes used to produce a desired chemical are defined based on the sequence of chemical reactions and unit operations required to produce the molecule and separate it from other materials used or produced during its manufacture. This paper introduces and demonstrates a tool that links a chemical's structure to information about its synthesis route and the manufacturing process for that chemical.

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The U.S. Environmental Protection Agency (EPA) is faced with the challenge of efficiently and credibly evaluating chemical safety often with limited or no available toxicity data.

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The goal of alternatives assessment (AA) is to facilitate a comparison of alternatives to a chemical of concern, resulting in the identification of safer alternatives. A two stage methodology for comparing chemical alternatives was developed. In the first stage, alternatives are compared using a variety of human health effects, ecotoxicity, and physicochemical properties.

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The mode of toxic action (MoA) has been recognized as a key determinant of chemical toxicity, but development of predictive MoA classification models in aquatic toxicology has been limited. We developed a Bayesian network model to classify aquatic toxicity MoA using a recently published dataset containing over one thousand chemicals with MoA assignments for aquatic animal toxicity. Two dimensional theoretical chemical descriptors were generated for each chemical using the Toxicity Estimation Software Tool.

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Background/aims: Clinical benefits of percutaneous treatment of renal artery stenosis (RAS) remain controversial. The aim of this study was to evaluate the effects of renal artery stenting on kidney function and blood pressure (BP) control in the log-term follow-up. Additionally angiographic follow up was performed in selected subgroup of patients.

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The ability to determine the mode of action (MOA) for a diverse group of chemicals is a critical part of ecological risk assessment and chemical regulation. However, existing MOA assignment approaches in ecotoxicology have been limited to a relatively few MOAs, have high uncertainty, or rely on professional judgment. In this study, machine based learning algorithms (linear discriminant analysis and random forest) were used to develop models for assigning aquatic toxicity MOA.

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Using a dataset with more than 6000 compounds, the performance of eight quantitative structure activity relationships (QSAR) models was evaluated: ACD/Tox Suite, Absorption, Distribution, Metabolism, Elimination, and Toxicity of chemical substances (ADMET) predictor, Derek, Toxicity Estimation Software Tool (T.E.S.

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Leading QSAR models provide supporting documentation in addition to a predicted toxicological value. Such information enables the toxicologist to explore the properties of chemical substances as well as to review and to increase the reliability of toxicity predictions. This article focuses on the use of this information in practice.

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