AIMC Topic: Xenobiotics

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Unveiling the effect of urinary xenoestrogens on chronic kidney disease in adults: A machine learning model.

Ecotoxicology and environmental safety Feb 22, 2025
Exposure to three primary xenoestrogens (XEs), including phthalates, parabens, and phenols, has been strongly associated with chronic kidney disease (CKD). An interpretable machine learning (ML) model was developed to predict CKD using data from the ...
Nutrition Surveys Renal Insufficiency, Chronic Phenols Middle Aged Estrogens Parabens Xenobiotics Triclosan Environmental Pollutants Phthalic Acids Humans Adult Machine Learning Male Female Aged
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Assessing chemical exposure risk in breastfeeding infants: An explainable machine learning model for human milk transfer prediction.

Ecotoxicology and environmental safety Jan 11, 2025
Breast milk is essential for infant health, but the transfer of xenobiotic chemicals poses significant risks. Ethical challenges in clinical trials necessitate the use of in vitro predictive models to assess chemical exposure risks in breastfeeding i...
Female Risk Assessment Infant Humans Machine Learning Breast Feeding Xenobiotics Milk, Human Environmental Exposure
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Harnessing machine learning to predict cytochrome P450 inhibition through molecular properties.

Archives of toxicology Apr 15, 2024
Cytochrome P450 enzymes are a superfamily of enzymes responsible for the metabolism of a variety of medicines and xenobiotics. Among the Cytochrome P450 family, five isozymes that include 1A2, 2C9, 2C19, 2D6, and 3A4 are most important for the metabo...
Xenobiotics Cytochrome P-450 Enzyme Inhibitors Isoenzymes Drug Interactions Cytochrome P-450 Enzyme System Machine Learning Support Vector Machine Humans
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Computational prediction of the metabolites of agrochemicals formed in rats.

The Science of the total environment Jun 22, 2023
Today, computational tools for the prediction of the metabolite structures of xenobiotics are widely available and employed in small-molecule research. Reflecting the availability of measured data, these in silico tools are trained and validated prim...
Agrochemicals Inactivation, Metabolic Animals Rats Xenobiotics Machine Learning
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GutBug: A Tool for Prediction of Human Gut Bacteria Mediated Biotransformation of Biotic and Xenobiotic Molecules Using Machine Learning.

Journal of molecular biology Mar 22, 2023
Dietary components and bioactive molecules present in functional foods and nutraceuticals provide various beneficial effects including modulation of host gut microbiome. These metabolites along with orally administered drugs can be potentially bio-tr...
Xenobiotics Machine Learning Humans Gastrointestinal Microbiome Pharmaceutical Preparations Bacteria Biotransformation
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Dietary Inhibitors of CYP3A4 Are Revealed Using Virtual Screening by Using a New Deep-Learning Classifier.

Journal of agricultural and food chemistry Feb 1, 2022
CYP3A4 is the main human enzyme responsible for phase I metabolism of dietary compounds, prescribed drugs and xenobiotics, steroid hormones, and bile acids. The inhibition of CYP3A4 activity might impair physiological mechanisms, including the endocr...
Humans Deep Learning Cytochrome P-450 CYP3A Inhibitors Enzyme Inhibitors Xenobiotics Cytochrome P-450 CYP3A
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CYPstrate: A Set of Machine Learning Models for the Accurate Classification of Cytochrome P450 Enzyme Substrates and Non-Substrates.

Molecules (Basel, Switzerland) Aug 2, 2021
The interaction of small organic molecules such as drugs, agrochemicals, and cosmetics with cytochrome P450 enzymes (CYPs) can lead to substantial changes in the bioavailability of active substances and hence consequences with respect to pharmacologi...
Cytochrome P-450 Enzyme System Substrate Specificity Xenobiotics Humans Machine Learning Animals
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Key Physicochemical Properties Dictating Gastrointestinal Bioaccessibility of Microplastics-Associated Organic Xenobiotics: Insights from a Deep Learning Approach.

Environmental science & technology Sep 25, 2020
A potential risk from human uptake of microplastics is the release of plastics-associated xenobiotics, but the key physicochemical properties of microplastics controlling this process are elusive. Here, we show that the gastrointestinal bioaccessibil...
Microplastics Xenobiotics Water Pollutants, Chemical Adsorption Humans Plastics Deep Learning
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GLORYx: Prediction of the Metabolites Resulting from Phase 1 and Phase 2 Biotransformations of Xenobiotics.

Chemical research in toxicology Aug 26, 2020
Predicting the structures of metabolites formed in humans can provide advantageous insights for the development of drugs and other compounds. Here we present GLORYx, which integrates machine learning-based site of metabolism (SoM) prediction with rea...
Biotransformation Toxicity Tests Xenobiotics Machine Learning Molecular Structure Humans
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Prediction of Farnesoid X Receptor Disruptors with Machine Learning Methods.

Chemical research in toxicology Nov 8, 2018
The farnesoid X receptor (FXR) emerges as a promising drug target involved in regulating various metabolic pathways, yet some xenobiotic compounds binding to FXR would be an important determinant to induce the receptor dysfunctions that lead to undes...
Area Under Curve Humans Xenobiotics Benzimidazoles Databases, Factual Machine Learning Receptors, Cytoplasmic and Nuclear ROC Curve
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