AIMC Topic: Endocrine Disruptors
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Machine Learning Consensus To Predict the Binding to the Androgen Receptor within the CoMPARA Project.
Journal of chemical information and modeling
Feb 11, 2019
The nuclear androgen receptor (AR) is one of the most relevant biological targets of Endocrine Disrupting Chemicals (EDCs), which produce adverse effects by interfering with hormonal regulation and endocrine system functioning. This paper describes n...
Machine learning models for predicting endocrine disruption potential of environmental chemicals.
Journal of environmental science and health. Part C, Environmental carcinogenesis & ecotoxicology reviews
Jan 10, 2019
We introduce here ML4Tox, a framework offering Deep Learning and Support Vector Machine models to predict agonist, antagonist, and binding activities of chemical compounds, in this case for the estrogen receptor ligand-binding domain. The ML4Tox mode...
Determination of 17 potential endocrine-disrupting chemicals in human saliva by dispersive liquid-liquid microextraction and liquid chromatography-tandem mass spectrometry.
Talanta
Dec 23, 2018
Endocrine-disrupting chemicals are a group of emerging contaminants that alters the function of the endocrine system, causing possible adverse health effects. In this study, a dispersive liquid-liquid microextraction method coupled with liquid chroma...
Maternal urinary paraben levels and offspring size at birth from a Chinese birth cohort.
Chemosphere
Dec 27, 2016
BACKGROUND: Parabens are suspected to impair fetal growth because of their endocrine disrupting effects. Epidemiological studies regarding the effects of prenatal exposure to parabens on birth outcomes are limited.
A ternary classification using machine learning methods of distinct estrogen receptor activities within a large collection of environmental chemicals.
The Science of the total environment
Dec 20, 2016
Endocrine-disrupting chemicals (EDCs), which can threaten ecological safety and be harmful to human beings, have been cause for wide concern. There is a high demand for efficient methodologies for evaluating potential EDCs in the environment. Herein ...
An automated high-throughput SPE micro-elution method for perfluoroalkyl substances in human serum.
Analytical and bioanalytical chemistry
Mar 21, 2015
An automated high-throughput solid phase extraction (SPE) micro-elution method for 8 perfluorosulfonic acids, 11 perfluorocarboxylic acids and fluorooctane sulfonamide in human serum was developed. Importance was attached to the application of small ...
A big data approach with artificial neural network and molecular similarity for chemical data mining and endocrine disruption prediction.
Indian journal of pharmacology
Jan 1, 2018
CONTEXT: Chemical toxicity prediction at early stage drug discovery phase has been researched for years, and newest methods are always investigated. Research data comprising chemical physicochemical properties, toxicity, assay, and activity details c...
The Association Between Bisphenol A and Polycystic Ovarian Syndrome: A Case-Control Study.
Acta medica Iranica
Dec 1, 2017
Polycystic ovarian syndrome (PCOS) is an endocrine metabolic disorder with unclear etiopathogenesis among reproductive age women. Evidences show genetic susceptibility and environmental factors were associated with PCOS. The aim of this study was to ...
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