AIMC Topic: Toxicity Tests, Acute

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Deep Learning-Based Multimodal Fusion Approach for Predicting Acute Dermal Toxicity.

Journal of chemical information and modeling Jul 18, 2025
Acute dermal toxicity testing is essential for assessing the safety of chemicals used in pharmaceuticals, pesticides, cosmetics, and industrial chemicals. Conventional toxicity testing methods rely significantly on animal tests, which are resource-in...
Rats Neural Networks, Computer Skin Animals Toxicity Tests, Acute Deep Learning
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ToxACoL: an endpoint-aware and task-focused compound representation learning paradigm for acute toxicity assessment.

Nature communications Jul 1, 2025
Multi-species acute toxicity assessment forms the basis for chemical classification, labelling and risk management. Existing deep learning methods struggle with diverse experimental conditions, imbalanced data, and scarce target data, hindering their...
Humans Machine Learning Animals Deep Learning Toxicity Tests, Acute
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Toxicological evaluation of Artocarpus lacucha ethyl acetate extract: in vitro and in vivo assessment.

Journal of ethnopharmacology Apr 12, 2025
ETHNOPHARMACOLOGICAL RELEVANCE: Artocarpus lacucha Buch. -Ham. (syn. Artocarpus lakoocha) (A. lacucha), is a tropical fruit tree and a member of the Moraceae family. Fruit, bark, foliage, and roots of A. lacucha are broadly utilized in folklore medic...
HEK293 Cells Toxicity Tests, Acute Animals Humans Artocarpus Rats Male Plant Bark Female Plant Extracts Dose-Response Relationship, Drug Acetates Cell Survival Solvents
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First report on Quantitative Structure-Toxicity Relationship modeling approaches for the prediction of acute toxicity of various organic chemicals against rotifer species.

The Science of the total environment Apr 10, 2025
Nowadays, organic chemicals are crucial components in virtually every aspect of daily life, serving as indispensable elements for modern society. The ongoing synthesis of chemicals and the various potential harmful effects on living organisms are pro...
Machine Learning Animals Toxicity Tests, Acute Linear Models Rotifera Quantitative Structure-Activity Relationship Organic Chemicals Water Pollutants, Chemical
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Safety assessment of the ethanolic extract of Siparuna guianensis: Cell viability, molecular risk predictions and toxicity risk for acute and sub-chronic oral ingestion.

Journal of ethnopharmacology Apr 5, 2025
ETHNOPHARMACOLOGICAL RELEVANCE: The species Siparuna guianensis Aublet (family Siparunaceae) is traditionally used by indigenous peoples and riverine communities in Central and South America to treat migraines, flu, respiratory diseases, fever, pain,...
Lethal Dose 50 Toxicity Tests, Acute Toxicity Tests, Subchronic Plant Leaves Administration, Oral Solvents Female Dose-Response Relationship, Drug Animals Male Cell Survival Rats, Wistar Risk Assessment Rats Mice Ethanol Plant Extracts
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Prediction of acute toxicity of organic contaminants to fish: Model development and a novel approach to identify reactive substructures.

Journal of hazardous materials Mar 12, 2025
In this study, count-based Morgan fingerprints (CMF) were employed to represent the fundamental chemical structures of contaminants, and a neural network model (R² = 0.76) was developed to predict acute fish toxicity (AFT) of organic compounds. Model...
Water Pollutants, Chemical Neural Networks, Computer Fishes Animals Toxicity Tests, Acute Organic Chemicals
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Explainable machine learning models for predicting the acute toxicity of pesticides to sheepshead minnow (Cyprinodon variegatus).

The Science of the total environment Nov 16, 2024
A quantitative structure-activity relationship (QSAR) study was conducted on 313 pesticides to predict their acute toxicity to Sheepshead minnow (Cyprinodon variegatus) by using DRAGON descriptors. Essentials accounting for a reliable model were all ...
Quantitative Structure-Activity Relationship Toxicity Tests, Acute Killifishes Water Pollutants, Chemical Pesticides Machine Learning Animals Support Vector Machine
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Using the super-learner to predict the chemical acute toxicity on rats.

Journal of hazardous materials Oct 28, 2024
With the rapid increase in the number of commercial chemicals, testing methods regarding on median lethal dose (LD) relying animal experiments face challenges such as high costs and ethical concerns. Classical quantitative structure-activity relation...
Toxicity Tests, Acute Machine Learning Algorithms Animals Rats Quantitative Structure-Activity Relationship Lethal Dose 50
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High-throughput prediction of oral acute toxicity in Rat and Mouse of over 100,000 polychlorinated persistent organic pollutants (PC-POPs) by interpretable data fusion-driven machine learning global models.

Journal of hazardous materials Oct 28, 2024
This study utilized available oral acute toxicity data in Rat and Mouse for polychlorinated persistent organic pollutants (PC-POPs) to construct data fusion-driven machine learning (ML) global models. Based on atom-centered fragments (ACFs), the coll...
Mice Rats Administration, Oral Machine Learning Animals Persistent Organic Pollutants High-Throughput Screening Assays Hydrocarbons, Chlorinated Toxicity Tests, Acute
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A comprehensive prediction system for silkworm acute toxicity assessment of environmental and in-silico pesticides.

Ecotoxicology and environmental safety Jul 18, 2024
The excessive application and loss of pesticides poses a great risk to the ecosystem, and the environmental safety assessment of pesticides is time-consuming and expensive using traditional animal toxicity tests. In this work, a pesticide acute toxic...
Machine Learning Lethal Dose 50 Bayes Theorem Animals Toxicity Tests, Acute Algorithms Bombyx Risk Assessment Computer Simulation Environmental Pollutants China Pesticides
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