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Toxicity Tests, Acute

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Toxicological evaluation of Artocarpus lacucha ethyl acetate extract: in vitro and in vivo assessment.

Journal of ethnopharmacology
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...

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
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,...

In silico prediction of chemical acute contact toxicity on honey bees via machine learning methods.

Toxicology in vitro : an international journal published in association with BIBRA
In recent years, the decline of honey bees and the collapse of bee colonies have caught the attention of ecologists, and the use of pesticides is one of the main reasons for the decline. Therefore, ecological risk assessment of pesticides is essentia...

Profiling mechanisms that drive acute oral toxicity in mammals and its prediction via machine learning.

Toxicological sciences : an official journal of the Society of Toxicology
We present a mechanistic machine-learning quantitative structure-activity relationship (QSAR) model to predict mammalian acute oral toxicity. We trained our model using a rat acute toxicity database compiled by the US National Toxicology Program. We ...

In Silico Prediction of Oral Acute Rodent Toxicity Using Consensus Machine Learning.

Journal of chemical information and modeling
Acute oral toxicity (AOT) is required for the classification and labeling of chemicals according to the global harmonized system (GHS). Acute oral toxicity studies are optimized to minimize the use of animals. However, with the advent of the three p...

A comprehensive prediction system for silkworm acute toxicity assessment of environmental and in-silico pesticides.

Ecotoxicology and environmental safety
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...

Explainable machine learning models for predicting the acute toxicity of pesticides to sheepshead minnow (Cyprinodon variegatus).

The Science of the total environment
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 ...

Using the super-learner to predict the chemical acute toxicity on rats.

Journal of hazardous materials
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...

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
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...