AIMC Topic: Toxicity Tests

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Deep Learning-Enabled Unbiased Precision Toxicity Assessment of Zebrafish Organ Development.

Environmental science & technology
Precise assessment of toxicological effects remains a key bottleneck in biomedical and environmental health assessments. Traditional toxicology relies on macroscopic end points and manual image analysis, which limit sensitivity to structural damage a...

In vitro test battery for testing molecular initiating events in chemical-induced cholestasis.

Toxicology
Cholestatic liver injury is a complex adversity leading to the toxic accumulation of.noxious bile salts in the liver and systemic circulation. Cholestasis can be instigated by a plethora of chemicals originating from several applicability domains. Cu...

Multimodal deep learning for chemical toxicity prediction and management.

Scientific reports
The accurate prediction of chemical toxicity is a crucial research focus in chemistry, biotechnology, and national defense. The development of comprehensive datasets for chemical toxicity prediction remains limited due to security constraints and the...

TabNet and TabTransformer: Novel Deep Learning Models for Chemical Toxicity Prediction in Comparison With Machine Learning.

Journal of applied toxicology : JAT
The prediction of chemical toxicity is crucial for applications in drug discovery, environmental safety, and regulatory assessments. This study aims to evaluate the performance of advanced deep learning architectures, TabNet and TabTransformer, in co...

Model-driven high-throughput zebrafish embryo assay for evaluating whole effluent toxicity variation across 100 full-scale wastewater treatment plants.

Water research
The zebrafish embryo is a valuable model for evaluating whole effluent toxicity (WET). However, the widely recognized acute toxicity indicator, based on International Organization of Standardization (ISO) methods, requires large numbers of embryos an...

Classification and regression machine learning models for predicting mixed toxicity of carbamazepine and its transformation products.

Environmental research
Carbamazepine (CBZ) and its transformation products (TPs) often occur in aquatic environments in the form of mixtures, posing potential risks to ecosystems. However, establishing standardized protocols for synthesizing, isolating, and acquiring these...

Chemical Space Networks Enhance Toxicity Recognition via Graph Embedding.

Journal of chemical information and modeling
Chemical space networks (CSNs) are a new effective strategy for detecting latent chemical patterns irrespective of defined coordinate systems based on molecular descriptors and fingerprints. CSNs can be a new powerful option as a new approach method ...

Quantitative prediction of toxicological points of departure using two-stage machine learning models: A new approach methodology (NAM) for chemical risk assessment.

Journal of hazardous materials
Point of departure (POD) is a concept used in risk assessment to calculate the reference dose of exposure that is likely to have no appreciable risk on health. POD can be directly utilized from no observed adverse effect levels (NOAEL) which is the d...

Machine learning-based analysis of microfluidic device immobilized C. elegans for automated developmental toxicity testing.

Scientific reports
Developmental toxicity (DevTox) tests evaluate the adverse effects of chemical exposures on an organism's development. Although current testing primarily relies on large mammalian models, the emergence of new approach methodologies (NAMs) is encourag...

NeuTox 2.0: A hybrid deep learning architecture for screening potential neurotoxicity of chemicals based on multimodal feature fusion.

Environment international
Chemically induced neurotoxicity is a critical aspect of chemical safety assessment. Traditional and costly experimental methods call for the development of high-throughput virtual screening. However, the small datasets of neurotoxicity have limited ...