AIMC Topic: Toxicity Tests

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The way to cover prediction for cytotoxicity for all existing nano-sized metal oxides by using neural network method.

Nanotoxicology
The regulatory agencies should fulfil the data gap in toxicity for new chemicals including nano-sized compounds, like metal oxides nanoparticles (MeO NPs) according to the registration, evaluation, authorisation and restriction of chemicals (REACH) l...

Toward a systematic exploration of nano-bio interactions.

Toxicology and applied pharmacology
Many studies of nanomaterials make non-systematic alterations of nanoparticle physicochemical properties. Given the immense size of the property space for nanomaterials, such approaches are not very useful in elucidating fundamental relationships bet...

Anticancer activity of biologically synthesized silver and gold nanoparticles on mouse myoblast cancer cells and their toxicity against embryonic zebrafish.

Materials science & engineering. C, Materials for biological applications
The aim of this study was to evaluate the anticancer activity of bioinspired silver nanoparticles (AgNPs) and gold nanoparticles (AuNPs) against mouse myoblast cancer cells (CC). Both AgNPs and AuNPs were biologically synthesized using Spinacia olera...

Robust modelling of acute toxicity towards fathead minnow (Pimephales promelas) using counter-propagation artificial neural networks and genetic algorithm.

SAR and QSAR in environmental research
Large worldwide use of chemicals has caused great concern about their possible adverse effects on human health, flora and fauna. Increased production of new chemicals has also increased demand for their risk assessment. Traditionally, results from an...

Cytotoxicity of chitosan/streptokinase nanoparticles as a function of size: An artificial neural networks study.

Nanomedicine : nanotechnology, biology, and medicine
Predicting the size and toxicity of chitosan/streptokinase nanoparticles at various values of processing parameters was the aim of this study. For the first time, a comprehensive model could be developed to determine the cytotoxicity of the nanoparti...

Probabilistic hazard assessment for skin sensitization potency by dose-response modeling using feature elimination instead of quantitative structure-activity relationships.

Journal of applied toxicology : JAT
Supervised learning methods promise to improve integrated testing strategies (ITS), but must be adjusted to handle high dimensionality and dose-response data. ITS approaches are currently fueled by the increasing mechanistic understanding of adverse ...

The potential of AOP networks for reproductive and developmental toxicity assay development.

Reproductive toxicology (Elmsford, N.Y.)
Historically, the prediction of reproductive and developmental toxicity has largely relied on the use of animals. The adverse outcome pathway (AOP) framework forms a basis for the development of new non-animal test methods. It also provides biologica...

Machine learning-driven prediction of eye irritation toxicity: Integration of in silico and in vitro study.

Toxicology and applied pharmacology
Eye irritation (EI) toxicity poses critical challenges in chemical safety assessment, demanding alternatives to ethically contentious animal testing. We present the first integrative framework combining computational prediction with experimental vali...

Predicting in vitro assays related to liver function using probabilistic machine learning.

Toxicology
While machine learning has gained traction in toxicological assessments, the limited data availability requires the quantification of uncertainty of in silico predictions for reliable decision-making. This study addresses the challenge of predicting ...

Artificial intelligence (AI)-driven morphological assessment of zebrafish larvae for developmental toxicity chemical screening.

Aquatic toxicology (Amsterdam, Netherlands)
Screening chemicals using the zebrafish embryo developmental toxicity assay requires visual assessment of larval morphological changes based on images by experienced screeners. The process is time-consuming and prone to subjectivity. However, deep le...