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DNA Damage

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Piperidine based 1,2,3-triazolylacetamide derivatives induce cell cycle arrest and apoptotic cell death in .

Journal of advanced research
The fungal pathogen , is a serious threat to public health and is associated with bloodstream infections causing high mortality particularly in patients with serious medical problems. As this pathogen is generally resistant to all the available clas...

Toxicity, genotoxicity, and carcinogenicity of 2-methylfuran in a 90-day comprehensive toxicity study in gpt delta rats.

Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association
2-Methylfuran (2-MF) exists naturally in foods and is used as a flavoring agent. Furan, the core structure of 2-MF, possesses hepatocarcinogenicity in rodents. Accumulation of toxicological information on furan derivatives is needed to elucidate thei...

Evaluation of genotoxicity after acute and chronic exposure to 2,4-dichlorophenoxyacetic acid herbicide (2,4-D) in rodents using machine learning algorithms.

The Journal of toxicological sciences
2,4-Dichlorophenoxyacetic acid (2,4-D) is one of the most widely used herbicides in the world, but its mutagenic and carcinogenic potential is still controversial. We simulated environmental exposure to 2,4-D, with the objective of evaluating the gen...

Machine learning guided prediction of liquid chromatography-mass spectrometry ionization efficiency for genotoxic impurities in pharmaceutical products.

Journal of pharmaceutical and biomedical analysis
The limitation and control of genotoxic impurities (GTIs) has continued to receive attention from pharmaceutical companies and authorities for several decades. Because GTIs have the ability to damage deoxyribonucleic acid (DNA) and the potential to c...

Machine learning uncovers independently regulated modules in the Bacillus subtilis transcriptome.

Nature communications
The transcriptional regulatory network (TRN) of Bacillus subtilis coordinates cellular functions of fundamental interest, including metabolism, biofilm formation, and sporulation. Here, we use unsupervised machine learning to modularize the transcrip...

Application of artificial intelligence for detection of chemico-biological interactions associated with oxidative stress and DNA damage.

Chemico-biological interactions
In recent years, various AI-based methods have been developed in order to uncover chemico-biological interactions associated with DNA damage and oxidative stress. Various decision trees, bayesian networks, random forests, logistic regression models, ...

Machine learning for sperm selection.

Nature reviews. Urology
Infertility rates and the number of couples seeking fertility care have increased worldwide over the past few decades. Over 2.5 million cycles of assisted reproductive technologies are being performed globally every year, but the success rate has rem...

Inter-laboratory automation of the in vitro micronucleus assay using imaging flow cytometry and deep learning.

Archives of toxicology
The in vitro micronucleus assay is a globally significant method for DNA damage quantification used for regulatory compound safety testing in addition to inter-individual monitoring of environmental, lifestyle and occupational factors. However, it re...

Prioritization of Mycotoxins Based on Their Genotoxic Potential with an In Silico-In Vitro Strategy.

Toxins
Humans are widely exposed to a great variety of mycotoxins and their mixtures. Therefore, it is important to design strategies that allow prioritizing mycotoxins based on their toxic potential in a time and cost-effective manner. A strategy combining...

An artificial neural network model based on DNA damage response genes to predict outcomes of lower-grade glioma patients.

Briefings in bioinformatics
Although the prognosis of lower-grade glioma (LGG) patients is better than others, outcomes are highly heterogeneous. Isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status can identify patient subsets with different prognosis. However,...