AIMC Topic: Rats
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Natural compounds for Alzheimer's prevention and treatment: Integrating SELFormer-based computational screening with experimental validation.
Computers in biology and medicine
Dec 9, 2024
BACKGROUND: This study aimed to develop and apply a novel computational pipeline combining SELFormer, a transformer architecture-based chemical language model, with advanced deep learning techniques to predict natural compounds (NCs) with potential i...
Assessing the effects of 5-HT and 5-HT receptor antagonists on DOI-induced head-twitch response in male rats using marker-less deep learning algorithms.
Pharmacological reports : PR
Nov 27, 2024
BACKGROUND: Serotonergic psychedelics, which display a high affinity and specificity for 5-HT receptors like 2,5-dimethoxy-4-iodoamphetamine (DOI), reliably induce a head-twitch response in rodents characterized by paroxysmal, high-frequency head rot...
Deep learning applied to the segmentation of rodent brain MRI data outperforms noisy ground truth on full-fledged brain atlases.
NeuroImage
Nov 26, 2024
Translational magnetic resonance imaging of the rodent brain provides invaluable information for preclinical drug development. However, the automated segmentation of such images for quantitative analyses is limited compared to human brain imaging mai...
Magnetic soft microrobots for erectile dysfunction therapy.
Proceedings of the National Academy of Sciences of the United States of America
Nov 18, 2024
Erectile dysfunction (ED) is a major threat to male fertility and quality of life, and mesenchymal stromal cells (MSCs) are a promising therapeutic option. However, therapeutic outcomes are compromised by low MSC retention and survival rates in corpu...
Comprehensive analysis and validation of TP73 as a biomarker for calcium oxalate nephrolithiasis using machine learning and in vivo and in vitro experiments.
Urolithiasis
Nov 16, 2024
Calcium oxalate (CaOx) nephrolithiasis constitutes approximately 75% of nephrolithiasis cases, resulting from the supersaturation and deposition of CaOx crystals in renal tissues. Despite their prevalence, precise biomarkers for CaOx nephrolithiasis ...
Deep learning algorithms reveal increased social activity in rats at the onset of the dark phase of the light/dark cycle.
PloS one
Nov 8, 2024
The rapid decrease of light intensity is a potent stimulus of rats' activity. The nature of this activity, including the character of social behavior and the composition of concomitant ultrasonic vocalizations (USVs), is unknown. Using deep learning ...
Estrogen-mediated modulation of sterile inflammatory markers and baroreflex sensitivity in ovariectomized female Wistar rats.
Archives of endocrinology and metabolism
Nov 6, 2024
OBJECTIVE: This study aims to explore the role of estrogen in providing cardioprotective benefits to premenopausal women, examining how hormonal differences between sexes influence the prevalence of cardiovascular diseases (CVDs) in women.
Characterization of Brain Abnormalities in Lactational Neurodevelopmental Poly I:C Rat Model of Schizophrenia and Depression Using Machine-Learning and Quantitative MRI.
Journal of magnetic resonance imaging : JMRI
Oct 28, 2024
BACKGROUND: A recent neurodevelopmental rat model, utilizing lactational exposure to polyriboinosinic-polyribocytidilic acid (Poly I:C) leads to mimics of behavioral phenotypes resembling schizophrenia-like symptoms in male offspring and depression-l...
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...
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...
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