AIMC Topic: Animals

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APOD: A biomarker associated with oxidative stress in acute rejection of kidney transplants based on multiple machine learning algorithms and animal experimental validation.

Transplant immunology
BACKGROUND: Oxidative stress is an unavoidable process in kidney transplantation and is closely related to the development of acute rejection after kidney transplantation. This study aimed to investigate the biomarkers associated with oxidative stres...

GraphPro: An interpretable graph neural network-based model for identifying promoters in multiple species.

Computers in biology and medicine
Promoters are DNA sequences that bind with RNA polymerase to initiate transcription, regulating this process through interactions with transcription factors. Accurate identification of promoters is crucial for understanding gene expression regulation...

Predicting the Hallucinogenic Potential of Molecules Using Artificial Intelligence.

ACS chemical neuroscience
The development of new drugs addressing serious mental health and other disorders should avoid the psychedelic experience. Analogs of psychedelic drugs can have clinical utility and are termed "psychoplastogens". These represent promising candidates ...

Biorobotic Drug Delivery for Biomedical Applications.

Molecules (Basel, Switzerland)
Despite extensive efforts, current drug-delivery systems face biological barriers and difficulties in bench-to-clinical use. Biomedical robotic systems have emerged as a new strategy for drug delivery because of their innovative diminutive engines. T...

AI-driven convolutional neural networks for accurate identification of yellow fever vectors.

Parasites & vectors
BACKGROUND: Identifying mosquito vectors is crucial for controlling diseases. Automated identification studies using the convolutional neural network (CNN) have been conducted for some urban mosquito vectors but not yet for sylvatic mosquito vectors ...

A competing risks machine learning study of neutron dose, fractionation, age, and sex effects on mortality in 21,000 mice.

Scientific reports
This study explores the impact of densely-ionizing radiation on non-cancer and cancer diseases, focusing on dose, fractionation, age, and sex effects. Using historical mortality data from approximately 21,000 mice exposed to fission neutrons, we empl...

Machine Learning Prediction of On/Off Target-driven Clinical Adverse Events.

Pharmaceutical research
OBJECTIVE: Currently, 90% of clinical drug development fails, where 30% of these failures are due to clinical toxicity. The current extensive animal toxicity studies are not predictive of clinical adverse events (AEs) at clinical doses, while current...

Explainable artificial intelligence for spectroscopy data: a review.

Pflugers Archiv : European journal of physiology
Explainable artificial intelligence (XAI) has gained significant attention in various domains, including natural and medical image analysis. However, its application in spectroscopy remains relatively unexplored. This systematic review aims to fill t...

Hydrogel-Based Artificial Synapses for Sustainable Neuromorphic Electronics.

Advanced materials (Deerfield Beach, Fla.)
Hydrogels find widespread applications in biomedicine because of their outstanding biocompatibility, biodegradability, and tunable material properties. Hydrogels can be chemically functionalized or reinforced to respond to physical or chemical stimul...

Machine Learning Allowed Interpreting Toxicity of a Fe-Doped CuO NM Library Large Data Set─An Environmental In Vivo Case Study.

ACS applied materials & interfaces
The wide variation of nanomaterial (NM) characters (size, shape, and properties) and the related impacts on living organisms make it virtually impossible to assess their safety; the need for modeling has been urged for long. We here investigate the c...