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Application of transfer learning to predict drug-induced human in vivo gene expression changes using rat in vitro and in vivo data.

PloS one
The liver is the primary site for the metabolism and detoxification of many compounds, including pharmaceuticals. Consequently, it is also the primary location for many adverse reactions. As the liver is not readily accessible for sampling in humans;...

Automatic segmentation of the interscapular brown adipose tissue in rats based on deep learning using the dynamic magnetic resonance fat fraction images.

Magma (New York, N.Y.)
OBJECTIVE: The study aims to propose an accurate labelling method of interscapular BAT (iBAT) in rats using dynamic MR fat fraction (FF) images with noradrenaline (NE) stimulation and then develop an automatic iBAT segmentation method using a U-Net m...

What is the impact of intraperitoneal surfactant administration against postoperative intraabdominal adhesion formation? an experimental study.

Turkish journal of medical sciences
BACKGROUND/AIM: Surfactant is a surface-active substance that, in addition to its detergent effect, also has effects that reduce inflammation and fibrosis. Because of these effects, it was aimed herein to investigate the effect of intraperitoneal sur...

Utilizing deep learning techniques to improve image quality and noise reduction in preclinical low-dose PET images in the sinogram domain.

Medical physics
BACKGROUND: Low-dose positron emission tomography (LD-PET) imaging is commonly employed in preclinical research to minimize radiation exposure to animal subjects. However, LD-PET images often exhibit poor quality and high noise levels due to the low ...

A systematic review of the development and application of home cage monitoring in laboratory mice and rats.

BMC biology
BACKGROUND: Traditionally, in biomedical animal research, laboratory rodents are individually examined in test apparatuses outside of their home cages at selected time points. However, the outcome of such tests can be influenced by various factors an...

Vascular persistence following precision micropuncture.

Microcirculation (New York, N.Y. : 1994)
OBJECTIVE: The success of engineered tissues continues to be limited by time to vascularization and perfusion. Recently, we described a simple microsurgical approach, termed micropuncture (MP), which could be used to rapidly vascularize an adjacently...

DeepMPSF: A Deep Learning Network for Predicting General Protein Phosphorylation Sites Based on Multiple Protein Sequence Features.

Journal of chemical information and modeling
Phosphorylation, as one of the most important post-translational modifications, plays a key role in various cellular physiological processes and disease occurrences. In recent years, computer technology has been gradually applied to the prediction of...

Application of multiple-finding segmentation utilizing Mask R-CNN-based deep learning in a rat model of drug-induced liver injury.

Scientific reports
Drug-induced liver injury (DILI) presents significant diagnostic challenges, and recently artificial intelligence-based deep learning technology has been used to predict various hepatic findings. In this study, we trained a set of Mask R-CNN-based de...

Discrimination of human and animal bloodstains using hyperspectral imaging.

Forensic science, medicine, and pathology
Blood is the most encountered type of biological evidence in violent crimes and contains pertinent information to a forensic investigation. The false presumption that blood encountered at a crime scene is human may not be realised until after costly ...