AIMC Topic: Mice

Clear Filters Showing 111 to 120 of 1565 articles

Light-microscopy-based connectomic reconstruction of mammalian brain tissue.

Nature
The information-processing capability of the brain's cellular network depends on the physical wiring pattern between neurons and their molecular and functional characteristics. Mapping neurons and resolving their individual synaptic connections can b...

Anti-drift pose tracker (ADPT), a transformer-based network for robust animal pose estimation cross-species.

eLife
Deep learning-based methods have advanced animal pose estimation, enhancing accuracy, and efficiency in quantifying animal behavior. However, these methods frequently experience tracking drift, where noise-induced jumps in body point estimates compro...

GBE1 alleviates MPTP-induced PD symptoms in mice by enhancing glycolysis and oxidative phosphorylation.

Brain research
In Parkinson's disease (PD), the disturbance of energy metabolism due to glucose metabolic reprogramming may be a critical factor contributing to neuronal degeneration and death. Glycolysis, as the core process of glucose metabolism, not only serves ...

Using artificial intelligence-based software for an unbiased discrimination of immune cell subtypes in the fracture hematoma and bone marrow of non-osteoporotic and osteoporotic mice.

PloS one
It is well established that the early inflammatory response following fracture is essential for initiating subsequent bone regeneration. An imbalance in inflammation, whether within the innate or adaptive immune response, can result in impaired fract...

Machine learning analysis of FOSL2 and RHoBTB1 as central immunological regulators in knee osteoarthritis synovium.

The Journal of international medical research
BackgroundKnee osteoarthritis is a debilitating disease with a complex pathogenesis. Synovitis, which refers to inflammation of the synovial membrane surrounding the joint, is believed to play an important role in the development and progression of k...

Automated detection and recognition of oocyte toxicity by fusion of latent and observable features.

Journal of hazardous materials
Oocyte quality is essential for successful pregnancy, yet no discriminant criterion exists to assess the effects of environmental pollutants on oocyte abnormalities. We developed a stepwise framework integrating deep learning-extracted latent feature...

Big data-driven target identification by machine learning: DRD2 as a therapeutic target for psoriasis.

Journal of dermatological science
BACKGROUND: The development of medical treatments has traditionally relied on researchers leveraging scientific knowledge to hypothesize disease mechanisms and identify therapeutic agents. However, the depletion of novel therapeutic targets has becom...

TransAnno-Net: A Deep Learning Framework for Accurate Cell Type Annotation of Mouse Lung Tissue Using Self-supervised Pretraining.

Computer methods and programs in biomedicine
BACKGROUND: Single-cell RNA sequencing (scRNA-seq) has become a significant tool for addressing complex issuess in the field of biology. In the context of scRNA-seq analysis, it is imperative to accurately determine the type of each cell. However, co...

Identification and verification of mitochondria-related genes biomarkers associated with immune infiltration for COPD using WGCNA and machine learning algorithms.

Scientific reports
Mitochondrial dysfunction plays a pivotal role in the pathogenesis of chronic obstructive pulmonary disease (COPD). This study combines bioinformatics analysis with machine learning to elucidate potential key mitochondrial-related genes associated wi...

Definer: A computational method for accurate identification of RNA pseudouridine sites based on deep learning.

PloS one
Pseudouridine is an important modification site, which is widely present in a variety of non-coding RNAs and is involved in a variety of important biological processes. Studies have shown that pseudouridine is important in many biological functions s...