AIMC Topic: Mice

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Unmasking Neuroendocrine Prostate Cancer with a Machine Learning-Driven Seven-Gene Stemness Signature That Predicts Progression.

International journal of molecular sciences
Prostate cancer (PCa) poses a significant global health challenge, particularly due to its progression into aggressive forms like neuroendocrine prostate cancer (NEPC). This study developed and validated a stemness-associated gene signature using adv...

Machine learning reveals prominent spontaneous behavioral changes and treatment efficacy in humanized and transgenic Alzheimer's disease models.

Cell reports
Computer-vision and machine-learning (ML) approaches are being developed to provide scalable, unbiased, and sensitive methods to assess mouse behavior. Here, we used the ML-based variational animal motion embedding (VAME) segmentation platform to ass...

A Novel Deep Learning Approach for Analyzing Glomerular Basement Membrane Lesions in a Mouse Model of X-Linked Alport Syndrome.

The American journal of pathology
Alport syndrome is a rare kidney disease typically more severe in males due to its X-linked inheritance. However, female patients with heterozygous X-linked Alport syndrome (XLAS) can develop renal failure over time, necessitating accurate pathologic...

"Dictionary of immune responses" reveals the critical role of monocytes and the core target IRF7 in intervertebral disc degeneration.

Frontiers in immunology
BACKGROUND: Intervertebral disc degeneration (IDD) is widely regarded as the primary contributor to low back pain(LBP). As an immune-privileged organ, upon the onset of IDD, various components of the nucleus pulposus (NP) are exposed to the host's im...

Identification of novel biomarkers for atherosclerosis using single-cell RNA sequencing and machine learning.

Mammalian genome : official journal of the International Mammalian Genome Society
Atherosclerosis (AS) is a predominant etiological factor in numerous cardiovascular diseases, with its associated complications such as myocardial infarction and stroke serving as major contributors to worldwide mortality rates. Here, we devised depe...

Spatially Informed Graph Structure Learning Extracts Insights from Spatial Transcriptomics.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Embeddings derived from cell graphs hold significant potential for exploring spatial transcriptomics (ST) datasets. Nevertheless, existing methodologies rely on a graph structure defined by spatial proximity, which inadequately represents the diversi...

PseU-KeMRF: A Novel Method for Identifying RNA Pseudouridine Sites.

IEEE/ACM transactions on computational biology and bioinformatics
Pseudouridine is a type of abundant RNA modification that is seen in many different animals and is crucial for a variety of biological functions. Accurately identifying pseudouridine sites within the RNA sequence is vital for the subsequent study of ...

Brain-wide neural recordings in mice navigating physical spaces enabled by robotic neural recording headstages.

Nature methods
Technologies that can record neural activity at cellular resolution at multiple spatial and temporal scales are typically much larger than the animals that are being recorded from and are thus limited to recording from head-fixed subjects. Here we ha...

Bubble-Inspired Multifunctional Magnetic Microrobots for Integrated Multidimensional Targeted Biosensing.

Nano letters
Microrobots possessing multifunctional integration are desired for therapeutics and biomedicine applications. However, existing microrobots with desired functionalities need to be fabricated through complex procedures due to their constrained volume,...

Automated analysis of a novel object recognition test in mice using image processing and machine learning.

Behavioural brain research
The novel object recognition test (NORT) is one of the most commonly employed behavioral tests in experimental animals designed to evaluate an animal's interest in and recognition of novelty. However, manual procedures, which rely on researchers' obs...