AIMC Topic: Mice

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Deep learning-based behavioral profiling of rodent stroke recovery.

BMC biology
BACKGROUND: Stroke research heavily relies on rodent behavior when assessing underlying disease mechanisms and treatment efficacy. Although functional motor recovery is considered the primary targeted outcome, tests in rodents are still poorly reprod...

Development of non-bias phenotypic drug screening for cardiomyocyte hypertrophy by image segmentation using deep learning.

Biochemical and biophysical research communications
The number of patients with heart failure and related deaths is rapidly increasing worldwide, making it a major problem. Cardiac hypertrophy is a crucial preliminary step in heart failure, but its treatment has not yet been fully successful. In this ...

Functional Gait Assessment Using Manual, Semi-Automated and Deep Learning Approaches Following Standardized Models of Peripheral Nerve Injury in Mice.

Biomolecules
Objective: To develop a standardized model of stretch−crush sciatic nerve injury in mice, and to compare outcomes of crush and novel stretch−crush injuries using standard manual gait and sensory assays, and compare them to both semi-automated as well...

Context dependent prediction in DNA sequence using neural networks.

PeerJ
One way to better understand the structure in DNA is by learning to predict the sequence. Here, we trained a model to predict the missing base at any given position, given its left and right flanking contexts. Our best-performing model was a neural n...

Technical note: Rapid and high-resolution deep learning-based radiopharmaceutical imaging with 3D-CZT Compton camera and sparse projection data.

Medical physics
BACKGROUND: The Compton camera (CC) has great potential in nuclear medicine imaging due to the high detection efficiency and the ability to simultaneously detect multi-energy radioactive sources. However, the finite resolution of the detectors will d...

A novel machine learning-based approach for the detection and analysis of spontaneous synaptic currents.

PloS one
Spontaneous synaptic activity is a hallmark of biological neural networks. A thorough description of these synaptic signals is essential for understanding neurotransmitter release and the generation of a postsynaptic response. However, the complexity...

Deep learning multi-organ segmentation for whole mouse cryo-images including a comparison of 2D and 3D deep networks.

Scientific reports
Cryo-imaging provided 3D whole-mouse microscopic color anatomy and fluorescence images that enables biotechnology applications (e.g., stem cells and metastatic cancer). In this report, we compared three methods of organ segmentation: 2D U-Net with 2D...

MouseNet: A biologically constrained convolutional neural network model for the mouse visual cortex.

PLoS computational biology
Convolutional neural networks trained on object recognition derive inspiration from the neural architecture of the visual system in mammals, and have been used as models of the feedforward computation performed in the primate ventral stream. In contr...

Deep learning-based approach to the characterization and quantification of histopathology in mouse models of colitis.

PloS one
Inflammatory bowel disease (IBD) is a chronic immune-mediated disease of the gastrointestinal tract. While therapies exist, response can be limited within the patient population. Researchers have thus studied mouse models of colitis to further unders...

Danshao Shugan Granule therapy for non-alcoholic fatty liver disease.

Lipids in health and disease
BACKGROUND: Danshao Shugan Granules (DSSG), a traditional Chinese medicine (TCM), is given to protect the liver. The objective is to evaluate the mechanisms of the effects of DSSG on non-alcoholic fatty liver disease (NAFLD).