AIMC Topic: Mice
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FastCellpose: A Fast and Accurate Deep-Learning Framework for Segmentation of All Glomeruli in Mouse Whole-Kidney Microscopic Optical Images.
Cells
Nov 30, 2023
Automated evaluation of all glomeruli throughout the whole kidney is essential for the comprehensive study of kidney function as well as understanding the mechanisms of kidney disease and development. The emerging large-volume microscopic optical ima...
Predicting intratumoral fluid pressure and liposome accumulation using physics informed deep learning.
Scientific reports
Nov 23, 2023
Liposome-based anticancer agents take advantage of the increased vascular permeability and transvascular pressure gradients for selective accumulation in tumors, a phenomenon known as the enhanced permeability and retention(EPR) effect. The EPR effec...
Shedding Light on Colorectal Cancer: An In Vivo Raman Spectroscopy Approach Combined with Deep Learning Analysis.
International journal of molecular sciences
Nov 21, 2023
Raman spectroscopy has emerged as a powerful tool in medical, biochemical, and biological research with high specificity, sensitivity, and spatial and temporal resolution. Recent advanced Raman systems, such as portable Raman systems and fiber-optic ...
Facemap: a framework for modeling neural activity based on orofacial tracking.
Nature neuroscience
Nov 20, 2023
Recent studies in mice have shown that orofacial behaviors drive a large fraction of neural activity across the brain. To understand the nature and function of these signals, we need better computational models to characterize the behaviors and relat...
A systematic review of the development and application of home cage monitoring in laboratory mice and rats.
BMC biology
Nov 13, 2023
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...
Deep learning-based image analysis identifies a DAT-negative subpopulation of dopaminergic neurons in the lateral Substantia nigra.
Communications biology
Nov 10, 2023
Here we present a deep learning-based image analysis platform (DLAP), tailored to autonomously quantify cell numbers, and fluorescence signals within cellular compartments, derived from RNAscope or immunohistochemistry. We utilised DLAP to analyse su...
Accurate classification of major brain cell types using in vivo imaging and neural network processing.
PLoS biology
Nov 9, 2023
Comprehensive analysis of tissue cell type composition using microscopic techniques has primarily been confined to ex vivo approaches. Here, we introduce NuCLear (Nucleus-instructed tissue composition using deep learning), an approach combining in vi...
High-Content Image-Based Screening and Deep Learning for the Detection of Anti-Inflammatory Drug Leads.
Chembiochem : a European journal of chemical biology
Nov 7, 2023
We developed a high-content image-based screen that utilizes the pro-inflammatory stimulus lipopolysaccharide (LPS) and murine macrophages (RAW264.7) with the goal of enabling the identification of novel anti-inflammatory lead compounds. We screened ...
Combined colour deconvolution and artificial intelligence approach for region-selective immunohistochemical labelling quantification: The example of alpha smooth muscle actin in mouse kidney.
Journal of biophotonics
Nov 7, 2023
Immunohistochemical (IHC) localisation of protein expression is a widely used tool in pathology. This is semi-quantitative and exhibits substantial intra- and inter-observer variability. Digital approaches based on stain quantification applied to IHC...
DeepMPSF: A Deep Learning Network for Predicting General Protein Phosphorylation Sites Based on Multiple Protein Sequence Features.
Journal of chemical information and modeling
Nov 6, 2023
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...
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