AIMC Topic: Microglia

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Image processing and supervised machine learning for retinal microglia characterization in senescence.

Methods in cell biology Jan 28, 2023
The process of senescence impairs the function of cells and can ultimately be a key factor in the development of disease. With an aging population, senescence-related diseases are increasing in prevalence. Therefore, understanding the mechanisms of c...
Animals Mice Supervised Machine Learning Aging Microglia Image Processing, Computer-Assisted Retina
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Automated characterisation of microglia in ageing mice using image processing and supervised machine learning algorithms.

Scientific reports Feb 2, 2022
The resident macrophages of the central nervous system, microglia, are becoming increasingly implicated as active participants in neuropathology and ageing. Their diverse and changeable morphology is tightly linked with functions they perform, enabli...
Cellular Senescence Microscopy Aging Image Processing, Computer-Assisted Mice, Inbred C57BL Mice Microglia Brain Support Vector Machine Animals Age Factors Male
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Development of deep learning models for microglia analyses in brain tissue using DeePathology™ STUDIO.

Journal of neuroscience methods Sep 27, 2021
BACKGROUND: Interest in artificial intelligence-driven analysis of medical images has seen a steep increase in recent years. Thus, our paper aims to promote and facilitate the use of this state-of-the-art technology to fellow researchers and clinicia...
Artificial Intelligence Brain Animals Mice Microglia Deep Learning Image Processing, Computer-Assisted
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Unified AI framework to uncover deep interrelationships between gene expression and Alzheimer's disease neuropathologies.

Nature communications Sep 10, 2021
Deep neural networks (DNNs) capture complex relationships among variables, however, because they require copious samples, their potential has yet to be fully tapped for understanding relationships between gene expression and human phenotypes. Here we...
Aged Aged, 80 and over Animals Humans Brain Female RNA-Seq Mice Microglia Alzheimer Disease Male Deep Learning Cohort Studies Sex Factors Datasets as Topic Gene Expression Regulation
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Deep learning assisted quantitative assessment of histopathological markers of Alzheimer's disease and cerebral amyloid angiopathy.

Acta neuropathologica communications Aug 21, 2021
Traditionally, analysis of neuropathological markers in neurodegenerative diseases has relied on visual assessments of stained sections. Resulting semiquantitative scores often vary between individual raters and research centers, limiting statistical...
Astrocytes Alzheimer Disease Cerebral Amyloid Angiopathy Brain Deep Learning Microglia Humans Neural Networks, Computer
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Structure-aware machine learning identifies microRNAs operating as Toll-like receptor 7/8 ligands.

RNA biology Jul 9, 2021
MicroRNAs (miRNAs) can serve as activation signals for membrane receptors, a recently discovered function that is independent of the miRNAs' conventional role in post-transcriptional gene regulation. Here, we introduce a machine learning approach, Br...
Humans Oligonucleotides Toll-Like Receptor 7 Ligands Gene Expression Regulation Toll-Like Receptor 8 Mice, Inbred C57BL Machine Learning MicroRNAs Animals Microglia Mice
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Utilizing supervised machine learning to identify microglia and astrocytes in situ: implications for large-scale image analysis and quantification.

Journal of neuroscience methods Sep 5, 2019
BACKGROUND: The evaluation of histological tissue samples plays a crucial role in deciphering preclinical disease and injury mechanisms. High-resolution images can be obtained quickly however data acquisition are often bottlenecked by manual analysis...
Fluorescent Antibody Technique Histological Techniques Neurosciences Reproducibility of Results Microglia Image Processing, Computer-Assisted Supervised Machine Learning Sensitivity and Specificity Astrocytes Animals, Genetically Modified Mice Animals Rats
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Automatic ground truth for deep learning stereology of immunostained neurons and microglia in mouse neocortex.

Journal of chemical neuroanatomy Mar 2, 2019
Collection of unbiased stereology data currently relies on relatively simple, low throughput technology developed in the mid-1990s. In an effort to improve the accuracy and efficiency of these integrated hardware-software-digital microscopy systems, ...
Neurons Animals Histological Techniques Deep Learning Microglia Neocortex Image Processing, Computer-Assisted Cell Count Mice
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Deep learning assisted quantitative analysis of Aβ and microglia in patients with idiopathic normal pressure hydrocephalus in relation to cognitive outcome.

Journal of neuropathology and experimental neurology Nov 1, 2024
Neuropathologic changes of Alzheimer disease (AD) including Aβ accumulation and neuroinflammation are frequently observed in the cerebral cortex of patients with idiopathic normal pressure hydrocephalus (iNPH). We created an automated analysis platfo...
Retrospective Studies Female Aged Aged, 80 and over Humans Microglia Amyloid beta-Peptides Male Alzheimer Disease Deep Learning Hydrocephalus, Normal Pressure Cognition
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Machine Learning-Supported Analyses Improve Quantitative Histological Assessments of Amyloid-β Deposits and Activated Microglia.

Journal of Alzheimer's disease : JAD Jan 1, 2021
BACKGROUND: Detailed pathology analysis and morphological quantification is tedious and prone to errors. Automatic image analysis can help to increase objectivity and reduce time. Here, we present the evaluation of the DeePathology STUDIO™ for automa...
Mice Disease Models, Animal Microglia Plaque, Amyloid Alzheimer Disease Mice, Transgenic Machine Learning Animals Image Processing, Computer-Assisted
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