The phenotypic changes of microglia in brain diseases are particularly diverse and their role in disease progression, beneficial, or detrimental, is still elusive. High-throughput molecular approaches such as single-cell RNA-sequencing can now resolve the high heterogeneity in microglia population for a specific physiological condition, however, the relation between the different microglial signatures and their surrounding brain microenvironment is barely understood. Thus, better tools to characterize the phenotypic variations of microglia in situ are needed, particularly for human brain postmortem samples analysis. To address this challenge, we developed MIC-MAC, a Microglia and Immune Cells Morphologies Analyser and Classifier pipeline that semiautomatically segments, extracts, and classifies all microglia and immune cells labeled in large three-dimensional (3D) confocal image stacks of mouse and human brain samples. Our imaging-based approach enables automatic 3D-morphology characterization and classification of thousands of individual microglia in situ and revealed species- and disease-specific morphological phenotypes in mouse aging, human Alzheimer's disease, and dementia with Lewy Bodie's samples. MIC-MAC is a precision diagnostic tool that allows a rapid, unbiased, and large-scale analysis of microglia morphological states in mouse models and patient brain samples.
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http://dx.doi.org/10.1002/glia.23623 | DOI Listing |
J Dent Sci
December 2024
Department of Laboratory Medicine, Karolinska Institutet, Huddinge, Sweden.
Background/purpose: Dysbiosis of oral microbiota has been reported in late stage of chronic hepatitis B (CHB) infection with cirrhosis. CHB is characterized by the constant virus-induced liver injury which may lead to liver cirrhosis and hepatocellular carcinoma (HCC). However, some patients show normal liver function without antiviral treatment, associating with favourable prognosis.
View Article and Find Full Text PDFJ Tradit Complement Med
January 2025
Institute of Food Science and Technology, College of Bioresources and Agriculture, National Taiwan University, Taipei, Taiwan.
Background And Aim: (CM) and (AM) are medicinal mushrooms with potential applications in the treatment of mood disorders, including depression and anxiety. While research suggests that both CM and AM possess anti-inflammatory properties and hold potential for treating depression when administered separately, there is limited knowledge about their efficacy when combined in a formula, as well as the underlying mechanism involving the modulation of microglia.
Experimental Procedure: Rats received oral administrations of the low-dose formulation, medium-dose formulation, and high-dose formulation over 28 consecutive days as part of the UCMS protocols.
BMC Nutr
January 2025
Clinic for Cognitive Neurology, University of Leipzig Medical Center, Leipzig, Germany.
Background: Obesity is a multifactorial disease reaching pandemic proportions with increasing healthcare costs, advocating the development of better prevention and treatment strategies. Previous research indicates that the gut microbiome plays an important role in metabolic, hormonal, and neuronal cross-talk underlying eating behavior. We therefore aim to examine the effects of prebiotic and neurocognitive behavioral interventions on food decision-making and to assay the underlying mechanisms in a Randomized Controlled Trial (RCT).
View Article and Find Full Text PDFBMC Microbiol
January 2025
Microbial Chemistry Department, Biotechnology Research Institute, National Research Center, Dokki, Giza, Egypt.
The red pigment was recovered from the S. phaeolivaceus GH27 isolate, which was molecularly identified using 16S rRNA gene sequencing and submitted to GenBank as OQ145635.1.
View Article and Find Full Text PDFJ Mol Neurosci
January 2025
Department of Biophysics, School of Life Sciences, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
Alzheimer's disease (AD), a prevalent neurodegenerative disorder, is characterized by mitochondrial dysfunction and immune dysregulation. This study is aimed at developing a risk prediction model for AD by integrating multi-omics data and exploring the interplay between mitochondrial energy metabolism-related genes (MEMRGs) and immune cell dynamics. We integrated four GEO datasets (GSE132903, GSE29378, GSE33000, GSE5281) for differential gene expression analysis, functional enrichment, and weighted gene co-expression network analysis (WGCNA).
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