A well-designed fluorescence-based analysis of extracellular vesicles (EV) can provide insights into the size, morphology, and biological function of EVs, which can be used in medical applications. Fluorescent nanoparticle tracking analysis with appropriate controls can provide reliable data for size and concentration measurements, while nanoscale flow cytometry is the most appropriate tool for characterizing molecular cargoes. Label selection is a crucial element in all fluorescence methods. The most comprehensive data can be obtained if several labeling approaches for a given marker are used, as they would provide complementary information about EV populations and interactions with the cells. In all EV-related experiments, the influence of lipoproteins and protein corona on the results should be considered. By reviewing and considering all the factors affecting EV labeling methods used in fluorescence-based techniques, we can assert that the data will provide as accurate as possible information about true EV biology and offer precise, clinically applicable information for future EV-based diagnostic or therapeutic applications.
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http://dx.doi.org/10.3389/fbioe.2024.1479516 | DOI Listing |
Adv Healthc Mater
December 2024
ETH Zürich, Department of Chemistry and Applied Biosciences, Institute for Chemical and Bioengineering, 8093, Zürich, Switzerland.
Coating synthetic nanoparticles (NPs) with lipid membranes is a promising approach to enhance the performance of nanomaterials in various biological applications, including therapeutic delivery to target organs. Current methods for achieving this coating often rely on bulk approaches which can result in low efficiency and poor reproducibility. Continuous processes coupled with quality control represent an attractive strategy to manufacture products with consistent attributes and high yields.
View Article and Find Full Text PDFJ Transl Med
December 2024
Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Background: Increased ribosome biogenesis is required for tumor growth. In this study, we investigated the function and underlying molecular mechanism of ribosome biogenesis factor (RBIS) in the progression of non-small cell lung cancer (NSCLC).
Methods: In our study, we conducted a comprehensive analysis to identify key genes implicated in ribosome biogenesis by leveraging a Gene Set Enrichment Analysis (GSEA) dataset.
Diabet Med
December 2024
Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter Medical School, Exeter, UK.
Aims: Acute hypoglycaemia promotes pro-inflammatory cytokine production, increasing the risk for cardiovascular events in diabetes. AMP-activated protein kinase (AMPK) is regulated by and influences the production of pro-inflammatory cytokines. We sought to examine the mechanistic role of AMPK in low glucose-induced changes in the pro-inflammatory cytokine macrophage migration inhibitory factor (MIF), which is elevated in people with diabetes.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Disease, Henry and Allison McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA.
Introduction: We previously demonstrated that regulating mitochondria-associated endoplasmic reticulum (ER) membranes (MAMs) affects axonal Aβ generation in a well-characterized three-dimensional (3D) neural Alzheimer's disease (AD) model. MAMs vary in thickness and length, impacting their functions. Here, we examined the effect of MAM thickness on Aβ in our 3D neural model of AD.
View Article and Find Full Text PDFMultiplexed tissue imaging (MTI) technologies enable high-dimensional spatial analysis of tumor microenvironments but face challenges with technical variability in staining intensities. Existing normalization methods, including z-score, ComBat, and MxNorm, often fail to account for the heterogeneous, right-skewed expression patterns of MTI data, compromising signal alignment and downstream analyses. We present UniFORM, a non-parametric, Python-based pipeline for normalizing both feature- and pixel-level MTI data.
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