ReviewBiomedical papers of the Medical Faculty of the University Palacky, Olomouc, Czechoslovakia2026
Mini review on the laboratory diagnosis of amyloidosis: An overview of methods, applications, and trends in analytical approaches.
Review in Biomedical papers of the Medical Faculty of the University Palacky, Olomouc, Czechoslovakia, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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9 authors.
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Abstract
Amyloidosis represents a clinically and molecularly heterogeneous group of serious, potentially life-threatening disorders characterized by the extracellular deposition of insoluble amyloid fibrils derived from misfolded precursor proteins. These deposits disrupt tissue architecture and function, often affecting vital organs such as the heart and kidneys. Accurate diagnosis and subtyping of amyloidosis are essential for effective clinical management and personalized therapeutic interventions. This review provides an integrated overview of modern approaches to the laboratory diagnosis of amyloidosis, divided into three main areas: (1) histological and immunological methods (including Congo red staining, immunohistochemistry, immunofluorescence, and immunoelectron microscopy) for the initial detection and characterization of amyloid deposition, (2) electrophoretic techniques (capillary electrophoresis, isoelectric focusing, immunofixation electrophoresis) used primarily for the analysis of amyloid-associated proteins in serum and urine, and (3) mass spectrometry-based proteomic analyses that have significantly improved subtype specificity and clinical decision-making. By emphasizing the complementary roles of these techniques, the review aims to support timely, accurate, and subtype-specific diagnosis, ultimately improving clinical outcomes and treatment strategies for patients affected by amyloidosis.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.