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Updated: Jan 10, 2026

Detecting Amyloid-β Accumulation via Immunofluorescent Staining in a Mouse Model of Alzheimer's Disease
Published on: April 19, 2021
Optimized methods for efficient application of immunogold electron microscopy to amyloid fibrils typing
Yan Zhou1, Weining Lu1,2, Eric Burks1
1Department of Pathology and Laboratory Medicine, Boston Medical Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.
Objective:
Amyloidosis is a group of disorders characterized by aggregation of abnormal amyloid protein in various tissues, often leading to organ dysfunction and failure. We optimized the immunogold electron microscopy (IEM) technique to enable efficient amyloid typing in 4% paraformaldehyde-fixed (PFA) and formalin-fixed paraffin-embedded (FFPE) tissues.
Methods:
The optimized IEM technique was applied to 151 Congo-red positive specimens from various tissues representing different amyloidosis types; 117 were fixed in 4% PFA and 34 were FFPE samples. Specimens were embedded in Lowicryl/K4M and stained with modified Richardson's blue solution to differentiate amyloid (lavender-plum coloration stained) from non-amyloid (blue stained) areas under light microscopy. Antibodies against kappa and lambda light chains, transthyretin and amyloid A were used for amyloid typing by IEM.
Results:
The optimized IEM technique enabled precise localization of amyloid deposits and rapid identification of target area under light microscopy for thin-section placement on nickel grids for immunogold staining. Of 151 specimens, 147 (97.4%) were classified as kappa or lambda light chains, transthyretin or amyloid A. Lambda light chain predominated in fat pad aspirates (56.8%), while transthyretin was most common in heart tissues (71.7%).
Conclusion:
This optimized IEM technique enhances the accuracy and efficiency of amyloid typing, especially in samples with trace amyloid deposit. It offers significant advantages over traditional epoxy embedding with toluidine blue staining, supporting timely clinical diagnosis and therapeutic decision-making.

