Neurobiology of disease · 2021
Quantitative detection of grey and white matter amyloid pathology using a combination of K114 and CRANAD-3 fluorescence.
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Stepanchuk Anastasiia A, Barber Philip A, Lashley Tammaryn, Joseph Jeffrey T, Stys Peter K
Аннотация
BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disease that exacts a huge toll on the patient, the healthcare system and society in general. Abundance and morphology of protein aggregates such as amyloid β plaques and tau tangles, along with cortical atrophy and gliosis are used as measures to assess the changes in the brain induced by the disease. Not all of these parameters have a direct correlation with cognitive decline. Studies have shown that only particular protein conformers can be the main drivers of disease progression, and conventional approaches are unable to distinguish different conformations of disease-relevant proteins.
METHODS AND RESULTS: Using the fluorescent amyloid probes K114 and CRANAD-3 and spectral confocal microscopy, we examined formalin-fixed paraffin-embedded brain samples from different control and AD cases. Based on the emission spectra of the probes used in this study, we found that certain spectral signatures can be correlated with different aggregates formed by different proteins. The combination of spectral imaging and advanced image analysis tools allowed us to detect variability of protein deposits across the samples.
CONCLUSION: Our proposed method offers a quicker and easier neuropathological assessment of tissue samples, as well as introducing an additional parameter by which protein aggregates can be discriminated.
METHODS AND RESULTS: Using the fluorescent amyloid probes K114 and CRANAD-3 and spectral confocal microscopy, we examined formalin-fixed paraffin-embedded brain samples from different control and AD cases. Based on the emission spectra of the probes used in this study, we found that certain spectral signatures can be correlated with different aggregates formed by different proteins. The combination of spectral imaging and advanced image analysis tools allowed us to detect variability of protein deposits across the samples.
CONCLUSION: Our proposed method offers a quicker and easier neuropathological assessment of tissue samples, as well as introducing an additional parameter by which protein aggregates can be discriminated.