Browsing by Subject "Spectral analysis"

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    Luminescent conjugated oligothiophenes distinguish between α-synuclein assemblies of Parkinson’s disease and multiple system atrophy
    (BMC, 2019-12-03) Klingstedt, Therése; Ghetti, Bernardino; Holton, Janice L.; Ling, Helen; Nilsson, K. Peter R.; Goedert, Michel; Pathology and Laboratory Medicine, School of Medicine
    Synucleinopathies [Parkinson’s disease with or without dementia, dementia with Lewy bodies and multiple system atrophy] are neurodegenerative diseases that are defined by the presence of filamentous α-synuclein inclusions. We investigated the ability of luminescent conjugated oligothiophenes to stain the inclusions of Parkinson’s disease and multiple system atrophy. They stained the Lewy pathology of Parkinson’s disease and the glial cytoplasmic inclusions of multiple system atrophy. Spectral analysis of HS-68-stained inclusions showed a red shift in multiple system atrophy, but the difference with Parkinson’s disease was not significant. However, when inclusions were double-labelled for HS-68 and an antibody specific for α-synuclein phosphorylated at S129, they could be distinguished based on colour shifts with blue designated for Parkinson’s disease and red for multiple system atrophy. The inclusions of Parkinson’s disease and multiple system atrophy could also be distinguished using fluorescence lifetime imaging. These findings are consistent with the presence of distinct conformers of assembled α-synuclein in Parkinson’s disease and multiple system atrophy.
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    Spectral analysis assisted photoacoustic imaging for lipid composition differentiation
    (Elsevier, 2017-06-06) Cao, Yingchun; Kole, Ayeeshik; Lan, Lu; Wang, Pu; Hui, Jie; Sturek, Michael; Cheng, Ji-Xin; Cellular and Integrative Physiology, School of Medicine
    Recent advances in atherosclerotic plaque detection have shown that not only does lipid core size and depth play important roles in plaque rupture and thrombi formation, but lipid composition, especially cholesterol deposition, is equally important in determining lesion vulnerability. Here, we demonstrate a spectral analysis assisted photoacoustic imaging approach to differentiate and map lipid compositions within an artery wall. The approach is based on the classification of spectral curves obtained from the sliding windows along time-of-flight photoacoustic signals via a numerical k-means clustering method. The evaluation result on a vessel-mimicking phantom containing cholesterol and olive oil shows accuracy and efficiency of this method, suggesting the potential to apply this approach in assessment of atherosclerotic plaques.