Extracting biochemical information from tissue autofluorescence is a promising approach to non-invasively monitor disease treatments at a cellular level, without using any external biomarkers. Our recently developed unsupervised hyperspectral unmixing by Dependent Component Analysis (DECA) provides robust and detailed metabolic information with proper account of intrinsic cellular heterogeneity. Moreover this method is compatible with established methods of fluorescent biomarker labelling.
Recently adipose-derived stem cell (ADSC) – based therapies have been introduced for treating different diseases in animals and humans. ADSC have been shown promise in regenerative treatments for osteoarthritis and other bone and joint disorders. One of the mechanism of their action is their anti-inflammatory effects within osteoarthritic joints which aid the regeneration of cartilage. These therapeutic effects are known to be driven by secretions of different cytokines from the ADSCs. We have been using the hyperspectral unmixing techniques to study in-vitro the effects of ADSC-derived cytokine-rich secretions with the cartilage chip in both human and bovine samples. The study of metabolic effects of different cytokine treatment on different cartilage layers makes it possible to compare the merits of those treatments for repairing cartilage.
Saabah B. Mahbub, Peter Succer, Martin E. Gosnell, Ayad G. Anwaer, Benjamin Herbert, Graham Vesey, and Ewa M. Goldys, "Non-invasive monitoring of cytokine-based regenerative treatment of cartilage by hyperspectral unmixing (Conference Presentation)," Proc. SPIE 9698, Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XIV, 96980B (Presented at SPIE BiOS: February 14, 2016; Published: 27 April 2016); https://doi.org/10.1117/12.2212336.4828055420001.
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