Débora Elisa da Costa Matoso

Dr. Débora Elisa da Costa Matoso


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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20 May 2024 in Neuroglia
Verified
Journal Article
Open access
PDF file
LCLilian de Oliveira Coser
Lilian de Oliveira Coser
MCManuela Tosi Comelis
Manuela Tosi Comelis
DMDébora Elisa da Costa Matoso
Débora Elisa da Costa Matoso
LCLuciana Cartarozzi
Luciana Cartarozzi
Alexandre OliveiraAlexandre Oliveira
Alexandre Oliveira
Several protocols have been developed with the aim of characterizing glial and immune cells from the central and peripheral nervous systems. However, a small number of these protocols have demonstrated the ability to yield satisfactory results following conventional isolation. Considering this necessity and the difficulties encountered in enzymatic and bead isolation, our work proposes a method for the isolation of glial and immune cells from the spinal cord utilizing a Percoll gradient. For this purpose, C57BL/6J spinal cords were dissected, and the lumbar intumescence was dissociated and subjected to a Percoll gradient centrifugation (70%, 50%, 37%, and 10%). Each layer was then separated and labeled for astrocytes (anti-GFAP, TNF-α, IFN-γ, IL-10, IL-4), microglia (anti-CD45, CD11b, CD206, CD68, TNF-α, IFN-γ), and lymphocytes (anti-CD3, CD4, IFN-γ, IL-4). The gate detections were mathematically performed by computational analysis utilizing the K-means clustering algorithm. The results demonstrated that astrocytes were concentrated at the Percoll 10/37 interface, microglia at the Percoll 37/50 layer, and lymphocytes at the Percoll 50/70 layer. Our findings indicate that astrocytes in healthy animals are putative of the A1 profile, while microglia and lymphocytes are more frequently labeled with M1 and Th1 markers, suggesting a propensity towards inflammatory responses. The computational method enabled the semi-autonomous gate detection of flow cytometry data, which might facilitate and expedite the processing of large amounts of data.