Combined unsupervised and semi-automated supervised analysis of flow cytometry data reveals cellular fingerprint associated with newly diagnosed pediatric type 1 diabetes

Combined unsupervised and semi-automated supervised analysis of flow cytometry data reveals cellular fingerprint associated with newly diagnosed pediatric type 1 diabetes

An unbiased and replicable profiling of type 1 diabetes (T1D)-specific circulating immunome at disease onset has yet to be identified due to experimental and patient selection limitations. Multicolor flow cytometry was performed on whole blood from a pediatric cohort of 107 patients with new-onset T...

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Bibliographic Details
Main Authors: Camillo Bechi Genzano, Eugenia Bezzecchi, Debora Carnovale, Alessandra Mandelli, Elisa Morotti, Valeria Castorani, Valeria Favalli, Angela Stabilini, Vittoria Insalaco, Francesca Ragogna, Valentina Codazzi, Giulia Maria Scotti, Stefania Del Rosso, Benedetta Allegra Mazzi, Maurizio De Pellegrin, Andrea Giustina, Lorenzo Piemonti, Emanuele Bosi, Manuela Battaglia, Marco J. Morelli, Riccardo Bonfanti, Alessandra Petrelli
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-10-01
Series:Frontiers in Immunology
Subjects:
type 1 diabetes
fingerprints
immune markers
pediatric diabetes
flow cytometry
computational biology
Online Access:https://www.frontiersin.org/articles/10.3389/fimmu.2022.1026416/full

Internet

https://www.frontiersin.org/articles/10.3389/fimmu.2022.1026416/full

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