Induced, but not natural, regulatory T cells retain phenotype and function following exposure to inflamed synovial fibroblasts is a research paper published in Science Advances (2020). On theSindex it has a DataRank of 0. It has been cited 53 times.
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National Institutes of Health
Grant: AR059103
National Institutes of Health
Grant: AR073409
China National Natural Science Foundation
Grant: No. 81671611and No.81871224
National Institutes of Health
Grant: 1R01AR059103-01A1
Therapeutic immunoregulation mediated by TGF-??-induced iTregs in autoimmune arth
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Sustainable Development Goals
Additional file 3 of Investigation of the acute pathogenesis of spondyloarthritis/HLA-B27-associated anterior uveitis based on genome-wide association analysis and single-cell transcriptomics
Additional file 3 of Investigation of the acute pathogenesis of spondyloarthritis/HLA-B27-associated anterior uveitis based on genome-wide association analysis and single-cell transcriptomics
Additional file 4 of Investigation of the acute pathogenesis of spondyloarthritis/HLA-B27-associated anterior uveitis based on genome-wide association analysis and single-cell transcriptomics
Additional file 4 of Investigation of the acute pathogenesis of spondyloarthritis/HLA-B27-associated anterior uveitis based on genome-wide association analysis and single-cell transcriptomics
Additional file 1 of Investigation of the acute pathogenesis of spondyloarthritis/HLA-B27-associated anterior uveitis based on genome-wide association analysis and single-cell transcriptomics
Additional file 2 of Investigation of the acute pathogenesis of spondyloarthritis/HLA-B27-associated anterior uveitis based on genome-wide association analysis and single-cell transcriptomics
Additional file 2 of Investigation of the acute pathogenesis of spondyloarthritis/HLA-B27-associated anterior uveitis based on genome-wide association analysis and single-cell transcriptomics
Additional file 1 of Investigation of the acute pathogenesis of spondyloarthritis/HLA-B27-associated anterior uveitis based on genome-wide association analysis and single-cell transcriptomics