Antidiabetogenic MHC class II promotes the differentiation of MHC-promiscuous autoreactive T cells into FOXP3 <sup>+</sup> regulatory T cells
Bibliographic record
Abstract
Polymorphisms in MHC class II molecules, in particular around β-chain position-57 (β57), afford susceptibility/resistance to multiple autoimmune diseases, including type 1 diabetes, through obscure mechanisms. Here, we show that the antidiabetogenic MHC class II molecule I-A(b) affords diabetes resistance by promoting the differentiation of MHC-promiscuous autoreactive CD4(+) T cells into disease-suppressing natural regulatory T cells, in a β56-67-regulated manner. We compared the tolerogenic and antidiabetogenic properties of CD11c promoter-driven transgenes encoding I-A(b) or a form of I-A(b) carrying residues 56-67 of I-Aβ(g7) (I-A(b-g7)) in wild-type nonobese diabetic (NOD) mice, as well as NOD mice coexpressing a diabetogenic and I-A(g7)-restricted, but MHC-promiscuous T-cell receptor (4.1). Both I-A transgenes protected NOD and 4.1-NOD mice from diabetes. However, whereas I-A(b) induced 4.1-CD4(+) thymocyte deletion and 4.1-CD4(+)Foxp3(+) regulatory T-cell development, I-A(b-g7) promoted 4.1-CD4(+)Foxp3(+) Treg development without inducing clonal deletion. Furthermore, non-T-cell receptor transgenic NOD.CD11cP-I-A(b) and NOD.CD11cP-IA(b-g7) mice both exported regulatory T cells with superior antidiabetogenic properties than wild-type NOD mice. We propose that I-A(b), and possibly other protective MHC class II molecules, afford disease resistance by engaging a naturally occurring constellation of MHC-promiscuous autoreactive T-cell clonotypes, promoting their deviation into autoregulatory T cells.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".