Proinsulin Expression Shapes the TCR Repertoire but Fails to Control the Development of Low-Avidity Insulin-Reactive CD8+ T Cells
Bibliographic record
Abstract
NOD mice, a model strain for human type 1 diabetes, express proinsulin (PI) in the thymus. However, insulin-reactive T cells escape negative selection, and subsequent activation of the CD8(+) T-cell clonotype G9C8, which recognizes insulin B15-23 via an αβ T-cell receptor (TCR) incorporating TRAV8-1/TRAJ9 and TRBV19/TRBJ2-3 gene rearrangements, contributes to the development of diabetes. In this study, we used fixed TRAV8-1/TRAJ9 TCRα-chain transgenic mice to assess the impact of PI isoform expression on the insulin-reactive CD8(+) T-cell repertoire. The key findings were: 1) PI2 deficiency increases the frequency of insulin B15-23-reactive TRBV19(+)CD8(+) T cells and causes diabetes; 2) insulin B15-23-reactive TRBV19(+)CD8(+) T cells are more abundant in the pancreatic lymph nodes of mice lacking PI1 and/or PI2; 3) overexpression of PI2 decreases TRBV19 usage in the global CD8(+) T-cell compartment; 4) a biased repertoire of insulin-reactive CD8(+) T cells emerges in the periphery regardless of antigen exposure; and 5) low-avidity insulin-reactive CD8(+) T cells are less affected by antigen exposure in the thymus than in the periphery. These findings inform our understanding of the diabetogenic process and reveal new avenues for therapeutic exploitation in type 1 diabetes.
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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) | 0.001 | 0.001 |
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".