Complete Diabetes Protection Despite Delayed Thymic Tolerance in NOD8.3 TCR Transgenic Mice Due to Antigen-Induced Extrathymic Deletion of T Cells
Bibliographic record
Abstract
Prevention of autoimmunity requires the elimination of self-reactive T cells during their development in the thymus and maturation in the periphery. Transgenic NOD mice that overexpress islet-specific glucose 6 phosphatase catalytic subunit-related protein (IGRP) in antigen-presenting cells (NOD-IGRP mice) have no IGRP-specific T cells. To study the relative contribution of central and peripheral tolerance mechanisms to deletion of antigen-specific T cells, we crossed NOD-IGRP mice to highly diabetogenic IGRP206-214 T-cell receptor transgenic mice (NOD8.3 mice) and studied the frequency and function of IGRP-specific T cells in the thymus and periphery. Peripheral tolerance was extremely efficient and completely protected NOD-IGRP/NOD8.3 mice from diabetes. Peripheral tolerance was characterized by activation of T cells in peripheral lymphoid tissue where IGRP was expressed followed by activation-induced cell death. Thymectomy showed that thymic output of IGRP-specific transgenic T cells compensated for peripheral deletion to maintain peripheral T-cell numbers. Central tolerance was undetectable until 10 weeks and complete by 15 weeks. These in vivo data indicate that peripheral tolerance alone can protect NOD8.3 mice from autoimmune diabetes and that profound changes in T-cell repertoire can follow subtle changes in thymic antigen presentation.
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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) | 0.001 | 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".