CD4+ T Cells from Glutamic Acid Decarboxylase (GAD)65-specific T Cell Receptor Transgenic Mice Are Not Diabetogenic and Can Delay Diabetes Transfer
Bibliographic record
Abstract
Glutamic acid decarboxylase (GAD)65 is an early and important antigen in both human diabetes mellitus and the nonobese diabetic (NOD) mouse. However, the exact role of GAD65-specific T cells in diabetes pathogenesis is unclear. T cell responses to GAD65 occur early in diabetes pathogenesis, yet only one GAD65-specific T cell clone of many identified can transfer diabetes. We have generated transgenic mice on the NOD background expressing a T cell receptor (TCR)-specific for peptide epitope 286-300 (p286) of GAD65. These mice have GAD65-specific CD4(+) T cells, as shown by staining with an I-A(g7)(p286) tetramer reagent. Lymphocytes from these TCR transgenic mice proliferate and make interferon gamma, interleukin (IL)-2, tumor necrosis factor (TNF)-alpha, and IL-10 when stimulated in vitro with GAD65 peptide 286-300, yet these TCR transgenic animals do not spontaneously develop diabetes, and insulitis is virtually undetectable. Furthermore, in vitro activated CD4 T cells from GAD 286 TCR transgenic mice express higher levels of CTL-associated antigen (CTLA)-4 than nontransgenic littermates. CD4(+) T cells, or p286-tetramer(+)CD4(+) Tcells, from GAD65 286-300-specific TCR transgenic mice delay diabetes induced in NOD.scid mice by diabetic NOD spleen cells. This data suggests that GAD65 peptide 286-300-specific T cells have disease protective capacity and are not pathogenic.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".