Exposure to sequestered self-antigens in vivo is not sufficient for the induction of autoimmune diabetes
Bibliographic record
Abstract
Although the role of T cells in autoimmunity has been explored for many years, the mechanisms leading to the initial priming of an autoimmune T cell response remain enigmatic. The 'hit and run' model suggests that self-antigens released upon cell death can provide the initial signal for a self-sustaining autoimmune response. Using a novel transgenic mouse model where we could induce the release of self-antigens via caspase-dependent apoptosis. We tracked the fate of CD8+ T cells specific for the self-antigen. Our studies demonstrated that antigens released from apoptotic cells were cross-presented by CD11c+ cells in the draining lymph node. This cross-presentation led to proliferation of self-antigen specific T cells, followed by a transient ability to produce IFN-γ, but did not lead to the development of autoimmune diabetes. Using this model we examined the consequences on T cell immunity when apoptosis was combined with dendritic cell maturation signals, an autoimmune susceptible genetic background, and the deletion of Tregs. The results of our study demonstrate that autoimmune diabetes cannot be initiated by the presentation of antigens released from apoptotic cells in vivo even in the presence of factors known to promote autoimmunity.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".