Autoantigen-Specific Immunotherapies for the Prevention and Treatment of Type 1 Diabetes
Bibliographic record
Abstract
Type 1 diabetes (T1D) is driven by an immunologically complex, diverse, and self-sustaining immune response directed against tissue autoantigens, leading to loss or dysfunction of β cells. To date, the single approved immune intervention in T1D is based on a strategy that is similar to that used in other related autoimmune diseases, namely, the attenuation of immune cell activation. As a next-generation approach that is more focused on underlying mechanisms of loss of tolerance, antigen-specific immunotherapy is designed to establish or restore bystander immunoregulation in a highly tissue- and target-specific fashion. Here, we describe the basis for this alternative approach, which could also have potential for complementarity if used in combination with more conventional immune modulators, and highlight recent advances, knowledge gaps, and next steps in clinical development.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".