Editing of an Immunodominant Epitope of Glutamate Decarboxylase by HLA-DM
Bibliographic record
Abstract
HLA-DM stabilizes peptide-receptive class II alphabeta dimers and facilitates the capture of high affinity peptides, thus influencing the peptide repertoire presented by class II molecules. Variations in DM levels may therefore have a profound effect on the antigenic focus of T cell-mediated immune responses. Specifically, DM expression may influence susceptibility and resistance to autoimmune diseases. In this study the role of DM in HLA-DR4-restricted presentation of an insulin-dependent diabetes mellitus autoantigen, glutamate decarboxylase (GAD), was tested. Presentation of immunodominant GAD epitope 273-285 was regulated by endogenous DM levels in human B lymphoblasts. T cell responses to exogenous GAD as well as an endogenous cytoplasmic form of this Ag were significantly diminished with increasing cellular expression of DM. Epitope editing by DM was observed only using Ag and not small synthetic peptides, suggesting that this process occurred within endosomes. Results with cytoplasmic GAD also indicated that peptides from this compartment intersect class II proteins in endocytic vesicles where DM editing was facilitated. Changes in DM levels within APC may therefore influence the presentation of autoantigens and the development of autoimmune disorders such as type I 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".