DRB1*0401-restricted human T cell clone specific for the major proinsulin73-90 epitope expresses a down-regulatory T helper 2 phenotype
Bibliographic record
Abstract
Recently, we have identified proinsulin (P-Ins)(73-90) as an immunodominant T cell epitope of HLA-DRB1*0401 (DR4) subjects with beta-islet cell autoimmunity and of HLA-DR4/CD4 double-transgenic mice immunized with human P-Ins. We have compared the fine specificities of one human CD4 T cell clone and two mouse T cell hybridoma clones recognizing this epitope, and, although these three clones all recognized the same core region (LALEGSLQK), there were major differences in how they interacted with the peptide (p)/HLA complex, reflecting the fact that human P-Ins is a foreign antigen in the mouse and an autoantigen in the type 1 diabetes patient. The human T cell clone was forkhead transcription factor 3 (Foxp3)-positive, a marker for regulatory T cell lineages, and secreted predominantly IL-5, IL-10, and low levels of IFNgamma in response to P-Ins(73-90). This finding is compatible with the previously detected regulatory cytokine pattern in subjects with beta-cell autoimmunity. However, added N- or C-terminal amino acids drastically changed HLA and tetramer binding capacity as well as T cell reactivity and the cytokine phenotype of the P-Ins(73-90)-specific human CD4 T cell clone, suggesting a potential for this P-Ins epitope as a target for therapeutic intervention in HLA-DR4-positive humans with beta-islet cell autoimmunity or recent-onset type 1 diabetes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.004 | 0.003 |
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".