HLA-DO promotes bacterial superantigen binding to MHC class II molecules (106.27)
Bibliographic record
Abstract
Abstract HLA-DO (H2-O in mice) is an intracellular non-classical MHC class II molecule. It forms a stable complex with HLA-DM (H2-M in mice) and by regulating its activity shapes the peptide repertoire. Using a stable cell line overexpressing HLA-DO (HeLa-CIITA-DO), we show here that HLA-DO improved binding of SEA and TSST-1 superantigens (SAgs) to MHC class II molecules. Binding of SEB was not affected in these conditions. Exogenous pulsing of Class II-associated invariant chain peptide (CLIP) elucidate that CLIP is a major player in this process. Accordingly, HLA-DO knock-down using specific siRNA, decreased SEA and TSST-1 binding in HeLa-CIITA-DO cells. Furthermore, silencing of DM increased SEA and TSST-1 binding in HeLa-CIITA and 293-CIITA cells. Shutting down of Ii reversely decreased binding of SEA and TSST-1 in 293-CIITA cells. However, in HeLa-CIITA, Ii depletion just decreased SEA binding but does not affect TSST-1 binding. H2-O did not show the same boosting effect on SAgs binding in splenocytes. In conclusion, our results show that HLA-DO can improve SEA and TSST-1 binding in line with a role for CLIP in SAgs binding.
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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) | 0.003 | 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".