Tollip-induced down-regulation of MARCH1
Bibliographic record
Abstract
In addition to their classical antigen presenting functions, MHC class II molecules potentiate the TLR-triggered production of pro-inflammatory cytokines. Here, we have addressed the effect of Tollip and MARCH1 on the regulation of MHC II trafficking and TLR signaling. Our results show that MARCH1-deficient mice splenocytes are impaired in their capacity to produce pro-inflammatory cytokines in response to poly(I:C) and that TLR3 and MHC II molecules interact in the endocytic pathway. Knocking down Tollip expression in human CIITA(+) HeLa cells increased expression of HLA-DR but reduced the proportion of MHC II molecules associated with the CLIP peptide. Truncation of the HLA-DR cytoplasmic tails abrogated the effect of Tollip on MHC class II expression. While overexpression of Tollip did not affect HLA-DR levels, it antagonized the function of co-transfected MARCH1. We found that Tollip strongly reduced MARCH1 protein levels and that the two molecules appear to compete for binding to MHC II molecules. Altogether, our results demonstrate that Tollip regulates MHC class II trafficking and that MARCH1 may represent a new Tollip target.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".