Regulation of dendritic cell function and autoimmunity by microRNA-155 (83.29)
Bibliographic record
Abstract
Abstract While many of the mechanisms that control self tolerance in the immune system have been discovered, there are many unanswered questions in understanding the molecular mechanisms that maintain immunological quiescence. The studies outlined here aims to examine how a newly discovered class of small RNA molecules called micro-RNA control one of the checkpoints limiting autoimmunity, namely the maturation state of dendritic cells. Micro-RNA are a class of non-protein coding RNA that act by binding the 3’ UTR end of messenger RNA and inhibiting translation. We have evidence implicating that one specific micro-RNA, miR-155, plays a role in maintaining self-tolerance in the immune system. We find that miR-155 levels increase in dendritic cells after maturation induced by TLR stimulation. In a new murine model of autoimmune diabetes developed in our lab, dendritic cells lacking miR-155 are unable to break immune tolerance to pancreatic islet cells antigens. Using this model we will investigate whether the lack of miR-155 in dendritic cells affects the induction and expansion of cytotoxic T lymphocytes as well as the pro-inflammatory response. Furthermore, we will also explore the targets that are regulated by miR-155 that mediate the induction of autoimmunity.
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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".