HDAC10 deletion promotes Foxp3+ T-regulatory cell function
Bibliographic record
Abstract
Abstract Foxp3+ T-regulatory (Treg) cells are capable of suppressing immune responses. Lysine acetylation is a key mechanism of post-translational control of various transcription factors, and when acetylated, Foxp3 is stabilized and transcriptionally active. Therefore, understanding the roles of various histone/protein deacetylases (HDAC) are key to promoting Treg-based immunotherapy. Several of the 11 classical HDAC enzymes are necessary for optimal Treg function while others are dispensable. We investigated the effect of HDAC10 in murine Tregs. HDAC10 deletion had no adverse effect on the health of mice, which retained normal CD4+ and CD8+ T cell function. However, HDAC10−/− Treg exhibited increased suppressive function in vitro and in vivo. C57BL/6 Rag1−/− mice adoptively transferred with HDAC10−/− but not wild Treg, were protected from developing colitis. HDAC10−/− but not wild-type mice receiving fully MHC-mismatched cardiac transplants became tolerant and showed long-term allograft survival (>100 d). We conclude that targeting of HDAC10 may be of therapeutic value for inflammatory disorders including colitis and also for transplantation.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".