Peroxisome proliferator-activated receptor-alpha (PPARα) suppresses T helper 1 (Th1) cytokine production in male mice by inducing post-translational histone modifications at the interferon-gamma (IFNγ) locus (IRM6P.724)
Bibliographic record
Abstract
Abstract Women develop more robust Th1 inflammatory responses than men. Previously, we showed that lower Th1 cytokine responses in males correlated with higher expression of the androgen-sensitive nuclear receptor PPARα, which represses IFNγ production by T cells (Zhang et al. PNAS 2012). The current study aimed to elucidate the molecular mechanism of repression of IFNγ by PPARα in male mouse CD4+ T cells. We first contrasted the expression of various Th-associated genes between anti-CD3 and anti-CD28-stimulated PPARα+/+ (WT) and PPARα-/- (KO) T cells. Of these genes, only T-bet, Eomes, and IFNγ mRNAs were expressed at higher levels in KO vs. WT T cells. Since these genes can reinforce each others’ expression, we further examined their expressions under conditions of either T-bet deficiency or IFNγ neutralization. We found that the higher expressions of T-bet and Eomes were lost, but IFNγ mRNAs remained elevated in KO cells, indicating IFNγ as the likely gene repressed by PPARα. We then performed chromatin immunoprecipitation experiments to examine the abundance of a permissive histone mark (acetylated-H4) and a co-repressor protein (NcoR) at conserved non-coding sequence sites across the ifng locus. We detected global de-repression of ifng in KO vs. WT cells while treating WT cells with a specific agonist induced PPARα recruitment and decreased H4 acetylation at certain sites. Thus, our data suggest that PPARα suppresses IFNγ in males by keeping ifng less poised for transcription.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".