<scp>NHR</scp> ‐49/ <scp>HNF</scp> 4 integrates regulation of fatty acid metabolism with a protective transcriptional response to oxidative stress and fasting
Bibliographic record
Abstract
Endogenous and exogenous stresses elicit transcriptional responses that limit damage and promote cell/organismal survival. Like its mammalian counterparts, hepatocyte nuclear factor 4 (HNF4) and peroxisome proliferator-activated receptor α (PPARα), Caenorhabditis elegans NHR-49 is a well-established regulator of lipid metabolism. Here, we reveal that NHR-49 is essential to activate a transcriptional response common to organic peroxide and fasting, which includes the pro-longevity gene fmo-2/flavin-containing monooxygenase. These NHR-49-dependent, stress-responsive genes are also upregulated in long-lived glp-1/notch receptor mutants, with two of them making critical contributions to the oxidative stress resistance of wild-type and long-lived glp-1 mutants worms. Similar to its role in lipid metabolism, NHR-49 requires the mediator subunit mdt-15 to promote stress-induced gene expression. However, NHR-49 acts independently from the transcription factor hlh-30/TFEB that also promotes fmo-2 expression. We show that activation of the p38 MAPK, PMK-1, which is important for adaptation to a variety of stresses, is also important for peroxide-induced expression of a subset of NHR-49-dependent genes that includes fmo-2. However, organic peroxide increases NHR-49 protein levels, by a posttranscriptional mechanism that does not require PMK-1 activation. Together, these findings establish a new role for the HNF4/PPARα-related NHR-49 as a stress-activated regulator of cytoprotective gene expression.
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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 | 0.000 | 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".