Repeated fasting events sensitize enhancers, transcription factor activity and gene expression to support augmented ketogenesis
Bibliographic record
Abstract
Mammals withstand frequent and prolonged fasting periods due to hepatic production of glucose and ketone bodies. Because the fasting response is transcriptionally regulated, we asked whether enhancer dynamics impose a transcriptional program during recurrent fasting and whether this generates effects distinct from a single fasting bout. We found that mice undergoing alternate-day fasting (ADF) respond profoundly differently to a following fasting bout compared to mice first experiencing fasting. Hundreds of genes enabling ketogenesis are 'sensitized' (i.e. induced more strongly by fasting following ADF). Liver enhancers regulating these genes are also sensitized and harbor increased binding of PPARα, the main ketogenic transcription factor. ADF leads to augmented ketogenesis compared to a single fasting bout in wild-type, but not hepatocyte-specific PPARα-deficient mice. Thus, we found that past fasting events are 'remembered' in hepatocytes, sensitizing their enhancers to the next fasting bout and augment ketogenesis. Our findings shed light on transcriptional regulation mediating adaptation to repeated signals.
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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) | 0.002 | 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".