The Circadian Clock Controls Hepatic Stellate Cell Activation in Liver Fibrosis via a BMAL1/CK1ε/REV-ERBα/Transgelin Signaling Pathway
Bibliographic record
Abstract
ABSTRACT Liver fibrosis is a progressive and life-threatening condition with no effective targeted treatments. Growing evidence indicates a two-way relationship between circadian rhythm and fibrogenesis, although the specific molecular signaling pathways involved are still not well understood. The molecular clock, which governs circadian rhythms, regulates metabolic and cellular functions, and its pharmacological manipulation has shown potential as a therapy for organ fibrosis. Although the liver’s molecular clock appeared resilient to the progression of chronic liver disease in humans from steatosis to fibrosis, detectable changes in the daily amplitude of clock genes were observed in a cohort of people living with obesity. We discovered a clock-controlled signaling pathway that drives hepatic stellate cell (HSC) activation, a key event in fibrosis progression. Interfering with this pathway, either by disrupting the core regulator CLOCK:BMAL1 or activating the nuclear receptors REV-ERBs, significantly reduced HSC activation. We also identified transgelin as the downstream effector of clock-regulated HSC contractility, a characteristic of HSC activation. Transgelin is regulated indirectly by a BMAL1-CK1ε signaling pathway and directly by REV-ERBα. Our findings identify a previously unknown circadian-controlled mechanism that links the molecular clock to HSC activation and cell contractile function, which is relevant to human diseases. This pathway provides several entry points for drugs to target and disrupt fibrogenic signaling. By connecting clock biology to the cellular processes that cause fibrosis, our work also offers a mechanistic basis for chronotherapeutic strategies against chronic liver disease.
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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) | 0.001 | 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".