Capsaicin induces de-differentiation of activated hepatic stellate cell
Bibliographic record
Abstract
Hepatic stellate cells (HSC) play a key role in liver fibrogenesis. Activation of PPARγ and inhibition of fibrogenic molecules are potential strategies to block HSC activation and differentiation. A number of natural products have been suggested to have antifibrotic effects for the de-activation and de-differentiation of HSCs. The purpose of this study was to investigate the in vitro effects of capsaicin on HSC de-activation and de-differentiation. The results demonstrated that capsaicin induced quiescent phenotype in GRX via PPARγ activation. Significant decrease in COX-2 and type I collagen mRNA expression was observed in the first 24 h of treatment. These events preceded the reduction of TGF-β1 and total collagen secretion. Thus, capsaicin promoted down-regulation of HSC activation by its antifibrotic and anti-inflammatory actions. These findings demonstrate that capsaicin may have potential as a novel therapeutic agent for the treatment of liver fibrosis.
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) | 0.000 | 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".