Antiproliferative effect of catechin in GRX cells
Bibliographic record
Abstract
The phenolic compounds present in cocoa seeds have been studied regarding health benefits, such as antioxidant and anti-inflammatory activities. Fibrosis is a wound healing response that occurs in almost all patients with chronic liver injury. A large number of cytokines and soluble intercellular mediators are related to changes in the behavior and phenotype of the hepatic stellate cell (HSC) that develop a fibrogenic and contractile phenotype leading to the development of fibrosis. The objective of this study was to assess the catechin effect in GRX liver cells in activities such as cell growth and inflammation. The GRX cells treatment with catechin induced a significant decrease in cell growth. This mechanism does not occur by apoptosis or even by autophagy because there were no alterations in expression of caspase 3 and PARP (apoptosis), and LC3 (autophagy). The expression of p27 and p53 proteins, regulators of the cell cycle, showed increased expression, while COX-2 and IL-6 mRNA showed a significant decrease in expression. This study shows that catechin decreases cell growth in GRX cells and, probably, this decrease does not occur by apoptosis or autophagy but through an anti-inflammatory effect and cell cycle arrest. Catechin also significantly decreased the production of TGF-β by GRX cells, showing a significant antifibrotic effect.
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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 | 0.000 |
| 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".