Inhibition of Cell Proliferation and Cell Viability by Sinecatechins in Cutaneous SCC Cells Is Related to an Imbalance of ROS and Loss of Mitochondrial Membrane Potential
Bibliographic record
Abstract
The term sinecatechins designates an extract containing a high percentage of catechins obtained from green tea, which is commercially registered as Veregen or Polyphenon E (PE) and may be considered for treatment of cutaneous squamous cell carcinoma (cSCC) and actinic keratosis (AK). As shown here, treatment of four cSCC cell lines with 200 µg/mL of PE resulted in strong, dose-dependent decrease in cell proliferation (20-30%) as well as strongly decreased cell viability (4-21% of controls, 48 h). Effects correlated with loss of mitochondrial membrane potential, whereas early apoptosis was less pronounced. At the protein level, some activation of caspase-3 and enhanced expression of the CDK inhibitor p21 were found. Loss of MMP and induced cell death were, however, largely independent of caspases and of the proapoptotic Bcl-2 proteins Bax and Bak, suggesting that sinecatechins induce also non-apoptotic, alternative cell death pathways, in addition to apoptosis. Reactive oxygen species (ROS) were downregulated in response to PE at 4 h, followed by an increase at 24 h. The contributory role of initially reduced ROS was supported by the antioxidant N-acetyl cysteine, which in combination with PE further enhanced the negative effects on cell viability. Thus, sinecatechins inhibited cell proliferation and viability of cSCC cells, which could suggest the use of PE for AK treatment. The mechanisms appear as linked to an imbalance of ROS levels.
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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".