Phloretin Inhibits Phorbol Ester–Induced Tumor Promotion and Expression of Cyclooxygenase-2 in Mouse Skin: Extracellular Signal-Regulated Kinase and Nuclear Factor-κB as Potential Targets
Bibliographic record
Abstract
The present study investigated the effect of phloretin [2',4',6'-trihydroxy-3-(4-hydroxyphenyl)-propiophenone] on 12-O-tetradecanoylphorbol 13-acetate (TPA)-induced cyclooxygenase-2 (COX-2) expression and tumor promotion in mouse skin and explored the underlying molecular mechanisms. Topical application of phloretin significantly inhibited 7,12-dimethylbenz[a]anthracene-initiated and TPA-promoted mouse skin carcinogenesis. Pretreatment with phloretin on the dorsal skin of mice inhibited TPA-induced COX-2 expression in a dose-dependent manner. To elucidate the molecular mechanism underlying COX-2 inhibition by phloretin, we examined its effect on TPA-induced activation of nuclear factor-κB (NF-κB), a ubiquitous transcription factor responsible for TPA-induced COX-2 expression in mouse skin. Topically applied phloretin decreased the TPA-induced DNA binding of NF-κB. In addition, phloretin inhibited the phosphorylation as well as the catalytic activity of extracellular signal-regulated kinase (ERK), which was previously found to activate NF-κB and induce COX-2 expression in TPA-treated mouse skin. Taken together, the inhibitory effects of phloretin on TPA-induced NF-κB activation and COX-2 expression through the modulation of ERK signaling may partly account for its antitumor-promoting effect on mouse skin carcinogenesis.
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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) | 0.001 | 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".