Hitting the Golden TORget: Curcumin’s Effects on mTOR Signaling
Bibliographic record
Abstract
The polyphenol natural product curcumin possesses a plethora of biological and pharmacological properties. For years, much interest has been placed in the development and use of curcumin and its derivatives for the prevention and treatment of cardiovascular, diabetic, and neurodegenerative diseases, as well as cancer. Increasing evidence suggests that curcumin displays amazing molecular versatility, and the number of its proposed cellular targets grows as the research continues. The mammalian target of rapamycin (mTOR) is a master kinase, regulating cell growth/proliferation, survival, and motility. Dysregulated mTOR signaling occurs frequently in cancer, and targeting mTOR signaling is a promising strategy for cancer therapy. Recent studies have identified mTOR as a novel target of curcumin. Here we focus on reviewing current knowledge regarding the effects of curcumin on mTOR signaling for better understanding the anticancer mechanism of curcumin. The emerging studies of mTOR signaling and clinical studies on curcumin with cancer patients are also discussed here.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".