Octahydrocurcumin, a final hydrogenated metabolite of curcumin, possesses superior anti-tumor activity through induction of cellular apoptosis
Bibliographic record
Abstract
The biological activity of curcumin (CUR), a promising naturally occurring dietary compound for the treatment of hepatocellular carcinoma (HCC), was closely associated with its metabolite. Octahydrocurcumin (OHC) is the final hydrogenated metabolite of CUR and has been reported to have potential biological activities. However, difficulties in access have hampered its biological studies. In the current investigation, we designed an efficient synthesis method to produce OHC, and comparatively explored the anti-cancer effect and potential mechanism of OHC and CUR in an H22 ascites tumor-bearing mice model. The results indicated that OHC had a relatively wide margin of safety, and exhibited superior effects to CUR in suppressing the tumor growth, including ascending weight, abdominal circumference, ascites volume and cancer cell viability. OHC significantly induced H22 cell apoptosis by upregulating the p53 expression and downregulating the MDM2 expression. OHC also remarkably decreased the Bcl-2 and Bcl-xl protein expressions, and increased the Bax and Bad expressions in ascitic cells. Furthermore, THC substantially induced the release of cytochrome C, caspase-3, caspase-9 and the cleavage of PARP to induce H22 cell apoptosis. Taken together, OHC was more effective than CUR in suppressing H22-induced HCC through the activation of the mitochondrial apoptosis pathway. OHC may thus be a promising anti-HCC agent.
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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".