Regulation of uncontrolled cell growth (cancer) by curcumin and piperine- A Review
Bibliographic record
Abstract
Cancer is a clinical condition of uncontrolled growth of cells. Today one in six people have been suffering from this life threatening disease. It may be benign (localized) or malignant (spread). Besides the common treatment therapies like surgery, chemotherapy and radiotherapy naturally occurring spices like curcumin, found in turmeric(Curcuma longa) and piperine obtained from black peeper (Piper nigrum L) are getting importance for regulation of cancer proliferation. Curcumin and piperine both have the properties to regulate several intracellular signaling pathways acting as antioxidant and antiproliferative agent. According to literature glucuronidation of curcumin leads to formation of other compound that makes the curcumin unavailable and tend to be excreted in feces. On the other hand, piperine increases bioavailability of curcumin by inhibiting glucuronidation of curcumin in the liver and small intestine. So, using both spices together in food and beverages daily can increase the bioavailability of curcumin that could be blessings for cancer patients. In this paper an initiative has been made to illustrate the functions of both curcumin and piperine in inhibition of cell growth proliferation. The knowledge of this paper may be helpful in bio-medical applications and in formulation of new drug development therapy.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".