PHYTOTHERAPEUTICS FOR CANCER THERAPY
Bibliographic record
Abstract
This chapter examines some of the recent evidence-based scientific information about the contribution of phytotherapeutics for effective cancer management with particular emphasis on results of human clinical trials. It discusses the clinical evidence of effectiveness of phytotherapeutics mainly in relation to the anticancer mechanisms through natural killer (NK) cell enhancement. NK cells play an important role in anticancer immunomodulation. Two commonly used phytotherapeutics, the medicinal mushrooms Lentinula edodes mycelia and Ganoderma lucidum, have been found to elicit their anticancer functions by regulating NK cells. If effects on both NK numbers and toxicity are taken into account, the recommended phytotherapy strategies appear to be Hochu-ekki-to, Shenqi Fuzheng Injection (SFI), and Aidi Injection. The chapter highlights the importance of careful documentation of the clinical effects for both overall survival and quality of life, in relation to potential mechanisms of action for further evidence-based use of selected cancer phytotherapeutics.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.010 |
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".