Advances in the Research and Development of Natural Health Products as Main Stream Cancer Therapeutics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Natural health products (NHPs) are defined as natural extracts containing polychemical mixtures; they play a leading role in the discovery and development of drugs, for disease treatment. More than 50% of current cancer therapeutics are derived from natural sources. However, the efficacy of natural extracts in treating cancer has not been explored extensively. Scientific research into the validity and mechanism of action of these products is needed to develop NHPs as main stream cancer therapy. The preclinical and clinical validation of NHPs would be essential for this development. This review summarizes some of the recent advancements in the area of NHPs with anticancer effects. This review also focuses on various NHPs that have been studied to scientifically validate their claims as anticancer agents. Furthermore, this review emphasizes the efficacy of these NHPs in targeting the multiple vulnerabilities of cancer cells for a more selective efficacious treatment. The studies reviewed here have paved the way for the introduction of more NHPs from traditional medicine to the forefront of modern medicine, in order to provide alternative, safer, and cheaper complementary treatments for cancer therapy and possibly improve the quality of life of cancer patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it