Cancer Chemopreventive and Therapeutic Effects of Diosgenin, a Food Saponin
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
Cancer chemoprevention is a strategy taken to retard, regress, or resist the multistep process of carcinogenesis, including the blockage of its vital morphogenetic milestones viz. normal-preneoplasia-neoplasia-metastasis. For several reasons, including safety, minimal (or no) toxicity and side-effects, and better availability, alternatives such as naturally occurring phytochemicals that are found in foods are becoming increasingly popular over synthetic drugs. Food saponins have been used in complimentary and traditional medicine against a variety of diseases including several cancers. Diosgenin, a naturally occurring steroid saponin found abundantly in legumes and yams, is a well-known precursor of various synthetic steroidal drugs that are extensively used in the pharmaceutical industry. Over the past decade, a series of preclinical and mechanistic studies have been conducted to understand the role of diosgenin as a chemopreventive/therapeutic agent against several cancers. This review highlights the biological activity of diosgenin that contributes to cancer chemoprevention and control. The anticancer mode of action of diosgenin has been demonstrated via modulation of multiple cell signaling events involving critical molecular candidates associated with growth, differentiation, apoptosis, and oncogenesis. Altogether, these preclinical and mechanistic findings strongly implicate the use of diosgenin as a novel, multitarget-based chemopreventive or therapeutic agent against several cancer types. Future research in this field will help to establish not only whether diosgenin is safe and efficacious as a chemopreventive agent against several human cancers, but also to develop and evaluate standards of evidence for health claims for diosgenin-containing foods as they become increasingly popular and enter the marketplace labeled as functional foods and nutraceuticals.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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