Resveratrol: Biological and pharmaceutical properties as anticancer molecule
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
There is ample evidence that shows an inverse relationship between consumption of fruit/vegetable-rich diets and the risk of cancer at various anatomical sites. In this review, we will assess and summarize recent advances on cancer prevention by resveratrol, a natural stilbenoid present in red grapes, peanuts, some common drinks, and dietary supplements. We will focus on data published within the past few years on in vivo model tumor animal studies that reinforce the chemopreventive efficacy of resveratrol against a multitude of cancers, as well as on its sensitization/enhancing activities against tumor cells when used in combination with established chemotherapeutic and pharmaceutical agents. In addition, we will review examples resveratrol-target proteins, denoted RTPs, including the 24-kDa cytosolic protein quinone reductase 2 (NQO2) discovered in our laboratory that may confer resveratrol responsiveness to cancer cells. We will discuss the possible role of NQO2 in mediating cancer prevention by resveratrol. Our analysis of published data strengthen support that resveratrol displays novel roles in various cellular processes, and help to establish an expanded molecular framework for cancer prevention by resveratrol in vivo.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it