Plant Polyphenols as Chemopreventive Agents for Lung Cancer
Bibliographic record
Abstract
Lung cancer may be prevented by a diet rich in fruits and vegetables as they are enriched with dietary antioxidant polyphenols, such as flavonoids, proanthocyanidins, lignans, stilbenes, and phenolic acids. Dietary polyphenols exert a wide range of beneficial biological functions beyond their antioxidative properties and are involved in regulation of cell survival pathways leading to anticarcinogenic and antimutagenic functions. There are sufficient evidence from in vitro, in vivo, and epidemiological studies to suggest that the dietary intervention of polyphenols in cancer prevention, including the chemopreventive ability of dietary polyphenols, act against lung carcinogens. Cohort and epidemiological studies in selected risk populations have evaluated clinical effects of polyphenols. Polyphenols have demonstrated three major actions: antioxidative activity, regulation of phase I and II enzymes, and regulation of cell survival pathways against lung carcinogenesis. They have also shown an inverse association of lung cancer occurrences among high risk populations who consumed considerable amounts of fruits and vegetables in their daily diet. In in vitro cell culture experimental models, polyphenols bind with electrophilic metabolites from carcinogens, inactivate cellular oxygen radicals, prevent membrane lipid peroxidation and DNA oxidative damage, and adduct formation. Further, polyphenols enhance the detoxifying enzymes such as the phase II enzymes, glutathione transferases and glucuronosyl transferases.
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.
How this classification was reachedexpand
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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".