Dietary Flavonoids in p53—Mediated Immune Dysfunctions Linking to Cancer Prevention
Bibliographic record
Abstract
The p53 protein plays a central role in mediating immune functioning and determines the fate of the cells. Its role as a tumor suppressor, and in transcriptional regulation and cytokine activity under stress conditions, is well defined. The wild type (WT) p53 functions as a guardian for the genome, while the mutant p53 has oncogenic roles. One of the ways that p53 combats carcinogenesis is by reducing inflammation. WT p53 functions as an anti-inflammatory molecule via cross-talk activity with multiple immunological pathways, such as the major histocompatibility complex I (MHCI) associated pathway, toll-like receptors (TLRs), and immune checkpoints. Due to the multifarious roles of p53 in cancer, it is a potent target for cancer immunotherapy. Plant flavonoids have been gaining recognition over the last two decades to use as a potential therapeutic regimen in ameliorating diseases. Recent studies have shown the ability of flavonoids to suppress chronic inflammation, specifically by modulating p53 responses. Further, the anti-oxidant Keap1/Nrf2/ARE pathway could play a crucial role in mitigating oxidative stress, leading to a reduction of chronic inflammation linked to the prevention of cancer. This review aims to discuss the pharmacological properties of plant flavonoids in response to various oxidative stresses and immune dysfunctions and analyzes the cross-talk between flavonoid-rich dietary intake for potential disease prevention.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".