The Role of Natural Chalcones and Their Derivatives in Targeting Prostate Cancer: Recent Updates
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
Prostate cancer (PCa) is the second most prevalent cancer among men and a major cause of cancer-related mortality worldwide. Despite an initial favorable response to hormone-based therapies, many patients ultimately develop an advanced and lethal form of the disease, referred to as castration-resistant PCa (CRPC). CRPC is associated with poor prognosis and a lack of effective curative treatments. As a result, new alternatives or improved therapeutic strategies to combat this life-threatening condition are urgently needed. Chalcones, also referred to as 1,3-diphenyl-2-propen-1-ones, have attracted significant attention because of their potent antitumor properties. Owing to their distinctive chemical structure and diverse biological activities, these compounds are promising candidates for treating various cancers, including PCa. Both naturally occurring and synthetically derived chalcones have demonstrated anticancer potential by modulating key cellular processes, including apoptosis, cell cycle regulation, cell migration, invasion, metastasis and angiogenesis, as well as major signaling pathways, such as PI3K/Akt/mTOR, androgen signaling, and NF-κB. This review aims to outline the recent advances in the therapeutic potential of chalcone derivatives in prostate cancer, with a focus on their molecular targets, mechanisms of action, and translational relevance.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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