Potential phytochemicals in the fight against skin cancer: Current landscape and future perspectives
Bibliographic record
Abstract
Skin cancer is a life threatening disease and their prevalence and risk has been increasing over the past three decades causing significant loss to human health worldwide. Mostly skin cancer has developed resistance against chemotherapy and radiotherapy. Therefore, development of novel, cost effective and efficient treatment methods are needed. Phytochemicals extracted from medicinal plants and dietary sources are often biologically active and has attracted the attention of researchers and pharmaceutical industries around the world. Many in vitro and in vivo studies of these bioactive compounds have shown potential antioxidant, anti-proliferative, anti-inflammatory and anti-angiogenic effects in the fight against skin cancer. These phytochemicals also regulate several other molecular processes such as angiogenesis, metastasis and cell cycle to combat skin cancer. The present review provides perspectives on the key phytochemicals, their therapeutic potentials, bioavailability and molecular mechanism of action in the cancer therapeutics. Current challenges and future directions for research are also critically discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".