Anti-Cancer Properties of Theaflavins
Bibliographic record
Abstract
Cancer is a disease characterized by aberrant proliferative and apoptotic signaling pathways, leading to uncontrolled proliferation of cancer cells combined with enhanced survival and evasion of cell death. Current treatment strategies are sometimes ineffective in eradicating more aggressive, metastatic forms of cancer, indicating the need to develop novel therapeutics targeting signaling pathways which are essential for cancer progression. Historically, plant-derived compounds have been utilized in the production of pharmaceuticals and chemotherapeutic compounds for the treatment of cancer, including paclitaxel and docetaxel. Theaflavins, phenolic components present in black tea, have demonstrated anti-cancer potential in cell cultures in vitro and in animal studies in vivo. Theaflavins have been shown to inhibit proliferation, survival, and migration of many cancer cellswhile promoting apoptosis. Treatment with theaflavins has been associated with increased levels of cleaved poly (ADP-ribose) polymerase (PARP) and cleaved caspases-3, -7, -8, and -9, all markers of apoptosis, and increased expression of the proapoptotic marker Bcl-2-associated X protein (Bax) and concomitant reduction in the antiapoptotic marker B-cell lymphoma 2 (Bcl-2). Additionally, theaflavin treatment reduced phosphorylated Akt, phosphorylated mechanistic target of rapamycin (mTOR), phosphatidylinositol 3-kinase (PI3K), and c-Myc levels with increased expression of the tumour suppressor p53. This review summarizes the current in vitro and in vivo evidence available investigating the anti-cancer effects of theaflavins across various cancer cell lines and animal models.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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 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".