Paradise Tree Extract (Simarouba glauca) Selectively Induces Cell Death, Enhances Efficacy of Common Chemotherapeutics and Reduces Their Toxicity in In-Vitro and In-Vivo Models of Breast Cancer
Bibliographic record
Abstract
Background: Although chemotherapeutics have proven to be effective in treating metastatic breast cancer, their limited target selectivity has resulted in adverse side effects, rendering them unsuitable for long-term usage. Alternatively, certain natural extracts provide a promising strategy to selectively target cancer while being safe to consume. Specifically, paradise tree (Simarouba glauca) has shown potential anti-tumour activity; however, its efficacy against cancer, mechanism of action, and interaction with standard chemotherapies have not been investigated. Method: We have demonstrated the anti-tumour activity of ethanolic paradise tree extract (PTE) in triple-negative and ER-positive breast cancer cell lines and its interaction with chemotherapeutics when used in combination. The anti-tumour efficacy of PTE was evaluated through the expression of apoptotic biochemical markers as well as changes in cell morphology. For mechanistic studies, fluorogenic dyes were used to quantify reactive oxygen species production and mitochondrial membrane potential destabilization. Results: Our results have shown that PTE selectively triggers apoptosis in breast cancer cells while having limited effects on noncancerous cells. Importantly, we have found that PTE enhances the anti-tumour efficacy of chemotherapeutics, cisplatin and Taxol, when given in combination, while reducing their toxicity in noncancerous cells. Furthermore, PTE inhibits growth of human tumour xenografts in immunocompromised mice. Importantly, PTE in combination with Taxol and cisplatin had the best anti-tumour effect. Conclusion: Our findings suggest that PTE could be a safe and effective treatment for breast cancer. Most importantly, as a supplement to chemotherapeutic regimens, it could enhance anti-tumour effects and reduce chemo-related toxicity.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".