Evaluation of the Efficacy of Dandelion Root and Lemongrass Extracts on Prostate Cancer
Why this work is in the frame
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Bibliographic record
Abstract
Current conventional approaches to cancer treatment have proven effective in treating many patients but have been shown to inadvertently cause severe side effects including organ damage and toxicity. Natural health products (NHPs) are generally plant-based products that have been shown to have some form of medicinal properties. Many chemotherapeutic compounds, such as taxol (from paclitaxel) have been derived from NHPs. NHPs have a potential to be an alternative to chemotherapeutic drugs. Indeed, some NHPs have been shown to have high anti-cancer efficacy, with minimal side effects. In addition, because many NHPs are well tolerated, they may be given over a long treatment periods and can be used as a preventative treatment. Previously, our lab has shown anti-cancer efficacy of dandelion root extract (DRE) in leukemia and colon cancer, and lemongrass extract in colon cancer. Furthermore, the interaction of these NHPs with currently used chemotherapies is not known. Our objective was to analyze the anti-cancer properties of DRE and lemongrass extracts on human prostate cancer. This was done by examining the efficacy of these extracts in vitro by assessing the viability, proliferation, and cell death of treated prostate cancer cells and in vivo on tumour xenographed mice models. In addition, we assessed if any drug-drug interactions exist in treatments of NHPs in combination with commonly used chemotherapeutics such as taxol (paclitaxel) and mitoxantrone. Preliminary results have shown that DRE and lemongrass extract treatments show anti-cancer efficacy and show neutral to positive synergy between NHP treatment and chemotherapeutics. If successful, this research has the potential to be developed into safer anti-cancer agents and possibly brought to market for human use.
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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 | 0.001 |
| 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) | 0.001 | 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 it