Lemongrass Extract Possesses Potent Anticancer Activity Against Human Colon Cancers, Inhibits Tumorigenesis, Enhances Efficacy of FOLFOX, and Reduces Its Adverse Effects
Bibliographic record
Abstract
Current chemotherapeutics for metastatic colorectal cancers have limited success and are extremely toxic due to nonselective targeting. Some natural extracts have been traditionally taken and have shown anticancer activity. These extracts have multiple phytochemicals that can target different pathways selectively in cancer cells. We have shown previously that lemongrass ( Cymbopogon citratus) extract is effective at inducing cell death in human lymphomas. However, the efficacy of lemongrass extract on human colorectal cancer has not been investigated. Furthermore, its interactions with current chemotherapies for colon cancer is unknown. In this article, we report the anticancer effects of ethanolic lemongrass extract in colorectal cancer models, and importantly, its interactions with FOLFOX and Taxol. Lemongrass extract induced apoptosis in colon cancer cells in a time and dose-dependent manner without harming healthy cells in vitro. Oral administration of lemongrass extract was well tolerated and effective at inhibiting colon cancer xenograft growth in mice. It enhanced the anticancer efficacy of FOLFOX and, interestingly, inhibited FOLFOX-related weight loss in animals given the combination treatment. Furthermore, feeding lemongrass extract to APC min/+ transgenic mice led to the reduction of intestinal tumors, indicating its preventative potential. Therefore, this natural extract has potential to be developed as a supplemental treatment for colorectal cancer.
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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) | 0.000 | 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) | 0.002 | 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".