Effects of Ursolic Acid on Colorectal Cancer: A Review of Recent Evidence
Bibliographic record
Abstract
Colorectal cancer is the third leading cause of cancer-related deaths, and the five-year survival rate of the metastatic disease is less than 15%. Treatment approaches include surgery, systemic chemotherapy and radiotherapy. The aggressive nature and low five-year survival rate of metastatic colorectal cancer indicate a need for new treatment options to help combat this disease. Ursolic acid is a pentacyclic triterpenoid naturally occurring in many plants, with high concentrations found in cranberries. This review summarizes evidence from the last ten years of the effects of ursolic acid on colorectal cancer. Overall, the available studies indicate that the treatment of colon cancer cells with ursolic acid results in a significant inhibition of proliferation and induction of apoptosis. In addition, the limited in vivo studies indicate a significant reduction in tumor volume and tumor angiogenesis in animal models of colorectal cancer administered ursolic acid. More in vivo animal studies are required to better understand the potential anticancer properties of ursolic acid and to form the basis for human clinical trials.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".