Anticancer Activity of Sea Cucumber Triterpene Glycosides
Bibliographic record
Abstract
Triterpene glycosides are characteristic secondary metabolites of sea cucumbers (Holothurioidea, Echinodermata). They have hemolytic, cytotoxic, antifungal, and other biological activities caused by membranotropic action. These natural products suppress the proliferation of various human tumor cell lines in vitro and, more importantly, intraperitoneal administration in rodents of solutions of some sea cucumber triterpene glycosides significantly reduces both tumor burden and metastasis. The anticancer molecular mechanisms include the induction of tumor cell apoptosis through the activation of intracellular caspase cell death pathways, arrest of the cell cycle at S or G2/M phases, influence on nuclear factors, NF-κB, and up-down regulation of certain cellular receptors and enzymes participating in cancerogenesis, such as EGFR (epidermal growth factor receptor), Akt (protein kinase B), ERK (extracellular signal-regulated kinases), FAK (focal adhesion kinase), MMP-9 (matrix metalloproteinase-9) and others. Administration of some glycosides leads to a reduction of cancer cell adhesion, suppression of cell migration and tube formation in those cells, suppression of angiogenesis, inhibition of cell proliferation, colony formation and tumor invasion. As a result, marked growth inhibition of tumors occurs in vitro and in vivo. Some holothurian triterpene glycosides have the potential to be used as P-gp mediated MDR reversal agents in combined therapy with standard cytostatics.
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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) | 0.001 | 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".