Frondoside A of <i>Cucumaria frondosa</i> (Gennerus, 1767): Chemistry, biosynthesis, medicinal applications, and mechanism of actions
Bibliographic record
Abstract
Cucumaria frondosa (Gennerus, 1767) or orange-footed sea cucumbers are traditional food and are used as natural sources of anti-diabetic, anti-inflammatory, antioxidant, anti-angiogenic, antimicrobial, and anticancer agents. Currently, the introduction of value-added sea cucumber products to the global market has inspired basic research on frondoside A and other saponins in sea cucumbers. These saponins serve as a means of their chemical defence. However, recent studies revealed that exposure to these saponins can lead to irritating symptoms from aerosolization of various holothurins. Moreover, extraction methods are critical to the bioavailability of various bioactive compounds found in sea cucumbers. Therefore, we have critically reviewed recent studies on the chemistry, biosynthesis, and pharmacological properties of frondoside A. Furthermore, the mechanism of actions of frondoside A was postulated and further studies are required for applications in functional foods, nutraceuticals, and pharmaceuticals. Frondoside A was first discovered from Cucumaria frondosa, and it is involved in protein kinase (PI3K/AKT/ERK1/2/p38 MAPK, RAC/CDC42 PAK1, NFκB/MAPK/JNK, and LXR-β) signalling pathways. It is also involved in the suppression of MYC oncogene transcriptional factors implicated and upregulated in over 70% of cancer types. Future research needs to be aimed at optimized green extraction techniques, efficient delivery methods, safety, and efficacy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".