Fucoxanthin and Its Metabolite Fucoxanthinol in Cancer Prevention and Treatment
Bibliographic record
Abstract
Fucoxanthin is a carotenoid present in the chloroplasts of brown seaweeds. When ingested, it is metabolized mainly to fucoxanthinol by digestive enzymes of the gastrointestinal tract. These compounds have been shown to have many beneficial health effects, including anti-mutagenic, anti-diabetic, anti-obesity, anti-inflammatory and anti-neoplastic actions. In every cancer tested, modulatory actions of fucoxanthinol on viability, cell-cycle arrest, apoptosis and members of the NF-κB pathway were more pronounced than that of fucoxanthin. Anti-proliferative and cancer preventing influences of fucoxanthin and fucoxanthinol are mediated through different signalling pathways, including the caspases, Bcl-2 proteins, MAPK, PI3K/Akt, JAK/STAT, AP-1, GADD45, and several other molecules that are involved in cell cycle arrest, apoptosis, anti-angiogenesis or inhibition of metastasis. In this review, we address the mechanisms of action of fucoxanthin and fucoxanthinol according to different types of cancers. Current findings suggest that these compounds could be effective for treatment and/or prevention of cancer development and aggressiveness.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".