Fishing for Targets of Alien Metabolites: A Novel Peroxisome Proliferator-Activated Receptor (PPAR) Agonist from a Marine Pest
Bibliographic record
Abstract
Although the chemical warfare between invasive and native species has become a central problem in invasion biology, the molecular mechanisms by which bioactive metabolites from invasive pests influence local communities remain poorly characterized. This study demonstrates that the alkaloid caulerpin (CAU)—a bioactive component of the green alga Caulerpa cylindracea that has invaded the entire Mediterranean basin—is an agonist of peroxisome proliferator-activated receptors (PPARs). Our interdisciplinary study started with the in silico prediction of the ligand-protein interaction, which was then validated by in vivo, ex vivo and in vitro assays. On the basis of these results, we candidate CAU as a causal factor of the metabolic and behavioural disorders observed in Diplodus sargus, a native edible fish of high ecological and commercial relevance, feeding on C. cylindracea. Moreover, given the considerable interest in PPAR activators for the treatment of relevant human diseases, our findings are also discussed in terms of a possible nutraceutical/pharmacological valorisation of the invasive algal biomasses, supporting an innovative strategy for conserving biodiversity as an alternative to unrealistic campaigns for the eradication of invasive pests.
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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".