Cytotoxic and Antimicrobial Activity of Pseudopterosins and seco-Pseudopterosins Isolated from the Octocoral Pseudopterogorgia elisabethae of San Andrés and Providencia Islands (Southwest Caribbean Sea)
Bibliographic record
Abstract
To expand the potential of pseudopterosins and seco-pseudopterosins isolated from the octocoral Pseudopterogorgia elisabethae of San Andrés and Providencia islands (southwest Caribbean Sea), we report the anti-microbial profile against four pathogenic microorganisms (Staphylococcus aureus, Enterococcus faecalis, Pseudomonas aeruginosa and Candida albicans) and report a more complete cytotoxic profile against five human cells lines (HeLa, PC-3, HCT116, MCF-7 and BJ) for the compounds PsG, PsP, PsQ, PsS, PsT, PsU, 3-O-acetyl-PsU, seco-PsJ, seco-PsK and IMNGD. For the cytotoxic profiles, all compounds evaluated showed moderate and non-selective activity against both tumor and normal cell lines, where PsQ and PsG were the most active compounds (GI₅₀ values between 5.8 μM to 12.0 μM). With respect to their anti-microbial activity the compounds showed good and selective activity against the Gram-positive bacteria, while they did not show activity against the Gram-negative bacterium or yeast. PsU, PsQ, PsS, seco-PsK and PsG were the most active compounds (IC₅₀ 2.9-4.5 μM) against S. aureus and PsG, PsU and seco-PsK showed good activity (IC₅₀ 3.1-3.8 μM) against E. faecalis, comparable to the reference drug vancomycin (4.2 μM).
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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".