Antibacterial and Enzymatic Activities of Symbiotic Bacteria from Gastropods and Bivalves in Marine Skincare Applications
Bibliographic record
Abstract
Marine symbiotic bacteria found in mollusks from the seagrass and coral reef ecosystem have shown potential as skincare products, specifically to treat acne.This study aimed to investigate the antibacterial and enzyme-producing abilities of these bacteria for their potential as natural cosmetic ingredients.Symbiotic bacteria were isolated from bivalves and gastropods collected from Padak Brambang, Lombok, West Nusa Tenggara, Indonesia.The isolates were tested against Cutibacterium acnes, Staphylococcus aureus, and Staphylococcus epidermidis for antibacterial activity using the disc diffusion method, and lipase and protease enzymes were detected.The top isolates, G4LC2.3 and G8LM2.4,showed strong antibacterial activity, while B4KS2.3 and G2LA2.1 demonstrated high enzyme production.Pseudomonas aeruginosa, Vibrio diabolicus, and Vibrio owensii were identified as potential species for use in cosmetics.Analysis of the bacterial compounds revealed potential ingredients such as 1-pyrroline-5-carboxylic acid, succinic acid, and dihydropinosylvin methyl ether in P. aeruginosa, and 5-hydroxy-3-(4-hydroxyphenyl)-4-phenylpyrrol-2-one, fuculose, and 2-hydroxy-5-[(1e,3z,5e,7r,8r,9e)-8-hydroxy-7,9,12-trimethyltrideca-1,3,5,9-tetraen-1-yl]-2,4dimethylfuran-3-one in V. diabolicus and V. owensii.These findings suggest that symbiotic bacteria from mollusks can be used as environmentally friendly and effective natural ingredients in marine skincare applications.The study highlighted the potential of these isolates for cosmetic use.
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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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".