Antioxidant, Antibacterial, and Antifungal Characteristics on Crude Collagen Extracts of Sea Cucumber (Stichopus hermanii)
Bibliographic record
Abstract
Stichopus hermanii is a species of sea cucumber commonly found in the western Indo-Pacific region and has been extensively utilized by local communities for commercial purposes and health benefits.This study aims to evaluate the antioxidant, antibacterial, antifungal, and SPF properties of crude collagen extracted from Stichopus hermanii.The research methodology included extraction processes using an ethyl acetate solution, measurement of antioxidant activity through the DPPH method, antibacterial and antifungal testing using the paper disc diffusion method, and SPF value measurement through UV-Vis spectrophotometry.Results indicated that a crude collagen yield of 3.75% was successfully obtained from the golden sea cucumber.The crude collagen extract of the golden sea cucumber exhibited antioxidant activity categorized as strong, with an IC50 value of 56.82 µg/mL.The percentage of inhibition was directly proportional to the extract concentration.Antibacterial activity against E. coli and S. aureus was observed only in extracts at a concentration of 2000 µg/disc, with clear zones of 6.3±0.1 mm and 5.4±0.01 mm, respectively, at the end of the study.The collagen extract exhibited antifungal activity against C. albicans at a concentration of 500 µg/disc with a clear zone diameter of 17.2±1.6mm at the end of the study, while no antifungal activity was observed against the test pathogen Trichoderma sp.The SPF value of the collagen extract was low, ranging from 0.2 to 1.46.The crude collagen extract from the golden sea cucumber Stichopus hermanii demonstrated potential as an antioxidant, antifungal, and antibacterial agent.
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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 | 0.001 | 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".