Enzyme-Assisted Extraction of Bioactive Material from Chondrus crispus and Codium fragile and Its Effect on Herpes simplex Virus (HSV-1)
Bibliographic record
Abstract
Codium fragile and Chondrus crispus are, respectively, green and red seaweeds which are abundant along the North Atlantic coasts. We investigated the chemical composition and antiviral activity of enzymatic extracts of C. fragile (CF) and C. crispus (CC). On a dry weight basis, CF consisted of 11% protein, 31% neutral sugars, 0.8% sulfate, 0.6% uronic acids, and 49% ash, while CC contained 27% protein, 28% neutral sugars, 17% sulfate, 1.8% uronic acids, and 25% ash. Enzyme-assisted hydrolysis improved the extraction efficiency of bioactive materials. Commercial proteases and carbohydrases significantly improved (p ≤ 0.001) biomass yield (40%-70% dry matter) as compared to aqueous extraction (20%-25% dry matter). Moreover, enzymatic hydrolysis enhanced the recovery of protein, neutral sugars, uronic acids, and sulfates. The enzymatic hydrolysates exhibited significant activity against Herpes simplex virus (HSV-1) with EC50 of 77.6-126.8 μg/mL for CC and 36.5-41.3 μg/mL for CF, at a multiplicity of infection (MOI) of 0.001 ID50/cells without cytotoxity (1-200 μg/mL). The extracts obtained from proteases (P1) and carbohydrases (C3) were also effective at higher virus MOI of 0.01 ID50/cells without cytotoxity. Taken together, these results indicate the potential application of enzymatic hydrolysates of C. fragile and C. crispus in functional food and antiviral drug discovery.
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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 | 0.000 | 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) | 0.000 | 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".