Sterol Composition of Blue Mussels Fed Algae and Effluent Diets from Finfish Culture
Bibliographic record
Abstract
Mussels are an excellent source of phytosterols, which have many health benefits including reduction of the level of cholesterol in the blood. This study examined free sterols in cultivated blue mussels obtained commercially and from laboratory feeding experiments. Mussels were fed algae or the effluent from cultured finfish for 6 mo, and others remained unfed for 10 wk. Mussels feeding on effluent is of interest for integrated multitrophic aquaculture. Fish waste-fed mussels had significantly higher cholesterol concentrations (710 mg/kg) compared with algae-fed mussels (409 mg/kg) and locally cultivated ones (321 mg/kg). Algae-fed mussels had significantly higher campesterol compared with locally cultivated and fish waste-fed mussels. In algae-fed mussels, 24-nordeydrocholesterol decreased significantly, and in fish waste-fed mussels, the concentration of 24-methylenecholesterol decreased significantly. In fish waste-fed mussels, the cholesterol proportion was 50.9% of total sterols and other beneficial sterols were 49.1%, whereas in algae-fed mussels, cholesterol was down to 36.7% and other sterols were 63.3%. In summary, fish waste-fed mussels had significantly higher cholesterol concentrations and proportions compared with locally cultivated and algaefed mussels, and algae-fed mussels had higher proportions of beneficial phytosterols than fish waste-fed mussels.
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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".