Red algal cellular biomass lowers circulating cholesterol concentrations in Syrian golden hamsters consuming hypercholesterolaemic diets
Bibliographic record
Abstract
Preliminary evidence suggests that consumption of Porphyridium cruentum (PC) biomass results in hypocholesterolaemic effects; however, mechanisms responsible have not been elucidated. The aim of the present study was to determine whether PC biomass lowers circulating cholesterol concentrations, dose dependently, in hamsters fed hypercholesterolaemic diets for 28 d and determine whether cholesterol biosynthesis is affected. Biomass added to diets at 2.5, 5 and 10% resulted in 14, 38 and 53% reductions (P < 0.001) in total plasma cholesterol, respectively, compared with a control diet. Similarly, non-HDL-cholesterol concentrations in the 5 and 10% PC groups were reduced (P < 0.001) 28 and 45%, respectively, v. controls. These effects were unrelated to cholesterol fractional synthesis rate (FSR), as this did not differ between either treatment or control animals. PC consumption had no effect on food intake, plasma glucose concentrations or energy expenditure, but percentage of body fat was lower (P < 0.001) in the 5 and 10% PC groups compared with controls. These data show that PC reduces total plasma cholesterol and non-HDL-cholesterol when incorporated into the diet at levels as low as 2.5%. The mechanism of action for this reduction may be related to increased excretion since food intakes and cholesterol FSR were not reduced in the animals receiving the PC. In conclusion, the use of PC biomass reduces circulating cholesterol, dose dependently, in hypercholesterolaemic hamsters but not via reductions in cholesterol FSR. There is potential for the use of this biomass as a functional ingredient to aid in the management of blood cholesterol concentrations.
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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) | 0.001 | 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 | 0.001 |
| 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".