Sea cucumber and blue mussel: new sources of phospholipid enriched omega-3 fatty acids with a potential role in 3T3-L1 adipocyte metabolism
Bibliographic record
Abstract
Omega (n)-3 polyunsaturated fatty acids (PUFA), namely docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), are known to reduce the risk of insulin resistance and ameliorate obesity-associated disorders. DHA and EPA structured in the phospholipid form possess superior biological effects compared to the triglyceride form available in fish oil. In this study, we have found that sea cucumber (SC) and blue mussel (BM) from Newfoundland and Labrador are rich sources of n-3 PUFA structured in the phospholipid form. Treatment with SC and BM methanolic extracts (250 and 100 μg mL(-1), respectively) significantly (p < 0.01) increased triglyceride accumulation in 3T3-L1 adipocytes, along with an increase in the mRNA expression of the peroxisome proliferator-activated receptor-γ (37 and 39%, respectively) and adiponectin (57 and 56%, respectively) compared with control cells (p < 0.05). Only SC extracts (250 μg mL(-1)) increased the mRNA expression of sterol regulatory element-binding protein-1 (SREBP-1). Treatment with higher concentrations of SC and BM extracts (500 and 750 μg mL(-1), respectively) significantly (p < 0.01) decreased triglyceride accumulation in 3T3-L1 cells as opposed to an increase in triglyceride accumulation at lower concentrations. This was due to inhibition of acetyl-CoA carboxylase-1 and SREBP-1 mRNA expression compared to control cells (p < 0.05). There was no effect of the extracts on the mRNA expression of hormone sensitive lipase or lipolysis, suggesting that the decrease in triglyceride accumulation at higher concentrations is not due to breakdown and release of fat. This is the first report to show that SC and BM are new sources of phospholipid bonded n-3 PUFA, with the potential to target insulin resistance and obesity.
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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) | 0.001 | 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".