Evaluation of the Metabolite Profile of Fish Oil Omega-3 Fatty Acids (n-3 FAs) in Micellar and Enteric-Coated Forms—A Randomized, Cross-Over Human Study
Bibliographic record
Abstract
This study evaluated the differences in the metabolite profile of three n-3 FA fish oil formulations in 12 healthy participants: (1) standard softgels (STD) providing 600 mg n-3 FA; (2) enteric-coated softgels (ENT) providing 600 mg n-3 FA; (3) a new micellar formulation (LMF) providing 374 mg n-3 FA. The pharmacokinetics (PKs), such as the area under the plot of plasma concentration (AUC), and the peak blood concentration (Cmax) of the different FA metabolites including HDHAs, HETEs, HEPEs, RvD1, RvD5, RvE1, and RvE2, were determined over a total period of 24 h. Blood concentrations of EPA (26,920.0 ± 10,021.0 ng/mL·h) were significantly higher with respect to AUC0-24 following LMF treatment vs STD and ENT; when measured incrementally, blood concentrations of total n-3 FAs (EPA/DHA/DPA3) up to 11 times higher were observed for LMF vs STD (iAUC 0-24: 16,150.0 ± 5454.0 vs 1498.9 ± 443.0; p ≤ 0.0001). Significant differences in n-3 metabolites including oxylipins were found between STD and LMF with respect to 12-HEPE, 9-HEPE, 12-HETE, and RvD1; 9-HEPE levels were significantly higher following the STD vs. ENT treatment. Furthermore, within the scope of this study, changes in blood lipid levels (i.e., cholesterol, triglycerides, LDL, and HDL) were monitored in participants for up to 120 h post-treatment; a significant decrease in serum triglycerides was detected in participants (~20%) following the LMF treatment; no significant deviations from the baseline were detected for all the other lipid biomarkers in any of the treatment groups. Despite a lower administered dose, LMF provided higher blood concentrations of n-3 FAs and certain anti-inflammatory n-3 metabolites in human participants—potentially leading to better health outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".