Consumption of<i>Buglossoides arvensis</i>seed oil is safe and increases tissue long-chain<i>n</i>-3 fatty acid content more than flax seed oil – results of a phase I randomised clinical trial
Bibliographic record
Abstract
Enrichment of tissues with ≥20-carbon n-3 PUFA like EPA is associated with positive cardiovascular outcomes. Stearidonic acid (SDA; 18 : 4n-3) and α-linolenic acid (ALA; 18 : 3n-3) are plant-derived dietary n-3 PUFA; however, direct comparisons of their impact on tissue n-3 PUFA content are lacking. Ahiflower(®) oil extracted from Buglossoides arvensis seeds is the richest known non-genetically modified source of dietary SDA. To investigate the safety and efficacy of dietary Ahiflower oil, a parallel-group, randomised, double-blind, comparator-controlled phase I clinical trial was performed. Diets of healthy subjects (n 40) were supplemented for 28 d with 9·1 g/d of Ahiflower (46 % ALA, 20 % SDA) or flax seed oil (59 % ALA). Blood and urine chemistries, blood lipid profiles, hepatic and renal function tests and haematology were measured as safety parameters. The fatty acid composition of fasting plasma, erythrocytes, polymorphonuclear cells and mononuclear cells were measured at baseline and after 14 and 28 d of supplementation. No clinically significant changes in safety parameters were measured in either group. Tissue ALA and EPA content increased in both groups compared with baseline, but EPA accrual in plasma and in all cell types was greater in the Ahiflower group (time × treatment interactions, P ≤ 0·01). Plasma and mononuclear cell eicosatetraenoic acid (20 : 4n-3) and docosapentaenoic acid (22 : 5n-3) content also increased significantly in the Ahiflower group compared with the flax group. In conclusion, the consumption of Ahiflower oil is safe and is more effective for the enrichment of tissues with 20- and 22-carbon n-3 PUFA than flax seed oil.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".