Low dietary n‐6/n‐3 fatty acid ratio reduce cardiovascular risks in mice regardless of the origin of n‐3 fatty acids
Bibliographic record
Abstract
Background: Health benefits from a low n‐6/n‐3 fatty acid (FA) ratio have been shown. However, the impact of the source of n‐3 FAs has not been fully investigated. The aim of this study was to investigate cardiovascular benefits of diets with a low ratio of n‐6/n‐3 FAs from different sources of n‐3 FAs in C57BL/6 mice. Methods: Twenty‐one C57BL6 mice were divided into 3 groups (n=7) and fed for 16 weeks an atherogenic diet supplemented with either a fish or flaxseed oil‐based ‘designer’ oil with a n‐6/n‐3 FA ratio of 2:1. The control group was fed a safflower oil‐based formulation with a 16:1 ratio of n‐6/n‐3 FAs. Food intake and body weight was recorded. Blood lipids were measured at baseline and every 4 week period. FA profile of the liver and heart were analyzed as well as plasma inflammatory proteins. Results: Both fish and flaxseed oil treated groups had significantly higher food intakes than the control group; however mean body weights did not differ between groups. Compared to controls, plasma triglyceride, cholesterol, IL‐2, IL‐4 and TNF‐α levels as well as the ratio of n‐6/n‐3 FAs of liver phospholipids declined significantly in both treated groups. Conclusion: Our data indicate that lowering dietary ratio of n‐6/n‐3 FAs may significantly reduce cardiovascular risks regardless of the source of n‐3 FAs. Acknowledgements: Supported by NSERC, CIHR, and the Heart and Stroke Foundation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".