Effects of cyclic fatty acids on rat liver and plasma fatty acid metabolism and inflammation mediators depend on dietary lipids
Bibliographic record
Abstract
Objective This study aimed to determine the interactions between dietary fatty acids and cyclic fatty acid monomers (CFAM) on liver and plasma lipids and inflammation Methods Two oils (canola oil and soybean oil) were used in the experiment while 0.5% of CFAM were added to the CFAM diets, thus generating four diet groups: canola oil (CO), soybean oil (SO), canola oil and CFAM (CC), and soybean oil and CFAM (SC). 36 male Wistar rats ( n=9 ) were fed those diets for 28 days, liver and plasma lipids were analyzed by gas‐liquid chromatography and inflammation markers were analyzed enzymatic methods. Results Although CFAM alone induced an accumulation of TAG, liver fatty acid analysis showed that rats fed the CC diet had less stearic acid (STA), arachidonic acid (ARA), and docosahexaenoic acid (DHA) but more oleic acid (OLA) and total MUFA than those fed the CO, SO and SC diets. However, no difference was observed between rats fed SO and SC diets. Significant interactions between the type of oil and CFAM were also observed in plasma fatty acids for the following fatty acids: palmitic acid (PAM, P = 0.039), linoleic acid (AL, P = 0.023), docosapentaenoic acid (DPAn‐3 P<0.0001), and total PUFAn‐3 (P = 0.028). In particular, it was observed that CC‐fed rats had less AL than the SC (P<0.0001). CFAM induced lower ALT levels (P<0.0001), lower ALT/AST ratio (P = 0.003), and higher plasma total cholesterol levels (P = 0.024) compared with the non‐CFAM diets. There were interactions between oil and CFAM for plasma AST (P = 0.04), AST/ALT ratio (P = 0.02), and IL‐6 (P = 0.02). Conclusions While showing that CFAM effects on lipid metabolism are exacerbated when used with a high‐oleic acid oil, these results suggest that CFAM effects are altered by dietary lipids. These results reinforce the need for a selected use of vegetable oils in domestic and industrial settings. Other associations of CFAM with oils of different ratios MUFA/PUFA, PUFAn‐6/n‐3, PUFA/SFA can be used to further assess the interactions between CFAM and dietary fats. Support or Funding Information Canadian Natural Sciences and Engineering Research Council
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) | 0.000 | 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) | 0.002 | 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".