Effect of dietary conjugated linoleic acid isomers on lipid metabolism in hamsters fed high-carbohydrate and high-fat diets
Bibliographic record
Abstract
Dietary conjugated linoleic acids (CLA) have been reported to have a number of isomer-dependent effects on lipid metabolism including reduction in adipose tissue deposition, changes in plasma lipoprotein concentrations and hepatic lipid accumulation. The aim of this study was to compare the effect of individual CLA isomers against lipogenic and high 'Western' fat background diets. Golden Syrian hamsters were fed a high-carbohydrate rodent chow or chow supplemented with 17.25 % fat formulated to represent the type and amount of fatty acids found in a typical 'Western' diet (including 0.2 % cholesterol). Diets were further supplemented with 0.25 % (w/w) rapeseed oil, cis9, trans11 (c9,t11)-CLA or trans10, cis12 (t10,c12)-CLA. Neither isomer had a significant impact on plasma lipid or lipoprotein concentrations. The t10,c12-CLA isomer significantly reduced perirenal adipose tissue depot mass. While adipose tissue acetyl CoA carboxylase and fatty acid synthase mRNA concentrations (as measured by quantitative PCR) were unaffected by CLA, lipoprotein lipase mRNA was specifically reduced by t10,c12-CLA, on both background diets (P < 0.001). This was associated with a specific reduction of sterol regulatory element binding protein 1c expression in perirenal adipose tissue (P = 0.018). The isomers appear to have divergent effects on liver TAG content with c9,t11-CLA producing lower concentrations than t10,c12-CLA. We conclude that t10,c12-CLA modestly reduces adipose tissue deposition in the Golden Syrian hamster independently of background diet and this may possibly result from reduced uptake of lipoprotein fatty acids, as a consequence of reduced lipoprotein lipase gene expression.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".