High intakes of fructose are associated with alterations in liver fatty acid composition in rats
Bibliographic record
Abstract
Background: Diets high in fructose may result in abnormalities in glucose and lipid metabolism. Purpose: To investigate the effects of a high‐fructose diet on liver fatty acid composition. Methods: Male Sprague‐Dawley rats were divided into two groups: a control group (n=5) receiving standard chow diet, and treatment group (n=7) receiving a diet containing 10% w/w lard and 60% w/w fructose for 20 weeks. Fatty acid profile of various lipid fractions in the liver of these animals was characterized. Results: Total liver lipids including cholesterol and triacyglycerol (TAG) were significantly higher in the treated group as compared to controls. The livers from treated animals had significantly lower levels of C16:0 and higher levels of C18:1 in the TAG fraction, and lower levels of C18:1c11, C18:2c9, C20:1c11, C20:1c13 along with higher levels of C16:1 and C18:1c9 in the free fatty acid fraction. The levels of C16:0, C18:2c9, C20:1c11, C20:1c13, C20:2c11 and C24:0 were significantly increased in the phosholipid fraction of the treated animals. Conclusions: High intakes of fructose change liver lipid composition and fatty acid profile in rats. TAG and phospholipid fractions seem to be affected more. These changes may lead to alterations in hepatocyte functions including lipid metabolism and may modify cardiovascular risk.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".