A comparison of effects of lard and hydrogenated vegetable shortening on the development of high-fat diet-induced obesity in rats
Bibliographic record
Abstract
BACKGROUND: Obesity is associated with increased consumption and preference for dietary fat. Experimental models of fat-induced obesity use either lard or vegetable shortening. Yet, there are no direct comparisons of these commonly used fat sources, or the influence of their fatty acid composition, on the development of diet-induced obesity. OBJECTIVE: To compare the effects of lard and hydrogenated vegetable-shortening diets, which differ in their fatty acid composition, on weight gain and the development of obesity and insulin resistance in rats. METHODS AND DESIGN: Male Wistar rats were fed ad libitum for 14 weeks high-fat diets containing either (1) high vegetable fat (HVF, 60 kcal% from vegetable shortening) or (2) high lard fat (HLF, 60 kcal% from lard). Rats fed normal-fat (NF, 16 kcal% from vegetable shortening) diet served as control. Body weight, food intake, adipose tissue mass, serum 25[OH]D3, glucose, insulin and fatty acid composition of diets were measured. RESULTS: Rats fed either of the two high-fat diets had higher energy intake, weight gain and fat accretion than rats fed normal-fat diet. However, rats fed the HLF diet consumed more calories and gained more weight and body fat with greater increases of 32% in total (158.5±8.2 vs 120.2±6.6 g, P<0.05), 30% in visceral (104.4±5.2 vs 80.3±4.2 g, P<0.05) and 36% in subcutaneous fat mass (54.1±3.6 vs 39.9±3.1 g, P<0.05), compared with rats fed the HVF diet. Higher visceral adiposity was positively correlated with serum insulin (r=0.376, P<0.05) and homeostatic model assessment insulin resistance (r=0.391, P<0.05). CONCLUSION: We conclude that lard-based high-fat diets accentuate the increase in weight gain and the development of obesity and insulin resistance more than hydrogenated vegetable-shortening diets. These results further point to the importance of standardizing fatty acid composition and type of fat used in determining outcomes of consuming high-fat diets.
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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 | 0.001 |
| 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 | 0.000 | 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".