Influence of high-fat diet from differential dietary sources on bone mineral density, bone strength, and bone fatty acid composition in rats
Bibliographic record
Abstract
Previous studies have suggested that high-fat diets adversely affect bone development. However, these studies included other dietary manipulations, including low calcium, folic acid, and fibre, and (or) high sucrose or cholesterol, and did not directly compare several common sources of dietary fat. Thus, the overall objective of this study was to investigate the effect of high-fat diets that differ in fat quality, representing diets high in saturated fatty acids (SFA), n-3 polyunsaturated fatty acids (PUFA), or n-6 PUFA, on femur bone mineral density (BMD), strength, and fatty acid composition. Forty-day-old male Sprague-Dawley rats were maintained for 65 days on high-fat diets (20% by weight), containing coconut oil (SFA; n = 10), flaxseed oil (n-3 PUFA; n = 10), or safflower oil (n-6 PUFA; n = 11). Chow-fed rats (n = 10), at 105 days of age, were included to represent animals on a control diet. Rats fed high-fat diets had higher body weights than the chow-fed rats (p < 0.001). Among all high-fat groups, there were no differences in femur BMD (p > 0.05) or biomechanical strength properties (p > 0.05). Femurs of groups fed either the high n-3 or high n-6 PUFA diets were stronger (as measured by peak load) than those of the chow-fed group, after adjustment for significant differences in body weight (p = 0.001). As expected, the femur fatty acid profile reflected the fatty acid composition of the diet consumed. These results suggest that high-fat diets, containing high levels of PUFA in the form of flaxseed or safflower oil, have a positive effect on bone strength when fed to male rats 6 to 15 weeks of age.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".