Long‐term effects of dietary long chain polyunsaturated fatty acids on bone in healthy rats
Bibliographic record
Abstract
Long‐term effects of long chain polyunsaturated fatty acids (LCPUFA), arachidonic acid (AA), eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) on bone mass are unclear. Objective: determine how AA and EPA would affect bone when introduced at different points or maintained throughout life. Male and female rats (n=108) received control or one of two LCPUFA diets: AA diet (0.5 g AA, 0.1 g EPA and 0.1 g DHA /100 g of fat) or EPA diet (0.5 g EPA, 0.1 g AA and 0.1 g DHA /100 g of fat). LCPUFA diets were fed in 4 patterns: early (4–18.9 wks old), mid (19–34.9 wks old) or late (35–49 wks old) introduction or continuously (4–49 wks old). Serial measurements included: bone area (BA), bone mineral content (BMC) and urinary Ca. End point measurements included: femur morphometry and mineral composition. In a diet by sex effect on femur BA (P=0.0214), neck width (P=0.024) and head width (P=0.024), males fed EPA had lower BA and males fed AA either mid or continuously had larger femur neck and head widths compared to control. In a diet by gender interaction females fed the EPA diet had lower urinary Ca (P=0.0030) compared to those fed the AA diet. Dietary LCPUFA had varied affects on femur Mg (P=0.0362), Zn (P=0.0107) and P (P=0.0202). Whole body and lumbar spine BMC and BA and femur BMC were not affected by diet. Whether changes in femur size, morphology and mineral composition influence bone strength and risk of osteoporosis requires further study. Funded by ILSI, NSERC and MICH.
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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 | 0.001 | 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".