Fat-1 gene modulates the fatty acid composition of femoral and vertebral phospholipids
Bibliographic record
Abstract
Dietary polyunsaturated fatty acid (PUFA) incorporation into bone may alter its metabolism through changes in the fatty acid composition of membrane phospholipids. Alteration of the membrane phospholipid fatty acid composition may influence bone cell signalling and, potentially, bone mineralization. The objective of this study was to use the fat-1 mouse, a transgenic model that synthesizes n-3 from n-6 PUFA, to determine if the fat-1 gene modulates the fatty acid composition of femoral and vertebral phospholipids, and if so, whether the fatty acid levels would correlate with bone mineral density (BMD) at both skeletal sites. Male and female wild-type and fat-1 mice were fed an AIN93-G diet, containing 10% safflower oil, from weaning to 12 weeks of age. The fatty acid composition of femoral and vertebral phospholipids was measured by gas liquid chromatography. At 12 weeks of age, phosphatidylcholine, phosphatidylethanolamine, and phosphatidylserine fractions in the vertebrae of fat-1 mice had a significantly lower n-6/n-3 ratio than wild-type mice (p<0.05). In fat-1 femurs, these fractions, along with phosphatidylinositol, had a lower n-6/n-3 ratio than wild-type mice (p<0.001). Docosahexaenoic acid (DHA) was positively correlated with BMD in all fractions in the vertebrae, and in phosphatidylinositol and phosphatidylserine in the femur (p<0.05). Overall, the fat-1 gene resulted in changes in the fatty acid composition of both femoral and vertebral phospholipids. Significant correlations between DHA and BMD may indicate a positive effect on bone mineralization.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".