Maternal Dietary Vitamin D Does Not Program Systemic Inflammation and Bone Health in Adult Female Mice Fed an Obesogenic Diet
Bibliographic record
Abstract
Obesity is associated with systemic inflammation and impaired bone health. Vitamin D regulates bone metabolism, and has anti-inflammatory properties and epigenetic effects. We showed that exposure to high dietary vitamin D during pregnancy and lactation beneficially programs serum concentration of lipopolysaccharide (LPS) and bone structure in male offspring fed an obesogenic diet. Here we assessed if this effect is also apparent in females. C57BL/6J dams were fed AIN93G diet with high (5000 IU/kg diet) or low (25 IU/kg diet) vitamin D during pregnancy and lactation. Post-weaning, female offspring remained on their respective vitamin D level or were switched and fed a high fat and sucrose diet (44.2% fat, 19.8% sucrose) until age seven months when glucose response, adiposity, serum LPS, and bone mineral, trabecular and cortical structure, and biomechanical strength properties of femur and vertebra were assessed. There was no evidence for a programming effect of vitamin D for any outcomes. However, females exposed to a high vitamin D diet post-weaning had higher bone mineral content (p = 0.037) and density (p = 0.015) of lumbar vertebra. This post-weaning benefit suggests that in females, bone mineral accrual but not bone structure is compromised with low vitamin D status in utero until weaning in an obesogenic context.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".