Low vitamin <scp>D</scp> status throughout life results in an inflammatory prone status but does not alter bone mineral or strength in healthy 3‐month‐old <scp>CD</scp>‐1 male mice
Bibliographic record
Abstract
SCOPE: The aim of this study was to assess if exposure to different levels of dietary vitamin D pre- and postweaning impacts the intestinal-bone axis. METHODS AND RESULTS: Female CD1 mice were exposed to high (5000 IU vitamin D3 /kg diet, H) or low (25 IU vitamin D3 /kg diet, L) vitamin D diet (modified AIN-93G) during pregnancy and lactation. At weaning (postnatal day 21), a subset of the male offspring was sacrificed and another subset was assigned to receive their dams' respective diet (HH and LL) or the other diet (HL and LH) until sacrifice at 3 months of age. Lower level of vitamin D resulted in reduced vitamin D receptor and increased expression of pro-inflammatory genes in the colon at 3 months, lower numbers of colonic Bacteroides/Prevotella at postnatal day 21 and higher serum LPS concentration at adulthood. There was a programming effect of vitamin D on LPS levels. Mineral content, density, and strength of femurs and vertebrae were not affected. CONCLUSION: Our findings suggest that low vitamin D exposure results in an inflammatory-prone status that may contribute to or be a risk factor for several diseases including inflammatory bowel disease, obesity, diabetes, and cardiovascular diseases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
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".