Higher Bifidobacteria counts in male offspring exposed to supplemental levels of vitamin D in utero and during suckling in IBD‐prone mice
Bibliographic record
Abstract
Vitamin D deficiency has been linked to an increased risk of inflammatory bowel disease (IBD), and microbial dysbiosis has been implicated in IBD. Our objective was to determine if exposure to supplemental levels of vitamin D can favourably modulate microbiota composition pre‐inflammation in the male interleukin‐10 knockout (IL‐10 KO) mouse that spontaneously develops intestinal inflammation at 6–8 weeks of age. The mice were randomized to a diet containing 25 IU (low group) or 5000 IU (high group) of vitamin D/kg of diet in utero and during suckling, and fecal samples were collected at 5 weeks of age. Fecal microbiota composition was determined by qPCR. Mice in the supplemental group had higher (p = 0.01) counts of Bifidobacteria than mice in the low group. Total bacteria, Bacteroides, Clostridium leptum , Clostridium coccoides and Escherichia coli counts were unaffected. Bifidobacteria have been found to sustain intestinal homeostasis and inhibit Th1‐driven inflammation and may favourably alter gut microbial composition to a more health‐promoting phenotype. Further investigation is needed to determine if this results in protection against developing intestinal inflammation.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".