Dietary vitamin D3 deficiency alters intestinal mucosal defense and increases susceptibility to<i>Citrobacter rodentium</i>-induced colitis
Bibliographic record
Abstract
Vitamin D deficiency affects more that 1 billion people worldwide. Although thought to increase risk of bacterial infections, the importance of vitamin D on host defense against intestinal bacterial pathogens is currently unclear since injection of the active form of vitamin D, 1,25(OH)2D3, increased susceptibility to the enteric bacterial pathogen Citrobacter rodentium by suppressing key immune/inflammatory factors. To further characterize the role of vitamin D during bacteria-induced colitis, we fed weanling mice either vitamin D3-deficient or vitamin D3-sufficient diets for 5 wk and then challenged them with C. rodentium. Vitamin D3-deficient mice lost significantly more body weight, carried higher C. rodentium burdens, and developed worsened histological damage. Vitamin D3-deficient mice also suffered greater bacterial translocation to extra-intestinal tissues, including mesenteric lymph nodes, spleen, and liver. Intestinal tissues of infected vitamin D3-deficient mice displayed increased inflammatory cell infiltrates as well as significantly higher gene transcript levels of inflammatory mediators TNF-α, IL-1β, IL-6, TGF-β, IL-17A, and IL-17F as well as the antimicrobial peptide REG3γ. Notably, these exaggerated inflammatory responses accelerated the loss of commensal microbes and were associated with an impaired ability to detoxify bacterial lipopolysaccharide. Overall, these studies show that dietary-induced vitamin D deficiency exacerbates intestinal inflammatory responses to infection, also impairing host defense.
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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) | 0.001 | 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".