Active vitamin D (1,25-dihydroxyvitamin D<sub>3</sub>) increases host susceptibility to<i>Citrobacter rodentium</i>by suppressing mucosal Th17 responses
Bibliographic record
Abstract
Vitamin D deficiency affects more that 1 billion people worldwide and is associated with an increased risk of developing a number of inflammatory/autoimmune diseases, including inflammatory bowel disease (IBD). At present, the basis for the impact of vitamin D on IBD and mucosal immune responses is unclear; however, IBD is known to reflect exaggerated immune responses to luminal bacteria, and vitamin D has been shown to play a role in regulating bacteria-host interactions. Therefore, to test the effect of active vitamin D on host responses to enteric bacteria, we gave 1,25(OH)(2)D(3) to mice infected with the bacterial pathogen Citrobacter rodentium, an extracellular microbe that causes acute colitis characterized by a strong Th1/Th17 immune response. 1,25(OH)(2)D(3) treatment of infected mice led to increased pathogen burdens and exaggerated tissue pathology. In association with their increased susceptibility, 1,25(OH)(2)D(3)-treated mice showed substantially reduced numbers of Th17 T cells within their infected colons, whereas only modest differences were noted in Th1 and Treg numbers. In accordance with the impaired Th17 responses, 1,25(OH)(2)D(3)-treated mice showed defects in their production of the antimicrobial peptide REG3γ. Taken together, these studies show that 1,25(OH)(2)D(3) suppresses Th17 T-cell responses in vivo and impairs mucosal host defense against an enteric bacterial pathogen.
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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) | 0.002 | 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".