Vitamin D receptor pathway is required for probiotic protection in colitis
Bibliographic record
Abstract
Low expression of vitamin D receptor (VDR) and dysfunction of vitamin D/VDR signaling are reported in patients with inflammatory bowel disease (IBD); therefore, restoration of VDR function to control inflammation in IBD is desirable. Probiotics have been used in the treatment of IBD. However, the role of probiotics in the modulation of VDR signaling to effectively reduce inflammation is unknown. We identified a novel role of probiotics in activating VDR activity, thus inhibiting inflammation, using cell models and VDR knockout mice. We found that the probiotics Lactobacillus rhamnosus strain GG (LGG) and Lactobacillus plantarum (LP) increased VDR protein expression in both mouse and human intestinal epithelial cells. Using the VDR luciferase reporter vector, we detected increased transcriptional activity of VDR after probiotic treatment. Probiotics increased the expression of the VDR target genes, such as antimicrobial peptide cathelicidin, at the transcriptional level. Furthermore, the role of probiotics in regulating VDR signaling was tested in vivo using a Salmonella-colitis model in VDR knockout mice. Probiotic treatment conferred physiological and histologic protection from Salmonella-induced colitis in VDR(+/+) mice, whereas probiotics had no effects in the VDR(-/-) mice. Probiotic treatment also enhanced numbers of Paneth cells, which secrete AMPs for host defense. These data indicate that the VDR pathway is required for probiotic protection in colitis. Understanding how probiotics enhance VDR signaling and inhibit inflammation will allow probiotics to be used effectively, resulting in innovative approaches to the prevention and treatment of chronic 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".