Colonic Inflammation in Mice Is Improved by Cigarette Smoke through iNKT Cells Recruitment
Bibliographic record
Abstract
Cigarette smoke (CS) protects against intestinal inflammation during ulcerative colitis. Immunoregulatory mechanisms sustaining this effect remain unknown. The aim of this study was to assess the effects of CS on experimental colitis and to characterize the intestinal inflammatory response at the cellular and molecular levels. Using the InExpose® System, a smoking device accurately reproducing human smoking habit, we pre-exposed C57BL/6 mice for 2 weeks to CS, and then we induced colitis by administration of dextran sodium sulfate (DSS). This system allowed us to demonstrate that CS exposure improved colonic inflammation (significant decrease in clinical score, body weight loss and weight/length colonic ratio). This improvement was associated with a significant decrease in colonic proinflammatory Th1/Th17 cytokine expression, as compared to unexposed mice (TNF (p=0.0169), IFNγ (p<0.0001), and IL-17 (p=0.0008)). Smoke exposure also induced an increased expression of IL-10 mRNA (p=0.0035) and a marked recruitment of iNKT (invariant Natural Killer T; CD45+ TCRβ+ CD1d tetramer+) cells in the colon of DSS-untreated mice. Demonstration of the role of iNKT cells in CS-dependent colitis improvement was performed using two different strains of NKT cells deficient mice. Indeed, in Jα18KO and CD1dKO animals, CS exposure failed to induce significant regulation of DSS-induced colitis both at the clinical and molecular levels. Thus, our study demonstrates that iNKT cells are pivotal actors in the CS-dependent protection of the colon. These results highlight the role of intestinal iNKT lymphocytes and their responsiveness to environmental stimuli. Targeting iNKT cells would represent a new therapeutic way for inflammatory bowel diseases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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; both teacher heads agree on what is shown here.
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".