Regenerating islet-derived 3-gamma regulates pulmonary Th17 immunity by altering the gut microbiome (120.37)
Bibliographic record
Abstract
Abstract Regenerating islet-derived 3-gamma (Reg3g) is a 17kDa lectin produced by intestinal paneth cells and has bactericidal activity against gram-positive organisms. Here, we find that lung infection with Staphylococcus aureus induces the expression of reg3g and reg3b in a MyD88-dependent manner. Expression of reg3b in the lung was localized to large airway cells, and increased following treatment with IL-17 and IL-22. Further, recombinant Reg3g had strong binding to S. aureus and growth inhibition in vitro. In vivo studies indicated that reg3g-/- mice were capable of clearing S. aureus infection, and produced significantly more IL-17 than control B6 mice. This was associated with increased segmented filamentous bacteria colonization in the gut of Reg3g-/- mice. To test the hypothesis that Reg3g regulates lung Th17 immunity by altering the gut microbiome, mice were treated with antibiotics prior to immunization with ovalbumin plus cholera toxin. Antibiotic treatment reduced lung Th17 numbers in Reg3g-/- mice to the level observed in B6 mice. Finally, gut vaccination with heat-killed Klebsiella pneumoniae increased Th17 cytokine expression in the lung and protected against live challenge, demonstrating the intestinal niche can augment pulmonary immunity. These data demonstrate dual roles for Reg3g in host defense: 1) direct anti-microbial activity against S. aureus, and 2) decreasing SFB levels in the gut, which could negatively impact Th17-mediated 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) | 0.001 | 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 | 0.001 |
| 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".