Pulmonary Th17 immunity is regulated by regenerating islet-derived III-gamma and the gut microbiome (MUC4P.826)
Bibliographic record
Abstract
Abstract Antimicrobial proteins provide an innate immune barrier against pathogen invasion. Here we identify a function for the bactericidal lectin regenerating islet-derived III-gamma (RegIIIγ) in shaping CD4 T cell polarization. Gram-positive bacteria in the intestine induce RegIIIγ expression, which modulates the immune tone of the gut, resulting in decreased Th17-type immunity during pulmonary fungal infection. This was associated with RegIIIγ inhibiting intestinal colonization with segmented filamentous bacteria (SFB), a pro-inflammatory commensal that augments Th17 differentiation. Vancomycin drinking water inhibited IL-17 production in lungs of RegIIIγ-/- and Il22-/- mice, demonstrating that intestinal Gram-positive commensals contribute to systemic inflammation. Reconstituting Il22-/- mice with IL-22 decreased the SFB/Clostridium ratio, while gastrointestinal delivery of recombinant RegIIIγ decreased inflammatory gene expression in lung tissue and protected Il22-/- mice from weight-loss during Aspergillus fumigatus infection. Therefore, intestinal antimicrobial proteins influence the development of adaptive immunity by altering the balance of pro- and anti-inflammatory intestinal commensal species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".