Innate T‐cell‐derived IL‐17A/F protects from bleomycin‐induced acute lung injury but not bleomycin or adenoviral TGF‐β1‐induced lung fibrosis in mice
Bibliographic record
Abstract
Abstract The pathobiology of IL‐17 in lung fibrogenesis is controversial. Here we examined the role of IL‐17A/F in bleomycin (BLM) and adenoviral TGF‐β1‐induced lung fibrosis in mice. In both experimental models, WT and IL17af−/− mice showed increased collagen contents and remodeled lung architecture as assessed by histopathological examination, suggesting that IL‐17A/F is dispensable for lung fibrogenesis. However, IL17af−/− mice responded to the BLM challenge with perturbed lung leukocyte subset recruitment. More specifically, bleomycin triggered angiocentric neutrophilic infiltrations of the lung accompanied by increased mortality of IL17af−/− but not WT mice. WT bone marrow transplantation failed to correct this phenotype in BLM‐challenged IL17af−/− mice. Conversely, IL17a/f−/− bone marrow transplantation → WT did not perturb lung leukocytic responses upon BLM. At the same time, IL17af−/− mice treated with recombinant IL‐17A/F showed an attenuated lung inflammatory response to BLM. Together, the data show that the degree of BLM‐driven acute lung injury was critically dependent on the presence of IL‐17A/F, while in both models, the fibrotic remodeling process was not.
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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) | 0.001 | 0.001 |
| 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 | 0.002 |
| 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".