Innate Lymphoid Cells Are the Predominant Source of IL-17A during the Early Pathogenesis of Acute Respiratory Distress Syndrome
Bibliographic record
Abstract
RATIONALE: IL-17A is purported to help drive early pathogenesis in acute respiratory distress syndrome (ARDS) by enhancing neutrophil recruitment. Although IL-17A is the archetypal cytokine of T-helper 17 cells, it is produced by a number of lymphocytes, the source during ARDS being unknown. OBJECTIVES: To identify the cellular source and the role of IL-17A in the early phase of lung injury. METHODS: Lung injury was induced in wild-type (C57BL/6) and IL-17 knockout (KO) mice with aerosolized LPS (100 μg) or Pseudomonas aeruginosa infection. Detailed phenotyping of the cells expressing RORγt, the transcriptional regulator of IL-17 production, in the mouse lung at 24 hours was performed by flow cytometry. MEASUREMENTS AND MAIN RESULTS: A 100-fold reduction in neutrophil infiltration was observed in the lungs of the IL-17A KO compared with wild-type mice. The majority of RORγt(+) cells in the mouse lung were the recently identified group 3 innate lymphoid cells (ILC3s). Detailed characterization revealed these pulmonary ILC3s (pILC3s) to be discrete from those described in the gut. The critical role of these cells was verified by inducing injury in recombinase-activating gene 2 KO mice, which lack T cells but retain innate lymphoid cells. No amelioration of pathology was observed in the recombinase-activating gene 2 KO mice. CONCLUSIONS: IL-17 is rapidly produced during lung injury and significantly contributes to early immunopathogenesis. This is orchestrated largely by a distinct population of pILC3s. Modulation of the activity of pILC3s may potentiate early control of the inflammatory dysregulation seen in ARDS, opening up new therapeutic targets.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".