Innate lymphoid cells in isocyanate-induced asthma: role of microRNA-155
Bibliographic record
Abstract
Background Occupational asthma, induced by workplace exposures to low molecular weight agents such as toluene 2,4-diisocyanate (TDI), causes a significant burden to patients and society. Little is known about innate lymphoid cells (ILCs) in TDI-induced asthma. A critical regulator of ILC function is microRNA-155, a microRNA associated with asthma. Objective To determine whether TDI exposure modifies the number of ILCs in the lung and whether microRNA-155 contributes to TDI-induced airway inflammation and hyperresponsiveness. Methods C57BL/6 wild-type and microRNA-155 knockout mice were sensitised and challenged with TDI or vehicle. Intracellular cytokine expression in ILCs and T-cells was evaluated in bronchoalveolar lavage (BAL) fluid using flow cytometry. Peribronchial eosinophilia and goblet cells were evaluated on lung tissue, and airway hyperresponsiveness was measured using the forced oscillation technique. Putative type 2 ILCs (ILC2) were identified in bronchial biopsies of subjects with TDI-induced occupational asthma using immunohistochemistry. Human bronchial epithelial cells were exposed to TDI or vehicle. Results TDI-exposed mice had higher numbers of airway goblet cells, BAL eosinophils, CD4+T-cells and ILCs, with a predominant type 2 response, and tended to have airway hyperresponsiveness. In TDI-exposed microRNA-155 knockout mice, inflammation and airway hyperresponsiveness were attenuated. TDI exposure induced IL-33 expression in human bronchial epithelial cells and in murine lungs, which was microRNA-155 dependent in mice. GATA3+CD3−cells, presumably ILC2, were present in bronchial biopsies. Conclusion TDI exposure is associated with increased numbers of ILCs. The proinflammatory microRNA-155 is crucial in a murine model of TDI asthma, suggesting its involvement in the pathogenesis of occupational asthma due to low molecular weight agents.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".