Deficiency of <scp>FHL</scp>2 attenuates airway inflammation in mice and genetic variation associates with human bronchial hyper‐responsiveness
Bibliographic record
Abstract
BACKGROUND: Asthma is an inflammatory disease that involves airway hyper-responsiveness and mucus hypersecretion. The LIM-only protein FHL2 is a crucial modulator of multiple signal transduction pathways and functions as a scaffold in specific protein-protein interactions. OBJECTIVE: We sought to investigate the role of FHL2 in airway inflammation. METHODS: Allergic airway inflammation was induced in WT and FHL2-knock out (FHL2-KO) mice with ovalbumin (OVA). Lung tissue, bronchoalveolar lavage fluid (BALF) and draining lymph node cells were analysed for inflammation. FHL2 loss and gain of function studies were performed in lung epithelial cells. RESULTS: FHL2-deficient mice challenged with OVA show significantly reduced airway inflammation as evidenced by reduced infiltration of inflammatory cells including eosinophils, dendritic cells, B cells and T cells. Furthermore, mucus production was decreased in FHL2-KO mice. In BALF, the levels of IL-5, IL-13, eotaxin-1 and eotaxin-2 were significantly lower in FHL2-KO mice. In addition, draining lymph node cells from FHL2-KO mice show reduced levels of IL-5 and IL-13. Consistent with this, OVA-specific serum IgG and IgE levels were reduced in FHL2-KO mice. We also found that phosphorylation of ERK1/2 is markedly attenuated in FHL2-KO lung. Knock-down of FHL2 in human lung epithelial cells resulted in a striking decrease in ERK1/2 phosphorylation and mRNA levels of inflammatory cytokines and MUC5AC, whereas FHL2 overexpression exhibited opposite effects. Finally, the SNP rs4851765 shows an association with the severity of bronchial hyper-responsiveness. CONCLUSION: These results highlight functional involvement of FHL2 in airway inflammation and identify FHL2 as a novel gene associated with asthma severity in human.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".