Deficiency of leukocyte-specific protein 1 (LSP1) alleviates asthmatic inflammation in a mouse model
Bibliographic record
Abstract
Abstract Background Asthma is a major cause of morbidity and mortality in humans. The mechanisms of asthma are still not fully understood. Leukocyte-specific protein-1 (LSP-1) regulates neutrophil migration during acute lung inflammation. However, its role in asthma remains unknown. Methods An OVA-induced mouse asthma model in LSP1-deficient (Lsp1 −/− ) and wild-type (WT) 129/SvJ mice were used to test the hypothesis that the absence of LSP1 would inhibit airway hyperresponsiveness and lung inflammation. Results Light and electron microscopic immunocytochemistry and Western blotting showed that, compared with normal healthy lungs, the levels of LSP1 were increased in lungs of OVA-asthmatic mice. Compared to Lsp1 −/− OVA mice, WT OVA mice had higher levels of leukocytes in broncho-alveolar lavage fluid and in the lung tissues (P < 0.05). The levels of OVA-specific IgE but not IgA and IgG1 in the serum of WT OVA mice was higher than that of Lsp1 −/− OVA mice (P < 0.05). Deficiency of LSP1 significantly reduced the levels of IL-4, IL-5, IL-6, IL-13, and CXCL1 (P < 0.05) but not total proteins in broncho-alveolar lavage fluid in asthmatic mice. The airway hyper-responsiveness to methacholine in Lsp1 −/− OVA mice was improved compared to WT OVA mice (P < 0.05). Histology revealed more inflammation (inflammatory cells, and airway and blood vessel wall thickening) in the lungs of WT OVA mice than in those of Lsp1 −/− OVA mice. Finally, immunohistology showed localization of LSP1 protein in normal and asthmatic human lungs especially associated with the vascular endothelium and neutrophils. Conclusion These data show that LSP1 deficiency reduces airway hyper-responsiveness and lung inflammation, including leukocyte recruitment and cytokine expression, in a mouse model of asthma.
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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 | 0.002 | 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".