Angiopoietin-2 concentration in serum is associated with severe asthma phenotype
Bibliographic record
Abstract
BACKGROUND: Several proangiogenic molecules have been implicated in the pathogenies of asthmatic inflammation and remodeling. The aim of the study was to compare the concentration of proangiogenic factors in the sera of asthmatic patients and in healthy subjects (HS), and to refer the concentrations to both clinical and inflammatory markers of the disease severity. METHODS: Serum was collected from 45 patients with severe/refractory asthma (SRA) and 51 patients with non-severe asthma (nSA). The control group included 30 HS. Serum concentrations of Angiopoietin-1, Angiopoietin-2, vascular endothelial growth factor (VEGF) and osteopontin were assessed by the enzyme-linked immunosorbent assay. RESULTS: The levels of Angiopoietin-1 (68.8 ± 2.7 vs 56.4 ± 9.3 ng/ml; p < 0.05), Angiopoietin-2 (4.9 ± 0.35 vs 1.38 ± 0.14 ng/ml; p < 0.0001) and VEGF were significantly higher in asthmatic patients (n = 94) as compared to HS (255 ± 45.4 vs 424.5 ± 27.8 pg/ml; p < 0.01). The mean serum level of Angiopoietin-2 was found to be significantly higher in patients with SRA as compared to nSA patients (6.04 ± 0.46 vs 3.84 ± 0.43; p < 0.001). Angiopoietin-2 serum level correlated with respiratory function and with parameters of asthma severity: the mean number of asthma exacerbations in the preceding 12 months (R = 0.21; p < 0.05), mean number of emergency visits due to severe asthma exacerbation (R = 0.24; p < 0.04) and mean number of hospitalizations (R = 0.21; p < 0.05) or dose of inhaled glucocorticosteroids taken by the patients (R = 0.36; p < 0.001). CONCLUSION: Angiopoietin-2 seems to be a crucial proangiogenic cytokine overproduced in patients with SRA characterized by repeated exacerbations and Angiopoietin-2 serum levels can serve as a biomarker of severe 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 | 0.000 | 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".