Emergent Inflammatory Markers and Echocardiographic Indices in Patients with Bronchial Asthma
Bibliographic record
Abstract
Asthma is a heterogeneous disease, characterized by chronic inflammation and oxidative stress of the airways. Several inflammatory pathways including activation of the receptor for advanced glycation end products (RAGE) have been described in the course of the disease. DJ-1 is a redox-sensitive protein with multifaceted roles in mast cell homeostasis and an emerging role in the pathogenesis of asthma. Moreover, cardiac function abnormalities have been described via echocardiography in patients with asthma. The main aim of this study was to investigate the plasma levels of RAGE, its ligands and DJ-1 in asthmatic patients pre- and post-treatment along with echocardiographic indices of cardiovascular function. The study population was divided into two groups. Group A included 13 patients with newly diagnosed bronchial asthma who were free of treatment for at least two weeks and Group B included 12 patients without asthma. An echocardiography examination was performed on all patients. The plasma levels of RAGE, its ligands (AGEs, S100A12, S100B, S100A8/A9), the interleukins (IL-6, IL-1β) and DJ-1 were measured. No differences were noted among the two groups for baseline characteristics and echocardiographic indices of cardiac function. In Group A, 31% suffered from mild asthma, 54% from moderate asthma and 15% from severe asthma. Plasma levels of IL-6, AGEs and AGE/RAGE ratio were increased and those of S100A12 and DJ-1 were decreased in asthmatics. Pharmacotherapy with corticosteroids/β2-agonists decreased IL-6, and AGEs, and increased DJ-1. In search of novel approaches in diagnosing and treating patients with asthma, S100A12, ratio AGE/sRAGE, and DJ-1 in addition to IL-6 may prove to be useful tools.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".