Increased upper airway cytokines and oxidative stress in severe obstructive sleep apnoea
Bibliographic record
Abstract
Inflammation may contribute to upper airway pathophysiology in obstructive sleep apnoea (OSA). Our objective was to compare upper airway pro-inflammatory cytokine expression, oxidative stress and connective tissue deposition in severe (n = 25) versus mild (n = 17) OSA patients. Upper airway surgical specimens were separated by predominance of either mucosal or muscle tissue. Expression levels of interleukin (IL)-1α, IL-6, interferon-γ, RANTES (regulated on activation, normal T-cell expressed and secreted), transforming growth factor (TGF)-β and l-selectin were measured by ribonuclease protection assay. Oxidative stress was assessed via protein carbonyl group detection by immunoblotting. Histochemistry was employed for immunolocalisation of selected cytokines and connective tissue morphometry. In the severe OSA group, expression of IL-1α, IL-6 and TGF-β was significantly higher in mucosa-predominant tissues, whereas in muscle-predominant specimens, RANTES expression was greater in severe OSA. Increased protein carbonylation was observed in severe OSA within both mucosal and muscle compartments. Immunohistochemistry localised TGF-β to submucosal and perimuscular inflammatory cells, while IL-6 was primarily localised to myocytes. Consistent with the pro-fibrotic cytokine profile observed in mucosa-predominant tissue, morphometric analysis revealed greater submucosal and perimuscular connective tissue in severe OSA subjects. There is increased pro-inflammatory and pro-fibrotic cytokine expression, oxidative stress, and connective tissue deposition in upper airway tissues from severe versus mild OSA patients.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.002 |
| 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 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".