Impact of standardized physical exertion on oxidative stress biomarkers in exhaled breath condensate of patients suffering from severe chronic obstructive pulmonary disease - The PHAETON project
Bibliographic record
Abstract
Chronic obstructive pulmonary disease (COPD) is linked to increased oxidative and nitrative stress (RNOS) in the airways and systemic circulation. RNOS causes damage of fosfolipids and proteins in cellular membrane including airway epithelium. Exhaled breath analysis (EBC) can reflex intensity of RNOS in COPD. We compared concentration of RNOS biomarkers and anti-inflammatory lipoxin A4 (LXA4) in EBC in COPD patients and healthy controls before and after incremental shuttle walk test (ISWT), actigraphy was used to follow average daily steps 1 week before ISWT. In 29 patents with severe COPD (age 62±1,7, FEV1 48,8 ± 15,6%) and 17 age matched healthy controls were during 1 day performed EBC collection, EBC samples were frozen and analyzed by mass spectrometry with liqid chromatography. After EBC sampling subjects underwent ISWT, and then again gave EBC. Results: We tested 8-isoprostane (8-ISO), cysteinyl leucotriens (LTB4, LTC4) and LXA4. In COPD was 8-ISO 48.2±3.5, LTB4 45.8±2.3, LTC4 56.4±14.9 pg/mL and LXA4 18.5±8.9 pg/mL, in control group were results of RNOS lower, and LXA4 higher (all differences p<0.001). In COPD we found positive correlation of ISWT results with level of LXA4 (R=0.57, p= 0.01), and positive correlation of average daily steps number with LXA4 levels (R=0.46, p=0.02). Patients with decreased tolerance of physical exertion had increased 8-ISO and LTC4 (R=-0.39, p=0.03, R=-0.44, p=0.02). Conclusion: The higher RNOS in EBC the lower ISWT and daily acitivity. COPD patients with lower oxidative stress production had better tolerance of physical activity.
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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) | 0.000 | 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) | 0.002 | 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".