Investigation of Individual Variability and Temporal Fluctuations in Exhaled Nitric Oxide (FeNO) Levels in Healthy Individuals
Bibliographic record
Abstract
Measurement of nitric oxide (NO) concentration in exhaled breath (FeNO) is a quantitative, non-invasive, simple, and safe method for assessing airway inflammation. It serves as a complementary tool to other methods for evaluating airway diseases. However, little is known about the typical NO levels in healthy individuals, including individual differences and the influence of measurement timing. Therefore, this study classified measurement times into four periods and statistically analyzed NO levels in healthy individuals. The mean values among groups were compared using repeated measures ANOVA on six participants. The analysis showed large individual variations in NO levels, resulting in no significant difference (p = 0.29). Notably, greater fluctuations were observed in the morning. These findings align with previous studies suggesting the influence of circadian rhythms and the redundancy of repeated measurements. This study highlights the need to consider timing and individual variability when using FeNO as a physiological marker in healthy populations.
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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 | 0.001 | 0.002 |
| 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) | 0.001 | 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".