Intranasal Filtration of Inhaled Aerosol in Human Subjects as a Function of Nasal Pressure Drop
Bibliographic record
Abstract
Abstract Background: Intersubject variability in nasal deposition of inhaled aerosol is significant because of the differences in nasal anatomy and breathing rate. The notable limitation of the majority of previously developed predictive correlations is including a limited number of subjects. A few recent studies have considered a wide age range of subjects, but the resulting correlations require the knowledge of the dimensions of the nasal airways and the properties of inhaled gas. In this study empirical correlations are proposed to predict aerosol deposition in nasal airways of subjects of different age as a function of intranasal pressure drop and the particle aerodynamic diameter. Methods: The experimental nasal deposition and pressure drop data in anatomically correct nasal replicas of 5 adults, 13 children aged 4–14 years, and 11 infants aged 3–18 months were reanalyzed. The range of aerodynamic diameter was 0.5–5.3 μm and physiological breathing at different activity levels was considered. Correlations between nasal deposition and a deposition parameter including the aerodynamic size of inhaled aerosol and nasal pressure drop were developed with nonlinear least-square algorithms. The general coefficient of determination r 2 was used to evaluate the fitting accuracy for each correlation. Results: New correlations were developed to predict the intranasal deposition of particles as a function of intranasal pressure drop and particle size for pediatric and adult subjects. The intranasal deposition fraction in adults and children can be calculated using the same correlation, whereas the intranasal deposition in infants followed a different trend line because of higher intranasal pressure drop in infants. Conclusion: This study was the first offering correlations to predict intranasal deposition in multiple age groups using only the aerodynamic size of inhaled aerosol and nasal pressure drop. These correlations include the effects of intersubject variability in nasal deposition within each age group and among different age groups.
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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".