Characterization of Medication Velocity and Size Distribution from Pressurized Metered-Dose Inhalers by Phase Doppler Anemometry
Bibliographic record
Abstract
BACKGROUND: Particle size and velocity are two of the most significant factors that impact the deposition of pressurized metered-dose inhaler (pMDI) sprays in the mouth cavity. pMDIs are prominently used around the world in the treatment of patients suffering from a variety of lung diseases such as asthma and chronic obstructive pulmonary disease. Since their introduction in the field, and as a result of their effectiveness and simplicity of usage, pMDIs are considered to be the most widely prescribed medical aerosol delivery system. METHODS: In the current study, particle velocity and size distribution were measured at three different locations along the centerline of a pMDI spray using Phase Doppler Anemometry. pMDIs from four different pharmaceutical companies were tested, each using salbutamol sulfate as the medication. RESULTS AND CONCLUSIONS: Measurements along at the pMDI centerline (at 0, 75, and 100 mm downstream of the inhaler mouthpiece) showed that the spray velocities were bimodal in time for all four pMDI brands. The first peak occurred as the spray was leaving the mouthpiece, while the second peak (at the same location, 0 mm) occurred at around 60, 95, 95, and 115 milliseconds later, respectively, for the four tested inhalers, with a drop in the velocity between the two peaks. Three probability density functions (PDFs) were tested, and the Rosin-Rammler PDF best fit the empirical data, as determined using a chi-squared test. These results suggest that there is a difference in the mean particle velocities at the centerline for the tested pMDIs and the diameter of released particles varied statistically for each brand.
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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 | 0.001 | 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 | 0.000 |
| 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".