Lung Delivery of Aerosolized Dextran
Bibliographic record
Abstract
The ability of nebulizers to deliver dextran (nominal molecular mass, 4,000 g/mol) to the lung as an inhaled aerosol is evaluated by in vitro experimental methods and mathematical models. Dextran in isotonic saline was aerosolized by four nebulizer types (Pari LC STAR, Hudson T-Updraft II, Acorn II, and Sonix 2000) at dextran concentrations </= 400 mg/ml and with 2.5- and 4-ml volume fills. Aerosols inhaled during breath simulation were characterized by in-line phase Doppler anemometry, filter collection, osmometry, and gravimetry. Mathematical models were used to estimate amounts of the characterized aerosols depositing in the different regions of lung models, and mathematical models of mucous thickness were then developed to estimate initial concentrations of the depositing dextran in the mucus of each conducting airway generation. Models of three subjects (4 yr old, 8 yr old, and adult) were used. The high viscosity of the dextran solutions tested (up to seven times that of water) negatively impacts nebulization, and results in poor performance with most delivery systems tested. Our results suggest that airway mucosal dextran concentrations associated with efficacy in previous animal and in vitro models are achievable with reasonable delivery times (</= 12 min) with only one of the delivery systems/formulations tested: the Pari LC STAR nebulizer, using a 2. 5-ml volume fill and a dextran concentration of 200 mg/ml.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".