Factors Affecting Magnetic Retention of Particles in the Upper Airways: An <i>In Vitro</i> and <i>Ex Vivo</i> Study
Bibliographic record
Abstract
This paper presents the results of experiments using an in vitro model and an ex vivo animal model (Rana catesbeiana) to study magnetic particle retention in the conducting airways, specifically the trachea and bronchi. The purpose of these experiments was to determine the significant factors for retention of magnetic particles deposited from an aerosol at the airway surface using a magnetic field. The results indicate that the apparent viscosity of the mucus layer at low shear rates is the most significant obstacle to particle retention. The results also show that particle size and aggregation play major roles in particle retention. The mucus transport rate, unlike the effect of fluid velocity in intravenous applications, did not appear to be a determining factor for particle retention. It was also found that a suitably designed magnetic system, aside from having a high intensity, needs to exert a strong radial field to promote particle aggregation. The findings suggest that one possible approach to magnetic particle retention could be delivery of a mucolytic agent along with the drug particles. This study provides the fundamentals needed for development of a targeted magnetic drug delivery system for inhaled therapeutic aerosol particles.
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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 | 0.001 |
| 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 | 0.001 | 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".