Feasibility Investigation of Cellulose Polymers for Mucoadhesive Nasal Drug Delivery Applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The feasibility of various cellulose polymer derivatives, including methylcellulose (MC), hydroxypropyl methylcellulose (HPMC), sodium-carboxymethylcellulose (sodium-CMC), and cationic-hydroxyethylcellulose (cationic-HEC), for use as an excipient to enhance drug delivery in nasal spray formulations was investigated. Three main parameters for evaluating the polymers in nasal drug delivery applications include rheology, ciliary beat frequency (CBF), and permeation across nasal tissue. Reversible thermally induced viscosity enhancement was observed at near nasal physiological temperature when cellulose derivatives were combined with an additional excipient, poly(vinyl caprolactam)-poly(vinyl acetate)-poly(ethylene glycol) graft copolymer (PVCL-PVA-PEG). Cationic-HEC was shown to enhance acyclovir permeation across the nasal mucosa. None of the tested cellulosic polymers caused any adverse effects on porcine nasal tissues and cells, as assessed by alterations in CBF. Upon an increase in polymer concentration, a reduction in CBF was observed when ciliated cells were immersed in the polymer solution, and this decrease returned to baseline when the polymer was removed. While each cellulose derivative exhibited unique advantages for nasal drug delivery applications, none stood out on their own to improve more than one of the performance characteristics examined. Hence, these data may be useful for the development of new cellulose derivatives in nasal drug formulations.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it