Permeation of losartan across human respiratory epithelium: An in vitro study with Calu-3 cells
Bibliographic record
Abstract
The potential for nasal delivery of losartan, a drug with poor oral bioavailability, was investigated using Calu-3 cells. Epithelial permeation of the drug with or without dimethyl-beta-cyclodextrin (DM-beta-CD) and glycocholate was investigated. Possible transport mechanism of the compound and epithelial mucosal tolerance were screened. Reversibility of epithelial membrane perturbation was also investigated by measuring transepithelial electrical resistance (TEER) recovery over a 24-h period following drug formulation exposure. The permeability coefficient of losartan was 1.3 + or - 0.5 x 10(-6) cm s(-1). This flux was not significantly different from that of formulations containing DM-beta-CD (0.5 and 1.0%) or glycocholate (0.5%). However, the formulation with 1.0% glycocholate significantly increased losartan permeation 7-fold. Losartan flux across the cells was concentration-dependent. Serosal to mucosal permeation was significantly higher than mucosal to serosal permeation. Concentration-dependency, as well as polarity in transport indicated that the flux of the compound across Calu-3 cells was not limited to passive diffusion. Cells exposed to DM-beta-CD (0.5 and 1.0%) and glycocholate (0.5%) caused no significant change in TEER and mitochondrial dehydrogenase activity (MDH). The results of the study showed that losartan may be a suitable drug candidate for nasal delivery.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".