Characterization of Calu-3 cell monolayers as a model of bronchial epithelial transport: organic cation interaction studies
Bibliographic record
Abstract
BACKGROUND: To fully exploit organic cation transporters for targeted drug delivery in the lung, the use of a readily available and well-characterized tissue culture model and cheap easily detectable substrates is indispensable. OBJECTIVES: To investigate the suitability of Calu-3 as tissue model for characterizing organic cation permeation across the bronchial cells using a fluorescent dye, 4-(4-(Dimethylamino)styryl)-N-methylpyridinium iodide (4-DI-1-ASP). METHODS: Substrate uptake, inhibition, and transport were performed to establish active transport mechanism. Organic cation transporter expression was determined with quantitative polymerase chain reaction (qPCR), immune-histochemistry, and fluorescent microscopy. RESULTS: 4-Di-1-ASP uptake in Calu-3 cells was concentration (K(m) = 2.7 ± 0.3 mM, V(max) = 4.6 ± 2.6 nmol/µg protein/30 min), temperature (uptake at 37°C>>4°C), and pH dependent (higher uptake at pH ≥ 7). L-carnitine, verapamil, and corticosterone significantly inhibited its uptake with IC(50) of 28.2, 0.81, and 0.12 mM, respectively. Transport of the dye across the cells was polarized (AP→BL transport was 2.5-fold > BL→AP), saturable (Km = 43.9 ± 3.2) (µM; Vmax =0.0228 ± nmol/cm(2)/sec) and reduced 3-fold by metabolic inhibition. The expression pattern of the organic cation transporters (OCT) and carnitine/organic cation transporter (OCTN) isoforms was: OCT1<<OCT3 <OCTN1
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".