Characterization of Commercially Available Human Primary Alveolar Epithelial Cells
Bibliographic record
Abstract
Abstract In vitro lung research requires appropriate cell culture models that adequately mimic in vivo structure and function. Previously, researchers extensively used commercially available and easily expandable A549 and NCI-H441 cells, which replicate some but not all features of alveolar epithelial cells. Specifically, these cells are often restricted by terminally altered expression while lacking important alveolar epithelial characteristics. Of late, human primary alveolar epithelial cells (hPAEpCs) have become commercially available but are so far poorly specified. Here, we applied a comprehensive set of technologies to characterize their morphology, surface marker expression, transcriptomic profile, and functional properties. At optimized seeding numbers of 7,500 cells per square centimeter and growth at a gas–liquid interface, hPAEpCs formed regular monolayers with tight junctions and amiloride-sensitive transepithelial ion transport. Electron microscopy revealed lamellar body and microvilli formation characteristic for alveolar type II cells. Protein and single-cell transcriptomic analyses revealed expression of alveolar type I and type II cell markers; yet, transcriptomic data failed to detect NKX2-1, an important transcriptional regulator of alveolar cell differentiation. With increasing passage number, hPAEpCs transdifferentiated toward alveolar-basal intermediates characterized as SFTPC−, KRT8high, and KRT5− cells. In spite of marked changes in the transcriptome as a function of passaging, Uniform Manifold Approximation and Projection plots did not reveal major shifts in cell clusters, and epithelial permeability was unaffected. The present work delineates optimized culture conditions, cellular characteristics, and functional properties of commercially available hPAEpCs. hPAEpCs may provide a useful model system for studies on drug delivery, barrier function, and transepithelial ion transport in vitro.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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) | 0.003 | 0.002 |
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".