Characterization of Side Population Cells from Human Airway Epithelium
Bibliographic record
Abstract
The airway epithelium is the first line of contact with the inhaled external environment and is continuously exposed to and injured by pollutants, allergens, and viruses. However, little is known about epithelial repair and in particular the identity and role of tissue resident stem/progenitor cells that may contribute to epithelial regeneration. The aims of the present study were to identify, isolate, and characterize side population (SP) cells in human tracheobronchial epithelium. Epithelial cells were obtained from seven nontransplantable healthy lungs and four asthmatic lungs by pronase digestion. SP cells were identified by verapamil-sensitive efflux of the DNA-binding dye Hoechst 33342. Using flow cytometry, CD45(-) SP, CD45(+) SP, and non-SP cells were isolated and sorted. CD45(-) SP cells made up 0.12% +/- 0.01% of the total epithelial cell population in normal airway but 4.1% +/- 0.06% of the epithelium in asthmatic airways. All CD45(-) SP cells showed positive staining for epithelial-specific markers cytokeratin-5, E-cadherin, ZO-1, and p63. CD45(-) SP cells exhibited stable telomere length and increased colony-forming and proliferative potential, undergoing population expansion for at least 16 consecutive passages. In contrast with non-SP cells, fewer than 100 CD45(-) SP cells were able to generate a multilayered and differentiated epithelium in air-liquid interface culture. SP cells are present in human tracheobronchial epithelium, exhibit both short- and long-term proliferative potential, and are capable of generation of differentiated epithelium in vitro. The number of SP cells is significantly greater in asthmatic airways, providing evidence of dysregulated resident SP cells in the asthmatic epithelium. Disclosure of potential conflicts of interest is found at the end of this article.
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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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".