Cystic fibrosis remodels the regulation of purinergic signaling by NTPDase1 (CD39) and NTPDase3
Bibliographic record
Abstract
Airway defenses are regulated by a complex purinergic signaling network located on the epithelial surfaces, where ATP stimulates the clearance of mucin and pathogens. The present study shows that the obstructive disease cystic fibrosis (CF) affects the activity, expression, and tissue distribution of two ectonucleotidases found critical for the regulation of ATP on airway surfaces: NTPDase1 and NTPDase3. Functional polarities and mRNA expression levels were determined on primary cultures of human bronchial epithelial (HBE) cells from healthy donors and CF patients. The in vitro model of the disease was completed by exposing CF HBE cultures for 4 days to supernatant of the mucopurulent material (SMM) collected from the airways of CF patients. We report that NTPDase1 and NTPDase3 are coexpressed on HBE cultures, where they regulate physiological and excess nucleotide concentrations, respectively. In aseptic conditions, CF epithelia exhibit >50% lower NTPDase1 activity, protein, and mRNA levels than normal epithelia, whereas these parameters are threefold higher for NTPDase3. Exposure to SMM induced opposite polarity shifts of the two NTPDases on both normal and CF epithelia, apical NTPDase1 being mobilized to basolateral surfaces and bilateral NTPDase3 to the apical surface. Their immunolocalization in human tissue revealed that NTPDase1 is expressed in epithelial, inflammatory, and endothelial cells, whereas NTPDase3 is restricted to epithelial cells. Furthermore, the SMM-exposed CF HBE cultures reproduced the impact of the disease on their in vivo distribution. This study provides evidence that an extensive remodeling of the enzymatic network regulating clearance occurs in the airways of CF patients.
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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) | 0.001 | 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 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".