Pulmonary surfactant and prostaglandin <scp>E<sub>2</sub></scp> in airway smooth muscle relaxation of human and male guinea pigs
Bibliographic record
Abstract
Abstract Pulmonary surfactant serves as a barrier to respiratory epithelium but can also regulate airway smooth muscle (ASM) tone. Surfactant (SF) relaxes contracted ASM, similar to β2‐agonists, anticholinergics, nitric oxide, and prostanoids. The exact mechanism of surfactant relaxation and whether surfactant relaxes hyperresponsive ASM remains unknown. Based on previous research, relaxation requires an intact epithelium and prostanoid synthesis. We sought to examine the mechanisms by which surfactant causes ASM relaxation. Organ bath measurements of isometric tension of ASM of guinea pigs in response to exogenous surfactant revealed that surfactant reduces tension of healthy and hyperresponsive tracheal tissue. The relaxant effect of surfactant was reduced if prostanoid synthesis was inhibited and/or if prostaglandin E2‐related EP2 receptors were antagonized. Atomic force microscopy revealed that human ASM cells stiffen during contraction and soften during relaxation. Surfactant softened ASM cells, similarly to the known bronchodilator prostaglandin E2 (PGE2) and the cell softening was abolished when EP4 receptors for PGE2 were antagonized. Elevated levels of PGE2 were found in cultures of normal human bronchial epithelial cells exposed to pulmonary surfactant. We conclude that prostaglandin E2 and its EP2 and EP4 receptors are likely involved in the relaxant effect of pulmonary surfactant in airways.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".