Real-time imaging of inflation-induced ATP release in the ex vivo rat lung
Bibliographic record
Abstract
Extracellular ATP and other nucleotides are important autocrine/paracrine mediators that regulate diverse processes critical for lung function, including mucociliary clearance, surfactant secretion, and local blood flow. Cellular ATP release is mechanosensitive; however, the impact of physical stimuli on ATP release during breathing has never been tested in intact lungs in real time and remains elusive. In this pilot study, we investigated inflation-induced ATP release in rat lungs ex vivo by real-time luciferin-luciferase (LL) bioluminescence imaging coupled with simultaneous infrared tissue imaging to identify ATP-releasing sites. With LL solution introduced into air spaces, brief inflation of such edematous lung (1 s, ∼20 cmH2O) induced transient (<30 s) ATP release in a limited number of air-inflated alveolar sacs during their recruitment/opening. Released ATP reached concentrations of ∼10−6 M, relevant for autocrine/paracrine signaling, but it remained spatially restricted to single alveolar sacs or their clusters. ATP release was stimulus dependent: prolonged (100 s) inflation evoked long-lasting ATP release that terminated upon alveoli deflation/derecruitment while cyclic inflation/suction produced cyclic ATP release. With LL introduced into blood vessels, inflation induced transient ATP release in many small patchlike areas the size of alveolar sacs. Findings suggest that inflation induces ATP release in both alveoli and the surrounding blood capillary network; the functional units of ATP release presumably consist of alveolar sacs or their clusters. Our study demonstrates the feasibility of real-time ATP release imaging in ex vivo lungs and provides the first direct evidence of inflation-induced ATP release in lung air spaces and in pulmonary blood capillaries, highlighting the importance of purinergic signaling in lung function.
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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 | 0.001 |
| 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".