Imaging and characterization of stretch‐induced ATP release from alveolar A549 cells
Bibliographic record
Abstract
Abstract Mechano-transduction at cellular and tissue levels often involves ATP release and activation of the purinergic signalling cascade. In the lungs, stretch is an important physical stimulus but its impact on ATP release, the underlying release mechanisms and transduction pathways are poorly understood. Here, we investigated the effect of unidirectional stretch on ATP release from human alveolar A549 cells by real-time luciferin-luciferase bioluminescence imaging coupled with simultaneous infrared imaging, to monitor the extent of cell stretch and to identify ATP releasing cells. In subconfluent (<90%) cell cultures, single 1 s stretch (10-40%)-induced transient ATP release from a small fraction (1.5%) of cells that grew in number dose-dependently with increasing extent of stretch. ATP concentration in the proximity (150 μm) of releasing cells often exceeded 10 μm, sufficient for autocrine/paracrine purinoreceptor stimulation of neighbouring cells. ATP release responses were insensitive to the putative ATP channel blockers carbenoxolone and 5-nitro-2-(3-phenylpropyl-amino) benzoic acid, but were inhibited by N-ethylmaleimide and bafilomycin. In confluent cell cultures, the maximal fraction of responding cells dropped to <0.2%, but was enhanced several-fold in the wound/scratch area after it was repopulated by new cells during the healing process. Fluo8 fluorescence experiments revealed two types of stretch-induced intracellular Ca(2+) responses, rapid sustained Ca(2+) elevations in a limited number of cells and delayed secondary responses in neighbouring cells, seen as Ca(2+) waves whose propagation was consistent with extracellular diffusion of released ATP. Our experiments revealed that a single >10% stretch was sufficient to initiate intercellular purinergic signalling in alveolar cells, which may contribute to the regulation of surfactant secretion and wound healing.
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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 | 0.001 | 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".