Lytic Release of Cellular ATP: Physiological Relevance and Therapeutic Applications
Bibliographic record
Abstract
The lytic release of ATP due to cell and tissue injury constitutes an important source of extracellular nucleotides and may have physiological and pathophysiological roles by triggering purinergic signalling pathways. In the lungs, extracellular ATP can have protective effects by stimulating surfactant and mucus secretion. However, excessive extracellular ATP levels, such as observed in ventilator-induced lung injury, act as a danger-associated signal that activates NLRP3 inflammasome contributing to lung damage. Here, we discuss examples of lytic release that we have identified in our studies using real-time luciferin-luciferase luminescence imaging of extracellular ATP. In alveolar A549 cells, hypotonic shock-induced ATP release shows rapid lytic and slow-rising non-lytic components. Lytic release originates from the lysis of single fragile cells that could be seen as distinct spikes of ATP-dependent luminescence, but under physiological conditions, its contribution is minimal <1% of total release. By contrast, ATP release from red blood cells results primarily from hemolysis, a physiological mechanism contributing to the regulation of local blood flow in response to tissue hypoxia, mechanical stimulation and temperature changes. Lytic release of cellular ATP may have therapeutic applications, as exemplified by the use of ultrasound and microbubble-stimulated release for enhancing cancer immunotherapy in vivo.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".