Wide field of view quantitative imaging of cellular ATP release
Bibliographic record
Abstract
Although several mechanical stressors promote ATP secretion from eukaryotic cells, few mechanosensitive pathways for ATP release have been precisely characterized and none have been clearly identified. To facilitate progress, we report here a wide field of view (∼20 × 20 mm sample area) imaging technique paired with a quantitative image analysis to accurately map the dynamics of ATP release from a cell population. The approach has been tested on A549 cells stretched at high initial strain rate (2–5 s−1) or swelled by hypotonic shock. The amount of ATP secreted in response to a series of five graded stretch pulses (5–37% linear deformation, 1-s duration at 25°C) changed nonmonotonically with respect to strain amplitude and was inhomogeneous across the cell monolayer. In a typical experiment, extracellular ATP density averaged 250 fmol/mm2, but the area of detectable signal covered only ∼40% of the cells. In some areas, ATP accumulation peaked around 900 fmol/mm2, which corresponded to an estimated concentration of 4.5 µM. The total amount of ATP released from the combined stretch pulses reached 384 ± 224 pmol/million cells ( n = 4). Compared with stretch, hypotonic shock (50%, 30°C) elicited a more homogeneous ATP secretion from the entire cell population but at a lower yield totaling 28 ± 12 pmol/million cells ( n = 4). The quantitative extracellular ATP mapping of several thousand cells at once, with this wide field of view imaging system, will help identify ATP release pathways by providing unique insights on the dynamics and inhomogeneities of the cellular ATP secretion that are otherwise difficult to assess within the smaller field of view of a microscope.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".