Single cell level analysis of ATP release kinetics and cell fate following ultrasound targeted microbubble cavitation using microscopy techniques
Bibliographic record
Abstract
It is known that ultrasound-targeted microbubble cavitation (UTMC) can induce vasodilation. This image-guided spatially targeted approach is called provascular therapy when used as a radiotherapy sensitizer in radiation oncology. Extracellular adenosine-5'-triphosphate (eATP), which plays an important role in vascular tone regulation, is released by cells following UTMC, possibly through sonoporation (formation of temporary and non-deadly pores in the cell membrane) and/or cell death. Herein, we were interested in quantifying UTMC-mediated ATP released in vitro using a microfluidics-based model and study its relationship with cell fate to better understand and improve bioeffects induced by UTMC. Lipid microbubbles (MB, Definity®), luciferin-luciferase (LL - for eATP quantification), and propidium iodide (PI - poration tracer) were flowed over HUVEC cells cultured in a microfluidic device. Ultrasound at 1 MHz, varying in pressure (peak negative pressure: 300, 400 kPa) and length (10, 100, 1000 cycles) were applied to the chip. The LL chemiluminescent signal after the ultrasound pulse was acquired with an EMCCD camera to characterize ATP release kinetics. Then, a viability assay was performed with calcein-AM. An in-house MATLAB program pairing eATP kinetics with PI/calcein data was used to classify cells into three categories (sonoporated, dead, and untreated). Within the testing conditions, a single UTMC pulse caused between 4% and 55% PI-positive (PI+) cells in the ultrasound-treated area. Amongst PI+ cells, we generally found more dead cells than sonoporated cells, except for milder pulses (300 kPa; 10 and 100 cycles). The analysis of individual responses of ATP release demonstrated that dead cells released more ATP (up to 22.4 ± 12.2 fmol/cell) than sonoporated cells (6.8 ± 3.4 fmol/cell) and at a faster release rate which peaked at 4s. This study showed that sonoporation plays a significant role in UTMC-mediated ATP release, advancing our understanding of UTMC's potential use as a radiosensitizer in solid tumors.
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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 | 0.001 | 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".