Enhancement of radiation therapy by ultrasonically-stimulated microbubbles in vitro: Effects of treatment scheduling on cell viability and production of ceramide
Bibliographic record
Abstract
Microbubbles are used as therapeutic agents to improve drug delivery across blood vessels and cell membranes. Recently, it was shown that the application of ultrasound and microbubbles can enhance the therapeutic effect of radiotherapy using in vitro and in vivo tumour models. This phenomenon depended on ultrasound, microbubble and x-ray exposure parameters. In this study, the effect of ultrasound-microbubble (US+MB) and ionizing radiation (XRT) treatment scheduling on cell viability and production of ceramide, an apoptosis messenger, was investigated in vitro. Human prostate cancer (PC3) and KHT-C murine fibrosarcoma cells in suspension were exposed to US+MB (f=500kHz; Pneg=580kPa; PD=32μs; PRF=3kHz; insonation time 30s; and 1% v/v microbubbles (DA04, Artenga Inc.)) and XRT (3 Gy single fraction). Timing between the treatments immediately (i.e. within 15 minutes), 3 and 6 hours and their order were varied. Following treatment, cell viability was assessed using clonogenic assay. Ceramide level within cells was quantified for up to 7.5 hours following treatment using immunohistochemistry and spectrophotometry. Ultrasound and microbubbles improved the therapeutic effect of radiotherapy in KHT-C and PC3 cells; cell death increased by ~3-5 folds with the combined treatment compared to each treatment alone. Maximal KHT-C cell death (70±2%) was achieved when US+MB was followed in three hours by XRT. KHT-C cell death of 43±2% and 25±2% was achieved with US+MB and XRT treatments, respectively. The maximal PC3 cell death (83±2%) was achieved when US+MB was followed by XRT immediately (i.e. within 15 minutes). PC3 cell death of 15±4% and 48±5% was achieved with US+MB and XRT treatments, respectively. US+MB and XRT treatments increased the level of ceramide in both cell lines compared to untreated controls. A correlation was found between cell death and ceramide at 3 h following treatment for the KHT-C and PC3 cells with correlation coefficients of 0.938 and 0.706, respectively. Ultrasonically-stimulated microbubbles can enhance the therapeutic effect of radiotherapy and the timing between the treatments and their order are important in the optimization of the therapeutic effect of radiotherapy. Future work will investigate this 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".