Microbubble and ultrasound radioenhancement of bladder cancer
Bibliographic record
Abstract
BACKGROUND: Tumour vasculature is an important component of tumour growth and survival. Recent evidence indicates tumour vasculature also has an important role in tumour radiation response. In this study, we investigated ultrasound and microbubbles to enhance the effects of radiation. METHODS: Human bladder cancer HT-1376 xenografts in severe combined immuno-deficient mice were used. Treatments consisted of no, low and high concentrations of microbubbles and radiation doses of 0, 2 and 8 Gy in short-term and longitudinal studies. Acute response was assessed 24 h after treatment and longitudinal studies monitored tumour response weekly up to 28 days using power Doppler ultrasound imaging for a total of 9 conditions (n=90 animals). RESULTS: Quantitative analysis of ultrasound data revealed reduced blood flow with ultrasound-microbubble treatments alone and further when combined with radiation. Tumours treated with microbubbles and radiation revealed enhanced cell death, vascular normalisation and areas of fibrosis. Longitudinal data demonstrated a reduced normalised vascular index and increased tumour cell death in both low and high microbubble concentrations with radiation. CONCLUSION: Our study demonstrated that ultrasound-mediated microbubble exposure can enhance radiation effects in tumours, and can lead to enhanced tumour cell death.
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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 | 0.000 | 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".