Effect of Treatment Sequencing on the Tumor Response to Combined Treatment With <scp>Ultrasound‐Stimulated</scp> Microbubbles and Radiotherapy
Bibliographic record
Abstract
OBJECTIVES: To investigate whether timing and sequencing of ultrasound-stimulated microbubbles (USMBs) and external beam radiotherapy (XRT) affect the treatment response in a preclinical prostate cancer model. METHODS: Prostate cancer xenografts were treated with ultrasound-stimulated lipid microspheres before and after 8-Gy XRT. Treatments were separated by 0, 3, 6, 12, and 24 hours, with 5 tumors per group. Tumor effects were evaluated by microvessel density (measured by CD31 staining), cell death (terminal deoxynucleotidyl transferase deoxyuridine triphosphate nick end-labeling and hematoxylin-eosin staining), and hypoxia (carbonic anhydrase 9 staining). RESULTS: Administering USMBs 6 hours before XRT showed the maximum treatment effect using all 3 assays. At this time, the mean cell death index ± SD was 36% ± 10%, compared with 19% ± 4% for no separation between USMB treatment and XRT; the microvessel density was 9 ± 3 counts per field (19 ± 5 without separation); and the percentage of hypoxic cells was 10% ± 5% (21% ± 4%). The observed treatment effect was greater with USMBs before XRT than when administering XRT first, but these differences were not statistically significant. CONCLUSIONS: The maximum tumor effect was observed with USMBs delivered 6 hours before XRT. The sequencing of treatment did not have a significant effect on the tumor response.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.000 | 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 teacher head, 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".