EXTH-41. A bench-top model for the sonodynamic therapy of medulloblastoma
Bibliographic record
Abstract
Abstract Medulloblastoma (MB), the most common malignant pediatric brain tumor, poses significant therapeutic challenges; current treatments often induce severe long-term morbidities. Sonodynamic therapy (SDT), a non-invasive modality using ultrasound to activate a sonosensitizer for targeted reactive oxygen species (ROS) generation, offers a promising alternative. However, in-vitro SDT models lack standardization and reproducible experimental setups. This study aimed to develop a bench-top model evaluating 5-aminolevulinic acid (5-ALA)-mediated SDT efficacy in the UW426 cell line, assessing ROS production, cell death, and proliferation. UW426 cells (SHH-activated, TP53-mutant) were incubated with 5-ALA (200µg/mL, 24h) to maximize protoporphyrin IX (PpIX) fluorescence. A 1.5MHz focused ultrasound (FUS) transducer (0.91MHz operating) targeted the base of 96-well plates; pressure wave delivery was confirmed by needle hydrophone. Groups included: untreated control, 5-ALA alone, FUS alone, and SDT (5-ALA + FUS). FUS/SDT utilized varied acoustic powers (1W, 3W, 6W) and durations (60s, 90s, 120s). 24h following treatment, intracellular ROS, apoptotic markers, and proliferation were quantified. SDT induced a statistically significant elevation in intracellular ROS levels in UW426 cells versus all controls (p<0.05). This correlated with significantly reduced cell viability and increased apoptotic cell death in the SDT group (p<0.05), demonstrating potent synergistic cytotoxicity. Proliferation was also significantly reduced in the SDT treatment group. Utilizing 6W power and 120s treatment duration yielded the most significant induction of ROS, cell death and decreased proliferation. In this study we demonstrated a reliable bench-top SDT model. The efficacy’s dependence on ultrasound parameters underscores the necessity of optimization and standardization.
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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) | 0.000 | 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 | 0.001 | 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".