In Vitro Sonodynamic Therapy Using a High Throughput 3D Glioblastoma Spheroid Model with 5‐ALA and TMZ Sonosensitizers
Bibliographic record
Abstract
Sonodynamic therapy (SDT) administered using low-intensity pulsed ultrasound and sonosensitizers is an emerging, minimally invasive, targeted deep-tissue therapy for solid tumors such as glioblastoma multiforme (GBM). Initial clinical trials show promising outcomes for SDT treatments of GBM. A crucial aspect of SDT is the sonosensitizer that interacts with ultrasound, facilitating energy transfer to the tumor, thus inducing therapeutic efficacy. Current in vitro methods for determining the therapeutic efficacies of sonosensitizers are time-consuming and expensive. A novel high-throughput magnetically printed 3D GBM model is used to overcome this challenge. The hypothesis is that the use of two sonosensitizers, one a chemotherapeutic drug, enhances SDT efficacy through their additive chemical interactions. The GBM model is used to evaluate the effectiveness of two sonosensitizer molecules, 5-aminolevulinic acid (5-ALA) and theU.S. Food and Drug Administration (FDA)-approved chemotherapeutic drug Temozolomide (TMZ). It is confirmed that implement high-throughput GBM models to evaluate sonosensitizer combinations and their efficacies is feasible and, for the first time, show that the combined effect of both sensitizers, 5-ALA and TMZ, is superior for preventing spheroid growth than employing each molecule separately. This finding is relevant for future clinical trials of GBM treatment with SDT.
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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 | 0.000 | 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) | 0.000 | 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".