Exploring Low-Intensity Pulsed Ultrasound As a Non-Invasive Strategy for Medulloblastoma Treatment
Bibliographic record
Abstract
Medulloblastoma (MB), the most common malignant pediatric brain tumor, poses significant clinical challenges due to its invasive nature, high recurrence rates, and treatment-associated neurocognitive impairments. Current therapeutic strategies, including surgical resection, chemotherapy, and radiation, remain invasive and contribute to long-term side effects. The Sonic Hedgehog (Shh) subgroup of MB, driven by aberrant Hedgehog (Hh) signaling, represents a promising target for intervention. The primary cilium (PC), a key regulator of the Shh pathway, has emerged as a potential therapeutic target. This review explores low-intensity pulsed ultrasound (LIPUS) as a non-invasive strategy for modulating primary cilia and disrupting aberrant Shh signaling in MB. By leveraging mechanical stimulation, LIPUS may offer a novel approach to overcoming challenges associated with tumor heterogeneity, blood-brain barrier (BBB) permeability, and treatment resistance. A literature search was conducted using PubMed and Web of Science, focusing on studies examining the role of the primary cilium in Hh signaling, medulloblastoma pathogenesis, and the application of LIPUS in neuro-oncology. Inclusion criteria prioritized peer-reviewed studies published within the last 10 years. Relevant methodologies, findings, and research gaps were synthesized to evaluate the feasibility of LIPUS in MB therapy. LIPUS has been shown to modulate ciliary length and function in neuronal models, demonstrating its potential to influence Shh pathway activity. Focused ultrasound techniques have also been utilized to enhance drug delivery across the BBB, presenting an additional therapeutic advantage. While mechanical stimulation has been explored in other cancer models, studies specifically investigating LIPUS in MB remain limited. Preliminary findings indicate that LIPUS may provide a pathway-independent mechanism for targeting tumor heterogeneity and resistant cell populations. LIPUS presents a promising non-invasive modality for MB treatment by targeting primary cilia and disrupting aberrant Shh signaling. Further research is required to optimize sonication parameters, assess long-term effects, and evaluate translational feasibility in preclinical models. Integrating LIPUS into current therapeutic strategies may enhance treatment precision, reduce neurotoxicity, and improve outcomes for pediatric MB patients. Keywords: Medulloblastoma, Sonic Hedgehog pathway, Primary Cilium, Low-Intensity Pulsed Ultrasound, Focused Ultrasound, Non-Invasive Therapy, Blood-Brain Barrier, Tumor Heterogeneity
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".