Establishing Intratumoral Modulation Therapy as a New Treatment Modality for High Grade Gliomas
Bibliographic record
Abstract
Glioblastoma (GBM) is the most common and lethal primary brain cancer in adults despite aggressive treatments with surgery and chemo-radiation. Advances in electrotherapeutics offer a foundation for developing new treatment modalities that exploit an innate vulnerability of glioblastoma (GBM). Low intensity, non-ablative electric fields are innocuous to normal neural structure, but incite GBM cell apoptosis by putatively disrupting cytokinesis and transmembrane ion homeostasis. Our collaborative research group is pioneering a new electrotherapeutic technology for GBM called Intratumoral Modulation Therapy (IMT) which uses customized, implanted bioelectrodes to deliver sustained, titratable and focused therapeutic electric fields into tumor-affected brain regions. My work has confirmed and expanded the group’s previous in vitro evidence of IMT efficacy against GBM and diffuse intrinsic pontine glioma (DIPG) and has demonstrated potent anti-neoplastic, pro-apoptotic effects of IMT in vitro without significant impact on non-cancerous post-mitotic neurons. The co-application of IMT also potentiates the benefits of chemotherapy and gene therapy. We have created a robust in vivo IMT model using allograft GBM cells in Fischer rats to test the efficacy of IMT in vivo. The GBM animal studies to date have demonstrated proof-of-concept efficacy of IMT against GBM using rudimentary, single-contact bioelectrodes. However, single-contact electrodes cannot adequately accommodate the entire tumor or GBM resection bed where recurrence is otherwise inevitable. In order to translate this technology to clinical use, new special purpose bioelectrodes must be designed and tested to optimize and contour IMT coverage. This thesis yielded key insight into the bioelectrode configuration and treatment settings for effective and safe IMT delivery in GBM and DIPG. Advances in this technology will facilitate clinical translation of IMT as a critically needed therapy for these devastating brain cancers.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".