ATPS-30INTRATUMORAL MODULATION THERAPY FOR GLIOBLASTOMA
Bibliographic record
Abstract
BACKGROUND: There is a critical need for innovative and effective treatment strategies for glioblastoma (GBM). The clinical indications for neuromodulation therapy in the brain are rapidly expanding and this technique is now the standard of surgical care for select neurological diseases (e.g., Parkinson's Disease). It is well known that glial tumors are vulnerable to perturbations of the electrochemical environment; however, direct neuromodulation techniques have not been exploited for glioma management. METHODS: Our group has developed an in vitro model to deliver continuous alternating or pulsed, low voltage electric current directly into GBM cultures, a technique we call intratumoral modulation therapy (IMT). GBM cell lines and primary GBM cells derived from operative specimens were studied for vulnerability to IMT without and with temozolomide (TMZ) or oncogene-targeting strategies. An F98 rat GBM model has also been established to evaluate the benefits of IMT in vivo. RESULTS: We report a marked vulnerability of patient GBM cells, but not primary neurons, to a spectrum of IMT parameters. GBM cells treated with IMT undergo enhanced caspase 3-activation and apoptosis, and develop heightened sensitivity to TMZ. Uptake and biodistribution of siRNA was enhanced in primary GBM cells, along with target gene knockdown and functional effect, in the presence of IMT. Preliminary in vivo studies indicate that IMT markedly attenuates GBM growth without significant treatment-related morbidity. CONCLUSIONS: The proposed use of minimally invasive implantable stimulation devices offers distinct advantages over existing electrotherapies, including direct lesion targeting for delivery of continuous IMT, titratible stimulation settings to maximize benefit and lessen off-target effects and low maintenance, concealed hardware for improved self-perception and quality of life. Results from these investigations provide proof of principle evidence that supports further evaluation of IMT for the treatment of GBM.
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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) | 0.000 | 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) | 0.001 | 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 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".