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The rapid integration of artificial intelligence (AI) and machine learning (ML) into medical devices has underscored the need for transparency in regulatory reporting. In 2021, the U.S. Food and Drug Administration (FDA) issued Good Machine Learning Practice (GMLP) principles, but adherence in FDA-reviewed devices remains uncertain. We reviewed 1,012 summaries of safety and effectiveness (SSEDs) for AI/ML-enabled devices approved or cleared by the FDA between 1970 and December 2024. Transparency in model development and performance was assessed using a novel AI Characteristics Transparency Reporting (ACTR) score across 17 categories. The average ACTR score was 3.3 out of 17, with modest improvement by 0.88 points (95% CI, 0.54–1.23) after the 2021 guidelines. Nearly half of devices did not report a clinical study and over half did not report any performance metric. These findings highlight transparency gaps and emphasize the need for enforceable standards to ensure trust in AI/ML medical technologies.

Pediatric high-grade gliomas are the leading cause of brain cancer-related death in children. High-grade gliomas include clinically and molecularly distinct subtypes that stratify by anatomical location into diffuse midline gliomas (DMG) such as diffuse intrinsic pontine glioma (DIPG) and hemispheric high-grade gliomas. Neuronal activity drives high-grade glioma progression both through paracrine signaling(1,2) and direct neuron-to-glioma synapses(3-5). Glutamatergic, AMPA receptor-dependent synapses between neurons and malignant glioma cells have been demonstrated in both pediatric(3) and adult high-grade gliomas(4), but neuron-to-glioma synapses mediated by other neurotransmitters remain largely unexplored. Using whole-cell patch clamp electrophysiology, in vivo optogenetics and patient-derived glioma xenograft models, we have now identified functional, tumor-promoting GABAergic neuron-to-glioma synapses mediated by GABAA receptors in DMGs. GABAergic input has a depolarizing effect on DMG cells due to NKCC1 expression and consequently elevated intracellular chloride concentration in DMG tumor cells. As membrane depolarization increases glioma proliferation(3), we find that the activity of GABAergic interneurons promotes DMG proliferation in vivo. Increasing GABA signaling with the benzodiazepine lorazepam, a positive allosteric modulator of GABAA receptors commonly administered to children with DMG for nausea or anxiety, increases GABAA receptor conductance and increases glioma proliferation in orthotopic xenograft models of DMG. Conversely, levetiracetam, an anti-epileptic drug that attenuates GABAergic neuron-to-glioma synaptic currents, reduces glioma proliferation in patient-derived DMG xenografts and extends survival of mice bearing DMG xenografts. Concordant with gene expression patterns of GABAA receptor subunit genes across subtypes of glioma, depolarizing GABAergic currents were not found in hemispheric high-grade gliomas. Accordingly, neither lorazepam nor levetiracetam influenced the growth rate of hemispheric high-grade glioma patient-derived xenograft models. Retrospective real-world clinical data are consistent with these conclusions and should be replicated in future prospective clinical studies. Taken together, these findings uncover GABAergic synaptic communication between GABAergic interneurons and diffuse midline glioma cells, underscoring a tumor subtype-specific mechanism of brain cancer neurophysiology with important potential implications for commonly used drugs in this disease context.Competing Interest StatementM.M. holds equity in MapLight Therapeutics and Syncopation Life Sciences.