Evidence map›Paper›PMID 40896334›Full record

ArticleFrontiers in neuroscience2025

Cenobamate reduces epileptiform activity in the

Ferdinand Forberger, Fabiana Santana Kragelund, Katrin Porath, Rüdiger Köhling, Timo Kirschstein, Falko Lange

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Article in Frontiers in neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Ferdinand ForbergerOscar Langendorff Institute of Physiology, University of Rostock, Rostock, Germany.
Fabiana Santana KragelundOscar Langendorff Institute of Physiology, University of Rostock, Rostock, Germany.
Katrin PorathOscar Langendorff Institute of Physiology, University of Rostock, Rostock, Germany.
Rüdiger KöhlingOscar Langendorff Institute of Physiology, University of Rostock, Rostock, Germany.
Timo KirschsteinOscar Langendorff Institute of Physiology, University of Rostock, Rostock, Germany.
Falko LangeOscar Langendorff Institute of Physiology, University of Rostock, Rostock, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Epileptic seizures are a common clinical sign in patients suffering from high-grade glioma. In addition to therapeutic interventions aiming to prolong the remaining lifespan, maintaining quality of life is a cornerstone of current treatment concepts. Consequently, anticonvulsants are frequently applied to keep seizures at bay, but drug resistance is still a challenge. There is a need for new anticonvulsants to address this issue. Therefore, for the first time, we evaluated the efficacy of cenobamate, a novel anticonvulsant shown to inhibit persistent sodium currents and modulate GABA Methods: To study the effect of cenobamate (60 and 120 μmol/L), we recorded local field potentials and evoked spontaneous network deflections using an acute disinhibition solution. To analyze seizure-like events (SLEs), we employed a deep learning approach, further supported by power spectral density (PSD) analysis. Results: Cenobamate attenuated the proportion of recording time occupied by SLEs, mainly by reducing their duration in slices of both sham-operated and F98 tumor-bearing animals. Additionally, the spike load within SLEs was diminished by the anticonvulsant. The PSD analysis confirmed the reduction of spike frequencies abundant in seizure-like events. Conclusion: Our data show that cenobamate effectively reduced the epileptic phenotype in glioma-bearing brain slices. We hence suggest that cenobamate may effectively contribute to seizure control in tumor-associated epilepsy.

Indexed as

cenobamatedeep learningelectrophysiologyepilepsyglioma

Identifiers

PMID40896334
PMCPMC12392110

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.