Background:Gangliogliomas (GGs) are low-grade glioneuronal tumors that frequently present with drug-resistant epilepsy. Although their indolent course contrasts with their high epileptogenic potential, the oncogenic mechanisms sustaining neuronal precursor-like populations within the tumor microenvironment remain poorly defined. Methods:We performed spatial transcriptomic profiling on eight histologically confirmed GGs and matched healthy cortex to map the cellular and molecular architecture of the tumor microenvironment. Integrated analysis with weighted gene correlation network analysis (WGCNA) defined recurrent oncogenic programs and spatially resolved tumor-stroma interactions. Results:Eight conserved gene modules emerged, encompassing physiological cortical, reactive glial, and oncopathological programs. The latter captured extracellular matrix (ECM) remodeling, vascular-immune signaling, and persistence of immature, proliferative neuronal-like states. Spatial modeling revealed that these oncopathological programs form structured niches at the tumor-brain interface, where radial glia-derived neuronal-like tumor cells coexist with immune and stromal elements engaged in ECM turnover and cytokine signaling. Conclusions:Ganglioglioma represents a hybrid glioneuronal neoplasm in which developmental neuronal programs are co-opted by tumor-associated stromal and immune cues. This convergence establishes a permissive oncogenic niche that sustains precursor-like tumor cells and provides a mechanistic basis for both the tumor's benign growth and its intrinsic epileptogenicity.

BACKGROUND:Glioblastoma (GB) is the most aggressive primary brain tumor in adults. Tumor-associated epilepsy at diagnosis (TAE) is common, yet its prognostic significance remains unclear. METHODS:We analyzed a retrospective multicenter test cohort of 855 GB patients (Aachen, Hamburg, Bielefeld) and validated findings in a prospectively collected cohort of 344 patients (Erlangen). Survival was assessed using multivariable Cox regression, propensity score matching, and interaction modeling of TAE and extent of resection (EOR). Molecular profiling included methylation-based classification, epigenetic deconvolution, and spatial transcriptomics. RESULTS:TAE was independently associated with improved survival (HR 0.81, 95% CI 0.69-0.99, P = .036, absolute survival advantage ∼4-5 months). This effect was validated in the independent cohort (C-index 0.68 (95% CI 0.62-0.74) and persisted in propensity-matched analyses (HR 0.74, 95% CI 0.56-0.96, P = .027). Interaction modeling revealed that gross total resection (GTR) improved survival in both groups but particularly in patients with TAE (EOR interaction HR 0.69, 95% CI 0.49-0.99, P = .041). In this subgroup, partial resection provided no significant advantage over biopsy, whereas patients without seizures benefited incrementally from both partial resection and GTR. Molecular analysis demonstrated enrichment of the RTK II subtype, differentiated cell states, and an inflammatory microenvironment in glioblastoma with TAE; tumors without seizures displayed neuronal and stem-like features. Functional validation using Electrogenomics showed that glioblastoma cortical slices with increased inflammatory score exhibited synchronization of action potentials characteristic for seizure-like epileptiform activity. CONCLUSIONS:TAE at diagnosis is a favorable prognostic marker in GB, defining a biologically distinct subgroup. Seizure status modifies the prognostic effect of surgical resection, underscoring the importance of GTR particularly in patients presenting with TAE.

Glioblastoma is a highly malignant brain tumor in which maximal safe resection is associated with improved survival, yet the oncological benefit of resection varies by molecular subtype. Recent work has shown that DNA methylation-defined subtypes, particularly receptor tyrosine kinase (RTK) I and II, benefit from complete CE (contrast-enriched) resection compared to mesenchymal tumors, highlighting the need for pre- or intraoperative tools that guide resection based on tumor biology. Here, we present iSTAMP ( i ntraoperative S patially-informed T umor A rchitecture M apping and P rofiling) a real-time, label-free molecular classification framework using stimulated Raman scattering microscopy and graph-based deep learning to predict glioblastoma epigenetic subtypes intraoperatively (within 5-7 minutes). Across 1,295 intraoperative tissue samples from 236 patients profiled with EPIC methylation arrays, our graph attention network achieved high predictive performance for all major subtypes (AUC range 0.88-0.99), with spatially stable predictions across tumor regions. RTK subtypes, but not mesenchymal tumors, showed significant survival benefit from GTR (HR = 0.42, p = 6.1 ×10 -6 ). Explainable AI methods revealed subtype-specific histopathological features, including necrosis and macrophage infiltration in mesenchymal tumors versus glio-fibrillary matrix or axon-rich regions in RTK tumors. Spatial transcriptomic validation confirmed cellular correlates with defined subtype specific SRH features. These findings support the integration of Raman-based molecular diagnostics into intraoperative workflows to guide biologically informed surgical strategies in glioblastoma.

Glioblastoma (GB) integrates into the human brain by exploiting spatially restricted neuronal microenvironments at tumor margins. Combining magnetoencephalography-based functional mapping in patients with GB, spatially resolved biopsies, single-cell RNA sequencing, spatial transcriptomics, and electrophysiological profiling in human cortical slice models, we identify peritumoral connectivity hubs enriched for synaptogenic and immature neuronal programs. Connectivity-rich regions preferentially involve projection-capable excitatory neurons and display convergent activation of the WNK-SPAK-NKCC1 chloride homeostasis, consistent with a reduction in inhibition via GABAergic transmission in peritumoral neurons. GB-conditioned neurons exhibit developmental regression, impaired inhibitory control, and immature dendritic spine remodeling while network-level recordings reveal a GABA-sensitive reorganization of circuit topology. NKCC1 blockade reduces tumor-neuron synaptic integration and dampens functional network connectivity. Clinically, peritumoral degree centrality is an independent predictor of survival beyond established covariates. These findings establish neuronal immaturity as a functional substrate for tumor-neuron connectivity and define actionable biomarkers and pathways at the tumor-brain interface.

OBJECTIVE:Epilepsy affects approximately 50 million people worldwide and, although primarily attributed to neuronal dysfunction, increasing evidence highlights a critical role of glial cells, particularly astrocytes, in the pathophysiological mechanisms. Mesial temporal lobe epilepsy (MTLE), the most common form of drug-resistant epilepsy, is frequently associated with hippocampal sclerosis (HS) and pronounced astrogliosis. Given the limited efficacy of current anti-seizure medication (ASM) and the side effects of surgical hippocampus removal, there is a need for more specific and effective therapies that potentially address non-neuronal mechanisms. Astrocytes, with their inherent heterogeneity, are key candidates for such approaches due to their role in regulating and maintaining neuronal activity. METHODS:To investigate subtype-specific astrocyte alterations in MTLE, we performed immunofluorescence analyses of human dentate gyrus (DG) tissue from MTLE patients (HS1, HS2, and noHS according to the International League Against Epilepsy (ILAE) consensus classification of HS in temporal lobe epilepsy) and postmortem controls. We analyzed the expression and spatial distribution of selected functionally relevant astrocytic proteins, including glial fibrillary acidic protein (GFAP), glutamine synthetase (GS), excitatory amino acid transporter 2 (EAAT2), and aquaporin-4 (AQP4). RESULTS:In control tissue, astrocyte subtypes, characterized by combinatorial expression of GFAP, GS, EAAT2, and AQP4, displayed distinct, layer-specific protein expression profiles across the DG compartments. While the subtype identities were largely preserved in MTLE, localization and expression levels of GFAP, EAAT2, and AQP4 were dramatically altered, suggesting functional deficits in glutamate transport and water homeostasis. Since GS expression was unaffected by MTLE, it served as a proxy to quantify the number of astrocytes. In contrast to existing reports, we found that astrocyte numbers did not differ between control and MTLE patients. SIGNIFICANCE:Our findings demonstrate that astrocyte reactivity in MTLE is not uniform but occurs in a subtype- and region-specific manner. This highlights astrocyte heterogeneity as an important feature of MTLE pathology and underscores the need to consider astrocyte diversity in understanding disease mechanisms and developing precision medicine-based therapeutic strategies. PLAIN LANGUAGE SUMMARY:Epilepsy is usually studied as a disease of nerve cells, but support cells, called astrocytes, are also involved. We studied brain tissue from patients with a common form of drug-resistant epilepsy and found that different groups of astrocytes showed distinct changes in proteins that help control brain activity and water movement in the brain. Although the overall number of astrocytes did not change compared with postmortem control patients, the cells displayed strong signs of disease-related reactivity. Our findings highlight astrocytes as potential targets for future epilepsy treatments.

Hippocampal sclerosis (HS) is the most common pathology in drug-resistant temporal lobe epilepsy (TLE). However, clinical diagnosis, prevalent epileptogenicity, and drug drug-resistance in individuals with HS remain an ongoing challenge demanding multidisciplinary research efforts. In this study, we examined the mechanical properties of neurosurgically en bloc resected HS specimens (n=8) ex vivo under compression, tension, and torsional shear. We fitted a two-term Ogden hyperelastic model to the measured mechanical responses to quantify nonlinear mechanical tissue properties. The resulting parameters revealed higher strain stiffening under compression in HS compared to hippocampus obtained post mortem (n=7). The distinction was most noticeable in the large-strain regime, which has important implications for using mechanical tissue properties as valuable diagnostic biomarker. Furthermore, we correlated the tissue microstructure with mechanical parameters. We trained a deep-learning histopathology classifier to detect and classify neurons and glial cells from hematoxylin-stained whole slide images (WSI). We identified a strong association between the small-strain stiffness (shear modulus µ ) and the overall cell density as well as the glial cell density. The negative relationship between the neuron-to-glia ratio and shear modulus is consistent with the hypothesis that neuronal cell loss and gliosis drives tissue stiffening, respectively. Magnetic resonance imaging (MRI) analysis of the specimens confirmed the previously reported negative association between MRI-derived fractional anisotropy and shear modulus µ . Taken together, our study establishes a direct link between tissue mechanics and microstructure, suggesting nonlinear continuum mechanics models as promising new tools for clinical diagnosis and novel research strategies.

Abstract Mild malformation of cortical development with oligodendroglial hyperplasia and epilepsy (MOGHE) is a recently recognized cause of drug-resistant focal epilepsy. It is often MRI-negative or shows imaging features mimicking focal cortical dysplasias, which makes recognition difficult and limits presurgical counseling. We aimed to identify an intracranial EEG (iEEG) biomarker that distinguishes MOGHE from other developmental brain lesions encountered in epilepsy surgery. In a retrospective multicenter test cohort of 38 patients (18 MOGHE, 20 non-MOGHE), we analyzed long-term stereo-EEG and subdural recordings. Only MOGHE patients showed highly stereotyped clusters of very brief low-voltage fast activity (LVFA) events, organized into status-like 3 to 12-minute episodes that often lacked clear clinical symptoms. LVFA clusters were present in 16/18 MOGHE and 0/22 non-MOGHE patients. We then tested diagnostic performance in an independent, blinded single-center validation cohort of 22 patients (11 MOGHE, 11 non-MOGHE), in which visual identification of LVFA clusters correctly classified 10/11 MOGHE and 10/11 non-MOGHE cases (Cohen’s κ=0.82). Penalized logistic regression further confirmed MOGHE histology as the strongest predictor of LVFA clusters, independent of age and lobe localization. Because LVFA clusters can be recognized visually on routine intracranial EEG recordings without specialized software, this biomarker is readily applicable in clinical practice and may improve presurgical identification of MOGHE. Future prospective studies should determine whether its recognition influences surgical planning, improves outcome prediction, or facilitates selection of patients for mechanism-based therapies. Highlights Clusters of brief LVFA in intracranial EEG are a lesion-specific biomarker of MOGHE compared to mMCD and FCD2 LVFA clusters reliably distinguished MOGHE from non-MOGHE lesions (mMCD and FCD2) in both a multicenter test cohort and an independent blinded validation cohort. Younger age at seizure onset is a secondary independent modifier, while frontal localization and age at intracranial recording are not. Clinicians can detect LVFA clusters on continuous intracranial EEG using routine montages and ≥60-second review windows, without any specialized software. LVFA clusters show a characteristic temporal organization and burden in MOGHE, indicating a distinct pattern of pathological network activity in this lesion type.

Background The role of MAPK pathway alterations in IDH-wildtype glioblastoma remains incompletely defined, particularly for BRAF and PTPN11 mutations. Methods We performed an integrated analysis of publicly available glioblastoma datasets (n = 641; IDH-wildtype n = 588), including 25 BRAF-mutated, 22 PTPN11-mutated, and 537 double-wildtype tumors. Clinical, genomic, transcriptomic, and epigenetic features were compared across subgroups. Results Clinical characteristics and overall survival did not differ between subgroups (global log-rank p = 0.60). In contrast, molecular analyses revealed distinct architectures. PTPN11-mutated tumors showed strong enrichment of RTK–RAS–MAPK signaling (OR 22.77, 95% CI 12.79–40.53, FDR < 0.001) with additional PI3K–AKT–mTOR and cell cycle activation, frequently co-occurring with NF1 alterations (68%). BRAF-mutated tumors also demonstrated MAPK enrichment (OR 4.09, 95% CI 2.21–7.56, FDR = 3.55 × 10⁻⁵) but with a more diffuse co-mutation landscape. Transcriptomic analyses identified a hyperactivated state in BRAF-mutated tumors, marked by proliferation, inflammatory, angiogenic, and metabolic programs, whereas PTPN11-mutated tumors clustered closer to double-wildtype glioblastoma. Conclusions BRAF- and PTPN11-mutant glioblastomas define distinct MAPK-centric subgroups without survival differences but with divergent molecular architectures, supporting pathway-informed stratification and therapeutic targeting.

Transporting human brain tissue blocks or slices from the operating theatre or on-site laboratory to an off-site laboratory may affect sample integrity for electrophysiological studies. In this study, we investigated how a 30-40 min transport influenced the intrinsic, synaptic and morphological properties of human cortical neurons. Electrophysiological recordings were performed on layer 2/3 (L2/3) pyramidal cells and fast-spiking (FS) interneurons from acute human cortical slices (n = 200 neurons from 32 surgeries, in which 112 neurons passed quality control for further analyses). Recordings were performed on-site at RWTH Aachen University Hospital and off-site at the Research Centre Jülich, which are approximately 40 km apart. Action potential (AP) firing patterns remained largely preserved across both recording sites, but several differences were observed. Off-site recorded pyramidal cells showed a depolarised resting membrane potential and a lowered rheobase current. In off-site recorded FS interneurons, we found a narrower AP half-width and an increased AP amplitude, suggesting altered ion channel kinetics and/or neuromodulatory environment. Additionally, a significant reduction in large rhythmic depolarisations and the amplitudes of spontaneous excitatory postsynaptic potentials in off-site recorded FS interneurons indicated an altered synaptic efficacy. Although overall dendritic architecture was preserved, the dendritic spine densities in apical oblique and apical tuft dendrites of off-site recorded pyramidal cells were also reduced. These findings emphasise the need for optimised transport conditions to preserve synaptic integrity, network activity and neuronal morphology. Standardised protocols are crucial for ensuring reliable and reproducible results in studies of human cortical function and structure. KEY POINTS: Effects of transportation on neuronal properties: Brief transportation of human brain tissue retains many key neuronal properties, while still exhibiting measurable alterations in certain intrinsic, synaptic and morphological properties. Mechanical stress and neuromodulator dysfunction may underlie alterations: These changes are likely due to the combined effects of mechanical stress and altered neuromodulator signalling during transportation. Advancing understanding of cortical function and structure: This research provides valuable insights into the impact of transportation on human brain tissue, advancing our understanding of cortical function and structure and highlighting the importance of optimising transport protocols to preserve tissue integrity and neuronal function.

OBJECTIVE:Despite advances in technical approaches, microsurgical resection remains the gold standard for treating drug-resistant mesial temporal lobe epilepsy (MTLE). However, current multicenter data on the risk of new focal neurological deficits following MTLE surgery and on factors predicting the likelihood of seizure freedom postsurgery are limited. This study aimed to evaluate the safety and efficacy of surgery by providing reliable data on the predictors of favorable postoperative outcomes. METHODS:The authors conducted a retrospective multicenter analysis across 20 epilepsy centers on 5 continents. Detailed standardized clinical data were collected, encompassing the preoperative status of patients, presurgical diagnostics, surgical techniques, complications, and neurological outcomes. Predictive factors for postoperative neurological deficits and a satisfactory response to surgery (defined as International League Against Epilepsy [ILAE] classes 1 and 2) were analyzed using a logistic regression model. Additionally, the authors assessed the relationship between neurological deficits, seizure outcomes, and neuropsychological performance. RESULTS:A total of 1167 patients were included in this study. Postoperative new neurological deficits were observed in 22.2% of cases, with new quadrantanopia being the most common (11.2%). No in-hospital mortality or 30-day mortality was recorded. Surgical revision was necessary in 4.3% of cases within the 1st year. A younger age and surgical intervention on the nondominant brain hemisphere were associated with a reduced risk of postoperative neurological deficits. After 1 year, 74.2% of patients achieved seizure outcomes classified as ILAE class 1 or 2. Known positive predictors of seizure outcomes, such as identifiable MRI lesions and a history of febrile seizures, were supported by data. Furthermore, even after adjusting for preoperative MRI findings, hemisphere dominance, occurrence of bilateral tonic-clonic seizures, age, and sex, anterior temporal lobe resection was linked to improved seizure outcomes. CONCLUSIONS:This study offers extensive multicenter data on outcomes following MTLE surgery from a large international patient cohort. The authors' analysis indicates a strong safety profile and high efficacy for epilepsy surgery in this patient group. The comprehensive breakdown of results facilitates the assessment of individual success prospects and improves informed patient counseling.

Abstract Micro-electrode array (MEA) recordings are widely used to characterize functional connectivity in neural cultures and have gained traction for the analysis of human brain slices. However, the impact of graph construction methodology on the resulting network topology has not been systematically quantified. Here, we benchmark three methods - shared spiking activity, Pearson cross-correlation, and the spike time tiling coefficient (STTC) - across 37 recordings from human cortical slice cultures classified into low, moderate, and high activity groups. We show that method choice alone produces large topological differences (Cohen’s d = 0.86–1.14 for clustering coefficient, d > 1.0 for node count), while higher-order features such as modularity remain stable. Each method exhibits a distinct sensitivity profile: shared spiking detects activity-dependent changes primarily through network size, correlation uniquely captures clustering differences, and STTC combines strong biological sensitivity with negligible parameter dependence across lag windows (all d < 0.1). Within shared spiking, z-score normalization dominates all other parameter choices (d > 1.0 versus bin size effects of d < 0.23), functioning as an implicit analytical null model that fundamentally reshapes the edge set rather than merely rescaling weights. Inter-method edge overlap is low (Jaccard index 0.08–0.45) and activity dependent, demonstrating that these methods identify substantially different connections from identical data. Our results reveal that methodological choices including construction method, threshold, and normalization introduce hidden degrees of freedom with effect sizes comparable to the biological signals being measured. We provide practical recommendations for parameter selection, reporting, and cross-method validation in MEA-based network neuroscience. Author Summary When we record electrical activity from brain tissue using grids of electrodes, we can ask how different sites influence one another and map the tissue as a network of connections. Thanks to novel culturing methods, this approach is increasingly used to study human brain slices. However, deciding what is “connected” is not well defined. Researchers use several different methods, and it has never been clear how much this choice shapes the network they end up describing. Here we compared three widely used methods on 37 recordings from human cortical slices spanning a range of activity levels. We found that the method alone can change the apparent structure of the network as much as real biological differences do. The methods frequently disagreed about which connections exist and some technical choices, including normalization techniques, had surprisingly large effects. Because these hidden choices can rival the biological signal, we provide this benchmarking work with practical recommendations for selecting, reporting, and cross-checking methods, so that network studies of brain tissue become more transparent, comparable, and reproducible.

Objective: Verb generation is associated with significant lateralized beta desynchronization in language but also motor related areas. Subsequent Memory Effect (SME) paradigms comprise receptive language and memory tasks. The current study examined whether lateralized beta patterns in language and/or motor related areas can be obtained with the receptive SME paradigm. Methods: MEG was recorded in 20 healthy right-handed adults during encoding and recognition phases of a word SME task. Measurements were repeated after 7-10 days to assess reliability. Post-stimulus beta (13-35 Hz) decrease was analyzed, and lateralization indices (LI > 0.1 indicating left dominance) were evaluated. Regions of interest (ROI) included IFG pars opercularis and triangularis (IFGO, IFGT), supramarginal gyrus, angular gyrus, superior temporal gyrus, and precentral gyrus (PreCG). An exploratory analysis included additional AAL regions. Results: Significant beta desynchronization within the ROIs was observed in 65-90% of participants. Lateralization was successful in up to 79% in the IFGT during encoding, 76% during recognition and 100% in the IFGO in encoding-recognition concordant cases. Exploratory analyses showed strong left lateralization in frontal, temporal and especially parietal areas. Initial reliability was limited, yet within-session concordance showed robust dominance with up to 100% concordance. Significant lateralized beta desynchronization was observed in the PreCG in 70-90% of participants. Conclusion: The SME paradigm shows promise in healthy participants, warranting investigation in patients with atypical language organization. Significance: Language related beta desynchronization is also observed in a receptive SME-task. Lateralized beta desynchronization in motor areas however suggest their contribution in verbal working memory and semantic control.

Background Peripheral nerve sheath tumors (PNSTs) encompass entities with different cellular differentiation and degrees of malignancy. Spatial heterogeneity complicates the diagnosis and grading of PNSTs in some cases. In malignant PNST (MPNST) for example, single-cell sequencing data has shown dissimilar differentiation states of tumor cells. Here, we aimed to determine the spatial and biological heterogeneity of PNSTs.Methods We performed spatial transcriptomics on formalin-fixed paraffin-embedded diseased peripheral nerve tissue. We used spatial clustering and weighted correlation network analysis to construct niche-similarity networks and gene expression modules. We determined differential expression in primary pathologies, analyzed pathways to investigate the biological significance of identified meta-signatures, integrated the transcriptional data with histological features and existing single-cell data, and validated expression data by immunohistochemistry.Results We identified distinct transcriptional signatures differentiating PNSTs. Immune cell infiltration, APOD, and perineurial fibroblast marker expression highlighted the neurofibroma component of hybrid PNSTs (HPNSTs). While APOD was evenly expressed in neurofibromatous tumor tissue in both, HPNST and pure neurofibromas, perineurial fibroblast markers were evenly expressed in HPNST, but restricted to the periphery in plexiform neurofibromas. Furthermore, we provide a spatial cellular differentiation map for MPNST, locating Schwann cell precursor and neural crest-like cells as well as those with mesenchymal transition.Conclusions This pilot study shows that applying spatial transcriptomics to PNSTs provides important insight into their biology. It helps establish new markers and provides spatial information about the cellular composition and distribution of cellular differentiation states. By integrating morphological and high-dimensional molecular data it can improve PNSTs classification in the future.

Recurrent glioblastoma has a poor prognosis, and its optimal management remains unclear. Reirradiation (re-RT) is a promising treatment option, but long-term outcomes and optimal patient selection criteria are not well established. This study analyzed 71 patients with recurrent CNS WHO grade 4, IDHwt glioblastoma (GBM) who underwent re-RT at the University of Erlangen-Nuremberg between January 2009 and June 2019. Imaging follow-ups were conducted every 3 months. Progression-free survival (PFS) was defined using RANO criteria. Outcomes, feasibility, and toxicity of re-RT were evaluated. Contrast-enhancing tumor volume was measured using a deep learning auto-segmentation pipeline with expert validation and jointly evaluated with clinical and molecular-pathologic factors. Most patients were prescribed conventionally fractionated re-RT (84.5

OBJECTIVE:Resective epilepsy surgery is an evidence-based treatment option for patients with focal drug-resistant epilepsy (DRE). Seizure outcome after surgery is largely dependent on detection and delineation of an epileptogenic lesion on magnetic resonance imaging (MRI). However, detection fails in 30% of patients at 3 Tesla (T) MRI, thereby limiting surgical options. Diagnostic and therapeutic gain of ultra-high-field MRI in patients with 3T MRI-negative DRE is evaluated in the EpiUltraStudy. Here we report the diagnostic gain of structural 7T MRI. METHODS:Inclusion criteria were age ≥12 years and DRE with a suspected epileptogenic focus and negative conventional 3T MRI during pre-surgical workup. Images were evaluated independently by two neuroradiologists and a neurologist or neurosurgeon in two runs: blinded (Run 1) and with the results of additional clinical investigations (Run 2). RESULTS:Sixty patients underwent 7T MRI. No persistent adverse events were reported. Visual assessment of 7T MRI identified lesions in 9 cases (15%), undetected on prior 3T MRI. Possible positive scan rates increased from 17% (10/60) in the blinded run to 47% (28/60) in the informed run. However, after consensus review, many of these were reclassified as negative. Eight of nine positive 7T MRI scans were initially identified by only one or two assessors. After reassessment, a total of 56% (5/9) of 7T lesions were retrospectively identified on 3T. SIGNIFICANCE:Our data suggest a benefit of 7T MRI for the detection of subtle epileptogenic lesions in patients with DRE and negative 3T MRI. Although the detection rate may appear modest compared to other reports, we present a nuanced discussion of our methodology and patient population, contributing meaningful context to the current literature. The availability of multimodal information and consensus reviews enhanced diagnostic accuracy but with higher rates of false positives, underscoring the importance of multidisciplinary cooperation in the clinical care for patients with DRE. TRIAL REGISTRATION NUMBER:www.trialregister.nl: NTR7536.

Background: Differentiating radiation necrosis (RN) from tumor progression after stereotactic radiosurgery (SRS) remains a critical challenge in brain metastases. While histopathology represents the gold standard, its invasiveness limits feasibility. Conventional supervised deep learning approaches are constrained by scarce biopsy-confirmed training data. Self-supervised learning (SSL) overcomes this by leveraging the growing availability of large-scale unlabeled brain metastases imaging datasets. Methods: In a two-phase deep learning strategy inspired by the foundation model paradigm, a Vision Transformer (ViT) was pre-trained via SSL on 10,167 unlabeled multi-source T1CE MRI sub-volumes. The pre-trained ViT was then fine-tuned for RN classification using a two-channel input (T1CE MRI and segmentation masks) on the public MOLAB dataset (n=109) using 20

INTRODUCTION:Seizures are a common symptom of pediatric high-grade gliomas (pHGG). This study aimed to characterize these seizures in the context of the underlying tumor disease in this age group. METHODS:We retrospectively analysed the medical files of children and adolescents treated in the University Hospital Erlangen for high-grade glioma between January 2000 and May 2021 and collected data including age, sex, tumor location, histopathology, extent of initial resection, tumor recurrence, seizure characteristics, EEG findings, seizure and oncological treatment, and seizure control. RESULTS:Our study included 39 children (14 boys, 35.9 %) diagnosed with high-grade glioma. The median age at diagnosis was 8.5 years (range 0-17 years), and the median follow-up interval was 353 days (range 28-9146 days). 16 children had supratentorial and 23 infratentorial gliomas. 17 children (43.6 %) experienced seizures of which 10/17 (58.8 %) had supratentorial tumors. 5 of these children (20 % of all patients with epilepsy and 12.8 % of the entire cohort) presented with seizures as the first sign. 11/17 children (64.7 %) had recurrent seizures. Status epilepticus occurred in one child (2.6 %). EEG was performed in 29 patients with interictal epileptiform discharges in 4/29 (13.8 %). CONCLUSIONS:Present data show a high incidence of seizures in pHGG associated with supratentorial but also infratentorial location. The pediatric incidence was comparable to that in adults. The majority of the children developed repetitive seizures.

Genetic variation in the α5 nicotinic acetylcholine receptor (nAChR) subunit of mice results in behavioral deficits linked to the prefrontal cortex (PFC). rs16969968 is the primary Single Nucleotide Polymorphism (SNP) in CHRNA5 strongly associated with nicotine dependence and schizophrenia in humans. We performed single cell-electrophysiology combined with morphological reconstructions on layer 6 (L6) excitatory neurons in the medial PFC (mPFC) of wild type (WT) rats, rats carrying the human coding polymorphism rs16969968 in Chrna5 and α5 knockout (KO) rats. Neuronal and synaptic properties were determined for the three rat genotypes. Compared with neurons in WT rats, L6 regular spiking (RS) neurons in the α5KO group exhibited altered electrophysiological properties, while those in α5SNP rats remained unchanged. L6 RS neurons in mPFC of α5SNP and α5KO rats differed from WT rats in dendritic morphology, spine density and spontaneous synaptic activity. Galantamine was applied to identified L6 neuron populations to specifically boost the nicotinic responses mediated by α5*nAChRs. Remarkably, it restored nicotinic modulation in neurons of α5SNP rats, while no such effect was observed in α5KO rats. Additionally, galantamine functioned as a positive allosteric modulator of α5*nAChRs in RS neurons, both in rat and human cortical L6, but did not affect burst spiking (BS) neurons. Our findings suggest that dysfunction in the α5 subunit gene leads to aberrant neuronal and synaptic properties, shedding light on the underlying mechanisms of cognitive deficits observed in human populations carrying α5SNPs. They highlight a potential pharmacological target for restoring the relevant behavioral output.