Purpose: PET using radiolabeled amino acid [¹⁸F]-fluoro-ethyl-_L-tyrosine (FET-PET) is a well-established imaging modality for glioma diagnostics. The biological tumor volume (BTV) as depicted by FET-PET often differs in volume and location from tumor volume of contrast enhancement (CE) in MRI. Our aim was to investigate whether a gross total resection of BTVs defined as < 1 cm³ of residual BTV (PET GTR) correlates with better oncological outcome. Methods: We retrospectively analyzed imaging and survival data from patients with primary and recurrent WHO grade III or IV gliomas who underwent FET-PET before surgical resection. Tumor overlap between FET-PET and CE was evaluated. Completeness of FET-PET resection (PET GTR) was calculated after superimposition and semi-automated segmentation of pre-operative FET-PET and postoperative MRI imaging. Survival analysis was performed using the Kaplan–Meier method and the log-rank test. Results: From 30 included patients, PET GTR was achieved in 20 patients. Patients with PET GTR showed improved median OS with 19.3 compared to 13.7 months for patients with residual FET uptake (p = 0.007; HR 0.3; 95% CI 0.12–0.76). This finding remained as independent prognostic factor after performing multivariate analysis (HR 0.19, 95% CI 0.06–0.62, p = 0.006). Other survival influencing factors such as age, IDH-mutation, MGMT promotor status, and adjuvant treatment modalities were equally distributed between both groups. Conclusion: Our results suggest that PET GTR improves the OS in patients with WHO grade III or IV gliomas. A multimodal imaging approach including FET-PET for surgical planning in newly diagnosed and recurrent tumors may improve the oncological outcome in glioma patients.

Effective pharmacological neuroprotection is one of the most desired aims in modern medicine. We postulated that a combination of two clinically used drugs—nimodipine (L-Type voltage-gated calcium channel blocker) and amiloride (acid-sensing ion channel inhibitor)—might act synergistically in an experimental model of ischaemia, targeting the intracellular rise in calcium as a pathway in neuronal cell death. We used organotypic hippocampal slices of mice pups and a well-established regimen of oxygen-glucose deprivation (OGD) to assess a possible neuroprotective effect. Neither nimodipine (at 10 or 20 µM) alone or in combination with amiloride (at 100 µM) showed any amelioration. Dissolved at 2.0 Vol.% dimethyl-sulfoxide (DMSO), the combination of both components even increased cell damage (p = 0.0001), an effect not observed with amiloride alone. We conclude that neither amiloride nor nimodipine do offer neuroprotection in an in vitro ischaemia model. On a technical note, the use of DMSO should be carefully evaluated in neuroprotective experiments, since it possibly alters cell damage.

Background: Glioblastoma (GB) is the most aggressive primary brain tumor in adults. Tumor-associated epilepsy (TAE) at diagnosis 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: Tumor-associated epilepsy was independently associated with improved survival (hazard ratio [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 GB with TAE; tumors without seizures displayed neuronal and stem-like features. Functional validation using electrogenomics showed that GB cortical slices with increased inflammatory score exhibited synchronization of action potentials characteristic for seizure-like epileptiform activity. Conclusions: Tumor-associated epilepsy 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.

Rhythmic brain activity has been implicated in many brain functions and it is sensible to neuromodulation, but so far very few studies have investigated this activity on the cellular level in vitro in human tissue samples. In this study we revealed and characterized a novel rhythmic network activity in human neocortex. Intracellular patch-clamp recordings showed that giant depolarizing potentials (GDPs) were frequently found in human cortical neurons. GDPs appeared in a low frequency band (∼ 0.3 Hz) similar to that described for slow oscillations in vivo and displayed large amplitudes and long decay times. Under the same experimental conditions, no rhythmic activity was found in L2/3 of the rat neocortex. GDPs were predominantly observed in a subset of L2/3 interneurons considered to be large basket cells based on previously described morphological features. In addition, GDPs are highly sensitive to norepinephrine (NE) and acetylcholine (ACh), two neuromodulators known to modulate low frequency oscillations. NE increased the frequency of the GDPs by enhancing β-adrenergic receptor activity while ACh decreased GDP frequency through M ₄ muscarinic receptor-activation. Multi-electrode array (MEA) recordings demonstrated that NE promoted synchronous oscillatory network activity while the application of ACh led to a desynchronization of neuronal activity. Our data indicate that the human neocortex is more prone to generate slow wave activity, which was reflected by more pronounced GDPs in L2/3 large basket cells. The distinct modulation of GDPs and slow wave activity by NE and ACh exerts a specific modulatory control over the human neocortex.

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.