Epileptic Tissue Research Articles

Best1 mitigates ER stress induced by the increased cellular microenvironment stiffness in epilepsy.

Changes in brain tissue stiffness are closely linked to the development and diseases of the nervous system. Endoplasmic reticulum (ER) stress plays a role in various pathological processes related to epilepsy. However, the relationship between stiffness changes, ER stress, and epilepsy remains unclear. This study aimed to investigate the impact of Best1 upregulation on alleviating ER stress and the underlying mechanism. Additionally, we proposed a protective strategy to prevent cell death resulting from ER stress in epilepsy. This study investigated the expression levels of ER stress-related proteins in epileptic tissues of varying stiffness. Atomic force microscopy revealed differences in stiffness across various lesion regions in patients with epilepsy. The expression levels of ECM and ER stress-related proteins were elevated in tissues with higher stiffness. Polypropionamide hydrogels were used to simulate extracellular matrix (ECM) with varying stiffness levels. Basal ER stress increased in the stiffer hydrogel substrates. Furthermore, the calcium-activated anion channel Bestrophin 1 (Best1) mitigated ER stress induced by both the stiffer substrate and thapsigargin. The loss-of-function mutations in Best1 inhibited this activity. The underlying mechanism involves the upregulation of the endosomal sorting complex required for the transport (ESCRT) components by Best1, which helps mitigate ER stress. These findings suggest that increased stiffness of the cellular microenvironment may contribute to neuronal death during epileptogenesis. Additionally, Best1 upregulation may serve as a protective strategy against excessive ER stress-induced neuronal damage in epilepsy.

LPM682000012, a Synthetic Neuroactive Steroid That Ameliorates Epileptic Seizures by Downregulating the Serpina3n/NF-κB Signaling Pathway.

Epilepsy is characterized by abnormal neuronal firing in the brain. Several therapeutic strategies exist for epilepsy; however, several patients remain poorly treated. Therefore, the development of effective treatments remains a high priority in the field. Neuroactive steroids can potentiate extra-synaptic and synaptic GABAA receptors, thereby providing therapeutic benefits relative to benzodiazepines. This research study investigated the therapeutic effectiveness and underlying mechanisms of LPM682000012, a new synthetic neuroactive steroid-positive allosteric modulator (PAM) of GABAA receptors employed for treating epilepsy. Acute and chronic rat epilepsy models were established to identify the anti-seizure potency of LPM682000012. The dose-dependent sedative effects of LPM682000012 and Ganaxolone in normal rats were evaluated, which revealed that they both dose-dependently alleviated acute epileptic seizure in the pentylenetetrazol (PTZ)-mediated seizure model. Furthermore, LPM682000012 indicated an enhanced safety profile than Ganaxolone. Moreover, LPM682000012 also indicated therapeutic effects in the kainic acid (KA)-induced chronic spontaneous seizure model. Morphologically, LPM682000012 decreased neuronal loss in the hippocampal CA1 and CA3 regions and increased dendritic spine density in the CA1 region. In addition, mechanical analyses, including transcriptomics, Western blot, and proteomics analyses, revealed that the Serpina3n/NF-κB signaling pathway was up-regulated in epileptic rat hippocampal tissue, and LPM682000012 treatment reversed these changes. In summary, this report demonstrated that the novel neurosteroid GABAA PAM LPM682000012 activated the synaptic and extra-synaptic GABAA receptors and alleviated KA-induced neuronal loss and synaptic remodeling, potentially by down-regulating the Serpina3n/NF-κB signaling pathways. The results provide evidence that LPM682000012 is a potential anti-seizure pharmacotherapy candidate for epilepsy and warrants further research.

Selective modulation of epileptic tissue by an adenosine A3 receptor-activating drug.

Adenosine, through the A1 receptor (A1R), is an endogenous anticonvulsant. The development of adenosine receptor agonists as antiseizure medications has been hampered by their cardiac side effects. A moderately A1R-selective agonist, MRS5474, has been reported to suppress seizures without considerable cardiac action. Hypothesizing that this drug could act through other than A1R and/or through a disease-specific mechanism, we assessed the effect of MRS5474 on the hippocampus. Excitatory synaptic currents, field potentials, spontaneous activity, [3H]GABA uptake and GABAergic currents were recorded from rodent or human hippocampal tissue. Alterations in adenosine A3 receptor (A3R) density in human tissue were assessed by Western blot. MRS5474 (50-500 nM) was devoid of effect upon rodent excitatory synaptic signals in hippocampal slices, except when hyperexcitability was previously induced in vivo or ex vivo. MRS5474 inhibited GABA transporter type 1 (GAT-1)-mediated γ-aminobutyric acid (GABA) uptake, an action not blocked by an A1R antagonist but blocked by an A3R antagonist and mimicked by an A3R agonist. A3R was overexpressed in human hippocampal tissue samples from patients with epilepsy that had focal resection from surgery. MRS5474 induced a concentration-dependent potentiation of GABA-evoked currents in oocytes micro-transplanted with human hippocampal membranes prepared from epileptic hippocampal tissue but not from non-epileptic tissue, an action blocked by an A3R antagonist. We identified a drug that activates A3R and has selective actions on epileptic hippocampal tissue. This underscores A3R as a promising target for the development of antiseizure medications.

Laser Ablation of Periventricular Nodular Heterotopia for Medically Refractory Epilepsy.

Periventricular nodular heterotopia (PVNH) is the most common neuronal heterotopia, frequently resulting in pharmaco-resistant epilepsy. Here, we characterize variables that predict good epilepsy outcomes following surgical intervention using stereo-electroencephalography (SEEG) -informed magnetic resonance-guided laser interstitial thermal therapy (MRgLITT). A retrospective review of consecutive cases from a single high-volume epilepsy referral center identified patients who underwent SEEG evaluation for PVNH to characterize the intervention and outcomes. Thirty-nine patients underwent SEEG-guided MRgLITT of the seizure onset zone (SoZ) in PVNH and associated epileptic tissue. PVNH and polymicrogyria (PMG) were densely sampled with a mean of 16.5 (SD = 2)/209.4 (SD = 36.9) SEEG probes/recording contacts per patient. Ablation principally targeted just the PVNH and cortex that was abnormal on imaging was ablated (5 patients) only if implicated in the SoZ. Volumetric analyses revealed a high percentage of PVNH SoZ ablation (96.6%, SD = 5.3%) in unilateral and bilateral (92.9%, SD = 7.2%) cases. Mean follow-up duration was 31.4 months (SD = 20.9). Seizure freedom (ILAE 1) was excellent: unilateral PVNH without other imaging abnormalities, 80%; PVNH with mesial temporal sclerosis (MTS) or PMG, 63%; bilateral PVNH, 50%. SoZ ablation percentage significantly impacted surgical outcomes (p < 0.001). PVNH plays a central role in seizure genesis as revealed by dense recordings and selective targeting by LITT. MRgLITT represents a transformative technological advance in PVNH-associated epilepsy with seizure control outcomes consistent with those seen in focal lesional epilepsies. In localized unilateral cases and otherwise normal imaging, PVNH ablation without invasive recordings may be considered, and this approach deserves to be explored further. ANN NEUROL 2024;96:1174-1184.

Metabolic Adaptation in Epilepsy: From Acute Response to Chronic Impairment.

Epilepsy is characterized by hypersynchronous neuronal discharges, which are associated with an increased cerebral metabolic rate of oxygen and ATP demand. Uncontrolled seizure activity (status epilepticus) results in mitochondrial exhaustion and ATP depletion, which potentially generate energy mismatch and neuronal loss. Many cells can adapt to increased energy demand by increasing metabolic capacities. However, acute metabolic adaptation during epileptic activity and its relationship to chronic epilepsy remains poorly understood. We elicited seizure-like events (SLEs) in an in vitro model of status epilepticus for eight hours. Electrophysiological recording and tissue oxygen partial pressure recordings were performed. After eight hours of ongoing SLEs, we used proteomics-based kinetic modeling to evaluate changes in metabolic capacities. We compared our findings regarding acute metabolic adaptation to published proteomic and transcriptomic data from chronic epilepsy patients. Epileptic tissue acutely responded to uninterrupted SLEs by upregulating ATP production capacity. This was achieved by a coordinated increase in the abundance of proteins from the respiratory chain and oxidative phosphorylation system. In contrast, chronic epileptic tissue shows a 25-40% decrease in ATP production capacity. In summary, our study reveals that epilepsy leads to dynamic metabolic changes. Acute epileptic activity boosts ATP production, while chronic epilepsy reduces it significantly.

Machine learning for (non–)epileptic tissue detection from the intraoperative electrocorticogram

ObjectiveClinical visual intraoperative electrocorticography (ioECoG) reading intends to localize epileptic tissue and improve epilepsy surgery outcome. We aimed to understand whether machine learning (ML) could complement ioECoG reading, how subgroups affected performance, and which ioECoG features were most important. MethodsWe included 91 ioECoG-guided epilepsy surgery patients with Engel 1A outcome. We allocated 71 training and 20 test set patients. We trained an extra trees classifier (ETC) with 14 spectral features to classify ioECoG channels as covering resected or non-resected tissue. We compared the ETC’s performance with clinical ioECoG reading and assessed whether patient subgroups affected performance. Explainable artificial intelligence (xAI) unveiled the most important ioECoG features learnt by the ETC. ResultsThe ETC outperformed clinical reading in five test set patients, was inferior in six, and both were inconclusive in nine. The ETC performed best in the tumor subgroup (area under ROC curve: 0.84 [95%CI 0.79–0.89]). xAI revealed predictors of resected (relative theta, alpha, and fast ripple power) and non-resected tissue (relative beta and gamma power). ConclusionsCombinations of subtle spectral ioECoG changes, imperceptible by the human eye, can aid healthy and pathological tissue discrimination. SignificanceML with spectral ioECoG features can support, rather than replace, clinical ioECoG reading, particularly in tumors.

The hemodynamic response to co-occurring interictal epileptiform discharges and high-frequency oscillations localizes the seizure-onset zone.

To use intracranial electroencephalography (EEG) to characterize functional magnetic resonance imaging (fMRI) activation maps associated with high-frequency oscillations (HFOs) (80-250 Hz) and examine their proximity to HFO- and seizure-generating tissue. Forty-five patients implanted with intracranial depth electrodes underwent a simultaneous EEG-fMRI study at 3 T. HFOs were detected algorithmically from cleaned EEG and visually confirmed by an experienced electroencephalographer. HFOs that co-occurred with interictal epileptiform discharges (IEDs) were subsequently identified. fMRI activation maps associated with HFOs were generated that occurred either independently of IEDs or within ±200 ms of an IED. For all significant analyses, the Maximum, Second Maximum, and Closest activation clusters were identified, and distances were measured to both the electrodes where the HFOs were observed and the electrodes involved in seizure onset. We identified 108 distinct groups of HFOs from 45 patients. We found that HFOs with IEDs produced fMRI clusters that were closer to the local field potentials of the corresponding HFOs observed within the EEG than HFOs without IEDs. In addition to the fMRI clusters being closer to the location of the EEG correlate, HFOs with IEDs generated Maximum clusters with greater z-scores and larger volumes than HFOs without IEDs. We also observed that HFOs with IEDs resulted in more discrete activation maps. Intracranial EEG-fMRI can be used to probe the hemodynamic response to HFOs. The hemodynamic response associated with HFOs that co-occur with IEDs better identifies known epileptic tissue than HFOs that occur independently.

Ferroptosis-Related Gene Signatures in Epilepsy: Diagnostic and Immune Insights.

Epilepsy is characterized by a multifaceted aetiology. Ferroptosis has recently been implicated in seizure pathophysiology, although its mechanistic role in epilepsy remains obscure. We examined the roles of ferroptosis-related genes (FRGs) in epilepsy cohorts from the GSE143272 dataset. We investigated the associations between gene expression and the immune response by performing CIBERSORT and MCP-counter analyses. By employing unsupervised consensus clustering and weighted gene coexpression network analysis (WGCNA), we delineated robust gene clusters across cohorts. Single-cell RNA sequencing data from the GSE201048 dataset provided insights into the interactions between pivotal ferroptosis-related genes and immune cells. Additionally, we employed qRT‒PCR technology to measure the levels of these central genes in the tissues of epileptic patients and mice. Our findings revealed seven pivotal genes (TFRC, POR, PTGS2, RELA, PGD, TRIM21, and QSOX1) at the forefront in epilepsy specimens. A diagnostic model harnessing these genes exhibited substantial efficacy (AUC = 0.913). Similarly, the qRT‒PCR analysis of samples from epileptic patients and mouse epileptic brain tissues substantiated these findings. Stratification of 91 patients with epilepsy via WGCNA, based on gene expression, revealed distinct immunological profiles. The scRNA-seq data further indicated increased expression of central genes in macrophages and microglia. Notably, these cells and those with elevated ferroptosis scores were significantly enriched in inflammation-related pathways. These findings support the strong involvement of FRGs in the pathogenesis of epilepsy, particularly neuroinflammation. These central genes hold promise as novel diagnostic biomarkers for epilepsy.

Water exchange across the blood-brain barrier and epilepsy: Review on pathophysiology and neuroimaging.

The blood-brain barrier (BBB) is a barrier protecting the brain and a milieu of continuous exchanges between blood and brain. There is emerging evidence that the BBB plays a major role in epileptogenesis and drug-resistant epilepsy, through several mechanisms, such as water homeostasis dysregulation, overexpression of drug transporters, and inflammation. Studies have shown abnormal water homeostasis in epileptic tissue and altered aquaporin-4 water channel expression in animal epilepsy models. This review focuses on abnormal water exchange in epilepsy and describes recent non-invasive MRI methods of quantifying water exchange. PLAIN LANGUAGE SUMMARY: Abnormal exchange between blood and brain contribute to seizures and epilepsy. The authors describe why correct water balance is necessary for healthy brain functioning and how it is impacted in epilepsy. This review also presents recent MRI methods to measure water exchange in human brain. These measures would improve our understanding of factors leading to seizures.

Spatial and temporal properties of intra-operatively recorded spikes and high frequency oscillations in focal cortical dysplasia

ObjectiveFocal cortical dysplasias (FCD) are characterized by distinct interictal spike patterns and high frequency oscillations (HFOs; ripples: 80–250 Hz; fast ripples: 250–500 Hz) in the intra-operative electrocorticogram (ioECoG). We studied the temporal relation between intra-operative spikes and HFOs and their relation to resected tissue in people with FCD with a favorable outcome. MethodsWe included patients who underwent ioECoG-tailored epilepsy surgery with pathology confirmed FCD and long-term Engel 1A outcome. Spikes and HFOs were automatically detected and visually checked in 1-minute pre-resection-ioECoG. Channels covering resected and non-resected tissue were compared using a logistic mixed model, assessing event numbers, co-occurrence ratios, and time-based properties. ResultsWe found pre-resection spikes, ripples in respectively 21 and 20 out of 22 patients. Channels covering resected tissue showed high numbers of spikes and HFOs, and high ratios of co-occurring events. Spikes, especially with ripples, have a relatively sharp rising flank with a long descending flank and early ripple onset over resected tissue. ConclusionsA combined analysis of event numbers, ratios, and temporal relationships between spikes and HFOs may aid identifying epileptic tissue in epilepsy surgery. SignificanceThis study shows a promising method for clinically relevant properties of events, closely associated with FCD.

Modification of brain conductivity in human focal epilepsy: A model-based estimation from stereoelectroencephalography.

We have developed a novel method for estimating brain tissue electrical conductivity using low-intensity pulse stereoelectroencephalography (SEEG) stimulation coupled with biophysical modeling. We evaluated the hypothesis that brain conductivity is correlated with the degree of epileptogenicity in patients with drug-resistant focal epilepsy. We used bipolar low-intensity biphasic pulse stimulation (.2 mA) followed by a postprocessing pipeline for estimating brain conductivity. This processing is based on biophysical modeling of the electrical potential induced in brain tissue between the stimulated contacts in response to pulse stimulation. We estimated the degree of epileptogenicity using a semi-automatic method quantifying the dynamic of fast discharge at seizure onset: the epileptogenicity index (EI). We also investigated how the location of stimulation within specific anatomical brain regions or within lesional tissue impacts brain conductivity. We performed 1034 stimulations of 511 bipolar channels in 16 patients. We found that brain conductivity was lower in the epileptogenic zone (EZ; unpaired median difference = .064, p < .001) and inversely correlated with the epileptogenic index value (p < .001, Spearman rho = -.32). Conductivity values were also influenced by anatomical site, location within lesion, and delay between SEEG electrode implantation and stimulation, and had significant interpatient variability. Mixed model multivariate analysis showed that conductivity is significantly associated with EI (F = 13.45, p < .001), anatomical regions (F = 5.586, p < .001), delay since implantation (F = 14.71, p = .003), and age at SEEG (F = 6.591, p = .027), but not with the type of lesion (F = .372, p = .773) or the delay since last seizure (F = 1.592, p = .235). We provide a novel model-based method for estimating brain conductivity from SEEG low-intensity pulse stimulations. The brain tissue conductivity is lower in EZ as compared to non-EZ. Conductivity also varies significantly across anatomical brain regions. Involved pathophysiological processes may include changes in the extracellular space (especially volume or tortuosity) in epileptic tissue.

Membranes and Synaptosomes Used to Investigate Synaptic GABAergic Currents in Epileptic Patients.

Among the most prevalent neurological disorders, epilepsy affects about 1% of the population worldwide. We previously found, using human epileptic tissues, that GABAergic neurotransmission impairment is a key mechanism that drives the pathological phenomena that ultimately lead to generation and recurrence of seizures. Using both a "microtransplantation technique" and synaptosomes preparations from drug-resistant temporal lobe epilepsies (TLEs), we used the technique of two-electrode voltage clamp to record GABA-evoked currents, focusing selectively on the synaptic "fast inhibition" mediated by low-affinity GABAA receptors. Here, we report that the use-dependent GABA current desensitization (i.e., GABA rundown, which is evoked by applying to the cells consecutive pulses of GABA, at high concentration), which is a distinguishing mark of TLE, is mainly dependent on a dysfunction that affects synaptic GABAA receptors. In addition, using the same approaches, we recorded a depolarized GABA reversal potential in synaptosomes samples from the human epileptic subicula of TLE patients. These results, which confirm previous experiments using total membranes, suggest an altered chloride homeostasis in the synaptic area. Finally, the lack of a Zn2+ block of GABA-evoked currents using the synaptosomes supports the enrichment of "synaptic fast inhibitory" GABAA receptors in this preparation. Altogether, our findings suggest a pathophysiological role of low-affinity GABAA receptors at the synapse, especially during the fast and repetitive GABA release underlying recurrent seizures.

Applying Proteomics and Computational Approaches to Identify Novel Targets in Blast-Associated Post-Traumatic Epilepsy.

Traumatic brain injury (TBI) can lead to post-traumatic epilepsy (PTE). Blast TBI (bTBI) found in Veterans presents with several complications, including cognitive and behavioral disturbances and PTE; however, the underlying mechanisms that drive the long-term sequelae are not well understood. Using an unbiased proteomics approach in a mouse model of repeated bTBI (rbTBI), this study addresses this gap in the knowledge. After rbTBI, mice were monitored using continuous, uninterrupted video-EEG for up to four months. Following this period, we collected cortex and hippocampus tissues from three groups of mice: those with post-traumatic epilepsy (PTE+), those without epilepsy (PTE-), and the control group (sham). Hundreds of differentially expressed proteins were identified in the cortex and hippocampus of PTE+ and PTE- relative to sham. Focusing on protein pathways unique to PTE+, pathways related to mitochondrial function, post-translational modifications, and transport were disrupted. Computational metabolic modeling using dysregulated protein expression predicted mitochondrial proton pump dysregulation, suggesting electron transport chain dysregulation in the epileptic tissue relative to PTE-. Finally, data mining enabled the identification of several novel and previously validated TBI and epilepsy biomarkers in our data set, many of which were found to already be targeted by drugs in various phases of clinical testing. These findings highlight novel proteins and protein pathways that may drive the chronic PTE sequelae following rbTBI.

Estimation of Circular Statistics in the Presence of Measurement Bias.

Circular statistics and Rayleigh tests are important tools for analyzing cyclic events. However, current methods are not robust to significant measurement bias, especially incomplete or otherwise non-uniform sampling. One example is studying 24-cyclicity but having data not recorded uniformly over the full 24-hour cycle. Our objective is to present a robust method to estimate circular statistics and their statistical significance in the presence of incomplete or otherwise non-uniform sampling. Our method is to solve the underlying Fredholm Integral Equation for the more general problem, estimating probability distributions in the context of imperfect measurements, with our circular statistics in the presence of incomplete/non-uniform sampling being one special case. The method is based on linear parameterizations of the underlying distributions. We simulated the estimation error of our approach for several toy examples as well as for a real-world example: analyzing the 24-hour cyclicity of an electrographic biomarker of epileptic tissue controlled for states of vigilance. We also evaluated the accuracy of the Rayleigh test statistic versus the direct simulation of statistical significance. Our method shows a very low estimation error. In the real-world example, the corrected moments had a root mean square error of [Formula: see text]. In contrast, the Rayleigh test statistic overestimated the statistical significance and was thus not reliable. The presented methods thus provide a robust solution to computing circular moments even with incomplete or otherwise non-uniform sampling. Since Rayleigh test statistics cannot be used in this circumstance, direct estimation of significance is the preferable option for estimating statistical significance.

Epileptic tissue localization using graph-based networks in the high frequency oscillation range of intracranial electroencephalography

PurposeHigh frequency oscillations (HFOs) are an emerging biomarker of epilepsy. However, very few studies have investigated the functional connectivity of interictal iEEG signals in the frequency range of HFOs. Here, we study the corresponding functional networks using graph theory, and we assess their predictive value for automatic electrode classification in a cohort of 20 drug resistant patients. MethodsCoherence-based connectivity analysis was performed on the iEEG recordings, and six different local graph measures were computed in both sub-bands of the HFO frequency range (80–250 Hz and 250–500 Hz). Correlation analysis was implemented between the local graph measures and the ripple and fast ripple rates. Finally, the WEKA software was employed for training and testing different predictive models on the aforementioned local graph measures. ResultsThe ripple rate was significantly correlated with five out of six local graph measures in the functional network. For fast ripples, their rate was also significantly (but negatively) correlated with most of the local metrics. The results from WEKA showed that the Logistic Regression algorithm was able to classify highly HFO-contaminated electrodes with an accuracy of 82.5 % for ripples and 75.4 % for fast ripples. ConclusionFunctional connectivity networks in the HFO band could represent an alternative to the direct use of distinct HFO events, while also providing important insights about hub epileptic areas that can represent possible surgical targets. Automatic electrode classification through FC-based classifiers can help bypass the burden of manual HFO annotation, providing at the same time similar amount of information about the epileptic tissue.

Persistent Kv7.2/7.3 downregulation in the rat pilocarpine model of mesial temporal lobe epilepsy

Mutations within the Kv7.2 and Kv7.3 genes are well described causes for genetic childhood epilepsies. Knowledge on these channels in acquired focal epilepsy, especially in mesial temporal lobe epilepsy (mTLE), however, is scarce. Here, we used the rat pilocarpine model of drug-resistant mTLE to elucidate both expression and function by quantitative polymerase-chain reaction, immunohistochemistry, and electrophysiology, respectively. We found transcriptional downregulation of Kv7.2 and Kv7.3 as well as reduced Kv7.2 expression in epileptic CA1. Consequences were altered synaptic transmission, hyperexcitability which consisted of epileptiform afterpotentials, and increased susceptibility to acute GABAergic disinhibition. Importantly, blocking Kv7 channels with XE991 increased hyperexcitability in control tissue, but not in chronically epileptic tissue suggesting that the Kv7 deficit had precluded XE991 effects in this tissue. Conversely, XE991 resulted in comparable reduction of the paired-pulse ratio in both experimental groups implying preserved presynaptic Kv7.2 function of Schaffer collateral terminals. Consistent with Kv7.2/7.3 downregulation, the Kv7.3 channel opener β-hydroxybutyrate failed to mitigate hyperexcitability. Our findings demonstrate that compromised Kv7 function is not only relevant in genetic epilepsy, but also in acquired focal epilepsy. Moreover, they help explain reduced anti-seizure efficacy of Kv7 channel openers in drug-resistant epilepsy.

Specificities of Living Human Microglial Cells.

Microglia are macrophages residing in the central nervous system, where they perform immune surveillance, synaptic remodeling, neurogenesis, and monitor signals arising from brain injuries or potential pathogens.Commonly, rodent models are used for studying microglia because of the available transgenic mouse lines in which specific genetic manipulations are successfully accomplished. However, human and rodents microglia showed significant differences, which are reflected in different morphological and functional properties. These differences are in genetic and transcriptomic, but also in the expression of signaling molecules and age-associated changes.Several strategies are available to study human microglia, as using surgical brain resections from epileptic and tumoral tissues and from post mortem brain samples. In addition, the generation of human-induced pluripotent stem cells (hPSCs) and the possibility to differentiate them in microglia-like cells provide unique opportunities to compare microglia functions between rodents' and human brain.The use of human ex vivo and in vitro brain models allows the study of human microglia, mimicking in vivo conditions. This will be useful for a better understanding of the real live behavior and functions of microglia in the human brain. This chapter aims to highlight significant similarities and differences between human and rodent microglia in order to re-evaluate mouse models of different human brain disorders, proposing the use of in vitro and ex vivo human brain models.Studies on living human microglia in the brain may help to define divergences from animal models and to improve clinical interventions to treat brain pathologies, using alternatives targets.

Intraoperative mapping of epileptogenic foci and tumor infiltration in neuro-oncology patients with epilepsy.

Epileptogenesis and glioma growth have a bidirectional relationship. We hypothesized people with gliomas can benefit from the removal of epileptic tissue and that tumor-related epileptic activity may signify tumor infiltration in peritumoral regions. We investigated whether intraoperative electrocorticography (ioECoG) could improve seizure outcomes in oncological glioma surgery, and vice versa, what epileptic activity (EA) tells about tumor infiltration. We prospectively included patients who underwent (awake) ioECoG-assisted diffuse-glioma resection through the oncological trajectory. The IoECoG-tailoring strategy relied on ictal and interictal EA (spikes and sharp waves). Brain tissue, where EA was recorded, was assigned for histopathological examination separate from the rest of the tumor. Weibull regression was performed to assess how residual EA and extent of resection (EOR) related to the time-to-seizure recurrence, and we investigated which type of EA predicted tumor infiltration. Fifty-two patients were included. Residual spikes after resection were associated with seizure recurrence in patients with isocitrate dehydrogenase (IDH) mutant astrocytoma or oligodendroglioma (HR = 7.6[1.4-40.0], P-value = .01), independent from the EOR. This was not observed in IDH-wildtype tumors. All tissue samples resected based on interictal spikes were infiltrated by tumor, even if the MRI did not show abnormalities. Complete resection of epileptogenic foci in ioECoG may promote seizure control in IDH-mutant gliomas. The cohort size of IDH-wildtype tumors was too limited to draw definitive conclusions. Interictal spikes may indicate tumor infiltration even when this area appears normal on MRI. Integrating electrophysiology guidance into oncological tumor surgery could contribute to improved seizure outcomes and precise guidance for radical tumor resection.

Clinical Correlation of Altered Molecular Signatures in Epileptic Human Hippocampus and Amygdala

Widespread alterations in the expression of various genes could contribute to the pathogenesis of epilepsy. The expression levels of various genes, including major inhibitory and excitatory receptors, ion channels, cell type-specific markers, and excitatory amino acid transporters, were assessed and compared between the human epileptic hippocampus and amygdala, and findings from autopsy controls. Moreover, the potential correlation between molecular alterations in epileptic brain tissues and the clinical characteristics of patients undergoing epilepsy surgery was evaluated. Our findings revealed significant and complex changes in the expression of several key regulatory genes in both the hippocampus and amygdala of patients with intractable epilepsy. The expression changes in various genes differed considerably between the epileptic hippocampus and amygdala. Different correlation patterns were observed between changes in gene expression and clinical characteristics, depending on whether the patients were considered as a whole or were subdivided. Altered molecular signatures in different groups of epileptic patients, defined within a given category, could be viewed as diagnostic biomarkers. Distinct patterns of molecular changes that distinguish these groups from each other appear to be associated with epilepsy-specific functional consequences.

Expressional Study of Permeability Glycoprotein and Multidrug Resistance Protein 1 in Drug-resistant Mesial Temporal Lobe Epilepsy.

About 30% of patients with epilepsy do not respond to anti-epileptic drugs, leading to refractory seizures. The pathogenesis of drug-resistance in mesial temporal lobe epilepsy (MTLE) is not completely understood. Increased activity of drug-efflux transporters might be involved, resulting in subclinical concentrations of the drug at the target site. The major drug-efflux transporters are permeability glycoprotein (P-gp) and multidrug-resistance associated protein-1 (MRP-1). The major drawback so far is the expressional analysis of transporters in equal numbers of drug-resistant epileptic tissue and age-matched non-epileptic tissue. We have studied P-gp and MRP-1 drug-efflux transporters in the sclerotic hippocampal tissues resected from the epilepsy surgery patients (n=15) and compared their expression profile with the tissues resected from non-epileptic autopsy cases (n=15). Statistically significant over expression of both P-gp (P<0.0001) and MRP-1 (P=0.01) at gene and protein levels were found in the MTLE cases. The fold change of P-gp was more pronounced than MRP-1. Immunohistochemistry of the patient group showed increased immunoreactivity of P-gp at blood-brain barrier and increased reactivity of MRP-1 in the parenchyma. The results were confirmed by confocal immunofluorescence microscopy. Our results suggested that P-gp in association with MRP-1 might be responsible for the multi-drug resistance in epilepsy. P-gp and MRP-1 could be important determinants of bio availability and tissue distribution of anti-epileptic drugs in the brain which can pharmacologically inhibited to achieve optimal drug penetration to target site.