Search Results (2,757)

Background/Objectives: Polyphenols have been suggested to possess anticonvulsant properties, which can be exploited as tools in novel strategies against epilepsy. Along that line, the aim of this study was to investigate the effects of a polyphenol-rich extract of white grape juice (WGJe) in different rodent models of epilepsy, exploring its putative mechanism of action. Methods: In this study, we employed pentylenetetrazole (PTZ)-injected ICR-CD1 mice, audiogenic seizure (AGS)-susceptible DBA/2 mice and WAG/Rij rats. Seizures were monitored and scored, while absence was assessed by electroencephalogram. The open-field test was employed to assess the anxiolytic effects of WGJe. In order to assess the involvement of the GABA_A receptor, we used the antagonist flumazenil in AGS-susceptible DBA/2 mice. Computational analyses were employed to evaluate the interaction of the main polyphenols of WGJe and GABA_A receptors. Results: Our results showed that the intraperitoneal injection of WGJe hindered tonic seizures in PTZ-injected ICR-CD1 mice. In WAG/Rij rats, WGJe did not elicit any significant effects on spike-wave discharges compared to untreated rats. In AGS-susceptible DBA/2 mice, WGJe significantly hampered both clonic and tonic seizures, as well as induced anxiolytic effects. Interestingly, when administering WGJe with flumazenil to DBA/2 mice, we noted that the observed effects were mediated by the GABA_A receptor. Moreover, docking simulations confirmed that the main polyphenols of WGJe are able to interact with the benzodiazepine sites located in both extracellular and transmembrane domains in the GABA_A receptor. Conclusions: This study outlines the mechanism underlying the anti-epileptic activity of WGJe, thus supporting its potential role in the management of epilepsy. Full article

Melatonin is indispensable for the homeostasis of plants and animals. In humans, it can help prevent or be an adjuvant treatment for several diseases mainly related to the immune system, inflammation, and oxidative stress. Moreover, a melatonin-rich diet is linked to several health benefits, such as regulation of circadian rhythm, regulation of the immunological system, epilepsy control, delaying the aging process, and diminishing hormones related to cancer. This review aimed to show the effects of melatonin in diseases beyond its traditional use. The results showed it can present scavenging of free radicals, reducing inflammatory cytokines, and modulating the immune system. Moreover, it can improve insulin resistance, blood pressure, LDL-c, adipose tissue mass, adhesion molecules, endothelial impairment, and plaque formation. These effects result in neuro- and cardioprotection, improvement of liver diseases, rheumatoid arthritis, dermatitis, COVID-19, polycystic ovaries, and sepsis. We conclude that plant melatonin can benefit patients with many diseases besides sleep problems and neurodegeneration. Plant melatonin may be more cost-effective and present fewer adverse events than synthetic. However, more clinical trials should be performed to show adequate doses, formulation, and treatment time. Full article

Goals of automated detection of epileptic seizures using wearable devices include objective documentation of seizures, prevention of sudden unexpected death in epilepsy (SUDEP) and seizure-related injuries, obviating both the unpredictability of seizures and potential social embarrassment, and finally to develop seizure-triggered on-demand therapies. Automated seizure detection devices are based on the analysis of EEG signals (scalp-EEG, subcutaneous EEG and intracranial EEG), of motor manifestations of seizures (surface EMG, accelerometry), and of physiologic autonomic changes caused by seizures (heart and respiration rate, oxygen saturation, sweat secretion, body temperature). While the detection of generalized tonic-clonic and of focal to bilateral tonic-clonic seizures can be achieved with high sensitivity and low false alarm rates, the detection of focal seizures is still suboptimal, especially in the everyday ambulatory setting. Multimodal seizure detection devices in general provide better performance than devices based on single measurement parameters. Long-term use of seizure detection devices in home environments helps to improve the accuracy of seizure diaries and to reduce seizure-related injuries, while evidence for prevention of SUDEP is still lacking. Automated seizure detection devices are generally well accepted by patients and caregivers. Full article

Background: Transforming one-dimensional (1D) biomedical signals into two-dimensional (2D) images enables the application of convolutional neural networks (CNNs) for classification tasks. In this study, we investigated the effectiveness of different 1D-to-2D transformation methods to classify electrocardiogram (ECG) and electroencephalogram (EEG) signals. Methods: We select five transformation methods: Continuous Wavelet Transform (CWT), Fast Fourier Transform (FFT), Short-Time Fourier Transform (STFT), Signal Reshaping (SR), and Recurrence Plots (RPs). We used the MIT-BIH Arrhythmia Database for ECG signals and the Epilepsy EEG Dataset from the University of Bonn for EEG signals. After converting the signals from 1D to 2D, using the aforementioned methods, we employed two types of 2D CNNs: a minimal CNN and the LeNet-5 model. Our results indicate that RPs, CWT, and STFT are the methods to achieve the highest accuracy across both CNN architectures. Results: These top-performing methods achieved accuracies of 99%, 98%, and 95%, respectively, on the minimal 2D CNN and accuracies of 99%, 99%, and 99%, respectively, on the LeNet-5 model for the ECG signals. For the EEG signals, all three methods achieved accuracies of 100% on the minimal 2D CNN and accuracies of 100%, 99%, and 99% on the LeNet-5 2D CNN model, respectively. Conclusions: This superior performance is most likely related to the methods’ capacity to capture time–frequency information and nonlinear dynamics inherent in time-dependent signals such as ECGs and EEGs. These findings underline the significance of using appropriate transformation methods, suggesting that the incorporation of time–frequency analysis and nonlinear feature extraction in the transformation process improves the effectiveness of CNN-based classification for biological data. Full article

Background/Objectives: Artificial intelligence (AI) and machine learning (ML) are transforming healthcare by enabling predictive, diagnostic, and therapeutic advancements. Pediatric healthcare presents unique challenges, including limited data availability, developmental variability, and ethical considerations. This narrative review explores the current trends, applications, challenges, and future directions of ML in pediatric healthcare. Methods: A systematic search of the PubMed database was conducted using the query: (“artificial intelligence” OR “machine learning”) AND (“pediatric” OR “paediatric”). Studies were reviewed to identify key themes, methodologies, applications, and challenges. Gaps in the research and ethical considerations were also analyzed to propose future research directions. Results: ML has demonstrated promise in diagnostic support, prognostic modeling, and therapeutic planning for pediatric patients. Applications include the early detection of conditions like sepsis, improved diagnostic imaging, and personalized treatment strategies for chronic conditions such as epilepsy and Crohn’s disease. However, challenges such as data limitations, ethical concerns, and lack of model generalizability remain significant barriers. Emerging techniques, including federated learning and explainable AI (XAI), offer potential solutions. Despite these advancements, research gaps persist in data diversity, model interpretability, and ethical frameworks. Conclusions: ML offers transformative potential in pediatric healthcare by addressing diagnostic, prognostic, and therapeutic challenges. While advancements highlight its promise, overcoming barriers such as data limitations, ethical concerns, and model trustworthiness is essential for its broader adoption. Future efforts should focus on enhancing data diversity, developing standardized ethical guidelines, and improving model transparency to ensure equitable and effective implementation in pediatric care. Full article

Seizure prediction is a critical challenge in epilepsy management, offering the potential to improve patient outcomes through timely interventions. This study proposes a novel framework combining a convolutional neural network (CNN) based on EfficientNet-B0 and an ensemble of six Support Vector Machines (SVMs) with a voting mechanism for robust seizure prediction. The framework leverages normalized Short-Time Fourier Transform (STFT) and channel correlation features extracted from EEG signals to capture both spectral and spatial information. The methodology was validated on the CHB-MIT dataset across preictal windows of 10, 20, and 30 min, achieving accuracies of 96.12%, 94.89%, and 94.21%, and sensitivities of 95.21%, 93.98%, and 93.55%, respectively. Comparing the results with state-of-the-art methods, we highlight the framework’s robustness and adaptability. The EfficientNet-B0 backbone ensures high accuracy with computational efficiency, while the SVM ensemble enhances prediction reliability by mitigating noise and variability in EEG data. Full article

Background: Epilepsy is a neurological disorder defined by the occurrence of epileptic seizures, which can significantly affect children, often leading to learning and cognitive impairments. Microglia, the resident immune cells of the central nervous system, are essential in clearing damaged neurons through phagocytosis. Notably, GAB_BR-associated microglia have been implicated in regulating phagocytic activity. Since the phagocytic function of microglia is critical in the pathogenesis of epilepsy, this study aims to investigate the role of GAB_BR-associated microglia in the development of the immature brain following epileptic seizures. Methods: Epilepsy was induced in a mouse model by the intraperitoneal injection of KA. Changes in the expression of the GAB_BR-related gene, GAB_BR2, in hippocampal microglia were analyzed using single-nucleus RNA sequencing (snRNA-seq). Cognitive and emotional changes in the mice were assessed through behavioral analyses. The expression of GAB_BR2 was semi-quantitatively measured using Western blotting, quantitative reverse transcription PCR, and immunofluorescence. Additionally, the spatial relationship between GAB_BR2 and hippocampal neurons was evaluated using Imaris software. Results: The snRNA-seq analysis revealed that GAB_BR2 expression was elevated in activated microglia in the hippocampus during chronic epilepsy compared to the early phase of seizures. Behavioral assessments demonstrated heightened anxiety levels and learning and memory impairments in the chronic epilepsy group compared to the control group. GAB_BR2 expression was upregulated in chronic epilepsy. Three-dimensional reconstruction analyses revealed a significantly increased contact volume between GAB_BR-associated microglia and neurons in the chronic epilepsy group compared to the control group. Conclusions: GAB_BR-associated microglia significantly contribute to the progression of immature brain diseases by promoting neuronal phagocytic activity. Full article

Background and Objectives: This study aimed to determine the initial clinical characteristics of children diagnosed with intentional head trauma (IHT) to obtain information about the long-term developmental, psychological, and psychosocial status of these children, to detect delayed sequelae, and to find out information about their judicial processes. Materials and Methods: Fourteen children who were followed up with the diagnosis of IHT in the Ankara Child Protection Unit between 2010 and 2021 were included in the study. These cases were evaluated in terms of physical, developmental, psychological, and visual findings. A complete physical examination was performed on the patients and their anthropometric measurements were taken. Anterior and posterior segment evaluations and visual field examinations were conducted in the visual assessment. The Expanded Guide for Monitoring Child Development and Vineland Adaptive Behavior Scale Third Edition was used in the developmental assessment. A psychiatric evaluation was performed using the Ankara Developmental Screening Inventory, Crowell observation, Affective Disorders and Schizophrenia Form, and Wechsler Intelligence Scale for Children. Results: Of the patients diagnosed with IHT, 71.4% were male and the mean age was 8.39 ± 5.86 (1.27–22.30; IQR: 3.55–11.96) months. In the long-term follow-up, cerebral palsy was detected in three of the children, epilepsy in one, optic atrophy and deviation due to this in one, and deviation due to brain trauma in one. Motor delay was detected in 50.0% of the patients, language delay in 37.5%, cognitive delay in 37.5%, and attention deficit and hyperactivity disorder in 25%. It was observed that the people who caused the injuries of two patients were punished. Conclusions: Children diagnosed with IHT should be monitored with transdisciplinary methods in terms of physical and mental health throughout childhood, starting from the first intervention. Awareness of IHT diagnosis should be increased with training in social service approaches and judicial authorities providing services for child neglect and abuse. Full article

Background: Psychogenic non-epileptic seizures (PNES) are seizure-like episodes that resemble behavioral aspects observed for epileptic seizures but are without the abnormal electrical activity typically seen in epilepsy. The lack of an etiologic model for PNES as well as limitations of available diagnostic methods largely hinders a clear-cut distinction from epilepsy and from a normal functioning brain. Methods: In this study, we investigate the brain dynamics of people with PNES and people with epilepsy during phases far-off seizures and seizure-like events as well as the brain dynamics of a control group. Probing for differences between these groups, we utilise the network ansatz and explore local and global characteristics of time-evolving functional brain networks. We observe subject-specific differences in local network characteristics across the groups, highlighting the physiological functioning of specific brain regions. Furthermore, we observe significant differences in global network characteristics—relating to communication, robustness, and stability aspects of the brain. Conclusions: Our findings may provide new insights into the mechanisms underlying PNES and offer a promising diagnostic approach to differentiate them from epilepsy. Full article

Pathogenic variants in DNM1L, encoding dynamin-like protein-1 (DRP1), cause a lethal encephalopathy. DRP1 defective function results in altered mitochondrial networks, characterized by elongated/spaghetti-like, highly interconnected mitochondria. We validated in yeast the pathogenicity of a de novo DNM1L variant identified by whole exome sequencing performed more than 10 years after the patient’s death. Meanwhile, we reviewed the broadness and specificities of DNM1L-related phenotype. The patient, who exhibited developmental delay in her third year, developed a therapy-refractory myoclonic status epilepticus, followed by neurological deterioration with brain atrophy and refractory epilepsy. She died of heart failure due to hypertrophic cardiomyopathy. She was found to be heterozygous for the DNM1L variant (NM_ 012062.5):c.1201G>A, p.(Gly401Ser). We demonstrated its deleterious impact and dominant negative effect by assessing haploid and diploid mutant yeast strains, oxidative growth, oxygen consumption, frequency of petite, and architecture of the mitochondrial network. Structural modeling of p.(Gly401Ser) predicted the interference of the mutant protein in the self-oligomerization of the DRP1 active complex. DNM1L-related phenotypes include static or (early) lethal encephalopathy and neurodevelopmental disorders. In addition, there may be ophthalmological impairment, peripheral neuropathy, ataxia, dystonia, spasticity, myoclonus, and myopathy. The clinical presentations vary depending on mutations in different DRP1 domains. Few pathogenic variants, the p.(Gly401Ser) included, cause an encephalocardiomyopathy with refractory status epilepticus. Full article

Background/Objectives: ZNF711(Zinc finger protein 711) encodes a zinc finger protein of currently undefined function, located on the X chromosome. Current knowledge includes a limited number of case reports where this gene has been exclusively associated with X-linked intellectual disability (XLID). As far as we are aware, we report the first cases of epilepsy associated with this particular variant. Our aim is to further delineate the phenotypic spectrum of ZNF711 gene pathogenic variants, adding clinical features to this rare condition, following a genotype-first approach. Case presentation: We describe the familiar case of two male siblings presenting with moderate intellectual disability (ID), language delay, and motor stereotypies. Additionally, they experienced generalized tonic–clonic seizures (GTCSs) and myoclonic seizures with interictal electroencephalographic abnormalities. Both children underwent various genetic testing and counselling, including an extended next-generation sequencing (NGS) panel, revealing a hemizygous c.657C > G pathogenic variant in the ZNF711 gene from maternal inheritance. Conclusions: This case expands the clinical range of ZNF711 variants by highlighting epilepsy as a potential comorbidity and suggesting other possible causal candidates for generalized epilepsy. Moreover, it emphasizes the need for further research into the phenotypic spectrum associated with this variant. Full article

Epilepsy affects 50 million people worldwide and is drug-resistant in approximately one-third of cases. Even when a structural lesion is identified as the epileptogenic focus, understanding the underlying genetic causes is crucial to guide both counseling and treatment decisions. Both somatic and germline DNA variants may contribute to the lesion itself and/or influence the severity of symptoms. We therefore used whole exome sequencing (WES) to search for potentially pathogenic somatic DNA variants in brain samples from children with lesional epilepsy who underwent epilepsy surgery. WES was performed on 20 paired DNA samples extracted from both lesional brain tissue and reference tissue from the same patient, such as leukocytes or fibroblasts. The paired WES data were jointly analyzed using GATK Mutect2 to identify somatic single nucleotide variants (SNVs) or insertions/deletions (InDels), which were subsequently evaluated in silico for their disease-causing potential using MutationTaster2021. We identified known pathogenic somatic variants in five patients (25%) with variant allele frequencies (VAF) ranging from 3–35% in the genes MTOR, TSC2, PIK3CA, FGFR1, and PIK3R1 as potential causes of cortical malformations or central nervous system (CNS) tumors. Depending on the VAF, we used different methods such as Sanger sequencing, allele-specific qPCR, or targeted ultra-deep sequencing (amplicon sequencing) to confirm the variant. In contrast to the usually straightforward confirmation of germline variants, the validation of somatic variants is more challenging because current methods have limitations in sensitivity, specificity, and cost-effectiveness. In our study, WES identified additional somatic variant candidates in additional genes with VAFs ranging from 0.7–7.0% that could not be validated by an orthogonal method. This highlights the importance of variant validation, especially for those with very low allele frequencies. Full article

Introduction: Joint hypermobility (JH) is mobility beyond the normal range of motion. JH can be an isolated finding or a characteristic of a syndrome. Characteristics related to the sitting position with atypical body positions, such as sitting in splits (S), with the foot on the head (F), in W (W), in a concave shape (C), episodes of dislocations, and subluxations, suggest impacts on body mechanics since childhood, with damage to the conformation of the joints. Objectives: Identify preclinical signs of JH, in addition to Beighton Score (BS), through signs that are easily recognized early by pediatricians and family members to avoid possible joint deformities in the future. Methods: The medical records of 124 children (59.7% girls) between one and nine years old were analyzed. JH was assessed using the BS, a history of luxations/subluxations, and the concave (C), “W”, “splits” (S), and foot (F) on head sitting positions. Results: The concave sitting position was the most common, followed by W, F, and S in decreasing order. A total of 52.4% of the children had BS > 6, with a higher prevalence among girls (60.8%) compared to boys (40.0%); a difference statistically significant (p = 0.024, Fisher’s exact test). Thirty-two patients (27.4%) had luxations/subluxations with the higher scores. Conclusions: Sitting in S, F, W, and C positions are preclinical phenotypic characteristics of JH, easily identified by pediatricians and family members to prevent possible joint deformities. BS ≥ 6 is more frequently observed in all positions. The majority of the total sample has BS > 6, with a significant female gender influence. Among those with a history of occasional joint dislocations and subluxations, half of them have the highest BS scores. Full article

Reactive astrogliosis and acidosis, common features of epileptogenic lesions, express a high level of astrocytic acid-sensing ion channel-1a (ASIC1a), a proton-gated cation channel and key mediator of responses to neuronal injury. This study investigates the role of astrocytic ASIC1a in cognitive impairment following epilepsy. Status epilepticus (SE) in C57/BL6 mice was induced using lithium–pilocarpine; the impact of ASIC1a on astrocytes was assessed using rAAV–ASIC1a–NC and rAAV–ASIC1a–shRNA, injected in the CA3 region of mice. Behavioral assessments were conducted using the Morris water maze (MWM). Western blotting and immunofluorescence were applied to evaluate ASIC1a and Gfap expression while analyzing intracellular calcium and extracellular glutamate (Glu) concentrations in primary cultured astrocytes isolated from the brains of 1 to 3-day-old mice and treated LPS. Results showed enhanced astrocyte proliferation and ASIC1a expression in the dentate gyrus of epileptic mice 7, 21, and 28 days post-SE (all p < 0.05). Escape latency in the MWM further suggested that ASIC1a regulates cognitive function in mice with chronic epilepsy. LPS stimulation in vitro mimicked inflammatory responses, increasing ASIC1a after 24 h, which increased the concentration of intracellular calcium and extracellular expression of Glu; inhibition of ASIC1a expression reversed this process. To sum up, these data confirm that astrocytic ASIC1a may facilitate cognitive dysfunction post-epilepsy, presenting a potential therapeutic target. Full article

Drug-induced gingival overgrowth is associated with various systemic diseases, including epilepsy. Among antiepileptic medications, phenytoin is commonly reported to cause this condition. In contrast, sodium valproate (VPA), another widely used antiepileptic drug, rarely induces gingival overgrowth. This difference in side effects highlights the variability in drug-induced oral complications among different antiepileptic medications. This case study presents a patient who developed significant gingival overgrowth after using VPA for over 10 years. The study aims to identify VPA as the causative agent and observe changes during long-term administration and after dose reduction. Our findings demonstrate that even long-standing gingival overgrowth can improve rapidly following discontinuation of the causative medication, providing valuable insights for managing similar cases in the future. Full article