The number of neurons in the developing brain is greater than typically found in adulthood, and the brain possesses delicate mechanisms to induce the death of excess cells and refine neural circuitry. The correct tuning between the processes of neuronal death and survival generates a mature and functional brain in its complexity and plastic capacity. Epilepsy is a highly prevalent neurological condition worldwide, including among young individuals. However, exposure to the main treatment approaches, the long-term use of Antiseizure Medication (ASM), during the critical period of development can induce a series of changes in this delicate balance. Acting by various mechanisms of action, ASMs may induce an increase in neuronal death, something that translates into deleterious neuropsychiatric effects in adulthood. Several investigations conducted in recent years have brought to light new aspects related to this dynamic, yet many questions, such as the cellular mechanisms of death and the pathophysiology of late effects, still have unresolved elements. In this review, we aimed to explore the mechanisms of action of the most widely used ASMs in the treatment of neonatal epilepsy, the broad aspects of neuronal death in the developing brain and the repercussions of this death and other effects in adulthood. We review the evidence indicating a relationship between exposure to ASMs and the manifestation of associated psychiatric comorbidities in adulthood and discuss some possible mechanisms underlying the induction of this process by morphological and physiological changes in the related behaviors.

Since ancient times many countries have employed medicinal plants as part of traditional medicine. Anethole is a substance found in various plants and has two isomers, cis-anethole (CA) and trans-anethole (TA). Currently, the food industry extensively use anethole as an aromatic and flavoring component. Extensive scientific research are warranted to provide scientific proof for the usage of anethole, given its widespread use and affordable price. Preclinical studies have suggested several pharmacological effects for anethole including neuroprotective properties. It has been determined that anethole through modulation of monoamines, gamma-aminobutyric acid (GABA)ergic and glutamatergic neurotransmissions as well as its possible anti-inflammatory and antioxidative stress properties affected central nervous system (CNS). In this concept previous studies have demonstrated anxiolytic, antidepressant, antinociceptive, anticonvulsant, and memory improvement effects for anethole. To fully understand its therapeutic potentials, more research are required to elucidate the precise mechanisms by which TA and CA affected CNS. This review summarizes the current knowledge on pharmacological activities of the anethole concentrating its neurological properties, and the possible mechanisms underlying these effects. Various pharmacological effects which have been reported suggesting that anethole could be considered as a potential agent for management of neurological disorders.

Perampanel (PER) is a selective non-competitive AMPA receptor antagonist approved for treating focal and generalized seizures. However, its efficacy in genetic generalized epilepsy (GGE) has not been extensively studied in Chinese populations. This retrospective, single-center study enrolled 54 patients with GGE treated with PER between March 2021 and November 2023. To ensure data quality and minimize bias, we implemented standardized data collection procedures including: (1) systematic documentation using standardized seizure diaries, (2) regular follow-up assessments at predefined intervals, and (3) rigorous application of inclusion/exclusion criteria. Efficacy was assessed by seizure freedom rate, responder rate (≥50 % seizure reduction) and retention rate at 3, 6, 12 months and last follow-up. Safety was evaluated by monitoring adverse events. At last follow-up (mean 14 ± 4.95 months), the overall seizure freedom rate was 53.7 % and responder rate was 70.4 %. Idiopathic generalized epilepsy (IGE) patients showed better outcomes compared to non-IGE patients (seizure freedom: 63.6 % vs 10 %; responder rate: 79.5 % vs 30 %). PER demonstrated highest efficacy in generalized tonic-clonic seizures (80.4 % responder rate), followed by myoclonic (70.8 %) and absence seizures (50 %). Among epilepsy syndromes, GTCA showed the best response (100 % responder rate), followed by JME (83.3 %). The mean effective dose was 3.86 mg/day in the seizure-free group. Treatment-emergent adverse events occurred in 18.5 % of patients, with dizziness (18.5 %) being most common, leading to discontinuation in 3.7 % of cases. PER demonstrated favorable efficacy and tolerability in Chinese patients with GGE, particularly in IGE patients and those with generalized tonic-clonic seizures. Lower doses were associated with better outcomes, suggesting careful dose titration may optimize therapeutic benefits.

Acute Mountain Sickness (AMS) is a prevalent and potentially debilitating condition affecting individuals who participate in high-altitude journeys, mostly above 2500 m. The main symptoms of AMS, listed in the Lake Louise Symptom score used to diagnose AMS, are headache, dizziness, nausea, and fatigue. However, mountaineering can also be associated with other neurological disturbances. Most records related to neurological disorders associated with high-altitude medicine focus on AMS and its typical neurological symptoms indicated in official criteria. Other conditions related to acute exposure to high altitudes are high-altitude headaches (HAH), which usually precede AMS and high-altitude cerebral oedema (HACE), which can be a complication of AMS or appear independently.

This review aimed to describe studies that included atypical neurological symptoms, which appear during acute exposure to high altitudes and are not mentioned in the criteria of AMS or HACE. Four databases, PubMed, Embase, Web of Science, and Medline Ultimate, were screened. PROSPERO registration ID for this review is CRD420250654251.

Studies that met our inclusion criteria presented symptoms related to well-known conditions, such as stroke, deep cerebral vein thrombosis, seizures, or transient neurological dysfunctions. Moreover, cranial nerve palsies, olfactory threshold impairment, multiple sclerosis worsening, or speech, memory, and sensation disturbances were described in patients at high altitudes.

This review shows that high altitude may be an inducing factor in other neurological disturbances besides AMS, HAH, and HACE symptoms. The growing popularity of high-altitude stays should be associated with increasing knowledge about the unusual neurological symptoms that may occur.

Current medications for seizure symptoms can reduce seizure severity but do not stop or slow their progression. These drugs often have unpleasant side effects and may not work for all patients. The search for new therapeutic targets for seizure progression can be expedited through drug repurposing, which leverages existing approved medications, ultimately reducing clinical trial costs. This study investigates the neuroprotective properties of pomalidomide, an immunomodulatory drug, in a male rat model of pentylenetetrazol-induced seizures. Pomalidomide pretreatment significantly decreased the frequency and severity of seizures and delayed their onset. It elevated glutathione peroxidase (GPX) and superoxide dismutase (SOD) levels while lowering malondialdehyde (MDA), showcasing its antioxidant effects. Furthermore, it activated the Nrf2/HO-1 signaling pathway by increasing gene expression in the hippocampus, providing neuroprotection in the CA1 and CA3 regions. These findings suggest that pomalidomide may enhance the antioxidant defense system, support the Nrf2/HO-1 pathway, and protect the hippocampus, indicating its potential for treating patients with seizures, particularly intractable ones.

Drug-resistant epilepsy (DRE) is a significant global public health challenge affecting people with epilepsy (PWE). Despite the availability of multiple drug therapies, a significant number of PWE with DRE continue to experience frequent seizures. Current data on the prevalence of DRE and associated risk factors in the Saudi population is limited. This study aimed to estimate and characterize DRE among PWE and identify associated predictive factors.

A cross-sectional study was conducted on PWE who attended Neurology clinics at the National Guard Health Affairs in Riyadh, Saudi Arabia (NGHA-R) between June 2016 and February 2023. Data were collected from patient medical records. Descriptive analyses of continuous and categorical variables were performed. Comparisons between categorical data were conducted using Pearson's chi-squared test. Multivariable logistic regression was used to identify independent factors associated with the development of DRE. A p-value of < 0.05 was considered statistically significant.

A total of 350 patients were analyzed, with a confirmed DRE prevalence of 26.86% (94 out of 350). Age-specific analysis revealed that DRE was most prevalent in the 29-39 age group, accounting for 35.1% (33 out of 94) of cases. The primary predictor for DRE was focal seizure type (AOR = 1.85; 95% CI: 1.05-3.27, p = 0.03). Additionally, DRE patients were more likely to visit the emergency room. Among antiseizure medications, treatment regimens of valproic acid (p = 0.0008), carbamazepine (p = 0.0097), and lamotrigine (p = 0.037) showed significant associations with DRE status.

The prevalence of DRE in Saudi Arabia remains within the previously reported range of global prevalence. Frequent emergency department visits and the use of ASM polytherapy should be followed up closely to ensure early diagnosis of DRE and improve clinical outcomes.

Epilepsy is a neurological disorder characterized by recurrent epileptic seizures, whose neurophysiological signature is altered electroencephalographic (EEG) activity. The use of artificial intelligence (AI) methods on EEG data can positively impact the management of the disease, significantly improving diagnostic and prognostic accuracy as well as treatment outcomes. Our work aims to systematically review the available literature on the use of unsupervised machine learning methods on EEG data in epilepsy, focusing on methodological and clinical differences in terms of algorithms used and clinical applications.

Following the PRISMA guidelines, a systematic literature search was performed in several databases for papers published in the last 10 years. Studies employing both unsupervised and self-supervised methods for the classification of EEG data in epilepsy patients were included. The main outcomes of the study were: (i) to provide an overview of the datasets used as input to train the algorithms; (ii) to identify trends in pre-processing, algorithm architectures, validation, and metrics for performance estimation; (iii) to identify and review the clinical applications of AI in epilepsy patients.

A total of 108 studies met the inclusion criteria. Of them, 86 (79.6 %) have been published in the last 5 years and 60 (55.5 %) in the last two years. The most used validation methods were: hold-out in 37 (34.2 %), k-fold-cross validation in 35 (32.4 %), and leave-one-out in 19 (17.6 %) studies, respectively. Accuracy, sensitivity, and specificity were the most used performance metrics being reported in 71 (65.7 %), 62 (57.4 %), and 42 (39.8 %) studies, respectively, followed by F1-score (27 studies; 25 %), precision (26 studies; 24 %), area under the curve (25 studies; 23.1 %), and false positive rate (22 studies; 20.3 %). Furthermore, 42 (38.9 %) compared to 63 (58.3 %) studies used individual patient versus multiple patients models, respectively. Finally, concerning the clinical applications of unsupervised learning methods on epilepsy patients, we identified six main fields of interest: seizure detection (69 studies; 63.9 %), seizure prediction (27 studies; 25 %), signal propagation and characterization (2 studies; 1.8 %), seizure localization (4 studies; 3.7 %), and seizure classification (22 studies; 20.3 %), respectively.

The results of this review suggest that the interest in the use of unsupervised learning methods in epilepsy has significantly increased in recent years. From a methodological perspective, the input EEG datasets used for training and testing the algorithms remain the hardest challenge. From a clinical standpoint, the vast majority of studies addressed seizure detection, prediction, and classification whereas studies focusing on seizure characterization and localization are lacking. Future work that can potentially improve the performance of these algorithms includes the use of context information via reinforcement learning and a focus on model explainability.

Epilepsy is a group of neurologic disorders with clinical and genetic heterogeneity. Epilepsy often affects children; thus, early diagnosis and precise treatment are vital to protecting the standard of life of a child. Progress in epilepsy-related gene discovery has caused enormous novelty in specific epilepsy diagnoses. Genetic testing using next-generation sequencing is now reachable, leading to higher diagnosis ratios and understanding of the disease's underlying mechanisms. The study's primary aim was to identify the genetic etiology based on targeted next-generation sequence analysis data and to calculate the diagnostic value of the epilepsy gene panel in the 0-17 age-group diagnosed with epilepsy. The secondary aim was to demonstrate the significance of periodic reinterpretation of variant of uncertain significance (VUS) variants and genotype-phenotype correlation.

This retrospective study comprised 107 patients with epilepsy aged 8 months to 17 years, for whom a targeted gene panel covered 110 genes. VUS variants were reanalyzed, and genotype-phenotype correlation was performed.

In the initial evaluation, causal variants were described in 23 patients (21.5%). After reinterpretation of VUS, we detected causal variants in 30 out of 107 patients (28%). By reinterpreting the VUS and evaluating genotype-phenotype correlations, we enhanced our diagnostic value by 30.32%. After reinterpretation of VUS variants, the ACMG classification of 36 variants, including 15 benign (31%), 15 likely benign (31%), 5 likely pathogenic (10%), and 1 pathogenic (2%), were redefined. We most frequently detected causal variants in TSC2 (n = 5), GRIN2A (n = 4), and ALDH7A1 (n = 4) genes.

The predictive value for epilepsy panel testing was 28% in the cohort. Our study revealed the importance of reanalysis of VUS variants and contributed to enriching the mutation spectrum in epilepsy.

Focal impaired awareness seizures are a common neurological disorder characterized by abnormal electrical activity in a specific brain region, resulting in impaired consciousness and neurological symptoms. Treatment options for patients may include antiepileptic medications, lifestyle modifications, or, in some cases, surgical intervention aimed at resecting the area of the brain responsible for seizure generation. Shunt malfunction can lead to seizures in cases of hydrocephalus; however, seizures triggered by stimulation of a specific brain area by the shunt catheter post-placement have not been reported.

This case provides a compelling example of a seizure triggered by the stimulation of a foreign body in the ventricle. The patient is a 31-year-old man who suffered seizures due to the proximal catheter remaining in the ventricle.

In general, accidental events during surgery should be carefully investigated and taken into consideration. And if necessary, timely intervention should be done to eliminate possible complications.

Background: Epilepsy is a prevalent condition that affects a large population. However, a lack of knowledge and misconceptions about seizures can lead to inappropriate reactions and negative attitudes toward people with epilepsy, who are more likely to experience stigma because of their illness. This study explored public knowledge, attitudes, and awareness of epilepsy and seizures among residents of Madinah, Saudi Arabia. Methods: A descriptive, cross-sectional study was conducted between September and November 2023 involving 2626 random adult residents of the Madinah Region in Saudi Arabia. Data were collected through an online survey consisting of 27 questions concerning epilepsy. Results: Regarding participants' awareness of epilepsy, 92.2% reported having heard or read about it, and 12.8% had attended a course on controlling epileptic seizures. The results showed an acceptable level of understanding about epilepsy. The mean knowledge and attitude scores about epilepsy for the sample were 22 (SD ± 3.2) and 27.1 (SD ± 3.1), respectively, indicating moderate knowledge and positive attitudes toward epilepsy. Among demographic characteristics, knowledge about epilepsy was significantly associated with gender, age, marital status, educational level, occupation, household monthly income, having heard about epilepsy, having a family member diagnosed with epilepsy, and course attendance. However, attitudes toward epilepsy were only significantly associated with gender, having heard about epilepsy, having a family member diagnosed with epilepsy, and course attendance. Similarly, actions toward seizure attacks were significantly associated with all demographic characteristics except education. Conclusions: The residents of Madinah have generally positive attitudes regarding epilepsy, although their knowledge levels could be enhanced by education. Therefore, more educational awareness campaigns are required to improve public understanding of epilepsy and appropriate actions to take when witnessing a seizure. The results of this study provide a foundation for worldwide comparisons of general levels of knowledge and attitudes concerning epilepsy in Saudi Arabia.

The piriform cortex (PC) plays a critical role in ictogenesis, where an excitation/inhibition imbalance contributes to epilepsy etiology. However, the epileptic dynamics of the gamma-aminobutyric acid (GABA) system and the precise role of GABAergic neurons within the PC in epilepsy remain unclear.

We combined Ca2+ and GABA sensors to investigate the dynamics of Gad2-expressing neurons and GABA levels, and selectively manipulated GABAergic neurons in the PC through chemogenetic inhibition and caspase3-mediated apoptosis targeting Gad2 interneurons.

GABAergic system dynamics in the PC were bidirectional and asymmetric, accompanied by PC optokindling-induced seizures, notably characterized by a robust response of Gad2 neurons but a rapid descent of GABA content during seizures. Chemogenetic inhibition of PC Gad2 neurons induced seizure-like behavior, with a discrepancy between the GABAergic neuron activities and GABA levels, signifying a transition from interictal to ictal states. Surprisingly, selective inhibition of Gad2 neurons in the PC produced paradoxical activation in a subset of Gad2 neurons. Moreover, the chronic deficiency of PC Gad2 neurons triggered spontaneous recurrent seizures.

Our findings uncover the dynamic interplay within PC inhibitory components and elaborate counteractive mechanisms in seizure regulation. These insights could inform future therapeutic strategies targeting GABAergic neurons to control epileptic activity.

Seizure-related injuries represent a significant concern for both individuals with epilepsy and their caregivers. Compared to the general population, those diagnosed with epilepsy face a heightened risk of sustaining injuries. Despite this, there is a notable scarcity of data regarding seizure-related injuries among epileptic patients. This study aimed to evaluate the incidence of seizure-related injuries and identify their predictors among epileptic patients undergoing follow-up treatment at selected public hospitals in Central Ethiopia, in 2023. A prospective follow-up study was carried out in selected public hospitals in central Ethiopia. The study included epileptic patients aged ≥ 18 years who had not experienced any previous injury during follow-up treatment from January 1st, 2023, to December 31st, 2023. Data collection involved conducting interviews with participants using a structured questionnaire and reviewing patients' charts. Univariate analysis, multivariate, and regression analysis were performed to identify potential associations between variables and seizure-related injuries. Variables were deemed significantly associated with seizure-related injuries if they attained a p value of 0.05 with a 95% confidence interval. Out of the 561 participants, 265 (47.2%) experienced seizure-related injuries (95% CI 43.12, 51.38). The incidence density rate of seizure-related injuries among epileptic patients was 11.97 per 100 person-months of observation (95% CI 10.61, 13.50). In multivariate analysis, epileptic patients who had generalized tonic-clonic seizures (adjusted hazard ratio 1.4, 95% CI 1.07-1.84), comorbidities (adjusted hazard ratio 1.3, 95% CI 1.11-1.71), were on polytherapy drug regimens (adjusted hazard ratio 1.80, 95% CI 0.30-2.49), and consumed alcoholic drinks (adjusted hazard ratio 1.5, 95% CI 1.21-1.89) were identified as independent predictors of seizure-related injuries. The incidence rate of seizure-related injuries among epileptic patients was found to be significant. Risk factors identified included experiencing generalized tonic-clonic seizures, having at least one additional health condition, being on multiple medications, and consuming alcohol. To improve survival from injuries, targeted precautions for generalized tonic-clonic seizures, strict adherence to prescribed medication regimens, and avoiding alcohol consumption are recommended.

The ability to differentiate epileptic- and non-epileptic events is challenging due to a lack of reliable molecular seizure biomarker that provide a retrospective diagnosis. Here, we use next generation sequencing methods on whole blood samples to identify changes in RNA expression following seizures.

Blood samples were obtained from 32 patients undergoing video electroencephalogram (vEEG) monitoring. Blood samples were collected in PaxGene tubes at baseline (admission) and following a seizure event (4-6 h and 24 h later or discharge). EEG and video of clinical events were reviewed by the clinical team and study epileptologist and were classified as epileptic seizure, psychogenic nonepileptic spell (PNES), or other. RNA was extracted from blood and RNA expression was determined using RNA-sequencing.

We show significant differences in RNA profiles between patients that did or did not experience an epileptic seizure. Compared to baseline patients with PNES show large increases in RNA expression 4-6 h and 24 h post seizure. Conversely, genes that changed following epileptic seizure showed more modest changes associated with a decrease in immune system function. Transcript usage was changed between patients with PNES and epileptic seizure at all three time points examined. Lists of genes differentially expressed following PNES or epileptic seizure vs. all baseline samples were used as classifiers for prediction. Models generated using random forest and radial support vector machine algorithms were 100% accurate at predicting both PNES and epileptic seizures.

These data suggest that blood gene expression changes may have utility to retrospectively identify patients who have suffered a seizure or seizure-like event as a cause of transient loss of consciousness.

Epilepsy is a pathophysiological condition displaying a highly diverse phenotype. Consequently, comprehending the mechanisms underlying seizures necessitates moving beyond a simplistic model focused on the imbalance between the classical excitatory and inhibitory neurotransmitter systems. Nitric oxide (NO), a nonclassical and multifunctional gaseous neurotransmitter, has the potential to exert a profound influence on epileptic reactivity. Unfortunately, numerous studies have not provided clear answers about its involvement in the pathophysiology of epilepsy. The objective of our study was to delineate the temporal dynamics of alterations in nitrergic system activation after experimentally induced seizures. Seizures were induced in 2-month-old male Wistar rats (n = 55) by an administration of pilocarpine. Over a 6-hour observation period, seizure behaviour intensity was continuously evaluated using a modified Racine scale. At intervals of 6, 12, 24, 48, or 96 h post-chemoconvulsant administration, NO spin trapping was conducted with ferrous-diethyldithiocarbamate complexes (Fe(DETC)2). Electron paramagnetic resonance (EPR) spectroscopy was employed to quantify mononitrosyl iron complexes (NO-Fe(DETC)2) in the brain. The temporal kinetic of NO release after seizures revealed a rise in NO synthesis during the initial 12 h. Subsequently, a sharp decline occurred, returning to baseline 96 h after pilocarpine injection. Notably, our research suggests that the level of NO synthesis does not interfere with the severity of the epileptic seizures that occur. In light of this, we propose that the nitrergic system is quickly activated in the epileptic brain as a compensatory mechanism of the central nervous system. However, under usual conditions, this activation is insufficient to effectively attenuate seizures.

Temporal lobe epilepsy affects nearly 50 million people worldwide and is a major burden to families and society. A significant portion of patients are living in developing countries with limited access to therapeutic resources. This highlights the urgent need to develop more readily available, noninvasive treatments for seizure control. This research explored the effectiveness of transcranial photobiomodulation (tPBM), a non-invasive method utilizing photon-tissue interactions, for preventing epileptogenesis and controlling seizures.

In a kainic acid (KA)-induced rat model of epilepsy, two different wavelengths of tPBM, 808 nm and 940 nm, were applied separately in two groups of animals (KA+808 and KA+940). The ability of tPBM for seizure control was evaluated by comparing the occurrence rate of interictal epileptiform discharges (IED) and behavioral seizures among three groups: KA, KA+808, KA+940. Prevention of epileptogenesis was assessed by comparing the occurrence rate of high frequency oscillations (HFOs), especially fast ripple (FR) rate, among the three groups. Nissl staining and immunostaining for the apoptosis marker caspase-3 were used as indications of neuroprotection.

The KA+808 group and the KA+940 group showed significantly lower FR and IED rates compared to the KA group. Weekly FR rates started to drop during the first week of tPBM treatment. The KA+808 and KA+940 groups also displayed milder seizure behaviors and less neuronal loss in hippocampal areas compared to KA rats without tPBM treatment. Similarly, lower caspase-3 levels in the KA+808 and KA+940 compared with the KA group suggested effectiveness of tPBM in reducing cell death.

tPBM of 808 nm/940 nm showed effectiveness in suppressing epileptogenesis and ictogenesis in the KA-induced rat epilepsy model. This effectiveness of tPBM can be linked to the neuroprotection benefits of photon-tissue interactions. Further studies are warranted to elucidate the fundamental mechanism of tPBM protection, determine optimal treatment parameters and validate its effectiveness in other epilepsy models.

Single Nucleotide Polymorphisms (SNPs) have found it be associated with drug resistance in epilepsy. The purpose of this study was to determine the role of SCN1A gene polymorphism in developing drug resistance in idiopathic generalized epilepsy (IGE) patients, along with increased oxidative stress. The study was conducted at a tertiary care hospital in Delhi, India. We recruited 100 patients diagnosed with IGE patients, grouped as drug-resistant and drug-responsive, and then further compared the SCN1A SNP rs10167228 A*/T analysis between the two groups. We utilized the PCR-RFLP technique to investigate the association between polymorphisms and refractory epilepsy. Serum HMGB1 levels were estimated using the ELISA technique to analyze oxidative stress in both groups. rs10167228 A*/T polymorphism genotypes AT and AA genotypes are significantly associated with an increased risk of developing drug resistance. Serum HMGB1, IL-1β, and IL-6 levels were significantly higher in drug-resistant cases, compared to the drug-responsive group. The association of SCN1A gene polymorphisms, in conjunction with raised oxidative stress, may be predictive of the development of drug-resistant epilepsy. The AT and AA genotypes of rs10167228 may pose a risk factor for developing drug-resistant epilepsy.

Epilepsy is a neurological disorder characterized by recurrent, unprovoked seizures. Currently, the associations among skin microbiota, circulating metabolites, and epilepsy are still not well studied. In this study, we applied univariate and two-step Mendelian randomization analysis using single nucleotide polymorphisms as instrumental variables to analyze the possible associations. Five skin microbiota (asv022, asv008, bacillales, clostridiale, and micrococcaceae) and four circulating metabolites were found to be associated with epilepsy. Our results also showed that leucine level (p-value = 0.0487, OR = 1.067) and glutamine level (p-value = 0.0372, OR = 1.065) show a slight increased association with epilepsy, while phospholipids in medium LDL (p-value = 0.0302, OR = 0.9308) and ratio of saturated fatty acids (p-value = 0.0309, OR = 0.9017) appear to show a slight inverse correlation with epilepsy. In addition, the heterogeneity test and horizontal pleiotropy analysis indicated these results are robust in different situations. By mapping analysis, 54 genes were associated with at least two metabolites. By functional analysis, these genes were enriched in the immune-related pathways, which may have systemic effects on brain function. Our results provide a novel insight for understanding possible mechanisms of some epilepsy associations, which by further study might provide avenues for therapy research.

Epilepsy, a clinical diagnosis characterised by paroxysmal episodes known as seizures, affects 1% of people worldwide. Safe and patient-specific treatment is vital and can be achieved by the development of rapid pre-clinical models of for identified epilepsy genes. Epilepsy can result from either brain injury or gene mutations, and can also be induced chemically. Xenopus laevis tadpoles could be a useful model for confirmation of variants of unknown significance found in epilepsy patients, and for drug re-purposing screens that could eventually lead to benefits for patients. Here, we characterise and quantify seizure-related behaviours in X. laevis tadpoles arrayed in 24-well plates. To provoke acute seizure behaviours, tadpoles were chemically induced with either pentylenetetrazole (PTZ) or 4-aminopyridine (4-AP). To test the capacity to adapt this method for drug testing, we also exposed induced tadpoles to the anti-seizure drug valproate (VPA). Four induced seizure-like behaviours were described and manually quantified, and two of these (darting, circling) could be accurately detected automatically, using the video analysis software TopScan. Additionally, we recorded swimming trajectories and mean swimming velocity. Automatic detection showed that either PTZ or 4-AP induced darting behaviour and increased mean swimming velocity compared to untreated controls. Both parameters were significantly reduced in the presence of VPA. In particular, darting behaviour was a shown to be a sensitive measure of epileptic seizure activity. While we could not automatically detect the full range of seizure behaviours, this method shows promise for future studies since X. laevis is a well-characterised and genetically tractable model organism.

Epilepsy is a chronic neurological disorder, and its prevalence presents a bimodal distribution with high incidences in children and older adults. The incidence of epilepsy does not generally differ between men and women; however, whether this holds true for new-onset epilepsy in older adults is unclear. While studies in animal models of epilepsy may help explore the biological mechanisms relevant to the influences of sex on epileptogenesis, relatively little information is available regarding sex differences in the genesis of epileptic seizures in middle-aged animals. In this study, we addressed this knowledge gap using a mouse model of extended hippocampal kindling. C57 black mice aged between the ages of 12 and 13 months underwent hippocampal kindling as this age roughly corresponds to middle age in humans (∼50 years). Relative to male mice, female mice showed faster-progressing and more severe evoked seizures, a higher tendency to experience spontaneous seizures in the early stage of extended kindling, less frequent expression of hippocampal interictal spikes, and insignificant decreases in hippocampal theta rhythm. Collectively, these results demonstrated the existence of sex-specific differences in hippocampal kindling-induced seizures and suggested that middle-aged female mice have greater but variable susceptibility to hippocampal kindling-induced epileptogenesis compared with male mice of similar age.

This paper develops a computationally efficient model for automatic patient-specific seizure prediction using a two-layer LSTM from multichannel intracranial electroencephalogram time-series data. We decrease the number of parameters by employing a smaller input size and fewer electrodes, thereby making the model a viable option for wearable and implantable devices. We test the proposed prediction model on 26 patients from the European iEEG dataset, which is the largest epileptic seizure dataset. We also apply an automatic preprocessing technique based on a common average reference to remove artifacts from this dataset. The simulation results show that the model with its simple structure in conjunction with the mean post-processing procedure performed the best, with an average AUC of 0.885. This study is the first that utilizes the European database for epilepsy prediction application and the first that analyzes the effect of the seizure type on the system performance and demonstrates that the seizure type has a considerable impact.

Cinnamic alcohol (CA) is a phenylpropanoid found in the essential oil of the bark of the genus Cinnamomum spp. Schaeff. (Lauraceae Juss.), known as cinnamon. To evaluate the neuroprotective effect of CA and its possible mechanism of action on mice submitted to the pentylenetetrazole (PTZ) induced epileptic seizures model. Behavioral, neurochemical, histomorphometric and immunohistochemistry analysis were carried out. The administration of CA (50-200 mg/kg, i.p., 30 min prior to PTZ and 0.7-25 mg/kg, i.p., 60 min prior to PTZ) increased the latency to seizure onset and the latency to death. The effects observed with CA treatment at 60 min were partially reversed by pretreatment with flumazenil. Furthermore, neurochemical assays indicated that CA reduced the concentration of malondialdehyde and nitrite, while increasing the concentration of reduced glutathione. Finally, histomorphometric and immunohistochemistry analysis revealed a reduction in inflammation and an increase in neuronal preservation in the hippocampi of CA pre-treated mice. Taken together, the results suggest that CA seems to modulate the GABAA receptor, decrease oxidative stress, mitigate neuroinflammation, and reduce cell death processes.

The simultaneous hyperexcitability of the neural network is the most well-known manifestation of epilepsy that causes recurrent seizures. The current study was aimed to examine any potential safety benefits of the culture filtrate of Trichoderma harzianum (ThCF) to ameliorate damaged histoarchitecture of the brain in epileptic rats by assessing seizure intensity scale and behavioral impairments and follow up the spontaneous motor seizures during status epilepticus phases in rats. Twenty-four rats were divided into four groups; control (C), epileptic (EP) valproic acid-treated epileptic (EP-VPA), and epileptic treated with T. harzianum cultured filtrate (ThCF). In addition to a seizure intensity score and behavioral tests, routine H&E and Golgi-Copsch histopathology, were used to examine the cell somas, dendrites, axons, and neural spines. ThCF treatment increased activity and recorded movements during grooming, rearing, and ambulation frequency. Brain tissues of epileptic rats exhibited detached meninges, hypercellularity, mild edema in the cortex and markedly degenerated neurons, degenerated glial cells, and microcyst formation in the hippocampus. Moreover, brains of EP-ThCF were noticed with average blood vessels, and increased dendritogenesis. The current data revealed some of negative effects of epileptogenesis brought on by seizure intensity score and retarded histopathological alterations in the hippocampus. Therefore, the study is forecasting to identify novel active components from the metabolites of T. harzianum with a crucial therapeutic role in various disorders.

Although there are numerous treatment options already available for epilepsy, over 30% of patients remain resistant to these antiseizure medications (ASMs). Historically, ASM discovery has relied on the demonstration of efficacy through the use of 'traditional' acute in vivo seizure models (e.g. maximal electroshock, subcutaneous pentylenetetrazol, and kindling). However, advances in genetic sequencing technologies and remaining medical needs for people with treatment-resistant epilepsy or special patient populations have encouraged recent efforts to identify novel compounds in syndrome-specific models of epilepsy. Syndrome-specific models, including Scn1a variant models of Dravet syndrome and APP/PS1 mice associated with familial early-onset Alzheimer's disease, have already led to the discovery of two mechanistically novel treatments for developmental and epileptic encephalopathies (DEEs), namely cannabidiol and soticlestat, respectively.

In this review, the authors discuss how it is likely that next-generation drug discovery efforts for epilepsy will more comprehensively integrate syndrome-specific epilepsy models into early drug discovery providing the reader with their expert perspectives.

The percentage of patients with pharmacoresistant epilepsy has remained unchanged despite over 30 marketed ASMs. Consequently, there is a high unmet need to reinvent and revise discovery strategies to more effectively address the remaining needs of patients with specific epilepsy syndromes, including drug-resistant epilepsy and DEEs.

Epilepsy is a common brain disorder, characterized by spontaneous recurrent seizures, with associated neuropsychiatric and cognitive comorbidities and increased mortality. Although people at risk can often be identified, interventions to prevent the development of the disorder are not available. Moreover, in at least 30% of patients, epilepsy cannot be controlled by current antiseizure medications (ASMs). As a result of considerable progress in epilepsy genetics and the development of novel disease models, drug screening technologies and innovative therapeutic modalities over the past 10 years, more than 200 novel epilepsy therapies are currently in the preclinical or clinical pipeline, including many treatments that act by new mechanisms. Assisted by diagnostic and predictive biomarkers, the treatment of epilepsy is undergoing paradigm shifts from symptom-only ASMs to disease prevention, and from broad trial-and-error treatments for seizures in general to mechanism-based treatments for specific epilepsy syndromes. In this Review, we assess recent progress in ASM development and outline future directions for the development of new therapies for the treatment and prevention of epilepsy.

This study aimed to identify the occurrence of excessive daytime sleepiness (EDS) in epilepsy patients with interictal epileptiform discharges and to explore the impact of interictal sleep architecture and sleep-related events on EDS.

This study included 101 epilepsy patients with interictal epileptiform discharges (IED) and 100 control patients who underwent simultaneous polysomnography and video ambulatory electroencephalography for >7 h throughout a single night. Multiple sleep latency tests were used to assess EDS. Comorbid EDS was present in 25 and 11 patients in the IED epilepsy and control groups, respectively. In addition, univariate and multivariate logistic regression analyses were performed to explore the factors influencing EDS.

The epilepsy group had a higher prevalence of comorbid EDS and shorter R sleep duration. Univariate logistic regression analysis indicated that an increased risk of EDS may be associated with prolonged N1 sleep duration, higher arousal index, lower mean saturation (mSaO2), higher oxygen desaturation index (ODI), and duration of wake after sleep onset (WASO). Multivariate logistic regression analysis revealed that N1 sleep duration was significantly correlated with EDS.

In epilepsy patients with IED, the arousal index, mSaO2, ODI, and duration of WASO were weakly correlated with EDS, and the duration of N1 sleep demonstrated a significant positive correlation with EDS, which requires further research.

Introduction Epilepsy, a chronic neurological disorder marked by recurrent seizures, affects approximately 50 million people worldwide with a higher prevalence in developing countries. This condition challenges motor skills and coordination, leading to poor oral health maintenance. The study aimed to evaluate the effect of epilepsy on oral health outcomes in adults by contrasting South Indian epileptics with healthy controls. The primary objective was to assess the prevalence of oral health issues in patients with epilepsy compared to healthy individuals and to analyze the types and frequency of dental procedures required in epileptic patients compared to healthy controls in the South Indian population. Materials and methods A retrospective study was conducted in the Department of Oral Medicine and Radiology, Saveetha Dental College and Hospitals, Chennai, India. Approved by the Institutional Human Ethical Committee (Registration ID: IHEC/SDC/OMED-2202/23/106), the study involved 105 epileptic patients and 105 healthy controls from records between January 2021 and December 2023. Both male and female patients within the age limit of 18-55 years were included. Statistical analysis was performed using IBM SPSS Statistics for Windows, Version 29.0 (Released 2022; IBM Corp., Armonk, New York, United States). Results The study involved 210 participants with an equal gender distribution. Valproate was the most common medication used by 39% of epileptic patients. Gingival hyperplasia was significantly more prevalent in the epileptic group (24%). The epileptic group also required more dental procedures, with 32% of teeth needing restoration, 20% root canal treatment, and 20% extraction, compared to 12%, 11%, and 5%, respectively, in the control group. Conclusion Epileptic patients exhibit poorer oral health outcomes, including higher rates of gingival hyperplasia and a greater need for dental procedures compared to healthy controls. These findings highlight the necessity for targeted dental care and regular monitoring for individuals with epilepsy to improve their oral health and overall quality of life.

New 2-(4-benzothiazol-2-yl-phenoxy)-1-(3,5-diphenyl-4,5-dihydro-pyrazol-1-yl)-ethanones (9a-o) have been designed and synthesized. All the synthesized compounds were characterized by thin layer chromatography and spectral analysis. The antiepileptic potential of the synthesized compounds has been tested by following standard animal screening models, including maximal electroshock (MES) and subcutaneous pentylenetetrazole (scPTZ) models. The neurotoxic and antidepression effects of the synthesized compounds were checked by utilizing rotarod apparatus, and motor impairment test (by actophotometer) respectively. The study concluded that compounds 9c, 9d, 9f, 9i, 9n, and 9o possessed good antiepileptic potential compared to standard drugs like carbamazepine and phenytoin. The results of the rotarod performance test also established them without any neurotoxicity. The motor impairment test revealed that the synthesized compounds are also good antidepressants. In-silico studies have been performed for calculation of pharmacophore pattern, prediction of pharmacokinetic properties which determine the eligibility of synthesized compounds as orally administered molecules and interactions with the target proteins. The result of in-silico studies reinforced results obtained by in vivo study of the synthesized compounds and their possible mechanism of antiepileptic action i. e. via inhibiting voltage-gated sodium channels (VGSCs) and gamma-aminobutyric acid-A receptor.

The aim of our study was to investigate the relationship between clinical indicators and gene dysregulation in different types of epilepsy, while also seeking to identify a diagnostic model capable of distinguishing between focal and generalized seizures. This highlights the critical importance of understanding clinical indicators and gene dysregulation for targeted therapeutic interventions to effectively address the specific seizure types effectively.

In this study, we conducted a comprehensive analysis of the peripheral blood of epilepsy patients (n = 100) and a control group (n = 51) to determine the differential gene expression. Our analysis involved a range of statistical approaches, including correlation analysis to establish the association between clinical indicators and gene dysregulation, and principal component analysis to highlight distinct disease group from control group. Furthermore, we developed diagnostic models using logistic regression to aid in the accurate diagnosis of epilepsy.

Among several selected genes in this study such as AVP (AUC = 0.832, p < 0.0001), IGF-1 (AUC = 0.658, p = 0.0015), TNF-α (AUC = 0.8970, p < 0.0001), APP (AUC = 0.742, p < 0.0001), CD44 (AUC = 0.614, p = 0.021) and NfL (AUC = 0.937, p < 0.0001), and CLU (AUC = 0.923, p < 0.0001) have shown the outstanding discrimination. In addition to this, when all genes were included in the model, the overall diagnostic power increased significantly (AUC = 0.9968). A differential diagnostic model for focal and generalized seizures was established which discloses AUC = 0.7027, (95 % CL, 0.5765 to 0.8289, p = 0.0019).

The conclusions drawn from these findings represented that this is the first study to highlight the distinctive gene patterns of both focal and generalized seizures, implying that peripheral blood can serve as a diagnostic source to distinguish between these seizures types, aiding in the accurate classification of epilepsy. The findings from this study indicate a promising direction for investigating more targeted pharmacological interventions directed to address the distinct needs of both focal and generalized epilepsy, which offers advancements in treatment strategies for distinctive seizure types.

Unexpected seizures significantly decrease the quality of life in epileptic patients. Seizure attacks are caused by hyperexcitability and anatomical lesions of special regions of the brain, and cognitive impairments and memory deficits are their most common concomitant effects. In addition to seizure reduction treatments, medical rehabilitation involving brain-computer interfaces and neurofeedback can improve cognition and quality of life in patients with focal epilepsy in most cases, in particular when resective epilepsy surgery has been considered treatment in drug-resistant epilepsy. Source estimation and precise localization of epileptic foci can improve such rehabilitation and treatment. Electroencephalography (EEG) monitoring and multimodal noninvasive neuroimaging techniques such as ictal/interictal single-photon emission computerized tomography (SPECT) imaging and structural magnetic resonance imaging are common practices for the localization of epileptic foci and have been studied in several kinds of researches. In this article, we review the most recent research on EEG-based localization of seizure foci and discuss various methods, their advantages, limitations, and challenges with a focus on model-based data processing and machine learning algorithms. In addition, we survey whether combined analysis of EEG monitoring and neuroimaging techniques, which is known as multimodal brain data fusion, can potentially increase the precision of the seizure foci localization. To this end, we further review and summarize the key parameters and challenges of processing, fusion, and analysis of multiple source data, in the framework of model-based signal processing, for the development of a multimodal brain data analyzing system. This article has the potential to be used as a valuable resource for neuroscience researchers for the development of EEG-based rehabilitation systems based on multimodal data analysis related to focal epilepsy.

We investigated perceived invalidating environment during childhood and stress-coping strategies in patients with; functional dissociative seizures (FDS, n=26), drug-resistant epilepsy patients with no psychiatric comorbidity (DREnc, n=23), and drug-resistant epilepsy patients with psychiatric comorbidity (DREpc, n=34).

We performed a cross-sectional study. Patients underwent Video Electroencephalography to confirm the diagnosis and completed a psychiatric assessment supported by clinical instruments. Invalidating environment and stress coping were studied through the ICES and CAE questionaries, respectively. A series of multinomial logistic regression analyses were performed with the explored variables.

The maternal negative response model predicted a higher probability of FDS condition. A chaotic family type increased the likelihood of DREpc instead of FDS. DREpc and FDS patients displayed many different behaviors to cope with stress other than trying to solve the problem, the most used strategy in the DREnc group. Parental invalidation was higher in DREpc than in FDS.

Our results deepen the data provided by previous studies indicating that multiple variables of biosocial origin have significant effects on these groups of patients. The presence of an invalidating environment may predict FDS but also the presence of psychiatric disorders among DRE. Psychotherapeutic strategies to enhance these variables might be necessary for this population.

Sulfur dioxide (SO2) is one of the most important gaseous air pollutants and the chemical index of sulfur oxides (SOx). SO2 is one of the six criteria pollutants in the air quality index (AQI). SO2 can be emitted by natural and anthropogenic sources. Although efforts have been made to reduce sulfur dioxide emissions worldwide, this pollutant and its adverse effects remain a major concern, especially in developing countries. The aim of this study was the investigated the effects of sulfur dioxide inhalation on human health. This narrative review was done based on the literature published from 2000 to 2022 through PubMed, Springer, Web of Science, Science Direct, and Google Scholar databases. In this study, was done screened first based on the abstract and Final assessment done based on the full text of the article. Finally, 38 articles were selected for inclusion in the study. The results of this study showed that sulfur dioxide has adverse health effects on the human respiratory, cardiovascular, and nervous systems and causes type 2 diabetes and non-accidental deaths. Although some evidence suggests that sulfur dioxide in given concentrations has no adverse health effect, its synergistic effects in combination with other air pollutants may be significant. Among the most important practical results of this study can be mentioned to increase the health awareness of the general public, help the politicians of the health sector in making decisions in the health field, creating awareness among polluting producing units and industries and efforts to reduce the emission of Sulfur dioxide.

Epilepsy is a global health and economic burden with major problems that have an impact on physical, psychological, and social activities. Quality of life (QoL) is often disturbed and can be influenced by many factors, like anti-seizure medication side effects, the sociocultural environment, and various disease-related factors. The aim of this systematic review and meta-analysis is to provide an overview of the most recent information available regarding the pooled prevalence of poor quality of life and associated factors among adult people with epilepsy in Ethiopia.

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) is an appropriate set of guidelines for reporting systematic reviews and meta-analyses. This systematic review and meta-analysis protocol was registered on the International Prospective Register of Systematic Reviews (PROSPERO) with CRD42024527914. To find publications for the systematic review and meta-analysis, we used both manual and electronic searches. The publications were searched by PubMed, MEDLINE, EMBASE, Cochrane Library, Scopus, and other grey publications were searched by Google Scholar. The Joanna Briggs Institute (JBI) for cross-sectional study quality assessment was employed to evaluate the methodological quality of the studies included in this review. The data was extracted in Microsoft Excel, and then it was exported into STATA 11.0 for analysis. A funnel plot and an objective examination of Egger's regression test were used to check for publication bias.

We have included 7 studies conducted in Ethiopia with 2123 study participants, of whom 1163 (54.78%) were male individuals, and 1196 (56.34%) of the participants were living without marriage (either single, divorced, or widowed). The pooled prevalence of poor quality of life among people with epilepsy in Ethiopia is 45.07 (95% CI: 39.73-50.42%). Further, in subgroup analysis regarding the assessment tool of poor quality of life of people with epilepsy, QOLIE-31 accounted for 50.05% (95%CI: 46.65-53.45) and WHO QOL BREF accounted for 39.72% (95%CI: 27.67-51.78). Among the associated factors, being unable to read and write, anxiey and depression were significantly linked to the quality of life of people with epilepsy.

This review found that there was a high pooled prevalence of poor quality of life related to people with epilepsy in Ethiopia. This study may provide further information to concerned bodies that do early screening and manage the quality of life of individuals with epilepsy. Also, screening and intervention for anxiety and depression problems should be considered in regular epilepsy care management.

Approximately 50 million people worldwide have epilepsy, with many not achieving seizure freedom. Organ-on-chip technology, which mimics organ-level physiology, could revolutionize drug development for epilepsy by replacing animal models in preclinical studies. The authors' goal is to determine if customized micro-physiological systems can lead to tailored drug treatments for epileptic patients.

A comprehensive literature search was conducted utilizing various databases, including PubMed, Ebscohost, Medline, and the National Library of Medicine, using a predetermined search strategy. The authors focused on articles that addressed the role of personalized micro-physiological systems in individual drug responses and articles that discussed different types of epilepsy, diagnosis, and current treatment options. Additionally, articles that explored the components and design considerations of micro-physiological systems were reviewed to identify challenges and opportunities in drug development for challenging epilepsy cases.

The micro-physiological system offers a more accurate and cost-effective alternative to traditional models for assessing drug effects, toxicities, and disease mechanisms. Nevertheless, designing patient-specific models presents critical considerations, including the integration of analytical biosensors and patient-derived cells, while addressing regulatory, material, and biological complexities. Material selection, standardization, integration of vascular systems, cost efficiency, real-time monitoring, and ethical considerations are also crucial to the successful use of this technology in drug development.

The future of organ-on-chip technology holds great promise, with the potential to integrate artificial intelligence and machine learning for personalized treatment of epileptic patients.

Epilepsy is a neurological disease characterized by spontaneous and recurrent seizures. Epileptic seizures can be initiated and facilitated by inflammatory mechanisms. As the dysregulation of the immune system would be involved in epileptogenesis, it is suggested that anti-inflammatory medications could impact epileptic seizures. These medications could potentially have a side effect by altering the structure and composition of the intestinal microbiota. These changes can disrupt microbial homeostasis, leading to dysbiosis and potentially exacerbating intestinal inflammation. We hypothesize that prednisolone may affect the development of epileptic seizures, potentially influencing the diversity of the intestinal microbiota and the regulation of pro-inflammatory cytokines in intestinal tissue. This study aimed to evaluate the effects of prednisolone treatment on epileptic seizures and investigate the effect of this drug on the bacterial diversity of the intestinal microbiota and markers of inflammatory processes in intestinal tissue. We used Male Wistar rat littermates (n = 31, 90-day-old) divided into four groups: positive control treated with 2 mg/kg of diazepam (n = 6), negative control treated with 0.9 g% sodium chloride (n = 6), and the remaining two groups were subjected to treatment with prednisolone, with one receiving 1 mg/kg (n = 9) and the other 5 mg/kg (n = 10). All administrations were performed intraperitoneally (i.p.) over 14 days. To induce the chronic model of epileptic seizures, we administered pentylenetetrazole (PTZ) 25 mg/kg i.p. on alternate days. Seizure latency (n = 6 - 10) and TNF-α and IL-1β concentrations from intestinal samples were measured by ELISA (n = 6 per group), and intestinal microbiota was evaluated with intergenic ribosomal RNA (rRNA) spacer (RISA) analysis (n = 6 per group). The prednisolone treatment demonstrated an increase in the latency time of epileptic seizures and TNF-α and IL-1β concentrations compared to controls. There was no statistically significant difference in intestinal microbiota diversity between the different treatments. However, there was a strong positive correlation between microbial diversity and TNF-α and IL-1β concentrations. The administration of prednisolone yields comparable results to diazepam on increasing latency between seizures, exhibiting promise for its use in clinical studies. Although there were no changes in intestinal microbial diversity, the increase in the TNF-α and IL-1β cytokines in intestinal tissue may be linked to immune system signaling pathways involving the intestinal microbiota. Additional research is necessary to unravel the intricacies of these pathways and to understand their implications for clinical practice.

Epilepsy is a prevalent neurological disorder that affects a significant number of individuals globally. This condition is associated with a high occurrence of psychiatric comorbidities, which can significantly affect the quality of life of individuals affected. The aim of this study was to investigate the association between antiseizure therapies and the likelihood of psychiatric comorbidities in individuals with epilepsy.

Data for this study was gathered from the Neurology referral center in Islamabad, Pakistan. A standardized questionnaire was utilized to gather data from 120 individuals diagnosed with epilepsy. The survey consisted of inquiries regarding the management of seizures, the utilization of anti-seizure medications, and the presence of psychiatric comorbidities. The data was analyzed using the Statistical Package for the Social Sciences (SPSS).

The findings indicated that individuals who were using multiple antiseizure medications had a notably higher likelihood of having psychiatric comorbidities in comparison to those who were on mono therapy (p = 0.010). suggests that patients with unsuccessful seizure control are more probable to have psychiatric comorbidities as compared to those with good seizure control (p = 0.029).

To conclude poor seizure control and poly therapy are associated with increased risk of psychiatric comorbidities.

Parvalbumin expressing (PV+) GABAergic interneurons are fast spiking neurons that provide powerful but relatively short-lived inhibition to principal excitatory cells in the brain. They play a vital role in feedforward and feedback synaptic inhibition, preventing run away excitation in neural networks. Hence, their dysfunction can lead to hyperexcitability and increased susceptibility to seizures. PV+ interneurons are also key players in generating gamma oscillations, which are synchronized neural oscillations associated with various cognitive functions. PV+ interneuron are particularly vulnerable to aging and their degeneration has been associated with cognitive decline and memory impairment in dementia and Alzheimer's disease (AD). Overall, dysfunction of PV+ interneurons disrupts the normal excitatory/inhibitory balance within specific neurocircuits in the brain and thus has been linked to a wide range of neurodevelopmental and neuropsychiatric disorders. This review focuses on the role of dysfunctional PV+ inhibitory interneurons in the generation of epileptic seizures and cognitive impairment and their potential as targets in the design of future therapeutic strategies to treat these disorders. Recent research using cutting-edge optogenetic and chemogenetic technologies has demonstrated that they can be selectively manipulated to control seizures and restore the balance of neural activity in the brains of animal models. This suggests that PV+ interneurons could be important targets in developing future treatments for patients with epilepsy and comorbid disorders, such as AD, where seizures and cognitive decline are directly linked to specific PV+ interneuron deficits.

Epilepsy is a life-threatening neurological condition. Manual detection of epileptic seizures (ES) is laborious and burdensome. Machine learning techniques applied to electroencephalography (EEG) signals are widely used for automatic seizure detection. Some key factors are worth considering for the real-world applicability of such systems: (i) continuous EEG data typically has a higher class imbalance; (ii) higher variability across subjects is present in physiological signals such as EEG; and (iii) seizure event detection is more practical than random segment detection. Most prior studies failed to address these crucial factors altogether for seizure detection. In this study, we intend to investigate a generalized cross-subject seizure event detection system using the continuous EEG signals from the CHB-MIT dataset that considers all these overlooked aspects. A 5-second non-overlapping window is used to extract 92 features from 22 EEG channels; however, the most significant 32 features from each channel are used in experimentation. Seizure classification is done using a Random Forest (RF) classifier for segment detection, followed by a post-processing method used for event detection. Adopting all the above-mentioned essential aspects, the proposed event detection system achieved 72.63% and 75.34% sensitivity for subject-wise 5-fold and leave-one-out analyses, respectively. This study presents the real-world scenario for ES event detectors and furthers the understanding of such detection systems.

Epilepsy, a prevalent neurodegenerative disorder, profoundly impacts the physical and mental well-being of millions globally. Historically, antiseizure drugs (ASDs) have been the primary treatment modality. However, despite the introduction of novel ASDs in recent decades, a significant proportion of patients still experiences uncontrolled seizures.

The rapid advancement of nanomedicine in recent years has enabled precise targeting of the brain, thereby enhancing therapeutic efficacy for brain diseases, including epilepsy.

Nanomedicine holds immense promise in epilepsy treatment, including but not limited to enhancing drug solubility and stability, improving drug across blood-brain barrier, overcoming resistance, and reducing side effects, potentially revolutionizing clinical management. This paper provides a comprehensive overview of current epilepsy treatment modalities and highlights recent advancements in nanomedicine-based drug delivery systems for epilepsy control. We discuss the diverse strategies used in developing novel nanotherapies, their mechanisms of action, and the potential advantages they offer compared to traditional treatment methods.

Mobile health app-based interventions are increasingly being developed to support chronic disease management, particularly for epilepsy patients. These interventions focus on managing stress, monitoring drug side effects, providing education, and promoting adherence to medication regimens. Therefore, this scoping review aims to assess how mobile health applications improve epilepsy patients' knowledge and seizure control, and to identify the features of these apps that are frequently used and have proven to be beneficial.

This scoping review was conducted using scientific databases such as ScienceDirect, PubMed, and Google Scholar, adhering to the Joanna Briggs Institute guidelines. The review framework consisted of five steps: identifying research questions, finding relevant articles, selecting articles, presenting data, and compiling the results. The literature search included all original articles published in English from 2013 to 2023.

Among six articles that discussed mobile applications for epilepsy patients, all featured similar functionalities, including education on epilepsy management and seizure monitoring. Four of the articles highlighted behavioral interventions, such as reminder systems, designed to improve medication adherence. The remaining two articles focused on a side-effect reporting system that enabled doctors or health workers to evaluate and regularly monitor adverse effects.

This scoping review reveals that mobile health applications employing a combination of educational and behavioral interventions for epilepsy patients significantly improve knowledge about patient self-management and medication adherence. These interventions can prevent seizures, increase awareness, enable better activity planning, improve safety, and reduce the frequency of seizures and side effects of antiepileptic drugs.

One of the epileptic patients' challenges is to detect the time of seizures and the possibility of predicting. This research aims to provide an algorithm based on deep learning to detect and predict the time of seizure from one to two minutes before its occurrence. The proposed Convolutional Neural Network (CNN) can detect and predict the occurrence of focal epilepsy seizures through single-lead-ECG signal processing instead of using EEG signals. The structure of the proposed CNN for seizure detection and prediction is the same. Considering the requirements of a wearable system, after a few light pre-processing steps, the ECG signal can be used as input to the neural network without any manual feature extraction step. The desired neural network learns purposeful features according to the labelled ECG signals and then performs the classification of these signals. Training of 39-layer CNN for seizure detection and prediction has been done separately. The proposed method can detect seizures with an accuracy of 98.84% and predict them with an accuracy of 94.29%. With this approach, the ECG signal can be a promising indicator for the construction of portable systems for monitoring the status of epileptic patients.

Epilepsy is a prevalent and severe neurological disorder and generally requires prolonged electrode implantation and tether brain stimulation in refractory cases. However, implants may cause potential chronic immune inflammation and permanent tissue damage due to material property mismatches with soft brain tissue. Here, we demonstrated a nanomaterial-enabled near-infrared (NIR) neuromodulation approach to provide nongenetic and nonimplantable therapeutic benefits in epilepsy mouse models. Our study showed that crystal-exfoliated photothermal black phosphorus (BP) flakes could enhance neural activity by altering the membrane capacitive currents in hippocampus neurons through NIR photothermal neuromodulation. Optical stimulation facilitated by BP flakes in hippocampal slices evoked action potentials with a high spatiotemporal resolution. Furthermore, BP flake-enabled NIR neuromodulation of hippocampus neural circuits can suppress epileptic signals in epilepsy model mice with minimal invasiveness and high biocompatibility. Consequently, nanomaterial-enabled NIR neuromodulation may open up opportunities for nonimplantable optical therapy of epilepsy in nontransgenic organisms.

Drug-resistant epilepsy (DRE) is a refractory neurological disorder. There is ample evidence that suggest that γ-aminobutyric acid-a (GABAA) receptors could be one of the mechanisms responsible for the development of drug resistance in epilepsy. It is also known that the cAMP response element binding protein (CREB) plays a possible key role in the transcriptional regulation of GABAA.

This study explores the role of CREB in the development of DRE and the effect of CREB on GABA-related receptors in DRE.

The CREB expression was increased or decreased in the hippocampus of normal rats by lentiviral transfection, who then underwent the lithium-pilocarpine-induced epilepsy model. Phenobarbital (PB) sodium and carbamazepine (CBZ) were used to select a drug-resistant epileptic model. The expression levels of GABAA receptor α1, β2, and γ2 subunits and CREB protein were measured in the rat hippocampus by western blot and fluorescent quantitative PCR.

The frequency and duration of seizures increased in the overexpression group compared to that in the control group. In addition, the severity, frequency, and duration of seizures decreased in the group with decreased expression. The hippocampus analysis of the expression levels of the CREB protein and CREB mRNA yielded similar findings. Altering the CREB protein expression in the rat hippocampus could negatively regulate the expression and transcript levels of GABAA receptors α1, β2, and γ2, suggesting that CREB may serve as a potential target for the development of treatment protocols and drugs for epilepsy.

Our study shows that enhanced CREB expression promotes the development of DRE and negatively regulates GABAA receptor levels and that the inhibition of CREB expression may reduce the incidence of DRE.

Regular physical activity may promote beneficial neuroplasticity, e.g., increased hippocampus volume. However, it is unclear whether self-reported physical exercise in leisure (PEL) levels are associated with the brain structure features demonstrated by exercise interventions. This pilot study investigated the relationship between PEL, mood, cognition, and neuromorphometry in patients with idiopathic generalized epilepsy (IGEs) compared to healthy controls (HCs). Seventeen IGEs and 19 age- and sex-matched HCs underwent magnetic resonance imaging (MRI) at 3T. The Baecke Questionnaire of Habitual Physical Activity, Profile of Mood States, and Montreal Cognitive Assessment (MoCA) assessed PEL, mood, and cognition, respectively. Structural MRI data were analyzed by voxel- and surface-based morphometry. IGEs had significantly lower PEL (p < 0.001), poorer mood (p = 0.029), and lower MoCA scores (p = 0.027) than HCs. These group differences were associated with reduced volume, decreased gyrification, and altered surface topology (IGEs < HCs) in frontal, temporal and cerebellar regions involved in executive function, memory retrieval, and emotional regulation, respectively. These preliminary results support the notion that increased PEL may promote neuroplasticity in IGEs, thus emphasizing the role of physical activity in promoting brain health in people with epilepsy.