Epilepsy Overview and Revised Classification of Seizures and Epilepsies

Unraveling the nutritional challenges in epilepsy: Risks, deficiencies, and management strategies: A systematic review

BACKGROUND

Malnutrition and epilepsy share a complex bidirectional relationship, with malnutrition serving as a potential risk factor for epilepsy development, while epilepsy, in turn, often exerts profound effects on nutritional status. Nutritional interventions have emerged as a critical adjunctive approach in epilepsy management.

AIM

To explore the multifaceted associations between malnutrition and epilepsy, structured into three primary sections: (1) Elucidating the impact of malnutrition as a risk factor for epilepsy onset; (2) Examining the reciprocal influence of epilepsy on nutritional status, and (3) Evaluating diverse nutritional interventions in the management of epilepsy.

METHODS

A systematic search was conducted across PubMed, Scopus, and Web of Science databases utilizing defined keywords related to malnutrition, epilepsy, and nutritional interventions. Inclusion criteria encompassed various study types, including clinical trials, animal models, cohort studies, case reports, meta-analyses, systematic reviews, guidelines, editorials, and review articles. Four hundred sixteen pertinent references were identified, with 198 review articles, 153 research studies, 21 case reports, 24 meta-analyses, 14 systematic reviews, 4 guidelines, and 2 editorials meeting the predefined criteria.

RESULTS

The review revealed the intricate interplay between malnutrition and epilepsy, highlighting malnutrition as a potential risk factor in epilepsy development and elucidating how epilepsy often leads to nutritional deficiencies. Findings underscored the importance of nutritional interventions in managing epilepsy, showing their impact on seizure frequency, neuronal function, and overall brain health.

CONCLUSION

This systematic review emphasizes the bidirectional relationship between malnutrition and epilepsy while emphasizing the critical role of nutritional management in epilepsy treatment. The multifaceted insights underscore the need for a holistic approach to addressing nutritional aspects alongside conventional epilepsy management strategies.

PBPK modelling for the evaluation of drug-drug interaction between meropenem and valproic acid

AIMS

The present study aimed to quantitatively investigate the potential drug-drug interaction (DDI) mechanism between meropenem (MEPM) and valproic acid (VPA).

METHODS

In the present study, we firstly developed a physiologically based pharmacokinetic (PBPK) model of MEPM and VPA. The verified PBPK model was then used to quantitatively investigate the potential DDI between MEPM and VPA. The effect of genetic polymorphisms of acylpeptide hydrolase (APEH) on DDI was also evaluated.

RESULTS

In our simulation, the plasma concentration of hydrolysate of VPAG decreased to 63% when combined with MEPM. Total plasma concentration of VPA before carbapenem use was 53.61 mg/L, whereas it was 45.42 mg/L during carbapenem use. The inhibition of hydrolysis of VPAG by MEPM alone could not result in a rapid and substantial decrease in the plasma concentration of VPA. Parameter sensitivity analysis showed that the changes of absorption played an important role in the maximum plasma concentration (Cmax) of VPA, whereas area under the plasma concentration-time profile (AUC) was more susceptible to elimination changes. In addition, a decrease in APEH activity had little impact on the plasma pharmacokinetics of VPA.

CONCLUSIONS

The DDI between MEPM and VPA might be a comprehensive result of multiple factors. On the basis of our simulation, interval medication of MEPM injection and VPA immediate release tablet at 4-6 h timed interval was recommended, or intravenous administration of VPA solution was preferred when combination regimen was necessary in a clinical setting.

Hypocalcemia-induced seizures in a peritoneal dialysis (PD) patient: A case report

Key Clinical Message

A thorough evaluation is necessary for seizures caused by hypocalcemia, both during the patient's presentation and following their recovery from the postictal seizure episode. This is because the underlying cause of hypocalcemia must be ruled out in order to ensure the best possible clinical outcome from calcium and vitamin D therapy.

Abstract

Patients with multiple systemic issues, including neurological involvement and seizure development, are not uncommon among nephrologists. Both the central and peripheral neural systems can be impacted by kidney disease. The main symptoms are myopathy, cranial or peripheral neuropathy, cognitive impairment, and seizures. A 22-year-old female with an unusual medical history who had been known to have end-stage kidney disease (ESKD) for a year and regularly had CAPD (continuous ambulatory peritoneal dialysis) suffered from two episodes of tonic-colonic seizures 2 weeks apart. On physical examination, symptoms of tongue biting, decreased vision in the left eye, and mild bilateral pulmonary air entry were notable. Upon examination, there was evidence of severe hypocalcemia, hyponatremia, a high renal profile (urea and creatinine), anemia, and a severe vitamin D deficiency. Her peritoneal dialysis (PD) prescription was reviewed, her seizures ceased, and she was released from the hospital after the hypocalcemia was treated with intravenous calcium and high doses of vitamin D. The issue of hypocalcemic seizures should be carefully evaluated both at the presentation and after the patient recovers from the postictal stage. By following this, seizure episodes can be prevented with good success if patients strictly adhere to the medication for which they are responsible.

Longitudinal adaptive behavioral outcomes in Ogden syndrome by seizure status and therapeutic intervention

Ogden syndrome, also known as NAA10-related neurodevelopmental syndrome, is a rare genetic condition associated with pathogenic variants in the NAA10 N-terminal acetylation family of proteins. The condition was initially described in 2011 and is characterized by a range of neurologic symptoms, including intellectual disability and seizures, as well as developmental delays, psychiatric symptoms, congenital heart abnormalities, hypotonia, and others. Previously published articles have described the etiology and phenotype of Ogden syndrome, mostly with retrospective analyses; herein, we report prospective data concerning its progress over time. The current study involves a total of 58 distinct participants; of these, 43 caregivers were interviewed using the Vineland-3 and answered a survey regarding therapy and other questions, 10 of whom completed the Vineland-3 but did not answer the survey, and 5 participants who answered the survey but have not yet performed the Vineland-3 due to language constraints. The average age at the time of the most recent assessment was 12.4 years, with individuals ranging in age from 11 months to 40.2 years. Using Vineland-3 scores, we show decline in cognitive function over time in individuals with Ogden syndrome (n = 53). Sub-domain analysis found the decline to be present across all modalities. In addition, we describe the nature of seizures in this condition in greater detail, as well as investigate how already-available non-pharmaceutical therapies impact individuals with NAA10-related neurodevelopmental syndrome. Additional investigation between seizure and non-seizure groups showed no significant difference in adaptive behavior outcomes. A therapy investigation showed speech therapy to be the most commonly used therapy by individuals with NAA10-related neurodevelopmental syndrome, followed by occupational and physical therapy, with more severely affected individuals receiving more types of therapy than their less-severe counterparts. Early intervention analysis was only significantly effective for speech therapy, with analyses of all other therapies being non-significant. Our study portrays the decline in cognitive function over time of individuals within our cohort, independent of seizure status, and therapies being received, and highlights the urgent need for the development of effective treatments for Ogden syndrome.

The National Institutes of Health COVID-19 Neuro Databank/Biobank: Creation and Evolution

INTRODUCTION

Diverse neurological conditions are reported associated with the SARS-CoV-2 virus; neurological symptoms are the most common conditions to persist after the resolution of acute infection, affecting 20% of patients 6 months after acute illness. The COVID-19 Neuro Databank (NeuroCOVID) was created to overcome the limitations of siloed small local cohorts to collect detailed, curated, and harmonized de-identified data from a large diverse cohort of adults with new or worsened neurological conditions associated with COVID-19 illness, as a scientific resource.

METHODS

A Steering Committee including US and international experts meets quarterly to provide guidance. Initial study sites were recruited to include a wide US geographic distribution; academic and non-academic sites; urban and non-urban locations; and patients of different ages, disease severity, and comorbidities seen by a variety of clinical specialists. The NeuroCOVID REDCap database was developed, incorporating input from professional guidelines, existing common data elements, and subject matter experts. A cohort of eligible adults is identified at each site; inclusion criteria are: a new or worsened neurological condition associated with a COVID-19 infection confirmed by testing. De-identified data are abstracted from patients' medical records, using standardized common data elements and five case report forms. The database was carefully enhanced in response to feedback from site investigators and evolving scientific interest in post-acute conditions and their timing. Additional US and international sites were added, focusing on diversity and populations not already described in published literature. By early 2024, NeuroCOVID included over 2,700 patient records, including data from 16 US and 5 international sites. Data are being shared with the scientific community in compliance with NIH requirements. The program has been invited to share case report forms with the National Library of Medicine as an ongoing resource for the scientific community.

CONCLUSION

The NeuroCOVID database is a unique and valuable source of comprehensive de-identified data on a wide variety of neurological conditions associated with COVID-19 illness, including a diverse patient population. Initiated early in the pandemic, data collection has been responsive to evolving scientific interests. NeuroCOVID will continue to contribute to scientific efforts to characterize and treat this challenging illness and its consequences.

Frailty as a comprehensive health measure beyond seizure control in patients with epilepsy: A cross-sectional study

OBJECTIVE

Due to the high clinical heterogeneity of epilepsy, there is a critical need for novel metrics aimed at capturing its biological and phenotypic complexity. Frailty is increasingly recognized in various medical disciplines as a useful construct to understand differences in susceptibility to adverse outcomes. Here, we develop a frailty index (FI) for patients with epilepsy (PwE) and explore its association with demographic and clinical features.

METHODS

In this cross-sectional study, we consecutively enrolled 153 PwE from an outpatient epilepsy clinic. Participants were assessed for various health deficits to calculate the FI. Associations between FI and demographic/clinical features, antiseizure medications (ASMs), and patient-reported outcomes were analyzed using general linear models and Spearman correlation.

RESULTS

The median age at the time of study visit was 47 years (interquartile range = 33-60), and 89 (58.2%) patients were females. Multiple linear regression revealed that the developed 33-item FI showed an independent association with age, female sex, higher body mass index, family history of epilepsy, intellectual disability, and the number of ASMs used. A robust analysis of covariance showed higher FI levels in patients using cytochrome P450 3A4-inducer ASMs. We found a moderate positive correlation between FI and psychological distress, lower quality of life, and physical frailty, measured by the Hospital Anxiety and Depression Scale, Quality of Life in Epilepsy Inventory-10, and handgrip strength, respectively. Finally, a weak association was observed between higher FI scores and an increased number of epileptic falls.

SIGNIFICANCE

This study highlights the significance of frailty as a comprehensive health measure in epilepsy. It suggests that frailty in this specific population is not only a manifestation of aging but is inherently linked to epilepsy and treatment-related factors. Future research is warranted to validate and refine the FI in diverse epilepsy populations and investigate its impact on specific adverse outcomes in longitudinal studies.

Pre-treatment risk predictors of valproic acid-induced dyslipidemia in pediatric patients with epilepsy

Background: Valproic acid (VPA) stands as one of the most frequently prescribed medications in children with newly diagnosed epilepsy. Despite its infrequent adverse effects within therapeutic range, prolonged VPA usage may result in metabolic disturbances including insulin resistance and dyslipidemia. These metabolic dysregulations in childhood are notably linked to heightened cardiovascular risk in adulthood. Therefore, identification and effective management of dyslipidemia in children hold paramount significance. Methods: In this retrospective cohort study, we explored the potential associations between physiological factors, medication situation, biochemical parameters before the first dose of VPA (baseline) and VPA-induced dyslipidemia (VID) in pediatric patients. Binary logistic regression was utilized to construct a predictive model for blood lipid disorders, aiming to identify independent pre-treatment risk factors. Additionally, The Receiver Operating Characteristic (ROC) curve was used to evaluate the performance of the model. Results: Through binary logistic regression analysis, we identified for the first time that direct bilirubin (DBIL) (odds ratios (OR) = 0.511, p = 0.01), duration of medication (OR = 0.357, p = 0.009), serum albumin (ALB) (OR = 0.913, p = 0.043), BMI (OR = 1.140, p = 0.045), and aspartate aminotransferase (AST) (OR = 1.038, p = 0.026) at baseline were independent risk factors for VID in pediatric patients with epilepsy. Notably, the predictive ability of DBIL (AUC = 0.690, p < 0.0001) surpassed that of other individual factors. Furthermore, when combined into a predictive model, incorporating all five risk factors, the predictive capacity significantly increased (AUC = 0.777, p < 0.0001), enabling the forecast of 77.7% of dyslipidemia events. Conclusion: DBIL emerges as the most potent predictor, and in conjunction with the other four factors, can effectively forecast VID in pediatric patients with epilepsy. This insight can guide the formulation of individualized strategies for the clinical administration of VPA in children.

The effect of valproate on the amino acids, monoamines, and kynurenic acid concentrations in brain structures involved in epileptogenesis in the pentylenetetrazol-kindled rats

BACKGROUND

The study aimed to assess the influence of a single valproate (VPA) administration on inhibitory and excitatory neurotransmitter concentrations in the brain structures involved in epileptogenesis in pentylenetetrazol (PTZ)-kindled rats.

METHODS

Adult, male Wistar rats were kindled by repeated intraperitoneal (ip) injections of PTZ at a subconvulsive dose (30 mg/kg, three times a week). Due to the different times required to kindle the rats (18-22 injections of PTZ), a booster dose of PTZ was administrated 7 days after the last rats were kindled. Then rats were divided into two groups: acute administration of VPA (400 mg/kg) or saline given ip. The concentration of amino acids, kynurenic acid (KYNA), monoamines, and their metabolites in the prefrontal cortex, hippocampus, amygdala, and striatum was assessed by high-pressure liquid chromatography (HPLC).

RESULTS

It was found that a single administration of VPA increased the gamma-aminobutyric acid (GABA), tryptophan (TRP), 5-hydroxyindoleacetic acid (5-HIAA), and KYNA concentrations and decreased aspartate (ASP) levels in PTZ-kindled rats in the prefrontal cortex, hippocampus, amygdala and striatum.

CONCLUSIONS

Our results indicate that a single administration of VPA in the PTZ-kindled rats restored proper balance between excitatory (decreasing the level of ASP) and inhibitory neurotransmission (increased concentration GABA, KYNA) and affecting serotoninergic neurotransmission in the prefrontal cortex, hippocampus, amygdala, and striatum.

Longitudinal Adaptive Behavioral Outcomes in Ogden Syndrome by Seizure Status and Therapeutic Intervention

Ogden syndrome, also known as NAA10-related neurodevelopmental syndrome, is a rare genetic condition associated with pathogenic variants in the NAA10 N-terminal acetylation family of proteins. The condition was initially described in 2011, and is characterized by a range of neurologic symptoms, including intellectual disability and seizures, as well as developmental delays, psychiatric symptoms, congenital heart abnormalities, hypotonia and others. Previously published articles have described the etiology and phenotype of Ogden syndrome, mostly with retrospective analyses; herein, we report prospective data concerning its progress over time. Additionally, we describe the nature of seizures in this condition in greater detail, as well as investigate how already-available non-pharmaceutical therapies impact individuals with NAA10-related neurodevelopmental syndrome. Using Vineland-3 scores, we show decline in cognitive function over time in individuals with Ogden syndrome. Sub-domain analysis found the decline to be present across all modalities. Additional investigation between seizure and non-seizure groups showed no significant difference in adaptive behavior outcomes. Therapy investigation showed speech therapy to be the most commonly used therapy by individuals with NAA10-related neurodevelopmental syndrome, followed by occupational and physical therapy. with more severely affected individuals receiving more types of therapy than their less-severe counterparts. Early intervention analysis was only significantly effective for speech therapy, with analyses of all other therapies being non-significant. Our study portrays the decline in cognitive function over time of individuals within our cohort, independent of seizure status and therapies being received, and highlights the urgent need for the development of effective treatments for Ogden syndrome.

Silencing PKM2 Attenuates Brain Injury Induced by Status Epilepticus by Inhibiting the AKT/mTOR Pathway and the NLRP3 Inflammasome

PKM2 is a glycolytic pyruvate kinase isoenzyme, and its role in neurological diseases has been published. However, the role and mechanism of PKM2 in the process of status epilepticus have not been reported. The purpose of this study is to explore the role and mechanism of PKM2 in epilepsy. Quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting were used to explore the expression of PKM2 in cells. Enzyme-linked immunosorbent assay kits were used to evaluate the level of inflammatory factors. An epilepsy model was established by intraperitoneal injection of lithium chloride in rats. Various behavioural assays were conducted to explore the learning ability and cognitive level of rats. PKM2 expression was upregulated in Mg2+-induced hippocampal neurons. PKM2 inhibition ameliorated Mg2+-induced hippocampal neuronal inflammation and reduced neuronal apoptosis. In addition, PKM2 silencing inhibited the metabolic dysfunction of Mg2+-induced hippocampal neurons. Subsequent experiments showed that the Akt/mTOR pathway and NLRP3 inflammasome are involved in PKM2-mediated neuronal regulation. More importantly, PKM2 inhibition could alleviate status epilepticus in rats. PKM2 inhibition attenuates Mg2+-induced hippocampal neuronal inflammation, apoptosis and metabolic dysfunction and improves the cognitive ability of rats. Therefore, PKM2 may be an important target for epilepsy treatment.

Epilepsy and Issues Related to Reproductive Health

Sexual disorders are prevalent and vary in men and women with epilepsy (WWE). Infertility and reproductive abnormalities are twice as common in females with epilepsy. Antiepileptic medications and seizures can both have an impact on sexual health in people with epilepsy. Seizures can alter the release of pituitary and hypothalamic hormones, and some antiepileptic drugs (AEDs) can alter sex steroid hormones (gonadal steroids and gonad corticoids). Females with epilepsy are more susceptible to menstrual cycle irregularity and polycystic ovary syndrome. Females and males had lower reproductive rates, and the causes are likely psychological and physiological, with epilepsy and AEDs again playing a role. Sexual disorders are common in WWE and men with epilepsy and can be caused by psychological, physical, or social factors. Specialists must address the gender-based biology of epilepsy and the impact of AEDs on sexual well-being to offer the best treatment possible for patients with epilepsy, particularly women of sexual maturity.

The standardized extract of Centella asiatica L. Urb attenuates the convulsant effect induced by lithium/pilocarpine without affecting biochemical and haematological parameters in rats

BACKGROUND

Status epilepticus (SE) is a type of epileptic activity characterized by a failure of the inhibitory mechanisms that limit seizures, which are mainly regulated by the GABAergic system. This imbalance increases glutamatergic neurotransmission and consequently produces epileptic activity. It is also associated with oxidative stress due to an imbalance between reactive oxygen species (ROS) and antioxidant defences. Unfortunately, long-term treatment with anti-epileptic drugs (AEDs) may produce hepatotoxicity, nephrotoxicity, and haematological alterations. In this way, some secondary metabolites of plants have been used to ameliorate the deterioration of nervous system disorders through their antioxidant properties, in addition to their anticonvulsant effects. An example is Centella asiatica, a plant noted to have a reputed neuroprotective effect related to its antioxidant activity. However, similar to conventional drugs, natural molecules may produce side effects when consumed in high doses, which could occur with Centella asiatica. Therefore, we aimed to evaluate the effect of a standardized extract of Centella asiatica L. Urb with tested anticonvulsant activity on biochemical and haematological parameters in rats subjected to lithium/pilocarpine-induced seizures.

METHODS

Twenty-eight adult male Wistar rats were randomly divided into four groups (n = 7 each): vehicle (purified water), Centella asiatica (200 and 400 mg/kg), and carbamazepine (CBZ) (300 mg/kg) as a pharmacological control of anticonvulsant activity. Treatments were administered orally every 24 h for 35 consecutive days. On Day 36, SE was induced using the lithium/pilocarpine model (3 mEq/kg, i.p. and 30 mg/kg s.c., respectively), and the behavioural and biochemical effects were evaluated.

RESULTS

Centella asiatica 400 mg/kg increased the latency to the first generalized seizure and SE onset and significantly reduced the time to the first generalized seizure compared to values in the vehicle group. Biochemical parameters, i.e., haematic cytometry, blood chemistry, and liver function tests, showed no significant differences among the different treatments.

CONCLUSION

The dose of Centella asiatica that produces anticonvulsant activity in the lithium/pilocarpine model devoid of hepatotoxicity, nephrotoxicity, and alterations in haematological parameters suggests that the standardized extract of this plant could be of utility in the development of new safe therapies for the treatment of convulsions associated with epilepsy.

Factors influencing community pharmacists' knowledge about women's issues in epilepsy

BACKGROUND

Previous studies have highlighted instances where pharmacists lacked knowledge regarding women's health issues related to epilepsy.

OBJECTIVES

To assess UAE community pharmacists' knowledge, toward women's issues in epilepsy.

METHODS

a cross-sectional research method was employed. A team of seven pharmacy students in their final year visited a randomly selected sample of community pharmacies in the UAE and face-to-face interviews were conducted with the pharmacists using a structured questionnaire. The questionnaire includes two parts; Eight questions designed to elicit data about the demographics of the study participants and 12 questions eliciting insights into the participants' knowledge of women's issues in epilepsy.

RESULTS

A total of 412 community pharmacist were recruited in the study. The overall level of knowledge about women's issues in epilepsy was good and the average knowledge score was 81% with a 95% confidence interval (CI) [79.1, 82.7%]. The results of multivariate analysis showed higher knowledge scores in chain pharmacies (OR 1.37; 95% CI 1.12-1.67), Chief pharmacists (OR 1.44; 95% CI 1.01-2.06), Pharmacists in charge (OR 3.46; 95% CI 2.7-4.45), pharmacists with 1-5 Years of experience (OR 2.87; 95% CI 1.71-4.82), pharmacists with 6-10 Years (OR 2.63; 95% CI 1.58-4.38), pharmacists with >10 years (OR 3.13; 95% CI 2.03-4.83), graduation form regional universities (OR 1.37; 95% CI 1.12-1.67), graduation form international universities (OR 1.73; 95% CI 1.36-2.20) and receiving a training on epilepsy (OR 1.36; 95% CI 1.12-1.67).

CONCLUSION

While the findings reveal an overall promising level of knowledge among community pharmacists regarding the issues faced by women with epilepsy, pinpointing which clinical and demographic factors have the most significant impact on this knowledge would permit the implementation of tailored educational interventions. Workshops and modules targeting the issues faced by women with epilepsy would further raise the knowledge and competence among community pharmacists in this area, ensuring better pharmaceutical care for this population.

Ecstatic or Mystical Experience through Epilepsy

Ecstatic epilepsy is a rare form of focal epilepsy, so named because the seizures' first symptoms consist of an ecstatic/mystical experience, including feelings of increased self-awareness, mental clarity, and "unity with everything that exists," accompanied by a sense of bliss and physical well-being. In this perspective article, we first describe the phenomenology of ecstatic seizures, address their historical context, and describe the primary brain structure involved in the genesis of these peculiar epileptic seizures, the anterior insula. In the second part of the article, we move onto the possible neurocognitive underpinnings of ecstatic seizures. We first remind the reader of the insula's role in interoceptive processing and consciously experienced feelings, contextualized by the theory of predictive coding. This leads us to hypothesize that temporary disruptions to activity in the anterior insula could interrupt the generation of interoceptive prediction errors, and cause one to experience the absence of uncertainty, and thereby, a sense of bliss. The absence of interoceptive prediction errors would in fact mimic perfect prediction of the body's physiological state. This sudden clarity of bodily perception could explain the ecstatic quality of the experience, as the interoceptive system forms the basis for unified conscious experience. Our alternative hypothesis is that the anterior insula plays an overarching role in the processing of surprise and that the dysfunction caused by the epileptic discharge could interrupt any surprise exceeding expectations, resulting in a sense of complete control and oneness with the environment.

The Application of Deep Learning to Electroencephalograms, Magnetic Resonance Imaging, and Implants for the Detection of Epileptic Seizures: A Narrative Review

Epilepsy is a neurological disorder characterized by recurrent seizures affecting millions worldwide. Medically intractable seizures in epilepsy patients are not only detrimental to the quality of life but also pose a significant threat to their safety. Outcomes of epilepsy therapy can be improved by early detection and intervention during the interictal window period. Electroencephalography is the primary diagnostic tool for epilepsy, but accurate interpretation of seizure activity is challenging and highly time-consuming. Machine learning (ML) and deep learning (DL) algorithms enable us to analyze complex EEG data, which can not only help us diagnose but also locate epileptogenic zones and predict medical and surgical treatment outcomes. DL models such as convolutional neural networks (CNNs), inspired by visual processing, can be used to classify EEG activity. By applying preprocessing techniques, signal quality can be enhanced by denoising and artifact removal. DL can also be incorporated into the analysis of magnetic resonance imaging (MRI) data, which can help in the localization of epileptogenic zones in the brain. Proper detection of these zones can help in good neurosurgical outcomes. Recent advancements in DL have facilitated the implementation of these systems in neural implants and wearable devices, allowing for real-time seizure detection. This has the potential to transform the management of drug-refractory epilepsy. This review explores the application of ML and DL techniques to Electroencephalograms (EEGs), MRI, and wearable devices for epileptic seizure detection. This review briefly explains the fundamentals of both artificial intelligence (AI) and DL, highlighting these systems' potential advantages and undeniable limitations.

Effects of rosiglitazone, an antidiabetic drug, on Kv3.1 channels

Rosiglitazone is a thiazolidinedione-class antidiabetic drug that reduces blood glucose and glycated hemoglobin levels. We here investigated the interaction of rosiglitazone with Kv3.1 expressed in Chinese hamster ovary cells using the whole-cell patch-clamp technique. Rosiglitazone rapidly and reversibly inhibited Kv3.1 currents in a concentration-dependent manner (IC₅₀ = 29.8 μM) and accelerated the decay of Kv3.1 currents without modifying the activation kinetics. The rosiglitazone-mediated inhibition of Kv3.1 channels increased steeply in a sigmoidal pattern over the voltage range of -20 to +30 mV, whereas it was voltage-independent in the voltage range above +30 mV, where the channels were fully activated. The deactivation of Kv3.1 current, measured along with tail currents, was also slowed by the drug. In addition, the steady-state inactivation curve of Kv3.1 by rosiglitazone shifts to a negative potential without significant change in the slope value. All the results with the use dependence of the rosiglitazone-mediated blockade suggest that rosiglitazone acts on Kv3.1 channels as an open channel blocker.

An aqueous extract of Syzygium cumini protects against kainate-induced status epilepticus and amnesia: evidence for antioxidant and anti-inflammatory intervention

Temporal lobe epilepsy is the most common drug-resistant epilepsy. To cure epilepsy, drugs must target the mechanisms at the origin of seizures. Thus, the present investigation aimed to evaluate the antiepileptic- and anti-amnesic-like effects of an aqueous extract of Syzygium cumini against kainate-induced status epilepticus in mice, and possible mechanisms of action. Mice were divided into 7 groups and treated as follows: normal group or kainate group received po distilled water (10 mL/kg), four test groups received Syzygium cumini (28.8, 72, 144, and 288 mg/kg, po), and the positive control group treated intraperitoneally (ip) with sodium valproate (300 mg/kg). An extra group of normal mice was treated with piracetam (200 mg/kg, po). Treatments were administered 60 min before the induction of status epilepticus with kainate (15 mg/kg, ip), and continued daily throughout behavioral testing. Twenty-four hours after the induction, T-maze and Morris water maze tasks were successively performed. The animals were then sacrificed and some markers of oxidative stress and neuroinflammation were estimated in the hippocampus. The extract significantly prevented status epilepticus and mortality. In the T-maze, the aqueous extract markedly increased the time spent and the number of entries in the discriminated arm. In the Morris water maze, the extract significantly increased the time spent in the target quadrant during the retention phase. Furthermore, the aqueous extract induced a significant reduction of oxidative stress and neuroinflammation. These results suggest that the aqueous extract of Syzygium cumini has antiepileptic- and anti-amnesic-like effects, likely mediated in part by antioxidant and anti-inflammatory activities.

Epilepsy Characteristics in Neurodevelopmental Disorders: Research from Patient Cohorts and Animal Models Focusing on Autism Spectrum Disorder

Epilepsy, a heterogeneous group of brain-related diseases, has continued to significantly burden society and families. Epilepsy comorbid with neurodevelopmental disorders (NDDs) is believed to occur due to multifaceted pathophysiological mechanisms involving disruptions in the excitation and inhibition (E/I) balance impeding widespread functional neuronal circuitry. Although the field has received much attention from the scientific community recently, the research has not yet translated into actionable therapeutics to completely cure epilepsy, particularly those comorbid with NDDs. In this review, we sought to elucidate the basic causes underlying epilepsy as well as those contributing to the association of epilepsy with NDDs. Comprehensive emphasis is put on some key neurodevelopmental genes implicated in epilepsy, such as MeCP2, SYNGAP1, FMR1, SHANK1-3 and TSC1, along with a few others, and the main electrophysiological and behavioral deficits are highlighted. For these genes, the progress made in developing appropriate and valid rodent models to accelerate basic research is also detailed. Further, we discuss the recent development in the therapeutic management of epilepsy and provide a briefing on the challenges and caveats in identifying and testing species-specific epilepsy models.

A Validation Study for SHE Score for Acute Subdural Hematoma in the Elderly

OBJECTIVE

The aim of this study was the verification of the Subdural Hematoma in the Elderly (SHE) score proposed by Alford et al. as a mortality predictor in patients older than 65 years with nontraumatic/minor trauma acute subdural hematoma (aSDH). Additionally, we evaluated further predictors associated with poor outcome.

METHODS

Patients were scored according to age (1 point is given if patients were older than 80 years), GCS by admission (1 point for GCS 5-12, 2 points for GCS 3-4), and SDH volume (1 point for volume 50 mL). The sum of points determines the SHE score. Multivariate logistic regression analysis was performed to identify additional independent risk factors associated with 30-day mortality.

RESULTS

We evaluated 131 patients with aSDH who were treated at our institution between 2008 and 2020. We observed the same 30-day mortality rates published by Alford et al.: SHE 0: 4.3% vs. 3.2%, p = 1.0; SHE 1: 12.2% vs. 13.1%, p = 1.0; SHE 2: 36.6% vs. 32.7%, p = 0.8; SHE 3: 97.1% vs. 95.7%, p = 1.0 and SHE 4: 100% vs. 100%, p = 1.0. Additionally, 18 patients who developed status epilepticus (SE) had a mortality of 100 percent regardless of the SHE score. The distribution of SE among the groups was: 1 for SHE 1, 6 for SHE 2, 9 for SHE 3, and 2 for SHE 4. The logistic regression showed the surgical evacuation to be the only significant risk factor for developing the seizure. All patients who developed SE underwent surgery (p = 0.0065). Furthermore, SHE 3 and 4 showed no difference regarding the outcome between surgical and conservative treatment.

CONCLUSIONS

SHE score is a reliable mortality predictor for minor trauma acute subdural hematoma in elderly patients. In addition, we identified status epilepticus as a strong life-expectancy-limiting factor in patients undergoing surgical evacuation.

The contribution of fenfluramine to the treatment of Dravet syndrome in Spain through Multi-Criteria Decision Analysis

INTRODUCTION

Dravet Syndrome (DS) is a severe, developmental epileptic encephalopathy (DEE) that begins in infancy and is characterized by pharmaco-resistant epilepsy and neurodevelopmental delay. Despite available antiseizure medications (ASMs), there is a need for new therapeutic options with greater efficacy in reducing seizure frequency and with adequate safety and tolerability profiles. Fenfluramine is a new ASM for the treatment of seizures associated with DS as add-on therapy to other ASMs for patients aged 2 years and older. Fenfluramine decreases seizure frequency, prolongs periods of seizure freedom potentially helping to reduce risk of Sudden Unexpected Death in Epilepsy (SUDEP) and improves patient cognitive abilities positively impacting on patients' Quality of Life (QoL). Reflective Multi-Criteria Decision Analysis (MCDA) methodology allows to determine what represents value in a given indication considering all relevant criteria for healthcare decision-making in a transparent and systematic manner from the perspective of relevant stakeholders. The aim of this study was to determine the relative value contribution of fenfluramine for the treatment of DS in Spain using MCDA.

METHOD

A literature review was performed to populate an adapted a MCDA framework for orphan-drug evaluation in Spain. A panel of ten Spanish experts, including neurologists, hospital pharmacists, patient representatives and decision-makers, scored four comparative evidence matrices. Results were analyzed and discussed in a group meeting through reflective MCDA discussion methodology.

RESULTS

Dravet syndrome is considered a severe, rare disease with significant unmet needs. Fenfluramine is perceived to have a higher efficacy profile than all available alternatives, with a better safety profile than stiripentol and topiramate and to provide improved QoL versus studied alternatives. Fenfluramine results in lower other medical costs in comparison with stiripentol and clobazam. Participants perceived that fenfluramine could lead to indirect costs savings compared to available alternatives due to its efficacy in controlling seizures. Overall, fenfluramine's therapeutic impact on patients with DS is considered high and supported by high-quality evidence.

CONCLUSIONS

Based on reflective MCDA, fenfluramine is considered to add greater benefit in terms of efficacy, safety and QoL when compared with available ASMs.

A Fusion-Based Technique With Hybrid Swarm Algorithm and Deep Learning for Biosignal Classification

The vital data about the electrical activities of the brain are carried by the electroencephalography (EEG) signals. The recordings of the electrical activity of brain neurons in a rhythmic and spontaneous manner from the scalp surface are measured by EEG. One of the most important aspects in the field of neuroscience and neural engineering is EEG signal analysis, as it aids significantly in dealing with the commercial applications as well. To uncover the highly useful information for neural classification activities, EEG studies incorporated with machine learning provide good results. In this study, a Fusion Hybrid Model (FHM) with Singular Value Decomposition (SVD) Based Estimation of Robust Parameters is proposed for efficient feature extraction of the biosignals and to understand the essential information it has for analyzing the brain functionality. The essential features in terms of parameter components are extracted using the developed hybrid model, and a specialized hybrid swarm technique called Hybrid Differential Particle Artificial Bee (HDPAB) algorithm is proposed for feature selection. To make the EEG more practical and to be used in a plethora of applications, the robust classification of these signals is necessary thereby relying less on the trained professionals. Therefore, the classification is done initially using the proposed Zero Inflated Poisson Mixture Regression Model (ZIPMRM) and then it is also classified with a deep learning methodology, and the results are compared with other standard machine learning techniques. This proposed flow of methodology is validated on a few standard Biosignal datasets, and finally, a good classification accuracy of 98.79% is obtained for epileptic dataset and 98.35% is obtained for schizophrenia dataset.

Blood-brain barrier: emerging trends on transport models and new-age strategies for therapeutics intervention against neurological disorders

The integrity of the blood–brain barrier (BBB) is essential for normal central nervous system (CNS) functioning. Considering the significance of BBB in maintaining homeostasis and the neural environment, we aim to provide an overview of significant aspects of BBB. Worldwide, the treatment of neurological diseases caused by BBB disruption has been a major challenge. BBB also restricts entry of neuro-therapeutic drugs and hinders treatment modalities. Hence, currently nanotechnology-based approaches are being explored on large scale as alternatives to conventional methodologies. It is necessary to investigate the in-depth characteristic features of BBB to facilitate the discovery of novel drugs that can successfully cross the barrier and target the disease effectively. It is imperative to discover novel strategies to treat life-threatening CNS diseases in humans. Therefore, insights regarding building blocks of BBB, activation of immune response on breach of this barrier, and various autoimmune neurological disorders caused due to BBB dysfunction are discussed. Further, special emphasis is given on delineating BBB disruption leading to CNS disorders. Moreover, various mechanisms of transport pathways across BBB, several novel strategies, and alternative routes by which drugs can be properly delivered into CNS are also discussed.

Dynamic training of a novelty classifier algorithm for real-time detection of early seizure onset

OBJECTIVE

To develop an adaptive framework for seizure detection in real-time that is practical to use in the Epilepsy Monitoring Unit (EMU) as a warning signal, and whose output helps characterize epileptiform activity.

METHODS

Our algorithm was tested on intracranial EEG from epilepsy patients admitted to the EMU for presurgical evaluation. Our framework uses a one-class Support Vector Machine (SVM) that is being trained dynamically according to past activity in all available channels to classify the novelty of the current activity. In this study we compared multiple configurations using a one-class SVM to assess if there is significance over specific neural features or electrode locations.

RESULTS

Our results show that the algorithm reaches a sensitivity of 87% for early-onset seizure detection and of 97.7% as a generic seizure detection.

CONCLUSIONS

Our algorithm is capable of running in real-time and achieving a high performance for early seizure-onset detection with a low false positive rate and robustness in detection of different type of seizure-onset patterns.

SIGNIFICANCE

This algorithm offers a solution to warning systems in the EMU as well as a tool for seizure characterization during post-hoc analysis of intracranial EEG data for surgical resection of the epileptogenic network.

Evaluating the Association of Calcified Neurocysticercosis and Mesial Temporal Lobe Epilepsy With Hippocampal Sclerosis in a Large Cohort of Patients With Epilepsy

BACKGROUND

Neurocysticercosis (NCC) is a parasitic infection of the central nervous system that has been associated with mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS). However, this association has not been completely established.

OBJECTIVE

To evaluate the prevalence of calcified NCC (cNCC), its characteristics and a possible association between cNCC and MTLE-HS in a cohort of 731 patients with epilepsy.

METHODS

We review clinical, EEG and neuroimaging findings of 731 patients with epilepsy. From these, 659 had CT-scans and 441 patients had complete neuroimaging with CT-scans and MRI. In these patients, we review the prevalence and characteristic of epilepsy in cNCC and in MTLE-HS patients.

RESULTS

Forty-two (6.4%) of the 659 patients studied with CT-scans had cNCC. cNCC lesions were more frequent in women than in men (n = 33-78.6% vs. n = 09-21.4%, respectively; OR = 3.64;(95%CI = 1.71-7.69); p < 0.001). cNCC was more often in patients who developed epilepsy later in life, in older patients, in patients who had a longer history of epilepsy, and in those with a lower educational level. MTLE-HS was observed in 93 (21.1%) of 441 patients that had complete neuroimaging, and 25 (26.9%) of these 93 patients also had cNCC. Calcified NCC was observed in only 17 (4.9%) of the remaining 348 patients that had other types of epilepsy rather than MTLE-HS. Thus, in our cohort, cNCC was more frequently associated with MTLE-HS than with other forms of epilepsy, O.R. = 11.90;(95%CI = 6.10-23.26); p < 0.0001).

CONCLUSIONS

As expected, in some patients the epilepsy was directly related to cNCC lesional zone, although this was observed in a surprisingly lower number of patients. Also, cNCC lesions were observed in other forms of epilepsy, a finding that could occur only by chance, with epilepsy probably being not related to cNCC at all. In this cohort, cNCC was very commonly associated with MTLE-HS, an observation in agreement with the hypothesis that NCC can contribute to or directly cause MTLE-HS in many patients. Given the broad world prevalence of NCC and the relatively few studies in this field, our findings add more data suggesting a possible and intriguing frequent interplay between NCC and MTLE-HS, two of the most common causes of focal epilepsy worldwide.

Determination of the Initial Abnormal Discharge Site in Temporal Lobe Epilepsy Through Combined EEG and Neuroimaging. What Is Next?

Objective: The objective of this study was to determine the relationship between atrophy of the hippocampus and severity of epilepsy in patients with temporal lobe epilepsy (TLE) as the first step to evaluate the possibility of surgery for epilepsy and analyze why patients cannot undergo epilepsy surgery.

Methods: Volumetric MRI of the hippocampus was performed in 51 consecutive patients (29 men; mean age 40) with TLE. TLE diagnosis, lateralization, and severity (mild, moderate, severe) of seizures were based on a comprehensive evaluation that included neurologic examination and EEG in all patients. Patients with evidence of a lesion other than hippocampal sclerosis were not included in the study. We assessed the relationship between hippocampal volumes and electrophysiological evidence of seizure severity.

Results: According to the affected side based on the EEG, a statistically significant difference (p < 0.001) in volume and a positive correlation between epilepsy and hippocampal atrophy were found.

Conclusion: Our results confirm that volume loss to the hippocampus in patients with TLE correlates with the severity of epilepsy based on the EEG. Therefore, surgical treatment is considered early when hippocampal atrophy is evident in patients with refractory TLE. However, in Latin American countries, it is a challenge to get a patient to undergo epilepsy surgery. Therefore, we try to analyze the sad situation in our hospital.

The Vulnerability of the Developing Brain: Analysis of Highly Expressed Genes in Infant C57BL/6 Mouse Hippocampus in Relation to Phenotypic Annotation Derived From Mutational Studies

The hippocampus has been shown to have a major role in learning and memory, but also to participate in the regulation of emotions. However, its specific role(s) in memory is still unclear. Hippocampal damage or dysfunction mainly results in memory issues, especially in the declarative memory but, in animal studies, has also shown to lead to hyperactivity and difficulty in inhibiting responses previously taught. The brain structure is affected in neuropathological disorders, such as Alzheimer's, epilepsy, and schizophrenia, and also by depression and stress. The hippocampus structure is far from mature at birth and undergoes substantial development throughout infant and juvenile life. The aim of this study was to survey genes highly expressed throughout the postnatal period in mouse hippocampus and which have also been linked to an abnormal phenotype through mutational studies to achieve a greater understanding about hippocampal functions during postnatal development. Publicly available gene expression data from C57BL/6 mouse hippocampus was analyzed; from a total of 5 time points (at postnatal day 1, 10, 15, 21, and 30), 547 genes highly expressed in all of these time points were selected for analysis. Highly expressed genes are considered to be of potential biological importance and appear to be multifunctional, and hence any dysfunction in such a gene will most likely have a large impact on the development of abilities during the postnatal and juvenile period. Phenotypic annotation data downloaded from Mouse Genomic Informatics database were analyzed for these genes, and the results showed that many of them are important for proper embryo development and infant survival, proper growth, and increase in body size, as well as for voluntary movement functions, motor coordination, and balance. The results also indicated an association with seizures that have primarily been characterized by uncontrolled motor activity and the development of proper grooming abilities. The complete list of genes and their phenotypic annotation data have been compiled in a file for easy access.

Epilepsy is overrepresented among young people who died from COVID-19: Analysis of nationwide mortality data in Hungary

BACKGROUND

Studies examining epilepsy as a COVID-related death risk have come to conflicting conclusions. Our aim was to assess the prevalence of epilepsy among COVID-related deaths in Hungary.

METHODS

Each COVID-19 infection case is required to be reported on a daily basis to the National Public Health Center of Hungary. This online report includes the beginning and end of the infection, as well as information on comorbidities. Death during infection is regarded as COVID-related. The anonymized data of each deceased patient are published on an information website (www.koronavirus.gov.hu) and provides up-to-date information on each patient with the date of death, the patient's sex, age, and chronic illness.

RESULTS

There were 11,968 patients who died of COVID-19 in Hungary between 13 March 2020 and 23 January 2021. Among 11,686 patients with no missing values for comorbidities, 255 patients had epilepsy (2.2%). Epilepsy was much more common among those who died at a young age: 9.3% of those who died under the age of 50 had epilepsy, compared with only 1.3% in those over the age of 80. The younger an age group was, the higher was the prevalence of epilepsy.

CONCLUSION

Patients who died of COVID-19 under the age of 50 were 10 to 20 times more likely to have epilepsy than what would have been expected from epidemiological data. Our results highlight the need for increased protection of young people with epilepsy from COVID-19 infection and the development of a vaccination strategy accordingly.

Electroencephalogram Image under Complex Domain Analysis Algorithm to Analyze Neurological Status Epilepticus and Poor Prognostic Factors of Children

This study was to adopt the electroencephalogram (EEG) image to analyze the neurological status epilepticus (SE) and adverse prognostic factors of children using the complex domain analysis algorithm, aiming at providing a theoretical basis for the clinical treatment of children with SE. 24-hour EEG was adopted to diagnose 197 children with SE. The patients were divided into an experimental group (100 cases) and a control group (97 cases) using a random number table method. The EEGs of children in the experimental group were analyzed using the compound domain analysis algorithm, and those in the control group were diagnosed by a professional doctor. The indicators of children in two groups were compared to analyze the effect of the compound domain analysis algorithm in diagnosing diseases through EEG. The prognostic scores of 197 children were scored one month after they were diagnosed, treated, and discharged, and the adverse prognostic factors were analyzed. As a result, EEG can accurately and effectively analyze the brain diseases in children. The sensitivity and specificity of the complex domain analysis algorithm for the detection of epilepsy EEG were much higher than those of the EEG automatic detection algorithm based on time-domain waveform similarity and the EEG automatic detection algorithm based on convolutional neural network (CNN), and the average running time was opposite, showing obvious difference (P < 0.05).The average accuracy, sensitivity, and specificity of children in the experimental group were 96.11%, 97.10%, and 95.19%, respectively; and those in the control group were 88.83%, 90.14%, and 87.82%, respectively, so there was an obvious difference in accuracy between two groups (P < 0.05). There were 57 cases with good prognosis and 140 cases with poor prognosis; there were 70 males with good prognosis and 19 poor prognoses and 69 women with good prognosis and 19 poor prognoses. Among 121 patients with infections, 84 cases had good prognosis and 37 cases had poor prognosis; 39 cases of irregular medication had good prognosis in 31 cases and a poor prognosis in 8 cases; and 37 cases had no obvious cause, including 25 cases with good prognosis and 12 cases with poor prognosis. In short, the EEG diagnosis and treatment effect of the compound domain analysis algorithm were better than those of professional doctors; the gender of the patient had no effect on the poor prognosis, and the pathogenic factors had an impact on the poor prognosis of the patient.

Analysis of the Clinical Effects of Sodium Valproate and Levetiracetam in the Treatment of Women with Epilepsy during Pregnancy

Objective

To explore the clinical effects of sodium valproate and levetiracetam in the treatment of women with epilepsy during pregnancy.

Methods

The clinical data of 124 women with epilepsy during pregnancy who received monotherapy with antiepileptic drugs (AEDs) in our hospital from September 2017 to January 2020 were retrospectively analyzed. According to the type of medication taken by the patients, they were recorded as the sodium valproate group (the VPA group, n = 56) and the levetiracetam group (the LEV group, n = 68 cases). The effects and the maternal and infant outcomes after treatment were compared between the two groups. The neuron-specific enolase (NSE), cognitive function-related parameters (brain-derived neurotrophic factor (BDNF) and myelin basic protein (MBP)), and related inflammatory factors (tumor necrosis factor- (TNF-) α and interleukin- (IL-) 6) levels were compared between the two groups before and after treatment.

Results

After treatment, the total clinical effective rate of the LEV group was 91.18% higher than that of the VPA group 73.21%, and the frequency and duration of seizures were lower than those of the VPA group (P < 0.05). After treatment, the probability of gestational hypertension, depression during pregnancy, low-weight infants, and neonatal deformities in the LEV group was lower than that in the VPA group (P < 0.05). After treatment, the levels of NSE, MBP, TNF-α, and IL-6 in the two groups decreased, and the levels of BDNF increased, and the LEV group changed significantly compared with the VPA group (P < 0.05).

Conclusion

Compared with sodium valproate monotherapy, levetiracetam is more effective in controlling seizures and improving maternal and infant outcomes in women with epilepsy during pregnancy and can effectively regulate their neurological and cognitive functions and reduce the serum inflammation factor level.

Pannexin 1 channels and ATP release in epilepsy: two sides of the same coin : The contribution of pannexin-1, connexins, and CALHM ATP-release channels to purinergic signaling

Purinergic signaling mediated by ATP and its metabolites contributes to various brain physiological processes as well as to several pathological conditions, including neurodegenerative and neurological disorders, such as epilepsy. Among the different ATP release pathways, pannexin 1 channels represent one of the major conduits being primarily activated in pathological contexts. Investigations on in vitro and in vivo models of epileptiform activity and seizures in mice and human tissues revealed pannexin 1 involvement in aberrant network activity and epilepsy, and highlighted that pannexin 1 exerts a complex role. Pannexin 1 can indeed either sustain seizures through release of ATP that can directly activate purinergic receptors, or tune down epileptic activity via ATP-derived adenosine that decreases neuronal excitability. Interestingly, in-depth analysis of the literature unveils that this dichotomy is only apparent, as it depends on the model of seizure induction and the type of evoked epileptiform activity, two factors that can differentially activate pannexin 1 channels and trigger distinct intracellular signaling cascades. Here, we review the general properties and ATP permeability of pannexin 1 channels, and discuss their impact on acute epileptiform activity and chronic epilepsy according to the regime of activity and disease state. These data pave the way for the development of new antiepileptic strategies selectively targeting pannexin 1 channels in a context-dependent manner.

Left ventricular dysfunction and cardiac autonomic imbalance in children with drug-resistant epilepsy

BACKGROUND

Resistance to antiepileptic drug treatment increases the risk of comorbidities and mortality due to a cardio-autonomic imbalance and left ventricular (LV) dysfunction.

OBJECTIVE

To assess the prevalence of LV dysfunction and cardio-autonomic imbalance in children with drug-resistant epilepsy (DRE).

PATIENTS AND METHODS

This cross-sectional study included 40 children with DRE and 40 healthy age- and sex-matched controls. LV function was evaluated by M-mode, two-dimensional, pulse-wave Doppler echocardiography, and tissue Doppler imaging (TDI). Cardio-autonomic function was assessed by 24 -h Holter monitoring of heart rate variability.

RESULTS

All time domain measures were significantly lower in the epilepsy group than in the control group (all Ps<0.01). Additionally, the mean high frequency (HF) parameters were significantly lower (P = 0.035), whereas the mean low frequency (LF) parameters and the LF/HF ratio were significantly higher (P < 0.001) in the epilepsy group than in the control group. LV function did not differ between groups regarding all standard echocardiographic parameters. There was evidence of subclinical LVdysfunction by tissue doppler among the epileptic group, as evidenced by the elevated Myocardial Performance Index, isovolumetric relaxation time and mitral E/Em ratio. There was no significant correlation between the duration of epilepsy or seizure frequency with any cardiac abnormality.

CONCLUSIONS

Children with DRE exhibited cardio-autonomic and subclinical LV dysfunction, independent of the duration of epilepsy, frequency, and seizure type.

Antiepileptic Drug Tiagabine Does Not Directly Target Key Cardiac Ion Channels Kv11.1, Nav1.5 and Cav1.2

Tiagabine is an antiepileptic drug used for the treatment of partial seizures in humans. Recently, this drug has been found useful in several non-epileptic conditions, including anxiety, chronic pain and sleep disorders. Since tachycardia-an impairment of cardiac rhythm due to cardiac ion channel dysfunction-is one of the most commonly reported non-neurological adverse effects of this drug, in the present paper we have undertaken pharmacological and numerical studies to assess a potential cardiovascular risk associated with the use of tiagabine. A chemical interaction of tiagabine with a model of human voltage-gated ion channels (VGICs) is described using the molecular docking method. The obtained in silico results imply that the adverse effects reported so far in the clinical cardiological of tiagabine could not be directly attributed to its interactions with VGICs. This is also confirmed by the results from the isolated organ studies (i.e., calcium entry blocking properties test) and in vivo (electrocardiogram study) assays of the present research. It was found that tachycardia and other tiagabine-induced cardiac complications are not due to a direct effect of this drug on ventricular depolarization and repolarization.

A BRD's (BiRD's) eye view of BET and BRPF bromodomains in neurological diseases

Neurological disorders (NLDs) are among the top leading causes for disability worldwide. Dramatic changes in the epigenetic topography of the brain and nervous system have been found in many NLDs. Histone lysine acetylation has prevailed as one of the well characterised epigenetic modifications in these diseases. Two instrumental components of the acetylation machinery are the evolutionarily conserved Bromodomain and PHD finger containing (BRPF) and Bromo and Extra terminal domain (BET) family of proteins, also referred to as acetylation 'readers'. Several reasons, including their distinct mechanisms of modulation of gene expression and their property of being highly tractable small molecule targets, have increased their translational relevance. Thus, compounds which demonstrated promising results in targeting these proteins have advanced to clinical trials. They have been established as key role players in pathologies of cancer, cardiac diseases, renal diseases and rheumatic diseases. In addition, studies implicating the role of these bromodomains in NLDs are gaining pace. In this review, we highlight the findings of these studies, and reason for the plausible roles of all BET and BRPF members in NLDs. A comprehensive understanding of their multifaceted functions would be radical in the development of therapeutic interventions.

Adaptive immunity cells are differentially distributed in the peripheral blood of glycine receptor antibody-positive patients with focal epilepsy of unknown cause

AIM

Glycine receptor (GlyR) autoantibodies (Ab) have been recently detected in epilepsy patients. Our study aimed to investigate the peripheral blood distribution of B and T cell subgroups responsible for antibody production to find clues supporting the distinct organization of adaptive immunity in focal epilepsy of unknown cause (FEUC).

METHOD

Seven GlyR-Ab positive and 15 GlyR-Ab negative FEUC patients and 25 age-sex matched healthy individuals were included. Peripheral blood mononuclear cells were isolated and immunophenotyped by flow cytometry.

RESULTS

There were no significant differences between CD19⁺ B, CD3⁺ T, CD4⁺ helper T, CD8⁺ cytotoxic T, and CD19⁺CD24⁺⁺CD38⁺⁺ regulatory B cell ratios among the groups. GlyR-Ab negative epilepsy patients had significantly higher CD19⁺IgD⁺CD27^- naive B cells and GlyR-Ab positive patients showed reduced percentages of CD19⁺CD38⁺CD138⁺ plasma cells than healthy controls. By contrast, GlyR-Ab positive patients exhibited significantly increased CD3⁺CD4⁺CD25^highregulatory T (Treg) cells and CD3⁺CD4⁺CD25^highCD127^low/- Treg cells and relatively increased CD19⁺IgD-CD27⁺ memory B cells without attaining statistical significance.

CONCLUSION

The increase of Tregs, which are capable of suppressing B cells, maybe a compensating countermeasure to prevent the conversion of effector B cell subgroups. Thus, our findings lend support to the involvement of adaptive immunity in focal epilepsy of unknown cause.

Uncovering the structure of clinical EEG signals with self-supervised learning

OBJECTIVE

Supervised learning paradigms are often limited by the amount of labeled data that is available. This phenomenon is particularly problematic in clinically-relevant data, such as electroencephalography (EEG), where labeling can be costly in terms of specialized expertise and human processing time. Consequently, deep learning architectures designed to learn on EEG data have yielded relatively shallow models and performances at best similar to those of traditional feature-based approaches. However, in most situations, unlabeled data is available in abundance. By extracting information from this unlabeled data, it might be possible to reach competitive performance with deep neural networks despite limited access to labels.

APPROACH

We investigated self-supervised learning (SSL), a promising technique for discovering structure in unlabeled data, to learn representations of EEG signals. Specifically, we explored two tasks based on temporal context prediction as well as contrastive predictive coding on two clinically-relevant problems: EEG-based sleep staging and pathology detection. We conducted experiments on two large public datasets with thousands of recordings and performed baseline comparisons with purely supervised and hand-engineered approaches.

MAIN RESULTS

Linear classifiers trained on SSL-learned features consistently outperformed purely supervised deep neural networks in low-labeled data regimes while reaching competitive performance when all labels were available. Additionally, the embeddings learned with each method revealed clear latent structures related to physiological and clinical phenomena, such as age effects.

SIGNIFICANCE

We demonstrate the benefit of SSL approaches on EEG data. Our results suggest that self-supervision may pave the way to a wider use of deep learning models on EEG data.

Multi-scale top-down approach for modelling epileptic protein-protein interaction network analysis to identify driver nodes and pathways

Protein - Protein Interaction Network (PPIN) analysis unveils molecular level mechanisms involved in disease condition. To explore the complex regulatory mechanisms behind epilepsy and to address the clinical and biological issues of epilepsy, in silico techniques are feasible in a cost- effective manner. In this work, a hierarchical procedure to identify influential genes and regulatory pathways in epilepsy prognosis is proposed. To obtain key genes and pathways causing epilepsy, integration of two benchmarked datasets which are exclusively devoted for complex disorders is done as an initial step. Using STRING database, PPIN is constructed for modelling protein-protein interactions. Further, key interactions are obtained from the established PPIN using network centrality measures followed by network propagation algorithm -Random Walk with Restart (RWR). The outcome of the method reveals some influential genes behind epilepsy prognosis, along with their associated pathways like PI3 kinase, VEGF signaling, Ras, Wnt signaling etc. In comparison with similar works, our results have shown improvement in identifying unique molecular functions, biological processes, gene co-occurrences etc. Also, CORUM provides an annotation for approximately 60% of similarity in human protein complexes with the obtained result. We believe that the formulated strategy can put-up the vast consideration of indigenous drugs towards meticulous identification of genes encoded by protein against several combinatorial disorders.