Epilepsy, one of the most common neurological diseases in China, is notorious for its spontaneous, unprovoked and recurrent seizures. The etiology of epilepsy varies among individual patients, including congenital gene mutation, traumatic injury, infections, etc. This heterogeneity partly hampered the accurate diagnosis and choice of appropriate treatments. Encouragingly, great achievements have been achieved in computational science, making it become a key player in medical fields gradually and bringing new hope for rapid and accurate diagnosis as well as targeted therapies in epilepsy. Here, we historically review the advances of computerized applications in epilepsy-especially those tremendous findings achieved in China-for different purposes including seizure prediction, localization of epileptogenic zone, post-surgical prognosis, etc. Special attentions are paid to the great progress based on artificial intelligence (AI), which is more "sensitive", "smart" and "in-depth" than human capacities. At last, we give a comprehensive discussion about the disadvantages and limitations of current computerized applications for epilepsy and propose some future directions as further stepping stones to embrace "the era of AI" in epilepsy.

Sudden unexpected death in epilepsy (SUDEP) is the major cause of premature death in epilepsy patients, particularly those with refractory epilepsy. Sudden unexpected death in epilepsy is thought to be related to peri-ictal cardiac dysfunction, respiratory depression, and autonomic dysfunction, albeit the exact etiology is unknown. Sudden unexpected death in epilepsy prevention remains a huge challenge. The sole presence and frequency of generalized tonic-clonic seizures (GTCS) are the most important risk factors for SUDEP, and nocturnal monitoring may lower the risk with the use of remote listening devices. In addition, studies in animal models of SUDEP have discovered that multiple neurotransmitters, including serotonin (5-HT) and adenosine, may be involved in the pathophysiological mechanisms of SUDEP and that these neurotransmitters could be the targets of future pharmacological intervention for SUDEP. The latest research findings on the epidemiology, clinical risk factors, and probable causes of SUDEP are presented in this review.

With the development and application of next-generation sequencing technology, the aetiological diagnosis of genetic epilepsy is rapidly becoming easier and less expensive. Additionally, there is a growing body of research into precision therapy based on genetic diagnosis. The numerous genes in the potassium ion channel family constitute the largest family of ion channels: this family is divided into different subtypes. Potassium ion channels play a crucial role in the electrical activity of neurons and are directly involved in the mechanism of epileptic seizures. In China, scientific research on genetic diagnosis and studies of precision therapy for genetic epilepsy are progressing rapidly. Many cases of epilepsy caused by mutation of potassium channel genes have been identified, and several potassium channel gene targets and drug candidates have been discovered. The purpose of this review is to briefly summarize the progress of research on the precise diagnosis and treatment of potassium ion channel-related genetic epilepsy, especially the research conducted in China. Here in, we review several large cohort studies on the genetic diagnosis of epilepsy in China in recent years, summarized the proportion of potassium channel genes. We focus on the progress of precison therapy on some hot epilepsy related potassium channel genes: KCNA1, KCNA2, KCNB1, KCNC1, KCND2, KCNQ2, KCNQ3, KCNMA1, and KCNT1.

Rasmussen's encephalitis (RE) is a rare condition of unknown etiology that causes a severe chronically neurological disorder with mostly affecting children. The main clinical feature of RE includes frequent seizures with drug-resistant, unilateral hemispheric atrophy, and progressive neurological deficits. In this review, we summarized five pathogenesis on the basis of the current research including virus infection, antibody-mediated degeneration, cell-mediated immunity, microglia-induced degeneration, and genetic mutations. So far, no exact virus in RE brain tissue or definite antigen in humoral immune system was confirmed as the determined etiology. The importance of cytotoxic CD8 T lymphocytes and activated microglial and the role of their immune mechanism in RE development are gradually emerging with the deep study. Genetic researches support the notion that the pathogenesis of RE is probably associated with single nucleotide polymorphisms on immune-related genes, which is driven by affecting inherent antiretroviral innate immunity. Recent advances in treatment suggest immunotherapy could partially slows down the progression of RE according to the histopathology and clinical presentation, which aimed at the initial damage to the brain by T cells and microglia in the early stage. However, the cerebral hemispherectomy is an effective means to controlling the intractable seizure, which is accompanied by neurological complications inevitably. So, the optimal timing for surgical intervention is still a challenge for RE patient. On the contrary, exploration on other aspects of pathogenesis such as dysfunction of adenosine system may offer a new therapeutic option for the treatment of RE in future.

With sudden and unpredictable nature, seizures lead to great risk of the secondary damage, status epilepticus, and sudden unexpected death in epilepsy. Thus, it is essential to use a wearable device to detect seizure and inform patients' caregivers for assistant to prevent or relieve adverse consequence. In this review, we gave an account of the current state of the field of seizure detection based on wearable devices from three parts: devices, physiological activities, and algorithms. Firstly, seizure monitoring devices available in the market primarily involve wristband-type devices, patch-type devices, and armband-type devices, which are able to detect motor seizures, focal autonomic seizures, or absence seizures. Secondly, seizure-related physiological activities involve the discharge of brain neurons presented, autonomous nervous activities, and motor. Plenty of studies focus on features from one signal, while it is a lack of evidences about the change of signal coupling along with seizures. Thirdly, the seizure detection algorithms developed from simple threshold method to complicated machine learning and deep learning, aiming at distinguish seizures from normal events. After understanding of some preliminary studies, we will propose our own thought for future development in this field.

F-fluoro-deoxyglucose position emission tomography ( F-FDG-PET) has been proven as a sensitive and reliable tool for diagnosis of autoimmune encephalitis (AE). More attention was paid to this kind of imaging because of the shortage of MRI, EEG, and CSF findings. FDG-PET has been assessed in a few small studies and case reports showing apparent abnormalities in cases where MRI does not. Here, we summarized the patterns (specific or not) in AE with different antibodies detected and the clinical outlook for the wide application of FDG-PET considering some limitations. Specific patterns based on antibody subtypes and clinical symptoms were critical for identifying suspicious AE, the most common of which was the anteroposterior gradient in anti- N -methyl- d -aspartate receptor (NMDAR) encephalitis and the medial temporal lobe hypermetabolism in limbic encephalitis. And the dynamic changes of metabolic presentations in different phases provided us the potential to inspect the evolution of AE and predict the functional outcomes. Except for the visual assessment, quantitative analysis was recently reported in some voxel-based studies of regions of interest, which suggested some clues of the future evaluation of metabolic abnormalities. Large prospective studies need to be conducted controlling the time from symptom onset to examination with the same standard of FDG-PET scanning.

Most seizures in critical ill patients are non-convulsive, and some patients may develop non-convulsive status epilepticus (NCSE), a state of continuous or repetitive seizures without convulsions. With the growing use of continuous electroencephalogram (EEG) monitoring in neuro-intensive care units, non-convulsive seizure (NCS) and NCSE are increasingly diagnosed in patients with impaired consciousness, and progress has been made in identifying various EEG characteristics of NCS/NCSE. Epidemiological studies have contributed to a better understanding of etiologies and risk factors for NCS and NCSE. However, sufficient clinical trials about the treatment of NCS and NCSE are still lacking. The appropriate level of aggressiveness in the treatment of NCSE is still debated, particularly with regard to the use of anesthetics in patients with refractory NCSE. In this review, we summarize the EEG, clinical, epidemiological, diagnostic and therapeutic knowledge of NCS and NCSE in the neuro-intensive care setting in detail.

Deep brain stimulation of the subthalamic nucleus (STN-DBS) is a promising palliative option for patients with refractory epilepsy. However, crucial questions remain unanswered: Which patients are the optimal candidates? How, where, and when to stimulate the STN? And what is the mechanism of STN-DBS action on epilepsy? Thus, we reviewed the clinical evidence on the antiepileptic effects of STN-DBS and its possible mechanisms on drug-resistant epilepsy, its safety, and the factors influencing stimulation outcomes. This information may guide clinical decision-making. In addition, based on the current knowledge on the effect of STN-DBS on epilepsy, we suggest research that needs to be carried out in the future.

Anti-neurofascin 155 (NF155) antibody has been discovered in chronic demyelinating conditions. However, the positive rate and clinical description were insufficient in acute demyelinating conditions, such as Guillain-Barré syndrome (GBS). This study aimed to explore the positive rate of anti-NF155 antibody in GBS patients and determine whether there were unique clinical characteristics in these patients.

To explore the relationship between walking measurements (i.e., walking speed, walking performance and walking confidence), and participation in ambulatory people with chronic stroke.

Unverricht-Lundborg disease (EPM1) typically leads to accumulating disability. Disability may also be caused by comorbidities but there are no data available on these.

To describe F-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging ( F-FDG PET/MRI) along with semiology and electroencephalography (EEG) in patients with gray matter heterotopia (GMH); to evaluate the concordance between F-FDG PET/MRI and clinical epileptogenic zone (EZ).

The purpose of this study is to investigate the reliability and validity as well as the clinical utility of the Silhouettes Fatigue Scale (SFS), a single-item visual scale to assess fatigue, in adult patients with multiple sclerosis (MS).

We previously investigated the preclinical state of idiopathic normal pressure hydrocephalus (iNPH): asymptomatic ventriculomegaly with features of iNPH on magnetic resonance imaging (AVIM) found in community inhabitants. The aim of the study was to determine how iNPH develops longitudinally.

The aim of this systematic review was to assess the effectiveness of Internet-based psychological interventions in the treatment of physical, socio-affective and cognitive symptoms and quality of life (QoL) in people with multiple sclerosis (pwMS) to provide currently available evidence. Systematic searches for eligible studies were carried out in four databases (August 2021) using key words. Studies were screened, data extracted, quality appraised and analysed by three independent reviewers, using predefined criteria and following the PRISMA rules. Study quality was assessed using Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields QUALSYST tool. Physical, socio-affective and cognitive symptoms and QoL were the primary outcomes. Thirteen studies were included. Two principal approaches were reported: Cognitive behavioural therapy (CBT) and mindfulness-based interventions (MBI). Interventions varied from tailored versions to videoconference by a clinician, duration mean 8 weeks, delivered via individually and groups, all online. The review found that iCBT interventions were effective for improve depression, anxiety, fatigue and QoL, and slightly in cognitive functioning in pwMS, whereas MBI interventions reported benefits in depression, anxiety, stress and QoL, and less evidence in fatigue. Generally, study quality was acceptable in most studies; eleven of the studies scored a low risk of bias on all items in the Qualsyst Tool, whereas only two studies were considered unacceptable. Psychological online interventions may improve physical, socio-affective and cognitive symptoms as well as QoL in pwMS, overcoming the face-to-face barriers (i.e. disability). Contact with the therapist and groups sessions have been identified as enablers of the online interventions. Nevertheless, the limited number of studies and the heterogeneity of health outcomes reported made difficult to afford robust conclusions on psychological intervention effects in pwMS.

Amyotrophic lateral sclerosis (ALS) is the most common motor neuron disease among adults. With diagnosis reached relatively late into the disease process, extensive motor cell loss narrows the window for therapeutic opportunities. Clinical heterogeneity in ALS and the lack of disease-specific biomarkers have so far led to large-sized clinical trials with long follow-up needed to define clinical outcomes. In advanced ALS patients, there is presently limited scope to use imaging or invasive cerebrospinal fluid (CSF) collection as a source of disease biomarkers. The development of more patient-friendly and accessible blood biomarker assays is hampered by analytical hurdles like the matrix effect of blood components. However, blood also provides the opportunity to identify disease-specific adaptive changes of the stoichiometry and conformation of target proteins and the endogenous immunological response to low-abundance brain peptides, such as neurofilaments (Nf). Among those biomarkers under investigation in ALS, the change in concentration before or after diagnosis of Nf has been shown to aid prognostication and to allow the a priori stratification of ALS patients into smaller sized and clinically more homogeneous cohorts, supporting more affordable clinical trials. Here, we discuss the technical hurdles affecting reproducible and sensitive biomarker measurement in blood. We also summarize the state of the art of non-CSF biomarkers in the study of prognosis, disease progression, and treatment response. We will then address the potential as disease-specific biomarkers of the newly discovered cryptic peptides which are formed down-stream of TDP-43 loss of function, the hallmark of ALS pathobiology.

Movement disorders have been carefully clinically defined, based on clinico-pathological series; however there is often diagnostic and prognostic uncertainty, especially in early stage disease. Blood-based biomarkers for Alzheimer's disease (AD), particularly p-tau181 and p-tau217, may be useful in the movement disorder clinic, especially in identifying corticobasal syndrome due to AD pathology and in identifying Parkinson's disease (PD) patients at high risk for the future development of dementia. Serum or plasma neurofilament light (NfL) may be useful in separating Parkinson's plus syndromes (progressive supranuclear palsy-PSP, multiple system atrophy - MSA, and corticobasal syndrome-CBS) from PD. NfL is also a prognostic biomarker, in that the level of baseline or cross-sectional plasma/serum NfL is associated with a worse prognosis in PD and PSP. The development of protein aggregation assays in cerebrospinal fluid and multiplex assays which can measure 100 s-1000s of proteins in blood will provide new tools and insights for movement disorders for clinicians and researchers. The challenge is in efficiently integrating these tools into clinical practice and multi-modal approaches, where biomarkers are combined with clinical, genetic, and imaging data may guide the future use of these technologies.