With the escalating global aging population, Alzheimer's disease (AD) has imposed social and economic burden on public health systems worldwide. In recent years, significant advancements have been achieved in understanding the pathogenesis, diagnostic methods, and disease-modifying therapy (DMT), which simultaneously present new directions and challenges for clinical practice. Therefore, there is an urgent need to develop standardized protocols aligned with current clinical diagnosis and treatment requirements. By comprehensively searching Alzheimer's disease-related literatures, including Meta-analyses, systematic reviews, randomized controlled trials, and cohort studies, we adopted modified Grades of Recommendations Assessment Development and Evaluation (GRADE) system to grade the quality of evidence and strength of recommendations, the "Consensus on diagnostic criteria for Alzheimer's disease" has been compiled, integrating key application points of integrating multimodal techniques such as neuropsychological assessment, neuroimaging and biomarkers, while balancing clinical applicability with cutting-edge evidence, to propose a practical framework and expert recommendations for the standardized diagnosis of Alzheimer's disease.

The fifth edition of the WHO classification of tumors of the central nervous system (CNS5, 2021) is based on the concept of precision medicine. CNS5 incorporates a large number of new molecular diagnostic indicators as well as more detailed clinical and molecular epidemiological follow-up data. Through this, CNS5 has formulated new schemes for reclassifying, sub-classifying, typing, sub-typing, grading, and/or renaming of CNS tumors, and also added a large number of new tumor entities, significantly improving the accuracy, reproducibility, and consistency of diagnosis. This article briefly describes the main modification and significance of CNS5 and the precautions for its application.

Brain-computer interface (BCI) technology, by establishing direct communication pathways between the brain and external devices, has brought groundbreaking advancements to the diagnosis, treatment and rehabilitation of neurological disorders. A typical BCI system comprises the core steps of "signal acquisition-decoding-control-feedback", an architecture that aligns closely with closed-loop neuromodulation systems, such as responsive neurostimulation (RNS) for epilepsy, which follows a "recording-decoding-intervention" paradigm. Thus, closed-loop neuromodulation can be viewed as an integrated form of BCI designed for specific therapeutic objectives. Currently, BCI has demonstrated significant potential in replacing, restoring and enhancing neural functions across various clinical domains, including the management of drug-resistant epilepsy, motor rehabilitation post-stroke, neuromodulation for Parkinson's disease, functional compensation in spinal cord injury, and objective assessment of consciousness disorder. However, the technology still faces multiple challenges, including biocompatibility, signal stability, algorithmic generalizability, clinical standardization, and ethical-regulatory considerations. This review systematically examines the clinical progress of BCI, with the aim of outlining its technological classifications (non-invasive, partially invasive, and invasive), current applications, and key issues. Furthermore, it explores future directions, such as high-precision bidirectional closed-loop interaction, multimodal neuromodulation integration, intelligent virtual rehabilitation systems, and international collaborative standardization. Ultimately, this review seeks to contribute to the evolution of BCI from an assistive tool toward an intelligent integrated paradigm, laying the groundwork for precision neurology.

In 2024, the field of epilepsy has achieved a number of far-reaching advancements in basic and clinical research. These advancements cover aspects including the discovery of new targets for epilepsy surgery, the analysis of molecular pathological mechanisms, precise pharmacological research at the ion channel level, clinical progress in cell therapy and gene therapy, the development of new drugs, the application of wearable digital health technology, integrated psychological intervention for childhood epilepsy, and seizure prediction. Summarizing these research advancements is conducive to a more comprehensive understanding of the complexity of epilepsy, providing targets for further basic research and guiding clinical diagnosis and treatment.

Vagus nerve stimulation (VNS) as an established neuromodulation technique, has seen a continuous expansion in its range of approved indications since its initial approval for the adjunctive treatment of drug-resistant epilepsy. As of 2025, the Food and Drug Administration (FDA) has approved VNS for drug-resistant epilepsy, treatment-resistant depression, obesity, and post-stroke upper limb motor rehabilitation. Furthermore, it has demonstrated therapeutic potential in areas such as cardiovascular diseases and inflammatory disorders. This narrative review examines the current clinical applications of implantable VNS, with a focus on evaluating the evidence for its efficacy in core indications including drug-resistant epilepsy, depression, and obesity. It also explores the underlying mechanisms of action and discusses future directions for the expansion of indications as well as the associated challenges. The aim is to provide a theoretical foundation and clinical reference for optimizing treatment strategies and advancing research in this field.

Objective: To report clinical characteristics of Lennox-Gastaut syndrome (LGS) caused by CHD2 gene de novo variation. Methods and Results: Three children with LGS admitted to Peking University People's Hospital from June 2023 to May 2024 were enrolled. Their onset ages were 3 months, 3 years and 4 months, and 3 years and 5 months, respectively. All 3 cases were transformed from infantile spasms (IS), presenting with spasm epileptic seizures, tonic seizures and global developmental delay. EEG initially showed hypsarrhythmia, which later progressed to generalized and multifocal discharges during disease progression. Whole exome sequencing (WES) revealed a missense variant c. 2740C > T (p. Arg914Cys) in Case 1, a nonsense variant c. 806C > G (p. Ser269*) in Case 2, and a missense variant c.2492A > C (p.His831Pro) in Case 3; neither parent carried the same type of variation, all variants were de novo. Three patients received antiepileptic seizure medicine (ASM), and at the last follow-up, seizures remained uncontrolled in all patients. Conclusions: LGS caused by CHD2 gene variation typically present in childhood, often with delayed motor and language development. Most patients have uncontrollable seizures that are often resistant to medication.

Sepsis-associated encephalopathy (SAE) is a serious complication of sepsis leading to neurological dysfunction. The pathogenesis of sepsis-associated encephalopathy is complex, and studies have proved that it is closely related to neuroinflammation, oxidative stress, pyroptosis, blood-brain barrier disruption, etc.. Nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3) inflammasome, a multiprotein complex mediating inflammatory response and participating in innate immunity, is involved in occurence and developing of sepsis-associated encephalopathy. The activation of NLRP3 inflammasome is associated with apoptosis, pyroptosis, ferroptosi and autophagy. Traditional Chinese medicine plays a role in preventing and treating sepsis-associated encephalopathy, and studies have found that traditional Chinese medicine intervention significantly inhibits the activation of NLRP3 inflammasome. This article discusses the relationship between NLRP3 inflammasome and sepsis-associated encephalopathy. It reviews the potential and promise of traditional Chinese medicine targeting NLRP3 inflammasome as a treatment for the corresponding conditions, to provide valuable references and assistance for future sepsis-associated encephalopathy treatment strategies.

Spinocerebellar ataxia type 3 (SCA3) is an autosomal dominant neurodegenerative disease, with core clinical symptoms including motor disorders and cognitive impairment. Since there is currently no effective radical treatment, the development of targeted diagnostic strategies and intervention measures to delay disease progression is particularly urgent. In recent years, neuromodulation technique has attracted widespread attention as an emerging therapeutic strategy for neurological diseases; they achieve therapeutic goals by precisely adjusting stimulation parameters to act on specific brain regions. This article aims to systematically discuss the existing efficacy studies of three neuromodulation techniques, including non-invasive techniques such as repetitive transcranial magnetic stimulation (rTMS), transcranial electrical stimulation (TES), and invasive technique such as deep brain stimulation (DBS), in the clinical application of SCA3, and explore the application potential of neuromodulation technique such as transcranial focused ultrasound stimulation (tFUS) and optogenetics in the field of SCA3 treatment. It is expected to provide new ideas and references for the in-depth research and clinical transformation of neuromodulation technique in SCA3.

Spinal cord stimulation (SCS) is a non-pharmacological neuromodulation technique used to treat various neurological disorders. It functions by delivering electrical impulses to specific areas of the dorsal columns of the spinal cord, thereby modulating abnormal neural signal transduction to alleviate symptoms. In recent years, the clinical applications of SCS have significantly expanded beyond its primary indication for refractory chronic pain. It is now increasingly utilized in diverse areas, including functional recovery in central paralysis, improvement of lower limb blood perfusion, intervention for diabetic foot pain and dysfunction, and promotion of arousal in consciousness disorder patients. This review summarizes recent clinical advances and mechanistic explorations of SCS in these expanding indications. It emphasizes the critical importance of postoperative programming management for optimizing therapeutic outcomes. Finally, the review discusses current challenge and future direction.

Deep brain stimulation (DBS), a reversible and adjustable neuromodulation technique, has expanded from its initial application in movement disorders to the treatment of mental disease. This review systematically summarizes the current applications and research progress of DBS in treatment-resistant obsessive-compulsive disorder (TR-OCD), treatment-resistant depression (TRD), anorexia nervosa (AN), substance use disorder (SUD), and treatment-resistant schizophrenia (TRS). Evidence indicates that DBS modulates dysfunctional neural circuits [e. g., cortito-striato-thalamo-cortical (CSTC) loop, reward system] and significantly alleviates symptoms, particularly showing high response and remission rates in TR-OCD. However, challenges remain, including interindividual variability in target selection, lack of predictive biomarkers, long-term safety concerns, and ethical issues. Future directions involve closed-loop stimulation, tractography-based targeting, and personalized medicine approaches to facilitate the transition of DBS from experimental therapy to clinical practice.

Resting-state electroencephalography (rsEEG) has emerged as a crucial tool in epilepsy research due to its advantages of high temporal resolution and non-invasiveness. Graph theory-based functional connectivity (FC) analysis has revealed common "locally enhanced, globally impaired" characteristics in epilepsy patients, including reduced global efficiency, deviation from small-world properties, and abnormal centrality of key nodes. These topological changes not only facilitate the understanding of the pathological mechanisms of epileptic networks but also assist in seizure detection, epileptogenic focus localization, and treatment outcome prediction. In recent years, studies combining machine learning (ML) and graph neural network (GNN) have further improved the accuracy of rsEEG in seizure prediction and treatment efficacy assessment. However, there are still shortcomings in segmentation strategies, threshold selection, and standardization of analysis procedures. This review summarizes research progress and clinical application prospects based on graph theory, emphasizes its potential value in precise diagnosis and treatment of epilepsy, and proposes that future verification and standardization in large-sample and multi-center studies are necessary.

Objective: To explore the clinical and molecular genetic characteristics of developmental and epileptic encephalopathy type 96 (DEE96) caused by de novo variation in NSF gene. Methods and Results: A male child, 96 days old, had the clinical manifestations of loss of consciousness, cyanosis of the mouth and lips, binocular gaze, limb rigidity and shaking. Head MRI showed that the bilateral frontal temporal extra cranial spaces and the anterior longitudinal fissure pool were widened. EEG showed that the peak dysrhythmia, spasm epileptic seizures, and focal seizures secondary to comprehensive tonic seizures. Gene testing showed that there was a deletion mutation of the NSF gene c.1694_1696del (p. Ile565del), which was a de novo mutation, and the diagnosis of developmental and epileptic encephalopathy type 96 was confirmed. Conclusions: The clinical phenotype of developmental and epileptic encephalopathy caused by NSF gene variation is similar, and the onset age varies. This study summarizes the clinical manifestations of pediatric patients, expands the NSF gene variation spectrum, and provides key evidence for clinical doctors to diagnose the disease.

Background: The cerebrospinal fluid/serum albumin ratio (QAlb) serves as a critical indicator for assessing blood-brain barrier (BBB) permeability. This study aimed to assess BBB permeability in children with drug-resistant epilepsy (DRE) by calculating QAlb and to investigate its correlation with clinical characteristics, as well as its potential as a biological marker. Methods: A total of 35 children diagnosed with DRE (epilepsy group) and 37 children with primary headache (control group) were admitted to The First Affiliated Hospital of Zhengzhou University between June 2018 and June 2023. QAlb values were derived from laboratory test results. Spearman rank correlation analysis was employed to explore the relationship between QAlb and variables such as disease duration, seizure type, seizure frequency, status epilepticus, and the number of antiepileptic seizure medicine (ASM). Results: Compared with control group, the QAlb values were elevated [3.29 (2.39, 4.54) ×10³ vs. 2.15 (1.42, 2.59) ×10³; Z=4.616, P=0.000], and the incidence of BBB dysfunction was higher [28.57% (10/35) vs. 2.70% (1/37); χ²=9.299, P=0.002] in epilepsy group. Spearman rank correlation analysis indicated a positive correlation between QAlb and both seizure frequency (r_s=0.587, P=0.000) and the number of ASM (r_s=0.367, P=0.030) in children with DRE. Conclusions: Some children with DRE exhibit BBB dysfunction. QAlb is positively correlated with seizure frequency and the number of ASM, suggesting its potential as a biological marker for identifying BBB dysfunction.

The pathogenesis of Alzheimer′s disease (AD) has not been fully elucidated to date, posing tremendous challenges for clinical treatment. An in-depth exploration of its pathogenesis is of great significance for early screening, prevention, diagnosis and treatment of AD. This paper comprehensively reviews numerous research hotspots in the pathogenesis of AD in recent years, including amyloid β-protein (Aβ) hypothesis, tau protein and neurofibrillary tangles (NFTs) hypothesis, neuroinflammatory hypothesis, oxidative stress injury hypothesis, vascular dysfunction hypothesis, synaptic dysfunction and neurotransmitter changes hypothesis, gut- brain axis hypothesis, and gene mutation hypothesis, so as to provide references for the early diagnosis and effective treatment.

Sudden unexpected death in epilepsy (SUDEP) refers to the sudden, unexpected, and witnessed or unwitnessed death of a patient with epilepsy, with or without evidence of a seizure, excluding status epilepticus, non-traumatic and non-drowning causes, and where autopsy reveals no structural or toxicological cause of death. Identifying high-risk populations and implementing appropriate interventions are crucial for SUDEP prevention. However, there is currently no consensus on how to select suitable recipients, content, responsible parties, and methods for disclosure. The Comorbidity Committee of China Association Against Epilepsy (CAAE) formed a working group to develop this consensus, employing the Delphi method to finalize 7 recommendations. The consensus addresses the recipients, content, responsible parties, and methods of SUDEP disclosure, with a focus on determining appropriate disclosure targets to avoid excessive anxiety caused by over-disclosure.

Objective: To report a case of subcortical band heterotopia (SBH) caused by CEP85L gene variation, summarize its clinical characteristics, and conduct a literature review to delineate the pathogenesis, clinical and imaging features, treatment, and prognosis of lissencephaly (LIS) spectrum disorders associated with pathogenic variation in CEP85L gene. Methods and Results: A 40-year-old female diagnosed as SBH due to a variation of CEP85L gene presented with drug-resistant epilepsy (DRE), and brain MRI showed posterior predominant SBH. The patient underwent ¹⁸F-FDG PET scan, showing hypometabolism in the posterior regions. Genetic test revealed that the patient had c.174T > A (p.Ser58Arg) heterozygous mutation in the second exon of CEP85L gene, and the genotype of her parents showed wild type. The patient was diagnosed as posterior predominant SBH caused by the CEP85L gene variation. After the adjustment of antiepileptic seizure medicine (ASM) and performing transcutaneous auricular vagus nerve stimulation (taVNS), the frequency of seizures decreased, but remained relatively frequent. Conclusions: The CEP85L gene variation is a rare cause of posterior predominant LIS spectrum disorders. Seizures are the most common clinical manifestation, and most patients present with DRE. The majority of patients are not suitable for surgical treatment. The case reported here expands the genetic lineage and clinical phenotypic spectrum of LIS spectrum disorders.

Accurate assessment and intervention for prolonged consciousness disorder remain critical challenges in neuroscience. Brain-computer interface (BCI) offers a novel pathway for diagnosis and treatment of consciousness disorder by decoding neural signals, reconstructing conscious communication, and guiding closed-loop neuromodulation. In diagnostic applications, EEG and functional near-infrared spectroscopy (fNIRS) detect brain signals to differentiate consciousness levels, while auditory P300 and steady-state visual evoked potential (SSVEP) paradigms show promise in identifying residual cognitive function. For communication, EEG-based BCI enable functional interaction in select patients, though accuracy and stability vary across modalities. Rehabilitation strategies leveraging BCI, such as neurofeedback and sensorimotor rhythm modulation, demonstrate potential for neural plasticity enhancement, particularly when combined with electrical stimulation. However, challenges persist, including high false-negative rates, signal instability, and limited generalizability of algorithms. Future directions emphasize interdisciplinary collaboration to optimize signal processing, validate multimodal approaches, and explore endovascular BCI for enhanced spatial resolution. Bridging neuroscientific insights with engineering innovations will be pivotal in translating BCI into clinical tools for improving outcomes in prolonged consciousness disorder patients.

Transcranial alternating current stimulation (tACS) is a non-invasive neuromodulation technique that applies low-intensity sinusoidal currents at specific frequencies to interact with endogenous neural oscillations. By modulating neuronal firing synchrony, tACS can improve neural functions. In recent years, this technique has shown potential in the treatment of depression. This article reviews advances in the application of various tACS modalities in depression, discusses optimization strategies and future directions, and provides insights for clinical practice and further research.

The association between immunological mechanisms and epilepsy has long been recognized. In 2017, the International League Against Epilepsy (ILAE) formally recognized "immune" as one of the etiological categories of epilepsy. Following increased diagnostic recognition of autoimmune encephalitis (AE, a condition frequently associated with acute symptomatic seizures), the term "autoimmune epilepsy" has gained widespread use. This has, however, led to conceptual ambiguity between "epilepsy" as a disease and "seizure" as acute symptoms, potentially affecting therapeutic strategies and prognostic evaluation. To address this issue, an ILAE expert consensus published in 2020 clarified the distinction between "acute symptomatic seizures secondary to autoimmune encephalitis" and "autoimmune-associated epilepsy". In response, Chinese Society of Electroencephalography and Epilepsy convened a multidisciplinary expert panel to develop "Definition of concepts related to immune epilepsy: Chinese expert consensus". This consensus seeks to standardize terminology, guide clinical management, optimize the use of antiepileptic seizure medicine (ASM), and provide a standardized framework for future research.

Over the recent years, electrical stimulation therapy has rapidly evolved as a commonly used neuromodulation therapy for epilepsy. Although open-loop stimulation [such as vagus nerve stimulation (VNS) and anterior nucleus of the thalamus deep brain stimulation (ANT-DBS)] has achieved certain success in treating drug-resistant epilepsy, its fixed-parameters, continuous stimulation paradigm suffers from limitations such as a mismatch between timing and dosage, poor individual adaptability, and more. In contrast, closed-loop stimulation [exemplified by responsive neurostimulator system (RNS)] significantly enhances treatment precision and energy efficiency by monitoring brain activity in real time and delivering responsive stimulation before or during seizures. It also leverages long-term data to optimize stimulation parameters and promote brain network remodeling. This review outlines the development, mechanisms, and recent advances in drug-resistant epilepsy neuromodulation from open-loop stimulation to closed-loop stimulation, and discusses future prospects for more predictive, adaptive, and network- oriented approaches, providing a theoretical foundation for personalized and precise epilepsy treatment.

Objective: Autoimmune cerebellar ataxia associated with anti-seizure related 6 homolog like 2 (SEZ6L2) antibody was reported, with the literature review and summary clinical features and treatment. Methods and Results: The patient was a 59-year-old female hospitaled in The First Affiliated Hospital of Zhengzhou University in July 2025, with progressive unsteady gait as the main clinical manifestation with dysarthria and mild cognitive dysfunction. Cell based assay (CBA) showed the titer of anti-SEZ6L2 antibody in serum was 1∶320, and cerebrospinal fluid was 1∶10. MRI showed cerebellar hemisphere and vermis mildly atrophy. The therapeutic effect of hormonotherapy was not good. After adding Efgartigimod α to eliminate pathogenic antibodies, the patient received sequential low-dose methylprednisolone therapy combined with mycophenolate mofetil for 3 months. The symptom was improved and could walk with unilateral assistance. Conclusions: Cerebellar ataxia was one of the clinical features of anti-SEZ6L2 antibody-associated disease, is associated with a poor prognosis. Efgartigimod α can be used as a treatment option to improve the prognosis of patients.

Objective: To summarize the visuo-oculomotor dysfunction in Parkinson's disease (PD) patients with dizziness, and to analyze the risk factors for dizziness. Methods: A total of 80 patients with PD visiting Peking University First Hospital between January 2019 and October 2022 were enrolled and divided into dizziness group (n=35) and non-dizziness group (n=45) based on the presence or absence of dizziness complaints within one month prior to enrollment. Subjective dizziness severity was assessed using the Visual Analog Scales (VAS) and the Dizziness Handicap Inventory (DHI) for patients with dizziness. All patients underwent video-nystagmography (VNG) examinations, including without-fixation test, fixation test, reflexive saccade test, memory-guided saccade test, smooth pursuit test and optokinetic test, to obtain visuo-oculomotor function related parameters. Univariate and multivariate linear regression analyses were used to analyze influencing factors for DHI score. Univariate and multivariate Logistic regression analyses were used to screen influencing factors for dizziness in PD patients. Subgroups analysis of clinical characteristics and visuo-oculomotor function related parameters was performed based on the presence or absence of neurogenic orthostatic hypotension (nOH) in dizziness group. Results: Multivariate linear regression analysis showed that the presence of nOH (standardized partial regression coefficient=0.385, P=0.031) and the average saccade latency (standardized partial regression coefficient=0.400, P=0.028) had positive influences on the DHI score. The presence of nOH (OR=4.701, 95%CI: 1.398-15.806; P=0.012) and a prolonged average saccade latency (OR=1.013, 95%CI: 1.002-1.025; P=0.022) were risk factors for dizziness in PD patients. Patients in the dizziness group were further divided into 2 subgroups based on the presence of nOH: subgroup without nOH (n=20) and subgroup with nOH (n=15). Compared to the subgroup without nOH, the subgroup with nOH had a higher proportion of obstructive sleep apnea-hypopnea syndrome (OSAHS, Fisher's exact probability: P=0.032), and shorter average saccade latencies at 10° (t=2.147, P=0.039) and 25° (t=2.698, P=0.011) targets. Conclusions: The complication of nOH and prolonged average saccade latency are risk factors for dizziness in PD patients and increase the severity of dizziness. PD patients with dizziness are prone to manifest sleep disorders such as rapid eye movement sleep behavior disorder (RBD) and OSAHS.

Objective: To explore the risk factors for cluster seizures in children with epilepsy and to construct a risk prediction Nomogram model based on these factors. Methods: Total 200 children with epilepsy who were treated at The Affiliated Hospital of Xuzhou Medical University between March 2022 and September 2023 were enrolled. Based on the presence or absence of cluster seizures, the pediatric patients were divided into cluster seizures group (n=98) and no cluster seizures group (n=102). Univariate and multivariate stepwise Logistic regression analyses were employed to identify risk factors for cluster seizures. A Nomogram model was then constructed based on these factors. The model's performance was evaluated using receiver operating characteristic (ROC) curve analysis, calibration curves, and the Hosmer-Lemeshow goodness-of-fit test to validate its discriminative capacity, calibration accuracy and stability. Results: Logistic regression analysis identified the following independent risk factors for cluster seizures: structural etiology (OR=3.403, 95%CI: 1.442-8.027; P=0.005), infantile-onset seizures (OR=4.720, 95%CI: 2.150-10.365; P=0.000), multiple seizure types (OR=6.446, 95%CI: 2.085-19.933; P=0.001), and generalized-multifocal discharges (OR=13.257, 95%CI: 4.669-37.641; P=0.000). The Nomogram model incorporating these risk factors demonstrated excellent predictive performance, with an area under the curve (AUC) of 0.768 (95%CI: 0.703-0.834, P=0.000). The optimal cutoff value for predicting cluster seizures was 0.513. Calibration curves showed good agreement between predicted and observed probabilities, and the Hosmer-Lemeshow goodness-of-fit test indicated that the model had good stability (P=0.988). Conclusions: Epileptic children exhibiting structural etiology, infantile-onset seizures, multiple seizure types, and generalized-multifocal discharges are more susceptible to cluster seizures. The developed Nomogram model based on these factors provides a valuable clinical tool for predicting the risk of cluster seizures in children with epilepsy.

Stroke is one of the main causes of adult disability. Patients after stroke often suffer from motor dysfunction, which affects their quality of life and requires effective treatment methods. Deep brain stimulation (DBS), as a mature neuromodulation technique, has shown significant potential in promoting the recovery of motor function after stroke in recent years. This article systematically reviews the mechanism of action of DBS in the treatment of motor dysfunction after stroke, especially summarizing the preclinical and clinical studies on the dentate nucleus of the cerebellum deep brain stimulation (DN-DBS), to provide scientific evidence and new therapeutic perspectives for clinical practice.

The management of Alzheimer's disease (AD) is transitioning from symptomatic management to disease-modifying therapy (DMT). Conventional pharmacologic treatments provide only symptomatic relief and do not alter disease progression. Anti-amyloid β-protein (Aβ) monoclonal antibody drugs, exemplified by Lecanemab and Donanemab, have demonstrated efficacy in slowing cognitive decline in patients with early Alzheimer's disease. Improved access through insurance coverage and optimized dosing regimens has enhanced treatments availability; however, their use remains restricted to well-defined populations, mandating rigorous biomarker-based patient selection, and ongoing safety surveillance. Recent years have witnessed rapid advances in novel agents targeting tau pathology and neuroinflammation, as well as in technologies designed to enhance blood-brain barrier (BBB) penetration. Non-pharmacological interventions and immune cell-based therapies also show promising synergistic effects. Looking ahead, future strategies should focus on earlier intervention, promotion of precision medicine and combination therapies, and integration of multimodal approaches to transform Alzheimer's disease into a preventable and manageable disorder.

The field of autoimmune encephalitis (AE) has undergone a profound paradigm shift in diagnosis and treatment over the past decade. Previously considered a rare and difficult-to-recognize condition, AE is now established as a major category of inflammatory central nervous system diseases. This evolution has fundamentally changed how neurologists evaluate acute encephalitis, new-onset neuropsychiatric symptoms, and rapidly progressive cognitive dysfunction. The driving force behind this shift has been the ongoing discovery of specific neural autoantibodies, together with refined characterization of their associated clinical syndromes and underlying pathology mechanisms. Despite these advances, several challenges remain. Key issues include diagnosing seronegative AE, balancing standardized and individualized treatment strategies, and managing long-term cognitive and psychiatric sequelae. This article systematically reviews the major developments underlying this paradigm shift, analyzes the core challenges currently confronting the field, and outlines future directions for achieving more precise and comprehensive patients management.

Objective: To investigate the risk factors for epilepsy recurrence in anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis patients with epileptic seizure. Methods: A total of 78 anti-NMDAR encephalitis patients with epileptic seizure admitted to Beijing Tiantan Hospital, Capital Medical University from August 2013 to September 2022 were included. Clinical data of the patients were analyzed, and epilepsy recurrence was observed during follow-up period. According to whether epilepsy recurrence occurred during the follow-up period, the patients were divided into epilepsy recurrence group (n=18) and epilepsy non-recurrence group (n=60). Univariate and multivariate Logistic regression analyses were used to screen risk factors for epilepsy recurrence in anti-NMDAR encephalitis patients with epileptic seizure. Results: During (2.21 ± 0.45) years' follow-up, 18 cases (23.08%) experienced epilepsy recurrence. Multivariate Logistic regression analysis showed that combined tumors (OR=24.154, 95%CI: 2.597-224.640; P=0.005), cognitive impairment (OR=7.809, 95%CI: 1.338-45.557; P=0.022), and cortical lesions on MRI (OR=9.868, 95%CI: 1.223-79.620; P=0.032) were risk factors for epilepsy recurrence in anti-NMDAR encephalitis patients with epileptic seizure. Conclusions: Combined tumors, cognitive impairment, and cortical lesions on MRI are risk factors for epilepsy recurrence in anti-NMDAR encephalitis patients with epileptic seizure. For patients with these factors, longer duration of antiepileptic seizure medicine (ASM) should be used to avoid epilepsy recurrence.

Objective: To investigate the expression of quinolinic acid phosphoribosyltransferase (QPRT) in glioma patients and its associations with clinicopathological features and prognosis. Methods: Public databases including The Cancer Genome Atlas (TCGA), TARGET, GTEx, GEPIA2 and UALCAN were used to analyze QPRT expression in glioma and its relationships with disease-specific survival (DSS), overall survival (OS) and progression free survival (PFS). Additionally, 219 pathologically confirmed glioma cases treated at The First Affiliated Hospital of Xinjiang Medical University from July 2010 to December 2018 were enrolled. Immunohistochemical staining was performed to determine QPRT positivity in lower-grade glioma (LGG) and glioblastoma (GBM). Factors affecting survival were identified using Log-rank test and multivariable Cox proportional hazards regression. Univariable and multivariable Logistic regression analyses were conducted to screen risk factors for OS and PFS in glioma patients. Results: Bioinformatic analyses showed that QPRT was highly expressed in the combined GBM and LGG (GBMLGG) cohort, LGG and GBM (P=0.000, 0.000, 0.000). QPRT expression was significantly correlated with immune cell infiltration scores in both LGG and GBM. It was positively associated with age in the GBMLGG cohort, LGG and GBM (P=0.000, 0.000, 0.000). It was negatively associated with tumor mutational burden (TMB) in the GBMLGG cohort, LGG and GBM (P=0.000, 0.000, 0.000), and positively associated with microsatellite instability (MSI; P=0.001, 0.019, 0.032). Immunohistochemical staining based on clinical samples showed a QPRT positivity rate was 59.82% (131/219). Compared with the QPRT-negative group, the QPRT-positive group had higher proportions of age > 50 years (P=0.027), receipt of adjuvant chemoradiotherapy (P=0.021), GBM diagnosis (P=0.000), death (P=0.000), disease progression (P=0.000) and tumor recurrence (P=0.000), and had shorter OS (P=0.000) and PFS (P=0.000). Logistic regression showed age > 50 years (OR=2.149, 95%CI: 1.037-4.453; P=0.040), GBM (OR=10.269, 95%CI: 3.635-29.013; P=0.000), and QPRT positivity (OR=5.444, 95%CI: 2.675-11.080; P=0.000) were risk factors for death; GBM (OR=28.821, 95%CI: 3.409-243.648; P=0.002), tumor recurrence (OR=23.538, 95%CI: 2.836-195.336; P=0.003) and QPRT positivity (OR=6.323, 95%CI: 2.850-14.025; P=0.000) were risk factors for progression. Cox proportional hazards regression analysis showed that GBM (RR=8.330, 95%CI: 4.727-14.681; P=0.000) and QPRT positivity (RR=1.692, 95%CI: 1.066-2.685; P=0.026) were risk factors for worse OS, while absence of recurrence was protective (RR=0.507, 95%CI: 0.314-0.819; P=0.006). For PFS, GBM (RR=5.825, 95%CI: 3.436-9.876; P=0.000) and QPRT positivity (RR=1.548, 95%CI: 1.017-2.356; P=0.041) were risk factors. Conclusions: QPRT is highly expressed in glioma and serves as an independent risk factor for poorer OS and PFS, suggesting that QPRT may be a potential molecular biomarker for prognostication in glioma.

Drug-resistant epilepsy remains a major challenge in management of epilepsy, with approximately half of patients being unsuitable candidates for resective surgery. In recent years, deep brain stimulation (DBS), as a neuromodulation therapy, has demonstrated promising potential. This review summarizes recent advances in DBS for drug -resistant epilepsy, focusing on major stimulation targets and their associated neurophysiological mechanisms. We also discuss the suitability of various DBS targets for different epilepsy types and provide perspectives on future directions, including individualized adjustment of stimulation parameters and the development of closed-loop stimulation, aiming to inform clinical practice and guide further research in the management of drug-resistant epilepsy.

Objective: To investigate the metabolic patterns of anti-glutamate decarboxylase 65 (GAD65) antibody-associated encephalitis using ¹⁸F-FDG PET, and to analyze the correlations between these patterns and clinical or neuroimaging features. Methods: A total of 25 patients with anti-GAD65 antibody-associated encephalitis admitted to Beijing Tiantan Hospital, Capital Medical University, from January 2018 to July 2024 were enrolled. All patients underwent ¹⁸F-FDG PET imaging. The whole brain of each patient was segmented into 116 brain regions, and cerebellum-normalized standard uptake value ratio (SUVRc) was calculated for each region. Principal component analysis (PCA) was used to reduce the dimensionality of SUVRc, and k-means clustering algorithm was applied to divide the patients into 2 clusters. Pearson and partial correlation analyses were performed to explore the correlations between metabolic activity of key brain regions and clinical indicators or MRI volumes. Results: PCA showed that the top 5 brain regions contributing most to Principal Component 1 were all located in the occipital lobe, in order of left cuneus, right cuneus, right lingual gyrus, left inferior occipital gyrus and right inferior occipital gyrus. The k-means clustering algorithm divided the patients into 2 clusters (14 cases in Cluster 1, 11 cases in Cluster 2). There were statistically significant differences in SUVRc of the left cuneus (F = 7.946, P = 0.000), right cuneus (F = 8.406, P = 0.000), right lingual gyrus (F = 9.447, P = 0.000), left inferior occipital gyrus (F = 17.036, P = 0.000), and right inferior occipital gyrus (F = 18.312, P = 0.000) between the 2 clusters and healthy controls. Further pairwise comparisons revealed that compared with the health controls, Cluster 2 had increased SUVRc in the left cuneus (t = 3.809, P = 0.000), right cuneus (t = 2.959, P = 0.000), right lingual gyrus (t = 3.726, P = 0.000), left inferior occipital gyrus (t = 3.948, P = 0.000), and right inferior occipital gyrus (t = 3.846, P = 0.000), so it was defined as the occipital lobe hypermetabolism cluster; Cluster 1 showed a decreasing trend in metabolic activity of these regions, thus defined as the non-occipital lobe hypermetabolism cluster. MRI volume analysis revealed that the brain regions with significant volume differences between the non-occipital lobe hypermetabolism cluster and occipital lobe hypermetabolism cluster were the cuneus (t = -2.214, P = 0.038), superior occipital gyrus (t = -2.213, P = 0.038), orbital gyrus (t = -2.829, P = 0.010), lateral part of the superior temporal gyrus (t = -2.246, P = 0.035), occipito-temporal medial sulcus (collateral sulcus), and lingual gyrus sulcus (t = -2.160, P = 0.042). Conclusions: Different metabolic patterns of anti-GAD65 antibody-associated encephalitis were identified by ¹⁸F-FDG PET combined with cluster analysis, and their associations with clinical and neuroimaging features were revealed, which deepens the understanding of the pathophysiological mechanisms of this disease.

Nervous system diseases have emerged as a leading cause of health loss and disability worldwide, and are increasingly recognized as a global public health challenge. In response to this challenge, the development and application of neuroscience technologies for treating nervous system diseases are of paramount importance. As a biomedical engineering technology characterized by multidisciplinary integration and medicine-engineering convergence, neuromodulation technique has become one of the most rapidly advancing fields in modern medicine. This article systematically reviews the principles of neuromodulation, its technological innovations, and progress in clinical applications, while also offering perspectives on future directions to promote the innovative development and clinical translation of neuromodulation technique.

The paradigm for diagnosing and treating Alzheimer's disease(AD) is undergoing a profound transformation, moving towards a biomarker-driven and early-intervention-oriented stage. In diagnosis, the emergence of high-performance biomarkers such as plasma p-tau217 has significantly advanced the ultra-early detection of AD pathology, substantially shifting the diagnostic window forward.Meanwhile, multimodal molecular imaging techniques based on the ATN(VIS) biomarkers diagnosis framework, including amyloid β-protein(Aβ)-PET and tau-PET, enable in vivo visualization and typing of pathological burden, greatly enhancing diagnostic accuracy. The therapeutic field has also witnessed significant progress, with anti-Aβ monoclonal antibody drugs like Lecanemab and Donanemab receiving approval, demonstrating that disease-modifying therapy(DMT) targeting core pathology can effectively delay clinical decline. Current research has expanded to multiple pathological mechanisms, such as Aβ, tau and neuroinflammation, alongside active exploration of personalized combination therapy strategies. Future challenges lie in promoting the clinical translation and equitable application of these innovations to address the growing public health burden. This article systematically reviews the latest advancements in the field of biomarkers diagnosis and targeted therapy for AD, aiming to provide important references for establishing an early and precise diagnosis and treatment system and promoting clinical translation applications.

Chronic pain and neurological dysfunction are important causes of disability in neurological diseases, and conventional treatments have limited efficacy for refractory cases. Spinal cord stimulation (SCS) has evolved from pain modulation to neurological function restoration, and can mediate multiple neuromodulatory and restorative effects by remodeling local spinal circuits, regulating supraspinal central networks and repairing multisystem neurological functions. However, numerous problems still exist in this field. This article systematically reviews the mechanistic evolution, technological progress and indication expansion of SCS, analyzes the current controversies and challenges in the field, explores future development paths, and provides references for the standardized clinical application and scientific innovation of SCS.

Objective: To report and analyze clinical features of anti-seizure related 6 homolog like 2 (SEZ6L2) antibody-associated encephalitis, and review relevant literatures. Methods and Results: Two patients were all diagnosed and treated by Ruijin Hospital, Shanghai Jiaotong University School of Medicine from January 2022 to July 2024. The clinical manifestations were mainly with ataxia, gait abnormalities, cognitive dysfunction and bradykinesia. One case exhibited dysautonomia. Cerebrospinal fluid (CSF) white cell counts were elevated, and both serum and CSF antibodies related to autoimmune encephalitis were negative. Further testing for anti-SEZ6L2 antibody revealed that CSF and (or) serum were positive. MRI showed cerebellar atrophy, while ¹⁸F-DPA714 PET/MRI indicated abnormal increased uptake in the cerebellum. ¹⁸F-FDG PET did not reveal any malignant tumors, however, one case showed decreased metabolism in the cerebellum, frontal lobe and temporal lobe. The clinical diagnosis was anti-SEZ6L2 antibody-associated encephalitis, and after immunotherapy, the symptoms improved. Conclusions: Anti-SEZ6L2 antibody-associated encephalitis is rare, and it has complicated clinical manifestations. There are difficulties in the early diagnosis and differential diagnosis, but early immunomodulatory treatment leads to a good prognosis in some patients.

Objective: To explore predictive efficiency of amplitude integrated electroencephalography (aEEG) combined with heart rate variability (HRV) parameters in early prognosis of acute ischemic stroke patients after mechanical thrombectomy. Methods: A total of 137 patients with acute ischemic stroke undergoing mechanical thrombectomy in He'nan Provincial People's Hospital were enrolled as the research objects between April 2021 and August 2024. According to 90 d prognosis by modified Rankin Scale (mRS), they were divided into good prognosis group (mRS score ≤ 2, n=77) and poor prognosis group (mRS score > 2, n=60). The clinical data (sociodemographic data, laboratory examination data at admission) were collected, preoperative aEEG data were collected to obtain aEEG score. After admission dynamic ECG examination was performed to obtain HRV parameters [standard deviation of normal R-R intervals (SDNN), standard deviation of normal R-R intervals index (SDNN index), root mean square successive difference of normal R-R intervals (RMSSD), and percentage of normal-to-normal intervals differing by more than 50 ms (pNN50)]. The influencing factors of early prognosis in acute ischemic stroke patients after mechanical thrombectomy were screened by univariate and multivariate Logistic regression analyses, and predictive efficiency of aEEG score and HRV parameters of early prognosis in acute ischemic stroke patients after mechanical thrombectomy was evaluated by area under the curve (AUC) of receiver operating characteristic (ROC) curve. Results: Multivariate Logistic regression analysis showed that higher National Institutes of Health Stroke Scale (NIHSS) score (OR=1.779, 95%CI: 1.038-3.050; P=0.037), higher neutrophil-to-lymphocyte ratio (OR=1.718, 95%CI: 1.016-2.905; P=0.044), and higher aEEG score (OR=1.933, 95%CI: 1.071-3.487; P=0.029) were risk factors for early poor prognosis in acute ischemic stroke patients after mechanial thrombectomy, while higher SDNN (OR=0.908, 95%CI: 0.864-0.953; P=0.000) and higher pNN50 (OR=0.930, 95%CI: 0.866-0.998; P=0.043) were protective factors for good prognosis. The AUC values of aEEG score, SDNN, SDNN index, RMSSD and pNN50 for predicting early poor prognosis were 0.673, 0.685, 0.685, 0.734 and 0.774, respectively. AUC of combined detection was 0.882, greater than those of single index (Z=4.742, P=0.000; Z=4.346, P=0.000; Z=4.360, P=0.000; Z=3.726, P=0.000; Z=2.776, P=0.006). Conclusions: aEEG score combined with HRV parameters have high predictive efficiency for early prognosis in acute ischemic stroke patients after mechanical thrombectomy, which can assist clinical determination.

Posttraumatic stress disorder (PTSD) is a severe mental disorder triggered by traumatic events. Its core clinical symptoms include intrusive memories, avoidance behaviors, negative alterations in mood and cognitive disorder, and hyperarousal. These symptoms are closely associated with aberrant neural circuitry involving the amygdala, hippocampus and prefrontal cortex. However, current pharmacological and psychological interventions are constrained by limited efficacy, poor compliance, and undesirable side effects. Given the high safety, strong reproducibility, and high patient acceptance, non-invasive electrical and magnetic neuromodulation techniques have emerged as a research focus for improving cognitive impairment in PTSD. This paper reviews the advancements in applying transcranial electrical stimulation (TES) and transcranial magnetic stimulation (TMS) to alleviate cognitive impairment in PTSD, and discusses the potential value of their combined use with psychological therapies. It aims to provide new perspectives for the clinical application of neuromodulation technique in treating cognitive impairment in PTSD.

The diagnostic criteria for Alzheimer's disease (AD) has undergone the fundamental shift, moving from clinical symptom-based approach to the focus on precise pathological changes. This paper focuses on the diagnostic advances and future prospects of cerebrospinal fluid biomarkers, blood biomarkers, and molecular imaging biomarkers for Alzheimer's disease, aiming to provide guidance for the early and accurate diagnosis of the disease.

PET imaging plays a crucial role in the diagnosis and management of autoimmune encephalitis (AE). By detecting the distribution of radiotracers, PET provides a direct visualization of cerebral metabolic activity, revealing distinct metabolic patterns associated with different types of AE. Furthermore, it allows for effective monitoring of disease progression and therapeutic response, offering robust support for clinical decision-making. This review aims to elucidate the cerebral ¹⁸F-FDG PET metabolic patterns in AE associated with various antibodies, and to discuss the applications of other emerging PET tracers, with the goal of advancing the precise diagnosis and treatment of this condition.