The comparison of DBS and RNS for adult drug-resistant epilepsy: a systematic review and meta-analysis.

Objective: Neuromodulation has been proven to be a promising alternative treatment for adult patients with drug-resistant epilepsy (DRE). Deep brain stimulation (DBS) and responsive neurostimulation (RNS) were approved by many countries for the treatment of DRE. However, there is a lack of systematic studies illustrating the differences between them. This meta-analysis is performed to assess the efficacy and clinical characteristics of DBS and RNS in adult patients with DRE. Methods: PubMed, Web of Science, and Embase were retrieved to obtain related studies including adult DRE patients who accepted DBS or RNS. The clinical characteristics of these patients were compiled for the following statistical analysis. Results: A total of 55 studies (32 of DBS and 23 of RNS) involving 1,568 adult patients with DRE were included in this meta-analysis. There was no significant difference in seizure reduction and responder rate between DBS and RNS for DRE. The seizure reduction of DBS and RNS were 56% (95% CI 50-62%, p > 0.05) and 61% (95% CI 54-68%, p > 0.05). The responder rate of DBS and RNS were 67% (95% CI 58-76%, p > 0.05) and 71% (95% CI 64-78%, p > 0.05). Different targets of DBS did not show significant effect on seizure reduction (p > 0.05). Patients with DRE who accepted DBS were younger than those of RNS (32.9 years old vs. 37.8 years old, p < 0.01). The mean follow-up time was 47.3 months for DBS and 39.5 months for RNS (p > 0.05). Conclusion: Both DBS and RNS are beneficial and alternative therapies for adult DRE patients who are not eligible to accept resection surgery. Further and larger studies are needed to clarify the characteristics of different targets and provide tailored treatment for patients with DRE.

EPAT: a user-friendly MATLAB toolbox for EEG/ERP data processing and analysis.

Background: At the intersection of neural monitoring and decoding, event-related potential (ERP) based on electroencephalography (EEG) has opened a window into intrinsic brain function. The stability of ERP makes it frequently employed in the field of neuroscience. However, project-specific custom code, tracking of user-defined parameters, and the large diversity of commercial tools have limited clinical application. Methods: We introduce an open-source, user-friendly, and reproducible MATLAB toolbox named EPAT that includes a variety of algorithms for EEG data preprocessing. It provides EEGLAB-based template pipelines for advanced multi-processing of EEG, magnetoencephalography, and polysomnogram data. Participants evaluated EEGLAB and EPAT across 14 indicators, with satisfaction ratings analyzed using the Wilcoxon signed-rank test or paired t-test based on distribution normality. Results: EPAT eases EEG signal browsing and preprocessing, EEG power spectrum analysis, independent component analysis, time-frequency analysis, ERP waveform drawing, and topological analysis of scalp voltage. A user-friendly graphical user interface allows clinicians and researchers with no programming background to use EPAT. Conclusion: This article describes the architecture, functionalities, and workflow of the toolbox. The release of EPAT will help advance EEG methodology and its application to clinical translational studies.

Aberrant individual structure covariance network in patients with mesial temporal lobe epilepsy.

Objective: Mesial temporal lobe epilepsy (mTLE) is a complex neurological disorder that has been recognized as a widespread global network disorder. The group-level structural covariance network (SCN) could reveal the structural connectivity disruption of the mTLE but could not reflect the heterogeneity at the individual level. Methods: This study adopted a recently proposed individual structural covariance network (IDSCN) method to clarify the alternated structural covariance connection mode in mTLE and to associate IDSCN features with the clinical manifestations and regional brain atrophy. Results: We found significant IDSCN abnormalities in the ipsilesional hippocampus, ipsilesional precentral gyrus, bilateral caudate, and putamen in mTLE patients than in healthy controls. Moreover, the IDSCNs of these areas were positively correlated with the gray matter atrophy rate. Finally, we identified several connectivities with weak associations with disease duration, frequency, and surgery outcome. Significance: Our research highlights the role of hippo-thalamic-basal-cortical circuits in the pathophysiologic process of disrupted whole-brain morphological covariance networks in mTLE, and builds a bridge between brain-wide covariance network changes and regional brain atrophy.

Wearable sensor devices can automatically identify the ON-OFF status of patients with Parkinson's disease through an interpretable machine learning model.

Introduction: Accurately and objectively quantifying the clinical features of Parkinson's disease (PD) is crucial for assisting in diagnosis and guiding the formulation of treatment plans. Therefore, based on the data on multi-site motor features, this study aimed to develop an interpretable machine learning (ML) model for classifying the "OFF" and "ON" status of patients with PD, as well as to explore the motor features that are most associated with changes in clinical symptoms. Methods: We employed a support vector machine with a recursive feature elimination (SVM-RFE) algorithm to select promising motion features. Subsequently, 12 ML models were constructed based on these features, and we identified the model with the best classification performance. Then, we used the SHapley Additive exPlanations (SHAP) and the Local Interpretable Model agnostic Explanations (LIME) methods to explain the model and rank the importance of those motor features. Results: A total of 96 patients were finally included in this study. The naive Bayes (NB) model had the highest classification performance (AUC = 0.956; sensitivity = 0.8947, 95% CI 0.6686-0.9870; accuracy = 0.8421, 95% CI 0.6875-0.9398). Based on the NB model, we analyzed the importance of eight motor features toward the classification results using the SHAP algorithm. The Gait: range of motion (RoM) Shank left (L) (degrees) [Mean] might be the most important motor feature for all classification horizons. Conclusion: The symptoms of PD could be objectively quantified. By utilizing suitable motor features to construct ML models, it became possible to intelligently identify whether patients with PD were in the "ON" or "OFF" status. The variations in these motor features were significantly correlated with improvement rates in patients' quality of life. In the future, they might act as objective digital biomarkers to elucidate the changes in symptoms observed in patients with PD and might be used to assist in the diagnosis and treatment of patients with PD.

A disease warranting attention from neurosurgeons: primary central nervous system post-transplant lymphoproliferative disorder.

Background: Primary central nervous system post-transplant lymphoproliferative disorder (PCNS-PTLD) is a rare condition, posing diagnostic and treatment challenges, with histological biopsy essential for diagnosis. Standardized treatment protocols are lacking. This disease requires urgent attention due to the increasing number of organ transplant surgeries and the use of immunosuppressive agents. Methods: From 2020 to 2023, our center diagnosed five patients with PCNS-PTLD. We reviewed their clinical records and conducted a comprehensive analysis of 22 literatures on PCNS-PTLD cases following renal transplantation or allogeneic hematopoietic stem cell transplantation (HSCT). Results: Four patients had previously received a kidney transplant, one had undergone allogeneic HSCT. The median time from the last transplant surgery to the diagnosis of PCNS-PTLD differs between kidney transplant (21.5 years) and allogeneic HSCT (9 months). Common symptoms included motor weakness (n = 4), headache (n = 2), confusion (n = 2), and nausea (n = 2), with ring-enhancing (n = 5), typically solitary (n = 3) and supratentorial (n = 3) lesions on imaging. Diagnosis involved robot-assisted stereotactic brain biopsy (n = 4) or craniotomy (n = 1), all showing Epstein-Barr virus and CD20 positivity. Most cases (n = 4) were monomorphic diffuse large B-cell lymphoma. Treatment included rituximab (n = 3), surgical resection (n = 2), zanubrutinib (n = 1), whole-brain radiation (n = 1), and methotrexate (n = 1). At the last follow-up, the median duration of follow-up for all patients was 19 months. During this time, 3 patients had died and 2 patients were still alive. Conclusion: In patients with a history of kidney transplantation or allogeneic HSCT who are on long-term immunosuppressive therapy, any neurological symptoms, particularly the presence of supratentorial ring-enhancing masses in the brain on imaging, whether solitary or multiple, should raise high suspicion for this disease, warranting a timely brain biopsy. Additionally, we found that besides reducing immunosuppressants, zanubrutinib may be a potential, safe, and effective treatment for this condition. Moreover, post-surgical administration of rituximab in conjunction with whole-brain radiotherapy also appears to be a potentially safe and effective approach.

The Interplay Between Epilepsy and Parkinson's Disease: Gene Expression Profiling and Functional Analysis.

The results of many epidemiological studies suggest a bidirectional causality may exist between epilepsy and Parkinson's disease (PD). However, the underlying molecular landscape linking these two diseases remains largely unknown. This study aimed to explore this possible bidirectional causality by identifying differentially expressed genes (DEGs) in each disease as well as their intersection based on two respective disease-related datasets. We performed enrichment analyses and explored immune cell infiltration based on an intersection of the DEGs. Identifying a protein-protein interaction (PPI) network between epilepsy and PD, and this network was visualised using Cytoscape software to screen key modules and hub genes. Finally, exploring the diagnostic values of the identified hub genes. NetworkAnalyst 3.0 and Cytoscape software were also used to construct and visualise the transcription factor-micro-RNA regulatory and co-regulatory networks, the gene-microRNA interaction network, as well as gene-disease association. Based on the enrichment results, the intersection of the DEGs mainly revealed enrichment in immunity-, phosphorylation-, metabolism-, and inflammation-related pathways. The boxplots revealed similar trends in infiltration of many immune cells in epilepsy and Parkinson's disease, with greater infiltration in patients than in controls. A complex PPI network comprising 186 nodes and 512 edges were constructed. According to node connection degree, top 15 hub genes were considered the kernel targets of epilepsy and PD. The area under curve values of hub gene expression profiles confirmed their excellent diagnostic values. This study is the first to analyse the molecular landscape underlying the epidemiological link between epilepsy and Parkinson's disease. The two diseases are closely linked through immunity-, inflammation-, and metabolism-related pathways. This information was of great help in understanding the pathogenesis, diagnosis, and treatment of the diseases. The present results may provide guidance for further in-depth analysis about molecular mechanisms of epilepsy and PD and novel potential targets.

Pyruvate is modified by tea/coffee metabolites and reversely correlated with multiple system atrophy and Parkinson's disease.

Introduction: Multiple system atrophy (MSA) is a rapidly progressing neurodegenerative disorder. Although diverse biomarkers have been established for Parkinson's disease (PD), no widely accepted markers have been identified in MSA. Pyruvate and lactate are the end-product of glycolysis and crucial for brain metabolism. However, their correlation with MSA remains unclear. Moreover, it is elusive how lifestyles modify these metabolites. Methods: To investigate the correlation and diagnostic value of plasma pyruvate and lactate levels in MSA and PD. Moreover, we explored how lifestyle-related metabolites interact with these metabolites in determining the disease risk. We assayed the 3 metabolites in pyruvate/lactate and 6 in the tea/coffee metabolic pathways by targeted mass spectrometry and evaluate their interactions and performance in diagnosis and differentiation between MSA and PD. Results: We found that 7 metabolites were significantly different between MSA, PD and healthy controls (HCs). Particularly, pyruvate was increased in PD while significantly decreased in MSA patients. Moreover, the tea/coffee metabolites were negatively associated with the pyruvate level in HCs, but not in MSA and PD patients. Using machine-learning models, we showed that the combination of pyruvate and tea/coffee metabolites diagnosed MSA (AUC = 0.878) and PD (AUC = 0.833) with good performance. Additionally, pyruvate had good performance in distinguishing MSA from PD (AUC = 0.860), and the differentiation increased (AUC = 0.922) when combined with theanine and 1,3-dimethyluric acid. Conclusions: This study demonstrates that pyruvate correlates reversely with MSA and PD, and may play distinct roles in their pathogenesis, which can be modified by lifestyle-related tea/coffee metabolites.

Risk Factors for Postoperative Cognitive Decline After Orthopedic Surgery in Elderly Chinese Patients: A Retrospective Cohort Study.

Purpose: We aimed to identify the risk factors for postoperative cognitive decline (POCD) by evaluating the outcomes from preoperative comprehensive geriatric assessment (CGA) and intraoperative anesthetic interventions. Patients and Methods: Data used in the study were obtained from the Aged Patient Perioperative Longitudinal Evaluation-Multidisciplinary Trial (APPLE-MDT) cohort recruited from the Department of Orthopedics in Xuanwu Hospital, Capital Medical University between March, 2019 and June, 2022. All patients accepted preoperative CGA by the multidisciplinary team using 13 common scales across 15 domains reflecting the multi-organ functions. The variables included demographic data, scales in CGA, comorbidities, laboratory tests and intraoperative anesthetic data. Cognitive function was assessed by Montreal Cognitive Assessment scale within 48 hours after admission and after surgery. Dropping of ≥1 point between the preoperative and postoperative scale was defined as POCD. Results: We enrolled 119 patients. The median age was 80.00 years [IQR, 77.00, 82.00] and 68 patients (57.1%) were female. Forty-two patients (35.3%) developed POCD. Three cognitive domains including calculation (P = 0.046), recall (P = 0.047) and attention (P = 0.007) were significantly worsened after surgery. Univariate analysis showed that disability of instrumental activity of daily living, incidence rate of postoperative respiratory failure (PRF) ≥4.2%, STOP-Bang scale score, Caprini risk scale score and Sufentanil for maintenance of anesthesia were different between the POCD and non-POCD patients. In the multivariable logistic regression analysis, PRF ≥ 4.2% (odds ratio [OR] = 2.343; 95% confidence interval [CI]: 1.028-5.551; P = 0.046) and Sufentanil for maintenance of anesthesia (OR = 0.260; 95% CI: 0.057-0.859; P = 0.044) was independently associated with POCD as risk and protective factors, respectively. Conclusion: Our study suggests that POCD is frequent among older patients undergoing elective orthopedic surgery, in which decline of calculation, recall and attention was predominant. Preoperative comprehensive geriatric assessments are important to identify the high-risk individuals of POCD.

IDH1 mutation predicts seizure occurrence and prognosis in lower-grade glioma adults.

Epileptic seizures are frequently the first symptom in glioma patients. However, the causal relationship between glioma and epilepsy is not yet fully understood, as it cannot be explained solely by tumor mass effect or peritumoral factors. In this study, we retrospectively enrolled 320 patients with grade 2-4 glioma who received treatment between January 2019 and July 2022, and explored the biomarkers of seizure occurrence and seizure outcome prediction using univariate and multivariate logistic regression analyses. Our results showed that IDH1 R132H mutation was an independent risk factor for seizure occurrence in lower-grade glioma (LGG) patients (OR = 4.915, 95%CI = 1.713 - 14.103, P = 0.003). Additionally, IDH1 R132H mutation predicted higher seizure-free ratios in LGG patients with intact ATRX expression (OR = 6.793, 95%CI = 1.217 - 37.923, P = 0.029) one year after diagnosis. Therefore, our findings suggest that IDH1 mutation can predict seizure occurrence and control in LGG patients, providing further insights into the relationship between glioma and epilepsy.

Structural and functional changes in the brain after chronic complete thoracic spinal cord injury.

This study aimed to investigate whether brain anatomical structures and functional network connectivity are altered after chronic complete thoracic spinal cord injury (cctSCI) and to determine how these changes impact clinical outcomes. Structural and resting-state functional MRI was performed for 19 cctSCI patients (18 for final statistics) and 19 healthy controls. Voxel-based morphometry (VBM) was used to assess gray matter volume (GMV) with differences between cctSCI patients and controls. VBM results were used as seeds for whole-brain functional connectivity (FC) analysis. The relationship between brain changes and clinical variables was investigated. Compared with those of the control group, the left triangular inferior frontal gyrus, middle frontal gyrus, orbital inferior frontal gyrus, precuneus and parietal superior gyrus volumes of SCI patients decreased, while the left superior frontal gyrus and supplementary motor area volumes increased. Additionally, when the regions with increased GMV were used as seeds, the FC of the parahippocampus and thalamus increased. Subsequent partial correlation analysis showed a positive correlation between FC and total sensorimotor score based on the ASIA criteria (p = 0.001, r = 0.746). Overall, the structural and functional changes in the brain after cctSCI occurred in some visual and cognitive areas and sensory or motor control areas. These findings aid in improving our understanding of the underlying brain injury mechanisms and the subsequent structural and functional reorganization to reveal potential therapeutic targets and track treatment outcomes.

Stereo-electroencephalography-guided three-dimensional radiofrequency thermocoagulation for mesial temporal lobe epilepsy with hippocampal sclerosis: A retrospective study with long-term follow-up.

OBJECTIVE: Stereo-electroencephalography-guided three-dimensional radiofrequency thermocoagulation (SEEG-3D RFTC) is a minimally invasive treatment for mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS). This study aimed to investigate the long-term prognosis after SEEG-3D RFTC treatment in patients with MTLE-HS. METHODS: This single-center retrospective study included 28 patients with MTLE-HS treated with SEEG-3D RFTC from January 2016 to May 2018. Postoperative curative effects were evaluated using the Engel classification, and the patients were followed up for 5 years. RESULTS: The proportions of patients categorized as Engel I between 1 and 5 years after surgery were 72.41% (12 months after surgery), 67.86% (18 months after surgery), 62.07% (24 months after surgery), 50.00% (36 months after surgery), 42.86% (48 months after surgery), and 42.86% (60 months after surgery), respectively. Regarding long-term efficacy, based on the Engel classification, SEEG-3D RFTC showed room for improvement. SIGNIFICANCE: This was the first study to evaluate the efficacy of SEEG-3D RFTC for MTLE-HS with long-term follow-up. SEEG-3D RFTC is a promising alternative for patients with MTLE-HS. PLAIN LANGUAGE SUMMARY: This study explored the potential of stereoelectroencephalography-guided three-dimensional radiofrequency thermocoagulation, a minimally invasive approach, for treating medial temporal lobe epilepsy with hippocampal sclerosis. Involving 28 patients, the research tracked the treatment's success over five years using the Engel classification. Initial results were promising, with 72.41% of patients achieving the most favorable outcome (Engel I) at one year. While there was a gradual decrease in this proportion over time, 42.86% of patients maintained this positive outcome at five years, highlighting the treatment's potential for long-term efficacy.

Enhanced Recovery After Surgery (ERAS) Program for Anterior Cervical Discectomy and Fusion (ACDF) in Patients Over 60 Years Old.

Background: Enhanced recovery after surgery (ERAS) is currently widely used in many surgical specialties, but there is still a lack of concern about the cervical ERAS program for old patients (>60 years old). We aimed to determine whether our ERAS program significantly improved satisfaction and outcomes in old patients (>60 years old) with anterior cervical discectomy and fusion (ACDF). Methods: This is a retrospective cohort study. The study enrolled patients if they were over the age of 60 years old underwent ACDF from July 2019 and June 2021 (ERAS group) and from January 2018 and June 2019 (non-ERAS group). Data including demographic, comorbidity, and surgical information were collected. We also evaluated ERAS process compliance, primary outcome, surgical complication, and length of stay (LOS). Results: There were 135 patients in the ERAS group, and 122 patients in the non-ERAS group were included. A comparison of the demographic data revealed that there were no statistically significant intergroup differences observed between the group. Overall, ERAS pathway compliance was 91.9%. There were no significant differences in the fusion levels, operative time, intraoperative blood loss, postoperative VAS score, and complications between the ERAS and non-ERAS groups. In addition, there was no significant difference in readmission and mortality at 30-day follow-up between the two groups. However, we observed a statistically significant decrease in the LOS in the ERAS group (8.68±2.34 of ERAS group versus 10.43±4.05 in non-ERAS group, p=0.013). Conclusion: This report describes the first ERAS protocol used in old patients with ACDF. Our ERAS program is safe and associated with incremental benefits with respect to LOS in old patients with ACDF.

CHIT1-positive microglia drive motor neuron ageing in the primate spinal cord.

Ageing is a critical factor in spinal-cord-associated disorders1, yet the ageing-specific mechanisms underlying this relationship remain poorly understood. Here, to address this knowledge gap, we combined single-nucleus RNA-sequencing analysis with behavioural and neurophysiological analysis in non-human primates (NHPs). We identified motor neuron senescence and neuroinflammation with microglial hyperactivation as intertwined hallmarks of spinal cord ageing. As an underlying mechanism, we identified a neurotoxic microglial state demarcated by elevated expression of CHIT1 (a secreted mammalian chitinase) specific to the aged spinal cords in NHP and human biopsies. In the aged spinal cord, CHIT1-positive microglia preferentially localize around motor neurons, and they have the ability to trigger senescence, partly by activating SMAD signalling. We further validated the driving role of secreted CHIT1 on MN senescence using multimodal experiments both in vivo, using the NHP spinal cord as a model, and in vitro, using a sophisticated system modelling the human motor-neuron-microenvironment interplay. Moreover, we demonstrated that ascorbic acid, a geroprotective compound, counteracted the pro-senescent effect of CHIT1 and mitigated motor neuron senescence in aged monkeys. Our findings provide the single-cell resolution cellular and molecular landscape of the aged primate spinal cord and identify a new biomarker and intervention target for spinal cord degeneration.

RNA modification regulator DDC in endometrial cancer affects the tumor microenvironment and patient prognosis.

Uterine corpus endometrial carcinoma (UCEC) is infiltrated by immune cells, which are involved in the growth and proliferation of malignant tumors and resistance to immunotherapy. This study suggested that RNA modification regulators played an important role in the development and prognosis of UCEC. Many studies confirmed that RNA modification played an essential role in tumor immune regulation, and abnormal RNA modification contributed to tumorigenesis and cancer progression. Based on the RNA modification regulatory factors, the UCEC samples from TCGA (The Cancer Genome Atlas) were classified into two clusters, namely Cluster A and Cluster B, using unsupervised consensus clustering. We obtained DEG (differentially expressed genes) between the two clusters, and constructed a risk model of RNA modification-related genes using DEGs. Cluster A had lower RNA modification regulatory factors, richer immune cell infiltration, and better prognosis. The differentially expressed genes between the two clusters were obtained, and these genes were used for modeling. This model divided patients with UCEC into two groups. The low-risk group had better immune infiltration, and the ROC (receiver operating characteristic) curve showed that this model had good predictive efficacy. The low-risk group had a better response to immunotherapy by immune checkpoint prediction. We obtained the key gene L-dopa decarboxylase (DDC) through the intersection of LASSO model genes and GEO dataset GSE17025. We evaluated the potential biological functions of DDC. The differences in the expression of DDC were verified by immunohistochemistry. We evaluated the relationship between DDC and immune cell infiltration and verified this difference using immunofluorescence. Cluster A with low expression of RNA modification regulators has better prognosis and richer immune cell infiltration, therefore, we believed that RNA modification regulators in UCEC were closely related to the tumor microenvironment. Also, the risk score could well predict the prognosis of patients and guide immunotherapy, which might benefit patients with UCEC.

A bibliometric and knowledge-map analysis of the glymphatic system from 2012 to 2022.

Objective: To explore the development context, research hotspots and frontiers in the glymphatic system (GS) field from 2012 to 2022 by bibliometric analysis. Methods: The Web of Science Core Collection (WoSCC) database was searched for articles published between 2012 and 2022. Microsoft Excel was used to manage the data. VOSviewer, CiteSpace, GraphPad Prism, the Web of Science, and an online analysis platform for bibliometrics (http://bibliometric.com/) were used to analyze the countries, institutions, journals, and collaboration networks among authors and the types of articles, developmental directions, references, and top keywords of published articles. Results: A total of 412 articles were retrieved, including 39 countries/regions, 223 research institutes and 171 academic journals. The subject classifications related to the GS were Neuroscience, Clinical Neuroscience and Radiology/Nuclear Medicine/Medical Imaging. The United States has maintained its dominant and most influential position in GS research. Among research institutions and journals, the Univ Rochester and Journal of Cerebral Blood Flow and Metabolism had the highest number of academic articles, respectively. Nedergaard M had the most published article, and Iliff JJ had the most co-citations. The top two keywords with the highest frequency were "glymphatic system" and "cerebrospinal fluid." Conclusion: This research provides valuable information for the study of the GS. The bibliometric analysis of this area will encourage potential collaborations among researchers, defining its frontiers and directions for development.