BMC Neurology最新文献

Background: Corticomuscular coupling (CMC) reflects the neural communication between the central and peripheral nervous systems, particularly during motor control. However, the corticomuscular coupling characteristics during upper limb motor tasks in stroke patients remain unclear. This study aims to explore the differences in corticomuscular coupling characteristics between stroke patients and healthy subjects.

Methods: A total of 25 stroke patients in the subacute phase with dominant hemisphere and 20 age-matched healthy controls were enrolled in the study. Participants performed an isometric wrist extension task at 50% of their maximum voluntary contraction (MVC) for 15 s, during which surface electromyography (sEMG) signals measured from the flexor carpi radialis and extensor carpi ulnaris, as well as functional near-infrared spectroscopy (fNIRS) data from the prefrontal cortex, supplementary motor area, and primary motor cortex, were simultaneously recorded. Corticomuscular coupling metrics (phase synchronization index (PSI), coherence), fNIRS measures (cortical activation, functional connectivity), and sEMG parameters (root mean square (RMS), median frequency (MF), and fuzzy approximate entropy (fApEn)) were analyzed.

Results: Stroke patients demonstrated significantly reduced PSI and coherence values in specific corticomuscular couplings compared to age-matched healthy controls. Moreover, enhanced cortical activation, stronger functional connectivity, and diminished muscle activation (with lower sEMG complexity) were observed in specific cortical regions and assessed muscles.

Conclusion: This study reveals differences in the mapping relationship between cortical activation and sEMG signals across time-domain and frequency-domain indices in stroke patients compared to healthy subjects, providing new theoretical insights into the interaction between brain activity and motor execution. These results underscore the disrupted corticomuscular coupling in stroke patients and suggest its value in characterizing the central-peripheral interaction during motor execution, which may inform future rehabilitation assessment strategies.

Objective: Status epilepticus (SE) is a common neurological emergency associated with significant morbidity and mortality, with approximately one-third of patients demonstrating resistance to first-line treatment. Electroencephalography (EEG) plays a critical role not only in the diagnosis of SE but also in its monitoring and prognostication. This study aims to evaluate the performance of SE-specific severity scoring systems-Status Epilepticus Severity Score (STESS) and Epidemiology-Based Mortality Score in Status Epilepticus (EMSE)-in predicting mortality, in comparison with four widely used systemic severity scores: Acute Physiology and Chronic Health Evaluation II (APACHE II), Simplified Acute Physiology Score II (SAPS II), Sequential Organ Failure Assessment (SOFA), and the Inflammation, Nutrition, Consciousness, Neurologic function, and Systemic condition (INCNS) score. Furthermore, the effects on mortality of the Glasgow Coma Scale (GCS) for assessing level of consciousness, the age-adjusted Charlson Comorbidity Index (ACCI) for evaluating comorbidities, and the pre-SE Modified Rankin Scale (mRS) for measuring pre-existing morbidity will also be investigated.

Methods: A total of 200 status epilepticus (SE) episodes in 188 patients with available EEG data, followed over a four-year period, were included in the study. The sensitivity, specificity, accuracy, and area under the curve (AUC) of each scoring system were calculated and compared.

Results: The SOFA score demonstrated the highest performance in predicting mortality (AUC = 0.81). Systemic severity scores such as SAPS II, SOFA, APACHE II, and INCNS were found to be more effective in predicting mortality than the SE-specific scores STESS and EMSE.

Conclusion: The evaluated scoring systems accounted for approximately 48% of mortality among adult SE patients; however, none were sufficient to predict mortality either alone or in combination. Therefore, there is a need for more specific prognostic scoring systems.

Background: Approximately 900,000 MRI brain scans are performed annually in the United Kingdom alone, with incidental findings frequently encountered. One of the most prevalent findings is white matter hyperintensities (WMHs). WMHs often indicate cerebral small vessel disease (cSVD) but can also be associated with migraine and demyelination. Prospective population studies have already confirmed a high prevalence of WMHs in elderly patients. In younger patients, or when the radiological burden is low, WMHs are commonly considered non-specific. Routinely collected data represents a valuable resource to facilitate further study. We aimed to describe the prevalence of WMHs in a direct to scan referral population and to understand associations with age, demographics, performance status and referral criteria.

Methods: We performed a service evaluation of our local two-week wait suspected central nervous system cancer pathway to understand the association between age, demographics, performance status, referral criteria, imaging outcomes and both the prevalence and radiological characteristics of WMHs. Analysis was performed using R version 4.1.3.

Results: We identified 1033 patients, referred over a 30-month period. Mean patient age was 51.3±18.3 years with 65% females. As expected, WMHs were present on 89.7% of scans in patients aged over 80, with 98.1% of these consistent with cSVD upon review by an experienced neuroradiologist. We show an important association between WMHs deemed representative of cSVD and both performance status and levels of deprivation. However, WMHs were also present in approximately 1 in 5 patients under 50 years old and were typically deemed non-specific. Our analysis showed prevalence of WMH, its radiological burden and likelihood of WMHs being attributed to cSVD all increased with age. It is therefore feasible to consider that these changes may represent early cSVD.

Conclusions: We demonstrate a prevalence of radiological cSVD comparable to the wider literature in elderly patients whilst highlighting the potential underestimation of cSVD in the younger population, in whom further study of WMHs is required. There is potential for routinely collected data to define the prevalence and characteristics of radiological cSVD more accurately whilst facilitating further research.

Background: This study employed neurite orientation dispersion and density imaging (NODDI) to investigate gray matter microstructural changes in obstructive sleep apnea hypopnea syndrome (OSAHS) patients with cognitive impairment, assessing early diagnostic potential.

Methods: The study comprised 23 OSAHS patients (OSA-NCI group), 43 OSAHS patients with experiencing cognitive impairment (OSA-CI group), and 15 healthy controls (HC group). Fractional anisotropy (FA), neurite density index (NDI), orientation dispersion index (ODI), and volume fraction of isotropic water molecules (Viso) in regions of interest (ROIs) were calculated. Correlations between these parameters and Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) scores were examined. Diagnostic effect was evaluated using receiver operating characteristic (ROC) curve analysis, and area under the curve (AUC) was calculated.

Results: Significant variations were observed in the NDI, ODI, Viso, and FA. Compared to HCs, the NDI and ODI in the OSA-NCI group decreased, while the Viso value increased. NDI and ODI showed slight increases in the OSA-CI group but remained below HC levels; Viso significantly increased. However, FA did not significantly differ. NDI, ODI, and Viso strongly correlated with MoCA scores in specific gray matter regions; FA showed weak correlations (r < 0.5). ROC analysis confirmed the effectiveness of the NODDI parameters, with average AUC values of 0.689 for the Viso value, 0.676 for the ODI, and 0.635 for the NDI; however, FA showed limited diagnostic utility (AUC 0.452).

Conclusion: This study suggests the potential diagnostic utility of NODDI in detecting gray matter pathology in OSAHS patients with cognitive impairment, though further validation in larger, independent cohorts is needed.

Background: Multiple sclerosis (MS) is a chronic autoimmune disease that affects the central nervous system through persistent inflammation and demyelination. Cladribine, an immunosuppressive agent, has emerged as a promising high-efficacy disease-modifying therapy. However, concerns remain regarding its long-term safety, particularly the risks of lymphopenia, infections, and malignancy. This study aimed to evaluate the efficacy and safety of oral cladribine, including a control group defined by placebo, fingolimod, and natalizumab, by analyzing the impact of cladribine on the annualized relapse rate, relapse-free rate, expanded disability status, and adverse outcomes, such as malignancy, infections, and persistent lymphopenia.

Methods: This systematic review and meta-analysis adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines. The databases PubMed, Web of Science, and Google Scholar were comprehensively searched to identify randomized controlled trials and observational studies comparing oral cladribine with other MS treatments or placebo.

Results: This study included 24,976 patients with MS. Cladribine significantly reduced annualized relapse rates (mean difference [MD] = - 0.09; P = 0.0004), especially versus placebo (MD = - 0.15; P = 0.0002). No overall difference in Expanded Disability Status Scale was identified, although fingolimod showed better post-treatment outcomes (MD = 0.40; P < 0.00001). Relapse-free rates were similar, except in the placebo subgroup favoring cladribine (MD = 2.46; P < 0.00001). Cladribine was associated with an increased risk of persistent lymphopenia (odds ratio [OR] = 20.20; P < 0.00001), whereas infection (OR = 1.18; P = 0.78) and malignancy rates (OR = 1.87; P = 0.63) were comparable to those of the controls. The interpretation was limited by study heterogeneity and the absence of a pooled analysis of several secondary outcomes.

Conclusion: Cladribine may be a valuable therapeutic option for relapsing-remitting MS with a strong efficacy profile. The lymphopenia incidence highlights the need for regular hematological monitoring to ensure the safety of cladribine.

Background: Prolonged disorders of consciousness (pDOC) pose significant clinical and societal challenges. Evaluating the prognosis of patients with pDOC is of a great concern for clinicians. This derivation study aimed to establish a nomogram based on mismatch negativity (MMN) to predict the recovery of consciousness in patients with pDOC.

Methods: This is a single-center retrospective derivation study. From September 2021 to June 2023, demographic and clinical information and MMN results of patients with pDOC were collected. The prognosis of patients who were admitted to the hospital for 6 months was assessed using the Glasgow Outcome Scale, categorized as "unfavorable prognosis" and "favorable prognosis." In this study, Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses were used to select the most relevant predictors and create the nomogram. Receiver Operating Characteristic (ROC), calibration curves and Decision Curves Analysis (DCA) in the nomogram explained the predictive efficacy and clinical utility of the patients.

Results: 101 patients with pDOC were included, with 57 and 44 having unfavorable and favorable prognose. Univariate and LASSO regression analysis indicated that the MMN amplitude at Fz, Coma Recovery Scale-Revised scores, disease duration, and multiple intensive care unit admissions were the independent factors that were used to develop the exploration nomogram. ROC curves, calibration curves, and DCA showed good predictive power (area under the ROC curve: 0.821), with DCA suggested potential net benefit within clinically relevant decision-probability ranges.

Conclusion: In this study, an exploratory nomogram developed based on MMN predicted the 6-month outcome of patients with pDOC. This exploratory, internally validated model may support prognostic assessment.

Background: Despite advancements in multimodal therapy, glioma remains a lethal brain tumor with limited prognostic biomarkers. Programmed cell death (PCD) pathways and long non-coding RNAs (lncRNAs) are emerging as therapeutic targets, but their combined prognostic potential in glioma remains underexplored.

Methods: RNA sequencing data from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) cohorts were analyzed to identify PCD-related lncRNAs. Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression and multivariate Cox proportional hazards regression analyses were applied to construct a prognostic signature, with external validation performed in an independent cohort. Tumor immune microenvironment characterization was subsequently conducted through the Tumor IMmune Estimation Resource (TIMER) database using the inverse fold product algorithm, which quantified six tumor-infiltrating immune cells (TIIC) subtypes across 10,897 pan-cancer samples. Immune checkpoint differential expression between risk strata was assessed via single-sample gene set enrichment analysis (ssGSEA). Drug sensitivity prediction was performed using the Cancer Genome Project (GCP) databases.

Results: A 4-lncRNA signature effectively stratified patients into high-risk and low-risk groups. The prognosis of the high-risk group is worse. In multivariate analysis, a risk score can independently predict the prognosis and has a robust prediction efficiency in the CGGA external verification set. The infiltration of immunosuppressive cells, such as M2 macrophages, increased the expression of immune checkpoints, such as PD-L1, increased, and the infiltration of CD8 + T cells decreased in high-risk patients. Computational screening identified elesclomol as a potential therapeutic agent showing subtype-specific efficacy.

Conclusions: This study highlights the prognostic significance of lncRNAs associated with PCD in glioma and provides computational evidence for their potential as therapeutic targets. While the results suggest novel avenues for treatment development, they must be interpreted cautiously due to the lack of experimental validation. Future studies should aim to validate these results through controlled clinical trials and explore underlying molecular mechanisms.

Background: Alzheimer's disease (AD) was a progressive neurodegenerative disorder characterised by an insidious onset and gradual cognitive decline. It remained a significant global health challenge. Methylparaben (MEP), a preservative commonly used in cosmetics and food processing, had been associated with the development and progression of AD.

Methods: First, we acquired the initial three-dimensional (3D) structure of MEP from PubChem (CID: 7456), followed by structural optimization via energy minimization using Chem3D software to complete its 3D structural characterisation. This was followed by systematic target prediction across the SwissTargetPrediction, SEA, GeneCards and OMIM databases. We then constructed protein-protein interaction (PPI) networks using STRING and visualised them in Cytoscape to identify core targets. Molecular docking simulations using CB-Dock2 elucidated the binding affinities between MEP and the key proteins. Experimental validation combined Gene Expression Omnibus (GEO) database analysis with quantitative reverse transcription polymerase chain reaction (qRT-PCR) to quantify transcriptional changes in SK-N-SH neural cells.

Results: A total of 153 potential targets associated with MEP and AD were identified. Ten core targets were determined through screening using the STRING platform and Cytoscape software, including HIF1A, IGF1R, PDGFRB, PTK2, VCAM1, CXCL12, ERBB2, ESR1, JAK2 and BCL2L1. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed that the core MEP targets in AD primarily concentrate on the following key signalling pathways: Neuroactive ligand-receptor interactions, EGFR tyrosine kinase inhibitor resistance, HIF-1 signalling pathway and gamma-aminobutyric acid (GABA) synapse. Molecular docking simulations using CB-Dock2 confirmed a high binding affinity between MEP and these core targets. To investigate the mechanism of action of MEP, we validated the findings using clinical datasets and the human neuroblastoma cell line SK-N-SH. Upregulation of ten transcriptional expressions was observed, suggesting that MEP might influence cognitive function in patients with AD.

Conclusion: This study elucidated the potential molecular mechanisms of MEP in the progression of Alzheimer's disease-related tau pathology, offering new insights for the prevention and intervention of degenerative diseases that might be triggered by excessive exposure to MEP environments.

Objective: Cholesterol, High-density lipoprotein, and Glucose (CHG) index has recently been proposed as a marker of metabolic dysfunction. However, the association of CHG and CHG modified indices with the risk of stroke remains unclear.

Methods: We analyzed 8908 participants aged 45 years or older from the CHARLS. Baseline CHG and its modified forms (CHG-WC, CHG-BMI, CHG-BRI, CHG-WWI, CHG-WHtR, CHG-ABSI, and CHG-CVAI) were collected. Kaplan-Meier curves, Cox proportional hazards models, and restricted cubic spline (RCS) analyses were applied to assess associations with incident stroke.

Results: During a 9-year follow-up period, 828 (9.3%) participants had occurred strokes. Our analysis found a significant positive association between CHG, CHG-WC, CHG-BMI, CHG-BRI, CHG-WWI, CHG-WHtR, CHG-ABSI, CHG-CVAI, with stroke risk. The adjusted HR for the highest quartile compared to the lowest were: CHG 1.57 (95% CI:1.18-2.10), CHG-WC 1.72 (95% CI:1.34-2.20), CHG-BMI 1.62 (95% CI:1.26-2.08), CHG-BRI 1.65 (95% CI:1.29-2.10), CHG-WWI 1.71 (95% CI:1.32-2.23), CHG-WHtR 1.67 (95% CI:1.29-2.16), CHG-ABSI 1.41 (95% CI:1.10-1.80), and CHG-CVAI 1.99 (95% CI:1.54-2.57), with CHG-CVAI showing strongest associations. The RCS revealed a significant linear association between CHG, CHG-WC, CHG-BMI, and CHG-CVAI with the risk of stroke, whereas CHG-BRI, CHG-WWI, CHG-WHtR, and CHG-ABSI showed significant nonlinear associations with stroke risk. According to ROC analysis, CHG-CVAI had the highest predictive power for stroke risk (C-index:0.618).

Conclusions: Elevated CHG and its modified indices were strongly associated with stroke risk in middle-aged and older Chinese populations. CHG-related indices combined with obesity measures may help enhance the identification of individuals at higher risk of stroke.