Behavioural Neurology最新文献

Objectives: To investigate the efficacy of sustained-release fampridine tablets (fampridine-SR) on walking impairment and fatigue on Chinese patients with multiple sclerosis (MS).

Methods: All patients (n = 12) had the baseline Expanded Disability Status Scale (EDSS) at 4-7 and orally administered fampridine-SR at 10 mg twice per day for at least 12 weeks. All patients were assessed using EDSS, Timed 25-Foot Walk (T25FW), the 12-item Multiple Sclerosis Walking Scale (MSWS-12), and Modified Fatigue Impact Scale (MFIS) at baseline, day 1, week 1, 2, 4, 8, and 12.

Results: The baseline EDSS score was 4.67 ± 0.36. Fampridine-SR significantly decreased the EDSS score by 0.63 ± 0.20 (p = 0.011) after 12-week treatment. T25FW was changed at day 1 and week 1 by - 12.73 ± 3.03% and - 14.20 ± 4.36% (p < 0.011), respectively. The statistically and clinically significant improvement of MSWS-12 was observed since week 1. The total, cognitive subscale, physical subscale, and psychosocial subscale of MFIS were significantly reduced in Chinese patients with MS.

Conclusion: Fampridine-SR was a fast-acting oral potassium channel blocker on improving walking ability of MS as early as day 1. It demonstrated the positive effects on walking impairment and fatigue, including the physical, cognitive, and psychosocial subscales of MFIS, in Chinese patients with MS.

Epilepsy is a long-lasting neurological condition often associated with cognitive and behavioral comorbidities, such as anxiety, depression, and memory deficits. This study examined the therapeutic effect of topiramate (TPM) and brivaracetam (BRV), both separately and combined, using pentylenetetrazole-kindled mice. Seizure severity was visually observed during the kindling process. After that, mice underwent a series of behavioral tests to evaluate anxiety, depression, and memory performance. Subsequently, neurochemical analyses were performed to assess cholinergic activity and oxidative stress markers. The TPM + BRV group showed significantly attenuated seizure progression during all PTZ doses (p < 0.001), with an 88.4% reduction in seizure scores compared to monotherapies. PTZ-kindled mice showed marked behavioral impairments and biochemical imbalances, including elevated oxidative stress and acetylcholinesterase activity. While monotherapy with BRV or TPM displayed partial improvements, combined therapy provided significantly greater effects, enhancing central explorations (152% and 259.6%), sociability (195.2%), memory retention (508.4% for discrimination index and 463.9% for aversive awareness), and reducing depressive-like behaviors (52.7%-73.7%). Biochemically, the combined treatment restored antioxidant enzyme levels (SOD, CAT, and GPx) by 45%-70% and significantly lowered MDA levels (70.7%) and restored SOD activity (220.9%). These findings suggest that low-dose rational polytherapy with TPM and BRV may enhance seizure control and ameliorate associated neuropsychiatric and oxidative imbalance.

Alzheimer's disease (AD) is a chronic progressive neurodegenerative disease characterized by amyloid β (Aβ) plaques and neurofibrillary tangles (NFTs) as its main pathological features. It mainly manifests as cognitive dysfunction, and its pathological process may occur before symptom onset. However, the current drugs and methods for treating AD have unsatisfactory therapeutic outcomes. Therefore, finding a treatment that can inhibit the progression of AD by targeting its pathological features is an urgent need. This review summarizes the current traditional drugs that can delay the progression of AD and new drugs that act on the pathological characteristics of AD and highlights the potential value of related plant extracts. In addition, this review explores the application of different vectors, such as viral vectors and nanoparticles, in gene therapy and drug delivery. These data will provide novel ideas for new drug development and the search for new therapeutic mechanisms.

Background: Stroke is the sixth leading cause of death and lifelong disability for millions of people in the United States. Cerebral ischemia leads to oxidative stress, excitotoxicity, inflammation, and apoptosis; additionally, impairment in memory and learning occurs in the majority of subjects with ischemic stroke. The lack of definitive treatment has sparked extensive research into novel therapeutic strategies, including the use of 4-methylumbelliferone (4-MU), a coumarin derivative with potential neuroprotective properties. The present study examines the impact of 4-MU on reducing cerebral ischemia-reperfusion (I/R) injury and learning and memory impairments in male Wistar rats.

Methods: Animals were exposed to middle cerebral artery occlusion (MCAO) and treated with a single dose of 4-MU (25 mg/kg) dissolved in 0.9% DMSO. An automated shuttle box and Morris water maze (MWM) tests were employed to evaluate learning and memory impairments. Western blot assay, TTC staining, and Nissl staining were used to measure protein expression, infarct volume, and cell death, respectively.

Results: Treatment with 4-MU reduced infarct volume and improved learning and memory impairments by downregulating HAS1 and HAS2. 4-MU modulated the release of proinflammatory cytokines including TNF-α and IL-1β, as well as anti-inflammatory markers like IL-10, and reduced oxidative stress markers in the brain.

Conclusion: The neuroprotective effects of 4-MU against cerebral I/R injury can be attributed to the downregulation of HAS1 and HAS2.

Background: Secondhand smoke exposure (SHSE) remains widespread in China and may be linked to mental health outcomes, yet evidence among older adults is limited. We examined the association between SHSE and depressive symptoms in a large cohort of nonsmoking older Chinese adults.

Methods: We conducted a cross-sectional analysis of 7958 nonsmoking participants aged 50 years or older from the Guangzhou Biobank Cohort Study. SHSE was assessed through structured interviews and quantified as cumulative exposure (in years at 40 h/week) and by context (home and workplace). Depressive symptoms were measured using the 15-item Geriatric Depression Scale (GDS-15). Linear regression models were used to examine associations between SHSE and GDS-15 scores, adjusting for age, sex, education, occupation, income, physical activity, and alcohol use.

Results: Higher cumulative SHSE was associated with greater depressive symptom severity. Participants with more than 5 years of exposure had significantly higher GDS-15 scores than those with less than 2 years (adjusted β 0.21, 95% CI 0.09-0.32; p < 0.001). Workplace exposure was independently associated with higher GDS-15 scores (β 0.23, 95% CI 0.08-0.38), while the association for home exposure was weaker and nonsignificant after adjustment. A greater number of smokers and higher frequency of SHSE at home were also linked to elevated GDS-15 scores. No associations were observed with childhood exposure.

Conclusion: Among older nonsmoking adults, prolonged SHSE, particularly in workplace settings, showed a positive association with depressive symptom severity, although the direction of this association cannot be determined. These cross-sectional associations warrant investigation in prospective studies to determine whether SHSE exposure precedes depression onset and whether the relationship is causal or reflects shared risk factors.

Schizophrenia (SZ) is categorized as a chronic severe highly heritable brain disease. Symptoms include positive, negative, and cognitive symptoms. Despite numerous theories concerning the etiopathogenesis of SZ, the symptoms, although characteristic in their phenomenology, manifest themselves in a rather heterogeneous manner, which makes them subject to clinical assessment and, at the same time, prone to errors resulting from diverse interpretations of the context of the patient's statements. Therefore, current research is focusing on identifying more subtle and stable features of SZ, such as the phenotype, endophenotype, and assessable abnormalities devoid of human clinical observation. The various biomarker developments focus on the role of transmitters and their corresponding receptors, in particular: glutamate, acetylcholine, dopamine, or serotonin. Also important in terms of etiopathogenesis remain growth factors such as brain-derived neurotrophic factor (BDNF), nerve growth factor receptor (NGFR), or vascular endothelial growth factor (VEGF). More recently, research has emphasized the role of inflammatory processes and secreted pro- as well as anti-inflammatory cytokines, included in the class of interleukins, chemokines, and tumor necrosis factors, as well as on inflammatory markers-C-reactive protein (CRP) or glutathione (GSH). Increasingly, changes at the genetic level have been implicated as the cause of diseases, and it is now believed that noncoding RNAs (micro-RNA [miRNA], long noncoding RNA [lnc-RNA], and circular RNA [circRNA]) are involved in the development of SZ. Among the genes that may prove to be potential biomarkers in SZ belong SEDT1A, FOXP2, GRIN2A, GRIA3, NRN1, BDNF, CACNA1C, and ZNF8A4. The peptide group molecules, Phospholipase A2, Klotho protein, and soluble urokinase plasminogen activator receptor (suPAR), also remain consistently important. From the perspective of SZ as a disease associated with neuronal damage, biomarkers correlating with brain injury, neuron-specific enolase (NSE), and S100B protein should be considered.

Neurological disorders frequently result in diverse forms of abnormal movement. Conventional clinical assessment approaches often lack the precision and objectivity needed to evaluate muscle involvement and associated functional limitations. With the development of various intelligent assessment devices, technologies such as wearable sensors, motion capture, radar, and imaging technology, which are based on myoelectricity, kinematics, mechanics, and optics, combined with mathematical models and algorithms, have been widely used for abnormal movement recognition. These technologies further improve the accuracy and validity of clinical evaluation. In this paper, we review the latest advances in intelligent technologies that help clinicians qualitatively and quantitatively assess abnormal movement patterns and carry out personalized rehabilitation treatment. Our work was also aimed at summarizing the research and application of intelligent assessment techniques.

[This corrects the article DOI: 10.1155/2024/9945392.].

Apathy is a prevalent yet frequently underrecognized neuropsychiatric syndrome characterized by diminished motivation and reduced goal-directed behavior across multiple domains. It is strongly associated with poorer functional outcomes, increased caregiver burden, and decreased quality of life in various neuropsychiatric conditions. Despite its clinical importance, apathy remains underdiagnosed and undertreated, partly due to overlapping features with depression and cognitive impairment. This narrative review synthesizes current knowledge on conceptualization, neurobiological mechanisms, diagnostic criteria, and management strategies for apathy, adopting a transdiagnostic perspective across disorders such as Alzheimer's disease, Parkinson's disease, frontotemporal dementia, multiple sclerosis, and major psychiatric conditions. This review distinguishes itself by integrating subtype-based approaches, biomarker insights, and emerging digital tools, providing a framework for more precise characterization and personalized intervention. This review is based on a nonsystematic literature search conducted in PubMed, Scopus, and Google Scholar for articles published between 2011 and 2025. Improved characterization and management of apathy are essential for optimizing patient outcomes, reducing caregiver burden, and guiding future research.

Temporary disturbances in brain function are caused by epilepsy, a chronic disorder resulting from sudden abnormal firing of brain neurons. This research introduces an innovative real-time methodology representing detecting epileptic spasms from electroencephalogram (EEG) data. It employs a support vector machine (SVM) alongside embedded zero tree wavelet (EZW) transform. To facilitate precise multiresolution analysis of epileptic convulsions, the EZW method is selected for its capacity to efficiently compress multichannel EEG data while preserving crucial diagnostic features. EZW effectively captures and encodes key patterns in EEG signals, enabling detailed analysis of the subtle variations associated with seizures. This study extracts statistical features such as entropy, kurtosis, skewness, and mean from the compressed EEG segments. These features are then classified using the SVM to distinguish between normal and epileptic states. With a remarkable 99.02% classification accuracy and a false positive rate of only 1.1%, the proposed algorithm demonstrates excellent performance. The novelty lies in integrating SVM with EZW-based feature extraction and advanced preprocessing, enabling efficient real-time EEG analysis. Unlike previous works, this approach preserves critical information, enhances classification accuracy, and supports multichannel signals, offering a robust and practical solution for real-time epilepsy detection. Based on these findings, the method is considered highly suitable for real-time implementation in clinical environments.