Diagnosis Of Neurological Disorders Research Articles

Frontal Horn of Lateral Ventricle of Brain and Its Relation with Age, Gender and Side: Morphometric Study by Computed Tomography among Bangladeshi Population

Background: Knowledge of the baseline reference value of frontal horn size is necessary for the initial and precise analysis of ventriculomegaly. The purpose of this study was to determine the size of frontal horn of lateral ventricle and its relation with age, gender and side among adult Bangladeshi population of Chattogram district. Materials and methods: This cross-sectional analytical study was conducted during the period from July 2022 to June 2023 in the Department of Anatomy, Chittagong Medical College, Chattogram, upon 150 respondents of 20-60 years who had normal Computed Tomography (CT) scans as reported by an expert radiologist. For statistical analysis, Mann-Whitney U test, Wilcoxon signed rank test and ANOVA test were done. p-value was considered significant if it was <0.05 at 95% level of confidence. Results: The mean right and left frontal horn length was 25.50 (±3.95) mm and 25.28 (±4.04) mm respectively. The length of the frontal horn of both right and left sided lateral ventricle were significantly higher in male than that of female (p<0.01). Spearman's correlation coefficient indicated positive linear correlation of length of frontal horn (Right and left side) with age, insignificant in right side (p=0.061) but significant in left side (p=0.046). Conclusion: Morphometric analysis of the frontal horn of the lateral ventricles among the Bangladeshi population produced a number of significant results that may help with the early diagnosis and treatment of neurological diseases that are particular to gender and age. These findings can be validated and expanded upon in future research using bigger sample sizes and cutting-edge imaging methods. IAHS Medical Journal Vol 7(1), June 2024; 54-59

Effectiveness and safety of therapeutic plasma exchange in neurological diseases: An 11-year report from a tertiary care center.

Therapeutic plasma exchange has been a well-known treatment method for many years and is widely available. It leads to the improvement of neurological symptoms in autoimmune neurological diseases by the removal of antibodies. The aim of this study was to present therapeutic plasma exchange responses and procedure-related adverse events in patients with autoimmune neurological diseases based on our 11-year experience. A retrospective evaluation was conducted on adult patients who underwent a therapeutic plasma exchange procedure due to neurological diseases between January 2013 and January 2024. Data were gathered from electronic and written hospital and apheresis unit records. A total of 265 patients underwent 1274 procedures with a preliminary diagnosis of autoimmune neurological disease. Five patients were excluded from the analysis due to their final diagnoses. The most common clinical indications were Guillain-Barré syndrome (45.4%), myasthenia gravis (26.1%), and multiple sclerosis (19.2%). The overall response rate was 81.3%, with 21.7% exhibiting a complete response and 59.6% demonstrating a partial response. With the exception of one patient (hypertensive crisis), no complications necessitating the termination of the procedure were observed. The most prevalent complication was an easily manageable allergic reaction. Therapeutic plasma exchange has been demonstrated to be an efficacious and safe treatment option in autoimmune neurological diseases, with a favorable overall response rate and a manageable mild-to-moderate side effect profile.

Laser-induced stripping defect for highly selective electrochemical quantification of dopamine: Anti-interference from other catecholamine neurotransmitters

Detecting dopamine (DA) is critical for early diagnosis of neurological and psychiatric disorders. However, the presence of other catecholamine neurotransmitters with structural similarities to DA causes significant interference in its detection. Herein, we introduce S stripping defects via laser-induced MoS2 to functionalize MoS2 electrodes and improve their selectivity for DA electrochemical detection. The sensing results show its excellent immunity to interference from other neurotransmitters, ensuring the preservation of the DA electrochemical signal even in the mixed neurotransmitters such as acetylcholine (ACh), γ-aminobutyric acid (GABA), epinephrine (EP), norepinephrine (NP), and serotonin (5-HT). DFT calculations further reveal that the negatively charged S-stripping defects enhance DA adsorption on the surface of the functionalized MoS2 electrode, contributing to its excellent performance. Moreover, this functionalized electrodes successfully monitor DA released from living PC12 cells in the presence of other interference, highlighting its potential applicability in intercellular signaling communication.

Astrocytes and Memory: Implications for the Treatment of Memory-related Disorders.

Memory refers to the imprint accumulated in the brain by life experiences and represents the basis for humans to engage in advanced psychological activities such as thinking and imagination. Previously, research activities focused on memory have always targeted neurons. However, in addition to neurons, astrocytes are also involved in the encoding, consolidation, and extinction of memory. In particular, astrocytes are known to affect the recruitment and function of neurons at the level of local synapses and brain networks. Moreover, the involvement of astrocytes in memory and memory-related disorders, especially in Alzheimer's disease (AD) and post-traumatic stress disorder (PTSD), has been investigated extensively. In this review, we describe the unique contributions of astrocytes to synaptic plasticity and neuronal networks and discuss the role of astrocytes in different types of memory processing. In addition, we also explore the roles of astrocytes in the pathogenesis of memory-related disorders, such as AD, brain aging, PTSD and addiction, thus suggesting that targeting astrocytes may represent a potential strategy to treat memory-related neurological diseases. In conclusion, this review emphasizes that thinking from the perspective of astrocytes will provide new ideas for the diagnosis and therapy of memory-related neurological disorders.

MRI and CT compatible asymmetric bilayer hydrogel electrodes for EEG-based brain activity monitoring

The exploration of multi-dimensional brain activity with high temporal and spatial resolution is of great significance in the diagnosis of neurological disease and the study of brain science. Although the integration of electroencephalogram (EEG) with magnetic resonance imaging (MRI) and computed tomography (CT) provides a potential solution to achieve a brain-functional image with high spatiotemporal resolution, the critical issues of interface stability and magnetic compatibility remain challenging. Therefore, in this research, we proposed a conductive hydrogel EEG electrode with an asymmetrical bilayer structure, which shows the potential to overcome the challenges. Benefiting from the bilayer structure with different moduli, the hydrogel electrode exhibits high biological and mechanical compatibility with the heterogeneous brain-electrode interface. As a result, the impedance can be reduced compared with conventional metal electrodes. In addition, the hydrogel-based ionic conductive electrodes, which are free from metal conductors, are compatible with MRI and CT. Therefore, they can obtain high spatiotemporal resolution multi-dimensional brain information in clinical settings. The research outcome provides a new approach for establishing a platform for early diagnosis of brain diseases and the study of brain science.

Fluorescence imaging of dopamine in living cells triggered by unique coupling reactions

BackgroundDopamine (DA) is a significant neurotransmitter and catecholamine molecule in the mammalian brain. It plays a crucial role in perception, cognition, central nervous system regulation, and hormone secretion. The detection of DA levels in living systems is a vital aspect of the research and early diagnosis of neurological disorders. ResultsIn this study, we achieved an effective fluorescence generation specific to DA under physiological pH conditions by coupling the DA detection reaction to the HClO oxidation reaction. This method has been used for the detection of DA in cells, as well as for the visualization of DA levels in cellular models of inflammation and depression. SignificanceThis is the first time that utilizes an organic fluorescent molecular probe to detect DA in living cells.

Towards Transforming Neurorehabilitation: The Impact of Artificial Intelligence on Diagnosis and Treatment of Neurological Disorders.

Background and Objectives: Neurological disorders like stroke, spinal cord injury (SCI), and Parkinson's disease (PD) significantly affect global health, requiring accurate diagnosis and long-term neurorehabilitation. Artificial intelligence (AI), such as machine learning (ML), may enhance early diagnosis, personalize treatment, and optimize rehabilitation through predictive analytics, robotic systems, and brain-computer interfaces, improving outcomes for patients. This systematic review examines how AI and ML systems influence diagnosis and treatment in neurorehabilitation among neurological disorders. Materials and Methods: Studies were identified from an online search of PubMed, Web of Science, and Scopus databases with a search time range from 2014 to 2024. This review has been registered on Open OSF (n) EH9PT. Results: Recent advancements in AI and ML are revolutionizing motor rehabilitation and diagnosis for conditions like stroke, SCI, and PD, offering new opportunities for personalized care and improved outcomes. These technologies enhance clinical assessments, therapy personalization, and remote monitoring, providing more precise interventions and better long-term management. Conclusions: AI is revolutionizing neurorehabilitation, offering personalized, data-driven treatments that enhance recovery in neurological disorders. Future efforts should focus on large-scale validation, ethical considerations, and expanding access to advanced, home-based care.

Clinical Applications of Micro/Nanobubble Technology in Neurological Diseases.

Nanomedicine, leveraging the unique properties of nanoparticles, has revolutionized the diagnosis and treatment of neurological diseases. Among various nanotechnological advancements, ultrasound-mediated drug delivery using micro- and nanobubbles offers promising solutions to overcome the blood-brain barrier (BBB), enhancing the precision and efficacy of therapeutic interventions. This review explores the principles, current clinical applications, challenges, and future directions of ultrasound-mediated drug delivery systems in treating stroke, brain tumors, neurodegenerative diseases, and neuroinflammatory disorders. Additionally, ongoing clinical trials and potential advancements in this field are discussed, providing a comprehensive overview of the impact of nanomedicine on neurological diseases.

Enhanced Neonatal Brain Tissue Analysis via Minimum Spanning Tree Segmentation and the Brier Score Coupled Classifier

Automatic assessment of brain regions in an MR image has emerged as a pivotal tool in advancing diagnosis and continual monitoring of neurological disorders through different phases of life. Nevertheless, current solutions often exhibit specificity to particular age groups, thereby constraining their utility in observing brain development from infancy to late adulthood. In our research, we introduce a novel approach for segmenting and classifying neonatal brain images. Our methodology capitalizes on minimum spanning tree (MST) segmentation employing the Manhattan distance, complemented by a shrunken centroid classifier empowered by the Brier score. This fusion enhances the accuracy of tissue classification, effectively addressing the complexities inherent in age-specific segmentation. Moreover, we propose a novel threshold estimation method utilizing the Brier score, further refining the classification process. The proposed approach yields a competitive Dice similarity index of 0.88 and a Jaccard index of 0.95. This approach marks a significant step toward neonatal brain tissue segmentation, showcasing the efficacy of our proposed methodology in comparison to the latest cutting-edge methods.

Robust, fast and accurate mapping of diffusional mean kurtosis

Diffusional kurtosis imaging (DKI) is a methodology for measuring the extent of non-Gaussian diffusion in biological tissue, which has shown great promise in clinical diagnosis, treatment planning, and monitoring of many neurological diseases and disorders. However, robust, fast, and accurate estimation of kurtosis from clinically feasible data acquisitions remains a challenge. In this study, we first outline a new accurate approach of estimating mean kurtosis via the sub-diffusion mathematical framework. Crucially, this extension of the conventional DKI overcomes the limitation on the maximum b-value of the latter. Kurtosis and diffusivity can now be simply computed as functions of the sub-diffusion model parameters. Second, we propose a new fast and robust fitting procedure to estimate the sub-diffusion model parameters using two diffusion times without increasing acquisition time as for the conventional DKI. Third, our sub-diffusion-based kurtosis mapping method is evaluated using both simulations and the Connectome 1.0 human brain data. Exquisite tissue contrast is achieved even when the diffusion encoded data is collected in only minutes. In summary, our findings suggest robust, fast, and accurate estimation of mean kurtosis can be realised within a clinically feasible diffusion-weighted magnetic resonance imaging data acquisition time.

Robust, fast and accurate mapping of diffusional mean kurtosis.

Diffusional kurtosis imaging (DKI) is a methodology for measuring the extent of non-Gaussian diffusion in biological tissue, which has shown great promise in clinical diagnosis, treatment planning, and monitoring of many neurological diseases and disorders. However, robust, fast, and accurate estimation of kurtosis from clinically feasible data acquisitions remains a challenge. In this study, we first outline a new accurate approach of estimating mean kurtosis via the sub-diffusion mathematical framework. Crucially, this extension of the conventional DKI overcomes the limitation on the maximum b-value of the latter. Kurtosis and diffusivity can now be simply computed as functions of the sub-diffusion model parameters. Second, we propose a new fast and robust fitting procedure to estimate the sub-diffusion model parameters using two diffusion times without increasing acquisition time as for the conventional DKI. Third, our sub-diffusion-based kurtosis mapping method is evaluated using both simulations and the Connectome 1.0 human brain data. Exquisite tissue contrast is achieved even when the diffusion encoded data is collected in only minutes. In summary, our findings suggest robust, fast, and accurate estimation of mean kurtosis can be realised within a clinically feasible diffusion-weighted magnetic resonance imaging data acquisition time.

482P Closing the gap in diagnosis of neuropathies and late-onset neurological disorders – a trans-Australia collaboration

482P Closing the gap in diagnosis of neuropathies and late-onset neurological disorders – a trans-Australia collaboration

Discussion on Magnetic Resonance Compatibility of Implantable Brain-Computer Interface Devices

Brain-computer interface (BCI) devices are crucial tools for neural stimulation and recording, offering broad prospects in the diagnosis and treatment of neurological disorders. Furthermore, magnetic resonance imaging (MRI) is an effective and non-invasive technique for capturing whole-brain signals, providing detailed information on brain structures and activation patterns. Integrating the neural stimulation/recording capabilities of BCI devices with the non-invasive detection function of MRI is considered highly significant for brain function analysis. However, this combination imposes specific requirements on the magnetic and electronic performance of neural interface devices. The interaction between BCI devices and MRI is initially explored. Subsequently, potential safety risks arising from their combination are summarized and organized. Starting from the source of these hazards, such as the metallic electrodes and wires of BCI devices, the issues are analyzed, and current research countermeasures are summarized. In conclusion, the regulatory oversight of BCI's magnetic resonance safety is briefly discussed, and suggestions for enhancing the magnetic resonance compatibility of related BCI devices are proposed.

Neural Dynamics Associated with Biological Variation in Normal Human Brain Regions.

The processes involved in encoding and decoding signals in the human brain are a continually studied topic, as neuronal information flow involves complex nonlinear dynamics. This study examines awake human intracranial electroencephalography (iEEG) data from normal brain regions to explore how biological sex influences these dynamics. The iEEG data were analyzed using permutation entropy and statistical complexity in the time domain and power spectrum calculations in the frequency domain. The Bandt and Pompe method was used to assess time series causality by associating probability distributions based on ordinal patterns with the signals. Due to the invasive nature of data acquisition, the study encountered limitations such as small sample sizes and potential sources of error. Nevertheless, the high spatial resolution of iEEG allows detailed analysis and comparison of specific brain regions. The results reveal differences between sexes in brain regions, observed through power spectrum, entropy, and complexity analyses. Significant differences were found in the left supramarginal gyrus, posterior cingulate, supplementary motor cortex, middle temporal gyrus, and right superior temporal gyrus. This study emphasizes the importance of considering sex as a biological variable in brain dynamics research, which is essential for improving the diagnosis and treatment of neurological and psychiatric disorders.

Insights from a Wolfram syndrome cohort: clinical and molecular findings from a specialized diabetes reference center.

Considering the rarity and clinical and molecular diversity of Wolfram syndrome (WS), the objective of this study was to identify patients with a clinical presentation suggestive of WS following up at a single Brazilian diabetes service and analyze their clinical and molecular characteristics. The study included all patients with a clinical presentation of WS following up between 1991 and 2022 with early-onset diabetes mellitus and other WS signs and symptoms. A retrospective analysis was conducted, including patients' age, sex, consanguinity, age at symptom onset, diagnosis of diabetes mellitus, optic atrophy, diabetes insipidus, neurological and psychiatric disorders, hearing loss, urinary disorders, hypogonadism, and WFS1 molecular analysis. Eight patients were identified, all of whom were diagnosed with diabetes mellitus at an average age of 3.7 years. Optic atrophy, diabetes insipidus, and hearing loss were common, while psychiatric and neurological alterations were observed in some cases. Genetic analysis revealed pathogenic variants in homozygosity or compound heterozygosity. The most frequent variant was p. Val412Serfs29, present in five of the seven families. This study represents the second-largest Brazilian sample of WS and is the first cohort from a single center in Southeast Brazil. The patients had an early, severe, and complete clinical presentation. The genetic variants identified were consistent with previous literature descriptions. The variant p. Val412Serfs29 was particularly common in this cohort, highlighting its relevance in the region.

Comprehensive EEG Signal Feature Extraction for Neurological Disorder Diagnosis: Focus on Alzheimer's, Parkinson's, and Seizure Disorders

This research paper examines the use of Electroencephalogram (EEG) signal feature extraction for diagnosing neurological disorders, specifically Alzheimer's, Parkinson's, and seizure disorders. It evaluates various methods for categorizing EEG signals, including time-domain, frequency-domain, and statistical transformations emphasizing their effectiveness in distinguishing relevant brainwave patterns (beta, alpha, theta, delta) from artifacts like eye blinks and muscle movements. The study highlights the challenges in artifact removal and provides an overview of key feature extraction techniques, particularly in the time and frequency domains. The implementation section details the application of machine learning algorithms to classify mental states using statistical features from EEG signals. The research identifies specific EEG patterns associated with Alzheimer's, Parkinson's, and seizure disorders, noting alterations in alpha, theta, and delta waves. The paper underscores the critical role of EEG feature extraction in diagnosing neurological disorders and recommends incorporating additional frequency-based methods to enhance predictive accuracy in future research.

Ultrasensitive Detection of Dimethylamine Gas for Early Diagnosis of Parkinson's Disease Using CeO2-Coated Ti3C2Tx MXene/Carbon Nanofibers.

Parkinson's disease is a prevalent neurological disorder, with dimethylamine (DMA) recognized as a crucial breath biomarker, particularly at the parts per billion (ppb) level. Detecting DMA gas at this level, especially at room temperature and high humidity, remains a formidable challenge. This study presents an ultrasensitive chemiresistor DMA gas sensor, leveraging the CeO2-coated Ti3C2Tx MXene/carbon nanofiber (CeO2/MXene/C NFs) heterostructure to enhance dimethylamine sensing. The high conductivity of MXene, combined with C-Ti-O bonds and a sp2 hybridized hexagonal carbon structure, increases surface active sites. The presence of Ce3+ promotes the formation of surface-active oxygen species, while the MXene-CeO2 heterojunction broadens the electron depletion layer. Theoretical calculations reveal that the highest adsorption energy for DMA gas is at the Ce top site, explaining the sensor's satisfactory sensitivity, rapid response and recovery process, low detection limit (5 ppb), and high selectivity at room temperature. The Ce3+/Ce4+ dynamic self-refresh mechanism, involving surface hydroxyl elimination, enhances the sensor's performance under high-humid conditions. Clinical breath tests demonstrate the sensor's ability to distinguish between healthy individuals and Parkinson's disease patients, paving the way for developing next-generation sensors for early diagnosis of neurological disorders.

Report of an unusual association of Oropouche Fever with Guillain-Barré syndrome in Cuba, 2024.

Oropouche virus is the aetiological agent of Oropouche fever. At present, this is currently considered one of the most important vector-borne diseases in Latin America. On 27 May 2024, the Ministry of Public Health of Cuba reported the first ever outbreak of Oropouche fever. In this report, we describe three human cases of Oropouche virus infection with symptoms and signs of neurological disease and clinical diagnosis of Guillain-Barré Syndrome. This study offers insights regarding that Oropouche virus is a causal agent of neurological disorders and it could be involved in the etiology of the Guillain-Barré Syndrome.

Incidence and pattern of neurological emergencies in Ramadan

ABSTRACT Background The impact of Ramadan fasting on various neurological emergencies remains relatively unexplored. This study aimed to clarify the incidence and pattern of the different neurological emergencies in Ramadan compared to Shaaban. Methods In this cross-sectional study, all adult patients attending the emergency room at two Egyptian centers with neurological emergencies during Shaaban and Ramadan were evaluated. Clinical, laboratory, and radiological assessments were made on an individual basis upon which the diagnosis of neurological disorder was made. IBM SPSS Version 25 was used to analyze the data. Results Seventy-twenty patients were included, 382 during Shaaban and 338 during Ramadan. Among causes of delirium, the frequency of dehydration was significantly higher, and the frequency of illicit drug abuse was significantly lower during Ramadan compared to Shaaban (P = 0.004, 0.030, respectively). The incidence of ICH was significantly reduced during Ramadan compared to Shaaban (10.8% vs 19.7%, P = 0.031). The incidence of cardioembolic strokes significantly increased during Ramadan than Shaaban (40.5% vs 26.4%, P = 0.014), whereas the incidence of small vessel disease (SVD) significantly decreased during Ramadan than Shaaban (21.6% vs. 42.1%, P < 0.001). The incidence of a single seizure was significantly higher in Ramadan than in Shaaban (69.4% vs. 34.6%, P = 0.007). The incidence of functional neurological disorders was significantly reduced in Ramadan than in Shaaban (P < 0.001). Conclusion The incidence of delirium caused by illicit drug abuse, ICH, SVD, and functional neurological disorders declined during Ramadan, while the incidence of delirium triggered by dehydration, cardioembolic strokes, and a single seizure increased during Ramadan.

Neuromelanin-targeted 18 F-P3BZA PET/MR imaging of the substantia nigra in rhesus macaques

BackgroundNeuromelanin is mostly located in dopaminergic neurons in the substantia nigra (SN) pars compacta, and can be detected by magnetic resonance imaging (MRI). It is a promising imaging-base biomarker for neurological diseases. We previously developed a melanin-specific probe N-(2-(diethylamino)-ethyl)-18F-5-fluoropicolinamide (18F-P3BZA), which was initially developed for the imaging of melanoma. 18F-P3BZA exhibited high levels of binding to the melanin in vitro and in vivo with high retention and favorable pharmacokinetics. In this study we further investigated whether 18F-P3BZA could be used to quantitatively detect neuromelanin in the SN in healthy rhesus macaques.Results18F-P3BZA exhibited desired hydrophobicity with estimated log Know 5.08 and log D7.4 1.68. 18F-P3BZA readily crossed the blood-brain barrier with brain transport coefficients (Kin) of 40 ± 8 µL g-1s-1. 18F-P3BZA accumulated specifically in neuromelanotic PC12 cells, melanin-rich melanoma cells, and melanoma xenografts. Binding of 18F-P3BZA to B16F10 cells was much higher than to SKOV3 cells at 60 min (6.17 ± 0.53%IA and 0.24 ± 0.05%IA, respectively). In the biodistribution study, 18F-P3BZA had higher accumulation in B16F10 tumors (6.31 ± 0.99%IA/g) than in SKOV3 tumors (0.25 ± 0.09%IA/g). Meanwhile, 18F-P3BZA uptake in B16F10 tumors could be blocked by excess cold 19F-P3BZA (0.81 ± 0.02%IA/g, 88% inhibition, p < 0.05). PET/MRI 18F-P3BZA provided clear visualization of neuromelanin-rich SN at 30–60 min after injection in healthy macaques. The SN to cerebella ratios were 2.7 and 2.4 times higher at 30 and 60 min after injection. In in vitro autoradiography studies 18F-P3BZA exhibited high levels of binding to the SN, and almost no binding to surrounding midbrain tissues.Conclusion18F-P3BZA PET/MRI clearly images neuromelanin in the SN, and may assist in the early diagnosis of neurological diseases associated with abnormal neuromelanin expression.