Diagnosis Of Neurological Disorders Research Articles

The Classification of Movement in Infants for the Autonomous Monitoring of Neurological Development

Neurodevelopmental delay following extremely preterm birth or birth asphyxia is common but diagnosis is often delayed as early milder signs are not recognised by parents or clinicians. Early interventions have been shown to improve outcomes. Automation of diagnosis and monitoring of neurological disorders using non-invasive, cost effective methods within a patient’s home could improve accessibility to testing. Furthermore, said testing could be conducted over a longer period, enabling greater confidence in diagnoses, due to increased data availability. This work proposes a new method to assess the movements in children. Twelve parent and infant participants were recruited (children aged between 3 and 12 months). Approximately 25 min 2D video recordings of the infants organically playing with toys were captured. A combination of deep learning and 2D pose estimation algorithms were used to classify the movements in relation to the children’s dexterity and position when interacting with a toy. The results demonstrate the possibility of capturing and classifying children’s complexity of movements when interacting with toys as well as their posture. Such classifications and the movement features could assist practitioners to accurately diagnose impaired or delayed movement development in a timely fashion as well as facilitating treatment monitoring.

Somatosensory Event-Related Potential as an Electrophysiological Correlate of Endogenous Spatial Tactile Attention: Prospects for Electrotactile Brain-Computer Interface for Sensory Training.

Tactile attention tasks are used in the diagnosis and treatment of neurological and sensory processing disorders, while somatosensory event-related potentials (ERP) measured by electroencephalography (EEG) are used as neural correlates of attention processes. Brain-computer interface (BCI) technology provides an opportunity for the training of mental task execution via providing online feedback based on ERP measures. Our recent work introduced a novel electrotactile BCI for sensory training, based on somatosensory ERP; however, no previous studies have addressed specific somatosensory ERP morphological features as measures of sustained endogenous spatial tactile attention in the context of BCI control. Here we show the morphology of somatosensory ERP responses induced by a novel task introduced within our electrotactile BCI platform i.e., the sustained endogenous spatial electrotactile attention task. By applying pulsed electrical stimuli to the two proximal stimulation hotspots at the user's forearm, stimulating sequentially the mixed branches of radial and median nerves with equal probability of stimuli occurrence, we successfully recorded somatosensory ERPs for both stimulation locations, in the attended and unattended conditions. Waveforms of somatosensory ERP responses for both mixed nerve branches showed similar morphology in line with previous reports on somatosensory ERP components obtained by stimulation of exclusively sensory nerves. Moreover, we found statistically significant increases in ERP amplitude on several components, at both stimulation hotspots, while sustained endogenous spatial electrotactile attention task is performed. Our results revealed the existence of general ERP windows of interest and signal features that can be used to detect sustained endogenous tactile attention and classify between spatial attention locations in 11 healthy subjects. The current results show that features of N140, P3a and P3b somatosensory ERP components are the most prominent global markers of sustained spatial electrotactile attention, over all subjects, within our novel electrotactile BCI task/paradigm, and this work proposes the features of those components as markers of sustained endogenous spatial tactile attention in online BCI control. Immediate implications of this work are the possible improvement of online BCI control within our novel electrotactile BCI system, while these finding can be used for other tactile BCI applications in the diagnosis and treatment of neurological disorders by employing mixed nerve somatosensory ERPs and sustained endogenous electrotactile attention task as control paradigms.

Study on Catecholamine Sensors Based on Noble Metal Nanoparticles Modified Ti3C2 Mxene

Catecholamines are neurotransmitters in the peripheral and central nervous systems, which maintain the normal physiological state of the human body. Studies have shown that the occurrence of many diseases are often accompanied by changes in catecholamine levels. Clinically, the detection of catecholamine levels in human plasma or urine can assist in the diagnosis of endocrine-related diseases and neurological diseases. However, catecholamines are easily oxidized, and the content in human body is very low. So the rapid detection of catecholamines is very important for the prevention and diagnosis of related diseases. In this paper, the electrochemical response characteristics of Ti3C2Tx MXene and noble metal nanoparticles modified Ti3C2Tx to dopamine (one type of catecholamine) were explored. The results shown that Ti3C2Tx would undergo irreversible oxidation at the anode potential and the single Ti3C2Tx modified electrode was not suitable for the detection of dopamine. So we further explored the modification of Pt and Au nanoparticles on the Ti3C2Tx/GCE electrode, and the experimental results shown that Au/Ti3C2Tx/GCE had higher sensitivity for measuring dopamine, while Pt/Ti3C2Tx/GCE had a larger linear range. Both electrodes had good stability and repeatability and could be used for the detection of catecholamines.

Quantitative and Qualitative Representation of Introductory and Advanced EEG Concepts: An Exploration of Different EEG Setups.

Electroencephalograms (EEGs) are the gold standard test used in the medical field to diagnose epilepsy and aid in the diagnosis of many other neurological and mental disorders. Growing in popularity in terms of nonmedical applications, the EEG is also used in research, neurofeedback, and brain-computer interface, making it increasingly relevant to student learning. Recent innovations have made EEG setups more accessible and affordable, thus allowing their integration into neuroscience educational settings. Introducing students to EEGs, however, can be daunting due to intricate setup protocols, individual variation, and potentially expensive equipment. This paper aims to provide guidance for introducing students and educators to fundamental beginning and advanced level EEG concepts. Specifically, this paper tested the potential of three different setups, with varying channel number and wired or wireless connectivity, for introducing students to qualitative and quantitative exploration of alpha enhancement when eyes are closed, and observation of the alpha/beta anterior to posterior gradient. The setups were compared to determine their relative advantages and their robustness in detecting these well-established parameters. The basic 1- or 2-channel setups are sufficient for observing alpha and beta waves, while more advanced systems containing 8 or 16 channels are required for consistent observation of an anterior-posterior gradient. In terms of localization, the 16-channel setup, in principle, was more adept. The 8-channel setup, however, was more effective than the 16-channel setup with regards to displaying the anterior to posterior gradient. Thus, an 8-channel setup is sufficient in an education setting to display these known trends. Modification of the 16-channel setup may provide a better observation of the anterior to posterior gradient.

Direct Clinical Applications of Natural Language Processing in Common Neurological Disorders: A Systematic Review (P5-4.005)

<h3>Objective:</h3> We sought to evaluate studies that applied natural language processing (NLP) to the diagnosis, prediction, or treatment of common neurological disorders. <h3>Background:</h3> NLP, a branch of artificial intelligence that analyzes unstructured language, is being increasingly utilized in medicine. However, the extent to which NLP has been studied in neurological disorders remains inconsistently characterized. <h3>Design/Methods:</h3> This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards and was registered with the Prospective Register of Systematic Reviews (PROSPERO; CRD42021228703). The search was conducted using MEDLINE and EMBASE on May 11, 2022. We included studies of NLP use in migraine, Parkinson disease, Alzheimer dementia, stroke and transient ischemic attack (TIA), epilepsy, or multiple sclerosis. We excluded non-English language, conference abstract, and review articles, as well as studies involving heterogeneous clinical populations or indirect clinical uses of NLP. Study characteristics were extracted and analyzed using descriptive statistics. <h3>Results:</h3> We identified 916 studies, of which 41 (4.5%), published between 2013 and 2022, were included in the final review. The most studied disorders were stroke and TIA (N=20 studies, 48.8%), followed by epilepsy (N=10, 24.4%), Alzheimer disease (N=6, 14.6%), and multiple sclerosis (N=5, 12.2%). We found no studies of NLP use in migraine or Parkinson disease that met our eligibility criteria. The main objective of NLP was diagnosis (N=20, 48.8%) followed by disease phenotyping (N=17, 41.5%), prognostication (N=9, 22%) and treatment (N=4, 9.8%). Eighteen (43.9%) studies used only machine learning approaches, 6 (14.6%) used only rule-based methods, and 17 (41.5%) used both. <h3>Conclusions:</h3> We found several gaps in neurological NLP research, with few to no studies in certain disorders, suggesting additional areas of inquiry. We observed that NLP was most widely studied in diagnostic applications, implying a potential role for NLP in augmenting diagnostic accuracy in settings with limited access to neurological expertise. <b>Disclosure:</b> Dr. Lefkovitz has nothing to disclose. Ms. Walsh has nothing to disclose. The institution of an immediate family member of Dr. Blank has received personal compensation in the range of $0-$499 for serving as a Consultant for Bristol Myers Squibb (Legal). The institution of Dr. Blank has received research support from American Epilepsy Foundation/Epilepsy Foundation/NORSE Foundation. The institution of Dr. Blank has received research support from NIA (Mount Sinai OAIC). Dr. Jette has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for ILAE Epilepsia. The institution of Dr. Jette has received research support from NIH. The institution of Dr. Jette has received research support from AES. The institution of Dr. Jette has received research support from PCORI. Dr. Kummer has received personal compensation in the range of $500-$4,999 for serving as a Consultant for MD Aware LLC. Dr. Kummer has received personal compensation in the range of $0-$499 for serving as a Consultant for Atheneum Partners. Dr. Kummer has received personal compensation in the range of $0-$499 for serving as a Consultant for AlphaSights. Dr. Kummer has received personal compensation in the range of $0-$499 for serving as a Consultant for Gehrson Lehrman Group . Dr. Kummer has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Syapse. Dr. Kummer has received personal compensation in the range of $0-$499 for serving as a Consultant for NeuraHealth. Dr. Kummer has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Syntrillo. Dr. Kummer has stock in Syntrillo. The institution of Dr. Kummer has received research support from Icahn School of Medicine at Mount Sinai.

Serum neurofilament light chain cut-off definition for clinical diagnosis and prognosis of amyotrophic lateral sclerosis.

The neurofilament light chain (NfL) assay is gradually becoming an essential diagnostic tool for the diagnosis of many neurological diseases including amyotrophic lateral sclerosis (ALS). Different methods for the determination of this biomarker in serum have been developed in recent years. We measured blood NfL in 429 patients referred to the tertiary ALS center of Montpellier, France using two different ultrasensitive methods (Ella™ and Simoa™) and we compared the clinical performances of these two approaches. We also converted NfL values into age and body mass index-adjusted Z-scores to assess cut-off values of this biomarker in this clinical context. We show comparable diagnostic and prognostic performance of Ella™ and Simoa™ technologies in ALS, with specificities and sensitivities exceeding 80% for both. We propose cut-off values for serum NfL in this clinical context, thus enabling the routine clinical use of this biomarker. The use of NfL in routine clinical practice will help predict survival and improve diagnostic accuracy by distinguishing ALS from other neurological diseases and motor neuron disease mimics.

Anti-AGO1 Antibodies Identify a Subset of Autoimmune Sensory Neuronopathy.

Autoantibodies (Abs) improve diagnosis and treatment decisions of idiopathic neurologic disorders. Recently, we identified Abs against Argonaute (AGO) proteins as potential autoimmunity biomarkers in neurologic disorders. In this study, we aim to reveal (1) the frequency of AGO1 Abs in sensory neuronopathy (SNN), (2) titers and IgG subclasses, and (3) their clinical pattern including response to treatment. This retrospective multicentric case/control study screened 132 patients with SNN, 301 with non-SNN neuropathies, 274 with autoimmune diseases (AIDs), and 116 healthy controls (HCs) for AGO1 Abs through ELISA. Seropositive cases were also tested for IgG subclasses, titers, and conformation specificity. AGO1 Abs occurred in 44 patients, comprising significantly more of those with SNN (17/132 [12.9%]) than those with non-SNN neuropathies (11/301 [3.7%]; p = 0.001), those with AIDs (16/274 [5.8%]; p = 0.02), or HCs (0/116; p < 0.0001). Ab titers ranged from 1:100 to 1:100,000. IgG subclass was mainly IgG1, and 11/17 AGO1 Ab-positive SNN (65%) had a conformational epitope. AGO1 Ab-positive SNN was more severe than AGO1 Ab-negative SNN (e.g., SNN score: 12.2 vs 11.0, p = 0.004), and they more frequently and more efficiently responded to immunomodulatory treatments than AGO1 Ab-negative SNN (7/13 [54%] vs 6/37 [16%], p = 0.02). Regarding the type of treatments more precisely, this significant difference was confirmed for the use of IV immunoglobulins (IVIg) but not for steroids or second-line treatments. Multivariate logistic regression adjusted for potential confounders showed that AGO1 Ab positivity was the only predictor of response to treatment (OR 4.93, 1.10-22.24 95% CI, p = 0.03). Although AGO Abs are not specific for SNN, based on our retrospective data, they may identify a subset of cases with SNN with more severe features and a possibly better response to IVIg. The significance of AGO1 Abs in clinical practice needs to be explored on a larger series.

Effect of geometric distortion correction on thickness and volume measurements of cortical parcellations in 3D T1w gradient echo sequences.

Automated brain volumetric analysis based on high-resolution T1-weighted MRI datasets is a frequently used tool in neuroimaging for early detection, diagnosis, and monitoring of various neurological diseases. However, image distortions can corrupt and bias the analysis. The aim of this study was to explore the variability of brain volumetric analysis due to gradient distortions and to investigate the effect of distortion correction methods implemented on commercial scanners. 36 healthy volunteers underwent brain imaging using a 3T magnetic resonance imaging (MRI) scanner, including a high-resolution 3D T1-weighted sequence. For all participants, each T1-weighted image was reconstructed directly on the vendor workstation with (DC) and without (nDC) distortion correction. For each participant's set of DC and nDC images, FreeSurfer was used for the determination of regional cortical thickness and volume. Overall, significant differences were found in 12 cortical ROIs comparing the volumes of the DC and nDC data and in 19 cortical ROIs comparing the thickness of the DC and nDC data. The most pronounced differences for cortical thickness were found in the precentral gyrus, the lateral occipital and postcentral ROI (2.69, -2.91% and -2.79%, respectively) while cortical volumes differed most prominently in the paracentral, the pericalcarine and lateral occipital ROI (5.52%, -5.40% and -5.11%, respectively). Correcting for gradient non-linearities can have significant influence on volumetric analysis of cortical thickness and volume. Since the distortion correction is an automatic feature of the MR scanner, it should be stated by each study that applies volumetric analysis which images were used.

Considerations in the Management of Functional Neurological Disorders in Patients with Hearing Loss.

Adam is a 14-year-old adolescent boy with hearing loss who presented to the pediatric neurology clinic accompanied by his father for evaluation of new-onset left hand tremor for a duration of 1 month. An American Sign Language interpreter was present and used throughout the visit.Adam has bilateral sensorineural hearing loss related to premature birth at 28 weeks' gestation. He uses sign language and attends a school for the hearing impaired. He has been diagnosed with attention-deficit/hyperactivity disorder (ADHD) and a nonspecific learning disorder. His ADHD symptoms are well controlled with a stimulant medication. He is independent in activities of daily living, and there is no concern for intellectual disability. His father is concerned that Adam may have anxiety, but this has not been evaluated.After careful history, it is found that the tremor was first noted the day after burglars broke into his home and stole precious belongings. Current stressors include difficulties with schoolwork and a strained relationship with an extended family member. There is no family history of tremor.The tremor was intermittent initially, with episodes lasting around 30 minutes. Over time, the tremor became more persistent. Adam is left-handed, and the tremor is now interfering with handwriting, eating, and other fine motor skills. The tremor worsens when Adam is tired or stressed and improves with relaxation. No tremor has been noted in other body parts. Adam denies any other neurological symptoms, including headache, vision changes, or gait abnormalities.On examination, Adam seemed anxious but showed no significant distress and had normal vital signs. His general examination was unremarkable. His neurological examination showed intact cranial nerves, apart from the hearing impairment. He had normal muscle tone, intact strength and coordination, and a normal casual gait. Rhythmic shaking of the left upper extremity was present with action, while maintaining posture. Using specific examination techniques, the examiner was able to alter the rhythm of the tremor, and the tremor was noted to subside when the patient was engaged with the examiner. These findings in addition to signs of suggestibility and variable frequency/direction were consistent with a functional etiology.The diagnosis of a functional neurological disorder manifesting in the form of functional tremor was discussed with the patient and his father with assistance from the sign language interpreter. Counseling regarding management consisting mainly of cognitive behavioral therapy and evaluation of possible coexisting conditions, such as anxiety, was discussed.What factors would you consider in diagnosis and management of functional neurological disorder in a hearing-impaired child/adolescent?

Exploring the Role of Cerebrospinal Fluid As Analyte in Neurologic Disorders

The cerebrospinal fluid (CSF) is a clear ultrafiltrate of blood that envelopes and protects the central nervous system while regulating neuronal function through the maintenance of interstitial fluid homeostasis in the brain. Due to its anatomic location and physiological functions, the CSF can provide a reliable source of biomarkers for the diagnosis and treatment monitoring of different neurological diseases, including neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and primary and secondary brain malignancies. The incorporation of CSF biomarkers into the drug discovery and development can improve the efficiency of drug development and increase the chances of success. This review aims to consolidate the current use of CSF biomarkers in clinical practice and explore future perspectives for the field.

Demyelinating polyneuropathy combined with brachial plexopathy after nivolumab therapy for hodgkin lymphoma: a case report

BackgroundNivolumab is an immune checkpoint inhibitor that targets the programmed cell death-1 protein and is effective in treating advanced cancer. However, it is also associated with various immune-related neurological complications, including myasthenia gravis, Guillain–Barré syndrome, and demyelinating polyneuropathy. These complications can easily mimic other neurological diseases and have greatly varying therapeutic approaches depending on the underlying pathophysiology.Case presentationHere, we report a case of nivolumab-induced demyelinating peripheral polyneuropathy involving the brachial plexus in a patient with Hodgkin lymphoma. Approximately 7 months after nivolumab treatment, the patient experienced muscle weakness with a tightness and tingling sensation in the right forearm. Electrodiagnostic studies showed features of demyelinating peripheral neuropathy with right brachial plexopathy. Magnetic resonance imaging revealed thickening with a diffuse enhancement of both brachial plexuses. The patient was eventually diagnosed with nivolumab-induced demyelinating polyneuropathy involving the brachial plexus. Oral steroid therapy improved motor weakness and sensory abnormalities without aggravation.ConclusionOur study indicates the possibility of nivolumab-induced neuropathies in cases involving muscle weakness with sensory abnormalities of the upper extremity following nivolumab administration in patients with advanced cancer. Comprehensive electrodiagnostic studies and magnetic resonance imaging are helpful in the differential diagnosis of other neurological diseases. Appropriate diagnostic and therapeutic approaches may prevent further neurological deterioration.

Recent progress in patent foramen ovale and related neurological diseases: A narrative review.

Patent foramen ovale (PFO) is a common congenital cardiac abnormality when the opening of the interatrial septum is not closed in adulthood. This abnormality affects 25% of the general population. With the development of precision medicine, an increasing number of clinical studies have reported that PFO is closely related to various neurological diseases such as stroke, migraine, obstructive sleep apnea, and decompression syndrome. It has also been suggested that PFO closure could be effective for preventing and treating these neurological diseases. Therefore, increasing attention has been given to the prevention, diagnosis, and treatment of PFO-related neurological diseases. By reviewing existing literature, this article focuses on the pathogenesis, epidemiology, and clinical characteristics of PFO-related neurological diseases, as well as the prevention and treatment of different neurological diseases to discuss, and aims to provide current progress for this field and decision-making evidence for clinical practice.

Materials and Structural Designs for Neural Interfaces

Rapid advances in neurotechnology enable bidirectional communication between the nervous system and engineered devices. The precise recording and stimulation of typical target neurons by neural interfaces with adequate materials and structures can provide revolutionized medical applications, including the diagnosis and treatment of neurological disorders. Thereby, a proper understanding of the electronic device and its interfacing biological surroundings is necessary. Here, this review highlights the basic concepts of neural signaling, neural recording, and stimulation to help understand neural interfaces. Then, we summarize the considerations of the materials and introduce a variety of materials that satisfy the requirements. Furthermore, the key challenges for next-generation neural interfaces are considered, and future directions are explored based on recent studies.

Epidemiology, Isolation, and Genetic Characterization of Toscana Virus in Algerian Patients Displaying Neurological Infection, 2016–2018

PurposeThe current study reports the results of the diagnosis of neuro-invasive Toscana virus (TOSV) infection in Algeria between 2016 and 2018 and describes the first isolation of TOSV strain from human samples in North Africa. Materiel and methodsCerebrospinal fluid (CSF) and sera samples were obtained from 720 hospitalized patients displaying neurological infection symptoms of unknown etiology, of which 604 were screened for TOSV. The diagnosis was performed by serological and/or RT-PCR tests. In addition, TOSV was isolated in vivo and in vitro from CSF and genetically characterized. Results23 cases of TOSV neurological infections were detected. Cases were located in 11 Wilayas (administrative provinces), mainly in northern Algeria. In addition, we report the isolation of TOSV strain belonging to lineage A from human samples with its complete coding sequence. ConclusionEven though the number of infections is probably underestimated, TOSV is endemic in Algeria, with several cases of neuro-invasive diseases in humans recorded each year. Therefore, the diagnosis of TOSV should be included in the differential diagnosis of neurological diseases, especially aseptic meningitis, during the period of activity of the phlebotomine vector. Further studies are required to measure precisely the nationwide prevalence of TOSV in Algeria.

Single Molecule with a Large Transistor – SiMoT cytokine IL‐6 Detection Benchmarked against a Chemiluminescent Ultrasensitive Immunoassay Array

AbstractEarly diagnosis and efficient treatments of oncological, neurological, inflammatory, and infectious diseases rely more and more on ultrasensitive detection of protein markers; the ultimate limit is a reliable immunoassay capable of single‐protein detection. Among protein biomarkers, cytokines play a key role in clinical diagnosis as they are involved in developing many complex diseases and disorders, such as chronic inflammatory diseases including metabolic syndrome, neurodegenerative diseases, and cardiovascular diseases, along with autoimmune diseases and cancer. Herein, the improvement of a Single Molecule with Transistor (SiMoT) is reported based on an electrolyte‐gated organic field‐effect transistor applied for the detection of cytokine IL‐6 in blood serum, reaching a limit‐of‐detection (LOD) of 1 ± 1 protein in a sample of 0.1 mL. The analytical performance levels are benchmarked against the Simoa Planar Array SP‐X technology, a benchtop chemiluminescent array. After comprehensive optimization, Simoa SP‐X by using a multivariate experimental design approach exhibits a LOD 103 higher than SiMoT. The proposed SiMoT electronic assay is label‐free, fast (30 min), and selective, paving the way for an ultra‐sensitive point‐of‐care immunoassay platform enabling pre‐symptomatic disease diagnosis.

Evaluation of glutamic acid decarboxylase (GAD) 65 antibody detection methods for neurological and diabetic investigation in an Australian diagnostic laboratory

The role of anti-glutamic acid decarboxylase (GAD) 65 autoantibodies in autoimmune neurological conditions is evolving, but testing recommendations remain unchanged in Australia with GAD enzyme-linked immunosorbent assay (ELISA) and immunoblot as the only two Therapeutic Goods Administration approved testing methods available in Australia. Common practice is for use of ELISA in diagnosis of type 1 diabetes mellitus (T1DM) and use of immunoblot for diagnosis of GAD65-associated neurological disease. We observed a cohort of patients with negative immunoblot results and positive ELISA in the context of GAD-associated neurological disease without T1DM. In the absence of robust consensus guidelines on preferred testing modalities, we sought to determine if ELISA could have a superior role in the diagnosis of GAD-associated neurological disease when compared to immunoblot in this paper. We tested for anti-GAD65 autoantibodies on 55 patient samples, 40 samples requested for neurological disease and 15 type 1 diabetes samples with detectable anti-GAD65, using two testing platforms: Euroimmun anti-GAD enzyme-linked immunosorbent assay (ELISA) and. Euroimmun EuroLine immunoblot for paraneoplastic neurologic syndromes. These results were correlated against the clinical scenario. Positive ELISA results had a sensitivity of 100% and specificity of 91% for GAD65-related neurological disease. Immunoblot showed sensitivity of 43% and specificity of 76% for GAD65-related neurological disease. ELISA proved more sensitive and specific for GAD65-related neurological disease compared to immunoblot, raising questions about the role of this testing modality in neurological disease. We propose that ELISA should be used as a sole diagnostic method for all GAD65 antibody-related neurological disease over immunoblot. The presence of anti-GAD65 antibody on immunoblot is of doubtful clinical significance.

Ultrasensitive and Simple Dopamine Electrochemical Sensor Based on the Synergistic Effect of Cu-TCPP Frameworks and Graphene Nanosheets

Dopamine (DA) is an important neurotransmitter. Abnormal concentration of DA can result in many neurological diseases. Developing reliable determination methods for DA is of great significance for the diagnosis and monitoring of neurological diseases. Here, a novel and simple electrochemical sensing platform for quantitative analysis of DA was constructed based on the Cu-TCPP/graphene composite (TCPP: Tetrakis(4-carboxyphenyl)porphyrin). Cu-TCPP frameworks were selected in consideration of their good electrochemical sensing potential. The graphene nanosheets with excellent conductivity were then added to further improve the sensing efficiency and stability of Cu-TCPP frameworks. The electrochemical properties of the Cu-TCPP/graphene composite were characterized, showing its large electrode active area, fast electron transfer, and good sensing performance toward DA. The signal enhancement mechanism of DA was explored. Strong accumulation ability and high electrocatalytic rate were observed on the surface of Cu-TCPP/graphene-modified glassy carbon electrode (Cu-TCPP/graphene/GCE). Based on the synergistic sensitization effect, an ultrasensitive and simple DA electrochemical sensor was developed. The linear range is 0.02-100 and 100-1000 µM, and the detection limit is 3.6 nM for the first linear range. It was also successfully used in detecting DA in serum samples, and a satisfactory recovery was obtained.

Convergence of Artificial Intelligence and Neuroscience towards the Diagnosis of Neurological Disorders-A Scoping Review.

Artificial intelligence (AI) is a field of computer science that deals with the simulation of human intelligence using machines so that such machines gain problem-solving and decision-making capabilities similar to that of the human brain. Neuroscience is the scientific study of the struczture and cognitive functions of the brain. Neuroscience and AI are mutually interrelated. These two fields help each other in their advancements. The theory of neuroscience has brought many distinct improvisations into the AI field. The biological neural network has led to the realization of complex deep neural network architectures that are used to develop versatile applications, such as text processing, speech recognition, object detection, etc. Additionally, neuroscience helps to validate the existing AI-based models. Reinforcement learning in humans and animals has inspired computer scientists to develop algorithms for reinforcement learning in artificial systems, which enables those systems to learn complex strategies without explicit instruction. Such learning helps in building complex applications, like robot-based surgery, autonomous vehicles, gaming applications, etc. In turn, with its ability to intelligently analyze complex data and extract hidden patterns, AI fits as a perfect choice for analyzing neuroscience data that are very complex. Large-scale AI-based simulations help neuroscientists test their hypotheses. Through an interface with the brain, an AI-based system can extract the brain signals and commands that are generated according to the signals. These commands are fed into devices, such as a robotic arm, which helps in the movement of paralyzed muscles or other human parts. AI has several use cases in analyzing neuroimaging data and reducing the workload of radiologists. The study of neuroscience helps in the early detection and diagnosis of neurological disorders. In the same way, AI can effectively be applied to the prediction and detection of neurological disorders. Thus, in this paper, a scoping review has been carried out on the mutual relationship between AI and neuroscience, emphasizing the convergence between AI and neuroscience in order to detect and predict various neurological disorders.

A novel framework for in-vivo diffusion tensor distribution MRI of the human brain

Neural tissue microstructure plays an important role in developmental, physiological and pathophysiological processes. Diffusion tensor distribution (DTD) MRI helps probe subvoxel heterogeneity by describing water diffusion within a voxel using an ensemble of non-exchanging compartments characterized by a probability density function of diffusion tensors. In this study, we provide a new framework for acquiring multiple diffusion encoding (MDE) images and estimating DTD from them in the human brain in vivo. We interfused pulsed field gradients (iPFG) in a single spin echo to generate arbitrary b-tensors of rank one, two, or three without introducing concomitant gradient artifacts. Employing well-defined diffusion encoding parameters we show that iPFG retains salient features of a traditional multiple-PFG (mPFG/MDE) sequence while reducing the echo time and coherence pathway artifacts thereby extending its applications beyond DTD MRI. Our DTD is a maximum entropy tensor-variate normal distribution whose tensor random variables are constrained to be positive definite to ensure their physicality. In each voxel, the second-order mean and fourth-order covariance tensors of the DTD are estimated using a Monte Carlo method that synthesizes micro-diffusion tensors with corresponding size, shape, and orientation distributions to best fit the measured MDE images. From these tensors we obtain the spectrum of diffusion tensor ellipsoid sizes and shapes, and the microscopic orientation distribution function (μODF) and microscopic fractional anisotropy (μFA) that disentangle the underlying heterogeneity within a voxel. Using the DTD-derived μODF, we introduce a new method to perform fiber tractography capable of resolving complex fiber configurations. The results revealed microscopic anisotropy in various gray and white matter regions and skewed MD distributions in cerebellar gray matter not observed previously. DTD MRI tractography captured complex white matter fiber organization consistent with known anatomy. DTD MRI also resolved some degeneracies associated with diffusion tensor imaging (DTI) and elucidated the source of diffusion heterogeneity which may help improve the diagnosis of various neurological diseases and disorders.

A Gender-Based Point of View in Pediatric Neurology.

While the significance of gender has only recently been recognized, gender assigned at birth has long been understood to have a significant influence on a number of illnesses. Due to the paucity of data in this regard in pediatrics, the purpose of this narrative review is to frame the most recent knowledge about the role of gender assigned at birth in the neurological development and neuropsychiatric disorders among young people. Literature analysis showed that gender disparities exist in neurologic and neuropsychiatric disorders among the pediatric population and supported the fact that new guidelines should take this into account. However, there is an urgent need for specific studies focused on gender role among children and adolescents in order to better understand how this can relate to diagnosis, development and treatment of different neurologic and neuropsychiatric diseases. Moreover, further efforts should be directed to identify unique risks linked to gender disorders and gender dysphoria as well as taking into account a gender point of view when approaching a pediatric patient.