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Functional movement disorders (FMD, aka psychogenic movement disorders) are very common and frequently chronic and disabling. Despite this, there is a paucity of evidence-based treatment to manage and alleviate these conditions. Specialized physical therapy (PT), involving sequential motor relearning and redirecting attention, has shown promise as a therapeutic intervention for motor symptoms.The objective of this study was to critically assess current evidence regarding specialized PT compared with usual care in improving motor symptoms among patients with FMD. This was addressed through the development of a structured critically appraised topic. This included a clinical scenario with a clinical question, literature search strategy, critical appraisal, results, evidence summary, commentary, and bottom-line conclusions. Participants included consultant and resident neurologists, a medical librarian, and content experts in the fields of physical medicine and rehabilitation, physical and occupational therapy, psychiatry, and psychology.A randomized controlled feasibility trial was identified and selected for critical appraisal. This study randomized 60 patients with FMD to a 5-day specialized outpatient PT program or to general outpatient PT referral, and measured patient-reported and clinician-measured outcomes. At 6 months, 72% of patients in the intervention group had a good outcome compared with 18% of control group patients. Patients in the specialized outpatient PT program had significantly better outcomes in 3 Short-Form 36 (SF36) domains (d=0.46 to 0.79) and multiple other scales of physical and social function as well as clinician-measured outcomes. The intervention resulted in 0.08 additional quality-adjusted life years in a cost-effective manner.Current evidence suggests that in patients with FMD, specialized PT improves motor symptoms in a clinically significant, sustained, and cost-effective manner. This promising intervention warrants further investigation and replication.

A thorough understanding of the neuroanatomy of peripheral nerves is required for a better insight into their function and the development of neuromodulation tools and strategies. In biophysical modeling, it is commonly assumed that the complex spatial arrangement of myelinated and unmyelinated axons in peripheral nerves is random, however, in reality the axonal organization is inhomogeneous and anisotropic. Present quantitative neuroanatomy methods analyze peripheral nerves in terms of the number of axons and the morphometric characteristics of the axons, such as area and diameter. In this study, we employed spatial statistics and point process models to describe the spatial arrangement of axons and Sinkhorn distances to compute the similarities between these arrangements (in terms of first- and second-order statistics) in various vagus and pelvic nerve cross-sections. We utilized high-resolution TEM images that have been segmented using a custom-built high-throughput deep learning system based on a highly modified U-Net architecture. Our findings show a novel and innovative approach to quantifying similarities between spatial point patterns using metrics derived from the solution to the optimal transport problem. We also present a generalizable pipeline for quantitative analysis of peripheral nerve architecture. Our data demonstrate differences between male- and female-originating samples and similarities between the pelvic and abdominal vagus nerves., Comment: 10 figures

Background Despite the increasing incidence of neuroinvasive West Nile virus (NiWNV) infection in the US, the spectrum of disease characteristics and neuroimaging findings in immunosuppressed (IS) individuals are not adequately described. We aimed to compare the clinical characteristics and outcomes of NiWNV infection in IS and immunocompetent (IC) patients. Methods We extracted relevant data from all NiWNV patients hospitalized 7/2003-10/2021 at Mayo Clinic hospitals. Cohort was inclusive of patients from the recent historic WNV outbreak in Arizona in 2021. Chi-Square or Kruskal-Wallis and logistic regression were used to compare relevant variables and determine predictors of mortality respectively. Results We included 115 patients (72 IC and 43 IS), mean age 63.5 years; neurologic syndromes included meningoencephalitis (85.2%), encephalomyelitis (8.7%) and myeloradiculitis (6.1%). Presenting symptoms were malaise (72%), fever (66%), altered mentation (64%), gastrointestinal (47%) and myalgia (35.7%). MRI brain was abnormal in 62.8% (49/78), demonstrating T2/FLAIR hyperintensities in 47.4% (brainstem, thalamus, temporal lobes), leptomeningeal enhancement (16.7%) and diffusion restriction (20.5%). Altered mental status (76.7% vs 56.9%), myalgia (44.4% vs. 20.9%), myoclonus (18.6% vs. 4.2%) and thalamic MRI T2 FLAIR abnormalities (11.4% vs 0%) were more common in IS patients. Higher CSF WBC counts were observed in IC vs IS patients (P< 0.05). Immunosuppressed patients were more likely to be treated with intravenous immunoglobulin (44.2% vs 8.3% p=< 0.001) and/or interferon therapy (32.6% vs 6.9%, p=0.0003) and had increased odds of 90-day mortality on multivariable analysis (Adjusted Odds Ratio, AOR 2.22; 95% CI 1.065-4.627, p=0.0334). In the IS subgroup, ICU admission, mechanical ventilation, and Glasgow coma scale of < 8 were associated with reduced overall survival/increased 90-day mortality (p< 0.005). Conclusion Individuals presenting in summer/fall months with the aforementioned symptoms and/or MRI abnormalities should be evaluated for NiWNV infection. Compared to the immunocompetent, immunosuppressed patients with NiWNV are at a significantly greater mortality risk. Novel and effective antiviral therapies aimed at improving outcomes are warranted. Disclosures All Authors: No reported disclosures.

We describe a generative network model of the architecture of the enteric nervous system (ENS) in the colon employing data from images of human and mouse tissue samples obtained through confocal microscopy. Our models combine spatial point pattern analysis with graph generation to characterize the spatial and topological properties of the ganglia (clusters of neurons and glial cells), the inter-ganglionic connections, and the neuronal organization within the ganglia. We employ a hybrid hardcore-Strauss process for spatial patterns and a planar random graph generation for constructing the spatially embedded network. We show that our generative model may be helpful in both basic and translational studies, and it is sufficiently expressive to model the ENS architecture of individuals who vary in age and health status. Increased understanding of the ENS connectome will enable the use of neuromodulation strategies in treatment and clarify anatomic diagnostic criteria for people with bowel motility disorders., Comment: 17 pages, 5 figures

OBJECTIVE: Measuring olfactory dysfunction shows promise as one of a number of nonmotor biomarkers that can be used to detect clinically manifest and prodromal Parkinson’s disease (PD) and dementia with Lewy bodies (DLB) and to differentiate these from nonsynucleinopathies. Using a larger sample size than in our previous study, we evaluated the relationship between olfactory dysfunction based on the University of Pennsylvania Smell Identification Test (UPSIT) to the clinicopathological findings in patients with PD (n=41), patients with incidental Lewy body disease (ILBD) (n=47), and controls with no neurodegenerative disease (n=137). DESIGN: This study was conducted through the Arizona Study of Aging and Neurodegenerative Disease (AZSAND). We selected individuals who had an UPSIT score completed antemortem and were clinicopathologically diagnosed with PD, ILBD, or control. Various measures included density of Lewy type synucleinopathy (aSyn) in the olfactory bulb and tract, as well as connected mesial temporal lobe structures. Cases and controls were analyzed using one-way analysis of variance (ANOVA) with pairwise contrasts. RESULTS: Compared to controls (mean: 27.8, standard deviation [SD]: 6.0), the mean UPSIT scores were lower for PD (15.8, SD: 6.0, p

Neuromyelitis optica spectrum disorder (NMOSD) is rarely reported following Coronavirus disease 2019 (COVID-19) vaccination. We identified 16 cases of new onset NMOSD with positive aquaporin-4 IgG (AQP4-IgG) following COVID-19 vaccination. Transverse myelitis was the most common clinical presentation (75%). Most patients received high dose steroids for acute treatment and maintenance therapy was started in 12 patients (75%). Twelve patients (75%) had improvement of their symptoms at the time of discharge or follow-up. The included cases share similar epidemiology and natural course to non-vaccine related cases. Clinicians should be aware of possible post-vaccination NMOSD to help with earlier diagnosis and treatment.

Axonal characterizations of connectomes in healthy and disease phenotypes are surprisingly incomplete and biased because unmyelinated axons, the most prevalent type of fibers in the nervous system, have largely been ignored as their quantitative assessment quickly becomes unmanageable as the number of axons increases. Herein, we introduce the first prototype of a high-throughput processing pipeline for automated segmentation of unmyelinated fibers. Our team has used transmission electron microscopy images of vagus and pelvic nerves in rats. All unmyelinated axons in these images are individually annotated and used as labeled data to train and validate a deep instance segmentation network. We investigate the effect of different training strategies on the overall segmentation accuracy of the network. We extensively validate the segmentation algorithm as a stand-alone segmentation tool as well as in an expert-in-the-loop hybrid segmentation setting with preliminary, albeit remarkably encouraging results. Our algorithm achieves an instance-level $$F_1$$ F 1 score of between 0.7 and 0.9 on various test images in the stand-alone mode and reduces expert annotation labor by 80% in the hybrid setting. We hope that this new high-throughput segmentation pipeline will enable quick and accurate characterization of unmyelinated fibers at scale and become instrumental in significantly advancing our understanding of connectomes in both the peripheral and the central nervous systems.

Objective. Autonomic symptoms are common in α-synuclein disorders: multiple system atrophy (MSA), Parkinson’s disease (PD), dementia with Lewy bodies (DLB), and Parkinson’s disease with dementia (PDD). These symptoms may precede the motor findings/clinical diagnosis by years. Erectile dysfunction (ED) is an autonomic symptom that has rarely been studied in these α-synuclein disorders. In this population-based, case-control study, we investigated the association between premonitory erectile dysfunction surfacing prior to the clinical-motor manifestations of these α-synucleinopathies. Methods. We used the medical record-linkage system of the Rochester Epidemiology Project to identify cases of α-synucleinopathies in Olmsted County from 1991 to 2010. Each male case was matched by age (±1 year) of symptom onset and sex to a control. We reviewed complete medical records of cases and controls to detect erectile dysfunction prior to the clinical-motor onset of α-synucleinopathies of any type. We used conditional logistic regression to calculate the odds ratio of all α-synucleinopathies, as well as by type, adjusting for diabetes, coffee, and smoking. Results. A history of male erectile dysfunction was associated with 1.5-fold increased odds of an α-synucleinopathy diagnosis of any type in univariate analyses (p=0.06). When stratifying α-synucleinopathies by type, early erectile dysfunction was most frequent in MSA cases than matched controls (45% vs. 9%). Premotor phase ED was next most frequent among the DLB cases (46% vs. 27% among the controls; OR = 2.83, p=0.03; when adjusted for diabetes, smoking, and coffee, OR = 2.98, p=0.04). Premotor phase ED was not significantly associated with PD or PDD. Conclusions. Early erectile dysfunction may be a premotor symptom of MSA and DLB, reflecting premonitory dysautonomia. It was not associated with premotor PD or PDD.

Contemporary patient surveillance systems have streamlined central surveillance into the electronic health record interface. They are able to process the sheer volume of patient data by adopting machine learning approaches. However, these systems are not suitable for implementation in many hospitals, mostly in developing countries, with limited human, financial, and technological resources. Through conducting thorough research on intensive care facilities, we designed a novel central patient monitoring system and in this paper, we describe the working prototype of our system. The proposed prototype comprises of inexpensive peripherals and simplistic user interface. Our central patient monitoring system implements Kernel-based On-line Anomaly Detection (KOAD) algorithm for emergency event signaling. By evaluating continuous patient data, we show that the system is able to detect critical events in real-time reliably and has low false alarm rate.

Background Several studies have proposed a role for infections to induce an inflammatory response triggering Parkinson's disease. This remains controversial and the influence of severe infections on other α-synucleinopathies (Dementia with Lewy Bodies, Parkinson's disease dementia, and Multiple System Atrophy) has not been adequately investigated. Objectives To assess the association between hospitalization-required infections or sepsis and risk of clinically diagnosed α-synucleinopathies. Methods Using the medical records-linkage system (Rochester Epidemiology Project), we identified all α-synucleinopathy cases of in Olmsted County (1991-2010). Cases were matched by symptom-onset age and sex to controls. We reviewed complete medical records to detect hospital-required infections or sepsis preceding clinical-motor onset of α-synucleinopathies. We used conditional logistic regression to calculate the odds ratio of all α-synucleinopathies, adjusting for medications, coffee, and smoking. Results There was no association between infection-related hospitalization (odds ratio: 1.05; 95% confidence interval: 0.78-1.40; P = 0.76) or sepsis (odds ratio: 0.86; 95% confidence interval: 0.40-1.85; P = 0.70) and all α-synucleinopathies in multivariable analyses. We did not identify any associations after stratifying for type of α-synucleinopathy, sex, and age at clinical-motor onset. We analyzed sepsis separately with similar results. Conclusion We did not observe any associations between infections leading to hospitalization or sepsis and development of any α-synucleinopathies. © 2020 International Parkinson and Movement Disorder Society.

ObjectiveTo determine the association between traumatic brain injury (TBI) and any clinically diagnosed α-synucleinopathy including Parkinson disease (PD), dementia with Lewy bodies (DLB), PD dementia (PDD), and multiple system atrophy (MSA).MethodsUsing the medical records-linkage system of the Rochester Epidemiology Project, we identified incident cases of α-synucleinopathies in Olmsted County, Minnesota, from 1991 to 2010, matching by age (±1 year) at symptom onset and sex to controls. We reviewed records of cases and controls to detect TBI prior to clinical-motor onset of any α-synucleinopathies. We based severity (possible, probable, and definite) upon the Mayo Classification System for TBI Severity. Using conditional-logistic regression, we calculated the odds ratio (OR) of all α-synucleinopathies and type, adjusting for coffee intake and smoking.ResultsTBI frequency was lower among cases (7.0%) than controls (8.2%). No association was found between TBI and all α-synucleinopathies in multivariable analyses (OR 0.90, 95% confidence interval [CI] 0.54–1.52). No association presented when examining the number of TBIs, TBI severity, time between TBI exposure and index date, age at index date, or sex. When stratifying by each individual α-synucleinopathy, we did not identify any associations between TBI and PD, DLB, or PDD. Among the MSA group, 1 (6.4%) and 0 controls experienced a TBI (OR could not be estimated).ConclusionsIn this nested case-control population-based analysis, TBI was not associated with subsequent α-synucleinopathies in general or any individual α-synucleinopathy. This did not change based on the temporality or the severity of the TBI. Our findings may be limited by the study power.

Telecommunication has seen distinct upgrade since the innovation of wireless communication. The latest addition is LTE-Advanced. LTE-Advanced requires implementation of femtocell. Spontaneous femtocell deployment introduces cross-tier and co-tier interference as well as further cost for uniform installation. In this paper, we describe outlines to solve the encountered problems and discuss the feasibility of the proposed outlines. The outlines contain efficient reuse of macrocell RF channels to indoor femtocells by dynamic spectrum allocation. The autonomous, Cognitive Radio-enabled technology is the premise of femtocells driven by LTE-Advanced. Cognitive Radio ensures offloading from macrocells by craftily imparting over accessible range. Application of on Access Control List concept further enhances femtocell capability. Additionally, hardware and software deployment costs are matched with macrocell. The reservations aim to satisfy the criterion identified as Quality of Service. The choice of femtocell over WLAN is favored by considering authorization and co-existential constraints.