Morvan Fibrillary Chorea Associated with Monoclonal B Cell Lymphocytosis.

BACKGROUND Morvan fibrillary chorea (Morvan syndrome) is a rare disorder marked by a collection of neurological symptoms such as myokymia, peripheral nerve excitability, neuromyotonia, autonomic instability, memory impairment, and delirium. Morvan syndrome is suspected to occur through antibodies directed against voltage gated potassium channels (VGKC), and has been linked with several autoimmune conditions and hematologic malignancies. We present a case of Morvan syndrome in association with monoclonal B cell lymphocytosis. Upon our literature review, we believe this to be the first documented case of Morvan syndrome associated with monoclonal B cell lymphocytosis. CASE REPORT The present case report describes a 75-year-old man with Morvan's syndrome. The patient had a diverse neurologic presentation with encephalopathy, progressive neuropathic pain, muscle fasciculations, myokymia, sensory deficits, and Bell's palsy. Ultimately, a paraneoplastic antibody panel revealed a positive titer of contactin-associated protein-like IgG (CASPR) and VGKC antibody. Flow cytometry showed a small population of abnormal lambda-restricted B cells. Given his symptoms, positive CASPR antibody, and flow cytometry findings, he was diagnosed with Morvan syndrome associated with monoclonal B cell lymphocytosis. He was treated with IV methylprednisolone and IVIG, with immediate improvement in neurologic symptoms. CONCLUSIONS Morvan syndrome presents with a spectrum of neurologic symptoms and is associated with autoantibodies against VGKC through anti-CASPR2 antibodies. Classically, Morvan syndrome presents as a paraneoplastic disease secondary to thymomas. Our case demonstrates that there is an association between B cell lymphoproliferative disorders and Morvan syndrome.

Comparison of the Phenotypic Flexibility of Muscle and Body Condition of Migrant and Resident White-Crowned Sparrows.

AbstractSeasonally breeding birds express variations of traits (phenotypic flexibility) throughout their life history stages that represent adaptations to environmental conditions. Changes of body condition during migration have been well studied, whereas alterations of skeletal and cardiac muscles, body mass, and fat scores have yet to be characterized throughout the spring or fall migratory stages. Additionally, we examined flexible patterns of muscle, body mass, and fat score in migrant white-crowned sparrows (Zonotrichia leucophrys gambelii) in comparison with those in a resident subspecies (Zonotrichia leucophrys nuttalli) during the stages they share to evaluate the influence of different life histories. Migrants showed hypertrophy of the pectoralis muscle fiber area on the wintering grounds in late prealternate molt, yet increased pectoralis muscle mass was not detected until birds readied for spring departure. While pectoralis profile and fat scores enlarged at predeparture in spring and fall, pectoralis, cardiac, and body masses were greater only in spring stages, suggesting seasonal differences for migratory preparation. Gastrocnemius mass showed little change throughout all stages, whereas gastrocnemius fiber area declined steadily but rebounded in fall on the wintering grounds, where migrants become more sedentary. In general, residents are heavier birds with larger leg structures, while migrants sport longer wings and greater heart mass. Phenotypic flexibility was most prominent among residents with peaks of pectoralis, gastrocnemius, and body masses during the winter stage, when local weather is most severe. Thus, the subspecies express specific patterns of phenotypic flexibility with peaks coinciding with the stages of heightened energy demands: the winter stage for residents and the spring stages for migrants.

Brain Tumor Imaging: Review of Conventional and Advanced Techniques.

Approaches to central nervous system (CNS) tumor classification and evaluation have undergone multiple iterations over the past few decades, in large part due to our growing understanding of the influence of genetics on tumor behavior and our refinement of brain tumor imaging techniques. Computed tomography and magnetic resonance imaging (MRI) both play a critical role in the diagnosis and monitoring of brain tumors, although MRI has become especially important due to its superior soft tissue resolution. The purpose of this article will be to briefly review the fundamentals of conventional and advanced techniques used in brain tumor imaging. We will also highlight the applications of these imaging tools in the context of commonly encountered tumors based on the most recently updated 2021 World Health Organization (WHO) classification of CNS tumors framework.

MRI-based radiomics for prognosis of pediatric diffuse intrinsic pontine glioma: an international study.

BACKGROUND: Diffuse intrinsic pontine gliomas (DIPGs) are lethal pediatric brain tumors. Presently, MRI is the mainstay of disease diagnosis and surveillance. We identify clinically significant computational features from MRI and create a prognostic machine learning model. METHODS: We isolated tumor volumes of T1-post-contrast (T1) and T2-weighted (T2) MRIs from 177 treatment-naïve DIPG patients from an international cohort for model training and testing. The Quantitative Image Feature Pipeline and PyRadiomics was used for feature extraction. Ten-fold cross-validation of least absolute shrinkage and selection operator Cox regression selected optimal features to predict overall survival in the training dataset and tested in the independent testing dataset. We analyzed model performance using clinical variables (age at diagnosis and sex) only, radiomics only, and radiomics plus clinical variables. RESULTS: All selected features were intensity and texture-based on the wavelet-filtered images (3 T1 gray-level co-occurrence matrix (GLCM) texture features, T2 GLCM texture feature, and T2 first-order mean). This multivariable Cox model demonstrated a concordance of 0.68 (95% CI: 0.61-0.74) in the training dataset, significantly outperforming the clinical-only model (C = 0.57 [95% CI: 0.49-0.64]). Adding clinical features to radiomics slightly improved performance (C = 0.70 [95% CI: 0.64-0.77]). The combined radiomics and clinical model was validated in the independent testing dataset (C = 0.59 [95% CI: 0.51-0.67], Noether's test P = .02). CONCLUSIONS: In this international study, we demonstrate the use of radiomic signatures to create a machine learning model for DIPG prognostication. Standardized, quantitative approaches that objectively measure DIPG changes, including computational MRI evaluation, could offer new approaches to assessing tumor phenotype and serve a future role for optimizing clinical trial eligibility and tumor surveillance.

Sustained release of a model water-soluble compound via dry powder aerosolizable acetalated dextran microparticles.

Objective: To design and characterize aerosol microparticles (MP) to provide sustained release of the water-soluble compound sulforhodamine B (SRB) and achieve effective aerosol dispersion. Significance: Modulating the release of water-soluble compounds remains a challenge in pulmonary drug delivery. Methods: SRB and water made up an aqueous solution, while acetalated dextran (Ac-Dex) and isopropyl alcohol made up an organic solution. The two solutions were mixed together, and the solution was spray dried to produce MP. MP were characterized for morphology, size, release kinetics, aerosol dispersion, and cellular interactions. Results: Ac-Dex MP exhibited corrugated morphology and aerodynamic diameters from 2.06 to 2.86 µm. MP deposited in all stages of a Next Generation Impactor, with >90% fine particle fraction. MP exhibited encapsulation efficiencies >129% with SRB loading values up to 16.7 µg SRB/mg MP. MP exhibited sustained release of SRB at pH 7 and fast release at pH 5. In vitro experiments showed minimal cytotoxicity, successful uptake of MP in epithelial cells, and no disruption to the integrity of epithelial monolayers. Conclusions: Ac-Dex MP systems demonstrated the ability to provide sustained the release of a water-soluble therapeutic in addition to effective aerosol dispersion for pulmonary applications.

A parental perspective concerning barriers to care for neural tube defects in China.

BACKGROUND: The People's Republic of China (PRC) has the highest incidence of neural tube defects (NTDs) in the world. NTDs remain a significant contributor to the global burden of disease amendable to surgical care; however, no studies to date have evaluated the patients' perspective regarding perceived barriers to care. METHODS: The study was conducted at the Shanghai Children's Medical Center (SCMC) between 6/11/2014 and 7/17/2014. Surveys were administered to families presenting to the clinic of the SCMC director for Pediatric Neurosurgery. Additionally, orphaned patients under the care of the Baobei Foundation were surveyed for comparison. Participants were allowed to mark as many barriers on the survey as they deemed relevant to their experience. RESULTS: A total of 69 patients were surveyed. The most frequently chosen barrier to care, with a P value < 10-5, was that the referring physician did not know enough about the child's condition. As compared to the Baobei Foundation orphans, surveyed patients presented at an older age for initial treatment (7 months versus 1 month, P value = 0.001), and visited more hospitals before reaching SCMC (3.14 versus 1.0, P value < 10-5). CONCLUSIONS: The results of this study highlight the referring physician as a primary barrier to care. The younger age at time of treatment for Baobei orphans born with NTDs supports this finding, as they essentially bypassed the referral process. An elaboration on reasons for this real or perceived barrier may provide insight into a means for expedited diagnosis and treatment of NTDs within the PRC.

Identifying predictors for postoperative clinical outcome in lumbar spinal stenosis patients using smart-shoe technology.

BACKGROUND: Approximately 33% of the patients with lumbar spinal stenosis (LSS) who undergo surgery are not satisfied with their postoperative clinical outcomes. Therefore, identifying predictors for postoperative outcome and groups of patients who will benefit from the surgical intervention is of significant clinical benefit. However, many of the studied predictors to date suffer from subjective recall bias, lack fine digital measures, and yield poor correlation to outcomes. METHODS: This study utilized smart-shoes to capture gait parameters extracted preoperatively during a 10 m self-paced walking test, which was hypothesized to provide objective, digital measurements regarding the level of gait impairment caused by LSS symptoms, with the goal of predicting postoperative outcomes in a cohort of LSS patients who received lumbar decompression and/or fusion surgery. The Oswestry Disability Index (ODI) and predominant pain level measured via the Visual Analogue Scale (VAS) were used as the postoperative clinical outcome variables. RESULTS: The gait parameters extracted from the smart-shoes made statistically significant predictions of the postoperative improvement in ODI (RMSE =0.13, r=0.93, and p<3.92×10-7) and predominant pain level (RMSE =0.19, r=0.83, and p<1.28×10-4). Additionally, the gait parameters produced greater prediction accuracy compared to the clinical variables that had been previously investigated. CONCLUSIONS: The reported results herein support the hypothesis that the measurement of gait characteristics by our smart-shoe system can provide accurate predictions of the surgical outcomes, assisting clinicians in identifying which LSS patient population can benefit from the surgical intervention and optimize treatment strategies.

Behavioral and physiological traits of migrant and resident white-crowned sparrows: a common garden approach.

To accommodate a migratory life history, migrants express a greater number of physiological and behavioral stages per annum than residents and are thus considered to have higher finite state diversity (FSD). To investigate the physiological mechanisms and constraints associated with migration, direct comparison of two subspecies of white-crowned sparrow - migrant, Zonotrichia leucophrys gambelii, and resident, Z. l. nuttalli - were made under common garden conditions of photoperiod and housing, as birds progressed from winter through the vernal life history stages. We tested the hypothesis that migrants (higher FSD) respond differently than residents (lower FSD) to the initial predictive cue, photoperiod, to initiate and integrate the progression of vernal stages of prenuptial molt, migration and development of breeding. If differences in vernal phenology were noted, then the basis for the distinctions was considered genetic. Results indicate that (1) residents had a lower threshold to vernal photoperiod with elevations of plasma androgen, growth and development of reproductive structures preceding those of migrants; (2) only migrants displayed prenuptial molt, preparations for migration and migratory restlessness; and (3) neither baseline nor stress-induced plasma corticosterone differed across subspecies, suggesting energetic demands of the common garden were insufficient to induce a differential adrenocortical response in either subspecies, highlighting the impact of environmental conditions on corticosterone secretion. Thus, in a common garden experiment, Z. l. gambelii responds differently to the initial predictive cue, photoperiod, to initiate and execute the vernal stages of molt, migration and development of breeding in comparison to the shared stage of breeding with Z. l. nuttalli, confirming a genetic basis for the subspecies differences.

Unobtrusive and Continuous Monitoring of Alcohol-impaired Gait Using Smart Shoes.

BACKGROUND: Alcohol ingestion influences sensory-motor function and the overall well-being of individuals. Detecting alcohol-induced impairments in gait in daily life necessitates a continuous and unobtrusive gait monitoring system. OBJECTIVES: This paper introduces the development and use of a non-intrusive monitoring system to detect changes in gait induced by alcohol intoxication. METHODS: The proposed system employed a pair of sensorized smart shoes that are equipped with pressure sensors on the insole. Gait features were extracted and adjusted based on individual's gait profile. The adjusted gait features were used to train a machine learning classifier to discriminate alcohol-impaired gait from normal walking. In experiment of pilot study, twenty participants completed walking trials on a 12 meter walkway to measure their sober walking and alcohol-impaired walking using smart shoes. RESULTS: The proposed system can detect alcohol-impaired gait with an accuracy of 86.2 % when pressure value analysis and person-dependent model for the classifier are applied, while statistical analysis revealed that no single feature was discriminative for the detection of gait impairment. CONCLUSIONS: Alcohol-induced gait disturbances can be detected with smart shoe technology for an automated monitoring in ubiquitous environment. We demonstrated that personal monitoring and machine learning-based prediction could be customized to detect individual variation rather than applying uniform boundary parameters of gait.