A Plasma Reactor for the Synthesis of High-Temperature Materials: Electro Thermal, Processing and Service Life Characteristics

The three-jet direct-flow plasma reactor with a channel diameter of 0.054 m was studied in terms of service life, thermal, technical, and functional capabilities. It was established that the near-optimal combination of thermal efficiency, required specific enthalpy of the plasma-forming gas and its mass flow rate is achieved at a reactor power of 150 kW. The bulk temperature of plasma flow over the rector of 12 gauges long varies within 5500±3200 K and the wall temperature within 1900±850 K, when a cylinder from zirconium dioxide of 0.005 m thick is used to thermally insulate the reactor. The specific electric power reaches a high of 1214 MW/m{3}. The rated service life of electrodes is 4700 hours for a copper anode and 111 hours for a tungsten cathode. The projected contamination of carbides and borides with elec-trode-erosion products doesn't exceed 0.0001% of copper and 0.00002% of tungsten

Sleep quality does not mediate the negative effects of chronodisruption on body composition and metabolic syndrome in healthcare workers in Ecuador

Background and aims: The objective of the present work was to determine to what extent sleep quality may mediate the association between chronodisruption (CD) and metabolic syndrome (MS), and between CD and body composition (BC). Methodology: Cross-sectional study which included 300 adult health workers, 150 of whom were night shift workers and thereby exposed to CD. Diagnosis of MS was made based on Adult Treatment Panel III criteria. Sleep quality was measured using the Pittsburgh Sleep Quality Index. Body mass index (BMI), fat mass percentage, and visceral fat percentage were mea

Satellites in the Ti 1s core level spectra of SrTiO3 and TiO2

Satellites in core level spectra of photoelectron spectroscopy (PES) can provide crucial information on the electronic structure and chemical bonding in materials, particularly in transition metal oxides. This paper explores satellites of the Ti 1s and 2p core level spectra of SrTiO3 and TiO2. Conventionally, soft x-ray PES (SXPS) probes the Ti 2p core level; however, it is not ideal to fully capture satellite features due to its inherent spin-orbit splitting (SOS). Here, hard x-ray PES (HAXPES) provides access to the Ti 1s spectrum instead, which allows us to study intrinsic charge responses upon core-hole creation without the complication from SOS and with favorable intrinsic linewidths. The experimental spectra are theoretically analyzed by two impurity models, including an Anderson impurity model (AIM) built on local density approximation (LDA) and dynamical mean-field theory (DMFT), and a conventional TiO6 cluster model. The theoretical results emphasize the importance of explicit inclusion of higher-order Ti-O charge-transfer processes beyond the nearest-neighboring Ti-O bond to simulate the core level spectra of SrTiO3 and TiO2. The AIM approach with continuous bath orbitals provided by LDA+DMFT represents the experimental spectra well. Crucially, with the aid of the LDA+DMFT method, this paper provides a robust prescription of how to use the computationally cheap cluster model in fitting analyses of core level spectra

Interventions with Music in PECTus excavatum treatment (IMPECT trial)

INTRODUCTION: Pectus excavatum repair is associated with substantial postoperative pain, despite the use of epidural analgesia and other analgesic regimens. Perioperative recorded music interventions have been shown to alleviate pain and anxiety in adults, but evidence for children and adolescents is still lacking. This study protocol describes a randomised controlled trial that evaluates the effects of recorded music interventions on postoperative pain relief in children and adolescents after pectus excavatum repair. METHODS: A multicentre randomised controlled trial was se

Evaluación del ISTH-BAT en los trastornos plaquetarios congénitos: correlación clínica, laboratorio y molecular

CO-153 Introducción: Los trastornos plaquetarios congénitos (TPC) son un grupo heterogéneo de enfermedades raras, que se clasifican en trombocitopenias hereditarias (THs) y en trombocitopatías hereditarias (TFPs). Su identificación inicial y su diagnóstico final son complejos. Éste, se basa en la la historia clínica, la exploración física, pruebas de laboratorio fenotípicas y la confirmación de la alteración molecular subyacente. Por otra parte, la valoración de la clínica hemorrágica suele ser subjetiva, por lo que la Sociedad Internacional de Trombosis y Hemostasia (ISTH) recomienda la utilización de escalas de sangrado (bleeding assessment tools, BAT). Los objetivos de nuestros estudios fueron a) evaluar la clínica hemorrágica con el ISTH-BAT en pacientes diagnosticados de TPC, b) su comparación entre THs y TFPs y c) su relación con las pruebas funcionales y moleculares. Métodos: Estudio retrospectivo de 138 pacientes con TPC incluidos en el proyecto nacional “Caracterización funcional y molecular de los TPC” de la SETH. La clínica hemorrágica se evaluó mediante el ISTHBAT, obteniendo un score de sangrado (BS). El diagnóstico fenotípico se realizó mediante hemograma y frotis de sangre periférica, la función plaquetaria mediante agregometría de transmisión de luz (LTA) y citometría de flujo (CMF) y el diagnóstico molecular mediante secuenciación ..

Mega-analysis of association between obesity and cortical morphology in bipolar disorders:ENIGMA study in 2832 participants

Background: Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact. Methods: We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations. Results: BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI. Conclusions: We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.</p

Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders—ENIGMA study in people with bipolar disorders and obesity

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. Practitioner Points: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.</p

Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders—ENIGMA study in people with bipolar disorders and obesity

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. Practitioner Points: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.</p

Genome-wide association analysis identifies variants associated with nonalcoholic fatty liver disease that have distinct effects on metabolic traits

Nonalcoholic fatty liver disease (NAFLD) clusters in families, but the only known common genetic variants influencing risk are near PNPLA3. We sought to identify additional genetic variants influencing NAFLD using genome-wide association (GWA) analysis of computed tomography (CT) measured hepatic steatosis, a non-invasive measure of NAFLD, in large population based samples. Using variance components methods, we show that CT hepatic steatosis is heritable (∼26%-27%) in family-based Amish, Family Heart, and Framingham Heart Studies (n = 880 to 3,070). By carrying out a fixed-effects meta-analysis of genome-wide association (GWA) results between CT hepatic steatosis and ∼2.4 million imputed or genotyped SNPs in 7,176 individuals from the Old Order Amish, Age, Gene/Environment Susceptibility-Reykjavik study (AGES), Family Heart, and Framingham Heart Studies, we identify variants associated at genome-wide significant levels (p<5×10(-8)) in or near PNPLA3, NCAN, and PPP1R3B. We genotype these and 42 other top CT hepatic steatosis-associated SNPs in 592 subjects with biopsy-proven NAFLD from the NASH Clinical Research Network (NASH CRN). In comparisons with 1,405 healthy controls from the Myocardial Genetics Consortium (MIGen), we observe significant associations with histologic NAFLD at variants in or near NCAN, GCKR, LYPLAL1, and PNPLA3, but not PPP1R3B. Variants at these five loci exhibit distinct patterns of association with serum lipids, as well as glycemic and anthropometric traits. We identify common genetic variants influencing CT-assessed steatosis and risk of NAFLD. Hepatic steatosis associated variants are not uniformly associated with NASH/fibrosis or result in abnormalities in serum lipids or glycemic and anthropometric traits, suggesting genetic heterogeneity in the pathways influencing these traits.Peer reviewe