Improving the design of industrial microwave processing systems through prediction of the dielectric properties of complex multi-layered materials

Rigorous design of industrial microwave processing systems requires in-depth knowledge of the dielectric properties of the materials to be processed. These values are not easy to measure, particularly when a material is multi-layered containing multiple phases, when one phase has a much higher loss than the other and the application is based on selective heating. This paper demonstrates the ability of the Clausius-Mossotti (CM) model to predict the dielectric constant of multi-layered materials. Furthermore, mixing rules and graphical extrapolation techniques were used to further evidence our conclusions and to estimate the loss factor. The material used for this study was vermiculite, a layered alumina-silicate mineral containing up to 10 % of an interlayer hydrated phase. It was measured at different bulk densities at two distinct microwave frequencies, namely 934 and 2143 MHz. The CM model, based on the ionic polarisability of the bulk material, gives only a prediction of the dielectric constant for experimental data with a deviation of less than 5 % at microwave frequencies. The complex refractive index model (CRIM), Landau, Lifshitz and Loyenga (LLL), Goldschmidt, Böttcher and Bruggeman-Hanai model equations are then shown to give a strong estimation of both dielectric constant and loss factor of the solid material compared to that of the measured powder with a deviation of less than 1 %. Results obtained from this work provide a basis for the design of further electromagnetic processing systems for multi-layered materials consisting of both high loss and low loss components

Clinical pregenetic screening for stroke monogenic diseases: Results from lombardia GENS registry

BACKGROUND AND PURPOSE: Lombardia GENS is a multicentre prospective study aimed at diagnosing 5 single-gene disorders associated with stroke (cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, Fabry disease, MELAS [mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes], hereditary cerebral amyloid angiopathy, and Marfan syndrome) by applying diagnostic algorithms specific for each clinically suspected disease METHODS: We enrolled a consecutive series of patients with ischemic or hemorrhagic stroke or transient ischemic attack admitted in stroke units in the Lombardia region participating in the project. Patients were defined as probable when presenting with stroke or transient ischemic attack of unknown etiopathogenic causes, or in the presence of <3 conventional vascular risk factors or young age at onset, or positive familial history or of specific clinical features. Patients fulfilling diagnostic algorithms specific for each monogenic disease (suspected) were referred for genetic analysis. RESULTS: In 209 patients (57.4\ub114.7 years), the application of the disease-specific algorithm identified 227 patients with possible monogenic disease. Genetic testing identified pathogenic mutations in 7% of these cases. Familial history of stroke was the only significant specific feature that distinguished mutated patients from nonmutated ones. The presence of cerebrovascular risk factors did not exclude a genetic disease. CONCLUSIONS: In patients prescreened using a clinical algorithm for monogenic disorders, we identified monogenic causes of events in 7% of patients in comparison to the 1% to 5% prevalence reported in previous series

Stoichiometric representation of geneproteinreaction associations leverages constraint-based analysis from reaction to gene-level phenotype prediction

Genome-scale metabolic reconstructions are currently available for hundreds of organisms. Constraint-based modeling enables the analysis of the phenotypic landscape of these organisms, predicting the response to genetic and environmental perturbations. However, since constraint-based models can only describe the metabolic phenotype at the reaction level, understanding the mechanistic link between genotype and phenotype is still hampered by the complexity of gene-protein-reaction associations. We implement a model transformation that enables constraint-based methods to be applied at the gene level by explicitly accounting for the individual fluxes of enzymes (and subunits) encoded by each gene. We show how this can be applied to different kinds of constraint-based analysis: flux distribution prediction, gene essentiality analysis, random flux sampling, elementary mode analysis, transcriptomics data integration, and rational strain design. In each case we demonstrate how this approach can lead to improved phenotype predictions and a deeper understanding of the genotype-to-phenotype link. In particular, we show that a large fraction of reaction-based designs obtained by current strain design methods are not actually feasible, and show how our approach allows using the same methods to obtain feasible gene-based designs. We also show, by extensive comparison with experimental 13C-flux data, how simple reformulations of different simulation methods with gene-wise objective functions result in improved prediction accuracy. The model transformation proposed in this work enables existing constraint-based methods to be used at the gene level without modification. This automatically leverages phenotype analysis from reaction to gene level, improving the biological insight that can be obtained from genome-scale models.DM was supported by the Portuguese Foundationfor Science and Technologythrough a post-doc fellowship (ref: SFRH/BPD/111519/ 2015). This study was supported by the PortugueseFoundationfor Science and Technology (FCT) under the scope of the strategic fundingof UID/BIO/04469/2013 unitand COMPETE2020 (POCI-01-0145-FEDER-006684) and BioTecNorte operation (NORTE-01-0145FEDER-000004) fundedby EuropeanRegional Development Fund under the scope of Norte2020Programa Operacional Regional do Norte. This project has received fundingfrom the European Union’s Horizon 2020 research and innovation programme under grant agreementNo 686070. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Treatment Patterns and Use of Resources in Patients With Tuberous Sclerosis Complex: Insights From the TOSCA Registry

Tuberous Sclerosis Complex (TSC) is a rare autosomal-dominant disorder caused by mutations in the TSC1 or TSC2 genes. Patients with TSC may suffer from a wide range of clinical manifestations; however, the burden of TSC and its impact on healthcare resources needed for its management remain unknown. Besides, the use of resources might vary across countries depending on the country-specific clinical practice. The aim of this paper is to describe the use of TSC-related resources and treatment patterns within the TOSCA registry. A total of 2,214 patients with TSC from 31 countries were enrolled and had a follow-up of up to 5 years. A search was conducted to identify the variables containing both medical and non-medical resource use information within TOSCA. This search was performed both at the level of the core project as well as at the level of the research projects on epilepsy, subependymal giant cell astrocytoma (SEGA), lymphangioleiomyomatosis (LAM), and renal angiomyolipoma (rAML) taking into account the timepoints of the study, age groups, and countries. Data from the quality of life (QoL) research project were analyzed by type of visit and age at enrollment. Treatments varied greatly depending on the clinical manifestation, timepoint in the study, and age groups. GAB Aergics were the most prescribed drugs for epilepsy, and mTOR inhibitors are dramatically replacing surgery in patients with SEGA, despite current recommendations proposing both treatment options. mTOR inhibitors are also becoming common treatments in rAML and LAM patients. Forty-two out of the 143 patients (29.4%) who participated in the QoL research project reported inpatient stays over the last year. Data from non-medical resource use showed the critical impact of TSC on job status and capacity. Disability allowances were more common in children than adults (51.1% vs 38.2%). Psychological counseling, social services and social worker services were needed by <15% of the patients, regardless of age. The long-term nature, together with the variability in its clinical manifestations, makes TSC a complex and resource-demanding disease. The present study shows a comprehensive picture of the resource use implications of TSC

Combined Tevatron upper limit on gg->H->W+W- and constraints on the Higgs boson mass in fourth-generation fermion models

Report number: FERMILAB-PUB-10-125-EWe combine results from searches by the CDF and D0 collaborations for a standard model Higgs boson (H) in the process gg->H->W+W- in p=pbar collisions at the Fermilab Tevatron Collider at sqrt{s}=1.96 TeV. With 4.8 fb-1 of integrated luminosity analyzed at CDF and 5.4 fb-1 at D0, the 95% Confidence Level upper limit on \sigma(gg->H) x B(H->W+W-) is 1.75 pb at m_H=120 GeV, 0.38 pb at m_H=165 GeV, and 0.83 pb at m_H=200 GeV. Assuming the presence of a fourth sequential generation of fermions with large masses, we exclude at the 95% Confidence Level a standard-model-like Higgs boson with a mass between 131 and 204 GeV.We combine results from searches by the CDF and D0 collaborations for a standard model Higgs boson (H) in the process gg→H→W+W- in pp̅ collisions at the Fermilab Tevatron Collider at √s=1.96  TeV. With 4.8  fb-1 of integrated luminosity analyzed at CDF and 5.4  fb-1 at D0, the 95% confidence level upper limit on σ(gg→H)×B(H→W+W-) is 1.75 pb at mH=120  GeV, 0.38 pb at mH=165  GeV, and 0.83 pb at mH=200  GeV. Assuming the presence of a fourth sequential generation of fermions with large masses, we exclude at the 95% confidence level a standard-model-like Higgs boson with a mass between 131 and 204 GeV.Peer reviewe

A comprehensive overview of radioguided surgery using gamma detection probe technology

The concept of radioguided surgery, which was first developed some 60 years ago, involves the use of a radiation detection probe system for the intraoperative detection of radionuclides. The use of gamma detection probe technology in radioguided surgery has tremendously expanded and has evolved into what is now considered an established discipline within the practice of surgery, revolutionizing the surgical management of many malignancies, including breast cancer, melanoma, and colorectal cancer, as well as the surgical management of parathyroid disease. The impact of radioguided surgery on the surgical management of cancer patients includes providing vital and real-time information to the surgeon regarding the location and extent of disease, as well as regarding the assessment of surgical resection margins. Additionally, it has allowed the surgeon to minimize the surgical invasiveness of many diagnostic and therapeutic procedures, while still maintaining maximum benefit to the cancer patient. In the current review, we have attempted to comprehensively evaluate the history, technical aspects, and clinical applications of radioguided surgery using gamma detection probe technology

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700

Search for Dark Matter and Supersymmetry with a Compressed Mass Spectrum in the Vector Boson Fusion Topology in Proton-Proton Collisions at root s=8 TeV

Peer reviewe