Particle-in-cell Simulation Concerning Heat-flux Mitigation Using Electromagnetic Fields

The Particle-in-Cell (PIC) method was used to study heat flux mitigation experiments with argon. In the experiment it was shown that a magnetic field allows to reduce the heat flux towards a target. PIC is well-suited for plasma simulation, giving the chance to get a better basic understanding of the underlying physics. The simulation demonstrates the importance of a self-consistent neutral-plasma description to understand the effect of heat flux reduction

Prediction of circulating adipokine levels based on body fat compartments and adipose tissue gene expression

BACKGROUND: Adipokines are hormones secreted from adipose tissue (AT), and a number of them have been established as risk factors for chronic diseases. However, it is not clear whether and to what extent adiposity, gene expression, and other factors determine their circulating levels. OBJECTIVES: To assess to what extent adiposity, as measured by the amount of subcutaneous AT (SAT) and visceral AT (VAT) using magnetic resonance imaging, and gene expression levels in SAT determine plasma concentrations of the adipokines adiponectin, leptin, soluble leptin receptor, resistin, interleukin 6, and fatty acid-binding protein 4 (FABP4). METHODS: We performed a cross-sectional analysis of 156 participants from the EPIC Potsdam cohort study and analyzed multiple regression models and partial correlation coefficients. RESULTS: For leptin and FABP4 concentrations, 81 and 45% variance were explained by SAT mass, VAT mass, and gene expression in SAT in multivariable regression models. For the remaining adipokines, AT mass and gene expression explained <16% variance of plasma concentrations. Gene expression in SAT was a less important predictor compared to AT mass. SAT mass was a better predictor than VAT mass for leptin (partial correlation r = 0.81, 95% confidence interval 0.75–0.86, vs. r = 0.58, 95% confidence interval 0.46–0.67), while differences between AT compartments were small for the other adipokines. CONLUSIONS: While plasma levels of leptin and FABP4 can be explained in a large and medium part by the amount of AT and SAT gene expression, surprisingly, these predictors explained only little variance for all other investigated adipokines

Joint analysis of multiple phenotypes: summary of results and discussions from the Genetic Analysis Workshop 19

For Genetic Analysis Workshop 19, 2 extensive data sets were provided, including whole genome and whole exome sequence data, gene expression data, and longitudinal blood pressure outcomes, together with nongenetic covariates. These data sets gave researchers the chance to investigate different aspects of more complex relationships within the data, and the contributions in our working group focused on statistical methods for the joint analysis of multiple phenotypes, which is part of the research field of data integration. The analysis of data from different sources poses challenges to researchers but provides the opportunity to model the real-life situation more realistically. Our 4 contributions all used the provided real data to identify genetic predictors for blood pressure. In the contributions, novel multivariate rare variant tests, copula models, structural equation models and a sparse matrix representation variable selection approach were applied. Each of these statistical models can be used to investigate specific hypothesized relationships, which are described together with their biological assumptions. The results showed that all methods are ready for application on a genome-wide scale and can be used or extended to include multiple omics data sets. The results provide potentially interesting genetic targets for future investigation and replication. Furthermore, all contributions demonstrated that the analysis of complex data sets could benefit from modeling correlated phenotypes jointly as well as by adding further bioinformatics information

Publisher Correction: Computer-aided interpretation of chest radiography reveals the spectrum of tuberculosis in rural South Africa

The original version of this Article contained errors in the affiliations of members of the Vukuzazi Team. Anand Ramnanan, Anele Mkhwanazi, Antony Rapulana, Anupa Singh, Ashentha Govender, Ayanda Zungu, Bongani Magwaza, Bongumenzi Ndlovu, Clive Mavimbela, Costa Criticos, Day Munatsi, Dilip Kalyan, Doctar Mlambo, Fezeka Mfeka, Freddy Mabetlela, Gregory Ording-Jespersen, Hannah Keal, Hlengiwe Dlamini, Hlengiwe Khathi, Hlobisile Chonco, Hlobisile Gumede, Hlolisile Khumalo, Hloniphile Ngubane, Hollis Shen, Innocentia Mpofana, Jaco Dreyer, Jade Cousins, Kandaseelan Chetty, Kayleen Brien, Khadija Khan, Khanyisani Buthelezi, Kimeshree Perumal, Kobus Herbst, Lindani Mthembu, Logan Pillay, Mandisi Dlamini, Mandlakayise Zikhali, Mbali Mbuyisa, Mbuti Mofokeng, Melusi Sibiya, Mlungisi Dube, Mpumelelo Steto, Mzamo Buthelezi, Nagavelli Padayachi, Nceba Gqaleni, Ngcebo Mhlongo, Nokukhanya Ntshakala, Nomathamsanqa Majozi, Nombuyiselo Zondi, Nomfundo Luthuli, Nomfundo Ngema, Nompilo Buthelezi, Nonceba Mfeka, Nondumiso Khuluse, Nondumiso Mabaso, Nondumiso Zitha, Nonhlanhla Mfekayi, Nonhlanhla Mzimela, Nozipho Mbonambi, Ntombiyenhlanhla Mkhwanazi, Ntombiyenkosi Ntombela, Pamela Ramkalawon, Phakamani Mkhwanazi, Philippa Mathews, Phumelele Mthethwa, Phumla Ngcobo, Raynold Zondo, Rochelle Singh, Rose Myeni, Sanah Bucibo, Sandile Mthembu, Sashin Harilall, Senamile Makhari, Seneme Mchunu, Senzeni Mkhwanazi, Sibahle Gumbi, Siboniso Nene, Sibusiso Mhlongo, Sibusiso Mkhwanazi, Sibusiso Nsibande, Simphiwe Ntshangase, Siphephelo Dlamini, Sithembile Ngcobo, Siyabonga Nsibande, Siyabonga Nxumalo, Sizwe Ndlela, Skhumbuzo Mthombeni, Smangaliso Zulu, Sphiwe Clement Mthembu, Sphiwe Ntuli, Talente Ntimbane, Thabile Zondi, Thandeka Khoza, Thengokwakhe Nkosi, Thokozani Bhengu, Thokozani Simelane, Tshwaraganang Modise, Tumi Madolo, Welcome Petros Mthembu, Xolani Mkhize, Zamashandu Mbatha, Zinhle Buthelezi, Zinhle Mthembu and Zizile Sikhosana were incorrectly associated with “Digital Health & Machine Learning, Hasso Plattner Institute for Digital Engineering, Berlin, Germany” and the affiliation “Africa Health Research Institute, KwaZulu-Natal, South Africa” was inadvertently omitted. This has now been corrected in both the PDF and HTML versions of the Article

Computer-aided interpretation of chest radiography reveals the spectrum of tuberculosis in rural South Africa.

Computer-aided digital chest radiograph interpretation (CAD) can facilitate high-throughput screening for tuberculosis (TB), but its use in population-based active case-finding programs has been limited. In an HIV-endemic area in rural South Africa, we used a CAD algorithm (CAD4TBv5) to interpret digital chest x-rays (CXR) as part of a mobile health screening effort. Participants with TB symptoms or CAD4TBv5 score above the triaging threshold were referred for microbiological sputum assessment. During an initial pilot phase, a low CAD4TBv5 triaging threshold of 25 was selected to maximize TB case finding. We report the performance of CAD4TBv5 in screening 9,914 participants, 99 (1.0%) of whom were found to have microbiologically proven TB. CAD4TBv5 was able to identify TB cases at the same sensitivity but lower specificity as a blinded radiologist, whereas the next generation of the algorithm (CAD4TBv6) achieved comparable sensitivity and specificity to the radiologist. The CXRs of people with microbiologically confirmed TB spanned a range of lung field abnormality, including 19 (19.2%) cases deemed normal by the radiologist. HIV serostatus did not impact CAD4TB's performance. Notably, 78.8% of the TB cases identified during this population-based survey were asymptomatic and therefore triaged for sputum collection on the basis of CAD4TBv5 score alone. While CAD4TBv6 has the potential to replace radiologists for triaging CXRs in TB prevalence surveys, population-specific piloting is necessary to set the appropriate triaging thresholds. Further work on image analysis strategies is needed to identify radiologically subtle active TB

An Experimental Study on Heat-Flux Reduction by Electromagnetic Effects in Ionized Flows

Flow Control using electromagnetic fields is one of the options to reduce aerothermal loads to the spacecraft structures in ionized high enthalpy flows. First computational studies made immediately evident the necessity of well designed and cleanly performed experiments. Therefore in the frame of ESA collaborative study on the electrodynamic-heatshield concept an experimental study has been carried out in the arc heated facility L2K. The results of the experiments should also lead to a better understanding of physical phenomena and providing reliable data for the validation of numerical codes. A cylinder with a flat upstream end with integrated magnet coils were investigated in a hypersonic high-enthalpy ionized-argon flow fiel