A parametric study on supercritical water gasification of Laminaria hyperborea: a carbohydrate-rich macroalga.

The potential of supercritical water gasification (SCWG) of macroalgae for hydrogen and methane production has been investigated in view of the growing interest in a future macroalgae biorefinery concept. The compositions of syngas from the catalytic SCWG of Laminaria hyperborea under varying parameters including catalyst loading, feed concentration, hold time and temperature have been investigated. Their effects on gas yields, gasification efficiency and energy recovery are presented. Results show that the carbon gasification efficiencies increased with reaction temperature, reaction hold time and catalyst loading but decreased with increasing feed concentrations. In addition, the selectivity towards hydrogen and/or methane production from the SCWG tests could be controlled by the combination of catalysts and varying reaction conditions. For instance, Ru/Al2O3 gave highest carbon conversion and highest methane yield of up to 11 mol/kg, whilst NaOH produced highest hydrogen yield of nearly 30 mol/kg under certain gasification conditions

Identification of regulatory variants associated with genetic susceptibility to meningococcal disease

Non-coding genetic variants play an important role in driving susceptibility to complex diseases but their characterization remains challenging. Here, we employed a novel approach to interrogate the genetic risk of such polymorphisms in a more systematic way by targeting specific regulatory regions relevant for the phenotype studied. We applied this method to meningococcal disease susceptibility, using the DNA binding pattern of RELA - a NF-kB subunit, master regulator of the response to infection - under bacterial stimuli in nasopharyngeal epithelial cells. We designed a custom panel to cover these RELA binding sites and used it for targeted sequencing in cases and controls. Variant calling and association analysis were performed followed by validation of candidate polymorphisms by genotyping in three independent cohorts. We identified two new polymorphisms, rs4823231 and rs11913168, showing signs of association with meningococcal disease susceptibility. In addition, using our genomic data as well as publicly available resources, we found evidences for these SNPs to have potential regulatory effects on ATXN10 and LIF genes respectively. The variants and related candidate genes are relevant for infectious diseases and may have important contribution for meningococcal disease pathology. Finally, we described a novel genetic association approach that could be applied to other phenotypes

Fully automated nipple detection in 3D breast ultrasound images

Nipple position provides useful diagnostic informations in reading automated 3D breast ultrasound (ABUS) images. The identification of nipples is required to localize and determine the quadrants of breast lesions. Additionally, the nipple position serves as an effective landmark to register an ABUS image to other imaging modalities, such as digital mammography, breast magnet resonance imaging (MRI), or tomosynthesis. Nevertheless, the presence of speckle noise induced by interference waves and variant imaging directions in ultrasonography poses challenges to the task. In this work, we propose a fast and automated algorithm to detect nipples in 3D breast ultrasound images. The method fully takes advantages of the consistent characteristics of ultrasonographic signals observed at nipples and employs a multi-scale Laplacian-based blob detector to eventually identify nipple positions. The accuracy of the proposed method was tested on 113 ABUS images, resulting in a distance error of 6.6±8.9 mm (mean ±std)

A hybrid method towards automated nipple detection in 3D breast ultrasound images

In clinical work-up of breast cancer, nipple position is an important marker to locate lesions. Moreover, it serves as an effective landmark to register a 3D automated breast ultrasound (ABUS) images to other imaging modalities, e.g., X-ray mammography, tomosynthesis or magnetic resonance imaging (MRI). However, the presence of speckle noises caused by the interference waves and variant imaging directions poses challenges to automatically identify nipple positions. In this work, a hybrid fully automatic method to detect nipple positions in ABUS images is presented. The method extends the multi-scale Laplacian-based method that we proposed previously, by integrating a specially designed Hessian-based method to locate the shadow area beneath the nipple and areola. Subsequently, the likelihood maps of nipple positions generated by both methods are combined to build a joint-likelihood map, where the final nipple position is extracted. To validate the efficiency and robustness, the extended hybrid method was tested on 926 ABUS images, resulting in a distance error of 7.08±10.96 mm (mean±standard deviation)

Dreidimensionale Beurteilung der Brustzusammensetzung mit dem Automatisierten Brust Volumen Scanner (ABVS)

Studienziel: In der Bildgebung der Brust ist die Information für das Erkrankungsrisiko für die Brusterkrankung enthalten. Die mammografische Dichte oder der Drüsenanteil in der MRT- Untersuchung sind mit dem Brustkrebsrisiko bereits assoziiert worden. Graustufenwerte des B-Bildes im Ultraschall sind weiterhin mit der mammografischen Dichte assoziiert. Ziel dieser Untersuchung war es, die dreidimensionale Information der ABVS-Brustuntersuchung mit der mammografischen Dichte und dem Brustkrebsrisiko zu assoziieren. Methoden: Im Rahmen einer prospektiven Studie (BMBF-Spitzencluster BD04) zur Risikoprädiktion und Detektion von Brustkrebs wurden ABVS Aufnahmen (ACUSON S2000, SIEMENS) von 100 invasiven Mammakarzinomen und 100 Kontrollen gewonnen. An den gewonnenen dreidimensionalen Bilddaten sind Graustufenwertanalysen vorgenommen und zwischen den Fällen und Kontrollen verglichen worden. Weiterhin sind die Graustufenwerte mit der Mammografischen Dichte verglichen worden. Ergebnisse: Die Gewinnung und Verarbeitung der Bilddaten konnte im Rahmen der klinischen Routine für Patientinnen der allgemeinen Brustsprechstunde problemlos implementiert worden. Die komplette Erfassung der dreidimensionalen Daten dauerte im Durchschnitt 20 Minuten. Die detaillierte Analyse der Graustufenwerte wird vorgestellt. Schlussfolgerungen: Dreidimensionaler Ultraschall mittels ABVS kann unkompliziert in die klinische Routine implementiert werden. Die datentechnische Prozessierung und Analyse der Bilddaten ist unkompliziert und kann zu klinischen und wissenschaftlichen Zwecken verwendet werden

DATASET Comparative and Integrated Analysis of Plasma Extracellular Vesicles Isolation Methods in Healthy Volunteers and Patients Following Myocardial Infarction - Healthy Volunteer Dataset used for Integrated Analysis

The file contains data from the manuscript: Comparative and Integrated Analysis of Plasma Extracellular Vesicles Isolations Methods in Healthy Volunteers and Patients Following Myocardial Infarction. In short, plasma extracellular vesicles (EV) were isolated from 500 µL of platelet poor plasma of healthy volunteers and characterised by nanoparticle tracking analysis, protein concentration assay (BCA), targeted EV protein array, unbiased proteomics and targeted sphingolipidomics. The data was collated in an excel file and transformed to a Z-score. The data is deposited for public access

DATASET Comparative and Integrated Analysis of Plasma Extracellular Vesicles Isolation Methods in Healthy Volunteers and Patients Following Myocardial Infarction - Healthy Volunteer Dataset used for Integrated Analysis

The file contains data from the manuscript: Comparative and Integrated Analysis of Plasma Extracellular Vesicles Isolations Methods in Healthy Volunteers and Patients Following Myocardial Infarction. In short, plasma extracellular vesicles (EV) were isolated from 500 µL of platelet poor plasma of healthy volunteers and characterised by nanoparticle tracking analysis, protein concentration assay (BCA), targeted EV protein array, unbiased proteomics and targeted sphingolipidomics. The data was collated in an excel file and transformed to a Z-score. The data is deposited for public access