Reynolds number effect on the wake of two staggered cylinders

Author name used in this publication: Y. Zhou2009-2010 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Measuring Invisible Particle Masses Using a Single Short Decay Chain

We consider the mass measurement at hadron colliders for a decay chain of two steps, which ends with a missing particle. Such a topology appears as a subprocess of signal events of many new physics models which contain a dark matter candidate. From the two visible particles coming from the decay chain, only one invariant mass combination can be formed and hence it is na\"ively expected that the masses of the three invisible particles in the decay chain cannot be determined from a single end point of the invariant mass distribution. We show that the event distribution in the $\log(E_{1T}/E_{2T})$ vs. invariant mass-squared plane, where $E_{1T}$, $E_{2T}$ are the transverse energies of the two visible particles, contains the information of all three invisible particle masses and allows them to be extracted individually. The experimental smearing and combinatorial issues pose challenges to the mass measurements. However, in many cases the three invisible particle masses in the decay chain can be determined with reasonable accuracies.Comment: 45 pages, 32 figure

Double differentiation in a cross-national comparison of populist political movements and online media uses in the United States and the Netherlands

In a context of highly visible and politically influential populist movements, this study considers the online self-representation of the Tea Party Patriots (TPP) in the United States and the Party for Freedom (PVV) in the Netherlands. A multi-methodological approach was adopted to compare the discursive manifestation of key populism concepts: leadership characteristics, adversary definition and mobilizing information. Analyses reconstruct and account for similarities and differences in discursive framing strategies of 'double differentiation' through which both movements attempt inclusion in and exclusion from the political establishment, and, in doing so, mobilize communities of support. Altogether, this study advances the understanding of what constitutes 'unmediated' content that is presented through user-generated media production, and how self-determined media spaces have facilitated shifts in populist media legitimation and political representation in two politically unique countries

The Oslo definitions for coeliac disease and related terms.

ObjectiveThe literature suggests a lack of consensus on the use of terms related to coeliac disease (CD) and gluten.DesignA multidisciplinary task force of 16 physicians from seven countries used the electronic database PubMed to review the literature for CD-related terms up to January 2011. Teams of physicians then suggested a definition for each term, followed by feedback of these definitions through a web survey on definitions, discussions during a meeting in Oslo and phone conferences. In addition to 'CD', the following descriptors of CD were evaluated (in alphabetical order): asymptomatic, atypical, classical, latent, non-classical, overt, paediatric classical, potential, refractory, silent, subclinical, symptomatic, typical, CD serology, CD autoimmunity, genetically at risk of CD, dermatitis herpetiformis, gluten, gluten ataxia, gluten intolerance, gluten sensitivity and gliadin-specific antibodies.ResultsCD was defined as 'a chronic small intestinal immune-mediated enteropathy precipitated by exposure to dietary gluten in genetically predisposed individuals'. Classical CD was defined as 'CD presenting with signs and symptoms of malabsorption. Diarrhoea, steatorrhoea, weight loss or growth failure is required.' 'Gluten-related disorders' is the suggested umbrella term for all diseases triggered by gluten and the term gluten intolerance should not to be used. Other definitions are presented in the paper.ConclusionThis paper presents the Oslo definitions for CD-related terms

Uptake and transport of novel amphiphilic polyelectrolyte-insulin nanocomplexes by caco-2 cells - towards oral insulin

“The original publication is available at www.springerlink.com”. Copyright SpringerPurpose: The influence of polymer architecture on cellular uptake and transport across Caco-2 cells of novel amphiphilic polyelectrolyte-insulin nanocomplexes was investigated. Method: Polyallylamine (PAA) (15 kDa) was grafted with palmitoyl chains (Pa) and subsequently modified with quaternary ammonium moieties (QPa). These two amphiphilic polyelectrolytes (APs) were tagged with rhodamine and their uptake by Caco-2 cells or their polyelectrolyte complexes (PECs) with fluorescein isothiocyanate-insulin (FITC-insulin) uptake were investigated using fluorescence microscopy. The integrity of the monolayer was determined by measurement of transepithelial electrical resistance (TEER). Insulin transport through Caco-2 monolayers was determined during TEER experiments. Result: Pa and insulin were co-localised in the cell membranes while QPa complexes were found within the cytoplasm. QPa complex uptake was not affected by calcium, cytochalasin D or nocodazole. Uptake was reduced by co-incubation with sodium azide, an active transport inhibitor. Both polymers opened tight junctions reversibly where the TEER values fell by up to 35 % within 30 minutes incubation with Caco-2 cells. Insulin transport through monolayers increased when QPa was used (0.27 ngmL-1 of insulin in basal compartment) compared to Pa (0.14 ngmL-1 of insulin in basal compartment) after 2 hours. Conclusion: These APs have been shown to be taken up by Caco-2 cells and reversibly open tight cell junctions. Further work is required to optimise these formulations with a view to maximising their potential to facilitate oral delivery of insulin.Peer reviewe

Improving the Generalizability of Convolutional Neural Network-Based Segmentation on CMR Images

Background: Convolutional neural network (CNN) based segmentation methods provide an efficient and automated way for clinicians to assess the structure and function of the heart in cardiac MR images. While CNNs can generally perform the segmentation tasks with high accuracy when training and test images come from the same domain (e.g., same scanner or site), their performance often degrades dramatically on images from different scanners or clinical sites. / Methods: We propose a simple yet effective way for improving the network generalization ability by carefully designing data normalization and augmentation strategies to accommodate common scenarios in multi-site, multi-scanner clinical imaging data sets. We demonstrate that a neural network trained on a single-site single-scanner dataset from the UK Biobank can be successfully applied to segmenting cardiac MR images across different sites and different scanners without substantial loss of accuracy. Specifically, the method was trained on a large set of 3,975 subjects from the UK Biobank. It was then directly tested on 600 different subjects from the UK Biobank for intra-domain testing and two other sets for cross-domain testing: the ACDC dataset (100 subjects, 1 site, 2 scanners) and the BSCMR-AS dataset (599 subjects, 6 sites, 9 scanners). / Results: The proposed method produces promising segmentation results on the UK Biobank test set which are comparable to previously reported values in the literature, while also performing well on cross-domain test sets, achieving a mean Dice metric of 0.90 for the left ventricle, 0.81 for the myocardium, and 0.82 for the right ventricle on the ACDC dataset; and 0.89 for the left ventricle, 0.83 for the myocardium on the BSCMR-AS dataset. / Conclusions: The proposed method offers a potential solution to improve CNN-based model generalizability for the cross-scanner and cross-site cardiac MR image segmentation task

Improving the Generalizability of Convolutional Neural Network-Based Segmentation on CMR Images

Convolutional neural network (CNN) based segmentation methods provide an efficient and automated way for clinicians to assess the structure and function of the heart in cardiac MR images. While CNNs can generally perform the segmentation tasks with high accuracy when training and test images come from the same domain (e.g. same scanner or site), their performance often degrades dramatically on images from different scanners or clinical sites. We propose a simple yet effective way for improving the network generalization ability by carefully designing data normalization and augmentation strategies to accommodate common scenarios in multi-site, multi-scanner clinical imaging data sets. We demonstrate that a neural network trained on a single-site single-scanner dataset from the UK Biobank can be successfully applied to segmenting cardiac MR images across different sites and different scanners without substantial loss of accuracy. Specifically, the method was trained on a large set of 3,975 subjects from the UK Biobank. It was then directly tested on 600 different subjects from the UK Biobank for intra-domain testing and two other sets for cross-domain testing: the ACDC dataset (100 subjects, 1 site, 2 scanners) and the BSCMR-AS dataset (599 subjects, 6 sites, 9 scanners). The proposed method produces promising segmentation results on the UK Biobank test set which are comparable to previously reported values in the literature, while also performing well on cross-domain test sets, achieving a mean Dice metric of 0.90 for the left ventricle, 0.81 for the myocardium and 0.82 for the right ventricle on the ACDC dataset; and 0.89 for the left ventricle, 0.83 for the myocardium on the BSCMR-AS dataset. The proposed method offers a potential solution to improve CNN-based model generalizability for the cross-scanner and cross-site cardiac MR image segmentation task

Missing Momentum Reconstruction and Spin Measurements at Hadron Colliders

We study methods for reconstructing the momenta of invisible particles in cascade decay chains at hadron colliders. We focus on scenarios, such as SUSY and UED, in which new physics particles are pair produced. Their subsequent decays lead to two decay chains ending with neutral stable particles escaping detection. Assuming that the masses of the decaying particles are already measured, we obtain the momenta by imposing the mass-shell constraints. Using this information, we develop techniques of determining spins of particles in theories beyond the standard model. Unlike the methods relying on Lorentz invariant variables, this method can be used to determine the spin of the particle which initiates the decay chain. We present two complementary ways of applying our method by using more inclusive variables relying on kinematic information from one decay chain, as well as constructing correlation variables based on the kinematics of both decay chains in the same event.Comment: Version to appear in JHE

Fungal Adenylyl Cyclase Acts As a Signal Sensor and Integrator and Plays a Central Role in Interaction with Bacteria

10.1371/journal.ppat.1003612PLoS Pathogens910

Transmembrane protease serine 5: a novel Schwann cell plasma marker for CMT1A

OBJECTIVE: Development of biomarkers for Charcot-Marie-Tooth (CMT) disease is critical for implementing effective clinical trials. The most common form of CMT, type 1A, is caused by a genomic duplication surrounding the PMP22 gene. A recent report (Neurology 2018;90:e518-3524) showed elevation of neurofilament light (NfL) in plasma of CMT1A disease patients, which correlated with disease severity. However, no plasma/serum biomarker has been identified that is specific to Schwann cells, the most directly affected cells in CMT1A. METHODS: We used the Olink immuno PCR platform to profile CMT1A patient (n = 47, 2 cohorts) and normal control plasma (n = 41, two cohorts) on five different Olink panels to screen 398 unique proteins. RESULTS: The TMPRSS5 protein (Transmembrane protease serine 5) was elevated 2.07-fold (P = <0.0001) in two independent cohorts of CMT1A samples relative to controls. TMPRSS5 is most highly expressed in Schwann cells of peripheral nerve. Consistent with early myelination deficits in CMT1A, TMPRSS5 was not significantly correlated with disease score (CMTES-R, CMTNS-R), nerve conduction velocities (Ulnar CMAP, Ulnar MNCV), or with age. TMPRSS5 was not significantly elevated in smaller sample sets from patients with CMT2A, CMT2E, CMT1B, or CMT1X. The Olink immuno PCR assays confirmed elevated levels of NfL (average 1.58-fold, P < 0.0001), which correlated with CMT1A patient disease score. INTERPRETATION: These data identify the first Schwann cell-specific protein that is elevated in plasma of CMT1A patients, and may provide a disease marker and a potentially treatment-responsive biomarker with good disease specificity for clinical trials