GP-Unet: Lesion Detection from Weak Labels with a 3D Regression Network

We propose a novel convolutional neural network for lesion detection from weak labels. Only a single, global label per image - the lesion count - is needed for training. We train a regression network with a fully convolutional architecture combined with a global pooling layer to aggregate the 3D output into a scalar indicating the lesion count. When testing on unseen images, we first run the network to estimate the number of lesions. Then we remove the global pooling layer to compute localization maps of the size of the input image. We evaluate the proposed network on the detection of enlarged perivascular spaces in the basal ganglia in MRI. Our method achieves a sensitivity of 62% with on average 1.5 false positives per image. Compared with four other approaches based on intensity thresholding, saliency and class maps, our method has a 20% higher sensitivity.Comment: Article published in MICCAI 2017. We corrected a few errors from the first version: padding, loss, typos and update of the DOI numbe

A multidimensional control architecture for combined fog-to-cloud systems

The fog/edge computing concept has set the foundations for the deployment of new services leveraging resources deployed at the edge paving the way for an innovative collaborative model, where end-users may collaborate with service providers by sharing idle resources at the edge of the network. Combined Fog-to-Cloud (F2C) systems have been recently proposed as a control strategy for managing fog and cloud resources in a coordinated way, aimed at optimally allocating resources within the fog-to-cloud resources stack for an optimal service execution. In this work, we discuss the unfeasibility of the deployment of a single control topology able to optimally manage a plethora of edge devices in future networks, respecting established SLAs according to distinct service requirements and end-user profiles. Instead, a multidimensional architecture, where distinct control plane instances coexist, is then introduced. By means of distinct scenarios, we describe the benefits of the proposed architecture including how users may collaborate with the deployment of novel services by selectively sharing resources according to their profile, as well as how distinct service providers may benefit from shared resources reducing deployment costs. The novel architecture proposed in this paper opens several opportunities for research, which are presented and discussed at the final section.This work was supported by the H2020 EU mF2C project, ref. 730929 and for UPC authors, also by the Spanish Ministry of Economy and Competitiveness and the European Regional Development Fund under contract RTI2018-094532-B-I00.Peer ReviewedPostprint (author's final draft

Orally active antischistosomal early leads identified from the open access malaria box.

BACKGROUND: Worldwide hundreds of millions of schistosomiasis patients rely on treatment with a single drug, praziquantel. Therapeutic limitations and the threat of praziquantel resistance underline the need to discover and develop next generation drugs. METHODOLOGY: We studied the antischistosomal properties of the Medicines for Malaria Venture (MMV) malaria box containing 200 diverse drug-like and 200 probe-like compounds with confirmed in vitro activity against Plasmodium falciparum. Compounds were tested against schistosomula and adult Schistosoma mansoni in vitro. Based on in vitro performance, available pharmacokinetic profiles and toxicity data, selected compounds were investigated in vivo. PRINCIPAL FINDINGS: Promising antischistosomal activity (IC50: 1.4-9.5 µM) was observed for 34 compounds against schistosomula. Three compounds presented IC50 values between 0.8 and 1.3 µM against adult S. mansoni. Two promising early leads were identified, namely a N,N'-diarylurea and a 2,3-dianilinoquinoxaline. Treatment of S. mansoni infected mice with a single oral 400 mg/kg dose of these drugs resulted in significant worm burden reductions of 52.5% and 40.8%, respectively. CONCLUSIONS/SIGNIFICANCE: The two candidates identified by investigating the MMV malaria box are characterized by good pharmacokinetic profiles, low cytotoxic potential and easy chemistry and therefore offer an excellent starting point for antischistosomal drug discovery and development

Systematic Assessment of the Accuracy of Subunit Counting in Biomolecular Complexes Using Automated Single-Molecule Brightness Analysis.

Analysis of single-molecule brightness allows subunit counting of high-order oligomeric biomolecular complexes. Although the theory behind the method has been extensively assessed, systematic analysis of the experimental conditions required to accurately quantify the stoichiometry of biological complexes remains challenging. In this work, we develop a high-throughput, automated computational pipeline for single-molecule brightness analysis that requires minimal human input. We use this strategy to systematically quantify the accuracy of counting under a wide range of experimental conditions in simulated ground-truth data and then validate its use on experimentally obtained data. Our approach defines a set of conditions under which subunit counting by brightness analysis is designed to work optimally and helps in establishing the experimental limits in quantifying the number of subunits in a complex of interest. Finally, we combine these features into a powerful, yet simple, software that can be easily used for the analysis of the stoichiometry of such complexes

Perivascular Spaces Segmentation in Brain MRI Using Optimal 3D Filtering

Perivascular Spaces (PVS) are a recently recognised feature of Small Vessel Disease (SVD), also indicating neuroinflammation, and are an important part of the brain's circulation and glymphatic drainage system. Quantitative analysis of PVS on Magnetic Resonance Images (MRI) is important for understanding their relationship with neurological diseases. In this work, we propose a segmentation technique based on the 3D Frangi filtering for extraction of PVS from MRI. Based on prior knowledge from neuroradiological ratings of PVS, we used ordered logit models to optimise Frangi filter parameters in response to the variability in the scanner's parameters and study protocols. We optimized and validated our proposed models on two independent cohorts, a dementia sample (N=20) and patients who previously had mild to moderate stroke (N=48). Results demonstrate the robustness and generalisability of our segmentation method. Segmentation-based PVS burden estimates correlated with neuroradiological assessments (Spearman's $\rho$ = 0.74, p $<$ 0.001), suggesting the great potential of our proposed metho

The MHC and body odors: arbitrary effects caused by shifts of mean pleasantness

The main conclusions of the study by Jacob et al.1 published in February's issue of Nature Genetics differ from those of most previous studies of the major histocompatibility complex (MHC) and mate or odor preference in any animal2. It is therefore important to understand what may have caused these differences

Spin chirality on a two-dimensional frustrated lattice

The collective behavior of interacting magnetic moments can be strongly influenced by the topology of the underlying lattice. In geometrically frustrated spin systems, interesting chiral correlations may develop that are related to the spin arrangement on triangular plaquettes. We report a study of the spin chirality on a two-dimensional geometrically frustrated lattice. Our new chemical synthesis methods allow us to produce large single crystal samples of KFe3(OH)6(SO4)2, an ideal Kagome lattice antiferromagnet. Combined thermodynamic and neutron scattering measurements reveal that the phase transition to the ordered ground-state is unusual. At low temperatures, application of a magnetic field induces a transition between states with different non-trivial spin-textures.Comment: 7 pages, 4 figure

Awareness of cancer symptoms and anticipated help seeking among ethnic minority groups in England

&lt;p&gt;Objective: Little is known about ethnic differences in awareness of cancer-warning signs or help-seeking behaviour in Britain. As part of the National Awareness and Early Diagnosis Initiative (NAEDI), this study aimed to explore these factors as possible contributors to delay in cancer diagnosis.&lt;/p&gt; &lt;p&gt;Methods: We used quota sampling to recruit 1500 men and women from the six largest minority ethnic groups in England (Indian, Pakistani, Bangladeshi, Caribbean, African and Chinese). In face-to-face interviews, participants completed the newly developed cancer awareness measure (CAM), which includes questions about warning signs for cancer, speed of consultation for possible cancer symptoms and barriers to help seeking.&lt;/p&gt; &lt;p&gt;Results: Awareness of warning signs was low across all ethnic groups, especially using the open-ended (recall) question format, with lowest awareness in the African group. Women identified more emotional barriers and men more practical barriers to help seeking, with considerable ethnic variation. Anticipated delay in help seeking was higher in individuals who identified fewer warning signs and more barriers.&lt;/p&gt; &lt;p&gt;Conclusions: The study suggests the need for culturally sensitive, community-based interventions to raise awareness and encourage early presentation.&lt;/p&gt

Poststaphylococcal coagulase negative reactive arthritis: a case report

We report a case of a 49-year-old patient who developed poststaphylococcal coagulase negative reactive arthritis. The woman presented with constitutional symptoms, arthritis, urinary infection and conjunctivitis. The blood culture was positive for the staphylococcal coagulase negative infection. Erythrocyte sedimentation rate and C-reactive protein were elevated, whereas the rheumatoid factor was negative. Radiographic findings confirmed diagnosis of pleuropneumonia, and one year later of chronic asymmetric sacroileitis. Physicians should be aware of possible reactive arthritis after staphylococcal coagulase negative bacteremia