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Current scenarios for app development are characterized by rich resources that often overwhelm the final users, especially in mobile app usage situations. It is therefore important to define design methods that enable dynamic filtering of the pertinent resources and appropriate tailoring of the retrieved content. This paper presents a design framework based on the specification of the possible contexts deemed relevant to a given application domain and on their mapping onto an integrated schema of the resources underlying the app. The context and the integrated schema enable the instantiation at runtime of templates of app pages in function of the context characterizing the user’s current situation of use.

This study aims at clarifying the prognostic role of high-grade tumor budding (TB) in pancreatic ductal adenocarcinoma (PDAC) with the first systematic review and meta-analysis on this topic. Furthermore, we analyzed with a systematic review the relationship between TB and a recently suggested TB-associated mechanism: the epithelial to mesenchymal transition (EMT). Analyzing a total of 613 patients, 251 of them (40.9%) with high grade-TB, we found an increased risk of all-cause mortality (RR, 1.46; 95% CI, 1.13-1.88, p = 0.004; HR, 2.65; 95% CI, 1.79-3.91; p < 0.0001) and of recurrence (RR, 1.61; 95% CI, 1.05-2.47, p = 0.03) for PDAC patients with high-grade TB. Moreover, we found that EMT is a central process in determining the presence of TB in PDAC. Thanks to this meta-analysis, we demonstrate the potential clinical significance of high-grade TB for prognostic stratification of PDAC. TB also shows a clear association with the process of EMT. Based on the results of the present study, TB should be conveyed in pathology reports and taken into account by future oncologic staging systems. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.

Carotid artery intima media thickness (cIMT) and carotid plaque are measures of subclinical atherosclerosis associated with ischemic stroke and coronary heart disease (CHD). Here, we undertake meta-analyses of genome-wide association studies (GWAS) in 71,128 individuals for cIMT, and 48,434 individuals for carotid plaque traits. We identify eight novel susceptibility loci for cIMT, one independent association at the previously-identified PINX1 locus, and one novel locus for carotid plaque. Colocalization analysis with nearby vascular expression quantitative loci (cis-eQTLs) derived from arterial wall and metabolic tissues obtained from patients with CHD identifies candidate genes at two potentially additional loci, ADAMTS9 and LOXL4. LD score regression reveals significant genetic correlations between cIMT and plaque traits, and both cIMT and plaque with CHD, any stroke subtype and ischemic stroke. Our study provides insights into genes and tissue-specific regulatory mechanisms linking atherosclerosis both to its functional genomic origins and its clinical consequences in humans. The work was supported by the following grants: National Institute of Health grants: R21HL123677, R21-HL140385, DK104806-01A1, R01-MD012765-01A1 (NF), National Institutes of Health awards R01HG009120, R01HG006399, U01CA194393, T32NS048004 (CG), the American Heart Association Grant #17POST33350042 (PV), the British Heart Foundation (RG/13/5/30112) and the National Institute for Health Research University College London Hospitals Biomedical Research Centre (RCL and RPH), the British Heart Foundation FS/14/55/30806 (JCH), the German Federal Ministry of Education and Research (BMBF) in the context of the e:Med program (e:AtheroSysMed), the DFG as part of the CRC 1123 (B3), and the FP7/2007-2103 European Union project CVgenes@target (grant agreement number Health-F2-2013-601456). We thank Li-Ming Gan for assistance with the STARNET study and Jon White for assistance with UCLEB analyses. Additional acknowledgements are included in Supplementary Note 2. Publisher's version (útgefin grein) Peer Reviewed

Abstract: Purpose: The EUropean Network of National Schizophrenia Networks Studying Gene–Environment Interactions (EU-GEI) study contains an unparalleled wealth of comprehensive data that allows for testing hypotheses about (1) variations in incidence within and between countries, including by urbanicity and minority ethnic groups; and (2) the role of multiple environmental and genetic risk factors, and their interactions, in the development of psychotic disorders. Methods: Between 2010 and 2015, we identified 2774 incident cases of psychotic disorders during 12.9 million person-years at risk, across 17 sites in 6 countries (UK, The Netherlands, France, Spain, Italy, and Brazil). Of the 2774 incident cases, 1130 cases were assessed in detail and form the case sample for case–control analyses. Across all sites, 1497 controls were recruited and assessed. We collected data on an extensive range of exposures and outcomes, including demographic, clinical (e.g. premorbid adjustment), social (e.g. childhood and adult adversity, cannabis use, migration, discrimination), cognitive (e.g. IQ, facial affect processing, attributional biases), and biological (DNA via blood sample/cheek swab). We describe the methodology of the study and some descriptive results, including representativeness of the cohort. Conclusions: This resource constitutes the largest and most extensive incidence and case–control study of psychosis ever conducted. Funder: FP7 Ideas: European Research Council; doi: http://dx.doi.org/10.13039/100011199; Grant(s): HEALTH-F2-2010-241909

Terms: "European Union (EU)" & "Horizon 2020" / Action: H2020-EU.3.6.3. - Reflective societies - cultural heritage and European identity / Acronym: Scan4Reco / Grant number: 665091

Heart failure (HF) is a leading cause of mortality. Inflammation is implicated in HF, yet clinical trials targeting pro-inflammatory cytokines in HF were unsuccessful, possibly due to redundant functions of individual cytokines. Searching for better cardiac inflammation targets, here we link T cells with HF development in a mouse model of pathological cardiac hypertrophy and in human HF patients. T cell costimulation blockade, through FDA-approved rheumatoid arthritis drug abatacept, leads to highly significant delay in progression and decreased severity of cardiac dysfunction in the mouse HF model. The therapeutic effect occurs via inhibition of activation and cardiac infiltration of T cells and macrophages, leading to reduced cardiomyocyte death. Abatacept treatment also induces production of anti-inflammatory cytokine interleukin-10 (IL-10). IL-10-deficient mice are refractive to treatment, while protection could be rescued by transfer of IL-10-sufficient B cells. These results suggest that T cell costimulation blockade might be therapeutically exploited to treat HF. Abatacept is an FDA-approved drug used for treatment of rheumatoid arthritis. Here the authors show that abatacept reduces cardiomyocyte death in a mouse model of heart failure by inhibiting activation and heart infiltration of T cells and macrophages, an effect mediated by IL-10, suggesting a potential therapy for heart failure.

Neutrophils are the first line of defense in the innate immune system, helping to maintain tissue homeostasis as well as eliminating pathogens and self-components. The traditional view of neutrophils as simple phagocytes has been revised over the last decade as new research reveals their unappreciated complexity. Neutrophils are phenotypically and functionally heterogeneous, allowing them to act as modulators of both inflammation and immune responses. During acute inflammation, neutrophils perform a variety of beneficial effector functions, but when inflammation is induced by injury (sterile inflammation) the benefits of neutrophils in tissue repair are more controversial. In several pathological conditions, including cancer and autoimmune diseases, neutrophils can trigger harmful tissue damage. Interestingly, neutrophils are also key players in neuroinflammatory disorders, during which they transmigrate in the central nervous system, acquire a toxic phenotype, home in on neurons, and release harmful molecules that compromise neuronal functions. In this review, we discuss recent data that redefine the cell biology and phenotype of neutrophils, focusing on the role of these cells in multiple sclerosis and Alzheimer's disease, both of which feature strong neuroinflammatory components.

Summary Can social gaze behavior reveal the leader during real-world group interactions? To answer this question, we developed a novel tripartite approach combining (1) computer vision methods for remote gaze estimation, (2) a detailed taxonomy to encode the implicit semantics of multi-party gaze features, and (3) machine learning methods to establish dependencies between leadership and visual behaviors. We found that social gaze behavior distinctively identified group leaders. Crucially, the relationship between leadership and gaze behavior generalized across democratic and autocratic leadership styles under conditions of low and high time-pressure, suggesting that gaze can serve as a general marker of leadership. These findings provide the first direct evidence that group visual patterns can reveal leadership across different social behaviors and validate a new promising method for monitoring natural group interactions. Highlights • Leadership shapes gaze dynamics during real-world human group interactions • Social gaze behavior distinctively identifies group leaders • Identification generalizes across leadership styles and situational conditions • Gaze can serve as a general marker of leadership Social Interaction; Neuroscience; Behavioral Neuroscience Graphical Abstract

In this paper we propose a new methodology to model surgical procedures that is specifically tailored to semi-autonomous robotic surgery. We propose to use a restricted version of statecharts to merge the bottom-up approach, based on data-driven techniques (e.g., machine learning), with the top-down approach based on knowledge representation techniques. We consider medical knowledge about the procedure and sensing of the environment in two concurrent regions of the statecharts to facilitate re-usability and adaptability of the modules. Our approach allows producing a well defined procedural model exploiting the hierarchy capability of the statecharts, while machine learning modules act as soft sensors to trigger state transitions. Integrating data driven and prior knowledge techniques provides a robust, modular, flexible and re-configurable methodology to define a surgical procedure which is comprehensible by both humans and machines. We validate our approach on the three surgical phases of a Robot-Assisted Radical Prostatectomy (RARP) that directly involve the assistant surgeon: bladder mobilization, bladder neck transection, and vesicourethral anastomosis, all performed on synthetic manikins.