BAT2 and BAT3 polymorphisms as novel genetic risk factors for rejection after HLA-related SCT.

The genetic background of donor and recipient is an important factor determining the outcome of allogeneic hematopoietic SCT (allo-HSCT). We applied whole-genome analysis to investigate genetic variants - other than HLA class I and II - associated with negative outcome after HLA-identical sibling allo-HSCT in a cohort of 110 β-Thalassemic patients. We identified two single-nucleotide polymorphisms (SNPs) in BAT2 (A/G) and BAT3 (T/C) genes, SNP rs11538264 and SNP rs10484558, both located in the HLA class III region, in strong linkage disequilibrium between each other (R2 =0.92). When considered as single SNP, none of them reached a significant association with graft rejection (nominal P<0.00001 for BAT2 SNP rs11538264, and P<0.0001 for BAT3 SNP rs10484558), whereas the BAT2/BAT3 A/C haplotype was present at significantly higher frequency in patients who rejected as compared to those with functional graft (30.0% vs 2.6%, nominal P=1.15 × 10-8; and adjusted P=0.0071). The BAT2/BAT3 polymorphisms and specifically the A/C haplotype may represent a novel immunogenetic factor associated with graft rejection in patients undergoing allo-HSCT

Food waste reduction in supply chains through innovations: a review

Purpose: Agri-food supply chains are facing a number of challenges, which cause inefficiencies resulting in the waste of natural and economic resources, and in negative environmental and social impacts. Food waste (FW) is a result of such inefficiencies and supply chain actors search for economically viable innovations to prevent and reduce it. This study aims to analyse the drivers and the barriers that affect the decision of supply chain operators to adopt innovations (technological – TI, organisational – OI and marketing – MI) to reduce FW. Design/methodology/approach: The analysis was carried out using a four-step approach that included: a literature review to identify factors affecting the decision to adopt innovations; analysis of FW drivers and reduction possibilities along agri-food supply chains through innovations; mapping the results of Steps 1 and 2 and deriving conclusions regarding the factors affecting the adoption of innovations to reduce and prevent FW. Findings: Results show that different types of innovations have a high potential in reducing and preventing FW along the supply chain; however, they still must be economically feasible to be adopted by decision makers in the food supply chain. TI, OI and MI are often interrelated and can trigger each other. When it comes to a combination of different types of innovation to reduce and prevent FW, a good example of combining TI, OI and MI may be observed in the retail sector in Europe. Here, innovative smartphone apps (TI) to promote the sale of products nearing their expiration dates (OI in terms of organising the sales differently and MI in terms of marketing it differently) were developed and adopted via different retailing channels, leading to the creation of a new business model. Practical implications: This study analyses the drivers of FW generation together with the factors affecting the decision to adopt innovations to reduce it and provides solutions to supply chain operators to prevent and reduce FW through different types of innovations. Originality/value: Literature has not systematically addressed innovations aiming at the reduction of FW yet. This paper provides a comprehensive literature review of the determinants of innovation adoption and offers a novel view on the problem of FW reduction by means of innovation, by linking factors affecting the decision to innovate with FW drivers

A Novel Cardiac Muscle-Derived Biomaterial Reduces Dyskinesia and Postinfarct Left Ventricular Remodeling in a Mouse Model of Myocardial Infarction

Extracellular matrix (ECM) degradation after myocardial infarction (MI) leaves the myocardium structurally weakened and, as a result, susceptible to early infarct zone dyskinesia and left ventricular (LV) remodeling. While various cellular and biomaterial preparations have been transplanted into the infarct zone in hopes of improving post-MI LV remodeling, an allogeneic cardiac muscle-derived ECM extract has yet to be developed and tested in the setting of reperfused MI. We sought to determine the effects of injecting a novel cardiac muscle-derived ECM into the infarct zone on early dyskinesia and LV remodeling in a mouse model of MI. Cardiac muscle ECM was extracted from frozen mouse heart tissue by a protocol that enriches for basement membrane constituents. The extract was injected into the infarct zone immediately after ischemia/reperfusion injury (n = 6). Echocardiography was performed at baseline and at days 2, 7, 14, and 28 post-MI to assess 3D LV volumes and cardiac function, as compared to infarcted controls (n = 9). Early infarct zone dyskinesia was measured on day 2 post-MI using a novel metric, the dyskinesia index. End-systolic volume was significantly reduced in the ECM-treated group compared to controls by day 14. Ejection fraction and stroke volume were also significantly improved in the ECM-treated group. ECM-treated hearts showed a significant (P \u3c 0.005) reduction in dyskinetic motion on day 2. Thus, using high-frequency ultrasound, it was shown that treatment with a cardiac-derived ECM preparation reduced early infarct zone dyskinesia and post-MI LV remodeling in a mouse model of reperfused MI

Exploring Play and Creativity in Pre-schooler's use of apps: Final Project Report

This report outlines the key findings of a co-produced study, developed in collaboration between academics at the Universities of Sheffield and Edinburgh, the BBC (CBeebies), Monteney Pirmary School and the children’s media companies Dubit and Foundling Bird (Appendix 1 outlines the project team members and Advisory Board members). The project was co-produced in that all project partners contributed to the development of the project aims and objectives and were involved in data collection, analysis and dissemination. The aim of the study was to identify pre-school children’s (aged 0-5) uses of and responses to tablet apps in terms of the impact on their play and creativity

Photocatalytic Performance of Undoped and Al-Doped ZnO Nanoparticles in the Degradation of Rhodamine B under UV-Visible Light:The Role of Defects and Morphology

Quasi-spherical undoped ZnO and Al-doped ZnO nanoparticles with different aluminum content, ranging from 0.5 to 5 at% of Al with respect to Zn, were synthesized. These nanoparticles were evaluated as photocatalysts in the photodegradation of the Rhodamine B (RhB) dye aqueous solution under UV-visible light irradiation. The undoped ZnO nanopowder annealed at 400 &deg;C resulted in the highest degradation efficiency of ca. 81% after 4 h under green light irradiation (525 nm), in the presence of 5 mg of catalyst. The samples were characterized using ICP-OES, PXRD, TEM, FT-IR, 27Al-MAS NMR, UV-Vis and steady-state PL. The effect of Al-doping on the phase structure, shape and particle size was also investigated. Additional information arose from the annealed nanomaterials under dynamic N2 at different temperatures (400 and 550 &deg;C). The position of aluminum in the ZnO lattice was identified by means of 27Al-MAS NMR. FT-IR gave further information about the type of tetrahedral sites occupied by aluminum. Photoluminescence showed that the insertion of dopant increases the oxygen vacancies reducing the peroxide-like species responsible for photocatalysis. The annealing temperature helps increase the number of red-emitting centers up to 400 &deg;C, while at 550 &deg;C, the photocatalytic performance drops due to the aggregation tendency

Speciation and milk adulteration analysis by rapid ambient liquid MALDI mass spectrometry profiling using machine learning

Growing interest in food quality and traceability by regulators as well as consumers demands advances in more rapid, versatile and cost-effective analytical methods. Milk, as most food matrices, is a heterogeneous mixture composed of metabolites, lipids and proteins. One of the major challenges is to have simultaneous, quantitative detection (profiling) of this panel of biomolecules to gather valuable information for assessing food quality, traceability and safety. Here, for milk analysis, atmospheric pressure (AP) matrix-assisted laser desorption/ionization (MALDI) employing homogenous liquid sample droplets was used on a Q-TOF mass analyzer. This method has the capability to produce multiply charged proteinaceous ions as well as highly informative profiles of singly charged lipids/metabolites. In two examples, this method is coupled with user-friendly machine-learning software. First, rapid speciation of milk (cow, goat, sheep and camel) is demonstrated with 100% classification accuracy. Second, the detection of cow milk as adulterant in goat milk is shown at concentrations as low as 5% with 92.5% sensitivity and 94.5% specificity

LAP-MALDI MS coupled with machine learning: an ambient mass spectrometry approach for high-throughput diagnostics

Large-scale population screening for early and accurate detection of disease is a key objective for future diagnostics. Ideally, diagnostic tests that achieve this goal are also cost-effective, fast and easily adaptable to new diseases with the potential of multiplexing. Mass spectrometry (MS), particularly MALDI MS profiling, has been explored for many years in disease diagnostics, most successfully in clinical microbiology but less in early detection of diseases. Here, we present liquid atmospheric pressure (LAP)-MALDI MS profiling as a rapid, large-scale and cost-effective analysis platform for multiplexing disease analysis. Using this new platform, two different types of tests exemplify its potential in early disease diagnosis and response to therapy. First, it is shown that LAP-MALDI MS profiling detects bovine mastitis two days before its clinical manifestation with a sensitivity of up to 70% and a specificity of up to 100%. This highly accurate, pre-symptomatic detection is demonstrated by using a large set of milk samples collected weekly over six months from approximately 500 dairy cows. Second, the potential of LAP-MALDI MS in antimicrobial resistance (AMR) detection is shown by employing the same mass spectrometric setup and similarly simple sample preparation as for the early detection of mastitis

Schmallenberg virus pathogenesis, tropism and interaction with the innate immune system of the host

Schmallenberg virus (SBV) is an emerging orthobunyavirus of ruminants associated with outbreaks of congenital malformations in aborted and stillborn animals. Since its discovery in November 2011, SBV has spread very rapidly to many European countries. Here, we developed molecular and serological tools, and an experimental in vivo model as a platform to study SBV pathogenesis, tropism and virus-host cell interactions. Using a synthetic biology approach, we developed a reverse genetics system for the rapid rescue and genetic manipulation of SBV. We showed that SBV has a wide tropism in cell culture and “synthetic” SBV replicates in vitro as efficiently as wild type virus. We developed an experimental mouse model to study SBV infection and showed that this virus replicates abundantly in neurons where it causes cerebral malacia and vacuolation of the cerebral cortex. These virus-induced acute lesions are useful in understanding the progression from vacuolation to porencephaly and extensive tissue destruction, often observed in aborted lambs and calves in naturally occurring Schmallenberg cases. Indeed, we detected high levels of SBV antigens in the neurons of the gray matter of brain and spinal cord of naturally affected lambs and calves, suggesting that muscular hypoplasia observed in SBV-infected lambs is mostly secondary to central nervous system damage. Finally, we investigated the molecular determinants of SBV virulence. Interestingly, we found a biological SBV clone that after passage in cell culture displays increased virulence in mice. We also found that a SBV deletion mutant of the non-structural NSs protein (SBVΔNSs) is less virulent in mice than wild type SBV. Attenuation of SBV virulence depends on the inability of SBVΔNSs to block IFN synthesis in virus infected cells. In conclusion, this work provides a useful experimental framework to study the biology and pathogenesis of SBV

Brain structural covariance networks in obsessive-compulsive disorder: a graph analysis from the ENIGMA Consortium.

Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P &lt; 0.0001), lower modularity (P &lt; 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions

An overview of the first 5 years of the ENIGMA obsessive–compulsive disorder working group: The power of worldwide collaboration

Abstract Neuroimaging has played an important part in advancing our understanding of the neurobiology of obsessive?compulsive disorder (OCD). At the same time, neuroimaging studies of OCD have had notable limitations, including reliance on relatively small samples. International collaborative efforts to increase statistical power by combining samples from across sites have been bolstered by the ENIGMA consortium; this provides specific technical expertise for conducting multi-site analyses, as well as access to a collaborative community of neuroimaging scientists. In this article, we outline the background to, development of, and initial findings from ENIGMA's OCD working group, which currently consists of 47 samples from 34 institutes in 15 countries on 5 continents, with a total sample of 2,323 OCD patients and 2,325 healthy controls. Initial work has focused on studies of cortical thickness and subcortical volumes, structural connectivity, and brain lateralization in children, adolescents and adults with OCD, also including the study on the commonalities and distinctions across different neurodevelopment disorders. Additional work is ongoing, employing machine learning techniques. Findings to date have contributed to the development of neurobiological models of OCD, have provided an important model of global scientific collaboration, and have had a number of clinical implications. Importantly, our work has shed new light on questions about whether structural and functional alterations found in OCD reflect neurodevelopmental changes, effects of the disease process, or medication impacts. We conclude with a summary of ongoing work by ENIGMA-OCD, and a consideration of future directions for neuroimaging research on OCD within and beyond ENIGMA