Mobilising Knowledge through Global Partnerships to Support Research-informed Teaching: Five Models for Translational Research

Education Futures Collaboration Charity The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Improving the quality of teaching is of global concern: UNESCO’s Sustainable Development Goal (SDG) 4c in the Education 2030: Framework for Action calls for high quality teaching for all. The OECD challenges the education system to improve Knowledge Management. JET’s (2015) special issue: Translational Research (TR) and Knowledge Mobilisation in Teacher Education introduced the concept of ‘translational’ or ‘theory to practice’ research - well-established in medicine but not in education. Five TR models were subsequently developed by the MESH charity’s international network with organisations in South Africa, Bangladesh, Australia, Pakistan, UK. These distinct models engage 1) university staff and teachers 2) subject associations, 3) research units, 4) an international NGO working in crisis settings, 5) PhD tutors and students. Each model shares common features forming the MESH Translational Research methodology introduced in this article. A TR repository is part of the MESH knowledge mobilisation strategy giving teachers access to research summaries which, overtime, accumulate knowledge. TR publications called MESHGuides (www.meshguides.org) complement existing forms of publication. This article proposes the MESH TR methodology as one affordable and scalable solution to OECD and UNESCO’s challenges of keeping teachers up-to-date and making new knowledge accessible to teachers regardless of location

Rare variants in KDR, encoding VEGF Receptor 2, are associated with tetralogy of Fallot

Purpose Rare genetic variants in KDR, encoding the vascular endothelial growth factor receptor 2 (VEGFR2), have been reported in patients with tetralogy of Fallot (TOF). However, their role in disease causality and pathogenesis remains unclear. Methods We conducted exome sequencing in a familial case of TOF and large-scale genetic studies, including burden testing, in >1,500 patients with TOF. We studied gene-targeted mice and conducted cell-based assays to explore the role of KDR genetic variation in the etiology of TOF. Results Exome sequencing in a family with two siblings affected by TOF revealed biallelic missense variants in KDR. Studies in knock-in mice and in HEK 293T cells identified embryonic lethality for one variant when occurring in the homozygous state, and a significantly reduced VEGFR2 phosphorylation for both variants. Rare variant burden analysis conducted in a set of 1,569 patients of European descent with TOF identified a 46-fold enrichment of protein-truncating variants (PTVs) in TOF cases compared to controls (P = 7 x 10(-11)). Conclusion Rare KDR variants, in particular PTVs, strongly associate with TOF, likely in the setting of different inheritance patterns. Supported by genetic and in vivo and in vitro functional analysis, we propose loss-of-function of VEGFR2 as one of the mechanisms involved in the pathogenesis of TOF.Developmen

In-depth analysis of protein inference algorithms using multiple search engines and well-defined metrics

In mass spectrometry-based shotgun proteomics, protein identifications are usually the desired result. However, most of the analytical methods are based on the identification of reliable peptides and not the direct identification of intact proteins. Thus, assembling peptides identified from tandem mass spectra into a list of proteins, referred to as protein inference, is a critical step in proteomics research. Currently, different protein inference algorithms and tools are available for the proteomics community. Here, we evaluated five software tools for protein inference (PIA, ProteinProphet, Fido, ProteinLP, MSBayesPro) using three popular database search engines: Mascot, X!Tandem, and MS-GF +. All the algorithms were evaluated using a highly customizable KNIME workflow using four different public datasets with varying complexities (different sample preparation, species and analytical instruments). We defined a set of quality control metrics to evaluate the performance of each combination of search engines, protein inference algorithm, and parameters on each dataset. We show that the results for complex samples vary not only regarding the actual numbers of reported protein groups but also concerning the actual composition of groups. Furthermore, the robustness of reported proteins when using databases of differing complexities is strongly dependant on the applied inference algorithm. Finally, merging the identifications of multiple search engines does not necessarily increase the number of reported proteins, but does increase the number of peptides per protein and thus can generally be recommended

Extensive identification of genes involved in congenital and structural heart disorders and cardiomyopathy

Clinical presentation of congenital heart disease is heterogeneous, making identification of the disease-causing genes and their genetic pathways and mechanisms of action challenging. By using in vivo electrocardiography, transthoracic echocardiography and microcomputed tomography imaging to screen 3,894 single-gene-null mouse lines for structural and functional cardiac abnormalities, here we identify 705 lines with cardiac arrhythmia, myocardial hypertrophy and/or ventricular dilation. Among these 705 genes, 486 have not been previously associated with cardiac dysfunction in humans, and some of them represent variants of unknown relevance (VUR). Mice with mutations in Casz1, Dnajc18, Pde4dip, Rnf38 or Tmem161b genes show developmental cardiac structural abnormalities, with their human orthologs being categorized as VUR. Using UK Biobank data, we validate the importance of the DNAJC18 gene for cardiac homeostasis by showing that its loss of function is associated with altered left ventricular systolic function. Our results identify hundreds of previously unappreciated genes with potential function in congenital heart disease and suggest causal function of five VUR in congenital heart disease