Design and Technology Educators’ Experiences of Competence, Relatedness and Autonomy with Educational Research

This article reports on the results of a survey of Design and Technology educators, predominantly based in England that sought evidence of the extent to which the educators engaged with educational research more generally and also specifically within Design and Technology Education. The survey was sponsored by the professional Association of Design and Technology Education and was undertaken by its Design and Technology Research Steering Group. The survey collected demographic data on the roles and responsibilities of the survey respondents, the types and levels of education where they worked and length of experience in Design and Technology  education. Questions explored the types of research of interest, confidence levels in accessing, using and undertaking research, the nature of support for engaging research that educators would welcome, how research was currently accessed, what the challenges and barriers might be and what would motivate educators to become more engaged with research. This article resorts on analysis of the data, drawing on Self Determination Theory and specifically concepts of competence, relatedness and autonomy. Findings indicated that  respondents had a great deal of interest in principle, but that there were considerable barriers to engaging with research which impacted on competence, relatedness and autonomy. The insights provided will now be used as the basis for developing support for Design and Technology practitioners to engage with research at a variety of levels

Genetic analysis suggests high misassignment rates in clinical Alzheimer's cases and controls

Genetic case-control association studies are often based on clinically ascertained cases and population or convenience controls. It is known that some of the controls will contain cases, as they are usually not screened for the disease of interest. However, even clinically assessed cases and controls can be misassigned. For Alzheimer's disease (AD), it is important to know the accuracy of the clinical assignment. The predictive accuracy of AD risk by polygenic risk score analysis has been reported in both clinical and pathologically confirmed cohorts. The genetic risk prediction can provide additional insights to inform classification of subjects to case and control sets at a preclinical stage. In this study, we take a mathematical approach and aim to assess the importance of a genetic component for the assignment of subjects to AD-positive and -negative groups, and provide an estimate of misassignment rates (MARs) in AD case/control cohorts accounting for genetic prediction modeling results. The derived formulae provide a tool to estimate MARs in any sample. This approach can also provide an estimate of the maximal and minimal MARs and therefore could be useful for statistical power estimation at the study design stage. We illustrate this approach in 2 independent clinical cohorts and estimate misdiagnosis rate up to 36% in controls unscreened for the APOE genotype, and up to 29% when E3 homozygous subjects are used as controls in clinical studies

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Common BACE2 Polymorphisms are Associated with Altered Risk for Alzheimer's Disease and CSF Amyloid Biomarkers in APOE ε4 Non-Carriers

It was recently suggested that beta-site amyloid precursor protein (APP)-cleaving enzyme 2 (BACE2) functions as an amyloid beta (A beta)-degrading enzyme; in addition to its better understood role as an APP secretase. Due to this finding we sought to understand the possible genetic risk contributed by the BACE2 locus to the development of late-onset Alzheimer's disease (AD). In this study, we report that common single nucleotide polymorphism (SNP) variation in BACE2 is associated with altered AD risk in apolipoprotein E gene (APOE) epsilon 4 variant (e4) non-carriers. In addition, in e4 non-carriers diagnosed with AD or mild cognitive impairment (MCI), SNPs within the BACE2 locus are associated with cerebrospinal fluid (CSF) levels of A beta 1-42. Further, SNP variants in BACE2 are also associated with BACE2 RNA expression levels suggesting a potential mechanism for the CSF A beta 1-42 findings. Lastly, overexpression of BACE2 in vitro resulted in decreased A beta 1-40 and A beta 1-42 fragments in a cell line model of A beta production. These findings suggest that genetic variation at the BACE2 locus modifies AD risk for those individuals who don't carry the e4 variant of APOE. Further, our data indicate that the biological mechanism associated with this altered risk is linked to amyloid generation or clearance possibly through BACE2 expression changes.National Institute on Aging (NIA); National Alzheimer's Coordinating Center (NACC) [U01 AG016976]; National Institute on Aging: Ruth Seemann, John Hopkins Alzheimer's Disease Research Center (NIA) [AG05146, P50 AG16570, AG05128]; NINDS [NS39764]; Glaxo Smith Kline [P50-AG053760, AG05144, P50AG05681, P50 AG05136, P30-AG13846, 211002]; Arizona Biomedical Research Commission [4001, 0011, 05_ 901]; Michael J. Fox Foundation [AG10161, HHSN-271-2013-00030C]; McGowan Endowment; Medical Research Council, local NHS trusts and Newcastle University; Medical Research Council; Safa Al-Sarraj; Netherlands Brain Bank; Stichting MS Research, Brain Net Europe; Hersenstichting Nederland Breinbrekend Werk, International Parkinson Fonds; Internationale Stiching Alzheimer Onderzoek; NIH-NIA [R01-AG041232]; State of Arizona DHS (Arizona Alzheimer's Consortium) - NIH EUREKA [R01-AG034504]; NIH intramural funds; UK Dementia Research Institute; DRI Ltd - UK Medical Research Council; Alzheimer's Society; Alzheimer's Research UK - Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health) [U01 AG024904]; DOD ADNI (Department of Defense) [W81XWH-12-2-0012]; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Alzheimer'sAssociation; Alzheimer's Drug Discovery Foundation; Araclon Biotech; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd; Fujirebio; Johnson & Johnson Pharmaceutical Research & Development LLC.; Merck Co., Inc.; Meso Scale Diagnostics; NeuroRx Research; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Takeda Pharmaceutical Company; Canadian Institutes of Health Research isproviding funds; ADNI clinical sites in Canada; Foundation for the National Institutes of Health; Northern California Institute for Research and Education; Laboratory for Neuro Imaging at the University of Southern CaliforniaOpen access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

DiSSCo Prepare WP7 –D7.3 Assessment tools and direction map to the implementation of common DiSSCo policies

The Distributed System for Scientific Collections (DiSSCo) Research Infrastructure will operate a number of e-services, all of which will have policy requirements for participating institutions. These policies include those related to digital and physical access to specimens, digital image and specimen metadata, and FAIR / Open Data. Previous projects have shown that the policy landscape is complex, and Task 7.3 has developed a policy self-assessment tool that will allow DiSSCo to assess policy alignment across the consortium. This deliverable describes the development of the policy self-assessment tool and provides a walkthrough of the key features. The same technical framework was used to create a digital maturity tool, which was initially proposed by Task 3.1, and this is also described within this document. A set of recommendations are included that outline the future direction for the development of the policy tool.The Distributed System for Scientific Collections (DiSSCo) Research Infrastructure will operate a number´of e-services, all of which will have policy requirements for participating institutions. These policies include those related to digital and physical access to specimens, digital image and specimen metadata, and FAIR / Open Data. Previous projects have shown that the policy landscape is complex, and Task 7.3 has developed a policy self-assessment tool that will allow DiSSCo to assess policy alignment across the consortium. This deliverable describes the development of the policy self-assessment tool and provides a walkthrough of the key features. The same technical framework was used to create a digital maturity tool, which was initially proposed by Task 3.1, and this is also described within this document. A set of recommendations are included that outline the future direction for the development of the policy tool

The pig X and Y Chromosomes: structure, sequence, and evolution.

We have generated an improved assembly and gene annotation of the pig X Chromosome, and a first draft assembly of the pig Y Chromosome, by sequencing BAC and fosmid clones from Duroc animals and incorporating information from optical mapping and fiber-FISH. The X Chromosome carries 1033 annotated genes, 690 of which are protein coding. Gene order closely matches that found in primates (including humans) and carnivores (including cats and dogs), which is inferred to be ancestral. Nevertheless, several protein-coding genes present on the human X Chromosome were absent from the pig, and 38 pig-specific X-chromosomal genes were annotated, 22 of which were olfactory receptors. The pig Y-specific Chromosome sequence generated here comprises 30 megabases (Mb). A 15-Mb subset of this sequence was assembled, revealing two clusters of male-specific low copy number genes, separated by an ampliconic region including the HSFY gene family, which together make up most of the short arm. Both clusters contain palindromes with high sequence identity, presumably maintained by gene conversion. Many of the ancestral X-related genes previously reported in at least one mammalian Y Chromosome are represented either as active genes or partial sequences. This sequencing project has allowed us to identify genes--both single copy and amplified--on the pig Y Chromosome, to compare the pig X and Y Chromosomes for homologous sequences, and thereby to reveal mechanisms underlying pig X and Y Chromosome evolution.This work was funded by BBSRC grant BB/F021372/1. The Flow Cytometry and Cytogenetics Core Facilities at the Wellcome Trust Sanger Institute and Sanger investigators are funded by the Wellcome Trust (grant number WT098051). K.B., D.C.-S., and J.H. acknowledge support from the Wellcome Trust (WT095908), the BBSRC (BB/I025506/1), and the European Molecular Biology Laboratory. The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007–2013) under grant agreement no. 222664 (“Quantomics”).This is the final version of the article. It first appeared from Cold Spring Harbor Laboratory Press via http://dx.doi.org/10.1101/gr.188839.11