Deficiency of the zinc finger protein ZFP106 causes motor and sensory neurodegeneration

Acknowledgements We are indebted to Jim Humphries, JennyCorrigan, LizDarley, Elizabeth Joynson, Natalie Walters, Sara Wells and the whole necropsy, histology, genotyping and MLC ward 6 teams at MRC Harwell for excellent technical assistance. We thank the staff of the WTSI Illumina Bespoke Team for the RNA-seq data, the Sanger Mouse Genetics Project for the initial mouse characterization and Dr David Adams for critical reading of the manuscript. We also thank KOMP for the mouse embryonic stem cells carrying the knockout first promoter-less allele (tm1a(KOMP)Wtsi) within Zfp016. Conflict of Interest statement. None declared. Funding This work was funded by the UK Medical Research Council (MRC) to A.A.-A. and a Motor Neurone Disease Association (MNDA) project grant to A.A.-A. and EMCF. D.L.H.B. is a Wellcome Trust Senior Clinical Scientist Fellow and P.F. is a MRC/MNDA Lady Edith Wolfson Clinician Scientist Fellow. Funding to pay the Open Access publication charges for this article was provided by the MRC grant number: MC_UP_A390_1106.Peer reviewedPublisher PD

Use of Noise to Augment Training Data: A Neural Network Method of Mineral-Potential Mapping in Regions of Limited Known Deposit Examples.

One of the main factors that affects the performance ofMLPneural networks trained using the backpropagation algorithm in mineral-potential mapping is the paucity of deposit relative to barren training patterns. To overcome this problem, random noise is added to the original training patterns in order to create additional synthetic deposit training data. Experiments on the effect of the number of deposits available for training in the Kalgoorlie Terrane orogenic gold province show that both the classification performance of a trained network and the quality of the resultant prospectivity map increase significantly with increased numbers of deposit patterns. Experiments are conducted to determine the optimum amount of noise using both uniform and normally distributed random noise. Through the addition of noise to the original deposit training data, the number of deposit training patterns is increased from approximately 50 to 1000. The percentage of correct classifications significantly improves for the independent test set as well as for deposit patterns in the test set. For example, using≥40% uniform random noise, the test-set classification performance increases from 67.9% and 68.0% to 72.8% and 77.1% (for test-set overall and test-set deposit patterns, respectively). Indices for the quality of the resultant prospectivity map, (i.e. D/A, D≥(D/A), where Dis the percentage of deposits and Ais the percentage of the total area for the highest prospectivity map-class, and area under an ROC curve) also increase from 8.2, 105, 0.79 to 17.9, 226, 0.87, respectively. Increasing the size of the training-stop data set results in a further increase in classification performance to 73.5%, 77.4%, 14.7, 296, 0.87 for test-set overall and test-set deposit patterns, D/A, D≥(D/A), and area under the ROC curve, respectively

The Role of Individual Variables, Organizational Variables and Moral Intensity Dimensions in Libyan Management Accountants’ Ethical Decision Making

This study investigates the association of a broad set of variables with the ethical decision making of management accountants in Libya. Adopting a cross-sectional methodology, a questionnaire including four different ethical scenarios was used to gather data from 229 participants. For each scenario, ethical decision making was examined in terms of the recognition, judgment and intention stages of Rest’s model. A significant relationship was found between ethical recognition and ethical judgment and also between ethical judgment and ethical intention, but ethical recognition did not significantly predict ethical intention—thus providing support for Rest’s model. Organizational variables, age and educational level yielded few significant results. The lack of significance for codes of ethics might reflect their relative lack of development in Libya, in which case Libyan companies should pay attention to their content and how they are supported, especially in the light of the under-development of the accounting profession in Libya. Few significant results were also found for gender, but where they were found, males showed more ethical characteristics than females. This unusual result reinforces the dangers of gender stereotyping in business. Personal moral philosophy and moral intensity dimensions were generally found to be significant predictors of the three stages of ethical decision making studied. One implication of this is to give more attention to ethics in accounting education, making the connections between accounting practice and (in Libya) Islam. Overall, this study not only adds to the available empirical evidence on factors affecting ethical decision making, notably examining three stages of Rest’s model, but also offers rare insights into the ethical views of practising management accountants and provides a benchmark for future studies of ethical decision making in Muslim majority countries and other parts of the developing world

Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility.

To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry

Identification and functional characterization of G6PC2 coding variants influencing glycemic traits define an effector transcript at the G6PC2-ABCB11 locus.

Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights

Structural and functional insight into human O-GlcNAcase.

O-GlcNAc hydrolase (OGA) removes O-linked N-acetylglucosamine (O-GlcNAc) from a myriad of nucleocytoplasmic proteins. Through co-expression and assembly of OGA fragments, we determined the three-dimensional structure of human OGA, revealing an unusual helix-exchanged dimer that lays a structural foundation for an improved understanding of substrate recognition and regulation of OGA. Structures of OGA in complex with a series of inhibitors define a precise blueprint for the design of inhibitors that have clinical value

Untangling knowledge creation and knowledge integration in enterprise wikis

A central challenge organizations face is how to build, store, and maintain knowledge over time. Enterprise wikis are community-based knowledge systems situated in an organizational context. These systems have the potential to play an important role in managing knowledge within organizations, but the motivating factors that drive individuals to contribute their knowledge to these systems is not very well understood. We theorize that enterprise wiki initiatives require two separate and distinct types of knowledge-sharing behaviors to succeed: knowledge creation (KC) and knowledge integration (KI). We examine a Wiki initiative at a major German bank to untangle the motivating factors behind KC and KI. Our results suggest KC and KI are indeed two distinct behaviors, reconcile inconsistent findings from past studies on the role of motivational factors for knowledge sharing to establish shared electronic knowledge resources in organizations, and identify factors that can be leveraged to tilt behaviors in favor of KC or KI