University of Cambridge

About: University of Cambridge is a education organization based out in Cambridge, United Kingdom. It is known for research contribution in the topics: Population & Galaxy. The organization has 118293 authors who have published 282289 publications receiving 14497093 citations. The organization is also known as: Cambridge University & Cambridge.

Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes

Abstract: Genome-wide association (GWA) studies have identified multiple loci at which common variants modestly but reproducibly influence risk of type 2 diabetes (T2D). Established associations to common and rare variants explain only a small proportion of the heritability of T2D. As previously published analyses had limited power to identify variants with modest effects, we carried out meta-analysis of three T2D GWA scans comprising 10,128 individuals of European descent and approximately 2.2 million SNPs (directly genotyped and imputed), followed by replication testing in an independent sample with an effective sample size of up to 53,975. We detected at least six previously unknown loci with robust evidence for association, including the JAZF1 (P = 5.0 x 10(-14)), CDC123-CAMK1D (P = 1.2 x 10(-10)), TSPAN8-LGR5 (P = 1.1 x 10(-9)), THADA (P = 1.1 x 10(-9)), ADAMTS9 (P = 1.2 x 10(-8)) and NOTCH2 (P = 4.1 x 10(-8)) gene regions. Our results illustrate the value of large discovery and follow-up samples for gaining further insights into the inherited basis of T2D.

Diagnostic Criteria for Mild Cognitive Impairment in Parkinson’s Disease: Movement Disorder Society Task Force Guidelines

Abstract: Mild cognitive impairment is common in nondemented Parkinson's disease (PD) patients and may be a harbinger of dementia. In view of its importance, the Movement Disorder Society commissioned a task force to delineate diagnostic criteria for mild cognitive impairment in PD. The proposed diagnostic criteria are based on a literature review and expert consensus. This article provides guidelines to characterize the clinical syndrome and methods for its diagnosis. The criteria will require validation, and possibly refinement, as additional research improves our understanding of the epidemiology, presentation, neurobiology, assessment, and long-term course of this clinical syndrome. These diagnostic criteria will support future research efforts to identify at the earliest stage those PD patients at increased risk of progressive cognitive decline and dementia who may benefit from clinical interventions at a predementia stage.

pkCSM: Predicting Small-Molecule Pharmacokinetic and Toxicity Properties Using Graph-Based Signatures

Abstract: Drug development has a high attrition rate, with poor pharmacokinetic and safety properties a significant hurdle. Computational approaches may help minimize these risks. We have developed a novel approach (pkCSM) which uses graph-based signatures to develop predictive models of central ADMET properties for drug development. pkCSM performs as well or better than current methods. A freely accessible web server (http://structure.bioc.cam.ac.uk/pkcsm), which retains no information submitted to it, provides an integrated platform to rapidly evaluate pharmacokinetic and toxicity properties.

Firefly Algorithm, Stochastic Test Functions and Design Optimisation

Abstract: Modern optimisation algorithms are often metaheuristic, and they are very promising in solving NP-hard optimization problems. In this paper, we show how to use the recently developed Firefly Algorithm to solve nonlinear design problems. For the standard pressure vessel design optimisation, the optimal solution found by FA is far better than the best solution obtained previously in literature. In addition, we also propose a few new test functions with either singularity or stochastic components but with known global optimality, and thus they can be used to validate new optimisation algorithms. Possible topics for further research are also discussed.