Variation in RTN3 and PPIL2 Genes Does not Influence Platelet Membrane β-Secretase Activity or Susceptibility to Alzheimer’s Disease in the Northern Irish Population

beta-site amyloid precursor protein cleaving enzyme (BACE1) is the rate-limiting enzyme for production of beta-amyloid peptides (A beta), which are proposed to drive the pathological changes found in Alzheimer's disease (AD). Reticulon 3 (RTN3) is a negative modulator of BACE1 (beta-secretase) proteolytic activity, while peptidylprolyl isomerase (cyclophilin)-like 2 (PPIL2) positively regulates BACE1 expression. The present study investigated whether there was any association between genetic variation in RTN3 and PPIL2, and either risk for AD, or levels of platelet beta-secretase activity, in a large Northern Irish case-control sample. Four hundred and sixty-nine patients with a diagnosis of probable AD (NINCDS-ADRDA criteria) and 347 control individuals (MMSE > 28/30) were genotyped. SNPs in both genes were selected by downloading genotype data from the International HapMap Project (Phase II) and tags selected using multimarker approach in Haploview, where r (2) > 0.8 and LOD > 3.0. Non-synonymous SNPs of interest were also included. Genotyping was performed by Sequenom iPLEX and TaqMan technologies. Alleles, genotypes and multi-marker haplotypes were tested for association with AD, and platelet beta-secretase activities were measured for a subset of individuals (n = 231). Eight SNPs in RTN3 and 7 in PPIL2 were genotyped. We found no significant associations between allele, genotype or haplotype frequencies and risk of AD. Further, there was no effect of genotype on platelet membrane beta-secretase activity. We conclude that common or potentially functional genetic variation in these BACE1 interacting proteins does not affect platelet membrane beta-secretase activity or contribute to risk of AD in this population.

Viscoelastic Material Models of Polypropylene for Thermoforming Applications

Polypropylene (PP), a semi-crystalline material, is typically solid phase thermoformed at temperatures associated with crystalline melting, generally in the 150° to 160°Celsius range. In this very narrow thermoforming window the mechanical properties of the material rapidly decline with increasing temperature and these large changes in properties make Polypropylene one of the more difficult materials to process by thermoforming. Measurement of the deformation behaviour of a material under processing conditions is particularly important for accurate numerical modelling of thermoforming processes. This paper presents the findings of a study into the physical behaviour of industrial thermoforming grades of Polypropylene. Practical tests were performed using custom built materials testing machines and thermoforming equipment at Queen′s University Belfast. Numerical simulations of these processes were constructed to replicate thermoforming conditions using industry standard Finite Element Analysis software, namely ABAQUS and custom built user material model subroutines. Several variant constitutive models were used to represent the behaviour of the Polypropylene materials during processing. This included a range of phenomenological, rheological and blended constitutive models. The paper discusses approaches to modelling industrial plug-assisted thermoforming operations using Finite Element Analysis techniques and the range of material models constructed and investigated. It directly compares practical results to numerical predictions. The paper culminates discussing the learning points from using Finite Element Methods to simulate the plug-assisted thermoforming of Polypropylene, which presents complex contact, thermal, friction and material modelling challenges. The paper makes recommendations as to the relative importance of these inputs in general terms with regard to correlating to experimentally gathered data. The paper also presents recommendations as to the approaches to be taken to secure simulation predictions of improved accuracy.

Real-time error detection but not error correction drives automatic visuomotor adaptation

We investigated the role of visual feedback of task performance in visuomotor adaptation. Participants produced novel two degrees of freedom movements (elbow flexion-extension, forearm pronation-supination) to move a cursor towards visual targets. Following trials with no rotation, participants were exposed to a 60A degrees visuomotor rotation, before returning to the non-rotated condition. A colour cue on each trial permitted identification of the rotated/non-rotated contexts. Participants could not see their arm but received continuous and concurrent visual feedback (CF) of a cursor representing limb position or post-trial visual feedback (PF) representing the movement trajectory. Separate groups of participants who received CF were instructed that online modifications of their movements either were, or were not, permissible as a means of improving performance. Feedforward-mediated performance improvements occurred for both CF and PF groups in the rotated environment. Furthermore, for CF participants this adaptation occurred regardless of whether feedback modifications of motor commands were permissible. Upon re-exposure to the non-rotated environment participants in the CF, but not PF, groups exhibited post-training aftereffects, manifested as greater angular deviations from a straight initial trajectory, with respect to the pre-rotation trials. Accordingly, the nature of the performance improvements that occurred was dependent upon the timing of the visual feedback of task performance. Continuous visual feedback of task performance during task execution appears critical in realising automatic visuomotor adaptation through a recalibration of the visuomotor mapping that transforms visual inputs into appropriate motor commands.