Mechanisms of expression of pyruvate dehydrogenase deficiency caused by an E1alpha subunit mutation

OBJECTIVE: To characterize the biochemical mechanisms of expression of the pyruvate dehydrogenase (PDH) E1alpha subunit exon 10 R302C missense mutation. BACKGROUND: Mutations in the X-linked E1alpha subunit gene are responsible for most cases of PDH deficiency, an important cause of neurodevelopmental defects and neurodegeneration with primary lactic acidemia. Although the disease shows extreme allelic heterogeneity, the R302C mutation has been defined in several unrelated cases. METHODS: Cell lines expressing selectively either the mutant or wild-type E1alpha alleles against identical genetic backgrounds were generated from the fibroblasts of a female heterozygous for the R302C mutation. Enzyme activity, mRNA, polypeptide expression, and turnover were studied in each. RESULTS: The residual PDH activity was below measurable levels in the cell line (B5) expressing only the mutant allele and normal in the wild-type polypeptide expressing (A10) cell line, confirming that the R302C mutation alone is sufficient to cause a severe PDH deficiency. The mutant polypeptide was less stable than the wild-type polypeptide, but the steady-state level of the mutant E1alpha protein was reduced only two- to threefold. CONCLUSIONS: The primary mechanism of expression of the R302C mutation must be limitation of catalytic efficiency. We speculate that catalysis may be inhibited in the mutant polypeptide because conformational changes are induced near serine 300, a residue that is particularly important as a regulatory phosphorylation site in the wild-type polypeptide.     

What are users’ intentions towards real money trading in massively multiplayer online games?

This study investigates user behaviour in massively multiplayer online games from the perspective of their intentions to engage in real money trading. Players who engage in real money trading purchase resources instead of spending time to acquire them in the game. This behaviour influences not just their own gaming experience, but those of other players as well as the operator??s revenues. We present an online survey which targets the players of World of Warcraft. Players?? relationships with real money trading are investigated using insights from behavioural economics. We propose a model which includes a set of behavioural determinants grounded in empirical research on online games. The study??s findings indicate that a player??s social status and the disinhibiting effects of online play are positive influences on players?? intentions to engage in real money trading, while perceived fairness, anticipated regret and uncertainty about the seller??s behaviour are negative influences. Interestingly, neither the perceived enjoyment nor the potential punishments influence intentions.     

Enhanced chain dynamics in loop-sorting-systems by means of layout optimization and a kinematic model of the polygon action

Poor dynamics owing to polygon action is a known concern in mechanical applications of closed articulated chains. In this paper a kinematic model of the polygon action in large chains of loop-sorting-systems is proposed. Through optimization techniques the chain dynamics is improved by minimizing the polygon action using a parametric model of the track layout as design variables. Three formulations of the kinematic polygon action are tested on an average sized planer tracks layout to find a superior model. Verification of the proposed optimization method is performed using a state-of-the-art multi-body simulation model of the chain dynamics.     

What you get is what you see: revisiting the evaluator effect in usability tests

Usability evaluation is essential to user-centred design; yet, evaluators who analyse the same usability test sessions have been found to identify substantially different sets of usability problems. We revisit this evaluator effect by having 19 experienced usability professionals analyse video-recorded test sessions with five users. Nine participants analysed moderated sessions; 10 participants analysed unmoderated sessions. For the moderated sessions, participants reported an average of 33% of the problems reported by all nine of these participants and 50% of the subset of problems reported as critical or serious by at least one participant. For the unmoderated sessions, the percentages were 32% and 40%. Thus, the evaluator effect was similar for moderated and unmoderated sessions, and it was substantial for the full set of problems and still present for the most severe problems. In addition, participants disagreed in their severity ratings. As much as 24% (moderated) and 30% (unmoderated) of the problems reported by multiple participants were rated as critical by one participant and minor by another. The majority of the participants perceived an evaluator effect when merging their individual findings into group evaluations. We discuss reasons for the evaluator effect and recommend ways of managing it.     

On the effect of peroxisomal β-oxidation and carnitine palmitoyltransferase activity by eicosapentaenoic acid in liver and heart from rats

Repeated administration of highly purified eicosapentaenoic acid (as ethyl ester) resulted in a decrease in plasma triglycerides and high density lipoprotein (HDL) cholesterol. This was accompanied by a stimulation in the activities of carnitine palmitoyltransferase, fatty acyl-CoA oxidase and peroxisomal β-oxidation in the liver. The results suggest that the triglyceride-lowering effect observed with eicosapentaenoic acid may be due to a reduced supply of fatty acids for hepatic triglyceride synthesis because of increased fatty acid oxidation. Eicosapentaenoic acid feeding marginally affected the triglyceride content of heart and mitochondrial and peroxisomal enzyme activities.     

3D interactive topology optimization on hand-held devices

This educational paper describes the implementation aspects, user interface design considerations and workflow potential of the recently published TopOpt 3D App. The app solves the standard minimum compliance problem in 3D and allows the user to change design settings interactively at any point in time during the optimization. Apart from its educational nature, the app may point towards future ways of performing industrial design. Instead of the usual geometrize, then model and optimize approach, the geometry now automatically adapts to the varying boundary and loading conditions. The app is freely available for iOS at Apple’s App Store and at http://www.topopt.dtu.dk/TopOpt3D for Windows and OSX.     

Suspension system performance optimization with discrete design variables

Suspension systems on commercial vehicles have become an important feature meeting the requirements from costumers and legislation. The performance of the suspension system is often limited by available catalogue components. Additionally the suspension performance is restricted by the travel speed which highly influences the ride comfort. In this article a suspension system for an articulated dump truck is optimized in sense of reducing elapsed time for two specified duty cycles without violating a certain comfort threshold level. The comfort threshold level is here defined as a whole-body vibration level calculated by ISO 2631-1. A three-dimensional multibody dynamics simulation model is applied to evaluate the suspension performance. A non-gradient optimization routine is used to find the best possible combination of continuous and discrete design variables including the optimum operational speed without violating a set of side constraints. The result shows that the comfort level converges to the comfort threshold level. Thus it is shown that the operational speed and hence the operator input influences the ride comfort level. Three catalogue components are identified by the optimization routine together with a set of continuous design variables and two operational speeds one for each load case. Thus the work demonstrates handling of human factors in optimization of a mechanical system with discrete and continuous design variables.     

Interactive topology optimization on hand-held devices

This paper presents an interactive topology optimization application designed for hand-held devices running iOS or Android. The TopOpt app solves the 2D minimum compliance problem with interactive control of load and support positions as well as volume fraction. Thus, it is possible to change the problem settings on the fly and watch the design evolve to a new optimum in real time. The use of an interactive app makes it extremely simple to learn and understand the influence of load-directions, support conditions and volume fraction. The topology optimization kernel is written in C# and the graphical user interface is developed using the game engine Unity3D. The underlying code is inspired by the publicly available 88 and 99 line Matlab codes for topology optimization but does not utilize any low-level linear algebra routines such as BLAS or LAPACK. The TopOpt App can be downloaded on iOS devices from the Apple App Store, at Google Play for the Android platform, and a web-version can be run from www.topopt.dtu.dk.     

Redesign of adaptive observers for improved parameter identification in nonlinear systems

We propose a method for redesigning adaptive observers for nonlinear systems. The redesign uses an adaptive law that is based on delayed observers. This increases the computational burden, but gives significantly better parameter identification and robustness properties. In particular, given that a special persistency of excitation condition is satisfied, we prove uniform global asymptotic stability and semi-global exponential stability of the origin of the state and parameter estimation error, and give explicit lower bounds on the convergence rate of both the state and parameter estimation error dynamics. For initial conditions with a known upper bound, we prove tunable exponential convergence rate. To illustrate the use of the proposed method, we apply it to estimate the unmeasured flow rate and the uncertain friction parameters in a model of a managed pressure drilling system. The simulation results clearly show the improved performance of the redesigned adaptive observer compared to a traditional design.     

Learning automata-based solutions to the nonlinear fractional knapsack problem with applications to optimal resource allocation.

This paper considers the nonlinear fractional knapsack problem and demonstrates how its solution can be effectively applied to two resource allocation problems dealing with the World Wide Web. The novel solution involves a "team" of deterministic learning automata (LA). The first real-life problem relates to resource allocation in web monitoring so as to "optimize" information discovery when the polling capacity is constrained. The disadvantages of the currently reported solutions are explained in this paper. The second problem concerns allocating limited sampling resources in a "real-time" manner with the purpose of estimating multiple binomial proportions. This is the scenario encountered when the user has to evaluate multiple web sites by accessing a limited number of web pages, and the proportions of interest are the fraction of each web site that is successfully validated by an HTML validator. Using the general LA paradigm to tackle both of the real-life problems, the proposed scheme improves a current solution in an online manner through a series of informed guesses that move toward the optimal solution. At the heart of the scheme, a team of deterministic LA performs a controlled random walk on a discretized solution space. Comprehensive experimental results demonstrate that the discretization resolution determines the precision of the scheme, and that for a given precision, the current solution (to both problems) is consistently improved until a nearly optimal solution is found--even for switching environments. Thus, the scheme, while being novel to the entire field of LA, also efficiently handles a class of resource allocation problems previously not addressed in the literature.