Heterogeneity evidence and linkage studies on Charcot-Marie-Tooth disease

Charcot-Marie-Tooth neuropathy type 1 (CMT1) is an autosomal dominant disorder originally localized to chromosome 1 by linkage to the Duffy blood group. Studies have since shown that the disorder may be heterogeneous, as not all families show this linkage. We tested genetic heterogeneity by the HOMOG computer program in 15 CMT1 pedigrees informative for Duffy. We detected no evidence for heterogeneity in this sample, but when we combined results with previously published lod scores, heterogeneity was statistically significant. Twelve of the 15 families studied did not show linkage to Duffy. We found six of these families to be informative for a chromosome 19 marker, apolipoprotein CII(ApoC2). Despite a previous report showing probable linkage of a non-Duffy-linked CMT1 pedigree to two chromosome 19 markers, we did not detect significant linkage of ApoC2 to CMT1 in these families.

Understanding requirements of novel healthcare information systems for management of advanced prostate cancer

Effective management of chronic diseases is a global health priority. A healthcare information system offers opportunities to address challenges of chronic disease management. However, the requirements of health information systems are often not well understood. The accuracy of requirements has a direct impact on the successful design and implementation of a health information system. Our research describes methods used to understand the requirements of health information systems for advanced prostate cancer management. The research conducted a survey to identify heterogeneous sources of clinical records. Our research showed that the General Practitioner was the common source of patient's clinical records (41%) followed by the Urologist (14%) and other clinicians (14%). Our research describes a method to identify diverse data sources and proposes a novel patient journey browser prototype that integrates disparate data sources.

Familial typical migraine: Linkage to chromosome 19p13 and evidence for genetic heterogeneity

Migraine is a frequent familial disorder that, in common with most multifactorial disorders, has an unknown etiology. The authors identified several families with multiple individuals affected by typical migraine using a single set of diagnostic criteria and studied these families for cosegregation between the disorder and markers on chromosome 19, the location of a mutation that causes a rare form of familial hemiplegic migraine (FHM). One large tested family showed both cosegregation and significant allele sharing for markers situated within or adjacent to the FHM locus. Multipoint GENEHUNTER results indicated significant excess allele sharing across a 12.6- cM region containing the FHM Ca2+ channel gene, CACNL1A4 (maximum nonparametric linkage Z score = 6.64, p = 0.0026), with a maximum parametric lod score of 1.92 obtained for a (CAG)(n) triplet repeat polymorphism situated in exon 47 of this gene. The CAG expansion did not, however, appear to be the cause of migraine in this pedigree. Other tested families showed neither cosegregation nor excess allele sharing to chromosome 19 markers. HOMOG analysis indicated heterogeneity, generating a maximum HLOD score of 3.6. It was concluded that Chr19 mutations either in the CACNL1A4 gene or a closely linked gene are implicated in some pedigrees with familial typical migraine, and that the disorder is genetically heterogeneous.

Composite SaaS resource management in cloud computing using evolutionary computation

Cloud computing is an emerging computing paradigm in which IT resources are provided over the Internet as a service to users. One such service offered through the Cloud is Software as a Service or SaaS. SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. SaaS is receiving substantial attention today from both software providers and users. It is also predicted to has positive future markets by analyst firms. This raises new challenges for SaaS providers managing SaaS, especially in large-scale data centres like Cloud. One of the challenges is providing management of Cloud resources for SaaS which guarantees maintaining SaaS performance while optimising resources use. Extensive research on the resource optimisation of Cloud service has not yet addressed the challenges of managing resources for composite SaaS. This research addresses this gap by focusing on three new problems of composite SaaS: placement, clustering and scalability. The overall aim is to develop efficient and scalable mechanisms that facilitate the delivery of high performance composite SaaS for users while optimising the resources used. All three problems are characterised as highly constrained, large-scaled and complex combinatorial optimisation problems. Therefore, evolutionary algorithms are adopted as the main technique in solving these problems. The first research problem refers to how a composite SaaS is placed onto Cloud servers to optimise its performance while satisfying the SaaS resource and response time constraints. Existing research on this problem often ignores the dependencies between components and considers placement of a homogenous type of component only. A precise problem formulation of composite SaaS placement problem is presented. A classical genetic algorithm and two versions of cooperative co-evolutionary algorithms are designed to now manage the placement of heterogeneous types of SaaS components together with their dependencies, requirements and constraints. Experimental results demonstrate the efficiency and scalability of these new algorithms. In the second problem, SaaS components are assumed to be already running on Cloud virtual machines (VMs). However, due to the environment of a Cloud, the current placement may need to be modified. Existing techniques focused mostly at the infrastructure level instead of the application level. This research addressed the problem at the application level by clustering suitable components to VMs to optimise the resource used and to maintain the SaaS performance. Two versions of grouping genetic algorithms (GGAs) are designed to cater for the structural group of a composite SaaS. The first GGA used a repair-based method while the second used a penalty-based method to handle the problem constraints. The experimental results confirmed that the GGAs always produced a better reconfiguration placement plan compared with a common heuristic for clustering problems. The third research problem deals with the replication or deletion of SaaS instances in coping with the SaaS workload. To determine a scaling plan that can minimise the resource used and maintain the SaaS performance is a critical task. Additionally, the problem consists of constraints and interdependency between components, making solutions even more difficult to find. A hybrid genetic algorithm (HGA) was developed to solve this problem by exploring the problem search space through its genetic operators and fitness function to determine the SaaS scaling plan. The HGA also uses the problem's domain knowledge to ensure that the solutions meet the problem's constraints and achieve its objectives. The experimental results demonstrated that the HGA constantly outperform a heuristic algorithm by achieving a low-cost scaling and placement plan. This research has identified three significant new problems for composite SaaS in Cloud. Various types of evolutionary algorithms have also been developed in addressing the problems where these contribute to the evolutionary computation field. The algorithms provide solutions for efficient resource management of composite SaaS in Cloud that resulted to a low total cost of ownership for users while guaranteeing the SaaS performance.

Effect of the mediator in feedback mode-based SECM interrogation of indium tin-oxide and boron-doped diamond electrodes

Indium tin-oxide (ITO) and polycrystalline boron-doped diamond (BDD) have been examined in detail using the scanning electrochemical microscopy technique in feedback mode. For the interrogation of electrodes made from these materials, the choice of mediator has been varied. Using Ru(CN) 4− 6 (aq), ferrocene methanol (FcMeOH), Fe(CN) 3− 6 (aq) and Ru(NH 3) 3+ 6 (aq), approach curve experiments have been performed, and for purposes of comparison, calculations of the apparent heterogeneous electron transfer rates (k app) have been made using these data. In general, it would appear that values of k app are affected mainly by the position of the mediator reversible potential relative to the relevant semiconductor band edge (associated with majority carriers). For both the ITO (n type) and BDD (p type) electrodes, charge transfer is impeded and values are very low when using FcMeOH and Fe(CN) 3− 6 (aq) as mediators, and the use of Ru(NH 3) 3+ 6(aq) results in the largest value of k app. With ITO, the surface is chemically homogeneous and no variation is observed for any given mediator. Data is also presented where the potential of the ITO electrode is fixed using a ratio of the mediators Fe(CN) 3− 6(aq) and Fe(CN) 4− 6(aq). In stark contrast, the BDD electrode is quite the opposite and a range of k app values are observed for all mediators depending on the position on the surface. Both electrode surfaces are very flat and very smooth, and hence, for BDD, variations in feedback current imply a variation in the electrochemical activity. A comparison of the feedback current where the substrate is biased and unbiased shows a surprising degree of proportionality.

Investigation of mediated oxidation of ascorbic acid by ferrocenemethanol using large-amplitude fourier transformed ac voltammetry under quasi-reversible electron-transfer conditions at an indium tin oxide electrode

The ability of the technique of large-amplitude Fourier transformed (FT) ac voltammetry to facilitate the quantitative evaluation of electrode processes involving electron transfer and catalytically coupled chemical reactions has been evaluated. Predictions derived on the basis of detailed simulations imply that the rate of electron transfer is crucial, as confirmed by studies on the ferrocenemethanol (FcMeOH)-mediated electrocatalytic oxidation of ascorbic acid. Thus, at glassy carbon, gold, and boron-doped diamond electrodes, the introduction of the coupled electrocatalytic reaction, while producing significantly enhanced dc currents, does not affect the ac harmonics. This outcome is as expected if the FcMeOH (0/+) process remains fully reversible in the presence of ascorbic acid. In contrast, the ac harmonic components available from FT-ac voltammetry are predicted to be highly sensitive to the homogeneous kinetics when an electrocatalytic reaction is coupled to a quasi-reversible electron-transfer process. The required quasi-reversible scenario is available at an indium tin oxide electrode. Consequently, reversible potential, heterogeneous charge-transfer rate constant, and charge-transfer coefficient values of 0.19 V vs Ag/AgCl, 0.006 cm s (-1) and 0.55, respectively, along with a second-order homogeneous chemical rate constant of 2500 M (-1) s (-1) for the rate-determining step in the catalytic reaction were determined by comparison of simulated responses and experimental voltammograms derived from the dc and first to fourth ac harmonic components generated at an indium tin oxide electrode. The theoretical concepts derived for large-amplitude FT ac voltammetry are believed to be applicable to a wide range of important solution-based mediated electrocatalytic reactions.

Rapid synthesis of porous honeycomb Cu/Pd through a hydrogen-bubble templating method

A rapid electrochemical method based on using a clean hydrogen-bubble template to form a bimetallic porous honeycomb Cu/Pd structure has been investigated. The addition of palladium salt to a copper-plating bath under conditions of vigorous hydrogen evolution was found to influence the pore size and bulk concentration of copper and palladium in the honeycomb bimetallic structure. The surface was characterised by X-ray photoelectron spectroscopy, which revealed that the surface of honeycomb Cu/Pd was found to be rich with a Cu/Pd alloy. The inclusion of palladium in the bimetallic structure not only influenced the pore size, but also modified the dendritic nature of the internal wall structure of the parent copper material into small nanometre-sized crystallites. The chemical composition of the bimetallic structure and substantial morphology changes were found to significantly influence the surface-enhanced Raman spectroscopic response for immobilised rhodamine B and the hydrogen-evolution reaction. The ability to create free-standing films of this honeycomb material may also have many advantages in the areas of gas- and liquid-phase heterogeneous catalysis.

Fabrication of metal-nanoparticle-modified semiconducting copper--and silver--TCNQ materials as substrates for the reduction of chromium (VI) using thiosulfate ions at ambient temperature

The formation of readily recoverable and reusable organic semiconducting Cu- and AgTCNQ (TCNQ=7,7,8,8-tetracyanoquinodimethane) microstructures decorated with Pt and Pd metallic nanoparticles is described for the effective reduction of CrVI ions in aqueous solution at room temperature using both formic acid and an environmentally friendly thiosulfate reductant. The M-TCNQ (M=metal) materials were formed by electrocrystallisation onto a glassy carbon surface followed by galvanic replacement in the presence of H2PtCl6 or PdCl2 to form the composite material. It was found that loading of the surface with nanoparticles could easily be controlled by changing the metal salt concentration. Significantly, the M-TCNQ substrates facilitated the formation of well-isolated metal nanoparticles on their surfaces under appropriate galvanic replacement conditions. The semiconductor–metal nanoparticle combination was also found to be critical to the catalyst performance, wherein the best-performing material was CuTCNQ modified by well-isolated Pt nanoparticles with both formic acid and thiosulfate ions as the reductant.

Single-agent versus combination chemotherapy in patients with advanced non-small cell lung cancer and a performance status of 2 : prognostic factors and treatment selection based on two large randomized clinical trials

Purpose: Data from two randomized phase III trials were analyzed to evaluate prognostic factors and treatment selection in the first-line management of advanced non-small cell lung cancer patients with performance status (PS) 2. Patients and Methods: Patients randomized to combination chemotherapy (carboplatin and paclitaxel) in one trial and single-agent therapy (gemcitabine or vinorelbine) in the second were included in these analyses. Both studies had identical eligibility criteria and were conducted simultaneously. Comparison of efficacy and safety was performed between the two cohorts. A regression analysis identified prognostic factors and subgroups of patients that may benefit from combination or single-agent therapy. Results: Two hundred one patients were treated with combination and 190 with single-agent therapy. Objective responses were 37 and 15%, respectively. Median time to progression was 4.6 months in the combination arm and 3.5 months in the single-agent arm (p < 0.001). Median survival imes were 8.0 and 6.6 months, and 1-year survival rates were 31 and 26%, respectively. Albumin <3.5 g, extrathoracic metastases, lactate dehydrogenase ≥200 IU, and 2 comorbid conditions predicted outcome. Patients with 0-2 risk factors had similar outcomes independent of treatment, whereas patients with 3-4 factors had a nonsignificant improvement in median survival with combination chemotherapy. Conclusion: Our results show that PS2 non-small cell lung cancer patients are a heterogeneous group who have significantly different outcomes. Patients treated with first-line combination chemotherapy had a higher response and longer time to progression, whereas overall survival did not appear significantly different. A prognostic model may be helpful in selecting PS 2 patients for either treatment strategy. © 2009 by the International Association for the Study of Lung Cancer.

Pulse-coupled neural network performance for real-time identification of vegetation during forced landing

Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the a mission should be aborted due to mechanical or other failure. On-board cameras provide information that can be used in the determination of potential landing sites, which are continually updated and ranked to prevent injury and minimize damage. Pulse Coupled Neural Networks have been used for the detection of features in images that assist in the classification of vegetation and can be used to minimize damage to the aerial vehicle. However, a significant drawback in the use of PCNNs is that they are computationally expensive and have been more suited to off-line applications on conventional computing architectures. As heterogeneous computing architectures are becoming more common, an OpenCL implementation of a PCNN feature generator is presented and its performance is compared across OpenCL kernels designed for CPU, GPU and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images obtained during unmanned aerial vehicle trials to determine the plausibility for real-time feature detection.

The RNA world in plants: Post-transcriptional control III

Post-transcriptional control of gene expression has gone from a curiosity involving a few special genes to a highly diverse and widespread set of processes that is truly pervasive in plant gene expression. Thus, Plant Cell readers interested in almost any aspect of plant gene expression in response to any environmental influence, or in development, are advised to read on. In May 2001, what has become the de facto third biennial Symposium on Post-Transcriptional Control of Gene Expression in Plants was held in Ames, Iowa. The meeting was hosted by the new Plant Sciences Institute of Iowa State University with additional funding from the National Science Foundation and the United States Department of Agriculture. In 1997, the annual University of California-Riverside Plant Physiology Symposium was devoted to this topic. This provided a wake-up call to the plant world, summarized in this journal (Gallie and Bailey-Serres, 1997), that not all gene expression is controlled at the level of transcription. This was expanded upon at a European Molecular Biology Organization Workshop in Leysin, Switzerland, in 1999 (Bailey-Serres et al., 1999). The 3-day meeting in Ames brought together a strong and diverse contingent of plant biologists from four continents. The participants represented an unusually heterogeneous group of disciplines ranging from virology to stress response to computational biology. The research approaches and techniques represented were similarly diverse. Here we discuss a sample of the many fascinating aspects of post-transcriptional control that were presented at this meeting; we apologize to those whose work is not described here.

Appetite, satiety, and food reward in obese individuals : a behavioral phenotype approach

Why do some people remain lean while others are susceptible to obesity, and why do obese individuals vary in their successes in losing weight? Despite physiological processes that promote satiety and satiation, some individuals are more susceptible to overeating. While the phenomena of susceptibility to weight gain, resistance to treatment or weight loss, and individual variability are not novel, they have yet to be exploited and systematically examined to better understand how to characterise phenotypes of obesity. The identification and characterisation of distinct phenotypes not only highlight the heterogeneous nature of obesity but may also help to inform the development of more tailored strategies for the treatment and prevention of obesity. This review examines the evidence for different susceptible phenotypes of obesity that are characterised by risk factors associated with the hedonic and homeostatic systems of appetite control.

Application of cepstrum pre-whitening for the diagnosis of bearing faults under variable speed conditions

Diagnostics of rolling element bearings involves a combination of different techniques of signal enhancing and analysis. The most common procedure presents a first step of order tracking and synchronous averaging, able to remove the undesired components, synchronous with the shaft harmonics, from the signal, and a final step of envelope analysis to obtain the squared envelope spectrum. This indicator has been studied thoroughly, and statistically based criteria have been obtained, in order to identify damaged bearings. The statistical thresholds are valid only if all the deterministic components in the signal have been removed. Unfortunately, in various industrial applications, characterized by heterogeneous vibration sources, the first step of synchronous averaging is not sufficient to eliminate completely the deterministic components and an additional step of pre-whitening is needed before the envelope analysis. Different techniques have been proposed in the past with this aim: The most widely spread are linear prediction filters and spectral kurtosis. Recently, a new technique for pre-whitening has been proposed, based on cepstral analysis: the so-called cepstrum pre-whitening. Owing to its low computational requirements and its simplicity, it seems a good candidate to perform the intermediate pre-whitening step in an automatic damage recognition algorithm. In this paper, the effectiveness of the new technique will be tested on the data measured on a full-scale industrial bearing test-rig, able to reproduce the harsh conditions of operation. A benchmark comparison with the traditional pre-whitening techniques will be made, as a final step for the verification of the potentiality of the cepstrum pre-whitening.

Plasmonic nanostructures to enhance catalytic performance of zeolites under visible light

Light absorption efficiency of heterogeneous catalysts has restricted their photocatalytic capability for commercially important organic synthesis. Here, we report a way of harvesting visible light efficiently to boost zeolite catalysis by means of plasmonic gold nanoparticles (Au-NPs) supported on zeolites. Zeolites possess strong Brønsted acids and polarized electric fields created by extra-framework cations. The polarized electric fields can be further intensified by the electric near-field enhancement of Au-NPs, which results from the localized surface plasmon resonance (LSPR) upon visible light irradiation. The acetalization reaction was selected as a showcase performed on MZSM-5 and Au/MZSM-5 (M = H+, Na+, Ca2+, or La3+). The density functional theory (DFT) calculations confirmed that the intensified polarized electric fields played a critical role in stretching the C = O bond of the reactants of benzaldehyde to enlarge their molecular polarities, thus allowing reactants to be activated more efficiently by catalytic centers so as to boost the reaction rates. This discovery should evoke intensive research interest on plasmonic metals and diverse zeolites with an aim to take advantage of sunlight for plasmonic devices, molecular electronics, energy storage, and catalysis.

Developing a dashboard for real-time data stream composition and visualization

Technological advances have led to an influx of affordable hardware that supports sensing, computation and communication. This hardware is increasingly deployed in public and private spaces, tracking and aggregating a wealth of real-time environmental data. Although these technologies are the focus of several research areas, there is a lack of research dealing with the problem of making these capabilities accessible to everyday users. This thesis represents a first step towards developing systems that will allow users to leverage the available infrastructure and create custom tailored solutions. It explores how this notion can be utilized in the context of energy monitoring to improve conventional approaches. The project adopted a user-centered design process to inform the development of a flexible system for real-time data stream composition and visualization. This system features an extensible architecture and defines a unified API for heterogeneous data streams. Rather than displaying the data in a predetermined fashion, it makes this information available as building blocks that can be combined and shared. It is based on the insight that individual users have diverse information needs and presentation preferences. Therefore, it allows users to compose rich information displays, incorporating personally relevant data from an extensive information ecosystem. The prototype was evaluated in an exploratory study to observe its natural use in a real-world setting, gathering empirical usage statistics and conducting semi-structured interviews. The results show that a high degree of customization does not warrant sustained usage. Other factors were identified, yielding recommendations for increasing the impact on energy consumption.