Methodological bias in cluster randomised trials

Background: Cluster randomised trials can be susceptible to a range of methodological problems. These problems are not commonly recognised by many researchers. In this paper we discuss the issues that can lead to bias in cluster trials. Methods: We used a sample of cluster randomised trials from a recent review and from a systematic review of hip protectors. We compared the mean age of participants between intervention groups in a sample of 'good' cluster trials with a sample of potentially biased trials. We also compared the effect sizes, in a funnel plot, between hip protector trials that used individual randomisation compared with those that used cluster randomisation. Results: There is a tendency for cluster trials, with evidence methodological biases, to also show an age imbalance between treatment groups. In a funnel plot we show that all cluster trials show a large positive effect of hip protectors whilst individually randomised trials show a range of positive and negative effects, suggesting that cluster trials may be producing a biased estimate of effect. Conclusion: Methodological biases in the design and execution of cluster randomised trials is frequent. Some of these biases associated with the use of cluster designs can be avoided through careful attention to the design of cluster trials. Firstly, if possible, individual allocation should be used. Secondly, if cluster allocation is required, then ideally participants should be identified before random allocation of the clusters. Third, if prior identification is not possible, then an independent recruiter should be used to recruit participants

Evaluation of Cybersecurity Threats on Smart Metering System

Smart metering has emerged as the next-generation of energy distribution, consumption, and monitoring systems via the convergence of power engineering and information and communication technology (ICT) integration otherwise known as smart grid systems. While the innovation is advancing the future power generation, distribution, consumption monitoring and information delivery, the success of the platform is positively correlated to the thriving integration of technologies upon which the system is built. Nonetheless, the rising trend of cybersecurity attacks on cyber infrastructure and its dependent systems coupled with the system’s inherent vulnerabilities present a source of concern not only to the vendors but also the consumers. These security concerns need to be addressed in order to increase consumer confidence so as to ensure greatest adoption and success of smart metering. In this paper, we present a functional communication architecture of the smart metering system. Following that, we demonstrate and discuss the taxonomy of smart metering common vulnerabilities exposure, upon which sophisticated threats can capitalize. We then introduce countermeasure techniques, whose integration is considered pivotal for achieving security protection against existing and future sophisticated attacks on smart metering systems

Electrically controlled long-distance spin transport through an antiferromagnetic insulator

Spintronics uses spins, the intrinsic angular momentum of electrons, as an alternative for the electron charge. Its long-term goal is in the development of beyond-Moore low dissipation technology devices. Recent progress demonstrated the long-distance transport of spin signals across ferromagnetic insulators. Antiferromagnetically ordered materials are however the most common class of magnetic materials with several crucial advantages over ferromagnetic systems. In contrast to the latter, antiferromagnets exhibit no net magnetic moment, which renders them stable and impervious to external fields. In addition, they can be operated at THz frequencies. While fundamentally their properties bode well for spin transport, previous indirect observations indicate that spin transmission through antiferromagnets is limited to short distances of a few nanometers. Here we demonstrate the long-distance, over tens of micrometers, propagation of spin currents through hematite (\alpha-Fe2O3), the most common antiferromagnetic iron oxide, exploiting the spin Hall effect for spin injection. We control the spin current flow by the interfacial spin-bias and by tuning the antiferromagnetic resonance frequency with an external magnetic field. This simple antiferromagnetic insulator is shown to convey spin information parallel to the compensated moment (N\'eel order) over distances exceeding tens of micrometers. This newly-discovered mechanism transports spin as efficiently as the net magnetic moments in the best-suited complex ferromagnets. Our results pave the way to ultra-fast, low-power antiferromagnet-insulator-based spin-logic devices that operate at room temperature and in the absence of magnetic fields

A novel approach to simulate gene-environment interactions in complex diseases

Background: Complex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the major part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc.). Despite a large amount of information that has been collected about both genetic and environmental risk factors, there are few examples of studies on their interactions in epidemiological literature. One reason can be the incomplete knowledge of the power of statistical methods designed to search for risk factors and their interactions in these data sets. An improvement in this direction would lead to a better understanding and description of gene-environment interactions. To this aim, a possible strategy is to challenge the different statistical methods against data sets where the underlying phenomenon is completely known and fully controllable, for example simulated ones. Results: We present a mathematical approach that models gene-environment interactions. By this method it is possible to generate simulated populations having gene-environment interactions of any form, involving any number of genetic and environmental factors and also allowing non-linear interactions as epistasis. In particular, we implemented a simple version of this model in a Gene-Environment iNteraction Simulator (GENS), a tool designed to simulate case-control data sets where a one gene-one environment interaction influences the disease risk. The main aim has been to allow the input of population characteristics by using standard epidemiological measures and to implement constraints to make the simulator behaviour biologically meaningful. Conclusions: By the multi-logistic model implemented in GENS it is possible to simulate case-control samples of complex disease where gene-environment interactions influence the disease risk. The user has full control of the main characteristics of the simulated population and a Monte Carlo process allows random variability. A knowledge-based approach reduces the complexity of the mathematical model by using reasonable biological constraints and makes the simulation more understandable in biological terms. Simulated data sets can be used for the assessment of novel statistical methods or for the evaluation of the statistical power when designing a study

Neuroblastoma Cell Death is Induced by Inorganic Arsenic Trioxide (As2O3) and Inhibited by a Normal Human Bone Marrow Cell-Derived Factor

Three phenotypically distinct cell types are present in human neuroblastomas (NB) and NB cell lines: I-type stem cells, N-type neuroblastic precursors, and S-type Schwannian/melanoblastic precursors. The stimulation of human N-type neuroblastoma cell proliferation by normal human bone marrow monocytic cell conditioned medium (BMCM) has been demonstrated in vitro, a finding consistent with the high frequency of bone marrow (BM) metastases in patients with advanced NB. Inorganic arsenic trioxide (As2O3), already clinically approved for the treatment of several hematological malignancies, is currently under investigation for NB. Recent studies show that As2O3 induces apoptosis in NB cells. We examined the impact of BMCM on growth and survival of As2O3-treated NB cell lines, to evaluate the response of cultured NB cell variants to regulatory agents. We studied the effect of BMCM on survival and clonogenic growth of eleven As2O3-treated NB cell lines grown in sparsely seeded, non-adherent, semi-solid cultures. As2O3 had a strong inhibitory effect on survival of all tested NB cell lines. BMCM augmented cell growth and survival and reversed the inhibitory action of As2O3 in all tested cell lines, but most strongly in N-type cells. While As2O3 effectively reduced survival of all tested NB cell lines, BMCM effectively impacted its inhibitory action. Better understanding of micro-environmental regulators affecting human NB tumor cell growth and survival may be seminal to the development of therapeutic strategies and clinically effective agents for this condition

Subcellular fractionation method to study endosomal trafficking of Kaposi’s sarcoma-associated herpesvirus

Background Virus entry involves multiple steps and is a highly orchestrated process on which successful infection collectively depends. Entry processes are commonly analyzed by monitoring internalized virus particles via Western blotting, polymerase chain reaction, and imaging techniques that allow scientist to track the intracellular location of the pathogen. Such studies have provided abundant direct evidence on how viruses interact with receptor molecules on the cell surface, induce cell signaling at the point of initial contact with the cell to facilitate internalization, and exploit existing endocytic mechanisms of the cell for their ultimate infectious agenda. However, there is dearth of knowledge in regards to trafficking of a virus via endosomes. Herein, we describe an optimized laboratory procedure to isolate individual organelles during different stages of endocytosis by performing subcellular fractionation. This methodology is established using Kaposi’s sarcoma-associated herpesvirus (KSHV) infection of human foreskin fibroblast (HFF) cells as a model. With KSHV and other herpesviruses alike, envelope glycoproteins have been widely reported to physically engage target cell surface receptors, such as integrins, in interactions leading to entry and subsequent infection. Results Subcellular fractionation was used to isolate early and late endosomes (EEs and LEs) by performing a series of centrifugations steps. Specifically, a centrifugation step post-homogenization was utilized to obtain the post-nuclear supernatant containing intact intracellular organelles in suspension. Successive fractionation via sucrose density gradient centrifugation was performed to isolate specific organelles including EEs and LEs. Intracellular KSHV trafficking was directly traced in the isolated endosomal fractions. Additionally, the subcellular fractionation approach demonstrates a key role for integrins in the endosomal trafficking of KSHV. The results obtained from fractionation studies corroborated those obtained by traditional imaging studies. Conclusions This study is the first of its kind to employ a sucrose flotation gradient assay to map intracellular KSHV trafficking in HFF cells. We are confident that such an approach will serve as a powerful tool to directly study intracellular trafficking of a virus, signaling events occurring on endosomal membranes, and dynamics of molecular events within endosomes that are crucial for uncoating and virus escape into the cytosol

GA-ANN Short-Term Electricity Load Forecasting

This paper presents a methodology for short-term load forecasting based on genetic algorithm feature selection and artificial neural network modeling. A feed forward artificial neural network is used to model the 24-h ahead load based on past consumption, weather and stock index data. A genetic algorithm is used in order to find the best subset of variables for modeling. Three data sets of different geographical locations, encompassing areas of different dimensions with distinct load profiles are used in order to evaluate the methodology. The developed approach was found to generate models achieving a minimum mean average percentage error under 2 %. The feature selection algorithm was able to significantly reduce the number of used features and increase the accuracy of the models

Living biointerfaces based on non-pathogenic bacteria to direct cell differentiation

Genetically modified Lactococcus lactis, non-pathogenic bacteria expressing the FNIII7-10 fibronectin fragment as a protein membrane have been used to create a living biointerface between synthetic materials and mammalian cells. This FNIII7-10 fragment comprises the RGD and PHSRN sequences of fibronectin to bind α5β1 integrins and triggers signalling for cell adhesion, spreading and differentiation. We used L. lactis strain to colonize material surfaces and produce stable biofilms presenting the FNIII7-10 fragment readily available to cells. Biofilm density is easily tunable and remains stable for several days. Murine C2C12 myoblasts seeded over mature biofilms undergo bipolar alignment and form differentiated myotubes, a process triggered by the FNIII7-10 fragment. This biointerface based on living bacteria can be further modified to express any desired biochemical signal, establishing a new paradigm in biomaterial surface functionalisation for biomedical applications

The Passive Yet Successful Way of Planktonic Life: Genomic and Experimental Analysis of the Ecology of a Free-Living Polynucleobacter Population

Background: The bacterial taxon Polynucleobacter necessarius subspecies asymbioticus represents a group of planktonic freshwater bacteria with cosmopolitan and ubiquitous distribution in standing freshwater habitats. These bacteria comprise,1 % to 70 % (on average about 20%) of total bacterioplankton cells in various freshwater habitats. The ubiquity of this taxon was recently explained by intra-taxon ecological diversification, i.e. specialization of lineages to specific environmental conditions; however, details on specific adaptations are not known. Here we investigated by means of genomic and experimental analyses the ecological adaptation of a persistent population dwelling in a small acidic pond. Findings: The investigated population (F10 lineage) contributed on average 11 % to total bacterioplankton in the pond during the vegetation periods (ice-free period, usually May to November). Only a low degree of genetic diversification of the population could be revealed. These bacteria are characterized by a small genome size (2.1 Mb), a relatively small number of genes involved in transduction of environmental signals, and the lack of motility and quorum sensing. Experiments indicated that these bacteria live as chemoorganotrophs by mainly utilizing low-molecular-weight substrates derived from photooxidation of humic substances. Conclusions: Evolutionary genome streamlining resulted in a highly passive lifestyle so far only known among free-living bacteria from pelagic marine taxa dwelling in environmentally stable nutrient-poor off-shore systems. Surprisingly, such a lifestyle is also successful in a highly dynamic and nutrient-richer environment such as the water column of the investigate