173 research outputs found

    A framework for power analysis using a structural equation modelling procedure

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    BACKGROUND: This paper demonstrates how structural equation modelling (SEM) can be used as a tool to aid in carrying out power analyses. For many complex multivariate designs that are increasingly being employed, power analyses can be difficult to carry out, because the software available lacks sufficient flexibility. Satorra and Saris developed a method for estimating the power of the likelihood ratio test for structural equation models. Whilst the Satorra and Saris approach is familiar to researchers who use the structural equation modelling approach, it is less well known amongst other researchers. The SEM approach can be equivalent to other multivariate statistical tests, and therefore the Satorra and Saris approach to power analysis can be used. METHODS: The covariance matrix, along with a vector of means, relating to the alternative hypothesis is generated. This represents the hypothesised population effects. A model (representing the null hypothesis) is then tested in a structural equation model, using the population parameters as input. An analysis based on the chi-square of this model can provide estimates of the sample size required for different levels of power to reject the null hypothesis. CONCLUSIONS: The SEM based power analysis approach may prove useful for researchers designing research in the health and medical spheres

    A Novel, All-Optical Tool for Controllable and Non- Destructive Poration of Cells with Single-Micron Resolution

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    We demonstrate controllable poration within ≈1 µm regions of individual cells, mediated by a near-IR laser interacting with thin-layer amorphous silicon substrates. This technique will allow new experiments in single-cell biology, particularly in neuroscience. As our understanding of the fundamental mechanistic processes underpinning biology expands, so does the need for high-precision tools to allow the dissection of the heterogeneity and stochastic processes that dominate at the single- and sub-cellular level. Here, we demonstrate a highly controllable and reproducible optical technique for inducing poration within specific regions of a target cell’s plasma membrane, permitting localized delivery of payloads, depolarization and lysis experiments to be conducted in unprecedented detail. Experiments support a novel mechanism for the process, based upon a thermally-induced change triggered by the interactions of a near-IR laser with a biocompatible thin film substrate at powers substantially below that used in standard optoporation experiments

    Non-stationary stochastic inventory lot-sizing with emission and service level constraints in a carbon cap-and-trade system

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    Firms worldwide are taking major initiatives to reduce the carbon footprint of their supply chains in response to the growing governmental and consumer pressures. In real life, these supply chains face stochastic and non-stationary demand but most of the studies on inventory lot-sizing problem with emission concerns consider deterministic demand. In this paper, we study the inventory lot-sizing problem under non-stationary stochastic demand condition with emission and cycle service level constraints considering carbon cap-and-trade regulatory mechanism. Using a mixed integer linear programming model, this paper aims to investigate the effects of emission parameters, product- and system-related features on the supply chain performance through extensive computational experiments to cover general type business settings and not a specific scenario. Results show that cycle service level and demand coefficient of variation have significant impacts on total cost and emission irrespective of level of demand variability while the impact of product's demand pattern is significant only at lower level of demand variability. Finally, results also show that increasing value of carbon price reduces total cost, total emission and total inventory and the scope of emission reduction by increasing carbon price is greater at higher levels of cycle service level and demand coefficient of variation. The analysis of results helps supply chain managers to take right decision in different demand and service level situations

    A population-based study of anxiety as a precursor for depression in childhood and adolescence

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    BACKGROUND: Anxiety and depression co-occur in children and adolescents with anxiety commonly preceding depression. Although there is some evidence to suggest that the association between early anxiety and later depression is explained by a shared genetic aetiology, the contribution of environmental factors is less well examined and it is unknown whether anxiety itself is a phenotypic risk factor for later depression. These explanations of the association between early anxiety and later depression were evaluated. METHODS: Anxiety and depressive symptoms were assessed longitudinally in a U.K. population-based sample of 676 twins aged 5–17 at baseline. At baseline, anxiety and depression were assessed by parental questionnaire. Depression was assessed three years later by parental and adolescent questionnaire. RESULTS: Shared genetic effects between early anxiety and later depression were found. A model of a phenotypic risk effect from early anxiety on later depression provided a poor fit to the data. However, there were significant genetic effects specific to later depression, showing that early anxiety and later depression do not index entirely the same genetic risk. CONCLUSIONS: Anxiety and depression are associated over time because they share a partly common genetic aetiology rather than because the anxiety phenotype leads to later depression

    Heritability of Self-reported Phobic Fear

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    Twin studies on fear and phobia suggest moderate genetic effects. However, results are inconclusive regarding the presence of dominant genetic effects and sex differences. Using an extended twin design, including male and female twins (n = 5,465) and their siblings (n = 1,624), we examined the genetic and environmental influences on blood-injury, social, and agoraphobic fear and investigated their interaction with sex and age. Data of spouses (n = 708) of twins were used to evaluate assortative mating for the three fear dimensions. Results showed that there was no assortative mating for blood-injury, social and agoraphobic fear. Resemblance between biological relatives could be explained by additive and non-additive genetic effects for blood-injury and agoraphobic fear in all participants, and social fear in participants aged 14–25 years. For social fear in participants aged 26–65 only additive genetic effects were detected. Broad-sense heritability estimates ranged from 36 to 51% and were similar for men and women

    A polygenic burden of rare disruptive mutations in schizophrenia.

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    Schizophrenia is a common disease with a complex aetiology, probably involving multiple and heterogeneous genetic factors. Here, by analysing the exome sequences of 2,536 schizophrenia cases and 2,543 controls, we demonstrate a polygenic burden primarily arising from rare (less than 1 in 10,000), disruptive mutations distributed across many genes. Particularly enriched gene sets include the voltage-gated calcium ion channel and the signalling complex formed by the activity-regulated cytoskeleton-associated scaffold protein (ARC) of the postsynaptic density, sets previously implicated by genome-wide association and copy-number variation studies. Similar to reports in autism, targets of the fragile X mental retardation protein (FMRP, product of FMR1) are enriched for case mutations. No individual gene-based test achieves significance after correction for multiple testing and we do not detect any alleles of moderately low frequency (approximately 0.5 to 1 per cent) and moderately large effect. Taken together, these data suggest that population-based exome sequencing can discover risk alleles and complements established gene-mapping paradigms in neuropsychiatric disease

    QTL analysis and genomic selection using RADseq derived markers in Sitka spruce: the potential utility of within family data

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    Sitka spruce (Picea sitchensis (Bong.) Carr) is the most common commercial plantation species in Britain and a breeding programme based on traditional lines has been in operation since the early 1960s. Rotation lengths of 40-years have led breeders to adopt a process of indirect selection at younger ages based on traits well correlated with final selection, but still the generation interval is unlikely to reduce much below twenty years. Recent successful developments with genomic selection in animal breeding have led tree breeders to consider the application of this technology. In this study a RAD sequence assay was developed as a means of investigating the potential of molecular breeding in a non-model species. DNA was extracted from nearly 500 clonally replicated trees growing in a single full-sibling family at one site in Britain. The technique proved successful in identifying 132 QTLs for 5-year bud-burst and 2 QTLs for 6-year height. In addition, the accuracy of predicting phenotypes by genomic selection was strikingly high at 0.62 and 0.59 respectively. Sensitivity analysis with 200 offspring found only a slight fall in correlation values (0.54 and 0.38) although when the training population reduced to 50 offspring predictive values fell further (0.33 and 0.25). This proved an encouraging first investigation into the potential use of genomic selection in the breeding of Sitka spruce. The authors investigate how problems associated with effective population size and linkage disequilibrium can be avoided and suggest a practical way of incorporating genomic selection into a dynamic breeding programme

    Targeted sequencing of lung function loci in chronic obstructive pulmonary disease cases and controls

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    Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide; smoking is the main risk factor for COPD, but genetic factors are also relevant contributors. Genome-wide association studies (GWAS) of the lung function measures used in the diagnosis of COPD have identified a number of loci, however association signals are often broad and collectively these loci only explain a small proportion of the heritability. In order to examine the association with COPD risk of genetic variants down to low allele frequencies, to aid fine-mapping of association signals and to explain more of the missing heritability, we undertook a targeted sequencing study in 300 COPD cases and 300 smoking controls for 26 loci previously reported to be associated with lung function. We used a pooled sequencing approach, with 12 pools of 25 individuals each, enabling high depth (30x) coverage per sample to be achieved. This pooled design maximised sample size and therefore power, but led to challenges during variant-calling since sequencing error rates and minor allele frequencies for rare variants can be very similar. For this reason we employed a rigorous quality control pipeline for variant detection which included the use of 3 independent calling algorithms. In order to avoid false positive associations we also developed tests to detect variants with potential batch effects and removed them before undertaking association testing. We tested for the effects of single variants and the combined effect of rare variants within a locus. We followed up the top signals with data available (only 67% of collapsing methods signals) in 4,249 COPD cases and 11,916 smoking controls from UK Biobank. We provide suggestive evidence for the combined effect of rare variants on COPD risk in TNXB and in sliding windows within MECOM and upstream of HHIP. These findings can lead to an improved understanding of the molecular pathways involved in the development of COPD
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