Nonlinear structural behaviour of membrane-type LNG carrier cargo containment systems under impact pressure loads at −163 °C

This paper is a sequel to the paper dealing with quasi-static responses previously studied by the authors. The structural failure of membrane-type liquefied natural gas carrier (LNGC) cargo tank is an important issue in the construction of ultra-large an LNG carrier. However, quasi-static analysis to investigate the structural failure is difficult and tends to give conservative results. To compensate the weak points of the quasi-static analysis, a procedure for the dynamic analysis was developed to assess the structural failure using nonlinear finite element method. A nonlinear finite element method is employed to model metal membrane, insulation and surface contacts. Various element formulations are tested at different points along a corrugated surface to optimise the accuracy of the model with respect to computation time. Material properties used in the model are calibrated based on experimentally measured values at cryogenic conditions (−163 °C). The model is used to predict the structural failure under different impact pressure loads and loading patterns. It is concluded that the structural damage is less likely to occur under 30 bar

The Association Between Smartphone Addiction and Sleep: A UK Cross-Sectional Study of Young Adults

Background: In a large UK study we investigated the relationship between smartphone addiction and sleep quality in a young adult population. Methods: We undertook a large UK cross-sectional observational study of 1,043 participants aged 18 to 30 between January 21st and February 30th 2019. Participants completed the Smartphone Addiction Scale Short Version, an adapted Pittsburgh Sleep Quality Score Index and reported smartphone use reduction strategies using both in-person (n = 968) and online (n = 75) questionnaires. A crude and adjusted logistic regression was fitted to assess risk factors for smartphone addiction, and the association between smartphone addiction and poor sleep. Results: One thousand seventy one questionnaires were returned, of which 1,043 participants were included, with median age 21.1 [interquartile range (IQR) 19–22]. Seven hundred and sixty three (73.2%) were female, and 406 reported smartphone addiction (38.9%). A large proportion of participants disclosed poor sleep (61.6%), and in those with smartphone addiction, 68.7% had poor sleep quality, compared to 57.1% of those without. Smartphone addiction was associated with poor sleep (aOR = 1.41, 95%CI: 1.06–1.87, p = 0.018). Conclusions: Using a validated instrument, 39% young adults reported smartphone addiction. Smartphone addiction was associated with poor sleep, independent of duration of usage, indicating that length of time should not be used as a proxy for harmful usage

Bivariate random-effects meta-analysis and the estimation of between-study correlation

BACKGROUND: When multiple endpoints are of interest in evidence synthesis, a multivariate meta-analysis can jointly synthesise those endpoints and utilise their correlation. A multivariate random-effects meta-analysis must incorporate and estimate the between-study correlation (ρ(B)). METHODS: In this paper we assess maximum likelihood estimation of a general normal model and a generalised model for bivariate random-effects meta-analysis (BRMA). We consider two applied examples, one involving a diagnostic marker and the other a surrogate outcome. These motivate a simulation study where estimation properties from BRMA are compared with those from two separate univariate random-effects meta-analyses (URMAs), the traditional approach. RESULTS: The normal BRMA model estimates ρ(B )as -1 in both applied examples. Analytically we show this is due to the maximum likelihood estimator sensibly truncating the between-study covariance matrix on the boundary of its parameter space. Our simulations reveal this commonly occurs when the number of studies is small or the within-study variation is relatively large; it also causes upwardly biased between-study variance estimates, which are inflated to compensate for the restriction on [Formula: see text] (B). Importantly, this does not induce any systematic bias in the pooled estimates and produces conservative standard errors and mean-square errors. Furthermore, the normal BRMA is preferable to two normal URMAs; the mean-square error and standard error of pooled estimates is generally smaller in the BRMA, especially given data missing at random. For meta-analysis of proportions we then show that a generalised BRMA model is better still. This correctly uses a binomial rather than normal distribution, and produces better estimates than the normal BRMA and also two generalised URMAs; however the model may sometimes not converge due to difficulties estimating ρ(B). CONCLUSION: A BRMA model offers numerous advantages over separate univariate synthesises; this paper highlights some of these benefits in both a normal and generalised modelling framework, and examines the estimation of between-study correlation to aid practitioners

Localization of the Drosophila Rad9 Protein to the Nuclear Membrane Is Regulated by the C-Terminal Region and Is Affected in the Meiotic Checkpoint

Rad9, Rad1, and Hus1 (9-1-1) are part of the DNA integrity checkpoint control system. It was shown previously that the C-terminal end of the human Rad9 protein, which contains a nuclear localization sequence (NLS) nearby, is critical for the nuclear transport of Rad1 and Hus1. In this study, we show that in Drosophila, Hus1 is found in the cytoplasm, Rad1 is found throughout the entire cell and that Rad9 (DmRad9) is a nuclear protein. More specifically, DmRad9 exists in two alternatively spliced forms, DmRad9A and DmRad9B, where DmRad9B is localized at the cell nucleus, and DmRad9A is found on the nuclear membrane both in Drosophila tissues and also when expressed in mammalian cells. Whereas both alternatively spliced forms of DmRad9 contain a common NLS near the C terminus, the 32 C-terminal residues of DmRad9A, specific to this alternative splice form, are required for targeting the protein to the nuclear membrane. We further show that activation of a meiotic checkpoint by a DNA repair gene defect but not defects in the anchoring of meiotic chromosomes to the oocyte nuclear envelope upon ectopic expression of non-phosphorylatable Barrier to Autointegration Factor (BAF) dramatically affects DmRad9A localization. Thus, by studying the localization pattern of DmRad9, our study reveals that the DmRad9A C-terminal region targets the protein to the nuclear membrane, where it might play a role in response to the activation of the meiotic checkpoint

Analysis of the dihydrofolate reductase-thymidylate synthase gene sequences in Plasmodium vivax field isolates that failed chloroquine treatment

<p>Abstract</p> <p>Background</p> <p>To use pyrimethamine as an alternative anti-malarial drug for chloroquine-resistant malaria parasites, it was necessary to determine the enzyme's genetic variation in dihydrofolate reductase-thymidylate syntase (DHFR-TS) among Korean strains.</p> <p>Methods</p> <p>Genetic variation of <it>dhfr-ts </it>genes of <it>Plasmodium vivax </it>clinical isolates from patients who did not respond to drug treatment (<it>n </it>= 11) in Korea were analysed. The genes were amplified using the polymerase chain reaction (PCR) with genomic DNA as a template.</p> <p>Results</p> <p>Sequence analysis showed that the open reading frame (ORF) of 1,857 nucleotides encoded a deduced protein of 618 amino acids (aa). Alignment with the DHFR-TS genes of other malaria parasites showed that a 231-residue DHFR domain and a 286-residue TS domain were seperated by a 101-aa linker region. This ORF shows 98.7% homology with the <it>P. vivax </it>Sal I strain (XM001615032) in the DHFR domain, 100% in the linker region and 99% in the TS domain. Comparison of the DHFR sequences from pyrimethamine-sensitive and pyrimethamine-resistant <it>P. vivax </it>isolates revealed that nine isolates belonged to the sensitive strain, whereas two isolates met the criteria for resistance. In these two isolates, the amino acid at position 117 is changed from serine to asparagine (S117N). Additionally, all Korean isolates showed a deletion mutant of THGGDN in short tandem repetitive sequences between 88 and 106 amino acid.</p> <p>Conclusions</p> <p>These results suggest that sequence variations in the DHFR-TS represent the prevalence of antifolate-resistant <it>P. vivax </it>in Korea. Two of 11 isolates have the Ser to Asn mutation in codon 117, which is the major determinant of pyrimethamine resistance in <it>P. vivax</it>. Therefore, the introduction of pyrimethamine for the treatment of chloroquine-resistant vivax malaria as alternative drug in Korea should be seriously considered.</p

GOPred: GO Molecular Function Prediction by Combined Classifiers

Functional protein annotation is an important matter for in vivo and in silico biology. Several computational methods have been proposed that make use of a wide range of features such as motifs, domains, homology, structure and physicochemical properties. There is no single method that performs best in all functional classification problems because information obtained using any of these features depends on the function to be assigned to the protein. In this study, we portray a novel approach that combines different methods to better represent protein function. First, we formulated the function annotation problem as a classification problem defined on 300 different Gene Ontology (GO) terms from molecular function aspect. We presented a method to form positive and negative training examples while taking into account the directed acyclic graph (DAG) structure and evidence codes of GO. We applied three different methods and their combinations. Results show that combining different methods improves prediction accuracy in most cases. The proposed method, GOPred, is available as an online computational annotation tool (http://kinaz.fen.bilkent.edu.tr/gopred)

Phosphorylation State-Dependent Interactions of Hepadnavirus Core Protein with Host Factors

Dynamic phosphorylation and dephosphorylation of the hepadnavirus core protein C-terminal domain (CTD) are required for multiple steps of the viral life cycle. It remains unknown how the CTD phosphorylation state may modulate core protein functions but phosphorylation state-dependent viral or host interactions may play a role. In an attempt to identify host factors that may interact differentially with the core protein depending on its CTD phosphorylation state, pulldown assays were performed using the CTD of the duck hepatitis B virus (DHBV) and human hepatitis B virus (HBV) core protein, either with wild type (WT) sequences or with alanine or aspartic acid substitutions at the phosphorylation sites. Two host proteins, B23 and I2PP2A, were found to interact preferentially with the alanine-substituted CTD. Furthermore, the WT CTD became competent to interact with the host proteins upon dephosphorylation. Intriguingly, the binding site on the DHBV CTD for both B23 and I2PP2A was mapped to a region upstream of the phosphorylation sites even though B23 or I2PP2A binding to this site was clearly modulated by the phosphorylation state of the downstream and non-overlapping sequences. Together, these results demonstrate a novel mode of phosphorylation-regulated protein-protein interaction and provide new insights into virus-host interactions

Two independent proteomic approaches provide a comprehensive analysis of the synovial fluid proteome response to Autologous Chondrocyte Implantation

Background: Autologous chondrocyte implantation (ACI) has a failure rate of approximately 20%, but it is yet to be fully understood why. Biomarkers are needed that can pre-operatively predict in which patients it is likely to fail, so that alternative or individualised therapies can be offered. We previously used label-free quantitation (LF) with a dynamic range compression proteomic approach to assess the synovial fluid (SF) of ACI responders and non-responders. However, we were able to identify only a few differentially abundant proteins at baseline. In the present study, we built upon these previous findings by assessing higher-abundance proteins within this SF, providing a more global proteomic analysis on the basis of which more of the biology underlying ACI success or failure can be understood. Methods: Isobaric tagging for relative and absolute quantitation (iTRAQ) proteomic analysis was used to assess SF from ACI responders (mean Lysholm improvement of 33; n = 14) and non-responders (mean Lysholm decrease of 14; n = 13) at the two stages of surgery (cartilage harvest and chondrocyte implantation). Differentially abundant proteins in iTRAQ and combined iTRAQ and LF datasets were investigated using pathway and network analyses. Results: iTRAQ proteomic analysis confirmed our previous finding that there is a marked proteomic shift in response to cartilage harvest (70 and 54 proteins demonstrating ≥ 2.0-fold change and p < 0.05 between stages I and II in responders and non-responders, respectively). Further, it highlighted 28 proteins that were differentially abundant between responders and non-responders to ACI, which were not found in the LF study, 16 of which were altered at baseline. The differential expression of two proteins (complement C1s subcomponent and matrix metalloproteinase 3) was confirmed biochemically. Combination of the iTRAQ and LF proteomic datasets generated in-depth SF proteome information that was used to generate interactome networks representing ACI success or failure. Functional pathways that are dysregulated in ACI non-responders were identified, including acute-phase response signalling. Conclusions: Several candidate biomarkers for baseline prediction of ACI outcome were identified. A holistic overview of the SF proteome in responders and non-responders to ACI  has been profiled, providing a better understanding of the biological pathways underlying clinical outcome, particularly the differential response to cartilage harvest in non-responders