493 resultados para Preimplantation genetic screening
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Background Screening tests of basic cognitive status or ‘mental state’ have been shown to predict mortality and functional outcomes in adults. This study examined the relationship between mental state and outcomes in children with type 1 diabetes. Objective We aimed to determine whether mental state at diagnosis predicts longer term cognitive function of children with a new diagnosis of type 1 diabetes. Methods Mental state of 87 patients presenting with newly diagnosed type 1 diabetes was assessed using the School-Years Screening Test for the Evaluation of Mental Status. Cognitive abilities were assessed 1 wk and 6 months postdiagnosis using standardized tests of attention, memory, and intelligence. Results Thirty-seven children (42.5%) had reduced mental state at diagnosis. Children with impaired mental state had poorer attention and memory in the week following diagnosis, and, after controlling for possible confounding factors, significantly lower IQ at 6 months compared to those with unimpaired mental state (p < 0.05). Conclusions Cognition is impaired acutely in a significant number of children presenting with newly diagnosed type 1 diabetes. Mental state screening is an effective method of identifying children at risk of ongoing cognitive difficulties in the days and months following diagnosis. Clinicians may consider mental state screening for all newly diagnosed diabetic children to identify those at risk of cognitive sequelae.
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Topographically and chemically modified titanium implants are recognized to have improved osteogenic properties; however, the molecular regulation of this process remains unknown. This study aimed to determine the microRNA profile and the potential regulation of osteogenic differentiation following early exposure of osteoprogenitor cells to sand-blasted, large-grit acid-etched (SLA) and hydrophilic SLA (modSLA) surfaces. Firstly, the osteogenic characteristics of the primary osteoprogenitor cells were confirmed using ALP activity and Alizarin Red S staining. The effect of smooth (SMO), SLA and modSLA surfaces on the TGF-β/BMP (BMP2, BMP6, ACVR1) and non-canonical WNT/Ca2+ (WNT5A, FZD6) pathways, as well as the integrins ITGB1 and ITGA2, was determined. It was revealed that the modified titanium surfaces could induce the activation of TGF-β/BMP and non-canonical WNT/Ca2+ signaling genes. The expression pattern of microRNAs (miRNAs) related to cell differentiation was evaluated. Statistical analysis of the differentially regulated miRNAs indicated that 35 and 32 miRNAs were down-regulated on the modSLA and SLA surfaces respectively, when compared with the smooth surface (SMO). Thirty-one miRNAs that were down-regulated were common to both modSLA and SLA. There were 10 miRNAs up-regulated on modSLA and nine on SLA surfaces, amongst which eight were the same as observed on modSLA. TargetScan predictions for the down-regulated miRNAs revealed genes of the TGF-β/BMP and non-canonical Ca2+ pathways as targets. This study demonstrated that modified titanium implant surfaces induce differential regulation of miRNAs, which potentially regulate the TGF-β/BMP and WNT/Ca2+ pathways during osteogenic differentiation on modified titanium implant surfaces.
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The redclaw crayfish Cherax quadricarinatus (von Martens) accounts for the entire commercial production of freshwater crayfish in Australia. Two forms have been recognized, an 'Eastern' form in northern Queensland and a 'Western' form in the Northern Territory and far northern Western Australia. To date, only the Eastern form has been exported overseas for culture (including to China). The genetic structure of three Chinese redclaw crayfish culture lines from three different geographical locations in China (Xiamen in Fujian Province, Guangzhou in Guangdong Province and Chongming in Shanghai) were investigated for their levels and patterns of genetic diversity using microsatellite markers. Twenty-eight SSR markers were isolated and used to analyse genetic diversity levels in three redclaw crayfish culture lines in China. This study set out to improve the current understanding of the molecular genetic characteristics of imported strains of redclaw crayfish reared in China. Microsatellite analysis revealed moderate allelic and high gene diversity in all three culture lines. Polymorphism information content estimates for polymorphic loci varied between 0.1168 and 0.8040, while pairwise F ST values among culture lines were moderate (0.0020-0.1244). The highest estimate of divergence was evident between the Xiamen and Guangzhou populations.
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An array of substrates link the tryptic serine protease, kallikrein-related peptidase 14 (KLK14), to physiological functions including desquamation and activation of signaling molecules associated with inflammation and cancer. Recognition of protease cleavage sequences is driven by complementarity between exposed substrate motifs and the physicochemical signature of an enzyme's active site cleft. However, conventional substrate screening methods have generated conflicting subsite profiles for KLK14. This study utilizes a recently developed screening technique, the sparse matrix library, to identify five novel high-efficiency sequences for KLK14. The optimal sequence, YASR, was cleaved with higher efficiency (k(cat)/K(m)=3.81 ± 0.4 × 10(6) M(-1) s(-1)) than favored substrates from positional scanning and phage display by 2- and 10-fold, respectively. Binding site cooperativity was prominent among preferred sequences, which enabled optimal interaction at all subsites as indicated by predictive modeling of KLK14/substrate complexes. These simulations constitute the first molecular dynamics analysis of KLK14 and offer a structural rationale for the divergent subsite preferences evident between KLK14 and closely related KLKs, KLK4 and KLK5. Collectively, these findings highlight the importance of binding site cooperativity in protease substrate recognition, which has implications for discovery of optimal substrates and engineering highly effective protease inhibitors.
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Recently, Software as a Service (SaaS) in Cloud computing, has become more and more significant among software users and providers. To offer a SaaS with flexible functions at a low cost, SaaS providers have focused on the decomposition of the SaaS functionalities, or known as composite SaaS. This approach has introduced new challenges in SaaS resource management in data centres. One of the challenges is managing the resources allocated to the composite SaaS. Due to the dynamic environment of a Cloud data centre, resources that have been initially allocated to SaaS components may be overloaded or wasted. As such, reconfiguration for the components’ placement is triggered to maintain the performance of the composite SaaS. However, existing approaches often ignore the communication or dependencies between SaaS components in their implementation. In a composite SaaS, it is important to include these elements, as they will directly affect the performance of the SaaS. This paper will propose a Grouping Genetic Algorithm (GGA) for multiple composite SaaS application component clustering in Cloud computing that will address this gap. To the best of our knowledge, this is the first attempt to handle multiple composite SaaS reconfiguration placement in a dynamic Cloud environment. The experimental results demonstrate the feasibility and the scalability of the GGA.
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This thesis is an ethical and empirical exploration of the late discovery of genetic origins in two contexts, adoption and sperm donor-assisted conception. This exploration has two interlinked strands of concern. The first is the identification of ‘late discovery’ as a significant issue of concern, deserving of recognition and acknowledgment. The second concerns the ethical implications of late discovery experiences for the welfare of the child. The apparently simple act of recognition of a phenomenon is a precondition to any analysis and critique of it. This is especially important when the phenomenon arises out of social practices that arouse significant debate in ethical and legal contexts. As the new reproductive technologies and some adoption practices remain highly contested, an ethical exploration of this long neglected experience has the potential to offer new insights and perspectives in a range of contexts. It provides an opportunity to revisit developmental debate on the relative merit or otherwise of biological versus social influences, from the perspective of those who have lived this dichotomy in practise. Their experiences are the human face of the effects arising from decisions taken by others to intentionally separate their biological and social worlds, an action which has then been compounded by family and institutional secrecy from birth. This has been accompanied by a failure to ensure that normative standards and values are upheld for them. Following discovery, these factors can be exacerbated by a lack of recognition and acknowledgement of their concerns by family, friends, community and institutions. Late discovery experiences offer valuable insights to inform discussions on the ethical meanings of child welfare, best interests, parental responsibility, duty of care and child identity rights in this and other contexts. They can strengthen understandings of what factors are necessary for a child to be able to live a reasonably happy or worthwhile life.
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A composite SaaS (Software as a Service) is a software that is comprised of several software components and data components. The composite SaaS placement problem is to determine where each of the components should be deployed in a cloud computing environment such that the performance of the composite SaaS is optimal. From the computational point of view, the composite SaaS placement problem is a large-scale combinatorial optimization problem. Thus, an Iterative Cooperative Co-evolutionary Genetic Algorithm (ICCGA) was proposed. The ICCGA can find reasonable quality of solutions. However, its computation time is noticeably slow. Aiming at improving the computation time, we propose an unsynchronized Parallel Cooperative Co-evolutionary Genetic Algorithm (PCCGA) in this paper. Experimental results have shown that the PCCGA not only has quicker computation time, but also generates better quality of solutions than the ICCGA.
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Background: Kallikrein 15 (KLK15)/Prostinogen is a plausible candidate for prostate cancer susceptibility. Elevated KLK15 expression has been reported in prostate cancer and it has been described as an unfavorable prognostic marker for the disease. Objectives: We performed a comprehensive analysis of association of variants in the KLK15 gene with prostate cancer risk and aggressiveness by genotyping tagSNPs, as well as putative functional SNPs identified by extensive bioinformatics analysis. Methods and Data Sources: Twelve out of 22 SNPs, selected on the basis of linkage disequilibrium pattern, were analyzed in an Australian sample of 1,011 histologically verified prostate cancer cases and 1,405 ethnically matched controls. Replication was sought from two existing genome wide association studies (GWAS): the Cancer Genetic Markers of Susceptibility (CGEMS) project and a UK GWAS study. Results: Two KLK15 SNPs, rs2659053 and rs3745522, showed evidence of association (p, 0.05) but were not present on the GWAS platforms. KLK15 SNP rs2659056 was found to be associated with prostate cancer aggressiveness and showed evidence of association in a replication cohort of 5,051 patients from the UK, Australia, and the CGEMS dataset of US samples. A highly significant association with Gleason score was observed when the data was combined from these three studies with an Odds Ratio (OR) of 0.85 (95% CI = 0.77-0.93; p = 2.7610 24). The rs2659056 SNP is predicted to alter binding of the RORalpha transcription factor, which has a role in the control of cell growth and differentiation and has been suggested to control the metastatic behavior of prostate cancer cells. Conclusions: Our findings suggest a role for KLK15 genetic variation in the etiology of prostate cancer among men of European ancestry, although further studies in very large sample sets are necessary to confirm effect sizes.
Novel molecular markers of Chlamydia pecorum genetic diversity in the koala (Phascolarctos cinereus)
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Background Chlamydia pecorum is an obligate intracellular bacterium and the causative agent of reproductive and ocular disease in several animal hosts including koalas, sheep, cattle and goats. C. pecorum strains detected in koalas are genetically diverse, raising interesting questions about the origin and transmission of this species within koala hosts. While the ompA gene remains the most widely-used target in C. pecorum typing studies, it is generally recognised that surface protein encoding genes are not suited for phylogenetic analysis and it is becoming increasingly apparent that the ompA gene locus is not congruent with the phylogeny of the C. pecorum genome. Using the recently sequenced C. pecorum genome sequence (E58), we analysed 10 genes, including ompA, to evaluate the use of ompA as a molecular marker in the study of koala C. pecorum genetic diversity. Results Three genes (incA, ORF663, tarP) were found to contain sufficient nucleotide diversity and discriminatory power for detailed analysis and were used, with ompA, to genotype 24 C. pecorum PCR-positive koala samples from four populations. The most robust representation of the phylogeny of these samples was achieved through concatenation of all four gene sequences, enabling the recreation of a "true" phylogenetic signal. OmpA and incA were of limited value as fine-detailed genetic markers as they were unable to confer accurate phylogenetic distinctions between samples. On the other hand, the tarP and ORF663 genes were identified as useful "neutral" and "contingency" markers respectively, to represent the broad evolutionary history and intra-species genetic diversity of koala C. pecorum. Furthermore, the concatenation of ompA, incA and ORF663 sequences highlighted the monophyletic nature of koala C. pecorum infections by demonstrating a single evolutionary trajectory for koala hosts that is distinct from that seen in non-koala hosts. Conclusions While the continued use of ompA as a fine-detailed molecular marker for epidemiological analysis appears justified, the tarP and ORF663 genes also appear to be valuable markers of phylogenetic or biogeographic divisions at the C. pecorum intra-species level. This research has significant implications for future typing studies to understand the phylogeny, genetic diversity, and epidemiology of C. pecorum infections in the koala and other animal species.
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We examined the structure and extent of genetic diversity in intrahost populations of Ross River virus (RRV) in samples from six human patients, focusing on the nonstructural (nsP3) and structural (E2) protein genes. Strikingly, although the samples were collected from contrasting ecological settings 3,000 kilometers apart in Australia, we observed multiple viral lineages in four of the six individuals, which is indicative of widespread mixed infections. In addition, a comparison with previously published RRV sequences revealed that these distinct lineages have been in circulation for at least 5 years, and we were able to document their long-term persistence over extensive geographical distances
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Objective Although several validated nutritional screening tools have been developed to “triage” inpatients for malnutrition diagnosis and intervention, there continues to be debate in the literature as to which tool/tools clinicians should use in practice. This study compared the accuracy of seven validated screening tools in older medical inpatients against two validated nutritional assessment methods. Methods This was a prospective cohort study of medical inpatients at least 65 y old. Malnutrition screening was conducted using seven tools recommended in evidence-based guidelines. Nutritional status was assessed by an accredited practicing dietitian using the Subjective Global Assessment (SGA) and the Mini-Nutritional Assessment (MNA). Energy intake was observed on a single day during first week of hospitalization. Results In this sample of 134 participants (80 ± 8 y old, 50% women), there was fair agreement between the SGA and MNA (κ = 0.53), with MNA identifying more “at-risk” patients and the SGA better identifying existing malnutrition. Most tools were accurate in identifying patients with malnutrition as determined by the SGA, in particular the Malnutrition Screening Tool and the Nutritional Risk Screening 2002. The MNA Short Form was most accurate at identifying nutritional risk according to the MNA. No tool accurately predicted patients with inadequate energy intake in the hospital. Conclusion Because all tools generally performed well, clinicians should consider choosing a screening tool that best aligns with their chosen nutritional assessment and is easiest to implement in practice. This study confirmed the importance of rescreening and monitoring food intake to allow the early identification and prevention of nutritional decline in patients with a poor intake during hospitalization.
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The study presents a multi-layer genetic algorithm (GA) approach using correlation-based methods to facilitate damage determination for through-truss bridge structures. To begin, the structure’s damage-suspicious elements are divided into several groups. In the first GA layer, the damage is initially optimised for all groups using correlation objective function. In the second layer, the groups are combined to larger groups and the optimisation starts over at the normalised point of the first layer result. Then the identification process repeats until reaching the final layer where one group includes all structural elements and only minor optimisations are required to fine tune the final result. Several damage scenarios on a complicated through-truss bridge example are nominated to address the proposed approach’s effectiveness. Structural modal strain energy has been employed as the variable vector in the correlation function for damage determination. Simulations and comparison with the traditional single-layer optimisation shows that the proposed approach is efficient and feasible for complicated truss bridge structures when the measurement noise is taken into account.
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Optimising the container transfer schedule at the multimodal terminals is known to be NP-hard, which implies that the best solution becomes computationally infeasible as problem sizes increase. Genetic Algorithm (GA) techniques are used to reduce container handling/transfer times and ships' time at the port by speeding up handling operations. The GA is chosen due to the relatively good results that have been reported even with the simplest GA implementations to obtain near-optimal solutions in reasonable time. Also discussed, is the application of the model to assess the consequences of increased scheduled throughput time as well as different strategies such as the alternative plant layouts, storage policies and number of yard machines. A real data set used for the solution and subsequent sensitivity analysis is applied to the alternative plant layouts, storage policies and number of yard machines.
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The Texas Department of Transportation (TxDOT) is concerned about the widening gap between pavement preservation needs and available funding. Thus, the TxDOT Austin District Pavement Engineer (DPE) has investigated methods to strategically allocate available pavement funding to potential projects that improve the overall performance of the District and Texas highway systems. The primary objective of the study presented in this paper is to develop a network-level project screening and ranking method that supports the Austin District 4-year pavement management plan development. The study developed candidate project selection and ranking algorithms that evaluated pavement conditions of each project candidate using data contained in the Pavement Management Information system (PMIS) database and incorporated insights from Austin District pavement experts; and implemented the developed method and supporting algorithm. This process previously required weeks to complete, but now requires about 10 minutes including data preparation and running the analysis algorithm, which enables the Austin DPE to devote more time and resources to conducting field visits, performing project-level evaluation and testing candidate projects. The case study results showed that the proposed method assisted the DPE in evaluating and prioritizing projects and allocating funds to the right projects at the right time.