980 resultados para genetic correlations


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The Kallikrein-related peptidase, KLK4, has been shown to be significantly overexpressed in prostate tumours in numerous studies and is suggested to be a potential biomarker for prostate cancer. KLK4 may also play a role in prostate cancer progression through its involvement in epithelial-mesenchymal transition, a more aggressive phenotype, and metastases to bone. It is well known that genetic variation has the potential to affect gene expression and/or various protein characteristics and hence we sought to investigate the possible role of single nucleotide polymorphisms (SNPs) in the KLK4 gene in prostate cancer. Assessment of 61 SNPs in the KLK4 locus (±10 kb) in approximately 1300 prostate cancer cases and 1300 male controls for associations with prostate cancer risk and/or prostate tumour aggressiveness (Gleason score <7 versus ≥7) revealed 7 SNPs to be associated with a decreased risk of prostate cancer at the Ptrend<0.05 significance level. Three of these SNPs, rs268923, rs56112930 and the HapMap tagSNP rs7248321, are located several kb upstream of KLK4; rs1654551 encodes a non-synonymous serine to alanine substitution at position 22 of the long isoform of the KLK4 protein, and the remaining 3 risk-associated SNPs, rs1701927, rs1090649 and rs806019, are located downstream of KLK4 and are in high linkage disequilibrium with each other (r2≥0.98). Our findings provide suggestive evidence of a role for genetic variation in the KLK4 locus in prostate cancer predisposition.

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Background: Ureaplasmas are the most frequently isolated microorganisms from the amniotic fluid (AF) of pregnant women and can cause chronic infections that are difficult to eradicate with standard macrolide treatment. We tested the effects of erythromycin treatment on phenotypic and genotypic markers of ureaplasmal antimicrobial resistance in sheep. Method: At 50 days of gestation (d, term=145d) 12 pregnant ewes received intra-amniotic injections of U. parvum serovar 3 (erythromycin-sensitive, 2x104 colony-forming-units). At 100d ewes received: erythromycin treatment (500 mg, q3h for 4 days, IM, n=6) or no treatment (n=6). Fetuses were delivered surgically (125d) and AF and chorioamnion were collected for: culture, minimum inhibitory concentration (MIC) and minimum biofilm inhibitory concentration (MBIC) testing; 23S rRNA sequencing; and detection of macrolide-lincosamide-streptogramin resistance (MLSr) genes. Results: MICs of erythromycin, azithromycin and roxithromycin against AF isolates were low (range = 0.06 mg/L to 1.0 mg/L); however, chorioamnion isolates demonstrated increased resistance to roxithromycin (0.13 – 5.33 mg/L). 62.5% of chorioamnion ureaplasmas formed biofilms in vitro and mutations (125 nucleotides, 29.6%) were found in the 23S rRNA gene (domain V) of chorioamnion (but not AF) ureaplasmas. MLSr genes (ermB, msrC and msrD) were detected in 100% of chorioamnion isolates and only msrD was detected in AF isolates (40%). Conclusions: 23S rRNA mutations and MLSr genes occurred independently of erythromycin treatment, suggesting that the anatomical site of infection and microenvironment may exert selective pressures on ureaplasmas that cause genetic changes and alter antimicrobial sensitivity profiles. These results have serious implications for treatment of in utero infections.

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Introduction: Participants may respond to phases of a workplace walking program at different rates. This study evaluated the factors that contribute to the number of steps through phases of the program. The intervention was automated through a web-based program designed to increase workday walking. Methods: The study reviewed independent variable influences throughout phases I–III. A convenience sample of university workers (n=56; 43.6±1.7 years; BMI 27.44±.2.15 kg/m2; 48 female) were recruited at worksites in Australia. These workers were given a pedometer (Yamax SW 200) and access to the website program. For analyses, step counts entered by workers into the website were downloaded and mean workday steps were compared using a seemingly unrelated regression. This model was employed to capture the contemporaneous correlation within individuals in the study across observed time periods. Results: The model predicts that the 36 subjects with complete information took an average 7460 steps in the baseline two week period. After phase I, statistically significance increases in steps (from baseline) were explained by age, working status (full or part time), occupation (academic or professional), and self reported public transport (PT) use (marginally significant). Full time workers walked more than part time workers by about 440 steps, professionals walked about 300 steps more than academics, and PT users walked about 400 steps more than non-PT users. The ability to differentiate steps after two weeks among participants suggests a differential affect of the program after only two weeks. On average participants increased steps from week two to four by about 525 steps, but regular auto users had nearly 750 steps less than non-auto users at week four. The effect of age was diminished in the 4th week of observation and accounted for 34 steps per year of age. In phase III, discriminating between participants became more difficult, with only age effects differentiating their increase over baseline. The marginal effect of age by phase III compared to phase I, increased from 36 to 50, suggesting a 14 step per year increase from the 2nd to 6th week. Discussion: The findings suggest that participants responded to the program at different rates, with uniformity of effect achieved by the 6th week. Participants increased steps, however a tapering off occurred over time. Age played the most consistent role in predicting steps over the program. PT use was associated with increased step counts, while Auto use was associated with decreased step counts.

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Biological systems involving proliferation, migration and death are observed across all scales. For example, they govern cellular processes such as wound-healing, as well as the population dynamics of groups of organisms. In this paper, we provide a simplified method for correcting mean-field approximations of volume-excluding birth-death-movement processes on a regular lattice. An initially uniform distribution of agents on the lattice may give rise to spatial heterogeneity, depending on the relative rates of proliferation, migration and death. Many frameworks chosen to model these systems neglect spatial correlations, which can lead to inaccurate predictions of their behaviour. For example, the logistic model is frequently chosen, which is the mean-field approximation in this case. This mean-field description can be corrected by including a system of ordinary differential equations for pair-wise correlations between lattice site occupancies at various lattice distances. In this work we discuss difficulties with this method and provide a simplication, in the form of a partial differential equation description for the evolution of pair-wise spatial correlations over time. We test our simplified model against the more complex corrected mean-field model, finding excellent agreement. We show how our model successfully predicts system behaviour in regions where the mean-field approximation shows large discrepancies. Additionally, we investigate regions of parameter space where migration is reduced relative to proliferation, which has not been examined in detail before, and our method is successful at correcting the deviations observed in the mean-field model in these parameter regimes.

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This study used next generation sequencing technologies to investigate growth in a cultured crustacean. The objective was to identify and characterise specific gene loci that contribute important phenotypic variation to growth as well as to develop a large set of SNP markers in candidate genes for assessing correlations between specific mutations and individual growth performance. The genomic dataset generated provides a fundamental resource for application in future crustacean stock improvement programs. Ultimately, the data can be applied to development of culture lines with improved growth performance.

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Considerate amount of research has proposed optimization-based approaches employing various vibration parameters for structural damage diagnosis. The damage detection by these methods is in fact a result of updating the analytical structural model in line with the current physical model. The feasibility of these approaches has been proven. But most of the verification has been done on simple structures, such as beams or plates. In the application on a complex structure, like steel truss bridges, a traditional optimization process will cost massive computational resources and lengthy convergence. This study presents a multi-layer genetic algorithm (ML-GA) to overcome the problem. Unlike the tedious convergence process in a conventional damage optimization process, in each layer, the proposed algorithm divides the GA’s population into groups with a less number of damage candidates; then, the converged population in each group evolves as an initial population of the next layer, where the groups merge to larger groups. In a damage detection process featuring ML-GA, as parallel computation can be implemented, the optimization performance and computational efficiency can be enhanced. In order to assess the proposed algorithm, the modal strain energy correlation (MSEC) has been considered as the objective function. Several damage scenarios of a complex steel truss bridge’s finite element model have been employed to evaluate the effectiveness and performance of ML-GA, against a conventional GA. In both single- and multiple damage scenarios, the analytical and experimental study shows that the MSEC index has achieved excellent damage indication and efficiency using the proposed ML-GA, whereas the conventional GA only converges at a local solution.

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Alterations in cognitive function are characteristic of the aging process in humans and other animals. However, the nature of these age related changes in cognition is complex and is likely to be influenced by interactions between genetic predispositions and environmental factors resulting in dynamic fluctuations within and between individuals. These inter and intra-individual fluctuations are evident in both so-called normal cognitive aging and at the onset of cognitive pathology. Mild Cognitive Impairment (MCI), thought to be a prodromal phase of dementia, represents perhaps the final opportunity to mitigate cognitive declines that may lead to terminal conditions such as dementia. The prognosis for people with MCI is mixed with the evidence suggesting that many will remain stable within 10-years of diagnosis, many will improve, and many will transition to dementia. If the characteristics of people who do not progress to dementia from MCI can be identified and replicated in others it may be possible to reduce or delay dementia onset, thus reducing a growing personal and public health burden. Furthermore, if MCI onset can be prevented or delayed, the burden of cognitive decline in aging populations worldwide may be reduced. A cognitive domain that is sensitive to the effects of advancing age, and declines in which have been shown to presage the onset of dementia in MCI patients, is executive function. Moreover, environmental factors such as diet and physical activity have been shown to affect performance on tests of executive function. For example, improvements in executive function have been demonstrated as a result of increased aerobic and anaerobic physical activity and, although the evidence is not as strong, findings from dietary interventions suggest certain nutrients may preserve or improve executive functions in old age. These encouraging findings have been demonstrated in older adults with MCI and their non-impaired peers. However, there are some gaps in the literature that need to be addressed. For example, little is known about the effect on cognition of an interaction between diet and physical activity. Both are important contributors to health and wellbeing, and a growing body of evidence attests to their importance in mental and cognitive health in aging individuals. Yet physical activity and diet are rarely considered together in the context of cognitive function. There is also little known about potential underlying biological mechanisms that might explain the physical activity/diet/cognition relationship. The first aim of this program of research was to examine the individual and interactive role of physical activity and diet, specifically long chain polyunsaturated fatty acid consumption(LCn3) as predictors of MCI status. The second aim is to examine executive function in MCI in the context of the individual and interactive effects of physical activity and LCn3.. A third aim was to explore the role of immune and endocrine system biomarkers as possible mediators in the relationship between LCn3, physical activity and cognition. Study 1a was a cross-sectional analysis of MCI status as a function of erythrocyte proportions of an interaction between physical activity and LCn3. The marine based LCn3s eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) have both received support in the literature as having cognitive benefits, although comparisons of the relative benefits of EPA or DHA, particularly in relation to the aetiology of MCI, are rare. Furthermore, a limited amount of research has examined the cognitive benefits of physical activity in terms of MCI onset. No studies have examined the potential interactive benefits of physical activity and either EPA or DHA. Eighty-four male and female adults aged 65 to 87 years, 50 with MCI and 34 without, participated in Study 1a. A logistic binary regression was conducted with MCI status as a dependent variable, and the individual and interactive relationships between physical activity and either EPA or DHA as predictors. Physical activity was measured using a questionnaire and specific physical activity categories were weighted according to the metabolic equivalents (METs) of each activity to create a physical activity intensity index (PAI). A significant relationship was identified between MCI outcome and the interaction between the PAI and EPA; participants with a higher PAI and higher erythrocyte proportions of EPA were more likely to be classified as non-MCI than their less active peers with less EPA. Study 1b was a randomised control trial using the participants from Study 1a who were identified with MCI. Given the importance of executive function as a determinant of progression to more severe forms of cognitive impairment and dementia, Study 1b aimed to examine the individual and interactive effect of physical activity and supplementation with either EPA or DHA on executive function in a sample of older adults with MCI. Fifty male and female participants were randomly allocated to supplementation groups to receive 6-months of supplementation with EPA, or DHA, or linoleic acid (LA), a long chain polyunsaturated omega-6 fatty acid not known for its cognitive enhancing properties. Physical activity was measured using the PAI from Study 1a at baseline and follow-up. Executive function was measured using five tests thought to measure different executive function domains. Erythrocyte proportions of EPA and DHA were higher at follow-up; however, PAI was not significantly different. There was also a significant improvement in three of the five executive function tests at follow-up. However, regression analyses revealed that none of the variance in executive function at follow-up was predicted by EPA, DHA, PAI, the EPA by PAI interaction, or the DHA by PAI interaction. The absence of an effect may be due to a small sample resulting in limited power to find an effect, the lack of change in physical activity over time in terms of volume and/or intensity, or a combination of both reduced power and no change in physical activity. Study 2a was a cross-sectional study using cognitively unimpaired older adults to examine the individual and interactive effects of LCn3 and PAI on executive function. Several possible explanations for the absence of an effect were identified. From this consideration of alternative explanations it was hypothesised that post-onset interventions with LCn3 either alone or in interation with self-reported physical activity may not be beneficial in MCI. Thus executive function responses to the individual and interactive effects of physical activity and LCn3 were examined in a sample of older male and female adults without cognitive impairment (n = 50). A further aim of study 2a was to operationalise executive function using principal components analysis (PCA) of several executive function tests. This approach was used firstly as a data reduction technique to overcome the task impurity problem, and secondly to examine the executive function structure of the sample for evidence of de-differentiation. Two executive function components were identified as a result of the PCA (EF 1 and EF 2). However, EPA, DHA, the PAI, or the EPA by PAI or DHA by PAI interactions did not account for any variance in the executive function components in subsequent hierarchical multiple regressions. Study 2b was an exploratory correlational study designed to explore the possibility that immune and endocrine system biomarkers may act as mediators of the relationship between LCn3, PAI, the interaction between LCn3 and PAI, and executive functions. Insulin-like growth factor-1 (IGF-1), an endocrine system growth hormone, and interleukin-6 (IL-6) an immune system cytokine involved in the acute inflammatory response, have both been shown to affect cognition including executive functions. Moreover, IGF-1 and IL-6 have been shown to be antithetical in so far as chronically increased IL-6 has been associated with reduced IGF-1 levels, a relationship that has been linked to age related morbidity. Further, physical activity and LCn3 have been shown to modulate levels of both IGF-1 and IL-6. Thus, it is possible that the cognitive enhancing effects of LCn3, physical activity or their interaction are mediated by changes in the balance between IL-6 and IGF-1. Partial and non-parametric correlations were conducted in a subsample of participants from Study 2a (n = 13) to explore these relationships. Correlations of interest did not reach significance; however, the coefficients were quite large for several relationships suggesting studies with larger samples may be warranted. In summary, the current program of research found some evidence supporting an interaction between EPA, not DHA, and higher energy expenditure via physical activity in differentiating between older adults with and without MCI. However, a RCT examining executive function in older adults with MCI found no support for increasing EPA or DHA while maintaining current levels of energy expenditure. Furthermore, a cross-sectional study examining executive function in older adults without MCI found no support for better executive function performance as a function of increased EPA or DHA consumption, greater energy expenditure via physical activity or an interaction between physical activity and either EPA or DHA. Finally, an examination of endocrine and immune system biomarkers revealed promising relationships in terms of executive function in non-MCI older adults particularly with respect to LCn3 and physical activity. Taken together, these findings demonstrate a potential benefit of increasing physical activity and LCn3 consumption, particularly EPA, in mitigating the risk of developing MCI. In contrast, no support was found for a benefit to executive function as a result of increased physical activity, LCn3 consumption or an interaction between physical activity and LCn3, in participants with and without MCI. These results are discussed with reference to previous findings in the literature including possible limitations and opportunities for future research.

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In the real world there are many problems in network of networks (NoNs) that can be abstracted to a so-called minimum interconnection cut problem, which is fundamentally different from those classical minimum cut problems in graph theory. Thus, it is desirable to propose an efficient and effective algorithm for the minimum interconnection cut problem. In this paper we formulate the problem in graph theory, transform it into a multi-objective and multi-constraint combinatorial optimization problem, and propose a hybrid genetic algorithm (HGA) for the problem. The HGA is a penalty-based genetic algorithm (GA) that incorporates an effective heuristic procedure to locally optimize the individuals in the population of the GA. The HGA has been implemented and evaluated by experiments. Experimental results have shown that the HGA is effective and efficient.

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Freshwater prawn (Macrobrachium rosenbergii) culture in the Western Hemisphere is primarily, if not entirely, derived from 36 individual prawns originally introduced to Hawaii from Malaysia in 1965 and 1966. Little information is available regarding genetic variation within and among cultured prawn stocks worldwide. The goal of the current study was to characterize genetic diversity in various prawn populations with emphasis on those cultured in North America. Five microsatellite loci were screened to estimate genetic diversity in two wild (Myanmar and India-wild) and seven cultured (Hawaii-1, Hawaii-2, India-cultured, Israel, Kentucky, Mississippi and Texas) populations. Average allelic richness ranged from 3.96 (Israel) to 20.45 (Myanmar). Average expected heterozygosity ranged from 0.580 (Israel) to 0.935 (Myanmar). Many of the cultured populations exhibited reduced genetic diversity when compared with the Myanmar and the India-cultured populations. Significant deficiency in heterozygotes was detected in the India-cultured, Mississippi and Kentucky populations (overall Fis estimated of 0.053, 0.067 and 0.108 respectively) reflecting moderate levels of inbreeding. Overall estimate of fixation index (Fst = 0.1569) revealed moderately high levels of differentiation among the populations. Outcome of this study provide a baseline assessment of genetic diversity in some available strains that will be useful for the development of breeding programmes.

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Global aquaculture has expanded rapidly to address the increasing demand for aquatic protein needs and an uncertain future for wild fisheries. To date, however, most farmed aquatic stocks are essentially wild and little is known about their genomes or the genes that affect important economic traits in culture. Biologists have recognized that recent technological advances including next generation sequencing (NGS) have opened up the possibility of generating genome wide sequence data sets rapidly from non-model organisms at a reasonable cost. In an era when virtually any study organism can 'go genomic', understanding gene function and genetic effects on expressed quantitative trait locus phenotypes will be fundamental to future knowledge development. Many factors can influence the individual growth rate in target species but of particular importance in agriculture and aquaculture will be the identification and characterization of the specific gene loci that contribute important phenotypic variation to growth because the information can be applied to speed up genetic improvement programmes and to increase productivity via marker-assisted selection (MAS). While currently there is only limited genomic information available for any crustacean species, a number of putative candidate genes have been identified or implicated in growth and muscle development in some species. In an effort to stimulate increased research on the identification of growth-related genes in crustacean species, here we review the available information on: (i) associations between genes and growth reported in crustaceans, (ii) growth-related genes involved with moulting, (iii) muscle development and degradation genes involved in moulting, and; (iv) correlations between DNA sequences that have confirmed growth trait effects in farmed animal species used in terrestrial agriculture and related sequences in crustacean species. The information in concert can provide a foundation for increasing the rate at which knowledge about key genes affecting growth traits in crustacean species is gained.

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The study assessed natural levels and patterns of genetic variation in Arabian Gulf populations of a native pearl oyster to define wild population structure considering potential intrinsic and extrinsic factors that could influence any wild structure detected. The study was also the first attempt to develop microsatellite markers and to generate a genome survey sequence (GSS) dataset for the target species using next generation sequencing technology. The partial genome dataset generated has potential biotechnological applications and for pearl oyster farming in the future.

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Migraine is a common neurological disease with a genetic basis affecting approximately 12% of the population. Pain during a migraine attack is associated with activation of the trigeminal nerve system, which carries pain signals from the meninges and the blood vessels infusing the meninges to the trigeminal nucleus in the brain stem. The release of inflammatory mediators following cortical spreading depression (CSD) may further promote and sustain the activation and sensitization of meningeal nociceptors, inducing the persistent throbbing headache characterised in migraine. Lymphotoxin α (LTA) is a cytokine secreted by lymphocytes and is a member of the tumour necrosis factor (TNF) family. Genetic variation with the TNF and LTA genes may contribute to threshold brain excitability, propagation of neuronal hyperexcitability and thus initiation and maintenance of a migraine attack. Three LTA variants rs2009658, rs2844482 and rs2229094 were identified in a recent pGWAS study conducted in the Norfolk Island population as being potentially implicated in migraine with nominally significant p values of p = 0.0093, p = 0.0088 and p = 0.033 respectively. To determine whether these SNPs played a role in migraine in a general outbred population these SNPs were gentoyped in a large case control Australian Caucasian population and tested for association with migraine. All three SNPs showed no association in our cohort (p > 0.05). Validation of GWAS data in independent case-controls cohorts is essential to establish risk validity within specific population groups. The importance of cytokines in modulating neural inflammation and pain threshold in addition to other studies showing associations between TNF-α and SNPs in the LTA gene with migraine, suggests that LTA could be an important factor contributing to migraine. Although the present study did not support a role for the tested LTA variants in migraine, investigation of other variants within the LTA gene is still warranted.

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Migraine is a neurological disorder that affects the central nervous system causing painful attacks of headache. A genetic vulnerability and exposure to environmental triggers can influence the migraine phenotype. Migraine interferes in many facets of people’s daily life including employment commitments and their ability to look after their families resulting in a reduced quality of life. Identification of the biological processes that underlie this relatively common affliction has been difficult because migraine does not have any clearly identifiable pathology or structural lesion detectable by current medical technology. Theories to explain the symptoms of migraine have focused on the physiological mechanisms involved in the various phases of headache and include the vascular and neurogenic theories. In relation to migraine pathophysiology the trigeminovascular system and cortical spreading depression have also been implicated with supporting evidence from imaging studies and animal models. The objective of current research is to better understand the pathways and mechanisms involved in causing pain and headache to be able to target interventions. The genetic component of migraine has been teased apart using linkage studies and both candidate gene and genome-wide association studies, in family and case-control cohorts. Genomic regions that increase individual risk to migraine have been identified in neurological, vascular and hormonal pathways. This review discusses knowledge of the pathophysiology and genetic basis of migraine with the latest scientific evidence from genetic studies.

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Migraine is a common and debilitating neurovascular disorder with a complex envirogenomic aetiology. Numerous studies have demonstrated a preponderance of women affected with migraine and previous pedigree linkage studies in our laboratory have identified susceptibility loci on chromosome Xq24-Xq28. In this study we have used the genetic isolate of Norfolk Island to further analyse the X chromosome for migraine susceptibility loci. An association approach was employed to analyse 14,124 SNPs spanning the entire X chromosome. Genotype data from 288 individuals comprising a large core-pedigree, of which 76 were affected with migraine, were analysed. Although no SNP reached chromosome-wide significance (empirical α = 1×10−5) ranking by P-value revealed two primary clusters of SNPs in the top 25. A 10 SNP cluster represents a novel migraine susceptibility locus at Xq12 whilst a 11 SNP cluster represents a previously identified migraine susceptibility locus at Xq27. The strongest association at Xq12 was seen for rs599958 (OR = 1.75, P = 8.92×10−4), whilst at Xq27 the strongest association was for rs6525667 (OR = 1.53, P = 1.65×10−4). Further analysis of SNPs at these loci was performed in 5,122 migraineurs from the Women’s Genome Health Study and provided additional evidence for association at the novel Xq12 locus (P<0.05). Overall, this study provides evidence for a novel migraine susceptibility locus on Xq12. The strongest effect SNP (rs102834, joint P = 1.63×10−5) is located within the 5′UTR of the HEPH gene, which is involved in iron homeostasis in the brain and may represent a novel pathway for involvement in migraine pathogenesis.