37 resultados para Terbruggen, A. J. L., Baron Van den Bogaerde Van, 1787-1855,

em Queensland University of Technology - ePrints Archive


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The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08×10 -33; 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.

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In this paper we introduce a formalization of Logical Imaging applied to IR in terms of Quantum Theory through the use of an analogy between states of a quantum system and terms in text documents. Our formalization relies upon the Schrodinger Picture, creating an analogy between the dynamics of a physical system and the kinematics of probabilities generated by Logical Imaging. By using Quantum Theory, it is possible to model more precisely contextual information in a seamless and principled fashion within the Logical Imaging process. While further work is needed to empirically validate this, the foundations for doing so are provided.

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The pattern of structural brain alterations associated with major depressive disorder (MDD) remains unresolved. This is in part due to small sample sizes of neuroimaging studies resulting in limited statistical power, disease heterogeneity and the complex interactions between clinical characteristics and brain morphology. To address this, we meta-analyzed three-dimensional brain magnetic resonance imaging data from 1728 MDD patients and 7199 controls from 15 research samples worldwide, to identify subcortical brain volumes that robustly discriminate MDD patients from healthy controls. Relative to controls, patients had significantly lower hippocampal volumes (Cohen’s d=−0.14, % difference=−1.24). This effect was driven by patients with recurrent MDD (Cohen’s d=−0.17, % difference=−1.44), and we detected no differences between first episode patients and controls. Age of onset ⩽21 was associated with a smaller hippocampus (Cohen’s d=−0.20, % difference=−1.85) and a trend toward smaller amygdala (Cohen’s d=−0.11, % difference=−1.23) and larger lateral ventricles (Cohen’s d=0.12, % difference=5.11). Symptom severity at study inclusion was not associated with any regional brain volumes. Sample characteristics such as mean age, proportion of antidepressant users and proportion of remitted patients, and methodological characteristics did not significantly moderate alterations in brain volumes in MDD. Samples with a higher proportion of antipsychotic medication users showed larger caudate volumes in MDD patients compared with controls. This currently largest worldwide effort to identify subcortical brain alterations showed robust smaller hippocampal volumes in MDD patients, moderated by age of onset and first episode versus recurrent episode status.

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The extent to which low-frequency (minor allele frequency (MAF) between 1-5%) and rare (MAF ariants contribute to complex traits and disease in the general population is mainly unknown. Bone mineral density (BMD) is highly heritable, a major predictor of osteoporotic fractures, and has been previously associated with common genetic variants, as well as rare, population-specific, coding variants. Here we identify novel non-coding genetic variants with large effects on BMD (ntotal = 53,236) and fracture (ntotal = 508,253) in individuals of European ancestry from the general population. Associations for BMD were derived from whole-genome sequencing (n = 2,882 from UK10K (ref. 10); a population-based genome sequencing consortium), whole-exome sequencing (n = 3,549), deep imputation of genotyped samples using a combined UK10K/1000 Genomes reference panel (n = 26,534), and de novo replication genotyping (n = 20,271). We identified a low-frequency non-coding variant near a novel locus, EN1, with an effect size fourfold larger than the mean of previously reported common variants for lumbar spine BMD (rs11692564(T), MAF = 1.6%, replication effect size = +0.20 s.d., Pmeta = 2 x 10(-14)), which was also associated with a decreased risk of fracture (odds ratio = 0.85; P = 2 x 10(-11); ncases = 98,742 and ncontrols = 409,511). Using an En1(cre/flox) mouse model, we observed that conditional loss of En1 results in low bone mass, probably as a consequence of high bone turnover. We also identified a novel low-frequency non-coding variant with large effects on BMD near WNT16 (rs148771817(T), MAF = 1.2%, replication effect size = +0.41 s.d., Pmeta = 1 x 10(-11)). In general, there was an excess of association signals arising from deleterious coding and conserved non-coding variants. These findings provide evidence that low-frequency non-coding variants have large effects on BMD and fracture, thereby providing rationale for whole-genome sequencing and improved imputation reference panels to study the genetic architecture of complex traits and disease in the general population.

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Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated approximately 2,000, approximately 3,700 and approximately 9,500 SNPs explained approximately 21%, approximately 24% and approximately 29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/beta-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.

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Principal Topic Although corporate entrepreneurship is of vital importance for long-term firm survival and growth (Zahra and Covin, 1995), researchers still struggle with understanding how to manage corporate entrepreneurship activities. Corporate entrepreneurship consists of three parts: innovation, venturing, and renewal processes (Guth and Ginsberg, 1990). Innovation refers to the development of new products, venturing to the creation of new businesses, and renewal to redefining existing businesses (Sharma, and Chrisman, 1999; Verbeke et al., 2007). Although there are many studies focusing on one of these aspects (cf. Burgelman, 1985; Huff et al., 1992), it is very difficult to compare the outcomes of these studies due to differences in contexts, measures, and methodologies. This is a significant lack in our understanding of CE, as firms engage in all three aspects of CE, making it important to compare managerial and organizational antecedents of innovation, venturing and renewal processes. Because factors that may enhance venturing activities may simultaneously inhibit renewal activities. The limited studies that did empirically compare the individual dimensions (cf. Zahra, 1996; Zahra et al., 2000; Yiu and Lau, 2008; Yiu et al., 2007) generally failed to provide a systematic explanation for potential different effects of organizational antecedents on innovation, venturing, and renewal. With this study we aim to investigate the different effects of structural separation and social capital on corporate entrepreneurship activities. The access to existing and the development of new knowledge has been deemed of critical importance in CE-activities (Floyd and Wooldridge, 1999; Covin and Miles, 2007; Katila and Ahuja, 2002). Developing new knowledge can be facilitated by structurally separating corporate entrepreneurial units from mainstream units (cf. Burgelman, 1983; Hill and Rothaermel, 2003; O'Reilly and Tushman, 2004). Existing knowledge and resources are available through networks of social relationships, defined as social capital (Nahapiet and Ghoshal, 1998; Yiu and Lau, 2008). Although social capital has primarily been studied at the organizational level, it might be equally important at top management level (Belliveau et al., 1996). However, little is known about the joint effects of structural separation and integrative mechanisms to provide access to social capital on corporate entrepreneurship. Could these integrative mechanisms for example connect the separated units to facilitate both knowledge creation and sharing? Do these effects differ for innovation, venturing, and renewal processes? Are the effects different for organizational versus top management team integration mechanisms? Corporate entrepreneurship activities have for example been suggested to take place at different levels. Whereas innovation is suggested to be a more bottom-up process, strategic renewal is a more top-down process (Floyd and Lane, 2000; Volberda et al., 2001). Corporate venturing is also a more bottom-up process, but due to the greater required resource commitments relative to innovation, it ventures need to be approved by top management (Burgelman, 1983). As such we will explore the following key research question in this paper: How do social capital and structural separation on organizational and TMT level differentially influence innovation, venturing, and renewal processes? Methodology/Key Propositions We investigated our hypotheses on a final sample of 240 companies in a variety of industries in the Netherlands. All our measures were validated in previous studies. We targeted a second respondent in each firm to reduce problems with single-rater data (James et al., 1984). We separated the measurement of the independent and the dependent variables in two surveys to create a one-year time lag and reduce potential common method bias (Podsakoff et al., 2003). Results and Implications Consistent with our hypotheses, our results show that configurations of structural separation and integrative mechanisms have different effects on the three aspects of corporate entrepreneurship. Innovation was affected by organizational level mechanisms, renewal by integrative mechanisms on top management team level and venturing by mechanisms on both levels. Surprisingly, our results indicated that integrative mechanisms on top management team level had negative effects on corporate entrepreneurship activities. We believe this paper makes two significant contributions. First, we provide more insight in what the effects of ambidextrous organizational forms (i.e. combinations of differentiation and integration mechanisms) are on venturing, innovation and renewal processes. Our findings show that more valuable insights can be gained by comparing the individual parts of corporate entrepreneurship instead of focusing on the whole. Second, we deliver insights in how management can create a facilitative organizational context for these corporate entrepreneurship activities.

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We performed an integrated genomic, transcriptomic and proteomic characterization of 373 endometrial carcinomas using array- and sequencing-based technologies. Uterine serous tumours and ∼25% of high-grade endometrioid tumours had extensive copy number alterations, few DNA methylation changes, low oestrogen receptor/progesterone receptor levels, and frequent TP53 mutations. Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS and novel mutations in the SWI/SNF chromatin remodelling complex gene ARID5B. A subset of endometrioid tumours that we identified had a markedly increased transversion mutation frequency and newly identified hotspot mutations in POLE. Our results classified endometrial cancers into four categories: POLE ultramutated, microsatellite instability hypermutated, copy-number low, and copy-number high. Uterine serous carcinomas share genomic features with ovarian serous and basal-like breast carcinomas. We demonstrated that the genomic features of endometrial carcinomas permit a reclassification that may affect post-surgical adjuvant treatment for women with aggressive tumours.

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Lung cancer is the most important cause of cancer-related mortality. Resectability and eligibility for treatment with adjuvant chemotherapy is determined by staging according to the TNM classification. Other determinants of tumour behaviour that predict disease outcome, such as molecular markers, may improve decision-making. Activation of the gene encoding human telomerase reverse transcriptase (hTERT) is implicated in the pathogenesis of lung cancer, and consequently detection of hTERT mRNA might have prognostic value for patients with early stage lung cancer. A cohort of patients who underwent a complete resection for early stage lung cancer was recruited as part of the European Early Lung Cancer (EUELC) project. In 166 patients expression of hTERT mRNA was determined in tumour tissue by quantitative real-time RT-PCR and related to that of a house-keeping gene (PBGD). Of a subgroup of 130 patients tumour-distant normal tissue was additionally available for hTERT mRNA analysis. The correlation between hTERT levels of surgical samples and disease-free survival was determined using a Fine and Gray hazard model. Although hTERT mRNA positivity in tumour tissue was significantly associated with clinical stage (Fisher's exact test p=0.016), neither hTERT mRNA detectability nor hTERT mRNA levels in tumour tissue were associated with clinical outcome. Conversely, hTERT positivity in adjacent normal samples was associated with progressive disease, 28% of patients with progressive disease versus 7.5% of disease-free patients had detectable hTERT mRNA in normal tissue [adjusted HR: 3.60 (1.64-7.94), p=0.0015]. hTERT mRNA level in tumour tissue has no prognostic value for patients with early stage lung cancer. However, detection of hTERT mRNA expression in tumour-distant normal lung tissue may indicate an increased risk of progressive disease.

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Dengue is the most prevalent arthropod-borne virus, with at least 40% of the world’s population at risk of infection each year. In Australia, dengue is not endemic, but viremic travelers trigger outbreaks involving hundreds of cases. We compared the susceptibility of Aedes aegypti mosquitoes from two geographically isolated populations with two strains of dengue virus serotype 2. We found, interestingly, that mosquitoes from a city with no history of dengue were more susceptible to virus than mosquitoes from an outbreak-prone region, particularly with respect to one dengue strain. These findings suggest recent evolution of population-based differences in vector competence or different historical origins. Future genomic comparisons of these populations could reveal the genetic basis of vector competence and the relative role of selection and stochastic processes in shaping their differences. Lastly, we show the novel finding of a correlation between midgut dengue titer and titer in tissues colonized after dissemination.

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Introduction Dengue is one of the most widespread mosquito-borne diseases in the world. The causative agent, dengue virus (DENV), is primarily transmitted by the mosquito Aedes aegypti, a species that has proved difficult to control using conventional methods. The discovery that A. aegypti transinfected with the wMel strain of Wolbachia showed limited DENV replication led to trial field releases of these mosquitoes in Cairns, Australia as a biocontrol strategy for the virus. Methodology/Principal Findings Field collected wMel mosquitoes that were challenged with three DENV serotypes displayed limited rates of body infection, viral replication and dissemination to the head compared to uninfected controls. Rates of dengue infection, replication and dissemination in field wMel mosquitoes were similar to those observed in the original transinfected wMel line that had been maintained in the laboratory. We found that wMel was distributed in similar body tissues in field mosquitoes as in laboratory ones, but, at seven days following blood-feeding, wMel densities increased to a greater extent in field mosquitoes. Conclusions/Significance Our results indicate that virus-blocking is likely to persist in Wolbachia-infected mosquitoes after their release and establishment in wild populations, suggesting that Wolbachia biocontrol may be a successful strategy for reducing dengue transmission in the field.

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Oncogene-induced senescence (OIS) is a potent tumor-suppressive mechanism that is thought to come at the cost of aging. The Forkhead box O (FOXO) transcription factors are regulators of life span and tumor suppression. However, whether and how FOXOs function in OIS have been unclear. Here, we show a role for FOXO4 in mediating senescence by the human BRAFV600E oncogene, which arises commonly in melanoma. BRAFV600E signaling through mitogen-activated protein kinase/extracellular signal-regulated kinase kinase resulted in increased reactive oxygen species levels and c-Jun NH 2 terminal kinase-mediated activation of FOXO4 via its phosphorylation on Thr223, Ser226, Thr447, and Thr451. BRAFV600E-induced FOXO4 phosphorylation resulted in p21cip1-mediated cell senescence independent of p16 ink4a or p27kip1. Importantly, melanocyte-specific activation of BRAFV600E in vivo resulted in the formation of skin nevi expressing Thr223/Ser226-phosphorylated FOXO4 and elevated p21cip1. Together, these findings support a model in which FOXOs mediate a trade-off between cancer and aging.

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Meta-analyses estimate a statistical effect size for a test or an analysis by combining results from multiple studies without necessarily having access to each individual study's raw data. Multi-site meta-analysis is crucial for imaging genetics, as single sites rarely have a sample size large enough to pick up effects of single genetic variants associated with brain measures. However, if raw data can be shared, combining data in a "mega-analysis" is thought to improve power and precision in estimating global effects. As part of an ENIGMA-DTI investigation, we use fractional anisotropy (FA) maps from 5 studies (total N=2, 203 subjects, aged 9-85) to estimate heritability. We combine the studies through meta-and mega-analyses as well as a mixture of the two - combining some cohorts with mega-analysis and meta-analyzing the results with those of the remaining sites. A combination of mega-and meta-approaches may boost power compared to meta-analysis alone.

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Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.

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Identifying genetic variants influencing human brain structures may reveal new biological mechanisms underlying cognition and neuropsychiatric illness. The volume of the hippocampus is a biomarker of incipient Alzheimer's disease and is reduced in schizophrenia, major depression and mesial temporal lobe epilepsy. Whereas many brain imaging phenotypes are highly heritable, identifying and replicating genetic influences has been difficult, as small effects and the high costs of magnetic resonance imaging (MRI) have led to underpowered studies. Here we report genome-wide association meta-analyses and replication for mean bilateral hippocampal, total brain and intracranial volumes from a large multinational consortium. The intergenic variant rs7294919 was associated with hippocampal volume (12q24.22; N = 21,151; P = 6.70 × 10 -16) and the expression levels of the positional candidate gene TESC in brain tissue. Additionally, rs10784502, located within HMGA2, was associated with intracranial volume (12q14.3; N = 15,782; P = 1.12 × 10 -12). We also identified a suggestive association with total brain volume at rs10494373 within DDR2 (1q23.3; N = 6,500; P = 5.81 × 10 -7).