56 research outputs found

    WHICH RISK FACTORS DRIVE OIL FUTURES PRICE CURVES? SPECULATION AND HEDGING IN THE SHORT AND LONG -TERM

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    Open House, ISM in Tachikawa, 2017.6.16統計数理研究所オープンハウス(立川)、H29.6.16ポスター発

    Which Risk Factors Drive Oil Futures Price Curves Speculation and Hedging in the Short and Long-Term

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    Open House, ISM in Tachikawa, 2018.6.15統計数理研究所オープンハウス(立川)、H30.6.15ポスター発

    A Multi-User Mobile GIS Solution for Documenting Large Surface Scatters: An Example from the Doring River, South Africa

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    This article discusses the development and implementation of a mobile GIS catch-and-release system for documenting large surface artifact scatters along the Doring River in South Africa. An integrated, cloud-based mobile GIS solution was built using a suite of ESRI ArcGIS applications with an aim to maximize the speed and breadth of techno-typological data capture, while minimizing data collection errors and post-processing requirements. The system was successfully implemented during the 2019 field season of the Doring River Archaeological Project. With the ability for project-specific customization and interchangeable hardware components, the system transcends geographic region and temporal focus. Moreover, the system accommodates connectivity limitations commonly faced by archaeologists seeking distributed database solutions. Other challenges embraced in the design include rotating personnel throughout a field season, scalability without large financial investment, and the ability to accommodate data collection needs of other components of the larger multi-disciplinary research project

    Alterations in dorsal and ventral posterior cingulate connectivity in APOE ε4 carriers at risk of Alzheimer's disease

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    Background Recent evidence suggests that exercise plays a role in cognition and that the posterior cingulate cortex (PCC) can be divided into dorsal and ventral subregions based on distinct connectivity patterns. Aims To examine the effect of physical activity and division of the PCC on brain functional connectivity measures in subjective memory complainers (SMC) carrying the epsilon 4 allele of apolipoprotein E (APOE 4) allele. Method Participants were 22 SMC carrying the APOE ɛ4 allele (ɛ4+; mean age 72.18 years) and 58 SMC non-carriers (ɛ4–; mean age 72.79 years). Connectivity of four dorsal and ventral seeds was examined. Relationships between PCC connectivity and physical activity measures were explored. Results ɛ4+ individuals showed increased connectivity between the dorsal PCC and dorsolateral prefrontal cortex, and the ventral PCC and supplementary motor area (SMA). Greater levels of physical activity correlated with the magnitude of ventral PCC–SMA connectivity. Conclusions The results provide the first evidence that ɛ4+ individuals at increased risk of cognitive decline show distinct alterations in dorsal and ventral PCC functional connectivity

    Novel genetic loci associated with hippocampal volume

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    The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (rg =-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness

    Genetic architecture of subcortical brain structures in 38,851 individuals

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    Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease

    The genetic architecture of the human cerebral cortex

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    The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

    Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting.

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    OBJECTIVE: To explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts. METHODS: We performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n = 20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI. RESULTS: The mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, p = 1.77 × 10-8; and LINC00539/ZDHHC20, p = 5.82 × 10-9. Both have been associated with blood pressure (BP)-related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits (p value for BI, p [BI] = 9.38 × 10-25; p [SSBI] = 5.23 × 10-14 for hypertension), smoking (p [BI] = 4.4 × 10-10; p [SSBI] = 1.2 × 10-4), diabetes (p [BI] = 1.7 × 10-8; p [SSBI] = 2.8 × 10-3), previous cardiovascular disease (p [BI] = 1.0 × 10-18; p [SSBI] = 2.3 × 10-7), stroke (p [BI] = 3.9 × 10-69; p [SSBI] = 3.2 × 10-24), and MRI-defined white matter hyperintensity burden (p [BI] = 1.43 × 10-157; p [SSBI] = 3.16 × 10-106), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p ≤ 0.0022), without indication of directional pleiotropy. CONCLUSION: In this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI
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