894 research outputs found
Tissue-specific network-based genome wide study of amygdala imaging phenotypes to identify functional interaction modules
Get PDFMotivation:
Network-based genome-wide association studies (GWAS) aim to identify functional modules from biological networks that are enriched by top GWAS findings. Although gene functions are relevant to tissue context, most existing methods analyze tissue-free networks without reflecting phenotypic specificity.
Results:
We propose a novel module identification framework for imaging genetic studies using the tissue-specific functional interaction network. Our method includes three steps: (i) re-prioritize imaging GWAS findings by applying machine learning methods to incorporate network topological information and enhance the connectivity among top genes; (ii) detect densely connected modules based on interactions among top re-prioritized genes; and (iii) identify phenotype-relevant modules enriched by top GWAS findings. We demonstrate our method on the GWAS of [18F]FDG-PET measures in the amygdala region using the imaging genetic data from the Alzheimer's Disease Neuroimaging Initiative, and map the GWAS results onto the amygdala-specific functional interaction network. The proposed network-based GWAS method can effectively detect densely connected modules enriched by top GWAS findings. Tissue-specific functional network can provide precise context to help explore the collective effects of genes with biologically meaningful interactions specific to the studied phenotype
Literature review on enhancing integration of disaster risk and climate change adaptation in Irish emergency planning
Get PDFThe scope of the present literature review is under the remit of a wider project entitled Enhancing Integration of Disaster Risk and Climate Change Adaptation into Irish Emergency Planning which is funded under the Environmental Protection Agency's Climate Topic 3 funding call. The project, which began in March 2020, is due to run until March 2021. The objective of the project is to help institutions responsible to further 'climate-proof' emergency planning and risk management systems in Ireland to the increasing risk of extreme hydrometeorological events, by addressing national policy and decision-making processes, as well as local and regional planning and response mechanisms
The Effect of Neighborhood Watch Programs on Neighborhood Crime in Medford Oregon
Get PDF27 pagesOver the past decade Medford Oregon expanded their Neighborhood Watch
program and increased the number of neighborhood watch groups they have
in each section of the city. Using robust panel regression analysis we studied
what effect this program had on crime rates of the treated areas. Our data
included total number of crimes across 7 years from 2007 to 2013 and across
the 7 areas, or beats, recognized by the Medford Police Department, each of
which had a varying number of active neighborhood watches over our sample
period. Our goal was to use the number of neighborhood watch groups per
beat and several other proxy variables to try and estimate how much, if at all,
this program is affecting crime rate in Medford. We found that one additional
neighborhood watch decreases the crime rate per beat by about 3%, and
one additional neighborhood watch per square kilometer decreases the crime
rate by about 18%, though there is also evidence of diminishing effects as the
number of watches increases in a given area
Time-dependent density functional theory/discrete reaction field spectra of open shell systems:The visual spectrum of [Fe-III(PyPepS)(2)](-) in aqueous solution
Get PDFWe report the calculated visible spectrum of [Fe-III(PyPepS)(2)](-) in aqueous solution. From all-classical molecular dynamics simulations on the solute and 200 water molecules with a polarizable force field, 25 solute/solvent configurations were chosen at random from a 50 ps production run and subjected the systems to calculations using time-dependent density functional theory (TD-DFT) for the solute, combined with a solvation model in which the water molecules carry charges and polarizabilities. In each calculation the first 60 excited states were collected in order to span the experimental spectrum. Since the solute has a doublet ground state several excitations to states are of type "three electrons in three orbitals," each of which gives rise to a manifold of a quartet and two doublet states which cannot properly be represented by single Slater determinants. We applied a tentative scheme to analyze this type of spin contamination in terms of Delta and Delta transitions between the same orbital pairs. Assuming the associated states as pure single determinants obtained from restricted calculations, we construct conformation state functions (CFSs), i.e., eigenfunctions of the Hamiltonian (S) over cap (z) and (S) over cap (2), for the two doublets and the quartet for each Delta,Delta pair, the necessary parameters coming from regular and spin-flip calculations. It appears that the lower final states remain where they were originally calculated, while the higher states move up by some tenths of an eV. In this case filtering out these higher states gives a spectrum that compares very well with experiment, but nevertheless we suggest investigating a possible (re)formulation of TD-DFT in terms of CFSs rather than determinants
Analytical Validation and Capabilities of the Epic CTC Platform: Enrichment-Free Circulating Tumour Cell Detection and Characterization
Get PDFThe Epic Platform was developed for the unbiased detection and molecular characterization of circulating tumour cells (CTCs). Here, we report assay performance data, including accuracy, linearity, specificity and intra/inter-assay precision of CTC enumeration in healthy donor (HD) blood samples spiked with varying concentrations of cancer cell line controls (CLCs). Additionally, we demonstrate clinical feasibility for CTC detection in a small cohort of metastatic castrate-resistant prostate cancer (mCRPC) patients. The Epic Platform demonstrated accuracy, linearity and sensitivity for the enumeration of all CLC concentrations tested. Furthermore, we established the precision between multiple operators and slide staining batches and assay specificity showing zero CTCs detected in 18 healthy donor samples. In a clinical feasibility study, at least one traditional CTC/mL (CK+, CD45-, and intact nuclei) was detected in 89 % of 44 mCRPC samples, whereas 100 % of samples had CTCs enumerated if additional CTC subpopulations (CK-/CD45- and CK+ apoptotic CTCs) were included in the analysis. In addition to presenting Epic Platform’s performance with respect to CTC enumeration, we provide examples of its integrated downstream capabilities, including protein biomarker expression and downstream genomic analyses at single cell resolution
Network-Based Analysis of Genetic Variants Associated with Hippocampal Volume in Alzheimer’S Disease: A Study of Adni Cohorts
Get PDFBackground: Alzheimer’s disease (AD) is a neurodegenerative disease that causes dementia. While molecular basis of AD is not fully understood, genetic factors are expected to participate in the development and progression of the disease. Our goal was to uncover novel genetic underpinnings of Alzheimer’s disease with a bioinformatics approach that accounts for tissue specificity. Findings: We performed genome-wide association studies (GWAS) for hippocampal volume in two Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohorts. We used these GWAS in a subsequent tissue-specific network-wide association study (NetWAS), which applied nominally significant associations in the initial GWAS to identify disease relevant patterns in a functional network for the hippocampus. We compared prioritized gene lists from NetWAS and GWAS with literature curated AD-associated genes from the Online Mendelian Inheritance in Man (OMIM) database. In the ADNI-1 GWAS, where we also observed an enrichment of low p-values, NetWAS prioritized disease-gene associations in accordance with OMIM annotations. This was not observed in the ADNI-2 dataset. We provide source code to replicate these analyses as well as complete results under permissive licenses. Conclusions: We performed the first analysis of hippocampal volume using NetWAS, which uses machine learning algorithms applied to tissue-specific functional interaction network to prioritize GWAS results. Our findings support the idea that tissue-specific networks may provide helpful context for understanding the etiology of common human diseases and reveal challenges that network-based approaches encounter in some datasets. Our source code and intermediate results files can facilitate the development of methods to address these challenges
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