Bayesian Inference of Spatial Organizations of Chromosomes

Knowledge of spatial chromosomal organizations is critical for the study of transcriptional regulation and other nuclear processes in the cell. Recently, chromosome conformation capture (3C) based technologies, such as Hi-C and TCC, have been developed to provide a genome-wide, three-dimensional (3D) view of chromatin organization. Appropriate methods for analyzing these data and fully characterizing the 3D chromosomal structure and its structural variations are still under development. Here we describe a novel Bayesian probabilistic approach, denoted as “Bayesian 3D constructor for Hi-C data” (BACH), to infer the consensus 3D chromosomal structure. In addition, we describe a variant algorithm BACH-MIX to study the structural variations of chromatin in a cell population. Applying BACH and BACH-MIX to a high resolution Hi-C dataset generated from mouse embryonic stem cells, we found that most local genomic regions exhibit homogeneous 3D chromosomal structures. We further constructed a model for the spatial arrangement of chromatin, which reveals structural properties associated with euchromatic and heterochromatic regions in the genome. We observed strong associations between structural properties and several genomic and epigenetic features of the chromosome. Using BACH-MIX, we further found that the structural variations of chromatin are correlated with these genomic and epigenetic features. Our results demonstrate that BACH and BACH-MIX have the potential to provide new insights into the chromosomal architecture of mammalian cells.Statistic

Measurement of impact of display advertisements on site traffic

Advertisers of display ads benefit from being able to measure the effectiveness of their campaigns for driving site traffic. However, some platforms do not enable such measurement due to the site metrics required to assess effectiveness of display ads being stored in a different location than bid management data pertaining to the ads. The techniques described herein measure the impact of the display ads bid management on site traffic. In particular, increased site engagement due to bid management of display ads is assessed along multiple dimensions of bid management, e.g., ad insertion order, ad creatives, target site, etc., to understand and improve the effectiveness of display ads. Data on the impact of ads enables advertisers to undertake a cost-benefit analysis of their campaigns

Direct Improvement of Hamiltonian Lattice Gauge Theory

We demonstrate that a direct approach to improving Hamiltonian lattice gauge theory is possible. Our approach is to correct errors in the Kogut-Susskind Hamiltonian by incorporating additional gauge invariant terms. The coefficients of these terms are chosen so that the order $a^2$ classical errors vanish. We conclude with a brief discussion of tadpole improvement in Hamiltonian lattice gauge theory.Comment: 9 page

Physical activity and sedentary behavior patterns using accelerometry from a national sample of United States adults

BackgroundThis study described the patterns of accelerometer-determined physical activity and sedentary behavior among adults using a nationally representative sample from the United States.MethodsUsing 2003-2006 National Health and Nutrition Examination Survey (NHANES) data, 7931 adults at least 18years old wore an ActiGraph accelerometer for one week, providing at least 3days of wear for >=8hours/day. Cutpoints defined moderate to vigorous physical activity (MVPA; >= 2020 and >=760 counts/minute), vigorous physical activity (> = 5999 counts/minute), and sedentary behavior (<100 counts/minute). Latent class analysis (LCA) was used to estimate patterns of physical activity and sedentary behavior. All estimates were weighted to reflect the United States population.ResultsFor weighted percent of MVPA out of total wearing time, 5 classes were identified from least to most active: 65.3% of population (weighted mean 9.3minutes/day), 24.9% (32.1minutes/day), 3.2% that was low on the weekdays but much higher on the weekends (52.0minutes/day), 5.9% (59.9minutes/day), and 0.7% in the highest class (113.6minutes/day). Using the lower MVPA threshold, 6 classes emerged with each class ranging in population from 1.2% to 43.6%. A vigorous activity class could not be derived due to low prevalence. For weighted percent of sedentary behavior out of total wearing time, 5 classes were identified from most to least sedentary: 6.3% of population (weighted mean 660.2minutes/day), 25.1% (546.8minutes/day), 37.7% (453.9minutes/day), 24.0% (354.8minutes/day), and 7.0% (256.3minutes/day). Four of the classes showed generally similar results across every day of the week, with the absolute percents differing across classes. In contrast, the least sedentary class showing a marked rise in percent of time spent in sedentary behavior on the weekend (weighted mean 336.7-346.5minutes/day) compared to weekdays (weighted mean 255.2-292.4minutes/day).ConclusionThe LCA models provided a data reduction process to identify patterns using minute-by-minute accelerometry data in order to explore meaningful contrasts. The models supported 5 or 6 distinct patterns for MVPA and sedentary behavior. These physical activity and sedentary behavior patterns can be used as intervention targets and as independent or dependent variables in future studies of correlates, determinants, or outcomes.Electronic supplementary materialThe online version of this article (doi:10.1186/s12966-015-0183-7) contains supplementary material, which is available to authorized users

2014-2015 Master Class - James Dunham (Viola)

https://spiral.lynn.edu/conservatory_masterclasses/1026/thumbnail.jp

An Analytic Variational Study of the Mass Spectrum in 2+1 Dimensional SU(3) Hamiltonian Lattice Gauge Theory

We calculate the masses of the lowest lying eigenstates of improved SU(2) and SU(3) lattice gauge theory in 2+1 dimensions using an analytic variational approach. The ground state is approximated by a one plaquette trial state and mass gaps are calculated in the symmetric and antisymmetric sectors by minimising over a suitable basis of rectangular states

Analysis of the Listeria monocytogenes Population Structure among Isolates from 1931 to 2015 in Australia

Listeriosis remains among the most important bacterial illnesses, with a high associated mortality rate. Efforts to control listeriosis require detailed knowledge of the epidemiology of the disease itself, and its etiological bacterium, Listeria monocytogenes. In this study we provide an in-depth analysis of the epidemiology of 224 L. monocytogenes isolates from Australian clinical and non-clinical sources. Non-human sources included meat, dairy, seafood, fruit, and vegetables, along with animal and environmental isolates. Serotyping, Multi-Locus Sequence Typing, and analysis of inlA gene sequence were performed. Serogroups IIA, IIB, and IVB comprised 94% of all isolates, with IVB over-represented among clinical isolates. Serogroup IIA was the most common among dairy and meat isolates. Lineage I isolates were most common among clinical isolates, and 52% of clinical isolates belonged to ST1. Overall 39 STs were identified in this study, with ST1 and ST3 containing the largest numbers of L. monocytogenes isolates. These STs comprised 40% of the total isolates (n = 90), and both harbored isolates from clinical and non-clinical sources. ST204 was the third most common ST. The high prevalence of this group among L. monocytogenes populations has not been reported outside Australia. Twenty-seven percent of the STs in this study contained exclusively clinical isolates. Analysis of the virulence protein InlA among isolates in this study identified a truncated form of the protein among isolates from ST121 and ST325. The ST325 group contained a previously unreported novel mutation leading to production of a 93 amino acid protein. This study provides insights in the population structure of L. monocytogenes isolated in Australia, which will contribute to public health knowledge relating to this important human pathogen