Cosmic cookery : making a stereoscopic 3D animated movie.

This paper describes our experience making a short stereoscopic movie visualizing the development of structure in the universe during the 13.7 billion years from the Big Bang to the present day. Aimed at a general audience for the Royal Society's 2005 Summer Science Exhibition, the movie illustrates how the latest cosmological theories based on dark matter and dark energy are capable of producing structures as complex as spiral galaxies and allows the viewer to directly compare observations from the real universe with theoretical results. 3D is an inherent feature of the cosmology data sets and stereoscopic visualization provides a natural way to present the images to the viewer, in addition to allowing researchers to visualize these vast, complex data sets. The presentation of the movie used passive, linearly polarized projection onto a 2m wide screen but it was also required to playback on a Sharp RD3D display and in anaglyph projection at venues without dedicated stereoscopic display equipment. Additionally lenticular prints were made from key images in the movie. We discuss the following technical challenges during the stereoscopic production process; 1) Controlling the depth presentation, 2) Editing the stereoscopic sequences, 3) Generating compressed movies in display speci¯c formats. We conclude that the generation of high quality stereoscopic movie content using desktop tools and equipment is feasible. This does require careful quality control and manual intervention but we believe these overheads are worthwhile when presenting inherently 3D data as the result is signi¯cantly increased impact and better understanding of complex 3D scenes

The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke

The goal of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well‐powered meta‐ and mega‐analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large‐scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided

A Monte Carlo Approach to Evolution of the Far-Infrared Luminosity Function with BLAST

We constrain the evolution of the rest-frame far-infrared (FIR) luminosity function out to high redshift, by combining several pieces of complementary information provided by the deep Balloon-borne Large-Aperture Submillimeter Telescope surveys at 250, 350 and 500 micron, as well as other FIR and millimetre data. Unlike most other phenomenological models, we characterise the uncertainties in our fitted parameters using Monte Carlo Markov Chains. We use a bivariate local luminosity function that depends only on FIR luminosity and 60-to-100 micron colour, along with a single library of galaxy spectral energy distributions indexed by colour, and apply simple luminosity and density evolution. We use the surface density of sources, Cosmic Infrared Background (CIB) measurements and redshift distributions of bright sources, for which identifications have been made, to constrain this model. The precise evolution of the FIR luminosity function across this crucial range has eluded studies at longer wavelengths (e.g., using SCUBA and MAMBO) and at shorter wavelengths (e.g., Spitzer), and should provide a key piece of information required for the study of galaxy evolution. Our adoption of Monte Carlo methods enables us not only to find the best-fit evolution model, but also to explore correlations between the fitted parameters. Our model-fitting approach allows us to focus on sources of tension coming from the combination of data-sets. We specifically find that our choice of parameterisation has difficulty fitting the combination of CIB measurements and redshift distribution of sources near 1 mm. Existing and future data sets will be able to dramatically improve the fits, as well as break strong degeneracies among the models. [abridged]Comment: 20 pages, 14 figures, accepted to MNRA

A Physical Model for z~2 Dust Obscured Galaxies

We present a physical model for the origin of z~2 Dust-Obscured Galaxies (DOGs), a class of high-redshift ULIRGs selected at 24 micron which are particularly optically faint (24/R>1000). By combining N-body/SPH simulations of high redshift galaxy evolution with 3D polychromatic dust radiative transfer models, we find that luminous DOGs (with F24 > 0.3 mJy at z~2 are well-modeled as extreme gas-rich mergers in massive (~5x10^12-10^13 Msun) halos, with elevated star formation rates (~500-1000 Msun/yr) and/or significant AGN growth (Mdot > 0.5 Msun/yr), whereas less luminous DOGs are more diverse in nature. At final coalescence, merger-driven DOGs transition from being starburst dominated to AGN dominated, evolving from a "bump" to a power-law shaped mid-IR (IRAC) spectral energy distribution (SED). After the DOG phase, the galaxy settles back to exhibiting a "bump" SED with bluer colors and lower star formation rates. While canonically power-law galaxies are associated with being AGN-dominated, we find that the power-law mid-IR SED can owe both to direct AGN contribution, as well as to a heavily dust obscured stellar bump at times that the galaxy is starburst dominated. Thus power-law galaxies can be either starburst or AGN dominated. Less luminous DOGs can be well-represented either by mergers, or by massive ($M_{\rm baryon} ~5x10^11 Msun) secularly evolving gas-rich disc galaxies (with SFR > 50 Msun/yr). By utilising similar models as those employed in the SMG formation study of Narayanan et al. (2010), we investigate the connection between DOGs and SMGs. We find that the most heavily star-forming merger driven DOGs can be selected as Submillimetre Galaxies (SMGs), while both merger-driven and secularly evolving DOGs typically satisfy the BzK selection criteria.Comment: Accepted by MNRAS; major changes include better description of dependency on ISM specification and updated models allowing dust to evolve with metallicity

The physical scale of the far-infrared emission in the most luminous submillimetre galaxies II: evidence for merger-driven star formation

We present high-resolution 345 GHz interferometric observations of two extreme luminous (L_{IR}>10^{13} L_sun), submillimetre-selected galaxies (SMGs) in the COSMOS field with the Submillimeter Array (SMA). Both targets were previously detected as unresolved point-sources by the SMA in its compact configuration, also at 345 GHz. These new data, which provide a factor of ~3 improvement in resolution, allow us to measure the physical scale of the far-infrared in the submillimetre directly. The visibility functions of both targets show significant evidence for structure on 0.5-1 arcsec scales, which at z=1.5 translates into a physical scale of 5-8 kpc. Our results are consistent with the angular and physical scales of two comparably luminous objects with high-resolution SMA followup, as well as radio continuum and CO sizes. These relatively compact sizes (<5-10 kpc) argue strongly for merger-driven starbursts, rather than extended gas-rich disks, as the preferred channel for forming SMGs. For the most luminous objects, the derived sizes may also have important physical consequences; under a series of simplifying assumptions, we find that these two objects in particular are forming stars close to or at the Eddington limit for a starburst.Comment: 9 pages, 3 Figures, submitted to MNRA

The First Measurements of Galaxy Clustering from IRAC Data of the Spitzer First Look Survey

We present the first results of the angular auto-correlation function of the galaxies detected by the Infrared Array Camera (IRAC) instrument in the First Look Survey (FLS) of the Spitzer Space Telescope. We detect significant signals of galaxy clustering within the survey area. The angular auto-correlation function of the galaxies detected in each of the four IRAC instrument channels is consistent with a power-law form $w(\theta)=A\theta^{1-\gamma}$ out to \theta = 0.2\arcdeg, with the slope ranging from $\gamma = 1.5$ to 1.8. We estimate the correlation amplitudes $A$ to be $2.95 \times 10^{-3}$, $2.03 \times 10^{-3}$, $4.53 \times 10^{-3}$, and $2.34 \times 10^{-3}$ at \theta=1\arcdeg for galaxies detected in the IRAC 3.6$\mu$m, 4.5$\mu$m, 5.8$\mu$m, and 8.0$\mu$m instrument channels, respectively. We compare our measurements at 3.6$\mu$m with the previous K-band measurements, and discuss the implications of these results.Comment: Accepted for publication in the ApJ Supplements Spitzer Special Issue; 12 pages including 3 figures and 1 tabl

The antibacterial activity of acetic acid against biofilm-producing pathogens of relevance to burns patients

Introduction: Localised infections, and burn wound sepsis are key concerns in the treatment of burns patients, and prevention of colonisation largely relies on biocides. Acetic acid has been shown to have good antibacterial activity against various planktonic organisms, however data is limited on efficacy, and few studies have been performed on biofilms. Objectives: We sought to investigate the antibacterial activity of acetic acid against important burn wound colonising organisms growing planktonically and as biofilms. Methods: Laboratory experiments were performed to test the ability of acetic acid to inhibit growth of pathogens, inhibit the formation of biofilms, and eradicate pre-formed biofilms. Results: Twenty-nine isolates of common wound-infecting pathogens were tested. Acetic acid was antibacterial against planktonic growth, with an minimum inhibitory concentration of 0.16-0.31% for all isolates, and was also able to prevent formation of biofilms (at 0.31 %). Eradication of mature biofilms was observed for all isolates after three hours of exposure. Conclusions: This study provides evidence that acetic acid can inhibit growth of key burn wound pathogens when used at very dilute concentrations. Owing to current concerns of the reducing efficacy of systemic antibiotics, this novel biocide application offers great promise as a cheap and effective measure to treat infections in burns patients

The Cerebral Microvasculature in Schizophrenia: A Laser Capture Microdissection Study

BACKGROUND: Previous studies of brain and peripheral tissues in schizophrenia patients have indicated impaired energy supply to the brain. A number of studies have also demonstrated dysfunction of the microvasculature in schizophrenia patients. Together these findings are consistent with a hypothesis of blood-brain barrier dysfunction in schizophrenia. In this study, we have investigated the cerebral vascular endothelium of schizophrenia patients at the level of transcriptomics. METHODOLOGY/PRINCIPAL FINDINGS: We used laser capture microdissection to isolate both microvascular endothelial cells and neurons from post mortem brain tissue from schizophrenia patients and healthy controls. RNA was isolated from these cell populations, amplified, and analysed using two independent microarray platforms, Affymetrix HG133plus2.0 GeneChips and CodeLink Whole Human Genome arrays. In the first instance, we used the dataset to compare the neuronal and endothelial data, in order to demonstrate that the predicted differences between cell types could be detected using this methodology. We then compared neuronal and endothelial data separately between schizophrenic subjects and controls. Analysis of the endothelial samples showed differences in gene expression between schizophrenics and controls which were reproducible in a second microarray platform. Functional profiling revealed that these changes were primarily found in genes relating to inflammatory processes. CONCLUSIONS/SIGNIFICANCE: This study provides preliminary evidence of molecular alterations of the cerebral microvasculature in schizophrenia patients, suggestive of a hypo-inflammatory state in this tissue type. Further investigation of the blood-brain barrier in schizophrenia is warranted

Remodeling of the Cortical Structural Connectome in Posttraumatic Stress Disorder:Results from the ENIGMA-PGC PTSD Consortium

BACKGROUND: Posttraumatic stress disorder (PTSD) is accompanied by disrupted cortical neuroanatomy. We investigated alteration in covariance of structural networks associated with PTSD in regions that demonstrate the case-control differences in cortical thickness (CT) and surface area (SA). METHODS: Neuroimaging and clinical data were aggregated from 29 research sites in >1,300 PTSD cases and >2,000 trauma-exposed controls (age 6.2-85.2 years) by the ENIGMA-PGC PTSD working group. Cortical regions in the network were rank-ordered by effect size of PTSD-related cortical differences in CT and SA. The top-n (n = 2 to 148) regions with the largest effect size for PTSD > non-PTSD formed hypertrophic networks, the largest effect size for PTSD < non-PTSD formed atrophic networks, and the smallest effect size of between-group differences formed stable networks. The mean structural covariance (SC) of a given n-region network was the average of all positive pairwise correlations and was compared to the mean SC of 5,000 randomly generated n-region networks. RESULTS: Patients with PTSD, relative to non-PTSD controls, exhibited lower mean SC in CT-based and SA-based atrophic networks. Comorbid depression, sex and age modulated covariance differences of PTSD-related structural networks. CONCLUSIONS: Covariance of structural networks based on CT and cortical SA are affected by PTSD and further modulated by comorbid depression, sex, and age. The structural covariance networks that are perturbed in PTSD comport with converging evidence from resting state functional connectivity networks and networks impacted by inflammatory processes, and stress hormones in PTSD