The Intermediate-Scale Clustering of Luminous Red Galaxies

We report the intermediate-scale (0.3 to 40 Mpc/h) clustering of 35,000 luminous early-type galaxies at redshifts 0.16 to 0.44 from the Sloan Digital Sky Survey. We present the redshift-space two-point correlation function \xi(s), the projected correlation function w_p(r_p), and the deprojected real-space correlation function \xi(r), for approximately volume-limited samples. As expected, the galaxies are highly clustered, with the correlation length varying from 9.8 +/- 0.2 Mpc/h to 11.2 +/- 0.2 Mpc/h, dependent on the specific luminosity range. For the -23.2 < Mg < -21.2 sample, the inferred bias relative to that of L* galaxies is 1.84 +/- 0.11 for 1 Mpc/h < r_p < 10 Mpc/h, with yet stronger clustering on smaller scales. We detect luminosity-dependent bias within the sample but see no evidence for redshift evolution between z=0.2 and z=0.4. We find a clear indication for deviations from a power-law in the real-space correlation function, with a dip at ~ 2 Mpc/h scales and an upturn on smaller scales. The precision measurements of these clustering trends offer new avenues for the study of the formation and evolution of these massive galaxies.Comment: 11 pages, 14 figures. Accepted to the Astrophysical Journa

Label-free Chemical Characterization of Polarized Immune Cells in vitro and Host Response to Implanted Bio-instructive Polymers in vivo Using 3D OrbiSIMS

The Three-dimensional OrbiTrap Secondary Ion Mass Spectrometry (3D OrbiSIMS) is a secondary ion mass spectrometry instrument, a combination of a Time of Flight (ToF) instrument with an Orbitrap analyzer. The 3D OrbiSIMS technique is a powerful tool for metabolic profiling in biological samples. This can be achieved at subcellular spatial resolution, high sensitivity, and high mass-resolving power coupled with MS/MS analysis. Characterizing the metabolic signature of macrophage subsets within tissue sections offers great potential to understand the response of the human immune system to implanted biomaterials. Here, we describe a protocol for direct analysis of individual cells after in vitro differentiation of naïve monocytes into M1 and M2 phenotypes using cytokines. As a first step in vivo, we investigate explanted silicon catheter sections as a medical device in a rodent model of foreign body response. Protocols are presented to allow the host response to different immune instructive materials to be compared. The first demonstration of this capability illustrates the great potential of direct cell and tissue section analysis for in situ metabolite profiling to probe functional phenotypes using molecular signatures. Details of the in vitro cell approach, materials, sample preparation, and explant handling are presented, in addition to the data acquisition approaches and the data analysis pipelines required to achieve useful interpretation of these complex spectra. This method is useful for in situ characterization of both in vitro single cells and ex vivo tissue sections. This will aid the understanding of the immune response to medical implants by informing the design of immune-instructive biomaterials with positive interactions. It can also be used to investigate a broad range of other clinically relevant therapeutics and immune dysregulations

Closing in on Omega_0: The Amplitude of Mass Fluctuations from Galaxy Clusters and the Lyman-alpha Forest

We estimate the value of the matter density parameter \Omega_0 by combining constraints from the galaxy cluster mass function with Croft et al.'s recent measurement of the mass power spectrum, P(k), from \lya forest data. The key assumption of the method is that cosmic structure formed by gravitational instability from Gaussian primordial fluctuations. For a specified value of \Omega_0, matching the observed cluster mass function then fixes the value of \sigma_8, the rms amplitude of mass fluctuations in 8\hmpc spheres, and it thus determines the normalization of P(k) at z=0. The value of \Omega_0 also determines the ratio of P(k) at z=0 to P(k) at z=2.5, the central redshift of the \lya forest data; the ratio is different for an open universe (\Lambda=0) or a flat universe. Because the \lya forest measurement only reaches comoving scales 2\pi/k ~ 15-20\hmpc, the derived value of \Omega_0 depends on the value of the power spectrum shape parameter \Gamma, which determines the relative contribution of larger scale modes to \sigma_8. Adopting \Gamma=0.2, a value favored by galaxy clustering data, we find \Omega_0 = 0.46^{+0.12}_{-0.10} for an open universe and \Omega_0=0.34^{+0.13}_{-0.09} for a flat universe (1\sigma errors, not including the uncertainty in cluster normalization). Cluster-normalized models with \Omega_0=1 predict too low an amplitude for P(k) at z=2.5, while models with \Omega_0=0.1 predict too high an amplitude. The more general best fit parameter combination is approximately \Omega_0 + 0.2\Lambda_0 = 0.46 + 1.3(\Gamma-0.2). Analysis of larger, existing samples of QSO spectra could greatly improve the measurement of P(k) from the \lya forest, allowing a determination of \Omega_0 by this method with a precision of ~15%, limited mainly by uncertainty in the cluster mass function.Comment: Submitted to ApJ, 6 emulateapj pages w/ 2 postscript fig

The Clustering of Luminous Red Galaxies in the Sloan Digital Sky Survey Imaging Data

We present the 3D real space clustering power spectrum of a sample of \~600,000 luminous red galaxies (LRGs) measured by the Sloan Digital Sky Survey (SDSS), using photometric redshifts. This sample of galaxies ranges from redshift z=0.2 to 0.6 over 3,528 deg^2 of the sky, probing a volume of 1.5 (Gpc/h)^3, making it the largest volume ever used for galaxy clustering measurements. We measure the angular clustering power spectrum in eight redshift slices and combine these into a high precision 3D real space power spectrum from k=0.005 (h/Mpc) to k=1 (h/Mpc). We detect power on gigaparsec scales, beyond the turnover in the matter power spectrum, on scales significantly larger than those accessible to current spectroscopic redshift surveys. We also find evidence for baryonic oscillations, both in the power spectrum, as well as in fits to the baryon density, at a 2.5 sigma confidence level. The statistical power of these data to constrain cosmology is ~1.7 times better than previous clustering analyses. Varying the matter density and baryon fraction, we find \Omega_M = 0.30 \pm 0.03, and \Omega_b/\Omega_M = 0.18 \pm 0.04, The detection of baryonic oscillations also allows us to measure the comoving distance to z=0.5; we find a best fit distance of 1.73 \pm 0.12 Gpc, corresponding to a 6.5% error on the distance. These results demonstrate the ability to make precise clustering measurements with photometric surveys (abridged).Comment: 23 pages, 27 figures, submitted to MNRA

A Novel Nonsense Mutation in the DMP1 Gene Identified by a Genome-Wide Association Study Is Responsible for Inherited Rickets in Corriedale Sheep

Inherited rickets of Corriedale sheep is characterized by decreased growth rate, thoracic lordosis and angular limb deformities. Previous outcross and backcross studies implicate inheritance as a simple autosomal recessive disorder. A genome wide association study was conducted using the Illumina OvineSNP50 BeadChip on 20 related sheep comprising 17 affected and 3 carriers. A homozygous region of 125 consecutive single-nucleotide polymorphism (SNP) loci was identified in all affected sheep, covering a region of 6 Mb on ovine chromosome 6. Among 35 candidate genes in this region, the dentin matrix protein 1 gene (DMP1) was sequenced to reveal a nonsense mutation 250C/T on exon 6. This mutation introduced a stop codon (R145X) and could truncate C-terminal amino acids. Genotyping by PCR-RFLP for this mutation showed all 17 affected sheep were “T T” genotypes; the 3 carriers were “C T”; 24 phenotypically normal related sheep were either “C T” or “C C”; and 46 unrelated normal control sheep from other breeds were all “C C”. The other SNPs in DMP1 were not concordant with the disease and can all be ruled out as candidates. Previous research has shown that mutations in the DMP1 gene are responsible for autosomal recessive hypophosphatemic rickets in humans. Dmp1_knockout mice exhibit rickets phenotypes. We believe the R145X mutation to be responsible for the inherited rickets found in Corriedale sheep. A simple diagnostic test can be designed to identify carriers with the defective “T” allele. Affected sheep could be used as animal models for this form of human rickets, and for further investigation of the role of DMP1 in phosphate homeostasis

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

Trends in publications regarding evidence-practice gaps: A literature review

<p>Abstract</p> <p>Background</p> <p>Well-designed trials of strategies to improve adherence to clinical practice guidelines are needed to close persistent evidence-practice gaps. We studied how the number of these trials is changing with time, and to what extent physicians are participating in such trials.</p> <p>Methods</p> <p>This is a literature-based study of trends in evidence-practice gap publications over 10 years and participation of clinicians in intervention trials to narrow evidence-practice gaps. We chose nine evidence-based guidelines and identified relevant publications in the PubMed database from January 1998 to December 2007. We coded these publications by study type (intervention versus non-intervention studies). We further subdivided intervention studies into those for clinicians and those for patients. Data were analyzed to determine if observed trends were statistically significant.</p> <p>Results</p> <p>We identified 1,151 publications that discussed evidence-practice gaps in nine topic areas. There were 169 intervention studies that were designed to improve adherence to well-established clinical guidelines, averaging 1.9 studies per year per topic area. Twenty-eight publications (34%; 95% CI: 24% - 45%) reported interventions intended for clinicians or health systems that met Effective Practice and Organization of Care (EPOC) criteria for adequate design. The median consent rate of physicians asked to participate in these well-designed studies was 60% (95% CI, 25% to 69%).</p> <p>Conclusions</p> <p>We evaluated research publications for nine evidence-practice gaps, and identified small numbers of well-designed intervention trials and low rates of physician participation in these trials.</p

Spatially resolved molecular analysis of host response to medical device implantation using the 3D OrbiSIMS highlights a critical role for lipids

A key goal for implanted medical devices is that they do not elicit a detrimental immune response. Macrophages play critical roles in modulation of the host immune response and are the major cells responsible for persistent inflammatory reactions to implanted biomaterials. We investigate two novel immune-instructive polymers that stimulate pro- or anti-inflammatory responses from macrophages in vitro. These also modulate in vivo foreign body responses (FBR) when implanted subcutaneously in mice as coatings on biomedical grade silicone rubber. The tissue surrounding the implant is mechanically sectioned and imaged to assess the response of the polymers compared to silicone rubber. Immunofluorescent staining reveals responses consistent with pro- or anti-inflammatory responses previously described for these polymers. We apply 3D OrbiSIMS analysis to provide spatial analysis of the metabolite signature in the tissue surrounding the implant for the first time, providing molecular histology insight into the metabolite response in the host tissue. For the pro-inflammatory coating, monoacylglycerols (MG) and diacylglycerols (DG) are observed at increased intensity, while for the anti-inflammatory coating the number of phospholipid species detected decrease and pyridine and pyrimidine levels were elevated. These findings link to observations of small molecule signature from single cell studies of M2 macrophages in vitro where cell and tissue ion intensities were found to correlate suggesting potential for prediction. This illustrates the power of metabolite characterization by the 3D OrbiSIMS to gain insight into the mechanism of bio-instructive materials as medical devices and to inform on the FBR to biomaterials

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

Recent artificial selection in U.S. Jersey cattle impacts autozygosity levels of specific genomic regions

Background: Genome signatures of artificial selection in U.S. Jersey cattle were identified by examining changes in haplotype homozygosity for a resource population of animals born between 1953 and 2007. Genetic merit of this population changed dramatically during this period for a number of traits, especially milk yield. The intense selection underlying these changes was achieved through extensive use of artificial insemination (AI), which also increased consanguinity of the population to a few superior Jersey bulls. As a result, allele frequencies are shifted for many contemporary animals, and in numerous cases to a homozygous state for specific genomic regions. The goal of this study was to identify those selection signatures that occurred after extensive use of AI since the 1960, using analyses of shared haplotype segments or Runs of Homozygosity. When combined with animal birth year information, signatures of selection associated with economically important traits were identified and compared to results from an extended haplotype homozygosity analysis. Results: Overall, our results reveal that more recent selection increased autozygosity across the entire genome, but some specific regions increased more than others. A genome-wide scan identified more than 15 regions with a substantial change in autozygosity. Haplotypes found to be associated with increased milk, fat and protein yield in U.S. Jersey cattle also consistently increased in frequency. Conclusions: The analyses used in this study was able to detect directional selection over the last few decades when individual production records for Jersey animals were available