The Influence of Patient-Centeredness on Minority and Socioeconomically-Disadvantaged Patients’ Trust in their Physicians: An Evidence-Based Structural Equation Modeling Investigation

The purpose of this investigation was to determine the effect of physician patient-centeredness on patient trust across randomly selected groups of patients from an inner city medical practice serving a preponderance of minority and socioeconomically-disadvantaged patients. METHODS: A two-factor multigroup structural equation modeling design was employed, with randomly selected test (N = 300) and cross-validation (N = 300) samples of medical practice patients. Equality constraints were established to test the invariance of effects across groups. The model was compared to its unconstrained counterpart to further test its trustworthiness. An additional 5,000 nonparametric bootstrapped samples for each group were generated to further cross-validate and assess the stability of effect estimates. RESULTS: The model fit well. Physician patient-centeredness significantly influenced patient trust, explaining 82 percent of its variability. When physician patient-centeredness increased by one unit, the predicted value for patient trust increased by 1.043 units (.903 standardized). Patient-centered physician behaviors increased patients’ confidence in and likelihood to recommend their physician. This pattern of effects held across the test and cross-validation groups. The hypothesized model was sustained when compared to its competing counterpart. CONCLUSIONS: Evidence supported the factor and structural validity of the model. This study offers a plausible two-factor model for the measurement and improvement of patient-centeredness, and concomitantly, patient trust in an inner city medical clinic serving minority and socioeconomically-disadvantaged patients. In addition to quality improvement and outcome measurement, the results have implications for improving patient-centeredness, patient trust, the patient–provider relationship, medical education, and reducing health care disparities

Sunfall: a collaborative visual analytics system for astrophysics

Computational and experimental sciences produce and collect ever-larger and complex datasets, often in large-scale, multi-institution projects. The inability to gain insight into complex scientific phenomena using current software tools is a bottleneck facing virtually all endeavors of science. In this paper, we introduce Sunfall, a collaborative visual analytics system developed for the Nearby Supernova Factory, an international astrophysics experiment and the largest data volume supernova search currently in operation. Sunfall utilizes novel interactive visualization and analysis techniques to facilitate deeper scientific insight into complex, noisy, high-dimensional, high-volume, time-critical data. The system combines novel image processing algorithms, statistical analysis, and machine learning with highly interactive visual interfaces to enable collaborative, user-driven scientific exploration of supernova image and spectral data. Sunfall is currently in operation at the Nearby Supernova Factory; it is the first visual analytics system in production use at a major astrophysics project

The emergence and diversification of a zoonotic pathogen from within the microbiota of intensively farmed pigs

The expansion and intensification of livestock production is predicted to promote the emergence of pathogens. As pathogens sometimes jump between species, this can affect the health of humans as well as livestock. Here, we investigate how livestock microbiota can act as a source of these emerging pathogens through analysis of Streptococcus suis, a ubiquitous component of the respiratory microbiota of pigs that is also a major cause of disease on pig farms and an important zoonotic pathogen. Combining molecular dating, phylogeography, and comparative genomic analyses of a large collection of isolates, we find that several pathogenic lineages of S. suis emerged in the 19th and 20th centuries, during an early period of growth in pig farming. These lineages have since spread between countries and continents, mirroring trade in live pigs. They are distinguished by the presence of three genomic islands with putative roles in metabolism and cell adhesion, and an ongoing reduction in genome size, which may reflect their recent shift to a more pathogenic ecology. Reconstructions of the evolutionary histories of these islands reveal constraints on pathogen emergence that could inform control strategies, with pathogenic lineages consistently emerging from one subpopulation of S. suis and acquiring genes through horizontal transfer from other pathogenic lineages. These results shed light on the capacity of the microbiota to rapidly evolve to exploit changes in their host population and suggest that the impact of changes in farming on the pathogenicity and zoonotic potential of S. suis is yet to be fully realized

The emergence and diversification of a zoonotic pathogen from within the microbiota of intensively farmed pigs

The expansion and intensification of livestock production is predicted to promote the emergence of pathogens. As pathogens sometimes jump between species, this can affect the health of humans as well as livestock. Here, we investigate how livestock microbiota can act as a source of these emerging pathogens through analysis of Streptococcus suis, a ubiquitous component of the respiratory microbiota of pigs that is also a major cause of disease on pig farms and an important zoonotic pathogen. Combining molecular dating, phylogeography, and comparative genomic analyses of a large collection of isolates, we find that several pathogenic lineages of S. suis emerged in the 19th and 20th centuries, during an early period of growth in pig farming. These lineages have since spread between countries and continents, mirroring trade in live pigs. They are distinguished by the presence of three genomic islands with putative roles in metabolism and cell adhesion, and an ongoing reduction in genome size, which may reflect their recent shift to a more pathogenic ecology. Reconstructions of the evolutionary histories of these islands reveal constraints on pathogen emergence that could inform control strategies, with pathogenic lineages consistently emerging from one subpopulation of S. suis and acquiring genes through horizontal transfer from other pathogenic lineages. These results shed light on the capacity of the microbiota to rapidly evolve to exploit changes in their host population and suggest that the impact of changes in farming on the pathogenicity and zoonotic potential of S. suis is yet to be fully realized.This work was primarily funded by an EU Horizon 2020 grant “PIGSs” (727966) and a ZELS BBSRC award “Myanmar Pigs Partnership (MPP)” (BB/L018934/1). G.G.R.M., E.L.M., and L.A.W. were supported by a Sir Henry Dale Fellowship to L.A.W. jointly funded by the Wellcome Trust and the Royal Society (109385/Z/15/Z). N.H. was supported by a Challenge grant from the Royal Society (CH16011) and an Isaac Newton Trust Research Grant [17.24(u)]. G.G.R.M. was also supported by a Research Fellowship at Newnham College. S.B. is supported by the Medical Research Council (MR/V032836/1). PIC North America provided part of the funds for the sequencing of the isolates from the USA. A.J.B. and M.M. were funded by Medical Research Council and Biotechnology and Biological Sciences Research Council studentships respectively, and M.M. was co-funded by the Raymond and Beverly Sackler Fund. We would like to acknowledge Susanna Williamson at the APHA for providing samples, Oscar Cabezón for sampling of the wild boar population in Spain, Mark O’Dea for access to sequence data from Australian isolates, the PIGSs and MPP consortiums for providing samples and helpful discussions, Julian Parkhill and John Welch for helpful discussions, and two anonymous reviewers for their valuable suggestions for improving the manuscript. This research was funded in whole or in part by the Wellcome Trust. For the purpose of Open Access, the author has applied a CC BY public copyright license to any Author Accepted Manuscript (AAM) version arising from this submission.info:eu-repo/semantics/publishedVersio

Hydrodynamic modelling of protein conformation in solution: ELLIPS and HYDRO

The last three decades has seen some important advances in our ability to represent the conformation of proteins in solution on the basis of hydrodynamic measurements. Advances in theoretical modeling capabilities have been matched by commensurate advances in the precision of hydrodynamic measurements. We consider the advances in whole-body (simple ellipsoid-based) modeling—still useful for providing an overall idea of molecular shape, particularly for those systems where only a limited amount of data is available—and outline the ELLIPS suite of algorithms which facilitates the use of this approach. We then focus on bead modeling strategies, particularly the surface or shell–bead approaches and the HYDRO suite of algorithms. We demonstrate how these are providing great insights into complex issues such as the conformation of immunoglobulins and other multi-domain complexes

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

The contribution of insects to global forest deadwood decomposition

The amount of carbon stored in deadwood is equivalent to about 8 per cent of the global forest carbon stocks. The decomposition of deadwood is largely governed by climate with decomposer groups—such as microorganisms and insects—contributing to variations in the decomposition rates. At the global scale, the contribution of insects to the decomposition of deadwood and carbon release remains poorly understood. Here we present a field experiment of wood decomposition across 55 forest sites and 6 continents. We find that the deadwood decomposition rates increase with temperature, and the strongest temperature effect is found at high precipitation levels. Precipitation affects the decomposition rates negatively at low temperatures and positively at high temperatures. As a net effect—including the direct consumption by insects and indirect effects through interactions with microorganisms—insects accelerate the decomposition in tropical forests (3.9% median mass loss per year). In temperate and boreal forests, we find weak positive and negative effects with a median mass loss of 0.9 per cent and −0.1 per cent per year, respectively. Furthermore, we apply the experimentally derived decomposition function to a global map of deadwood carbon synthesized from empirical and remote-sensing data, obtaining an estimate of 10.9 ± 3.2 petagram of carbon per year released from deadwood globally, with 93 per cent originating from tropical forests. Globally, the net effect of insects may account for 29 per cent of the carbon flux from deadwood, which suggests a functional importance of insects in the decomposition of deadwood and the carbon cycle

Evasion of IFN-γ Signaling by Francisella novicida Is Dependent upon Francisella Outer Membrane Protein C

Francisella tularensis is a Gram-negative facultative intracellular bacterium and the causative agent of the lethal disease tularemia. An outer membrane protein (FTT0918) of F. tularensis subsp. tularensis has been identified as a virulence factor. We generated a F. novicida (F. tularensis subsp. novicida) FTN_0444 (homolog of FTT0918) fopC mutant to study the virulence-associated mechanism(s) of FTT0918.The ΔfopC strain phenotype was characterized using immunological and biochemical assays. Attenuated virulence via the pulmonary route in wildtype C57BL/6 and BALB/c mice, as well as in knockout (KO) mice, including MHC I, MHC II, and µmT (B cell deficient), but not in IFN-γ or IFN-γR KO mice was observed. Primary bone marrow derived macrophages (BMDM) prepared from C57BL/6 mice treated with rIFN-γ exhibited greater inhibition of intracellular ΔfopC than wildtype U112 strain replication; whereas, IFN-γR KO macrophages showed no IFN-γ-dependent inhibition of ΔfopC replication. Moreover, phosphorylation of STAT1 was downregulated by the wildtype strain, but not the fopC mutant, in rIFN-γ treated macrophages. Addition of NG-monomethyl-L-arginine, an NOS inhibitor, led to an increase of ΔfopC replication to that seen in the BMDM unstimulated with rIFN-γ. Enzymatic screening of ΔfopC revealed aberrant acid phosphatase activity and localization. Furthermore, a greater abundance of different proteins in the culture supernatants of ΔfopC than that in the wildtype U112 strain was observed.F. novicida FopC protein facilitates evasion of IFN-γ-mediated immune defense(s) by down-regulation of STAT1 phosphorylation and nitric oxide production, thereby promoting virulence. Additionally, the FopC protein also may play a role in maintaining outer membrane stability (integrity) facilitating the activity and localization of acid phosphatases and other F. novicida cell components

Strategy for the management of diabetic macular edema: the European Vitreo-Retinal Society macular edema study

Objective. To compare the efficacy of different therapies in the treatment of diabetic macular edema (DME). Design. Nonrandomized, multicenter clinical study. Participants. 86 retina specialists from 29 countries provided clinical information on 2,603 patients with macular edema including 870 patients with DME. Methods. Reported data included the type and number of treatment(s) performed, the pre-and posttreatment visual acuities, and other clinical findings.The results were analyzed by the French INSEE (National Institute of Statistics and Economic Studies). Main Outcome Measures. Mean change of visual acuity and mean number of treatments performed. Results.The change in visual acuity over time in response to each treatment was plotted in second order polynomial regression trend lines. Intravitreal triamcinolone monotherapy resulted in some improvement in vision. Treatmentwith threshold or subthreshold grid laser also resulted in minimal vision gain. Anti-VEGF therapy resulted in more significant visual improvement. Treatment with pars plana vitrectomy and internal limiting membrane (ILM) peeling alone resulted in an improvement in vision greater than that observed with anti-VEGF injection alone. In our DME study, treatment with vitrectomy and ILM peeling alone resulted in the better visual improvement compared to other therapies

The 13th Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-IV Survey Mapping Nearby Galaxies at Apache Point Observatory

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) began observations in July 2014. It pursues three core programs: APOGEE-2,MaNGA, and eBOSS. In addition, eBOSS contains two major subprograms: TDSS and SPIDERS. This paper describes the first data release from SDSS-IV, Data Release 13 (DR13), which contains new data, reanalysis of existing data sets and, like all SDSS data releases, is inclusive of previously released data. DR13 makes publicly available 1390 spatially resolved integral field unit observations of nearby galaxies from MaNGA,the first data released from this survey. It includes new observations from eBOSS, completing SEQUELS. In addition to targeting galaxies and quasars, SEQUELS also targeted variability-selected objects from TDSS and X-ray selected objects from SPIDERS. DR13 includes new reductions ofthe SDSS-III BOSS data, improving the spectrophotometric calibration and redshift classification. DR13 releases new reductions of the APOGEE-1data from SDSS-III, with abundances of elements not previously included and improved stellar parameters for dwarf stars and cooler stars. For the SDSS imaging data, DR13 provides new, more robust and precise photometric calibrations. Several value-added catalogs are being released in tandem with DR13, in particular target catalogs relevant for eBOSS, TDSS, and SPIDERS, and an updated red-clump catalog for APOGEE.This paper describes the location and format of the data now publicly available, as well as providing references to the important technical papers that describe the targeting, observing, and data reduction. The SDSS website, http://www.sdss.org, provides links to the data, tutorials and examples of data access, and extensive documentation of the reduction and analysis procedures. DR13 is the first of a scheduled set that will contain new data and analyses from the planned ~6-year operations of SDSS-IV.PostprintPeer reviewe