Cosmology and Astrophysics from Relaxed Galaxy Clusters II: Cosmological Constraints

We present cosmological constraints from measurements of the gas mass fraction, $f_{gas}$, for massive, dynamically relaxed galaxy clusters. Our data set consists of Chandra observations of 40 such clusters, identified in a comprehensive search of the Chandra archive, as well as high-quality weak gravitational lensing data for a subset of these clusters. Incorporating a robust gravitational lensing calibration of the X-ray mass estimates, and restricting our measurements to the most self-similar and accurately measured regions of clusters, significantly reduces systematic uncertainties compared to previous work. Our data for the first time constrain the intrinsic scatter in $f_{gas}$, $(7.4\pm2.3)$% in a spherical shell at radii 0.8-1.2 $r_{2500}$, consistent with the expected variation in gas depletion and non-thermal pressure for relaxed clusters. From the lowest-redshift data in our sample we obtain a constraint on a combination of the Hubble parameter and cosmic baryon fraction, $h^{3/2}\Omega_b/\Omega_m=0.089\pm0.012$, that is insensitive to the nature of dark energy. Combined with standard priors on $h$ and $\Omega_b h^2$, this provides a tight constraint on the cosmic matter density, $\Omega_m=0.27\pm0.04$, which is similarly insensitive to dark energy. Using the entire cluster sample, extending to $z>1$, we obtain consistent results for $\Omega_m$ and interesting constraints on dark energy: $\Omega_\Lambda=0.65^{+0.17}_{-0.22}$ for non-flat $\Lambda$CDM models, and $w=-0.98\pm0.26$ for flat constant-$w$ models. Our results are both competitive and consistent with those from recent CMB, SNIa and BAO data. We present constraints on models of evolving dark energy from the combination of $f_{gas}$ data with these external data sets, and comment on the possibilities for improved $f_{gas}$ constraints using current and next-generation X-ray observatories and lensing data. (Abridged)Comment: 25 pages, 14 figures, 8 tables. Accepted by MNRAS. Code and data can be downloaded from http://www.slac.stanford.edu/~amantz/work/fgas14/ . v2: minor fix to table 1, updated bibliograph

Robust Weak-lensing Mass Calibration of Planck Galaxy Clusters

In light of the tension in cosmological constraints reported by the Planck team between their SZ-selected cluster counts and Cosmic Microwave Background (CMB) temperature anisotropies, we compare the Planck cluster mass estimates with robust, weak-lensing mass measurements from the Weighing the Giants (WtG) project. For the 22 clusters in common between the Planck cosmology sample and WtG, we find an overall mass ratio of \left = 0.688 \pm 0.072. Extending the sample to clusters not used in the Planck cosmology analysis yields a consistent value of $\left< M_{Planck}/M_{\rm WtG} \right> = 0.698 \pm 0.062$ from 38 clusters in common. Identifying the weak-lensing masses as proxies for the true cluster mass (on average), these ratios are $\sim 1.6\sigma$ lower than the default mass bias of 0.8 assumed in the Planck cluster analysis. Adopting the WtG weak-lensing-based mass calibration would substantially reduce the tension found between the Planck cluster count cosmology results and those from CMB temperature anisotropies, thereby dispensing of the need for "new physics" such as uncomfortably large neutrino masses (in the context of the measured Planck temperature anisotropies and other data). We also find modest evidence (at 95 per cent confidence) for a mass dependence of the calibration ratio and discuss its potential origin in light of systematic uncertainties in the temperature calibration of the X-ray measurements used to calibrate the Planck cluster masses. Our results exemplify the critical role that robust absolute mass calibration plays in cluster cosmology, and the invaluable role of accurate weak-lensing mass measurements in this regard.Comment: 5 pages, 2 figure

Focusing Cosmic Telescopes: Exploring Redshift z~5-6 Galaxies with the Bullet Cluster 1E0657-56

The gravitational potential of clusters of galaxies acts as a cosmic telescope allowing us to find and study galaxies at fainter limits than otherwise possible and thus probe closer to the epoch of formation of the first galaxies. We use the Bullet Cluster 1E0657-56 (z = 0.296) as a case study, because its high mass and merging configuration makes it one of the most efficient cosmic telescopes we know. We develop a new algorithm to reconstruct the gravitational potential of the Bullet Cluster, based on a non-uniform adaptive grid, combining strong and weak gravitational lensing data derived from deep HST/ACS F606W-F775W-F850LP and ground-based imaging. We exploit this improved mass map to study z~5-6 Lyman Break Galaxies (LBGs), which we detect as dropouts. One of the LBGs is multiply imaged, providing a geometric confirmation of its high redshift, and is used to further improve our mass model. We quantify the uncertainties in the magnification map reconstruction in the intrinsic source luminosity, and in the volume surveyed, and show that they are negligible compared to sample variance when determining the luminosity function of high-redshift galaxies. With shallower and comparable magnitude limits to HUDF and GOODS, the Bullet cluster observations, after correcting for magnification, probe deeper into the luminosity function of the high redshift galaxies than GOODS and only slightly shallower than HUDF. We conclude that accurately focused cosmic telescopes are the most efficient way to sample the bright end of the luminosity function of high redshift galaxies and - in case they are multiply imaged - confirm their redshifts.Comment: 12 pages, Accepted for publication in Ap

Maximum levels of hepatitis C virus lipoviral particles are associated with early and persistent infection

Background & Aims: Hepatitis C virus (HCV) is bound to plasma lipoproteins and circulates as an infectious lipoviral particle (LVP). Experimental evidence indicates that LVPs have decreased susceptibility to antibody-mediated neutralisation and higher infectivity. This study tested the hypothesis that LVPs are required to establish persistent infection, and conversely, low levels of LVP in recent HCV infection increase the probability of spontaneous HCV clearance. Methods: LVP in non-fasting plasma was measured using the concentration of HCV RNA bound to large >100 nm sized lipoproteins after ex vivo addition of a lipid emulsion, that represented the maximum concentration of LVP (maxi-LVP). This method correlated with LVP in fasting plasma measured using iodixanol density gradient ultracentrifugation. Maxi-LVP was measured in a cohort of 180 HCV participants with recent HCV infection and detectable HCV RNA from the Australian Trial in Acute Hepatitis C (ATAHC) and Hepatitis C Incidence and Transmission Study in prison (HITS-p) cohorts. Results: Spontaneous clearance occurred in 15% (27 of 180) of individuals. In adjusted analyses, low plasma maxi-LVP level was independently associated with spontaneous HCV clearance (≤827 IU/ml; adjusted odds ratio 3.98, 95% CI: 1.02, 15.51, P = 0.047), after adjusting for interferon lambda-3 rs8099917 genotype, estimated duration of HCV infection and total HCV RNA level. Conclusions: Maxi-LVP is a biomarker for the maximum concentration of LVP in non-fasting samples. Low maxi-LVP level is an independent predictor of spontaneous clearance of acute HCV

The Building Blocks of Interoperability. A Multisite Analysis of Patient Demographic Attributes Available for Matching.

BackgroundPatient matching is a key barrier to achieving interoperability. Patient demographic elements must be consistently collected over time and region to be valuable elements for patient matching.ObjectivesWe sought to determine what patient demographic attributes are collected at multiple institutions in the United States and see how their availability changes over time and across clinical sites.MethodsWe compiled a list of 36 demographic elements that stakeholders previously identified as essential patient demographic attributes that should be collected for the purpose of linking patient records. We studied a convenience sample of 9 health care systems from geographically distinct sites around the country. We identified changes in the availability of individual patient demographic attributes over time and across clinical sites.ResultsSeveral attributes were consistently available over the study period (2005-2014) including last name (99.96%), first name (99.95%), date of birth (98.82%), gender/sex (99.73%), postal code (94.71%), and full street address (94.65%). Other attributes changed significantly from 2005-2014: Social security number (SSN) availability declined from 83.3% to 50.44% (p&lt;0.0001). Email address availability increased from 8.94% up to 54% availability (p&lt;0.0001). Work phone number increased from 20.61% to 52.33% (p&lt;0.0001).ConclusionsOverall, first name, last name, date of birth, gender/sex and address were widely collected across institutional sites and over time. Availability of emerging attributes such as email and phone numbers are increasing while SSN use is declining. Understanding the relative availability of patient attributes can inform strategies for optimal matching in healthcare

Effect of lipid-lowering medications in patients with coronary artery bypass grafting surgery outcomes

Background: Increased life expectancy and improved medical technology allow increasing numbers of elderly patients to undergo cardiac surgery. Elderly patients may be at greater risk of postoperative morbidity and mortality. Complications can lead to worsened quality of life, shortened life expectancy and higher healthcare costs. Reducing perioperative complications, especially severe adverse events, is key to improving outcomes in patients undergoing cardiac surgery. The objective of this study is to determine whether perioperative lipid-lowering medication use is associated with a reduced risk of complications and mortality after coronary artery bypass grafting (CABG) with cardiopulmonary bypass (CPB). Methods: After IRB approval, we reviewed charts of 9,518 patients who underwent cardiac surgery with CPB at three medical centers between July 2001 and June 2015. The relationship between perioperative lipid-lowering treatment and postoperative outcome was investigated. 3,988 patients who underwent CABG met inclusion criteria and were analyzed. Patients were divided into lipid-lowering or non-lipid-lowering treatment groups. Results: A total of 3,988 patients were included in the final analysis. Compared to the patients without lipid-lowering medications, the patients with lipid-lowering medications had lower postoperative neurologic complications and overall mortality (P \u3c 0.05). Propensity weighted risk-adjustment showed that lipid-lowering medication reduced in-hospital total complications (odds ratio (OR) = 0.856; 95% CI 0.781-0.938; P \u3c 0.001); all neurologic complications (OR = 0.572; 95% CI 0.441-0.739; P \u3c 0.001) including stroke (OR = 0.481; 95% CI 0.349-0.654; P \u3c 0.001); in-hospital mortality (OR = 0.616; 95% CI 0.432-0.869; P = 0.006; P \u3c 0.001); and overall mortality (OR = 0.723; 95% CI 0.634-0.824; P \u3c 0.001). In addition, the results indicated postoperative lipid-lowering medication use was associated with improved long-term survival in this patient population. Conclusions: Perioperative lipid-lowering medication use was associated with significantly reduced postoperative adverse events and improved overall outcome in elderly patients undergoing CABG surgery with CPB

Weighing the Giants - I. Weak-lensing masses for 51 massive galaxy clusters: project overview, data analysis methods and cluster images

This is the first in a series of papers in which we measure accurate weak-lensing masses for 51 of the most X-ray luminous galaxy clusters known at redshifts 0.15<z<0.7, in order to calibrate X-ray and other mass proxies for cosmological cluster experiments. The primary aim is to improve the absolute mass calibration of cluster observables, currently the dominant systematic uncertainty for cluster count experiments. Key elements of this work are the rigorous quantification of systematic uncertainties, high-quality data reduction and photometric calibration, and the "blind" nature of the analysis to avoid confirmation bias. Our target clusters are drawn from RASS X-ray catalogs, and provide a versatile calibration sample for many aspects of cluster cosmology. We have acquired wide-field, high-quality imaging using the Subaru and CFHT telescopes for all 51 clusters, in at least three bands per cluster. For a subset of 27 clusters, we have data in at least five bands, allowing accurate photo-z estimates of lensed galaxies. In this paper, we describe the cluster sample and observations, and detail the processing of the SuprimeCam data to yield high-quality images suitable for robust weak-lensing shape measurements and precision photometry. For each cluster, we present wide-field color optical images and maps of the weak-lensing mass distribution, the optical light distribution, and the X-ray emission, providing insights into the large-scale structure in which the clusters are embedded. We measure the offsets between X-ray centroids and Brightest Cluster Galaxies in the clusters, finding these to be small in general, with a median of 20kpc. For offsets <100kpc, weak-lensing mass measurements centered on the BCGs agree well with values determined relative to the X-ray centroids; miscentering is therefore not a significant source of systematic uncertainty for our mass measurements. [abridged]Comment: 26 pages, 19 figures (Appendix C not included). Accepted after minor revisio

Machine learning approaches to enhance diagnosis and staging of patients with MASLD using routinely available clinical information

Aims: Metabolic dysfunction Associated Steatotic Liver Disease (MASLD) outcomes such as MASH (metabolic dysfunction associated steatohepatitis), fibrosis and cirrhosis are ordinarily determined by resource-intensive and invasive biopsies. We aim to show that routine clinical tests offer sufficient information to predict these endpoints. Methods: Using the LITMUS Metacohort derived from the European NAFLD Registry, the largest MASLD dataset in Europe, we create three combinations of features which vary in degree of procurement including a 19-variable feature set that are attained through a routine clinical appointment or blood test. This data was used to train predictive models using supervised machine learning (ML) algorithm XGBoost, alongside missing imputation technique MICE and class balancing algorithm SMOTE. Shapley Additive exPlanations (SHAP) were added to determine relative importance for each clinical variable. Results: Analysing nine biopsy-derived MASLD outcomes of cohort size ranging between 5385 and 6673 subjects, we were able to predict individuals at training set AUCs ranging from 0.719-0.994, including classifying individuals who are At-Risk MASH at an AUC = 0.899. Using two further feature combinations of 26-variables and 35-variables, which included composite scores known to be good indicators for MASLD endpoints and advanced specialist tests, we found predictive performance did not sufficiently improve. We are also able to present local and global explanations for each ML model, offering clinicians interpretability without the expense of worsening predictive performance. Conclusions: This study developed a series of ML models of accuracy ranging from 71.9—99.4% using only easily extractable and readily available information in predicting MASLD outcomes which are usually determined through highly invasive means