The XXL Survey VII: A supercluster of galaxies at z=0.43

The XXL Survey is the largest homogeneous and contiguous survey carried out with XMM-Newton. Covering an area of 50 square degrees distributed over two fields, it primarily investigates the large-scale structures of the Universe using the distribution of galaxy clusters and active galactic nuclei as tracers of the matter distribution. Given its depth and sky coverage, XXL is particularly suited to systematically unveiling the clustering of X-ray clusters and to identifying superstructures in a homogeneous X-ray sample down to the typical mass scale of a local massive cluster. A friends-of-friends algorithm in three-dimensional physical space was run to identify large-scale structures. In this paper we report the discovery of the highest redshift supercluster of galaxies found in the XXL Survey. We describe the X-ray properties of the clusters members of the structure and the optical follow-up. The newly discovered supercluster is composed of six clusters of galaxies at a median redshift z around 0.43 and distributed across approximately 30 by 15 arc minutes (10 by 5 Mpc on sky) on the sky. This structure is very compact with all the clusters residing in one XMM pointing; for this reason this is the first supercluster discovered with the XXL Survey. Spectroscopic follow-up with WHT (William Herschel Telescope) and NTT (New Technology Telescope) confirmed a median redshift of z = 0.43. An estimate of the X-ray mass and luminosity of this supercluster and of its total gas mass put XLSSC-e at the average mass range of superclusters; its appearance, with two members of equal size, is quite unusual with respect to other superclusters and provides a unique view of the formation process of a massive structure.Comment: A&A, accepted; special XXL issu

The XXL Survey: VI. The 1000 brightest X-ray point sources

X-ray extragalactic surveys are ideal laboratories for the study of the evolution and clustering of active galactic nuclei (AGN). The XXL Survey spans two fields of a combined 50 $deg^2$ observed for more than 6Ms with XMM-Newton, occupying the parameter space between deep surveys and very wide area surveys; at the same time it benefits from a wealth of ancillary data. This paper marks the first release of the XXL point source catalogue selected in the 2-10 keV energy band with limiting flux $F_{2-10keV}=4.8\cdot10^{-14}\rm{erg\,s^{-1}\,cm^{-2}}$. We use both public and proprietary data sets to identify the counterparts of the X-ray point-like sources and improved upon the photometric redshift determination for AGN by applying a Random Forest classification trained to identify for each object the optimal photometric redshift model library. We also assign a probability to each source to be a star or an outlier. We model with Bayesian analysis the X-ray spectra assuming a power-law model with the presence of an absorbing medium. We find an average unabsorbed photon index of $\Gamma=1.85$ and average hydrogen column density $\log{N_{H}}=21.07 cm^{-2}$. We find no trend of $\Gamma$ or $N_H$ with redshift and a fraction of 26% absorbed sources ($\log N_{H}>22$). We show that the XXL-1000-AGN number counts extended the number counts of the COSMOS survey to higher fluxes and are fully consistent with the Euclidean expectation. We constrain the intrinsic luminosity function of AGN in the 2-10 keV energy band where the unabsorbed X-ray flux is estimated from the X-ray spectral fit up to z=3. Finally, we demonstrate the presence of a supercluster size structure at redshift 0.14, identified by means of percolation analysis of the XXL-1000-AGN sample. The XXL survey, reaching a medium flux limit and covering a wide area is a stepping stone between current deep fields and planned wide area surveys

The XXL Survey. II. The bright cluster sample: catalogue and luminosity function

Context. The XXL Survey is the largest survey carried out by the XMM-Newton satellite and covers a total area of 50 square degrees distributed over two fields. It primarily aims at investigating the large-scale structures of the Universe using the distribution of galaxy clusters and active galactic nuclei as tracers of the matter distribution. Aims. This article presents the XXL bright cluster sample, a subsample of 100 galaxy clusters selected from the full XXL catalogue by setting a lower limit of $3\times 10^{-14}\,\mathrm{erg \,s^{-1}cm^{-2}}$ on the source flux within a 1$^{\prime}$ aperture. Methods. The selection function was estimated using a mixture of Monte Carlo simulations and analytical recipes that closely reproduce the source selection process. An extensive spectroscopic follow-up provided redshifts for 97 of the 100 clusters. We derived accurate X-ray parameters for all the sources. Scaling relations were self-consistently derived from the same sample in other publications of the series. On this basis, we study the number density, luminosity function, and spatial distribution of the sample. Results. The bright cluster sample consists of systems with masses between $M_{500}=7\times 10^{13}$ and $3\times 10^{14} M_\odot$, mostly located between $z=0.1$ and 0.5. The observed sky density of clusters is slightly below the predictions from the WMAP9 model, and significantly below the predictions from the Planck 2015 cosmology. In general, within the current uncertainties of the cluster mass calibration, models with higher values of $\sigma_8$ and/or $\Omega_m$ appear more difficult to accommodate. We provide tight constraints on the cluster differential luminosity function and find no hint of evolution out to $z\sim1$. We also find strong evidence for the presence of large-scale structures in the XXL bright cluster sample and identify five new superclusters

The XXL survey: first results and future

The XXL survey currently covers two 25 sq. deg. patches with XMM observations of ~10ks. We summarise the scientific results associated with the first release of the XXL data set, that occurred mid 2016. We review several arguments for increasing the survey depth to 40 ks during the next decade of XMM operations. X-ray (z1 cluster density. It will eventually constitute a reference study and an ideal calibration field for the upcoming eROSITA and Euclid missions

The XXL Survey: I. Scientific motivations - XMM-Newton observing plan - Follow-up observations and simulation programme

We present the XXL Survey, the largest XMM programme totaling some 6.9 Ms to date and involving an international consortium of roughly 100 members. The XXL Survey covers two extragalactic areas of 25 deg2 each at a point-source sensitivity of ~ 5E-15 erg/sec/cm2 in the [0.5-2] keV band (completeness limit). The survey's main goals are to provide constraints on the dark energy equation of state from the space-time distribution of clusters of galaxies and to serve as a pathfinder for future, wide-area X-ray missions. We review science objectives, including cluster studies, AGN evolution, and large-scale structure, that are being conducted with the support of approximately 30 follow-up programmes. We describe the 542 XMM observations along with the associated multi-lambda and numerical simulation programmes. We give a detailed account of the X-ray processing steps and describe innovative tools being developed for the cosmological analysis. The paper provides a thorough evaluation of the X-ray data, including quality controls, photon statistics, exposure and background maps, and sky coverage. Source catalogue construction and multi-lambda associations are briefly described. This material will be the basis for the calculation of the cluster and AGN selection functions, critical elements of the cosmological and science analyses. The XXL multi-lambda data set will have a unique lasting legacy value for cosmological and extragalactic studies and will serve as a calibration resource for future dark energy studies with clusters and other X-ray selected sources. With the present article, we release the XMM XXL photon and smoothed images along with the corresponding exposure maps. The XMM XXL observation list (Table B.1) is available in electronic form at the CDS. The present paper is the first in a series reporting results of the XXL-XMM survey

The XXL Survey: VI. The 1000 brightest X-ray point sources

X-ray extragalactic surveys are ideal laboratories for the study of the evolution and clustering of active galactic nuclei (AGN). The XXL Survey spans two fields of a combined 50 $deg^2$ observed for more than 6Ms with XMM-Newton, occupying the parameter space between deep surveys and very wide area surveys; at the same time it benefits from a wealth of ancillary data. This paper marks the first release of the XXL point source catalogue selected in the 2-10 keV energy band with limiting flux $F_{2-10keV}=4.8\cdot10^{-14}\rm{erg\,s^{-1}\,cm^{-2}}$. We use both public and proprietary data sets to identify the counterparts of the X-ray point-like sources and improved upon the photometric redshift determination for AGN by applying a Random Forest classification trained to identify for each object the optimal photometric redshift model library. We also assign a probability to each source to be a star or an outlier. We model with Bayesian analysis the X-ray spectra assuming a power-law model with the presence of an absorbing medium. We find an average unabsorbed photon index of $\Gamma=1.85$ and average hydrogen column density $\log{N_{H}}=21.07 cm^{-2}$. We find no trend of $\Gamma$ or $N_H$ with redshift and a fraction of 26% absorbed sources ($\log N_{H}>22$). We show that the XXL-1000-AGN number counts extended the number counts of the COSMOS survey to higher fluxes and are fully consistent with the Euclidean expectation. We constrain the intrinsic luminosity function of AGN in the 2-10 keV energy band where the unabsorbed X-ray flux is estimated from the X-ray spectral fit up to z=3. Finally, we demonstrate the presence of a supercluster size structure at redshift 0.14, identified by means of percolation analysis of the XXL-1000-AGN sample. The XXL survey, reaching a medium flux limit and covering a wide area is a stepping stone between current deep fields and planned wide area surveys

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

The Hubble Space Telescope Survey of M31 Satellite Galaxies. II. The Star Formation Histories of Ultrafaint Dwarf Galaxies

We present the lifetime star formation histories (SFHs) for six ultrafaint dwarf (UFD; M V > − 7.0, 4.9<log10(M*(z=0)/M⊙)<5.5 ) satellite galaxies of M31 based on deep color–magnitude diagrams constructed from Hubble Space Telescope imaging. These are the first SFHs obtained from the oldest main-sequence turnoff of UFDs outside the halo of the Milky Way (MW). We find that five UFDs formed at least 50% of their stellar mass by z = 5 (12.6 Gyr ago), similar to known UFDs around the MW, but that 10%–40% of their stellar mass formed at later times. We uncover one remarkable UFD, And xiii, which formed only 10% of its stellar mass by z = 5, and 75% in a rapid burst at z ∼ 2–3, a result that is robust to choices of underlying stellar model and is consistent with its predominantly red horizontal branch. This “young” UFD is the first of its kind and indicates that not all UFDs are necessarily quenched by reionization, which is consistent with predictions from several cosmological simulations of faint dwarf galaxies. SFHs of the combined MW and M31 samples suggest reionization did not homogeneously quench UFDs. We find that the least-massive MW UFDs (M *(z = 5) ≲ 5 × 104 M ⊙) are likely quenched by reionization, whereas more-massive M31 UFDs (M *(z = 5) ≳ 105 M ⊙) may only have their star formation suppressed by reionization and quench at a later time. We discuss these findings in the context of the evolution and quenching of UFDs

AI-Assisted vs Unassisted Identification of Prostate Cancer in Magnetic Resonance Images

Importance: Artificial intelligence (AI) assistance in magnetic resonance imaging (MRI) assessment for prostate cancer shows promise for improving diagnostic accuracy but lacks large-scale observational evidence. Objective: To evaluate whether use of AI-assisted assessment for diagnosing clinically significant prostate cancer (csPCa) on MRI is superior to unassisted readings. Design, Setting, and Participants: This diagnostic study was conducted between March and July 2024 to compare unassisted and AI-assisted diagnostic performance using the AI system developed within the international Prostate Imaging-Cancer AI (PI-CAI) Consortium. The study involved 61 readers (34 experts and 27 nonexperts) from 53 centers across 17 countries. Readers assessed prostate magnetic resonance images both with and without AI assistance, providing Prostate Imaging Reporting and Data System (PI-RADS) annotations from 3 to 5 (higher PI-RADS indicated a higher likelihood of csPCa) and patient-level suspicion scores ranging from 0 to 100 (higher scores indicated a greater likelihood of harboring csPCa). Biparametric prostate MRI examinations were included for 780 men from the PI-CAI study who were included in the newly-conducted observer study. All men within the PI-CAI study had suspicion of harboring prostate cancer, sufficient diagnostic image quality, and no prior clinically significant cancer findings. Disease presence was defined by histopathology, and absence was determined by 3 or more years of follow-up. The AI system was recalibrated using 420 Dutch examinations to generate lesion-detection maps, with AI scores ranging from 1 to 10, in which 10 indicates the highest likelihood of csPCa. The remaining 360 examinations, originating from 3 Dutch centers and 1 Norwegian center, were included in the observer study. Main Outcomes and Measures: The primary outcome was diagnosis of csPCa, evaluated using the area under the receiver operating characteristic curve and sensitivity and specificity at a PI-RADS threshold of 3 or more. The secondary outcomes included analysis at alternate operating points and reader expertise. Results: Among the 360 examinations of 360 men (median age, 65 years [IQR, 62-70 years]) who were included for testing, 122 (34%) harbored csPCa. AI assistance was associated with significantly improved performance, achieving a 3.3% increase in the area under the receiver operating characteristic curve (95% CI, 1.8%-4.9%; P <.001), from 0.882 (95% CI, 0.854-0.910) in unassisted assessments to 0.916 (95% CI, 0.893-0.938) with AI assistance. Sensitivity improved by 2.5% (95% CI, 1.1%-3.9%; P <.001), from 94.3% (95% CI, 91.9%-96.7%) to 96.8% (95% CI, 95.2%-98.5%), and specificity increased by 3.4% (95% CI, 0.8%-6.0%; P =.01), from 46.7% (95% CI, 39.4%-54.0%) to 50.1% (95% CI, 42.5%-57.7%), at a PI-RADS score of 3 or more. Secondary analyses demonstrated similar performance improvements across alternate operating points and a greater benefit of AI assistance for nonexpert readers. Conclusions and Relevance: The findings of this diagnostic study of patients suspected of harboring prostate cancer suggest that AI assistance was associated with improved radiologic diagnosis of clinically significant disease. Further research is required to investigate the generalization of outcomes and effects on workflow improvement within prospective settings