Population of Merging Compact Binaries Inferred Using Gravitational Waves through GWTC-3

We report on the population properties of compact binary mergers inferred from gravitational-wave observations of these systems during the first three LIGO-Virgo observing runs. The Gravitational-Wave Transient Catalog 3 (GWTC-3) contains signals consistent with three classes of binary mergers: binary black hole, binary neutron star, and neutron star–black hole mergers. We infer the binary neutron star merger rate to be between 10 and 1700  Gpc−3 yr−1 and the neutron star–black hole merger rate to be between 7.8 and 140  Gpc−3 yr−1, assuming a constant rate density in the comoving frame and taking the union of 90% credible intervals for methods used in this work. We infer the binary black hole merger rate, allowing for evolution with redshift, to be between 17.9 and 44  Gpc−3 yr−1 at a fiducial redshift (z=0.2). The rate of binary black hole mergers is observed to increase with redshift at a rate proportional to (1+z)κ with κ=2.9+1.7−1.8 for z≲1. Using both binary neutron star and neutron star–black hole binaries, we obtain a broad, relatively flat neutron star mass distribution extending from 1.2+0.1−0.2 to 2.0+0.3−0.3M⊙. We confidently determine that the merger rate as a function of mass sharply declines after the expected maximum neutron star mass, but cannot yet confirm or rule out the existence of a lower mass gap between neutron stars and black holes. We also find the binary black hole mass distribution has localized over- and underdensities relative to a power-law distribution, with peaks emerging at chirp masses of 8.3+0.3−0.5 and 27.9+1.9−1.8M⊙. While we continue to find that the mass distribution of a binary’s more massive component strongly decreases as a function of primary mass, we observe no evidence of a strongly suppressed merger rate above approximately 60M⊙, which would indicate the presence of a upper mass gap. Observed black hole spins are small, with half of spin magnitudes below χi≈0.25. While the majority of spins are preferentially aligned with the orbital angular momentum, we infer evidence of antialigned spins among the binary population. We observe an increase in spin magnitude for systems with more unequal-mass ratio. We also observe evidence of misalignment of spins relative to the orbital angular momentum

The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy

Background: The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations. Methods: Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves. Results: After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45–85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p  90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score. Conclusion: The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care

Genome-wide association study of classical Hodgkin lymphoma identifies key regulators of disease susceptibility

Several susceptibility loci for classical Hodgkin lymphoma (cHL) have been reported, however much of the heritable risk is unknown. Here, we perform a meta-analysis of two existing genome-wide association studies (GWAS), a new GWAS, and replication totalling 5,314 cases and 16,749 controls. We identify risk loci for all cHL at 6q22.33 (rs9482849, P=1.52 × 10-8) and for nodular sclerosis HL (NSHL) at 3q28 (rs4459895, P=9.43 × 10-17), 6q23.3 (rs6928977, P=4.62 × 10-55 11), 10p14 (rs3781093, P=9.49 × 10-13), 13q34 (rs112998813, P=4.58 × 10-8) and 16p13.13 (rs34972832, P=2.12 × 10-8). Additionally, independent loci within the HLA region are observed for NSHL (rs9269081, HLA-DPB1*03:01, Val86 in HLA-DRB1) and mixed cellularity HL (rs1633096, rs13196329, Val86 in HLA-DRB1). The new and established risk loci localise to areas of active chromatin and show an over-representation of transcription factor binding for determinants of B-cell development and immune response.In the United Kingdom, Bloodwise (LLR; 10021) provided principal funding for the study. Support from Cancer Research UK (C1298/A8362 supported by the Bobby Moore Fund) and the Lymphoma Research Trust is also acknowledged. A.S. is supported by a clinical fellowship from Cancer Research UK. For the UK-GWAS, sample and data acquisition were supported by Breast Cancer Now, the European Union and the Lymphoma Research Trust. The UK-GWAS made use of control genotyping data generated by the WTCCC. For further information, please visit the publishr's website

Proceedings of the 3rd Biennial Conference of the Society for Implementation Research Collaboration (SIRC) 2015: advancing efficient methodologies through community partnerships and team science

It is well documented that the majority of adults, children and families in need of evidence-based behavioral health interventionsi do not receive them [1, 2] and that few robust empirically supported methods for implementing evidence-based practices (EBPs) exist. The Society for Implementation Research Collaboration (SIRC) represents a burgeoning effort to advance the innovation and rigor of implementation research and is uniquely focused on bringing together researchers and stakeholders committed to evaluating the implementation of complex evidence-based behavioral health interventions. Through its diverse activities and membership, SIRC aims to foster the promise of implementation research to better serve the behavioral health needs of the population by identifying rigorous, relevant, and efficient strategies that successfully transfer scientific evidence to clinical knowledge for use in real world settings [3]. SIRC began as a National Institute of Mental Health (NIMH)-funded conference series in 2010 (previously titled the “Seattle Implementation Research Conference”; $150,000 USD for 3 conferences in 2011, 2013, and 2015) with the recognition that there were multiple researchers and stakeholdersi working in parallel on innovative implementation science projects in behavioral health, but that formal channels for communicating and collaborating with one another were relatively unavailable. There was a significant need for a forum within which implementation researchers and stakeholders could learn from one another, refine approaches to science and practice, and develop an implementation research agenda using common measures, methods, and research principles to improve both the frequency and quality with which behavioral health treatment implementation is evaluated. SIRC’s membership growth is a testament to this identified need with more than 1000 members from 2011 to the present.ii SIRC’s primary objectives are to: (1) foster communication and collaboration across diverse groups, including implementation researchers, intermediariesi, as well as community stakeholders (SIRC uses the term “EBP champions” for these groups) – and to do so across multiple career levels (e.g., students, early career faculty, established investigators); and (2) enhance and disseminate rigorous measures and methodologies for implementing EBPs and evaluating EBP implementation efforts. These objectives are well aligned with Glasgow and colleagues’ [4] five core tenets deemed critical for advancing implementation science: collaboration, efficiency and speed, rigor and relevance, improved capacity, and cumulative knowledge. SIRC advances these objectives and tenets through in-person conferences, which bring together multidisciplinary implementation researchers and those implementing evidence-based behavioral health interventions in the community to share their work and create professional connections and collaborations

Leveraging gravitational-wave memory to distinguish neutron star-black hole binaries from black hole binaries

In the observation of gravitational waves (GWs) from a compact binary coalescence where the mass of one of the companions is <5  M⊙ the nature of the object is ambiguous until the measurements of tidal effects give evidence for the presence of a neutron star (NS) or a low mass black hole (BH). The relevance of tidal effects in a neutron star-black hole (NSBH) binary system depends crucially upon the mass and the spin of the companion BH. These effects become important predominantly when the binary system is of comparable mass and/or has large aligned spins. Depending upon the masses and spins the NS can even get tidally disrupted before the innermost stable circular orbit (ISCO) is reached. The gravitational-wave signatures of various tidal effects are encoded in the phasing of the signal and in the case of tidal disruption an abrupt cutoff of the signal amplitude occurs. In this work we show that tidal effects can also be captured by the nonlinear memory of the GW signal. Although small in amplitude, nonlinear memory is present at low frequency in contrast to the oscillatory GW signal. We introduce nonlinear memory in the NSBH and binary black hole (BBH) waveform models and show how the addition of memory aids in distinguishing NSBH systems from BBH systems for a larger part of the parameter space. We discuss the recently detected events of interest by LIGO-Virgo and provide the future prospects for the third generation detectors where nonlinear memory can play a crucial role in inferring the nature of the coalescence as BBH or NSBH from its GW signal alone

Enhancing Gravitational Wave Parameter Estimation with Non-Linear Memory: Breaking the Distance-Inclination Degeneracy

International audienceIn this study, we investigate the role of the non-linear memory effect in gravitational wave (GW) parameter estimation, particularly we explore its capability to break the degeneracy between luminosity distance and inclination angle in binary coalescence events. Motivated by the rapid growth in GW detections and the increasing sensitivity of GW observatories enhancing the precision of cosmological and astrophysical measurements is crucial. We propose leveraging the non-linear memory effect -- a subtle, persistent feature in the GW signal resulting from the cumulative impact of emitted gravitational waves -- as a novel approach to enhance parameter estimation accuracy. Through a comprehensive series of injection studies, encompassing both reduced and full parameter spaces, we evaluate the effectiveness of non-linear memory in various scenarios for aligned-spin systems. Our findings demonstrate the significant potential of non-linear memory in resolving the inclination-distance degeneracy, particularly for events with high signal-to-noise ratios (SNR $>$ 60) for the current generation of detectors and in the context of future detector sensitivities such as the planned LIGO A$^\sharp$ upgrade. The results also suggest that excluding non-linear memory from parameter estimation could introduce significant systematics in future LIGO A$^\sharp$ detections. This observation will hold even greater weight for next-generation detectors, highlighting the importance of including non-linear memory in GW models for achieving high-accuracy measurements for gravitational wave (GW) astronomy

Enhancing Gravitational Wave Parameter Estimation with Non-Linear Memory: Breaking the Distance-Inclination Degeneracy

International audienceIn this study, we investigate the role of the non-linear memory effect in gravitational wave (GW) parameter estimation, particularly we explore its capability to break the degeneracy between luminosity distance and inclination angle in binary coalescence events. Motivated by the rapid growth in GW detections and the increasing sensitivity of GW observatories enhancing the precision of cosmological and astrophysical measurements is crucial. We propose leveraging the non-linear memory effect -- a subtle, persistent feature in the GW signal resulting from the cumulative impact of emitted gravitational waves -- as a novel approach to enhance parameter estimation accuracy. Through a comprehensive series of injection studies, encompassing both reduced and full parameter spaces, we evaluate the effectiveness of non-linear memory in various scenarios for aligned-spin systems. Our findings demonstrate the significant potential of non-linear memory in resolving the inclination-distance degeneracy, particularly for events with high signal-to-noise ratios (SNR $>$ 60) for the current generation of detectors and in the context of future detector sensitivities such as the planned LIGO A$^\sharp$ upgrade. The results also suggest that excluding non-linear memory from parameter estimation could introduce significant systematics in future LIGO A$^\sharp$ detections. This observation will hold even greater weight for next-generation detectors, highlighting the importance of including non-linear memory in GW models for achieving high-accuracy measurements for gravitational wave (GW) astronomy