StepMix: A Python Package for Pseudo-Likelihood Estimation of Generalized Mixture Models with External Variables

StepMix is an open-source software package for the pseudo-likelihood estimation (one-, two- and three-step approaches) of generalized finite mixture models (latent profile and latent class analysis) with external variables (covariates and distal outcomes). In many applications in social sciences, the main objective is not only to cluster individuals into latent classes, but also to use these classes to develop more complex statistical models. These models generally divide into a measurement model that relates the latent classes to observed indicators, and a structural model that relates covariates and outcome variables to the latent classes. The measurement and structural models can be estimated jointly using the so-called one-step approach or sequentially using stepwise methods, which present significant advantages for practitioners regarding the interpretability of the estimated latent classes. In addition to the one-step approach, StepMix implements the most important stepwise estimation methods from the literature, including the bias-adjusted three-step methods with BCH and ML corrections and the more recent two-step approach. These pseudo-likelihood estimators are presented in this paper under a unified framework as specific expectation-maximization subroutines. To facilitate and promote their adoption among the data science community, StepMix follows the object-oriented design of the scikit-learn library and provides interfaces in both Python and R.Comment: Sacha Morin and Robin Legault contributed equall

Quasars Are Not Light-Bulbs: Testing Models of Quasar Lifetimes with the Observed Eddington Ratio Distribution

We use the observed distribution of Eddington ratios as a function of supermassive black hole (BH) mass to constrain models of AGN lifetimes and lightcurves. Given the observed AGN luminosity function, a model for AGN lifetimes (time above a given luminosity) translates directly to a predicted Eddington ratio distribution. Models for self-regulated BH growth, in which feedback produces a 'blowout' decay phase after some peak luminosity (shutting down accretion) make specific predictions for the lifetimes distinct from those expected if AGN are simply gas starved (without feedback) and very different from simple phenomenological 'light bulb' models. Present observations of the Eddington ratio distribution, spanning 5 decades in Eddington ratio, 3 in BH mass, and redshifts z=0-1, agree with the predictions of self-regulated models, and rule out 'light-bulb', pure exponential, and gas starvation models at high significance. We compare the Eddington ratio distributions at fixed BH mass and fixed luminosity (both are consistent, but the latter are much less constraining). We present empirical fits to the lifetime distribution and show how the Eddington ratio distributions place tight limits on AGN lifetimes at various luminosities. We use this to constrain the shape of the typical AGN lightcurve, and provide simple analytic fits. Given independent constraints on episodic lifetimes, most local BHs must have gained their mass in no more than a couple of bright episodes, in agreement with merger-driven fueling models.Comment: 21 pages, 13 figures, accepted to ApJ (revised to match accepted version; modeling and tests of redshift evolution added

The Evolution of Compact Binary Star Systems

We review the formation and evolution of compact binary stars consisting of white dwarfs (WDs), neutron stars (NSs), and black holes (BHs). Binary NSs and BHs are thought to be the primary astrophysical sources of gravitational waves (GWs) within the frequency band of ground-based detectors, while compact binaries of WDs are important sources of GWs at lower frequencies to be covered by space interferometers (LISA). Major uncertainties in the current understanding of properties of NSs and BHs most relevant to the GW studies are discussed, including the treatment of the natal kicks which compact stellar remnants acquire during the core collapse of massive stars and the common envelope phase of binary evolution. We discuss the coalescence rates of binary NSs and BHs and prospects for their detections, the formation and evolution of binary WDs and their observational manifestations. Special attention is given to AM CVn-stars -- compact binaries in which the Roche lobe is filled by another WD or a low-mass partially degenerate helium-star, as these stars are thought to be the best LISA verification binary GW sources.Comment: 105 pages, 18 figure

Gas kinematics in powerful radio galaxies at z ∼2: Energy supply from star formation, AGN, and radio jets⋆

We compare the kinetic energy and momentum injection rates from intense star formation, bolometric AGN radiation, and radio jets with the kinetic energy and momentum observed in the warm ionized gas in 24 powerful radio galaxies at z~2. These galaxies are amongst our best candidates for being massive galaxies near the end of their active formation period, when intense star formation, quasar activity, and powerful radio jets all co-exist. All galaxies have VLT/SINFONI imaging spectroscopy of the rest-frame optical line emission, showing emission-line regions with large velocity offsets (up to 1500 km/s) and line widths (typically 800-1000 km/s) consistent with very turbulent, often outflowing gas. As part of the HeRGE sample, they also have FIR estimates of the star formation and quasar activity obtained with Herschel/PACS and SPIRE, which enables us to measure the relative energy and momentum release from each of the three main sources of feedback in massive, star-forming AGN host galaxies during their most rapid formation phase. We find that star formation falls short by factors 10-1000 of providing the energy and momentum necessary to power the observed gas kinematics. The obscured quasars in the nuclei of these galaxies provide enough energy and momentum in about half of the sample, however, only if these are transfered to the gas relatively efficiently. We compare with theoretical and observational constraints on the efficiency of the energy and momentum transfer from jet and AGN radiation, which advocates that the radio jet is the main driver of the gas kinematics.Comment: A&A accepted. Comments welcom

Role for miR-204 in human pulmonary arterial hypertension

Reduced miR-204 expression facilitates the excessive proliferation and apoptosis resistance of pulmonary artery smooth muscle cells characteristic of human pulmonary arterial hypertension

Estrogen receptor transcription and transactivation: Basic aspects of estrogen action

Estrogen signaling has turned out to be much more complex and exciting than previously thought; the paradigm shift in our understanding of estrogen action came in 1996, when the presence of a new estrogen receptor (ER), ERβ, was reported. An intricate interplay between the classical ERα and the novel ERβ is of paramount importance for the final biological effect of estrogen in different target cells

External validation of prognostic models to predict stillbirth using the International Prediction of Pregnancy Complications (IPPIC) Network database: an individual participant data meta-analysis

Objective Stillbirth is a potentially preventable complication of pregnancy. Identifying women at high risk of stillbirth can guide decisions on the need for closer surveillance and timing of delivery in order to prevent fetal death. Prognostic models have been developed to predict the risk of stillbirth, but none has yet been validated externally. In this study, we externally validated published prediction models for stillbirth using individual participant data (IPD) meta-analysis to assess their predictive performance. Methods MEDLINE, EMBASE, DH-DATA and AMED databases were searched from inception to December 2020 to identify studies reporting stillbirth prediction models. Studies that developed or updated prediction models for stillbirth for use at any time during pregnancy were included. IPD from cohorts within the International Prediction of Pregnancy Complications (IPPIC) Network were used to validate externally the identified prediction models whose individual variables were available in the IPD. The risk of bias of the models and cohorts was assessed using the Prediction study Risk Of Bias ASsessment Tool (PROBAST). The discriminative performance of the models was evaluated using the C-statistic, and calibration was assessed using calibration plots, calibration slope and calibration-in-the-large. Performance measures were estimated separately in each cohort, as well as summarized across cohorts using random-effects meta-analysis. Clinical utility was assessed using net benefit. Results Seventeen studies reporting the development of 40 prognostic models for stillbirth were identified. None of the models had been previously validated externally, and the full model equation was reported for only one-fifth (20%, 8/40) of the models. External validation was possible for three of these models, using IPD from 19 cohorts (491 201 pregnant women) within the IPPIC Network database. Based on evaluation of the model development studies, all three models had an overall high risk of bias, according to PROBAST. In the IPD meta-analysis, the models had summary C-statistics ranging from 0.53 to 0.65 and summary calibration slopes ranging from 0.40 to 0.88, with risk predictions that were generally too extreme compared with the observed risks. The models had little to no clinical utility, as assessed by net benefit. However, there remained uncertainty in the performance of some models due to small available sample sizes. Conclusions The three validated stillbirth prediction models showed generally poor and uncertain predictive performance in new data, with limited evidence to support their clinical application. The findings suggest methodological shortcomings in their development, including overfitting. Further research is needed to further validate these and other models, identify stronger prognostic factors and develop more robust prediction models. (c) 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.Peer reviewe

Clinical Pathway and Monthly Feedback Improve Adherence to Antibiotic Guideline Recommendations for Community-Acquired Pneumonia

Background: Compliance with community-acquired pneumonia (CAP) guidelines remains poor despite a substantial body of evidence indicating that guideline-concordant care improves patient outcomes. The aim of this study was to compare the relative effectiveness of a general educational and a targeted emergency department intervention on improving physicians’ concordance with CAP guidelines. Methods: Two distinct interventions were implemented over specific time periods. The first intervention was educational, focusing on the development of local CAP guidelines and their dissemination through hospital-wide educational programmes. The second intervention was a targeted one for the emergency department, where a clinical pathway for the initial management of CAP patients was introduced, followed by monthly feedback to the emergency department (ED) physicians about concordance rates with the guidelines. Data on the concordance rate to CAP guidelines was collected from a retrospective chart review. Results: A total of 398 eligible patient records were reviewed to measure concordance to CAP guidelines over the study period. Concordance rates during the baseline and educational intervention periods were similar (28.1% vs. 31.2%; p > 0.05). Significantly more patients were treated in accordance with the CAP guidelines after the ED focused intervention when compared to the baseline (61.5% vs. 28.1%; p < 0.05) or educational period (61.5% vs. 31.2%; p < 0.05). Conclusions: A targeted intervention with a CAP clinical pathway and monthly feedback was a successful strategy to increase adherence to empirical antibiotic recommendations in CAP guidelines

Ontogenetic phase shifts in metabolism in a flounder Paralichthys olivaceus

Size-scaling metabolism is widely considered to be of significant importance in biology and ecology. Thus, allometric relationships between metabolic rate (VO2) and body mass (M), V O25aiMb, have long been a topic of interest and speculation. It has been proposed that intraspecifically metabolic rate scales isometrically or near isometrically with body mass during the early life history in fishes, invertebrates, birds and mammals. We developed a new perspective on intraspecific size-scaling metabolism through determination of metabolic rate in the Japanese flounder, Paralichthys olivaceus, during their early life stages spanning approximately four orders of magnitude in body mass. With the increase of body mass, the Japanese flounder had four distinct negative allometric phases in which three stepwise increases in scaling constants (ai, i51?4), i.e. ontogenetic phase shifts in metabolism, occurred with growth during its early life stages at around 0.002, 0.01 and 0.2 g, maintaining each scaling exponent constant in each phase (b50.831).These shifts in metabolism during the early life stages are similar to the tiger puffer, Takifugu rubripes. Our results indicate that ontogenetic phase shifts in metabolism are key to understanding intraspecific size-scaling metabolism in fishes

Jdp2 downregulates Trp53 transcription to promote leukaemogenesis in the context of Trp53 heterozygosity

We performed a genetic screen in mice to identify candidate genes that are associated with leukaemogenesis in the context of Trp53 heterozygosity. To do this we generated Trp53 heterozygous mice carrying the T2/Onc transposon and SB11 transposase alleles to allow transposon-mediated insertional mutagenesis to occur. From the resulting leukaemias/lymphomas that developed in these mice, we identified nine loci that are potentially associated with tumour formation in the context of Trp53 heterozygosity, including AB041803 and the Jun dimerization protein 2 (Jdp2). We show that Jdp2 transcriptionally regulates the Trp53 promoter, via an atypical AP-1 site, and that Jdp2 expression negatively regulates Trp53 expression levels. This study is the first to identify a genetic mechanism for tumour formation in the context of Trp53 heterozygosity