Recoiling black holes: prospects for detection and implications of spin alignment

Supermassive black hole (BH) mergers produce powerful gravitational wave (GW) emission. Asymmetry in this emission imparts a recoil kick to the merged BH, which can eject the BH from its host galaxy altogether. Recoiling BHs could be observed as offset active galactic nuclei (AGN). Several candidates have been identified, but systematic searches have been hampered by large uncertainties regarding their observability. By extracting merging BHs and host galaxy properties from the Illustris cosmological simulations, we have developed a comprehensive model for recoiling AGN. Here, for the first time, we model the effects of BH spin alignment and recoil dynamics based on the gas-richness of host galaxies. We predict that if BH spins are not highly aligned, seeing-limited observations could resolve offset AGN, making them promising targets for all-sky surveys. For randomly-oriented spins, less than about 10 spatially-offset AGN may be detectable in HST-COSMOS, and > 10^3 could be found with Pan-STARRS, LSST, Euclid, and WFIRST. Nearly a thousand velocity-offset AGN are predicted within the SDSS footprint; the rarity of large broad-line offsets among SDSS quasars is likely due in part to selection effects but suggests that spin alignment plays a role in suppressing recoils. Nonetheless, in our most physically motivated model where alignment occurs only in gas-rich mergers, hundreds of offset AGN should be found in all-sky surveys. Our findings strongly motivate a dedicated search for recoiling AGN.Comment: 30 pages, 19 figures. Accepted to MNRAS after minor revision

The Technological Development of Minimally Invasive Spine Surgery

Minimally invasive spine surgery has its roots in the mid-twentieth century with a few surgeons and a few techniques, but it has now developed into a large field of progressive spinal surgery. A wide range of techniques are now called \ minimally invasive,\ and case reports are submitted constantly with new \ minimally invasive\ approaches to spinal pathology. As minimally invasive spine surgery has become more mainstream over the past ten years, in this paper we discuss its history and development. © 2014 Laura A. Snyder et al

Maternal Depressive Symptoms Predict General Liability in Child Psychopathology

Objective: The current study examines how maternal depressive symptoms relate to child psychopathology when structured via the latent bifactor model of psychopathology, a new organizational structure of psychopathological symptoms consisting of a general common psychopathology factor (p-factor) and internalizing- and externalizing-specific risk. Method: Maternal report of depressive symptoms (Beck Depression Inventory – II) and child psychopathological symptoms (Child Behavior Checklist and Children’s Behavior Questionnaire) were provided by 554 mother-child pairs. Children in the sample were 7.7 years old on average (SD = 1.35, range = 5–11 years), and were 49.8% female, 46% Latinx, and 67% White, 6% Black, 5% Asian/Pacific Islander, and 21% multiracial. Results: Maternal depressive symptoms were positively associated with the child p-factor but not with the internalizing- or externalizing-specific factors. We did not find evidence of sex/gender or race/ethnicity moderation when using latent factors of psychopathology. Consistent with past research, maternal depressive symptoms were positively associated with internalizing and externalizing composite scores on the Child Behavior Checklist. Conclusions: Findings suggest that maternal depressive symptoms are associated with transdiagnostic risk for broad child psychopathology (p-factor). Whereas the traditional Achenbach-style approach of psychopathological assessment suggests that maternal depressive symptoms are associated with both child internalizing and externalizing problems, the latent bifactor model suggests that these associations may be accounted for by risk pathways related to the p-factor rather than internalizing or externalizing specific risk. We discuss clinical and research implications of using a latent bifactor structure of psychopathology to understand how maternal depression may impact children’s mental health

Temperament Factors and Dimensional, Latent Bifactor Models of child psychopathology: Transdiagnostic and Specific Associations in Two Youth Samples

Common emotional and behavioral symptoms co-occur and are associated with core temperament factors. This study investigated links between temperament and dimensional, latent psychopathology factors, including a general common psychopathology factor (p factor) and specific latent internalizing and externalizing liabilities, as captured by a bifactor model, in two independent samples of youth. Specifically, we tested the hypothesis that temperament factors of negative affectivity (NA), positive affectivity (PA), and effortful control (EC) could serve as both transdiagnostic and specific risks in relation to recent bifactor models of child psychopathology. Sample 1 included 571 youth (average age 13.6, SD = 2.37, range 9.3–17.5) with both youth and parent report. Sample 2 included 554 preadolescent children (average age 7.7, SD = 1.35, range = 5–11 years) with parent report. Structural equation modeling showed that the latent bifactor models fit in both samples. Replicated in both samples, the p factor was associated with lower EC and higher NA (transdiagnostic risks). Several specific risks replicated in both samples after controlling for co-occurring symptoms via the p factor: internalizing was associated with higher NA and lower PA, lower EC related to externalizing problems

Differential Associations of Deprivation and Threat With Cognitive Control and Fear Conditioning in Early Childhood

Early-life adversity (ELA) is strongly associated with risk for psychopathology. Within adversity, deprivation, and threat may lead to psychopathology through different intermediary pathways. Specifically, deprivation, defined as the absence of expected cognitive and social inputs, is associated with lower performance on complex cognitive tasks whereas threatening experiences, defined as the presence of experiences that reflect harm to the child, are associated with atypical fear learning and emotional processes. However, distinct associations of deprivation and threat on behavioral outcomes have not been examined in early childhood. The present study examines how deprivation and threat are associated with cognitive and emotional outcomes in early childhood. Children 4–7 years old completed behavioral tasks assessing cognitive control (N = 58) and fear conditioning (N = 45); deprivation and threat were assessed using child interview and parent questionnaires. Regression analyses were performed including deprivation and threat scores and controls for age, gender, and IQ. Because this is the first time these variables have been examined in early childhood, interactions with age were also examined. Deprivation, but not threat was associated with worse performance on the cognitive control task. Threat, but not deprivation interacted with age to predict fear learning. Young children who experienced high levels of threat showed evidence of fear learning measured by differential skin conductance response even at the earliest age measured. In contrast, for children not exposed to threat, fear learning emerged only in older ages. Children who experienced higher levels of threat also showed blunted reactivity measured by amplitude of skin conductance response to the reinforced stimuli regardless of age. Results suggest differential influences of deprivation and threat on cognitive and emotional outcomes even in early childhood. Future work should examine the neural mechanisms underlying these behavioral changes and link changes with increased risk for negative outcomes associated with adversity exposure, such as psychopathology

A Pharmacology-Based Enrichment Program for Undergraduates Promotes Interest in Science

There is a strong need to increase the number of undergraduate students who pursue careers in science to provide the “fuel” that will power a science and technology–driven U.S. economy. Prior research suggests that both evidence-based teaching methods and early undergraduate research experiences may help to increase retention rates in the sciences. In this study, we examined the effect of a program that included 1) a Summer enrichment 2-wk minicourse and 2) an authentic Fall research course, both of which were designed specifically to support students\u27 science motivation. Undergraduates who participated in the pharmacology-based enrichment program significantly improved their knowledge of basic biology and chemistry concepts; reported high levels of science motivation; and were likely to major in a biological, chemical, or biomedical field. Additionally, program participants who decided to major in biology or chemistry were significantly more likely to choose a pharmacology concentration than those majoring in biology or chemistry who did not participate in the enrichment program. Thus, by supporting students\u27 science motivation, we can increase the number of students who are interested in science and science careers

Galaxy morphology and star formation in the Illustris Simulation at

We study how optical galaxy morphology depends on mass and star formation rate (SFR) in the Illustris Simulation. To do so, we measure automated galaxy structures in 10 808 simulated galaxies at z = 0 with stellar masses 10[superscript 9.7] < M*/Mȯ < 10[superscript12.3]. We add observational realism to idealized synthetic images and measure non-parametric statistics in rest-frame optical and near-IR images from four directions. We find that Illustris creates a morphologically diverse galaxy population, occupying the observed bulge strength locus and reproducing median morphology trends versus stellar mass, SFR, and compactness. Morphology correlates realistically with rotation, following classification schemes put forth by kinematic surveys. Type fractions as a function of environment agree roughly with data. These results imply that connections among mass, star formation, and galaxy structure arise naturally from models matching global star formation and halo occupation functions when simulated with accurate methods. This raises a question of how to construct experiments on galaxy surveys to better distinguish between models. We predict that at fixed halo mass near 10[superscript 12] Mȯ, disc-dominated galaxies have higher stellar mass than bulge-dominated ones, a possible consequence of the Illustris feedback model. While Illustris galaxies at M* ∼ 10[superscript 11] Mȯ have a reasonable size distribution, those at M* ∼ 10[superscript 10] Mȯ have half-light radii larger than observed by a factor of 2. Furthermore, at M* ∼ 10[superscript 10.5]–10[superscript 11] Mȯ, a relevant fraction of Illustris galaxies have distinct ‘ring-like’ features, such that the bright pixels have an unusually wide spatial extent

Active Learning Pipeline for Brain Mapping in a High Performance Computing Environment

This paper describes a scalable active learning pipeline prototype for large-scale brain mapping that leverages high performance computing power. It enables high-throughput evaluation of algorithm results, which, after human review, are used for iterative machine learning model training. Image processing and machine learning are performed in a batch layer. Benchmark testing of image processing using pMATLAB shows that a 100$\times$ increase in throughput (10,000%) can be achieved while total processing time only increases by 9% on Xeon-G6 CPUs and by 22% on Xeon-E5 CPUs, indicating robust scalability. The images and algorithm results are provided through a serving layer to a browser-based user interface for interactive review. This pipeline has the potential to greatly reduce the manual annotation burden and improve the overall performance of machine learning-based brain mapping.Comment: 6 pages, 5 figures, submitted to IEEE HPEC 2020 proceeding

Molecular Recognition of Glycan-Bearing Glycomacromolecules Presented at Membrane Surfaces by Lectins: An NMR View

Lectin–glycan interactions are at the heart of a multitude of biological events. Glycans are usually presented in a multivalent manner on the cell surface as part of the so-called glycocalyx, where they interact with other entities. This multivalent presentation allows us to overcome the typical low affinities found for individual glycan–lectin interactions. Indeed, the presentation of glycans may drastically impact their binding by lectins, highly affecting the corresponding binding affinity and even selectivity. In this context, we herein present the study of the interaction of a variety of homo- and heteromultivalent lactose-functionalized glycomacromolecules and their lipid conjugates with two human galectins. We have employed as ligands the glycomacromolecules, as well as liposomes decorated with those structures, to evaluate their interactions in a cell-mimicking environment. Key details of the interaction have been unravelled by NMR experiments, both from the ligand and receptor perspectives, complemented by cryo-electron microscopy methods and molecular dynamics simulations.M.H. and L.H. thank the DFG for support through the ViroCarb research consortium (HA5950/5-2) and the CeMSA@HHU (Center for Molecular and Structural Analytics @ Heinrich-Heine University) for recording the mass spectrometric and the NMR-spectroscopic data for the structural conformation of the glycomacromolecules and their lipid conjugates. The CIC bioGUNE EM platform is also thanked for infrastructural support during cryo-EM data collection. The group in Spain thank the European Research Council (RECGLYCANMR, Advanced grant no. 788143), MCIN/AEI/10.13039/501100011033 for grants PDI2021-1237810B-C21, PID2021-126130OB-I00, CEX2021-001136-S, and CIBERES, an initiative of Instituto de Salud Carlos III (ISCIII), Madrid, Spain, for generous funding