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Universal depression screening in youth typically focuses on strategies for identifying current distress and impairment. However, these protocols also play a critical role in primary prevention initiatives that depend on correctly estimating future depression risk. Thus, the present study aimed to identify the best screening approach for predicting depression onset in youth.
Two multi-wave longitudinal studies (N = 591, AgeM = 11.74; N = 348, AgeM = 12.56) were used as the ‘test’ and ‘validation’ datasets among youth who did not present with a history of clinical depression. Youth and caregivers completed inventories for depressive symptoms, adversity exposure (including maternal depression), social/academic impairment, cognitive vulnerabilities (rumination, dysfunctional attitudes, and negative cognitive style), and emotional predispositions (negative and positive affect) at baseline. Subsequently, multi-informant diagnostic interviews were completed every 6 months for 2 years.
Self-reported rumination, social/academic impairment, and negative affect best predicted first depression onsets in youth across both samples. Self- and parent-reported depressive symptoms did not consistently predict depression onset after controlling for other predictors. Youth with high scores on the three inventories were approximately twice as likely to experience a future first depressive episode compared to the sample average. Results suggested that one's likelihood of developing depression could be estimated based on subthreshold and threshold risk scores.
Most pediatric depression screening protocols assess current manifestations of depressive symptoms. Screening for prospective first onsets of depressive episodes can be better accomplished via an algorithm incorporating rumination, negative affect, and impairment.
The search for life in the Universe is a fundamental problem of astrobiology and modern science. The current progress in the detection of terrestrial-type exoplanets has opened a new avenue in the characterization of exoplanetary atmospheres and in the search for biosignatures of life with the upcoming ground-based and space missions. To specify the conditions favourable for the origin, development and sustainment of life as we know it in other worlds, we need to understand the nature of global (astrospheric), and local (atmospheric and surface) environments of exoplanets in the habitable zones (HZs) around G-K-M dwarf stars including our young Sun. Global environment is formed by propagated disturbances from the planet-hosting stars in the form of stellar flares, coronal mass ejections, energetic particles and winds collectively known as astrospheric space weather. Its characterization will help in understanding how an exoplanetary ecosystem interacts with its host star, as well as in the specification of the physical, chemical and biochemical conditions that can create favourable and/or detrimental conditions for planetary climate and habitability along with evolution of planetary internal dynamics over geological timescales. A key linkage of (astro)physical, chemical and geological processes can only be understood in the framework of interdisciplinary studies with the incorporation of progress in heliophysics, astrophysics, planetary and Earth sciences. The assessment of the impacts of host stars on the climate and habitability of terrestrial (exo)planets will significantly expand the current definition of the HZ to the biogenic zone and provide new observational strategies for searching for signatures of life. The major goal of this paper is to describe and discuss the current status and recent progress in this interdisciplinary field in light of presentations and discussions during the NASA Nexus for Exoplanetary System Science funded workshop ‘Exoplanetary Space Weather, Climate and Habitability’ and to provide a new roadmap for the future development of the emerging field of exoplanetary science and astrobiology.
A national need is to prepare for and respond to accidental or intentional disasters categorized as chemical, biological, radiological, nuclear, or explosive (CBRNE). These incidents require specific subject-matter expertise, yet have commonalities. We identify 7 core elements comprising CBRNE science that require integration for effective preparedness planning and public health and medical response and recovery. These core elements are (1) basic and clinical sciences, (2) modeling and systems management, (3) planning, (4) response and incident management, (5) recovery and resilience, (6) lessons learned, and (7) continuous improvement. A key feature is the ability of relevant subject matter experts to integrate information into response operations. We propose the CBRNE medical operations science support expert as a professional who (1) understands that CBRNE incidents require an integrated systems approach, (2) understands the key functions and contributions of CBRNE science practitioners, (3) helps direct strategic and tactical CBRNE planning and responses through first-hand experience, and (4) provides advice to senior decision-makers managing response activities. Recognition of both CBRNE science as a distinct competency and the establishment of the CBRNE medical operations science support expert informs the public of the enormous progress made, broadcasts opportunities for new talent, and enhances the sophistication and analytic expertise of senior managers planning for and responding to CBRNE incidents.
Waiting periods and deadlines are so ubiquitous that we often take them for granted. Yet they form a critical part of any democratic architecture. When a precise moment or amount of time is given political importance, we ought to understand why this is so. The Political Value of Time explores the idea of time within democratic theory and practice. Elizabeth F. Cohen demonstrates how political procedures use quantities of time to confer and deny citizenship rights. Using specific dates and deadlines, states carve boundaries around a citizenry. As time is assigned a form of political value it comes to be used to transact over rights. Cohen concludes with a normative analysis of the ways in which the devaluation of some people's political time constitutes a widely overlooked form of injustice. This book shows readers how and why they need to think about time if they want to understand politics.
Acinetobacter spp. are important healthcare pathogens, being closely linked to antibiotic resistance and outbreaks worldwide. Although such species are rarely observed in patients with cystic fibrosis (CF), we describe the characteristics of 53 strains of Acinetobacter spp. isolated from the sputum of 39 Brazilian patients with CF. The species distribution was A. baumannii (n = 29), A. pittii (n = 13), A. nosocomialis (n = 8), A. seifertii (n = 1), A. soli (n = 1) and A. variabilis (n = 1) determined by partial rpoB gene sequencing. Sixteen strains (10 A. baumannii, 3 A. pittii and 3 A. nosocomialis) were multidrug-resistant (MDR) by disk diffusion test (30%) and eight MDR carbapenem-resistant A. baumannii strains harboured the blaOXA-23-like oxacillinase gene. Thirty-three sequence types (STs) were identified by multilocus sequence typing of which eight were novel (A. baumannii: 843, 844, 845, 847, 848; A. pitti: 643; A. nosocomialis: 862 and A. seifertii: 846); six STs (2 A. baumannii, 3 A. pittii and 1 A. nosocomialis) were found in more than one patient. Four strains of A. baumannii were assigned to two common clonal complexes (CCs), namely, CC1 (ST1, ST20 and ST160), and CC79 (ST79). This study underlines the extensive species diversity of Acinetobacter spp. strains in CF lung infections which may present difficulties for therapy due to significant antimicrobial resistance.
In order to contribute to the discussion of Holocene climate changes, four sediment cores were collected from the northern Brazilian Amazonia lowland. These cores were studied through pollen analysis and sedimentary features, and the results were discussed within a chronological framework provided by radiocarbon dating. The cores were sampled from fluvial terraces representative of channel, floodplain/lake and crevasse splay deposits formed since the mid-Holocene. The pollen samples derive from floodplain/lake deposits and the pollen grains are mainly composed by families Moraceae, Euphorbiaceae, Caesalpiniaceae, Fabaceae, Rubiaceae, Melastomataceae, Combretaceae, Sapindaceae, Poaceae, Cyperaceae, Aizoaceae, Apiaceae and genus Sebastiana. The pollen data suggest no significant vegetation changes in the study area for the past 4808–4886 cal yr BP. This led to proposing stable climatic conditions since at least the middle Holocene. Such a finding is contrary to the occurrence of a dry period during the middle Holocene. The stabilization of the relative sea level about 6000 cal yr BP along the northern Brazilian littoral may have influenced the water table, and favored the establishment and maintenance of Amazonian lowland forest during the mid- and late Holocene. In addition, this process may have attenuated the impact of that dry period in areas under most fluvial influence.
Schizotypal traits are considered a phenotypic-indicator of schizotypy, a latent personality organization reflecting a putative liability for psychosis. To date, no previous study has examined the comparability of factorial structures across samples originating from different countries and cultures. The main goal was to evaluate the factorial structure and reliability of the Schizotypal Personality Questionnaire (SPQ) scores by amalgamating data from studies conducted in 12 countries and across 21 sites.
The overall sample consisted of 27 001 participants (37.5% males, n = 4251 drawn from the general population). The mean age was 22.12 years (s.d. = 6.28, range 16–55 years). The SPQ was used. Confirmatory factor analysis (CFA) and Multilevel CFA (ML-CFA) were used to evaluate the factor structure underlying the SPQ scores.
At the SPQ item level, the nine factor and second-order factor models showed adequate goodness-of-fit. At the SPQ subscale level, three- and four-factor models displayed better goodness-of-fit indices than other CFA models. ML-CFA showed that the intraclass correlation coefficients values were lower than 0.106. The three-factor model showed adequate goodness of fit indices in multilevel analysis. The ordinal α coefficients were high, ranging from 0.73 to 0.94 across individual samples, and from 0.84 to 0.91 for the combined sample.
The results are consistent with the conceptual notion that schizotypal personality is a multifaceted construct and support the validity and utility of SPQ in cross-cultural research. We discuss theoretical and clinical implications of our results for diagnostic systems, psychosis models and cross-national mental health strategies.