Are there researcher allegiance effects in diagnostic validation studies of the PHQ-9? : A systematic review and meta-analysis

OBJECTIVES: To investigate whether an authorship effect is found that leads to better performance in studies conducted by the original developers of the Patient Health Questionnaire (PHQ-9) (allegiant studies). DESIGN: Systematic review with random effects bivariate diagnostic meta-analysis. Search strategies included electronic databases, examination of reference lists and forward citation searches. INCLUSION CRITERIA: Included studies provided sufficient data to calculate the diagnostic accuracy of the PHQ-9 against a gold standard diagnosis of major depression using the algorithm or the summed item scoring method at cut-off point 10. DATA EXTRACTION: Descriptive information, methodological quality criteria and 2×2 contingency tables. RESULTS: Seven allegiant and 20 independent studies reported the diagnostic performance of the PHQ-9 using the algorithm scoring method. Pooled diagnostic OR (DOR) for the allegiant group was 64.40, and 15.05 for non-allegiant studies group. The allegiance status was a significant predictor of DOR variation (p<0.0001).Five allegiant studies and 26 non-allegiant studies reported the performance of the PHQ-9 at recommended cut-off point of 10. Pooled DOR for the allegiant group was 49.31, and 24.96 for the non-allegiant studies. The allegiance status was a significant predictor of DOR variation (p=0.015).Some potential alternative explanations for the observed authorship effect including differences in study characteristics and quality were found, although it is not clear how some of them account for the observed differences. CONCLUSIONS: Allegiant studies reported better performance of the PHQ-9. Allegiance status was predictive of variation in the DOR. Based on the observed differences between independent and non-independent studies, we were unable to conclude or exclude that allegiance effects are present in studies examining the diagnostic performance of the PHQ-9. This study highlights the need for future meta-analyses of diagnostic validation studies of psychological measures to evaluate the impact of researcher allegiance in the primary studies

Predicting and preventing relapse of depression in primary care

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STAT4 is expressed in neutrophils and promotes antimicrobial immunity

Signal transducer and activator of transcription 4 (STAT4) is expressed in hematopoietic cells and plays a key role in the differentiation of T helper 1 cells. Although STAT4 is required for immunity to intracellular pathogens, the T cell-independent protective mechanisms of STAT4 are not clearly defined. In this report, we demonstrate that STAT4-deficient mice were acutely sensitive to methicillin-resistant Staphylococcus aureus (MRSA) infection. We show that STAT4 was expressed in neutrophils and activated by IL-12 via a JAK2-dependent pathway. We demonstrate that STAT4 was required for multiple neutrophil functions, including IL-12-induced ROS production, chemotaxis, and production of the neutrophil extracellular traps. Importantly, myeloid-specific and neutrophil-specific deletion of STAT4 resulted in enhanced susceptibility to MRSA, demonstrating the key role of STAT4 in the in vivo function of these cells. Thus, these studies identify STAT4 as an essential regulator of neutrophil functions and a component of innate immune responses in vivo

Cross-National Differences in Victimization : Disentangling the Impact of Composition and Context

Varying rates of criminal victimization across countries are assumed to be the outcome of countrylevel structural constraints that determine the supply ofmotivated o¡enders, as well as the differential composition within countries of suitable targets and capable guardianship. However, previous empirical tests of these ‘compositional’ and ‘contextual’ explanations of cross-national di¡erences have been performed upon macro-level crime data due to the unavailability of comparable individual-level data across countries. This limitation has had two important consequences for cross-national crime research. First, micro-/meso-level mechanisms underlying cross-national differences cannot be truly inferred from macro-level data. Secondly, the e¡ects of contextual measures (e.g. income inequality) on crime are uncontrolled for compositional heterogeneity. In this paper, these limitations are overcome by analysing individual-level victimization data across 18 countries from the International CrimeVictims Survey. Results from multi-level analyses on theft and violent victimization indicate that the national level of income inequality is positively related to risk, independent of compositional (i.e. micro- and meso-level) di¡erences. Furthermore, crossnational variation in victimization rates is not only shaped by di¡erences in national context, but also by varying composition. More speci¢cally, countries had higher crime rates the more they consisted of urban residents and regions with lowaverage social cohesion.

Global Carbon Budget 2015

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates as well as consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (E-FF) are based on energy statistics and cement production data, while emissions from land-use change (E-LUC), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (G(ATM)) is computed from the annual changes in concentration. The mean ocean CO2 sink (S-OCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in S-OCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (S-LAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2, and land-cover change (some including nitrogen-carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as +/- 1 sigma, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (20052014), E-FF was 9.0 +/- 0.5 GtC yr(-1) E-LUC was 0.9 +/- 0.5 GtC yr(-1), GATM was 4.4 +/- 0.1 GtC yr(-1), S-OCEAN was 2.6 +/- 0.5 GtC yr(-1), and S LAND was 3.0 +/- 0.8 GtC yr(-1). For the year 2014 alone, E FF grew to 9.8 +/- 0.5 GtC yr(-1), 0.6% above 2013, continuing the growth trend in these emissions, albeit at a slower rate compared to the average growth of 2.2% yr(-1) that took place during 2005-2014. Also, for 2014, E-LUC was 1.1 +/- 0.5 GtC yr(-1), G(ATM) was 3.9 +/- 0.2 GtC yr(-1), S-OCEAN was 2.9 +/- 0.5 GtC yr(-1), and S-LAND was 4.1 +/- 0.9 GtC yr(-1). G(ATM) was lower in 2014 compared to the past decade (2005-2014), reflecting a larger S-LAND for that year. The global atmospheric CO2 concentration reached 397.15 +/- 0.10 ppm averaged over 2014. For 2015, preliminary data indicate that the growth in E-FF will be near or slightly below zero, with a projection of 0.6 [ range of 1.6 to C 0.5] %, based on national emissions projections for China and the USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the global economy for the rest of the world. From this projection of E-FF and assumed constant E LUC for 2015, cumulative emissions of CO2 will reach about 555 +/- 55 GtC (2035 +/- 205 GtCO(2)) for 1870-2015, about 75% from E FF and 25% from E LUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quere et al., 2015, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi: 10.3334/CDIAC/GCP_2015)

Global carbon budget 2013

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates, consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil-fuel combustion and cement production (EFF) are based on energy statistics, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated for the first time in this budget with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2 and land cover change (some including nitrogen–carbon interactions). All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2003–2012), EFF was 8.6 ± 0.4 GtC yr−1, ELUC 0.9 ± 0.5 GtC yr−1, GATM 4.3 ± 0.1 GtC yr−1, SOCEAN 2.5 ± 0.5 GtC yr−1, and SLAND 2.8 ± 0.8 GtC yr−1. For year 2012 alone, EFF grew to 9.7 ± 0.5 GtC yr−1, 2.2% above 2011, reflecting a continued growing trend in these emissions, GATM was 5.1 ± 0.2 GtC yr−1, SOCEAN was 2.9 ± 0.5 GtC yr−1, and assuming an ELUC of 1.0 ± 0.5 GtC yr−1 (based on the 2001–2010 average), SLAND was 2.7 ± 0.9 GtC yr−1. GATM was high in 2012 compared to the 2003–2012 average, almost entirely reflecting the high EFF. The global atmospheric CO2 concentration reached 392.52 ± 0.10 ppm averaged over 2012. We estimate that EFF will increase by 2.1% (1.1–3.1%) to 9.9 ± 0.5 GtC in 2013, 61% above emissions in 1990, based on projections of world gross domestic product and recent changes in the carbon intensity of the economy. With this projection, cumulative emissions of CO2 will reach about 535 ± 55 GtC for 1870–2013, about 70% from EFF (390 ± 20 GtC) and 30% from ELUC (145 ± 50 GtC). This paper also documents any changes in the methods and data sets used in this new carbon budget from previous budgets (Le Quéré et al., 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2013_V2.3)

Structural basis of the filamin A actin-binding domain interaction with F-actin

Cryo-EM reconstructions were deposited in the Electron Microscopy Data Bank with the following accession numbers: F20-F-actin-FLNaABD, EMD-7833; F20-F-actin-FLNaABD-Q170P, EMD-7832; F20-F-actin-FLNaABD-E254K, EMD-8918; Krios-F-actin-FLNaABD-E254K, EMD-7831. The corresponding FLNaABD-E254K filament model was deposited in the PDB with accession number 6D8C. Source data for F-actin-targeting analyses (Figs. 2c,d,g,h, 3b,c,e,f, 4d,e, 5c,d, and 6a,b) and co-sedimentation assays (Figs. 5g and 6d) are available with the paper online. Other data are available from the corresponding author upon reasonable request. We thank Z. Razinia for generating numerous FLNa constructs, S. Wu for expertise in using the Krios microscope, J. Lees for advice on model refinement, and M. Lemmon for helpful comments in preparing the manuscript. We also thank the Yale Center for Research Computing for guidance and use of the Farnam Cluster, as well as the staff at the YMS Center for Molecular Imaging for the use of the EM Core Facility. This work was funded by grants from the National Institutes of Health (R01-GM068600 (D.A.C.), R01-NS093704 (D.A.C.), R37-GM057247 (C.V.S.), R01-GM110530 (C.V.S.), T32-GM007324, T32-GM008283) and an award from American Heart Association (15PRE25700119 (D.V.I.)).Peer reviewedPostprin