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3 The Relationship Between Apolipoprotein-E4 Genotype, Memory, and the Medial Temporal Lobe and How These Relationships Vary by Race in Middle-Aged Persons with HIV
- Laura M Campbell, Maulika Kohli, Erin E Sundermann, Christine Fennema-Notestine, Averi Barrett, Cinnamon Bloss, Mark W Bondi, David B Clifford, Ronald J Ellis, Donald Franklin, Benjamin Gelman, Igor Grant, Robert K Heaton, Scott Letendre, Payal B Patel, David J Moore, Susan Morgello, Raeanne C Moore
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 683-684
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Objective:
Many people with HIV (PWH) are at risk for age-related neurodegenerative disorders such as Alzheimer’s disease (AD). Studies on the association between cognition, neuroimaging outcomes, and the Apolipoprotein E4 (APOE4) genotype, which is associated with greater risk of AD, have yielded mixed results in PWH; however, many of these studies have examined a wide age range of PWH and have not examined APOE by race interactions that are observed in HIV-negative older adults. Thus, we examined how APOE status relates to cognition and medial temporal lobe (MTL) structures (implicated in AD pathogenesis) in mid- to older-aged PWH. In exploratory analyses, we also examined race (African American (AA)/Black and non-Hispanic (NH) White) by APOE status interactions on cognition and MTL structures.
Participants and Methods:The analysis included 88 PWH between the ages of 45 and 68 (mean age=51±5.9 years; 86% male; 51% AA/Black, 38% NH-White, 9% Hispanic/Latinx, 2% other) from the CNS HIV Antiretroviral Therapy Effects Research multi-site study. Participants underwent APOE genotyping, neuropsychological testing, and structural MRI; APOE groups were defined as APOE4+ (at least one APOE4 allele) and APOE4- (no APOE4 alleles). Eighty-nine percent of participants were on antiretroviral therapy, 74% had undetectable plasma HIV RNA (<50 copies/ml), and 25% were APOE4+ (32% AA/Black/15% NH-White). Neuropsychological testing assessed seven domains, and demographically-corrected T-scores were calculated. FreeSurfer 7.1.1 was used to measure MTL structures (hippocampal volume, entorhinal cortex thickness, and parahippocampal thickness) and the effect of scanner was regressed out prior to analyses. Multivariable linear regressions tested the association between APOE status and cognitive and imaging outcomes. Models examining cognition covaried for comorbid conditions and HIV disease characteristics related to global cognition (i.e., AIDS status, lifetime methamphetamine use disorder). Models examining the MTL covaried for age, sex, and
relevant imaging covariates (i.e., intracranial volume or mean cortical thickness).
Results:APOE4+ carriers had worse learning (ß=-0.27, p=.01) and delayed recall (ß=-0.25, p=.02) compared to the APOE4- group, but APOE status was not significantly associated with any other domain (ps>0.24). APOE4+ status was also associated with thinner entorhinal cortex (ß=-0.24, p=.02). APOE status was not significantly associated with hippocampal volume (ß=-0.08, p=0.32) or parahippocampal thickness (ß=-0.18, p=.08). Lastly, race interacted with APOE status such that the negative association between APOE4+ status and cognition was stronger in NH-White PWH as compared to AA/Black PWH in learning, delayed recall, and verbal fluency (ps<0.05). There were no APOE by race interactions for any MTL structures (ps>0.10).
Conclusions:Findings suggest that APOE4 carrier status is associated with worse episodic memory and thinner entorhinal cortex in mid- to older-aged PWH. While APOE4+ groups were small, we found that APOE4 carrier status had a larger association with cognition in NH-White PWH as compared to AA/Black PWH, consistent with studies demonstrating an attenuated effect of APOE4 in older AA/Black HIV-negative older adults. These findings further highlight the importance of recruiting diverse samples and suggest exploring other genetic markers (e.g., ABCA7) that may be more predictive of AD in some races to better understand AD risk in diverse groups of PWH.
Associations of alcohol and cannabis use with change in posttraumatic stress disorder and depression symptoms over time in recently trauma-exposed individuals
- Cecilia A. Hinojosa, Amanda Liew, Xinming An, Jennifer S. Stevens, Archana Basu, Sanne J. H. van Rooij, Stacey L. House, Francesca L. Beaudoin, Donglin Zeng, Thomas C. Neylan, Gari D. Clifford, Tanja Jovanovic, Sarah D. Linnstaedt, Laura T. Germine, Scott L. Rauch, John P. Haran, Alan B. Storrow, Christopher Lewandowski, Paul I. Musey, Phyllis L. Hendry, Sophia Sheikh, Christopher W. Jones, Brittany E. Punches, Michael C. Kurz, Robert A. Swor, Lauren A. Hudak, Jose L. Pascual, Mark J. Seamon, Elizabeth M. Datner, Anna M. Chang, Claire Pearson, David A. Peak, Roland C. Merchant, Robert M. Domeier, Niels K. Rathlev, Paulina Sergot, Leon D. Sanchez, Steven E. Bruce, Mark W. Miller, Robert H. Pietrzak, Jutta Joormann, Diego A. Pizzagalli, John F. Sheridan, Steven E. Harte, James M. Elliott, Ronald C. Kessler, Karestan C. Koenen, Samuel A. McLean, Kerry J. Ressler, Negar Fani
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- Journal:
- Psychological Medicine / Volume 54 / Issue 2 / January 2024
- Published online by Cambridge University Press:
- 13 June 2023, pp. 338-349
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Background
Several hypotheses may explain the association between substance use, posttraumatic stress disorder (PTSD), and depression. However, few studies have utilized a large multisite dataset to understand this complex relationship. Our study assessed the relationship between alcohol and cannabis use trajectories and PTSD and depression symptoms across 3 months in recently trauma-exposed civilians.
MethodsIn total, 1618 (1037 female) participants provided self-report data on past 30-day alcohol and cannabis use and PTSD and depression symptoms during their emergency department (baseline) visit. We reassessed participant's substance use and clinical symptoms 2, 8, and 12 weeks posttrauma. Latent class mixture modeling determined alcohol and cannabis use trajectories in the sample. Changes in PTSD and depression symptoms were assessed across alcohol and cannabis use trajectories via a mixed-model repeated-measures analysis of variance.
ResultsThree trajectory classes (low, high, increasing use) provided the best model fit for alcohol and cannabis use. The low alcohol use class exhibited lower PTSD symptoms at baseline than the high use class; the low cannabis use class exhibited lower PTSD and depression symptoms at baseline than the high and increasing use classes; these symptoms greatly increased at week 8 and declined at week 12. Participants who already use alcohol and cannabis exhibited greater PTSD and depression symptoms at baseline that increased at week 8 with a decrease in symptoms at week 12.
ConclusionsOur findings suggest that alcohol and cannabis use trajectories are associated with the intensity of posttrauma psychopathology. These findings could potentially inform the timing of therapeutic strategies.
Settlement Scaling in the Northern Maya Lowlands: Human-Scale Implications
- Scott R. Hutson, Adrian S. Z. Chase, Jeffrey B. Glover, William M. Ringle, Travis W. Stanton, Walter R. T. Witschey, Traci Ardren
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- Journal:
- Latin American Antiquity / Volume 35 / Issue 1 / March 2024
- Published online by Cambridge University Press:
- 03 April 2023, pp. 238-245
- Print publication:
- March 2024
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Settlement scaling theory predicts that higher site densities lead to increased social interactions that, in turn, boost productivity. The scaling relationship between population and land area holds for several ancient societies, but as demonstrated by the sample of 48 sites in this study, it does not hold for the Northern Maya Lowlands. Removing smaller sites from the sample brings the results closer to scaling expectations. We argue that applications of scaling theory benefit by considering social interaction as a product not only of proximity but also of daily life and spatial layouts.
WALLABY Pilot Survey: Public release of HI kinematic models for more than 100 galaxies from phase 1 of ASKAP pilot observations
- N. Deg, K. Spekkens, T. Westmeier, T. N. Reynolds, P. Venkataraman, S. Goliath, A. X. Shen, R. Halloran, A. Bosma, B Catinella, W. J. G. de Blok, H. Dénes, E. M. DiTeodoro, A. Elagali, B.-Q. For, C Howlett, G. I. G. Józsa, P. Kamphuis, D. Kleiner, B Koribalski, K. Lee-Waddell, F. Lelli, X. Lin, C. Murugeshan, S. Oh, J. Rhee, T. C. Scott, L. Staveley-Smith, J. M. van der Hulst, L. Verdes-Montenegro, J. Wang, O. I. Wong
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- Journal:
- Publications of the Astronomical Society of Australia / Volume 39 / 2022
- Published online by Cambridge University Press:
- 15 November 2022, e059
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We present the Widefield ASKAP L-band Legacy All-sky Blind surveY (WALLABY) Pilot Phase I Hi kinematic models. This first data release consists of Hi observations of three fields in the direction of the Hydra and Norma clusters, and the NGC 4636 galaxy group. In this paper, we describe how we generate and publicly release flat-disk tilted-ring kinematic models for 109/592 unique Hi detections in these fields. The modelling method adopted here—which we call the WALLABY Kinematic Analysis Proto-Pipeline (WKAPP) and for which the corresponding scripts are also publicly available—consists of combining results from the homogeneous application of the FAT and 3DBarolo algorithms to the subset of 209 detections with sufficient resolution and $S/N$ in order to generate optimised model parameters and uncertainties. The 109 models presented here tend to be gas rich detections resolved by at least 3–4 synthesised beams across their major axes, but there is no obvious environmental bias in the modelling. The data release described here is the first step towards the derivation of similar products for thousands of spatially resolved WALLABY detections via a dedicated kinematic pipeline. Such a large publicly available and homogeneously analysed dataset will be a powerful legacy product that that will enable a wide range of scientific studies.
Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach – CORRIGENDUM
- Micah Cearns, Azmeraw T. Amare, Klaus Oliver Schubert, Anbupalam Thalamuthu, Joseph Frank, Fabian Streit, Mazda Adli, Nirmala Akula, Kazufumi Akiyama, Raffaella Ardau, Bárbara Arias, JeanMichel Aubry, Lena Backlund, Abesh Kumar Bhattacharjee, Frank Bellivier, Antonio Benabarre, Susanne Bengesser, Joanna M. Biernacka, Armin Birner, Clara Brichant-Petitjean, Pablo Cervantes, HsiChung Chen, Caterina Chillotti, Sven Cichon, Cristiana Cruceanu, Piotr M. Czerski, Nina Dalkner, Alexandre Dayer, Franziska Degenhardt, Maria Del Zompo, J. Raymond DePaulo, Bruno Étain, Peter Falkai, Andreas J. Forstner, Louise Frisen, Mark A. Frye, Janice M. Fullerton, Sébastien Gard, Julie S. Garnham, Fernando S. Goes, Maria Grigoroiu-Serbanescu, Paul Grof, Ryota Hashimoto, Joanna Hauser, Urs Heilbronner, Stefan Herms, Per Hoffmann, Andrea Hofmann, Liping Hou, Yi-Hsiang Hsu, Stephane Jamain, Esther Jiménez, Jean-Pierre Kahn, Layla Kassem, Po-Hsiu Kuo, Tadafumi Kato, John Kelsoe, Sarah Kittel-Schneider, Sebastian Kliwicki, Barbara König, Ichiro Kusumi, Gonzalo Laje, Mikael Landén, Catharina Lavebratt, Marion Leboyer, Susan G. Leckband, Mario Maj, the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Mirko Manchia, Lina Martinsson, Michael J. McCarthy, Susan McElroy, Francesc Colom, Marina Mitjans, Francis M. Mondimore, Palmiero Monteleone, Caroline M. Nievergelt, Markus M. Nöthen, Tomas Novák, Claire O'Donovan, Norio Ozaki, Vincent Millischer, Sergi Papiol, Andrea Pfennig, Claudia Pisanu, James B. Potash, Andreas Reif, Eva Reininghaus, Guy A. Rouleau, Janusz K. Rybakowski, Martin Schalling, Peter R. Schofield, Barbara W. Schweizer, Giovanni Severino, Tatyana Shekhtman, Paul D. Shilling, Katzutaka Shimoda, Christian Simhandl, Claire M. Slaney, Alessio Squassina, Thomas Stamm, Pavla Stopkova, Fasil TekolaAyele, Alfonso Tortorella, Gustavo Turecki, Julia Veeh, Eduard Vieta, Stephanie H. Witt, Gloria Roberts, Peter P. Zandi, Martin Alda, Michael Bauer, Francis J. McMahon, Philip B. Mitchell, Thomas G. Schulze, Marcella Rietschel, Scott R. Clark, Bernhard T. Baune
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- Journal:
- The British Journal of Psychiatry / Volume 221 / Issue 2 / August 2022
- Published online by Cambridge University Press:
- 04 May 2022, p. 494
- Print publication:
- August 2022
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Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach
- Micah Cearns, Azmeraw T. Amare, Klaus Oliver Schubert, Anbupalam Thalamuthu, Joseph Frank, Fabian Streit, Mazda Adli, Nirmala Akula, Kazufumi Akiyama, Raffaella Ardau, Bárbara Arias, Jean-Michel Aubry, Lena Backlund, Abesh Kumar Bhattacharjee, Frank Bellivier, Antonio Benabarre, Susanne Bengesser, Joanna M. Biernacka, Armin Birner, Clara Brichant-Petitjean, Pablo Cervantes, Hsi-Chung Chen, Caterina Chillotti, Sven Cichon, Cristiana Cruceanu, Piotr M. Czerski, Nina Dalkner, Alexandre Dayer, Franziska Degenhardt, Maria Del Zompo, J. Raymond DePaulo, Bruno Étain, Peter Falkai, Andreas J. Forstner, Louise Frisen, Mark A. Frye, Janice M. Fullerton, Sébastien Gard, Julie S. Garnham, Fernando S. Goes, Maria Grigoroiu-Serbanescu, Paul Grof, Ryota Hashimoto, Joanna Hauser, Urs Heilbronner, Stefan Herms, Per Hoffmann, Andrea Hofmann, Liping Hou, Yi-Hsiang Hsu, Stephane Jamain, Esther Jiménez, Jean-Pierre Kahn, Layla Kassem, Po-Hsiu Kuo, Tadafumi Kato, John Kelsoe, Sarah Kittel-Schneider, Sebastian Kliwicki, Barbara König, Ichiro Kusumi, Gonzalo Laje, Mikael Landén, Catharina Lavebratt, Marion Leboyer, Susan G. Leckband, Mario Maj, the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Mirko Manchia, Lina Martinsson, Michael J. McCarthy, Susan McElroy, Francesc Colom, Marina Mitjans, Francis M. Mondimore, Palmiero Monteleone, Caroline M. Nievergelt, Markus M. Nöthen, Tomas Novák, Claire O'Donovan, Norio Ozaki, Vincent Millischer, Sergi Papiol, Andrea Pfennig, Claudia Pisanu, James B. Potash, Andreas Reif, Eva Reininghaus, Guy A. Rouleau, Janusz K. Rybakowski, Martin Schalling, Peter R. Schofield, Barbara W. Schweizer, Giovanni Severino, Tatyana Shekhtman, Paul D. Shilling, Katzutaka Shimoda, Christian Simhandl, Claire M. Slaney, Alessio Squassina, Thomas Stamm, Pavla Stopkova, Fasil Tekola-Ayele, Alfonso Tortorella, Gustavo Turecki, Julia Veeh, Eduard Vieta, Stephanie H. Witt, Gloria Roberts, Peter P. Zandi, Martin Alda, Michael Bauer, Francis J. McMahon, Philip B. Mitchell, Thomas G. Schulze, Marcella Rietschel, Scott R. Clark, Bernhard T. Baune
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- Journal:
- The British Journal of Psychiatry / Volume 220 / Issue 4 / April 2022
- Published online by Cambridge University Press:
- 28 February 2022, pp. 219-228
- Print publication:
- April 2022
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Background
Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.
AimsTo use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.
MethodThis study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.
ResultsThe best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.
ConclusionsUsing PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.
Characterisation of age and polarity at onset in bipolar disorder
- Janos L. Kalman, Loes M. Olde Loohuis, Annabel Vreeker, Andrew McQuillin, Eli A. Stahl, Douglas Ruderfer, Maria Grigoroiu-Serbanescu, Georgia Panagiotaropoulou, Stephan Ripke, Tim B. Bigdeli, Frederike Stein, Tina Meller, Susanne Meinert, Helena Pelin, Fabian Streit, Sergi Papiol, Mark J. Adams, Rolf Adolfsson, Kristina Adorjan, Ingrid Agartz, Sofie R. Aminoff, Heike Anderson-Schmidt, Ole A. Andreassen, Raffaella Ardau, Jean-Michel Aubry, Ceylan Balaban, Nicholas Bass, Bernhard T. Baune, Frank Bellivier, Antoni Benabarre, Susanne Bengesser, Wade H Berrettini, Marco P. Boks, Evelyn J. Bromet, Katharina Brosch, Monika Budde, William Byerley, Pablo Cervantes, Catina Chillotti, Sven Cichon, Scott R. Clark, Ashley L. Comes, Aiden Corvin, William Coryell, Nick Craddock, David W. Craig, Paul E. Croarkin, Cristiana Cruceanu, Piotr M. Czerski, Nina Dalkner, Udo Dannlowski, Franziska Degenhardt, Maria Del Zompo, J. Raymond DePaulo, Srdjan Djurovic, Howard J. Edenberg, Mariam Al Eissa, Torbjørn Elvsåshagen, Bruno Etain, Ayman H. Fanous, Frederike Fellendorf, Alessia Fiorentino, Andreas J. Forstner, Mark A. Frye, Janice M. Fullerton, Katrin Gade, Julie Garnham, Elliot Gershon, Michael Gill, Fernando S. Goes, Katherine Gordon-Smith, Paul Grof, Jose Guzman-Parra, Tim Hahn, Roland Hasler, Maria Heilbronner, Urs Heilbronner, Stephane Jamain, Esther Jimenez, Ian Jones, Lisa Jones, Lina Jonsson, Rene S. Kahn, John R. Kelsoe, James L. Kennedy, Tilo Kircher, George Kirov, Sarah Kittel-Schneider, Farah Klöhn-Saghatolislam, James A. Knowles, Thorsten M. Kranz, Trine Vik Lagerberg, Mikael Landen, William B. Lawson, Marion Leboyer, Qingqin S. Li, Mario Maj, Dolores Malaspina, Mirko Manchia, Fermin Mayoral, Susan L. McElroy, Melvin G. McInnis, Andrew M. McIntosh, Helena Medeiros, Ingrid Melle, Vihra Milanova, Philip B. Mitchell, Palmiero Monteleone, Alessio Maria Monteleone, Markus M. Nöthen, Tomas Novak, John I. Nurnberger, Niamh O'Brien, Kevin S. O'Connell, Claire O'Donovan, Michael C. O'Donovan, Nils Opel, Abigail Ortiz, Michael J. Owen, Erik Pålsson, Carlos Pato, Michele T. Pato, Joanna Pawlak, Julia-Katharina Pfarr, Claudia Pisanu, James B. Potash, Mark H Rapaport, Daniela Reich-Erkelenz, Andreas Reif, Eva Reininghaus, Jonathan Repple, Hélène Richard-Lepouriel, Marcella Rietschel, Kai Ringwald, Gloria Roberts, Guy Rouleau, Sabrina Schaupp, William A Scheftner, Simon Schmitt, Peter R. Schofield, K. Oliver Schubert, Eva C. Schulte, Barbara Schweizer, Fanny Senner, Giovanni Severino, Sally Sharp, Claire Slaney, Olav B. Smeland, Janet L. Sobell, Alessio Squassina, Pavla Stopkova, John Strauss, Alfonso Tortorella, Gustavo Turecki, Joanna Twarowska-Hauser, Marin Veldic, Eduard Vieta, John B. Vincent, Wei Xu, Clement C. Zai, Peter P. Zandi, Psychiatric Genomics Consortium (PGC) Bipolar Disorder Working Group, International Consortium on Lithium Genetics (ConLiGen), Colombia-US Cross Disorder Collaboration in Psychiatric Genetics, Arianna Di Florio, Jordan W. Smoller, Joanna M. Biernacka, Francis J. McMahon, Martin Alda, Bertram Müller-Myhsok, Nikolaos Koutsouleris, Peter Falkai, Nelson B. Freimer, Till F.M. Andlauer, Thomas G. Schulze, Roel A. Ophoff
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- Journal:
- The British Journal of Psychiatry / Volume 219 / Issue 6 / December 2021
- Published online by Cambridge University Press:
- 25 August 2021, pp. 659-669
- Print publication:
- December 2021
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Background
Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.
AimsTo examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.
MethodGenome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.
ResultsEarlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.
ConclusionsAAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
Mass balance of the Antarctic ice sheet 1992–2016: reconciling results from GRACE gravimetry with ICESat, ERS1/2 and Envisat altimetry
- H. Jay Zwally, John W. Robbins, Scott B. Luthcke, Bryant D. Loomis, Frédérique Rémy
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- Journal:
- Journal of Glaciology / Volume 67 / Issue 263 / June 2021
- Published online by Cambridge University Press:
- 29 March 2021, pp. 533-559
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GRACE and ICESat Antarctic mass-balance differences are resolved utilizing their dependencies on corrections for changes in mass and volume of the same underlying mantle material forced by ice-loading changes. Modeled gravimetry corrections are 5.22 times altimetry corrections over East Antarctica (EA) and 4.51 times over West Antarctica (WA), with inferred mantle densities 4.75 and 4.11 g cm−3. Derived sensitivities (Sg, Sa) to bedrock motion enable calculation of motion (δB0) needed to equalize GRACE and ICESat mass changes during 2003–08. For EA, δB0 is −2.2 mm a−1 subsidence with mass matching at 150 Gt a−1, inland WA is −3.5 mm a−1 at 66 Gt a−1, and coastal WA is only −0.35 mm a−1 at −95 Gt a−1. WA subsidence is attributed to low mantle viscosity with faster responses to post-LGM deglaciation and to ice growth during Holocene grounding-line readvance. EA subsidence is attributed to Holocene dynamic thickening. With Antarctic Peninsula loss of −26 Gt a−1, the Antarctic total gain is 95 ± 25 Gt a−1 during 2003–08, compared to 144 ± 61 Gt a−1 from ERS1/2 during 1992–2001. Beginning in 2009, large increases in coastal WA dynamic losses overcame long-term EA and inland WA gains bringing Antarctica close to balance at −12 ± 64 Gt a−1 by 2012–16.
Neutron Star Extreme Matter Observatory: A kilohertz-band gravitational-wave detector in the global network
- Part of
- K. Ackley, V. B. Adya, P. Agrawal, P. Altin, G. Ashton, M. Bailes, E. Baltinas, A. Barbuio, D. Beniwal, C. Blair, D. Blair, G. N. Bolingbroke, V. Bossilkov, S. Shachar Boublil, D. D. Brown, B. J. Burridge, J. Calderon Bustillo, J. Cameron, H. Tuong Cao, J. B. Carlin, S. Chang, P. Charlton, C. Chatterjee, D. Chattopadhyay, X. Chen, J. Chi, J. Chow, Q. Chu, A. Ciobanu, T. Clarke, P. Clearwater, J. Cooke, D. Coward, H. Crisp, R. J. Dattatri, A. T. Deller, D. A. Dobie, L. Dunn, P. J. Easter, J. Eichholz, R. Evans, C. Flynn, G. Foran, P. Forsyth, Y. Gai, S. Galaudage, D. K. Galloway, B. Gendre, B. Goncharov, S. Goode, D. Gozzard, B. Grace, A. W. Graham, A. Heger, F. Hernandez Vivanco, R. Hirai, N. A. Holland, Z. J. Holmes, E. Howard, E. Howell, G. Howitt, M. T. Hübner, J. Hurley, C. Ingram, V. Jaberian Hamedan, K. Jenner, L. Ju, D. P. Kapasi, T. Kaur, N. Kijbunchoo, M. Kovalam, R. Kumar Choudhary, P. D. Lasky, M. Y. M. Lau, J. Leung, J. Liu, K. Loh, A. Mailvagan, I. Mandel, J. J. McCann, D. E. McClelland, K. McKenzie, D. McManus, T. McRae, A. Melatos, P. Meyers, H. Middleton, M. T. Miles, M. Millhouse, Y. Lun Mong, B. Mueller, J. Munch, J. Musiov, S. Muusse, R. S. Nathan, Y. Naveh, C. Neijssel, B. Neil, S. W. S. Ng, V. Oloworaran, D. J. Ottaway, M. Page, J. Pan, M. Pathak, E. Payne, J. Powell, J. Pritchard, E. Puckridge, A. Raidani, V. Rallabhandi, D. Reardon, J. A. Riley, L. Roberts, I. M. Romero-Shaw, T. J. Roocke, G. Rowell, N. Sahu, N. Sarin, L. Sarre, H. Sattari, M. Schiworski, S. M. Scott, R. Sengar, D. Shaddock, R. Shannon, J. SHI, P. Sibley, B. J. J. Slagmolen, T. Slaven-Blair, R. J. E. Smith, J. Spollard, L. Steed, L. Strang, H. Sun, A. Sunderland, S. Suvorova, C. Talbot, E. Thrane, D. Töyrä, P. Trahanas, A. Vajpeyi, J. V. van Heijningen, A. F. Vargas, P. J. Veitch, A. Vigna-Gomez, A. Wade, K. Walker, Z. Wang, R. L. Ward, K. Ward, S. Webb, L. Wen, K. Wette, R. Wilcox, J. Winterflood, C. Wolf, B. Wu, M. Jet Yap, Z. You, H. Yu, J. Zhang, J. Zhang, C. Zhao, X. Zhu
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- Journal:
- Publications of the Astronomical Society of Australia / Volume 37 / 2020
- Published online by Cambridge University Press:
- 05 November 2020, e047
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Gravitational waves from coalescing neutron stars encode information about nuclear matter at extreme densities, inaccessible by laboratory experiments. The late inspiral is influenced by the presence of tides, which depend on the neutron star equation of state. Neutron star mergers are expected to often produce rapidly rotating remnant neutron stars that emit gravitational waves. These will provide clues to the extremely hot post-merger environment. This signature of nuclear matter in gravitational waves contains most information in the 2–4 kHz frequency band, which is outside of the most sensitive band of current detectors. We present the design concept and science case for a Neutron Star Extreme Matter Observatory (NEMO): a gravitational-wave interferometer optimised to study nuclear physics with merging neutron stars. The concept uses high-circulating laser power, quantum squeezing, and a detector topology specifically designed to achieve the high-frequency sensitivity necessary to probe nuclear matter using gravitational waves. Above 1 kHz, the proposed strain sensitivity is comparable to full third-generation detectors at a fraction of the cost. Such sensitivity changes expected event rates for detection of post-merger remnants from approximately one per few decades with two A+ detectors to a few per year and potentially allow for the first gravitational-wave observations of supernovae, isolated neutron stars, and other exotica.
Overview of the SPARC tokamak
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- A. J. Creely, M. J. Greenwald, S. B. Ballinger, D. Brunner, J. Canik, J. Doody, T. Fülöp, D. T. Garnier, R. Granetz, T. K. Gray, C. Holland, N. T. Howard, J. W. Hughes, J. H. Irby, V. A. Izzo, G. J. Kramer, A. Q. Kuang, B. LaBombard, Y. Lin, B. Lipschultz, N. C. Logan, J. D. Lore, E. S. Marmar, K. Montes, R. T. Mumgaard, C. Paz-Soldan, C. Rea, M. L. Reinke, P. Rodriguez-Fernandez, K. Särkimäki, F. Sciortino, S. D. Scott, A. Snicker, P. B. Snyder, B. N. Sorbom, R. Sweeney, R. A. Tinguely, E. A. Tolman, M. Umansky, O. Vallhagen, J. Varje, D. G. Whyte, J. C. Wright, S. J. Wukitch, J. Zhu, the SPARC Team
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- Journal:
- Journal of Plasma Physics / Volume 86 / Issue 5 / October 2020
- Published online by Cambridge University Press:
- 29 September 2020, 865860502
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The SPARC tokamak is a critical next step towards commercial fusion energy. SPARC is designed as a high-field ($B_0 = 12.2$ T), compact ($R_0 = 1.85$ m, $a = 0.57$ m), superconducting, D-T tokamak with the goal of producing fusion gain $Q>2$ from a magnetically confined fusion plasma for the first time. Currently under design, SPARC will continue the high-field path of the Alcator series of tokamaks, utilizing new magnets based on rare earth barium copper oxide high-temperature superconductors to achieve high performance in a compact device. The goal of $Q>2$ is achievable with conservative physics assumptions ($H_{98,y2} = 0.7$) and, with the nominal assumption of $H_{98,y2} = 1$, SPARC is projected to attain $Q \approx 11$ and $P_{\textrm {fusion}} \approx 140$ MW. SPARC will therefore constitute a unique platform for burning plasma physics research with high density ($\langle n_{e} \rangle \approx 3 \times 10^{20}\ \textrm {m}^{-3}$), high temperature ($\langle T_e \rangle \approx 7$ keV) and high power density ($P_{\textrm {fusion}}/V_{\textrm {plasma}} \approx 7\ \textrm {MW}\,\textrm {m}^{-3}$) relevant to fusion power plants. SPARC's place in the path to commercial fusion energy, its parameters and the current status of SPARC design work are presented. This work also describes the basis for global performance projections and summarizes some of the physics analysis that is presented in greater detail in the companion articles of this collection.
Comorbidity within mental disorders: a comprehensive analysis based on 145 990 survey respondents from 27 countries
- J. J. McGrath, C. C. W. Lim, O. Plana-Ripoll, Y. Holtz, E. Agerbo, N. C. Momen, P. B. Mortensen, C. B. Pedersen, J. Abdulmalik, S. Aguilar-Gaxiola, A. Al-Hamzawi, J. Alonso, E. J. Bromet, R. Bruffaerts, B. Bunting, J. M. C. de Almeida, G. de Girolamo, Y. A. De Vries, S. Florescu, O. Gureje, J. M. Haro, M. G. Harris, C. Hu, E. G. Karam, N. Kawakami, A. Kiejna, V. Kovess-Masfety, S. Lee, Z. Mneimneh, F. Navarro-Mateu, R. Orozco, J. Posada-Villa, A. M. Roest, S. Saha, K. M. Scott, J. C. Stagnaro, D. J. Stein, Y. Torres, M. C. Viana, Y. Ziv, R. C. Kessler, P. de Jonge
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- Journal:
- Epidemiology and Psychiatric Sciences / Volume 29 / 2020
- Published online by Cambridge University Press:
- 12 August 2020, e153
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Aims
Epidemiological studies indicate that individuals with one type of mental disorder have an increased risk of subsequently developing other types of mental disorders. This study aimed to undertake a comprehensive analysis of pair-wise lifetime comorbidity across a range of common mental disorders based on a diverse range of population-based surveys.
MethodsThe WHO World Mental Health (WMH) surveys assessed 145 990 adult respondents from 27 countries. Based on retrospectively-reported age-of-onset for 24 DSM-IV mental disorders, associations were examined between all 548 logically possible temporally-ordered disorder pairs. Overall and time-dependent hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using Cox proportional hazards models. Absolute risks were estimated using the product-limit method. Estimates were generated separately for men and women.
ResultsEach prior lifetime mental disorder was associated with an increased risk of subsequent first onset of each other disorder. The median HR was 12.1 (mean = 14.4; range 5.2–110.8, interquartile range = 6.0–19.4). The HRs were most prominent between closely-related mental disorder types and in the first 1–2 years after the onset of the prior disorder. Although HRs declined with time since prior disorder, significantly elevated risk of subsequent comorbidity persisted for at least 15 years. Appreciable absolute risks of secondary disorders were found over time for many pairs.
ConclusionsSurvey data from a range of sites confirms that comorbidity between mental disorders is common. Understanding the risks of temporally secondary disorders may help design practical programs for primary prevention of secondary disorders.
Findings from an in-Depth Annual Tree-Ring Radiocarbon Intercomparison
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- L Wacker, E M Scott, A Bayliss, D Brown, E Bard, S Bollhalder, M Friedrich, M Capano, A Cherkinsky, D Chivall, B J Culleton, M W Dee, R Friedrich, G W L Hodgins, A Hogg, D J Kennett, T D J Knowles, M Kuitems, T E Lange, F Miyake, M-J Nadeau, T Nakamura, J P Naysmith, J Olsen, T Omori, F Petchey, B Philippsen, C Bronk Ramsey, G V Ravi Prasad, M Seiler, J Southon, R Staff, T Tuna
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- Journal:
- Radiocarbon / Volume 62 / Issue 4 / August 2020
- Published online by Cambridge University Press:
- 04 September 2020, pp. 873-882
- Print publication:
- August 2020
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The radiocarbon (14C) calibration curve so far contains annually resolved data only for a short period of time. With accelerator mass spectrometry (AMS) matching the precision of decay counting, it is now possible to efficiently produce large datasets of annual resolution for calibration purposes using small amounts of wood. The radiocarbon intercomparison on single-year tree-ring samples presented here is the first to investigate specifically possible offsets between AMS laboratories at high precision. The results show that AMS laboratories are capable of measuring samples of Holocene age with an accuracy and precision that is comparable or even goes beyond what is possible with decay counting, even though they require a thousand times less wood. It also shows that not all AMS laboratories always produce results that are consistent with their stated uncertainties. The long-term benefits of studies of this kind are more accurate radiocarbon measurements with, in the future, better quantified uncertainties.
Methodological checklists for improving research quality and reporting consistency
- Lillian T. Eby, Kristen M. Shockley, Talya N. Bauer, Bryan Edwards, Astrid C. Homan, Russell Johnson, Jonas W. B. Lang, Scott B. Morris, Frederick L. Oswald
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- Journal:
- Industrial and Organizational Psychology / Volume 13 / Issue 1 / March 2020
- Published online by Cambridge University Press:
- 01 May 2020, pp. 76-83
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Machine learning enhances prediction of illness course: a longitudinal study in eating disorders
- Ann F. Haynos, Shirley B. Wang, Sarah Lipson, Carol B. Peterson, James E. Mitchell, Katherine A. Halmi, W. Stewart Agras, Scott J. Crow
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- Psychological Medicine / Volume 51 / Issue 8 / June 2021
- Published online by Cambridge University Press:
- 28 February 2020, pp. 1392-1402
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Background
Psychiatric disorders, including eating disorders (EDs), have clinical outcomes that range widely in severity and chronicity. The ability to predict such outcomes is extremely limited. Machine-learning (ML) approaches that model complexity may optimize the prediction of multifaceted psychiatric behaviors. However, the investigations of many psychiatric concerns have not capitalized on ML to improve prognosis. This study conducted the first comparison of an ML approach (elastic net regularized logistic regression) to traditional regression to longitudinally predict ED outcomes.
MethodsFemales with heterogeneous ED diagnoses completed demographic and psychiatric assessments at baseline (n = 415) and Year 1 (n = 320) and 2 (n = 277) follow-ups. Elastic net and traditional logistic regression models comprising the same baseline variables were compared in ability to longitudinally predict ED diagnosis, binge eating, compensatory behavior, and underweight BMI at Years 1 and 2.
ResultsElastic net models had higher accuracy for all outcomes at Years 1 and 2 [average Area Under the Receiving Operating Characteristics Curve (AUC) = 0.78] compared to logistic regression (average AUC = 0.67). Model performance did not deteriorate when the most important predictor was removed or an alternative ML algorithm (random forests) was applied. Baseline ED (e.g. diagnosis), psychiatric (e.g. hospitalization), and demographic (e.g. ethnicity) characteristics emerged as important predictors in exploratory predictor importance analyses.
ConclusionsML algorithms can enhance the prediction of ED symptoms for 2 years and may identify important risk markers. The superior accuracy of ML for predicting complex outcomes suggests that these approaches may ultimately aid in advancing precision medicine for serious psychiatric disorders.
Equivalency of the diagnostic accuracy of the PHQ-8 and PHQ-9: a systematic review and individual participant data meta-analysis – ERRATUM
- Yin Wu, Brooke Levis, Kira E. Riehm, Nazanin Saadat, Alexander W. Levis, Marleine Azar, Danielle B. Rice, Jill Boruff, Pim Cuijpers, Simon Gilbody, John P.A. Ioannidis, Lorie A. Kloda, Dean McMillan, Scott B. Patten, Ian Shrier, Roy C. Ziegelstein, Dickens H. Akena, Bruce Arroll, Liat Ayalon, Hamid R. Baradaran, Murray Baron, Charles H. Bombardier, Peter Butterworth, Gregory Carter, Marcos H. Chagas, Juliana C. N. Chan, Rushina Cholera, Yeates Conwell, Janneke M. de Manvan Ginkel, Jesse R. Fann, Felix H. Fischer, Daniel Fung, Bizu Gelaye, Felicity Goodyear-Smith, Catherine G. Greeno, Brian J. Hall, Patricia A. Harrison, Martin Härter, Ulrich Hegerl, Leanne Hides, Stevan E. Hobfoll, Marie Hudson, Thomas Hyphantis, Masatoshi Inagaki, Nathalie Jetté, Mohammad E. Khamseh, Kim M. Kiely, Yunxin Kwan, Femke Lamers, Shen-Ing Liu, Manote Lotrakul, Sonia R. Loureiro, Bernd Löwe, Anthony McGuire, Sherina Mohd-Sidik, Tiago N. Munhoz, Kumiko Muramatsu, Flávia L. Osório, Vikram Patel, Brian W. Pence, Philippe Persoons, Angelo Picardi, Katrin Reuter, Alasdair G. Rooney, Iná S. Santos, Juwita Shaaban, Abbey Sidebottom, Adam Simning, Lesley Stafford, Sharon Sung, Pei Lin Lynnette Tan, Alyna Turner, Henk C. van Weert, Jennifer White, Mary A. Whooley, Kirsty Winkley, Mitsuhiko Yamada, Andrea Benedetti, Brett D. Thombs
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- Journal:
- Psychological Medicine / Volume 50 / Issue 16 / December 2020
- Published online by Cambridge University Press:
- 19 August 2019, p. 2816
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Equivalency of the diagnostic accuracy of the PHQ-8 and PHQ-9: a systematic review and individual participant data meta-analysis
- Yin Wu, Brooke Levis, Kira E. Riehm, Nazanin Saadat, Alexander W. Levis, Marleine Azar, Danielle B. Rice, Jill Boruff, Pim Cuijpers, Simon Gilbody, John P.A. Ioannidis, Lorie A. Kloda, Dean McMillan, Scott B. Patten, Ian Shrier, Roy C. Ziegelstein, Dickens H. Akena, Bruce Arroll, Liat Ayalon, Hamid R. Baradaran, Murray Baron, Charles H. Bombardier, Peter Butterworth, Gregory Carter, Marcos H. Chagas, Juliana C. N. Chan, Rushina Cholera, Yeates Conwell, Janneke M. de Man-van Ginkel, Jesse R. Fann, Felix H. Fischer, Daniel Fung, Bizu Gelaye, Felicity Goodyear-Smith, Catherine G. Greeno, Brian J. Hall, Patricia A. Harrison, Martin Härter, Ulrich Hegerl, Leanne Hides, Stevan E. Hobfoll, Marie Hudson, Thomas Hyphantis, Masatoshi Inagaki, Nathalie Jetté, Mohammad E. Khamseh, Kim M. Kiely, Yunxin Kwan, Femke Lamers, Shen-Ing Liu, Manote Lotrakul, Sonia R. Loureiro, Bernd Löwe, Anthony McGuire, Sherina Mohd-Sidik, Tiago N. Munhoz, Kumiko Muramatsu, Flávia L. Osório, Vikram Patel, Brian W. Pence, Philippe Persoons, Angelo Picardi, Katrin Reuter, Alasdair G. Rooney, Iná S. Santos, Juwita Shaaban, Abbey Sidebottom, Adam Simning, Lesley Stafford, Sharon Sung, Pei Lin Lynnette Tan, Alyna Turner, Henk C. van Weert, Jennifer White, Mary A. Whooley, Kirsty Winkley, Mitsuhiko Yamada, Andrea Benedetti, Brett D. Thombs
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- Psychological Medicine / Volume 50 / Issue 8 / June 2020
- Published online by Cambridge University Press:
- 12 July 2019, pp. 1368-1380
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Background
Item 9 of the Patient Health Questionnaire-9 (PHQ-9) queries about thoughts of death and self-harm, but not suicidality. Although it is sometimes used to assess suicide risk, most positive responses are not associated with suicidality. The PHQ-8, which omits Item 9, is thus increasingly used in research. We assessed equivalency of total score correlations and the diagnostic accuracy to detect major depression of the PHQ-8 and PHQ-9.
MethodsWe conducted an individual patient data meta-analysis. We fit bivariate random-effects models to assess diagnostic accuracy.
Results16 742 participants (2097 major depression cases) from 54 studies were included. The correlation between PHQ-8 and PHQ-9 scores was 0.996 (95% confidence interval 0.996 to 0.996). The standard cutoff score of 10 for the PHQ-9 maximized sensitivity + specificity for the PHQ-8 among studies that used a semi-structured diagnostic interview reference standard (N = 27). At cutoff 10, the PHQ-8 was less sensitive by 0.02 (−0.06 to 0.00) and more specific by 0.01 (0.00 to 0.01) among those studies (N = 27), with similar results for studies that used other types of interviews (N = 27). For all 54 primary studies combined, across all cutoffs, the PHQ-8 was less sensitive than the PHQ-9 by 0.00 to 0.05 (0.03 at cutoff 10), and specificity was within 0.01 for all cutoffs (0.00 to 0.01).
ConclusionsPHQ-8 and PHQ-9 total scores were similar. Sensitivity may be minimally reduced with the PHQ-8, but specificity is similar.
Neurocognitive SuperAging in Older Adults Living With HIV: Demographic, Neuromedical and Everyday Functioning Correlates
- Rowan Saloner, Laura M. Campbell, Vanessa Serrano, Jessica L. Montoya, Elizabeth Pasipanodya, Emily W. Paolillo, Donald Franklin, Ronald J. Ellis, Scott L. Letendre, Ann C. Collier, David B. Clifford, Benjamin B. Gelman, Christina M. Marra, J. Allen McCutchan, Susan Morgello, Ned Sacktor, Dilip V. Jeste, Igor Grant, Robert K. Heaton, David J. Moore, the CHARTER and HNRP Groups
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- Journal of the International Neuropsychological Society / Volume 25 / Issue 5 / May 2019
- Published online by Cambridge University Press:
- 20 March 2019, pp. 507-519
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Objectives: Studies of neurocognitively elite older adults, termed SuperAgers, have identified clinical predictors and neurobiological indicators of resilience against age-related neurocognitive decline. Despite rising rates of older persons living with HIV (PLWH), SuperAging (SA) in PLWH remains undefined. We aimed to establish neuropsychological criteria for SA in PLWH and examined clinically relevant correlates of SA. Methods: 734 PLWH and 123 HIV-uninfected participants between 50 and 64 years of age underwent neuropsychological and neuromedical evaluations. SA was defined as demographically corrected (i.e., sex, race/ethnicity, education) global neurocognitive performance within normal range for 25-year-olds. Remaining participants were labeled cognitively normal (CN) or impaired (CI) based on actual age. Chi-square and analysis of variance tests examined HIV group differences on neurocognitive status and demographics. Within PLWH, neurocognitive status differences were tested on HIV disease characteristics, medical comorbidities, and everyday functioning. Multinomial logistic regression explored independent predictors of neurocognitive status. Results: Neurocognitive status rates and demographic characteristics differed between PLWH (SA=17%; CN=38%; CI=45%) and HIV-uninfected participants (SA=35%; CN=55%; CI=11%). In PLWH, neurocognitive groups were comparable on demographic and HIV disease characteristics. Younger age, higher verbal IQ, absence of diabetes, fewer depressive symptoms, and lifetime cannabis use disorder increased likelihood of SA. SA reported increased independence in everyday functioning, employment, and health-related quality of life than non-SA. Conclusions: Despite combined neurological risk of aging and HIV, youthful neurocognitive performance is possible for older PLWH. SA relates to improved real-world functioning and may be better explained by cognitive reserve and maintenance of cardiometabolic and mental health than HIV disease severity. Future research investigating biomarker and lifestyle (e.g., physical activity) correlates of SA may help identify modifiable neuroprotective factors against HIV-related neurobiological aging. (JINS, 2019, 25, 507–519)
Probability of major depression diagnostic classification using semi-structured versus fully structured diagnostic interviews
- Brooke Levis, Andrea Benedetti, Kira E. Riehm, Nazanin Saadat, Alexander W. Levis, Marleine Azar, Danielle B. Rice, Matthew J. Chiovitti, Tatiana A. Sanchez, Pim Cuijpers, Simon Gilbody, John P. A. Ioannidis, Lorie A. Kloda, Dean McMillan, Scott B. Patten, Ian Shrier, Russell J. Steele, Roy C. Ziegelstein, Dickens H. Akena, Bruce Arroll, Liat Ayalon, Hamid R. Baradaran, Murray Baron, Anna Beraldi, Charles H. Bombardier, Peter Butterworth, Gregory Carter, Marcos H. Chagas, Juliana C. N. Chan, Rushina Cholera, Neerja Chowdhary, Kerrie Clover, Yeates Conwell, Janneke M. de Man-van Ginkel, Jaime Delgadillo, Jesse R. Fann, Felix H. Fischer, Benjamin Fischler, Daniel Fung, Bizu Gelaye, Felicity Goodyear-Smith, Catherine G. Greeno, Brian J. Hall, John Hambridge, Patricia A. Harrison, Ulrich Hegerl, Leanne Hides, Stevan E. Hobfoll, Marie Hudson, Thomas Hyphantis, Masatoshi Inagaki, Khalida Ismail, Nathalie Jetté, Mohammad E. Khamseh, Kim M. Kiely, Femke Lamers, Shen-Ing Liu, Manote Lotrakul, Sonia R. Loureiro, Bernd Löwe, Laura Marsh, Anthony McGuire, Sherina Mohd Sidik, Tiago N. Munhoz, Kumiko Muramatsu, Flávia L. Osório, Vikram Patel, Brian W. Pence, Philippe Persoons, Angelo Picardi, Alasdair G. Rooney, Iná S. Santos, Juwita Shaaban, Abbey Sidebottom, Adam Simning, Lesley Stafford, Sharon Sung, Pei Lin Lynnette Tan, Alyna Turner, Christina M. van der Feltz-Cornelis, Henk C. van Weert, Paul A. Vöhringer, Jennifer White, Mary A. Whooley, Kirsty Winkley, Mitsuhiko Yamada, Yuying Zhang, Brett D. Thombs
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- Journal:
- The British Journal of Psychiatry / Volume 212 / Issue 6 / June 2018
- Published online by Cambridge University Press:
- 02 May 2018, pp. 377-385
- Print publication:
- June 2018
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Background
Different diagnostic interviews are used as reference standards for major depression classification in research. Semi-structured interviews involve clinical judgement, whereas fully structured interviews are completely scripted. The Mini International Neuropsychiatric Interview (MINI), a brief fully structured interview, is also sometimes used. It is not known whether interview method is associated with probability of major depression classification.
AimsTo evaluate the association between interview method and odds of major depression classification, controlling for depressive symptom scores and participant characteristics.
MethodData collected for an individual participant data meta-analysis of Patient Health Questionnaire-9 (PHQ-9) diagnostic accuracy were analysed and binomial generalised linear mixed models were fit.
ResultsA total of 17 158 participants (2287 with major depression) from 57 primary studies were analysed. Among fully structured interviews, odds of major depression were higher for the MINI compared with the Composite International Diagnostic Interview (CIDI) (odds ratio (OR) = 2.10; 95% CI = 1.15–3.87). Compared with semi-structured interviews, fully structured interviews (MINI excluded) were non-significantly more likely to classify participants with low-level depressive symptoms (PHQ-9 scores ≤6) as having major depression (OR = 3.13; 95% CI = 0.98–10.00), similarly likely for moderate-level symptoms (PHQ-9 scores 7–15) (OR = 0.96; 95% CI = 0.56–1.66) and significantly less likely for high-level symptoms (PHQ-9 scores ≥16) (OR = 0.50; 95% CI = 0.26–0.97).
ConclusionsThe MINI may identify more people as depressed than the CIDI, and semi-structured and fully structured interviews may not be interchangeable methods, but these results should be replicated.
Declaration of interestDrs Jetté and Patten declare that they received a grant, outside the submitted work, from the Hotchkiss Brain Institute, which was jointly funded by the Institute and Pfizer. Pfizer was the original sponsor of the development of the PHQ-9, which is now in the public domain. Dr Chan is a steering committee member or consultant of Astra Zeneca, Bayer, Lilly, MSD and Pfizer. She has received sponsorships and honorarium for giving lectures and providing consultancy and her affiliated institution has received research grants from these companies. Dr Hegerl declares that within the past 3 years, he was an advisory board member for Lundbeck, Servier and Otsuka Pharma; a consultant for Bayer Pharma; and a speaker for Medice Arzneimittel, Novartis, and Roche Pharma, all outside the submitted work. Dr Inagaki declares that he has received grants from Novartis Pharma, lecture fees from Pfizer, Mochida, Shionogi, Sumitomo Dainippon Pharma, Daiichi-Sankyo, Meiji Seika and Takeda, and royalties from Nippon Hyoron Sha, Nanzando, Seiwa Shoten, Igaku-shoin and Technomics, all outside of the submitted work. Dr Yamada reports personal fees from Meiji Seika Pharma Co., Ltd., MSD K.K., Asahi Kasei Pharma Corporation, Seishin Shobo, Seiwa Shoten Co., Ltd., Igaku-shoin Ltd., Chugai Igakusha and Sentan Igakusha, all outside the submitted work. All other authors declare no competing interests. No funder had any role in the design and conduct of the study; collection, management, analysis and interpretation of the data; preparation, review or approval of the manuscript; and decision to submit the manuscript for publication.
Follow Up of GW170817 and Its Electromagnetic Counterpart by Australian-Led Observing Programmes
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- I. Andreoni, K. Ackley, J. Cooke, A. Acharyya, J. R. Allison, G. E. Anderson, M. C. B. Ashley, D. Baade, M. Bailes, K. Bannister, A. Beardsley, M. S. Bessell, F. Bian, P. A. Bland, M. Boer, T. Booler, A. Brandeker, I. S. Brown, D. A. H. Buckley, S.-W. Chang, D. M. Coward, S. Crawford, H. Crisp, B. Crosse, A. Cucchiara, M. Cupák, J. S. de Gois, A. Deller, H. A. R. Devillepoix, D. Dobie, E. Elmer, D. Emrich, W. Farah, T. J. Farrell, T. Franzen, B. M. Gaensler, D. K. Galloway, B. Gendre, T. Giblin, A. Goobar, J. Green, P. J. Hancock, B. A. D. Hartig, E. J. Howell, L. Horsley, A. Hotan, R. M. Howie, L. Hu, Y. Hu, C. W. James, S. Johnston, M. Johnston-Hollitt, D. L. Kaplan, M. Kasliwal, E. F. Keane, D. Kenney, A. Klotz, R. Lau, R. Laugier, E. Lenc, X. Li, E. Liang, C. Lidman, L. C. Luvaul, C. Lynch, B. Ma, D. Macpherson, J. Mao, D. E. McClelland, C. McCully, A. Möller, M. F. Morales, D. Morris, T. Murphy, K. Noysena, C. A. Onken, N. B. Orange, S. Osłowski, D. Pallot, J. Paxman, S. B. Potter, T. Pritchard, W. Raja, R. Ridden-Harper, E. Romero-Colmenero, E. M. Sadler, E. K. Sansom, R. A. Scalzo, B. P. Schmidt, S. M. Scott, N. Seghouani, Z. Shang, R. M. Shannon, L. Shao, M. M. Shara, R. Sharp, M. Sokolowski, J. Sollerman, J. Staff, K. Steele, T. Sun, N. B. Suntzeff, C. Tao, S. Tingay, M. C. Towner, P. Thierry, C. Trott, B. E. Tucker, P. Väisänen, V. Venkatraman Krishnan, M. Walker, L. Wang, X. Wang, R. Wayth, M. Whiting, A. Williams, T. Williams, C. Wolf, C. Wu, X. Wu, J. Yang, X. Yuan, H. Zhang, J. Zhou, H. Zovaro
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- Journal:
- Publications of the Astronomical Society of Australia / Volume 34 / 2017
- Published online by Cambridge University Press:
- 20 December 2017, e069
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The discovery of the first electromagnetic counterpart to a gravitational wave signal has generated follow-up observations by over 50 facilities world-wide, ushering in the new era of multi-messenger astronomy. In this paper, we present follow-up observations of the gravitational wave event GW170817 and its electromagnetic counterpart SSS17a/DLT17ck (IAU label AT2017gfo) by 14 Australian telescopes and partner observatories as part of Australian-based and Australian-led research programs. We report early- to late-time multi-wavelength observations, including optical imaging and spectroscopy, mid-infrared imaging, radio imaging, and searches for fast radio bursts. Our optical spectra reveal that the transient source emission cooled from approximately 6 400 K to 2 100 K over a 7-d period and produced no significant optical emission lines. The spectral profiles, cooling rate, and photometric light curves are consistent with the expected outburst and subsequent processes of a binary neutron star merger. Star formation in the host galaxy probably ceased at least a Gyr ago, although there is evidence for a galaxy merger. Binary pulsars with short (100 Myr) decay times are therefore unlikely progenitors, but pulsars like PSR B1534+12 with its 2.7 Gyr coalescence time could produce such a merger. The displacement (~2.2 kpc) of the binary star system from the centre of the main galaxy is not unusual for stars in the host galaxy or stars originating in the merging galaxy, and therefore any constraints on the kick velocity imparted to the progenitor are poor.
Socio-economic variations in the mental health treatment gap for people with anxiety, mood, and substance use disorders: results from the WHO World Mental Health (WMH) surveys
- S. Evans-Lacko, S. Aguilar-Gaxiola, A. Al-Hamzawi, J. Alonso, C. Benjet, R. Bruffaerts, W. T. Chiu, S. Florescu, G. de Girolamo, O. Gureje, J. M. Haro, Y. He, C. Hu, E. G. Karam, N. Kawakami, S. Lee, C. Lund, V. Kovess-Masfety, D. Levinson, F. Navarro-Mateu, B. E. Pennell, N. A. Sampson, K. M. Scott, H. Tachimori, M. ten Have, M. C. Viana, D. R. Williams, B. J. Wojtyniak, Z. Zarkov, R. C. Kessler, S. Chatterji, G. Thornicroft
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- Journal:
- Psychological Medicine / Volume 48 / Issue 9 / July 2018
- Published online by Cambridge University Press:
- 27 November 2017, pp. 1560-1571
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Background
The treatment gap between the number of people with mental disorders and the number treated represents a major public health challenge. We examine this gap by socio-economic status (SES; indicated by family income and respondent education) and service sector in a cross-national analysis of community epidemiological survey data.
MethodsData come from 16 753 respondents with 12-month DSM-IV disorders from community surveys in 25 countries in the WHO World Mental Health Survey Initiative. DSM-IV anxiety, mood, or substance disorders and treatment of these disorders were assessed with the WHO Composite International Diagnostic Interview (CIDI).
ResultsOnly 13.7% of 12-month DSM-IV/CIDI cases in lower-middle-income countries, 22.0% in upper-middle-income countries, and 36.8% in high-income countries received treatment. Highest-SES respondents were somewhat more likely to receive treatment, but this was true mostly for specialty mental health treatment, where the association was positive with education (highest treatment among respondents with the highest education and a weak association of education with treatment among other respondents) but non-monotonic with income (somewhat lower treatment rates among middle-income respondents and equivalent among those with high and low incomes).
ConclusionsThe modest, but nonetheless stronger, an association of education than income with treatment raises questions about a financial barriers interpretation of the inverse association of SES with treatment, although future within-country analyses that consider contextual factors might document other important specifications. While beyond the scope of this report, such an expanded analysis could have important implications for designing interventions aimed at increasing mental disorder treatment among socio-economically disadvantaged people.