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Pantazatos SP, Ogden T, Melhem NM, Brent DA, Lesanpezeshki M, Burke A, Keilp JG, Miller JM, Mann JJ. Smaller cornu ammonis (CA3) as a potential risk factor for suicidal behavior in mood disorders. J Psychiatr Res 2023; 163:262-269. [PMID: 37244064 DOI: 10.1016/j.jpsychires.2023.05.051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 05/05/2023] [Accepted: 05/15/2023] [Indexed: 05/29/2023]
Abstract
Mood disorders and suicidal behavior have moderate heritability and familial transmission, and are associated with smaller hippocampal volumes. However, it is unclear whether hippocampal alterations reflect heritable risk or epigenetic effects of childhood adversity, compensatory mechanisms, illness-related changes, or treatment effects. We sought to separate the relationships of hippocampal substructure volumes to mood disorder, suicidal behavior, and risk and resilience to both by examining high familial risk individuals (HR) who have passed the age of greatest risk for psychopathology onset. Structural brain imaging and hippocampal substructure segmentation quantified Cornu Ammonis (CA1-4), dentate gyrus, and subiculum gray matter volumes in healthy volunteers (HV, N = 25) and three groups with one or more relatives reporting early-onset mood disorder and suicide attempt: 1. Unaffected HR (N = 20); 2. HR with lifetime mood disorder and no suicide attempt (HR-MOOD, N = 25); and 3. HR with lifetime mood disorder and a previous suicide attempt (HR-MOOD + SA, N = 18). Findings were tested in an independent cohort not selected for family history (HV, N = 47; MOOD, N = 44; and MOOD + SA, N = 21). Lower CA3 volume was found in HR (vs. HV), consistent with the direction of previously published findings in MOOD+SA (vs. HV and MOOD), suggesting the finding reflects a familial biological risk marker, not illness or treatment-related sequelae, of suicidal behavior and mood disorder. Familial suicide risk may be mediated in part by smaller CA3 volume. The structure may serve as a risk indicator and therapeutic target for suicide prevention strategies in high-risk families.
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Affiliation(s)
- Spiro P Pantazatos
- Molecular Imaging and Neuropathology Area, New York State Psychiatric Institute, New York, NY, USA; Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA.
| | - Todd Ogden
- Molecular Imaging and Neuropathology Area, New York State Psychiatric Institute, New York, NY, USA; Mailman School of Public Health, Columbia University, New York, USA
| | - Nadine M Melhem
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - David A Brent
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Mohammad Lesanpezeshki
- Molecular Imaging and Neuropathology Area, New York State Psychiatric Institute, New York, NY, USA; Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
| | - Ainsley Burke
- Molecular Imaging and Neuropathology Area, New York State Psychiatric Institute, New York, NY, USA; Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
| | - John G Keilp
- Molecular Imaging and Neuropathology Area, New York State Psychiatric Institute, New York, NY, USA; Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
| | - Jeffrey M Miller
- Molecular Imaging and Neuropathology Area, New York State Psychiatric Institute, New York, NY, USA; Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
| | - J John Mann
- Molecular Imaging and Neuropathology Area, New York State Psychiatric Institute, New York, NY, USA; Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA.
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Knudsen GM, Ganz M, Appelhoff S, Boellaard R, Bormans G, Carson RE, Catana C, Doudet D, Gee AD, Greve DN, Gunn RN, Halldin C, Herscovitch P, Huang H, Keller SH, Lammertsma AA, Lanzenberger R, Liow JS, Lohith TG, Lubberink M, Lyoo CH, Mann JJ, Matheson GJ, Nichols TE, Nørgaard M, Ogden T, Parsey R, Pike VW, Price J, Rizzo G, Rosa-Neto P, Schain M, Scott PJ, Searle G, Slifstein M, Suhara T, Talbot PS, Thomas A, Veronese M, Wong DF, Yaqub M, Zanderigo F, Zoghbi S, Innis RB. Guidelines for the content and format of PET brain data in publications and archives: A consensus paper. J Cereb Blood Flow Metab 2020; 40:1576-1585. [PMID: 32065076 PMCID: PMC7370374 DOI: 10.1177/0271678x20905433] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
It is a growing concern that outcomes of neuroimaging studies often cannot be replicated. To counteract this, the magnetic resonance (MR) neuroimaging community has promoted acquisition standards and created data sharing platforms, based on a consensus on how to organize and share MR neuroimaging data. Here, we take a similar approach to positron emission tomography (PET) data. To facilitate comparison of findings across studies, we first recommend publication standards for tracer characteristics, image acquisition, image preprocessing, and outcome estimation for PET neuroimaging data. The co-authors of this paper, representing more than 25 PET centers worldwide, voted to classify information as mandatory, recommended, or optional. Second, we describe a framework to facilitate data archiving and data sharing within and across centers. Because of the high cost of PET neuroimaging studies, sample sizes tend to be small and relatively few sites worldwide have the required multidisciplinary expertise to properly conduct and analyze PET studies. Data sharing will make it easier to combine datasets from different centers to achieve larger sample sizes and stronger statistical power to test hypotheses. The combining of datasets from different centers may be enhanced by adoption of a common set of best practices in data acquisition and analysis.
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Affiliation(s)
- Gitte M Knudsen
- Neurobiology Research Unit, Rigshospital and University of Copenhagen, Copenhagen, Denmark
| | - Melanie Ganz
- Neurobiology Research Unit, Rigshospital and University of Copenhagen, Copenhagen, Denmark
| | - Stefan Appelhoff
- Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Guy Bormans
- Laboratory for Radiopharmaceutical Research, KU, Leuven, Belgium
| | - Richard E Carson
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, USA
| | - Ciprian Catana
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School, Department of Radiology, Boston, MA, USA
| | - Doris Doudet
- Department of Medicine/Neurology, Pacific Parkinson Research Center, Vancouver, Canada
| | - Antony D Gee
- Clinical PET Centre, King's College London, London, UK
| | - Douglas N Greve
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School, Department of Radiology, Boston, MA, USA
| | - Roger N Gunn
- Invicro and Division of Brain Sciences, Imperial College London, London, UK
| | - Christer Halldin
- Center for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden
| | - Peter Herscovitch
- Department of Positron Emission Tomography, National Institutes of Health, Bethesda, USA
| | - Henry Huang
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, USA
| | - Sune H Keller
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Adriaan A Lammertsma
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Wien, Austria
| | - Jeih-San Liow
- Molecular Imaging Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, USA
| | | | - Mark Lubberink
- Uppsala University, Department of Surgical Sciences/Radiology and Nuclear Medicine, Uppsala University Hospital, Department of Medical Physics, Sweden
| | - Chul H Lyoo
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - J John Mann
- Department of Psychiatry, Molecular Imaging and Neuropathology Division, Columbia University, New York, USA
| | - Granville J Matheson
- Center for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden
| | - Thomas E Nichols
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, UK
| | - Martin Nørgaard
- Neurobiology Research Unit, Rigshospital and University of Copenhagen, Copenhagen, Denmark
| | - Todd Ogden
- Columbia Mailman School of Public Health, Columbia University, New York, USA
| | - Ramin Parsey
- Department of Psychiatry, School of Medicine, Stony Brook University, Stony Brook, NY, USA
| | - Victor W Pike
- Molecular Imaging Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, USA
| | - Julie Price
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School, Department of Radiology, Boston, MA, USA
| | - Gaia Rizzo
- Invicro and Division of Brain Sciences, Imperial College London, London, UK
| | - Pedro Rosa-Neto
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada.,Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, Douglas Mental Health University Institute, Montreal, Canada
| | - Martin Schain
- Columbia Mailman School of Public Health, Columbia University, New York, USA
| | - Peter Jh Scott
- Department of Radiology, University of Michigan, Ann Arbor, USA
| | - Graham Searle
- Invicro and Division of Brain Sciences, Imperial College London, London, UK
| | - Mark Slifstein
- Department of Psychiatry, School of Medicine, Stony Brook University, Stony Brook, NY, USA
| | - Tetsuya Suhara
- Institute for Quantum Life Science, National Institute for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Peter S Talbot
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Adam Thomas
- National Institute of Mental Health, Bethesda, USA
| | - Mattia Veronese
- Centre for Neuroimaging Sciences, King's College London, London, UK
| | - Dean F Wong
- Department of Radiology, Johns Hopkins Hospital, Baltimore, USA
| | - Maqsood Yaqub
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | | | - Sami Zoghbi
- Molecular Imaging Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, USA
| | - Robert B Innis
- Molecular Imaging Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, USA
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Ciarleglio A, Petkova E, Ogden T, Tarpey T. Constructing treatment decision rules based on scalar and functional predictors when moderators of treatment effect are unknown. J R Stat Soc Ser C Appl Stat 2018; 67:1331-1356. [PMID: 30546161 DOI: 10.1111/rssc.12278] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Treatment response heterogeneity poses serious challenges for selecting treatment for many diseases. To better understand this heterogeneity and to help in determining the best patient-specific treatments for a given disease, many clinical trials are collecting large amounts of patient-level data prior to administering treatment in the hope that some of these data can be used to identify moderators of treatment effect. These data can range from simple scalar values to complex functional data such as curves or images. Combining these various types of baseline data to discover "biosignatures" of treatment response is crucial for advancing precision medicine. Motivated by the problem of selecting optimal treatment for subjects with depression based on clinical and neuroimaging data, we present an approach that both (1) identifies covariates associated with differential treatment effect and (2) estimates a treatment decision rule based on these covariates. We focus on settings where there is a potentially large collection of candidate biomarkers consisting of both scalar and functional data. The validity of the proposed approach is justified via extensive simulation experiments and illustrated using data from a placebo-controlled clinical trial investigating antidepressant treatment response in subjects with depression.
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Affiliation(s)
- Adam Ciarleglio
- Mailman School of Public Health, Columbia University and New York State Psychiatric Institute, New York, U. S. A
| | - Eva Petkova
- New York University School of Medicine, New York, U. S. A
| | - Todd Ogden
- Mailman School of Public Health, Columbia University, New York, U. S. A
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Perlman G, Bartlett E, DeLorenzo C, Weissman M, McGrath P, Ogden T, Jin T, Adams P, Trivedi M, Kurian B, Oquendo M, McInnis M, Weyandt S, Fava M, Cooper C, Malchow A, Parsey R. Cortical thickness is not associated with current depression in a clinical treatment study. Hum Brain Mapp 2017; 38:4370-4385. [PMID: 28594150 DOI: 10.1002/hbm.23664] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2016] [Revised: 05/13/2017] [Accepted: 05/16/2017] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Reduced cortical thickness is a candidate biological marker of depression, although findings are inconsistent. This could reflect analytic heterogeneity, such as use of region-wise cortical thickness based on the Freesurfer Desikan-Killiany (DK) atlas or surface-based morphometry (SBM). The Freesurfer Destrieux (DS) atlas (more, smaller regions) has not been utilized in depression studies. This could also reflect differential gender and age effects. METHODS Cortical thickness was collected from 170 currently depressed adults and 52 never-depressed adults. Visually inspected and approved Freesurfer-generated surfaces were used to extract cortical thickness estimates according to the DK atlas (68 regions) and DS atlas (148 regions) for region-wise analysis (216 total regions) and for SBM. RESULTS Overall, except for small effects in a few regions, the two region-wise approaches generally failed to discriminate depressed adults from nondepressed adults or current episode severity. Differential effects by age and gender were also rare and small in magnitude. Using SBM, depressed adults showed a significantly thicker cluster in the left supramarginal gyrus than nondepressed adults (P = 0.047) but there were no associations with current episode severity. CONCLUSIONS Three analytic approaches (i.e., DK atlas, DS atlas, and SBM) converge on the notion that cortical thickness is a relatively weak discriminator of current depression status. Differential age and gender effects do not appear to represent key moderators. Robust associations with demographic factors will likely hinder translation of cortical thickness into a clinically useful biomarker. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc. Hum Brain Mapp 38:4370-4385, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Greg Perlman
- Department of Psychiatry, Stony Brook University, Stony Brook, New York
| | - Elizabeth Bartlett
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York
| | | | - Myrna Weissman
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY, USA
| | - Patrick McGrath
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY, USA
| | - Todd Ogden
- Department of Biostatistics, Mailman School of Public Health, Columbia University
| | - Tony Jin
- Department of Psychiatry, Stony Brook University, Stony Brook, New York
| | - Phillip Adams
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY, USA
| | - Madhukar Trivedi
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Benji Kurian
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Maria Oquendo
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY, USA
| | - Melvin McInnis
- Department of Psychiatry, University of Michigan, Ann Arbor, Michigan
| | - Sarah Weyandt
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Maurizio Fava
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
| | - Crystal Cooper
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Ashley Malchow
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Ramin Parsey
- Department of Psychiatry, Stony Brook University, Stony Brook, New York
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5
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Delaparte L, Yeh FC, Adams P, Malchow A, Trivedi MH, Oquendo MA, Deckersbach T, Ogden T, Pizzagalli DA, Fava M, Cooper C, McInnis M, Kurian BT, Weissman MM, McGrath PJ, Klein DN, Parsey RV, DeLorenzo C. A comparison of structural connectivity in anxious depression versus non-anxious depression. J Psychiatr Res 2017; 89:38-47. [PMID: 28157545 PMCID: PMC5374003 DOI: 10.1016/j.jpsychires.2017.01.012] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2016] [Revised: 12/16/2016] [Accepted: 01/19/2017] [Indexed: 12/13/2022]
Abstract
BACKGROUND Major depressive disorder (MDD) and anxiety disorders are highly co-morbid. Research has shown conflicting evidence for white matter alteration and amygdala volume reduction in mood and anxiety disorders. To date, no studies have examined differences in structural connectivity between anxious depressed and non-anxious depressed individuals. This study compared fractional anisotropy (FA) and density of selected white matter tracts and amygdala volume between anxious depressed and non-anxious depressed individuals. METHODS 64- direction DTI and T1 scans were collected from 110 unmedicated subjects with MDD, 39 of whom had a co-morbid anxiety disorder diagnosis. Region of interest (ROI) and tractography methods were performed to calculate amygdala volume and FA in the uncinate fasciculus, respectively. Diffusion connectometry was performed to identify whole brain group differences in white matter health. Correlations were computed between biological and clinical measures. RESULTS Tractography and ROI analyses showed no significant differences between bilateral FA values or bilateral amygdala volumes when comparing the anxious depressed and non-anxious depressed groups. The diffusion connectometry analysis showed no significant differences in anisotropy between the groups. Furthermore, there were no significant relationships between MRI-based and clinical measures. CONCLUSION The lack of group differences could indicate that structural connectivity and amygdalae volumes of those with anxious-depression are not significantly altered by a co-morbid anxiety disorder. Improving understanding of anxiety co-morbid with MDD would facilitate development of treatments that more accurately target the underlying networks.
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Affiliation(s)
- Lauren Delaparte
- Department of Psychology, Stony Brook University, Stony Brook, NY, USA; Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA.
| | - Fang-Cheng Yeh
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, Pittsburgh
| | - Phil Adams
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University College of Physicians and Surgeons, New York, New York
| | - Ashley Malchow
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Madhukar H. Trivedi
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Maria A. Oquendo
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University College of Physicians and Surgeons, New York, New York
| | - Thilo Deckersbach
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
| | - Todd Ogden
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University College of Physicians and Surgeons, New York, New York
| | | | - Maurizio Fava
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
| | - Crystal Cooper
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Melvin McInnis
- Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor, Michigan
| | - Benji T. Kurian
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Myrna M. Weissman
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University College of Physicians and Surgeons, New York, New York
| | - Patrick J. McGrath
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University College of Physicians and Surgeons, New York, New York
| | - Daniel N. Klein
- Department of Psychology, Stony Brook University, Stony Brook, New York
| | - Ramin V. Parsey
- Department of Psychiatry, Stony Brook University, Stony Brook, New York,Department of Radiology, Stony Brook University, Stony Brook, New York
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Abstract
For regression models with functional responses and scalar predictors, it is common for the number of predictors to be large. Despite this, few methods for variable selection exist for function-on-scalar models, and none account for the inherent correlation of residual curves in such models. By expanding the coefficient functions using a B-spline basis, we pose the function-on-scalar model as a multivariate regression problem. Spline coefficients are grouped within coefficient function, and group-minimax concave penalty (MCP) is used for variable selection. We adapt techniques from generalized least squares to account for residual covariance by "pre-whitening" using an estimate of the covariance matrix, and establish theoretical properties for the resulting estimator. We further develop an iterative algorithm that alternately updates the spline coefficients and covariance; simulation results indicate that this iterative algorithm often performs as well as pre-whitening using the true covariance, and substantially outperforms methods that neglect the covariance structure. We apply our method to two-dimensional planar reaching motions in a study of the effects of stroke severity on motor control, and find that our method provides lower prediction errors than competing methods.
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Affiliation(s)
- Yakuan Chen
- Department of Biostatistics, Mailman School of Public Health, Columbia University
| | - Jeff Goldsmith
- Department of Biostatistics, Mailman School of Public Health, Columbia University
| | - Todd Ogden
- Department of Biostatistics, Mailman School of Public Health, Columbia University
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Kim J, Ogden T. Variance components estimation in the presence of drift. CSAM 2016. [DOI: 10.5351/csam.2016.23.1.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Jaehee Kim
- Department of Statistics, Duksung Women’s University, Korea
| | - Todd Ogden
- Department of Biostatistics, Columbia University, USA
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Thøgersen J, Nielsen J, Knak Jensen S, Keiding S, Odelius M, Ogden T, Réhault J, Helbing J. The rotation of NO 3−as a probe of molecular ion - water interactions. EPJ Web of Conferences 2013. [DOI: 10.1051/epjconf/20134106002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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11
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Chen P, Hao W, Rife L, Wang XP, Shen D, Chen J, Ogden T, Van Boemel GB, Wu L, Yang M, Fong HK. A photic visual cycle of rhodopsin regeneration is dependent on Rgr. Nat Genet 2001; 28:256-60. [PMID: 11431696 DOI: 10.1038/90089] [Citation(s) in RCA: 132] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
During visual excitation, rhodopsin undergoes photoactivation and bleaches to opsin and all-trans-retinal. To regenerate rhodopsin and maintain normal visual sensitivity, the all-trans isomer must be metabolized and reisomerized to produce the chromophore 11-cis-retinal in biochemical steps that constitute the visual cycle and involve the retinal pigment epithelium (RPE; refs. 3-8). A key step in the visual cycle is isomerization of an all-trans retinoid to 11-cis-retinol in the RPE (refs. 9-11). It could be that the retinochrome-like opsins, peropsin, or the retinal G protein-coupled receptor (RGR) opsin12-16 are isomerases in the RPE. In contrast to visual pigments, RGR is bound predominantly to endogenous all-trans-retinal, and irradiation of RGR in vitro results in stereospecific conversion of the bound all-trans isomer to 11-cis-retinal. Here we show that RGR is involved in the formation of 11-cis-retinal in mice and functions in a light-dependent pathway of the rod visual cycle. Mutations in the human gene encoding RGR are associated with retinitis pigmentosa.
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Affiliation(s)
- P Chen
- Department of Ophthalmology, University of Southern California, Los Angeles, California 90033 USA
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Ogden T. Editorial Note. The Annals of Occupational Hygiene 2001. [DOI: 10.1016/s0003-4878(00)00085-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
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13
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Ogden T. Magic Mineral to Killer Dust: Turner & Newall and the Asbestos Hazard; Geoffrey Tweedale. Oxford University Press, Oxford, UK. ISBN 0-19-829690-8. £40. The Annals of Occupational Hygiene 2000. [DOI: 10.1016/s0003-4878(00)00042-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
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Ogden T. Reverie and metaphor. Some thoughts on how I work as a psychoanalyst. Int J Psychoanal 1997; 78 ( Pt 4):719-32. [PMID: 9306185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
In this paper, the author presents parts of an ongoing internal dialogue concerning how he works as an analyst. He describes the way in which he attempts to sense what is most alive and most real in each analytic encounter, as well as his use of his own reveries in his effort to locate himself in what is going on at an unconscious level in the analytic relationship. The author views each analytic situation as reflecting, to a large degree, a specific type of unconscious intersubjective construction. Since unconscious experience is by definition outside of conscious awareness, the analyst must make use of indirect (associational) methods such as the scrutiny of his own reverie experience in his efforts to 'catch the drift' (Freud, 1923, p. 239) of the unconscious intersubjective constructions being generated. Reveries (and all other derivatives of the unconscious) are viewed not as glimpses into the unconscious, but as metaphorical expressions of what the unconscious experience is like. In the author's experience, when an analysis is 'a going concern', the analytic dialogue often takes the form of a verbal 'squiggle game' (Winnicott, 1971a, p. 3) in which the analytic pair elaborates and modifies the metaphors that the other has unself-consciously introduced. The analytic use of reverie and of the role of metaphor in the analytic experience is clinically illustrated.
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Abstract
The effects of intravitreal injections of blood or ferrous chloride solutions on experimental posterior penetrating eye injury in the rabbit are described. An 8-mm standard posterior penetrating wound, without additional manipulation, healed without retinal detachment or membrane formation. Injection into the vitreous cavity of blood or ferrous chloride solution in addition to the wound resulted in fibroblastic proliferation with membrane formation. A critical amount of blood or iron solution was associated with marked traction and traction retinal detachment. Severe inflammation in association with the development of thick intravitreal membranes was also observed in eyes receiving the ferrous chloride solutions, the extent of which was related to the severity of the retinal detachment. These results show that iron is an important stimulus to inflammation and to intravitreal fibroblastic proliferation in rabbit eyes with posterior penetrating eye injuries.
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Affiliation(s)
- O Vergara
- Department of Ophthalmology, University of Southern California School of Medicine, Los Angeles
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