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Article ; Online: Perceptual Observer Modeling Reveals Likely Mechanisms of Face Expression Recognition Deficits in Depression.

Soto, Fabian A / Beevers, Christopher G

Biological psychiatry. Cognitive neuroscience and neuroimaging

2024

Abstract: Background: Deficits in face emotion recognition are well documented in depression, but the underlying mechanisms are poorly understood. Psychophysical observer models provide a way to precisely characterize such mechanisms. Using model-based analyses, ... ...

Abstract	Background: Deficits in face emotion recognition are well documented in depression, but the underlying mechanisms are poorly understood. Psychophysical observer models provide a way to precisely characterize such mechanisms. Using model-based analyses, we tested 2 hypotheses about how depression may reduce sensitivity to detect face emotion: 1) via a change in selectivity for visual information diagnostic of emotion or 2) via a change in signal-to-noise ratio in the system performing emotion detection. Methods: Sixty adults, one half meeting criteria for major depressive disorder and the other half healthy control participants, identified sadness and happiness in noisy face stimuli, and their responses were used to estimate templates encoding the visual information used for emotion identification. We analyzed these templates using traditional and model-based analyses; in the latter, the match between templates and stimuli, representing sensory evidence for the information encoded in the template, was compared against behavioral data. Results: Estimated happiness templates produced sensory evidence that was less strongly correlated with response times in participants with depression than in control participants, suggesting that depression was associated with a reduced signal-to-noise ratio in the detection of happiness. The opposite results were found for the detection of sadness. We found little evidence that depression was accompanied by changes in selectivity (i.e., information used to detect emotion), but depression was associated with a stronger influence of face identity on selectivity. Conclusions: Depression is more strongly associated with changes in signal-to-noise ratio during emotion recognition, suggesting that deficits in emotion detection are driven primarily by deprecated signal quality rather than suboptimal sampling of information used to detect emotion.
Language	English
Publishing date	2024-02-07
Publishing country	United States
Document type	Journal Article
ZDB-ID	2879089-3
ISSN	2451-9030 ; 2451-9022
ISSN (online)	2451-9030
ISSN	2451-9022
DOI	10.1016/j.bpsc.2024.01.011
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Oligoclonal immunoglobulin G in acute subarachnoid hemorrhage and stroke.

Tsementzis, S A / Chao, S W / Hitchcock, E R / Gill, J S / Beevers, D G

Neurology

1986 Volume 36, Issue 3, Page(s) 395–397

Abstract: Oligoclonal Ig bands were found in serum and CSF of 13 of 83 patients (16%) with verified subarachnoid hemorrhage (SAH). Serum Ig bands were more common in patients with SAH than in those with cerebral ischemia. The reverse was true with oligoclonal Ig ... ...

Abstract	Oligoclonal Ig bands were found in serum and CSF of 13 of 83 patients (16%) with verified subarachnoid hemorrhage (SAH). Serum Ig bands were more common in patients with SAH than in those with cerebral ischemia. The reverse was true with oligoclonal Ig bands in CSF. These patterns suggest that there are two different mechanisms and sites of IgG synthesis: an inflammatory process after acute stage of vascular damage and a latent immunologic process--ie, polyclonal B-cell activation by injury to the brain.
MeSH term(s)	Acute Disease ; Adult ; Aged ; Brain Ischemia/blood ; Brain Ischemia/cerebrospinal fluid ; Brain Ischemia/immunology ; Brain Ischemia/metabolism ; Cerebral Infarction/blood ; Cerebral Infarction/cerebrospinal fluid ; Cerebral Infarction/immunology ; Cerebral Infarction/metabolism ; Cerebrovascular Disorders/blood ; Cerebrovascular Disorders/cerebrospinal fluid ; Cerebrovascular Disorders/immunology ; Cerebrovascular Disorders/metabolism ; Female ; Humans ; Immunoglobulin G/analysis ; Immunoglobulin G/biosynthesis ; Immunoglobulin G/cerebrospinal fluid ; Leukocyte Count ; Lymphocytes ; Male ; Middle Aged ; Subarachnoid Hemorrhage/blood ; Subarachnoid Hemorrhage/cerebrospinal fluid ; Subarachnoid Hemorrhage/immunology ; Subarachnoid Hemorrhage/metabolism
Chemical Substances	Immunoglobulin G
Language	English
Publishing date	1986-03
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	207147-2
ISSN	1526-632X ; 0028-3878
ISSN (online)	1526-632X
ISSN	0028-3878
DOI	10.1212/wnl.36.3.395
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Article ; Online: Toward Identifying Neurocognitive Processes That Confer Suicidal Behavior.

McNamara, Mary E / Zisser, Mackenzie / Beevers, Christopher G

Biological psychiatry global open science

2021 Volume 1, Issue 1, Page(s) 3–4

Language	English
Publishing date	2021-06-15
Publishing country	United States
Document type	Journal Article
ISSN	2667-1743
ISSN (online)	2667-1743
DOI	10.1016/j.bpsgos.2021.04.008
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Article: Editorial overview: The assessment, etiology, and treatment of unipolar depression.

Beevers, Christopher G

Current opinion in psychology

2015 Volume 4, Page(s) v–viii

Language	English
Publishing date	2015-08-01
Publishing country	United States
Document type	Journal Article
ZDB-ID	2831565-0
ISSN	2352-250X ; 2352-2518 ; 2352-250X
ISSN (online)	2352-250X ; 2352-2518
ISSN	2352-250X
DOI	10.1016/j.copsyc.2015.05.003
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Article ; Online: Not just "big" data: Importance of sample size, measurement error, and uninformative predictors for developing prognostic models for digital interventions.

McNamara, Mary E / Zisser, Mackenzie / Beevers, Christopher G / Shumake, Jason

Behaviour research and therapy

2022 Volume 153, Page(s) 104086

Abstract: ... nonlinear effects (e.g., decision tree ensembles such as gradient boosted machines) perform particularly ...

Abstract	There is strong interest in developing a more efficient mental health care system. Digital interventions and predictive models of treatment prognosis will likely play an important role in this endeavor. This article reviews the application of popular machine learning models to the prediction of treatment prognosis, with a particular focus on digital interventions. Assuming that the prediction of treatment prognosis will involve modeling a complex combination of interacting features with measurement error in both the predictors and outcomes, our simulations suggest that to optimize complex prediction models, sample sizes in the thousands will be required. Machine learning methods capable of discovering complex interactions and nonlinear effects (e.g., decision tree ensembles such as gradient boosted machines) perform particularly well in large samples when the predictors and outcomes have virtually no measurement error. However, in the presence of moderate measurement error, these methods provide little or no benefit over regularized linear regression, even with very large sample sizes (N = 100,000) and a non-linear ground truth. Given these sample size requirements, we argue that the scalability of digital interventions, especially when used in combination with optimal measurement practices, provides one of the most effective ways to study treatment prediction models. We conclude with suggestions about how to implement these algorithms into clinical practice.
MeSH term(s)	Algorithms ; Humans ; Linear Models ; Machine Learning ; Prognosis ; Sample Size
Language	English
Publishing date	2022-04-14
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	211997-3
ISSN	1873-622X ; 0005-7967
ISSN (online)	1873-622X
ISSN	0005-7967
DOI	10.1016/j.brat.2022.104086
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Book: Treatment of depression in adolescents and adults

Springer, David W. / Rubin, Allen / Beevers, Christopher G.

(Clinician's guide to evidence-based practice series)

2011

Abstract: Mental health practitioners are increasingly forced to use evidence-based practices by third-party providers. However, studies have shown practitioners rarely use evidence-based practices because of difficulties obtaining training and expertise. This ... ...

Author's details	ed. by David W. Springer ; Allen Rubin and Christopher G. Beevers ed
Series title	Clinician's guide to evidence-based practice series
Abstract	"Mental health practitioners are increasingly forced to use evidence-based practices by third-party providers. However, studies have shown practitioners rarely use evidence-based practices because of difficulties obtaining training and expertise. This volume in the Clinician's Guide to Evidence-Based Practice Series provides clinicians with a beginning level of understanding in evidence-based practice for depression in a manner that fits clinician time constraints. Forgoing the typical academic approach for a more user-friendly "how-to" and "what-now" style, the book is an easy-to-use and essential resource for practitioners and students-in-training"--
Keywords	Depressive Disorder / therapy ; Cognitive Therapy ; Evidence-Based Practice ; Adolescent ; Adult
Subject code	616.85/2700835
Language	English
Size	XV, 289 S., 28 cm
Publisher	Wiley
Publishing place	Hoboken, NJ
Publishing country	United States
Document type	Book
Note	Includes bibliographical references and indexes
HBZ-ID	HT017242965
ISBN	978-0-470-58759-1 ; 0-470-58759-8
Database	Catalogue ZB MED Medicine, Health

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2012 A 2280	order for loan	Magazin

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Article ; Online: Could the association between ozone and arterial stiffness be modified by fish oil supplementation?

Han, Wenxing / Zhang, Jin / Xu, Zhihu / Yang, Teng / Huang, Jing / Beevers, Sean / Kelly, Frank / Li, Guoxing

Environmental research

2024 Volume 249, Page(s) 118354

Abstract: Background: Arterial stiffness (AS) is an important predicting factor for cardiovascular disease. However, no epidemiological studies have ever explored the mediating role of biomarkers in the association between ozone and AS, nor weather fish oil ... ...

Abstract	Background: Arterial stiffness (AS) is an important predicting factor for cardiovascular disease. However, no epidemiological studies have ever explored the mediating role of biomarkers in the association between ozone and AS, nor weather fish oil modified such association. Methods: Study participants were drawn from the UK biobank, and a total of 95,699 middle-aged and older adults were included in this study. Ozone was obtained from Community Multiscale Air Quality (CMAQ) model matched to residential addresses, fish oil from self-reported intake, and arterial stiffness was based on device measurements. First, we applied a double robust approach to explore the association between ozone or fish oil intake and arterial stiffness, adjusting for potential confounders at the individual and regional levels. Then, how triglycerides, apolipoprotein B (Apo B)/apolipoprotein A (ApoA) and non-high-density lipoprotein cholesterol (Non-HDL-C) mediate the relationship between ozone and AS. Last, the modifying role of fish oil was further explored by stratified analysis. Results: The mean age of participants was 55 years; annual average ozone exposure was associated with ASI (beta:0.189 [95%CI: 0.146 to 0.233], P < 0.001), and compared to participants who did not consume fish oil, fish oil users had a lower ASI (beta: 0.061 [95%CI: -0.111 to -0.010], P = 0.016). The relationship between ozone exposure and AS was mediated by triglycerides, ApoB/ApoA, and Non-HDL-C with mediation proportions ranging from 10.90% to 18.30%. Stratified analysis showed lower estimates on the ozone-AS relationship in fish oil users (P = 0.011). Conclusion: Ozone exposure was associated with higher levels of arterial stiffness, in contrast to fish oil consumption, which showed a protective association. The association between ozone exposure and arterial stiffness was partially mediated by some biomarkers. In the general population, fish oil consumption might provide protection against ozone-related AS.
Language	English
Publishing date	2024-02-06
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	205699-9
ISSN	1096-0953 ; 0013-9351
ISSN (online)	1096-0953
ISSN	0013-9351
DOI	10.1016/j.envres.2024.118354
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Zs.A 726: Show issues

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Article ; Online: Long-term ambient ozone, omega-3 fatty acid, genetic susceptibility, and risk of mental disorders among middle-aged and older adults in UK biobank.

Jin, Jianbo / Xu, Zhihu / Beevers, Sean D / Huang, Jing / Kelly, Frank / Li, Guoxing

Environmental research

2023 Volume 243, Page(s) 117825

Abstract: Background: Evidence linking ozone to depression and anxiety disorders remains sparse and results are heterogeneous. It remains unknown whether omega-3 fatty acid, or genetic susceptibility of mental disorders modify the impacts of ozone. The aim is to ... ...

Abstract	Background: Evidence linking ozone to depression and anxiety disorders remains sparse and results are heterogeneous. It remains unknown whether omega-3 fatty acid, or genetic susceptibility of mental disorders modify the impacts of ozone. The aim is to assess the associations of ambient ozone with depression and anxiety, and further explore the potential modification effects of omega-3 fatty acid and genetic susceptibility. Methods: In total of 257,534 participants were enrolled from 2006 to 2010 and followed up to 2016. Depression and anxiety were assessed using mental health questionnaires, primary care records and hospital admission records. The annual average concentrations of ozone were calculated and linked to individuals by home address. Dietary intake and plasma concentration were selected to reflect levels of omega-3 fatty acid. Polygenetic risk scores were selected to reflect genetic susceptibility. We examined the associations of ozone and incident mental disorders, and potential modification of omega-3 fatty acid and genetic susceptibility. Results: Incidences of depression (N = 6957) and anxiety (N = 6944) was associated with increase of ozone. Higher levels of omega-3 fatty acid might attenuate the ozone related depression risk. However, the modification effects of genetic susceptibility were not found. Conclusions: Long-term exposure to ambient ozone increase the risk of mental disorders among the middle aged and older adults, and omega-3 fatty acid could reduce the adverse effects of ozone on mental health. Higher intake of omega-3 fatty acid is a potential strategy to prevent the risks caused by ozone on public mental health.
MeSH term(s)	Middle Aged ; Humans ; Aged ; Fatty Acids, Omega-3 ; Ozone/toxicity ; UK Biobank ; Biological Specimen Banks ; Mental Disorders/chemically induced ; Mental Disorders/epidemiology ; Genetic Predisposition to Disease
Chemical Substances	Fatty Acids, Omega-3 ; Ozone (66H7ZZK23N)
Language	English
Publishing date	2023-12-09
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	205699-9
ISSN	1096-0953 ; 0013-9351
ISSN (online)	1096-0953
ISSN	0013-9351
DOI	10.1016/j.envres.2023.117825
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Article ; Online: Sir William Osler and the nature of essential hypertension.

Beevers, D G

Journal of human hypertension

2013 Volume 28, Issue 1, Page(s) 15–17

MeSH term(s)	Blood Pressure Determination/history ; England ; Essential Hypertension ; History, 20th Century ; Humans ; Hypertension/history ; Publishing/history ; Textbooks as Topic/history
Language	English
Publishing date	2013-05-23
Publishing country	England
Document type	Biography ; Historical Article ; Journal Article
ZDB-ID	639472-3
ISSN	1476-5527 ; 0950-9240
ISSN (online)	1476-5527
ISSN	0950-9240
DOI	10.1038/jhh.2013.40
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Multi‐Level Monte Carlo Models for Flood Inundation Uncertainty Quantification

Aitken, G. / Beevers, L. / Christie, M. A.

Water Resources Research. 2022 Nov., v. 58, no. 11 p.e2022WR032599-

2022

Abstract: Flood events are the most commonly occurring natural disaster, with over 5 million properties at risk in the UK alone. Changes in the global climate are expected to increase the frequency and magnitude of flood events. Flood hazard assessments, using ... ...

Abstract	Flood events are the most commonly occurring natural disaster, with over 5 million properties at risk in the UK alone. Changes in the global climate are expected to increase the frequency and magnitude of flood events. Flood hazard assessments, using climate projections as input, guide policy decisions and engineering projects to reduce the impact of large return period events. Probabilistic flood modeling is required to take into account uncertainties in climate model projections. However, the dichotomous relationship between probabilistic modeling, computational cost and model resolution limits the applicability of such techniques. This paper examines improvements to traditional Monte Carlo methods using Latin hypercube sampling (LHS) and Multi‐level Monte Carlo (MLMC) to quantify the uncertainty in flood extent resulting from input hydrograph uncertainty. The results demonstrate that MLMC is a more efficient modeling strategy than current methods (i.e., traditional Monte Carlo) with high resolution outputs produced in less time than previously possible. The novel application of MLMC technique to three Scottish case studies, demonstrating a variety of river characteristics, domain sizes and computational costs, using a high resolution 5 m grid resulted in a 99.2% reduction in computational cost compared to traditional Monte Carlo methods and up to 2.3 times speedup over Latin Hypercube Sampling.
Keywords	climate ; climate models ; hydrograph ; issues and policy ; research ; risk ; rivers ; uncertainty ; water
Language	English
Dates of publication	2022-11
Publishing place	John Wiley & Sons, Ltd
Document type	Article ; Online
Note	JOURNAL ARTICLE
ZDB-ID	5564-5
ISSN	1944-7973 ; 0043-1397
ISSN (online)	1944-7973
ISSN	0043-1397
DOI	10.1029/2022WR032599
Database	NAL-Catalogue (AGRICOLA)

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