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Biomarkers in Psychiatry

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Cover of 'Biomarkers in Psychiatry'

Table of Contents

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    Book Overview
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    Chapter 41 Network Neuroscience: A Framework for Developing Biomarkers in Psychiatry
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    Chapter 42 Reappraising Preclinical Models of Separation Anxiety Disorder, Panic Disorder, and CO 2 Sensitivity: Implications for Methodology and Translation into New Treatments
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    Chapter 43 Immunological Processes in Schizophrenia Pathology: Potential Biomarkers?
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    Chapter 44 Translational Shifts in Preclinical Models of Depression: Implications for Biomarkers for Improved Treatments
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    Chapter 45 Neuroimmune Biomarkers in Mental Illness
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    Chapter 46 Imaging and Genetic Biomarkers Predicting Transition to Psychosis
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    Chapter 47 Using Pattern Classification to Identify Brain Imaging Markers in Autism Spectrum Disorder
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    Chapter 48 Deconstructing Schizophrenia: Advances in Preclinical Models for Biomarker Identification
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    Chapter 49 Imaging and Genetic Approaches to Inform Biomarkers for Anxiety Disorders, Obsessive–Compulsive Disorders, and PSTD
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    Chapter 50 Cognitive Phenotypes for Biomarker Identification in Mental Illness: Forward and Reverse Translation
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    Chapter 52 Genomic and Imaging Biomarkers in Schizophrenia
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    Chapter 57 Stem Cells to Inform the Neurobiology of Mental Illness
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    Chapter 58 Biomarkers in Neuropsychiatry: A Prospect for the Twenty-First Century?
  15. Altmetric Badge
    Chapter 64 Correction to: Imaging and Genetic Approaches to Inform Biomarkers for Anxiety Disorders, Obsessive–Compulsive Disorders, and PSTD
Attention for Chapter 48: Deconstructing Schizophrenia: Advances in Preclinical Models for Biomarker Identification
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Chapter title
Deconstructing Schizophrenia: Advances in Preclinical Models for Biomarker Identification
Chapter number 48
Book title
Biomarkers in Psychiatry
Published in
Current topics in behavioral neurosciences, January 2018
DOI 10.1007/7854_2018_48
Pubmed ID
Book ISBNs
978-3-31-999641-7, 978-3-31-999642-4
Authors

Judith A. Pratt, Brian Morris, Neil Dawson, Pratt, Judith A., Morris, Brian, Dawson, Neil

Abstract

Schizophrenia is considered to develop as a consequence of genetic and environmental factors impacting on brain neural systems and circuits during vulnerable neurodevelopmental periods, thereby resulting in symptoms in early adulthood. Understanding of the impact of schizophrenia risk factors on brain biology and behaviour can help in identifying biologically relevant pathways that are attractive for informing clinical studies and biomarker development. In this chapter, we emphasize the importance of adopting a reciprocal forward and reverse translation approach that is iteratively updated when additional new information is gained, either preclinically or clinically, for offering the greatest opportunity for discovering panels of biomarkers for the diagnosis, prognosis and treatment of schizophrenia. Importantly, biomarkers for identifying those at risk may inform early intervention strategies prior to the development of schizophrenia. Given the emerging nature of this approach in the field, this review will highlight recent research of preclinical biomarkers in schizophrenia that show the most promise for informing clinical needs with an emphasis on relevant imaging, electrophysiological, cognitive behavioural and biochemical modalities. The implementation of this reciprocal translational approach is exemplified firstly by the production and characterization of preclinical models based on the glutamate hypofunction hypothesis, genetic and environmental risk factors for schizophrenia (reverse translation), and then the recent clinical recognition of the thalamic reticular thalamus (TRN) as an important locus of brain dysfunction in schizophrenia as informed by preclinical findings (forward translation).

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 14%
Other 4 9%
Researcher 4 9%
Student > Bachelor 3 7%
Student > Ph. D. Student 3 7%
Other 5 12%
Unknown 18 42%
Readers by discipline Count As %
Psychology 7 16%
Medicine and Dentistry 5 12%
Neuroscience 4 9%
Biochemistry, Genetics and Molecular Biology 1 2%
Business, Management and Accounting 1 2%
Other 4 9%
Unknown 21 49%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 May 2018.
All research outputs
#15,535,385
of 23,088,369 outputs
Outputs from Current topics in behavioral neurosciences
#325
of 500 outputs
Outputs of similar age
#270,124
of 442,628 outputs
Outputs of similar age from Current topics in behavioral neurosciences
#8
of 10 outputs
Altmetric has tracked 23,088,369 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 500 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.0. This one is in the 23rd percentile – i.e., 23% of its peers scored the same or lower than it.
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