Chapter title |
Application of Proteomic Techniques for Improved Stratification and Treatment of Schizophrenia Patients
|
---|---|
Chapter number | 1 |
Book title |
Proteomic Methods in Neuropsychiatric Research
|
Published in |
Advances in experimental medicine and biology, March 2017
|
DOI | 10.1007/978-3-319-52479-5_1 |
Pubmed ID | |
Book ISBNs |
978-3-31-952478-8, 978-3-31-952479-5, 978-3-31-952478-8, 978-3-31-952479-5
|
Authors |
Steiner, Johann, Guest, Paul C., Martins-de-Souza, Daniel, Johann Steiner, Paul C. Guest, Daniel Martins-de-Souza |
Editors |
Paul C. Guest |
Abstract |
For major psychiatric disorders such as schizophrenia, there have been shortcomings in the translation of scientific findings into new treatments and this has led to diminished interest for large pharmaceutical companies. This chapter describes how incorporation of proteomic approaches into the clinical pipeline can lead to identification and implementation of biomarker tests for improved patient characterization, prediction of treatment response and monitoring treatment effects to help revitalize efforts in this important area. In addition, the construction of specific biomarker tests for disease prediction should smooth the progress of early intervention strategies which, in turn, may help to slow disease onset or progression. Finally, the development of purpose-built biomarker tests using lab-on-a-chip platforms with smartphone readouts will help to shift the diagnosis and treatment of this major psychiatric disorder into point-of-care settings for increased effectiveness and improved patient outcomes. |
X Demographics
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Brazil | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 37 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 7 | 19% |
Researcher | 6 | 16% |
Student > Bachelor | 5 | 14% |
Student > Master | 4 | 11% |
Other | 3 | 8% |
Other | 6 | 16% |
Unknown | 6 | 16% |
Readers by discipline | Count | As % |
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Medicine and Dentistry | 8 | 22% |
Psychology | 8 | 22% |
Computer Science | 4 | 11% |
Nursing and Health Professions | 3 | 8% |
Biochemistry, Genetics and Molecular Biology | 2 | 5% |
Other | 4 | 11% |
Unknown | 8 | 22% |