Chapter title |
Translational implications of inflammatory biomarkers and cytokine networks in psychoneuroimmunology.
|
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Chapter number | 6 |
Book title |
Psychoneuroimmunology
|
Published in |
Methods in molecular biology, January 2012
|
DOI | 10.1007/978-1-62703-071-7_6 |
Pubmed ID | |
Book ISBNs |
978-1-62703-070-0, 978-1-62703-071-7
|
Authors |
Qing Yan, Yan, Qing |
Abstract |
Developments in psychoneuroimmunology (PNI) need to be translated into personalized medicine to achieve better clinical outcomes. One of the most critical steps in this translational process is to identify systemic biomarkers for better diagnosis and treatment. Applications of systems biology approaches in PNI would enable the insights into the correlations among various systems and different levels for the identification of the basic elements of the psychophysiological framework. Among the potential PNI biomarkers, inflammatory markers deserve special attention as they play a pivotal role linking various health conditions and disorders. The elucidation of inflammatory markers, cytokine networks, and immune-brain-behavior interactions may help establish PNI profiles for the identification of potential targets for personalized interventions in at risk populations. The understanding of the general systemic pathways among different disorders may contribute to the transition from the disease-centered medicine to patient-centered medicine. Integrative strategies targeting these factors and pathways would be useful for the prevention and treatment of a spectrum of diseases that share the common links. Examples of the translational implications of potential PNI biomarkers and networks in diseases including depression, Alzheimer's disease, obesity, cardiovascular disease, stroke, and HIV are discussed in details. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 2% |
Unknown | 51 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 10 | 19% |
Student > Master | 9 | 17% |
Student > Ph. D. Student | 7 | 13% |
Student > Doctoral Student | 4 | 8% |
Other | 3 | 6% |
Other | 7 | 13% |
Unknown | 12 | 23% |
Readers by discipline | Count | As % |
---|---|---|
Psychology | 15 | 29% |
Medicine and Dentistry | 13 | 25% |
Neuroscience | 3 | 6% |
Social Sciences | 2 | 4% |
Agricultural and Biological Sciences | 2 | 4% |
Other | 4 | 8% |
Unknown | 13 | 25% |