Translational Research Approach to Neurobiology and Treatment of Major Depression: From Animal Models to Clinical Treatment
Neuromethods, ISSN: 1940-6045, Vol: 179, Page: 57-84
2022
- 9Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Captures9
- Readers9
Book Chapter Description
The literature indicates that about two-thirds of patients with depression do not achieve remission on initial treatment and that the likelihood of non-response increases with the number of treatments tested. Providing ineffective therapies has significant consequences on individual and societal costs, including persistent distress and poor well-being, risk of suicide, loss of productivity, and waste of healthcare resources. The vast literature on depression indicates a large number of biomarkers that may improve the treatment of people with depression. In addition to the neurotransmitter and neuroendocrine markers that have been studied extensively for many decades, recent data points to the inflammatory response (and more generally the immune system) and metabolic and growth factors involved in depression. The combination of these biological biomarkers found in animals has led to the creation of behavioral models in rodents and zebrafish capable of better understanding depression and contributing to the discovery of new antidepressants.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85126211387&origin=inward; http://dx.doi.org/10.1007/978-1-0716-2083-0_4; https://link.springer.com/10.1007/978-1-0716-2083-0_4; https://dx.doi.org/10.1007/978-1-0716-2083-0_4; https://link.springer.com/protocol/10.1007/978-1-0716-2083-0_4
Springer Science and Business Media LLC
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