| Literature DB >> 31505162 |
Xi Tao1, Wanlin Yang2, Shuzhen Zhu2, Rongfang Que2, Chujuan Liu3, Tao Fan4, Jia Wang5, Danheng Mo6, Zhuohua Zhang7, Jieqiong Tan7, Kunlin Jin8, Midori A Yenari9, Tao Song10, Qing Wang11.
Abstract
Our previous studies have indicated that depression and declined cognition have been involved in some neurodegenerative diseases including Stroke, Parkinson's diseases and Vascular Parkinsonism. Post-stroke depression (PSD) is the most common psychiatric disorder following a stroke and has high morbidity and mortality. Studies on PSD are increasingly common, but the specific mechanisms remain unknown. Current research mainly includes clinical and animal aspects. Questionnaires and peripheral blood examination are two of the most common methods used to study clinical PSD. The results of questionnaires are influenced by multiple factors such as disease history, education background, occupation, economic status, family relationships and social support. There are certain limitations to blood sample testing; for example, it is influenced by cerebrovascular diseases and some other disruptions of the internal environment. It is difficult for either method to fully clarify the pathophysiological mechanism of PSD. Animal models provide alternative methods to further understand the pathophysiological mechanisms of PSD, such as the involvement of neuronal circuits and cytokines. More than ten animal models of PSD have been developed, and new models are constantly being introduced. Therefore, it is important to choose the appropriate model for any given study. In this paper, we will discuss the characteristics of the different models of PSD and comment on the advantages and disadvantages of each model, drawing from research on model innovation. Finally, we briefly describe the current assessment methods for the core symptoms of PSD models, point out the shortcomings, and present the improved sucrose preference test as a rational evaluation of anhedonia.Entities:
Keywords: Assessment; Core symptom; Model; Post stroke depression
Mesh:
Year: 2019 PMID: 31505162 DOI: 10.1016/j.expneurol.2019.113060
Source DB: PubMed Journal: Exp Neurol ISSN: 0014-4886 Impact factor: 5.330