scholarly journals Blood and urinary metabolomic evidence validating traditional Chinese medicine diagnostic classification of major depressive disorder

2018 ◽  
Vol 13 (1) ◽  
Author(s):  
Lan-Ying Liu ◽  
Hong-Jian Zhang ◽  
Li-Yuan Luo ◽  
Jin-Bao Pu ◽  
Wei-Qing Liang ◽  
...  
2014 ◽  
Vol 2014 ◽  
pp. 1-14
Author(s):  
Tzu-Chieh Hung ◽  
Wen-Yuan Lee ◽  
Kuen-Bao Chen ◽  
Hung-Jin Huang ◽  
Yueh-Chiu Chan ◽  
...  

Recently, an important topic of major depressive disorder (MDD) had been published in 2013. MDD is one of the most prevalent and disabling mental disorders. Consequently, much research is being undertaken into the causes and treatment. It has been found that inhibition of theβform of calcium/calmodulin-dependent protein kinase type II (β-CaMKII) can ameliorate the disorder. Upon screening the traditional Chinese medicine (TCM) database by molecular docking, sengesterone, labiatic acid, and methyl 3-O-feruloylquinate were selected for molecular dynamics. After 20 ns simulation, the RMSD, total energy, and structure variation could define the protein-ligand interaction. Furthermore, sengesterone, the principle candidate compound, has been found to have an effect on the regulation of emotions and memory development. In structure variation, we find the sample functional group of important amino acids make the protein stable and have limited variation. Due to similarity of structure variations, we suggest that these compounds may have an effect onβ-CaMKII and that sengesterone may have a similar efficacy as the control. However labiatic acid may be a stronger inhibitor ofβ-CaMKII based on the larger RMSD and variation.


Author(s):  
Masakazu Higuchi ◽  
Shinichi Tokuno ◽  
Mitsuteru Nakamura ◽  
Shuji Shinohara ◽  
Shunji Mitsuyoshi ◽  
...  

Objective: In this study, we propose a voice index to identify healthy individuals, patients with bipolar disorder, and patients with major depressive disorder using polytomous logistic regression analysis.Methods: Voice features were extracted from voices of healthy individuals and patients with mental disease. Polytomous logistic regression analysis was performed for some voice features.Results: With the prediction model obtained using the analysis, we identified subject groups and were able to classify subjects into three groups with 90.79% accuracy.Conclusion: These results show that the proposed index may be used as a new evaluation index to identify depression.


2017 ◽  
Author(s):  
Dajiang Zhu ◽  
Qingyang Li ◽  
Brandalyn C. Riedel ◽  
Neda Jahanshad ◽  
Derrek P. Hibar ◽  
...  

2016 ◽  
Vol 11 (1) ◽  
Author(s):  
Wing-Fai Yeung ◽  
Ka-Fai Chung ◽  
Nevin Lian-Wen Zhang ◽  
Shi Ping Zhang ◽  
Kam-Ping Yung ◽  
...  

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