Improved Resting-State Functional Dynamics in Post-stroke Depressive Patients After Shugan Jieyu Capsule Treatment

Abstract

Shugan Jieyu Capsule (SG), a Chinese herbal medicine mainly composed of Acanthopanax and Hypericum perforatum, has been used to ameliorate cognitive impairments and emotional problems induced by post-stroke depression (PSD), while the altered brain dynamics underlying the ameliorative effects of SG have remained unclear. Our study focused on investigating the potential neurobiological mechanisms of SG in improving the cognitive function of PSD patients via restingstate functional magnetic resonance imaging (fMRI). Fifteen PSD patients (mean ages: 64.13 ± 6.01 years) were instructed to take 0.72 g of SG twice a day for 8 weeks. PSD patients underwent fMRIs, the 24-item Hamilton Depression Scale (HAMD-24) and the Montreal Cognitive Assessment (MoCA) at baseline and the end of intervention, and these assessments were also performed on twenty-one healthy controls (HC) (mean ages: 60.67 ± 6.95 years). Additionally, the dynamic amplitude of low-frequency fluctuations (dALFF) and functional connectivity (dFC) were determined to reveal changes in dynamic functional patterns. We found that taking SG significantly reduced the depressive symptoms assessed by HAMD-24 and improved cognitive functions assessed by MoCA in PSD patients. Furthermore, at baseline, PSD patients showed decreased dALFF in the right precuneus and increased dFC between the right precuneus and left angular gyrus, compared with HC. After intervention, the dALFF and dFC variances of the abnormal patterns were reversed. Additionally, the dALFF variance in the right precuneus was positively correlated with MoCA scores in PSD patients after SG treatment. Collectively, our results indicate that SG may improve the cognitive function of PSD patients through alteration of brain dynamics. Our findings lay a foundation for the exploration of the neurobiological mechanisms of SG in ameliorating symptoms of PSD patients.

MicroRNA-124: A Key Player in Microglia-Mediated Inflammation in Neurological Diseases

“…MicroRNA (miR) is a multifunctional endogenous non-coding small molecule RNA, consisting of 18–25 nucleotide sequences and an incomplete 3′-untranslated region of the target mRNA molecule complementary combination. The miRs regulate gene expression and protein synthesis at the post-transcriptional level and participate in cell proliferation, differentiation, apoptosis, and other life activities ( Yao et al, 2020 ). Emerging studies have shown that various miRs, such as miR-21, miR-124, miR-146a, and miR-132, play key roles in neurological disorders and may be feasible therapeutic targets ( Gascon et al, 2014 ; Devaux et al, 2016 ).…”

Distinct Functional Cortico-Striato-Thalamo-Cerebellar Networks in Genetic Generalized and Focal Epilepsies with Generalized Tonic-Clonic Seizures

“…The correlation coefficient was converted to z-values using Fisher’s r-to-z transformation, to improve normality. Dynamic functional connectivity (dFC) was calculated using a sliding-window method [ 19 ]; here, the sliding window size was set as 50 TRs (100 s) and sliding step size as 5 TRs (10 s), in line with previous studies [ 20 , 21 , 22 , 23 , 24 ]. For the time series in each window, the dFC matrix was obtained.…”

Dynamic Alterations of Amplitude of Low-Frequency Fluctuations in Patients With Drug-Naïve First-Episode Early Onset Schizophrenia

“…Previous research has suggested that the window length is a critical parameter to acquire dynamic spontaneous brain activity ( Li et al, 2018 ; Cui et al, 2019 ), in which too short a window length might not allow for sufficient estimation of dynamic changes, and too long a window length may not be sufficiently sensitive to detect dynamic activity ( Zhang et al, 2019a ). Therefore, to calculate the dALFF of each participant, we applied 50 TR (125 s) as a moderate sliding window length and 5 TR (10 s) as the step size ( Li et al, 2018 ; Cui et al, 2019 ; Yao et al, 2020 ). The post-processed 202 volume of each participant was divided into 31 windows, and the ALFF map was computed within each window.…”