[Mechanism of Sijunzi Decoction in treatment of Alzheimer's disease based on UPLC-Q-TOF-MS, network pharmacology, and experimental verification].

The study identified the blood-entering components of Sijunzi Decoction after gavage administration in rats by UPLC-Q-TOF-MS/MS, and investigated the mechanism of Sijunzi Decoction in treating Alzheimer's disease by virtue of network pharmacology, molecular docking, and experimental verification. The blood-entering components of Sijunzi Decoction were identified based on the mass spectra and data from literature and databases. The potential targets of the above-mentioned blood-entering components in the treatment of Alzheimer's disease were searched against PharmMapper, OMIM, DisGeNET, GeneCards, and TTD. Next, STRING was employed to establish a protein-protein interaction(PPI) network. DAVID was used to perform the Gene Ontology(GO) annotation and the Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment. Cytoscape 3.9.0 was used to carry out visual analysis. AutoDock Vina and PyMOL were used for molecular docking of the blood-entering components with the potential targets. Finally, the phosphatidylinositol 3-kinase(PI3K)/protein kinase B(Akt) signaling pathway enriched by the KEGG analysis was selected for validation by animal experiments. The results showed that 17 blood-entering components were detected in the serum samples after administration. Among them, poricoic acid B, liquiritigenin, atractylenolide Ⅱ, atractylenolide Ⅲ, ginsenoside Rb_1, and glycyrrhizic acid were the key components of Sijunzi Decoction in treating Alzheimer's disease. HSP90AA1, PPARA, SRC, AR, and ESR1 were the main targets for Sijunzi Decoction to treat Alzheimer's disease. Molecular docking showed that the components bound well with the targets. Therefore, we hypothesized that the mechanism of Sijunzi Decoction in treating Alzheimer's disease may be associated with the PI3K/Akt, cancer treatment, and mitogen-activated protein kinase(MAPK) signaling pathways. The results of animal experiments showed that Sijunzi Decoction significantly attenuated the neuronal damage in the hippocampal dentate gyrus area, increased the neurons, and raised the ratios of p-Akt/Akt and p-PI3K/PI3K in the hippocampus of mice. In conclusion, Sijunzi Decoction may treat Alzheimer's disease by activating the PI3K/Akt signaling pathway. The findings of this study provide a reference for further studies about the mechanism of action and clinical application of Sijunzi Decoction.

Central deficiency of norepinephrine synthesis and norepinephrinergic neurotransmission contributes to seizure-induced respiratory arrest.

Sudden unexpected death in epilepsy (SUDEP) is the leading cause of mortality in patients with intractable epilepsy. However, the pathogenesis of SUDEP seems to be poorly understood. Our previous findings showed that the incidence of seizure-induced respiratory arrest (S-IRA) was markedly reduced by atomoxetine in a murine SUDEP model. Because the central norepinephrine α-1 receptor (NEα-1R) plays a vital role in regulating respiratory function, we hypothesized that the suppression of S-IRA by atomoxetine was mediated by NE/NEα-1R interactions that can be reversed by NEα-1R antagonism. We examined whether atomoxetine-mediated suppression of S-IRA evoked by either acoustic stimulation or pentylenetetrazole (PTZ) in DBA/1 mice can be reversed by intraperitoneal (IP) and intracerebroventricular (ICV) administration of prazosin, a selective antagonist of NEα-1R. The content and activity of tyrosine hydroxylase (TH), a rate-limiting enzyme for NE synthesis, in the lower brainstem was measured by ELISA. Electroencephalograms (EEG) were obtained from using the PTZ-evoked SUDEP model. In our models, atomoxetine-mediated suppression of S-IRA evoked by either acoustic stimulation or PTZ was significantly reversed by low doses of IP and ICV prazosin. Neither repetitive acoustic stimulation nor S-IRA reduced TH levels in lower brainstem. However, the enzyme activity of TH levels in lower brainstem was significantly increased by mechanical ventilation with DBA/1 mice, which makes the dying DBA/1 mice suffering from S-IRA and SUDEP recover. EEG data showed that although the protective effect of atomoxetine was reversed by prazosin, neither drug suppressed EEG activity. These data suggest that deficient synthesis of NE and norepinephrinergic neurotransmission contributed to S-IRA and that the NEα-1R is a potential therapeutic target for the prevention of SUDEP.

Associated and predictive factors of quality of life in patients with temporal lobe epilepsy.

OBJECTIVE: Identifying the factors that are correlated with and predictive of reduced quality of life (QOL) is essential to optimize the treatment of epilepsy and the management of comorbidities. METHODS: We analyzed the independent associations between the Quality of Life in Epilepsy-31 (QOLIE-31) inventory and the demographic, clinical, psychiatric, and cognitive variables of 47 consecutive patients with temporal lobe epilepsy (TLE). Predictors of the correlated variables were analyzed by multiple linear regression analysis. RESULTS: The QOLIE-31 total score was positively correlated with occupational status and Mini-Mental State Examination (MMSE) scores (r = 0.290 and 0.295, respectively; P < 0.05) and negatively correlated with the duration of seizures, adverse effects of antiepileptic drugs (AEDs), and the Pittsburgh Sleep Quality Inventory (PSQI), Self-rating Anxiety Scale (SAS), and Self-rating Depression Scale (SDS) scores (r = -0.357, 0.321, 0.328, -0.672, and -0.565, respectively; P < 0.05; P < 0.01 for the SAS and SDS). In the final multivariate regression model, anxiety, long durations of seizures, adverse effects of AEDs, and depression explained approximately 60.6% (adjusted R2 = 0.606, R coefficient = 0.800) of the QOLIE-31 overall score variance. CONCLUSION: Anxiety, long durations of seizures, adverse effects of AEDs, and depression were significant predictors of QOL, and these variables had relatively high prediction capacities for the overall QOLIE-31 in the regression model. Comorbid anxiety is the most powerful negative determinant of the QOLIE-31.