ABSTRACT
Chaihu-jia-Longgu-Muli decoction (CLMD) has been proven clinically effective in treating vertigo with anxiety disorder. However, the mechanism is not clear. This study aimed to explore the mechanism of CLMD in treating vertigo with anxiety disorder based on ultra-performance liquid chromatography-quadrupole time-of-flight/mass spectrometry (UPLC-Q-TOF/MS) and network pharmacology. UPLC-Q-TOF/MS was performed to identify the compounds in blood and the targets of compounds of CLMD in vertigo and anxiety were searched using databases. A protein-protein interaction network was built to screen the core targets. The core targets were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. In addition, the vertigo with anxiety rat model was used to verify the results. A total of 22 compounds were absorbed into the blood. Eighty-one potential targets associated with CLMD for vertigo with anxiety disorder were identified through network pharmacological analysis. Subsequently, GO and KEGG analysis showed that CLMD treatment for vertigo with anxiety disorder is associated with neurotransmitter levels and other pertinent physiological processes. The results of the animal experiments showed that CLMD decreased the levels of serotonin, norepinephrine and dopamine, alleviating the symptoms of vertigo and anxiety disorder in model rats. The study revealed CLMD could alleviate vertigo and anxiety symptoms through reducing the levels of neurotransmitters.
Subject(s)
Anxiety Disorders , Drugs, Chinese Herbal , Network Pharmacology , Rats, Sprague-Dawley , Vertigo , Animals , Drugs, Chinese Herbal/pharmacology , Drugs, Chinese Herbal/chemistry , Chromatography, High Pressure Liquid/methods , Rats , Vertigo/drug therapy , Male , Anxiety Disorders/drug therapy , Mass Spectrometry/methods , Protein Interaction Maps/drug effects , Disease Models, AnimalABSTRACT
The outbreak of the 2019 novel coronavirus disease (COVID-19) has impacted the mental health of healthcare providers at the frontline. Therefore, we conducted this study to estimate the prevalence rate of anxiety and insomnia and identify associated risk factors among healthcare workers in Jilin, China, during the period from January 25 to February 25, 2020. Zung's Self-Reported Anxiety Scale (SAS) and the Insomnia Severity Index (ISI) scale were used to diagnose anxiety and insomnia, respectively. Associated risk factors were identified through a multivariate logistic regression model. A total of 300 healthcare workers were invited and 236 completed the study. Of them, 234 (99.15%) were medical workers, 197 (83.47%) were working at frontline departments, and 159 (67.37%) were fighting against COVID-19. Fifty-seven respondents (24.15%) had anxiety (SAS index score ≥45) and 94 (39.83%) had insomnia (ISI score ≥8). Based on the multivariate analysis, contact with people from Hubei province during work (no vs not clear) [OR=0.25, 95%CI: 0.10-0.61] and personal protective equipment (PPE) (not in place vs in place) [OR=6.22, 95%CI: 2.23-17.40] were significantly correlated with anxiety. PPE (not in place vs in place) was the only significant risk factor of insomnia [OR=10.56, 95%CI: 4.00-27.87]. The prevalence of anxiety and insomnia was high in our study, reflecting the psychological impact of COVID-19 on healthcare workers. The unavailability of PPE in place was a significant risk factor of both anxiety and insomnia.
Subject(s)
COVID-19 , Sleep Initiation and Maintenance Disorders , Anxiety/epidemiology , China/epidemiology , Cross-Sectional Studies , Depression , Health Personnel , Humans , Pandemics , Prevalence , SARS-CoV-2 , Sleep Initiation and Maintenance Disorders/epidemiologyABSTRACT
The outbreak of the 2019 novel coronavirus disease (COVID-19) has impacted the mental health of healthcare providers at the frontline. Therefore, we conducted this study to estimate the prevalence rate of anxiety and insomnia and identify associated risk factors among healthcare workers in Jilin, China, during the period from January 25 to February 25, 2020. Zung's Self-Reported Anxiety Scale (SAS) and the Insomnia Severity Index (ISI) scale were used to diagnose anxiety and insomnia, respectively. Associated risk factors were identified through a multivariate logistic regression model. A total of 300 healthcare workers were invited and 236 completed the study. Of them, 234 (99.15%) were medical workers, 197 (83.47%) were working at frontline departments, and 159 (67.37%) were fighting against COVID-19. Fifty-seven respondents (24.15%) had anxiety (SAS index score ≥45) and 94 (39.83%) had insomnia (ISI score ≥8). Based on the multivariate analysis, contact with people from Hubei province during work (no vs not clear) [OR=0.25, 95%CI: 0.10-0.61] and personal protective equipment (PPE) (not in place vs in place) [OR=6.22, 95%CI: 2.23-17.40] were significantly correlated with anxiety. PPE (not in place vs in place) was the only significant risk factor of insomnia [OR=10.56, 95%CI: 4.00-27.87]. The prevalence of anxiety and insomnia was high in our study, reflecting the psychological impact of COVID-19 on healthcare workers. The unavailability of PPE in place was a significant risk factor of both anxiety and insomnia.