Anxiety, depression, insomnia, and PTSD among college students after optimizing the COVID-19 response in China.

BACKGROUND: The number of COVID-19 infections has increased sharply and quickly after optimizing the COVID-19 response in China. In the context of this population-size infection, college students' psychological response is yet to be understood. METHODS: A cross-sectional study was designed to investigate anxiety, depression, insomnia, and post-traumatic stress disorder (PTSD) symptoms among college students from December 31, 2022, to January 7, 2023. The questionnaire included the Generalized Anxiety Disorder 7 (GAD-7), Patient Health Questionnaire 9 (PHQ-9), Insomnia Severity Index (ISI), Impact of Event Scale (IES-R), and self-designed questionnaire. RESULTS: Of the 22,624 respondents, the self-reported prevalence of anxiety, depression, insomnia, PTSD, and any of the four psychological symptoms appeared as 12.7 %, 25.8 %, 11.6 %, 7.9 %, and 29.7 %, respectively. The self-reported COVID-19 infection rate was 80.2 %. Changes in the place for learning, longer time online, not recovering after infection, a higher proportion of family member infection, insufficient drug reserve, worry about sequela after infection, future studies, or employment contributed to a higher risk of anxiety/depression/insomnia symptoms or PTSD symptoms. Multinomial logistic regression showed that those who spent more extended time on the Internet, recovered after infection, and had insufficient drug reserves were less likely to have PTSD than anxiety/depression/insomnia symptoms. LIMITATIONS: The study was a non-probability sampling survey. CONCLUSIONS: Anxiety, depression, insomnia, and PTSD were common psychological symptoms among college students when infection went through a large-scale population. This study highlights the importance of continuing to care for the psychological symptoms of college students, especially timely responses to their concerns related to the epidemic situation and COVID-19 infection.

Molecular mechanism prediction analysis of compound kushen injection in the treatment of COVID-19 based on network pharmacology and molecular docking

Background: As one of the eight effective traditional Chinese medicines for the treatment of atypical pneumonia, compound Kushen injection (CKI) played an important role in combating pneumonia caused by severe acute respiratory syndrome coronavirus 2 virus in China in 2003. CKI is known to inhibit inflammation, and its main chemical components, namely matrine and oxymatrine, can promote Th cells to recognize and eliminate viruses. In this study, network pharmacology and molecular docking were used to explore the mechanisms of CKI for treating coronavirus disease 2019.

Treating COVID-19 by traditional Chinese medicine: a charming strategy?

On April 14, 2020, the State Council of China announced that "three proprietary Chinese medicines and three decoctions" of effective traditional Chinese medicine (TCM) in the treatment of the novel coronavirus pneumonia have passed clinical practice screenings. Some scholars believe that early TCM intervention of mild and moderate cases and recovery period may reduce the ratio of mild cases progressing into severe and critical cases. Some data have also suggested that the combination of TCM and Western medicine may reduce the mortality rate in severe and critical cases.

Efficacy of Xuebijing injection for the treatment of coronavirus disease 2019 via network pharmacology

Background: To evaluate the mechanism of Chinese patent drug Xuebijing (XBJ) injection in the treatment of a new coronavirus disease 2019 (COVID-19) based on network pharmacology and molecular docking technology.

Molecular mechanism prediction analysis of compound Kushen injection in the treatment of COVID-19 based on network pharmacology and molecular docking

Background: As one of the eight effective traditional Chinese medicines for the treatment of atypical pneumonia, compound Kushen injection (CKI) played an important role in combating pneumonia caused by severe acute respiratory syndrome coronavirus 2 virus in China in 2003. CKI is known to inhibit inflammation, and its main chemical components, namely matrine and oxymatrine, can promote Th cells to recognize and eliminate viruses. In this study, network pharmacology and molecular docking were used to explore the mechanisms of CKI for treating coronavirus disease 2019. Methods: The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform and other related literature were used to screen CKI's active ingredients in the blood. Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, Swiss Target Prediction and STITCH were used to search for potential targets of the active ingredients. The "ingredient-target" network was constructed using the Cytoscape software. The STRING online database was used to construct a target protein-protein interaction network that can be visualized and analyzed using the Cytoscape software to obtain key targets. Results: Sophocarpine, sophoridine, matrine, (+)-allomatrine, AIDS211310, and sophranol were the six active ingredients. After docking the active ingredients with severe acute respiratory syndrome coronavirus 2 3CL hydrolase and angiotensin-converting enzyme 2 (ACE2), they displayed suitable affinity, which could block viral replication and its binding to ACE2. The key targets mainly involved inflammatory factors, such as interleukin-6 (IL-6) and tumor necrosis factor (TNF). Gene Ontology enrichment analysis mainly indicated the IL-6 cytokine-mediated signaling pathway and cytokine-mediated signaling pathway. The Kyoto Encyclopedia of Genes and Genome pathway enrichment analysis mainly indicated steroid hormone biosynthesis and the TNF signaling pathway. Conclusion: The alkaloids in CKI can block viral replication and its binding to severe acute respiratory syndrome coronavirus 2 and ACE2 receptors. They regulate the IL-6-mediated signaling pathway, TNF signaling pathway, and steroid hormone biosynthesis, thereby initiating therapeutic responses against coronavirus disease 2019.

Clinical characteristics of rehospitalized patients with COVID-19 in China.

This study aims to observe the clinical characteristics of recovered patients from Coronavirus Disease 2019 (COVID-19) with positive in reverse transcription-polymerase chain reaction (RT-PCR) or serum antibody. The profile, clinical symptoms, laboratory outcomes, and radiologic assessments were extracted on 11 patients, who tested positive for COVID-19 with RT-PCR or serum antibody after discharged and was admitted to Hubei No. 3 People's Hospital of Jianghan University for a second treatment in March 2020. The average interval time between the first discharge and the second admission measured 16.00 ± 7.14 days, ranging from 6 to 27 days. In the second hospitalization, one patient was positive for RT-PCR and serum antibody immunoglobulin M (IgM)-immunoglobulin G (IgG), five patients were positive for both IgM and IgG but negative for RT-PCR. Three patients were positive for both RT-PCR and IgG but negative for IgM. The main symptoms were cough (54.55%), fever (27.27%), and feeble (27.27%) in the second hospitalization. Compared with the first hospitalization, there were significant decreases in gastrointestinal symptoms (5 vs 0, P = .035), elevated levels of both white blood cell count (P = .036) and lymphocyte count (P = .002), remarkedly decreases in C-reactive protein and serum amyloid A (P < .05) in the second hospitalization. Additionally, six patients' chest computed tomography (CT) exhibited notable improvements in acute exudative lesions. There could be positive results for RT-PCR analysis or serum IgM-IgG in discharged patients, even with mild clinical symptoms, however, their laboratory outcomes and chest CT images would not indicate the on-going development in those patients.