To Explore the Network Pharmacology and Molecular Docking Mechanism of Chaihu Shugan Powder with the “Same Treatment for Different Diseases” for Insomnia and Depression Based on the COVID-19 Pandemic (preprint)

Background: The classic prescription Chaihu Shugan Powder (CHSGP) has been widely used in clinical Chinese medicine treatment and has clear clinical effects in the treatment of emotional diseases. Based on the increasing incidence of emotional diseases such as insomnia and depression in the population during the COVID-19 pandemic, we will explore the mechanism of CHSGP in the treatment of insomnia and depression with “Same Treatment for Different Diseases”. Methods: Using a bioinformatics and network pharmacology platform, protein database and STRING database, we collected CHSGP chemical composition and related target data and constructed a "component-target" action network through Gene Ontology and Kyoto Encyclopedia of Genes and Genome pathway enrichment analysis. Molecular docking technology was used to verify key active ingredients and core targets. Results: A total of 119 active compounds of CHSGP were screened, such as quercetin, kaempferol, and β-sitosterol, and 113 common related targets overlapped with insomnia and depression. GO enrichment and KEGG pathway analysis mainly involved immune, inflammation, cell proliferation, apoptosis, endocrine and other related targets and signaling pathways. Molecular docking showed that small molecular compounds (kaempferol, luteolin, quercetin, 7-methoxy-2-methyl isoflavone and beta-sitosterol) had good binding effects with five target proteins (AKT1, IL1B, IL-6, FOS, GSK3B) to play a role in regulating immunity, the inflammatory response, cell proliferation, apoptosis, and endocrine signaling. Conclusions: Under the context of the COVID-19 pandemic, it revealed the complex mechanism of multicomponent, multitarget, and multipathway of the classic CHSGP for insomnia and depression, laying a theoretical foundation for its clinical application of its "same treatment for different diseases".

Persistent while declined neutralizing antibody responses in the convalescents of COVID-19 across clinical spectrum during the 16 months follow up (preprint)

Elucidation the kinetics of neutralizing antibody response in the coronavirus disease 2019 (COVID-19) convalescents is crucial for the future control of the COVID-19 pandemic and vaccination strategies. Here we tested 411 sequential plasma samples collected up to 480 days post symptoms onset (d.a.o) from 214 convalescents of COVID-19 across clinical spectrum without re-exposure history after recovery and vaccination of SARS-CoV-2, using authentic SARS-CoV-2 microneutralization (MN) assays. COVID-19 convalescents free of re-exposure and vaccination could maintain relatively stable anti-RBD IgG and MN titers during 400[~]480 d.a.o after the peak at around 120 d.a.o and the subsequent decrease. Undetectable neutralizing activity started to occur in mild and asymptomatic infections during 330 to 480 d.a.o with an overall rate of 14.29% and up to 50% for the asymptomatic infections. Significant decline in MN titers was found in 91.67% COVID-19 convalescents with [≥] 50% decrease in MN titers when comparing the available peak and current MN titers ([≥] 300 d.a.o). Antibody-dependent immunity could also provide protection against most of circulating variants after one year, while significantly decreased neutralizing activities against the Beta, Delta and Lambda variants were found in most of individuals. In summary, our results indicated that neutralizing antibody responses could last at least 480 days in most COVID-19 convalescents despite of the obvious decline of neutralizing activity, while the up to 50% undetectable neutralizing activity in the asymptomatic infections is of great concern.

A Dialogue-based Information Extraction System for Medical Insurance Assessment (preprint)

In the Chinese medical insurance industry, the assessor's role is essential and requires significant efforts to converse with the claimant. This is a highly professional job that involves many parts, such as identifying personal information, collecting related evidence, and making a final insurance report. Due to the coronavirus (COVID-19) pandemic, the previous offline insurance assessment has to be conducted online. However, for the junior assessor often lacking practical experience, it is not easy to quickly handle such a complex online procedure, yet this is important as the insurance company needs to decide how much compensation the claimant should receive based on the assessor's feedback. In order to promote assessors' work efficiency and speed up the overall procedure, in this paper, we propose a dialogue-based information extraction system that integrates advanced NLP technologies for medical insurance assessment. With the assistance of our system, the average time cost of the procedure is reduced from 55 minutes to 35 minutes, and the total human resources cost is saved 30% compared with the previous offline procedure. Until now, the system has already served thousands of online claim cases.

Pulmonary Fibrosis and Its Related Factors in Discharged Patients with New Coronavirus Pneumonia: A Cohort Study of 90-150 Days Follow-Up after Onset (preprint)

Background: The Coronavirus Disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a pandemic, posing a serious threat to public health worldwide. Whether survivors of COVID-19 pneumonia may be at risk of pulmonary fibrosis is still unknown.Methods: This study involves 462 laboratory confirmed patients with COVID-19 who were admitted to Shenzhen Third People’s Hospital. A total of 457 patients underwent thin-section chest CT scans during the hospitalization or after discharge to identify the pulmonary lesion. A total of 287 patients were followed up from 90 days to 150 days after the onset of the disease.Finding: 397 (86.87%), 311 (74.40%), 222 (79.56%), 141 (68.12%) and 49 (62.03%) patients developed with pulmonary fibrosis during the 0-30, 31-60, 61-90, 91-120 and >120 days after onset, respectively. Reversal of pulmonary fibrosis were found in 18 (4.53%), 61 (19.61%), 40 (18.02%), 54 (38.30%) and 24 (48.98%) COVID-19 patients during the 0-30, 31-60, 61-90, 91-120 and >120 days after onset, respectively. It was observed that Age, BMI, Fever, and Highest PCT were predictive factors for sustaining fibrosis even after 90 days from onset. Only a fraction of COVID-19 patients suffered with abnormal lung function after 90 days from onset.Interpretation: Long-term pulmonary fibrosis was more likely to develop in patients with older age, high BMI, severe/critical condition, fever, long time to turn the viral RNA negative, pre-existing disease and delay to admission. Fibrosis developed in COVID-19 patients could be reversed in about a half of the patients after 120 days from onset. The pulmonary function of most of COVID-19 patients with pulmonary fibrosis could turn to normal condition after three months from onset.Funding Statement: Shenzhen Science and Technology Research and Development Project (202002073000001 and 202002073000002), Shenzhen Fund for Guangdong Provincial High-level Clinical Key Specialties (SZGSP011).Declaration of Interests: The authors declare no competing interests.Ethics Approval Statement: This study was conducted at Shenzhen Third People's Hospital and approved by the Ethics Committees, each patient gave written informed consent.

Pulmonary fibrosis and its related factors in discharged patients with new coronavirus pneumonia: A cohort study (preprint)

Background: Thousands of the Coronavirus Disease 2019 (COVID-19) patients have been discharged from hospitals, persistent follow-up studies are required to evaluate the prevalence of post-COVID-19 fibrosis.Methods: This study involves 462 laboratory confirmed patients with COVID-19 who were admitted to Shenzhen Third People’s Hospital from January 11, 2020 to April 26, 2020. A total of 457 patients underwent thin-section chest CT scans during the hospitalization or after discharge to identify the pulmonary lesion. A total of 287 patients were followed up from 90 days to 150 days after the onset of the disease, and lung function tests were conducted in about three months after the onset. The risk factors affecting the persistence of pulmonary fibrosis were identified through regression analysis and the prediction model of the persistence of pulmonary fibrosis was established.Results:  Parenchymal bands, irregular interfaces, reticulation and traction bronchiectasis were the most common CT features in all COVID-19 patients. During the 0-30, 31-60, 61-90, 91-120 and >120 days after onset, 86.87%, 74.40%, 79.56%, 68.12% and 62.03% patients developed with pulmonary fibrosis and 4.53%, 19.61%, 18.02%, 38.30% and 48.98% patients reversed pulmonary fibrosis, respectively. It was observed that Age, BMI, Fever, and Highest PCT were predictive factors for sustaining fibrosis even after 90 days from onset. A predictive model of the persistence with pulmonary fibrosis was developed based-on the Logistic Regression method with an accuracy, PPV, NPV, Sensitivity and Specificity of the model of 76%, 71%, 79%, 67%, and 82%, respectively. More than half of COVID-19 patients revealed abnormal condition in lung function after 90 days from onset, and the ratio of abnormal lung function did not differ on a statistically significant level between the fibrotic and non-fibrotic groups.Conclusions: Persistent pulmonary fibrosis was more likely to develop in patients with older age, high BMI, severe/critical condition, fever, long time to turn the viral RNA negative, pre-existing disease and delay to admission. Fibrosis developed in COVID-19 patients could be reversed in about a third of the patients after 120 days from onset. The pulmonary function of less than half of COVID-19 patients could turn to normal condition after three months from onset. An effective prediction model with an average Area Under the Curve (AUC) of 0.84 was established to predict the persistence of pulmonary fibrosis in COVID-19 patients for early diagnosis.

Exuberant elevation of IP-10, MCP-3 and IL-1ra during SARS-CoV-2 infection is associated with disease severity and fatal outcome (preprint)

The outbreak of Coronavirus Disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, December 2019, and continuously poses a serious threat to public health. Our previous study has shown that cytokine storm occurred during SARS-CoV-2 infection, while the detailed role of cytokines in the disease severity and progression remained unclear due to the limited case number. In this study, we examined 48 cytokines in the plasma samples from 53 COVID-19 cases, among whom 34 were severe cases, and the others moderate. Results showed that 14 cytokines were significantly elevated upon admission in COVID-19 cases. Moreover, IP-10, MCP-3, and IL-1ra were significantly higher in severe cases, and highly associated with the PaO2/FaO2 and Murray score. Furthermore, the three cytokines were independent predictors for the progression of COVID-19, and the combination of IP-10, MCP-3 and IL-1ra showed the biggest area under the curve (AUC) of the receiver-operating characteristics (ROC) calculations. Serial detection of IP-10, MCP-3 and IL-1ra in 14 severe cases showed that the continuous high levels of these cytokines were associated with disease deterioration and fatal outcome. In conclusion, we report three cytokines that closely associated with disease severity and outcome of COVID-19. These findings add to our understanding of the immunopathologic mechanisms of SARS-CoV-2 infection, which suggested novel therapeutic targets and strategy.

Laboratory diagnosis and monitoring the viral shedding of 2019-nCoV infections (preprint)

Background: The outbreak of novel coronavirus pneumonia (NCP) caused by 2019-nCoV spread rapidly, and elucidation the diagnostic accuracy of different respiratory specimens is crucial for the control and treatment of this diseases. Methods: Respiratory samples including nasal swabs, throat swabs, sputum and bronchoalveolar lavage fluid (BALF) were collected from Guangdong CDC confirmed NCP patients, and viral RNAs were detected using a CFDA approved detection kit. Results were analyzed in combination with sample collection date and clinical information. Finding: Except for BALF, the sputum possessed the highest positive rate (74.4%~88.9%), followed by nasal swabs (53.6%~73.3%) for both severe and mild cases during the first 14 days after illness onset (d.a.o). For samples collected [≥] 15 d.a.o, sputum and nasal swabs still possessed a high positive rate ranging from 42.9%~61.1%. The positive rate of throat swabs collected [≥] 8 d.a.o was low, especially in samples from mild cases. Viral RNAs could be detected in all the lower respiratory tract of severe cases, but not the mild cases. CT scan of cases 02, 07 and 13 showed typical viral pneumonia with ground glass opacity, while no viral RNAs were detected in first three or all the upper respiratory samples. Interpretation: Sputum is most accurate for laboratory diagnosis of NCP, followed by nasal swabs. Detection of viral RNAs in BLAF is necessary for diagnosis and monitoring of viruses in severe cases. CT scan could serve as an important make up for the diagnosis of NCP. Funding National Science and Technology Major Project, Sanming Project of Medicine and China Postdoctoral Science Foundation.