The evolution of structural resilience of global oil and gas resources trade network

This paper establishes anetwork resilience evaluation framework of the global oil and gas resourcetrade network in 2010, 2015 and 2020. The results are as follows: The links of the oil trade network present a gradually shrinking trend, and the gas tradenetwork presents a trend of close connection first and then reduced. In termsof network density, network centrality, network connectivity and network size, the structural resilience of the oil and gas resource trade network displays ashrinking trend, and the gas trade network is superior. Concerninginvulnerability and recovery, the resilience of the oil trade network issuperior to the natural gas trade network. In simulated attacks, the oil tradenetwork reveals a higher resilience towards intentional attacks, and the gastrade network shows a higher resilience towards random attacks. The Strait ofHormuz and the Strait of Malacca are critical chokepoints in the networks.

Early severity prediction of BPD for premature infants from chest X-ray images using deep learning: A study at the 28th day of oxygen inhalation.

BACKGROUND AND OBJECTIVE: Bronchopulmonary dysplasia is a common respiratory disease in premature infants. The severity is diagnosed at the 56th day after birth or discharge by analyzing the clinical indicators, which may cause the delay of the best treatment opportunity. Thus, we proposed a deep learning-based method using chest X-ray images of the 28th day of oxygen inhalation for the early severity prediction of bronchopulmonary dysplasia in clinic. METHODS: We first adopted a two-step lung field extraction method by combining digital image processing and human-computer interaction to form the one-to-one corresponding image and label. The designed XSEG-Net model was then trained for segmenting the chest X-ray images, with the results being used for the analysis of heart development and clinical severity. Therein, Six-Point cardiothoracic ratio measurement algorithm based on corner detection was designed for the analysis of heart development; and the transfer learning of deep convolutional neural network models were used for the early prediction of clinical severities. RESULTS: The dice and cross-entropy loss value of the training of XSEG-Net network reached 0.9794 and 0.0146. The dice, volumetric overlap error, relative volume difference, precision, and recall were used to evaluate the trained model in testing set with the result being 98.43 ± 0.39%, 0.49 ± 0.35%, 0.49 ± 0.35%, 98.67 ± 0.40%, and 98.20 ± 0.47%, respectively. The errors between the Six-Point cardiothoracic ratio measurement method and the gold standard were 0.0122 ± 0.0084. The deep convolutional neural network model based on VGGNet had the promising prediction performance, with the accuracy, precision, sensitivity, specificity, and F1 score reaching 95.58 ± 0.48%, 95.61 ± 0.55%, 95.67 ± 0.44%, 96.98 ± 0.42%, and 95.61±0.48%, respectively. CONCLUSIONS: These experimental results of the proposed methods in lung field segmentation, cardiothoracic ratio measurement and clinic severity prediction were better than previous methods, which proved that this method had great potential for clinical application.

Reflections on development of rapid and living evidence-based Chinese medicine guidelines for Coronavirus disease 2019

As evidence is rapidly accumulated and updated during the coronavirus disease 2019 (COVID-19) pandemic, rapid and living guidelines are needed to guide the clinical practice of Chinese medicine (CM), for which the WHO handbook of rapid guideline development should be referred to, and the characteristics of CM should be addressed. When constructing the body of evidence, we need to systematically search the studies related to COVID-19 (direct) and indirect diseases, and to collect the experience evidence from ancient documents and expert consensus, thereby maximumly presenting the advantages of CM. When the recommendations are developed, the co-existing direct and indirect evidence, as well as the co-existing research and experience evidence should be fully considered and synthesized by taking priority on whichever higher level evidence it is. The development of the rapid and living CM guidelines meets the ever-changing clinical needs during COVID-19 pandemic, and can provide CM evidence supports for decision making during public health emergencies.

Drug repurposing against coronavirus disease 2019 (COVID-19): A review.

Since December 2019, severe acute respiratory syndrome coronavirus 2 has been found to be the culprit in the coronavirus disease 2019 (COVID-19), causing a global pandemic. Despite the existence of many vaccine programs, the number of confirmed cases and fatalities due to COVID-19 is still increasing. Furthermore, a number of variants have been reported. Because of the absence of approved anti-coronavirus drugs, the treatment and management of COVID-19 has become a global challenge. Under these circumstances, drug repurposing is an effective method to identify candidate drugs with a shorter cycle of clinical trials. Here, we summarize the current status of the application of drug repurposing in COVID-19, including drug repurposing based on virtual computer screening, network pharmacology, and bioactivity, which may be a beneficial COVID-19 treatment.

A review of therapeutic agents and Chinese herbal medicines against SARS-COV-2 (COVID-19).

The epidemic of pneumonia (COVID-19) caused by novel coronavirus (SARS-CoV-2) infection has been listed as a public health emergency of international concern by the World Health Organization (WHO), and its harm degree is defined as a global "pandemic". At present, the efforts of various countries focus on the rapid diagnosis and isolation of patients, as well as to find a treatment that can combat the most serious impact of the disease. The number of reported COVID-19 virus infections is still increasing. Unfortunately, no drugs or vaccines have been approved for the treatment of human coronaviruses, but there is an urgent need for in-depth research on emerging human infectious coronaviruses. Clarification transmission routes and pathogenic mechanisms, and identification of potential drug treatment targets will promote the development of effective prevention and treatment measures. In the absence of confirmed effective treatments, due to public health emergencies, it is essential to study the possible effects of existing approved antivirals drugs or Chinese herbal medicines for SARS-CoV-2. This review summarizes the epidemiological characteristics, pathogenesis, virus structure and targeting strategies of COVID-19. Meanwhile, this review also focus on the re-purposing of clinically approved drugs and Chinese herbal medicines that may be used to treat COVID-19 and provide new ideas for the discovery of small molecular compounds with potential therapeutic effects on novel COVID-19.

Depression and Anxiety Among Quarantined People, Community Workers, Medical Staff, and General Population in the Early Stage of COVID-19 Epidemic.

Background: We described the prevalence of anxiety and depression related to COVID-19 pandemic among different types of population and examined their potential risk factors. Methods: A cross-sectional survey was conducted to collect demographic characteristics, exposure histories, and many other concerns about COVID-19. The Zung's self-rating anxiety scale (SAS) and self-rating depression scale (SDS), followed by a four-step multiple logistic regression analysis was performed to identify factors associated with mental health outcomes. Results: Out of 3,303 participants, the quarantined people (40.9%), community workstation staffs-policemen-volunteers (CPV) (36.4%) and general public (30.7%) reported higher percentages of depression than the general medical staff (18.4%). Moreover, the quarantined people (19.1%) also showed higher prevalence of anxiety than the general public (9.1%) and the general medical staff (7.8%). The quarantined people had the highest risk of anxiety and depression, whereas the self-rated health was negatively associated with the risks of anxiety and depression. Younger age group (18 to 30 years) showed higher risks of anxiety (OR = 6.22, 95% CI = 2.89-13.38, p < 0.001) and depression (OR = 3.69, 95% CI = 2.40-5.69, p < 0.001). People who had exposure history or contact from Hubei province after December 1, 2019 (OR = 1.57, 95% CI = 1.07-2.30, p < 0.001), had family or friends engaged in front-line health care work (OR = 1.47, 95% CI = 1.02-2.14, p < 0.001), had confirmed case nearby (OR = 2.44, 95% CI = 1.43-4.18, p < 0.001) were all more likely to suffer from anxiety. Moreover, the negligence (OR = 1.85, 95% CI = 1.37-2.51, p < 0.001) or overindulgence (OR = 1.45, 95% CI = 1.03-2.04, p < 0.001) toward the epidemic information was associated with a higher risk of depression and anxiety. Conclusions: Our findings show that the CPV and quarantined people were most at-risk population. We have identified that the young people, people with exposure histories and negligence or overindulgence toward epidemic information are in grave need of attention.

[Survey of Online Outpatient Clinic Usage Experiences and Analysis of Factors Influencing Retreatment].

BACKGROUND: Because of the COVID-19 epidemic, people are mostly isolated at home and must seek medical advice over the internet. In addition, government authorities are currently investing greater efforts in developing internet hospitals. PURPOSE: The purpose of this essay was to assess how outpatients feel about online outpatient clinics and to analyze the factors that affect their satisfaction and willingness to return to these clinics. The results provide advice regarding how to more effectively encourage patients to use online outpatient clinics. METHODS: A self-developed questionnaire was used to survey 191 patients who had visited the online outpatient clinic of a tertiary hospital in Sichuan Province from January to July 2019. A descriptive analysis was conducted on the collected data, and factors influencing satisfaction were identified. RESULTS: The majority of the surveyed patients were young or middle-aged (92.7%) and 42.9% held a college degree or higher. Nearly three-quarters (72.2%) expressed feeling satisfied or better with the online outpatient clinic, with 31.4% of these expressing feeling very satisfied. Nearly all (91.1%) expressed the opinion that the online outpatient clinic had improved their awareness of health self-management . Furthermore, 176 (92.1%) were willing to use the online outpatient clinic again. The results of univariate analysis showed that the main factors negatively influencing re-use of the online outpatient clinic were: failure to solve the problem in a timely manner (χ2 = 8.603, p = .045), the complicated process of online registration (χ2 = 8.322, p = .016), the failure of the online physical examination (χ2 = 8.958, p = .015), and unreliable quality (χ2 = 15.373, p = .004). CONCLUSIONS: The participants surveyed in this study reported a lower satisfaction for their online outpatient clinic experience than reported in similar surveys of traditional outpatient services. However, many reported that their health-related self-management awareness had improved after use, indicating that they feel better about the online outpatient clinic. The factors that affected willingness to reuse to the online outpatient clinic related mainly to imperfections related to the clinic and its inability to adequately meet patient needs. Online outpatient clinics should simplify the process of registration, improve functions, and increase service functions such as online examination appointments and follow-up visits to improve patient satisfaction.

Chemical composition and pharmacological mechanism of ephedra-glycyrrhiza drug pair against coronavirus disease 2019 (COVID-19).

Traditional Chinese medicine (TCM) had demonstrated effectiveness in the prevention and control of COVID-19. Statistics showed that Ephedra and Glycyrrhiza were frequently used in the treatment of COVID-19. We hypothesized that the Ephedra-Glycyrrhiza drug pair is a potential choice for the treatment of COVID-19. Here, 112 active compounds were identified from Ephedra-Glycyrrhiza via network pharmacology approach. Ephedra-Glycyrrhiza pair enrichment analysis demonstrated that these compounds might participate in the cAMP, PI3K-Akt, JAK-STAT and chemokine signaling pathways, which had a high correlation with respiratory, nervous, blood circulation and digestive system-related diseases. Pathway analysis between Ephedra-Glycyrrhiza and COVID-19 showed that the key targets were TNF-α, IL2, FOS, ALB, and PTGS2. They might control PI3K-Akt signaling pathway to exert immune regulation, organ protection and antiviral effects. Molecular docking results showed that the active compounds from the Ephedra-Glycyrrhiza pair bound well to COVID-19 related targets, including the main protease (Mpro, also called 3CLpro), the spike protein (S protein), and the angiotensin-converting enzyme 2 (ACE2). The Molecular dynamics simulation was analyzed for the stability and flexibility of the complex. In conclusion, our study elucidated the potential pharmacological mechanism of Ephedra-Glycyrrhiza in the treatment of COVID-19 through multiple targets and pathways.

Potential Therapeutic Effect of Traditional Chinese Medicine on Coronavirus Disease 2019: A Review.

The Coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 has been rapidly spreading globally and has caused worldwide social and economic disruption. Currently, no specific antiviral drugs or clinically effective vaccines are available to prevent and treat COVID-19. Traditional Chinese medicine (TCM) can facilitate syndrome differentiation and treatment according to the clinical manifestations of patients and has demonstrated effectiveness in epidemic prevention and control. In China, TCM intervention has helped to control the epidemic; however, TCM has not been fully recognized worldwide. In this review, we summarize the epidemiology and etiological characteristics of severe acute respiratory syndrome coronavirus 2 and the prevention and treatment measures of COVID-19. Additionally, we describe the application of TCM in the treatment of COVID-19 and the identification of small molecules of TCM that demonstrate anti-coronavirus activity. We also analyze the current problems associated with the recognition of TCM. We hope that, through the contribution of TCM, combined with modern technological research and the support of our international counterparts, COVID-19 can be effectively controlled and treated.

TMPRSS2 Correlated With Immune Infiltration Serves as a Prognostic Biomarker in Prostatic Adenocarcinoma: Implication for the COVID-2019.

Type 2 transmembrane serine protease (TMPRSS2) is a new member of the serine proteases, and studies have shown that TMPRSS2 plays a role in the occurrence of prostate malignancies and is closely related to the occurrence of the coronavirus disease 2019 (COVID-19). However, the role of TMPRSS2 in prostatic adenocarcinoma (PRAD) remains largely unclear. To better explore its function in PRAD, we examined the expression level of TMPRSS2 in the GEO, tumor immune assessment resource (TIMER), as well as Oncomine databases and studied the association between TMPRSS2 and overall survival (OS) rates in the UALCAN and gene expression profiling interactive analysis (GEPIA) databases. In addition, we studied the correlation of the level of immune infiltration and markers of immune cell type in the TIMER database, analyzed the prognosis based on the expression level of TMPRSS2 in the related immune cell subsets, and determined the methylation profile of TMPRSS2 promoter by UALCAN database. Subsequently, we conducted a survival analysis and gene ontology (GO) pathway analysis in the TISID database and detected the expression of TMPRSS2 in the Human Protein Atlas (HPA) database. We also studied the protein-protein interaction (PPI) network of TMPRSS2 in the GENEMANIA database. Additionally, we used the microarray GSE56677 and GSE52920 to illustrate changes in TMPRSS2 expression in vivo and in vitro after severe acute respiratory syndrome-coronavirus (SARS-COV) infection, finding that expression of TMPRSS2 decreased after SARS-COV infection in vitro. The function of TMPRSS2 in the dataset was further verified by gene set enrichment analysis (GSEA). In conclusion, the expression of TMPRSS2 is significantly increased in PRAD, elevated TMPRSS2 is associated with immune infiltration, and prognosis is positively correlated. In addition, tumor tissue from COVID-19 patients with PRAD may be more susceptible to infection with SARS-COV-2, which may render the prognosis gets worse.

Chemical composition and pharmacological mechanism of shenfu decoction in the treatment of novel coronavirus pneumonia (COVID-19).

PURPOSE: Shenfu decoction has outstanding curative effects in the treatment of COVID-19. This study aimed to explore the material basis and molecular mechanism of Shenfu Decoction through network pharmacology and molecular mechanisms, to provide a research basis for clinical medication and clues for subsequent research. METHODS: The active components and targets of Shenfu decoction were searched in the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the COVID-19-associated genes were collected using the Gene Cards platform. The target protein-protein interaction network map was constructed by mapping two genes, and the 'drug-active ingredient-target' network was constructed using Cytoscape software. The Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment of the mapping targets were analyzed. RESULT: Based on Traditional Chinese medicine, Shenfu Decoction can take effect in the lung, spleen, kidney and heart. Considering oral bioavailability (OB) ≥ 30% and drug-like (DL) ≥ 0.18 as the standard, 43 active compounds were screened and 114 Shenfu decoction action targets were collected. The key targets were CASP3, MAPK8, PTGS2, IL1B, PPARG, ICAM1, IFNG, RELA, NOS2, NOS3, HMOX1, CASP8, STAT1, and TGFB1. According to the standard of p < .05, GO function was enriched in 108 biological processes, 16 cell processes and 27 molecular processes. Sixty-three signaling pathways were enriched by KEGG, which can be divided into four types: viral infection pathways, signal pathways, biological process pathways and different disease pathways. The comparison of negative and positive prescriptions further reflects the positive effect of Shenfu decoction against COVID-19. Finally, the effective ingredients with the high degree were molecular docked with Mpro, Rdrp and Spro proteins to further confirm the intervention effect of Shenfu Decoction on COVID-19. CONCLUSION: Shenfu decoction played an important role in regulating the anti-virus process, regulating immunity, inhibiting inflammation and regulating apoptosis through the interrelated regulation mechanism of multi-components and multi-targets, to treat patients with severe COVID-19.