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2.
Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi ; 57(6): 683-691, 2022 Jun 07.
Article in Chinese | MEDLINE | ID: covidwho-1903517

ABSTRACT

Objective: To explore the relationship between pathogens in the olfactory cleft area and olfactory disorders in patients with upper respiratory inflammation (URI) during the prevention and control of 2019 novel coronavirus disease (COVID-19). Methods: A total of 234 URI patients including acute upper respiratory infection, chronic rhinosinusitis (CRS), allergic rhinitis (AR) were continuously selected from September 2020 to March 2021 in Beijing Anzhen Hospital and 98 healthy adults were enrolled as controls. The secretions from the olfactory cleft of all subjects were collected with nasal swabs under nasal endoscopy. Multiple real-time fluorescent quantitative polymerase chain reaction detection method was used to detect nucleic acids of 33 types of respiratory pathogenic microorganism. Sniffin' Sticks olfactory test was performed on all patients with URI. URI patients with olfactory dysfunction were followed up for 9 (8, 10) months (M (Q1, Q3)). SPSS 20.0 software was used for statistical analysis. Results: Among the 98 controls, 9 (9.18%) were positive for pathogenic microorganisms, including 1 (1.02%) rhinovirus, 1 (1.02%) parainfluenza virus type 3, 3 (3.06%) enterovirus, 1 (1.02%) staphylococcus aureus and 3 (3.06%) Moraxella catarrhalis. Among the 234 URI patients, 111 (47.44%) had olfactory disorders and 123 (52.56%) had normal sense of smell. In the olfactory disorder group (111 cases), 38 cases (34.23%) were positive for pathogenic microorganisms, and 4 cases (3.60%) were mixed infection, including 11 cases of rhinovirus (9.91%), 5 cases of coronavirus 229E (4.50%), 2 cases of coronavirus OC43/NL63 (1.80%), 3 cases of parainfluenza virus type 1 (2.70%), 2 cases of enterovirus (1.80%), 1 case of influenza B virus type BV (0.90%), 11 cases of Staphylococcus aureus (9.91%), 7 cases of Moraxella catarrhalis (6.31%), and 1 case of Klebsiella pneumoniae (0.90%). In the normal smell group (123 cases), 18 cases (14.63%) were positive for pathogenic microorganisms, and 1 case (0.81%) was mixed infection, including 3 cases of rhinovirus (2.44%), 4 cases of coronavirus 229E (3.25%), 1 case of Influenza virus type 3 (0.81%), 3 cases of enterovirus (2.44%), 3 cases of Staphylococcus aureus (2.44%), 4 cases of Moraxella catarrhalis (3.25%), and 1 case of Klebsiella pneumoniae (0.81%). Univariate analysis between the two groups found that there were significant differences in the detection rate of pathogenic microorganisms, rhinovirus and Staphylococcus aureus between the groups (all P<0.05). The detection rate of parainfluenza virus type 1, Staphylococcus aureus, and rhinovirus were different between the patients with olfactory disorder and normal olfactory function in the three subgroups of acute upper respiratory tract infection, CRS and AR, respectively (χ2 value was 3.88, 4.53 and 4.73, respectively, all P<0.05). During the follow-up period, among the 111 patients with olfactory disorder, 71 (63.96%) patients' olfactory function returned to normal, 32 (28.83%) patients' olfactory function improved but not completely returned to normal, 8 (7.21%) patients' olfactory function did not improve. Conclusions: During the prevention and control of COVID-19, rhinovirus or Staphylococcus aureus infection or colonization of URI patients is closely related to olfactory disorders. Parainfluenza virus type 1 infection can cause relatively persistent olfactory disorders in patients with acute upper respiratory tract infection. Staphylococcus aureus and rhinovirus colonization are related to the occurrence of olfactory dysfunction in CRS and AR patients respectively.


Subject(s)
COVID-19 , Coinfection , Olfaction Disorders , Respiratory Tract Infections , Sinusitis , Adult , Coinfection/epidemiology , Humans , Inflammation , Rhinovirus , Smell
3.
Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi ; 57(6): 774-777, 2022 Jun 07.
Article in Chinese | MEDLINE | ID: covidwho-1903516
4.
11th International Conference on Frontier Computing, FC 2021 ; 827 LNEE:143-151, 2022.
Article in English | Scopus | ID: covidwho-1899032

ABSTRACT

Due to rapid change in influenza viruses, a prediction model for outbreaks of influenza-like illnesses helps to find out the spread of the illnesses in real time. In addition to using traditional hydrological and atmospheric data, popular search keywords on Google Trends are used as features in this research. Google Trends are popular keyword searches on the Google search engine. Popular keywords used in discussions of influenza-like symptoms at specific regions within specific periods are used in this research. Public holiday information in Taiwan, the population density, air quality indices, and the numbers of COVID-19 confirmed cases are also used as features in this research. An Ensemble Learning model, combining Random Forest and XGBoost, is used in this research. It can be confirmed from the actual experimental results in this research that the use of the ensemble learning prediction model proposed in this research can accurately predict the trend of influenza-like cases. The evaluation results show that the mean RMSLE of our proposed model is 0.2 in comparison with the actual number of influenza-like cases. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

5.
Topics in Antiviral Medicine ; 30(1 SUPPL):116-117, 2022.
Article in English | EMBASE | ID: covidwho-1881009

ABSTRACT

Background: SARS-CoV-2 induces cytokine response dysregulation and immune dysfunction. What remains unclear is how cytokine signaling shapes immune responses during early SARS-CoV-2 infection when adaptive immunity is developing. Our goal is to identify immune pathways that shape the early development of adaptive immune responses in COVID-19 patients. We performed paired single-cell transcriptomic and epigenomic profiling at two time-points of early SARS-CoV-2 infection to determine immune signatures of acute infection and epigenetic drivers that underpin immune response dynamics. Methods: PBMC samples were collected from four moderate to severe COVID-19 patients at two early time-points (n = 3 for Week 1 and n = 3 for Week 2 after symptom onset, including 2 participants having paired blood sampling at both time points) and from two healthy controls (n = 2). Using paired scRNA-Seq and scATAC-Seq, we captured transcriptomic and epigenomic profiles in the same single cells to identify chromatin accessibility changes as a potential mechanism for the surge and decline of immune responses elicited during acute SARS-CoV-2 infection. Using bioinformatic approaches, we identified heterogeneous immune cell populations, modeled cell differentiation trajectories, determined dysregulated immune pathways through gene set enrichment analysis, and connected chromatin co-accessible landscapes. Results: We captured transcriptomic and epigenomic profiles of 43,726 single cells and identified paired transcriptional and epigenetic landscapes in six major immune cell types: CD4+ T cells, CD8+ T cells, B cells, dendritic cells, monocytes, and NK cells. We found that early SARS-CoV-2 infection induced a surge in IL-2, IL-6, IFN-α, IFN-γ, TNF-α, and NF-κB responses at Week 1 that declined at Week 2 in adaptive immune cells (CD4+ T, CD8+ T, and B cells). In contrast, TGF-β responses surged early at Week 1 and continued to increase at Week 2 in these cells. In B cells and plasmablasts, we found early surges of IGHA1 (encoding IgA heavy chain) and SOX4 (an essential transcription factor for B cell development) expressions that correlated with expression of SMAD-dependent TGF-β signaling pathway. Further, we found a notable increase in chromatin accessibility at the SMAD binding regulatory element 150 kb upstream of SOX4 in B cells of infected patients. Conclusion: Our data suggest a significant increase in TGF-β activity that instructs dynamic B cell-associated protective immunity during early SARS-CoV-2 infection.

6.
Journal of Image and Graphics ; 27(3):750-761, 2022.
Article in Chinese | Scopus | ID: covidwho-1789677

ABSTRACT

Objective: The primary routine clinical diagnosis of COVID-19(corona virus disease 2019) is usually conducted based on epidemiological history, clinical manifestations and various laboratory detection methods, including nucleic acid amplification test (NAAT), computed tomography (CT) scan and serological techniques. However, manual detection is costly, time-consuming and leads to the potential increase of the infection risk of clinicians. As a good alternative, artificial intelligence techniques on available data from laboratory tests play an important role in the confirmation of COVID-19 cases. Some studies have been designed for distinguishing between novel coronavirus pneumonia, community-acquired pneumonia and normal people by graph neural network. However, these studies leverage the relationships between features to build a topological structure graph (e.g., connecting the nodes with high similarity), while ignoring the inner relationships between different parts of the lung, and thus limiting the performance of their models. To address this issue, we propose a graph neural network with hierarchical information inherent to the physical structure of lungs for the improved diagnosis of COVID-19. Besides, an attention mechanism is introduced to capture the discriminative features of different severities of infection in the left and right lobes of different patients. Method: Firstly, the topological structure is constructed based on the lungs' physical structure, and different lung segments are regarded as different nodes. Each node in the graph contains three kinds of handcrafted features, such as volume, density and mass feature, which reflect the infection in each lung segment and can be extracted from chest CT images using VB-Net. Secondly, based on graph neural network (GNN) and attention mechanism, we propose a novel structural attention graph neural network (SAGNN), which can perform the graph classification task. The SAGNN first aggregates the features in a given sample graph, and then uses the attention mechanism to effectively fuse the different features to obtain the final graph representation. This representation is then fed into a linear layer with softmax activation function that performs graph classification, so that the corresponding sample graph can be finally classified as a mild case or a severe one. To alleviate the effect of category imbalance on the classification results, we use the focal loss function. We optimize the proposed model via back propagation and learn the representations of graphs. Result: To verify the effectiveness of the proposed method, we compared SAGNN with several classical machine learning methods and graph classification methods on a real COVID-19 dataset, which includes 358 severe cases and 1 329 mild cases, provided by Shanghai Public Health Clinical Center. The result of comparative experiments was measured using three evaluation metrics including the sensitivity (SEN), the specificity (SPE) and the area under the receiver operating characteristic(ROC) curve (AUC). In the experiments, our model had a good performance, indicating the effectiveness of our model. Based on comparison with the classical machine learning methods and the graph neural network methods, SAGNN outperformed by 14.2%42.0% and 3.6%4.8% in terms of SEN, respectively. In terms of AUC, the performance of SAGNN increased by 8.9%18.7% and 3.1%3.6%, respectively. In addition, through the ablation experiments of SAGNN, we found that the SAGNN with attention mechanism outperformed by 2.4%, 1.4% and 1.1% in SPE, SEN and AUC than the SAGNN not with attention mechanism, respectively. The SAGNN with focal loss function outperformed by 2.1%, 1.1% and 0.9% in SPE, SEN and AUC than the SAGNN with cross-entropy loss function, respectively. Conclusion: In this work, we propose SAGNN, a new architecture for the diagnosis of severe and mild cases of COVID-19. Experimental results show the superior performance of SAGNN on classification task. Experimental results show that concatenating features of lung segments by t eir structure is effective. Moreover, we introduce an attention mechanism to distinguish the infection degree of right and left lungs. The focal loss is used to solve the issue of imbalanced group distribution, which further improves the overall network performance. We thus demonstrate the potential of SAGNN as clinical diagnosis support in this highly critical domain of medical intervention. We believe that our architecture provides a valuable case study for the early diagnosis of COVID-19, which is helpful for improvement in the field of computer-aided diagnosis and clinical practice. © 2022, Editorial Office of Journal of Image and Graphics. All right reserved.

7.
Disease Surveillance ; 37(1):7-11, 2022.
Article in Chinese | CAB Abstracts | ID: covidwho-1789480

ABSTRACT

Objective: To assess the risk of public health emergencies, both the indigenous ones and the imported ones, which might occur in the mainland of China in January 2022.

8.
Dili Xuebao/Acta Geographica Sinica ; 77(2):426-442, 2022.
Article in Chinese | Scopus | ID: covidwho-1726805

ABSTRACT

The Chinese government has curbed the rapid transmission of COVID-19 through a population flow control rarely seen in history. What is the effect of population flow control on pandemic prevention and control? How does it affect China's population mobility and short-term population distribution? In this paper, an SEIR model of virus transmission dynamics is used to evaluate the effectiveness of the control measures, and mobile location data are employed to track the temporal and spatial changes of population mobility in China, in order to review the positive and negative effects of population flow control during the major outbreaks of COVID-19: (1) Population flow control has significantly stabilized the daily new infection, serving as an essential part of China's non-pharmacological intervention measures in response to major public emergencies of COVID-19. Population flow control postponed the arrival of the peak day of daily new infections in China by 1.9 times, and reduced the number of newly infected people on that day by 63.4%. In the selected 5 provinces, 5 cities in Hubei, and 6 cities outside Hubei, the peak days were postponed by 1.4-8 times, 5.6-16.7 times, and 2.3-7.2 times, respectively, and the number of newly infected people on that day was reduced by 56.9%-85.5%, 62.2%-89.2%, and 67.1%-86.2%, respectively. Therefore, population flow control bought valuable buffer time for the prevention and control of the pandemic, and greatly weakened the impact of concentrated transmissions on medical facilities. (2) Population flow control limited intercity population flow. From January to April 2020, the average daily population flow intensity in China decreased by 40.18% compared with the same period in 2019. In particular, the coming-back-to-work flow after the Spring Festival travel rush in 2020 (from January 25 to February 18) decreased by 66.4% on average. (3) Population flow control and people's fear of the pandemic greatly affected the Spring Festival travel rush in 2020, and the spatial and temporal and distribution of China's population was changed for a short period. This paper helps the understanding of the impact of the population flow control strategy introduced by the government on major public emergencies, as well as the influences of geographical characteristics upon on the population flow and distribution. © 2022, Science Press. All right reserved.

9.
Clinical and Experimental Rheumatology ; 39(2):442-443, 2021.
Article in English | GIM | ID: covidwho-1716904

ABSTRACT

This study aimed to investigate the epidemiology and clinical characteristics of COVID-19 in RD. The median age of the infected patients was 54.5 years (range: 32-78 years). All infected patients had comorbidities. Half of the patients were in the active phase of rheumatic diseases. Half of them received anti-rheumatic treatments. All patients had fever, while three (37.5%) had dyspnea and cough. Median time of hospitalisation was 11 days (range: 5-21 days). Three patients (37.5%) who were classified as severe cases and died, were older (median age 65 years) and had multiple comorbidities. Moreover, they had higher disease activity.

10.
Clinical Trials ; 18(SUPPL 5):98, 2021.
Article in English | EMBASE | ID: covidwho-1582560

ABSTRACT

Important safety measures limiting in-person contact to curb COVID-19 transmission make it more difficult for patients to access clinical trials and for sponsors to conduct trial management. These measures may lead to pausing or delaying study activities, to the determent of study participants and the study's integrity. The COVID-19 pandemic highlights the importance of efficient, innovative clinical trials designed with the capacity to be rapidly responsive to unique challenges. The US Department of Veterans Affairs Pentoxifylline in Diabetic Kidney Disease study is a multi-site, pragmatically designed randomized controlled trial that tests the hypothesis that pentoxifylline, when added to standard of care, leads to a reduction in the incidence of End Stage Renal Disease and mortality. The study opened for recruitment at six Veterans Affairs medical centers in December 2019, months before the COVID-19 pandemic disrupted all aspects of clinical care and halted all non-essential, in-person research activities. The study's protocol was designed to accommodate either in-person or remote participant follow-up and data collection for all visits after baseline. In addition, participant study visit schedules were built with the flexibility to align with existing clinic visits. The ability to collect data remotely resulted in a minimal amount of missing data. The study's investigational product is maintained and distributed centrally by the Albuquerque Cooperative Studies Program Pharmacy Center. This allowed for the continuation of distribution of the study investigational product without the need for an in-person visit to a Veterans Affairs medical center. Pentoxifylline in Diabetic Kidney Disease's trial design and protocol leverage the Veterans Affairs's research infrastructure, remote platforms, and a centralized mail-order pharmacy, and allowed the study to safely continue during a uniquely challenging global pandemic.

11.
12th International Conference on E-business, Management and Economics, ICEME 2021 ; : 202-209, 2021.
Article in English | Scopus | ID: covidwho-1575891

ABSTRACT

This study employs the TVP-VAR connectedness method to explore the stock market interdependence among nine Asian major economies from 2010 to 2020. From the results, I observe that the interdependence level in the system varies in different years corresponding to global events. For example, the stock markets are more closely connected during the covid-19 pandemic. Moreover, each country has distinctive influence power on other countries, which also fluctuates with time. There exists great heterogeneity in terms of pairwise connectedness between every two countries. The findings have instructive meanings for investors to construct the optimal investing portfolio. The results are also meaningful for policymakers in terms of taking measures to stabilize the stock market in turbulent times. © 2021 ACM.

12.
4th International Conference on Information Systems and Computer Aided Education, ICISCAE 2021 ; : 1958-1963, 2021.
Article in English | Scopus | ID: covidwho-1566398

ABSTRACT

Since COVID-19, the already fragile food system has become even more overburdened, and food security has become an urgent issue. Due to the excessive pursuit of efficiency and profit, the food system in the past has created various problems, the most prominent problem is the inability to find a balance between profit and ecological environment. Therefore, this article focuses on how to build a model that includes both aspects. In order to analyse the existing food system and introduce new ones, firstly, divide the food system into four subsystems of profitability, efficiency, sustainability, and equity, and set up several secondary indicators under each subsystem, and select appropriate countries as samples. Use the AHP, EWM, and CEM to calculate the corresponding index of each subsystem to form a new comprehensive evaluation model for the food system. © 2021 ACM.

13.
Medical Journal of Peking Union Medical College Hospital ; 12(1):136-140, 2021.
Article in Chinese | Scopus | ID: covidwho-1513190

ABSTRACT

Objective To investigate the impact of the outbreak of coronavirus disease 2019 (COVID-19) as an intervention factor on residency training at different stages, and look into the enhancement effect of post-graduation medical training program based on competency of residency training, so as to provide reference for the optimization of medical education at the postgraduate stage. Methods After the initial success of COVID-19 prevention and control, 169 clinical postdoctoral trainess(clinical postdocs) and 515 graduate students specializing in clinical medicine(professional postdocs) were surveyed by an anonymous online questionnaire. To analyze the differences of cognition and self- evaluation of core competence between the two groups. Results There were 141 valid questionnaires collected from clinical postdocs (83.43%, 141/169) and 264 valid questionnaires collected from professional postdocs (51.26%, 264/515). In both groups, more than 85% of the students agreed or strongly agreed that they had a deeper understanding of the profession of doctors during the epidemic. The results of competency self-evaluation showed that, except for the items of "self-improvement", the self-evaluation scores of clinical postdoctoral students on other items were significantly higher than those of professional postdoctoral students (all P <0.05). Conclusions COVID-19, as a factor of emergency intervention, can improve the competency cognition of residents. The core-competency based post-graduation medical education model can comprehensively improve the students' comprehensive ability, which is an effective training program for residents. It is suggested that the vocational planning education for residents should be paid attention to in the stage of college education, and a new mode of college education that is closely combined with the post-graduation education should be further explored. © 2021 Thomson Reuters and Contributors.

14.
Acs Es&T Water ; 1(10):2174-2185, 2021.
Article in English | Web of Science | ID: covidwho-1486380

ABSTRACT

A novel coronavirus (SARS-CoV-2) causing corona virus disease 2019 (COVID-19) has attracted global attention due to its highly infectious and pathogenic properties. Most of current studies focus on aerosols released from infected individuals, but the presence of SARS-CoV-2 in wastewater also should be examined. In this review, we used bibliometrics to statistically evaluate the importance of water-related issues in the context of COVID-19. The results show that the levels and transmission possibilities of SARS-CoV-2 in wastewater are the main concerns, followed by potential secondary pollution by the intensive use of disinfectants, sludge disposal, and the personal safety of workers. The presence of SARS-CoV-2 in wastewater requires more attention during the COVID-19 pandemic. Thus, the most effective techniques, i.e., wastewater-based epidemiology and quantitative microbial risk assessment, for virus surveillance in wastewater are systematically analyzed. We further explicitly review and analyze the successful operation of a sewage treatment plant in Huoshenshan Hospital in China as an example and reference for other sewage treatment systems to properly ensure discharge safety and tackle the COVID-19 pandemic. This review offers deeper insight into the prevention and control of SARS-CoV-2 and similar viruses in the post-COVID-19 era from a wastewater perspective.

15.
Sustainability (Switzerland) ; 13(19), 2021.
Article in English | Scopus | ID: covidwho-1448927

ABSTRACT

Food safety issues have become increasingly important in the retail sector. This study focused on the perception of the safety of ready-to-eat (RTE) foods at hypermarkets. The objectives of the current study were to evaluate the perception of food safety-related attributes of RTE food and identify the key influencing factors to satisfaction at hypermarkets. A survey was conducted through a structured questionnaire that was administered at a hypermarket in Taipei, Taiwan. The hypermarket had a Hazard Analysis and Critical Control Points certification for RTE foods, while the target population was employees who had purchased RTE foods there. In total, 130 of the obtained questionnaires were valid. The statistical analysis encompassed descriptive statistics (means, percentages, and frequencies), exploratory factor analysis, and regression analysis. Four dimensions, i.e., facility, food, ambience/layout, and work staff, were identified to evaluate the food safety-related attributes of RTE foods at the hypermarket. A significant relationship between the food safety-related attributes and the overall customer satisfaction exists for ready-to-eat foods at hypermarkets. The facility, food, and work staff are all significantly impacting customer satisfaction. The results of this study promote a better understanding of consumer behavior toward food safety, thereby encouraging and supporting hypermarkets to design their layout and marketing strategies vis à vis RTE food. © 2021 by the author. Licensee MDPI, Basel, Switzerland.

16.
China CDC Weekly ; 2(6):83-86, 2020.
Article in English | MEDLINE | ID: covidwho-1445121
17.
Chinese Education and Society ; 54(1-2):68-89, 2021.
Article in English | Scopus | ID: covidwho-1402206

ABSTRACT

Abstract: An online survey of 1577 private kindergarten teachers was conducted during the pandemic, and their career situation and its influencing factors were described and analyzed. The results indicate that, although the private kindergarten teachers tended to cope positively with the impact of the COVID-19 pandemic, their concern for future development exhibited significant correlation with work fatigue and avoidance of learning, reflecting the negative occupational ecology for private kindergarten teachers during the pandemic. The COVID-19 pandemic resulted in a substantial reduction in income for the private kindergarten teachers, with a decline of 50% or more in income for more than 76% of teachers;the higher the reduction in income for the private kindergarten teachers, the more strongly their work fatigue, concern for future development, and avoidance of learning were expressed, accompanied by a significant decline in the frequency of online teaching activities. To address the current state of career situation among private kindergarten teachers produced by the pandemic, support mechanisms should be strengthened, to prevent the erosion of teachers;measures to combat the pandemic in the industry should be furthered, to build occupational confidence;educational equity should be promoted, to achieve balanced development;and online educational resources should be enriched, to standardize online educational activities. © 2021 Taylor & Francis Group, LLC.

18.
Chinese Traditional and Herbal Drugs ; 52(16):4959-4972, 2021.
Article in Chinese | EMBASE | ID: covidwho-1377102

ABSTRACT

Objective: To mine the distribution rules of antiviral traditional Chinese medicine (TCM), in order to provide the basis for the screening of antiviral activity of TCM and candidate prescriptions for current epidemic prevention and control. Methods: Taking the Research and Application of Antiviral Chinese Herbal Medicine and the literature reports of antiviral TCM in CNKI and Web of science as information sources, the relevant information was standardized, and the distribution rules of medicinal properties, families and genera, active ingredients and activity of antiviral TCM were mined by frequency analysis, co-occurrence analysis and phylogenetic tree construction methods. Results: A total of 511 antiviral TCM were screened, containing 41 of the 48 herbs involved in the "three medicines and three prescriptions" of coronavirus disease 2019 (COVID-19). Mostly with medicinal properties such as cold nature, bitter taste, return to the lung and liver meridian, among which Bailangen (Isatidis Radix), Huangqin (Scutellariae Radix), and Jinyinhua (Lonicerae Japonicae Flos) were the most common. The data of coronaviridae was 135, and the high-frequency TCM were Chaihu (Bupleuri Radix), Gancao (Glycyrrhizae Radix et Rhizoma), and Isatidis Radix. Meanwhile, it was found that Isatidis Radix and Kudouzi (the seed of Sophora alopecuroides) were the most studied TCM during the SARS period in 2003, while in 2020, the research on Sangbaipi (Mori Cortex) was the first when COVID-19 was sudden. The effective ingredients of antiviral TCM were mostly polysaccharides and flavonoids. TCM with antiviral effects involved a total of 564 base source species, which had significant clustering on phylogenetic trees and were mainly distributed in the chrysanthemum and rose branches of the seed plant phylum, with Asteraceae, Labiatae, Leguminosae, and Rosaceae having the most antiviral TCM. Conclusion: These results suggested that the attributes of TCM with antiviral effects are mainly bitter, cold, lung and liver meridian. TCM origin from Asteraceae, Labiatae, and Leguminosae are more likely to have antiviral effects. Their effective components such as astragalus polysaccharide, Isatidis Radix polysaccharide, quercetin, caffeic acid and ursolic acid are polysaccharides or flavonoids, and these rules are basically consistent with the "three medicines and three prescriptions" promoted and used in this fight against the COVID-19 epidemic. This study provides a reference for the screening of antiviral TCM activity, especially for the screening of candidate TCM for the prevention and control of the current COVID-19.

19.
Methods Pharmacol. Toxicol.. ; : 631-660, 2021.
Article in English | EMBASE | ID: covidwho-1361269

ABSTRACT

Coronavirus infectious disease (COVID-19), caused by deadly severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been declared as a pandemic by the World Health Organization. This disease has become the world’s worst infectious disease, killing about 1.05 million lives as of September 2020. The absence of vaccines and effective drugs is a key trouble responsible for the ineffective management of this pandemic. Considering this emergency situation, several trials have been made to identify repurposing on-market drugs known for their antiviral behavior. Several modern technologies such as deep machine learning are used to combat this deadly disease with faster prediction and greater accuracy. More interestingly, these studies have provided clues for the antiviral properties and are believed to help in effective control of this pandemic. The drugs identified by deep learning-based virtual screening will help in unraveling molecular mechanisms of therapeutic and antiviral properties and will pave the way for designing artificial drugs. Hence we focus in this chapter on the integrated applications of deep learning models as a pipeline for drug and vaccine discovery which has implications in therapeutic drug targeting for COVID-19.

20.
Blood ; 136:9-10, 2020.
Article in English | EMBASE | ID: covidwho-1348341

ABSTRACT

Introduction: A growing body of data has shown that higher cumulative anesthesia exposure is associated with neurocognitive impairment in children with chronic disease, including those with hematologic malignancies [Banerjee JAMA Oncology 2019]. To limit general anesthesia (GA) exposure alternative means of sedation and acceptance of alternatives by patients, families and providers need to be explored for children with acute lymphoblastic leukemia or lymphoma (ALL/LL) undergoing repeated lumbar punctures (LP) to deliver intrathecal (IT) chemotherapy. Methods: Patients age 1 to 25 years with ALL/LL treated at the Children's Hospital of Philadelphia main outpatient clinic (CHOP Main) and two CHOP satellite oncology offices (KOP, VOR) were analyzed for baseline rates of sedation for lumbar punctures. GA was defined as the use of intravenous (IV) propofol or an inhalational flurane. Moderate sedation was defined as IV fentanyl (maximum 2 mcg/kg dosing) for analgesia and midazolam (maximum 0.1 mg/kg) for anxiolysis. IV or oral midazolam only was considered mild sedation. We created a comprehensive quality improvement (QI) pathway to implement the use of mild/moderate sedation as a new Division of Oncology standard for LP-only procedures. Our QI goal was a 10% reduction in use of GA with concomitant measurement of outpatient clinic length of stay (LOS) as an additional metric. LOS was measured as time from triage to port de-access. Results: Our interdisciplinary QI team leveraged the CHOP QI framework utilizing tools that included a driver diagram (Figure 1) and impact/effort matrix to develop and prioritize interventions associated with achieving the QI goal. The Plan-Do-Study Act methodology was used to optimize the intervention. This required extensive collaboration with pediatric oncologists, nurse practitioners, nursing, child life, pharmacy, and QI staff to encourage methodology adoption and to optimize clinic workflow for maximal provider/patient participation and procedural efficiency. In the immediate period preceding the QI intervention (October 2019 to February 2020), baseline rates of GA use for across all 3 clinic sites were 73.1%, 15% (plus 34.6% deep sedation), and 24.7% at CHOP Main, KOP, and VNJ, respectively in 310 LP only procedures for patients with ALL/LL. After a delay in implementation due to COVID, the rate of GA usage at CHOP Main from May to July 2020 was reduced to 55.6% for 81 LPs (p=0.001) (Figure 2), while GA rates at the satellite clinics were unchanged. Decreased GA use at CHOP main was replaced by a significant increase in mild/moderate sedation (26.9% to 44.5%;p=0.001). Of the 18 newly diagnosed patients participating in the intervention to date, 16 receive their LPs with no or mild/moderate sedation. The median age of this cohort is 7 years of age with 6 patients ≤ 5 and 12 patients ≤ 10 years. The other two patients have medical syndromes deemed not conducive to replacing GA with moderate sedation. No child has experienced complications from moderate sedation or returned to GA due to sedation intolerance. Overall clinic LOS decreased significantly for all patients getting LPs (GA and sedation) (mean 4.88 hours vs 4.08 hours;p=0.033). An unintended benefit of the QI initiative is that the average LOS for patients receiving moderate sedation decreased from 6.67 hours to 4.15 hours (p=0.017) with the new streamlined clinic workflow. Conclusion: Baseline rates of sedation varied by oncology clinic site and appeared to align with ease of access to GA. GA is available in the oncology main clinic 3 days/week, and 73% of ALL/LL patients were using GA for LPs prior to the intervention. Since March 2020, nearly all patients with newly diagnosed ALL/LL are now undergoing LPs with no or mild/moderate sedation. Our data show that with appropriate education and preparation, LP with mild/moderate sedation is a feasible alternative to GA even for very young patients and reduces clinic LOS. We have expanded this QI intervention to include children with other newly-diagnosed cancers who require LP and/or IT chemotherapy. Future directions include converting patients in ALL/LL maintenance and those undergoing other minimally invasive procedures from GA to moderate sedation. [Formula presented] Disclosures: Tasian: Incyte Corporation: Research Funding;Gilead Sciences: Research Funding;Aleta Biotherapeutics: Membership on an entity's Board of Directors or advisory committees. Rheingold: Pfizer: Research Funding.

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