Extracellular Disintegration of Viral Proteins as an Innovative Strategy for Developing Broad-Spectrum Antivirals Against Coronavirus

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has claimed millions of lives and caused innumerable economic losses worldwide. Unfortunately, state-of-the-art treatments still lag behind the continual emergence of new variants. Key to resolving this issue is developing antivirals to deactivate coronaviruses regardless of their structural evolution. Here, we report an innovative antiviral strategy involving extracellular disintegration of viral proteins with hyperanion-grafted enediyne (EDY) molecules. The core EDY generates reactive radical species and causes significant damage to the spike protein of coronavirus, while the hyperanion groups ensure negligible cytotoxicity of the molecules. The EDYs exhibit antiviral activity down to nanomolar concentrations, and the selectivity index of up to 20,000 against four kinds of human coronavirus, including the SARS-CoV-2 Omicron variant, suggesting the high potential of this new strategy in combating the COVID-19 pandemic and a future "disease X."

[Related factors of negative conversion time of nucleic acid in children with COVID-19].

Objective: To explore the related factors of negative conversion time (NCT) of nucleic acid in children with COVID-19. Methods: A retrospective cohort study was conducted. A total of 225 children who were diagnosed with COVID-19 and admitted to Changxing Branch of Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from April 3rd to May 31st 2022 were enrolled in the study. The infection age, gender, viral load, basic disease, clinical symptoms and information of accompanying caregivers were retrospectively analyzed. According to age, the children were divided into<3 years of age group and 3-<18 years of age group. According to the viral nucleic acid test results, the children were divided into positive accompanying caregiver group and negative accompanying caregiver group. Comparisons between groups were performed using Mann-Whitney U test or Chi-square test. Multivariate Logistic regression analysis was used to analyze the related factors of NCT of nucleic acid in children with COVID-19. Results: Among the 225 patients (120 boys and 105 girls) of age 2.8 (1.3, 6.2) years, 119 children <3 years and 106 children 3-<18 years of age, 19 cases were diagnosed with moderate COVID-19, and the other 206 cases were diagnosed with mild COVID-19. There were 141 patients in the positive accompanying caregiver group and 84 patients in the negative accompanying caregiver group.Patients 3-<18 years of age had a shorter NCT (5 (3, 7) vs.7 (4, 9) d, Z=-4.17, P<0.001) compared with patients <3 years of age. Patients in the negative accompanying caregiver group had a shorter NCT (5 (3, 7) vs.6 (4, 9) d,Z=-2.89,P=0.004) compared with patients in the positive accompanying caregiver group. Multivariate Logistic regression analysis showed that anorexia was associated with NCT of nucleic acid (OR=3.74,95%CI 1.69-8.31, P=0.001). Conclusion: Accompanying caregiver with positive nucleic acid test may prolong NCT of nucleic acid, and decreased appetite may be associated with prolonged NCT of nucleic acid in children with COVID-19.

Assessment of Research Performance during COVID-19 Pandemic among Nursing Researchers

The purpose of this study was to assess the research performance during Coronavirus Disease 2019 (COVID-19) pandemic among nursing researchers. Methods: A cross-sectional online survey was conducted for Korean Society of Adult Nursing where 103 subjects participated from April 15 to May 14, 2021. The survey tool developed by researchers had 32 items including difficulties in performing research activities, perception of the impact of COVID-19 on research validity, and three open-ended questions. Results: In the research planning phase, 88 subjects (90.7%) reported difficulties in the recruitment plan and 83 subjects (89.3%) reported difficulties selecting a research design. In the recruitment and data collection phase, 85 subjects (88.6%) had difficulties accessing data collection site and 78 subjects (85.7%) had difficulties in face-to-face data collection. In the provision of intervention phase (for experimental study), 26 subjects (66.7%) reported that they should have changed the method of delivery of intervention. In research administration and manpower management, 62 subjects (75.6%) reported difficulties in face-to-face meeting. In research outcome management, 65 subjects (85.5%) reported that they should have changed the way of research-related events. Lastly, 80 subjects (81.6%) perceived that difficulties caused by COVID-19 impacted research validity. Conclusion: Majority of participants perceived that the difficulties in research activities may decrease research validity. To ensure research quality during COVID-19 pandemic, we should recognize potential threats to research validity and actively pursue adaptable innovations of research designs and data collection methods. © 2021,Korean Journal of Adult Nursing. All Rights Reserved.

A scoping review of health professional oncosexology education and training programs focused on adolescents and young adults (AYA)

Background: AYA with cancer commonly experience sexuality concerns during and post treatment. Evaluation andmanagement of these critical aspects are often neglected by health professionals due to factors such as poor knowledge, confidence and communication, lack of comfort, time and prioritisation of sexuality concerns. It is not known what policy and practice tools are available to bridge this evidence gap. Aim(s): To scope, analyse and map the literature on policy and practice tools, specific to AYA oncosexology education and training programs, for health professionals. Method(s): A scoping review was conducted using the Joanna Briggs Institute methodology. A search strategy was developed using key words initially tested in OVID MEDLINE. The formal search was conducted in July 2022 in Medline, EMCARE, EMBASE and PsychINFO (all on OVID platform) for articles: published after 2012;in English;qualitative, quantitative, mixed method studies, case studies, review articles or grey literature;in patients aged 15-39 years. Articles were excluded if they did not meet these criteria, only examined potential education/training programs or health professionals' knowledge, attitudes or practices, or only focused on patients' perspectives. Retrieved articles were extracted into Covidence and two screening roundswere independently performed by two authors each for the final analysis and evidence synthesis. Result(s): After removing 1140 duplicate records, 1825 records were screened of which 1523 were excluded and 302 full texts assessed for eligibility. The final number of studies included along with other quantitative findings will be reported against the PRISMA-ScR reporting checklist. Results from the basic content analysis to organise qualitative findings into higher level categories will also be presented. Conclusion(s): Evidence gaps, limitations and implications for research will be discussed. We will seek stakeholders' views on whether our findings are locally relevant and how they can inform improvements in health professional oncosexology policy and practice tools.

COVID-19 Datasets: A Brief Overview

The outbreak of the COVID-19 pandemic affects lives and social-economic development around the world. The affecting of the pandemic has motivated researchers from different domains to find effective solutions to diagnose, prevent, and estimate the pandemic and relieve its adverse effects. Numerous COVID-19 datasets are built from these studies and are available to the public. These datasets can be used for disease diagnosis and case prediction, speeding up solving problems caused by the pandemic. To meet the needs of researchers to understand various COVID-19 datasets, we examine and provide an overview of them. We organise the majority of these datasets into three categories based on the category of ap-plications, i.e., time-series, knowledge base, and media-based datasets. Organising COVID-19 datasets into appropriate categories can help researchers hold their focus on methodology rather than the datasets. In addition, applications and COVID-19 datasets suffer from a series of problems, such as privacy and quality. We discuss these issues as well as potentials of COVID-19 datasets. © 2022, ComSIS Consortium. All rights reserved.

Research Progress and Trend Analysis Based on Bibliometric of the National Key Research and Development Program "animal Project" during the 13th Five-Year Period

The 13th Five-Year National Key Research and Development Program has established a key project of "Prevention and Control of Major Animal Diseases, Efficient and Safe Husbandry Technology Research and Development" (Animal Project), which supported scientific and technological innovation research in the field of animal epidemic prevention and control, efficient and safe breeding and breeding environment treatment. This project carried out the design of "whole chain design and integrated implementation" according to basic research, key technology research and development and integrated demonstration to solve the important basic theory and technical bottleneck of animal breeding in China. Based on the method of bibliometric, a statistical analysis was conducted of the papers supported mainly by the project to master the research progress and hot spots of the special project in basic research and frontier theory. Moreover, the future key research direction and development trend in the field of animal husbandry and veterinary medicine was discussed in combination with the layout of animal husbandry and veterinary related projects in the 14th Five-Year Plan. The results showed that this special funded papers had achieved breakthrough research in the basic research fields of major animal diseases and zoonotic diseases such as the COVID-19, Zika virus and African Swine Fever Achievements: Agriculture-related universities and scientific research institutes cooperate closely and have made great contributions;International cooperation is not only with the United States and other developed countries, but also closely cooperated with developing countries such as Pakistan and Egypt related to the "Belt and Road" initiative. The probability of publishing high-quality papers which cooperated with scientific research teams in developed countries has increased significantly;Research hotspots mainly focus on epidemiology, pathogen replication and evolution, drug resistance, pathogen and host interaction and network regulation, immune and pathogenic mechanisms, cross-species transmission, etc. The livestock and poultry special project focuses on the research direction of the prevention and control of major livestock and poultry diseases and efficient and safe breeding, and has made important research progress in major basic theories, supporting the research and application demonstration of key core technologies. The 14th Five-Year National Key Research and Development Program will make a comprehensive layout in the field of animal seed industry innovation, prevention and control of animal diseases, purification and eradication, nutrition regulation and efficient breeding, waste resource utilization and green breeding, breeding equipment and intelligent breeding. Copyright © 2022 Editorial Board, Institute of Animal Science of the Chinese Academy of Agricultural Sciences.

Incorporating Fuzzy Cognitive Inference for Vaccine Hesitancy Measuring

Vaccine hesitancy plays a key role in vaccine delay and refusal, but its measurement is still a challenge due to multiple intricacies and uncertainties in factors. This paper attempts to tackle this problem through fuzzy cognitive inference techniques. Firstly, we formulate a vaccine hesitancy determinants matrix containing multi-level factors. Relations between factors are formulated through group decision-making of domain experts, which results in a fuzzy cognitive map. The subjective uncertainty of linguistic variables is expressed by fuzzy numbers. A double-weighted method is designed to integrate the distinguished decisions, in which the subjective hesitancy is considered for each decision. Next, three typical scenarios are constructed to identify key and sensitive factors under different experimental conditions. The experimental results are further discussed, which enrich the approaches of vaccine hesitancy estimation for the post-pandemic global recovery.

Improved marine predators algorithm for feature selection and SVM optimization

Owing to the rapid development of information science, data analysis based on machine learning has become an interdisciplinary and strategic area. Marine predators algorithm (MPA) is a novel metaheuristic algorithm inspired by the foraging strategies of marine organisms. Considering the randomness of these strategies, an improved algorithm called co-evolutionary cultural mechanism-based marine predators algorithm (CECMPA) is proposed. Through this mechanism, search agents in different spaces can share knowledge and experience to improve the performance of the native algorithm. More specifically, CECMPA has a higher probability of avoiding local optimum and can search the global optimum quickly. In this paper, it is the first to use CECMPA to perform feature subset selection and optimize hyperparameters in support vector machine (SVM) simultaneously. For performance evaluation the proposed method, it is tested on twelve datasets from the university of California Irvine (UCI) repository. Moreover, the coronavirus disease 2019 (COVID-19) can be a real-world application and is spreading in many countries. CECMPA is also applied to a COVID-19 dataset. The experimental results and statistical analysis demonstrate that CECMPA is superior to other compared methods in the literature in terms of several evaluation metrics. The proposed method has strong competitive abilities and promising prospects.

CT Image Classification and Detection of COVID-19 Based on Convolutional Neural Network

As Corona Virus Disease (COVID-19) emerged at the end of 2019, traditional detection is mainly carried out using four methods: coronavirus screening detection strips, COVID-19 antibody detection kits, COVID-19 nucleic acid detection and CT detection, and the problem of low efficiency exists. In order to solve the problem of using neural network to detection a large number of data, slow speed, low efficiency, high cost, complex algorithm structure and low accuracy of detection of large data sets at present. In this paper, by collecting known public COVID-19 CT image data sets, a convolutional neural network algorithm based on residual network is proposed to reduce parameter complexity, modify weights and biases associated with neurons, and simplify the overall network structure. This algorithm is used to improve the accuracy of COVID-19 case classification detection and the convergence speed of the model. Through model verification, the accuracy of the proposed algorithm model is 0.985, the precision is 0.805, the area under the curve (AUC) of the ROC curve is found to be 0.852, and the recall rate is 0.897. The results show that the classification detection algorithm model proposed in this paper has higher accuracy than the general image classification model, is more concise in the network model, reduces the complexity, and can be more effectively applied to the detection of COVID-19. The combination of traditional medical imaging diagnosis and deep learning technology helps medical personnel to make more rapid, accurate and effective diagnosis.

Teaching Preservice Teachers in the Time of COVID: What's Worth Keeping?

As we begin to transition from online instruction to in-person, we (four mathematics teacher educators) reflect on how COVID-19 impacted our instruction and address the question: what will we take back to in-person instruction? This article includes our individual reflections and an analytical synthesis of them. Findings reveal that there were unanticipated ways that human connection and consideration arose from teaching online, much of which we want to maintain in some form when returning to brick and mortar classrooms. We conclude by highlighting the value and importance of reflection for our own well-being.

COVID-19 Lockdowns Afford the First Satellite-Based Confirmation That Vehicles Are an Under-recognized Source of Urban NH3 Pollution in Los Angeles

In situ measurements have suggested vehicle emissions may dominate agricultural sources of NH3 in many cities, which is alarming given the potential for urban NH3 to significantly increase human exposure to ambient particulate matter. However, confirmation of the prevalence of vehicle NH3 throughout a city has been challenging because of mixing with agricultural sources, and the latter are thus routinely assumed to dominate. Here we report vehicle NH3 emissions based on TROPOMI NO2 and CrIS NH3 (0.152 kg s(-1)) that are consistent with a model-based estimate (0.178 kg s(-1)) and show that COVID-19 lockdowns provide a unique opportunity for making the first satellite-based constraints on vehicle NH3 emissions for an entire urban region (western Los Angeles), which we find make up 60-95% of total NH3 emissions, substantially higher than the values of 13-22% in state and national inventories. This provides a new means of constraining a component of transportation emissions whose impacts may rival those of NOx yet which has been largely under-recognized and uncontrolled.

Right ventricular dilation and mortality in acute covid-19

Introduction: Myocardial injury is associated with COVID-19 mortality, but the prognostic value of adverse right ventricular (RV) remodeling on transthoracic echocardiogram (TTE) is uncertain. Therefore we studied the association between RV dilation and in-hospital mortality in acute COVID19. Methods: We included all adults hospitalized with COVID-19 between March 2020 and February 2021 who had a clinical TTE performed during hospitalization at UCSF Health (Parnassus, Mission Bay, or Mount Zion) or Zuckerberg San Francisco General. Clinical and echo data were extracted from the electronic medical record. Biomarkers (BNP & troponin) were log transformed. The primary exposure was qualitative assessment of RV dilation on TTE and the primary outcome was inhospital mortality. We conducted analysis with STATA MP 16.1 using logistic regression models with adjustment for age and sex (Model 1) and age, sex, log(BNP), log(troponin), and mechanical ventilation (Model 2) and compared models with and without RV size with the likelihood ratio test. Results: There were 225 people hospitalized with COVID-19 who had a clinical TTE performed. The mean age was 62.9 years old, 77 (34%) were female, and 48 (21%) died. The majority of patients identified as Latinx (40%), and most patients received Medicaid (58%). Of 212 TTEs adequate to assess RV size, 47 (22%) had RV dilation of whom 16 (34%) died compared to 31 (19%) with normal RV size (RR 1.81, 95%CI 1.09-3.01, p=0.03). Of 185 TTEs adequate to assess RV function, 18 (10%) had RV dysfunction of whom 6 (33%) died compared to 12 (18%) with normal RV function (RR 1.86, 95%CI 0.89-3.84, p=0.12). There were no differences in tricuspid annulus plane systolic excursion or RV systolic excursion velocity. Adjusted for age and sex, RV dilation was associated with mortality (OR 2.16, 95%CI 1.02-4.58;p=0.045), with a larger effect among those with RV dilation and dysfunction (OR 3.40, 95% CI 0.93-12.4, p=0.063). This effect was attenuated after adjusting for BNP, troponin and mechanical ventilation at the time of TTE (OR 1.61, 95%CI 0.52-4.98, p=0.41). Conclusions: RV dilation on TTE is associated with mortality in acute COVID-19, although the effect is attenuated after accounting for mechanical ventilation and biomarkers.

Research on the Elastic Development of Spatial Layout of Hospitals Based on GIS Platform under COVID-19 Background: A Case Study of Wuhan

COVID-19 has become a major public health emergency in the world. At the beginning of the outbreak of the COVID-19 epidemic, a series of medical squeezes appeared in Wuhan, which exposed the problems existing in the implementation of the hierarchical diagnosis and treatment system. Based on GIS platform, this paper analyzes the spatial layout of medical facilities at all levels in Wuhan and compares and analyzes the usage of daily and epidemic periods. It is found that the interlevel gap in the development of daily medical resources leads to spatial differences in the reserved development flexibility, showing the characteristics of weak elastic coping ability and low reserved development flexibility in the surrounding urban areas, strong elastic coping ability and high-reserved development flexibility in the central old urban area. Therefore, to improve the resilience of medical institutions at all levels, we should promote the balanced layout of primary medical institutions and the "decentralization"of high-level medical institutions in spatial layout, coordinate the number and organizational structure of medical resources at different levels, and implement differentiated allocation strategies. © ASCE.

Modelling infectious disease dynamics with probabilistic logic programming

Motivated by the SARS-CoV-2 pandemic, we implemented a stochastic, network-based model of infectious disease transmission in the probabilistic logic programming language ProbLog. In this contribution, we show how probabilistic logic programming lends itself to very concise, transparent and adaptable modelling of infectious disease dynamics. We illustrate how some key features can contribute to succinct and expressive representation of epidemiological models. Our work makes full use of the compact relational representation, the support for stratified negation and flexible probabilities evaluated at run time, which are supported by the ProbLog 2 engine. © 2021 CEUR-WS. All rights reserved.