ABSTRACT
9870 thousand people develop tuberculosis (TB) in 2020. Despite being a preventable as well as curable communicable disease, tuberculosis still is the leading communicable disease killer globally. The WHO's End TB Strategy envisions a world free of TB, zero deaths, disease, and suffering due to tuberculosis by 2035. China ranks second for TB cases globally. Over the past 20 years, China has made remarkable achievements in tuberculosis control, with the prevalence and mortality rate of tuberculosis reduced by half compared with 1990. China has achieved the United Nations Millennium Development Goals on tuberculosis control 5 years ahead of schedule. However, in spite of concerted international, regional, and national efforts to address tuberculosis in China, the tuberculosis burden in China is still high. At the same time, China also faces problems such as the high burden of latent TB infection, rifampicin-resistant/ multidrug-resistant tuberculosis, and low detection rate of tuberculosis. China needs to further improve the quality of tuberculosis control work to reduce the incidence of tuberculosis and ultimately achieve the goal of ending tuberculosis. © People's Medical Publishing House, PR of China 2022.
ABSTRACT
Interest in online learning is increasing due to its advantages and pedagogical potential. However, few studies have investigated the effects of task-driven instruction on learning outcomes. This study examines the effectiveness of the application of task-driven instruction as a means of verifying that the use of task-driven instruction in online learning is effective by comparing changes in students' grades, intrinsic motivation, perceived social presence, and perceived cognitive load before and after the application of the method. Eighty high school students (33 males) were recruited for this experiment. Prior to the experiment, the purpose and steps of the study were explained frankly and candidly, problems and risks that might arise from participation in the study were pointed out, the benefits that would result from participation in the study were explained, and the possibility of voluntarily withdrawing from the study at any time was clearly communicated and approved by the study subjects or guardians. They were divided into experimental group I and control group II, with 40 students in each group. The results of the study showed that after the implementation of the instruction, the experimental group I performed significantly better than the control group II. In addition, the experimental group II outperformed the control group II in terms of perceived intrinsic motivation, social presence, and cognitive load. © 2023 ACM.
ABSTRACT
Corona Virus Disease 2019 (COVID-19) has caused several pandemic peaks worldwide due to its high variability and infectiousness, and COVID-19 has become a long-standing global public health problem. There is growing evidence that severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) frequently causes multi-organ injuries and more severe neurological manifestations. Therefore, increased awareness of possible neurological complications is beneficial in preventing and mitigating the impact of long-term sequelae and improving the prognostic outcome of critically ill patients with COVID-19. Here, we review the main pathways of SARS-CoV-2 neuroinvasion and the potential mechanisms causing neurological damage. We also discuss in detail neurological complications, aiming to provide cutting-edge basis for subsequent related basic research and clinical studies of diagnosis and treatment.
Subject(s)
COVID-19 , Nervous System Diseases , Humans , COVID-19/complications , SARS-CoV-2 , Nervous System Diseases/etiology , Nervous System Diseases/therapyABSTRACT
Purpose: The purpose of this study is to investigate the impact of religiosity on banks' lending behavior during the COVID-19 pandemic in the USA. Design/methodology/approach: This study uses the evidence from the issuance of Paycheck Protection Program (PPP) loans to relate local religiosity to banks' participation in the PPP loan program and to banks' loan portfolio performance during the pandemic. Findings: The results of this study show that banks located in more religious counties have a higher level of lending through the PPP, supporting the ethical and moral concerns cultivated by local religious beliefs. In addition, banks' lending before the pandemic is more prudential in more religious areas, as reflected in lower losses and higher returns at the onset of the crisis, especially in areas where business activities were most disrupted, supporting the stewardship role encouraged by religiosity. Originality/value: Thanks to the structure of the PPP loans programs, the authors are able to disentangle the conflicting effects of morality and prudence on banks' behavior. © 2023, Emerald Publishing Limited.
ABSTRACT
Overall survival (OS) is considered the standard clinical endpoint to support effectiveness claims in new drug applications globally, particularly for lethal conditions such as cancer. However, the source and reliability of OS in the setting of clinical trials have seldom been doubted and discussed. This study first raised the common issue that data integrity and reliability are doubtful when we collect OS information or other time-to-event endpoints based solely on simple follow-up records by investigators without supporting material, especially since the 2019 COVID-19 pandemic. Then, two rounds of discussions with 30 Chinese experts were held and 12 potential source scenarios of three methods for obtaining the time of death of participants, including death certificate, death record and follow-up record, were sorted out and analysed. With a comprehensive assessment of the 12 scenarios by legitimacy, data reliability, data acquisition efficiency, difficulty of data acquisition, and coverage of participants, both short-term and long-term recommended sources, overall strategies and detailed measures for improving the integrity and reliability of death date are presented. In the short term, we suggest integrated sources such as public security systems made available to drug inspection centres appropriately as soon as possible to strengthen supervision. Death certificates provided by participants' family members and detailed standard follow-up records are recommended to investigators as the two channels of mutual compensation, and the acquisition of supporting materials is encouraged as long as it is not prohibited legally. Moreover, we expect that the sharing of electronic medical records and the legal disclosure of death records in established health registries can be realized with the joint efforts of the whole industry in the long-term. The above proposed solutions are mainly based on the context of China and can also provide reference for other countries in the world. © 2022 The Authors
ABSTRACT
China's port investments in countries along the Belt and Road are growing, while the global investment environment has deteriorated due to the Sino-US trade friction and the COVID-19 epidemic. However, the recent quantitative research on overseas port investment risk has not considered the time weight, and the related research is less. Therefore, this paper proposes a dynamic evaluation method specially for port investment risk of countries along the B&R based on entropy weight-TOPSIS and BP neural network. First, we figure out the static comprehensive risk value by entropy weight-TOPSIS method, and get the dynamic comprehensive risk value by time weighting method. Second, select three-dimensional data of 32 indicators in 18 host countries from 2010 to 2019 for empirical analysis, and obtain the risk level of each country. Lastly, compared with multiple regression, ridge regression, partial least square, we find BP neural network is the most effective means to estimate the simulation weight of evaluation indicators. The experimental result shows that, the proposed dynamic risk assessment approach for overseas port investment is able to assess risk well and can be extended to other fields. © 2022 IEEE.
ABSTRACT
Aim To determine the antiviral and anti-inflammatory effects of the recommended prescription for COVID-2019-lung-spleen qi deficiency(4-1)against in vitro infection of SARS-CoV-2 and common coronaviruses.Methods The main chemical substances of 4-1 were analyzed by LC-MS.The toxicity and antiviral effects of of 4-1 were detected by MTT and by CPE assay, respectively.The viral loads in cell supernatant and the expression of inflammatory factors induced by viral infection were determined by qRT-PCR.Results The recommended prescription 4-1 contained 94 chemical compounds, including flavonoids, steroids, sesquiterpenoids, and so on.The range of selection indexes for SARS-CoV-2 and common coronaviruses was 8.44+/-0.49~52.26+/-2.3.This prescription could inhibit the proliferation of SARS-CoV-2, the expression of ACE2 and S mRNA, and down regulate IL-1alpha and CCL-5/RANTES at 10, 5, and 2.5 g*L-1 doses.Further, at doses of 20, 10 and 5 g*L-1, it could inhibit the proliferation of three common coronaviruses and suppress the overexpression of IL-6, CXCL-8/IL-8, CXCL-10/IP-10, TNF-alpha, IFN-alpha, CCL-2/MCP-1, MIG and CCL-5/RANTES induced by OC43/229E infection.The inhibitory effects were dose-dependent.Conclusions The prescription 4-1 has antiviral and anti-inflammation effects against multiple coronaviruses.This study provides the research basis for the treatment of common respiratory viral infections and emerging infectious diseases such as COVID-19 by using traditional Chinese medicine. Copyright © 2022 Publication Centre of Anhui Medical University. All rights reserved.
ABSTRACT
Non-pharmaceutical interventions such as hand-washing hygiene, avoiding large gatherings, and avoiding visiting nursing homes remain important in mitigating risks of COVID infection among at-risk populations such as older adults. The NIH's All of Us Research Program offers a unique dataset which contains detailed survey data that medical records often lack. Leveraging this dataset and impact scores, we were able to compare deep neural network (DNN) models to more conventional logistic regression and XGBoost models in the task of examining the relationships between social determinants of health and COVID-related behaviors in older adults. LR and DNN models found that African American participants were more likely than White participants to report adherence to guidelines regarding attending large social gatherings, abiding by stay-at-home recommendations and practicing pandemic-related hygiene. Both models also showed that respondents who were employed were less likely than their unemployed/retired counterparts to avoid large social gatherings or participate in activities outside their homes but were more likely to report practice pandemic-related hygiene. DNN models combined with impact scores to explain their output present an alternate approach to modeling outcomes in large, multi-variate cohorts which can outperform conventional statistical modeling. © 2022 IEEE.
ABSTRACT
The COVID-19 has forced global museums to face unprecedented challenges. During the epidemic period, many museums took the initiative to seek change and flexibly use digital technology to cope with the crisis. In addition to its outstanding role in the protection of cultural heritage, Jingdezhen Ceramic Museum also gives full play to the role of cultural communication and cultural leading in the development of cultural industry and the city itself, which has played an important role in Jingdezhen cultural and tourism industry. Starting from the current situation of Jingdezhen Ceramic Museum and combined with the development trend of global museums in the digital era, the future development direction of Jingdezhen Ceramic Museum in the dual background of the digital era and COVID-19 is discussed. © 2022 Editorial Office of Journal of Ceramics. All rights reserved.
ABSTRACT
Background: Patients with multiple myeloma (MM), an age-dependent neoplasm of antibody-producing plasma cells, have compromised immune systems due to multiple factors that may increase the risk of severe COVID-19. The NCATS' National COVID Cohort Collaborative (N3C) is a centralized data resource representing the largest multi-center cohort of ∼12M COVID-19 cases and controls nationwide. In this study, we aim to analyze risk factors associated with COVID-19 severity and death in MM patients using the N3C database. Methods: Our cohort included MM patients within the N3C registry diagnosed with COVID-19 based on positive PCR or antigen tests or ICD-10-CM. The outcomes of interest include all-cause mortality (including discharge to hospice) during the index encounter, and clinical indicators of severity (hospitalization/ED visit, use of mechanical ventilation, or extracorporeal membrane oxygenation/ECMO). Results: As of 09/10/2021, the N3C registry included 690371 cancer patients, out of which 17791 were MM patients (4707 were COVID-19+). The mean age at diagnosis was 65.9yrs, 57.6% were >65yo, 46.4% were females, and 21.8% were Blacks. 25.6% had a Charlson Comorbidity Index (CCI) score of ≥2. 55.6% required an inpatient or ED visit, and 3.65% required invasive ventilation. 11.4% developed acute kidney injury during hospitalization. Multivariate logistic regression analysis showed histories of pulmonary disease (OR 2.2;95%CI: 1.7-2.8), renal disease (OR 1.8;95%CI: 1.4-2.4), and black race (p<0.001) were associated with higher risk of severity. Interestingly, smoking status was significantly associated with a lower risk of severity (OR 0.7;95%CI: 0.5-0.9). Further, protective association was also observed between COVID-19 severity and blood or marrow transplant (BMT) (OR 0.52;95%CI: 0.4-0.7), daratumumab therapy (OR 0.64;95%CI: 0.42- 0.99) and COVID-19 vaccination (OR 0.28;95%CI: 0.18-0.44). IMiDs were associated increase in the risk of COVID-19 severity (OR 2.1;95%CI: 1.6-2.7). 2.3% of N3C-myeloma COVID-19+ patients died within the first 10 days, while 4.95% died within 30 days of COVID-19 hospitalization. Overall, the survival probability was 90.5% across the course of the study. Multivariate cox proportional hazard model showed that CCI score ≥2 (HR 4.4;95%CI: 2.2-8.8), hypertension (HR 1.6;95%CI: 1.02- 2.4), IMiD (HR 2.6;95%CI: 1.8-3.8) and proteasome inhibitor (HR 1.6;95%CI: 1.1-2.5) therapy were associated with worse survival. COVID-19 vaccination (HR 0.195;95%CI: 0.09-0.45) and BMT (HR 0.65;95%CI: 0.4-0.995) were associated with lower risk of death. Conclusions: We have identified previously unpublished potential risk factors for COVID-19 severity and death in MM as well as validated some published ones. To the best of our knowledge, this is the largest nationwide study on multiple myeloma patients with COVID-19.
ABSTRACT
An effective and accurate method of detecting COVID-19 infection is to analyze medical diagnostic images (e.g. CT scans). However, patients' information is privacy, and it is illegal to share diagnostic images among medical institutions. In this case, a critical issue faced by the model that detects the CT images is lacking enough training images dataset, then the features of COVID-19 cannot be accurately obtained. The data privacy attracts extensive attentions recently and is particularly important for the fast-developing medical institution database and. Considering this point, this paper presents a blockchain federated learning model, which overcomes the burden of centralized collection of large amounts of sensitive data. The model uses a trained model to recognize CT scans, and shares data between hospitals with privacy protection mechanism. This model is able to learn from shared resources or data between different hospital repositories to discover patients with new coronary pneumonia by detecting the computed tomography (CT) images. Finally, we conduct extensive experiments to verify the performance of the model. © 2021 IEEE.
ABSTRACT
Big Traffic data [1] is cross-border multi-source data for multiple industries, but traffic roads have brought significant economic and social benefits, the number of traffic accidents and casualties is on the rise. Among them, traffic accidents are related to many factors, such as weather and population density. The data set used in this article is open source in Barcelona. The Random Forest algorithm is used to screen essential risk factors, establish a traffic risk prediction model, and compare traffic risks before and after COVID-19. It is concluded that the outbreak of the new crown virus -19-19 has a great impact on people's travel and transportation. Finally, the R square of the model established by Random Forest is 0.9. The K-means clustering algorithm is used to determine the location of the accident handling centre. Moreover, the scope of each accident risk management centre can cover more than 85 percent of traffic accident sites from 2016 to 2020. © 2021 IEEE.
ABSTRACT
Along with the continuous outbreak of COVID-19, countries all over the world have taken measures to prevent and control the virus, moreover, the pandemic measures taken in the communities are the most strict ones in particular. Currently, the health data of residents is collected manually in most communities when the pandemic is stable to some extent. Then, the pandemic risks confronted by residents are assessed accordingly, however, only the minority of communities verify the health identities of residents by scanning their health code. In such a background, the completed and humanized platform systems have not yet been designed and promoted in the market for further pandemic prevention and control. This system distinguishes the administrator from the user, the user homepage mainly has the function of viewing the announcement, the problem feedback, the membership application, the volunteer service and so on. The administrator homepage has the functions of registered user management, isolation audit management, volunteer service management, access management and so on. In addition, based on the fundamental pandemic prevention measures, the system is also endowed with function as big data analysis, which can analyze the epidemic data of inland provinces in China at the present stage to further strengthen epidemic prevention and control. Prevent infected people from entering the community and form a large-scale infection. © 2021 IEEE.
ABSTRACT
COVID-19 is a severe and complex epidemic ravaging many countries. Traditional Chinese medicine (TCM) has accumulated rich experience and achieved outstanding effects in its struggle against epidemics for thousands of years. As an essential intervention means for prevention and control of COVID-19, TCM boasts significant effects in relieving fever symptoms, slowing down disease progression, preventing disease transformation, reducing hormone dosage, and alleviating complications. Establishing and improving the emergency supply service mode of Chinese medicine in response to public health emergencies, and scientifically managing and allocating Chinese medicine medical resources are conducive to establishing a green channel for the emergency supply of Chinese medicine in response to major public health emergencies. This book focuses on the four oral Chinese patent medicines used in the clinical treatment period based on the Guidelines for the Diagnosis and Treatment of COVID-19 by the National Health Commission and National Administration of Traditional Chinese Medicine of China. This work is not only an important part of the theoretical system of TCM treatment based on syndrome differentiation but also an effective way to promote an even deeper integration of clinical pharmaceutical service and clinical medical practice. © 2021 by Chemical Industry Press Co., Ltd.
ABSTRACT
Objective: To determine the odds of critical illness by day 28 and duration of mechanical ventilation (MV) over 45-day observation period in patients with history of cerebrovascular disease and COVID-19. Background: COVID-19-associated morbidity is correlated with multiple factors including age, comorbidities, and host response to the virus. Our understanding of the risk of critical illness due to prior neurological conditions remains limited. Here, we hypothesized that prior cerebrovascular disease is a risk factor for severe outcomes in COVID-19, including increased duration of MV. Design/Methods: A cross-sectional study of 1128 consecutive adult patients admitted to a tertiary care center in Boston, Massachusetts, and diagnosed with laboratory-confirmed COVID-19. The association between history of cerebrovascular disease and critical illness defined as MV or death was examined using logistic regression with inverse probability weighting of the propensity score. Cumulative incidence of successful extubation without death over 45 days was examined using competing risk analysis. Results: Of the 1128 adults admitted with COVID-19, 350 (36%) were critically ill by day 28. The median age was 59 years (standard deviation: 18 years), 640 (57%) were men, and 401 (36%) were Latinx ethnicity. As of June 2nd, 2020, 127 (11%) patients died. A total of 257 (23%) of patients had a prior neurological diagnosis;most common was cerebrovascular disease (16%). Prior cerebrovascular disease was significantly associated with critical illness (OR 1.54 [95% CI: 1.14 - 2.07]), lower rate of successful extubation (cause-specific HR 0.57 [95% CI: 0.33-0.98]), and increased duration of intubation (restricted mean time difference 4.02 days [95% CI: 0.34- 10.92]) compared to patients without cerebrovascular disease. Conclusions: History of cerebrovascular disease adversely affects COVID-19 outcomes including increased risk of critical illness and prolonged intubation. Further studies are needed to define measures that reduce risk of poor outcomes in this subpopulation.
ABSTRACT
The novel coronavirus disease 2019 (COVID-19) broke out in December 2019 and has been rapidly escalating throughout the world. Clinical findings show that the patients with either symptomatic or asymptomatic COVID-19 can be a potential source of infection. Although respiratory droplets and close contact are considered to be the main routes of transmission, there is the possibility of aerosol transmission in a relatively closed environment. The nucleic acid of the novel coronavirus can be detected in nasopharyngeal swabs, sputum and other lower respiratory tract secretions, blood, feces, urine and so on, but whether it exists in the semen has not been confirmed. It is reported that the novel coronavirus may affect the testis that highly expresses angiotensin-converting enzyme 2 (ACE2) and theoretically the semen is a possible carrier of the virus considering the fact that it is discharged from the same channel as the urine. Andrology laboratorians are exposed to most of the specimens above, including semen, and some open operations in the laboratory increase the risk of aerosol generation. Therefore, corresponding protective procedures are necessitated in andrology laboratories to reduce the risk of infection during the outbreak of COVID-19. Based on the knowledge and experience available as regards the pandemic and the characteristics of the work in the andrology laboratory, we summarize some biosafety points for andrology laboratorians to attend to during the outbreak of COVID-19.
ABSTRACT
The rapid growth of the coronavirus disease 2019 (COVID-19) pandemic, limited availability of personal protective equipment, and uncertainties regarding transmission modes of severe acute respiratory syndrome coronavirus-2 have heightened concerns for the safety of healthcare workers (HCWs). Systematic studies of occupational risks for COVID-19 in the context of community risks are difficult and have only recently started to be reported. Ongoing quality improvement studies in various locales and within many affected healthcare institutions are needed. A template design for small-scale quality improvement surveys is proposed. Such surveys have the potential for rapid implementation and completion, are cost-effective, impose little administrative or workforce burden, can reveal occupational risks while taking community risks into account, and can be repeated easily with short time intervals between repetitions. This article describes a template design and proposes a survey instrument that is easily modifiable to fit the particular needs of various healthcare institutions in the hope of beginning a collaborative effort to refine the design and instrument. These methods, along with data management and analytic techniques, can be widely useful and shared globally. The authors' goal is to facilitate quality improvement surveys aimed at reducing the risk of occupational infection of HCWs during the COVID-19 pandemic.