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AbstractBispecific killer cells engagers (BiKEs) which can bind to natural killer (NK) cells through the activating receptor CD16A and guide them to cells expressing the HIV-1 envelope glycoprotein (Env) are a promising new weapon for elimination of infected cells and eradication of the virus. Here we report the design, generation and characterization of BiKEs which consist of CD16A binding human antibody domains fused through a flexible linker to an engineered one-domain soluble human CD4. In presence of cells expressing HIV-1 envelope glycoproteins (Envs), these BiKEs activated specifically CD16A-expressing Jurkat T cells, degranulated NK cells, induced cytokine production and killed Env-expressing cells. They also effectively mediated killing of chronically and acutely HIV-1 infected T cells by human peripheral blood mononuclear cells. The presumed ability of these CD4-based BiKEs to bind all HIV-1 isolates, their small size and fully human origin, combined with high efficacy suggest their potential for HIV-1 eradication.

Abstract The outbreak of COVID-19 plunged the world into unprecedented difficulties, bringing life to a terrible standstill around the world and claiming thousands of lives. It seriously endangers human life and health. Thus, a high-efficiency COVID-19 and community-acquired pneumonia (CAP) detection method based on computed tomography (CT) images were developed to combat the pandemic. Sixty-one confirmed COVID-19 cases were consecutively enrolled together with 27 confirmed community-acquired pneumonia patients and 87 normal control patients with no finding of COVID-19 and CAP from Ruian People’s Hospital, from January 2020 to March 2020. The final cohort of 175 patients (1611 CT slices) was divided into training and test sets in an 8:2 and equal ratio. Three senior radiologists assessed clinical Characteristics of COVID-19 patients and abnormalities in chest CT images independently. The proposed model, EfficientNet-B1 was applied for the classification task, which consists of 16 mobile inverted bottleneck convolutions (MBConv), 2 convolutional (Conv) layers, 1 global average-pooling layer, and 1 fully connected layer, obtained a test accuracy of 94.24% and 93.64% for binary and three-class classification, respectively. It also achieved a sensitivity of 92.35%, a specificity of 95.93%, a positive predictive value of 95.26%, negative predictive value of 93.39% with an area under the receiver operating characteristic curve of 0.9414 for COVID-19 and CAP classification. Fever (58 [95.1%]) with a mean axillary temperature of 37.3 ± 0.8 °C, cough (52 [85.2%]), and sputum production (35 [57.4%]) are the most common symptoms of COVID-19 patients at the onset of illness. More importantly, more than 50% of COVID-19 images show ground-glass opacities. The proposed model achieves state-of-the-art performance and can be applied as a supplementary tool for radiologists, which is beneficial for pandemic control.

Respiratory viral infections are a leading cause of disease and mortality. The severity of these illnesses can vary markedly from mild or asymptomatic upper airway infections to severe wheezing, bronchiolitis or pneumonia. In this article, we review the viral sensing pathways and organizing principles that govern the innate immune response to infection. Then, we reconstruct the molecular networks that differentiate symptomatic from asymptomatic respiratory viral infections, and identify the underlying molecular drivers of these networks. Finally, we discuss unique aspects of the biology and pathogenesis of infections with respiratory syncytial virus, rhinovirus and influenza, drawing on insights from genomics.

Objectives During the 2019 Coronavirus disease (COVID-19) outbreak, malnutrition may contribute to COVID-19 adverse outcomes. We conducted a clinical epidemiological analysis to investigate the association of malnutrition with hospitalized duration in patients with COVID-19. Design Retrospective survey study. Setting Taikang Tongji (Wuhan) hospital in Wuhan, China. Participants 139 patients with COVID-19. Methods In total, 139 patients with COVID-19 from patients in the Infection Department of Taikang Tongji (Wuhan) hospital from February 2020 to April 2020 were analyzed retrospectively. We used the “Global leadership Initiative on Malnutrition(GLIM)” assessment standard published in 2019 to assess nutritional status. Prolonged hospitalization was lasting more than the median value of the hospitalized days (17 days) in this population. Results According to the assessment results of GLIM nutrition assessment, the patients were divided into malnutrition group and normal nutrition group. Compared with the patients in the normal nutrition group, the hospitalization time was longer(15.67±6.26 days versus 27.48±5.04 days, P = 0.001). Kaplan-Meier analysis showed patients with malnutrition were more likely to be hospitalized longer compared with those normal nutrition (mean with 95% confidence interval [CI]: 28.91[27.52–30.30] versus 22.78[21.76–23.79], P = 0.001). COX regression analysis showed that malnutrition (hazard ratio [HR] = 3.773, P for trend = 0.001) was proportional associated with being discharged from hospital delayed. Conclusion and implications Present findings suggested that malnutrition contributed to predicting a probability of prolonged hospitalization in patients with COVID-19 infection, to whom extra attentions and precautions should be paid during clinical treatments. Based on the existing results, it is recommended that inpatients with nutritional risk or malnutrition start nutritional support treatment as soon as possible.

Novel coronavirus pneumonia (COVID-19) is rampant in many countries and regions and there is no time to delay the exploration of the scheme for its prevention and control. The pathogenic characteristics of novel coronavirus and the effect of moxibustion for warming up yang and strengthening the antipathogenic qi were analyzed in this paper. From the perspective of modern medical mechanism, during the prevention and treatment of novel coronaviral infection, moxibustion may be able to prevent and treat COVID-19 by improving the body's immunity so as to conquer virus, by anti-inflammation to alleviate the inflammatory response of COVID-19 and by improving lung function to inhibit pulmonary fibrosis.

Abstract Background Coronavirus disease 2019 (COVID-19) has evolved as a pandemic of unimaginable magnitude. The health care system is facing a tremendous challenge to provide ethical and quality care. The transformation of the patient-based care to population-based care during the COVID-19 pandemic has raised ethical dilemma among urologists. Our objective is to explore the consensus in modified standard urology care, that can be adopted and applied during COVID-19 and similar pandemic. Methods We adopted an exploratory study design using secondary data. The data were extracted from a web-based medical library using keywords “COVID-19,” “severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2),” and “urology.” We identify and extrapolate (screening, eligibility, and inclusion) the data using PRISMA protocol, and summarize pandemic standard urology care under four main themes: (1) general urology care, (2) choice of surgical modality, (3) triage, and (4) urology training. Result We identified 63 academic papers related to our research question. The majority are expert opinions and perspectives on urology care. The common consensus is triage-based urology care and surgeries. Life or organ threatening conditions need immediate attention. Universal protective measures (personal protective equipment, safe operative environment) and protocol-based patient care are necessary to prevent and control SARS-CoV-2 infection. Conservation of the resources and its rational distribution provide an ethical basis for population-based health care during a pandemic. Informed decision making serves best to patients, families, and society during the public health crisis. Conclusion COVID-19 pandemic tends to transform standard urology practice into crisis standard population-based care. The consensus in crisis is drawn from evolving pieces of medical evidence and public health ethics. The provision of urology care during a pandemic is based on the availability of resources; severity of the disease, consequences of deferment of service, and dynamics of the pandemic.

Coronavirus disease 2019 (COVID‐19) is a viral disease which is declared as a pandemic by WHO This disease is posing a global threat, and almost every country in the world is now affected by this disease Currently, there is no vaccine for this disease, and because of this, containing COVID‐19 is not an easy task It is noticed that elderly people got severely affected by this disease specially in Europe In the present paper, we propose and analyze a mathematical model for COVID‐19 virus transmission by dividing whole population in old and young groups We find disease‐free equilibrium and the basic reproduction number (R0) We estimate the parameter corresponding to rate of transmission and rate of detection of COVID‐19 using real data from Italy and Spain by least square method We also perform sensitivity analysis to identify the key parameters which influence the basic reproduction number and hence regulate the transmission dynamics of COVID‐19 Finally, we extend our proposed model to optimal control problem to explore the best cost‐effective and time‐dependent control strategies that can reduce the number of infectives in a specified interval of time [ABSTRACT FROM AUTHOR] Copyright of Mathematical Methods in the Applied Sciences is the property of John Wiley & Sons, Inc and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission However, users may print, download, or email articles for individual use This abstract may be abridged No warranty is given about the accuracy of the copy Users should refer to the original published version of the material for the full abstract (Copyright applies to all Abstracts )

Background Coronavirus disease 2019 (COVID-19) is already a pandemic. Few studies investigated the epidemic characteristics of the COVID-19 outbreak in the well-developed cities. Methods Epidemiological data of 136 confirmed COVID-19 cases were collected from the dataset of COVID-19 in Tianjin. All confirmed cases were categorized according to their potential infection sources. Daily numbers of confirmed cases of each category were plotted by date of onset, and the epidemic form of each category was inferred. Results Among the 136 confirmed COVID-19 cases, 48 cases were categorized as imported cases and their close contacts, which were the majority of early cases. A total of 43 cases were found an epidemiological link to the Baodi department store, and they were inferred to be a common-source outbreak. Additionally, 35 cases were considered as familial clusters of COVID-19 cases, and 10 cases were sporadic. The 45 cases were inferred to be a propagated epidemic. Conclusions Local transmission of COVID-19 mainly occurred within families and a poorly ventilated public place in Tianjin. Besides the imported cases, the pattern of local transmission of COVID-19 was a mixture of the propagated epidemic and the common-source outbreak in Tianjin. Highlights • Local transmission of COVID-19 is largely occurring in the well-developed cities. • The epidemic pattern was propagated combined with the common-source outbreak. • COVID-19 mainly occurred within families and a poorly ventilated public place.