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Background The global spread of coronavirus disease 2019 (COVID-19) continues to threaten human health security, exerting considerable pressure on healthcare systems worldwide. While prognostic models for COVID-19 hospitalized or intensive care patients are currently available, prognostic models developed for large cohorts of thousands of individuals are still lacking. Methods Between February 4 and April 16, 2020, we enrolled 3,974 patients admitted with COVID-19 disease in the Wuhan Huo-Shen-Shan Hospital and the Maternal and Child Hospital, Hubei Province, China. (1) Screening of key prognostic factors: A univariate Cox regression analysis was performed on 2,649 patients in the training set, and factors affecting prognosis were initially screened. Subsequently, a random survival forest model was established through machine analysis to further screen for factors that are important for prognosis. Finally, multivariate Cox regression analysis was used to determine the synergy among various factors related to prognosis. (2) Establishment of a scoring system: The nomogram algorithm established a COVID-19 patient death risk assessment scoring system for the nine selected key prognostic factors, calculated the C index, drew calibration curves and drew training set patient survival curves. (3) Verification of the scoring system: The scoring system assessed 1,325 patients in the test set, splitting them into high- and low-risk groups, calculated the C-index, and drew calibration and survival curves. Results The cross-sectional study found that age, clinical classification, sex, pulmonary insufficiency, hypoproteinemia, and four other factors (underlying diseases: blood diseases, malignant tumor;complications: digestive tract bleeding, heart dysfunction) have important significance for the prognosis of the enrolled patients with COVID-19. Herein, we report the discovery of the effects of hypoproteinemia and hematological diseases on the prognosis of COVID-19. Meanwhile, the scoring system established here can effectively evaluate objective scores for the early prognoses of patients with COVID-19 and can divide them into high- and low-risk groups (using a scoring threshold of 117.77, a score below which is considered low risk). The efficacy of the system was better than that of clinical classification using the current COVID-19 guidelines (C indexes, 0.95 vs. 0.89). Conclusions Age, clinical typing, sex, pulmonary insufficiency, hypoproteinemia, and four other factors were important for COVID-19 survival. Compared with general statistical methods, this method can quickly and accurately screen out the relevant factors affecting prognosis, provide an order of importance, and establish a scoring system based on the nomogram model, which is of great clinical significance. © Wolters Kluwer Health, Inc. All rights reserved.
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Infections caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A (Flu A), and influenza B (Flu B) show similar clinical symptoms, such as cough, fever, and dyspnea, but patients infected by these viruses should be treated differently. The rapid and accurate diagnosis of infections caused by SARS-CoV-2, Flu A or Flu B is critical during the influenza season. Herein, we synthesized core-shell magnetic particles (MNPs) with excellent antifouling properties and applied them in the MNP-based immunochromatographic test (MICT) for simultaneous detection of SARS-CoV-2, Flu A, and Flu B nucleocapsid(N) proteins in 20 min. Two kinds of carboxyl -modified MNPs, MNP@pMBAA and MNP@Si-SA, were prepared and evaluated as probes in the MICT. Among them, the MNP@ pMBAA showed lower nonspecific adsorption of proteins and low background noise in the application in MICTs. Particularly, the MNP@pMBAA50 bead-based MICT strip exhibited the highest signal-to-noise ratio for SARS-CoV-2 N protein detection with a limit of detection (LOD) of 0.072 ng/mL. Moreover, the proposed MICT strip demonstrated a minimal cross-reactivity and a broad linear dynamic detection range under a magnetic assay reader in the simultaneous detection of SARS-CoV-2, Flu A, and Flu B N proteins with relative LOD values of 0.0086, 0.012, and 0.018 ng/mL, respectively. The results demonstrated that the synthesized MNPs showed great potential for use as MICT probes for sensitive and multiplex detection of biomarkers in the development of point-of-care testing systems.
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Deep learning is a sub-discipline of artificial intelligence that uses artificial neural networks, a machine learning technique, to extract patterns and make predictions from large datasets. In recent years, it has achieved rapid development and is widely used in numerous disciplines with fruitful results. Learning valuable information from complex, high-dimensional, and heterogeneous biomedical data is a key challenge in transforming healthcare. In this review, we provide an overview of emerging deep-learning techniques, COVID-19 research involving deep learning, and concrete examples of deep-learning methods in COVID-19 diagnosis, prognosis, and treatment management. Deep learning can process medical imaging data, laboratory test results, and other relevant data to diagnose diseases and judge disease progression and prognosis, and even recommend treatment plans and drug-use strategies to accelerate drug development and improve drug quality. Furthermore, it can help governments develop proper prevention and control measures. We also assess the current limitations and challenges of deep learning in therapy precision for COVID-19, including the lack of phenotypically abundant data and the need for more interpretable deep-learning models. Finally, we discuss how current barriers can be overcome to enable future clinical applications of deep learning. © 2023 by the authors.
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Mental stress has been recognized as an essential risk factor for hypertension. Therefore, experts specializing in cardiology, psychiatry, and Traditional Chinese Medicine organized by the Psycho-cardiology Group, College of Cardiovascular Physicians of Chinese Medical Doctor Association, and Hypertension Group of the Chinese Society of Cardiology proposed the expert consensus on the diagnosis and treatment of adult mental stress-induced hypertension in March 2021, which includes the epidemiology, etiology, diagnosis, and treatment of the mental stress-induced hypertension. This consensus will hopefully facilitate the clinical practice of this disorder. In addition, the COVID-19 pandemic has become one of the primary global sources of psychosocial stressors since the beginning of 2020, and the revision of this expert consensus in 2022 has increased the relevant content. This consensus consists of two parts. The sections of Part A include (I) Background and epidemiological characteristics, (II) Pathogenesis, and (III) Diagnosis. The sections of Part B contain (IV) Treatment recommendations, and (V) Prospects. This article presents Part B of the consensus. © 2022 Heart and Mind ;Published by Wolters Kluwer - Medknow.
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Mental stress has been recognized as an essential risk factor for hypertension. Therefore, experts specializing in cardiology, psychiatry, and Traditional Chinese Medicine organized by the Psycho-Cardiology Group of College of Cardiovascular Physicians of Chinese Medical Doctor Association and Hypertension Group of Chinese Society of Cardiology proposed the expert consensus on the diagnosis and treatment of adult mental stress-induced hypertension in March 2021, which includes the epidemiology, etiology, diagnosis, and treatment of the mental stress-induced hypertension. This consensus will hopefully facilitate the clinical practice of this disorder. In addition, the COVID-19 pandemic has become one of the primary global sources of psychosocial stressors since the beginning of 2020, and the revision of this expert consensus in 2022 has increased the relevant content. This consensus consists of Part A and Part B. Part A includes (I) Background and epidemiological characteristics, (II) Pathogenesis, and (III) Diagnosis and Part B includes (IV) Treatment recommendations and (V) Prospects. This part presents the content of Part A. © 2022 Heart and Mind ;Published by Wolters Kluwer - Medknow.
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COVID-19 is a global pandemic, which is the third outbreak and epidemic of infectious disease caused by coronavirus in this century and constitutes a major threat to human health.In this paper, COCOVID-19, Severeacute respiratory syndrome (SARS) and Middle East Respiratory syndrome (MERS) were analyzed to distinguish their clinical features, diagnosis, prognosis and prevention, so as to better prevent and treat related diseases.Copyright © 2020 Chinese Medical Association
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COVID-19 is a global pandemic, which is the third outbreak and epidemic of infectious disease caused by coronavirus in this century and constitutes a major threat to human health.In this paper, COCOVID-19, Severeacute respiratory syndrome (SARS) and Middle East Respiratory syndrome (MERS) were analyzed to distinguish their clinical features, diagnosis, prognosis and prevention, so as to better prevent and treat related diseases.Copyright © 2020 Chinese Medical Association
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COVID-19 is a global pandemic, which is the third outbreak and epidemic of infectious disease caused by coronavirus in this century and constitutes a major threat to human health.In this paper, COCOVID-19, Severeacute respiratory syndrome (SARS) and Middle East Respiratory syndrome (MERS) were analyzed to distinguish their clinical features, diagnosis, prognosis and prevention, so as to better prevent and treat related diseases.Copyright © 2020 Chinese Medical Association
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Infections caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A (Flu A), and influenza B (Flu B) show similar clinical symptoms, such as cough, fever, and dyspnea, but patients infected by these viruses should be treated differently. The rapid and accurate diagnosis of infections caused by SARS-CoV-2, Flu A or Flu B is critical during the influenza season. Herein, we synthesized core-shell magnetic particles (MNPs) with excellent antifouling properties and applied them in the MNP-based immunochromatographic test (MICT) for simultaneous detection of SARS-CoV-2, Flu A, and Flu B nucleocapsid(N) proteins in 20 min. Two kinds of carboxyl-modified MNPs, MNP@pMBAA and MNP@Si-SA, were prepared and evaluated as probes in the MICT. Among them, the MNP@pMBAA showed lower nonspecific adsorption of proteins and low background noise in the application in MICTs. Particularly, the MNP@pMBAA50 bead-based MICT strip exhibited the highest signal-to-noise ratio for SARS-CoV-2 N protein detection with a limit of detection (LOD) of 0.072 ng/mL. Moreover, the proposed MICT strip demonstrated a minimal cross-reactivity and a broad linear dynamic detection range under a magnetic assay reader in the simultaneous detection of SARS-CoV-2, Flu A, and Flu B N proteins with relative LOD values of 0.0086, 0.012, and 0.018 ng/mL, respectively. The results demonstrated that the synthesized MNPs showed great potential for use as MICT probes for sensitive and multiplex detection of biomarkers in the development of point-of-care testing systems. © 2023 American Chemical Society.
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In this paper, we formulate and analyze a class of discrete state-structured epidemic models that spread through both horizontal and vertical transmissions on networks, where infected individuals can move from one infected state to any other state so that our models include all possible state-transfers (disease deterioration and amelioration) among different states. Many epidemic transmissions with or without vertical transmission in nature can be analyzed by referring to our models, such as HIV-1, viral hepatitis, and Covid-19. We derive the basic reproduction number R0= Rh+ Rv, and prove that the global dynamics are completely determined by the basic reproduction number: if R0 ≤ 1, the disease-free equilibrium is globally asymptotically stable and the disease always dies out;if R0 > 1, the disease-free equilibrium is unstable, and there exists a unique endemic equilibrium that is globally asymptotically stable, and the disease persists at a positive level in the population. It also implies that vertical transmission has an impact on maintaining infectious diseases when horizontal transmission cannot sustain the disease on its own. The proof of global stability is based on the graph-theoretic approach and answer the open problem left in [1]. Finally, numerical simulations are performed to illustrate the theoretical results. © 2023 American Institute of Mathematical Sciences. All rights reserved.
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We introduce the maximum n-times coverage problem that selects k overlays to maximize the summed coverage of weighted elements, where each element must be covered at least n times. We also define the min-cost n-times coverage problem where the objective is to select the minimum set of overlays such that the sum of the weights of elements that are covered at least n times is at least τ. Maximum n-times coverage is a generalization of the multi-set multi-cover problem, is NP-complete, and is not submodular. We introduce two new practical solutions for n-times coverage based on integer linear programming and sequential greedy optimization. We show that maximum n-times coverage is a natural way to frame peptide vaccine design, and find that it produces a pan-strain COVID-19 vaccine design that is superior to 29 other published designs in predicted population coverage and the expected number of peptides displayed by each individual's HLA molecules. © 2022 ICLR 2022 - 10th International Conference on Learning Representationss. All rights reserved.
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Semantic relation prediction aims to mine the implicit relationships between objects in heterogeneous graphs, which consist of different types of objects and different types of links. In real-world scenarios, new semantic relations constantly emerge and they typically appear with only a few labeled data. Since a variety of semantic relations exist in multiple heterogeneous graphs, the transferable knowledge can be mined from some existing semantic relations to help predict the new semantic relations with few labeled data. This inspires a novel problem of few-shot semantic relation prediction across heterogeneous graphs. However, the existing methods cannot solve this problem because they not only require a large number of labeled samples as input, but also focus on a single graph with a fixed heterogeneity. Targeting this novel and challenging problem, in this paper, we propose a Meta-learning based Graph neural network for Semantic relation prediction, named MetaGS. Firstly, MetaGS decomposes the graph structure between objects into multiple normalized subgraphs, then adopts a two-view graph neural network to capture local heterogeneous information and global structure information of these subgraphs. Secondly, MetaGS aggregates the information of these subgraphs with a hyper-prototypical network, which can learn from existing semantic relations and adapt to new semantic relations. Thirdly, using the well-initialized two-view graph neural network and hyper-prototypical network, MetaGS can effectively learn new semantic relations from different graphs while overcoming the limitation of few labeled data. Extensive experiments on three real-world datasets have demonstrated the superior performance of MetaGS over the state-of-the-art methods. IEEE
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At present, severe acute respiratory syndrome coronavirus-2(SARS-CoV-2)infection is still rampant worldwide.As of September 10, 2021, there were about 222 million confirmed cases of corona virus disease 2019(COVID-19)and more than 4.6 million deaths worldwide.With the development of COVID-19 vaccines and the gradual vaccination worldwide, the increasing number of cases in children and unvaccinated young people has drawn attention.According to World Health Organization surveillance data, the proportion of COVID-19 infection cases in children gradually increased, and the proportion of cases in the age groups of under 5 years and 5-14 years increased from 1.0% and 2.5% in January 2020 to 2.0% and 8.7% in July 2021, respectively.At present, billions of adults have been vaccinated with various COVID-19 vaccines worldwide, and their protective effects including reducing infection and transmission, reducing severe disease and hospitalization, and reducing death, as well as high safety have been confirmed.Canada, the United States, Europe and other countries have approved the emergency COVID-19 vaccination in children and adolescents aged 12 to 17 years, and China has also approved the phased vaccination of COVID-19 vaccination in children and adolescents aged 3 to 17 years. For smooth advancement and implementation of COVID-19 vaccination in children, academic institutions, including National Clinical Research Center for Respiratory Diseases, National Center for Children's Health, and The Society of Pediatrics, Chinese Medical Association organized relevant experts to reach this consensus on COVID-19 vaccination in children.Copyright © 2021 by the Chinese Medical Association.
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Severe acute respiratory syndrome coronavirus-2(SARS-CoV-2)infection is still worldwide.As a vulnerable group, severe and dead pediatric cases are also reported.Under this severe epidemic situation, children should be well protected.With the widespread vaccination of SARS-CoV-2 vaccine in adults, the infection rate have decreased.Therefore, SARS-CoV-2 vaccine inoculation for children groups step by step is of great significance to the protection of children and the prevention and control of corona virus disease 2019(COVID-19) as a whole.But the safety of children vaccinated with SARS-CoV-2 vaccine is a main concern of parents.Therefore, in order to ensure the safety of vaccination and the implementation of vaccination work, National Clinical Research Center for Respiratory Diseases, National Center for Children's Health and the Society of Pediatrics, Chinese Medical Association organized experts to interpret the main issue of parents about SARS-CoV-2 vaccine for children, in order to answer the doubts of parents.Copyright © 2021 by the Chinese Medical Association.
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The changes of indoor environment and occupant behavior (OB) are two main causes for the gap between predicted and actual airborne infection risk. To improve the accuracy of COVID-19 airborne infection risk assessment, the environment (CO2 concentration) and OBs (occupant area per person (OA) and activity level (AL)) in three typical classrooms of a primary school in Tianjin, China was selected to conduct the on-site measurement. Based on the measured data, a modified Wells-Riley model was proposed to predict the infection risk, and a risk-controlled ventilation strategy was developed to calculate the ventilation demand. Results indicated that classrooms in the breaking time (B-T) showed a lower indoor CO2 concentration (C in), larger OA, and higher AL than in the teaching time (T-T). The variation tendency of the calculated infection risk increment in T-T was consistent with C in while in B-T was significantly affected by OA and AL, and the maximum fluctuation extent in B-T was two times of that in T-T. Moreover, to avoid the risk spreading in classrooms, a feasible solution of dynamic ventilation control based on the real-time infection risk was proposed, thus facilitating to provide a healthy and sustainable environment for students in classrooms. © 2023 Informa UK Limited, trading as Taylor & Francis Group.
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Understanding the transmission of volatility across markets is essential for managing risk and financial stability, especially under crisis periods during which an extreme event occurring in one market is easily transmitted to another market. To gain such an understanding and enrich the related literature, we examine in this article the system of volatility spillovers across various equity markets and asset classes using a quantile-based approach, allowing us to capture spillovers under normal and high volatility states. The sample period is 16 March 2011–10 November 2020 and the employed dataset comprises 12 implied volatility indices representing a forward-looking measure of uncertainty of global equities, strategic commodities and the US Treasury bond market. The results show that the identity of transmitters and receivers of volatility shocks differ between normal and high volatility states. The US stock market is at the centre of volatility spillovers in the normal volatility state. European and Chinese stock markets and strategic commodities (e.g. crude oil and gold) become major volatility transmitters in the high volatility state, after acting as volatility receivers during normal periods. Furthermore, we study the drivers of implied volatility spillovers using regression models and find that US Default spread contributes to the total volatility spillover index in both volatility states, whereas TED spread plays a significant role in the normal volatility state. As for the role of short rate and risk aversion, it is significant in the high volatility state. These findings matter to the decision-making process of risk managers and policymakers. © 2022 John Wiley & Sons Ltd.
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Objective To effectively express the receptor binding domain (RBD) of SARS-CoV-2 spike protein in Pichia pastoris and to evaluate its immunogenicity. Methods The gene encoding the RBD protein was synthesized and cloned into the pPICZalphaA plasmid. After linearization, the plasmid was transferred and integrated into the genome of Pichia pastoris. The expressed RBD protein in culture supernatant was analyzed by Western blot and Biolayer interferometry. After screening, a single clone expressing the RBD protein was selected. The high-level expression of RBD protein was achieved by optimizing the fermentation process, including the salt concentration adjusting of the medium and induction condition optimization (pH, temperature and duration) . The immunogenicity of the expressed RBD protein was evaluated in a mouse model. Results A single clone with a high expression level of RBD protein was obtained and named RBD-X33. The expression level of RBD protein in the fermentation supernatant reached up to 240 mg / L after optimization of the induction condition (HBSM medium, pH = 6. 5 +/- 0. 3, 22 and 120 h) . In the mouse experiment, the recombinant RBD protein was formulated with Alum + CpG dual adjuvant and injected into mice. The binding IgG antibody levels were up to 2. 7 x 106 tested by ELISA and the neutralizing antibody levels were up to 726. 8 tested by live virus neutralizing antibody assay (prototype) . Conclusions The RBD protein could be efficiently expressed in Pichia pastoris and induce stronger immune response in animals. This study suggested that the recombinant SARS-CoV-2 RBD protein expressed in Pichia pastoris could serve as a candidate antigen in the development of SARS-CoV-2 vaccine.Copyright © 2022 Society of Microbiology and Immunology. All rights reserved.
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- Alzheimer's disease (AD) is an irreversible degenerative illness of the central nervous system with characteristic histological alterations, known as amyloid plaques and plaques and tangles in the brain induces neurotoxicity and synaptic dysfunction, ev
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Since the pandemic broke out in 2020, China has widely presented the covid crisis in its mass media and actively constructed collective identity thereof to mobilize medical workers, unify political stances, boost domestic solidarity, and promote international support. This paper combines the Discourse-Historical Approach and a multimodal perspective to investigate how the Chinese state-run news agency People's Daily discursively achieves these purposes on TikTok. A combination of qualitative and quantitative methods is used to present the high-frequency topoi of justifying the crisis and referential and predicational strategies of shaping collective identity within, which can fall into four dimensions: positive Self, negative Self, negative Others, and positive Others. The linguistic resources can be intensified/mitigated by visual-aural ensembles, which can draw the audience's attention and arouse their emotional attachments. This study also summarizes the embedded values in the discourses and situates them in socio-political contexts. © John Benjamins Publishing Company
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The total energy recovery ventilator for outdoor air handing plays an important role in reducing energy consumption of the ventilation system. At the same time, the cross infection between fresh air and return air is a direct threat to the safety of energy recovery components with the influence of COVID-19. Therefore, how to improve the total exchange effectiveness and net outdoor air flow ratio in supply air of the heat recovery system has become an urgent problem to be solved. In this study, the composite membrane was prepared by non-woven fabric, siloxaneamide and lithium chloride solution, which was used as the membrane for the heat and mass transfer between fresh air and return air. The variation of the selective permeability of the composite membrane was studied experimentally. The experimental results show that the highest permeance of the composite membrane for the water vapor permeability can reach until 32.5×10-8kg/m2wswPa. The net outdoor air flow ratio in supply air is 94% when the air volume is 550m3/h. The heat exchange efficiency of the heat recovery device is 63.2% under the conditions of the dry and wet bulb temperatures of return air and outdoor air are 21.2°C/12.9°C and 2.3°C/1.2°C, respectively. © The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/)