•Male gender and comorbidity were the independent risk factors for death in COVID-19 patients.•Lymphopenia and high CRP were the independent risk factors for poor outcome in COVID-19.•The risk ...factors would facilitate early identification of high-risk COVID-19 patients.
A few studies have revealed the clinical characteristics of hospitalized patients with COVID-19. However, predictive factors for the outcomes remain unclear.
Attempted to determine the predictive factors for the poor outcomes of patients with COVID-19.
This is a single-center, retrospective study. Clinical, laboratory, and treatment data were collected and analyzed from 111 hospitalized patients with laboratory-confirmed COVID-19 in Union Hospital. The gathered data of discharged and deteriorated patients were compared.
Among these 111 patients, 93 patients were discharged and 18 patients were deteriorated. The lymphocyte count (0.56 G/L 0.47−0.63 vs 1.30 G/L 0.95−1.65) was lower in the deteriorated group than those in the discharged group. The numbers of pulmonary lobe involved (5.00 5.00–5.00 vs 4.00 2.00−5.00), serum C‐reactive protein (CRP, 79.52 mg/L 61.25−102.98 vs 7.93 mg/L 3.14−22.50), IL-6 (35.72 pg/mL 9.24−85.19 vs 5.09 pg/mL 3.16−9.72), and IL-10 (5.35 pg/mL 4.48−7.84 vs 3.97 pg/mL 3.34−4.79) concentrations in deteriorated patients were elevated compared with discharged patients. Multivariate logistic regression analysis showed that male gender (OR, 24.8 1.8−342.1), comorbidity (OR, 52.6 3.6−776.4), lymphopenia (OR, 17.3 1.1−261.8), and elevated CRP (OR, 96.5 4.6−2017.6) were the independent risk factors for the poor prognosis in COVID-19 patients.
This finding would facilitate the early identification of high-risk COVID-19 patients.
Since the novel coronavirus pandemic, people around the world have been touched in varying degrees, and this pandemic has raised a major global health concern. As there is no effective drug or ...vaccine, it is urgent to find therapeutic drugs that can serve to deal with the current epidemic situation in all countries and regions. We searched drugs and response measures for SARS-CoV-2 in the PubMed database, and then updated the potential targets and therapeutic drugs from the perspective of the viral replication cycle. The drug research studies of the viral replication cycle are predominantly focused on the process of the virus entering cells, proteases, and RdRp. The inhibitors of the virus entry to cells and RdRp, such as Arbidol, remdesivir, favipiravir, EIDD-2081, and ribavirin, are in clinical trials, while most of the protease inhibitors are mainly calculated by molecular docking technology, which needs in vivo and in vitro experiments to prove the effect for SARS-CoV-2. This review summarizes the drugs targeting the viral replication process and provides a basis and directions for future drug development and reuse on the protein level of COVID-19.
We present the complete first order relativistic quantum kinetic theory with spin for massive fermions derived from the Wigner function formalism in a concise form that shows explicitly how the 32 ...Wigner equations reduce in practice to 4 independent transport equations. We solve the modified on-shell conditions to obtain the general solution and present the corresponding transport equations in three different forms that are suitable for different purposes. We demonstrate how different spin effects arise from the kinetic theory by calculating the chiral separation effect with mass correction, the chiral anomaly from the axial current and the quantum magnetic moment density induced by vorticity and magnetic field. We also show how to generate the global polarization effect due to spin vorticity coupling. The formalism presented may serve as a practical theoretical framework to study different spin effects in relativistic fermion systems encountered in different areas such as heavy ion, astro-particle and condensed matter physics as well.
Deep neural networks (DNN) have achieved unprecedented success in numerous machine learning tasks in various domains. However, the existence of adversarial examples raises our concerns in adopting ...deep learning to safety-critical applications. As a result, we have witnessed increasing interests in studying attack and defense mechanisms for DNN models on different data types, such as images, graphs and text. Thus, it is necessary to provide a systematic and comprehensive overview of the main threats of attacks and the success of corresponding countermeasures. In this survey, we review the state of the art algorithms for generating adversarial examples and the countermeasures against adversarial examples, for three most popular data types, including images, graphs and text.
Crystalline and porous covalent organic frameworks (COFs) and metal‐organic frameworks (MOFs) materials have attracted enormous attention in the field of photocatalytic H2 evolution due to their ...long‐range order structures, large surface areas, outstanding visible light absorbance, and tunable band gaps. In this work, we successfully integrated two‐dimensional (2D) COF with stable MOF. By covalently anchoring NH2‐UiO‐66 onto the surface of TpPa‐1‐COF, a new type of MOF/COF hybrid materials with high surface area, porous framework, and high crystallinity was synthesized. The resulting hierarchical porous hybrid materials show efficient photocatalytic H2 evolution under visible light irradiation. Especially, NH2‐UiO‐66/TpPa‐1‐COF (4:6) exhibits the maximum photocatalytic H2 evolution rate of 23.41 mmol g−1 h−1 (with the TOF of 402.36 h−1), which is approximately 20 times higher than that of the parent TpPa‐1‐COF and the best performance photocatalyst for H2 evolution among various MOF‐ and COF‐based photocatalysts.
Effective separation: A novel MOF/COF hybrid material assembled by covalent connecting two components, exhibits effective visible‐light‐driven photocatalytic H2 evolution due to the ideal band matching and effectively promoting the separation of the photogenerated charges and holes.
Coronavirus disease-2019 (COVID-19), a viral respiratory illness caused by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), may predispose patients to thrombotic disease, both in the ...venous and arterial circulations, because of excessive inflammation, platelet activation, endothelial dysfunction, and stasis. In addition, many patients receiving antithrombotic therapy for thrombotic disease may develop COVID-19, which can have implications for choice, dosing, and laboratory monitoring of antithrombotic therapy. Moreover, during a time with much focus on COVID-19, it is critical to consider how to optimize the available technology to care for patients without COVID-19 who have thrombotic disease. Herein, the authors review the current understanding of the pathogenesis, epidemiology, management, and outcomes of patients with COVID-19 who develop venous or arterial thrombosis, of those with pre-existing thrombotic disease who develop COVID-19, or those who need prevention or care for their thrombotic disease during the COVID-19 pandemic.
In this paper, we deal with the problem of tracking control for a class of uncertain nonlinear systems in strictfeedback form subject to completely unknown system nonlinearities, hard constraints on ...full states, and unknown time-varying bounded disturbances. Integral barrier Lyapunov functionals are constructed to handle the unknown affine control gains (g(·)) with state constraints simultaneously. This removes the need on the knowledge of control gains for control design and avoids the conservative step of transforming original state constraints into new bounds on tracking errors. Neural networks (NNs) are used to approximate the unknown continuous packaged functions. To enhance the robustness, adapting parameters are developed to compensate the unknown bounds on NNs approximations and external disturbances. Design parameters-dependent feasibility conditions are formulated as sufficient conditions for the existence of feasible design parameters to guarantee the state constraints, and an offline constrained optimization step is proposed to obtain the optimal design parameters prior to the implementation of the proposed control. It is proved that the proposed control can guarantee the semiglobal uniform ultimate boundedness of all signals in closed-loop system, all states are ensured to remain in the predefined constrained state space, and tracking error converges to an adjustable neighborhood of the origin by choosing appropriate design parameters. Simulations are performed to validate the proposed control.
Cases of thrombotic thrombocytopenia induced by coronavirus disease 2019 (COVID-19) vaccines have been reported recently. Herein, we describe the first case of another critical disorder, ...hemophagocytic lymphohistiocytosis (HLH), in a healthy individual after COVID-19 vaccination. A 43-year-old Chinese farmer developed malaise, vomiting, and persistent high fever (up to 39.7 degreesC) shortly after receiving the first dose of the inactivated SARS-CoV-2 vaccine. The initial evaluation showed pancytopenia (neutrophil count, 0.70 x 10.sup.9/L; hemoglobin, 113 g/L; platelet, 27 x 10.sup.9/L), elevated triglyceride (2.43 mmol/L), and decreased fibrinogen (1.41 g/L). Further tests showed high serum ferritin levels (8140.4 mug/L), low NK cell cytotoxicity (50.13%-60.83%), and positive tests for Epstein-Barr virus (EBV) DNA. Hemophagocytosis was observed in the bone marrow. Therefore, HLH was confirmed, and dexamethasone acetate (10 mg/day) was immediately prescribed without etoposide. Signs and abnormal laboratory results resolved gradually, and the patient was discharged. HLH is a life-threatening hyperinflammatory syndrome caused by aberrantly activated macrophages and cytotoxic T cells, which may rapidly progress to terminal multiple organ failure. In this case, HLH was induced by the COVID-19 vaccination immuno-stimulation on a chronic EBV infection background. This report indicates that it is crucial to exclude the presence of active EBV infection or other common viruses before COVID-19 vaccination. Keywords: Hemophagocytic lymphohistiocytosis, SARS-CoV-2 vaccine, Epstein-Barr virus, Coagulopathy, COVID-19
The separation of ethane from its analogous ethylene is of great importance in the petrochemical industry, but very challenging and energy intensive. Adsorptive separation using C2H6-selective porous ...materials can directly produce high-purity C2H4 in a single operation but suffers from poor selectivity. Here, we report an approach to boost the separation of C2H6 over C2H4, involving the control of pore structures in two isoreticular ultramicroporous metal–organic framework (MOF) materials with weakly polar pore surface for strengthened binding affinity toward C2H6 over C2H4. Under ambient conditions, the prototypical compound shows a very small uptake difference and selectivity for C2H6/C2H4, whereas its smaller-pore isoreticular analogue exhibits a quite large uptake ratio of 237% (60.0/25.3 cm3 cm–3), remarkably increasing the C2H6/C2H4 selectivity. Neutron powder diffraction studies clearly reveal that the latter material shows self-adaptive sorption behavior for C2H6, which enables it to continuously maintain close van der Waals contacts with C2H6 molecules in its optimized pore structure, thus preferentially binds C2H6 over C2H4. Gas sorption isotherms, crystallographic analyses, molecular modeling, selectivity calculation, and breakthrough experiment comprehensively demonstrate this unique MOF material as an efficient C2H6-selective adsorbent for C2H4 purification.
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