Optimization-driven distribution of relief materials in emergency disasters.

The distribution of relief materials is an important part of post-disaster emergency rescue. To meet the needs of the relief materials in the affected areas after a sudden disaster and ensure its smooth progress, an optimized dispatch model for multiple periods and multiple modes of transportation supported by the Internet of Things is established according to the characteristics of relief materials. Through the urgent production of relief materials, market procurement, and the use of inventory collection, the needs of the disaster area are met and the goal of minimizing system response time and total cost is achieved. The model is solved using CPLX software, and numerical simulation and results are analyzed using the example of the COVID-19 in Wuhan City, and the dispatching strategies are given under different disruption scenarios. The results show that the scheduling optimization method can meet the material demand of the disaster area with shorter time and lower cost compared with other methods, and can better cope with the supply interruptions that occur in post-disaster rescue.

Job Satisfaction and Negative Coping Style Affect the Relationship between Transition Shock and Intent to Stay among Newly Graduated Nurses during the COVID-19 Pandemic

Aim. The study is aimed at exploring the relationship between newly graduated nurses' transition shock, negative coping, job satisfaction, and intent to stay during the time of COVID-19. Background. The shortage of nurses is a global dilemma aggravated by the COVID-19 pandemic. It has been a hot topic in recent years to help newly graduated nurses transition smoothly. Transition shock is one of the essential indicators to describe the transition state of newly graduated nurses, which has a far-reaching impact on the intention of newly graduated nurses to stay in their posts. However, few studies have studied the mechanism behind this relationship, which may affect the effectiveness of retention strategies. Methods. A descriptive cross-sectional study was conducted from July to August 2021 in 31 tertiary hospitals in Shanghai, China. Participants comprised a convenience sample of 759 newly graduated nurses for surveys. Structural equation models were used to examine the study's hypothetical model. Results. The results showed that transition shock had a significant direct effect on job satisfaction (b = −0.412, p<0.001) and intent to stay (b = −0.145, p<0.001). Job satisfaction had a significant direct effect on intent to stay (b = 0.702, p<0.001). The indirect effect of transition shock on intent to stay through job satisfaction was statistically significant (b = −0.289), the 95% C.I. was (−0.493, −0.357), and the proportion of mediating effect to total effect was 66.59%. Moreover, the moderated mediation analysis showed that the interaction effect of transition shock and negative coping style on job satisfaction was significant (b = −0.082, p<0.001). Conclusion. This study revealed the impact of transition shock on intent to stay of newly graduated nurses during the time of COVID-19, and found that job satisfaction played a mediating role and negative coping played a moderating role. These findings are of great significance for nursing managers to take measures to improve the intention of newly graduated nurses to stay. Implication for Nursing Management. The level of transition shock is an important indicator reflecting the transition state of newly graduated nurses, and can further predict the job satisfaction and intention of newly graduated nurses to stay. Therefore, nursing managers should pay attention to taking corresponding measures to reduce the level of transition shock of newly graduated nurses.

Nurse-led virtual interventions in managing chronic diseases: a protocol for a systematic review of randomised controlled trials.

INTRODUCTION: Technological advances are changing nursing practice; however, nurse-led virtual care for chronic disease management has not yet been adequately explored and described. This study will review and analyse the effects of nurse-led virtual services and describe the virtual intervention characteristics relevant to the scope of nursing practice in chronic disease management. METHODS AND ANALYSIS: This study will systematically review randomised controlled trials evaluating the effects of nurse-led virtual care interventions on patients with chronic conditions. Databases including PubMed, Embase, Web of Science, CINAHL, Chinese National Knowledge Infrastructure, Wanfang (Chinese) and VIP Chinese Science and Technology Periodicals will be searched. All studies will be screened and selected using the criteria described in 'population, intervention, comparison, outcome and study design' format. Relevant studies will be searched using the reference lists of eligible studies and review articles. The risk of bias will be assessed using the Joanna Briggs Institute Quality Appraisal Form. Two reviewers will independently extract data from all the included studies using a standardised data extraction form on the Covidence platform. RevMan V.5.3 software will be used to perform the meta-analysis. Data synthesis will be conducted with descriptive synthesis by summarising and tabulating the data and presenting them according to the research questions. ETHICS AND DISSEMINATION: Formal ethical approval is not required as the data used in this systematic review are abstracted from the pre-existing literature. The results of this study will be disseminated through peer-reviewed journals and conference presentations. PROSPERO REGISTRATION NUMBER: CRD42022361260.

Comprehensive structural analysis reveals broad-spectrum neutralizing antibodies against SARS-CoV-2 Omicron variants.

The pandemic of COVID-19 caused by SARS-CoV-2 continues to spread around the world. Mutant strains of SARS-CoV-2 are constantly emerging. At present, Omicron variants have become mainstream. In this work, we carried out a systematic and comprehensive analysis of the reported spike protein antibodies, counting the epitopes and genotypes of these antibodies. We further comprehensively analyzed the impact of Omicron mutations on antibody epitopes and classified these antibodies according to their binding patterns. We found that the epitopes of the H-RBD class antibodies were significantly less affected by Omicron mutations than other classes. Binding and virus neutralization experiments showed that such antibodies could effectively inhibit the immune escape of Omicron. Cryo-EM results showed that this class of antibodies utilized a conserved mechanism to neutralize SARS-CoV-2. Our results greatly help us deeply understand the impact of Omicron mutations. Meanwhile, it also provides guidance and insights for developing Omicron antibodies and vaccines.

Effect of Farmers' Awareness of Climate Change on Their Willingness to Adopt Low-Carbon Production: Based on the TAM-SOR Model.

The COVID-19 pandemic highlighted the intricate relationships between human health and the social-ecological system in an era of climate and global change. Widespread COVID-19 adversely affected farmers' employment, production practices, and livelihood resilience. At the same time, climate change is a key issue limiting agricultural production worldwide. Emissions of greenhouse gases, such as carbon dioxide, are a major factor leading to global climate change. Greenhouse gas emissions from agricultural production are receiving increasing attention. Therefore, it is particularly important to develop low-carbon agriculture. Based on data from 920 family farms in Jiangsu province and Shaanxi province, this study constructs a structural equation model and empirically tests the relationship between the variables using the bootstrap method. The results show that: (1) climate change awareness did not directly stimulate farmers' willingness to pursue low-carbon production; (2) climate change awareness has an impact on low-carbon production willingness through perceived ease of use and consequence awareness; and (3) anti-risk ability can effectively moderate the impact of climate change awareness on low-carbon production behavior in agriculture. The theoretical model framework proposed in this study provides a reference for research in the field of low-carbon agriculture and also provides some insights and suggestions for environmentalists and governments. In addition, policymakers should effectively raise the sense of responsibility of farmers to address climate change and promote low-carbon agricultural production to achieve healthy and sustainable agricultural development.

Dual-Gene-Controlled Rolling Circle Amplification Strategy for SARS-CoV-2 Analysis.

The development of sensitive, accurate, and conveniently operated methods for the simultaneous assay of two nucleic acids is promising while still challenging. In this work, by using two genes (the N gene and RdRp gene) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as examples, we have designed an ingenious dual-gene-controlled rolling circle amplification (RCA) strategy to propose an accurate and sensitive electrochemical method. Specifically, the coexistence of the two target genes can trigger the RCA reaction to generate a number of repeated G-quadruplex (G4)-forming sequences. These sequences then switch into G4/hemin complexes with redox activity after the incubation of hemin, which can catalyze the TMB/H2O2 substrates to produce significantly enhanced current responses. Experimental results reveal that the proposed method exhibits satisfying feasibility and analytical performance, enabling the sensitive detection of SARS-CoV-2 in the range of 0.1-5000 pM, with the detection limit of 57 fM. Meanwhile, because only the simultaneous existence of the two target genes can effectively trigger the downstream amplification reaction, this method can effectively avoid false-positives and ensure specificity as well as accuracy. Furthermore, our method can distinguish the COVID-19 samples from healthy people, and the outcomes show a satisfying agreement with the results of RT-PCR, manifesting that our label-free dual-gene-controlled RCA strategy exhibits great possibility in clinical application.

Rapid Development of an Integrated Network Infrastructure to Conduct Phase 3 COVID-19 Vaccine Trials.

Importance: The COVID-19 pandemic has caused millions of infections and deaths and resulted in unprecedented international public health social and economic crises. As SARS-CoV-2 spread across the globe and its impact became evident, the development of safe and effective vaccines became a priority. Outlining the processes used to establish and support the conduct of the phase 3 randomized clinical trials that led to the rapid emergency use authorization and approval of several COVID-19 vaccines is of major significance for current and future pandemic response efforts. Observations: To support the rapid development of vaccines for the US population and the rest of the world, the National Institute of Allergy and Infectious Diseases established the COVID-19 Prevention Network (CoVPN) to assist in the coordination and implementation of phase 3 efficacy trials for COVID-19 vaccine candidates and monoclonal antibodies. By bringing together multiple networks, CoVPN was able to draw on existing clinical and laboratory infrastructure, community partnerships, and research expertise to quickly pivot clinical trial sites to conduct COVID-19 vaccine trials as soon as the investigational products were ready for phase 3 testing. The mission of CoVPN was to operationalize phase 3 vaccine trials using harmonized protocols, laboratory assays, and a single data and safety monitoring board to oversee the various studies. These trials, while staggered in time of initiation, overlapped in time and course of conduct and ultimately led to the successful completion of multiple studies and US Food and Drug Administration-licensed or -authorized vaccines, the first of which was available to the public less than 1 year from the discovery of the virus. Conclusions and Relevance: This Special Communication describes the design, geographic distribution, and underlying principles of conduct of these efficacy trials and summarizes data from 136 382 prospectively followed-up participants, including more than 2500 with documented COVID-19. These successful efforts can be replicated for other important research initiatives and point to the importance of investments in clinical trial infrastructure integral to pandemic preparedness.

Evaluation of a high-sensitivity SARS-CoV-2 antigen test on the fully automated light-initiated chemiluminescent immunoassay platform.

OBJECTIVES: To describe a high-sensitivity SARS-CoV-2 antigen test that is based on the fully automated light-initiated chemiluminescent immunoassay (LiCA®), and to validate its analytical characteristics and clinical agreement on detecting SARS-CoV-2 infection against the reference molecular test. METHODS: Analytical performance was validated and detection limits were determined using different types of nucleocapsid protein samples. 798-pair anterior nasal swab specimens were collected from hospitalized patients and asymptomatic screening individuals. Agreement between LiCA® antigen and real-time reverse transcription polymerase chain reaction (rRT-PCR) was evaluated. RESULTS: Repeatability and within-lab precision were 1.6-2.3%. The C5∼C95 interval was -5.1-4.6% away from C50. Detection limits in average (SD) were 325 (±141) U/mL on the national reference panel, 0.07 (±0.04) TCID50/mL on active viral cultures, 0.27 (±0.09) pg/mL on recombinant nucleocapsid proteins and 1.07 (±1.01) TCID50/mL on inactivated viral suspensions, respectively. LiCA detected a median of 374-fold (IQR 137-643) lower levels of the viral antigen than comparative rapid tests. As reference to the rRT-PCR method, overall sensitivity and specificity were determined to be 97.5% (91.4-99.7%) and 99.9% (99.2-100%), respectively. Total agreement between both methods was 99.6% (98.7-99.9%) with Cohen's kappa 0.98 (0.96-1). A positive detection rate of 100% (95.4-100%) was obtained as Ct≤37.8. CONCLUSIONS: The LiCA® system provides an exceptionally high-sensitivity and fully automated platform for the detection of the SARS-CoV-2 antigen in nasal swabs. The assay may have high potential use for large-scale population screening and surveillance of COVID-19 as an alternative to the rRT-PCR test.

The effectiveness and associated factors of online psychotherapy on COVID-19 related distress: A systematic review and meta-analysis

Objective A quantitative synthesis of online psychotherapies' effectiveness in managing COVID-19 related distress is lacking. This study aimed to estimate online psychological interventions' effectiveness and associated factors on COVID-19 related psychological distress. Methods Multi-databases including PubMed, EBSCO, ProQuest, and Cochrane were searched repeatedly till the end of June 2022. Hand-picking was also utilized for relevant papers. Depression, anxiety, stress, and quality of sleep were evaluated as outcomes. The risk of bias was evaluated using the Cochrane tool. Data analyses were conducted through Review Manager (version 5.4.1). Results A total of 13 studies involving 1,897 participants were included for meta-analysis. Results showed that online psychotherapy significantly reduced the levels of depression [standard mean difference, SMD = −0.45, 95% CI (−0.69, −0.20)], anxiety [SMD = −0.67, 95% CI (−0.99, −0.36)], and stress [SMD = −0.73, 95% CI (−1.11, −0.34)], but not quality of sleep [SMD = −0.53, 95% CI (−1.23, 0.17)]. In addition, guided therapies were more effective than self-help ones on reducing levels of anxiety (χ2 = 5.58, p = 0.02, and I2 = 82.1%), and ≤ 2 weeks' daily interventions were more effective on treating depression than 2-month weekly interventions (χ2 = 7.97, p = 0.005, I2 = 87.5%). Conclusion Online psychological interventions effectively reduced COVID-19 related depression, anxiety, and stress levels, and the effectiveness was influenced by settings like guidance and duration and frequency. Systematic review registration https://inplasy.com/inplasy-2022-7-0081/, identifier: INPLASY202270081.

Epidemiological Trend of RSV Infection Before and During COVID-19 Pandemic: A Three-Year Consecutive Study in China.

Objective: This study aimed to explore the epidemiological trend and clinical characteristics of respiratory syncytial virus (RSV) infection among inpatient children with lower respiratory tract infection (LRTI) before and during the coronavirus disease 2019 (COVID-19) pandemic. Methods: A retrospective study of inpatients with LRTI was conducted at the Department of Pulmonology, The Children's Hospital, Zhejiang University School of Medicine (Hangzhou, China) from January 2019 to December 2021. All respiratory specimens were tested for common respiratory pathogens. The clinical data in children with RSV-induced LRTI in the past three years were collected and analyzed. Results: A total of 11,290 patients were enrolled, and RSV positive cases were 402 (7.6%), 288 (9.6%), 415 (13.8%) in 2019, 2020, 2021, respectively, with a significant statistical difference of the RSV positive rate among the three groups (p < 0.001). Most patients were under 2-year old, especially under 1-year old, and the median age of patients was 4 months, 5 months, 6 months in 2019, 2020, 2021, respectively, with a tendency to increase in age. In terms of the seasonal distribution, most patients of LRTI with RSV infection were admitted in winter, while in 2021 compared with in 2019, the cases significantly reduced in winter and increased in autumn. From 2019 to 2021, there was an increase in autumn trend year by year. Conclusion: RSV infection was still an important cause of hospitalization in children with LRTI after the outbreak of COVID-19, and its proportion increased gradually. LRTI caused by RSV is still more common in infants under 1-year old, but there is a trend of increasing in older children. What deserves the attention of pediatricians and Center for Disease Control is that the incidence of RSV infection continues to rise in autumn, and the difference in seasonal distribution is narrowed.

Epidemiological and clinical characteristics of vaccinated COVID-19 patients: A meta-analysis and systematic review.

OBJECTIVE: With the global epidemic of coronavirus disease 2019 (COVID-19), vaccination rates are increasing globally. This study evaluated the relevant clinical manifestations of vaccinated COVID-19 patients. METHODS: We searched carefully in 11 databases such as PubMed, Embase, Scopus, Cochrane Library, Web of Science, Ovid, China National Knowledge Infrastructure Database, Wan Fang Data, Sinomed, VIP Database, and Reading Showing Database up to 26 March 2022. To search for articles that have described the characteristics of vaccinated patients including epidemiological and clinical symptoms. Statistical analysis of the extracted data using STATA 14.0. RESULTS: A total of 58 articles and 263,708 laboratory-confirmed COVID-19 patients were included. Most of the patients in the vaccinated group had more asymptomatic infection and fewer severe illnesses. There were significant differences in ethnicity, and strain infected with COVID-19, and comorbidities (hyperlipidemia, diabetes, obesity, kidney disease, immunocompromised, cardiovascular disease, and tumor) and symptoms (fever, cough, gastrointestinal symptoms, neurological symptoms, and dysgeusia/anosmia) between vaccinated group and unvaccinated group. Oxygen support, use of steroid, days in hospital, hospital treatment, ICU treatment, death, and poor prognosis were also significantly different. CONCLUSION: Compared with the vaccinated group, patients in the unvaccinated group had a more severe clinical manifestations. Vaccines are also protective for infected people.

A study on the evolution of economic patterns and urban network system in Guangdong-Hong Kong-Macao greater bay area.

The COVID-19 pandemic has seriously affected China's macroeconomy, industrial transformation, and high-quality development. Research on economic patterns and urban network systems can provide a reference for healthy development of the regional economic system. The evolution of the economic pattern and urban network system of Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 2010 to 2020 is investigated using methods (e.g., the gravity center model, the gravitational force model, social network analysis, and geographic information system). (1) The gravity center of gross domestic product (GDP) of the GBA is located in Nansha district, Guangzhou, with a skewing direction northwest-east-northwest and a movement rate of "large-small-large." The center of import and export and the center of consumption show a "zigzagging migration" in which the center of investment shows an "irregular (random) migration". (2) The economic connection degree of cities in the GBA exhibits a high ascending velocity, and the whole area tends to be mature, with a significant effect of spatial proximity. With the steady increase in network density, there is significant polarization of network centrality in the region. The four major cohesive subgroups have been relatively stable and consistent with the degree of geographic proximity of the cities. The center-periphery structure is more significant, in which the core area is extended to the cities on the east coast of the Pearl River Estuary, thus forming the core cluster of "Hong Kong-Shenzhen-Guangzhou-Dongguan." In this study, the evolution of economic patterns and urban network systems in the GBA over the past decade is analyzed using multiple methods (i.e., gravity model, urban network system analysis, and geographic information system) based on urban socioeconomic data by starting from various spatial elements (e.g., "points, lines, and networks") to gain insights into and optimize research on regional economic development after the COVID-19 pandemic.

The effects of indoor plants and traffic noise on English reading comprehension of Chinese university students in home offices

Owing to the COVID-19 pandemic, working from home promotes the importance of indoor environment qualities. With the settings and functions of home offices, an experiment was carried out to determine the interaction effects between indoor plants and traffic noise levels (TNLs) on the performance and environmental evaluations of English reading comprehension tasks (ERCTs) and the performance of short-term breaks. A sample of 22 Chinese university students (12 males and 10 females) took part in the experiment. Two visual conditions (with and without plants) and five TNLs (i.e., 35, 45, 50, 55, and 60 dBA TNL) were included. Participants’ accuracy rates, eye movements, mental workload, and feelings about the environment were collected. The mental fatigue recovery (MFR), visual fatigue recovery (VFR), anxiety recovery (AR), and unfriendly recovery (UR) were measured for the analysis of a 5-min short-term break. The results demonstrate (1) plants have significant effects on ERCTs and short-term breaks, especially at 45 and 50 dBA TNL;(2) the effects of TNLs on ERCTs’ eye movements and work environment satisfaction differ by the presence of plants, e.g., the average pupil diameter (APD), lighting and layout satisfaction;(3) The effects of indoor plants on ERCT differ by the range of TNLs. In conclusion, indoor plants are beneficial to home workers engaged in ERCT when TNL does not exceed 50 dBA. The current data highlight the importance of audio-visual interaction in home offices and provide insights into the interaction mechanism between indoor plants and traffic noise.

Evaluating the influence of constant source profile presumption on PMF analysis of PM2.5 by comparing long- and short-term hourly observation-based modeling.

Hourly PM2.5 speciation data have been widely used as an input of positive matrix factorization (PMF) model to apportion PM2.5 components to specific source-related factors. However, the influence of constant source profile presumption during the observation period is less investigated. In the current work, hourly concentrations of PM2.5 water-soluble inorganic ions, bulk organic and elemental carbon, and elements were obtained at an urban site in Nanjing, China from 2017 to 2020. PMF analysis based on observation data during specific pollution (firework combustion, sandstorm, and winter haze) and emission-reduction (COVID-19 pandemic) periods was compared with that using the whole 4-year data set (PMFwhole). Due to the lack of data variability, event-based PMF solutions did not separate secondary sulfate and nitrate. But they showed better performance in simulating average concentrations and temporal variations of input species, particularly for primary source markers, than the PMFwhole solution. After removing event data, PMF modeling was conducted for individual months (PMFmonth) and the 4-year period (PMF4-year), respectively. PMFmonth solutions reflected varied source profiles and contributions and reproduced monthly variations of input species better than the PMF4-year solution, but failed to capture seasonal patterns of secondary salts. Additionally, four winter pollution days were selected for hour-by-hour PMF simulations, and three sample sizes (500, 1000, and 2000) were tested using a moving window method. The results showed that using short-term observation data performed better in reflecting immediate changes in primary sources, which will benefit future air quality control when primary PM emissions begin to increase.

Contamination assessment of Listeria monocytogenes in fresh pork in the post-epidemic era

[Background] The epidemic of novel coronavirus disease 2019 (COVID-19) at the end of 2019 brought challenges to food safety. 【Objective】To evaluate the contamination of Listeria monocytogenes in fresh pork sold in the post-epidemic era. [Methods] During the epidemic period from 2020 to 2021, fresh pork from different locations, different packaging methods and different seasons were selected to analyze the contamination rate and contamination level of Listeria monocytogenes, and the epidemiological characteristics of the isolated strains were analyzed. [Results] The contamination rate of Listeria monocytogenes in fresh pork was 15.28% (77/504), and the contamination rate in pork direct-sale stores and farmers' markets was higher than that in supermarkets. Among different packaging methods, the contamination rates of pre-packaging and simple packaging were higher than those of bulk samples, and there were significant differences in the contamination rates in different quarters, with the highest contamination rate in the third quarter, which was 27.78%. Quantitative results found that 40.26% exceeded 10 MPN/g (MPN: most probable number), and 3 samples had contamination levels over 100 MPN/g. The results of serotype analysis showed that 1/2a-3a (48.05%) and 1/2c-3c (44.16%) were the main serotypes. The results of drug resistance test showed that 19.50% of the isolates were multi-drug resistant, 2 (2.60%) were sensitive to all antibiotics, 68 (88.30%) were resistant to oxacillin, and 46 (59.70%) were resistant to oxacillin. Ampicillin-resistant, 45 strains (58.40%) were resistant to cefotaxime. 【Conclusion】In the post-epidemic era, there are different degrees of Listeria monocytogenes contamination in the marketed fresh pork in different locations, different packaging methods and different seasons. The contamination level of individual products is high, and the serum distribution and drug resistance characteristics are diverse. It is necessary to strengthen food safety supervision to reduce the occurrence of foodborne diseases.

Clinical Features and Outcomes of COVID-19 Patients with Acute Kidney Injury and Acute Kidney Injury on Chronic Kidney Disease.

COVID-19 emerged in Wuhan in December 2019 and soon became a worldwide pandemic. We collected and analyzed the data from 1077 patients with COVID-19 who were admitted to the west campus of Wuhan Union Hospital from January 16 to April 16, 2020. Sixty (5.6%) of the 1077 COVID-19 patients were diagnosed with acute kidney injury (AKI) during hospitalization, and 18 of them (30%) had AKI on chronic kidney disease (AKI/CKD). COVID-19 patients with AKI had a worse prognosis, with higher intensive care unit (ICU) admission (28.3%) and fatality (65%) rates than patients without AKI (3.4% and 10.7%, respectively). Among the COVID-19 patients, AKI was more likely to occur in male patients, the elderly, patients with more severe disease states and those with comorbidities (such as hypertension, diabetes, coronary heart disease (CHD), chronic obstructive pulmonary disease (COPD) and CKD). COVID-19 patients with AKI were more likely to develop respiratory failure, gastrointestinal bleeding, acute liver injury, acute myocardial injury, heart failure, acute respiratory distress syndrome (ARDS), cerebrovascular accident, and disseminated intravascular coagulation (DIC) than those without AKI. Compared with patients without AKI, COVID-19 patients with AKI had lower platelet counts, lymphocyte counts, albumin levels and serum calcium levels but had elevated leukocyte counts, neutrophil counts and serum potassium levels. Inflammatory indicators, such as C-reactive protein (CRP), interleukin-6 (IL-6), and procalcitonin (PCT), were significantly higher in patients with AKI than in those without AKI. COVID-19 patients with AKI also exhibited a longer prothrombin time (PT), a longer activated partial thromboplastin time (APTT), and a higher D-dimer level than those without AKI. Survival analysis revealed that COVID-19 patients with AKI had a reduced survival rate compared with those without AKI. Furthermore, COVID-19 patients with AKI/CKD had a lower survival rate than those with AKI or CKD only. Multiple logistic regression indicated that the predictors of AKI in COVID-19 patients included complications, such as respiratory failure and acute myocardial injury, and higher creatinine and PCT levels during hospitalization.

Structural and functional analysis of an inter-Spike bivalent neutralizing antibody against SARS-CoV-2 variants.

The different variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have attracted most public concern because they caused "wave and wave" COVID-19 pandemic. The initial step of viral infection is mediated by the SARS-CoV-2 Spike (S) protein, which mediates the receptor recognition and membrane fusion between virus and host cells. Neutralizing antibodies (nAbs) targeting the S protein of SARS-CoV-2 have become promising candidates for clinical intervention strategy, while multiple studies have shown that different variants have enhanced infectivity and antibody resistance. Here, we explore the structure and function of STS165, a broadly inter-Spike bivalent nAb against SARS-CoV-2 variants and even SARS-CoV, contributing to further understanding of the working mechanism of nAbs.

The Impact of Lockdown, Patient Classification, and the Large-Scale Case Screening on the Spread of the Coronavirus Disease 2019 (COVID-19) in Hubei.

The coronavirus disease (COVID-19) which emerged in Wuhan, China, in December 2019, is widely controlled now in China. However, the global epidemic is still severe. To study and comment on Hubei's approaches for responding to the disease, the paper considered some factors such as suspected cases (part of them are influenza patients or common pneumonia patients, etc.), quarantine, patient classification (three types), clinically diagnosed cases, and lockdown of Wuhan and Hubei. After that, the paper established an SELIHR model based on the surveillance data of Hubei published by the Hubei Health Commission from 10 January 2020 to 30 April 2020 and used the fminsearch optimization method to estimate the optimal parameters of the model. We obtained the basic reproduction number ℛ 0 = 3.1571 from 10 to 22 January. ℛ 0 was calculated as 2.0471 from 23 to 27 January. From 28 January to 30 April, ℛ 0 = 1.5014. Through analysis, it is not hard to find that the patients without classification during the period of confirmed cases will result in the cumulative number of cases in Hubei to increase. In addition, regarding the lockdown measures implemented by Hubei during the epidemic, our simulations also show that if the lockdown time of either Hubei or Wuhan is advanced, it will effectively curb the spread of the epidemic. If the lockdown measures are not taken, the total cumulative number of cases will increase substantially. From the results of the study, it can be concluded that the lockdown, patient classification, and the large-scale case screening are essential to slow the spread of COVID-19, which can provide references for other countries or regions.

Broadly neutralizing antibodies against Omicron-included SARS-CoV-2 variants induced by vaccination.

The SARS-CoV-2 Omicron variant shows substantial resistance to neutralization by infection- and vaccination-induced antibodies, highlighting the demands for research on the continuing discovery of broadly neutralizing antibodies (bnAbs). Here, we developed a panel of bnAbs against Omicron and other variants of concern (VOCs) elicited by vaccination of adenovirus-vectored COVID-19 vaccine (Ad5-nCoV). We also investigated the human longitudinal antibody responses following vaccination and demonstrated how the bnAbs evolved over time. A monoclonal antibody (mAb), named ZWD12, exhibited potent and broad neutralization against SARS-CoV-2 variants Alpha, Beta, Gamma, Kappa, Delta, and Omicron by blocking the spike protein binding to the angiotensin-converting enzyme 2 (ACE2) and provided complete protection in the challenged prophylactic and therapeutic K18-hACE2 transgenic mouse model. We defined the ZWD12 epitope by determining its structure in complex with the spike (S) protein via cryo-electron microscopy. This study affords the potential to develop broadly therapeutic mAb drugs and suggests that the RBD epitope bound by ZWD12 is a rational target for the design of a broad spectrum of vaccines.