A Strategy Formulation Framework for Efficient Screening during the Early Stage of a Pandemic.

For viruses that can be transmitted by contacts of people, efficiently screening infected individuals is beneficial for controlling outbreaks rapidly and avoiding widespread diffusion, especially during the early stage of a pandemic. The process of virus transmission can be described as virus diffusion in complex networks such as trajectory networks. We propose a strategy formulation framework (SFF) for generating various screening strategies to identify influential nodes in networks. We propose two types of metrics to measure the nodes' influence and three types of screening modes. Then, we can obtain six combinations, i.e., six strategies. To verify the efficiencies of the strategies, we build a scenario model based on the multi-agent modelling. In this model, people can move according to their self-decisions, and a virtual trajectory network is generated by their contacts. We found that (1) screening people will have a better performance based on their contact paths if there is no confirmed case yet, and (2) if the first confirmed case has been discovered, it is better to screen people sequentially by their influences. The proposed SFF and strategies can provide support for decision makers, and the proposed scenario model can be applied to simulate and forecast the virus-diffusion process.

Coarse particulate matter air quality in East Asia: implications for fine particulate nitrate

Air quality network data in China and South Korea show very high year-round mass concentrations of coarse particulate matter (PM), as inferred by the difference between PM10 and PM2.5. Coarse PM concentrations in 2015 averaged 52 µg m-3 in the North China Plain (NCP) and 23 µg m-3 in the Seoul Metropolitan Area (SMA), contributing nearly half of PM10. Strong daily correlations between coarse PM and carbon monoxide imply a dominant source from anthropogenic fugitive dust. Coarse PM concentrations in the NCP and the SMA decreased by 21 % from 2015 to 2019 and further dropped abruptly in 2020 due to COVID-19 reductions in construction and vehicle traffic. Anthropogenic coarse PM is generally not included in air quality models but scavenges nitric acid to suppress the formation of fine particulate nitrate, a major contributor to PM2.5 pollution. GEOS-Chem model simulation of surface and aircraft observations from the Korea–United States Air Quality (KORUS-AQ) campaign over the SMA in May–June 2016 shows that consideration of anthropogenic coarse PM largely resolves the previous model overestimate of fine particulate nitrate. The effect is smaller in the NCP which has a larger excess of ammonia. Model sensitivity simulations for 2015–2019 show that decreasing anthropogenic coarse PM directly increases PM2.5 nitrate in summer, offsetting 80 % the effect of nitrogen oxide and ammonia emission controls, while in winter the presence of coarse PM increases the sensitivity of PM2.5 nitrate to ammonia and sulfur dioxide emissions. Decreasing coarse PM helps to explain the lack of decrease in wintertime PM2.5 nitrate observed in the NCP and the SMA over the 2015–2021 period despite decreases in nitrogen oxide and ammonia emissions. Continuing decrease of fugitive dust pollution means that more stringent nitrogen oxide and ammonia emission controls will be required to successfully decrease PM2.5 nitrate.

Current understanding of the airborne transmission of important viral animal pathogens in spreading disease

Current research on airborne transmission of African swine fever virus (ASFV), porcine epidemic diarrhoea virus (PEDV), avian influenza (AIV), porcine reproductive and respiratory syndrome virus (PRRSV), and foot and mouth disease virus (FMDV) was reviewed to evaluate commonalities, knowledge gaps, and methodologies of studying airborne transmission of animal diseases. The reviewed studies were categorised as short-range transmission (within a single facility) and long-range transmission (beyond a single site). Short-range airborne transmission was demonstrated for at least one strain of the above-mentioned pathogens in experimental settings. Most studies reported in the literature concern FMDV, with limited information for ASFV and PEDV, particularly for short-range airborne transmission. Air sampling upwind, downwind, and within infected facilities has been commonly used to demonstrate long-range airborne transmission. The amount of evidence from air sampling for each of the reviewed viruses varies from no evidence on ASFV to evidence from multiple settings for AIV. Computer modelling has been used to study past outbreaks of infectious diseases to assess the contribution of airborne transmission with a multitude of computer models reported in the literature for simulating long-range airborne transmission of FMDV based on past outbreaks. This has resulted in predictive tools for assessing future risk of airborne transmission. Some important computer models are based on epidemiology analysis, weather analysis, and air dispersion. Few models are reported for ASFV, PEDV, and PRRSV. Studies in the literature indicate that airborne transmission is generally affected by virus strain, aerosol type, shedding duration and concentration, environmental conditions, and infectious dose.

Novel Virtual Vision Screening Program: Give Kids Sight Day 2020.

PURPOSE: To determine whether a low-technology novel virtual vision screening protocol can reliably screen pediatric visual acuity. METHODS: Give Kids Sight Day (GKSD), an annual out-reach program, aims to provide free vision screening and ophthalmic care to underserved children in Philadelphia, Pennsylvania. Children were screened virtually through the low-technology protocol. Based on screening results, 152 children were provided in-person eye examinations. Data from in-person examinations were compared to data from virtual screenings for 151 children who were seen in-person. RESULTS: Of 475 children screened virtually, 152 children were seen in-person for examination, and 151 children were included in the analysis. Results from 151 children (mean age: 10.7 years, age range: 5 to 18 years, 43% female, 28% speaking a non-English language) were reviewed. There was a moderate correlation (R = .64, P < .0001; n = 100 children) between screening and in-person visual acuity without refractive correction and a strong correlation (R = 0.82, P < .0001; n = 18 children) between screening and in-person visual acuity with refractive correction. Of the 140 children who were seen in-person, 133 children were provided glasses prescriptions. Seventeen children required a referral to a pediatric ophthalmologist for evaluation of ophthalmic conditions, most commonly strabismus (5.3%) and amblyopia (4%). CONCLUSIONS: The GKSD virtual visual acuity testing demonstrated good correlation with in-person visual acuity testing, supporting the virtual screening approach as a useful tool for future applications in widespread community vision outreach programs. Further studies are needed to refine virtual ophthalmic screening to optimize its applications in bridging the gaps in ophthalmic care. [J Pediatr Ophthalmol Strabismus. 20XX;X(X):XX-XX.].

Abiotic Synthetic Antibody Inhibitor with Broad-Spectrum Neutralization and Antiviral Efficacy against Escaping SARS-CoV-2 Variants.

The rapid emergence and spread of vaccine/antibody-escaping variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has posed serious challenges to our efforts in combating corona virus disease 2019 (COVID-19) pandemic. A potent and broad-spectrum neutralizing reagent against these escaping mutants is extremely important for the development of strategies for the prevention and treatment of SARS-CoV-2 infection. We herein report an abiotic synthetic antibody inhibitor as a potential anti-SARS-CoV-2 therapeutic agent. The inhibitor, Aphe-NP14, was selected from a synthetic hydrogel polymer nanoparticle library created by incorporating monomers with functionalities complementary to key residues of the SARS-CoV-2 spike glycoprotein receptor binding domain (RBD) involved in human angiotensin-converting enzyme 2 (ACE2) binding. It has high capacity, fast adsorption kinetics, strong affinity, and broad specificity in biologically relevant conditions to both the wild type and the current variants of concern, including Beta, Delta, and Omicron spike RBD. The Aphe-NP14 uptake of spike RBD results in strong blockage of spike RBD-ACE2 interaction and thus potent neutralization efficacy against these escaping spike protein variant pseudotyped viruses. It also inhibits live SARS-CoV-2 virus recognition, entry, replication, and infection in vitro and in vivo. The Aphe-NP14 intranasal administration is found to be safe due to its low in vitro and in vivo toxicity. These results establish a potential application of abiotic synthetic antibody inhibitors in the prevention and treatment of the infection of emerging or possibly future SARS-CoV-2 variants.

Community Resilience and COVID-19: A Fuzzy-Set Qualitative Comparative Analysis of Resilience Attributes in 16 Countries.

The COVID-19 pandemic has caused massive disruptions to governments and societies across the world. While public healthcare systems have come under immense pressure, public trust in governments and institutions are also in decline. In this paper, we seek to assess the resilience of policy systems and processes in 16 countries during the COVID-19 pandemic through the use of fuzzy-set Qualitative Comparative Analysis (fsQCA). We focus specifically on robustness, preparedness, social capital, and institutional strength as key attributes of community resilience at city-level. Our analysis of the data reveals that COVID-19 resilience is dependent on a combination of factors, with a multi-factorial approach to policy design and governance necessary for effective pandemic and disaster recovery.

Anxiety, depression, and somatic symptom disorders in health care workers at high altitude during the rapid spread of the SARS-CoV-2 Omicron variant: A prospective cohort study.

Objective: The ongoing spread of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Omicron variant and hypoxia exposure to high altitude are the susceptible factors of people's psychological abnormalities, especially the health care workers (HCWs) in the front line of the epidemic. There is no dynamic observation data on the prevalence of mental health disorders among HCWs at high altitude. The study is to assess the prevalence of mental health outcomes and its influencing factors among HCWs at high altitude exposed to the SARS-CoV-2 Omicron variant. Methods: This prospective cohort study collected sociodemographic data and mental health measurements from 647 HCWs in 3 hospitals in Xining, Qinghai province from 13 April to 4 May 2022. After the mental health intervention for the above-mentioned people in the Chengdong district, we collected mental health indicators on days 7 and 14, respectively. We used the generalized linear model and the generalized estimation equation and for further analysis. Results: The baseline cross-sectional survey of 647 HCWs in the Chengdong and Chengbei districts of Xining, Qinghai province shows that the prevalence of depression, anxiety, and somatic disorders were 45.75, 46.52, and 52.55%, respectively. The multivariable model showed that chronic diseases and nucleic acid collection were associated with increased scores of GAD-7, PHQ-9, and PHQ-15. And the GAD-7 score of HCWs with elderly people at home increased by 0.92 points. Subsequent repeated measurements of the mental health of HCWs in Chengdong district in Xining, Qinghai province, showed that anxiety, depression, and somatic disorders were significantly relieved, and physical exercise showed a significant protective effect, while loans and nucleic acid collection showed an adverse effect after 2 weeks of intervention. Additionally, engaged in nucleic acid collection was the risk factor of anxiety and depression. Conclusion: In this survey of HCWs on frontline at high altitude during the rapid spread of the SARS-CoV-2 Omicron variant, participants reported experiencing mental health disorders, especially in those with chronic disease, loans, and those who worked with longer hours and engaged in nucleic acid collection in Xining, Qinghai province, China. Exercise may help to improve anxiety and physical disorders.

Clinical significance of serum IgM and IgG levels in COVID-19 patients in Hubei Province, China.

Background: There have been many studies about coronavirus disease 2019 (COVID-19), but the clinical significance of quantitative serum severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2)-specific IgM and IgG levels of COVID-19 patients have not been exhaustively analyzed. We aimed to investigate the time profiles of these IgM/IgG levels in COVID-19 patients and their correlations with clinical features. Methods: A multicenter clinical study was conducted from February 20 to March 5 2020. It involved 179 COVID-19 patients (108 males and 71 females) from five hospitals in Huangshi in Hubei Province, China. To detect SARS-CoV-2-specific IgM/IgG, quantitative antibody assays (two-step indirect immunoassays with direct chemiluminescence technology) based on the nucleocapsid protein (NP) and spike protein 1 (S1) were used. For normally distributed data, means were compared using the t-test, χ 2-test, or exact probability method. For categorical data, medians were compared using Mann-Whitney U test. Results: The median age was 57 (44-69) years (58 [38-69] for males and 57 [49-68] for females). The median duration of positive nucleic acid test was 22.32 (17.34-27.43) days. The mortality rate was relatively low (3/179, 1.68%). Serum SARS-CoV-2-specific IgG was detected around week 1 after illness onset, gradually increased until peaking in weeks 4 and 5, and then declined. Serum IgM peaked in weeks 2 and 3, then gradually declined and returned to its normal range by week 7 in all patients. Notably, children had milder respiratory symptoms with lower SARS-CoV-2-specific IgM/IgG levels. The duration of positive nucleic acid test in the chronic obstructive pulmonary disease (COPD) group was 30.36 (18.99-34.76) days, which was significantly longer than that in the non-COPD group (21.52 [16.75-26.51] days; P = 0.025). The peak serum SARS-CoV-2-specific IgG was significantly positively correlated with the duration of positive nucleic acid test. The incidence rate of severe and critical cases in the IgMhi group (using the median IgM level of 29.95 AU/mL as the cutoff for grouping) was about 38.0% (19/50), which was twice as much as that in the IgMlo group (18.4%; 9/49). The patients with positive chest imaging and lymphocytopenia (<1 × 109/L) had a higher SARS-CoV-2-specific IgM level. Conclusions: Quantitative SARS-CoV-2-specific IgM and IgG levels are helpful for the diagnosis, severity classification, and management of COVID-19 patients, and they should be monitored in each stage of this disease.

Mining the vaccination willingness of China using social media data.

OBJECTIVE: Vaccination is one of the most powerful and effective protective measures against Coronavirus disease 2019 (COVID-19). Currently, several blogs hold content on vaccination attitudes expressed on social media platforms, especially Sina Weibo, which is one of the largest social media platforms in China. Therefore, Weibo is a good data source for investigating public opinions about vaccination attitudes. In this paper, we aimed to effectively mine blogs to quantify the willingness of the public to get the COVID-19 vaccine. MATERIALS AND METHODS: First, data including 144,379 Chinese blogs from Weibo, were collected between March 24 and April 28, 2021. The data were cleaned and preprocessed to ensure the quality of the experimental data, thereby reducing it to an experimental dataset of 72,496 blogs. Second, we employed a new fusion sentiment analysis model to analyze the sentiments of each blog. Third, the public's willingness to get the COVID-19 vaccine was quantified using the organic fusion of sentiment distribution and information dissemination effect. RESULTS: (1) The intensity of bloggers' sentiment toward COVID-19 vaccines changed over time. (2) The extremum of positive and negative sentiment intensities occurred when hot topics related to vaccines appeared. (3) The study revealed that the public's willingness to get the COVID-19 vaccine and the actual vaccination doses shares a linear relationship. CONCLUSION: We proposed a method for quantifying the public's vaccination willingness from social media data. The effectiveness of the method was demonstrated by a significant consistency between the estimates of public vaccination willingness and actual COVID-19 vaccination doses.

X-linked Charcot-Marie-Tooth disease after SARS-CoV-2 vaccination mimicked stroke-like episodes: A case report.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccinations have been administered worldwide, with occasional reports of associated neurological complications. Specifically, the impact of vaccinations on individuals with X-linked Charcot-Marie-Tooth disease type 1 (CMTX1) is unclear. Patients with CMTX1 can have stroke-like episodes with posterior reversible encephalopathy syndrome on magnetic resonance imaging (MRI), although this is rare. CASE SUMMARY: A 39-year-old man was admitted with episodic aphasia and dysphagia for 2 d. He received SARS-CoV-2 vaccination 39 d before admission. Physical examination showed pes cavus and reduced tendon reflexes. Brain MRI showed bilateral, symmetrical, restricted diffusion with T2 hyperintensities in the cerebral hemispheres. Nerve conduction studies revealed peripheral nerve damage. He was diagnosed with Charcot-Marie-Tooth disease, and a hemizygous mutation in the GJB1 gene on the X chromosome, known to be pathogenic for CMTX1, was identified. Initially, we suspected transient ischemic attack or demyelinating leukoencephalopathy. We initiated treatment with antithrombotic therapy and immunotherapy. At 1.5 mo after discharge, brain MRI showed complete resolution of lesions, with no recurrence. CONCLUSION: SARS-CoV-2 vaccination could be a predisposing factor for CMTX1 and trigger a sudden presentation.

Is Nuclear Factor Erythroid 2-Related Factor 2 a Target for the Intervention of Cytokine Storms?

The term "cytokine storm" describes an acute pathophysiologic state of the immune system characterized by a burst of cytokine release, systemic inflammatory response, and multiple organ failure, which are crucial determinants of many disease outcomes. In light of the complexity of cytokine storms, specific strategies are needed to prevent and alleviate their occurrence and deterioration. Nuclear factor erythroid 2-related factor 2 (NRF2) is a CNC-basic region-leucine zipper protein that serves as a master transcription factor in maintaining cellular redox homeostasis by orchestrating the expression of many antioxidant and phase II detoxification enzymes. Given that inflammatory response is intertwined with oxidative stress, it is reasonable to assume that NRF2 activation limits inflammation and thus cytokine storms. As NRF2 can mitigate inflammation at many levels, it has emerged as a potential target to prevent and treat cytokine storms. In this review, we summarized the cytokine storms caused by different etiologies and the rationale of interventions, focusing mainly on NRF2 as a potential therapeutic target.

Mining the vaccination willingness of China using social media data

Objective Vaccination is one of the most powerful and effective protective measures against Coronavirus disease 2019 (COVID-19). Currently, several blogs hold content on vaccination attitudes expressed on social media platforms, especially Sina Weibo, which is one of the largest social media platforms in China. Therefore, Weibo is a good data source for investigating public opinions about vaccination attitudes. In this paper, we aimed to effectively mine blogs to quantify the willingness of the public to get the COVID-19 vaccine. Materials and Methods First, data including 144,379 Chinese blogs from Weibo, were collected between March 24 and April 28, 2021. The data were cleaned and preprocessed to ensure the quality of the experimental data, thereby reducing it to an experimental dataset of 72,496 blogs. Second, we employed a new fusion sentiment analysis model to analyze the sentiments of each blog. Third, the public’s willingness to get the COVID-19 vaccine was quantified using the organic fusion of sentiment distribution and information dissemination effect. Results (1) The intensity of bloggers’ sentiment toward COVID-19 vaccines changed over time. (2) The extremum of positive and negative sentiment intensities occurred when hot topics related to vaccines appeared. (3) The study revealed that the public’s willingness to get the COVID-19 vaccine and the actual vaccination doses shares a linear relationship. Conclusion We proposed a method for quantifying the public’s vaccination willingness from social media data. The effectiveness of the method was demonstrated by a significant consistency between the estimates of public vaccination willingness and actual COVID-19 vaccination doses.

Mental health problems among healthcare professionals following the workplace violence issue-mediating effect of risk perception.

Although there have been numerous studies on mental wellbeing impairment or other negative consequences of Workplace Violence (WPV) against healthcare professionals, however, the effects of WPV are not limited to those who experience WPV in person, but those who exposed to WPV information indirectly. In the aftermath of "death of Dr. Yang Wen," a cross-sectional study was conducted to explore the psychological status of healthcare professionals. A total of 965 healthcare professionals from 32 provinces in China participated in our research. The prevalence rates of Post-Traumatic Stress Disorder (PTSD) symptoms, depression, anxiety among healthcare professional in the current study were 25.60, 46.01, and 27.88%, respectively. Moreover, our research suggested that the awareness of WPV-incident had a significant association with PTSD symptoms. In addition, risk perception was shown to mediate the effect of WPV awareness on PTSD symptoms. Furthermore, the present research also found a U-shaped relationship between issue salience and PTSD symptoms, and the relationship between issue salience and anxiety, indicating that higher awareness of WPV issue was negatively related to mental health status (including PTSD and anxiety) but only to the points at which there were no additional effects of more issue salience. This study highlighted that more protective measures for healthcare professionals need to be implemented in response to potential WPV events. More importantly, risk perception was found to mediate the effect of WPV issue salience on PTSD symptoms, it is critical to reduce the mental health burden through intervening in risk perception.

Research progress of origin traceability technology for food and drug homologous products

The idea of 'food and drug homology' plays a very important role in Chinese history. Especially, in the COVID-19 epidemic situation, 'food and drug homology' products improved health as medicated diet, thus promoting traditional Chinese drugs industry becomingmoreinternational. However, the quality of food and drug homology products were uneven, intermingled quality products and fake ones happen occasionally. In recent years, traceability technology for food and drug homologous products has gradually become a research hotspot due to the complex and diverse means of adulteration of food and drug homologous products. The aim of the development of origin traceability technology is to protect the 'genuineness' and 'distinctiveness' of food and drug homologous products. At the same time, it protects the rights and interests of consumersand protects the authenticity of food and drug homologous products and the healthy development of the food and drug homologous industry. Based on the basic data of journals and master's and doctoral dissertations collected from CNKI, Web of Sciences and Pud Med till June 2021, this paper analyzed the development trend of traceability technology in the application of global food and drug homologous products. The source, classification, origin traceability technology and application progress in food and drug homologous products were summarized in order to provide a theoretical basis for future research on origin traceability technology for food and drug homologous products.

An empirical study of the effect of a flooding event caused by extreme rainfall on preventive behaviors against COVID-19

Since the outbreak of COVID-19, wearing masks, vaccinations, and maintaining a safe distance has become social behaviors advocated by the government and widely adopted by the public. At the same time, unpredictable natural disaster risks brought by extreme climate change compound difficulties during epidemics and cause systemic risks that influence the existing pattern of epidemic prevention. Therefore, it is necessary to explore the effect of natural disaster risk caused by climate change on the response to outbreaks in the context of the COVID-19 epidemic. This study will focus on individual-level epidemic prevention behaviors, taking as an example the significant risk of severe destructive flooding caused by heavy rains in Henan, China, on July 20, 2021, which claimed 398 lives, to explore the effect of floods on the preventive behaviors of residents in the hardest hit areas against COVID-19. Through the multi-stage stratified random sampling of the affected residents in Zhengzhou, Xinxiang, Hebi, Luoyang, Anyang, and other cities in Henan Province, 2,744 affected people were surveyed via questionnaires. Through the linear regression model and moderating effect analysis, the study found that after floods, the individual's flood risk perception and response behaviors significantly correlated with the individual's prevention behaviors against COVID-19. Specifically, both flood risk perception and response behaviors strengthened the individual's prevention behaviors. Furthermore, the study also found that community risk preparation behavior and social capital can moderate the above relationship to a certain extent. The research can guide risk communication under the compound risk scenario and prevent risky public behavior under the consistent presence of COVID-19 in the community.

Risk-Aware Travel Path Planning Algorithm Based on Reinforcement Learning during COVID-19

The outbreak of COVID-19 brought great inconvenience to people's daily travel. In order to provide people with a path planning scheme that takes into account both safety and travel distance, a risk aversion path planning model in urban traffic scenarios was established through reinforcement learning. We have designed a state and action space of agents in a 'point-to-point';way. Moreover, we have extracted the road network model and impedance matrix through SUMO simulation, and have designed a Restricted Reinforcement Learning-Artificial Potential Field (RRL-APF) algorithm, which can optimize the Q-table initialization operation before the agent learning and the action selection strategy during learning. The greedy coefficient is dynamically adjusted through the improved greedy strategy. Finally, according to different scenarios, our algorithm is verified by the road network model and epidemic historical data in the surrounding areas of Xinfadi, Beijing, China, and comparisons are made with common Q-Learning, the Sarsa algorithm and the artificial potential field-based reinforcement learning (RLAFP) algorithm. The results indicate that our algorithm improves convergence speed by 35% on average and the travel distance is reduced by 4.3% on average, while avoiding risk areas, compared with the other three algorithms.

Highly Prevalent SARS-CoV-2 Antigenemia in COVID-19 Patients

Background: Many issues, such as severity assessment and antibody responses, remain to be answered eagerly for evaluation and understanding of COVID-19. Immune lesion is one of key pathogenesis of the disease. It would be helpful to understand the disease if an investigation on antigenemia and association was conducted in the patients with SARS-CoV-2 infection. Methods: A total of 156 patients admitted to the First People's Hospital of Hefei or Anhui Provincial Hospital on January to February 2020 were involved in this study. SARS-CoV-2 nucleocapsid (NP) antigen, specific IgM/IgG antibodies, and RNA were detected in sequential sera from three COVID-19 patients, and additional 153 COVID-19 patients by means of NP-antigen capture enzyme-linked immunosorbent assay, colloidal gold quick diagnosis, and real-time RT-PCR, respectively. The clinical types of COVID-19 patients were classified into asymptomatic, mild, moderate, severe, and critical, following on the Chinese guideline of COVID-19 diagnosis and treatment. The demographic and clinical data of patients were obtained for comparable analysis. Results: NP antigen was detected in 5 of 20 sequential sera collected from three COVID-19 patients with typically clinical symptoms, and 60.13% (92/153) expanded samples collected within 17 days after illness onset. No SARS-CoV-2 RNA segment was detected in these sera. The NP positive proportion reached a peak (84.85%, 28/33) on 6 to 8 days after illness onset. Both NP concentration and positive proportion were increased with the increase of clinical severity of COVID-19. Compared to NP negative patients, NP positive patients had older age [years, medians (interquartile ranges (IQR)), 49 (6) vs. 31 (11)], lower positive proportion of NP specific IgM [27.17% (25/92) vs. 59.02% (36/61)], and IgG [21.74% (20/92) vs. 59.02% (36/61)] antibodies, and longer duration [days, medians (IQR), 24 (10) vs. 21 (13)] from illness to recovery. Conclusions: SARS-CoV-2 NP antigenemia occurred in COVID-19, and presented highly prevalent at early stage of the disease. The antigenemia was related to clinical severity of the disease, and may be responsible for the delay of detectable SARS-Cov-2 IgM.

Daily Emission Patterns of Coal-Fired Power Plants in China Based on Multisource Data Fusion.

Daily emission estimates are essential for tracking the dynamic changes in emission sources. In this work, we estimate daily emissions of coal-fired power plants in China during 2017-2020 by combining information from the unit-based China coal-fired Power plant Emissions Database (CPED) and real-time measurements from continuous emission monitoring systems (CEMS). We develop a step-by-step method to screen outliers and impute missing values for data from CEMS. Then, plant-level daily profiles of flue gas volume and emissions obtained from CEMS are coupled with annual emissions from CPED to derive daily emissions. Reasonable agreement is found between emission variations and available statistics (i.e., monthly power generation and daily coal consumption). Daily power emissions are in the range of 6267-12,994, 0.4-1.3, 6.5-12.0, and 2.5-6.8 Gg for CO2, PM2.5, NO x , and SO2, respectively, with high emissions in winter and summer caused by heating and cooling demand. Our estimates can capture sudden decreases (e.g., those associated with COVID-19 lockdowns and short-term emission controls) or increases (e.g., those related to a drought) in daily power emissions during typical socioeconomic events. We also find that weekly patterns from CEMS exhibit no obvious weekend effect compared to those in previous studies. The daily power emissions will help to improve chemical transport modeling and facilitate policy formulation.

A New Way to Trace SARS-CoV-2 Variants Through Weighted Network Analysis of Frequency Trajectories of Mutations.

Early detection of SARS-CoV-2 variants enables timely tracking of clinically important strains in order to inform the public health response. Current subtype-based variant surveillance depending on prior subtype assignment according to lag features and their continuous risk assessment may delay this process. We proposed a weighted network framework to model the frequency trajectories of mutations (FTMs) for SARS-CoV-2 variant tracing, without requiring prior subtype assignment. This framework modularizes the FTMs and conglomerates synchronous FTMs together to represent the variants. It also generates module clusters to unveil the epidemic stages and their contemporaneous variants. Eventually, the module-based variants are assessed by phylogenetic tree through sub-sampling to facilitate communication and control of the epidemic. This process was benchmarked using worldwide GISAID data, which not only demonstrated all the methodology features but also showed the module-based variant identification had highly specific and sensitive mapping with the global phylogenetic tree. When applying this process to regional data like India and South Africa for SARS-CoV-2 variant surveillance, the approach clearly elucidated the national dispersal history of the viral variants and their co-circulation pattern, and provided much earlier warning of Beta (B.1.351), Delta (B.1.617.2), and Omicron (B.1.1.529). In summary, our work showed that the weighted network modeling of FTMs enables us to rapidly and easily track down SARS-CoV-2 variants overcoming prior viral subtyping with lag features, accelerating the understanding and surveillance of COVID-19.

A Gradient pH-Sensitive Polymer-Based Antiviral Strategy via Viroporin-Induced Membrane Acidification.

Lipid-membrane-targeting strategies hold great promise to develop broad-spectrum antivirals. However, it remains a big challenge to identify novel membrane-based targets of viruses and virus-infected cells for development of precision targeted approaches. Here, it is discovered that viroporins, viral-encoded ion channels, which have been reported to mediate release of hydrogen ions, trigger membrane acidification of virus-infected cells. Through development of a fine-scale library of gradient pH-sensitive (GPS) polymeric nanoprobes, the cellular membrane pH transitions are measured from pH 6.8-7.1 (uninfection) to pH 6.5-6.8 (virus-infection). In response to the subtle pH alterations, the GPS polymer with sharp response at pH 6.8 (GPS6.8 ) selectively binds to virus-infected cell membranes or the viral envelope, and even completely disrupts the viral envelope. Accordingly, GPS6.8 treatment exerts suppressive effects on a wide variety of viruses including SARS-CoV-2 through triggering viral-envelope lysis rather than affecting immune pathway or viability of host cells. Murine viral-infection models exhibit that supplementation of GPS6.8 decreases viral titers and ameliorates inflammatory damage. Thus, the gradient pH-sensitive nanotechnology offers a promising strategy for accurate detection of biological pH environments and robust interference with viruses.