Study of fusion peptide release for the spike protein of SARS-CoV-2.

The spike protein of SARS-CoV-2 can recognize the ACE2 membrane protein on the host cell and plays a key role in the membrane fusion process between the virus envelope and the host cell membrane. However, to date, the mechanism for the spike protein recognizing host cells and initiating membrane fusion remains unknown. In this study, based on the general assumption that all three S1/S2 junctions of the spike protein are cleaved, structures with different forms of S1 subunit stripping and S2' site cleavage were constructed. Then, the minimum requirement for the release of the fusion peptide was studied by all-atom structure-based MD simulations. The results from simulations showed that stripping an S1 subunit from the A-, B- or C-chain of the spike protein and cleaving the specific S2' site on the B-chain (C-chain or A-chain) may result in the release of the fusion peptide, suggesting that the requirement for the release of FP may be more relaxed than previously expected.

The cysS gene (ncgl0127) of Corynebacterium glutamicum is required for sulfur assimilation and affects oxidative stress-responsive cysteine import.

The OsnR protein functions as a transcriptional repressor of genes involved in redox-dependent stress responses. Here, we studied Corynebacterium glutamicum ORF ncgl0127 (referred to as cysS in this study), one of the target genes of OsnR, to reveal its role in osnR-mediated stress responses. The ΔcysS strain was found to be a cysteine auxotroph, and the transcription levels of the sulfur assimilatory genes and cysR, the master regulatory gene for sulfur assimilation, were low in this strain. Complementation of the strain with cysR transformed the strain into a cysteine prototroph. Cells challenged with oxidants or cysteine showed transcriptional stimulation of the cysS gene and decreased transcription of the ncgl2463 gene, which encodes a cysteine/cystine importer. The transcription of the ncgl2463 gene was increased in the ΔcysS strain and further stimulated by cysteine. Unlike the wild-type strain, ΔcysS cells grown with an excess amount of cysteine showed an oxidant- and alkylating agent-resistant phenotype, suggesting deregulated cysteine import. Collectively, our data suggest that the cysS gene plays a positive role in sulfur assimilation and a negative role in cysteine import, in particular in cells under oxidative stress.

Clinical Value of Platelets and Coagulation Parameters in Predicting the Severity of Delta Variant SARS-CoV-2.

INTRODUCTION: The present study aimed to analyze the clinical features and laboratory markers of patients with Delta variant SARS-CoV-2 and explore the role of platelet in predicting the severity of Delta. METHODS: This retrospective, observational study was conducted on 863 patients laboratory-confirmed Delta variant SARS-CoV-2. These cases were sub-classified based on disease severity into mild (n = 304), moderate (n = 537), and severe (n = 22). A series of laboratory findings and clinical data were collected and analyzed during hospitalization. RESULTS: Of 863 hospitalized patients with Delta, the median age was 38 years (interquartile range, 30-51 years) and 471 (54.58%) were male. The most common clinical symptoms mainly included cough, fever, pharyngalgia, expectoration, dyspnea, fatigue, and headache, and the commonest comorbidities were hypertension and diabetes. Among the hematological variables, neutrophil count, red blood cell count, and hemoglobin, were found to be statistically significant with regard to subcategories based of disease severity (p < 0.05). Among coagulation parameters, there was a statistically significant difference in D-dimer, fibrinogen, international normalized ratio, and prothrombin time (p < 0.05). Statistically significant differences were observed in platelet markers including platelet count, large platelet count, and plateletcrit (p < 0.05). Additionally, there was strong correlation between platelet and other parameters with disease severity. Logistical regression analysis and ROC curves showed that D-dimer was a single best marker of disease severity (p = 0.005, p < 0.0001); however, platelet (p = 0.009, p = 0.002) and plateletcrit (p = 0.002, p = 0.001) could also predict severe disease. Platelet was identified as an independent risk factor for severe Delta. CONCLUSION: Low platelet may be a marker of disease severity in Delta variant SARS-CoV-2 and may contribute to determine the severity of patients infected with Delta.

An credible traceability system for cold chain logistics developed for China's agricultural products in the context of COVID-19

Cold chain logistics is important for reducing post-harvest losses of agricultural products and ensuring the safety of agricultural products. COVID-19 cases related to cold chains have occasionally occurred, prompting considerable and widespread attention to cold chain logistics. The establishment of an effective traceability system for agricultural products within cold chain logistics is vital for ensuring their safety during the COVID-19 pandemic and achieving accurate traceability and recall. A study was conducted to assess the developmental status of cold chain logistics for China's agriculture products and identify challenges associated with cold chain logistics in the context of COVID-19. The study highlighted the advantages of blockchain-based traceability of agricultural products within cold chain logistics. Accordingly, a blockchain-based system was constructed for ensuring effective traceability of agricultural products within cold chain logistics extending from the production to the sales areas (i.e., from the field to the table). First, the demand for a traceability system was analyzed in detail from the perspective of the government, enterprises, and consumers. Second, six layers of the system architecture, comprising perceptions, data, networks, and the core, application, and user layers were delineated. Next, a storage mechanism and the system flow were designed and analyzed, and the on-chain and off-chain storage mechanisms of the "Inter Planetary File System+ blockchain" were applied for data storage, thereby addressing the deficiency of the blockchain and improving the operation and query efficiency of the traceability system. Lastly, the main functions of three respective ports for the government, enterprises, and consumers were introduced. This system can effectively resolve various challenges, such as tracing the entire process of cold chain logistics for agricultural products and a lack of clarity regarding assigned responsibility. Thus, the traceability of the entire process of cold chain logistics for agricultural products can be achieved, thereby enhancing the effectiveness of oversight of agricultural production, which ensures the quality and safety of agricultural products and strengthens consumers' trust in food safety.

Epidemiology of hand, foot, and mouth disease and the genetic characteristics of Coxsackievirus A16 in Taiyuan, Shanxi, China from 2010 to 2021

Hand, foot, and mouth disease (HFMD) is a common childhood infectious disease caused by human enteroviruses (EV). This study aimed to describe the epidemiological features of HFMD and the genetic characteristics of Coxsackievirus A16 (CVA16) in Taiyuan, Shanxi, China, from 2010 to 2021. Descriptive epidemiological methods were used to analyze the time and population distribution of HFMD and the genetic characteristics of CVA16. Except being affected by the COVID-19 epidemic in 2020, HFMD epidemics were sporadic from January to March each year, and began to increase in April, with a major epidemic peak from May to August, which declined in September, followed by a secondary peak from October to December. The prevalence of EV infection was the highest in children aged one to five years (84.42%), whereas its incidence was very low in children under one year of age (5.48%). Enterovirus nucleic acid was detected by real-time reverse transcription polymerase chain reaction in 6641 clinical specimens collected from patients with HFMD from 2010 to 2021, and 4236 EV-positive specimens were detected, including 988 enterovirus A71 (EV-A71), 1488 CVA16, and 1760 other enteroviruses. CVA16 remains prevalent and has co-circulated with other EVs in Taiyuan from 2010 to 2021. A phylogenetic tree constructed based on the VP1 region showed that all CVA16 strains belonged to two different clades of the B1 genotype, B1a and B1b. They showed a nucleotide similarity of 86.5–100%, and an amino acid similarity of 96.9–100%. Overall, these findings add to the global genetic resources of CVA16, demonstrate the epidemiological characteristics of HFMD as well as the genetic features of CVA16 in Taiyuan City during 2010–2021, and provide supporting evidence for the prevention and control of HFMD.

Food Values, Food Purchasing, and Eating-Related Outcomes Among a Sample of Quebec Adults During the COVID-19 Pandemic.

Purpose: This investigation evaluated food values, food purchasing, and other food and eating-related outcomes during the COVID-19 pandemic in Quebec, Canada. The role of stress in eating outcomes was also examined.Methods: An online household survey was conducted among Quebec adults aged ≥18 years (n = 658). Changes in outcomes during, as compared to before, the pandemic were evaluated using descriptive statistics and thematic analysis of free text responses. Eating outcomes by daily stress level (low, some, high) were assessed using Cochran-Armitage test for trend.Results: Most respondents reported increased importance and purchasing of local food products (77% and 68%, respectively) and 60% reported increased grocery spending (mean ± standard deviation: 28% ± 23%). Respondents with a higher daily stress level had a higher frequency of reporting eating more than usual compared to before the pandemic (low stress 21%, some stress 34%, high stress 39%, p-trend <0.0001). Free text responses described more time spent at home as a reason for eating more than usual.Conclusions: To support healthy eating during and post-pandemic, dietitians should consider patients' mental/emotional well-being and time spent at home. Moreover, support of local food products may provide opportunities to promote healthy eating, sustainability, and post-pandemic resiliency of food systems.

Advances in Next-Generation Coronavirus Vaccines in Response to Future Virus Evolution.

Coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread to more than 230 countries and territories worldwide since its outbreak in late 2019. In less than three years, infection by SARS-CoV-2 has resulted in over 600 million cases of COVID-19 and over 6.4 million deaths. Vaccines have been developed with unimaginable speed, and 11 have already been approved by the World Health Organization and given Emergency Use Listing. The administration of several first-generation SARS-CoV-2 vaccines has successfully decelerated the spread of COVID-19 but not stopped it completely. In the ongoing fight against viruses, genetic mutations frequently occur in the viral genome, resulting in a decrease in vaccine-induced antibody neutralization and widespread breakthrough infection. Facing the evolution and uncertainty of SARS-CoV-2 in the future, and the possibility of the spillover of other coronaviruses to humans, the need for vaccines with a broad spectrum of antiviral variants against multiple coronaviruses is recognized. It is imperative to develop a universal coronavirus or pan-coronavirus vaccine or drug to combat the ongoing COVID-19 pandemic as well as to prevent the next coronavirus pandemic. In this review, in addition to summarizing the protective effect of approved vaccines, we systematically summarize current work on the development of vaccines aimed at suppressing multiple SARS-CoV-2 variants of concern as well as multiple coronaviruses.

A Generalized Multinomial Probabilistic Model for SARS-CoV-2 Infection Prediction and Public Health Intervention Assessment in an Indoor Environment (preprint)

SARS-CoV-2 Omicron has become the predominant variant globally. Current infection models are limited by the need for large datasets or calibration to specific contexts, making them difficult to cater for different settings. To ensure public health decision-makers can easily consider different public health interventions (PHIs) over a wide range of scenarios, we propose a generalized multinomial probabilistic model of airborne infection to systematically capture group characteristics, epidemiology, viral loads, social activities, environmental conditions, and PHIs, with assumptions made on social distancing and contact duration, and estimate infectivity over short time-span group gatherings. This study is related to our 2021 work published in Nature Scientific Reports that modelled airborne SARS-CoV-2 infection (Han, Lam, Li, et al., 2021). It is differentiated from former works on probabilistic infection modelling in terms of the following: (1) predicting new cases arising from more than one infectious in a gathering, (2) incorporating additional key infection factors, and (3) evaluating the effectiveness of multiple PHIs on SARS-CoV-2 infection simultaneously. Although our results reveal that limiting group size has an impact on infection, improving ventilation has a much greater positive health impact. Our model is versatile and can flexibly accommodate other scenarios by allowing new factors to be added, to support public health decision-making.

Inactivated vaccine injection and immunoglobulin G levels related to severe coronavirus disease 2019 (Delta) pneumonia in Xi'an, China: A single-centered, retrospective, observational study.

The World Health Organization declared a public health emergency of international concern in January 2020. The Delta variant became the main epidemic strain on 11 May 2021. Vaccines were proven highly effective in controlling hospitalization and deaths associated with severe acute respiratory syndrome coronavirus 2 infections. Real data on vaccine efficacy against B.1.617.2 infection in the Chinese population were currently limited. This study aimed to evaluate the protective effect of inactivated vaccine injection and immunoglobulin (Ig) G levels in coronavirus disease 2019 (COVID-19) severity. This retrospective study included patients with COVID-19 in Xi'an Chest Hospital from December 2021 to January 2022. The protective effect of inactivated vaccine injection and IgG levels on COVID-19 severity was analyzed using multiple logistic regressions. A total of 580 patients were included in the study, of whom 158 (27.24%) were mild, 412 (71.03%) were moderate, 5 (0.9%) were severe, and 5 (0.86%) were critical. Severe case (including severe and critical) rates were 1.72% (10/580). Compared with the unvaccinated group, the vac+IgG- group had a 0.21 (0.02-2.05)-fold risk of suffering from severe cases, and the vac+IgG+ group had a 0.05 (0-0.63)-fold risk of suffering from severe cases. Of the 10 severe cases, 8 were older than 60 years, 8 were men, 8 had underlying diseases, 6 were in the unvaccinated group, and 2 were in the vac+IgG- group. Vaccination and sufficient IgG antibody production can protect patients with COVID-19 from severe cases. Booster vaccine injection can produce a stronger immune response and protection.

Contact patterns of UK home delivery drivers and their use of protective measures during the COVID-19 pandemic: a cross-sectional study (preprint)

ABSTRACT Objectives To quantify contact patterns of UK home delivery drivers and identify protective measures adopted during the pandemic. Methods We conducted a cross-sectional online survey to measure the interactions of 170 UK delivery drivers during a working shift between 7 December 2020 and 31 March 2021. Results Delivery drivers had a mean number of 71.6 (95% Confidence Interval (CI) 61.0 to 84.1) customer contacts per shift and 15.0 (95%CI 11.19 to 19.20) depot contacts per shift. Maintaining physical distancing with customers was more common than at delivery depots. Prolonged contact (more than 5 minutes) with customers was reported by 5.4% of drivers on their last shift. We found 3.0% of drivers had tested positive for SARS-CoV-2 since the start of the pandemic and 16.8% of drivers had self-isolated due to a suspected or confirmed case of COVID-19. Additionally, 5.3% (95%CI 2.3% to 10.2%) of participants reported having worked whilst ill with COVID-19 symptoms, or with a member of their household having a suspected or confirmed case of COVID-19. Conclusion Delivery drivers had a large number of face-to-face customer and depot contacts per shift compared to other working adults during this time. However, transmission risk may be curtailed as contact with customers was of short duration. Most drivers were unable to maintain physical distance with customers and at depots at all times. Usage of protective items such as face masks and hand sanitizer was widespread.

Using generative adversarial networks for genome variant calling from low depth ONT sequencing data.

Genome variant calling is a challenging yet critical task for subsequent studies. Existing methods almost rely on high depth DNA sequencing data. Performance on low depth data drops a lot. Using public Oxford Nanopore (ONT) data of human being from the Genome in a Bottle (GIAB) Consortium, we trained a generative adversarial network for low depth variant calling. Our method, noted as LDV-Caller, can project high depth sequencing information from low depth data. It achieves 94.25% F1 score on low depth data, while the F1 score of the state-of-the-art method on two times higher depth data is 94.49%. By doing so, the price of genome-wide sequencing examination can reduce deeply. In addition, we validated the trained LDV-Caller model on 157 public Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) samples. The mean sequencing depth of these samples is 2982. The LDV-Caller yields 92.77% F1 score using only 22x sequencing depth, which demonstrates our method has potential to analyze different species with only low depth sequencing data.

Detecting Potentially Adaptive Mutations from the Parallel and Fixed Patterns in SARS-CoV-2 Evolution

Early identification of adaptive mutations could provide timely help for the control and prevention of the COVID-19 pandemic. The fast accumulation of SARS-CoV-2 sequencing data provides important support, while also raising a great challenge for the recognition of adaptive mutations. Here, we proposed a computational strategy to detect potentially adaptive mutations from their fixed and parallel patterns in the phylogenetic trajectory. We found that the biological meanings of fixed substitution and parallel mutation are highly complementary, and can reasonably be integrated as a fixed and parallel (paraFix) mutation, to identify potentially adaptive mutations. Tracking the dynamic evolution of SARS-CoV-2, 37 sites in spike protein were identified as having experienced paraFix mutations. Interestingly, 70% (26/37) of them have already been experimentally confirmed as adaptive mutations. Moreover, most of the mutations could be inferred as paraFix mutations one month earlier than when they became regionally dominant. Overall, we believe that the concept of paraFix mutations will help researchers to identify potentially adaptive mutations quickly and accurately, which will provide invaluable clues for disease control and prevention.

Modelling the impact of non-pharmaceutical interventions on workplace transmission of SARS-CoV-2 in the home-delivery sector (preprint)

Objective: We aimed to use mathematical models of SARS-COV-2 to assess the potential efficacy of non-pharmaceutical interventions on transmission in the parcel delivery and logistics sector. Methods: We developed a network-based model of workplace contacts based on data and consultations from companies in the parcel delivery and logistics sectors. We used these in stochastic simulations of disease transmission to predict the probability of workplace outbreaks in this settings. Individuals in the model have different viral load trajectories based on SARS-CoV-2 in-host dynamics, which couple to their infectiousness and test positive probability over time, in order to determine the impact of testing and isolation measures. Results: The baseline model (without any interventions) showed different workplace infection rates for staff in different job roles. Based on our assumptions of contact patterns in the parcel delivery work setting we found that when a delivery driver was the index case, on average they infect only 0.18 other employees , while for warehouse and office workers this went up to 0.93 and 2.58 respectively. In the large-item delivery setting this was predicted to be 0.83, 0.94, and 1.61 respectively. Nonetheless, the vast majority of simulations resulted in $0$ secondary cases among customers (even without contact-free delivery). Our results showed that a combination of social distancing, office staff working from home, and fixed driver pairings (all interventions carried out by the companies we consulted) reduce the risk of workplace outbreaks by 3-4 times. Conclusion: This work suggests that, without interventions, significant transmission could occur in these workplaces, but that these pose minimal risk to customers. We found that identifying and isolating regular close-contacts of infectious individuals (i.e. house-share, carpools, or delivery pairs) is an efficient measure for stopping workplace outbreaks. Regular testing can make these isolation measures even more effective but also increases the number of staff isolating at one time. It is therefore more efficient to combine these measures with social distancing and contact reduction interventions, as these reduce both transmission and the number of people needing to isolate.

Rapid, Highly Sensitive, and Label-Free Pathogen Assay System Using a Solid-Phase Self-Interference Recombinase Polymerase Amplification Chip and Hyperspectral Interferometry.

Recombinase polymerase amplification (RPA) is a useful pathogen identification method. Several label-free detection methods for RPA amplicons have been developed in recent years. However, these methods still lack sensitivity, specificity, efficiency, or simplicity. In this study, we propose a rapid, highly sensitive, and label-free pathogen assay system based on a solid-phase self-interference RPA chip (SiSA-chip) and hyperspectral interferometry. The SiSA-chips amplify and capture RPA amplicons on the chips, rather than irrelevant amplicons such as primer dimers, and the SiSA-chips are then analysed by hyperspectral interferometry. Optical length increases of SiSA-chips are used to demonstrate RPA detection results, with a limit of detection of 1.90 nm. This assay system can detect as few as six copies of the target 18S rRNA gene of Plasmodium falciparum within 20 min, with a good linear relationship between the detection results and the concentration of target genes (R2 = 0.9903). Single nucleotide polymorphism (SNP) genotyping of the dhfr gene of Plasmodium falciparum is also possible using the SiSA-chip, with as little as 1% of mutant gene distinguished from wild-type loci (m/wt). This system offers a high-efficiency (20 min), high-sensitivity (6 copies/reaction), high-specificity (1% m/wt), and low-cost (∼1/50 of fluorescence assays for RPA) diagnosis method for pathogen DNA identification. Therefore, this system is promising for fast identification of pathogens to help diagnose infectious diseases, including SNP genotyping.

Food cold chain management improvement: A conjoint analysis on COVID-19 and food cold chain systems.

Cold chains are effective in maintaining food quality and reducing food losses, especially for long-distance international food commerce. Several recent reports have demonstrated that frozen foods are serving as carriers of SARS-CoV-2 and transmitting the virus from one place to another without any human-to-human contact. This finding highlights significant difficulties facing efforts to control the spread of COVID-19 and reveal a transmission mechanism that may have substantially worsened the global pandemic. Traditional food cold chain management practices do not include specific procedures related to SARS-CoV-2-related environmental control and information warnings; therefore, such procedures are urgently needed to allow food to be safely transported without transmitting SARS-CoV-2. In this study, a conjoint analysis of COVID-19 and food cold chain systems was performed, and the results of this analysis were used to develop an improved food cold chain management system utilizing internet of things (IoT) and blockchain technology. First, 45 COVID-19-related food cold chain incidents in China, primarily involving frozen meat and frozen aquatic products, were summarized. Critical food cold chain control points related to COVID-19 were analyzed, including temperature and cold chain requirements. A conceptual system structure to improve food cold chain management, including information sensing, chain linking and credible tracing, was proposed. Finally, a prototype system, which consisted of cold chain environment monitoring equipment, a cold chain blockchain platform, and a food chain management system, was developed. The system includes: 1) a defining characteristic of the newly developed food cold chain system presented here is the use of IoT technology to enhance real-time environmental information sensing capacity; 2) a hybrid data storage mechanism consisting of off-chain and on-chain systems was applied to enhance data security, and smart contracts were used to establish warning levels for food cold chain incidents; and 3) a hypothetical food cold chain failure scenario demonstration in which information collection, intelligent decision making, and cold chain tracing were integrated and automatically generated for decision-making. By integrating existing technologies and approaches, our study provides a novel solution to improve traditional food cold chain management and thus meet the challenges associated with the COVID-19 pandemic. Although our system has been shown to be effective, subsequent studies are still required to develop precise risk evaluation models for SARs-CoV-2 in food cold chains and more precisely control the entire process. By ensuring food safety and reliable traceability, our system could also contribute to the formulation of appropriate mechanisms for international cooperation and minimize the effect of the COVID-19 pandemic on international food commerce.

Agility and sustainability: A qualitative evaluation of COVID-19 Non-pharmaceutical Interventions (NPIs) in the UK logistics sector (preprint)

Background: The emergence of SARS-CoV-2 triggered a chain of public health responses that radically changed our way of living and working. Non-healthcare sectors, such as the logistics sector, play a key role in such responses. This research aims to qualitatively evaluate the non-pharmaceutical interventions (NPIs) implemented in the UK logistics sector during the COVID-19 pandemic. Methods: We conducted nine semi-structured interviews in July-August 2020 and May-June 2021. In total 11 interviewees represented six companies occupying a range of positions in the UK logistics sector, including takeaway food delivery, large and small goods delivery and home appliance installation, and logistics technology providers. Inductive thematic analysis was completed using NVivo12 to generate emerging themes and subthemes. Themes/subthemes relevant to interventions were mapped deductively onto an adapted Hierarchy of Control (HoC) framework, focusing on delivery workers. Themes/subthemes relevant to the process of implementation were analyzed to understand the barriers and facilitators of rapid responses. Results: HoC analysis suggests the sector has implemented a wide range of risk mitigation measures, with each company developing their own portfolio of measures. Contact-free delivery was the most commonly implemented measure and perceived effective. In addition, a broad range of measures were implemented, including social distancing, internal contact tracing, communication and collaboration with other key stakeholders of the sector. Process evaluation identified facilitators of rapid responses including capacity to develop interventions internally, localized government support, overwhelming external mandates, effective communication, leadership support and financial support for self-isolation, while barriers included unclear government guidance, shortage of testing capacity and supply, high costs and diversified language and cultural backgrounds. Main sustainability issues included compliance fatigue, and the possible mental health impacts of a prolonged rapid response. Conclusions: This research identified drivers and obstacles of rapid implementation of NPIs in response to a respiratory infection pandemic. Existing implementation process models do not consider speed to respond and the absence or lack of guidance in emergency situations such as the COVID-19. We recommend the development of a rapid response model to inform the design of effective and sustainable infection prevention and control policies and to focus future research priorities.

SARS-CoV-2 variants exhibit increased kinetic stability of open spike conformations as an evolutionary strategy (preprint)

SARS-CoV-2 variants of concern harbor mutations in the Spike (S) glycoprotein that confer more efficient transmission and dampen the efficacy of COVID-19 vaccines and antibody therapies. S mediates virus entry and is the primary target for antibody responses. Structural studies of soluble S variants have revealed an increased propensity towards conformations accessible to receptor human Angiotensin-Converting Enzyme 2 (hACE2). However, real-time observations of conformational dynamics that govern the structural equilibriums of the S variants have been lacking. Here, we report single-molecule Forster Energy Transfer (smFRET) studies of S variants containing critical mutations, including D614G and E484K, in the context of virus particles. Investigated variants predominantly occupied more open hACE2-accessible conformations, agreeing with previous structures of soluble trimers. Additionally, these S variants exhibited decelerated transitions in hACE2-accessible/bound states. Our finding of increased S kinetic stability in the open conformation provides a new perspective on SARS-CoV-2 adaptation to the human population.

Updated pharmacological effects of Lonicerae japonicae flos, with a focus on its potential efficacy on coronavirus disease-2019 (COVID-19).

Lonicerae japonicae flos (LJF), known as Jin Yin Hua in Chinese, is one of the most commonly used traditional Chinese herbs and nutraceuticals. Nowadays, LJF is broadly applied in an array of afflictions, such as fever, sore throat, flu infection, cough, and arthritis, with the action mechanism to be elucidated. Here, we strove to summarize the main phytochemical components of LJF and review its updated pharmacological effects, including inhibition of inflammation, pyrexia, viruses, and bacteria, immunoregulation, and protection of the liver, nervous system, and heart, with a focus on the potential efficacy of LJF on coronavirus disease-2019 based on network pharmacology so as to fully underpin the utilization of LJF as a medicinal herb and a favorable nutraceutical in daily life.

The coSIR model predicts effective strategies to limit the spread of SARS-CoV-2 variants with low severity and high transmissibility.

Multiple new variants of SARS-CoV-2 have been identified as the COVID-19 pandemic spreads across the globe. However, most epidemic models view the virus as static and unchanging and thus fail to address the consequences of the potential evolution of the virus. Here, we built a competitive susceptible-infected-removed (coSIR) model to simulate the competition between virus strains of differing severities or transmissibility under various virus control policies. The coSIR model predicts that although the virus is extremely unlikely to evolve into a "super virus" that causes an increased fatality rate, virus variants with less severe symptoms can lead to potential new outbreaks and can cost more lives over time. The present model also demonstrates that the protocols restricting the transmission of the virus, such as wearing masks and social distancing, are the most effective strategy in reducing total mortality. A combination of adequate testing and strict quarantine is a powerful alternative to policies such as mandatory stay-at-home orders, which may have an enormous negative impact on the economy. In addition, building Mobile Cabin Hospitals can be effective and efficient in reducing the mortality rate of highly infectious virus strains. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11071-021-06705-8.

SARS-CoV-2 Induces Lymphocytopenia by Promoting Inflammation and Decimates Secondary Lymphoid Organs.

While lymphocytopenia is a common characteristic of coronavirus disease 2019 (COVID-19), the mechanisms responsible for this lymphocyte depletion are unclear. Here, we retrospectively reviewed the clinical and immunological data from 18 fatal COVID-19 cases, results showed that these patients had severe lymphocytopenia, together with high serum levels of inflammatory cytokines (IL-6, IL-8 and IL-10), and elevation of many other mediators in routine laboratory tests, including C-reactive protein, lactate dehydrogenase, α-hydroxybutyrate dehydrogenase and natriuretic peptide type B. The spleens and hilar lymph nodes (LNs) from six additional COVID-19 patients with post-mortem examinations were also collected, histopathologic detection showed that both organs manifested severe tissue damage and lymphocyte apoptosis in these six cases. In situ hybridization assays illustrated that SARS-CoV-2 viral RNA accumulates in these tissues, and transmission electronic microscopy confirmed that coronavirus-like particles were visible in the LNs. SARS-CoV-2 Spike and Nucleocapsid protein (NP) accumulated in the spleens and LNs, and the NP antigen restricted in angiotensin-converting enzyme 2 (ACE2) positive macrophages and dendritic cells (DCs). Furthermore, SARS-CoV-2 triggered the transcription of Il6, Il8 and Il1b genes in infected primary macrophages and DCs in vitro, and SARS-CoV-2-NP+ macrophages and DCs also manifested high levels of IL-6 and IL-1ß, which might directly decimate human spleens and LNs and subsequently lead to lymphocytopenia in vivo. Collectively, these results demonstrated that SARS-CoV-2 induced lymphocytopenia by promoting systemic inflammation and direct neutralization in human spleen and LNs.