Plasma cell-free DNA promise monitoring and tissue injury assessment of COVID-19.

Coronavirus 2019 (COVID-19) is a complex disease that affects billions of people worldwide. Currently, effective etiological treatment of COVID-19 is still lacking; COVID-19 also causes damages to various organs that affects therapeutics and mortality of the patients. Surveillance of the treatment responses and organ injury assessment of COVID-19 patients are of high clinical value. In this study, we investigated the characteristic fragmentation patterns and explored the potential in tissue injury assessment of plasma cell-free DNA in COVID-19 patients. Through recruitment of 37 COVID-19 patients, 32 controls and analysis of 208 blood samples upon diagnosis and during treatment, we report gross abnormalities in cfDNA of COVID-19 patients, including elevated GC content, altered molecule size and end motif patterns. More importantly, such cfDNA fragmentation characteristics reflect patient-specific physiological changes during treatment. Further analysis on cfDNA tissue-of-origin tracing reveals frequent tissue injuries in COVID-19 patients, which is supported by clinical diagnoses. Hence, our work demonstrates and extends the translational merit of cfDNA fragmentation pattern as valuable analyte for effective treatment monitoring, as well as tissue injury assessment in COVID-19.

Saliva - a new opportunity for fluid biopsy.

Saliva is a complex biological fluid with a variety of biomolecules, such as DNA, RNA, proteins, metabolites and microbiota, which can be used for the screening and diagnosis of many diseases. In addition, saliva has the characteristics of simple collection, non-invasive and convenient storage, which gives it the potential to replace blood as a new main body of fluid biopsy, and it is an excellent biological diagnostic fluid. This review integrates recent studies and summarizes the research contents of salivaomics and the research progress of saliva in early diagnosis of oral and systemic diseases. This review aims to explore the value and prospect of saliva diagnosis in clinical application.

Quantified multidimensional public sentiment characteristics on social media for public opinion management: Evidence from the COVID-19 pandemic.

Background: Public sentiments arising from public opinion communication pose a serious psychological risk to public and interfere the communication of nonpharmacological intervention information during the COVID-19 pandemic. Problems caused by public sentiments need to be timely addressed and resolved to support public opinion management. Objective: This study aims to investigate the quantified multidimensional public sentiments characteristics for helping solve the public sentiments issues and strengthen public opinion management. Methods: This study collected the user interaction data from the Weibo platform, including 73,604 Weibo posts and 1,811,703 Weibo comments. Deep learning based on pretraining model, topics clustering and correlation analysis were used to conduct quantitative analysis on time series characteristics, content-based characteristics and audience response characteristics of public sentiments in public opinion during the pandemic. Results: The research findings were as follows: first, public sentiments erupted after priming, and the time series of public sentiments had window periods. Second, public sentiments were related to public discussion topics. The more negative the audience sentiments were, the more deeply the public participated in public discussions. Third, audience sentiments were independent of Weibo posts and user attributes, the steering role of opinion leaders was invalid in changing audience sentiments. Discussion: Since the COVID-19 pandemic, there has been an increasing demand for public opinion management on social media. Our study on the quantified multidimensional public sentiments characteristics is one of the methodological contributions to reinforce public opinion management from a practical perspective.

Regulating the microenvironment with nanomaterials: Potential strategies to ameliorate COVID-19.

COVID-19, caused by SARS-CoV-2, has resulted in serious economic and health burdens. Current treatments remain inadequate to extinguish the epidemic, and efficient therapeutic approaches for COVID-19 are urgently being sought. Interestingly, accumulating evidence suggests that microenvironmental disorder plays an important role in the progression of COVID-19 in patients. In addition, recent advances in nanomaterial technologies provide promising opportunities for alleviating the altered homeostasis induced by a viral infection, providing new insight into COVID-19 treatment. Most literature reviews focus only on certain aspects of microenvironment alterations and fail to provide a comprehensive overview of the changes in homeostasis in COVID-19 patients. To fill this gap, this review systematically discusses alterations of homeostasis in COVID-19 patients and potential mechanisms. Next, advances in nanotechnology-based strategies for promoting homeostasis restoration are summarized. Finally, we discuss the challenges and prospects of using nanomaterials for COVID-19 management. This review provides a new strategy and insights into treating COVID-19 and other diseases associated with microenvironment disorders.

Guild-Level Microbiome Signature Associated with COVID-19 Severity and Prognosis.

Coronavirus disease 2019 (COVID-19) severity has been associated with alterations of the gut microbiota. However, the relationship between gut microbiome alterations and COVID-19 prognosis remains elusive. Here, we performed a genome-resolved metagenomic analysis on fecal samples from 300 in-hospital COVID-19 patients, collected at the time of admission. Among the 2,568 high quality metagenome-assembled genomes (HQMAGs), redundancy analysis identified 33 HQMAGs which showed differential distribution among mild, moderate, and severe/critical severity groups. Co-abundance network analysis determined that the 33 HQMAGs were organized as two competing guilds. Guild 1 harbored more genes for short-chain fatty acid biosynthesis, and fewer genes for virulence and antibiotic resistance, compared with Guild 2. Based on average abundance difference between the two guilds, the guild-level microbiome index (GMI) classified patients from different severity groups (average AUROC [area under the receiver operating curve] = 0.83). Moreover, age-adjusted partial Spearman's correlation showed that GMIs at admission were correlated with 8 clinical parameters, which are predictors for COVID-19 prognosis, on day 7 in hospital. In addition, GMI at admission was associated with death/discharge outcome of the critical patients. We further validated that GMI was able to consistently classify patients with different COVID-19 symptom severities in different countries and differentiated COVID-19 patients from healthy subjects and pneumonia controls in four independent data sets. Thus, this genome-based guild-level signature may facilitate early identification of hospitalized COVID-19 patients with high risk of more severe outcomes at time of admission. IMPORTANCE Previous reports on the associations between COVID-19 and gut microbiome have been constrained by taxonomic-level analysis and overlook the interaction between microbes. By applying a genome-resolved, reference-free, guild-based metagenomic analysis, we demonstrated that the relationship between gut microbiota and COVID-19 is genome-specific instead of taxon-specific or even species-specific. Moreover, the COVID-19-associated genomes were not independent but formed two competing guilds, with Guild 1 potentially beneficial and Guild 2 potentially more detrimental to the host based on comparative genomic analysis. The dominance of Guild 2 over Guild 1 at time of admission was associated with hospitalized COVID-19 patients at high risk for more severe outcomes. Moreover, the guild-level microbiome signature is not only correlated with the symptom severity of COVID-19 patients, but also differentiates COVID-19 patients from pneumonia controls and healthy subjects across different studies. Here, we showed the possibility of using genome-resolved and guild-level microbiome signatures to identify hospitalized COVID-19 patients with a high risk of more severe outcomes at the time of admission.

Immune response and homeostasis mechanism following administration of BBIBP-CorV SARS-CoV-2 inactivated vaccine.

The BBIBP-CorV severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) inactivated vaccine has been authorized for emergency use and widely distributed. We used single-cell transcriptome sequencing to characterize the dynamics of immune responses to the BBIBP-CorV inactivated vaccine. In addition to the expected induction of humoral immunity, we found that the inactivated vaccine induced multiple, comprehensive immune responses, including significantly increased proportions of CD16+ monocytes and activation of monocyte antigen presentation pathways; T cell activation pathway upregulation in CD8+ T cells, along with increased activation of CD4+ T cells; significant enhancement of cell-cell communications between innate and adaptive immunity; and the induction of regulatory CD4+ T cells and co-inhibitory interactions to maintain immune homeostasis after vaccination. Additionally, comparative analysis revealed higher neutralizing antibody levels, distinct expansion of naive T cells, a shared increased proportion of regulatory CD4+ T cells, and upregulated expression of functional genes in booster dose recipients with a longer interval after the second vaccination. Our research will support a comprehensive understanding of the systemic immune responses elicited by the BBIBP-CorV inactivated vaccine, which will facilitate the formulation of better vaccination strategies and the design of new vaccines.

School resources, self-control and problem behaviors in Chinese adolescents: a longitudinal study in the post-pandemic era.

The outbreak of COVID-19 has brought many challenges to youth development. During this specific period, adolescents have suffered from numerous behavioral problems, which will lead to more maladaptive consequences. It is necessary to explore several protective factors to prevent or reduce the occurrence of problem behaviors in adolescence. The current study combined school resources and self-control to evaluate the multiple protective effects on adolescents' problematic behaviors in a two-wave longitudinal study. A sample of 789 Chinese adolescents (Mage = 14.00 years, SD = 2.05, 418 boys) were recruited via the random cluster sampling method to participate in the survey. The results confirmed the assumptions about the multiple protective effects of school resources and self-control on adolescents' problem behaviors. Specifically, school resources could negatively predict IGD and victimization, and self-control mediated these associations. Moreover, one problematic behavior could also mediate the associations between self-control and another problematic behavior. This is the first study to focus on the multiple protective effects of positive factors on adolescents' problem behaviors during the post-pandemic period, which has made several contributions to the literature and practice.

Determinants and mechanisms driving energy-saving behaviours of long-stay hotel guests: Comparison of leisure, business and extended-stay residential cases

The global hospitality industry is fast-turning sustainable and environmentally friendly. Behaviour-driven energy conservation is an emerging green hotel operation strategy to support this change. The long-stay accommodation services have gained momentum in the hospitality sector since the COVID-19 pandemic. However, the characteristics of long-stay hotel guests are often overlooked in sustainable interventions. Based on an empirical survey in China, this study aims to explore the factors driving energy-saving behaviours of long-stay hotel guests and to compare their effects on guests for different visiting purposes (leisure, business, and extended-stay resident). The analysis indicates that attitude, personal norm and place attachment present a direct contribution to energy-saving behaviour. Besides, the results support that attitude and personal norm connect environmental values and energy-saving behaviour. Both altruistic and biospheric values have positive effects, while egoistic values seem to play a negative role. Biospheric values have stronger impact on attitude and personal norm of business guests. Place attachment has a stronger influence on extended-stay residents while its contribution to energy-saving behaviours of business guests is smaller than other guests. Besides, leisure guests are more sensitive to moral obligations. This research sheds novel lights on the psychological perspectives of the observed heterogeneity of energy-saving behaviours of hotel guests with different visiting purposes. The findings provide hotel operators with a novel theoretical reference for targeted energy-saving interventions to promote energy-saving actions of long-term hotel guests. The study, therefore, can contribute to sustainable tourism policymaking and behaviour-driven hotel energy management.

The rapid and efficient strategy for SARS-CoV-2 Omicron transmission control: analysis of outbreaks at the city level.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron (B.1.1.529) variant is highly transmissible with potential immune escape. Hence, control measures are continuously being optimized to guard against large-scale coronavirus disease 2019 (COVID-19) outbreaks. This study aimed to explore the relationship between the intensity of control measures in response to different SARS-CoV-2 variants and the degree of outbreak control at city level. METHODS: A retrospective study was conducted in 49 cities with COVID-19 outbreaks between January 2020 and June 2022. Epidemiological data on COVID-19 were extracted from the National Health Commission, People's Republic of China, and the population flow data were sourced from the Baidu migration data provided by the Baidu platform. Outbreak control was quantified by calculating the degree of infection growth and the time-varying reproduction number ([Formula: see text]). The intensity of the outbreak response was quantified by calculating the reduction in population mobility during the outbreak period. Correlation and regression analyses of the intensity of the control measures and the degree of outbreak control for the Omicron variant and non-Omicron mutants were conducted, respectively. RESULTS: Overall, 65 outbreaks occurred in 49 cities in China from January 2020 to June 2022. Of them, 66.2% were Omicron outbreaks and 33.8% were non-Omicron outbreaks. The intensity of the control measures was positively correlated with the degree of outbreak control (r = 0.351, P = 0.03). The degree of reduction in population mobility was negatively correlated with the Rt value (r = - 0.612, P < 0.01). Therefore, under the same control measure intensity, the number of new daily Omicron infections was 6.04 times higher than those attributed to non-Omicron variants, and the Rt value of Omicron outbreaks was 2.6 times higher than that of non-Omicron variants. In addition, the duration of non-Omicron variant outbreaks was shorter than that of the outbreaks caused by the Omicron variant (23.0 ± 10.7, 32.9 ± 16.3, t = 2.243, P = 0.031). CONCLUSIONS: Greater intensity of control measures was associated with more effective outbreak control. Thus, in response to the Omicron variant, the management to restrict population movement should be used to control its spread quickly, especially in the case of community transmission occurs widely. Faster than is needed for non-Omicron variants, and decisive control measures should be imposed and dynamically adjusted in accordance with the evolving epidemic situation.

Optimal control strategies of SARS-CoV-2 Omicron supported by invasive and dynamic models.

BACKGROUND: There is a raising concern of a higher infectious Omicron BA.2 variant and the latest BA.4, BA.5 variant, made it more difficult in the mitigation process against COVID-19 pandemic. Our study aimed to find optimal control strategies by transmission of dynamic model from novel invasion theory. METHODS: Based on the public data sources from January 31 to May 31, 2022, in four cities (Nanjing, Shanghai, Shenzhen and Suzhou) of China. We segmented the theoretical curves into five phases based on the concept of biological invasion. Then, a spatial autocorrelation analysis was carried out by detecting the clustering of the studied areas. After that, we choose a mathematical model of COVID-19 based on system dynamics methodology to simulate numerous intervention measures scenarios. Finally, we have used publicly available migration data to calculate spillover risk. RESULTS: Epidemics in Shanghai and Shenzhen has gone through the entire invasion phases, whereas Nanjing and Suzhou were all ended in the establishment phase. The results indicated that Rt value and public health and social measures (PHSM)-index of the epidemics were a negative correlation in all cities, except Shenzhen. The intervention has come into effect in different phases of invasion in all studied cities. Until the May 31, most of the spillover risk in Shanghai remained above the spillover risk threshold (18.81-303.84) and the actual number of the spillovers (0.94-74.98) was also increasing along with the time. Shenzhen reported Omicron cases that was only above the spillover risk threshold (17.92) at the phase of outbreak, consistent with an actual partial spillover. In Nanjing and Suzhou, the actual number of reported cases did not exceed the spillover alert value. CONCLUSIONS: Biological invasion is positioned to contribute substantively to understanding the drivers and mechanisms of the COVID-19 spread and outbreaks. After evaluating the spillover risk of cities at each invasion phase, we found the dynamic zero-COVID strategy implemented in four cities successfully curb the disease epidemic peak of the Omicron variant, which was highly correlated to the way to perform public health and social measures in the early phases right after the invasion of the virus.

Intermodal transportation hub location optimization with governments subsidies under the Belt and Road Initiative.

Driven by globalization, the COVID-19 outbreak has severely impacted global transport and logistics systems. To better cope with this globalization crisis, the Belt and Road Initiative (BRI)-based on the concept of cooperation-is more important than ever in the post-pandemic era. Taking the BRI as the background, we design an intermodal hub-and-spoke network to provide reference for governments along BRI routes to improve their cross-border transportation system and promote economic recovery. In the context of the BRI, local governments at different nodes have incentives to subsidize hub construction and/or rail transportation to boost economic development. We consider co-opetition behavior among different levels of government caused by subsidies in this intermodal hub location problem, which we call the intermodal hub location problem based on government subsidies. We establish a two-stage mixed-integer programming model. In the first stage, local governments provide subsidies, then the central government decides the number and location of hubs. In the second stage, freight carriers choose the optimal route to transport the goods. To solve the model, we design an optimization method combining a population-based algorithm using contest theory. The results show that rail subsidies are positively correlated with construction subsidies but are not necessarily related to the choice of hubs. Compared with monomodal transportation, intermodal transportation can reduce costs more effectively when there are not too many hubs and the cost of different modes of transportation varies greatly. The influences of local government competition and hub construction investment on network design and government subsidies are further examined.

The more developmental assets, the less internet gaming disorder? Testing the cumulative effect and longitudinal mechanism during the COVID-19 pandemic.

The COVID-19 pandemic has triggered the dramatical development and prosperity of online games, while worldwide people are suffering from it. Considering the high prevalence, serious impacts, and huge development potential of internet gaming disorder (IGD), it is extremely necessary to develop a protective model to prevent and intervene with it among young people. Based on the developmental assets theory, the present study adopted a two-wave longitudinal design to evaluate the cumulative effects of developmental assets on IGD, as well as the underlying mechanisms during this specific period. Data were collected from a sample of 1023 adolescents in Hubei province, Central China through self-report questionnaires. The results indicated that (1) developmental assets were negatively associated with adolescents' IGD concurrently and longitudinally; (2) the overall developmental assets had cumulative effects in linear patterns on adolescents' IGD, concurrently and longitudinally; and (3) internal developmental assets mediated the relationship between external developmental assets and adolescents' IGD longitudinally. Theoretically, the present study supports the developmental assets theory and expands the literature about developmental assets and IGD in younger generations. Practically, the present study provides guidance for prevention and intervention of IGD among adolescents during and after the COVID-19 pandemic. Comprehensive measures should be taken to assist in developing positive internal and external resources to promote youth thriving.

Lineage-specific positive selection on ACE2 contributes to the genetic susceptibility of COVID-19.

The Angiotensin-Converting Enzyme-2 (ACE2) gene, located on Xp22.2, attracts a great deal of attention because the protein it encodes is believed to be the functional cellular receptor for the new coronavirus (SARS-CoV-2). However, recent studies are controversial, especially concerning the intrinsic link between ACE2 diversity and COVID-19 susceptibility. Here, we conduct a population genetic study on ACE2 in 6354 individuals representing 210 present-day populations and 5329 individuals of ancient or archaic groups. We dissected the genetic architecture of ACE2 and identified two major haplogroups (hg) in East Asians, i.e. ACE2-hg1 (43%) and ACE2-hg2 (53%), while other populations harbor more diverse ACE2-hgs. Accordingly, there was a significant loss of ACE2 common variations in East Asians in contrast to the X-chromosome-wide and genome-wide patterns. Notably, association analysis between ACE2-hgs and COVID-19 severity in 1229 Han Chinese individuals with various levels of COVID-19 severity showed a higher risk of ACE2-hg1 (odds ratio = 1.56, P < 0.01) and a lower risk of ACE2-hg2 (odds ratio = 0.65, P < 0.01). Interestingly, ACE2-hg1 is in strong linkage disequilibrium with rs1849863-C, which is an assumed risk factor of elevated plasma ACE2 level and is related to a higher risk of COVID-19 severity, hospitalization and infection. Strikingly, remarkable signatures of positive selection were detected, especially on ACE2-hg2, and were traced back to 100 000 years ago (but rose to a strong level during the Bronze Age, 5000∼3000 years ago, in East Asians). The selection pressures could have stemmed from multiple sources, but pre-COVID-19 viral epidemics and pandemics might have been potential driving forces, which consequently contributed to the genetic susceptibility to COVID-19 within and between populations.

Comparative analysis of single cell lung atlas of bat, cat, tiger, and pangolin.

Horseshoe bats (Rhinolophus sinicus) might help maintain coronaviruses severely affecting human health, such as severe acute respiratory syndrome coronavirus (SARS-CoV). Bats may be more tolerant of viral infection than other mammals due to their unique immune system, but the exact mechanism remains to be fully explored. During the coronavirus disease 2019 (COVID-19) pandemic, multiple animal species were diseased by coronavirus infection, especially in the respiratory system. Herein, a comparative analysis with single nucleus transcriptomic data of the lungs across four species, including horseshoe bat, cat, tiger, and pangolin, were conducted. The distribution of entry factors for twenty-eight respiratory viruses was characterized for the four species. Our findings might increase our understanding of the immune background of horseshoe bats.

Rare Variants in Inborn Errors of Immunity Genes Associated With Covid-19 Severity.

Host genetic factors have been shown to play an important role in SARS-CoV-2 infection and the course of Covid-19 disease. The genetic contributions of common variants influencing Covid-19 susceptibility and severity have been extensively studied in diverse populations. However, the studies of rare genetic defects arising from inborn errors of immunity (IEI) are relatively few, especially in the Chinese population. To fill this gap, we used a deeply sequenced dataset of nearly 500 patients, all of Chinese descent, to investigate putative functional rare variants. Specifically, we annotated rare variants in our call set and selected likely deleterious missense (LDM) and high-confidence predicted loss-of-function (HC-pLoF) variants. Further, we analyzed LDM and HC-pLoF variants between non-severe and severe Covid-19 patients by (a) performing gene- and pathway-level association analyses, (b) testing the number of mutations in previously reported genes mapped from LDM and HC-pLoF variants, and (c) uncovering candidate genes via protein-protein interaction (PPI) network analysis of Covid-19-related genes and genes defined from LDM and HC-pLoF variants. From our analyses, we found that (a) pathways Tuberculosis (hsa:05152), Primary Immunodeficiency (hsa:05340), and Influenza A (hsa:05164) showed significant enrichment in severe patients compared to the non-severe ones, (b) HC-pLoF mutations were enriched in Covid-19-related genes in severe patients, and (c) several candidate genes, such as IL12RB1, TBK1, TLR3, and IFNGR2, are uncovered by PPI network analysis and worth further investigation. These regions generally play an essential role in regulating antiviral innate immunity responses to foreign pathogens and in responding to many inflammatory diseases. We believe that our identified candidate genes/pathways can be potentially used as Covid-19 diagnostic markers and help distinguish patients at higher risk.

Rare Variants in Inborn Errors of Immunity Genes Associated With Covid-19 Severity

Host genetic factors have been shown to play an important role in SARS-CoV-2 infection and the course of Covid-19 disease. The genetic contributions of common variants influencing Covid-19 susceptibility and severity have been extensively studied in diverse populations. However, the studies of rare genetic defects arising from inborn errors of immunity (IEI) are relatively few, especially in the Chinese population. To fill this gap, we used a deeply sequenced dataset of nearly 500 patients, all of Chinese descent, to investigate putative functional rare variants. Specifically, we annotated rare variants in our call set and selected likely deleterious missense (LDM) and high-confidence predicted loss-of-function (HC-pLoF) variants. Further, we analyzed LDM and HC-pLoF variants between non-severe and severe Covid-19 patients by (a) performing gene- and pathway-level association analyses, (b) testing the number of mutations in previously reported genes mapped from LDM and HC-pLoF variants, and (c) uncovering candidate genes via protein-protein interaction (PPI) network analysis of Covid-19-related genes and genes defined from LDM and HC-pLoF variants. From our analyses, we found that (a) pathways Tuberculosis (hsa:05152), Primary Immunodeficiency (hsa:05340), and Influenza A (hsa:05164) showed significant enrichment in severe patients compared to the non-severe ones, (b) HC-pLoF mutations were enriched in Covid-19-related genes in severe patients, and (c) several candidate genes, such as IL12RB1, TBK1, TLR3, and IFNGR2, are uncovered by PPI network analysis and worth further investigation. These regions generally play an essential role in regulating antiviral innate immunity responses to foreign pathogens and in responding to many inflammatory diseases. We believe that our identified candidate genes/pathways can be potentially used as Covid-19 diagnostic markers and help distinguish patients at higher risk.

A Comprehensive Review of Pharmacokinetics and Pharmacodynamics in Animals: Exploration of Interaction with Antibiotics of Shuang-Huang- Lian Preparations.

As a traditional Chinese medicine (TCM), Shuang-Huang-Lian (SHL) has been widely used for treating infectious diseases of the respiratory tract such as encephalitis, pneumonia, and asthma. During the past few decades, considerable research has focused on pharmacological action, pharmacokinetic interaction with antibiotics, and clinical applications of SHL. A huge and more recent body of pharmacokinetic studies support the combination of SHL and antibiotics have different effects such as antagonism and synergism. SHL has been one of the best-selling TCM products. However, there is no systematic review of SHL preparations, ranging from protection against respiratory tract infections to interaction with antibiotics. Since their important significance in clinical therapy, the pharmacodynamics, pharmacokinetics, and interactions with antibiotics of SHL were reviewed and discussed. In addition, this review attempts to explore the possible potential mechanism of SHL preparations in the prevention and treatment of COVID-19. We are concerned about the effects of SHL against viruses and bacteria, as well as its interactions with antibiotics in an attempt to provide a new strategy for expanding the clinical research and medication of SHL preparations.