Virological characteristics of the SARS-CoV-2 JN.1 variant (preprint)

The SARS-CoV-2 BA.2.86 lineage, first identified in August 2023, is phylogenetically distinct from the currently circulating SARS-CoV-2 Omicron XBB lineages, including EG.5.1 and HK.3. Comparing to XBB and BA.2, BA.2.86 carries more than 30 mutations in the spike (S) protein, indicating a high potential for immune evasion. BA.2.86 has evolved and its descendant, JN.1 (BA.2.86.1.1), emerged in late 2023. JN.1 harbors S:L455S and three mutations in non-S proteins. S:L455S is a hallmark mutation of JN.1: we have recently shown that HK.3 and other "FLip" variants carry S:L455F, which contributes to increased transmissibility and immune escape ability compared to the parental EG.5.1 variant. Here, we investigated the virological properties of JN.1.

Virological characteristics of the SARS-CoV-2 Omicron HK.3 variant harboring the "FLip" substitution (preprint)

In November 2023, SARS-CoV-2 XBB descendants, including EG.5.1 (XBB.1.9.2.5.1), the currently predominant lineage, are circulating worldwide according to Nextstrain. EG.5.1 has a characteristic amino acid substitution in the spike protein (S), S:F456L, which contributes to its escape from humoral immunity. EG.5.1 has further evolved, and its descendant lineage harboring S:L455F (i.e., EG.5.1+S:L455F) emerged and was named HK.3 (XBB.1.9.2.5.1.1.3). HK.3 was initially discovered in East Asia and is rapidly spreading worldwide. Notably, the XBB subvariants bearing both S:L455F and S:F456L substitutions, including HK.3, are called the "FLip" variants. These FLip variants, such as JG.3 (XBB.1.9.2.5.1.3.3), JF.1 (XBB.1.16.6.1) and GK.3 (XBB.1.5.70.3), have emerged convergently, suggesting that the acquisition of these two substitutions confers a growth advantage to XBB in the human population. Here, we investigated the virological properties of HK.3 as a representative of the FLip variants.

Virological characteristics of the SARS-CoV-2 Omicron EG.5.1 variant (preprint)

In middle-late 2023, a sublineage of SARS-CoV-2 Omicron XBB, EG.5.1 (a progeny of XBB.1.9.2), is spreading rapidly around the world. Here, we performed multiscale investigations to reveal virological features of newly emerging EG.5.1 variant. Our phylogenetic-epidemic dynamics modeling suggested that two hallmark substitutions of EG.5.1, S:F456L and ORF9b:I5T, are critical to the increased viral fitness. Experimental investigations addressing the growth kinetics, sensitivity to clinically available antivirals, fusogenicity and pathogenicity of EG.5.1 suggested that the virological features of EG.5.1 is comparable to that of XBB.1.5. However, the cryo-electron microscopy reveals the structural difference between the spike proteins of EG.5.1 and XBB.1.5. We further assessed the impact of ORF9b:I5T on viral features, but it was almost negligible at least in our experimental setup. Our multiscale investigations provide the knowledge for understanding of the evolution trait of newly emerging pathogenic viruses in the human population.

The knowledge map of gender equality in cross-cultural communication: A bibliometric approach.

It is urgent to solve the gender issues in global cross-cultural communication. Countries worldwide should responsible for achieving gender equality (SDG5). Hence, the study aims to portray the knowledge map of the gender issue in intercultural communication to explore the research status and future potential. The study used CiteSpace to conduct a bibliometric method within 2728 English articles on cross-cultural communication and gender equality topics from the Web of Science (WoS). After cluster analysis and time series analysis, this study emphasis the continued attention and increasing trend of publications and elaborates on the critical authors, institutions, and countries of research on this issue. The results introduced Putnick as the dominant author contributed to the topic. The University of Oxford ranked the top1 in the institution cooperation relationship. Europe countries and the United States have made major contributions and influenced Asian and African countries, such as Burkina Faso, North Macedonia, and Kosovo. Gender issues in Asia and Africa are getting much attention. The keyword clusters formed by the authors' cooperation include gender equality, life satisfaction, network analysis, and alcohol use. In addition, childbirth technology, patient safety competition, life satisfaction, capital safety, and sex difference are the key word clustering results of institutional cooperation. At the level of national cooperation, internet addition, risk sexual behavior, covid-19 pandemic and suicidal idea have become the main keywords The results of keyword cluster analysis show that gender role attribute, psychological properties, dating policy, professional fulfillment, and entrepreneurial intention have become the main topics in the current research. The research frontier analysis reflects the importance of gender, women and health. The research on self-efficacy, diversity, image, life satisfaction and choice has become the trend of cross-cultural communication and gender issues. Furthermore, abundant achievement emerged in the subjects of Psychology, Education, Sociology, and Business economics. Geography, Language and Literature, Medicine, and Health industries also have been highly influential in recent years. Therefore, the conclusion suggests the studies of gender issues can be further deepened into more authors, areas, subject and other multiple cooperation sectors.

Neutralization effect of plasma from vaccinated COVID-19 convalescents on SARS-CoV-2 Omicron variants.

Background: COVID-19 has caused a global pandemic and the death toll is increasing. With the coronavirus continuously mutating, Omicron has replaced Delta as the most widely reported variant in the world. Studies have shown that the plasma of some vaccinated people does not neutralize the Omicron variant. However, further studies are needed to determine whether plasma neutralizes Omicron after one- or two-dose vaccine in patients who have recovered from infection with the original strain. Methods: The pseudovirus neutralization assays were performed on 64 plasma samples of convalescent COVID-19 patients, which were divided into pre-vaccination group, one-dose vaccinated group and two-dose vaccinated group. Results: In the three groups, there were significant reductions of sera neutralizing activity from WT to Delta variant (B.1.617.2), and from WT to Omicron variant (B.1.1.529) (ps<0.001), but the difference between Delta and Omicron variants were not significant (p>0.05). The average neutralization of the Omicron variant showed a significant difference between pre-vaccination and two-dose vaccinated convalescent individuals (p<0.01). Conclusions: Among the 64 plasma samples of COVID-19 convalescents, whether vaccinated or not, Omicron (B.1.1.529) escaped the neutralizing antibodies, with a significantly decreased neutralization activity compared to WT. And two-dose of vaccine could significantly raise the average neutralization of Omicron in convalescent individuals.

Neutralization effect of plasma from vaccinated COVID-19 convalescents on SARS-CoV-2 Omicron variants

Background COVID-19 has caused a global pandemic and the death toll is increasing. With the coronavirus continuously mutating, Omicron has replaced Delta as the most widely reported variant in the world. Studies have shown that the plasma of some vaccinated people does not neutralize the Omicron variant. However, further studies are needed to determine whether plasma neutralizes Omicron after one- or two-dose vaccine in patients who have recovered from infection with the original strain. Methods The pseudovirus neutralization assays were performed on 64 plasma samples of convalescent COVID-19 patients, which were divided into pre-vaccination group, one-dose vaccinated group and two-dose vaccinated group. Results In the three groups, there were significant reductions of sera neutralizing activity from WT to Delta variant (B.1.617.2), and from WT to Omicron variant (B.1.1.529) (ps<0.001), but the difference between Delta and Omicron variants were not significant (p>0.05). The average neutralization of the Omicron variant showed a significant difference between pre-vaccination and two-dose vaccinated convalescent individuals (p<0.01). Conclusions Among the 64 plasma samples of COVID-19 convalescents, whether vaccinated or not, Omicron (B.1.1.529) escaped the neutralizing antibodies, with a significantly decreased neutralization activity compared to WT. And two-dose of vaccine could significantly raise the average neutralization of Omicron in convalescent individuals.

Multiplicity and dynamics of social representations of the COVID-19 pandemic on Chinese social media from 2019 to 2020.

Documenting the emergent social representations of COVID-19 in public communication is necessary for critically reflecting on pandemic responses and providing guidance for global pandemic recovery policies and practices. This study documents the dynamics of changing social representations of the COVID-19 pandemic on one of the largest Chinese social media, Weibo, from December 2019 to April 2020. We draw on the social representation theory (SRT) and conceptualize topics and topic networks as a form of social representation. We analyzed a dataset of 40 million COVID-19 related posts from 9.7 million users (including the general public, opinion leaders, and organizations) using machine learning methods. We identified 12 topics and found an expansion in social representations of COVID-19 from a clinical and epidemiological perspective to a broader perspective that integrated personal illness experiences with economic and sociopolitical discourses. Discussions about COVID-19 science did not take a prominent position in the representations, suggesting a lack of effective science and risk communication. Further, we found the strongest association of social representations existed between the public and opinion leaders and the organizations' representations did not align much with the other two groups, suggesting a lack of organizations' influence in public representations of COVID-19 on social media in China.

Complex analysis of the personalized pharmacotherapy in the management of COVID-19 patients and suggestions for applications of predictive, preventive, and personalized medicine attitude.

AIMS: Coronavirus disease 2019 (COVID-19) is rapidly spreading worldwide. Drug therapy is one of the major treatments, but contradictory results of clinical trials have been reported among different individuals. Furthermore, comprehensive analysis of personalized pharmacotherapy is still lacking. In this study, analyses were performed on 47 well-characterized COVID-19 drugs used in the personalized treatment of COVID-19. METHODS: Clinical trials with published results of drugs use for COVID-19 treatment were collected to evaluate drug efficacy. Drug-to-Drug Interactions (DDIs) were summarized and classified. Functional variations in actionable pharmacogenes were collected and systematically analysed. "Gene Score" and "Drug Score" were defined and calculated to systematically analyse ethnicity-based genetic differences, which are important for the safer use of COVID-19 drugs. RESULTS: Our results indicated that four antiviral agents (ritonavir, darunavir, daclatasvir and sofosbuvir) and three immune regulators (budesonide, colchicine and prednisone) as well as heparin and enalapril could generate the highest number of DDIs with common concomitantly utilized drugs. Eight drugs (ritonavir, daclatasvir, sofosbuvir, ribavirin, interferon alpha-2b, chloroquine, hydroxychloroquine (HCQ) and ceftriaxone had actionable pharmacogenomics (PGx) biomarkers among all ethnic groups. Fourteen drugs (ritonavir, daclatasvir, prednisone, dexamethasone, ribavirin, HCQ, ceftriaxone, zinc, interferon beta-1a, remdesivir, levofloxacin, lopinavir, human immunoglobulin G and losartan) showed significantly different pharmacogenomic characteristics in relation to the ethnic origin of the patient. CONCLUSION: We recommend that particularly for patients with comorbidities to avoid serious DDIs, the predictive, preventive, and personalized medicine (PPPM, 3 PM) strategies have to be applied for COVID-19 treatment, and genetic tests should be performed for drugs with actionable pharmacogenes, especially in some ethnic groups with a higher frequency of functional variations, as our analysis showed. We also suggest that drugs associated with higher ethnic genetic differences should be given priority in future pharmacogenetic studies for COVID-19 management. To facilitate translation of our results into clinical practice, an approach conform with PPPM/3 PM principles was suggested. In summary, the proposed PPPM/3 PM attitude should be obligatory considered for the overall COVID-19 management. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13167-021-00247-0.

Exploring public perceptions of the COVID-19 vaccine online from a cultural perspective: Semantic network analysis of two social media platforms in the United States and China.

The development and uptake of the COVID-19 (coronavirus disease 2019) vaccine is a top priority in stifling the COVID-19 pandemic. How the public perceives the COVID-19 vaccine is directly associated with vaccine compliance and vaccination coverage. This study takes a cultural sensitivity perspective and adopts two well-known social media platforms in the United States (Twitter) and China (Weibo) to conduct a public perception comparison around the COVID-19 vaccine. By implementing semantic network analysis, results demonstrate that the two countries' social media users overlapped in themes concerning domestic vaccination policies, priority groups, challenges from COVID-19 variants, and the global pandemic situation. However, Twitter users were prone to disclose individual vaccination experiences, express anti-vaccine attitudes. In comparison, Weibo users manifested evident deference to authorities and exhibited more positive feelings toward the COVID-19 vaccine. Those disparities were explained by the cultural characteristics' differences between the two countries. The findings provide insights into comprehending public health issues in cross-cultural contexts and illustrate the potential of utilizing social media to conduct health informatics studies and investigate public perceptions during public health crisis time.

Exploring the Expression Differences Between Professionals and Laypeople Toward the COVID-19 Vaccine: Text Mining Approach.

BACKGROUND: COVID-19 is still rampant all over the world. Until now, the COVID-19 vaccine is the most promising measure to subdue contagion and achieve herd immunity. However, public vaccination intention is suboptimal. A clear division lies between medical professionals and laypeople. While most professionals eagerly promote the vaccination campaign, some laypeople exude suspicion, hesitancy, and even opposition toward COVID-19 vaccines. OBJECTIVE: This study aims to employ a text mining approach to examine expression differences and thematic disparities between the professionals and laypeople within the COVID-19 vaccine context. METHODS: We collected 3196 answers under 65 filtered questions concerning the COVID-19 vaccine from the China-based question and answer forum Zhihu. The questions were classified into 5 categories depending on their contents and description: adverse reactions, vaccination, vaccine effectiveness, social implications of vaccine, and vaccine development. Respondents were also manually coded into two groups: professional and laypeople. Automated text analysis was performed to calculate fundamental expression characteristics of the 2 groups, including answer length, attitude distribution, and high-frequency words. Furthermore, structural topic modeling (STM), as a cutting-edge branch in the topic modeling family, was used to extract topics under each question category, and thematic disparities were evaluated between the 2 groups. RESULTS: Laypeople are more prevailing in the COVID-19 vaccine-related discussion. Regarding differences in expression characteristics, the professionals posted longer answers and showed a conservative stance toward vaccine effectiveness than did laypeople. Laypeople mentioned countries more frequently, while professionals were inclined to raise medical jargon. STM discloses prominent topics under each question category. Statistical analysis revealed that laypeople preferred the "safety of Chinese-made vaccine" topic and other vaccine-related issues in other countries. However, the professionals paid more attention to medical principles and professional standards underlying the COVID-19 vaccine. With respect to topics associated with the social implications of vaccines, the 2 groups showed no significant difference. CONCLUSIONS: Our findings indicate that laypeople and professionals share some common grounds but also hold divergent focuses toward the COVID-19 vaccine issue. These incongruities can be summarized as "qualitatively different" in perspective rather than "quantitatively different" in scientific knowledge. Among those questions closely associated with medical expertise, the "qualitatively different" characteristic is quite conspicuous. This study boosts the current understanding of how the public perceives the COVID-19 vaccine, in a more nuanced way. Web-based question and answer forums are a bonanza for examining perception discrepancies among various identities. STM further exhibits unique strengths over the traditional topic modeling method in statistically testing the topic preference of diverse groups. Public health practitioners should be keenly aware of the cognitive differences between professionals and laypeople, and pay special attention to the topics with significant inconsistency across groups to build consensus and promote vaccination effectively.

Analysis of viral load in different specimen types and serum antibody levels of COVID-19 patients.

BACKGROUND: COVID-19 has caused a global pandemic and the death toll is increasing. However, there is no definitive information regarding the type of clinical specimens that is the best for SARS-CoV-2 detection, the antibody levels in patients with different duration of disease, and the relationship between antibody level and viral load. METHODS: Nasopharyngeal swabs, anal swabs, saliva, blood, and urine specimens were collected from patients with a course of disease ranging from 7 to 69 days. Viral load in different specimen types was measured using droplet digital PCR (ddPCR). Meanwhile, anti-nucleocapsid protein (anti-N) IgM and IgG antibodies and anti-spike protein receptor-binding domain (anti-S-RBD) IgG antibody in all serum samples were tested using ELISA. RESULTS: The positive detection rate in nasopharyngeal swab was the highest (54.05%), followed by anal swab (24.32%), and the positive detection rate in saliva, blood, and urine was 16.22%, 10.81%, and 5.41%, respectively. However, some patients with negative nasopharyngeal swabs had other specimens tested positive. There was no significant correlation between antibody level and days after symptoms onset or viral load. CONCLUSIONS: Other specimens could be positive in patients with negative nasopharyngeal swabs, suggesting that for patients in the recovery period, specimens other than nasopharyngeal swabs should also be tested to avoid false negative results, and anal swabs are recommended. The antibody level had no correlation with days after symptoms onset or the viral load of nasopharyngeal swabs, suggesting that the antibody level may also be affected by other factors.

What triggers online help-seeking retransmission during the COVID-19 period? Empirical evidence from Chinese social media.

The past nine months witnessed COVID-19's fast-spreading at the global level. Limited by medical resources shortage and uneven facilities distribution, online help-seeking becomes an essential approach to cope with public health emergencies for many ordinaries. This study explores the driving forces behind the retransmission of online help-seeking posts. We built an analytical framework that emphasized content characteristics, including information completeness, proximity, support seeking type, disease severity, and emotion of help-seeking messages. A quantitative content analysis was conducted with a probability sample consisting of 727 posts. The results illustrate the importance of individual information completeness, high proximity, instrumental support seeking. This study also demonstrates slight inconformity with the severity principle but stresses the power of anger in help-seeking messages dissemination. As one of the first online help-seeking diffusion analyses in the COVID-19 period, our research provides a reference for constructing compelling and effective help-seeking posts during a particular period. It also reveals further possibilities for harnessing social media's power to promote reciprocal and cooperative actions as a response to this deepening global concern.

Using Reports of Symptoms and Diagnoses on Social Media to Predict COVID-19 Case Counts in Mainland China: Observational Infoveillance Study.

BACKGROUND: Coronavirus disease (COVID-19) has affected more than 200 countries and territories worldwide. This disease poses an extraordinary challenge for public health systems because screening and surveillance capacity is often severely limited, especially during the beginning of the outbreak; this can fuel the outbreak, as many patients can unknowingly infect other people. OBJECTIVE: The aim of this study was to collect and analyze posts related to COVID-19 on Weibo, a popular Twitter-like social media site in China. To our knowledge, this infoveillance study employs the largest, most comprehensive, and most fine-grained social media data to date to predict COVID-19 case counts in mainland China. METHODS: We built a Weibo user pool of 250 million people, approximately half the entire monthly active Weibo user population. Using a comprehensive list of 167 keywords, we retrieved and analyzed around 15 million COVID-19-related posts from our user pool from November 1, 2019 to March 31, 2020. We developed a machine learning classifier to identify "sick posts," in which users report their own or other people's symptoms and diagnoses related to COVID-19. Using officially reported case counts as the outcome, we then estimated the Granger causality of sick posts and other COVID-19 posts on daily case counts. For a subset of geotagged posts (3.10% of all retrieved posts), we also ran separate predictive models for Hubei province, the epicenter of the initial outbreak, and the rest of mainland China. RESULTS: We found that reports of symptoms and diagnosis of COVID-19 significantly predicted daily case counts up to 14 days ahead of official statistics, whereas other COVID-19 posts did not have similar predictive power. For the subset of geotagged posts, we found that the predictive pattern held true for both Hubei province and the rest of mainland China regardless of the unequal distribution of health care resources and the outbreak timeline. CONCLUSIONS: Public social media data can be usefully harnessed to predict infection cases and inform timely responses. Researchers and disease control agencies should pay close attention to the social media infosphere regarding COVID-19. In addition to monitoring overall search and posting activities, leveraging machine learning approaches and theoretical understanding of information sharing behaviors is a promising approach to identify true disease signals and improve the effectiveness of infoveillance.