Safety of COVID-19 vaccine in patients with myasthenia gravis: a self-controlled case series study.

Background: The safety of COVID-19 vaccines has been clarified in clinical trials; however, some immunocompromised patients, such as myasthenia gravis (MG) patients, are still hesitant to receive vaccines. Whether COVID-19 vaccination increases the risk of disease worsening in these patients remains unknown. This study aims to evaluate the risk of disease exacerbation in COVID-19-vaccinated MG patients. Methods: The data in this study were collected from the MG database at Tangdu Hospital, the Fourth Military Medical University, and the Tertiary Referral Diagnostic Center at Huashan Hospital, Fudan University, from 1 April 2022 to 31 October 2022. A self-controlled case series method was applied, and the incidence rate ratios were calculated in the prespecified risk period using conditional Poisson regression. Results: Inactivated COVID-19 vaccines did not increase the risk of disease exacerbation in MG patients with stable disease status. A few patients experienced transient disease worsening, but the symptoms were mild. It is noted that more attention should be paid to thymoma-related MG, especially within 1 week after COVID-19 vaccination. Conclusion: COVID-19 vaccination has no long-term impact on MG relapse.

Mitochondria-Targeted Fluorescent Nanoparticles with Large Stokes Shift for Long-Term BioImaging.

Mitochondria (MITO) play a significant role in various physiological processes and are a key organelle associated with different human diseases including cancer, diabetes mellitus, atherosclerosis, Alzheimer's disease, etc. Thus, detecting the activity of MITO in real time is becoming more and more important. Herein, a novel class of amphiphilic aggregation-induced emission (AIE) active probe fluorescence (AC-QC nanoparticles) based on a quinoxalinone scaffold was developed for imaging MITO. AC-QC nanoparticles possess an excellent ability to monitor MITO in real-time. This probe demonstrated the following advantages: (1) lower cytotoxicity; (2) superior photostability; and (3) good performance in long-term imaging in vitro. Each result of these indicates that self-assembled AC-QC nanoparticles can be used as effective and promising MITO-targeted fluorescent probes.

Exploring the Influencing Factors of COVID-19 Vaccination Willingness among Young Adults in China

Vaccine uptake is considered as one of the most effective methods of defending against COVID-19 (coronavirus disease 2019). However, many young adults are hesitant regarding COVID-19 vaccines, and they actually play an important role in virus transmission. Based on a multi-theory model, this study aims to explore the influencing factors related to COVID-19 vaccine willingness among young adults in China. Using semi-structured interviews, this study explored the factors that would motivate young adults with vaccine hesitancy to get the COVID-19 vaccine. Thematic analysis was used to analyze the interview data with topic modeling as a complementarity method. After comparing the differences and similarities of results generated by thematic analysis and topic modeling, this study ultimately identified ten key factors related to COVID-19 vaccination intention, including the effectiveness and safety of vaccines, application range of vaccine, etc. This study combined thematic analysis with machine learning and provided a comprehensive and nuanced picture of facilitating factors for COVID-19 vaccine uptake among Chinese young adults. Results may be taken as potential themes for authorities and public health workers in vaccination campaigns.

Knowledge mapping of global trends for myasthenia gravis development: A bibliometrics analysis

Background Myasthenia gravis (MG) is an autoimmune disease with acquired neuromuscular junction transmission disorders. In the last two decades, various pathogenesis, application of immunosuppressive agents, and targeted immunotherapy have been significant events. However, extracting the most critical information from complex events is very difficult to guide clinical work. Therefore, we used bibliometrics to summarize and look forward. Methods Science Citation Index Expanded (SCI-E) from the Web of Science Core Collection (WoSCC) database was identified as a source of material for obtaining MG-related articles. Scimago Graphica, CiteSpace, VOSviewer, and bibliometrix were utilized for bibliometric analysis. Knowledge network graphs were constructed and visualized;countries, institutions, authors, journals, references, and keywords were evaluated. In addition, GraphPad Prism and Microsoft Excel 365 were applied for statistical analysis. Results As of October 25, 2022, 9,970 original MG-related articles were used for the bibliometric analysis;the cumulative number of citations to these articles was 236,987, with an H-index of 201. The United States ranked first in terms of the number of publications (2,877) and H-index (134). Oxford has the highest H-index (67), and Udice French Research University has the highest number of publications (319). The author with the highest average number of citations (66.19), publications (151), and H-index (53) was Vincent A. 28 articles have remained in an explosive period of citations. The final screening yielded predictive keywords related to clinical trials and COVID-19. Conclusion We conducted a bibliometric analysis of 9,970 original MG-related articles published between 1966 and 2022. Ultimately, we found that future MG research hotspots include two major parts: (1) studies directly related to MG disease itself: clinical trials of various targeted biological agents;the relationship between biomarkers and therapeutic decisions, pathogenesis and outcome events, ultimately serving individualized management or precision therapy;(2) studies related to MG and COVID-19: different variants of COVID-19 (e.g., Omicron) on MG adverse outcome events;assessment of the safety of different COVID-19 vaccines for different subtypes of MG.

Research progress on specific and non-specific immune effects of BCG and the possibility of BCG protection against COVID-19.

Bacille Calmette-Guérin (BCG) is the only approved vaccine for tuberculosis (TB) prevention worldwide. BCG has an excellent protective effect on miliary tuberculosis and tuberculous meningitis in children or infants. Interestingly, a growing number of studies have shown that BCG vaccination can induce nonspecific and specific immunity to fight against other respiratory disease pathogens, including SARS-CoV-2. The continuous emergence of variants of SARS-CoV-2 makes the protective efficiency of COVID-19-specific vaccines an unprecedented challenge. Therefore, it has been hypothesized that BCG-induced trained immunity might protect against COVID-19 infection. This study comprehensively described BCG-induced nonspecific and specific immunity and the mechanism of trained immunity. In addition, this study also reviewed the research on BCG revaccination to prevent TB, the impact of BCG on other non-tuberculous diseases, and the clinical trials of BCG to prevent COVID-19 infection. These data will provide new evidence to confirm the hypotheses mentioned above.

Exploring the Influencing Factors of COVID-19 Vaccination Willingness among Young Adults in China.

Vaccine uptake is considered as one of the most effective methods of defending against COVID-19 (coronavirus disease 2019). However, many young adults are hesitant regarding COVID-19 vaccines, and they actually play an important role in virus transmission. Based on a multi-theory model, this study aims to explore the influencing factors related to COVID-19 vaccine willingness among young adults in China. Using semi-structured interviews, this study explored the factors that would motivate young adults with vaccine hesitancy to get the COVID-19 vaccine. Thematic analysis was used to analyze the interview data with topic modeling as a complementarity method. After comparing the differences and similarities of results generated by thematic analysis and topic modeling, this study ultimately identified ten key factors related to COVID-19 vaccination intention, including the effectiveness and safety of vaccines, application range of vaccine, etc. This study combined thematic analysis with machine learning and provided a comprehensive and nuanced picture of facilitating factors for COVID-19 vaccine uptake among Chinese young adults. Results may be taken as potential themes for authorities and public health workers in vaccination campaigns.

Knowledge mapping of global trends for myasthenia gravis development: A bibliometrics analysis.

Background: Myasthenia gravis (MG) is an autoimmune disease with acquired neuromuscular junction transmission disorders. In the last two decades, various pathogenesis, application of immunosuppressive agents, and targeted immunotherapy have been significant events. However, extracting the most critical information from complex events is very difficult to guide clinical work. Therefore, we used bibliometrics to summarize and look forward. Methods: Science Citation Index Expanded (SCI-E) from the Web of Science Core Collection (WoSCC) database was identified as a source of material for obtaining MG-related articles. Scimago Graphica, CiteSpace, VOSviewer, and bibliometrix were utilized for bibliometric analysis. Knowledge network graphs were constructed and visualized; countries, institutions, authors, journals, references, and keywords were evaluated. In addition, GraphPad Prism and Microsoft Excel 365 were applied for statistical analysis. Results: As of October 25, 2022, 9,970 original MG-related articles were used for the bibliometric analysis; the cumulative number of citations to these articles was 236,987, with an H-index of 201. The United States ranked first in terms of the number of publications (2,877) and H-index (134). Oxford has the highest H-index (67), and Udice French Research University has the highest number of publications (319). The author with the highest average number of citations (66.19), publications (151), and H-index (53) was Vincent A. 28 articles have remained in an explosive period of citations. The final screening yielded predictive keywords related to clinical trials and COVID-19. Conclusion: We conducted a bibliometric analysis of 9,970 original MG-related articles published between 1966 and 2022. Ultimately, we found that future MG research hotspots include two major parts: (1) studies directly related to MG disease itself: clinical trials of various targeted biological agents; the relationship between biomarkers and therapeutic decisions, pathogenesis and outcome events, ultimately serving individualized management or precision therapy; (2) studies related to MG and COVID-19: different variants of COVID-19 (e.g., Omicron) on MG adverse outcome events; assessment of the safety of different COVID-19 vaccines for different subtypes of MG.

Dumbbell-type triplex molecular switch-based logic molecular assays of SARS-CoV-2.

Accurate detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is of great importance to control the COVID-19 pandemic. The gold standard assays for COVID-19 diagnostics are mainly based on separately detecting open reading frame 1ab (ORF1ab) and nucleoprotein (N) genes by RT-PCR. However, the current approaches often obtain false positive-misdiagnose caused by cross-contamination or undesired amplification. To address this issue, herein, we proposed a dumbbell-type triplex molecular switch (DTMS)-based, logic-gated strategy for high-fidelity SARS-CoV-2 RNA detection. The DTMS consists of a triple-helical stem region and two-loop regions for recognizing the ORF1ab and N genes of SARS-CoV-2. Only when the ORF1ab and N gene are concurrent, DTMS experiences a structural rearrangement, thus, bringing the two pyrenes into spacer proximity and leading to a new signal readout. This strategy allows detecting SARS-CoV-2 RNA with a detection limit of 1.3 nM, independent of nucleic acid amplification, holding great potential as an indicator probe for screening of COVID-19 and other population-wide epidemics.

Emerging role of the cGAS-STING signaling pathway in autoimmune diseases: Biologic function, mechanisms and clinical prospection.

The cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) signaling pathway, as vital component of innate immune system, acts a vital role in distinguishing invasive pathogens and cytosolic DNA. Cytosolic DNA sensor cGAS first binds to cytosolic DNA and catalyzes synthesis of cyclic guanosine monophosphate-adenosine monophosphate (cGAMP), which is known as the second messenger. Next, cGAMP activates the adaptor protein STING, triggering a molecular chain reaction to stimulate cytokines including interferons (IFNs). Recently, many researches have revealed that the regulatory role of cGAS-STING signaling pathway in autoimmune diseases (AIDs) such as Rheumatoid arthritis (RA), Aicardi Goutières syndrome (AGS) and systemic lupus erythematosus (SLE). Moreover, accumulated evidence have showed inhibition of the cGAS-STING signaling pathway could remarkably suppress the joint swelling and inflammatory cell infiltration in RA mice. Therefore, in this review, we describe the molecular properties, biologic function and mechanisms of the cGAS-STING signaling pathway in AIDs. In addition, potential clinical applications especially selective small molecule inhibitors targeting the cGAS-STING signaling pathway are also discussed.

Acute Hepatitis of Unknown Origin in Children: Early Observations from the 2022 Outbreak

Recent reports of acute hepatitis of unknown origin in previously healthy children have been increasing worldwide. The main characteristics of the affected children were jaundice and gastrointestinal symptoms. Their serum aminotransaminase levels were above 500 IU/L, with negative tests for hepatitis viruses A–E. By 31 May 2022, the outbreak had affected over 800 children under the age of 16 years in more than 40 countries, resulting in acute liver failure in approximately 10%, including at least 21 deaths and 38 patients requiring liver transplantation. There was still no confirmed cause or causes, although there were several different working hypotheses, such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), adenovirus serotype 41, or SARS-CoV-2 superantigen-mediated immune cell activation. Here, we review early observations of the 2022 outbreak which may inform diagnosis, treatment, and prevention in the context of an overlapping COVID-19 pandemic. Graphical

Effects of mesenchymal stromal cell-derived extracellular vesicles in acute respiratory distress syndrome (ARDS): Current understanding and future perspectives.

Acute respiratory distress syndrome (ARDS) is a devastating and life-threatening syndrome that results in high morbidity and mortality. Current pharmacologic treatments and mechanical ventilation have limited value in targeting the underlying pathophysiology of ARDS. Mesenchymal stromal cells (MSCs) have shown potent therapeutic advantages in experimental and clinical trials through direct cell-to-cell interaction and paracrine signaling. However, safety concerns and the indeterminate effects of MSCs have resulted in the investigation of MSC-derived extracellular vesicles (MSC-EVs) due to their low immunogenicity and tumorigenicity. Over the past decades, soluble proteins, microRNAs, and organelles packaged in EVs have been identified as efficacious molecules to orchestrate nearby immune responses, which attenuate acute lung injury by facilitating pulmonary epithelium repair, reducing acute inflammation, and restoring pulmonary vascular leakage. Even though MSC-EVs possess similar bio-functional effects to their parental cells, there remains existing barriers to employing this alternative from bench to bedside. Here, we summarize the current established research in respect of molecular mechanisms of MSC-EV effects in ARDS and highlight the future challenges of MSC-EVs for clinical application.

Twitter Discussions and Emotions About the COVID-19 Pandemic: Machine Learning Approach.

BACKGROUND: It is important to measure the public response to the COVID-19 pandemic. Twitter is an important data source for infodemiology studies involving public response monitoring. OBJECTIVE: The objective of this study is to examine COVID-19-related discussions, concerns, and sentiments using tweets posted by Twitter users. METHODS: We analyzed 4 million Twitter messages related to the COVID-19 pandemic using a list of 20 hashtags (eg, "coronavirus," "COVID-19," "quarantine") from March 7 to April 21, 2020. We used a machine learning approach, Latent Dirichlet Allocation (LDA), to identify popular unigrams and bigrams, salient topics and themes, and sentiments in the collected tweets. RESULTS: Popular unigrams included "virus," "lockdown," and "quarantine." Popular bigrams included "COVID-19," "stay home," "corona virus," "social distancing," and "new cases." We identified 13 discussion topics and categorized them into 5 different themes: (1) public health measures to slow the spread of COVID-19, (2) social stigma associated with COVID-19, (3) COVID-19 news, cases, and deaths, (4) COVID-19 in the United States, and (5) COVID-19 in the rest of the world. Across all identified topics, the dominant sentiments for the spread of COVID-19 were anticipation that measures can be taken, followed by mixed feelings of trust, anger, and fear related to different topics. The public tweets revealed a significant feeling of fear when people discussed new COVID-19 cases and deaths compared to other topics. CONCLUSIONS: This study showed that Twitter data and machine learning approaches can be leveraged for an infodemiology study, enabling research into evolving public discussions and sentiments during the COVID-19 pandemic. As the situation rapidly evolves, several topics are consistently dominant on Twitter, such as confirmed cases and death rates, preventive measures, health authorities and government policies, COVID-19 stigma, and negative psychological reactions (eg, fear). Real-time monitoring and assessment of Twitter discussions and concerns could provide useful data for public health emergency responses and planning. Pandemic-related fear, stigma, and mental health concerns are already evident and may continue to influence public trust when a second wave of COVID-19 occurs or there is a new surge of the current pandemic.

Public emotion responses during COVID-19 in China on social media: An observational study

Abstract COVID-19 (Corona Virus Disease 2019) has attacked many countries around world and caused profound impacts on public life. The outbreak of pandemic and other relevant factors are considered to cause emotion responses of residents. And the emotion responses of individuals are crucial for the execution of the prevention and control measures. By analyzing the linguistic features of posts on social media, this study aims to explore the change of public emotion responses during COVID-19 in China. We sampled 22,423 Weibo users and collected their Weibo posts by provincial area each day from January 1st, 2020 to April 18th, 2020. Next, we extracted linguistic features from posts according to the emotion-related dictionary. Based on important news and information released by the national and international organizations of public health, we divided the period from January 1st, 2020 to April 18th, 2020 into four stages (the initial period, the outbreak period, the stable period, and the prevention and control period). Then we gathered linguistic features by stage. After that, ANOVA was performed to examine the differences among these four stages. The results showed that the frequencies of 11 word categories showed significant differences among four stages, including fear, disappointment, guilt, missing, anger, panic, blessing, faith, love, praise, and surprise. The uses of several negative emotion words, such as fear, disappointment, guilt, and anger, increased saliently in the outbreak period compared with the initial period. Besides, panic words decreased significantly in the prevention and control period compared with the outbreak period. However, missing words were used more in the prevention and control period than other three periods. Moreover, people expressed more faith words and less love words in the outbreak period than the initial periods. Besides, people used more blessing words in the outbreak period compared with the stable period and prevention and control period. And praise words were used more in the outbreak period and the stable period compared with the initial period. The frequency of surprise words was significantly low only in the initial period. This study contributed to the understanding of public emotion responses during COVID-19, and had implications for the evidence-based execution of prevention and control measures.

Pattern of COVID-19 in Sichuan province, China: A descriptive epidemiological analysis.

This study described the epidemiology of 487 confirmed coronavirus disease 2019 (COVID-19) cases in Sichuan province of China, and aimed to provide epidemiological evidence to support public health decision making. Epidemiological information of 487 COVID-19 cases were collected from the official websites of 21 districts (including 18 cities, 3 autonomous prefecture) health commissions within Sichuan between 21st of January 2020 to 17th of April 2020. We focus on the single-day diagnosis, demographics (gender and age), regional distribution, incubation period and symptoms. The number of single-day confirmed COVID-19 cases reach a peak on January 29 (33 cases), and then decreased. Chengdu (121 cases), Dazhou (39 cases) Nanchong (37 cases) and Ganzi Tibetan Autonomous Prefecture (78 cases) contributed 275 cases (56.5% of the total cases) of Sichuan province. The median age of patients was 44.0 years old and 52.6% were male. The history of living in or visiting Hubei, close contact, imported and unknown were 170 cases (34.9%), 136 cases (27.9%), 21 cases (4.3%) and 160 cases (32.9%) respectively. The interval from the onset of initial symptoms to laboratory diagnosis was 4.0 days in local cases, while that of imported cases was 4.5 days. The most common symptoms of illness onset were fever (71.9%) and cough (35.9%). The growth rate of COVID-19 in Sichuan has significantly decreased. New infected cases have shifted from the living in or visiting Wuhan and close contact to imported. It is necessary to closely monitor the physical condition of imported cases.

Examining the Impact of COVID-19 Lockdown in Wuhan and Lombardy: A Psycholinguistic Analysis on Weibo and Twitter.

Many countries are taking strict quarantine policies to prevent the rapid spread of COVID-19 (Corona Virus Disease 2019) around the world, such as city lockdown. Cities in China and Italy were locked down in the early stage of the pandemic. The present study aims to examine and compare the impact of COVID-19 lockdown on individuals' psychological states in China and Italy. We achieved the aim by (1) sampling Weibo users (geo-location = Wuhan, China) and Twitter users (geo-location = Lombardy, Italy); (2) fetching all the users' published posts two weeks before and after the lockdown in each region (e.g., the lockdown date of Wuhan was 23 January 2020); (3) extracting the psycholinguistic features of these posts using the Simplified Chinese and Italian version of Language Inquiry and Word Count (LIWC) dictionary; and (4) conducting Wilcoxon tests to examine the changes in the psycholinguistic characteristics of the posts before and after the lockdown in Wuhan and Lombardy, respectively. Results showed that individuals focused more on "home", and expressed a higher level of cognitive process after a lockdown in both Wuhan and Lombardy. Meanwhile, the level of stress decreased, and the attention to leisure increased in Lombardy after the lockdown. The attention to group, religion, and emotions became more prevalent in Wuhan after the lockdown. Findings provide decision-makers timely evidence on public reactions and the impacts on psychological states in the COVID-19 context, and have implications for evidence-based mental health interventions in two countries.

A child with household transmitted COVID-19.

BACKGROUND: Although people of all ages are susceptible to the novel coronavirus infection, which is presently named "Coronavirus Disease 2019" (COVID-19), there has been relatively few cases reported among children. Therefore, it is necessary to understand the clinical characteristics of COVID-19 in children and the differences from adults. CASE PRESENTATION: We report one pediatric case of COVID-19. A 14-month-old boy was admitted to the hospital with a symptom of fever, and was diagnosed with a mild form of COVID-19. The child's mother and grandmother also tested positive for SARS-CoV-2 RNA. However, the lymphocyte counts were normal. The chest computed tomography (CT) revealed scattered ground glass opacities in the right lower lobe close to the pleura and resorption after the treatment. The patient continued to test positive for SARS-CoV-2 RNA in the nasopharyngeal swabs and stool at 17 days after the disappearance of symptoms. CONCLUSION: The present pediatric case of COVID-19 was acquired through household transmission, and the symptoms were mild. Lymphocyte counts did not significantly decrease. The RNA of SARS-CoV-2 in stool and nasopharyngeal swabs remained positive for an extended period of time after the disappearance of symptoms. This suggests that attention should be given to the potential contagiousness of pediatric COVID-19 cases after clinical recovery.