College Graduates' Negative Life Experiences, Coping Strategies and Enlightenment During the COVID-19 Pandemic: A Qualitative Study in China.

Objective: The current study aimed to explore comprehensively college graduates' negative life experiences, coping strategies, and enlightenment in a qualitative way. Methods: This was a qualitative study. Purposeful sampling was used to select 31 college graduates majoring in various subjects from a Chinese University. The one-on-one semi-structured interviews were conducted online through Tencent QQ/WeChat and were recorded and transcribed verbatim. A phenomenological approach was used to guide this research in the data collection and analysis. Thematic analysis was used to identify themes across interviews around their negative life experiences, coping strategies, and enlightenment. Results: College graduates' negative life experiences were mainly focused on three aspects: negative work experience (eg, lack of adaptation, busy schedule, low salary), negative personal life experience (eg, multiple pressure, psychological problems, the hardship of life), and negative social life experience (eg, the incomprehension of those around you, complex interpersonal relationship, social complexity). The coping strategies they used can be classified into two categories: emotion-focused strategies (eg, accepting reality, self-persuasion, keeping a positive attitude), and problem-focused strategies (eg, goal-setting, asking for help to solve the problem, persistence). As for life enlightenment, six themes emerged: accept life, strive to life, love life, cherish life, recognize life, and learn to live. Conclusion: College graduates' negative experiences came from multiple levels, and they use multiple coping strategies to deal with the challenges. Our results provide important guidance for researchers and policymakers to design effective and targeted intervention programs to improve college graduates' coping abilities in response to negative life experiences and help them better transition from school to work. Specifically, future research and intervention to promote college graduates' mental health should target various social-ecological levels, focus on promoting coping from an ecological perspective, as well as facilitate post-traumatic growth to help them grow from negative life experiences and cope positively.

Retrospect of the Two-Year Debate: What Fuels the Evolution of SARS-CoV-2: RNA Editing or Replication Error?

Mutation is one of the mechanisms of the evolutionary divergence of an organism. Under this global COVID-19 pandemic, the fast evolution of SARS-CoV-2 became one of the most worrying issues. Some researchers believed that the hosts' RNA deamination systems (APOBECs and ADARs) are the major source of mutations and have driven the evolution of SARS-CoV-2. However, apart from RNA editing, the RDRP (RNA-dependent RNA polymerase)-mediated replication errors may also contribute to the mutation of SARS-CoV-2 (just like the single-nucleotide polymorphisms/variations in eukaryotes caused by DNA replication errors). Unfortunately, it is technically unable to distinguish RNA editing and replication errors (SNPs) in this RNA virus. Here comes a fundamental question: we indeed observed the fast evolution of SARS-CoV-2, but what exactly fuels its evolution: RNA editing or replication errors? This debate lasts for 2 years. In this piece, we will retrospect the 2-year debate on RNA editing versus SNPs.

Classification of Coronavirus Spike Proteins by Deep-Learning-Based Raman Spectroscopy and its Interpretative Analysis.

The outbreak of COVID-19 has spread worldwide, causing great damage to the global economy. Raman spectroscopy is expected to become a rapid and accurate method for the detection of coronavirus. A classification method of coronavirus spike proteins by Raman spectroscopy based on deep learning was implemented. A Raman spectra dataset of the spike proteins of five coronaviruses (including MERS-CoV, SARS-CoV, SARS-CoV-2, HCoVHKU1, and HCoV-OC43) was generated to establish the neural network model for classification. Even for rapidly acquired spectra with a low signal-to-noise ratio, the average accuracy exceeded 97%. An interpretive analysis of the classification results of the neural network was performed, which indicated that the differences in spectral characteristics captured by the neural network were consistent with the experimental analysis. The interpretative analysis method provided a valuable reference for identifying complex Raman spectra using deep-learning techniques. Our approach exhibited the potential to be applied in clinical practice to identify COVID-19 and other coronaviruses, and it can also be applied to other identification problems such as the identification of viruses or chemical agents, as well as in industrial areas such as oil and gas exploration.

Classification of Coronavirus Spike Proteins by Deep-Learning-Based Raman Spectroscopy and its Interpretative Analysis

The outbreak of COVID-19 has spread worldwide, causing great damage to the global economy. Raman spectroscopy is expected to become a rapid and accurate method for the detection of coronavirus. A classification method of coronavirus spike proteins by Raman spectroscopy based on deep learning was implemented. A Raman spectra dataset of the spike proteins of five coronaviruses (including MERS-CoV, SARS-CoV, SARS-CoV-2, HCoVHKU1, and HCoV-OC43) was generated to establish the neural network model for classification. Even for rapidly acquired spectra with a low signal-to-noise ratio, the average accuracy exceeded 97%. An interpretive analysis of the classification results of the neural network was performed, which indicated that the differences in spectral characteristics captured by the neural network were consistent with the experimental analysis. The interpretative analysis method provided a valuable reference for identifying complex Raman spectra using deep-learning techniques. Our approach exhibited the potential to be applied in clinical practice to identify COVID-19 and other coronaviruses, and it can also be applied to other identification problems such as the identification of viruses or chemical agents, as well as in industrial areas such as oil and gas exploration.

SARS-CoV-2 Spike Stem Protein Nanoparticles Elicited Broad ADCC and Robust Neutralization against Variants in Mice.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the global pandemic. The virus is rapidly evolving, characterized by the emergence of several major variants. Stable prefusion spike protein (Pre) is the immunogen in current vaccines but is limited in protecting against different variants. Here, the immune responses induced by the relatively conserved stem subunit (S2) of spike protein versus Pre are investigated. Pre generates the most robust neutralization responses against SARS-CoV-2 variants in vesicular stomatitis virus pseudovirus-based assessment but elicits less antibody-dependent cellular cytotoxicity (ADCC) activity than S2. By contrast, S2 induces the most balanced immunoglobulin G (IgG) antibodies with potent and broad ADCC activity although produces weaker neutralization. The immunogenicity of S2 and Pre improves by incorporating the two proteins into double-layered protein nanoparticles. The resulting protein nanoparticles Pre/S2 elicit higher neutralizing antibodies than Pre alone, and stronger ADCC than S2 alone. Moreover, nanoparticles produce more potent and balanced serum IgG antibodies than the corresponding soluble protein mixture, and the immune responses are sustained for at least four months after the immunization. Thus, the double-layered protein nanoparticles have the potential to be developed into broader SARS-CoV-2 vaccines with excellent safety profiles.

Promoting COVID-19 Vaccination Using the Health Belief Model: Does Information Acquisition from Divergent Sources Make a Difference?

As a promising approach to stop the escalation of the pandemic, COVID-19 vaccine promotion is becoming a challenging task for authorities worldwide. The purpose of this study was to identify the effective sources for disseminating information on the COVID-19 vaccine to promote individuals' behavioral intention to take the vaccine. Based on the Health Belief Model (HBM), this study illustrated the mechanism of how COVID-19 information acquisition from different sources was transformed into vaccination intentions via health beliefs. Using an online survey in China, the structural equation model results revealed that perceived benefits and cues to action were positively associated with COVID-19 vaccination intentions, and perceived barriers were negatively related to the intentions. However, perceived susceptibility and perceived severity had no significant relationships with the intentions. Moreover, the findings unveiled differences in the effects of acquiring information via multiple sources among traditional media, new media, and interpersonal interactions. Notably, new media and interpersonal interactions were more salient in promoting vaccination intention via health beliefs, compared with traditional media. The findings from this study will benefit health officials in terms of utilizing different information sources in vaccine programs.

Constructing high-accuracy theoretical Raman spectra of SARS-CoV-2 spike proteins based on a large fragment method.

In order to control COVID-19, rapid and accurate detection of the pathogenic, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is an urgent task. The target spike proteins of SARS-CoV-2 have been detected experimentally via Raman spectroscopy. However, there lacks high-accuracy theoretical Raman spectra of the spike proteins to as a standard reference for the clinic diagnostic purpose. In this paper, we propose a large fragment method to construct the high-precision Raman spectra for the spike proteins. The large fragment method not only reduces the calculation error but also improves the accuracy of the protein Raman spectra by completely calculating the interactions within the large fragment. The Pearson correlation coefficient of theoretical Raman spectra is greater than 0.929 or more. Compared with the experimental spectra, the characteristic patterns are easily visible. This work provides a detection standard for the spike proteins which shall bring a step closer to the fast recognition of SARS-CoV-2 via Raman spectroscopy method.

Promoting COVID-19 Vaccination Using the Health Belief Model: Does Information Acquisition from Divergent Sources Make a Difference?

As a promising approach to stop the escalation of the pandemic, COVID-19 vaccine promotion is becoming a challenging task for authorities worldwide. The purpose of this study was to identify the effective sources for disseminating information on the COVID-19 vaccine to promote individuals' behavioral intention to take the vaccine. Based on the Health Belief Model (HBM), this study illustrated the mechanism of how COVID-19 information acquisition from different sources was transformed into vaccination intentions via health beliefs. Using an online survey in China, the structural equation model results revealed that perceived benefits and cues to action were positively associated with COVID-19 vaccination intentions, and perceived barriers were negatively related to the intentions. However, perceived susceptibility and perceived severity had no significant relationships with the intentions. Moreover, the findings unveiled differences in the effects of acquiring information via multiple sources among traditional media, new media, and interpersonal interactions. Notably, new media and interpersonal interactions were more salient in promoting vaccination intention via health beliefs, compared with traditional media. The findings from this study will benefit health officials in terms of utilizing different information sources in vaccine programs.

RAPID: A Rep-Seq Dataset Analysis Platform With an Integrated Antibody Database.

The antibody repertoire is a critical component of the adaptive immune system and is believed to reflect an individual's immune history and current immune status. Delineating the antibody repertoire has advanced our understanding of humoral immunity, facilitated antibody discovery, and showed great potential for improving the diagnosis and treatment of disease. However, no tool to date has effectively integrated big Rep-seq data and prior knowledge of functional antibodies to elucidate the remarkably diverse antibody repertoire. We developed a Rep-seq dataset Analysis Platform with an Integrated antibody Database (RAPID; https://rapid.zzhlab.org/), a free and web-based tool that allows researchers to process and analyse Rep-seq datasets. RAPID consolidates 521 WHO-recognized therapeutic antibodies, 88,059 antigen- or disease-specific antibodies, and 306 million clones extracted from 2,449 human IGH Rep-seq datasets generated from individuals with 29 different health conditions. RAPID also integrates a standardized Rep-seq dataset analysis pipeline to enable users to upload and analyse their datasets. In the process, users can also select set of existing repertoires for comparison. RAPID automatically annotates clones based on integrated therapeutic and known antibodies, and users can easily query antibodies or repertoires based on sequence or optional keywords. With its powerful analysis functions and rich set of antibody and antibody repertoire information, RAPID will benefit researchers in adaptive immune studies.

Authoritarian responsiveness and political attitudes during COVID-19: evidence from Weibo and a survey experiment

How do citizens react to authoritarian responsiveness? To investigate this question, we study how Chinese citizens reacted to a novel government initiative which enabled social media users to publicly post requests for COVID-related medical assistance. To understand the effect of this initiative on public perceptions of government effectiveness, we employ a two-part empirical strategy. First, we conduct a survey experiment in which we directly expose subjects to real help-seeking posts, in which we find that viewing posts did not improve subjects’ ratings of government effectiveness, and in some cases worsened them. Second, we analyze over 10,000 real-world Weibo posts to understand the political orientation of the discourse around help-seekers. We find that negative and politically critical posts far outweighed positive and laudatory posts, complementing our survey experiment results. To contextualize our results, we develop a theoretic framework to understand the effects of different types of responsiveness on citizens’ political attitudes. We suggest that citizens’ negative reactions in this case were primarily influenced by public demands for help, which illuminated existing problems and failures of governance. [ABSTRACT FROM AUTHOR] Copyright of Chinese Sociological Review is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Global view on virus infection in non-human primates and implications for public health and wildlife conservation.

Viruses can be transmitted from animals to humans (and vice versa) and across animal species. As such, host-virus interactions and transmission have attracted considerable attention. Non-human primates (NHPs), our closest evolutionary relatives, are susceptible to human viruses and certain pathogens are known to circulate between humans and NHPs. Here, we generated global statistics on VI-NHPs based on a literature search and public data mining. In total, 140 NHP species from 12 families are reported to be infected by 186 DNA and RNA virus species, 68.8% of which are also found in humans, indicating high potential for crossing species boundaries. The top 10 NHP species with high centrality in the NHP-virus network include two great apes (Pan troglodytes, Pongo pygmaeus) and eight Old World monkeys (Macaca mulatta, M. fascicularis, M. leonina, Papio cynocephalus, Cercopithecus ascanius, C. erythrotis, Chlorocebus aethiops, and Allochrocebus lhoesti). Given the wide distribution of Old World monkeys and their frequent contact with humans, there is a high risk of virus circulation between humans and such species. Thus, we suggest recurring epidemiological surveillance of NHPs, specifically Old World monkeys that are in frequent contact with humans, and other effective measures to prevent potential circulation and transmission of viruses. Avoidance of false positives and sampling bias should also be a focus in future work.

Acute graft-versus-host disease after liver transplantation in a close contact with COVID-19: A case report.

Acute graft-versus-host disease (aGVHD) is a rare complication after liver transplantation that characterized by high mortality. We presented a case of aGVHD after orthotopic liver transplantation (OLT) for hepatocellular carcinoma (HCC). The patient suffered from fever, oral ulcer, rashes and diarrhea and had a co-infection with Cytomegalovirus (CMV). Short tandem repeat (STR) analysis for cluster of differentiation (CD3) cells and skin biopsy indicated aGVHD. His regimens included high dose of steroids, ruxolitinib, basiliximab, local liver radiotherapy and antibiotics prophylaxis, with the withdrawal of tacrolimus and MMF. Unfortunately, he developed an acute rejection followed by cytomegalovirus infection and lung infection. Soon afterwards he was sent to "isolation ward" due to high suspicion for clinical coronavirus disease 2019 (COVID-19). Fortunately, He was excluded from COVID-19 after nucleic acid and antibody tests. Though closely contact with other COVID-19 patients for a month, the patient was not affected with COVID-19 through his careful protective measures. Finally, the patient recovered after antiviral and antifungal treatment. To our knowledge, this is the first case report of a patient recovered from aGVHD as a close contact.

On-Site Detection of SARS-CoV-2 Antigen by Deep Learning-Based Surface-Enhanced Raman Spectroscopy and Its Biochemical Foundations.

A rapid, on-site, and accurate SARS-CoV-2 detection method is crucial for the prevention and control of the COVID-19 epidemic. However, such an ideal screening technology has not yet been developed for the diagnosis of SARS-CoV-2. Here, we have developed a deep learning-based surface-enhanced Raman spectroscopy technique for the sensitive, rapid, and on-site detection of the SARS-CoV-2 antigen in the throat swabs or sputum from 30 confirmed COVID-19 patients. A Raman database based on the spike protein of SARS-CoV-2 was established from experiments and theoretical calculations. The corresponding biochemical foundation for this method is also discussed. The deep learning model could predict the SARS-CoV-2 antigen with an identification accuracy of 87.7%. These results suggested that this method has great potential for the diagnosis, monitoring, and control of SARS-CoV-2 worldwide.

Low serum calcium: a new, important indicator of COVID-19 patients from mild/moderate to severe/critical.

BACKGROUND:  Coronavirus disease 2019 (COVID-19) virus is still spreading, finding out the initial hits of viral infection is important to minimize the mild/moderate population, prevent disease aggravation and organs dysfunction. Objective: We investigated COVID-19 patients with different serum calcium levels. DESIGN:  We checked the serum calcium level of the patients based on days after symptom onset as well as the severity of COVID-19. We also checkeed multi-organ injuries and immune cytokines level in their blood. RESULTS:  Both mild/moderate and severe critical cases we observed showed low calcium level in the early stage of viral infection, while the severe/critical cases showed significant lower calcium level than mild/moderate cases in the early stage. We also found that low calcium level related to severe/critical multi-organ injuries especially in the mild/moderate population. Proinflammatory cytokine IL-6 also correlated to calcium change in both mild/moderate and severe/critical cases. CONCLUSIONS:  Our finding indicates that calcium balance is a primal hit of COVID-19 and a biomarker of clinical severity at the beginning of symptom onset. Calcium is closely associated with virus-associated multiple organ injuryes and the increase of inflammatory cytokines. Our results provide a new, important indicator of COVID-19 patients from mild/moderate to severe/critical: serum calcium.

Limited role for meteorological factors on the variability in COVID-19 incidence: A retrospective study of 102 Chinese cities.

While many studies have focused on identifying the association between meteorological factors and the activity of COVID-19, we argue that the contribution of meteorological factors to a reduction of the risk of COVID-19 was minimal when the effects of control measures were taken into account. In this study, we assessed how much variability in COVID-19 activity is attributable to city-level socio-demographic characteristics, meteorological factors, and the control measures imposed. We obtained the daily incidence of COVID-19, city-level characteristics, and meteorological data from a total of 102 cities situated in 27 provinces/municipalities outside Hubei province in China from 1 January 2020 to 8 March 2020, which largely covers almost the first wave of the epidemic. Generalized linear mixed effect models were employed to examine the variance in the incidence of COVID-19 explained by different combinations of variables. According to the results, including the control measure effects in a model substantially raised the explained variance to 45%, which increased by >40% compared to the null model that did not include any covariates. On top of that, including temperature and relative humidity in the model could only result in < 1% increase in the explained variance even though the meteorological factors showed a statistically significant association with the incidence rate of COVID-19. In conclusion, we showed that very limited variability of the COVID-19 incidence was attributable to meteorological factors. Instead, the control measures could explain a larger proportion of variance.

Immunology of Transplant Patients with SARS-CoV-2 Infection: Transmission, Immune Response, and Therapeutic Strategy.

Coronavirus disease (COVID-19), caused by the virus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had a huge impact on global human health and was declared a worldwide distributed pandemic by the World Health Organization. SARS-CoV-2 has strong transmission and pathogenicity; so far, there are more than 16,000,000 cases of infections around the world and COVID-19 has caused more than 656,000 deaths. Current data indicate risk factors of patients infected by SARS-CoV-2 are older age, male sex, and chronic underlying diseases such as hypertension, diabetes, cardiovascular diseases, chronic respiratory disease, and cancer. After the outbreak of COVID-19, concern whether transplant patients are more susceptible to SARS-CoV-2 has been raised. It is inconclusive whether patients after transplantation on chronic immunosuppressive therapy are more susceptible to developing a more severe disease course. There is limited literature mainly aimed at post-transplantation populations whose immunity was suppressive before the disease occurred. Therefore, we attempted to systematically introduce the characteristics of transplant recipients with COVID-19, immunology in SARS-CoV-2 infection, and potential therapeutic strategy.

Screening druggable targets and predicting therapeutic drugs for COVID-19 via integrated bioinformatics analysis.

BACKGROUND: Since the outbreak of coronavirus disease 2019 (COVID-19) in China, numerous research institutions have invested in the development of anti-COVID-19 vaccines and screening for efficacious drugs to manage the virus. OBJECTIVE: To explore the potential targets and therapeutic drugs for the prevention and treatment of COVID-19 through data mining and bioinformatics. METHODS: We integrated and profoundly analyzed 10 drugs previously assessed to have promising therapeutic potential in COVID-19 management, and have been recommended for clinical trials. To explore the mechanisms by which these drugs may be involved in the treatment of COVID-19, gene-drug interactions were identified using the DGIdb database after which functional enrichment analysis, protein-protein interaction (PPI) network, and miRNA-gene network construction were performed. We adopted the DGIdb database to explore the candidate drugs for COVID-19. RESULTS: A total of 43 genes associated with the 10 potential COVID-19 drugs were identified. Function enrichment analysis revealed that these genes were mainly enriched in response to other invasions, toll-like receptor pathways, and they play positive roles in the production of cytokines such as IL-6, IL-8, and INF-ß. TNF, TLR3, TLR7, TLR9, and CXCL10 were identified as crucial genes in COVID-19. Through the DGIdb database, we predicted 87 molecules as promising druggable molecules for managing COVID-19. CONCLUSIONS: Findings from this work may provide new insights into COVID-19 mechanisms and treatments. Further, the already identified candidate drugs may improve the efficiency of pharmaceutical treatment in this rapidly evolving global situation.

Prolonged shedding of SARS-CoV-2 in an elderly liver transplant patient infected by COVID-19: a case report.

Coronavirus disease 2019 (COVID-19) pandemic gripped the globe. SARS-CoV-2 is highly infectious and is susceptible to all populations. Immunosuppressed patients have greater risk for opportunistic infections. However, the understanding regarding the biological characteristics of SARS-CoV-2 in immunosuppressed patients remains unclear. Herein, we present a case of prolonged shedding of SARS-CoV-2 in a liver transplant patient with COVID-19. A 61-year-old male post liver transplant was confirmed COVID-19 infection on day 10 of illness onset. The patient has received immunosuppressive treatment for over 11 years and has a history of hypertension for 10 years. With antiviral treatment and temporary discontinuation of tacrolimus immunosuppression, he had complete clinical symptoms relieve on day 24. However, recurrently positive tests of SARS-CoV-2 RNA were presented on day 35 and on day 39 after two consecutive negative tests. IgG antibody test for SARS-CoV-2 was positive with IgM negative on day 41. The final shedding duration lasted 52 days. Prolonged shedding of SARS-CoV-2 should be a matter of concern and might attribute to long-term immunosuppression. Therefore, dynamic surveillance and prolonged quarantine are required for immunocompromised individuals. Further data should be collected to investigate if there is a universal prolonged shedding window of SARS-CoV-2 in immunosuppressed patients.