Anxiety, depression, and related factors in hemodialysis patients during the lockdown period of COVID- 19 in China: a multicenter study.

The outbreak of coronavirus disease 2019 (COVID-19) made a huge impact on hemodialysis (HD) patients. The aim of the study was to survey the anxiety, depression and related factors of HD patients during the lockdown and to explore the factors that affect their anxiety and depression. From February 1 to 15, 2020, an online survey was conducted in HD patients; the survey collected information on demographic data, epidemic perception, travel status and Zung's Self-rating Anxiety Scale (SAS) and Zung's Self-rating Depression Scale (SDS). The original SAS and SDS data from 96 HD patients gathered between May and August 2018 were retained as data for the control group. A total of 506 HD patients were recruited, and the prevalence of anxiety and depression was 22.33% and 45.45%, respectively. They had significantly higher SAS and SDS scores than the HD patients before the epidemic (p < 0.01; p < 0.05). It was found that self-threat perception, trouble related to transportation and skipping dialysis sessions were factors related to anxiety in HD patients during the lockdown (p ˂ 0.05). Education level, trouble related to transportation and the awareness of the seriousness of the epidemic were factors related to depression (p ˂ 0.05). During the COVID-19 lockdown period, HD patients reported higher levels of psychological distress than HD patients before the pandemic. Psychological support and transport policies should be provided to them.

Mpox multi-antigen mRNA vaccine candidates by a simplified manufacturing strategy afford efficient protection against lethal orthopoxvirus challenge.

Current unprecedented mpox outbreaks in non-endemic regions represent a global public health concern. Although two live-attenuated vaccinia virus (VACV)-based vaccines have been urgently approved for people at high risk for mpox, a safer and more effective vaccine that can be available for the general public is desperately needed. By utilizing a simplified manufacturing strategy of mixing DNA plasmids before transcription, we developed two multi-antigen mRNA vaccine candidates, which encode four (M1, A29, B6, A35, termed as Rmix4) or six (M1, H3, A29, E8, B6, A35, termed as Rmix6) mpox virus antigens. We demonstrated that those mpox multi-antigen mRNA vaccine candidates elicited similar potent cross-neutralizing immune responses against VACV, and compared to Rmix4, Rmix6 elicited significantly stronger cellular immune responses. Moreover, immunization with both vaccine candidates protected mice from the lethal VACV challenge. Investigation of B-cell receptor (BCR) repertoire elicited by mpox individual antigen demonstrated that the M1 antigen efficiently induced neutralizing antibody responses, and all neutralizing antibodies among the top 20 frequent antibodies appeared to target the same conformational epitope as 7D11, revealing potential vulnerability to viral immune evasion. Our findings suggest that Rmix4 and Rmix6 from a simplified manufacturing process are promising candidates to combat mpox.

Effects of mindfulness decompression therapy on mental health and job burnout among nurses working in the frontline of the novel coronavirus pandemic: A retrospective study.

OBJECTIVES: As the coronavirus disease 2019 (COVID-19) pandemic continues to spread worldwide, nucleic acid detection is a key step in controlling it. Psychological issues and job burnout of nurses working in nucleic acid sampling roles for long periods have become apparent. This study aimed to explore the effects of mindfulness decompression therapy on mental health and job burnout in front-line nurses working in nucleic acid sampling during the pandemic. METHODS: Nucleic acid sampling frontline nurses who were positive for burnout on both the Symptom Checklist-90 (SCL-90) and the Maslach Burnout Inventory-General Scale (MBI-GS) were selected as the participants. Frontline nurses in the nucleic acid testing area who received routine psychological nursing intervention from June 2020 to April 2021 were used as the control group. Nurses who received both routine psychological nursing and mindfulness decompression therapy from May 2021 to December 2021 formed the "mindfulness" subject group. We compared the two groups' primary outcome measures of SCL-90 and MBI-GS scores. RESULTS: Before the intervention, there were no significant differences between the two groups in general data, SCL-90 scores, and MBI-GS scores. After the mindfulness decompression therapy, according to SCL-90 and MBI-GS scales, psychological distress and job burnout of nurses in the mindfulness group were significantly better than those in the control group. CONCLUSION: Mindfulness decompression therapy can effectively improve mental health and relieve job burnout in frontline nurses in nucleic acid sampling areas, which is worthy of clinical application. Randomized controlled trials are still needed, however, to fully confirm the effects of mindfulness decompression therapy.

Strengthened public awareness of one health to prevent zoonosis spillover to humans.

The COVID-19 outbreak has forced the world to rethink the interconnected health of humans and nature, i.e. One Health (OH). However, the current sector-technology-based solutions have a high cost. We propose a human-oriented One Health (HOH) concept to restrain the unsustainable behaviors of natural resource exploitation and consumption, which may trigger original zoonosis spillover from an imbalanced natural ecosystem. HOH can complement a nature-based solution (NBS), where the former refers to the unknown part of nature, while the latter is based on already known natural knowledge. Additionally, a systemic analysis of popular Chinese social media during the pandemic outbreak (January 1-March 31, 2020) revealed that the wide public was influenced by OH thought. In the post-pandemic era, it is time to deepen public awareness of HOH to guide the world onto a more sustainable track and prevent more serious zoonosis spillover in the future.

Clinical experiences of final-year nursing students during the COVID-19 pandemic: A systematic review and meta-synthesis.

OBJECTIVES: This systematic review aimed to qualitatively synthesise existing literature to examine the clinical nursing experiences of final-year nursing students during the COVID-19 pandemic and provide recommendations for the effective management of clinical placement of nursing students. DESIGN: A qualitative systematic review was conducted and reported following Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. DATA SOURCES: Five electronic databases were searched and qualitative studies were included for analysis if they focussed on the clinical nursing experiences of final-year nursing students during the COVID-19 pandemic. REVIEW METHODS: Data synthesis was conducted by extracting all findings, developing categories, and producing synthesised findings. RESULTS: Four synthesised findings were concluded: 1) facing the unknown and willingness to help, 2) challenging the clinical environment, 3) transition improving professional identity, and 4) finding ways out of the pandemic. CONCLUSIONS: The transition of nursing students to clinical nursing practice during the pandemic is a personally and professionally challenging process, while nursing students try to adapt to the changing clinical environment and enhance their professional identity. Nursing managers and health policymakers should acknowledge the challenges encountered by nursing students during the pandemic and support the professional growth of future nursing teams by providing high-quality supervision.

Epidemiological characteristics of COVID-19 patients and asymptomatic infected people in Dongguan

Objective: The epidemiological characteristics of corona virus disease 2019 (COVID-19) in Dongguan were analyzed to provide reference for epidemic prevention and control.

Artificial Intelligence in Action: Addressing the COVID-19 Pandemic with Natural Language Processing.

The COVID-19 (coronavirus disease 2019) pandemic has had a significant impact on society, both because of the serious health effects of COVID-19 and because of public health measures implemented to slow its spread. Many of these difficulties are fundamentally information needs; attempts to address these needs have caused an information overload for both researchers and the public. Natural language processing (NLP)-the branch of artificial intelligence that interprets human language-can be applied to address many of the information needs made urgent by the COVID-19 pandemic. This review surveys approximately 150 NLP studies and more than 50 systems and datasets addressing the COVID-19 pandemic. We detail work on four core NLP tasks: information retrieval, named entity recognition, literature-based discovery, and question answering. We also describe work that directly addresses aspects of the pandemic through four additional tasks: topic modeling, sentiment and emotion analysis, caseload forecasting, and misinformation detection. We conclude by discussing observable trends and remaining challenges.

LitSuggest: a web-based system for literature recommendation and curation using machine learning.

Searching and reading relevant literature is a routine practice in biomedical research. However, it is challenging for a user to design optimal search queries using all the keywords related to a given topic. As such, existing search systems such as PubMed often return suboptimal results. Several computational methods have been proposed as an effective alternative to keyword-based query methods for literature recommendation. However, those methods require specialized knowledge in machine learning and natural language processing, which can make them difficult for biologists to utilize. In this paper, we propose LitSuggest, a web server that provides an all-in-one literature recommendation and curation service to help biomedical researchers stay up to date with scientific literature. LitSuggest combines advanced machine learning techniques for suggesting relevant PubMed articles with high accuracy. In addition to innovative text-processing methods, LitSuggest offers multiple advantages over existing tools. First, LitSuggest allows users to curate, organize, and download classification results in a single interface. Second, users can easily fine-tune LitSuggest results by updating the training corpus. Third, results can be readily shared, enabling collaborative analysis and curation of scientific literature. Finally, LitSuggest provides an automated personalized weekly digest of newly published articles for each user's project. LitSuggest is publicly available at https://www.ncbi.nlm.nih.gov/research/litsuggest.

Synthesis of a novel anti-fog and high-transparent coating with high wear resistance inspired by dry rice fields.

During the outbreak of COVID-19, the fogging of goggles was a fatal problem for doctors. At present, there are many ways to prevent fogging by adjusting surface wettability. However, the mechanical properties of most super-hydrophilic antifogging coatings are poor, easy to lose their antifogging properties when encountering fingers or cloth friction. To address this issue, the Konjac Glucomannan was cross-linked with water-soluble silicone fluid to form a binder, then being combined with the modified Ecokimera to prepare an eco-friendly super-hydrophilic coating that possessed excellent super-hydrophilicity, and the water contact angle (WCA) was 2.51 ± 1°. In addition, the WCA is still about 5° after 180 times of antifogging tests. The friction resistance of the coating was as high as 24 m. Moreover, the light transmittance was only reduced by 3%. Besides, they also had the excellent self-cleaning property. After being stored in the laboratory environment for 90 days, it can still maintain the hydrophilic property (WCA is about 5°). In general, the method proposed in this study is low-cost and eco-friendly, and can be widely used in the preparation of antifogging coatings.

Multi-platform omics analysis reveals molecular signature for COVID-19 pathogenesis, prognosis and drug target discovery.

Disease progression prediction and therapeutic drug target discovery for Coronavirus disease 2019 (COVID-19) are particularly important, as there is still no effective strategy for severe COVID-19 patient treatment. Herein, we performed multi-platform omics analysis of serial plasma and urine samples collected from patients during the course of COVID-19. Integrative analyses of these omics data revealed several potential therapeutic targets, such as ANXA1 and CLEC3B. Molecular changes in plasma indicated dysregulation of macrophage and suppression of T cell functions in severe patients compared to those in non-severe patients. Further, we chose 25 important molecular signatures as potential biomarkers for the prediction of disease severity. The prediction power was validated using corresponding urine samples and plasma samples from new COVID-19 patient cohort, with AUC reached to 0.904 and 0.988, respectively. In conclusion, our omics data proposed not only potential therapeutic targets, but also biomarkers for understanding the pathogenesis of severe COVID-19.

Intra-host variation and evolutionary dynamics of SARS-CoV-2 populations in COVID-19 patients.

BACKGROUND: Since early February 2021, the causative agent of COVID-19, SARS-CoV-2, has infected over 104 million people with more than 2 million deaths according to official reports. The key to understanding the biology and virus-host interactions of SARS-CoV-2 requires the knowledge of mutation and evolution of this virus at both inter- and intra-host levels. However, despite quite a few polymorphic sites identified among SARS-CoV-2 populations, intra-host variant spectra and their evolutionary dynamics remain mostly unknown. METHODS: Using high-throughput sequencing of metatranscriptomic and hybrid captured libraries, we characterized consensus genomes and intra-host single nucleotide variations (iSNVs) of serial samples collected from eight patients with COVID-19. The distribution of iSNVs along the SARS-CoV-2 genome was analyzed and co-occurring iSNVs among COVID-19 patients were identified. We also compared the evolutionary dynamics of SARS-CoV-2 population in the respiratory tract (RT) and gastrointestinal tract (GIT). RESULTS: The 32 consensus genomes revealed the co-existence of different genotypes within the same patient. We further identified 40 intra-host single nucleotide variants (iSNVs). Most (30/40) iSNVs presented in a single patient, while ten iSNVs were found in at least two patients or identical to consensus variants. Comparing allele frequencies of the iSNVs revealed a clear genetic differentiation between intra-host populations from the respiratory tract (RT) and gastrointestinal tract (GIT), mostly driven by bottleneck events during intra-host migrations. Compared to RT populations, the GIT populations showed a better maintenance and rapid development of viral genetic diversity following the suspected intra-host bottlenecks. CONCLUSIONS: Our findings here illustrate the intra-host bottlenecks and evolutionary dynamics of SARS-CoV-2 in different anatomic sites and may provide new insights to understand the virus-host interactions of coronaviruses and other RNA viruses.

Kinetics of viral load and antibody response in relation to COVID-19 severity.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent for coronavirus 2019 (COVID-19) pneumonia. Little is known about the kinetics, tissue distribution, cross-reactivity, and neutralization antibody response in patients with COVID-19. Two groups of patients with RT-PCR-confirmed COVID-19 were enrolled in this study: 12 severely ill patients in intensive care units who needed mechanical ventilation and 11 mildly ill patients in isolation wards. Serial clinical samples were collected for laboratory detection. Results showed that most of the severely ill patients had viral shedding in a variety of tissues for 20-40 days after onset of disease (8/12, 66.7%), while the majority of mildly ill patients had viral shedding restricted to the respiratory tract and had no detectable virus RNA 10 days after onset (9/11, 81.8%). Mildly ill patients showed significantly lower IgM response compared with that of the severe group. IgG responses were detected in most patients in both the severe and mild groups at 9 days after onset, and remained at a high level throughout the study. Antibodies cross-reactive to SARS-CoV and SARS-CoV-2 were detected in patients with COVID-19 but not in patients with MERS. High levels of neutralizing antibodies were induced after about 10 days after onset in both severely and mildly ill patients which were higher in the severe group. SARS-CoV-2 pseudotype neutralization test and focus reduction neutralization test with authentic virus showed consistent results. Sera from patients with COVID-19 inhibited SARS-CoV-2 entry. Sera from convalescent patients with SARS or Middle East respiratory syndrome (MERS) did not. Anti-SARS-CoV-2 S and N IgG levels exhibited a moderate correlation with neutralization titers in patients' plasma. This study improves our understanding of immune response in humans after SARS-CoV-2 infection.

Isolation of infectious SARS-CoV-2 from urine of a COVID-19 patient.

SARS-CoV-2 caused a major outbreak of severe pneumonia (COVID-19) in humans. Viral RNA was detected in multiple organs in COVID-19 patients. However, infectious SARS-CoV-2 was only isolated from respiratory specimens. Here, infectious SARS-CoV-2 was successfully isolated from urine of a COVID-19 patient. The virus isolated could infect new susceptible cells and was recognized by its' own patient sera. Appropriate precautions should be taken to avoid transmission from urine.