An Interpretable Fake News Detection Method Based on Commonsense Knowledge Graph

Existing deep learning-based methods for detecting fake news are uninterpretable, and they do not use external knowledge related to the news. As a result, the authors of the paper propose a graph matching-based approach combined with external knowledge to detect fake news. The approach focuses on extracting commonsense knowledge from news texts through knowledge extraction, extracting background knowledge related to news content from a commonsense knowledge graph through entity extraction and entity disambiguation, using external knowledge as evidence for news identification, and interpreting the final identification results through such evidence. To achieve the identification of fake news containing commonsense errors, the algorithm uses random walks graph matching and compares the commonsense knowledge embedded in the news content with the relevant external knowledge in the commonsense knowledge graph. The news is then discriminated as true or false based on the results of the comparative analysis. From the experimental results, the method can achieve 91.07%, 85.00%, and 89.47% accuracy, precision, and recall rates, respectively, in the task of identifying fake news containing commonsense errors.

Prevalence of depression and its association with quality of life among guardians of hospitalized psychiatric patients during the COVID-19 pandemic: a network perspective.

Background: The COVID-19 pandemic has greatly affected treatment-seeking behaviors of psychiatric patients and their guardians. Barriers to access of mental health services may contribute to adverse mental health consequences, not only for psychiatric patients, but also for their guardians. This study explored the prevalence of depression and its association with quality of life among guardians of hospitalized psychiatric patients during the COVID-19 pandemic. Methods: This multi-center, cross-sectional study was conducted in China. Symptoms of depression and anxiety, fatigue level and quality of life (QOL) of guardians were measured with validated Chinese versions of the Patient Health Questionnaire - 9 (PHQ-9), Generalized Anxiety Disorder Scale - 7 (GAD-7), fatigue numeric rating scale (FNRS), and the first two items of the World Health Organization Quality of Life Questionnaire - brief version (WHOQOL-BREF), respectively. Independent correlates of depression were evaluated using multiple logistic regression analysis. Analysis of covariance (ANCOVA) was used to compare global QOL of depressed versus non-depressed guardians. The network structure of depressive symptoms among guardians was constructed using an extended Bayesian Information Criterion (EBIC) model. Results: The prevalence of depression among guardians of hospitalized psychiatric patients was 32.4% (95% CI: 29.7-35.2%). GAD-7 total scores (OR = 1.9, 95% CI: 1.8-2.1) and fatigue (OR = 1.2, 95% CI: 1.1-1.4) were positively correlated with depression among guardians. After controlling for significant correlates of depression, depressed guardians had lower QOL than non-depressed peers did [F(1, 1,101) = 29.24, p < 0.001]. "Loss of energy" (item 4 of the PHQ-9), "concentration difficulties" (item 7 of the PHQ-9) and "sad mood" (item 2 of the PHQ-9) were the most central symptoms in the network model of depression for guardians. Conclusion: About one third of guardians of hospitalized psychiatric patients reported depression during the COVID-19 pandemic. Poorer QOL was related to having depression in this sample. In light of their emergence as key central symptoms, "loss of energy," "concentration problems," and "sad mood" are potentially useful targets for mental health services designed to support caregivers of psychiatric patients.

Early autoimmunity and outcome in virus encephalitis: a retrospective study based on tissue-based assay.

To explore the autoimmune response and outcome in the central nervous system (CNS) at the onset of viral infection and correlation between autoantibodies and viruses. METHODS: A retrospective observational study was conducted in 121 patients (2016-2021) with a CNS viral infection confirmed via cerebrospinal fluid (CSF) next-generation sequencing (cohort A). Their clinical information was analysed and CSF samples were screened for autoantibodies against monkey cerebellum by tissue-based assay. In situ hybridisation was used to detect Epstein-Barr virus (EBV) in brain tissue of 8 patients with glial fibrillar acidic protein (GFAP)-IgG and nasopharyngeal carcinoma tissue of 2 patients with GFAP-IgG as control (cohort B). RESULTS: Among cohort A (male:female=79:42; median age: 42 (14-78) years old), 61 (50.4%) participants had detectable autoantibodies in CSF. Compared with other viruses, EBV increased the odds of having GFAP-IgG (OR 18.22, 95% CI 6.54 to 50.77, p<0.001). In cohort B, EBV was found in the brain tissue from two of eight (25.0%) patients with GFAP-IgG. Autoantibody-positive patients had a higher CSF protein level (median: 1126.00 (281.00-5352.00) vs 700.00 (76.70-2899.00), p<0.001), lower CSF chloride level (mean: 119.80±6.24 vs 122.84±5.26, p=0.005), lower ratios of CSF-glucose/serum-glucose (median: 0.50[0.13-0.94] vs 0.60[0.26-1.23], p=0.003), more meningitis (26/61 (42.6%) vs 12/60 (20.0%), p=0.007) and higher follow-up modified Rankin Scale scores (1 (0-6) vs 0 (0-3), p=0.037) compared with antibody-negative patients. A Kaplan-Meier analysis revealed that autoantibody-positive patients experienced significantly worse outcomes (p=0.031). CONCLUSIONS: Autoimmune responses are found at the onset of viral encephalitis. EBV in the CNS increases the risk for autoimmunity to GFAP.

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.

Precise Epitope Organization with Self‐adjuvant Framework Nucleic Acid for Efficient COVID‐19 Peptide Vaccine Construction

Peptide vaccines have advantages in easy fabrication and high safety, but their effectiveness is hampered by the poor immunogenicity of the epitopes themselves. Herein, we constructed a series of framework nucleic acids (FNAs) with regulated rigidity and size to precisely organize epitopes in order to reveal the influence of epitope spacing and carrier rigidity on the efficiency of peptide vaccines. We found that assembling epitopes on rigid tetrahedral FNAs (tFNAs) with the appropriate size could efficiently enhance their immunogenicity. Further, by integrating epitopes from SARS‐CoV‐2 on preferred tFNAs, we constructed a COVID‐19 peptide vaccine which could induce high titers of IgG against the receptor binding domain (RBD) of SARS‐CoV‐2 spike protein and increase the ratio of memory B and T cells in mice. Considering the good biocompatibility of tFNAs, our research provides a new idea for developing efficient peptide vaccines against viruses and possibly other diseases.

Combating the COVID-19 infodemic using Prompt-Based curriculum learning.

The COVID-19 pandemic has been accompanied by a proliferation of online misinformation and disinformation about the virus. Combating this 'infodemic' has been identified as one of the top priorities of the World Health Organization, because false and misleading information can lead to a range of negative consequences, including the spread of false remedies, conspiracy theories, and xenophobia. This paper aims to combat the COVID-19 infodemic on multiple fronts, including determining the credibility of information, identifying its potential harm to society, and the necessity of intervention by relevant organizations. We present a prompt-based curriculum learning method to achieve this goal. The proposed method could overcome the challenges of data sparsity and class imbalance issues. Using online social media texts as input, the proposed model can verify content from multiple perspectives by answering a series of questions concerning the text's reliability. Experiments revealed the effectiveness of prompt tuning and curriculum learning in assessing the reliability of COVID-19-related text. The proposed method outperforms typical text classification methods, including fastText and BERT. In addition, the proposed method is robust to the hyperparameter settings, making it more applicable with limited infrastructure resources.

Depression and quality of life among Macau residents in the 2022 COVID-19 pandemic wave from the perspective of network analysis.

Background: In the summer of 2022, Macau experienced a surge of COVID-19 infections (the 618 COVID-19 wave), which had serious effects on mental health and quality of life (QoL). However, there is scant research on mental health problems and QoL among Macau residents during the 618 COVID-19 wave. This study examined the network structure of depressive symptoms (hereafter depression), and the interconnection between different depressive symptoms and QoL among Macau residents during this period. Method: A cross-sectional study was conducted between 26th July and 9th September 2022. Depressive symptoms were measured with the 9-item Patient Health Questionnaire (PHQ-9), while the global QoL was measured with the two items of the World Health Organization Quality of Life-brief version (WHOQOL-BREF). Correlates of depression were explored using univariate and multivariate analyses. The association between depression and QoL was investigated using analysis of covariance (ANCOVA). Network analysis was used to evaluate the structure of depression. The centrality index "Expected Influence" (EI) was used to identify the most central symptoms and the flow function was used to identify depressive symptoms that had a direct bearing on QoL. Results: A total 1,008 participants were included in this study. The overall prevalence of depression was 62.5% (n = 630; 95% CI = 60.00-65.00%). Having depression was significantly associated with younger age (OR = 0.970; p < 0.001), anxiety (OR = 1.515; p < 0.001), fatigue (OR = 1.338; p < 0.001), and economic loss (OR = 1.933; p = 0.026). Participants with depression had lower QoL F (1, 1,008) =5.538, p = 0.019). The most central symptoms included PHQ2 ("Sad Mood") (EI: 1.044), PHQ4 ("Fatigue") (EI: 1.016), and PHQ6 ("Guilt") (EI: 0.975) in the depression network model, while PHQ4 ("Fatigue"), PHQ9 ("Suicide"), and PHQ6 ("Guilt") had strong negative associations with QoL. Conclusion: Depression was common among Macao residents during the 618 COVID-19 wave. Given the negative impact of depression on QoL, interventions targeting central symptoms identified in the network model (e.g., cognitive behavioral therapy) should be developed and implemented for Macau residents with depression.

Patent-Based Analysis of China's Emergency Logistics Industry Convergence

Technology and innovation have promoted industry convergence and brought new opportunities for industrial development, and a degree of convergence exists in the emergency logistics industry. The purpose of this study is to explore the convergence of the emergency logistics industry and the change in convergence degree among related industries, so as to find a solution to the lack of robustness of the emergency logistics system. This study measures the technical relationship between industries and analyzes the overall trend of emergency logistics industry convergence using the consistency between patent co-classification analysis and patent categories and technical fields. The dominance index and relative strength index are used to assess the strength of industry nodes and the convergence of the emergency logistics industry. Social network analysis is used to investigate the industries and technical fields that are important in the convergence industry. The findings indicate that there is significant convergence between the technical fields of the emergency logistics industry. Twelve industries are actively involved in the emergency logistics industry convergence, and nine industry pairs have strong convergence relationships between them. The information industry is critical to the convergence of the emergency logistics industry. Industry convergence is assisting in the coordinated growth of the emergency logistics sector, lowering informational barriers between sectors, and boosting the system's resilience. This study contributes theoretical significance to the development of the emergency logistics industry and enriches the emergency logistics industry's research system.

Establishment and application of a triplex RT-PCR method for detection of PDCoV, SADS-CoV, and SVA

[Background] Porcine delta coronavirus（PDCoV）, swine acute diarrhea syndrome coronavirus（SADS-CoV）, and Seneca virus A（SVA） are new pathogens which seriously endanger the development of pig industry. The clinical symptoms of pigs infected with the three pathogens are difficult to distinguish. Therefore, it is urgent to establish a multiplex RT-PCR detection method for rapid diagnosis of suspected pigs and reduce economic losses. [Objective] To establish a triplex RT-PCR method for simultaneous detection of single or mixed infection of PDCoV, SADS-CoV, and SVA. [Methods] Three pairs of specific primers were designed according to the conserved regions of the N genes of PDCoV and SADS-CoV and the L/P1 genes of SVA registered in GenBank, and the optimal annealing temperature（Tm） was determined by temperature gradient PCR method. The primer concentration was optimized by array method. The recombinant plasmids PMD-PDCoV, PMD-SADS-CoV,and PMD-SVA were constructed as standards to determine the limits of detection（LOD）. The specificity of the triplex RT-PCR method was determined with the nucleic acid samples of 6 common pig viruses including porcine transmissible gastroenteritis virus, porcine epidemic diarrhea virus, and porcine reproductive and respiratory syndrome virus. The repeatability of the established method was verified by inter-batch and intra-batch tests. Finally, we employed the triplex RT-PCR method to detect the clinical samples suspected of infection and compared the results with those obtained with the reported detection methods, thus evaluating the clinical application performance of the method. [Results] The optimal Tm was 58.3 ℃, and the optimal primer concentrations were 0.5 μmol/L, 0.25 μmol/L, and 0.25 μmol/L,respectively. The established method had high sensitivity, with the LODs of 1 copy/μL, 1 copy/μL, and 10 copies/μL for PMD-PDCoV, PMD-SADS-CoV, and PMD-SVA, respectively. It had strong specificity, with specific bands only for PDCoV, SADS-CoV, and SVA and no bands for other viruses.Moreover, the method had good repeatability as the test results were consistent between and within batches. The positive rates of PDCoV, SADS-CoV, and SVA in the clinical samples detected by the established method were 65.85%, 30.49%, and 57.32%, respectively, which were consistent with the results obtained with the reported detection methods. Finally, 5 samples were randomly selected from 13 positive samples of PDCoV, SADS-CoV, and SVA for sequencing, and the phylogenetic tree indicated that the PCR amplification sequences of the five positive samples had high homology（above 96%） between each other and also with the reference sequences. [Conclusion] The triplex RT-PCR method established in this study is accurate and reliable for the simultaneous detection of PDCoV,SADS-CoV, and SVA in clinical samples.

[Appropriate Use and Abuse of Sedative-Hypnotic Drugs].

The incidence of insomnia has been increasing in recent years. In addition, due to the impact of the COVID-19 pandemic, more and more people are experiencing a variety of insomniac problems, including having difficulty in sleep initation, waking up too early, and short sleep duration. Chronic insomnia may seriously affect patients' life and work, increase their risks of developing physical and mental illnesses, and cause crushing social and economic burdens. Sedative-hypnotics, including benzodiazepine agonists, melatonin receptor agonists, orexin receptor antagonists, and antidepressants with hypnotic effects, are widely used to treat most patients suffering from insomnia. However, there is the phenomenon of the non-medical use and abuse of sedative-hypnotic drugs, especially benzodiazepine receptor agonists. The abuse of sedative-hypnotic drugs may lead to mental and physical dependence, cognitive impairment, depression and anxiety, as well as an increased risks of falls and death. Therefore, drug regulatory authorities in China and other countries have issued relevant policies to reinforce regulation. Herein, we reviewed the prevalent use and safety of sedative-hypnotic drugs and proposed suggestions concerning their appropriate use. Both the efficacy and safety of sedative-hypnotic drugs should be carefully considered so that patients suffering from insomnia receive thorough and prompt treatment and the problem of potential abuse of sedative-hypnotic drugs is assessed in an objective and scientific manner. We also hope to provide references for the standardized clinical use of insomnia drugs.

Global Scientific Trends on Healthy Eating from 2002 to 2021: A Bibliometric and Visualized Analysis.

Diet has been recognized as a vital risk factor for non-communicable diseases (NCDs), climate changes, and increasing population, which has been reflected by a rapidly growing body of the literature related to healthy eating. To reveal a panorama of the topics related to healthy eating, this study aimed to characterize and visualize the knowledge structure, hotspots, and trends in this field over the past two decades through bibliometric analyses. Publications related to healthy eating between 1 January 2002 and 31 December 2021 were retrieved and extracted from the Web of Science database. The characteristics of articles including publication years, journals, authors, institutions, countries/regions, references, and keywords were assessed. The analyses on co-authorship, co-occurrence, and co-citation were performed and network visualization maps were constructed by VOSviewer. Major subdomains identified by bibliometrics were further discussed and analyzed. A total of 12,442 articles on healthy eating were identified. Over the past two decades, the annual global publications increased from 71 to 1764, showing a nearly 25-fold growth. The journal Nutrients published the most articles and The American Journal of Clinical Nutrition possessed the highest citations. The United States, Harvard University, and Hu, Frank B. were identified as the most productive and influential country, institution, and author, respectively. The co-occurrence cluster analysis of the top 100 keywords formed four clusters: (1) the food insecurity environment for youths highlighting the necessity and significance of implementing healthy eating in early life; (2) sustainable advantages of the Mediterranean diet; (3) the importance of an overall healthy lifestyle optimization leveraged by eHealth; (4) the challenges during the course of healthy eating against obesity, which are prominent in reflecting the knowledge structure, hotspots, and trends. Moreover, COVID-19, orthorexia nervosa, sustainability, microbiota, food insecurity, and e-health are identified keywords that represented the latest high-frequency keywords and indicated the emerging frontiers of healthy eating. This study indicates that the number of publications on healthy eating will increase in the future and that healthy dietary patterns and clinical applications of healthy eating will be the next hotspots in this research field.

Precise Epitope Organization with Self-adjuvant Framework Nucleic Acid for Efficient COVID-19 Peptide Vaccine Construction.

Peptide vaccines have advantages in easy fabrication and high safety, but their effectiveness is hampered by the poor immunogenicity of the epitopes themselves. Herein, we constructed a series of framework nucleic acids (FNAs) with regulated rigidity and size to precisely organize epitopes in order to reveal the influence of epitope spacing and carrier rigidity on the efficiency of peptide vaccines. We found that assembling epitopes on rigid tetrahedral FNAs (tFNAs) with the appropriate size could efficiently enhance their immunogenicity. Further, by integrating epitopes from SARS-CoV-2 on preferred tFNAs, we constructed a COVID-19 peptide vaccine which could induce high titers of IgG against the receptor binding domain (RBD) of SARS-CoV-2 spike protein and increase the ratio of memory B and T cells in mice. Considering the good biocompatibility of tFNAs, our research provides a new idea for developing efficient peptide vaccines against viruses and possibly other diseases.

Factors affecting psychological health and career choice among medical students in eastern and western region of China after COVID-19 pandemic.

Introduction: To unearth superior countermeasures that improve psychological health and upgrade the quality of employment for medical students in China in post-epidemic era, this study was designed to determine the possible factors affecting psychological status and future career choice of this population. Methods: A cross-sectional observational study was carried out. Depression Anxiety Stress Scale-21 (DASS-21) and Insomnia Severity Index (ISI) were applied to measure psychological state. Chi-square and logistic regression analyses were adopted to filtrate related factors for psychological health and employment intention. Results: A total of 936 medical students, including 522 from eastern universities and 414 from western universities, were enrolled in the study. Anxiety among students in China's western universities was higher than that in China's eastern universities (30.4% vs. 22.0%), but no differences in the occurrences of stress (11.4% vs. 13.4%), depression (28.7% vs. 24.5%) and insomnia (30.7% vs. 25.7%). Grades, academic ranking, household income, attitudes about COVID-19 were associated with the occurrence of psychological problems. In addition, major, education level, academic ranking, family income, and clinical experience may affect the choice of future employment location and employment income. Notably, household income affected by COVID-19 and the perception of epidemic prevention and control resulted in changes in future employment region and income. COVID-19 can lead medical students with psychological problems to have a negative attitude toward future employment. Encouragingly, multiple activities, namely, proactive consideration of employment, taking part in career planning training lectures and timely adjustment of career planning, were beneficial to the professional identity of medical students. Conclusion: This study suggests that medical student psychology is influenced by COVID-19 and academic and financial pressures; actively coping with COVID-19 and making career planning in advance will contribute to optimizing future employment. Our findings provide a potent guideline for relevant departments to accurately adjust job deployment and for medical students to actively choose a career in the future.

Development and validation of a nomogram to predict failure of 14-day negative nucleic acid conversion in adults with non-severe COVID-19 during the Omicron surge: a retrospective multicenter study.

BACKGROUND: With the variability in emerging data, guidance on the isolation duration for patients with coronavirus disease 2019 (COVID-19) due to the Omicron variant is controversial. This study aimed to determine the predictors of prolonged viral RNA shedding in patients with non-severe COVID-19 and construct a nomogram to predict patients at risk of 14-day PCR conversion failure. METHODS: Adult patients with non-severe COVID-19 were enrolled from three hospitals of eastern China in Spring 2022. Viral shedding time (VST) was defined as either the day of the first positive test or the day of symptom onset, whichever was earlier, to the date of the first of two consecutively negative PCR tests. Patients from one hospital (Cohort I, n = 2033) were randomly grouped into training and internal validation sets. Predictors of 14-day PCR conversion failure were identified and a nomogram was developed by multivariable logistic regression using the training dataset. Two hospitals (Cohort II, n = 1596) were used as an external validation set to measure the performance of this nomogram. RESULTS: Of the 2033 patients from Cohort I, the median VST was 13.0 (interquartile range: 10.0‒16.0) days; 716 (35.2%) lasted > 14 days. In the training set, increased age [per 10 years, odds ratio (OR) = 1.29, 95% confidence interval (CI): 1.15‒1.45, P < 0.001] and high Charlson comorbidity index (OR = 1.25, 95% CI: 1.08‒1.46, P = 0.004) were independent risk factors for VST > 14 days, whereas full or boosted vaccination (OR = 0.63, 95% CI: 0.42‒0.95, P = 0.028) and antiviral therapy (OR = 0.56, 95% CI: 0.31‒0.96, P = 0.040) were protective factors. These predictors were used to develop a nomogram to predict VST > 14 days, with an area under the ROC curve (AUC) of 0.73 in the training set (AUC, 0.74 in internal validation set; 0.76 in external validation set). CONCLUSIONS: Older age, increasing comorbidities, incomplete vaccinations, and lack of antiviral therapy are risk factors for persistent infection with Omicron variant for > 14 days. A nomogram based on these predictors could be used as a prediction tool to guide treatment and isolation strategies.

Characterization of RNA G-quadruplexes in porcine epidemic diarrhea virus genome and the antiviral activity of G-quadruplex ligands.

Porcine epidemic diarrhea virus (PEDV), an enteropathogenic coronavirus, has catastrophic impacts on the global pig industry. However, there are still no anti-PEDV drugs with accurate targets. G-quadruplexes (G4s) are non-canonical secondary structures formed within guanine-rich regions of DNA or RNA, and have attracted great attention as potential targets for antiviral strategy. In this study, we reported two putative G4-forming sequences (PQS) in S and Nsp5 genes of PEDV genome based on bioinformatic analysis, and identified that S-PQS and Nsp5-PQS were enabled to fold into G4 structure by using circular dichroism spectroscopy and fluorescence turn-on assay. Furthermore, we verified that both S-PQS and Nsp5-PQS PQS could form G4 structure in live cells by immunofluorescence microscopy. In addition, G4-specific compounds, such as TMPyP4 and PDS, could significantly inhibit transcription, translation and proliferation of PEDV in vitro. Importantly, these compounds exert antiviral activity at the post-entry step of PEDV infection cycle, by inhibiting viral genome replication and protein expression. Lastly, we demonstrated that TMPyP4 can inhibit reporter gene expression by targeting G4 structure in Nsp5. Taken together, these findings not only reinforce the presence of viral G-quadruplex sequences in PEDV genome but also provide new insights into developing novel antiviral drugs targeting PEDV RNA G-quadruplexes.

RMDisease V2.0: an updated database of genetic variants that affect RNA modifications with disease and trait implication.

Recent advances in epitranscriptomics have unveiled functional associations between RNA modifications (RMs) and multiple human diseases, but distinguishing the functional or disease-related single nucleotide variants (SNVs) from the majority of 'silent' variants remains a major challenge. We previously developed the RMDisease database for unveiling the association between genetic variants and RMs concerning human disease pathogenesis. In this work, we present RMDisease v2.0, an updated database with expanded coverage. Using deep learning models and from 873 819 experimentally validated RM sites, we identified a total of 1 366 252 RM-associated variants that may affect (add or remove an RM site) 16 different types of RNA modifications (m6A, m5C, m1A, m5U, Ψ, m6Am, m7G, A-to-I, ac4C, Am, Cm, Um, Gm, hm5C, D and f5C) in 20 organisms (human, mouse, rat, zebrafish, maize, fruit fly, yeast, fission yeast, Arabidopsis, rice, chicken, goat, sheep, pig, cow, rhesus monkey, tomato, chimpanzee, green monkey and SARS-CoV-2). Among them, 14 749 disease- and 2441 trait-associated genetic variants may function via the perturbation of epitranscriptomic markers. RMDisease v2.0 should serve as a useful resource for studying the genetic drivers of phenotypes that lie within the epitranscriptome layer circuitry, and is freely accessible at: www.rnamd.org/rmdisease2.

Trends in incident diagnoses and drug prescriptions for anxiety and depression during the COVID-19 pandemic: an 18-month follow-up study based on the UK Biobank.

Serious concerns have been raised about the negative effects of the COVID-19 pandemic on population psychological well-being. However, limited data exist on the long-term effects of the pandemic on incident psychiatric morbidities among individuals with varying exposure to the pandemic. Leveraging prospective data from the community-based UK Biobank cohort, we included 308,400 participants free of diagnosis of anxiety or depression, as well as 213,757 participants free of anxiolytics or antidepressants prescriptions, to explore the trends in incident diagnoses and drug prescriptions for anxiety and depression from 16 March 2020 to 31 August 2021, compared to the pre-pandemic period (i.e., 1 January 2017 to 31 December 2019) and across populations with different exposure statuses (i.e., not tested for COVID-19, tested negative and tested positive). The age- and sex-standardized incidence ratios (SIRs) were calculated by month which indicated an increase in incident diagnoses of anxiety or depression among individuals who were tested for COVID-19 (tested negative: SIR 3.05 [95% confidence interval 2.88-3.22]; tested positive: 2.03 [1.76-2.34]), especially during the first six months of the pandemic (i.e., March-September 2020). Similar increases were also observed for incident prescriptions of anxiolytics or antidepressants (tested negative: 1.56 [1.47-1.67]; tested positive: 1.41 [1.22-1.62]). In contrast, individuals not tested for COVID-19 had consistently lower incidence rates of both diagnoses of anxiety or depression (0.70 [0.67-0.72]) and prescriptions of respective psychotropic medications (0.70 [0.68-0.72]) during the pandemic period. These data suggest a distinct rise in health care needs for anxiety and depression among individuals tested for COVID-19, regardless of the test result, in contrast to a reduction in health care consumption for these disorders among individuals not tested for and, presumably, not directly exposed to the disease.

Identification of niclosamide as a novel antiviral agent against porcine epidemic diarrhea virus infection by targeting viral internalization.

Porcine epidemic diarrhea virus (PEDV), an enteropathogenic coronavirus, has catastrophic impacts on the global pig industry. However, there remain no effective drugs against PEDV infection. In this study, we utilized a recombinant PEDV expressing renilla luciferase (PEDV-Rluc) to screen potential anti-PEDV agents from an FDA-approved drug library in Vero cells. Four compounds were identified that significantly decreased luciferase activity of PEDV-Rluc. Among them, niclosamide was further characterized because it exhibited the most potent antiviral activity with the highest selectivity index. It can efficiently inhibit viral RNA synthesis, protein expression and viral progeny production of classical and variant PEDV strains in a dose-dependent manner. Time of addition assay showed that niclosamide exhibited potent anti-PEDV activity when added simultaneously with or after virus infection. Furthermore, niclosamide significantly inhibited the entry stage of PEDV infection by affecting viral internalization rather than viral attachment to cells. In addition, a combination with other small molecule inhibitors of endosomal acidification enhanced the anti-PEDV effect of niclosamide in vitro. Taken together, these findings suggested that niclosamide is a novel antiviral agent that might provide a basis for the development of novel drug therapies against PEDV and other related pathogenic coronavirus infections.

A novel cartridge for nucleic acid extraction, amplification and detection of infectious disease pathogens with the help of magnetic nanoparticles

Nucleic acid detection (NAD) based on real-time polymerase chain reaction (real-time PCR) is gold standard for infectious disease detection. Magnetic nanoparticles (MNPs) are widely used for nucleic acid extraction (NAE) because of their excellent properties. Microfluidic technology makes automated NAD possible. However, most of the NAD microfluidic chips are too complex to be applied to point-of-care (POC) testing. In this paper, a simple-structure cartridge was developed for POC detection of infectious diseases. This self-contained cartridge can be divided into a magnetic-controlled NAE part, a valve-piston combined fluidic control part and a PCR chip, which is able to extract nucleic acid from up to 500 μL of liquid samples by MNPs and finish the detection process from "sample in” to "answer out” automatically. Performance tests of the cartridges show that it met the demands of automated NAD. Results of on-cartridge detection of hepatitis B virus (HBV) demonstrated that this system has good uniformity and no cross-contamination between different cartridges, and the limit of detection (LOD) of this system for HBV in serum is 50 IU/mL. Multiplex detections of severe acute respiratory syndrome coronaviruses 2 (SARS-CoV-2) with a concentration of 500 copies/mL were carried out on the system and 100% positive detection rate was achieved.

Rapid and Sensitive Genotyping of SARS-CoV-2 Key Mutation L452R with an RPA-PfAgo Method.

In the two years of COVID-19 pandemic, the SARS-CoV-2 variants have caused waves of infections one after another, and the pandemic is not ending. The key mutations on the S protein enable the variants with enhanced viral infectivity, immune evasion, and/or antibody neutralization resistance, bringing difficulties to epidemic prevention and control. In support of precise epidemic control and precision medicine of the virus, a fast and simple genotyping method for the key mutations of SARS-CoV-2 variants needs to be developed. By utilizing the specific recognition and cleavage property of the nuclease Argonaute from Pyrococcus furiosus (PfAgo), we developed a recombinase polymerase amplification (RPA) and PfAgo combined method for a rapid and sensitive genotyping of SARS-CoV-2 key mutation L452R. With a delicate design of the strategy, careful screening of the RPA primers and PfAgo gDNA, and optimization of the reaction, the method achieves a high sensitivity of a single copy per reaction, which is validated with the pseudovirus. This is the highest sensitivity that can be achieved theoretically and the highest sensitivity as compared to the available SARS-CoV-2 genotyping assays. Using RPA, the procedure of the method is finished within 1.5 h and only needs a minimum laboratorial support, suggesting that the method can be easily applied locally or on-site. The RPA-PfAgo method established in this study provides a strong support to the precise epidemic control and precision medicine of SARS-CoV-2 variants and can be readily developed for the simultaneous genotyping of multiple SARS-CoV-2 mutations.