Reliability and validity evaluation of the chinese revision of the attitude towards adult vaccination scale.

BACKGROUND: Although vaccination is one of the critical interventions to address global health issues, inadequate vaccination rates has become an international challenge. Vaccine hesitancy is the key to affecting inadequate vaccination rates. According to the WHO SAGE working group's definition, vaccine hesitancy refers to delaying or refusing vaccination and has been ranked as one of the top 10 health threats. There has yet to be a scale that evaluates vaccination attitudes among Chinese adults. However, an attitude quantity, the adult vaccination attitude scale, has been developed to assess adult vaccination attitudes and reasons for vaccine hesitancy. OBJECTIVE: The Adult Attitudes to Vaccination Scale (ATAVAC) was initially developed by Professor Zoi Tsimtsiou et al. This study aimed to analyze the structure of the Chinese version of the ATAVAC and explore the relationship between adult vaccination attitudes, e-health literacy, and medical distrust. METHODS: After obtaining author permission for the initial scales, the study was translated using the Brislin back-translation method. 693 adults were enrolled to the study. To validate this hypothesis, participants finished the socio-demographic questionnaire, the Chinese version of the ATAVAC, the electronic Health Literacy Scale (e-HEALS) and the Medical Mistrust Index (MMI). The exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to examine the underlying structure of the factors of the Chinese version of the Adult Vaccination Attitude Scale and to measure its reliability and validity. RESULTS: The Cronbach's alpha coefficient for the Chinese version of the ATAVAC was 0.885, with Cronbach's alpha coefficients ranging from 0.850 to 0.958 for each dimension. The content validity index was 0.90, and the retest reliability was 0.943. The exploratory factor analysis (EFA) supported the 3-factor structure of the translation instrument, and the scale had good discriminant validity. The confirmatory factor analysis (CFA) revealed a degree of freedom of 1.219, a model fit index (GFI) of 0.979, a normative fit index (NFI) of 0.991, a Tucker-Lewis index (TLI) of 0.998, a comparability index (CFI) of 0.998 and a root mean square error of approximation (RMSEA) of 0.026. CONCLUSION: The results show that the Chinese version of the ATAVAC has demonstrated good reliability and validity. Hence, it can be used as an effective tool to assess vaccination attitudes among Chinese adults.

Prevalence and potential risk factors of PDCoV in pigs based on publications during 2015-2021 in China: Comprehensive literature review and meta-analysis.

Porcine deltacoronavirus (PDCoV), a novel coronavirus which infects pigs, spreading around the world and causing huge economic losses. In recent years, there have also been human cases of PDCoV infection, which poses a potential threat to public health. Therefore, we conducted a systematic review and meta-analysis to assess the prevalence of PDCoV in pigs in China between 2015 and 2021. The prevalence of PDCoV in China was searched from five databases (CNKI, VIP, WanFang, PubMed and ScienceDirect) and 65 articles met the inclusion criteria, with a total of 25,977 samples, including 3828 positive cases. The overall prevalence of PDCoV was 13.61% (3828/25,977), with the highest prevalence in northern China (19.18%) and the lowest prevalence in southwest China (7.19%). We also analyzed other subgroup information, such as sampling years, test methods, age and geographic factors. The results show that PDCoV is endemic in China and climate may be a potential risk factor for PDCoV infection. It is suggested that appropriate measures should be taken in different climatic areas to reduce local PDCoV infection.

Discovery of novel SARS-CoV-2 3CL protease covalent inhibitors using deep learning-based screen.

SARS-CoV-2 3CL protease is one of the key targets for drug development against COVID-19. Most known SARS-CoV-2 3CL protease inhibitors act by covalently binding to the active site cysteine. Yet, computational screens against this enzyme were mainly focused on non-covalent inhibitor discovery. Here, we developed a deep learning-based stepwise strategy for selective covalent inhibitor screen. We used a deep learning framework that integrated a directed message passing neural network with a feed-forward neural network to construct two different classifiers for either covalent or non-covalent inhibition activity prediction. These two classifiers were trained on the covalent and non-covalent 3CL protease inhibitors dataset, respectively, which achieved high prediction accuracy. We then successively applied the covalent inhibitor model and the non-covalent inhibitor model to screen a chemical library containing compounds with covalent warheads of cysteine. We experimentally tested the inhibition activity of 32 top-ranking compounds and 12 of them were active, among which 6 showed IC50 values less than 12 µM and the strongest one inhibited SARS-CoV-2 3CL protease with an IC50 of 1.4 µM. Further investigation demonstrated that 5 of the 6 active compounds showed typical covalent inhibition behavior with time-dependent activity. These new covalent inhibitors provide novel scaffolds for developing highly active SARS-CoV-2 3CL covalent inhibitors.

Screening and Identification of Novel Soluble Epoxide Hydrolase Inhibitors from Corn Gluten Peptides.

The objective of this study was to investigate the soluble epoxide hydrolase (sEH) inhibitory properties of corn gluten peptides. In total, 400 dipeptides and 8000 tripeptides were first virtually screened by molecular docking and 30 potential sEH inhibitory peptides were selected. Among them, WEY, WWY, WYW, YFW, and YFY showed the highest sEH inhibitory activities with IC50 values of 55.41 ± 1.55, 68.80 ± 7.72, 70.66 ± 9.90, 96.00 ± 7.5, and 94.06 ± 12.86 µM, respectively. These five peptides all behaved as mixed-type inhibitors and were predicted to form hydrogen bond interactions mainly with Asp333, a key residue located in the catalytic active site of sEH. Moreover, it was found that the corn gluten hydrolysates of Alcalase, Flavourzyme, pepsin and pancreatin all exhibited high sEH inhibitory activities, with IC50 values of 1.07 ± 0.08, 1.19 ± 0.24, and 1.46 ± 0.31 mg/mL, respectively. In addition, the sEH inhibitory peptides WYW, YFW, and YFY were successfully identified from the corn gluten hydrolysates by Alcalase using nano-LC-MS/MS. This study demonstrated the sEH inhibitory capacity of peptides for the first time and corn gluten might be a promising food protein source for discovering novel natural sEH inhibitory peptides.

SARS-CoV-2 ORF10 impairs cilia by enhancing CUL2ZYG11B activity.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causal pathogen of the ongoing global pandemic of coronavirus disease 2019 (COVID-19). Loss of smell and taste are symptoms of COVID-19, and may be related to cilia dysfunction. Here, we found that the SARS-CoV-2 ORF10 increases the overall E3 ligase activity of the CUL2ZYG11B complex by interacting with ZYG11B. Enhanced CUL2ZYG11B activity by ORF10 causes increased ubiquitination and subsequent proteasome-mediated degradation of an intraflagellar transport (IFT) complex B protein, IFT46, thereby impairing both cilia biogenesis and maintenance. Further, we show that exposure of the respiratory tract of hACE2 mice to SARS-CoV-2 or SARS-CoV-2 ORF10 alone results in cilia-dysfunction-related phenotypes, and the ORF10 expression in primary human nasal epithelial cells (HNECs) also caused a rapid loss of the ciliary layer. Our study demonstrates how SARS-CoV-2 ORF10 hijacks CUL2ZYG11B to eliminate IFT46 and leads to cilia dysfunction, thereby offering a powerful etiopathological explanation for how SARS-CoV-2 causes multiple cilia-dysfunction-related symptoms specific to COVID-19.

Discovery of novel SARS-CoV-2 3CL protease covalent inhibitors using deep learning-based screen

SARS-CoV-2 3CL protease is one of the key targets for drug development against COVID-19. Most known SARS-CoV-2 3CL protease inhibitors act by covalently binding to the active site cysteine. Yet, computational screens against this enzyme were mainly focused on non-covalent inhibitor discovery. Here, we developed a deep learning-based stepwise strategy for selective covalent inhibitor screen. We used a deep learning framework that integrated a directed message passing neural network with a feed-forward neural network to construct two different classifiers for either covalent or non-covalent inhibition activity prediction. These two classifiers were trained on the covalent and non-covalent 3CL protease inhibitors dataset, respectively, which achieved high prediction accuracy. We then successively applied the covalent inhibitor model and the non-covalent inhibitor model to screen a chemical library containing compounds with covalent warheads of cysteine. We experimentally tested the inhibition activity of 32 top-ranking compounds and 12 of them were active, among which 6 showed IC50 values less than 12 μM and the strongest one inhibited SARS-CoV-2 3CL protease with an IC50 of 1.4 μM. Further investigation demonstrated that 5 of the 6 active compounds showed typical covalent inhibition behavior with time-dependent activity. These new covalent inhibitors provide novel scaffolds for developing highly active SARS-CoV-2 3CL covalent inhibitors. Graphical Image 1

Response and Assessment of the Effectiveness of the Countermeasures for a COVID-19 Outbreak - Guizhou Province, China, March 2022.

What is already known about this topic?: Many regions in China have recently reported outbreaks of the coronavirus disease 2019 (COVID-19) caused by the Omicron variant. What is added by this report?: Wuchuan County, Guizhou Province reacted quickly and implemented accurate intervention measures to effectively control the outbreak. The susceptible-exposed-infectious-asymptomatic-removed (SEIAR) model was applied to evaluate the effectiveness of intervention measures. What are the implications for public health practice?: Fast response measures should be taken to prevent the spread of outbreaks caused by the Omicron variant.

Identifying Japanese Encephalitis Virus Using Metatranscriptomic Sequencing, Xinjiang, China.

The treat of infectious disease epidemics has increased the critical need for continuous broad-ranging surveillance of pathogens with outbreak potential. Using metatranscriptomic sequencing of blood samples, we identified several cases of Japanese encephalitis virus infection from Xinjiang Uyghur Autonomous Region, China. This discovery highlights the risk for known viral diseases even in nonendemic areas.

External Quality Assessment for Severe Acute Respiratory Syndrome Coronavirus 2 RNA Detection in Chongqing, China.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a huge threat to public health. Therefore, clinical laboratories must have the ability to detect SARS-CoV-2 RNA. With the enhanced detection in Chongqing, many laboratories rapidly implemented assays for the molecular detection of SARS-CoV-2 based on real-time reverse transcription polymerase chain reaction (rRT-PCR) assays. This study aimed to improve the detection capabilities of clinical laboratories by evaluating their performance for SARS-CoV-2 RNA detection through the external quality assessment (EQA) programs of 2020 in Chongqing to contribute to the prevention of this epidemic. METHODS: The EQA panels consist of eight positive samples with concentrations within 2.7 - 5.0 log10 copies/mL quantified by digital PCR and two negative samples with other human coronaviruses clinically validated by four commercial assays. All 21 samples from four rounds were distributed to the participating laboratories through cold-chain transportation. Depending on the results from each sample, laboratories were asked to use one or two assays to detect SARS-CoV-2 RNA. Test results and raw data were also required. All data were evaluated, and the testing performance of commercial assays was compared. For the rounds, all laboratories used commercial assays. RESULTS: Four rounds of EQA programs were performed, and the percent agreements of participants were 97.5% (39/40), 97.5% (39/40), 98.9% (88/89), 100.0% (131/131). Only three false negative results and one false positive result were obtained. Statistical significance in the Ct values of the ORF region and N region of SARS-CoV-2-RNA was found by using one-step, one-step concentration, and magnetic bead methods (p < 0.05). The Ct values of the ORF region of SARS-CoV-2-RNA in P5 and P6 were significantly different in the different batches of reagent A (p < 0.05). The ORF region of SARS-CoV-2-RNA was not detected in a batch of reagent B. CONCLUSIONS: The majority of laboratories in Chongqing have reliable diagnostic ability for SARS-CoV-2 detection. Our data emphasized the importance of EQA for monitoring the performance of clinical laboratories. However, clinical laboratories must first effectively evaluate the performance of reagents prior to their use.

Suppression and Activation of Intracellular Immune Response in Initial Severe Acute Respiratory Syndrome Coronavirus 2 Infection.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently the most important emerging pathogen worldwide, but its early transcriptional dynamics and host immune response remain unclear. Herein, the expression profiles of viral interactions with different types of hosts were comprehensively dissected to shed light on the early infection strategy of SARS-CoV-2 and the host immune response against infection. SARS-CoV-2 was found to exhibit a two-stage transcriptional strategy within the first 24 h of infection, comprising a lag phase that ends with the virus being paused and a log phase that starts when the viral load increases rapidly. Interestingly, the host innate immune response was found not to be activated (latent period) until the virus entered the log stage. Noteworthy, when intracellular immunity is suppressed, SARS-CoV-2 shows a correlation with dysregulation of metal ion homeostasis. Herein, the inhibitory activity of copper ions against SARS-CoV-2 was further validated in in vitro experiments. Coronavirus disease 2019-related genes (including CD38, PTX3, and TCN1) were also identified, which may serve as candidate host-restricted factors for interventional therapy. Collectively, these results confirm that the two-stage strategy of SARS-CoV-2 effectively aids its survival in early infection by regulating the host intracellular immunity, highlighting the key role of interferon in viral infection and potential therapeutic candidates for further investigations on antiviral strategies.

Programmable nano-reactors for stochastic sensing.

Chemical reactions of single molecules, caused by rapid formation or breaking of chemical bonds, are difficult to observe even with state-of-the-art instruments. A biological nanopore can be engineered into a single molecule reactor, capable of detecting the binding of a monatomic ion or the transient appearance of chemical intermediates. Pore engineering of this type is however technically challenging, which has significantly restricted further development of this technique. We propose a versatile strategy, "programmable nano-reactors for stochastic sensing" (PNRSS), by which a variety of single molecule reactions of hydrogen peroxide, metal ions, ethylene glycol, glycerol, lactic acid, vitamins, catecholamines or nucleoside analogues can be observed directly. PNRSS presents a refined sensing resolution which can be further enhanced by an artificial intelligence algorithm. Remdesivir, a nucleoside analogue and an investigational anti-viral drug used to treat COVID-19, can be distinguished from its active triphosphate form by PNRSS, suggesting applications in pharmacokinetics or drug screening.

Traditional Chinese Medicine guidelines for coronavirus disease 2019.

OBJECTIVE: To summarize the evidence from Traditional Chinese Medicine (TCM) practice in the treatment of coronavirus disease 2019 (COVID-19) and provide timely clinical practice guidance. METHODS: The guidelines were developed in accordance with the World Health Organization rapid guideline process. The evidence on TCM for COVID-19 from published guidelines, direct and indirect published clinical evidence, first hand clinical data, and expert experience and consensus were collected. The grading of recommendations assessment, development and evaluation (GRADE) method was used to grade the evidence and make the recommendations. RESULTS: Based on the available evidence, the guidelines recommended 17 Chinese medicines for COVID-19: 2 Chinese herbal granules, 7 Chinese patent medicines, and 8 Chinese herbal injections. CONCLUSION: As the literature search was conducted on March, any subsequent versions of these guidelines require an up-to-date literature review. We hope that the evidence summary in these will be helpful in global efforts to address COVID-19.

Potential effects of SARS-CoV-2 infection during pregnancy on fetuses and newborns are worthy of attention.

The outbreak of the 2019 novel coronavirus disease (SARS-CoV-2) has resulted in a major epidemic threat worldwide. However, the effects of neoviruses on infected pregnant women and especially on their fetuses and newborns are not well understood. Most up-to-date evidences about how SARS-CoV-2 affected patients especially in pregnancy were collected by conducting a comprehensive search of medical literature electronic databases. Immune-related data of pregnant women, fetuses and newborns were further analysis. According to the limited literature, SARS-CoV-2 utilizes angiotensin converting enzyme 2 as its receptor and causes severe hypoxemia. Insufficiency of angiotensin converting enzyme 2 in pregnant women and the effects of hypoxia on the placental oxygen supply will cause severe perinatal complications. In addition, SARS-CoV-2 infection may disrupt maternal-fetal immune tolerance and cause immunological damage to embryos. Because of these reasons, pregnancy complications such as fetal demise or premature birth, preeclampsia, intrauterine growth restriction, respiratory dyspnea, nervous system dysplasia and immune system defects are likely to occur in pregnant women with COVID-19 or their newborns. Pregnant women infected with SARS-CoV-2 should be treated as a special group and given special attention. Fetuses and newborns of SARS-CoV-2-infected pregnant women should be given more protection to reduce the occurrence of adverse events. In this review, we intend to provide an overview of the physiological and immunological changes that induce the pregnancy complications. This article will benefit the treatment and prognosis of fetuses and newborns of SARS-CoV-2-infected pregnant women.

Popular Mental Health Apps (MH Apps) as a Complement to Telepsychotherapy: Guidelines for Consideration

With the increasing need to minimize in-person contact as a way to stem the rapid spread of the novel coronavirus across the world, many clinicians are now providing mental health care exclusively through telepsychotherapy. Mental health mobile applications (MH apps) offer clients complementary therapeutic resources available outside of the telepsychotherapy session and have the potential to enhance the quality of care. However, not all mental health apps are created equal and clinicians lack guidance on how best to evaluate MH apps. This article discusses several ethical and practical considerations involved in using MH apps as an adjunct to telepsychotherapy, proposes recommendations for app evaluation, and provides a summary table of 28 popular English-language MH apps to assist clinicians in evaluating the manyMHapps available on the market today. The authors conducted a review of recent literature in EBSCO Discovery Service (EDS) and included 10 peer reviewed, English language meta-analyses and systematic reviews on the efficacy of MH apps. The emerging literature suggests that the MH apps that have been studied in randomized control trials provide some benefit for targeted problems (e.g., depression) over waitlist control groups and under some circumstances are comparable to active intervention groups, although effect sizes tend to be small. However, of the 28 popular MH apps featured in this article, only 5 were found to have empirical support. Of note, few empirical studies reference any harmful effects, although risks have been posited.