CRISPR-Cas12a Coupled with DNA Nanosheet-Amplified Fluorescence Anisotropy for Sensitive Detection of Biomolecules.

DNA nanosheets (DNSs) have been utilized effectively as a fluorescence anisotropy (FA) amplifier for biosensing. But, their sensitivity needs to be further improved. Herein, CRISPR-Cas12a with strong trans-cleavage activity was utilized to enhance the FA amplification ability of DNSs for the sensitive detection of miRNA-155 (miR-155) as a proof-of-principle target. In this method, the hybrid of the recognition probe of miR-155 (T1) and a blocker sequence (T2) was immobilized on the surface of magnetic beads (MBs). In the presence of miR-155, T2 was released by a strand displacement reaction, which activated the trans-cleavage activity of CRISPR-Cas12a. The single-stranded DNA (ssDNA) probe modified with a carboxytetramethylrhodamine (TAMRA) fluorophore was cleaved in large quantities and could not bind to the handle chain on DNSs, inducing a low FA value. In contrast, in the absence of miR-155, T2 could not be released and the trans-cleavage activity of CRISPR-Cas12a could not be activated. The TAMRA-modified ssDNA probe remained intact and was complementary to the handle chain on the DNSs, and a high FA value was obtained. Thus, miR-155 was detected through the obviously decreased FA value with a low limit of detection (LOD) of 40 pM. Impressively, the sensitivity of this method was greatly improved about 322 times by CRISPR-Cas12a, confirming the amazing signal amplification ability of CRISPR-Cas12a. At the same time, the SARS-CoV-2 nucleocapsid protein was detected by the strategy successfully, indicating that this method was general. Moreover, this method has been applied in the analysis of miR-155 in human serum and the lysates of cells, which provides a new avenue for the sensitive determination of biomarkers in biochemical research and disease diagnosis.

Parallel evolution and control method for predicting the effectiveness of non-pharmaceutical interventions in pandemics.

Aim: Nonpharmaceutical interventions (NPIs) are important strategies to utilize in reducing the negative systemic impact pandemic disasters have on human health. However, early on in the pandemic, the lack of prior knowledge and the rapidly changing nature of pandemics make it challenging to construct effective epidemiological models that can be used for anti-contagion decision-making. Subject and methods: Based on the parallel control and management theory (PCM) and epidemiological models, we developed a Parallel Evolution and Control Framework for Epidemics (PECFE), which can optimize epidemiological models according to the dynamic information during the evolution of pandemics. Results: The cross-application between PCM and epidemiological models enabled us to successfully construct an anti-contagion decision-making model for the early stages of COVID-19 in Wuhan, China. Using the model, we estimated the effects of gathering bans, intra-city traffic blockades, emergency hospitals, and disinfection, forecasted pandemic trends under different NPIs strategies, and analyzed specific strategies to prevent pandemic rebounds. Conclusion: The successful simulation and forecasting of the pandemic showed that the PECFE could be effective in constructing decision models during pandemic outbreaks, which is crucial for emergency management where every second counts. Supplementary Information: The online version contains supplementary material available at 10.1007/s10389-023-01843-2.

Social Media Overload and Anxiety Among University Students During the COVID-19 Omicron Wave Lockdown: A Cross-Sectional Study in Shanghai, China, 2022.

Objectives: The increase in the intensity of social media use during the COVID-19 lockdown has affected mental health. Therefore, it is of practical implications to explore the association between social media overload and anxiety and the underlying mechanisms. Methods: Using data from 644 university students during the COVID-19 blockade in Shanghai from March to April 2022, the chain mediation model of information strain and risk perception of omicron between social media overload and anxiety was then tested using the macro PROCESS4.0 tool. Results: The findings showed that social media overload (including information overload and social overload) was positively associated with anxiety. This relationship was mediated by information strain and risk perception of Omicron. A chain mediating role of information strain and risk perception of Omicron has also been proved in this study. Conclusion: Social media overload has a positive effect on anxiety by increasing information strain and risk perception of Omicron. This study provides some implications for future interventions on how to use social media properly for mental health during the pandemic and health management of urban governance.

Evaluation of RT-LAMP Assay for Rapid Detection of SARS-CoV-2.

OBJECTIVE: To evaluate the accuracy of the reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay for rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in community or primary-care settings. METHOD: We systematically searched the Web of Science, Embase, PubMed, and Cochrane Library databases. We conducted quality evaluation using ReviewManager software (version 5.0). We then used MetaDisc software (version 1.4) and Stata software (version 12.0) to build forest plots, along with a Deeks funnel plot and a bivariate boxplot for analysis. RESULT: Overall, the sensitivity, specificity, and diagnostic odds ratio were 0.79, 0.97, and 328.18, respectively. The sensitivity for the subgroup with RNA extraction appeared to be higher, at 0.88 (0.86-0.90), compared to the subgroup without RNA extraction, at 0.50 (0.45-0.55), with no significant difference in specificity. CONCLUSION: RT-LAMP assay exhibited high specificity regarding current SARS-CoV-2 infection. However, its overall sensitivity was relatively moderate. Extracting RNA was found to be beneficial in improving sensitivity.

Social Media Overload and Anxiety Among University Students During the COVID-19 Omicron Wave Lockdown: A Cross-Sectional Study in Shanghai, China, 2022

Objectives: The increase in the intensity of social media use during the COVID-19 lockdown has affected mental health. Therefore, it is of practical implications to explore the association between social media overload and anxiety and the underlying mechanisms. Methods: Using data from 644 university students during the COVID-19 blockade in Shanghai from March to April 2022, the chain mediation model of information strain and risk perception of omicron between social media overload and anxiety was then tested using the macro PROCESS4.0 tool. Results: The findings showed that social media overload (including information overload and social overload) was positively associated with anxiety. This relationship was mediated by information strain and risk perception of Omicron. A chain mediating role of information strain and risk perception of Omicron has also been proved in this study. Conclusion: Social media overload has a positive effect on anxiety by increasing information strain and risk perception of Omicron. This study provides some implications for future interventions on how to use social media properly for mental health during the pandemic and health management of urban governance.

Development of Physical Activity Guidelines for a Healthy China Using the Life Cycle Concept: The Perspective of Policy Tools from Five Countries

Developing physical activity guidelines based on the life cycle concept is conducive to accelerating the realization of the goal of “all-round, full-cycle maintenance and protection to greatly improve people’s health” in the Healthy China 2030 Planning Outline. Based on a policy tools perspective, this study uses the text analysis method to collect and analyze physical activity guidelines based on the life cycle concept from five economically developed countries: the USA, Japan, Canada, Australia, and the UK. The policy tools, country data, and stages of the life cycle were used to develop physical activity guidelines in China to accelerate the realization of the Healthy China 2030 strategy based on the following principles: (1) Strengthen sectoral cooperation and establish a system of policy instruments;(2) increase publicity and scientific awareness of physical activity and exercise;(3) focus on talent cultivation and improve guideline research and development;and (4) mobilize the power of all sectors to promote the implementation of physical activity guidelines.

Relationship between internet use intensity and quality of life in chronic patients during the COVID-19 pandemic: The role of physical exercise and health insurance

The internet use intensity of human has increased substantially during the COVID-19 Pandemic, and it is severely impacting the well-being of chronic patients. This study aimed to explore the underlying mechanism of the relationship between internet use intensity and quality of life in chronic patients, based on the cross-sectional data from China Family Panel Studies (CFPS) during the COVID-19 Pandemic in 2020. The results showed that the internet use intensity had significant positive association with quality of life among chronic patients, and such association has been found in both urban and rural samples. Among the relationship of internet use intensity and quality of life in chronic patients, the mediating effect of physical exercise reached 10.25%. Furthermore, health insurance positively moderated this relationship. There are new insights for policy recommendations and clinical guidance on the role of physical activity and health insurance aimed at improving chronic patients' quality of life. Meanwhile, in both rural and urban governance, public health agencies should promote the “Internet + Healthcare” program to improve health insurance and physical activity literacy, thus providing a higher level of quality of life for patients with chronic diseases during the COVID-19 Pandemic.

Research progress of histone deacetylases inhibitors in antiviral drugs discovery

Histone deacetylases (HDACs) are a class of key enzymes that regulate epigenetics. There are 5 small-molecule HDACs inhibitors having been approved for anti-cancer therapy on the market. In recent years, there have been more and more studies on the antiviral aspects of HDACs inhibitors. This article classifies viruses into human immunodeficiency virus 1 (HIV-1), new coronavirus (SARS-CoV-2), Epstein-Barr virus (EBV) and other viruses, systematically summarizes the recent advances of antiviral effects of the HDACs inhibitors from the perspective of medicinal chemistry. This review aims to provide the researchers the convenience of accessing the latest advances of the antiviral effects of HDACs inhibitors, and to analyze the challenges and prospects of this field in future drug discovery.

The Association of Internet Use Intensity and Lifestyle Behaviors During the COVID-19 Pandemic: A Cross-Sectional Study in Chinese Adults

The COVID-19 pandemic substantially increased the intensity of internet use in humans, which has made public opinion around health and public perceptions of it more vital, and this phenomenon has had a significant impact on human lifestyle behavior. This study used cross-sectional data during the COVID-19 pandemic to explore how internet use intensity influenced lifestyle behaviors among adults, and compared the differences between samples of different ages. The findings showed that the internet use intensity among adults increased the probability of physical activity, staying up late, and high-quality eating behaviors, and that they had a statistically significant positive association. Such associations were also found in independent younger, middle-aged, and older samples. However, the internet use intensity elevated the probability of body weight gain only in the independent samples of younger, middle-aged, and older adults. Besides, internet use intensity was able to increase the probability of smoking & drinking only among the younger sample. Notably, the effect of internet use intensity on lifestyle behaviors, including body weight gain, physical activity, staying up late, and a high-quality diet, was strongest among the elderly, followed by the middle-aged, and weakest among the younger. In the process of rural and urban governance regarding citizens' health, public health agencies should remind citizens to spend a reasonable amount of time on internet use to reduce the probability of unhealthy lifestyle behaviors and improve their physical health.

Decrease of atmospheric black carbon and CO2 concentrations due to COVID-19 lockdown at the Mt. Waliguan WMO/GAW baseline station in China.

The Coronavirus Disease 2019 (COVID-19) lockdown policy reduced anthropogenic emissions and impacted the atmospheric chemical characteristics in Chinese urban cities. However, rare studies were conducted at the high mountain site. In this work, in-situ measurements of light absorption by carbonaceous aerosols and carbon dioxide (CO2) concentrations were conducted at Waliguan (WLG) over the northeastern Tibetan Plateau of China from January 3 to March 30, 2020. The data was employed to explore the influence of the COVID-19 lockdown on atmospheric chemistry in the background-free troposphere. During the sampling period, the light absorption near-infrared (>470 nm) was mainly contributed by BC (>72%), however, BC and brown carbon (BrC) contributed equally to light absorption in the short wavelength (∼350 nm). The average BC concentrations in the pre-, during and post-lockdown were 0.28 ±â€¯0.25, 0.18 ±â€¯0.16, and 0.28 ±â€¯0.20 µg m-3, respectively, which decreased by approximately 35% during the lockdown period. Meanwhile, CO2 also showed slight decreases during the lockdown period. The declined BC was profoundly attributed to the reduced emissions (∼86%), especially for the combustion of fossil fuels. Moreover, the declined light absorption of BC, primary and secondary BrC decreased the solar energy absorbance by 35, 15, and 14%, respectively. The concentration weighted trajectories (CWT) analysis suggested that the decreased BC and CO2 at WLG were exclusively associated with the emission reduction in the eastern region of WLG. Our results highlighted that the reduced anthropogenic emissions attributed to the lockdown in the urban cities did impact the atmospheric chemistry in the free troposphere of the Tibetan Plateau.

Evaluation of CRISPR-Based Assays for Rapid Detection of SARS-CoV-2: A Systematic Review and Meta-Analysis.

PURPOSE: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pathogen of coronavirus disease 2019. Diagnostic methods based on the clustered regularly interspaced short palindromic repeats (CRISPR) have been developed to detect SARS-CoV-2 rapidly. Therefore, a systematic review and meta-analysis were performed to assess the diagnostic accuracy of CRISPR for detecting SARS-CoV-2 infection. MATERIALS AND METHODS: Studies published before August 2021 were retrieved from four databases, using the keywords "SARS-CoV-2" and "CRISPR." Data were collected from these publications, and the sensitivity, specificity, negative likelihood ratio (NLR), positive likelihood ratio (PLR), and diagnostic odds ratio (DOR) were calculated. The summary receiver operating characteristic curve was plotted for analysis with MetaDiSc 1.4. The Stata 15.0 software was used to draw Deeks' funnel plots to evaluate publication bias. RESULTS: We performed a pooled analysis of 38 independent studies shown in 30 publications. The reference standard was reverse transcription-quantitative PCR. The results indicated that the sensitivity of CRISPR-based methods for diagnosis was 0.94 (95% CI 0.93-0.95), the specificity was 0.98 (95% CI 0.97-0.99), the PLR was 34.03 (95% CI 20.81-55.66), the NLR was 0.08 (95% CI 0.06-0.10), and the DOR was 575.74 (95% CI 382.36-866.95). The area under the curve was 0.9894. CONCLUSION: Studies indicate that a diagnostic method based on CRISPR has high sensitivity and specificity. Therefore, this would be a potential diagnostic tool to improve the accuracy of SARS-CoV-2 detection.

Parallel simulation and optimization framework of supplies production processes for unconventional emergencies.

The outbreak of unconventional emergencies leads to a surge in demand for emergency supplies. How to effectively arrange emergency production processes and improve production efficiency is significant. The emergency manufacturing systems are typically complex systems, which are difficult to be analyzed by using physical experiments. Based on the theory of Random Service System (RSS) and Parallel Emergency Management System (PeMS), a parallel simulation and optimization framework of production processes for surging demand of emergency supplies is constructed. Under this novel framework, an artificial system model paralleling with the real scenarios is established and optimized by the parallel implementation processes. Furthermore, a concrete example of mask shortage, which occurred at Huoshenshan Hospital in the COVID-19 pandemic, verifies the feasibility of this method.

The Active Role of the Internet and Social Media Use in Nonpharmaceutical and Pharmaceutical Preventive Measures against COVID-19.

During the COVID-19 pandemic, does more internet and social media use lead to taking more- or less-effective preventive measures against the disease? A two-wave longitudinal survey with the general population in mainland China in mid-2020 found that during the COVID-19 pandemic, internet and social media use intensity promoted the adoption of nonpharmaceutical and pharmaceutical antipandemic measures. The first wave of data (n = 1014) showed that the more intensively people used the internet/social media, the more they perceived the threat of the pandemic, and took more nonpharmaceutical preventive measures (e.g., wearing masks, maintaining social distance, and washing hands) as a result. The second wave (n = 220) showed firstly the predicted relationship between internet/social media use intensity and the perceived threat of the pandemic and the adoption of nonpharmaceutical preventive measures by cross-lagged analysis; secondly, the predictive effect of internet/social media use on the adoption of pharmacological measures (i.e., willingness to vaccinate against COVID-19) and the mediating role of perceived pandemic threat were verified. The article concludes with a discussion of the role of the internet and social media use in the fight against COVID-19 in specific macrosocial contexts.

An integrative bioinformatics analysis for identifying hub genes associated with infection of lung samples in patients infected with SARS-CoV-2.

BACKGROUND: At the end of 2019, the world witnessed the emergence and ravages of a viral infection induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Also known as the coronavirus disease 2019 (COVID-19), it has been identified as a public health emergency of international concern (PHEIC) by the World Health Organization (WHO) because of its severity. METHODS: The gene data of 51 samples were extracted from the GSE150316 and GSE147507 data set and then processed by means of the programming language R, through which the differentially expressed genes (DEGs) that meet the standards were screened. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed on the selected DEGs to understand the functions and approaches of DEGs. The online tool STRING was employed to construct a protein-protein interaction (PPI) network of DEGs and, in turn, to identify hub genes. RESULTS: A total of 52 intersection genes were obtained through DEG identification. Through the GO analysis, we realized that the biological processes (BPs) that have the deepest impact on the human body after SARS-CoV-2 infection are various immune responses. By using STRING to construct a PPI network, 10 hub genes were identified, including IFIH1, DDX58, ISG15, EGR1, OASL, SAMD9, SAMD9L, XAF1, IFITM1, and TNFSF10. CONCLUSION: The results of this study will hopefully provide guidance for future studies on the pathophysiological mechanism of SARS-CoV-2 infection.

Identification of Key Pathways and Genes in SARS-CoV-2 Infecting Human Intestines by Bioinformatics Analysis.

COVID-19 is a serious infectious disease that has recently swept the world, and research on its causative virus, SARS-CoV-2, remains insufficient. Therefore, this study uses bioinformatics analysis techniques to explore the human digestive tract diseases that may be caused by SARS-CoV-2 infection. The gene expression profile data set, numbered GSE149312, is from the Gene Expression Omnibus (GEO) database and is divided into a 24-h group and a 60-h group. R software is used to analyze and screen out differentially expressed genes (DEGs) and then gene ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses are performed. In KEGG, the pathway of non-alcoholic fatty liver disease exists in both the 24-h group and 60-h group. STRING is used to establish a protein-protein interaction (PPI) network, and Cytoscape is then used to visualize the PPI and define the top 12 genes of the node as the hub genes. Through verification, nine statistically significant hub genes are identified: AKT1, TIMP1, NOTCH, CCNA2, RRM2, TTK, BUB1B, KIF20A, and PLK1. In conclusion, the results of this study can provide a certain direction and basis for follow-up studies of SARS-CoV-2 infection of the human digestive tract and provide new insights for the prevention and treatment of diseases caused by SARS-CoV-2.

Races of small molecule clinical trials for the treatment of COVID-19: An up-to-date comprehensive review.

The coronavirus disease-19 (COVID-19) pandemic has become a global threat since its first outbreak at the end of 2019. Several review articles have been published recently, focusing on the aspects of target biology, drug repurposing, and mechanisms of action (MOAs) for potential treatment. This review gathers all small molecules currently in active clinical trials, categorizes them into six sub-classes, and summarizes their clinical progress. The aim is to provide the researchers from both pharmaceutical industries and academic institutes with the handful information and dataset to accelerate their research programs in searching effective small molecule therapy for treatment of COVID-19.

Effects of different corticosteroid therapy on severe COVID-19 patients: a meta-analysis of randomized controlled trials.

BACKGROUND: To assess the efficacy and safety of corticosteroids in COVID-19 patients compared with standard care or placebo. METHODS: Electronic databases were searched to identify relevant studies. The mortality, adverse events, and other data from studies were pooled for statistical analysis. RESULTS: Ten randomized clinical trials were eligible for inclusion. Corticosteroid treatment in COVID-19 patients did not significantly reduce the risk of death (RR: 0.93; CI: 0.82, 1.05) and the need for mechanical ventilation (RR: 0.82; CI: 0.62, 1.08). No mortality reduction was also observed in the subgroup of patients requiring mechanical ventilation (RR: 0.90; CI: 0.79-1.03). The use of corticosteroids increased mortality in the subgroup of patients not requiring oxygen support (RR: 1.24; CI: 1.00-1.55). The survival benefit was observed in a low dosage of corticosteroids (RR: 0.90; CI: 0.84-0.97) and dexamethasone (RR: 0.90; 95% CI: 0.79-1.04). There was no difference in the rates of adverse events (RR: 1.13; CI: 0.58, 2.20) and secondary infections (RR: 0.87; CI: 0.66, 1.15). CONCLUSION: Corticosteroid treatment did not convincingly improve survival in severe COVID-19 patients. Low-dose dexamethasone could be considered as a drug for the treatment of COVID-19 patients. More high-quality trials are needed to further verify this conclusion.Expert Opinion: The effect of corticosteroids on patient survival highly depended on the selection of the right dosage and type and in a specific subgroup of patients. This meta-analysis, which included more RCTs, evaluated the safety and efficacy in severe COVID-19 patients and analyzed the effects of different types of corticosteroid treatments. Corticosteroid treatment did not convincingly improve survival in severe COVID-19 patients. But the low dose dexamethasone appear to have a role in the management of severe COVID-19 patients.

The Impact of Individual Behaviors and Governmental Guidance Measures on Pandemic-Triggered Public Sentiment Based on System Dynamics and Cross-Validation.

Negative online public sentiment generated by government mishandling of pandemics and other disasters can easily trigger widespread panic and distrust, causing great harm. It is important to understand the law of public sentiment dissemination and use it in a timely and appropriate way. Using the big data of online public sentiment during the COVID-19 period, this paper analyzes and establishes a cross-validation based public sentiment system dynamics model which can simulate the evolution processes of public sentiment under the effects of individual behaviors and governmental guidance measures. A concrete case of a violation of relevant regulations during COVID-19 epidemic that sparked public sentiment in China is introduced as a study sample to test the effectiveness of the proposed method. By running the model, the results show that an increase in government responsiveness contributes to the spread of positive social sentiment but also promotes negative sentiment. Positive individual behavior suppresses negative emotions while promoting the spread of positive emotions. Changes in the disaster context (epidemic) have an impact on the spread of sentiment, but the effect is mediocre.

Immune dysregulation and system pathology in COVID-19.

The coronavirus disease 19 (COVID-19) caused by the novel coronavirus known as SARS-CoV-2 has caused a global public health crisis. As of 7 January 2021, 87,640,402 confirmed cases and 1,891,692 mortalities have been reported worldwide. Studies focusing on the epidemiological and clinical characteristics of COVID-19 patients have suggested a dysregulated immune response characterized by lymphopenia and cytokine storm in these patients. The exaggerated immune response induced by the cytokine storm causes septic shock, acute respiratory distress syndrome (ARDS), and/or multiple organs failure, which increases the fatality rate of patients with SARS-CoV-2 infection. Herein, we review the recent research progress on epidemiology, clinical features, and system pathology in COVID-19. Moreover, we summarized the recent therapeutic strategies, which are either approved, under clinical trial, and/or under investigation by the local or global health authorities. We assume that treatments should focus on the use of antiviral drugs in combination with immunomodulators as well as treatment of the underlying comorbidities.

Exploration and validation of related hub gene expression during SARS-CoV-2 infection of human bronchial organoids.

BACKGROUND: In the novel coronavirus pandemic, the high infection rate and high mortality have seriously affected people's health and social order. To better explore the infection mechanism and treatment, the three-dimensional structure of human bronchus has been employed in a better in-depth study on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: We downloaded a separate microarray from the Integrated Gene Expression System (GEO) on a human bronchial organoids sample to identify differentially expressed genes (DEGS) and analyzed it with R software. After processing with R software, Gene Ontology (GO) and Kyoto PBMCs of Genes and Genomes (KEGG) were analyzed, while a protein-protein interaction (PPI) network was constructed to show the interactions and influence relationships between these differential genes. Finally, the selected highly connected genes, which are called hub genes, were verified in CytoHubba plug-in. RESULTS: In this study, a total of 966 differentially expressed genes, including 490 upregulated genes and 476 downregulated genes were used. Analysis of GO and KEGG revealed that these differentially expressed genes were significantly enriched in pathways related to immune response and cytokines. We construct protein-protein interaction network and identify 10 hub genes, including IL6, MMP9, IL1B, CXCL8, ICAM1, FGF2, EGF, CXCL10, CCL2, CCL5, CXCL1, and FN1. Finally, with the help of GSE150728, we verified that CXCl1, CXCL8, CXCL10, CCL5, EGF differently expressed before and after SARS-CoV-2 infection in clinical patients. CONCLUSIONS: In this study, we used mRNA expression data from GSE150819 to preliminarily confirm the feasibility of hBO as an in vitro model to further study the pathogenesis and potential treatment of COVID-19. Moreover, based on the mRNA differentiated expression of this model, we found that CXCL8, CXCL10, and EGF are hub genes in the process of SARS-COV-2 infection, and we emphasized their key roles in SARS-CoV-2 infection. And we also suggested that further study of these hub genes may be beneficial to treatment, prognostic prediction of COVID-19.