Analysis of public opinion on food safety in Greater China with big data and machine learning.

The Internet contains a wealth of public opinion on food safety, including views on food adulteration, food-borne diseases, agricultural pollution, irregular food distribution, and food production issues. To systematically collect and analyze public opinion on food safety in Greater China, we developed IFoodCloud, which automatically collects data from more than 3,100 public sources. Meanwhile, we constructed sentiment classification models using multiple lexicon-based and machine learning-based algorithms integrated with IFoodCloud that provide an unprecedented rapid means of understanding the public sentiment toward specific food safety incidents. Our best model's F1 score achieved 0.9737, demonstrating its great predictive ability and robustness. Using IFoodCloud, we analyzed public sentiment on food safety in Greater China and the changing trend of public opinion at the early stage of the 2019 Coronavirus Disease pandemic, demonstrating the potential of big data and machine learning for promoting risk communication and decision-making.

Multidimensional self-rating biological rhythm disorder and its association with depression and anxiety symptoms among adolescents aged 11-23 years: a school-based cross-sectional study from China.

BACKGROUND: Depression and anxiety are topical concerns worldwide, especially among adolescents. Besides, biological rhythm disorder as a candidate mechanism for mood disorders is highly prevalent, but relevant research among adolescents in China is presently limited. We conducted the present study to investigate the distribution of multi-dimensional self-rating biological rhythm disorder and the association of self-rating biological rhythm disorders with depression and anxiety symptoms among Chinese adolescents in different academic stages. METHODS: In the cross-sectional study, 3693 students aged 11-23 from Zhengzhou City, Henan Province, China were included. The Patient Health Questionnaire (PHQ-9) and General Anxiety Disorder (GAD-7) were used to evaluate symptoms of depression and anxiety, respectively. Additionally, the Self-Rating of Biological Rhythm Disorder for Adolescents (SBRDA) was used to assess status of biological rhythm disorders. Multivariate logistic regression was developed to explore factors potentially associated with symptoms of depression and anxiety stratified by academic stages. RESULTS: Among all participants, 44.14 and 36.15% suffered from depression and anxiety symptoms, respectively. On average, participants scored 74.66 ± 19.37 on the measure of total biological rhythm disorder. Adjusted for demographic confounding factors, the logistic regression analysis showed higher scores of total biological rhythm disorder were associated with more severe depression (OR = 14.38, 95%CI: 11.38-18.16) and anxiety symptoms (OR = 11.63, 95%CI: 9.14-14.81). The similar results were also found in the stratified analysis by academic stages. CONCLUSIONS: Self-rating biological rhythm disorders are significantly associated with depression and anxiety symptoms among adolescents. Discrepancy across academic stages should also be taken into account in establishing public health strategies.

Transcriptome Analysis Reveals Hub Genes Regulating Autophagy in Patients With Severe COVID-19.

Background: The COVID-19 pandemic has currently developed into a worldwide threat to humankind. Importantly, patients with severe COVID-19 are believed to have a higher mortality risk than those with mild conditions. However, despite the urgent need to develop novel therapeutic strategies, the biological features and pathogenic mechanisms of severe COVID-19 are poorly understood. Methods: Here, peripheral blood mononuclear cells (PBMCs) from four patients with severe COVID-19, four patients with mild COVID-19, and four healthy controls were examined by RNA sequencing (RNA-Seq). We conducted gene expression analysis and Venn diagrams to detect specific differentially expressed genes (DEGs) in patients with severe disease compared with those with mild conditions. Gene Ontology (GO) enrichment analysis was performed to identify the significant biological processes, and protein-protein interaction networks were constructed to extract hub genes. These hub genes were then subjected to regulatory signatures and protein-chemical interaction analysis for certain regulatory checkpoints and identification of potent chemical agents. Finally, to demonstrate the cell type-specific expression of these genes, we performed single-cell RNA-Seq analyses using an online platform. Results: A total of 144 DEGs were specifically expressed in severe COVID-19, and GO enrichment analysis revealed a significant association of these specific DEGs with autophagy. Hub genes such as MVB12A, CHMP6, STAM, and VPS37B were then found to be most significantly involved in the biological processes of autophagy at the transcriptome level. In addition, six transcription factors, including SRF, YY1, CREB1, PPARG, NFIC, and GATA2, as well as miRNAs, namely, hsa-mir-1-3p, and potent chemical agents such as copper sulfate and cobalt chloride, may cooperate in regulating the autophagy hub genes. Furthermore, classical monocytes may play a central role in severe COVID-19. Conclusion: We suggest that autophagy plays a crucial role in severe COVID-19. This study might facilitate a more profound knowledge of the biological characteristics and progression of COVID-19 and the development of novel therapeutic approaches to achieve a breakthrough in the current COVID-19 pandemic.

Transcriptome Analysis Reveals Hub Genes Regulating Autophagy in Patients With Severe COVID-19

Background: The COVID-19 pandemic has currently developed into a worldwide threat to humankind. Importantly, patients with severe COVID-19 are believed to have a higher mortality risk than those with mild conditions. However, despite the urgent need to develop novel therapeutic strategies, the biological features and pathogenic mechanisms of severe COVID-19 are poorly understood. Methods: Here, peripheral blood mononuclear cells (PBMCs) from four patients with severe COVID-19, four patients with mild COVID-19, and four healthy controls were examined by RNA sequencing (RNA-Seq). We conducted gene expression analysis and Venn diagrams to detect specific differentially expressed genes (DEGs) in patients with severe disease compared with those with mild conditions. Gene Ontology (GO) enrichment analysis was performed to identify the significant biological processes, and protein–protein interaction networks were constructed to extract hub genes. These hub genes were then subjected to regulatory signatures and protein–chemical interaction analysis for certain regulatory checkpoints and identification of potent chemical agents. Finally, to demonstrate the cell type-specific expression of these genes, we performed single-cell RNA-Seq analyses using an online platform. Results: A total of 144 DEGs were specifically expressed in severe COVID-19, and GO enrichment analysis revealed a significant association of these specific DEGs with autophagy. Hub genes such as MVB12A, CHMP6, STAM, and VPS37B were then found to be most significantly involved in the biological processes of autophagy at the transcriptome level. In addition, six transcription factors, including SRF, YY1, CREB1, PPARG, NFIC, and GATA2, as well as miRNAs, namely, hsa-mir-1-3p, and potent chemical agents such as copper sulfate and cobalt chloride, may cooperate in regulating the autophagy hub genes. Furthermore, classical monocytes may play a central role in severe COVID-19. Conclusion: We suggest that autophagy plays a crucial role in severe COVID-19. This study might facilitate a more profound knowledge of the biological characteristics and progression of COVID-19 and the development of novel therapeutic approaches to achieve a breakthrough in the current COVID-19 pandemic.

The increasing hunger concern and current need in the development of sustainable food security in the developing countries.

Background: COVID-19 has affected millions of people worldwide. Recently, international agencies have revealed that poverty and hunger could kill more people than COVID-19 victims. Many global workforces have lost their jobs during this pandemic situation. In developing countries, most of the workers and their families live hand to mouth, depending on daily wage, and loss of income would be a hunger pandemic. Globally, the proportion of undernourished and hungry people have been on an upswing due to climate changes and violent conflicts. The millions of people are facing chronic malnourishment and COVID-19 menaces undermining the endeavour of philanthropic and food security. COVID-19 has increased the risk of livelihood by the shortage of food and distraction of the supply chain especially in the developing countries where rural expanses depend on agriculture production and seasonal jobs. So, if they are forced to limit their activities, their livelihoods will be demolished. Scope and approach: COVID-19 is increasing the jeopardy of food prices over the world, which would prompt a crisis in several developing countries. The government organizations in developing countries are doing well to protect people from the current pandemic. But they are also in critical situation regarding food supply chains and are facing difficulties in providing nutrient-rich foods. The susceptible people are fraught to secure household income and manage their food. In this review, we have explored the food security approach, food supply chain and risk of food shortage. Every country in the world needs to implement effective interventions to maintain open trade and food supply chains, ensure access to nutrients for all at affordable prices and develop co-operation to preserve the flexibility of universal food markets.

Statistical measure researches for the impacts of COVID-19 on Shanghai Securities Composite Index: based on mode regression model using skew-normal distribution

The economy of China has been affected by the COVID-19 and it is necessary to measure and investigate it. The mode regression model and its data deletion model using skew-normal distribution are established via the industry sub-index data of Shanghai Stock Exchange. Statistical diagnosis method of the model is proposed by using Pena distance diagnosis statistics, and the unknown parameters are estimated by the EM algorithm facilitated by gradient descent (GDEM) method. The results show that the outliers are accurately identified by the proposed statistical diagnostic method, and parameter estimation results indicate that the contribution of all industries to economy during the COVID-19 is lower than before, among which industry and commerce are the hardest hit.

Psychological Distress Reported by Primary Care Physicians in China During the COVID-19 Pandemic.

OBJECTIVE: Primary care physicians (PCPs) play a key role in responding to the COVID-19 epidemic. The objective of this study was to explore the influencing factors associated with self-reported psychological distress among a sample of PCPs in China in relation to COVID-19. METHODS: An online survey was distributed to a sample of PCPs in Chengdu city between February 10 and February 13, 2020. The survey consisted of three sections: demographic characteristics, COVID-19-related questions, and the General Health Questionnaire-12 (GHQ-12). After 5 months, a follow-up survey investigating the change of the GHQ-12 was conducted. RESULTS: A total of 712 PCPs completed the baseline survey (11.8% of those invited), 55.6% were female and 74.4% were aged between 30 and 49 years. High levels of psychological distress (GHQ-12 ≥3) were observed in 29.2% and were associated with low preparedness, high work impact, working with infected residents, personal life impact, and concerns, as well as older age and being married (p values < .05). Logistic regression analysis showed that psychological distress was associated with low preparedness (odds ratio [OR] = 0.91, 95% confidence interval [CI] = 0.87-0.96), high work impact (OR = 1.11, 95% CI = 1.03-1.20), personal life impact (OR = 1.12, 95% CI = 1.07-1.17), and safety-related concerns (OR = 1.09, 95% CI = 1.02-1.16). At the 5-month assessment point, high psychological distress was less frequent (21.8%). CONCLUSIONS: COVID-19 has resulted in high levels of distress in approximately 30% of PCPs in China. Factors associated with high psychological distress levels include low preparedness and high levels of work impact, personal life impact, and concerns. These findings highlight the importance of enhancing psychological health throughout the course of infectious pandemics.

High expression of ACE2 receptor of 2019-nCoV on the epithelial cells of oral mucosa.

It has been reported that ACE2 is the main host cell receptor of 2019-nCoV and plays a crucial role in the entry of virus into the cell to cause the final infection. To investigate the potential route of 2019-nCov infection on the mucosa of oral cavity, bulk RNA-seq profiles from two public databases including The Cancer Genome Atlas (TCGA) and Functional Annotation of The Mammalian Genome Cap Analysis of Gene Expression (FANTOM5 CAGE) dataset were collected. RNA-seq profiling data of 13 organ types with para-carcinoma normal tissues from TCGA and 14 organ types with normal tissues from FANTOM5 CAGE were analyzed in order to explore and validate the expression of ACE2 on the mucosa of oral cavity. Further, single-cell transcriptomes from an independent data generated in-house were used to identify and confirm the ACE2-expressing cell composition and proportion in oral cavity. The results demonstrated that the ACE2 expressed on the mucosa of oral cavity. Interestingly, this receptor was highly enriched in epithelial cells of tongue. Preliminarily, those findings have explained the basic mechanism that the oral cavity is a potentially high risk for 2019-nCoV infectious susceptibility and provided a piece of evidence for the future prevention strategy in dental clinical practice as well as daily life.

Effects of mask wearing on anxiety of teachers affected by COVID-19: A large cross-sectional study in China.

OBJECTIVE: There is a limited information on mask wearing in relation to anxiety. The aim of this study was to evaluate the association between mask wearing practice and the risk of anxiety during the COVID-19 epidemic among teachers in Henan province, China. METHODS: We enrolled 88,611 teachers in an online cross-sectional survey across three cities of Henan Province in China. A total of 94.75% of study participants completed an online questionnaire between February 4, 2020 and February 12, 2020. Mask wearing practice was defined according to its type, how it is worn, and the behavior exhibited in relation to wearing a mask. We used the Generalized Anxiety Disorder tool (GAD-7) to assess anxiety levels among study participants. Odds ratios (OR) with 95% confidence intervals (CI) were used to estimate the association between mask wearing practice and anxiety by using multivariable logistic regression models. RESULTS: A total of 67,357 registered teachers (25.91% men) were included in this study. After adjusting for potential confounders, participants who knew the wrong type of mask had 17% increased odds of having anxiety compared to those who knew the proper type (Aor = 1.17; 95%CI: 1.11-1.24). Odds for anxiety were higher for teachers who did not know the proper way of wearing mask compared to those who knew it properly (aOR = 1.18; 95%CI: 1.07-1.30). Not adhering to proper behavior of mask wearing was associated with 39% increased odds for anxiety (aOR = 1.39; 95%CI: 1.18-1.64). The odds for anxiety for teachers who did not adhere to all the three parameters of proper mask wearing was about 2.55 times as much compared to those who reported full compliance to the parameters (aOR = 2.55; 95%CI: 1.22-5.35). We observed similar ORs on stratified analyses across gender and age groups. CONCLUSION: Our findings suggest that improper mask wearing is another important attribute that play a significant role in increasing the risk of anxiety during the COVID-19 epidemic situation. However, these results should be considered as exploratory and hence interpreted with caution.

Prevalence and factors for anxiety during the coronavirus disease 2019 (COVID-19) epidemic among the teachers in China.

OBJECTIVE: To assess the prevalence of anxiety and explore its factors during the Coronavirus Disease 2019 (COVID-19) epidemic among the teachers in China. METHODS: We involved 88611 teachers (response rate: 94.75%) from three cities of Henan Province, China, during February 4, 2020 and February 12, 2020. Anxiety was assessed by using Generalized Anxiety Disorder tool (GAD-7). Odds ratios (OR) with 95% Confidence intervals (CI) for potential factors of anxiety were estimated using multiple logistic regression models. RESULTS: The overall prevalence of anxiety was 13.67%. The prevalence was higher for women than men (13.89% vs. 12.93%). The highest prevalence of anxiety was 14.06% (SE 2.51%) with age of 60 to 100 years in men, and 14.70% (SE 0.56%) with age of 50 to 60 years in women. Participants located in country-level city school had the lowest prevalence of anxiety across all age categories (12.01% for age of 18-30 years; 12.50% for age of 30-40 years; 12.13% for age of 40-50 years; 9.52% for age of 60-100 years). After adjusting for potential confounders, age, sex, education status, type of teachers, school location, information source, worried level, fear level, and behavior status were found to be associated with anxiety. CONCLUSIONS: This large-scale study assessed the prevalence of anxiety in teachers, as well as its potential influence of factors, which is useful for international and national decision-makers.

Isolation of a human monoclonal antibody specific for the receptor binding domain of SARS-CoV-2 using a competitive phage biopanning strategy.

The infection of the novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused more than 200 000 deaths, but no vaccine or therapeutic monoclonal antibody is currently available. SARS-CoV-2 relies on its spike protein, in particular the receptor-binding domain (RBD), to bind human cell receptor angiotensin-converting enzyme 2 (ACE2) for viral entry, and thus targeting RBD holds the promise for preventing SARS-CoV-2 infection. In this work, a competitive biopanning strategy of a phage display antibody library was applied to screen blocking antibodies against RBD. High-affinity antibodies were enriched after the first round using a standard panning process in which RBD-His was immobilized as a bait. At the next two rounds, immobilized ACE2-Fc and free RBD-His were mixed with the enriched phage antibodies. Antibodies binding to RBD at epitopes different from ACE2-binding site were captured by the immobilized ACE2-Fc, forming a "sandwich" complex. Only antibodies competed with ACE2 can bind to the free RBD-His in the supernatant and be subsequently separated by the nickel-nitrilotriacetic acid magnetic beads. rRBD-15 from the competitive biopanning of our synthetic antibody library, Lib AB1, was produced as the full-length IgG1 format. It was proved to competitively block the binding of RBD to ACE2 and potently inhibit SARS-CoV-2 pseudovirus infection with IC50 values of 12 nM. Nevertheless, rRBD-16 from the standard biopanning can only bind to RBD in vitro, but not have the blocking or neutralization activity. Our strategy can efficiently isolate the blocking antibodies of RBD, and it would speed up the discovery of neutralizing antibodies against SARS-CoV-2.