Predicting the distribution of COVID-19 through CGAN-Taking Macau as an example.

Machine learning (ML) is an innovative method that is widely used in data prediction. Predicting the COVID-19 distribution using ML is essential for urban security risk assessment and governance. This study uses conditional generative adversarial network (CGAN) to construct a method to predict the COVID-19 hotspot distribution through urban texture and business formats and establishes a relationship between urban elements and COVID-19 so that machines can automatically predict the epidemic hotspots in cities. Taking Macau as an example, this method is used to determine the correlation between the urban texture and business hotspots of Macau and the new epidemic hotspot clusters. Different types of samples afforded different epidemic prediction accuracies. The results show the following: (1) CGAN can accurately predict the distribution area of COVID-19, and the accuracy can exceed 70%. (2) The results of predicting the COVID-19 distribution through urban texture and POI data of hospitals and stations are the best, with an accuracy of more than 60% in experiments in different regions of Macau. (3) The proposed method can also predict other areas in the city that may be at risk of COVID-19 and help urban epidemic prevention and control.

Corrigendum: Genetic predisposition between COVID-19 and four mental illnesses: A bidirectional, two-sample Mendelian randomization study.

[This corrects the article DOI: 10.3389/fpsyt.2021.746276.].

Seasonal variation and ecological risk assessment of Pharmaceuticals and Personal Care Products (PPCPs) in a typical semi-enclosed bay — The Bohai Bay in northern China

The Bohai Bay as a typical semi-enclosed bay in northern China with poor water exchange capacity and significant coastal urbanization, is greatly influenced by land-based inputs and human activities. As a class of pseudo-persistent organic pollutants, the spatial and temporal distribution of Pharmaceuticals and Personal Care Products (PPCPs) is particularly important to the ecological environment, and it will be imperfect to assess the ecological risk of PPCPs for the lack of systematic investigation of their distribution in different season. 14 typical PPCPs were selected to analyze the spatial and temporal distribution in the Bohai Bay by combining online solid-phase extraction (SPE) and HPLC-MS/MS techniques in this study, and their ecological risks to aquatic organisms were assessed by risk quotients (RQs) and concentration addition (CA) model. It was found that PPCPs widely presented in the Bohai Bay with significant differences of spatial and seasonal distribution. The concentrations of ∑PPCPs were higher in autumn than in summer. The distribution of individual pollutants also showed significant seasonal differences. The high values were mainly distributed in estuaries and near-shore outfalls. Mariculture activities in the northern part of the Bohai Bay made a greater contribution to the input of PPCPs. Caffeine, florfenicol, enrofloxacin and norfloxacin were the main pollutants in the Bohai Bay, with detection frequencies exceeding 80 %. The ecological risk of PPCPs to algae was significantly higher than that to invertebrates and fish. CA model indicated that the potential mixture risk of total PPCPs was not negligible, with 34 % and 88 % of stations having mixture risk in summer and autumn, respectively. The temporary stagnation of productive life caused by Covid-19 weakened the input of PPCPs to the Bohai Bay, reducing the cumulative effects of the pollutants. This study was the first full-coverage investigation of PPCPs in the Bohai Bay for different seasons, providing an important basis for the ecological risk assessment and pollution prevention of PPCPs in the bay.

The histopathological changes of piglets intestinal tissues and the effection of pathogenicity-associated factors induced by porcine deltacoronavirus

For exploring the histopathological changes of intestinal tissues and the mechanism of porcine deltacoronavirus(PDCo V) replication and leading to inflammatory lesions of piglets intestine which induced by PDCo V infection, 10-day-old piglets were infected by PDCo V strain TJ1 which isolated from Tianjin through oral route in this study. The piglets were necropsied at 4 days post-infection. Through histopathological observation, the main lesions of jejunum, ileum, colon and cecum were investigated. The diffuse inflammatory cell infiltration was found in mesenchyme, lamina propria and submucosa of intestinal mucosa, and the mucosal villi atrophy occurred in response to local tissues. The m RNA expression level of PDCo V M gene, innate immune genes including IFN-a, IFN-beta, DDX58 and STAT2 as well as the inflammatory cytoines including TNF-a and IL-6 in intestinal tissues were examined. The results showed that PDCo V replication was achieved by inhibiting host cell innate immune response, and the occurrence of inflammatory lesions in jejunum, ileum and colon were promoted through the enhancement of TNF-a and IL-6 expression. This study can provide a theoretical basis for the pathogenic mechanism study of porcine deltacoronavirus.

A translational genomics approach identifies IL10RB as the top candidate gene target for COVID-19 susceptibility.

Recent efforts have identified genetic loci that are associated with coronavirus disease 2019 (COVID-19) infection rates and disease outcome severity. Translating these genetic findings into druggable genes that reduce COVID-19 host susceptibility is a critical next step. Using a translational genomics approach that integrates COVID-19 genetic susceptibility variants, multi-tissue genetically regulated gene expression (GReX), and perturbagen signatures, we identified IL10RB as the top candidate gene target for COVID-19 host susceptibility. In a series of validation steps, we show that predicted GReX upregulation of IL10RB and higher IL10RB expression in COVID-19 patient blood is associated with worse COVID-19 outcomes and that in vitro IL10RB overexpression is associated with increased viral load and activation of disease-relevant molecular pathways.

Ångstrom-scale silver particles potently combat SARS-CoV-2 infection by suppressing the ACE2 expression and inflammatory responses.

The SARS-CoV-2 pandemic has become a severe global public health event, and the development of protective and therapeutic strategies is urgently needed. Downregulation of angiotensin converting enzyme 2 (ACE2; one of the important SARS-CoV-2 entry receptors) and aberrant inflammatory responses (cytokine storm) are the main targets to inhibit and control COVID-19 invasion. Silver nanomaterials have well-known pharmaceutical properties, including antiviral, antibacterial, and anticancer properties. Here, based on a self-established metal evaporation-condensation-size graded collection system, smaller silver particles reaching the Ångstrom scale (AgÅPs) were fabricated and coated with fructose to obtain a stabilized AgÅP solution (F-AgÅPs). F-AgÅPs potently inactivated SARS-CoV-2 and prevented viral infection. Considering the application of anti-SARS-CoV-2, a sterilized F-AgÅP solution was produced via spray formulation. In our model, the F-AgÅP spray downregulated ACE2 expression and attenuated proinflammatory factors. Moreover, F-AgÅPs were found to be rapidly eliminated to avoid respiratory and systemic toxicity in this study as well as our previous studies. This work presents a safe and potent anti-SARS-CoV-2 agent using an F-AgÅP spray.

Combined cooling, heating, power and oxygen for hospital buildings employing photovoltaic power and liquefied methane

To enhance the energy and gas supply security and reduce the greenhouse gas emission simultaneously, this paper presents a new cryogen-based co-production concept of combined cooling, heating, power and oxygen (CCHPO) for hospital buildings. By integrating with local photovoltaic power generation, two cryogenic liquids of liquefied methane and liquefied oxygen are used to store and produce multiple energies and medical gas. Detailed system modeling and performance analysis are carried out regarding the actual energy and gas consumption data from hospital buildings. The results obtained show the proposed CCHPO solution can be expected to fulfill the simultaneous requirements of energy conservation during normal operation and sustainable energy and gas supply during emergency operations.

Identification and integrated analysis of lncRNAs and miRNAs in IPEC-J2 cells provide novel insight into the regulation of the innate immune response by PDCoV infection.

BACKGROUND: Noncoding RNAs (ncRNAs), including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), are pivotal regulators involved in the pathogenic mechanism of multiple coronaviruses. Porcine deltacoronavirus (PDCoV) has evolved multiple strategies to escape the innate immune response of host cells, but whether ncRNAs are involved in this process during PDCoV infection is still unknown. RESULTS: In this study, the expression profiles of miRNAs, lncRNAs and mRNAs in IPEC-J2 cells infected with PDCoV at 0, 12 and 24 hours postinfection (hpi) were identified through small RNA and RNA sequencing. The differentially expressed miRNAs (DEmiRNAs), lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) were screened from the comparison group of IPEC-J2 cells at 0 and 12 hpi as well as the comparison group of IPEC-J2 cells at 12 and 24 hpi. The target genes of these DEncRNAs were predicted. The bioinformatics analysis of the target genes revealed multiple significantly enriched functions and pathways. Among them, the genes that were associated with innate immunity were specifically screened. The expression of innate immunity-related ncRNAs and mRNAs was validated by RT-qPCR. Competing endogenous RNA (ceRNA) regulatory networks among innate immunity-related ncRNAs and their target mRNAs were established. Moreover, we found that the replication of PDCoV was significantly inhibited by two innate immunity-related miRNAs, ssc-miR-30c-3p and ssc-miR-374b-3p, in IPEC-J2 cells. CONCLUSIONS: This study provides a data platform to conduct studies of the pathogenic mechanism of PDCoV from a new perspective and will be helpful for further elucidation of the functional role of ncRNAs involved in PDCoV escaping the innate immune response.

An Analysis of Life-Year Lost Due to COVID-19 - 34 Countries, December 2019-March 2021.

What is already known about this topic?: The coronavirus disease 2019 (COVID-19) pandemic has caused severe health consequences. Though most COVID-19 deaths occurred among very old people, their life-year loss might be very large because of their life expectancy at that age. What is added by this report?: This study quantified how many years of life were lost due to COVID-19 in 34 countries. COVID-19 caused 9 to 21 years of life lost (YLL) per deceased patient. East Asia and Oceania had substantially lower per capita YLL than North America and Europe. Among all countries included, the United States had the greatest total YLL, Peru had the largest YLL per 100,000 people, and Mexico had the largest YLL per 100,000 COVID-19 patients. What are the implications for public health practice?: The YLL quantification indicated that the vulnerable population, especially the elderly, should be protected under careful public health measures to reduce their YLL. It also implied that it might be too early to lift anti-epidemic restrictions now, since the extreme disproportionate consequences (total and per-capita YLL) in different countries underscored the scrutinization over the variation in disease control strategies to optimize future disease control and prevention.

Development of a Perceptions of Online Learning Scale to Assess Teachers’ Beliefs

During the COVID pandemic, the sudden switch to online learning brought an unintended spotlight to this gradually expanding educational innovation. However, while numerous tools exist to assess student perceptions of or readiness for online learning quantitatively, a research gap exists regarding teachers' perceptions of online learning. To facilitate future research among teachers, the authors describe the development of a new perceptions of online learning scale (POOLS). The POOLS seeks to measure teachers' perceptions of online learning across four theoretical constructs associated with quality education in online and traditional face-to-face formats. The POOLS was constructed using expert review and a sample (N=654), where an exploratory and confirmatory factor analysis were conducted on split halves of these data. The results of this initial validation study provide the basis for using the POOLS as an approach to measuring four aspects of perceptions of online learning: Effective Learning (?2 = 0.77), Student-Centered Learning (?2 = 0.67), Interactive Learning (?2 = 0.73), and Engaged Learning (?2 = 0.66). We recommend that the POOLS be used in research settings to describe the relationship among POOLS factors and other characteristics such as self-efficacy, amount or type of experience with online learning, and personality traits.

Genetic Predispositions Between COVID-19 and Three Cardio-Cerebrovascular Diseases.

Aims: This study was aimed to apply a Mendelian randomization design to explore the causal association between coronavirus disease 2019 (COVID-19) and three cardio-cerebrovascular diseases, including atrial fibrillation, ischemic stroke, and coronary artery disease. Methods: Two-sample Mendelian randomization was used to determine the following: 1) the causal effect of COVID-19 on atrial fibrillation (55,114 case participants vs 482,295 control participants), coronary artery disease (34,541 case participants vs 261,984 control participants), and ischemic stroke (34,217 case participants vs 40,611 control participants), which were obtained from the European Bioinformatics Institute, and 2) the causal effect of three cardio-cerebrovascular diseases on COVID-19. The single-nucleotide polymorphisms (SNPs) of COVID-19 were selected from the summary-level genome-wide association study data of COVID-19-hg genome-wide association study (GWAS) meta-analyses (round 5) based on the COVID-19 Host Genetics Initiative for participants with European ancestry. The random-effects inverse-variance weighted method was conducted for the main analyses, with a complementary analysis of the weighted median and Mendelian randomization (MR)-Egger approaches. Results: Genetically predicted hospitalized COVID-19 was suggestively associated with ischemic stroke, with an odds ratio (OR) of 1.049 [95% confidence interval (CI) 1.003-1.098; p = 0.037] in the COVID-19 Host Genetics Initiative GWAS. When excluding the UK Biobank (UKBB) data, our analysis revealed a similar odds ratio of 1.041 (95% CI 1.001-1.082; p = 0.044). Genetically predicted coronary artery disease was associated with critical COVID-19, with an OR of 0.860 (95% CI 0.760-0.973; p = 0.017) in the GWAS meta-analysis and an OR of 0.820 (95% CI 0.722-0.931; p = 0.002) when excluding the UKBB data, separately. Limited evidence of causal associations was observed between critical or hospitalized COVID-19 and other cardio-cerebrovascular diseases included in our study. Conclusion: Our findings provide suggestive evidence about the causal association between hospitalized COVID-19 and an increased risk of ischemic stroke. Besides, other factors potentially contribute to the risk of coronary artery disease in patients with COVID-19, but not genetics.

Difficulty and help with activities of daily living among older adults living alone during the COVID-19 pandemic: a multi-country population-based study.

BACKGROUND: Older adults who live alone and have difficulties in activities of daily living (ADLs) may have been more vulnerable during the COVID-19 pandemic. However, little is known about pandemic-related changes in ADL assistance (such as home care, domiciliary care) and its international variation. We examined international patterns and changes in provision of ADL assistance, and related these to country-level measures including national income and health service expenditure. METHODS: We analysed data covering 29 countries from three longitudinal cohort studies (Health and Retirement Study, English Longitudinal Study of Aging, and Survey of Health, Ageing and Retirement in Europe). Eligible people were aged ≥50 years and living alone. Outcomes included ADL difficulty status (assessed via six basic ADLs and five instrumental ADLs) and receipt of ADL assistance. Wealth-related inequality and need-related inequity in ADL assistance were measured using Erreygers' corrected concentration index (ECI). Correlations were estimated between prevalence/inequality/inequity in ADL assistance and national health-related indicators. We hypothesized these measures would be associated with health system factors such as affordability and availability of ADL assistance, as well as active ageing awareness. RESULTS: During COVID-19, 18.4% of older adults living alone reported ADL difficulties (ranging from 8.8% in Switzerland to 29.2% in the USA) and 56.8% of those reporting difficulties received ADL assistance (ranging from 38.7% in the UK to 79.8% in Lithuania). Females were more likely to receive ADL assistance than males in 16/29 countries; the sex gap increased further during the pandemic. Wealth-related ECIs indicated socioeconomic equality in ADL assistance within 24/39 countries before the pandemic, and significant favouring of the less wealthy in 18/29 countries during the pandemic. Needs-related ECIs indicated less equity in assistance with ADLs during the pandemic than before. Our hypotheses on the association between ADL provision measures and health system factors were confirmed before COVID-19, but unexpectedly disconfirmed during COVID-19. CONCLUSION: This study revealed an unequal (and in some countries, partly needs-mismatched) response from countries to older adults living alone during the COVID-19 pandemic. The findings might inform future research about, and policies for, older adults living alone, particularly regarding social protection responses during crises.

Tracing Management and Epidemiological Characteristics of COVID-19 Close Contacts in Cities Around Chengdu, China.

Introduction: Close contacts have become a potential threat to the spread of coronavirus disease 2019 (COVID-19). The purpose of this study was to understand the epidemiological characteristics of close contacts of confirmed or suspected cases of COVID-19 in the surrounding cities of Chengdu, China, so as to provide a basis for the management strategy of close contacts. Methods: Close contacts were determined through epidemiological investigation of indicated cases, and relevant information was entered in the "Close Contact Information Management System." Retrospective data of close contacts from January 22 to May 1, 2020 were collected and organized. Meanwhile, the contact mode, isolation mode, and medical outcome of close contacts were descriptively analyzed. Results: A total of 986 close contacts were effectively traced, with an average age of (36.69 ± 16.86) years old, who were mainly distributed in cities of eastern Chengdu. The frequency of contact was mainly occasional contact, 80.42% of them were relatives and public transportation personnel. Besides, the time of tracking close contacts and feedback was (10.64 ± 5.52) and (7.19 ± 6.11) days, respectively. A total of seven close contacts were converted to confirmed cases. Conclusions: Close contacts of COVID-19 have a risk of invisible infection. Early control of close contacts may be helpful to control the epidemic of COVID-19.

Automatic diagnosis of COVID-19 infection based on ontology reasoning.

BACKGROUND: 2019-nCoV has been spreading around the world and becoming a global concern. To prevent further widespread of 2019-nCoV, confirmed and suspected cases of COVID-19 infection are suggested to be kept in quarantine. However, the diagnose of COVID-19 infection is quite time-consuming and labor-intensive. To alleviate the burden on the medical staff, we have done some research on the intelligent diagnosis of COVID-19. METHODS: In this paper, we constructed a COVID-19 Diagnosis Ontology (CDO) by utilizing Protégé, which includes the basic knowledge graph of COVID-19 as well as diagnostic rules translated from Chinese government documents. Besides, SWRL rules were added into the ontology to infer intimate relationships between people, thus facilitating the efficient diagnosis of the suspected cases of COVID-19 infection. We downloaded real-case data and extracted patients' syndromes from the descriptive text, so as to verify the accuracy of this experiment. RESULTS: After importing those real instances into Protégé, we demonstrated that the COVID-19 Diagnosis Ontology showed good performances to diagnose cases of COVID-19 infection automatically. CONCLUSIONS: In conclusion, the COVID-19 Diagnosis Ontology will not only significantly reduce the manual input in the diagnosis process of COVID-19, but also uncover hidden cases and help prevent the widespread of this epidemic.

Genetic Predisposition Between COVID-19 and Four Mental Illnesses: A Bidirectional, Two-Sample Mendelian Randomization Study.

Background: The outbreak of 2019 coronavirus disease (COVID-19) has become a global pandemic. Although it has long been suspected that COVID-19 could contribute to the development of mental illness, and individuals with a pre-existing mental illness may have a higher risk of and poorer outcomes from COVID-19 infection, no evidence has established a causal association between them thus far. Methods: To investigate associations in support of a causal association between the severity of COVID-19 and mental illnesses, we leveraged large-scale genetic summary data from genome-wide association study (GWAS) summary datasets, including attention-deficit/hyperactivity disorder (ADHD) (n = 55,374), schizophrenia (n = 77,096), bipolar disorder (n = 51,710), and depression (n = 173,005), based on a previous observational study. The random-effects inverse-variance weighted method was conducted for the main analyses, with a complementary analysis of the weighted median and MR-Egger approaches and multiple sensitivity analyses assessing horizontal pleiotropy and removing outliers in two different COVID-19 databases. Results: The Mendelian randomization (MR) analysis indicated that ADHD [odds ratio (OR) = 1.297; 95% confidence interval (CI), 1.029-1.634; p = 0.028] increased the risk of hospitalization due to COVID-19. A similar association was obtained in MR sensitivity analyses of the weighted median. In addition, genetically predicted COVID-19 was significantly associated with schizophrenia (OR = 1.043; 95% CI, 1.005-1.082; p = 0.027). Conclusions: Although many studies have reported a causal relationship between COVID-19 and mental illness, our study shows that this increased risk is modest. However, considering the characteristics of ADHD that might further increase the individuals' vulnerability to being infected by COVID-19, the ongoing massive worldwide exposure to COVID-19, and the high burden of schizophrenia, we believe that it is necessary to offer preventative measures to these populations and to provide more evidence in understanding the neurological impact of COVID-19.

Genetic predisposition to COVID-19 may increase the risk of hypertension disorders in pregnancy: A two-sample Mendelian randomization study.

AIMS: The aim of this study was to apply the Mendelian randomization (MR) design to explore the potential causal association between COVID-19 and the risk of hypertension disorders in pregnancy. METHODS: Our primary genetic instrument comprised 8 single-nucleotide polymorphisms (SNPs) associated with COVID-19 at genome-wide significance. Data on the associations between the SNPs and the risk of hypertension disorders in pregnancy were obtained from study based on a very large cohort of European population. The random-effects inverse-variance weighted method was conducted for the main analyses, with a complementary analysis of the weighted median and MR-Egger approaches. RESULTS: Using IVW, we found that genetically predicted COVID-19 was significantly positively associated with hypertension disorders in pregnancy, with an odds ratio (OR) of 1.111 [95% confidence interval (CI) 1.042-1.184; P = 0.001]. Weighted median regression also showed directionally similar estimates [OR 1.098 (95% CI, 1.013-1.190), P = 0.023]. Both funnel plots and MR-Egger intercepts suggest no directional pleiotropic effects observed. CONCLUSIONS: Our findings provide direct evidence that there is a shared genetic predisposition so that patients infected with COVID-19 may be causally associated with increased risk of hypertension disorders in pregnancy.

Investigation and precautions of SARS-CoV-2 infection among healthcare workers in Emergency Center

Objective: To analyze the causes of SARS-CoV-2 nosocomial infection among healthcare workers (HCWs) and explore the effective precaution strategies in Emergency Center.

Comparison of epidemiological and clinical characteristics of COVID-19 patients with and without Wuhan exposure / 浙江省有无武汉暴露史新型冠状肺炎患者的流行 病学和临床特征的比较研究

Background: A novel coronavirus called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first identified in Wuhan, China, has been rapidly spreading around the world. This study investigates the epidemiological and clinical characteristics of coronavirus disease 2019 (COVID-19) patients in Zhejiang Province who did or did not have a history of Wuhan exposure. Methods: We collected data from medical records of confirmed COVID-19 patients in Zhejiang Province from Jan. 17 to Feb. 7, 2020 and analyzed epidemiological, clinical, and treatment data of those with and without recorded recent exposure in Wuhan. Results: Patients in the control group were older than those in the exposure group ((48.19±16.13) years vs. (43.47±13.12) years, P<0.001), and more were over 65 years old (15.95% control vs. 5.60% exposure, P<0.001). The rate of clustered onset was also significantly higher in the control group than in the exposure group (31.39% vs. 18.66%, P<0.001). The symptom of a sore throat in patients in the exposure group was significantly higher than that in the control group (17.30% vs. 10.89%, P=0.01); however, headache in the exposure group was significantly lower than that in the control group (6.87% vs. 12.15%, P=0.015). More patients in the exposure group had a significantly lower level of lactate dehydrogenase (LDH) and aspartate aminotransferase (AST) than those in the control group. There was no significant difference in any degree of COVID-19 including mild, severe, and critical between the two groups. Conclusions: From the perspective of epidemiological and clinical characteristics, there was no significant difference between COVID-19 patients with and without Wuhan exposure history.

Single-nucleus transcriptome analysis of human brain immune response in patients with severe COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, has been associated with neurological and neuropsychiatric illness in many individuals. We sought to further our understanding of the relationship between brain tropism, neuro-inflammation, and host immune response in acute COVID-19 cases. METHODS: Three brain regions (dorsolateral prefrontal cortex, medulla oblongata, and choroid plexus) from 5 patients with severe COVID-19 and 4 controls were examined. The presence of the virus was assessed by western blot against viral spike protein, as well as viral transcriptome analysis covering > 99% of SARS-CoV-2 genome and all potential serotypes. Droplet-based single-nucleus RNA sequencing (snRNA-seq) was performed in the same samples to examine the impact of COVID-19 on transcription in individual cells of the brain. RESULTS: Quantification of viral spike S1 protein and viral transcripts did not detect SARS-CoV-2 in the postmortem brain tissue. However, analysis of 68,557 single-nucleus transcriptomes from three distinct regions of the brain identified an increased proportion of stromal cells, monocytes, and macrophages in the choroid plexus of COVID-19 patients. Furthermore, differential gene expression, pseudo-temporal trajectory, and gene regulatory network analyses revealed transcriptional changes in the cortical microglia associated with a range of biological processes, including cellular activation, mobility, and phagocytosis. CONCLUSIONS: Despite the absence of detectable SARS-CoV-2 in the brain at the time of death, the findings suggest significant and persistent neuroinflammation in patients with acute COVID-19.