Restorative properties of green sheltered spaces and their morphological characteristics in urban parks

The properties of green space for physical and mental health have been widely demonstrated, especially after the COVID-19 pandemic. However, few studies have systematically focused on spatial indicator thresholds that provide a sense of refuge with restoration benefits. Four morphological indicators as area, coverage, enclosure, and the ratio of width to height(D/H), were quantified for thirty-one scenes in outdoor green sheltered spaces in seven urban parks of Harbin in China. The results show that the sense of refuge and the morphological character of a green space constitute elements that influence restorative properties. Green spaces with different morphological indicators have different restorative properties. The morphological indicator ranges that produce better restorative properties were obtained: 250 m2 to 500 m2 for area, 0.25-0.35 for coverage, 0.3-0.4 or 0.8-1 for enclosure, and 0.7-1.5 for D/H. This can provide references for the construction of restorative activity spaces in urban parks.

The preclinical and clinical progress of cell sheet engineering in regenerative medicine.

Cell therapy is an accessible method for curing damaged organs or tissues. Yet, this approach is limited by the delivery efficiency of cell suspension injection. Over recent years, biological scaffolds have emerged as carriers of delivering therapeutic cells to the target sites. Although they can be regarded as revolutionary research output and promote the development of tissue engineering, the defect of biological scaffolds in repairing cell-dense tissues is apparent. Cell sheet engineering (CSE) is a novel technique that supports enzyme-free cell detachment in the shape of a sheet-like structure. Compared with the traditional method of enzymatic digestion, products harvested by this technique retain extracellular matrix (ECM) secreted by cells as well as cell-matrix and intercellular junctions established during in vitro culture. Herein, we discussed the current status and recent progress of CSE in basic research and clinical application by reviewing relevant articles that have been published, hoping to provide a reference for the development of CSE in the field of stem cells and regenerative medicine.

Interpretation of guidelines for medical observation management of close contacts with COVID-19 cases part 3: home-based medical observation

Effectively blocking the transmission route of coronavirus and protecting the susceptible population play significant roles in the control of COVID-19 pandemic. Strengthening home-based medical observation is one of the key points in preventing the spread of SARS-CoV-2 virus in families and communities. Therefore, in order to meet the needs for COVID-19 prevention and control in Beijing, a group of experts organized by Beijing Association of Preventive Medicine developed the Guidelines for medical observation management of close contacts with COVID-19 cases Part 3: home-based medical observation(T/BPMA007.3-2020), which offers the specific provisions for close contacts of COVID-19 cases who need home-based medical observation as well as home environmental condition, prevention and control requirements, waste disposal, disinfection, community prevention and control work requirements, basic requirements for training and education and management guidelines.It provides standard support for home-based medical observation of close contacts with COVID-19 cases.

Bidirectional and persistent immunomodulation of Astragalus polysaccharide as an adjuvant of influenza and recombinant SARS-CoV-2 vaccine.

Respiratory viral infections, such as coronavirus disease of 2019 (COVID-19) and influenza, cause significant morbidity and mortality and have become a worldwide public health concern with tremendous economic and societal burdens. Vaccination is a major strategy for preventing infections. However, some new vaccines have an unmet need for impairing responses in certain individuals, especially COVID-19 vaccines, despite ongoing vaccine and adjuvant research. Here, we evaluated the effectiveness of Astragalus polysaccharide (APS), a bioactive polysaccharide extracted from the traditional Chinese herb Astragalus membranaceus as an immune adjuvant to regulate the efficacy of influenza split vaccine (ISV) and recombinant severe acute respiratory syndrome (SARS)-Cov-2 vaccine in mice. Our data indicated that APS as an adjuvant can facilitate the induction of high levels of hemagglutination inhibition (HAI) titer and specific antibody immunoglobulin G (IgG) and confer protection against the lethal challenge of influenza A viruses, including increased survival and amelioration of weight loss in mice immunized with the ISV. RNA sequencing (RNA-seq) analysis revealed that the NF-κB and Fc gamma R-mediated phagocytosis signaling pathways are essential for the immune response of mice immunized with the recombinant SARS-Cov-2 vaccine (RSV). Another important finding was that bidirectional immunomodulation of APS on cellular and humoral immunity was observed, and APS-adjuvant-induced antibodies persisted at a high level for at least 20 weeks. These findings suggest that APS is a potent adjuvant for influenza and COVID-19 vaccines, and has the advantages of bidirectional immunoregulation and persistent immunity.

Spike protein mediated membrane fusion during SARS-CoV-2 infection.

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has posed a serious threat to public health and has quickly become a global concern. The infection of SARS-CoV-2 begins with the binding of its spike protein to the receptor-angiotensin-converting enzyme 2 (ACE2), which, after a series of conformation changes, results in the fusion of viral-cell membranes and the release of the viral RNA genome into the cytoplasm. In addition, infected host cells can express spike protein on their cell surface, which will interact with ACE2 on neighboring cells, leading to cell membrane fusion and the formation of multinucleated cells or syncytia. Both viral entry and syncytia formation are mediated by spike-ACE2 interaction and share some common mechanisms of membrane fusion. Here in this review, we will summarize our current understanding of spike-mediated membrane fusion, which may shed light on future broad-spectrum antiviral development.

A bio-inspired LIDA cognitive-based Digital Twin architecture for unmanned maintenance of machine tools

Affected by COVID-19, the maintenance process of machine tools is significantly hindered, while unmanned maintenance becomes an emerging trend in such background. So far, three challenges, namely, the dependence on maintenance experts, the dynamic maintenance environments, and unsynchronized interactions between physical and information sides, exist as the main obstacles in its widespread applications. In order to fill this gap, a bio-inspired LIDA cognitive-based Digital Twin architecture is proposed, so as to achieve unmanned maintenance of machine tools through a self-constructed, self-evaluated, and self-optimized manner. A three phases process in the architecture, including the physical phase, virtual phase, and service phase, is further introduced to support the cognitive cycle for unmanned maintenance of machine tools. An illustrative example is depicted in the unmanned fault diagnosis on the rolling bearing of a drilling platform, which validates the feasibility and advantages of the proposed architecture. As an explorative study, it is wished that this work provides useful insights for unmanned maintenance of machine tools in a dynamic production environment.

Interpretation of Guidelines for medical observation management of close contacts with COVID-19 cases Part 3: home-based medical observation

Effectively blocking the transmission route of coronavirus and protecting the susceptible population play significant roles in the control of COVID-19 pandemic.Strengthening home-based medical observation is one of the key points in preventing the spread of SARS-CoV-2 virus in families and communities.Therefore, in order to meet the needs for COVID-19 prevention and control in Beijing, a group of experts organized by Beijing Association of Preventive Medicine developed the Guidelines for medical observation management of close contacts with COVID-19 cases Part 3: home-based medical observation（T/BPMA007.3-2020）, which offers the specific provisions for close contacts of COVID-19 cases who need home-based medical observation as well as home environmental condition, prevention and control requirements, waste disposal, disinfection, community prevention and control work requirements, basic requirements for training and education and management guidelines.It provides standard support for home-based medical observation of close contacts with COVID-19 cases.

Effect of SARS-CoV-2 infection on asthma patients.

Background: SARS-CoV-2 causes coronavirus disease 2019 (COVID-19), a new coronavirus pneumonia, and containing such an international pandemic catastrophe remains exceedingly difficult. Asthma is a severe chronic inflammatory airway disease that is becoming more common around the world. However, the link between asthma and COVID-19 remains unknown. Through bioinformatics analysis, this study attempted to understand the molecular pathways and discover potential medicines for treating COVID-19 and asthma. Methods: To investigate the relationship between SARS-CoV-2 and asthma patients, a transcriptome analysis was used to discover shared pathways and molecular signatures in asthma and COVID-19. Here, two RNA-seq data (GSE147507 and GSE74986) from the Gene Expression Omnibus were used to detect differentially expressed genes (DEGs) in asthma and COVID-19 patients to find the shared pathways and the potential drug candidates. Results: There were 66 DEGs in all that were classified as common DEGs. Using a protein-protein interaction (PPI) network created using various bioinformatics techniques, five hub genes were found. We found that asthma has some shared links with the progression of COVID-19. Additionally, protein-drug interactions with common DEGs were also identified in the datasets. Conclusion: We investigated possible links between COVID-19 and asthma using bioinformatics databases, which might be useful in treating COVID-19 patients. More studies on populations affected by these diseases are needed to elucidate the molecular mechanism behind their association.

Development of functional anti-Gn nanobodies specific for SFTSV based on next-generation sequencing and proteomics.

Severe fever with thrombocytopenia syndrome (SFTS) is an acute infectious disease caused by novel bunyavirus (SFTSV), with a mortality rate of 6.3% ~ 30%. To date, there is no specific treatment for SFTS. Previously, we demonstrated that SFTSV surface glycoprotein (Glycoprotein N, Gn) was a potential target for the development of SFTS vaccine or therapeutic antibodies, and anti-Gn neutralizing antibodies played a protective role in SFTS infection. Compared with traditional antibodies, nanobodies from camelids have various advantages, including small molecular weight, high affinity, low immunogenicity, convenient production by gene engineering, etc. In this study, we combined next-generation sequencing (NGS) with proteomics technology based on affinity purification-mass spectrometry (AP-MS) and bioinformatics analysis to high-throughput screen monoclonal anti-Gn nanobodies from camel immunized with Gn protein. We identified 19 anti-Gn monoclonal nanobody sequences, of which six sequences were selected for recombinant protein expression and purification. Among these six anti-Gn nanobodies, nanobody 57,493 was validated to be highly specific for Gn. The innovative high-throughput technical route developed in this study could also be expanded to the production of nanobodies specific for other viruses like SARS-CoV-2.

Prevalence and influencing factors of psychological distress among nurses in sichuan, china during the COVID-19 outbreak: A cross-sectional study

Background The COVID-19 pandemic has spread across the world. Nurses have inevitably been influenced by it. Purpose To investigate the prevalence and influencing factors of psychological distress among nurses in Sichuan, China over the COVID-19 outbreak. Methods This study used a cross-sectional survey design. Thousand eight hundred and seventy nurses who worked in COVID-19-designated hospitals participated in the study during the pandemic. Data was collected online between February 8 and February 13, 2020. The self-designed General Information Questionnaire, the General Health Questionnaire-12, the Perception of Hospital Safety Climate Scale, and the Simplified Coping Style Questionnaire were used. The binomial logistic regression model was applied to assess the association between psychological distress and potential explanatory variables. Findings At the beginning of the epidemy of the COVID-19 outbreak, 12% of nurses were found to experience psychological distress. The main influencing factors were personal precautionary measures at work, discomfort caused by protective equipment, perception of the hospital safety climate, coping style, and professional title. Conclusions In the pandemic, wearing protective equipment correctly, a safe hospital climate, and positive coping style for nurses could be beneficial for nurses' mental health. Nurse managers should take measures to build a safe hospital climate.

Evaluating the ability of the NLHA2 and artificial neural network models to predict COVID-19 severity, and comparing them with the four existing scoring systems.

To improve the identification and subsequent intervention of COVID-19 patients at risk for ICU admission, we constructed COVID-19 severity prediction models using logistic regression and artificial neural network (ANN) analysis and compared them with the four existing scoring systems (PSI, CURB-65, SMARTCOP, and MuLBSTA). In this prospective multi-center study, 296 patients with COVID-19 pneumonia were enrolled and split into the General-Ward-Care group (N = 238) and the ICU-Admission group (N = 58). The PSI model (AUC = 0.861) had the best results among the existing four scoring systems, followed by SMARTCOP (AUC = 0.770), motified-MuLBSTA (AUC = 0.761), and CURB-65 (AUC = 0.712). Data from 197 patients (training set) were analyzed for modeling. The beta coefficients from logistic regression were used to develop a severity prediction model and risk score calculator. The final model (NLHA2) included five covariates (consumes alcohol, neutrophil count, lymphocyte count, hemoglobin, and AKP). The NLHA2 model (training: AUC = 0.959; testing: AUC = 0.857) had similar results to the PSI model, but with fewer variable items. ANN analysis was used to build another complex model, which had higher accuracy (training: AUC = 1.000; testing: AUC = 0.907). Discrimination and calibration were further verified through bootstrapping (2000 replicates), Hosmer-Lemeshow goodness of fit testing, and Brier score calculation. In conclusion, the PSI model is the best existing system for predicting ICU admission among COVID-19 patients, while two newly-designed models (NLHA2 and ANN) performed better than PSI, and will provide a new approach for the development of prognostic evaluation system in a novel respiratory viral epidemic.

Effect of SARS-CoV-2 infection on asthma patients

Background SARS-CoV-2 causes coronavirus disease 2019 (COVID-19), a new coronavirus pneumonia, and containing such an international pandemic catastrophe remains exceedingly difficult. Asthma is a severe chronic inflammatory airway disease that is becoming more common around the world. However, the link between asthma and COVID-19 remains unknown. Through bioinformatics analysis, this study attempted to understand the molecular pathways and discover potential medicines for treating COVID-19 and asthma. Methods To investigate the relationship between SARS-CoV-2 and asthma patients, a transcriptome analysis was used to discover shared pathways and molecular signatures in asthma and COVID-19. Here, two RNA-seq data (GSE147507 and GSE74986) from the Gene Expression Omnibus were used to detect differentially expressed genes (DEGs) in asthma and COVID-19 patients to find the shared pathways and the potential drug candidates. Results There were 66 DEGs in all that were classified as common DEGs. Using a protein-protein interaction (PPI) network created using various bioinformatics techniques, five hub genes were found. We found that asthma has some shared links with the progression of COVID-19. Additionally, protein-drug interactions with common DEGs were also identified in the datasets. Conclusion We investigated possible links between COVID-19 and asthma using bioinformatics databases, which might be useful in treating COVID-19 patients. More studies on populations affected by these diseases are needed to elucidate the molecular mechanism behind their association.

Delayed-Onset PTSD and Coping Strategies of Chinese College Students During the COVID-19 Pandemic.

Coronavirus disease 2019 (COVID-19) has become a pandemic, and many Chinese college students both in China and abroad were house-quarantined. This study aimed to investigate the prevalence and symptoms of delayed-onset post-traumatic stress disorder (PTSD) and coping strategies among Chinese overseas and domestic college students during this pandemic. A questionnaire was opportunistically distributed to Chinese college students studying both domestically and abroad six months after the COVID-19 outbreak. The questionnaire consisted of IES-R, SCSQ, and SSRS. The average score of delayed-onset PTSD in our population was 21.411 (full mark, 88 points), which reflected a total high level of delayed-onset PTSD symptoms. Statistical differences were shown between students who have been back to universities during the pandemic or not in the hyperarousal dimension (p = 0.016). Three coping strategies were recognized to influence the respondent's delayed-onset PTSD symptoms, and there was a significant correlation between social support and the coping strategies students chose. A moderate to high level of delayed-onset PTSD was observed among both Chinese overseas and domestic college students 6 months after the COVID-19 outbreak. The useful coping strategies and powerful social supports are significantly important to help them stay mentally healthy and alleviate delayed-onset PTSD during the COVID-19 pandemic.

Discrete simulation analysis of COVID-19 and prediction of isolation bed numbers.

BACKGROUND: The outbreak of COVID-19 has been defined by the World Health Organization as a pandemic, and containment depends on traditional public health measures. However, the explosive growth of the number of infected cases in a short period of time has caused tremendous pressure on medical systems. Adequate isolation facilities are essential to control outbreaks, so this study aims to quickly estimate the demand and number of isolation beds. METHODS: We established a discrete simulation model for epidemiology. By adjusting or fitting necessary epidemic parameters, the effects of the following indicators on the development of the epidemic and the occupation of medical resources were explained: (1) incubation period, (2) response speed and detection capacity of the hospital, (3) disease healing time, and (4) population mobility. Finally, a method for predicting the number of isolation beds was summarized through multiple linear regression. This is a city level model that simulates the epidemic situation from the perspective of population mobility. RESULTS: Through simulation, we show that the incubation period, response speed and detection capacity of the hospital, disease healing time, degree of population mobility, and infectivity of cured patients have different effects on the infectivity, scale, and duration of the epidemic. Among them, (1) incubation period, (2) response speed and detection capacity of the hospital, (3) disease healing time, and (4) population mobility have a significant impact on the demand and number of isolation beds (P <0.05), which agrees with the following regression equation: N = P × (-0.273 + 0.009I + 0.234M + 0.012T1 + 0.015T2) × (1 + V).

The networks of m6A-SARS-CoV-2 related genes and immune infiltration patterns in idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with a poor prognosis. The current coronavirus disease 2019 (COVID-19) shares some similarities with IPF. SARS-CoV-2 related genes have been reported to be broadly regulated by N6-methyladenosine (m6A) RNA modification. Here, we identified the association between m6A methylation regulators, COVID-19 infection pathways, and immune responses in IPF. The characteristic gene expression networks and immune infiltration patterns of m6A-SARS-CoV-2 related genes in different tissues of IPF were revealed. We subsequently evaluated the influence of these related gene expression patterns and immune infiltration patterns on the prognosis/lung function of IPF patients. The IPF cohort was obtained from the Gene Expression Omnibus dataset. Pearson correlation analysis was performed to identify the correlations among genes or cells. The CIBERSORT algorithm was used to assess the infiltration of 22 types of immune cells. The least absolute shrinkage and selection operator (LASSO) and proportional hazards model (Cox model) were used to develop the prognosis prediction model. Our research is pivotal for further understanding of the cellular and genetic links between IPF and SARS-CoV-2 infection in the context of the COVID-19 pandemic, which may contribute to providing new ideas for prognosis assessment and treatment of both diseases.

The Influence of Public Transport Delays on Mobility on Demand Services

Demand for different modes of transportation clearly interacts. If public transit is delayed or out of service, customers might use mobility on demand (MoD), including taxi and carsharing for their trip, or discard the trip altogether, including a first and last mile that might otherwise be covered by MoD. For operators of taxi and carsharing services, as well as dispatching agencies, understanding increasing demand, and changing demand patterns due to outages and delays is important, as a more precise demand prediction allows for them to more profitably operate. For public authorities, it is paramount to understand this interaction when regulating transportation services. We investigate the interaction between public transit delays and demand for carsharing and taxi, as measured by the fraction of demand variance that can be explained by delays and the changing OD-patterns. A descriptive analysis of the public transit data set yields that delays and MoD demand both highly depend on the weekday and time of day, as well as the location within the city, and that delays in the city and in consecutive time intervals are correlated. Thus, demand variations must by corrected for these external influences. We find that demand for taxi and carsharing increases if the delay of public transit increases and this effect is stronger for taxi. Delays can explain at least 4.1% (carsharing) and 18.8% (taxi) of the demand variance, which is a good result when considering that other influencing factors, such as time of day or weather exert stronger influences. Further, planned public transit outages significantly change OD-patterns of taxi and carsharing.

Evaluation of psychological stress in scientific researchers during the 2019-2020 COVID-19 outbreak in China.

BACKGROUND: Beginning in December 2019, coronavirus disease 2019 (COVID-19) caused an outbreak of infectious pneumonia. The Chinese government introduced a series of grounding measures to prevent the spread of COVID-19. The living and working patterns of many scientific researchers also underwent significant changes during this period. METHODS: An opportunity sample (n = 251) was obtained in China using a questionnaire with 42 questions on scientific research progress and psychological stress during the COVID-19 epidemic. RESULTS: Of the 251 participants, 76.9% indicated that their research was affected by the COVID-19 outbreak, and participants who were affected by the outbreak had higher stress levels than those who were not affected. Participants who conducted COVID-19 research and indicated concern that they would fail to finish the research on time were more likely to indicate high levels of stress. Respondents indicated that extending deadlines (64.1%), receiving support from superiors for research (51.8%), and increasing benefits for researchers (51.0%) would likely relieve outbreak-related stress. CONCLUSION: The COVID-19 outbreak had a major impact on the experiments of researchers in the life sciences, especially in basic and clinical medicine. It has also caused high levels of psychological stress in these populations. Measures should be taken to relieve psychological pressure on basic medical researchers and students who will soon complete their degrees (e.g., Master's and PhD candidates in graduation years).

Basic epidemiological parameter values from data of real-world in mega-cities: the characteristics of COVID-19 in Beijing, China.

BACKGROUND: With the spread of SARS-CoV-2 worldwide, understanding the basic epidemiological parameter values of COVID-19 from real-world data in mega-cities is essential for disease prevention and control. METHODS: To investigate the epidemiological parameters in SARS-CoV-2 infected cases in Beijing, we studied all confirmed cases and close contacts in Beijing from Jan 1st to Apr 3rd 2020. The epidemiological and virological characteristics of SARS-CoV-2 were analyzed. RESULTS: A total of 602 cases were positive for SARS-CoV-2, including 585 confirmed patients and 17 asymptomatic infections. The imported cases were mainly from Wuhan initially and then from abroad. Among 585 confirmed case-patients, the median age was 39 years old. The mean incubation period was 6.3 days. The secondary attack rate among households was higher than social contacts (15.6 vs 4.6%). The secondary attack rate of healthcare workers (HCWs) was higher than non-HCWs' (7.3 vs 4.2%). The basic reproduction number was 2.0, and the average serial interval was 7.6 days. No significant genetic variant was identified. CONCLUSIONS: The transmissibility of SARS-CoV-2 was relatively high, especially among households and from HCWs, which draws specific public health attention. So far, no evidence of widespread circulation of SARS-CoV-2 in communities in Beijing was found.