How to Promote Online Education through Educational Software-An Analytical Study of Factor Analysis and Structural Equation Modeling with Chinese Users as an Example

Online learning has emerged as a fresh method to successfully prevent teacher and student gatherings as well as the propagation of viruses in the context of the ongoing influence of the COVID-19. A problem deserving of consideration is how to increase users' desire to participate in online learning through online class APPs, identify the variables that affect users' use of them, and create a useful assessment scale. In this study, user ratings from 68 students who had used an online class APP were collected using the combination of qualitative and quantitative research, and 200 online questionnaires were sent out to complement the interview findings, based on which 328 assessment questionnaires were gathered and 23 valid items were obtained. The influencing elements that had an impact on users' online learning experiences were identified using factor analysis, and the relationships among the components were investigated using structural equation modeling. Perceived benefits are the main influencing factors, subjective norms and functional quality are the direct factors influencing users' perceived benefits, and self-efficacy is influenced by subjective norms while promoting the perception of functional quality. The factors influencing users' use of online class APPs are ultimately identified as perceived benefits, functional quality and self-efficacy. In order to facilitate users' online learning, user psychological traits, social ties and software functions should be integrated into a cohesive system while designing online class APPs.

BA.2.12.1, BA.4 and BA.5 escape antibodies elicited by Omicron infection.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron sublineages BA.2.12.1, BA.4 and BA.5 exhibit higher transmissibility than the BA.2 lineage1. The receptor binding and immune-evasion capability of these recently emerged variants require immediate investigation. Here, coupled with structural comparisons of the spike proteins, we show that BA.2.12.1, BA.4 and BA.5 (BA.4 and BA.5 are hereafter referred collectively to as BA.4/BA.5) exhibit similar binding affinities to BA.2 for the angiotensin-converting enzyme 2 (ACE2) receptor. Of note, BA.2.12.1 and BA.4/BA.5 display increased evasion of neutralizing antibodies compared with BA.2 against plasma from triple-vaccinated individuals or from individuals who developed a BA.1 infection after vaccination. To delineate the underlying antibody-evasion mechanism, we determined the escape mutation profiles2, epitope distribution3 and Omicron-neutralization efficiency of 1,640 neutralizing antibodies directed against the receptor-binding domain of the viral spike protein, including 614 antibodies isolated from people who had recovered from BA.1 infection. BA.1 infection after vaccination predominantly recalls humoral immune memory directed against ancestral (hereafter referred to as wild-type (WT)) SARS-CoV-2 spike protein. The resulting elicited antibodies could neutralize both WT SARS-CoV-2 and BA.1 and are enriched on epitopes on spike that do not bind ACE2. However, most of these cross-reactive neutralizing antibodies are evaded by spike mutants L452Q, L452R and F486V. BA.1 infection can also induce new clones of BA.1-specific antibodies that potently neutralize BA.1. Nevertheless, these neutralizing antibodies are largely evaded by BA.2 and BA.4/BA.5 owing to D405N and F486V mutations, and react weakly to pre-Omicron variants, exhibiting narrow neutralization breadths. The therapeutic neutralizing antibodies bebtelovimab4 and cilgavimab5 can effectively neutralize BA.2.12.1 and BA.4/BA.5, whereas the S371F, D405N and R408S mutations undermine most broadly sarbecovirus-neutralizing antibodies. Together, our results indicate that Omicron may evolve mutations to evade the humoral immunity elicited by BA.1 infection, suggesting that BA.1-derived vaccine boosters may not achieve broad-spectrum protection against new Omicron variants.

Could Air Quality Get Better during Epidemic Prevention and Control in China? An Analysis Based on Regression Discontinuity Design

Though many scholars and practitioners are paying more attention to the health and life of the public after the COVID-19 outbreak, extant literature has so far failed to explore the variation of ambient air quality during this pandemic. The current study attempts to fill the gap by disentangling the causal effects of epidemic prevention on air quality in China, measured by the individual pollutant dimensionless index, from other confounding factors. Using the fixed effects model, this article finds that five air indicators, PM2.5, PM10, CO, NO2, and SO2, significantly improved during the shutdown period, with NO2 showing the most improvement. On the contrary, O3 shows an inverse pattern, that is, O3 gets worse unexpectedly. The positive impact of epidemic prevention on air quality, especially in terms of PM2.5, PM10, and NO2, become manifest five days after the resumption of labor, indicated by the result of a regression discontinuity design. These findings are still robust and consistent after the dataset of 2019 as a counterfactual sample is utilized. The findings of this paper make contributions to both environmental governance and pandemic prevention, with relevant guidelines regarding the health and life of the public and governmental behavioral management strategies discussed.

The Influences of COVID-19 on Patients with Chronic Kidney Disease: A Multicenter Cross-Sectional Study (preprint)

Background: The outbreak of coronavirus disease 2019 (COVID-19) has attracted global attention. This study aimed at exploring the change of illness, daily life and psychological responses during the pandemic of COVID-19 among chronic kidney disease patients.Methods: The study was conducted by collecting the questionnaires in 5 nephrology centers. The questionnaire consisted of two main parts: the influences of COVID-19 and assessment of anxiety by using Self-Rating Anxiety Scale. The first part included (1) basic demographic data; (2) the influences of COVID-19 on the illness and daily life; (3) patients’ psychological responses during the epidemic.Findings: 612 patients were included and divided into two groups according to eGFR. 96 patients (34%) in CKD stages1-2 group and 141 patients (42.7%) in CKD stages 3-5 group had reduced their follow-up frequency (p=0.031). More patients with CKD stages 1-2 consulted online (25.9%), p=0.005. Besides, patients with CKD stages 3-5 group tended to be more anxious about follow-up(p=0.002), fearful of being infected with COVID-19 (P=0.009), more likely to feel symptoms getting worse (p=0.006) and gained more help from medical staff during the pandemic period (p=0.038). The standard scores of SAS were 48.58±7.082 and 51.19±5.944 in CKD stages 1-2 group and CKD stages 3-5 group, respectively (p<0.001). And there were significant differences in the severity of anxiety (p=0.004).Interpretation: COVID-19 had a greater impact on patients with CKD stages 3-5 than stages 1-2 in illness, daily life and psychological disorder. Patients with CKD stages 3-5 were more anxious during the pandemic of COVID-19. Funding: None.Declaration of Interests: The authors declare that they have no conflict of interest.Ethics Approval Statement: The study was in compliance with the Declaration of Helsinki and was approved by the ethical committee of West China Hospital of Sichuan University.

Atmospheric pressure and population density as super-factors influencing the transmission of coronavirus disease 2019 (COVID-19) (preprint)

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiologic agent of coronavirus disease (COVID-19), recently emerged and led to a global pandemic with enormous consequent losses to global health and economies. To date, more than 30 million cases have been reported globally and have affected almost every with varying degrees. Meteorological and non-meteorological factors such as temperature, relative humidity, atmospheric pressure, population density, and latitude, are considered critical in virus transmission. To explore the correlation of environmental factors with the transmission of SARS-CoV-2 based on parameters including infection rate, effective reproduction number, and compound growth rate, we analyzed data of confirmed cases from 487 counties in the United States. We found a small impact of temperature and humidity on virus transmission, but observed a considerable positive influence of atmospheric pressure and population density on virus transmission. Geographic areas and seasons (autumn and winter), with exposure to higher atmospheric pressure, are more likely at higher risk of an outbreak. Social distancing and other measures could be effective strategies to combat COVID-19 outbreaks in densely populated areas. Additional studies are needed to explore the mechanisms underlying the relationship between meteorological parameters and transmission of SARS-CoV-2.

Artesunate interacts with the vitamin D receptor to reverse sepsis-induced immunosuppression in a mouse model via enhancing autophagy.

BACKGROUND AND PURPOSE: Immunosuppression is the predominant cause of mortality for sepsis because of failure to eradicate pathogens. No effective and specific drugs capable of reversing immunosuppression are clinically available. Evidences implicate the involvement of the vitamin D receptor (NR1I1) in sepsis-induced immunosuppression. The anti-malarial artesunate was investigated to determine action on sepsis-induced immunosuppression. EXPERIMENTAL APPROACH: The effect of artesunate on sepsis-induced immunosuppression was investigated in mice and human and mice cell lines. Bioinformatics predicted vitamin D receptor as a candidate target for artesunate, which was then identified using PCR and immunoblotting. Vdr, Atg16l1 and NF-κB p65 were modified to investigate artesunate 's effect on pro-inflammatory cytokines release, bacterial clearance and autophagy activities in sepsis-induced immunosuppression. KEY RESULTS: Artesunate significantly reduced the mortality of caecal ligation and puncture (CLP)-induced sepsis immunosuppression mice challenged with Pseudomonas aeruginosa and enhanced pro-inflammatory cytokine release and bacterial clearance to reverse sepsis-induced immunosuppression in vivo and in vitro. Mechanistically, artesunate interacted with vitamin D receptor, inhibiting its nuclear translocation, which influenced ATG16L1 transcription and subsequent autophagy activity. Artesunate inhibited the physical interaction between vitamin D receptor and NF-κB p65 in LPS-tolerant macrophages and then promoted the nuclear translocation of NF-κB p65, which activated the transcription of NF-κB p65 target genes such as pro-inflammatory cytokines. CONCLUSION AND IMPLICATIONS: Our findings provide evidence that artesunate interacted with vitamin D receptor to reverse sepsis-induced immunosuppression in an autophagy and NF-κB-dependent manner, highlighting a novel approach for sepsis treatment and drug repurposing of artesunate has a bidirectional immunomodulator.

Combining Visible Light and Infrared Imaging for Efficient Detection of Respiratory Infections such as COVID-19 on Portable Device (preprint)

Coronavirus Disease 2019 (COVID-19) has become a serious global epidemic in the past few months and caused huge loss to human society worldwide. For such a large-scale epidemic, early detection and isolation of potential virus carriers is essential to curb the spread of the epidemic. Recent studies have shown that one important feature of COVID-19 is the abnormal respiratory status caused by viral infections. During the epidemic, many people tend to wear masks to reduce the risk of getting sick. Therefore, in this paper, we propose a portable non-contact method to screen the health condition of people wearing masks through analysis of the respiratory characteristics. The device mainly consists of a FLIR one thermal camera and an Android phone. This may help identify those potential patients of COVID-19 under practical scenarios such as pre-inspection in schools and hospitals. In this work, we perform the health screening through the combination of the RGB and thermal videos obtained from the dual-mode camera and deep learning architecture.We first accomplish a respiratory data capture technique for people wearing masks by using face recognition. Then, a bidirectional GRU neural network with attention mechanism is applied to the respiratory data to obtain the health screening result. The results of validation experiments show that our model can identify the health status on respiratory with the accuracy of 83.7\% on the real-world dataset. The abnormal respiratory data and part of normal respiratory data are collected from Ruijin Hospital Affiliated to The Shanghai Jiao Tong University Medical School. Other normal respiratory data are obtained from healthy people around our researchers. This work demonstrates that the proposed portable and intelligent health screening device can be used as a pre-scan method for respiratory infections, which may help fight the current COVID-19 epidemic.

Portable Health Screening Device of Respiratory Infections (preprint)

The COVID-19 epidemic was listed as a public health emergency of international concern by the WHO on January 30, 2020. To curb the secondary spread of the epidemic, many public places were equipped with thermal imagers to check the body temperature. However, the COVID-19 pneumonia has concealed symptoms: the first symptom may not be fever, and can be shortness of breath. During epidemic prevention, many people tend to wear masks. Therefore, in this demo paper, we proposed a portable non-contact healthy screening system for people wearing masks, which can simultaneously obtain body temperature and respiration state. This system consists of three modules viz. thermal image collection module, health indicator calculation module and health assessment module. In this system, the thermal video of human faces is first captured through a portable thermal imaging camera. Then, body temperature and respiration state are extracted from the video and are imported into the following health assessment module. Finally, the screening result can be obtained. The results of preliminary experiments show that this syetem can give an accurate screening result within 15 seconds. This system can be applied to many application scenarios such as community and campus.