Understanding consumers' intention to use autonomous delivery vehicles during the COVID-19 pandemic: The stimulus-organism-response approach (preprint)

Autonomous delivery vehicles (ADVs) have attracted much attention since COVID-19. As an emerging last-mile delivery tool, the large-scale implementation of ADVs depends on consumers’ willingness to adopt them. However, until recently, research on user acceptance and adopting emerging technology has been relatively rare. The present study is the first that applies the stimulus-organism-response (S-O-R) model to investigate how stimulating factors (COVID-19 risk and human-computer interaction) affect consumers’ intention to use ADVs in last-mile delivery by triggering consumers’ inner states (delivery risk, price sensitivity, perceived enjoyment, trust in technology). Quantitative data based on university students in Zhejiang, China, was collected through an online survey platform (n = 298), and structural equation modeling was undertaken. The results reveal that COVID-19 risk and human-computer interaction can lead to adoption behaviors by triggering different inner states of consumers. Further, innovation is also considered to be one of the factors determining behavioral intention. The findings have profound theoretical and practical contributions to last-mile delivery and technology acceptance research.

Minimalist Nanocomplex with Dual Regulation of Endothelial Function and Inflammation for Targeted Therapy of Inflammatory Vascular Diseases.

Vascular disorders, characterized by vascular endothelial dysfunction combined with inflammation, are correlated with numerous fatal diseases, such as coronavirus disease-19 and atherosclerosis. Achieving vascular normalization is an urgent problem that must be solved when treating inflammatory vascular diseases. Inspired by the vascular regulatory versatility of nitric oxide (NO) produced by endothelial nitric oxide synthase (eNOS) catalyzing l-arginine (l-Arg), the eNOS-activating effects of l-Arg, and the powerful anti-inflammatory and eNOS-replenishing effects of budesonide (BUD), we constructed a bi-prodrug minimalist nanoplatform co-loaded with BUD and l-Arg via polysialic acid (PSA) to form BUD-l-Arg@PSA. This promoted vascular normalization by simultaneously regulating vascular endothelial dysfunction and inflammation. Mediated by the special affinity between PSA and E-selectin, which is highly expressed on the surface of activated endothelial cells (ECs), BUD-l-Arg@PSA selectively accumulated in activated ECs, targeted eNOS expression and activation, and promoted NO production. Consequently, the binary synergistic regulation of the NO/eNOS signaling pathway occurred and improved vascular endothelial function. NO-induced nuclear factor-kappa B alpha inhibitor (IκBα) stabilization and BUD-induced nuclear factor-kappa B (NF-κB) response gene site occupancy achieved dual-site blockade of the NF-κB signaling pathway, thereby reducing the inflammatory response and inhibiting the infiltration of inflammation-related immune cells. In a renal ischemia-reperfusion injury mouse model, BUD-l-Arg@PSA reduced acute injury. In an atherosclerosis mouse model, BUD-l-Arg@PSA decreased atherosclerotic plaque burden and improved vasodilation. This represents a revolutionary therapeutic strategy for inflammatory vascular diseases.

The Efficacy of WeChat-Based Parenting Training on the Psychological Well-being of Mothers With Children With Autism During the COVID-19 Pandemic: Quasi-Experimental Study.

BACKGROUND: During the COVID-19 pandemic, special education schools for children in most areas of China were closed between the end of January and the beginning of June in 2020. The sudden interruption in schooling and the pandemic itself caused parents to be anxious and even to panic. Mobile-based parenting skills education has been demonstrated to be an effective method for improving the psychological well-being of mothers with children with autism. However, whether it can improve the psychological states of mothers in the context of the COVID-19 pandemic is a subject that should be urgently investigated. OBJECTIVE: The aim of this study is to evaluate the efficacy of WeChat-based parenting training on anxiety, depression, parenting stress, and hope in mothers with children with autism, as well as the feasibility of the program during the COVID-19 pandemic. METHODS: This was a quasi-experimental trial. A total of 125 mothers with preschool children with autism were recruited in January 2020. The participants were assigned to the control group (n=60), in which they received routine care, or the intervention group (n=65), in which they received the 12-week WeChat-based parenting training plus routine care, according to their preferences. Anxiety, depression, parenting stress, hope, satisfaction, and adherence to the intervention were measured at three timepoints: baseline (T0), postintervention (T1), and a 20-week follow-up (T2). RESULTS: In total, 109 mothers completed the T1 assessment and 104 mothers completed the T2 assessment. The results of the linear mixed model analysis showed statistically significant group × time interaction effects for the intervention on anxiety (F=14.219, P<.001), depression (F=26.563, P<.001), parenting stress (F=68.572, P<.001), and hope (F=197.608, P<.001). Of all mothers in the intervention group, 90.4% (48.8/54) reported that they were extremely satisfied with the WeChat-based parenting training. In total, 40.0% (26/65) logged their progress in home training each week and 61.5% (40/65) logged their progress more than 80% of the time for all 20 weeks. CONCLUSIONS: The WeChat-based parenting training is acceptable and appears to be an effective approach for reducing anxiety, depression, and parenting stress, as well as increasing hope in mothers with children with autism during the global COVID-19 pandemic. Future studies with rigorous designs and longer follow-up periods are needed to further detect the effectiveness of the WeChat-based parenting training. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2000031772; http://www.chictr.org.cn/showproj.aspx?proj=52165.

The Efficacy of WeChat-Based Parenting Training on the Psychological Well-being of Mothers With Children With Autism During the COVID-19 Pandemic: Quasi-Experimental Study.

BACKGROUND: During the COVID-19 pandemic, special education schools for children in most areas of China were closed between the end of January and the beginning of June in 2020. The sudden interruption in schooling and the pandemic itself caused parents to be anxious and even to panic. Mobile-based parenting skills education has been demonstrated to be an effective method for improving the psychological well-being of mothers with children with autism. However, whether it can improve the psychological states of mothers in the context of the COVID-19 pandemic is a subject that should be urgently investigated. OBJECTIVE: The aim of this study is to evaluate the efficacy of WeChat-based parenting training on anxiety, depression, parenting stress, and hope in mothers with children with autism, as well as the feasibility of the program during the COVID-19 pandemic. METHODS: This was a quasi-experimental trial. A total of 125 mothers with preschool children with autism were recruited in January 2020. The participants were assigned to the control group (n=60), in which they received routine care, or the intervention group (n=65), in which they received the 12-week WeChat-based parenting training plus routine care, according to their preferences. Anxiety, depression, parenting stress, hope, satisfaction, and adherence to the intervention were measured at three timepoints: baseline (T0), postintervention (T1), and a 20-week follow-up (T2). RESULTS: In total, 109 mothers completed the T1 assessment and 104 mothers completed the T2 assessment. The results of the linear mixed model analysis showed statistically significant group × time interaction effects for the intervention on anxiety (F=14.219, P<.001), depression (F=26.563, P<.001), parenting stress (F=68.572, P<.001), and hope (F=197.608, P<.001). Of all mothers in the intervention group, 90.4% (48.8/54) reported that they were extremely satisfied with the WeChat-based parenting training. In total, 40.0% (26/65) logged their progress in home training each week and 61.5% (40/65) logged their progress more than 80% of the time for all 20 weeks. CONCLUSIONS: The WeChat-based parenting training is acceptable and appears to be an effective approach for reducing anxiety, depression, and parenting stress, as well as increasing hope in mothers with children with autism during the global COVID-19 pandemic. Future studies with rigorous designs and longer follow-up periods are needed to further detect the effectiveness of the WeChat-based parenting training. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2000031772; http://www.chictr.org.cn/showproj.aspx?proj=52165.

Management of Endovascular Treatment for Acute Ischemic Stroke During the COVID-19 Pandemic at a Single Institution in Beijing, China: A Brief Report.

BACKGROUND: The coronavirus disease (COVID-19) pandemic is currently a major challenge for health care systems around the world. For a time-sensitive emergency such as acute ischemic stroke (AIS), streamlined workflow times are essential to ensure good clinical outcomes. METHODS: The aim of this single-center, retrospective, observational study was to describe changes in stroke workflow patterns and clinical care during the COVID-19 pandemic. Data from AIS patients undergoing emergent endovascular treatment (EVT) between 23 January and 8 April 2020 were retrospectively collected and compared with data from patients admitted during a similar period in 2019. The primary outcome was difference in time from symptom onset to recanalization. Secondary outcomes included workflow times, clinical management, discharge outcomes, and health-economic data. RESULTS: In all, 21 AIS patients were admitted for emergent EVT during the 77-day study period, compared with 42 cases in 2019. Median time from symptom onset to recanalization was 132 minutes longer during the pandemic compared with the previous year (672 vs. 540 min, P=0.049). Patients admitted during the pandemic had a higher likelihood of endotracheal intubation (84.6% vs. 42.4%, P<0.05) and a higher incidence of delayed extubation after EVT (69.2% vs. 45.5%, P<0.05). National Institutes of Health Stroke Scale at hospital discharge was similar in the 2 cohorts, whereas neurointensive care unit stay was longer in patients admitted during the pandemic (10 vs. 7 days, P=0.013) and hospitalization costs were higher (123.9 vs. 95.2 thousand Chinese Yuan, P=0.052). CONCLUSION: Disruptions to medical services during the COVID-19 pandemic has particularly impacted AIS patients undergoing emergent EVT, resulting in increased workflow times. A structured and multidisciplinary protocol should be implemented to minimize treatment delays and maximize patient outcomes.

Gold/Silver Hybrid Nanoparticles with Enduring Inhibition of Coronavirus Multiplication through Multisite Mechanisms.

As a large enveloped RNA virus, coronavirus is of considerable medical and veterinary significance, and anticoronavirus treatment is challenging due to its biodiversity and rapid variability. In this study, Au@Ag nanorods (Au@AgNRs) were successfully synthesized by coating AuNRs with silver and were shown for the first time to have activity against the replication of porcine epidemic diarrhea virus (PEDV). Viral titer analysis demonstrated that Au@AgNRs could inhibit PEDV infection by 4 orders of magnitude at 12 h post-infection, which was verified by viral protein expression analysis. The potential mechanism of action showed that Au@AgNRs could inhibit the entry of PEDV and decrease the mitochondrial membrane potential and caspase-3 activity. Additionally, we demonstrated that a large amount of virus proliferation can cause the generation of reactive oxygen species in cells, and the released Ag+ and exposed AuNRs by Au@AgNRs after the stimulation of reactive oxygen species has superior antiviral activity to ensure long-term inhibition of the PEDV replication cycle. The integrated results support that Au@AgNRs can serve as a potential therapeutic strategy to prevent the replication of coronavirus.

The Perioperative Management of Subarachnoid Hemorrhage During the Coronavirus Disease 2019 Pandemic in China.

BACKGROUND: For most of the international community outside the epicenter, coronavirus disease 2019 (COVID-19) containment is normalizing, and daily medical practice runs parallel to preventing and treating COVID-19. This experience of simultaneously conducting emergent surgery and infection control for COVID-19 disease is useful outside the epicenter during the pandemic. CASE DESCRIPTION: In this single-center retrospective observational study, we enrolled patients with subarachnoid hemorrhage (SAH) who were emergently admitted from January 23 to April 8, 2020. Based on the COVID-19 triage, patients with SAH were divided into 3 categories: positive, negative, and under investigation. During 77 days, 90 patients with SAH were admitted at the center. The median age was 55 years (range, 18-80 years) and 40 patients (44.4%) were male. None was positive, 42 patients were negative, and 48 patients were under investigation for COVID-19 before surgery. During the same period, 9 patients were diagnosed with COVID-19 without nosocomial infection. CONCLUSIONS: Rescuing patients with SAH and containment of COVID-19 benefit from joint prevention and control, a centralized system of equipment distribution and personnel assignment, and quick workflow establishment.

The impact of epidemics on agricultural production and forecast of COVID-19

Purpose This article investigates the mechanism of the direct and indirect effects of epidemics on agricultural production and projects the impact of COVID-19 on agricultural output in China. Design/methodology/approach This article first adopts a dynamic panel model and spatial Durbin model to estimate the direct and indirect effects, followed by a growth accounting method to identify the channels by which epidemics affect agriculture;finally, it projects the overall impact of COVID-19 on agriculture. Findings The incidence rate of epidemics in a province has a negative impact on that province's own agricultural productivity, but the increase in the input factors (land, fertilizer and machinery) can make up for the loss and thus lead to insignificant direct effects. However, this "input-offset-productivity" mechanism fails to radiate to the surrounding provinces and therefore leads to significant indirect/spillover effects. It is projected that COVID-19 will lower China's agricultural growth rate by 0.4%-2.0% in 2020 under different scenarios. Research limitations/implications It is crucial to establish a timely disclosure and sharing system of epidemic information across provinces, improve the support and resilience of agricultural production in the short run and accelerate the process of agricultural modernization in the long run. Originality/value Considering the infectivity of epidemics, this article evaluates the mechanism of the direct and indirect effects by introducing a spatial dynamic model into the growth accounting framework. Moreover, besides the impact on input portfolio and productivity, this article also investigates whether epidemics reshape agricultural production processes due to panic effects and control measures.

An epidemiological modelling approach for COVID-19 via data assimilation.

The global pandemic of the 2019-nCov requires the evaluation of policy interventions to mitigate future social and economic costs of quarantine measures worldwide. We propose an epidemiological model for forecasting and policy evaluation which incorporates new data in real-time through variational data assimilation. We analyze and discuss infection rates in the UK, US and Italy. We furthermore develop a custom compartmental SIR model fit to variables related to the available data of the pandemic, named SITR model, which allows for more granular inference on infection numbers. We compare and discuss model results which conducts updates as new observations become available. A hybrid data assimilation approach is applied to make results robust to initial conditions and measurement errors in the data. We use the model to conduct inference on infection numbers as well as parameters such as the disease transmissibility rate or the rate of recovery. The parameterisation of the model is parsimonious and extendable, allowing for the incorporation of additional data and parameters of interest. This allows for scalability and the extension of the model to other locations or the adaption of novel data sources.

Radiomics Analysis of Computed Tomography helps predict poor prognostic outcome in COVID-19.

Rationale: Given the rapid spread of COVID-19, an updated risk-stratify prognostic tool could help clinicians identify the high-risk patients with worse prognoses. We aimed to develop a non-invasive and easy-to-use prognostic signature by chest CT to individually predict poor outcome (death, need for mechanical ventilation, or intensive care unit admission) in patients with COVID-19. Methods: From November 29, 2019 to February 19, 2020, a total of 492 patients with COVID-19 from four centers were retrospectively collected. Since different durations from symptom onsets to the first CT scanning might affect the prognostic model, we designated the 492 patients into two groups: 1) the early-phase group: CT scans were performed within one week after symptom onset (0-6 days, n = 317); and 2) the late-phase group: CT scans were performed one week later after symptom onset (≥7 days, n = 175). In each group, we divided patients into the primary cohort (n = 212 in the early-phase group, n = 139 in the late-phase group) and the external independent validation cohort (n = 105 in the early-phase group, n = 36 in the late-phase group) according to the centers. We built two separate radiomics models in the two patient groups. Firstly, we proposed an automatic segmentation method to extract lung volume for radiomics feature extraction. Secondly, we applied several image preprocessing procedures to increase the reproducibility of the radiomics features: 1) applied a low-pass Gaussian filter before voxel resampling to prevent aliasing; 2) conducted ComBat to harmonize radiomics features per scanner; 3) tested the stability of the features in the radiomics signature by several image transformations, such as rotating, translating, and growing/shrinking. Thirdly, we used least absolute shrinkage and selection operator (LASSO) to build the radiomics signature (RadScore). Afterward, we conducted a Fine-Gray competing risk regression to build the clinical model and the clinic-radiomics signature (CrrScore). Finally, performances of the three prognostic signatures (clinical model, RadScore, and CrrScore) were estimated from the two aspects: 1) cumulative poor outcome probability prediction; 2) 28-day poor outcome prediction. We also did stratified analyses to explore the potential association between the CrrScore and the poor outcomes regarding different age, type, and comorbidity subgroups. Results: In the early-phase group, the CrrScore showed the best performance in estimating poor outcome (C-index = 0.850), and predicting the probability of 28-day poor outcome (AUC = 0.862). In the late-phase group, the RadScore alone achieved similar performance to the CrrScore in predicting poor outcome (C-index = 0.885), and 28-day poor outcome probability (AUC = 0.976). Moreover, the RadScore in both groups successfully stratified patients with COVID-19 into low- or high-RadScore groups with significantly different survival time in the training and validation cohorts (all P < 0.05). The CrrScore in both groups can also significantly stratify patients with different prognoses regarding different age, type, and comorbidities subgroups in the combined cohorts (all P < 0.05). Conclusions: This research proposed a non-invasive and quantitative prognostic tool for predicting poor outcome in patients with COVID-19 based on CT imaging. Taking the insufficient medical recourse into account, our study might suggest that the chest CT radiomics signature of COVID-19 is more effective and ideal to predict poor outcome in the late-phase COVID-19 patients. For the early-phase patients, integrating radiomics signature with clinical risk factors can achieve a more accurate prediction of individual poor prognostic outcome, which enables appropriate management and surveillance of COVID-19.

The impact of type 2 diabetes and its management on the prognosis of patients with severe COVID-19.

BACKGROUND: Although type 2 diabetes mellitus (T2DM) patients with coronavirus disease 2019 (COVID-19) develop a more severe condition compared to those without diabetes, the mechanisms for this are unknown. Moreover, the impact of treatment with antihyperglycemic drugs and glucocorticoids is unclear. METHODS: From 1584 COVID-19 patients, 364 severe/critical COVID-19 patients with clinical outcome were enrolled for the final analysis, and patients without preexisting T2DM but elevated glucose levels were excluded. Epidemiological data were obtained and clinical status evaluation carried out to assess the impact of T2DM and its management on clinical outcomes. RESULTS: Of 364 enrolled severe COVID-19 inpatients, 114 (31.3%) had a history of T2DM. Twenty-seven (23.7%) T2DM patients died, who had more severe inflammation, coagulation activation, myocardia injury, hepatic injury, and kidney injury compared with non-DM patients. In severe COVID-19 patients with T2DM, we demonstrated a higher risk of all-cause fatality with glucocorticoid treatment (adjusted hazard ratio [HR], 3.61; 95% CI, 1.14-11.46; P = .029) and severe hyperglycemia (fasting plasma glucose ≥11.1 mmol/L; adjusted HR, 11.86; 95% CI, 1.21-116.44; P = .034). CONCLUSIONS: T2DM status aggravated the clinical condition of COVID-19 patients and increased their critical illness risk. Poor fasting blood glucose (≥ 11.1 mmol/L) and glucocorticoid treatment are associated with poor prognosis for T2DM patients with severe COVID-19.