Borderland Economic Resilience under COVID-19: Evidence from China-Russia Border Regions.

The COVID-19 pandemic has had a great impact on the global economy and trade, and border regions have been hit severely because of their high dependency on foreign trade. To understand better the economic impact of COVID-19 on border regions, we developed a COVID-19 economic resilience analytical framework and empirically examined 10 Chinese-Russian border cities in Northeast China. We quantitatively analyzed five dimensions of economic resilience, distinguished four types of shock, and examined the determinants of economic resilience. The results show that: (1) the COVID-19 pandemic has wide-ranging impacts in the border areas, with import-export trade and retail sales of consumer goods being the most vulnerable and sensitive to the shock. The whole economy of the border areas is in the downward stage of the resistance period; (2) from a multi-dimensional perspective, foreign trade and consumption are the most vulnerable components of the borderland economic system, while industrial resilience and income resilience have improved against the trend, showing that they have good crisis resistance; (3) borderland economic resilience is a spatially heterogeneous phenomenon, with each border city showing different characteristics; (4) economic openness, fiscal expenditure, and asset investment are the key drivers of economic resilience, and the interaction between the influencing factors presents a nonlinear and bi-factor enhancement of them. The findings shed light on how border economies can respond to COVID-19, and how they are useful in formulating policies to respond to the crisis.

Acute stress of the typical disinfectant glutaraldehyde-didecyldimethylammonium bromide (GD) on sludge microecology in livestock wastewater treatment plants: Effect and its mechanisms.

Glutaraldehyde and didecyldimethylammonium bromide (GD) is a disinfectant widely used to prevent African swine fever (ASF) in livestock farms. However, the effect of residual GD on the activated sludge microbial ecology of receiving wastewater treatment plants (WWTPs) remains largely unknown. In this study, seven simulated systems were established to research the effects of GD on WWTPs and reveal the underlying mechanisms of microecological responses to GD at different concentrations. Both the nitrogen and carbon removal rates decreased with increasing GD concentrations, and nitrogen metabolism was inhibited more obviously, but the inhibition weakened with increasing stress duration. Microorganisms activated their SoxRS systems to promote ATP synthesis and electron transfer to support the hydrolysis and efflux of GD by producing a small number of ROS when exposed to GD at less than 1 mg/L. The overproduction of ROS led to a decrease of antioxidant and nitrogen removal enzyme activities, and upregulation of the porin gene increased the risk of GD entering the intracellular space upon exposure to GD at concentrations higher than 1 mg/L. Some denitrifiers survived via resistance and their basic capabilities of sugar metabolism and nitrogen assimilation. Notably, low concentrations of disinfectants could promote vertical and horizontal transfer of multiple resistance genes, especially aminoglycosides, among microorganisms, which might increase not only the adaptation capability of denitrifiers but also the risk to ecological systems. Therefore, the risks of disinfectants targeting ASF on ecology and health as well as the effects of disinfectant residuals from the COVID-19 epidemic should receive more attention.

A case report of possible concurrent vasculitis in vertebral bodies and partial transverse myelitis following COVID-19 vaccination.

INTRODUCTION: Cases with organ-specific and systemic vasculitis associated with corona virus disease 2019 (COVID-19) vaccination have been reported. However, acute partial transverse myelitis (APTM) is rare adverse events following received COVID-19 vaccines. To the best of our knowledge, there is no report on vaccine-associated APTM accompanied by possible concurrent vasculitis. Herein we present a case with possible concurrent spinal vasculitis and APTM following the second dose of inactivated COVID-19 vaccine. CASE SUMMARY: A 33-year-old man presented with weakness of left lower limb and aberrant sensation of his left lower trunk and limb (from T9 level to toes) for 2 days following receipt of an inactivated COVID-19 vaccine. Remarkable demyelinating lesion at T7 spinal cord was showed by 3.0T magnetic resonance imaging (MRI) scan. Moreover, vertebral bodies of T3-T7 also presented high signal in T-2 weighted imaging (T2WI) accompanied by multiple sites of flowing void effect indicating possible vasculitis. Oligoclonal band was positive in cerebrospinal fluid (CSF) while it was negative in sera. Intravenous methylprednisolone (1 g/d) was administrated for 5 days followed by subsequent dose-tapering prednisone. His limb weakness and aberrant sensation both improved and he was able to walk unaided after treatment. The MRI recheck also showed remarkable improvement on the lesions in spinal cord and vertebral bodies. CONCLUSION: this case illustrates the concurrence of possible vasculitis in vertebral bodies and acute transverse myelitis (ATM) following COVID-19 vaccination.

Synthetic Biology-Powered Biosensors Based on CRISPR/Cas Mediated Cascade Signal Amplification for Precise RNA Detection

Synthetic biology enabling technologies have been harnessed to create new diagnostic technologies. However, most strategies involve error-prone amplification steps and limitations of accuracy in RNA detection. Here, a cell-free synthetic biology-powered biosensing strategy, termed as SHARK (Synthetic Enzyme Shift RNA Signal Amplifier Related Cas13a Knockdown Reaction), could efficiently and accurately amplify RNA signal by leveraging the collateral cleavage of activated Cas13a to regulate cell-free enzyme synthesis. Based on cascade amplification and tailored enzyme output, SHARK behaves broad compatibility in different scenarios. The portable device based on SHARK was successfully used as SARS-CoV-2 biosensors with high sensitivity and selectivity, and the results were highly consistent with Ct values of qRT-PCR. In addition, when combined with machine learning, SHARK performs bio-computations and thus for cancer diagnosis and staging based on 64 clinical samples. SHARK shows characteristics of precise recognition, cascade amplification and tailored signal outputting comparisons with established assays, presenting significant potential in developing next-generation RNA detection technology.

Positive Sentiment and the Donation Amount: Social Norms in Crowdfunding Donations During the COVID-19 Pandemic

Public welfare fundraising has been used to collect donations for medical supplies and has played an important role in the fight against the COVID-19 pandemic. This paper studies online crowdfunding donations from the Alumni Association of Wuhan University to North American alumni;donation data are used to investigate how individuals' donation behavior is affected by the previous donation amount and information provided by the fundraising platform. First, our results show that one's donation amount is positively affected by the previous donation amount. Second, the donor's positive sentiment in the message that he or she leaves, as measured by either natural language processing or a manual rating, can affect the subsequent anonymity and messages but not the subsequent donation amount. Third, anonymous donations are much smaller than non-anonymous donations.

Serial-Multiple Mediation of Job Burnout and Fatigue in the Relationship Between Sickness Presenteeism and Productivity Loss in Nurses: A Multicenter Cross-Sectional Study.

Background: In China, sickness presenteeism, job burnout, and fatigue are common among nurses during the COVID-19 pandemic. We propose the prevalence of sickness presenteeism can adversely affect nurses' physical and mental health, negatively impact their work productivity and quality, and pose a threat to patients' safety. Therefore, this study examines the mechanism of productivity loss caused by sickness presenteeism, fatigue, and job burnout. Objectives: To investigate the serial-multiple mediating effect of job burnout and fatigue in the relationship between sickness presenteeism and productivity loss among nurses. Methods: A multicenter cross-sectional survey was undertaken by administering an online questionnaire from December 2020 to May 2021. Stratified cluster sampling was used to include 3,491 nurses from 14 hospitals in Shandong Province, China. Variables were measured using the Sickness Presenteeism Questionnaire, Stanford Presenteeism Scale, Chalder Fatigue Scale, and Maslach Burnout Inventory. Data analyses were carried out using descriptive statistics, one-way analysis of variance, independent-samples t-test, Pearson correlation analysis, hierarchical regression, and bootstrapping method. Results: From the 3,491 nurses who volunteered in this online survey, only 2,968 valid questionnaires were returned. Sickness presenteeism exhibited a prevalence of 70.6% during the COVID-19 pandemic. The average score of health-related productivity loss was 15.05 ± 4.52, fatigue was 8.48 ± 3.40, and job burnout was 39.14 ± 19.64. Sickness presenteeism was positively associated with fatigue and job burnout while job burnout was positively associated with nurse fatigue. Sickness presenteeism, fatigue, and job burnout were also positively correlated with health-related productivity loss. Statistically significant paths via the single mediation of fatigue and job burnout were established. A statistically significant serial-multiple mediating effect of fatigue and job burnout on the association between sickness presenteeism and productivity loss accounted for 35.12% of the total effect size. Conclusions: There was a high incidence of sickness presenteeism and job burnout among Chinese nurses. High-frequency sickness presenteeism may result in increased productivity loss through the two mediating effects of fatigue and job burnout. Sickness presenteeism may increase fatigue, promote job burnout, and result in increased productivity loss among Chinese nurses during the COVID-19 pandemic.

Predictors of Shift Work Sleep Disorder Among Nurses During the COVID-19 Pandemic: A Multicenter Cross-Sectional Study.

Background: Nurses have a high incidence of shift work sleep disorder, which places their health and patient safety in danger. Thus, exploring the factors associated with shift work sleep disorder in nurses is of great significance in improving their sleep health, nursing personnel staffing, and scheduling during the COVID-19 pandemic. Objectives: The purpose of this study was to investigate the incidence of shift work sleep disorder during the COVID-19 pandemic and explore the factors associated with shift work sleep disorder in Chinese nurses. Methods: This was a multicenter cross-sectional study using an online survey. Stratified cluster sampling was used to include 4,275 nurses from 14 hospitals in Shandong, China from December 2020 to June 2021. Stepwise multivariate logistic regression analysis and random forest were used to identify the factors associated with shift work sleep disorder. Results: The prevalence of shift work sleep disorder in the sampled shift nurses was 48.5% during the COVID-19 pandemic. Physical fatigue, psychological stress, shift work more than 6 months per year, busyness during night shift, working more than 40 h per week, working more than four night shifts per month, sleeping more than 8 h before night shift, using sleep medication, irregular meals, and high-intensity physical activity were associated with increased odds of shift work sleep disorder. Good social support, good work-family balance, napping two or three times per week, resting more than one day after shifts, intervals of 8 days or more between shifts, and taking turns to rest during the night shift were associated with decreased odds of shift work sleep disorder. Conclusions: Shift work sleep disorder may be associated with scheduling strategies and personal behavior during the COVID-19 pandemic. To reduce the incidence of shift work sleep disorders in nurses, nursing managers should increase night shift staffing, extend rest days after shift, increase night shift spacing, and reduce overtime, and nurses need to seek more family and social support and control their sleep schedules and diet.

China's Social Policy Response to Covid-19: Pragmatic Adjustment of Existing Welfare Institutions

In response to the Covid-19 pandemic, the Chinese government has utilized and pragmatically adjusted existing welfare institutions to ensure social and economic stability. This report describes the Chinese social policy responses in 2020 to mitigate the effects of the coronavirus crisis and focuses on specific countermeasures, such as cash benefits and benefits-in-kind for vulnerable people in the fields of health, social assistance, unemployment, and elderly care. Moreover, social insurance contributions for enterprises were reduced and deferred to help revive the economy. As shown in this report, many countermeasures were of a temporary nature, and can be defined as adaptations of the existing basic social security net, supplemented by administrative innovations such as the digitalization of means testing, for instance.

Evaluating the Disaster Risk of the COVID-19 Pandemic Using an Ecological Niche Model

Since 2019, the novel coronavirus has spread rapidly worldwide, greatly affecting social stability and human health. Pandemic prevention has become China’s primary task in responding to the transmission of COVID-19. Risk mapping and the proposal and implementation of epidemic prevention measures emphasize many research efforts. In this study, we collected location information for confirmed COVID-19 cases in Beijing, Shenyang, Dalian, and Shijiazhuang from 5 October 2020 to 5 January 2021, and selected 15 environmental variables to construct a model that comprehensively considered the parameters affecting the outbreak and spread of COVID-19 epidemics. Annual average temperature, catering, medical facilities, and other variables were processed using ArcGIS 10.3 and classified into three groups, including natural environmental variables, positive socio-environmental variables, and benign socio-environmental variables. We modeled the epidemic risk distribution for each area using the MaxEnt model based on the case occurrence data and environmental variables in four regions, and evaluated the key environmental variables influencing the epidemic distribution. The results showed that medium-risk zones were mainly distributed in Changping and Shunyi in Beijing, while Huanggu District in Shenyang and the southern part of Jinzhou District and the eastern part of Ganjingzi District in Dalian also represented areas at moderate risk of epidemics. For Shijiazhuang, Xinle, Gaocheng and other places were key COVID-19 epidemic spread areas. The jackknife assessment results revealed that positive socio-environmental variables are the most important factors affecting the outbreak and spread of COVID-19. The average contribution rate of the seafood market was 21.12%, and this contribution reached as high as 61.3% in Shenyang. The comprehensive analysis showed that improved seafood market management, strengthened crowd control and information recording, industry-catered specifications, and well-trained employees have become urgently needed prevention strategies in different regions. The comprehensive analysis indicated that the niche model could be used to classify the epidemic risk and propose prevention and control strategies when combined with the assessment results of the jackknife test, thus providing a theoretical basis and information support for suppressing the spread of COVID-19 epidemics.

The Patterns and Predictors of Loneliness for the Chinese Medical Students Since Post-Lockdown to New Normal With COVID-19.

Background: The coronavirus disease 2019 (COVID-19)-related quarantine has had unique psychological challenges for medical students, particularly loneliness. In this study, we demonstrated the patterns and predictors of loneliness in medical students since post-lockdown to new normal with COVID-19. Methods: A convenience sampling method was used in this study. Face-to-face online questionnaires of UCLA Loneliness Scale and psychological characteristics scales were completed by 1,478 participants. Latent profile analysis and multinominal logistic regressions were performed. Results: Three latent profile models were identified in this study: low loneliness (52.3%), interpersonal sensitivity loneliness (3.5%), and high loneliness (44.1%). Sophomore (Est = 1.937; p < 0.05) and junior students (Est = 2.939; p < 0.05), neuroticism (Est = 2.475; p < 0.05), high arousal symptoms (Est = 2.618; p < 0.01), and the quality of support from friends (Est = 2.264; p < 0.05) were the risk factors for high loneliness profile. In addition, sophomore (Est = 2.065; p < 0.05) and junior students (Est = 2.702; p < 0.01), openness (Est = 2.303; p < 0.05), and conscientiousness personality (Est = -2.348; p < 0.05) were the predictors of an interpersonal sensitive loneliness profile. Good peer relationship (Est = -2.266; p < 0.05) and other support (Est = -2.247; p < 0.05) were protective factors for low loneliness profile. Limitations: Participants were selected from one medical university; the generalizability is limited. Conclusions: Timely loneliness-focused interventions should be targeted on the different profiles and predictors of loneliness in medical students.

Yindan Jiedu Granules, a Traditional Chinese Medicinal Formulation, as a Potential Treatment for Coronavirus Disease 2019.

Background: Yindan Jiedu Granules (YDJDG) have been newly prescribed as a Chinese herbal formula. This study aimed to compare the efficacy of YDJDG and lopinavir-ritonavir in the treatment of coronavirus disease 2019 (COVID-19). Methods: Overall, 131 patients with COVID-19 were included in this study. In addition to standard care, 60 of these patients received YDJDG (YDJDG group) and 71 received lopinavir-ritonavir (lopinavir-ritonavir group). Propensity score matching (PSM) was used to match the characteristics of individuals in the two groups, while the Kaplan-Meier method was used to compare the proportion recovery observed. Results: Cox analysis revealed that YDJDG and CD4 ≥ 660 cells/µL were independent predictive factors of proportion recovery. At baseline, disease types differed between the YDJDG and lopinavir-ritonavir treatment groups. Furthermore, no significant adverse effects or toxicities relevant to YDJDG were observed. The median recovery time was 21 days in the YDJDG group and 27 days in the lopinavir-ritonavir group. After PSM (1:1), 50 patient pairs, YDJDG vs. lopinavir-ritonavir, were analyzed. In the YDJDG group, the proportion of recovered patients was remarkably higher than that observed in the lopinavir-ritonavir group (p = 0.0013), especially for those presenting mild/moderate disease type and CD4 < 660 cells/µL. In the YDJDG group, the mean duration of fever and pulmonary exudative lesions was significantly shorter than that observed in the lopinavir-ritonavir group (p = 0.0180 and p = 0.0028, respectively). Conclusion: YDJDG reveals the potential to hasten the recovery period in COVID-19 patients with mild/moderate disease type or CD4 < 660 cells/µL by shortening the mean duration of fever and pulmonary exudative lesions.

Multistage CT features of coronavirus disease 2019. / 2019å† çŠ¶ç— æ¯’ç— å¤šé˜¶æ®µCT影像学特征.

OBJECTIVES: To determine imaging features of coronavirus disease 2019 (COVID-19) in different stages, and to provide foundations for early diagnosis and treatment. METHODS: CT image data of 187 COVID-19 patients were analyzed in the period of hospitalization. CT scanning was performed on admission and repeated every 3 days. The improvement time of clinical symptoms and the image changes of follow-up CT were statistically analyzed. RESULTS: All 187 patients' nucleic acid test were positive to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The early CT images of lung in 187 cases (100%) showed multiple patchy and ground-glass opacities with fine mesh and consolidation shade, which mainly distributed in pulmonary band or under the pleura. In the progressive stage, the pulmonary lesions in 146 cases (78.1%) were mainly consolidation, accompanied by air bronchogram, thickening of blood vessels, and interstitial changes. Severe pulmonary CT images in 15 cases (8%) showed diffuse lesions in both lungs, displaying consolidation, or "white lung". The CT imaging features in 185 cases (98.9%) at the absorptive period showed that the lesions diminished and fibrogenesis. The imaging features of 6 times of lung CT examination in one case showed continuous progress. The original lesion in one case was obviously absorbed, but new lesions appeared under the pleura of both lungs at the third review of CT scanning. The changes of CT imaging lesions during follow-up were significantly different in different clinical symptoms improvement time (P< 0.01). CONCLUSIONS: Images of COVID-19 in various stages have special characteristics. The change of clinical symptoms is synchronous with the change of reexamination CT. Follow-up CT can reflect the trend of clinical changes. Repeat CT examination plays an important role in the early clinical diagnosis and the evaluation for the therapeutic effect on COVID-19 patient.