Effectiveness of an "online + in-person" hybrid model for an undergraduate molecular biology lab during COVID-19.

The COVID-19 outbreak has created turbulence and uncertainty into multiple aspects of life in countries around the world. In China, the pandemic continues to pose a great challenge to the nature of traditional in-class education in schools. Chinese education has faced the difficult decision of whether to resume in-person teaching in an unprecedented and time-pressured manner. To ensure the quality of teaching and learning during this time, this study aims to explore the effectiveness of an "online + in-person" hybrid teaching model with a new three-part approach to the hybrid teaching lab, where students prepare for the in-person lab using virtual simulated experiments and learning modules and debrief their learning afterwards online as well. This approach not only enhances the efficiency during the in-person lab but also strongly reinforces concepts and laboratory skills by providing a "practice run" before physically attending the lab. A total of 400 medical undergraduates from Dalian Medical University in China were recruited for this study. In an undergraduate molecular biology laboratory course, we observed 200 students in a hybrid teaching model. We evaluated the learning outcomes from the "online + in-person" hybrid teaching model with a questionnaire survey and assessed the quality of experiment execution, report writing, and group collaboration. Moreover, the 200 students from the hybrid group were evaluated during an annual science competition at the university and compared to 200 students from the competition cohort who had no experience with a hybrid learning model. The comparison data were analyzed using a student's t-test statistical analysis. The students in the hybrid learning group demonstrated a strong enthusiasm for the model, high amount of time utilizing the online system, and high scores on laboratory evaluation assignments. Approximately 98% of the hybrid learning students reported that they preferred mixed teaching to the traditional teaching mode, and all students scored above 96% on the online laboratory report. Teachers of the course observed that the hybrid group had a noticeably higher level of proficiency in lab skills compared to the previous students. At the Dalian Medical University annual science competition, where we compared our hybrid group to a traditional learning group, scores for both the objective and subjective items showed that the students instructed with the hybrid lab model had superior performance (p < 0.05). In the context of the COVID-19 pandemic, we developed a new three-part molecular biology laboratory course that strongly improved students' laboratory skills, knowledge retention, and enthusiasm for the course using online learning to improve their learning efficiency and expedite the in-person laboratory experience. We found that these students performed at a higher level in a combined theoretical/practical science competition compared to the students in traditional in-person lab courses. Additionally, our model subjectively fostered enthusiasm and excellence in both teachers and students. Further, cultivation of the students' independent learning and creative problem solving skills were emphasized. The exploration of an effective teaching model, such as the one described here, not only provides students with a solid foundation for their future medical studies and career development but also promotes more efficient in-person laboratory time.

Mapping the long-term associations between air pollutants and COVID-19 risks and the attributable burdens in the continental United States.

Numerous studies have investigated the associations between COVID-19 risks and long-term exposure to air pollutants, revealing considerable heterogeneity and even contradictory regional results. Studying the spatial heterogeneity of the associations is essential for developing region-specific and cost-effective air-pollutant-related public health policies for the prevention and control of COVID-19. However, few studies have investigated this issue. Using the USA as an example, we constructed single/two-pollutant conditional autoregressions with random coefficients and random intercepts to map the associations between five air pollutants (PM2.5, O3, SO2, NO2, and CO) and two COVID-19 outcomes (incidence and mortality) at the state level. The attributed cases and deaths were then mapped at the county level. This study included 3108 counties from 49 states within the continental USA. The county-level air pollutant concentrations from 2017 to 2019 were used as long-term exposures, and the county-level cumulative COVID-19 cases and deaths through May 13, 2022, were used as outcomes. Results showed that considerably heterogeneous associations and attributable COVID-19 burdens were found in the USA. The COVID-19 outcomes in the western and northeastern states appeared to be unaffected by any of the five pollutants. The east of the USA bore the greatest COVID-19 burdens attributable to air pollution because of its high pollutant concentrations and significantly positive associations. PM2.5 and CO were significantly positively associated with COVID-19 incidence in 49 states on average, whereas NO2 and SO2 were significantly positively associated with COVID-19 mortality. The remaining associations between air pollutants and COVID-19 outcomes were not statistically significant. Our study provided implications regarding where a major concern should be placed on a specific air pollutant for COVID-19 control and prevention, as well as where and how to conduct additional individual-based validation research in a cost-effective manner.

Supply forecasting and profiling of urban supermarket chains based on tensor quantization exponential regression for social governance.

Background: During the COVID-19 pandemic, the accurate forecasting and profiling of the supply of fresh commodities in urban supermarket chains may help the city government make better economic decisions, support activities of daily living, and optimize transportation to support social governance. In urban supermarket chains, the large variety of fresh commodities and the short shelf life of fresh commodities lead to the poor performance of the traditional fresh commodity supply forecasting algorithm. Methods: Unlike the classic method of forecasting a single type of fresh commodity, we proposed a third-order exponential regression algorithm incorporating the block Hankle tensor. First, a multi-way delay embedding transform was used to fuse multiple fresh commodities sales to a Hankle tensor, for aggregating the correlation and mutual information of the whole category of fresh commodities. Second, high-order orthogonal iterations were performed for tensor decomposition, which effectively extracted the high-dimensional features of multiple related fresh commodities sales time series. Finally, a tensor quantization third-order exponential regression algorithm was employed to simultaneously predict the sales of multiple correlated fresh produce items. Results: The experiment result showed that the provided tensor quantization exponential regression method reduced the normalized root mean square error by 24% and the symmetric mean absolute percentage error by 22%, compared with the state-of-the-art approaches.

Relationship between Income and Mental Health during the COVID-19 Pandemic in China.

Mental health problems represent one most pressing concerns in the world, which produce costly consequences for individuals, families and society as a whole. One of the determinants on mental health during the COVID-19 pandemic is income. To complement relevant research and provide valuable recommendations for governments and societies, this study investigates the nexus between income and mental health in China by employing 8049 observations from the 2020 China Family Panel Studies. Using ordinary least squares regression we find the significant positive relationship between income and mental health, and estimate the effect of income on mental health. Furthermore, this effect is heterogeneous depending on individuals' education level and registered residence type. Finally, individuals' economic status and happiness are shown to be the potential mechanism through which the effect of income on mental health operates.

Differential Peripheral Blood Glycoprotein Profiles in Symptomatic and Asymptomatic COVID-19.

Glycosylation is the most common form of post-translational modification of proteins, critically affecting their structure and function. Using liquid chromatography and mass spectrometry for high-resolution site-specific quantification of glycopeptides coupled with high-throughput artificial intelligence-powered data processing, we analyzed differential protein glycoisoform distributions of 597 abundant serum glycopeptides and nonglycosylated peptides in 50 individuals who had been seriously ill with COVID-19 and in 22 individuals who had recovered after an asymptomatic course of COVID-19. As additional comparison reference phenotypes, we included 12 individuals with a history of infection with a common cold coronavirus, 16 patients with bacterial sepsis, and 15 healthy subjects without history of coronavirus exposure. We found statistically significant differences, at FDR < 0.05, for normalized abundances of 374 of the 597 peptides and glycopeptides interrogated between symptomatic and asymptomatic COVID-19 patients. Similar statistically significant differences were seen when comparing symptomatic COVID-19 patients to healthy controls (350 differentially abundant peptides and glycopeptides) and common cold coronavirus seropositive subjects (353 differentially abundant peptides and glycopeptides). Among healthy controls and sepsis patients, 326 peptides and glycopeptides were found to be differentially abundant, of which 277 overlapped with biomarkers that showed differential expression between symptomatic COVID-19 cases and healthy controls. Among symptomatic COVID-19 cases and sepsis patients, 101 glycopeptide and peptide biomarkers were found to be statistically significantly abundant. Using both supervised and unsupervised machine learning techniques, we found specific glycoprotein profiles to be strongly predictive of symptomatic COVID-19 infection. LASSO-regularized multivariable logistic regression and K-means clustering yielded accuracies of 100% in an independent test set and of 96% overall, respectively. Our findings are consistent with the interpretation that a majority of glycoprotein modifications observed which are shared among symptomatic COVID-19 and sepsis patients likely represent a generic consequence of a severe systemic immune and inflammatory state. However, there are glycoisoform changes that are specific and particular to severe COVID-19 infection. These may be representative of either COVID-19-specific consequences or susceptibility to or predisposition for a severe course of the disease. Our findings support the potential value of glycoproteomic biomarkers in the biomedical understanding and, potentially, the clinical management of serious acute infectious conditions.

Effect of Salt Substitution on Cardiovascular Events and Death.

BACKGROUND: Salt substitutes with reduced sodium levels and increased potassium levels have been shown to lower blood pressure, but their effects on cardiovascular and safety outcomes are uncertain. METHODS: We conducted an open-label, cluster-randomized trial involving persons from 600 villages in rural China. The participants had a history of stroke or were 60 years of age or older and had high blood pressure. The villages were randomly assigned in a 1:1 ratio to the intervention group, in which the participants used a salt substitute (75% sodium chloride and 25% potassium chloride by mass), or to the control group, in which the participants continued to use regular salt (100% sodium chloride). The primary outcome was stroke, the secondary outcomes were major adverse cardiovascular events and death from any cause, and the safety outcome was clinical hyperkalemia. RESULTS: A total of 20,995 persons were enrolled in the trial. The mean age of the participants was 65.4 years, and 49.5% were female, 72.6% had a history of stroke, and 88.4% a history of hypertension. The mean duration of follow-up was 4.74 years. The rate of stroke was lower with the salt substitute than with regular salt (29.14 events vs. 33.65 events per 1000 person-years; rate ratio, 0.86; 95% confidence interval [CI], 0.77 to 0.96; P = 0.006), as were the rates of major cardiovascular events (49.09 events vs. 56.29 events per 1000 person-years; rate ratio, 0.87; 95% CI, 0.80 to 0.94; P<0.001) and death (39.28 events vs. 44.61 events per 1000 person-years; rate ratio, 0.88; 95% CI, 0.82 to 0.95; P<0.001). The rate of serious adverse events attributed to hyperkalemia was not significantly higher with the salt substitute than with regular salt (3.35 events vs. 3.30 events per 1000 person-years; rate ratio, 1.04; 95% CI, 0.80 to 1.37; P = 0.76). CONCLUSIONS: Among persons who had a history of stroke or were 60 years of age or older and had high blood pressure, the rates of stroke, major cardiovascular events, and death from any cause were lower with the salt substitute than with regular salt. (Funded by the National Health and Medical Research Council of Australia; SSaSS ClinicalTrials.gov number, NCT02092090.).

Does learning longer improve student achievement? Evidence from online education of graduating students in a high school during COVID-19 period

This paper examines the effect of online learning time on graduating students' test scores in a senior high school. Decisions regarding online education, including those related to participation and learning hours, are endogenous due to both reverse causality and omitted variables. This paper is the result of the natural experiment of the outbreak of COVID-19, which made every student to participate in online education when the spring semester began. In addition, this paper uses a value-added model controlling for the scores that preceded online education, which is a sufficient statistic of students' unobserved ability and motivation. If this cannot completely eliminate the endogeneity problem, it should be able to largely alleviate the problem. The results indicate that: online education has positive but limited impacts on test scores on average, particularly those in the subject of math within the natural sciences track;top-tier students are most positively affected by online education;and the benefits of online education vary among students with different backgrounds. The quantile regression suggests that a 10% increase in online education time raises math test scores by more than 0.25 for the students between the 0.60th and 0.80th quantiles. Surprisingly, it is evident that online learning time has a significant negative effect for some students in certain subjects. Finally, online education neither widens nor narrows the inequality of students' test scores.

Duration of Viral Shedding of Discharged Patients With Severe COVID-19.

COVID-19 has drawn global intensive attention. We analyzed the duration of viral shedding and the total time from illness onset to discharge in groups. This has important implications for making decisions for isolation of discharged patients and to provide guidance for the duration of hospitalization of patients with severe COVID-19.

Risk profiles of severe illness in children with COVID-19: a meta-analysis of individual patients.

BACKGROUND: We prepared a meta-analysis on case reports in children with COVID-19, aiming to identify potential risk factors for severe illness and to develop a prediction model for risk assessment. METHODS: Literature retrieval, case report selection, and data extraction were independently completed by two authors. STATA software (version 14.1) and R programming environment (v4.0.2) were used for data handling. RESULTS: This meta-analysis was conducted based on 52 case reports, including 203 children (96 boys) with COVID-19. By severity, 26 (12.94%), 160 (79.60%), and 15 (7.46%) children were diagnosed as asymptomatic, mild/moderate, and severe cases, respectively. After adjusting for age and sex, 11 factors were found to be significantly associated with the risk of severe illness relative to asymptomatic or mild/moderate illness, especially for dyspnea/tachypnea (odds ratio, 95% confidence interval, P: 6.61, 4.12-9.09, <0.001) and abnormal chest X-ray (3.33, 1.84-4.82, <0.001). A nomogram modeling age, comorbidity, cough, dyspnea or tachypnea, CRP, and LDH was developed, and prediction performance was good as reflected by the C-index. CONCLUSIONS: Our findings provide systematic evidence for the contribution of comorbidity, cough, dyspnea or tachypnea, CRP, and LDH, both individually and jointly, to develop severe symptoms in children with asymptomatic or mild/moderate COVID-19. IMPACT: We have identified potential risk factors for severe illness in children with COVID-19. We have developed a prediction model to facilitate risk assessment in children with COVID-19. We found the contribution of five risk factors to develop severe symptoms in children with asymptomatic or mild/moderate COVID-19.

The effect of a short-term Balint group on the communication ability and self-efficacy of pre-examination and triage nurses during COVID-19.

AIMS AND OBJECTIVES: To investigate the effect of a short-term Balint group on the improvement in communication ability and self-efficacy of pre-examination and triage nurses during coronavirus disease 2019 (COVID-19). BACKGROUND: Working on the front lines of COVID-19 has brought unprecedented psychological stress on pre-examination and triage nurses. Nurse-patient communication ability and the level of self-efficacy are both significant for nurses' psychosomatic health and work input. However, limited empirical evidence exists regarding nurse-patient communication and self-efficacy and specific psychological intervention effects. DESIGN: Cross-sectional research fulfilling the completed checklist of items that should be included in reports of cross-sectional studies (Appendix S1). METHODS: Nurses (n = 41) in the first layer of pre-examination and triage were engaged in a Balint group activity twice a week for two weeks. They were assessed with the General Self-Efficacy Scale (GSES) pre- and postintervention, and a nurse-patient communication survey form was developed for further postintervention evaluation. The sample was recruited from a class A third-grade hospital in Sichuan, China. RESULTS: Most of the subjects reported improvement in nurse-patient communication, increased cooperation between patients and their families, and a decreased missed examination rate after the intervention. Moreover, the total mean score of the GSES of nurses after the intervention was increased, but the difference was not statistically significant. The scores of all items in the GSES were improved, and the scores increase for item 4 (I am confident that I can effectively deal with any unexpected event) was statistically significant. CONCLUSIONS: During the COVID-19 pandemic, a short-term Balint group activity can improve the communication ability and self-efficacy level of front-line nurses to some extent. RELEVANCE TO CLINICAL PRACTICE: This information may provide some theoretical support for the development of early psychological interventions during major epidemic situations.

Prevalence and prognostic value of elevated troponins in patients hospitalised for coronavirus disease 2019: a systematic review and meta-analysis.

BACKGROUND: The clinical significance of cardiac troponin measurement in patients hospitalised for coronavirus disease 2019 (covid-19) is uncertain. We investigated the prevalence of elevated troponins in these patients and its prognostic value for predicting mortality. METHODS: Studies were identified by searching electronic databases and preprint servers. We included studies of hospitalised covid-19 patients that reported the frequency of troponin elevations above the upper reference limit and/or the association between troponins and mortality. Meta-analyses were performed using random-effects models. RESULTS: Fifty-one studies were included. Elevated troponins were found in 20.8% (95% confidence interval [CI] 16.8-25.0 %) of patients who received troponin test on hospital admission. Elevated troponins on admission were associated with a higher risk of subsequent death (risk ratio 2.68, 95% CI 2.08-3.46) after adjusting for confounders in multivariable analysis. The pooled sensitivity of elevated admission troponins for predicting death was 0.60 (95% CI 0.54-0.65), and the specificity was 0.83 (0.77-0.88). The post-test probability of death was about 42% for patients with elevated admission troponins and was about 9% for those with non-elevated troponins on admission. There was significant heterogeneity in the analyses, and many included studies were at risk of bias due to the lack of systematic troponin measurement and inadequate follow-up. CONCLUSION: Elevated troponins were relatively common in patients hospitalised for covid-19. Troponin measurement on admission might help in risk stratification, especially in identifying patients at high risk of death when troponin levels are elevated. High-quality prospective studies are needed to validate these findings. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42020176747.

Social Distance Monitor with a Wearable Magnetic Field Proximity Sensor.

Social distancing and contact/exposure tracing are accepted to be critical strategies in the fight against the COVID-19 epidemic. They are both closely connected to the ability to reliably establish the degree of proximity between people in real-world environments. We proposed, implemented, and evaluated a wearable proximity sensing system based on an oscillating magnetic field that overcomes many of the weaknesses of the current state of the art Bluetooth based proximity detection. In this paper, we first described the underlying physical principle, proposed a protocol for the identification and coordination of the transmitter (which is compatible with the current smartphone-based exposure tracing protocols). Subsequently, the system architecture and implementation were described, finally an elaborate characterization and evaluation of the performance (both in systematic lab experiments and in real-world settings) were performed. Our work demonstrated that the proposed system is much more reliable than the widely-used Bluetooth-based approach, particularly when it comes to distinguishing between distances above and below the 2.0 m threshold due to the magnetic field's physical properties.

A Case of Coronavirus Disease 2019 With Concomitant Acute Cerebral Infarction and Deep Vein Thrombosis.

We report a case of a 75-year-old woman diagnosed with severe coronavirus disease 2019 (COVID-19) complicated by acute cerebral infarction. The patient was admitted to our hospital on 5 February 2020 with severe COVID-19. On 20 February 2020, she was diagnosed with concomitant acute cerebral infarction via head computed tomography (CT) and deep vein thrombosis in both lower limbs. After symptomatic and supportive treatments, the patient was discharged on 13 March 2020. She will comply with quarantine for another 2 weeks and receive rehabilitation training from a specialist doctor. Cerebral infarction should be considered and promptly managed in patients with COVID-19.

Venous thrombosis and arteriosclerosis obliterans of lower extremities in a very severe patient with 2019 novel coronavirus disease: a case report.

The outbreak of 2019 novel coronavirus disease (COVID-19) began since early December 2019, and has been declared as a public health emergency by the World Health Organization. Due to the hypercoagulable state, blood stasis and endothelial injury, severe patients with COVID-19 are at high risk for thrombosis. We report a case of very severe COVID-19 complicated with venous thrombosis and arteriosclerosis obliterans of lower extremities. Risk stratification for deep vein thrombosis and peripheral arterial disease are of vital importance for the prognosis of COVID-19.