Hematological Features and Risk Factors of Hospitalized COVID-19 Patients: A Retrospective Analysis (preprint)

Background: Coronavirus disease 2019 (COVID-19) has become pandemic in 2020 and recently mutated coronavirus has emerged in many countries. This study firstly identified the clinical characteristics and risk factors for COVID-19 patients in Zhengzhou for clinical prevention and management. Methods: A total of 70 patients hospitalized with COVID-19 were enrolled between 21th January and 29th February 2020, in Zhengzhou, China. Clinical characteristics, hematological findings, neutrophil lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR) and inflammatory index on admission were selected from medical records and the comparison between COVID-19 patients with different outcomes were evaluated. Results : The median age was 55 years. Forty-three (43%) patients were classified as severe or critical cases. Eighteen (12.8%) patients died in hospital and the remaining fifty-two were discharged. Patients who died tend to old aged, expectoration, with chronic obstructive pulmonary disease. Compared to survivor, non-survivor has significantly higher leucocytes, neutrophils, NLR, AST, GGT, TBIL, DBIL, LDH, PT, D-dimer, CRP, and decreased platelet, lymphocyte, UA, ALB, CHE, PTA. Multiple logistic regression analysis identified leucocytes, platelet, PLR, NLR, AST, and ALB as independent factors for poor outcomes. The AUC of combination of leucocyte, PLR, NLR, and AST have the largest area under curve at 0.87, with the sensitivity of 0.83 and specificity of 0.81. Conclusion : Our results identified the risk factors among COVID-19 patients in-hospital fatality. Leucocyte, PLR, NLR, and AST could have important reference value for prognostic prediction and early intervention.

Investigation on the Occupational Situation of Clinical Research Associates in China (preprint)

Objective To understand the occupational situation of clinical research associates (CRAs) in terms of workloads, difficulties in monitoring and occupational satisfaction. To provide reference for further improving the occupational status of CRA, enhance the quality of clinical trials, and monitoring efficiency.Methods This study is a national cross-sectional survey, and over a 2-month period. The research data are collected through self-made questionnaires, consisting of such five sections on CRAs as basic information, work situation, satisfaction with other participants in clinical trials, career satisfaction, suggestions. The questionnaire was put into a QR code for invited CRAs to scan and participate anonymously. All the data were directly exported for statistical analysis after collected.Results The survey ultimately included 401 valid questionnaires, of which 71.32% were female, the average age is 27.86 years old, 95.01% had a bachelor's degree or above, and 60% had a pharmaceutical major. 80% of CRA work hours exceed the standard working hours requirement. The frequency of CRA business trips has decreased under the impact of the Covid-19 epidemic, with 79.3% of CRAs traveling for less than 7 days per month. Only 49.63% of people were satisfied with the current salary level, but about 80% of people are satisfied with promotion channels and company training. It was suggested by more than 80% of CRAs that the application materials for clinical trials should be unified nationwide and an ethical mutual recognition system, which allows the approved ethical results of one ethics committee to be recognized across all research sites involved, be implemented.Conclusions Currently, CRAs has a relatively large workload and generally works overtime. The monitoring difficulties faced by CRAs from three aspects: hospitals, companies, and themselves. With the number of CRAs on the rise, it is necessary to generate more professional associates with higher quality and increase corresponding training channels. Meanwhile, efforts remain to be made by hospitals to reinforce their management and provide better training for investigators so as to improve the efficiency of monitoring. It is incumbent on the enterprises to provide matching salaries and benefits with a view to improving the retention of employees.

Hyperglycemia-induced cathepsin L maturation: Implications for diabetic comorbidities and COVID-19 susceptibility (preprint)

Diabetes is the second most frequent chronic comorbidity for COVID-19 mortality, yet the underlying mechanism remains unclear. Previous studies suggest that Cathepsin L (CTSL) is implicated in diabetic complications such as nephropathy and retinopathy. Our previous research identified CTSL as a critical protease that promotes SARS-CoV-2 infection and a potential drug target. Here, we show that individuals with diabetes have elevated blood CTSL levels, which facilitates SARS-CoV-2 infection. Chronic hyperglycemia, as indicated by HbA1c levels, is positively correlated with CTSL concentration and activity in diabetic patients. Acute hyperglycemia induced by a hyperglycemic clamp in healthy individuals increases CTSL activity. In vitro, high glucose, but not high insulin, promotes SARS-CoV-2 infection in wild-type (WT) cells, while CTSL knockout (KO) cells show reduced susceptibility to high glucose-promoted effects. Using lung tissue samples from diabetic and non-diabetic patients, as well as db/db diabetic and control mice, our findings demonstrate that diabetic conditions increase CTSL activity in both humans and mice. Mechanistically, high glucose levels promote CTSL maturation and CTSL translocation from the endoplasmic reticulum (ER) to the lysosome via the ER-Golgi-lysosome axis. This study emphasizes the significance of hyperglycemia-induced cathepsin L maturation in the development of diabetic comorbidities and complications.

CRISPR-Cas12a Coupled with DNA Nanosheet-Amplified Fluorescence Anisotropy for Sensitive Detection of Biomolecules.

DNA nanosheets (DNSs) have been utilized effectively as a fluorescence anisotropy (FA) amplifier for biosensing. But, their sensitivity needs to be further improved. Herein, CRISPR-Cas12a with strong trans-cleavage activity was utilized to enhance the FA amplification ability of DNSs for the sensitive detection of miRNA-155 (miR-155) as a proof-of-principle target. In this method, the hybrid of the recognition probe of miR-155 (T1) and a blocker sequence (T2) was immobilized on the surface of magnetic beads (MBs). In the presence of miR-155, T2 was released by a strand displacement reaction, which activated the trans-cleavage activity of CRISPR-Cas12a. The single-stranded DNA (ssDNA) probe modified with a carboxytetramethylrhodamine (TAMRA) fluorophore was cleaved in large quantities and could not bind to the handle chain on DNSs, inducing a low FA value. In contrast, in the absence of miR-155, T2 could not be released and the trans-cleavage activity of CRISPR-Cas12a could not be activated. The TAMRA-modified ssDNA probe remained intact and was complementary to the handle chain on the DNSs, and a high FA value was obtained. Thus, miR-155 was detected through the obviously decreased FA value with a low limit of detection (LOD) of 40 pM. Impressively, the sensitivity of this method was greatly improved about 322 times by CRISPR-Cas12a, confirming the amazing signal amplification ability of CRISPR-Cas12a. At the same time, the SARS-CoV-2 nucleocapsid protein was detected by the strategy successfully, indicating that this method was general. Moreover, this method has been applied in the analysis of miR-155 in human serum and the lysates of cells, which provides a new avenue for the sensitive determination of biomarkers in biochemical research and disease diagnosis.

Systemic Lupus Erythematosus Risk: The Role of Environmental Factors.

Systemic lupus erythematosus (SLE) is a complex, chronic autoimmune disease. The etiology of SLE is multifactorial and includes potential environmental triggers, which may occur sequentially (the "multi-hit" hypothesis). This review focuses on SLE risk potentially associated with environmental factors including infections, the microbiome, diet, respirable exposures (eg, crystalline silica, smoking, air pollution), organic pollutants, heavy metals, and ultraviolet radiation.

COVID-19 epidemic and public health interventions in Shanghai, China: Statistical analysis of transmission, correlation and conversion

Background The Shanghai COVID-19 epidemic is an important example of a local outbreak and of the implementation of normalized prevention and disease control strategies. The precise impact of public health interventions on epidemic prevention and control is unknown. Methods We collected information on COVID-19 patients reported in Shanghai, China, from January 30 to May 31, 2022. These newly added cases were classified as local confirmed cases, local asymptomatic infections, imported confirmed cases and imported asymptomatic infections. We used polynomial fitting correlation analysis and illustrated the time lag plot in the correlation analysis of local and imported cases. Analyzing the conversion of asymptomatic infections to confirmed cases, we proposed a new measure of the conversion rate (Cr). In the evolution of epidemic transmission and the analysis of intervention effects, we calculated the effective reproduction number (Rt). Additionally, we used simulated predictions of public health interventions in transmission, correlation, and conversion analyses. Results (1) The overall level of Rt in the first three stages was higher than the epidemic threshold. After the implementation of public health intervention measures in the third stage, Rt decreased rapidly, and the overall Rt level in the last three stages was lower than the epidemic threshold. The longer the public health interventions were delayed, the more cases that were expected and the later the epidemic was expected to end. (2) In the correlation analysis, the outbreak in Shanghai was characterized by double peaks. (3) In the conversion analysis, when the incubation period was short (3 or 7 days), the conversion rate fluctuated smoothly and did not reflect the effect of the intervention. When the incubation period was extended (10 and 14 days), the conversion rate fluctuated in each period, being higher in the first five stages and lower in the sixth stage. Conclusion Effective public health interventions helped slow the spread of COVID-19 in Shanghai, shorten the outbreak duration, and protect the healthcare system from stress. Our research can serve as a positive guideline for addressing infectious disease prevention and control in China and other countries and regions.

Human Mobility Modeling During the COVID-19 Pandemic via Deep Graph Diffusion Infomax (preprint)

Non-Pharmaceutical Interventions (NPIs), such as social gathering restrictions, have shown effectiveness to slow the transmission of COVID-19 by reducing the contact of people. To support policy-makers, multiple studies have first modeled human mobility via macro indicators (e.g., average daily travel distance) and then studied the effectiveness of NPIs. In this work, we focus on mobility modeling and, from a micro perspective, aim to predict locations that will be visited by COVID-19 cases. Since NPIs generally cause economic and societal loss, such a micro perspective prediction benefits governments when they design and evaluate them. However, in real-world situations, strict privacy data protection regulations result in severe data sparsity problems (i.e., limited case and location information). To address these challenges, we formulate the micro perspective mobility modeling into computing the relevance score between a diffusion and a location, conditional on a geometric graph. we propose a model named Deep Graph Diffusion Infomax (DGDI), which jointly models variables including a geometric graph, a set of diffusions and a set of locations.To facilitate the research of COVID-19 prediction, we present two benchmarks that contain geometric graphs and location histories of COVID-19 cases. Extensive experiments on the two benchmarks show that DGDI significantly outperforms other competing methods.

Consumer-Related Antecedents of Waste Behavior in Online Food Ordering: A Study among Young Adults in China.

Food waste in the catering industry currently accounts for almost half of the total food waste in China and entails a large amount of land, water, and labor costs, in addition to the carbon footprint's impacts on climate change. Under the background of increasing food consumption and waste from online catering, this study investigates the factors influencing the food waste behaviors (FW) of online food ordering in China and provides policy recommendations for food waste reduction. Using survey data from 482 consumers, we constructed a theoretical framework and examined the influence path of each factor using structural equation modeling (SEM) and a bootstrap test. The results showed that young consumers without farming experience and females wasted more on ordering food online. The more frequently the consumer ordered, the more they wasted. The level of consumers' perceived behavioral control (PBC) was found to be lower than other factors, indicating that it was difficult for consumers to reduce food waste. Attitudes toward behavior (ATT), subjective norm (SN), PBC, and price consciousness (PC) were all positively related to behavioral intention to reduce food waste (BI). PBC and BI were negatively related to FW, and over-consumption behavior (OC) was positively related to FW. BI had a mediating effect on the paths of ATT, PBC, and PC to FW, but the pathway through which PC influenced FW was primarily through BI or PBC, not OC. In our research, BI had no mediating effect between SN and FW. Ultimately, our findings inform some policy recommendations to help nations, restaurants, food-ordering platforms, and consumers reduce waste.

Comparison of epidemiological characteristics and transmissibility of different strains of COVID-19 based on the incidence data of all local outbreaks in China as of March 1, 2022

Background The epidemiological characteristics and transmissibility of Coronavirus Disease 2019 (COVID-19) may undergo changes due to the mutation of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) strains. The purpose of this study is to compare the differences in the outbreaks of the different strains with regards to aspects such as epidemiological characteristics, transmissibility, and difficulties in prevention and control. Methods COVID-19 data from outbreaks of pre-Delta strains, the Delta variant and Omicron variant, were obtained from the Chinese Center for Disease Control and Prevention (CDC). Case data were collected from China's direct-reporting system, and the data concerning outbreaks were collected by on-site epidemiological investigators and collated by the authors of this paper. Indicators such as the effective reproduction number (Reff), time-dependent reproduction number (Rt), rate of decrease in transmissibility (RDT), and duration from the illness onset date to the diagnosed date (DID)/reported date (DIR) were used to compare differences in transmissibility between pre-Delta strains, Delta variants and Omicron variants. Non-parametric tests (namely the Kruskal-Wallis H and Mean-Whitney U tests) were used to compare differences in epidemiological characteristics and transmissibility between outbreaks of different strains. P < 0.05 indicated that the difference was statistically significant. Results Mainland China has maintained a “dynamic zero-out strategy” since the first case was reported, and clusters of outbreaks have occurred intermittently. The strains causing outbreaks in mainland China have gone through three stages: the outbreak of pre-Delta strains, the outbreak of the Delta variant, and outbreaks involving the superposition of Delta and Omicron variant strains. Each outbreak of pre-Delta strains went through two stages: a rising stage and a falling stage, Each outbreak of the Delta variant and Omicron variant went through three stages: a rising stage, a platform stage and a falling stage. The maximum Reff value of Omicron variant outbreaks was highest (median: 6.7;ranged from 5.3 to 8.0) and the differences were statistically significant. The RDT value of outbreaks involving pre-Delta strains was smallest (median: 91.4%;[IQR]: 87.30–94.27%), and the differences were statistically significant. The DID and DIR for all strains was mostly in a range of 0–2 days, with more than 75%. The range of duration for outbreaks of pre-Delta strains was the largest (median: 20 days, ranging from 1 to 61 days), and the differences were statistically significant. Conclusion With the evolution of the virus, the transmissibility of the variants has increased. The transmissibility of the Omicron variant is higher than that of both the pre-Delta strains and the Delta variant, and is more difficult to suppress. These findings provide us with get a more clear and precise picture of the transmissibility of the different variants in the real world, in accordance with the findings of previous studies. Reff is more suitable than Rt for assessing the transmissibility of the disease during an epidemic outbreak.

Serum miR-101, HSP-70 and IL-1 beta in gastric cancer patients with hp infection correlation between expression level and tmor proliferation and invasion

Objective: To investigate correlation between expression level and tumor proliferation and invasiveness of the serum miR-101, heat shock protein-70 (HSP-70) and interleukin-1beta (Interleukin-1beta, IL-1beta) in patients with gastric cancer complicated by Helicobacter pylori (Hp) infection.

IoT-Based Epidemic Monitoring via Improved Gated Recurrent Unit Model

During the Coronavirus Disease 2019 (COVID-19) pandemic, non-contact health monitoring and human activity detection by various sensors have attracted tremendous attention. Robot monitoring will result in minimizing the life threat to health providers during the COVID-19 pandemic period. How to improve the performance and generalization of the monitoring model is a critical but challenging task. This paper constructs an epidemic monitoring architecture based on multi-sensor information fusion and applies it in medical robots’ services, such as patient-care, disinfection, garbage disposal, etc. We propose a gated recurrent unit model based on a genetic algorithm (GA-GRU)to realize the effective feature selection and improve the effectiveness and accuracy of the localization, navigation, and activity monitoring for indoor wireless sensor networks (WSNs). By using two GRU layers in the GA-GRU, we improve the generalization capability in multiple WSNs. All these advantages of GA-GRU make it outperform other representative algorithms in a variety of evaluation metrics. The experiments on the WSNs verify that the proposed GA-GRU leads to successful runs and provides optimal performances. These results suggest the GA-GRU method may be preferable for epidemic monitoring in medicine and allied areas with particular relation to the control of the epidemic or pandemic such as COVID-19 pandemic.

Research on the Application of Blockchain Technology in Coal Supply Chain Finance

The implementation of measures to limit electricity consumption in many provinces of China has caused coal prices to rise irrationally, further aggravating the financing problems of small and medium-sized enterprises in the supply chain. Small and medium-sized enterprises lacking funds cannot effectively participate in the green transformation and development of the coal industry, which slows down the sustainable development process of the coal industry. Under the current background of low-carbon advocacy, blockchain technology can reasonably allocate resources and efficiently process information, thereby providing a solution for this financing problem. This paper first proposes a coal accounts receivable financing model based on blockchain technology, then builds a coal accounts receivable financing system dominated by ports through blockchain technology. Finally, the Stackelberg yield–benefit model is used to analyze the income function of each participant in the process of accounts receivable financing. The results show that the use of blockchain technology can reduce the financing condition of financial institutions and improve the maximum income of cooperative enterprises in the chain while solving the financing problems of small and medium-sized enterprises in the coal supply chain. This study provides practical significance and theoretical value for promoting the transformation and upgrading of coal enterprises and accelerating the opening of the sustainable development model of the coal industry.

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.

Prone position reduces the risk of patients with mild or moderate COVID-19 progressing to severe or even critical cases: a retrospective study.

BACKGROUND: To investigate whether prone position can reduce the risk of patients with mild or moderate COVID-19 who progress to severe or critical illness. METHODS: The prone position group was treated in prone position on the day of admission in addition to conventional treatment. Indicators such as saturation of pulse oximetry (SpO2), heart rate, blood pressure, respiratory rate, and prone position-related adverse events were recorded before prone ventilation, 5 min after prone position and 30 min after prone position. Meanwhile, the cases of severe and critical patients, the percentage of transformation and the final clinical outcome of this group were analyzed. Conversion rates and mortality were calculated for patients with mild or moderate COVID-19 retrieved from the database who received only conventional care without combined prone positioning as control group. RESULTS: (1) A total of 34 patients were included in prone position group. There were significant differences in SpO2 between the first 4 days after admission and the day of discharge (F = 3.17, P < 0.001). (2) The main complications were back and neck muscle soreness (55.9%), followed by abdominal distension (8.9%). (3) In control group, a total of 4873 cases of mild and moderate patients were included from 19 literatures, with an average deterioration rate of 22.7% and mortality rate of 1.7%. (4) In prone position group, there were no severe or critical transformation cases and also no death cases. The prone position group had a significantly lower deterioration rate when compared with the control group (χ2 = 9.962, P < 0.01). CONCLUSION: Prone position improves SpO2 in patients with mild or moderate COVID-19. It can also reduce the percentage of mild or moderate patients progressing to severe or critical patients. The application of prone position is a simple, feasible, safe and effective treatment method in such patients.

Whole-process management system of COVID-19 vaccination based on SpringBoot+Vue

After the large-scale vaccination of the coronavirus disease 2019(COVID-19), the traditional manual registration cannot track each vaccine from production to vaccination, as well as the vaccinators. It is easy to cause the lack and omission of registration information, and is not conducive to analyze the data of large-scale vaccine and vaccination. Therefore, this paper uses the front-end and back-end separated patterns with front-end using Vue and Elment-UI technology, and back-end using SpringBoot and Mybatis-Plus framework. It designs and realizes the whole-process management system of novel coronavirus vaccine, from vaccine logistics and vaccine warehousing management, to vaccination and post-vaccination tracking, and then to the forum management of vaccinators. The system aims to achieve "whole-process, traceable" management goal of vaccines. The system is feasible and practical, which can alleviate the problem of manual recording and collation of medical staff in vaccine management, and provide a convenient and information-based vaccination platform for medical staff and vaccinators. In addition, the system can collect the data on the whole process of vaccines and provide strong data support for scientific research work.

Work-family conflict and posttraumatic stress symptoms among college teachers during the COVID-19 pandemic.

The study aimed to examine the indirect factors underlying the association between work-family conflict and posttraumatic stress symptoms (PTSS) in college teachers during the COVID-19 pandemic. Three potential indirect factors were examined: perceived stress, basic psychological needs, and rumination. A total of 274 college teachers were recruited. All participants completed an electronic questionnaire that assessed their exposure to the pandemic, work-family conflict, perceived stress, basic psychological needs, rumination, and PTSS. The results showed that after controlling for pandemic exposure, gender, and age, work-family conflict was associated with PTSS via perceived stress alone, rumination alone, a path from perceived stress to basic psychological needs, and a path from perceived stress to rumination. These results indicate that work-family conflict is positively associated with PTSS indirectly via perceived stress, rumination, and basic psychological needs during the COVID-19 pandemic. These three mediators may completely explain the relation of work-family conflict to PTSS.