Association of interleukin-6 and CD4+ T cells and two-week prognosis of patients with COVID-19: a predictive role.

OBJECTIVE:  The aim of this study was to determine the association of inflammation and immune responses with the outcomes of patients at various stages, and to develop risk stratification for improving clinical practice and reducing mortality. PATIENTS AND METHODS: We included 77 patients with primary outcomes of either death or survival. Demographics, clinical features, comorbidities, and laboratory tests were compared. Linear, logistic, and Cox regression analyses were performed to determine prognostic factors. RESULTS: The average age was 59 years (35-87 years). There were 12 moderate cases (16.2%), 42 severe cases (54.5%), and 23 critical cases (29.9%); and 41 were male (53.2%). Until March 20, 68 cases were discharged (88.3%), and nine critically ill males (11.7%) died. Interleukin-6 (IL-6) levels on the 1st day were compared with IL-6 values on the 14th day in the severe and the critically ill surviving patients (F=4.90, p=0.034, ß=0.35, 95% CI: 0.00-0.10), and predicted death in the critically ill patients (p=0.028, ß=0.05, OR: 1.05, 95% CI: 1.01-1.10). CD4+ T-cell counts at admission decreased the hazard ratio of death (p=0.039, ß=-0.01, hazard ratio=0.99, 95% CI: 0.98-1.00, and median survival time 13.5 days). CONCLUSIONS: The present study demonstrated that IL-6 levels and CD4+ T-cell count at admission played key roles of predictors in the prognosis, especially for critically ill patients. High levels of IL-6 and impaired CD4+t cells are seen in severe and critically ill patients with COVID-19.

High-precision estimation of hourly PM2.5 concentration based on a grid scale of satellite-derived products

Continuous and accurate surface pollutant data can provide data support for health effect analysis. Based on the hourly AOD data of the Himawari-8 satellite as the basic data set, this study collected auxiliary parameters including meteorological reanalysis data and geospatial data to estimate the surface PM2.5 hourly concentration. The random forest (RF) and CatBoost models with superior performance were integrated by linear fitting. The experimental results showed that the sample-CV R2 and RMSE of the integrating model were 0.929 and 9.846 μg/m3;time-CV R2 = 0.903, RMSE = 11.521 μg/m3;station-CV R2 = 0.894, RMSE = 12.05 μg/m3, which had the best validation accuracy among all the comparison models and were also better than the estimation results of many previous studies. The spatial and temporal analysis results of PM2.5 showed that the surface PM2.5 concentration was generally high in winter and spring, and low in summer and autumn during the study period. During COVID-2019, PM2.5 concentration on the surface of China showed a significant decreasing trend. The model with the estimation method used in this study can produce reliable surface PM2.5 data products. © 2023 Turkish National Committee for Air Pollution Research and Control

[Clinical characteristics of children infected with SARS-CoV-2 Omicron variant combined with allergic disease].

Objective: To investigate the clinical characteristics of children with allergic diseases suffering from SARS-CoV-2 Omicron variant strains. Methods: This was a cross-sectional study. A total of 43 pediatric patients with allergic diseases infected by SARS-CoV-2 from April 25, 2022 to June 8, 2022 in Shanghai Jiao Tong University School of Medicine were selected as the allergic disease group, while 114 cases without underlying diseases and 16 cases with other underlying diseases were selected as control groups diagnosed at the same period. Clinical data including clinical features, laboratory tests, duration of hospitalization, and the time to negative turn of novel coronavirus nucleic acid were collected and analysed. Kruskal-Wallis H test, chi-square test or Fisher exact test were used for comparison among three groups. Results: Among the 43 patients with allergic diseases, 28 were males and 15 were females, with an age of 4.4 (2.1, 8.2) years on admission, including 32 mild cases and 11 common cases. The allergic disease group included 20 cases (46.5%) of atopic dermatitis and eczema, followed by 14 cases (32.6%) of rhinitis, 8 cases (18.6%) of food allergies, 7 cases (16.3%) of asthma, 4 cases (9.3%) of allergic conjunctivitis and 2 cases (4.7%) of drug allergy. Among the 114 cases without underlying diseases, 57 were males and 57 were females, with an age of 2.8 (1.2, 5.6) years on admission, including 93 mild cases and 21 common cases. Among the 16 cases with other underlying diseases, 9 were males and 7 were females, with an age of 3.0 (2.6, 10.8) years on admission, including 13 cases mild and 3 cases common cases. Children with allergic diseases had higher frequency of sore throat and vomiting than those without underlying diseases (10 cases (23.3%) vs.9 cases (7.9%), 14 cases (32.6%) vs. 11 cases (9.6%), χ²=6.93, 12.24, both P<0.05). The lymphocyte count of patients with allergic disease was lower than those without underlying disease (1.1 (0.7,1.7)×109 vs. 1.6 (1.1,2.7)×109/L, H=-28.00,P=0.005). There were no significant differences in age, gender, typing of SARS-CoV-2, the duration of hospitalization, cycle threshold values of SARS-CoV-2 and the time to negative turn of novel coronavirus nucleic acid among the three groups (all P>0.05). Conclusions: Children with allergic diseases may suffer from sore throat and vomiting more frequently when infected with SARS-CoV-2 Omicron variant. The combination of allergic diseases hardly influenced the disease course of SARS-CoV-2 in children.

Rapid Design and Construction Management of Emergency Hospital During the COVID-19 Epidemic

In order to control the spread of the COVID-19 epidemic across the country, China has used all available resources to build infectious disease hospitals in various ways. These hospitals include three modes and adapt to different disease levels: temporary emergency hospitals;makeshift hospitals by transforming public buildings;and existing general wards transformed into infectious wards. Through the practice of several projects, on the basis of the original standard system, China urgently issued a series of relevant standards and guidelines to guide the construction of temporary hospitals. As one of the earliest cases of temporary emergency infectious disease hospital, the Thunder God Mountain Hospital adopted a prefabricated modular design concept in plan design, plane design and component design, and also combined the application of Building Information Modeling (BIM) and Computational Fluid Dynamics (CFD) technology. Based on industrialized module processing and manufacturing, combined with an efficient on-site construction management system, the problem was solved of completing the construction in a very short time, which played a key role in controlling the epidemic situation. © IABSE Congress Nanjing 2022 - Bridges and Structures: Connection, Integration and Harmonisation, Report. All rights reserved.

The development and implementation of training mode for diabetes educators amid normalization stage of novel coronavirus pandemic prevention and control

Objective To develop an program for training diabetes educators amid normalization stage of novel coronavirus pandemic prevention and control, and provide reference for clinical teaching under special circumstances. Methods From January 2020 to June 2021, The head member of Diabetes Education and Management Committee of Hunan Health Management Association Xiangya Hospital of Central South University, developed and implemented a program based on core competencies of diabetes educators. It included 26 online courses, one to one education demonstration video with 7 themes, one diabetes conversation map and simulation, and three-week clinical practice. From April 2021 to June 2021, 55 health workers participated in the program. Theoretical tests, video feedback and questionnaires were used to evaluate the trainees′ diabetes knowledge, educational skills and satisfaction with the training program. Results A total of 55 health workers participated in the program. All the participants completed the online courses and passed the quizzes, the theoretical examination score was (92.93 ± 5.28). Fifty-four participants finished the tasks of clinical practice and obtained the certificate of diabetes educator. Their communication skills and strategies of behavior change were significantly improved (χ2 values were 4.17 - 26.34, all P＜0.05), and all of them were satisfied with the program. Conclusions The training mode based on online training is flexible, convenient and effective,which is suitable for stage of novel coronavirus pandemic prevention and control. © 2022 The authors.

[Characteristics and related factors of viral nucleic acid negative conversion in children infected with Omicron variant strain of SARS-CoV-2].

Objective: To understand the characteristics and associated factors of viral nucleic acid conversion in children infected with Omicron variant strain of SARS-CoV-2 in Shanghai. Methods: The clinical symptoms, laboratory results and other data of 177 children infected with SARS-CoV-2 who were hospitalized in Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University (designated hospital for SARS-CoV-2 infection in Shanghai) from April 25 to June 8, 2022 were retrospectively analyzed. According to the chest imaging findings, the children were divided into mild and common type groups. According to their age, the unvaccinated children were divided into<3 years old group and 3-<18 years old group. According to the vaccination status, the children aged 3-<18 year were divided into non-vaccination group, 1-dose vaccination group and 2-dose vaccination group. Comparison between groups was performed by independent sample t-test and analysis of variance, and multivariate linear regression analysis was used for multivariate analysis. Results: Among the 177 children infected with Omicron variant of SARS-CoV-2, 96 were males and 81 were females, aged 3 (1, 6) years. The time of viral nucleic acid negative conversion was (10.3±3.1) days. The 177 children were 138 cases of mild type and 39 cases of common type. Among the children aged 3-<18 years old, 55 cases were not vaccinated, 5 cases received 1-dose and 36 cases received 2-dose vaccination. Among the 36 children who received 2 doses of vaccination, the time of viral nucleic acid negative conversion was shorter in those vaccinated within 6 months than those over 6 months ((7.1±1.9) vs. (10.8±3.0) d, t=-3.23, P=0.004). Univariate analysis showed that the time of nucleic acid negative conversion of SARS-CoV-2 was associated with age, underlying diseases, gastrointestinal symptoms, white blood cell count, proportion of neutrophils, proportion of lymphocytes, and the number of doses of SARS-CoV-2 vaccine (t=3.87, 2.55, 2.04, 4.24, 3.51, 2.92, F=16.27, all P<0.05). Multiple linear regression analysis showed that older age (ß=-0.33, 95% CI -0.485--0.182, P<0.001) and more doses of vaccination (ß=-0.79, 95% CI -1.463--0.120, P=0.021) were associated with shortened nucleic acid negative conversion time in children, while lower lymphocyte proportion (ß=-0.02, 95% CI -0.044--0.002, P=0.031) and underlying diseases (ß=1.52, 95% CI 0.363-2.672, P=0.010) were associated with prolonged nucleic acid negative conversion time in children. Conclusion: The children infected with Omicron variant of SARS-CoV-2 with reduced lymphocyte proportion and underlying diseases may have longer time of viral nucleic acid negative conversion,while children with older age and more doses of vaccination may have shorter time of viral nucleic acid negative conversion.

[COVID-19 treated with oral Nirmatrelvir-Ritonavir in 3 children].

Objective: To summarize the application experience and the therapeutic effect of Nirmatrelvir-Ritonavir (trade name: Paxlovid) for COVID-19 in children. Methods: A retrospective analysis was performed on the clinical data, including collecting the clinical manifestations and clinical outcomes, dynamically monitoring the blood routine, hepatic and renal function and SARS-CoV-2 nucleic acid results, and observing the related side effects during the treatment, etc, of 3 cases with COVID-19 treated with Paxlovid admitted to Shanghai Children's Hospital (designated referral hospital for SARS-CoV-2 infection in Shanghai) from May 1st to June 1st, 2022. Results: The 3 cases were 12, 14, 17 years of age, among which 2 cases were males, 1 case was female. All 3 cases were mild cases with underlying diseases and risk of developing into severe COVID-19, with symptoms of high fever, sore throat and dry cough. The treatment of Paxlovid at 3rd day of symptom onset contributed to the symptom-free after 1-2 days and negative results of SARS-CoV-2 nucleic acid after 2-4 days. All patients had no adverse manifestations of gastrointestinal tract and nervous system but a case had little skin rashes, which recovered after the withdrawal of Paxlovid. Three cases had normal hepatic and renal function during the Paxlovid treatment. At 3 months after discharge, no clinical manifestations of post-COVID syndrome were found in all 3 cases. Conclusion: Paxlovid was effective and relatively safe in the treatment of 3 children with COVID-19.

Detection of SARS-CoV-2 and Other Viruses in Wastewater: Optimization and Automation of an Aluminum Hydroxide Adsorption-Precipitation Method for Virus Concentration

This study aimed to provide a low-cost technique for virus detection in wastewater by improving an aluminum hydroxide adsorption-precipitation method. The releasing efficiency of viruses trapped by the aluminum hydroxide precipitates was improved by adding ethylenediaminetetraacetic acid disodium salt (EDTA-2Na) to dissolve the precipitates at a Na(2)EDTA center dot 2H(2)O:AlCl3 molar ratio of 1.8-3.6. The recovery rates of the improved method for seven viruses, including SARS-CoV-2-abEN pseudovirus and six animal viruses, were 5.9-22.3% in tap water and 4.9-35.1% in wastewater. Rotavirus A (9.0-4.5 X 10(3) copies/mL), porcine circovirus type 2 (5.8-6.4 X 10(5) copies/mL), and porcine parvovirus (5.6-2.7 X 10(4) copies/mL) were detected in China's pig farm wastewater, while rotavirus A (2.0 X 10(3) copies/mL) was detected in hospital wastewater. SARS-CoV-2 was detected in hospital wastewater (8.4 X 10(2) to 1.4 X 10(4) copies/mL), sewage (6.4 X 10 to 2.3 X 10(3) copies/mL), and river water (6.6 X 10 to 9.3 X 10 copies/mL) in Nepal. The method was automized, with a rate of recovery of 4.8 +/- 1.4% at a virus concentration of 10(2) copies/mL. Thus, the established method could be used for wastewater-based epidemiology with sufficient sensitivity in coping with the COVID-19 epidemic and other virus epidemics.

Smart Infrared Temperature Measurement System Based On Elastic Compute Service Platform

In the fight against the novel coronavirus, this paper designs a smart infrared temperature measurement system based on the Elastic Compute Service platform. In the perceptual layer part of the Internet of Things(IoT), the system uses infrared temperature sensors to quickly collect the temperature of the forehead or arm of the human body and Uses the MCU to automatically transmits the measured data to the Elastic Compute Service through the WiFi module. In the network layer part of the Internet of Things,the data written into the database of the Elastic Compute Service through the program deployed on the Elastic Compute Service. In the application layer of the Internet of Things, the remote management terminal monitors the collected body temperature data in real-time and provides quick warnings. Finally, the User can log in to the applet on his mobile phone to quickly and easily obtain personal information. © 2021 IEEE

Early Identification of COVID-19 Progression to Its Severe Form Using Artificial Intelligence

Background: Early prediction of disease progression in COVID-19 patients can be helpful for personalized therapy, as well as the optimal allocation of public health resources. Objectives: This study aimed to present predictive models for identifying potential high-risk COVID-19 patients upon hospital ad-mission, based on the examination of clinical and radiological features by radiologists and artificial intelligence (AI). Patients and Methods: A total of 786 initially non-severe COVID-19 patients were retrospectively enrolled in this study between January 2 and May 28, 2020. The patients were randomly divided into training (n = 628, 80%) and test (n = 158, 20%) groups. Clinical factors, laboratory indicators, and radiologist-and AI-extracted radiological features of pneumonia lesions were determined using a convolution neural network. The features were selected based on the Boruta algorithm with five-fold cross-validation. Four mod-els, including a model based on clinical findings (model C), a model based on the physician’s examination of radiological features (R-Doc model), a model based on AI-derived radiological features (R-AI model), and an AI-based model mimicking the physician’s examinations (AI-Mimic-Doc model), were constructed for predicting COVID-19 progression upon admission, using a logistic regres-sion analysis. The predictive performance of the four models was evaluated by calculating the area under the receiver operating characteristic (AUC) curve with a 95% confidence interval (95% CI) and then compared using the DeLong test. Results: Overall, 238 out of 786 patients (30.3%) progressed into severe or critical pneumonia during the 14-day follow-up. Nine clinical findings, 17 laboratory indicators, 48 physician-extracted radiological features of pneumonia lesions, and 126 AI-driven radiological features were collected. The urea, albumin level, and lesion size in the basal segment of the right lower lobe of the lung or the proportion of CT values in the range of-200-60 in the left lung were the representative features for constructing the R-Doc and R-AI models, respectively. Comparison of the R-Doc model (AUC: 0.840, 95% CI: 0.747-0.933 for the training set and 0.731, 95% CI: 0.606-0.857 for the test set) with the R-AI model (AUC: 0.803, 95% CI: 0.701-0.906 for the training set and AUC: 0.731, 95% CI: 0.606-0.857 for the validation set) indicated a marginal difference in identifying patients at risk of progression to pneumonia upon admission (P < 0.1). The R-AI model was superior to model C, with an AUC of 0.770 for the training set (95% CI: 0.657-0.882) and 0.666 for the validation set to identify high-risk non-severe cases upon admission. Conclusion: By using radiological features along with blood tests, early identification of COVID-19 patients, who are at risk of disease progression, can be achieved on admission (rapidly by using AI);therefore, the use of these features can contribute to the clinical management of COVID-19. © 2022, Author(s).

Application of Autonomous Driving Technologies in the presence of COVID-19: To reduce occupational exposure and potential nosocomial infections of care workers, during transportation in Emergency Medical Service (EMS)

The responsibility of transporting COVID-19 patients usually falls on the Emergency Medical Service (EMS) department in a hospital. This responsibility exposes EMS workers to high coronavirus infection risks, and we cannot bear the cost of the collapse of EMS. In this paper we explore the feasibility of utilizing autonomous vehicles for patient transportation for reducing the risks of care workers. © 2021 IEEE.

A high-performance humidity sensor based on alkalized MXenes and poly(dopamine) for touchless sensing and respiration monitoring

The typical mode of interaction between humans and machines in current intelligent equipment and personalized health care systems is mainly contact-type. However, there are severe problems associated with direct contact, such as uncomfortable wear and cross-infection of bacteria or viruses, especially under global pandemic conditions (e.g., COVID-19, MERS-CoV). In this study, a flexible humidity sensor is developed based on alkalized MXenes and polydopamine (PDA). The unique accordion-like hierarchical structure of the alkalized MXenes with large specific surface area and the chemical structure of the abundant water-absorbing functional groups of PDA wrapped on the MXene surface contribute synergistically to the outstanding performance of the sensor, which has high sensitivity, rapid response, and large detection range. The device was successfully used to control a noncontact switch system based on the distance of the fingertip and monitor different breathing patterns of a volunteer from a long range, proving its potential application in future noncontact human-machine interaction and human physiology monitoring.

Exploration of nitrogen-doped grape peels carbon dots for baicalin detection

Baicalin, a flavonoid compound extracted from the rhizome of Scutellar iae Baicalensis, plays a vital role in improving liver function after injury, reducing liver disease and treating primary liver cancer, which is also the first SARS-CoV-2 3CLpro virus inhibitor according to the latest research data published in Bio-Rxiv. Therefore, constructing a simple and highly sensitive analytical method for the determination of baicalin is of great significance for the clinical and pharmacy settings. Herein, for the first time, carbon dots are explored for baicalin detection. Using biomass waste grape peels as the organic carbon source, nitrogen-doped fluorescent carbon dots (PT-NCDs) were fabricated, which were synthesized perfectly by a simple, environmentally friendly and one-step solid-phase thermal method without adding any other organic or acid/base reagents. Based on the synergistic effect of photo-induced electron transfer and dynamic quenching, a quenched fluorescence sensor for the determination of baicalin with a good linear range of 0.1-20 mu M and a satisfactory detection limit of 43.8 nM was constructed, which successfully quantified trace amount of baicalin in baicalin capsules, human serum and urine samples. The results indicate that PT-CDs are expected to become potential sensing materials for the real-time monitoring of baicalin in organisms, which is very important for our health. (C) 2021 Elsevier Ltd. All rights reserved.

Epidemics, Convergence, and Common Prosperity: Evidence from China

This article investigates the impact of previous epidemics on rural development and convergence, and identifies the impact's mechanism based on convergence tests. Using a balanced panel of 31 provinces, the empirical results from 2002 to 2019 show that epidemics decelerated convergence in rural per capita income. The mechanism analysis shows that the accelerated divergence in wages and the decelerated convergence in business income were the major drivers, which also led to decelerated convergence in rural per capita consumption. Although epidemics have not threatened rural food consumption and the Engel coefficient of rural households, these two indicators of basic living needs have failed to achieve convergence across regions. The overall impact of an epidemic on convergence in rural-urban income disparity has also been insignificant, indicating that epidemics have affected rural and urban development simultaneously. Finally, COVID-19 is likely to decelerate convergence in rural income, rural consumption, and urban income.

LuMiRa: An Integrated Lung Deformation Atlas and 3D-CNN Model of Infiltrates for COVID-19 Prognosis

Although, recently convolutional neural networks (CNNs) based prognostic models have been developed for COVID-19 severity prediction, most of these studies have analyzed characteristics of lung infiltrates (ground-glass opacities and consolidations) on chest radiographs or CT. However, none of the studies have explored the possible lung deformations due to the disease. Our hypothesis is that more severe disease results in more pronounced deformation. The key contributions of this work are three-fold: (1) A new lung deformation based biomarker analyzing regions of differential distensions between COVID-19 patients with mild and severe disease. (2) Integrating 3D-CNN characterization of lung deformation regions and lung infiltrates on lung CT into a novel framework (LuMiRa) for prognosticating COVID-19 severity. (3) Validating LuMiRa on one of the largest multi-institutional cohort till date (N = 948 patients). We found that majority of the shape deformations were observed in the mediastinal surface of both the lungs and in left interior lobe. On a testing cohort based on two institutions, Av (N = 419) and Bv (N = 113), LuMiRa yielded an area under the receiver operating characteristic curve (AUC) of 0.89 and 0.77 respectively showing significant improvement over a 3D-CNN trained over just lung infiltrates (AUC = 0.85 (p < 0.001), AUC = 0.75 (p = 0.01)). Additionally, LuMiRa performed significantly better than machine learning models trained on clinical and radiomic features (0.82, 0.78 and 0.72, 0.72 on Av and Bv respectively). © 2021, Springer Nature Switzerland AG.

Ergonomics of Virtual Learning During COVID-19

Virtual learning has been widely adopted in many higher education institutes. This is especially necessary and important during the ongoing COVID-19 pandemic. In order to identify the ergonomic issues that college students faced while learning remotely during the pandemic, a five-question survey was conducted in October 2020. While 60% of the respondents reported more or most comfortability while working/studying at home, 56% of the students claimed more stress and 64% of the students reported average or less-than-average productivity. In terms of using ergonomic postures while learning remotely, 56% of the survey respondents answered that they used them occasionally and another 20% reported that they never used them. Overall, the survey results are in line with the findings that were reported by other studies. The study results may contribute to the knowledge about the ergonomic challenges that virtual learning presents, especially during this unusual time. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Graphic Perception Design of Social Fear Release for College Students

Exploring the ways in which social phobic groups among university students regulate their emotions before and after the start of the school year in the post-epidemic period of COVID-19.Through the methods of literature research, questionnaire survey, interview and research, this paper analyzes the emotional fluctuation of college students before and after the beginning of school in the post-epidemic period, so as to carry out the graphic perception design of college students “social fear release, which is used to guide and induce college students with social phobia to generate positive emotions, overcome psychological barriers, and form a positive and healthy social mentality. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

A Dynamic Model for Measuring Resilient Dividend Including the Levels of Shocks and Resilience Based on Covid-19 Data at the Subnational Level of China

Resilience has been mentioned frequently as an essential component of Sustainable Development and a solution to climate change. However, resilience does not impose an additional burden, but provide dividend on development. After an overview of definitions for resilient dividend, we proposed a dynamic framework to measure the resilient dividend under different levels of shocks and resilience. We did an empirical study in the context of COVID-19 to verify the correlations between resilience and dividend. A bunch of indicators and quantitative data at the subnational level of China were collected to represent the impact of the pandemic, the resilient levels and the dividend gained from resilience for 30 provinces in China. After descending the dataset with PCA (Principal Component Analysis) and maximum variance method, we experimented hierarchical regression which revealed that more dividends could be expected with a higher level of resilience, particularly under severe shocks. The conclusions could provide a better understanding of resilience and a theoretical basis for further discussion on resilient dividends. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.