An Effective COVID-19 CT Image Denoising Method Based on a Deep Convolutional Neural Network

Background: Faced with the global threat posed by SARS-CoV-2 (COVID-19), low-dose computed tomography (LDCT), as the primary diagnostic tool, is often accompanied by high levels of noise. This can easily interfere with the radiologist's assessment. Convolutional neural networks (CNN), as a method of deep learning, have been shown to have excellent effects in image denoising. Objective: The objective of the study was to use modified convolutional neural network algorithm to train the denoising model. The purpose was to make the model extract the highlighted features of the lesion region better and ensure its effectiveness in removing noise from COVID-19 lung CT images, preserving more important detail information of the images and reducing the adverse effects of denoising. Methods: We propose a CNN-based deformable convolutional denoising neural network (DCDNet). By combining deformable convolution methods with residual learning on the basis of CNN structure, more image detail features are retained in CT image denoising. Results: According to the noise reduction evaluation index of PSNR, SSIM and RMSE, DCDNet shows excellent denoising performance for COVID-19 CT images. From the visual effect of denoising, DCDNet can effectively remove image noise and preserve more detailed features of lung lesions. Conclusion: The experimental results indicate that the DCDNet-trained model is more suitable for image denoising of COVID-19 than traditional image denoising algorithms under the same training set. © 2023 Bentham Science Publishers.

Impact of short-term ambient air pollution exposure on the risk of severe COVID-19

Ecological studies suggested a link between air pollution and severe COVID-19 outcomes, while studies accounting for individual-level characteristics are limited. In the present study, we aimed to investigate the impact of short-term ambient air pollution exposure on disease severity among a cohort of 569 laboratory confirmed COVID-19 patients admitted to designated hospitals in Zhejiang province, China, from January 17 to March 3, 2020, and elucidate the possible biological processes involved using transcriptomics. Compared with mild cases, severe cases had higher proportion of medical conditions as well as unfavorable results in most of the laboratory tests, and manifested higher air pollution exposure levels. Higher exposure to air pollutants was associated with increased risk of severe COVID-19 with odds ratio (OR) of 1.89 (95% confidence interval (CI): 1.01, 3.53), 2.35 (95% CI: 1.20, 4.61), 2.87 (95% CI: 1.68, 4.91), and 2.01 (95% CI: 1.10, 3.69) for PM2.5, PM10, NO2 and CO, respectively. OR for NO2 remained significant in two-pollutant models after adjusting for other pollutants. Transcriptional analysis showed 884 differentially expressed genes which mainly were enriched in virus clearance related biological processes between patients with high and low NO2 exposure levels, indicating that compromised immune response might be a potential underlying mechanistic pathway. These findings highlight the impact of short-term air pollution exposure, particularly for NO2, on COVID-19 severity, and emphasize the significance in mitigating the COVID-19 burden of commitments to improve air quality. © 2022

Impact of short-term ambient air pollution exposure on the risk of severe COVID-19

Ecological studies suggested a link between air pollution and severe COVID-19 outcomes, while studies accounting for individual-level characteristics are limited. In the present study, we aimed to investigate the impact of short-term ambient air pollution exposure on disease severity among a cohort of 569 laboratory confirmed COVID-19 patients admitted to designated hospitals in Zhejiang province, China, from January 17 to March 3, 2020, and elucidate the possible biological processes involved using transcriptomics. Compared with mild cases, severe cases had higher proportion of medical conditions as well as unfavorable results in most of the laboratory tests, and manifested higher air pollution exposure levels. Higher exposure to air pollutants was associated with increased risk of severe COVID-19 with odds ratio (OR) of 1.89 (95% confidence interval (CI): 1.01, 3.53), 2.35 (95% CI: 1.20, 4.61), 2.87 (95% CI: 1.68, 4.91), and 2.01 (95% CI: 1.10, 3.69) for PM2.5, PM10, NO2 and CO, respectively. OR for NO2 remained significant in two-pollutant models after adjusting for other pollutants. Transcriptional analysis showed 884 differentially expressed genes which mainly were enriched in virus clearance related biological processes between patients with high and low NO2 exposure levels, indicating that compromised immune response might be a potential underlying mechanistic pathway. These findings highlight the impact of short-term air pollution exposure, particularly for NO2, on COVID-19 severity, and emphasize the significance in mitigating the COVID-19 burden of commitments to improve air quality.

IMPACTS AND MEASURES COVID-19 PANDEMIC AND TOURISM INDUSTRY IN SABAH

The COVID-19 pandemic has had a significant adverse influence on the country’s economic and social situation, especially with regard to the tourism industry. This study examines the implications of the global pandemic on the tourism industry in Sabah, the study will consider the impact of the movement control order (MCO) and other mitigating measures adopted by tourism industry players. The survey and focus group findings indicate that the pandemic has had a significant impact on the tourism industry in the state, compelling operators and policymakers to re-evaluate current response strategies. The adoption of the MCO in response to the pandemic has resulted in business interruptions and income loss for tourism industry service-providers, with most of them losing more than 80% of their revenues. Diversification is one of the strategies used by operators in the industry to ensure long and short-term viability. Meanwhile, a government vaccination program is a long-term strategy aimed at ensuring that the tourism sector in Sabah can return to normalcy. As with any study, this study too has limitations in terms of the number of industry sectors studied and sample size used to collect data © Penerbit UMT

High-Resolution Lagrangian Inverse Modeling of CO2 Emissions Over the Paris Region During the First 2020 Lockdown Period

Stringent mobility restrictions across the world during the COVID 19 pandemic have impacted local economies and, consequently, city carbon budgets, offering a unique opportunity to evaluate the capability of scientific approaches to quantify emissions changes. Our study aims to quantify and map CO2 emissions from fossil fuel and biogenic CO2 fluxes over the Paris metropolitan area during the first lockdown period (March-May 2020) in France, in comparison with the same period in 2019. Our inversion system relies on transport model simulations initiated with the Weather Research and Forecasting chemistry transport model combined with a high-resolution fossil fuel CO2 emissions inventory, and biogenic CO2 fluxes from a vegetation model. The inversion with atmospheric observations from a network of six towers resulted in a positive re-adjustment of fossil fuel CO2 emissions in 2019 and 2020 compared to prior. In 2020, the inversion resulted in a large emission reduction (43%) compared to 2019, while the reductions were estimated to be 37% based on the prior inventory itself. By assimilating CO mixing ratios in addition to CO2, the traffic emission estimates were reduced by 68% in 2020, compared to nontraffic (29%). Various sensitivity tests show that prior emission uncertainty and different background conditions significantly impacted the emissions estimates. We conclude that our current inversion system with atmospheric CO2 monitoring makes it possible to identify the emission decrease in 2020 partly over the urban region. However, additional information on prior emission errors and a dense network will be needed to map emissions precisely. © 2022. American Geophysical Union. All Rights Reserved.

[Analysis of differences and influencing factors of liver injury associated with different strains of 2019-nCoV infection].

Objective: To analyze whether there are differences and related influencing factors in liver injury associated with different strains of 2019-nCoV/SARS-CoV-2 infection. Methods: Data of epidemiology, clinical symptoms, laboratory tests, and treatment outcomes of patients with COVID-19 infection confirmed with Alpha and Delta virus strain in Zhejiang Province were retrospectively collected. Statistical analysis was performed using independent samples t-test or Mann-Whitney U test, χ2 test or Fisher's exact test, and logistic regression analysis. Results: A total of 788 and 381 cases with Alpha and Delta virus strain were included. Vaccination ratio was 0% in Alpha and 85.30% in Delta group (P<0.001), The proportion of patients with fever (80.71% vs. 40.94%, P<0.001) was significantly higher in Alpha than Delta strain group. The proportion of critical ill patients was significantly higher in Delta group (9.90% vs. 1.57%, respectively, P<0.001). The virus negative conversion time was significantly longer in Delta than Alpha group (22 d vs. 11 d, P<0.001), but the incidence of liver injury was significantly higher in Alpha than Delta group (20.05% vs. 13.91%, P=0.011). Univariate analysis showed that Alpha virus strain infection, male sex, body mass index, chronic liver disease, fever, diarrhea, shortness of breath, severe/critical illness, elevated creatine kinase (CK), elevated international normalized ratio (INR) and an elevated neutrophil/lymphocyte ratio was significantly associated with an increased risk of liver injury occurrence, and in patients with pharyngeal pain the risk of liver injury occurrence was significantly reduced. Multivariate analysis showed that shortness of breath [OR, 2.667 (CI: 1.389-5.122); P=0.003], increased CK [OR, 2.544 (CI: 1.414-4.576); P=0.002] and increased INR [OR, 1.721] (CI: 1.074-2.758); P=0.024] was significantly associated with an increased risk of liver injury occurrence, and in patients with pharyngeal pain the risk of liver injury occurrence was significantly reduced [OR, 0.424 (CI: 0.254-0.709); P=0.001]. Conclusion: Although the virulence of the Delta is stronger than Alpha strain, most patients infected with Delta strain vaccinated against COVID-19 in Zhejiang province had milder clinical symptoms and a lower incidence and degree of liver injury. Notably, the infection risk even remains after vaccination; however, symptoms and the incidence of severe and critical illness can be significantly reduced.

The Diagnosis, Treatment and Prevention of COVID-19

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and this kind of virus is highly infectious. Patients will experience severe acute respiratory infection symptoms if they are infected by the virus. Unfortunately, some patients have a very bleak prognosis or even die of it. Therefore, it seriously affects people’s normal life. Nowadays, various countries are actively conducting relevant research and have conducted in-depth discussions on the response plan to be adopted after the outbreak of COVID-19. This review includes not only the pathogenic characteristics, pathogenic mechanism and detection methods of SARS-CoV-2, but also the treatment and prevention of COVID-19. © 2021 Institute of Biophysics,Chinese Academy of Sciences. All rights reserved.

In Search for a Cure: Recommendation with Knowledge Graph on CORD-19

The whole globe has cranked up for coping with the COVID-19 situation. The hands-on tutorial targets at providing a comprehensive and pragmatic end-to-end walk-through for building an academic research paper recommender for the use case of COVID-19 related study, with the help of knowledge graph technology. The code examples that demonstrate the theories are reproducible and can hopefully provide value for researchers to build tools that support conducting research to find a cure to COVID-19. © 2020 Owner/Author.

[Clinical characteristics and influencing factors of patients with novel coronavirus pneumonia combined with liver injury in Shaanxi region].

Objective: To understand the clinical characteristics, change of liver function, influencing factors and prognosis in hospitalized patients with coronavirus disease-19 (COVID-19) combined with liver injury. Methods: The general conditions, biochemical indicators of liver, blood clotting mechanism, routine blood test, UGT1A1 * 28 gene polymorphism and other data of 40 cases with COVID-19 admitted to the isolation ward of Tangdu Hospital were retrospectively analyzed. The clinical characteristics, influencing factors and prognosis of liver injury in patients with liver injury group and those with normal liver function group were compared. The mean of two samples in univariate analysis was compared by t-test and analysis of variance. The counting data was measured by χ(2) tests. The non-normal distribution measurement data were described by the median, and the non-parametric test was used. Statistically significant influencing factors were used as the independent variables in univariate analysis. Multiple logistic regression analysis was used to analyze the main influencing factors of liver injury. Results: Of the 40 cases, 25 were male (62.5%) and 15 were female (37.5%), aged 22 to 83 (53.87 ± 15.84) years. Liver injury was occurred in 22 cases (55%) during the course of the disease. Alanine aminotransferase (ALT) and aspartate aminotransferase (AST) level was initially increased (4.4 to 3.5 times of the normal value) along with decrease of albumin in the second week, and the difference was statistically significant (P < 0.001). Ten cases (43.5%) had highest abnormal total blood bilirubin (54.1 µmol/ L). There was no correlation between the increase in transaminase and the increase in total blood bilirubin (R = -0.006, P = 0.972). Three cases had prothrombin activity (PTA) of ≤50%, 10 cases had elevated FDP, and 13 cases had elevated D-dimer, all of whom were severe or critically ill. Liver function injury was more likely to occur in patients who used many types of drugs and large amounts of hormones (P = 0.002, P = 0.031), and there was no correlation with the TA6TA7 mutation in the UGT1A1 * 28 gene locus. Multiple regression analysis showed that the occurrence of liver injury was only related to critical illness. The liver function of all patients had recovered within one week after conventional liver protection treatment. Conclusion: COVID-19 combined with liver function injury may be due to the slight elevation of transaminase, mostly around the second week of the disease course. Severe patients have a higher proportion of liver injury, and critical type is an independent risk factor for liver injury.