Synthesis and enzymatic inhibition effects of thiazolidinedione 3C-like protease inhibitors

The 3C-like protease (also known as Mpro) plays a key role in SARS-CoV-2 replication and has similar substrates across mutant coronaviruses, making it an ideal drug target. We synthesized 19 thiazolidinedione derivatives via the Knoevenagel condensations and Mitsunobu reactions as potential 3C-like protease inhibitors. The activity of these inhibitors is screened in vitro by employing the enzymatic screening model of 3C-like protease using fluorescence resonance energy transfer. Dithiothreitol is included in the enzymatic reaction system to avoid non-specific enzymatic inhibition. Active inhibitors with diverse activity are found in this series of compounds, and two representative inhibitors with potent inhibitory activity are highlighted. © The Author(s) 2023.

Preparation, characterization, and air filtration property of electrospun bimodal fibrous membrane based on low conductivity blended polymers solution

One–step preparation of electrospun bimodal fibrous membrane based on single nozzle is the key to the efficient fabrication of high–performance air filter. However, the preparation mechanism of electrospun bimodal fibers at low conductivity solution system is not clear, and there is a lack of evaluation methods for the quality of bimodal nanofibers, which limits the applicability of single nozzle electrospinning and the preparation efficiency of electrospun bimodal fibers. Here, three electrospinning processes at low conductivity solution systems of polyamide–6 (PA6), PA6 blended PVP (PA6/PVP), and PA6 blended polyethylene oxide (PA6/PEO) were studied according to the rheological properties and the fluid electrics (i.e., zeta potential), and the quality of the prepared bimodal fibrous membrane was creatively evaluated by R value. Inhomogeneous phase separations of the electrospinning jet along the direction parallel (x–axis) or perpendicular (y–axis) to the electric field were responsible for the formation of bimodal fibers. In addition, for the same solution system, the R value had a positive correlation with the air filtration performance. This work will greatly enhance the applicability of one–step single nozzle electrospinning for the preparation of bimodal nanofibers, improve the preparation efficiency, and promote the development of high–performance air filter. © 2022 Elsevier Ltd

Risk spillovers in global financial markets: Evidence from the COVID-19 crisis

This paper aims to comprehensively investigate the dynamics of short-, medium- and long-term risk spillovers across the major financial markets in the context of COVID-19. Our main empirical findings are as follows. First, we find that the deterioration of the COVID-19 pandemic raised the risk of stock, bond, crude oil, and foreign exchange markets sequentially in the short term. Second, from the perspective of the medium and long term, the COVID-19 pandemic triggered substantial risk spillovers across financial markets, which is also highly correlated with the degree of investor panic. Third, we show that different markets played different roles in terms of risk transmission during the pandemic. Specifically, the stock and crude oil markets acted more as risk senders, the gold and foreign exchange markets acted more as risk receivers, and the bond market served as a transfer station of risk. Finally, we find that containment and health responses can effectively mitigate risk spillovers across markets in the short term, while expansionary fiscal policy can reduce them more effectively in the medium and long term. Our findings have important implications for policymakers and investors who aim to mitigate the adverse impact of the COVID-19 pandemic on financial markets. © 2022 Elsevier Inc.

Pathogenic infection characteristics and risk factors for bovine respiratory disease complex based on the detection of lung pathogens in dead cattle in northeast China.

Bovine respiratory disease complex (BRDC) involves multiple pathogens, shows diverse lung lesions, and is a major concern in calves. Pathogens from 160 lung samples of dead cattle from 81 cattle farms in northeast China from 2016 to 2021 were collected to characterize the molecular epidemiology and risk factors of BRDC and to assess the major pathogens involved in bovine suppurative or caseous necrotizing pneumonia. The BRDC was diagnosed by autopsy, pathogen isolation, PCR, or reverse transcription-PCR detection, and gene sequencing. More than 18 species of pathogens, including 491 strains of respiratory pathogens, were detected. The positivity rate of bacteria in the 160 lung samples was 31.77%, including Trueperella pyogenes (9.37%), Pasteurella multocida (8.35%), Histophilus somni (4.48%), Mannheimia haemolytica (2.44%), and other bacteria (7.13%). The positivity rate of Mycoplasma spp. was 38.9%, including M. bovis (7.74%), M. dispar (11.61%), M. bovirhinis (7.94%), M. alkalescens (6.11%), M. arginini (0.81%), and undetermined species (4.68%). Six species of viruses were detected with a positivity rate of 29.33%, including bovine herpesvirus-1 (BoHV-1; 13.25%), bovine respiratory syncytial virus (BRSV; 5.50%), bovine viral diarrhea virus (BVDV; 4.89%), bovine parainfluenza virus type-3 (BPIV-3; 4.28%), bovine parainfluenza virus type-5 (1.22%), and bovine coronavirus (2.24%). Mixed infections among bacteria (73.75%), viruses (50%), and M. bovis (23.75%) were the major features of BRDC in these cattle herds. The risk analysis for multi-pathogen co-infection indicated that BoHV-1 and H. somni; BVDV and M. bovis, P. multocida, T. pyogenes, or Mann. haemolytica; BPIV-3 and M. bovis; BRSV and M. bovis, P. multocida, or T. pyogenes; P. multocida and T. pyogenes; and M. bovis and T. pyogenes or H. somni showed co-infection trends. A survey on molecular epidemiology indicated that the occurrence rate of currently prevalent pathogens in BRDC was 46.15% (6/13) for BoHV-1.2b and 53.85% (7/13) for BoHV-1.2c, 53.3% (8/15) for BVDV-1b and 46.7% (7/15) for BVDV-1d, 29.41% (5/17) for BPIV-3a and 70.59% (12/17) for BPIV-3c, 100% (2/2) for BRSV gene subgroup IX, 91.67% (33/36) for P. multocida serotype A, and 8.33% (3/36) for P. multocida serotype D. Our research discovered new subgenotypes for BoHV-1.2c, BRSV gene subgroup IX, and P. multocida serotype D in China's cattle herds. In the BRDC cases, bovine suppurative or caseous necrotizing pneumonia was highly related to BVDV [odds ratio (OR) = 4.18; 95% confidence interval (95% CI): 1.6-10.7], M. bovis (OR = 2.35; 95% CI: 1.1-4.9), H. somni (OR = 8.2; 95% CI: 2.6-25.5) and T. pyogenes (OR = 13.92; 95% CI: 5.8-33.3). The risk factor analysis found that dairy calves <3 mo and beef calves >3 mo (OR = 5.39; 95% CI: 2.7-10.7) were more susceptible to BRDC. Beef cattle were more susceptible to bovine suppurative or caseous necrotizing pneumonia than dairy cattle (OR = 2.32; 95% CI: 1.2-4.4). These epidemiological data and the new pathogen subgenotypes will be helpful in formulating strategies of control and prevention, developing new vaccines, improving clinical differential diagnosis by necropsy, predicting the most likely pathogen, and justifying antimicrobial use.

COVID-19 and SARS Virus Function Sites Classification with Machine Learning Methods

COVID-19 and SARS virus are two related coronaviruses. In recent years, the increasingly serious epidemic situation has become the focus of all human beings, and has brought a significant impact on daily life. So, we proposed a link analysis of the two viruses. We obtained all the required COVID-19 and SARS virus data from the Uniprot database website, and we preprocessed the data after obtaining the data. In the prediction of the binding site of the COVID-19 and SARS, it is to judge the validity between the two binding sites. In response to this problem, we used Adaboost, voting-classifier and SVM classifier, and compared different classifier strategies through experiments. Among them, Metal binding site can effectively improve the accuracy of protein binding site prediction, and the effect is more obvious. Provide assistance for bioinformatics research. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

An Improved VGG16 Model for Pneumonia Image Classification

Image recognition has been applied to many fields, but it is relatively rarely applied to medical images. Recent significant deep learning progress for image recognition has raised strong research interest in medical image recognition. First of all, we found the prediction result using the VGG16 model on failed pneumonia X-ray images. Thus, this paper proposes IVGG13 (Improved Visual Geometry Group-13), a modified VGG16 model for classification pneumonia X-rays images. Open-source thoracic X-ray images acquired from the Kaggle platform were employed for pneumonia recognition, but only a few data were obtained, and datasets were unbalanced after classification, either of which can result in extremely poor recognition from trained neural network models. Therefore, we applied augmentation pre-processing to compensate for low data volume and poorly balanced datasets. The original datasets without data augmentation were trained using the proposed and some well-known convolutional neural networks, such as LeNet AlexNet, GoogLeNet and VGG16. In the experimental results, the recognition rates and other evaluation criteria, such as precision, recall and f-measure, were evaluated for each model. This process was repeated for augmented and balanced datasets, with greatly improved metrics such as precision, recall and F1-measure. The proposed IVGG13 model produced superior outcomes with the F1-measure compared with the current best practice convolutional neural networks for medical image recognition, confirming data augmentation effectively improved model accuracy.

Correlation between dynamic changes of chest ct findings and therapeutic response of covid-19: A multicenter experience in shanghai, china

Background: The novel coronavirus disease 2019 (COVID-19) has become a global public health emergency. Computed tomography (CT) offers valuable clues to the diagnosis of COVID-19. However, little is known about the correlation between dynamic changes of CT scores and therapeutic response in the course of COVID-19. Objectives: To describe the temporal changes of CT findings and characterize the time window of disease progression on the follow-up CT scans of patients with COVID-19. Patients and Methods: In this historical cohort study performed in Shanghai, China, the follow-up chest CT images of 91 patients with COVID-19 with different therapeutic responses were reviewed in multiple centers, with an emphasis on characterizing the changing trend of CT scores for lung lesions at 13-15 days after the symptom onset and thereafter. The CT score curve patterns were categorized into type 1 (characterized by an increase to the peak level, followed by a decrease), type 2 (characterized by a steady change without an obvious peak), and type 3 (characterized by a progressive increase). Results: The CT scores of the progression group (n = 9) with a longer time to the peak were significantly higher than those of the non-progression group (n = 82) on the first day and days 13-15 (P < 0.05), except for the median CT scores before days 13-15. The CT curve type 1 and type 2 were commonly observed in the non-progression group (63.4% and 36.6%, respectively), while type 3 was more common in the progression group (88.9%). Conclusion: Most patients with COVID-19 show favorable responses to clinical treatments in Shanghai. Thirteen to fifteen days after the symptom onset can be considered as a turning point for the therapeutic response. The CT curve type 3 usually represents a poor response. The CT scores of patients with different therapeutic responses may overlap before days 13-15. The changing trend of longitudinal CT scores may contribute to the prediction of disease progression.

Analyzing the anti-contagion policies of COVID-19 based on the epidemiological and economic coefficients

In the early months of 2020, the regional propagation of COVID-19, a novel coronavirus, has evolved into a global public health emergency. Governments have not yet decided on an optimal plan to defend from COVID-19 due to lack of previous experience with such large-scale pandemics. Neither have researchers published a holistic approach of anticontagion policy analysis. In order to explore the middle ground of minimized negative effects on health and economy, this paper evaluated 1, 637 non-pharmaceutical anti-contagion policies from sub-regions in China, France, Italy, and South Korea. Inspired by previous research [1] [2], we utilized reduced-form approach and Computable General Equilibrium (CGE) model in the field of macroeconomics to calculate the effect of each individual policy on infection and GDP growth rates. These methods are based on filtered financial accounts (i.e. social accounting matrices) obtained from Global Trade Analysis Project (GTAP) database along with a published G-Cubed (G20) model, as well as the epidemiological data concerning the national conditions of each aforementioned country. We complete more than 1, 000 random samplings and iterations to average the policy coefficients of infection and GDP growth rates and minimize their standard errors. The major observation on the results is that an early implementation of travel ban for 2 weeks will effectively undermine the spread of COVID-19 at a low economic price. In addition, some policies (e.g. social distancing) require adjustment in their duration or range to improve their price-performance ratio (here, economic-health ratio). This form of hybrid policy analysis not only prevents further infectivity, but also ensures the stability of the global economy. © 2021 IEEE.

Monitoring work resumption of wuhan in the covid-19 epidemic using daily nighttime light

This study analyzes the characteristics of nighttime light (NTL) radiance variation, aiming to demonstrate the possibility of using NTL to monitor work resumption and evaluate the impact of COVID-19 on economic activities in Wuhan, China. The results show that NTL radiance generally decreased during the epidemic. Despite the fact that increased NTL radiance was observed after lifting the lockdown, it was still lower than normal, indicating that socioeconomic activities have been largely resumed but the production scale has not been fully restored, and the decrease in nitrogen dioxide concentration verified this phenomenon. We find that central urban areas and distant suburban areas present different modes of NTL radiance variation. We further observed a decrease in NTL radiance from different urban functional areas, including industrial parks, airports, business districts, loop lines, and residential area, that corresponds to the impact of the COVID-19 epidemic on both industrial production and the service sector. © 2021 American Society for Photogrammetry and Remote Sensing.

On the molecular structure of Remdesivir for the treatment of Covid-19.

(SARS-CoV-2), was first identified in December 2019 as the cause of a respiratory illness designated coronavirus disease 2019, or Covid-19. Several therapeutic agents have been evaluated for the treatment of Covid-19, but none have yet been shown to be efficacious. Remdesivir (GS-5734), an inhibitor of the viral RNA-dependent, RNA polymerase with inhibitory activity against SARS-CoV and the Middle East respiratory syndrome (MERS-CoV), was identified early as a promising therapeutic candidate for Covid-19 because of its ability to inhibit SARS-CoV-2 in vitro. Besides, in nonhuman primate studies, remdesivir initiated 12 hours after inoculation with MERS-CoV9,10 reduced lung virus levels and lung damage. In the field of Medical Science, concerning the definition of the topological index on the molecular structure and corresponding medical, biological, chemical, pharmaceutical properties of drugs can be studied by the topological index calculation. In this paper, we compute some of the general temperature topological properties of remdesivir that the results in this paper may be useful in finding new drug and vaccine for the treatment and prevention of COVID-19.

Influence of Corona Virus Disease 2019 (COVID-19) on Renovation of Rural Living Environment

In rural areas with low economic level and weak environmental control, the spread of Corona Virus Disease 2019 (COVID-19) impacts on agricultural and rural development. This study analyzed the relationship between COVID-19 prevention process and rural living environment renovation, and explored the major influences of the former on the latter. It is found that there are risks of virus proliferation in rural living environment, such as rural garbage accumulation, improper sewage treatment, the substandard disposal of toilet waste and imperfect infrastructure construction. Transportation restrictions not only effectively curb the spread of COVID-19, but also delay the renovation of rural living environment work. Meanwhile, the spread of the COVID-19 has limited farmers' activities in the short term. Therefore, this paper proposed to improve the rural living environment improvement system and the technologies to effectively control the spread of COVID-19, and promote the improvement of rural living environment and upgrade the life quality of farmers, which lay a solid foundation to restore farmers' lives, agricultural production and rural development after COVID-19. © 2020, Editorial Board, Research of Environmental Sciences. All right reserved.

A review on clinical application of high frequency traditional Chinese medicine in treatment of coronavirus pneumonia 2019

Since December 2019, there has been a sharp increase in the number of confirmed cases of pneumonia caused by the novel coronavirus (SARS-CoV-2) in China, which has caused great concern around the world. In face of severe epidemic, no specific drugs have been found in clinical practice. However, some Chinese medicine compounds have shown obvious clinical efficacy, and it is feasible to find and develop natural drugs for the treatment of novel coronavirus pneumonia from these compounds. In this paper, based on the recommends of new type of coronavirus infection pneumonia diagnosis and treatment scheme (trial version 6), the use frequency of Chinese herbal medicines was calculated. The antiviral reports of high frequency Chinese herbal medicines were reviewed, in order to provide the reference for screening the active components against SARS-CoV-2 from traditional Chinese medicine.