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1.
Adv Ther (Weinh) ; 4(7): 2100055, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-2287445

ABSTRACT

Identifying effective drug treatments for COVID-19 is essential to reduce morbidity and mortality. Although a number of existing drugs have been proposed as potential COVID-19 treatments, effective data platforms and algorithms to prioritize drug candidates for evaluation and application of knowledge graph for drug repurposing have not been adequately explored. A COVID-19 knowledge graph by integrating 14 public bioinformatic databases containing information on drugs, genes, proteins, viruses, diseases, symptoms and their linkages is developed. An algorithm is developed to extract hidden linkages connecting drugs and COVID-19 from the knowledge graph, to generate and rank proposed drug candidates for repurposing as treatments for COVID-19 by integrating three scores for each drug: motif scores, knowledge graph PageRank scores, and knowledge graph embedding scores. The knowledge graph contains over 48 000 nodes and 13 37 000 edges, including 13 563 molecules in the DrugBank database. From the 5624 molecules identified by the motif-discovery algorithms, ranking results show that 112 drug molecules had the top 2% scores, of which 50 existing drugs with other indications approved by health administrations reported. The proposed drug candidates serve to generate hypotheses for future evaluation in clinical trials and observational studies.

2.
Environ Res ; 221: 115282, 2023 03 15.
Article in English | MEDLINE | ID: covidwho-2178501

ABSTRACT

To inhibit the COVID-19 (Coronavirus disease 2019) outbreak, unprecedented nationwide lockdowns were implemented in China in early 2020, resulting in a marked reduction of anthropogenic emissions. However, reasons for the insignificant improvement in air quality in megacities of northeast China, including Shenyang, Changchun, Jilin, Harbin, and Daqing, were scarcely reported. We assessed the influences of meteorological conditions and changes in emissions on air quality in the five megacities during the COVID-19 lockdown (February 2020) using the WRF-CMAQ model. Modeling results indicated that meteorology contributed a 14.7% increment in Air Quality Index (AQI) averaged over the five megacities, thus, the local unfavorable meteorology was one of the causes to yield little improved air quality. In terms of emission changes, the increase in residential emissions (+15%) accompanied by declining industry emissions (-15%) and transportation (-90%) emissions resulted in a slight AQI decrease of 3.1%, demonstrating the decrease in emissions associated with the lockdown were largely offset by the increment in residential emissions. Also, residential emissions contributed 42.3% to PM2.5 concentration on average based on the Integrated Source Apportionment tool. These results demonstrated the key role residential emissions played in determining air quality. The findings of this study provide a scenario that helps make appropriate emission mitigation measures for improving air quality in this part of China.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Humans , COVID-19/epidemiology , Air Pollutants/analysis , Cities , Particulate Matter/analysis , Environmental Monitoring , Communicable Disease Control , Air Pollution/analysis , China/epidemiology
3.
Comput Biol Med ; 152: 106385, 2023 01.
Article in English | MEDLINE | ID: covidwho-2130528

ABSTRACT

BACKGROUND: Numerous traditional filtering approaches and deep learning-based methods have been proposed to improve the quality of ultrasound (US) image data. However, their results tend to suffer from over-smoothing and loss of texture and fine details. Moreover, they perform poorly on images with different degradation levels and mainly focus on speckle reduction, even though texture and fine detail enhancement are of crucial importance in clinical diagnosis. METHODS: We propose an end-to-end framework termed US-Net for simultaneous speckle suppression and texture enhancement in US images. The architecture of US-Net is inspired by U-Net, whereby a feature refinement attention block (FRAB) is introduced to enable an effective learning of multi-level and multi-contextual representative features. Specifically, FRAB aims to emphasize high-frequency image information, which helps boost the restoration and preservation of fine-grained and textural details. Furthermore, our proposed US-Net is trained essentially with real US image data, whereby real US images embedded with simulated multi-level speckle noise are used as an auxiliary training set. RESULTS: Extensive quantitative and qualitative experiments indicate that although trained with only one US image data type, our proposed US-Net is capable of restoring images acquired from different body parts and scanning settings with different degradation levels, while exhibiting favorable performance against state-of-the-art image enhancement approaches. Furthermore, utilizing our proposed US-Net as a pre-processing stage for COVID-19 diagnosis results in a gain of 3.6% in diagnostic accuracy. CONCLUSIONS: The proposed framework can help improve the accuracy of ultrasound diagnosis.


Subject(s)
COVID-19 Testing , COVID-19 , Humans , Ultrasonography/methods , Image Enhancement/methods , Image Processing, Computer-Assisted , Algorithms
4.
Front Public Health ; 10: 973843, 2022.
Article in English | MEDLINE | ID: covidwho-2121817

ABSTRACT

The COVID-19 pandemic has seriously affected China's macroeconomy, industrial transformation, and high-quality development. Research on economic patterns and urban network systems can provide a reference for healthy development of the regional economic system. The evolution of the economic pattern and urban network system of Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 2010 to 2020 is investigated using methods (e.g., the gravity center model, the gravitational force model, social network analysis, and geographic information system). (1) The gravity center of gross domestic product (GDP) of the GBA is located in Nansha district, Guangzhou, with a skewing direction northwest-east-northwest and a movement rate of "large-small-large." The center of import and export and the center of consumption show a "zigzagging migration" in which the center of investment shows an "irregular (random) migration". (2) The economic connection degree of cities in the GBA exhibits a high ascending velocity, and the whole area tends to be mature, with a significant effect of spatial proximity. With the steady increase in network density, there is significant polarization of network centrality in the region. The four major cohesive subgroups have been relatively stable and consistent with the degree of geographic proximity of the cities. The center-periphery structure is more significant, in which the core area is extended to the cities on the east coast of the Pearl River Estuary, thus forming the core cluster of "Hong Kong-Shenzhen-Guangzhou-Dongguan." In this study, the evolution of economic patterns and urban network systems in the GBA over the past decade is analyzed using multiple methods (i.e., gravity model, urban network system analysis, and geographic information system) based on urban socioeconomic data by starting from various spatial elements (e.g., "points, lines, and networks") to gain insights into and optimize research on regional economic development after the COVID-19 pandemic.


Subject(s)
COVID-19 , Humans , Hong Kong/epidemiology , Macau , COVID-19/epidemiology , Pandemics , Cities
5.
Cell Rep Med ; 3(10): 100752, 2022 10 18.
Article in English | MEDLINE | ID: covidwho-2031746

ABSTRACT

Increasing evidence indicates that gut microbiota may play a key role in vaccination immunity. Here, we investigate whether the human gut microbiota and metabolic function correlate with the BBIBP-CorV vaccine response. A total of 207 participants who received the BBIBP-CorV vaccine are enrolled. The gut microbiome and metabolic functions are investigated using metagenomic sequencing and metabolomic assays. We find that BBIBP-CorV vaccination is accompanied by altered microbiome composition and functional pathways, and the gut microbiome and its functional profiles correlate with the vaccine response. The levels of short-chain fatty acids (SCFAs) are much higher in the high antibody response group compared to the low response group, and several SCFAs display a positive correlation with the antibody response. Our study highlights that the gut microbiome and its function is associated with the BBIBP-CorV vaccine response, providing evidence for further exploration of microbiome modulation to improve COVID-19 vaccine efficacy.


Subject(s)
COVID-19 , Gastrointestinal Microbiome , Humans , Gastrointestinal Microbiome/physiology , COVID-19 Vaccines , Antibody Formation , Fatty Acids, Volatile/metabolism
6.
Front Cell Infect Microbiol ; 12: 832672, 2022.
Article in English | MEDLINE | ID: covidwho-1686456

ABSTRACT

The gastrointestinal tract (GIT) is considered the largest immunological organ, with a diverse gut microbiota, that contributes to combatting pathogens and maintaining human health. Under physiological conditions, the crosstalk between gut microbiota and intestinal epithelial cells (IECs) plays a crucial role in GIT homeostasis. Gut microbiota and derived metabolites can compromise gut barrier integrity by activating some signaling pathways in IECs. Conversely, IECs can separate the gut microbiota from the host immune cells to avoid an excessive immune response and regulate the composition of the gut microbiota by providing an alternative energy source and releasing some molecules, such as hormones and mucus. Infections by various pathogens, such as bacteria, viruses, and parasites, can disturb the diversity of the gut microbiota and influence the structure and metabolism of IECs. However, the interaction between gut microbiota and IECs during infection is still not clear. In this review, we will focus on the existing evidence to elucidate the crosstalk between gut microbiota and IECs during infection and discuss some potential therapeutic methods, including probiotics, fecal microbiota transplantation (FMT), and dietary fiber. Understanding the role of crosstalk during infection may help us to establish novel strategies for prevention and treatment in patients with infectious diseases, such as C. difficile infection, HIV, and COVID-19.


Subject(s)
COVID-19 , Clostridioides difficile , Gastrointestinal Microbiome , Epithelial Cells , Fecal Microbiota Transplantation , Humans , Intestinal Mucosa , SARS-CoV-2
7.
Adv Ther (Weinh) ; 4(10): 2100179, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-1567924

ABSTRACT

[This corrects the article DOI: 10.1002/adtp.202100055.].

8.
Sci Rep ; 11(1): 8062, 2021 04 13.
Article in English | MEDLINE | ID: covidwho-1182868

ABSTRACT

The 2019 Coronavirus Disease (COVID-19) has become an unprecedented public crisis. We retrospectively investigated the clinical data of 197 COVID-19 patients and identified 88 patients as disease aggravation cases. Compared with patients without disease aggravation, the aggravation cases had more comorbidities, including hypertension (25.9%) and diabetes (20.8%), and presented with dyspnoea (23.4%), neutrophilia (31.5%), and lymphocytopenia (46.7%). These patients were more prone to develop organ damage in liver, kidney, and heart (P < 0.05). A multivariable regression analysis showed that advanced age, comorbidities, dyspnea, lymphopenia, and elevated levels of Fbg, CTnI, IL-6, and serum ferritin were significant predictors of disease aggravation. Further, we performed a Kaplan-Meier analysis to evaluate the prognosis of COVID-19 patients, which suggested that 64.9% of the patients had not experienced ICU transfers and survival from the hospital.


Subject(s)
COVID-19/pathology , Adolescent , Adult , Aged , COVID-19/mortality , COVID-19/virology , Child , Comorbidity , Female , Humans , Intensive Care Units , Kaplan-Meier Estimate , Male , Middle Aged , Prognosis , Regression Analysis , Retrospective Studies , Risk Factors , SARS-CoV-2/isolation & purification , Thorax , Tomography, X-Ray Computed , Young Adult
9.
Clin Chim Acta ; 510: 35-46, 2020 Nov.
Article in English | MEDLINE | ID: covidwho-625718

ABSTRACT

The outbreak of Coronavirus Disease-2019 (COVID-19) caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) has threatened health worldwide. As of the end of 2020, there were nearly 10 million confirmed cases and nearly 5 million deaths associated with COVID-19. Rapid and early laboratory diagnosis of COVID-19 is the main focus of treatment and control. Molecular tests are the basis for confirmation of COVID-19, but serological tests for SARS-CoV-2 are widely available and play an increasingly important role in understanding the epidemiology of the virus and in identifying populations at higher risk for infection. Point-of-care tests have the advantage of rapid, accurate, portable, low cost and non-specific device requirements, which provide great help for disease diagnosis and detection. This review will discuss the performance of different laboratory diagnostic tests and platforms, as well as suitable clinical samples for testing, and related biosafety protection. This review shall guide for the diagnosis of COVID-19 caused by SARS-CoV-2.


Subject(s)
Clinical Laboratory Techniques/methods , Coronavirus Infections/diagnosis , Pneumonia, Viral/diagnosis , COVID-19 , COVID-19 Testing , Coronavirus Infections/genetics , Coronavirus Infections/transmission , Coronavirus Infections/virology , Genomics , Humans , Pandemics , Pneumonia, Viral/genetics , Pneumonia, Viral/transmission , Pneumonia, Viral/virology , Virology
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