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1.
Lab Chip ; 22(18): 3436-3452, 2022 09 13.
Article in English | MEDLINE | ID: covidwho-1991687

ABSTRACT

The pandemic of coronavirus disease 2019 (COVID-19), due to the novel coronavirus (SARS-CoV-2), has created an unprecedented threat to the global health system, especially in resource-limited areas. This challenge shines a spotlight on the urgent need for a point-of-care (POC) quantitative real-time PCR (qPCR) test for sensitive and rapid diagnosis of viral infections. In a POC system, a closed, single-use, microfluidic cartridge is commonly utilized for integration of nucleic acid preparation, PCR amplification and florescence detection. But, most current cartridge systems often involve complicated nucleic acid extraction via active pumping that relies on cumbersome external hardware, causing increases in system complexity and cost. In this work, we demonstrate a gravity-driven cartridge design for an integrated viral RNA/DNA diagnostic test that does not require auxiliary hardware for fluid pumping due to adopted extraction-free amplification. This microfluidic cartridge only contains two reaction chambers for nucleic acid lysis and amplification respectively, enabling a fast qPCR test in less than 30 min. This gravity-driven pumping strategy can help simplify and minimize the microfluidic cartridge, thus enabling high-throughput (up to 12 test cartridges per test) molecular detection via a small cartridge readout system. Thus, this work addresses the scalability limitation of POC molecular testing and can be run in any settings. We verified the analytical sensitivity and specificity of the cartridge testing for respiratory pathogens and sexually transmitted diseases using SARS-CoV-2, influenza A/B RNA samples, and human papillomavirus 16/18 DNA samples. Our cartridge system exhibited a comparable detection performance to the current gold standard qPCR instrument ABI 7500. Moreover, our system showed very high diagnostic accuracy for viral RNA/DNA detection that was well validated by ROC curve analysis. The sample-to-answer molecular testing system reported in this work has the advantages of simplicity, rapidity, and low cost, making it highly promising for prevention and control of infectious diseases in poor-resource areas.


Subject(s)
COVID-19 , Influenza, Human , COVID-19/diagnosis , COVID-19 Testing , DNA, Viral/genetics , Human papillomavirus 16/genetics , Humans , Influenza, Human/diagnosis , Microfluidics , Nucleic Acid Amplification Techniques , RNA, Viral/analysis , RNA, Viral/genetics , Real-Time Polymerase Chain Reaction , SARS-CoV-2/genetics , Sensitivity and Specificity
2.
PLoS One ; 16(3): e0248957, 2021.
Article in English | MEDLINE | ID: covidwho-1146198

ABSTRACT

The characteristics and evolution of pulmonary fibrosis in patients with coronavirus disease 2019 (COVID-19) have not been adequately studied. AI-assisted chest high-resolution computed tomography (HRCT) was used to investigate the proportion of COVID-19 patients with pulmonary fibrosis, the relationship between the degree of fibrosis and the clinical classification of COVID-19, the characteristics of and risk factors for pulmonary fibrosis, and the evolution of pulmonary fibrosis after discharge. The incidence of pulmonary fibrosis in patients with severe or critical COVID-19 was significantly higher than that in patients with moderate COVID-19. There were significant differences in the degree of pulmonary inflammation and the extent of the affected area among patients with mild, moderate and severe pulmonary fibrosis. The IL-6 level in the acute stage and albumin level were independent risk factors for pulmonary fibrosis. Ground-glass opacities, linear opacities, interlobular septal thickening, reticulation, honeycombing, bronchiectasis and the extent of the affected area were significantly improved 30, 60 and 90 days after discharge compared with at discharge. The more severe the clinical classification of COVID-19, the more severe the residual pulmonary fibrosis was; however, in most patients, pulmonary fibrosis was improved or even resolved within 90 days after discharge.


Subject(s)
Artificial Intelligence , COVID-19/pathology , Pulmonary Fibrosis/diagnosis , Thorax/diagnostic imaging , COVID-19/complications , COVID-19/virology , Female , Humans , Image Processing, Computer-Assisted , Interleukin-6/metabolism , Male , Middle Aged , Patient Discharge , Pulmonary Fibrosis/etiology , Risk Factors , SARS-CoV-2/isolation & purification , Severity of Illness Index , Tomography, X-Ray Computed
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