Biosensors-Basel
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2023
·Vol. 13
·期 2
·180
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IF 5.4
Sheng Li,Wenlong Guo,Minmin Xiao,Yulin Chen,Xinyi Luo,Wenfei Xu,Jianhua Zhou,Jiasi Wang
Rapid and sensitive detection of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential for early diagnosis and effective treatment. Nucleic acid testing has been considered the gold standard method for the diagnosis of COVID-19 for its high sensitivity and specificity. However, the polymerase chain reaction (PCR)-based method in the central lab requires expensive equipment and well-trained personnel, which makes it difficult to be used in resource-limited settings. It highlights the need for a sensitive and simple assay that allows potential patients to detect SARS-CoV-2 by themselves. Here, we developed an electricity-free self-testing system based on reverse transcription loop-mediated isothermal amplification (RT-LAMP) that allows for rapid and accurate detection of SARS-CoV-2. Our system employs a heating bag as the heat source, and a 3D-printed box filled with phase change material (PCM) that successfully regulates the temperature for the RT-LAMP. The colorimetric method could be completed in 40 min and the results could be read out by the naked eye. A ratiometric measurement for exact readout was also incorporated to improve the detection accuracy of the system. This self-testing system is a promising tool for point-of-care testing (POCT) that enables rapid and sensitive diagnosis of SARS-CoV-2 in the real world and will improve the current COVID-19 screening efforts for control and mitigation of the pandemic.Keywords:SARS-CoV-2;self-testing;reverse transcription loop-mediated isothermal amplification
研究领域:
病毒学
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医学诊断
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分子生物学
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DOI
PubMed
高影响因子
BMC PUBLIC HEALTH
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2021
·Vol. 21
·期 1
·2001
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IF 3.295
Mao Zijun,Zou Qi,Yao Hong,Wu Jingyi
Background As COVID-19 continues to spread globally, traditional emergency management measures are facing many practical limitations. The application of big data analysis technology provides an opportunity for local governments to conduct the COVID-19 epidemic emergency management more scientifically. The present study, based on emergency management lifecycle theory, includes a comprehensive analysis of the application framework of China’s SARS epidemic emergency management lacked the support of big data technology in 2003. In contrast, this study first proposes a more agile and efficient application framework, supported by big data technology, for the COVID-19 epidemic emergency management and then analyses the differences between the two frameworks. Methods This study takes Hainan Province, China as its case study by using a file content analysis and semistructured interviews to systematically comprehend the strategy and mechanism of Hainan’s application of big data technology in its COVID-19 epidemic emergency management. Results Hainan Province adopted big data technology during the four stages, i.e., migration, preparedness, response, and recovery, of its COVID-19 epidemic emergency management. Hainan Province developed advanced big data management mechanisms and technologies for practical epidemic emergency management, thereby verifying the feasibility and value of the big data technology application framework we propose. Conclusions This study provides empirical evidence for certain aspects of the theory, mechanism, and technology for local governments in different countries and regions to apply, in a precise, agile, and evidence-based manner, big data technology in their formulations of comprehensive COVID-19 epidemic emergency management strategies.
研究领域:
公共卫生
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应急管理体系
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信息科学
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流行病学
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数据驱动决策
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DOI
高影响因子
International Insolvency Review
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2021
·Vol. 30
·期 3
·329-343
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IF 0.848
Daniel A. Austin,Yu Huan
Business bankruptcy in China is governed by the Enterprise Bankruptcy Law (EBL), a national insolvency code enacted in 2007. The EBL contains provisions for business liquidation, reorganization, and compromise of debt. Although adjustment of debt through bankruptcy is far less common in China than in western nations, Chinese courts have established a body of bankruptcy procedures and judicial interpretations that give insolvency in China a measure of predictability and effectiveness. Notwithstanding the EBL provisions, soon after the onset of the pandemic, PRC courts began to adopt ad-hoc rules and guidelines in bankruptcy cases for businesses whose financial woes were caused or exacerbated by coronavirus, or for enterprises that produced medical equipment and supplies to help prevent and control the virus. This paper examines these court measures, explores their political and judicial context, and demonstrates how they produced bankruptcy outcomes that were often significantly different than what would have resulted if the EBL had been applied based on pre-COVID-19 EBL practices.
研究领域:
法学
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经济法学
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破产法
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司法制度
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公共政策
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高影响因子
BIOSENSORS & BIOELECTRONICS
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2021
·
IF 10.618
Jiahao Li,Ding Wu,Yi Yu,Tingxian Li,Kun Li,Meng-Meng Xiao,Yirong Li,Zhi-Yong Zhang,Guo-Jun Zhang
SARS-CoV-2 RNA is identified as a pivotal player to bolster energizing zones of COVID-19 detection. Herein, we develop a rapid and unamplified nanosensing platform for detection of SARS-CoV-2 RNA in human throat swab specimens. A gold nanoparticle (AuNP)-decorated graphene field-effect transistor (G-FET) sensor was fabricated, after which complementary phosphorodiamidate morpholino oligos (PMO) probe was immobilized on the AuNP surface. This sensor allowed for highly sensitive testing of SARS-CoV-2 RdRp as PMO does not have charges, leading to low background signal. Not only did the method present a low limit of detection in PBS (0.37 fM), throat swab (2.29 fM), and serum (3.99 fM), but also it achieved a rapid response to COVID-19 patients’ samples within 2 min. The developed nanosensor was capable of analyzing RNA extracts from 30 real clinical samples. The results show that the sensor could differentiate the healthy people from infected people, which are in high agreement with RT-PCR results (Kappa index = 0.92). Furthermore, a well-defined distinction between SARS-CoV-2 RdRp and SARS-CoV RdRp was also made. Therefore, we believe that this work provides a satisfactory, attractive option for COVID-19 diagnosis.
研究领域:
生物医学工程
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纳米技术
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病毒学
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分子诊断
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DOI
PubMed
高影响因子
BMC INFECTIOUS DISEASES
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2022
·Vol. 22
·期 1
·1-8
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IF 3.667
An Qingyu,Wu Jun,Bai Jin jian,Li Xiaofeng
Objectives To forecast the development trend of current outbreak in Dalian, mainly to predict turning points of COVID-19 outbreak in Dalian, Liaoning province, China, the results can be used to provide a scientific reference for timely adjustment of prevention and control strategies. Methods During the outbreak, Bayesian framework was used to calculated the time-dependent reproduction number ( \({R_{t}}\) ), and then above acquired \({R_{t}}\) and exponential trend equation were used to establish the prediction model, through the model, predict the \({R_{t}}\) value of following data and know when \({R_{t}}\) smaller than 1. Results From July 22 to August 5, 2020, and from March 14 to April 2, 2022, 92 and 632 confirmed cases and asymptomatic infected cases of COVID-19 were reported (324 males and 400 females) in Dalian. The R square for exponential trend equation were 0.982 and 0.980, respectively which fit the \({R_{t}}\) with illness onset between July 19 to July 28, 2020 and between March 5 to March 17, 2022. According to the result of prediction, under the current strength of prevention and control, the \({R_{t}}\) of COVID-19 will drop below 1 till August 2, 2020 and March 26, 2022, respectively in Dalian, one day earlier or later than the actual date. That is, the turning point of the COVID-19 outbreak in Dalian, Liaoning province, China will occur on August 2, 2020 and March 26, 2022. Conclusions Using time-dependent reproduction number values to predict turning points of COVID-19 outbreak in Dalian, Liaoning province, China was effective and reliable on the whole, and the results can be used to establish a sensitive early warning mechanism to guide the timely adjustment of COVID-19 prevention and control strategies.
研究领域:
流行病学
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公共卫生
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传染病学
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生物统计学
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预测模型
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疫情防控
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DOI
高影响因子
ANALYTICAL CHEMISTRY
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2022
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IF 8.008
Jia Xu,Xiaoqin Tao,Xiaoxuan Liu,Li Yang
We develop a novel noninvasive wearable biosensor to simultaneously assay multiple key biomarkers in human tears. The sensor is uniquely designed as a convenient-to-use eye patch that can be easily and comfortably fit under eyes. Different sensing regions on the eye patch are modified with specific chromogenic reagents to selectively determine the hydrogen ion (pH), protein, ascorbic acid, and glucose in tears. The assay takes only one drop of tear (∼20 μL) and a 30 s response time. The resulting color signals from each sensing region on the eye patch are captured and analyzed using a smartphone, and a cloud model based on the internet of things concept is recommended, which can extend the application of the eye patch biosensors in point-of-care testing and health monitoring, especially during the pandemic. Tear detection of the human subjects is performed using the proposed method, and the results display good correlation to parallel measurements using assay kits. The results show the great potential and versatility of the proposed eye patch biosensor for noninvasive determination of diverse tear biomarkers, facilitating the widespread application of the tear-based noninvasive wearable biosensor in emerging personal health care and clinical monitoring fields.
研究领域:
生物医学工程
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传感器
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即时检测
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医疗技术
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生物传感器
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DOI
PubMed
高影响因子
危险品化学品经营许可证（带存储）