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利用蛋白质-肽杂交微阵列进行新型冠状病毒肺炎的时间分辨诊断和预后评估

Utilizing Protein-Peptide Hybrid Microarray for Time-Resolved Diagnosis and Prognosis of COVID-19.

作者信息

Zheng Peiyan, Liao Baolin, Yang Jiao, Cheng Hu, Cheng Zhangkai J, Huang Huimin, Luo Wenting, Sun Yiyue, Zhu Qiang, Deng Yi, Yang Lan, Zhou Yuxi, Wu Wenya, Wu Shanhui, Cai Weiping, Li Yueping, Mo Xiaoneng, Tan Xinghua, Li Linghua, Ma Hongwei, Sun Baoqing

机构信息

Department of Clinical Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China.

Guangzhou Institute of Clinical Medicine of Infectious Diseases, Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou 510440, China.

出版信息

Microorganisms. 2023 Sep 28;11(10):2436. doi: 10.3390/microorganisms11102436.

Abstract

The COVID-19 pandemic has highlighted the urgent need for accurate, rapid, and cost-effective diagnostic methods to identify and track the disease. Traditional diagnostic methods, such as PCR and serological assays, have limitations in terms of sensitivity, specificity, and timeliness. To investigate the potential of using protein-peptide hybrid microarray (PPHM) technology to track the dynamic changes of antibodies in the serum of COVID-19 patients and evaluate the prognosis of patients over time. A discovery cohort of 20 patients with COVID-19 was assembled, and PPHM technology was used to track the dynamic changes of antibodies in the serum of these patients. The results were analyzed to classify the patients into different disease severity groups, and to predict the disease progression and prognosis of the patients. PPHM technology was found to be highly effective in detecting the dynamic changes of antibodies in the serum of COVID-19 patients. Four polypeptide antibodies were found to be particularly useful for reflecting the actual status of the patient's recovery process and for accurately predicting the disease progression and prognosis of the patients. The findings of this study emphasize the multi-dimensional space of peptides to analyze the high-volume signals in the serum samples of COVID-19 patients and monitor the prognosis of patients over time. PPHM technology has the potential to be a powerful tool for tracking the dynamic changes of antibodies in the serum of COVID-19 patients and for improving the diagnosis and prognosis of the disease.

摘要

新冠疫情凸显了对准确、快速且经济高效的诊断方法的迫切需求,以识别和追踪该疾病。传统诊断方法,如聚合酶链反应(PCR)和血清学检测,在敏感性、特异性和及时性方面存在局限性。为了研究使用蛋白质 - 肽杂交微阵列(PPHM)技术追踪新冠患者血清中抗体动态变化并评估患者随时间预后的潜力。组建了一个由20名新冠患者组成的发现队列,并使用PPHM技术追踪这些患者血清中抗体的动态变化。对结果进行分析,将患者分类为不同疾病严重程度组,并预测患者的疾病进展和预后。发现PPHM技术在检测新冠患者血清中抗体的动态变化方面非常有效。发现四种多肽抗体对于反映患者恢复过程的实际状况以及准确预测患者的疾病进展和预后特别有用。本研究结果强调了肽的多维空间,以分析新冠患者血清样本中的大量信号并随时间监测患者的预后。PPHM技术有潜力成为追踪新冠患者血清中抗体动态变化以及改善该疾病诊断和预后的有力工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e623/10609375/e399ef2a8be6/microorganisms-11-02436-g003.jpg

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