JOURNAL OF LIGHT INDUSTRY

CN 41-1437/TS  ISSN 2096-1553

生物标志物检测方法的研究进展

武丰龙,崔艳英,张志锋,王丹丹

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武丰龙, 崔艳英, 张志锋, 等. 生物标志物检测方法的研究进展[J]. 轻工学报, 2022, 37(5): 50-60. doi: 10.12187/2022.05.006
引用本文:武丰龙, 崔艳英, 张志锋, 等. 生物标志物检测方法的研究进展[J]. 轻工学报, 2022, 37(5): 50-60.doi:10.12187/2022.05.006
WU Fenglong, CUI Yanying, ZHANG Zhifeng and et al. Research progress of methods for biomarker detection[J]. Journal of Light Industry, 2022, 37(5): 50-60. doi: 10.12187/2022.05.006
Citation:WU Fenglong, CUI Yanying, ZHANG Zhifeng and et al. Research progress of methods for biomarker detection[J]. Journal of Light Industry, 2022, 37(5): 50-60.doi:10.12187/2022.05.006

生物标志物检测方法的研究进展

    作者简介:武丰龙(1976-),男,河南省南阳市人,18新利直播 讲师,主要研究方向为智能信息检测与信息计算。E-mail:wufenglong1112@163.com;
  • 基金项目:国家自然科学基金面上基金项目(61975187)

  • 中图分类号:TS207.4;R318

Research progress of methods for biomarker detection

  • Received Date:2021-06-11
    Accepted Date:2022-01-20

    CLC number:TS207.4;R318

  • 摘要:综述了基于遗传物质(RNA和DNA)、免疫学(抗原/抗体)及结合微芯片技术的生物标志物检测方法的应用研究进展,指出:基于遗传物质的检测方法直接作用于靶标物质,准确性和灵敏度高,但其检测步骤繁多,对检测环境要求高;基于免疫学的检测方法操作简单、便携性高、能实现即时检测但准确性稍低,适用于快速、大规模的病毒筛查;结合微芯片技术的检测方法更加多元化,并能在短时间内实现靶标物质的检测,精确性、自动化程度得到提高,在病毒筛查、疾病诊断等方面表现出巨大的发展潜力。未来生物标志物检测技术可就优化免疫催化反应物、加大核酸提取物纯化程度、提高检测设备自动化程度、构建多重检测系统、实现检测设备微型化及检测信息可视化等方面开展进一步研究,以提高检测准确性、设备便携性,从而实现该技术的持续发展。
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  • 收稿日期:2021-06-11
  • 修回日期:2022-01-20
    通讯作者:陈斌, bchen63@163.com
    • 1.

      沈阳化工大学材料科学与工程学院 沈阳 110142

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    武丰龙, 崔艳英, 张志锋, 等. 生物标志物检测方法的研究进展[J]. 轻工学报, 2022, 37(5): 50-60. doi: 10.12187/2022.05.006
    引用本文:武丰龙, 崔艳英, 张志锋, 等. 生物标志物检测方法的研究进展[J]. 轻工学报, 2022, 37(5): 50-60.doi:10.12187/2022.05.006
    WU Fenglong, CUI Yanying, ZHANG Zhifeng and et al. Research progress of methods for biomarker detection[J]. Journal of Light Industry, 2022, 37(5): 50-60. doi: 10.12187/2022.05.006
    Citation:WU Fenglong, CUI Yanying, ZHANG Zhifeng and et al. Research progress of methods for biomarker detection[J]. Journal of Light Industry, 2022, 37(5): 50-60.doi:10.12187/2022.05.006

    生物标志物检测方法的研究进展

      作者简介:武丰龙(1976-),男,河南省南阳市人,18新利直播 讲师,主要研究方向为智能信息检测与信息计算。E-mail:wufenglong1112@163.com
    • 1. 18新利直播 软件学院, 河南 郑州 450001;
    • 2. 18新利直播 计算机与通信工程学院, 河南 郑州 450001
    基金项目:国家自然科学基金面上基金项目(61975187)

    摘要:综述了基于遗传物质(RNA和DNA)、免疫学(抗原/抗体)及结合微芯片技术的生物标志物检测方法的应用研究进展,指出:基于遗传物质的检测方法直接作用于靶标物质,准确性和灵敏度高,但其检测步骤繁多,对检测环境要求高;基于免疫学的检测方法操作简单、便携性高、能实现即时检测但准确性稍低,适用于快速、大规模的病毒筛查;结合微芯片技术的检测方法更加多元化,并能在短时间内实现靶标物质的检测,精确性、自动化程度得到提高,在病毒筛查、疾病诊断等方面表现出巨大的发展潜力。未来生物标志物检测技术可就优化免疫催化反应物、加大核酸提取物纯化程度、提高检测设备自动化程度、构建多重检测系统、实现检测设备微型化及检测信息可视化等方面开展进一步研究,以提高检测准确性、设备便携性,从而实现该技术的持续发展。

    English Abstract

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