生牛乳中乳铁蛋白的蛋白质芯片检测平台的评价研究
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(中国疾病预防控制中心营养与健康所,北京 100050)

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殷继永 男 副研究员 研究方向为营养与食品卫生学E-mail:jyyin7579@163.com通信作者:霍军生 男 研究员 研究方向为营养与食品卫生学E-mail:jshuo@263.net.cn

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中国疾病预防控制中心青年科研基金(2015A202)


The evaluation of protein microarray platform for lactoferrin detection in raw milk
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(National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050,China)

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    摘要:

    目的 对本研究前期建立的用于乳铁蛋白的蛋白质芯片检测平台进行评价。方法 使用3份生牛乳样品,批内重复8次检测,计算批内精密度;另对3份生牛乳分别重复8个批次检测,计算批间精密度。对高浓度标准品稀释3个浓度后,进行稀释回收率试验;另对3个浓度基础液分别进行加标回收率试验;取10份生牛乳样品,分别用蛋白质芯片检测平台与商用酶联免疫吸附测定(ELISA)试剂盒进行检测并对结果进行方法学比较。结果 用于生牛乳中乳铁蛋白的蛋白质芯片检测平台的批内精密度在9.79%~15.90%之间,批间精密度在11.63%~23.38%之间;稀释回收率在79.8%~129.7%之间,加标回收率在105.7%~133.9%之间;经比较,两种方法的相关系数r=0.825 2,差异有统计学意义(t=4.132,P<0.05),配对比较t检验结果显示两种方法差异无统计学意义(t=1.282,P>0.05)。结论 本研究建立的用于乳铁蛋白的蛋白质芯片检测平台能够满足实验室检测需要,尚有操作偏倚需进一步优化。

    Abstract:

    Objective To evaluate the protein microarray platform that previously established for lactoferrin detection in raw milk. Methods Triplet raw milk samples were used to implement within-run precision of 8 repeats and other triplet raw milk samples were used to implement between-run precision of 8 batches. The high concentration standard was consecutively diluted for recovery test. Three concentrations of spiked samples were used for recovery. Ten raw milk samples were detected by protein chip platform and commercial ELISA Kit, respectively. Results The within-run precision and between-run precision were 9.79%-15.90% and 11.63%-23.38%, respectively. The dilution recovery and recovery were 79.8%-129.7% and 105.7%-133.9%, respectively. The relevant coefficient of the two detection method was 0.825 2, the difference was significant (t=4.132, P<0.05), but the result of paired t test showed that there was no difference between the two method (t=1.282, P>0.05). Conclusion The protein chip platform could satisfy the requirement of laboratory test, and its operation error need to be further optimized.

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殷继永,霍军生,马欣欣,孙静,黄建.生牛乳中乳铁蛋白的蛋白质芯片检测平台的评价研究[J].中国食品卫生杂志,2017,29(6):666-670.

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  • 收稿日期:2017-10-12
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  • 在线发布日期: 2018-01-29
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