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自动化 ELISA 芯片法用于检测抗 SARS-CoV-2 抗体。

Automated ELISA On-Chip for the Detection of Anti-SARS-CoV-2 Antibodies.

机构信息

Delee Corp., Mountain View, CA 94041, USA.

Escuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Monterrey 64849, NL, Mexico.

出版信息

Sensors (Basel). 2021 Oct 13;21(20):6785. doi: 10.3390/s21206785.

Abstract

The COVID-19 pandemic has been the most critical public health issue in modern history due to its highly infectious and deathly potential, and the limited access to massive, low-cost, and reliable testing has significantly worsened the crisis. The recovery and the vaccination of millions of people against COVID-19 have made serological tests highly relevant to identify the presence and levels of SARS-CoV-2 antibodies. Due to its advantages, microfluidic-based technologies represent an attractive alternative to the conventional testing methodologies used for these purposes. In this work, we described the development of an automated ELISA on-chip capable of detecting anti-SARS-CoV-2 antibodies in serum samples from COVID-19 patients and vaccinated individuals. The colorimetric reactions were analyzed with a microplate reader. No statistically significant differences were observed when comparing the results of our automated ELISA on-chip against the ones obtained from a traditional ELISA on a microplate. Moreover, we demonstrated that it is possible to carry out the analysis of the colorimetric reaction by performing basic image analysis of photos taken with a smartphone, which constitutes a useful alternative when lacking specialized equipment or a laboratory setting. Our automated ELISA on-chip has the potential to be used in a clinical setting and mitigates some of the burden caused by testing deficiencies.

摘要

由于其高度传染性和致命性潜力,COVID-19 大流行是现代历史上最严重的公共卫生问题,而大规模、低成本、可靠检测的有限获取使得危机更加恶化。对数百万人进行 COVID-19 的康复和接种使得血清学检测对于确定 SARS-CoV-2 抗体的存在和水平变得非常重要。由于其优势,基于微流控的技术代表了用于这些目的的传统检测方法的有吸引力的替代方法。在这项工作中,我们描述了一种自动化 ELISA 芯片的开发,该芯片能够检测来自 COVID-19 患者和接种个体的血清样本中的抗 SARS-CoV-2 抗体。通过微孔板读取器分析比色反应。当将我们的自动化 ELISA 芯片的结果与在微孔板上进行的传统 ELISA 的结果进行比较时,没有观察到统计学上的显著差异。此外,我们证明可以通过对使用智能手机拍摄的照片进行基本图像分析来进行比色反应的分析,这在缺乏专业设备或实验室环境时是一种有用的替代方法。我们的自动化 ELISA 芯片有可能在临床环境中使用,并减轻测试不足带来的一些负担。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8730/8539637/d4a4bbd5a6c5/sensors-21-06785-g001.jpg

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