机器学习辅助和智能手机集成的同质电化学发光生物传感器平台用于样本,以应对各种人类代谢物的检测
Abhishek Kumar1, Dravyansh Jain2, Janhvi Bahuguna2
1MEMS, Microfluidics and Nanoelectronics (MMNE) Lab, Birla Institute of Technology and Science (BITS) Pilani, Hyderabad Campus, Hyderabad 500078, India; Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science (BITS) Pilani, Hyderabad Campus, Hyderabad 500078, India.
Biosensors & bioelectronics
|August 12, 2023
概括
一个具有智能手机集成的新型3D打印电化学发光 (ECL) 系统为检测葡萄糖和乳酸提供了一个便携式解决方案. 这种点照顾设备可以快速诊断和实时监测人类代谢物.
科学领域:
- 分析化学 分析化学
- 生物传感技术的技术
- 临床诊断 临床诊断 临床诊断 临床诊断
背景情况:
- 精确检测葡萄糖和乳酸对于管理糖尿病及其并发症至关重要.
- 传统的电化学发光 (ECL) 方法需要复杂的设备,这限制了它们在护理场所的使用.
- 需要便携式,负担得起的,自动化的诊断工具来实时监测代谢物.
研究的目的:
- 开发一个3D打印的ECL成像系统与智能手机集成,用于便携式代谢物检测.
- 创建一个通用的跨平台应用程序,用于自动化ECL信号分析和实时诊断.
- 评估开发的系统的性能,用于检测葡萄糖和乳酸盐在 point-of-care应用.
主要方法:
- 一个3D打印的单电极ECL生物传感平台的制造.
- 将ECL系统与智能手机集成,通过定制应用程序进行数据采集和分析.
- 对葡萄糖和乳酸盐检测系统的验证,包括对线性,检测极限和量化极限的评估.
- 使用不同方法 (激光诱导石墨烯,丝网印刷,3D打印) 制造的ECL设备的比较研究,以评估电极导电性影响.
主要成果:
- 开发的3D打印ECL系统成功和有效地检测出葡萄糖和乳酸盐.
- 线性检测范围是从0.1mM到1mM的葡萄糖和0.1mM到4mM的乳酸.
- 葡萄糖的检测极限 (LoD) 为0.04mM,乳酸的检测极限为0.1mM,量化极限 (LoQ) 分别为0.142mM和0.342mM.
- 发现ECL信号强度在不同的制造方法中独立于电极电导率.
结论:
- 微型,智能手机集成的3D打印ECL平台提供了一个便携式,经济实惠的,自动化解决方案,用于点的护理代谢物检测.
- 该系统显示了实时监测和快速诊断的潜力,适用于各种人类代谢物.
- 开发的技术对未来诊断和疾病管理的临床应用具有前景.
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