Institute of Environmental Medicine, Tongji Medical College, Huazhong University of Science and Technology, 430030 Wuhan, PR China.
Biosens Bioelectron. 2011 Nov 15;29(1):115-8. doi: 10.1016/j.bios.2011.08.003. Epub 2011 Aug 6.
Detection of analytes in complex biological samples, such as milk and blood, normally requires sample pretreatment. These pretreatment regimes reduce assay throughput and increase testing costs. Technologies that make it possible to eliminate sample pretreatment are of great industrial interest. Here we report the development of a dual-signal flow injected analysis device which eliminates the need for sample pretreatment. The device employs thermal traducers to measure the signal from an enzyme and a reference column. This makes it possible to independently monitor and correct for non-specifically generated heat, thereby eliminating the need for sample pretreatment. The ability of the dual-signal device to determine urea and lactate in milk samples without any prior treatment was evaluated. The spiked milk samples, the urea assay had a linear range from 0.1 to 50mM (R=0.996), and the lactate assay had a linear range from 0.025 to 5.0mM (R=0.9998). The linear regression values for urea and lactate for 0.5%, 1.5% and 3.0% fat milk were at least 0.990. The dual-signal design improves assay reproducibility, accuracy and sensitivity. Addition benefits are shorter assay times and lowers costs, as well as reducing equipment and training requirements. The potential application of the technology for multi-analyte analysis in point of care and decentralized diagnostic testing in healthcare, agriculture and environmental areas is discussed.
在复杂的生物样本(如牛奶和血液)中分析物的检测通常需要样品预处理。这些预处理方案降低了检测通量并增加了检测成本。能够消除样品预处理的技术具有巨大的工业价值。在这里,我们报告了一种双信号流动注射分析装置的开发,该装置消除了对样品预处理的需求。该装置采用热传感器来测量酶和参比柱的信号。这使得能够独立监测和校正非特异性产生的热,从而消除了对样品预处理的需求。评估了该双信号装置在无需任何预处理的情况下测定牛奶样品中尿素和乳酸的能力。对于加标牛奶样品,尿素测定的线性范围为 0.1 至 50mM(R=0.996),乳酸测定的线性范围为 0.025 至 5.0mM(R=0.9998)。0.5%、1.5%和 3.0%脂肪牛奶的尿素和乳酸的线性回归值至少为 0.990。双信号设计提高了测定的重现性、准确性和灵敏度。此外,还具有缩短测定时间、降低成本以及减少设备和培训需求的优点。讨论了该技术在医疗保健、农业和环境领域中用于即时护理和分散式诊断测试的多分析物分析的潜在应用。