A novel assay platform consisting of a microfluidic sliding double-track paper-based chip and a hand-held Raspberry Pi detection system is proposed for determining the albumin-to-creatine ratio (ACR) in human urine. It is a clinically important parameter and can be used for the early detection of related diseases, such as renal insufficiency. In the proposed method, the sliding layer of the microchip is applied and the sample diffuses through two parallel filtration channels to the reaction/detection areas of the microchip to complete the detection reaction, which is a simple method well suited for self-diagnosis of ACR index in human urine. The RGB (red, green, and blue) value intensity signals of the reaction complexes in these two reaction zones are analyzed by a Raspberry Pi computer to derive the ACR value (ALB and CRE concentrations). It is shown that the G + B value intensity signal is linearly related to the ALB and CRE concentrations with the correlation coefficients of R2 = 0.9919 and R2 = 0.9923, respectively. It is additionally shown that the ALB and CRE concentration results determined using the proposed method for 23 urine samples were collected from real suffering chronic kidney disease (CKD) patients are in fine agreement with those acquired operating a traditional high-reliability macroscale method. Overall, for point-of-care (POC) CKD diagnosis and monitoring in clinical applications, the results prove that the proposed method offers a convenient, real time, reliable, and low-spending solution for POC CKD diagnosis.
A microfluidic distillation system is proposed to facilitate the separation and subsequent determination of propionic acid (PA) in foods. The system comprises two main components: (1) a polymethyl methacrylate (PMMA) micro-distillation chip incorporating a micro-evaporator chamber, a sample reservoir, and a serpentine micro-condensation channel; and (2) and a DC-powered distillation module with built-in heating and cooling functions. In the distillation process, homogenized PA sample and de-ionized water are injected into the sample reservoir and micro-evaporator chamber, respectively, and the chip is then mounted on a side of the distillation module. The de-ionized water is heated by the distillation module, and the steam flows from the evaporation chamber to the sample reservoir, where it prompts the formation of PA vapor. The vapor flows through the serpentine microchannel and is condensed under the cooling effects of the distillation module to produce a PA extract solution. A small quantity of the extract is transferred to a macroscale HPLC and photodiode array (PDA) detector system, where the PA concentration is determined using a chromatographic method. The experimental results show that the microfluidic distillation system achieves a distillation (separation) efficiency of around 97% after 15 min. Moreover, in tests performed using 10 commercial baked food samples, the system achieves a limit of detection of 50 mg/L and a limit of quantitation of 96 mg/L, respectively. The practical feasibility of the proposed system is thus confirmed.
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