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.

With the growing concern over the adverse effects of environmental pollution on human health, the combination of environmentally friendly and nontoxic biomaterials with metal oxide semiconductor materials for electronic devices has emerged as a prominent trend in current research. In this study, we utilized 150 mg apple biotemplates to assist in the hydrothermal synthesis of ZnO nanospheres. It successfully achieved high sensitivity for detecting 35 and 350 ppb NO₂ at room temperature, with responses of 13.74 and 132.44%, respectively. Simultaneously, the 5-cycle repeatability and multiple-gas selectivity exhibited significant improvements. The ZnO nanospheres demonstrated enhanced sensing performance compared to pure ZnO nanorods, which is attributed to the following mechanisms: reason I, the modified surface morphology increasing the surface-to-volume ratio; reason II, an increase in oxygen vacancies, leading to reduced crystallinity and a higher electron concentration; reason III, incorporation of carbon elements on the nanostructure surface to increase active sites. The novel gas sensor assisted by the apple pectin biotemplate offers a promising solution for NO₂ gas detection, featuring low operating temperatures, low concentrations, and high response sensitivity.