###### Abstract  
Diabetic nephropathy (DN) refers to kidney damage caused by diabetes and is one of the major microvascular complications of diabetes. This disease has a certain degree of concealment in the early stage, with clinical symptoms appearing later and a higher mortality rate. Therefore, the detection of early biomarkers for DN is of great importance in reducing kidney function damage. The common biomarkers for DN mainly include glomerular and tubular lesion markers. At present, clinical diagnosis often uses a combination of multiple indicators and symptoms, and the development of a simple, efficient, and sensitive multi-marker detection platform is particularly important for the early diagnosis of DN. In recent years, with the vigorous development of various biomimetic molecular recognition technologies, biomimetic recognition biosensors (BRBS) have many advantages, such as easy preparation, low cost, high stability, and repeatability under harsh environmental conditions, and have great application potential in the analysis of DN biomarkers. This article reviews the research progress of molecularly imprinted polymers (MIPs) construction technology and aptamers assembly technology developed in the field of biomimetic sensor research in recent years, as well as the detection of DN biomarkers based on BRBS, and prospects for their development. b pacs: 2023  
Dabetic nephropathy (DN) refers to kidney damage caused by diabetes, which is one of the main microvascular complications of diabetes. High blood sugar-induced kidney damage leads to a decrease in the glomerular filtration rate (GFR) and the appearance of symptoms such as proteinuria. The disease has a high mortality rate [1]. Currently, DN has seriously threatened human health and the development of socio-economic progress [2]. According to the classification of DN by [PERSON] from Denmark, stage I-II lacks obvious clinical manifestations, stage III begins to show trace albuminuria and GFR may be normal, and it is not until stage IV that there is a persistent and progressively worsening amount of albuminuria accompanied by a decline in GFR, which is difficult to reverse, eventually leading to renal failure. Therefore, early DN is reversible, and if diagnosed and treated with early intervention, the development of nephropathy can be halted or reversed. Hence, early screening and diagnosis are particularly important for DN. The screening of DN mainly follows the standards of the American Diabetes Association (ADA), including albuminuria and GFR. However, a large number of clinical observations have found that 20-50% of chronic kidney disease patients have no albuminuria, and the number of such patients is on the rise [3]. This means that these DN patients without albuminuria will be missed, and will not receive timely diagnosis and treatment. Therefore, it is of great practical significance to find highly sensitive and specific early biomarkers for DN and establish accurate and convenient detection methods. So far, several analytical methods have been developed for the detection of biomarkers (urinary albumin, creatinine, cystatin C, homocysteine, vascular endothelial growth factor, epidermal growth factor receptor, mRNA-21, ceruloplasmin, platelet-derived growth factor, etc.) for DN [4; 5; 6; 7], including ultra-high performance liquid chromatography (UHPLC), capillary electrophoresis (CE), liquid chromatography-tandem mass spectrometry (LC-MS), radioimmunoassay (RIA), enzyme-linked immunosorbent assay (ELISA), immunoreactivity (IRMA), and electrochemiluminescence immunofluorescence immunoassay (ECLI). Although the results of these methods are reliable and accurate, they have many disadvantages, such as large sample sizes, complex instruments, expensive antibodies, long incubation time, and complicated protocols. These limitations restrict their application in real-time detection [8; 9]. Therefore, the introduction of rapid, universal, powerful, and high-throughput sensing technologies for early detection of DN has significant social value.