BackgroundCatecholamines (CAs) are involved in a wide range of physiological and pathological processes in the body and are progressively being used as important biomarkers for a variety of diseases. It is of great significance for accurate quantification of CAs to the diagnosis and treatment of diseases. However, the separation of CAs from complex biological matrices is still a great challenge due to the trace levels of CAs and the limited selectivity of existing pretreatment methods. ResultsIn this work, a dual-recognition imprinted membrane (BA-MIM) was developed to utilize the synergistic action of pH-responsive boron affinity and molecular imprinted cavities for highly selective capture and release of CAs. The prepared BA-MIM possessed remarkable adsorption capacity (maximum capacity, 43.3 mg g−1), desirable surface hydrophilicity (46.2°), superior selectivity (IF = 6.2, α = 14.3), as well as favorable reusability (number of cycles, 6 times). On this basis, an integrated analytical method based on BA-MIM extraction combined with ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) was innovatively developed to highly selective separation, enrichment, and detection of CAs in rat brain tissue. Under the optimum conditions, a low quantitation limits (0.05–0.10 ng mL−1), wide linear range (10–1000 ng mL−1), good linearity (r2 > 0.99), and satisfactory recoveries (88.5%–98.5 %) were obtained for CAs. The proven method was further applied to kidney-yang-deficiency-syndrome (KYDS) group rat model, revealed the intrinsic connection between kidney disease and catecholamine metabolism. SignificanceThis work provides an excellent reference paradigm for the effective construction of dual-recognition functional membrane material to the high-selective analysis of trace targets in complex matrices. Additionally, this integrated analytical strategy demonstrates its efficiency, sustainability, versatility, and convenience, showing remarkable prospect in a variety of applications for biological sample analysis.