"Midas Touch": Revealing the Collaborative Mechanism of Nanoconfined Aggregation-Induced Luminescence and Antibody Recognition for AI-Assisted Pathogen Immunochromatographic Detection.

Foodborne pathogen contamination poses a persistent and severe threat to global public health and safety, creating an urgent need for rapid, sensitive, and user-friendly on-site detection technologies. Herein, we report a synergistic strategy, termed "Midas Touch," anchoring tetrakis(4-ethynylphenyl)ethylene (TEE) into NH2-UIO-66 to develop the NH2-UIO-66/TEE (NUT) nanohybrid with high-affinity antibody recognition for AI-assisted immunochromatographic assays (ICA). Molecular dynamics simulations reveal that TEE tended to confined aggregation and generated a strong restriction intramolecular motion (RIM) effect for TEE, which is expected to improve the fluorescent emission. The electron dynamics mechanism reveals that the vibrational relaxation of NUT nanohybrids is accelerated, resulting in amplifying quantum yield of TEE and prolonging fluorescent lifetime. Crucially, isothermal titration calorimetry reveals the NUT-antibody interaction exhibits exceptionally high affinity, driven predominantly by the pronounced hydrophobic effect, complemented by secondary electrostatic/hydrogen-bonding interactions. Therefore, NUT nanohybrids are deployed as immunoprobes to develop NUT-based ICA strips, which achieve an ultralow visual detection limit of sensitive visual detection limit of Salmonella typhimurium with 23-fold lower levels than AuNPs-based strips. The assay also demonstrates excellent specificity, stability, and reliable performance in complex food matrices. Furthermore, a custom-built convolutional neural network model automates result interpretation with 100% classification accuracy. This "Midas Touch" approach provides a fundamental thermodynamic and photophysical framework for designing advanced biointerface materials to create next-generation point-of-care diagnostics.