Ratiometric, 3D Fluorescence Spectrum with Abundant Information for Tetracyclines Discrimination via Dual...

Tetracyclines are widely used in bacteria infection treatment, while the subtle chemical differences between tetracyclines make it a challenge to accurate discrimination via biosensors. A 3D fluorescence spectrum can provide fingerprint structure information for many analytes, but a single probe-based method is prone to information overlap. Here, aptamers are first reported to obtain abundant information in a ratiometric, 3D fluorescence spectrum for deep learning to accurately discriminate tetracyclines. So, each tetracycline can be related to a distinct, ratiometric, 3D fluorescence spectrum via the strategy of dual biomolecules recognition. One artificial neural network model can efficiently treat this fingerprint information, and the qualitative/quantitative analysis of tetracyclines is successfully realized. The proposed dual biomolecule recognition strategy has been demonstrated to show a higher accuracy than a conventional single probe method. So, the ratiometric 3D fluorescence spectrum can enrich the fingerprint information for deep learning, providing a new strategy for 3D fluorescence-based analytes discrimination.