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The research on pharmacology usually focuses on the structure-activity relationships of drugs, such as antibiotics, to enhance their activity, but often ignores their optical properties. However, investigating the photophysical properties of drugs is of great significance because they could be used to in situ visualize their positions and help us to understand their working metabolism. In this work, we identified a class of commercialized antibiotics, such as levofloxacin, norfloxacin, and moxifloxacin (MXF) hydrochloride, featuring the unique aggregation-induced emission (AIE) characteristics. By taking advantage of their AIE feature, antibiotic metabolism in cells could be in situ visualized, which clearly shows that the luminescent aggregates accumulate in the lysosomes. Moreover, after a structure-activity relationship study, we found an ideal site of MXF to be modified with a triphenylphosphonium and an antibiotic derivative MXF-P was prepared, which is able to specifically differentiate bacterial species after only 10 min of treatment. Moreover, MXF-P shows highly effective broad-spectrum antibacterial activity, excellent therapeutic effects and biosafety for S. aureus-infected wound recovery. Thus, this work not only discovers the multifunctionalities of the antibiotics but also provides a feasible strategy to make the commercialized drugs more powerful.

Radix Angelicae Sinensis, known as Danggui in China, is an effective and wide applied material in Traditional Chinese Medicine (TCM) and it is used in more than 80 composite formulae. Danggui from Minxian County, Gansu Province is the best in quality. To rapidly and nondestructively discriminate Danggui from the authentic region of origin from that from an unauthentic region, an electronic nose coupled with multivariate statistical analyses was developed. Two different feature extraction methods were used to ensure the authentic region and unauthentic region of Danggui origin could be discriminated. One feature extraction method is to capture the average value of the maximum response of the electronic nose sensors (feature extraction method 1). The other one is to combine the maximum response of the sensors with their inter-ratios (feature extraction method 2). Multivariate statistical analyses, including principal component analysis (PCA), soft independent modeling of class analogy (SIMCA), and hierarchical clustering analysis (HCA) were employed. Nineteen samples were analyzed by PCA, SIMCA and HCA. Then the remaining samples (GZM1, SH) were projected onto the SIMCA model to validate the models. The results indicated that, in the use of feature extraction method 2, Danggui from Yunnan Province and Danggui from Gansu Province could be successfully discriminated using the electronic nose coupled with PCA, SIMCA and HCA, which suggested that the electronic-nose system could be used as a simple and rapid technique for the discrimination of Danggui between authentic and unauthentic region of origin.