OBJECTIVE: To explore the mechanism of antibiotic delivery system targeting bacterial biofilm with linezolid (LZD) based on ε-poly- L-lysine (ε-PLL) and cyclodextrin (CD) (ε-PLL-CD-LZD), aiming to enhance antibiotic bioavailability, effectively penetrate and disrupt biofilm structures, and thereby improve the treatment of bone and joint infections. METHODS: ε-PLL-CD-LZD was synthesized via chemical methods. The grafting rate of CD was characterized using nuclear magnetic resonance. In vitro biocompatibility was evaluated through live/dead cell staining after co-culturing with mouse embryonic osteoblast precursor cells (MC3T3-E1), human umbilical vein endothelial cells, and mouse embryonic fibroblast cells (3T3-L1). The biofilm-enrichment capacity of ε-PLL-CD-LZD was assessed using Staphylococcus aureus biofilms through enrichment studies. Its biofilm eradication efficacy was investigated via minimum inhibitory concentration (MIC) determination, scanning electron microscopy, and live/dead bacterial staining. A bone and joint infection model in male Sprague-Dawley rats was established to validate the antibacterial effects of ε-PLL-CD-LZD. RESULTS: In ε-PLL-CD-LZD, the average grafting rate of CD reached 9.88%. The cell viability exceeded 90% after co-culturing with three types cells. The strong biofilm enrichment capability was observed with a MIC of 2 mg/L. Scanning electron microscopy observations revealed the effective disruption of biofilm structure, indicating potent biofilm eradication capacity. In vivo rat experiments demonstrated that ε-PLL-CD-LZD significantly reduced bacterial load and infection positivity rate at the lesion site ( P<0.05). CONCLUSION The ε-PLL-CD antibiotic delivery system provides a treatment strategy for bone and joint infections with high clinical translational significance. By effectively enhancing antibiotic bioavailability, penetrating, and disrupting biofilms, it demonstrated significant anti-infection effects in animal models.
Biofilms/drug effects* ; Animals ; Anti-Bacterial Agents/pharmacology* ; Polylysine/chemistry* ; Cyclodextrins/administration & dosage* ; Humans ; Linezolid/pharmacology* ; Staphylococcus aureus/physiology* ; Rats, Sprague-Dawley ; Mice ; Rats ; Male ; Drug Delivery Systems ; Staphylococcal Infections/drug therapy* ; Microbial Sensitivity Tests ; Human Umbilical Vein Endothelial Cells ; Osteoblasts/cytology*

OBJECTIVE:To compare the performance of several pattern recognition methods in the identification of volatile oils of traditional Chinese medicine(TCM)by infrared spectroscopy. METHODS:The volatile oils of several Lonicera and Citrus TCM were determined by infrared spectroscopy. All samples of infrared spectrum were classified by hierarchical clustering,K-mean clustering,artificial neural networks,and support vector machine. RESULTS:The results of hierarchical clustering and K-mean clus-tering were ineffective. Methods of artificial neural networks and support vector machine achieved correct classification rate of 100%. CONCLUSIONS:Artificial neural networks and support vector machine can be combined with infrared spectroscopy to cre-ate chemometric fingerprinting for the identification of volatile oils of TCM.

Objective To set up a method for identification of Lonicerae japonicae flos volatile oils using Fourier-transform infrared spectroscopy. Methods The volatile oils of Lonicerae japonicae flos and Lonicerae flos was extracted by steam distillation combined with continuous liquid-liquid extraction with hexane. An oil film was prepared for Fourier-transform infrared spectroscopy scanning by dropping the volatile oils solution on the KBr disc and evaporating the solvent. The obtained infrared spectrum was treated by baseline removing and median filter smoothing. The spectral data within 1800-850 cm-1 was selected as the characteristic spectrum for hierarchical cluster analysis. And the volatile oils of Lonicerae japonicae flos and Lonicerae flos were discriminated by the result of hierarchical cluster analysis. Results Enough volatile oils were extracted for obtaining Fourier-transform infrared spectrum from small amount of Lonicerae japonicae flos. The method developed in the study was able to discriminate Lonicerae japonicae flos volatile oils from Lonicerae flos volatile oils. Conclusion The method can be used for identification of Lonicerae japonicae flos volatile oils.