Optimization of ultrasonic sterilization parameters for Pseudomonas aeruginosa by neural network and its application in chronic osteomyelitis

ObjectiveTo explore the effect of ultrasound in adjuvant treatment of chronic osteomyelitis from the aspect of antibacterial effect.

MethodsThe neural network model was used to optimize the ultrasonic sterilization parameters in vitro, and the optimized parameters were applied to treat rabbit femoral chronic osteomyelitis model.The number of microbial infection and the Norden score were used to evaluate the effect of ultrasound treatment on chronic osteomyelitis.

ResultsThrough fitting the neural network model, it was found that the fitting effect was the best in the case of hidden node 4, and the best parameters were as follows: 40 W/cm³ as the ultrasound intensity, 60 kHz as the ultrasound frequency, and 15 min as the ultrasound time, which resulted in the best sterilization effect.These parameters were applied to treat rabbit femoral chronic osteomyelitis model, and it was found that the antibiotic azithromycin had the best synergistic effect, which had good effects on microbial infection and Norden score.

ConclusionsUltrasound can assist the treatment of chronic osteomyelitis through bacteriostasis, and its synergistic effect with antibiotics has the best effect.