ObjectiveTo explore the diagnostic value of plasma C-C motif chemokine ligand 3（CCL3） levels in infectious diseases. MethodsThe study enrolled patients in hospital or outpatient service and individuals undergoing health check-ups at Guangdong Provincial People's Hospital from July to October 2023. Patients clinically diagnosed with infectious diseases were assigned to the experimental group， while those who were healthy or diagnosed with non-infectious diseases were included in the control group. After non-qualifying samples were excluded， residual blood specimens from complete blood count （CBC） tests were collected to measure the plasma CCL3 levels.The CBC parameters including white blood cell count （WBC）， neutrophils count （NEUT）， eosinophils count （EOS），etc， and the plasma CCL3 levels were analyzed between the infectious and control groups to evaluate the clinical diagnostic value of CCL3 in infectious diseases. ResultsA total of 257 cases were enrolled， with 167 in the experimental group （active infections confirmed via clinical symptoms， CBC， inflammatory markers， or etiological examinations） and 90 in the control group （confirmed absence of active infections）. The experimental group exhibited higher levels of WBC， NEUT and CCL3 than the control group， while the lymphocytes count（LYMPH）， EOS in the experimental group were lower， with statistical significance （P<0.001） in univariate analysis. By using these significantly different indicators as independent variables， logistics regression modeling identified WBC， NEUT and CCL3 as independent risk factors for infection. Receiver operating characteristic（ROC） curve analysis revealed superior diagnostic performance of CCL3 over WBC and NEUT， while LYMP and EOS showed no diagnostic performance. The area under the curve （AUC） for CCL3 was 0.844 （95% CI： 0.795， 0.892）， with a sensitivity of 84.4%， a specificity of 69.8%， and an optimal threshold of 106.405 ng/mL. ConclusionPlasma CCL3 levels have clinical diagnostic value in predicting infectious diseases and may serve as a potential clinical biomarker for detecting infectious diseases.

Objective The stress variations during the wear process of an artificial knee joint were studied.Then,a signal acquisition system was designed to capture the vibration signals induced by the wear of knee joint prosthesis.The aim was to provide new technical means for online wear monitoring of the artificial knee joint.Methods To effectively collect vibration signals,the optimal installation position of the vibration sensors was determined by analyzing the dynamic model of the knee joint prosthesis during motion and identifying the main distribution areas of the tibial insert contact stress.The dynamic model of the femoral prosthesis was solved using Lagrangian equations.The torque variation curve of the femoral prosthesis was obtained to validate the effectiveness of finite element analysis.The signals collected by the vibration sensors installed at different positions in the friction wear experiments and the surface morphology in different areas were compared to verify the effectiveness of the acquisition system design and finite element analysis results.Results The stress concentration regions of the tibial pad under four degrees of freedom(flexion,internal and external rotation,anterior-posterior displacement,and up-and-down displacement)were obtained based on a dynamic simulation.A stress concentration was evident in the middle and posterior regions of the tibial pad.A vibration signal with a higher amplitude was collected when the vibration sensor was installed at the rear end of the tibial pad.This aided the vibration feature extraction of the knee joint prosthesis.Conclusions The vibration signal acquisition system designed based on the dynamic simulation analysis effectively collected the vibration signals generated by the artificial knee joint during the wear process.This study provides an important means for evaluating the wear mechanisms of artificial knee joints and monitoring their full-life health status.

Objective The stress variations during the wear process of an artificial knee joint were studied.Then,a signal acquisition system was designed to capture the vibration signals induced by the wear of knee joint prosthesis.The aim was to provide new technical means for online wear monitoring of the artificial knee joint.Methods To effectively collect vibration signals,the optimal installation position of the vibration sensors was determined by analyzing the dynamic model of the knee joint prosthesis during motion and identifying the main distribution areas of the tibial insert contact stress.The dynamic model of the femoral prosthesis was solved using Lagrangian equations.The torque variation curve of the femoral prosthesis was obtained to validate the effectiveness of finite element analysis.The signals collected by the vibration sensors installed at different positions in the friction wear experiments and the surface morphology in different areas were compared to verify the effectiveness of the acquisition system design and finite element analysis results.Results The stress concentration regions of the tibial pad under four degrees of freedom(flexion,internal and external rotation,anterior-posterior displacement,and up-and-down displacement)were obtained based on a dynamic simulation.A stress concentration was evident in the middle and posterior regions of the tibial pad.A vibration signal with a higher amplitude was collected when the vibration sensor was installed at the rear end of the tibial pad.This aided the vibration feature extraction of the knee joint prosthesis.Conclusions The vibration signal acquisition system designed based on the dynamic simulation analysis effectively collected the vibration signals generated by the artificial knee joint during the wear process.This study provides an important means for evaluating the wear mechanisms of artificial knee joints and monitoring their full-life health status.