Based on CT scan data,a bionic model of lumbar spine injuries with high biofidelity is developed and validated through cadaver experiments.Decoupling the constraint system that affects occupants during collisions due to inertial forces and the subsequent pressure exerted by the seat upon returning to position,a simulated fall experiment is designed.The simulated outcomes are trained and predicted using deep learning algorithms,and the accuracy of the trained neural network prediction model is verified.Key parameters are analyzed for correlation using principal component analysis and cross-reverse methods.The results shows that the predicted lumbar spine injury model obtained from training has high reliability(R2>0.9).Comprehensive analysis reveals that after experiencing axial impact,the L4 vertebral body bears the highest impact load and can be used as a representative measure of lumbar spine injury.Among the environmental variables,the axial force on the L4 lumbar spine is mainly affected by torso mass and fall height,both of which have positive correlations.Torso mass,fall height,and posture angle all have positive effects on internal energy.Conversely,torso mass and fall height have negative correlations with stress.These research findings provide a scientific basis for further elucidating lumbar spine injury mechanisms in intelligent cockpit environments,devising corresponding safety protection measures,and evaluating occupant safety in automobiles.

Objective The finite element pelvis model with detailed anatomical structures which meets the Chinese human 95th percentile characteristics is developed,and the influence of cortical bone modeling method on the biomechanical response of the real pelvis is explored.Methods Based on the pelvic medical images of a 95th percentile male volunteer,two finite element pelvis models with real hip bone cortical bone thickness(REA-M)and 2 mm uniform cortical bone thickness(CON-M)dominated by hexahedral elements were constructed.Using the simulation method to reconstruct the loading conditions of cadaver experiments,the validation of models was verified by comparing the cadaver experimental results and simulation results,and biomechanical response differences of two models under different working conditions were discussed.Results The simulation data showed that there was a strong correlation between the overall biomechanical responses of two pelvic models and the cadaver experiment,and the mechanical response difference between two models was mostly within 8％,and the correlation score difference between two models was smaller than 2％.Conclusions The validation of two pelvic models established in this study is verified by rebuilding multiple simulation experiments.Although the biomechanical responses of CON-M and REA-M models were different,the difference was small.From the perspective of model simplification,the CON-M model can be used to study the biomechanical response of the pelvis.

Objective To explore the predictive value of growth differentiation factor 15(GDF-15)for atrial fibrillation(AF)in patients with coronary heart disease(CHD).Methods A prospective observation cohort of 1261 elderly CHD patients was randomly sampled from the First Medical Center of Chinese PLA General Hospital from January 2012 to December 2015.ELISA was used to detect GDF-15 level in all the subjects,and their baseline data were collected.Until March 2023,93 patients were lost during the follow-up period,and finally 1168 patients completed the follow-up,with a median time of 9.4 years.According to AF occurred or not during the period,the eligible patients were divided into an AF group(197 cases)and a non-AF group(971 cases),and based on their medical history,also assigned into a stable angina pectoris(SAP,n=304)and an acute coronary syndrome group(ACS,n=864).Logistic regression analysis was used to determine whether GDF-15 is a risk factor for AF in elderly CHD patients.ROC curve was plotted to assess the predictive value of GDF-15,guideline recommended CHARGE-AF scoring model,and their combination for AF events in the patients.Results The AF group had significantly advanced age,larger proportions of smoking history,type 2 diabetes,hypertension,old myocardial infarction,stroke,ACS and administration of statins,higher ratio of angiotensin converting enzyme inhibi-tor/angiotensin receptor blocker,and elevated levels of GDF-15 and N-terminal pro-B-type natri-uretic peptide,and lower left ventricular ejection fraction,SAP incidence,and low-density lipopro-tein cholesterol,total cholesterol and triglycerides levels when compared with the non-AF group(P＜0.05,P＜0.01).Multivariate logistic regression analysis showed that GDF-15 was not a risk factor for AF in elderly CHD patients(OR=0.92,95％CI:0.74-1.16,P=0.489),but was a risk factor for AF in SAP patients(OR=1.38,95％CI:1.07-2.79,P=0.015),and in ACS patients,still not a risk factor for AF(OR=0.81,95％CI:0.63-1.05,P=0.814).ROC curve analysis showed that the AUC value of GDF-15 combined with the CHARGE-AF scoring model in predic-ting AF was 0.682 in the elderly CHD patients,0.746 in the SAP patients,and 0.680 in the ACS patients.Conclusion Elevated GDF-15 level is an independent risk factor and predictor of AF in elderly SAP patients.In SAP patients,the combination of GDF-15 and CHARGE-AF scoring model further improves the predictive performance of AF occurrence.

Abnormal deployment of the airbag during a frontal car collision can cause injuries to the upper extremity of drivers with non-standard driving postures.Finite element simulation offers an effective approach for evaluating such injury risks.In this study,a biomechanical finite element model of the upper limb of the 95th percentile human body with detailed anatomical structures was developed.The validity of the upper extremity-airbag collision model was confirmed by reconstructing the cadaveric forearm and airbag impact experiments.Based on the validated model,the influence of factors such as airbag mass rate parameters,upper limb grip angle,and grip force on upper limb injuries in frontal collisions was investigated.The results indicate that variations in these three parameters have a significant influence on upper extremity injury,and these factors should be considered in the assessment of upper extremity injuries during car collision.

Objective To investigate the risk of thoracoabdominal injuries in six-year-old child occupants in a reclined seating posture during frontal collisions,and provide a reference for developing child restraint systems(CRS).Methods Three validated biomechanical models of six-year-old child occupants in different seating postures with detailed anatomical structures were used.The acceleration curve from a sport utility vehicle crash test was applied to analyze the effects of seating posture on thoracic motion trajectory,chest acceleration,thoracoabdominal compression,viscous criterion(VC)of the chest and abdomen,internal organ strain,and spinal stress.Results Thoracic motion trajectories varied in the Z-direction under three seating postures.As the upper torso angle increased,thoracoabdominal kinematic injury parameters showed an upward trend.The thoracic and abdominal VC under 120° and 135° posture increased by 67％and 113％,10.7％and 25％compared with that under 105° standard sitting posture.The risk of thoracic internal organ injury was inversely related to the seating angle,while the risk of abdominal internal organ injury was positively related to the seating angle.The primary spinal injury mechanism was compression-flexion.Conclusions CRS protection evaluation should comprehensively consider thoracoabdominal kinematic parameters,internal organ biomechanics,and spinal injury risk.These findings have important implications for CRS development in intelligent driving systems and occupant protection strategy formulation.

Objective To investigate the risk of thoracoabdominal injuries in six-year-old child occupants in a reclined seating posture during frontal collisions,and provide a reference for developing child restraint systems(CRS).Methods Three validated biomechanical models of six-year-old child occupants in different seating postures with detailed anatomical structures were used.The acceleration curve from a sport utility vehicle crash test was applied to analyze the effects of seating posture on thoracic motion trajectory,chest acceleration,thoracoabdominal compression,viscous criterion(VC)of the chest and abdomen,internal organ strain,and spinal stress.Results Thoracic motion trajectories varied in the Z-direction under three seating postures.As the upper torso angle increased,thoracoabdominal kinematic injury parameters showed an upward trend.The thoracic and abdominal VC under 120° and 135° posture increased by 67％and 113％,10.7％and 25％compared with that under 105° standard sitting posture.The risk of thoracic internal organ injury was inversely related to the seating angle,while the risk of abdominal internal organ injury was positively related to the seating angle.The primary spinal injury mechanism was compression-flexion.Conclusions CRS protection evaluation should comprehensively consider thoracoabdominal kinematic parameters,internal organ biomechanics,and spinal injury risk.These findings have important implications for CRS development in intelligent driving systems and occupant protection strategy formulation.

Based on CT scan data,a bionic model of lumbar spine injuries with high biofidelity is developed and validated through cadaver experiments.Decoupling the constraint system that affects occupants during collisions due to inertial forces and the subsequent pressure exerted by the seat upon returning to position,a simulated fall experiment is designed.The simulated outcomes are trained and predicted using deep learning algorithms,and the accuracy of the trained neural network prediction model is verified.Key parameters are analyzed for correlation using principal component analysis and cross-reverse methods.The results shows that the predicted lumbar spine injury model obtained from training has high reliability(R2>0.9).Comprehensive analysis reveals that after experiencing axial impact,the L4 vertebral body bears the highest impact load and can be used as a representative measure of lumbar spine injury.Among the environmental variables,the axial force on the L4 lumbar spine is mainly affected by torso mass and fall height,both of which have positive correlations.Torso mass,fall height,and posture angle all have positive effects on internal energy.Conversely,torso mass and fall height have negative correlations with stress.These research findings provide a scientific basis for further elucidating lumbar spine injury mechanisms in intelligent cockpit environments,devising corresponding safety protection measures,and evaluating occupant safety in automobiles.

Objective The finite element pelvis model with detailed anatomical structures which meets the Chinese human 95th percentile characteristics is developed,and the influence of cortical bone modeling method on the biomechanical response of the real pelvis is explored.Methods Based on the pelvic medical images of a 95th percentile male volunteer,two finite element pelvis models with real hip bone cortical bone thickness(REA-M)and 2 mm uniform cortical bone thickness(CON-M)dominated by hexahedral elements were constructed.Using the simulation method to reconstruct the loading conditions of cadaver experiments,the validation of models was verified by comparing the cadaver experimental results and simulation results,and biomechanical response differences of two models under different working conditions were discussed.Results The simulation data showed that there was a strong correlation between the overall biomechanical responses of two pelvic models and the cadaver experiment,and the mechanical response difference between two models was mostly within 8％,and the correlation score difference between two models was smaller than 2％.Conclusions The validation of two pelvic models established in this study is verified by rebuilding multiple simulation experiments.Although the biomechanical responses of CON-M and REA-M models were different,the difference was small.From the perspective of model simplification,the CON-M model can be used to study the biomechanical response of the pelvis.

Abnormal deployment of the airbag during a frontal car collision can cause injuries to the upper extremity of drivers with non-standard driving postures.Finite element simulation offers an effective approach for evaluating such injury risks.In this study,a biomechanical finite element model of the upper limb of the 95th percentile human body with detailed anatomical structures was developed.The validity of the upper extremity-airbag collision model was confirmed by reconstructing the cadaveric forearm and airbag impact experiments.Based on the validated model,the influence of factors such as airbag mass rate parameters,upper limb grip angle,and grip force on upper limb injuries in frontal collisions was investigated.The results indicate that variations in these three parameters have a significant influence on upper extremity injury,and these factors should be considered in the assessment of upper extremity injuries during car collision.

Objective To explore the predictive value of growth differentiation factor 15(GDF-15)for atrial fibrillation(AF)in patients with coronary heart disease(CHD).Methods A prospective observation cohort of 1261 elderly CHD patients was randomly sampled from the First Medical Center of Chinese PLA General Hospital from January 2012 to December 2015.ELISA was used to detect GDF-15 level in all the subjects,and their baseline data were collected.Until March 2023,93 patients were lost during the follow-up period,and finally 1168 patients completed the follow-up,with a median time of 9.4 years.According to AF occurred or not during the period,the eligible patients were divided into an AF group(197 cases)and a non-AF group(971 cases),and based on their medical history,also assigned into a stable angina pectoris(SAP,n=304)and an acute coronary syndrome group(ACS,n=864).Logistic regression analysis was used to determine whether GDF-15 is a risk factor for AF in elderly CHD patients.ROC curve was plotted to assess the predictive value of GDF-15,guideline recommended CHARGE-AF scoring model,and their combination for AF events in the patients.Results The AF group had significantly advanced age,larger proportions of smoking history,type 2 diabetes,hypertension,old myocardial infarction,stroke,ACS and administration of statins,higher ratio of angiotensin converting enzyme inhibi-tor/angiotensin receptor blocker,and elevated levels of GDF-15 and N-terminal pro-B-type natri-uretic peptide,and lower left ventricular ejection fraction,SAP incidence,and low-density lipopro-tein cholesterol,total cholesterol and triglycerides levels when compared with the non-AF group(P＜0.05,P＜0.01).Multivariate logistic regression analysis showed that GDF-15 was not a risk factor for AF in elderly CHD patients(OR=0.92,95％CI:0.74-1.16,P=0.489),but was a risk factor for AF in SAP patients(OR=1.38,95％CI:1.07-2.79,P=0.015),and in ACS patients,still not a risk factor for AF(OR=0.81,95％CI:0.63-1.05,P=0.814).ROC curve analysis showed that the AUC value of GDF-15 combined with the CHARGE-AF scoring model in predic-ting AF was 0.682 in the elderly CHD patients,0.746 in the SAP patients,and 0.680 in the ACS patients.Conclusion Elevated GDF-15 level is an independent risk factor and predictor of AF in elderly SAP patients.In SAP patients,the combination of GDF-15 and CHARGE-AF scoring model further improves the predictive performance of AF occurrence.