Objective By exploring changes of six degrees of freedom(6DOF)kinematics of the knee joint during extra weight bearing of the body trunk,the influence of extra weight on knee joint movement patterns was studied.Methods A total of 24 healthy subjects were recruited to walk/run on a treadmill at four speeds under two states:self-weight and wearing a 16 kg vest,and gait analysis was conducted.A three-dimensional(3D)portable knee kinematics analysis system based on infrared stereophotography was used to capture 6DOF movement trajectory data of the tibia relative to the femur.Results Compared to the self-weight state,when additional trunk weight was added,the knee external rotation angle was reduced at 3.6 km/h speed(1.4°-2.1°)and 5.4 km/h speed(2.2°-2.7°);the knee internal rotation angle was reduced at 10.8 km/h speed(2.1°-4.2°);the knee flexion angles was increased significantly at the speed of 3.6 km/h(1.5°-1.8°),9 km/h(1.6°-3.3°)和 10.8 km/h(1.9°-3.1°);the knee adduction angle increased at 5.4 km/h speed(0.5°-0.6°),and decreased at 10.8 km/h speed(0.9°-1.3°).At 10.8 km/h speed,the distal knee displacement(0.2-0.4 mm)was increased,and the lateral knee displacement(0.1-0.2 mm),and anterior knee displacement(0.2-0.3 mm)were significantly reduced.Conclusions The 6DOF kinematics of human knee is significantly affected by the extra trunk weight.Performance is also different at lower and higher speeds.It is suggested that there may exist a hidden injury in military training,and this study provides a kinematic basis for the occurrence of sports injury.

The differentiation between benign and malignant thyroid nodules is pivotal in clinical practice. However, current diagnostic systems face challenges, such as heterogeneity in ultrasound interpretation, the invasiveness of fine-needle aspiration cytology and indeterminate of results. Artificial intelligence (AI) has evolved from traditional machine learning to deep learning, enabling advances in image recognition, feature extraction, and multimodal data integration. Nevertheless, AI applications remain constrained by limitations, including the insufficiency of high-quality annotated data and inadequate cross-center generalizability. Future progress will focus on algorithm refinement, multimodal data fusion, and multicenter clinical validation to enhance model generalizability and diagnostic accuracy.

The differentiation between benign and malignant thyroid nodules is pivotal in clinical practice. However, current diagnostic systems face challenges, such as heterogeneity in ultrasound interpretation, the invasiveness of fine-needle aspiration cytology and indeterminate of results. Artificial intelligence (AI) has evolved from traditional machine learning to deep learning, enabling advances in image recognition, feature extraction, and multimodal data integration. Nevertheless, AI applications remain constrained by limitations, including the insufficiency of high-quality annotated data and inadequate cross-center generalizability. Future progress will focus on algorithm refinement, multimodal data fusion, and multicenter clinical validation to enhance model generalizability and diagnostic accuracy.

Objective By exploring changes of six degrees of freedom(6DOF)kinematics of the knee joint during extra weight bearing of the body trunk,the influence of extra weight on knee joint movement patterns was studied.Methods A total of 24 healthy subjects were recruited to walk/run on a treadmill at four speeds under two states:self-weight and wearing a 16 kg vest,and gait analysis was conducted.A three-dimensional(3D)portable knee kinematics analysis system based on infrared stereophotography was used to capture 6DOF movement trajectory data of the tibia relative to the femur.Results Compared to the self-weight state,when additional trunk weight was added,the knee external rotation angle was reduced at 3.6 km/h speed(1.4°-2.1°)and 5.4 km/h speed(2.2°-2.7°);the knee internal rotation angle was reduced at 10.8 km/h speed(2.1°-4.2°);the knee flexion angles was increased significantly at the speed of 3.6 km/h(1.5°-1.8°),9 km/h(1.6°-3.3°)和 10.8 km/h(1.9°-3.1°);the knee adduction angle increased at 5.4 km/h speed(0.5°-0.6°),and decreased at 10.8 km/h speed(0.9°-1.3°).At 10.8 km/h speed,the distal knee displacement(0.2-0.4 mm)was increased,and the lateral knee displacement(0.1-0.2 mm),and anterior knee displacement(0.2-0.3 mm)were significantly reduced.Conclusions The 6DOF kinematics of human knee is significantly affected by the extra trunk weight.Performance is also different at lower and higher speeds.It is suggested that there may exist a hidden injury in military training,and this study provides a kinematic basis for the occurrence of sports injury.

To develop Senecavirus A (SVA) virus-like particles (VLPs), a recombinant prokaryotic expression plasmid pET28a-SVA-VP031 was constructed to co-express SVA structural proteins VP0, VP3 and VP1, according to the genomic sequence of the field isolate CH-FJ-2017 after the recombinant proteins were expressed in E .coli system, and purified by Ni+ ion chromatographic method. The SVA VLPs self-assemble with a high yield in vitro buffer. A typical VLPs with an average diameter of 25-30 nm which is similar to native virions by using TEM detection. Animals immunized by SVA VLPs shown that the VLPs induced high titers neutralizing antibodies in Guinea pigs. This study indicated that the VLPs produced with co-expressing SVA structural proteins VP0, VP3 and VP1 in prokaryotic system is a promising candidate and laid an important foundation for the development of a novel SVA VLPs vaccine.
Animals ; Antibodies, Neutralizing ; Escherichia coli/genetics* ; Genomics ; Guinea Pigs ; Picornaviridae/genetics*