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Background: Postural sway could be separated into several components according to frequencies. Higher frequency sway is indicative of hip strategy but how is it impaired in ataxia patients is still unknown. Methods: Static posturography examination were administered to 37 patients with spinocerebellar ataxia (SCA), 58 patients with the cerebellar type of multiple system atrophy and 53 healthy controls. Energy value trajectory during the four-step sensory organization tests were evaluated by generalized additive mixed model (GAMM). Repeated measures correlation analysis between energy value/proportions and postural performance (total postural sway, fall and tremor occurrence) were also performed. Results: GAMM analysis revealed that the middle frequency band proportion did not increase with test difficulties in MSA and SCA, indicating a failure of frequency shift. Repeated measures correlation analysis revealed that the highest correlation coefficient between energy values were found between MFV and HFV in healthy controls, illustrating components of a complete hip strategy, which was not found in SCA or MSA. In normal adults, there is a significant and positive relationship between MFP and HFP with total energy values, illustrating frequency shifts of normal stance. However, MFP was negatively related with total energy values in SCA (p>0.05) and MSA (pConclusion: Hip strategy was not complete in SCA while it was completely disrupted in MSA, which explains why there were more falls in MSA patients. High frequency band postural sway (>2Hz) is an important component of a complete hip strategy and its origin needs further investigation.

Gestodene (GES), altrenogest (ALT), and medroxyprogesterone acetate (MPA) are three potent synthetic progestins detected in agricultural soils; however, their biotransformation outcomes in soils remain unclear. This study explored the biotransformation of these progestins in five agricultural soils with different physicochemical properties. The biotransformation data were well-described by a first-order decay model (R

Objective: To construct a comprehensive simulation framework of "gait-musculoskeletal system(MS)-finite element(FE)" for analysis of hip joint dynamics characteristics and the changes in the contact stress in the hip throughout a gait cycle.Methods:Two healthy volunteers (male and female) were recruited. The 3D gait trajectories during normal walking and the CT images including the hip and femur of the volunteers were obtained. CT Imaging data in the DICOM were extracted for subjected 3D hip joint reconstruction. The reconstructed 3D model files were used to realize the subject-specific registration of the pelvis and thigh segment of general musculoskeletal model. The captured marker trajectory data were used to drive subject-specific musculoskeletal model to complete inverse dynamic analysis. Results of inverse dynamic analysis were exported and appliedas boundary and load settings of the hip joint finite element in ABAQUS. Finally, the finite element analysis(FEA) was performed to analyze contact stress of hip joint during a gait cycle of left foot.Results: In the inverse dynamic analysis, the dynamic changes of the main hip-femoral muscle force with respect to each phase of a single gait cycle were plotted. The hip joint reaction force reached a maximum value of 2.9%BW（Body weight）and appeared at the end of the terminal stance phase. Twin peaks appeared at the initial contact phase and the end of the terminal stance phase respectively. FEA showed the temporal changes in contact stress in the acetabulum. In the visual stress cloud chart, the acetabular contact stress was mainly distributed in the dome of the acetabulum and in the anterolateral area at the top of the femoral head during a single gait cycle. The acetabular contact area was 293.8-998.4 mm2 and the maximum contact area appear at the mid-stance phase or the loading response phase of gait. The maximum contact stress of the acetabulum reached 6.91 Mpa (Model 1) / 6.92 Mpa(Model 2) at the terminal stance phase. Conclusions:The "Gait-MS-FE" technology is integrated to construct a comprehensive simulation framework. Based on human gait trajectories and their CT images, individualized simulation modeling can be achieved. Subject-specific gait in combination with an inverse dynamic analysis of the MS provides pre-processing parameters for FE simulation for more accurate biomechanical analysis of hip joint.

Objective To construct a comprehensive simulation method of “gait-musculoskeletal system (MS)-finite element (FE)” for analysis of hip joint dynamics characteristics and the changes in the contact stress in the hip throughout a gait cycle. Methods Two healthy volunteers (male and female) were recruited. The 3D gait trajectories during normal walking and the CT images including the hip and femur of the volunteers were obtained. CT imaging data in the DICOM format were extracted for subjected 3D hip joint reconstruction. The reconstructed 3D model files were used to realize the subject-specific registration of the pelvis and thigh segment of general musculoskeletal model. The captured marker trajectory data were used to drive subject-specific musculoskeletal model to complete inverse dynamic analysis. Results of inverse dynamic analysis were exported and applied as boundary and load settings of the hip joint finite element in ABAQUS. Finally, the finite element analysis (FEA) was performed to analyze contact stress of hip joint during a gait cycle of left foot. Results In the inverse dynamic analysis, the dynamic changes of the main hip-femoral muscle force with respect to each phase of a single gait cycle were plotted. The hip joint reaction force reached a maximum value of 2.9%BW (body weight) and appeared at the end of the terminal stance phase. Twin peaks appeared at the initial contact phase and the end of the terminal stance phase, respectively. FEA showed the temporal changes in contact stress in the acetabulum. In the visual stress cloud chart, the acetabular contact stress was mainly distributed in the dome of the acetabulum and in the anterolateral area at the top of the femoral head during a single gait cycle. The acetabular contact area was between 293.8 and 998.4 mm2, and the maximum contact area appear at the mid-stance phase or the loading response phase of gait. The maximum contact stress of the acetabulum reached 6.91 MPa for the model 1 and 6.92 MPa for the model 2 at the terminal stance phase. Conclusions The “Gait-MS-FE” technology is integrated to construct a comprehensive simulation framework. Based on human gait trajectories and their CT images, individualized simulation modeling can be achieved. Subject-specific gait in combination with an inverse dynamic analysis of the MS provides pre-processing parameters for FE simulation for more accurate biomechanical analysis of hip joint. Graphical abstract