Objective:To evaluate the potential value of 18×10 3 translocator protein (TSPO) radioligand ( N, N-diethy1-2-(2-(4-(2- 18F-fluoroethoxy) phenyl)-5, 7-dimethylpyrazolo[1, 5-A]pyrimidin-3-yl)acetamide, 18F-DPA-714) PET compared with conventional MR in the detection of autoimmune encephalitis (AE), the correlation with clinical symptoms, and the monitoring of immunotherapy efficacy in patients with AE. Methods:From December 2021 to June 2024, 45 AE patients (17 males, 28 females, age (38.3±17.0) years) diagnosed at Ruijin Hospital, Shanghai Jiao Tong University School of Medicine and 10 healthy volunteers (7 males, 3 females, age (28.7±5.1) years) were enrolled in this prospective study. All participants underwent baseline 18F-DPA-714 PET/MR scans, and 23 of these AE patients underwent further follow-up 18F-DPA-714 PET/MR scans. 18F-DPA-714 PET positivity was defined as having an uptake intensity threshold higher than the mean SUV ratio (SUVR)+ 2 s of the corresponding brain region in healthy controls. MR positivity was defined as abnormal hyperintensity in a specific brain region or multiple brain regions on the T 2 fluid attenuated inversion recovery (FLAIR). The positive detection rates of 18F-DPA-714 PET and MR was analyzed using McNemar χ2 test, and the differences in the uptake intensity (SUVR) of 18F-DPA-714 between symptomatic and non-symptomatic groups, and between remission and non-remission groups after immunotherapy were compared using independent-sample t test or Wilcoxon rank sum test. Spearman rank correlation analysis was used to analyze the correlation between the changing rate of SUVR and the changing of the modified Rankin Scale (mRS) score before and after treatment. Results:The positive detecting rate of 18F-DPA-714 PET for AE was significantly higher than that of MR (73.3%(33/45) vs 35.6%(16/45); χ2=11.56, P=0.001). The cerebellar SUVR of ataxia patients was significantly higher than that of asymptomatic patients (1.22(1.06, 1.33) vs 1.08(0.99, 1.20); Z=-2.14, P=0.034). Follow-up imaging showed that the SUVR of patients in the remission group after immunotherapy was significantly lower than that in the non-remission group ((-15.19±10.17)% vs (14.26±13.36)%; t=5.81, P<0.001). There was a significant correlation between the changing rate of SUVR and the changing of the mRS score before and after treatment ( rs=0.65, P<0.001). Conclusion:Compared with conventional MR, 18F-DPA-714 PET has a higher positive detecting rate for AE, and has the potential to reflect the clinical symptoms of AE and monitor the efficacy of immunotherapy.

Objective:To evaluate the potential value of 18×10 3 translocator protein (TSPO) radioligand ( N, N-diethy1-2-(2-(4-(2- 18F-fluoroethoxy) phenyl)-5, 7-dimethylpyrazolo[1, 5-A]pyrimidin-3-yl)acetamide, 18F-DPA-714) PET compared with conventional MR in the detection of autoimmune encephalitis (AE), the correlation with clinical symptoms, and the monitoring of immunotherapy efficacy in patients with AE. Methods:From December 2021 to June 2024, 45 AE patients (17 males, 28 females, age (38.3±17.0) years) diagnosed at Ruijin Hospital, Shanghai Jiao Tong University School of Medicine and 10 healthy volunteers (7 males, 3 females, age (28.7±5.1) years) were enrolled in this prospective study. All participants underwent baseline 18F-DPA-714 PET/MR scans, and 23 of these AE patients underwent further follow-up 18F-DPA-714 PET/MR scans. 18F-DPA-714 PET positivity was defined as having an uptake intensity threshold higher than the mean SUV ratio (SUVR)+ 2 s of the corresponding brain region in healthy controls. MR positivity was defined as abnormal hyperintensity in a specific brain region or multiple brain regions on the T 2 fluid attenuated inversion recovery (FLAIR). The positive detection rates of 18F-DPA-714 PET and MR was analyzed using McNemar χ2 test, and the differences in the uptake intensity (SUVR) of 18F-DPA-714 between symptomatic and non-symptomatic groups, and between remission and non-remission groups after immunotherapy were compared using independent-sample t test or Wilcoxon rank sum test. Spearman rank correlation analysis was used to analyze the correlation between the changing rate of SUVR and the changing of the modified Rankin Scale (mRS) score before and after treatment. Results:The positive detecting rate of 18F-DPA-714 PET for AE was significantly higher than that of MR (73.3%(33/45) vs 35.6%(16/45); χ2=11.56, P=0.001). The cerebellar SUVR of ataxia patients was significantly higher than that of asymptomatic patients (1.22(1.06, 1.33) vs 1.08(0.99, 1.20); Z=-2.14, P=0.034). Follow-up imaging showed that the SUVR of patients in the remission group after immunotherapy was significantly lower than that in the non-remission group ((-15.19±10.17)% vs (14.26±13.36)%; t=5.81, P<0.001). There was a significant correlation between the changing rate of SUVR and the changing of the mRS score before and after treatment ( rs=0.65, P<0.001). Conclusion:Compared with conventional MR, 18F-DPA-714 PET has a higher positive detecting rate for AE, and has the potential to reflect the clinical symptoms of AE and monitor the efficacy of immunotherapy.

BACKGROUND:Finite element modeling,as an important engineering analysis technique,has been widely used in various fields of bioengineering research.However,there is little literature on what material properties should be selected for each anatomical structure of the knee joint finite element modeling at different ages for different research purposes.OBJECTIVE:To summarize the material properties of knee joint finite element models at different ages based on previous knee joint finite element studies.METHODS:The search terms were"knee,finite element,material selection,ligament injury,osteoarthritis,elderly,children,young people"in Chinese and English.Articles were searched on CNKI and PubMed,with a timeframe of 1950 to 2024.According to inclusion and exclusion criteria,108 articles were finally included for summary.RESULTS AND CONCLUSION:Children's knee bone density will increase with age,reaching peaks in adulthood.From middle-aged to the age,the elastic modulus of knee joint femur,tibia,fibula,and patella will decrease with age,and then return to the elastic modulus of childhood.The elastic modulus of children and adult cartilage is basically the same,and the elastic modulus of the elderly increases.With the increase of age,the elastic modulus of the knee ligament will decrease to a certain extent,but there is no significant difference in the elastic modulus of the knee ligament of young people and the elderly.With the increase of age,the loss of mechanical integrity of the knee meniscus will damage the biomechanical function of the tissue and disturb the various anisotropic biomechanical responses that are effectively carried and transmitted by the tissue.Knee joint finite element modeling can be used to deeply understand the biomechanical characteristics of the knee joints,develop new implanted materials,predict knee joint diseases,improve surgical technology,and guide patients to rehabilitate exercise.

BACKGROUND:Knee finite element modelling can provide insight into knee mechanics,but its complex image segmentation is more difficult for researchers.With the development of deep learning techniques,deep learning techniques have been widely used in knee joint finite element modelling.OBJECTIVE:To replace the manual segmentation step in finite element modelling of the knee joint by using 3D Swin UNETR in combination with a semi-automatic segmentation technique for statistical shape models.METHODS:Manual(artificial)knee joint finite element model was developed based on MR and semi-automatic knee joint finite element model was developed based on 3D Swin UNETR+statistical shape model segmentation.The same loads and boundary conditions were applied to both models.Validation was performed by calculating the Dice similarity coefficient,mean distance,and comparing the peak equivalent stresses,maximum principal stresses,and maximum shear stresses of the two models.RESULTS AND CONCLUSION:(1)The Dice similarity coefficients of the manual and semi-automatic segmented femur and tibia were more than 98％,and the average distances were less than or equal to(0.35±0.08)mm.(2)With the longitudinal load of 750 N and 10 Nm internal overturning moment applied to the femur tip of both manual and semi-automatic finite element models,the peak equivalent stress,maximum principal stress,and maximum shear stresses of meniscus in manual finite element model were 14.12,18.54,and 7.35 MPa;peak equivalent force,maximum principal stress,and maximum shear stress of femoral cartilage were 2.22,2.15,and 1.18 MPa;peak equivalent force,maximum principal stress,and maximum shear stress of tibial cartilage were 2.50,1.91,and 1.41 MPa;semi-automatic finite element model of meniscus:peak equivalent force,maximum principal stress,and maximum shear stress were 14.93,18.53,and 7.75 MPa.The peak equivalent force,maximum principal stress,and maximum shear stress of femoral cartilage were 2.26,2.18,and 1.20 MPa;the peak equivalent stress,maximum principal stress,and maximum shear stress of tibial cartilage were 2.60,1.91,and 1.46 MPa.The peak equivalent stress,maximum principal stress,and maximum shear stress of manual and semi-automatic finite element models were basically consistent,with no significant difference(P＞0.05).(3)The semi-automatic segmentation technique proposed in this study can replace manual segmentation in creating accurate finite element models of the knee joint.

Under stress,the cold-inducible RNA-binding protein(CIRP)is translocated from the nucleus to the cytoplasm and subsequently released outside the cell.Extracellular CIRP(eCIRP),acting as a damage-associated mo-lecular pattern,amplifies inflammation through various mechanisms and leads to an uncontrolled inflammatory response,thereby contributing to the occurrence and progression of sepsis and other critical pathological processes.Certain CIRP-tar-geting drugs have demonstrated promising anti-sepsis effects through the reduction of CIRP expression,the decrease of eCIRP release,the neutralization of eCIRP,or the intervention in receptor binding.This review examines the release mechanism of CIRP and the role of eCIRP in the development of sepsis,with the aim of providing new insights for the pre-vention and treatment of sepsis by targeting eCIRP.

Under stress,the cold-inducible RNA-binding protein(CIRP)is translocated from the nucleus to the cytoplasm and subsequently released outside the cell.Extracellular CIRP(eCIRP),acting as a damage-associated mo-lecular pattern,amplifies inflammation through various mechanisms and leads to an uncontrolled inflammatory response,thereby contributing to the occurrence and progression of sepsis and other critical pathological processes.Certain CIRP-tar-geting drugs have demonstrated promising anti-sepsis effects through the reduction of CIRP expression,the decrease of eCIRP release,the neutralization of eCIRP,or the intervention in receptor binding.This review examines the release mechanism of CIRP and the role of eCIRP in the development of sepsis,with the aim of providing new insights for the pre-vention and treatment of sepsis by targeting eCIRP.

BACKGROUND:Finite element modeling,as an important engineering analysis technique,has been widely used in various fields of bioengineering research.However,there is little literature on what material properties should be selected for each anatomical structure of the knee joint finite element modeling at different ages for different research purposes.OBJECTIVE:To summarize the material properties of knee joint finite element models at different ages based on previous knee joint finite element studies.METHODS:The search terms were"knee,finite element,material selection,ligament injury,osteoarthritis,elderly,children,young people"in Chinese and English.Articles were searched on CNKI and PubMed,with a timeframe of 1950 to 2024.According to inclusion and exclusion criteria,108 articles were finally included for summary.RESULTS AND CONCLUSION:Children's knee bone density will increase with age,reaching peaks in adulthood.From middle-aged to the age,the elastic modulus of knee joint femur,tibia,fibula,and patella will decrease with age,and then return to the elastic modulus of childhood.The elastic modulus of children and adult cartilage is basically the same,and the elastic modulus of the elderly increases.With the increase of age,the elastic modulus of the knee ligament will decrease to a certain extent,but there is no significant difference in the elastic modulus of the knee ligament of young people and the elderly.With the increase of age,the loss of mechanical integrity of the knee meniscus will damage the biomechanical function of the tissue and disturb the various anisotropic biomechanical responses that are effectively carried and transmitted by the tissue.Knee joint finite element modeling can be used to deeply understand the biomechanical characteristics of the knee joints,develop new implanted materials,predict knee joint diseases,improve surgical technology,and guide patients to rehabilitate exercise.

OBJECTIVE To establish the HPLC fingerprint of Xintong granules and the quantitative analysis of multi-components by single-marker method(QAMS)to determine the contents of 7 components,so as to provide a scientific basis for their quality control.METHODS HPLC method was used to establish the fingerprints for 10 batches of Xintong granules(No.S1-S10),and similarity evaluation,cluster analysis(CA)and partial least squares-discriminant analysis(PLS-DA)were performed.At the same time,the contents of seven components,including puerarin,daidzin,calycosin-7-O-β-D-glucoside,stilbene glycoside,naringin,icariin and tanshinone ⅡA,were determined by QAMS method,and were compared with the results of external standard method.RESULTS A total of 18 common peaks were marked and 7 peaks were identified in the HPLC fingerprints for 10 batches of Xintong granules,namely puerarin(peak 4),daidzin(peak 7),calycosin-7-O-β-D-glucoside(peak 9),stilbene glycoside(peak 10),naringin(peak 12),icariin(peak 17),and tanshinone ⅡA(peak 18);the similarities among them were more than 0.990,and CA and PLS-DA results showed that S4-S5,S8-S10,S1-S3 and S6-S7 were clustered into three categories,respectively.Using naringin as the internal standard,the contents of puerarin,daidzin,calycosin-7-O-β-D-glucoside,stilbene glycoside,icariin and tanshinone ⅡA were determined to be 7.868 1-10.181 2,1.709 2-2.374 1,0.285 2-0.326 3,1.024 1-1.523 9,0.140 2-0.290 4,and 0.077 1-0.219 4 mg/g,respectively,by the QAMS.These results showed no significant differences compared to those obtained by the external standard method.CONCLUSIONS Established HPLC fingerprint and QAMS method are convenient,stable and accurate,which can provide a basis for the quality evaluation of Xintong granules.

BACKGROUND:Knee finite element modelling can provide insight into knee mechanics,but its complex image segmentation is more difficult for researchers.With the development of deep learning techniques,deep learning techniques have been widely used in knee joint finite element modelling.OBJECTIVE:To replace the manual segmentation step in finite element modelling of the knee joint by using 3D Swin UNETR in combination with a semi-automatic segmentation technique for statistical shape models.METHODS:Manual(artificial)knee joint finite element model was developed based on MR and semi-automatic knee joint finite element model was developed based on 3D Swin UNETR+statistical shape model segmentation.The same loads and boundary conditions were applied to both models.Validation was performed by calculating the Dice similarity coefficient,mean distance,and comparing the peak equivalent stresses,maximum principal stresses,and maximum shear stresses of the two models.RESULTS AND CONCLUSION:(1)The Dice similarity coefficients of the manual and semi-automatic segmented femur and tibia were more than 98％,and the average distances were less than or equal to(0.35±0.08)mm.(2)With the longitudinal load of 750 N and 10 Nm internal overturning moment applied to the femur tip of both manual and semi-automatic finite element models,the peak equivalent stress,maximum principal stress,and maximum shear stresses of meniscus in manual finite element model were 14.12,18.54,and 7.35 MPa;peak equivalent force,maximum principal stress,and maximum shear stress of femoral cartilage were 2.22,2.15,and 1.18 MPa;peak equivalent force,maximum principal stress,and maximum shear stress of tibial cartilage were 2.50,1.91,and 1.41 MPa;semi-automatic finite element model of meniscus:peak equivalent force,maximum principal stress,and maximum shear stress were 14.93,18.53,and 7.75 MPa.The peak equivalent force,maximum principal stress,and maximum shear stress of femoral cartilage were 2.26,2.18,and 1.20 MPa;the peak equivalent stress,maximum principal stress,and maximum shear stress of tibial cartilage were 2.60,1.91,and 1.46 MPa.The peak equivalent stress,maximum principal stress,and maximum shear stress of manual and semi-automatic finite element models were basically consistent,with no significant difference(P＞0.05).(3)The semi-automatic segmentation technique proposed in this study can replace manual segmentation in creating accurate finite element models of the knee joint.

Objective To predict the torque on the affected side of the hip,knee,and ankle joints in stroke patients during walking using principal component analysis(PCA)and backpropagation(BP)neural networks.Methods Kinematic and dynamic data from 30 stroke patients were synchronously collected using an 8-lens Qualisys infrared point high-speed motion capture system and Kistler three-dimensional(3D)force measurement platform.The torques of the hip,knee,and ankle joints in the stroke patients were calculated using OpenSim,and the initial variables with a cumulative contribution rate of 99％were screened using PCA.The normalized root mean square error(NRMSE),root mean square error(RMSE),mean absolute percentage error(MAPE),mean absolute error(MAE),and R2 were used as evaluation indicators for the PCA-BP model.The consistency between the calculated joint torque and predicted torque was evaluated using Kendall's W coefficient.Results PCA data showed that the trunk,pelvis,and affected sides of the hip,knee,and ankle joints had a significant impact on the torque of the affected sides of the hip,knee,and ankle joints on the x,y,and z axes(sagittal,coronal,and vertical axes,respectively).The NRMSE between predicted and measured values was 5.14％-8.86％,RMSE was 0.184-0.371,MAPE was 3.5％-4.0％,MAE was 0.143-0.248,and R was 0.998-0.999.Conclusions The established PCA-BP model can accurately predict the torque of the hip,knee,and ankle joints in stroke patients during walking,with a significantly shortened measurement time.This model can replace traditional joint torque calculation in the gait analysis of stroke patients,provides a new approach to obtaining biomechanical data of stroke patients,and is an effective method for the clinical treatment of stroke patients.