BACKGROUND:A large number of studies have demonstrated that stem cell exosomes play an important role in the repair of bone defects,either directly as carriers for loading other small molecules or surface modifications,or by binding to biomaterials to promote the repair and regeneration of bone tissue.OBJECTIVE:To summarize the osteogenic mechanisms of stem cell exosomes from different sources and their research progress in bone defect repair.METHODS:Chinese search terms"stem cell,exosome,bone,biomaterial,carrier,bioceramic,polymer,metal,hydrogel,engineered exosome"were used to search CNKI.English search terms"stem cell,exosome,bone defect,biomaterial,carrier,bioceramic,ploymer,metal material,hydrogel,engineering exosome"were used to search PubMed database.According to the inclusion and exclusion criteria,77 relevant articles were finally included for summary.RESULTS AND CONCLUSION:Exosomes from stem cells of different origins can promote osteoblast proliferation and differentiation,promote angiogenesis,and regulate osteoclast activity and macrophage phenotype to promote bone formation and bone mineralization.In addition,many achievements of exosomes in the field of bone defect repair were described from two aspects:biomaterial-assisted exosomes and engineered exosomes.However,the current research on stem cell exosomes in bone tissue engineering is still insufficient,and most of these studies are limited to small animal models,while the treatment of bone defects in large animals,including humans,will be more complex,which will also become a major challenge for the treatment of bone defects.This will also be a great challenge in the dissemination of exosome therapy.

BACKGROUND:A large number of studies have demonstrated that stem cell exosomes play an important role in the repair of bone defects,either directly as carriers for loading other small molecules or surface modifications,or by binding to biomaterials to promote the repair and regeneration of bone tissue.OBJECTIVE:To summarize the osteogenic mechanisms of stem cell exosomes from different sources and their research progress in bone defect repair.METHODS:Chinese search terms"stem cell,exosome,bone,biomaterial,carrier,bioceramic,polymer,metal,hydrogel,engineered exosome"were used to search CNKI.English search terms"stem cell,exosome,bone defect,biomaterial,carrier,bioceramic,ploymer,metal material,hydrogel,engineering exosome"were used to search PubMed database.According to the inclusion and exclusion criteria,77 relevant articles were finally included for summary.RESULTS AND CONCLUSION:Exosomes from stem cells of different origins can promote osteoblast proliferation and differentiation,promote angiogenesis,and regulate osteoclast activity and macrophage phenotype to promote bone formation and bone mineralization.In addition,many achievements of exosomes in the field of bone defect repair were described from two aspects:biomaterial-assisted exosomes and engineered exosomes.However,the current research on stem cell exosomes in bone tissue engineering is still insufficient,and most of these studies are limited to small animal models,while the treatment of bone defects in large animals,including humans,will be more complex,which will also become a major challenge for the treatment of bone defects.This will also be a great challenge in the dissemination of exosome therapy.

The disease-syndrome combination animal model in traditional Chinese medicine （TCM） andrology serves as an important bridge linking TCM theory with modern medical research， providing a key experimental platform for elucidating the 'syndrome-disease' correlation mechanism in male-specific diseases and for screening effective prescriptions. This article reviews recent progress in animal model research on common TCM andrological diseases， including prostatic diseases， sexual dysfunction， and male infertility， with a focus on analyzing the application， advantages， and disadvantages of various modeling strategies， such as immune induction， hormonal intervention， and multi-factor combination across different syndrome types. However， despite breakthroughs in model construction techniques， current research still faces several challenges， including insufficient standardization of syndrome differentiation and difficulties in quantifying TCM-specific indicators. Future studies need to optimize model evaluation systems by integrating modern technologies， in order to promote the standardization and internationalization of TCM andrology research.

Objective To investigate the the effects of fracture fragment size and fixation method on biomechanical stability of distal tibial epiphyseal injuries in children.Methods A three-dimensional(3D)finite element model of a Salter-Harris Ⅱ(SH-Ⅱ)epiphyseal injury with fracture fragments of varying sizes(Small,Middle,Big)was constructed using computed tomography(CT)data from the lower limb of a 10-year-old volunteer.and bone-internal fixation assemblies were created with 1-3 screws(1 S group,2 S group,3 S group)and Kirschner wire(K group).The model was subjected to gravitational forces,posterior drawer forces,and external rotation.Displacement and stress distributions on fracture fragments and fixation devices were analyzed.Results The maximum displacement for the four groups of models was concentrated at the distal end of the fracture fragment.Under gravity conditions,the maximum displacement of the distal end of the fracture fragment in the 1 S,2 S,3 S and K models in Small group was 5.69,5.57,5.56,0.11 mm,respectively,and the bone stress was 16.95,12.26,8.57 and 5.00 MPa,respectively.A high stress area at the epiphyseal plate and the fracture line was easily formed under screw fixation,while a high stress area at the edge of the epiphyseal plate was formed under Kirschner wire fixation.Conclusions When distal tibial epiphyseal injuries in children are treated by using screws,increasing the number of screws can improve the fixation stability and share local bone stress,but the connection area between the fracture fragment and the epiphyseal plate cannot be too small.Kirschner wire fixation can provide better biomechanical effects than screw fixation.

Objective:To analyze the iodine nutrition status of children and adolescents and influencing factors in Zhejiang Province, providing scientific basis for optimizing iodine deficiency disorders (IDD) prevention and control strategies.Methods:In June 2022, a multistage stratified sampling method was used to divide 16 counties (cities, districts, abbreviated as counties) in Zhejiang Province into three categories based on their geographical locations (average distance from the coastline): coastal areas (including Dinghai District, Jiaojiang District, Sanmen County, Cixi City and Lucheng District), sub-coastal areas (including Wuxing District, Haining City, Linping District, Fuyang District and Fenghua District), and inland areas(including Suichang County, Changshan County, Shengzhou City, Jindong District, Dongyang City and Yongjia County). One county was selected from each category, and one township (street) was selected from each county. Two administrative villages (neighborhood committees) were selected from each township (street). Ten households including all children and adolescents aged 6-17 in each household were selected from each administrative village (neighborhood committee). Demographic information and personal dietary characteristics were collected via questionnaires, while household salt and a random urine sample were tested for iodine level. Trend analysis was conducted using a χ 2trend test, and a multivariate logistic stepwise regression model was used to analyze the influencing factors of urinary iodine levels. Results:A total of 755 children and adolescents aged 6-17 were selected, including 387 males (51.26%) and 368 females (48.74%), with an age of (11.24 ± 3.32) years. There were 269 children and adolescents in coastal areas (35.63%) and 409 children and adolescents in urban areas (54.17%). A total of 755 household salt samples were collected, with a median salt iodine concentration of 21.80 mg/kg. These included 263 non-iodized salt samples, 38 unqualified iodized salt samples, and 454 qualified iodized salt samples. The coverage rate of iodized salt was 65.17% (492/755), and the consumption rate of qualified iodized salt was 60.13% (454/755). The distribution of salt iodine quality among children and adolescents in different geographical locations showed statistically significant differences (χ 2 = 111.95, P < 0.001), with the proportion of non-iodized salt gradually decreasing from coastal areas to inland areas (χ 2trend = 90.17, P < 0.001). A total of 755 urine samples were collected, with a median urinary iodine concentration of 186.60 μg/L. The proportions of urinary iodine < 100, 100-199, 200-299, and ≥300 μg/L were 16.95% (128/755), 37.62% (284/755), 24.37% (184/755), and 21.06% (159/755), respectively. The χ 2trend test revealed a nonlinear positive correlation between salt iodine level and urinary iodine level (χ 2regression = 21.98, P < 0.001; χ 2partial = 6.96, P < 0.001). The frequency distribution of urinary iodine in children and adolescents from different geographical locations and between urban and rural areas showed statistically significant differences (χ 2 = 29.63, 16.56, P < 0.001). Among them, the proportion of children and adolescents with urinary iodine < 100 μg/L gradually decreasing from coastal areas to inland areas (χ 2trend = 6.15, P = 0.013). The results of multivariate logistic regression analysis revealed that sub-coastal regions, inland regions, and urban-rural regions ( OR = 1.57, 1.53, 1.64, 95% CI: 1.11-2.24, 1.03-2.27, 1.17-2.32, P < 0.05) were significantly associated with urinary iodine levels in children and adolescents aged 6-17. Conclusions:In 2022, the iodine nutrition of children and adolescents in Zhejiang Province is generally suitable, but there is a risk of iodine deficiency among coastal children and adolescents. Geographic location and urban/rural areas are influencing factors on iodine nutrition status of children and adolescents in Zhejiang Province.

Objective:To investigate the clinical value of enhanced magnetic resonance imaging (MRI)-based deep learning model in preoperative prediction of proliferative hepatocellular carcinoma (HCC).Methods:The retrospective cohort study was conducted. The clinical data of 906 HCC patients who were admitted to The First Affiliated Hospital of Army Medical University and The Second Affiliated Hospital of Chongqing Medical University from May 2017 to October 2022 were collected. There were 769 males and 137 females, aged (53.2±10.9)years. Of the 906 patients, 815 cases who were admitted to The First Affiliated Hospital of Army Medical University were divided into the training set of 634 patients and the internal validation set of 181 patients using a random number table method with a ratio of 8:2, and 91 patients who were admitted to The Second Affiliated Hospital of Chongqing Medical University were divided into the external validation set. The training set was used to construct the prediction model, while the validation set was used to validate the prediction model. Observation indicators: (1) analysis of factors influencing the pathological classification of HCC patients; (2) deep learning imaging features of HCC patients; (3) evaluation of the efficacy of prediction model for proliferative HCC; (4) validation of the prediction model for proliferative HCC; (5) prognosis of HCC patients. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Multivariate analysis was conducted using the binary Logistic regression model. The model perfor-mance was evaluated through five-fold cross-validation, and receiver operating characteristic (ROC) curve was plotted to assess the diagnostic value of the model based on the area under curve (AUC), sensitivity, and specificity. The Delong test was used to compare the diagnostic performance of models. The Hosmer-Lemeshow test was employed to evaluate the calibration of models. The optimal cutoff value of the prediction model was determined by the maximum Youden index, with the value >0.175 indicating high-risk patients and value ≤0.175 indicating low-risk patients.The Kaplan-Meier method was used to calculate the survival rate and the Log-rank test was used for survival analysis. Results:(1) Analysis of factors influencing the pathological classification of HCC patients. Of 634 patients in the training set, there were 190 cases of proliferative HCC and 444 cases of non-proliferative HCC. Results of multivariate analysis showed that alpha fetoprotein (AFP) ≥400 μg/L and tumor diameter >5 cm were independent risk factors for pathological type of HCC as proli-ferative [ odds ratio=1.73, 1.88, 95% confidence interval ( CI) as 1.19-2.50, 1.30-2.71, P<0.05]. (2) Deep learning imaging features of HCC patients. In the training set of 634 patients, the probability predicted by MRI-based deep learning model was 84.8%(30.5%,95.4%) for proliferative HCC and 5.8%(3.2%,12.5%) for non-proliferative HCC, showing a significant difference between them ( Z=-16.01, P<0.05). (3) Evaluation of the efficacy of prediction model for proliferative HCC. In the training set, the AUC of clinical prediction model for proliferative HCC was 0.63(95% CI as 0.59-0.68, P<0.05), with sensitivity of 54.74% and specificity of 64.19%. The AUC of MRI-based deep learning prediction model was 0.90(95% CI as 0.87-0.93, P<0.05), with sensitivity of 80.53% and specificity of 86.94%. The AUC of combined MRI-based deep learning with clinical prediction model was 0.90 (95% CI as 0.87-0.93, P<0.05), with sensitivity of 83.16% and specificity of 86.04%. Results of Delong test showed that there was a significant difference between the combined MRI-based deep learning with clinical prediction model and the clinical prediction model ( P<0.05), and there was no signifi-cant difference between the combined MRI-based deep learning with clinical prediction model and the MRI-based deep learning prediction model ( P>0.05). Results of Hosmer-Lemeshow test showed good calibration for the clinical prediction model, the MRI-based deep learning prediction model and the combined MRI-based deep learning with clinical prediction model ( χ2=0.84, 6.38, 3.93, P>0.05), indicating that the predicted probabilities of these three prediction models matched the actual risk well. (4) Validation of the prediction model for proliferative HCC. Results of validation of the prediction model in internal validation set showed the AUC of MRI-based deep learning prediction model for proliferative HCC was 0.84(95% CI as 0.77-0.91, P<0.05), with sensitivity of 82.35% and specificity of 77.69%. Results of validation of the prediction model in external validation set showed the AUC of MRI-based deep learning prediction model for proliferative HCC was 0.81(95% CI as 0.71-0.92, P<0.05), with sensitivity of 70.00% and specificity of 81.69%. (5) Prognosis of HCC patients. Of the 906 patients, the 1-, 3-, and 5-year recurrence-free survival rates for 645 proliferative HCC patients were 56.9%, 31.4%, and 29.1%, respectively, and the 1-, 3-, and 5-year recurrence-free survival rates for 261 non-proliferative HCC patients were 88.8%, 68.6%, and 56.0%, respectively. There were significant differences in recurrence-free survival time between proliferative HCC and non-proliferative HCC patients of the training set, internal validation set and external validation set ( P<0.05). The 1-, 3-, 5-year recurrence-free survival rates for 331 high-risk HCC patients were 64.6%, 50.4%, 43.6%, versus 88.5%, 71.9%, 62.7% for 575 low-risk HCC patients. There were significant differences in recurrence-free survival time between high-risk HCC patients and low-risk HCC patients of the training set, internal validation set and external validation set ( P<0.05). Conclusion:The MRI-based deep learning model can effectively predict proliferative HCC and recurrence-free survival of patients before the surgery.

Purpose To explore factors influencing vaginal delivery during the first stage of labor using intrapartum ultrasound and to construct predictive models for delivery decision-making.Materials and Methods A total of 473 nulliparous women admitted to Heping Hospital,Northern Theater General Hospital from July to December 2021 were prospectively enrolled as the training set.Clinical data on admission and fetal biometric parameters(biparietal diameter,femur length,head circumference and abdominal circumference)measured within one week before delivery were collected.Ultrasound assessments of fetal position,angle of progression(AOP)and head-perineum distance(HPD)were performed during the first stage of labor.The latent phase group(n=255)was subdivided into vaginal delivery group(n=186)and cesarean section group(n=69);the active phase group(n=218)was divided into vaginal delivery group(n=168)and cesarean section group(n=50).The associations between fetal position,AOP,HPD and vaginal delivery were analyzed,and predictive models were constructed for the latent phase(model 1)and active phase(model 2).A validation set of 547 women from January to September 2022 was used to evaluate model performance via area under the curve(AUC),calibration curves and decision curve analysis.Results In the latent phase,multivariate regression identified maternal height(OR=3.970,P=0.002),pre-pregnancy body mass index(OR=0.893,P=0.036),labor onset type(OR=2.415,P=0.045),neonatal birth weight(OR=3.728,P=0.002),AOP(OR=11.649,P<0.001)and HPD(OR=4.240,P=0.004)as significant predictors.The training and validation sets showed AUCs of 0.917 and 0.869,respectively.Goodness-of-fit tests indicated excellent model calibration(χ2=3.437,P=0.904;χ2=10.877,P=0.209).Decision curve analysis demonstrated strong clinical utility.For the active phase,significant predictors included maternal height(OR=6.532,P<0.001),neonatal birth weight(OR=11.890,P<0.001),fetal position(OR=4.600,P=0.003),AOP(OR=7.229,P<0.001)and HPD(OR=4.722,P=0.005).AUCs were 0.943(training)and 0.906(validation),with good calibration(χ2=4.340,P=0.740;χ2=9.836,P=0.277)and clinical applicability.Conclusion First stage ultrasound assessment of fetal position,AOP and HPD correlates with delivery outcomes.The developed nomogram models combining these parameters with clinical factors provide valuable guidance for delivery decision-making.

Objective To investigate the clinical value of baseline 18F-fluorodeoxyglucose(18F-FDG)PET/CT metabolic parame-ters and certain clinical indicators in predicting the prognosis of patients with diffuse large B-cell lymphoma(DLBCL).Methods A retrospec-tive analysis was conducted on the baseline 18 F-FDG PET/CT data of 73 DLBCL patients who received R-CHOP treatment.Patients were divided into progression group(24 cases)and non-progression group(49 cases)based on disease progression within 2 years post-treatment.The lesion maximum standardized uptake value(SUVmax),tumour-to-liver blood pool SUVmax ratio(LLR)and tumour-to-mediastinal blood pool SUVmax ratio(L-BPR)were analyzed using receiver operating characteristic(ROC)curves.Kaplan-Meier(K-M)survival curves analysis were performed based on the optimal thresholds of SUVmax,LLR and L-BPR.x2 tests were used to analyze and compare the relationship between each parameter and disease progression.Indicators that were significant in the x2 tests were included in the multivariate Cox regression analysis.Results The area under the curve(AUC)for LLR,L-BPR,and SUVmax were 0.920,0.914,and 0.848,respectively,with optimal thresholds of 7.41,10.67,and 14.70.Based on these thresholds,K-M survival curves analysis showed that the 2-year progression-free survival(PFS)rates for DLBCL patients were 79.2％vs 30.8％(P＜0.001),74.3％vs 22.0％(P=0.009),and 79.5％vs 51.6％(P=0.002),respectively.Significant differences were observed between the progression and non-progression groups in terms of LLR,L-BPR,SUVmax,extranodal involvement,international prognostic index(IPI)score,lactate dehydrogenase(LDH)level,Eastern Cooperative Oncology Group(ECOG)score,and β2-microglobulin(β2-MG)levels(P＜0.05).Multivariate Cox regression analysis revealed that the IPI score and LLR were independent predictors affecting the 2-year PFS of DLBCL patients(P＜0.05).Conclusion Baseline 18F-FDG PET/CT metabolic parameter LLR and IPI score are inde-pendent factors for predicting the prognosis of DLBCL patients.

Objective To assess the prognostic value of serum lysine hydroxylase 3(PLOD3)and cytokeratin 19 fragment(CYFRA21-1)in predicting the efficacy of three-dimensional brachytherapy in patients with pulmonary metastases.Methods A total of 102 patients with lung metastases who underwent three-dimensional brachytherapy at our hospital were selected as the lung metastasis group from August 2021 to August 2023.During the same period,a control group consisting of 60 healthy individuals who underwent physical examinations was selected.The lung metastasis group was further divided into an effective group(n=66)and an ineffective group(n=36)based on therapeutic outcomes.Enzyme-linked immunosorbent assay was employed to measure the levels of serum PLOD3 and CYFRA21-1.Multiple logistic regression analysis was conducted to identify factors influencing the efficacy of three-dimensional brachytherapy in the lung metastasis group.Receiver operating characteristic(ROC)curves were used to assess the predictive value of serum PLOD3 and CYFRA21-1 for treatment efficacy.Results The levels of serum PLOD3 and CYFRA21-1 in the case group were(34.47±6.17)μg/L,(27.85±5.14)μg/L,respectively,which exhibited significantly higher values compared to those observed in the control group(7.26±2.21)μg/L,(9.31±2.46)μg/L(P<0.05).A positive correlation was found between serum PLOD3 and CYFRA21-1 in the Lung metastasis group(r=0.667,P=0.000).Logistic regression analysis revealed that multiple metastatic lesions along with elevated serum levels of PLOD3 and CYFRA21-1 were identified as risk factors for the efficacy of three-dimensional brachytherapy in patients with lung metastases(P<0.05).Furthermore,when combined with three-dimensional brachytherapy,the area under the curve(AUC)for serum PLOD3 and CYFRA21-1 was calcu-lated as 0.868,demonstrating a superior performance compared to individual measurements of either serum PLOD3 alone(AUC=0.815)or CYFRA21-1 alone(P<0.05).Conclusions The levels of serum PLOD3 and CYFRA21-1 are elevated in patients with lung metastases,exhibiting a significant correlation with the efficacy of three-dimensional brachytherapy.The combined utilization of these two biomarkers demonstrates a robust predictive value for treatment efficacy in patients suffering from lung metastases.

Objective To observe the effect of Kaixin Powder on neuroinflammation in APP/PS1 mice by regulating WDFY1/TLR4/NF-κB signaling pathway;To explore its mechanism of intervening in Alzheimer disease(AD).Methods APP/PS1 transgenic mice were randomly divided into model group,donepezil hydrochloride group(0.66 mg/kg),and Kaixin Powder low-,medium-and high-dosage groups(1.625,3.25,6.5 g/kg),C57BL/6J mice were set as blank control group,with 8 mice in each group,and corresponding drug intervention was given to medicaction group for 24 weeks.Morris water maze,Y maze and novel object recognition experiments were conducted to assess the cognitive function and learning and memory abilities of mice,immunohistochemical staining was used to detect the deposition of β-amyloid protein(Aβ)in hippocampus,the morphology and Nissl bodies of hippocampal CA1 neurons were observed using HE staining and Nissl staining,ELISA was used to detect the serum contents of interleukin(IL)-6,IL-17,IL-1β and tumor necrosis factor-α(TNF-α),Western blot was used to detect the protein expression of calcium-binding adapter molecule 1(Iba1),glial fibrillary acidic protein(GFAP),WDFY1,Toll like receptor 4(TLR4),Toll like receptor associated molecule(TRAM),TIR domain adapter protein(TRIF),NF-κB p65 and p-NF-κB p65 in hippocampal tissue,RT-qPCR was used to detect the mRNA expression of WDFY1,TLR4,TRAM,TRIF and NF-κB p65 in hippocampal tissue.Results Compared with the blank control group,the model group had significantly prolonged escape latency,reduced platform crossings,decreased autonomous reaction alternation rate and relative recognition index(P<0.05,P<0.01),with increased deposition of Aβ in hippocampal tissue(P<0.01),damaged morphological structure of neurons,reduced number of neurons and Nissl bodies,the serum contents of IL-6,IL-17,IL-1β and TNF-α significantly increased,the expression of Iba1,GFAP,WDFY1,TLR4,TRAM,TRIF,p-NF-κB p65 protein and WDFY1,TLR4,TRAM,TRIF mRNA in hippocampal tissue significantly increased(P<0.01).Compared with the model group,Kaixin Powder groups and donepezil hydrochloride group had significantly shortened escape latency and increased platform crossings,autonomous reaction alternation rate and relative recognition index(P<0.05,P<0.01),hippocampal Aβ deposition reduced in Kaixin Powder medium-,high-dosage groups and donepezil hydrochloride group,the morphological structure of neurons recovered,the number of neurons and Nissl bodies increased,the serum contents of IL-6,IL-17,IL-1β and TNF-α significantly decreased(P<0.05,P<0.01),and the protein expression of Iba1,GFAP,WDFY1,TLR4,TRAM,TRIF,p-NF-κB p65 and the mRNA expressions of WDFY1,TLR4,TRAM and TRIF in hippocampal tissue significantly decreased(P<0.05,P<0.01).Conclusion Kaixin Powder can improve cognitive function and learning and memory abilities in AD model mice,alleviate hippocampal neuron damage and Aβ deposition,inhibit the activation of microglia and astrocytes,and thereby reduce serum inflammatory cytokine release.Its mechanism may be related to regulating the WDFY1/TLR4/NF-κB signaling pathway to inhibit neuroinflammation.