Objective To observe the value of contrast-enhanced ultrasound(CEUS)for diagnosing malignant adnexal tumors.Methods Totally 112 patients with single adnexal masse were retrospectively enrolled and divided into benign adnexal tumor group(benign group,n=73)and malignant adnexal tumor group(malignant group,n=39).Clinical data,laboratory indicators,ovarian-adnexal ultrasound reporting and data system(O-RADS)classification based on conventional ultrasound(US),CEUS manifestations and CEUS classification of benign and malignant tumors were compared between groups.Multivariable logistic regression analysis of clinical and laboratory indicators being statistically different between groups,as well as US O-RADS classification and CEUS classification was performed to screen the independent predictors of malignant adnexal tumors,and combined models were constructed using forward stepwise regression method.The efficacy of each independent predictor and combined model for diagnosing malignant adnexal tumors was analyzed.Results Statistical differences of carbohydrate antigen 125(CA125),US O-RADS classification,enhancement time and level of CEUS,as well as CEUS classification were found between groups(all P＜0.05).CA125,US O-RADS classification and CEUS classification were all independent predictors of malignant adnexal tumors(all P＜0.05).Combined model Ⅰ,Ⅱ and Ⅲ were constructed based on CA125+CEUS classification,US O-RADS classification+CEUS classification and CA125+US O-RADS classification+CEUS classification,respectively.The area under the curve(AUC)of single CA125 level,US O-RADS classification,CEUS classification and combined model Ⅰ,Ⅱ and Ⅲ for diagnosing malignant adnexal tumor was 0.708,0.809,0.908,0.918,0.945 and 0.954,respectively.AUC of combined model Ⅲ was higher than that of combined model Ⅰ(Z=-2.142,P=0.032),while no significant difference of AUC was found between combined model Ⅱ and Ⅰ nor Ⅱ and Ⅲ(both P＞0.05).Conclusion CEUS could be used to effectively diagnose malignant adnexal tumor.Combining with CA125 level and US O-RADS classification could significantly improve its diagnostic efficacy.

Rheumatoid arthritis(RA)is characterized by bidi-rectional bone remodeling imbalance,clinically termed the "high resorption-low formation" paradox,stemming not only from osteoclast hyperactivation but also critically involving pro-found suppression of osteoblast differentiation and function.No-tably,this suppression cannot be fully attributed to osteoclast hyperactivity;synovium-resident immune cells exert a pivotal regulatory influence through distinct mechanisms.This review systematically examines how synovial immune cells orchestrate bone remodeling in RA through both paracrine cytokine networks and direct cell-cell communication with bone lineage cells,thereby perturbing physiological homeostasis and driving patho-logical progression.These mechanistic revelations yield innova-tive perspectives on RA pathogenesis,positioning immune-medi-ated osteoimmune dysregulation as a promising therapeutic fron-tier for targeted intervention.

Objective To explore the application value of combining the ultrasound breast imaging reporting and data system(BI-RADS)classification with serum fibroblast growth factor receptor 1(FGFR1)and growth differentiation factor 3(GDF3)in the differential diagnosis of benign and malignant breast masses.Methods A total of 159 patients with breast masses were selected and divided into the benign mass group(n=83)and the malignant mass group(n=76)based on postoperative pathological diagnosis.All patients underwent ultrasound examination,and enzyme-linked immunosorbent assay(ELISA)was applied to detect serum levels of FGFR1 and GDF3.Receiver operating characteristic(ROC)curve was applied to analyze the diagnostic value of ultrasound BI-RADS classification and serum FGFR1 and GDF3 levels for benign and malignant breast masses.Kappa test was applied to analyze the consistency between various diagnostic methods and pathological diagnosis.Results The serum levels of FGFR1 and GDF3,the proportions of irregular morphology,unclear boundaries,spiculation,microcalcifications,blood flow grade Ⅱ-Ⅲ and posterior echo attenuation,RI and PI were higher in the malignant tumor group than those in the benign tumor group(P＜0.05).The area under the curve(AUC)of FGFR1,GDF3 and ultrasound BI-RADS classification in the differential diagnosis of benign and malignant breast masses separately and in combination was 0.802(95%CI:0.732-0.871),0.817(95%CI:0.751-0.884),0.848(95%CI:0.784-0.912)and 0.956(95%CI:0.918-0.993),respectively.The combined diagnosis was more effective than that of the individual diagnosis of each indicator.The consistency between the individual and combined diagnosis of benign and malignant breast masses and pathological diagnosis showed that the Kappa values were 0.517,0.514,0.688 and 0.912,respectively,with the highest consistency observed in the combined diagnosis(P＜0.05).Conclusion Ultrasound BI-RADS classification combined with serum FGFR1 and GDF3 has high application value in the differential diagnosis of benign and malignant breast masses.

Objective:To predict mechanical complications (MC) following spinal deformity surgery for adult spine deformity (ASD) using machine learning models, identify key risk factors, and develop a visualizable tool for individualized risk assessment.Methods:Clinical and radiological data from 525 patients with ASD who underwent surgery in our hospital between January 2017 and December 2021 were collected. Patients were randomly assigned to a training set (70%) and a test set (30%) for model development. The cohort included 88 males and 437 females, with a mean age of 42.2±18.1 years. Variables included demographic data, comorbidities, local and systemic radiological parameters, paraspinal muscle fat infiltration (FI), and vertebral bone quality (VBQ) scores. Multiple machine learning algorithms: Random Forest (RF), Gaussian Naive Bayes (GNB), Light GBM, Support Vector Machine (SVM), XGBoost (XGB), and Logistic Regression (LR) were trained and evaluated. Model performance was compared using the receiver operating characteristic curve (ROC) and precision-recall curve (PRC). SHAP (Shapley Additive Explanations) was used to rank risk factors, while LIME (Local Interpretable Model-Agnostic Explanations) was applied to visualize MC risk in individual cases.Results:Of the 525 patients, 135 (25.7%) developed postoperative MC. Among these, 80 (59.3%) experienced proximal junction kyphosis or failure (PJK/PJF), 7 (5.2%) had distal junction kyphosis or failure (DJK/DJF), 28 (20.7%) sustained rod fractures, and 29 (21.5%) showed significant loss of correction. In the validation cohort, the RF model achieved the highest area under the curve (AUC=0.80), followed by GNB (0.77), XGB (0.76), LR (0.74), LightGBM (0.73), and SVM (0.66). The RF model also demonstrated the best PRC value (0.58), highest sensitivity (0.65), and lowest Brier score (0.20). GNB, Light GBM, and LR models achieved the highest accuracy (0.78 each), while LightGBM exhibited the highest specificity (0.93). SHAP analysis identified higher preoperative VBQ scores, larger T 1 pelvic angle (TPA), and higher paraspinal muscle FI as the main risk factors for MC. Based on the RF model, a LIME-based tool was successfully constructed for individualized MC risk estimation. Conclusion:The RF model demonstrated the best overall predictive performance for MC. A machine learning-based prediction model has the potential to provide valuable guidance for surgical decision-making in ASD patients.

Aim To explore the mechanism of the syn-ergistic effect of the ferroptosis inducer erastin com-bined with shikonin in promoting ferroptosis in human hypertrophic scar fibroblasts(HSFBs).Methods Hypertrophic scar tissues provided by the General Hos-pital of Ningxia Medical University were collected,and HSFBs were extracted.HSFBs were identified by HE staining and immunofluorescence.The inhibitory rates of Era and SHK on HSFBs at different concentrations were detected by CCK-8 assay,and the IC50 value was calculated.CompuSyn software was used to calculate the co-use index(CI).Control group,Erastin(Era)group,shikonin(SHK)group and Era+SHK group were set up,and the number and morphological chan-ges of cells were observed after 24 hours of interven-tion.The ability of cell migration and invasion was de-tected by scratch test and Transwell test.The changes of malondialdehyde(MDA),total iron ion and reactive oxygen species(ROS)were detected by corresponding biochemical kits.The expressions of collagen I,α-SMA and GOT1,SLC7A11,GPX4 and FTH1 were detected by Western blot.Results The IC50 value of Era and SHK of primary HSFBs was 2.22 μmol·L-1 and 3.94μmol·L-1 respectively,which was used as the single drug concentration for subsequent experiments.The CompuSyn software was employed to calculate the CI value when the two drugs were used in combination,and the concentrations corresponding to CI=0.39597(Era:1.2 μmol·L-1+SHK:1.5 μmol·L-1)were selected as subsequent combination concentrations(Because when CI was equal to 0.395 97,the concen-tration of each drug was lower than the concentration of single drug,and the inhibition rate of combined drug was greater than 50％).Compared with the monother-apy group,the number of HSFBs in the SHK+Era group was significantly reduced,cell membrane showed breakage and vesiculation,cell wrinkling became smal-ler,and cytoplasm was concentrated.The migration and invasion ability of HSFBs in the SHK+Era group were obviously weakened(P＜0.05),and the expres-sion of fibrosis-related proteins collagen Ⅰ and α-SMA was reduced(P＜0.05);the contents of MDA,total i-ron ions,and ROS in HSFBs of the SHK+Era group increased(P＜0.05),and the protein expression lev-els of SLC7A11,GOT1,GPX4,and FTH1 further de-creased(P＜0.05).Conclusions Erastin in combi-nation with shikonin can synergistically inhibit the pro-liferation,migration and fibrosis levels of HSFBs.The mechanism may be that erastin enhances the inhibition of shikotin on GOT1,increases the levels of cellular i-ron ions,ROS,and lipid peroxides,thereby promoting ferroptosis in HSFBs.

ObjectivePhotoacoustic pump-probe imaging can effectively eliminate the interference of blood background signal in traditional photoacoustic imaging, and realize the imaging of weak phosphorescence molecules and their triplet lifetimes in deep tissues. However, background differential noise in photoacoustic pump-probe imaging often leads to large fitting results of phosphorescent molecule concentration and triplet lifetime. Therefore, this paper proposes a novel triplet lifetime fitting method for photoacoustic pump-probe imaging. By extracting the phase of the triplet differential signal and the background noise, the fitting bias caused by the background noise can be effectively corrected. MethodsThe advantages and feasibility of the proposed algorithm are verified by numerical simulation, phantom and in vivo experiments, respectively. ResultsIn the numerical simulation, under the condition of noise intensity being 10% of the signal amplitude, the new method can optimize the fitting deviation from 48.5% to about 5%, and has a higher exclusion coefficient (0.88>0.79), which greatly improves the fitting accuracy. The high specificity imaging ability of photoacoustic pump imaging for phosphorescent molecules has been demonstrated by phantom experiments. In vivo experiments have verified the feasibility of the new fitting method proposed in this paper for fitting phosphoometric lifetime to monitor oxygen partial pressure content during photodynamic therapy of tumors in nude mice. ConclusionThis work will play an important role in promoting the application of photoacoustic pump-probe imaging in biomedicine.

Rheumatoid arthritis(RA)is characterized by bidi-rectional bone remodeling imbalance,clinically termed the "high resorption-low formation" paradox,stemming not only from osteoclast hyperactivation but also critically involving pro-found suppression of osteoblast differentiation and function.No-tably,this suppression cannot be fully attributed to osteoclast hyperactivity;synovium-resident immune cells exert a pivotal regulatory influence through distinct mechanisms.This review systematically examines how synovial immune cells orchestrate bone remodeling in RA through both paracrine cytokine networks and direct cell-cell communication with bone lineage cells,thereby perturbing physiological homeostasis and driving patho-logical progression.These mechanistic revelations yield innova-tive perspectives on RA pathogenesis,positioning immune-medi-ated osteoimmune dysregulation as a promising therapeutic fron-tier for targeted intervention.

Objective To propose a whole-life cycle management model for valvular heart disease (VHD), systematically elucidate its underlying logic and implementation pathways, and concurrently review and analyze its preliminary application outcomes. Methods Since 2020, West China Hospital of Sichuan University has established a management system encompassing "assessment-decision-intervention-follow-up", including: (1) a risk-stratified, tiered management pathway; (2) six core functions ("promotion, screening, prevention, diagnosis, treatment, and rehabilitation") coordinated by disease-specific managers; (3) an intelligent decision support information platform; and (4) a collaborative network of multidisciplinary teams and regional academic alliances. To evaluate the effectiveness of this management model, we retrospectively included three cohorts: (1) the population screened by echocardiography from 2020 to 2024, analyzing the detection rate of aortic valve disease and risk stratification; (2) patients enrolled in the whole-life cycle management from April 2021 to December 2024, assessing follow-up outcomes, hospital satisfaction, and changes in quality of life; (3) patients who underwent transcatheter aortic valve replacement (TAVR) from January 2022 to January 2024, evaluating the one-year all-cause mortality rate, perioperative complications, and improvements in New York Heart Association (NYHA) classification. Results Between 2020 and 2024, a total of 583 874 individuals underwent echocardiographic screening. A total of 48 089 patients with aortic valve disease were identified, including 3 401 (7.1%) high-risk patients, 18 657 (38.8%) moderate-risk patients, and 26 031 (54.1%) low-risk patients. Among them, 2 417 patients were enrolled in whole-life cycle management. Patient satisfaction scores showed a yearly increase, rising from 73.89 points before 2020 to 93.74 points in 2024. The 1-year mortality rate in the TAVR cohort decreased to 5.3%, significantly lower than the 8.2% observed under early standard management between 2014 and 2019 (P<0.01). Conclusion Through process optimization and resource integration, the VHD whole-life cycle management model has demonstrated significant effectiveness in standardizing diagnostic and follow-up procedures, enhancing patient satisfaction and quality of life, and reducing mortality. These outcomes highlight its practical value for broader implementation in China.

Objective:To predict mechanical complications (MC) following spinal deformity surgery for adult spine deformity (ASD) using machine learning models, identify key risk factors, and develop a visualizable tool for individualized risk assessment.Methods:Clinical and radiological data from 525 patients with ASD who underwent surgery in our hospital between January 2017 and December 2021 were collected. Patients were randomly assigned to a training set (70%) and a test set (30%) for model development. The cohort included 88 males and 437 females, with a mean age of 42.2±18.1 years. Variables included demographic data, comorbidities, local and systemic radiological parameters, paraspinal muscle fat infiltration (FI), and vertebral bone quality (VBQ) scores. Multiple machine learning algorithms: Random Forest (RF), Gaussian Naive Bayes (GNB), Light GBM, Support Vector Machine (SVM), XGBoost (XGB), and Logistic Regression (LR) were trained and evaluated. Model performance was compared using the receiver operating characteristic curve (ROC) and precision-recall curve (PRC). SHAP (Shapley Additive Explanations) was used to rank risk factors, while LIME (Local Interpretable Model-Agnostic Explanations) was applied to visualize MC risk in individual cases.Results:Of the 525 patients, 135 (25.7%) developed postoperative MC. Among these, 80 (59.3%) experienced proximal junction kyphosis or failure (PJK/PJF), 7 (5.2%) had distal junction kyphosis or failure (DJK/DJF), 28 (20.7%) sustained rod fractures, and 29 (21.5%) showed significant loss of correction. In the validation cohort, the RF model achieved the highest area under the curve (AUC=0.80), followed by GNB (0.77), XGB (0.76), LR (0.74), LightGBM (0.73), and SVM (0.66). The RF model also demonstrated the best PRC value (0.58), highest sensitivity (0.65), and lowest Brier score (0.20). GNB, Light GBM, and LR models achieved the highest accuracy (0.78 each), while LightGBM exhibited the highest specificity (0.93). SHAP analysis identified higher preoperative VBQ scores, larger T 1 pelvic angle (TPA), and higher paraspinal muscle FI as the main risk factors for MC. Based on the RF model, a LIME-based tool was successfully constructed for individualized MC risk estimation. Conclusion:The RF model demonstrated the best overall predictive performance for MC. A machine learning-based prediction model has the potential to provide valuable guidance for surgical decision-making in ASD patients.

Vertebral refracture following percutaneous vertebral augmentation (PVA) is commonly seen in elderly patients with osteoporotic thoracolumbar compression fractures (OTLCF). It can lead to recurrent pain, loss of vertebral height, progression of kyphosis, and even neurological dysfunction, significantly impairing patients′ quality of life. Current diagnosis and treatment face multiple challenges, including high misdiagnosis rate, difficulty in choosing between surgical and non-surgical treatment options, lack of standardized surgical protocols, interference from intralesional bone cement during procedures, inadequate stability of internal fixation in osteoporotic bone, and suboptimal compliance of anti-osteoporotic therapy. Establishing a standardized diagnostic and therapeutic framework is urgently needed. To standardize the management process and improve outcomes for vertebral refractures after PVA in elderly OTLCF patients, Spinal Trauma Group of the Orthopedic Branch of Chinese Medical Doctor Association organized experts in the field to develop Guideline for the diagnosis and treatment of vertebral refracture after percutaneous vertebral augmentation in elderly patients with osteoporotic thoracolumbar compression fractures ( version 2025), based on current literature and clinical experience, and adhering to principles of scientific rigor and clinical applicability. A total of 11 recommendations were proposed, encompassing diagnosis, treatment, and rehabilitation of vertebral refracture after PVA in elderly patients with OTLCF, aiming to provide a foundation for a standardized management.