Objective:To develop a quality control model for anal sphincter ultrasound images and validate its diagnostic performance across multiple centers.Methods:A retrospective analysis was conducted on anal sphincter ultrasound images from seven medical centers in China between May 2019 and June 2022. A total of 7 040 images from 3 116 patients were included and divided into a training set（4 912 images）and a validation set（2 128 images）. The images were classified as standard or non-standard images by three experts. Three models were developed based on different image feature extraction methods：a single-branch model，a multi-branch weighted model，and a multi-branch ensemble model. The diagnostic performance of each model was evaluated using the area under the ROC curve（AUC），sensitivity，specificity，accuracy，positive predictive value，and negative predictive value，respectively. The optimal model was selected and compared with the performance of 4 doctors with varying experience levels. Sixty days later，the images with the assistance of the model's output were reassessed by the doctors to evaluate its impact on manual quality control.Results:① Among the 3 models，the multi-branch ensemble model demonstrated the highest AUC and sensitivity，with an AUC of 0.966（95% CI=0.958 - 0.974），a sensitivity of 91.83%，and a specificity of 91.41%. This model was named M quality. ② M quality's AUC was slightly lower than that of Senior A and B（0.966 vs. 0.976，0.976，and P<0.05），its sensitivity was slightly lower than that of Senior A（91.83% vs. 95.61%， P<0.001）but comparable to Senior B（91.83% vs. 92.89%， P=0.315），its specificity was slightly lower than Senior A and B（91.41% vs. 94.44%，98.18%，and P<0.05）. However，M quality significantly outperformed Junior A and B in AUC and sensitivity（AUC：0.966 vs. 0.850，0.818；sensitivity：91.83% vs. 84.90%，61.46%；all P<0.001），its specificity was higher than that of Junior A（91.41% vs. 80.28%， P<0.001）but lower than that of Junior B（91.41% vs. 95.96%， P<0.001）. ③ With model assistance，Senior B's sensitivity（92.89% vs. 94.20%， P=0.001）and Senior A's specificity（94.44% vs. 96.56%， P<0.001）improved significantly. Junior A and B showed significant improvements in AUC and sensitivity（AUC：0.931 vs. 0.850，0.914 vs. 0.818；sensitivity：91.83% vs. 84.90%，89.53% vs. 61.46%；all P<0.001）. After model assistance，Junior A's specificity increased（93.62% vs. 80.28%， P<0.001），while Junior B's specificity decreased（91.60% vs. 95.96%， P=0.013）. Conclusions:This study develops a quality control model for anal sphincter ultrasound images with robust diagnostic performance，approaching the level of seniors. The model significantly enhances the image quality assessment capabilities of juniors，demonstrating promising clinical application potential.

Objective:To screen the optimal machine learning model for predicting the recurrence condition of hepatocellular carcinoma (HCC) at different time points post-surgery, based on the cutoff value of the Ki67 positive proliferation index condition calculated from recurrence-free survival and combined with various clinical features.Methods:retrospective study included initially treated patients with solitary HCC who underwent radical surgery at the Fifth Medical Center of the PLA General Hospital from January 2013 to March 2023. Data included general clinical data, preoperative laboratory parameters, and surgical pathology information about the subjects. The postoperative recurrence status was assessed by querying the medical record system or by telephone follow-up. The Ki67 positive index cutoff value was determined by the X-tile software based on the patient's recurrence-free survival status and time analysis. Survival rates were calculated using the Kaplan-Meier method, and survival curves were plotted. The study population was randomly divided into training and testing groups in a 7:3 ratio using a computer-generated random number method. The minimum redundancy maximum relevance (mRMR) method was used for feature variable selection. Predictive models for postoperative HCC recurrence conditions in patients with HCC were constructed using random forest, support vector machine, logistic regression, and gradient boosting decision tree machine learning algorithms. Inter-group comparisons for continuous data were performed using the t-test or Mann-Whitney U test. Inter-group comparisons of enumeration data were performed using the Pearson χ2 test, continuity-corrected χ2 test, or Fisher's exact test. Results:The cutoff values for the Ki67 positivity index were 0.3 and 0.5 in 510 cases, with a follow-up time ranging from 1.2 to 11.4 years (median: 6.2 years). The recurrence-free survival time was between 1 and 135 months (median: 32 months), with recurrence-free survival rates post-surgery at 1, 2, 3, and 5 years were 87.5%, 77.1%, 61.2%, and 54.5%, respectively. The top five variables predicted HCC recurrence and non-recurrence conditions following surgical follow-up at 6 months, 1 year, 2 years, and beyond 2 years, in accordance with information obtained by the mRMR screen out. The Ki67 positivity index screened a successfully constructed machine learning model to predict HCC recurrence and non-recurrence conditions following surgical follow-up at 6 months, 1 year, 2 years, and beyond 2 years. The machine learning model based on the gradient boosting decision tree algorithm had the best prediction performance among them (areas under the receiver operating characteristic curves for predicting HCC recurrence within six months in the training and validation sets were 0.996 and 0.946, and accuracies were 0.972 and 0.935, respectively).Conclusion:A machine learning model was successfully constructed using the Ki67 positivity index combined with four readily available clinical features to predict HCC recurrence. The machine learning model based on the gradient boosting decision tree algorithm demonstrated the best performance in terms of predicting HCC recurrence within six months after surgery.

Angiogenesis is a key link in the development of atherosclerotic plaques.Inhibiting angiogenesis con-tributes to plaque stabilization and reduces the risk of related cardiovascular events.Apolipoprotein A1 binding protein(A1 BP),an important secretory protein,has been shown in a growing body of research to play a significant role in the reg-ulation of angiogenesis.This article aims to elucidate the mechanisms of action of A1 BP on angiogenesis and cardiovascu-lar diseases,thereby providing new perspectives for the clinical treatment of cardiovascular diseases.

Objective:To explore the regulatory mechanism of voltage-dependent anion channel 1(VDAC1) on the proliferation, migration and invasion of lung adenocarcinoma(LUAD) cells.Methods:This study employed a combination of bioinformatics and experimental validation methods, conducting bioinformatics analysis and cytological experimental validation in the central laboratory of the School of Medicine, Anhui University of Science and Technology from February 2023 to August 2024.Clinical histological specimen validation was performed using immunohistochemistry, and a retrospective analysis was conducted on 5 cases of lung adenocarcinoma and adjacent samples from Huai′an First People′s Hospital affiliated with Nanjing Medical University. The TCGA network database was analyzed for the expression pattern, prognostic value, and functional enrichment of VDAC1 in LUAD. A549 cells with VDAC1 knockdown and H1650 cells with VDAC1 overexpression were established through lentiviral transfection. The expression difference of VDAC1 protein in LUAD and adjacent tissue specimens was detected by immunohistochemistry.The effects of VDAC1 on the proliferation, migration, and invasion capabilities were explored through CCK8 assay, scratch healing assay, and Transwell assay.The activation levels of epithelial-mesenchymal transition (EMT) marker proteins, cell cycle-dependent kinases, and molecules in the PI3K/AKT/mTOR signaling pathway were detected by Western blot.Results:Bioinformatics analysis revealed that VDAC1 was highly expressed in LUAD cells ( P<0.000 1) and was an independent risk factor for LUAD ( P<0.000 1). Functional enrichment analysis showed significant enrichment of the PI3K/AKT/mTOR, G2M checkpoint, and P53 signaling pathways ( P<0.001). Compared to adjacent control tissues, the expression level of VDAC1 protein is higher in lung adenocarcinoma tissues.Overexpression of VDAC1 promoted the proliferation ( P<0.000 1), migration, and invasion( P<0.01) of H1650 cells, while knockdown of VDAC1 inhibited the proliferation ( P<0.000 1), migration, and invasion ( P<0.05) of A549 cells.Western Blot experiments showed that compared to the control group, the expression levels of vimentin (1.10±0.11 vs 2.39±0.15, P<0.001), N-cadherin (0.94±0.12 vs 2.72±0.06, P<0.001), CDK1 (0.93±0.04 vs 1.53±0.03, P<0.000 1), CDK2 (1.04±0.13 vs 2.29±0.06, P<0.001), CDK4 (0.90±0.03 vs 2.00±0.11, P<0.01), p-PI3K (1.08±0.13 vs 1.85±0.12, P<0.01), and p-AKT (1.03±0.11 vs 1.69±0.06, P<0.001) were increased in H1650 cells overexpressing VDAC1, while E-cadherin expression decreased (2.18±0.14 vs 0.997±0.11, P<0.001).In contrast, in A549 cells with VDAC1 knockdown, the expression levels of vimentin (1.70±0.26 vs 0.97±0.09, P<0.05), N-cadherin (1.98±0.25 vs 1.03±0.06, P<0.05), CDK1 (1.13±0.03 vs 0.95±0.02, P<0.01), CDK2 (2.29±0.12 vs 0.92±0.10, P<0.001), CDK4 (1.71±0.096 vs 1.12±0.11, P<0.01), p-PI3K (1.67±0.09 vs 0.97±0.03, P<0.001), and p-AKT (1.53±0.04 vs 1.02±0.03, P<0.000 1) decreased, while E-cadherin expression increased (1.04±0.04 vs 1.85±0.26, P<0.05). Conclusions:VDAC1 may promote the proliferation, migration, and invasion of LUAD cells by activating EMT and cyclin-dependent kinases through the PI3K/AKT/mTOR pathway.

OBJECTIVE: To review and summarize the research progress on repairing segmental bone defects using three-dimensional (3D)-printed bone scaffolds combined with vascularized tissue flaps in recent years. METHODS: Relevant literature was reviewed to summarize the application of 3D printing technology in artificial bone scaffolds made from different biomaterials, as well as methods for repairing segmental bone defects by combining these scaffolds with various vascularized tissue flaps. RESULTS: The combination of 3D-printed artificial bone scaffolds with different vascularized tissue flaps has provided new strategies for repairing segmental bone defects. 3D-printed artificial bone scaffolds include 3D-printed polymer scaffolds, bio-ceramic scaffolds, and metal scaffolds. When these scaffolds of different materials are combined with vascularized tissue flaps ( e.g., omental flaps, fascial flaps, periosteal flaps, muscular flaps, and bone flaps), they provide blood supply to the inorganic artificial bone scaffolds. After implantation into the defect site, the scaffolds not only achieve structural filling and mechanical support for the bone defect area, but also promote osteogenesis and vascular regeneration. Additionally, the mechanical properties, porous structure, and biocompatibility of the 3D-printed scaffold materials are key factors influencing their osteogenic efficiency. Furthermore, loading the scaffolds with active components such as osteogenic cells and growth factors can synergistically enhance bone defect healing and vascularization processes. CONCLUSION The repair of segmental bone defects using 3D-printed artificial bone scaffolds combined with vascularized tissue flap transplantation integrates material science technologies with surgical therapeutic approaches, which will significantly improve the clinical treatment outcomes of segmental bone defect repair.
Printing, Three-Dimensional ; Tissue Scaffolds ; Humans ; Surgical Flaps/blood supply* ; Tissue Engineering/methods* ; Plastic Surgery Procedures/methods* ; Bone and Bones/surgery* ; Biocompatible Materials ; Bone Regeneration ; Bone Transplantation/methods* ; Bone Substitutes ; Osteogenesis

OBJECTIVE: To summarize the biomechanical research progress on different fixation methods in medial opening-wedge high tibial osteotomy (MOWHTO) and provide references for selecting appropriate fixation methods in clinical applications of MOWHTO for treating knee osteoarthritis (KOA). METHODS: Recent domestic and international literature on the biomechanical studies of MOWHTO fixation methods was reviewed to analyze the characteristics and biomechanical performance of various fixation techniques. RESULTS: The medial-specific osteotomy plate system has become the mainstream due to its high stiffness and stability, but issues such as soft tissue irritation and stress shielding remain. The use of filler blocks significantly enhances fixation stability and promotes bone healing when the osteotomy gap is large, reducing axial displacement by 73%-76% and decreasing plate stress by 90%. Auxiliary screws improve axial and torsional stability, particularly in cases with large correction angles, effectively preventing lateral hinge fractures. Alternative fixation methods like external fixators hold unique clinical value by minimizing soft tissue irritation and allowing postoperative adjustment. CONCLUSION There is currently no unified standard for selecting MOWHTO fixation methods. Clinical decisions should comprehensively consider factors such as bone quality, correction angle, and postoperative rehabilitation needs.
Humans ; Osteotomy/instrumentation* ; Biomechanical Phenomena ; Tibia/surgery* ; Bone Plates ; Osteoarthritis, Knee/surgery* ; Bone Screws ; External Fixators ; Knee Joint/surgery*

To compare the efficacy of remote rehabilitation training versus in-hospital rehabilitation training in improving motor function and quality of life in patients with Parkinson's disease (PD).

Objective To analyze the predictive value of spermatic vein diameter in diagnosing occult oblique inguinal hernia in children.Methods A total of 93 children of oblique inguinal hernia were admitted to Hangzhou Linping District Maternal &Child Health Care Hospital from August 2021 to August 2023 as research objects,including 15 with 30 sides of bilateral dominant hernia and 78 with 78 sides of unilateral dominant hernia.Among them,21 with 21 sides of contralateral recessive hernia were found by laparoscopic exploration in unilateral dominant hernia.The 108 sides of dominant hernia were used as dominant hernia group and 21 sides of occult hernia group as recessive hernia group.According to different ages,the patients were divided into 1 to 3 years old group 60 cases,4 to 6 years old group 33 cases;Children with oblique inguinal hernia were divided into＜2 years group(68 cases)and ≥2 years group(25 cases).The color ultrasound diagnostic instrument uses a 7.5MHz linear transducer to measure the diameter of the spermatic vein in the inguinal region of the child using blood flow imaging with a signal displayed at 2mm/s.Receiver operating characteristic(ROC)curve analysis of the predictive value of spermatic vein diameter for the diagnosis of occult inguinal hernia in children.Results Compared with occult hernia group,diameter of spermatic cord was increased in dominant hernia group(P＜0.05).Compared with overt hernia group,diameter of spermatic cord in＜2 year group and ≥2 year group was smaller,and difference was statistically significant(P＜0.05).In prediction of disease diagnosis with different age and course of disease,sensitivity of 1 to 3 years old was lower than that of 4 to 6 years old,and specificity was higher.The sensitivity of ≥2 years group was lower than that of＜2 years group.The specificity was higher and difference was statistically significant(P＜0.05).Conclusion diameter of spermatic vein can be used to predict the diagnosis of occult oblique inguinal hernia in children with high sensitivity and specificity.

Klebsiella pneumoniae,as a clinically prevalent opportunistic pathogen,ranks as the second most com-monly detected pathogen in clinical isolates in China.The extensive clinical use of carbapenem antibiotics has led to a high global detection rate of carbapenem-resistant K.pneumoniae(CRKP).Characterized by complex resist-ance mechanisms and diverse evolutionary pathways,CRKP infections pose significant challenges in prevention and treatment,with high associated mortality rates,creating substantial obstacles for clinical anti-infective therapy.In recent years,the emergence and global spread of carbapenem-resistant hypervirulent K.pneumoniae(CR-hvKP)have escalated into a major public health threat.Notably,hypervirulent K.pneumoniae isolates carry-ing carbapenem resistance genes are rapidly disseminating worldwide,causing fatal infections even in immunocom-petent individuals.This article systematically reviews the latest research advances on the resistance mechanisms,evolutionary pathways,adaptive changes,and clinical management strategies of CR-hvKP,aiming to deepen un-derstanding of this"superbug"and provide a theoretical foundation for clinical prevention and control.

Objective:To develop and validate machine learning models for predicting the cumulative live birth rate (CLBR) following in vitro fertilization (IVF) and to analyze key predictive features using SHAP values. Methods:This retrospective study included data from patients who underwent IVF-embryo transfer at the Department of Reproductive Medicine, Baoding Maternal and Child Health Hospital, between January 2017 and December 2022. Patients were categorized into two groups based on live birth outcome: the live birth group ( n=1 036) and the non-live birth group ( n=756). The dataset was randomly divided into a training set and a validation set in a ratio of 7∶3. Five algorithms were utilized for model development: logistic regression, random forest, extreme gradient boosting (XGBoost), support vector machine, and neural networks. Model performance was assessed using the area under the receiver operating characteristic (AUC) curve, F1 score, and calibration curves. Clinical decision curve analysis (DCA) was employed to evaluate the clinical utility of the models. SHAP values were used to interpret feature importance in the XGBoost model and enhance its explainability. Results:The XGBoost model demonstrated the best performance in predicting CLBR,with accuracy of 72.44%, AUC of 0.775, and F1 score of 0.654, accuracy and F1 score outperforming logistic regression (accuracy was 70.02%, F1 score was 0.585), random forest (accuracy was 71.69%, F1 score was 0.606), support vector machine (accuracy was 70.20%, F1 score was 0.607), and neural network (accuracy was 68.72%, F1 score was 0.560). The calibration curve of XGBoost closely aligned with the diagonal line, indicating that the predicted probabilities were very close to the actual outcomes, demonstrating good calibration. DCA indicated that the XGBoost model provided higher net benefits across a wide range of clinical decision thresholds. SHAP value analysis identified number of previous IVF failures, antral follicle count, anti-Müllerian hormone level, percentage of normal sperm morphology, and sperm DNA fragmentation index as key predictors of CLBR.Conclusion:The XGBoost model exhibits excellent predictive performance and calibration for CLBR, with SHAP values providing important insights into feature importance. This model has the potential to support the development of personalized treatment strategies in clinical practice. However, its generalizability needs to be validated using external datasets to ensure its applicability to diverse populations.