Objective In response to the clinical needs for personalized wrist orthoses,a topological optimization design method was proposed to achieve an integrated macro-and micro-structural optimization of a personalized,lightweight,and comfortable wrist orthosis.Methods A composite biomechanical finite element model of the wrist orthosis and upper limb was established to quantify the effects of the orthosis geometry on its fixation performance and comfort.A multi-condition topological optimization and microstructure design approach was employed to optimize the non-load-bearing areas of the orthosis.The orthosis was manufactured using three-dimensional(3D)-printed polyether ether ketone(PEEK),and the feasibility of the design was validated.Results While maintaining mechanical strength,the weight of the 3D-printed PEEK orthosis was reduced by 28％compared to the traditional orthoses.Both the pressure at the skin contact interface and the results of a subjective questionnaire indicated that test subjects experienced a high level of comfort wearing the orthosis.Conclusions The orthosis design achieved personalization,lightweight structure,and high comfort while ensuring mechanical strength and fixation performance.

Objective:To retrospectively evaluate the clinical efficacy and safety of total 3D laparo-scopic ileal ureters replacement for bilateral ureters combined with bladder augmentation in patients with post-radiotherapy long-segment bilateral ureteral strictures and contracted bladder.Methods:Clinical data of two patients(aged 72 and 54 years)with radiation-induced long-segment bilateral ureteral stric-tures and reduced bladder capacity,treated at the Sixth Affiliated Hospital of Jinan University from Octo-ber 2023 to June 2024,were analyzed.Both presented with bilateral flank pain,recurrent chills/fever,urinary frequency,and urgency.Preoperative ureteral stricture lengths were measured as follows:left 10.4 cm and right 8.7 cm in the first case;left 10.6 cm and right 11.7 cm in the second case.Bladder capacity assessed by nephrostomy-assisted antegrade urography was 90 mL and 130 mL respectively.Both underwent single-position,one-stage totally 3D laparoscopic bilateral ileal ureteral replacement and blad-der augmentation based on membrane anatomy principles,with regular postoperative follow-up.Results:Procedures were completed by the same experienced urologist.Operative times were 420 min and 355 min,with intraoperative blood loss of 50 mL(no transfusion required).Postoperative bowel function re-sumed at the end of 4.5 and 3 days.No major perioperative complications occurred.Ureteral stents were removed at 2 months postoperatively,with imaging showing improved hydronephrosis,unobstructed ure-teral drainage,symmetrical bladder morphology,and smooth walls.Postoperative bladder capacities were 230 mL and 250 mL.Follow-up durations were 10 and 8 months.Both patients experienced significant relief of flank pain and lower urinary tract symptoms.No complications(enteric fistula,urinary fistula,or metabolic acidosis)were observed.At the final follow-up,one patient had mildly elevated serum cre-atinine,while the other showed reduced levels compared with preoperative values;both remained stable.Conclusion:Membrane anatomy-based dissection facilitates safe mobilization of fibrotic ureters with mini-mal bleeding and collateral damage.Total intracorporeal 3D laparoscopic ileal ureters replacement for bi-lateral ureters combined with bladder augmentation effectively addresses long-segment ureteral obstruction and improves bladder capacity.This approach is technically safe and feasible,though further validation with larger clinical cohorts is warranted.

Objective:To establish a model based on the characteristics of breast cancer ultrasound images through deep learning methods to predict the risk of axillary lymph node metastasis（ALNM）in patients with breast cancer（maximum diameter ≤2.5 cm）before surgery.Methods:A total of 419 patients（3 433 breast tumor ultrasound images）with breast cancer（maximum diameter ≤2.5 cm）who underwent axillary lymph node dissection at Beijing Tiantan Hospital，Capital Medical University from January 2019 to December 2024 were retrospectively included. According to the pathological results of axillary lymph nodes，they were divided into 220 cases in the ALNM occurrence group（positive group）and 199 cases in the non-ALNM occurrence group（negative group）. The breast cancer ultrasound images of the two groups of cases were randomly classified into the training set（2 404 images），the validation set（687 images）and the test set（342 images）according to a ratio of 7∶2∶1. YOLOv8 was used as the basic model of You Only Look Once（YOLO）and optimized. The optimized model was applied to locate and capture the potential ultrasound features of breast cancer cases in the training set. A prediction model was constructed based on the captured ultrasound features. The model was adjusted and optimized through the validation set，and then matched with the case images in the test set. The confusion classification matrix graph and the curve graph for measuring the model performance were used to evaluate the model prediction performance and interpret the model，and the efficacy of this model in identifying breast cancer patients at risk of ALNM was analyzed.Results:There were statistically significant differences between the positive and negative groups in terms of the pathological maximum diameter of breast tumors，pathological T staging，the differentiation degree，the presence of distant metastasis，the maximum diameter measured by ultrasound，the quadrant of breast tumor occurrence，the Breast Imaging - Reporting and Data System（BI-RADS）classification of breast tumors，and the presence of abnormal ultrasound features of lymph node（all P<0.05）. The established deep learning model could automatically perform bounding box localization for the breast cancer of patients.The breast tumors in the positive group had potential ultrasound features that could be captured by the model compared with those in the negative group. The mean average precision（mAP）50 was 0.883，mAP 50-95 was 0.636，PR-AUC was 0.884 5，strict PR-AUC was 0.636 4，the sensitivity was 90.5%，and the specificity was 91.2%，and it had a good predictive efficacy. Conclusions:This prediction model based on the ultrasound characteristics of breast cancer through deep learning can effectively predict breast cancer（maximum diameter ≤ 2.5 cm）with the risk of ALNM，providing an effective basis for the clinical management of axillary lymph nodes in breast cancer patients.

Objective:To investigate the role of the Smad3 signaling pathway in the process of silica-induced epithelial-mesenchymal transition (EMT) .Methods:In September 2022, lung epithelial cells (BEAS-2B) were exposed to different concentrations of silica suspension (0, 50, 100, and 150 μg/ml) for 6 and 12 hours. Additionally, SIS3, a specific inhibitor of phosphorylated Smad3 (p-Smad3) , was utilized to establish the p-Smad3 inhibition model. The cells were divided into four groups: blank control gruop, silica group, SIS3 intervention group, and SIS3 +silica group. Cell morphology was observed using an inverted fluorescence microscope, while cell viability was assessed using a Cell Counting Kit-8 (CCK-8) . The mRNA and protein expression levels of E-cadherin (E-Cad) , N-cadherin (N-Cad) , Vimentin, Smad3, and p-Smad3 were analyzed by Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting, respectively. Differences between two groups were compared using Student's t-test, and multiple group comparisons were analyzed using a one-way analysis of variance with the Student-Newman-Keuls test.Results:Compared with the blank control group, the morphology of BEAS-2B cells shifted from epithelial to mesenchymal cell-like following silica exposure, and the cell viability of BEAS-2B cells declined after exposure to 150 μg/ml silica for 6 and 12 hours. Furthermore, silica exposure led to significant reductions in mRNA and protein expression levels of the epithelial cellular marker (E-Cad) in BEAS-2B cells, accompanied by increased expressions of interstitial cellular markers (N-Cad and Vimentin) . Importantly, the level of p-Smad3/Smad3 expression levels was also elevated in silica-treated cells ( P<0.05) . Compared to the blank control group, the level of p-Smad3/Smad3 expression levels was significantty reduced. Moreover, compared to the silica group, the protein expression levels of N-Cad and Vimentin in the cell of the SIS3+silica group were significantly reduced, while the E-Cad expression was increased ( P<0.05) . Conclusion:Silica exposure can prmote the epithelial mesenchymaol transformotion process by activating smod3 signa ling pathuay, and in hibiting smad3 signa ling pathuay can effctively alleviate the occurrence of epithelial mesenchymal transformation process.

Objective To analyze the application value of assisted compressed sensing(ACS)combined with deep reconstruction(DR)(ACS+DR)algorithm in MR abdominal T2WI.Methods A total of 60 patients were prospectively selected to undergo three types of respiratory-triggered transverse T2 sequence scans:fast spin echo(FSE),propeller scanning(ARMS),and ACS+DR.Two radiologists independently evaluated the images for respiratory motion artifacts,gastrointestinal peristalsis artifacts,sharpness of intrahepatic vessel and bile duct,lesion clarity,and overall image quality.Additionally,the signal-to-noise ratio(SNR),contrast-to-noise ratio(CNR),and contrast ratio(CR)between lesions and liver parenchyma signal intensity were calculated.Wilcoxon and independent sample Mann-Whitney U tests were used to compare objective scores and subjective evaluations among different groups.Results The scan time for the ACS+DR sequence was 35 s,for the ARMS sequence 180 s,and for the FSE sequence 210 s.The ACS+DR sequence showed superior performance over the other sequences in terms of scan time,respiratory motion artifacts,intrahepatic vessel and bile duct sharpness,lesion clarity,and overall image quality(P＜0.05).Compared with FSE sequence,the ARMS and ACS+DR sequences exhibited higher SNR,CNR,and CR(P＜0.05).The ACS+DR sequence showed better SNR and CNR than the ARMS sequence(P＜0.05);however,there was no significant difference between the two sequences in CR(P＞0.05).No significant difference was found among the three sequences in the number of detected lesions(P＞0.05).Conclusion The ACS+DR reconstruction algorithm for upper abdominal imaging not only ensures high image quality but also significantly improves scan speed,making it valuable for clinical application.

Objective To explore the injury types,associated injuries,and correlations of the lateral meniscus posterior root(LMPR),and to improve the comprehensive understanding of LMPR and its associated injuries.Methods The patients with LMPR who underwent knee MRI examination were retrospectively selected.A total of 223 patients with LMPR injury were classified into 4 types.The integ-rity of the meniscofemoral ligament and the grading of the cartilage injuries in the lateral tibiofemoral compartment were recorded.The relationship between the types of LMPR injury and the lateral meniscus tear locations,as well as lateral meniscus extrusion were analyzed.The relationship between the integrity of the meniscofemoral ligament and lateral meniscus extrusion was analyzed.The correlation between the time to clinical presentation after injury and the grading of the cartilage injuries was analyzed in patients with anterior cruciate ligament(ACL)ruptures.Results The incidence of LMPR injury was 1.02％,with males affected 2.19 times more frequently than females.Among patients with ACL ruptures,the incidence was 13.17％.Both type Ⅰ and type Ⅱ LMPR inju-ries predominantly involved only the posterior root,while type Ⅲ injuries mainly affected the posterior root extending to the posterior horn and body.The incidence of the lateral meniscus extrusion was higher in type Ⅲ LMPR injury than in type Ⅱ.When the menis-cofemoral ligament was not intact,the incidence of the lateral meniscus extrusion increased.In patients with ACL ruptures,a longer time to clinical presentation after injury was associated with more severe cartilage injuries grading in the lateral tibiofemoral compart-ment.Conclusion Males are more susceptible to LMPR injuries than females.The classification of LMPR injuries is correlated with the location of the lateral meniscus tears and the incidence of the lateral meniscus extrusion.The integrity of the meniscofemoral lig-ament is related to the incidence of the lateral meniscus extrusion.The time to clinical presentation after injury is related to the sever-ity of cartilage injury in ACL rupture patients.

Objective To evaluate the utility of tuberculosis antibody(TB-Ab),adenosine deaminase(ADA),and carbohydrate antigen 125(CA125)alone or in combination for differentiating tuberculous from non-tuberculous pleural effusion.Methods This retrospective study included 75 patients initially diagnosed with tuberculous pleural effusion(observation group)and 75 patients hospitalized with non-tuberculous pleural effusion(control group)between January 2020 and June 2024.Receiver operating characteristic(ROC)curve analysis was used to compare the diagnostic performance of TB-Ab,ADA,CA125 alone or in combination for diagnosing tuberculous pleurisy.Results The patients with tuberculous pleural effusion showed significantly higher TB-Ab positive rate than the patients with non-tuberculous pleural effusion(control group)(60.00％vs 9.33％,P＜0.001).Tuberculous pleural effusion was associated with significantly higher levels of ADA[(43.44±15.51)U/L]and CA125[(175.57±64.66)U/mL]compared to the control group[(27.81±3.42)U/L]and(122.35±41.22)U/mL,respectively(P＜0.001).Taking 34 U/L as cutoff value,ADA showed good diagnostic performance with an AUC of 0.856,sensitivity of 98.67％,and specificity of 78.67％.Taking 180 U/mL as cutoff value,CA125 demonstrated high sensitivity(89.94％)but low specificity(52.33％)with an AUC of 0.739.CA125 alone was not so specific for detecting tuberculous pleurisy.TB-Ab had an AUC of 0.753 in detecting tuberculous pleurisy,with a sensitivity of 90.67％and specificity of 61.22％.These three markers in combination significantly improved diagnostic performance,with an AUC of 0.926,sensitivity of 90.67％,and specificity of 86.67％.Conclusions TB-Ab,ADA,and CA125 in combination performed better than these biomarkers alone in diagnosing tuberculous pleurisy.

Objective To analyze the lung function condition and the prevalence of pulmonary ventilation disorders in the occupational population of Wuhan, and to explore their influencing factors. Methods Physical examination data from the Wuhan Prevention and Treatment Center for Occupational Diseases were used in this study, and finally 9499 people were selected as the study subjects. The linear regression model and logistic regression model were used to analyze the influencing factors of pulmonary ventilation function and pulmonary dysfunction. The restricted cubic spline was used to explore the nonlinear relationship. Results The prevalence of pulmonary ventilation disorders was 1.7%, and the lung function indexes FVC, FEV1, and FEV1/FVC were significantly lower in the population aged >27 years than in the population aged <27 years (P<0.001). The lung function indexes FVC and FEV1 were significantly lower in females than in males (P<0.001). The lung function indexes FVC and FEV1 were significantly lower in underweight occupational groups than in normal-weight groups (P<0.001), and FVC and FEV1 were significantly lower in dust-exposed occupational groups than in groups without dust exposure(P<0.05). Restricted cubic spline plots showed a nonlinear relationship between age and lung function indexes FVC and FEV1 (P_nonlinear< 0.05). Age and BMI were the risk factors for pulmonary ventilation disorders. Conclusion Age, gender, BMI, and dust exposure are risk factors for decreased FVC and FEV1. Age is the risk factor for decreased FEV1/FVC. Age and BMI are the risk factors for pulmonary ventilation disorders.

OBJECTIVES: To develop a heterogeneous graph prediction method based on the fusion of multi-layer semantics and topological information for addressing the challenges in drug-target interaction prediction, including insufficient modeling of high-order semantic dependencies, lack of adaptive fusion of semantic paths, and over-smoothing of node features. METHODS: A heterogeneous graph network with multiple types of entities such as drugs, proteins, side effects, and diseases was constructed, and graph embedding techniques were used to obtain low-dimensional feature representations. An adaptive metapath search module was introduced to automatically discover semantic path combinations for guiding the propagation of high-order semantic information. A semantic aggregation mechanism integrating multi-head attention was designed to automatically learn the importance of each semantic path based on contextual information and achieve differentiated aggregation and dynamic fusion among paths. A structure-aware gated graph convolutional module was then incorporated to regulate the feature propagation intensity for suppressing redundant information and redcuing over-smoothing. Finally, the potential interactions between drugs and targets were predicted through an inner product operation. RESULTS: Compared with existing drug-target interaction prediction methods, the proposed method achieved an average improvement of 3.4% and 2.4%, 3.0% and 3.8% in terms of the area under the receiver operating characteristic curve (AUC) and the area under the precision-recall curve (AUPRC) on public datasets, respectively. CONCLUSIONS The drug-target interaction prediction method developed in this study can effectively extract complex high-order semantic and topological information from heterogeneous biological networks, thereby improving the accuracy and stability of drug-target interaction prediction. This method provides technical support and theoretical foundation for precise drug target discovery and targeted treatment of complex diseases.
Semantics ; Humans ; Drug Interactions ; Neural Networks, Computer ; Algorithms