Objective:To compare the efficacy of inverted triangular and equilateral triangular cannulated screw internal fixation (CSIF) in the treatment of femoral neck fracture (FNF) in young and middle-aged patients.Methods:A retrospective cohort study was conducted to analyze the clinical data of 52 patients with FNF admitted to Qingdao Central Hospital of Rehabilitation University from January 2020 to January 2022, including 18 males and 34 females, aged 28-60 years [(45.7±9.3)years]. Based on the Garden classification, the fractures were classified as type I in 11 patients, type II in 34, and type III in 7. According to Pauwels classification, the fractures were classified as type I in 33 patients, type II in 13, and type III in 6. Among them, 28 patients received inverted triangular CSIF (inverted triangle group) and 24 received equilateral triangular CSIF (equilateral triangle group). Before surgery and at 3 months after surgery, nuclear medicine three-phase bone scan and bone tomography imaging were performed to evaluate the proximal blood supply recovery in the fractured sites in the two groups. The Harris hip joint function scores before surgery, at 1 day, 3 months after surgery, and at the last follow-up, the posterior tilt angles of the femoral head before surgery and at 3 months after surgery, and the fracture nonunion rate and ischemic necrosis rate of the femoral head at the last follow-up were compared between the two groups.Results:All the patients were followed up for 18-30 months [(24.2±5.6)months]. Before surgery, the fracture of both groups showed extensive blood supply defects at the proximal end. At 3 months after surgery, the excellent and good rate of the proximal blood supply recovery in the inverted triangle group was 92.9% (26/28), significantly higher than 70.8% (17/24) in the equilateral triangle group ( P<0.05). The Harris hip joint function scores before surgery were (44.1±4.1)points and (43.5±5.1)points in the inverted triangle group and equilateral triangle group ( P>0.05). At 1 day, 3 months after surgery, and at the last follow-up, the Harris hip joint function scores in the inverted triangle group were (71.7±3.6)points, (87.0±3.6)points, and (88.7±2.6)points respectively, higher than those in the equilateral triangle group [(65.0±5.4)points, (80.5±5.2)points, and (82.6±4.0)points] ( P<0.05). In both groups, there were no significant differences between the Harris hip joint function scores at the last follow-up and those at 3 months after surgery ( P>0.05), which were all higher than those at 1 day after surgery ( P<0.05). The posterior tilt angles of the femoral head were (16.9±4.4)° and (16.8±5.0)° in the inverted triangle group and equilateral triangle group preoperatively ( P>0.05). At 3 months after surgery, the posterior tilt angles of the inverted femoral head were (8.9±1.9)° and (9.0±1.8)° in the inverted triangle group and equilateral triangle group ( P>0.05). The posterior tilt angles of the femoral head at 3 months after surgery were lower than those before surgery in both groups ( P<0.05). At the last follow-up, there were no statistically significant differences in the fracture nonunion rate and ischemic necrosis rate of the femoral head between the two groups ( P>0.05). Conclusion:Compared with equilateral triangle CSIF, inverted triangle CSIF achieves better recovery of the proximal blood supply and hip joint function in the treatment of femoral neck fracture in young and middle-aged patients.

Objective:To identify independent risk factors for early recurrence following curative resection of resectable pancreatic cancer and establish a nomogram prediction model.Methods:Clinical data from 405 patients with resectable pancreatic cancer treated at Renji Hospital, Shanghai Jiao Tong University School of Medicine from February 2010 to December 2020 were retrospectively reviewed. Patients were stratified into a training cohort (265 patients form February 2010 to December 2018) and a validation cohort (140 patients from January 2019 to December 2020) based on surgery dates. Optimal cutoff values for clinical variables were determined using X-tile software. Independent risk factors were identified through univariate and multivariate Cox proportional hazards regression analyses. Kaplan-Meier curves for recurrence-free survival (RFS) were generated across subgroups, and a nomogram was developed to predict early recurrence (within 1 year post-surgery). Time-dependent receiver operating characteristic (tROC) curves was drawn and area under the curve (AUC) metrics were utilized to evaluate predictive accuracy, while model reliability was assessed by calibration curves. Individualized risk scores derived from the nomogram were stratified into high- and low-risk groups using X-tile-derived cutoff values. Survival differences between groups were analyzed via log-rank tests. The clinical application value was judged by decision curve analysis (DCA) compared to TNM staging. Results:In the training cohort, 139 patients (52.45%) experienced early recurrence, with a median RFS of 11.1 months [interquartile range ( IQR): 6.0-26.0]. The validation cohort reported 70 early recurrences (50.00%) and a median RFS of 11.8 months ( IQR: 4.9-21.4). Univariate analysis revealed significant associations between early recurrence and tumor diameter, carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 125 (CA125), systemic immune-inflammation index (SⅡ), and prognostic nutritional index (PNI). Multivariate analysis identified tumor diameter ≥3.75 cm ( HR=1.718, 95% CI 1.223-2.412, P=0.002), CA19-9≥218 U/ml ( HR=1.567, 95% CI 1.107-2.220, P=0.011), CA125≥20.98 U/ml ( HR=2.501, 95% CI 1.768-3.539, P<0.001), SⅡ≥388.28 ( HR=1.708, 95% CI 1.096-2.662, P=0.018), and PNI<53.18 ( HR=0.596, 95% CI 0.404-0.879, P=0.009) as independent risk factors for early recurrence. The nomogram achieved AUC values of 0.771 and 0.708 in the training and validation cohorts, respectively. Calibration curves demonstrated strong agreement between predicted and observed survival probabilities. Kaplan-Meier analysis revealed significantly lower 1-year RFS rates in high-risk versus low-risk groups for both cohorts (training: HR=3.65, 95% CI 2.45-5.44, P<0.001; validation: HR=2.37, 95% CI 1.39-4.06, P=0.001). DCA indicated superior net benefit of the nomogram over TNM staging across threshold probabilities of 0.2-0.9. Conclusions:The proposed nomogram effectively integrates clinical and serological biomarkers to preoperatively assess early recurrence risk in resectable pancreatic cancer patients, offering enhanced precision for clinical decision-making.

Objective:To construct a temperature-sensitive hydrogel (PF-CA@AS-IV hydrogel) composed of Pluronic F-127 (PF-127)/calcium alginate (CA) loaded with astragaloside IV (AS-IV), and to explore its repair effect and potential mechanism on diabetic skin ulcers (DSU).Methods:The PF-CA@AS-IV hydrogel loaded with AS-IV and gelling at 37 ℃ was prepared. Its temperature sensitivity, rheological properties, and morphology were characterized. A rat model of DSU was established, and the rats were randomly divided into blank control group, model group, AS-IV spray group, PF-CA hydrogel group, and PF-CA@AS-IV hydrogel group ( n=5 each). After 21 days of intervention, the wound healing rate of each group was evaluated. Hematoxylin-eosin (HE) staining was used to observe the pathological changes of granulation tissue, and immunohistochemistry was applied to detect the expression level of CD34, a marker of new blood vessels. Results:Rheological analysis showed that the storage modulus (G′) of PF-CA@AS-IV hydrogel began to exceed the loss modulus (G″) at 33 ℃, and a stable three-dimensional network structure was formed at 37 ℃. Scanning electron microscopy confirmed its loose and porous microstructure. Animal experiment results indicated that compared with the blank control group, the model group had a significantly lower wound healing rate, massive infiltration of inflammatory cells, and fewer new capillaries and CD34 expression (all P<0.05). Compared with the model group, each treatment group can promote wound healing, reduce inflammatory infiltration and increase the positive expression of CD34 to varying degrees (all P<0.05), and the curative effect of PF-CA@AS-IV hydrogel group is the most significant, which is better than that of AS-IV spray group and PF-CA hydrogel group (all P<0.05). Conclusions:PF-CA@AS-IV hydrogel can effectively regulate inflammatory response and promote angiogenesis through sustained release of AS-IV, thereby accelerating DSU healing, and has good translational potential in the field of chronic wound repair.

Depression,as a severe psychological and psychiatric disorder,significantly impairs the long-term physical and mental health of patients.Current depression detection methods are plagued by strong subjectivity,limited techniques,and inadequate intelligence.Previous studies have mostly relied on single-modal signal analysis,making it difficult to comprehensively reflect the multidimensional characteristics of depression.Based on the independently developed intelligent depression detection system,wearable devices are used to collect prefrontal dual-lead EEG signals,PPG signals,and single-lead ECG signals.Data from 30 patients with depression and 40 healthy controls are collected and analyzed.A multimodal depression recognition model named RBLF-Net is proposed,which integrates spatiotemporal features,weighted attention,and random forests to utilize the multi-signal features for depression recognition.The model exhibits superior performance in the five-fold cross-validation,achieving a classification accuracy of 81.43%,a precision of 81.02%,and a recall rate of 81.25%,outperforming other comparative models,and thus providing an intelligent analysis approach for depression recognition from the perspective of multi-modal fusion.

Objective To present an assessment method based on oscillometric upper-arm cuff pressure wave for realizing home-based detection of arteriosclerosis.Methods An upper-arm cuff pressure wave acquisition device based on an electronic blood pressure monitor was designed to implement data collection for cuff inflation and deflation,as well as the 15 s pressure holding phase.Following preprocessing of the data collected during this holding phase,individual pulse waves were extracted for pulse decomposition analysis(PDA).A novel model that superimposed a logarithmic normal function with two Gaussian functions,and an optimization method that combined template matching and particle swarm optimization were proposed to efficiently and accurately extract PDA features.Gaussian process regression was employed for multifeature fusion analysis,leading to the proposal of a new predictive indicator for arteriosclerosis.Results The mean absolute error of PDA was less than 1.2%,and the average processing time for a single pulse wave was less than 0.2 s.The regression determination coefficient R2 between the obtained indicators and baPWV was 0.8178.Conclusion The analysis on upper-arm cuff pressure wave provides a new reference for non-invasive arteriosclerosis detection,and it can be applied to electronic blood pressure monitors for home-based monitoring,offering significant practical value.

Cardiovascular diseases and psychological disorders represent two major threats to human physical and mental health. Research on electrocardiogram (ECG) signals offers valuable opportunities to address these issues. However, existing methods are constrained by limitations in understanding ECG features and transferring knowledge across tasks. To address these challenges, this study developed a multi-resolution feature encoding network based on residual networks, which effectively extracted local morphological features and global rhythm features of ECG signals, thereby enhancing feature representation. Furthermore, a model compression-based continual learning method was proposed, enabling the structured transfer of knowledge from simpler tasks to more complex ones, resulting in improved performance in downstream tasks. The multi-resolution learning model demonstrated superior or comparable performance to state-of-the-art algorithms across five datasets, including tasks such as ECG QRS complex detection, arrhythmia classification, and emotion classification. The continual learning method achieved significant improvements over conventional training approaches in cross-domain, cross-task, and incremental data scenarios. These results highlight the potential of the proposed method for effective cross-task knowledge transfer in ECG analysis and offer a new perspective for multi-task learning using ECG signals.
Humans ; Electrocardiography/methods* ; Mental Health ; Algorithms ; Signal Processing, Computer-Assisted ; Machine Learning ; Arrhythmias, Cardiac/diagnosis* ; Cardiovascular Diseases ; Neural Networks, Computer ; Mental Disorders

Depression,as a severe psychological and psychiatric disorder,significantly impairs the long-term physical and mental health of patients.Current depression detection methods are plagued by strong subjectivity,limited techniques,and inadequate intelligence.Previous studies have mostly relied on single-modal signal analysis,making it difficult to comprehensively reflect the multidimensional characteristics of depression.Based on the independently developed intelligent depression detection system,wearable devices are used to collect prefrontal dual-lead EEG signals,PPG signals,and single-lead ECG signals.Data from 30 patients with depression and 40 healthy controls are collected and analyzed.A multimodal depression recognition model named RBLF-Net is proposed,which integrates spatiotemporal features,weighted attention,and random forests to utilize the multi-signal features for depression recognition.The model exhibits superior performance in the five-fold cross-validation,achieving a classification accuracy of 81.43%,a precision of 81.02%,and a recall rate of 81.25%,outperforming other comparative models,and thus providing an intelligent analysis approach for depression recognition from the perspective of multi-modal fusion.

Objective:To identify independent risk factors for early recurrence following curative resection of resectable pancreatic cancer and establish a nomogram prediction model.Methods:Clinical data from 405 patients with resectable pancreatic cancer treated at Renji Hospital, Shanghai Jiao Tong University School of Medicine from February 2010 to December 2020 were retrospectively reviewed. Patients were stratified into a training cohort (265 patients form February 2010 to December 2018) and a validation cohort (140 patients from January 2019 to December 2020) based on surgery dates. Optimal cutoff values for clinical variables were determined using X-tile software. Independent risk factors were identified through univariate and multivariate Cox proportional hazards regression analyses. Kaplan-Meier curves for recurrence-free survival (RFS) were generated across subgroups, and a nomogram was developed to predict early recurrence (within 1 year post-surgery). Time-dependent receiver operating characteristic (tROC) curves was drawn and area under the curve (AUC) metrics were utilized to evaluate predictive accuracy, while model reliability was assessed by calibration curves. Individualized risk scores derived from the nomogram were stratified into high- and low-risk groups using X-tile-derived cutoff values. Survival differences between groups were analyzed via log-rank tests. The clinical application value was judged by decision curve analysis (DCA) compared to TNM staging. Results:In the training cohort, 139 patients (52.45%) experienced early recurrence, with a median RFS of 11.1 months [interquartile range ( IQR): 6.0-26.0]. The validation cohort reported 70 early recurrences (50.00%) and a median RFS of 11.8 months ( IQR: 4.9-21.4). Univariate analysis revealed significant associations between early recurrence and tumor diameter, carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 125 (CA125), systemic immune-inflammation index (SⅡ), and prognostic nutritional index (PNI). Multivariate analysis identified tumor diameter ≥3.75 cm ( HR=1.718, 95% CI 1.223-2.412, P=0.002), CA19-9≥218 U/ml ( HR=1.567, 95% CI 1.107-2.220, P=0.011), CA125≥20.98 U/ml ( HR=2.501, 95% CI 1.768-3.539, P<0.001), SⅡ≥388.28 ( HR=1.708, 95% CI 1.096-2.662, P=0.018), and PNI<53.18 ( HR=0.596, 95% CI 0.404-0.879, P=0.009) as independent risk factors for early recurrence. The nomogram achieved AUC values of 0.771 and 0.708 in the training and validation cohorts, respectively. Calibration curves demonstrated strong agreement between predicted and observed survival probabilities. Kaplan-Meier analysis revealed significantly lower 1-year RFS rates in high-risk versus low-risk groups for both cohorts (training: HR=3.65, 95% CI 2.45-5.44, P<0.001; validation: HR=2.37, 95% CI 1.39-4.06, P=0.001). DCA indicated superior net benefit of the nomogram over TNM staging across threshold probabilities of 0.2-0.9. Conclusions:The proposed nomogram effectively integrates clinical and serological biomarkers to preoperatively assess early recurrence risk in resectable pancreatic cancer patients, offering enhanced precision for clinical decision-making.

With the rapid advancements in minimally invasive spine surgery and the increasingly sophisti-cated concept of visualization,transforaminal endoscopic lumbar discectomy(TELD)has become a primary treatment for lumbar disc herniation.Among the critical preoperative steps in TELD,foraminalplasty plays a pivotal role,as its quality directly impacts surgical outcomes and postoperative recurrence rates.This article systemati-cally reviews the evolution of foraminalplasty techniques,evaluates the selection and application of plasty sites,examines factors influencing stability after lumbar foraminalplasty,and highlights recent advancements in computer-assisted navigation.The goal is to serve as a comprehensive reference for clinicians.

Objective To explore the relationship between fibrinogen to albumin ratio(FAR),prognostic nutritional index(PNI),systemic immune inflammation index(SII)and prognosis of patients with lung cancer undergoing thoracoscopic surgery.Methods The clinical data of 287 patients with lung cancer who underwent thoracoscopic lobectomy in the hospital from February 2018 to February 2020 were retrospectively collected.The FAR,PNI,and SII values were measured within one week before surgery.The 3-year survival after operation was counted.The relationship between clinical data,preoperative FAR,PNI,SII and 3-year survival prognosis was observed.The receiver operating characteristic curve(ROC)was used to determine the optimal cut-off values of preoperative FAR,PNI,and SII values for predicting the 3-year survival prognosis after surgery,and the prognostic value of single index and combination of each index was observed.Multivariate Logistic regression analysis was used to evaluate the influencing factors of prognosis.Pearson correlation analysis was used to explore the correlation between FAR,PNI and SII values.Results Finally,242 patients with lung cancer were included in the study,and 199 patients survived 3 years after operation,with an overall survival rate of 82.23％.43 cases(17.77％)died in 3 years.Age,serum carcinoembryonic antigen(CEA)level,lymph node metastasis,TNM stage,preoperative FAR,PNI and SII value were related to the 3-year survival prognosis of lung cancer patients after thoracoscopic lobectomy(P＜0.05).The ROC curve showed that the preoperative FAR,PNI and SII values had certain predictive value for the 3-year survival prognosis of patients after operation.The combined prediction of the three showed better predictive efficacy,and the area under the curve(AUC)was 0.772.Multivariate Logistic regression analysis showed that lymph node metastasis,TNM stage,FAR value and SII value were independent risk factors for postoperative survival and prognosis.PNI was an independent protective factor(P＜0.05).Pearson correlation analysis showed that there was a negative correlation between FAR and PNI,PNI and SII,and a positive correlation between FAR and SII(P＜0.05).Conclusion The values of FAR,PNI and SII are independently related to the prognosis of patients with lung cancer undergoing thoracoscopic surgery.The combined application has a higher prognostic value.