BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95％Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2％and a specificity of 87.6％,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1％to 92％,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.

BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95％Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2％and a specificity of 87.6％,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1％to 92％,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.

OBJECTIVE To analyze the prototype components absorbed into blood and brain of Lithocarpus litseifolius leaves， so as to provide a reference for clarifying the pharmacological material basis of its prevention and treatment of central nervous system dis eases. METHODS The ethanol extract of L. litseifolius leaves， as well as the gastric lavage fluid and perfusion solution were prepared. Using rats as subjects， plasma samples of intestinal wall metabolism， intestinal flora metabolism and hepatic metabolism were prepared via in situ intestinal perfusion and closed intestinal loop method； while comprehensive metabolic plasma samples， brain tissue samples， and cerebrospinal fluid samples were collected after intragastric administration. UPLC-HRMS technology was utilized to analyze and identify chemical components and prototype components absorbed into blood and brain of L. litseifolius leaves. RESULTS A total of 66 chemical constituents were identified in L. litseifolius leaves， primarily consisting of flavonoids， organic acids， and others. A total of 16， 13， 11， and 5 prototype components were identified in intestinal wall metabolism， intestinal flora metabolism， hepatic metabolism， and comprehensive metabolic plasma samples， respectively. Additionally， 4 prototype components were detected in brain tissue and 9 in cerebrospinal fluid. Phloridzin， trilobatin， phloretin-2- O -malonyl hexoside， and phloretin were identified as common components across all sample types. CONCLUSIONS Prototype components absorbed into blood and brain of L. litseifolius leaves， such as phloridzin， trilobatin， phloretin， and other components may serve as the pharmacological material basis for their therapeutic effects on central nervous system diseases.

With the accelerating trend of population aging, the number of elderly patients with lung cancer continues to rise, and the disease burden is becoming increasingly heavy. The clinical management of these patients faces severe challenges due to their decreased physiological reserve, complex comorbidities, and significant individual heterogeneity. Consequently, under traditional diagnosis and treatment models, doctors often struggle to identify the individualized risks of elderly patients in a timely and comprehensive manner, which can easily lead to decision biases such as undertreatment or overtreatment. In view of this, this study advocates for the establishment of an umbrella decision-making model specifically tailored for elderly lung cancer patients. Grounded in a multidisciplinary team (MDT) platform, this model deeply integrates oncological indicators with the comprehensive geriatric assessment (CGA) system. By holistically considering multidimensional variables including tumor burden, organ function, frailty index, cognitive status, and social support, the model establishes an operational mechanism characterized by "single entry, precise stratification, and targeted selection". Accordingly, patients can be scientifically triaged into distinct intervention tiers, such as active surveillance, minimally invasive surgery, drug therapy, radiotherapy, and best supportive care, thereby achieving real-time alignment between treatment intensity and patient fitness. This article elaborates on the construction logic and key operational procedures of this novel decision-making framework, aiming to guide clinical practice beyond the limitations of a tumor-centric perspective toward a holistic, dynamic, whole-course management strategy. This transition seeks to ensure optimal quality of life and clinical net benefit for elderly patients alongside survival prolongation.

Objective To organize and summarize the medication rules of GU Nai-fang in treating skin diseases through real-world data.Methods We collected traditional Chinese medicine prescriptions for GU Nai-fang's treatment of skin diseases from the outpatient medical record system of Shanghai Traditional Chinese Medicine Hospital to establish a database.Statistical analysis of disease types,performance,and efficacy was conducted,and association rules and systematic clustering analysis were performed using SPSS Modeler 18.0 and SPSS 26.0 software,respectively.Results A total of 5 020 patients were included,and 5 020 prescriptions were collected,involving 241 traditional Chinese medicines with a total frequency of 85 758 uses.The frequency of using heat clearing drugs,deficiency tonifying drugs,blood activating and stasis removing drugs,surface clearing drugs,and wind and dampness dispelling drugs was relatively high;most drugs tended to be cold and warm,mainly targeting the heart,lungs,and colon meridians.The top 15 Chinese medicines with the highest frequency of use were Smilacis Glabrae Rhixoma,Cortex Moutan,Radix Paeoniae Rubra,Rehmanniae Radix,Scutellariae Radix,Cynanchi Paniculati Radix et Rhizoma,Schisandrae Chinensis Fructus,Violsse Herba,Mume Fructus,Herba Pyrolae,Hedyotis Diffusae Herba,Lonicerae Japonicae Flos,Cicadae Periostracum,Bombyx Batryticatus,Radix Salviae.Association rule analysis obtained 15 high-frequency combinations of 2 traditional Chinese medicines and 3 traditional Chinese medicines.Cluster analysis resulted in 7 clustered prescriptions.Conclusion GU Nai-fang commonly used heat clearing drugs,deficiency tonifying drugs,blood activating and stasis removing drugs,surface resolving drugs,and wind and dampness dispelling drugs in the treatment of skin diseases,and Smilacis Glabrae Rhixoma,Cortex Moutan,Radix Paeoniae Rubra,Rehmanniae Radix,and Scutellariae Radix were the most frequently used drugs.

Objective To explore the effect of a health behaviour intervention program based on health action process approach(HAPA)on patients after implantation of a pacemaker.Methods Convenience sampling was conducted to select 154 patients who had implantation of a pacemaker in our hospital as research subjects.A random table was used to divide the patients into a control group and an trial group,with 77 patients per group.Patients in the control group were treated with conventional care and issued with exercise brochures,while the patients in the trial group were treated with conventional care with a HAPA-based health behaviour intervention program for 3 months.Both groups were evaluated using the rehabilitation exercise adherence questionnaire and the adult health self-management ability assessment scale before the intervention,at 3 and 6 months after the intervention.Cardiopulmonary function of the patients in both groups was assessed by 6-minute walk test.Results After 3 months and 6 months of intervention,the scores of rehabilitation exercise compliance and self-management ability of the patients in the trial group were better than those in the control group.The difference between the two groups was statistically significant(P<0.05).Six months after discharge,the 6-minute walking distance(6MWD)of the patients in the trial group was longer than that of the control group,and the difference between the two groups was statistically significant(P<0.05).Conclusion The health behaviour intervention program based on the HAPA enhances the exercise compliance in patients who were implanted with a pacemaker,as well as improves the self-management behaviour and cardiopulmonary function.

Aim To investigate the protective effect of Vaccarin(Va)on epithelial-mesenchymal transition(EMT)in renal fibrosis model mice through regulating STAT3,and the underlying mechanism.Methods Left ureter ligation was used to establish a mouse model of unilateral ureteral obstruction(UUO);human kid-ney tubular epithelial(HK2)cells were induced to differentiate by transforming growth factor-β(TGF-β)in vitro.HE and Masson staining were used to observe the morphological changes of renal tissue;kits were used to detect the levels of BUN,Cr,IL-1β and IL-7 in mouse serum;CCK-8 was used to detect the effect of Va on the viability of HK2 cells;RT-PCR was used to detect the levels of inflammatory factors in HK2 cells;Western blot was used to detect the expression of STAT3,p-STAT3,E-cadherin,and α-SMA proteins in renal tissue and HK2 cells;to further investigate the regulation of Va on STAT3,JAK/STAT3 pathway acti-vator RO8191 was used to treat TGF-β-induced HK2 cells,and functional loss was detected.Results Va improved the pathological damage in UUO mice,inhibi-ted the levels of BUN,Cr and inflammatory factors;Va inhibited the phosphorylation of STAT3,upregulated E-cadherin,and downregulated α-SMA protein expres-sion;RO8191 counteracted the inhibitory effect of Va on the phosphorylation of STAT3.Conclusions Va inhibits the phosphorylation of STAT3 and the release of inflammatory factors,improves EMT,thus exerting an anti-renal fibrosis effect.

BACKGROUND:Knee finite element modelling can provide insight into knee mechanics,but its complex image segmentation is more difficult for researchers.With the development of deep learning techniques,deep learning techniques have been widely used in knee joint finite element modelling.OBJECTIVE:To replace the manual segmentation step in finite element modelling of the knee joint by using 3D Swin UNETR in combination with a semi-automatic segmentation technique for statistical shape models.METHODS:Manual(artificial)knee joint finite element model was developed based on MR and semi-automatic knee joint finite element model was developed based on 3D Swin UNETR+statistical shape model segmentation.The same loads and boundary conditions were applied to both models.Validation was performed by calculating the Dice similarity coefficient,mean distance,and comparing the peak equivalent stresses,maximum principal stresses,and maximum shear stresses of the two models.RESULTS AND CONCLUSION:(1)The Dice similarity coefficients of the manual and semi-automatic segmented femur and tibia were more than 98％,and the average distances were less than or equal to(0.35±0.08)mm.(2)With the longitudinal load of 750 N and 10 Nm internal overturning moment applied to the femur tip of both manual and semi-automatic finite element models,the peak equivalent stress,maximum principal stress,and maximum shear stresses of meniscus in manual finite element model were 14.12,18.54,and 7.35 MPa;peak equivalent force,maximum principal stress,and maximum shear stress of femoral cartilage were 2.22,2.15,and 1.18 MPa;peak equivalent force,maximum principal stress,and maximum shear stress of tibial cartilage were 2.50,1.91,and 1.41 MPa;semi-automatic finite element model of meniscus:peak equivalent force,maximum principal stress,and maximum shear stress were 14.93,18.53,and 7.75 MPa.The peak equivalent force,maximum principal stress,and maximum shear stress of femoral cartilage were 2.26,2.18,and 1.20 MPa;the peak equivalent stress,maximum principal stress,and maximum shear stress of tibial cartilage were 2.60,1.91,and 1.46 MPa.The peak equivalent stress,maximum principal stress,and maximum shear stress of manual and semi-automatic finite element models were basically consistent,with no significant difference(P＞0.05).(3)The semi-automatic segmentation technique proposed in this study can replace manual segmentation in creating accurate finite element models of the knee joint.

Objective To organize and summarize the medication rules of GU Nai-fang in treating skin diseases through real-world data.Methods We collected traditional Chinese medicine prescriptions for GU Nai-fang's treatment of skin diseases from the outpatient medical record system of Shanghai Traditional Chinese Medicine Hospital to establish a database.Statistical analysis of disease types,performance,and efficacy was conducted,and association rules and systematic clustering analysis were performed using SPSS Modeler 18.0 and SPSS 26.0 software,respectively.Results A total of 5 020 patients were included,and 5 020 prescriptions were collected,involving 241 traditional Chinese medicines with a total frequency of 85 758 uses.The frequency of using heat clearing drugs,deficiency tonifying drugs,blood activating and stasis removing drugs,surface clearing drugs,and wind and dampness dispelling drugs was relatively high;most drugs tended to be cold and warm,mainly targeting the heart,lungs,and colon meridians.The top 15 Chinese medicines with the highest frequency of use were Smilacis Glabrae Rhixoma,Cortex Moutan,Radix Paeoniae Rubra,Rehmanniae Radix,Scutellariae Radix,Cynanchi Paniculati Radix et Rhizoma,Schisandrae Chinensis Fructus,Violsse Herba,Mume Fructus,Herba Pyrolae,Hedyotis Diffusae Herba,Lonicerae Japonicae Flos,Cicadae Periostracum,Bombyx Batryticatus,Radix Salviae.Association rule analysis obtained 15 high-frequency combinations of 2 traditional Chinese medicines and 3 traditional Chinese medicines.Cluster analysis resulted in 7 clustered prescriptions.Conclusion GU Nai-fang commonly used heat clearing drugs,deficiency tonifying drugs,blood activating and stasis removing drugs,surface resolving drugs,and wind and dampness dispelling drugs in the treatment of skin diseases,and Smilacis Glabrae Rhixoma,Cortex Moutan,Radix Paeoniae Rubra,Rehmanniae Radix,and Scutellariae Radix were the most frequently used drugs.

Objective To explore the effect of a health behaviour intervention program based on health action process approach(HAPA)on patients after implantation of a pacemaker.Methods Convenience sampling was conducted to select 154 patients who had implantation of a pacemaker in our hospital as research subjects.A random table was used to divide the patients into a control group and an trial group,with 77 patients per group.Patients in the control group were treated with conventional care and issued with exercise brochures,while the patients in the trial group were treated with conventional care with a HAPA-based health behaviour intervention program for 3 months.Both groups were evaluated using the rehabilitation exercise adherence questionnaire and the adult health self-management ability assessment scale before the intervention,at 3 and 6 months after the intervention.Cardiopulmonary function of the patients in both groups was assessed by 6-minute walk test.Results After 3 months and 6 months of intervention,the scores of rehabilitation exercise compliance and self-management ability of the patients in the trial group were better than those in the control group.The difference between the two groups was statistically significant(P<0.05).Six months after discharge,the 6-minute walking distance(6MWD)of the patients in the trial group was longer than that of the control group,and the difference between the two groups was statistically significant(P<0.05).Conclusion The health behaviour intervention program based on the HAPA enhances the exercise compliance in patients who were implanted with a pacemaker,as well as improves the self-management behaviour and cardiopulmonary function.