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.

Pharmacotranscriptomic profiles, which capture drug-induced changes in gene expression, offer vast potential for computational drug discovery and are widely used in modern medicine. However, current computational approaches neglected the associations within gene‒gene functional networks and unrevealed the systematic relationship between drug efficacy and the reversal effect. Here, we developed a new genome-scale functional module (GSFM) transformation framework to quantitatively evaluate drug efficacy for in silico drug discovery. GSFM employs four biologically interpretable quantifiers: GSFM_Up, GSFM_Down, GSFM_ssGSEA, and GSFM_TF to comprehensively evaluate the multi-dimension activities of each functional module (FM) at gene-level, pathway-level, and transcriptional regulatory network-level. Through a data transformation strategy, GSFM effectively converts noisy and potentially unreliable gene expression data into a more dependable FM active matrix, significantly outperforming other methods in terms of both robustness and accuracy. Besides, we found a positive correlation between RS_GSFM and drug efficacy, suggesting that RS_GSFM could serve as representative measure of drug efficacy. Furthermore, we identified WYE-354, perhexiline, and NTNCB as candidate therapeutic agents for the treatment of breast-invasive carcinoma, lung adenocarcinoma, and castration-resistant prostate cancer, respectively. The results from in vitro and in vivo experiments have validated that all identified compounds exhibit potent anti-tumor effects, providing proof-of-concept for our computational approach.

Objective To explore the predictive value of the nomogram model based on multimodal MRI signs for adverse pregnancy outcomes in placenta accreta spectrum disorders(PAS).Methods The clinical and MRI data of 60 patients with PAS diagnosed by surgery and/or pathology were collected.Multivariate logistic regression was used to analyze the independent risk factors of adverse pregnancy outcomes in PAS.According to the results of multivariate logistic regression analysis,the nomogram prediction model of adverse pregnancy outcomes in PAS was constructed.Results Placenta/uterine protrusion[odds ratio(OR)=6.717,P=0.015],abnormal blood vessels in the placenta(OR=7.929,P=0.009),and diffusion weighted imaging(DWI)placental spike/nodular protrusion into the muscular layer(OR=12.134,P=0.003)were independent risk factors for adverse pregnancy outcomes in PAS.Based on the results,a nomogram prediction model was constructed.The area under the curve(AUC)of the model for predicting adverse pregnancy outcomes of PAS was 0.907,with a sensitivity of 0.906 and a specificity of 0.821.Conclusion The nomogram model constructed based on multimodal MRI signs has certain value in predicting adverse pregnancy outcomes of PAS.

Objective To explore the value of multi-parameter MRI in predicting the Ki-67 expression level in nasopharyngeal carcinoma(NPC).Methods The clinical and MRI data of 63 patients with pathologically confirmed NPC were prospectively collected.All patients underwent routine plain and enhanced nasopharyngeal MRI,diffusion weighted imaging(DWI),and arterial spin labeling(ASL)scans before treatment.Multivariate logistic regression analysis was used to identify the independent risk factors for the Ki-67 expression level.Results The degree of enhancement,the maximum blood flow(BFmax),and the minimum apparent diffusion coefficient(ADCmin)were independent risk factors for the Ki-67 expression level in NPC patients.The area under the curve(AUC)of the prediction model established based on these three factors was 0.920,with a sensitivity of 0.792 and a specificity of 0.897,respectively.Conclusion Multi-parameter MRI based on conventional enhancement,ASL,and DWI can effectively predict the Ki-67 expression level in NPC patients.

Objective To explore the predictive value of the nomogram model based on multimodal MRI signs for adverse pregnancy outcomes in placenta accreta spectrum disorders(PAS).Methods The clinical and MRI data of 60 patients with PAS diagnosed by surgery and/or pathology were collected.Multivariate logistic regression was used to analyze the independent risk factors of adverse pregnancy outcomes in PAS.According to the results of multivariate logistic regression analysis,the nomogram prediction model of adverse pregnancy outcomes in PAS was constructed.Results Placenta/uterine protrusion[odds ratio(OR)=6.717,P=0.015],abnormal blood vessels in the placenta(OR=7.929,P=0.009),and diffusion weighted imaging(DWI)placental spike/nodular protrusion into the muscular layer(OR=12.134,P=0.003)were independent risk factors for adverse pregnancy outcomes in PAS.Based on the results,a nomogram prediction model was constructed.The area under the curve(AUC)of the model for predicting adverse pregnancy outcomes of PAS was 0.907,with a sensitivity of 0.906 and a specificity of 0.821.Conclusion The nomogram model constructed based on multimodal MRI signs has certain value in predicting adverse pregnancy outcomes of PAS.

Objective To explore the value of multi-parameter MRI in predicting the Ki-67 expression level in nasopharyngeal carcinoma(NPC).Methods The clinical and MRI data of 63 patients with pathologically confirmed NPC were prospectively collected.All patients underwent routine plain and enhanced nasopharyngeal MRI,diffusion weighted imaging(DWI),and arterial spin labeling(ASL)scans before treatment.Multivariate logistic regression analysis was used to identify the independent risk factors for the Ki-67 expression level.Results The degree of enhancement,the maximum blood flow(BFmax),and the minimum apparent diffusion coefficient(ADCmin)were independent risk factors for the Ki-67 expression level in NPC patients.The area under the curve(AUC)of the prediction model established based on these three factors was 0.920,with a sensitivity of 0.792 and a specificity of 0.897,respectively.Conclusion Multi-parameter MRI based on conventional enhancement,ASL,and DWI can effectively predict the Ki-67 expression level in NPC patients.

Objective To investigate the value of high-resolution 3.0T MR in the assessment of local infiltration of preoperative rectal cancer.Methods A total of 168 patients pathologically proved rectal cancer underwent both conventional pelvic and rectal high-resolution before operation, and the imaging findings were reviewed retrospectively.The accuracy of preoperative high-resolution 3.0T MR in prediction of pathological staging was assessed,and the characteristic imaging features of local infiltration in preoperative rectal cancer were discussed.Results The relationship between circumference invasion of colorectal cancer and the pathological T staging was moderately positive (rs=0.530,P=0.003).Compared the staging of colorectal cancer on MRI with pathologic T staging,the overall diagnostic accuracy was 84.52%,and there was a stronger correlation between MRI findings and pathological staging (rs=0.837,P=0.001).The best single parameters for diagnosing T3 stage rectal cancer on MRI were nodular convex of the tumor and muscular signal interruption,with 91.1% specificity and 89.7% sensitively respectively.And the best combination of parameters was the cord appearence of intestinal wall and muscular signal interruption,with 89.3% specificity and 78.0% sensitively respectively.Conclusion High-resolution 3.0T MR can be preferable to evaluating local infiltration of rectal cancer, showing a higher clinical value to asseee T staging of preoperative rectal cancer.

ObjectiveTo explore the application value of thoracoscopic pleural lavage for empyema after liver transplantation (LT).MethodsClinical data of 5 patients who underwent thoracoscopic pleural lavage for empyema after LT in the Third Afifliated Hospital of Sun Yat-sen University from October 2002 to October 2013 were analyzed retrospectively. All 5 patients were males with the age ranging from 42 to 56 years old and the median of 51 years old. The informed consents of all patients were obtained and the local ethical committee approval had been received. The patients received thoracoscopic pleural lavage for empyema under endotracheal general anesthesia. The thoracoscope was introduced in the seventh intercostal space on the mid-axillary line. The aspirator was inserted in the third intercostal space on the anterior line to drain the pus. And the pleural ifberboard was peeled off. The intraoperative situation and perioperative recovery of the patients were observed.ResultsFive patients received successful operations and recovered and were discharged from hospital. The median length of operation was 2(1-3) h. The length of respirator assisted ventilation was 26(6-42) h. The intraoperative blood loss was 600(300-1 000) ml. The length of indwelling chest drainage tube was 4(2-6) h. The volume of chest drainage was 680(350-1 200) ml. No mortality, empyema recurrence and other serious complications were observed. The postoperative hospital stay was 7(5-11) d.ConclusionThoracoscopic pleural lavage for empyema after LT is a safe and effective treatment.

ObjectiveTo investigate the value of the MSCT liver perfusion imaging parameters inthe evaluation of the chronic hepatic fibrosis and cirrhosis. Methods Liver CT perfusion ( CTP ) was performed in 107 participants,including 31 patients with mild hepatic fibrosis( S1,S2),34 patients with severe hepatic fibrosis ( S3,S4 ) and early stage of hepatic cirrhosis which conformed by liver pathologic biopsy,42 patients with hepatic cirrhosis who had typical clinical and image signs,and 30 healthy subjects as control group.The data of CTP ( HAP,PVP,LTP,HPI and TTP) at different stages were obtained with Body perfect CT-syngo CT2007A and control study with histopathologic stage.Compared the study index by the one-way ANOVA analysis. Used Spearman rank correlation to analysis the relationship between liver perfusion imaging parameters and the degrees of the chronic hepatic fibrosis. Used Logistic regression to analysis the maximum.regression coefficient among the liver perfusion imaging paraneters,which affected the histopathologic stage mostly.ResultsIn the subgroups of the chronic hepatic fibrosis S1,S2,S3,S4 to the hepatic cirrhosis,HAP values was (28.9 ±8.6),(24.6 ±2.4),(29.2 ±2.3) and (38.9 ± 7.0) ml · 100 ml -1 · min-1,respectively.HAP decreased firstly,then increased.Statistic analysis showed the difference of HAP between later-stage cirrhosis and other groups( F =40.26,P ＜ 0.01 ).PVP values of above subgroups was (111.3 ± 18.1),(92.9 ±5.3),(73.0 ±9.0) and (54.1 ± 13.8) ml · 100 ml-1 ·min -1,respectively.TLP values of above subgroups was ( 140.2 ± 25.9 ),( 117.1 ± 4.5 ),( 102.3 ± 8.7 )and (93.0 ± 11.8) ml · 100 ml-1.min-1,respectively.The difference of PVP,TL.P among each subgroup was significant ( F =136.79,67.40,respectively,P ＜ 0.01 ).HPI values of above subgroups was (20.4 ± 2.6)％,(21.0 ±2.1)％,(28.5 ±3.1)％ and (42.6± 11.1)％,respectively.TTP values of above subgroups was (123.7±22.2),(137.1 ±27.1),(145.0 ±28.6) and (166.5 ±25.1)s,respectively.The difference of HPI,TTP among each subgroup was significant( F =93.05,17.37,respectively; P ＜0.01 ).PVP,TLP was significant negative correlation with the degree of the hepatic fibrosis( r =-0.920,-0.846,respectively; P ＜0.01 ).HAP,HPI and TTP was significant positive correlation with the degree of the hepatic fibrosis( r =0.611,0.882 and 0.545,respectively; P ＜ 0.01 ).Logistic regression analysis showed the regression coefficient of PVP( - 8.798) was maximum.With an area under the receiver operating characteristic curve of PVP =84.76 ml · 100 ml- 1 · min- 1 as a diagnose critical point.The sensitivity was 0.890,the specificity was 0.950,and the accuracy was 0.931 in the prediction of the chronic hepatic fibrosis.Conclusions MSCT liver perfusion imaging parameters can reflect the hemodynamic changes of chronic hepatic fibrosis and cirrhosis.CTP may be helpful for differentiation the severe hepatic fibrosis and early stage of hepatic cirrhosis and later-stage cirrhosis.