Objective:To evaluate the diagnostic performance of resting echocardiography in detecting severe coronary artery stenosis.Methods:A total of 136 patients with suspected coronary artery disease（CAD）who presented to Sichuan Provincial People's Hospital between January 2021 and December 2024 were prospectively enrolled. All patients underwent both coronary computed tomography angiography（CCTA）and transthoracic echocardiography within one week. Based on CCTA results，the patients were divided into non-severe stenosis group（ n=78）and severe stenosis group（ n=58）. Echocardiographic parameters including left atrial maximum volume（LAVmax），left ventricular global longitudinal strain（GLS），left ventricular longitudinal strain of endo-myocardium，mid-myocardium，epi-myocardium（LSendo，LSmid，LSepi），early diastolic mitral inflow velocity（E），early diastolic mitral annular velocity of the lateral and septal walls（e'），and E/e' were measured. Predictive factors for severe coronary stenosis were identified using LASSO regression，and a nomogram model was developed via multivariate Logistic regression. Model performance was evaluated using ROC curves，calibration curves，and decision curve analysis. Results:Multivariate Logistic regression analysis revealed LSendo，LAVmax，and E/e' as independent predictors of severe coronary artery stenosis. The nomogram constructed based on these predictors achieved an area under the curve of 0.798（95% CI=0.723-0.873），with sensitivity and specificity of 0.756 and 0.759，respectively. Conclusions:The resting echocardiography-based nomogram model demonstrates good diagnostic efficacy for severe coronary artery stenosis. It may serve as a noninvasive tool to assist in risk stratification and clinical decision-making in patients with suspected CAD.

Objective To retrospectively analyze the association between metabolic factors and high-risk colorectal adenoma(CRA).Methods The medical records of patients aged 18-75 years who underwent their initial colonoscopy at Karamay Central Hospital of Xinjiang Uygur Autonomous Region from Jul 2000 to Mar 2017 were collected.The comparison between normal colonoscopy(NC)and high-risk CRA patients was conducted using an unpaired t-test,while chi-square test was used for categorical variables.Least absolute shrinkage and selection operator(LASSO)regression and Logistic regression were utilized to analyze the association between metabolic factors and high-risk CRA.Results A total of 1 798 patients meeting the inclusion and exclusion criteria were enrolled and divided into normal colonoscopy(NC)findings group(n=972)and high-risk CRA group(n=826).The high-risk CRA group exhibited significantly lower levels of high-density lipoprotein cholesterol(HDL-C)in comparison to the NC group,while uric acid and fibrosis 4(FIB-4)index levels were significantly higher than those observed in the NC group(all P<0.05).Based on LASSO regression analysis,we identified 12 variables that potentially influence the occurrence of high-risk CRA,including age,gender,smoking history,alcohol consumption history,non-alcoholic fatty liver disease(NAFLD),hypertension,coronary artery disease,hyperglycemia,hypercholesterolemia,low levels of HDL-C,elevated alanine aminotransferase,and elevated gamma-glutamyl transferase.Multivariate analysis revealed that individuals aged over 50 years,male gender,cigarette and alcohol consumption,low HDL-C levels,history of NAFLD and hypertension were identified as independent risk factors associated with high-risk CRA(P<0.05).In addition,without or with adjusting for age,sex,smoking,and drinking history,patients with a high TG/HDL-C ratio(the ratio≥2.68)had a significantly higher risk of high-risk CRA than those with a low TG/HDL-C ratio(the ratio<2.68)[odds ratios(ORs)were1.430 and 1.235 respectively,all P<0.05)].Without or with adjusting variables,the ORs for NAFLD patients with FIB-4 index>2.67 were 1.849(P=0.466)and 1.435(P=0.707),respectively.Conclusion A significant association exists between metabolic factors and high-risk CRA.Independent risk factors for high-risk CRA include older age(≥50 years),male,smoking history,alcohol consumption history,low levels of HDL-C,and a history of NAFLD and hypertension.Individuals exhibiting a TG/HDL-C ratio exceeding 2.68 manifest a significantly heightened susceptibility to the development of high-risk CRA.Therefore,elderly males with one or more aforementioned metabolic abnormalities should be considered a priority population for colorectal screening.

The medulla oblongata,situated at the caudal portion of the brainstem,serves as a critical regulatory center responsible for maintaining fundamental vital functions including respiratory and cardiovascular homeostasis.As a pivotal hub within the autonomic nervous system,it orchestrates the coordinated control of afferent and efferent neural pathways.Dysfunction of this region may precipitate life-threatening cardiorespiratory arrest,associated with substantial mortality rates.This case report presents a patient who developed acute extensive anterior myocardial infarction during treatment with dual antiplatelet therapy and moderate-intensity statins following acute medullary infarction.It is hypothesized that the pathogenesis may involve the acceleration of plaque erosion by the stroke-heart syndrome.This clinical case provides valuable insights into the complex neurocardiac interplay,particularly highlighting the imperative for enhanced recognition of brain-heart axis interactions in cerebrovascular pathology.

Objective:To investigate the impact of postoperative complications on adverse outcomes following curative-intent resection for gallbladder cancer (GBC).Methods:The multi-center real-world study was conducted. The clinicopathological data of 629 patients with GBC, who were admitted to 14 medical centers including The First Affiliated Hospital of Army Medical University from the national multicenter database of Biliary Surgery Group of Elite Group of Chinese Journal of Digestive Surgery, from April 2020 to April 2024 were collected. There were 225 males and 404 females, aged (64±10)years. Patients underwent open curative-intent resection for GBC. Observation indicators: (1)surgery, postoperative complica-tions and adverse outcomes; (2) analysis of risk factors affecting postoperative adverse outcomes in patients and population attributable fraction (PAF). Missing data in predictor variables were addressed using multiple imputation with chained equations, while cases with missing outcome variables were addressed using the "multiple imputation then deletion (MID)" strategy. The severity of multicollinearity among independent variables was assessed using the variance inflation factor (VIF) test. Multivariable possion regression models with log link and robust error variance were construc-ted incorporating restricted cubic splines (3 knots) to address nonlinear relationships in continuous variables, calculating adjusted relative risk ( RR) with corresponding 95% confidence interval ( CI). Adjusted PAF was calculated for each imputed dataset using the AF package of R software, with subsequent pooling performed according to Rubin's rules. Results:(1) Surgery, postoperative complications and adverse outcomes. All 629 patients underwent curative-intent resection for GBC, of which 143 cases had postoperative complications, including 68 cases of intra-abdominal ascites, 39 cases of pulmonary infection, 21 cases of bile leakage, 12 cases of intra-abdominal hemorrhage, 11 cases of liver failure, 10 cases of pan-creatic fistula, 10 cases of wound infection, 10 cases of gastroparesis, 7 cases of cholangitis, 7 cases of sepsis. The same patient could have more than one kind of complication. Of 629 patients, there were 19 cases of postoperative 90-day death and 11 cases of missing data, 42 cases with post-operative 90-day reoperation and 7 cases with missing data, 44 cases with postoperative 90-day readmission and 3 cases with missing data, 155 cases with prolonged postoperative hospital stay and 3 cases with missing data. (2) Analysis of risk factors affecting the postoperative adverse outcomes in patients and PAF. Results of multivariate analysis showed that pulmonary infection and liver failure were independent risk factors for postoperative 90-day mortality ( RR=3.74, 12.15, 95% CI as 1.18-11.83, 1.98-74.48, P<0.05). Pulmonary infection demons-trated the highest PAF as 4.61% (95% CI as 3.94%-5.28%, P<0.05). Intra-abdominal ascites, pulmonary infection, bile leakage, and intra-abdominal hemorrhage were independent risk factors for post-operative 90-day reoperation ( RR=4.80, 3.62, 3.46, 4.99, 95% CI as 2.49-9.26, 1.42-9.21, 1.34-8.92, 1.55-16.06, P<0.05). Intra-abdominal ascites demonstrated the highest PAF as 8.65% (95% CI as 8.22%-9.08%, P<0.05). Intra-abdominal ascites, bile leakage, and liver failure were independent risk factors for postoperative 90-day readmission ( RR=6.20, 3.33, 14.33, 95% CI as 3.21-11.95, 1.33-8.35, 3.72-55.28, P<0.05). Intra-abdominal ascites demonstrated the highest PAF as 9.11% (95% CI as 8.85%-9.37%, P<0.05). Intra-abdominal ascites, pulmonary infection, bile leakage, liver failure, and wound infection were independent risk factors for prolonged postoperative hospital stay ( RR=2.29, 2.21, 2.26, 2.14, 3.35, 95% CI as 1.63-3.23, 1.41-3.46, 1.32-3.86, 1.11-4.13, 1.70-6.60, P<0.05). Intra-abdominal ascites demonstrated the highest PAF as 6.03% (95% CI as 5.71%-6.35%, P<0.05). Conclusion:Pulmonary infection is the most significant risk factor for postoperative 90-day mortality after curative-intent resection for GBC, while intra-abdominal ascites is the most significant risk factor for postoperative 90-day reoperation, postoperative 90-day readmission, and prolonged postoperative hospital stay.

Objective To explore the correlations between interleukin-6(IL-6),interleukin-8(IL-8),antimicrobial peptide LL-37 and the microbial abundance and the degree of mucosal injury in patients with trichomonal vaginitis(TV).Methods A total of 120 TV patients admitted from January 2022 to December 2024 were selected and divided into the occurrence group(n=63)and the non-occurrence group(n=57)according to presence and absence of mucosal injury.The general data,IL-6,IL-8,LL-37 and microbial abundance were compared between the two groups.According to the degree of mucosal injury,the occurrence group was divided into the mild subgroup(n=34),the moderate subgroup(n=20),and the severe subgroup(n=9).Pearson correlation analysis was applied to investigate the correlations between IL-6,IL-10,antimicrobial peptide LL-37,microbial abundance and the degree of mucosal injury.Multivariate logistic regression was used to analyze the influencing factors of mucosal injury in TV patients.The receiver operating characteristic curve(ROC)was used to evaluate the predictive value of relevant indicators for mucosal injury in TV patients.Result The levels of IL-6,IL-8,antimicrobial peptide LL-37,and the abundance of Actinobacteria and Gardnerella in the occurrence group were higher than those in the non-occurrence group,while the abundance of Firmicutes and Lactobacillus was lower than that in the non-occurrence group(P<0.05,P<0.01).Pearson correlation analysis showed that IL-6,IL-8,antimicrobial peptide LL-37,and abundance of Actinobacteria and Gardnerella were positively correlated with the degree of mucosal injury(r=0.543,0.713,0.352,0.409,0.659,P<0.01),while the abundance of Firmicutes and Lactobacillus was negatively correlated with the degree of mucosal injury(r=-0.540,-0.504,P<0.01).Multivariate logistic regression analysis showed that IL-6,IL-8,antimicrobial peptide LL-37,and abundance of Actinobacteria were risk factors for mucosal injury in TV patients,while the abundance of Firmicutes and the abundance of Lactobacillus were protective factors(P<0.05).The ROC curve showed that the area under the ROC curve(AUC)of the combined detection of IL-6,IL-8,antibacterial peptide 37,and the abundance of Actinobacteria,Firmicutes,and Lactobacillus in evaluating mucosal injury in TV patients was higher than that of the single detection(P<0.01).Conclusion IL-6,IL-8,antimicrobial peptide LL-37 and microbial abundance are closely related to the degree of mucosal injury in TV patients.The combined detection has a high value in evaluating the occurrence of mucosal injury in TV patients.

The medulla oblongata,situated at the caudal portion of the brainstem,serves as a critical regulatory center responsible for maintaining fundamental vital functions including respiratory and cardiovascular homeostasis.As a pivotal hub within the autonomic nervous system,it orchestrates the coordinated control of afferent and efferent neural pathways.Dysfunction of this region may precipitate life-threatening cardiorespiratory arrest,associated with substantial mortality rates.This case report presents a patient who developed acute extensive anterior myocardial infarction during treatment with dual antiplatelet therapy and moderate-intensity statins following acute medullary infarction.It is hypothesized that the pathogenesis may involve the acceleration of plaque erosion by the stroke-heart syndrome.This clinical case provides valuable insights into the complex neurocardiac interplay,particularly highlighting the imperative for enhanced recognition of brain-heart axis interactions in cerebrovascular pathology.

Objective To explore the correlations between interleukin-6(IL-6),interleukin-8(IL-8),antimicrobial peptide LL-37 and the microbial abundance and the degree of mucosal injury in patients with trichomonal vaginitis(TV).Methods A total of 120 TV patients admitted from January 2022 to December 2024 were selected and divided into the occurrence group(n=63)and the non-occurrence group(n=57)according to presence and absence of mucosal injury.The general data,IL-6,IL-8,LL-37 and microbial abundance were compared between the two groups.According to the degree of mucosal injury,the occurrence group was divided into the mild subgroup(n=34),the moderate subgroup(n=20),and the severe subgroup(n=9).Pearson correlation analysis was applied to investigate the correlations between IL-6,IL-10,antimicrobial peptide LL-37,microbial abundance and the degree of mucosal injury.Multivariate logistic regression was used to analyze the influencing factors of mucosal injury in TV patients.The receiver operating characteristic curve(ROC)was used to evaluate the predictive value of relevant indicators for mucosal injury in TV patients.Result The levels of IL-6,IL-8,antimicrobial peptide LL-37,and the abundance of Actinobacteria and Gardnerella in the occurrence group were higher than those in the non-occurrence group,while the abundance of Firmicutes and Lactobacillus was lower than that in the non-occurrence group(P<0.05,P<0.01).Pearson correlation analysis showed that IL-6,IL-8,antimicrobial peptide LL-37,and abundance of Actinobacteria and Gardnerella were positively correlated with the degree of mucosal injury(r=0.543,0.713,0.352,0.409,0.659,P<0.01),while the abundance of Firmicutes and Lactobacillus was negatively correlated with the degree of mucosal injury(r=-0.540,-0.504,P<0.01).Multivariate logistic regression analysis showed that IL-6,IL-8,antimicrobial peptide LL-37,and abundance of Actinobacteria were risk factors for mucosal injury in TV patients,while the abundance of Firmicutes and the abundance of Lactobacillus were protective factors(P<0.05).The ROC curve showed that the area under the ROC curve(AUC)of the combined detection of IL-6,IL-8,antibacterial peptide 37,and the abundance of Actinobacteria,Firmicutes,and Lactobacillus in evaluating mucosal injury in TV patients was higher than that of the single detection(P<0.01).Conclusion IL-6,IL-8,antimicrobial peptide LL-37 and microbial abundance are closely related to the degree of mucosal injury in TV patients.The combined detection has a high value in evaluating the occurrence of mucosal injury in TV patients.

This study was aimed at establishing a method of ultra-fast quantitative PCR for Brucella detection.We used an exogenous recombinant plasmid as the internal reference and targeted the T4SS secretion system,an important Brucella viru-lence factor,to design specific primers and probes.The sensitivity,specificity,and repeatability of this method were evaluated,and a standard curve was constructed.The coincidence rate of detection findings with this method versus quantitative PCR was determined.This method markedly decreased the detection time to only 10 minutes.The standard curve demonstrated a good linear relationship(Y=-3.410 7x+38.357,R2=0.998 5)with a low minimum detection limit of 10 copies/μL.The method exhibited good specificity and did not specifically amplify several common clinical bacteria other than Brucella.The de-tection of three concentrations of positive plasmids yielded coefficients of variation(CVs)of 0.20％to 0.91％,thus demonstra-ting the method's excellent repeatability.Furthermore,140 clinical samples were analyzed concurrently with the fluorescence PCR method,which yielded a 100％compliance rate and consistent results.Our findings indicated that the Brucella ultra-fast quantitative PCR was ultrafast;had high sensitivity,high specificity,and good specificity;and can be used for the clinical de-tection of Brucella and emergency investigation of epidemics.Therefore,this method is valuable for the early diagnosis of Bru-cella.

ObjectiveBased on analytic hierarchy process（AHP）-criteria importance through intercriteria correlation（CRITIC） hybrid weighting method， grey relational analysis and backpropagation artificial neural network（BP-ANN）， to optimize the water extraction process of Qizhi prescription， so as to provide an experimental basis for optimization of the preparation process of this prescription and the establishment of quality standards. MethodsL₉（3⁴） orthogonal test was employed， and the AHP-CRITIC hybrid weighting method was utilized to determine the weight coefficients of the quality fractions of various components， including astragaloside Ⅳ， polygalaxanthone Ⅲ， calycosin-7-O-β-D-glucoside， tenuifolin， and 3，6′-disinapoylsucrose， as well as the dry extract yield. The comprehensive score of each factor level combination in the orthogonal test were calculated as evaluation indicator to select the optimal extraction process parameters. The effects of extraction times， extraction time， and solvent dosage on the aqueous extraction process of the formula were investigated through intuitive analysis， variance analysis， and grey relational analysis. Meanwhile， a BP-ANN model was established to reverse-predict the optimal extraction process parameters of Qizhi prescription， and the optimized process parameters were validated. ResultsThe weight coefficients of the five index components（astragaloside Ⅳ， tenuifolin， calycosin-7-O-β-D-glucoside， polygalaxanthone Ⅲ， and 3，6′-disinapoylsucrose） and dry extract yield were 25.7%， 20.82%， 16.41%， 12.45%， 15.96% and 8.67%， respectively. The optimized extraction process parameters were extracted 3 times with 8， 6， 6 times the amount of water， each time for 1 h. The network prediction results of BP-ANN test samples were consistent with the orthogonal test results， and the mean square error（MSE） of the predicted and measured values of the network was <1%. The water extraction process of Qizhi prescription analyzed and predicted by relevant mathematical models was stable and feasible， which could effectively improve the extraction efficiency of the active ingredients of Astragali Radix and Polygalae Radix， and the average comprehensive score of the validation test was 90.85 with the relative standard deviation（RSD） of 1.55%. ConclusionThis study establishes a water extraction process for compound Qizhi granules， and the optimized extraction process can effectively improve the extraction efficiency of active ingredients， which provides useful references for the optimization of preparation process and the establishment of quality standards for other clinical experience formulas.

Objective:To develop and validate CT radiomics models based on machine learning for predicting recurrence of chronic subdural hematoma (cSDH) after endoscopic treatment.Methods:A retrospective study was performed; 252 patients with cSDH who underwent endoscopic treatment in Department of Neurosurgery, the Second Affiliated Hospital of Soochow University from October 2016 to October 2024 were selected. The clinical and imaging data of these patients were collected, and these patients were divided into a training set ( n=176) and a validation set ( n=76) at a ratio of 7:3. Patients in both sets were further sub-divided into a recurrence group and a non-recurrence group based on whether they had recurrence within 3 months of discharge. (1) Radiomics features of cSDH on initial non-enhanced CT images were extracted using 3D-Slicer software. Optimal features were selected through univariate analysis and least absolute shrinkage and selection operator (LASSO) regression analysis; based on these optimal features, 3 machine learning algorithms (Logistic, support vector machine [SVM], and K-nearest neighbor [KNN]) were used to construct CT radiomics models. Differences in predictive performance of different radiomics models were compared by analyzing indicators such as sensitivity, specificity, and area under receiver operating characteristic (ROC) curve (AUC), and the best model was selected. (2) Based on the initial non-enhanced CT images, cSDH was classified into homogeneous type, laminar type, septated type, and trabecular type according to Nakaguchi classification system; combined these cSDH typing with clinical features (clinical Markwalder's grade and bilateral hematoma), univariate analysis and multivariate Logistic regression analysis were used to screen the independent risk factors for cSDH recurrence. Based on these factors, the 3 machine learning algorithms (Logistic, SVM, KNN) were used to construct hematoma typing-clinical feature models; differences in predictive performance of different hematoma typing-clinical feature models were compared by analyzing indicators such as sensitivity, specificity, and AUC, and the best model was selected. (3) DeLong's test was used to compare the ROC curve differences between the CT radiomics model and hematoma typing-clinical feature model. Decision curve analysis was used to compare the effective scope of the CT radiomics model and hematoma typing-clinical feature model. Results:(1) Seven optimal CT radiomics features based on wavelet transform were obtained after univariate analysis and LASSO regression: one gray-level dependence matrix feature, one first-order energy feature, two gray-level co-occurrence matrix features, two gray level size zone matrix features, and one gray-level run-length matrix feature. The KNN model constructed based on these 7 optimal features had the best performance in predicting cSDH recurrence, with an AUC of 0.845, a sensitivity of 0.833, a specificity of 0.857, a recall rate of 0.833, and an F1 score of 0.476 in patients from the validation set. (2) Three independent risk factors for cSDH recurrence were screened out through univariate analysis and multivariate Logistic regression analysis: hematoma Nakaguchi classification, Markwalder's grade, and bilateral hematoma. Logistic model constructed based on these 3 factors had the best performance in predicting cSDH recurrence, with an AUC of 0.675, a sensitivity of 0.609, a specificity of 0.654, a recall rate of 0.609, and an F1 score of 0.311 in patients from the validation set. (3) DeLong's test showed that the AUC of the CT radiomics model was significantly greater than that of the hematoma typing-clinical feature model in patients from the training set and validation set ( P=0.027 and P=0.035). Decision curve analysis showed that in the CT radiomics model, the net benefit of the model was >0 when the risk threshold was 0.05-0.95; in the hematoma typing-clinical feature model, the net benefit of the model was >0 when the risk threshold was 0.05-0.55. Conclusion:The KNN model based on 7 CT radiomics features in this study can effectively predict the cSDH recurrence in patients after endoscopic treatment, and its performance is obviously better than that of hematoma typing-clinical feature model constructed in this study.