Objective:To discuss the associations of mismatch repair(MMR)in gastric cancer with preoperative inflammatory indicators and clinicopathological features in the gastric cancer patients,and to construct a gastric cancer MMR predictive model based on preoperative inflammatory indicators and clinicopathological features of the gastric cancer patients,and to provide new ideas for evaluation of MMR status in gastric cancer.Methods:The data of 254 gastric cancer patients who underwent surgical treatment from September 2020 to October 2023 were included.According to the expression of MMR protein,the patients were divided into MMR normal(proficiout MMR,pMMR)group and MMR deficient(dMMR)group.The preoperative inflammatory indicators and clinicopathological features data of the gastric cancer patients in two groups were collected.The associations between inflammatory indicators,clinicopathological features,and MMR in dMMR group and pMMR group were analyzed using Chi-square test.The independent predictive factors for dMMR were selected to construct the nomogram.Receiver operating characteristic(ROC)curve and calibration curve were used to evaluate the predictive efficacy,and decision curve was used to evaluate the practicality of the predication model.Results:A total of 254 gastric cancer patients were included in the study,with 221 patients(87％)in pMMR group and 33 patients(13％)in dMMR group.There were statistically significant differences(P＜0.05)in age,tumor location,tumor differentiation degree,maximum tumor diameter,platelet-to-lymphocyte ratio(PLR),alkaline phosphatase(AKP),alkaline phosphatase-to-albumin ratio(AAR),fibrinogen(FB)-to-lymphocyte(FLR),FB-to-albumin(AL)(FAR),D-dimer(D-D),and FB of the gastric cancer patients between dMMR group and pMMR group.Univariate and multivariate Logistic regression analysis revealed maximum tumor diameter[odd ratio(OR)=2.958,95％confidence interval(CI):1.196-7.314,P=0.019],tumor location(OR=4.013,95％CI:1.596-10.089,P=0.003),tumor differentiation(OR=3.006,95％CI:1.250-7.230,P=0.014),FAR(OR=2.793,95％CI:1.179-6.616,P=0.020),and carbohydrate antigen 199(CA199)(OR=0.279,95％CI:0.084-0.929,P-0.038)were the independent predictors of dMMR.The area under the ROC curve(AUC)value of the gastric cancer MMR prediction model constructed based on inflammatory indicators and clinical pathological characteristics was 0.800 with the sensitivity of 0.851 and the specificity of 0.606.The calibration curve of the nomogram was found to fit the ideal curve well,and in Hosmer-Lemeshow test P=0.412,the clinical decision curve showed a better net benefit.Conclusion:The preoperative inflammatory indicators and clinicopathological features are associated with MMR in gastric cancer;maximum tumor diameter,tumor location,tumor differentiation,CA199,and FAR are the independent predictors of dMMR.The prediction model based on the above predictors could predict the MMR status of the dMMR gastric cancer patients.

Objective:To investigate the multiple mediating effects of anxiety and depression on the relationship between dietary nutri-tion and perimenopausal symptoms in middle-aged and elderly women.Methods:A total of 1129 middle-aged and older women were surveyed using a dietary nutrition status questionnaire,the modified Kupperman Index,the Patient Health Questionnaire-9,and the Generalized Anxiety Disorder 7-item scale.The multiple mediating effect analysis was performed using the PROCESS macro in SPSS.Results:Dietary nutrition,anxiety,and depression were all significantly associated with perimenopausal symptoms(P<0.01).Dietary nutrition had a significant direct impact on perimenopausal symptoms(β=0.06,95%CI=0.002-0.119),and also exerted indirect nega-tive effects through three pathways:anxiety(β=0.059,95%CI=0.031-0.091),accounting for 29.65%of the total effect;depression(β=0.034,95%CI=0.017-0.054),accounting for 17.29%of the total effect;and anxiety-depression(β=0.045,95%CI=0.024-0.073),accounting for 22.76%of the total effect.Conclusion:Dietary nutrition not only directly affects perimenopausal symptoms,but also influences them through the mediating effects of anxiety and depression.

Empathy is one of the basic qualities that modern clinicians need to possess.Although traditional Chinese medicine has no definition for empathy,it does have practical applications.TCM clinical empathy,nurtured by Chinese excellent traditional culture,can be seen in TCM classics and clinical practice of famous doctors of previous generations,and has been inherited in the spiritual thinking of modern colleges and universities of Chinese medicine.However,at present,there is a relative lack of special training courses for"empathy"in Chinese medicine higher education.This paper first briefly describes the connotation,history,and neuroscience mechanism of the concept of"empathy".Secondly,the manifestations and characteristics of"empathy"in the clinical practice of traditional Chinese medicine were sorted out.Finally,we use modern medicine and psychology for reference,and combine the characteristics of traditional Chinese medicine to make suggestions for the cultivation of the ability of"empathy"in clinical Chinese medicine.

Currently, in precision cardiac surgery, there are still some pressing issues that need to be addressed. For example, cardiopulmonary bypass remains a critical factor in precise surgical treatment, and many core aspects still rely on the experience and subjective judgment of cardiopulmonary bypass specialists and surgeons, lacking precise data feedback. With the increasing elderly population and rising surgical complexity, precise feedback during cardiopulmonary bypass becomes crucial for improving surgical success rates and facilitating high-complexity procedures. Overcoming these key challenges requires not only a solid medical background but also close collaboration among multiple interdisciplinary fields. Establishing a multidisciplinary team encompassing professionals from the medical, information, software, and related industries can provide high-quality solutions to these challenges. This article shows several patents from a collaborative medical and electronic information team, illustrating how to identify unresolved technical issues and find corresponding solutions in the field of precision cardiac surgery while sharing experiences in applying for invention patents.

Objective     To establish a machine learning based framework to rapidly screen out high-risk patients who may develop atrial fibrillation (AF) from patients with valvular heart disease and provide the information related to risk prediction to clinicians as clinical guidance for timely treatment decisions. Methods     Clinical data were retrospectively collected from 1 740 patients with valvular heart disease at West China Hospital of Sichuan University and its branches, including 831 (47.76%) males and 909 (52.24%) females at an average age of 54 years. Based on these data, we built classical logistic regression, three standard machine learning models, and three integrated machine learning models for risk prediction and characterization analysis of AF. We compared the performance of machine learning models with classical logistic regression and selected the best two models, and applied the SHAP algorithm to provide interpretability at  the population and single-unit levels. In addition, we provided visualization of feature analysis results. Results    The Stack model performed best among all models (AF detection rate 85.6%, F1 score 0.753), while XGBoost outperformed the standard machine learning models (AF detection rate 71.9%, F1 score 0.732), and both models performed significantly better than the logistic regression model (AF detection rate 65.2%, F1 score 0.689). SHAP algorithm showed that left atrial internal diameter, mitral E peak flow velocity (Emv), right atrial internal diameter output per beat, and cardiac function class were the most important features affecting AF prediction. Both the Stack model and XGBoost had excellent predictive ability and interpretability. Conclusion    The Stack model has the highest AF detection performance and comprehensive performance. The Stack model loaded with the SHAP algorithm can be used to screen high-risk patients for AF and reveal the corresponding risk characteristics. Our framework can be used to guide clinical intervention and monitoring of AF.

Objective    To evaluate the use of machine learning algorithms for the prediction and characterization of cardiac thrombosis in patients with valvular heart disease and atrial fibrillation. Methods    This article collected data of patients with valvular disease and atrial fibrillation from West China Hospital of Sichuan University and its branches from 2016 to 2021. From a total of 2 515 patients who underwent valve surgery, 886 patients with valvular disease and atrial fibrillation were included in the study, including 545 (61.5%) males and 341 (38.5%) females, with a mean age of 55.62±9.26 years, and 192 patients had intraoperatively confirmed cardiac thrombosis. We used five supervised machine learning algorithms to predict thrombosis in patients. Based on the clinical data of the patients (33 features after feature screening), the 10-fold nested cross-validation method was used to evaluate the predictive effect of the model through evaluation indicators such as area under the curve, F1 score and Matthews correlation coefficient. Finally, the SHAP interpretation method was used to interpret the model, and the characteristics of the model were analyzed using a patient as an example. Results    The final experiment showed that the random forest classifier had the best comprehensive evaluation indicators, the area under the receiver operating characteristic curve was 0.748±0.043, and the accuracy rate  reached 79.2%. Interpretation and analysis of the model showed that factors such as stroke volume, peak mitral E-wave velocity and tricuspid pressure gradient were important factors influencing the prediction. Conclusion    The random forest model achieves the best predictive performance and is expected to be used by clinicians as an aided decision-making tool for screening high-embolic risk patients with valvular atrial fibrillation.

Purpose: This study aimed to investigate the factors associated with chemoresistance to neoadjuvant chemotherapy (NACT) followed by radical hysterectomy (RH) and construct a nomogram to predict the chemoresistance in patients with locally advanced cervical squamous carcinoma (LACSC). Materials and Methods: This retrospective study included 516 patients with International Federation of Gynecology and Obstetrics (2003) stage IB2 and IIA2 cervical cancer treated with NACT and RH between 2007 and 2017. Clinicopathologic data were collected, and patients were assigned to training (n=381) and validation (n=135) sets. Univariate and multivariate analyses were performed to analyze factors associated with chemoresistance to NACT. A nomogram was built using the multivariate logistic regression analysis results. We evaluated the discriminative ability and accuracy of the model using a concordance index and a calibration curve. The predictive probability of chemoresistance to NACT was defined as > 34%. Results: Multivariate analysis confirmed menopausal status, clinical tumor diameter, serum squamous cell carcinoma antigen level, and parametrial invasion on magnetic resonance imaging before treatment as independent prognostic factors associated with chemoresistance to NACT. The concordance indices of the nomogram for training and validation sets were 0.861 (95% confidence interval [CI], 0.822 to 0.900) and 0.807 (95% CI, 0.807 to 0.888), respectively. Calibration plots revealed a good fit between the modelpredicted probabilities and actual probabilities (Hosmer-Lemeshow test, p=0.597). Furthermore, grouping based on the nomogram was associated with progression-free survival. Conclusion We developed a nomogram for predicting chemoresistance in LACSC patients treated with RH. This nomogram can help physicians make clinical decisions regarding primary management and postoperative follow-up of the patients.

Objective:To investigate the application value of phase contrast MR angiography (PC MRA) in quantitative assessment for the hemodynamic features of functional posterior communicating artery (F-PCoA) in the patients with posterior circulation ischemia (PCI).Methods:Data of PC MRA in our Hospital from April 2015 to March 2017 were collected retrospectively. Twenty-six patients (PCI group) were diagnosed as PCI with F-PCoA, and other 25 patients were defined as non-PCI group including 10 patients with F-PCoA (non-PCI group 1) and 15 patients without F-PCoA (non-PCI group 2). The cross-sectional area, mean flux, mean velocity, minimum flux, maximum flux, minimum velocity, and maximum velocity were recorded, and the peak height of flux (maximum flux-minimum flux) and peak height of velocity (maximum velocity - minimum velocity) of basilar artery (BA) were calculated. The subtype, cross-sectional area, mean flux, mean velocity, blood flow direction, and absolute flux of F-PCoA in anterior-posterior direction(sum of both sides)were recorded and analyzed statistically.Results:The F-PCoA of 36 cases in PCI group and non-PCI group 1 were divided into three types: type A: the F-PCoA was consistent with anatomical posterior communicating artery (A-PCoA), accounting for 83.3%(30/36 cases); type B: the F-PCoA was not consistent with A-PCoA, accounting for 13.9%(5/36 cases);and type C: a mixed type with the F-PCoA was consistent with A-PCoA in only one side, accounting for 2.8%(1/36 cases). There were no significant differences in the composition of F-PCoA subtype (χ 2=0.609, P=0.737) and the absolute flux of F-PCoA in anterior-posterior direction( t=-0.576, P=0.568) between PCI group and non PCI group 1. It could be unidirectional or bidirectional blood flow forasingle F-PCoA during a cardiac cycle. The blood flow direction of bilateral F-PCoA was similar or not in one single case. The obviously main wave peak of the absolute flux curve of F-PCoA in anterior-posterior direction in PCI group were observed. There was a significant difference in the cross-sectional area of BA between non PCI group 1 and 2( t=-2.856, P=0.009), however no significant differences were found in the genders, mean flux, mean velocity, minimum flux, maximum flux, peak height of flux, minimum velocity, maximum velocity, and peak height of velocity of BA. Conclusions:PC MRA can be used to quantificationally assess the hemodynamic characteristics of F-PCoA such as flow direction, velocity and flux direction, absolute flux in anterior-posterior direction and morphological changes of F-PCoA, which may provide more information for the PCI diagnosis and treatment.

Objective: To establish a standard operation procedure (SOP) for ribosome genotyping (ribotyping) on Clostridioides (C.) difficile, supplement and verify ribotyping typing library, so as to improve the comparability of data between different laboratories and to develop surveillance network of C. difficil in China. Methods: Molecular typing of 54 reference strains from the United States and Europe of C. difficile were performed by using the SOP referencing correspondence from abroad and from our laboratory with a BioNumerics 7.6 software to estimate the reference library of types of C. difficile. Identification of 374 clinical and animal isolates of C. difficile from 13 cities in China between 2010 and 2018, to supplement the library information. Kappa test was used to evaluate the consistency. Results: Results of capillary electrophoresis of reference strains appeared clear and stable, which guaranteed the clustering results being fast and accurate. Results from the supplementary typing showed that there were 84 types of isolates, of which 25 RT types were consistent with reference strains from abroad, while 58 RT types were different from referenced types. In the 40 referenced types, 15 RT types were not found in this study. In the consistency evaluation, the Kappa value was 0.891 and (P<0.01), showing the two Molecular typing as consistent and with close resemblance. Conclusions The result of capillary electrophoresis by applying SOP for ribotyping on C. difficile base on QIAxcel capillary electrophoresis system, appeared clear and stable. The standardized library seemed more easily used for comparability and data sharing between the laboratories.

Objective To quantitatively compare the diagnostic capability of 68Ga-NGR and 18F-FDG in well-differentiated hepatocellular carcinoma (HCC) bearing mice by microPET/CT imaging.Methods The in vitro cellular uptake, in vivo microPET/CT imaging and biodistribution studies of 68Ga-NGR and 18F-FDG were quantitatively compared in SMMC-7721-based well-differentiated HCC.The human fibrosarcoma (HT-1080) and human colorectal adenocarcinoma (HT-29) cells/xenografts were respectively used as positive and negative reference groups for CD13.The expression of CD13 was qualitatively verified by immunohistostaining.The levels of CD13 and glucose-6-phosphatase (G6Pase) were semi-quantitatively analyzed by Western blot test for all 3 types of tumors.Two-sample t test was used for data analysis.Results The in vitro cellular uptake showed that the 68Ga-NGR uptake in SMMC-7721 and HT-1080 cells was higher than that in HT-29 cells, and the 68Ga-NGR uptake was higher than 18F-FDG uptake in SMMC-7721 cells.The in vivo microPET/CT imaging results revealed that the uptake of 68Ga-NGR in SMMC-7721 tumor was (2.17±0.21) %ID/g, remarkably higher compared to (0.73±0.26) %ID/g of 18F-FDG uptake (t=8.826, P<0.01).The tumor/liver ratio of 68Ga-NGR was 2.05±0.16, which was 2.03-fold higher than that of 18F-FDG.In the HT-1080 tumors, the uptakes of 68Ga-NGR and 18F-FDG were both high, and the values were (2.46±0.23) %ID/g, (3.47±0.31) %ID/g.The uptake of 68Ga-NGR was significantly lower than that of 18F-FDG in HT-29 tumors: (0.67±0.20) %ID/g vs (3.17±0.29) %ID/g;t=4.221, P<0.01.Western blot and immunohistostaining results were as follows: HT-1080(CD13+, G6Pase-), SMMC-7721(CD13+, G6Pase+), HT-29(CD13-, G6Pase-).Conclusions The uptake of 68Ga-NGR is higher than 18F-FDG uptake in SMMC-7721 tumor bearing mice, therefore it is worthwhile to consider the feasibility of clinical translation for PET/CT in diagnosis of HCC.Furthermore, because of the difference in 68Ga-NGR and 18F-FDG avidities in tumors with different molecular phenotypes of CD13 and G6Pase, there is an underlying potential for molecular imaging in the determination of molecular phenotypes.