ObjectiveTo establish a new noninvasive， simple， and convenient clinical predictive model by identifying independent predictive factors for rebleeding after endoscopic therapy in cirrhotic patients with esophagogastric variceal bleeding （EGVB）， and to provide a basis for individualized risk assessment and development of clinical intervention strategies. MethodsCirrhotic patients with EGVB who were diagnosed and treated in The First Affiliated Hospital of Xi’an Medical University from September 2018 to October 2023 were enrolled as subjects， and according to whether the patient experienced rebleeding within 1 year after endoscopic therapy， they were divided into rebleeding group with 93 patients and non-rebleeding group with 84 patients. Clinical data were collected and analyzed. The independent samples t-test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test was used for comparison of categorical data between two groups. A Logistic model was established based on the results of the univariate and multivariate analyses， and the receiver operating characteristic （ROC） curve and the area under the ROC curve （AUC） were used to assess the accuracy of the model. R software was used to visualize the model by plotting a nomogram， and the Bootstrap method was used for internal validation of the model. ResultsThe multivariate analysis showed that red blood cell count （RBC）， cholinesterase （ChE）， alkaline phosphatase （ALP）， albumin （Alb）， thrombin time （TT）， portal vein trunk diameter， sequential therapy， and primary prevention were independent predictive factors for rebleeding. Based on the results of the multivariate analysis， a logistic model was established as logit（P）=-0.805-1.978×（RBC）+0.001×（ChE）-0.020×（ALP）-0.314×（Alb）+0.567×（TT）+0.428×（portal vein trunk diameter）-2.303×［sequential therapy （yes=1， no=0）］-2.368×［primary prevention （yes=1， no=0）］. The logistic model （AUC=0.928， 95% confidence interval ［CI］： 0.893—0.964， P<0.001） had a better performance in predicting rebleeding than MELD score （AUC=0.603， 95%CI： 0.520—0.687， P=0.003）， Child-Pugh class （AUC=0.650， 95%CI： 0.578—0.722， P=0.001）， and FIB-4 index （AUC=0.587， 95%CI： 0.503—0.671， P=0.045）. The model had an optimal cut-off value of 0.607， a sensitivity of 0.817， and a specificity of 0.817. Internal validation confirmed that the model had good predictive performance and accuracy. ConclusionSequential therapy， implementation of primary prevention， an increase in RBC， and an increase in Alb are protective factors against rebleeding， while prolonged TT and widened main portal vein diameter are risk factors. The logistic model based on these independent predictive factors can predict rebleeding and thus holds promise for clinical application.

Purpose To investigate the value of intratumoral and peritumoral radiomics features based on multi-parametric MRI for preoperative prediction of lymphovascular invasion(LVI)in clinical lymph node-negative(cN0)breast cancer.Materials and Methods This retrospective study included 280 patients with pathologically confirmed breast cancer who underwent preoperative MRI at Henan Provincial People's Hospital from January 2017 to May 2021.Patients were randomly divided into a training cohort and a testing cohort.After Z-score normalization,feature selection was performed using Select K Best and least absolute shrinkage and selection operator regression.Random forest algorithms were used to construct intratumoral,peritumoral,and combined intratumoral-peritumoral radiomics models for LVI prediction.Model performance and clinical utility were evaluated using the area under the receiver operating characteristic curve(AUC),calibration curves and decision curve analysis.Results High Ki-67 expression(≥20%),axillary lymph node metastasis and positive diffusion weighted imaging(DWI)margin sign were more common in the LVI-positive group(χ2=5.959,18.316,20.554,all P<0.05).In the testing cohort,the AUC values of the dynamic contrast-enhanced(DCE)-Intra and DCE-Com models for predicting LVI status were higher than those of the DWI sequence,whereas the AUC value of the DWI-Peri model was higher than that of the DCE sequence.The DWI-DCE-Com model achieved AUCs of 0.836 and 0.818 in the training and testing cohorts,respectively,which surpassed the predictive performance of single-sequence intratumoral-peritumoral radiomics models(DWI-Com,DCE-Com).Decision curve analysis showed that the DWI-DCE-Com model provided greater net clinical benefit across a reasonable range of threshold probabilities.Conclusion Radiomics models based on multiparametric MRI features from intratumoral and peritumoral regions can effectively predict LVI status in cN0 breast cancer,offering valuable support for preoperative individualized treatment decision-making.

Objective To develop and validate an efficient and simple liquid chromatography with tandem mass spectrometry(LC-MS/MS)method for determination of polymyxin E in human plasma,and apply the established method in therapeutic drug monitoring(TDM)of polymyxin E.Methods The LC-MS/MS platform was based on AB SCIEX HPLC-4500MD system.Gradient elution was performed with 0.2％formic acid in water and 0.2％formic acid in acetonitrile.Phenomenex Kinetex XB-C18 column(100 mm × 2.1 mm,2.6 μm)were used.The analytes were detected by electrospray ionization(ESI)positive multiple reaction monitoring mode.The ion pairs for analytes(polymyxins E1,E2)and internal standard(polymyxins B1)were m/z 390.7→101.3,m/z 386.0→101.2,and m/z 402.3→101.2,respectively.Plasma samples were processed with protein precipitation method.Results Polymyxin E1 and E2 showed good linearity in the range of 0.031 2-6.24 mg/L and 0.006 15-1.23 mg/L,respectively.The within-run accuracy of polymyxin E1 and E2 in plasma ranged from 89.4％to 99.8％and 91.5％to 108.2％,respectively,while the between-run accuracy ranged from 91.8％to 104.7％and 95.6％to 105.2％,respectively.The within-run precision of polymyxin E1 and E2 in plasma ranged from 4.9％to 8.9％and 2.8％to 8.5％,respectively,while the between-run precision ranged from 4.1％to 7.6％and 4.2％to 9.8％,respectively.The average internal standard normalized matrix effect factors of polymyxins E1 and E2 were 96.9％-111.2％and 106.1％-112.8％in blank plasma samples from 6 different sources,102.5％-106.8％and 98.8％-105.2％in lipemic plasma,respectively,107.8％-108.9％and 106.9％-1 07.4％in hemolyzed plasma,respectively.The precision of matrix effects was less than 15.0％.The average recovery rate was 102.9％-107.5％for polymyxin E1 and E2,and 107.0％for internal standard polymyxin B1.The precision was less than 3.7％.Conclusions In this study,a simple and efficient LC-MS/MS method was established for determination of polymyxin E1 and E2 in human plasma,which is reliable in the therapeutic drug monitoring and pharmacokinetic study of polymyxin E.

Purpose To investigate the value of intratumoral and peritumoral radiomics features based on multi-parametric MRI for preoperative prediction of lymphovascular invasion(LVI)in clinical lymph node-negative(cN0)breast cancer.Materials and Methods This retrospective study included 280 patients with pathologically confirmed breast cancer who underwent preoperative MRI at Henan Provincial People's Hospital from January 2017 to May 2021.Patients were randomly divided into a training cohort and a testing cohort.After Z-score normalization,feature selection was performed using Select K Best and least absolute shrinkage and selection operator regression.Random forest algorithms were used to construct intratumoral,peritumoral,and combined intratumoral-peritumoral radiomics models for LVI prediction.Model performance and clinical utility were evaluated using the area under the receiver operating characteristic curve(AUC),calibration curves and decision curve analysis.Results High Ki-67 expression(≥20%),axillary lymph node metastasis and positive diffusion weighted imaging(DWI)margin sign were more common in the LVI-positive group(χ2=5.959,18.316,20.554,all P<0.05).In the testing cohort,the AUC values of the dynamic contrast-enhanced(DCE)-Intra and DCE-Com models for predicting LVI status were higher than those of the DWI sequence,whereas the AUC value of the DWI-Peri model was higher than that of the DCE sequence.The DWI-DCE-Com model achieved AUCs of 0.836 and 0.818 in the training and testing cohorts,respectively,which surpassed the predictive performance of single-sequence intratumoral-peritumoral radiomics models(DWI-Com,DCE-Com).Decision curve analysis showed that the DWI-DCE-Com model provided greater net clinical benefit across a reasonable range of threshold probabilities.Conclusion Radiomics models based on multiparametric MRI features from intratumoral and peritumoral regions can effectively predict LVI status in cN0 breast cancer,offering valuable support for preoperative individualized treatment decision-making.

Objective To analyze the temporal trends of gout disezse burden in China from 1990 to 2021,and construct an age-period-cohort(APC)model to explore the independent effects of age,period,and birth cohort on epidemiological indicators,and predict the future burden of gout disease in China from 2022 to 2035.Methods Data on gout disease burden in China during 1990-2021 were extracted from the Global Burden of Disease(GBD)2021 database.Joinpoint regression analysis was used to assess temporal trends.The APC model was applied to evaluate the age,period and cohort effects on prevalence risk and disability-adjusted life years(DALYs).A Bayesian age-period-cohort(BAPC)model was employed to project the age-standardized prevalence rate(ASPR)and age-standardized DALY rate(ASDR)of gout in China from 2022 to 2035.Results From 1990 to 2021,the incidence,prevalence and DALYs of gout in China all increased substantially,with overall rising trends in the age-standardized incidence rate(ASIR),ASPR and ASDR.Compared with 1990,the incidence,prevalence and DALYs in 2021 increased by 160.45%,181.12%,and 175.93%,respectively,while their age-standardized rates increased by 23.74%,26.48%and 25.89%.Joinpoint regression analysis revealed that average annual percentage changes(AAPCs)of 0.73%for ASIR,0.82%for ASPR and 0.80%for ASDR during 1990-2021.In 2021,the number of cases and DALYs reached their peaks in males aged 55-59 years and females aged 65-69 years.Both prevalence and DALY rates increased steadily with age,with marked rises starting at age 30 in men and age 40 in women.Overall,males showed higher prevalence,DALYs and corresponding rates than those of females across all age groups.APC model results indicated that the age effect,period effect and cohort effects on prevalence and DALY rates presented an overall upward tread.Decomposition analysis showed that population aging contributed the most to the increase in incidence and DALYs from 1990 to 2021.BAPC projections suggested that by 2035,the ASPR and ASDR of gout in China reached 890.50 per 100,000 and 27.26 per 100,000,respectively.Conclusion The ASPR and ASDR of gout in China are projected to continue increasing from 2022 to 2035.Targeted public health strategies for high-risk populations are urgently needed to reduce the growing burden of gout.

Objective:To identify risk factors influencing the incidence of hypertension among steelworkers (Homo sapiens) and establish an effective and easily implementable hypertension prediction model.Methods:In September 2023, 2214 steelworkers (Homo sapiens) were selected as study subjects. Basic demographic information, lifestyle, and occupational exposure data were collected, along with physiological measurements such as height, weight, and blood pressure. Multivariate unconditional logistic regression analysis was employed based on relevant literature to determine influencing factors for hypertension among steelworkers (Homo sapiens). Python 3.9 software was used to construct and compare logistic regression, support vector machine (SVM), random forest, extreme gradient boosting tree (XGBoost), and LGBM models. Model performance was evaluated using metrics such as receiver operating characteristic (ROC) curves, accuracy, calibration curves, and F1 scores. The Shapley Additive Explanations (SHAP) model was introduced for feature importance analysis to enhance the interpretability of the prediction model.Results:A total of 432 cases of hypertension were detected among 2214 study subjects, with a detection rate of 19.51%. Age, smoking status, salt intake, use of cooling equipment, carbon monoxide exposure, family history of hypertension, fasting blood glucose, triglycerides, and hemoglobin were identified as independent risk factors for hypertension ( P<0.05). A comparison of the five models revealed the following performance metrics: logistic regression achieved an accuracy of 0.853, F1 score of 0.680, Brier score of 0.108, and AUC of 0.907; SVM demonstrated an accuracy of 0.863, F1 score of 0.687, Brier score of 0.081, and AUC of 0.910; random forest showed an accuracy of 0.857, F1 score of 0.603, Brier score of 0.105, and AUC of 0.861; XGBoost yielded an accuracy of 0.850, F1 score of 0.684, Brier score of 0.117, and AUC of 0.899; and the LGBM model exhibited an accuracy of 0.838, F1 score of 0.625, Brier score of 0.112, and AUC of 0.870. Conclusion:The SVM model demonstrated strong predictive performance, effectively assessing the risk of hypertension among steelworkers (Homo sapiens) and facilitating targeted health management interventions.

Objective To develop and validate an efficient and simple liquid chromatography with tandem mass spectrometry(LC-MS/MS)method for determination of polymyxin E in human plasma,and apply the established method in therapeutic drug monitoring(TDM)of polymyxin E.Methods The LC-MS/MS platform was based on AB SCIEX HPLC-4500MD system.Gradient elution was performed with 0.2％formic acid in water and 0.2％formic acid in acetonitrile.Phenomenex Kinetex XB-C18 column(100 mm × 2.1 mm,2.6 μm)were used.The analytes were detected by electrospray ionization(ESI)positive multiple reaction monitoring mode.The ion pairs for analytes(polymyxins E1,E2)and internal standard(polymyxins B1)were m/z 390.7→101.3,m/z 386.0→101.2,and m/z 402.3→101.2,respectively.Plasma samples were processed with protein precipitation method.Results Polymyxin E1 and E2 showed good linearity in the range of 0.031 2-6.24 mg/L and 0.006 15-1.23 mg/L,respectively.The within-run accuracy of polymyxin E1 and E2 in plasma ranged from 89.4％to 99.8％and 91.5％to 108.2％,respectively,while the between-run accuracy ranged from 91.8％to 104.7％and 95.6％to 105.2％,respectively.The within-run precision of polymyxin E1 and E2 in plasma ranged from 4.9％to 8.9％and 2.8％to 8.5％,respectively,while the between-run precision ranged from 4.1％to 7.6％and 4.2％to 9.8％,respectively.The average internal standard normalized matrix effect factors of polymyxins E1 and E2 were 96.9％-111.2％and 106.1％-112.8％in blank plasma samples from 6 different sources,102.5％-106.8％and 98.8％-105.2％in lipemic plasma,respectively,107.8％-108.9％and 106.9％-1 07.4％in hemolyzed plasma,respectively.The precision of matrix effects was less than 15.0％.The average recovery rate was 102.9％-107.5％for polymyxin E1 and E2,and 107.0％for internal standard polymyxin B1.The precision was less than 3.7％.Conclusions In this study,a simple and efficient LC-MS/MS method was established for determination of polymyxin E1 and E2 in human plasma,which is reliable in the therapeutic drug monitoring and pharmacokinetic study of polymyxin E.

Liver cirrhosis is the terminal stage of various chronic liver diseases， with the main clinical manifestation of portal hypertension， which can lead to spontaneous portosystemic shunt （SPSS）. SPSS is very common in clinical practice and is closely associated with the prognosis of patients. This article summarizes the recent studies in the clinical significance of cirrhotic portal hypertension with SPSS， the controversies in studies， and the current status and future prospects and challenges of treatment， in order to provide a reference for the standardized diagnosis and treatment of portal hypertension.

The lacrimal gland organoids are innovative in vitro cultured tissue model that mimics the lacrimal gland, retaining its original histological and molecular biological properties. This model can more accurately reproduce the physiological environment of the lacrimal gland, including its ductal system and tear film protein secretion. It offers a new platform for studying the physiopathological basis of the lacrimal gland, establishing disease models, conducting regenerative medicine applications, and performing drug screening. Currently, organoids technology is continuously evolving, with ongoing updates to the methods for in vitro culturing of the lacrimal gland. These advancements gradually address challenges related to cultivation complexity, cost, and time, demonstrating a wide range of application potential. In this paper, we summarize the latest progress in lacrimal gland organoids research both domestically and internationally, exploring the development of lacrimal gland organoids, 3D construction technologies, and their potential for clinical applications, in order to provide new insights for clinical research on lacrimal gland-related diseases and to promote broader application of lacrimal gland organoids in drug development and personalized diagnosis and treatment.

The lacrimal gland organoids are innovative in vitro cultured tissue model that mimics the lacrimal gland, retaining its original histological and molecular biological properties. This model can more accurately reproduce the physiological environment of the lacrimal gland, including its ductal system and tear film protein secretion. It offers a new platform for studying the physiopathological basis of the lacrimal gland, establishing disease models, conducting regenerative medicine applications, and performing drug screening. Currently, organoids technology is continuously evolving, with ongoing updates to the methods for in vitro culturing of the lacrimal gland. These advancements gradually address challenges related to cultivation complexity, cost, and time, demonstrating a wide range of application potential. In this paper, we summarize the latest progress in lacrimal gland organoids research both domestically and internationally, exploring the development of lacrimal gland organoids, 3D construction technologies, and their potential for clinical applications, in order to provide new insights for clinical research on lacrimal gland-related diseases and to promote broader application of lacrimal gland organoids in drug development and personalized diagnosis and treatment.