The prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) is higher among individuals with inflammatory bowel disease (IBD) than in the general population. Emerging evidence indicates that the development of MASLD in patients with IBD may occur independently of traditional metabolic risk factors, suggesting a unique pathophysiological mechanism distinct from conventional MASLD pathways. Bile acids (BAs), which act as critical signaling molecules in enterohepatic circulation, play an essential role in maintaining gastrointestinal homeostasis through bidirectional gut–liver axis communication. These molecules are increasingly recognized as pivotal regulators in the progression of both MASLD and IBD. While previous studies have characterized the dynamics of BA in blood or fecal samples under both conditions, a comprehensive understanding of their metabolic profiles and the associated interactions within the gut–liver axis is still lacking. This review synthesizes current evidence from studies employing BA metabolomics to investigate IBD and MASLD. By focusing on BA signatures, we summarize conserved alterations between these two conditions and their potential mechanisms of disease progression. Our review advances understanding of BA-mediated pathways in IBD and MASLD, providing a foundation for assessing their roles in contributing to the pathogenesis of MASLD in patients with IBD.

Cholestatic liver disease(CLD)encompasses a range of acute and chronic disorders characterized by impaired bile formation and/or flow.If left untreated,it may progress to cirrhosis and even liver failure.In recent years,with the development of molecular biology and omics technologies,the diagnosis and treatment of CLD are entering the era of precision medicine.This article reviews the advances in the diagnosis of CLD based on genetic testing and omics biomarkers and summarizes the latest studies and clinical trials on hydrophilic bile acid,FXR agonist,PPAR agonist,antibiotics,and novel molecules in targeted therapy for CLD.In the future,integrating omics data and implementing individualized diagnosis and treatment will be the main directions in precision medicine for CLD.This article aims to provide a reference for basic research and clinical translation in the field of CLD.

Regarding the challenge of early identification of critically ill patients with acute exacerbation of chronic obstructive pulmonary disease(AECOPD),a radiomics-clinical fusion model is proposed based on non-contrast CT images of accessory respiratory muscles to predict life-threatening conditions.A retrospective study is conducted involving 233 AECOPD patients(153 non-life-threatening and 80 life-threatening cases).Patients are divided into a training set(n=186)and a test set(n=47)at a 4:1 ratio.A total of 1 874 radiomic features are extracted from the erector spinae and pectoralis muscle regions delineated by radiologists on non-contrast CT images,and the features selection is performed using maximum relevance minimum redundancy and least absolute shrinkage and selection operator(LASSO)algorithms.Meanwhile,clinical data are analyzed with t-test and LASSO for variable screening.The selected features are input into C-support vector classification,Logistic regression,random forest,adaptive boosting(AdaBoost),and extreme gradient boosting(XGBoost)to construct radiomics model,clinical model,and fusion model.Predictive performance and clinical practicality are evaluated in the test set using receiver operating characteristic curve,area under the curve(AUC),and decision curve analysis.The radiomics-clinical fusion model built with XGBoost outperformed standalone radiomics and clinical models,achieving an AUC of 0.902(95％CI 0.846,0.994),with accuracy,sensitivity,specificity,and precision of 0.837,0.933,0.786,and 0.7,respectively.Results demonstrate that the fusion model based on the non-contrast CT radiomics of accessory respiratory muscles and clinical data exhibits promising diagnostic performance,highlighting its potential clinical significance for stratified management and preemptive critical care intervention in AECOPD patients.

Objective To collect and analyze outpatient prescription data for exogenous cough treatment from a hospital in Shenzhen,and to identify the characteristics and medication patterns of traditional Chinese medicine(TCM).Methods This study collected prescriptions from a hospital in Shenzhen for exogenous cough treatment in January 2024.R language for data mining were used to analyze the medication frequency,clustering patterns,and association rules in the treatment of exogenous cough by TCM and to explore the medication patterns and the usage of classic formulas in TCM for this condition.Results A total of 451 outpatient prescriptions for exogenous cough were include,the top ten most frequently used herbs were Licorice,Bitter almond,Bellflower,Ephedra,Tangerine peel,Stemonae radix,Tuckahoe,Pinellia ternata,Nepeta,Bulb of thunberg fritillary.Cluster analysis and association rules revealed that San'ao decoction,Kikyodon soup,and Zhisou powder were commonly prescribed,targeting lung function,dispersing wind,and resolving phlegm to effectively alleviate cough symptoms.Significant differences in medication usage were observed across different syndrome types.For the wind cold attacking lung pattern,the core herbs were warm in nature and focused on dispersing with acrid-warm properties.Conversely,the treatment of wind heat attacking the lung pattern typically involved cold-natured herbs,with a primary focus on clearing and draining lung heat.Stratification by age revealed that the pediatric group often used drugs with mild properties,such as Stemona and Shegan.The young adult group tended to be prescribed cold-natured drugs like Forsythia and Hogfonnel Root.The middle-aged and elderly group preferred warming and tonifying drugs such as Japanese Catnip and Perilla frutescens.Conclusion The TCM treatment of exogenous cough primarily focuses on releasing the exterior and dispersing the lung.Due to the region's subtropical monsoon climate and temperature fluctuations physicians flexibly modified classical formulas such as San'ao decoction and Zhisou powder according to individual constitutions and symptom patterns.This targeted,syndrome-based approach effectively disperses the lung qi,stops cough and transforms phlegm,and alleviates cough.

Cholestatic liver disease(CLD)encompasses a range of acute and chronic disorders characterized by impaired bile formation and/or flow.If left untreated,it may progress to cirrhosis and even liver failure.In recent years,with the development of molecular biology and omics technologies,the diagnosis and treatment of CLD are entering the era of precision medicine.This article reviews the advances in the diagnosis of CLD based on genetic testing and omics biomarkers and summarizes the latest studies and clinical trials on hydrophilic bile acid,FXR agonist,PPAR agonist,antibiotics,and novel molecules in targeted therapy for CLD.In the future,integrating omics data and implementing individualized diagnosis and treatment will be the main directions in precision medicine for CLD.This article aims to provide a reference for basic research and clinical translation in the field of CLD.

Regarding the challenge of early identification of critically ill patients with acute exacerbation of chronic obstructive pulmonary disease(AECOPD),a radiomics-clinical fusion model is proposed based on non-contrast CT images of accessory respiratory muscles to predict life-threatening conditions.A retrospective study is conducted involving 233 AECOPD patients(153 non-life-threatening and 80 life-threatening cases).Patients are divided into a training set(n=186)and a test set(n=47)at a 4:1 ratio.A total of 1 874 radiomic features are extracted from the erector spinae and pectoralis muscle regions delineated by radiologists on non-contrast CT images,and the features selection is performed using maximum relevance minimum redundancy and least absolute shrinkage and selection operator(LASSO)algorithms.Meanwhile,clinical data are analyzed with t-test and LASSO for variable screening.The selected features are input into C-support vector classification,Logistic regression,random forest,adaptive boosting(AdaBoost),and extreme gradient boosting(XGBoost)to construct radiomics model,clinical model,and fusion model.Predictive performance and clinical practicality are evaluated in the test set using receiver operating characteristic curve,area under the curve(AUC),and decision curve analysis.The radiomics-clinical fusion model built with XGBoost outperformed standalone radiomics and clinical models,achieving an AUC of 0.902(95％CI 0.846,0.994),with accuracy,sensitivity,specificity,and precision of 0.837,0.933,0.786,and 0.7,respectively.Results demonstrate that the fusion model based on the non-contrast CT radiomics of accessory respiratory muscles and clinical data exhibits promising diagnostic performance,highlighting its potential clinical significance for stratified management and preemptive critical care intervention in AECOPD patients.

Objective:To construct a clinical decision-making ability indicator system based on evidence-based practice for pediatric nursing interns, and to provide a scientific basis for clinical teaching and evaluation.Methods:A method combining literature analysis, Delphi expert consultation, and empirical research was used. Firstly, a systematic search of Chinese and English databases (2018-2023) was conducted. Literature was screened based on the PICO framework and evidence-based data were extracted, resulting in a preliminary system consisting of 4 primary indicators, 12 secondary indicators, and 39 tertiary indicators. Subsequently, the indicators were revised through two rounds of Delphi expert consultation (25 experts with 19-27 years of work experience). The expert authority coefficients (Cr) were 0.898-0.907 and the Kendall's concordance coefficients were 0.351-0.420 ( P<0.001). Finally, the analytic hierarchy process was used to determine the weights, and the reliability and validity were verified through a questionnaire survey (sample size: 30 participants in preliminary survey and 58 participants in formal survey). Results:The constructed indicator system included 4 primary indicators (weights), 13 secondary indicators, and 42 tertiary indicators. The weights of the primary indicators were as follows: knowledge integration ability (0.300), evidence-based practice ability (0.250), clinical judgment ability (0.280), and ethical decision-making ability (0.170). The importance scores of all items exceeded 4.0 points (out of 5 points), and the coefficients of variation were less than 0.20. The reliability and validity tests showed that the Cronbach's α of the overall scale was 0.89, and the intraclass correlation coefficient was 0.88. The cumulative variance contribution rate of exploratory factor analysis was 69.30%. The confirmatory factor analysis demonstrated a good model fit with a comparative fit index of 0.93 and a root mean square error of approximation of 0.05. Conclusions:This indicator system has high scientificity and practicality, and can provide a reference for the standardized cultivation and evaluation of clinical decision-making ability of pediatric nursing interns. In the future, it is necessary to strengthen advanced evidence-based skills training and long-term application effectiveness tracking.

There are difficulties in the treatment of Alzheimer's disease (AD) in medical community. Since the surgery of cervical deep lymphatic vessel/lymphatic node-vein anastomosis (LVA/LnVA) has made clinical improvement in patients with AD, it offers a surgical option to treat AD. Especially improvements in cognitive impairment. However the mechanism in treatment of AD is not yet made clear. This article preliminarily explores the mechanism in improvement of some symptoms in patients with AD through cervical deep LVA/LnVA on the basis of morphological characteristics of the cribriform plate-cervical lymphatic pathway.

Objective:To establish tumor specific protein (SP70) targeted tumor cell enrichment technology and to assess applicational value of next-generation sequencing (NGS) analysis for enriched circulating tumor cell (CTC) in precision medicines of non-small cell lung cancer (NSCLC).Methods:The monoclonal antibody NJ001 was covalently coupled to the surface of magnetic beads to build targeted magnetic bead enrichment technology based on SP70. The limit of detection, coincidence rate, interference experiment, recovery test and clinical performance were evaluated. From March 2016 to August 2017, NGS analysis with or without pre-treatment of targeted enrichment for serous fluids of 43 NSCLC in the First Affiliated Hospital with Nanjing Medical University were compared (Kappa or Fisher exact test).Results:The CTC enrichment technology based on SP70 targeted immunomagnetic beads can specifically enrich tumor cells. The limit of detection was 10 4 SPC-A1 cells/L, and the coincidence rate, sensitivity and specificity were 100% (3/3). The endogenous interfering substances such as red blood cells, hemoglobin, white blood cells, epithelial cells and triglycerides had no interfering effects, as well as the exogenous interfering substances such as EDTA-K2, cefoxitin, carboplatin and paclitaxel. The recovery rate was 56.0% (56 000/100 000). A total of 30 gene mutations including 65 loci were found in 43 NSCLC under SP70 targeted enrichment, with a higher detection rate compared with unenrichment method [95.0% (19/20) vs 65.0% (13/20), χ 2=5.625, P=0.044]. Conclusion:In this study, SP70-targeted enriched CTC liquid biopsy method was established, with higher sensitivity and specificity of NGS detection than unenrichment method.

Objective:To construct a clinical decision-making ability indicator system based on evidence-based practice for pediatric nursing interns, and to provide a scientific basis for clinical teaching and evaluation.Methods:A method combining literature analysis, Delphi expert consultation, and empirical research was used. Firstly, a systematic search of Chinese and English databases (2018-2023) was conducted. Literature was screened based on the PICO framework and evidence-based data were extracted, resulting in a preliminary system consisting of 4 primary indicators, 12 secondary indicators, and 39 tertiary indicators. Subsequently, the indicators were revised through two rounds of Delphi expert consultation (25 experts with 19-27 years of work experience). The expert authority coefficients (Cr) were 0.898-0.907 and the Kendall's concordance coefficients were 0.351-0.420 ( P<0.001). Finally, the analytic hierarchy process was used to determine the weights, and the reliability and validity were verified through a questionnaire survey (sample size: 30 participants in preliminary survey and 58 participants in formal survey). Results:The constructed indicator system included 4 primary indicators (weights), 13 secondary indicators, and 42 tertiary indicators. The weights of the primary indicators were as follows: knowledge integration ability (0.300), evidence-based practice ability (0.250), clinical judgment ability (0.280), and ethical decision-making ability (0.170). The importance scores of all items exceeded 4.0 points (out of 5 points), and the coefficients of variation were less than 0.20. The reliability and validity tests showed that the Cronbach's α of the overall scale was 0.89, and the intraclass correlation coefficient was 0.88. The cumulative variance contribution rate of exploratory factor analysis was 69.30%. The confirmatory factor analysis demonstrated a good model fit with a comparative fit index of 0.93 and a root mean square error of approximation of 0.05. Conclusions:This indicator system has high scientificity and practicality, and can provide a reference for the standardized cultivation and evaluation of clinical decision-making ability of pediatric nursing interns. In the future, it is necessary to strengthen advanced evidence-based skills training and long-term application effectiveness tracking.