Cholangiocarcinoma (CCA) is a malignancy characterized by tumor cells originating in the liver or bile ducts, exhibiting features of cholangiocyte differentiation. It poses a significant clinical challenge due to the limited diagnostic and therapeutic options available. Robust animal models are essential for advancing our understanding of CCA pathogenesis and developing effective treatments. This review provides a comprehensive overview of CCA mouse models, highlighting various approaches, including chemical induction, genetically engineered models, and tumor xenografts. Each model is discussed in terms of its establishment techniques, pathological characteristics, and research significance, with a focus on intrahepatic CCA. Chemical induction models, such as diethylnitrosamine- and azoxymethane-induced models, offer insights into tumorigenesis processes, whereas genetically modified models involving alterations in key genes such as Kirsten rat sarcoma viral oncogene homolog, tumor protein 53, and isocitrate dehydrogenase serve as important tools for studying the molecular mechanisms underlying CCA. Xenograft models, including patient-derived xenografts, bridge the gap between experimental research and clinical applications, allowing for precise therapeutic evaluations. By comparing these models, this review underscores their respective advantages and limitations, paving the way for future studies aiming to optimize and innovate CCA modeling strategies.

Objective:To screen the Alzheimer's disease(AD)-related genes and construct its diagnostic model using bioinformatics technology and machine learning(ML)algorithms,to discuss the immunological characteristics of AD patients,and to provide novel biomarkers for AD diagnosis.Methods:The AD-related gene expression dataset GSE125583 was downloaded from the Gene Expression Omnibus(GEO)database.Differentially expressed genes(DEGs)were identified through differential analysis.Gene Ontology(GO)functional enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)signaling pathway enrichment analyses were performed to explore the biological functions and signaling pathways of DEGs.A protein-protein interaction(PPI)network was constructed,and hub genes were screened using Cytoscape software combined with three ML algorithms:Least Absolute Shrinkage and Selection Operator(LASSO),eXtreme Gradient Boosting(XGBoost),and Random Forest(RF).The screened hub genes were utilized to build an AD diagnostic model via RF,followed by feature importance ranking.The model's efficacy and key genes were evaluated using a test set.Single-sample gene set enrichment analysis(ssGSEA)was used for immune cell infiltration analysis between AD group and control group.Results:Differential analysis identified 1 287 DEGs.The GO functional enrichment analysis results revealed that DEGs were primarily involved in biological functions related to neural signaling,synapses,and vesicles.KEGG signaling pathway enrichment analysis indicated significant enrichment of DEGs in ion transport,neurotransmitter,and ligand-gated channel pathways.Nine overlapping hub genes were screened by the three ML algorithms.In the AD diagnostic model,the top four key genes with highest diagnostic performance were adenylate cyclase-activating polypeptide 1(ADCYAP1),brain-derived neurotrophic factor(BDNF),platelet-derived growth factor receptor β(PDGFRB),and C-X-C motif chemokine receptor 4(CXCR4),with corresponding area under the curve(AUC)values of 0.852,0.795,0.820,and 0.756,respectively.The model achieved an AUC of 0.828,accuracy of 81.25%,sensitivity of 84.40%,and specificity of 71.43%.The immune cell infiltration analysis results demonstrated higher infiltration of macrophages,monocytes,natural killer(NK)cells,and lymphocytes in AD tissue.Among these,NK/natural killer T(NKT)cells and plasmacytoid dendritic cells showed significant correlations with the four key genes(P<0.05).Conclusion:The feature genes screened based on bioinformatics and ML exhibit diagnostic potential for AD.Genes such as ADCYAP1 may serve as potential biomarkers for AD diagnosis,offering significant implications for early prevention and treatment.

Objective To conduct a bibliometric analysis of domestic and international literature on the research of Sijunzi Decoction over the past 20 years,and to explore the research status,hotspots,and development trends of Sijunzi Decoction.Methods This article retrieved journal articles related to the research of Sijunzi Decoction from 2004 to 2024 in the CNKI,Wanfang,VIP,and Web of Science databases.Microsoft Excel was used for publication volume analysis,while CiteSpace software was employed for keyword co-occurrence,clustering,and burst analysis,and then the analysis results were visualized.Results After literature retrieval and screening,3 573 Chinese articles and 113 English articles were included.Over the past two decades,the publication volume showed a trend of steadily increasing.The most frequent keywords in Chinese and English literature on the research of Sijunzi Decoction were spleen deficiency syndrome and gene expression,while the keywords with strongest burst were experimental research and data mining.Conclusion The research of Sijunzi Decoction in the last 20 years was mainly through animal experiments and clinical applications,and the research hotspots focus on the treatment of diseases of spleen deficiency syndrome and on the improvement of immune function of cancer patients.The extraction and identification of active components in Sijunzi Decoction and the study on the therapeutic mechanism in diseases of spleen deficiency syndrome are probably the future research trends.

Objective:To screen the main characteristic variables affecting the incidence of cardiovascular and cerebrovascular diseases,and to construct the Bayesian network model of cardiovascular and cerebrovascular disease incidence risk based on the top 10 characteristic variables,and to provide the reference for predicting the risk of cardiovascular and cerebrovascular disease incidence.Methods:From the UK Biobank Database,315 896 participants and related variables were included.The feature selection was performed by categorical boosting(CatBoost)algorithm,and the participants were randomly divided into training set and test set in the ratio of 7∶3.A Bayesian network model was constructed based on the max-min hill-climbing(MMHC)algorithm.Results:The prevalence of cardiovascular and cerebrovascular diseases in this study was 28.8％.The top 10 variables selected by the CatBoost algorithm were age,body mass index(BMI),low-density lipoprotein cholesterol(LDL-C),total cholesterol(TC),the triglyceride-glucose(TyG)index,family history,apolipoprotein A/B ratio,high-density lipoprotein cholesterol(HDL-C),smoking status,and gender.The area under the receiver operating characteristic(ROC)curve(AUC)for the CatBoost training set model was 0.770,and the model accuracy was 0.764;the AUC of validation set model was 0.759 and the model accuracy was 0.763.The clinical efficacy analysis results showed that the threshold range for the training set was 0.06-0.85 and the threshold range for the validation set was 0.09-0.81.The Bayesian network model analysis results indicated that age,gender,smoking status,family history,BMI,and apolipoprotein A/B ratio were directly related to the incidence of cardiovascular and cerebrovascular diseases and they were the significant risk factors.TyG index,HDL-C,LDL-C,and TC indirectly affect the risk of cardiovascular and cerebrovascular diseases through their impact on BMI and apolipoprotein A/B ratio.Conclusion:Controlling BMI,apolipoprotein A/B ratio,and smoking behavior can reduce the incidence risk of cardiovascular and cerebrovascular diseases.The Bayesian network model can be used to predict the risk of cardiovascular and cerebrovascular disease incidence.

Objective:To discuss the clinical efficacy of recombinant human growth hormone(rhGH)in the treatment of the pediatric patients with growth hormone deficiency(GHD)and idiopathic short stature(ISS),and to clarify its clinical application value in the pediatric patients with short stature of different etiologies.Methods:The clinical data of 132 children with short stature who treated with rhGH from January 2018 to January 2023 were collected.They were divided into GHD group(n=70)and ISS group(n=62)based on different etiologies.The bone age,target height(TH),body mass index(BMI),height standard deviation score(HtSDS),changes in height standard deviation scores(ΔHtSDS)before treatment and 6 months after treatment,and growth velocity(GV)of the pediatric patients were calculated.Propensity score matching(PSM)and inverse probability of treatment weighting(IPTW)were used to balance the confounding factors between the pediatric patients in two groups and the efficacy and safety of the pediatric patients in two groups were evaluated.Results:There were significant differences in whether children were full-term,bone age,bone age maturity,and TH of the pediatric patients between two groups(P<0.05).Compared with before treatment,the height and HtSDS of the pediatric patients in both GHD and ISS groups were significantly increased after treated for 6 months(P<0.05).Before matched by PSM,there were significant differences in full-term,bone age,bone age maturity,and TH of the pediatric patients between two groups(P<0.05).After matched by PSM,there were no significant differences in gender,region,term birth status,mode of delivery,feeding method,age,bone age,height,BMI,TH,and pretreatment HtSDS of the pediatric patients between two groups(P>0.05);the standardized mean difference(SMD)differences of covariates except for region were<0.2.After weighted by IPTW,there were no significant differences in gender,region,term birth status,mode of delivery,feeding method,age,bone age,height,BMI,TH,and pretreatment HtSDS of the pediatric patients between two groups(P>0.05);all SMD of covariates except for term birth status were<0.2.Before balancing covariates,after meatched by PSM matching,and after weighted by IPTW weighting compared with GHD group,the GV and ΔHtSDS of the pediatric patients in ISS group were slightly increased,but the difference was not significant(P>0.05).In terms of adverse reactions,2 cases(2.68%)of fasting hyperglycemia and 7 cases(10.00%)of hypothyroidism occurred in GHD group;3 cases(4.84%)of fasting hyperglycemia and 2 cases(3.23%)of hypothyroidism occurred in ISS group.Conclusion:rhGH can promote the height increase in the patients with GHD and ISS,and there is no significant difference in the height-increasing efficacy between GHD and ISS children.The incidence of adverse reactions is relatively low during treatment,indicating good overall safety.

Objective:Abnormal immune system activation and inflammation are crucial in causing Parkinson's disease.However,we still don't fully understand how certain immune-related genes contribute to the disease's development and progression.This study aims to screen key immune-related gene in Parkinson's disease based on weighted gene co-expression network analysis(WGCNA)and machine learning. Methods:This study downloaded the gene chip data from the Gene Expression Omnibus(GEO)database,and used WGCNA to screen out important gene modules related to Parkinson's disease.Genes from important modules were exported and a Venn diagram of important Parkinson's disease-related genes and immune-related genes was drawn to screen out immune related genes of Parkinson's disease.Gene ontology(GO)analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)were used to analyze the the functions of immune-related genes and signaling pathways involved.Immune cell infiltration analysis was performed using the CIBERSORT package of R language.Using bioinformatics method and 3 machine learning methods[least absolute shrinkage and selection operator(LASSO)regression,random forest(RF),and support vector machine(SVM)],the immune-related genes of Parkinson's disease were further screened.A Venn diagram of differentially expressed genes screened using the 4 methods was drawn with the intersection gene being hub nodes(hub)gene.The downstream proteins of the Parkinson's disease hub gene was identified through the STRING database and a protein-protein interaction network diagram was drawn. Results:A total of 218 immune genes related to Parkinson's disease were identified,including 45 upregulated genes and 50 downregulated genes.Enrichment analysis showed that the 218 genes were mainly enriched in immune system response to foreign substances and viral infection pathways.The results of immune infiltration analysis showed that the infiltration percentages of CD4+ T cells,NK cells,CD8+ T cells,and B cells were higher in the samples of Parkinson's disease patients,while resting NK cells and resting CD4+ T cells were significantly infiltrated in the samples of Parkinson's disease patients.ANK1 was screened out as the hub gene.The analysis of the protein-protein interaction network showed that the ANK1 translated and expressed 11 proteins which mainly participated in functions such as signal transduction,iron homeostasis regulation,and immune system activation. Conclusion:This study identifies the Parkinson's disease immune-related key gene ANK1 via WGCNA and machine learning methods,suggesting its potential as a candidate therapeutic target for Parkinson's disease.

The mesencephalic astrocyte-derived neurotrophic factor (MANF) has been recently identified as a neurotrophic factor, but its role in hepatic fibrosis is unknown. Here, we found that MANF was upregulated in the fibrotic liver tissues of the patients with chronic liver diseases and of mice treated with CCl₄. MANF deficiency in either hepatocytes or hepatic mono-macrophages, particularly in hepatic mono-macrophages, clearly exacerbated hepatic fibrosis. Myeloid-specific MANF knockout increased the population of hepatic Ly6C^high macrophages and promoted HSCs activation. Furthermore, MANF-sufficient macrophages (from WT mice) transfusion ameliorated CCl₄-induced hepatic fibrosis in myeloid cells-specific MANF knockout (MKO) mice. Mechanistically, MANF interacted with S100A8 to competitively block S100A8/A9 heterodimer formation and inhibited S100A8/A9-mediated TLR4-NF-κB signal activation. Pharmacologically, systemic administration of recombinant human MANF significantly alleviated CCl₄-induced hepatic fibrosis in both WT and hepatocytes-specific MANF knockout (HKO) mice. This study reveals a mechanism by which MANF targets S100A8/A9-TLR4 as a "brake" on the upstream of NF-κB pathway, which exerts an impact on macrophage differentiation and shed light on hepatic fibrosis treatment.

Objective To study the radiation injury of rat C6 glioma cell line by high resolution,1 H-nuclear magnetic resonance (1 H NMR) spectroscopy,and to preliminarily investigate its mechanism.Methods Metabolite concentrations in C6 cells were determined by 1 H NMR spectroscopy.Comet assay was used to evaluate DNA damage.Flow cytometry was used to determine the cell cycle and apoptosis rate.Colony-forming assay was used to measure the colony-forming rate and preliminarily investigate the mechanism of radiation injury.The resuhs were analyzed by one-way analysis of variance and Pearson correlation analysis.Results With the increase in radiation dose from 0 Gy to 1,5,10,and 15 Gy,DNA damage was enhanced in a dose-dependent manner (P=0.000-0.690);the percentage of cells in G1 phase increased (P =0.026-0.749);the apoptosis rate significantly increased (all P =0.000);the colony-forming rate significantly declined (P =0.000-0.004);the Lac/Cr ratio significantly decreased (P =0.000-0.015),which had a negative linear correlation with DNA damage parameters (tail length,r=-0.971;％DNA in the tail,r =-0.998;tail moment,r =-0.995) and apoptosis rate (r =0.978).Conclusions 1 H NMR spectroscopy reveals that the change in the Lac/Cr ratio is associated with injury and apoptosis of C6 cells after radiation.1 H NMR spectroscopy has the potential to predict radiation injury of glioma.

Objective To explore relationship of the anesthetic risks and intraoperative complications.Methods Preoperative anesthetic risks were assessed with Hussman's method from May 2015 to May 2016 in 2 494 surgical patients, including 1 462 males and 1 032 females.Intraoperative data and complications were tracked and recorded.Results Three hundred and thirty-six intraoperative complications occurred, accounting for 13.47% of total patients.The cardiovascular complications were a major intraoperative complications, accounting for 80.7%.2 494 patients were graded respectively into risk grade 1 with 1 540 (61.75%), grade 2 with 660 (26.46%), grade 3 with 202 (8.10%), grade 4 with 80 (3.21%) and grade 5 with 12 (0.48%).The incidence of complications were 112 (7.28%), 82 (12.42%), 82 (40.59%), 50 (62.50%) and 10 (83.33%) respectively.The sensitivity of prediction was 33.33%, 24.40%, 24.40%, 14.88% and 2.78%;the specificity 33.76%, 73.26%, 94.44%, 98.61% and 99.91%;and the accuracy 33.76%, 66.64%, 85.01%, 87.33% and 86.85%, respectively, in patients with risk grade 1, 2, 3, 4 and 5.Conclusion Hussman's method of anesthetic risks well predicts the intraoperative complications.

Objective To investigate and analyse the status and influential factors of palliative care knowledge of nursing undergraduates,then provide theoretical basis for palliative care education. Methods Using random sampling method, 400 nursing undergraduates were investigated by Palliative Care Quiz for Nursing (PCQN) and palliative care attitude questionnaire. Results 366 nursing undergraduates completed the survey whose scores were 8.363 ± 4.240, and 66.9%(244/366) of them had never heard of palliative care. Choosed right rate of PCQN was 41.13% (150/366). The scores of palliative care philosophy and principles 0.298±0.248, pain and symptom control and psychological scores 0.436 ± 0.235 and social and spiritual support scores 0.499 ± 0.318 had significant difference (F=38.866, P=0.000). The scores of palliative care attitude questionnaire were 36.756 ± 3.183, and the average score of all items were over 3. The palliative care attitude scores had significant difference in different grade (F=2.737, P=0.043). Conclusions Nursing undergraduates hold positive attitudes of palliative care, but the cognition degree were at a low level. To promote the development of palliative care, it should be strengthened publicity, education and training in this area. It is necessary to carry out palliative care education in nursing undergraduate students.