In epidemiological research, accurate estimation of prevalence is important for understanding disease distribution, evaluating the effectiveness of interventions, and allocating health resources. However, the prevalence estimation is often influenced by misclassification bias. Quantitative bias analysis (QBA) can comprehensively evaluate the potential impact of bias on outcomes from three dimensions: bias type, level, and uncertainty. Although QBA research has been developed rapidly in the world in recent years, the introduction of QBA design principles, evaluation methods, and application cases is still insufficient in China. In our previous study, we introduced a new method for adjusting misclassification bias of prevalence and suggested the corresponding analytical tools. Based on the results of previous studies, this paper introduces the principles of QBA design, evaluation indexes, and the application of Bayesian methods in bias adjustment, which provide methodological support for epidemiologists conducting research in this field.

In epidemiological research, accurate estimation of prevalence is important for understanding disease distribution, evaluating the effectiveness of interventions, and allocating health resources. However, the prevalence estimation is often influenced by misclassification bias. Quantitative bias analysis (QBA) can comprehensively evaluate the potential impact of bias on outcomes from three dimensions: bias type, level, and uncertainty. Although QBA research has been developed rapidly in the world in recent years, the introduction of QBA design principles, evaluation methods, and application cases is still insufficient in China. In our previous study, we introduced a new method for adjusting misclassification bias of prevalence and suggested the corresponding analytical tools. Based on the results of previous studies, this paper introduces the principles of QBA design, evaluation indexes, and the application of Bayesian methods in bias adjustment, which provide methodological support for epidemiologists conducting research in this field.

Biliary atresia is a progressive disease involving the intrahepatic and extrahepatic bile ducts. At present, the widely used treatment strategy is portojejunostomy (Kasai procedure). However, fat-soluble vitamin deficiency is common in children with biliary atresia, leading to growth retardation and malnutrition, which further affects the therapeutic effect prognosis of children. This article reviews the etiology, performance, prevention and treatment of fat-soluble vitamins deficiency in children with biliary atresia.

Objective To investigate the relationship between between the levels of serum malondialdehyde(MDA)and superoxide dismutase(SOD),the balance of oxidative/antioxidant stress,and the prognostic nu-tritional index(PNI)and the risk of early neurological deterioration in patients with acute ischemic stroke(AIS).Methods A total of 95 patients with suspected AIS admitted to the Second People's Hospital of Fos-han,Foshan from January to April 2023 were selected as the research subjects.Among them,71 patients who were finally diagnosed with AIS were included in the stroke group,and the remaining 24 non-AIS patients were included in the control group.According to the National Institutes of Health Stroke Rating Scale(NIH-SS)score,the stroke group was divided into the moderate-severe stroke group and the mild stroke group.Ac-cording to whether early neurological deterioration(END)occurred,it was divided into the END group and the non-END group.To analyze the correlations between the levels of serum SOD and MDA,SOD/MDA,and the PNI and the severity of stroke.The receiver operating characteristic(ROC)curve was applied to evaluate the predictive value of each index for the risk of END.By fitting the indicators with high diagnostic efficacy,a Fisher discriminant function model for evaluating the risk of END was established to verify the overall accura-cy rate.Results The levels of serum MDA and SOD,SOD/MDA and the PNI in the moderate to severe stroke group were statistically different from those in the mild stroke group(P＜0.05).There were statistically sig-nificant differences in the levels of serum MDA and SOD,SOD/MDA and the PNI among the END group,the non-END group and the control group(P＜0.05).The areas under the curve(AUC)of SOD,MDA,SOD/MDA and PNI for evaluating END were 0.692,0.727,0.777 and 0.819,respectively.The Fisher discriminant function model established by fitting the NIHSS score,the SOD/MDA and the PNI has an overall accuracy rate of 85.9％.Conclusion The END risk prediction model established by applying the Fisher discriminant function can provide early and objective reference basis for clinical prediction of END risk and has certain practical value.

Biliary atresia is a progressive disease involving the intrahepatic and extrahepatic bile ducts. At present, the widely used treatment strategy is portojejunostomy (Kasai procedure). However, fat-soluble vitamin deficiency is common in children with biliary atresia, leading to growth retardation and malnutrition, which further affects the therapeutic effect prognosis of children. This article reviews the etiology, performance, prevention and treatment of fat-soluble vitamins deficiency in children with biliary atresia.

Objective:To elucidate the causal relationship between serum metabolites and hepatocellular carcinoma (HCC) by the Mendelian randomization.Methods:The serum metabolite genome-wide association study (GWAS) data from the Metabolomics GWAS server was selected as the exposure group. The study sample includes 7 824 adults from two European population studies. The GWAS data of HCC was obtained from the IEU Open GWAS project as the outcome group, including a total sample of 197 611 cases, to evaluate the relationship between 486 serum metabolites and HCC. The inverse variance weighting method (IVW) was used as the primary analysis method. Supplementary analysis methods included MR-Egger, weighted median, simple mode, and weighted mode. Sensitivity analyses were conducted using Cochran's Q test, MR-Egger intercept test, leave-one-out analysis, and MR-PRESSO. Reverse MR and MR-Steiger tests were employed to exclude the influence of reverse causality. Metabolomic pathway analysis was performed using MetaboAnalyst 5.0. Results:The MR results finally identified six metabolites with potential causal relationships with HCC: mannose ( OR=0.38, 95% CI: 0.16-0.92, P=0.032), γ-glutamyltyrosine ( OR=3.34, 95% CI: 1.14-9.83, P=0.028), glycerol-3-phosphate ( OR=0.17, 95% CI: 0.04-0.70, P=0.014), 2-linoleoylglycerophosphocholine ( OR=0.33, 95% CI: 0.13-0.98, P=0.028), 1-stearoylglycerophosphoethanolamine ( OR=2.44, 95% CI: 1.05-5.65, P=0.038), and palmitoyl sphingomyelin ( OR=5.62, 95% CI: 1.56-20.18, P=0.008). Sensitivity analyses for the six metabolites showed robustness, with no abnormal variables in the heterogeneity tests, and no evidence of genetic pleio-tropy was observed. Both reverse MR and Steiger tests did not support the existence of reverse causality between the metabolites and HCC. Metabolic pathway analysis indicated that ether lipid metabolism is closely related to the occurrence of HCC ( P=0.002). Conclusion:Six serum metabolites (mannose, γ-glutamyltyrosine, glycerol-3-phosphate, 2-linoleoylglycerophosphocholine, 1-stearoylglycerophosphoethanolamine, and palmitoyl sphingomyelin) have causal relationships with HCC.

Objective To study the diagnostic value of miR-571 for liver fibrosis by detecting miR-571 expression in the peripheral blood of patients with liver fibrosis.Methods From December 2022 to September 2023,40 patients with liver fibrosis,40 patients with chronic hepatitis,and 40 healthy controls were chosen as research subjects.The expression level of miR-571 in peripheral blood was detected using a real-time quantitative polymerase chain reaction,and the relative expression of miR-571 in each group was evaluated.The Spearman correlation method was utilized to examine the relationship between miR-571 and clinical detection indices.To assess the capacity of miR-571 and the multivariate diagnostic model to identify liver fibrosis,binary logistic regression was used to create a multivariate diagnostic model,and ROC curves were generated.Results The expression of miR-571 was significantly higher in the liver fibrosis group than in the healthy control and hepatitis groups,and the difference was statistically significant(P<0.001).The expression level of miR-571 was positively connected with ALT,APRI score,and FIB-4 index(r = 0.23,0.30,0.22,P<0.05)and negatively correlated with PLT(r =-0.19,P<0.05)according to Spearman correlation analysis.Logistic regression research revealed that miR-571 and the FIB-4 index were independent risk factors for liver fibrosis.The AUC for miR-571 to diagnose fibrosis was 0.91(95%CI:0.85～0.96),while the AUC for miR-571 paired with the FIB-4 index was 0.94(95%CI:0.90～0.98).Conclusion MiR-571 expression was shown to be considerably higher in the peripheral blood of hepatic fibrosis patients,and the combined FIB-4 index offers some clinical diagnostic value for hepatic fibrosis.

Objective:To elucidate the causal relationship between serum metabolites and hepatocellular carcinoma (HCC) by the Mendelian randomization.Methods:The serum metabolite genome-wide association study (GWAS) data from the Metabolomics GWAS server was selected as the exposure group. The study sample includes 7 824 adults from two European population studies. The GWAS data of HCC was obtained from the IEU Open GWAS project as the outcome group, including a total sample of 197 611 cases, to evaluate the relationship between 486 serum metabolites and HCC. The inverse variance weighting method (IVW) was used as the primary analysis method. Supplementary analysis methods included MR-Egger, weighted median, simple mode, and weighted mode. Sensitivity analyses were conducted using Cochran's Q test, MR-Egger intercept test, leave-one-out analysis, and MR-PRESSO. Reverse MR and MR-Steiger tests were employed to exclude the influence of reverse causality. Metabolomic pathway analysis was performed using MetaboAnalyst 5.0. Results:The MR results finally identified six metabolites with potential causal relationships with HCC: mannose ( OR=0.38, 95% CI: 0.16-0.92, P=0.032), γ-glutamyltyrosine ( OR=3.34, 95% CI: 1.14-9.83, P=0.028), glycerol-3-phosphate ( OR=0.17, 95% CI: 0.04-0.70, P=0.014), 2-linoleoylglycerophosphocholine ( OR=0.33, 95% CI: 0.13-0.98, P=0.028), 1-stearoylglycerophosphoethanolamine ( OR=2.44, 95% CI: 1.05-5.65, P=0.038), and palmitoyl sphingomyelin ( OR=5.62, 95% CI: 1.56-20.18, P=0.008). Sensitivity analyses for the six metabolites showed robustness, with no abnormal variables in the heterogeneity tests, and no evidence of genetic pleio-tropy was observed. Both reverse MR and Steiger tests did not support the existence of reverse causality between the metabolites and HCC. Metabolic pathway analysis indicated that ether lipid metabolism is closely related to the occurrence of HCC ( P=0.002). Conclusion:Six serum metabolites (mannose, γ-glutamyltyrosine, glycerol-3-phosphate, 2-linoleoylglycerophosphocholine, 1-stearoylglycerophosphoethanolamine, and palmitoyl sphingomyelin) have causal relationships with HCC.

Glioblastoma multiforme (GBM), a highly malignant and heterogeneous brain tumor, contains various types of tumor and non-tumor cells. Whether GBM cells can trans-differentiate into non-neural cell types, including mural cells or endothelial cells (ECs), to support tumor growth and invasion remains controversial. Here we generated two genetic GBM models de novo in immunocompetent mouse brains, mimicking essential pathological and molecular features of human GBMs. Lineage-tracing and transplantation studies demonstrated that, although blood vessels in GBM brains underwent drastic remodeling, evidence of trans-differentiation of GBM cells into vascular cells was barely detected. Intriguingly, GBM cells could promiscuously express markers for mural cells during gliomagenesis. Furthermore, single-cell RNA sequencing showed that patterns of copy number variations (CNVs) of mural cells and ECs were distinct from those of GBM cells, indicating discrete origins of GBM cells and vascular components. Importantly, single-cell CNV analysis of human GBM specimens also suggested that GBM cells and vascular cells are likely separate lineages. Rather than expansion owing to trans-differentiation, vascular cell expanded by proliferation during tumorigenesis. Therefore, cross-lineage trans-differentiation of GBM cells is very unlikely to occur during gliomagenesis. Our findings advance understanding of cell lineage dynamics during gliomagenesis, and have implications for targeted treatment of GBMs.
Mice ; Animals ; Humans ; Glioblastoma/pathology* ; Endothelial Cells/pathology* ; DNA Copy Number Variations ; Brain/metabolism* ; Brain Neoplasms/pathology*

Objective:To explore the common signaling pathways of Helicobacter pylori(Hp) infection and rosacea and screen Hub genes by bioinformatic analysis. Methods:Gene expression data sets related to Hp (GSE70394) and rosacea (GSE65914) were downloaded from GEO database. The common differentially expressed genes (DEGs) were screened by using the limma package of R and Venn diagram. Metascape database was used for gene ontology(GO) enrichment analysis, and clusterProfiler package of R was used for Kyoto encyclopedia of genes and genomes(KEGG) analysis on up-regulated and down-regulated genes. Subsequently, STRING and Cytoscape software were used to establish protein-protein interaction(PPI) network and its internal plug-in MCODE and Cytohubba were applied to screen key functional modules and Hub genes, then Hub genes were imported into GeneMANIA to construct Hub genes co-expression network. Finally, GO and KEGG enrichment analysis of Hub genes were performed again.Results:GSE70394 and GSE65914 data sets included three samples of AGS cells without Hp infection and three samples of AGS cells 24 hours after Hp infection, skin tissues from nineteen rosacea patients and ten healthy volunteers, respectively. Finally, 139 common DEGs were obtained including 93 up-regulated genes and 46 down-regulated genes. GO enrichment analysis mainly focused on smooth muscle cell regulation, vascular development and lipid metabolism. KEGG enrichment analysis mainly involved lipid and atherosclerosis, inflammatory response and immune-related pathways, such as PPAR signaling pathway, cytokine-cytokine receptor interaction, Th17 cell differentiation, IL-17 signaling pathway and NF-κB signaling pathway. Total of 16 Hub genes were identified by Cytohubba, including SPRR1B, GCLM, KRT16, GPX2, S100A2, SOD2, MMP1, MSMO1, HMOX1, GLRX, IL-1β, CXCL1, PPARγ, HMGCS1, SRXN1 and SPRR3.Conclusion:There is a link existing between Hp infection infection and rosacea. Hp may be involved in the occurrence and development of rosacea by mediating inflammatory immune response and regulating lipid metabolism, the selected Hub genes and related signaling pathways may provide a theoretical reference for subsequent correlation analysis.