Objective:This study used data-independent acquisition (DIA) proteomics to analyze plasma protein expression in sepsis-induced coagulopathy (SIC), identify key biomarkers, and develop a diagnostic model.Methods:This prospective study included 46 adult sepsis patients from the intensive care unit. Patients were categorized into a general sepsis group ( n=26) and an SIC group ( n=20) based on established SIC criteria. Plasma samples underwent proteomic and bioinformatics analyses to identify differentially expressed protein (DEP) using LASSO regression and Random Forest. A diagnostic model was constructed and assessed via receiver operating characteristic (ROC) curve analysis. Results:The baseline data revealed that SIC patients exhibited longer prothrombin times, lower platelet counts, and higher D-dimer, fibrin degradation products, blood lactate, SOFA scores, and APACHE Ⅱ scores compared with general sepsis patients ( P<0.05). DIA proteomics identified 2 637 proteins, with 240 DEP meeting the criteria (fold change >1.5, P<0.05), including 81 upregulated and 159 downregulated DEP. Subcellular localization analysis revealed that DEPs were predominantly extracellular and nuclear. Gene ontology (GO) annotation showed that DEP were mainly involved in cellular physiology, biological regulation, and stress response processes in biological processes. Domain annotation revealed a predominance of immunoglobulin V regions in DEP, which are crucial for antigen recognition and binding. KEGG enrichment analysis showed significant enrichment of DEP in pathways related to natural killer cell-mediated cytotoxicity, glycosylphosphatidylinositol anchor biosynthesis, tumor necrosis factor signaling, and NF-κB signaling. LASSO regression identified angiogenin and C-type lectin domain family 10 member A as key DEP. The SIC diagnostic nomogram showed an area under the curve of 0.896, with 0.731 specificity and 0.900 sensitivity. Conclusion:The nomogram incorporating angiogenin and C-type lectin domain family 10 member A provides an accurate tool for SIC diagnosis.

Objective:This study used data-independent acquisition (DIA) proteomics to analyze plasma protein expression in sepsis-induced coagulopathy (SIC), identify key biomarkers, and develop a diagnostic model.Methods:This prospective study included 46 adult sepsis patients from the intensive care unit. Patients were categorized into a general sepsis group ( n=26) and an SIC group ( n=20) based on established SIC criteria. Plasma samples underwent proteomic and bioinformatics analyses to identify differentially expressed protein (DEP) using LASSO regression and Random Forest. A diagnostic model was constructed and assessed via receiver operating characteristic (ROC) curve analysis. Results:The baseline data revealed that SIC patients exhibited longer prothrombin times, lower platelet counts, and higher D-dimer, fibrin degradation products, blood lactate, SOFA scores, and APACHE Ⅱ scores compared with general sepsis patients ( P<0.05). DIA proteomics identified 2 637 proteins, with 240 DEP meeting the criteria (fold change >1.5, P<0.05), including 81 upregulated and 159 downregulated DEP. Subcellular localization analysis revealed that DEPs were predominantly extracellular and nuclear. Gene ontology (GO) annotation showed that DEP were mainly involved in cellular physiology, biological regulation, and stress response processes in biological processes. Domain annotation revealed a predominance of immunoglobulin V regions in DEP, which are crucial for antigen recognition and binding. KEGG enrichment analysis showed significant enrichment of DEP in pathways related to natural killer cell-mediated cytotoxicity, glycosylphosphatidylinositol anchor biosynthesis, tumor necrosis factor signaling, and NF-κB signaling. LASSO regression identified angiogenin and C-type lectin domain family 10 member A as key DEP. The SIC diagnostic nomogram showed an area under the curve of 0.896, with 0.731 specificity and 0.900 sensitivity. Conclusion:The nomogram incorporating angiogenin and C-type lectin domain family 10 member A provides an accurate tool for SIC diagnosis.

Objective:To analyze the incidence, mortality, survival patterns, and distribution characteristics of modifiable risk factors for colorectal cancer in selected global regions.Methods:Secondary analysis was conducted using data from the GLOBOCAN database and previous literature. We described the number of cases and age-standardized rates (ASRs) of incidence and mortality for colorectal cancer in China, the United States, the United Kingdom, and globally in 2022 and 2020, with gender-stratified analysis. ASRs were calculated using Segi's world standard population. Temporal trends in 5-year net survival rates were compared across three periods (2000-2004, 2005-2009, 2010-2014) among countries. Regional distribution differences in colorectal cancer deaths attributable to modifiable risk factors by gender were assessed in China.Results:In 2022, global colorectal cancer incidence and mortality were estimated at 1.926 million new cases and 904 000 deaths. China accounted for 27% of both global incidence (517 000 cases) and mortality (240 000 deaths). China's age-standardized incidence rate (20.1 per 100 000) was lower than those of the United States (27.0 per 100 000) and the UK (30.9 per 100 000). However, China's mortality rate (8.6 per 100 000) exceeded that of the US (7.9 per 100 000) but was lower than the UK (11.8 per 100 000). Compared to 2020, China demonstrated significant mortality reductions in 2022: males declined from 14.8 to 10.9 per 100 000, females from 9.4 to 6.5 per 100 000. Five-year net survival rates in China improved across periods for colon cancer (51.4%, 55.6%, 57.6%) and rectal cancer (49.5%, 52.5%, 56.9%), yet remained consistently lower than US and UK rates. Modifiable risk factors contributed to 45.1% of male and 41.4% of female colorectal cancer deaths in China, with marked regional disparities.Conclusions:China exhibits higher colorectal cancer incidence and mortality than global averages, with survival gaps persisting compared to developed nations. Regionally tailored comprehensive prevention strategies are essential to reduce disease burden through risk factor modification and optimized clinical management.

Objective:To examine the interaction between gender and the visceral adiposity index (VAI) in relation to the risk of type 2 diabetes mellitus (T2DM).Methods:This retrospective cohort study utilized data from the public Dryad database derived from the NAGALA (NAFLD in the Gifu Area, Longitudinal Analysis) project (1994-2016). Participants were stratified into quartiles based on VAI levels. A multivariate Cox proportional hazards regression model was employed to evaluate whether VAI independently predicts T2DM risk. Kaplan-Meier survival curves and receiver operating characteristic (ROC) curves were constructed for each VAI quartile. Subgroup analyses were conducted to examine associations across age and body mass index categories. Both multiplicative and additive interaction effects between gender and VAI were assessed. Additionally, gender-specific Cox models were fitted to further explore these associations.Results:A total of 15 453 participants [8 419 males and 7 034 females; mean age, (43.7±8.9) years] were included, with a median follow-up duration of 5.39 years. During follow-up, 373 participants (2.4%) developed T2DM. After adjustment for potential confounders, higher VAI levels were independently associated with increased T2DM risk ( HR=1.16; 95% CI 1.11-1.21), consistent with the results across VAI quartiles. Kaplan-Meier analysis revealed a significant trend of increasing T2DM incidence across VAI quartiles ( P<0.001). The area under the ROC curve for VAI in predicting T2DM at 3, 5, and 10 years was 0.755, 0.735, and 0.696, respectively. Sensitivity analyses showed that elevated VAI was associated with increased T2DM risk across all age and body mass index subgroups (all P<0.05). Regarding interaction analysis, the HR (95% CI) for the multiplicative interaction between VAI and gender was 1.22 (1.19-1.26). The relative excess risk of interaction was -1.08 (95% CI -2.96 to -0.06), the attributable proportion of interaction was -0.54 (95% CI -1.35 to -0.01), and the synergy index was 0.48 (95% CI 0.26-0.91), indicating a negative additive interaction. Using low-VAI women as the reference group, the risk of T2DM in high-VAI women was higher ( HR=2.53, 95% CI 1.59-4.02) compared to high-VAI men ( HR=2.01, 95% CI 1.49-2.72). In gender-specific analyses, increasing VAI remained significantly associated with elevated T2DM risk after adjustment in both females ( HR=1.43, 95% CI 1.21-1.68) and males ( HR=1.16; 95% CI 1.11-1.22), with consistent findings across VAI quartiles. Conclusions:VAI and gender demonstrated multiplicative and additive interaction in relation to T2DM risk. The association between increasing VAI and T2DM risk was more pronounced in women than in men.

IgA nephropathy (IgAN) is the most common primary glomerulonephritis. Mesangial hyperplasia and deposition of IgA immune complex are typical pathological changes of IgAN. Animal model is an important tool to explore the pathogenesis, diagnosis and treatment plan, and evaluate the safety and efficacy of drugs. At present, there are many kinds of IgAN animal models, including humanized animal models and non-humanized animal models, and there are great differences in the modeling principle, method, time and pathological changes. The humanized animal model is closer to the pathogenesis of IgAN in humans and has gradually become a research hotspot. In this paper, common animal models of IgAN in detail from the aspects of modeling method and time, characteristics and significance of each model, and the research progress of anthropomorphic animal models are reviewed to provide reference and inspiration for the basic research of IgAN.

Objective:To analyze the incidence, mortality, survival patterns, and distribution characteristics of modifiable risk factors for colorectal cancer in selected global regions.Methods:Secondary analysis was conducted using data from the GLOBOCAN database and previous literature. We described the number of cases and age-standardized rates (ASRs) of incidence and mortality for colorectal cancer in China, the United States, the United Kingdom, and globally in 2022 and 2020, with gender-stratified analysis. ASRs were calculated using Segi's world standard population. Temporal trends in 5-year net survival rates were compared across three periods (2000-2004, 2005-2009, 2010-2014) among countries. Regional distribution differences in colorectal cancer deaths attributable to modifiable risk factors by gender were assessed in China.Results:In 2022, global colorectal cancer incidence and mortality were estimated at 1.926 million new cases and 904 000 deaths. China accounted for 27% of both global incidence (517 000 cases) and mortality (240 000 deaths). China's age-standardized incidence rate (20.1 per 100 000) was lower than those of the United States (27.0 per 100 000) and the UK (30.9 per 100 000). However, China's mortality rate (8.6 per 100 000) exceeded that of the US (7.9 per 100 000) but was lower than the UK (11.8 per 100 000). Compared to 2020, China demonstrated significant mortality reductions in 2022: males declined from 14.8 to 10.9 per 100 000, females from 9.4 to 6.5 per 100 000. Five-year net survival rates in China improved across periods for colon cancer (51.4%, 55.6%, 57.6%) and rectal cancer (49.5%, 52.5%, 56.9%), yet remained consistently lower than US and UK rates. Modifiable risk factors contributed to 45.1% of male and 41.4% of female colorectal cancer deaths in China, with marked regional disparities.Conclusions:China exhibits higher colorectal cancer incidence and mortality than global averages, with survival gaps persisting compared to developed nations. Regionally tailored comprehensive prevention strategies are essential to reduce disease burden through risk factor modification and optimized clinical management.

IgA nephropathy (IgAN) is the most common primary glomerulonephritis. Mesangial hyperplasia and deposition of IgA immune complex are typical pathological changes of IgAN. Animal model is an important tool to explore the pathogenesis, diagnosis and treatment plan, and evaluate the safety and efficacy of drugs. At present, there are many kinds of IgAN animal models, including humanized animal models and non-humanized animal models, and there are great differences in the modeling principle, method, time and pathological changes. The humanized animal model is closer to the pathogenesis of IgAN in humans and has gradually become a research hotspot. In this paper, common animal models of IgAN in detail from the aspects of modeling method and time, characteristics and significance of each model, and the research progress of anthropomorphic animal models are reviewed to provide reference and inspiration for the basic research of IgAN.

Objective:To examine the interaction between gender and the visceral adiposity index (VAI) in relation to the risk of type 2 diabetes mellitus (T2DM).Methods:This retrospective cohort study utilized data from the public Dryad database derived from the NAGALA (NAFLD in the Gifu Area, Longitudinal Analysis) project (1994-2016). Participants were stratified into quartiles based on VAI levels. A multivariate Cox proportional hazards regression model was employed to evaluate whether VAI independently predicts T2DM risk. Kaplan-Meier survival curves and receiver operating characteristic (ROC) curves were constructed for each VAI quartile. Subgroup analyses were conducted to examine associations across age and body mass index categories. Both multiplicative and additive interaction effects between gender and VAI were assessed. Additionally, gender-specific Cox models were fitted to further explore these associations.Results:A total of 15 453 participants [8 419 males and 7 034 females; mean age, (43.7±8.9) years] were included, with a median follow-up duration of 5.39 years. During follow-up, 373 participants (2.4%) developed T2DM. After adjustment for potential confounders, higher VAI levels were independently associated with increased T2DM risk ( HR=1.16; 95% CI 1.11-1.21), consistent with the results across VAI quartiles. Kaplan-Meier analysis revealed a significant trend of increasing T2DM incidence across VAI quartiles ( P<0.001). The area under the ROC curve for VAI in predicting T2DM at 3, 5, and 10 years was 0.755, 0.735, and 0.696, respectively. Sensitivity analyses showed that elevated VAI was associated with increased T2DM risk across all age and body mass index subgroups (all P<0.05). Regarding interaction analysis, the HR (95% CI) for the multiplicative interaction between VAI and gender was 1.22 (1.19-1.26). The relative excess risk of interaction was -1.08 (95% CI -2.96 to -0.06), the attributable proportion of interaction was -0.54 (95% CI -1.35 to -0.01), and the synergy index was 0.48 (95% CI 0.26-0.91), indicating a negative additive interaction. Using low-VAI women as the reference group, the risk of T2DM in high-VAI women was higher ( HR=2.53, 95% CI 1.59-4.02) compared to high-VAI men ( HR=2.01, 95% CI 1.49-2.72). In gender-specific analyses, increasing VAI remained significantly associated with elevated T2DM risk after adjustment in both females ( HR=1.43, 95% CI 1.21-1.68) and males ( HR=1.16; 95% CI 1.11-1.22), with consistent findings across VAI quartiles. Conclusions:VAI and gender demonstrated multiplicative and additive interaction in relation to T2DM risk. The association between increasing VAI and T2DM risk was more pronounced in women than in men.

Objective:To explore the relationship between insomnia and osteoporosis.Methods:Mendelian randomization (MR) analysis were used in this study. The single nucleotide polymorphisms (SNPs) related to insomnia from genome-wide association analysis research data were selected as the instrumental variables by using inverse variance weighted (IVW), MR-Egger regression, weighted median method, maximum likelihood, penalized weighted median estimator, and Mendelian randomization robust adjusted profile score (MR-RAPS) to determine the causal relationship between insomnia and osteoporosis. Odds ratio ( OR) and 95% confidence interval ( CI) values were used to evaluate the association between insomnia and osteoporosis. Cochran′s Q-test was used to detect heterogeneity of SNPs, MR-Egger regression was used to test for level pleiotropy, and the leave-one-out method was used to test sensitivity, MR pleiotropy residual sum and outlier (MR-PRESSO) method and radial MR were used to detect erroneous outliers. Results:The screening criteria were set based on the three major assumptions of MR; finally, 31 SNPs were included in the MR analysis. The results of MR causal effect analysis using the IVW method showed that insomnia increased the risk of osteoporosis by about 0.7% ( OR=1.007, 95% CI 1.001-1.014, P=0.044); heterogeneity testing showed heterogeneity between SNPs ( Q=57.91, P<0.001); and the MR- Egger intercept test did not indicate horizontal pleiotropy in this study (intercept value=3.807×10 -5, P=0.888). Leave-one-out method showed that no single SNP had a significant impact on the overall results. No abnormal SNP was detected according to the MR-PRESSO results ( P=0.059), and radial MR did not detect any outliers. Conclusion:Mendelian randomization analysis showed that insomnia can increase the risk of osteoporosis.

Objective To investigate the predictive value of the expression levels of YY1 transcription fac-tor(YY1)and microRNA(miR)-181a-5p in peripheral blood mononuclear cell for adverse pregnancy out-comes in gestational diabetes mellitus(GDM).Methods A total of 200 patients with GDM were enrolled as the GDM group.100 healthy pregnant women who underwent prenatal examinations during the same period were selected as the control group.The expressions levels of YY1 and miR-181a-5p in peripheral blood mono-nuclear cell were detected by fluorescent quantitative PCR.Receiver operating characteristic(ROC)curve was drawn to analyze the predictive value of YY1 and miR-181a-5p for adverse pregnancy outcomes in GDM pa-tients.Results Compared with the control group,the expression levels of YY1 and miR-181a-5p in peripheral blood mononuclear cell of GDM group were obviously decreased(P＜0.05),and the incidence rates of post-partum hemorrhage,macrosomia and neonatal hypoglycemia in GDM group were obviously higher(P＜0.05).Multivariate Logistic regression analysis showed that age and poor blood glucose control were inde-pendent risk factors for adverse pregnancy outcomes in GDM patients(P＜0.05),and the expression levels of peripheral blood mononuclear cell YY1 and miR-181a-5p were independent protective factors for adverse preg-nancy outcomes in GDM patients(P＜0.05).ROC curve results showed that the area under the curve(AUC)of the expression levels of YY1 and miR-181a-5p in peripheral blood alone and in combination in predicting ad-verse pregnancy outcomes in GDM patients was 0.717,0.751 and 0.832,respectively,and the AUC of their combination was obviously higher than that of the two alone(P＜0.05).Conclusion The decreased expres-sion levels of YY1 and miR-181a-5p in peripheral blood mononuclear cell of GDM patients could increase the risk of adverse pregnancy outcomes,YY1 and miR-181a-5p are closely related to adverse pregnancy outcomes in GDM patients,and both could be used as predictors of adverse pregnancy outcomes in GDM patients.