Cardiovascular-Kidney-Metabolic (CKM) syndrome, a newly defined systemic disorder, is characterized by the pathological interplay among diabetes, chronic kidney disease (CKD), and cardiovascular disease (CVD). Recent studies have identified chronic inflammation not only as a central mediator in the pathological progression of CKM syndrome but also as a pivotal molecular hub that drives coordinated damage across multiple organ systems. Mechanistic investigations have revealed that aberrant activation of signaling pathways such as NF-κB, Wnt, PI3K-AKT, JAK-STAT, and PPAR constitutes a complex inflammatory regulatory network. Notably, these pathways facilitate inter-organ inflammatory crosstalk, establishing positive feedback loops among the heart, kidneys, and metabolic tissues. This, in turn, amplifies pathological processes such as oxidative stress, endothelial dysfunction, and fibrosis in a cascading manner.This review systematically delineates the multidimensional pathophysiological mechanisms of CKM syndrome, with particular emphasis on the inter-organ inflammatory regulation mediated by key signaling pathways. Furthermore, we explore the translational potential of therapeutic strategies targeting inflammatory cytokines (e.g., IL-1β, IL-6, and TNF-α) based on the latest clinical evidence, aiming to provide a theoretical framework and novel perspectives for disrupting the vicious cycle of CKM syndrome.

Although anthracyclines are important anticancer agents, their use is limited due to various adverse effects, particularly cardiac toxicity. Mechanisms underlying anthracycline-induced cardiotoxicity (AIC) are complex. Given the irreplaceable role of anthracyclines in treatment of malignancies and other serious diseases, early monitoring of AIC is paramount. In recent years, multiple studies have investigated various biomarkers for early detection of AIC. Currently, the two most common are cardiac troponin and B-type natriuretic peptide. In addition, a range of other molecules, including RNAs, myeloperoxidase (MPO), C-reactive protein (CRP), various genes, and others, also play roles in AIC prediction. Unfortunately, current research indicates a need to validate their sensitivity and specificity of these biomarkers especially in large study populations. In this review, we summarize the mechanisms and potential biomarkers of AIC, although some remain preliminary.

Patients with chronic kidney disease (CKD) exhibit a heightened risk of myocardial infarction. Chronic elevation of cardiac troponin levels frequently occurs in CKD patients, thereby diminishing their diagnostic utility in the evaluation of suspected non-ST-segment elevation acute myocardial infarction (NSTE-AMI). This study aimed to assess the diagnostic performance of initial high-sensitivity cardiac troponin I (hs-cTnI) for AMI in populations with and without chronic kidney disease. A total of 142 consecutive CKD patients attending the nephrology outpatient clinic were enrolled to investigate the association between baseline hs-cTnI concentrations and estimated glomerular filtration rate (eGFR). In parallel, A total of 237 CKD patients presenting to the emergency department with suspected NSTE-AMI were consecutively recruited, alongside a control group of 261 individuals with normal renal function. Receiver operating characteristic (ROC) curves assessed hs-cTnI diagnostic performance, with subgroup comparisons. CKD patients exhibited significantly higher median hs-cTnI levels which correlated inversely with eGFR (p < 0.001). The incidence of adjudicated NSTE-AMI was higher in the CKD cohort (18.1 % vs. 6.9 % in controls, p < 0.001). Diagnostic accuracy of initial hs-cTnI did not differ significantly between groups, as reflected by comparable AUC values (0.949 in CKD vs. 0.937 in controls, P = 0.783). However, specificity for NSTE-AMI was lower in CKD (60.1 % vs. 90.6 %, p < 0.001), which can be restored by applying a higher cutoff. Despite of reduced specificity in patients with CKD, hs-cTnI continues to be a valuable diagnostic marker. Adopting higher diagnostic thresholds and prospectively validating them may lead to improved diagnostic performance

INTRODUCTION: Cholangiocarcinoma (CHOL), a malignant tumor of the biliary system, is particularly concerning because of its high malignancy and poor prognosis, often leading to obstructive jaundice. The advent of metagenomic next-generation sequencing technology has expanded diagnostic capabilities, including the identification of microbes within tumors and their potential role in cancer progression. The aims of this study were to explore the bacterial composition in bile from patients with obstructive jaundice of different etiologies and to investigate the association between bile microbiota and biochemical analytes, as well as their potential as biomarkers for diagnosis of obstructive jaundice diseases. METHODS: Bile samples from patients with obstructive jaundice admitted to Beijing Friendship Hospital were collected and subjected to 16S rRNA and metagenomic sequencing. The study included patients diagnosed with benign biliary stricture, gallstone, and CHOL. Clinical data and bile chemical components were analyzed. The potential functional roles of the identified microbiota were predicted using bioinformatics tools. RESULTS: The study enrolled 13 patients with benign biliary stricture, 19 with gallstones, and 10 with CHOL. Significant differences in bile chemical components and microbial diversity were observed among the groups. The bile microbiota was dominated by distinct phyla and genera across the groups, with Proteobacteria and Fusobacteriota enriched in benign biliary stricture, Firmicutes and Desulfobacterota in CHOL, and Synergistota in patients with gallstone. Functional analysis revealed differences in gene functions related to metabolism and other biological processes. A correlation between bile microbiota and biochemical markers was established, and the combination of differential microbiota showed potential as a diagnostic marker for obstructive jaundice of different etiologies. DISCUSSION: Bile microbiota varies significantly among patients with obstructive jaundice of different etiologies. The identified microbial signatures and their functional roles could serve as novel diagnostic markers and provide insights into the pathogenesis of biliary diseases.

The cardiovascular-kidney-metabolic (CKM) syndrome represents a continuum linking metabolic dysfunction, chronic kidney disease, and cardiovascular disease, in which chronic inflammation plays a central role. However, conventional inflammatory biomarkers may not fully capture local inflammatory processes involved in CKM stage transitions. Pentraxin 3 (PTX3), a long pentraxin produced locally at sites of inflammation, may provide complementary information, yet its association with CKM staging has not been systematically evaluated. In this cross-sectional study, circulating PTX3 levels were measured in 240 adults, including healthy controls (stage 0, S0; n = 60) and individuals with stage 2 (S2; n = 60), stage 3 (S3; n = 60), and stage 4 (S4; n = 60) CKM, classified according to the CKM staging framework. Associations between PTX3 and inflammatory, metabolic, cardiac, and renal biomarkers were assessed using Spearman correlation analysis. Multivariable logistic regression models were constructed within the CKM population (S2–S4) to distinguish early-stage CKM (S2) from mid-advanced-stage CKM (S3 + S4). Model discrimination and calibration were evaluated using receiver operating characteristic (ROC) analysis and the Hosmer–Lemeshow goodness-of-fit test. PTX3 levels were significantly elevated in early-stage CKM (S2) compared with healthy controls (p < 0.001) and showed further differentiation between S2 and S3 (p < 0.01). PTX3 showed moderate correlations with biomarkers reflecting inflammatory activation, metabolic dysregulation, myocardial injury, and renal dysfunction, including high-sensitivity C-reactive protein (hs-CRP; r_s = 0.361, p < 0.001), glycated hemoglobin (HbA1c; r_s = 0.434, p < 0.001), triglycerides (TG; r_s = 0.296, p < 0.001), and high-sensitivity cardiac troponin T (hs-cTnT; r_s = 0.411, p < 0.001), and was inversely correlated with estimated glomerular filtration rate (eGFR; r_s = -0.419, p < 0.001). In multivariable logistic regression models adjusting for demographic factors, metabolic indices, and cardiorenal biomarkers, PTX3 remained independently associated with classification into mid-advanced-stage CKM (S3 + S4 vs S2; odds ratio [OR] per unit increase = 1.05, 95% confidence interval [CI]: 1.03–1.08; p < 0.001), whereas hs-CRP and procalcitonin (PCT) showed no independent associations. Compared with the clinical base model, addition of PTX3 improved model discrimination, increasing the AUC from 0.833 to 0.892 (ΔAUC = 0.059; DeLong p = 0.008), without evidence of impaired calibration. Circulating PTX3 is cross-sectionally associated with CKM stage classification and demonstrates incremental discriminative value beyond demographic, metabolic, and cardiorenal variables, as well as conventional inflammatory markers, in distinguishing early-stage from mid-advanced-stage CKM. These findings suggest that PTX3 may reflect inflammatory processes not fully captured by systemic markers, supporting its potential role in CKM risk stratification.

Background: The cardiovascular-kidney-metabolic (CKM) syndrome represents a continuum linking metabolic dysfunction, chronic kidney disease, and cardiovascular disease, in which chronic inflammation plays a central role. However, conventional inflammatory biomarkers may not fully capture local inflammatory processes involved in CKM stage transitions. Pentraxin 3 (PTX3), a long pentraxin produced locally at sites of inflammation, may provide complementary information, yet its association with CKM staging has not been systematically evaluated. Methods: In this cross-sectional study, circulating PTX3 levels were measured in 240 adults, including healthy controls (stage 0, S0; n = 60) and individuals with stage 2 (S2; n = 60), stage 3 (S3; n = 60), and stage 4 (S4; n = 60) CKM, classified according to the CKM staging framework. Associations between PTX3 and inflammatory, metabolic, cardiac, and renal biomarkers were assessed using Spearman correlation analysis. Multivariable logistic regression models were constructed within the CKM population (S2-S4) to distinguish early-stage CKM (S2) from mid-advanced-stage CKM (S3 + S4). Model discrimination and calibration were evaluated using receiver operating characteristic (ROC) analysis and the Hosmer-Lemeshow goodness-of-fit test. Results: PTX3 levels were significantly elevated in early-stage CKM (S2) compared with healthy controls ( p < 0.001) and showed further differentiation between S2 and S3 ( p < 0.01). PTX3 showed moderate correlations with biomarkers reflecting inflammatory activation, metabolic dysregulation, myocardial injury, and renal dysfunction, including high-sensitivity C-reactive protein (hs-CRP; ρ = 0.361, p < 0.001), glycated hemoglobin (HbA1c; ρ = 0.434, p < 0.001), triglycerides (TG; ρ = 0.296, p < 0.001), and high-sensitivity cardiac troponin T (hs-cTnT; ρ = 0.411, p < 0.001), and was inversely correlated with estimated glomerular filtration rate (eGFR; ρ = -0.419, p < 0.001). In multivariable logistic regression models adjusting for demographic factors, metabolic indices, and cardiorenal biomarkers, PTX3 remained independently associated with classification into mid-advanced-stage CKM (S3 + S4 vs S2; odds ratio [OR] per unit increase = 1.05, 95% confidence interval [CI]: 1.03–1.08; p < 0.001), whereas hs-CRP and procalcitonin (PCT) showed no independent associations. Incorporation of PTX3 significantly improved model discrimination (area under the curve [AUC], 0.892 vs 0.804 for the baseline model; ΔAUC = 0.088, p = 0.001 by DeLong test), without evidence of compromised calibration. Conclusions: Circulating PTX3 is cross-sectionally associated with CKM stage classification and demonstrates incremental discriminative value beyond conventional inflammatory markers in distinguishing early-stage from mid-advanced-stage CKM. These findings suggest that PTX3 may reflect inflammatory processes not fully captured by systemic markers, supporting its potential role in CKM risk stratification.