The aberrant expression of miR-433 has been validated in some types of cancers. However, the expression profile and the biological function of miR-433 on colon cancer are still elusive. This study was designed to investigate the function of miR-433 on the proliferation and invasion of colon cancer cells. We detected the expression of miR-433 in colon cancer tissues, adjacent normal tissues, and cell lines. CCK8 and Transwell assays were performed to explore the impact of miR-433 on colon cancer cell proliferation and invasion. The luciferase reporter assay was applied to identify the direct target of miR-433. The results demonstrated that miR-433 was downregulated in colon cancer tissues and cell lines when compared with the control. Overexpression of miR-433 significantly suppressed the ability of colon cancer cell proliferation and invasion, whereas knockdown of miR-433 remarkably enhanced cell proliferation and invasion. Homeobox A1 (HOXA1) was identified as a target of miR-433, and it mediated the functions of miR-433 on colon cancer cells. To conclude, we revealed that miR-433 was downregulated in colon cancer, and it inhibited colon cancer cell proliferation and invasion by directly targeting HOXA1.

Aims Atrial fibrillation (AF) is a common arrhythmia associated with increased risks of stroke and heart failure. Early differentiation between paroxysmal and persistent AF at first diagnosis is critical for guiding treatment decisions. This study aimed to develop an interpretable machine learning model based on structured electronic health records (EHR) to distinguish AF subtypes and identify key contributing factors. Methods and results In this multicenter, retrospective cohort study, data were collected from three tertiary hospitals in China between January 2013 and January 2023. A total of 11,986 patients with suspected AF were screened, of whom 4155 patients with first-diagnosed AF were included (paroxysmal: 2565 [61.3%]; persistent: 1620 [38.7%]). Structured EHR variables including clinical demographics, serological indicators, and echocardiographic parameters were extracted. Variable selection was performed using Spearman correlation and least absolute shrinkage and selection operator regression. Three machine learning algorithms were trained and externally validated. The CatBoost model achieved the best performance, with an area under the receiver operating characteristic curve of 0.876 (95% CI: 0.871–0.880) and accuracy of 0.808 (95% CI: 0.803–0.816). Sensitivity and specificity ranged from 0.802 to 0.811. Shapley additive explanations (SHAP) were used to interpret model outputs and identify variables most associated with AF subtype classification. Conclusion This multicenter study demonstrates that interpretable machine learning models based on structured EHR data can accurately distinguish paroxysmal from persistent AF at first diagnosis. The proposed model may facilitate early subtype-specific risk stratification and personalized treatment, potentially improve outcomes and reduce disparities in AF care across different medical conditions.

Background: Atrial fibrillation and flutter (AF/AFL) represent a major global public health challenge, contributing significantly to stroke, heart failure, and cardiovascular mortality. While previous studies have documented a rising AF/AFL burden, comprehensive comparisons of long-term trends and forecasts across regions—particularly benchmarking China against Southeast Asia, Europe, and global averages—remain limited. This study aims to quantify the AF/AFL burden across these regions from 1990 to 2021 and project trends to 2050. Methods: Using data from the Global Burden of Disease Study 2021, we analysed the burden of AF/AFL from 1990 to 2021 in China, Southeast Asia, Europe, and globally. We examined incidence, prevalence, mortality, and disability-adjusted life years (DALYs). Advanced analytical methods, including Joinpoint regression, age-period-cohort modelling, decomposition analysis, Frontier analysis and Bayesian forecasting were employed to assess trends, drivers, and projections to 2050. Finding: From 1990 to 2021, China experienced the most rapid increase in age-standardized incidence rate (ASIR) globally (AAPC +0.16%), with incident cases rising to 916,180, accounting for 20.43% of the global total. In contrast, Europe saw a slight decline in ASIR, while the global ASIR remained stable. China also recorded the largest increase in age-standardized prevalence rate (ASPR), whereas Europe’s ASPR declined. Despite rising incidence, China achieved the sharpest reduction in age-standardized mortality rate (ASMR; AAPC −0.45%), while Southeast Asia’s ASMR increased (AAPC +0.76%), and Europe maintained the highest ASMR globally. Frontier analysis highlighted China’s rapid efficiency improvements in mortality reduction relative to its SDI, outperforming several high-income European countries. Projections to 2050 suggest China’s ASIR and ASPR will continue to rise, whereas Europe’s are forecast to decline. Southeast Asia faces persistently increasing mortality, and global aggregates mask significant regional heterogeneity. Conclusion: AF/AFL burdens are increasingly driven by population aging and metabolic risks, with heterogeneous mortality trends reflecting regional disparities in healthcare access and prevention. China’ s success in reducing mortality despite rising incidence highlights the impact of improved anticoagulation and stroke prevention, yet unchecked prevalence growth signals future complications. Southeast Asia’ s rising mortality underscores urgent needs for equitable resource allocation, while Europe’s stagnant burden reflects challenges in aging populations. Globally, prioritising primordial prevention—such as metabolic risk control—alongside targeted screening and gender-specific interventions, is critical to mitigating AF/AFL-related morbidity and mortality. Future efforts should integrate digital health technologies and address structural barriers to optimize care efficiency worldwide. Research in Context: Evidence before this study: Prior to undertaking this analysis, we systematically reviewed the existing epidemiological literature on atrial fibrillation and atrial flutter (AF/AFL), with a particular emphasis on global and regional comparative studies. Our searches covered PubMed, Embase, Web of Science, the Cochrane Library, and the Global Burden of Disease (GBD) repository from January 1990 to December 2023, without language restrictions. Key terms included “atrial fibrillation,” “atrial flutter,” “global burden,” “epidemiology,” “trend,” and “GBD.” We included studies providing representative estimates of AF/AFL burden and excluded small-sample or non-age-standardized reports. Previous analyses indicated a rising global AF/AFL burden, largely due to population aging and improved detection. However, comprehensive assessments capturing temporal dynamics, risk drivers, and forecasting across major world regions—especially benchmarking China, Southeast Asia, and Europe against global patterns—remained limited. Most studies focused on isolated regions or short spans, lacking integrative multidimensional approaches such as age-period-cohort modeling, decomposition, or Bayesian forecasting. Added value of this study: This study provides a comprehensive and comparative assessment of the atrial fibrillation and atrial flutter (AF/AFL) burden across China, Southeast Asia, Europe, and globally from 1990 to 2021, utilizing the latest GBD 2021 data and advanced statistical methodologies, including Joinpoint regression, age-period-cohort modeling, Bayesian forecasting, decomposition analysis, and data envelopment frontier analysis. Our analysis reveals significant regional disparities against a backdrop of global stability: while the global age-standardized incidence rate (ASIR) remained stable (52·51 in 1990 vs. 52·12 in 2021), China experienced the most rapid increase worldwide (ASIR rising from 42·63 to 44·92), with a substantial number of new cases (916,180), accounting for 20·43% of the global total (4,484,926 cases). In contrast, Europe recorded a slight decline in ASIR. China also demonstrated the most pronounced increase in prevalence globally, while Europe’s age-standardized prevalence rate (ASPR) declined and the global rate remained largely unchanged. Notably, China achieved a significant reduction in mortality (age-standardized mortality rate [ASMR] declining from 4·93 to 4·33) despite rising incidence, sharply contrasting with Southeast Asia, where ASMR increased from 2·94 to 4·06 (estimated annual percentage change +1·07%)—trends potentially associated with structural challenges in Southeast Asia—while Europe maintained the highest ASMR globally (5·10 in 2021) despite interventions. We further identified key drivers:...

Atrial fibrillation (AF) is a common arrhythmia associated with increased risks of stroke and heart failure. Early differentiation between paroxysmal and p

Sepsis-associated acute kidney injury (SA-AKI) is a highly heterogeneous syndrome with variable clinical trajectories and outcomes. Conventional staging systems, such as KDIGO, fail to capture this heterogeneity, limiting risk stratification and personalized management. We aimed to identify reproducible SA-AKI subphenotypes using unsupervised machine learning on routinely collected clinical data and to characterize their clinical profiles and prognostic implications. We conducted a retrospective cohort study of 9,029 adult patients with SA-AKI from the MIMIC-IV v3.1 database. Within the 24-hour period before and after the diagnosis of SA-AKI, 19 core clinical variables—including vital signs and laboratory values—were extracted. A multi-algorithm consensus clustering framework integrating K-means, hierarchical clustering, and K-medoids was applied to identify subphenotypes. Cluster stability was assessed using consensus strength, entropy, and silhouette analysis, with visualization via t-SNE. Key discriminative features were identified using XGBoost with SHapley Additive exPlanations (SHAP). Primary outcome was in-hospital mortality; secondary outcome was 30-day survival. Four robust SA-AKI subphenotypes were identified: Subphenotype I (Hypoinflammatory): preserved oxygenation (SpO₂≈100%), low inflammation (WBC 8.9 × 10⁹/L), hospital mortality 16.4%; Subphenotype II (Stable): highest urine output (470 mL/6 h), lowest mortality (14.3%); Subphenotype III (Hyperdynamic): elevated heart/respiratory rates, impaired oxygenation (SpO₂≈96%), mortality 21.6%; Subphenotype IV (Critical): severe renal dysfunction (creatinine 2.2 mg/dL, urine output 253.5 mL/6 h), coagulopathy, metabolic acidosis, and highest mortality (34.2%).Kaplan-Meier analysis confirmed significant differences in 30-day survival across subphenotypes (log-rank P < 0.0001), with Subphenotype IV showing the poorest prognosis (median survival: ~18 days). Unsupervised consensus clustering reveals four clinically meaningful SA-AKI subphenotypes with markedly different outcomes. The “Critical” subphenotype is identifiable by routine parameters and warrants early aggressive intervention. This framework supports precision phenotyping for risk stratification and future targeted trials in SA-AKI.