Yiyin Zhang

Background: Breast cancer (BC) and atrial fibrillation (AF) represent increasing global health burdens with shared risk factors. However, their coincidence burden and global distribution among older women (≥55 years) remain unclear. Methods: This study integrated data from the Global Burden of Disease 2021 database spanning 204 countries and territories, covering incidence rates of BC and AF and exposure rates of 58 risk factors. Using a 4‐quartile classification algorithm, we divided the globe into 3 regions (consistent, BC‐dominant, and AF‐dominant area). Risk factors were screened by using machine learning models (random forest, spatial statistics, and SHAP interpretability framework). Population‐attributable fraction and a composite risk index model were generated to evaluate disease burdens and spatial risk localization of BC and AF. Results: The consistent area (80 countries, 39.60%) exhibited overlapping BC‐AF incidence, while BC‐dominant (65 countries, 32.18%) and AF‐dominant (57 countries, 28.22%) regions highlighted geographic disparities. After screening of machine learning models, 2 shared factors (smoking and alcohol use) and 2 BC‐specific factors (high body mass index and low physical activity) were included in the calculation of population‐attributable fraction, potentially reducing global BC and AF incidence by 29.05% and 11.75% after shifting these factors to theoretical minimum exposure levels. For most factors, high‐risk zones clustered in North and South America, Europe, and Oceania mainly correlate with dietary and lifestyle patterns. Conclusions: The spatial coincidence of BC and AF present a significant global health challenge. Addressing both shared and region‐specific risk factors can substantially reduce the dual burden of these diseases.

AIM: This study evaluated the effect of the presence of air bubbles in a drainage tube on its pressure difference and analyzed the relationship between air bubble volume, tube diameter, drainage fluid viscosity, and pressure difference. Accordingly, it provides a theoretical basis for optimizing drainage treatment and preventing obstruction in clinical practice.METHODS: A custom-designed experimental device was used to measure the pressure difference in medical-grade silicone drainage tubes. Tubes with various diameters (3 and 6 mm), air bubble volumes (0, 0.1, 0.2, and 0.3 mL), and drainage fluids (low and high viscosities) were used. The pressure difference between the two ends of each drainage tube was measured using a pressure sensor and calculated. A rotational viscometer was used to measure the viscosity of each drainage fluid. Differences in the pressure difference under different conditions of air bubbles, air bubble volumes, tube diameters, and drainage fluid viscosities were compared.RESULTS: The presence of air bubbles in each drainage tube significantly increased the pressure difference, with the pressure difference being higher compared to that under the bubble-free condition (0.591 ± 0.069 vs. 0.830 ± 0.039 kPa, p < 0.01). In addition, the pressure difference progressively increased with increasing air bubble volume, with the maximum increase occurring at a bubble volume of 0.3 mL (0.951 ± 0.039 kPa). The pressure difference was negatively correlated with the tube diameter, with higher pressure difference observed at smaller diameters, and the differences between the values of the different diameter groups were statistically significant (p < 0.01). The pressure difference was positively correlated with the viscosity of the drainage fluid, with a higher pressure difference observed at a higher viscosity. The enhancing effect of air bubbles on the pressure difference was more pronounced in more viscous fluids (p < 0.0001).CONCLUSIONS: This study showed that the presence of air bubbles in a drainage tube significantly increases the outflow pressure difference, and this effect is enhanced by increasing the bubble volume, decreasing the tube diameter, and increasing the drainage fluid viscosity. These findings reveal that the hydrodynamic factors associated with air bubbles can theoretically contribute to a poor outflow. Therefore, they provide a preliminary in vitro basis for exploring the rational selection of drainage tube diameter, early detection of air bubble-related obstructions, and development of targeted interventions in future clinical practice.

Background: Estradiol, the key endogenous estrogen, reduces the risk of urinary obstruction by smooth muscle relaxation but also increases susceptibility to breast cancer (BC). However, whether estradiol serves as a mechanistic mediator linking urinary tract obstruction and BC remains unclear. This study aimed to determine if there is an association between urinary tract obstruction and the risk of BC and to assess the potential mediating role of systemic estradiol. Methods: A case‐control study and survival analysis of Cox regression were conducted using clinical data from the United Kingdom Biobank (UKB) (502,129 participants). To explore genetic causality, we performed a two‐sample Mendelian randomization (MR) study leveraging extensive genomic data. For obstructive uropathy, we relied on female‐only summary statistics sourced from the UKB (520 cases, 193,654 controls), while BC data, categorized by estrogen receptor status, HER2 status, and triple‐negative subtypes, were sourced from the open genome‐wide association studies database. We identified single‐nucleotide polymorphisms with strong links to obstructive uropathy as instrumental variables. Inverse variance‐weighted analysis, backed by robustness checks such as Cochran's Q test and MR‐Egger regression, were used to ensure reliable results. Results: The UKB research revealed a marked correlation between urinary obstruction and the risk of BC ( χ ² = 576.25, p < 0.001), with particularly robust findings for obstruction caused by kidney stones ( χ ² = 271.42, p < 0.001) and notable significance for urinary calculi overall ( χ ² = 9.97, p = 0.041). Survival analysis showed that calculus‐related urinary obstruction was an independent protective factor against incident BC (hazard ratio = 0.61, 95% confidence interval: 0.38–0.98, p = 0.041) after adjusting for confounders. The mean estradiol level was significantly lower in women with urinary obstruction than in controls (245.05 [IQR: 200.80–404.60] pmol/L vs. 313.55 [IQR: 216.10–535.50] pmol/L). The MR study found no evidence of a genetic causal association between obstructive uropathy and overall BC (inverse variance‐weighted β = −0.60, p = 0.923). A nominally significant association was observed with ER‐positive BC in the training set ( β = −7.62, p = 0.038), but failed to replicate in the validation set ( p > 0.05). Given the significant heterogeneity ( Q = 58.01, p = 1.44 × 10 ⁻⁵ ) and low exposure heritability (heritabilty explained by single‐nudleotide polymorphisms = 0.0282, standard error = 0.0015), this finding likely represents a false positive rather than a true causal effect. No pleiotropy or heterogeneity was detected in other analyses (all p > 0.05). Conclusions: These observational data suggest that urinary obstruction protects against BC and that estradiol may play a mediating role. However, this association does not appear to be caused by a relationship at the genetic level, highlighting the need to explore alternative biological pathways.

Radiation enteritis (RE) is a severe, dose-limiting complication of cancer radiotherapy that affects the therapeutic outcomes of patients and their quality of life. Current risk assessments primarily rely on physical dosimetry. However, this approach inherently ignores the substantial individual variability in radiation susceptibility, creating an urgent clinical need for personalized predictive tools. Emerging evidence suggests that the gut microbiota plays a central role in RE pathogenesis. Ionizing radiation can cause rapid and profound changes in intestinal ecological structure by reducing the number of beneficial microbes while increasing that of harmful pathogens; these factors interact to exacerbate damage to the mucosal barrier and the ongoing inflammatory response. This review synthesizes the multifaceted role the gut microbiome plays in RE, uniquely emphasizing its clinical translational value. Baseline microbial signatures and dynamic multi-omics data, particularly specific taxa and metabolites of the gut microbiota, emerged as powerful predictive biomarkers. These biological signals could inform risk stratification; however, large-scale clinical validation is required. Moreover, integrating microbiome data into machine learning algorithms represents an exploratory approach for toxicity prediction. Crucially, the evaluation of microbiota-targeted therapies reveals an expanding landscape of preclinical and early-phase clinical research. Future interventions may expand beyond conventional probiotics and fecal microbiota transplantation to include experimental therapies such as rationally designed consortia and engineered biotherapeutics. Finally, a strategic roadmap is proposed, utilizing large-scale longitudinal cohorts, high-resolution spatial transcriptomics, and explainable artificial intelligence. These advances may support the transition toward proactive microbiome-guided management strategies.

The microbiota is present in many parts of the human body and plays essential roles. The most typical case is the occurrence and development of cancer. Pancreatic cancer (PC), one of the most aggressive and lethal types of cancer, has recently attracted the attention of researchers. Recent research has revealed that the microbiota regulates PC carcinogenesis via an altered immune response. Specifically, the microbiota, in several sites, including the oral cavity, gastrointestinal tract, and pancreatic tissue, along with the numerous small molecules and metabolites it produces, influences cancer progression and treatment by activating oncogenic signaling, enhancing oncogenic metabolic pathways, altering cancer cell proliferation, and triggering chronic inflammation that suppresses tumor immunity. Diagnostics and treatments based on or in combination with the microbiota offer novel insights to improve efficiency compared with existing therapies.