Objective: To address systemic challenges in the blood system, such as supply-demand imbalance, inefficient allocation, and inappropriate clinical use, while bridging gaps in current theories regarding the integration of social mobilization, institutional practice, and policy coordination. It sought to construct a system dynamics model spanning from macro to micro levels to analyze the blood management system holistically. Methods: Key variables were identified by a systematic literature search in both Chinese and English databases. An improved Delphi method was then employed to conduct expert consultations across different fields, leading to the selection and determination of core variable sets for each sub-model. Furthermore, by defining their logical relationships, a system dynamics model was constructed to systematically analyze the operation mechanism of the blood management system. Results: Four core sub-models were developed: 1) A macro "Dynamic Balance" model quantifying regional supply-demand equilibrium and inventory control; 2) a mobilization "Three-Layer Funnel" model analyzing how socio-cultural factors, service channels, and policy incentives influence donation behavior; 3) an institutional "Dual-Cycle Regulation" model revealing hospital blood usage is driven by both disease burden (demand cycle) and management practices (regulation cycle); and 4) an individual "Three-Layer Filter" model standardizing clinical transfusion decisions based on necessity, risk-benefit, and context. These were integrated into a "Multi-Layer Linkage and Feedback" model, elucidating bidirectional interactions among five levels: policy environment, regional supply, blood station mobilization, hospital application, and clinical decision-making. Conclusion: This study constructed a system dynamics model for blood management. By defining key variables and their logical relationships, it systematically analyzes the system′s operational mechanism. The integrated framework connects multiple levels—regional supply, voluntary donation, hospital blood use, and clinical decision-making—revealing their intrinsic linkages. Future efforts should employ systems thinking to synergistically enhance supply-side mobilization, demand-side management, systemic regulation, and decision standardization to build a safe, efficient, and sustainable blood security system.

Lung transplantation is a definitive treatment for end-stage lung disease and can significantly improve patient prognosis. However, postoperative complications such as infection, rejection, ischemia-reperfusion injury and chronic lung allograft dysfunction intertwine to form a complex pathological network, posing persistent challenges to long-term patient survival. In 2025, research teams worldwide have made systematic progress in the field of basic lung transplantation research. By integrating cutting-edge technologies including single-cell multi-omics, spatial transcriptomics and novel animal models, significant breakthroughs have been achieved in the evolutionary dynamics of drug-resistant infections, molecular mechanisms of immune regulation, programmed cell death, optimization of donor lung protection strategies and early warning of chronic lung allograft dysfunction. This article systematically reviews the representative advances in basic lung transplantation research worldwide in 2025, and deeply analyzes the implications of mechanistic breakthroughs for optimizing diagnosis and treatment strategies, aiming to anchor the direction for innovative breakthroughs and clinical translation in basic lung transplantation research.

Exercise-induced metabolic remodeling is a fundamental adaptive process whereby the body reorganizes systemic and cellular metabolism to meet the dynamic energy demands posed by physical activity. Emerging evidence reveals that such remodeling not only enhances energy homeostasis but also profoundly influences immune function through complex molecular interactions involving glucose, lipid, and protein metabolism. This review presents an in-depth synthesis of recent advances, elucidating how exercise modulates immune regulation via metabolic reprogramming, highlighting key molecular mechanisms, immune-metabolic signaling axes, and the authors’ academic perspective on the integrated “exercise-metabolism-immunity” network. In the domain of glucose metabolism, regular exercise improves insulin sensitivity and reduces hyperglycemia, thereby attenuating glucose toxicity-induced immune dysfunction. It suppresses the formation of advanced glycation end-products (AGEs) and interrupts the AGEs-RAGE-inflammation positive feedback loop in innate and adaptive immune cells. Importantly, exercise-induced lactate, traditionally viewed as a metabolic byproduct, is now recognized as an active immunomodulatory molecule. At high concentrations, lactate can suppress immune function through pH-mediated effects and GPR81 receptor activation. At physiological levels, it supports regulatory T cell survival, promotes macrophage M2 polarization, and modulates gene expression via histone lactylation. Additionally, key metabolic regulators such as AMPK and mTOR coordinate immune cell energy balance and phenotype; exercise activates the AMPK-mTOR axis to favor anti-inflammatory immune cell profiles. Simultaneously, hypoxia-inducible factor-1α (HIF-1α) is transiently activated during exercise, driving glycolytic reprogramming in T cells and macrophages, and shaping the immune landscape. In lipid metabolism, exercise alleviates adipose tissue inflammation by reducing fat mass and reshaping the immune microenvironment. It promotes the polarization of adipose tissue macrophages from a pro-inflammatory M1 phenotype to an anti-inflammatory M2 phenotype. Moreover, exercise alters the secretion profile of adipokines—raising adiponectin levels while reducing leptin and resistin—thereby influencing systemic immune balance. At the circulatory level, exercise improves lipid profiles by lowering pro-inflammatory free fatty acids (particularly saturated fatty acids) and triglycerides, while enhancing high-density lipoprotein (HDL) function, which has immunoregulatory properties such as endotoxin neutralization and macrophage cholesterol efflux. Regarding protein metabolism, exercise triggers the expression of heat shock proteins (HSPs) that act as intracellular chaperones and extracellular immune signals. Exercise also promotes the secretion of myokines (e.g., IL-6, IL-15, irisin, FGF21) from skeletal muscle, which modulate immune responses, facilitate T cell and macrophage function, and support immunological memory. Furthermore, exercise reshapes amino acid metabolism, particularly of glutamine, arginine, and branched-chain amino acids (BCAAs), thereby influencing immune cell proliferation, biosynthesis, and signaling. Leucine-mTORC1 signaling plays a key role in T cell fate, while arginine metabolism governs macrophage polarization and T cell activation. In summary, this review underscores the complex, bidirectional relationship between exercise and immune function, orchestrated through metabolic remodeling. Future research should focus on causative links among specific metabolites, signaling pathways, and immune phenotypes, as well as explore the epigenetic consequences of exercise-induced metabolic shifts. This integrated perspective advances understanding of exercise as a non-pharmacological intervention for immune regulation and offers theoretical foundations for individualized exercise prescriptions in health and disease contexts.

Objective: To assess the association between the metabolic score for insulin resistance index (METS-IR) and overactive bladder (OAB) in the US population，so as to explore the potential of METS-IR as a predictive tool for OAB risk and to provide insights for early screening and intervention strategies. Methods: Based on the data from the National Health and Nutrition Examination Survey (NHANES) 2005-2018，a cross-sectional design was employed，and multivariate logistic regression models were used to analyze the association between METS-IR and OAB. METS-IR was analyzed both as a continuous variable and categorized into quartiles. To further validate the association between METS-IR and OAB across diverse populations，subgroup analyses were conducted in participants stratified by clinical characteristics. Smooth curve fitting was employed to test the linearity of the METS-IR-OAB relationship. Results: Elevated METS-IR was associated with an increased risk of OAB (P<0.001)，and this positive correlation remained stable when METS-IR was categorized into quartiles (P<0.001). Subgroup analyses revealed that the association between METS-IR and OAB was more pronounced in females，participants younger than 55 years，and non-diabetic individuals (P<0.05). Furthermore，smooth curve fitting confirmed a linear positive correlation between METS-IR and OAB，with this linear relationship observed in both diabetic and non-diabetic groups. Conclusion: This study，based on the NHANES 2005-2018 database，found a linear positive correlation between METS-IR and OAB.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Objective: To explore the relationship between nuclear factor-kappa B subunit 1 (NFKB1) and LIM-homeobox gene 2 (LHX2) polymorphisms and esophageal cancer susceptibility, so as to provide the reference for the prevention and treatment of esophageal cancer. Methods: A total of 100 patients with primary esophageal cancer diagnosed at the Affiliated Tumor Hospital of Xinjiang Medical University from 2019 to 2023 were selected as the case group, and 100 healthy individuals undergoing physical examination during the same period of time were selected as the control group. Demographic information, disease history and lifestyle data were collected through questionnaire surveys. The single nucleotide polymorphisms at the rs28362491 and rs4648068 loci of NFKB1 gene as well as rs10760310 and rs10121751 loci of LHX2 gene were detected using multiplex high-temperature ligase detection reaction technology. The relationship between these loci and esophageal cancer susceptibility were analyzed using a multivariable conditional logistic regression, linkage disequilibrium and haplotype analysis. The impact of the interaction between the above-mentioned loci and environmental factors on esophageal cancer susceptibility using the generalized multifactor dimensionality reduction (GMDR) method. Results: The case group comprised 73 males and 27 females, with a mean age of (64.02±8.90) years. The control group included 73 males and 27 females, with a mean age of (64.54±9.43) years. The genotype distributions of rs28362491, rs4648068, rs10760310 and rs10121751, loci in both groups conformed to Hardy-Weinberg equilibrium (all P>0.05). Multivariable conditional logistic regression analysis showed that rs10760310 and rs10121751 loci of LHX2 gene were associated with the esophageal cancer susceptibility (both P<0.05). The overdominant model of rs10760310 loci of LHX2 gene had the lowest Akaike information criterion value (OR=0.22, 95%CI: 0.10-0.47). GAA haplotypes at rs4648068, rs10760310 and rs10121751 loci were associated with a lower risk of esophageal cancer susceptibility (OR=0.26, 95%CI: 0.13-0.50). GMDR analysis revealed a statistically significant interaction between rs10760310 loci and smoking on esophageal cancer susceptibility (P<0.05, cross-validation consistency coefficient: 10/10). Conclusion The rs10760310 and rs10121751 loci polymorphisms of LHX2 gene may be associated with esophageal cancer susceptibility, and there is an interaction between rs10760310 loci and smoking on the esophageal cancer susceptibility.

Objective:This study aimed to retrospectively analyze the incidence and influencing factors of tricuspid regurgitation (TR) in the short term after pacemaker lead implantation at the Second Affiliated Hospital of Zhejiang University School of Medicine, so as to provide evidence for understanding pacemaker lead-related TR.Methods:Consecutive patients who underwent single- or dual-chamber permanent pacemaker implantation between June 2019 and December 2023 in the Department of Cardiology were enrolled. General clinical data and relevant parameters were collected. Changes in TR severity before and shortly after the procedure were assessed using echocardiography. TR progression was defined as an increase by one grade or more, and TR improvement as a decrease by one grade or more. Logistic regression analysis was employed to identify factors associated with TR progression.Results:A total of 219 patients were included (128 males, 91 females), with a mean age of 69.7 ± 11.2 years. The median follow-up time was 99 (26, 199) days. TR remained unchanged in 114 patients (52.1%), improved in 46 (21.0%)—including 36 (16.4%) with one-grade reduction, 9 (4.1%) with two-grade reduction, and 1 (0.5%) with three-grade reduction—and progressed in 59 patients (26.9%). Among those with progression, 51 (23.3%) had mild-to-moderate TR worsening by one grade, and 8 (3.7%) had moderate or worse TR worsening by at least two grades. Notably, one case involved lead perforation of the leaflet and two cases had lead impingement. Compared with the non-progression group ( n = 114), pacemaker indication (AV block vs. sick sinus syndrome), baseline left atrial diameter, pulmonary artery systolic pressure (PASP), and the severity of mitral regurgitation (MR) and TR were significantly associated with TR progression or improvement (all P < 0.05). Ordinal logistic regression analysis identified preoperative TR severity [ OR=10.57 (3.77–29.68), P < 0.001] and pacemaker indication [ OR=0.452 (0.222–0.918), P = 0.028] as independent predictors of postoperative TR progression. Patients with AV block were more likely to receive left bundle branch pacing ( P < 0.001), which may contribute to their lower risk of TR. Conclusions:Short-term progression of TR after pacemaker implantation is relatively common, although severe TR remains rare. Preoperative TR severity and pacemaker indication are independent predictors of short-term TR progression. The use of physiological pacing modalities may help reduce the incidence of TR following pacemaker lead implantation.

AIM To study the chemical constituents from Citri reticulatae Pericarpium Viride and their anti-triple negative breast cancer activities in vitro.METHODS The ethanolic extract of Citri reticulatae Pericarpium Viride was isolated and purified by silica gel,polyamide,MCI,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The anti-triple negative breast cancer activities were screened by SRB assay,and their effects on the proliferation of triple negative breast cancer cell lines HCC1806,HCC1937 and MDA-MB-231 in vitro were evaluated.RESULTS Twenty compounds were isolated and identified as nobiletin(1),tangeritin(2),5,4'-dihydroxy-7,8-dimethoxy flavonoid(3),naringenin(4),artemetin(5),5-demethynobiletin(6),3,5,6,7,8,3',4'-pentamethoxy flavonoid(7),5,4'-dihydroxy-3,6,7,8,3'-pentamethoxyflavone(8),xanthomicrol(9),p-hydroxycinnamic acid(10),5,4'-dihydroxy-6,7,8,3'-tetramethoxyflavone(11),pectolinarigenin(12),4'-dihydroxy-5,6,7-tetramethoxyflavone(13),hispidulin(14),4',5,6,7-tetramethoxy-flavone(15),1-methyl-4-(prop-1-en-2-yl)cyclohexane-1,2-diol(16),umbelliferone(17),5-hydroxymethyl furfural(18),hydroquinone(19),1H-indole-3-carbaldehyde(20).Compound 8 showed a significant inhibitory effect with the IC50 value of(5.36±0.24)μmol/L on HCC1806 cells.CONCLUSION Compound 20 is isolated from genus Citrus for the first time,8,12-13,16-17 are isolated from this plant for the first time.Compound 8 show inhibitory effects on the proliferation of HCC1806,HCC1937 and MDA-MB-231 cells in vitro and have the strongest activities.Compounds 3-4,11-12,15,17 and 19 show strong inhibitory effect on HCC1806 cells.Compounds 15,19 also inhibit the proliferation of HCC1937 cells in vitro.

In this work,near infrared carbon quantum dots(NIR-CDs)were synthesized by hydrothermal method using biomass material Clausena lansium leaves.The synthesized NIR-CDs emitted maximum fluorescence signal at 677 nm,which was independent of excitation wavelength.The characterization results showed that there were abundant groups on the surface of NIR-CDs.Pd2+could form non-fluorescent compounds with the surface groups of NIR-CDs,resulting in fluorescence quenching(Fluorescence signal was denoted as F0).Because chlorpromazine hydrochloride(CPZ)parent nucleus contained unoxidized S atom,CPZ could form stable colored complex with Pd2+under acidic conditions.In the presence of CPZ,Pd2+dissociated from the surface of NIR-CDs and bonded with CPZ,so that the fluorescence signal could be restored(Fluorescence signal was denoted as F).An"on-off-on"fluorescence sensor was thus constructed.The fluorescence signal recovery value of NIR-CDs(△F=F-F0)showed a good linear relationship with the concentration of CPZ in the range of 5.68-28.43 μg/mL,and the detection limit(3σ)was 0.078 μg/mL.The sensor was applied to determination of CPZ in pharmaceutical preparations,and the recoveries were 94％-106％.The developed fluorescence sensor was expected to be used in quality control of actual pharmaceutical preparations.

OBJECTIVE To explore the association between the use of oral progesterone drugs in early pregnancy and gestational diabetes mellitus （GDM）. METHODS Through real-world retrospective cohort research method， pregnant women who underwent the oral glucose tolerance test （OGTT） at the Affiliated Maternal and Child Health Hospital of Nantong University between January 2022 and January 2023 were enrolled. Based on whether oral progesterone drugs were used in early pregnancy， they were divided into treatment group and control group； propensity score matching （PSM） with a 1∶1 ratio was employed to control for confounding factors； Logistic regression and linear regression were employed to analyze the association between drug factors （whether use of oral progesterone drug， duration of medication， dosage， and drug type） and outcome indicators （occurrence of GDM， fasting blood glucose levels， and OGTT 1 and 2 h blood glucose levels in late pregnancy）. RESULTS A total of 709 pregnant women were enrolled in the two groups before PSM； after PSM， 256 cases were included in both the treatment group and the control group. The results of association analysis indicated that there was no significant association between the use of oral progesterone drugs and GDM （P＞0.05）； but a significant correlation was found with OGTT 1 h blood glucose levels [β＝0.965， 95%CI （0.007，1.922）， P＜0.05]， specifically with Dydrogesterone tablets [β＝0.977， 95%CI （0.009， 1.944）， P＜0.05] and Progesterone soft capsules [β ＝1.089， 95%CI （0.077， 2.102）， P＜0.05]. There was no significant correlation between other drug factors and outcome indicators （P＞0.05）. CONCLUSIONS The use of oral progestogen drugs in early pregnancy is not significantly associated with GDM. The blood glucose levels in late pregnancy， especially OGTT 1 h blood glucose levels， have a certain correlation with Progesterone soft capsules and Dydrogesterone tablets.