ObjectivePhotoacoustic pump-probe imaging can effectively eliminate the interference of blood background signal in traditional photoacoustic imaging, and realize the imaging of weak phosphorescence molecules and their triplet lifetimes in deep tissues. However, background differential noise in photoacoustic pump-probe imaging often leads to large fitting results of phosphorescent molecule concentration and triplet lifetime. Therefore, this paper proposes a novel triplet lifetime fitting method for photoacoustic pump-probe imaging. By extracting the phase of the triplet differential signal and the background noise, the fitting bias caused by the background noise can be effectively corrected. MethodsThe advantages and feasibility of the proposed algorithm are verified by numerical simulation, phantom and in vivo experiments, respectively. ResultsIn the numerical simulation, under the condition of noise intensity being 10% of the signal amplitude, the new method can optimize the fitting deviation from 48.5% to about 5%, and has a higher exclusion coefficient (0.88>0.79), which greatly improves the fitting accuracy. The high specificity imaging ability of photoacoustic pump imaging for phosphorescent molecules has been demonstrated by phantom experiments. In vivo experiments have verified the feasibility of the new fitting method proposed in this paper for fitting phosphoometric lifetime to monitor oxygen partial pressure content during photodynamic therapy of tumors in nude mice. ConclusionThis work will play an important role in promoting the application of photoacoustic pump-probe imaging in biomedicine.

Cholelithiasis is a common biliary system disease with a high incidence worldwide. Abnormal lipid metabolism has been shown to play a key role in the mechanism of gallstones. Therefore, recent research literature on the genes, proteins, and molecular substances involved in lipid metabolism during the pathogenesis of gallstones has been conducted. This study aimed to determine the role of lipid metabolism in the pathogenesis of gallstones and provide insights for future studies using previous research in genomics, metabolomics, transcriptomics, and other fields.

Cholelithiasis is a common biliary system disease with a high incidence worldwide. Abnormal lipid metabolism has been shown to play a key role in the mechanism of gallstones. Therefore, recent research literature on the genes, proteins, and molecular substances involved in lipid metabolism during the pathogenesis of gallstones has been conducted. This study aimed to determine the role of lipid metabolism in the pathogenesis of gallstones and provide insights for future studies using previous research in genomics, metabolomics, transcriptomics, and other fields.

Cholelithiasis is a common biliary system disease with a high incidence worldwide. Abnormal lipid metabolism has been shown to play a key role in the mechanism of gallstones. Therefore, recent research literature on the genes, proteins, and molecular substances involved in lipid metabolism during the pathogenesis of gallstones has been conducted. This study aimed to determine the role of lipid metabolism in the pathogenesis of gallstones and provide insights for future studies using previous research in genomics, metabolomics, transcriptomics, and other fields.

Cholelithiasis is a common biliary system disease with a high incidence worldwide. Abnormal lipid metabolism has been shown to play a key role in the mechanism of gallstones. Therefore, recent research literature on the genes, proteins, and molecular substances involved in lipid metabolism during the pathogenesis of gallstones has been conducted. This study aimed to determine the role of lipid metabolism in the pathogenesis of gallstones and provide insights for future studies using previous research in genomics, metabolomics, transcriptomics, and other fields.

Cholelithiasis is a common biliary system disease with a high incidence worldwide. Abnormal lipid metabolism has been shown to play a key role in the mechanism of gallstones. Therefore, recent research literature on the genes, proteins, and molecular substances involved in lipid metabolism during the pathogenesis of gallstones has been conducted. This study aimed to determine the role of lipid metabolism in the pathogenesis of gallstones and provide insights for future studies using previous research in genomics, metabolomics, transcriptomics, and other fields.

Objective To propose a whole-life cycle management model for valvular heart disease (VHD), systematically elucidate its underlying logic and implementation pathways, and concurrently review and analyze its preliminary application outcomes. Methods Since 2020, West China Hospital of Sichuan University has established a management system encompassing "assessment-decision-intervention-follow-up", including: (1) a risk-stratified, tiered management pathway; (2) six core functions ("promotion, screening, prevention, diagnosis, treatment, and rehabilitation") coordinated by disease-specific managers; (3) an intelligent decision support information platform; and (4) a collaborative network of multidisciplinary teams and regional academic alliances. To evaluate the effectiveness of this management model, we retrospectively included three cohorts: (1) the population screened by echocardiography from 2020 to 2024, analyzing the detection rate of aortic valve disease and risk stratification; (2) patients enrolled in the whole-life cycle management from April 2021 to December 2024, assessing follow-up outcomes, hospital satisfaction, and changes in quality of life; (3) patients who underwent transcatheter aortic valve replacement (TAVR) from January 2022 to January 2024, evaluating the one-year all-cause mortality rate, perioperative complications, and improvements in New York Heart Association (NYHA) classification. Results Between 2020 and 2024, a total of 583 874 individuals underwent echocardiographic screening. A total of 48 089 patients with aortic valve disease were identified, including 3 401 (7.1%) high-risk patients, 18 657 (38.8%) moderate-risk patients, and 26 031 (54.1%) low-risk patients. Among them, 2 417 patients were enrolled in whole-life cycle management. Patient satisfaction scores showed a yearly increase, rising from 73.89 points before 2020 to 93.74 points in 2024. The 1-year mortality rate in the TAVR cohort decreased to 5.3%, significantly lower than the 8.2% observed under early standard management between 2014 and 2019 (P<0.01). Conclusion Through process optimization and resource integration, the VHD whole-life cycle management model has demonstrated significant effectiveness in standardizing diagnostic and follow-up procedures, enhancing patient satisfaction and quality of life, and reducing mortality. These outcomes highlight its practical value for broader implementation in China.

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.

ObjectiveTo investigate the effect of modified Baduanjin exercise, as an rehabilitation exercise, on cardiopulmonary function, motor function and activities of daily living in patients with stroke. MethodsFrom January to September, 2023, 42 stroke patients in the Nanjing Qixia District Hospital were randomly divided into control group (n = 21) and experimental group (n = 21). The control group received routine rehabilitation, and the experimental group received modified Baduanjin exercise in addition, for four weeks. They were assessed with peak oxygen uptake (VO_2peak), anaerobic threshold (AT), peak oxygen pulse (VO_2peak/HR), forced vital capacity (FVC), forced expiratory volume in the first second (FEV₁), peak expiratory flow (PEF), Fugl-Meyer Assessment-upper extremities (FMA-UE), Berg Balance Scale (BBS) and modified Barthel Index (MBI) before and after intervention. ResultsVO_2peak, AT, and the scores of FMA-UE, BBS and MBI improved in the control group after intervention (|t| > 2.256, |Z| > 2.936, P < 0.05); while VO_2peak, AT, VO_2peak/HR, FVC, FEV₁, PEF, and the scores of FMA-UE, BBS and MBI improved in the experimental group (|t| > 4.390, |Z| > 3.451, P < 0.001); and all the indexes were better in the experimental group than in the control group (|t| > 4.136，|Z| > 2.751，P < 0.01), except the scores of BBS and MBI. ConclusionModified Baduanjin exercise can improve the cardiopulmonary function and upper limb motor function for stroke patients.

Objective To investigate the predictive value of new simplified insulin resistance(IR)assessment indexes in identifying subclinical left ventricular systolic function impairment in patients with type 2 diabetes mellitus(T2DM).Methods A total of 150 T2DM patients with preserved left ventricular ejection fraction(LVEF≥50%)who were admitted to Department of Endocrinology of the First Affiliated Hospital of Air Force Medical University from June 2021 to December 2021 were retrospectively analyzed.All patients underwent two-dimensional speckle tracking echocardiography to measure left ventricular global longitudinal strain(GLS).According to GLS value,the subjects were divided into the normal group(GLS≥18%group,n=80)and the impaired group(GLS<18%group,n=70).Some new simplified IR assessment indicators were calculated and compared between the two groups,including body mass index(BMI),TG/HDL-C ratio,triglyceride-glucose(TyG)index,TyG-BMI index,TyG-WHR and metabolic score for IR(METS-IR).Correlation between the GLS and the new simplified IR assessment indexes was analyzed.The receiver operating characteristic(ROC)curve was used to analyze the diagnostic efficacy of different simplified IR assessment indexes,with the area under the curve(AUC)calculated.Furthermore,according to whether the subjects were complicated with hypertension,binary logistics regression analysis was performed to explore the independent correlation between the simplified IR assessment index and GLS<18%.Results Total 150 were included with aged(54.5±13.7)years with 96(64.0%)men and 54(36.0%)women.Compared with the GLS≥18%group,the TG/HDL-C ratio,TyG index,TyG-BMI,and METS-IR of subjects in the GLS<18%group were significantly increased(P<0.05).Pearson correlation analysis showed that TG/HDL-C ratio,TyG index,TyG-BMI,TyG-WHR,and METS-IR were negatively correlated with GLS(P<0.05).ROC analysis showed that TyG index had a certain predictive value for the evaluation of GLS<18%(AUC=0.678,95%CI 0.591-0.765,P<0.001).Stratification based on hypertension and further adjusting for confounding factors,TyG index remains significantly associated with GLS<18%(OR=3.249,95%CI 1.045-10.103,P=0.042).Conclusions The novel simplified insulin resistance evaluation indexes are closely associated with left ventricular subclinical systolic dysfunction in T2DM patients with preserved ejection fraction.TyG index is an effective index to identify left ventricular subclinical dysfunction in these populations.