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 investigate the expression of CSF-1 and CSF-1R in the peripheral blood of children with immune thrombocytopenia (ITP) and its clinical significance. METHODS: Forty-four children with ITP treated in our hospital from February 2023 to January 2024 were selected as the observation group, and 40 healthy children were selected as the control group during the same period, and relevant clinical data were collected. Peripheral blood mononuclear cells (PBMC) of children with ITP and healthy children were separated, and the plasma levels of M1 macrophage-associated cytokines (TNF-α, IL-6), M2 macrophage-associated cytokines (IL-10, TGF-β), and CSF-1 were detected by ELISA in the children of both groups. The mRNA levels of M1 macrophage surface markers (CD86, iNOS), M2 macrophage surface markers (CD206, Arg-1) and CSF-1R were detected by RT-PCR in PBMC of children in both groups. Western blot was used to detect the expression of CSF-1R protein in PBMC of the two groups of children. The correlation between platelet count and CSF-1R mRNA expression in PBMC, TNF-α, IL-6, IL-10, TGF-β and CSF-1 in plasma was analyzed. RESULTS: Compared with the control group, the levels of IL-10, TGF-β, CSF-1 and platelet count in plasma of children with ITP were significantly decreased (P < 0.01), and the levels of TNF-α and IL-6 were significantly increased (P < 0.01); the mRNA levels of the M1 macrophage surface markers (CD86, iNOS) in PBMC of children with ITP were significantly increased (P < 0.05), mRNA levels of M2 macrophage surface marker CD206 in PBMC of children with ITP were decreased compared with controls but the difference was not statistically significant ( P >0.05), mRNA levels of Arg-1 were decreased, the difference was statistically significant (P < 0.05). The mRNA and protein levels of CSF-1R in PBMC of ITP children were higher than that in controls. CSF-1R expression in PBMC of ITP was positively correlated with platelet count, IL-10, CSF-1 were positively correlated (r =0.822,0.481,0.405). CONCLUSION CSF-1 is significantly reduced in the plasma of ITP, and CSF-1R mRNA and protein expression is significantly elevated in PBMC of ITP, which are involved in the regulation of macrophage M1/M2 imbalance, and could serve as a potential therapeutic target for ITP.
Humans ; Purpura, Thrombocytopenic, Idiopathic/blood* ; Macrophage Colony-Stimulating Factor/metabolism* ; Leukocytes, Mononuclear/metabolism* ; Child ; Interleukin-10/blood* ; Macrophages/metabolism* ; Tumor Necrosis Factor-alpha/blood* ; Interleukin-6/blood* ; Male ; Female ; Transforming Growth Factor beta/blood* ; Receptor, Macrophage Colony-Stimulating Factor/metabolism* ; Clinical Relevance

OBJECTIVE: To investigate the effect of zedoarondiol on neovascularization of atherosclerotic (AS) plaque by exosomes experiment. METHODS: ApoE^-/- mice were fed with high-fat diet to establish AS model and treated with high- and low-dose (10, 5 mg/kg daily) of zedoarondiol, respectively. After 14 weeks, the expressions of anti-angiogenic protein thrombospondin 1 (THBS-1) and its receptor CD36 in plaques, as well as platelet activation rate and exosome-derived miR-let-7a were detected. Then, zedoarondiol was used to intervene in platelets in vitro, and miR-let-7a was detected in platelet-derived exosomes (Pexo). Finally, human umbilical vein endothelial cells (HUVECs) were transfected with miR-let-7a mimics and treated with Pexo to observe the effect of miR-let-7a in Pexo on tube formation. RESULTS: Animal experiments showed that after treating with zedoarondiol, the neovascularization density in plaques of AS mice was significantly reduced, THBS-1 and CD36 increased, the platelet activation rate was markedly reduced, and the miR-let-7a level in Pexo was reduced (P<0.01). In vitro experiments, the platelet activation rate and miR-let-7a levels in Pexo were significantly reduced after zedoarondiol's intervention. Cell experiments showed that after Pexo's intervention, the tube length increased, and the transfection of miR-let-7a minics further increased the tube length of cells, while reducing the expressions of THBS-1 and CD36. CONCLUSION Zedoarondiol has the effect of inhibiting neovascularization within plaque in AS mice, and its mechanism may be potentially related to inhibiting platelet activation and reducing the Pexo-derived miRNA-let-7a level.
Animals ; MicroRNAs/genetics* ; Exosomes/drug effects* ; Plaque, Atherosclerotic/genetics* ; Neovascularization, Pathologic/genetics* ; Human Umbilical Vein Endothelial Cells/metabolism* ; Humans ; Blood Platelets/drug effects* ; Apolipoproteins E/deficiency* ; Thrombospondin 1/metabolism* ; CD36 Antigens/metabolism* ; Platelet Activation/drug effects* ; Male ; Mice ; Mice, Inbred C57BL

[This corrects the article DOI: 10.1016/j.apsb.2022.05.019.].

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

Objective:To establish and validate a gallstones classification method based on deep learning.Methods:A total of 618 gallstones samples were collected from East Hospital Affiliated to Tongji University, and 1 023 high-definition cross-sectional gallstones profile images were captured to construct a cross-sectional gallstones profile image dataset. Based on the traditional eight-category gallstones classification method, a lightweight network model, MobileNet V3, was trained using deep learning and transfer learning methods. The classification performance of MobileNet was evaluated using a confusion matrix with metrics such as accuracy rate, precision rate, F1 score, and recall rate. The MobileNet V3 was improved and further validated using accuracy and loss values.Results:The accuracy rate (94.17%), precision rate (94.03%), F1 score (92.96%) and recall rate (92.99%) of the improved MobileNet V3 model were better than other networks. The improved MobileNet V3 model achieved the highest accuracy rate (94.17%) in gallstones profile classification and was validated by the test set. The confusion matrix showed a weighted average of accuracy rate (92.0%), precision rate (92.6%), and F1 score (92.2%) for each category of gallstones.Conclusions:Based on deep learning, a high-accuracy gallstones classification method is proposed, which provides a new idea for the intelligent identification of gallstones.

Objective To analyse the acupoint selection rules of acupuncture in the treatment of non-small cell lung cancer,and to provide reference for clinical application.Methods The clinical research,practitioner's experience and academic thought of acupuncture treatment for non-small cell lung cancer were retrieved to obtain the acupuncture prescriptions of modern practitioners for the treatment of non-small cell lung cancer.Based on the statistical methods of acupoint frequency,prescription rules,acupoint clustering and core combination,the core theoretical system and acupoint selection rules of acupuncture treatment of non-small cell lung cancer by modern practitioner were analyzed.Results According to the inclusion and exclusion criteria,94 acupuncture prescriptions were finally included.There were eight acupoints used more than 20 times,which were Zusanli(ST36),Neiguan(PC6),Feishu(BL13),Sanyinjiao(SP6),Qihai(RN6),Guanyuan(RN4),Hegu(LI4)and Zhongwan(RN12).The top three high-frequency acupoint combinations were Zusanli-Neiguan,Zusanli-Sanyinjiao and Qihai-Zusanli;correlation analysis showed that the correlation strength of Zusanli-Neiguan was the highest,followed by Zusanli-Sanyinjiao and Zusanli-Hegu.The cluster analysis showed that the acupoints with frequency＞10 times could be divided into three categories.Category 1 includes:Zusanli,Neiguan,Sanyinjiao,Hegu;category 2 includes Guanyuan,Qihai,Zhongwan,Xuehai(SP10),Taichong(LR3);category 3 consists of two parts,one is Danzhong(RN17),Tiantu(RN22),Fenglong(ST40),Taiyuan(LU9);the second is Feishu(BL13),Lieque(LU7),Chize(LU5),Zhongfu(LU1),Xinshu(BL15),Gaohuang(BL43),Fengmen(BL12).Conclusion The core acupoints for acupuncture treatment of non-small cell lung cancer include four categories:① invigorating the spleen and benefiting qi:Zusanli,Sanyinjiao,Zhongwan and Fenglong;②replenishing and supplementing original qi:Guanyuan,Qihai and Gaohuang;③regulating qi and broadening the chest:Danzhong,Neiguan,Tiantu and Fengmen;④ diffusing the lung and ventilating qi:Feishu,Hegu,Chize and Lieque.The three treatment methods of replenishing qi,regulating qi and venting pathogen are the basis of acupuncture treatment of advanced non-small cell lung cancer.The core idea of acupuncture treatment of non-small cell lung cancer focuses on supplementation,supplemented by dredging,and to dredge and supplement simultaneously.

Officers and soldiers exposed to high temperature and high-humidity environments are highly susceptible to exertional heat illness and even heatstroke.Reports indicated that after conventional treatment,the heat endurance damage in officers/soldiers with exertional heat illness can persist for months or even years.Therefore,the Expert Group of Heatstroke Prevention and Treatment of Heatstroke of Chinese PLA has specially formulated a technical proposal for the reconstruction of heat endurance in officers/soldiers suffering from exertional heatstroke,aiming to provide a safeguard for reconstruction of heat endurance in affected personnel.This article mainly elaborates on the basic concepts,technical requirements,initiation timing,implementation assessment,and follow-up of the heat endurance reconstruction for officers/soldiers with exertional heatstroke.

Human respiratory syncytial virus (HRSV) can infect individuals of all ages, with children under five years old, the elderly, and immunocompromised persons as the main high-risk groups. Although older children and adults often exhibit mild or no symptoms, they may still be potential carriers of the virus. Therefore, employing efficient, accurate, and rapid detection methods to timely identify infection sources and quickly halt transmission is an important means to curb the potential spread of the epidemic. However, the clinical manifestations of HRSV infection are difficult to distinguish from acute respiratory infections caused by other respiratory viruses, and the identification relies on the results of pathogen testing. This article summarizes four commonly used detection methods for HRSV based on detection principles: antigen detection, nucleic acid testing, antibody detection, and virus isolation. The advantages, disadvantages, principles, and applicable scenarios of these four methods are summarized and compared. Furthermore, the research progress and prospects of HRSV detection methods are reviewed.

Objective To explore the distribution of traditional Chinese medicine(TCM)syndrome elements in patients with multi-drug resistant bacteria-infected pneumonia.Methods Clinical data of 126 patients with multi-drug resistant bacteria-infected pneumonia admitted to the intensive care unit of Lung Disease Centre of Qingdao Hospital of Traditional Chinese Medicine from May 2020 to July 2022 were retrospectively collected.The clinical data included the patients'gender,age,underlying diseases,history of bad additions of smoking and alcohol,multi-drug resistant bacteria,and the information of four diagnostic methods of TCM,etc.The disease-nature syndrome elements in patients with drug-resistance to various strains of drug-resistant bacteria were extracted,and then deficiency-excess syndrome differentiation was carried out.Results(1)A total of 201 strains of multi-drug resistant bacteria were detected in 126 patients with multi-drug resistant bacterial pneumonia.The main pathogenic species were Gram-negative bacteria,and the proportion accounted for 95.52%(192/201),which was significantly higher than that of Gram-positive bacteria[4.48%(9/201)],with a statistically significant difference(χ2 = 166.612,P＜0.001).Klebsiella pneumoniae accounted for the highest percentage of 23.38%in the gram-negative bacterium.(2)A total of 12 syndrome elements were extracted from the 126 patients.The excess syndrome elements were predominated by phlegm and heat,and the deficiency syndrome elements were predominated by yin deficiency.There was no statistically significant difference in the distribution of yin deficiency,blood deficiency,heat,phlegm,fluid-retention and damp syndrome elements among patients with different strains of drug-resistant bacterial infection(P＞0.05).(3)Of the 126 patients,62 cases(49.21%)had simple excess syndrome,one case(0.79%)had simple deficiency syndrome,and 63 cases(50.00%)had concurrent deficiency-excess syndrome.Among the 126 patients,there were 19 cases of single syndrome element,41 cases of concurrent two-syndrome element,49 cases of concurrent three-syndrome element,16 cases of concurrent four-syndrome element,and one case of concurrent five-syndrome element.And the combined syndrome element of phlegm-heat-yin deficiency occurred most frequently for 26 times.Conclusion Gram-negative bacteria are the primary infectious pathogens for the patients with multi-drug resistant bacterial infections,and the TCM syndrome elements of the patients are characterized by the concurrence of deficiency and excess and simple excess syndrome,mainly manifesting as phlegm,heat,and yin deficiency.