ObjectivePost-ischemic acute inflammation and the subsequent persistent dysregulation of the immune microenvironment represent major pathological drivers that aggravate neuronal injury and severely restrict functional recovery following ischemic stroke. Although current reperfusion therapies partially restore blood flow, they fail to effectively modulate the secondary inflammatory cascade and oxidative stress, which remain critical barriers to neurological restoration. To address this challenge, this study aimed to engineer and systematically evaluate a biomimetic nanosystem composed of transforming growth factor-β1 (TGF-β1)-loaded platelet membrane-camouflaged lipid nanoparticles (PLP). This nanosystem was designed to achieve dual lesion-targeted delivery and immune microenvironment remodeling. By verifying its spatiotemporal accumulation, anti-inflammatory activity, and neuroprotective efficacy, we sought to establish an integrated therapeutic strategy that simultaneously enables lesion targeting, immune regulation, and functional recovery after ischemic injury. MethodsThe physicochemical properties of PLP, including hydrodynamic particle size, zeta potential, structural stability, and morphology, were characterized using dynamic light scattering, zeta potential analysis, and transmission electron microscopy. The preservation of platelet membrane-derived adhesion and immunoregulatory proteins was confirmed by SDS-PAGE through comparative analysis of protein band profiles between PLP and native platelet membranes. The in vitro biological activities of PLP were evaluated using two complementary cellular models. LPS-induced M1-polarized RAW264.7 macrophages were employed to assess inflammatory modulation, while oxygen glucose deprivation/reperfusion (OGD/R)-induced BV2 microglial cells and SH-SY5Y neuronal cells were utilized to investigate neuroinflammatory regulation and neuronal protection. For in vivo validation, a transient middle cerebral artery occlusion (tMCAO) mouse model was established to mimic ischemia-reperfusion injury. The spatiotemporal biodistribution and lesion-targeting capability of the PLP were monitored through live fluorescence imaging. Therapeutic efficacy was comprehensively evaluated by triphenyltetrazolium chloride (TTC) staining, glial fibrillary acidic protein (GFAP) immunofluorescence analysis, body weight monitoring, and neurological severity score (NSS) assessment. ResultsPLP nanoparticles displayed a uniform spherical morphology, nanoscale particle size distribution, and stable negative surface charge, indicating favorable colloidal stability and circulation potential. SDS-PAGE results confirmed the effective retention of key platelet membrane proteins associated with endothelial adhesion, immune evasion, and inflammatory regulation, demonstrating the successful biomimetic construction. Optimal therapeutic concentrations were determined in OGD/R-induced BV2 cells, where PLP exhibited excellent cytocompatibility and anti-inflammatory activity.In vitro experiments demonstrated that PLP significantly inhibited the polarization of RAW264.7 macrophages toward the pro-inflammatory M1 phenotype and markedly reduced neuronal apoptosis under ischemia-reperfusion conditions. In vivo fluorescence imaging revealed that PLP rapidly accumulated in the ischemic brain hemisphere and maintained prolonged retention for up to 7 d, suggesting enhanced lesion-specific targeting and sustained drug release. Compared with control group, PLP treatment significantly reduced cerebral infarct volume, attenuated reactive astrogliosis, improved weight recovery, and accelerated neurological functional restoration, as reflected by significantly improved NSS scores. ConclusionThis study establishes a multifunctional biomimetic nanoplatform that integrates platelet membrane-mediated active targeting with the anti-inflammatory, antioxidative, and neuroprotective properties of TGF-β1. The PLP system enables rapid lesion homing and long-term retention while synergistically regulating the post-stroke inflammatory microenvironment by suppressing pro-inflammatory immune activation, reducing neuronal apoptosis, and limiting excessive astrocyte reactivity. Importantly, this study proposes a conceptually therapeutic paradigm that combines targeted delivery with immune microenvironment remodeling to achieve comprehensive neurovascular protection. These findings provide strong experimental evidence supporting the translational potential of biomimetic nanotherapeutics as next-generation precision interventions for ischemic stroke.

Objective To explore risk factors of sodium-dependent glucose transporters 2 （SGLT2） inhibitor-associated euglycemic diabetic ketoacidosis （euDKA） and to construct a risk prediction model. Methods A retrospective analysis was performed on the clinical data of type 2 diabetes patients treated with SGLT2 inhibitors in Dongnan Hospital of Xiamen University from January 2020 to December 2023, including age, gender and course of diabetes. The risk factors of SGLT2 inhibitor-associated euDKA were analyzed by univariate analysis and multivariate Logistic regression, and a prediction model was established. According to the receiver's operating characteristic （ROC） curve, the area under the curve （AUC） and the optimal critical value of the prediction model were determined. The prediction model was subjected to both internal and external validation. Results A total of 119 patients with type 2 diabetes treated with SGLT2 inhibitors were included in this study. Among them, there were 98 cases without euDKA （non-euDKA group）and 21 cases with euDKA （euDKA group）. Multivariate Logistic regression analysis showed the DKA history (OR=114.153), appetite or diet decreased three days before admission (OR=21.774), elevated neutrophil count (OR=2.056) and pre-hospital adjustment of hypoglycemic agents (OR=45.745) were independent factors to increase risks of euDKA associated with SGLT2 inhibitors （P<0.05）. Surgical history before admission was an independent factor to reduce this risk （OR=0.007, P<0.05）. By establishing the calculation formula of the prediction model = neutrophil count+6.571 （DKA history）−6.874 （surgical history before admission）+4.273 （appetite or diet decreased three days before admission）+5.302 （pre-hospital adjustment of hypoglycemic drugs）, the ROC curve was drawn. The AUC of the ROC of the prediction model was 0.982 （95%CI: 0.961-1.000, P<0.001）, with accuracy of 94.96%, sensitivity of 0.905, specificity of 0.959 and a critical value of 7.405. The AUC of ROC curve after the model’s ten-fold cross validation was 0.930. And the accuracy of the external validation of the prediction model was 85.29%. Conclusion The DKA history, appetite or diet decreased three days before admission, elevated neutrophil count and pre-hospital adjustment of hypoglycemic agents increased the risk of SGLT2 inhibitor-associated euDKA, while the surgical history before admission reduced this risk. The risk prediction model constructed on this basis could better predict the risk of SGLT2 inhibitor-associated euDKA.

ObjectiveTo investigate the contamination status of ochratoxin A (OTA) in commercially available food products in Shanghai, and to assess OTA exposure levels and the associated non-carcinogenic and carcinogenic risks among pregnant women by integrating dietary consumption data of this population. MethodsThe levels of OTA contamination in 1 520 food samples collected in Shanghai from 2022 to 2023 were determined using liquid chromatography-tandem mass spectrometry. An exposure assessment model was developed based on the dietary consumption levels of pregnant women from the 2016‒2017 Shanghai Pregnant Women Dietary Monitoring Survey to calculate the estimated daily intake (EDI) of OTA, the margin of exposure for non-carcinogenic toxicity (MOE₁), and the margin of exposure for carcinogenic toxicity (MOE₂). An MOE₁ greater than 200 and an MOE₂ greater than 10 000 indicate that the non-carcinogenic toxicity and carcinogenic toxicity resulting from exposure are negligible, respectively. For samples with OTA contamination levels below the limit of detection (LOD), which accounted for more than 80% of the samples, the OTA levels were assigned values of 0 and LOD, respectively, for subsequent calculations. ResultsThe detection rates of OTA in cereals, nuts, dried fruits, and alcohol samples collected in 2022 were 2.03%, 0, 0, and 0, respectively. The OTA detection rates in cereals, nuts, dried fruits, beans, and alcohol samples collected in 2023 were 2.50%, 0.39%, 2.47%, 1.67%, and 13.33%, respectively. For pregnant women in Shanghai in 2022, simulation results indicated that when assigning a value of 0 and the LOD, theP₅₀ values of EDI for dietary OTA exposure were 0.05 and 0.72 ng·(kg·d)^-1, respectively, and the P₉₅ values of EDI for dietary OTA exposure were 0.25 and 2.40 ng·(kg·d)^-1, respectively. For pregnant women in Shanghai in 2023, the P₅₀ values of EDI for dietary OTA exposure were 0.04 and 1.00 ng·(kg·d)^-1, respectively, and the P₉₅ values of EDI for dietary OTA exposure were 0.23 and 2.67 ng·(kg·d)^-1, respectively, both substantially below the tolerable daily intake (TDI) for OTA [17 ng·(kg·d)^-1]. The EDI for dietary OTA exposure in 100.0% of Shanghai pregnant women was lower than the TDI, indicating an overall low level of dietary OTA exposure among this population. For 100.0% of pregnant women, the MOE₁ for dietary OTA exposure exceeded 200. When assigned a value of 0, the MOE₂ for 100.0% of pregnant women in both 2022 and 2023 exceeded10 000. When assigned the LOD value, 72.3% and 81.8% of pregnant women in 2022 and 2023, respectively, had an MOE₂ exceeding 10 000. ConclusionFrom 2022 to 2023, samples of cereals, nuts, dried fruits, beans, and alcohol sold in Shanghai exhibited varying degrees of OTA contamination. The overall EDI of OTA exposure among pregnant women in Shanghai remained at a low level. The non-carcinogenic and carcinogenic risks associated with OTA exposure were generally low and at controllable levels.

ObjectiveTo analyze the epidemiological characteristics of 21 respiratory pathogens in influenza-like illness (ILI) cases in Jing’an District, Shanghai in 2024, and to provide a scientific basis for the prevention and control of respiratory infectious diseases. MethodsData of1 907 ILI cases at four sentinel hospitals in Jing’an District were collected from January to December 2024. Nasopharyngeal swab samples were collected and tested for 21 respiratory pathogens using polymerase chain reaction (PCR) methods. Chi-square test and Cochran-Armitage trend test were used for data analyses. ResultsAmong the 1 907 ILI cases, 1 340 were tested positive (70.27%), including 1 160 (60.83%) virus-positive cases, 424 (22.23%) bacteria-positive cases , and 86 (4.51%) positive cases of other pathogens (fungi, mycoplasma, and chlamydia). The top five viruses by detection rate were: influenza virus (14.84%), SARS-CoV-2 (14.47%), rhinovirus (12.69%), adenovirus (7.08%), and parainfluenza virus (6.71%). The top two bacteria by detection rate were Streptococcus pneumoniae (14.47%) and Haemophilus influenzae (10.33%). Among other pathogens (fungi, mycoplasma, and chlamydia), Mycoplasma pneumoniae showed the highest detection rate (4.30%). In terms of age distribution, statistically significant differences were observed in the detection rates of SARS-CoV-2, Legionella, and Klebsiella pneumoniae (P<0.05), with the highest rates found in individuals aged 65 years and above. Statistically significant differences were also found in the detection rates of rhinovirus, adenovirus, enterovirus, common coronavirus, respiratory syncytial virus, bocavirus, parainfluenza virus, human metapenu-movirus, Streptococcus pneumoniae, Haemophilus influenzae, and Mycoplasma pneumoniae among different age groups (P<0.05), all showing the highest detection rates in the 0‒<15 years age group. In terms of seasonal distribution, SARS-CoV-2, adenovirus, parainfluenza virus, enterovirus, Streptococcus pneumoniae, Haemophilus influenzae, and Mycoplasma pneumoniae showed epidemic peaks in summer; rhinovirus, common coronavirus, bocavirus, and Klebsiella pneumoniae had higher detection rates in autumn. Influenza virus exhibited a peak incidence during winter, while human metapenu-movirus peaked in winter and spring. Significant differences in co-infection detection rates were observed among age groups, with the rate in children aged 0‒<15 years (34.81%) being the highest. The co-infection detection rate was higher in males than in females (P=0.019). Both the single-pathogen detection rate and the co-infection detection rate (P<0.001) varied significantly across seasons: the single-pathogen detection rate was highest in winter (62.06%), while the co-infection detection rate peaked in summer (31.20%) and was lowest in winter (14.52%). ConclusionBased on detection rates, the main pathogens in the ILI population of Jing’an District, Shanghai, 2024 were influenza virus, SARS-CoV-2, rhinovirus, adenovirus, parainfluenza virus, common coronavirus, enterovirus, Human metapenu-movirus, Streptococcus pneumoniae, Haemophilus influenzae, and Mycoplasma pneumoniae. Pathogen detection rates varied by age and season. Coinfection rates were much higher in children than in adults, higher in males than in females, and peaked in summer while being lowest in winter.

Objective To investigate the temporal changes in pathological damage and macrophage polarization in liver and spleen tissues of mice infected with Angiostrongylus cantonensis, and to preliminarily unravel the peripheral immune responses during the early stage of A. cantonensis infection. Methods Forty female BALB/c mice at ages of 6 to 8 weeks were randomly divided into four groups, including the control group and 7-, 14-, and 21-day infection groups, with 10 mice in each group. Each mouse in the infection groups was inoculated with 30 third-stage (L3) larvae of A. cantonensis by oral gavage, and five mice were randomly selected from each infection group on days 7, 14, and 21 post-infection, while mice in the control group were given the same volume of physiological saline and five mice were randomly selected from the control group on the day of oral gavage. Mouse liver and spleen tissues were sampled. The histopathological changes of mouse liver and spleen tissues were observed using hematoxylin and eosin (HE) staining, and the percentage of positive staining area and the co-localization positive rates of the macrophage surface antigens F4/80, CD86, and CD206 were quantified in mouse liver and spleen tissues using immunohistochemical and immunofluorescence staining. In addition, five mice were collected from each infection group on days 7, 14, and 21 post-infection, and five mice were collected from the control group on the day of oral gavage. Mouse liver and spleen tissues were sampled for detection of macrophage markers CD86 and CD206 and macrophage phenotyping using flow cytometry, and the expression of M1 macrophage markers, including inducible nitric oxide synthase (Nos2), tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β) and M2 markers, including arginase 1 (Arg1), mannose receptor C-type 1 (Mrc1) and chitinase-like protein 3 (Chil3) was quantified in mouse liver and spleen tissues using real-time quantitative PCR (RT-qPCR) assay. Results Proliferative lesions of the hepatocyte were observed in mouse liver tissues and the follicular structures of the mouse spleen white pulp were disrupted 21 days post-infection with A. cantonensis. Immunohistochemical staining showed that there were significant differences in the percentages of F4/80, CD86 and CD206 positive staining areas in the liver and spleen tissues among the four groups of mice (F = 242.40, 197.14, 183.19, 157.65, 242.35 and 146.24; all P values < 0.001), and the percentages of positive staining in the liver and spleen tissues of mice in the 14-day infection group [(4.45 ± 0.51)%, (3.74 ± 0.67)%, (8.32 ± 0.72)%, (16.56 ± 1.14)%, (11.62 ± 0.52)%, and (8.29 ± 0.72)%, respectively] and the 21-day infection group [(3.70 ± 0.11)%, (3.22 ± 0.43)%, (11.53 ± 1.03)%, (12.59 ± 1.05)%, (9.02 ± 0.83)%, and (11.67 ± 1.10)%, respectively] were higher than in the control group [(0.35 ± 0.16)%, (0.40 ± 0.02)%, (0.93 ± 0.05)%, (2.78 ± 0.26)%, (2.33 ± 0.20)%, and (1.85 ± 0.20)%, respectively] (all P values < 0.05). Immunofluorescence staining showed significant differences in the positive rates of F4/80 co-localization with CD86 and CD206 in mouse liver and spleen tissues among the four groups (F = 24.42, 25.28, 54.51 and 130.55; all P values < 0.001). Flow cytometry detected significant differences in the proportions of CD86⁺ and CD206⁺ macrophages in mouse liver and spleen tissues among the four groups (F = 67.98, 18.41, 29.77, 172.80; all P values < 0.001), and the proportions of CD206⁺ macrophages in the liver and spleen of the 21-day infection group were significantly higher than those in the control group [(9.25 ± 2.55)% vs (3.83 ± 0.72)%, and (4.22 ± 0.56)% vs (0.47 ± 0.18)%, respectively] (both P values < 0.05). In addition, RT-qPCR assay quantified significant differences in the relative mRNA expression of M1 macrophage markers (IL-1β, TNF-α and Nos2) and M2 macrophage markers (Arg1, Chil3 and Mrc1) in mouse liver and spleen tissues among the four groups (F = 41.30, 31.82, 199.33, 19.96, 62.01, 119.76, 23.67, 95.90, 72.27, 82.59, 123.41 and 29.75; all P values < 0.05). Conclusions A. cantonensis infection may cause progressive pathological damage in mouse liver and spleen tissues, accompanied by dynamic temporal changes in macrophage polarization. M1 macrophage polarization predominates at the early stage of A. cantonensis infection and shifts towards M2 polarization at the later stages, suggesting that M2 polarization may participate in immune regulation at late stages of A. cantonensis infection by suppressing excessive inflammatory responses and promoting tissue repair.

BackgroundFear of progression is one of the typical psychological consequences in patients with chronic obstructive pulmonary disease （COPD）. The level of fear of progression is affected by the illness perception status， and the link between social support and fear of progression is acknowledged， whereas the mechanism underlying the three remains unclear due to the lack of empirical research evidence and needs to be further studied. ObjectiveTo explore the mediating role of social support in the relationship between illness perception and fear of progression in COPD patients， and to provide references for effectively alleviating fear in COPD patients. MethodsA total of 435 COPD patients admitted to the Department of Respiratory and Critical Care Medicine， the Affiliated Hospital of Southwest Medical University from March 9 to July 31， 2024 were selected as the study objects. The Chinese version of Fear of Progression Questionnaire-Short Form （FoP-Q-SF）， Chinese version of Brief Illness Perception Questionnaire （BIPQ） and Social Support Rate Scale （SSRS） were used for the evaluation. Pearson's coefficient was calculated to assess the correlation among above scales. Model 4 of the Process macro 3.4.1 for SPSS 25.0 was used to test the mediating effect of social support on the relationship between illness perception and fear of progression， with Bootstrapping used to evaluate the significance of mediating effect. ResultsA total of 412 patients （94.71%） completed this study.BIPQ score was positively correlated with FoP-Q-SF score （r=0.238， P<0.01）， and negatively correlated with SSRS score in COPD patients （r=-0.260， P<0.01）. FoP-Q-SF score was negatively correlated with SSRS score （r=-0.271， P<0.01）. Social support mediated the relationship between illness perception and fear of progression， with an indirect effect value of 0.025 （95% CI： 0.009~0.041）， accounting for 13.02% of the total effect. ConclusionIllness perception can affect the fear of progression in COPD patients both directly and indirectly through social support. ［Funded by Nursing Research Project of Sichuan Province （number， H22010）］

ObjectiveTo analyze the current status of per⁃ and polyfluoroalkyl substances (PFASs) contamination in animal⁃derived foods in Shanghai and to assess the risk of dietary exposure among local residents, thereby providing a scientific basis for future dietary safety and risk management. MethodsA total of 300 commonly consumed animal⁃derived food samples were collected in Shanghai in 2023 and tested for 17 types of PFASs. Based on local dietary consumption data, the weekly exposure intake (EWI) of four representative PFASs was calculated using the exposure assessment model recommended by Food and Agriculture Organization (FAO) and the World Health Organization (WHO). The calculated EWI was compared with the tolerable weekly intake (TWI) set by the European Food Safety Authority (EFSA) to assess the health risks associated with dietary intake of PFASs. ResultsThe predominant PFASs detected in aquatic products were PFUnDA (98.67%), PFTrDA (98.00%), and PFOS (95.33%), with PFUnDA having the highest median mass fraction (0.378 ng·g^-1). In meat samples, PFBA (54.17%), PFOA (20.83%), and PFOS (18.33%) were mainly detected, with PFBA showing the highest median mass fraction (0.027 ng·g^-1). In egg samples, the most frequently detected compounds were PFBA (90.00%), PFOA (63.33%), PFOS (50.00%), PFDA (50.00%), PFNA (50.00%), and PFHxDA (50.00%), with PFBA again having the highest median mass fraction (0.068 ng·g^-1). The median mass fractions of the four key PFASs (PFOA, PFOS, PFNA, and PFHxS) in aquatic products were significantly higher than those in meat products and eggs (all P<0.001), and there were statistically significant differences in the median mass fractions of the four PFASs among different types of aquatic products (all P<0.05). The EWI of the four PFASs was 2.970 ng·kg^-1 for the mean consumption group and 6.676 ng·kg^-1 for the high consumption group (P₉₅), with females having higher EWI values than males. ConclusionPFOS, PFOA, and PFBA are the major PFAS contaminants in animal⁃derived foods consumed by Shanghai residents, with aquatic products having the highest levels of contamination. The EWIs of four PFASs among Shanghai residents did not exceed EFSA’s recommended TWI at average consumption levels. However, the EWIs for high⁃consumption populations exceeded the EFSA⁃recommended TWI, posing potential health risks to these populations. Aquatic products contribute the most to dietary PFAS exposure. It is necessary to strengthen PFAS monitoring in aquatic products and conduct targeted risk assessments for high⁃consumption groups.

Objective: To evaluate the efficacy and safety of plasma exchange (PE) in thymoma-associated myasthenia gravis (MG), thereby to provide theoretical support for its application in the treatment of thymoma-associated MG. Methods: A total of 133 patients with thymoma-associated MG admitted from January 2018 to September 2024 were retrospectively analyzed. Patients were matched using propensity score to reduce selection bias, yielding 22 matched pairs for both PE group (n=22) and non-PE group (n=22). Patient characteristics including gender, age of disease onset, course of disease, history of thymoma resection, clinical absolute scores [clinical absolute scores (CAS) and clinical relative scores (CRS)], and synchronized immunotherapy regimen of the two groups were analyzed. The CAS scores before and after treatment were compared between the two groups, and the CRS was used to assess the treatment efficiency. Safety of the two treatment regimens were also compared. Continuous variables were compared using the t-test or ANOVA, while categorical data were compared by the chi-square test. Results: A total of 133 patients were included and divided into two groups according to whether they underwent plasma exchange treatment: the PE group (n=22) and the non-PE group (n=111). To exclude bias caused by large difference in the number of cases between the two groups, we performed propensity score matching. After matching, the number of cases in both groups was 22. There was no significant difference in baseline clinical characteristics between the two groups (P>0.05), including gender, age of onset, duration of disease course, history of thymectomy and baseline CAS score before treatment. Compared to the non-PE group, patients in the PE group showed more significant improvement in CAS score (5.09±1.95 vs 3.59±1.50, P<0.05) and a higher CRS score (75.00% vs 50.00%, P<0.001). Compared to the non-PE group, PE group had significantly longer ICU stay, longer hospital stay and higher hospitalization cost (P<0.05). There was no statistically significant difference in adverse events between the two groups during treatment (P>0.05). During long-term follow-up, both the PE and non-PE groups showed relatively low 1-, 3-, and 5-year recurrence rate, with no significant difference between the two groups (P>0.05). Conclusion: This study indicates that plasma exchange has clear value in the treatment of patients with thymoma-associated myasthenia gravis. It can not only significantly improve patients' muscle strength to alleviate motor dysfunction and enhance quality of life, but also does not significantly increase the incidence of adverse reactions. Therefore, it can be regarded as one of the preferred treatment options that achieve a "balance between efficacy and safety" for such patients, and provides an important basis for optimizing treatment strategies, improving prognosis, and promoting the application of subsequent treatment regimens.

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 create a prediction model for stroke risk among middle-aged and elderly populations, so as to provide a basis for early identification of high-risk population for stroke. Methods: From October to December 2023, residents aged ≥45 years in Chongchuan District, Nantong City, Jiangsu Province were selected using a multi-stage stratified random sampling method. The demographic information, life behavior, and chronic disease data were collected through a questionnaire survey. The standardized prevalence of stroke was calculated using data from the seventh National Population Census. The subjects were randomly divided into the training set and the internal validation set according to the ratio of 8∶2. The basic demographic information, life behavior, and chronic diseases of residents aged ≥45 years in Rugao City were collected from July to August 2023 as the external validation set. Predictive factors were selected using multivariable logistic regression model, and a nomogram for stroke among residents aged ≥45 years was established. The prediction effect was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC), calibration curve, and Hosmer-Lemeshow goodness of fit test. Results: A total of 6 290 residents aged ≥45 years were included, including 2 975 males (47.30%) and 3 315 females (52.70%). The average age was (61.90±10.20) years. The prevalence of stroke was 3.80%, and the standardized prevalence was 3.36%. The multivariable logistic regression showed that age, smoking, hypertension, and hyperlipidemia were predictors of stroke risk among residents aged ≥45 years, and the prediction model was ln[p/(1-p)]=-4.619+0.046×age+0.383×smoking+0.887×hypertension+0.678×hyperlipidemia. The AUC values of the training set, internal validation set, and external validation set were 0.748, 0.755, and 0.738, respectively. The consistency indexes were 0.748, 0.755, and 0.738, respectively. The Hosmer-Lemeshow goodness of fit test showed a good fitting effect (P>0.05). Conclusion The prediction model based on age, smoking, hypertension, and hyperlipidemia has good discrimination and calibration, and can be used to predict the risk of stroke among middle-aged and elderly populations aged ≥45 years.