Subtype-DCC: decoupled contrastive clustering method for cancer subtype identification based on multi-omics data.

Due to the high heterogeneity and complexity of cancers, patients with different cancer subtypes often have distinct groups of genomic and clinical characteristics. Therefore, the discovery and identification of cancer subtypes are crucial to cancer diagnosis, prognosis and treatment. Recent technological advances have accelerated the increasing availability of multi-omics data for cancer subtyping. To take advantage of the complementary information from multi-omics data, it is necessary to develop computational models that can represent and integrate different layers of data into a single framework. Here, we propose a decoupled contrastive clustering method (Subtype-DCC) based on multi-omics data integration for clustering to identify cancer subtypes. The idea of contrastive learning is introduced into deep clustering based on deep neural networks to learn clustering-friendly representations. Experimental results demonstrate the superior performance of the proposed Subtype-DCC model in identifying cancer subtypes over the currently available state-of-the-art clustering methods. The strength of Subtype-DCC is also supported by the survival and clinical analysis.

MDF-SA-DDI: predicting drug-drug interaction events based on multi-source drug fusion, multi-source feature fusion and transformer self-attention mechanism.

One of the main problems with the joint use of multiple drugs is that it may cause adverse drug interactions and side effects that damage the body. Therefore, it is important to predict potential drug interactions. However, most of the available prediction methods can only predict whether two drugs interact or not, whereas few methods can predict interaction events between two drugs. Accurately predicting interaction events of two drugs is more useful for researchers to study the mechanism of the interaction of two drugs. In the present study, we propose a novel method, MDF-SA-DDI, which predicts drug-drug interaction (DDI) events based on multi-source drug fusion, multi-source feature fusion and transformer self-attention mechanism. MDF-SA-DDI is mainly composed of two parts: multi-source drug fusion and multi-source feature fusion. First, we combine two drugs in four different ways and input the combined drug feature representation into four different drug fusion networks (Siamese network, convolutional neural network and two auto-encoders) to obtain the latent feature vectors of the drug pairs, in which the two auto-encoders have the same structure, and their main difference is the number of neurons in the input layer of the two auto-encoders. Then, we use transformer blocks that include self-attention mechanism to perform latent feature fusion. We conducted experiments on three different tasks with two datasets. On the small dataset, the area under the precision-recall-curve (AUPR) and F1 scores of our method on task 1 reached 0.9737 and 0.8878, respectively, which were better than the state-of-the-art method. On the large dataset, the AUPR and F1 scores of our method on task 1 reached 0.9773 and 0.9117, respectively. In task 2 and task 3 of two datasets, our method also achieved the same or better performance as the state-of-the-art method. More importantly, the case studies on five DDI events are conducted and achieved satisfactory performance. The source codes and data are available at https://github.com/ShenggengLin/MDF-SA-DDI.

High-precision optical modeling method for galvanometer-driven dual-camera systems.

To build a galvanometer-driven dual-camera sensing system, it is important to accurately correlate the wide-view image coordinates with the pan-tilt mirror angles for adjusting the incident light path of the zoom-in camera. Existing optical modeling methods assume sufficient target distance and simplify dual-camera optical centers as coincident. However, this simplification is not valid in many practical cases and might cause severe system malfunctions, such as complete loss tracking of important targets. To address this problem, we propose a novel approach, to the best of our knowledge, to facilitate high-precision optical modeling and calibration of galvanometer-driven dual-camera systems. The proposed method takes into consideration the dual-camera optical center misalignment issue and builds a model for accurate estimation and rectification of target localization errors under various optical configurations. Qualitative and quantitative experimental results demonstrate the superiority of our method, improving the performance of galvanometer-driven dual-camera systems for high-precision optical sensing applications.

Identification and Validation of Cytotoxicity-Related Features to Predict Prognostic and Immunotherapy Response in Patients with Clear Cell Renal Cell Carcinoma.

Background: Clear cell renal cell carcinoma (ccRCC) is a renal cortical malignancy with a complex pathogenesis. Identifying ideal biomarkers to establish more accurate promising prognostic models is crucial for the survival of kidney cancer patients. Methods: Seurat R package was used for single-cell RNA-sequencing (scRNA-seq) data filtering, dimensionality reduction, clustering, and differentially expressed genes analysis. Gene coexpression network analysis (WGCNA) was performed to identify the cytotoxicity-related module. The independent cytotoxicity-related risk model was established by the survival R package, and Kaplan-Meier (KM) survival analysis and timeROC with area under the curve (AUC) were employed to confirm the prognosis and effectiveness of the risk model. The risk and prognosis in patients suffering from ccRCC were predicted by establishing a nomogram. A comparison of the level of immune infiltration in different risk groups and subtypes using the CIBERSORT, MCP-counter, and TIMER methods, as well as assessment of drug sensitivity to conventional chemotherapeutic agents in risk groups using the pRRophetic package, was made. Results: Eleven ccRCC subpopulations were identified by single-cell sequencing data from the GSE224630 dataset. The identified cytotoxicity-related T-cell cluster and module genes defined three cytotoxicity-related molecular subtypes. Six key genes (SOWAHB, SLC16A12, IL20RB, SLC12A8, PLG, and HHLA2) affecting prognosis risk genes were selected for developing a risk model. A nomogram containing the RiskScore and stage revealed that the RiskScore contributed the most and exhibited excellent predicted performance for prognosis in the calibration plots and decision curve analysis (DCA). Notably, high-risk patients with ccRCC demonstrate a poorer prognosis with higher immune infiltration characteristics and TIDE scores, whereas low-risk patients are more likely to benefit from immunotherapy. Conclusions: A ccRCC survival prognostic model was produced based on the cytotoxicity-related signature, which had important clinical significance and may provide guidance for ccRCC treatment.

Tuning the Mechanical Properties of 3D-printed Objects by Mixing Chain Transfer Agents in Radical Promoted Cationic RAFT Polymerization.

The utilization of (cationic) reversible addition-fragmentation chain transfer (RAFT) polymerization in photoinduced three-dimensional (3D) printing has emerged as a robust technique for fabricating a variety of stimuli-responsive materials. However, methods for precisely adjusting the mechanical properties of these materials remain limited, thereby constraining their broader applicability. In this study, a facile way is introduced to modulate the mechanical properties of 3D printed objects by mixing two chain transfer agents (CTAs) within a radical-promoted cationic RAFT (RPC-RAFT) polymerization-based 3D printing process. Through systematic investigations employing tensile testing and dynamic mechanical analysis (DMA), the influence of CTA concentration and molar ratio between two CTAs on the mechanical behavior of the printed objects are explored. These findings demonstrate that higher concentrations of CTAs or a greater molar ratio of the more active CTA within the mixed CTAs result in decreased Young's modulus and glass transition temperatures of the printed objects. Moreover, the tensile failure strain increased with the increasing CTA content, i.e., the samples became more ductile. This methodology broadens the toolbox available for tailoring the mechanical properties of 3D printed materials.

Surface activation via selective dealloying of Cu-based metallic glasses for efficient catalytic behavior.

Surface activation is considered to regulate the electronic structures of materials for enhancing catalytic capability. Herein, we report a controllable strategy for constructing three-dimensional micro-nanoporous copper catalysts with high reactivity and activity for the degradation reaction of organic pollutants. Various micro-nanoporous structures and in situ formation processes by chemical selective dealloying of Cu-based metallic glasses are evaluated due to the surface modification. The porous catalysts exhibit superior catalytic performance, attributing to the catalytic mechanisms related to the superior surface activity of nanoscale copper composites and the strong oxidizing capability of activated radicals. These findings will provide a promising synthesis approach for three-dimensional micro-nanoporous catalysts for many chemical reactions.

Type III fetal redundancy of the foramen ovale flap mimics hemodynamic changes of mitral stenosis.

Type III redundancy of the foramen ovale flap (RFOF) mimics hemodynamic changes of mitral stenosis(MS), which has not been particularly highlighted in previous literature but carries a favorable prognosis.

Prenatal features and postnatal follow-up of congenital ventricular outpouching: A retrospective study of two centers in China.

OBJECTIVES: Congenital ventricular outpouching (CVO) is a rare cardiac malformation that can manifest as congenital ventricular aneurysm (CVA) and/or congenital ventricular diverticula (CVD). In this study, we describe the prenatal features and postnatal follow-up of 27 cases of CVO. METHODS: The clinical data of 27 patients with CVO who attended Sir Run Run Shaw Hospital Affiliated to the Medical College of Zhejiang University (Zhejiang Province, China) and Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University (Zhejiang Province, China) from April 2013 to October 2022 were retrospectively analyzed. The patients were also followed up by telephone. The prenatal characteristics and postnatal outcomes of the patients with CVO were evaluated. RESULTS: CVO was detected in 26 cases prenatally, 14 (51.85%) were diagnosed with CVA, nine (33.33%) were diagnosed with CVD, three (11.11%) were equivocal for CVA/CVD, and one (3.70%) was detected with CVA postnatally. Six patients underwent follow-up fetal echocardiography approximately 4 weeks after the initial echocardiography examination, and a significant difference in CVO size was observed between the two examinations (P = .02). Eight patients (29.63%) demonstrated cardiovascular dysfunction, and the median CVO size in fetuses with and without cardiovascular dysfunction was 205 (range: 169-396) mm2 and 124 (range: 92-154.5) mm2 , respectively (P = .01). Correlation was found between CVO size and fetal cardiac dysfunction (p = .000, r = .778). Eight patients (29.63%) had cardiac/extracardiac defects. Thirteen patients were live born, 12 were terminated pregnancies, and two were lost to follow-up. The postpartum size of the CVOs remained stable in six patients, decreased in two patients, dissolved in three patients, and were surgically removed in two patients. With the exception of one patient with CVA complicated with complex congenital cardiac malformation who underwent surgical treatment after birth and who had postoperative left ventricular dysfunction (Case 1), the prognosis of all of the patients was good. CONCLUSION: CVO is often associated with cardiac malformations. The size of prenatal CVOs can increase with gestational development, and cardiovascular dysfunction is significantly related to CVO size. The postpartum prognosis of patients with CVO is good. Echocardiography plays a key role in the diagnosis of congenital ventricular outpouching. Prenatal counseling should be cautious regarding the diagnosis and the prognosis although our cases had a favorable prognosis.

Evaluating fetal pulmonary vascular development in congenital heart disease: a comparative study using the McGoon index and multiple parameters of fetal echocardiography.

OBJECTIVES: The purpose of this study was to evaluate the value of MGI and multi-parameter in the assessment of different pulmonary circulation blood volumes in congenital heart disease. METHODS: This study included 350 fetuses categorized into two groups: Normal group consisted of 258 fetuses with no discernible abnormalities through echocardiography as control Group A; Abnormal group with abnormal echocardiogram, including Group B of 71 fetuses with decreased pulmonary blood flow or pulmonary atresia and Group C of 21 fetuses with reduced or detached aortic blood flow. RESULTS: The MGI and Z-scores were measured and compared among these groups. Significant variations were noted in the aortic outflow Z-scores (AO-Zs) (p<0.01), pulmonary artery (PA) (p<0.01), PA Z-scores (PA-Zs) (p<0.01), PA/AO (p<0.01), right PA (p<0.01), and MGI (p<0.01) among the three groups (all p<0.05). Among fetuses with decreased pulmonary blood flow or pulmonary atresia, PA, PA-Zs, and MGI in fetuses with reverse DA flow perfusion were lower than those in the DA forward perfusion group. CONCLUSIONS: Fetal echocardiography, incorporating the MGI and multi-parameter, not only allows for the evaluation of pulmonary blood flow and pulmonary vascular development of the fetus but also enables the observation of changes in pulmonary blood flow and MGI development across different gestational weeks.

Quantitative Analysis of Morphology and Function in the Fetal Heart with Severe Tricuspid Regurgitation by Speckle Tracking Imaging.

Morphology and function in a fetal heart with severe tricuspid regurgitation remains challenging. The aim of this study was to assess cardiac morphology and function in fetuses with severe tricuspid regurgitation by fetal heart quantification (HQ) and to assess the practical value of fetal HQ. Clinical information was analyzed for 63 pregnant women who underwent fetal cardiac ultrasonography. The women were divided into those who had a fetus with severe tricuspid regurgitation (n = 20) and those with a normal fetus (n = 40). The global sphericity index (GSI), fractional area change (FAC), and global longitudinal strain (GLS) of both ventricles and the sphericity index (SI) and fractional shortening (FS) of 24 segments were quantified by fetal HQ using speckle tracking imaging. Fetuses with severe tricuspid regurgitation had a significantly lower GSI (1.14 ± 0.10 vs. 1.26 ± 0.08, p < 0.001) and a higher GSI Z-score (-0.98 ± 1.01 vs. 0.25 ± 0.87, p < 0.001) as well as a significantly lower right ventricular FAC (36.50 ± 7.34% vs. 45.19 ± 3.39%, p < 0.001), FAC Z-score (-1.02 ± 1.41 vs. 0.49 ± 0.74, p < 0.001), and GLS (-21.01 ± 5.66% vs. 45.19 ± 3.49%, p < 0.001). The SI and SI Z-score were significantly lower in segments 1-18 of the right ventricle in fetuses with severe tricuspid regurgitation (p < 0.05); furthermore, FS of segments 1-12 and 19-24 and the FS Z-score of segments 18-24 were significantly lower in fetuses with severe tricuspid regurgitation (p < 0.05). Fetal HQ is useful for evaluation of cardiac morphology and function in fetuses with severe tricuspid regurgitation and can provide important reference information for both clinical diagnosis and treatment.

Study on the correlation between retrograde ductus arteriosus flow and right ventricular function evaluated by Z-score of tricuspid annular plane systolic excursion in fetuses with Ebstein anomaly.

PURPOSE: To analyze the influence of RV dysfunction evaluated by Free-angle M-mode (FAM) TAPSE Z-score on retrograde ductus arteriosus flow (RDAF) in fetuses with Ebstein anomaly (EA). METHODS: A retrospective cohort study of 30 EA and 60 normal fetuses were enrolled. The EA group was divided into two groups: with RDAF (EA-RDAF group) and without RDAF (EA-NRDAF group). FAM was used to measure TAPSE of EA and normal fetuses, and Z-scores were calculated. The differences of FAM-TAPSE Z-score, gestational week (GW), maternal age (MA), and mitral valve-tricuspid valve distance (MTD) between three groups were compared. The correlation and binary logistic regression between FAM-TAPSE Z-score, GW, MA, MTD, and RDAF were analyzed. RESULTS: FAM-TAPSE Z-score was significantly lower in EA-RDAF group compared to other groups (p < 0.05). FAM-TAPSE Z-score, GW, and MA were negatively correlated with RDAF (p < 0.05), but no correlation was found between TR, MDT, and RDAF (p > 0.05). Multivariate logistic regression showed that FAM-TAPSE Z-score was an independent influencing factor for RDAF (OR = 0.102, p < 0.05). CONCLUSION: RV dysfunction is an independent factor leading to RDAF in EA fetus, which provides a feasible theoretical basis for further study on improvement of RV function through intrauterine treatment to delay and prevent the RDAF, to avoid death cycle and improve live-birth rate.

Echocardiographic features and outcomes of fetuses with isolated restrictive foramen ovale or redundant foramen ovale flap using atrial septum excursion index.

PURPOSE: This study was designed to investigate the application value of the atrial septum excursion index (ASEI) in fetuses with isolated restrictive foramen ovale (RFO) or redundant foramen ovale flap (RFOF) and the outcomes of these fetuses. METHODS: This was a retrospective study. Healthy pregnant women who were examined by antenatal fetal echocardiography from January 1, 2019 to December 31, 2021, at Sir Run Run Shaw Hospital were enrolled. One hundred seventy-seven (177) fetuses were categorized into three groups by diagnosis: (1) RFOF (n = 33), (2) RFO (n = 21), and (3) normal (n = 123). Fetal echocardiographic features and postnatal outcomes were collected. RESULTS: The median ASEIs were 0.50 (range, 0.41-0.65) in the control group, 0.76 (range, 0.67-0.88) in the RFOF group and 0.31 (range, 0.14-0.35) in the RFO group, and the differences were significant (p < 0.001). The ratios of right atrium/left atrium, right ventricle/left ventricle, and pulmonary artery diameter to aorta diameter (PA/AO) and the pulmonary annulus Z-scores were greater in fetuses with RFOF and RFO than in the controls (p < 0.05). Twenty-seven of 33 fetuses (87.9%) with RFOF and 19 of 21 fetuses (90.5%) with RFO had good outcomes after birth. CONCLUSION: The ASEI may be a new tool for quantitatively assessing the mobility of foramen ovale flaps in fetuses with isolated RFOF or RFO.

Exploring microproteins from various model organisms using the mip-mining database.

Microproteins, prevalent across all kingdoms of life, play a crucial role in cell physiology and human health. Although global gene transcription is widely explored and abundantly available, our understanding of microprotein functions using transcriptome data is still limited. To mitigate this problem, we present a database, Mip-mining ( https://weilab.sjtu.edu.cn/mipmining/ ), underpinned by high-quality RNA-sequencing data exclusively aimed at analyzing microprotein functions. The Mip-mining hosts 336 sets of high-quality transcriptome data from 8626 samples and nine representative living organisms, including microorganisms, plants, animals, and humans, in our Mip-mining database. Our database specifically provides a focus on a range of diseases and environmental stress conditions, taking into account chemical, physical, biological, and diseases-related stresses. Comparatively, our platform enables customized analysis by inputting desired data sets with self-determined cutoff values. The practicality of Mip-mining is demonstrated by identifying essential microproteins in different species and revealing the importance of ATP15 in the acetic acid stress tolerance of budding yeast. We believe that Mip-mining will facilitate a greater understanding and application of microproteins in biotechnology. Moreover, it will be beneficial for designing therapeutic strategies under various biological conditions.

Oxidative stress and epigenetics in ocular vascular aging: an updated review.

Vascular aging is an inevitable process with advancing age, which plays a crucial role in the pathogenesis of cardiovascular and microvascular diseases. Diabetic retinopathy (DR) and age-related macular degeneration (AMD), characterized by microvascular dysfunction, are the common causes of irreversible blindness worldwide, however there is still a lack of effective therapeutic strategies for rescuing the visual function. In order to develop novel treatments, it is essential to illuminate the pathological mechanisms underlying the vascular aging during DR and AMD progression. In this review, we have summarized the recent discoveries of the effects of oxidative stress and epigenetics on microvascular degeneration, which could provide potential therapeutic targets for DR and AMD.

Microglial SIRT1 activation attenuates synapse loss in retinal inner plexiform layer via mTORC1 inhibition.

BACKGROUND: Optic nerve injury (ONI) is a key cause of irreversible blindness and triggers retinal ganglion cells (RGCs) change and synapse loss. Microglia is the resistant immune cell in brain and retina and has been demonstrated to be highly related with neuron and synapse injury. However, the function of Sirtuin 1 (SIRT1), a neuroprotective molecule, in mediating microglial activation, retinal synapse loss and subsequent retinal ganglion cells death in optic nerve injury model as well as the regulatory mechanism remain unclear. METHOD: To this end, optic nerve crush (ONC) model was conducted to mimic optic nerve injury. Resveratrol and EX527, highly specific activator and inhibitor of SIRT1, respectively, were used to explore the function of SIRT1 in vivo and vitro. Cx3Cr1-CreERT2/RaptorF/F mice were used to delete Raptor for inhibiting mammalian target of rapamycin complex 1 (mTORC1) activity in microglia. HEK293 and BV2 cells were transfected with plasmids to explore the regulatory mechanism of SIRT1. RESULTS: We discovered that microglial activation and synapse loss in retinal inner plexiform layer (IPL) occurred after optic nerve crush, with later-development retinal ganglion cells death. SIRT1 activation induced by resveratrol inhibited microglial activation and attenuated synapse loss and retinal ganglion cells injury. After injury, microglial phagocytosed synapse and SIRT1 inhibited this process to protect synapse and retinal ganglion cells. Moreover, SIRT1 exhibited neuron protective effects via activating tuberous sclerosis complex 2 (TSC2) through deacetylation, and enhancing the inhibition effect of tuberous sclerosis complex 2 on mammalian target of rapamycin complex 1 activity. CONCLUSION: Our research provides novel insights into microglial SIRT1 in optic nerve injury and suggests a potential strategy for neuroprotective treatment of optic nerve injury disease.

Fast Living 3D Printing via Free Radical Promoted Cationic RAFT Polymerization.

The application of reversible deactivation radical polymerization techniques in 3D printing is emerging as a powerful method to build "living" polymer networks, which can be easily postmodified with various functionalities. However, the building speed of these systems is still limited compared to commercial systems. Herein, a digital light processing (DLP)-based 3D printing system via photoinduced free radical-promoted cationic reversible addition-fragmentation chain transfer polymerization of vinyl ethers, which can build "living" objects by a commercial DLP 3D printer at a relatively fast building speed (12.99 cm h-1 ), is reported. The polymerization behavior and printing conditions are studied in detail. The livingness of the printed objects is demonstrated by spatially controlled postmodification with a fluorescent monomer.

NeuroPpred-Fuse: an interpretable stacking model for prediction of neuropeptides by fusing sequence information and feature selection methods.

Neuropeptides acting as signaling molecules in the nervous system of various animals play crucial roles in a wide range of physiological functions and hormone regulation behaviors. Neuropeptides offer many opportunities for the discovery of new drugs and targets for the treatment of neurological diseases. In recent years, there have been several data-driven computational predictors of various types of bioactive peptides, but the relevant work about neuropeptides is little at present. In this work, we developed an interpretable stacking model, named NeuroPpred-Fuse, for the prediction of neuropeptides through fusing a variety of sequence-derived features and feature selection methods. Specifically, we used six types of sequence-derived features to encode the peptide sequences and then combined them. In the first layer, we ensembled three base classifiers and four feature selection algorithms, which select non-redundant important features complementarily. In the second layer, the output of the first layer was merged and fed into logistic regression (LR) classifier to train the model. Moreover, we analyzed the selected features and explained the feasibility of the selected features. Experimental results show that our model achieved 90.6% accuracy and 95.8% AUC on the independent test set, outperforming the state-of-the-art models. In addition, we exhibited the distribution of selected features by these tree models and compared the results on the training set to that on the test set. These results fully showed that our model has a certain generalization ability. Therefore, we expect that our model would provide important advances in the discovery of neuropeptides as new drugs for the treatment of neurological diseases.

Endothelial CYP2J2 overexpression restores the BRB via METTL3-mediated ANXA1 upregulation.

Blood-retinal barrier (BRB) breakdown is responsible for multiple ocular diseases, such as diabetic retinopathy, age-related macular degeneration, and retinal vascular occlusive diseases. Increased vascular permeability contributes to vasogenic edema and tissue damage, with consequent adverse effects on vision. Herein, we found that endothelial CYP2J2 overexpression maintained BRB integrity after ischemia-reperfusion injury and consequently protected against retinal ganglion cell loss. Oxidative stress repressed endothelial ANXA1 expression in vivo and in vitro. CYP2J2 upregulated methyltransferase-like 3 (METTL3) expression and hence promoted ANXA1 translation via ANXA1 m6 A modification in endothelium under oxidative stress. CYP2J2 maintained the distribution of endothelial tight junctions and adherens junctions in an ANXA1-dependent manner. Endothelial ANXA1 plays an indispensable role in vascular homeostasis and stabilization during development. Endothelial ANXA1 deletion disrupted retinal vascular perfusion as well as BRB integrity. CYP2J2 metabolites restored BRB integrity in the presence of ANXA1. Our findings identified the CYP2J2-METTL3-ANXA1 pathway as a potential therapeutic target for relieving BRB impairments.

Construction of disulfide containing redox-responsive polymeric nanomedicine.

Disulfide bonds (S-S) are widely found in chemistry, biology, and materials science. Polymer nanomaterials containing disulfide bonds with a variety of excellent properties have great potential as drug and gene delivery carriers. The disulfide bond can exist stably in extracellular environment, but upon entering cancer cells, it will undergo a sulfhydryl-disulfide bond exchange reaction with glutathione (GSH) in the cytoplasm, causing the disulfide bond cleavage. Therefore, polymeric nanomaterials containing disulfide bonds are promising in cancer treatment due to the elevated GSH concentration inside cancer cells. This review highlights various synthetic approaches to prepare disulfide containing redox-responsive polymeric nanomedicine, including synthesis of disulfide bonds containing polymers, construction of polymeric nanoparticle with shell or core crosslinked disulfide bonds, preparation of polymer-drug conjugates via disulfide linkers, and disulfide linked responsive payloads.

Long-term cardiometabolic effects of ambient ozone pollution in a large Chinese population.

Limited studies investigated the effects of long-term ozone exposure on cardiometabolic health. We aimed to examine the association of long-term ozone exposure with a range of cardiometabolic diseases, as well as the subclinical indicators in Eastern China. The study included 202,042 adults living in 11 prefecture-level areas in Zhejiang Province between 2014 and 2021. Using a satellite-based model with a 1 × 1 km spatial resolution, we estimated residential 5-year average ozone exposures for each subject. Mixed-effects logistic and linear regression models were applied to explore the associations of ozone exposure with cardiometabolic diseases and subclinical indicators, respectively. We found that a 9% [95% confidence interval (95% CI): 7-12%] higher in odds of cardiometabolic disease per 10 µg/m3 increase in ozone exposure. Specifically, we also found higher prevalence of cardiovascular diseases (15%), stroke (19%), hypertension (7%), dyslipidemia (15%), and hypertriglyceridemia (9%) associated with ozone exposure. However, we did not find significant associations between ozone exposure and coronary heart disease, myocardial infarction, or diabetes mellitus. Long-term ozone exposures were also significantly associated with adverse changes in systolic blood pressure, diastolic blood pressure, total serum cholesterol, triglyceride, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, glucose concentration, and body mass index. Our results showed that people with lower education levels, those over 50 years old, and those who were overweight or obese were more susceptible to the effects of ozone on cardiometabolic diseases. Our findings demonstrated the detrimental effects of long-term ozone exposure on cardiometabolic health, emphasizing the need for ozone control strategies to reduce the burden of cardiometabolic diseases.