To address the constrains imposed by insufficient hydrogen peroxide (H2O2) and high glutathione (GSH) expression in tumor cells on the efficacy of chemodynamic therapy (CDT), zeolitic imidazolate framework-8 (ZIF-8) loaded with disulfiram (DSF) and 3-amino-1,2,4-triazole (3-AT) was synthesized via a one-pot approach. Subsequently, hyaluronic acid (HA)-modified cupric peroxide (CuO2) was in-situ grown on its surface through biomineralization to construct a multifunctional copper-based nanozyme ADZCH (3-AT/DSF@ZIF-8@CuO2-HA). This nanoplatform disrupts the intratumoral H2O2 homeostasis, depletes GSH, and synchronously delivers DSF and Cu2+ via cascade catalysis, thereby enhancing CDT and sensitizing tumors to DSF-based chemotherapy. The results of physicochemical characterization indicated that ADZCH presented a uniform core-shell structure with favorable dispersibility. Its particle size and Zeta potential were 196.5 nm and −19.5 mV, respectively. It possessed a microporous structure with a specific surface area of 81.8600 m2/g, and demonstrated efficient loading capacity for DSF and 3-AT, achieving drug loading efficiencies of 5.91% and 45.07%, respectively. Moreover, ADZCH can continuously and slowly release drugs in an acidic environment and maintain good stability under diverse physiological conditions. In vitro functional assays verified that ADZCH catalytically generated H2O2 and hydroxyl radicals while concurrently depleting GSH in a concentration- and incubation time-dependent manner. Cellular uptake experiments showed that HA modification significantly improved the uptake of nanoparticles by 4T1 cells. Cytotoxicity tests showed that 80 μg/mL ADZCH had a significant cytotoxic effect on 4T1 cells but no significant toxicity on L929 cells. DCFH-DA probe detection indicated that ADZCH could significantly induce intracellular reactive oxygen species (ROS) generation, thereby enhancing CDT efficacy. Live/dead staining experiments showed that ADZCH efficiently induced apoptosis, with the proportion of dead cells reaching 94.74%, demonstrating its promising potential for anti-tumor applications.This study provides new research ideas and experimental basis for overcoming the tumor microenvironment barrier and enhancing the anti-tumor effect of CDT combined with chemotherapy.

Background/Aims: Lenvatinib resistance remains a critical barrier in advanced hepatocellular carcinoma (HCC) therapy. However, the underlying mechanisms and strategies for reversing resistance remain incompletely understood. Methods: Integrated transcriptomics of lenvatinib-resistant patient tumors and an acquired-resistance murine model identified a novel macrophage subpopulation. Functional validation employed CRISPR-SAM screening, conditioned medium (CM) assays, subcutaneous/orthotopic xenografts, patient-derived organoids (PDOs), and patient-derived xenografts (PDXs). Mechanistic studies included ChIP-qPCR, co-immunoprecipitation, and pharmacologic targeting. Clinical relevance was assessed in a retrospective cohort. Results: Resistant HCC exhibited significant enrichment of a COLEC12high TAM subset , which correlated with poor survival and treatment response. These TAMs secreted neuregulin-1 (NRG1) , activating HER2/HER3-AKT signaling in tumor cells to drive cancer stemness and lenvatinib resistance. Mechanistically, in TAMs COLEC12 sequestered STAT1 in the cytoplasm, preventing its phosphorylation, and thereby derepressing STAT3-mediated NRG1 transcription. Depletion of NRG1 reversed the stemness phenotypes and resensitized tumors to lenvatinib both in vitro and in vivo. Clinically, high NRG1 expression predicted an inferior lenvatinib response and shorter survival. Crucially, the bispecific anti-HER2/HER3 antibody zenocutuzumab restored lenvatinib efficacy in PDOs, PDXs, and murine models. Conclusions Our work establishes the COLEC12high TAM/NRG1 axis as a master regulator of therapeutic resistance and identifies NRG1 as a predictive biomarker, providing a clinically actionable strategy to overcome lenvatinib resistance in HCC.

Multidrug-resistant (MDR) bacterial infections have emerged as a serious challenge of global public health crisis. The overuse and misuse of conventional antibiotics have dramatically accelerated the emergence, evolution and worldwide spread of drug-resistant bacterial strains, necessitating urgent exploration of novel antibacterial strategies. Bacteriophages serve as natural bacterial predators offering distinct advantages including high host specificity, autonomous self-replication capabilities and cost-effective large-scale production. However, wild-type phages present significant clinical limitations due to their narrow host ranges, susceptibility to rapid immune clearance and poor penetration of bacterial biofilms, which severely restrict their therapeutic applications. The convergence of synthetic biology, nanotechnology and advanced gene editing technologies has accelerated the development of engineered bacteriophage platforms, providing programmable, scalable and clinically translatable pathways to overcome these inherent biological constraints. Here, we systematically delineate four fundamental strategies for engineered bacteriophage development. Chemical modification utilizes reactive functional groups such as amino, carboxyl and thiol moieties on capsid proteins through esterification, amidation or click chemistry reactions to achieve precise drug conjugation and surface functionalization. In vivo editing encompasses ultraviolet or chemical mutagenesis for random mutation induction, homologous recombination for targeted genetic alterations, recombineering methodologies including electroporation-mediated bacteriophage recombination engineering, and CRISPR-Cas systems for precise genome editing to enable exact genetic reconstruction and host range reprogramming. In vitro synthesis leverages genome engineering platforms where intact phage genomes are transferred into yeast or host bacteria to facilitate highly efficient homologous recombination, enabling large DNA fragment assembly and cross-gene host range expansion without bacterial toxicity constraints. Directed evolution combines artificial selection through mutation library screening with rational design approaches involving chimeric receptor binding protein construction or site-specific mutagenesis, effectively balancing the discovery of unknown adaptive pathways with targeted host specificity modification. Moreover, we comprehensively discuss therapeutic applications across diverse clinical scenarios. Engineered bacteriophage effectively disrupt bacterial biofilms through sophisticated functionalized delivery platforms including nanozyme-conjugated phages, phage-liposome nanoconjugates and bio-responsive hydrogels, demonstrating significantly enhanced bactericidal efficiency compared to unmodified free phages. These bioengineered vectors attenuate bacterial virulence and resensitize pathogens to antibiotics by delivering CRISPR-Cas systems or base editors to disrupt critical virulence factors such as pili, capsule synthesis machineries and quorum sensing systems, or by inactivating antibiotic resistance determinants including beta-lactamase genes. As an intelligent nanomedicine delivery platform, engineered bacteriophage enable precise pathogen elimination an through photocatalytic reactive oxygen species generation, immunomodulatory interventions, or controlled release of antibacterial drugs. Furthermore, oral administration of engineered bacteriophage facilitates microbiota modulation, which selectively eliminate intestinal pathogens while preserve beneficial commensal microbiota, thereby restoring microbial community balance and preventing complications associated with dysbiosis. Finally, we critically analyze persistent challenges including host strain matching complexity, evolution of bacterial resistance mechanisms, pharmacokinetic optimization requirements, optimal administration route selection, large-scale production quality control standards and clinical dosing determination protocols. Through multidisciplinary integration of synthetic biology, infectious disease medicine and immunology, future translational medicine studies of bacteriophage should establish comprehensive technical platforms encompassing rapid phage screening, intelligent rational design, rigorous in vivo evaluation and standardized clinical validation processes, ultimately advancing engineered bacteriophage from laboratory innovations to clinically approved therapeutics for effectively combating MDR bacterial infections.

OBJECTIVE To analyze trends in the burden of disease associated with falls from 1990 to 2023， identify risk factors for falls， and provide a reference for the development of measures to reduce the burden of disease associated with falls and the formulation of public health policies. METHODS Based on the data of 2023 from the Global Burden of Disease （GBD） database， the changes in fall-related prevalence， mortality， disability-adjusted life years （DALYs） and incidence in China and globally from 1990 to 2023 were analyzed， and the stratified analyses by gender， age and socio-demographic index （SDI） were conducted. The risk factors related to falls in 2023 were systematically analyzed， and the impact of multimorbidity and polypharmacy on the occurrence of falls by combining relevant literature evidence was explored. RESULTS & CONCLUSIONS Globally， the percentage changes in age-standardized rates of fall-related prevalence， mortality， DALYs and incidence from 1990 to 2023 were －2.4% （95%UI： －4.8% to －0.3%）， －7.8% （95%UI： －20.5% to 10.9%）， －10.6% （95%UI： －16.5% to －4.3%）， and －4.6% （95%UI： －8.1% to －0.8%）， respectively. However， in some regions， the percentage changes in age-standardized rates for these indicators were greater than 0 （e.g.， prevalence， mortality and DALYs in Australasia， and incidence in Andean Latin America）. In China， the percentage changes in age-standardized rates of fall-related mortality and DALYs from 1990 to 2023 were －18.3% （95%UI： －56.7% to 32.3%） and 1.9% （95%UI： －10.1% to 12.4%）， while the percentage changes in age-standardized rates of prevalence and incidence were 25.9% （95%UI： 20.2% to 32.0%） and 35.7% （95%UI： 28.5% to 44.1%）， respectively. Globally， in regions with high and medium-to-high SDI levels， the percentage changes in age-standardized rates of fall-related prevalence and incidence showed an upward trend， while DALYs showed a downward trend； however， the trend in mortality was unclear. In regions with a middle SDI level， the percentage changes in age-standardized rates of fall-related prevalence and incidence both showed an upward trend， while the trends in mortality and DALYs were unclear. In regions with low-to-medium SDI level， the percentage changes in age-standardized rate of fall-related prevalence， DALYs and incidence all showed a downward trend， while the trend in mortality was unclear； in regions with low SDI level， the trends for all above indicators were unclear. Correlation analyses of the burden of fall-related diseases in China and globally indicated that the risk of fall-related diseases was higher among younger and middle-to-older adult male populations， while women were concentrated in older age groups. Meanwhile， as the SDI levels increase， the percentage change in age-standardized rate of DALYs for fall-related diseases showed a clear upward trend， and this trend was more pronounced in high-SDI regions. Tobacco use， alcohol consumption， low bone density， and occupational risks were risk factors for falls， with low bone density and occupational risks contributing significantly （exceeding 20% in some regions）； multimorbidity and polypharmacy could also significantly increase the risk of falls. It is recommended that clinical settings establish a list of fall-risk increasing drugs and a warning system， improve medication reviews， strengthen medication education and adherence management， foster multidisciplinary collaboration， and develop medication strategies for specific patient populations to reduce the incidence of falls and alleviate the burden of disease.

Colorectal cancer (CRC) is a common malignant tumor. The treatment of patients with advanced disease still faces severe challenges. Among patients with metastatic colorectal cancer (mCRC), most of those with microsatellite stable (MSS)/proficient mismatch repair (pMMR) tumors are highly insensitive to monotherapy with immune checkpoint inhibitors. With in-depth investigations into the mechanisms of the tumor immune microenvironment in MSS/pMMR CRC, the combination strategies of immunotherapy and targeted therapy have become a key direction to break through the treatment bottleneck in this population. These strategies include combinations of immunotherapy with antiangiogenic agents, epidermal growth factor receptor inhibitors, histone deacetylase inhibitors, and MAPK pathway inhibitors. Although the current relevant evidence is mainly derived from early-phase clinical trials, a number of studies demonstrated that immunotherapy combined with targeted therapy can improve the objective response rate and survival benefit in patients with MSS/pMMR mCRC and shows remarkable efficacy advantages in specific subgroups. This article systematically reviews the biological basis and clinical research progress of relevant combination therapeutic strategies, discusses potential beneficiary subgroups, and prospects future research directions. It aims to provide theoretical evidence and clinical references for optimizing the individualized treatment paradigm for this large patient population.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveObesity, a global chronic metabolic disease, is closely associated with disruptions in lipid metabolism and gut microbiota. Current intervention strategies still have limitations in terms of safety and microecological regulation, necessitating the exploration of novel natural regulatory approaches. Based on the early pathological characteristics of obesity, this study innovatively employs a rectal delivery method alongside a high-fat diet (HFD)-induced obesity model to systematically evaluate the inhibitory effects, safety, and gut microbiota regulation mechanisms of leek-derived and konjac-derived extracellular vesicles on obesity development. By simulating early clinical intervention scenarios, this study aims to explore the preventive potential of plant-derived extracellular vesicles during the initial stages of obesity onset. MethodsExtracellular vesicles from leek and konjac were isolated using ultracentrifugation combined with density gradient centrifugation. Their nanoscale properties were characterized by dynamic light scattering (DLS), transmission electron microscopy (TEM), and nanoparticle tracking analysis (NTA). Male C57BL/6J mice were randomly divided into four groups: normal control (NC), high-fat diet (HFD), leek-derived extracellular vesicles (LEVs), and konjac-derived extracellular vesicles (KEVs). Beginning simultaneously with HFD feeding, mice in the intervention groups received 20 g/L vesicles rectally every 3 d for 4 weeks. Body mass and body composition were monitored throughout. At endpoint, mouse serum, adipose tissue, and colonic contents were collected. Serum biochemical indices (lipid profile, liver and kidney function, cardiac markers) were assessed to evaluate safety and metabolic efficacy, while 16S rRNA sequencing was employed to analyze gut microbial structure and diversity. ResultsDLS, NTA, and TEM confirmed that both LEVs and KEVs exhibited typical cup-shaped nanostructures with average particle sizes of approximately 284 nm and 223 nm, respectively. LEVs and KEVs treatment significantly suppressed HFD-induced weight gain and elevation of body-fat percentage (P<0.05), and reduced accumulation of abdominal white and epididymal adipose tissue. Serological analyses showed that both vesicles lowered total cholesterol, triglycerides and LDL-cholesterol, and ameliorated liver enzyme profiles (ALT, AST), demonstrating lipid-metabolic regulation and hepatoprotective effects. No hepatic, renal or cardiac dysfunction was observed, indicating favorable safety. Gut microbiota analyses revealed that vesicle intervention partially restored HFD-depleted microbial diversity and reshaped community structure. Notably, LEVs markedly increased the relative abundance of the beneficial taxon Lachnospiraceae at the family level, which is known for producing short-chain fatty acids and enhancing intestinal barrier function. Furthermore, Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) functional prediction suggested that LEVs and KEVs modulated gut microbial functions through distinct mechanisms: LEVs downregulated pathways related to ribosomes and DNA replication while enhancing xenobiotic degradation, whereas KEVs tended to upregulate energy metabolism and protein synthesis toward healthy levels. ConclusionRectally administered LEVs and KEVs exhibit excellent safety and pronounced metabolic benefits during the early phase of obesity, suppressing weight gain, correcting lipid dysregulation, and exerting effects via modulation of gut microbial composition and function. This study provides systematic experimental evidence supporting plant-derived exosome-like vesicles as an early intervention strategy against obesity.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveTo explore the vascular endothelial injury in male mice caused by exposure to polystyrene microplastics （PS-MPs） and the intervention effect of luteolin on vascular remodeling. Additionally， to investigate the mechanism through the oxidative system and metabolomics. MethodsThirty-two C57BL/6 mice （6-8 weeks old） were randomly divided into the saline group （saline group）， the 0.1 mg/kg PS-MPs exposure group （0.1PS-MPs group）， the 1 mg/kg PS-MPs exposure group （1PS-MPs group）， and the 1 mg/kg PS-MPs + luteolin treatment group （1PS-MPs + Lut group）， with 8 mice in each group. After 8 weeks of intervention， the body weight， blood pressure， aortic organ coefficient， and aortic histopathological changes of mice in each group were detected； the total cholesterol （TC）， triglyceride （TG）， and high-density lipoprotein cholesterol （HDL-C） lipid metabolism-related indicators in the aorta of mice were detected； the reactive oxygen species （ROS）， glutathione （GSH）， and malondialdehyde （MDA） oxidative stress-related indicators were detected； the endothelin （ET-1）， nitric oxide （NO）， vascular endothelial growth factor A （VEGF-A）， vascular cell adhesion molecule-1 （VCAM-1/CD106）， and intercellular adhesion molecule-1 （ICAM-1/CD54） endothelial function-related indicators and serum metabolomics were detected. ResultsCompared to the saline group， exposure to PS-MPs resulted in pathological thickening of the mouse aorta， increased aortic organ coefficient， and elevated blood pressure. Lipid metabolism-related indicators， including TC and TG， were elevated， while HDL-C was reduced， indicating lipid metabolism disorder in mice. Oxidative stress markers such as ROS and MDA increased， whereas GSH decreased， demonstrating oxidative damage. Vascular endothelial inflammation and injury markers， including ET-1， VEGF-A， VCAM-1， and ICAM-1， were upregulated， while the vasodilatory substance NO was downregulated， confirming endothelial injury. Furthermore， serum metabolomics results revealed that PS-MPs exposure induced endothelial damage by disrupting metabolic pathways such as the citrate cycle. Compared to the PS-MPs group， luteolin significantly reversed these effects， attenuating oxidative stress and lipid metabolism disorders， and effectively repairing endothelial injury. ConclusionPS-MPs induce vascular toxicity through oxidative stress and lipid metabolism. Luteolin effectively alleviates endothelial damage and vascular remodeling.

ObjectiveTo investigate the effects of Trpc6 knockout on chronic lipopolysaccharide （LPS）-induced myocardial inflammation and fibrosis in mice and its potential mechanisms. MethodsMale C57BL/6 wild-type （WT） mice and Trpc6 knockout （Trpc6^-/-） mice of the same background were randomly divided into four groups： WT control， WT+LPS （200 μg/kg）， Trpc6^-/- control， and Trpc6^-/-+LPS （200 μg/kg）. Group with LPS received intraperitoneal LPS injections for 21 consecutive days to induce chronic myocardial inflammatory injury. Cardiac ultrasound assessed changes in left ventricular ejection fraction （EF）， left ventricular shortening fraction （FS）， and cardiac output （CO）. Hematoxylin and eosin （HE） staining and periodic acid-Schiff （PAS） staining were used to examine morphological alterations in myocardial tissue. Masson’s trichrome staining was used to assess myocardial fiber alterations； Western blot analysis was used to measure myocardial tissue expression of transient receptor potential calcium channel 6 （TRPC6）， NOD-like receptor family pyrin domain-containing 3 inflammasome （NLRP3），absent in melanoma 2 inflammasome （AIM2）， Caspase-1， interleukin （IL）-6， and IL-1β in mouse myocardial tissue. ResultsCompared with the WT control group， the WT+LPS group exhibited decreased cardiac EF （P<0.01）， FS （P<0.01）， and CO （P<0.05）， along with significantly increased myocardial tissue damage， glycoprotein deposition， and fibrosis （P<0.01）. Further analysis revealed that compared with the WT control group， the WT+LPS group exhibited markedly increased myocardial tissue expression of TRPC6， NLRP3， AIM2， Caspase-1， IL-6， and IL-1β （P<0.01）. Compared with the WT+LPS group， mice in the Trpc6^-/- +LPS group exhibited elevated EF （P<0.01） and FS （P<0.05）， along with reduced myocardial tissue injury， glycoprotein deposition， and fibrosis （P<0.05）. ConclusionChronic LPS treatment can activate NLRP3/AIM2 inflammasomes through the up-regulation of TRPC6 expression， and then lead to chronic myocardial inflammatory injury and fibrosis， while Trpc6 knockdown can reduce myocardial inflammatory injury and fibrosis， and the mechanism is related to inhibiting the activation of NLRP3/AIM2 inflammasomes.