Atherosclerosis (AS), the primary pathological contributor to cardiovascular diseases (CVDs), has increasingly affected younger populations due to modern dietary habits and sedentary lifestyles. Current diagnostic modalities, including ultrasound, MRI, and CT, primarily identify advanced lesions and inadequately evaluate plaque vulnerability, thereby hindering early detection. Conventional treatments, which involve long-term medications associated with side effects such as hepatic injury and surgical interventions that carry risks of restenosis and hemorrhage, underscore the urgent need for non-invasive, cost-effective early diagnostic methods and targeted therapies. Gut microbiota metabolites are pivotal in AS pathogenesis, with trimethylamine N-oxide (TMAO) and short-chain fatty acids (SCFAs) serving as functionally opposing biomarkers. TMAO is produced when gut bacteria, specifically Firmicutes and Proteobacteria, metabolize dietary choline and carnitine into trimethylamine (TMA), which the liver subsequently converts to TMAO via flavin-containing monooxygenase 3 (FMO3); TMAO is then excreted in urine. Variability in TMAO levels is influenced by marine food consumption and FMO3 modulation, which can be affected by genetics, age, and diet. Mechanistically, TMAO exacerbates AS by disrupting cholesterol metabolism, inducing endothelial dysfunction through the elevation of reactive oxygen species (ROS) and pro-inflammatory cytokines such as IL-6, and reducing nitric oxide levels. Additionally, TMAO activates NF-κB and NLRP3 pathways while enhancing platelet reactivity. Clinically, elevated TMAO levels correlate with early AS and serve as predictors of mortality in patients with stable coronary artery disease (CAD) and acute coronary syndrome (ACS), as well as major adverse cardiovascular events (MACE) in stroke patients. Conversely, SCFAs—namely acetate, propionate, and butyrate—are produced by gut bacteria such as Akkermansia muciniphila and Faecalibacterium prausnitzii through the fermentation of dietary fiber. These metabolites exert anti-AS effects: acetate aids in maintaining metabolic homeostasis; propionate protects endothelial function and reduces plaque area; and butyrate fortifies intestinal barriers while suppressing inflammation. Furthermore, SCFAs cross-regulate bile acid metabolism, thereby influencing TMAO levels, and antagonize the pro-inflammatory and lipid-disrupting effects of TMAO. The use of TMAO and SCFAs as standalone biomarkers is constrained by limitations. TMAO lacks specificity, while SCFA levels fluctuate based on gut microbiota and dietary intake. Traditional AS risk assessment tools, which include clinical indicators, imaging techniques, and single biomarkers such as CRP, LDL-C, and ASCVD scores, overlook gut metabolism and demonstrate inadequate performance in younger populations. This review advocates for an “antagonistic-complementary” combined strategy: utilizing acetate and TMAO for early AS, propionate and TMAO for progressive AS, and butyrate and TMAO for advanced AS, addressing endothelial dysfunction, lipid deposition, and plaque stability/thrombosis risk, respectively. For clinical application, standardization of detection methods is crucial; liquid chromatography-mass spectrometry (LC-MS) is the gold standard, necessitating a unified sample pretreatment protocol, such as extraction with 1% formic acid in methanol. Additionally, dried blood spots (DBS) facilitate non-invasive testing, provided that dietary controls are implemented prior to detection, including a 12-hour fast and avoidance of high-choline and high-fiber foods. Existing challenges encompass the absence of standardized systems, limited large-scale validation, and ambiguous interactions with conditions such as hypertension. The authors’ team has previously established connections between gut metabolites and AS, including the reduction of TMAO as a preventive measure for AS, thereby reinforcing this proposed strategy. Future research should prioritize standardization, the development of machine learning-optimized models, validation of interventions, and the exploration of multi-omics-based “gut microbiota-metabolite-vascular” networks. In conclusion, the combined detection of TMAO and SCFAs offers a novel framework for AS risk assessment, facilitating early diagnosis and targeted interventions while enhancing the integration of gut metabolism into cardiovascular disease management.

Atherosclerosis (AS), the primary pathological contributor to cardiovascular diseases (CVDs), has increasingly affected younger populations due to modern dietary habits and sedentary lifestyles. Current diagnostic modalities, including ultrasound, MRI, and CT, primarily identify advanced lesions and inadequately evaluate plaque vulnerability, thereby hindering early detection. Conventional treatments, which involve long-term medications associated with side effects such as hepatic injury and surgical interventions that carry risks of restenosis and hemorrhage, underscore the urgent need for non-invasive, cost-effective early diagnostic methods and targeted therapies. Gut microbiota metabolites are pivotal in AS pathogenesis, with trimethylamine N-oxide (TMAO) and short-chain fatty acids (SCFAs) serving as functionally opposing biomarkers. TMAO is produced when gut bacteria, specifically Firmicutes and Proteobacteria, metabolize dietary choline and carnitine into trimethylamine (TMA), which the liver subsequently converts to TMAO via flavin-containing monooxygenase 3 (FMO3); TMAO is then excreted in urine. Variability in TMAO levels is influenced by marine food consumption and FMO3 modulation, which can be affected by genetics, age, and diet. Mechanistically, TMAO exacerbates AS by disrupting cholesterol metabolism, inducing endothelial dysfunction through the elevation of reactive oxygen species (ROS) and pro-inflammatory cytokines such as IL-6, and reducing nitric oxide levels. Additionally, TMAO activates NF-κB and NLRP3 pathways while enhancing platelet reactivity. Clinically, elevated TMAO levels correlate with early AS and serve as predictors of mortality in patients with stable coronary artery disease (CAD) and acute coronary syndrome (ACS), as well as major adverse cardiovascular events (MACE) in stroke patients. Conversely, SCFAs—namely acetate, propionate, and butyrate—are produced by gut bacteria such as Akkermansia muciniphila and Faecalibacterium prausnitzii through the fermentation of dietary fiber. These metabolites exert anti-AS effects: acetate aids in maintaining metabolic homeostasis; propionate protects endothelial function and reduces plaque area; and butyrate fortifies intestinal barriers while suppressing inflammation. Furthermore, SCFAs cross-regulate bile acid metabolism, thereby influencing TMAO levels, and antagonize the pro-inflammatory and lipid-disrupting effects of TMAO. The use of TMAO and SCFAs as standalone biomarkers is constrained by limitations. TMAO lacks specificity, while SCFA levels fluctuate based on gut microbiota and dietary intake. Traditional AS risk assessment tools, which include clinical indicators, imaging techniques, and single biomarkers such as CRP, LDL-C, and ASCVD scores, overlook gut metabolism and demonstrate inadequate performance in younger populations. This review advocates for an “antagonistic-complementary” combined strategy: utilizing acetate and TMAO for early AS, propionate and TMAO for progressive AS, and butyrate and TMAO for advanced AS, addressing endothelial dysfunction, lipid deposition, and plaque stability/thrombosis risk, respectively. For clinical application, standardization of detection methods is crucial; liquid chromatography-mass spectrometry (LC-MS) is the gold standard, necessitating a unified sample pretreatment protocol, such as extraction with 1% formic acid in methanol. Additionally, dried blood spots (DBS) facilitate non-invasive testing, provided that dietary controls are implemented prior to detection, including a 12-hour fast and avoidance of high-choline and high-fiber foods. Existing challenges encompass the absence of standardized systems, limited large-scale validation, and ambiguous interactions with conditions such as hypertension. The authors’ team has previously established connections between gut metabolites and AS, including the reduction of TMAO as a preventive measure for AS, thereby reinforcing this proposed strategy. Future research should prioritize standardization, the development of machine learning-optimized models, validation of interventions, and the exploration of multi-omics-based “gut microbiota-metabolite-vascular” networks. In conclusion, the combined detection of TMAO and SCFAs offers a novel framework for AS risk assessment, facilitating early diagnosis and targeted interventions while enhancing the integration of gut metabolism into cardiovascular disease management.

Objective:To investigate the effect of COX6C on the proliferation of multiple myeloma(MM)cells and its mechanism of action.Methods:The expression of COX6C in MM cell lines were detected by RT-PCR.siRNA technology was used to knockdown COX6C expression in OPM2 cells.MTT assay and flow cytometry were employed to assess the effect of COX6C knockdown by siRNA on cell proliferation,mitochondrial membrane potential(Δ Ψm),and intracellular adenosine triphosphate(ATP)levels.The mitochondrial morphological changes in OPM2 cells pre-and post-siRNA-mediated COX6C knockdown were observed by transmission electron microscopy(TEM).Results:The relative expression level of COX6C was significantly increased in MM cell lines(P＜0.01).Following siRNA-mediated COX6C knockdown,OPM2 cell proliferation was inhibited,with viable cells accounting for 62.32％±3.43％and 47.01％±5.12％after 48 and 72 hours of culture,respectively.siRNA-mediated COX6C knockdown also caused significant reductions in mitochondrial membrane potential and intracellular ATP levels(P＜0.05),accompanied by mitochondrial shortening,swelling,and incomplete cristae structures.Conclusion:COX6C may promote the proliferation of MM cells by altering the mitochondrial structure and elevating intracellular ATP levels.

Objective:In order to clarify the ABO phenotype and genotype,and explore the molecular biological mechanism,serological detection,genotyping and gene sequencing were performed on an upper gastrointestinal hemorrhage patient with inconsistent forward and reverse ABO blood typing.Methods:ABO forward and reverse blood typing,H antigen identification,capillary centrifugation test and salivary substance detection were performed by classical serological method,moreover,polymerase chain reaction-sequence specific primer(PCR-SSP)was used for ABO genotyping,ABO gene 1-7 exons were sequenced by Sanger analysis in order to identify mutation.Results:Mixed field agglutination with anti-A,anti-AB and no agglutination with anti-A1 were appeared in the forward typing tests,agglutination with B cells but no agglutination with A1 cells and O cells were appeared in the reverse typing tests.3+agglutination strength was showed with anti-H.In capillary centrifugation experiment,erythrocyte after isolation in proximal part and distal end had same strength of agglutination with anti-A.Substances A and H were detected in saliva.The patient was assigned an A3 phenotype according to serological characteristics.Sequencing results of ABO gene 1-7 exons showed c.261delG,c.467C＞T,c.865A＞G,in which,865A＞G was the first discovered mutation,and this new mutation had been submitted to GenBank with accession number PP187306.Conclusion:A novel site mutation c.865A＞G is reported in this study,and this new mutation can result in a replacement of Met with Val at residue 289(p.Met289Val)and lead to an A3 phenotype.

Objective:To evaluate the cost-effectiveness and impact on mortality of health management services for the elderly aged 65 years and older in national essential public health service project.Methods:Based on the data of county-level medical institutions in Henan Province from 2019 to 2024,the Random Forest Method was used to construct a counterfactual framework to predict the hospitalization expenses under the unmanaged scenario,and then the cost-benefit ratio(BCR)and net income were calculated.Time-dependent Cox proportional hazards model was used to evaluate the effect of health management on all-cause mortality and cardiovascular and cerebrovascular disease mortality in the elderly.Results:A total of 962 955 elderly patients were included,451 119(46.85%)were included in the management group.The average hospitalization cost of the management group was significantly lower than that of the non-management group(P<0.05).Except for 2020-2021,BCRS in 2019 and 2022-2024 were 6.34,2.05,4.45 and 6.60,respectively.The risk of all-cause death was reduced by 76.96%,and the risk of cardiovascular and cerebrovascular death was reduced by 75.57%in the elderly patients included in the management group compared with those not included in the management group.Suggestions:It is necessary to establish a health outcomes-based evaluation system and promote the transformation and upgrading of the service model from single chronic disease management to"integrated health services with multi-disease management".

Objective:To investigate the effects of combination therapy with aqueous extract of corn silk(CS)and training on exercise capacity and glycolipid metabolism in mice with metabolic syndrome(MS).Methods:In this study,db/db mice were used as the animal model of MS.The mice were administered aqueous extract of CS via gavage and subjected to different intensities of training for 12 weeks(3 months).The specific experimental design was as follows:24 db/db mice were randomly divided into four groups on average:negative control group(NC),aqueous extract of CS group(CS),aqueous extract of CS+moderate-intensity training group(CS+MT),and CS aqueous extract of CS+high-intensity training group(CS+HT).The maximum running speed,forelimb grip strength,body weight and fasting blood glucose of mice were measured before and after treatment.After the intervention,oral glucose tolerance test(OGTT)and insulin tolerance test(ITT)were conducted to assess glucose metabolism,while serum triglyceride(TG),total cholesterol(TC),high-density lipoprotein cholesterol(HDL-C),and low-density lipoprotein cholesterol(LDL-C)levels were measured to evaluate lipid metabolism.Results:After 3 months of intervention,there were significant differences in the maximum running speed and forelimb grip strength among the four groups(P＜0.05).The maximum running speed and forelimb grip strength of CS group,CS+MT group and CS+HT group were higher than those of NC group(P＜0.05).The CS+MT group exhibited higher forelimb grip strength,and the CS+HT group showed higher maximum running speed and forelimb grip strength compared to the CS group(P＜0.05),while no significant difference was found between the CS+MT and CS+HT groups(P＞0.05).Significant differences in body weight were observed among the four groups after 3 months of intervention(P＜0.05).Specifically,the CS+MT and CS+HT groups exhibited significantly lower body weight compared to both the NC and CS groups(P＜0.05),with the CS+MT group having the lowest body weight(P＜0.05).Fasting blood glucose levels also differed significantly among the groups after 2 and 3 months of intervention(P＜0.05).The CS,CS+MT,and CS+HT groups had lower fasting blood glucose levels compared to the NC group(P＜0.05),with the CS+MT and CS+HT groups showing the lowest levels(P＜0.05).No significant difference was found between the CS+MT and CS+HT groups(P＞0.05).After 3 months of intervention,significant differences in the area under the curve(AUC)of OGTT and ITT were observed among the four groups(P＜0.05).The AUC of OGTT and ITT were significantly lower in the CS,CS+MT,and CS+HT groups compared to the NC group(P＜0.05).The CS+MT and CS+HT groups exhibited the lowest AUC values for both OGTT and ITT(P＜0.05),with the CS+MT group showing the lowest AUC for OGTT(P＜0.05).Significant differences in serum lipid levels were observed among the four groups after 3 months of intervention(P＜0.05).TG,TC,and LDL-C levels were significantly lower,while HDL-C levels were higher in the CS,CS+MT,and CS+HT groups compared to the NC group(P＜0.05).The CS+MT group had the lowest TG levels and the highest HDL-C levels compared to the CS+HT group(P＜0.05),with no significant differences in TC and LDL-C levels between these two groups(P＞0.05).Conclusion:Aqueous extract of CS combined with different intensity training can significantly improve the exercise capacity and glycolipid metabolism of MS mice and reduce body weight,especially CS combined with MT treatment is more effective in improving lipid metabolism.In addition,when combined with HT,aqueous extract of CS can also play an auxiliary role in reducing the side effects of high-intensity exercise and improving the therapeutic effect.

Objective To evaluate the efficacy and safety of a novel intravascular lithotripsy(IVL)balloon—Vesscrack shockwave balloon—for vascular preparation before stent implantation in patients with severe coronary artery calcification(CAC).Methods This was a prospective,single-arm,multicenter study conducted in China from June 2022 to October 2022.Patients with severe CAC were treated with the Vesscrack shockwave balloon for lesion preparation,followed by drug-eluting stent(DES)implantation.Of these,33 patients underwent optical coherence tomography(OCT).The primary endpoint was procedural success,defined as successful stent implantation with residual stenosis≤30％and the absence of in-hospital major adverse events,including cardiac death,target vessel-related myocardial infarction,or target lesion revascularization.Results A total of 170 patients[mean age:(65.9±7.9)years,116 males]were enrolled.After treatment with IVL and DES,the minimum lumen diameter increased significantly compared to baseline[(2.34±0.40)mm vs.(0.95±0.33)mm,P＜0.001],the degree of stenosis was significantly reduced[(13.24±6.60)％vs.(65.18±10.59)％,P＜0.001].Procedural success was achieved in 100％of cases,and device success was 98.8％.The 30-day patient-related cardiovascular clinical composite endpoint(POCE)rate was 0.0,with no target lesion failure,no confirmed or potential thrombotic events were observed.The shockwave energy generator demonstrated excellent stability and ease of use.Among the 33 patients assessed with OCT,after IVL intervention,the maximum calcified area of the lumen[(3.51±1.51)mm2 vs.(2.85±1.80)mm2,P＜0.001],and the minimum lumen area within the target lesion[(3.08±1.04)mm2 vs.(2.02±0.75)mm2,P＜0.001],and after DES intervention,the luminal area of the largest calcified site[(6.59±1.64)mm2 vs.(2.85±1.80)mm2,P＜0.001]and the minimum luminal area within the target lesion[(6.19±1.45)mm2 vs.(2.02±0.75)mm2,P＜0.001]were significantly increased,and the differences were statistically significant.Conclusions The Vesscrack shockwave balloon is effective and safe for vascular preparation in patients with severe CAC prior to stent implantation.It achieves significant calcified plaque modification,high procedural success rates,and minimal complications.

Objective To explore the predictive efficacy of several multimodal MRI-based machine learning models for the promoter methylation states of O6-methylguanine-DNA methyltransferase(MGMT)of glioblastoma muliforme(GBM)patients in terms of the GBM heterogeneity and the complexity of the tumor microenvironment.Methods Firstly,the multimodal MRI images of 317 GBM patients from The University of Pennsylvania Glioblastoma(UPENN-GBM)dataset were pre-processed,with four sequences involved in including T1-weighted imaging(T1WI)sequence,T1-weighted contrast-enhanced imaging(T1CE)sequence,T2-weighted imaging(T2WI)sequence and fluid-attenuated inversion recovery(FLAIR)sequence,and the radiomics features were extracted for two regions of interest(ROIs)such as the tumor core region and the tumor edema region.Secondly,the data of the 317 GBM patients were randomly divided into a training set(254 cases)and a test set(63 cases),which underwent normalization with Z-scores and feature selection and dimensionality reduction with Lasso regression.Finally,three models were established respectively with particle swarm optimization-support vector machine(PSO-SVM),C-support vector classification(C-SVC)and adaptive boosting(adaptive boosting(Adaboost)algorithms,and the predictive efficacy of the three models for glioblastoma multiforme MGMT promoter methylation states were evaluated in terms of accuracy and AUC.Results The Adaboost model based on T2WI sequence and radiomics features of the tumor core region had the highest predictive efficacy with accuracy and AUC values of 67％and 0.74,respectively,higher than those of other combinations of sequences,models and regions of interest.Conclusion The multimodal MRI-based machine learning models can be used for the prediction of glioblastoma multiforme MGMT promoter methylation states,which provides powerful support for personalized treatment and prognostic assessment of GBM.[Chinese Medical Equipment Journal,2025,46(6):7-13]

Objective To evaluate the efficacy and safety of a novel intravascular lithotripsy(IVL)balloon—Vesscrack shockwave balloon—for vascular preparation before stent implantation in patients with severe coronary artery calcification(CAC).Methods This was a prospective,single-arm,multicenter study conducted in China from June 2022 to October 2022.Patients with severe CAC were treated with the Vesscrack shockwave balloon for lesion preparation,followed by drug-eluting stent(DES)implantation.Of these,33 patients underwent optical coherence tomography(OCT).The primary endpoint was procedural success,defined as successful stent implantation with residual stenosis≤30％and the absence of in-hospital major adverse events,including cardiac death,target vessel-related myocardial infarction,or target lesion revascularization.Results A total of 170 patients[mean age:(65.9±7.9)years,116 males]were enrolled.After treatment with IVL and DES,the minimum lumen diameter increased significantly compared to baseline[(2.34±0.40)mm vs.(0.95±0.33)mm,P＜0.001],the degree of stenosis was significantly reduced[(13.24±6.60)％vs.(65.18±10.59)％,P＜0.001].Procedural success was achieved in 100％of cases,and device success was 98.8％.The 30-day patient-related cardiovascular clinical composite endpoint(POCE)rate was 0.0,with no target lesion failure,no confirmed or potential thrombotic events were observed.The shockwave energy generator demonstrated excellent stability and ease of use.Among the 33 patients assessed with OCT,after IVL intervention,the maximum calcified area of the lumen[(3.51±1.51)mm2 vs.(2.85±1.80)mm2,P＜0.001],and the minimum lumen area within the target lesion[(3.08±1.04)mm2 vs.(2.02±0.75)mm2,P＜0.001],and after DES intervention,the luminal area of the largest calcified site[(6.59±1.64)mm2 vs.(2.85±1.80)mm2,P＜0.001]and the minimum luminal area within the target lesion[(6.19±1.45)mm2 vs.(2.02±0.75)mm2,P＜0.001]were significantly increased,and the differences were statistically significant.Conclusions The Vesscrack shockwave balloon is effective and safe for vascular preparation in patients with severe CAC prior to stent implantation.It achieves significant calcified plaque modification,high procedural success rates,and minimal complications.

Objective To explore the predictive efficacy of several multimodal MRI-based machine learning models for the promoter methylation states of O6-methylguanine-DNA methyltransferase(MGMT)of glioblastoma muliforme(GBM)patients in terms of the GBM heterogeneity and the complexity of the tumor microenvironment.Methods Firstly,the multimodal MRI images of 317 GBM patients from The University of Pennsylvania Glioblastoma(UPENN-GBM)dataset were pre-processed,with four sequences involved in including T1-weighted imaging(T1WI)sequence,T1-weighted contrast-enhanced imaging(T1CE)sequence,T2-weighted imaging(T2WI)sequence and fluid-attenuated inversion recovery(FLAIR)sequence,and the radiomics features were extracted for two regions of interest(ROIs)such as the tumor core region and the tumor edema region.Secondly,the data of the 317 GBM patients were randomly divided into a training set(254 cases)and a test set(63 cases),which underwent normalization with Z-scores and feature selection and dimensionality reduction with Lasso regression.Finally,three models were established respectively with particle swarm optimization-support vector machine(PSO-SVM),C-support vector classification(C-SVC)and adaptive boosting(adaptive boosting(Adaboost)algorithms,and the predictive efficacy of the three models for glioblastoma multiforme MGMT promoter methylation states were evaluated in terms of accuracy and AUC.Results The Adaboost model based on T2WI sequence and radiomics features of the tumor core region had the highest predictive efficacy with accuracy and AUC values of 67％and 0.74,respectively,higher than those of other combinations of sequences,models and regions of interest.Conclusion The multimodal MRI-based machine learning models can be used for the prediction of glioblastoma multiforme MGMT promoter methylation states,which provides powerful support for personalized treatment and prognostic assessment of GBM.[Chinese Medical Equipment Journal,2025,46(6):7-13]