High-purity graphite is extensively utilized in the semiconductor industry.Enhancing its corrosion resistance is crucial for reducing the manufacturing costs of the third-generation semiconductors.In this study,a cont...High-purity graphite is extensively utilized in the semiconductor industry.Enhancing its corrosion resistance is crucial for reducing the manufacturing costs of the third-generation semiconductors.In this study,a continuous and dense TaC coating was fabricated on the surface of graphite using CVD method.The corrosion resistance and mechanism of the coating were investigated in a high-temperature steam environment.This environment involved temperatures exceeding 2200 K and the erosion of the coating by Si-containing mixed steam flows.The results indicated that the corrosion in the affected areas was primarily due to chemical reactions,characterized by the formation of pores and micro-cracks,whereas failure areas were dominated by mechanical delamination,which led to macroscopic defects.Moreover,the mixed high-temperature steam corrosion of the TaC coating showed preferential selectivity,resulting in a stepped corrosion morphology at the crystalline level.The surface roughness of the samples significantly increased after corrosion,from 0.36 to 5.28μm,although the surface composition remained largely unchanged.The TaC coating provides a certain level of protection to the graphite substrate,enhancing the service life of graphite components and demonstrating promising application potential.展开更多
Cardiovascular diseases(CVDs)are one of the most serious diseases threatening human health in the world.Therefore,effective monitoring and treatment of CVDs are urgently needed.Compared with traditional rigid devices,...Cardiovascular diseases(CVDs)are one of the most serious diseases threatening human health in the world.Therefore,effective monitoring and treatment of CVDs are urgently needed.Compared with traditional rigid devices,nanomaterials based flexible devices open up new opportunities for further development beneficial from the unique properties of nanomaterials which contribute to excellent performance to better prevent and treat CVDs.This review summarizes recent advances of nanomaterials based flexible devices for the monitoring and treatment of CVDs.First,we review the outstanding characteristics of nanomaterials.Next,we introduce flexible devices based on nanomaterials for practical use in CVDs including in vivo,ex vivo,and in vitro methods.At last,we make a conclusion and discuss the further development needed for nanomaterials and monitoring and treatment devices to better care CVDs.展开更多
Objective Elevated depressive symptoms are well-documented among geriatric adults with cardiovascular disease(CVD);however,few studies have accounted for long-term cumulative depressive symptom exposure.This study det...Objective Elevated depressive symptoms are well-documented among geriatric adults with cardiovascular disease(CVD);however,few studies have accounted for long-term cumulative depressive symptom exposure.This study determined the relationship between cumulative depressive symptoms and CVD.Methods Individual participant data were obtained from the China Health and Retirement Longitudinal Study(CHARLS)and Health and Retirement Study(HRS).Eligible participants had access to assessment information on depressive symptoms and had no history of CVD at baseline.Long-term cumulative depressive symptoms were estimated by calculating the area under the curve based on the Center for Epidemiological Studies Depression Scale.Results Herein,8,861 participants from CHARLS(mean age:58.58 years;male:48.6%)and 7,284 from HRS(60.94 years;35.0%)were enrolled.The median follow-up period was 5 years for the CHARLS and10 years for the HRS.Compared with the first quartile of cumulative depressive symptoms,the HRs(95%CI)in the fourth quartile were 1.73(1.48,2.02)for predicting CVD(P<0.001),1.83(1.52,2.19)for heart disease(P<0.001),1.53(95%CI:1.17,1.99)for stroke(P=0.002)in CHARLS.For HRS,the HRs(95%CI)were 1.41(95%CI:1.27,1.57;P<0.001),1.42(95%CI:1.26,1.59;P<0.001),and 1.30(95%CI:1.06,1.58;P=0.010)respectively.Strong dose-response relationships were observed,with similar results for the two cohorts.Conclusion Long-term cumulative depressive symptoms were significantly associated with incident CVD in middle-aged and older adults,providing insights into controlling long-term depressive symptoms to improve this cohort's health.展开更多
Cardiovascular disease(CVD)is often accompanied by chronic kidney disease(CKD)and metabolic disorders such as obesity and type 2 diabetes^([1]).The coexistence of these conditions can lead to systemic dysfunction and ...Cardiovascular disease(CVD)is often accompanied by chronic kidney disease(CKD)and metabolic disorders such as obesity and type 2 diabetes^([1]).The coexistence of these conditions can lead to systemic dysfunction and substantially increase adverse cardiovascular outcomes.To describe this interplay,the American Heart Association(AHA)recently proposed the concept of cardiovascular-kidney-metabolic(CKM)syndrome^([1]).However,its risk-enhancing factors and underlying mechanisms remain unclear.展开更多
In the effort to enhance cardiovascular diagnostics,deep learning-based heart sound classification presents a promising solution.This research introduces a novel preprocessing method:iterative k-means clustering combi...In the effort to enhance cardiovascular diagnostics,deep learning-based heart sound classification presents a promising solution.This research introduces a novel preprocessing method:iterative k-means clustering combined with silhouette score analysis,aimed at downsampling.This approach ensures optimal cluster formation and improves data quality for deep learning models.The process involves applying k-means clustering to the dataset,calculating the average silhouette score for each cluster,and selecting the clusterwith the highest score.We evaluated this method using 10-fold cross-validation across various transfer learningmodels fromdifferent families and architectures.The evaluation was conducted on four datasets:a binary dataset,an augmented binary dataset,amulticlass dataset,and an augmentedmulticlass dataset.All datasets were derived from the Heart Wave heart sounds dataset,a novelmulticlass dataset introduced by our research group.To increase dataset sizes and improve model training,data augmentation was performed using heartbeat cycle segmentation.Our findings highlight the significant impact of the proposed preprocessing approach on the HeartWave datasets.Across all datasets,model performance improved notably with the application of our method.In augmented multiclass classification,the MobileNetV2 model showed an average weighted F1-score improvement of 27.10%.In binary classification,ResNet50 demonstrated an average accuracy improvement of 8.70%,reaching 92.40%compared to its baseline performance.These results underscore the effectiveness of clustering with silhouette score analysis as a preprocessing step,significantly enhancing model accuracy and robustness.They also emphasize the critical role of preprocessing in addressing class imbalance and advancing precision medicine in cardiovascular diagnostics.展开更多
Background It remains unclear whether sleep duration and physical activity(PA)trajectories in middle-aged and older adults are associated with different risks of cardiovascular diseases(CVDs).This study aimed to explo...Background It remains unclear whether sleep duration and physical activity(PA)trajectories in middle-aged and older adults are associated with different risks of cardiovascular diseases(CVDs).This study aimed to explore the trajectories of total sleep duration and PA among middle-aged and older Chinese adults and their impact on CVD risk.Methods This study was based on the China Health and Retirement Longitudinal Study.12009 adults aged 45 years and older from five waves were included.CVD events were measured by self-reports of heart disease and stroke.We first used groupbased trajectory modeling to identify total sleep duration and PA trajectories from 2011 to 2020,and then employed logistic regression models to analyze their risk for CVD.Results We identified three sleep duration and PA trajectories.The risk of heart disease increased by 33%(OR=1.31,95%CI:1.12-1.53)for the short sleep duration trajectory(vs.moderate sleep duration trajectory),by 40%(OR=1.40,95%CI:1.06-1.84)for the high decreasing PA trajectory,and by 20%(OR=1.20,95%CI:1.01-1.42)for the low stable PA trajectory(vs.high stable PA trajectory),respectively.Similar results for stroke and CVD as the outcomes were also observed,but the higher risk of stroke in the high decreasing PA trajectory group was not statistically significant.The joint effects of sleep and PA showed lower risks of heart disease and stroke in trajectories with moderate or long sleep duration and high stable PA compared with short sleep duration and a low stable PA trajectory.Conclusions Short total sleep duration,high decreasing PA,and low stable PA trajectories could increase the risk of CVDs among middle-aged and older adults.Long-term moderate to long total sleep durations and high stable PA trajectories might be optimal for preventing CVDs.展开更多
Cardiovascular diseases(CVDs)are the leading cause of global mortality,with chronic inflammation playing an important role in their pathogenesis[1].Inflammatory bowel disease(IBD)has been associated with an increased ...Cardiovascular diseases(CVDs)are the leading cause of global mortality,with chronic inflammation playing an important role in their pathogenesis[1].Inflammatory bowel disease(IBD)has been associated with an increased risk of CVDs,including arrhythmias and atherosclerotic disease,potentially mediated by persistent systemic inflammation[2,3].展开更多
Background Ischemic heart disease(IHD) represents the most significant disease burden among all cardiovascular diseases(CVDs). The increasing prevalence of metabolic risks in the 21st century has a profound impact on ...Background Ischemic heart disease(IHD) represents the most significant disease burden among all cardiovascular diseases(CVDs). The increasing prevalence of metabolic risks in the 21st century has a profound impact on the disease burden associated with IHD. We analyzed the global, regional, and national burdens of IHD attributable to metabolic risks from 1990 to 2021.Methods The data were taken from Global Burden of Disease(GBD) study 2021. Deaths, disability-adjusted life years(DALYs),the average annual percent change(AAPC), age-standardized death rates per 100,000 persons(ASDR) and age-standardized rate per 100,000 persons(ASR) of DALYs ranging from 1990 to 2021, were extracted and stratified according to region, nationality, socio-demographic index(SDI), sex, and age. Additionally, the global future trends were predicted using Nordpred prediction model.Results Compared to 1990, in 2021, the number of death and DALYs from metabolic risk-attributed IHD increased globally by67.35% and 59.91%, respectively;whereas ASDR and ASR of DALYs showed a decreasing trend and the most severe impact was observed in male and elderly populations. In addition, the burden of disease showed an inverted V-shaped relationship with SDI from 1990 to 2021. AAPC showed a significant increase in developing countries and a decrease in developed countries. We also analyzed the effects of different risk factors including metabolic risk factors on IHD in different SDI regions and genders. The prediction of future disease burden showed that the number of death and DALYs will keep rising, while ASDR and ASR of DALYs will maintain a certain downward trend.Conclusions The results of this study highlighted the need for screening and intervention for metabolic risk factors in specific regions and populations, this should call for increased collaboration between developing and developed countries to reduce the burden of disease and improve the prognosis of patients with IHD.展开更多
文摘High-purity graphite is extensively utilized in the semiconductor industry.Enhancing its corrosion resistance is crucial for reducing the manufacturing costs of the third-generation semiconductors.In this study,a continuous and dense TaC coating was fabricated on the surface of graphite using CVD method.The corrosion resistance and mechanism of the coating were investigated in a high-temperature steam environment.This environment involved temperatures exceeding 2200 K and the erosion of the coating by Si-containing mixed steam flows.The results indicated that the corrosion in the affected areas was primarily due to chemical reactions,characterized by the formation of pores and micro-cracks,whereas failure areas were dominated by mechanical delamination,which led to macroscopic defects.Moreover,the mixed high-temperature steam corrosion of the TaC coating showed preferential selectivity,resulting in a stepped corrosion morphology at the crystalline level.The surface roughness of the samples significantly increased after corrosion,from 0.36 to 5.28μm,although the surface composition remained largely unchanged.The TaC coating provides a certain level of protection to the graphite substrate,enhancing the service life of graphite components and demonstrating promising application potential.
基金supported by the National Key R&D Program of China(No.2018YFA0108100)the National Natural Science Foundation of China(No.62104009).
文摘Cardiovascular diseases(CVDs)are one of the most serious diseases threatening human health in the world.Therefore,effective monitoring and treatment of CVDs are urgently needed.Compared with traditional rigid devices,nanomaterials based flexible devices open up new opportunities for further development beneficial from the unique properties of nanomaterials which contribute to excellent performance to better prevent and treat CVDs.This review summarizes recent advances of nanomaterials based flexible devices for the monitoring and treatment of CVDs.First,we review the outstanding characteristics of nanomaterials.Next,we introduce flexible devices based on nanomaterials for practical use in CVDs including in vivo,ex vivo,and in vitro methods.At last,we make a conclusion and discuss the further development needed for nanomaterials and monitoring and treatment devices to better care CVDs.
基金supported by the Guangdong Basic and Applied Basic Research Foundation(2021A1515011629)Construction of High-level University of Guangdong(G623330580and G621331128)Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme(2019)。
文摘Objective Elevated depressive symptoms are well-documented among geriatric adults with cardiovascular disease(CVD);however,few studies have accounted for long-term cumulative depressive symptom exposure.This study determined the relationship between cumulative depressive symptoms and CVD.Methods Individual participant data were obtained from the China Health and Retirement Longitudinal Study(CHARLS)and Health and Retirement Study(HRS).Eligible participants had access to assessment information on depressive symptoms and had no history of CVD at baseline.Long-term cumulative depressive symptoms were estimated by calculating the area under the curve based on the Center for Epidemiological Studies Depression Scale.Results Herein,8,861 participants from CHARLS(mean age:58.58 years;male:48.6%)and 7,284 from HRS(60.94 years;35.0%)were enrolled.The median follow-up period was 5 years for the CHARLS and10 years for the HRS.Compared with the first quartile of cumulative depressive symptoms,the HRs(95%CI)in the fourth quartile were 1.73(1.48,2.02)for predicting CVD(P<0.001),1.83(1.52,2.19)for heart disease(P<0.001),1.53(95%CI:1.17,1.99)for stroke(P=0.002)in CHARLS.For HRS,the HRs(95%CI)were 1.41(95%CI:1.27,1.57;P<0.001),1.42(95%CI:1.26,1.59;P<0.001),and 1.30(95%CI:1.06,1.58;P=0.010)respectively.Strong dose-response relationships were observed,with similar results for the two cohorts.Conclusion Long-term cumulative depressive symptoms were significantly associated with incident CVD in middle-aged and older adults,providing insights into controlling long-term depressive symptoms to improve this cohort's health.
基金supported by the Natural Science Foundation of Beijing Municipality(Grant No.7234401)the Postdoctoral Research Foundation of China(Grant No.88014Y0226)。
文摘Cardiovascular disease(CVD)is often accompanied by chronic kidney disease(CKD)and metabolic disorders such as obesity and type 2 diabetes^([1]).The coexistence of these conditions can lead to systemic dysfunction and substantially increase adverse cardiovascular outcomes.To describe this interplay,the American Heart Association(AHA)recently proposed the concept of cardiovascular-kidney-metabolic(CKM)syndrome^([1]).However,its risk-enhancing factors and underlying mechanisms remain unclear.
基金supported by the Deanship of Scientific Research(DSR),King Abdulaziz University,Jeddah,under grant No.IPP:533-611-2025DSR technical and financial support.
文摘In the effort to enhance cardiovascular diagnostics,deep learning-based heart sound classification presents a promising solution.This research introduces a novel preprocessing method:iterative k-means clustering combined with silhouette score analysis,aimed at downsampling.This approach ensures optimal cluster formation and improves data quality for deep learning models.The process involves applying k-means clustering to the dataset,calculating the average silhouette score for each cluster,and selecting the clusterwith the highest score.We evaluated this method using 10-fold cross-validation across various transfer learningmodels fromdifferent families and architectures.The evaluation was conducted on four datasets:a binary dataset,an augmented binary dataset,amulticlass dataset,and an augmentedmulticlass dataset.All datasets were derived from the Heart Wave heart sounds dataset,a novelmulticlass dataset introduced by our research group.To increase dataset sizes and improve model training,data augmentation was performed using heartbeat cycle segmentation.Our findings highlight the significant impact of the proposed preprocessing approach on the HeartWave datasets.Across all datasets,model performance improved notably with the application of our method.In augmented multiclass classification,the MobileNetV2 model showed an average weighted F1-score improvement of 27.10%.In binary classification,ResNet50 demonstrated an average accuracy improvement of 8.70%,reaching 92.40%compared to its baseline performance.These results underscore the effectiveness of clustering with silhouette score analysis as a preprocessing step,significantly enhancing model accuracy and robustness.They also emphasize the critical role of preprocessing in addressing class imbalance and advancing precision medicine in cardiovascular diagnostics.
基金supported by Peking University,the National Natural Science Foundation of China,the National Institute on Aging and the World Bank。
文摘Background It remains unclear whether sleep duration and physical activity(PA)trajectories in middle-aged and older adults are associated with different risks of cardiovascular diseases(CVDs).This study aimed to explore the trajectories of total sleep duration and PA among middle-aged and older Chinese adults and their impact on CVD risk.Methods This study was based on the China Health and Retirement Longitudinal Study.12009 adults aged 45 years and older from five waves were included.CVD events were measured by self-reports of heart disease and stroke.We first used groupbased trajectory modeling to identify total sleep duration and PA trajectories from 2011 to 2020,and then employed logistic regression models to analyze their risk for CVD.Results We identified three sleep duration and PA trajectories.The risk of heart disease increased by 33%(OR=1.31,95%CI:1.12-1.53)for the short sleep duration trajectory(vs.moderate sleep duration trajectory),by 40%(OR=1.40,95%CI:1.06-1.84)for the high decreasing PA trajectory,and by 20%(OR=1.20,95%CI:1.01-1.42)for the low stable PA trajectory(vs.high stable PA trajectory),respectively.Similar results for stroke and CVD as the outcomes were also observed,but the higher risk of stroke in the high decreasing PA trajectory group was not statistically significant.The joint effects of sleep and PA showed lower risks of heart disease and stroke in trajectories with moderate or long sleep duration and high stable PA compared with short sleep duration and a low stable PA trajectory.Conclusions Short total sleep duration,high decreasing PA,and low stable PA trajectories could increase the risk of CVDs among middle-aged and older adults.Long-term moderate to long total sleep durations and high stable PA trajectories might be optimal for preventing CVDs.
文摘Cardiovascular diseases(CVDs)are the leading cause of global mortality,with chronic inflammation playing an important role in their pathogenesis[1].Inflammatory bowel disease(IBD)has been associated with an increased risk of CVDs,including arrhythmias and atherosclerotic disease,potentially mediated by persistent systemic inflammation[2,3].
基金supported by the National Natural Science Foundation of China (82070055 and 82470054)the Project Program of National Clinical Research Center for Geriatric Disorders (Xiangya Hospital, Grant No.2023LNJJ18)。
文摘Background Ischemic heart disease(IHD) represents the most significant disease burden among all cardiovascular diseases(CVDs). The increasing prevalence of metabolic risks in the 21st century has a profound impact on the disease burden associated with IHD. We analyzed the global, regional, and national burdens of IHD attributable to metabolic risks from 1990 to 2021.Methods The data were taken from Global Burden of Disease(GBD) study 2021. Deaths, disability-adjusted life years(DALYs),the average annual percent change(AAPC), age-standardized death rates per 100,000 persons(ASDR) and age-standardized rate per 100,000 persons(ASR) of DALYs ranging from 1990 to 2021, were extracted and stratified according to region, nationality, socio-demographic index(SDI), sex, and age. Additionally, the global future trends were predicted using Nordpred prediction model.Results Compared to 1990, in 2021, the number of death and DALYs from metabolic risk-attributed IHD increased globally by67.35% and 59.91%, respectively;whereas ASDR and ASR of DALYs showed a decreasing trend and the most severe impact was observed in male and elderly populations. In addition, the burden of disease showed an inverted V-shaped relationship with SDI from 1990 to 2021. AAPC showed a significant increase in developing countries and a decrease in developed countries. We also analyzed the effects of different risk factors including metabolic risk factors on IHD in different SDI regions and genders. The prediction of future disease burden showed that the number of death and DALYs will keep rising, while ASDR and ASR of DALYs will maintain a certain downward trend.Conclusions The results of this study highlighted the need for screening and intervention for metabolic risk factors in specific regions and populations, this should call for increased collaboration between developing and developed countries to reduce the burden of disease and improve the prognosis of patients with IHD.
