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
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
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
面向原子力显微镜(atomic force microscope,AFM)探针的应用需求,提出一种基于硅尖的垂直取向碳纳米管(carbon nanotubes,CNTs)制备方法。首先,通过优化掩膜设计和KOH湿法腐蚀工艺,制备了高度约为6μm的硅尖阵列;然后,采用图案化催化剂...面向原子力显微镜(atomic force microscope,AFM)探针的应用需求,提出一种基于硅尖的垂直取向碳纳米管(carbon nanotubes,CNTs)制备方法。首先,通过优化掩膜设计和KOH湿法腐蚀工艺,制备了高度约为6μm的硅尖阵列;然后,采用图案化催化剂定位投放技术,在硅尖顶端实现了铁蛋白分子的选择性附着;最后,通过热化学气相沉积(chemical vapor deposition,CVD)法,在优化的工艺参数下,成功在硅尖上生长出直径约16~20 nm、垂直取向的单根碳纳米管。扫描电子显微镜(scanning electron microscopy,SEM)和透射电子显微镜(transmission electron microscopy,TEM)表征结果显示,所制备的CNTs结构均匀且结晶度良好;拉曼光谱分析进一步证实其具有高度石墨化特性。研究结果可为高性能AFM探针的制备提供可行的技术方案,具有重要的应用价值。展开更多
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 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.
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.
文摘面向原子力显微镜(atomic force microscope,AFM)探针的应用需求,提出一种基于硅尖的垂直取向碳纳米管(carbon nanotubes,CNTs)制备方法。首先,通过优化掩膜设计和KOH湿法腐蚀工艺,制备了高度约为6μm的硅尖阵列;然后,采用图案化催化剂定位投放技术,在硅尖顶端实现了铁蛋白分子的选择性附着;最后,通过热化学气相沉积(chemical vapor deposition,CVD)法,在优化的工艺参数下,成功在硅尖上生长出直径约16~20 nm、垂直取向的单根碳纳米管。扫描电子显微镜(scanning electron microscopy,SEM)和透射电子显微镜(transmission electron microscopy,TEM)表征结果显示,所制备的CNTs结构均匀且结晶度良好;拉曼光谱分析进一步证实其具有高度石墨化特性。研究结果可为高性能AFM探针的制备提供可行的技术方案,具有重要的应用价值。
