Background As the population in China rapidly ages,the prevalence of mild cognitive impairment(MCI)is increasing considerably.However,the causes of MCI vary.The continued lack of understanding of the various subtypes ...Background As the population in China rapidly ages,the prevalence of mild cognitive impairment(MCI)is increasing considerably.However,the causes of MCI vary.The continued lack of understanding of the various subtypes of MCI impedes the implementation of effective measures to reduce the risk of advancing to more severe cognitive diseases.Aims To estimate the prevalence and incidence rates of two MCI subtypes—amnestic MCI(aMCI)and vascular cognitive impairment without dementia(VCIND)—and to determine modifiable factors for them among older individuals in a multiregional Chinese cohort.Method This 1-year longitudinal study surveyed a random sample of participants aged≥60 years from a large,community-dwelling cohort in China.Baseline lifestyle data were self-reported,while vascular and comorbid conditions were obtained from medical records and physical examinations.In total,3514 and 2051 individuals completed the baseline and 1-year follow-up assessments,respectively.Logistic and linear regression analyses were used to identify the modifiable factors for MCI subtypes and predictors of cognitive decline,respectively.Results Among our participants,aMCI and VCIND demonstrated prevalence of 14.83%and 2.71%,respectively,and annual incidence(per 1000 person-years)of 69.6 and 10.6,respectively.The risk factor for aMCI was age,whereas its protective factors were high education level,tea consumption and physical activity.Moreover,VCIND risk factors were age,hypertension and depression.The presence of endocrine disease,cerebral trauma or hypertension was associated with a faster decline in cognition over 1 year.Conclusions MCI is a serious health problem in China that will only worsen as the population ages if no widespread interventions are implemented.Preventive strategies that promote brain activity and support healthy lifestyle choices are required.We identified modifiable factors for MCI in older individuals.The easy-to-adopt solutions such as tea consumption and physical activity can aid in preventing MCI.展开更多
Single-pixel imaging(SPI)is a prominent scattering media imaging technique that allows image transmission via one-dimensional detection under structured illumination,with applications spanning from long-range imaging ...Single-pixel imaging(SPI)is a prominent scattering media imaging technique that allows image transmission via one-dimensional detection under structured illumination,with applications spanning from long-range imaging to microscopy.Recent advancements leveraging deep learning(DL)have significantly improved SPI performance,especially at low compression ratios.However,most DL-based SPI methods proposed so far rely heavily on extensive labeled datasets for supervised training,which are often impractical in real-world scenarios.Here,we propose an unsupervised learningenabled label-free SPI method for resilient information transmission through unknown dynamic scattering media.Additionally,we introduce a physics-informed autoencoder framework to optimize encoding schemes,further enhancing image quality at low compression ratios.Simulation and experimental results demonstrate that high-efficiency data transmission with structural similarity exceeding 0.9 is achieved through challenging turbulent channels.Moreover,experiments demonstrate that in a 5 m underwater dynamic turbulent channel,USAF target imaging quality surpasses traditional methods by over 13 dB.The compressive encoded transmission of 720×720 resolution video exceeding 30 seconds with great fidelity is also successfully demonstrated.These preliminary results suggest that our proposed method opens up a new paradigm for resilient information transmission through unknown dynamic scattering media and holds potential for broader applications within many other scattering media imaging technologies.展开更多
基金supported by the Major Project of Wuxi Municipal Health Commission[grant number:Z202406]the Jiangsu Commission of Health Program[grant number:M2024010]+3 种基金the National Key Research and Development Program[grant number:2022YFC3600600]the China Ministry of Science and Technology grants[grant number:2009BAI77B03]the Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support[grant number:20172029]the Innovative Research Team of High-level Local Universities in Shanghai[grant number:ZDCX20211201].
文摘Background As the population in China rapidly ages,the prevalence of mild cognitive impairment(MCI)is increasing considerably.However,the causes of MCI vary.The continued lack of understanding of the various subtypes of MCI impedes the implementation of effective measures to reduce the risk of advancing to more severe cognitive diseases.Aims To estimate the prevalence and incidence rates of two MCI subtypes—amnestic MCI(aMCI)and vascular cognitive impairment without dementia(VCIND)—and to determine modifiable factors for them among older individuals in a multiregional Chinese cohort.Method This 1-year longitudinal study surveyed a random sample of participants aged≥60 years from a large,community-dwelling cohort in China.Baseline lifestyle data were self-reported,while vascular and comorbid conditions were obtained from medical records and physical examinations.In total,3514 and 2051 individuals completed the baseline and 1-year follow-up assessments,respectively.Logistic and linear regression analyses were used to identify the modifiable factors for MCI subtypes and predictors of cognitive decline,respectively.Results Among our participants,aMCI and VCIND demonstrated prevalence of 14.83%and 2.71%,respectively,and annual incidence(per 1000 person-years)of 69.6 and 10.6,respectively.The risk factor for aMCI was age,whereas its protective factors were high education level,tea consumption and physical activity.Moreover,VCIND risk factors were age,hypertension and depression.The presence of endocrine disease,cerebral trauma or hypertension was associated with a faster decline in cognition over 1 year.Conclusions MCI is a serious health problem in China that will only worsen as the population ages if no widespread interventions are implemented.Preventive strategies that promote brain activity and support healthy lifestyle choices are required.We identified modifiable factors for MCI in older individuals.The easy-to-adopt solutions such as tea consumption and physical activity can aid in preventing MCI.
基金supported by the Natural Science Foundation of China Project(No.62525102).
文摘Single-pixel imaging(SPI)is a prominent scattering media imaging technique that allows image transmission via one-dimensional detection under structured illumination,with applications spanning from long-range imaging to microscopy.Recent advancements leveraging deep learning(DL)have significantly improved SPI performance,especially at low compression ratios.However,most DL-based SPI methods proposed so far rely heavily on extensive labeled datasets for supervised training,which are often impractical in real-world scenarios.Here,we propose an unsupervised learningenabled label-free SPI method for resilient information transmission through unknown dynamic scattering media.Additionally,we introduce a physics-informed autoencoder framework to optimize encoding schemes,further enhancing image quality at low compression ratios.Simulation and experimental results demonstrate that high-efficiency data transmission with structural similarity exceeding 0.9 is achieved through challenging turbulent channels.Moreover,experiments demonstrate that in a 5 m underwater dynamic turbulent channel,USAF target imaging quality surpasses traditional methods by over 13 dB.The compressive encoded transmission of 720×720 resolution video exceeding 30 seconds with great fidelity is also successfully demonstrated.These preliminary results suggest that our proposed method opens up a new paradigm for resilient information transmission through unknown dynamic scattering media and holds potential for broader applications within many other scattering media imaging technologies.
