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您的检索式：作者名="Aonan Zhao"
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| 1 | Increased prediction value of biomarker combinations for the conversion of mild cognitive impairment to Alzheimer's dementia显示文摘Background:Progression of mild cognitive impairment(MCI)to Alzheimer's disease(AD)dementia can be predicted by clinical features and a combination of biomarkers may increase the predictive power.In the present study,we investigated whether the combination of olfactory function and plasma neuronal-derived exosome(NDE)Aβ1-42 can best predict progression to AD dementia.Methods:Eighty-seven MCI patients were enrolled and received cognitive assessment at 2-year and 3-year follow-up to reevaluate cognition.In the meanwhile,80 healthy controls and 88 AD dementia patients were enrolled at baseline as well to evaluate the diagnose value in cross-section.Olfactory function was evaluated with the sniffin sticks(SS-16)and Aβ142 levels in NDES were determined by ELISA.Logistic regression was performed to evaluate the risk factors for cognitive decline in MCI at 2-year and 3-year revisits.Results:In the cross cohort,lower SS-16 scores and higher AB142 levels in NDES were found in MCI and AD dementia compared to healthy controls.For the longitudinal set,8 MCI individuals developed AD dementia within 2 years,and 16 MCI individuals developed AD dementia within 3 years.The two-parameter combination of SS-16 scores and Aβ1-42 level in NDEs showed better prediction in the conversion of MCI to AD dementia at 2-year and 3-year revisits.Moreover,after a 3-year follow-up,SS-16 scores also significantly predicted the conversion to AD dementia,where lower scores were associated with a 10-fold increased risk of developing AD dementia(p=0.006).Similarly,higher AB1-42 levels in NDES in patients with MCI increased the risk of developing AD dementia by 8.5-fold(p=0.002).Conclusion:A combination of two biomarkers NDE AB1-42 and SS-16 predicted the conversion of MCI to AD dementia more accurately.These findings have critical implications for understanding the pathophysiology of AD dementia and for developing preventative treatments for cognitive decline. | Aonan Zhao Yuanyuan Li Yi Yan Yinghui Qiu Binyin Li Wei Xu Ying Wang Jun Liu Yulei Deng | 2020 | Translational Neurodegeneration2020，9，3： | 2 |
| 2 | A study on carbon emission calculation in operation stage of residential buildings based on micro electricity usage behavior:Three case studies in China显示文摘Along with the improvement of social productivity and living standard,residential buildings generate a growing portion of carbon emissions,especially during the operation stage.However,energy use behaviors are usually ignored in carbon emission calculation.This study focuses on calculating carbon emissions during the operation stage for residential buildings based on the characteristics of energy use behaviors in different regions.Firstly,we investigated energy use behaviors in dwellings across three cities in China:Xi'an,Shanghai and Fuzhou.Then,we established calibrated carbon emission models and optimization models with different green building measures for residential buildings.The results of this research reveal a significant disparity between the energy usage habits of residents in different climate regions.The carbon emissions of residential electricity bills in Xi'an,Shanghai and Fuzhou are 13.6 kgCO_(2)/(m^(2)·a)(excluding central heating),29.3 kgCO_(2)/(m^(2)·a)and 17.2 kgCO_(2)/(m^(2)·a),respectively.Equipment carbon emissions account for 32.2%-64.1% of the total.In comparison to the model based on internal standard setting,the accuracy of the models using actual internal has improved by 25.9%-37.4%.The three-star green building methods have the highest carbon reduction rate among different star buildings,the emission reduction rates are around 30%.This study's findings are useful for carbon emission calculation and green building design of residential buildings in the future. | Menghan Niu Ying Ji Miao Zhao Jiefan Gu Aonan Li | 2024 | Building Simulation2024，17，1： | 0 |
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