目的初步探究肾虚证亚健康人群认知功能改变的神经影像学机制。方法对35例肾虚型亚健康受试者和35例健康对照进行重复性成套神经心理状态测验(Repeatable Battery for the Assessment of Neuropsychological Status,RBANS)及评估,并进...目的初步探究肾虚证亚健康人群认知功能改变的神经影像学机制。方法对35例肾虚型亚健康受试者和35例健康对照进行重复性成套神经心理状态测验(Repeatable Battery for the Assessment of Neuropsychological Status,RBANS)及评估,并进行静息态功能磁共振扫描。应用皮质分析方法计算两组被试脑区的低频震荡振幅(amplitude of low frequency fluctuations,ALFF)值和分数低频振幅(fractional ALFF,fALFF)值,并分析异常功能活动脑区与认知功能及临床症状之间的相关性。结果与健康受试者相比,肾虚型亚健康受试者的即刻记忆、注意编码及RBANS测验总分显著降低;并发现其左侧初级视觉皮质、左侧背侧枕叶皮质及右侧辅助运动皮质等脑区的ALFF/fALFF值异常改变。此外,左侧背侧枕叶皮质、右侧额叶眼动区ALFF值,左侧初级视觉皮质fALFF值与肾虚证积分均成正比。右侧额叶眼动区ALFF值,右侧辅助运动皮质fALFF值与测验总分成反比。结论肾虚型亚健康受试者的记忆与注意功能受损,左侧枕叶和右侧额叶等多个脑区神经活动的改变可能是肾虚证亚健康人群认知功能改变的潜在神经机制。展开更多
The variability characteristics of Guangdong daily power load from 2002 to 2004 and its connection to meteorological variables are analyzed with wavelet analysis and correlation analysis. Prediction equations are esta...The variability characteristics of Guangdong daily power load from 2002 to 2004 and its connection to meteorological variables are analyzed with wavelet analysis and correlation analysis. Prediction equations are established using optimization subset regression. The results show that a linear increasing trend is very significant and seasonal change is obvious. The power load exhibits significant quasi-weekly (5 – 7 days) oscillation, quasi-by-weekly (10 – 20 days) oscillation and intraseasonal (30 – 60 days) oscillation. These oscillations are caused by atmospheric low frequency oscillation and public holidays. The variation of Guangdong daily power load is obviously in decrease on Sundays, shaping like a funnel during Chinese New Year in particular. The minimum is found at the first and second day and the power load gradually increases to normal level after the third day during the long vacation of Labor Day and National Day. Guangdong power load is the most sensitive to temperature, which is the main affecting factor, as in other areas in China. The power load also has relationship with other meteorological elements to some extent during different seasons. The maximum of power load in summer, minimum during Chinese New Year and variation during Labor Day and National Day are well fitted and predicted using the equation established by optimization subset regression and accounting for the effect of workdays and holidays.展开更多
文摘目的初步探究肾虚证亚健康人群认知功能改变的神经影像学机制。方法对35例肾虚型亚健康受试者和35例健康对照进行重复性成套神经心理状态测验(Repeatable Battery for the Assessment of Neuropsychological Status,RBANS)及评估,并进行静息态功能磁共振扫描。应用皮质分析方法计算两组被试脑区的低频震荡振幅(amplitude of low frequency fluctuations,ALFF)值和分数低频振幅(fractional ALFF,fALFF)值,并分析异常功能活动脑区与认知功能及临床症状之间的相关性。结果与健康受试者相比,肾虚型亚健康受试者的即刻记忆、注意编码及RBANS测验总分显著降低;并发现其左侧初级视觉皮质、左侧背侧枕叶皮质及右侧辅助运动皮质等脑区的ALFF/fALFF值异常改变。此外,左侧背侧枕叶皮质、右侧额叶眼动区ALFF值,左侧初级视觉皮质fALFF值与肾虚证积分均成正比。右侧额叶眼动区ALFF值,右侧辅助运动皮质fALFF值与测验总分成反比。结论肾虚型亚健康受试者的记忆与注意功能受损,左侧枕叶和右侧额叶等多个脑区神经活动的改变可能是肾虚证亚健康人群认知功能改变的潜在神经机制。
基金Platform for Meteorological Prediction of Power Load in Guangdong Province
文摘The variability characteristics of Guangdong daily power load from 2002 to 2004 and its connection to meteorological variables are analyzed with wavelet analysis and correlation analysis. Prediction equations are established using optimization subset regression. The results show that a linear increasing trend is very significant and seasonal change is obvious. The power load exhibits significant quasi-weekly (5 – 7 days) oscillation, quasi-by-weekly (10 – 20 days) oscillation and intraseasonal (30 – 60 days) oscillation. These oscillations are caused by atmospheric low frequency oscillation and public holidays. The variation of Guangdong daily power load is obviously in decrease on Sundays, shaping like a funnel during Chinese New Year in particular. The minimum is found at the first and second day and the power load gradually increases to normal level after the third day during the long vacation of Labor Day and National Day. Guangdong power load is the most sensitive to temperature, which is the main affecting factor, as in other areas in China. The power load also has relationship with other meteorological elements to some extent during different seasons. The maximum of power load in summer, minimum during Chinese New Year and variation during Labor Day and National Day are well fitted and predicted using the equation established by optimization subset regression and accounting for the effect of workdays and holidays.
