AIM:To compare spontaneous brain regional activities between diabetic vitreous hemorrhage patients(DVHs)and healthy controls(HCs).METHODS:Thirty-two DVHs and 32 HCs were enrolled in this study.Baseline demographic and...AIM:To compare spontaneous brain regional activities between diabetic vitreous hemorrhage patients(DVHs)and healthy controls(HCs).METHODS:Thirty-two DVHs and 32 HCs were enrolled in this study.Baseline demographic and vision data were compared between groups using an independent sample t-test.Resting-state functional magnetic resonance imaging(rs-fMRI)was used in all participants.fMRI data was obtained and analyzed using MRIcro and SPM8 software.Fractional amplitude of low-frequency fluctuation(fALFF)technology was used to measure regional spontaneous brain activity,and sensitivity was tested using receiver operating characteristic curves(ROCs).The fALFF values were analyzed using REST software and two-sample t-tests were used to compare values between groups.Hospital anxiety and depression scale(HADS)score was assessed in DVHs and Pearson’s correlation was used to test relationships between mean fALFF value and both HADS score and duration of DVH.RESULTS:Except for the best-corrected visual acuity(BCVA)in both eyes,which showed a statistically significant difference(P<0.05),there were no statistically significant differences in the other indicators(P>0.05)between the HCs and DVHs group.Compared with controls,fALFF value was higher in DVH in cerebellum posterior lobe(CPL)and lower in right anterior cingulate cortex(ACC)and right medial orbitofrontal cortex(OFC).In DVH patients,mean fALFF value of CPL was positively correlated with HADS score and duration of diabetes.However,no such correlation was found,for right ACC or right medial OFC.DVH may lead to abnormal activities in certain brain regions related to visual control and mood.CONCLUSION:Visual impairment caused by DVH may lead to adjustment in regional visual brain activities and may be related to depression or reward system processing in some brain regions.展开更多
为优化不同降水年型下春小麦高产稳产和高效利用水氮资源的管理决策方案,利用2009-2012年内蒙古自治区额尔古纳市上库力农场试验站与拉布大林农场试验站春小麦(内麦19)的试验观测资料,确定APSIM-wheat模型中小麦生长发育关键参数;基于...为优化不同降水年型下春小麦高产稳产和高效利用水氮资源的管理决策方案,利用2009-2012年内蒙古自治区额尔古纳市上库力农场试验站与拉布大林农场试验站春小麦(内麦19)的试验观测资料,确定APSIM-wheat模型中小麦生长发育关键参数;基于校准后的APSIM-wheat模型模拟分析1967-2017年雨养条件下春小麦生长发育过程,并依据降水量划分了3种降水年型(干旱、平水和湿润年型),根据土壤水分亏缺指数(soil water deficit on photosynthesis,SWD_(ef))确定最优水分管理时期;设计8个灌溉量梯度(15、30、45、60、90、120、150和180 mm)和13个施N量梯度(30、45、60、75、90、105、120、150、180、210、240、270和300 kg·hm^(-2))情景模式,结合水氮管理决策的遴选关键指标[水分利用效率(water use efficiency,WUE)、氮肥利用效率(nitrogen use efficiency,NUE)和产量],探究不同气候年型下最优春小麦水氮管理模式。结果表明:(1)校准后的APSIM-wheat模型春小麦发育期模块(出苗期、抽穗期和成熟期)模拟值与观测值的均方根误差(root mean square error,RMSE)在1.17~3.64 d范围内,归一化均方根误差(normalized root mean square error,NRMSE)在0.82%~1.90%范围内;产量模块模拟值与观测值的RMSE为371.50 kg·hm^(-2),NRMSE为8.54%,说明APSIM-wheat模型可以较好地反映不同降水年型下小麦的动态生长发育过程。(2)雨养条件下春小麦分蘖期—拔节期、拔节期—抽穗期和抽穗期—开花期的SWD_(ef)较低,且在生育期内仅灌溉一次的前提下,拔节期灌溉可以减轻干旱胁迫并显著提高产量。(3)干旱、平水和湿润年型春小麦拔节期最优水氮管理模式分别为灌溉量60 mm和施氮量105 kg·hm^(-2)、灌溉量60 mm和施氮量120 kg·hm^(-2)、灌溉量30 mm和施氮量150 kg·hm^(-2),其产量分别为4810.96±551.43、5378.06±768.86和6421.33±454.09 kg·hm^(-2)。展开更多
基金Supported by National Natural Science Foundation of China(No.82160195,No.82460203)Zhejiang Traditional Chinese Medicine Science and Technology Plan Project(No.2025ZR172).
文摘AIM:To compare spontaneous brain regional activities between diabetic vitreous hemorrhage patients(DVHs)and healthy controls(HCs).METHODS:Thirty-two DVHs and 32 HCs were enrolled in this study.Baseline demographic and vision data were compared between groups using an independent sample t-test.Resting-state functional magnetic resonance imaging(rs-fMRI)was used in all participants.fMRI data was obtained and analyzed using MRIcro and SPM8 software.Fractional amplitude of low-frequency fluctuation(fALFF)technology was used to measure regional spontaneous brain activity,and sensitivity was tested using receiver operating characteristic curves(ROCs).The fALFF values were analyzed using REST software and two-sample t-tests were used to compare values between groups.Hospital anxiety and depression scale(HADS)score was assessed in DVHs and Pearson’s correlation was used to test relationships between mean fALFF value and both HADS score and duration of DVH.RESULTS:Except for the best-corrected visual acuity(BCVA)in both eyes,which showed a statistically significant difference(P<0.05),there were no statistically significant differences in the other indicators(P>0.05)between the HCs and DVHs group.Compared with controls,fALFF value was higher in DVH in cerebellum posterior lobe(CPL)and lower in right anterior cingulate cortex(ACC)and right medial orbitofrontal cortex(OFC).In DVH patients,mean fALFF value of CPL was positively correlated with HADS score and duration of diabetes.However,no such correlation was found,for right ACC or right medial OFC.DVH may lead to abnormal activities in certain brain regions related to visual control and mood.CONCLUSION:Visual impairment caused by DVH may lead to adjustment in regional visual brain activities and may be related to depression or reward system processing in some brain regions.
文摘为优化不同降水年型下春小麦高产稳产和高效利用水氮资源的管理决策方案,利用2009-2012年内蒙古自治区额尔古纳市上库力农场试验站与拉布大林农场试验站春小麦(内麦19)的试验观测资料,确定APSIM-wheat模型中小麦生长发育关键参数;基于校准后的APSIM-wheat模型模拟分析1967-2017年雨养条件下春小麦生长发育过程,并依据降水量划分了3种降水年型(干旱、平水和湿润年型),根据土壤水分亏缺指数(soil water deficit on photosynthesis,SWD_(ef))确定最优水分管理时期;设计8个灌溉量梯度(15、30、45、60、90、120、150和180 mm)和13个施N量梯度(30、45、60、75、90、105、120、150、180、210、240、270和300 kg·hm^(-2))情景模式,结合水氮管理决策的遴选关键指标[水分利用效率(water use efficiency,WUE)、氮肥利用效率(nitrogen use efficiency,NUE)和产量],探究不同气候年型下最优春小麦水氮管理模式。结果表明:(1)校准后的APSIM-wheat模型春小麦发育期模块(出苗期、抽穗期和成熟期)模拟值与观测值的均方根误差(root mean square error,RMSE)在1.17~3.64 d范围内,归一化均方根误差(normalized root mean square error,NRMSE)在0.82%~1.90%范围内;产量模块模拟值与观测值的RMSE为371.50 kg·hm^(-2),NRMSE为8.54%,说明APSIM-wheat模型可以较好地反映不同降水年型下小麦的动态生长发育过程。(2)雨养条件下春小麦分蘖期—拔节期、拔节期—抽穗期和抽穗期—开花期的SWD_(ef)较低,且在生育期内仅灌溉一次的前提下,拔节期灌溉可以减轻干旱胁迫并显著提高产量。(3)干旱、平水和湿润年型春小麦拔节期最优水氮管理模式分别为灌溉量60 mm和施氮量105 kg·hm^(-2)、灌溉量60 mm和施氮量120 kg·hm^(-2)、灌溉量30 mm和施氮量150 kg·hm^(-2),其产量分别为4810.96±551.43、5378.06±768.86和6421.33±454.09 kg·hm^(-2)。
