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Objective:To investigate the relationship between brain derived neurotrophic factor (BDNF) gene polymorphism and the change of grey matter volume (GMV) and fractional amplitude of low-frequency fluctuation (fALFF) in cerebral small vessel disease (CSVD) patients with subcortical ischemic depression (SID).Methods:Eighty-seven CSVD patients in the First Affiliated Hospital of Anhui Medical University were enrolled from July 2017 to November 2020 and divided into CSVD-SID group [Geriatric Depression Scale (GDS) score>10] and CSVD-non - depression group (CSVD-ND group, GDS score≤10) according to GDS. Both GMV and fALFF were calculated based on structural and functional magnetic resonance imaging data, and the interactions between SID diagnosis and BDNF gene on brain function and structure alteration were explored.Results:GMV was significantly increased in the posterior default network (pDMN; such as posterior cingulate gyrus/precuneus and middle temporal gyrus) in the CSVD-SID group compared with the CSVD-ND group. On GMV property, significant interactions between BDNF gene and SID were found in the cuneus ( F=25.50, P<0.001), precuneus lobe ( F=13.61, P<0.001) and cerebellum ( F=17.23, P<0.001). In the aspect of fALFF, the brain functional activity in the superior frontal gyrus was significantly increased in the CSVD-SID group compared with that in the CSVD-ND group (0.363±0.648 vs -0.427±0.514,cluster size=48 voxels, t=5.63, P<0.001). But there was no significant interaction between diagnosis and BDNF genotype on brain function. Conclusions:Both the GMV and fALFF were increased in CSVD-SID, mainly located in the pDMN and frontal lobe. Significant interaction was found between CSVD-SID and BDNF genotype on GMV.
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Objective:To investigate the impact of altering brain gray matter volume (GMV) on cognition and gait disorder in patients with amnestic mild cognitive impairment (aMCI).Methods:Thirty-six patients with aMCI, who admitted to the First Affiliated Hospital of Anhui Medical University from July 2018 to August 2020, were collected, and 33 normal controls (NC) matched with age, sex and education level were included in the same period. The neuropsychological assessment was done in all the subjects using Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment scale (MoCA), Cambridge Cognitive Examination-Chinese version (CAMCOG-C), Geriatric Depression Scale (GDS) and Activities of Daily Living scale (ADL). The timed up and go test (TUG), dual task of timed up and go test (D-TUG) and Berg Balance Scale (BBS) were used in the subjects for assessment. The parameters such as stride length, gait speed, gait frequency were collected by intelligent device for energy expenditure and activity. All the subjects received 3.0 T magnetic resonance imaging scan to obtain high-resolution T 1 structural images. Voxel-based morphometry (VBM) was used to compare the difference of GMV between aMCI patients and NC. Partial correlation analysis was performed among altering GMV in the regions of interest (ROI), cognitive score and gait parameters, respectively. Linear regression analysis was used between whole brain GMV and gait parameters. Results:The scores of MMSE, MoCA, CAMCOG-C and the subitems of CAMCOG-C in aMCI group were significantly lower than those in NC group ( P<0.05). In aMCI patients, both the test time of TUG and D-TUG increased, gait speed slowed down, stride length shortened, and stride frequency and BBS score decreased ( P<0.05).VBM analysis showed that the whole brain GMV in aMCI patients was obviously lower than that of NC. In the aMCI group, GMV in ROI1 (right hippocampus, right parahippocampal gyrus, right amygdala and right fusiform gyrus), ROI2 (right middle temporal gyrus), ROI3 (right angular gyrus), ROI4 (right occipital lobe), ROI5 (bilateral orbital frontal lobe), ROI6 (left middle frontal gyrus and rectus gyrus), ROI7 (left fusiform gyrus and left parahippocampal gyrus) was significantly decreased compared with the NC group [Gaussian random field (GRF) correction, two-tailed test, voxel level P<0.001, cluster level P<0.05). In the aMCI group, GMV in ROI1 was positively correlated with orientation ( r=0.437, P=0.012), memory ( r=0.360, P=0.043), execution ( r=0.414, P=0.019), and negatively correlated with ADL score ( r=-0.529, P=0.002). GMV in ROI2 was negatively correlated with ADL score ( r=-0.400, P=0.023). GMV in ROI4 and in ROI5 was positively correlated with the calculation ( r=0.370, P=0.037) and execution ( r=0.360, P=0.043), respectively. GMV in ROI6 was positively correlated with MMSE score ( r=0.357, P=0.045), CAMCOG-C total score ( r=0.503, P=0.003) and calculation ( r=0.395, P=0.025), and negatively correlated with ADL score ( r=-0.387, P=0.028). GMV in ROI5 was positively correlated with gait speed ( r=0.391, P=0.027). In the aMCI group, CAMCOG-C total score was negatively correlated with D-TUG results ( r=-0.387, P=0.035), executive function was negatively correlated with TUG results ( r=-0.450, P=0.013) and D-TUG results ( r=-0.553, P=0.002), and positively correlated with gait speed ( r=0.379, P=0.039). Attention was positively correlated with gait speed ( r=0.590, P=0.001), and computing was positively correlated with gait speed ( r=0.371, P=0.044). The linear regression of whole brain GMV and gait parameters showed negative correlation between the GMV of left occipital lobe and TUG results in the aMCI group. The GMV of bilateral prefrontal cortex, right occipital lobe and surrounding cortex was positively correlated with gait speed (GRF correction, two-tailed test, voxel level P<0.001, cluster level P<0.05). Conclusions:Patients with aMCI presented with gray matter atrophy, cognition impairment, and gait disorders. The cognition impairment was closely related to the atrophy of medial temporal lobe. Gait disorders were not only associated with cognition impairment but also with gray matter volume in the prefrontal lobe, occipital lobe and its surrounding cortex, and anterior central gyrus.
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Objective To explore the expression and relationship of PTEN and mTOR in the development of cholangiocarcinoma,determine the effect of the PI3K/PTEN/AKT/mTOR signal transduction on the(development) of cholangiocarcinoma.Methods The expression of mTOR and PTEN in the cholangiocarcinoma was detected by the immunohistochemistry and RT-PCR method.Results Compared to normal tissues,the(expression) of mTOR gene in cholangiocarcinoma significantly increased,but the expression of PTEN gene(decreased).There was a negative correlation between mTOR gene and PTEN gene expression in(cholangiocarcinoma). Conclusions The expression of mTOR gene in cholangiocarcinoma was increased and the expression of PTEN was decreased.It suggested that the mTOR gene and PTEN gene could play an important role in the process of development of cholangiocarcinoma.