Objective:To investigate the changes in gray matter volume (GMV) and abnormalities in structural covariant network (SCN) patterns in patients with chronic pontine infarction (PI).Methods:Patients with unilateral chronic PI (case group) with the first onset admitted to the First Affiliated Hospital of Zhengzhou University and Tianjin Medical University General Hospital from October 2014 to June 2021 were prospectively included. At the same time, healthy subjects matched with age, gender and education years (normal control group) were included. High-resolution three-dimensional T 1 structural MRI images and behavioral scores of the subjects were collected. The voxel-based morphometry and two-sample t test were used to explore the differences in GMV between the groups. Using GMV differential brain regions as seed points, SCN was constructed to explore the abnormality of structural covariant patterns in patients with PI. Spearman rank correlation analysis was used to analyze the correlation between GMV in differential brain regions and behavioral scores. Results:A total of 60 patients with PI were enrolled, including 33 left PI and 27 right PI, while 34 healthy controls were also enrolled. Compared with the normal control group, the GMV in bilateral posterior cerebellar lobe decreased significantly in the left PI group, and the GMV in left anterior and posterior cerebellar lobes and the right posterior cerebellar lobe decreased significantly in the right PI group (Gaussian random field correction with voxel level P<0.001 and cluster level P<0.05, cluster voxel >20), and there was a significant correlation between GMV values in the left anterior and posterior cerebellar lobes and the right posterior cerebellar lobe and the motor function score ( P<0.05). In addition, compared with the normal control group, the right PI group had broader covariate brain regions and a significant increase in the number of structural connections between covariate brain regions (family-wise error correction with voxel level P<0.05, cluster voxel >20). Conclusions:The GMV in bilateral posterior cerebellar lobe decreases significantly in patients with chronic PI, and were secondary to broader covariate brain regions and structural connections. This may be the neural mechanism of impaired behavioral function in patients with PI.

Objective To Analyze the expression profiles of LncRNAs and mRNAs in ovarian epithelial cancer cell lines by gene mi-croarray, and then provide experimental evidences for investigating the function of LncRNAs associated with ovarian cancer. Methods The differentially expressed LncRNAs and mRNAs in ovarian epithelial cancer cell lines, such as A2780, HO8910 and SKOV3, and ovarian epithelial cell line HOSEpiC were analyzed by gene microarray. The differentially expressed mRNAs were further performed the KEGG pathway enrichment analysis. The expression levels of six candidate LncRNAs, which had significant difference between the o-varian epithelial cancer cell line and the ovarian epithelial cell line, were further verified by qRT-PCR. Results There were 227 up-regulated LncRNAs and 483 down-regulated LncRNAs in A2780, HO8910 and SKOV3 cell lines. The differentially expressed mRNAs in A2780, HO8910 and SKOV3 cell lines were mainly enriched in the tumor-related pathways such as PI3K-AKT, mTOR and TNF-α( P<0.05) . The expression levels of PTPRG-AS1, CCNT2-AS1, XLOC 009869 and LINC01138 in ovarian epithelial cancer A2780, SKOV3 and OVCR3 cell lines were up-regulated (P<0.05), while those of RP11-252P19.2 and RP11-744I24.2 in ovarian epithelial cancer A2780, SKOV3, OVCR3 and 3AO cell lines were down-regulated ( P<0.05) . Conclusion The differentially expressed LncR-NAs and mRNAs in ovarian epithelial cancer cell lines may be obtained by gene microarray, and the differentially expressed mRNAs are associated with the tumor-related pathways such as PI3K-AKT, mTOR and TNF-α, which may provide new targets for the diagnosis and treatment of ovarian cancer.