Evaluation of Neonatal Cerebral Circulation Under Hypoxic Ischemic Risk Factors Based on Quantitative Analysis of Cerebral Veins with Magnetic Resonance Susceptibility Weighted Imaging.

PURPOSE: To observe the regulation of cerebral circulation in vivo based on image segmentation algorithms for deep learning in medical imaging to automatically detect and quantify the neonatal deep medullary veins (DMVs) on susceptibility weighted imaging (SWI) images. To evaluate early cerebral circulation self-rescue for neonates undergoing risk of cerebral hypoxia-ischaemia in vivo. METHODS: SWI images and clinical data of 317 neonates with or without risk of cerebral hypoxia-ischaemia were analyzed. Quantitative parameters showing the number, width, and curvature of DMVs were obtained using an image segmentation algorithm. RESULTS: The number of DMVs was greater in males than in females (p < 0.01), and in term than in preterm infants (p = 0.001). The width of DMVs was greater in term than in preterm infants (p < 0.01), in low-risk than in high-risk group (p < 0.01), and in neonates without intracranial extracerebral haemorrhage (ICECH) than with ICECH (p < 0.05). The curvature of DMVs was greater in term than in preterm infants (P < 0.05). The width of both bilateral thalamic veins and anterior caudate nucleus veins were positively correlated with the number of DMVs; the width of bilateral thalamic veins was positively correlated with the width of DMVs. CONCLUSION: The DMVs quantification based on image segmentation algorithm may provide more detailed and stable quantitative information in neonate. SWI vein quantification may be an observable indicator for in vivo assessment of cerebral circulation self-regulation in neonatal hypoxic-ischemic brain injury.

Downregulation of USP33 inhibits Slit/Robo signaling pathway and is associated with poor patient survival of glioma.

BACKGROUND: Gliomas are the most common malignant tumors in the central nervous system originating from brain glial cells. Although characterized as highly invasive and highly malignant, few molecular targeting therapies have been developed. Ubiquitin Specific Protease 33 (USP33), a gene encoding a deubiquinating enzyme important in a variety of processes, including Slit-dependent cell migration and beta-2 adrenergic receptor signaling, participates in the development of several malignant tumors, however, its role in the development of glioma has not been evaluated. METHODS: Real-time quantitative PCR was performed to examine the expression of USP33 in glioma tissues and cell lines. Immunohistochemistry was performed to determine USP33 expressions in glioma tissue microarray. Transwell assay was performed to analyze the effect of USP33 on glioma cell line migration. The Kaplan-Meier method and log rank test were applied to evaluate the prognostic value of USP33 expression. Univariate and multivariate Cox proportional hazard regression models were used to identify the independent prognostic factors associated with overall survival (OS) or disease-free survival. RESULTS: The present study demonstrated that USP33 expression was significantly downregulated in glioma tissues. Lower expression of USP33 was associated with a poorer patient disease-free survival and overall survival. In vitro studies revealed that overexpression of USP33 significantly inhibited the migration ability of glioma cells. Mechanistically, USP33 inhibits glioma cell migration by regulating the function of Slit/Robo signaling pathway. CONCLUSIONS: Downregulation of USP33 is associated with poor patient survival of glioma. USP33 inhibits glioma cell migration by Slit/Robo signaling pathway. This mechanism may be applied for development of targeting therapy especially for the high-grade glioma.