Application of Deep Learning Technology in Glioma.

A common and most basic brain tumor is glioma that is exceptionally dangerous to health of various patients. A glioma segmentation, which is primarily magnetic resonance imaging (MRI) oriented, is considered as one of common tools developed for doctors. These doctors use this system to examine, analyse, and diagnose appearance of the glioma's outward for both patients, i.e., indoor and outdoor. In the literature, a widely utilized approach for the segmentation of glioma is the deep learning-oriented method. To cope with this issue, a segmentation of glioma approach, i.e., primarily on the convolution neural networks, is developed in this manuscript. A DM-DA-enabled cascading approach for the segmentation of glioma, which is 2DResUnet-enabled model, is reported to resolve the problem of spatial data acquisition of insufficient 3D specifically in the 2D full CNN along with the core issue of memory consumption of 3D full CNN. For gliomas segmentation at various stages, we have utilized multiscale fusion approach, attention, segmentation, and DenseBlock. Moreover, for reducing three dimensionalities of the Unet model, a sampling of fixed region is used along with multisequence data of the glioma image. Finally, the CNN model has the ability of producing a better segmentation of tumor preferably with minimum possible memory. The proposed model has used BraTS18 and BraTS17 benchmark data sets for fivefold cross-validation (local) and online evaluation preferably official, respectively. Evaluation results have verified that edema's Dice Score preferable average, enhancement, and core areas of the segmentation of the glioma with DM-DA-Unet perform exceptionally well on the validation set of BraTS17. Finally, average sensitivity was observed to be high as well, which is approximately closer to the best segmentation model and its effect on the validation set of BraTS1 and has segmented gliomas accurately.

DUSP1 alleviates cerebral ischaemia reperfusion injury via inactivating JNK-Mff pathways and repressing mitochondrial fission.

AIMS: Evidence continues to accrue implicating mitochondrial fission in the aetiology of cerebral ischaemia reperfusion (IR) injury. Dual-specificity phosphatase-1 (DUSP1) has been found to be associated with mitochondrial protection in several diseases. We aimed to explore the functional role of DUSP1 in cerebral IR injury, focusing on its influence on mitochondrial fission. MAIN METHODS: WT mice and DUSP1 transgenic mice were subjected to cerebral IR in vivo. In vitro, the hypoxia-reoxygenation model was used with N2a cells to mimic cerebral IR injury. Mitochondrial function was monitored via western blotting and immunofluorescence. Pathway blocker was used to establish the role of the JNK-Mff signaling pathway in mitochondrial fission. KEY FINDINGS: DUSP1 expression is downregulated after cerebral IR injury, and overexpression of DUSP1 could significantly reduce the infarction area and attenuate neuronal death exerted by cerebral IR injury. In vitro, we found that HR injury induced neuronal mitochondrial damage via augmenting mitochondrial fission. DUSP1 overexpression inhibited mitochondrial fission, thereby preserving mitochondrial homeostasis against HR injury. Furthermore, our data illustrated that DUSP1 regulated mitochondrial fission via JNK-Mff pathways. Increased DUSP1 prevented JNK activation, upregulated Yap expression, and suppressed Mff phosphorylation, reducing the formation of mitochondrial fragmentation. However, re-activation of JNK-Mff pathways abrogated the inhibitory effect of DUSP1 overexpression on mitochondrial fission. SIGNIFICANCE: This finding first uncovers that DUSP1 downregulation could be considered the primary reason for cerebral IR injury via evoking deleterious mitochondrial fission and activating harmful JNK-Mff pathways.

MAPK8 mediates resistance to temozolomide and apoptosis of glioblastoma cells through MAPK signaling pathway.

OBJECTIVE: In this study, we aimed to evaluate the expression and functions of MAPK8 in temozolomide (TMZ) -resistant glioblastoma cells as well as to explore the mechanism of TMZ resistance in glioblastoma cells. METHODS: Gene Expression Omnibus (GEO) database was used for identifying the differentially expressed genes (DEGs) in TMZ resistant samples. The functional partner genes of TMZ were screened out by Gene-drug interaction network (STITCH) and the glioblastoma-related genes were selected by gene search engine with evidence sentences (Digsee). The interactions among identified DEGs and glioblastoma-related genes were detected by Search Tool for the Retrieval of Interacting Genes (STRING). The dysregulated pathways were identified by Gene set enrichment analysis (GSEA). qRT-PCR was performed to detect the expression level of MAPK8 in glioblastoma cells. Western blot was used to detect the expressions of MAPK8 and MAPK signaling pathway-related proteins. MTT assay was utilized to measure the cell viability of TMZ sensitive and resistant cells. Colony formation assay was performed to detect the clone ability and flow cytometry (FCM) assay was applied to identify the apoptosis rate of TMZ resistant glioblastoma cells. RESULTS: MAPK8 was one of the DEGs and was up-regulated in TMZ resistant glioblastoma cells. The MAPK signaling pathway was activated in TMZ resistant glioblastoma cells under the condition of over-expression of MAPK8. The inhibition of MAPK8 restrained the colony formation, inducing apoptosis of TMZ resistant glioblastoma cells and suppressed the MAPK signaling pathway. CONCLUSION: MAPK8 promoted the resistance to TMZ, accelerated cell proliferation and inhibited the apoptosis of glioblastoma cells via activating MAPK signaling pathway.

Diagnostic and prognostic value of a disintegrin and metalloproteinase-17 in patients with gliomas.

A disintegrin and metalloproteinase-17 (ADAM17) has been shown to regulate numerous proteins involved in the cell cycle, as well as tumor oncogenes. The expression pattern of ADAM17 in glioma patients, however, is unclear. In the present study, the expression pattern and prognostic significance of ADAM17 was investigated in patients with glioma. A total of 60 glioma specimens and eight normal control samples were obtained. Immunohistochemical and western blot analyses were used to examine the expression of ADAM17. In addition, the association of ADAM17 expression with the clinicopathological parameters and the survival rates of the glioma patients was analyzed. The results showed that ADAM17 was upregulated in the high-grade glioma tissues compared with that in the low-grade and normal brain tissues of the glioma patients, and that the level increased with ascending World Health Organization tumor grade (P<0.05). Furthermore, the survival rate of the patients with ADAM17-positive tumors was lower compared with the patients with ADAM17-negative tumors. These results indicated that the overexpression of ADAM17 was correlated with a high tumor grade and a poor prognosis in patients with glioma. ADAM17 may have an important oncogenic function in glioma progression, and is a potential diagnostic and therapeutic target.