Purpose Myelin and lymphocyte protein (MAL) plays an essential role in esophageal cancer, classic Hodgkin’s lymphoma and breast cancer. However, its role in uterine corpus endometrial carcinoma (UCEC) has not been explored. Therefore, the current study sought to explore the role of MAL in UCEC. Patients and Methods Differentially expressed genes (DEGs) were identified by using Limma package in R based on TCGA-UCEC data. Kaplan–Meier plotter analysis was performed to explore the prognostic value of MAL. Function enrichment analyses were performed using GSVA. Further, roles of MAL in UCEC were validated using clinical cohort, which included 120 tumor and adjacent tissues. qRT-PCR and immunohistochemistry analyze the samples. Chi-square tests were performed to explore the associations between MAL expressions and clinicopathological features. Results The findings showed that overexpression level of MAL in tumor was correlated with worse survival (p = 0.000424). MAL exhibited predictive power for survival time of UCEC patients (3 years: AUC = 0.635; 5 years: AUC = 0.635). Notably, high expression level of MAL was correlated with advanced stage of UCEC. MAL overexpression was significant in UCEC with microsatellite instability (MSI). Enrichment analysis showed that MAL was enriched mainly in MYC targets, epithelial mesenchymal transition and KRAS signaling. Furthermore, MAL was associated with infiltration of immune cells in the tumor micro-environment and immune checkpoint. Analysis showed a positive association between MAL and T cell (CD4+ memory resting). Correlation analysis showed that MAL was significantly positively correlated with several immune checkpoint, including CD274 (R = 0.3389, p = 0.0081), LAG3 (R = 0.2913, p = 0.0229), PDCD1LG2 (R = 0.5345, p < 0.0001). The prognosis value of MAL was confirmed through the experiment. Conclusion The findings of the current study indicated that MAL is an effective prognostic biomarker and potential therapeutic target for UCEC patients. These results indicated that MAL functions as a diagnosis and therapeutic marker in UCEC treatment.

In this paper, an interface reconstruction technology similar with SLIC method on structured grid is developed for the unstructured grid. For a cell containing the interface, a straight line segment parallel with one edge of the triangle cell is set to the interface according to the VOF function values in the three neighbor cells and volume flux of the particular fluid is determined by the geometry relation between the interface line and volume flux on each edge. Finally, four classical cases are used to test this unstructured SLIC-VOF interface reconstruction method including advection test of a right-angled triangle and a hollowed circle, Zalesak slotted disk rotation test as a test of scalar advection, and single-vortex shearing flow test, which are effective to test interface capturing method. It was found that the interface transported back by the reversed velocity field is comparative with SLIC-VOF on structure grid. Through the comparison between two triangle grids generated by Delaunay Triangulation Method and Bubble Packing Method, it is found that the grid quality has great effect on the proposed unstructured SLIC-VOF method. More regular triangle cells will lead to better interface capturing result.

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