BackgroundIn recent years, long non-coding RNAs (lncRNAs) are of great importance in development of different types of tumors, while the function of lncRNA ZFAS1 is rarely discussed in esophageal squamous cell carcinoma (ESCC). Therefore, we performed this study to explore the expression of exosomal lncRNA ZFAS1 and its molecular mechanism on ESCC progression.MethodsExpression of ZFAS1 and miR-124 in ESCC tissues was detected. LncRNA ZFAS1 was silenced to detect its function in the biological functions of ESCC cells. A stable donor and recipient culture model was established. Eca109 cells transfected with overexpressed and low expressed ZFAS1 plasmid and miR-124 inhibitor labeled by Cy3 were the donor cells, and then co-cultured with recipient cells to observe the transmission of Cy3-ZFAS1 between donor cells and recipient cells. The changes of cell proliferation, apoptosis, invasion, and migration in recipient cells were detected. The in vivo experiment was conducted for verifying the in vitro results.ResultsLncRNA ZFAS1 was upregulated and miR-124 was down-regulated in ESCC tissues. Silencing of ZFAS1 contributed to suppressed proliferation, migration, invasion and tumor growth in vitro and induced apoptosis of ESCC cells. LncRNA ZFAS1 was considered to be a competing endogenous RNA to regulate miR-124, thereby elevating STAT3 expression. Exosomes shuttled ZFAS1 stimulated proliferation, migration and invasion of ESCC cells and restricted their apoptosis with increased STAT3 and declined miR-124. Furthermore, in vivo experiment suggested that elevated ZFAS1-exo promoted tumor growth in nude mice.ConclusionThis study highlights that exosomal ZFAS1 promotes the proliferation, migration and invasion of ESCC cells and inhibits their apoptosis by upregulating STAT3 and downregulating miR-124, thereby resulting in the development of tumorigenesis of ESCC.
We present the first formal verification of a networked server implemented in C. Interaction trees, a general structure for representing reactive computations, are used to tie together disparate verification and testing tools (Coq, VST, and Quick-Chick) and to axiomatize the behavior of the operating system on which the server runs (CertiKOS). The main theorem connects a specification of acceptable server behaviors, written in a straightforward "one client at a time" style, with the CompCert semantics of the C program. The variability introduced by low-level buffering of messages and interleaving of multiple TCP connections is captured using network refinement, a variant of observational refinement.
Lactic acid, formerly thought of as a byproduct of glycolysis or a metabolic waste produced, has now been identified as a key regulator of cancer growth, maintenance, and progression. However, the results of investigations on lactic acid metabolism-related long non-coding RNAs (LRLs) in esophageal squamous cell carcinoma (ESCC) remain inconclusive. In this study, univariate Cox regression analysis was carried out in the TCGA cohort, and 9 lncRNAs were shown to be significantly associated with prognosis. Least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate Cox regression analysis were then used in the GEO cohort. 6 LRLs were identified as independent prognostic factors for ESCC patients used to construct a prognostic risk-related signature subsequently. Two groups were formed based on the middle value of risk scores: a low-risk group and a high-risk group. Following that, we conducted Kaplan-Meier survival analysis, which revealed that the high-risk group had a lower survival probability than the low-risk group in both GEO and TCGA cohorts. On multivariate Cox regression analysis, the prognostic signature was shown to be independent prognostic factor, and it was found to be a better predictor of the prognosis of ESCC patients than the currently widely used grading and staging approaches. The established nomogram can be conveniently applied in the clinic to predict the 1-, 3-, and 5- year survival rates of patients. There was a significant link found between the 6 LRLs-based prognostic signature and immune-cell infiltration, tumor microenvironment (TME), tumor somatic mutational status, and chemotherapeutic treatment sensitivity in the study population. Finally, we used GTEx RNA-seq data and qRT-PCR experiments to verify the expression levels of 6 LRLs. In conclusion, we constructed a prognostic signature which could predict the prognosis and immunotherapy response of ESCC patients.
Based on large-scale human mobility data collected in San Francisco and Boston, the morning peak urban rail transit (URT) ODs (origin-destination matrix) were estimated and the most vulnerable URT segments, those capable of causing the largest service interruptions, were identified. In both URT networks, a few highly vulnerable segments were observed. For this small group of vital segments, the impact of failure must be carefully evaluated. A bipartite URT usage network was developed and used to determine the inherent connections between urban rail transits and their passengers' travel demands. Although passengers' origins and destinations were easy to locate for a large number of URT segments, a few show very complicated spatial distributions. Based on the bipartite URT usage network, a new layer of the understanding of a URT segment's vulnerability can be achieved by taking the difficulty of addressing the failure of a given segment into account. Two proof-of-concept cases are described here: Possible transfer of passenger flow to the road network is here predicted in the cases of failures of two representative URT segments in San Francisco.
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