Objective: Long noncoding RNA FGD5 antisense RNA 1 (FGD5-AS1) participates in the regulation of non-small cell lung cancer (NSCLC) progression, but the underlying mechanisms are not fully revealed. This study aimed to determine the regulatory mechanism of FGD5-AS1 on the viability, migration, and invasion of NSCLC cells. Methods: QRT-PCR was performed to measure the expression of FGD5-AS1, microRNA-944 (miR-944), and MACC1 in NSCLC. The correlation between FGD5-AS1 and clinicopathological features of NSCLC patients was analyzed. The viability of NSCLC cells were detected using MTT assay, and the migration and invasion were measured by transwell assay. Additionally, dual-luciferase reporter assay was used to demonstrate the interactions among FGD5-AS1, miR-944, and MACC1. Furthermore, exosomes were isolated from NSCLC cells and identified by transmission electron microscopy (TEM) and western blot. Then, the macrophages treated with exosomes were co-cultured with NSCLC cells to assess the effect of exosomes containing lower FGD5-AS1 level on NSCLC. Results: The expression of FGD5-AS1 and MACC1 was increased in NSCLC, but miR-944 expression was decreased. FGD5-AS1 expression had significantly correlation with TNM stage and metastasis in NSCLC patients. FGD5-AS1 knockdown decreased the viability, migration, and invasion of NSCLC cells. Additionally, FGD5-AS1 and MACC1 were both targeted by miR-944 with the complementary binding sites at 3’ UTR. In the feedback experiments, miR-944 inhibition or MACC1 overexpression reversed the reduction effect of FGD5-AS1 knockdown on the tumorigenesis of NSCLC. Moreover, silencing of FGD5-AS1 suppressed macrophages M2 polarization, and eliminated the promoting effects of exosomes mediated macrophages on NSCLC cell migration and invasion. Conclusions: FGD5-AS1 knockdown attenuated viability, migration, and invasion of NSCLC cells by regulating the miR-944/MACC1 axis, providing a new therapeutic target for NSCLC.

As more and more parallel programs are migrating to shared computing platforms, bounding their parallel execution times under resource constraints is particularly important for their efficient executions. The parallel program is often modeled as a task graph, which is composed of a collection of control or data-dependent sub-tasks organized as a directed acyclic graph (DAG) for scheduling. In this paper, we propose a simple yet effective method to bound the parallel execution time of a task graph when the memory resources are constrained. The essence of this method is to extend Brent's theorem by incorporating the memory factor. To this end, we introduce a concept of range of concurrent tasks (RCT) and leverage it to estimate an upper bound on the parallel execution time of task graph with respect to work-conserving scheduling algorithm. And also we exploit the estimated bound to develop a metric to help determine optimal memory capacity for a given task graph. Through an empirical study, we evaluate how good the estimated bound is via a designed scheduling algorithm and demonstrate the effectiveness of the metric in the selection of optimal memory capacity for a task graph. INDEX TERMS Task graph scheduling, time bounds, parallel execution, multicores, shared memory, memory constraints.

No abstract