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This study aimed to investigate the interaction between miR-1278 and Caldesmon (CALD1) in gastric cancer (GC) and the regulatory mechanism. In both GC cells and tissues, the levels of CALD1, miR-1278, migration-related markers (E-cadherin, N-cadherin, and Snail), and MAPK signaling pathway-related proteins were clarified using quantitative real-time PCR and western blotting analyses. The effects of miR-1278 and CALD1 on GC cell viability and migration were analyzed using CCK-8 and Transwell assays, respectively. The targeting effect of miR-1278 on CALD1 was investigated using bioinformatics prediction and a dual luciferase reporter assay. The effect of miR-1278 on tumor growth was estimated in vivo using a tumor xenograft assay. In GC, miR-1278 expression decreased, whereas CALD1 was highly expressed. Transfecting an miR-1278 mimic into cells inhibited the viability as well as migration of GC cells, and suppressed Ras, phosphorylated (p)-P38, and p-ERK1/2 protein levels. Moreover, miR-1278 targeted and negatively regulated CALD1 expression. CALD1 overexpression promoted GC cell survival and migration and activated the MAPK pathway. Treatment with an miR-1278 mimic partially rescued the changes caused by CALD1 overexpression. Overall, our study revealed that miR-1278 suppresses the malignant behavior of GC cells by targeting CALD1 and regulating the MAPK pathway.

Data-driven recovery of topology is challenging for networks beyond pairwise interactions. The authors propose a framework to reconstruct complex networks with higher-order interactions from time series, focusing on networks with 2-simplexes where social contagion and Ising dynamics generate binary data.

Objective To explore the effect of lncRNA FGD5-AS1 on oxidized low-density lipoprotein (ox-LDL)-induced vascular endothelial cell damage and its regulatory effect on miR-106a-5p. Methods Ox-LDL was used to induce human umbilical vein endothelial cells(HUVECs) to establish a cellular injury model. pcDNA-FGD5-AS1, anti-miR-106a-5p and its negative control were transfected into HUVECs and then added to ox-LDL-treated cells. pcDNA-FGD5-AS1 was co-transfected with miR-NC and miR-106a-5p mimics to HUVECs, then added ox-LDL to treat cells. RT-qPCR was used to detect the expression of FGD5-AS1 and miR-106a-5p. The level of MDA, SOD, and CAT was tested with commercially available kit. Flow cytometry was used to detect the apoptosis rate. The dual luciferase reporter gene experiment was used to detect the targeting relationship between FGD5-AS1 and miR-106a-5p. Western blot was used to detect the protein expression of cleaved caspase-3 and cleaved caspase-9. Results The expression of FGD5-AS1 mRNA in HUVECs induced by ox-LDL decreased (P＜0.05) while the expression of miR-106a-5p mRNA increased (P＜0.05). Both transfection of pcDNA-FGD5-AS1 and transfection of anti-miR-106a-5p reduced the level of MDA, apoptosis rate and protein level of cleaved caspase-3, cleaved caspase-9 in HUVECs induced by ox-LDL(P＜0.05),enhanced the activity of SOD and CAT (P＜0.05). FGD5-AS1 could target at miR-106a-5p. Co-transfection of pcDNA-FGD5-AS1 and miR-106a-5p mimics could reverse the effect of pcDNA-FGD5-AS1 on ox-LDL-induced HUVECs apoptosis and oxidative stress. Conclusions Over-expression of FGD5-AS1 may inhibit oxidative stress and apoptosis through targeted regulation of miR-106a-5p, thereby reducing ox-LDL-induced vascular endothelial cell damage.

Wind-solar-electric vehicles coordinated optimization scheduling can effectively reduce the adverse effects of multiple uncertainties of wind-solar output and disorderly charging of electric vehicles on the power system. Most of the existing optimization scheduling models take the minimum equivalent load fluctuation as the optimization objective, which, only considering the overall fluctuation of equivalent load, cannot measure the matching degree of output-load, and do not consider the difference of output in different output scenarios. Therefore, a wind-solar-electric vehicles coordination scheduling method for high proportion new energy grid-connected scenarios is proposed. First, the disordered charging model of electric vehicles by Monte Carlo simulation is constructed. Then, a wind-solar output typical day classification model using Gap statistical and K-means++ is constructed based on the forecasting data of wind and solar power. Finally, taking the minimum equivalent load variance and load tracking coefficient as the double optimization objectives, a wind-solar-electric vehicles coordination optimization scheduling model is established, and the NSGA-II algorithm is used to solve it. The results demonstrate that the proposed model can effectively improve the matching degree of wind-solar output and load, and reduce the fluctuation of equivalent load, so as to reduce the adverse effects of multiple uncertainties of wind-solar output and disorderly charging of electric vehicles on the power system.