EZH2, as a histone methyltransferase, has been associated with cancer development and metastasis possibly through the regulation of microRNAs and cellular pathways such as EMT. In this study, the effect of EZH2 expression on miR-200c and important genes of the EMT pathway was investigated in esophageal squamous cell carcinoma (ESCC). Comparative qRT-PCR was used to examine EZH2 expression in ESCC lines (YM-1 and KYSE‐30) following the separately transfected silencing and ectopic expressional EZH2 vectors in ESCC. Subsequently, expression of miR-200c and EMT markers was also assessed using qRT-PCR, western blotting and immunocytochemistry. Underexpression of Mir200c was detected in YM-1 and KYSE-30 cells after EZH2 silencing, while its overexpression was observed after EZH2 induced expression. Following EZH2 silencing, downregulation of mesenchymal markers and upregulation of epithelial markers were detected in the ESCCs. Our results demonstrate that EZH2 regulates the expression of miR-200c and critical EMT genes, implying that overexpression of Zeb2, Fibronectin, N-cadherin, and Vimentin lead to a mesenchymal phenotype and morphology while underexpression of epithelial genes, enhance cell migration after enforced expression of EZH2 in ESCCs. EZH2 gene can be a beneficial treatment marker for patients with esophageal cancer through decrease invasiveness of the disease and efficient response to neoadjuvant therapy.
Tourism is one of the most important economic sectors in the world and is heavily influenced by climate conditions. Insight into tourists’ weather preferences within contexts of extremely arid climates is particularly useful, not only for regions and tourism destinations that currently display such characteristics, but also for regions and tourism destinations for which climate change forecasts predict radicalization in terms of their weather conditions. The objective of this study was to identify the weather preferences of Iranians in relation to nature-based tourism (NBT) in regions with extremely arid climates in Iran. To achieve this aim, the study used a survey to identify the optimal preferences with respect to temperature (maximum and minimum), rainfall, wind speed, sunshine hours, and cloud cover, as well as the thresholds past which the conditions in relation to these elements were considered intolerable. The results of this research may be useful for designing tourism climate indices and/or associated rating scales—adapted to the segment under consideration—that enable the present and future evaluation of the tourism suitability of a region’s climate.
Simulation-based dynamic traffic assignment models are increasingly used in urban transportation systems analysis and planning. They replicate traffic dynamics across transportation networks by capturing the complex interactions between travel demand and supply. However, their applications particularly for large-scale networks have been hindered by the challenges associated with the collection, parsing, development, and sharing of data-intensive inputs. In this paper, we develop and share an open dataset for reproduction of a dynamic multi-modal transportation network model of Melbourne, Australia. The dataset is developed consistently with the General Modeling Network Specification (GMNS), enabling software-agnostic human and machine readability. GMNS is a standard readable format for sharing routable transportation network data that is designed to be used in multimodal static and dynamic transportation operations and planning models.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.