Direct numerical simulation of a turbulent boundary layer was performed to investigate the spatially coherent structures associated with very-large-scale motions (VLSMs). The Reynolds number was varied in the range Reθ = 570–2560. The main simulation was conducted by using a computational box greater than 50δo in the streamwise domain, where δo is the boundary layer thickness at the inlet, and inflow data was obtained from a separate inflow simulation based on Lund's method. Inspection of the three-dimensional instantaneous fields showed that groups of hairpin vortices are coherently arranged in the streamwise direction and that these groups create significantly elongated low- and high-momentum regions with large amounts of Reynolds shear stress. Adjacent packet-type structures combine to form the VLSMs; this formation process is attributed to continuous stretching of the hairpins coupled with lifting-up and backward curling of the vortices. The growth of the spanwise scale of the hairpin packets occurs continuously, so it increases rapidly to double that of the original width of the packets. We employed the modified feature extraction algorithm developed by Ganapathisubramani, Longmire & Marusic (J. Fluid Mech., vol. 478, 2003, p. 35) to identify the properties of the VLSMs of hairpin vortices. In the log layer, patches with the length greater than 3δ–4δ account for more than 40% of all the patches and these VLSMs contribute approximately 45% of the total Reynolds shear stress included in all the patches. The VLSMs have a statistical streamwise coherence of the order of ~6δ; the spatial organization and coherence decrease away from the wall, but the spanwise width increases monotonically with the wall-normal distance. Finally, the application of linear stochastic estimation demonstrated the presence of packet organization in the form of a train of packets in the log layer.
Nanoporous metal oxide materials are ubiquitous in the material sciences because of their numerous potential applications in various areas, including adsorption, catalysis, energy conversion and storage, optoelectronics, and drug delivery. While synthetic strategies for the preparation of siliceous nanoporous materials are well-established, nonsiliceous metal oxide-based nanoporous materials still present challenges. Herein, we report a novel synthetic strategy that exploits a metal-organic framework (MOF)-driven, self-templated route toward nanoporous metal oxides via thermolysis under inert atmosphere. In this approach, an aliphatic ligand-based MOF is thermally converted to nanoporous metal oxides with highly nanocrystalline frameworks, in which aliphatic ligands act as the self-templates that are afterward evaporated to generate nanopores. We demonstrate this concept with hierarchically nanoporous magnesia (MgO) and ceria (CeO2), which have potential applicability for adsorption, catalysis, and energy storage. The pore size of these nanoporous metal oxides can be readily tuned by simple control of experimental parameters. Significantly, nanoporous MgO exhibits exceptional CO2 adsorption capacity (9.2 wt %) under conditions mimicking flue gas. This MOF-driven strategy can be expanded to other nanoporous monometallic and multimetallic oxides with a multitude of potential applications.
CaAmong ion channels, the transient receptor potential (TRP) melastatin 6 and 7 channel is similarly permeable to both of the dominant divalent cations Ca 2+ and Mg 2+ .(4) TRP channels were first cloned from the Drosophila species (TRP and transient receptor potential-like protein) and constitute a superfamily of proteins that encode a diverse group of Ca 2+ -permeable nonselective cation channels.(5) The TRP family is divided into three subfamilies: classic, vanilloid (TRPV), and melastatin type (TRPM).(5) The eight TRPM family members differ significantly from other TRP channels in terms of domain structure, cation selectivity, and activation mechanisms.(5) By mediating cation entry as well as membrane depolarization, activation of the TRPM subfamily of ion channels has a profound influence on various physiologic and pathologic processes. (6,7) TRPM7 is endogenously expressed in a wide variety of tissues including brain and hematopoietic tissues (8) as well as kidney and heart tissues.(9-11) The TRPM7 cation channel supports multiple cellular and physiological functions, including cellular Mg 2+ homeostasis, (12,13) cell viability and growth, (13)(14)(15)(16) anoxic neuronal cell death, (17) synaptic transmission, (18) cell adhesion, (19,20) and intestinal pacemaking.(21) Recently, Wykes et al. (22) suggested that TRPM7 channels are critical for human mast cell survival, and Jiang et al. (23) suggested that activation of TRPM7 channels is critical for the growth and proliferation of human head and neck carcinoma cells. Also Abed et al. (24) proposed the importance of TRPM7 in human osteoblast-like cell proliferation. However, the presence and potential function of TRPM7 channels in human gastric cancer cells are unknown.In this study, we examined the presence and potential role of TRPM7 channels in the growth and survival of AGS cells, the most common human gastric adenocarcinoma cell line. Our data suggest that TRPM7 channels have an important role in the survival of these tumor cells. Materials and MethodsCells. Five human gastric adenocarcinoma cell lines (AGS, MKN-1, MKN-45, SNU-1, and SNU-484) were used. Among them, we used mainly AGS cell line, the most common human gastric adenocarcinoma cell line. All cell lines were established at
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.