59 research outputs found
Exploring the Immunotoxicity of Carbon Nanotubes
Mass production of carbon nanotubes (CNTs) and their applications in nanomedicine lead to the increased exposure risk of nanomaterials to human beings. Although reports on toxicity of nanomaterials are rapidly growing, there is still a lack of knowledge on the potential toxicity of such materials to immune systems. This article reviews some existing studies assessing carbon nanotubes’ toxicity to immune system and provides the potential mechanistic explanation
α-Mangostin extracted from the pericarp of the mangosteen (Garcinia mangostana Linn) reduces tumor growth and lymph node metastasis in an immunocompetent xenograft model of metastatic mammary cancer carrying a p53 mutation
<p>Abstract</p> <p>Background</p> <p>The mangosteen fruit has a long history of medicinal use in Chinese and Ayurvedic medicine. Recently, the compound α-mangostin, which is isolated from the pericarp of the fruit, was shown to induce cell death in various types of cancer cells in <it>in vitro </it>studies. This led us to investigate the antitumor growth and antimetastatic activities of α-mangostin in an immunocompetent xenograft model of mouse metastatic mammary cancer having a p53 mutation that induces a metastatic spectrum similar to that seen in human breast cancers.</p> <p>Methods</p> <p>Mammary tumors, induced by inoculation of BALB/c mice syngeneic with metastatic BJMC3879luc2 cells, were subsequently treated with α-mangostin at 0, 10 and 20 mg/kg/day using mini-osmotic pumps and histopathologically examined. To investigate the mechanisms of antitumor ability by α-mangostin, <it>in vitro </it>studies were also conducted.</p> <p>Results</p> <p>Not only were <it>in vivo </it>survival rates significantly higher in the 20 mg/kg/day α-mangostin group versus controls, but both tumor volume and the multiplicity of lymph node metastases were significantly suppressed. Apoptotic levels were significantly increased in the mammary tumors of mice receiving 20 mg/kg/day and were associated with increased expression of active caspase-3 and -9. Other significant effects noted at this dose level were decreased microvessel density and lower numbers of dilated lymphatic vessels containing intraluminal tumor cells in mammary carcinoma tissues.</p> <p><it>In vitro</it>, α-mangostin induced mitochondria-mediated apoptosis and G1-phase arrest and S-phase suppression in the cell cycle. Since activation by Akt phosphorylation plays a central role in a variety of oncogenic processes, including cell proliferation, anti-apoptotic cell death, angiogenesis and metastasis, we also investigated alterations in Akt phosphorylation induced by α-mangostin treatment both <it>in vitro </it>and <it>in vivo</it>. Quantitative analysis and immunohistochemistry showed that α-mangostin significantly decreased the levels of phospho-Akt-threonine 308 (Thr308), but not serine 473 (Ser473), in both mammary carcinoma cell cultures and mammary carcinoma tissues <it>in vivo</it>.</p> <p>Conclusions</p> <p>Since lymph node involvement is the most important prognostic factor in breast cancer patients, the antimetastatic activity of α-mangostin as detected in mammary cancers carrying a p53 mutation in the present study may have specific clinical applications. In addition, α-mangostin may have chemopreventive benefits and/or prove useful as an adjuvant therapy, or as a complementary alternative medicine in the treatment of breast cancer.</p
RNA delivery by extracellular vesicles in mammalian cells and its applications.
The term 'extracellular vesicles' refers to a heterogeneous population of vesicular bodies of cellular origin that derive either from the endosomal compartment (exosomes) or as a result of shedding from the plasma membrane (microvesicles, oncosomes and apoptotic bodies). Extracellular vesicles carry a variety of cargo, including RNAs, proteins, lipids and DNA, which can be taken up by other cells, both in the direct vicinity of the source cell and at distant sites in the body via biofluids, and elicit a variety of phenotypic responses. Owing to their unique biology and roles in cell-cell communication, extracellular vesicles have attracted strong interest, which is further enhanced by their potential clinical utility. Because extracellular vesicles derive their cargo from the contents of the cells that produce them, they are attractive sources of biomarkers for a variety of diseases. Furthermore, studies demonstrating phenotypic effects of specific extracellular vesicle-associated cargo on target cells have stoked interest in extracellular vesicles as therapeutic vehicles. There is particularly strong evidence that the RNA cargo of extracellular vesicles can alter recipient cell gene expression and function. During the past decade, extracellular vesicles and their RNA cargo have become better defined, but many aspects of extracellular vesicle biology remain to be elucidated. These include selective cargo loading resulting in substantial differences between the composition of extracellular vesicles and source cells; heterogeneity in extracellular vesicle size and composition; and undefined mechanisms for the uptake of extracellular vesicles into recipient cells and the fates of their cargo. Further progress in unravelling the basic mechanisms of extracellular vesicle biogenesis, transport, and cargo delivery and function is needed for successful clinical implementation. This Review focuses on the current state of knowledge pertaining to packaging, transport and function of RNAs in extracellular vesicles and outlines the progress made thus far towards their clinical applications
Induced pluripotent stem cells in Alzheimer’s disease: applications for disease modeling and cell-replacement therapy
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Design of the ECCE Detector for the Electron Ion Collider
Preprint submitted to Nuclear Instruments and Methods A. The file archived on this institutional repository has not been certified by peer review.32 pages, 29 figures, 9 tablesThe EIC Comprehensive Chromodynamics Experiment (ECCE) detector has been designed to address the full scope of the proposed Electron Ion Collider (EIC) physics program as presented by the National Academy of Science and provide a deeper understanding of the quark-gluon structure of matter. To accomplish this, the ECCE detector offers nearly acceptance and energy coverage along with excellent tracking and particle identification. The ECCE detector was designed to be built within the budget envelope set out by the EIC project while simultaneously managing cost and schedule risks. This detector concept has been selected to be the basis for the EIC project detector.Office of Science in the Department of Energy, the National Science Foundation, and the Los Alamos National
Laboratory Laboratory Directed Research and Development (LDRD) 20200022DR; This research used resources of the Compute and Data Environment for Science (CADES) at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-
00OR22725. The work of AANL group are supported by the Science Committee of RA, in the frames of the research project # 21AG-1C028. And we gratefully acknowledge that support of Brookhaven National Lab and the Thomas Jefferson National Accelerator Facility which are operated under contracts DESC0012704 and DE-AC05-06OR23177 respectivel
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AI-assisted optimization of the ECCE tracking system at the Electron Ion Collider
arXiv preprint [v2] Fri, 20 May 2022 03:23:44 UTC (2,296 KB) made available under a Creative Commons (CC BY) Attribution Licence, now in press, published by Elsevier: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, available online 17 November 2022 at: https://doi.org/10.1016/j.nima.2022.167748The Electron-Ion Collider (EIC) is a cutting-edge accelerator facility that will study the nature of the "glue" that binds the building blocks of the visible matter in the universe. The proposed experiment will be realized at Brookhaven National Laboratory in approximately 10 years from now, with detector design and R&D currently ongoing. Notably, EIC is one of the first large-scale facilities to leverage Artificial Intelligence (AI) already starting from the design and R&D phases. The EIC Comprehensive Chromodynamics Experiment (ECCE) is a consortium that proposed a detector design based on a 1.5T solenoid. The EIC detector proposal review concluded that the ECCE design will serve as the reference design for an EIC detector. Herein we describe a comprehensive optimization of the ECCE tracker using AI. The work required a complex parametrization of the simulated detector system. Our approach dealt with an optimization problem in a multidimensional design space driven by multiple objectives that encode the detector performance, while satisfying several mechanical constraints. We describe our strategy and show results obtained for the ECCE tracking system. The AI-assisted design is agnostic to the simulation framework and can be extended to other sub-detectors or to a system of sub-detectors to further optimize the performance of the EIC detector.Office of Nuclear Physics in the Office of Science in the Department of Energy; National Science Foundation, and the Los Alamos National Laboratory Laboratory Directed Research and Development (LDRD) 20200022DR
Proposal and requirements for a real-time hybrid simulator of the distribution network
International audienc
Proposal and requirements for a real-time hybrid simulator of the distribution network
International audienc
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