Institution
University of Extremadura
Education•Badajoz, Spain•
About: University of Extremadura is a education organization based out in Badajoz, Spain. It is known for research contribution in the topics: Population & Hyperspectral imaging. The organization has 7856 authors who have published 18299 publications receiving 396126 citations. The organization is also known as: Universidad de Extremadura.
Papers published on a yearly basis
Papers
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TL;DR: It is demonstrated that MSCs-derived exosomes are a cell-derived product that could be considered as a therapeutic agent for the treatment of inflammation-related diseases.
Abstract: In the recent years, it has been widely demonstrated that the biological activity of mesenchymal stem cells (MSCs) is mediated through the release of paracrine factors. Many of these factors are released into exosomes, which are small membranous vesicles that participate in cell-cell communication. Exosomes from MSCs are thought to have similar functions to MSCs such as repairing and regeneration of damaged tissue, but little is known about the immunomodulatory effect of these vesicles. Based on previous reports where the immunomodulatory capacity of MSCs has been demonstrated, here we hypothesized that exosomes from MSCs may have an immunomodulatory role on the differentiation, activation and function of different lymphocyte subsets. According to this hypothesis, in vitro experiments were performed to characterize the immunomodulatory effect of MSCs-derived exosomes on in vitro stimulated T cells. The phenotypic characterization of cytotoxic and helper T cells (activation and differentiation markers) together with functional assays (proliferation and IFN-γ production) demonstrated that MSCs-derived exosomes exerted an inhibition effect in the differentiation and activation of T cells as well as a reduced T cell proliferation and IFN-γ release on in vitro expanded cells. In summary, here we demonstrate that MSCs-derived exosomes are a cell-derived product that could be considered as a therapeutic agent for the treatment of inflammation-related diseases.
284 citations
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TL;DR: The analyses of the immune system in elderly individuals determined several immune signatures constituting an immune risk phenotype that predicts mortality, and the contribution of latent cytomegalovirus infection to immunosenescence of T and NK cells has been shown.
283 citations
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TL;DR: A fast iterative algorithm to implement the pixel purity index (PPI) is proposed, referred to as fast iteratives PPI (FIPPI), which improves the PPI in several aspects and converges very rapidly with significant savings in computation.
Abstract: The pixel purity index (PPI) has been widely used in hyperspectral image analysis for endmember extraction due to its publicity and availability in the Environment for Visualizing Images (ENVI) software. Unfortunately, its detailed implementation has never been made available in the literature. This paper investigates the PPI based on limited published results and proposes a fast iterative algorithm to implement the PPI, referred to as fast iterative PPI (FIPPI). It improves the PPI in several aspects. Instead of using randomly generated vectors as initial endmembers, the FIPPI produces an appropriate initial set of endmembers to speed up its process. Additionally, it estimates the number of endmembers required to be generated by a recently developed concept, virtual dimensionality (VD) which is one of the most crucial issues in the implementation of PPI. Furthermore, it is an iterative algorithm, where an iterative rule is developed to improve each of the iterations until it reaches a final set of endmembers. Most importantly, it is an unsupervised algorithm as opposed to the PPI, which requires human intervention to manually select a final set of endmembers. The experiments show that both the FIPPI and the PPI produce very close results, but the FIPPI converges very rapidly with significant savings in computation.
282 citations
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TL;DR: A unique role is revealed for arginase 1 in the pathogenesis of nonhealing leishmaniasis, a prototype Th2 disease, and it is demonstrated that the activity of this enzyme promotes pathology and uncontrolled growth of Leishmania parasites in vivo.
Abstract: Arginase 1, an enzyme induced by Th2 cytokines, is a hallmark of alternatively activated macrophages and is responsible for the hydrolysis of L-arginine into ornithine, the building block for the production of polyamines. Upregulation of arginase 1 has been observed in a variety of diseases, but the mechanisms by which arginase contributes to pathology are not well understood. We reveal here a unique role for arginase 1 in the pathogenesis of nonhealing leishmaniasis, a prototype Th2 disease, and demonstrate that the activity of this enzyme promotes pathology and uncontrolled growth of Leishmania parasites in vivo. Inhibition of arginase activity during the course of infection has a clear therapeutic effect, as evidenced by markedly reduced pathology and efficient control of parasite replication. Despite the clear amelioration of the disease, this treatment does not alter the Th2 response. To address the underlying mechanisms, the arginase-induced L-arginine catabolism was investigated and the results demonstrate that arginase regulates parasite growth directly by affecting the polyamine synthesis in macrophages.
280 citations
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TL;DR: Fourier transform-infrared spectroscopy was used in the study of rockrose (Cistus ladaniferus, L.) and rockrose chars and activated carbons as mentioned in this paper.
280 citations
Authors
Showing all 8001 results
Name | H-index | Papers | Citations |
---|---|---|---|
Russel J. Reiter | 169 | 1646 | 121010 |
Donald G. Truhlar | 165 | 1518 | 157965 |
Manel Esteller | 146 | 713 | 96429 |
David J. Williams | 107 | 2060 | 62440 |
Keijo Häkkinen | 99 | 421 | 31355 |
Robert H. Anderson | 97 | 1237 | 41250 |
Leif Bertilsson | 87 | 321 | 23933 |
Mario F. Fraga | 84 | 267 | 32957 |
YangQuan Chen | 84 | 1048 | 36543 |
Antonio Plaza | 79 | 631 | 29775 |
Robert D. Gibbons | 75 | 349 | 26330 |
Jocelyn Chanussot | 73 | 614 | 27949 |
Naresh Magan | 72 | 400 | 17511 |
Luis Puelles | 71 | 269 | 19858 |
Jun Li | 70 | 799 | 19510 |