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Institution

University of Oviedo

EducationOviedo, Spain
About: University of Oviedo is a education organization based out in Oviedo, Spain. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 13423 authors who have published 31649 publications receiving 844799 citations. The organization is also known as: Universidá d'Uviéu & Universidad de Oviedo.


Papers
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Journal ArticleDOI
01 Oct 2003-Fuel
TL;DR: In this paper, the Arrhenius kinetic parameters were calculated from the experimental results, considering the process as a series of consecutive first order reactions for coal-sludge blends.

158 citations

Journal ArticleDOI
Albert M. Sirunyan1, Armen Tumasyan1, Wolfgang Adam, Federico Ambrogi  +2291 moreInstitutions (195)
TL;DR: In this paper, a search for the direct electroweak production of charginos and neutralinos in signatures with either two or more leptons (electrons or muons) of the same electric charge, or with three or more hadronically decaying tau-leptons.
Abstract: Results are presented from a search for the direct electroweak production of charginos and neutralinos in signatures with either two or more leptons (electrons or muons) of the same electric charge, or with three or more leptons, which can include up to two hadronically decaying tau leptons. The results are based on a sample of proton-proton collision data collected at $ \sqrt{s}=13 $ TeV, recorded with the CMS detector at the LHC, corresponding to an integrated luminosity of 35.9 fb$^{−1}$. The observed event yields are consistent with the expectations based on the standard model. The results are interpreted in simplified models of supersymmetry describing various scenarios for the production and decay of charginos and neutralinos. Depending on the model parameters chosen, mass values between 180 GeV and 1150 GeV are excluded at 95% CL. These results significantly extend the parameter space probed for these particles in searches at the LHC. In addition, results are presented in a form suitable for alternative theoretical interpretations.

158 citations

Book ChapterDOI
TL;DR: The finding that MMPs are enzymes whose effects on biologically active substrates can have profound consequences on cell behaviour, suggests that selective inhibition of a limited set of M MPs at early stages of tumor evolution might be much more effective than using wide-spectrum inhibitors active against most family members, and administered to patients at late stages of the disease.
Abstract: The matrix metalloproteinases (MMPs) are a family of more than 20 distinct enzymes that are frequently overexpressed in human tumors. Functional studies have shown that MMPs play an important role in the proteolytic destruction of extracellular matrix and basement membranes, thereby facilitating tumor invasion and metastasis. In addition, these enzymes may also be important in other steps of tumor evolution including neoplastic cell proliferation and angiogenesis stimulation. On the basis of the relevance of MMPs in tumor progression, a number of different strategies aimed to block the unwanted activity of these enzymes in cancer have been developed. Unfortunately, most clinical trials with the first series of MMP inhibitors have failed to show clear benefit in patients with advanced cancer. Explanations for this lack of success include the failure to recognize the role of these enzymes in early stages of the disease as well as inadequacy of either the employed inhibitors or the proteases to be targeted.

158 citations

Journal ArticleDOI
TL;DR: The different salvage treatment options and associated prognostic factors for each of them are reviewed and a treatment algorithm based on the latest available evidence is proposed to discuss the future directions of treatment for locally recurrent NPC.

158 citations

Journal Article
TL;DR: According to these results, collagenase-3 should be included among the molecular factors that are detected during the stromal reaction to invasive breast cancer and that, by concerted action, may be essential for tumor growth and progression.
Abstract: Collagenase-3 (MMP-13) is a recently identified member of the human matrix metalloproteinase gene family that is expressed in breast carcinomas and in articular cartilage from arthritic patients Here, we have studied the cellular origin of this enzyme in breast carcinomas by in situ RNA hybridization, and we found that collagenase-3 is expressed by stromal cells immediately adjacent to epithelial tumor cells but not by the tumor cells themselves; nor is it expressed by the normal breast glandular epithelium Consistent with this observation, coculture experiments using human fibroblasts and MCF-7 breast cancer cells revealed that conditioned medium from breast cancer cells stimulated the fibroblastic expression of collagenase-3 mRNA In contrast, no stimulatory effect was observed when medium from fibroblast cells was added to breast cancer cells These results strongly suggest that transcription of collagenase-3 in stromal cells is activated by diffusible factors released from epithelial breast cancer cells A survey of a series of cytokines and growth factors known for their ability to induce collagenase-3 expression in human fibroblasts identified interleukin-1α and interleukin-1β as potential candidates for inducing the expression of this MMP gene in breast carcinomas According to these results, collagenase-3 should be included among the molecular factors that are detected during the stromal reaction to invasive breast cancer and that, by concerted action, may be essential for tumor growth and progression

158 citations


Authors

Showing all 13643 results

NameH-indexPapersCitations
Russel J. Reiter1691646121010
Carlo Rovelli1461502103550
J. González-Nuevo144500108318
German Martinez1411476107887
Roland Horisberger1391471100458
Francisco Herrera139100182976
Javier Cuevas1381689103604
Teresa Rodrigo1381831103601
L. Toffolatti13637695529
Elias Campo13576185160
Gabor Istvan Veres135134996104
Francisco Matorras134142894627
Joe Incandela134154993750
Nikhil C. Munshi13490667349
Luca Scodellaro134174198331
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202396
2022268
20211,825
20201,913
20191,806
20181,721