Examinando por Autor "Navarro, C."

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    Microbiota and diabetes mellitus: Role of lipid mediators
    (MDPI AG, 2020-10) Salazar, J.; Angarita, L.; Morillo, V.; Navarro, C.; Martínez, M.S.; Chacín, M.; Torres, W.; Rajotia, A.; Rojas, M.; Cano, C.; Añez, R.; Rojas, J.
    Diabetes Mellitus (DM) is an inflammatory clinical entity with different mechanisms involved in its physiopathology. Among these, the dysfunction of the gut microbiota stands out. Currently, it is understood that lipid products derived from the gut microbiota are capable of interacting with cells from the immune system and have an immunomodulatory effect. In the presence of dysbiosis, the concentration of lipopolysaccharides (LPS) increases, favoring damage to the intestinal barrier. Furthermore, a pro-inflammatory environment prevails, and a state of insulin resistance and hyperglycemia is present. Conversely, during eubiosis, the production of short-chain fatty acids (SCFA) is fundamental for the maintenance of the integrity of the intestinal barrier as well as for immunogenic tolerance and appetite/satiety perception, leading to a protective effect. Additionally, it has been demonstrated that alterations or dysregulation of the gut microbiota can be reversed by modifying the eating habits of the patients or with the administration of prebiotics, probiotics, and symbiotics. Similarly, different studies have demonstrated that drugs like Metformin are capable of modifying the composition of the gut microbiota, promoting changes in the biosynthesis of LPS, and the metabolism of SCFA. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
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    The VVV templates project towards an automated classification of VVV light-curves: I. Building a database of stellar variability in the near-infrared
    (EDP Sciences, 2014-07) Angeloni, R.; Contreras Ramos, R.; Catelan, M.; Dékány, I.; Gran, F.; Alonso-García, J.; Hempel, M.; Navarrete, C.; Andrews, H.; Aparicio, A.; Beamín, J.C.; Berger, C.; Borissova, J.; Contreras Peña, C.; Cunial, A.; De Grijs, R.; Espinoza, N.; Eyheramendy, S.; Eyheramendy, S.; Fiaschi, M.; Hajdu, G.; Han, J.; Hełminiak, K.G.; Hempel, A.; Hidalgo, S.L.; Ita, Y.; Jeon Y., -B; Jordán, A.; Kwon, J.; Lee, J.T.; Martín, E.L.; Masetti, N.; Matsunaga, N.; Milone, A.P.; Minniti, D.; Morelli, L.; Murgas, F.; Nagayama, T.; Navarro, C.; Ochner, P.; Pérez, P.; Pichara, K.; Rojas-Arriagada, A.; Roquette, J.; Saito, R.K.; Siviero, A.; Sohn, J.; Sung, H.-I.; Tamura, M.; Tata, R.; Tomasella, L.; Townsend, B.; Whitelock, P.
    Context. The Vista Variables in the Vía Láctea (VVV) ESO Public Survey is a variability survey of the Milky Way bulge and an adjacent section of the disk carried out from 2010 on ESO Visible and Infrared Survey Telescope for Astronomy (VISTA). The VVV survey will eventually deliver a deep near-IR atlas with photometry and positions in five passbands (ZYJHKS) and a catalogue of 1−10 million variable point sources – mostly unknown – that require classifications. Aims. The main goal of the VVV Templates Project, which we introduce in this work, is to develop and test the machine-learning algorithms for the automated classification of the VVV light-curves. As VVV is the first massive, multi-epoch survey of stellar variability in the near-IR, the template light-curves that are required for training the classification algorithms are not available. In the first paper of the series we describe the construction of this comprehensive database of infrared stellar variability. Methods. First, we performed a systematic search in the literature and public data archives; second, we coordinated a worldwide observational campaign; and third, we exploited the VVV variability database itself on (optically) well-known stars to gather high-quality infrared light-curves of several hundreds of variable stars. Results. We have now collected a significant (and still increasing) number of infrared template light-curves. This database will be used as a training-set for the machine-learning algorithms that will automatically classify the light-curves produced by VVV. The results of such an auto mated classification will be covered in forthcoming papers of the series.
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    YOUNG STELLAR CLUSTERS CONTAINING MASSIVE YOUNG STELLAR OBJECTS IN THE VVV SURVEY
    (IOP PUBLISHING, 2016-09) Borissova, J.; Ramírez Alegría, S.; Alonso, J.; Lucas, P. W.; Kurtev, R.; Medina, N.; Navarro, C.; Kuhn, M.; Gromadzki, M.; Retamales, G.; Fernandez, M. A.; Agurto-Gangas, C.; Chené, A.-N.; Minniti, D.; Contreras Pena, C.; Catelan, M.; Decany, I.; Thompson, M. A.; Morales, E. F. E.; Amigo, P.
    The purpose of this research is to study the connections of the global properties of eight young stellar clusters projected in the Vista Variables in the Via Lactea (VVV) ESO Large Public Survey disk area and their young stellar object (YSO) populations. The analysis is based on the combination of spectroscopic parallax-based reddening and distance determinations with main-sequence and pre-main-sequence ishochrone fitting to determine the basic parameters (reddening, age, distance) of the sample clusters. The lower mass limit estimations show that all clusters are low or intermediate mass (between 110 and 1800 M-circle dot), the slope Gamma of the obtained present-day mass functions of the clusters is close to the Kroupa initial mass function. The YSOs in the cluster's surrounding fields are classified using low resolution spectra, spectral energy distribution fits with theoretical predictions, and variability, taking advantage of multi-epoch VVV observations. All spectroscopically confirmed YSOs (except one) are found to be massive (more than 8 M-circle dot). Using VVV and GLIMPSE color-color cuts we have selected a large number of new YSO candidates, which are checked for variability and 57% are found to show at least low-amplitude variations. In few cases it was possible to distinguish between YSO and AGB classifications on the basis of light curves.