A numerical study of interactions and stellar bars

For several decades it has been known that stellar bars in disc galaxies can be triggered by interactions, or by internal processes such as dynamical instabilities. In this work, we explore the differences between these two mechanisms using numerical simulations. We perform two groups of simulations based on isolated galaxies, one group in which a bar develops naturally, and another group in which the bar could not develop in isolation. The rest of the simulations recreate 1:1 coplanar fly-by interactions computed with the impulse approximation. The orbits we use for the interactions represent the fly-bys in groups or clusters of different masses accordingly to the velocity of the encounter. In the analysis we focus on bars' amplitude, size, pattern speed and their rotation parameter, ${\cal R}=R_{CR}/R_{bar}$. The latter is used to define fast (${\cal R}1.4$). Compared with equivalent isolated galaxies we find that bars affected or triggered by interactions: (i) remain in the slow regime for longer; (ii) are more boxy in face-on views; (iii) they host kinematically hotter discs. Within this set of simulations we do not see strong differences between retrograde or prograde fly-bys. We also show that slow interactions can trigger bar formation.Comment: 12 pages, 7 figures. Accepted for publication in MNRA

Binding of retinoids to uteroglobin

AbstractUteroglobin, a progesterone-binding secretory protein, was shown to bind retinoic acid and retinol in a non-saturable manner, at least up to concentrations of retinoids of 20 μM. Binding is increased about 10-fold by previous reduction of uteroglobin with 10 mM dithothreitol and it is not affected by previous saturation of the progesterone binding site, suggesting different binding sites for the steroid and the retinoids. The results are discussed in relation to a possible physiological role for this protein

eCOMMONtech: plataforma sofrware para monitorización del balance de Gases de Efecto Invernadero en el Marco de Mecanismos de Desarrollo Limpio Forestales y Proyectos REDD+

La monitorización de las condiciones que debe cumplir un área forestal en proyectos MDL o REDD de manera tradicional, es decir, mediante mediciones y controles in situ, conlleva unos costes difíciles de asumir. Por ello, se ha planteado el desarrollo de una metodología capaz de integrar tecnologías orientadas a la realización de inventarios de carbono en áreas forestales de países en vías de desarrollo, mediante la utilización de diferentes tecnologías (sensorización ambiental, teledetección espacial, técnicas forestales, internet, etc.) que permiten determinar aquellos procedimientos más eficaces desde el punto de vista de la calidad y fiabilidad de la información obtenida y del coste/beneficio; analizando, las mejoras que suponen frente a los métodos tradicionales. Para ello, se desarrollan algoritmos y métodos de análisis necesarios para extraer las variables e indicadores medioambientales con el fin de realizar la monitorización de los ciclos de carbono en ámbitos forestales atribuibles a proyectos de absorciones de CO2.El resultado es la creación de una plataforma web que permite la monitorización remota y en tiempo real de inventarios de carbono a través de la integración de datos provenientes de sistemas de sensorización, imágenes tratadas con tecnologías de observación de la tierra y datos de campo

A Bayesian Joinpoint regression model with an unknown number of break-points

Joinpoint regression is used to determine the number of segments needed to adequately explain the relationship between two variables. This methodology can be widely applied to real problems, but we focus on epidemiological data, the main goal being to uncover changes in the mortality time trend of a specific disease under study. Traditionally, Joinpoint regression problems have paid little or no attention to the quantification of uncertainty in the estimation of the number of change-points. In this context, we found a satisfactory way to handle the problem in the Bayesian methodology. Nevertheless, this novel approach involves significant difficulties (both theoretical and practical) since it implicitly entails a model selection (or testing) problem. In this study we face these challenges through (i) a novel reparameterization of the model, (ii) a conscientious definition of the prior distributions used and (iii) an encompassing approach which allows the use of MCMC simulation-based techniques to derive the results. The resulting methodology is flexible enough to make it possible to consider mortality counts (for epidemiological applications) as Poisson variables. The methodology is applied to the study of annual breast cancer mortality during the period 1980--2007 in Castell\'{o}n, a province in Spain.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS471 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Total Roman Domination Number of Rooted Product Graphs

[EN] Let G be a graph with no isolated vertex and f:V(G)->{0,1,2} a function. If f satisfies that every vertex in the set {v is an element of V(G):f(v)=0} is adjacent to at least one vertex in the set {v is an element of V(G):f(v)=2}, and if the subgraph induced by the set {v is an element of V(G):f(v)>= 1} has no isolated vertex, then we say that f is a total Roman dominating function on G. The minimum weight omega(f)= n-ary sumation v is an element of V(G)f(v) among all total Roman dominating functions f on G is the total Roman domination number of G. In this article we study this parameter for the rooted product graphs. Specifically, we obtain closed formulas and tight bounds for the total Roman domination number of rooted product graphs in terms of domination invariants of the factor graphs involved in this product.Cabrera Martinez, A.; Cabrera García, S.; Carrión García, A.; Hernandez Mira, FA. (2020). Total Roman Domination Number of Rooted Product Graphs. Mathematics. 8(10):1-13. https://doi.org/10.3390/math8101850S11381

Computational and analytical studies of the harmonic index on Erdös-Rényi models

A main topic in the study of topological indices is to find bounds of the indices involving several parameters and/or other indices. In this paper we perform statistical (numerical) and analytical studies of the harmonic index H(G), and other topological indices of interest, on Erdos-Rényi (ER) graphs G(n, p) characterized by n vertices connected independently with probability p ∈ (0, 1). Particularly, in addition to H(G), we study here the (−2) sum-connectivity index χ−2(G), the modified Zagreb index MZ(G), the inverse degree index ID(G) and the Randic index R(G). First, to perform the statistical study of these indices, we define the averages of the normalized indices to their maximum value: {H(G)}, {χ−2(G)}, {MZ(G)}, {ID(G)}, {R(G)}. Then, from a detailed scaling analysis, we show that the averages of the normalized indices scale with the product ξ ≈ np. Moreover, we find two different behaviors. On the one hand, hH(G)i and hR(G)i, as a function of the probability p, show a smooth transition from zero to n/2 as p increases from zero to one. Indeed, after scaling, it is possible to define three regimes: a regime of mostly isolated vertices when ξ 10 (H(G), R(G) ≈ n/2). On the other hand, hχ−2(G)i, hMZ(G)i and hID(G)i increase with p until approaching their maximum value, then they decrease by further increasing p. Thus, after scaling the curves corresponding to these indices display bell-like shapes in log scale, which are symmetric around ξ ≈ 1; i.e. the percolation transition point of ER graphs. Therefore, motivated by the scaling analysis, we analytically (i) obtain new relations connecting the topological indices H, χ−2, MZ, ID and R that characterize graphs which are extremal with respect to the obtained relations and (ii) apply these results in order to obtain inequalities on H, χ−2, MZ, ID and R for graphs in ER models.J.A.M.-B. acknowledges financial support from FAPESP (Grant No. 2019/ 06931-2), Brazil, CONACyT (Grant No. 2019-000009-01EXTV-00067) and PRODEP-SEP (Grant No. 511-6/2019.-11821), Mexico. J.M.R. and J.M.S. acknowledge financial support from Agencia Estatal de Investigación (PID2019-106433GB-I00/AEI/ 10.13039/501100011033), Spain

Myristic acid potentiates palmitic acid-induced lipotoxicity and steatohepatitis associated with lipodystrophy by sustaning de novo ceramide synthesis.

Palmitic acid (PA) induces hepatocyte apoptosis and fuels de novo ceramide synthesis in the endoplasmic reticulum (ER). Myristic acid (MA), a free fatty acid highly abundant in copra/palmist oils, is a predictor of nonalcoholic steatohepatitis (NASH) and stimulates ceramide synthesis. Here we investigated the synergism between MA and PA in ceramide synthesis, ER stress, lipotoxicity and NASH. Unlike PA, MA is not lipotoxic but potentiated PA-mediated lipoapoptosis, ER stress, caspase-3 activation and cytochrome c release in primary mouse hepatocytes (PMH). Moreover, MA kinetically sustained PA-induced total ceramide content by stimulating dehydroceramide desaturase and switched the ceramide profile from decreased to increased ceramide 14:0/ceramide16:0, without changing medium and long-chain ceramide species. PMH were more sensitive to equimolar ceramide14:0/ceramide16:0 exposure, which mimics the outcome of PA plus MA treatment on ceramide homeostasis, than to either ceramide alone. Treatment with myriocin to inhibit ceramide synthesis and tauroursodeoxycholic acid to prevent ER stress ameliorated PA plus MA induced apoptosis, similar to the protection afforded by the antioxidant BHA, the pan-caspase inhibitor z-VAD-Fmk and JNK inhibition. Moreover, ruthenium red protected PMH against PA and MA-induced cell death. Recapitulating in vitro findings, mice fed a diet enriched in PA plus MA exhibited lipodystrophy, hepatosplenomegaly, increased liver ceramide content and cholesterol levels, ER stress, liver damage, inflammation and fibrosis compared to mice fed diets enriched in PA or MA alone. The deleterious effects of PA plus MA-enriched diet were largely prevented by in vivo myriocin treatment. These findings indicate a causal link between ceramide synthesis and ER stress in lipotoxicity, and imply that the consumption of diets enriched in MA and PA can cause NASH associated with lipodystrophy

A bioprinted 3D gut model with crypt-villus structures to mimic the intestinal epithelial-stromal microenvironment

The intestine is a complex tissue with a characteristic three-dimensional (3D) crypt-villus architecture, which plays a key role in the intestinal function. This function is also regulated by the intestinal stroma that actively supports the intestinal epithelium, maintaining the homeostasis of the tissue. Efforts to account for the 3D complex structure of the intestinal tissue have been focused mainly in mimicking the epithelial barrier, while solutions to include the stromal compartment are scarce and unpractical to be used in routine experiments. Here we demonstrate that by employing an optimized bioink formulation and the suitable printing parameters it is possible to produce fibroblast-laden crypt-villus structures by means of digital light projection stereolithography (DLP-SLA). This process provides excellent cell viability, accurate spatial resolution, and high printing throughput, resulting in a robust biofabrication approach that yields functional gut mucosa tissues compatible with conventional testing techniques.Copyright © 2023 Elsevier B.V. All rights reserved

A spectroscopic atlas of post-AGB stars and planetary nebulae selected from the IRAS Point Source Catalogue

Aims: We study the optical spectral properties of a sample of stars showing far infrared colours similar to those of well-known planetary nebulae. The large majority of them were unidentified sources or poorly known in the literature at the time when this spectroscopic survey started, some 15 years ago. Methods: We present low-resolution optical spectroscopy, finding charts and improved astrometric coordinates of a sample of 253 IRAS sources. Results: We have identified 103 sources as post-AGB stars, 21 as ``transition sources'', and 36 as planetary nebulae, some of them strongly reddened. Among the rest of sources in the sample, we were also able to identify 38 young stellar objects, 5 peculiar stars, and 2 Seyfert galaxies. Up to 49 sources in our spectroscopic sample do not show any optical counterpart, and most of them are suggested to be heavily obscured post-AGB stars, rapidly evolving on their way to becoming planetary nebulae. Conclusions: An analysis of the galactic distribution of the sources identified as evolved stars in the sample is presented together with a study of the distribution of these stars in the IRAS two-colour diagram. Finally, the spectral type distribution and other properties of the sources identified as post-AGB in this spectroscopic survey are discussed in the framework of stellar evolution.Comment: 69 pages, 413 figures. Accepted by Astronomy and Astrophysic

Learning a Battery of COVID-19 Mortality Prediction Models by Multi-objective Optimization

The COVID-19 pandemic is continuously evolving with drastically changing epidemiological situations which are approached with different decisions: from the reduction of fatalities to even the selection of patients with the highest probability of survival in critical clinical situations. Motivated by this, a battery of mortality prediction models with different performances has been developed to assist physicians and hospital managers. Logistic regression, one of the most popular classifiers within the clinical field, has been chosen as the basis for the generation of our models. Whilst a standard logistic regression only learns a single model focusing on improving accuracy, we propose to extend the possibilities of logistic regression by focusing on sensitivity and specificity. Hence, the log-likelihood function, used to calculate the coefficients in the logistic model, is split into two objective functions: one representing the survivors and the other for the deceased class. A multi-objective optimization process is undertaken on both functions in order to find the Pareto set, composed of models not improved by another model in both objective functions simultaneously. The individual optimization of either sensitivity (deceased patients) or specificity (survivors) criteria may be conflicting objectives because the improvement of one can imply the worsening of the other. Nonetheless, this conflict guarantees the output of a battery of diverse prediction models. Furthermore, a specific methodology for the evaluation of the Pareto models is proposed. As a result, a battery of COVID-19 mortality prediction models is obtained to assist physicians in decision-making for specific epidemiological situations.This research is supported by the Basque Government (IT1504- 22, Elkartek) through the BERC 2022–2025 program and BMTF project, and by the Ministry of Science, Innovation and Universities: BCAM Severo Ochoa accreditation SEV-2017-0718 and PID2019-104966GB-I00. Furthermore, the work is also supported by the AXA Research Fund project “Early prognosis of COVID-19 infections via machine learning”