Stanilov-Tsankov-Videv Theory

We survey some recent results concerning Stanilov-Tsankov-Videv theory, conformal Osserman geometry, and Walker geometry which relate algebraic properties of the curvature operator to the underlying geometry of the manifold.Comment: This is a contribution to the Proceedings of the 2007 Midwest Geometry Conference in honor of Thomas P. Branson, published in SIGMA (Symmetry, Integrability and Geometry: Methods and Applications) at http://www.emis.de/journals/SIGMA

PredIG: a predictor of T-cell immunogenicity

The identification of immunogenic epitopes (such as fragments of proteins, in particular peptides, that can trigger an immune response) is a fundamental need for immune-based therapies. A computational tool that could predict such immunogenic epitopes would have vast potential applications in biomedicine ranging, from vaccine design against viruses or bacteria to therapeutic vaccination of cancer patients. While there are several methods that predict whether a peptide will be shown to the immune system via the Human Leukocyte Antigen (HLA) proteins of a patient, most of them cannot predict whether such presentation will indeed trigger an immune response. Additionally, T-cell immunogenicity is determined by multiple cellular processes, some of which are often overlooked by the current state-of-the-art immunogenicity predictors. The aim of this project is to build PredIG, an immunogenicity predictor that discriminates immunogenic from non-immunogenic T-cell epitopes given the peptide sequence and the HLA typing. After a careful study of the drivers of antigen processing and presentation on HLA class I molecules and an assessment of the physicochemical factors influencing epitope recognition by T-cell receptors (TCRs), we have used a selection of publicly available tools and in-house developed algorithms to identify the most relevant features that determine epitope immunogenicity. We then used these features to build an immunogenicity predictor (PredIG) modelled by XGBoost against immunogenically validated epitopes by the ImmunoEpitope DataBase (IEDB)(1), the PRIME dataset(2) and the TANTIGEN database(3). Pondering the feature importance in the model, the in-house developed softwares, NOAH for HLA Binding Affinity and NetCleave for Proteasomal Processing were identified as the major contributors to the performance of the model. Once PredIG was developed, we benchmarked the capacity to predict the immunogenicity of validated T-cell epitopes versus a set of state-of-the-art methods (Fig.1). Relevantly, PredIG showed a greater performance than the Immunogenicity predictors from Prime(2) and IEDB(4). Additionally, our results confirm that predicting T-cell immunogenicity based on data from T-cell assays is more accurate than using HLA Binding assays, the method mostly used in the field. An AUC value of 0.67 and an enrichment factor in the TOP10 epitopes of 90% outperforms the predictive performance of the available methods. In the context of the immune response against cancers, Tcell immunogenicity of tumoral mutations has been described as a response biomarker for immunotherapies such as immune checkpoint inhibitors. Similarly, the presence of immune infiltrate in a tumor has been related to a better prognosis for many cancer types. What is missing is the link between T-cell immunogenicity of tumoral mutations and the capacity of a tumor to attract immune cells. For this reason, we correlated the PredIG immunogenicity score obtained in a dataset of the The Cancer Genome Atlas (TCGA) against the tumor infiltrate in such tumors demonstrating that rather the total number of mutations a tumor accumulates, the tumor mutation burden (TMB), it is the number of immunogenic mutations what should be accounted for as biomarker of response

Modeling two-language competition dynamics

During the last decade, much attention has been paid to language competition in the complex systems community, that is, how the fractions of speakers of several competing languages evolve in time. In this paper we review recent advances in this direction and focus on three aspects. First we consider the shift from two-state models to three state models that include the possibility of bilingual individuals. The understanding of the role played by bilingualism is essential in sociolinguistics. In particular, the question addressed is whether bilingualism facilitates the coexistence of languages. Second, we will analyze the effect of social interaction networks and physical barriers. Finally, we will show how to analyze the issue of bilingualism from a game theoretical perspective.Comment: 15 pages, 5 figures; published in the Special Issue of Advances in Complex Systems "Language Dynamics

Impact of distance determinations on Galactic structure. II. Old tracers

Here we review the efforts of a number of recent results that use old tracers to understand the build up of the Galaxy. Details that lead directly to using these old tracers to measure distances are discussed. We concentrate on the following: (1) the structure and evolution of the Galactic bulge and inner Galaxy constrained from the dynamics of individual stars residing therein; (2) the spatial structure of the old Galactic bulge through photometric observations of RR Lyrae-type stars; (3) the three\--dimensional structure, stellar density, mass, chemical composition, and age of the Milky Way bulge as traced by its old stellar populations; (4) an overview of RR Lyrae stars known in the ultra-faint dwarfs and their relation to the Galactic halo; and (5) different approaches for estimating absolute and relative cluster ages.Comment: Review article, 80 pages (25 figures); Space Science Reviews, in press (chapter of a special collection resulting from the May 2016 ISSI-BJ workshop on Astronomical Distance Determination in the Space Age

Kerr-Sen dilaton-axion black hole lensing in the strong deflection limit

In the present work we study numerically quasi-equatorial lensing by the charged, stationary, axially-symmetric Kerr-Sen dilaton-axion black hole in the strong deflection limit. In this approximation we compute the magnification and the positions of the relativistic images. The most outstanding effect is that the Kerr-Sen black hole caustics drift away from the optical axis and shift in clockwise direction with respect to the Kerr caustics. The intersections of the critical curves on the equatorial plane as a function of the black hole angular momentum are found, and it is shown that they decrease with the increase of the parameter $Q^{2}/M$. All of the lensing quantities are compared to particular cases as Schwarzschild, Kerr and Gibbons-Maeda black holes.Comment: 31 pages, 17 figures; V2 references added, some typos corrected, V3 references added, language corrections, V4 table added, minor technical correction

Voter Dynamics on an Ising Ladder: Coarsening and Persistence

Coarsening and persistence of Ising spins on a ladder is examined under voter dynamics. The density of domain walls decreases algebraically with time as $t^-{1/2}$ for sequential as well as parallel dynamics. The persistence probability decreases as $t^{-\theta_{s}}$ under sequential dynamics, and as $t^{-\theta_{p}}$ under parallel dynamics where $\theta_{p} = 2 \theta_{s} \approx .88$. Numerical values of the exponents are explained. The results are compared with the voter model on one and two dimensional lattices, as well as Ising model on a ladder under zero-temperature Glauber dynamics.Comment: replaced with published version (text somewhat expanded): 11 pages, 2 figure

Scale-free Networks from Optimal Design

A large number of complex networks, both natural and artificial, share the presence of highly heterogeneous, scale-free degree distributions. A few mechanisms for the emergence of such patterns have been suggested, optimization not being one of them. In this letter we present the first evidence for the emergence of scaling (and smallworldness) in software architecture graphs from a well-defined local optimization process. Although the rules that define the strategies involved in software engineering should lead to a tree-like structure, the final net is scale-free, perhaps reflecting the presence of conflicting constraints unavoidable in a multidimensional optimization process. The consequences for other complex networks are outlined.Comment: 6 pages, 2 figures. Submitted to Europhysics Letters. Additional material is available at http://complex.upc.es/~sergi/software.ht

Quarantine generated phase transition in epidemic spreading

We study the critical effect of quarantine on the propagation of epidemics on an adaptive network of social contacts. For this purpose, we analyze the susceptible-infected-recovered (SIR) model in the presence of quarantine, where susceptible individuals protect themselves by disconnecting their links to infected neighbors with probability w, and reconnecting them to other susceptible individuals chosen at random. Starting from a single infected individual, we show by an analytical approach and simulations that there is a phase transition at a critical rewiring (quarantine) threshold w_c separating a phase (w<w_c) where the disease reaches a large fraction of the population, from a phase (w >= w_c) where the disease does not spread out. We find that in our model the topology of the network strongly affects the size of the propagation, and that w_c increases with the mean degree and heterogeneity of the network. We also find that w_c is reduced if we perform a preferential rewiring, in which the rewiring probability is proportional to the degree of infected nodes.Comment: 13 pages, 6 figure