Class of correlated random networks with hidden variables

We study a class models of correlated random networks in which vertices are characterized by \textit{hidden variables} controlling the establishment of edges between pairs of vertices. We find analytical expressions for the main topological properties of these models as a function of the distribution of hidden variables and the probability of connecting vertices. The expressions obtained are checked by means of numerical simulations in a particular example. The general model is extended to describe a practical algorithm to generate random networks with an \textit{a priori} specified correlation structure. We also present an extension of the class, to map non-equilibrium growing networks to networks with hidden variables that represent the time at which each vertex was introduced in the system

Un acercamiento teórico a la estratégica retórica femenina de Gertrudis Gómez de Avellaneda

This study aims to define and examine Gertrudis Gómez de Avellaneda’s strategic feminine rhetoric. Avellaneda wrote an extensive corpus of poetry, plays, journalistic articles and prose works, but particularly her prose works offer the best paradigm of her evolution as a writer and as a feminist. Through these narratological strategies, Avellaneda’s fictional characters are created as figures of resistance, reflecting the author’s personal conflicts as a woman divided between her own identity and the need to conform to cultural norms. The ultimate aim of this study is to investigate how Avellaneda´s literary devices and narrative strategies subvert and redefine the textual tradition from which her work evolved, and are part of an important project that painstakingly creates a place for Avellaneda at the forefront of nineteenth-century Hispanic literature and feminist thought.<br><br>Este estudio pretende definir y examinar la estratégica retórica femenina de Gertrudis Gómez de Avellaneda. Avellaneda escribió un corpus extenso de poesía, teatro, artículos periodísticos y obras en prosa, pero es en su prosa donde mejor podemos hallar el paradigma de su evolución como literata y como escritora feminista. A través de estas estrategias narratológicas, los personajes de ficción de Avellaneda se crean como figuras de resistencia, reflejando los conflictos personales de la autora como una mujer fragmentada entre su propia identidad y la necesidad de adherirse a las normas culturales. Finalidad última de este estudio es la de investigar cómo las estrategias narrativas y recursos literarios de Avellaneda subvierten y redefinen la tradición textual desde la que su obra ha evolucionado, y forman parte de un importante proyecto que crea un lugar para Avellaneda en la vanguardia de la literatura hispánica del siglo XIX y del pensamiento feminista

Density-Matrix functional theory of strongly-correlated lattice fermions

A density functional theory (DFT) of lattice fermion models is presented, which uses the single-particle density matrix gamma_{ij} as basic variable. A simple, explicit approximation to the interaction-energy functional W[gamma] of the Hubbard model is derived from exact dimer results, scaling properties of W[gamma] and known limits. Systematic tests on the one-dimensional chain show a remarkable agreement with theBethe-Ansatz exact solution for all interaction regimes and band fillings. New results are obtained for the ground-state energyand charge-excitation gap in two dimensions. A successful description of strong electron correlations within DFT is achieved.Comment: 15 pages, 6 figures Submitted to PR

Density-matrix functional theory of the Hubbard model: An exact numerical study

A density functional theory for many-body lattice models is considered in which the single-particle density matrix is the basic variable. Eigenvalue equations are derived for solving Levy's constrained search of the interaction energy functional W, which is expressed as the sum of Hartree-Fock energy and the correlation energy E_C. Exact results are obtained for E_C of the Hubbard model on various periodic lattices. The functional dependence of E_C is analyzed by varying the number of sites, band filling and lattice structure. The infinite one-dimensional chain and one-, two-, or three-dimensional finite clusters with periodic boundary conditions are considered. The properties of E_C are discussed in the limits of weak and strong electronic correlations, as well as in the crossover region. Using an appropriate scaling we observe a pseudo-universal behavior which suggests that the correlation energy of extended systems could be obtained quite accurately from finite cluster calculations. Finally, the behavior of E_C for repulsive (U>0) and attractive (U<0) interactions are contrasted.Comment: Phys. Rev. B (1999), in pres

Interaction energy functional for lattice density functional theory: Applications to one-, two- and three-dimensional Hubbard models

The Hubbard model is investigated in the framework of lattice density functional theory (LDFT). The single-particle density matrix $\gamma_{ij}$ with respect the lattice sites is considered as the basic variable of the many-body problem. A new approximation to the interaction-energy functional $W[\gamma]$ is proposed which is based on its scaling properties and which recovers exactly the limit of strong electron correlations at half-band filling. In this way, a more accurate description of $W$ is obtained throughout the domain of representability of $\gamma_{ij}$, including the crossover from weak to strong correlations. As examples of applications results are given for the ground-state energy, charge-excitation gap, and charge susceptibility of the Hubbard model in one-, two-, and three-dimensional lattices. The performance of the method is demonstrated by comparison with available exact solutions, with numerical calculations, and with LDFT using a simpler dimer ansatz for $W$. Goals and limitations of the different approximations are discussed.Comment: 25 pages and 8 figures, submitted to Phys. Rev.

Ising-like agent-based technology diffusion model: adoption patterns vs. seeding strategies

The well-known Ising model used in statistical physics was adapted to a social dynamics context to simulate the adoption of a technological innovation. The model explicitly combines (a) an individual's perception of the advantages of an innovation and (b) social influence from members of the decision-maker's social network. The micro-level adoption dynamics are embedded into an agent-based model that allows exploration of macro-level patterns of technology diffusion throughout systems with different configurations (number and distributions of early adopters, social network topologies). In the present work we carry out many numerical simulations. We find that when the gap between the individual's perception of the options is high, the adoption speed increases if the dispersion of early adopters grows. Another test was based on changing the network topology by means of stochastic connections to a common opinion reference (hub), which resulted in an increment in the adoption speed. Finally, we performed a simulation of competition between options for both regular and small world networks.Comment: 23 pages and 5 figure

Dose‐dependent proteomic analysis of glioblastoma cancer stem cells upon treatment with γ‐secretase inhibitor

Notch signaling has been demonstrated to have a central role in glioblastoma (GBM) cancer stem cells (CSCs) and we have demonstrated recently that Notch pathway blockade by γ‐secretase inhibitor (GSI) depletes GBM CSCs and prevents tumor propagation both in vitro and in vivo. In order to understand the proteome alterations involved in this transformation, a dose‐dependent quantitative mass spectrometry (MS)‐based proteomic study has been performed based on the global proteome profiling and a target verification phase where both Immunoassay and a multiple reaction monitoring (MRM) assay are employed. The selection of putative protein candidates for confirmation poses a challenge due to the large number of identifications from the discovery phase. A multilevel filtering strategy together with literature mining is adopted to transmit the most confident candidates along the pipeline. Our results indicate that treating GBM CSCs with GSI induces a phenotype transformation towards non‐tumorigenic cells with decreased proliferation and increased differentiation, as well as elevated apoptosis. Suppressed glucose metabolism and attenuated NFR2‐mediated oxidative stress response are also suggested from our data, possibly due to their crosstalk with Notch Signaling. Overall, this quantitative proteomic‐based dose‐dependent work complements our current understanding of the altered signaling events occurring upon the treatment of GSI in GBM CSCs.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/88055/1/4529_ftp.pd

Genome-wide single-cell-level screen for protein abundance and localization changes in response to DNA damage in S. cerevisiae

An effective response to DNA damaging agents involves modulating numerous facets of cellular homeostasis in addition to DNA repair and cell-cycle checkpoint pathways. Fluorescence microscopy-based imaging offers the opportunity to simultaneously interrogate changes in both protein level and subcellular localization in response to DNA damaging agents at the single-cell level. We report here results from screening the yeast Green Fluorescent Protein (GFP)-fusion library to investigate global cellular protein reorganization on exposure to the alkylating agent methyl methanesulfonate (MMS). Broad groups of induced, repressed, nucleus- and cytoplasm-enriched proteins were identified. Gene Ontology and interactome analyses revealed the underlying cellular processes. Transcription factor (TF) analysis identified principal regulators of the response, and targets of all major stress-responsive TFs were enriched amongst the induced proteins. An unexpected partitioning of biological function according to the number of TFs targeting individual genes was revealed. Finally, differential modulation of ribosomal proteins depending on methyl methanesulfonate dose was shown to correlate with cell growth and with the translocation of the Sfp1 TF. We conclude that cellular responses can navigate different routes according to the extent of damage, relying on both expression and localization changes of specific proteins.National Cancer Institute (U.S.) (R01-CA055042 (now NIEHS R01-ES022872))Massachusetts Institute of Technology. Center for Environmental Health Sciences (Grant NIEHS P30-ES002109)National Cancer Institute (U.S.) (KI Center Grant U54-CA112967)National Cancer Institute (U.S.) (Cancer Center Support Grant P30-CA14051)National Institute of Environmental Health Sciences (R01-ES022872)MIT Faculty Start-up FundMassachusetts Institute of Technology. Computational and Systems Biology Initiative (Merck & Co. Postdoctoral Fellowship

Defending the genome from the enemy within:mechanisms of retrotransposon suppression in the mouse germline

The viability of any species requires that the genome is kept stable as it is transmitted from generation to generation by the germ cells. One of the challenges to transgenerational genome stability is the potential mutagenic activity of transposable genetic elements, particularly retrotransposons. There are many different types of retrotransposon in mammalian genomes, and these target different points in germline development to amplify and integrate into new genomic locations. Germ cells, and their pluripotent developmental precursors, have evolved a variety of genome defence mechanisms that suppress retrotransposon activity and maintain genome stability across the generations. Here, we review recent advances in understanding how retrotransposon activity is suppressed in the mammalian germline, how genes involved in germline genome defence mechanisms are regulated, and the consequences of mutating these genome defence genes for the developing germline