226 resultados para stochastic discount factor
Resumo:
The computational architecture that enables the flexible coupling between otherwise independent eye and hand effector systems is not understood. By using a drift diffusion framework, in which variability of the reaction time (RT) distribution scales with mean RT, we tested the ability of a common stochastic accumulator to explain eye-hand coordination. Using a combination of behavior, computational modeling and electromyography, we show how a single stochastic accumulator to threshold, followed by noisy effector-dependent delays, explains eye-hand RT distributions and their correlation, while an alternate independent, interactive eye and hand accumulator model does not. Interestingly, the common accumulator model did not explain the RT distributions of the same subjects when they made eye and hand movements in isolation. Taken together, these data suggest that a dedicated circuit underlies coordinated eye-hand planning.
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Actions of transforming growth factor-beta are largely context dependent. For instance, TGF-beta is growth inhibitory to epithelial cells and many tumor cell-lines while it stimulates the growth of mesenchymal cells. TGF-beta also activates fibroblast cells to a myofibroblastic phenotype. In order to understand how the responsiveness of fibroblasts to TGF-beta would change in the context of transformation, we have compared the differential gene regulation by TGF-beta in immortal fibroblasts (hFhTERT), transformed fibroblasts (hFhTERT-LTgRAS) and a human fibrosarcoma cell-line (HT1080). The analysis revealed regulation of 6735, 4163, and 3478 probe-sets by TGF-beta in hFhTERT, hFhTERT-LTgRAS and HT1080 cells respectively. Intriguingly, 5291 probe-sets were found to be either regulated in hFhTERT or hFhTERT-LTgRAS cells while 2274 probe-sets were regulated either in hFhTERT or HT1080 cells suggesting that the response of immortal hFhTERT cells to TGF-beta is vastly different compared to the response of both the transformed cells hFhTERT-LTgRAS and HT1080 to TGF-beta. Strikingly, WNT pathway showed enrichment in the hFhTERT cells in Gene Set Enrichment Analysis. Functional studies showed induction of WNT4 by TGF-beta in hFhTERT cells and TGF-beta conferred action of these cells was mediated by WNT4. While TGF-beta activated both canonical and non-canonical WNT pathways in hFhTERT cells, Erk1/2 and p38 Mitogen Activated Protein Kinase pathways were activated in hFhTERT-LTgRAS and HT1080 cells. This suggests that transformation of immortal hFhTERT cells by SV40 large T antigen and activated RAS caused a switch in their response to TGF-beta which matched with the response of HT1080 cells to TGF-beta. These data suggest context dependent activation of non-canonical signaling by TGF-beta. (C) 2015 Published by Elsevier Inc.
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Transactivator protein C is required for the expression of bacteriophage Mu late genes from lys, I, P and mom promoters during lytic life cycle of the phage. The mechanism of transcription activation of mom gene by C protein is well understood. C activates transcription at Pmom by initial unwinding of the promoter DNA, thereby facilitating RNA polymerase (RNAP) recruitment. Subsequently, C interacts with the (sic) subunit of RNAP to enhance promoter clearance. The mechanism by which C activates other late genes of the phage is not known. We carried out promoter-polymerase interaction studies with all the late gene promoters to determine the individual step of C mediated activation. Unlike at P-mom, at the other three promoters, RNAP recruitment and closed complex formation are not C dependent. Instead, the action of C at P-lys, P-I, and P-P is during the isomerization from closed complex to open complex with no apparent effect at other steps of initiation pathway. The mechanism of transcription activation of mom and other late promoters by their common activator is different. This distinction in the mode of activation (promoter recruitment and escape versus isomerization) by the same activator at different promoters appears to be important for optimized expression of each of the late genes.
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The annotated whole-genome sequence of Mycobacterium tuberculosis indicated that Rv1388 (Mtihf) likely encodes a putative 20 kDa integration host factor (mIHF). However, very little is known about the functional properties of mIHF or organization of mycobacterial nucleoid. Molecular modeling of the mIHF three-dimensional structure, based on the cocrystal structure of Streptomyces coelicolor IHF-duplex DNA, a bona fide relative of mIHF, revealed the presence of Arg170, Arg171, and Arg173, which might be involved in DNA binding, and a conserved proline (P150) in the tight turn. The phenotypic sensitivity of Escherichia coli Delta ihfA and Delta ihfB strains to UV and methylmethanesulfonate could be complemented with the wild-type Mtihf, but not its alleles bearing mutations in the DNA-binding residues. Protein DNA interaction assays revealed that wild-type mIHF, but not its DNA-binding variants, bind with high affinity to fragments containing attB and attP sites and curved DNA. Strikingly, the functionally important amino acid residues of mIHF and the mechanism(s) underlying its binding to DNA, DNA bending, and site-specific recombination are fundamentally different from that of E. coli IHF alpha beta. Furthermore, we reveal novel insights into IHF-mediated DNA compaction depending on the placement of its preferred binding sites; mIHF promotes compaction of DNA into nucleoid-like or higher-order filamentous structures. We hence propose that mIHF is a distinct member of a subfamily of proteins that serve as essential cofactors in site-specific recombination and nucleoid organization and that these findings represent a significant advance in our understanding of the role(s) of nucleoid-associated proteins.
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Mycobacterium tuberculosis has multiple sigma factors which enable the bacterium to reprogram its transcriptional machinery under diverse environmental conditions. sigma(J), an extracytoplasmic function sigma factor, is upregulated in late stationary phase cultures and during human macrophage infection. sigma(J) governs the cellular response to hydrogen peroxide-mediated oxidative stress. sigma(J) differs from other canonical sigma factors owing to the presence of a SnoaL_2 domain at the C-terminus. sigma(J) crystals belonged to the tetragonal space group I422, with unit-cell parameters a = b = 133.85, c = 75.08 angstrom. Diffraction data were collected to 2.16 angstrom resolution on the BM14 beamline at the European Synchrotron Radiation Facility (ESRF).
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Identification of dominant modes is an important step in studying linearly vibrating systems, including flow-induced vibrations. In the presence of uncertainty, when some of the system parameters and the external excitation are modeled as random quantities, this step becomes more difficult. This work is aimed at giving a systematic treatment to this end. The ability to capture the time averaged kinetic energy is chosen as the primary criterion for selection of modes. Accordingly, a methodology is proposed based on the overlap of probability density functions (pdf) of the natural and excitation frequencies, proximity of the natural frequencies of the mean or baseline system, modal participation factor, and stochastic variation of mode shapes in terms of the modes of the baseline system - termed here as statistical modal overlapping. The probabilistic descriptors of the natural frequencies and mode shapes are found by solving a random eigenvalue problem. Three distinct vibration scenarios are considered: (i) undamped arid damped free vibrations of a bladed disk assembly, (ii) forced vibration of a building, and (iii) flutter of a bridge model. Through numerical studies, it is observed that the proposed methodology gives an accurate selection of modes. (C) 2015 Elsevier Ltd. All rights reserved.
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Glioblastoma (grade IV glioma/GBM) is the most common primary adult malignant brain tumor with poor prognosis. To characterize molecular determinants of tumor-stroma interaction in GBM, we profiled 48 serum cytokines and identified macrophage colony-stimulating factor (MCSF) as one of the elevated cytokines in sera from GBM patients. Both MCSF transcript and protein were up-regulated in GBM tissue samples through a spleen tyrosine kinase (SYK)-dependent activation of the PI3K-NF kappa B pathway. Ectopic overexpression and silencing experiments revealed that glioma-secreted MCSF has no role in autocrine functions and M2 polarization of macrophages. In contrast, silencing expression of MCSF in glioma cells prevented tube formation of human umbilical vein endothelial cells elicited by the supernatant from monocytes/microglial cells treated with conditioned medium from glioma cells. Quantitative proteomics based on stable isotope labeling by amino acids in cell culture showed that glioma-derived MCSF induces changes in microglial secretome and identified insulin-like growth factor-binding protein 1 (IGFBP1) as one of the MCSF-regulated proteins secreted by microglia. Silencing IGFBP1 expression in microglial cells or its neutralization by an antibody reduced the ability of supernatants derived from microglial cells treated with glioma cell-conditioned medium to induce angiogenesis. In conclusion, this study shows up-regulation of MCSF in GBM via a SYK-PI3K-NF kappa B-dependent mechanism and identifies IGFBP1 released by microglial cells as a novel mediator of MCSF-induced angiogenesis, of potential interest for developing targeted therapy to prevent GBM progression.
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Response analysis of a linear structure with uncertainties in both structural parameters and external excitation is considered here. When such an analysis is carried out using the spectral stochastic finite element method (SSFEM), often the computational cost tends to be prohibitive due to the rapid growth of the number of spectral bases with the number of random variables and the order of expansion. For instance, if the excitation contains a random frequency, or if it is a general random process, then a good approximation of these excitations using polynomial chaos expansion (PCE) involves a large number of terms, which leads to very high cost. To address this issue of high computational cost, a hybrid method is proposed in this work. In this method, first the random eigenvalue problem is solved using the weak formulation of SSFEM, which involves solving a system of deterministic nonlinear algebraic equations to estimate the PCE coefficients of the random eigenvalues and eigenvectors. Then the response is estimated using a Monte Carlo (MC) simulation, where the modal bases are sampled from the PCE of the random eigenvectors estimated in the previous step, followed by a numerical time integration. It is observed through numerical studies that this proposed method successfully reduces the computational burden compared with either a pure SSFEM of a pure MC simulation and more accurate than a perturbation method. The computational gain improves as the problem size in terms of degrees of freedom grows. It also improves as the timespan of interest reduces.
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Many studies of reaching and pointing have shown significant spatial and temporal correlations between eye and hand movements. Nevertheless, it remains unclear whether these correlations are incidental, arising from common inputs (independent model); whether these correlations represent an interaction between otherwise independent eye and hand systems (interactive model); or whether these correlations arise from a single dedicated eye-hand system (common command model). Subjects were instructed to redirect gaze and pointing movements in a double-step task in an attempt to decouple eye-hand movements and causally distinguish between the three architectures. We used a drift-diffusion framework in the context of a race model, which has been previously used to explain redirect behavior for eye and hand movements separately, to predict the pattern of eye-hand decoupling. We found that the common command architecture could best explain the observed frequency of different eye and hand response patterns to the target step. A common stochastic accumulator for eye-hand coordination also predicts comparable variances, despite significant difference in the means of the eye and hand reaction time (RT) distributions, which we tested. Consistent with this prediction, we observed that the variances of the eye and hand RTs were similar, despite much larger hand RTs (similar to 90 ms). Moreover, changes in mean eye RTs, which also increased eye RT variance, produced a similar increase in mean and variance of the associated hand RT. Taken together, these data suggest that a dedicated circuit underlies coordinated eye-hand planning.
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In this paper we first derive a necessary and sufficient condition for a stationary strategy to be the Nash equilibrium of discounted constrained stochastic game under certain assumptions. In this process we also develop a nonlinear (non-convex) optimization problem for a discounted constrained stochastic game. We use the linear best response functions of every player and complementary slackness theorem for linear programs to derive both the optimization problem and the equivalent condition. We then extend this result to average reward constrained stochastic games. Finally, we present a heuristic algorithm motivated by our necessary and sufficient conditions for a discounted cost constrained stochastic game. We numerically observe the convergence of this algorithm to Nash equilibrium. (C) 2015 Elsevier B.V. All rights reserved.
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We introduce a new method for studying universality of random matrices. Let T-n be the Jacobi matrix associated to the Dyson beta ensemble with uniformly convex polynomial potential. We show that after scaling, Tn converges to the stochastic Airy operator. In particular, the top edge of the Dyson beta ensemble and the corresponding eigenvectors are universal. As a byproduct, these ideas lead to conjectured operator limits for the entire family of soft edge distributions. (C) 2015 Wiley Periodicals, Inc.
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Specific and coordinated regulation of innate immune receptor-driven signaling networks often determines the net outcome of the immune responses. Here, we investigated the cross-regulation of toll-like receptor (TLR)2 and nucleotide-binding oligomerization domain (NOD)2 pathways mediated by Ac2PIM, a tetra-acylated form of mycobacterial cell wall component and muramyl dipeptide (MDP), a peptidoglycan derivative respectively. While Ac2PIM treatment of macrophages compromised their ability to induce NOD2-dependent immunomodulators like cyclooxygenase (COX)-2, suppressor of cytokine signaling (SOCS)-3, and matrix metalloproteinase (MMP)-9, no change in the NOD2-responsive NO, TNF-alpha, VEGF-A, and IL-12 levels was observed. Further, genome-wide microRNA expression profiling identified Ac2PIM-responsive miR-150 and miR-143 to target NOD2 signaling adaptors, RIP2 and TAK1, respectively. Interestingly, Ac2PIM was found to activate the SRC-FAK-PYK2-CREB cascade via TLR2 to recruit CBP/P300 at the promoters of miR-150 and miR-143 and epigenetically induce their expression. Loss-of-function studies utilizing specific miRNA inhibitors establish that Ac2PIM, via the miRNAs, abrogate NOD2-induced PI3K-PKC delta-MAPK pathway to suppress beta-catenin-mediated expression of COX-2, SOCS-3, and MMP-9. Our investigation has thus underscored the negative regulatory role of Ac2PIM-TLR2 signaling on NOD2 pathway which could broaden our understanding on vaccine potential or adjuvant utilities of Ac2PIM and/or MDP.
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In this paper, we study two multi-dimensional Goodness-of-Fit tests for spectrum sensing in cognitive radios. The multi-dimensional scenario refers to multiple CR nodes, each with multiple antennas, that record multiple observations from multiple primary users for spectrum sensing. These tests, viz., the Interpoint Distance (ID) based test and the h, f distance based tests are constructed based on the properties of stochastic distances. The ID test is studied in detail for a single CR node case, and a possible extension to handle multiple nodes is discussed. On the other hand, the h, f test is applicable in a multi-node setup. A robustness feature of the KL distance based test is discussed, which has connections with Middleton's class A model. Through Monte-Carlo simulations, the proposed tests are shown to outperform the existing techniques such as the eigenvalue ratio based test, John's test, and the sphericity test, in several scenarios.
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In this article, we look at the political business cycle problem through the lens of uncertainty. The feedback control used by us is the famous NKPC with stochasticity and wage rigidities. We extend the New Keynesian Phillips Curve model to the continuous time stochastic set up with an Ornstein-Uhlenbeck process. We minimize relevant expected quadratic cost by solving the corresponding Hamilton-Jacobi-Bellman equation. The basic intuition of the classical model is qualitatively carried forward in our set up but uncertainty also plays an important role in determining the optimal trajectory of the voter support function. The internal variability of the system acts as a base shifter for the support function in the risk neutral case. The role of uncertainty is even more prominent in the risk averse case where all the shape parameters are directly dependent on variability. Thus, in this case variability controls both the rates of change as well as the base shift parameters. To gain more insight we have also studied the model when the coefficients are time invariant and studied numerical solutions. The close relationship between the unemployment rate and the support function for the incumbent party is highlighted. The role of uncertainty in creating sampling fluctuation in this set up, possibly towards apparently anomalous results, is also explored.
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We first study a class of fundamental quantum stochastic processes induced by the generators of a six dimensional non-solvable Lie dagger-algebra consisting of all linear combinations of the generalized Gross Laplacian and its adjoint, annihilation operator, creation operator, conservation, and time, and then we study the quantum stochastic integrals associated with the class of fundamental quantum stochastic processes, and the quantum Ito formula is revisited. The existence and uniqueness of solution of a quantum stochastic differential equation is proved. The unitarity conditions of solutions of quantum stochastic differential equations associated with the fundamental processes are examined. The quantum stochastic calculus extends the Hudson-Parthasarathy quantum stochastic calculus. (C) 2016 AIP Publishing LLC.