Acid-sensing ion channel 3 decreases phosphorylation of extracellular signal-regulated kinases and induces synoviocyte cell death by increasing intracellular calcium.

IntroductionAcid-sensing ion channel 3 (ASIC3) is expressed in synoviocytes, activated by decreases in pH, and reduces inflammation in animal models of inflammatory arthritis. The purpose of the current study was to characterize potential mechanisms underlying the control of inflammation by ASIC3 in fibroblast-like synoviocytes (FLS).MethodsExperiments were performed in cultured FLS from wild-type (WT) and ASIC3-/- mice, ASIC1-/- mice, and people with rheumatoid arthritis. We assessed the effects of acidic pH with and without interleukin-1β on FLS and the role of ASICs in modulating intracellular calcium [Ca(2+)](i), mitogen activated kinase (MAP kinase) expression, and cell death. [Ca(2+)](i) was assessed by fluorescent calcium imaging, MAP kinases were measured by Western Blots; ASIC, cytokine and protease mRNA expression were measured by quantitative PCR and cell death was measured with a LIVE/DEAD assay.ResultsAcidic pH increased [Ca(2+)](i) and decreased p-ERK expression in WT FLS; these effects were significantly smaller in ASIC3-/- FLS and were prevented by blockade of [Ca(2+)]i. Blockade of protein phosphatase 2A (PP2A) prevented the pH-induced decreases in p-ERK. In WT FLS, IL-1β increases ASIC3 mRNA, and when combined with acidic pH enhances [Ca(2+)](i), p-ERK, IL-6 and metalloprotienase mRNA, and cell death. Inhibitors of [Ca(2+)](i) and ERK prevented cell death induced by pH 6.0 in combination with IL-1β in WT FLS.ConclusionsDecreased pH activates ASIC3 resulting in increased [Ca(2+)](i), and decreased p-ERK. Under inflammatory conditions, acidic pH results in enhanced [Ca(2+)](i) and phosphorylation of extracellular signal-regulated kinase that leads to cell death. Thus, activation of ASIC3 on FLS by acidic pH from an inflamed joint could limit synovial proliferation resulting in reduced accumulation of inflammatory mediators and subsequent joint damage

Efficient non-parametric Bayesian hawkes processes

© 2019 International Joint Conferences on Artificial Intelligence. All rights reserved. In this paper, we develop an efficient nonparametric Bayesian estimation of the kernel function of Hawkes processes. The non-parametric Bayesian approach is important because it provides flexible Hawkes kernels and quantifies their uncertainty. Our method is based on the cluster representation of Hawkes processes. Utilizing the stationarity of the Hawkes process, we efficiently sample random branching structures and thus, we split the Hawkes process into clusters of Poisson processes. We derive two algorithms - a block Gibbs sampler and a maximum a posteriori estimator based on expectation maximization - and we show that our methods have a linear time complexity, both theoretically and empirically. On synthetic data, we show our methods to be able to infer flexible Hawkes triggering kernels. On two large-scale Twitter diffusion datasets, we show that our methods outperform the current state-of-the-art in goodness-of-fit and that the time complexity is linear in the size of the dataset. We also observe that on diffusions related to online videos, the learned kernels reflect the perceived longevity for different content types such as music or pets videos

Interstellar Turbulence and Star Formation

We provide a brief overview of recent advances and outstanding issues in simulations of interstellar turbulence, including isothermal models for interior structure of molecular clouds and larger-scale multiphase models designed to simulate the formation of molecular clouds. We show how self-organization in highly compressible magnetized turbulence in the multiphase ISM can be exploited in simple numerical models to generate realistic initial conditions for star formation.Comment: 8 pages, 5 color figures; submitted to Proceedings of IAU Symposium 270 "Computational Star Formation" held in Barcelona, May 31 - June 4, 201

Quantile Propagation for Wasserstein-Approximate Gaussian Processes

We develop a new approximate Bayesian inference method for Gaussian process models with factorized non-Gaussian likelihoods. Our method---dubbed Quantile Propagation (QP)---is similar to expectation propagation (EP) but minimizes the L_2 Wasserstein distance rather than the Kullback-Leibler (KL) divergence. We consider the case where likelihood factors are approximated by a Gaussian form. We show that QP matches quantile functions rather than moments as in EP and has the same mean update but a smaller variance update than EP, thereby alleviating the over-estimation of the posterior variance exhibited by EP. Crucially, QP has the same favorable locality property as EP, and thereby admits an efficient algorithm. Experiments on classification and Poisson regression tasks demonstrate that QP outperforms both EP and variational Bayes

Gravitational Waves from Axisymmetric, Rotational Stellar Core Collapse

We have carried out an extensive set of two-dimensional, axisymmetric, purely-hydrodynamic calculations of rotational stellar core collapse with a realistic, finite-temperature nuclear equation of state and realistic massive star progenitor models. For each of the total number of 72 different simulations we performed, the gravitational wave signature was extracted via the quadrupole formula in the slow-motion, weak-field approximation. We investigate the consequences of variation in the initial ratio of rotational kinetic energy to gravitational potential energy and in the initial degree of differential rotation. Furthermore, we include in our model suite progenitors from recent evolutionary calculations that take into account the effects of rotation and magnetic torques. For each model, we calculate gravitational radiation wave forms, characteristic wave strain spectra, energy spectra, final rotational profiles, and total radiated energy. In addition, we compare our model signals with the anticipated sensitivities of the 1st- and 2nd-generation LIGO detectors coming on line. We find that most of our models are detectable by LIGO from anywhere in the Milky Way.Comment: 13 pages, 22 figures, accepted for publication in ApJ (v600, Jan. 2004). Revised version: Corrected typos and minor mistakes in text and references. Minor additions to the text according to the referee's suggestions, conclusions unchange

Benzoyl­dicarbon­yl(η5-inden­yl)ruthenium(II)

In the title mol­ecule, [Ru(C9H7)(C7H5O)(CO)2], the dihedral angle between the mean plane of the indene ring system and the phenyl ring is 86.28 (8)°. The crystal structure is stabilized by weak inter­molecular C—H⋯O and C—H⋯π(arene) inter­actions. The Ru—η5-cyclopentadienyl centroid bond length is 1.946 (11) 

Offspring in response to parental female densities in the fruit fly parasitoid Diachasmimorpha longicaudata (Hymenoptera: Braconidae: Opiinae).

El presente trabajo forma parte de um programa de evaluación del parasitoide bracónido Diachasmimorpha longicaudata (Ashmead) como agente de biocontrol de Ceratitis capitata (Wiedemann) en Brasil