Identification of atropine-and P2X1 receptor antagonist-reistant, neurogenic contractions of the urinary bladder

Acetylcholine and ATP are excitatory cotransmitters in parasympathetic nerves. We used P2X1 receptor antagonists to further characterize the purinergic component of neurotransmission in isolated detrusor muscle of guinea pig urinary bladder. In the presence of atropine (1 μm) and prazosin (100 nm), pyridoxalphosphate-6-azophenyl-2′,4′-disulfonic acid (PPADS) (0.1–100 μm) and suramin (1–300 μm) inhibited contractions evoked by 4 Hz nerve stimulation in a concentration-dependent manner (IC50 of 6.9 and 13.4 μm, respectively). Maximum inhibition was 50–60%, which was unaffected by coadministration of the ectonucleotidase inhibitor ARL67156 (6-N,N-diethyl-d-β,γ-dibromomethyleneATP) (100 μm). The remaining responses were abolished by tetrodotoxin (1 μm). PPADS and suramin also reduced contractions to exogenous ATP (300 μm) by 40–50%, but abolished those to the P2X1 agonist α,β-methyleneATP (α,β-meATP) (1 μm). The P2X1 antagonists reactive blue 2, NF279 (8,8′-[carbonylbis(imino-4,1-phenylenecarbonylimino-4,1-phenylenecarbonylimino)] bis-1,3,5-naphthalenetrisulfonic acid), MRS2159 (pyridoxal-α5-phosphate-6-phenylazo-4′-carboxylic acid) (100 μm), and NF449 [4,4′,4,4-(carbonylbis(imino-5,1,3-benzenetriylbis(carbonylimino)))tetrakis-benzene-1,3-disulfonic acid] (3 μm) abolished contractions to α,β-meATP (1 μm; n = 4–5), but only reduced contractions evoked by 4 Hz nerve stimulation by ∼40–60% (n = 4–6) and ATP by 30–60% (n = 4–7). However, prolonged exposure to α,β-meATP (50 μm) abolished contractions evoked by all three stimuli (n = 5–12). PPADS (100 μm) and suramin (300 μm) reduced the peak neurogenic contraction of the mouse urinary bladder to 30–40% of control. At the same concentrations, the P2X1 antagonists abolished the nonadrenergic, purinergic component of neurogenic contractions in the guinea pig vas deferens (n = 4–5). Thus, P2X1 receptor antagonists inhibit, but do not abolish, the noncholinergic component of neurogenic contractions of guinea pig and mouse urinary bladder, indicating a second mode of action of neuronally released ATP. This has important implications for treatment of dysfunctional urinary bladder, for which this atropine- and P2X1 antagonist-resistant site represents a novel therapeutic target

Computing the Loewner driving process of random curves in the half plane

We simulate several models of random curves in the half plane and numerically compute their stochastic driving process (as given by the Loewner equation). Our models include models whose scaling limit is the Schramm-Loewner evolution (SLE) and models for which it is not. We study several tests of whether the driving process is Brownian motion. We find that just testing the normality of the process at a fixed time is not effective at determining if the process is Brownian motion. Tests that involve the independence of the increments of Brownian motion are much more effective. We also study the zipper algorithm for numerically computing the driving function of a simple curve. We give an implementation of this algorithm which runs in a time O(N^1.35) rather than the usual O(N^2), where N is the number of points on the curve.Comment: 20 pages, 4 figures. Changes to second version: added new paragraph to conclusion section; improved figures cosmeticall

Generating Interpretable Fuzzy Controllers using Particle Swarm Optimization and Genetic Programming

Autonomously training interpretable control strategies, called policies, using pre-existing plant trajectory data is of great interest in industrial applications. Fuzzy controllers have been used in industry for decades as interpretable and efficient system controllers. In this study, we introduce a fuzzy genetic programming (GP) approach called fuzzy GP reinforcement learning (FGPRL) that can select the relevant state features, determine the size of the required fuzzy rule set, and automatically adjust all the controller parameters simultaneously. Each GP individual's fitness is computed using model-based batch reinforcement learning (RL), which first trains a model using available system samples and subsequently performs Monte Carlo rollouts to predict each policy candidate's performance. We compare FGPRL to an extended version of a related method called fuzzy particle swarm reinforcement learning (FPSRL), which uses swarm intelligence to tune the fuzzy policy parameters. Experiments using an industrial benchmark show that FGPRL is able to autonomously learn interpretable fuzzy policies with high control performance.Comment: Accepted at Genetic and Evolutionary Computation Conference 2018 (GECCO '18

Monte Carlo Tests of SLE Predictions for the 2D Self-Avoiding Walk

The conjecture that the scaling limit of the two-dimensional self-avoiding walk (SAW) in a half plane is given by the stochastic Loewner evolution (SLE) with $\kappa=8/3$ leads to explicit predictions about the SAW. A remarkable feature of these predictions is that they yield not just critical exponents, but probability distributions for certain random variables associated with the self-avoiding walk. We test two of these predictions with Monte Carlo simulations and find excellent agreement, thus providing numerical support to the conjecture that the scaling limit of the SAW is SLE$_{8/3}$.Comment: TeX file using APS REVTeX 4.0. 10 pages, 5 figures (encapsulated postscript

Mott transition in lattice boson models

We use mathematically rigorous perturbation theory to study the transition between the Mott insulator and the conjectured Bose-Einstein condensate in a hard-core Bose-Hubbard model. The critical line is established to lowest order in the tunneling amplitude.Comment: 20 page

SMCKAT, a Sequential Multi-Dimensional CNV Kernel-Based Association Test.

Copy number variants (CNVs) are the most common form of structural genetic variation, reflecting the gain or loss of DNA segments compared with a reference genome. Studies have identified CNV association with different diseases. However, the association between the sequential order of CNVs and disease-related traits has not been studied, to our knowledge, and it is still unclear that CNVs function individually or whether they work in coordination with other CNVs to manifest a disease or trait. Consequently, we propose the first such method to test the association between the sequential order of CNVs and diseases. Our sequential multi-dimensional CNV kernel-based association test (SMCKAT) consists of three parts: (1) a single CNV group kernel measuring the similarity between two groups of CNVs; (2) a whole genome group kernel that aggregates several single group kernels to summarize the similarity between CNV groups in a single chromosome or the whole genome; and (3) an association test between the CNV sequential order and disease-related traits using a random effect model. We evaluate SMCKAT on CNV data sets exhibiting rare or common CNVs, demonstrating that it can detect specific biologically relevant chromosomal regions supported by the biomedical literature. We compare the performance of SMCKAT with MCKAT, a multi-dimensional kernel association test. Based on the results, SMCKAT can detect more specific chromosomal regions compared with MCKAT that not only have CNV characteristics, but the CNV order on them are significantly associated with the disease-related trait

Quantum interference of electromagnetic fields from remote quantum memories

We observe quantum, Hong-Ou-Mandel, interference of fields produced by two remote atomic memories. High-visibility interference is obtained by utilizing the finite atomic memory time in four-photon delayed coincidence measurements. Interference of fields from remote atomic memories is a crucial element in protocols for scalable generation of multi-node remote qubit entanglement.Comment: 4 pages, 3 figure

Identification of proteins in the postsynaptic density fraction by mass spectrometry

Our understanding of the organization of postsynaptic signaling systems at excitatory synapses has been aided by the identification of proteins in the postsynaptic density (PSD) fraction, a subcellular fraction enriched in structures with the morphology of PSDs. In this study, we have completed the identification of most major proteins in the PSD fraction with the use of an analytical method based on mass spectrometry coupled with searching of the protein sequence databases. At least one protein in each of 26 prominent protein bands from the PSD fraction has now been identified. We found 7 proteins not previously known to be constituents of the PSD fraction and 24 that had previously been associated with the PSD by other methods. The newly identified proteins include the heavy chain of myosin-Va (dilute myosin), a motor protein thought to be involved in vesicle trafficking, and the mammalian homolog of the yeast septin protein cdc10, which is important for bud formation in yeast. Both myosin-Va and cdc10 are threefold to fivefold enriched in the PSD fraction over brain homogenates. Immunocytochemical localization of myosin-Va in cultured hippocampal neurons shows that it partially colocalizes with PSD-95 at synapses and is also diffusely localized in cell bodies, dendrites, and axons. Cdc10 has a punctate distribution in cell bodies and dendrites, with some of the puncta colocalizing with PSD-95. The results support a role for myosin-Va in transport of materials into spines and for septins in the formation or maintenance of spines