Discovery and characterization of small molecule Rac1 inhibitors

Aberrant activation of Rho GTPase Rac1 has been observed in various tumor types, including pancreatic cancer. Rac1 activates multiple signaling pathways that lead to uncontrolled proliferation, invasion and metastasis. Thus, inhibition of Rac1 activity is a viable therapeutic strategy for proliferative disorders such as cancer. Here we identified small molecule inhibitors that target the nucleotide-binding site of Rac1 through in silico screening. Follow up in vitro studies demonstrated that two compounds blocked active Rac1 from binding to its effector PAK1. Fluorescence polarization studies indicate that these compounds target the nucleotide-binding site of Rac1. In cells, both compounds blocked Rac1 binding to its effector PAK1 following EGF-induced Rac1 activation in a dose-dependent manner, while showing no inhibition of the closely related Cdc42 and RhoA activity. Furthermore, functional studies indicate that both compounds reduced cell proliferation and migration in a dose-dependent manner in multiple pancreatic cancer cell lines. Additionally, the two compounds suppressed the clonogenic survival of pancreatic cancer cells, while they had no effect on the survival of normal pancreatic ductal cells. These compounds do not share the core structure of the known Rac1 inhibitors and could serve as additional lead compounds to target pancreatic cancers with high Rac1 activity

Spatial patterns and cell surface clusters in perineuronal nets

© 2016 Elsevier B.V.Perineuronal nets (PNN) ensheath GABAergic and glutamatergic synapses on neuronal cell surface in the central nervous system (CNS), have neuroprotective effect in animal models of Alzheimer disease and regulate synaptic plasticity during development and regeneration. Crucial insights were obtained recently concerning molecular composition and physiological importance of PNN but the microstructure of the network remains largely unstudied. Here we used histochemistry, fluorescent microscopy and quantitative image analysis to study the PNN structure in adult mouse and rat neurons from layers IV and VI of the somatosensory cortex. Vast majority of meshes have quadrangle, pentagon or hexagon shape with mean mesh area of 1.29 µm2 in mouse and 1.44 µm2 in rat neurons. We demonstrate two distinct patterns of chondroitin sulfate distribution within a single mesh – with uniform (nonpolar) and node-enriched (polar) distribution of the Wisteria floribunda agglutinin-positive signal. Vertices of the node-enriched pattern match better with local maxima of chondroitin sulfate density as compared to the uniform pattern. PNN is organized into clusters of meshes with distinct morphologies on the neuronal cell surface. Our findings suggest the role for the PNN microstructure in the synaptic transduction and plasticity

sPlotOpen – An environmentally balanced, open-access, global dataset of vegetation plots

Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called ?sPlot?, compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained: Vegetation plots (n = 95,104) recording cover or abundance of naturally co-occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot-level data also include community-weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain: Global, 0.01?40,000 m². Time period and grain: 1888-2015, recording dates. Major taxa and level of measurement: 42,677 vascular plant taxa, plot-level records.Fil: Sabatini, Francesco Maria. Martin-universität Halle-wittenberg; Alemania. German Centre For Integrative Biodiversity Research (idiv) Halle-jena-leipzig; AlemaniaFil: Lenoir, Jonathan. Université de Picardie Jules Verne; FranciaFil: Hattab, Tarek. Université de Montpellier; FranciaFil: Arnst, Elise Aimee. Manaaki Whenua - Landcare Research; Nueva ZelandaFil: Chytrý, Milan. Masaryk University; República ChecaFil: Giorgis, Melisa Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Vanselow, Kim André. University of Erlangen-Nuremberg; AlemaniaFil: Vásquez Martínez, Rodolfo. Jardín Botánico de Missouri Oxapampa; PerúFil: Vassilev, Kiril. Bulgarian Academy of Sciences; BulgariaFil: Vélez-Martin, Eduardo. ILEX Consultoria Científica; BrasilFil: Venanzoni, Roberto. University of Perugia; ItaliaFil: Vibrans, Alexander Christian. Universidade Regional de Blumenau; BrasilFil: Violle, Cyrille. Paul Valéry Montpellier University; FranciaFil: Virtanen, Risto. German Centre for Integrative Biodiversity Research; AlemaniaFil: von Wehrden, Henrik. Leuphana University of Lüneburg; AlemaniaFil: Wagner, Viktoria. University of Alberta; CanadáFil: Walker, Donald A.. University of Alaska; Estados UnidosFil: Waller, Donald M.. University of Wisconsin-Madison; Estados UnidosFil: Wang, Hua-Feng. Hainan University; ChinaFil: Wesche, Karsten. Senckenberg Museum of Natural History Görlitz; Alemania. Technische Universität Dresden; AlemaniaFil: Whitfeld, Timothy J. S.. University of Minnesota; Estados UnidosFil: Willner, Wolfgang. University of Vienna; AustriaFil: Wiser, Susan K.. Manaaki Whenua. Landcare Research; Nueva ZelandaFil: Wohlgemuth, Thomas. Swiss Federal Institute for Forest, Snow and Landscape Research; SuizaFil: Yamalov, Sergey. Russian Academy of Sciences; RusiaFil: Zobel, Martin. University of Tartu; EstoniaFil: Bruelheide, Helge. German Centre for Integrative Biodiversity Research; Alemani

Declining mortality following acute myocardial infarction in the Department of Veterans Affairs Health Care System

<p>Abstract</p> <p>Background</p> <p>Mortality from acute myocardial infarction (AMI) is declining worldwide. We sought to determine if mortality in the Veterans Health Administration (VHA) has also been declining.</p> <p>Methods</p> <p>We calculated 30-day mortality rates between 2004 and 2006 using data from the VHA External Peer Review Program (EPRP), which entails detailed abstraction of records of all patients with AMI. To compare trends within VHA with other systems of care, we estimated relative mortality rates between 2000 and 2005 for all males 65 years and older with a primary diagnosis of AMI using administrative data from the VHA Patient Treatment File and the Medicare Provider Analysis and Review (MedPAR) files.</p> <p>Results</p> <p>Using EPRP data on 11,609 patients, we observed a statistically significant decline in adjusted 30-day mortality following AMI in VHA from 16.3% in 2004 to 13.9% in 2006, a relative decrease of 15% and a decrease in the odds of dying of 10% per year (p = .011). Similar declines were found for in-hospital and 90-day mortality.</p> <p>Based on administrative data on 27,494 VHA patients age 65 years and older and 789,400 Medicare patients, 30-day mortality following AMI declined from 16.0% during 2000-2001 to 15.7% during 2004-June 2005 in VHA and from 16.7% to 15.5% in private sector hospitals. After adjusting for patient characteristics and hospital effects, the overall relative odds of death were similar for VHA and Medicare (odds ratio 1.02, 95% C.I. 0.96-1.08).</p> <p>Conclusion</p> <p>Mortality following AMI within VHA has declined significantly since 2003 at a rate that parallels that in Medicare-funded hospitals.</p

GMRES with embedded ensemble propagation for the efficient solution of parametric linear systems in uncertainty quantification of computational models

In a previous work, embedded ensemble propagation was proposed to improve the efficiency of sampling-based uncertainty quantification methods of computational models on emerging computational architectures. It consists of simultaneously evaluating the model for a subset of samples together, instead of evaluating them individually. A first approach introduced to solve parametric linear systems with ensemble propagation is ensemble reduction. In Krylov methods for example, this reduction consists in coupling the samples together using an inner product that sums the sample contributions. Ensemble reduction has the advantages of being able to use optimized implementations of BLAS functions and having a stopping criterion which involves only one scalar. However, the reduction potentially decreases the rate of convergence due to the gathering of the spectra of the samples. In this paper, we investigate a second approach: ensemble propagation without ensemble reduction in the case of GMRES. This second approach solves each sample simultaneously but independently to improve the convergence compared to ensemble reduction. This raises two new issues which are solved in this paper: the fact that optimized implementations of BLAS functions cannot be used anymore and that ensemble divergence, whereby individual samples within an ensemble must follow different code execution paths, can occur. We tackle those issues by implementing a high-performing ensemble GEMV and by using masks. The proposed ensemble GEMV leads to a similar cost per GMRES iteration for both approaches, i.e. with and without reduction. For illustration, we study the performances of the new linear solver in the context of a mesh tying problem. This example demonstrates improved ensemble propagation speed-up without reduction

Discovery and characterization of small molecule Rac1 inhibitors

Aberrant activation of Rho GTPase Rac1 has been observed in various tumor types, including pancreatic cancer. Rac1 activates multiple signaling pathways that lead to uncontrolled proliferation, invasion and metastasis. Thus, inhibition of Rac1 activity is a viable therapeutic strategy for proliferative disorders such as cancer. Here we identified small molecule inhibitors that target the nucleotide-binding site of Rac1 through in silico screening. Follow up in vitro studies demonstrated that two compounds blocked active Rac1 from binding to its effector PAK1. Fluorescence polarization studies indicate that these compounds target the nucleotide-binding site of Rac1. In cells, both compounds blocked Rac1 binding to its effector PAK1 following EGF-induced Rac1 activation in a dose-dependent manner, while showing no inhibition of the closely related Cdc42 and RhoA activity. Furthermore, functional studies indicate that both compounds reduced cell proliferation and migration in a dose-dependent manner in multiple pancreatic cancer cell lines. Additionally, the two compounds suppressed the clonogenic survival of pancreatic cancer cells, while they had no effect on the survival of normal pancreatic ductal cells. These compounds do not share the core structure of the known Rac1 inhibitors and could serve as additional lead compounds to target pancreatic cancers with high Rac1 activity

Quantitative changes in perineuronal nets in development and posttraumatic condition

© 2019, The Author(s). Perineuronal net (PNN) is a highly structured portion of the CNS extracellular matrix (ECM) regulating synaptic plasticity and a range of pathologic conditions including posttraumatic regeneration and epilepsy. Here we studied Wisteria floribunda agglutinin-stained histological sections to quantify the PNN size and enrichment of chondroitin sulfates in mouse brain and spinal cord. Somatosensory cortex sections were examined during the period of PNN establishment at postnatal days 14, 21 and 28. The single cell PNN size and the chondroitin sulfate intensity were quantified for all cortex layers and specifically for the cortical layer IV which has the highest density of PNN-positive neurons. We demonstrate that the chondroitin sulfate proteoglycan staining intensity is increased between P14 and P28 while the PNN size remains unchanged. We then addressed posttraumatic changes of the PNN expression in laminae 6 and 7 of cervical spinal cord following hemisection injury. We demonstrate increase of the chondroitin sulfate content at 1.6–1.8 mm rostrally from the injury site and increase of the density of PNN-bearing cells at 0.4–1.2 mm caudally from the injury site. We further demonstrate decrease of the single cell PNN area at 0.2 mm caudally from the injury site suggesting that the PNN ECM takes part in the posttraumatic tissue rearrangement in the spinal cord. Our results demonstrate new insights on the PNN structure dynamics in the developing and posttraumatic CNS

Postnatal development of the microstructure of cortical GABAergic synapses and perineuronal nets requires sensory input

The brain synaptic circuitry is formed as a result of pre-defined genetic programs and sensory experience during postnatal development. Perineuronal nets ensheath synaptic boutons and control several crucial features of the synapse physiology. Formation of the perineuronal net microstructure during the brain development remains largely unstudied. Here we provide a detailed quantitative description of the 3-dimensional geometry of the synapse and the surrounding perineuronal net in the mouse somatosensory cortex layer IV. We compare the morphology of the synapse+perineuronal net complex in the adult brain formed under normal conditions or in the whisker shaving model of somatosensory deprivation. We demonstrate that the sensory deprivation causes flattening of the 3D PNN mesh geometry and reduction of the VGAT-positive cluster volume in presynaptic boutons. These results reveal a mechanism of the sensory input-dependent synapse morphogenesis during the brain development

Spatial patterns and cell surface clusters in perineuronal nets

© 2016 Elsevier B.V.Perineuronal nets (PNN) ensheath GABAergic and glutamatergic synapses on neuronal cell surface in the central nervous system (CNS), have neuroprotective effect in animal models of Alzheimer disease and regulate synaptic plasticity during development and regeneration. Crucial insights were obtained recently concerning molecular composition and physiological importance of PNN but the microstructure of the network remains largely unstudied. Here we used histochemistry, fluorescent microscopy and quantitative image analysis to study the PNN structure in adult mouse and rat neurons from layers IV and VI of the somatosensory cortex. Vast majority of meshes have quadrangle, pentagon or hexagon shape with mean mesh area of 1.29 µm2 in mouse and 1.44 µm2 in rat neurons. We demonstrate two distinct patterns of chondroitin sulfate distribution within a single mesh – with uniform (nonpolar) and node-enriched (polar) distribution of the Wisteria floribunda agglutinin-positive signal. Vertices of the node-enriched pattern match better with local maxima of chondroitin sulfate density as compared to the uniform pattern. PNN is organized into clusters of meshes with distinct morphologies on the neuronal cell surface. Our findings suggest the role for the PNN microstructure in the synaptic transduction and plasticity