Predicting language diversity with complex network

Evolution and propagation of the world's languages is a complex phenomenon, driven, to a large extent, by social interactions. Multilingual society can be seen as a system of interacting agents, where the interaction leads to a modification of the language spoken by the individuals. Two people can reach the state of full linguistic compatibility due to the positive interactions, like transfer of loanwords. But, on the other hand, if they speak entirely different languages, they will separate from each other. These simple observations make the network science the most suitable framework to describe and analyze dynamics of language change. Although many mechanisms have been explained, we lack a qualitative description of the scaling behavior for different sizes of a population. Here we address the issue of the language diversity in societies of different sizes, and we show that local interactions are crucial to capture characteristics of the empirical data. We propose a model of social interactions, extending the idea from, that explains the growth of the language diversity with the size of a population of country or society. We argue that high clustering and network disintegration are the most important characteristics of models properly describing empirical data. Furthermore, we cancel the contradiction between previous models and the Solomon Islands case. Our results demonstrate the importance of the topology of the network, and the rewiring mechanism in the process of language change

Ask yeast how to burn your fats: lessons learned from the metabolic adaptation to salt stress

[EN] Here, we review and update the recent advances in the metabolic control during the adaptive response of budding yeast to hyperosmotic and salt stress, which is one of the best understood signaling events at the molecular level. This environmental stress can be easily applied and hence has been exploited in the past to generate an impressively detailed and comprehensive model of cellular adaptation. It is clear now that this stress modulates a great number of different physiological functions of the cell, which altogether contribute to cellular survival and adaptation. Primary defense mechanisms are the massive induction of stress tolerance genes in the nucleus, the activation of cation transport at the plasma membrane, or the production and intracellular accumulation of osmolytes. At the same time and in a coordinated manner, the cell shuts down the expression of housekeeping genes, delays the progression of the cell cycle, inhibits genomic replication, and modulates translation efficiency to optimize the response and to avoid cellular damage. To this fascinating interplay of cellular functions directly regulated by the stress, we have to add yet another layer of control, which is physiologically relevant for stress tolerance. Salt stress induces an immediate metabolic readjustment, which includes the up-regulation of peroxisomal biomass and activity in a coordinated manner with the reinforcement of mitochondrial respiratory metabolism. Our recent findings are consistent with a model, where salt stress triggers a metabolic shift from fermentation to respiration fueled by the enhanced peroxisomal oxidation of fatty acids. We discuss here the regulatory details of this stress-induced metabolic shift and its possible roles in the context of the previously known adaptive functions.The work of the authors was supported by grants from Ministerio de Economía y Competitividad (BFU2011- 23326 and BFU2016-75792-R).Pascual-Ahuir Giner, MD.; Manzanares-Estreder, S.; Timón Gómez, A.; Proft ., MH. (2017). Ask yeast how to burn your fats: lessons learned from the metabolic adaptation to salt stress. Current Genetics. 64(1):63-69. https://doi.org/10.1007/s00294-017-0724-5S6369641Aguilera J, Prieto JA (2001) The Saccharomyces cerevisiae aldose reductase is implied in the metabolism of methylglyoxal in response to stress conditions. Curr Genet 39:273–283Albertyn J, Hohmann S, Thevelein JM, Prior BA (1994) GPD1, which encodes glycerol-3-phosphate dehydrogenase, is essential for growth under osmotic stress in Saccharomyces cerevisiae, and its expression is regulated by the high-osmolarity glycerol response pathway. Mol Cell Biol 14:4135–4144Alepuz PM, Jovanovic A, Reiser V, Ammerer G (2001) Stress-induced map kinase Hog1 is part of transcription activation complexes. Mol Cell 7:767–777Alepuz PM, de Nadal E, Zapater M, Ammerer G, Posas F (2003) Osmostress-induced transcription by Hot1 depends on a Hog1-mediated recruitment of the RNA Pol II. EMBO J 22:2433–2442Ansell R, Granath K, Hohmann S, Thevelein JM, Adler L (1997) The two isoenzymes for yeast NAD+-dependent glycerol 3-phosphate dehydrogenase encoded by GPD1 and GPD2 have distinct roles in osmoadaptation and redox regulation. EMBO J 16:2179–2187Babazadeh R, Lahtvee PJ, Adiels CB, Goksor M, Nielsen JB, Hohmann S (2017) The yeast osmostress response is carbon source dependent. Sci Rep 7:990Bender T, Pena G, Martinou JC (2015) Regulation of mitochondrial pyruvate uptake by alternative pyruvate carrier complexes. EMBO J 34:911–924Berry DB, Gasch AP (2008) Stress-activated genomic expression changes serve a preparative role for impending stress in yeast. Mol Biol Cell 19:4580–4587Bilsland-Marchesan E, Arino J, Saito H, Sunnerhagen P, Posas F (2000) Rck2 kinase is a substrate for the osmotic stress-activated mitogen-activated protein kinase Hog1. Mol Cell Biol 20:3887–3895Brewster JL, Gustin MC (2014) Hog 1: 20 years of discovery and impact. Sci Signal 7:re7Clotet J, Posas F (2007) Control of cell cycle in response to osmostress: lessons from yeast. Methods Enzymol 428:63–76Clotet J, Escote X, Adrover MA, Yaakov G, Gari E, Aldea M, de Nadal E, Posas F (2006) Phosphorylation of Hsl1 by Hog1 leads to a G2 arrest essential for cell survival at high osmolarity. EMBO J 25:2338–2346Cook KE, O’Shea EK (2012) Hog1 controls global reallocation of RNA Pol II upon osmotic shock in Saccharomyces cerevisiae. Genes Genomes Genetics 2:1129–1136de Nadal E, Posas F (2015) Osmostress-induced gene expression—a model to understand how stress-activated protein kinases (SAPKs) regulate transcription. FEBS J 282:3275–3285de Nadal E, Alepuz PM, Posas F (2002) Dealing with osmostress through MAP kinase activation. EMBO Rep 3:735–740de Nadal E, Casadome L, Posas F (2003) Targeting the MEF2-like transcription factor Smp1 by the stress-activated Hog1 mitogen-activated protein kinase. Mol Cell Biol 23:229–237de Nadal E, Zapater M, Alepuz PM, Sumoy L, Mas G, Posas F (2004) The MAPK Hog1 recruits Rpd3 histone deacetylase to activate osmoresponsive genes. Nature 427:370–374Duch A, de Nadal E, Posas F (2013a) Dealing with transcriptional outbursts during S phase to protect genomic integrity. J Mol Biol 425:4745–4755Duch A, Felipe-Abrio I, Barroso S, Yaakov G, Garcia-Rubio M, Aguilera A, de Nadal E, Posas F (2013b) Coordinated control of replication and transcription by a SAPK protects genomic integrity. Nature 493:116–119Escote X, Zapater M, Clotet J, Posas F (2004) Hog1 mediates cell-cycle arrest in G1 phase by the dual targeting of Sic1. Nat Cell Biol 6:997–1002Ferreira C, van Voorst F, Martins A, Neves L, Oliveira R, Kielland-Brandt MC, Lucas C, Brandt A (2005) A member of the sugar transporter family, Stl1p is the glycerol/H+ symporter in Saccharomyces cerevisiae. Mol Biol Cell 16:2068–2076Gonzalez R, Morales P, Tronchoni J, Cordero-Bueso G, Vaudano E, Quiros M, Novo M, Torres-Perez R, Valero E (2016) New genes involved in osmotic stress tolerance in Saccharomyces cerevisiae. Front Microbiol 7:1545Ho YH, Gasch AP (2015) Exploiting the yeast stress-activated signaling network to inform on stress biology and disease signaling. Curr Genet 61:503–511Hohmann S (2015) An integrated view on a eukaryotic osmoregulation system. Curr Genet 61:373–382Hohmann S, Krantz M, Nordlander B (2007) Yeast osmoregulation. Methods Enzymol 428:29–45Hong SP, Carlson M (2007) Regulation of snf1 protein kinase in response to environmental stress. J Biol Chem 282:16838–16845Li SC, Diakov TT, Rizzo JM, Kane PM (2012) Vacuolar H+-ATPase works in parallel with the HOG pathway to adapt Saccharomyces cerevisiae cells to osmotic stress. Eukaryot Cell 11:282–291Maeta K, Izawa S, Inoue Y (2005) Methylglyoxal, a metabolite derived from glycolysis, functions as a signal initiator of the high osmolarity glycerol-mitogen-activated protein kinase cascade and calcineurin/Crz1-mediated pathway in Saccharomyces cerevisiae. J Biol Chem 280:253–260Manzanares-Estreder S, Espi-Bardisa J, Alarcon B, Pascual-Ahuir A, Proft M (2017) Multilayered control of peroxisomal activity upon salt stress in Saccharomyces cerevisiae. Mol Microbiol 104:851–868Mao K, Wang K, Zhao M, Xu T, Klionsky DJ (2011) Two MAPK-signaling pathways are required for mitophagy in Saccharomyces cerevisiae. J Cell Biol 193:755–767Martinez-Montanes F, Pascual-Ahuir A, Proft M (2010) Toward a genomic view of the gene expression program regulated by osmostress in yeast. OMICS 14:619–627Martinez-Pastor M, Proft M, Pascual-Ahuir A (2010) Adaptive changes of the yeast mitochondrial proteome in response to salt stress. OMICS 14:541–552Mas G, de Nadal E, Dechant R, Rodriguez de la Concepcion ML, Logie C, Jimeno-Gonzalez S, Chavez S, Ammerer G, Posas F (2009) Recruitment of a chromatin remodelling complex by the Hog1 MAP kinase to stress genes. EMBO J 28:326–336Mettetal JT, Muzzey D, Gomez-Uribe C, van Oudenaarden A (2008) The frequency dependence of osmo-adaptation in Saccharomyces cerevisiae. Science 319:482–484Molin C, Jauhiainen A, Warringer J, Nerman O, Sunnerhagen P (2009) mRNA stability changes precede changes in steady-state mRNA amounts during hyperosmotic stress. RNA 15:600–614Nadal-Ribelles M, Conde N, Flores O, Gonzalez-Vallinas J, Eyras E, Orozco M, de Nadal E, Posas F (2012) Hog1 bypasses stress-mediated down-regulation of transcription by RNA polymerase II redistribution and chromatin remodeling. Genome Biol 13:R106Pastor MM, Proft M, Pascual-Ahuir A (2009) Mitochondrial function is an inducible determinant of osmotic stress adaptation in yeast. J Biol Chem 284:30307–30317Petelenz-Kurdziel E, Kuehn C, Nordlander B, Klein D, Hong KK, Jacobson T, Dahl P, Schaber J, Nielsen J, Hohmann S, Klipp E (2013) Quantitative analysis of glycerol accumulation, glycolysis and growth under hyper osmotic stress. PLoS Comput Biol 9:e1003084Posas F, Chambers JR, Heyman JA, Hoeffler JP, de Nadal E, Arino J (2000) The transcriptional response of yeast to saline stress. J Biol Chem 275:17249–17255Proft M, Struhl K (2002) Hog1 kinase converts the Sko1-Cyc8-Tup1 repressor complex into an activator that recruits SAGA and SWI/SNF in response to osmotic stress. Mol Cell 9:1307–1317Proft M, Struhl K (2004) MAP kinase-mediated stress relief that precedes and regulates the timing of transcriptional induction. Cell 118:351–361Proft M, Pascual-Ahuir A, de Nadal E, Arino J, Serrano R, Posas F (2001) Regulation of the Sko1 transcriptional repressor by the Hog1 MAP kinase in response to osmotic stress. EMBO J 20:1123–1133Proft M, Mas G, de Nadal E, Vendrell A, Noriega N, Struhl K, Posas F (2006) The stress-activated Hog1 kinase is a selective transcriptional elongation factor for genes responding to osmotic stress. Mol Cell 23:241–250Ratnakumar S, Young ET (2010) Snf1 dependence of peroxisomal gene expression is mediated by Adr1. J Biol Chem 285:10703–10714Regot S, de Nadal E, Rodriguez-Navarro S, Gonzalez-Novo A, Perez-Fernandez J, Gadal O, Seisenbacher G, Ammerer G, Posas F (2013) The Hog1 stress-activated protein kinase targets nucleoporins to control mRNA export upon stress. J Biol Chem 288:17384–17398Rep M, Krantz M, Thevelein JM, Hohmann S (2000) The transcriptional response of Saccharomyces cerevisiae to osmotic shock. Hot1p and Msn2p/Msn4p are required for the induction of subsets of high osmolarity glycerol pathway-dependent genes. J Biol Chem 275:8290–8300Rep M, Proft M, Remize F, Tamas M, Serrano R, Thevelein JM, Hohmann S (2001) The Saccharomyces cerevisiae Sko1p transcription factor mediates HOG pathway-dependent osmotic regulation of a set of genes encoding enzymes implicated in protection from oxidative damage. Mol Microbiol 40:1067–1083Rienzo A, Poveda-Huertes D, Aydin S, Buchler NE, Pascual-Ahuir A, Proft M (2015) Different mechanisms confer gradual control and memory at nutrient- and stress-regulated genes in yeast. Mol Cell Biol 35:3669–3683Romero-Santacreu L, Moreno J, Perez-Ortin JE, Alepuz P (2009) Specific and global regulation of mRNA stability during osmotic stress in Saccharomyces cerevisiae. RNA 15:1110–1120Roy A, Hashmi S, Li Z, Dement AD, Cho KH, Kim JH (2016) The glucose metabolite methylglyoxal inhibits expression of the glucose transporter genes by inactivating the cell surface glucose sensors Rgt2 and Snf3 in yeast. Mol Biol Cell 27:862–871Ruiz-Roig C, Noriega N, Duch A, Posas F, de Nadal E (2012) The Hog1 SAPK controls the Rtg1/Rtg3 transcriptional complex activity by multiple regulatory mechanisms. Mol Biol Cell 23:4286–4296Saito H, Posas F (2012) Response to hyperosmotic stress. Genetics 192:289–318Sekito T, Thornton J, Butow RA (2000) Mitochondria-to-nuclear signaling is regulated by the subcellular localization of the transcription factors Rtg1p and Rtg3p. Mol Biol Cell 11:2103–2115Silva RD, Sotoca R, Johansson B, Ludovico P, Sansonetty F, Silva MT, Peinado JM, Corte-Real M (2005) Hyperosmotic stress induces metacaspase- and mitochondria-dependent apoptosis in Saccharomyces cerevisiae. Mol Microbiol 58:824–834Sole C, Nadal-Ribelles M, de Nadal E, Posas F (2015) A novel role for lncRNAs in cell cycle control during stress adaptation. Curr Genet 61:299–308Tamas MJ, Luyten K, Sutherland FC, Hernandez A, Albertyn J, Valadi H, Li H, Prior BA, Kilian SG, Ramos J, Gustafsson L, Thevelein JM, Hohmann S (1999) Fps1p controls the accumulation and release of the compatible solute glycerol in yeast osmoregulation. Mol Microbiol 31:1087–1104Teige M, Scheikl E, Reiser V, Ruis H, Ammerer G (2001) Rck2, a member of the calmodulin-protein kinase family, links protein synthesis to high osmolarity MAP kinase signaling in budding yeast. Proc Natl Acad Sci USA 98:5625–5630Timon-Gomez A, Proft M, Pascual-Ahuir A (2013) Differential regulation of mitochondrial pyruvate carrier genes modulates respiratory capacity and stress tolerance in yeast. PLoS One 8:e79405Vanacloig-Pedros E, Bets-Plasencia C, Pascual-Ahuir A, Proft M (2015) Coordinated gene regulation in the initial phase of salt stress adaptation. J Biol Chem 290:10163–10175Warringer J, Hult M, Regot S, Posas F, Sunnerhagen P (2010) The HOG pathway dictates the short-term translational response after hyperosmotic shock. Mol Biol Cell 21:3080–3092Wei CJ, Tanner RD, Malaney GW (1982) Effect of sodium chloride on bakers’ yeast growing in gelatin. Appl Environ Microbiol 43:757–763Westfall PJ, Patterson JC, Chen RE, Thorner J (2008) Stress resistance and signal fidelity independent of nuclear MAPK function. Proc Natl Acad Sci USA 105:12212–12217Ye T, Garcia-Salcedo R, Ramos J, Hohmann S (2006) Gis4, a new component of the ion homeostasis system in the yeast Saccharomyces cerevisiae. Eukaryot Cell 5:1611–1621Yoshida A, Wei D, Nomura W, Izawa S, Inoue Y (2012) Reduction of glucose uptake through inhibition of hexose transporters and enhancement of their endocytosis by methylglyoxal in Saccharomyces cerevisiae. J Biol Chem 287:701–71

Comparative evaluation of methods for estimating retinal ganglion cell loss in retinal sections and wholemounts

To investigate the reliability of different methods of quantifying retinal ganglion cells (RGCs) in rat retinal sections and wholemounts from eyes with either intact optic nerves or those axotomised after optic nerve crush (ONC). Adult rats received a unilateral ONC and after 21 days the numbers of Brn3a+ , bIII-tubulin+ and Islet-1+ RGCs were quantified in either retinal radial sections or wholemounts in which FluoroGold (FG) was injected 48 h before harvesting. Phenotypic antibody markers were used to distinguish RGCs from astrocytes, macrophages/microglia and amacrine cells. In wholemounted retinae, counts of FG+ and Brn3a+ RGCs were of similar magnitude in eyes with intact optic nerves and were similarly reduced after ONC. Larger differences in RGC number were detected between intact and ONC groups when images were taken closer to the optic nerve head. In radial sections, Brn3a did not stain astrocytes, macrophages/microglia or amacrine cells, whereas βIII-tubulin and Islet-1 did localize to amacrine cells as well as RGCs. The numbers of βIII-tubulin+ RGCs was greater than Brn3a+ RGCs, both in retinae from eyes with intact optic nerves and eyes 21 days after ONC. Islet-1 staining also overestimated the number of RGCs compared to Brn3a, but only after ONC. Estimates of RGC loss were similar in Brn3astained radial retinal sections compared to both Brn3a-stained wholemounts and retinal wholemounts in which RGCs were backfilled with FG, with sections having the added advantage of reducing experimental animal usage

In Vivo Delta Opioid Receptor Internalization Controls Behavioral Effects of Agonists

GPCRs regulate a remarkable diversity of biological functions, and are thus often targeted for drug therapies. Stimulation of a GPCR by an extracellular ligand triggers receptor signaling via G proteins, and this process is highly regulated. Receptor activation is typically accompanied by desensitization of receptor signaling, a complex feedback regulatory process of which receptor internalization is postulated as a key event. The in vivo significance of GPCR internalization is poorly understood. In fact, the majority of studies have been performed in transfected cell systems, which do not adequately model physiological environments and the complexity of integrated responses observed in the whole animal.In this study, we used knock-in mice expressing functional fluorescent delta opioid receptors (DOR-eGFP) in place of the native receptor to correlate receptor localization in neurons with behavioral responses. We analyzed the pain-relieving effects of two delta receptor agonists with similar signaling potencies and efficacies, but distinct internalizing properties. An initial treatment with the high (SNC80) or low (AR-M100390) internalizing agonist equally reduced CFA-induced inflammatory pain. However, subsequent drug treatment produced highly distinct responses. Animals initially treated with SNC80 showed no analgesic response to a second dose of either delta receptor agonist. Concomitant receptor internalization and G-protein uncoupling were observed throughout the nervous system. This loss of function was temporary, since full DOR-eGFP receptor responses were restored 24 hours after SNC80 administration. In contrast, treatment with AR-M100390 resulted in retained analgesic response to a subsequent agonist injection, and ex vivo analysis showed that DOR-eGFP receptor remained G protein-coupled on the cell surface. Finally SNC80 but not AR-M100390 produced DOR-eGFP phosphorylation, suggesting that the two agonists produce distinct active receptor conformations in vivo which likely lead to differential receptor trafficking.Together our data show that delta agonists retain full analgesic efficacy when receptors remain on the cell surface. In contrast, delta agonist-induced analgesia is abolished following receptor internalization, and complete behavioral desensitization is observed. Overall these results establish that, in the context of pain control, receptor localization fully controls receptor function in vivo. This finding has both fundamental and therapeutic implications for slow-recycling GPCRs

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT

Search for the neutral Higgs bosons of the minimal supersymmetric standard model in pp collisions at root s=7 TeV with the ATLAS detector

A search for neutral Higgs bosons of the Minimal Supersymmetric Standard Model (MSSM) is reported. The analysis is based on a sample of proton-proton collisions at a centre-of-mass energy of 7TeV recorded with the ATLAS detector at the Large Hadron Collider. The data were recorded in 2011 and correspond to an integrated luminosity of 4.7 fb-1 to 4.8 fb-1. Higgs boson decays into oppositely-charged muon or τ lepton pairs are considered for final states requiring either the presence or absence of b-jets. No statistically significant excess over the expected background is observed and exclusion limits at the 95% confidence level are derived. The exclusion limits are for the production cross-section of a generic neutral Higgs boson, φ, as a function of the Higgs boson mass and for h/A/H production in the MSSM as a function of the parameters mA and tan β in the mhmax scenario for mA in the range of 90GeV to 500 GeV. Copyright CERN

Search for pair-produced long-lived neutral particles decaying to jets in the ATLAS hadronic calorimeter in ppcollisions at √s=8TeV

The ATLAS detector at the Large Hadron Collider at CERN is used to search for the decay of a scalar boson to a pair of long-lived particles, neutral under the Standard Model gauge group, in 20.3fb−1of data collected in proton–proton collisions at √s=8TeV. This search is sensitive to long-lived particles that decay to Standard Model particles producing jets at the outer edge of the ATLAS electromagnetic calorimeter or inside the hadronic calorimeter. No significant excess of events is observed. Limits are reported on the product of the scalar boson production cross section times branching ratio into long-lived neutral particles as a function of the proper lifetime of the particles. Limits are reported for boson masses from 100 GeVto 900 GeV, and a long-lived neutral particle mass from 10 GeVto 150 GeV

Search for R-parity-violating supersymmetry in events with four or more leptons in sqrt(s) =7 TeV pp collisions with the ATLAS detector

A search for new phenomena in final states with four or more leptons (electrons or muons) is presented. The analysis is based on 4.7 fb−1 of $\sqrt{s}=7\;\mathrm{TeV}$ proton-proton collisions delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with Standard Model expectations in two signal regions: one that requires moderate values of missing transverse momentum and another that requires large effective mass. The results are interpreted in a simplified model of R-parity-violating supersymmetry in which a 95% CL exclusion region is set for charged wino masses up to 540 GeV. In an R-parity-violating MSUGRA/CMSSM model, values of m 1/2 up to 820 GeV are excluded for 10 < tan β < 40