1,815 research outputs found
Stability of the replica symmetric solution for the information conveyed by by a neural network
The information that a pattern of firing in the output layer of a feedforward
network of threshold-linear neurons conveys about the network's inputs is
considered. A replica-symmetric solution is found to be stable for all but
small amounts of noise. The region of instability depends on the contribution
of the threshold and the sparseness: for distributed pattern distributions, the
unstable region extends to higher noise variances than for very sparse
distributions, for which it is almost nonexistant.Comment: 19 pages, LaTeX, 5 figures. Also available at
http://www.mrc-bbc.ox.ac.uk/~schultz/papers.html . Submitted to Phys. Rev. E
Minor change
Positive feedback induces switch between distributive and processive phosphorylation of Hog1
Cellular decision making often builds on ultrasensitive MAPK pathways. The phosphorylation mechanism of MAP kinase has so far been described as either distributive or processive, with distributive mechanisms generating ultrasensitivity in theoretical analyses. However, the in vivo mechanism of MAP kinase phosphorylation and its activation dynamics remain unclear. Here, we characterize the regulation of the MAP kinase Hog1 in Saccharomyces cerevisiae via topologically different ODE models, parameterized on multimodal activation data. Interestingly, our best fitting model switches between distributive and processive phosphorylation behavior regulated via a positive feedback loop composed of an affinity and a catalytic component targeting the MAP kinase-kinase Pbs2. Indeed, we show that Hog1 directly phosphorylates Pbs2 on serine 248 (S248), that cells expressing a non-phosphorylatable (S248A) or phosphomimetic (S248E) mutant show behavior that is consistent with simulations of disrupted or constitutively active affinity feedback and that Pbs2-S248E shows significantly increased affinity to Hog1 in vitro. Simulations further suggest that this mixed Hog1 activation mechanism is required for full sensitivity to stimuli and to ensure robustness to different perturbations.© 2023. The Author(s)
Statistical distribution of quantum entanglement for a random bipartite state
We compute analytically the statistics of the Renyi and von Neumann entropies
(standard measures of entanglement), for a random pure state in a large
bipartite quantum system. The full probability distribution is computed by
first mapping the problem to a random matrix model and then using a Coulomb gas
method. We identify three different regimes in the entropy distribution, which
correspond to two phase transitions in the associated Coulomb gas. The two
critical points correspond to sudden changes in the shape of the Coulomb charge
density: the appearance of an integrable singularity at the origin for the
first critical point, and the detachement of the rightmost charge (largest
eigenvalue) from the sea of the other charges at the second critical point.
Analytical results are verified by Monte Carlo numerical simulations. A short
account of some of these results appeared recently in Phys. Rev. Lett. {\bf
104}, 110501 (2010).Comment: 7 figure
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 EconomÃa 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
Modular Control Plane Implementation for Disaggregated Optical Transport Networks with Multi-band Support
This demo paper presents the B5G-OPEN control plane modular architecture designed to enable dynamic control of multi-band disaggregated optical networks through open-source software and standard interfaces. Such control plane will be demonstrated in a distributed testbed including real IPoWDM nodes, ROADMs and transponders
A recovery-explicit error estimator in energy norm for linear elasticity
[EN] Significant research effort has been devoted to produce one-sided error estimates for Finite Element Analyses, in particular to provide upper bounds of the actual error. Typically, this has been achieved using residual-type estimates. One of the most popular and simpler (in terms of implementation) techniques used in commercial codes is the recovery-based error estimator. This technique produces accurate estimations of the exact error but is not designed to naturally produce upper bounds of the error in energy norm.
Some attempts to remedy this situation provide bounds depending on unknown constants. Here, a new step towards obtaining error bounds from the recovery-based estimates is proposed. The idea is (1) to use a locally equilibrated recovery technique to obtain an accurate estimation of the exact error, (2) to add an explicit-type error bound of the lack of equilibrium of the recovered stresses in order to guarantee a bound of the actual error and (3) to efficiently and accurately evaluate the constants appearing in the bounding expressions, thus providing asymptotic bounds. The numerical tests with h-adaptive refinement process show that the bounding property holds even for coarse meshes, providing upper bounds in practical applications.The authors also thank the support of the Framework Programme 7 Initial Training Network Funding under grant number 289361 "Integrating Numerical Simulation and Geometric Design Technology".Nadal Soriano, E.; DÃez, P.; Ródenas, J.; Tur Valiente, M.; Fuenmayor Fernández, FJ. (2015). A recovery-explicit error estimator in energy norm for linear elasticity. Computer Methods in Applied Mechanics and Engineering. 287:172-190. https://doi.org/10.1016/j.cma.2015.01.013S17219028
Computing Naturally in the Billiard Ball Model
Fredkin's Billiard Ball Model (BBM) is considered one of the fundamental
models of collision-based computing, and it is essentially based on elastic
collisions of mobile billiard balls. Moreover, fixed mirrors or reflectors are
brought into the model to deflect balls to complete the computation. However,
the use of fixed mirrors is "physically unrealistic" and makes the BBM not
perfectly momentum conserving from a physical point of view, and it imposes an
external architecture onto the computing substrate which is not consistent with
the concept of "architectureless" in collision-based computing. In our initial
attempt to reduce mirrors in the BBM, we present a class of gates: the
m-counting gate, and show that certain circuits can be realized with few
mirrors using this gate. We envisage that our findings can be useful in future
research of collision-based computing in novel chemical and optical computing
substrates.Comment: 10 pages, 7 figure
Circulating CD5L is associated with cardiovascular events and all-cause mortality in individuals with chronic kidney disease
This study assessed the association of CD5L and soluble CD36 (sCD36) with the risk of a cardiovascular event (CVE), including CV death and all-cause mortality in CKD. We evaluated the association of CD5L and sCD36 with a predefined composite CV endpoint (unstable angina, myocardial infarction, transient ischemic attack, cerebrovascular accident, congestive heart failure, arrhythmia, peripheral arterial disease [PAD] or amputation by PAD, aortic aneurysm, or death from CV causes) and all-cause mortality using Cox proportional hazards regression, adjusted for CV risk factors. The analysis included 1,516 participants free from pre-existing CV disease followed up for 4 years. The median age was 62 years, 38.8% were female, and 26.8% had diabetes. There were 98 (6.5%) CVEs and 72 (4.8%) deaths, of which 26 (36.1%) were of CV origin. Higher baseline CD5L concentration was associated with increased risk of CVE (HR, 95% CI, 1.17, 1.0-1.36), and all-cause mortality (1.22, 1.01-1.48) after adjusting for age, sex, diabetes, systolic blood pressure, dyslipidemia, waist circumference, smoking, and CKD stage. sCD36 showed no association with adverse CV outcomes or mortality. Our study showed for the first time that higher concentrations of CD5L are associated with future CVE and all-cause mortality in individuals with CKD
Prediabetes is independently associated with subclinical carotid atherosclerosis : An observational study in a non-urban mediterranean population
This was a prospective, observational study to compare the burden of subclinical atherosclerosis as measured by carotid ultrasonography in a cohort of subjects with prediabetes vs. subjects with normal glucose tolerance (NGT) from a non-urban Mediterranean population. Atherosclerosis was assessed through carotid intima-media thickness (c-IMT), the presence/absence of carotid plaques, and plaque number. Among 550 subjects included, 224 (40.7%) had prediabetes. The mean c-IMT and the prevalence of carotid plaque were significantly higher in the prediabetes group compared to the NGT group (0.72 vs. 0.67 mm, p < 0.001; and 37.9% vs. 19.6%; p < 0.001, respectively). Older age, male gender, and increased systolic blood pressure were positively correlated with c-IMT and were independent predictors of the presence of plaques. In contrast, prediabetes and low-density lipoprotein (LDL)-c were predictors of the presence of plaque (odds ratio [OR] = 1.64; 95% confidence interval [CI] = 1.05-2.57; p = 0.03 and OR = 1.01; 95% CI = 1.00-1.02; p = 0.006, respectively) together with tobacco exposure and the leukocyte count (OR = 1.77; 95% CI = 1.08-2.89; p = 0.023 and OR = 1.20; 95% CI = 1.05-1.38; p = 0.008, respectively). In a non-urban Mediterranean population, prediabetes was associated with established subclinical carotid atherosclerosis. These findings could have implications for the prevention and treatment of CV risk in these subjects before the first symptoms of cardiovascular disease appear
Structure of the Homodimeric androgen receptor ligand-binding domain
The androgen receptor (AR) plays a crucial role in normal physiology, development and metabolism as well as in the aetiology and treatment of diverse pathologies such as androgen insensitivity syndromes (AIS), male infertility and prostate cancer (PCa). Here we show that dimerization of AR ligand-binding domain (LBD) is induced by receptor agonists but not by antagonists. The 2.15-Ã… crystal structure of homodimeric, agonist- and coactivator peptide-bound AR-LBD unveils a 1,000-Ã…2 large dimerization surface, which harbours over 40 previously unexplained AIS- and PCa-associated point mutations. An AIS mutation in the self-association interface (P767A) disrupts dimer formation in vivo, and has a detrimental effect on the transactivating properties of full-length AR, despite retained hormone-binding capacity. The conservation of essential residues suggests that the unveiled dimerization mechanism might be shared by other nuclear receptors. Our work defines AR-LBD homodimerization as an essential step in the proper functioning of this important transcription factor
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