BBF RFC 105: The Intein standard - a universal way to modify proteins after translation

This Request for Comments (RFC) proposes a new standard that allows for easy and flexible cloning of intein constructs and thus makes this technology accessible to the synthetic biology community

Liquid–Liquid Equilibria of Systems with Linear Aldehydes. Experimental Data and Modeling with PCP-SAFT

Liquid–liquid equilibrium (LLE) data were measured for the binary system propylene carbonate/decane (288.15 to 403.15 K) as well as for the ternary systems propylene carbonate/decane + linear aldehyde (C4, C8, C10, C12, C13) and DMF/decane + linear aldehyde (C4, C8, C10, C13) at 298.15 K using the analytic method. The reliability of the ternary LLE data is ascertained by employing Othmer–Tobias plots. Concerning the aldehyde distribution coefficients in the ternary systems, a distinctive dependency on the chain length of the aldehyde was observed. The LLE data were modeled with the Perturbed Chain Polar Statistical Associating Fluid Theory (PCP-SAFT) equation of state using a heterosegmented approach for describing the aldehyde molecules

Hydroformylation of 1‑Dodecene in the Thermomorphic Solvent System Dimethylformamide/Decane. Phase Behavior–Reaction Performance–Catalyst Recycling

An economically meaningful hydroformylation of long-chain olefins requires an efficient combination of both a high-yield reaction step and efficient catalyst recycling. The application of thermomorphic multicomponent solvent (TMS) systems allows for optimal reaction as well as catalyst-recycling conditions. In this work, the TMS concept was applied to the homogeneously rhodium-catalyzed hydroformylation of 1-dodecene in the TMS system dimethylformamide (DMF)/decane using Rh­(acac)­(CO)₂/Biphephos as the catalyst system. Thermodynamic investigations focused on the influence of the olefin (hydroformulation educt) and the aldehyde (hydroformylation product) on the phase behavior of the TMS system. Temperature dependent liquid–liquid equilibrium (LLE) data were measured for the binary systems DMF/decane and DMF/1-dodecene and for the ternary systems DMF/decane/1-dodecene and DMF/decane/dodecanal. Additionally, the corresponding LLE data were modeled applying the Perturbed Chain Polar Statistical Associating Fluid Theory (PCP-SAFT) using a heterosegmented approach for modeling the long-chain aldehyde. On the basis of the LLE data, adequate working points for hydroformylation experiments in the TMS system were selected. In these experiments, aldehyde yields of up to 87% with an n/iso ratio of up to 99:1 were achieved. Moreover, the TMS system was successfully applied to catalyst recycling in eight recycling runs with a catalyst leaching of 7 ppm rhodium at lowest

Association of BMI, lipid-lowering medication, and age with prevalence of type 2 diabetes in adults with heterozygous familial hypercholesterolaemia: a worldwide cross-sectional study

Background: Statins are the cornerstone treatment for patients with heterozygous familial hypercholesterolaemia but research suggests it could increase the risk of type 2 diabetes in the general population. A low prevalence of type 2 diabetes was reported in some familial hypercholesterolaemia cohorts, raising the question of whether these patients are protected against type 2 diabetes. Obesity is a well known risk factor for the development of type 2 diabetes. We aimed to investigate the associations of known key determinants of type 2 diabetes with its prevalence in people with heterozygous familial hypercholesterolaemia. Methods: This worldwide cross-sectional study used individual-level data from the EAS FHSC registry and included adults older than 18 years with a clinical or genetic diagnosis of heterozygous familial hypercholesterolaemia who had data available on age, BMI, and diabetes status. Those with known or suspected homozygous familial hypercholesterolaemia and type 1 diabetes were excluded. The main outcome was prevalence of type 2 diabetes overall and by WHO region, and in relation to obesity (BMI ≥30·0 kg/m2) and lipid-lowering medication as predictors. The study population was divided into 12 risk categories based on age (tertiles), obesity, and receiving statins, and the risk of type 2 diabetes was investigated using logistic regression. Findings: Among 46 683 adults with individual-level data in the FHSC registry, 24 784 with heterozygous familial hypercholesterolaemia were included in the analysis from 44 countries. 19 818 (80%) had a genetically confirmed diagnosis of heterozygous familial hypercholesterolaemia. Type 2 diabetes prevalence in the total population was 5·7% (1415 of 24 784), with 4·1% (817 of 19 818) in the genetically diagnosed cohort. Higher prevalence of type 2 diabetes was observed in the Eastern Mediterranean (58 [29·9%] of 194), South-East Asia and Western Pacific (214 [12·0%] of 1785), and the Americas (166 [8·5%] of 1955) than in Europe (excluding the Netherlands; 527 [8·0%] of 6579). Advancing age, a higher BMI category (obesity and overweight), and use of lipid-lowering medication were associated with a higher risk of type 2 diabetes, independent of sex and LDL cholesterol. Among the 12 risk categories, the probability of developing type 2 diabetes was higher in people in the highest risk category (aged 55-98 years, with obesity, and receiving statins; OR 74·42 [95% CI 47·04-117·73]) than in those in the lowest risk category (aged 18-38 years, without obesity, and not receiving statins). Those who did not have obesity, even if they were in the upper age tertile and receiving statins, had lower risk of type 2 diabetes (OR 24·42 [15·57-38·31]). The corresponding results in the genetically diagnosed cohort were OR 65·04 (40·67-104·02) for those with obesity in the highest risk category and OR 20·07 (12·73-31·65) for those without obesity. Interpretation: Adults with heterozygous familial hypercholesterolaemia in most WHO regions have a higher type 2 diabetes prevalence than in Europe. Obesity markedly increases the risk of diabetes associated with age and use of statins in these patients. Our results suggest that heterozygous familial hypercholesterolaemia does not protect against type 2 diabetes, hence managing obesity is essential to reduce type 2 diabetes in this patient population. Funding: Pfizer, Amgen, MSD, Sanofi-Aventis, Daiichi-Sankyo, and Regeneron

A deep neural network to search for new long-lived particles decaying to jets

International audienceA tagging algorithm to identify jets that are significantly displaced from the proton-proton (pp) collision region in the CMS detector at the LHC is presented. Displaced jets can arise from the decays of long-lived particles (LLPs), which are predicted by several theoretical extensions of the standard model. The tagger is a multiclass classifier based on a deep neural network, which is parameterised according to the proper decay length $\mathrm{c}\tau_0$ of the LLP. A novel scheme is defined to reliably label jets from LLP decays for supervised learning. Samples of pp collision data, recorded by the CMS detector at a centre-of-mass energy of 13 TeV, and simulated events are used to train the neural network. Domain adaptation by backward propagation is performed to improve the simulation modelling of the jet class probability distributions observed in pp collision data. The potential performance of the tagger is demonstrated with a search for long-lived gluinos, a manifestation of split supersymmetric models. The tagger provides a rejection factor of 10 000 for jets from standard model processes, while maintaining an LLP jet tagging efficiency of 30-80% for gluinos with 1 mm $\leq$ $c\tau_0$ $\leq$ 10 m. The expected coverage of the parameter space for split supersymmetry is presented

Search for supersymmetry in hadronic final states with missing transverse energy using the variables αT and b-quark multiplicity in pp collisions at √s = 8 TeV

Submitted by Vitor Silverio Rodrigues ([email protected]) on 2014-05-27T11:30:34Z No. of bitstreams: 0Bitstream added on 2014-05-27T14:48:49Z : No. of bitstreams: 1 2-s2.0-84883824987.pdf: 1540579 bytes, checksum: be6bbff5192436d9fcdbc367ffd1650e (MD5) Made available in DSpace on 2014-05-27T11:30:34Z (GMT). No. of bitstreams: 0 Previous issue date: 2013-09-01 An inclusive search for supersymmetric processes that produce final states with jets and missing transverse energy is performed in pp collisions at a centre-of-mass energy of 8 TeV. The data sample corresponds to an integrated luminosity of 11.7 fb-1 collected by the CMS experiment at the LHC. In this search, a dimensionless kinematic variable, αT, is used to discriminate between events with genuine and misreconstructed missing transverse energy. The search is based on an examination of the number of reconstructed jets per event, the scalar sum of transverse energies of these jets, and the number of these jets identified as originating from bottom quarks. No significant excess of events over the standard model expectation is found. Exclusion limits are set in the parameter space of simplified models, with a special emphasis on both compressed-spectrum scenarios and direct or gluino-induced production of third-generation squarks. For the case of gluino-mediated squark production, gluino masses up to 950-1125 GeV are excluded depending on the assumed model. For the direct pair-production of squarks, masses up to 450 GeV are excluded for a single light first- or second-generation squark, increasing to 600 GeV for bottom squarks. © 2013 CERN for the benefit of the CMS collaboration. CERN, Geneva Yerevan Physics Institute, Yerevan Institut für Hochenergiephysik der OeAW, Wien National Centre for Particle and High Energy Physics, Minsk Universiteit Antwerpen, Antwerpen Vrije Universiteit Brussel, Brussel Université Libre de Bruxelles, Bruxelles Ghent University, Ghent Université Catholique de Louvain, Louvain-la-Neuve Université de Mons, Mons Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro Universidade do Estado do Rio de Janeiro, Rio de Janeiro Universidade Estadual Paulista, São Paulo Universidade Federal do ABC, São Paulo Institute for Nuclear Research and Nuclear Energy, Sofia University of Sofia, Sofia Institute of High Energy Physics, Beijing State Key Laboratory of Nuclear Physics and Technology Peking University, Beijing Universidad de Los Andes, Bogota Technical University of Split, Split University of Split, Split Institute Rudjer Boskovic, Zagreb University of Cyprus, Nicosia Charles University, Prague Academy of Scientific Research and Technology of the Arab Republic of Egypt Egyptian Network of High Energy Physics, Cairo National Institute of Chemical Physics and Biophysics, Tallinn Department of Physics University of Helsinki, Helsinki Helsinki Institute of Physics, Helsinki Lappeenranta University of Technology, Lappeenranta DSM/IRFU CEA/Saclay, Gif-sur-Yvette Laboratoire Leprince-Ringuet, Ecole Polytechnique IN2P3-CNRS, Palaiseau Institut Pluridisciplinaire Hubert Curien, Universite de Strasbourg, Universite de Haute Alsace Mulh CNRS/IN2P3, Strasbourg CNRS-IN2P3, Institut de Physique Nucléaire de Lyon Université de Lyon, Université Claude Bernard Lyon 1, Villeurbanne Institute of High Energy Physics and Informatization Tbilisi State University, Tbilisi I. Physikalisches Institut RWTH Aachen University, Aachen III. Physikalisches Institut A RWTH Aachen University, Aachen III. Physikalisches Institut B RWTH Aachen University, Aachen Deutsches Elektronen-Synchrotron, Hamburg University of Hamburg, Hamburg Institut für Experimentelle Kernphysik, Karlsruhe Institute of Nuclear and Particle Physics (INPP) NCSR Demokritos, Aghia Paraskevi University of Athens, Athens University of Ioánnina, Ioánnina KFKI Research Institute for Particle and Nuclear Physics, Budapest Institute of Nuclear Research ATOMKI, Debrecen University of Debrecen, Debrecen Panjab University, Chandigarh University of Delhi, Delhi Saha Institute of Nuclear Physics, Kolkata Bhabha Atomic Research Centre, Mumbai Tata Institute of Fundamental Research - EHEP, Mumbai Tata Institute of Fundamental Research - HECR, Mumbai Institute for Research in Fundamental Sciences (IPM), Tehran INFN Sezione di Bari, Bari Università di Bari, Bari Politecnico di Bari, Bari INFN Sezione di Bologna, Bologna Università di Bologna, Bologna INFN Sezione di Catania, Catania Università di Catania, Catania INFN Sezione di Firenze, Firenze Università di Firenze, Firenze INFN Laboratori Nazionali di Frascati, Frascati INFN Sezione di Genova, Genova Università di Genova, Genova INFN Sezione di Milano-Bicocca, Milano Università di Milano-Bicocca, Milano INFN Sezione di Napoli, Napoli Università di Napoli 'Federico II', Napoli Università della Basilicata (Potenza), Napoli Università G. Marconi (Roma), Napoli INFN Sezione di Padova, Padova Università di Padova, Padova Università di Trento (Trento), Padova INFN Sezione di Pavia, Pavia Università di Pavia, Pavia INFN Sezione di Perugia, Perugia Università di Perugia, Perugia INFN Sezione di Pisa, Pisa Università di Pisa, Pisa Scuola Normale Superiore di Pisa, Pisa INFN Sezione di Roma, Roma Università di Roma, Roma INFN Sezione di Torino, Torino Università di Torino, Torino Università del Piemonte Orientale (Novara), Torino INFN Sezione di Trieste, Trieste Università di Trieste, Trieste Kangwon National University, Chunchon Kyungpook National University, Daegu Institute for Universe and Elementary Particles Chonnam National University, Kwangju Korea University, Seoul University of Seoul, Seoul Sungkyunkwan University, Suwon Vilnius University, Vilnius Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City Universidad Iberoamericana, Mexico City Benemerita Universidad Autonoma de Puebla, Puebla Universidad Autónoma de San Luis Potosí, San Luis Potosí University of Auckland, Auckland University of Canterbury, Christchurch National Centre for Physics Quaid-I-Azam University, Islamabad National Centre for Nuclear Research, Swierk Institute of Experimental Physics, Faculty of Physics University of Warsaw, Warsaw Laboratório de Instrumentação e Física Experimental de Partículas, Lisboa Joint Institute for Nuclear Research, Dubna Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg) Institute for Nuclear Research, Moscow Institute for Theoretical and Experimental Physics, Moscow P.N. Lebedev Physical Institute, Moscow Skobeltsyn Institute of Nuclear Physics Lomonosov Moscow State University, Moscow State Research Center of Russian Federation Institute for High Energy Physics, Protvino Faculty of Physics and Vinca Institute of Nuclear Sciences University of Belgrade, Belgrade Centro de Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid Universidad Autónoma de Madrid, Madrid Universidad de Oviedo, Oviedo Instituto de Física de Cantabria (IFCA) CSIC-Universidad de Cantabria, Santander European Organization for Nuclear Research CERN, Geneva Paul Scherrer Institut, Villigen Institute for Particle Physics ETH Zurich, Zurich Universität Zürich, Zurich National Central University, Chung-Li National Taiwan University (NTU), Taipei Chulalongkorn University, Bangkok Cukurova University, Adana Physics Department Middle East Technical University, Ankara Bogazici University, Istanbul Istanbul Technical University, Istanbul National Scientific Center Kharkov Institute of Physics and Technology, Kharkov University of Bristol, Bristol Rutherford Appleton Laboratory, Didcot Imperial College, London Brunel University, Uxbridge Baylor University, Waco The University of Alabama, Tuscaloosa Boston University, Boston Brown University, Providence University of California, Davis, Davis University of California, Los Angeles University of California, Riverside, Riverside University of California, San Diego, La Jolla University of California, Santa Barbara, Santa Barbara California Institute of Technology, Pasadena Carnegie Mellon University, Pittsburgh University of Colorado at Boulder, Boulder Cornell University, Ithaca Fairfield University, Fairfield Fermi National Accelerator Laboratory, Batavia University of Florida, Gainesville Florida International University, Miami Florida State University, Tallahassee Florida Institute of Technology, Melbourne University of Illinois at Chicago (UIC), Chicago The University of Iowa, Iowa City Johns Hopkins University, Baltimore The University of Kansas, Lawrence Kansas State University, Manhattan Lawrence Livermore National Laboratory, Livermore University of Maryland, College Park Massachusetts Institute of Technology, Cambridge University of Minnesota, Minneapolis University of Mississippi, Oxford University of Nebraska-Lincoln, Lincoln State University of New York at Buffalo, Buffalo Northeastern University, Boston Northwestern University, Evanston University of Notre Dame, Notre Dame The Ohio State University, Columbus Princeton University, Princeton University of Puerto Rico, Mayaguez Purdue University, West Lafayette Purdue University Calumet, Hammond Rice University, Houston University of Rochester, Rochester The Rockefeller University, New York Rutgers The State University of New Jersey, Piscataway University of Tennessee, Knoxville Texas A and M University, College Station Texas Tech University, Lubbock Vanderbilt University, Nashville University of Virginia, Charlottesville Wayne State University, Detroit University of Wisconsin, Madison Universidade Estadual Paulista, São Paul

Search for high-mass resonances decaying to a jet and a Lorentz-boosted resonance in proton-proton collisions at $\sqrt{s}=13\text{ }\text{ }\mathrm{TeV}

Physics letters / B 832, 137263 (2022). doi:10.1016/j.physletb.2022.137263 Published by North-Holland Publ., Amsterda