The article addresses factors that allowed large Russian companies to withstand the economic crisis, as well as prospects for their business expansion in the post-crisis setting. While anti-crisis policies adopted by Russian government supported big business substantially during the first months of the recession, they hardly played any pro-business role since mid-2009. The analysis of capitalization figures and sales volumes shows that leading positions of state-owned companies in oil, gas and financial sectors were in fact strengthened during the crisis. Excessive state control over corporate assets and decision-making works as a barrier to post-crisis recovery of large Russian companies and should be substituted for by policies supporting internationalization strategies and productivity improvements.
A 2 inch, cold-leg loss-of-coolant accident (LOCA) in a 900 MWe generic Western PWR was simulated using ASTEC 2.1.1 and MAAP 5.02. The progression of the accident predicted by the two codes up to the time of vessel failure is compared. It includes the primary system depressurization, accumulator discharge, core heat-up, hydrogen generation, core relocation to lower plenum, and lower head breach. The purpose of the code comparison exercise is to identify modelling differences between the two codes and the user choices affecting the results. The two codes predict similar primary system depressurization behaviour until the accumulation injection, confirming similar break flow and primary system thermal-hydraulic response calculations between the two codes. The choice of the accumulator gas expansion model, either isentropic or isothermal, affects the rate and total amount of coolant injected and thereby determines whether the core is quenched or overheated and attains a noncoolable geometry during reflooding. A sensitivity case was additionally simulated by each code to allow comparisons to be made with either accumulator gas expansion models. The two codes predict similar amount of in-vessel hydrogen generated and core quench status for a given accumulator gas expansion model. ASTEC predicts much larger initial core relocation to lower plenum leading to an earlier vessel failure time. MAAP predicts more gradual core relocation to lower plenum, prolonging the lower plenum debris bed heat-up and time to vessel failure. Beside the effect of the code user in conducting severe accident simulations, some discrepancies are found in the modelling approaches in each code. The biggest differences are found in the in-vessel melt progression and relocation into the lower plenum, which deserve further research to reduce the uncertainties.
OBJECTIVES: Recently, autoantibodies directed against muscarinic type 3 receptor (M3R) have been reported in patients with primary SS. However, the precise epitope(s) of the M3R that interacts with SS autoantibodies remains unclear. The aim of this study was to identify the functional epitope of M3R which interacts with SS immunoglobulin G (IgG). METHODS: Purified IgGs were obtained from the sera of seven SS patients (six primary and one secondary SS) and two normal persons. We examined whether SS IgG inhibits M3R function and identified the epitope using six synthetic peptides covering all the extracellular domains of M3R by microspectrofluorimetry and surface plasmon resonance-based optical biosensor system (BIAcore system). RESULTS: A volume of 0.5 mg/ml SS IgG inhibited carbachol (CCh)-induced [Ca(2+)](i) transient (CICT) in human submandibular gland (HSG) cells. However, co-incubation of SS IgG with the 6th peptide (514-527 amino acid region) corresponding to the third extracellular loop of M3R, recovered CICT. The result was further confirmed by BIAcore analysis. We found that the 6th peptide interacts with IgGs from three primary SS patients in a concentration-dependent manner. The synthetic peptide which consists of amino acids 228-237 corresponding to the COOH-terminus of the second extracellular loop of M3R also bound to SS IgG. However, normal IgGs did not interact with the 6th peptide. CONCLUSIONS: The results suggest that the third extracellular loop of M3R represents a functional epitope bound by SS IgG, and thereby partly inhibits M3R function. ; This work was supported by the Korea Research Foundation Grant funded by the Korean Government(MOEHRD KRF-2005-015-E00207).
16 páginas, 5 figuras ; Genetic discoveries of Alzheimer's disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer's disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer's disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer's disease. ; The present work has been performed as part of the doctoral program of I. de Rojas at the Universitat de Barcelona (Barcelona, Spain) supported by national grant from the Instituto de Salud Carlos III FI20/00215. The Genome Research @ Fundació ACE project (GR@ACE) is supported by Grifols SA, Fundación bancaria "La Caixa", Fundació ACE, and CIBERNED. A.R. and M.B. receive support from the European Union/EFPIA Innovative Medicines Initiative Joint undertaking ADAPTED and MOPEAD projects (grant numbers 115975 and 115985, respectively). M.B. and A.R. are also supported by national grants PI13/02434, PI16/01861, PI17/01474, PI19/01240 and PI19/01301. Acción Estratégica en Salud is integrated into the Spanish National R + D + I Plan and funded by ISCIII (Instituto de Salud Carlos III)—Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (FEDER—"Una manera de hacer Europa"). Some control samples and data from patients included in this study were provided in part by the National DNA Bank Carlos III (www.bancoadn.org, University of Salamanca, Spain) and Hospital Universitario Virgen de Valme (Sevilla, Spain); they were processed following standard operating procedures with the appropriate approval of the Ethical and Scientific Committee. Amsterdam dementia Cohort (ADC): Research of the Alzheimer center Amsterdam is part of the neurodegeneration research program of Amsterdam Neuroscience. The Alzheimer Center Amsterdam is supported by Stichting Alzheimer Nederland and Stichting VUmc fonds. The clinical database structure was developed with funding from Stichting Dioraphte. Genotyping of the Dutch case-control samples was performed in the context of EADB (European Alzheimer DNA biobank) funded by the JPco-fuND FP-829-029 (ZonMW project number 733051061). 100-Plus study: We are grateful for the collaborative efforts of all participating centenarians and their family members and/or relations. This work was supported by Stichting Alzheimer Nederland (WE09.2014-03), Stichting Diorapthe, horstingstuit foundation, Memorabel (ZonMW project number 733050814, 733050512) and Stichting VUmc Fonds. Genotyping of the 100-Plus Study was performed in the context of EADB (European Alzheimer DNA biobank) funded by the JPco-fuND FP-829-029 (ZonMW project number 733051061). Longitudinal Aging Study Amsterdam (LASA) is largely supported by a grant from the Netherlands Ministry of Health, Welfare and Sports, Directorate of Long-Term Care. The authors are grateful to all LASA participants, the fieldwork team and all researchers for their ongoing commitment to the study. This work was supported by a grant (European Alzheimer DNA BioBank, EADB) from the EU Joint Program—Neurodegenerative Disease Research (JPND) and also funded by Inserm, Institut Pasteur de Lille, the Lille Métropole Communauté Urbaine, the French government's LABEX DISTALZ program (development of innovative strategies for a transdisciplinary approach to AD). Genotyping of the German case-control samples was performed in the context of EADB (European Alzheimer DNA biobank) funded by the JPco-fuND (German Federal Ministry of Education and Research, BMBF: 01ED1619A). Full acknowledgments for the studies that contributed data can be found in the Supplementary Note. We thank the numerous participants, researchers, and staff from many studies who collected and contributed to the data. We thank the International Genomics of Alzheimer's Project (IGAP) for providing summary results data for these analyses. The investigators within IGAP contributed to the design and implementation of IGAP and/or provided data but did not participate in analysis or writing of this report. IGAP was made possible by the generous participation of the control subjects, the patients, and their families. The i–Select chips was funded by the French National Foundation on AD and related disorders. EADI was supported by the LABEX (laboratory of excellence program investment for the future) DISTALZ grant, Inserm, Institut Pasteur de Lille, Université de Lille 2 and the Lille University Hospital. GERAD was supported by the Medical Research Council (Grant n° 503480), Alzheimer's Research UK (Grant n° 503176), the Wellcome Trust (Grant n° 082604/2/07/Z) and German Federal Ministry of Education and Research (BMBF): Competence Network Dementia (CND) grant n° 01GI0102, 01GI0711, 01GI0420. CHARGE was partly supported by the NIA/NHLBI grants AG049505, AG058589, HL105756 and AGES contract N01–AG–12100, the Icelandic Heart Association, and the Erasmus Medical Center and Erasmus University. ADGC was supported by the NIH/NIA grants: U01 AG032984, U24 AG021886, U01 AG016976, and the Alzheimer's Association grant ADGC–10–196728. This research has been conducted using the UK Biobank public resource obtained through the University of Edinburg Data Share (https://datashare.is.ed.ac.uk/handle/10283/3364). ; Peer reviewed
ANPCyT, Argentina ; YerPhI, Armenia ; ARC, Australia ; BMWFW, Austria ; FWF, Austria ; ANAS, Azerbaijan ; SSTC, Belarus ; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) ; Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) ; NSERC, Canada ; NRC, Canada ; CFI, Canada ; CERN ; CONICYT, Chile ; CAS, China ; MOST, China ; NSFC, China ; COLCIENCIAS, Colombia ; MSMT CR, Czech Republic ; MPO CR, Czech Republic ; VSC CR, Czech Republic ; DNRF, Denmark ; DNSRC, Denmark ; IN2P3-CNRS, CEA-DRF/IRFU, France ; SRNSFG, Georgia ; BMBF, Germany ; HGF, Germany ; MPG, Germany ; GSRT, Greece ; RGC, Hong Kong SAR, China ; ISF, Israel ; Benoziyo Center, Israel ; INFN, Italy ; MEXT, Japan ; JSPS, Japan ; CNRST, Morocco ; NWO, Netherlands ; RCN, Norway ; MNiSW, Poland ; NCN, Poland ; FCT, Portugal ; MNE/IFA, Romania ; MES of Russia, Russian Federation ; NRC KI, Russian Federation ; JINR ; MESTD, Serbia ; MSSR, Slovakia ; ARRS, Slovenia ; MIZS, Slovenia ; DST/NRF, South Africa ; MINECO, Spain ; SRC, Sweden ; Wallenberg Foundation, Sweden ; SERI, Switzerland ; SNSF, Switzerland ; Canton of Bern, Switzerland ; MOST, Taiwan ; TAEK, Turkey ; STFC, United Kingdom ; DOE, United States of America ; NSF, United States of America ; BCKDF, Canada ; CANARIE, Canada ; CRC, Canada ; Compute Canada, Canada ; COST, European Union ; ERC, European Union ; ERDF, European Union ; Horizon 2020, European Union ; Marie Sk lodowska-Curie Actions, European Union ; Investissements d' Avenir Labex and Idex, ANR, France ; DFG, Germany ; AvH Foundation, Germany ; Greek NSRF, Greece ; BSF-NSF, Israel ; GIF, Israel ; CERCA Programme Generalitat de Catalunya, Spain ; Royal Society, United Kingdom ; Leverhulme Trust, United Kingdom ; BMBWF (Austria) ; FWF (Austria) ; FNRS (Belgium) ; FWO (Belgium) ; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) ; Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) ; FAPERGS (Brazil) ; MES (Bulgaria) ; CAS (China) ; MoST (China) ; NSFC (China) ; COLCIENCIAS (Colombia) ; MSES (Croatia) ; CSF (Croatia) ; RPF (Cyprus) ; SENESCYT (Ecuador) ; MoER (Estonia) ; ERC IUT (Estonia) ; ERDF (Estonia) ; Academy of Finland (Finland) ; MEC (Finland) ; HIP (Finland) ; CEA (France) ; CNRS/IN2P3 (France) ; BMBF (Germany) ; DFG (Germany) ; HGF (Germany) ; GSRT (Greece) ; NKFIA (Hungary) ; DAE (India) ; DST (India) ; IPM (Iran) ; SFI (Ireland) ; INFN (Italy) ; MSIP (Republic of Korea) ; NRF (Republic of Korea) ; MES (Latvia) ; LAS (Lithuania) ; MOE (Malaysia) ; UM (Malaysia) ; BUAP (Mexico) ; CINVESTAV (Mexico) ; CONACYT (Mexico) ; LNS (Mexico) ; SEP (Mexico) ; UASLP-FAI (Mexico) ; MOS (Montenegro) ; MBIE (New Zealand) ; PAEC (Pakistan) ; MSHE (Poland) ; NSC (Poland) ; FCT (Portugal) ; JINR (Dubna) ; MON (Russia) ; RosAtom (Russia) ; RAS (Russia) ; RFBR (Russia) ; NRC KI (Russia) ; MESTD (Serbia) ; SEIDI (Spain) ; CPAN (Spain) ; PCTI (Spain) ; FEDER (Spain) ; MOSTR (Sri Lanka) ; MST (Taipei) ; ThEPCenter (Thailand) ; IPST (Thailand) ; STAR (Thailand) ; NSTDA (Thailand) ; TAEK (Turkey) ; NASU (Ukraine) ; SFFR (Ukraine) ; STFC (United Kingdom ; DOE (U.S.A.) ; NSF (U.S.A.) ; Marie-Curie programme ; Horizon 2020 Grant (European Union) ; Leventis Foundation ; A.P. Sloan Foundation ; Alexander von Humboldt Foundation ; Belgian Federal Science Policy Office ; Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium) ; Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium) ; F.R.S.-FNRS (Belgium) ; Beijing Municipal Science & Technology Commission ; Ministry of Education, Youth and Sports (MEYS) of the Czech Republic ; Hungarian Academy of Sciences (Hungary) ; New National Excellence Program UNKP (Hungary) ; Council of Science and Industrial Research, India ; HOMING PLUS programme of the Foundation for Polish Science ; European Union, Regional Development Fund ; Mobility Plus programme of the Ministry of Science and Higher Education ; National Science Center (Poland) ; National Priorities Research Program by Qatar National Research Fund ; Programa Estatal de Fomento de la Investigacion Cientfica y Tecnica de Excelencia Maria de Maeztu ; Programa Severo Ochoa del Principado de Asturias ; EU-ESF ; Greek NSRF ; Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University (Thailand) ; Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand) ; Welch Foundation ; Weston Havens Foundation (U.S.A.) ; Canton of Geneva, Switzerland ; Herakleitos programme ; Thales programme ; Aristeia programme ; European Research Council (European Union) ; Horizon 2020 Grant (European Union): 675440 ; FWO (Belgium): 30820817 ; Beijing Municipal Science & Technology Commission: Z181100004218003 ; NKFIA (Hungary): 123842 ; NKFIA (Hungary): 123959 ; NKFIA (Hungary): 124845 ; NKFIA (Hungary): 124850 ; NKFIA (Hungary): 125105 ; National Science Center (Poland): Harmonia 2014/14/M/ST2/00428 ; National Science Center (Poland): Opus 2014/13/B/ST2/02543 ; National Science Center (Poland): 2014/15/B/ST2/03998 ; National Science Center (Poland): 2015/19/B/ST2/02861 ; National Science Center (Poland): Sonata-bis 2012/07/E/ST2/01406 ; Programa Estatal de Fomento de la Investigacion Cientfica y Tecnica de Excelencia Maria de Maeztu: MDM-2015-0509 ; Welch Foundation: C-1845 ; This paper presents the combinations of single-top-quark production cross-section measurements by the ATLAS and CMS Collaborations, using data from LHC proton-proton collisions at = 7 and 8 TeV corresponding to integrated luminosities of 1.17 to 5.1 fb(-1) at = 7 TeV and 12.2 to 20.3 fb(-1) at = 8 TeV. These combinations are performed per centre-of-mass energy and for each production mode: t-channel, tW, and s-channel. The combined t-channel cross-sections are 67.5 +/- 5.7 pb and 87.7 +/- 5.8 pb at = 7 and 8 TeV respectively. The combined tW cross-sections are 16.3 +/- 4.1 pb and 23.1 +/- 3.6 pb at = 7 and 8 TeV respectively. For the s-channel cross-section, the combination yields 4.9 +/- 1.4 pb at = 8 TeV. The square of the magnitude of the CKM matrix element V-tb multiplied by a form factor f(LV) is determined for each production mode and centre-of-mass energy, using the ratio of the measured cross-section to its theoretical prediction. It is assumed that the top-quark-related CKM matrix elements obey the relation |V-td|, |V-ts| « |V-tb|. All the |f(LV)V(tb)|(2) determinations, extracted from individual ratios at = 7 and 8 TeV, are combined, resulting in |f(LV)V(tb)| = 1.02 +/- 0.04 (meas.) +/- 0.02 (theo.). All combined measurements are consistent with their corresponding Standard Model predictions.