Measurement of the top-quark mass in tt¯ events with dilepton final states in pp collisions at √s = 7 TeV

Open Access: This article is distributed under the terms of the Creative Commons Attribution License.-- Chatrchyan, S. et al.The top-quark mass is measured in proton-proton collisions at s√=7 TeV using a data sample corresponding to an integrated luminosity of 5.0 fb−1 collected by the CMS experiment at the LHC. The measurement is performed in the dilepton decay channel tt¯→(ℓ+νℓb)(ℓ−ν¯¯ℓb¯), where ℓ=e,μ. Candidate top-quark decays are selected by requiring two leptons, at least two jets, and imbalance in transverse momentum. The mass is reconstructed with an analytical matrix weighting technique using distributions derived from simulated samples. Using a maximum-likelihood fit, the top-quark mass is determined to be 172.5±0.4 (stat.)±1.5 (syst.) GeV.Acknowledge support from BMWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES (Croatia); RPF (Cyprus); MoER, SF0690030s09 and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France);BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NKTH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); NRF and WCU (Korea); LAS (Lithuania); CINVESTAV, CONACYT, SEP, and UASLP-FAI (Mexico); MSI (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Armenia, Belarus, Georgia, Ukraine, Uzbekistan); MON, RosAtom, RAS and RFBR (Russia); MSTD (Serbia); SEIDI and CPAN (Spain); Swiss Funding Agencies (Switzerland); NSC (Taipei); ThEP, IPST and NECTEC (Thailand); TUBITAK and TAEK (Turkey); NASU (Ukraine); STFC (United Kingdom); DOE and NSF (USA). Individuals have received support from the Marie-Curie program and the European Research Council (European Union); the Leventis Foundation; the A. P. Sloan Foundation; the Alexander von Humboldt Foundation; the Austrian Science Fund (FWF); the Belgian Federal Science Policy Office; the Fonds pour la Formation à la Recherche dans l’Industrie et dans l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWTBelgium); the Ministry of Education, Youth and Sports (MEYS) of Czech Republic; the Council of Science and Industrial Research, India; the Compagnia di San Paolo (Torino); and the HOMING PLUS program of Foundation for Polish Science, cofinanced from European Union, Regional Development Fund.Peer Reviewe

Comparative effects of glimepiride and glibenclamide on blood glucose, C-peptide and insulin concentrations in the fasting and postprandial state in normal man

A single-center, randomised, placebo- controlled, crossover study was conducted to characterize the new sulfonylurea glimepiride and to compare its profile of action with the second generation sulfonylurea glibenclamide. The total duration of each experiment was 5 hours. At zero time an i.v. injection of 2 and 4 mg glimepiride, 1 mg glibenclamide or placebo was given IV to 24 healthy volunteers. Blood samples were collected for three hours after the injection (0-3 hours, preprandial experiment). At 3 hours, a standard mixed meal was given (20% of a 30 Kcal/Kg Body Weight diet) and blood samples were collected for 2 more hours (postprandial experiment). Pre-prandially (0-3 hrs) blood glucose (expressed as the area under the curve divided by the time) was significantly lower (p < 0.0001) after the administration of 2 and 4 mg glimepiride (3.8 +/- 0.22 and 3.5 +/- 10.3 mM respectively) compared to placebo (4.63 +/- 0.31 mM), but not compared to glibenclamide. Insulin and C-peptide were not different after glimepiride or glibenclamide. Both glimepiride and glibenclamide had similar effects on insulin secretion. Post-prandially (3-5 hrs) blood glucose was significantly higher after glibenclamide (6.54 +/- 0.8 mM) (p < 0.0001) than after 2 mg glimepiride (5.75 +/- 0.5 mM). Despite this C-peptide was significantly higher (p < 0.002) glibendamide (5.7 +/- 1.5 ng/ml) compared to glimepiride (5.1 +/- 1.3 ng/ml); the trend was the same for insulin but the results were not significantly different (p = 0.06) In conclusion, in the fasting state, glimepiride and glibenclamide had similar effects on the changes in blood glucose levels after TV administration. After the meal, less pronounced hyperglycemia and lower insulin and C-peptide levels following glimepiride (2 mg) suggests either that glimepiride induces insulin secretion through a pathway which is different from that of glibenclamide or that glimepiride facilitates insulin action through extrapancreatic effects

Curvularin-Type Metabolites from the Fungus Curvularia sp. Isolated from a Marine Alga

Two new curvularin-type macrolides, curvulone A (1) and B (2), and two known ones (3a, 4) of the rare 15R series have been isolated from the fungus Curvularia sp., which has been isolated from the marine alga Gracilaria folifera. Their structures were determined by extensive 2D NMR experiments and supported by the single-crystal X-ray analysis of 1. The structural elucidation of 1, which has a benzo[b]furanone moiety as part of a 12-membered macrolactone, has led to a revision of the structure of the previously reported (11S,15S)-11β-hydroxy-12-oxocurvularin. The absolute configuration of curvulone A was established independently by the solid-state TD-DFT ECD method and by measuring the anomalous dispersion effect. The absolute configuration of curvulone B was determined by TD-DFT ECD calculations on the computed solution conformers. Two different solid-state conformers of 4 were identified by X-ray analysis of the single crystals obtained from different solvents; TD-DFT ECD calculations were performed to reproduce the experimental ECD spectra. All four metabolites were biologically active against fungal, bacterial and algal test organisms

Systematic discovery of uncharacterized transcription factors in Escherichia coli K-12 MG1655

Transcriptional regulation enables cells to respond to environmental changes. Of the estimated 304 candidate transcription factors (TFs) in Escherichia coli K-12 MG1655, 185 have been experimentally identified, but ChIP methods have been used to fully characterize only a few dozen. Identifying these remaining TFs is key to improving our knowledge of the E. coli transcriptional regulatory network (TRN). Here, we developed an integrated workflow for the computational prediction and comprehensive experimental validation of TFs using a suite of genome-wide experiments. We applied this workflow to (i) identify 16 candidate TFs from over a hundred uncharacterized genes; (ii) capture a total of 255 DNA binding peaks for ten candidate TFs resulting in six high-confidence binding motifs; (iii) reconstruct the regulons of these ten TFs by determining gene expression changes upon deletion of each TF and (iv) identify the regulatory roles of three TFs (YiaJ, YdcI, and YeiE) as regulators of L-ascorbate utilization, proton transfer and acetate metabolism, and iron homeostasis under iron-limited conditions, respectively. Together, these results demonstrate how this workflow can be used to discover, characterize, and elucidate regulatory functions of uncharacterized TFs in parallel