1,327 research outputs found

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

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

    Get PDF
    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 s=7  TeV \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

    Search for high-mass resonances decaying to dilepton final states in pp collisions at s√=7 TeV with the ATLAS detector

    Get PDF
    The ATLAS detector at the Large Hadron Collider is used to search for high-mass resonances decaying to an electron-positron pair or a muon-antimuon pair. The search is sensitive to heavy neutral Z′ gauge bosons, Randall-Sundrum gravitons, Z * bosons, techni-mesons, Kaluza-Klein Z/γ bosons, and bosons predicted by Torsion models. Results are presented based on an analysis of pp collisions at a center-of-mass energy of 7 TeV corresponding to an integrated luminosity of 4.9 fb−1 in the e + e − channel and 5.0 fb−1 in the μ + μ −channel. A Z ′ boson with Standard Model-like couplings is excluded at 95 % confidence level for masses below 2.22 TeV. A Randall-Sundrum graviton with coupling k/MPl=0.1 is excluded at 95 % confidence level for masses below 2.16 TeV. Limits on the other models are also presented, including Technicolor and Minimal Z′ Models

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

    Get PDF
    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

    Get PDF
    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

    Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

    Get PDF
    We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

    Lipid profile, cardiovascular disease and mortality in a Mediterranean high-risk population: the ESCARVAL-RISK study

    Get PDF
    The potential impact of targeting different components of an adverse lipid profile in populations with multiple cardiovascular risk factors is not completely clear. This study aims to assess the association between different components of the standard lipid profile with all cause mortality and hospitalization due to cardiovascular events in a high-risk population. Methods This prospective registry included high risk adults over 30 years old free of cardiovascular disease (2008±2012). Diagnosis of hypertension, dyslipidemia or diabetes mellitus was inclusion criterion. Lipid biomarkers were evaluated. Primary endpoints were all-cause mortality and hospital admission due to coronary heart disease or stroke. We estimated adjusted rate ratios (aRR), absolute risk differences and population attributable risk associated with adverse lipid profiles. Results 51,462 subjects were included with a mean age of 62.6 years (47.6% men). During an average follow-up of 3.2 years, 919 deaths, 1666 hospitalizations for coronary heart disease and 1510 hospitalizations for stroke were recorded. The parameters that showed an increased rate for total mortality, coronary heart disease and stroke hospitalization were, respectively, low HDL-Cholesterol: aRR 1.25, 1.29 and 1.23; high Total/HDL-Cholesterol: aRR 1.22, 1.38 and 1.25; and high Triglycerides/HDL-Cholesterol: aRR 1.21, 1.30, 1.09. The parameters that showed highest population attributable risk (%) were, respectively, low HDL-Cholesterol: 7.70, 11.42, 8.40; high Total/HDL-Cholesterol: 6.55, 12.47, 8.73; and high Triglycerides/ HDL-Cholesterol: 8.94, 15.09, 6.92. Conclusions In a population with cardiovascular risk factors, HDL-cholesterol, Total/HDL-cholesterol and triglycerides/HDL-cholesterol ratios were associated with a higher population attributable risk for cardiovascular disease compared to other common biomarkers

    The French national prospective cohort of patients co-infected with HIV and HCV (ANRS CO13 HEPAVIH): Early findings, 2006-2010

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>In France, it is estimated that 24% of HIV-infected patients are also infected with HCV. Longitudinal studies addressing clinical and public health questions related to HIV-HCV co-infection (HIV-HCV clinical progression and its determinants including genetic dimension, patients' experience with these two diseases and their treatments) are limited. The ANRS CO 13 HEPAVIH cohort was set up to explore these critical questions.</p> <p>To describe the cohort aims and organization, monitoring and data collection procedures, baseline characteristics, as well as follow-up findings to date.</p> <p>Methods</p> <p>Inclusion criteria in the cohort were: age > 18 years, HIV-1 infection, chronic hepatitis C virus (HCV) infection or sustained response to HCV treatment. A standardized medical questionnaire collecting socio-demographic, clinical, biological, therapeutic, histological, ultrasound and endoscopic data is administered at enrolment, then every six months for cirrhotic patients or yearly for non-cirrhotic patients. Also, a self-administered questionnaire documenting socio-behavioral data and adherence to HIV and/or HCV treatments is administered at enrolment and yearly thereafter.</p> <p>Results</p> <p>A total of 1,175 patients were included from January 2006 to December 2008. Their median age at enrolment was 45 years and 70.2% were male. The median CD4 cell count was 442 (IQR: 304-633) cells/μl and HIV RNA plasma viral load was undetectable in 68.8%. Most participants (71.6%) were on HAART. Among the 1,048 HIV-HCV chronically co-infected patients, HCV genotype 1 was predominant (56%) and cirrhosis was present in 25%. As of January, 2010, after a median follow-up of 16.7 months (IQR: 11.3-25.3), 13 new cases of decompensated cirrhosis, nine hepatocellular carcinomas and 20 HCV-related deaths were reported, resulting in a cumulative HCV-related severe event rate of 1.9/100 person-years (95% CI: 1.3-2.5). The rate of HCV-related severe events was higher in cirrhotic patients and those with a low CD4 cells count, but did not differ according to sex, age, alcohol consumption, CDC clinical stage or HCV status.</p> <p>Conclusion</p> <p>The ANRS CO 13 HEPAVIH is a nation-wide cohort using a large network of HIV treatment, infectious diseases and internal medicine clinics in France, and thus is highly representative of the French population living with these two viruses and in care.</p

    The bHLH transcription factor SPATULA enables cytokinin signaling, and both activate auxin biosynthesis and transport genes at the medial domain of the gynoecium

    Get PDF
    [EN] Fruits and seeds are the major food source on earth. Both derive from the gynoecium and, therefore, it is crucial to understand the mechanisms that guide the development of this organ of angiosperm species. In Arabidopsis, the gynoecium is composed of two congenitally fused carpels, where two domains: medial and lateral, can be distinguished. The medial domain includes the carpel margin meristem (CMM) that is key for the production of the internal tissues involved in fertilization, such as septum, ovules, and transmitting tract. Interestingly, the medial domain shows a high cytokinin signaling output, in contrast to the lateral domain, where it is hardly detected. While it is known that cytokinin provides meristematic properties, understanding on the mechanisms that underlie the cytokinin signaling pattern in the young gynoecium is lacking. Moreover, in other tissues, the cytokinin pathway is often connected to the auxin pathway, but we also lack knowledge about these connections in the young gynoecium. Our results reveal that cytokinin signaling, that can provide meristematic properties required for CMM activity and growth, is enabled by the transcription factor SPATULA (SPT) in the medial domain. Meanwhile, cytokinin signaling is confined to the medial domain by the cytokinin response repressor ARABIDOPSIS HISTIDINE PHOSPHOTRANSFERASE 6 (AHP6), and perhaps by ARR16 (a type-A ARR) as well, both present in the lateral domains (presumptive valves) of the developing gynoecia. Moreover, SPT and cytokinin, probably together, promote the expression of the auxin biosynthetic gene TRYPTOPHAN AMINOTRANSFERASE OF ARABIDOPSIS 1 (TAA1) and the gene encoding the auxin efflux transporter PIN-FORMED 3 (PIN3), likely creating auxin drainage important for gynoecium growth. This study provides novel insights in the spatiotemporal determination of the cytokinin signaling pattern and its connection to the auxin pathway in the young gynoecium.IRO, VMZM, HHU and PLS were supported by the Mexican National Council of Science and Technology (CONACyT) with a PhD fellowship (210085, 210100, 243380 and 219883, respectively). Work in the SDF laboratory was financed by the CONACyT grants CB-2012-177739, FC-2015-2/1061, and INFR-2015-253504, and NMM by the CONACyT grant CB-2011-165986. SDF, CF and LC acknowledge the support of the European Union FP7-PEOPLE-2009-IRSES project EVOCODE (grant no. 247587) and H2020-MSCARISE-2015 project ExpoSEED (grant no. 691109). SDF also acknowledges the Marine Biological Laboratory (MBL) in Woods Hole for a scholarship for the Gene Regulatory Networks for Development Course 2015 (GERN2015). IE acknowledges the International European Fellowship-METMADS project and the Universita degli Studi di Milano (RTD-A; 2016). Research in the laboratory of MFY was funded by NSF (grant IOS-1121055), NIH (grant 1R01GM112976-01A1) and the Paul D. Saltman Endowed Chair in Science Education (MFY). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Reyes Olalde, J.; Zuñiga, V.; Serwatowska, J.; Chávez Montes, R.; Lozano-Sotomayor, P.; Herrera-Ubaldo, H.; Gonzalez Aguilera, K.... (2017). The bHLH transcription factor SPATULA enables cytokinin signaling, and both activate auxin biosynthesis and transport genes at the medial domain of the gynoecium. PLoS Genetics. 13(4):1-31. https://doi.org/10.1371/journal.pgen.1006726S131134Reyes-Olalde, J. I., Zuñiga-Mayo, V. M., Chávez Montes, R. A., Marsch-Martínez, N., & de Folter, S. (2013). Inside the gynoecium: at the carpel margin. Trends in Plant Science, 18(11), 644-655. doi:10.1016/j.tplants.2013.08.002Alvarez-Buylla, E. R., Benítez, M., Corvera-Poiré, A., Chaos Cador, Á., de Folter, S., Gamboa de Buen, A., … Sánchez-Corrales, Y. E. (2010). Flower Development. The Arabidopsis Book, 8, e0127. doi:10.1199/tab.0127Bowman, J. L., Baum, S. F., Eshed, Y., Putterill, J., & Alvarez, J. (1999). 4 Molecular Genetics of Gynoecium Development in Arabidopsis. Current Topics in Developmental Biology Volume 45, 155-205. doi:10.1016/s0070-2153(08)60316-6Chávez Montes, R. A., Herrera-Ubaldo, H., Serwatowska, J., & de Folter, S. (2015). Towards a comprehensive and dynamic gynoecium gene regulatory network. Current Plant Biology, 3-4, 3-12. doi:10.1016/j.cpb.2015.08.002Marsch-Martínez, N., & de Folter, S. (2016). Hormonal control of the development of the gynoecium. Current Opinion in Plant Biology, 29, 104-114. doi:10.1016/j.pbi.2015.12.006Marsch-Martínez, N., Ramos-Cruz, D., Irepan Reyes-Olalde, J., Lozano-Sotomayor, P., Zúñiga-Mayo, V. M., & de Folter, S. (2012). The role of cytokinin during Arabidopsis gynoecia and fruit morphogenesis and patterning. The Plant Journal, 72(2), 222-234. doi:10.1111/j.1365-313x.2012.05062.xZhao, Z., Andersen, S. U., Ljung, K., Dolezal, K., Miotk, A., Schultheiss, S. J., & Lohmann, J. U. (2010). Hormonal control of the shoot stem-cell niche. Nature, 465(7301), 1089-1092. doi:10.1038/nature09126Ashikari, M. (2005). Cytokinin Oxidase Regulates Rice Grain Production. Science, 309(5735), 741-745. doi:10.1126/science.1113373Bartrina, I., Otto, E., Strnad, M., Werner, T., & Schmülling, T. (2011). Cytokinin Regulates the Activity of Reproductive Meristems, Flower Organ Size, Ovule Formation, and Thus Seed Yield in Arabidopsis thaliana. The Plant Cell, 23(1), 69-80. doi:10.1105/tpc.110.079079Hwang, I., Sheen, J., & Müller, B. (2012). Cytokinin Signaling Networks. Annual Review of Plant Biology, 63(1), 353-380. doi:10.1146/annurev-arplant-042811-105503Schaller, G. E., Bishopp, A., & Kieber, J. J. (2015). The Yin-Yang of Hormones: Cytokinin and Auxin Interactions in Plant Development. The Plant Cell, 27(1), 44-63. doi:10.1105/tpc.114.133595Kieber, J. J., & Schaller, G. E. (2010). The Perception of Cytokinin: A Story 50 Years in the Making: Figure 1. Plant Physiology, 154(2), 487-492. doi:10.1104/pp.110.161596Long, J. A., Moan, E. I., Medford, J. I., & Barton, M. K. (1996). A member of the KNOTTED class of homeodomain proteins encoded by the STM gene of Arabidopsis. Nature, 379(6560), 66-69. doi:10.1038/379066a0Jasinski, S., Piazza, P., Craft, J., Hay, A., Woolley, L., Rieu, I., … Tsiantis, M. (2005). KNOX Action in Arabidopsis Is Mediated by Coordinate Regulation of Cytokinin and Gibberellin Activities. Current Biology, 15(17), 1560-1565. doi:10.1016/j.cub.2005.07.023Yanai, O., Shani, E., Dolezal, K., Tarkowski, P., Sablowski, R., Sandberg, G., … Ori, N. (2005). Arabidopsis KNOXI Proteins Activate Cytokinin Biosynthesis. Current Biology, 15(17), 1566-1571. doi:10.1016/j.cub.2005.07.060Scofield, S., Dewitte, W., Nieuwland, J., & Murray, J. A. H. (2013). The Arabidopsis homeobox gene SHOOT MERISTEMLESS has cellular and meristem-organisational roles with differential requirements for cytokinin and CYCD3 activity. The Plant Journal, 75(1), 53-66. doi:10.1111/tpj.12198Gordon, S. P., Chickarmane, V. S., Ohno, C., & Meyerowitz, E. M. (2009). Multiple feedback loops through cytokinin signaling control stem cell number within the Arabidopsis shoot meristem. Proceedings of the National Academy of Sciences, 106(38), 16529-16534. doi:10.1073/pnas.0908122106Chickarmane, V. S., Gordon, S. P., Tarr, P. T., Heisler, M. G., & Meyerowitz, E. M. (2012). Cytokinin signaling as a positional cue for patterning the apical-basal axis of the growing Arabidopsis shoot meristem. Proceedings of the National Academy of Sciences, 109(10), 4002-4007. doi:10.1073/pnas.1200636109Leibfried, A., To, J. P. C., Busch, W., Stehling, S., Kehle, A., Demar, M., … Lohmann, J. U. (2005). WUSCHEL controls meristem function by direct regulation of cytokinin-inducible response regulators. Nature, 438(7071), 1172-1175. doi:10.1038/nature04270Werner, T., Motyka, V., Laucou, V., Smets, R., Van Onckelen, H., & Schmülling, T. (2003). Cytokinin-Deficient Transgenic Arabidopsis Plants Show Multiple Developmental Alterations Indicating Opposite Functions of Cytokinins in the Regulation of Shoot and Root Meristem Activity. The Plant Cell, 15(11), 2532-2550. doi:10.1105/tpc.014928Larsson, E., Franks, R. G., & Sundberg, E. (2013). Auxin and the Arabidopsis thaliana gynoecium. Journal of Experimental Botany, 64(9), 2619-2627. doi:10.1093/jxb/ert099Weijers, D., & Wagner, D. (2016). Transcriptional Responses to the Auxin Hormone. Annual Review of Plant Biology, 67(1), 539-574. doi:10.1146/annurev-arplant-043015-112122Robert, H. S., Crhak Khaitova, L., Mroue, S., & Benková, E. (2015). The importance of localized auxin production for morphogenesis of reproductive organs and embryos inArabidopsis. Journal of Experimental Botany, 66(16), 5029-5042. doi:10.1093/jxb/erv256Kuusk, S., Sohlberg, J. J., Magnus Eklund, D., & Sundberg, E. (2006). Functionally redundantSHIfamily genes regulate Arabidopsis gynoecium development in a dose-dependent manner. The Plant Journal, 47(1), 99-111. doi:10.1111/j.1365-313x.2006.02774.xSohlberg, J. J., Myrenås, M., Kuusk, S., Lagercrantz, U., Kowalczyk, M., Sandberg, G., & Sundberg, E. (2006). STY1regulates auxin homeostasis and affects apical-basal patterning of the Arabidopsis gynoecium. The Plant Journal, 47(1), 112-123. doi:10.1111/j.1365-313x.2006.02775.xStåldal, V., Sohlberg, J. J., Eklund, D. M., Ljung, K., & Sundberg, E. (2008). Auxin can act independently ofCRC,LUG,SEU,SPTandSTY1in style development but not apical-basal patterning of theArabidopsisgynoecium. New Phytologist, 180(4), 798-808. doi:10.1111/j.1469-8137.2008.02625.xVan Gelderen, K., van Rongen, M., Liu, A., Otten, A., & Offringa, R. (2016). An INDEHISCENT-Controlled Auxin Response Specifies the Separation Layer in Early Arabidopsis Fruit. Molecular Plant, 9(6), 857-869. doi:10.1016/j.molp.2016.03.005José Ripoll, J., Bailey, L. J., Mai, Q.-A., Wu, S. L., Hon, C. T., Chapman, E. J., … Yanofsky, M. F. (2015). microRNA regulation of fruit growth. Nature Plants, 1(4). doi:10.1038/nplants.2015.36Larsson, E., Roberts, C. J., Claes, A. R., Franks, R. G., & Sundberg, E. (2014). Polar Auxin Transport Is Essential for Medial versus Lateral Tissue Specification and Vascular-Mediated Valve Outgrowth in Arabidopsis Gynoecia. Plant Physiology, 166(4), 1998-2012. doi:10.1104/pp.114.245951Nole-Wilson, S., Azhakanandam, S., & Franks, R. G. (2010). Polar auxin transport together with AINTEGUMENTA and REVOLUTA coordinate early Arabidopsis gynoecium development. Developmental Biology, 346(2), 181-195. doi:10.1016/j.ydbio.2010.07.016De Folter, S. (2016). Auxin Is Required for Valve Margin Patterning in Arabidopsis After All. Molecular Plant, 9(6), 768-770. doi:10.1016/j.molp.2016.05.005Moubayidin, L., & Østergaard, L. (2014). Dynamic Control of Auxin Distribution Imposes a Bilateral-to-Radial Symmetry Switch during Gynoecium Development. Current Biology, 24(22), 2743-2748. doi:10.1016/j.cub.2014.09.080Girin, T., Paicu, T., Stephenson, P., Fuentes, S., Körner, E., O’Brien, M., … Østergaard, L. (2011). INDEHISCENT and SPATULA Interact to Specify Carpel and Valve Margin Tissue and Thus Promote Seed Dispersal in Arabidopsis. The Plant Cell, 23(10), 3641-3653. doi:10.1105/tpc.111.090944Ioio, R. D., Nakamura, K., Moubayidin, L., Perilli, S., Taniguchi, M., Morita, M. T., … Sabatini, S. (2008). A Genetic Framework for the Control of Cell Division and Differentiation in the Root Meristem. Science, 322(5906), 1380-1384. doi:10.1126/science.1164147Bishopp, A., Help, H., El-Showk, S., Weijers, D., Scheres, B., Friml, J., … Helariutta, Y. (2011). A Mutually Inhibitory Interaction between Auxin and Cytokinin Specifies Vascular Pattern in Roots. Current Biology, 21(11), 917-926. doi:10.1016/j.cub.2011.04.017De Rybel, B., Adibi, M., Breda, A. S., Wendrich, J. R., Smit, M. E., Novák, O., … Weijers, D. (2014). Integration of growth and patterning during vascular tissue formation in Arabidopsis. Science, 345(6197), 1255215. doi:10.1126/science.1255215Pernisova, M., Klima, P., Horak, J., Valkova, M., Malbeck, J., Soucek, P., … Hejatko, J. (2009). Cytokinins modulate auxin-induced organogenesis in plants via regulation of the auxin efflux. Proceedings of the National Academy of Sciences, 106(9), 3609-3614. doi:10.1073/pnas.0811539106Cheng, Z. J., Wang, L., Sun, W., Zhang, Y., Zhou, C., Su, Y. H., … Zhang, X. S. (2012). Pattern of Auxin and Cytokinin Responses for Shoot Meristem Induction Results from the Regulation of Cytokinin Biosynthesis by AUXIN RESPONSE FACTOR3. Plant Physiology, 161(1), 240-251. doi:10.1104/pp.112.203166Alvarez, J., & Smyth, D. R. (2002). CRABS CLAWandSPATULAGenes Regulate Growth and Pattern Formation during Gynoecium Development inArabidopsis thaliana. International Journal of Plant Sciences, 163(1), 17-41. doi:10.1086/324178Groszmann, M., Bylstra, Y., Lampugnani, E. R., & Smyth, D. R. (2010). Regulation of tissue-specific expression of SPATULA, a bHLH gene involved in carpel development, seedling germination, and lateral organ growth in Arabidopsis. Journal of Experimental Botany, 61(5), 1495-1508. doi:10.1093/jxb/erq015Smyth, D. R., Bowman, J. L., & Meyerowitz, E. M. (1990). Early flower development in Arabidopsis. The Plant Cell, 2(8), 755-767. doi:10.1105/tpc.2.8.755Müller, B., & Sheen, J. (2008). Cytokinin and auxin interaction in root stem-cell specification during early embryogenesis. Nature, 453(7198), 1094-1097. doi:10.1038/nature06943Argyros, R. D., Mathews, D. E., Chiang, Y.-H., Palmer, C. M., Thibault, D. M., Etheridge, N., … Schaller, G. E. (2008). Type B Response Regulators of Arabidopsis Play Key Roles in Cytokinin Signaling and Plant Development. The Plant Cell, 20(8), 2102-2116. doi:10.1105/tpc.108.059584Mason, M. G., Mathews, D. E., Argyros, D. A., Maxwell, B. B., Kieber, J. J., Alonso, J. M., … Schaller, G. E. (2005). Multiple Type-B Response Regulators Mediate Cytokinin Signal Transduction in Arabidopsis. The Plant Cell, 17(11), 3007-3018. doi:10.1105/tpc.105.035451Ishida, K., Yamashino, T., Yokoyama, A., & Mizuno, T. (2008). Three Type-B Response Regulators, ARR1, ARR10 and ARR12, Play Essential but Redundant Roles in Cytokinin Signal Transduction Throughout the Life Cycle of Arabidopsis thaliana. Plant and Cell Physiology, 49(1), 47-57. doi:10.1093/pcp/pcm165Yokoyama, A., Yamashino, T., Amano, Y.-I., Tajima, Y., Imamura, A., Sakakibara, H., & Mizuno, T. (2006). Type-B ARR Transcription Factors, ARR10 and ARR12, are Implicated in Cytokinin-Mediated Regulation of Protoxylem Differentiation in Roots of Arabidopsis thaliana. Plant and Cell Physiology, 48(1), 84-96. doi:10.1093/pcp/pcl040Schuster, C., Gaillochet, C., & Lohmann, J. U. (2015). Arabidopsis HECATE genes function in phytohormone control during gynoecium development. Development, 142(19), 3343-3350. doi:10.1242/dev.120444Toledo-Ortiz, G., Huq, E., & Quail, P. H. (2003). The Arabidopsis Basic/Helix-Loop-Helix Transcription Factor Family. The Plant Cell, 15(8), 1749-1770. doi:10.1105/tpc.013839Reymond, M. C., Brunoud, G., Chauvet, A., Martínez-Garcia, J. F., Martin-Magniette, M.-L., Monéger, F., & Scutt, C. P. (2012). A Light-Regulated Genetic Module Was Recruited to Carpel Development in Arabidopsis following a Structural Change to SPATULA. The Plant Cell, 24(7), 2812-2825. doi:10.1105/tpc.112.097915Ballester, P., Navarrete-Gómez, M., Carbonero, P., Oñate-Sánchez, L., & Ferrándiz, C. (2015). Leaf expansion in Arabidopsis is controlled by a TCP-NGA regulatory module likely conserved in distantly related species. Physiologia Plantarum, 155(1), 21-32. doi:10.1111/ppl.12327Hellens, R., Allan, A., Friel, E., Bolitho, K., Grafton, K., Templeton, M., … Laing, W. (2005). Plant Methods, 1(1), 13. doi:10.1186/1746-4811-1-13Makkena, S., & Lamb, R. S. (2013). The bHLH transcription factor SPATULA regulates root growth by controlling the size of the root meristem. BMC Plant Biology, 13(1), 1. doi:10.1186/1471-2229-13-1Stepanova, A. N., Robertson-Hoyt, J., Yun, J., Benavente, L. M., Xie, D.-Y., Doležal, K., … Alonso, J. M. (2008). TAA1-Mediated Auxin Biosynthesis Is Essential for Hormone Crosstalk and Plant Development. Cell, 133(1), 177-191. doi:10.1016/j.cell.2008.01.047Bhargava, A., Clabaugh, I., To, J. P., Maxwell, B. B., Chiang, Y.-H., Schaller, G. E., … Kieber, J. J. (2013). Identification of Cytokinin-Responsive Genes Using Microarray Meta-Analysis and RNA-Seq in Arabidopsis. Plant Physiology, 162(1), 272-294. doi:10.1104/pp.113.217026Sakai, H., Aoyama, T., & Oka, A. (2000). Arabidopsis ARR1 and ARR2 response regulators operate as transcriptional activators. The Plant Journal, 24(6), 703-711. doi:10.1046/j.1365-313x.2000.00909.xSakai, H. (2001). ARR1, a Transcription Factor for Genes Immediately Responsive to Cytokinins. Science, 294(5546), 1519-1521. doi:10.1126/science.1065201Moubayidin, L., Di Mambro, R., Sozzani, R., Pacifici, E., Salvi, E., Terpstra, I., … Sabatini, S. (2013). Spatial Coordination between Stem Cell Activity and Cell Differentiation in the Root Meristem. Developmental Cell, 26(4), 405-415. doi:10.1016/j.devcel.2013.06.025Benková, E., Michniewicz, M., Sauer, M., Teichmann, T., Seifertová, D., Jürgens, G., & Friml, J. (2003). Local, Efflux-Dependent Auxin Gradients as a Common Module for Plant Organ Formation. Cell, 115(5), 591-602. doi:10.1016/s0092-8674(03)00924-3Okada, K., Ueda, J., Komaki, M. K., Bell, C. J., & Shimura, Y. (1991). Requirement of the Auxin Polar Transport System in Early Stages of Arabidopsis Floral Bud Formation. The Plant Cell, 677-684. doi:10.1105/tpc.3.7.677Blilou, I., Xu, J., Wildwater, M., Willemsen, V., Paponov, I., Friml, J., … Scheres, B. (2005). The PIN auxin efflux facilitator network controls growth and patterning in Arabidopsis roots. Nature, 433(7021), 39-44. doi:10.1038/nature03184Mahonen, A. P. (2006). Cytokinin Signaling and Its Inhibitor AHP6 Regulate Cell Fate During Vascular Development. Science, 311(5757), 94-98. doi:10.1126/science.1118875Besnard, F., Refahi, Y., Morin, V., Marteaux, B., Brunoud, G., Chambrier, P., … Vernoux, T. (2013). Cytokinin signalling inhibitory fields provide robustness to phyllotaxis. Nature, 505(7483), 417-421. doi:10.1038/nature12791Longabaugh, W. J. R., Davidson, E. H., & Bolouri, H. (2005). Computational representation of developmental genetic regulatory networks. Developmental Biology, 283(1), 1-16. doi:10.1016/j.ydbio.2005.04.023Faure, E., Peter, I. S., & Davidson, E. H. (2013). A New Software Package for Predictive Gene Regulatory Network Modeling and Redesign. Journal of Computational Biology, 20(6), 419-423. doi:10.1089/cmb.2012.0297Mangan, S., & Alon, U. (2003). Structure and function of the feed-forward loop network motif. Proceedings of the National Academy of Sciences, 100(21), 11980-11985. doi:10.1073/pnas.2133841100Chen, Q., Liu, Y., Maere, S., Lee, E., Van Isterdael, G., Xie, Z., … Vanneste, S. (2015). A coherent transcriptional feed-forward motif model for mediating auxin-sensitive PIN3 expression during lateral root development. Nature Communications, 6(1). doi:10.1038/ncomms9821Qiu, K., Li, Z., Yang, Z., Chen, J., Wu, S., Zhu, X., … Zhou, X. (2015). EIN3 and ORE1 Accelerate Degreening during Ethylene-Mediated Leaf Senescence by Directly Activating Chlorophyll Catabolic Genes in Arabidopsis. PLOS Genetics, 11(7), e1005399. doi:10.1371/journal.pgen.1005399Seaton, D. D., Smith, R. W., Song, Y. H., MacGregor, D. R., Stewart, K., Steel, G., … Halliday, K. J. (2015). Linked circadian outputs control elongation growth and flowering in response to photoperiod and temperature. Molecular Systems Biology, 11(1), 776. doi:10.15252/msb.20145766Roeder, A. H. K., & Yanofsky, M. F. (2006). Fruit Development in Arabidopsis. The Arabidopsis Book, 4, e0075. doi:10.1199/tab.0075Marsch-Martínez, N., Reyes-Olalde, J. I., Ramos-Cruz, D., Lozano-Sotomayor, P., Zúñiga-Mayo, V. M., & de Folter, S. (2012). Hormones talking. Plant Signaling & Behavior, 7(12), 1698-1701. doi:10.4161/psb.22422Balanza, V., Navarrete, M., Trigueros, M., & Ferrandiz, C. (2006). Patterning the female side of Arabidopsis: the importance of hormones. Journal of Experimental Botany, 57(13), 3457-3469. doi:10.1093/jxb/erl188Kamiuchi, Y., Yamamoto, K., Furutani, M., Tasaka, M., & Aida, M. (2014). The CUC1 and CUC2 genes promote carpel margin meristem formation during Arabidopsis gynoecium development. Frontiers in Plant Science, 5. doi:10.3389/fpls.2014.00165Scofield, S., Dewitte, W., & Murray, J. A. H. (2007). The KNOX gene SHOOT MERISTEMLESS is required for the development of reproductive meristematic tissues in Arabidopsis. The Plant Journal, 50(5), 767-781. doi:10.1111/j.1365-313x.2007.03095.xLi, K., Yu, R., Fan, L.-M., Wei, N., Chen, H., & Deng, X. W. (2016). DELLA-mediated PIF degradation contributes to coordination of light and gibberellin signalling in Arabidopsis. Nature Communications, 7(1). doi:10.1038/ncomms11868Oh, E., Zhu, J.-Y., & Wang, Z.-Y. (2012). Interaction between BZR1 and PIF4 integrates brassinosteroid and environmental responses. Nature Cell Biology, 14(8), 802-809. doi:10.1038/ncb2545Sharma, N., Xin, R., Kim, D.-H., Sung, S., Lange, T., & Huq, E. (2016). NO FLOWERING IN SHORT DAY (NFL) is a bHLH transcription factor that promotes flowering specifically under short-day conditions inArabidopsis. Development, 143(4), 682-690. doi:10.1242/dev.128595Varaud, E., Brioudes, F., Szécsi, J., Leroux, J., Brown, S., Perrot-Rechenmann, C., & Bendahmane, M. (2011). AUXIN RESPONSE FACTOR8 Regulates Arabidopsis Petal Growth by Interacting with the bHLH Transcription Factor BIGPETALp. The Plant Cell, 23(3), 973-983. doi:10.1105/tpc.110.081653Savaldi-Goldstein, S., & Chory, J. (2008). Growth coordination and the shoot epidermis. Current Opinion in Plant Biology, 11(1), 42-48. doi:10.1016/j.pbi.2007.10.009Schuster, C., Gaillochet, C., Medzihradszky, A., Busch, W., Daum, G., Krebs, M., … Lohmann, J. U. (2014). A Regulatory Framework for Shoot Stem Cell Co
    corecore