692 research outputs found

    SOCS2-Induced Proteasome-Dependent TRAF6 Degradation: A Common Anti-Inflammatory Pathway for Control of Innate Immune Responses

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    Pattern recognition receptors and receptors for pro-inflammatory cytokines provide critical signals to drive the development of protective immunity to infection. Therefore, counter-regulatory pathways are required to ensure that overwhelming inflammation harm host tissues. Previously, we showed that lipoxins modulate immune response during infection, restraining inflammation during infectious diseases in an Aryl hydrocarbon receptor (AhR)/suppressors of cytokine signaling (SOCS)2-dependent-manner. Recently, Indoleamine-pyrrole 2,3- dioxygenase (IDO)-derived tryptophan metabolites, including L-kynurenine, were also shown to be involved in several counter-regulatory mechanisms. Herein, we addressed whether the intracellular molecular events induced by lipoxins mediating control of innate immune signaling are part of a common regulatory pathway also shared by L-kynurenine exposure. We demonstrate that Tumor necrosis factor receptor-associated factor (TRAF)6 – member of a family of adapter molecules that couple the TNF receptor and interleukin-1 receptor/Toll-like receptor families to intracellular signaling events essential for the development of immune responses – is targeted by both lipoxins and L-kynurenine via an AhR/SOCS2-dependent pathway. Furthermore, we show that LXA4- and L-kynurenine-induced AhR activation, its subsequent nuclear translocation, leading SOCS2 expression and TRAF6 Lys47-linked poly-ubiquitination and proteosome-mediated degradation of the adapter proteins. The in vitro consequences of such molecular interactions included inhibition of TLR- and cytokine receptor-driven signal transduction and cytokine production. Subsequently, in vivo proteosome inhibition led to unresponsiveness to lipoxins, as well as to uncontrolled pro-inflammatory reactions and elevated mortality during toxoplasmosis. In summary, our results establish proteasome degradation of TRAF6 as a key molecular target for the anti-inflammatory pathway triggered by lipoxins and L-kynurenine, critical counter-regulatory mediators in the innate and adaptive immune systems

    Quantitative electroencephalography reveals different physiological profiles between benign and remitting-relapsing multiple sclerosis patients

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    <p>Abstract</p> <p>Background</p> <p>A possible method of finding physiological markers of multiple sclerosis (MS) is the application of EEG quantification (QEEG) of brain activity when the subject is stressed by the demands of a cognitive task. In particular, modulations of the spectral content that take place in the EEG of patients with multiple sclerosis remitting-relapsing (RRMS) and benign multiple sclerosis (BMS) during a visuo-spatial task need to be observed.</p> <p>Methods</p> <p>The sample consisted of 19 patients with RRMS, 10 with BMS, and 21 control subjects. All patients were free of medication and had not relapsed within the last month. The power spectral density (PSD) of different EEG bands was calculated by Fast-Fourier-Transformation (FFT), those analysed being delta, theta, alpha, beta and gamma. Z-transformation was performed to observe individual profiles in each experimental group for spectral modulations. Lastly, correlation analyses was performed between QEEG values and other variables from participants in the study (age, EDSS, years of evolution and cognitive performance).</p> <p>Results</p> <p>Nearly half (42%) the RRMS patients showed a statistically significant increase of two or more standard deviations (SD) compared to the control mean value for the beta-2 and gamma bands (F = 2.074, p = 0.004). These alterations were localized to the anterior regions of the right hemisphere, and bilaterally to the posterior areas of the scalp. None of the BMS patients or control subjects had values outside the range of ± 2 SD. There were no significant correlations between these values and the other variables analysed (age, EDSS, years of evolution or behavioural performance).</p> <p>Conclusion</p> <p>During the attentional processing, changes in the high EEG spectrum (beta-2 and gamma) in MS patients exhibit physiological alterations that are not normally detected by spontaneous EEG analysis. The different spectral pattern between pathological and controls groups could represent specific changes for the RRMS patients, indicative of compensatory mechanisms or cortical excitatory states representative of some phases during the RRMS course that are not present in the BMS group.</p

    Genetic variability of the neogregarine apicystis bombi, an etiological agent of an emergent bumblebee disease

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    The worldwide spread of diseases is considered a major threat to biodiversity and a possible driver of the decline of pollinator populations, particularly when novel species or strains of parasites emerge. Previous studies have suggested that populations of introduced European honeybee (Apis mellifera) and bumblebee species (Bombus terrestris and Bombus ruderatus) in Argentina share the neogregarine parasite Apicystis bombi with the native bumblebee (Bombus dahlbomii). In this study we investigated whether A. bombi is acting as an emergent parasite in the non-native populations. Specifically, we asked whether A. bombi, recently identified in Argentina, was introduced by European, non-native bees. Using ITS1 and ITS2 to assess the parasite's intraspecific genetic variation in bees from Argentina and Europe, we found a largely unstructured parasite population, with only 15% of the genetic variation being explained by geographic location. The most abundant haplotype in Argentina (found in all 9 specimens of non-native species) was identical to the most abundant haplotype in Europe (found in 6 out of 8 specimens). Similarly, there was no evidence of structuring by host species, with this factor explaining only 17% of the genetic variation. Interestingly, parasites in native Bombus ephippiatus from Mexico were genetically distant from the Argentine and European samples, suggesting that sufficient variability does exist in the ITS region to identify continent-level genetic structure in the parasite. Thus, the data suggest that A. bombi from Argentina and Europe share a common, relatively recent origin. Although our data did not provide information on the direction of transfer, the absence of genetic structure across space and host species suggests that A. bombi may be acting as an emergent infectious disease across bee taxa and continents

    Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

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    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

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

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    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

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

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    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

    Biomarkers characterization of circulating tumour cells in breast cancer patients

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    Introduction: Increasing evidence supports the view that the detection of circulating tumor cells (CTCs) predicts outcomes of nonmetastatic breast cancer patients. CTCs differ genetically from the primary tumor and may contribute to variations in prognosis and response to therapy. As we start to understand more about the biology of CTCs, we can begin to address how best to treat this form of disease. Methods: Ninety-eight nonmetastatic breast cancer patients were included in this study. CTCs were isolated by immunomagnetic techniques using magnetic beads labelled with a multi-CK-specific antibody (CK3-11D5) and CTC detection through immunocytochemical methods. Estrogen receptor, progesterone receptor and epidermal growth factor receptor (EGFR) were evaluated by immunofluorescence experiments and HER2 and TOP2A by fluorescence in situ hybridization. We aimed to characterize this set of biomarkers in CTCs and correlate it with clinical-pathological characteristics. Results: Baseline detection rate was 46.9% ≥ 1 CTC/30 ml threshold. CTC-positive cells were more frequent in HER2-negative tumors (p = 0.046). In patients younger than 50 years old, HER2-amplified and G1-G2 tumors had a higher possibility of being nondetectable CTCs. Heterogeneous expression of hormonal receptors (HRs) in samples from the same patients was found. Discordances between HR expression, HER2 and TOP2A status in CTCs and their primary tumor were found in the sequential blood samples. Less that 35% of patients switched their CTC status after receiving chemotherapy. EGFR-positive CTCs were associated with Luminal tumors (p = 0.03). Conclusions: This is the largest exploratory CTC biomarker analysis in nonmetastatic BC patients. Our study suggests that CTC biomarkers profiles might be useful as a surrogate marker for therapeutic selection and monitoring since heterogeneity of the biomarker distribution in CTCs and the lack of correlation with the primary tumor biomarker status were found. Further exploration of the association between EGFR-positive CTCs and Luminal tumors is warranted

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

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    [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

    Planck 2015 results: XV. gravitational lensing

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    We present the most significant measurement of the cosmic microwave background (CMB) lensing potential to date (at a level of 40 sigma), using temperature and polarization data from the Planck 2015 full-mission release. Using a polarization-only estimator we detect lensing at a significance of 5 sigma. We cross-check the accuracy of our measurement using the wide frequency coverage and complementarity of the temperature and polarization measurements. Public products based on this measurement include an estimate of the lensing potential over approximately 70% of the sky, an estimate of the lensing potential power spectrum in bandpowers for the multipole range 40<L<400 and an associated likelihood for cosmological parameter constraints. We find good agreement between our measurement of the lensing potential power spectrum and that found in the best-fitting LCDM model based on the Planck temperature and polarization power spectra. Using the lensing likelihood alone we obtain a percent-level measurement of the parameter combination σ 8 Ω 0.25 m =0.591±0.021 . We combine our determination of the lensing potential with the E-mode polarization also measured by Planck to generate an estimate of the lensing B-mode. We show that this lensing B-mode estimate is correlated with the B-modes observed directly by Planck at the expected level and with a statistical significance of 10 sigma, confirming Planck's sensitivity to this known sky signal. We also correlate our lensing potential estimate with the large-scale temperature anisotropies, detecting a cross-correlation at the 3 sigma level, as expected due to dark energy in the concordance LCDM model
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