Repeat bleaching of a central Pacific coral reef over the past six decades (1960–2016)

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Communications Biology 1 (2018): 177, doi:10.1038/s42003-018-0183-7.The oceans are warming and coral reefs are bleaching with increased frequency and severity, fueling concerns for their survival through this century. Yet in the central equatorial Pacific, some of the world’s most productive reefs regularly experience extreme heat associated with El Niño. Here we use skeletal signatures preserved in long-lived corals on Jarvis Island to evaluate the coral community response to multiple successive heatwaves since 1960. By tracking skeletal stress band formation through the 2015-16 El Nino, which killed 95% of Jarvis corals, we validate their utility as proxies of bleaching severity and show that 2015-16 was not the first catastrophic bleaching event on Jarvis. Since 1960, eight severe (>30% bleaching) and two moderate (<30% bleaching) events occurred, each coinciding with El Niño. While the frequency and severity of bleaching on Jarvis did not increase over this time period, 2015–16 was unprecedented in magnitude. The trajectory of recovery of this historically resilient ecosystem will provide critical insights into the potential for coral reef resilience in a warming world.Funding for this study was provided by National Science Foundation awards OCE 1537338, OCE 1605365, and OCE 1031971 to A.L.C., and the Robertson Foundation to A.L.C., National Science Foundation Graduate Research Fellowships to T.M.D. and A.E.A., and a National Defense Science and Engineering Graduate Fellowship to H.E.R

Identification of Keratinocyte Growth Factor as a Target of microRNA-155 in Lung Fibroblasts: Implication in Epithelial-Mesenchymal Interactions

International audienceBACKGROUND: Epithelial-mesenchymal interactions are critical in regulating many aspects of vertebrate embryo development, and for the maintenance of homeostatic equilibrium in adult tissues. The interactions between epithelium and mesenchyme are believed to be mediated by paracrine signals such as cytokines and extracellular matrix components secreted from fibroblasts that affect adjacent epithelia. In this study, we sought to identify the repertoire of microRNAs (miRNAs) in normal lung human fibroblasts and their potential regulation by the cytokines TNF-alpha, IL-1beta and TGF-beta. METHODOLOGY/PRINCIPAL FINDINGS: MiR-155 was significantly induced by inflammatory cytokines TNF-alpha and IL-1beta while it was down-regulated by TGF-beta. Ectopic expression of miR-155 in human fibroblasts induced modulation of a large set of genes related to "cell to cell signalling", "cell morphology" and "cellular movement". This was consistent with an induction of caspase-3 activity and with an increase in cell migration in fibroblasts tranfected with miR-155. Using different miRNA bioinformatic target prediction tools, we found a specific enrichment for miR-155 predicted targets among the population of down-regulated transcripts. Among fibroblast-selective targets, one interesting hit was keratinocyte growth factor (KGF, FGF-7), a member of the fibroblast growth factor (FGF) family, which owns two potential binding sites for miR-155 in its 3'-UTR. Luciferase assays experimentally validated that miR-155 can efficiently target KGF 3'-UTR. Site-directed mutagenesis revealed that only one out of the 2 potential sites was truly functional. Functional in vitro assays experimentally validated that miR-155 can efficiently target KGF 3'-UTR. Furthermore, in vivo experiments using a mouse model of lung fibrosis showed that miR-155 expression level was correlated with the degree of lung fibrosis. CONCLUSIONS/SIGNIFICANCE: Our results strongly suggest a physiological function of miR-155 in lung fibroblasts. Altogether, this study implicates this miRNA in the regulation by mesenchymal cells of surrounding lung epithelium, making it a potential key player during tissue injury

The NANOGrav 15-year Data Set: Evidence for a Gravitational-Wave Background

We report multiple lines of evidence for a stochastic signal that is correlated among 67 pulsars from the 15-year pulsar-timing data set collected by the North American Nanohertz Observatory for Gravitational Waves. The correlations follow the Hellings-Downs pattern expected for a stochastic gravitational-wave background. The presence of such a gravitational-wave background with a power-law-spectrum is favored over a model with only independent pulsar noises with a Bayes factor in excess of $10^{14}$, and this same model is favored over an uncorrelated common power-law-spectrum model with Bayes factors of 200-1000, depending on spectral modeling choices. We have built a statistical background distribution for these latter Bayes factors using a method that removes inter-pulsar correlations from our data set, finding $p = 10^{-3}$ (approx. $3\sigma$) for the observed Bayes factors in the null no-correlation scenario. A frequentist test statistic built directly as a weighted sum of inter-pulsar correlations yields $p = 5 \times 10^{-5} - 1.9 \times 10^{-4}$ (approx. $3.5 - 4\sigma$). Assuming a fiducial $f^{-2/3}$ characteristic-strain spectrum, as appropriate for an ensemble of binary supermassive black-hole inspirals, the strain amplitude is $2.4^{+0.7}_{-0.6} \times 10^{-15}$ (median + 90% credible interval) at a reference frequency of 1/(1 yr). The inferred gravitational-wave background amplitude and spectrum are consistent with astrophysical expectations for a signal from a population of supermassive black-hole binaries, although more exotic cosmological and astrophysical sources cannot be excluded. The observation of Hellings-Downs correlations points to the gravitational-wave origin of this signal.Comment: 30 pages, 18 figures. Published in Astrophysical Journal Letters as part of Focus on NANOGrav's 15-year Data Set and the Gravitational Wave Background. For questions or comments, please email [email protected]

Extraction of the Muon Signals Recorded with the Surface Detector of the Pierre Auger Observatory Using Recurrent Neural Networks

We present a method based on the use of Recurrent Neural Networks to extract the muon component from the time traces registered with water-Cherenkov detector (WCD) stations of the Surface Detector of the Pierre Auger Observatory. The design of the WCDs does not allow to separate the contribution of muons to the time traces obtained from the WCDs from those of photons, electrons and positrons for all events. Separating the muon and electromagnetic components is crucial for the determination of the nature of the primary cosmic rays and properties of the hadronic interactions at ultra-high energies. We trained a neural network to extract the muon and the electromagnetic components from the WCD traces using a large set of simulated air showers, with around 450 000 simulated events. For training and evaluating the performance of the neural network, simulated events with energies between 1018.5, eV and 1020 eV and zenith angles below 60 degrees were used. We also study the performance of this method on experimental data of the Pierre Auger Observatory and show that our predicted muon lateral distributions agree with the parameterizations obtained by the AGASA collaboration