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Explanations of leaf size variation commonly focus on water availability, yet leaf size also varies with latitude and elevation in environments where water is not strongly limiting. We provide the first conclusive test of a prediction of leaf energy balance theory that may explain this pattern: large leaves are more vulnerable to night-time chilling, because their thick boundary layers impede convective exchange with the surrounding air. Seedlings of 15 New Zealand evergreens spanning 12-fold variation in leaf width were exposed to clear night skies, and leaf temperatures were measured with thermocouples. We then used a global dataset to assess several climate variables as predictors of leaf size in forest assemblages. Leaf minus air temperature was strongly correlated with leaf width, ranging from −0.9 to −3.2°C in the smallest- and largest-leaved species, respectively. Mean annual temperature and frost-free period were good predictors of evergreen angiosperm leaf size in forest assemblages, but no climate variable predicted deciduous leaf size. Although winter deciduousness makes large leaves possible in strongly seasonal climates, large-leaved evergreens are largely confined to frost-free climates because of their susceptibility to radiative cooling. Evergreen leaf size data can therefore be used to enhance vegetation models, and to infer palaeotemperatures from fossil leaf assemblages.

Studying extreme events and how they evolve in a changing climate is one of the most important current scientific challenges. Starting from complex climate models, a key difficulty is to be able to run long enough simulations in order to observe those extremely rare events. In physics, chemistry, and biology, rare event algorithms have recently been developed to compute probabilities of events that cannot be observed in direct numerical simulations. Here we propose such an algorithm, specifically designed for extreme heat or cold waves, based on statistical physics approaches. This gives an improvement of more than two orders of magnitude in the sampling efficiency. We describe the dynamics of events that would not be observed otherwise. We show that European extreme heat waves are related to a global teleconnection pattern involving North America and Asia. This tool opens a full range of studies, so far impossible, aimed at assessing quantitatively climate change impacts., Proceedings of the National Academy of Sciences (2017)

International audience; Nitrogen fertilisation of agricultural soil contributes significantly to emissions of the potent greenhouse gas nitrous oxide (N2O), which is generated during denitrification and, in oxic soils, mainly by ammonia oxidisers. Although laboratory cultures of ammonia oxidising bacteria (AOB) and archaea (AOA) produce N2O, their relative activities in soil are unknown. This work tested the hypothesis that AOB dominate ammonia oxidation and N2O production under conditions of high inorganic ammonia (NH3) input, but result mainly from the activity of AOA when NH3 is derived from mineralisation. 1‐octyne, a recently discovered inhibitor of AOB, was used to distinguish N2O production resulting from archaeal and bacterial ammonia oxidation in soil microcosms, and specifically inhibited AOB growth, activity and N2O production. In unamended soils, ammonia oxidation and N2O production were lower and resulted mainly from ammonia oxidation by AOA. The AOA N2O yield relative to nitrite produced was half that of AOB, likely due to additional enzymatic mechanisms in the latter, but ammonia oxidation and N2O production were directly linked in all treatments. Relative contributions of AOA and AOB to N2O production, therefore, reflect their respective contributions to ammonia oxidation. These results suggest potential mitigation strategies for N2O emissions from fertilised agricultural soils.

Background and Aims Experimental drought is well documented to induce a decline in photosynthetic capacity. However, if given time to acclimate to low water availability, the photosynthetic responses of plants to low soil moisture content may differ from those found in short-term experiments. This study aims to test whether plants acclimate to long-term water stress by modifying the functional relationships between photosynthetic traits and water stress, and whether species of contrasting habitat differ in their degree of acclimation. Methods Three Eucalyptus taxa from xeric and riparian habitats were compared with regard to their gas exchange responses under short- and long-term drought. Photosynthetic parameters were measured after 2 and 4 months of watering treatments, namely field capacity or partial drought. At 4 months, all plants were watered to field capacity, then watering was stopped. Further measurements were made during the subsequent ‘drying-down’, continuing until stomata were closed. Key Results Two months of partial drought consistently reduced assimilation rate, stomatal sensitivity parameters (g1), apparent maximum Rubisco activity (V′cmaxVcmax′) and maximum electron transport rate (J′maxJmax′). Eucalyptus occidentalis from the xeric habitat showed the smallest decline in V′cmaxVcmax′ and J′maxJmax′; however, after 4 months, V′cmaxVcmax′ and J′maxJmax′ had recovered. Species differed in their degree of V′cmaxVcmax′ acclimation. Eucalyptus occidentalis showed significant acclimation of the pre-dawn leaf water potential at which the V′cmaxVcmax′ and ‘true’ Vcmax (accounting for mesophyll conductance) declined most steeply during drying-down. Conclusions The findings indicate carbon loss under prolonged drought could be over-estimated without accounting for acclimation. In particular, (1) species from contrasting habitats differed in the magnitude of V′cmax reduction in short-term drought; (2) long-term drought allowed the possibility of acclimation, such that V′cmax reduction was mitigated; (3) xeric species showed a greater degree of V′cmax acclimation; and (4) photosynthetic acclimation involves hydraulic adjustments to reduce water loss while maintaining photosynthesis.

Goodson, William H. et al., © The Author 2015. Lifestyle factors are responsible for a considerable portion of cancer incidence worldwide, but credible estimates from the World Health Organization and the International Agency for Research on Cancer (IARC) suggest that the fraction of cancers attributable to toxic environmental exposures is between 7% and 19%. To explore the hypothesis that low-dose exposures to mixtures of chemicals in the environment may be combining to contribute to environmental carcinogenesis, we reviewed 11 hallmark phenotypes of cancer, multiple priority target sites for disruption in each area and prototypical chemical disruptors for all targets, this included dose-response characterizations, evidence of low-dose effects and cross-hallmark effects for all targets and chemicals. In total, 85 examples of chemicals were reviewed for actions on key pathways/ mechanisms related to carcinogenesis. Only 15% (13/85) were found to have evidence of a dose-response threshold, whereas 59% (50/85) exerted low-dose effects. No dose-response information was found for the remaining 26% (22/85). Our analysis suggests that the cumulative effects of individual (non-carcinogenic) chemicals acting on different pathways, and a variety of related systems, organs, tissues and cells could plausibly conspire to produce carcinogenic synergies. Additional basic research on carcinogenesis and research focused on low-dose effects of chemical mixtures needs to be rigorously pursued before the merits of this hypothesis can be further advanced. However, the structure of the World Health Organization International Programme on Chemical Safety 'Mode of Action' framework should be revisited as it has inherent weaknesses that are not fully aligned with our current understanding of cancer biology., We gratefully acknowledge the support of the National Institute of Health-National Institute of Environmental Health Sciences (NIEHS) conference grant travel support (R13ES023276); Glenn Rice, Office of Research and Development, United States Environmental Protection Agency, Cincinnati, OH, USA also deserves thanks for his thoughtful feedback and inputs on the manuscript; William H.Goodson III was supported by the California Breast Cancer Research Program, Clarence Heller Foundation and California Pacific Medical Center Foundation; Abdul M.Ali would like to acknowledge the financial support of the University of Sultan Zainal Abidin, Malaysia; Ahmed Lasfar was supported by an award from the Rutgers Cancer Institute of New Jersey; Ann-Karin Olsen and Gunnar Brunborg were supported by the Research Council of Norway (RCN) through its Centres of Excellence funding scheme (223268/F50), Amancio Carnero’s lab was supported by grants from the Spanish Ministry of Economy and Competitivity, ISCIII (Fis: PI12/00137, RTICC: RD12/0036/0028) co-funded by FEDER from Regional Development European Funds (European Union), Consejeria de Ciencia e Innovacion (CTS-1848) and Consejeria de Salud of the Junta de Andalucia (PI-0306-2012); Matilde E. Lleonart was supported by a trienal project grant PI12/01104 and by project CP03/00101 for personal support. Amaya Azqueta would like to thank the Ministerio de Educacion y Ciencia (‘Juande la Cierva’ programme, 2009) of the Spanish Government for personal support; Amedeo Amedei was supported by the Italian Ministry of University and Research (2009FZZ4XM_002), and the University of Florence (ex60%2012); Andrew R.Collins was supported by the University of Oslo; Annamaria Colacci was supported by the Emilia-Romagna Region - Project ‘Supersite’ in Italy; Carolyn Baglole was supported by a salary award from the Fonds de recherche du Quebec-Sante (FRQ-S); Chiara Mondello’s laboratory is supported by Fondazione Cariplo in Milan, Italy (grant n. 2011-0370); Christian C.Naus holds a Canada Research Chair; Clement Yedjou was supported by a grant from the National Institutes of Health (NIH-NIMHD grant no. G12MD007581); Daniel C.Koch is supported by the Burroughs Wellcome Fund Postdoctoral Enrichment Award and the Tumor Biology Training grant: NIH T32CA09151; Dean W. Felsher would like to acknowledge the support of United States Department of Health and Human Services, NIH grants (R01 CA170378 PQ22, R01 CA184384, U54 CA149145, U54 CA151459, P50 CA114747 and R21 CA169964); Emilio Rojas would like to thank CONACyT support 152473, Ezio Laconi was supported by AIRC (Italian Association for Cancer Research, grant no. IG 14640) and by the Sardinian Regional Government (RAS); Eun-Yi Moon was supported by grants from the Public Problem-Solving Program (NRF-015M3C8A6A06014500) and Nuclear R&D Program (#2013M2B2A9A03051296 and 2010-0018545) through the National Research Foundation of Korea (NRF) and funded by the Ministry of Education, Science and Technology (MEST) in Korea; Fahd Al-Mulla was supported by the Kuwait Foundation for the Advancement of Sciences (2011-1302-06); Ferdinando Chiaradonna is supported by SysBioNet, a grant for the Italian Roadmap of European Strategy Forum on Research Infrastructures (ESFRI) and by AIRC (Associazione Italiana Ricerca sul Cancro; IG 15364); Francis L.Martin acknowledges funding from Rosemere Cancer Foundation; he also thanks Lancashire Teaching Hospitals NHS trust and the patients who have facilitated the studies he has undertaken over the course of the last 10 years; Gary S.Goldberg would like to acknowledge the support of the New Jersey Health Foundation; Gloria M.Calaf was supported by Fondo Nacional de Ciencia y Tecnología (FONDECYT), Ministerio de Educación de Chile (MINEDUC), Universidad de Tarapacá (UTA); Gudrun Koppen was supported by the Flemish Institute for Technological Research (VITO), Belgium; Hemad Yasaei was supported from a triennial project grant (Strategic Award) from the National Centre for the Replacement, Refinement and Reduction (NC3Rs) of animals in research (NC.K500045.1 and G0800697); Hiroshi Kondoh was supported in part by grants from the Ministry of Education, Culture, Sports, Science, and Technology of Japan, Japan Science and Technology Agency and by JST, CREST; Hsue-Yin Hsu was supported by the Ministry of Science and Technology of Taiwan (NSC93-2314-B-320-006 and NSC94-2314-B-320-002); Hyun Ho Park was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) of the Ministry of Education, Science and Technology (2012R1A2A2A01010870) and a grant from the Korea Healthcare Technology R&D project, Ministry of Health and Welfare, Republic of Korea (HI13C1449); Igor Koturbash is supported by the UAMS/NIH Clinical and Translational Science Award (UL1TR000039 and KL2TR000063) and the Arkansas Biosciences Institute, the major research component of the Arkansas Tobacco Settlement Proceeds Act of 2000; Jan Vondráček acknowledges funding from the Czech Science Foundation (13-07711S); Jesse Roman thanks the NIH for their support (CA116812), John Pierce Wise Sr. and Sandra S.Wise were supported by National Institute of Environmental Health Sciences (ES016893 to J.P.W.) and the Maine Center for Toxicology and Environmental Health; Jonathan Whitfield acknowledges support from the FERO Foundation in Barcelona, Spain; Joseph Christopher is funded by Cancer Research UK and the International Journal of Experimental Pathology; Julia Kravchenko is supported by a philanthropic donation by Fred and Alice Stanback; Jun Sun is supported by a Swim Across America Cancer Research Award; Karine A.Cohen-Solal is supported by a research scholar grant from the American Cancer Society (116683-RSG-09-087-01-TBE); Laetitia Gonzalez received a postdoctoral fellowship from the Fund for Scientific Research–Flanders (FWO-Vlaanderen) and support by an InterUniversity Attraction Pole grant (IAP-P7-07); Laura Soucek is supported by grant #CP10/00656 from the Miguel Servet Research Contract Program and acknowledges support from the FERO Foundation in Barcelona, Spain; Liang-Tzung Lin was supported by funding from the Taipei Medical University (TMU101-AE3-Y19); Linda Gulliver is supported by a Genesis Oncology Trust (NZ) Professional Development Grant, and the Faculty of Medicine, University of Otago, Dunedin, New Zealand; Louis Vermeulen is supported by a Fellowship of the Dutch Cancer Society (KWF, UVA2011-4969) and a grant from the AICR (14–1164); Mahara Valverde would like to thank CONACyT support 153781; Masoud H. Manjili was supported by the office of the Assistant Secretary of Defense for Health Affairs (USA) through the Breast Cancer Research Program under Award No. W81XWH-14-1-0087 Neetu Singh was supported by grant #SR/FT/LS-063/2008 from the Department of Science and Technology, Government of India; Nicole Kleinstreuer is supported by NIEHS contracts (N01-ES 35504 and HHSN27320140003C); P.K. Krishnakumar is supported by the Funding (No. T.K. 11-0629) of King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia; Paola A.Marignani is supported by the Dalhousie Medical Research Foundation, The Beatrice Hunter Cancer Institute and CIHR and the Nova Scotia Lung Association; Paul Dent is the holder of the Universal Inc.Chair in Signal Transduction Research and is supported with funds from PHS grants from the NIH (R01-CA141704, R01-CA150214, R01-DK52825 and R01-CA61774); Petr Heneberg was supported by the Charles University in Prague projects UNCE 204015 and PRVOUK P31/2012, and by the Czech Science Foundation projects P301/12/1686 and 15-03834Y; Po Sing Leung was supported by the Health and Medical Research Fund of Food and Health Bureau, Hong Kong Special Administrative Region, Ref. No: 10110021; Qiang Cheng was supported in part by grant NSF IIS-1218712; R. Brooks Robey is supported by the United States Department of Veterans Affairs; Rabindra Roy was supported by United States Public Health Service Grants (RO1 CA92306, RO1 CA92306-S1 and RO1 CA113447); Rafaela Andrade-Vieira is supported by the Beatrice Hunter Cancer Research Institute and the Nova Scotia Health Research Foundation, Renza Vento was partially funded by European Regional Development Fund, European Territorial Cooperation 2007–13 (CCI 2007 CB 163 PO 037, OP Italia-Malta 2007–13) and grants from the Italian Ministry of Education, University and Research (MIUR) ex-60%, 2007; Riccardo Di Fiore was a recipient of fellowship granted by European Regional Development Fund, European Territorial Cooperation 2007–2013 (CCI 2007 CB 163 PO 037, OP Italia-Malta 2007–2013); Rita Dornetshuber-Fleiss was supported by the Austrian Science Fund (FWF, project number T 451-B18) and the Johanna Mahlke, geb.-Obermann-Stiftung; Roberta Palorini is supported by a SysBioNet fellowship; Roslida Abd Hamid is supported by the Ministry of Education, Malaysia-Exploratory Research Grant Scheme-Project no: ERGS/1-2013/5527165; Sabine A.S.Langie is the beneficiary of a postdoctoral grant from the AXA Research Fund and the Cefic-LRI Innovative Science Award 2013; Sakina Eltom is supported by NIH grant SC1CA153326; Samira A.Brooks was supported by National Research Service Award (T32 ES007126) from the National Institute of Environmental Health Sciences and the HHMI Translational Medicine Fellowship; Sandra Ryeom was supported by The Garrett B. Smith Foundation and the TedDriven Foundation; Thierry Massfelder was supported by the Institut National de la Santé et de la Recherche Médicale INSERM and Université de Strasbourg; Thomas Sanderson is supported by the Canadian Institutes of Health Research (CIHR; MOP-115019), the Natural Sciences and Engineering Council of Canada (NSERC; 313313) and the California Breast Cancer Research Program (CBCRP; 17UB-8703); Tiziana Guarnieri is supported by a grant from Fundamental Oriented Research (RFO) to the Alma Mater Studiorum University of Bologna, Bologna, Italy and thanks the Fondazione Cassa di Risparmio di Bologna and the Fondazione Banca del Monte di Bologna e Ravenna for supporting the Center for Applied Biomedical Research, S.Orsola-Malpighi University Hospital, Bologna, Italy; W.Kimryn Rathmell is supported by the V Foundation for Cancer Research and the American Cancer Society; William K.Decker was supported in part by grant RP110545 from the Cancer Prevention Research Institute of Texas; William H.Bisson was supported with funding from the NIH P30 ES000210; Yon Rojanasakul was supported with NIH grant R01-ES022968; Zhenbang Chen is supported by NIH grants (MD004038, CA163069 and MD007593); Zhiwei Hu is grateful for the grant support from an institutional start-up fund from The Ohio State University College of Medicine and The OSU James Comprehensive Cancer Center (OSUCCC) and a Seed Award from the OSUCCC Translational Therapeutics Program.

Summary Dynamic global vegetation models (DGVMs) can disentangle causes and effects in the control of vegetation and fire. We used a DGVM to analyse climate, CO2 and fire influences on biome distribution and net primary production (NPP) in last glacial maximum (LGM) and pre-industrial (PI) times. The Land surface Processes and eXchanges (LPX) DGVM was run in a factorial design with fire ‘off’ or ‘on’, CO2 at LGM (185 ppm) or PI (280 ppm) concentrations, and LGM (modelled) or recent climates. Results were analysed by Stein–Alpert decomposition to separate primary effects from synergies. Fire removal causes forests to expand and global NPP to increase slightly. Low CO2 greatly reduces forest area (dramatically in a PI climate; realistically under an LGM climate) and global NPP. NPP under an LGM climate was reduced by a quarter as a result of low CO2. The reduction in global NPP was smaller at low temperatures, but greater in the presence of fire. Global NPP is controlled by climate and CO2 directly through photosynthesis, but also through biome distribution, which is strongly influenced by fire. Future vegetation simulations will need to consider the coupled responses of vegetation and fire to CO2 and climate.

Land-surface models (LSMs) are increasingly called upon to represent not only the exchanges of energy, water and momentum across the land–atmosphere interface (their original purpose in climate models), but also how ecosystems and water resources respond to climate, atmospheric environment, land-use and land-use change, and how these responses in turn influence land–atmosphere fluxes of carbon dioxide (CO2), trace gases and other species that affect the composition and chemistry of the atmosphere. However, the LSMs embedded in state-of-the-art climate models differ in how they represent fundamental aspects of the hydrological and carbon cycles, resulting in large inter-model differences and sometimes faulty predictions. These "third-generation" LSMs respect the close coupling of the carbon and water cycles through plants, but otherwise tend to be under-constrained, and have not taken full advantage of robust hydrological parameterizations that were independently developed in offline models. Benchmarking, combining multiple sources of atmospheric, biospheric and hydrological data, should be a required component of LSM development, but this field has been relatively poorly supported and intermittently pursued. Moreover, benchmarking alone is not sufficient to ensure that models improve. Increasing complexity may increase realism but decrease reliability and robustness, by increasing the number of poorly known model parameters. In contrast, simplifying the representation of complex processes by stochastic parameterization (the representation of unresolved processes by statistical distributions of values) has been shown to improve model reliability and realism in both atmospheric and land-surface modelling contexts. We provide examples for important processes in hydrology (the generation of runoff and flow routing in heterogeneous catchments) and biology (carbon uptake by species-diverse ecosystems). We propose that the way forward for next-generation complex LSMs will include: (a) representations of biological and hydrological processes based on the implementation of multiple internal constraints; (b) systematic application of benchmarking and data assimilation techniques to optimize parameter values and thereby test the structural adequacy of models; and (c) stochastic parameterization of unresolved variability, applied in both the hydrological and the biological domains.

© Oxford University Press 2015. All rights reserved. This article employs a Bayesian methodology to measure the uncertainty involved in the long-run holding of the purchasing power parity (PPP) and in the half-life (HL) of deviations from it. Our Bayesian approach combines estimates obtained from ARMA, ARFIMA, and ARIMA specifications so that it is able to take into account model uncertainty. Exact posterior distributions corresponding to all the features of interest (fractional orders of integration, impulse responses, HLs, etc.) are derived. Our results suggest that model uncertainty is high, which implies that uncertainty estimates can be severely biased downwards when the former is not explicitly considered. In spite of that, support for the long-run holding of the PPP is substantial in most countries. However, the speed at which this happens seems to be much slower than what has been suggested, as shown by the fact that the probability of the HL lying in the three- to five-year interval is very small., Ministerio de Ciencia e Innovación (ECO2011–30260–C03–02 to M.D.G., ECO2011–25293 to L.M.); Axa research fund

Functional, molecular and genetic neuroimaging has highlighted the existence of brain anomalies and neural vulnerability factors related to obesity and eating disorders such as binge eating or anorexia nervosa. In particular, decreased basal metabolism in the prefrontal cortex and striatum as well as dopaminergic alterations have been described in obese subjects, in parallel with increased activation of reward brain areas in response to palatable food cues. Elevated reward region responsivity may trigger food craving and predict future weight gain. This opens the way to prevention studies using functional and molecular neuroimaging to perform early diagnostics and to phenotype subjects at risk by exploring different neurobehavioral dimensions of the food choices and motivation processes. In the first part of this review, advantages and limitations of neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), positron emission tomography (PET), single photon emission computed tomography (SPECT), pharmacogenetic fMRI and functional near-infrared spectroscopy (fNIRS) will be discussed in the context of recent work dealing with eating behavior, with a particular focus on obesity. In the second part of the review, non-invasive strategies to modulate food-related brain processes and functions will be presented. At the leading edge of non-invasive brain-based technologies is real-time fMRI (rtfMRI) neurofeedback, which is a powerful tool to better understand the complexity of human brain–behavior relationships. rtfMRI, alone or when combined with other techniques and tools such as EEG and cognitive therapy, could be used to alter neural plasticity and learned behavior to optimize and/or restore healthy cognition and eating behavior. Other promising non-invasive neuromodulation approaches being explored are repetitive transcranial magnetic stimulation (rTMS) and transcranial direct-current stimulation (tDCS). Converging evidence points at the value of these non-invasive neuromodulation strategies to study basic mechanisms underlying eating behavior and to treat its disorders. Both of these approaches will be compared in light of recent work in this field, while addressing technical and practical questions. The third part of this review will be dedicated to invasive neuromodulation strategies, such as vagus nerve stimulation (VNS) and deep brain stimulation (DBS). In combination with neuroimaging approaches, these techniques are promising experimental tools to unravel the intricate relationships between homeostatic and hedonic brain circuits. Their potential as additional therapeutic tools to combat pharmacorefractory morbid obesity or acute eating disorders will be discussed, in terms of technical challenges, applicability and ethics. In a general discussion, we will put the brain at the core of fundamental research, prevention and therapy in the context of obesity and eating disorders. First, we will discuss the possibility to identify new biological markers of brain functions. Second, we will highlight the potential of neuroimaging and neuromodulation in individualized medicine. Third, we will introduce the ethical questions that are concomitant to the emergence of new neuromodulation therapies., Highlights • We review the neural vulnerability factors related to obesity and eating disorders. • We compare the pros and cons of neuroimaging techniques to study eating behavior. • We present non-invasive strategies to modulate food-related brain processes. • We also present invasive neuromodulation methods such as VNS and DBS. • We discuss about neuroimaging and neuromodulation for prevention and therapy.

Gutiérrez, Lucía et al., We review current synthetic routes to magnetic iron oxide nanoparticles for biomedical applications. We classify the different approaches used depending on their ability to generate magnetic particles that are either single-core (containing only one magnetic core, i.e. a single domain nanocrystal) or multi-core (containing several magnetic cores, i.e. single domain nanocrystals). The synthesis of single-core magnetic nanoparticles requires the use of surfactants during the particle generation, and careful control of the particle coating to prevent aggregation. Special attention has to be paid to avoid the presence of any toxic reagents after the synthesis if biomedical applications are intended. Several approaches exist to obtain multi-core particles based on the coating of particle aggregates; nevertheless, the production of multi-core particles with good control of the number of magnetic cores per particle, and of the degree of polydispersity of the core sizes, is still a difficult task. The control of the structure of the particles is of great relevance for biomedical applications as it has a major influence on the magnetic properties of the materials., This work was supported by the European Commission Framework Programme 7 under grant agreement no [604448], Nanomag project. LG is the beneficiary of a post-doctoral grant from the AXA Research Fund.

We present a simple, generic model of annual tree growth, called "T". This model accepts input from a first-principles light-use efficiency model (the "P" model). The P model provides values for gross primary production (GPP) per unit of absorbed photosynthetically active radiation (PAR). Absorbed PAR is estimated from the current leaf area. GPP is allocated to foliage, transport tissue, and fine-root production and respiration in such a way as to satisfy well-understood dimensional and functional relationships. Our approach thereby integrates two modelling approaches separately developed in the global carbon-cycle and forest-science literature. The T model can represent both ontogenetic effects (the impact of ageing) and the effects of environmental variations and trends (climate and CO2) on growth. Driven by local climate records, the model was applied to simulate ring widths during the period 1958–2006 for multiple trees of Pinus koraiensis from the Changbai Mountains in northeastern China. Each tree was initialised at its actual diameter at the time when local climate records started. The model produces realistic simulations of the interannual variability in ring width for different age cohorts (young, mature, and old). Both the simulations and observations show a significant positive response of tree-ring width to growing-season total photosynthetically active radiation (PAR0) and the ratio of actual to potential evapotranspiration (α), and a significant negative response to mean annual temperature (MAT). The slopes of the simulated and observed relationships with PAR0 and α are similar; the negative response to MAT is underestimated by the model. Comparison of simulations with fixed and changing atmospheric CO2 concentration shows that CO2 fertilisation over the past 50 years is too small to be distinguished in the ring-width data, given ontogenetic trends and interannual variability in climate.

International audience; The spread of Zika virus in the Americas has been associated with a surge in Guillain-Barré syndrome (GBS) cases. Given the severity of GBS, territories affected by Zika virus need to plan health-care resources to manage GBS patients. To inform such planning in Martinique, we analyzed Zika virus surveillance and GBS data from Martinique in real time with a modeling framework that captured dynamics of the Zika virus epidemic, the risk of GBS in Zika virus–infected persons, and the clinical management of GBS cases. We compared our estimates with those from the 2013–2014 Zika virus epidemic in French Polynesia. We were able to predict just a few weeks into the epidemic that, due to lower transmission potential and lower probability of developing GBS following infection in Martinique, the total number of GBS cases in Martinique would be substantially lower than suggested by simple extrapolations from French Polynesia. We correctly predicted that 8 intensive-care beds and 7 ventilators would be sufficient to treat GBS cases. This study showcased the contribution of modeling to inform local health-care planning during an outbreak. Timely studies that estimate the proportion of infected persons that seek care are needed to improve the predictive power of such approaches.

A new kind of fluorescent organic nanoparticles (FONs) is obtained using quatsomes (QSs), a family of nanovesicles proposed as scaffolds for the nanostructuration of commercial lipophilic carbocyanines (1,1′‐dioctadecyl‐3,3,3′,3′‐tetramethyl‐indocarbocyanine perchlorate (DiI), 1,1′‐dioctadecyl‐3,3,3′,3′‐tetramethyl‐indodicarbocyanine perchlorate (DiD), and 1,1′‐dioctadecyl‐3,3,3′,3′‐tetramethyl‐indotricarbocyanine iodide (DiR)) in aqueous media. The obtained FONs, prepared by a CO2‐based technology, show excellent colloidal‐ and photostability, outperforming other nanoformulations of the dyes, and improve the optical properties of the fluorophores in water. Molecular dynamics simulations provide an atomistic picture of the disposition of the dyes within the membrane. The potential of QSs for biological imaging is demonstrated by performing superresolution microscopy of the DiI‐loaded vesicles in vitro and in cells. Therefore, fluorescent QSs constitute an appealing nanomaterial for bioimaging applications., This work was financially supported by MINECO/FEDER, Spain (Grant Nos. CTQ2013‐40480‐R, SAF2016‐7524‐R, and MAT 2016‐80826‐R), by AGAUR, Generalitat de Catalunya (Grant No. 2014‐SGR‐17), and through the CERCA program, the Networking Research Center on Bioengineering, Biomaterials, and Nanomedicine (CIBER‐BBN) and the Spanish Ministry of Economy and Competitiveness, through the “Severo Ochoa” Programme for Centres of Excellence in R&D (SEV‐2015‐0496, Grant FLOWERS, and SEV‐2014‐0425). L.A. thanks the financial support of AXA Research Fund and D.H. and E.V.S. the Army Research Laboratory (Grant No. W911NF‐15‐2‐0090). The research leading to these results received funding from the People Programme (Marie Curie Actions) of the European Union's Seventh Framework ProgrammeFP7/2007–2013 under REA grant Agreement No. 607721 (Nano2Fun) A.A. and S.I.‐T. are enrolled in the Materials Science Ph.D. program of UAB. A.A. and S.I.‐T. gratefully acknowledge help of Dr. M. Masino in photostability measurements.

International audience; Zika virus (ZIKV) infection has been associated with complications during pregnancy. Although the presence of symptoms might be a risk factor for complication, the proportion of ZIKV-infected pregnant women with symptoms remains unknown. Following the emergence of ZIKV in French Guiana, all pregnancies in the territory were monitored by RT-PCR and/or detection of ZIKV antibodies. Follow-up data collected during pregnancy monitoring interviews were analysed from 1 February to 1 June 2016. We enrolled 3,050 pregnant women aged 14-48 years and 573 (19%) had laboratory-confirmed ZIKV infection. Rash, arthralgia, myalgia and conjunctival hyperaemia were more frequently observed in ZIKV-positive women; 23% of them (95% confidence interval (CI): 20-27) had at least one symptom compatible with ZIKV infection. Women 30 years and older were significantly more likely to have symptoms than younger women (28% vs 20%). The proportion of symptomatic infections varied from 17% in the remote interior to 35% in the urbanised population near the coast (adjusted risk ratio: 1.6; 95% CI: 1.4-1.9.). These estimates put findings on cohorts of symptomatic ZIKV-positive pregnant women into the wider context of an epidemic with mainly asymptomatic infections. The proportion of symptomatic ZIKV infections appears to vary substantially between populations.

International audience; BackgroundFrom earlier studies it is known that the APOE ε2/ε3/ε4 polymorphism modulates the concentrations of cerebrospinal fluid (CSF) beta-amyloid1–42 (Aβ42) in patients with cognitive decline due to Alzheimer’s disease (AD), as well as in cognitively healthy controls. Here, in a large cohort consisting solely of cognitively healthy individuals, we aimed to evaluate how the effect of APOE on CSF Aβ42 varies by age, to understand the association between APOE and the onset of preclinical AD.MethodsAPOE genotype and CSF Aβ42 concentration were determined in a cohort comprising 716 cognitively healthy individuals aged 17–99 from nine different clinical research centers.ResultsCSF concentrations of Aβ42 were lower in APOE ε4 carriers than in noncarriers in a gene dose-dependent manner. The effect of APOE ε4 on CSF Aβ42 was age dependent. The age at which CSF Aβ42 concentrations started to decrease was estimated at 50 years in APOE ε4-negative individuals and 43 years in heterozygous APOE ε4 carriers. Homozygous APOE ε4 carriers showed a steady decline in CSF Aβ42 concentrations with increasing age throughout the examined age span.ConclusionsPeople possessing the APOE ε4 allele start to show a decrease in CSF Aβ42 concentration almost a decade before APOE ε4 noncarriers already in early middle age. Homozygous APOE ε4 carriers might deposit Aβ42 throughout the examined age span. These results suggest that there is an APOE ε4-dependent period of early alterations in amyloid homeostasis, when amyloid slowly accumulates, that several years later, together with other downstream pathological events such as tau pathology, translates into cognitive decline.

International audience; We propose a method for selecting pre-symptomatic subjects likely to have amyloid plaques in the brain, based on the automatic analysis of neuropsychological and MRI data and using a cross-validated binary classifier. By avoiding systematic PET scan for selecting subjects, it reduces the cost of forming cohorts of subjects with amyloid plaques for clinical trials, by scanning fewer subjects but increasing the number of recruitments. We validate our method on three cohorts of subjects at different disease stages, and compare the performance of six classifiers, showing that the random forest yields good results more consistently, and that the method generalizes well when tested on an unseen data set.

Nature Communications 7: Article number:13428 (2017); Published 8 November 2016; Updated 14 July 2017 An earlier publication by Leggett and Ball presented statistical evidence for a relationship between the pause in global temperature, a pause in the global rate of change of CO2 and an increase in global vegetation cover.

International audience; Growth hormone (GH) and insulinlike growth factor (IGF) promote aging and age-related pathologies. Inhibiting this pathway by targeting IGF receptor (IGF-1R) is a promising strategy to extend life span, alleviate age-related diseases, and reduce tumor growth. Although anti-IGF-1R agents are being developed, long-term effects of IGF-1R blockade remain unknown. In this study, we used ubiquitous inducible IGF-1R knockout (UBIKOR) to suppress signaling in all adult tissues and screened health extensively. Surprisingly, UBIKOR mice showed no overt defects and presented with rather inconspicuous health, including normal cognition. Endocrine GH and IGF-1 were strongly upregulated without causing acromegaly. UBIKOR mice were strikingly lean with coordinate changes in body composition and organ size. They were insulin resistant but preserved physiological energy expenditure and displayed enhanced fasting metabolic flexibility. Thus, long-term IGF-1R blockade generated beneficial effects on aging-relevant metabolism, but exposed to high GH. This needs to be considered when targeting IGF-1R to protect from neurodegeneration, retard aging, or fight cancer.

Recent advances in the representation of soil carbon decomposition (Goll et al., 2015) and carbon-nitrogen interactions (Parida, 2011; Goll et al., 2012) implemented previously into separate versions of the land surface scheme JSBACH are here combined in a single version which is set to be used in the upcoming 6th phase of coupled model intercomparison project (CMIP6) (Eyring et al., 2016). Here we demonstrate that the new version of JSBACH is able to reproduce the spatial variability in the reactive nitrogen loss pathways as derived from a compilation of δ15N data (r=.63, RMSE=.26, Taylor score=.81). The inclusion of carbon-nitrogen interactions leads to a moderate reduction (−10 %) of the carbon-concentration feedback (βL) and has a negligible effect on the sensitivity of the land carbon cycle to warming (γL) compared to the same version of the model without carbon-nitrogen interactions in idealized simulations (1 % increase in atmospheric carbon dioxide per yr). In line with evidence from elevated carbon dioxide manipulation experiments (Shi et al., 2015; Liang et al., 2016), pronounced nitrogen scarcity is alleviated by (1) the accumulation of nitrogen due to enhanced nitrogen inputs by biological nitrogen fixation and reduced losses by leaching and volatilization as well as the (2) enhanced turnover of organic nitrogen. The strengths of the land carbon feedbacks of the recent version of JSBACH, with βL=0.61 Pg ppm−1 and γL=−27.5 Pg °C−1, are 34 % and 53 % less than the averages of CMIP5 models (Arora et al., 2013), although the CMIP5 version of JSBACH simulated βL and γL which are 59 % and 42 % higher than multi-model average. These changes are primarily due to the new decomposition model, stressing the importance of getting the basics right (here: the decomposition of soil carbon) before increasing the complexity of the model (here: carbon-nitrogen interactions).

We image vortex creep at very low temperatures using Scanning Tunneling Microscopy (STM) in the superconductor Rh$_9$In$_4$S$_4$ ($T_c$=2.25 K). We measure the superconducting gap of Rh$_9$In$_4$S$_4$, finding $\Delta\approx 0.33$meV and image a hexagonal vortex lattice up to close to H$_{c2}$, observing slow vortex creep at temperatures as low as 150 mK. We estimate thermal and quantum barriers for vortex motion and show that thermal fluctuations likely cause vortex creep, in spite of being at temperatures $T/T_c, Comment: 11 pages, 9 figures, 3 videos

International audience; HyMeX (HYdrological cycle in the Mediterranean EXperiment) aims at a better understanding andquantification of the hydrological cycle and related processes in the Mediterranean, notably withemphasis on high-impact weather events.This study investigates the interest of GNSS tomography for nowcasting. For this purpose, the 3Dfield of water vapour density is retrieved (resolution of 10 km and 0.5 km, respectively horizontallyand vertically) for 23 days of Autumn 2012, covering 6 intensive observation periods during severeweather events. An optimal strategy in tomography process developed in the frame of the COSTaction ES1206 (GNSS4SWEC - Advanced Global Navigation Satellite Systems tropospheric productsfor monitoring severe weather events and climate) is used for the permanent GNSS networkconsidered (about 130 stations with a mean baseline of 30 km). The sensitivity to the model a priori,which is needed to initialize the tomographic retrievals, is investigated by considering both analysesand very-short-term (3-h) forecasts from a high resolution numerical weather prediction system (i.e.the 3DVAR data assimilation system AROME-WMED; its domain covers the western Mediterraneanarea and additional observations available during HyMeX field campaigns are assimilated). Theadditional information provided by GNSS tomography in comparison to these forecasts is presented.

We examine issues to consider when reframing conservation science and practice in the context of global change. New framings of the links between ecosystems and society are emerging that are changing peoples' values and expectations of nature, resulting in plural perspectives on conservation. Reframing conservation for global change can thus be regarded as a stage in the evolving relationship between people and nature rather than some recent trend. New models of how conservation links with transformative adaptation include how decision contexts for conservation can be reframed and integrated with an adaptation pathways approach to create new options for global-change-ready conservation. New relationships for conservation science and governance include coproduction of knowledge that supports social learning. New processes for implementing adaptation for conservation outcomes include deliberate practices used to develop new strategies, shift world views, work with conflict, address power and intergenerational equity in decisions, and build consciousness and creativity that empower agents to act. We argue that reframing conservation for global change requires scientists and practitioners to implement approaches unconstrained by discipline and sectoral boundaries, geopolitical polarities, or technical problematization. We consider a stronger focus on inclusive creation of knowledge and the interaction of this knowledge with societal values and rules is likely to result in conservation science and practice that meets the challenges of a postnormal world.

Isotopic measurements on junipers growing in southern California during the last glacial, when the ambient atmospheric [CO2] (ca) was ~180 ppm, show the leaf-internal [CO2] (ci) was approaching the modern CO2 compensation point for C3 plants. Despite this, stem growth rates were similar to today. Using a coupled light-use efficiency and tree growth model, we show that it is possible to maintain a stable ci/ca ratio because both vapour pressure deficit and temperature were decreased under glacial conditions at La Brea, and these have compensating effects on the ci/ca ratio. Reduced photorespiration at lower temperatures would partly mitigate the effect of low ci on gross primary production, but maintenance of present-day radial growth also requires a ~27% reduction in the ratio of fine root mass to leaf area. Such a shift was possible due to reduced drought stress under glacial conditions at La Brea. The necessity for changes in allocation in response to changes in [CO2] is consistent with increased below-ground allocation, and the apparent homoeostasis of radial growth, as ca increases today.

International audience; BackgroundMRI computational tools represent promising instruments to improve the diagnostic accuracy of dementias including Alzheimer’s disease (AD). The Automated Segmentation Softwares (ASS) measure various regions of interest (ROI) volumes, thus supporting physicians in clinical decision-making processes. However, their accuracy has mainly been evaluated for research. Recent developments in Support Vector Machine (SVM) classifier might increase the diagnostic value of MRI indexes compared with ASS. Our objective was to investigate the classification rate based on two-class classifiers.MethodsOur study evaluated two ASS (VolBrain and NeuroReader) and two SVM approaches in a monocentric memory center routine clinical cohort of 263 patients with various dementia etiologies (Early and Late-Onset AD (EOAD, LOAD), Cortico-Basal Degeneration, Lewy Body Dementia, Fronto-Temporal Dementia (FTD), Logopenic Variant of Primary Progressive Aphasia and Semantic Dementia) and depression. All patients had a routine MRI at 1, 1.5 or 3 Tesla. We first entered all ROI volumes from ASS in a univariate analysis. Then, we entered volumes obtained from each ASS separately in an SVM classifier. Finally, results where compared to a classifier based on whole brain gray matter (GM) segmentation maps using SPM12.ResultsIn the univariate classification paradigm, the diagnostic accuracy ranged from 50% to 70%, Frontal and Temporal Lobe providing the most accurate scores and hippocampal volumetry only distinguishing LOAD and EOAD from FTD with a respectively 50% and 60% accuracy. SVM classification provided similar accuracy for both ASS ranging from 60 to 80%. Nonetheless, classification using whole brain GM improved the accuracies ranging from 65 to 85% (FTD vs EAOD: 82%, EOAD vs Depression: 83%, FTD vs Depression: 82%).ConclusionsNovel computational tools can be useful in clinical practice and provide comprehensive information supporting clinicians in decision-making processes. ASS analyzed in a univariate way was moderately adequate, with poor accuracy compared with its implementation in an SVM classifier. SVM using whole brain segmentation yielded the highest diagnostic accuracies. Furthermore, SVM performed as well as published accuracies of pathophysiological markers of AD to distinguish this etiology from other dementias and depression. Implementation of whole brain SVM classification in clinical routine could represent a valuable diagnostic tool.

Ammonia oxidising bacteria (AOB) are thought to emit more nitrous oxide (N2O) than ammonia oxidising archaea (AOA), due to their higher N2O yield under oxic conditions and denitrification in response to oxygen (O2) limitation. We determined the kinetics of growth and turnover of nitric oxide (NO) and N2O at low cell densities of Nitrosomonas europaea (AOB) and Nitrosopumilus maritimus (AOA) during gradual depletion of TAN (NH3 + NH4+) and O2. Half-saturation constants for O2 and TAN were similar to those determined by others, except for the half-saturation constant for ammonium in N. maritimus (0.2 mM), which is orders of magnitudes higher than previously reported. For both strains, cell-specific rates of NO turnover and N2O production reached maxima near O2 half-saturation constant concentration (2-10 µM O2) and decreased to zero in response to complete O2-depletion. Modelling of the electron flow in N. europaea demonstrated low electron flow to denitrification (≤1.2% of the total electron flow), even at sub-micromolar O2 concentrations. The results corroborate current understanding of the role of NO in the metabolism of AOA and suggest that denitrification is inconsequential for the energy metabolism of AOB, but possibly important as a route for dissipation of electrons at high ammonium concentration. Kinetics of NH3-oxidation, NO-turnover, N2O-production and electron flow during oxygen depletion in model bacterial and archaeal ammonia oxidisers

Introduction We assessed the diagnostic accuracy of cerebrospinal fluid (CSF) YKL-40 in discriminating (1) clinical Alzheimer's disease (AD) from cognitively healthy controls (HCs) and frontotemporal dementia (FTD) (level I) and (2) patients stratified by different pathophysiological profiles from HCs and FTD following a novel unbiased/descriptive categorization based on CSF biomarkers, independent of cognitive impairment severity (level II). Methods YKL-40 was compared among HCs ( n = 21), mild cognitive impairment ( n = 41), AD ( n = 35), and FTD ( n = 9) (level I) and among HCs ( n = 21), AD pathophysiology (tau and amyloid-β) negative ( n = 15), tau positive ( n = 15), amyloid-β positive ( n = 13), AD pathophysiology positive ( n = 33), and FTD ( n = 9) (level II). Results Level I: YKL-40 discriminated AD from HC and FTD (area under the receiver operating characteristic curves [AUROCs] = 0.69, 0.71). Level II: YKL-40 discriminated tau-positive individuals and AD pathophysiology–positive individuals from HC, AD pathophysiology–positive patients from FTD (AUROCs = 0.76, 0.72, 0.73). Discussion YKL-40 demonstrates fair performance in distinguishing tau-positive patients from HCs, suggesting it may aid clinical diagnosis and support a biomarker-guided pathophysiological stratification.

International audience; Bioclimatic indices for use in studies of ecosystem function, species distribution, and vegetation dynamics under changing climate scenarios depend on estimates of surface fluxes and other quantities, such as radiation, evapotranspi-ration and soil moisture, for which direct observations are sparse. These quantities can be derived indirectly from meteorological variables, such as near-surface air temperature, precipitation and cloudiness. Here we present a consolidated set of simple process-led algorithms for simulating habitats (SPLASH) allowing robust approximations of key quantities at ecologically relevant timescales. We specify equations, derivations, simplifications, and assumptions for the estimation of daily and monthly quantities of top-of-the-atmosphere solar radiation, net surface radiation, photosynthetic photon flux density, evapotranspiration (potential, equilibrium, and actual), condensation, soil moisture, and runoff, based on analysis of their relationship to fundamental climatic drivers. The climatic drivers include a minimum of three meteorological inputs: precipitation, air temperature, and fraction of bright sunshine hours. Indices, such as the moisture index, the climatic water deficit, and the Priestley–Taylor coefficient , are also defined. The SPLASH code is transcribed in C++, FORTRAN, Python, and R. A total of 1 year of results are presented at the local and global scales to exemplify the spatiotemporal patterns of daily and monthly model outputs along with comparisons to other model results.

To successfully develop biomedical applications for magnetic nanoparticles, it is imperative that these nanoreagents maintain their magnetic properties in vivo and that their by-products are safely metabolized. When placed in biological milieu or internalized into cells, nanoparticle aggregation degree can increase which could affect magnetic properties and metabolization. To evaluate these aggregation effects, we synthesized citric acid-coated iron oxide nanoparticles whose magnetic susceptibility can be modified by aggregation in agar dilutions and dextran-layered counterparts that maintain their magnetic properties unchanged. Macrophage models were used for in vitro uptake and metabolization studies, as these cells control iron homeostasis in the organism. Electron microscopy and magnetic susceptibility studies revealed a cellular mechanism of nanoparticle degradation, in which a small fraction of the particles is rapidly degraded while the remaining ones maintain their size. Both nanoparticle types produced similar iron metabolic profiles but these profiles differed in each macrophage model. Thus, nanoparticles induced iron responses that depended on macrophage programming. In vivo studies showed that nanoparticles susceptible to changes in magnetic properties through aggregation effects had different behavior in lungs, liver and spleen. Liver ferritin levels increased in these animals showing that nanoparticles are degraded and their by-products incorporated into normal metabolic routes. These data show that nanoparticle iron metabolization depends on cell type and highlight the necessity to assess nanoparticle aggregation in complex biological systems to develop effective in vivo biomedical applications. Statement of Significance Magnetic iron oxide nanoparticles have great potential for biomedical applications. It is however imperative that these nanoreagents preserve their magnetic properties once inoculated, and that their degradation products can be eliminated. When placed in a biological milieu nanoparticles can aggregate and this can affect their magnetic properties and their degradation. In this work, we showed that iron oxide nanoparticles trigger the iron metabolism in macrophages, the main cell type involved in iron homeostasis in the organism. We also show that aggregation can affect nanoparticle magnetic properties when inoculated in animal models. This work confirms iron oxide nanoparticle biocompatibility and highlights the necessity to assess in vivo nanoparticle aggregation to successfully develop biomedical applications., José M. Rojas was supported by a JAEdoc grant co-financed by the CSIC and the European Social Fund. Laura Sanz-Ortega receives a predoctoral FPU grant (13/05037) from the Spanish Ministry of Economy and Competitiveness. Marina Talelli received a JdC post-doctoral grant (JCI-2012-13159) from the Spanish Ministry of Economy and Competitiveness. Gustavo B. da Silva was beneficiary of a sandwich-PhD grant of the Brazilian agency CNPq (Science without borders – Process: 279444/2013-9). Lucía Gutiérrez was the beneficiary of a post-doctoral grant from the AXA Research Fund and also acknowledges financial support from the Ramón y Cajal subprogram (RYC-2014-15512). This work was supported in part by grants from the Spanish Ministry of Economy and Competitiveness (SAF-2011-23639 and SAF-2014-54057-R to DFB and MAT2014-52069-R to Sabino Veintemillas-Verdaguer).

International audience; Preclinical Alzheimer's disease (AD) is a relatively recent concept describing an entity characterized by the presence of a pathophysiological biomarker signature characteristic for AD in the absence of specific clinical symptoms. There is rising interest in the scientific community to define such an early target population mainly due to failures of all recent clinical trials despite evidence of biological effects on brain amyloidosis for some compounds. A conceptual framework has recently been proposed for this preclinical phase of AD. However, few data exist on this silent stage of AD. We performed a systematic review in order to investigate how the concept is defined across studies. The review highlights the substantial heterogeneity concerning the three main determinants of preclinical AD: " normal cognition " , " cognitive decline " and " AD pathophysiological signature ". We emphasize the need for a harmonized nomenclature of the preclinical AD concept and standardized population-based and case-control studies using unified operationalized criteria.

International audience; Physiological and pathological conditions that affect the folding capacity of the endoplasmic reticulum (ER) provoke ER stress and trigger the unfolded protein response (UPR). The UPR aims to either restore the balance between newly synthesized and misfolded proteins or if the damage is severe, to trigger cell death. However, the molecular events underlying the switch between repair and cell death are not well understood. The ER-resident chaperone BiP governs the UPR by sensing misfolded proteins and thereby releasing and activating the three mediators of the UPR: PERK, IRE1 and ATF6. PERK promotes G2 cell cycle arrest and cellular repair by inducing the alternative translated p53 isoform p53ΔN40 (p53/47), which activates 14-3-3σ via suppression of p21(CDKN1A). Here we show that prolonged ER stress promotes apoptosis via a p53-dependent inhibition of BiP expression. This leads to the release of the pro-apoptotic BH3-only BIK from BiP and activation of apoptosis. Suppression of bip mRNA translation is mediated via the specific binding of p53 to the first 346-nt of the bip mRNA and via a p53 trans-suppression domain located within the first seven N-terminal amino acids of p53ΔN40. This work shows how p53 targets BiP to promote apoptosis during severe ER stress and further illustrates how regulation of mRNA translation has a key role in p53-mediated regulation of gene expression during the UPR.

HMG-box proteins, including Sox/SRY (Sox) and TCF/LEF1 (TCF) family members, bind DNA via their HMG-box. This binding, however, is relatively weak and both Sox and TCF factors employ distinct mechanisms for enhancing their affinity and specificity for DNA. Here we report that Capicua (CIC), an HMG-box transcriptional repressor involved in Ras/MAPK signaling and cancer progression, employs an additional distinct mode of DNA binding that enables selective recognition of its targets. We find that, contrary to previous assumptions, the HMG-box of CIC does not bind DNA alone but instead requires a distant motif (referred to as C1) present at the C-terminus of all CIC proteins. The HMG-box and C1 domains are both necessary for binding specific TGAATGAA-like sites, do not function via dimerization, and are active in the absence of cofactors, suggesting that they form a bipartite structure for sequence-specific binding to DNA. We demonstrate that this binding mechanism operates throughout Drosophila development and in human cells, ensuring specific regulation of multiple CIC targets. It thus appears that HMG-box proteins generally depend on auxiliary DNA binding mechanisms for regulating their appropriate genomic targets, but that each sub-family has evolved unique strategies for this purpose. Finally, the key role of C1 in DNA binding also explains the fact that this domain is a hotspot for inactivating mutations in oligodendroglioma and other tumors, while being preserved in oncogenic CIC-DUX4 fusion chimeras associated to Ewing-like sarcomas, This work was funded by grants from the Spanish Ministry of Economy and Competitiveness (MINECO) (BFU2011-23611 and BFU2014-52863-P) to GJ; the European Research Council (ERC-AG/ 250297-RAS AHEAD), the EU-Framework Programme (LSHG-CT-2007-037665/CHEMORES, HEALTH-F2-2010-259770/LUNGTARGET and HEALTH-2010-260791/EUROCANPLATFORM), the MINECO (SAF2011-30173 and SAF2014-59864-R), the Autonomous Community of Madrid (S2011/BDM-2470/ONCOCYCLE) to MB; and the Fundació La Marató de TV3 (20131730/1). LSC was supported by a fellowship from the Programa de Formación de Personal Investigador (FPI, MINECO). MB is a recipient of an Endowed Chair from the AXA Research Fund. GJ is an ICREA investigator.

Background Leptospirosis is an important re-emerging infectious disease that affects humans worldwide. Infection occurs from indirect environment-mediated exposure to pathogenic leptospires through contaminated watered environments. The ability of pathogenic leptospires to persist in the aqueous environment is a key factor in transmission to new hosts. Hence, an effort was made to detect pathogenic leptospires in complex environmental samples, to genotype positive samples and to assess leptospiral viability over time. Methodology/Principal findings We focused our study on human leptospirosis cases infected with the New Caledonian Leptospira interrogans serovar Pyrogenes. Epidemiologically related to freshwater contaminations, this strain is responsible for ca. 25% of human cases in New Caledonia. We screened soil and water samples retrieved from suspected environmental infection sites for the pathogen-specific leptospiral gene lipL-32. Soil samples from all suspected infection sites tested showed detectable levels of pathogenic leptospiral DNA. More importantly, we demonstrated by viability qPCR that those pathogenic leptospires were viable and persisted in infection sites for several weeks after the index contamination event. Further, molecular phylogenetic analyses of the leptospiral lfb-1 gene successfully linked the identity of environmental Leptospira to the corresponding human-infecting strain. Conclusions/Significance Altogether, this study illustrates the potential of quantitative viability-PCR assay for the rapid detection of viable leptospires in environmental samples, which might open avenues to strategies aimed at assessing environmental risk., Author summary Leptospirosis is an emerging zoonotic disease caused by infection with pathogenic strains of Leptospira. Most human infections arise from environmental exposure to contaminated freshwater environments or watered soils where pathogenic Leptospira are considered as able to survive for prolonged periods. Therefore, a good understanding of Leptospira survival strategy in the environment is a key step to identifying crucial factors amenable to interventions and public health actions to lower leptospirosis burden. In this study, we investigated the environmental presence and survival of pathogenic leptospires in areas where recent human leptospirosis cases had been reported. Although detection of Leptospira from complex environmental samples is difficult, we successfully detected the presence of pathogenic Leptospira in soils of suspected infection sites. In addition, we showed that these pathogenic leptospires were alive and present in soils several weeks after the infecting event. Typing of leptospiral DNA retrieved from the environment revealed identities between environmental pathogenic Leptospira and the causative strains involved in human leptospirosis index cases. Interestingly, we also identified yet unreported genotypes. Altogether, our work illustrates the potential of quantitative molecular assays for the rapid detection and typing of viable leptospires in environmental samples, which could prove useful to assess the risk of environmental exposure.

We present a novel method to quantify the ecophysiological effects of changes in CO2 concentration during the reconstruction of climate changes from fossil pollen assemblages. The method does not depend on any particular vegetation model. Instead, it makes use of general equations from ecophysiology and hydrology that link moisture index (MI) to transpiration and the ratio of leaf-internal to ambient CO2 (χ). Statistically reconstructed MI values are corrected post facto for effects of CO2 concentration. The correction is based on the principle that e, the rate of water loss per unit carbon gain, should be inversely related to effective moisture availability as sensed by plants. The method involves solving a non-linear equation that relates e to MI, temperature and CO2 concentration via the Fu-Zhang relation between evapotranspiration and MI, Monteith's empirical relationship between vapour pressure deficit and evapotranspiration, and recently developed theory that predicts the response of χ to vapour pressure deficit and temperature. The solution to this equation provides a correction term for MI. The numerical value of the correction depends on the reconstructed MI. It is slightly sensitive to temperature, but primarily sensitive to CO2 concentration. Under low LGM CO2 concentration the correction is always positive, implying that LGM climate was wetter than it would seem from vegetation composition. A statistical reconstruction of last glacial maximum (LGM, 21±1 kyr BP) palaeoclimates, based on a new compilation of modern and LGM pollen assemblage data from Australia, is used to illustrate the method in practice. Applying the correction brings pollen-reconstructed LGM moisture availability in southeastern Australia better into line with palaeohydrological estimates of LGM climate.

The evolutionary success of bacteria depends greatly on their capacity to continually generate phenotypic diversity. Structured environments are particularly favorable for diversification because of attenuated clonal interference, which renders selective sweeps nearly impossible and enhances opportunities for adaptive radiation. We examined at the microscale level the emergence and the spatial and temporal dynamics of phenotypic diversity and their underlying causes in Escherichia coli colonies. An important dynamic heterogeneity in the growth, metabolic activity, morphology, gene expression patterns, stress response induction, and death patterns among cells within colonies was observed. Genetic analysis indicated that the phenotypic variation resulted mostly from mutations and that indole production, oxidative stress, and the RpoS-regulated general stress response played an important role in the generation of diversity. We observed the emergence and persistence of phenotypic variants within single colonies that exhibited variable fitness compared to the parental strain. Some variants showed improved capacity to produce biofilms, whereas others were able to use different nutrients or to tolerate antibiotics or oxidative stress. Taken together, our data show that bacterial colonies provide an ecological opportunity for the generation and maintenance of vast phenotypic diversity, which may increase the probability of population survival in unpredictable environments.

International audience; A broad range of mortality patterns has been documented across species, some even including decreasing mortality over age. Whether there exist a common denominator to explain both similarities and differences in these mortality patterns remains an open question. The disposable soma theory, an evolutionary theory of aging, proposes that universal intracellular trade-offs between maintenance/lifespan and reproduction would drive aging across species. The disposable soma theory has provided numerous insights concerning aging processes in single individuals. Yet, which specific population mortality patterns it can lead to is still largely unexplored. In this article, we propose a model exploring the mortality patterns which emerge from an evolutionary process including only the disposable soma theory core principles. We adapt a well-known model of genomic evolution to show that mortality curves producing a kink or mid-life plateaus derive from a common minimal evolutionary framework. These mortality shapes qualitatively correspond to those of Drosophila melanogaster, Caenorhabditis elegans, medflies, yeasts and humans. Species evolved in silico especially differ in their population diversity of maintenance strategies, which itself emerges as an adaptation to the environment over generations. Based on this integrative framework, we also derive predictions and interpretations concerning the effects of diet changes and heat-shock treatments on mortality patterns.

International audience; Lumbar intervertebral discs (IVDs) are prone to degeneration upon skeletal maturity. In fact, this process could explain approximately 40% of the cases of low back pain in humans. Despite the efficiency of pain-relieving treatments, the scientific community seeks to develop innovative therapeutic approaches that might limit the use of invasive surgical procedures (e.g., spine fusion and arthroplasty). As a prerequisite to the development of these strategies, we must improve our fundamental knowledge regarding IVD path-ophysiology. Recently, several studies have demonstrated that there is a singular phenotype associated with Nucleus pulposus (NP) cells, which is distinct from that of articular chondrocytes. In parallel, recent studies concerning the origin and development of NP cells, as well as their role in intervertebral tissue homeostasis, have yielded new insights into the complex mechanisms involved in disc degeneration. This review summarizes our current understanding of IVD physiology and the complex cell-mediated processes that contribute to IVD degeneration. Collectively, these recent advances could inspire the scientific community to explore new biotherapeutic strategies.

Trabajo presentado en el EEA-ESEM: (31 Annual Congress of the European Economic Association & 69th European Meeting of the Econometric Society) celebrado en Genova del 22 al 26 de agosto de 2016, In this paper we study the role of religiosity in influencing the choice of labor effort. Many religions promote restrictions on personal liberties such as divorce, abortion, gender parity, or gay marriage. We assume that the higher the degree of religiosity of an individual the less he enjoys such personal liberties, and moreover the less he likes to be in a society which allows such liberties. The model implies that under some simple conditions, individual labor supply is decreasing in the level of religiosity and that this negative relationship is enhanced by the width of liberties. We show empirically that this holds and that the size of the effect is large. Specifically, we construct an index of personal liberties and find solid evidence in support of the joint effect of religiosity and liberties on labor effort. Our empirical results indicate that negative externalities experienced by religious individuals when society allows for or practices such personal liberties are an important part of the effect of liberties on their economic choices, Joan Esteban and Laura Mayoral gratefully acknowledge financial support from the AXA Research Fund, the Generalitat de Catalunya, and the CICYT (ECO2011-25293).

International audience; Bluetongue virus serotype 8 (BTV-8) was reported for the first time in Europe in 2006, causing the largest bluetongue outbreak ever recorded. France was mostly impacted in 2007/09. Trade restrictions were implemented all along. Vaccination became available from 2008: a limited number of doses was first administered in an emergency vaccination campaign, followed by two nationwide compulsory vaccination campaigns in 2009 and 2010. France regained a disease-free status in December 2012, but BTV may have kept circulating undetected as infected herds have been reported again since August 2015. We developed a stochastic dynamic compartmental model of BTV transmission in cattle and sheep to analyze the relative importance of vector active flight and host movements in disease spread, and assess the effectiveness of control measures. We represented BTV transmission both within and between French administrative subdivisions called cantons, during the 2007/09 outbreak and until the end of 2010, when compulsory vaccination was interrupted. Within-canton transmission was vector-borne, and between canton transmission could occur through three contact networks that accounted for movements of: (i) vectors between pastures located at close distance; (ii) cattle and sheep between pastures of the same farm; (iii) traded cattle. We estimated the model parameters by approximate Bayesian computation, using data from the 2007 French outbreak. With this framework, we were able to reproduce the BTV-8 epizootic wave. Host movements between distant pastures of the same farm were found to have a major contribution to BTV spread to disease-free areas, thus raising practical questions about herd management during outbreaks. We found that cattle trade restrictions had been well complied with; without them, the whole French territory would have been infected by winter 2007. The 2008 emergency vaccination campaign had little impact on disease spread as almost half vaccine doses had likely been administered to already immune cattle. Alternatively, establishing a vaccination buffer zone would have allowed a better control of BTV in 2008: limiting its spatial expansion and decreasing the number of infected cattle and sheep. We also showed a major role of compulsory vaccination in controlling the outbreak in 2009 and 2010, though we predicted a possible low-level circulation after the last detection.

Motivation: Sampling the conformational space of biological macromolecules generates large sets of data with considerable complexity. Data-mining techniques, such as clustering, can extract meaningful information. Among them, the self-organizing maps (SOMs) algorithm has shown great promise; in particular since its computation time rises only linearly with the size of the data set. Whereas SOMs are generally used with few neurons, we investigate here their behavior with large numbers of neurons. Results: We present here a python library implementing the full SOM analysis workflow. Large SOMs can readily be applied on heavy data sets. Coupled with visualization tools they have very interesting properties. Descriptors for each conformation of a trajectory are calculated and mapped onto a 3D landscape, the U-matrix, reporting the distance between neighboring neurons. To delineate clusters, we developed the flooding algorithm, which hierarchically identifies local basins of the U-matrix from the global minimum to the maximum. Availability and implementation: The python implementation of the SOM library is freely available on github: https://github.com/bougui505/SOM. Contact: michael.nilges@pasteur.fr or guillaume.bouvier@pasteur.fr Supplementary information: Supplementary data are available at Bioinformatics online.

The influence of microorganisms growing as sessile communities in a large number of human infections has been extensively studied and recognized for 30–40 years, therefore warranting intense scientific and medical research. Nonetheless, mimicking the biofilm-life style of bacteria and biofilm-related infections has been an arduous task. Models used to study biofilms range from simple in vitro to complex in vivo models of tissues or device-related infections. These different models have progressively contributed to the current knowledge of biofilm physiology within the host context. While far from a complete understanding of the multiple elements controlling the dynamic interactions between the host and biofilms, we are nowadays witnessing the emergence of promising preventive or curative strategies to fight biofilm-related infections. This review undertakes a comprehensive analysis of the literature from a historic perspective commenting on the contribution of the different models and discussing future venues and new approaches that can be merged with more traditional techniques in order to model biofilm-infections and efficiently fight them., Pathogens, 2 (2), ISSN:2076-0817

Questions The objectives of this study were to examine altitudinal shifts in tree species distributions over one decade to quantify the potential for tree migration. Location Spain. Methods We analysed presence-absence data using two successive surveys of the Spanish Forest Inventory in five Fagaceae tree species (two temperate Fagus sylvatica and Quercus petraea, one sub-Mediterranean Q. faginea and two Mediterranean Q. suber and Q. ilex) in two mountain ranges (the Pyrenees and the Iberian system). Half of the fitted altitudinal distributions were skewed and required use of an asymmetric model for unbiased estimates of optimum altitude and changes in the probability of presence along the altitudinal gradient. For each species and mountain range, shifts were considered to have occurred when the difference in optimum altitude was significant or when differences in probability of occurrence between the two surveys demonstrated the occurrence of colonization or extirpation events. Results Overall, depending on species and mountain range, shifts in optimum altitude ranged between -34 m and +181 m. The altitudinal distribution of the Mediterranean species at the core of their latitudinal distribution range presented no sign of change. For the temperate and sub-Mediterranean Fagaceae species, the patterns demonstrated the existence of distribution changes over a 10-yr period. The largest, although not statistically significant, upward shift in optimum altitude was observed for Q. petraea in the Iberian system. More interestingly, its distribution indicated colonization events at higher altitudes. For Q. faginea in the Pyrenees, the shift in optimum altitude was the second largest and statistically significant, and was associated with large extirpation events at the lower altitudes. No evidence of shifts was observed for F. sylvatica. Conclusion: This work demonstrates that changes in altitudinal distribution could occur over a 10-yr time period for tree species located at the southern limit of their distribution, such as some temperate and sub-Mediterranean oaks, whereas no movement was detected for Mediterranean oaks in the core of their distribution area. © 2013 International Association for Vegetation Science.

Nitrogen content per unit leaf area (Narea) is a key variable in plant functional ecology and biogeochemistry. Narea comprises a structural component, which scales with leaf mass per area (LMA), and a metabolic component, which scales with Rubisco capacity. The co-ordination hypothesis, as implemented in LPJ and related global vegetation models, predicts that Rubisco capacity should be directly proportional to irradiance but should decrease with increases in ci : ca and temperature because the amount of Rubisco required to achieve a given assimilation rate declines with increases in both. We tested these predictions using LMA, leaf δ13C, and leaf N measurements on complete species assemblages sampled at sites on a north–south transect from tropical to temperate Australia. Partial effects of mean canopy irradiance, mean annual temperature, and ci : ca (from δ13C) on Narea were all significant and their directions and magnitudes were in line with predictions. Over 80 % of the variance in community-mean (ln) Narea was accounted for by these predictors plus LMA. Moreover, Narea could be decomposed into two components, one proportional to LMA (slightly steeper in N-fixers), and the other to Rubisco capacity as predicted by the co-ordination hypothesis. Trait gradient analysis revealed ci : ca to be perfectly plastic, while species turnover contributed about half the variation in LMA and Narea. Interest has surged in methods to predict continuous leaf-trait variation from environmental factors, in order to improve ecosystem models. Coupled carbon–nitrogen models require a method to predict Narea that is more realistic than the widespread assumptions that Narea is proportional to photosynthetic capacity, and/or that Narea (and photosynthetic capacity) are determined by N supply from the soil. Our results indicate that Narea has a useful degree of predictability, from a combination of LMA and ci : ca – themselves in part environmentally determined – with Rubisco activity, as predicted from local growing conditions. This finding is consistent with a plant-centred approach to modelling, emphasizing the adaptive regulation of traits. Models that account for biodiversity will also need to partition community-level trait variation into components due to phenotypic plasticity and/or genotypic differentiation within species vs. progressive species replacement, along environmental gradients. Our analysis suggests that variation in Narea is about evenly split between these two modes.

International audience; Whether an individual becomes infected in an infectious disease outbreak depends on many interconnected risk factors, which may relate to characteristics of the individual (e.g., age, sex), his or her close relatives (e.g., household members), or the wider community. Studies monitoring individuals in households or schools have helped elucidate the determinants of transmission in small social structures due to advances in statistical modeling; but such an approach has so far largely failed to consider individuals in the wider context they live in. Here, we used an outbreak of chikungunya in a rural community in Bangladesh as a case study to obtain a more comprehensive characterization of risk factors in disease spread. We developed Bayesian data augmentation approaches to account for uncertainty in the source of infection, recall uncertainty, and unobserved infection dates. We found that the probability of chikungunya transmission was 12% [95% credible interval (CI): 8–17%] between household members but dropped to 0.3% for those living 50 m away (95% CI: 0.2–0.5%). Overall, the mean transmission distance was 95 m (95% CI: 77–113 m). Females were 1.5 times more likely to become infected than males (95% CI: 1.2–1.8), which was virtually identical to the relative risk of being at home estimated from an independent human movement study in the country. Reported daily use of antimosquito coils had no detectable impact on transmission. This study shows how the complex interplay between the characteristics of an individual and his or her close and wider environment contributes to the shaping of infectious disease epidemics.

Terrestrial ecosystems play a significant role in the global carbon cycle and offset a large fraction of anthropogenic CO2 emissions. The terrestrial carbon sink is increasing, yet the mechanisms responsible for its enhancement, and implications for the growth rate of atmospheric CO2, remain unclear. Here using global carbon budget estimates, ground, atmospheric and satellite observations, and multiple global vegetation models, we report a recent pause in the growth rate of atmospheric CO2, and a decline in the fraction of anthropogenic emissions that remain in the atmosphere, despite increasing anthropogenic emissions. We attribute the observed decline to increases in the terrestrial sink during the past decade, associated with the effects of rising atmospheric CO2 on vegetation and the slowdown in the rate of warming on global respiration. The pause in the atmospheric CO2 growth rate provides further evidence of the roles of CO2 fertilization and warming-induced respiration, and highlights the need to protect both existing carbon stocks and regions, where the sink is growing rapidly., Year-to-year variability in atmospheric CO2 is strongly influenced by the terrestrial biosphere. Despite increasing anthropogenic emissions, Keenan et al. report a recent pause in the growth rate of atmospheric CO2 using observations and vegetation models, attributed to an enhanced terrestrial carbon sink.

et al., Fasting is a physiological stress that elicits well-known metabolic adaptations, however, little is known about the role of stress-responsive tumor suppressors in fasting. Here, we have examined the expression of several tumor suppressors upon fasting in mice. Interestingly, p21 mRNA is uniquely induced in all the tissues tested, particularly in liver and muscle (>10 fold), and this upregulation is independent of p53. Remarkably, in contrast to wild-type mice, p21-null mice become severely morbid after prolonged fasting. The defective adaptation to fasting of p21-null mice is associated to elevated energy expenditure, accelerated depletion of fat stores, and premature activation of protein catabolism in the muscle. Analysis of the liver transcriptome and cell-based assays revealed that the absence of p21 partially impairs the transcriptional program of PPARα, a key regulator of fasting metabolism. Finally, treatment of p21-null mice with a PPARα agonist substantially protects them from their accelerated loss of fat upon fasting. We conclude that p21 plays a relevant role in fasting adaptation through the positive regulation of PPARα., E.L.-G. was recipient of a predoctoral contract from the Spanish Ministry of Education. P.J.F.-M. has been funded by the Spanish Association Against Cancer (aecc). Work in the laboratory of M.S. is funded by the CNIO and by grants from the Spanish Ministry of Economy co-funded by the European Regional Development Fund (SAF project), the European Research Council (ERC Advanced Grant), the Regional Government of Madrid co-funded by the European Social Fund (ReCaRe project), the Botin Foundation and Banco Santander (Santander Universities Global Division), the Ramon Areces Foundation, and the AXA Foundation.

We report that two laboratory colonies of Culex quinquefasciatus and Culex pipiens mosquitoes were experimentally unable to transmit ZIKV either up to 21 days post an infectious blood meal or up to 14 days post intrathoracic inoculation. Infectious viral particles were detected in bodies, heads or saliva by a plaque forming unit assay on Vero cells. We therefore consider it unlikely that Culex mosquitoes are involved in the rapid spread of ZIKV.

In an effort to limit global temperature rise to well below 2˚C, the COP21 Paris Agreement stipulates that a ‘balance’ between anthropogenic (man-made) sources and sinks of greenhouse gases must be reached by 2050-2100. An overall greenhouse gas ‘balance’ must consider individual gases in terms of how strongly they absorb solar infrared radiation, their concentration in the atmosphere, and their lifetime in the atmosphere. • Long-lived greenhouse gases, including carbon dioxide (CO2), accumulate in the atmosphere and continue to affect the climate for many centuries. To stabilise the concentrations of these long-lived gases, and thereby their effect on the climate, their sources must be progressively reduced towards zero. • For short-lived greenhouse gases that remain in the atmosphere for less than 100 years, including methane, stable or decreasing concentrations could be achieved within decades if emissions were stabilised or decreased. However, these gases currently only contribute about 20% of the total warming from greenhouse gases, so their reduction alone cannot successfully stabilise global temperature. • An overall ‘balance’ of sources and sinks of greenhouse gases could be facilitated by deliberate removal of CO2 from the atmosphere, for example, by combining biomass energy production with carbon capture and storage. Most current greenhouse gas emission scenarios that keep global temperature rise below 2˚C include some deliberate removal of CO2 to compensate for continued emissions of CO2 and other greenhouse gases

Purpose In a modern world increasingly perceived as uncertain, the mere purchase of a household cleaning product, or a seemingly harmless bottle of milk, conveys interrogations about potential hazards, from environmental to health impacts. The main purpose of this paper is to suggest that risk could be considered as one of the major dimensions of choice for a wide range of concerns and markets, alongside aspiration/satisfaction, and tackled efficiently by mobilizing the recent findings of cognitive sciences, neurosciences and evolutionary psychology. It is felt that consumer research could benefit more widely from psychological and evolutionary-grounded risk theories. Design/methodology/approach In this study, some 50 years of marketing management literature, as well as risk-specialized literature, was examined in an attempt to get a grasp of how risk is handled by consumer sciences and of whether they make some use of the most recent academic works on mental biases, non-mainstream decision-making processes or evolutionary roots of behavior. We then tested and formulated several hypotheses regarding risk profiles and preferences in the sector of insurance, by participating in an Axa Research Fund–Paris School of Economics research project. Findings It is suggested that consumer profiles could be enriched by risk-taking attitudes, that risk could be part of the “reason why” of brand positioning, and that brand, as well as public policy communication, could benefit from a targeted use of risk perception biases. Originality/value This paper proposes to apply evolutionary-based psychological concepts to build perceptual maps describing people and consumers on both aspiration and risk attitude axis, and to design communication tools according to psychological research on message framing and biases. Such an approach mobilizes not only the recent findings of cognitive sciences and neurosciences but also the understanding of the roots of risk attitudes and perception. Those maps and framing could probably be applied to many sectors, markets and public issues, from commodities to personal products and services (food, luxury goods, electronics, financial products, tourism, design or insurance).

International audience; Rapidly treating infections with adequate antibiotics is of major importance. This requires a fast and accurate determination of the antibiotic susceptibility of bacterial pathogens. The most frequently used methods are slow because they are based on the measurement of growth inhibition. Faster methods, such as PCR-based detection of determinants of antibiotic resistance, do not always provide relevant information on susceptibility, particularly that which is not genetically based. Consequently, new methods, such as the detection of changes in bacterial physiology caused by antibiotics using flow cytometry and fluorescent viability markers, are being explored. In this study, we assessed whether Alexa Fluor® 633 Hydrazide (AFH), which targets carbonyl groups, can be used for antibiotic susceptibility testing. Carbonylation of cellular macromolecules, which increases in antibiotic-treated cells, is a particularly appropriate to assess for this purpose because it is irreversible. We tested the susceptibility of clinical isolates of Gram-negative bacteria, Escherichia coli and Pseudomonas aeruginosa, to antibiotics from the three classes: β-lactams, aminoglycosides, and fluoroquinolones. In addition to AFH, we used TO-PRO®-3, which enters cells with damaged membranes and binds to DNA, and DiBAC4 (3), which enters cells with depolarized membranes. We also monitored antibiotic-induced morphological alterations of bacterial cells by analyzing light scattering signals. Although all tested dyes and light scattering signals allowed for the detection of antibiotic-sensitive cells, AFH proved to be the most suitable for the fast and reliable detection of antibiotic susceptibility.

Part I comprises three chapters (2-4) that analyse the optimal combination of a universal benefit (B≥0) and categorical benefit (C≥0) for an economy where individuals differ in both their ability to work and, if able to work, their productivity. C is ex-ante conditioned on applicants being unable to work, and ex-post conditioned on recipients not working. In Chapter 2 the benefit budget is fixed but the test awarding C makes Type I and Type II errors. Type I errors guarantee B>0 at the optimum to ensure all unable individuals have positive consumption. The analysis with Type II errors depends on the enforcement of the ex-post condition. Under No Enforcement C>0 at the optimum conditional on the awards test having some discriminatory power; whilst maximum welfare falls with both error propensities. Under Full Enforcement C>0 at the optimum always; and whilst maximum welfare falls with the Type I error propensity it may increase with the Type II error propensity. Chapters 3 and 4 generalise the analysis to a linear-income tax framework. In Chapter 3 categorical status is perfectly observable. Optimal linear and piecewise-linear tax expressions are written more generally to capture cases where it is suboptimal to finance categorical transfers to eliminate inequality in the average social marginal value of income. Chapter 4 then derives the optimal linear income tax for the case with classification errors and Full Enforcement. Both equity and efficiency considerations capture the incentives an increase in the tax rate generates for able individuals to apply for C. Part II (Chapter 5) focuses on the decisions of individuals to work when receiving C, given a risk of being detected and fined proportional to C. Under CARA preferences the risk premium associated with the variance in benefit income is convex-increasing in C, thus giving C a role in enforcement.