Methicillin-Resistant Coagulase-Negative Staphylococci in the Community: High Homology of SCCmec IVa between Staphylococcus epidermidis and Major Clones of Methicillin-Resistant Staphylococcus aureus

Background. Data on community spread of methicillin-resistant coagulase-negative staphylococci (MR-CoNS) are scarce. We assessed their potential role as a reservoir of staphylococcal cassette chromosome mec (SCCmec) IVa, the leading SCCmec subtype in community-acquired methicillin-resistant Staphylococcus aureus (CA-MRSA). Methods. Nasal carriage of MR-CoNS was prospectively investigated in 291 adults at hospital admission. MR-CoNS were characterized by SCCmec typing, long-range polymerase chain reaction (PCR) for SCCmec IV, and multiple-locus variable-number tandem repeat analysis (MLVA) for Staphylococcus epidermidis (MRSE) strains. Three SCCmec IVa elements were fully sequenced. Results. The carriage rate of MR-CoNS was 19.2% (25.9% and 16.5% in patients with and patients without previous exposure to the health care system, respectively; P = .09). MR-CoNS strains (n=83, including 58 MRSE strains with highly heterogeneous MLVA patterns) carried SCCmec type IVa (n=9, all MRSE), other SCCmec IV subtypes (n=9, including 7 MRSE), other SCCmec types (n=15), and nontypeable SCCmec (n=50). Long-range PCR indicated structural homology between SCCmec IV in MRSE and that in MRSA. Complete sequences of SCCmec IVa from 3 MRSE strains were highly homologous to those available for CA-MRSA, including major clones USA300 and USA400. Conclusions. MR-CoNS are probably disseminated in the community, notably in subjects without previous exposure to the health care system. MRSE, the most prevalent species, may act as a reservoir of SCCmec IVa for CA-MRS

Sucrose interacts with auxin in the burst of axillary buds

National audienceResearch focus. Branching is an important process for productivity (number of productive branches) and for visual quality of ornamental plants (branches spatial arrangement). But branching behaviour is difficult to predict due to the lack of knowledge on the all mechanisms regulating the plasticity of the burst of axillary buds. Auxin has an inhibitory action on bud burst and interacts with cytokinins (CKs) and strigolactones (SLs) [1]. Our study focuses on understanding and modelling how a newly-identified player, sugars [2,3], interact with the hormonal network to control bud burst. Methods. Experiments consisted in cultivating nodal stem segments of rosebush in vitro with different sucrose and auxin levels, and in quantifying bud elongation, CK level, and the expression of genes involve in SL biosynthesis and signalling. From these data, we designed and calibrated a computational model accounting for sucrose modulation of bud inhibition by auxin. Results. We observed that increasing sucrose level decreased the inhibition of bud elongation by auxin, so that buds fed with high sucrose level were less inhibited by a given amount of auxin than those fed with low sucrose level. In accordance with literature, auxin repressed CKs and stimulated the expression of SLs biosynthesis genes. We demonstrate that the main effect of sucrose was to repress SL signalling. The model developed from these results reproduced the combined action of sucrose and auxin on bud burst. We validated it for its capacity to predict the effect of external CK supply for different sucrose levels. Conclusions. Our study proposes for the first time a physiological model of the effect of sucrose on bud regulation by auxin at the scale of the bud. Initially observed for rosebush, our results were also validated in pea, demonstrating model genericity. Next step is to understand the role of sugars, together with hormones, in the spatio-temporal regulation of bud burst at the scale of the plant. For that, we will use the computational tool, by coupling our bud model to models simulating sugar and hormone fluxes within a plant architecture

Measurement of the Tau Lepton Polarisation at LEP2

A first measurement of the average polarisation P_tau of tau leptons produced in e+e- annihilation at energies significantly above the Z resonance is presented. The polarisation is determined from the kinematic spectra of tau hadronic decays. The measured value P_tau = -0.164 +/- 0.125 is consistent with the Standard Model prediction for the mean LEP energy of 197 GeV.A first measurement of the average polarisation Pτ of tau leptons produced in e + e − annihilation at energies significantly above the Z resonance is presented. The polarisation is determined from the kinematic spectra of tau hadronic decays. The measured value Pτ=−0.164±0.125 is consistent with the Standard Model prediction for the mean LEP energy of 197 GeV.A first measurement of the average polarisation P_tau of tau leptons produced in e+e- annihilation at energies significantly above the Z resonance is presented. The polarisation is determined from the kinematic spectra of tau hadronic decays. The measured value P_tau = -0.164 +/- 0.125 is consistent with the Standard Model prediction for the mean LEP energy of 197 GeV

Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA’s Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI’s footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI’s waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available

Sex-based differences in ICU management and outcomes of immunocompromised patients:A post hoc analysis of the prospective multicenter multinational Efraim cohort

Purpose: There may be sex-based disparities in intensive care unit (ICU) management and outcomes. We compared baseline variables, interventions, and outcomes of immunocompromised critically ill men and women. Methods: We performed a post hoc analysis of the Efraim study, a prospective multinational cohort study of immunocompromised adults with acute hypoxemic respiratory failure admitted to one of 68 ICU in 16 countries between November 2015 and July 2016. We compared in unadjusted and adjusted analyses baseline variables, ICU interventions, and outcomes between men and women. Results: We included 1536 immunocompromised adults (922 men, 614 women) in this study. Women and men had similar age, BMI, and diagnoses leading to immunosuppression; hematopoietic cell transplant was more common in men. On the first ICU day, SOFA score was higher in men vs. women (7 [IQR 4–10] vs 6 [4–10]), p = 0.0005). The use of ICU supportive interventions, including mechanical ventilation, vasopressors, renal replacement, bronchoalveolar lavage, and ARDS adjuncts, were similar between men and women; as were mortality in ICU, in hospital, and at 90 days. After adjustment, female sex (sub-hazard ratio 1.19, 95 % CI 1.05–1.36, p = 0.007), SOFA score on ICU day 1 (sHR 1.16, 95 % CI 1.12–1.19, p &lt; 0.001) and chronic kidney disease (sHR 0.74, 95 % CI 0.59–0.93, p = 0.009) were associated with mechanical ventilation. Age, performance status and SOFA score on ICU day 1 were associated with hospital mortality. Conclusions: In this post hoc analysis of immunocompromised adult ICU patients with hypoxemic respiratory failure, women and men received similar ICU interventions, and had similar outcomes.</p

Influenza and associated co-infections in critically ill immunosuppressed patients

Abstract Background It is unclear whether influenza infection and associated co-infection are associated with patient-important outcomes in critically ill immunocompromised patients with acute respiratory failure. Methods Preplanned secondary analysis of EFRAIM, a prospective cohort study of 68 hospitals in 16 countries. We included 1611 patients aged 18 years or older with non-AIDS-related immunocompromise, who were admitted to the ICU with acute hypoxemic respiratory failure. The main exposure of interest was influenza infection status. The primary outcome of interest was all-cause hospital mortality, and secondary outcomes ICU length of stay (LOS) and 90-day mortality. Results Influenza infection status was categorized into four groups: patients with influenza alone (n = 95, 5.8%), patients with influenza plus pulmonary co-infection (n = 58, 3.6%), patients with non-influenza pulmonary infection (n = 820, 50.9%), and patients without pulmonary infection (n = 638, 39.6%). Influenza infection status was associated with a requirement for intubation and with LOS in ICU (P < 0.001). Patients with influenza plus co-infection had the highest rates of intubation and longest ICU LOS. On crude analysis, influenza infection status was associated with ICU mortality (P < 0.001) but not hospital mortality (P = 0.09). Patients with influenza plus co-infection and patients with non-influenza infection alone had similar ICU mortality (41% and 37% respectively) that was higher than patients with influenza alone or those without infection (33% and 26% respectively). A propensity score-matched analysis did not show a difference in hospital mortality attributable to influenza infection (OR = 1.01, 95%CI 0.90–1.13, P = 0.85). Age, severity scores, ARDS, and performance status were all associated with ICU, hospital, and 90-day mortality. Conclusions Category of infectious etiology of respiratory failure (influenza, non-influenza, influenza plus co-infection, and non-infectious) was associated with ICU but not hospital mortality. In a propensity score-matched analysis, influenza infection was not associated with the primary outcome of hospital mortality. Overall, influenza infection alone may not be an independent risk factor for hospital mortality in immunosuppressed patients

Consistent patterns of common species across tropical tree communities

D.L.M.C. was supported by the London Natural Environmental Research Council Doctoral Training Partnership grant (grant no. NE/L002485/1). This paper developed from analysing data from the African Tropical Rainforest Observatory Network (AfriTRON), curated at ForestPlots.net. AfriTRON has been supported by numerous people and grants since its inception. We sincerely thank the people of the many villages and local communities who welcomed our field teams and without whose support this work would not have been possible. Grants that have funded the AfriTRON network, including data in this paper, are a European Research Council Advanced Grant (T-FORCES; 291585; Tropical Forests in the Changing Earth System), a NERC standard grant (NER/A/S/2000/01002), a Royal Society University Research Fellowship to S.L.L., a NERC New Investigators Grant to S.L.L., a Philip Leverhulme Award to S.L.L., a European Union FP7 grant (GEOCARBON; 283080), Leverhulme Program grant (Valuing the Arc); a NERC Consortium Grant (TROBIT; NE/D005590/), NERC Large Grant (CongoPeat; NE/R016860/1) the Gordon and Betty Moore Foundation the David and Lucile Packard Foundation, the Centre for International Forestry Research (CIFOR), and Gabon’s National Parks Agency (ANPN). This paper was supported by ForestPlots.net approved Research Project 81, ‘Comparative Ecology of African Tropical Forests’. The development of ForestPlots.net and data curation has been funded by several grants, including NE/B503384/1, NE/N012542/1, ERC Advanced Grant 291585—‘T-FORCES’, NE/F005806/1, NERC New Investigators Awards, the Gordon and Betty Moore Foundation, a Royal Society University Research Fellowship and a Leverhulme Trust Research Fellowship. Fieldwork in the Democratic Republic of the Congo (Yangambi and Yoko sites) was funded by the Belgian Science Policy Office BELSPO (SD/AR/01A/COBIMFO, BR/132/A1/AFRIFORD, BR/143/A3/HERBAXYLAREDD, FED-tWIN2019-prf-075/CongoFORCE, EF/211/TREE4FLUX); by the Flemish Interuniversity Council VLIR-UOS (CD2018TEA459A103, FORMONCO II); by L’Académie de recherche et d’enseignement supérieur ARES (AFORCO project) and by the European Union through the FORETS project (Formation, Recherche, Environnement dans la TShopo) supported by the XIth European Development Fund. EMV was supported by fellowship from the CNPq (Grant 308543/2021-1). RAPELD plots in Brazil were supported by the Program for Biodiversity Research (PPBio) and the National Institute for Amazonian Biodiversity (INCT-CENBAM). BGL post-doc grant no. 2019/03379-4, São Paulo Research Foundation (FAPESP). D.A.C. was supported by the CCI Collaborative fund. Plots in Mato Grosso, Brazil, were supported by the National Council for Scientific and Technological Development (CNPq), PELD-TRAN 441244/2016-5 and 441572/2020-0, and Mato Grosso State Research Support Foundation (FAPEMAT)—0346321/2021. We thank E. Chezeaux, R. Condit, W. J. Eggeling, R. M. Ewers, O. J. Hardy, P. Jeanmart, K. L. Khoon, J. L. Lloyd, A. Marjokorpi, W. Marthy, H. Ntahobavuka, D. Paget, J. T. A. Proctor, R. P. Salomão, P. Saner, S. Tan, C. O. Webb, H. Woell and N. Zweifel for contributing forest inventory data. We thank numerous field assistants for their invaluable contributions to the collection of forest inventory data, including A. Nkwasibwe, ITFC field assistant.Peer reviewe

Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (similar to 25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available

Consistent patterns of common species across tropical tree communities

Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees