TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

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

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Urocortin protects chondrocytes from NO-induced apoptosis: a future therapy for osteoarthritis?

Osteoarthritis (OA) is characterized by a loss of joint mobility and pain resulting from progressive destruction and loss of articular cartilage secondary to chondrocyte death and/ or senescence. Certain stimuli including nitric oxide (NO) and the pro-inflammatory cytokine tumor necrosis factor α (TNF-α have been implicated in this chondrocyte death and the subsequent accelerated damage to cartilage. In this study, we demonstrate that a corticotrophin releasing factor (CRF) family peptide, urocortin (Ucn), is produced by a human chondrocyte cell line, C-20/A4, and acts both as an endogenous survival signal and as a cytoprotective agent reducing the induction of apoptosis by NO but not TNF-α when added exogenously. Furthermore, treatment with the NO donor S-nitroso-N-acetyl-D-L-penicillamine upregulates chondrocyte Ucn expression, whereas treatment with TNF-α does not. The chondroprotective effects of Ucn are abolished by both specific ligand depletion (with an anti-Ucn antibody) and by CRF receptor blockade with the pan-CRFR antagonist α-helical CRH(9-41). CRFR expression was confirmed by reverse transcription-PCR with subsequent amplicon sequence analysis and demonstrates that C-20/A4 cells express both CRFR1 and CRFR2, specifically CRFR1α and CRFR2β. Protein expression of these receptors was confirmed by western blotting. The presence of both Ucn and its receptors in these cells, coupled with the induction of Ucn by NO, suggests the existence of an endogenous autocrine/paracrine chondroprotective mechanism against stimuli inducing chondrocyte apoptosis via the intrinsic/mitochondrial pathway

Risk factors for incident falls in older men and women:The English longitudinal study of ageing

Background: falls are a major cause of disability and death in older people, particularly women. Cross-sectional surveys suggest that some risk factors associated with a history of falls may be sex-specific, but whether risk factors for incident falls differ between the sexes is unclear. We investigated whether risk factors for incident falls differ between men and women.Methods: participants were 3298 people aged ≥60 who took part in the Waves 4-6 surveys of the English Longitudinal Study of Ageing. At Wave 4, they provided information about sociodemographic, lifestyle, behavioural and medical factors and had their physical and cognitive function assessed. Data on incident falls during the four-year follow-up period was collected from them at Waves 5 and 6. Poisson regression with robust variance estimation was used to derive relative risks (RR) for the association between baseline characteristics and incident falls.Results: in multivariable-adjusted models that also controlled for history of falls, older age was the only factor associated with increased risk of incident falls in both sexes. Some factors were only predictive of falls in one sex, namely more depressive symptoms (RR (95% CI) 1.03 (1.01,1.06)), incontinence (1.12 (1.00,1.24)) and never having married in women (1.26 (1.03,1.53)), and greater comorbidity (1.04 (1.00,1.08)), higher levels of pain (1.10 (1.04,1.17) and poorer balance, as indicated by inability to attempt a full-tandem stand, (1.23 (1.04,1.47)) in men. Of these, only the relationships between pain, balance and comorbidity and falls risk differed significantly by sex.Conclusions: there were some differences between the sexes in risk factors for incident falls. Our observation that associations between pain, balance and comorbidity and incident falls risk varied by sex needs further investigation in other cohorts. <br/

Chondroprotection by urocortin involves blockade of the mechanosensitive ion channel Piezo1

Osteoarthritis (OA) is characterised by progressive destruction of articular cartilage and chondrocyte cell death. Here, we show the expression of the endogenous peptide urocortin1 (Ucn1) and two receptor subtypes, CRF-R1 and CRF-R2, in primary human articular chondrocytes (AC) and demonstrate its role as an autocrine/paracrine pro-survival factor. This effect could only be removed using the CRF-R1 selective antagonist CP-154526, suggesting Ucn1 acts through CRF-R1 when promoting chondrocyte survival. This cell death was characterised by an increase in p53 expression, and cleavage of caspase 9 and 3. Antagonism of CRF-R1 with CP-154526 caused an accumulation of intracellular calcium (Ca2+) over time and cell death. These effects could be prevented with the non-selective cation channel blocker Gadolinium (Gd3+). Therefore, opening of a non-selective cation channel causes cell death and Ucn1 maintains this channel in a closed conformation. This channel was identified to be the mechanosensitive channel Piezo1. We go on to determine that this channel inhibition by Ucn1 is mediated initially by an increase in cyclic adenosine monophosphate (cAMP) and a subsequent inactivation of phospholipase A2 (PLA2), whose metabolites are known to modulate ion channels. Knowledge of these novel pathways may present opportunities for interventions that could abrogate the progression of OA

Unraveling infectious structures, strain variants and species barriers for the yeast prion [PSI+]

Prions are proteins that can access multiple conformations, at least one of which is beta-sheet rich, infectious and self-perpetuating in nature. These infectious proteins show several remarkable biological activities, including the ability to form multiple infectious prion conformations, also known as strains or variants, encoding unique biological phenotypes, and to establish and overcome prion species (transmission) barriers. In this Perspective, we highlight recent studies of the yeast prion [PSI+], using various biochemical and structural methods, that have begun to illuminate the molecular mechanisms by which self-perpetuating prions encipher such biological activities. We also discuss several aspects of prion conformational change and structure that remain either unknown or controversial, and we propose approaches to accelerate the understanding of these enigmatic, infectious conformers

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Pneumatic wound compression after hip fracture surgery did not reduce postoperative blood transfusion: A randomized controlled trial involving 292 fractures

Background and purpose Patients with fracture of the proximal femur often undergo blood transfusion. A pneumatic compression bandage has been shown to reduce transfusion after primary hip arthroplasty for osteoarthritis. In this randomized trial, we evaluated the efficacy of this bandage following surgery for hip fracture

Predictors of outcome in infant and toddlers functional or behavioral disorders after a brief parent–infant psychotherapy

The efficacy of parent–child psychotherapies is widely recognized today. There are, however, less data on predictive factors for outcome in infants and toddlers and their parents. The aim of this study was to highlight predictive factors for outcome after a brief psychotherapy in a population of 49 infants and toddlers aged 3–30 months presenting functional or behavioral disorders. Two assessments were performed, the first before treatment and the second a month after the end of the therapy. These assessments included an evaluation of the child’s symptoms, and of depressive or anxiety symptoms in the parents. The assessments after therapy show complete or partial improvement in the child’s symptoms for nearly three quarters, and a decrease in the number of anxious and depressive mothers, and also in the number of depressive fathers. Three independent factors appear as predictive of unfavorable outcome for the child: frequency and intensity of behavioral problems and fears, and the absence of the father at more than two-thirds of consultations. The outcome for the mother is associated solely with her anxiety score at the start of the therapy. This study underlines the particular difficulties involved in the treatment of infants and toddlers presenting behavioral disturbances and emotional difficulties, and the value of involving the father in treatment

Automatic detection for bioacoustic research: a practical guide from and for biologists and computer scientists

Recent years have seen a dramatic rise in the use of passive acoustic monitoring (PAM) for biological and ecological applications, and a corresponding increase in the volume of data generated. However, data sets are often becoming so sizable that analysing them manually is increasingly burdensome and unrealistic. Fortunately, we have also seen a corresponding rise in computing power and the capability of machine learning algorithms, which offer the possibility of performing some of the analysis required for PAM automatically. Nonetheless, the field of automatic detection of acoustic events is still in its infancy in biology and ecology. In this review, we examine the trends in bioacoustic PAM applications, and their implications for the burgeoning amount of data that needs to be analysed. We explore the different methods of machine learning and other tools for scanning, analysing, and extracting acoustic events automatically from large volumes of recordings. We then provide a step-by-step practical guide for using automatic detection in bioacoustics. One of the biggest challenges for the greater use of automatic detection in bioacoustics is that there is often a gulf in expertise between the biological sciences and the field of machine learning and computer science. Therefore, this review first presents an overview of the requirements for automatic detection in bioacoustics, intended to familiarise those from a computer science background with the needs of the bioacoustics community, followed by an introduction to the key elements of machine learning and artificial intelligence that a biologist needs to understand to incorporate automatic detection into their research. We then provide a practical guide to building an automatic detection pipeline for bioacoustic data, and conclude with a discussion of possible future directions in this field