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

Signatures of arithmetic simplicity in metabolic network architecture

Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. While these are the best characterized networks in living systems, understanding their evolutionary history and complex wiring constitutes one of the most fascinating open questions in biology, intimately related to the enigma of life's origin itself. Is the evolution of metabolism subject to general principles, beyond the unpredictable accumulation of multiple historical accidents? Here we search for such principles by applying to an artificial chemical universe some of the methodologies developed for the study of genome scale models of cellular metabolism. In particular, we use metabolic flux constraint-based models to exhaustively search for artificial chemistry pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles and hierarchical modules, the appearance of universally preferable metabolites and reactions, and a logarithmic trend of pathway length as a function of input/output molecule size. Some of these properties can be derived analytically, borrowing methods previously used in cryptography. In addition, by mapping biochemical networks onto a simplified carbon atom reaction backbone, we find that several of the properties predicted by the artificial chemistry model hold for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity

Observation of Bc+ →j /ψD (∗)K (∗) decays

A search for the decays B+c→J/ψD(*)0K+ and B+c→J/ψD(*)+K*0 is performed with data collected at the LHCb experiment corresponding to an integrated luminosity of 3 fb−1. The decays B+c→J/ψ0K+ and B+c→J/ψD*0K+ are observed for the first time, while first evidence is reported for the B+c→JψD*+K*0 and B+c→J/ψD+K*0 decays. The branching fractions of these decays are determined relative to the B+c→J/ψπ+ decay. The B+c mass is measured, using the J/ψD0K+ final state, to be 6274.28±1.40(stat)±0.32(syst) MeV/c2. This is the most precise single measurement of the B+c mass to date

Evolution of sex-specific pace-of-life syndromes: genetic architecture and physiological mechanisms

Sex differences in life history, physiology, and behavior are nearly ubiquitous across taxa, owing to sex-specific selection that arises from different reproductive strategies of the sexes. The pace-of-life syndrome (POLS) hypothesis predicts that most variation in such traits among individuals, populations, and species falls along a slow-fast pace-of-life continuum. As a result of their different reproductive roles and environment, the sexes also commonly differ in pace-of-life, with important consequences for the evolution of POLS. Here, we outline mechanisms for how males and females can evolve differences in POLS traits and in how such traits can covary differently despite constraints resulting from a shared genome. We review the current knowledge of the genetic basis of POLS traits and suggest candidate genes and pathways for future studies. Pleiotropic effects may govern many of the genetic correlations, but little is still known about the mechanisms involved in trade-offs between current and future reproduction and their integration with behavioral variation. We highlight the importance of metabolic and hormonal pathways in mediating sex differences in POLS traits; however, there is still a shortage of studies that test for sex specificity in molecular effects and their evolutionary causes. Considering whether and how sexual dimorphism evolves in POLS traits provides a more holistic framework to understand how behavioral variation is integrated with life histories and physiology, and we call for studies that focus on examining the sex-specific genetic architecture of this integration

A study of the Z production cross-section in pp collisions at √s = 7 using tau final states

A measurement of the inclusive Z → ττ cross-section in pp collisions at √s =7 is presented based on a dataset of 1.0 fb[superscript −1] collected by the LHCb detector. Candidates for Z → τ τ decays are identified through reconstructed final states with two muons, a muon and an electron, a muon and a hadron, or an electron and a hadron. The production cross-section for Z bosons, with invariant mass between 60 and 120 GeV/c[superscript 2], which decay to τ leptons with transverse momenta greater than 20 GeV/c and pseudorapidities between 2.0 and 4.5, is measured to be σ[subscript pp]→Z→ττ = 71.4 ± 3.5 ± 2.8 ± 2.5 pb; the first uncertainty is statistical, the second is systematic, and the third is due to the uncertainty on the integrated luminosity. The ratio of the cross-sections for Z → τ τ to Z → μμ is determined to be 0.93 ± 0.09, where the uncertainty is the combination of statistical, systematic, and luminosity uncertainties of the two measurements.National Science Foundation (U.S.

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

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Bone Biomarkers Measured on Salivary Matrix: Study of Biological Variability in a Cohort of Young Subjects

Levels of bone turnover markers (BTM) can be measured using saliva. The aim of the present study was to determine the Biological Variability of BTM in young subjects, on serial biological salivary samples. Saliva samples of 20 apparently healthy young subjects (9 females and 11 males) have been analyzed. Samples collected using salivette with cotton swabs were obtained three times every 15 days. PTHrP; TRAcP-5b and P1NP have been assayed. The ANOVA test was used to calculate intra and interindividual variance (CVI and CVG). The individuality index (II) and reference change value (RCV) were evaluated for the clinically significant variation between two results in the same individual. CVI was highest for PTHrP and lowest for P1NP while CVG was highest for TRAcP-5b. RCV was maximum for PTHrP and minimum for P1NP. The critical difference (RCV) is of particular interest in evaluating variations in the concentrations of BMT on the salivary matrix during oral pathologies and/or dental treatments The salivary dosage of BMT during dental treatments could be fundamental to establishing establish the timing of the treatment and, in the case of orthodontic treatments, to evaluate the effectiveness of the applied forces

Genome-wide analysis identifies 12 loci influencing human reproductive behavior.

The genetic architecture of human reproductive behavior-age at first birth (AFB) and number of children ever born (NEB)-has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the underlying mechanisms of AFB and NEB are poorly understood. We report a large genome-wide association study of both sexes including 251,151 individuals for AFB and 343,072 individuals for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study and 4 additional loci associated in a gene-based effort. These loci harbor genes that are likely to have a role, either directly or by affecting non-local gene expression, in human reproduction and infertility, thereby increasing understanding of these complex traits

Precision measurement of the B0s-B¯0s oscillation frequency with the decay B0s → D−sπ+

A key ingredient to searches for physics beyond the Standard Model in B0s mixing phenomena is the measurement of the B0s– ${{\overline{ {\mathrm {B}}}{}}^0_{\mathrm { s}}}$ oscillation frequency, which is equivalent to the mass difference Δms of the B0s mass eigenstates. Using the world's largest B0s meson sample accumulated in a dataset, corresponding to an integrated luminosity of 1.0 fb−1, collected by the LHCb experiment at the CERN LHC in 2011, a measurement of Δms is presented. A total of about 34 000 B0s → D−sπ+ signal decays are reconstructed, with an average decay time resolution of 44 fs. The oscillation frequency is measured to be Δms = 17.768 ± 0.023 (stat) ± 0.006 (syst) ps−1, which is the most precise measurement to date

CRISPR-Cas9 In Vivo Gene Editing for Transthyretin Amyloidosis

BACKGROUND: Transthyretin amyloidosis, also called ATTR amyloidosis, is a life-threatening disease characterized by progressive accumulation of misfolded transthyretin (TTR) protein in tissues, predominantly the nerves and heart. NTLA-2001 is an in vivo gene-editing therapeutic agent that is designed to treat ATTR amyloidosis by reducing the concentration of TTR in serum. It is based on the clustered regularly interspaced short palindromic repeats and associated Cas9 endonuclease (CRISPR-Cas9) system and comprises a lipid nanoparticle encapsulating messenger RNA for Cas9 protein and a single guide RNA targeting TTR. METHODS: After conducting preclinical in vitro and in vivo studies, we evaluated the safety and pharmacodynamic effects of single escalating doses of NTLA-2001 in six patients with hereditary ATTR amyloidosis with polyneuropathy, three in each of the two initial dose groups (0.1 mg per kilogram and 0.3 mg per kilogram), within an ongoing phase 1 clinical study. RESULTS: Preclinical studies showed durable knockout of TTR after a single dose. Serial assessments of safety during the first 28 days after infusion in patients revealed few adverse events, and those that did occur were mild in grade. Dose-dependent pharmacodynamic effects were observed. At day 28, the mean reduction from baseline in serum TTR protein concentration was 52% (range, 47 to 56) in the group that received a dose of 0.1 mg per kilogram and was 87% (range, 80 to 96) in the group that received a dose of 0.3 mg per kilogram. CONCLUSIONS: In a small group of patients with hereditary ATTR amyloidosis with polyneuropathy, administration of NTLA-2001 was associated with only mild adverse events and led to decreases in serum TTR protein concentrations through targeted knockout of TTR. (Funded by Intellia Therapeutics and Regeneron Pharmaceuticals; ClinicalTrials.gov number, NCT04601051. opens in new tab.