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

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

Association between single nucleotide polymorphisms in the mu opioid receptor gene (OPRM1) and self-reported responses to alcohol in American Indians

Abstract Background Variation in response to the hedonic and adverse effects of a substance is in part an inherited factor that may influence its use, abuse and dependence. The mu opioid receptor is the primary site of action for opiates and individuals with polymorphisms in this receptor appear to have variation in the CNS effects of opiates. Several studies have suggested that this receptor may also mediate some of the effects of non-opioid drugs, such as alcohol. The purpose of this study was to investigate associations between 13 single nucleotide polymorphisms in the mu opioid receptor gene (OPRM1) with self-reported responses to alcohol, an endophenotype associated with the development of alcohol dependence, in American Indians living on eight contiguous reservations. Methods Each participant gave a blood sample and completed a structured diagnostic interview. Additionally, response to alcohol was indexed using the expectation version of the subjective high assessment scale (SHAS-E). SNPs were genotyped in 251 participants and data analyses were conducted using SOLAR. Results The estimated heritability (h2) for the SHAS-E phenotypes ranged from 0.01 to 0.28. Endorsing the expectation of a more intense response on one or more of the following items from the SHAS-E: buzzed, clumsy, dizzy, drunk, effects, high, nausea, sleepy, talkative, terrible, and/or uncomfortable after imbibing 2–3 drinks was significantly associated with having at least one minor allele for at least one of 7 SNPs (p < 0.01) in the OPRM1 receptor gene. Conclusion These studies provide data to suggest that the minor allele, for most of the polymorphisms in the OPRM1 receptor gene investigated, was found to be associated with a more intense, and/or more adverse, response to alcohol, traits that are significantly correlated with lowered quantity of alcohol consumption and less susceptibility to dependence in this Indian population. These data further suggest that making conclusions on the role of the mu opiod receptor gene in the development of alcohol dependence may be limited if only one polymorphism in the gene is evaluated in isolation

PD-1 promotes immune exhaustion by inducing antiviral T cell motility paralysis.

Immune responses to persistent viral infections and cancer often fail because of intense regulation of antigen-specific T cells-a process referred to as immune exhaustion. The mechanisms that underlie the induction of exhaustion are not completely understood. To gain novel insights into this process, we simultaneously examined the dynamics of virus-specific CD8(+) and CD4(+) T cells in the living spleen by two-photon microscopy (TPM) during the establishment of an acute or persistent viral infection. We demonstrate that immune exhaustion during viral persistence maps anatomically to the splenic marginal zone/red pulp and is defined by prolonged motility paralysis of virus-specific CD8(+) and CD4(+) T cells. Unexpectedly, therapeutic blockade of PD-1-PD-L1 restored CD8(+) T cell motility within 30 min, despite the presence of high viral loads. This result was supported by planar bilayer data showing that PD-L1 localizes to the central supramolecular activation cluster, decreases antiviral CD8(+) T cell motility, and promotes stable immunological synapse formation. Restoration of T cell motility in vivo was followed by recovery of cell signaling and effector functions, which gave rise to a fatal disease mediated by IFN-γ. We conclude that motility paralysis is a manifestation of immune exhaustion induced by PD-1 that prevents antiviral CD8(+) T cells from performing their effector functions and subjects them to prolonged states of negative immune regulation