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

Trace Levels of Innate Immune Response Modulating Impurities (IIRMIs) Synergize to Break Tolerance to Therapeutic Proteins

Therapeutic proteins such as monoclonal antibodies, replacement enzymes and toxins have significantly improved the therapeutic options for multiple diseases, including cancer and inflammatory diseases as well as enzyme deficiencies and inborn errors of metabolism. However, immune responses to these products are frequent and can seriously impact their safety and efficacy. Of the many factors that can impact protein immunogenicity, this study focuses on the role of innate immune response modulating impurities (IIRMIs) that could be present despite product purification and whether these impurities can synergize to facilitate an immunogenic response to therapeutic proteins. Using lipopolysaccharide (LPS) and CpG ODN as IIRMIs we showed that trace levels of these impurities synergized to induce IgM, IFNγ, TNFα and IL-6 expression. In vivo, trace levels of these impurities synergized to increase antigen-specific IgG antibodies to ovalbumin. Further, whereas mice treated with human erythropoietin showed a transient increase in hematocrit, those that received human erythropoietin containing low levels of IIRMIs had reduced response to erythropoietin after the 1st dose and developed long-lasting anemia following subsequent doses. This suggests that the presence of IIRMIs facilitated a breach in tolerance to the endogenous mouse erythropoietin. Overall, these studies indicate that the risk of enhancing immunogenicity should be considered when establishing acceptance limits of IIRMIs for therapeutic proteins

Estrogen receptor transcription and transactivation: Estrogen receptor alpha and estrogen receptor beta - regulation by selective estrogen receptor modulators and importance in breast cancer

Estrogens display intriguing tissue-selective action that is of great biomedical importance in the development of optimal therapeutics for the prevention and treatment of breast cancer, for menopausal hormone replacement, and for fertility regulation. Certain compounds that act through the estrogen receptor (ER), now referred to as selective estrogen receptor modulators (SERMs), can demonstrate remarkable differences in activity in the various estrogen target tissues, functioning as agonists in some tissues but as antagonists in others. Recent advances elucidating the tripartite nature of the biochemical and molecular actions of estrogens provide a good basis for understanding these tissue-selective actions. As discussed in this thematic review, the development of optimal SERMs should now be viewed in the context of two estrogen receptor subtypes, ERα and ERβ, that have differing affinities and responsiveness to various SERMs, and differing tissue distribution and effectiveness at various gene regulatory sites. Cellular, biochemical, and structural approaches have also shown that the nature of the ligand affects the conformation assumed by the ER-ligand complex, thereby regulating its state of phosphorylation and the recruitment of different coregulator proteins. Growth factors and protein kinases that control the phosphorylation state of the complex also regulate the bioactivity of the ER. These interactions and changes determine the magnitude of the transcriptional response and the potency of different SERMs. As these critical components are becoming increasingly well defined, they provide a sound basis for the development of novel SERMs with optimal profiles of tissue selectivity as medical therapeutic agents

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

Factors associated with parental adaptation to children with an undiagnosed medical condition

Little is known about the adaptive process and experiences of parents raising a child with an undiagnosed medical condition. The present study aims to assess how uncertainty, hope, social support, and coping efficacy contributes to adaptation among parents of children with an undiagnosed medical condition. Sixty-two parents of child affected by an undiagnosed medical condition for at least two years completed an electronically self-administered survey. Descriptive analysis suggested parents in this population had significantly lower adaptation scores when compared to other parents of children with undiagnosed medical conditions, and parents of children with a diagnosed intellectual and/or physical disability. Similarly, parents in this population had significantly lower hope, perceived social support and coping efficacy when compared to parents of children with a diagnosed medical condition. Multiple linear regression was used to identify relationships between independent variables and domains of adaptation. Positive stress response was negatively associated with emotional support (B\ua0=\ua0−0.045, p\ua0≤\ua00.05), and positively associated with coping efficacy (B\ua0=\ua00.009, p\ua0≤\ua00.05). Adaptive self-esteem was negatively associated with uncertainty towards one’s social support (B\ua0=\ua0−0.248, p\ua0≤\ua00.05), and positively associated with coping efficacy (B\ua0=\ua00.007, p\ua0≤\ua00.05). Adaptive social integration was negatively associated with uncertainty towards one’s social support (B-0.273, p\ua0≤\ua00.05), and positively associated with uncertainty towards child’s health (B\ua0=\ua00.323, p\ua0≤\ua00.001), and affectionate support (B\ua0=\ua00.110, p\ua0≤\ua00.001). Finally, adaptive spiritual wellbeing was negatively associated with uncertainty towards one’s family (B\ua0=\ua0−0.221, p\ua0≤\ua00.05). Findings from this study have highlighted the areas where parents believed additional support was required, and provided insight into factors that contribute to parental adaptation