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

Congenital malaria in Urabá, Colombia

<p>Abstract</p> <p>Background</p> <p>Congenital malaria has been considered a rare event; however, recent reports have shown frequencies ranging from 3% to 54.2% among newborns of mothers who had suffered malaria during pregnancy. There are only a few references concerning the epidemiological impact of this entity in Latin-America and Colombia.</p> <p>Objective</p> <p>The aim of the study was to measure the prevalence of congenital malaria in an endemic Colombian region and to determine some of its characteristics.</p> <p>Methods</p> <p>A prospective, descriptive study was carried out in the mothers who suffered malaria during pregnancy and their newborns. Neonates were clinically evaluated at birth and screened for <it>Plasmodium spp</it>. infection by thick smear from the umbilical cord and peripheral blood, and followed-up weekly during the first 21 days of postnatal life through clinical examinations and thick smears.</p> <p>Results</p> <p>116 newborns were included in the study and 80 umbilical cord samples were obtained. Five cases of congenital infection were identified (four caused by <it>P. vivax </it>and one by <it>P. falciparum</it>), two in umbilical cord blood and three in newborn peripheral blood. One case was diagnosed at birth and the others during follow-up. Prevalence of congenital infection was 4.3%. One of the infected newborns was severely ill, while the others were asymptomatic and apparently healthy. The mothers of the newborns with congenital malaria had been diagnosed with malaria in the last trimester of pregnancy or during delivery, and also presented placental infection.</p> <p>Conclusions</p> <p>Congenital malaria may be a frequent event in newborns of mothers who have suffered malaria during pregnancy in Colombia. An association was found between congenital malaria and the diagnosis of malaria in the mother during the last trimester of pregnancy or during delivery, and the presence of placental infection.</p

Translational models for vascular cognitive impairment: a review including larger species.

BACKGROUND: Disease models are useful for prospective studies of pathology, identification of molecular and cellular mechanisms, pre-clinical testing of interventions, and validation of clinical biomarkers. Here, we review animal models relevant to vascular cognitive impairment (VCI). A synopsis of each model was initially presented by expert practitioners. Synopses were refined by the authors, and subsequently by the scientific committee of a recent conference (International Conference on Vascular Dementia 2015). Only peer-reviewed sources were cited. METHODS: We included models that mimic VCI-related brain lesions (white matter hypoperfusion injury, focal ischaemia, cerebral amyloid angiopathy) or reproduce VCI risk factors (old age, hypertension, hyperhomocysteinemia, high-salt/high-fat diet) or reproduce genetic causes of VCI (CADASIL-causing Notch3 mutations). CONCLUSIONS: We concluded that (1) translational models may reflect a VCI-relevant pathological process, while not fully replicating a human disease spectrum; (2) rodent models of VCI are limited by paucity of white matter; and (3) further translational models, and improved cognitive testing instruments, are required

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