Wood density profiles reveal a tree’s life strategy and growth. Density profiles are, however, rarely defined in terms of tissue fractions for wood of tropical angiosperm trees. Here, we aim at linking these fractions to corresponding density profiles of tropical trees from the Congo Basin. Cores of 8 tree species were scanned with X-ray Computed Tomography to calculate density profiles. Then, cores were sanded and the outermost 3 cm were used to semi-automatically measure vessel lumen, parenchyma and fibre fractions using the Weka segmentation tool in ImageJ. Fibre wall and lumen widths were measured using a newly developed semi-automated method. An assessment of density variation in function of growth ring boundary detection is done. A mixed regression model estimated the relative contribution of each trait to the density, with a species effect on slope and intercept of the regression. Position-dependent correlations were made between the fractions and the corresponding wood density profile. On average, density profile variation mostly reflects variations in fibre lumen and wall fractions, but these are species- and position-dependent: on some positions, parenchyma and vessels have a more pronounced effect on density. The model linking density to traits explains 92% of the variation, with 65% of the density profile variation attributed to the three measured traits. The remaining 27% is explained by species as a random effect. There is a clear variation between trees and within trees that have implications for interpreting density profiles in angiosperm trees: the exact driving anatomical fraction behind every density value will depend on the position within the core. The underlying function of density will thus vary accordingly.

Introduction As the accurate diagnosis and treatment of gestational diabetes mellitus (GDM) is of increasing importance; new diagnostic approaches for the assessment of GDM in early pregnancy were recently suggested. We evaluate the diagnostic power of an ‘early’ oral glucose tolerance test (OGTT) 75 g and glycosylated fibronectin (glyFn) for GDM screening in a normal cohort. Methods and analysis In a prospective cohort study, 748 singleton pregnancies are recruited in 6 centres in Switzerland, Austria and Germany. Women are screened for pre-existing diabetes mellitus and GDM by an ‘early’ OGTT 75 g and/or the new biomarker, glyFn, at 12–15 weeks of gestation. Different screening strategies are compared to evaluate the impact on detection of GDM by an OGTT 75 g at 24–28 weeks of gestation as recommended by the International Association of Diabetes and Pregnancy Study Groups (IADPSG). A new screening algorithm is created by using multivariable risk estimation based on ‘early’ OGTT 75 g and/or glyFn results, incorporating maternal risk factors. Recruitment began in May 2014. Ethics and dissemination This study received ethical approval from the ethics committees in Basel, Zurich, Vienna, Salzburg and Freiburg. It was registered under http://www.ClinicalTrials.gov (NCT02035059) on 12 January 2014. Data will be presented at international conferences and published in peer-reviewed journals. Trial registration number NCT02035059.