Mortality, Neonatal Morbidity and Two Year Follow-Up of Extremely Preterm Infants Born in the Netherlands in 2007

Contains fulltext : 108726.pdf (publisher's version ) (Open Access)BACKGROUND: Extremely preterm infants are at high risk of neonatal mortality and adverse outcome. Survival rates are slowly improving, but increased survival may come at the expense of more handicaps. METHODOLOGY/PRINCIPAL FINDINGS: Prospective population-based cohort study of all infants born at 23 to 27 weeks of gestation in the Netherlands in 2007. 276 of 345 (80%) infants were born alive. Early neonatal death occurred in 96 (34.8%) live born infants, including 61 cases of delivery room death. 29 (10.5%) infants died during the late neonatal period. Survival rates for live born infants at 23, 24, 25 and 26 weeks of gestation were 0%, 6.7%, 57.9% and 71% respectively. 43.1% of 144 surviving infants developed severe neonatal morbidity (retinopathy of prematurity grade >/=3, bronchopulmonary dysplasia and/or severe brain injury). At two years of age 70.6% of the children had no disability, 17.6% was mild disabled and 11.8% had a moderate-to-severe disability. Severe brain injury (p = 0.028), retinopathy of prematurity grade >/=3 (p = 0.024), low gestational age (p = 0.019) and non-Dutch nationality of the mother (p = 0.004) increased the risk of disability. CONCLUSIONS/SIGNIFICANCE: 52% of extremely preterm infants born in the Netherlands in 2007 survived. Surviving infants had less severe neonatal morbidity compared to previous studies. At two years of age less than 30% of the infants were disabled. Disability was associated with gestational age and neonatal morbidity

Effect of Polydispersity and Anisotropy in Colloidal and Protein Solutions: an Integral Equation Approach

Application of integral equation theory to complex fluids is reviewed, with particular emphasis to the effects of polydispersity and anisotropy on their structural and thermodynamic properties. Both analytical and numerical solutions of integral equations are discussed within the context of a set of minimal potential models that have been widely used in the literature. While other popular theoretical tools, such as numerical simulations and density functional theory, are superior for quantitative and accurate predictions, we argue that integral equation theory still provides, as in simple fluids, an invaluable technique that is able to capture the main essential features of a complex system, at a much lower computational cost. In addition, it can provide a detailed description of the angular dependence in arbitrary frame, unlike numerical simulations where this information is frequently hampered by insufficient statistics. Applications to colloidal mixtures, globular proteins and patchy colloids are discussed, within a unified framework.Comment: 17 pages, 7 figures, to appear in Interdiscip. Sci. Comput. Life Sci. (2011), special issue dedicated to Prof. Lesser Blu

C9ORF72-derived poly-GA DPRs undergo endocytic uptake in iAstrocytes and spread to motor neurons

Dipeptide repeat (DPR) proteins are aggregation-prone polypeptides encoded by the pathogenic GGGGCC repeat expansion in the C9ORF72 gene, the most common genetic cause of amyotrophic lateral sclerosis and frontotemporal dementia. In this study, we focus on the role of poly-GA DPRs in disease spread. We demonstrate that recombinant poly-GA oligomers can directly convert into solid-like aggregates and form characteristic β-sheet fibrils in vitro. To dissect the process of cell-to-cell DPR transmission, we closely follow the fate of poly-GA DPRs in either their oligomeric or fibrillized form after administration in the cell culture medium. We observe that poly-GA DPRs are taken up via dynamin-dependent and -independent endocytosis, eventually converging at the lysosomal compartment and leading to axonal swellings in neurons. We then use a co-culture system to demonstrate astrocyte-to-motor neuron DPR propagation, showing that astrocytes may internalise and release aberrant peptides in disease pathogenesis. Overall, our results shed light on the mechanisms of poly-GA cellular uptake and propagation, suggesting lysosomal impairment as a possible feature underlying the cellular pathogenicity of these DPR species

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

Extending the use of the conceptions of learning and teaching (COLT) instrument to the postgraduate setting

© 2021, The Author(s). Background: Several studies have shown that conceptions of teachers on teaching and learning can influence the teaching practices and behavior in higher education. This association is also found in undergraduate medical education but not yet established in postgraduate medical setting. An instrument, Conceptions of Learning and Teaching (COLT) was developed to measure conception of teachers in undergraduate medical education. COLT is a 3-factor 18-item questionnaire. The objective of this study is to evaluate if COLT is valid for postgraduate medical education. Methods: We invited postgraduate clinical faculty from 3 hospitals in the Netherlands to fill out the COLT. Confirmatory and exploratory factor analysis were performed to evaluate the fit of the postgraduate clinical faculty data to the COLT. Analysis of variance was done to evaluate if there was difference among the 3 hospitals in terms of the response by the clinical faculty. Results: Confirmatory factor analysis showed that the postgraduate faculty data had a 2 factor structure after removal of five items. These factors were Teacher Centeredness (TC) and combined Appreciation of Active Learning and Orientation to Professional Practice (A-P) and were considered as comparable to the factors in the original COLT, expressing the post-graduate learning and teaching setting. As several items were removed, the fit was suboptimal, yet did suggest validity for use of the COLT for postgraduate medical education. Conclusion: The modified COLT can be used to measure conceptions of teaching and learning in postgraduate medical education. We recommend further study to improve the factor structure of the modified COLT