Utrecht University

About: Utrecht University is a education organization based out in Utrecht, Utrecht, Netherlands. It is known for research contribution in the topics: Population & Poison control. The organization has 58176 authors who have published 139351 publications receiving 6214282 citations. The organization is also known as: UU & Universiteit Utrecht.

25th Anniversary Article: Engineering Hydrogels for Biofabrication

Abstract: With advances in tissue engineering, the possibility of regenerating injured tissue or failing organs has become a realistic prospect for the first time in medical history. Tissue engineering - the combination of bioactive materials with cells to generate engineered constructs that functionally replace lost and/or damaged tissue - is a major strategy to achieve this goal. One facet of tissue engineering is biofabrication, where three-dimensional tissue-like structures composed of biomaterials and cells in a single manufacturing procedure are generated. Cell-laden hydrogels are commonly used in biofabrication and are termed "bioinks". Hydrogels are particularly attractive for biofabrication as they recapitulate several features of the natural extracellular matrix and allow cell encapsulation in a highly hydrated mechanically supportive three-dimensional environment. Additionally, they allow for efficient and homogeneous cell seeding, can provide biologically-relevant chemical and physical signals, and can be formed in various shapes and biomechanical characteristics. However, despite the progress made in modifying hydrogels for enhanced bioactivation, cell survival and tissue formation, little attention has so far been paid to optimize hydrogels for the physico-chemical demands of the biofabrication process. The resulting lack of hydrogel bioinks have been identified as one major hurdle for a more rapid progress of the field. In this review we summarize and focus on the deposition process, the parameters and demands of hydrogels in biofabrication, with special attention to robotic dispensing as an approach that generates constructs of clinically relevant dimensions. We aim to highlight this current lack of effectual hydrogels within biofabrication and initiate new ideas and developments in the design and tailoring of hydrogels. The successful development of a "printable" hydrogel that supports cell adhesion, migration, and differentiation will significantly advance this exciting and promising approach for tissue engineering.

Critical Evaluation of Nanoparticle Tracking Analysis (NTA) by NanoSight for the Measurement of Nanoparticles and Protein Aggregates

Abstract: Purpose To evaluate the nanoparticle tracking analysis (NTA) technique, compare it with dynamic light scattering (DLS) and test its performance in characterizing drug delivery nanoparticles and protein aggregates.

Global Carbon Budget 2018

Abstract: . Accurate assessment of anthropogenic carbon dioxide ( CO2 ) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions ( EFF ) are based on energy statistics and cement production data, while emissions from land use and land-use change ( ELUC ), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate ( GATM ) is computed from the annual changes in concentration. The ocean CO2 sink ( SOCEAN ) and terrestrial CO2 sink ( SLAND ) are estimated with global process models constrained by observations. The resulting carbon budget imbalance ( BIM ), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ . For the last decade available (2008–2017), EFF was 9.4±0.5 GtC yr −1 , ELUC 1.5±0.7 GtC yr −1 , GATM 4.7±0.02 GtC yr −1 , SOCEAN 2.4±0.5 GtC yr −1 , and SLAND 3.2±0.8 GtC yr −1 , with a budget imbalance BIM of 0.5 GtC yr −1 indicating overestimated emissions and/or underestimated sinks. For the year 2017 alone, the growth in EFF was about 1.6 % and emissions increased to 9.9±0.5 GtC yr −1 . Also for 2017, ELUC was 1.4±0.7 GtC yr −1 , GATM was 4.6±0.2 GtC yr −1 , SOCEAN was 2.5±0.5 GtC yr −1 , and SLAND was 3.8±0.8 GtC yr −1 , with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 405.0±0.1 ppm averaged over 2017. For 2018, preliminary data for the first 6–9 months indicate a renewed growth in EFF of + 2.7 % (range of 1.8 % to 3.7 %) based on national emission projections for China, the US, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. The analysis presented here shows that the mean and trend in the five components of the global carbon budget are consistently estimated over the period of 1959–2017, but discrepancies of up to 1 GtC yr −1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations show (1) no consensus in the mean and trend in land-use change emissions, (2) a persistent low agreement among the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models, originating outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding the global carbon cycle compared with previous publications of this data set (Le Quere et al., 2018, 2016, 2015a, b, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2018 .

A checklist for testing measurement invariance

Abstract: The analysis of measurement invariance of latent constructs is important in research across groups, or across time. By establishing whether factor loadings, intercepts and residual variances are equivalent in a factor model that measures a latent concept, we can assure that comparisons that are made on the latent variable are valid across groups or time. Establishing measurement invariance involves running a set of increasingly constrained structural equation models, and testing whether differences between these models are significant. This paper provides a step-by-step guide to analysing measurement invariance.