Platelet Counts and Risk of Severe Retinopathy of Prematurity: A Bayesian Model-Averaged Meta-Analysis

Background: We aimed to conduct a systematic review and Bayesian model-averaged meta-analysis (BMA) on the association between platelet counts and severe retinopathy of prematurity (ROP). Methods: We searched for studies reporting on platelet counts (continuous variable) or thrombocytopenia (categorical variable) and severe ROP or aggressive posterior ROP (APROP). The timing of platelet counts was divided into Phase 1 (<2 weeks) and Phase 2 (around ROP treatment). BMA was used to calculate Bayes factors (BFs). The BF10 is the ratio of the probability of the data under the alternative hypothesis (H1) over the probability of the data under the null hypothesis (H0). Results: We included 21 studies. BMA showed an association between low platelet counts and severe ROP. The evidence was strong (BF10 = 13.5, 7 studies) for phase 1 and very strong (BF10 = 51.0, 9 studies) for phase 2. Thrombocytopenia (<100 × 109/L) in phase 2 was associated with severe ROP (BF10 = 28.2, 4 studies). Following adjustment for publication bias, only the association of severe ROP with thrombocytopenia remained with moderate evidence in favor of H1 (BF10 = 4.30). Conclusions: Thrombocytopenia is associated with severe ROP. However, the evidence for this association was tempered when results were adjusted for publication bias

Quantifying Parameter Sensitivity, Interaction and Transferability in Hydrologically Enhanced Versions of Noah-LSM over Transition Zones

We use sensitivity analysis to identify the parameters that are most responsible for shaping land surface model (LSM) simulations and to understand the complex interactions in three versions of the Noah LSM: the standard version (STD), a version enhanced with a simple groundwater module (GW), and version augmented by a dynamic phenology module (DV). We use warm season, high-frequency, near-surface states and turbulent fluxes collected over nine sites in the US Southern Great Plains. We quantify changes in the pattern of sensitive parameters, the amount and nature of the interaction between parameters, and the covariance structure of the distribution of behavioral parameter sets. Using Sobol s total and first-order sensitivity indexes, we show that very few parameters directly control the variance of the model output. Significant parameter interaction occurs so that not only the optimal parameter values differ between models, but the relationships between parameters change. GW decreases parameter interaction and appears to improve model realism, especially at wetter sites. DV increases parameter interaction and decreases identifiability, implying it is overparameterized and/or underconstrained. A case study at a wet site shows GW has two functional modes: one that mimics STD and a second in which GW improves model function by decoupling direct evaporation and baseflow. Unsupervised classification of the posterior distributions of behavioral parameter sets cannot group similar sites based solely on soil or vegetation type, helping to explain why transferability between sites and models is not straightforward. This evidence suggests a priori assignment of parameters should also consider climatic differences

Hanbury Brown and Twiss interferometry at a free-electron laser

We present measurements of second- and higher-order intensity correlation functions (so-called Hanbury Brown and Twiss experiment) performed at the free-electron laser (FEL) FLASH in the non-linear regime of its operation. We demonstrate the high transverse coherence properties of the FEL beam with a degree of transverse coherence of about 80% and degeneracy parameter of the order 10^9 that makes it similar to laser sources. Intensity correlation measurements in spatial and frequency domain gave an estimate of the FEL average pulse duration of 50 fs. Our measurements of the higher-order correlation functions indicate that FEL radiation obeys Gaussian statistics, which is characteristic to chaotic sources.Comment: 19 pages, 6 figures, 1 table, 40 reference

Improving Land-Surface Model Hydrology: Is an Explicit Aquifer Model Better than a Deeper Soil Profile?

Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the storage and movement of water (including soil moisture, snow, evaporation, and runoff) after it falls to the ground as precipitation. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy. Hence LSMs have been developed to integrate the available information, including satellite observations, using powerful computers, in order to track water storage and redistribution. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth's water cycle and climate variability. Recently, the models have begun to simulate groundwater storage. In this paper, we compare several possible approaches, and examine the pitfalls associated with trying to estimate aquifer parameters (such as porosity) that are required by the models. We find that explicit representation of groundwater, as opposed to the addition of deeper soil layers, considerably decreases the sensitivity of modeled terrestrial water storage to aquifer parameter choices. We also show that approximate knowledge of parameter values is not sufficient to guarantee realistic model performance: because interaction among parameters is significant, they must be prescribed as a harmonious set

Cyclic nucleotide-dependent relaxation in human umbilical vessels

Umbilical vessels have a low sensitivity to dilate, and this property is speculated to have physiological implications. We aimed to investigate the different relaxing responses of human umbilical arteries (HUAs) and veins (HUVs) to agonists acting through the cAMP and cGMP pathways. Vascular rings were suspended in organ baths for isometric force measurement. Following precontraction with the thromboxane prostanoid (TP) receptor agonist U44069, concentration-response curves to the nitric oxide (NO) donor sodium nitroprusside (SNP), the soluble guanylate cyclase (sGC) stimulator BAY 41-2272, the adenylate cyclase (AC) activator forskolin, the \u3b2-adrenergic receptor agonists isoproterenol (ADRB1), salmeterol (ADRB2), and BRL37344 (ADRB3), and the phosphodiesterase (PDE) inhibitors milrinone (PDE3), rolipram (PDE4), and sildenafil (PDE5) were performed. None of the tested drugs induced a relaxation higher than 30% of the U44069-induced tone. Rings from HUAs and HUVs showed a similar relaxation to forskolin, SNP, PDE inhibitors, and ADRB agonists. BAY 41-2272 was significantly more efficient in relaxing veins than arteries. ADRB agonists evoked weak relaxations (< 20%), which were impaired in endothelium-removed vessels or in the presence of the NO synthase inhibitor L-NAME, sGC inhibitor ODQ. PKA and PKG inhibitors impaired ADBR1-mediated relaxation but did not affect ADRB2-mediated relaxation. ADRB3-mediated relaxation was impaired by PKG inhibition in HUAs and by PKA inhibition in HUVs. Although HUA and HUV rings were relaxed by BRL37344, immunohistochemistry and RT-qPCR analysis showed that, compared to ADRB1 and ADRB2, ADRB3 receptors are weakly or not expressed in umbilical vessels. In conclusion, our study confirmed the low relaxing capacity of HUAs and HUVs from term infants. ADRB-induced relaxation is partially mediated by endothelium-derived NO pathway in human umbilical vessels

A combinatorial cell-laden gel microarray for inducing osteogenic differentiation of human mesenchymal stem cells

Development of three dimensional (3D) microenvironments that direct stem cell differentiation into functional cell types remains a major challenge in the field of regenerative medicine. Here, we describe a new platform to address this challenge by utilizing a robotic microarray spotter for testing stem cell fates inside various miniaturized cell-laden gels in a systematic manner. To demonstrate the feasibility of our platform, we evaluated the osteogenic differentiation of human mesenchymal stem cells (hMSCs) within combinatorial 3D niches. We were able to identify specific combinations, that enhanced the expression of osteogenic markers. Notably, these ‘hit' combinations directed hMSCs to form mineralized tissue when conditions were translated to 3D macroscale hydrogels, indicating that the miniaturization of the experimental system did not alter stem cell fate. Overall, our findings confirmed that the 3D cell-laden gel microarray can be used for screening of different conditions in a rapid, cost-effective, and multiplexed manner for a broad range of tissue engineering applications

Amniotic fluid-derived stem cells for cardiovascular tissue engineering applications

Recent research has demonstrated that a population of stem cells can be isolated from amniotic fluid removed by amniocentesis that are broadly multipotent and non-tumorogenic. These amniotic fluid-derived stem cells (AFSC) could potentially provide an autologous cell source for treatment of congenital defects identified during gestation, particularly cardiovascular defects. In this review, the various methods of isolating, sorting and culturing AFSC are compared, along with techniques for inducing differentiation into cardiac myocytes and endothelial cells. Though research has not demonstrated complete and high yield cardiac differentiation, AFSC have been shown to effectively differentiate into endothelial cells and can effectively support cardiac tissue. Additionally, several tissue engineering and regenerative therapeutic approaches for the use of these cells in heart patches, injection after myocardial infarction, heart valves, vascularized scaffolds and blood vessels are summarized. These applications show great promise in the treatment of congenital cardiovascular defects, and further studies of isolation, culture, and differentiation of AFSC will help to develop their use for tissue engineering, regenerative medicine, and cardiovascular therapies