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Summary: Down syndrome (DS), the genetic condition caused by trisomy 21 (T21), is characterized by delayed neurodevelopment, accelerated aging, and increased risk of many co-occurring conditions. Hypoxemia and dysregulated hematopoiesis have been documented in DS, but the underlying mechanisms and clinical consequences remain ill defined. We report an integrative multi-omic analysis of ∼400 research participants showing that people with DS display transcriptomic signatures indicative of elevated heme metabolism and increased hypoxic signaling across the lifespan, along with chronic overproduction of erythropoietin, elevated biomarkers of tissue-specific hypoxia, and hallmarks of stress erythropoiesis. Elevated heme metabolism, transcriptional signatures of hypoxia, and stress erythropoiesis are conserved in a mouse model of DS and associated with overexpression of select triplicated genes. These alterations are independent of the hyperactive interferon signaling characteristic of DS. These results reveal lifelong dysregulation of key oxygen-related processes that could contribute to the developmental and clinical hallmarks of DS.

COVID19 is a heterogeneous medical condition involving diverse underlying pathophysiological processes including hyperinflammation, endothelial damage, thrombotic microangiopathy, and end-organ damage. Limited knowledge about the molecular mechanisms driving these processes and lack of staging biomarkers hamper the ability to stratify patients for targeted therapeutics. We report here the results of a cross-sectional multi-omics analysis of hospitalized COVID19 patients revealing that seroconversion status associates with distinct underlying pathophysiological states. Low antibody titers associate with hyperactive T cells and NK cells, high levels of IFN alpha, gamma and lambda ligands, markers of systemic complement activation, and depletion of lymphocytes, neutrophils, and platelets. Upon seroconversion, all of these processes are attenuated, observing instead increases in B cell subsets, emergency hematopoiesis, increased D-dimer, and hypoalbuminemia. We propose that seroconversion status could potentially be used as a biosignature to stratify patients for therapeutic intervention and to inform analysis of clinical trial results in heterogenous patient populations.

The quantification of fluid flow in rough fractures is of high interest for reservoir engineering, especially for deep geothermal applications. Herein, rough self-affine fractures are stochastically generated with incremental shear displacement and geometrically described by two aperture definitions, the vertical aperture avert and the effective aperture aeff. In order to compare their effect on fracture flow, such as anisotropy and channelling, Local Cubic Law (LCL) model-based 2D fluid flow is simulated. The particularity of this approach is the combination of a stochastic generation of self-affine fractures with a statistical analysis (560 individual realizations) of the impact of the LCL’s aperture constraint on fracture flow. The results show that aperture definition affects the quantitative interpretation of flow anisotropy and channeling as well as the aperture distribution of the fractures with shearing. Higher values of mean aperture for a given fracture are found using avert, whereas the aperture standard deviation is larger with aeff. In addition, flow anisotropy is significantly sensitive to aperture definition for small shear displacements and shows a relative higher dispersion with aeff. Thus, LCL prediction models based on avert are expected to lead to higher dispersion of anisotropy results with a higher uncertainty (factor ~ 2). Realizations based on avert lead to an enhanced clustering of high flow rates for higher shearing displacements. This channeling development results in higher total flow rates for these simulations. These findings support the direct calibration of pre-existing LCL anisotropy simulations based on avert towards more representative results using aeff.

Damage distribution and evolution have a significant effect on borehole stress concentrations. To model the complex fracturing process and inelastic deformation in the development of the borehole breakout, we implement a continuum damage mechanics (CDM) concept that takes tensile and compressive failure mechanisms into account. The proposed approach explicitly models the dissipative behavior of the material due to cracking and its evolution, which leads to an inhomogeneous redistribution of material properties and stresses in the vicinity of the borehole wall. We apply a constitutive plastic model for Berea sandstone and compare our numerical results to laboratory experiments performed on Tablerock sandstone. We are able to reproduce several characteristics of the failure process during the breakout development as observed in experimental tests, e.g. localized crack distribution in the vicinity of the borehole wall, damage evolution, which exhibits a widening process in the beginning followed by subsequent growth in depth, and shear fracturing-dominated breakout growth in sandstone. A comparison of our results with laboratory experiments performed on a range of stress conditions shows a good agreement of the size of borehole breakouts. The importance of the constitutive damage law in defining the failure mechanisms of the damaging processes is discussed. We show that the depth and the width of breakouts are not independent of each other and no single linear relation can be found between the size of breakouts and the magnitude of the applied stress. Consequently, only one far field principal stress component can be estimated from breakout geometry, if the other two principal stresses are known and sufficient data on the plastic parameters are available.

In order to reach Europes 2020 and 2050 targets in terms of greenhouse gas emissions, geothermal resources will have to contribute substantially to meeting carbon-free energy needs. However, public opinion may prevent future large-scale application of deep geothermal power plants, because induced seismicity is often perceived as an unsolicited and uncontrollable side effect of geothermal development. In the last decade, significant advances were made in the development of models to forecast induced seismicity, which are either based on catalogues of induced seismicity, on the underlying physical processes, or on a hybrid philosophy. In this paper, we provide a comprehensive overview of the existing approaches applied to geothermal contexts. This overview will outline the advantages and drawbacks of the different approaches, identify the gaps in our understanding, and describe the needs for geothermal observations. Most of the forecasting approaches focus on the stimulation phase of enhanced geothermal systems which are most prone to generate seismic events. Besides the statistical models suited for real-time applications during reservoir stimulation, the physics-based models have the advantage of considering sub-surface characteristics and estimating the impact of fluid circulation on the reservoir. Hence, to mitigate induced seismicity during major hydraulic stimulations, application of hybrid methods in a decision support system seems the best available solution. So far, however, little attention has been paid to geochemical effects on the failure process and to production periods. Quantitative modelling of induced seismicity still is a challenging and complex matter. Appropriate resources remain to be invested for the scientific community to continue its research and development efforts to successfully forecast induced seismicity in geothermal fields. This is a prerequisite for making this renewable energy resource sustainable and accessible worldwide.

Ultrathin single- and three-stage Cu(In,Ga)Se2 absorber layers were analyzed with room temperature photoluminescence (PL) spectra. An anomalous blueshift was observed upon increasing carrier injection for both samples. This blueshift was attributed to the presence of bandgap fluctuations that are of the same order as the minority carrier diffusion length. From time resolved measurements, a diffusion length of a few 100 nms was deduced. The single-stage spectrum consists of two peaks, and the sample was, therefore, also analyzed by hyperspectral imaging, providing lateral PL and reflectance data with 1 μm resolution. Marginal variations were observed in the PL yield and spectra. This homogeneity could again be attributed to an intermediate scale of the bandgap fluctuation with an upper limit of 1 μm for the scale of the lateral bandgap fluctuations. The two peaks in the PL spectra of the single-stage sample could be attributed to interference, and correction methods were applied. The bandgap fluctuations were extracted for the three-stage and single-stage sample and were 45 meV and 72 ± 3 meV, respectively. It is suggested that this difference is attributed to the smaller grains and larger amount of grain boundaries in the single-stage sample. [ABSTRACT FROM AUTHOR]