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Contains fulltext : 284073.pdf (Publisher’s version ) (Open Access), Long noncoding RNAs (lncRNAs) have emerged as critical regulators of gene expression, yet their contribution to immune regulation in humans remains poorly understood. Here, we report that the primate-specific lncRNA CHROMR is induced by influenza A virus and SARS-CoV-2 infection and coordinates the expression of interferon-stimulated genes (ISGs) that execute antiviral responses. CHROMR depletion in human macrophages reduces histone acetylation at regulatory regions of ISG loci and attenuates ISG expression in response to microbial stimuli. Mechanistically, we show that CHROMR sequesters the interferon regulatory factor (IRF)-2-dependent transcriptional corepressor IRF2BP2, thereby licensing IRF-dependent signaling and transcription of the ISG network. Consequently, CHROMR expression is essential to restrict viral infection of macrophages. Our findings identify CHROMR as a key arbitrator of antiviral innate immune signaling in humans.

Contains fulltext : 284073.pdf (Publisher’s version ) (Open Access), Long noncoding RNAs (lncRNAs) have emerged as critical regulators of gene expression, yet their contribution to immune regulation in humans remains poorly understood. Here, we report that the primate-specific lncRNA CHROMR is induced by influenza A virus and SARS-CoV-2 infection and coordinates the expression of interferon-stimulated genes (ISGs) that execute antiviral responses. CHROMR depletion in human macrophages reduces histone acetylation at regulatory regions of ISG loci and attenuates ISG expression in response to microbial stimuli. Mechanistically, we show that CHROMR sequesters the interferon regulatory factor (IRF)-2-dependent transcriptional corepressor IRF2BP2, thereby licensing IRF-dependent signaling and transcription of the ISG network. Consequently, CHROMR expression is essential to restrict viral infection of macrophages. Our findings identify CHROMR as a key arbitrator of antiviral innate immune signaling in humans.

Objectively assessing horse movement symmetry as an adjunctive to the routine lameness evaluation is on the rise with several commercially available systems on the market. Prerequisites for quantifying such symmetries include knowledge of the gait and gait events, such as hoof to ground contact patterns over consecutive strides. Extracting this information in a robust and reliable way is essential to accurately calculate many kinematic variables commonly used in the field. In this study, optical motion capture was used to measure 222 horses of various breeds, performing a total of 82 664 steps in walk and trot under different conditions, including soft, hard and treadmill surfaces as well as moving on a straight line and in circles. Features were extracted from the pelvis and withers vertical movement and from pelvic rotations. The features were then used in a quadratic discriminant analysis to classify gait and to detect if the left/right hind limb was in contact with the ground on a step by step basis. The predictive model achieved 99.98% accuracy on the test data of 120 horses and 21 845 steps, all measured under clinical conditions. One of the benefits of the proposed method is that it does not require the use of limb kinematics making it especially suited for clinical applications where ease of use and minimal error intervention are a priority. Future research could investigate the extension of this functionality to classify other gaits and validating the use of the algorithm for inertial measurement units.

General thermoelastic material models have been investigated over the past decades, see e.g. Reese and Govindjee [1], Holzapfel and Simo [2] and Miehe [3] among many oth- ers. In this paper we present a novel computational framework for large strain thermo- elasticity. The ideas of a new formulation for polyconvex large strain elasticity originally introduced by Ball [4] and recently resumed by Bonet et al. [5] are extended to non-linear coupled thermoelasticity, see also Dittmann [6]. In particular, the deformation gradient (line map), its co-factor (area map) and its determinant (volume map) along with the absolute temperature are formulated as independent variables to obtain a polyconvex free energy function. Moreover, we introduce work conjugate stresses to the extended kine- matic set to define a complementary energy principle of Hellinger-Reissner type, where the introduced conjugate stresses along with the deformed geometry and the absolute tem- perature constitute the set of primal variables, see also Hesch condensed.Eventually,quasi-staticaswellastransientnumericalexamplesareinvesti-gatedtodemonstratethecapabilityoftheproposedframework. et al. [7] for the application of a mixed Hu-Washizu type variational principle in the context of coupled phase-field fracture problems. The finite element discretization relies on a quadratic approximation of the deformed geometry and the absolute temperature, whereas discontinuous linear interpolations are used for the conjugate stresses such that the stress unknowns can be

In the present contribution we focus on a phase-field approach to ductile fracture applied to large deformation contact problems. Phase-field approaches to fracture allow for an efficient numerical investigation of complex three-dimensional fracture problems, as they arise in contact and impact situations. To account for large deformations the underlying formulation is based on a multiplicative decomposition of the deformation gradient into an elastic and plastic part. Moreover, we make use of a fourth-order crack regularization combined with gradient plasticity. Eventually, a demonstrative example shows the capability of the proposed framework.

We present a computational environment for Fast Analysis of multidimensional NMR DAta Sets (FANDAS) that allows assembling multidimensional data sets from a variety of input parameters and facilitates comparing and modifying such “in silico” data sets during the various stages of the NMR data analysis. The input parameters can vary from (partial) NMR assignments directly obtained from experiments to values retrieved from in silico prediction programs. The resulting predicted data sets enable a rapid evaluation of sample labeling in light of spectral resolution and structural content, using standard NMR software such as Sparky. In addition, direct comparison to experimental data sets can be used to validate NMR assignments, distinguish different molecular components, refine structural models or other parameters derived from NMR data. The method is demonstrated in the context of solid-state NMR data obtained for the cyclic nucleotide binding domain of a bacterial cyclic nucleotide-gated channel and on membrane-embedded sensory rhodopsin II. FANDAS is freely available as web portal under WeNMR (http://www.wenmr.eu/services/FANDAS).