Protein kinase N2 regulates AMP kinase signaling and insulin responsiveness of glucose metabolism in skeletal muscle

Insulin resistance is central to the development of type 2 diabetes and related metabolic disorders. Because skeletal muscle is responsible for the majority of whole body insulin-stimulated glucose uptake, regulation of glucose metabolism in this tissue is of particular importance. Although Rho GTPases and many of their affecters influence skeletal muscle metabolism, there is a paucity of information on the protein kinase N (PKN) family of serine/threonine protein kinases. We investigated the impact of PKN2 on insulin signaling and glucose metabolism in primary human skeletal muscle cells in vitro and mouse tibialis anterior muscle in vivo. PKN2 knockdown in vitro decreased insulin-stimulated glucose uptake, incorporation into glycogen, and oxidation. PKN2 siRNA increased 5′-adenosine monophosphate-activated protein kinase (AMPK) signaling while stimulating fatty acid oxidation and incorporation into triglycerides and decreasing protein synthesis. At the transcriptional level, PKN2 knockdown increased expression of PGC-1α and SREBP-1c and their target genes. In mature skeletal muscle, in vivo PKN2 knockdown decreased glucose uptake and increased AMPK phosphorylation. Thus, PKN2 alters key signaling pathways and transcriptional networks to regulate glucose and lipid metabolism. Identification of PKN2 as a novel regulator of insulin and AMPK signaling may provide an avenue for manipulation of skeletal muscle metabolism

Genome-wide DNA methylation changes in a mouse model of infection-mediated neurodevelopmental disorders

Background Prenatal exposure to infectious or inflammatory insults increases the risk of neurodevelopmental disorders. Using a well-established mouse model of prenatal viral-like immune activation, we examined whether this pathological association involves genome-wide DNA methylation differences at single nucleotide resolution. Methods Prenatal immune activation was induced by maternal treatment with the viral mimetic polyriboinosinic-polyribocytidylic acid in middle or late gestation. Following behavioral and cognitive characterization of the adult offspring (n = 12 per group), unbiased capture array bisulfite sequencing was combined with subsequent matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and quantitative real-time polymerase chain reaction analyses to quantify DNA methylation changes and transcriptional abnormalities in the medial prefrontal cortex of immune-challenged and control offspring. Gene ontology term enrichment analysis was used to explore shared functional pathways of genes with differential DNA methylation. Results Adult offspring of immune-challenged mothers displayed hyper- and hypomethylated CpGs at numerous loci and at distinct genomic regions, including genes relevant for gamma-aminobutyric acidergic differentiation and signaling (e.g., Dlx1, Lhx5, Lhx8), Wnt signaling (Wnt3, Wnt8a, Wnt7b), and neural development (e.g., Efnb3, Mid1, Nlgn1, Nrxn2). Altered DNA methylation was associated with transcriptional changes of the corresponding genes. The epigenetic and transcriptional effects were dependent on the offspring\u2019s age and were markedly influenced by the precise timing of prenatal immune activation. Conclusions Prenatal viral-like immune activation is capable of inducing stable DNA methylation changes in the medial prefrontal cortex. These long-term epigenetic modifications are a plausible mechanism underlying the disruption of prefrontal gene transcription and behavioral functions in subjects with prenatal infectious histories

Sparsity and Incoherence in Compressive Sampling

We consider the problem of reconstructing a sparse signal $x^0\in\R^n$ from a limited number of linear measurements. Given $m$ randomly selected samples of $U x^0$, where $U$ is an orthonormal matrix, we show that $\ell_1$ minimization recovers $x^0$ exactly when the number of measurements exceeds $$m\geq \mathrm{Const}\cdot\mu^2(U)\cdot S\cdot\log n,$$ where $S$ is the number of nonzero components in $x^0$, and $\mu$ is the largest entry in $U$ properly normalized: $\mu(U) = \sqrt{n} \cdot \max_{k,j} |U_{k,j}|$. The smaller $\mu$, the fewer samples needed. The result holds for ``most'' sparse signals $x^0$ supported on a fixed (but arbitrary) set $T$. Given $T$, if the sign of $x^0$ for each nonzero entry on $T$ and the observed values of $Ux^0$ are drawn at random, the signal is recovered with overwhelming probability. Moreover, there is a sense in which this is nearly optimal since any method succeeding with the same probability would require just about this many samples

Level set based eXtended finite element modelling of the response of fibrous networks under hygroscopic swelling

Materials like paper, consisting of a network of natural fibres, exposed to variations in moisture, undergo changes in geometrical and mechanical properties. This behaviour is particularly important for understanding the hygro-mechanical response of sheets of paper in applications like digital printing. A two-dimensional microstructural model of a fibrous network is therefore developed to upscale the hygro-expansion of individual fibres, through their interaction, to the resulting overall expansion of the network. The fibres are modelled with rectangular shapes and are assumed to be perfectly bonded where they overlap. For realistic networks the number of bonds is large and the network is geometrically so complex that discretizing it by conventional, geometry-conforming, finite elements is cumbersome. The combination of a level-set and XFEM formalism enables the use of regular, structured grids in order to model the complex microstructural geometry. In this approach, the fibres are described implicitly by a level-set function. In order to represent the fibre boundaries in the fibrous network, an XFEM discretization is used together with a Heaviside enrichment function. Numerical results demonstrate that the proposed approach successfully captures the hygro-expansive properties of the network with fewer degrees of freedom compared to classical FEM, preserving desired accuracy.Comment: 27 pages, 22 figures, 4 tables, J. Appl. Mech. June 19, 202

Assimilation of atmospheric methane products into the MACC-II system: From SCIAMACHY to TANSO and IASI

The Monitoring Atmospheric Composition and Climate Interim Implementation (MACC-II) delayed-mode (DM) system has been producing an atmospheric methane (CH4) analysis 6 months behind real time since June 2009. This analysis used to rely on the assimilation of the CH4 product from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument onboard Envisat. Recently the Laboratoire de Météorologie Dynamique (LMD) CH4 products from the Infrared Atmospheric Sounding Interferometer (IASI) and the SRON Netherlands Institute for Space Research CH4 products from the Thermal And Near-infrared Sensor for carbon Observation (TANSO) were added to the DM system. With the loss of Envisat in April 2012, the DM system now has to rely on the assimilation of methane data from TANSO and IASI. This paper documents the impact of this change in the observing system on the methane tropospheric analysis. It is based on four experiments: one free run and three analyses from respectively the assimilation of SCIAMACHY, TANSO and a combination of TANSO and IASI CH4 products in the MACC-II system. The period between December 2010 and April 2012 is studied. The SCIAMACHY experiment globally underestimates the tropospheric methane by 35 part per billion (ppb) compared to the HIAPER Pole-to-Pole Observations (HIPPO) data and by 28 ppb compared the Total Carbon Column Observing Network (TCCON) data, while the free run presents an underestimation of 5 ppb and 1 ppb against the same HIPPO and TCCON data, respectively. The assimilated TANSO product changed in October 2011 from version v.1 to version v.2.0. The analysis of version v.1 globally underestimates the tropospheric methane by 18 ppb compared to the HIPPO data and by 15 ppb compared to the TCCON data. In contrast, the analysis of version v.2.0 globally overestimates the column by 3 ppb. When the high density IASI data are added in the tropical region between 30° N and 30° S, their impact is mainly positive but more pronounced and effective when combined with version v.2.0 of the TANSO products. The resulting analysis globally underestimates the column-averaged dry-air mole fractions of methane (xCH4) just under 1 ppb on average compared to the TCCON data, whereas in the tropics it overestimates xCH4 by about 3 ppb. The random error is estimated to be less than 7 ppb when compared to TCCON data

First Report of Little Cherry Virus 1 Infecting Apricot (Prunus armeniaca) in Africa

peer reviewedLittle cherry disease (LChD) is an important viral disease of many stone fruit species (Prunus spp.), sweet cherry (Prunus avium L.) being the most common host. It is associated with two different virus species belonging to the family Closteroviridae, namely, Little cherry virus 1 (LChV-1, Velarivirus) and Little cherry virus 2 (LChV-2, Ampelovirus). The impact of LChD on sweet cherry production consists in the decrease of yield and fruit quality, which is mainly associated with LChV-2, whereas most of LChV-1 reported infections remain associated with an unclear etiology. Other stone fruit species, such as peach and plum, hosting LChV-1 have been reported (Matic et al. 2007; Šafářová et al. 2017). LChV-1 is mainly transmitted through propagation of infected plant material, and no vector transmission is known (Jelkmann and Eastwell 2011). In 2018, during the early vegetative season, a limited survey was carried out for virus detection in apricot and sweet cherry orchards in the main southern Moroccan stone fruit-producing regions of Agadir, Agdez, and Dayat Aoua. Two sweet cherry trees (P. avium ‘Coeur de Pigeon’ and ‘Bigarreau’) and three apricot trees (Prunus armeniaca L.), all asymptomatic, were sampled (five branches with leaves) from three different orchards. RNA was extracted (both leaves and cambial scrapings) using the Spectrum Plant Total RNA kit (Sigma-Aldrich, Belgium), prior to cDNA synthesis using the iScript Reverse Transcription Kit (Bio-Rad, Belgium). LChV-1 detection was done by reverse transcription PCR (RT-PCR) using the specific primers LCUW7090 (5′-GGTTGTCCTCGGTTGATTAC-3′)/LCUWc7389 (5′-GGCTTGGTTCCATACATCTC-3′) (Bajet et al. 2008), amplifying a 300-bp fragment spanning the ORF1b encoding the RdRp gene, and 1LC_12776F (5′-TCAAGAAAAGTTCTGGTGTGC-3′)/1LC_13223R (5′-CGAGCTAGACGTATCAGTATC-3′) (Glasa et al. 2015), targeting a 456-bp fragment of the CP gene. LChV-2 specific primers were used according to Eastwell and Bernardy (2001). RT-PCR results revealed the presence of LChV-1 in two apricot samples from Agdez. No LChV-1 was detected in the sweet cherry samples. The presence of LChV-1 was confirmed by means of the LChV-1 specific reverse transcription loop-mediated isothermal amplification approach as described by Tahzima et al. (2019). No LChV-2 was detected in any of the samples. The RdRp and CP specific amplification products were bidirectionally sequenced (Genewiz, Leipzig, Germany) and assembled. RdRp and CP partial nucleotide sequences of the Moroccan LChV-1 isolates MOT2 and MOA1 were deposited in GenBank (accession nos. MK905349, MK905350; and MK905351, MK905352, respectively). Based on BLAST analysis of RdRp and CP, the Moroccan LChV-1 sequences shared 99% nucleotide identity (99.55% amino acids) with the No2ISTO isolate (HG792418) from Greece and 97.96% (98.64% amino acids) with the Spanish Ponferrada isolate (KX192367), respectively. Although the presence of LChV-1 has previously been reported in many countries in different continents, to our knowledge, this represents the first detection of LChV-1 in Africa

User-friendly tail bounds for sums of random matrices

This paper presents new probability inequalities for sums of independent, random, self-adjoint matrices. These results place simple and easily verifiable hypotheses on the summands, and they deliver strong conclusions about the large-deviation behavior of the maximum eigenvalue of the sum. Tail bounds for the norm of a sum of random rectangular matrices follow as an immediate corollary. The proof techniques also yield some information about matrix-valued martingales. In other words, this paper provides noncommutative generalizations of the classical bounds associated with the names Azuma, Bennett, Bernstein, Chernoff, Hoeffding, and McDiarmid. The matrix inequalities promise the same diversity of application, ease of use, and strength of conclusion that have made the scalar inequalities so valuable.Comment: Current paper is the version of record. The material on Freedman's inequality has been moved to a separate note; other martingale bounds are described in Caltech ACM Report 2011-0