Lipotoxicity in type 2 diabetic cardiomyopathy

As obesity and type 2 diabetes are becoming an epidemic in westernized countries, the incidence and prevalence of obesity- and diabetes-related co-morbidities are increasing. In type 2 diabetes ectopic lipid accumulation in the heart has been associated with cardiac dysfunction and apoptosis, a process termed lipotoxicity. Since cardiovascular diseases are the main cause of death in diabetic patients, diagnosis and treatment become increasingly important. Although ischaemic heart disease is a major problem in diabetes, non-ischaemic heart disease (better known as diabetic cardiomyopathy) becomes increasingly important with respect to the impairment of cardiac function and mortality in type 2 diabetes. The underlying aetiology of diabetic cardiomyopathy is incompletely understood but is beginning to be elucidated. Various mechanisms have been proposed that may lead to lipotoxicity. Therefore, this review will focus on the mechanisms of cardiac lipid accumulation and its relation to the development of cardiomyopathy

OLED Encapsulation by Room Temperature Plasma-Assisted ALD Al2O3 Films

Organic light emitting diodes (OLEDs, both small molecule and polymer LEDs) require excellent gas and moisture permeation barrier layers to increase their lifetime. The quality of the barrier layer is ultimately controlled by the presence of defects in the layer. Although a barrier layer may be intrinsically excellent (water vapor transmission rate, WVTR = 10-6 g·m-2·day-1) the protected device may fail in the presence of defects that lead to preferential diffusion pathways for H2O (e.g., defects caused by particles from the environment and/or production process). The state-of-the-art barrier coatings are micrometer-thick multi-layer structure, in which organic interlayers are alternated with inorganic barrier layers with the purpose of decoupling the above-mentioned defects. Recently, atomic layer deposition (ALD) has been successfully tested for the deposition of very thin (<50 nm) single layer permeation barriers on pristine polymer substrates [1,2], showing the potential of this highly uniform and conformal deposition technique in the field of moisture permeation barriers. In this contribution the encapsulation of OLEDs by plasma-assisted ALD of thin (20-40 nm) Al2O3 layers is addressed. The layers are synthesized at room temperature by sequentially exposing the substrate to Al(CH3)3 vapor and a remote inductively coupled O2 plasma in Oxford Instruments FlexALTM and OpALTM reactors. The intrinsic quality of the deposited ALD layers was determined by monitoring the oxidation of a Ca film encapsulated by the Al2O3 film: WVTR values as low as 2·10-6 g·m-2·day-1 have been measured. The potential of ALD layers in encapsulating OLEDs, and therefore in successfully covering the defects present on the device, has been investigated by means of electroluminescence measurements of polymer-LEDs (effective emitting area of 5.8 cm2). The black spot density and area growth were followed as a function of the time under standard conditions of 20°C and 50% relative humidity. Within a 500 h test ALD-encapsulated OLEDs show approximately half the black spot density compared to devices encapsulated by plasma deposited a-SiNx:H (300 nm thick). The black spot density is further reduced by combining the a-SiNx:H and ALD Al2O3 layers. These results point towards a very promising application of ALD Al2O3 layers in the field of OLED encapsulation and will be interpreted in terms of possible mechanisms related to film growth in multi-layer structures

Organic acid production from potato starch waste fermentation by rumen microbial communities from Dutch and Thai dairy cows

Background: Exploring different microbial sources for biotechnological production of organic acids is important. Dutch and Thai cow rumen samples were used as inocula to produce organic acid from starch waste in anaerobic reactors. Organic acid production profiles were determined and microbial communities were compared using 16S ribosomal ribonucleic acid gene amplicon pyrosequencing. Results: In both reactors, lactate was the main initial product and was associated with growth of Streptococcus spp. (86% average relative abundance). Subsequently, lactate served as a substrate for secondary fermentations. In the reactor inoculated with rumen fluid from the Dutch cow, the relative abundance of Bacillus and Streptococcus increased from the start, and lactate, acetate, formate and ethanol were produced. From day 1.33 to 2, lactate and acetate were degraded, resulting in butyrate production. Butyrate production coincided with a decrease in relative abundance of Streptococcus spp. and increased relative abundances of bacteria of other groups, including Parabacteroides, Sporanaerobacter, Helicobacteraceae, Peptostreptococcaceae and Porphyromonadaceae. In the reactor with the Thai cow inoculum, Streptococcus spp. also increased from the start. When lactate was consumed, acetate, propionate and butyrate were produced (day 3-4). After day 3, bacteria belonging to five dominant groups, Bacteroides, Pse udoramibacter_Eubacterium, Dysgonomonas, Enterobacteriaceae and Porphyromonadaceae, were detected and these showed significant positive correlations with acetate, propionate and butyrate levels. Conclusions: The complexity of rumen microorganisms with high adaptation capacity makes rumen fluid a suitable source to convert organic waste into valuable products without the addition of hydrolytic enzymes. Starch waste is a source for organic acid production, especially lactate.Peer reviewe

The UFM1 Pathway Impacts HCMV US2-Mediated Degradation of HLA Class I

To prevent accumulation of misfolded proteins in the endoplasmic reticulum, chaperones perform quality control on newly translated proteins and redirect misfolded proteins to the cytosol for degradation by the ubiquitin-proteasome system. This pathway is called ER-associated protein degradation (ERAD). The human cytomegalovirus protein US2 induces accelerated ERAD of HLA class I molecules to prevent immune recognition of infected cells by CD8(+) T cells. Using US2-mediated HLA-I degradation as a model for ERAD, we performed a genome-wide CRISPR/Cas9 library screen to identify novel cellular factors associated with ERAD. Besides the identification of known players such as TRC8, p97, and UBE2G2, the ubiquitin-fold modifier1 (UFM1) pathway was found to affect degradation of HLA-I. UFMylation is a post-translational modification resembling ubiquitination. Whereas we observe ubiquitination of HLA-I, no UFMylation was detected on HLA-I or several other proteins involved in degradation of HLA-I, suggesting that the UFM1 pathway impacts ERAD in a different manner than ubiquitin. Interference with the UFM1 pathway seems to specifically inhibit the ER-to-cytosol dislocation of HLA-I. In the absence of detectable UFMylation of HLA-I, UFM1 may contribute to US2-mediated HLA-I degradation by misdirecting protein sorting indirectly. Mass spectrometry analysis of US2-expressing cells showed that ribosomal proteins are a major class of proteins undergoing extensive UFMylation; the role of these changes in protein degradation may be indirect and remains to be established.This article belongs to the Special Issue Ubiquitin and Ubiquitin-Like Proteins: From Basic Mechanisms to Human Disorder

Geometrical models for cardiac MRI in rodents: comparison of quantification of left ventricular volumes and function by various geometrical models with a full-volume MRI data set in rodents.

van de Weijer T, van Ewijk PA, Zandbergen HR, Slenter JM, Kessels AG, Wildberger JE, Hesselink MK, Schrauwen P, Schrauwen-Hinderling VB, Kooi ME. Geometrical models for cardiac MRI in rodents: comparison of quantification of left ventricular volumes and function by various geometrical models with a full-volume MRI data set in rodents. Am J Physiol Heart Circ Physiol 302: H709-H715, 2012. First published November 18, 2011; doi:10.1152/ajpheart.00710.2011.-MRI has been proven to be an accurate method for noninvasive assessment of cardiac function. One of the current limitations of cardiac MRI is that it is time consuming. Therefore, various geometrical models are used, which can reduce scan and postprocessing time. It is unclear how appropriate their use is in rodents. Left ventricular (LV) volumes and ejection fraction (EF) were quantified based on 7.0 Tesla cine-MRI in 12 wild-type (WT) mice, 12 adipose triglyceride lipase knockout (ATGL(-/-)) mice (model of impaired cardiac function), and 11 rats in which we induced cardiac ischemia. The LV volumes and function were either assessed with parallel short-axis slices covering the full volume of the left ventricle (FV, gold standard) or with various geometrical models [modified Simpson rule (SR), biplane ellipsoid (BP), hemisphere cylinder (HC), single-plane ellipsoid (SP), and modified Teichholz Formula (TF)]. Reproducibility of the different models was tested and results were correlated with the gold standard (FV). All models and the FV data set provided reproducible results for the LV volumes and EF, with interclass correlation coefficients >= 0.87. All models significantly over-or underestimated EF, except for SR. Good correlation was found for all volumes and EF for the SR model compared with the FV data set (R-2 ranged between 0.59-0.95 for all parameters). The HC model and BP model also predicted EF well (R-2 >= 0.85), although proved to be less useful for quantitative analysis. The SP and TF models correlated poorly with the FV data set (R-2 >= 0.45 for EF and R-2 >= 0.29 for EF, respectively). For the reduction in acquisition and postprocessing time, only the SR model proved to be a valuable method for calculating LV volumes, stroke volume, and EF

Reduced incorporation of Fatty acids into triacylglycerol in myotubes from obese individuals with type 2 diabetes.

Altered skeletal muscle lipid metabolism is a hallmark feature of type 2 (T2D). Here we investigated muscle lipid turnover in T2D versus BMI- controls and examined if putative in vivo differences would be preserved myotubes.Male obese T2D individuals (T2D) (n=6) and their BMI-matched (C) (n=6) underwent a hyperinsulinemic-euglycemic clamp, VO2max test, underwater weighing and muscle biopsy of v. lateralis. 14C-palmitate and 14C-oleate oxidation rates and incorporation into lipids were measured tissue, as well as in primary myotubes.Palmitate oxidation (C: 0.99 +/- T2D: 0.53 +/- 0.07nmol/mg protein; P=0.03) and incorporation of fatty into triacylglycerol (TAG) (C: 0.45 +/- 0.13, T2D: 0.11 +/- 0.02nmol/mg P=0.047) were significantly reduced in muscle homogenates of T2D. These reductions were not retained for palmitate oxidation in primary myotubes (P=0.38); however, incorporation of FAs into TAG was lower in T2D oleate and P=0.11 for palmitate), with a strong correlation of TAG between muscle tissue and primary myotubes (r=0.848, P=0.008).Our data that the ability to incorporate FAs into TAG is an intrinsic feature of muscle cells that is reduced in individuals with T2D

Unveiling the Power of Deep Tracking

In the field of generic object tracking numerous attempts have been made to exploit deep features. Despite all expectations, deep trackers are yet to reach an outstanding level of performance compared to methods solely based on handcrafted features. In this paper, we investigate this key issue and propose an approach to unlock the true potential of deep features for tracking. We systematically study the characteristics of both deep and shallow features, and their relation to tracking accuracy and robustness. We identify the limited data and low spatial resolution as the main challenges, and propose strategies to counter these issues when integrating deep features for tracking. Furthermore, we propose a novel adaptive fusion approach that leverages the complementary properties of deep and shallow features to improve both robustness and accuracy. Extensive experiments are performed on four challenging datasets. On VOT2017, our approach significantly outperforms the top performing tracker from the challenge with a relative gain of 17% in EAO

Combining Image-Level and Segment-Level Models for Automatic Annotation

Abstract. For the task of assigning labels to an image to summarize its contents, many early attempts use segment-level information and try to determine which parts of the images correspond to which labels. Best performing methods use global image similarity and nearest neighbor techniques to transfer labels from training images to test images. However, global methods cannot localize the labels in the images, unlike segment-level methods. Also, they cannot take advantage of training images that are only locally similar to a test image. We propose several ways to combine recent image-level and segment-level techniques to predict both image and segment labels jointly. We cast our experimental study in an unified framework for both image-level and segment-level annotation tasks. On three challenging datasets, our joint prediction of image and segment labels outperforms either prediction alone on both tasks. This confirms that the two levels offer complementary information