Anti-TNF antibody-induced psoriasiform skin lesions in patients with inflammatory bowel disease are characterised by interferon-γ-expressing Th1 cells and IL-17A/IL-22-expressing Th17 cells and respond to anti-IL-12/IL-23 antibody treatment

Background We analysed incidence, predictors, histological features and specific treatment options of anti-tumour necrosis factor alpha (TNF-alpha) antibody-induced psoriasiform skin lesions in patients with inflammatory bowel diseases (IBD).

Design Patients with IBD were prospectively screened for anti-TNF-induced psoriasiform skin lesions. Patients were genotyped for IL23R and IL12B variants. Skin lesions were examined for infiltrating Th1 and Th17 cells. Patients with severe lesions were treated with the anti-interleukin (IL)-12/IL-23 p40 antibody ustekinumab.

Results Among 434 anti-TNF-treated patients with IBD, 21 (4.8%) developed psoriasiform skin lesions. Multiple logistic regression revealed smoking (p=0.007; OR 4.24, 95% CI 1.55 to 13.60) and an increased body mass index (p=0.029; OR 1.12, 95% CI 1.01 to 1.24) as main predictors for these lesions. Nine patients with Crohn's disease and with severe psoriasiform lesions and/or anti-TNF antibody-induced alopecia were successfully treated with the anti-p40-IL-12/IL-23 antibody ustekinumab (response rate 100%). Skin lesions were histologically characterised by infiltrates of IL-17A/IL-22-secreting T helper 17 (Th17) cells and interferon (IFN)-gamma-secreting Th1 cells and IFN-alpha-expressing cells. IL-17A expression was significantly stronger in patients requiring ustekinumab than in patients responding to topical therapy (p=0.001). IL23R genotyping suggests disease-modifying effects of rs11209026 (p.Arg381Gln) and rs7530511 (p.Leu310Pro) in patients requiring ustekinumab.

Conclusions New onset psoriasiform skin lesions develop in nearly 5% of anti-TNF-treated patients with IBD. We identified smoking as a main risk factor for developing these lesions. Anti-TNF-induced psoriasiform skin lesions are characterised by Th17 and Th1 cell infiltrates. The number of IL-17A-expressing T cells correlates with the severity of skin lesions. Anti-IL-12/IL23 antibody therapy is a highly effective therapy for these lesions.

Vitamin D analogs differentially control antimicrobial peptide/"alarmin" expression in psoriasis

Antimicrobial peptides (AMPs) are strongly expressed in lesional skin in psoriasis and play an important role as proinflammatory "alarmins" in this chronic skin disease. Vitamin D analogs like calcipotriol have antipsoriatic effects and might mediate this effect by changing AMP expression. In this study, keratinocytes in lesional psoriatic plaques showed decreased expression of the AMPs beta-defensin (HBD) 2 and HBD3 after topical treatment with calcipotriol. At the same time, calcipotriol normalized the proinflammatory cytokine milieu and decreased interleukin (IL)-17A, IL-17F and IL-8 transcript abundance in lesional psoriatic skin. In contrast, cathelicidin antimicrobial peptide expression was increased by calcipotriol while psoriasin expression remained unchanged. In cultured human epidermal keratinocytes the effect of different vitamin D analogs on the expression of AMPs was further analyzed. All vitamin D analogs tested blocked IL-17A induced HBD2 expression by increasing IkappaB-alpha protein and inhibition of NF-kappaB signaling. At the same time vitamin D analogs induced cathelicidin through activation of the vitamin D receptor and MEK/ERK signaling. These studies suggest that vitamin D analogs differentially alter AMP expression in lesional psoriatic skin and cultured keratinocytes. Balancing AMP "alarmin" expression might be a novel goal in treatment of chronic inflammatory skin diseases.

On the Exploitation of the Inherent Error Resilience of Wireless Systems under Unreliable Silicon

In this paper, we investigate the impact of circuit misbehavior due to parametric variations and voltage scaling on the performance of wireless communication systems. Our study reveals the inherent error resilience of such systems and argues that sufficiently reliable operation can be maintained even in the presence of unreliable circuits and manufacturing defects. We further show how selective application of more robust circuit design techniques is sufficient to deal with high defect rates at low overhead and improve energy efficiency with negligible system performance degradation.

Low Complexity Spectral Analysis of Heart-Rate-Variability through a Wavelet based FFT

In this paper, a low complexity system for spectral analysis of heart rate variability (HRV) is presented. The main idea of the proposed approach is the implementation of the Fast-Lomb periodogram that is a ubiquitous tool in spectral analysis, using a wavelet based Fast Fourier transform. Interestingly we show that the proposed approach enables the classification of processed data into more and less significant based on their contribution to output quality. Based on such a classification a percentage of less-significant data is being pruned leading to a significant reduction of algorithmic complexity with minimal quality degradation. Indeed, our results indicate that the proposed system can achieve up-to 45% reduction in number of computations with only 4.9% average error in the output quality compared to a conventional FFT based HRV system.

Data Mapping for Unreliable Memories

Future digital signal processing (DSP) systems must provide robustness on algorithm and application level to the presence of reliability issues that come along with corresponding implementations in modern semiconductor process technologies. In this paper, we address this issue by investigating the impact of unreliable memories on general DSP systems. In particular, we propose a novel framework to characterize the effects of unreliable memories, which enables us to devise novel methods to mitigate the associated performance loss. We propose to deploy specifically designed data representations, which have the capability of substantially improving the system reliability compared to that realized by conventional data representations used in digital integrated circuits, such as 2's-complement or sign-magnitude number formats. To demonstrate the efficacy of the proposed framework, we analyze the impact of unreliable memories on coded communication systems, and we show that the deployment of optimized data representations substantially improves the error-rate performance of such systems.

Functional and genetic analysis of the colon cancer network

Cancer is a complex disease that has proven to be difficult to understand on the single-gene level. For this reason a functional elucidation needs to take interactions among genes on a systems-level into account. In this study, we infer a colon cancer network from a large-scale gene expression data set by using the method BC3Net. We provide a structural and a functional analysis of this network and also connect its molecular interaction structure with the chromosomal locations of the genes enabling the definition of cis- and trans-interactions. Furthermore, we investigate the interaction of genes that can be found in close neighborhoods on the chromosomes to gain insight into regulatory mechanisms. To our knowledge this is the first study analyzing the genome-scale colon cancer network.

IRIDE:Interdisciplinary research infrastructure based on dual electron linacs and lasers

This paper describes the scientific aims and potentials as well as the preliminary technical design of IRIDE, an innovative tool for multi-disciplinary investigations in a wide field of scientific, technological and industrial applications. IRIDE will be a high intensity "particles factory", based on a combination of high duty cycle radio-frequency superconducting electron linacs and of high energy lasers. Conceived to provide unique research possibilities for particle physics, for condensed matter physics, chemistry and material science, for structural biology and industrial applications, IRIDE will open completely new research possibilities and advance our knowledge in many branches of science and technology. IRIDE is also supposed to be realized in subsequent stages of development depending on the assigned priorities. © 2013 Elsevier B.V.

New genetic loci link adipose and insulin biology to body fat distribution

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.

A quality-scalable and energy-efficient approach for spectral analysis of heart rate variability

Today there is a growing interest in the integration of health monitoring applications in portable devices necessitating the development of methods that improve the energy efficiency of such systems. In this paper, we present a systematic approach that enables energy-quality trade-offs in spectral analysis systems for bio-signals, which are useful in monitoring various health conditions as those associated with the heart-rate. To enable such trade-offs, the processed signals are expressed initially in a basis in which significant components that carry most of the relevant information can be easily distinguished from the parts that influence the output to a lesser extent. Such a classification allows the pruning of operations associated with the less significant signal components leading to power savings with minor quality loss since only less useful parts are pruned under the given requirements. To exploit the attributes of the modified spectral analysis system, thresholding rules are determined and adopted at design- and run-time, allowing the static or dynamic pruning of less-useful operations based on the accuracy and energy requirements. The proposed algorithm is implemented on a typical sensor node simulator and results show up-to 82% energy savings when static pruning is combined with voltage and frequency scaling, compared to the conventional algorithm in which such trade-offs were not available. In addition, experiments with numerous cardiac samples of various patients show that such energy savings come with a 4.9% average accuracy loss, which does not affect the system detection capability of sinus-arrhythmia which was used as a test case. 

Bioactive Gyroid Scaffolds Formed by Sacrificial Templating of Nanocellulose and Nanochitin Hydrogels as Instructive Platforms for Biomimetic Tissue Engineering

A sacrificial templating process using lithographically printed minimal surface structures allows complex de novo geometries of delicate hydrogel materials. The hydrogel scaffolds based on cellulose and chitin nanofibrils show differences in terms of attachment of human mesenchymal stem cells, and allow their differentiation into osteogenic outcomes. The approach here serves as a first example toward designer hydrogel scaffolds viable for biomimetic tissue engineering.

Role of the receptor for advanced glycation endproducts (RAGE) in retinal vasodegenerative pathology during diabetes in mice

Aims/hypothesis
The receptor for AGEs (RAGE) is linked to proinflammatory pathology in a range of tissues. The objective of this study was to assess the potential modulatory role of RAGE in diabetic retinopathy.
Methods
Diabetes was induced in wild-type (WT) and Rage −/− mice (also known as Ager −/− mice) using streptozotocin while non-diabetic control mice received saline. For all groups, blood glucose, HbA1c and retinal levels of methylglyoxal (MG) were evaluated up to 24 weeks post diabetes induction. After mice were killed, retinal glia and microglial activation, vasopermeability, leucostasis and degenerative microvasculature changes were determined. 

Results
Retinal expression of RAGE in WT diabetic mice was increased after 12 weeks (p < 0.01) but not after 24 weeks. Rage −/− mice showed comparable diabetes but accumulated less MG and this corresponded to enhanced activity of the MG-detoxifying enzyme glyoxalase I in their retina when compared with WT mice. Diabetic Rage −/− mice showed significantly less vasopermeability, leucostasis and microglial activation (p < 0.05–0.001). Rage −/− mice were also protected against diabetes-related retinal acellular capillary formation (p < 0.001) but not against pericyte loss. 

Conclusions/interpretation Rage −/− in diabetic mice is protective against many retinopathic lesions, especially those related to innate immune responses. Inhibition of RAGE could be a therapeutic option to prevent diabetic retinopathy.

Enhancing design space exploration by extending CPU/GPU specifications onto FPGAs

The design cycle for complex special-purpose computing systems is extremely costly and time-consuming. It involves a multiparametric design space exploration for optimization, followed by design verification. Designers of special purpose VLSI implementations often need to explore parameters, such as optimal bitwidth and data representation, through time-consuming Monte Carlo simulations. A prominent example of this simulation-based exploration process is the design of decoders for error correcting systems, such as the Low-Density Parity-Check (LDPC) codes adopted by modern communication standards, which involves thousands of Monte Carlo runs for each design point. Currently, high-performance computing offers a wide set of acceleration options that range from multicore CPUs to Graphics Processing Units (GPUs) and Field Programmable Gate Arrays (FPGAs). The exploitation of diverse target architectures is typically associated with developing multiple code versions, often using distinct programming paradigms. In this context, we evaluate the concept of retargeting a single OpenCL program to multiple platforms, thereby significantly reducing design time. A single OpenCL-based parallel kernel is used without modifications or code tuning on multicore CPUs, GPUs, and FPGAs. We use SOpenCL (Silicon to OpenCL), a tool that automatically converts OpenCL kernels to RTL in order to introduce FPGAs as a potential platform to efficiently execute simulations coded in OpenCL. We use LDPC decoding simulations as a case study. Experimental results were obtained by testing a variety of regular and irregular LDPC codes that range from short/medium (e.g., 8,000 bit) to long length (e.g., 64,800 bit) DVB-S2 codes. We observe that, depending on the design parameters to be simulated, on the dimension and phase of the design, the GPU or FPGA may suit different purposes more conveniently, thus providing different acceleration factors over conventional multicore CPUs.