Mechanisms of Inflammation in Neutrophil-Mediated Skin Diseases

Neutrophil-mediated skin diseases, originally named neutrophilic dermatoses (NDs), are a group of conditions due to an altered neutrophil recruitment and activation, characterized by polymorphic cutaneous manifestations with possible internal organ involvement. Although a number of diseases are included in this setting, the two prototypic forms are pyoderma gangrenosum (PG) and Sweet's syndrome (SS) which usually present with skin ulcers and plaque-type lesions, respectively. They have central features significantly overlapping with autoinflammatory conditions which manifest as repeated episodes of tissue inflammation. However, in contrast to appropriate inflammatory responses to insults or to autoimmune disease, there is an absence of identifiable pathogens, autoantibodies, or autoreactive lymphocytes. The recognition of monogenic autoinflammatory diseases which can present with NDs has led to study several genes involved in autoinflammation in NDs. Based on discovering of a number of mutations involving different autoinflammatory genes, neutrophil-mediated skin diseases are nowadays regarded as a spectrum of polygenic autoinflammatory conditions. Although disease mechanisms have not yet been completely elucidated, NDs are recognized as diseases involving dysfunctional cellular signaling mediated by pathways mainly related to inflammasome and IL-1 with the contributory role of IL-17 and other effector molecules. The precise elucidation of the above-mentioned pathologic mechanisms may pave the way to tailored treatments for patients with different neutrophil-mediated skin diseases

A jump-growth model for predator-prey dynamics: derivation and application to marine ecosystems

This paper investigates the dynamics of biomass in a marine ecosystem. A stochastic process is defined in which organisms undergo jumps in body size as they catch and eat smaller organisms. Using a systematic expansion of the master equation, we derive a deterministic equation for the macroscopic dynamics, which we call the deterministic jump-growth equation, and a linear Fokker-Planck equation for the stochastic fluctuations. The McKendrick--von Foerster equation, used in previous studies, is shown to be a first-order approximation, appropriate in equilibrium systems where predators are much larger than their prey. The model has a power-law steady state consistent with the approximate constancy of mass density in logarithmic intervals of body mass often observed in marine ecosystems. The behaviours of the stochastic process, the deterministic jump-growth equation and the McKendrick--von Foerster equation are compared using numerical methods. The numerical analysis shows two classes of attractors: steady states and travelling waves.Comment: 27 pages, 4 figures. Final version as published. Only minor change

Whole genome sequencing in an acrodermatitis enteropathica family from the Middle East.

We report a family from Tabuk, Saudi Arabia, previously screened for Acrodermatitis Enteropathica (AE), in which two siblings presented with typical features of acral dermatitis and a pustular eruption but differing severity. Affected members of our family carry a rare genetic variant, p.Gly512Trp in the SLC39A4 gene which encodes a zinc transporter; disease is thought to result from zinc deficiency. Similar mutations have been reported previously; however, the variable severity within cases carrying the p.Gly512Trp variant and in AE overall led us to hypothesise that additional genetic modifiers may be contributing to the disease phenotype. Therefore whole genome sequencing was carried out in five family members, for whom material was available to search for additional modifiers of AE; this included one individual with clinically diagnosed AE. We confirmed that the p.Gly512Trp change in SLC39A4 was the only candidate homozygous change which was sufficiently rare (ExAC allele frequency 1.178e-05) and predicted deleterious (CADD score 35) to be attributable as a fully penetrant cause of AE. To identify other genes which may carry relevant genetic variation, we reviewed the relevant literature and databases including Gene Ontology Consortium, GeneMANIA, GeneCards, and MalaCards to identify zinc transporter genes and possible interacting partners. The affected individual carried variants in RECQL4 and GPAA1 genes with ExAC allele frequency 10. p.Gly512Trp is highly likely to be the pathogenic variant in this family. This variant was previously detected in a Tunisian proband with perfect genotype-phenotype segregation suggestive of pathogenicity. Further research is required in this area due to small sample size, but attention should be given to RECQL4 and GPAA1 to understand their role in the skin disease

A general framework for combining ecosystem models

When making predictions about ecosystems, we often have available a number of different ecosystem models that attempt to represent their dynamics in a detailed mechanistic way. Each of these can be used as a simulator of large-scale experiments and make projections about the fate of ecosystems under different scenarios to support the development of appropriate management strategies. However, structural differences, systematic discrepancies and uncertainties lead to different models giving different predictions. This is further complicated by the fact that the models may not be run with the same functional groups, spatial structure or time scale. Rather than simply trying to select a “best” model, or taking some weighted average, it is important to exploit the strengths of each of the models, while learning from the differences between them. To achieve this, we construct a flexible statistical model of the relationships between a collection of mechanistic models and their biases, allowing for structural and parameter uncertainty and for different ways of representing reality. Using this statistical meta-model, we can combine prior beliefs, model estimates and direct observations using Bayesian methods and make coherent predictions of future outcomes under different scenarios with robust measures of uncertainty. In this study, we take a diverse ensemble of existing North Sea ecosystem models and demonstrate the utility of our framework by applying it to answer the question what would have happened to demersal fish if fishing was to stop

Adsorption of mono- and multivalent cat- and anions on DNA molecules

Adsorption of monovalent and multivalent cat- and anions on a deoxyribose nucleic acid (DNA) molecule from a salt solution is investigated by computer simulation. The ions are modelled as charged hard spheres, the DNA molecule as a point charge pattern following the double-helical phosphate strands. The geometrical shape of the DNA molecules is modelled on different levels ranging from a simple cylindrical shape to structured models which include the major and minor grooves between the phosphate strands. The densities of the ions adsorbed on the phosphate strands, in the major and in the minor grooves are calculated. First, we find that the adsorption pattern on the DNA surface depends strongly on its geometrical shape: counterions adsorb preferentially along the phosphate strands for a cylindrical model shape, but in the minor groove for a geometrically structured model. Second, we find that an addition of monovalent salt ions results in an increase of the charge density in the minor groove while the total charge density of ions adsorbed in the major groove stays unchanged. The adsorbed ion densities are highly structured along the minor groove while they are almost smeared along the major groove. Furthermore, for a fixed amount of added salt, the major groove cationic charge is independent on the counterion valency. For increasing salt concentration the major groove is neutralized while the total charge adsorbed in the minor groove is constant. DNA overcharging is detected for multivalent salt. Simulations for a larger ion radii, which mimic the effect of the ion hydration, indicate an increased adsorbtion of cations in the major groove.Comment: 34 pages with 14 figure

Influence of Anodic Conditions on Self-ordered Growth of Highly Aligned Titanium Oxide Nanopores

Self-aligned nanoporous TiO2templates synthesized via dc current electrochemical anodization have been carefully analyzed. The influence of environmental temperature during the anodization, ranging from 2 °C to ambient, on the structure and morphology of the nanoporous oxide formation has been investigated, as well as that of the HF electrolyte chemical composition, its concentration and their mixtures with other acids employed for the anodization. Arrays of self-assembled titania nanopores with inner pores diameter ranging between 50 and 100 nm, wall thickness around 20–60 nm and 300 nm in length, are grown in amorphous phase, vertical to the Ti substrate, parallel aligned to each other and uniformly disordering distributed over all the sample surface. Additional remarks about the photoluminiscence properties of the titania nanoporous templates and the magnetic behavior of the Ni filled nanoporous semiconductor Ti oxide template are also included

Measurement of (anti)deuteron and (anti)proton production in DIS at HERA

The first observation of (anti)deuterons in deep inelastic scattering at HERA has been made with the ZEUS detector at a centre-of-mass energy of 300--318 GeV using an integrated luminosity of 120 pb-1. The measurement was performed in the central rapidity region for transverse momentum per unit of mass in the range 0.3<p_T/M<0.7. The particle rates have been extracted and interpreted in terms of the coalescence model. The (anti)deuteron production yield is smaller than the (anti)proton yield by approximately three orders of magnitude, consistent with the world measurements.Comment: 26 pages, 9 figures, 5 tables, submitted to Nucl. Phys.

Forward jet production in deep inelastic ep scattering and low-x parton dynamics at HERA

Differential inclusive jet cross sections in neutral current deep inelastic ep scattering have been measured with the ZEUS detector. Three phase-space regions have been selected in order to study parton dynamics where the effects of BFKL evolution might be present. The measurements have been compared to the predictions of leading-logarithm parton shower Monte Carlo models and fixed-order perturbative QCD calculations. In the forward region, QCD calculations at order alpha_s^1 underestimate the data up to an order of magnitude at low x. An improved description of the data in this region is obtained by including QCD corrections at order alpha_s^2, which account for the lowest-order t-channel gluon-exchange diagrams, highlighting the importance of such terms in parton dynamics at low x.Comment: 25 pages, 4 figure

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types