Assessment and optimisation of normalisation methods for dual-colour antibody microarrays

<p>Abstract</p> <p>Background</p> <p>Recent advances in antibody microarray technology have made it possible to measure the expression of hundreds of proteins simultaneously in a competitive dual-colour approach similar to dual-colour gene expression microarrays. Thus, the established normalisation methods for gene expression microarrays, e.g. loess regression, can in principle be applied to protein microarrays. However, the typical assumptions of such normalisation methods might be violated due to a bias in the selection of the proteins to be measured. Due to high costs and limited availability of high quality antibodies, the current arrays usually focus on a high proportion of regulated targets. Housekeeping features could be used to circumvent this problem, but they are typically underrepresented on protein arrays. Therefore, it might be beneficial to select invariant features among the features already represented on available arrays for normalisation by a dedicated selection algorithm.</p> <p>Results</p> <p>We compare the performance of several normalisation methods that have been established for dual-colour gene expression microarrays. The focus is on an invariant selection algorithm, for which effective improvements are proposed. In a simulation study the performances of the different normalisation methods are compared with respect to their impact on the ability to correctly detect differentially expressed features. Furthermore, we apply the different normalisation methods to a pancreatic cancer data set to assess the impact on the classification power.</p> <p>Conclusions</p> <p>The simulation study and the data application demonstrate the superior performance of the improved invariant selection algorithms in comparison to other normalisation methods, especially in situations where the assumptions of the usual global loess normalisation are violated.</p

QCD-like theories at nonzero temperature and density

We investigate the properties of hot and/or dense matter in QCD-like theories with quarks in a (pseudo)real representation of the gauge group using the Nambu-Jona-Lasinio model. The gauge dynamics is modeled using a simple lattice spin model with nearest-neighbor interactions. We first keep our discussion as general as possible, and only later focus on theories with adjoint quarks of two or three colors. Calculating the phase diagram in the plane of temperature and quark chemical potential, it is qualitatively confirmed that the critical temperature of the chiral phase transition is much higher than the deconfinement transition temperature. At a chemical potential equal to half of the diquark mass in the vacuum, a diquark Bose-Einstein condensation (BEC) phase transition occurs. In the two-color case, a Ginzburg-Landau expansion is used to study the tetracritical behavior around the intersection point of the deconfinement and BEC transition lines, which are both of second order. We obtain a compact expression for the expectation value of the Polyakov loop in an arbitrary representation of the gauge group (for any number of colors), which allows us to study Casimir scaling at both nonzero temperature and chemical potential.Comment: JHEP class, 31 pages, 7 eps figures; v2: error in Eq. (3.11) fixed, two references added; matches published versio

Broken symmetry and the variation of critical properties in the phase behaviour of supramolecular rhombus tilings

The degree of randomness, or partial order, present in two-dimensional supramolecular arrays of isophthalate tetracarboxylic acids is shown to vary due to subtle chemical changes such as the choice of solvent or small differences in molecular dimensions. This variation may be quantified using an order parameter and reveals a novel phase behaviour including random tiling with varying critical properties as well as ordered phases dominated by either parallel or non-parallel alignment of neighbouring molecules, consistent with long-standing theoretical studies. The balance between order and randomness is driven by small differences in the intermolecular interaction energies, which we show, using numerical simulations, can be related to the measured order parameter. Significant variations occur even when the energy difference is much less than the thermal energy highlighting the delicate balance between entropic and energetic effects in complex self-assembly processes

RNase 7 Contributes to the Cutaneous Defense against Enterococcus faecium

Background: Human skin is able to mount a fast response against invading microorganisms by the release of antimicrobial proteins such as the ribonuclease RNase 7. Because RNase 7 exhibits high activity against Enterococcus faecium the aim of this study was to further explore the role of RNase 7 in the cutaneous innate defense system against E. faecium. Methodology/Principal Findings: Absolute quantification using real-time PCR and ELISA revealed that primary keratinocytes expressed high levels of RNase 7. Immunohistochemistry showed RNase 7 expression in all epidermal layers of the skin with an intensification in the upper more differentiated layers. Furthermore, RNase 7 was secreted by keratinocytes in vitro and in vivo in a site-dependent way. RNase 7 was still active against E. faecium at low pH (5.5) or high NaCl (150 mM) concentration and the bactericidal activity of RNase 7 against E. faecium required no ribonuclease activity as shown by recombinant RNase 7 lacking enzymatic activity. To further explore the role of RNase 7 in cutaneous defense against E. faecium, we investigated whether RNase 7 contributes to the E. faecium killing activity of skin extracts derived from stratum corneum. Treatment of the skin extract with an RNase 7 specific antibody, which neutralizes the antimicrobial activity of RNase 7, diminished its E. faecium killing activity. Conclusions/Significance: Our data indicate that RNase 7 contributes to the E. faecium-killing activity of skin extracts an

Calculating the energy spectra of magnetic molecules: application of real- and spin-space symmetries

The determination of the energy spectra of small spin systems as for instance given by magnetic molecules is a demanding numerical problem. In this work we review numerical approaches to diagonalize the Heisenberg Hamiltonian that employ symmetries; in particular we focus on the spin-rotational symmetry SU(2) in combination with point-group symmetries. With these methods one is able to block-diagonalize the Hamiltonian and thus to treat spin systems of unprecedented size. In addition it provides a spectroscopic labeling by irreducible representations that is helpful when interpreting transitions induced by Electron Paramagnetic Resonance (EPR), Nuclear Magnetic Resonance (NMR) or Inelastic Neutron Scattering (INS). It is our aim to provide the reader with detailed knowledge on how to set up such a diagonalization scheme.Comment: 29 pages, many figure

CAR-T cell. the long and winding road to solid tumors

Adoptive cell therapy of solid tumors with reprogrammed T cells can be considered the "next generation" of cancer hallmarks. CAR-T cells fail to be as effective as in liquid tumors for the inability to reach and survive in the microenvironment surrounding the neoplastic foci. The intricate net of cross-interactions occurring between tumor components, stromal and immune cells leads to an ineffective anergic status favoring the evasion from the host's defenses. Our goal is hereby to trace the road imposed by solid tumors to CAR-T cells, highlighting pitfalls and strategies to be developed and refined to possibly overcome these hurdles

Modes, mechanisms and evidence of bet hedging in rotifer diapause traits

In this contribution, we review our knowledge on bet-hedging strategies associated with rotifer diapause. First, we describe the ecological scenario under which bet hedging is likely to have evolved in three diapause-related traits in monogonont rotifer populations: (1) the timing of sex (because diapausing eggs are produced via sexual reproduction), (2) the sexual reproduction ratio (i.e. the fraction of sexually reproducing females) and (3) the timing of diapausing egg hatching. Then, we describe how to discriminate among bet-hedging modes and discuss which modes and mechanisms better fit the variability observed in these traits in rotifers. Finally, we evaluate the strength of the empirical evidence for bet hedging in the scarce studies available, and we call for the need of research at different levels of biological complexity to fully understand bet hedging in rotifer diapause

Antimicrobial Peptides and Skin: A Paradigm of Translational Medicine

Antimicrobial peptides (AMPs) are small, cationic, amphiphilic peptides with broad-spectrum microbicidal activity against both bacteria and fungi. In mammals, AMPs form the first line of host defense against infections and generally play an important role as effector agents of the innate immune system. The AMP era was born more than 6 decades ago when the first cationic cyclic peptide antibiotics, namely polymyxins and tyrothricin, found their way into clinical use. Due to the good clinical experience in the treatment of, for example, infections of mucus membranes as well as the subsequent understanding of mode of action, AMPs are now considered for treatment of inflammatory skin diseases and for improving healing of infected wounds. Based on the preclinical findings, including pathobiochemistry and molecular medicine, targeted therapy strategies are developed and first results indicate that AMPs influence processes of diseased skin. Importantly, in contrast to other antibiotics, AMPs do not seem to propagate the development of antibiotic-resistant micro-organisms. Therefore, AMPs should be tested in clinical trials for their efficacy and tolerability in inflammatory skin diseases and chronic wounds. Apart from possible fields of application, these peptides appear suited as an example of the paradigm of translational medicine for skin diseases which is today seen as a `two-way road' - from bench to bedside and backwards from bedside to bench. Copyright (c) 2012 S. Karger AG, Base

Extreme sensitivity in Snowball Earth formation to mountains on PaleoProterozoic supercontinents

During the PaleoProterozoic 2.45 to 2.2 billion years ago, several glaciations may have produced Snowball Earths. These glacial cycles occurred during large environmental change when atmospheric oxygen was increasing, a supercontinent was assembled from numerous landmasses, and collisions between these landmasses formed mountain ranges. Despite uncertainties in the composition of the atmosphere and reconstruction of the landmasses, paleoclimate model simulations can test the sensitivity of the climate to producing a Snowball Earth. Here we present a series of simulations that vary the atmospheric methane concentration and latitudes of west–east-oriented mountain ranges on an idealised supercontinent. For a given methane concentration, the latitudes of mountains control whether a Snowball Earth forms or not. Significantly, mountains in middle latitudes inhibited Snowball Earth formation, and mountains in low latitudes promoted Snowball Earth formation, with the supercontinent with mountains at ±30° being most conducive to forming a Snowball Earth because of reduced albedo at low latitudes. We propose that the extreme sensitivity of a Snowball Earth to reconstructions of the paleogeography and paleoatmospheric composition may explain the observed glaciations, demonstrating the importance of high-quality reconstructions to improved understanding of this early period in Earth’s history

Label-free integrative pharmacology on-target of drugs at the β2-adrenergic receptor

We describe a label-free integrative pharmacology on-target (iPOT) method to assess the pharmacology of drugs at the β2-adrenergic receptor. This method combines dynamic mass redistribution (DMR) assays using an array of probe molecule-hijacked cells with similarity analysis. The whole cell DMR assays track cell system-based, ligand-directed, and kinetics-dependent biased activities of the drugs, and translates their on-target pharmacology into numerical descriptors which are subject to similarity analysis. We demonstrate that the approach establishes an effective link between the label-free pharmacology and in vivo therapeutic indications of drugs