Neurogenic Inflammation of Guinea-Pig Bladder

Capsaicin, substance P, and ovalbumin, instilled into the bladders of naive and ovalbumin (OVA) sensitized guineapigs caused inflammation, as indicated by increased vascular permeability. Histological changes after exposure to these compounds progressed with time from intense vasodilatation to marginalization of granulocytes followed by interstitial migration of leukocytes. In vitro incubation of guinea-pig bladder tissue with substance P and ovalbumin stimulated release of prostaglandin D2 and leukotrienes. In vitro incubation of bladder tissue with capsaicin, OVA, prostaglandin D2, leukotriene C4, histamine, or calcium ionophore A-23587 all stimulated substance P release. These data suggest that bladder inflammation initiated by a variety of stimuli could lead to a cyclic pattern of release of inflammatory mediators and neuropeptides, which could result in amplification and persistence of cystitis after the inciting cause has subsided

Self Consistent Molecular Field Theory for Packing in Classical Liquids

Building on a quasi-chemical formulation of solution theory, this paper proposes a self consistent molecular field theory for packing problems in classical liquids, and tests the theoretical predictions for the excess chemical potential of the hard sphere fluid. Results are given for the self consistent molecular fields obtained, and for the probabilities of occupancy of a molecular observation volume. For this system, the excess chemical potential predicted is as accurate as the most accurate prior theories, particularly the scaled particle (Percus-Yevick compressibility) theory. It is argued that the present approach is particularly simple, and should provide a basis for a molecular-scale description of more complex solutions.Comment: 6 pages and 5 figure

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

Testing for heterogeneity among the components of a binary composite outcome in a clinical trial

<p>Abstract</p> <p>Background</p> <p>Investigators designing clinical trials often use composite outcomes to overcome many statistical issues. Trialists want to maximize power to show a statistically significant treatment effect and avoid inflation of Type I error rate due to evaluation of multiple individual clinical outcomes. However, if the treatment effect is not similar among the components of this composite outcome, we are left not knowing how to interpret the treatment effect on the composite itself. Given significant heterogeneity among these components, a composite outcome may be judged as being invalid or un-interpretable for estimation of the treatment effect. This paper compares the power of different tests to detect heterogeneity of treatment effect across components of a composite binary outcome.</p> <p>Methods</p> <p>Simulations were done comparing four different models commonly used to analyze correlated binary data. These models included: logistic regression for ignoring correlation, logistic regression weighted by the intra cluster correlation coefficient, population average logistic regression using generalized estimating equations (GEE), and random effects logistic regression.</p> <p>Results</p> <p>We found that the population average model based on generalized estimating equations (GEE) had the greatest power across most scenarios. Adequate power to detect possible composite heterogeneity or variation between treatment effects of individual components of a composite outcome was seen when the power for detecting the main study treatment effect for the composite outcome was also reasonably high.</p> <p>Conclusions</p> <p>It is recommended that authors report tests of composite heterogeneity for composite outcomes and that this accompany the publication of the statistically significant results of the main effect on the composite along with individual components of composite outcomes.</p

HIV-2 interaction with cell coreceptors: amino acids within the V1/V2 region of viral envelope are determinant for CCR8, CCR5 and CXCR4 usage

© 2014 Santos-Costa et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background: Human immunodeficiency virus 1 and 2 (HIV-1 and HIV-2) use cellular receptors in distinct ways. Besides a more promiscuous usage of coreceptors by HIV-2 and a more frequent detection of CD4-independent HIV-2 isolates, we have previously identified two HIV-2 isolates (HIV-2MIC97 and HIV-2MJC97) that do not use the two major HIV coreceptors: CCR5 and CXCR4. All these features suggest that in HIV-2 the Env glycoprotein subunits may have a different structural organization enabling distinct - although probably less efficient - interactions with cellular receptors. Results: By infectivity assays using GHOST cell line expressing CD4 and CCR8 and blocking experiments using CCR8-specific ligand, I-309, we show that efficient replication of HIV-2MIC97 and HIV-2MJC97 requires the presence of CCR8 at plasma cell membrane. Additionally, we disclosed the determinants of chemokine receptor usage at the molecular level, and deciphered the amino acids involved in the usage of CCR8 (R8 phenotype) and in the switch from CCR8 to CCR5 or to CCR5/CXCR4 usage (R5 or R5X4 phenotype). The data obtained from site-directed mutagenesis clearly indicates that the main genetic determinants of coreceptor tropism are located within the V1/V2 region of Env surface glycoprotein of these two viruses. Conclusions: We conclude that a viral population able to use CCR8 and unable to infect CCR5 or CXCR4-positive cells, may exist in some HIV-2 infected individuals during an undefined time period, in the course of the asymptomatic stage of infection. This suggests that in vivo alternate molecules might contribute to HIV infection of natural target cells, at least under certain circumstances. Furthermore we provide direct and unequivocal evidence that the usage of CCR8 and the switch from R8 to R5 or R5X4 phenotype is determined by amino acids located in the base and tip of V1 and V2 loops of HIV-2 Env surface glycoprotein.This work was supported by grants from: Fundação para a Ciência e Tecnologia (FCT; PPCDT/SAU-IMI/55726/2004); Fundação para a Ciência e Tecnologia and Ministério da Saúde de Portugal (VIH/SAU/0006/2011); and from Gilead Sciences Portugal (Programa Gilead Génese).info:eu-repo/semantics/publishedVersio

Experimental detection of short regulatory motifs in eukaryotic proteins: tips for good practice as well as for bad

It has become clear in outline though not yet in detail how cellular regulatory and signalling systems are constructed. The essential machines are protein complexes that effect regulatory decisions by undergoing internal changes of state. Subcomponents of these cellular complexes are assembled into molecular switches. Many of these switches employ one or more short peptide motifs as toggles that can move between one or more sites within the switch system, the simplest being on-off switches. Paradoxically, these motif modules (termed short linear motifs or SLiMs) are both hugely abundant but difficult to research. So despite the many successes in identifying short regulatory protein motifs, it is thought that only the “tip of the iceberg” has been exposed. Experimental and bioinformatic motif discovery remain challenging and error prone. The advice presented in this article is aimed at helping researchers to uncover genuine protein motifs, whilst avoiding the pitfalls that lead to reports of false discovery. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12964-015-0121-y) contains supplementary material, which is available to authorized users