Catecholamines Inhibit Gastric Epithelial [RGM-1] Cell Proliferation via Beta Adrenoceptors

Catecholamines have been implicated in the modulation of normal cell growth, exerting inhibitory or excitatory control depending on the cell type. However, there is a dearth of information on the role of adrenergic mediators in gastric cell proliferation. In the present study, the effects of adrenaline (ADR) and noradrenaline (NOR) on mucosal cell growth and the cell cycle were evaluated in vitro using a normal rat gastric mucosal cell line RGM-1. Cell proliferation was assessed using [3H]-thymidine incorporation and cell cycle patterns were determined by DNA labeling with propidium iodide and flow cytometric quantification. The expressions of adrenoceptors in RGM-1 were determined by Western blot. ADR (0.01 - 10microM) and NOR (0.01 - 10microM) inhibited the growth of RGM-1 cells in a concentration-dependent manner. Pre-treatment of cells with ADR and NOR also inhibited the proliferation stimulated by epidermal growth factor (EGF). Neither phentolamine (non-selective alpha-adrenergic blocker), methoxamine (alpha1-selective agonist) nor clonidine (alpha2-selective agonist) significantly affected the inhibition of cell proliferation produced by ADR and NOR. Propranolol (non-selective beta-adrenergic blocker) and butoxamine (selective beta2-adrenergic blocker) significantly (but not totally) reversed the inhibitory action of ADR on cell proliferation. Furthermore, procaterol (selective beta-2 agonist) but not dobutamine (selective beta-1 agonist) had effects similar to those produced by ADR and NOR. Exposure of RGM-1 cells to both ADR and NOR caused significant inhibition of the G1 - S cycle progression as evidenced by the higher percentage of the G0/G1 phase and a decreased S- phase. This effect was blocked by pre-treatment with propranolol but not phentolamine These results indicate that catecholamines inhibit the proliferation of RGM-1 cells probably partly through beta-2 receptors. ©Physiological Society of Nigeria.published_or_final_versio

Topological Homogeneity for Electron Microscopy Images

In this paper, the concept of homogeneity is defined, from a topological perspective, in order to analyze how uniform is the material composition in 2D electron microscopy images. Topological multiresolution parameters are taken into account to obtain better results than classical techniques.Ministerio de Economía y Competitividad MTM2016-81030-PMinisterio de Economía y Competitividad TEC2012-37868-C04-0

Seir immune strategy for instance weighted naive bayes classification

© Springer International Publishing Switzerland 2015. Naive Bayes (NB) has been popularly applied in many classification tasks. However, in real-world applications, the pronounced advantage of NB is often challenged by insufficient training samples. Specifically, the high variance may occur with respect to the limited number of training samples. The estimated class distribution of a NB classier is inaccurate if the number of training instances is small. To handle this issue, in this paper, we proposed a SEIR (Susceptible, Exposed, Infectious and Recovered) immune-strategy-based instance weighting algorithm for naive Bayes classification, namely SWNB. The immune instance weighting allows the SWNB algorithm adjust itself to the data without explicit specification of functional or distributional forms of the underlying model. Experiments and comparisons on 20 benchmark datasets demonstrated that the proposed SWNB algorithm outperformed existing state-of-the-art instance weighted NB algorithm and other related computational intelligence methods

Dislocation network at InN/GaN interface revealed by scanning tunneling microscopy

For heteroepitaxy of InN on GaN(0001) by molecular-beam epitaxy, the lattice misfit strain is relieved by misfit dislocations (MDs) formed at the interface between InN and GaN. Imaging by scanning tunneling microscopy (STM) of the surfaces of thin InN epifilms reveals line feature parallel to 〈112 0〉. Their contrast becomes less apparent for thicker epifilms. From the interline spacing as well as a comparison with transmission electron microscopy studies, it is suggested that they correspond to the MDs beneath the surface. The STM contrast originates from both the surface distortion caused by the local strain at MDs and the electronic states of the defects. © 2008 American Institute of Physics.published_or_final_versio

A γ-secretase inhibitor, but not a γ-secretase modulator, induced defects in BDNF axonal trafficking and signaling: evidence for a role for APP.

Clues to Alzheimer disease (AD) pathogenesis come from a variety of different sources including studies of clinical and neuropathological features, biomarkers, genomics and animal and cellular models. An important role for amyloid precursor protein (APP) and its processing has emerged and considerable interest has been directed at the hypothesis that Aβ peptides induce changes central to pathogenesis. Accordingly, molecules that reduce the levels of Aβ peptides have been discovered such as γ-secretase inhibitors (GSIs) and modulators (GSMs). GSIs and GSMs reduce Aβ levels through very different mechanisms. However, GSIs, but not GSMs, markedly increase the levels of APP CTFs that are increasingly viewed as disrupting neuronal function. Here, we evaluated the effects of GSIs and GSMs on a number of neuronal phenotypes possibly relevant to their use in treatment of AD. We report that GSI disrupted retrograde axonal trafficking of brain-derived neurotrophic factor (BDNF), suppressed BDNF-induced downstream signaling pathways and induced changes in the distribution within neuronal processes of mitochondria and synaptic vesicles. In contrast, treatment with a novel class of GSMs had no significant effect on these measures. Since knockdown of APP by specific siRNA prevented GSI-induced changes in BDNF axonal trafficking and signaling, we concluded that GSI effects on APP processing were responsible, at least in part, for BDNF trafficking and signaling deficits. Our findings argue that with respect to anti-amyloid treatments, even an APP-specific GSI may have deleterious effects and GSMs may serve as a better alternative

Microbial fuel cells: a green and alternative source for bioenergy production

Microbial fuel cell (MFC) represents one of the green technologies for the production of bioenergy. MFCs using microalgae produce bioenergy by converting solar energy into electrical energy as a function of metabolic and anabolic pathways of the cells. In the MFCs with bacteria, bioenergy is generated as a result of the organic substrate oxidation. MFCs have received high attention from researchers in the last years due to the simplicity of the process, the absence in toxic by-products, and low requirements for the algae growth. Many studies have been conducted on MFC and investigated the factors affecting the MFC performance. In the current chapter, the performance of MFC in producing bioenergy as well as the factors which influence the efficacy of MFCs is discussed. It appears that the main factors affecting MFC’s performance include bacterial and algae species, pH, temperature, salinity, substrate, mechanism of electron transfer in an anodic chamber, electrodes materials, surface area, and electron acceptor in a cathodic chamber. These factors are becoming more influential and might lead to overproduction of bioenergy when they are optimized using response surface methodology (RSM)

Temperature-sensitive sarcomeric protein post-translational modifications revealed by top-down proteomics

Despite advancements in symptom management for heart failure (HF), this devastating clinical syndrome remains the leading cause of death in the developed world. Studies using animal models have greatly advanced our understanding of the molecular mechanisms underlying HF; however, differences in cardiac physiology and the manifestation of HF between animals, particularly rodents, and humans necessitates the direct interrogation of human heart tissue samples. Nevertheless, an ever-present concern when examining human heart tissue samples is the potential for artefactual changes related to temperature changes during tissue shipment or sample processing. Herein, we examined the effects of temperature on the post-translational modifications (PTMs) of sarcomeric proteins, the proteins responsible for muscle contraction, under conditions mimicking those that might occur during tissue shipment or sample processing. Using a powerful top-down proteomics method, we found that sarcomeric protein PTMs were differentially affected by temperature. Specifically, cardiac troponin I and enigma homolog isoform 2 showed robust increases in phosphorylation when tissue was incubated at either 4 °C or 22 °C. The observed increase is likely due to increased cyclic AMP levels and activation of protein kinase A in the tissue. On the contrary, cardiac troponin T and myosin regulatory light chain phosphorylation decreased when tissue was incubated at 4 °C or 22 °C. Furthermore, significant protein degradation was also observed after incubation at 4 °C or 22 °C. Overall, these results indicate that temperature exerts various effects on sarcomeric protein PTMs and careful tissue handling is critical for studies involving human heart samples. Moreover, these findings highlight the power of top-down proteomics for examining the integrity of cardiac tissue samples

Deletion of parasite immune modulatory sequences combined with immune activating signals enhances vaccine mediated protection against filarial nematodes

<p>Background: Filarial nematodes are tissue-dwelling parasites that can be killed by Th2-driven immune effectors, but that have evolved to withstand immune attack and establish chronic infections by suppressing host immunity. As a consequence, the efficacy of a vaccine against filariasis may depend on its capacity to counter parasite-driven immunomodulation.</p> <p>Methodology and Principal Findings: We immunised mice with DNA plasmids expressing functionally-inactivated forms of two immunomodulatory molecules expressed by the filarial parasite Litomosoides sigmodontis: the abundant larval transcript-1 (LsALT) and cysteine protease inhibitor-2 (LsCPI). The mutant proteins enhanced antibody and cytokine responses to live parasite challenge, and led to more leukocyte recruitment to the site of infection than their native forms. The immune response was further enhanced when the antigens were targeted to dendritic cells using a single chain Fv-αDEC205 antibody and co-administered with plasmids that enhance T helper 2 immunity (IL-4) and antigen-presenting cell recruitment (Flt3L, MIP-1α). Mice immunised simultaneously against the mutated forms of LsALT and LsCPI eliminated adult parasites faster and consistently reduced peripheral microfilaraemia. A multifactorial analysis of the immune response revealed that protection was strongly correlated with the production of parasite-specific IgG1 and with the numbers of leukocytes present at the site of infection.</p> <p>Conclusions: We have developed a successful strategy for DNA vaccination against a nematode infection that specifically targets parasite-driven immunosuppression while simultaneously enhancing Th2 immune responses and parasite antigen presentation by dendritic cells.</p&gt

Clades and clans: a comparison study of two evolutionary models

The Yule-Harding-Kingman (YHK) model and the proportional to distinguishable arrangements (PDA) model are two binary tree generating models that are widely used in evolutionary biology. Understanding the distributions of clade sizes under these two models provides valuable insights into macro-evolutionary processes, and is important in hypothesis testing and Bayesian analyses in phylogenetics. Here we show that these distributions are log-convex, which implies that very large clades or very small clades are more likely to occur under these two models. Moreover, we prove that there exists a critical value $\kappa(n)$ for each $n\geqslant 4$ such that for a given clade with size $k$, the probability that this clade is contained in a random tree with $n$ leaves generated under the YHK model is higher than that under the PDA model if $1<k<\kappa(n)$, and lower if $\kappa(n)<k<n$. Finally, we extend our results to binary unrooted trees, and obtain similar results for the distributions of clan sizes.Comment: 21page