Differential regulation of CCL-11/eotaxin-1 and CXCL-8/IL-8 by Gram-positive and Gram-negative bacteria in human airway smooth muscle cells

Background: Bacterial infections are a cause of exacerbation of airway disease. Airway smooth muscle cells (ASMC) are a source of inflammatory cytokines/chemokines that may propagate local airway inflammatory responses. We hypothesize that bacteria and bacterial products could induce cytokine/chemokine release from ASMC.Methods: Human ASMC were grown in culture and treated with whole bacteria or pathogen associated molecular patterns (PAMPs) for 24 or 48 h. The release of eotaxin-1, CXCL-8 or GMCSF was measured by ELISA.Results: Gram-negative E. coli or Gram-positive S. aureus increased the release of CXCL-8, as did IL-1β, LPS, FSL-1 and Pam3CSK4, whereas FK565, MODLys18 or Poly I:C did not. E. coli inhibited eotaxin-1 release under control conditions and after stimulation with IL-1β. S. aureus tended to inhibit eotaxin-1 release stimulated with IL-1β. E. coli or LPS, but not S. aureus, induced the release of GMCSF.Conclusion: Gram-positive or Gram-negative bacteria activate human ASMC to release CXCL-8. By contrast Gram-negative bacteria inhibited the release of eotaxin-1 from human ASMCs. E. coli, but not S. aureus induced GMCSF release from cells.Our findings that ASMC can respond directly to Gram-negative and Gram-positive bacteria by releasing the neutrophil selective chemokine, CXCL-8, is consistent with what we know about the role of neutrophil recruitment in bacterial infections in the lung. Our findings that bacteria inhibit the release of the eosinophil selective chemokine, eotaxin-1 may help to explain the mechanisms by which bacterial immunotherapy reduces allergic inflammation in the lung. © 2008 Issa et al; licensee BioMed Central Ltd

Differential regulation of CCL-11/eotaxin-1 and CXCL-8/IL-8 by Gram-positive and Gram-negative bacteria in human airway smooth muscle cells.

Background: Bacterial infections are a cause of exacerbation of airway disease. Airway smooth muscle cells (ASMC) are a source of inflammatory cytokines/chemokines that may propagate local airway inflammatory responses. We hypothesize that bacteria and bacterial products could induce cytokine/chemokine release from ASMC. Methods: Human ASMC were grown in culture and treated with whole bacteria or pathogen associated molecular patterns (PAMPs) for 24 or 48 h. The release of eotaxin-I, CXCL-8 or GMCSF was measured by ELISA. Results: Gram-negative E. coli or Gram-positive S. aureus increased the release of CXCL-8, as did IL-1 beta, LPS, FSL-1 and Pam(3)CSK4, whereas FK565, MODLys18 or Poly I:C did not. E. coli inhibited eotaxin-I release under control conditions and after stimulation with IL-1 beta. S. aureus tended to inhibit eotaxin-I release stimulated with IL-1 beta. E. coli or LPS, but not S. aureus, induced the release of GMCSF. Conclusion: Gram-positive or Gram-negative bacteria activate human ASMC to release CXCL-8. By contrast Gram-negative bacteria inhibited the release of eotaxin-I from human ASMCs. E. coli, but not S. aureus induced GMCSF release from cells. Our findings that ASMC can respond directly to Gram-negative and Gram-positive bacteria by releasing the neutrophil selective chemokine, CXCL-8, is consistent with what we know about the role of neutrophil recruitment in bacterial infections in the lung. Our findings that bacteria inhibit the release of the eosinophil selective chemokine, eotaxin-I may help to explain the mechanisms by which bacterial immunotherapy reduces allergic inflammation in the lung

A parabolic approach to the control of opinion spreading

We analyze the problem of controlling to consensus a nonlinear system modeling opinion spreading. We derive explicit exponential estimates on the cost of approximately controlling these systems to consensus, as a function of the number of agents N and the control time-horizon T. Our strategy makes use of known results on the controllability of spatially discretized semilinear parabolic equations. Both systems can be linked through time-rescalin

Geographical distribution of publications in the field of medical education

BACKGROUND: The geographical distribution of publications as an indicator of the research productivity of individual countries, regions or institutions has become a field of interest. We investigated the geographical distribution of contributions to the two leading journals in the field of medical education, Academic Medicine and Medical Education. METHODS: PubMed was used to search Medline. For both journals all journal articles in each year from 1995 to 2000 were included into the study. Then the affiliation was retrieved from the affiliation field of the MEDLINE format. If this was not possible, it was obtained from the paper version of the journal. RESULTS: Academic Medicine published contributions from 25 countries between 1995 and 2000. Authors from 50 countries contributed to Medical Education in the same period of time. Authors from the USA and Canada wrote ca. 95% off all articles in Academic Medicine, whereas authors from the UK, Australia, the USA, Canada and the Netherlands were responsible for ca. 74% of all articles in Medical Education in the investigated period of time. CONCLUSIONS: While many countries contributed to both journals, only a few of them were responsible for the majority of all articles

Problems with Using the Normal Distribution – and Ways to Improve Quality and Efficiency of Data Analysis

Background: The Gaussian or normal distribution is the most established model to characterize quantitative variation of original data. Accordingly, data are summarized using the arithmetic mean and the standard deviation, by x 6 SD, or with the standard error of the mean, x 6 SEM. This, together with corresponding bars in graphical displays has become the standard to characterize variation. Methodology/Principal Findings: Here we question the adequacy of this characterization, and of the model. The published literature provides numerous examples for which such descriptions appear inappropriate because, based on the ‘‘95 % range check’’, their distributions are obviously skewed. In these cases, the symmetric characterization is a poor description and may trigger wrong conclusions. To solve the problem, it is enlightening to regard causes of variation. Multiplicative causes are by far more important than additive ones, in general, and benefit from a multiplicative (or log-) normal approach. Fortunately, quite similar to the normal, the log-normal distribution can now be handled easily and characterized at the level of the original data with the help of both, a new sign, x /, times-divide, and notation. Analogous to x 6 SD, it connects the multiplicative (or geometric) mean x * and the multiplicative standard deviation s * in the form x * x /s*, that is advantageous and recommended. Conclusions/Significance: The corresponding shift from the symmetric to the asymmetric view will substantially increas

TRAF6 Mediates IL-1β/LPS-Induced Suppression of TGF-β Signaling through Its Interaction with the Type III TGF-β Receptor

Transforming growth factor-β1 (TGF-β1) is an important anti-inflammatory cytokine that modulates and resolves inflammatory responses. Recent studies have demonstrated that inflammation enhances neoplastic risk and potentiates tumor progression. In the evolution of cancer, pro-inflammatory cytokines such as IL-1β must overcome the anti-inflammatory effects of TGF-β to boost pro-inflammatory responses in epithelial cells. Here we show that IL-1β or Lipopolysaccharide (LPS) suppresses TGF-β-induced anti-inflammatory signaling in a NF-κB-independent manner. TRAF6, a key molecule in IL-1β signaling, mediates this suppressive effect through interaction with the type III TGF-β receptor (TβRIII), which is TGF-β-dependent and requires type I TGF-β receptor (TβRI) kinase activity. TβRI phosphorylates TβRIII at residue S829, which promotes the TRAF6/TβRIII interaction and consequent sequestration of TβRIII from the TβRII/TβRI complex. Our data indicate that IL-1β enhances the pro-inflammatory response by suppressing TGF-βsignaling through TRAF6-mediated sequestration of TβRIII, which may be an important contributor to the early stages of tumor progression

Antimycobacterial drug discovery using Mycobacteria-infected amoebae identifies anti-infectives and new molecular targets

Tuberculosis remains a serious threat to human health world-wide, and improved efficiency of medical treatment requires a better understanding of the pathogenesis and the discovery of new drugs. In the present study, we performed a whole-cell based screen in order to complete the characterization of 168 compounds from the GlaxoSmithKline TB-set. We have established and utilized novel previously unexplored host-model systems to characterize the GSK compounds, i.e. the amoeboid organisms D. discoideum and A. castellanii, as well as a microglial phagocytic cell line, BV2. We infected these host cells with Mycobacterium marinum to monitor and characterize the anti-infective activity of the compounds with quantitative fluorescence measurements and high-content microscopy. In summary, 88.1% of the compounds were confirmed as antibiotics against M. marinum, 11.3% and 4.8% displayed strong anti-infective activity in, respectively, the mammalian and protozoan infection models. Additionally, in the two systems, 13-14% of the compounds displayed pro-infective activity. Our studies underline the relevance of using evolutionarily distant pathogen and host models in order to reveal conserved mechanisms of virulence and defence, respectively, which are potential "universal" targets for intervention. Subsequent mechanism of action studies based on generation of over-expresser M. bovis BCG strains, generation of spontaneous resistant mutants and whole genome sequencing revealed four new molecular targets, including FbpA, MurC, MmpL3 and GlpK

Emergence of structural patterns out of synchronization in networks with competitive interactions

Synchronization is a collective phenomenon occurring in systems of interacting units, and is ubiquitous in nature, society and technology. Recent studies have enlightened the important role played by the interaction topology on the emergence of synchronized states. However, most of these studies neglect that real world systems change their interaction patterns in time. Here, we analyze synchronization features in networks in which structural and dynamical features co-evolve. The feedback of the node dynamics on the interaction pattern is ruled by the competition of two mechanisms: homophily (reinforcing those interactions with other correlated units in the graph) and homeostasis (preserving the value of the input strength received by each unit). The competition between these two adaptive principles leads to the emergence of key structural properties observed in real world networks, such as modular and scale–free structures, together with a striking enhancement of local synchronization in systems with no global order