Stem cell factor and its soluble receptor (c-kit) in serum of asthmatic patients- correlation with disease severity

<p>Abstract</p> <p>Background</p> <p>SCF (stem cell factor) is a pleiotropic cytokine exerting its role at different stages of bone marrow development and affecting eosinophil activation, mast cells and basophil chemotaxis and survival. The aim of the study was to assess concentration of SCF and its soluble receptor c-kit (sc-kit) in peripheral blood of patients with asthma referring it to asthma severity and phenotype.</p> <p>Methods</p> <p>The study involved 107 patients with bronchial asthma, well characterized with respect to severity and 21 healthy controls. Concentration of SCF and sc-kit in the patients serum were measured by ELISA method.</p> <p>Results</p> <p>Mean serum SCF level in the group of asthmatics (n = 88) was significantly higher as compared to healthy controls (1010 pg/ml ± 37 vs 799 ± 33; p < 0,001). The level of SCF was higher in patients with severe asthma as compared to patients with non-severe asthma (1054 +/- 41 pg/ml vs 819 +/- 50; p < 0,01) and correlated with dose of inhaled glucocorticosteroids taken by the patients to achieve asthma control (R = 0,28; p < 0,01). The mean sc-kit serum level did not differ between asthmatic patients and healthy controls, however the level of sc-kit in non-severe asthmatics was significantly higher as compared to patients with severe asthma and healthy controls. In asthmatic patients (n = 63) the level of sc-kit correlated positively with FEV1% predicted value (R = 0,45; p < 0,001) and MEF25% predicted value (R = 0,33; p < 0,01). The level of sc-kit inversely correlated with the dose of inhaled glucocorticosteroids taken by the patients (R = -0,26; p < 0,01).</p> <p>Conclusion</p> <p>Serum levels of SCF and its soluble receptor c-kit seem to be reflect asthma severity suggesting a role for these molecules in asthmatic inflammation.</p

The phylogenetically-related pattern recognition receptors EFR and XA21 recruit similar immune signaling components in monocots and dicots

During plant immunity, surface-localized pattern recognition receptors (PRRs) recognize pathogen-associated molecular patterns (PAMPs). The transfer of PRRs between plant species is a promising strategy for engineering broad-spectrum disease resistance. Thus, there is a great interest in understanding the mechanisms of PRR-mediated resistance across different plant species. Two well-characterized plant PRRs are the leucine-rich repeat receptor kinases (LRR-RKs) EFR and XA21 from Arabidopsis thaliana (Arabidopsis) and rice, respectively. Interestingly, despite being evolutionary distant, EFR and XA21 are phylogenetically closely related and are both members of the sub-family XII of LRR-RKs that contains numerous potential PRRs. Here, we compared the ability of these related PRRs to engage immune signaling across the monocots-dicots taxonomic divide. Using chimera between Arabidopsis EFR and rice XA21, we show that the kinase domain of the rice XA21 is functional in triggering elf18-induced signaling and quantitative immunity to the bacteria Pseudomonas syringae pv. tomato (Pto) DC3000 and Agrobacterium tumefaciens in Arabidopsis. Furthermore, the EFR:XA21 chimera associates dynamically in a ligand-dependent manner with known components of the EFR complex. Conversely, EFR associates with Arabidopsis orthologues of rice XA21-interacting proteins, which appear to be involved in EFR-mediated signaling and immunity in Arabidopsis. Our work indicates the overall functional conservation of immune components acting downstream of distinct LRR-RK-type PRRs between monocots and dicots

Synthetic Peptides Mimic gp75 from Paracoccidioides brasiliensis in the Diagnosis of Paracoccidioidomycosis

Paracoccidioidomycosis (PCM) is a systemic granulomatous disease, endemic in Latin America, caused by the thermal dimorphic fungus Paracoccidioides brasiliensis. Although some fungal antigens have already been characterized and used for serological diagnosis, cross-reactions have been frequently observed. Thus, the examination of fungal forms in clinical specimens or isolation of P. brasiliensis by culture is still the most frequent method for the diagnosis of this mycosis. In this study, a random peptide phage display library was used to select mimotopes of P. brasiliensis, which were employed as antigens in an indirect enzyme-linked immunosorbent assay. The protective monoclonal antibody against experimental PCM (anti-gp75) was used as molecular target to screen a phage display library. That approach led to a synthetic peptide named P2, which was synthesized and tested against PCM patients’ sera to check whether it was recognized. There was significant recognition of P2 by sera of untreated PCM patients when compared with normal human sera. Sera from treated PCM group, patients with other mycosis or co-infected with HIV had much lower recognition of P2 than untreated patient group. The test showed a sensitivity of 100 and 94.59% of specificity in relation to human sera control. These data indicate a potential use of P2 as diagnostic tool in PCM. Its application for serological diagnosis of PCM may contribute to the development and standardization of simpler, faster and highly reproducible immunodiagnostic tests at low cost

Practical computational toolkits for dendrimers and dendrons structure design

Dendrimers and dendrons offer an excellent platform for developing novel drug delivery systems and medicines. The rational design and further development of these repetitively branched systems are restricted by difficulties in scalable synthesis and structural determination, which can be overcome by judicious use of molecular modelling and molecular simulations. A major difficulty to utilise in silico studies to design dendrimers lies in the laborious generation of their structures. Current modelling tools utilise automated assembly of simpler dendrimers or the inefficient manual assembly of monomer precursors to generate more complicated dendrimer structures. Herein we describe two novel graphical user interface (GUI) toolkits written in Python that provide an improved degree of automation for rapid assembly of dendrimers and generation of their 2D and 3D structures. Our first toolkit uses the RDkit library, SMILES nomenclature of monomers and SMARTS reaction nomenclature to generate SMILES and mol files of dendrimers without 3D coordinates. These files are used for simple graphical representations and storing their structures in databases. The second toolkit assembles complex topology dendrimers from monomers to construct 3D dendrimer structures to be used as starting points for simulation using existing and widely available software and force fields. Both tools were validated for ease-of-use to prototype dendrimer structure and the second toolkit was especially relevant for dendrimers of high complexity and size.Peer reviewe