A novel grass pollen allergen mimotope identified by phage display peptide library inhibits allergen-human IgE antibody interaction

The aim of this study was to investigate the molecular basis of human IgE-allergen interaction by screening a phage-displayed peptide library with an allergen-specific human IgE-mimicking monoclonal antibody (mAb). A mAb that reacted with major grass pollen allergens was successfully identified and shown to inhibit human IgE-allergen interaction. Biopanning of a phage-displayed random peptide library with this mAb yielded a 12 amino acid long mimotope. A synthetic peptide based on this 12-mer mimotope inhibited mAb and human IgE binding to grass pollen extracts. Our results indicate that such synthetic peptide mimotopes of allergens have potential as novel therapeutic agents. © 2001 Published by Elsevier Science B.V. on behalf of the Federation of European Biochemical Societies.

Discovery and Pharmacological Characterization of a Novel Small Molecule Antagonist of Integrin α4β1: Focus on Antiallergic Activity

Allergy is a common hypersensitivity disorder that affects 15% to 20% of the population and its prevalence is increasing worldwide. Its severity correlates with the degree of eosinophil infiltration into the conjunctiva, which is mediated by chemokines that stimulate the production of adhesion molecules like intercellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1) on the endothelial cell surface. The α4β1 and α4β7 integrins are expressed in eosinophils and contribute to their activation and infiltration in AC through the binding to VCAM-1 or fibronectin, expressed on vascular endothelial cells. Blockade of α4 integrins might be a therapeutical achievement in allergic eye diseases. DS 70, that show an IC50 in the nanomolar range against α4β1 integrin in Jurkat cells and in the eosinophilic cell line EOL-1. This compound was able to prevent cell adhesion to VCAM-1 and FN in vitro. In a scintillation proximity assay DS70 displaced 125I-FN binding to human α4β1 integrin and, in flow cytometry analysis, it antagonized the binding of a primary antibody to α4β1 integrin expressed on the Jurkat cells surface as well. Furthermore, we analysed also its effects on integrin α4β1 signalling. In an vivo model of allergic conjunctivitis, topical DS70 reduced the clinical aspects of EPR (early phase reaction) and LPR (late phase reaction), by reducing clinical score, eosinophil accumulation, mRNA levels of cytochines and chemochines pro-inflammatory and the conjunctival expression of α4 integrin. In conclusion, DS70 seems a novel antiallergic ocular agent that has significant effects on both early and late phases of ocular allergy.

Lyprinol : is it a useful anti-inflammatory agent?

The New Zealand green lipped mussel preparation Lyprinol is available without a prescription from a supermarket, pharmacy or Web. The Food and Drug Administration have recently warned Lyprinol USA about their extravagant anti-inflammatory claims for Lyprinol appearing on the web. These claims are put to thorough review. Lyprinol does have anti-inflammatory mechanisms, and has anti-inflammatory effects in some animal models of inflammation. Lyprinol may have benefits in dogs with arthritis. There are design problems with the clinical trials of Lyprinol in humans as an anti-inflammatory agent in osteoarthritis and rheumatoid arthritis, making it difficult to give a definite answer to how effective Lyprinol is in these conditions, but any benefit is small. Lyprinol also has a small benefit in atopic allergy. As anti-inflammatory agents, there is little to choose between Lyprinol and fish oil. No adverse effects have been reported with Lyprinol. Thus, although it is difficult to conclude whether Lyprinol does much good, it can be concluded that Lyprinol probably does no major harm.

Load–frequency control : a GA-based multi-agent reinforcement learning

The load–frequency control (LFC) problem has been one of the major subjects in a power system. In practice, LFC systems use proportional–integral (PI) controllers. However since these controllers are designed using a linear model, the non-linearities of the system are not accounted for and they are incapable of gaining good dynamical performance for a wide range of operating conditions in a multi-area power system. A strategy for solving this problem because of the distributed nature of a multi-area power system is presented by using a multi-agent reinforcement learning (MARL) approach. It consists of two agents in each power area; the estimator agent provides the area control error (ACE) signal based on the frequency bias estimation and the controller agent uses reinforcement learning to control the power system in which genetic algorithm optimisation is used to tune its parameters. This method does not depend on any knowledge of the system and it admits considerable flexibility in defining the control objective. Also, by finding the ACE signal based on the frequency bias estimation the LFC performance is improved and by using the MARL parallel, computation is realised, leading to a high degree of scalability. Here, to illustrate the accuracy of the proposed approach, a three-area power system example is given with two scenarios.