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      Reduction of Mosquito Survival in Mice Vaccinated with Anopheles stephensi Glucose Transporter

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          Abstract

          Despite the fact that recent efforts to control/eradicate malaria have contributed to a significant decrease in the number of cases and deaths, the disease remains a global health challenge. Vaccines based on mosquito salivary gland antigens are a potential approach for reducing vector populations and malaria parasites. The Anopheles AGAP007752 gene encodes for a glucose transporter that is upregulated during Plasmodium infection, and its knockdown decreases the number of sporozoites in mosquito salivary glands. These results together with the fact that glucose is a vital source of energy suggested that a glucose transporter is a candidate protective antigen for the control of mosquito infestations and Plasmodium infection. To address this hypothesis, herein we investigate the effect of mice vaccination with an immunogenic peptide from mosquito glucose transporter on Anopheles stephensi fitness and Plasmodium berghei infection. We showed that vaccination with a peptide of glucose transporter reduced mosquito survival by 5% when compared to controls. However, the reduction in Plasmodium infection was not significant in mosquitoes fed on vaccinated mice. The effect of the peptide vaccination on mosquito survival is important to reduce infestation by malaria vectors. These results support further research on developing glucose transporter-based vaccines to reduce mosquito fitness.

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          NIH Image to ImageJ: 25 years of image analysis.

          For the past 25 years NIH Image and ImageJ software have been pioneers as open tools for the analysis of scientific images. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.
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            A semi-empirical method for prediction of antigenic determinants on protein antigens.

            Analysis of data from experimentally determined antigenic sites on proteins has revealed that the hydrophobic residues Cys, Leu and Val, if they occur on the surface of a protein, are more likely to be a part of antigenic sites. A semi-empirical method which makes use of physicochemical properties of amino acid residues and their frequencies of occurrence in experimentally known segmental epitopes was developed to predict antigenic determinants on proteins. Application of this method to a large number of proteins has shown that our method can predict antigenic determinants with about 75% accuracy which is better than most of the known methods. This method is based on a single parameter and thus very simple to use.
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              GUIDANCE2: accurate detection of unreliable alignment regions accounting for the uncertainty of multiple parameters

              Inference of multiple sequence alignments (MSAs) is a critical part of phylogenetic and comparative genomics studies. However, from the same set of sequences different MSAs are often inferred, depending on the methodologies used and the assumed parameters. Much effort has recently been devoted to improving the ability to identify unreliable alignment regions. Detecting such unreliable regions was previously shown to be important for downstream analyses relying on MSAs, such as the detection of positive selection. Here we developed GUIDANCE2, a new integrative methodology that accounts for: (i) uncertainty in the process of indel formation, (ii) uncertainty in the assumed guide tree and (iii) co-optimal solutions in the pairwise alignments, used as building blocks in progressive alignment algorithms. We compared GUIDANCE2 with seven methodologies to detect unreliable MSA regions using extensive simulations and empirical benchmarks. We show that GUIDANCE2 outperforms all previously developed methodologies. Furthermore, GUIDANCE2 also provides a set of alternative MSAs which can be useful for downstream analyses. The novel algorithm is implemented as a web-server, available at: http://guidance.tau.ac.il.
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                Author and article information

                Journal
                Biomed Res Int
                Biomed Res Int
                BMRI
                BioMed Research International
                Hindawi
                2314-6133
                2314-6141
                2017
                19 July 2017
                : 2017
                : 3428186
                Affiliations
                1Global Health and Tropical Medicine, Instituto de Higiene e Medicina, Universidade Nova de Lisboa (GHMT-IHMT-UNL), Rua da Junqueira 100, 1349-008 Lisboa, Portugal
                2SaBio, Instituto de Investigación en Recursos Cinegéticos (IREC), CSIC-UCLM-JCCM, Ronda de Toledo s/n, 13005 Ciudad Real, Spain
                3Department of Veterinary Pathobiology, Center for Veterinary Health Sciences, Oklahoma State University, Stillwater, OK 74078, USA
                Author notes

                Academic Editor: Yu-Chang Tyan

                Author information
                http://orcid.org/0000-0002-5512-9093
                http://orcid.org/0000-0002-4570-2060
                Article
                10.1155/2017/3428186
                5540378
                28804714
                f0f93fcd-9e60-43a1-a36b-e7b46adf6ae3
                Copyright © 2017 J. Couto et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 21 April 2017
                : 12 June 2017
                Funding
                Funded by: Fundação para a Ciência e a Tecnologia-Global Health and Tropical Medicine
                Award ID: UID/Multi/04413/2013
                Categories
                Research Article

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