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      Immunofocusing humoral immunity potentiates the functional efficacy of the AnAPN1 malaria transmission-blocking vaccine antigen

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          Abstract

          Malaria transmission-blocking vaccines (TBVs) prevent the completion of the developmental lifecycle of malarial parasites within the mosquito vector, effectively blocking subsequent infections. The mosquito midgut protein Anopheline alanyl aminopeptidase N (AnAPN1) is the leading, mosquito-based TBV antigen. Structure-function studies identified two Class II epitopes that can induce potent transmission-blocking (T-B) antibodies, informing the design of the next-generation AnAPN1. Here, we functionally screened new immunogens and down-selected to the UF6b construct that has two glycine-linked copies of the T-B epitopes. We then established a process for manufacturing UF6b and evaluated in outbred female CD1 mice the immunogenicity of the preclinical product with the human-safe adjuvant Glucopyranosyl Lipid Adjuvant in a liposomal formulation with saponin QS21 (GLA-LSQ). UF6b:GLA-LSQ effectively immunofocused the humoral response to one of the key T-B epitopes resulting in potent T-B activity, underscoring UF6b as a prime TBV candidate to aid in malaria elimination and eradication efforts.

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          Most cited references21

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          Epidemiology and infectivity of Plasmodium falciparum and Plasmodium vivax gametocytes in relation to malaria control and elimination.

          Malaria remains a major cause of morbidity and mortality in the tropics, with Plasmodium falciparum responsible for the majority of the disease burden and P. vivax being the geographically most widely distributed cause of malaria. Gametocytes are the sexual-stage parasites that infect Anopheles mosquitoes and mediate the onward transmission of the disease. Gametocytes are poorly studied despite this crucial role, but with a recent resurgence of interest in malaria elimination, the study of gametocytes is in vogue. This review highlights the current state of knowledge with regard to the development and longevity of P. falciparum and P. vivax gametocytes in the human host and the factors influencing their distribution within endemic populations. The evidence for immune responses, antimalarial drugs, and drug resistance influencing infectiousness to mosquitoes is reviewed. We discuss how the application of molecular techniques has led to the identification of submicroscopic gametocyte carriage and to a reassessment of the human infectious reservoir. These components are drawn together to show how control measures that aim to reduce malaria transmission, such as mass drug administration and a transmission-blocking vaccine, might better be deployed.
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            Detecting outliers when fitting data with nonlinear regression – a new method based on robust nonlinear regression and the false discovery rate

            Background Nonlinear regression, like linear regression, assumes that the scatter of data around the ideal curve follows a Gaussian or normal distribution. This assumption leads to the familiar goal of regression: to minimize the sum of the squares of the vertical or Y-value distances between the points and the curve. Outliers can dominate the sum-of-the-squares calculation, and lead to misleading results. However, we know of no practical method for routinely identifying outliers when fitting curves with nonlinear regression. Results We describe a new method for identifying outliers when fitting data with nonlinear regression. We first fit the data using a robust form of nonlinear regression, based on the assumption that scatter follows a Lorentzian distribution. We devised a new adaptive method that gradually becomes more robust as the method proceeds. To define outliers, we adapted the false discovery rate approach to handling multiple comparisons. We then remove the outliers, and analyze the data using ordinary least-squares regression. Because the method combines robust regression and outlier removal, we call it the ROUT method. When analyzing simulated data, where all scatter is Gaussian, our method detects (falsely) one or more outlier in only about 1–3% of experiments. When analyzing data contaminated with one or several outliers, the ROUT method performs well at outlier identification, with an average False Discovery Rate less than 1%. Conclusion Our method, which combines a new method of robust nonlinear regression with a new method of outlier identification, identifies outliers from nonlinear curve fits with reasonable power and few false positives.
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              Drug-resistant malaria: molecular mechanisms and implications for public health.

              Resistance to antimalarial drugs has often threatened malaria elimination efforts and historically has led to the short-term resurgence of malaria incidences and deaths. With concentrated malaria eradication efforts currently underway, monitoring drug resistance in clinical settings complemented by in vitro drug susceptibility assays and analysis of resistance markers, becomes critical to the implementation of an effective antimalarial drug policy. Understanding of the factors, which lead to the development and spread of drug resistance, is necessary to design optimal prevention and treatment strategies. This review attempts to summarize the unique factors presented by malarial parasites that lead to the emergence and spread of drug resistance, and gives an overview of known resistance mechanisms to currently used antimalarial drugs. Copyright © 2011 Federation of European Biochemical Societies. All rights reserved.
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                Author and article information

                Contributors
                rdinglasan@epi.ufl.edu
                Journal
                NPJ Vaccines
                NPJ Vaccines
                NPJ Vaccines
                Nature Publishing Group UK (London )
                2059-0105
                6 April 2021
                6 April 2021
                2021
                : 6
                : 49
                Affiliations
                [1 ]GRID grid.15276.37, ISNI 0000 0004 1936 8091, Emerging Pathogens Institute, Department of Infectious Diseases and Immunology, College of Veterinary Medicine, , University of Florida, ; Gainesville, FL USA
                [2 ]Ology Bioservices, Inc., Alachua, FL USA
                [3 ]GRID grid.21107.35, ISNI 0000 0001 2171 9311, Department of Molecular Microbiology & Immunology, Johns Hopkins Malaria Research Institute, ; Baltimore, MD USA
                [4 ]GRID grid.467642.5, ISNI 0000 0004 0540 3132, Center for Global Health, Division of Parasitic Diseases and Malaria, Malaria Research and Reference Reagent Resource Center in the Entomology Branch of the Centers for Disease Control & Prevention, ; Atlanta, GA USA
                [5 ]GRID grid.53959.33, ISNI 0000 0004 1794 8076, Infectious Disease Research Institute, ; Seattle, WA USA
                [6 ]GRID grid.413096.9, ISNI 0000 0001 2107 607X, University of Douala, Faculty of Medicine and Pharmaceutical Sciences, ; Douala, Cameroon
                [7 ]GRID grid.459418.5, ISNI 0000 0004 0404 8335, CellFree Sciences, Co. Ltd, ; Yokohama, Japan
                [8 ]RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
                Author information
                http://orcid.org/0000-0003-1084-9596
                http://orcid.org/0000-0002-7159-5836
                http://orcid.org/0000-0001-9848-0142
                http://orcid.org/0000-0002-8670-3721
                http://orcid.org/0000-0002-9695-4356
                http://orcid.org/0000-0001-5433-8179
                Article
                309
                10.1038/s41541-021-00309-4
                8024329
                33824336
                62daf02e-221a-4066-ba79-60c8b73e6a90
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 18 November 2020
                : 24 February 2021
                Funding
                Funded by: Global Health Innovative Technology Fund (GHIT FUND), Japan
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                protein vaccines,infectious diseases,vaccines,malaria
                protein vaccines, infectious diseases, vaccines, malaria

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