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      Biological effects of Lippia alba essential oil against Anopheles gambiae and Aedes aegypti

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          Abstract

          The management of mosquito resistance to chemical insecticides and the biting behaviour of some species are motivating the search for complementary and/or alternative control methods. The use of plants is increasingly considered as a sustainable biological solution for vector control. The aim of this study was to evaluate the biological effects of the essential oil (EO) of Lippia alba harvested in Abidjan (Côte d’Ivoire) against Anopheles gambiae and Aedes aegypti mosquitoes. Phytochemical compounds were identified by GC–MS. Knockdown and mortality were determined according to the WHO test tube protocol. Contact irritancy was assessed by observing the movement of mosquitoes from a treated WHO tube to a second untreated tube. Non-contact repellency was assessed using a standardised high-throughput screening system (HITSS). Blood meal inhibition was assessed using a membrane feeding assay treated with EO. The EO was identified as the citral chemotype. The EO gave 100% KD60 in both species at a concentration of 1%. Mortalities of 100% were recorded with An. gambiae and Ae. aegypti at concentrations of 1% and 5% respectively. The highest proportions of females escaping during the contact irritancy test were 100% for An. gambiae at 1% concentration and 94% for Ae. aegypti at 2.5% concentration. The 1% concentration produced the highest proportions of repelled mosquitoes in the non-contact repellency tests: 76.8% ( An. gambiae) and 68.5% ( Ae. aegypti). The blood meal inhibition rate at a dose of 10% was 98.4% in Ae. aegypti but only 15.5% in An. gambiae. The citral chemotype of L. alba EO has promising biological effects in both species that make it a potentially good candidate for its use in mosquito control. The results obtained in this study encourage the further evaluation of L. alba EOs from other localities and of different chemotypes, under laboratory and field conditions.

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          Fitting Linear Mixed-Effects Models Usinglme4

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            MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data

            Background Mass spectrometry (MS) coupled with online separation methods is commonly applied for differential and quantitative profiling of biological samples in metabolomic as well as proteomic research. Such approaches are used for systems biology, functional genomics, and biomarker discovery, among others. An ongoing challenge of these molecular profiling approaches, however, is the development of better data processing methods. Here we introduce a new generation of a popular open-source data processing toolbox, MZmine 2. Results A key concept of the MZmine 2 software design is the strict separation of core functionality and data processing modules, with emphasis on easy usability and support for high-resolution spectra processing. Data processing modules take advantage of embedded visualization tools, allowing for immediate previews of parameter settings. Newly introduced functionality includes the identification of peaks using online databases, MSn data support, improved isotope pattern support, scatter plot visualization, and a new method for peak list alignment based on the random sample consensus (RANSAC) algorithm. The performance of the RANSAC alignment was evaluated using synthetic datasets as well as actual experimental data, and the results were compared to those obtained using other alignment algorithms. Conclusions MZmine 2 is freely available under a GNU GPL license and can be obtained from the project website at: http://mzmine.sourceforge.net/. The current version of MZmine 2 is suitable for processing large batches of data and has been applied to both targeted and non-targeted metabolomic analyses.
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              MZmine: toolbox for processing and visualization of mass spectrometry based molecular profile data.

              New additional methods are presented for processing and visualizing mass spectrometry based molecular profile data, implemented as part of the recently introduced MZmine software. They include new features and extensions such as support for mzXML data format, capability to perform batch processing for large number of files, support for parallel processing, new methods for calculating peak areas using post-alignment peak picking algorithm and implementation of Sammon's mapping and curvilinear distance analysis for data visualization and exploratory analysis. MZmine is available under GNU Public license from http://mzmine.sourceforge.net/.
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                Author and article information

                Contributors
                cool_hamidou@yahoo.fr
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                12 February 2024
                12 February 2024
                2024
                : 14
                : 3508
                Affiliations
                [1 ]UMR MIVEGEC (Montpellier University/IRD/CNRS), ( https://ror.org/051escj72) 911 avenue Agropolis, 34394 Montpellier Cedex 5, France
                [2 ]Université Nangui Abrogoua, ( https://ror.org/0462xwv27) 02 BP 801, Abidjan, Côte d’Ivoire
                [3 ]Centre Suisse de Recherches Scientifiques en Côte d’Ivoire, ( https://ror.org/03sttqc46) 01 BP 1303, Abidjan 01, Côte d’Ivoire
                [4 ]UMR 152 Pharma Dev, Université de Toulouse, IRD, UPS, ( https://ror.org/004raaa70) 35 chemin des Maraîchers, 31062 Toulouse Cedex 9, France
                Article
                52801
                10.1038/s41598-024-52801-1
                10861474
                38346996
                3a9a0024-c121-4a25-913f-caea6f6dfe99
                © The Author(s) 2024

                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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 23 November 2023
                : 23 January 2024
                Funding
                Funded by: Strategic support programme for scientific research in Côte d'Ivoire
                Award ID: (PASRES_Project N°250)
                Funded by: FundRef http://dx.doi.org/10.13039/100012947, Institut de Recherche pour le Développement;
                Categories
                Article
                Custom metadata
                © Springer Nature Limited 2024

                Uncategorized
                animal behaviour,entomology,disease prevention,infectious diseases
                Uncategorized
                animal behaviour, entomology, disease prevention, infectious diseases

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