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      Monitoring Aedes populations for arboviruses, Wolbachia, insecticide resistance and its mechanisms in various agroecosystems in Benin

      , , , , , ,
      Acta Tropica
      Elsevier BV

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          A new mathematical model for relative quantification in real-time RT-PCR.

          M. Pfaffl (2001)
          Use of the real-time polymerase chain reaction (PCR) to amplify cDNA products reverse transcribed from mRNA is on the way to becoming a routine tool in molecular biology to study low abundance gene expression. Real-time PCR is easy to perform, provides the necessary accuracy and produces reliable as well as rapid quantification results. But accurate quantification of nucleic acids requires a reproducible methodology and an adequate mathematical model for data analysis. This study enters into the particular topics of the relative quantification in real-time RT-PCR of a target gene transcript in comparison to a reference gene transcript. Therefore, a new mathematical model is presented. The relative expression ratio is calculated only from the real-time PCR efficiencies and the crossing point deviation of an unknown sample versus a control. This model needs no calibration curve. Control levels were included in the model to standardise each reaction run with respect to RNA integrity, sample loading and inter-PCR variations. High accuracy and reproducibility (<2.5% variation) were reached in LightCycler PCR using the established mathematical model.
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            Is Open Access

            Contemporary status of insecticide resistance in the major Aedes vectors of arboviruses infecting humans

            Both Aedes aegytpi and Ae. albopictus are major vectors of 5 important arboviruses (namely chikungunya virus, dengue virus, Rift Valley fever virus, yellow fever virus, and Zika virus), making these mosquitoes an important factor in the worldwide burden of infectious disease. Vector control using insecticides coupled with larval source reduction is critical to control the transmission of these viruses to humans but is threatened by the emergence of insecticide resistance. Here, we review the available evidence for the geographical distribution of insecticide resistance in these 2 major vectors worldwide and map the data collated for the 4 main classes of neurotoxic insecticide (carbamates, organochlorines, organophosphates, and pyrethroids). Emerging resistance to all 4 of these insecticide classes has been detected in the Americas, Africa, and Asia. Target-site mutations and increased insecticide detoxification have both been linked to resistance in Ae. aegypti and Ae. albopictus but more work is required to further elucidate metabolic mechanisms and develop robust diagnostic assays. Geographical distributions are provided for the mechanisms that have been shown to be important to date. Estimating insecticide resistance in unsampled locations is hampered by a lack of standardisation in the diagnostic tools used and by a lack of data in a number of regions for both resistance phenotypes and genotypes. The need for increased sampling using standard methods is critical to tackle the issue of emerging insecticide resistance threatening human health. Specifically, diagnostic doses and well-characterised susceptible strains are needed for the full range of insecticides used to control Ae. aegypti and Ae. albopictus to standardise measurement of the resistant phenotype, and calibrated diagnostic assays are needed for the major mechanisms of resistance.
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              Global risk mapping for major diseases transmitted by Aedes aegypti and Aedes albopictus.

              The objective of this study was to map the global risk of the major arboviral diseases transmitted by Aedes aegypti and Aedes albopictus by identifying areas where the diseases are reported, either through active transmission or travel-related outbreaks, as well as areas where the diseases are not currently reported but are nonetheless suitable for the vector.
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                Author and article information

                Contributors
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                Journal
                Acta Tropica
                Acta Tropica
                Elsevier BV
                0001706X
                May 2024
                May 2024
                : 253
                : 107178
                Article
                10.1016/j.actatropica.2024.107178
                043c6704-4c08-4661-a9fb-3e8abe89caff
                © 2024

                https://www.elsevier.com/tdm/userlicense/1.0/

                https://doi.org/10.15223/policy-017

                https://doi.org/10.15223/policy-037

                https://doi.org/10.15223/policy-012

                https://doi.org/10.15223/policy-029

                https://doi.org/10.15223/policy-004

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