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Integrating data from multiple African countries to identify and validate novel insecticide resistance candidates in the malaria vector An. gambiae sl

Integrating data from multiple African countries to identify and validate novel insecticide resistance candidates in the malaria vector An. gambiae sl
整合来自多个非洲国家的数据,以识别和验证疟疾媒介 An 中的新型杀虫剂抗性候选者。
批准号:
MR/R024839/1
负责人:
Victoria Anne Ingham
金额:
$37.04万
依托单位国家:
英国
项目类别:
Fellowship
财政年份:
2017
资助国家:
英国
项目状态:
已结题
起止时间:
2017 至 --

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中文摘要
翻译
病媒控制战略是消灭疟疾工作的关键;自2000年以来预防的6.63亿疟疾病例中,估计有80%是由于使用了驱虫蚊帐(驱虫蚊帐和室内滞留喷洒)。由于病媒控制工作的扩大,对公共卫生杀虫剂的抗药性现已广泛传播。所有经杀虫剂处理过的蚊帐都用拟除虫菊酯处理,但80%的非洲国家报告对这类杀虫剂有抗药性。这种抗药性对经杀虫剂处理过的蚊帐的保护效力的确切影响仍在辩论之中,但人们一致认为,迫切需要有知情的实地战略,以防止这些关键的干预措施失败,因此;在世界上最贫穷的地区,与疟疾有关的发病率和死亡率重新抬头。在撒哈拉以南非洲地区,疟疾病媒的基因组数据是可用的,包括广泛的人口遗传学资源和整个非洲大陆的基因表达数据。这些数据代表了一组令人难以置信的多样化和丰富的信息,这些信息以前曾被孤立地研究过。以客观的方式整合这些多物种,多国家的数据集,预计将确定以前未被识别的基因和与杀虫剂抗性相关的途径。在开发诊断之前,将在实验室环境中验证这些计算机模拟结果,并在现场环境中进行评价。一套全面的抗药性制造者的可用性也将使人们能够更详细地研究抗药性对蚊子健康及其传播疟疾寄生虫能力的影响。所产生的数据将有助于控制方案,以帮助减轻耐药性的影响,并有助于工业合作伙伴开发新的杀虫剂和病媒控制工具。
英文摘要
Vector control strategies are key to malaria eradication efforts; an estimated 80 % of the 663 million malaria cases prevented since the year 2000 were due to insecticide treated nets (ITNs and indoor residual spraying). As a result of this scale up in vector control, resistance to public health insecticides is now wide spread. All ITNs are treated with pyrethroids and yet 80% of African countries reporting resistance to this class. The precise impact of this resistance on the protective efficacy of ITNs is still being debated but there is consensus that there is an urgent need for informed field strategies to prevent failure of these crucial interventions and hence; the resurgence of malaria associated morbidity and mortality in the world's poorest regions.Concerns over the potential impact of vector control failure have stimulated the generation of a wide variety of field data available on malaria vectors in sub-Saharan Africa, including extensive population genetics resources and continent-wide gene expression data. These data represent an incredibly diverse and rich set of information that have previously been examined in isolation. Integrating these multi-species, multi-country datasets in an objective way, is expected to identify previously unrecognised genes and pathways associated with insecticide resistance. These in silico results will be validated in a laboratory setting prior to the development of diagnostics which will be evaluated under field settings. The availability of a comprehensive set of resistance makers will also enable more detailed studies of the impact of resistance on the fitness of the mosquito and its ability to transmit the malaria parasite. The data generated will be of value to control programmes to help mitigate the impact of resistance, and industry partners, developing new insecticides and vector control tools.
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1016/j.ibmb.2020.103372
发表时间: 2020-06
期刊: INSECT BIOCHEMISTRY AND MOLECULAR BIOLOGY
影响因子: 3.8
作者: [Brown, Faye, Paton, Douglas G., Catteruccia, Flaminia, Ranson, Hilary, Ingham, Victoria A.]
通讯作者: Ingham, Victoria A.
Capturing the transcription factor interactome in response to sub-lethal insecticide exposure
捕获响应亚致死杀虫剂暴露的转录因子相互作用组
DOI: 10.1101/2020.11.26.399691
发表时间: 2020
期刊:
影响因子: --
作者: [Ingham V]
通讯作者: Ingham V
Additional file 11 of Transcriptomic analysis reveals pronounced changes in gene expression due to sub-lethal pyrethroid exposure and ageing in insecticide resistance Anopheles coluzzii
转录组分析的附加文件 11 揭示了由于亚致死拟除虫菊酯暴露和杀虫剂抗性老化导致的基因表达的显着变化。
DOI: 10.6084/m9.figshare.14570537
发表时间: 2021
期刊:
影响因子: --
作者: [Ingham V]
通讯作者: Ingham V
DOI: 10.1016/j.cris.2021.100018
发表时间: 2021
期刊: Current research in insect science
影响因子: --
作者: [Ingham VA, Elg S, Nagi SC, Dondelinger F]
通讯作者: Dondelinger F
8
    国内基金
    海外基金
    Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
    Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
    复杂数据下半参数转换模型及其在老年慢性病发展中的应用研究
    • 批准号:
      72101261
    • 项目类别:
      青年科学基金项目(C类)
    • 资助金额:
      30.0万元
    • 批准年份:
      2021
    • 负责人:
      孙韬
    • 依托单位:
    Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
    • 批准号:
      --
    • 项目类别:
      --
    • 资助金额:
      40万元
    • 批准年份:
      2020
    • 负责人:
      Vikrant Gupta
    • 依托单位: