Literature DB >> 35895347

Back to the Future: Quantifying Wing Wear as a Method to Measure Mosquito Age.

Lyndsey Gray1, Bryce C Asay2, Blue Hephaestus2, Ruth McCabe3, Greg Pugh1, Erin D Markle1, Thomas S Churcher3, Brian D Foy1.   

Abstract

Vector biologists have long sought the ability to accurately quantify the age of wild mosquito populations, a metric used to measure vector control efficiency. This has proven difficult due to the difficulties of working in the field and the biological complexities of wild mosquitoes. Ideal age grading techniques must overcome both challenges while also providing epidemiologically relevant age measurements. Given these requirements, the Detinova parity technique, which estimates age from the mosquito ovary and tracheole skein morphology, has been most often used for mosquito age grading despite significant limitations, including being based solely on the physiology of ovarian development. Here, we have developed a modernized version of the original mosquito aging method that evaluated wing wear, expanding it to estimate mosquito chronological age from wing scale loss. We conducted laboratory experiments using adult Anopheles gambiae held in insectary cages or mesocosms, the latter of which also featured ivermectin bloodmeal treatments to change the population age structure. Mosquitoes were age graded by parity assessments and both human- and computational-based wing evaluations. Although the Detinova technique was not able to detect differences in age population structure between treated and control mesocosms, significant differences were apparent using the wing scale technique. Analysis of wing images using averaged left- and right-wing pixel intensity scores predicted mosquito age at high accuracy (overall test accuracy: 83.4%, average training accuracy: 89.7%). This suggests that this technique could be an accurate and practical tool for mosquito age grading though further evaluation in wild mosquito populations is required.

Entities:  

Year:  2022        PMID: 35895347      PMCID: PMC9490652          DOI: 10.4269/ajtmh.21-1173

Source DB:  PubMed          Journal:  Am J Trop Med Hyg        ISSN: 0002-9637            Impact factor:   3.707


  47 in total

1.  Determination of physiological age in anophelines and of age distribution in anopheline populations in the USSR.

Authors:  W N BEKLEMISHEV; T S DETINOVA; V P POLOVODOVA
Journal:  Bull World Health Organ       Date:  1959       Impact factor: 9.408

2.  Age determination of Aedes cantans using the ovarian oil injection technique.

Authors:  T Q Hoc; J D Charlwood
Journal:  Med Vet Entomol       Date:  1990-04       Impact factor: 2.739

3.  Analysis of survival of young and old Aedes aegypti (Diptera: Culicidac) from Puerto Rico and Thailand.

Authors:  L C Harrington; J P Buonaccorsi; J D Edman; A Costero; P Kittayapong; G G Clark; T W Scott
Journal:  J Med Entomol       Date:  2001-07       Impact factor: 2.278

4.  Lethal and sublethal effects of avermectin/milbemycin parasiticides on the African malaria vector, Anopheles arabiensis.

Authors:  Megan L Fritz; Edward D Walker; James R Miller
Journal:  J Med Entomol       Date:  2012-03       Impact factor: 2.278

5.  Ivermectin-treated cattle reduces blood digestion, egg production and survival of a free-living population of Anopheles arabiensis under semi-field condition in south-eastern Tanzania.

Authors:  Issa N Lyimo; Stella T Kessy; Kasian F Mbina; Ally A Daraja; Ladslaus L Mnyone
Journal:  Malar J       Date:  2017-06-06       Impact factor: 2.979

6.  Delimiting cryptic morphological variation among human malaria vector species using convolutional neural networks.

Authors:  Jannelle Couret; Danilo C Moreira; Davin Bernier; Aria Mia Loberti; Ellen M Dotson; Marco Alvarez
Journal:  PLoS Negl Trop Dis       Date:  2020-12-17

7.  A novel fluorescence and DNA combination for versatile, long-term marking of mosquitoes.

Authors:  Roy Faiman; Benjamin J Krajacich; Leland Graber; Adama Dao; Alpha Seydou Yaro; Ousmane Yossi; Zana Lamissa Sanogo; Moussa Diallo; Djibril Samaké; Daman Sylla; Moribo Coulibaly; Salif Kone; Sekou Goita; Mamadou B Coulibaly; Olga Muratova; Ashley McCormack; Bronner P Gonçalves; Jennifer Hume; Patrick Duffy; Tovi Lehmann
Journal:  Methods Ecol Evol       Date:  2021-03-28       Impact factor: 7.781

8.  Proteomic biomarkers for ageing the mosquito Aedes aegypti to determine risk of pathogen transmission.

Authors:  Leon E Hugo; James Monkman; Keyur A Dave; Leesa F Wockner; Geoff W Birrell; Emma L Norris; Vivian J Kienzle; Maggy T Sikulu; Peter A Ryan; Jeffery J Gorman; Brian H Kay
Journal:  PLoS One       Date:  2013-03-11       Impact factor: 3.240

9.  Analysis of near infrared spectra for age-grading of wild populations of Anopheles gambiae.

Authors:  Benjamin J Krajacich; Jacob I Meyers; Haoues Alout; Roch K Dabiré; Floyd E Dowell; Brian D Foy
Journal:  Parasit Vectors       Date:  2017-11-07       Impact factor: 3.876

10.  Prediction of mosquito species and population age structure using mid-infrared spectroscopy and supervised machine learning.

Authors:  Mario González Jiménez; Simon A Babayan; Pegah Khazaeli; Margaret Doyle; Finlay Walton; Elliott Reedy; Thomas Glew; Mafalda Viana; Lisa Ranford-Cartwright; Abdoulaye Niang; Doreen J Siria; Fredros O Okumu; Abdoulaye Diabaté; Heather M Ferguson; Francesco Baldini; Klaas Wynne
Journal:  Wellcome Open Res       Date:  2019-09-16
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