Evidence map›Paper›PMID 36690979›Full record

ArticleBMC biology2023

Rapid identification of mosquito species and age by mass spectrometric analysis.

Iris Wagner, Linda Grigoraki, Peter Enevoldson, Michael Clarkson, Sam Jones, Jane L Hurst, Robert J Beynon, Hilary Ranson

Open access · goldAbstract read
In one paragraph

Article in BMC biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.9field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Accurate identification of medically importantCurrent research in parasitology & vector-borne diseases · 2025
    Article
  6. Predicting the age of fieldScience advances · 2024
    Article
  7. Review
  8. Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Iris WagnerCentre for Proteome Research, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK.ORCID 0000-0001-9198-4532
Linda GrigorakiDepartment of Vector Biology, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK.ORCID 0000-0001-8997-0406
Peter EnevoldsonWalton Centre NHS Foundation Trust, Lower Lane, Liverpool, L9 7LJ, UK.
Michael ClarksonDepartment of Livestock and One Health, University of Liverpool, Institute of Infection, Veterinary and Ecological Sciences, Leahurst Campus, Neston, CH64 7TE, UK.
Sam JonesInternational Pheromone Systems Ltd, Evolution House, Long Acres Road, Clayhill Industrial Estate, Neston, CH64 3RL, Cheshire, UK.ORCID 0000-0002-0732-3115
Jane L HurstMammalian Behaviour and Evolution Group, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Leahurst Campus, Neston, CH64 7TE, UK.ORCID 0000-0002-3728-9624
Robert J Beynon *Centre for Proteome Research, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK. r.beynon@liverpool.ac.uk.ORCID 0000-0003-0857-495X
Hilary Ranson *Department of Vector Biology, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK.ORCID 0000-0003-2332-8247
University of Liverpool · GBLiverpool School of Tropical Medicine · GB

Funding

Biotechnology and Biological Sciences Research Council BB/L014793/1Wellcome TrustWellcome Trust 215894/Z/19/Z
6 · The paper itself

Abstract

backgroundA rapid, accurate method to identify and to age-grade mosquito populations would be a major advance in predicting the risk of pathogen transmission and evaluating the public health impact of vector control interventions. Whilst other spectrometric or transcriptomic methods show promise, current approaches rely on challenging morphological techniques or simple binary classifications that cannot identify the subset of the population old enough to be infectious. In this study, the ability of rapid evaporative ionisation mass spectrometry (REIMS) to identify the species and age of mosquitoes reared in the laboratory and derived from the wild was investigated.

resultsThe accuracy of REIMS in identifying morphologically identical species of the Anopheles gambiae complex exceeded 97% using principal component/linear discriminant analysis (PC-LDA) and 84% based on random forest analysis. Age separation into 3 different age categories (1 day, 5-6 days, 14-15 days) was achieved with 99% (PC-LDA) and 91% (random forest) accuracy. When tested on wild mosquitoes from the UK, REIMS data could determine the species and age of the specimens with accuracies of 91 and 90% respectively.

conclusionsThe accuracy of REIMS to resolve the species and age of Anopheles mosquitoes is comparable to that achieved by infrared spectroscopy approaches. The processing time and ease of use represent significant advantages over current, dissection-based methods. Importantly, the accuracy was maintained when using wild mosquitoes reared under differing environmental conditions, and when mosquitoes were stored frozen or desiccated. This high throughput approach thus has potential to conduct rapid, real-time monitoring of vector populations, providing entomological evidence of the impact of alternative interventions.

Indexed as

AnophelesMosquito VectorsAnimalsMass SpectrometryAge gradingMass spectrometryMosquitoRapid evaporative ionisation mass spectrometryREIMSSpecies identification

Identifiers

PMID36690979
PMCPMC9872345
OpenAlexW4317788327

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.