Evidence map›Paper›PMID 39524315›Full record

ArticleEcology and evolution2024

DNA Barcoding for the Identification of Adult Mosquitoes (Diptera: Culicidae) in Western Australia.

Binit Lamichhane, Craig Brockway, Kimberly Evasco, Jay Nicholson, Peter J Neville, John S Mackenzie, David Smith, Allison Imrie

Abstract read
In one paragraph

Article in Ecology and evolution, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. A Species-SpecificBiology · 2026
    Article
  3. Article
  4. Accurate identification of medically importantCurrent research in parasitology & vector-borne diseases · 2025
    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.

Binit LamichhaneSchool of Biomedical Sciences University of Western Australia Perth Western Australia Australia.
Craig BrockwayEnvironmental Health Directorate Department of Health Perth Western Australia Australia.
Kimberly EvascoEnvironmental Health Directorate Department of Health Perth Western Australia Australia.
Jay NicholsonSchool of Biomedical Sciences University of Western Australia Perth Western Australia Australia.
Peter J NevilleEnvironmental Health Directorate Department of Health Perth Western Australia Australia.
John S MackenzieFaculty of Health Sciences Curtin University Bentley Western Australia Australia.
David SmithPathWest Laboratory Medicine Perth Western Australia Australia.
Allison ImrieSchool of Biomedical Sciences University of Western Australia Perth Western Australia Australia.ORCID https://orcid.org/0000-0003-4715-6662

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Precise mosquito identification is integral to effective arbovirus surveillance. Nonetheless, the conventional morphological approach to identifying mosquito species is laborious, demands expertise and presents challenges when specimens are damaged. DNA barcoding offers a promising alternative, surmounting challenges inherent in morphological identification. To integrate DNA barcoding into arbovirus surveillance effectively, a robust dataset of mosquito barcode sequences is required. This study established a comprehensive repository of Cytochrome Oxidase I (COI) barcodes, encompassing 177 samples representing 45 mosquito species from southern and northern Western Australia (WA), including 16 species which have not been previously barcoded. The average intraspecific and interspecific genetic distances were 1% and 6.8%, respectively.

Indexed as

CulicidaeDNA barcodingmitochondrial COImosquitoesWestern Australia

Identifiers

PMID39524315
PMCPMC11549376

What OpenQuestion holds

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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.