Evidence map›Paper›PMID 23936017›Full record

ArticlePloS one2013

Gene expression-based biomarkers for Anopheles gambiae age grading.

Mei-Hui Wang, Osvaldo Marinotti, Daibin Zhong, Anthony A James, Edward Walker, Tom Guda, Eliningaya J Kweka, John Githure, Guiyun Yan

Abstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
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  4. Article
  5. Predicting the age of fieldScience advances · 2024
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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

9 authors.

Mei-Hui WangProgram in Public Health, University of California Irvine, Irvine, California, United States of America.
Osvaldo Marinotti
Daibin Zhong
Anthony A James
Edward Walker
Tom Guda
Eliningaya J Kweka
John Githure
Guiyun Yan

Funding

Ecology of African Highland MalariaR01AI050243 · NIAID · UNIVERSITY OF CALIFORNIA-IRVINE · PI YAN, GUIYUN · 2001 to 2018
$8.8M
Research Training in Mosquito Genomics and Bioinformat*D43TW001505 · FIC · UNIVERSITY OF CALIFORNIA-IRVINE · PI Guiyun Yan · 2000 to 2026
$6.0M
Molecular Markers for Anopheles Gambiae Age GradingR21AI078463 · NIAID · UNIVERSITY OF CALIFORNIA-IRVINE · PI YAN, GUIYUN · 2008 to 2009
$398k
FIC NIH HHS D43 TW001505NIAID NIH HHS R01 AI050243NIAID NIH HHS R21 AI078463
6 · The paper itself

Abstract

Information on population age structure of mosquitoes under natural conditions is fundamental to the understanding of vectorial capacity and crucial for assessing the impact of vector control measures on malaria transmission. Transcriptional profiling has been proposed as a method for predicting mosquito age for Aedes and Anopheles mosquitoes, however, whether this new method is adequate for natural conditions is unknown. This study tests the applicability of transcriptional profiling for age-grading of Anopheles gambiae, the most important malaria vector in Africa. The transcript abundance of two An. gambiae genes, AGAP009551 and AGAP011615, was measured during aging under laboratory and field conditions in three mosquito strains. Age-dependent monotonic changes in transcript levels were observed in all strains evaluated. These genes were validated as age-grading biomarkers using the mark, release and recapture (MRR) method. The MRR method determined a good correspondence between actual and predicted age, and thus demonstrated the value of age classifications derived from the transcriptional profiling of these two genes. The technique was used to establish the age structure of mosquito populations from two malaria-endemic areas in western Kenya. The population age structure determined by the transcriptional profiling method was consistent with that based on mosquito parity. This study demonstrates that the transcription profiling method based on two genes is valuable for age determination of natural mosquitoes, providing a new approach for determining a key life history trait of malaria vectors.

Indexed as

Gene Expression ProfilingAgingAnimalsAnophelesBiomarkersFemaleKenyaMaleRNA, MessengerTranscriptomeBiomarkersRNA, Messenger

Identifiers

PMID23936017
PMCPMC3720620

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Registered trials

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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.