Evidence map›Paper›PMID 35073364›Full record

ArticlePloS one2022

Assessing risk of vector transmission of Chagas disease through blood source analysis using LC-MS/MS for hemoglobin sequence identification.

Daniel Penados, José P Pineda, Elisa Laparra-Ruiz, Manuel F Galván, Anna M Schmoker, Bryan A Ballif, M Carlota Monroy, Lori Stevens

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 44% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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 2 countries.

Daniel PenadosFaculty of Chemical Sciences and Pharmacy, Applied Entomology and Parasitology Laboratory, University of San Carlos, Guatemala City, Guatemala.ORCID 0000-0003-2186-6121
José P PinedaFaculty of Chemical Sciences and Pharmacy, Applied Entomology and Parasitology Laboratory, University of San Carlos, Guatemala City, Guatemala.
Elisa Laparra-RuizFaculty of Chemical Sciences and Pharmacy, Applied Entomology and Parasitology Laboratory, University of San Carlos, Guatemala City, Guatemala.
Manuel F GalvánFaculty of Engineering, Science and Systems School, University of San Carlos, Guatemala City, Guatemala.ORCID 0000-0002-2160-1177
Anna M SchmokerDepartment of Biology, University of Vermont, Burlington, Vermont, United States of America.
Bryan A BallifDepartment of Biology, University of Vermont, Burlington, Vermont, United States of America.
M Carlota MonroyFaculty of Chemical Sciences and Pharmacy, Applied Entomology and Parasitology Laboratory, University of San Carlos, Guatemala City, Guatemala.ORCID 0000-0003-0938-607X
Lori StevensDepartment of Biology, University of Vermont, Burlington, Vermont, United States of America.ORCID 0000-0003-3847-5979
Universidad de San Carlos de Guatemala · GTUniversity of Vermont · US

Funding

Vermont INBRE Administrative Supplement 2024 AWD 118P20GM103449 · NIGMS · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI CHRISTOPHER S FRANCKLYN · 2012 to 2026
$58.4M
NIGMS NIH HHS P20 GM103449
6 · The paper itself

Abstract

Chagas disease is mainly transmitted by triatomine insect vectors that feed on vertebrate blood. The disease has complex domiciliary infestation patterns and parasite transmission dynamics, influenced by biological, ecological, and socioeconomic factors. In this context, feeding patterns have been used to understand vector movement and transmission risk. Recently, a new technique using Liquid chromatography tandem mass spectrometry (LC-MS/MS) targeting hemoglobin peptides has showed excellent results for understanding triatomines' feeding patterns. The aim of this study was to further develop the automated computational analysis pipeline for peptide sequence taxonomic identification, enhancing the ability to analyze large datasets data. We then used the enhanced pipeline to evaluate the feeding patterns of Triatoma dimidiata, along with domiciliary infestation risk variables, such as unkempt piles of firewood or construction material, cracks in bajareque and adobe walls and intradomiciliary animals. Our new python scripts were able to detect blood meal sources in 100% of the bugs analyzed and identified nine different species of blood meal sources. Human, chicken, and dog were the main blood sources found in 78.7%, 50.4% and 44.8% of the bugs, respectively. In addition, 14% of the bugs feeding on chicken and 15% of those feeding on dogs were captured in houses with no evidence of those animals being present. This suggests a high mobility among ecotopes and houses. Two of the three main blood sources, dog and chicken, were significantly (p < 0.05) affected by domiciliary infestation risk variables, including cracks in walls, construction material and birds sleeping in the intradomicile. This suggests that these variables are important for maintaining reproducing Triatoma dimidiata populations and that it is critical to mitigate these variables in all the houses of a village for effective control of these mobile vectors.

Indexed as

AnimalsBlood Chemical AnalysisChagas DiseaseChickensDogsFeeding BehaviorGas Chromatography-Mass SpectrometryGuatemalaHemoglobinsHumansInsect VectorsLogistic ModelsRisk AssessmentRisk FactorsTriatomaHemoglobins

Identifiers

PMID35073364
PMCPMC8786159
OpenAlexW4206949144

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.