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Detection of Plasmodium falciparum infected Anopheles gambiae using near-infrared spectroscopy
by
Ferguson, Heather M.
, Ranford-Cartwright, Lisa
, Kapulu, Melissa
, Baldini, Francesco
, Maia, Marta F.
, Dowell, Floyd E.
, Muthui, Michelle
, Wagah, Martin G.
in
Animals
/ Anopheles
/ Anopheles - parasitology
/ Anopheles gambiae
/ Biomedical and Life Sciences
/ Biomedicine
/ Disease transmission
/ Entomology
/ Entomology - methods
/ Female
/ Health screening
/ Infection
/ Infectious Diseases
/ Infrared spectroscopy
/ Intelligence gathering
/ Malaria
/ Mass Screening - methods
/ Medical research
/ Methodology
/ Microbiology
/ Near infrared spectroscopy
/ Oocyst
/ Parasite Load
/ Parasitology
/ Patient outcomes
/ Plasmodium falciparum
/ Plasmodium falciparum - growth & development
/ Polymerase chain reaction
/ Public Health
/ Real-Time Polymerase Chain Reaction
/ Risk factors
/ Spectroscopy
/ Spectroscopy, Near-Infrared - methods
/ Sporozoite
/ Tropical Medicine
2019
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Detection of Plasmodium falciparum infected Anopheles gambiae using near-infrared spectroscopy
by
Ferguson, Heather M.
, Ranford-Cartwright, Lisa
, Kapulu, Melissa
, Baldini, Francesco
, Maia, Marta F.
, Dowell, Floyd E.
, Muthui, Michelle
, Wagah, Martin G.
in
Animals
/ Anopheles
/ Anopheles - parasitology
/ Anopheles gambiae
/ Biomedical and Life Sciences
/ Biomedicine
/ Disease transmission
/ Entomology
/ Entomology - methods
/ Female
/ Health screening
/ Infection
/ Infectious Diseases
/ Infrared spectroscopy
/ Intelligence gathering
/ Malaria
/ Mass Screening - methods
/ Medical research
/ Methodology
/ Microbiology
/ Near infrared spectroscopy
/ Oocyst
/ Parasite Load
/ Parasitology
/ Patient outcomes
/ Plasmodium falciparum
/ Plasmodium falciparum - growth & development
/ Polymerase chain reaction
/ Public Health
/ Real-Time Polymerase Chain Reaction
/ Risk factors
/ Spectroscopy
/ Spectroscopy, Near-Infrared - methods
/ Sporozoite
/ Tropical Medicine
2019
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Detection of Plasmodium falciparum infected Anopheles gambiae using near-infrared spectroscopy
by
Ferguson, Heather M.
, Ranford-Cartwright, Lisa
, Kapulu, Melissa
, Baldini, Francesco
, Maia, Marta F.
, Dowell, Floyd E.
, Muthui, Michelle
, Wagah, Martin G.
in
Animals
/ Anopheles
/ Anopheles - parasitology
/ Anopheles gambiae
/ Biomedical and Life Sciences
/ Biomedicine
/ Disease transmission
/ Entomology
/ Entomology - methods
/ Female
/ Health screening
/ Infection
/ Infectious Diseases
/ Infrared spectroscopy
/ Intelligence gathering
/ Malaria
/ Mass Screening - methods
/ Medical research
/ Methodology
/ Microbiology
/ Near infrared spectroscopy
/ Oocyst
/ Parasite Load
/ Parasitology
/ Patient outcomes
/ Plasmodium falciparum
/ Plasmodium falciparum - growth & development
/ Polymerase chain reaction
/ Public Health
/ Real-Time Polymerase Chain Reaction
/ Risk factors
/ Spectroscopy
/ Spectroscopy, Near-Infrared - methods
/ Sporozoite
/ Tropical Medicine
2019
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Detection of Plasmodium falciparum infected Anopheles gambiae using near-infrared spectroscopy
Journal Article
Detection of Plasmodium falciparum infected Anopheles gambiae using near-infrared spectroscopy
2019
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Overview
Background
Large-scale surveillance of mosquito populations is crucial to assess the intensity of vector-borne disease transmission and the impact of control interventions. However, there is a lack of accurate, cost-effective and high-throughput tools for mass-screening of vectors.
Methods
A total of 750
Anopheles gambiae
(Keele strain) mosquitoes were fed
Plasmodium falciparum
NF54 gametocytes through standard membrane feeding assay (SMFA) and afterwards maintained in insectary conditions to allow for oocyst (8 days) and sporozoite development (14 days). Thereupon, each mosquito was scanned using near infra-red spectroscopy (NIRS) and processed by quantitative polymerase chain reaction (qPCR) to determine the presence of infection and infection load. The spectra collected were randomly assigned to either a training dataset, used to develop calibrations for predicting oocyst- or sporozoite-infection through partial least square regressions (PLS); or to a test dataset, used for validating the calibration’s prediction accuracy.
Results
NIRS detected oocyst- and sporozoite-stage
P. falciparum
infections with 88% and 95% accuracy, respectively. This study demonstrates proof-of-concept that NIRS is capable of rapidly identifying laboratory strains of human malaria infection in African mosquito vectors.
Conclusions
Accurate, low-cost, reagent-free screening of mosquito populations enabled by NIRS could revolutionize surveillance and elimination strategies for the most important human malaria parasite in its primary African vector species. Further research is needed to evaluate how the method performs in the field following adjustments in the training datasets to include data from wild-caught infected and uninfected mosquitoes.
Publisher
BioMed Central,BioMed Central Ltd,BMC
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