Limits...
The influence of physiological status on age prediction of Anopheles arabiensis using near infra-red spectroscopy.

Ntamatungiro AJ, Mayagaya VS, Rieben S, Moore SJ, Dowell FE, Maia MF - Parasit Vectors (2013)

Bottom Line: Mosquitoes of the same chronological age, but at different physiological stages, were scanned and compared using cross-validations.It was advantageous to include mosquitoes of different chronological ages and physiological stages in calibrations, as it increases the robustness of the model resulting in better age predictions.Entomologists that wish to use NIR technology to predict the age of field-caught An. gambiae s.l from their study area should use a calibration developed from their field strain using mosquitoes of diverse chronological ages and physiological stages to increase the robustness and accuracy of the predictions.

View Article: PubMed Central - HTML - PubMed

Affiliation: Ifakara Health Institute, Environmental Health and Ecological Sciences, P,O, Box 53, Ifakara, Tanzania. ajohn@ihi.or.tz.

ABSTRACT

Background: Determining the age of malaria vectors is essential for evaluating the impact of interventions that reduce the survival of wild mosquito populations and for estimating changes in vectorial capacity. Near infra-red spectroscopy (NIRS) is a simple and non-destructive method that has been used to determine the age and species of Anopheles gambiae s.l. by analyzing differences in absorption spectra. The spectra are affected by biochemical changes that occur during the life of a mosquito and could be influenced by senescence and also the life history of the mosquito, i.e., mating, blood feeding and egg-laying events.

Methods: To better understand these changes, we evaluated the influence of mosquito physiological status on NIR energy absorption spectra. Mosquitoes were kept in individual cups to permit record keeping of each individual insect's life history. Mosquitoes of the same chronological age, but at different physiological stages, were scanned and compared using cross-validations.

Results: We observed a slight trend within some physiological stages that suggest older insects tend to be predicted as being physiologically more mature. It was advantageous to include mosquitoes of different chronological ages and physiological stages in calibrations, as it increases the robustness of the model resulting in better age predictions.

Conclusions: Progression through different physiological statuses of An. arabiensis influences the chronological age prediction by the NIRS. Entomologists that wish to use NIR technology to predict the age of field-caught An. gambiae s.l from their study area should use a calibration developed from their field strain using mosquitoes of diverse chronological ages and physiological stages to increase the robustness and accuracy of the predictions.

Show MeSH

Related in: MedlinePlus

NIRS predicted chronological age versus the actual age of An. arabiensis. Chronological age predictions by NIRS using model that includes all physiological stages (virgin, pre-gravid, 1st oviposition, 2nd oviposition).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3852719&req=5

Figure 1: NIRS predicted chronological age versus the actual age of An. arabiensis. Chronological age predictions by NIRS using model that includes all physiological stages (virgin, pre-gravid, 1st oviposition, 2nd oviposition).

Mentions: The objective of this study was to determine if the progression through different physiological changes would alter the NIRS chronological age prediction of An. arabiensis. In order to investigate models to predict chronological age, we first developed a calibration using pre-gravid mosquitoes of different chronological age to predict the age of other mosquitoes at other physiological stages. Results showed that the predicted chronological age increased along with the real age (FigureĀ 1), but younger mosquitoes were predicted as older than their actual age, and older mosquitoes were predicted as younger than their actual age.


The influence of physiological status on age prediction of Anopheles arabiensis using near infra-red spectroscopy.

Ntamatungiro AJ, Mayagaya VS, Rieben S, Moore SJ, Dowell FE, Maia MF - Parasit Vectors (2013)

NIRS predicted chronological age versus the actual age of An. arabiensis. Chronological age predictions by NIRS using model that includes all physiological stages (virgin, pre-gravid, 1st oviposition, 2nd oviposition).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3852719&req=5

Figure 1: NIRS predicted chronological age versus the actual age of An. arabiensis. Chronological age predictions by NIRS using model that includes all physiological stages (virgin, pre-gravid, 1st oviposition, 2nd oviposition).
Mentions: The objective of this study was to determine if the progression through different physiological changes would alter the NIRS chronological age prediction of An. arabiensis. In order to investigate models to predict chronological age, we first developed a calibration using pre-gravid mosquitoes of different chronological age to predict the age of other mosquitoes at other physiological stages. Results showed that the predicted chronological age increased along with the real age (FigureĀ 1), but younger mosquitoes were predicted as older than their actual age, and older mosquitoes were predicted as younger than their actual age.

Bottom Line: Mosquitoes of the same chronological age, but at different physiological stages, were scanned and compared using cross-validations.It was advantageous to include mosquitoes of different chronological ages and physiological stages in calibrations, as it increases the robustness of the model resulting in better age predictions.Entomologists that wish to use NIR technology to predict the age of field-caught An. gambiae s.l from their study area should use a calibration developed from their field strain using mosquitoes of diverse chronological ages and physiological stages to increase the robustness and accuracy of the predictions.

View Article: PubMed Central - HTML - PubMed

Affiliation: Ifakara Health Institute, Environmental Health and Ecological Sciences, P,O, Box 53, Ifakara, Tanzania. ajohn@ihi.or.tz.

ABSTRACT

Background: Determining the age of malaria vectors is essential for evaluating the impact of interventions that reduce the survival of wild mosquito populations and for estimating changes in vectorial capacity. Near infra-red spectroscopy (NIRS) is a simple and non-destructive method that has been used to determine the age and species of Anopheles gambiae s.l. by analyzing differences in absorption spectra. The spectra are affected by biochemical changes that occur during the life of a mosquito and could be influenced by senescence and also the life history of the mosquito, i.e., mating, blood feeding and egg-laying events.

Methods: To better understand these changes, we evaluated the influence of mosquito physiological status on NIR energy absorption spectra. Mosquitoes were kept in individual cups to permit record keeping of each individual insect's life history. Mosquitoes of the same chronological age, but at different physiological stages, were scanned and compared using cross-validations.

Results: We observed a slight trend within some physiological stages that suggest older insects tend to be predicted as being physiologically more mature. It was advantageous to include mosquitoes of different chronological ages and physiological stages in calibrations, as it increases the robustness of the model resulting in better age predictions.

Conclusions: Progression through different physiological statuses of An. arabiensis influences the chronological age prediction by the NIRS. Entomologists that wish to use NIR technology to predict the age of field-caught An. gambiae s.l from their study area should use a calibration developed from their field strain using mosquitoes of diverse chronological ages and physiological stages to increase the robustness and accuracy of the predictions.

Show MeSH
Related in: MedlinePlus