ArticleScientific reports2021
Near infrared spectroscopy accurately detects Trypanosoma cruzi non-destructively in midguts, rectum and excreta samples of Triatoma infestans.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 13 citations in OpenAlex.
- Article
- Article
- A New Approach for Chagas Disease Screening Using Serum Infrared Spectroscopy and Machine Learning Algorithms.ACS infectious diseases · 2025Article
- Near-infrared spectroscopy discriminates mass-reared sterile and wild tsetse flies.PLoS neglected tropical diseases · 2025Article
- Age, sex, and mating status discrimination in the sand fly Lutzomyia longipalpis using near infra-red spectroscopy (NIRS).Parasites & vectors · 2024Article
- Near-infrared spectroscopy and machine learning algorithms for rapid and non-invasive detection of Trichuris.PLoS neglected tropical diseases · 2023Article
- First Report of the Detection of DENV1 in Human Blood Plasma with Near-Infrared Spectroscopy.Viruses · 2022Article
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Authors and funding
12 authors at 4 institutions in 2 countries.
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No grant is acknowledged in the PubMed record.
Abstract
Chagas disease is a neglected tropical disease caused by Trypanosoma cruzi parasite with an estimated 70 million people at risk. Traditionally, parasite presence in triatomine vectors is detected through optical microscopy which can be low in sensitivity or molecular techniques which can be costly in endemic countries. The aim of this study was to evaluate the ability of a reagent-free technique, the Near Infrared Spectroscopy (NIRS) for rapid and non-invasive detection of T. cruzi in Triatoma infestans body parts and in wet/dry excreta samples of the insect. NIRS was 100% accurate for predicting the presence of T. cruzi infection Dm28c strain (TcI) in either the midgut or the rectum and models developed from either body part could predict infection in the other part. Models developed to predict infection in excreta samples were 100% accurate for predicting infection in both wet and dry samples. However, models developed using dry excreta could not predict infection in wet samples and vice versa. This is the first study to report on the potential application of NIRS for rapid and non-invasive detection of T. cruzi infection in T. infestans in the laboratory. Future work should demonstrate the capacity of NIRS to detect T. cruzi in triatomines originating from the field.
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