Near-infrared spectroscopy and machine learning algorithms for rapid and non-invasive detection of Trichuris.

ABSTRACT:

Background

Trichuris trichiura (whipworm) is one of the most prevalent soil transmitted helminths (STH) affecting 604-795 million people worldwide. Diagnostic tools that are affordable and rapid are required for detecting STH. Here, we assessed the performance of the near-infrared spectroscopy (NIRS) technique coupled with machine learning algorithms to detect Trichuris muris in faecal, blood, serum samples and non-invasively through the skin of mice.

Methodology

We orally infected 10 mice with 30 T. muris eggs (low dose group), 10 mice with 200 eggs (high dose group) and 10 mice were used as the control group. Using the NIRS technique, we scanned faecal, serum, whole blood samples and mice non-invasively through their skin over a period of 6 weeks post infection. Using arti

SUBMITTER: Kariyawasam TN 

PROVIDER: S-EPMC10681298 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature