Journal
ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY
Volume 241, Issue -, Pages -Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.ecoenv.2022.113728
Keywords
Sea urchin embryo test; High-throughput screening; Machine learning; Image analysis; Ecotoxicology; Effect-directed analysis
Categories
Funding
- Agencia Estatal de Investigacion (AEI) of Spain
- European Regional Development Fund [CTM2017-84763-C3-1-R]
- Basque Government [IT1213-19]
- University of the Basque Country
- Universite de Pau et des Pays de L' Adour
Ask authors/readers for more resources
The study aims to develop a new high throughput screening method that can be used as a predictive expert system and automatically quantify the size increase and malformation of larvae, thus facilitating the use of sea urchin embryo test in complex toxicant identification pipelines such as effect-directed analysis.
Since countless xenobiotic compounds are being found in the environment, ecotoxicology faces an astounding challenge in identifying toxicants. The combination of high-throughput in vivo/in vitro bioassays with high resolution chemical analysis is an effective way to elucidate the cause-effect relationship. However, these combined strategies imply an enormous workload that can hinder their implementation in routine analysis. The purpose of this study was to develop a new high throughput screening method that could be used as a predictive expert system that automatically quantifies the size increase and malformation of the larvae and, thus, eases the application of the sea urchin embryo test in complex toxicant identification pipelines such as effect-directed analysis. For this task, a training set of 242 images was used to calibrate the size-increase and malformation level of the larvae. Two classification models based on partial least squares discriminant analysis (PLS-DA) were built and compared. Moreover, Hierarchical PLS-DA shows a high proficiency in classifying the larvae, achieving a prediction accuracy of 84 % in validation. The scripts built along the work were compiled in a user-friendly standalone app (SETApp) freely accessible at https://github.com/UPV-EHU-IBeA/SETApp. The SETApp was tested in a real case scenario to fulfill the tedious requirements of a WWTP effect-directed analysis.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available