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Machine learning-powered electrochemical aptasensor for simultaneous monitoring of di(2-ethylhexyl) phthalate and bisphenol A in variable pH environments

Authors
 Kyungyeon Lee  ;  Seong Min Ha  ;  N G Gurudatt  ;  Woong Heo  ;  Kyung-A Hyun  ;  Jayoung Kim  ;  Hyo-Il Jung 
Citation
 JOURNAL OF HAZARDOUS MATERIALS, Vol.462 : 132775, 2024-01 
Journal Title
JOURNAL OF HAZARDOUS MATERIALS
ISSN
 0304-3894 
Issue Date
2024-01
MeSH
Benzhydryl Compounds / analysis ; Diethylhexyl Phthalate* ; Ecosystem ; Humans ; Hydrogen-Ion Concentration ; Phthalic Acids* ; Reproducibility of Results
Keywords
Concentration prediction ; Electrochemical biosensor ; Least-squares boosting (LSBoost) ; Plastics contaminants ; Water monitoring
Abstract
Plastic waste is a pernicious environmental pollutant that threatens ecosystems and human health by releasing contaminants including di(2-ethylhexyl) phthalate (DEHP) and bisphenol A (BPA). Therefore, a machine-learning (ML)-powered electrochemical aptasensor was developed in this study for simultaneously detecting DEHP and BPA in river waters, particularly to minimize the electrochemical signal errors caused by varying pH levels. The aptasensor leverages a straightforward and effective surface modification strategy featuring gold nanoflowers to achieve low detection limits for DEHP and BPA (0.58 and 0.59 pg/mL, respectively), excellent specificity, and stability. The least-squares boosting (LSBoost) algorithm was introduced to reliably monitor the targets regardless of pH; it employs a layer that adjusts the number of multi-indexes and the parallel learning structure of an ensemble model to accurately predict concentrations by preventing overfitting and enhancing the learning effect. The ML-powered aptasensor successfully detected targets in 12 river sites with diverse pH values, exhibiting higher accuracy and reliability. To our knowledge, the platform proposed in this study is the first attempt to utilize ML for the simultaneous assessment of DEHP and BPA. This breakthrough allows for comprehensive investigations into the effects of contamination originating from diverse plastics by eliminating external interferent-caused influences.
Full Text
https://www.sciencedirect.com/science/article/pii/S0304389423020599
DOI
10.1016/j.jhazmat.2023.132775
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Medical Engineering (의학공학교실) > 1. Journal Papers
Yonsei Authors
Kim, Jayoung(김자영)
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/198123
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