Advancing DNA Structural Analysis: A SERS Approach Free from Citrate Interference Combined with Machine Learning

The Journal of Physical Chemistry Letters, Год журнала: 2025, Номер unknown, С. 1199 - 1205

Опубликована: Янв. 23, 2025

Surface-enhanced Raman spectroscopy (SERS) has become an indispensable tool for biomolecular analysis, yet the detection of DNA signals remains hindered by spectral interference from citrate ions, which overlap with key features. This study introduces innovative, ultrasensitive SERS platform utilizing thiol-modified silver nanoparticles (Ag@SDCNPs) that overcomes this challenge eliminating interference. enables direct, interference-free and structural characterization a wide range conformations, including single-stranded (ssDNA), double-stranded (dsDNA), i-motif, hairpin, G-quadruplex, triple-stranded (tsDNA). Employing calcium ions as aggregating agents deuterated methanol internal standard, system achieved high quality reproducibility. Machine learning (ML) techniques, such linear discriminant analysis (LDA) t-distributed stochastic neighbor embedding (t-SNE), were utilized classification, alongside support vector machines (SVM) predictive modeling, yielding accuracies above 99%. These findings establish robust versatile offering transformative potential applications in clinical diagnostics biomedical research.

Язык: Английский

Intelligent decoding platform for peptide sequences: SERS detection via high affinity self-assembled silver nanoparticles and machine learning analysis

Analytica Chimica Acta, Год журнала: 2025, Номер 1347, С. 343797 - 343797

Опубликована: Фев. 13, 2025

Язык: Английский

An ultra-sensitive, intelligent platform for food safety monitoring: Label-free detection of illegal additives using self-assembled SERS substrates and machine learning

Food Chemistry, Год журнала: 2025, Номер 479, С. 143754 - 143754

Опубликована: Март 7, 2025

Язык: Английский