ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025
Plasmonic Molecular Entrapment for Label-Free Methylated DNA Detection and Machine-Learning Assisted Quantification.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Ligand-Defined Interfacial Chemistry Enables Instant and Sequence-General DNA Chemisorption on Gold Nanoparticles Toward Label-Free SERS With Single-Base Resolution.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Plasmonic Molecular Entrapment for Label-Free Methylated DNA Detection and Machine-Learning Assisted Quantification.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Epigenetic DNA methylations are linked to the activation of oncogenes and inactivation of tumor suppressor genes. A reliable and label-free method to quantitatively measure DNA methylation levels is essential for diagnosing and monitoring methylation-related diseases. Herein, plasmonic molecular entrapment (PME) method assisted SERS as facile strategy for trapping and label-free sensing of DNA methylation, utilizing in situ surface growth of plasmonic particle in the presence of target analytes, are developed. This highly sensitive and adaptable technique forms hotspot sites around target analytes, overcoming mismatch geometrical properties and producing a strong electromagnetic field that leads to significant SERS signal enhancement. The PME method effectively profiles and quantifies DNA methylation, demonstrating robust capabilities for DNA analysis. A logistic regression (LR)-based machine learning accurately quantifies and classifies methylation levels in clinical serum samples of colorectal cancer and normal patients with high sensitivity, specificity, and accuracy, highlighting the feasibility of this technique. The developed PME method combined with machine learning offers promising sensing techniques for disease screening and diagnosis, marking a significant advancement in disease detection and patient care.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.