Umbrella‐Popcorn Chip With Planar Hotspots Enables Uniform SERS Fingerprinting for Accurate HPV DNA Subtyping and Clinical Validation

ABSTRACT Conventional SERS‐based nucleic acid typing is severely challenged due to the dominance of adenine signals, obscuring the accurate detection of other nucleobases and thus limiting precise DNA fingerprinting. Herein, we introduce U‐PopChip (Umbrella‐Popcorn Chip), a novel SERS substrate engineered with uniformly distributed surface hotspots through umbrella‐shaped structured templates integrated with silver “popcorn” nanoparticles. Calculate the angle between complementary bases and the substrate surface, confirming that all four bases are nearly perpendicular to the substrate surface. Quantitatively demonstrate that this perpendicular orientation effectively eliminates angle‐induced enhancement bias. This innovative design significantly mitigates the overwhelming A‐base signals, enabling balanced and ultrasensitive detection of all four nucleobases (A, T, C, G). Coupled with machine learning algorithms, the platform demonstrated precise subtype discrimination of high‐risk HPV DNA, HPV 18 DNA the lowest detection concentration achieving 19.2 copies/mL. Validation in clinical cervical secretion samples exhibited excellent consistency with conventional Gene chips and TCT results. This study provides a transformative approach, significantly enhancing the practical capability of SERS technology for viral nucleic acid typing and clinical diagnostics.

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Publication Details

Journal
Advanced Functional Materials
Published
2026-08-25
DOI
https://doi.org/10.1002/adfm.77883
Primary Topic
Biosensors and Analytical Detection
Type
article
Field-Weighted Citation Impact
0.00

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article

Umbrella‐Popcorn Chip With Planar Hotspots Enables Uniform SERS Fingerprinting for Accurate HPV DNA Subtyping and Clinical Validation

Siqi Gong, Chaochao Ma, Yang Li, Zibo Gao et al.
Advanced Functional Materials
Biosensors and Analytical Detection
article

Umbrella‐Popcorn Chip With Planar Hotspots Enables Uniform SERS Fingerprinting for Accurate HPV DNA Subtyping and Clinical Validation

Siqi Gong, Chaochao Ma, Yang Li, Zibo Gao, Liangliang Jiang, Yingji Wang, Yizhen Tang, Yaowen Xing, Mingxu Zhang, Sijia Liu, Guangrun Wu, Xianqi Sun, Jing Wang, Jiacheng Li, Jing Wu
article en

Abstract

ABSTRACT Conventional SERS‐based nucleic acid typing is severely challenged due to the dominance of adenine signals, obscuring the accurate detection of other nucleobases and thus limiting precise DNA fingerprinting. Herein, we introduce U‐PopChip (Umbrella‐Popcorn Chip), a novel SERS substrate engineered with uniformly distributed surface hotspots through umbrella‐shaped structured templates integrated with silver “popcorn” nanoparticles. Calculate the angle between complementary bases and the substrate surface, confirming that all four bases are nearly perpendicular to the substrate surface. Quantitatively demonstrate that this perpendicular orientation effectively eliminates angle‐induced enhancement bias. This innovative design significantly mitigates the overwhelming A‐base signals, enabling balanced and ultrasensitive detection of all four nucleobases (A, T, C, G). Coupled with machine learning algorithms, the platform demonstrated precise subtype discrimination of high‐risk HPV DNA, HPV 18 DNA the lowest detection concentration achieving 19.2 copies/mL. Validation in clinical cervical secretion samples exhibited excellent consistency with conventional Gene chips and TCT results. This study provides a transformative approach, significantly enhancing the practical capability of SERS technology for viral nucleic acid typing and clinical diagnostics.

Advanced Functional Materials
Qingdao University (CN), Qingdao University of Science and Technology (CN), Harbin Medical University (CN), Nantong University (CN), Third Affiliated Hospital of Harbin Medical University (CN), Qingdao Municipal Hospital (CN), Heilongjiang Provincial Hospital (CN), Second Affiliated Hospital of Harbin Medical University (CN), Qingdao University of Technology (CN), Oulu University of Applied Sciences (FI), University of Oulu (FI)
Natural Science Foundation of Heilongjiang Province
Reduced inequalities
Openalex Percentile: Top 19%
Biosensors and Analytical Detection
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