Evidence map›Paper›PMID 39064915›Full record

ReviewMolecules (Basel, Switzerland)2024

Surface-Enhanced Raman Spectroscopy (SERS)-Based Sensors for Deoxyribonucleic Acid (DNA) Detection.

Shireen Zangana, Miklós Veres, Attila Bonyár

Abstract readReview
In one paragraph

Review in Molecules (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Shireen ZanganaDepartment of Electronics Technology, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, 1111 Budapest, Hungary.
Miklós VeresHUN-REN Wigner Research Centre for Physics, 1525 Budapest, Hungary.
Attila BonyárDepartment of Electronics Technology, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, 1111 Budapest, Hungary.

Funding

National Research, Development and Innovation Office 2022-2.1.1-NL-2022-00002
6 · The paper itself

Abstract

Surface-enhanced Raman spectroscopy (SERS) has emerged as a powerful technique for the detection and analysis of biomolecules due to its high sensitivity and selectivity. In recent years, SERS-based sensors have received significant attention for the detection of deoxyribonucleic acid (DNA) molecules, offering promising applications in fields such as medical diagnostics, forensic analysis, and environmental monitoring. This paper provides a concise overview of the principles, advancements, and potential of SERS-based sensors for DNA detection. First, the fundamental principles of SERS are introduced, highlighting its ability to enhance the Raman scattering signal by several orders of magnitude through the interaction between target molecules with metallic nanostructures. Then, the fabrication technologies of SERS substrates tailored for DNA detection are reviewed. The performances of SERS substrates previously reported for DNA detection are compared and analyzed in terms of the limit of detection (LOD) and enhancement factor (EF) in detail, with respect to the technical parameters of Raman spectroscopy (e.g., laser wavelength and power). Additionally, strategies for functionalizing the sensor surfaces with DNA-specific capture probes or aptamers are outlined. The collected data can be of help in selecting and optimizing the most suitable fabrication technology considering nucleotide sensing applications with Raman spectroscopy.

Indexed as

Biosensing TechniquesDNASpectrum Analysis, RamanHumansLimit of DetectionMetal NanoparticlesDNADNA detectionenhancement factorRaman spectroscopySERSsurface-enhanced Raman spectroscopy

Identifiers

PMID39064915
PMCPMC11279622

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Registered trials

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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.