Evidence map›Paper›PMID 39727829›Full record

ReviewBiosensors2024

Advances in Surface-Enhanced Raman Spectroscopy for Urinary Metabolite Analysis: Exploiting Noble Metal Nanohybrids.

Ningbin Zhao, Peizheng Shi, Zengxian Wang, Zhuang Sun, Kaiqiang Sun, Chen Ye, Li Fu, Cheng-Te Lin

Abstract readReview
In one paragraph

Review in Biosensors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

8 authors.

Ningbin ZhaoFaculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, China.
Peizheng ShiQianwan Institute, Ningbo Institute of Materials Technology and Engineering (NIMTE), Chinese Academy of Sciences, Ningbo 315201, China.
Zengxian WangTaiyuan Municipal Construction Group Co., Ltd., Taiyuan 030002, China.
Zhuang SunQianwan Institute, Ningbo Institute of Materials Technology and Engineering (NIMTE), Chinese Academy of Sciences, Ningbo 315201, China.
Kaiqiang SunQianwan Institute, Ningbo Institute of Materials Technology and Engineering (NIMTE), Chinese Academy of Sciences, Ningbo 315201, China.
Chen YeQianwan Institute, Ningbo Institute of Materials Technology and Engineering (NIMTE), Chinese Academy of Sciences, Ningbo 315201, China.
Li FuCollege of Materials and Environmental Engineering, Hangzhou Dianzi University, Hangzhou 310018, China.ORCID 0000-0002-5957-7790
Cheng-Te LinKey Laboratory of Marine Materials and Related Technologies, Zhejiang Key Laboratory of Marine Materials and Protective Technologies, Ningbo Institute of Materials Technology and Engineering (NIMTE), Chinese Academy of Sciences, Ningbo 315201, China.ORCID 0000-0002-7090-9610

Funding

CAS Youth Innovation Promotion Association 2020301China Postdoctoral Science Foundation 2022M713243Ningbo 3315 Innovation Team 2019A-18-CNingbo Key Scientific and Technological Project 2021Z120, 2021Z115, 2022Z084, 2022Z191Science and Technology Major Project of Ningbo 2021ZDYF020196, 2021ZDYF020198The authors are grateful for the financial support by the National Key R&D Program of China 2022YFA1203100the National Natural Science Foundation of China 52272053, 52102055, 52302120the Project of Chinese Academy of Science ZDKYYQ2020001the Yongjiang Talent Introduction Programme of Ningbo 2021A-037-C, 2021A-108-Gthe Youth Fund of Chinese Academy of Sciences JCPYJ-22030
6 · The paper itself

Abstract

This review examines recent advances in surface-enhanced Raman spectroscopy (SERS) for urinary metabolite analysis, focusing on the development and application of noble metal nanohybrids. We explore the diverse range of hybrid materials, including carbon-based, metal-organic-framework (MOF), silicon-based, semiconductor, and polymer-based systems, which have significantly improved SERS performance for detecting key urinary biomarkers. The principles underlying SERS enhancement in these nanohybrids are discussed, elucidating both electromagnetic and chemical enhancement mechanisms. We analyze various fabrication methods that enable precise control over nanostructure morphology, composition, and surface chemistry. The review critically evaluates the analytical performance of different hybrid systems for detecting specific urinary metabolites, considering factors such as sensitivity, selectivity, and stability. We address the analytical challenges associated with SERS-based urinary metabolite analysis, including sample preparation, matrix effects, and data interpretation. Innovative solutions, such as the integration of SERS with microfluidic devices and the application of machine learning algorithms for spectral analysis, are highlighted. The potential of these advanced SERS platforms for point-of-care diagnostics and personalized medicine is discussed, along with future perspectives on wearable SERS sensors and multi-modal analysis techniques. This comprehensive overview provides insights into the current state and future directions of SERS technology for urinary metabolite detection, emphasizing its potential to revolutionize non-invasive health monitoring and disease diagnosis.

Indexed as

Spectrum Analysis, RamanBiomarkersBiosensing TechniquesHumansMetal NanoparticlesNanostructuresBiomarkersbiomarker detectionmolecular fingerprintingplasmonic nanostructurespoint-of-care diagnosticsspectroscopic sensing

Identifiers

PMID39727829
PMCPMC11674540

What OpenQuestion holds

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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.