Evidence map›Paper›PMID 41654595›Full record

ArticleMikrochimica acta2026

SERS monitoring of biothiols in serum based on thiol-alkyne click reaction.

Haomiao Dou, Danni Luo, Lingge Shi, Feiyan Ma, Yunbo Zhao, Tingwei Huang, Jingshu Yang, Jingwen Ma, Guangda Xu, Longshan Zhao

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Article in Mikrochimica acta, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Haomiao DouSchool of Pharmacy, Shenyang Pharmaceutical University, Shenyang, 110016, China.
Danni LuoSchool of Pharmacy, Shenyang Pharmaceutical University, Shenyang, 110016, China.
Lingge ShiSchool of Pharmacy, Shenyang Pharmaceutical University, Shenyang, 110016, China.
Feiyan MaSchool of Pharmacy, Shenyang Pharmaceutical University, Shenyang, 110016, China.
Yunbo ZhaoSchool of Pharmacy, Shenyang Pharmaceutical University, Shenyang, 110016, China.
Tingwei HuangSchool of Pharmaceutical Engineering, Shenyang Pharmaceutical University, Shenyang, 110016, China.
Jingshu YangSchool of Pharmaceutical Engineering, Shenyang Pharmaceutical University, Shenyang, 110016, China.
Jingwen MaSchool of Pharmaceutical Engineering, Shenyang Pharmaceutical University, Shenyang, 110016, China.
Guangda XuSchool of Pharmacy, Shenyang Pharmaceutical University, Shenyang, 110016, China. xuguangda@syphu.edu.cn.
Longshan ZhaoSchool of Pharmacy, Shenyang Pharmaceutical University, Shenyang, 110016, China. longshanzhao@163.com.

Funding

Basic Scientific Research Project of Liaoning Provincial Department of Education LJ212510163019Basic Scientific Research Project Youth project of Liaoning Provincial Department of Education JYTQN2023331College Students' Innovation and Entrepreneurship Training Program of Shenyang Pharmaceutical University X202410163282Doctoral Startup Research Program of Liaoning Provincial Natural Science Foundation 2025-BS-0752Liaoning Provincial Natural Science Foundation of China 2024-MS-088Middle-aged Backbone Personnel Training Program of Shenyang Pharmaceutical University ZQN2016011Youqing lift Program of Shenyang Pharmaceutical University YQ202206
6 · The paper itself

Abstract

A novel surface-enhanced Raman scattering (SERS) sensing strategy based on thiol-yne click reactions for highly sensitive and selective detection of biothiols in serum has been developed. By combining gold-core silver-shell nanoparticles (Ag@AuNPs) with 1,4-diethynylbenzene (DTBN) and immobilizing them in an agarose hydrogel matrix, a flexible SERS sensor was constructed. The alkyne group (C ≡ C) of DTBN generated a strong characteristic signal in the Raman-silent region (2209 cm⁻1). This group underwent a click reaction with the thiol (-SH) group of biothiols under a photoinitiator, leading to a proportional attenuation of the SERS signal intensity with increasing thiol concentration. Experimental results demonstrated a linear detection range for Cys from 1 × 10⁻5 to 1 × 10⁻10 M, with a detection limit as low as 16 pM, surpassing traditional methods. Additionally, the three-dimensional network structure of the hydrogel matrix effectively shielded interference from serum components, and recoveries of 93.4%–113.3% confirmed its applicability in complex biological samples. The prepared Ag@AuNPs@DTBN hydrogel chip exhibited excellent stability and reproducibility, providing a new approach for rapid clinical monitoring of biothiols. This advancement holds promise for early warning and therapeutic evaluation of cardiovascular and neurodegenerative diseases.

Indexed as

AlkynesCysteineSpectrum Analysis, RamanSulfhydryl CompoundsClick ChemistryGoldHumansHydrogelsLimit of DetectionMetal NanoparticlesSilverAlkynesCysteineGoldHydrogelsSilverSulfhydryl CompoundsBiothiolsSERS hydrogel chip; Gold-core silver-shell nanoparticlesThiol-yne click reaction

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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.