• Deep learning-assisted SERS pl...

Treffer: Deep learning-assisted SERS platform for label-free detection of celecoxib in serum using ag@Pt@porous silicon Bragg mirror composite substrate.

Title:
Deep learning-assisted SERS platform for label-free detection of celecoxib in serum using ag@Pt@porous silicon Bragg mirror composite substrate.
Authors:
Zhao X; College of Chemical Engineering, Xinjiang University, Urumqi 830046, China., Han S; College of Physical Science and Technology, Xinjiang University, Urumqi 830046, China., Chen C; College of Software, Xinjiang University, Urumqi 830046, China; Red You Software Co., LTD, Karamay 834000,China., Lv X; College of Software, Xinjiang University, Urumqi 830046, China; The Key Laboratory of Signal Detection and Processing, Xinjiang Uygur Autonomous Region, Xinjiang University, Urumqi 840046, China., Li J; College of Software, Xinjiang University, Urumqi 830046, China., Chen C; College of Software, Xinjiang University, Urumqi 830046, China. Electronic address: 1343432873@qq.com.
Source:
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy [Spectrochim Acta A Mol Biomol Spectrosc] 2026 Mar 05; Vol. 348 (Pt 1), pp. 127165. Date of Electronic Publication: 2025 Nov 10.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Elsevier Country of Publication: England NLM ID: 9602533 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-3557 (Electronic) Linking ISSN: 13861425 NLM ISO Abbreviation: Spectrochim Acta A Mol Biomol Spectrosc Subsets: MEDLINE
Imprint Name(s):
Publication: : Amsterdam : Elsevier
Original Publication: [Kidlington, Oxford, U.K. ; Tarrytown, NY] : Pergamon, c1994-
MeSH Terms:
Celecoxib*/blood , Spectrum Analysis, Raman*/methods , Silver*/chemistry , Silicon*/chemistry , Platinum*/chemistry , Deep Learning*, Porosity ; Humans ; Limit of Detection ; Reproducibility of Results
Contributed Indexing:
Keywords: Celecoxib; Deep learning; Porous silicon Bragg mirror; SERS; Serum; TDM
Substance Nomenclature:
JCX84Q7J1L (Celecoxib)
3M4G523W1G (Silver)
Z4152N8IUI (Silicon)
49DFR088MY (Platinum)
Entry Date(s):
Date Created: 20251116 Date Completed: 20251212 Latest Revision: 20251212
Update Code:
20260130
DOI:
10.1016/j.saa.2025.127165
PMID:
41242102
Database:
MEDLINE

Weitere Informationen

Celecoxib (CXB) is a non-steroidal anti-inflammatory drug used to prevent and treat arthritis. However, overdosing or improper use can cause adverse reactions. SERS is an important tool for therapeutic drug monitoring (TDM).The present study proposes an innovative detection scheme based on SERS deep learning, aiming to achieve qualitative identification and quantitative detection of CXB at the Raman spectrum level. In this paper, a composite SERS substrate consisting of silver (Ag)@ platinum (Pt)@ porous silicon Bragg mirror (PSB) was synthesized. Crystal violet (CV) was used as probe to characterize the substrate properties, and the substrate showed excellent SERS properties and long-term stability. The substrate significantly enhanced the SERS response capacity to CXB, showing excellent reproducibility and high sensitivity. The LOD and the recovery rate were both within the reasonable range when the substrate was used to detect CXB concentration in serum. Three deep learning models, GoogleNet, ResNet and VGG, were used to classify five kinds of blood drug concentrations. Among them, the GoogleNet model based on spectral dataset achieved the highest classification accuracy of 84.17 %. The deep learning-SERS integrated system supports blood drug concentration discrimination, helping doctors personalize treatment strategies for arthritis patients and improving clinical efficiency.
(Copyright © 2025 Elsevier B.V. All rights reserved.)

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.