Chem
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2025
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IF 19.6
Xinyuan Bi,Xiaohang Qian,Bingsen Xue,Miao Zhang,Shuyu Liu,Haoran Chen,Cheng Jin,Huidong Tang,Jian Ye
Multiplexed detection is a challenging yet essential task in analytical chemistry, especially for complex systems. Surface-enhanced Raman spectroscopy (SERS) is a promising analytical tool due to its molecular fingerprinting capability, sensitivity, low cost, and tractability. Considering the molecular profusion and diversity, SERSome, namely, spectral set, facilitates robust detection but is still challenged by spectral overlapping-induced uncertainty of molecular assignment and multiplexed quantification. Herein, we introduce molecule-resolvable (MORE) SERSome, identifying specific analytes contributing to the complex SERS spectra, which are then used in spectral decomposition for multiplexed analysis. Taking metabolic profiling for Alzheimer’s disease as a proof of concept, ten metabolites are screened in human serum. A deep-learning model enables accurate and rapid diagnosis, achieving an area under the receiver operating characteristic curve as high as 91.5%. Comparing with conventional methods, MORE SERSome presents a methodological advancement in multiplexed detection with strong potential for general applications and fundamental research in analytical chemistry.
研究领域:
分析化学
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生物医学工程
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疾病诊断
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产品关联
DOI
高影响因子
TALANTA
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2025
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IF 6.1
Shuang Jiang,Yue Zhao,Qingyu Meng,Rongheng Ma,Xiaomeng Sun,Xiaoming Lyu,Li Zhang,Guangrun Wu,Xiaotong Wang,Yiyang He,Jiayue Liang,Yuxin Qiao,Zhibin Wang,Yanli Wu,Jing Wu,Chunjuan Yang,Huimin Yu,Yang Li
Medicinal and edible homologs (MEHs) offer significant preventive and therapeutic benefits for various diseases and health functions. However, the widespread application of MEHs faces significant challenges, particularly in quality control, rapid identification, and authentication. In this study, we present a novel approach that combines surface-enhanced Raman spectroscopy (SERS) based on spectral set, referred to as “SERSome”, with deep learning to develop an identification model for analyzing MEHs. The platform uses silver nanoparticles prepared via reduction with NaBH 4 , activation with sodium borohydride, and aggregation with calcium ions. The method avoids the use of additional protective agents during the reaction process, thereby reducing interference from the protective agents and other materials. Additionally, the method also overcomes the fluorescence interference from MEHs. SERSomes provide comprehensive molecular fingerprint recognition, significantly enhancing the system's detection accuracy. The introduction of Ca 2+ as aggregator promotes the aggregation of silver nanoparticle, significantly enhancing the electromagnetic field of the nanoparticle system. The study achieves up to 98% accuracy in identifying specific MEHs. The integration of SERSomes with deep learning offers a promising methodology for the rapid and modern detection of MEHs, advancing the MEHs industry and contributing to the protection of human health.
研究领域:
分析化学
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生物医学
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人工智能
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食品科学
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DOI
PubMed
高影响因子
Stem Cell Research & Therapy
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2024
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IF 7.1
Xinyuan Bi,Bin Ma,Wei Liu,Wei-Qiang Gao,Jian Ye,Hanyu Rao
Background Mesenchymal stem cells (MSCs) are widely applied in the treatment of various clinical diseases and in the field of medical aesthetics. However, MSCs exhibit greater heterogeneity limited stability, and more complex molecular and mechanistic characteristics compared to conventional drugs, making rapid and precise monitoring more challenging. Methods Surface-enhanced Raman spectroscopy (SERS) is an ultrasensitive, tractable and low-cost fingerprinting technique capable of identifying a wide range of molecules related to biological processes. Here, we employed SERS for reproducible quantification of ultralow concentrations of molecules and utilized spectral sets, termed SERSomes, for robust and comprehensive intracellular multi-metabolite profiling. Results We revealed that with increasing passage number, there is a gradual decline in cell expansion efficiency, accompanied by significant changes in intracellular amino acids, purines, and pyrimidines. By integrating these metabolic features detected by SERS with transcriptomic data, we established a correlation between SERS signals and biological changes, as well as differentially expressed genes. Conclusion In this study, we explore the application of SERS technique to provide robust metabolic characteristics of MSCs across different passages and donors. These results demonstrate the effectiveness of SERSome in reflecting biological characteristics. Due to its sensitivity, adaptability, low cost, and feasibility for miniaturized instrumentation throughout pretreatment, measurement, and analysis, the label-free SERSome technique is suitable for monitoring MSC expansion and offers significant advantages for large-scale MSC manufacturing. Supplementary Information The online version contains supplementary material available at 10.1186/s13287-024-04109-0.
研究领域:
生物医学
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分子生物学
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分析化学
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产品关联
DOI
PubMed
高影响因子
ACS Nano
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2025
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IF 16
Yao Yao,Yue Zhao,Huijuan Zhang,Wenting Pan,Wei Liang,Yijian Jiang,Xinlong Yan,Yinzhou Yan
The development of surface-enhanced Raman spectroscopy (SERS) as an ultrasensitive fingerprint analysis technique in precision medicine requires high-performance SERS substrates with controllable nanostructure (hot-spot) distribution, simple fabrication, superior stability, biocompatibility, and extraordinary optical responses. Unfortunately, fabrication of arbitrary nanostructures with high homogeneity on a large scale for SERS is still challenging. Herein, we report an ultrafast laser parallel fabrication protocol for Au/2D-transition-metal dichalcogenide hybrid SERS biosensors. The leveraged photonic nanojets (PNJs) are generated by a micron-sized microsphere monolayer to simultaneously trigger localized phase transition in 2H-MoTe2, achieving a 1T′-MoTe2 nanopattern array with a density of 1 million per mm2 by a single laser shot. The Au nanoparticle clusters (AuNCs) are subsequently grown in situ from the 1T′ regions, creating a AuNCs on 1T′/2H-MoTe2 (AuNCs@1T’/2H-MoTe2) hybrid SERS substrate. The fabricated feature diameter and overlay accuracy of the patterned AuNCs are 210.1 ± 3.4 and 9.2 ± 1.7 nm, respectively. To eliminate background noise, we designed dimer-AuNCs@1T′/2H-MoTe2 (dAuNCs@1T′/2H-MoTe2), achieving a detection limit of 10–13 M with an enhancement factor of 4.9 × 108 for the methylene blue (MB) analyte. The strong localized surface plasmon resonances in the dAuNCs as well as efficient charge transfers between Au, 2H-MoTe2, and MB contribute to the majority of Raman enhancement. The multiscale dAuNCs@1T′/2H-MoTe2 array provides a powerful SERSome (comprising multiple SERS spectra) platform for therapeutic drug monitoring, by which we successfully identified the metabolic behaviors of living gastric adenocarcinoma cells administered with two drugs, i.e., capecitabine, oxaliplatin, and their combination. The present work establishes opportunities for creating a highly ordered nanopattern array for ultrasensitive SERSome analysis of cell metabolism in cancer therapy.
研究领域:
纳米技术
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生物医学工程
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分析化学
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癌症研究
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材料科学
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光学与光子学
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精准医学
✓ 已验证
产品关联
DOI
PubMed
高影响因子
危险品化学品经营许可证（带存储）