Early Diagnosis and Prognosis Prediction of Pancreatic Cancer Using Engineered Hybrid Core‐Shells in Laser Desorption/Ionization Mass Spectrometry

Zhang, Juxiang; Teng, Fei; Hu, Beiyuan; Liu, Wanshan; Huang, Yida; Wu, Jiao; Wang, Yuning; Su, Haiyang; Yang, Shouzhi; Zhang, Lumin; Guo, Lingchuan; Lei, Zhe; Yan, Meng; Xu, Xiaoyu; Wang, Ruimin; Bao, Qingui; Dong, Qiongzhu; Long, Jiang; Qian, Kun

doi:10.1002/adma.202311431

Cited by 3 publications

(1 citation statement)

References 80 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The adhesion of a silicon layer keeps the gold nanomaterial stable. Furthermore, methods for coating nanoparticles with SiO 2 are well established, and methods for the coating of precious metals, semiconductors, and magnetic nanoparticles have been reported [18][19][20][21][22]. SiO 2 shells can improve the stability of gold nanorods and inhibit their degradation in harsh thermochemical environments.…”

Section: Introductionmentioning

confidence: 99%

Surface-Enhanced Raman Scattering for Probe Detection via Gold Nanorods and AuNRs@SiO2 Composites

Li,

Tian,

Yan

et al. 2024

Coatings

View full text Add to dashboard Cite

In this paper, a self-assembly method was used to prepare gold nanorod composites, and a seed-growth method was used to adjust the amount of AgNO3 solution, enabling the preparation of gold nanorods with different aspect ratios. AuNRs@SiO2 nanocomposite particles were then prepared by using the Stöber method to coat the gold nanorod surface with silica. Transmission electron microscopy showed that the maximum aspect ratio of the gold nanorods was 4.53, which was achieved using 2 mL of 10 mM AgNO3 solution. The Raman-scattering intensity of the gold nanorods was studied using rhodamine 6G, thiram, melamine, and piroxicam, and detection limits of 10−8 M, 10−5 M, and 10−3 M were, respectively, achieved. As a substrate, these gold nanorods showed good repeatability and reproducibility, and trace detection was successfully achieved. A transmission electron microscopy analysis shows that the SiO2 shell became thicker with increasing tetraethyl orthosilicate addition. Using AuNRs@SiO2 as the base and R6G, thiram, and piroxicam as the probes, measurable detection limits of 10−9 M, 10−6 M, and 10−5 M were achieved, and this composite also showed excellent repeatability and reproducibility.

show abstract

Section: Introductionmentioning

confidence: 99%

Surface-Enhanced Raman Scattering for Probe Detection via Gold Nanorods and AuNRs@SiO2 Composites

Li,

Tian,

Yan

et al. 2024

Coatings

View full text Add to dashboard Cite

show abstract

Serum and Urine Metabolic Fingerprints Characterize Renal Cell Carcinoma for Classification, Early Diagnosis, and Prognosis

Xu,

Fang,

Wang

et al. 2024

Advanced Science

View full text Add to dashboard Cite

Renal cell carcinoma (RCC) is a substantial pathology of the urinary system with a growing prevalence rate. However, current clinical methods have limitations for managing RCC due to the heterogeneity manifestations of the disease. Metabolic analyses are regarded as a preferred noninvasive approach in clinics, which can substantially benefit the characterization of RCC. This study constructs a nanoparticle‐enhanced laser desorption ionization mass spectrometry (NELDI MS) to analyze metabolic fingerprints of renal tumors (n = 456) and healthy controls (n = 200). The classification models yielded the areas under curves (AUC) of 0.938 (95% confidence interval (CI), 0.884–0.967) for distinguishing renal tumors from healthy controls, 0.850 for differentiating malignant from benign tumors (95% CI, 0.821–0.915), and 0.925–0.932 for classifying subtypes of RCC (95% CI, 0.821–0.915). For the early stage of RCC subtypes, the averaged diagnostic sensitivity of 90.5% and specificity of 91.3% in the test set is achieved. Metabolic biomarkers are identified as the potential indicator for subtype diagnosis (p < 0.05). To validate the prognostic performance, a predictive model for RCC participants and achieve the prediction of disease (p = 0.003) is constructed. The study provides a promising prospect for applying metabolic analytical tools for RCC characterization.

show abstract

Noble Metal Nanoparticle Assisted Mass Spectrometry for Metabolite‐Based In Vitro Diagnostics

Liu,

Yang,

et al. 2024

Small

View full text Add to dashboard Cite

In vitro diagnostics (IVD) makes clinical diagnosis rapid, simple, and noninvasive to patients, playing a crucial role in the early diagnosis and monitoring of diseases. Metabolic biomarkers are closely correlated to the phenotype of diseases. However, most IVD platforms are constrained by the sensitivity and throughput of assay. In recent years, noble‐metal‐nanoparticle (NMNP)‐assisted laser desorption/ionization mass spectrometry (LDI MS) has generated major advances in metabolite analysis, significantly improving the sensitivity, accuracy, and throughput of IVD due to the unique optical and electrical properties of NMNPs. This review systematically assesses the development of NMNPs as LDI MS matrices in the detection of metabolites for IVD application. The analysis of several NMNP structures, such as core–shell, porous, and 2D nanoparticles, elucidates their significant contribution to the enhancement of MS performance. Furthermore, the recent advancements in the application of NMNPs for diagnosing various systemic diseases are summarized. Finally, the prospects and challenges of NMNP‐assisted MS for IVD are discussed. This review elucidates the roles of NMNPs' structure in enhancing MS‐based metabolic detection and provides an overview of various IVD applications, consequently offering comprehensive insights for researchers and developers in this field.

show abstract

Early Diagnosis and Prognosis Prediction of Pancreatic Cancer Using Engineered Hybrid Core‐Shells in Laser Desorption/Ionization Mass Spectrometry

Cited by 3 publications

References 80 publications

Surface-Enhanced Raman Scattering for Probe Detection via Gold Nanorods and AuNRs@SiO2 Composites

Surface-Enhanced Raman Scattering for Probe Detection via Gold Nanorods and AuNRs@SiO2 Composites

Serum and Urine Metabolic Fingerprints Characterize Renal Cell Carcinoma for Classification, Early Diagnosis, and Prognosis

Noble Metal Nanoparticle Assisted Mass Spectrometry for Metabolite‐Based In Vitro Diagnostics

Contact Info

Product

Resources

About