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Recent progress in plasmonic nanoparticle-based biomarker detection and cytometry for the study of central nervous system disorders
Cytometry Part A ( IF 2.5 ) Pub Date : 2021-07-30 , DOI: 10.1002/cyto.a.24489
Fei Peng 1 , Sinyoung Jeong 1 , Alexander Ho 1 , Conor L Evans 1
Affiliation  

Neurological disorders affect hundreds of millions of people around the world, are often life-threatening, untreatable, and can result in debilitating symptoms. The high prevalence of these disorders, which feature biochemical or structural abnormalities in neuronal systems, has spurned innovations in both rapid and early detection to assist in the selection of appropriate treatment strategies to improve the patients' quality of life. Plasmonic nanoparticles (PNPs), a versatile and promising class of nanomaterials, are widely utilized in numerous imaging techniques, drug delivery systems, and biomarker detection methods. Recently, PNP-based nanoprobes have attracted considerable attention for the early diagnosis of neurological disorders. Gold nanoparticles (AuNPs), with high local surface plasmon resonance (LSPR) signals, have been particularly well exploited as probes for dynamic biomarker detection, with quantification sensitivity demonstrated down to the single-molecule level. In this review, we will discuss the possibilities of PNPs in the methodological development for rapid neurological disease identification. In addition, we will also describe a new digital cytometry method that combines dark-field imaging and machine learning for precise biomarker enumeration on single cells. The aim of this review is to attract researchers working on the future development of new plasmonic nanoprobe-based strategies for the diagnosis of neurological disorders.

中文翻译:

基于等离子体纳米颗粒的生物标志物检测和细胞计数在中枢神经系统疾病研究中的最新进展

神经系统疾病影响着全世界数亿人,通常会危及生命,无法治愈,并可能导致虚弱的症状。这些以神经元系统生化或结构异常为特征的疾病的高患病率,已经摒弃了快速和早期检测方面的创新,以帮助选择适当的治疗策略来改善患者的生活质量。等离子纳米粒子 (PNP) 是一类用途广泛且前景广阔的纳米材料,广泛用于众多成像技术、药物输送系统和生物标志物检测方法。最近,基于 PNP 的纳米探针在神经系统疾病的早期诊断方面引起了相当大的关注。金纳米粒子 (AuNPs),具有高局部表面等离子体共振 (LSPR) 信号,已被特别充分地用作动态生物标志物检测的探针,其量化灵敏度已证明低至单分子水平。在这篇综述中,我们将讨论 PNPs 在快速神经系统疾病识别的方法学开发中的可能性。此外,我们还将介绍一种新的数字细胞计数方法,该方法结合了暗场成像和机器学习,可对单个细胞进行精确的生物标志物计数。这篇综述的目的是吸引研究人员致力于未来开发基于新等离子体纳米探针的神经系统疾病诊断策略。我们将讨论 PNP 在快速神经系统疾病识别方法学开发中的可能性。此外,我们还将介绍一种新的数字细胞计数方法,该方法结合了暗场成像和机器学习,可对单个细胞进行精确的生物标志物计数。这篇综述的目的是吸引研究人员致力于未来开发基于新等离子体纳米探针的神经系统疾病诊断策略。我们将讨论 PNP 在快速神经系统疾病识别方法学开发中的可能性。此外,我们还将介绍一种新的数字细胞计数方法,该方法结合了暗场成像和机器学习,可对单个细胞进行精确的生物标志物计数。这篇综述的目的是吸引研究人员致力于未来开发基于新等离子体纳米探针的神经系统疾病诊断策略。
更新日期:2021-07-30
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