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使用NaYbF:Yb,Er纳米颗粒通过光致发光增强红细胞可视化

Enhanced Visualization of Erythrocytes Through Photoluminescence Using NaYbF:Yb,Er Nanoparticles.

作者信息

Torres-Vera Vivian, Coronado Lorena M, Valencia Ana Patricia, Von Chong Alejandro, Rua Esteban, Ng Michelle, Rubio-Retama Jorge, Spadafora Carmenza, Correa Ricardo

机构信息

Biomedical Physics and Engineering Unit, Center of Cellular and Molecular Biology of Diseases (CBCMe), Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), Panama City 1843-01103, Panama.

Department of Chemistry in Pharmaceutical Sciences, Faculty of Pharmacy, Complutense University of Madrid, Plaza Ramon y Cajal 2, 28040 Madrid, Spain.

出版信息

Biosensors (Basel). 2025 Jun 20;15(7):396. doi: 10.3390/bios15070396.

Abstract

Rare-earth nanoparticles (RE-NPs), particularly NaYF:Yb,Er, have emerged as a promising class of photoluminescent probes for bioimaging and sensing applications. These nanomaterials are characterized by their ability to absorb low-energy photons and emit higher-energy photons through an upconversion luminescence process. This process can be triggered by continuous-wave (CW) light excitation, providing a unique optical feature that is not exhibited by native biomolecules. However, the application of upconversion nanoparticles (UCNPs) in bioimaging requires systematic optimization to maximize the signal and ensure biological compatibility. In this work, we synthesized hexagonal-phase UCNPs (average diameter: 29 ± 3 nm) coated with polyacrylic acid (PAA) and established the optimal conditions for imaging human erythrocytes. The best results were obtained after a 4-h incubation in 100 mM HEPES buffer, using a nanoparticle concentration of 0.01 mg/mL and a laser current intensity of 250-300 mA. Under these conditions, the UCNPs exhibited minimal cytotoxicity and were found to predominantly localize at the erythrocyte membrane periphery, indicating surface adsorption rather than internalization. Additionally, a machine learning model (Random Forest) was implemented that classified the photoluminescent signal with 80% accuracy and 83% precision, with the signal intensity identified as the most relevant feature. This study establishes a quantitative and validated protocol that balances signal strength with cell integrity, enabling robust and automated image analysis.

摘要

稀土纳米颗粒(RE-NPs),特别是NaYF:Yb,Er,已成为一类有前途的用于生物成像和传感应用的光致发光探针。这些纳米材料的特点是能够吸收低能量光子,并通过上转换发光过程发射更高能量的光子。这个过程可以由连续波(CW)光激发触发,提供了一种天然生物分子所不具备的独特光学特性。然而,上转换纳米颗粒(UCNPs)在生物成像中的应用需要系统优化,以最大化信号并确保生物相容性。在这项工作中,我们合成了涂覆有聚丙烯酸(PAA)的六方相UCNPs(平均直径:29±3nm),并确定了对人类红细胞成像的最佳条件。在100mM HEPES缓冲液中孵育4小时后,使用0.01mg/mL的纳米颗粒浓度和250 - 300mA的激光电流强度,获得了最佳结果。在这些条件下,UCNPs表现出最小的细胞毒性,并且发现它们主要定位在红细胞膜周边,表明是表面吸附而非内化。此外,实施了一个机器学习模型(随机森林),该模型对光致发光信号的分类准确率为80%,精确率为83%,信号强度被确定为最相关的特征。这项研究建立了一个定量且经过验证的方案,该方案在信号强度与细胞完整性之间取得平衡,实现了强大且自动化的图像分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99dc/12292841/519dfe1f649a/biosensors-15-00396-g001.jpg

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