Biocompatible Nanoparticles with Aggregation-Induced Emission Characteristics as Far-Red/Near-Infrared Fluorescent Bioprobes for In Vitro and In Vivo Imaging Applications

2011 ◽  
Vol 22 (4) ◽  
pp. 771-779 ◽  
Author(s):  
Wei Qin ◽  
Dan Ding ◽  
Jianzhao Liu ◽  
Wang Zhang Yuan ◽  
Yong Hu ◽  
...  
The Analyst ◽  
2019 ◽  
Vol 144 (21) ◽  
pp. 6262-6269 ◽  
Author(s):  
Meng Zhao ◽  
Yinjia Gao ◽  
Shuyue Ye ◽  
Jianan Ding ◽  
Anna Wang ◽  
...  

A new light-up near-infrared probe with aggregation-induced emission (AIE) characteristics was developed for highly specific and sensitive detection of alkaline phosphatase both in vitro and in vivo.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Hongwei Zhao ◽  
Hasaan Hayat ◽  
Xiaohong Ma ◽  
Daguang Fan ◽  
Ping Wang ◽  
...  

Abstract Artificial Intelligence (AI) algorithms including deep learning have recently demonstrated remarkable progress in image-recognition tasks. Here, we utilized AI for monitoring the expression of underglycosylated mucin 1 (uMUC1) tumor antigen, a biomarker for ovarian cancer progression and response to therapy, using contrast-enhanced in vivo imaging. This was done using a dual-modal (magnetic resonance and near infrared optical imaging) uMUC1-specific probe (termed MN-EPPT) consisted of iron-oxide magnetic nanoparticles (MN) conjugated to a uMUC1-specific peptide (EPPT) and labeled with a near-infrared fluorescent dye, Cy5.5. In vitro studies performed in uMUC1-expressing human ovarian cancer cell line SKOV3/Luc and control uMUC1low ES-2 cells showed preferential uptake on the probe by the high expressor (n = 3, p < .05). A decrease in MN-EPPT uptake by SKOV3/Luc cells in vitro due to uMUC1 downregulation after docetaxel therapy was paralleled by in vivo imaging studies that showed a reduction in probe accumulation in the docetaxel treated group (n = 5, p < .05). The imaging data were analyzed using deep learning-enabled segmentation and quantification of the tumor region of interest (ROI) from raw input MRI sequences by applying AI algorithms including a blend of Convolutional Neural Networks (CNN) and Fully Connected Neural Networks. We believe that the algorithms used in this study have the potential to improve studying and monitoring cancer progression, amongst other diseases.


2018 ◽  
Vol 30 (39) ◽  
pp. 1802105 ◽  
Author(s):  
Dong Wang ◽  
Michelle M. S. Lee ◽  
Guogang Shan ◽  
Ryan T. K. Kwok ◽  
Jacky W. Y. Lam ◽  
...  

Nanomaterials ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 1360 ◽  
Author(s):  
Asma Khalid ◽  
Romina Norello ◽  
Amanda N. Abraham ◽  
Jean-Philippe Tetienne ◽  
Timothy J. Karle ◽  
...  

Imaging of biological matter by using fluorescent nanoparticles (NPs) is becoming a widespread method for in vitro imaging. However, currently there is no fluorescent NP that satisfies all necessary criteria for short-term in vivo imaging: biocompatibility, biodegradability, photostability, suitable wavelengths of absorbance and fluorescence that differ from tissue auto-fluorescence, and near infrared (NIR) emission. In this paper, we report on the photoluminescent properties of magnesium oxide (MgO) NPs that meet all these criteria. The optical defects, attributed to vanadium and chromium ion substitutional defects, emitting in the NIR, are observed at room temperature in NPs of commercial and in-house ball-milled MgO nanoparticles, respectively. As such, the NPs have been successfully integrated into cultured cells and photostable bright in vitro emission from NPs was recorded and analyzed. We expect that numerous biotechnological and medical applications will emerge as this nanomaterial satisfies all criteria for short-term in vivo imaging.


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