Use of a Ferritin L134P Mutant for the Facile Conjugation of Prussian Blue in the Apoferritin Cavity

2021 ◽  
Vol 60 (7) ◽  
pp. 4693-4704
Author(s):  
Yuta Ikenoue ◽  
Yuhei O. Tahara ◽  
Makoto Miyata ◽  
Takanori Nishioka ◽  
Shigetoshi Aono ◽  
...  
Keyword(s):  
RSC Advances ◽  
2015 ◽  
Vol 5 (61) ◽  
pp. 49671-49679 ◽  
Author(s):  
Prem. C. Pandey ◽  
Richa Singh ◽  
Yashashwa Pandey

A facile method for the synthesis of functional AgNPs and bimetallic Ag–Au/Au–Ag are reported, enabling the formation of nanocomposite with prussian blue in a crystalline framework for bioanalytical applications, showing the active role of organic reducing agents and 3-aminopropyltrimethoxysilane.


Biosensors ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 157
Author(s):  
Bárbara V. M. Silva ◽  
Marli T. Cordeiro ◽  
Marco A. B. Rodrigues ◽  
Ernesto T. A. Marques ◽  
Rosa F. Dutra

Zika virus (ZIKV) is a mosquito-borne infection, predominant in tropical and subtropical regions causing international concern due to the ZIKV disease having been associated with congenital disabilities, especially microcephaly and other congenital abnormalities in the fetus and newborns. Development of strategies that minimize the devastating impact by monitoring and preventing ZIKV transmission through sexual intercourse, especially in pregnant women, since no vaccine is yet available for the prevention or treatment, is critically important. ZIKV infection is generally asymptomatic and cross-reactivity with dengue virus (DENV) is a global concern. An innovative screen-printed electrode (SPE) was developed for amperometric detection of the non-structural protein (NS2B) of ZIKV by exploring the intrinsic redox catalytic activity of Prussian blue (PB), incorporated into a carbon nanotube–polypyrrole composite. Thus, this immunosensor has the advantage of electrochemical detection without adding any redox-probe solution (probe-less detection), allowing a point-of-care diagnosis. It was responsive to serum samples of only ZIKV positive patients and non-responsive to negative ZIKV patients, even if the sample was DENV positive, indicating a possible differential diagnosis between them by NS2B. All samples used here were confirmed by CDC protocols, and immunosensor responses were also checked in the supernatant of C6/36 and in Vero cell cultures infected with ZIKV.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Christian Crouzet ◽  
Gwangjin Jeong ◽  
Rachel H. Chae ◽  
Krystal T. LoPresti ◽  
Cody E. Dunn ◽  
...  

AbstractCerebral microhemorrhages (CMHs) are associated with cerebrovascular disease, cognitive impairment, and normal aging. One method to study CMHs is to analyze histological sections (5–40 μm) stained with Prussian blue. Currently, users manually and subjectively identify and quantify Prussian blue-stained regions of interest, which is prone to inter-individual variability and can lead to significant delays in data analysis. To improve this labor-intensive process, we developed and compared three digital pathology approaches to identify and quantify CMHs from Prussian blue-stained brain sections: (1) ratiometric analysis of RGB pixel values, (2) phasor analysis of RGB images, and (3) deep learning using a mask region-based convolutional neural network. We applied these approaches to a preclinical mouse model of inflammation-induced CMHs. One-hundred CMHs were imaged using a 20 × objective and RGB color camera. To determine the ground truth, four users independently annotated Prussian blue-labeled CMHs. The deep learning and ratiometric approaches performed better than the phasor analysis approach compared to the ground truth. The deep learning approach had the most precision of the three methods. The ratiometric approach has the most versatility and maintained accuracy, albeit with less precision. Our data suggest that implementing these methods to analyze CMH images can drastically increase the processing speed while maintaining precision and accuracy.


Sign in / Sign up

Export Citation Format

Share Document