A highly sensitive electrochemical aptasensor for vascular endothelial growth factor detection based on toehold-mediated strand displacement reaction

2021 ◽  
Author(s):  
Zhong Gao ◽  
Fangling Ren ◽  
Guangyi Yang ◽  
Guangjun Feng ◽  
Lun Wu ◽  
...  
Keyword(s):  
Vascular Endothelial Growth Factor ◽  
Growth Factor ◽  
High Sensitivity ◽  
Vascular Endothelial ◽  
Electrochemical Aptasensor ◽  
Strand Displacement ◽  
Highly Sensitive ◽  
Recycling Amplification ◽  
Sensitivity Specificity ◽  
Endothelial Growth Factor

An electrochemical aptasensor with high sensitivity, specificity and good intra-day reproducibility is reported to meet the detection needs of vascular endothelial growth factor (VEGF). The toehold-mediated strand displacement recycling amplification...

scholarly journals Fabrication of Zinc Protoporphyrin-Modified Gold Electrode for Sensitive and Fast Detection of Vascular Endothelial Growth Factor

Chemosensors ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 21
Author(s):  
Hung-Yu Lin ◽  
Chin-Cheng Liao ◽  
Mu-Yi Hua
Keyword(s):  
Vascular Endothelial Growth Factor ◽  
Growth Factor ◽  
Gold Electrode ◽  
Near Infrared ◽  
High Sensitivity ◽  
Zinc Protoporphyrin ◽  
Electrochemical Characteristics ◽  
Vascular Endothelial ◽  
Detection Range ◽  
Endothelial Growth Factor

Vascular endothelial growth factor (VEGF) is directly related to cancer growth and its distant spread, and thus, it is considered a promising biomarker for diagnosis and post-treatment monitoring of patients with malignancies. Zinc protoporphyrin (ZnPP) is a zinc-centered raw purple compound (protoporphyrin) that has unique optical and electrochemical characteristics. In this study, we used a ZnPP-modified gold electrode to generate a chemical bond with Avastin by self-assembly and fabricate a Au/ZnPP/Avastin electrode. Bovine serum protein (BSA) was added to the electrode to prevent non-specific linkage with biomolecules. The prepared Au/ZnPP/Avastin/BSA electrodes were used for the detection of VEGF by cyclic voltammetry and amperometry. The optical properties of ZnPP were analyzed with an ultraviolet/visible/near-infrared spectrometer and a photoluminescence spectrometer. The structural and hydrophilic/hydrophobic properties of the ZnPP-modified gold electrodes were investigated by Fourier-transform infrared spectroscopy and contact angle gauge, respectively. VEGF was detected with the Au/ZnPP/Avastin/BSA electrodes prepared either with (w/LT) or without light treatment (w/o LT). The w/LT electrode showed a linear range and a sensitivity of 0.1 pg/mL–10 ng/mL and 6.52 μA/log(pg/mL)-cm2, respectively; the corresponding values for the w/o LT electrode were 10 pg/mL–10 ng/mL and 3.15 μA/log(pg/mL)-cm2, respectively. The w/LT electrode had good specificity for VEGF and was minimally influenced by other molecules. The excellent detection range, high sensitivity, and high selectivity for VEGF detection indicate that Au/ZnPP/Avastin electrodes have great potential for diagnostic and prognostic applications in patients with malignancies.

A highly sensitive photoelectrochemical VEGF165 biosensor with a dual signal amplification strategy by using AgVO3 as a photoactive material

2019 ◽  
Vol 55 (56) ◽  
pp. 8076-8078 ◽  
Author(s):  
Huimei Da ◽  
Yaling Liu ◽  
Mengjie Li ◽  
Ruo Yuan ◽  
Hongyan Liu ◽  
...  
Keyword(s):  
Vascular Endothelial Growth Factor ◽  
Growth Factor ◽  
Signal Amplification ◽  
Sensitive Detection ◽  
Vascular Endothelial ◽  
Background Signal ◽  
Highly Sensitive ◽  
Amplification Strategy ◽  
Dual Signal Amplification ◽  
Endothelial Growth Factor

We developed a novel “signal-on” photoelectrochemical (PEC) aptasensor with a near-zero background signal by using AgVO3 as a single photoactive material for the sensitive detection of vascular endothelial growth factor (VEGF165).

scholarly journals Automated and Reproducible Detection of Vascular Endothelial Growth Factor (VEGF) in Renal Tissue Sections

2019 ◽  
Vol 2019 ◽  
pp. 1-7 ◽  
Author(s):  
Nayana Damiani Macedo ◽  
Aline Rodrigues Buzin ◽  
Isabela Bastos de Araujo ◽  
Breno Valentim Nogueira ◽  
Tadeu Uggere Andrade ◽  
...  
Keyword(s):  
Machine Learning ◽  
Vascular Endothelial Growth Factor ◽  
Image Analysis ◽  
Growth Factor ◽  
Kidney Tissue ◽  
High Sensitivity ◽  
Renal Tissue ◽  
Vascular Endothelial ◽  
Tissue Sections ◽  
Endothelial Growth Factor

Background. Manual analysis of tissue sections, such as for pathological diagnosis, requires an analyst with substantial knowledge and experience. Reproducible image analysis of biological samples is steadily gaining scientific importance. The aim of the present study was to employ image analysis followed by machine learning to identify vascular endothelial growth factor (VEGF) in kidney tissue that had been subjected to hypoxia. Methods. Light microscopy images of renal tissue sections stained for VEGF were analyzed. Subsequently, machine learning classified the cells as VEGF+ and VEGF- cells. Results. VEGF was detected and cells were counted with high sensitivity and specificity. Conclusion. With great clinical, diagnostic, and research potential, automatic image analysis offers a new quantitative capability, thereby adding numerical information to a mostly qualitative diagnostic approach.

Sign in / Sign up

Export Citation Format

Share Document