Zwitterionic Modification of Nanomaterials for Improved Diagnosis of Cancer Cells

2019 ◽  
Vol 30 (10) ◽  
pp. 2519-2527 ◽  
Author(s):  
Zhijuan Xiong ◽  
Mingwu Shen ◽  
Xiangyang Shi
Keyword(s):  
Cancer Cells ◽  
Diagnosis Of Cancer

Tunable and selective detection of cancer cells using a betainized zwitterionic polymer with BODIPY and graphene oxide

2014 ◽  
Vol 38 (6) ◽  
pp. 2225-2228 ◽  
Author(s):  
So Yeong Lee ◽  
Sung Han Kim ◽  
Sung Min Kim ◽  
Hyukjin Lee ◽  
Gibaek Lee ◽  
...  
Keyword(s):  
Graphene Oxide ◽  
Cancer Cells ◽  
Reduced Graphene Oxide ◽  
Fluorescence Probes ◽  
Fluorescent Nanoparticles ◽  
Selective Detection ◽  
Reduced Graphene ◽  
Diagnosis Of Cancer ◽  
Zwitterionic Polymer ◽  
Effective Diagnosis

Novel fluorescence probes, reduced graphene oxide (rGO) containing zwitterionic fluorescent nanoparticles, for effective diagnosis of cancer cells.

Application of the Blending of PNIPAM-co-PS Nanofibers with Functionalized Au Nanoparticles for the High-Sensitive Diagnosis of Cancer Cells

2009 ◽  
Vol 9 (2) ◽  
pp. 876-879 ◽  
Author(s):  
Min Song ◽  
Xuemei Wang ◽  
Chunxia Wang ◽  
Chao Pan ◽  
Degang Fu ◽  
...  
Keyword(s):  
Cancer Cells ◽  
Au Nanoparticles ◽  
Diagnosis Of Cancer

scholarly journals Lung Cancer Detection using Nearest Neighbour Classifier

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3641-3645
Keyword(s):  
Lung Cancer ◽  
Cancer Cells ◽  
Cancer Detection ◽  
Early Stage ◽  
Second Step ◽  
Nearest Neighbour ◽  
Cancer Data ◽  
Diagnosis Of Cancer ◽  
Nearest Neighbour Classifier ◽  
Lung Cancer Detection

One of the most precarious diseases is lung cancer. Lung cancer detection is one of the main challenging dilemma nowadays. Most of the cancer cells are overlies with each other. It is tough to detect the cell but also important to identify the existence of cancer cells in the early stage unless unable to prevent. According to 2018 reports, 17 million new lung cancer cases are identified worldwide. The Computer Tomography can be used for diagnosis of cancer with image processing. In this research, we proposed two steps of process for diagnosing the presence of cancer either benign or malignant. In the first step, features are extracted by using GLCM. In the second step, the lung cancer cells are classified either benign or malignant by using Nearest Neighbour classifier. Experimental results demonstrated that the proposed approach performance is 98.76% classification accuracy for diagnosing the lung cancer data.

scholarly journals The Identification Nanoparticle Sensor Using Back Propagation Neural Network Optimized by Genetic Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yiwen Hu ◽  
Ashutosh Sharma ◽  
Gaurav Dhiman ◽  
Mohammad Shabaz
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Early Diagnosis ◽  
Cancer Cells ◽  
Bp Neural Network ◽  
Back Propagation ◽  
Dark Field ◽  
Green Fluorescence ◽  
Early Diagnosis Of Cancer ◽  
Diagnosis Of Cancer

This study draws attention towards the application of identification nanoparticle (NPs) sensor based on back propagation (BP) neural network optimized by genetic algorithm (GA) in the early diagnosis of cancer cells. In this study, the traditional and optimized BP neural networks are compared in terms of error between the actual value and the predictive value, and they are further applied to the NP sensor for early diagnosis of cancer cells. The results show that the root mean square (RMS) and mean absolute error (MAE) of the optimized BP neural network are comparatively much smaller than the traditional ones. The particle size of silicon-coated fluorescent NPs is about 105 nm, and the relative fluorescence intensity of silicon-coated fluorescent NPs decreases slightly, maintaining the accuracy value above 80%. In the fluorescence imaging, it is found that there is obvious green fluorescence on the surface of the cancer cells, and the cancer cells still emit bright green fluorescence under the dark-field conditions. In this study, a phenolic resin polymer CMK-2 with a large surface area is successfully combined with Au. NPs with good dielectric property and bioaffinity are selectively bonded to the modified electrode through a sulfur-gold bond to prepare NP sensor. The sensor shows good stability, selectivity, and anti-interference property, providing a new method for the detection of early cancer cells.

Single-cell resolution diagnosis of cancer cells by carbon nanotube electrical spectroscopy

Nanoscale ◽  
2013 ◽  
Vol 5 (8) ◽  
pp. 3421 ◽  
Author(s):  
M. Abdolahad ◽  
M. Janmaleki ◽  
M. Taghinejad ◽  
H. Taghnejad ◽  
F. Salehi ◽  
...  
Keyword(s):  
Carbon Nanotube ◽  
Single Cell ◽  
Cancer Cells ◽  
Diagnosis Of Cancer

scholarly journals Multiple antibodies identify glypican-1 associated with exosomes from pancreatic cancer cells and serum from patients with pancreatic cancer

2017 ◽  
Author(s):  
Chengyan Dong ◽  
Li Huang ◽  
Sonia A. Melo ◽  
Paul Kurywchak ◽  
Qian Peng ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Monoclonal Antibodies ◽  
Cancer Cells ◽  
Specific Detection ◽  
Liquid Biopsies ◽  
Pancreatic Cancer Cells ◽  
Diagnosis Of Cancer ◽  
Cellular Components ◽  
Different Sources ◽  
Conceptual Advance

Exosomes are man-sized vesicles shed by all cells, including cancer cells. Exosomes can serve as novel liquid biopsies for diagnosis of cancer with potential prognostic value. The exact mechanism/s associated with sorting or enrichment of cellular components into exosomes are still largely unknown. We reported Glypican-1 (GPC1) on the surface of cancer exosomes and provided evidence for the enrichment of GPC1 in exosomes from patients with pancreatic cancer1. Several different laboratories have validated this novel conceptual advance and reproduced the original experiments using multiple antibodies from different sources. These include anti-GPC1 antibodies from ThermoFisher (PA5-28055 and PA-5-24972)1,2, Sigma (SAB270028), Abnova (MAB8351, monoclonal antibodies clone E9E)3, EMD Millipore (MAB2600-monoclonal antibodies)4, SantaCruz5, and R&D Systems (BAF4519)2. This report complements such independent findings and report on the specific detection of Glypican-1 on the exosomes derived from the serum of pancreas cancer patients using multiple antibodies. Additionally, the specificity of the antibodies to GPC1 was determined by western blot and Protein Simple analyses of pancreatic cancer cells and their exosomes. Interestingly, our results highlight a specific enrichment of high molecular weight GPC1 on exosomes, potentially contributed by heparan sulfate and other glycosylation modifications.

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