Abstract
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.
Highlights
In the past few years, people’s increasingly high requirements for microscopic detection technology have led to an evolution, in the applications of various nanomaterials in the biological field
Preparation of CMK-2 (1) Preparation of the Phenolic Resin Prepolymer. 3.25 g of phenol is dissolved in 0.5 g of 20 wt% NaOH solution. 15 minutes later, the uniform mixture is slowly dripped into 5.5 g of 37 wt% formaldehyde solution, with the temperature adjusted to 75°C, followed by reflux for 1 h
The back propagation (BP) Neural Network Optimized by genetic algorithm (GA)
Summary
In the past few years, people’s increasingly high requirements for microscopic detection technology have led to an evolution, in the applications of various nanomaterials in the biological field. The NP-based nanotechnology can be applied to the diagnosis and treatment of tumors [2]. Compared with ordinary fluorescent dyes, fluorescent NPs have high brightness, good stability, strong water solubility, and good biocompatibility [4]. Cancer cell imaging is of great significance in the diagnosis of tumors. Fluorescent NPs can enhance biological signals to facilitate detection [5]. Hyaluronic acid (HA) has a good application prospect in the diagnosis and treatment of tumor diseases [6]. A nanodrug-carrying system prepared by combining NPs and HA can bind to receptor proteins on the cell surface to detect cancer cells. Shen et al [7] prepared diamine-hyaluronic acid-iron-modified rhodamine fluorescent NPs for cancer imaging detection. The results proved that fluorescent NPs had high sensitivity and stability
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