Evaluations of 5-fluorourcil treated lung cancer cells by atomic force microscopy

Atomic force microscopy (AFM) can be used to obtain the physical information of single live cancer cells; however, the physical changes in live cells with time based on AFM remain to be studied, which play a key role in the evaluation of the efficacy and side effects of drugs. Herein, the treatment of the A549 cell line with the anticarcinogen 5-fluorouracil has been discussed based on the AFM analysis of their continuous physical changes, including their surface morphology, height, adhesion and Young's modulus, with time. In comparison, the African green monkey kidney (Vero) cell line was tested as normal cells to determine the side effects of 5-fluorouracil. The results show that the optimal concentration of 5-fluorouracil is about 500 μM, which presents the best anticancer effect and mild side effects

Effect of extract from ginseng rust rot on the inhibition of human hepatocellular carcinoma cells in vitro

Hepatocellular carcinoma (HCC) is one of major leading causes of cancer death worldwide. As a traditional medicine, the anti-cancer function of ginseng is being growingly recognized and investigated. However, the effect of ginseng rust rot on human HCC is unknown yet. In this study, the HCC cells were treated with different parts of mountain cultivated ginseng rust rot and compared with human normal liver cells. The morphology, survival rate and β-actin expression of the cells were changed by introducing the ginseng epidermis during the incubation process. Notably, the results reveal that the ginseng epidermis can induce apoptosis by altering the morphologies of cells, indicating the practical implication for the HCC treatment and drug development

A New Approach to the Degradation Stage Prediction of Rolling Bearings Using Hierarchical Grey Entropy and a Grey Bootstrap Markov Chain

Degradation stage prediction, which is crucial to monitoring the health condition of rolling bearings, can improve safety and reduce maintenance costs. In this paper, a novel degradation stage prediction method based on hierarchical grey entropy (HGE) and a grey bootstrap Markov chain (GBMC) is presented. Firstly, HGE is proposed as a new entropy that measures complexity, considers the degradation information embedded in both lower- and higher-frequency components and extracts the degradation features of rolling bearings. Then, the HGE values containing degradation information are fed to the prediction model, based on the GBMC, to obtain degradation stage prediction results more accurately. Meanwhile, three parameter indicators, namely the dynamic estimated interval, the reliability of the prediction result and dynamic uncertainty, are employed to evaluate the prediction results from different perspectives. The estimated interval reflects the upper and lower boundaries of the prediction results, the reliability reflects the credibility of the prediction results and the uncertainty reflects the dynamic fluctuation range of the prediction results. Finally, three rolling bearing run-to-failure experiments were conducted consecutively to validate the effectiveness of the proposed method, whose results indicate that HGE is superior to other entropies and the GBMC surpasses other existing rolling bearing degradation prediction methods; the prediction reliabilities are 90.91%, 90% and 83.87%, respectively

A Structural Design Method of 3D Electromagnetic Wave-Absorbing Woven Fabrics

Based on the wave absorption model of 3D woven fabric and the zero-reflection equations, a new structural design method of 3D electromagnetic (EM) wave-absorbing woven fabrics was obtained. The 3D woven fabrics fabricated by the proposed method had the structure of a bidirectional angle interlock. Continuous S-2 glass fibers were used as the matching layer of this 3D woven fabric, and continuous carbon fibers were used as the absorbing layer. The absorbing layer satisfied the equivalent EM parameters under the condition of zero reflection. The results of the simulation and experiment showed that the performance trends of the 3D wave-absorbing fabric obtained by this method were consistent with the theory, which verified the correctness of the structure design method. The 3D fabrics obtained by this method have the advantages of wide absorbing frequencies and good absorbing performance (−20 dB). This structural design method also has theoretical guiding significance for the development of 3D wave-absorbing fabrics

A Review of Electromagnetic Shielding Fabric, Wave-Absorbing Fabric and Wave-Transparent Fabric

As the basic materials with specific properties, fabrics have been widely applied in electromagnetic (EM) wave protection and control due to their characteristics of low density, excellent mechanical properties as well as designability. According to the different mechanisms and application scenarios on EM waves, fabrics can be divided into three types: EM shielding fabric, wave-absorbing fabric and wave-transparent fabric, which have been summarized and prospected from the aspects of mechanisms and research status, and it is believed that the current research on EM wave fabrics are imperfect in theory. Therefore, in order to meet the needs of different EM properties and application conditions, the structure of fabrics will be diversified, and more and more attentions should be paid to the research on structure of fabrics that meets EM properties, which will be conductive to guiding the development and optimization of fabrics. Furthermore, the application of fabrics in EM waves will change from 2D to 3D, from single structure to multiple structures, from large to small, as well as from heavy to light

Research on the Construction Method of Intelligent Prediction and Analysis Model for the Whole Process of Power Grid Project Cost

The government’s supervision of power grid enterprises will gradually focus on the transmission and distribution price, and the investment and income will be more strictly supervised. Under the new management requirements, the company must pay more attention to the compliance of the investment process, further strengthen the investment risk control, put an end to inefficient or invalid investment, strengthen the all-round and whole process supervision, and scientifically and accurately determine and carry out effective project cost control and management. It is the key to achieve project management objectives, and also an important measure of investment fine management and control. This paper takes historical cost data as the research object, constructs the whole process intelligent prediction and analysis model of power grid project cost, assists investment decision-making, reduces the balance rate, and improves the efficiency and efficiency of the company’s investment and lean management level

Multi‐scale characterization and analysis of cellular viscoelastic mechanical phenotypes by atomic force microscopy

The viscoelasticity of cells serves as a biomarker that reveals changes induced by malignant transformation, which aids the cytological examinations. However, differences in the measurement methods and parameters have prevented the consistent and effective characterization of the viscoelastic phenotype of cells. To address this issue, nanomechanical indentation experiments were conducted using an atomic force microscope (AFM). Multiple indentation methods were applied, and the indentation parameters were gradually varied to measure the viscoelasticity of normal liver cells and cancerous liver cells to create a database. This database was employed to train machine‐learning algorithms in order to analyze the differences in the viscoelasticity of different types of cells and as well as to identify the optimal measurement methods and parameters. These findings indicated that the measurement speed significantly influenced viscoelasticity and that the classification difference between the two cell types was most evident at 5 μm/s. In addition, the precision and the area under the receiver operating characteristic curve were comparatively analyzed for various widely employed machine‐learning algorithms. Unlike previous studies, this research validated the effectiveness of measurement parameters and methods with the assistance of machine‐learning algorithms. Furthermore, the results confirmed that the viscoelasticity obtained from the multiparameter indentation measurement could be effectively used for cell classification.Research Highlights This study aimed to analyze the viscoelasticity of liver cancer cells and liver cells. Different nano‐indentation methods and parameters were used to measure the viscoelasticity of the two kinds of cells. The neural network algorithm was used to reverse analyze the dataset, and the methods and parameters for accurate classification and identification of cells are successfully found

Imaging the substructures of individual IgE antibodies with atomic force microscopy

The interaction between antibodies and substrates directly affects its conformation and thus its immune function. Therefore, it is desirable to study the structure of antibodies at the single molecule level. Herein, the substructures of Immunoglobulin E (IgE) on solid surfaces were investigated. For this purpose, the tapping-mode atomic force microscopy (AFM) was applied to observe the individual IgE substructures adsorbed onto Mg2+ and Na+ modified mica substrates in air. As expected, the AFM images revealed that the IgE antibodies exhibited different conformations on the surface of mica substrate, consisting of the four basic orientations: three domain, two equivalent domain, two unequal domain and single domain morphologies. Moreover, the differences of the different orientations in single IgE antibodies were also identified clearly