laya ebrahimi

Considering the broad spectrum of using nanoparticles in food coatings as a potent antimicrobial agent and their possible cytotoxic effects and accidental consumption of these toxic materials, this study was performed. The present study aimed to investigate the cytotoxicity of chitosan and nano-chitosan in vitro.

This cross-sectional study was conducted in 2019 in the Laboratory of the Department of Food Hygiene and Public Health, School of Veterinary Medicine, Shiraz University, Shiraz, Iran. The XRD and FITR techniques were employed to study the characteristics of these nanoparticles. Moreover, two cell lines, HT-29 and Vero, were used to study the cytotoxic effects of chitosan and nano-chitosan by MTT assay, acridine orange, and ethidium bromide staining. One-way ANOVA and independent t-test were used to analyze the collected data with the help of SPSS software (version 19).

Based on the obtained findings, the maximum values of XRD at the angle of θ2 were observed at 20°. The highest peak appeared at 1530 cm-1, which was associated with tensile vibration of N-P-N. The spectrum diagram of chitosan due to the tensile vibration of synthetic nanochitosan of N-H bound appeared at 1646 cm-1. The results showed a proportional increase in the cytotoxicity with time and concentration of nanoparticles in the cells.

Since by increase in time and concentration of nanoparticles, toxicity was observed in cells; therefore, the time and concentration of chitosan nanoparticles are important in causing cytotoxicity. Considering the toxic effects of these nanocomposites on cancer cells, they can be used in cancer treatment, which requires further studies.

In this study, cytotoxic effects of silver-chitosan nanocomposites with aqueous sodium hydroxide solution (SCNC-ASHS) and aqueous acetic acid solution (SCNC-AAAS) were evaluated in vitro. The morphology of the synthesized nanoparticles was characterized by Fourier-Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscopy (SEM). Their cytotoxicities were then evaluated using MTT in concentrations of 1.56 to 400 µg/ml, and Acridine orange/Ethidium bromide (AO/EB) staining test after 24 h and 48 h. Results showed that the highest cytotoxicity was at 400 µg/ml concentration at which SCNC-ASHS respectively showed 80.57% and 84.37% toxicity on Vero and HT-29 cells after 24 h, and 82.20% and 84.84% after 48 h. While, the cytotoxicities for SCNC-AAAS on Vero and HT-29 cell lines were respectively 80.63% and 87.64% after 24 h, and 83.60% and 87.44% after 48 h. The most toxicity on HT-29 cells belonged to SCNC-AAAS with IC50 of 40.4 µg/ml. In the staining test, SCNC-AAAS revealed 41.84% HT-29 cell viability at 25 µg/ml concentration and 37.51% Vero cell viability at 6.25 µg/ml concentration. Generally, by increasing both SCNCs concentrations, the cell viabilities were decreased, and early and late apoptosis and necrosis were increased in AO/AE test. In conclusion, types of nanoparticles, synthesis methods, and different cell lines play considerable roles in inducing cytotoxicity. According to the higher significant cytotoxicity effects of both SCNCs on colon cancerous cells (HT-29) than normal cells (Vero) (p<0.05), it seems that they have anticancer effects; of those SCNC-AAAS displayed the higher effect with the IC50 of 4.4 µg/ml on HT-29 cells.

With the advancement of nanotechnology, nanoparticles have been applied in our modern society. However, the hazardous effects of nanoparticles on organisms have not been thoroughly clarified yet. Considering the migration of nanoparticles in food and its subsequent consumption by humans, we have employed normal cell line, the African green monkey kidney cell line (Vero) for evaluation of the cytotoxic activity of the silver nanoparticles. Currently, there are various approaches to perform toxicity tests. In this study, we investigated the effects of citrate-based silver nanoparticles on Vero cells to explore the adverse effects of these nanoparticles. In an experimental work, to synthetize silver nanoparticles, silver nitrate and citric acid were used. Nanoparticles were further characterized by UV-Visible Spectroscopy, Dynamic Light scattering (DLS) and Scanning Electron Microscopy (SEM). Cells were exposed to various concentrations of the nanoparticles (1.56 to 1000 µg/ml) for 24 h and 48h. The cytotoxic activity and apoptosis were determined using MTT assay and acridine orange/ethidium bromide (AO/EB) staining, respectively. The present study showed a dose-dependent cytotoxicity of the silver nanoparticles with log IC50 values of ~ 10.68 and 2.06 µg/ml for 24 h and 48 h, respectively on Vero cell lines. Analysis by AO/EB staining indicated that the silver nanoparticles induced apoptosis in the cell lines. Silver nanoparticles revealed cytotoxic effects on the Vero cells which was associated with the method of synthesis of silver nanoparticles.

In recent years, liver diseases have increased to a great extent in a way that it has turned into one of the most fatal diseases in the world. On time diagnosis of this disease can be effective in the prevention of its bad effects, its control and remedy. With technology advancement and changing many issues in software industry, doctors have developed a tendency towards intelligent systems for better diagnosis. Thus, in this paper, we have diagnosed liver sickness using fuzzy logic by obtaining important laboratory parameters. We have used two types of triangular membership function and Gussy membership function per 3 membership function for each input and output and also the design of reference table (search) to construct fuzzy heuristic system and we have managed to compare 243 rules. At the end, we were able to reach to 79/83% of accuracy with the appropriate choice of input parameters, the number and type of membership functions.

In software development and software project management, Software Cost Estimation (SCE) will be considered a major step in the start of projects. SCE is one of the main activities at the decisions of software's time and expense management which has a special status in a software project. SCE in software development is considered as a key parameter in software project management. Therefore, to achieve the basic goals requires accurate and reliable cost estimate. Actual estimate in software development is based on effective factors that its accurate value should be recognized using algorithmic models and Artificial Intelligence (AI). Boehm used COCOMO model for SCE which is an algorithmic model in 1981. Algorithmic models such as COCOMO are based on criteria such as the number of lines of code or the Function Point (FP). In COCOMO model, project development and then the cost is calculated by such units. Therefore, the lower accuracy and unreliability of the algorithmic models creates a substantial risk in software projects, so, regularly estimating the cost throughout the project is necessary and it should be compared with other techniques. In the meantime, meta-heuristic algorithms in recent years have made ??good progress in the area of ??software and it has been used widely in SCE. Among meta-heuristic algorithms, Particle Swarm Optimization (PSO), Differential Evolution (DE), Artificial Bee Colony (ABC), and Ant Colony Optimization (ACO) used to optimize the issues based on population and they have good effects in optimizing estimation factors. In this paper, a hybrid model DE-ACO, PSO-ACO and ABC-ACO based on ACO algorithm have been proposed for optimization based on effective factors in COCOMO model. Test results show that hybrid models have less magnitude of relative error (MRE) and Mean MRE (MMRE) in estimating software project cost in comparison with COCOMO model.