There are numerous studies reported on the usage of the sapindus emarginatus (SE) fruit in cancer and other treatments in the past few years. In this study, crude SE fruit extract was prepared and it was further used to synthesis gold nanoparticles (Au Nps). The synthesized Au Nps were left embedded in the SE fruit extract. The Au Nps embedded in the SE fruit extract (SE-Au Nps) were characterized using UV-Visiable Spectroscopy, Centrifugal Particle Size analyzer (CPS), Scanning Electron Microscope (SEM) and Fourier Transform Infrared Spectroscopy (FTIR). MTT assay was carried out for both SE fruit extract and SE-Au Nps on MCF7 breast cancer cell line and thus compared. The UV-Visible Absorbance for the SE-Au Nps was obtained at 543 nm. The centrifugal particle size analysis of the Au Nps embedded in SE fruit extract showed the size of the nanoparticles to be widely varying with higher fraction of particles between the size ranges of 15 to 20 nm. The morphology of the Au Nps embedded in SE fruit extract was observed using SEM. The presence of Au Nps in SE fruit extract was confirmed using FTIR. The results of the MTT assay on MCF7 breast cancer cell line proved that the % cell viability was less for SE-Au Nps than that of the SE fruit extract alone. Thus, the antiproliferative activity of the SE fruit extract was significantly enhanced by embedding it with Au Nps and it can be effectively used in therapeutic applications after further studies.
According to the World Health Organization (WHO), breast cancer is among the most common cancers worldwide. Most of the anticancer agents have been showing a variety of side effects. Recently, bacterial proteins have been investigated as promising anticancer agents. Azurin is a bacterial cupredoxin protein secreted from Pseudomonas aeruginosa and has been reported as a potent multi-targeting anticancer agent, which makes it an appropriate candidate for drug delivery. Azurin may be delivered to cancer cells using different carriers like polymeric micro and nanoparticles. In the present study, azurin was extracted from the bacterial host and loaded into chitosan particles. Then its effect on MCF-7 cell line was investigated. Chitosan-azurin particles were made using the ion gelation method. Results showed that chitosan-azurin particles are about 200 nm, and the loading of the protein in particles did not affect its integrity. The MTT assay showed a significant reduction in cell viability in azurin and chitosan-azurin-treated cells. The toxicity level after 5 days was 63.78% and 82.53% for free azurin and chitosan-azurin-treated cells, respectively. It seems using an appropriate carrier system for anticancer proteins like azurin is a promising tool for developing low side effect anticancer agents.
Breast cancer was a prevalent form of cancer worldwide. Thermography, a method for diagnosing breast cancer, involves recording the thermal patterns of the breast. This article explores the use of a convolutional neural network (CNN) algorithm to extract features from a dataset of thermographic images. Initially, the CNN network was used to extract a feature vector from the images. Subsequently, machine learning techniques can be used for image classification. This study utilizes four classification methods, namely Fully connected neural network (FCnet), support vector machine (SVM), classification linear model (CLINEAR), and KNN, to classify breast cancer from thermographic images. The accuracy rates achieved by the FCnet, SVM, CLINEAR, and k-nearest neighbors (KNN) algorithms were 94.2%, 95.0%, 95.0%, and 94.1%, respectively. Furthermore, the reliability parameters for these classifiers were computed as 92.1%, 97.5%, 96.5%, and 91.2%, while their respective sensitivities were calculated as 95.5%, 94.1%, 90.4%, and 93.2%. These findings can assist experts in developing an expert system for breast cancer diagnosis.
The MDA-MB-231 cell line is derived from triple-negative breast cancer (TNBC), representing one of the most aggressive forms of breast cancer. Innovative therapeutic strategies, including s targeted therapies using nanocarriers, hold significant promise, particularly for difficult-to-treat cancers such as TNBC. Nanoparticles have transformed the medical field by serving as advanced drug delivery systems for cancer treatment. They play a critical role in overcoming the drug resistance often associated with cancer therapies. When utilized as drug delivery vehicles, nanoparticles can specifically target cancer cells and effectively reduce or eliminate multidrug resistance. Among them, chitosan-coated magnetic nanoparticles (MNPs) have been widely explored for the loading and controlled release of various anticancer agents. In this study, we evaluated the effects of dexamethasone-loaded chitosan-coated MNPs on MDA-MB-231 cell lines. Fourier transform infrared spectroscopy and scanning electron microscopy were employed to verify the successful loading of dexamethasone onto the nanoparticles. To assess cytotoxicity, empty nanoparticles, free drug, and drug-loaded nanoparticles were tested on the cells. The results indicated that empty nanoparticles exhibited no toxic effects. The IC50 value of the free drug was 123 µg/mL, while the IC50 value of the drug-loaded nanoparticles was significantly lower, at 63 µg/mL. These findings confirmed the successful conjugation of dexamethasone to the chitosan-coated MNPs, demonstrating substantial cytotoxic effects on breast cancer cells. Although dexamethasone has been reported to exhibit both tumor-suppressive and pro-metastatic effects, its specific impact on TNBC warrants further investigation in future studies.
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