The issue of nuclear proliferation is one of the most vital issues as it reflects a form of dealing in the field of international relations. Therefore, the Middle East region has taken great interest in reducing the levels of nuclear armament and acquiring nuclear power within the strategic framework of the international and regional powers. The establishment of a nuclear-weapon-free zone in the Middle East region is currently one of the most important international and regional arrangements for controlling the levels of nuclear proliferation and attempting to build a state of stability and balance. In the Middle East and the world. The importance of the research comes from the fact that it deals with an important and vital issue

A large number of natural or synthetic dyes have been removed from both national and international lists of permitted food colors because of their mutagenic or carcinogenic activity. Therefore, this study aimed to use the Random Amplified Polymorphic DNA-Based Polymerase Chain Reaction (RAPD-PCR) assay as a feasible method to evaluate the ability of some food colors as genotoxin-induced DNA damage and mutations. Lactiplantibacillus plantarum was used as a bioindicator to determine the genotoxic effects by RAPD-PCR using M13 primer after treatment with some synthetic dyes currently used as food color additives, including Sunset Yellow, Carmoisine, and Tartrazine. Besides qualitative analysis, the bioinformatic GelJ software was used for clus

In this study, NAC-capped CdTe/CdS/ZnS core/double shell QDs were synthesized in an aqueous medium to investigate their utility in distinguishing normal DNA from mutated DNA extracted from biological samples. Following the interaction between the synthesized QDs with DNA extracted from leukemia cases (represents damaged DNA) and that of healthy donors (represents undamaged DNA), differential fluorescent emission maxima and intensities were observed. It was found that damaged DNA from leukemic cells DNA-QDs conjugates at 585 nm while intact DNA (from healthy subjects) DNA–QDs conjugates at 574 nm. The obtained results from the optical analyses indicate that the prepared QDs could be utilized as probe for detecting disrupted DNA th

Chemotherapy is one of the most efficient methods for treating cancer patients. Chemotherapy aims to eliminate cancer cells as thoroughly as possible. Delivering medications to patients’ bodies through various methods, either oral or intravenous is part of the chemotherapy process. Different cell-kill hypotheses take into account the interactions of the expansion of the tumor volume, external drugs, and the rate of their eradication. For the control of drug usage and tumor volume, a model based smooth super-twisting control (MBSSTC) is proposed in this paper. Firstly, three nonlinear cell-kill mathematical models are considered in this work, including the log-kill, Norton-Simon, and hypotheses subject to parametric uncertainties and exo

Letrozole (LZL) is a non-steroidal competitive aromatase enzyme system inhibitor. The aim of this study is to improve the permeation of LZL through the skin by preparing as nanoemulsion using various numbers of oils, surfactants and co-surfactant with deionized water. Based on solubility studies, mixtures of oleic acid oil and tween 80/ transcutol p as surfactant/co-surfactant (Smix) in different percentages were used to prepare nanoemulsions (NS). Therefore, 9 formulae of (o/w) LZL NS were formulated, then pseudo-ternary phase diagram was used as a useful tool to evaluate the NS domain at Smix ratios: 1:1, 2:1 and 3:1.

This paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that

This study focused on extracting the outer membrane nanovesicles (OMVs) from Escherichia coli BE2 (EC- OMVs) by ultracentrifugation, and the yield was 2.3mg/ml. This was followed by purification with gel filtration chromatography using Sephadex G-150, which was 2mg/ml. The morphology and size of purified EC-OMVs were confirmed by transmission electron microscopy (TEM) at 40-200 nm. The nature of functional groups in the vesicle vesicle was determined by Fourier transforms infrared spectroscopy (FT-IR) analysis. The antitumor activity of EC-OMVs was conducted in vitro by MTT assay in human ovarian (OV33) cancer cell line at 24,48 and 96hrs. The cytotoxicity test showed high susceptibility to the vesicles in ovarian compared to normal

Background: The presence of cancer has a profound psychological impact on the quality of life of patients and their families, on family and social relationships, and on role functioning.

Aim of the study: Assess the impact of childhood cancer on patients and their families.

Subjects and methods: A Prospective questionnaire-based study, for 151 patients, had malignancy identified by tumor registry of Children Welfare Teaching Hospital. The information was taken from the parent(s) in the presence of the patient who sometimes answered some questions during the interview.

Result: There was an interview with 151 families of children with cancer in t

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p