The objective of this research was to estimate the dose distribution delivered by radioactive gold nanoparticles (198 AuNPs or 199 AuNPs) to the tumor inside the human prostate as well as to normal tissues surrounding the tumor using the Monte-Carlo N-Particle code (MCNP-6.1. 1 code). Background Radioactive gold nanoparticles are emerging as promising agents for cancer therapy and are being investigated to treat prostate cancer in animals. In order to use them as a new therapeutic modality to treat human prostate cancer, accurate radiation dosimetry simulations are required to estimate the energy deposition in the tumor and surrounding tissue and to establish the course of therapy for the patient. Materials and methods A simple geometrical

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

The current work reports a new Schiff base [N1-benzylidenebenezene-1,2-diamine(L) = C20H16N2] has been synthesized from benzaldehyde (C6H5CHO) and O- aminoaniline (O-C6H4(NH2)2. Metal mixed ligand complexes of the Schiff base were prepared from chloride salts of Zn(II), Cd(II) and Hg(II) in ethanol and 8-hydroxyquinoline(8HQ)(C9H7NO) containing sodium hydroxide. All the complexes were characterized on the basis of their; FT-IR and U.V spectra, melting point, molar conductance, and determination of the percentage of the metal in the complexes by flame (AAS). In the all complexes, (8HQ) behaves as a bidentate ligand as primary ligand through –-OH phenolic group and –N groups of pyridine group. Also, the prepared ligand (L) was bidentate i

Background: Metabolic syndrome (Mets) is partially heritable. High mobility group AT-hook1 (HMGA1), an architectural transcription factor, affects the homeostasis of glucose. The marked inter-individual differences between T

Collaborative learning in class‐based teaching presents a challenge for a tutor to ensure every group and individual student has the best learning experience. We present Group Tagging, a web application that supports reflection on collaborative, group‐based classroom activities. Group Tagging provides students with an opportunity to record important moments within the class‐based group work and enables reflection on and promotion of professional skills such as communication, collaboration and critical thinking. After class, students use the tagged clips to create short videos showcasing their group work activities, which can later be reviewed by the teacher. We report on a deployment of Group Tagging in an undergraduate Computing Scie

Asthma is a chronic in?ammatory respiratory disease associated with the changes of asthmatic airway structural that result from interact remodeling and in?ammatory processes lead to obstruction of airway. Guggulsterone (GS) is a bioactive compound and plant steroid present in  guggul gum of Commiphora wightii, which has anti-inflammatory and antioxidant activities. This study designed to investigate of anti-inflammatory activity of gugglsterone in improvement of asthma. Forty eight healthy albino male rats divided to six groups, Group I: Control group (distal water), Group II: Positive control group (distal water) with sensitization, Group III: Guggulsterone (25 mg/kg/day) with sens