Mycobacterium tuberculosis resistance to rifampicin is mainly mediated through mutations in the rpoB gene. The effects of rpoB mutations are relieved by secondary mutations in rpoA or rpoC genes. This study aims to identify mutations in rpoB, rpoA, and rpoC genes of Mycobacterium tuberculosis isolates and clarify their contribution to rifampicin resistance. Seventy isolates were identified by acid-fast bacilli smear, Genexpert assay, and growth on Lowenstein Jensen medium. Drug susceptibility, testing was performed by the proportional method.  DNA extraction, PCR, and sequencing were accomplished for the entire rpoA, rpoB, and

   Neural stem cells (NSCs) are progenitor cells which have the ability to self‑renewal and potential for differentiating into neurons, oligodendrocytes, and astrocytes. The in vitro isolation, culturing, identification, cryopreservation were investigated to produce neural stem cells in culture as successful sources for further studies before using it for clinical trials. In this study, mouse bone marrow was the source of neural stem cells. The results of morphological study and immunocytochemistry of isolated cells showed that NSCs can be produced successfully and maintaining their self‑renewal and successfully forming neurosphere for multiple passages. The spheres preserved their morphology in culture and cryopreserved t

Optimized Link State Routing Protocol (OLSR) is an efficient routing protocol used for various Ad hoc networks. OLSR employs the Multipoint Relay (MPR) technique to reduce network overhead traffic. A mobility model's main goal is to realistically simulate the movement behaviors of actual users. However, the high mobility and mobility model is the major design issues for an efficient and effective routing protocol for real Mobile Ad hoc Networks (MANETs). Therefore, this paper aims to analyze the performance of the OLSR protocol concerning various random and group mobility models. Two simulation scenarios were conducted over four mobility models, specifically the  Random Waypoint model (RWP), Random Direction model (RD), Nomadic Co

The subject of the Internet of Things is very important, especially at present, which is why it has attracted the attention of researchers and scientists due to its importance in human life. Through it, a person can do several things easily, accurately, and in an organized manner. The research addressed important topics, the most important of which are the concept of the Internet of Things, the history of its emergence and development, the reasons for its interest and importance, and its most prominent advantages and characteristics. The research sheds light on the structure of the Internet of Things, its structural components, and its most important components. The research dealt with the most important search engines in the Intern

In the absence of environmental regulation, food stays to be contaminated with heavy metals, which is becoming a big worry for human health. The present research focusses on the environmental and health effects of irrigating a number of crops grown in the soils surrounding the Al-Rustamia old plant using treated wastewater generated by the plant. The physicochemical properties, alkalinity, and electrical conductivity of the samples were evaluated, and vegetable samples were tested for Cd, Pb, Ni, and Zn, levels, and even the transfer factor (TF) from soils to crops and crop and multi-targeted risk, daily intake (DIM) of metals, and health risk index (HRI) was calculated. The findings found that the average contents of Zn, Pb, Ni, an

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims