The application of physiological oxygen (physoxia) concentrations is becoming increasingly commonplace within a mammalian stem cell culture. Human mesenchymal stem cells (hMSCs) attract widespread interest for clinical application due to their unique immunomodulatory, multi-lineage potential, and regenerative capacities. Descriptions of the impact of physoxia on global DNA methylation patterns in hMSCs and the activity of enzymatic machinery responsible for its regulation remain limited. Human bone marrow-derived mesenchymal stem cells (BM-hMSCs, passage 1) isolated in reduced oxygen conditions displayed an upregulation of SOX2 in reduced oxygen conditions vs. air oxygen (21% O2, AO), while no change was noted for either OCT-4 or NA

Background: Patients with chronic kidney
disease have different grades of sensorineural
deafness .
Objective: To study the incidence of
sensorineural hearing loss and possible contributing
factors in patients with chronic kidney disease.
Methods: A total of 100 patients with chronic
kidney disease were studied. All of them were
males. 92 of them were on regular haemodialysis
programme. Only 8 patients were on conservative
management the age range of the study patients was
18-40 year patients were divided into three groups
according to age. All patients were assessed
clinically and were evaluated by audiometry , and
analysis was made on bone conduction threshold
.The mean follow up period was 2

Objectives: Serratia marcescens is a gram-negative pathogen of many species. The ability of S. marcescens to form biofilms and its potent innate resistance to antimicrobials and cleaning solutions are both essential for its pathogenicity and survival. The present study was conducted to investigate the effect of glyceryl trinitrate (GTN) on the biofilm of S. marcescens, as an alternative for antibiotic therapy. Methods: Different specimens, including ear swabs, burns, mid-stream urine, wound swabs, and sputum, were collected from patients who were brought to Al-Ramadi Hospital, Iraq. All samples were cultured, and the colonies that were obtained were detected using the VITEK® 2 compact. The ability of biofilms to develop was e

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a

Background: COVID-19 is a disease that started in Wuhan/China in late 2019 and continued through 2020 worldwide. Scientists worldwide continue to research to find vaccines, treatments, and medication for this disease. Studies also conenue to find the pathogenicity and epidemiology mechanisms. Materials and Methods: In this work, we analyzed cases obtained from Alshifaa center in Baghdad/Iraq for 23/2/2020-31/5/2020 with total instances of 797, positive cases of 393, and death cases of 30. Results: Results showed that the highest infection cases were among people aged between 41-45. Also, it was found that males' number of cases was more than females. In contrast, death cases were significantly higher in males than females. It was not

Inelastic transverse magnetic dipole electron scattering form
factors in 48Ca have been investigated through nuclear shell model
in an excited state energy Ex= 10.23 MeV which is so called
"mystery case" with different optional choices like effective
interaction, restricted occupation and core polarization interaction.
40Ca as an inert core will be adopted and four orbits with eight
particles distributed mainly in 2p1f model space and in some extend
restricted to make sure about the major accuse about this type of
transition. Theoretical results have been constituted mainly with
experimental data and compared with some important theoretical
results of the same transition.

The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach