Beta thalassemia major (BTM) is a genetic disorder that has been linked to an increased risk of contracting blood-borne viral infections, primarily due to the frequent blood transfusions required to manage the condition. One such virus that can be transmitted through blood is the Human Parvovirus B19 (B19V). The aim of this study was to investigate the frequency and molecular detection of B19V. This study included 60 blood donors as controls and 120 BTM patients. B19V was identified by serology, which measured B19-IgG and B19-IgM antibodies. Nested Polymerase Chain Reaction (nPCR) was employed to target the VP1/VP2 structural proteins. The results showed that B19V seropositivity represents 27.5% (33 out of 120) in BTM patients, and only 8 out of 60 subjects represents (13.3%) in the control group (P-value 0.078). Notably, male patients exhibited a significantly higher prevalence of B19-IgM and B19-IgG antibodies, with 32% and 24% of males testing positive, respectively, compared to female patients. Elevated levels of Aspartate and Alanine Transaminase were observed with values of 51.94±50.09 and 46.81±50.20, respectively. Additionally, nPCR analysis detected B19V DNA in 4.16% (5 out of 120) of BTM patients, while no positive results were detected in the control group. Screening the blood and blood products for the virus in high-risk group can considerably reduce the prevalence. Preventive measures are required in such vulnerable population.
This research aims to shed light on the reality of the process of rehabilitation of human resources for the implementation of electronic management practice in the ministry, and availability requirements of the application of electronic management and diagnosis of the most important stages and steps that can be followed in the process of transition towards electronic management to keep abreast of developments in the field of information technology, has been the application of this research in the Ministry of science and technology on a group of heads of departments and directors of the people in the departments of the Ministry through the use of case study method, which includes cohabitation field intervi
... Show MoreThe outbreak of a current public health coronavirus 2019 disease is a causative agent of a serious acute respiratory syndrome and even death. COVID-19 has exposed to multi-suggested pharmaceutical agents to control this global disease. Baricitinib, a well-known antirheumatic agent, was one of them. This article reviews the likely pros and cons of baricitinib in attenuation of COVID-19 based on the mechanism of drug action as well as its pharmacokinetics. The inhibitory effect of baricitinib on receptor mediated endocytosis promoter, AKK1, and on JAK-STAT signaling pathway is benefacial in inhibition of both viral assembling and inflammation. Also, its pharmacokinetic has encouraged the physicians toward the drug
... Show MoreObjective: Synthesized a series of new thiourea (TU) derivatives, tested their antioxidant activity, and investigated their expected biological activity by theoretical study (computational methods). Methods: The derivatives were made using a one-pot reaction with two steps. Initially, succinyl chloride was mixed with KSCN to make succinyl isothiocyanate. Then, primary and secondary amines were used to make TU derivatives. The theoretical studies were done by Swiss ADME and molecular docking via Genetic Optimization of Linkage Docking (GOLD). Then evaluate antioxidant activity using the DPPH scavenging method. Results: FT-IR, 1H NMR, and 13C NMR spectroscopy show the verification of all the prepared derivatives. Compounds (II), (VIII),
... Show MoreThe primary toxin class discovered in freshwater pufferfish is a category of neurotoxins called PSTs (Paralytic shellfish toxins) and pufferfish toxin has been observed to have biological, biochemical, and cytotoxic effects on cancer cell lines. Therefore, it is crucial to determine the cytotoxic activity, toxins present in the ovary of T. leiurus, and interaction between ligand (toxin compound) and receptors test. This study used the MTT method in the T47D cell lines, liquid chromatograph-tandem mass spectrometry (LC-MS/MS), and analysis of the molecular interaction using molecular docking. The ovary of T. leiurus had cytotoxicity on the T47D cell, having an IC50 value of 229.535 μg/ml, and generated a chroma
... Show MoreEnterococci species (spp.) are naturally found in the gastrointestinal tract (GIT), oral cavity of both human and animals causing several infections including bacteremia, meningitis, endocarditis, intra-abdominal infections, wound infections, urinary tract infections (UTI), atherosclerosis and play a critical role in the riskiness or development of periodontitis, particularly in a suitable mouth environment (Comerlato et al., 2020; Mendes et al., 2020; Xiong et al., 2021; H Elaywe, 2007). Recurrent and continues antimicrobial resistance (AMR) of opportunistic microorganisms is one of the serious public health risk, enterococci spp are often intrinsic resistant to antibiotics class routinly used in treatment such as Cephalosporins, Macrolids
... Show MoreThe rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz
... Show MoreThe rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz
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