Background/Aim: Knee osteoarthritis is a frequently crippling chronic condition. Numerous pharmacological medications have been successfully utilised to treat knee osteoarthritis. This research aimed to compare the efficiency of metformin and serratiopeptidase in treating and preventing osteoarthritis development via distinct mechanisms. Methods: Between 1 January and 30 May 2019, a randomised-clinical-trial was done at Al-Kindy Hospital on 80 osteoarthritis patients, divided in two groups. Group I was given metformin 850 mg orally, whereas Group II was given serratiopeptidase 20 mg and metformin 850 mg orally. Parameters in these groups were compared with forty healthy normal controls. Results: Following treatment, patients in Grou

Background: Monocyte chemotactic protein-1 (MCP-1) is a chemokine expressed by inflammatory and endothelial cells. It has a crucial role in initiating, regulating, and mobilizing monocytes to active sites of periodontal inflammation. Its expression is also elevated in response to pro-inflammatory stimuli and tissue injury, both of which are linked to atherosclerotic lesions. Aim of the study: To determine the serum level of MCP-1 in patients with periodontitis and atherosclerotic cardiovascular disease in comparison to healthy control and evaluate the biomarker's correlations with periodontal parameters. methods: This study enrolled 88 subjects, both males and females, ranging in age from 36-66 years old, and divided into four groups: 1<

This study aims at detecting the differences in genotyping of coding region fusA gene in clinical isolates of Acinetobacter baumannii from Baghdad, Iraq. Collected two hundred clinical samples (50 samples from urine, 50 samples from wound, 50 samples from sputum and 50 samples from otitis infections). Laboratory diagnosis for bacterial isolates carried out by some biochemical tests and confirmed by using VITEK- 2 compact system. The results appeared that twenty isolates of Acinetobacter baumannii in all these samples. Genotyping study was performed of coding region fusA gene of the extracted genome of all bacterial isolates and used specific primers in achieved amplification process of this target gene. DNA sequencing of this gene and alig

Opportunistic fungal infections due to the immune- compromised status of renal transplant patients are related to high rates of morbidity and mortality regardless of their minor incidence. Delayed in identification of invasive fungal infections (IFIs), will lead to delayed treatment and results in high mortality in those populations. The study aimed to assess the frequency of invasive fungal infection in kidney transplant recipients by conventional and molecular methods. This study included 100 kidney transplant recipients (KTR) (75 males, and 25 females), collected from the Centre of Kidney Diseases and Transplantation in the Medical City of Baghdad. Blood samples were collected during the period from June 2018 to April 2019. Twent

Panax ginseng (PG), one of the most widely used herbal medicines, has demonstrated various beneficial effects such as anti-inflammatory, antioxidant, and anticancer impacts. Naturally occurring ginsenosides in the ginseng plant inhibit cell proliferation and significantly reduce liver damage induced by certain chemicals. Aflatoxin B1 (AFB1) is a primary mycotoxin due to its hepatotoxic, immunotoxic, and oncogenic effects in animal models and humans. In this study, we examined the effects of assorted doses of PG aqueous crude extract on the expression of matrix metalloproteinase 1 and 7 (MMP-1 and MMP-7) in the kidney, spleen, and liver of experimental AFB1-exposed mice, using immunohistochemistry (IHC). Mice were orally administered

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D