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<

S Khalifa E, AM Sabeeh A, AN Adil A…, 2007

Objective: The study the association of procalcitonin (PCT) and c-reactive protein (CRP) levels in COVID-19 patients and it's role as a guide in progress and management of those patients. Methodology: This cross-sectional study analyzed 200 CIOVID-19 patients in a single privet center in Baghdad, Iraq from January 1, 2021 to January 1, 2022. Demographic data like age, sex, and clinical symptoms were recorded. High sensitivity CRP and PCT in the serum were measured via dry fluorescence immunoassay (Lansionbio-China). Results: Out of 200 patients, 50 had moderate Covid and 150 had severe disease. Mean serum PCT levels was 0.039±0.05 ng/mL in the moderate group (range 0.011-0.067) and 0.43±0.21 ng/mL in the severe group (range 0.21

Stroke is the second largest cause of death worldwide and one of the most common causes of disability. However, several approaches have been proposed to deal with stroke patient rehabilitation like robotic devices and virtual reality systems, researchers have found that the brain-computer interfaces (BCI) approaches can provide better results. In this study, the electroencephalography (EEG) dataset from post-stroke patients were investigated to identify the effects of the motor imagery (MI)-based BCI therapy by investigating sensorimotor areas using frequency and time-domain features and to select particular methods that help in enhancing the MI-based BCI systems for stroke patients using EEG signal processing. Therefore, to detect

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

Bedside clinical teaching is a fundamental part of the medical education that offers invaluable opportunities for the students to build and improve their clinical and communication skills. However, there is a growing concern about the increasing refusal of patients to participate in clinical sessions, especially in certain settings where there are sensitive cultural traditions and decreased trust in institutions.

KE Sharquie, AA Noaimi, HA Al-Mudaris, Journal of Drugs in Dermatology: JDD, 2013 - Cited by 22