Oral carcinoma is the 6th most common cancer in the world. MicroRNAs are small non-coding single stranded RNAs. They have been shown to be capable of altering mRNA expression; thus some are oncogenic or tumor suppressive in nature. The salivary microRNA-31 has been proposed as a sensitive marker for oral malignancy since it was abundant in saliva more than in plasma. A total of 55 whole saliva samples were collected from 35 cases diagnosed with OC their ages and gender matched with 20 healthy subjects. TaqManq RT-PCR was performed for RNA samples. Mean age was 52.23+13.73 years in cases (range:17-70 years) with male predominance represented 69%. Risk of smoking and alcoholism was highly significant. The median fold change of miR-31 was sign

Abstract: The present study aimed to evaluate calcium, potassium, albumin, protein, creatinine, urea, uric acid levels, and the level of total sialic acid in the sera of patients with chronic renal failure who had been infected with Hepatitis C virus and in the sera of patients with chronic renal failure, and compare them with healthy volunteers. A total of 90 subjects with age 25-55 years, were divided into three groups. G1 represents 30 patients with chronic renal failure who had treated by dialysis and infected with chronic Hepatitis C virus (positive group). G2 represents 30 patients with chronic failure who had been treated by dialysis (negative group), while G3 represents 30 healthy volunteers (control group). The results showed

Background: The COVID-19 infection is a more recent pandemic disease all over the world and studying the pulmonary findings on survivors of this disease has lately commenced.

Objective: We aimed to estimate the cumulative percentage of whole radiological resolution after 3 months from recovery and to define the residual chest CT findings and exploring the relevant affecting factors.

Subjects and Methods: Patients who had been previously diagnosed with COVID-19 pneumonia confirmed by RT-PCR test and had radiological evidence of pulmonary involvement by Chest CT during the acute illness were included in the present study. The radiol

Background: Epilepsy is a common neurological disorder of incidence rate 1-2%. Genetic, congenital, developmental, tumors, head trauma and central nervous system infections maybe the cause of epilepsy. This study aimed to determine the prevalence of stomatitis, xerostomia and taste disorder among patients taking carbamazepine or sodium valproate and to make salivary analysis for IgA, cystatin c and salivary flow rate. Material and method:This study performed in al- Yarmuk teaching hospital in Baghdad, Samples consist of (70) epileptics half of them treated with carbamazepine and other half treated with sodium valproate, and (18) healthy control group of both genders and with different ages to detect the prevalence of oral manifestations, s

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.

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

Background: Fractures of the humeral shaft accounting for approximately 3% of all fractures. There is a wide array of good options for their treatment and controversy over the best methods. Although good techniques of osteosynthesis are available, the aim of this article is toemphasize on the benefit and good outcome of conservative treatment for properly selected cases to decrease the cost and avoid the complications of surgery. Method : During the period from February 2011 to June 2012 fifty-five fractures of humeral shaft were treated at orthopedicdepartment in the ALKindyteaching hospital. 22 fractures considered suitable for the study. The patients treatedconservatively by using the‘U’ shaped coaptation slab. Then we shift to POP c

In this study, 158 clinical samples were collected from hospitalized burn patients during the period from December 2012 to June 2013 in Karbala province\ Iraq. Bacterial isolates were identified using conventional biochemical tests and then identification was confirmed by using Vitek-2 compact system. Pseudomonas aeruginosa recovery was 60 isolates in this study. These isolates were analyzed for antibiotic susceptibility by the disk diffusion test (DDT) according to Kirby Bauer's method using seven clinically important antipseudomonal agents: carbapenems (Imipenem and Meropenem), pencillins (Piperacillin), cephalosporins (Ceftazidim), monobactam (Aztreonam), quinolones (Ciprofloxacin) and aminoglycosides (Gentamicin). The results of resista

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al