Background: Endometrial Cancer (EC) is the malignant tumor originating from endometrium cell (lining of the uterus). EC incidence and mortality have increased in recent years. Routinely used methods for EC diagnosis and treatment are histopathological tissue culture after surgery and postoperative radiotherapy, however there is still not enough efficient treatment for recurrence or progression of this disease. So, there is a critical need for further EC identification by new biological ways for the prognostic diagnosis of it. Objective: This study aimed to look for ways by which could help in diagnosis of EC before the hysterectomy. Materials and Methods: 55 patients with EC and 57 healthy women were involved in this study (up to 45 years)

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

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.

Background : The aim of this work is to study the clinical features and causative fungi of tinea pedis in diabetic and non-diabetic patients. Result : Tinea pedis was estimated to be the second most common skin disease in the United States, after acne. Up to 15% of the U.S., population may have tinea pedis. Across Europe and East Asia, prevalence rates reach 20 %. Methods: The Complete history taking regarding: age, sex, occupation, residency, history of diabetes and diabetic profile (fasting blood sugar and post prandial).and Clinical examination of the feet Aim of the study : The aim of this work was to study the clinical features and causative fungi of tinea pedis in diabetic and non-diabetic patients Conclusion : Tinea pedis is more

Cutaneous leishmaniasis (CL) is a widespread, yet often overlooked, parasitic disease caused by the Leishmania protozoan, which is prevalent in numerous countries, including Iraq. This condition is marked by the appearance of skin lesions on various exposed areas of the body. In most old-world regions, sodium stibogluconate (SSG) is the classical widely used drug to treat CL. The progression of skin ulceration is controlled by different inflammatory modulators including cytokines and enzymes. In this study, the possible role of the enzyme Matrix metalloproteinase9 (MMP-9) and its inhibitor Metallopeptidase inhibitor-1 (TIMP-1) as immunological markers was evaluated in CL patients suffering from cutaneous leishmaniasis before and aft

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

The major of DDoS attacks use TCP protocol and the TCP SYN flooding attack is the most common one among them. The SYN Cookie mechanism is used to defend against the TCP SYN flooding attack. It is an effective defense, but it has a disadvantage of high calculations and it doesn’t differentiate spoofed packets from legitimate packets. Therefore, filtering the spoofed packet can effectively enhance the SYN Cookie activity. Hop Count Filtering (HCF) is another mechanism used at the server side to filter spoofed packets. This mechanism has a drawback of being not a perfect and final solution in defending against the TCP SYN flooding attack. An enhanced mechanism of Integrating and combining the SYN Cookie with Hop Count Filtering (HCF) mech

With the development of communication technologies for mobile devices and electronic communications, and went to the world of e-government, e-commerce and e-banking. It became necessary to control these activities from exposure to intrusion or misuse and to provide protection to them, so it's important to design powerful and efficient systems-do-this-purpose. It this paper it has been used several varieties of algorithm selection passive immune algorithm selection passive with real values, algorithm selection with passive detectors with a radius fixed, algorithm selection with passive detectors, variable- sized intrusion detection network type misuse where the algorithm generates a set of detectors to distinguish the self-samples. Practica

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.