The B-type Raf kinase (BRAF) is a member of RAS\RAF\MEK\ERK pathway and this pathway can lead to increased cellular growth, invasion and metastasis. The mutated BRAF protein activates MAPK signaling pathway, results in abnormal cellular growth, apoptosis resistance, tumor progression and metastasis. Pan-BRAF is one of available BRAF monoclonal antibodies and shared by both the wild and mutant BRAF.BRAF status is mostly determined by DNA sequencing methods. In this investigation we assessed the monoclonal Pan BRAF specific antibody that can identify wild and mutant type proteins together in formalin-fixed paraffin-embedded thyroid tumor tissues by Immunohistochemistry (IHC). Archival thyroid samples from 43 iraqi patients were immunohisto

Reactive arthritis (ReA) is an incendiary joint inflammation that occurs few days to weeks after a gastrointestinal or genitourinary infection. The etiology of the disease is not well-known. Therefore, the present study included 80 females and 25 males, divided into 51 patients with reactive arthritis and 54 healthy individuals as control group.  The study involved the detection of serum levels of anti-rheumatoid factor and anti-cyclic citrullinated peptide antibodies (anti-CCP) as well as those of CRP and C3 in all subjects. In addition, EBV levels were detected by Real Time-PCR technique. The results showed significantly increased levels (P < 0.05) of CRP, C3 and anti-CCP Ab in ReA patients’ group compared to th

Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin

Psoriasis is a common, chronic, immune-mediated skin disease with systemic pro-inflammatory activation.  This study was designed to estimate the level of two cytokines, Interleukin-36 (IL-36) and Interleukin-10 (IL-10), in psoriasis female patients. The study was accomplished on 50 Iraqi patients with psoriasis who were referred to the consulting clinic at Al-Yarmouk Teaching Hospital during the period from November 2018 to March 2019. These patients were diagnosed under the supervision of dermatologists. For the purpose of comparison, the study included 30 healthy women as a healthy control group. The serum levels of cytokines  were measured using the enzyme-linked immunosorbent technique (ELISA).The results of this study show

Human cytomegalovirus (HCMV) infection is ubiquitous and successfully reactivated in patients with immune dysfunction as in patient with multiple myeloma (MM), causing a wide range of life-threatening diseases. Early detection of HCMV and significant advances in MM management has amended patient outcomes and prolonged survival rates.

The fingerprints are the more utilized biometric feature for person identification and verification. The fingerprint is easy to understand compare to another existing biometric type such as voice, face. It is capable to create a very high recognition rate for human recognition. In this paper the geometric rotation transform is applied on fingerprint image to obtain a new level of features to represent the finger characteristics and to use for personal identification; the local features are used for their ability to reflect the statistical behavior of fingerprint variation at fingerprint image. The proposed fingerprint system contains three main stages, they are: (i) preprocessing, (ii) feature extraction, and (iii) matching. The preprocessi

      The modern systems that have been based upon the hash function are more suitable compared to the conventional systems; however, the complicated algorithms for the generation of the invertible functions have a high level of time consumption. With the use of the GAs, the key strength is enhanced, which results in ultimately making the entire algorithm sufficient. Initially, the process of the key generation is performed by using the results of n-queen problem that is solved by the genetic algorithm, with the use of a random number generator and through the application of the GA operations. Ultimately, the encryption of the data is performed with the use of the Modified Reverse Encryption Algorithm (MREA). It was noticed that the

Magnesium-doped Zinc oxide (ZnO: Mg) nanorods (NRs) films and pure Zinc oxide deposited on the p-silicon substrates were prepared by hydrothermal method. The doping level of the Mg concentration (atoms ratio of Mg to Zn was chosen to be 0.75% and 1.5%. X-ray diffraction (XRD) and energy-dispersive X-ray spectroscopy (EDX) were performed to characterize the prepared films. X-ray diffraction analysis showed a decrease in the lattice parameters of the Mg-doped ZnO NRs. Under 10V applied bias voltage, the responsivity of p-n junction UV photodiode based on pure ZnO and Mg: ZnO with doping ratio (0.75% and 1.5%) was 0.06 A/W and (0.15A/W and 0.27A/W) at UV illumination of wavelength 365 nm respectively, 0.071 A/W and (0.084A/W and 0.11A/W) fo

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database