The acute phase response is a major pathophysiologic phenomenon that accompanies inflammation whether acute or chronic. Complement (C3 and C4) and C - reactive protein (CRP) are positive acute phase proteins (+ ve APPs ). Their production takes place in hepatocyte and the blood concentration of these parameters are increased in osteoarthritis (OA). Chloroquine (CQ) is a diprotic weak base traditionally used to treat malaria. Recently the phosphate salt of CQ is used to decrease this type of (+ve APPs) . In this study,  patients who suffered from knee osteoarthritis (KOA) are treated with oral dosage form of chloroquine phosphate (CQP) for one month, twice daily. Our results demonstrate that CQP improves the patient status by decreas

Background : Coronary artery disease is theunderlying cause in approximately two thirds of
patients with systolic heart failure ;
Coronary artery angiogriphy may be useful to
define the presence ,
Anatomical characteristics ,and functional
significance of Coronary artery disease in
selected heart failure patients with or without signs
and aymptoms of Coronary artery disease.
Objectives: to verify the clinical usefulness of
coronary angiography (CA) in congestive heart
failure (CHF) patients with no history of ischemic
heart disease and to identify predictive factors for
performing coronary angiography to patients with
congestive heart failure with no obvious ischemia.
Methods :this is a cross-ses

Rheumatoid arthritis (RA) is characterized by persistent joint inflammation, which is a defining feature of this chronic inflammatory condition. Considerable advancements have been made in the field of disease-modifying anti-rheumatic medicines (DMARDs), which effectively mitigate inflammation and forestall further joint deterioration. Anti-tumor necrosis factor-alpha (TNF-α) drugs, which are a class of biological DMARDs (bDMARDs), have been efficaciously employed in the treatment of RA in recent times Adalimumab, a TNF inhibitor, has demonstrated significant efficacy in reducing disease symptoms and halting disease progression in patients with RA. However, its use is associated with major side effects and high costs. In addition,

Background: The treatment of an ovarian cyst relies on its nature, the discrimination of benign and malignant cysts is, therefore of crucial importance, and in spite of the continuous improvement of diagnostic means, it remains sometimes impossible to differentiate functional from organic (malignant or not) ovarian cysts. The therapeutic decision will search for the main midway between cancer’s negligence and the fear of performing an unnecessary surgical operation for an ovarian cyst.Objective: To review of 116 cases of ovarian cystic diseases aiming in identify proper management and reducing unnecessary surgical intervention.Methods: A retrospective study was conducted at Al-Elwiya maternity teaching hospital/ Baghdad/ Iraq. One hund

Introduction and Aim: Graves ophthalmopathy is one of the pandemic public health disorders in Iraq. The current investigation attempts to determine the variation in the complete total blood cells on the recovery of individuals with Graves' ophthalmopathy following low and high-dose Radioactive Iodine 131 (RI-131) exposures.   Materials and Methods: The complete blood CBC level in people with Graves' illness and healthy, normal controls were quantitatively identified using the CBC counter. Thyroid stimulating hormone was utilized to compare the recovery of ophthalmopathy patients in comparison to a control group.    Results: In comparison to healthy controls, patients with Graves' ophthalmopathy disease who received 10 mci of RAI-

ECG is an important tool for the primary diagnosis of heart diseases, which shows the electrophysiology of the heart. In our method, a single maternal abdominal ECG signal is taken as an input signal and the maternal P-QRS-T complexes of original signal is averaged and repeated and taken as a reference signal. LMS and RLS adaptive filters algorithms are applied. The results showed that the fetal ECGs have been successfully detected. The accuracy of Daisy database was up to 84% of LMS and 88% of RLS while PhysioNet was up to 98% and 96% for LMS and RLS respectively.

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

The aim of the present study was to distinguish between healthy children and those with epilepsy by electroencephalography (EEG). Two biomarkers including Hurst exponents (H) and Tsallis entropy (TE) were used to investigate the background activity of EEG of 10 healthy children and 10 with epilepsy. EEG artifacts were removed using Savitzky-Golay (SG) filter. As it hypothesize, there was a significant changes in irregularity and complexity in epileptic EEG in comparison with healthy control subjects using t-test (p< 0.05). The increasing in complexity changes were observed in H and TE results of epileptic subjects make them suggested EEG biomarker associated with epilepsy and a reliable tool for detection and identification of this di

With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect