Primary and secondary response loss , often mediated by the development of anti-drug antibodies (ADAs), limit treatment efficacy. Therapeutic drug monitoring (TDM) is important in optimizing infliximab therapy by correlating drug level with clinical outcomes. This study aimed to find the relationship between infliximab level, ADA presence, and clinical activity in Iraqi Crohn's disease (CD) patients. This cross-sectional study included adult Crohn's disease patients receiving maintenance infliximab (IFX) treatment. Data on demographics and clinical characteristics were collected. Infliximab level and ADA were measured using ELISA. Forty-three patients were included. Patients in remission had significantly higher infliximab levels and lower

Background: Rheumatoid arthritis is an autoimmune disease that affects mainly the synovial membranes and articular structures and is characterized by chronic, systemic inflammation involving multiple joints.Being a synovial joint, the Temporomandibular Joint is subject to the same disorders affecting other synovial joints, including RA.Beside it was considered as a specific serological marker for diagnosing RA disease ,antibodies to cyclic citrullinated peptide have proven to be associated with joints destruction, though; it may play a potential role in the prediction of the disease severity. Materials and Methods: Sixty nine individuals (69) were enrolled in this study, forty nine (49) were patients diagnosed with Rheumatoid Arthritis, a

         Long-term use of sulfonylureas including chlorpropamide, is known to potentiate the antidiuretic action of arginine vasopressin (AVP), predisposing to hyponatremia.The present study was designed to evaluate the effect of long term use of glibenclamide on serum and urinary levels of sodium and potassium in Type 2 DM patients in Iraqi DM centers. Ninety eight patients with Type 2 DM who were maintained on different doses of glibenclamide for at least 1 year, attending the centre for Diabetes and Endocrinology in Al-Rusafa, Baghdad, were enrolled in the study, in addition to 15 normal healthy subjects. Patients were allocated into three groups according to the dose of glibenc

Rheumatoid arthritis is an autoimmune diseasecharacterized by chronic inflammationthat affects joints and cartilage. Bone complications such asRA-relatedosteoporosis are one of the most extra-articular manifestations. Many inflammatory mediators are released during RA disease pathophysiology; these mediators stimulate osteoclast genesis of bone by direct effects on RANKL and OPG. The study aimedto measure RANKL, OPG in RA patients treated with Etanercept only and other groups treated with Methotrexate onlyat baseline and after three months to evaluate bone state. An observational case-control prospective study was done on 30 RA patients who received MTX, 30 RA patients who received ETN, and 30 healthy,age-matched control groups. The

Objective: Using green chemistry, an effective, inexpensive, and environmentally safe method, sulfur nanoparticles with specific properties can be prepared and used in nanotechnology. This research aimed to prepare sulfur nanoparticles from chilli pepper extract and determine their effectiveness against colon cancer. Method: Chilli pepper extract obtained from local markets was treated with aqueous sodium thiosulfate (Na2S2O7.5H2O). After mixing, it was continuously stirred, heated, and filtered. NaBH4 was then added, resulting in a yellow precipitate. The precipitate was centrifuged, purified, and dried at 250°C. Results: Standardised tests such as UV-Vis, XRD, SEM, TEM, AFM, and EDX were used, resulting in sulfur nanoparticles with an av

<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c