Mefenamic acid (MA) is one of the non-steroidal anti-inflammatory drugs, it is widely used probably due to having both anti-inflammatory and analgesic activity, the main side effects of mefenamic acid include gastrointestinal tract (GIT) disturbance mainly diarrhea, peptic ulceration, and gastric bleeding. The analgesic effects of NSAIDs are probably linked to COX-2 inhibition, while COX-1 inhibition is the major cause of this classic adverse effects. Introduction of thiazolidinone may lead to the increase in the bulkiness leads to the preferential inhibition of COX-2 rather than COX-1 enzyme. The study aimed to synthesize derivatives of mefenamic acid with more potency and to decrease the drug's potential side effects, new series of 4-t

The research seeks to identify the impact of fraud detection skills in the settlement of compensatory claims for the fire and accident insurance portfolio and the reflection of these skills in preventing and reducing the payment of undue compensation to some who seek profit and enrichment at the expense of the insurance contract. And compensatory claims in the portfolio of fire and accident insurance in the two research companies, which show the effect and positive return of the detection skills and settlement of the compensation on the amount of actual compensation against the claims inflated by some of the insured, The research sample consisted of (70) respondents from a community size (85) individuals between the director and assistan

Rheumatoid arthritis (RA) is one of the autoimmune diseases characterized by the synovial inflammation which causes organs and tissues damage especially synovial tissues and joints. The study included 50 serum samples from patients with rheumatoid arthritis (RA) when compared with 50 serum samples from healthy individuals as control with age range 35 – 60 years (41.3 ± 2.4 years vs. 41.0 ± 2.0 years, respectively). ELISA technique was used to assess the Anti-cyclic citrullinated peptide IgG antibody (anti-CCP IgG Ab) level, anti-rheumatoid factor IgG antibody (anti-RF IgG) and anti-Cytomegalovirus (anti-CMV IgG) antibodies frequencies in the studied groups. The present findings demonstrated that all RA patients have 100% seropositive fr

Objectives: Many medication errors occur in the hospital, and these can endanger patients. The purpose of this study was to evaluate the incidence of medication errors in hospitalized patients, and to categorize the most frequent types of errors, and to asses the possible measures that may prevent the occurrence of such errors.
Methods: A prospective, exploratory, and evaluative study, using direct observation method to detect medication errors in adult hospitalized patients in medical and surgical units in Baquba Teaching Hospital- Diyala-Iraq.. The files of 299 patients had been reviewed from July 2009 to September 2009, including medication orders and treatment sheets to detect existing errors. The detected errors were recorded and

Copper (Cu) Zinc (Zn) and Magnesium (Mg) in serum, RBC, urine and dialyzate fluids were
studied in 39 patients, who have been undergoing chronic haemodialysis treatment. They were
divided in to polyuric , oliguric and anuric depending on their urinary output. Elevated serum and
RBC Mg was observed before dialysis, while decreased serum and RBC level was noticed except
serum Mg of polyuric patients. Before dialysis elevated serum and RBC Zn were observed. While
after dialysis these parameters were increased. Normal RBC Cu value before dialysis was observed.
While low serum Cu was noticed. After dialysis serum Cu showed raised value, while RBC level
decreased in oliguric and increased in polyuric patients. Zn / Cu rati

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

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