This work studies the role of serum apelin-36 and Glutathione S-transferases (GST) activity in association with the hormonal, metabolic profiles and their link to the risk of cardiovascular disease (CVD) in healthy and patients' ladies with polycystic ovary syndrome (PCOS). A total of fifty-four (PCOS) patients and thirty-one healthy woman as a control have been studied. The PCOS patients were subdivided on the basis of body-mass-index (BMI), into 2-subgroups (the first group was obese-PCOS with BMI ≥ 30 and the second group was non-obese PCOS MBI<30). Fasting-insulin-levels and Lipid-profile, Homeostatic-model assessment-of-insulin-resistance (HOMA-IR), follicle-stimulating-hormone (FSH), luteinizing-hormone (LH), testosterone and

KE Sharquie, JR Al-Rawi, AA Noaimi, RA Al-Khammasi, Iraqi Journal of Community Medicine, 2018

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

Therapeutically and prophylactically using Microspheres containing doxycycline isolated from shell of shrimp. Low molecule weight poly lactic acid was prepared. In this study, Poly lactic acid (PLA)/ poly vinyl alcohol (PVA)/poly ethyleneglycol(PEG) loading doxycycline blend solutions was prepared. Also Poly lactic acid (PLA)-Tannin blend via solvent evaporation method was prepared. Microspheres of chitosan/gelatin microsphere loading doxycycline was prepared by emulsion crosslinking technique. Both microsphere and blends were characterized by Fourier transform infrared (FTIR) spectrophotometer. The FTIR spectra were shown distinguish bands. The in vitro release of doxcycline from its matrix at pH 7 was studied. The prophylactic

Abstract Objective: The underlying molecular basis of ischemic heart diseases (IHDs) has not yet been studied among Iraqi people. This study determined the frequency and types of some cardiovascular genetic risk factors among Iraqi patients with IHDs. Methods: This is a cross-sectional study recruiting 56 patients with acute IHD during a 2-month period excluding patients >50 years and patients with documented hyperlipidemia. Their ages ranged between 18 and 50 years; males were 54 and females were only 2. Peripheral blood samples were aspirated from all patients for troponin I and DNA testing. Molecular analysis to detect 12 common cardiovascular genetic risk factors using CVD StripAssay® (ViennaLab Diagnostics GmbH, Austria) was performed

The present research aimed to study the polymorphisms of the chicken insulin-like growth factor 2 (IGF2) in two commercial broiler breeds (Cobb 500 and Hubbard F-15). In total, 300 avian blood samples were obtained. The genomic DNA was isolated using a fast salt-extraction technique. Moreover, polymerase chain reaction (PCR) was used to amplify 1146 bp fragments of the gene. The amplified fragments were subjected to restriction enzyme digestion using the HinfI endonuclease enzyme, and the digested products were separated on a 2% agarose gel. The findings indicated that there were two alleles, T and C, for the target locus, with frequencies of 73.3% and 26.7%, respectively. Three distinct genotype variations, TT, TC, and CC, were found, with

Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was ad