Hyperthyroidism or thyrotoxicosis occurs due to excess release of thyroid hormone. These hormones regulate the body’s energy balance and have effects on adipokine level. There are several reports suggesting interrelation between adipokines (resistin and leptin) with thyroid dysfunction. Objectives: This study was established to investigate the effect of thyroid hormones in hyperthyroidism state on the level of some adipokines, leptin and resistin; in comparison with control. Patients and Methods: The present study included 50 Iraqi female patients with hyperthyroidism with age ranged between 30-58 years and 30 healthy controls with age ranged between 30-53 years. Serum samples were collected from study groups. The levels of thyroid hormones (TSH, T4 and T3) were determined by using automated Chemiluminescence Immunoassay (CLIA) analysis system. Detection of leptin hormone and resistin hormone levels in the serum were determined by an enzyme linked immunosorbent assay (ELISA) kits. Results: The results revealed that serum leptin levels were significantly low (P<0.004) in hyperthyroid patient groups as compared to control, and there were significant negative correlations between T4 and leptin (P<0.0001); also, T3 and leptin (P<0.05). Resistin hormone level increased non-significantly (P˃0.05) than control level; and there was significant negative correlation between TSH and resistin (P<0.035). Conclusion: The study shows that there is complex interrelation between adipocytokines (leptin and resistin) with thyroid gland and pituitary gland. Leptin levels were decreased in hyperthyroid patients than control and associated negatively with T4 and T3 levels, while resistin levels were increased non-significantly than control and associated negatively with TSH level. They affect each other in their physiological function in the human body.
The objective of the current research is to find an optimum design of hybrid laminated moderate thick composite plates with static constraint. The stacking sequence and ply angle is required for optimization to achieve minimum deflection for hybrid laminated composite plates consist of glass and carbon long fibers reinforcements that impeded in epoxy matrix with known plates dimension and loading. The analysis of plate is by adopting the first-order shear deformation theory and using Navier's solution with Genetic Algorithm to approach the current objective. A program written with MATLAB to find best stacking sequence and ply angles that give minimum deflection, and the results comparing with ANSYS.
In this work, an efficient energy management (EEM) approach is proposed to merge IoT technology to enhance electric smart meters by working together to satisfy the best result of the electricity customer's consumption. This proposed system is called an integrated Internet of things for electrical smart meter (2IOT-ESM) architecture. The electric smart meter (ESM) is the first and most important technique used to measure the active power, current, and energy consumption for the house’s loads. At the same time, the effectiveness of this work includes equipping ESM with an additional storage capacity that ensures that the measurements are not lost in the event of a failure or sudden outage in WiFi network. Then then these
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Microencapsulation is used to modify and retard drug release as well as to overcome the unpleasant effect
(gastrointestinal disturbances) which are associated with repeated and overdose of ibuprofen per day.
So that, a newly developed method of microencapsulation was utilized (a modified organic method) through a
modification of aqueous colloidal polymer dispersion method using ethylcellulose and sodium alginate coating materials to
prepare a sustained release ibuprofen microcapsules.
The effect of core : wall ratio on the percent yield and encapsulation efficiency of prepared microcapsules was low, whereas
, the release of drug from prepared microcapsules was affected by core: wall ratio ,proportion of coa
The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of
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