The aim of this study is to find a relationship between oxidative stress and adiponectin in Iraqi patients with acromegaly. The present study included 30 patients with acromegaly disease attending at Al-Yarmuk teaching hospital , and 30 healthy individuals as a control group.The two groups with ages ranging (30-55) years. The results revealed a highly significant elevation in all parameters (GH,IGF-1 , adiponectin , malondialdehyde , and peroxynitrite ) levels in sera of patients when compared with healthy control .It can be concluded that oxidative stress (malondialdehyde and peroxynitrite ) may be valuable in detecting of endocrine diseases like acromegaly .

The aim of this study is to find a relationship between oxidative stress and adiponectin in Iraqi patients with acromegaly. The present study included 30 patients with acromegaly disease attending at Al-Yarmuk teaching hospital , and 30 healthy individuals as a control group.The two groups with ages ranging (30-55) years. The results revealed a highly significant elevation in all parameters (GH,IGF-1 , adiponectin , malondialdehyde , and peroxynitrite ) levels in sera of patients when compared with healthy control .It can be concluded that oxidative stress (malondialdehyde and peroxynitrite ) may be valuable in detecting of endocrine diseases like acromegaly .

Background & objective: Difficult intubation remains a risk for patients undergoing general anesthesia (GA) or mechanical ventilation in an intensive care unit (ICU). Macroglossia is a known factor for difficult intubation. But it is not routine to assess the tongue size to predict difficult intubation. Studies are found deficient in comparing usefulness of measuring thyromental distance and the tongue thickness (TT) measured by ultrasonography to estimate difficult intubation. We compared tongue thickness measured by ultrasonography and thyromental distance as a means to anticipate difficult intubation. Methodology: A convenient sample of 60 patients; 32 males and 28 females, who were undergoing elective surgery with GA were i

The second most commonly diagnosed cancer is colorectal cancer (CRC) is in female. The levels of progranulin, obestatin and liver enzymes including ALT, AST and ALP were measured in forty five sera in female patients suffering from CRC before chemotherapy initiation treatment as G1, G2 after first chemotherapy cycle and G3 after second chemotherapy cycle compared with thirty female as a healthy control G4. Results showed a high significant increased in progranulin concentration and a high significant decrease in obestatin in G2 than other groups. The correlation between progranulin and ALP was a significant negative (-ve) relation while obestatin with AST gave a significant positive (+ve) correlation in G. The results also showed non signif

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

The blade pitch angle (BPA) in wind turbine (WT) is controlled to maximize output power generation above the rated wind speed (WS). In this paper, four types of controllers are suggested and compared for BPA controller in WT: PID controller (PIDC), type-1 fuzzy logic controller (T1-FLC), type-2 fuzzy logic controller (T2-FLC), and hybrid fuzzy-PID controller (FPIDC). The Mamdani and Sugeno fuzzy inference systems (FIS) have been compared to find the best inference system used in FLC. Genetic algorithm (GA) and Particle swarm optimization algorithm (PSO) are used to find the optimal tuning of the PID parameter. The results of500-kw horizontal-axis wind turbine show that PIDC based on PSO can reduced 2.81% in summation error of power

Wireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener