493 research outputs found

    Association of interleukin-6 level and DNA polymorphism in type 2 diabetic patients in Kirkuk city

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    The basic inflammatory factor interleukin-6 plays an important role in the inflammatory response. It has been shown that IL-6 has a role in insulin resistance and T2DM. The IL-6 gene is found on chromosome 7p15-p21 in humans, it works via a receptor composed of two components, the IL-6 receptor, and gp130. Single nucleotide polymorphisms in the regulatory areas of IL-6R genes influence their expression levels and are linked to a higher risk of T2DM. There were 80 T2DM patients and 80 healthy people enrolled in the present work. Fasting blood glucose levels, HbA1C, and IL-6 concentrations were estimated in both groups. The allelic frequencies of 2 single nucleotide polymorphisms (rs2229238, rs4845625) were identified by PCR-SSP. In this study, we found that the fasting blood sugar levels, HbA1c, and IL-6 levels were statistically highly significant in patients in comparison with controls. In regarding the association of genotypic (CC, CT, TT) and allelic frequencies of rs2229238, and rs4845625 polymorphism of the gene IL6R, and prevalence of diabetes mellitus. The results of PCR-SPP products of rs2229238 (C/T) of the IL6R gene indicated the significant correlation the rs4845625 IL6R polymorphism with T2DM, where no significant association was observed between these genotypes (CC, CT, TT) and allelic (T) frequencies of rs2229238 as a risk factor and T2D

    Intravenous Lidocaine Infusion with Single Low-Dose Ketamine as an Adjuvant to General Anesthesia in Posterior Spine Fusion

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    Background: Posterior spinal fusion (PSF) is a common surgical operation used to correct degeneration of the lumbar spine with considerable postoperative pain. The primary objective of this study is to compare the total intraoperative and postoperative opioid consumption and numeric pain scale during the first 24 hours after surgery between the lidocaine/ketamine group and the narcotic-only group. Materials and Methods: Sixty adult patients (age 18–65 years) scheduled for elective PSF were included. Patients were divided randomly into either the lidocaine/ketamine group (LK group), who received lidocaine and ketamine injection in addition to usual perioperative narcotic analgesia, and the narcotic-only group (N group) who depended on narcotics only. The primary outcome measures were total intraoperative and postoperative opioid consumption and pain scores during the first 24 hours postoperatively. The secondary outcome measures were sedation score, intravenous rescue analgesia, postoperative nausea and vomiting, and pruritis during the first 24 hours postoperatively. Results: Patients in the LK group had lower intraoperative fentanyl consumption (216.3 ± 28.8 μg) than those in the N group (363 ± 35 μg). The LK group consumed less morphine during the first 24 hours after surgery (49.5 ± 6.0 mg) than the N group did (57.8 ± 8.6 mg). The LK group had lower pain scores at all-time intervals during the first 24 hours (2, 6, 12, and 24 hours) than the N group did. Conclusions: Intraoperative lidocaine infusion with low-dose ketamine reduced opioid consumption and pain scores in patients undergoing PSF

    Multilevel Thresholding for Image Segmentation Using an Improved Electromagnetism Optimization Algorithm

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    Image segmentation is considered one of the most important tasks in image processing, which has several applications in different areas such as; industry agriculture, medicine, etc. In this paper, we develop the electromagnetic optimization (EMO) algorithm based on levy function, EMO-levy, to enhance the EMO performance for determining the optimal multi-level thresholding of image segmentation. In general, EMO simulates the mechanism of attraction and repulsion between charges to develop the individuals of a population. EMO takes random samples from search space within the histogram of image, where, each sample represents each particle in EMO. The quality of each particle is assessed based on Otsu’s or Kapur objective function value. The solutions are updated using EMO operators until determine the optimal objective functions. Finally, this approach produces segmented images with optimal values for the threshold and a few number of iterations. The proposed technique is validated using different standard test images. Experimental results prove the effectiveness and superiority of the proposed algorithm for image segmentation compared with well-known optimization methods

    Developing Artificial Neural Network and Multiple Linear Regression Models to Predict the Ultimate Load Carrying Capacity of Reactive Powder Concrete Columns

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    The study focuses on development a model to predict the ultimate load carrying capacity of Reactive Powder Concrete (RPC) columns. Two different statistical methods regression techniques (RT) and the artificial neural network (ANN) methods were used for determining the RPC columns ultimate load carrying capacity. The data is collected from three experimental studies the first used to develop the model and the other two used as a case study. Experimental results used as input data to develop prediction models. Two different techniques adopted to develop the models the first was Artificial Neural Network (ANN) and the second was multi linear regression techniques (RT). The models use to predict the ultimate load carrying capacity of RPC columns. To predict the ultimate load carrying capacity of RPC columns four input parameters were identified cross-section, micro steel fiber volume fraction content, compressive strength and main steel reinforcement area. Both models build with assistance of MATLAB software. The results exhibit that the cross section area has most significant effect on ultimate load carrying capacity. The performance of ANNs with different architecture was considered to adopt the pest ANN. An ANN with one layer consist of 7 neurons provide the best prediction. The results of this investigation indicate that ANNs have strong potential as statistical method for prediction the ultimate load carrying capacity of RPC columns. Keywords: Reactive powder concrete, artificial neural network, multiple linear regressions, ultimate load carrying capacity, Statistical analysis

    Design of optimal rule-based controller for plug-in series hybrid electric vehicle

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    International audienceEnergy consumption of Hybrid Electric Vehicles (HEV) strongly depends on the adopted energy management strategy (EMS). Rule-Based (RB) controllers are the most commonly used for their ability of integration in real-time applications. Unlike global optimization routines, RB controllers do not ensure optimal energy savings. This study presents a methodology to design a close-to-optimal RB controller derived from global optimization strategies. First, dynamic programming (DP) optimization is used to derive the optimal behaviour of the powertrain components on the Worldwide Harmonized Light Vehicles Test Cycle (WLTC), and then, the resulting performance of the powertrain components is used to design an optimized RB energy management strategy. Furthermore, the strategy is developed to cope with the variations in trip length and traffic conditions. The plug-in series hybrid electric vehicle is modelled using the energetic macroscopic representation (EMR). Results show that the proposed optimal RB controller is only consuming 1-2% more fuel compared to DP controllers and is resulting in a 13-16% less fuel consumption compared to basic RB controllers

    Molecular detection of Toxoplasma gondii specific repeat element in blood of recurrent aborted women by real-time PCR

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    Toxoplasmosis caused by ingestion of raw or undercooked meat contains tissue cyst or contaminated food or water with oocyst of Toxoplasma gondii. This parasite is prevalent in humans, domestic and wild animals and is causative agent of abortion and congenital abnormalities. Methods: From october-2019 to April 2020, blood and serum samples were collected from 63 women with recurrent abortion. Serum samples were used for identification of anti-Toxoplasma IgM and IgG antibodies by ELISA technique. Real time- Polymerase Chain reaction technique utilized for revealing of the DNA of Toxoplasma gondii in the blood specimens. Presented study results showed the high aborted women 33 (52%) in age group (20-29), and high number of aborted women 36 (57%) have 3-6 abortions. Serodiagnosis results of 63 aborted women showed that 19 (30%) were seropositive for only IgG antibody, 6(10%) were seropositive for IgM antibody, and 6 (10%) were positive for both IgG and IgM antibodies. Molecular diagnosis of T. gondii DNA infection by RT- PCR for amplification of repeat region 529 bp of T. gondii DNA, revealed that only 7 (11.1%) blood samples were positive. RT-PCR assay was more sensitive and specific than serologic ELISA method in diagnosis of Toxoplasma gondii infection in recurrent aborted women

    Direct Precipitation and Characterization of ZnO Nanoparticles

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    ZnO nanoparticles are prepared through hydrolysis and condensation of zinc acetate dihydrate by potassium hydroxide in alcoholic medium at low temperatures. Thermal gravimetric analysis (TGA) of the precursor is made in order to specify the temperature range over which the weight loss and thermal effect are significant. X-ray diffraction of the as-prepared specimens shows that the hexagonal (a=3.2459 Å, c=5.1999 Å) structure is the predominant crystallographic structure. According to Scherer’s formula, the average size of the nanoparticles is 22.4 ± 0.6 nm. The structural properties of the synthesized ZnO nanoparticles have been confirmed using the TEM micrographs. The optical energy gap of the ZnO nanoparticles, as obtained from applying Tauc’s equation, is equal to 3.52 eV, which is higher than that of the bulk material. Absorption peak of the as-prepared sample is 298 nm which is highly blue shifted as compared to the bulk (360 nm). Large optical energy gap and highly blue shifted absorption edge confirm that the prepared ZnO nanoparticle exhibits strong quantum confinement effect

    The Culture of Peace and the Prevention of Terrorism from the Perspectives of Islamic Education and the United Nations

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    Terrorism is an unfamiliar phenomenon to the Islamic religion and it is in opposition to its doctrine. It leads to the loss of innocent lives, destruction of properties, spreading rumors, terrorizing the innocents and destabilization. All this makes fighting and preventing the phenomenon of terrorism the duty of all human beings. This study aimed to highlight and clarify the concept of the culture of peace and the prevention of terrorism from the perspective of Islamic Education and the United Nations

    Effect of nitrogen fertilizer and compost rates addition at different depths on some soil chemical properties

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    Two field experiments were conducted on clay loam soil during the two successive seasons, summer season 2017 using maize plants and winter season 2017/2018 using barley plants at El-Gemmeiza Agricultural Research Station, El-Gharbia Governorate to evaluate the direct and residual effects of compost rates mixed with the surface soil layer to 10 cm or added in 30 cm mole depth, arranged in parallel orientation with respect to one another and spaced at 3 m apart besides the nitrogen fertilizer rates on improving some soil chemical properties. Furthermore economical analysis was done by calculating the net income for every treatment to determine the economical treatment. The rates of compost were 0.0, 2.5, 5.0 and 7.5 Ton fed-1, while the nitrogen rates were 0.0, 50, 75 and 100 % of the recommended dose for every growing crop. The experiments were conducted in a split-split plot in a randomized complete block design (RCBD) with three replicates. Results can be summarized as follows: 1- All treatments slightly decreased the soil reaction (pH) in the two growing seasons. 2- Soil salinity (EC), soluble cations and anions and total soluble salts (TSS) significantly increased by increasing nitrogen or compost rates and significantly decreased by increasing application depth. On the other hand, SAR values were significantly decreased with all treatments. 3- All treatments led to significant increases in Ex. Ca, Mg, K and cation exchange capacity (CEC), whereas Ex. Na and ESP were significantly decreased with all treatments in the two seasons. 4- All treatments clearly enhanced total nutrients (N. P and K) of the investigated soil. Also, Organic carbon (O.C, %) and C/N ratio were significantly increased with all treatments. 5- According to the economical analysis, the application of 5 ton compost fed-1 in 30 cm mole depth with 100 % the recommended dose of nitrogen fertilizer for every crop was the best treatment compared with the other treatments, since it gave the highest net income (16809.80 L.E fed-1). 6- Therefore, it is more useful to use those treatments (compost rates at 30cm mole depth with nitrogen fertilizer) to get a markedly improve in chemical properties which reflect on higher yield
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