Background: Hybrid diabetes (or double diabetes, DD) occur when the patient which exhibits characteristics that combine type 1 diabetes (T1DM) and type 2 diabetes (T2DM). Formerly epidemiological studies found that quarter of people with T1D also had the metabolic syndrome. Subfatin, Also called cometin, it is a small (~27kDa) cytokine secreted by protein encoded by a gene called METRNL (simeler of meteorin). is much expressed in skin in the mucosal tissues and activated macrophages. Subfatin has also been described as a hormone that effected in some diseases such as metabolic diseases (including dyslipidemia), type 2 diabetes and obesity. Objectives: The current study objective is evaluating the subfatin in the blood serum of double diabetes patients to find predictive significance of diagnosis for this disease. Subjects and methods: Eighty individuals were studied , divided them into two groups . Forty patients with double diabetes represented the first group (G1), and the second group (G2), which represented the control group, consisted of (40) individuals, and the range ages of the study were (18-60)years. Whole blood was used to determine HbA1c. Samples were centrifuged, and the obtained serum was used to evaluate other biochemical markers. The technique used to determine the level of subfatin in the blood was a quantitative sandwich enzyme-linked immunosorbent assay (ELISA). Results: A significant increase shown by this study in the serum levels of subfatin in (DD) patients (n = 40) compared with control subjects (n = 40) (p value < 0.05). The ROC curves analysis for serum subfatin level when used as test for diagnosis subjects into of double diabetes cases (G1) and control group (G2), showed the AUC ( area under curve) for serum of subfatin was (1.000) have interval of confidence (95% ) and both lower and upper bound was (1.000). Conclusions: serum subfatin level could be a used as a novel biomarker of double diabetes (DD) and may contribute to the early diagnosis of diabetes.
In this work, the geomagnetic storms that occurred during solar cycles 23 and 24 were classified based on the value of the Disturbance Storm Time index (Dst), which was considered an indicator of the strength of geomagnetic conditions. The special criterion of Dst >-50 nT was adopted in the classification process of the geomagnetic storms based on the minimum daily value of the Dst-index. The number of geomagnetic storms that occurred during the study period was counted according to the adopted criteria, including moderate storms with (Dst >-50 nT), strong storms with (Dst >-100 nT), severe storms with (Dst >-200 nT), and great storms with (Dst >-350 nT). The statistica
A genetic algorithm model coupled with artificial neural network model was developed to find the optimal values of upstream, downstream cutoff lengths, length of floor and length of downstream protection required for a hydraulic structure. These were obtained for a given maximum difference head, depth of impervious layer and degree of anisotropy. The objective function to be minimized was the cost function with relative cost coefficients for the different dimensions obtained. Constraints used were those that satisfy a factor of safety of 2 against uplift pressure failure and 3 against piping failure.
Different cases reaching 1200 were modeled and analyzed using geo-studio modeling, with different values of input variables. The soil wa
In this work, some mechanical properties of the polymer coating were improved by preparing a hybrid system containing Graphene (GR) of different weight percentages (0.25, 0.5, 1, and 2wt%) with 5wt% carbon fibres (CF) and added to a polymer coating by using casting method. The properties were improved as GR was added with further improvement on adding 5wt% of CF. The impact strength of acrylic polymer with GR increases with increasing weight ratio of GR; maximum value was obtained when the polymer coating was incorporated with 1wt% GR and 5wt% CF. The impact strength of acrylic polymer with GR and GR/CF composites incorporated with GR at 1wt% and CF at 5wt%. Hardness increase with increasing weight ratio of Gr and a significant imp
... Show MoreToxic substances have been released into water supplies in recent decades because of fast industrialization and population growth. Fenton electrochemical process has been addressed to treat wastewater which is very popular because of its high efficiency and straightforward design. One of the advanced oxidation processes (AOPs) is electro-Fenton (EF) process, and electrode material significantly affects its performance. Nickel foam was chosen as the source of electro-generated hydrogen peroxide (H2O2) due to its good characteristics. In the present study, the main goals were to explore the effects of operation parameters (FeSO4 concentration, current density, and electrolysis time) on the catalytic performance that was optimized by r
... Show MoreReservoir characterization plays a crucial role in comprehending the distribution of formation properties and fluids within heterogeneous reservoirs. This knowledge is instrumental in constructing an accurate three-dimensional model of the reservoir, facilitating predictions regarding porosity, permeability, and fluid flow distribution. Among the various methods employed for reservoir characterization, the hydraulic flow unit stands out as a widely adopted approach. By effectively subdividing the reservoir into distinct zones, each characterized by unique petrophysical and geological properties, hydraulic flow units enable comprehensive reservoir analysis. The concept of the flow unit is closely tied to the flow zone indicator, a cr
... Show MoreKE Sharquie, HM Al-Hamamy, AA Noaimi, IA Al-Shawi, Journal of the Saudi Society of Dermatology & Dermatologic Surgery, 2011 - Cited by 9
The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi
... Show MoreABSTRACT. The reaction between benzil and hexamethylenediamine formed a new ligand [L], [(1Z,3Z)-2,3-diphenyl-5,6,7,8,9,10-hexahydro-1,4-diazecine], of the type [N2], was synthesized by the condensation reaction through Schiff base reaction between benzil and hexamethylenediamine. The new Schiff base ligand reacts with Mnп, Niп and Coп metal ions to give the complexes with the general formula: [M(L)Cl2]. The elemental investigations have been used to analyze the ligand and its complexes by CHN, FT-IR, UV-Vis, TLC, mass spectrum, melting point with the study of biological activity to the formed compounds. From the data obtained, the proposed molecular structure adopts square planar structure about the metal ions. The study reveals
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