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Background: Double diabetes is the term used to describe situations in which a patient exhibits characteristics that are a combination of type 1 and type 2 Diabetes Mellitus. Metalloendopeptidase or Neprilysin is membrane-bound metallopeptidase. It has a wide range of physiological function and a variety of substrates. It has a significant impact on the proteolytic functions of the kidney, cardiovascular health, immunological response, cell proliferation, and fetal development. It also has a preventative effect on the onset of type 2 diabetes, obesity, and cancer. Objective: The study aims to assess the level of MEP in patients with double diabetes and determine its predictive value in the diagnosis of double diabetes. Subjects and Methods: Eighty participants were divided into two groups for this study. 40 patients with double diabetes made up the first group (G1), whereas 40 age- and gender-matched apparently healthy subjects made up the second group (G2), which served as the control group. ELISA was used to measure the serum's metalloendopeptidase level. For the measurement of HbA1c, whole blood was used. The measurement of insulin, blood glucose, and lipid profile were performed using serum. The HOMA test measured insulin resistance. Results: This study revealed a significant elevation in serum metalloendopeptidase levels in patients with DD (p value < 0.05). The ROC curves analysis for serum metalloendopeptidase level showed the area under the curve (AUC) of serum metalloendopeptidase (pg/mL) was 0.992. Conclusions: Serum metalloendopeptidase level could be used as a novel biomarker in patients with double diabetes. |
In this paper, a discretization of a three-dimensional fractional-order prey-predator model has been investigated with Holling type III functional response. All its fixed points are determined; also, their local stability is investigated. We extend the discretized system to an optimal control problem to get the optimal harvesting amount. For this, the discrete-time Pontryagin’s maximum principle is used. Finally, numerical simulation results are given to confirm the theoretical outputs as well as to solve the optimality problem.
In this paper, a discrete SIS epidemic model with immigrant and treatment effects is proposed. Stability analysis of the endemic equilibria and disease-free is presented. Numerical simulations are conformed the theoretical results, and it is illustrated how the immigrants, as well as treatment effects, change current model behavior
The study evaluates the incidence of inferior alveolar nerve injuries in mandibular fractures, the duration of their recovery, and the factors associated with them. Fifty-two patients with mandibular fractures involving the ramus, angle, and body regions were included in this study; the inferior alveolar nerve was examined for neurological deficit posttraumatically using sharp/blunt differentiation method, and during the follow-up period the progression of neural recovery was assessed. The incidence of neural injury of the inferior alveolar nerve was 42.3%, comminuted and displaced linear fractures were associated with higher incidence of inferior alveolar nerve injury and prolonged recovery time, and recovery of inferior alveolar nerve fun
... Show MoreIn this paper, simulation studies and applications of the New Weibull-Inverse Lomax (NWIL) distribution were presented. In the simulation studies, different sample sizes ranging from 30, 50, 100, 200, 300, to 500 were considered. Also, 1,000 replications were considered for the experiment. NWIL is a fat tail distribution. Higher moments are not easily derived except with some approximations. However, the estimates have higher precisions with low variances. Finally, the usefulness of the NWIL distribution was illustrated by fitting two data sets
This paper deals with constructing a model of fuzzy linear programming with application on fuels product of Dura- refinery , which consist of seven products that have direct effect ondaily consumption . After Building the model which consist of objective function represents the selling prices ofthe products and fuzzy productions constraints and fuzzy demand constraints addition to production requirements constraints , we used program of ( WIN QSB ) to find the optimal solution
The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue
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