Nandrolone decanoate safely combats catabolism in burned patients: A new potential indication after recall
Introduction: The hyper-catabolic state is a devastating pathophysiological response to severe injury, infection or burns. Nandrolone decanoate (ND) is a potent anabolic steroid have many clinical indications, but not investigated in burn injuries yet. Patients and methods: A prospective randomized control study included 40 burned patients who were treated in Burn unit from burn injuries ranged from 20 to 40%. Both groups are objectively assessed, clinically and laboratory during treatment period till full recovery from burns’ injury. Recall assessment of the drug safety after many years is
Association between long noncoding RNA taurine-upregulated gene 1 and microRNA-377 in vitiligo
Background: Taurine-upregulated gene 1 (TUG1) is one of the long noncoding RNAs (lncRNAs) that plays a role in melanogenesis. MicroRNA-377 (miRNA-377) is a conserved noncoding RNA that regulates angiogenesis and promotes oxidative stress. Peroxisome proliferator-activated receptors (PPARs) are components of the nuclear hormone receptor superfamily. PPAR-γ activators stimulate melanogenesis. Interleukin (IL)-17 has been implicated in the pathogenesis of several immunological diseases. This work aimed at detecting the expression levels of lncRNA TUG1, miRNA-377, PPAR-γ, and IL-17 among vitiligo
Support for increased cardiovascular risk in non-segmental vitiligo among Egyptians: A hospital-based, case–control study
Background: Data have been accumulating in the past few years that identify vitiligo as a disorder with systemic implications. Results and methods: In this hospital-based, cross-sectional, case–control study, 50 patients with non-segmental vitiligo and 50 age- and sex-matched controls underwent analysis of serum lipid profile, oxidative stress biomarkers and carotid duplex. Hydrogen peroxide (H2O2) and malondialdehyde (MDA) were significantly higher in patients than controls (p-value <.001, <.001, respectively); on the other hand, total antioxidant capacity (TAC) was significantly lower in
Salinity stress reveals three types of RNA editing sites in mitochondrial Nad7 gene of wild barley both in silico and in qRT-PCR experiments
Cellular respiration is an important process performed by mitochondria. Nad complex is the major complex involved in this process and one of the main subunits in this complex is the nad7 (nad dehydrogenase subunit 7). In Hordeum vulgare subsp. spontaneum, four nad7 cDNAs are described at 500 mM salinity, 0 h, or control (GenBank accession no. MW433884), after 2 h (GenBank accession no. MW433885), after 12 h (GenBank accession no. MW433886) and after 24 h (GenBank accession no. MW433887). Twenty six RNA editing sites were revealed in positions: C44, C45, C77, C83, C99, C137, C224, C244, C251
Improved Production Key Performance Indicators (KPI’s) Using Intelligent-Manufacturing Execution Systems (I-MES)
The aim of this research is to reduce the gap between manufacture expertise and management expertise by using modern technology like Manufacturing Execution System (MES) via Artificial Intelligence (AI) and Machin Learning (ML). A design of MES has been proposed and implemented on El-Araby Plastic Injection Molding (PIM) factory. This work is based on the International Society of Automation Standard (ISA-S95). A fully automated data management system has been designed and implemented to control data follow between shop floor e.g. (machines and operators) and management floor e.g. (production
Fractional canny edge detection for biomedical applications
This paper presents a comparative study of edge detection algorithms based on integer and fractional order differentiation. A performance comparison of the two algorithms has been proposed. Then, a soft computing technique has been applied to both algorithms for better edge detection. From the simulations, it shows that better performance is obtained compared to the classical approach. The noise performances of those algorithms are analyzed upon the addition of random Gaussian noise, as well as the addition of salt and pepper noise. The performance has been compared to peak signal to noise
Study of Energy Harvesters for Wearable Devices
Energy harvesting was and still an important point of research. Batteries have been utilized for a long time, but they are now not compatible with the downsizing of technology. Also, their need to be recharged and changed periodically is not very desirable, therefore over the years energy harvesting from the environment and the human body have been investigated. Three energy harvesting methods which are the Piezoelectric energy harvesters, the Enzymatic Biofuel cells, and Triboelectric nanogenerators (TENGs) are being discussed in the paper. Although Biofuel cells have been investigated for a
Neuro-fuzzy system for 3-dof parallel robot manipulator
Planar Parallel manipulators (PPMs) are widely used these days, as they have many advantages compared to their serial counterparts. However, their inverse and direct kinematics are hard to obtain, due to the complexity of the manipulators' behavior. Therefore, this paper provides a comparative analysis for two methods that were used to obtain the inverse kinematics of a 3-RRR manipulator. Instead of the conventional algebraic and graphical methods used for attaining the mathematical models for such manipulators, an adaptive neuro-fuzzy inference structure (AFNIS) model was alternatively
Neural Network Based Switching State Selection for Direct Power Control of Three Phase PWM-Rectifier
This article proposes an intelligent approach to the Direct Power Control technique of the PWM rectifier, this control technique improves the performance of PWM converter, called Direct Power Control Based on Artificial Neural Network (ANN), applied for the selection of the optimal control vector. DPC-ANN ensures smooth control of active and reactive power in all Sectors and reduces current ripple. Finally, the developed DPC was tested by simulation, the simulation results proved the excellent performance of the proposed DPC scheme. © 2018 IEEE.
Stochastic travelling advisor problem simulation with a case study: A novel binary gaining-sharing knowledge-based optimization algorithm
This article proposes a new problem which is called the Stochastic Travelling Advisor Problem (STAP) in network optimization, and it is defined for an advisory group who wants to choose a subset of candidate workplaces comprising the most profitable route within the time limit of day working hours. A nonlinear binary mathematical model is formulated and a real application case study in the occupational health and safety field is presented. The problem has a stochastic nature in travelling and advising times since the deterministic models are not appropriate for such real-life problems. The
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