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Effects of Nigella sativa on outcome of hepatitis C in Egypt

World Journal of Gastroenterology 2013年第16期19卷 2529-2536页

作者： Eman Mahmoud Fathy Barakat Lamia Mohamed El Wakeel radwa sa.ir hagag Department of Tropical Medicine Faculty of Medicine Ain Shams University Department of Clinical Pharmacy Faculty of Pharmacy Ain Shams University Department of Clinical Pharmacy Faculty of Pharmacy Egyptian Russian University

AIM: To evaluate the safety, efficacy and tolerability of Nigella sativa (N. sativa ) in patients with hepatitis C not eligible for interferon (IFN)-α. METHODS: Thirty patients with hepatitis C virus (HCV) infection, who were not eligible for IFN/ribavirin therapy, were included in the present study. Inclusion criteria included: patients with HCV with or without cirrhosis, who had a contraindication to IFN-α therapy, or had refused or had a financial constraint to IFN-α therapy. Exclusion criteria included: patients on IFN-α therapy, infection with hepatitis B or hepatitis Ⅰ virus, hepatocellular carcinoma, other malignancies, major severe illness, or treatment non-compliance. Various parameters, including clinical parameters, complete blood count, liver function, renal function, plasma glucose, total antioxidant capacity (TAC), and polymerase chain reaction, were all assessed at baseline and at the end of the study. Clinical assessment included: hepato and/ or splenomegaly, jaundice, palmar erythema, flapping tremors, spider naevi, lower-limb edema, and ascites. N. sativa was administered for three successive months at a dose of (450 mg three times daily). Clinical response and incidence of adverse drug reactions were assessed initially, periodically, and at the end of the study. RESULTS: N. sativa administration significantly improved HCV viral load (380808.7 ± 610937 vs 147028.2 ± 475225.6, P = 0.001) and TAC (1.35 ± 0.5 vs 1.612 ± 0.56, P = 0.001). After N. sativa administration, the following laboratory parameters improved: total protein (7.1 ± 0.7 vs 7.5 ± 0.8, P = 0.001), albumin (3.5 ± 0.87 vs 3.69 ± 0.91, P = 0.008), red blood cell count (4.13 ± 0.9 vs 4.3 ± 0.9, P = 0.001), and platelet count (167.7 ± 91.2 vs 198.5 ± 103, P = 0.004). Fasting blood glucose (104.03 ± 43.42 vs 92.1 ± 31.34, P = 0.001) and postprandial blood glucose (143.67 ± 72.56 vs 112.1 ± 42.9, P = 0.001) were significantly decreased in both diabetic and non-diabetic HCV patients. Patients

关键词： Hepatitis C virus Nigella sativa Oxidative stress Viral load

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Deep Reinforcement Learning Enabled Smart City Recycling Waste Object Classification

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Computers, Materials & Continua 2022年第6期71卷 5699-5715页

作者： Mesfer Al Duhayyim Taiseer Abdalla Elfadil Eisa Fahd NAl-Wesabi Abdelzahir Abdelmaboud Manar Ahmed Hamza Abu sarwar Zamani Mohammed Rizwanullah radwa Marzouk Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Information Systems-Girls Section King Khalid UniversityMahayil62529Saudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerSaudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Information Systems King Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversitySaudi Arabia Department of Mathematics Faculty of ScienceCairo UniversityGiza12613Egypt Corresponding Author:Manar Ahmed Hamza.Email:ma.hamza@psau.edu.sa

The Smart City concept revolves around gathering real time data from citizen,personal vehicle,public transports,building,and other urban infrastructures like power grid and waste disposal *** understandings obtained from the data can assist municipal authorities handle assets and services *** the same time,the massive increase in environmental pollution and degradation leads to ecological imbalance is a hot research ***,the progressive development of smart cities over the globe requires the design of intelligent waste management systems to properly categorize the waste depending upon the nature of *** of the commonly available wastes are paper,paper boxes,food,glass,*** order to classify the waste objects,computer vision based solutions are cost effective to separate out the waste from the huge dump of garbage and *** to the recent developments of deep learning(DL)and deep reinforcement learning(DRL),waste object classification becomes possible by the identification and detection of *** this aspect,this paper designs an intelligence DRL based recycling waste object detection and classification(IDRL-RWODC)model for smart *** goal of the IDRLRWODC technique is to detect and classify waste objects using the DL and DRL *** IDRL-RWODC technique encompasses a twostage process namely Mask Regional Convolutional Neural Network(Mask RCNN)based object detection and DRL based object *** addition,DenseNet model is applied as a baseline model for the Mask RCNN model,and a deep Q-learning network(DQLN)is employed as a ***,a dragonfly algorithm(DFA)based hyperparameter optimizer is derived for improving the efficiency of the DenseNet *** order to ensure the enhanced waste classification performance of the IDRL-RWODC technique,a series of simulations take place on benchmark dataset and the experimental results pointed out the better performance over the recent techniques

关键词： Smart cities deep reinforcement learning computer vision image classification object detection waste management

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Improved Metaheuristics with Deep Learning Enabled Movie Review Sentiment Analysis

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Computer Systems Science & Engineering 2023年第10期47卷 1249-1266页

作者： Abdelwahed Motwakel Najm Alotaibi Eatedal Alabdulkreem Hussain Alshahrani MohamedAhmed Elfaki Mohamed K Nour radwa Marzouk Mahmoud Othman Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Prince saud AlFaisal Institute for Diplomatic Studies RiyadhSaudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt

Sentiment Analysis(sa)of natural language text is not only a challenging process but also gains significance in various Natural Language Processing(NLP)*** sa is utilized in various applications,namely,education,to improve the learning and teaching processes,marketing strategies,customer trend predictions,and the stock *** researchers have applied lexicon-related approaches,Machine Learning(ML)techniques and so on to conduct the sa for multiple languages,for instance,English and *** to the increased popularity of the Deep Learning models,the current study used diverse configuration settings of the Convolution Neural Network(CNN)model and conducted sa for Hindi movie *** current study introduces an Effective Improved Metaheuristics with Deep Learning(DL)-Enabled Sentiment Analysis for Movie Reviews(IMDLsa-MR)*** presented IMDLsa-MR technique initially applies different levels of pre-processing to convert the input data into a compatible ***,the Term Frequency-Inverse Document Frequency(TF-IDF)model is exploited to generate the word vectors from the pre-processed *** Deep Belief Network(DBN)model is utilized to analyse and classify the ***,the improved Jellyfish Search Optimization(IJSO)algorithm is utilized for optimal fine-tuning of the hyperparameters related to the DBN model,which shows the novelty of the *** experimental analyses were conducted to validate the better performance of the proposed IMDLsa-MR *** comparative study outcomes highlighted the enhanced performance of the proposed IMDLsa-MR model over recent DL models with a maximum accuracy of 98.92%.

关键词： Corpus linguistics sentiment analysis natural language processing deep learning word embedding

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Selenoprotein-p and insulin resistance in children and adolescents with obesity

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World Journal of Clinical Pediatrics 2024年第3期13卷 40-52页

作者： Amany Elbarky Kholoud Gamal Ismail Yousef Fouad Yousef Rasha Mohamed Gamal Elshafiey radwa Mahmoud Elsharaby Asmaa El-Kaffas Mohammed Al-Beltagi Gastroenterology and Clinical Nutrition Unit Pediatric DepartmentFaculty of MedicineTanta UniversityTanta 31511AlghrabiaEgypt Department of Pediatric Faculty of MedicineTanta UniversityTanta 31511AlghrabiaEgypt Department of Clinical Pathology Faculty of MedicineTanta UniversityTanta 31511AlghrabiaEgypt Department of Paediatric University Medical CenterKing Abdulla Medical CityArabian Gulf UniversityManama 26671ManamaBahrain

BACKGROUND Insulin resistance and obesity present significant challenges in pediatric *** P1(SEPP1)serves as a biomarker for assessing selenium levels in the *** its association with metabolic syndrome is established in adults,its relevance in children remains *** To ascertain SEPP1 blood levels in children and adolescents diagnosed with obesity and to assess its correlation with insulin resistance and adiposity *** 170 children participated in this study,including 85 diagnosed with obesity and an equal number of healthy counterparts matched for age and *** participant underwent a comprehensive medical evaluation,encompassing a detailed medical history,clinical examination,and anthropometric measurements like waist circumference and waist-to-height ***,routine blood tests were conducted,including serum SEPP1,visceral adiposity index(VAI),and Homeostatic Model Assessment of Insulin Resistance(HOMA-ir)*** Our findings revealed significantly lower serum SEPP1 levels in children with obesity compared to their healthy ***,notable negative correlations were observed between serum SEPP1 levels and body mass index,VAI,and *** The study suggests that SEPP1 could serve as a valuable predictor for insulin resistance among children and adolescents diagnosed with *** highlights the potential utility of SEPP1 in pediatric metabolic health assessment and warrants further investigation.

关键词： Obesity Childhood obesity Selenium status Selenoprotien P1 Insulin resistance

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