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Changes in hepatic fibrosis and incidence of hCC following direct-acting antiviral treatment of F3 chronic hepatitis c patients:a prospective observational study

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hepatoma Research 2022年第1期8卷 340-351页

作者： Gamal Shiha reham Soliman Ayman Ahassan Nabiel N.h.Mikhail Egyptian Liver Research Institute and hospital(ELRIAh) SherbinMansoura 35111Egypt hepatology and Gastroenterology Unit Internal Medicine DepartmentFaculty of MedicineMansoura UniversityMansoura 35516Egypt Tropical Medicine Department Faculty of MedicinePort Said UniversityPort Said 42526Egypt Biostatistics and Cancer Epidemiology Department South Egypt Cancer InstituteAssiut UniversityAssiut 71515Egypt

Aim:Studies of clinical outcomes in chronic hepatitis C(ChC)patients with pretreatment advanced liver fibrosis(F3)after sustained virologic response(SVR)are scarce,and most studies are of small cohorts and retrospective in *** aim was to assess the clinical outcomes following direct acting antiviral(DAA)treatment among hepatitis C F3 patients after ***:This study included 1517 chronic hepatitis C patients with F3 fibrosis receiving DAAs in the out-patient clinics at the Egyptian Liver Research Institute and hospital(ELRIAh).We included patients 18 years or older with hCV who received DAAs,have F3 by transient elastography,and have no history of hepatocellular carcinoma(hCC).Patients were followed up every six months after end of treatment using ultrasonography and ***:Significant improvement of fibrosis occurred with decreases in LSM,FIB-4,APRI,and *** changes in LSM were categorized depending on delta LSM,873 patients(57.5%)showed regression,454(29.9%)were stable,and 190 patients(12.5%)showed progression of ***,33 cases developed hCC during follow-up with incidence rate of 0.915/100 py(95%CI:0.64-1.27).Incidence was high with progression of liver fibrosis(6.17/100 py)compared to patients with stable fibrosis(1.09/100 py)and regression of liver fibrosis(0.75/100 py).There were no significant differences as regards fibrosis indicators at baseline(LSM,FIB-4,APRI,and FIB-6)between those who developed hCC and those who did ***:ChC Patients with F3 fibrosis showed a high rate of regression of fibrosis and decreased hCC incidence after achieving SVR following DAAs.

关键词： hCC fibrosis changes F3 DAAs

COVID19 Classification Using CT Images via Ensembles of Deep Learning Models

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Computers, Materials & Continua 2021年第10期69卷 319-337页

作者： Abdul Majid Muhammad Attique Khan Yunyoung Nam Usman Tariq Sudipta Roy reham R.Mostafa Rasha h.Sakr Department of Computer Science HITEC University TaxilaTaxila47080Pakistan Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia PRTTL Washington University in Saint LouisSaint LouisMO 63110USA Department of Information Systems Faculty of Computers and Information SciencesMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computers and Information SciencesMansoura UniversityMansoura35516Egypt

The recent COVID-19 pandemic caused by the novel coronavirus,severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),has had a significant impact on human life and the economy around the world.A reverse transcription polymerase chain reaction(RT-PCR)test is used to screen for this disease,but its low sensitivity means that it is not sufficient for early detection and *** RT-PCR is a time-consuming procedure,there is interest in the introduction of automated techniques for *** learning has a key role to play in the field of medical *** most important issue in this area is the choice of key ***,we propose a set of deep learning features based on a system for automated classification of computed tomography(CT)images to identify ***,this method was used to prepare a database of three classes:Pneumonia,COVID19,and *** dataset consisted of 6000 CT images refined by a hybrid contrast stretching *** the next step,two advanced deep learning models(ResNet50 and DarkNet53)were fine-tuned and trained through transfer *** features were extracted from the second last feature layer of both models and further optimized using a hybrid optimization *** each deep model,the Rao-1 algorithm and the PSO algorithm were combined in the hybrid ***,the selected features were merged using the new minimum parallel distance non-redundant(PMDNR)*** final fused vector was finally classified using the extreme machine *** experimental process was carried out on a set of prepared data with an overall accuracy of 95.6%.Comparing the different classification algorithms at the different levels of the features demonstrated the reliability of the proposed framework.

关键词： COVID19 preprocessing deep learning information fusion firefly algorithm extreme learning machine

Cyanidin 3-glucoside modulated cell cycle progression in liver precancerous lesion,in vivo study

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World Journal of Gastroenterology 2021年第14期27卷 1435-1450页

作者： Marwa Matboli Amany h hasanin reham hussein Sarah El-Nakeep Eman K habib Rawan Ellackany Lobna A Saleh Department of Biochemistry Ain Shams Faculty of MedicineCairo 11318Egypt Department of Clinical Pharmacology Ain Shams Faculty of MedicineCairo 11381Egypt Department of General Internal Medicine Ain Shams Faculty of MedicineCairo 11381Egypt Department of Anatomy&Embryology Ain Shams Faculty of MedicineCairo 11318Egypt Department of Undergraduate Faculty of MedicineModern University for Technology and InformationCairo 11381Egypt

BACKGROUND Cyanidin-3-O-glucoside(cyan)exhibits antioxidant and anticancer *** cell cycle proteins and antimitotic drugs might be promising therapeutic targets in hepatocellular *** To investigate the effect of cyan administration on cell cycle in hepatic precancerous lesion(PCL)induced by diethylnitrosamine/2-acetylaminofluorene(DEN/2-AAF)in Wistar *** In vivo,DEN/2-AAF-induced hepatic PCL,rats were treated with three doses of cyan(10,15,and 20 mg/kg/d,for four consecutive days per week for 16 wk).Blood and liver tissue samples were collected for measurement of the followings;alpha fetoprotein(AFP)liver function and RNA panel differential expression was evaluated via real time polymerase chain *** examination of liver sections stained with h&E and immunohistochemical study using glutathione S-transferase placental(GSTP)and proliferating cell nuclear antigen(PCNA)antibodies were *** Cyan administration mitigated the effect of DEN/2-AFF induced PCL,decreased AFP levels,and improved liver ***,treatment with cyan dose dependently decreased the long non-coding RNA MALAT1 and tubulin gamma 1 mRNA expressions and increased the levels of miR-125b,all of which are involved in cell cycle and mitotic spindle *** note,cyan decreased GSTP foci percent area and PCNA positively stained *** Our results indicated that cyan could be used as a potential therapeutic agent to inhibit liver carcinogenesis in rat model via modulation of cell cycle.

关键词： hepatocellular carcinoma therapy hepatocellular-carcinoma growth hepatocellular-carcinoma model hepatocellular-carcinoma size

Experimental validation of double-fed induction generator in oscillating water column using circulatory system-based optimization

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Clean Energy 2024年第2期8卷 127-143页

作者： Basem E.Elnaghi Ahmed M.Ismaiel Fathy El Sayed Abdel-Kader reham h.moham.ed M.N.Abelwhab Electrical Power and Machine Department Suez Canal UniversityIsmailiaEgypt Electrical Power and Machine Department Menoufia UniversityMenoufiaEgypt Computer and Control Department Suez Canal UniversityIsmailiaEgypt

This paper validates the optimal operation for a grid-connected double-fed induction generator(DFIG)in an oscillating water column power plant(OWCPP).This study presents a novel optimization technique called the circulatory system-based optimization(CSBO)approach to develop six adaptive fuzzy logic controllers(AFLCs)with 30 parameters and compare them to chaotic-billiards optimization(C-BO)and genetic algorithm(GA).The proposed controller is also compared with a proportional-integral differential(PID)controller based on a self-adaptive global-best harmony search(SGhS).CSBO-based AFLCs are fully investigated under different scenarios and experimented with using a real-time interface *** results of using CSBO-AFLCs revealed a fast time response,fast convergence,less overshoot and minimal error compared with those achieved with C-BO-AFLC,SGhS-PID and GA-AFLC during different case *** CSBO-based AFLCs ensure maximum power from the DFIG in an OWCPP and enhance dynamic response with very low *** results show that the CSBO shows better power tracking by 25%as compared with C-BO,by 45%when compared with the GA and by 56%when compared with ***,the integral absolute errors of six controllers are investigated to demonstrate the feasibility of *** root mean square of the errors of six controllers using CSBO is improved by 68.27%when compared with GA,by 22.57%when compared with C-BO and by 38.42%when compared with *** indicators demonstrate the feasibility of CSBO when compared with other algorithms with the same OWCPP.

关键词： circulatory system-based optimization approach adaptive fuzzy logic controller grid-tied oscillating water column power plant maximum power point tracking

An Ensemble of Optimal Deep Learning Features for Brain Tumor Classification

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Computers, Materials & Continua 2021年第11期69卷 2653-2670页

作者： Ahsan Aziz Muhammad Attique Usman Tariq Yunyoung Nam Muhammad Nazir Chang-Won Jeong reham R.Mostafa Rasha h.Sakr Department of Computer Science HITEC UniversityTaxilaPakistan College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia Department of ICT Convergence Soonchunhyang UniversityAsanKorea Medical Convergence Research Center Wonkwang UniversityIksanKorea Department of Information Systems Faculty of Computers and Information SciencesMansoura UniversityMansouraEgypt Department of Computer Science Faculty of Computers and Information SciencesMansoura UniversityMansouraEgypt

Owing to technological developments,Medical image analysis has received considerable attention in the rapid detection and classification of *** brain is an essential organ in *** tumors cause loss of memory,vision,and *** 2020,approximately 18,020 deaths occurred due to brain *** cases can be minimized if a brain tumor is diagnosed at a very early *** vision researchers have introduced several techniques for brain tumor detection and ***,owing to many factors,this is still a challenging *** challenges relate to the tumor size,the shape of a tumor,location of the tumor,selection of important features,among *** this study,we proposed a framework for multimodal brain tumor classification using an ensemble of optimal deep learning *** the proposed framework,initially,a database is normalized in the form of high-grade glioma(hGG)and low-grade glioma(LGG)patients and then two pre-trained deep learning models(ResNet50 and Densenet201)are *** deep learning models were modified and trained using transfer ***,the enhanced ant colony optimization algorithm is proposed for best feature selection from both deep *** selected features are fused using a serial-based approach and classified using a cubic support vector *** experimental process was conducted on the BraTs2019 dataset and achieved accuracies of 87.8%and 84.6%for hGG and LGG,*** comparison is performed using several classification methods,and it shows the significance of our proposed technique.

关键词： Brain tumor data normalization transfer learning features optimization features fusion

Influence of the ph,Pretreatment and hydraulic Retention Time on the Enhancement of the Biohydrogen and Volatile Fatty Acids Production from Food Waste in the Semi-continuously Running Reactor

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Influence of the pH,Pretreatment and Hydraulic Retention Tim...

作者： reham YASSER FAROUK hAMed 华中农业大学

学位级别：硕士

食物垃圾(FW)是一种未开发的资源,具有很高的资源回收能力。在暗发酵(DF)中使用FW作为底物被广泛研究,因为FW含有大量有机物质和水分,如脂质、淀粉和蛋白质。暗发酵具有从食物垃圾中生产高价值副产物生产的能力,如乳酸(LA),氢(h2),醇(Et... 详细信息

食物垃圾(FW)是一种未开发的资源,具有很高的资源回收能力。在暗发酵(DF)中使用FW作为底物被广泛研究,因为FW含有大量有机物质和水分,如脂质、淀粉和蛋白质。暗发酵具有从食物垃圾中生产高价值副产物生产的能力,如乳酸(LA),氢(h2),醇(EtOh),短链脂肪酸和甲烷。此外,已经证明氢是有前景的能源之一,对减少对化石燃料的依赖至关重要。另外,VFA也被广泛应用,如作为替代碳源的利用。本研究采用中温半连续的反应器系统,以食品垃圾废水为底物进行产氢和挥发性脂肪酸VFAs,研究PhP(预处理、hRT和ph)系统对氢和挥发性脂肪酸(VFA)产生的影响。另外,将PhP和非调控的系统进行比较。首先研究了酸碱度和预处理的影响。通过重复SAS分析表明,这些因素(酸碱度和预处理)对h2产率、VFA浓度、VFA/可溶性化学耗氧量(SCOD)和h2/SCOD这些指标有显著影响(Ph=7条件下,化学处理(CT)的h2产率和产量最高,而在ph=6时,化学处理(CT)组的VFA产量和浓度最高,VFA浓度为55.44±2.39 g/L,产率为926.21±42.27mg/g SCOD,此时 h2 产量为 280.82±5.72 ml/L,产率为 4.44±0.10ml/g SCOD。最佳条件时(ph=6,CT预处理)发酵液中的丁酸盐和乙酸盐含量占总挥发性脂肪酸VFAs总量的62.43%。另一方面,实验结果表明,ph=5对h2和VFA的生成没有显著促进作用。此外,在ph=7和CT预处理的基础之上,本课题研究了水力停留时间(hRT)对发酵过程的影响。其中三种不同的hRT(2d、3d和4d)用于评估其对氢和VFA生产的影响。单因素方差分析表明,hRT对h2的产量和产率有显著影响,而在hRT=3d时出现h2的最高产量和产率,分别为263.82±18.44,5.19±0.40 ml/g SCOD。相反,hRT对VFA的产率无显著影响,当hRT在2d到4d内变化时,VFA浓度在36.03±1.72至40.19±1.53 g/L范围内波动。但是hRT对VFA的浓度有显著影响,在hRT=2d时VFA浓度达到最高值40.19±1.53 g/L。本实验产物以丁酸盐为主,占总VFA的50%。另外,结果表明,hRT=2d时的h2和VFA产量最低。通过聚合酶链反应(PCR)的变性梯度凝胶电泳(DGGE)-在16S rDNA分析的扩增的V3-V4区域,在所有hRT水平上均检测出产氢和产VFA的菌种。结果表明,微生物的高度多样性为hRT2,其具有最高的氢产率和VFA浓度。所检测出来的主要菌种是乳酸杆菌,事实证明,乳酸杆菌不会影响氢的产生,而梭菌属是产氢所必需的菌种。同时本研究发现,丁酸梭菌的存在是形成丁酸盐发酵的主要原因。此外,还对同一 hRT条件下PhP系统与非调控系统进行了比较研究。配对样本T检验表明,PhP系统与非调控系统对氢气和VFA的产生有显著性差异(PhP系统的氢气产率升高至263.82ml/L。PhP系统的VFA产量比非调控系统高1.8倍,因此PhP是一种可以提高h2和VFA产量的较为理想的工艺。

关键词：生物制氢餐厨垃圾挥发性脂肪酸 ph hRT 预处理

Skin Lesion Segmentation and Classification Using Conventional and Deep Learning Based Framework

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Computers, Materials & Continua 2022年第5期71卷 2477-2495页

作者： Amina Bibi Muhamamd Attique Khan Muhammad Younus Javed Usman Tariq Byeong-Gwon Kang Yunyoung Nam reham R.Mostafa Rasha h.Sakr Department of Computer Science HITEC UniversityTaxilaPakistan College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia Department of ICT Convergence Soonchunhyang UniversityAsan31538Korea Information Systems Department Faculty of Computers and Information SciencesMansoura UniversityMansoura35516Egypt Computer Science Department Faculty of Computers and Information SciencesMansoura UniversityMansoura35516Egypt

Background:In medical image analysis,the diagnosis of skin lesions remains a challenging *** lesion is a common type of skin cancer that exists *** is one of the latest technologies used for the diagnosis of skin ***:Many computerized methods have been introduced in the literature to classify skin ***,challenges remain such as imbalanced datasets,low contrast lesions,and the extraction of irrelevant or redundant *** Work:In this study,a new technique is proposed based on the conventional and deep learning *** proposed framework consists of two major tasks:lesion segmentation and *** the lesion segmentation task,contrast is initially improved by the fusion of two filtering techniques and then performed a color transformation to color lesion area color ***,the best channel is selected and the lesion map is computed,which is further converted into a binary form using a thresholding *** the lesion classification task,two pre-trained CNN models were modified and trained using transfer *** features were extracted from both models and fused using canonical correlation *** the fusion process,a few redundant features were also added,lowering classification accuracy.A new technique called maximum entropy score-based selection(MESbS)is proposed as a solution to this *** features selected through this approach are fed into a cubic support vector machine(C-SVM)for the final ***:The experimental process was conducted on two datasets:ISIC 2017 and *** ISIC 2017 dataset was used for the lesion segmentation task,whereas the hAM10000 dataset was used for the classification *** achieved accuracy for both datasets was 95.6% and 96.7%, respectively, which was higher thanthe existing techniques.

关键词： Skin cancer lesion segmentation deep learning features fusion classification

Residual Attention Deep SVDD for COVID-19 Diagnosis Using CT Scans

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Computers, Materials & Continua 2023年第2期74卷 3333-3350页

作者： Akram Ali Alhadad Omar Tarawneh reham R.Mostafa hazem M.El-Bakry Information Systems Department Faculty of Computers and InformationMansoura UniversityMansoura35511Egypt Computer Science Department Ibb UniversityIbbYemen SE Department Faculty of Computer Sciences and InformaticsAmman Arab UniversityAmman11953Jordan

COVID-19 is the common name of the disease caused by the novel coronavirus(2019-nCoV)that appeared in Wuhan,China in *** the infected people is the most important factor in the fight against the *** gold-standard test to diagnose COVID-19 is polymerase chain reaction(PCR),but it takes 5–6 h and,in the early stages of infection,may produce false-negative *** Computed Tomography(CT)images to diagnose patients infected with COVID-19 has become an urgent *** this study,we propose a residual attention deep support vector data description SVDD(RADSVDD)approach to diagnose *** is a novel approach combining residual attention with deep support vector data description(DSVDD)to classify the CT *** the best of our knowledge,we are the first to combine residual attention with DSVDD in general,and specifically in the diagnosis of *** attention with DSVDD naively may cause model *** in the proposed RADSVDD guides the network during training and enables quick learning,residual connectivity prevents vanishing *** approach consists of three models,each model is devoted to recognizing one certain disease and classifying other diseases as *** models learn in an end-to-end *** proposed approach attained high performance in classifying CT images into intact,COVID-19,and non-COVID-19 *** evaluate the proposed approach,we created a dataset from published datasets and had it assessed by an experienced *** proposed approach achieved high performance,with the normal model attained sensitivity(0.96–0.98),specificity(0.97–0.99),F1-score(0.97–0.98),and area under the receiver operator curve(AUC)0.99;the COVID-19 model attained sensitivity(0.97–0.98),specificity(0.97–0.99),F1-score(0.97–0.99),and AUC 0.99;and the non-COVID pneumoniamodel attained sensitivity(0.97–1),specificity(0.98–0.99),F1-score(0.97–0.99),and AUC 0.99.

关键词： Deep learning deep SVDD residual attention anomaly detection COVID-19 Coronavirus

Optimization of double chamber microbial fuel cell for domestic wastewater treatment and electricity production

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燃料化学学报 2015年第9期43卷 1092-1099页

作者： Amr El-hag Ali Ola M.Gomaa reham Fathey hussein Abd El Kareem mohamed Abou Zaid Polymer Chemistry Department Microbiology Department National Center for Radiation Research and Technology (NCRRT) Egyptian Atomic energy Authority ( EAEA ) Nasr City Cairo Egypt DAS Taibah University Medinah KSA

Microbial fuel cells(M FCs)represent a new approach for treating w aste w ater along w ith electricity *** present study addressed electricity production from domestic w astew ater using a mediator-less double chamber M *** electricity production w as monitored under different operational conditions for both summer and w inter *** of the anodic and cathodic chambers resulted in a maximal current of 0.784 and 0.645 m A w ith the maximal pow er intensity of 209 and 117 m W/m2in pow er duration of 24 h for the summer and w inter samples,*** electron microscopy show ed that the bacterial biofilm formation on the anode w as denser for the summer sample than that w hen the w inter sample w as used,so w as the total bacterial ***,samples taken during summer w ere considered better in electricity production and w aste w ater treatment than those taken during w inter basically because of the high microbial load during the hot *** parallel,there w as a decrease in both biological oxygen demand(BOD5)and chemical oxygen demand(COD)values which reached 71.8%and 72.85%,respectively at the end of the operation process for the summer sample,w hile there w as no evident decrease for the w inter *** the operating conditions not only increased the potential of using domestic w aste w ater in microbial fuel cells to produce electricity,but also improved the quality of the domestic w aste w ater.

关键词：微生物引起的燃料房间国内废水处理操作条件电生产