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Asian Pacific Journal of Tropical Biomedicine 2023年第3期13卷 131-138页

作者： naglaa m.el-lakkany Hadeel H.elkattan Alaa E.elsisi Department of Pharmacology Theodor Bilharz Research InstituteWarrak El-HadarImbabaGiza 12411Egypt Department of Pharmacology and Toxicology Faculty of PharmacyTanta UniversityTantaEgypt

Objective:To evaluate the efficacy of ponatinib plus gossypol against colorectal cancer HCT-116 and Caco-2 ***:Cells were treated with ponatinib and/or gossypol at increasing concentrations to evaluate synergistic drug interactions by combination *** viability,FGF19/FGFR4,and apoptotic and autophagic cell death were ***:Ponatinib(1.25-40μm)and gossypol(2.5-80μm)monotherapy inhibited HCT-116 and Caco-2 cell viability in a doseand time-dependent *** combination of ponatinib and gossypol at a ratio of 1 to 2 significantly decreased cell viability(P2-and>4-fold reduction in IC50,respectively,after 24 h and 48 h,as compared to the IC50 of *** combined concentrations showed greater synergism(combination indexmorphological changes in HCT-116and Caco-2 cells,increased beclin-1 and caspase-3,and decreased FGF19,FGFR4,Bcl-2 and p-Akt as compared to treatment with drugs ***:Gossypol enhances ponatinib's anticancer effects against colorectal cancer cells through antiproliferative,apoptotic,and autophagic *** may open the way for the future use of ponatinib at lower doses with gossypol as a potentially safer targeted strategy for colorectal cancer treatment.

关键词： Autophagy Apoptosis Cell viability FGF19/FGFR4 Gossypol Ponatinib HCT-116 Caco-2 Colorectal cancer

Hydroxysafflor yellow A protects against thioacetamide-induced liver fibrosis in rats via suppressing proinflammatory/fibrogenic mediators and promoting hepatic stellate cell senescence and apoptosis

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Asian Pacific Journal of Tropical Biomedicine 2023年第8期13卷 348-358页

作者： Sayed H.Seif el-Din Olfat A.Hammam Shahira m.Ezzat Samira Saleh marwa m.Safar Walaa H.el-maadawy naglaa m.el-lakkany Pharmacology Department Theodor Bilharz Research InstituteWarak El-HadarImbaba P.O.Box 30Giza 12411Egypt Pathology Department Theodor Bilharz Research InstituteWarak El-HadarImbaba P.O.Box 30Giza 12411Egypt Pharmacognosy Department Faculty of PharmacyCairo UniversityCairo 11562Egypt Pharmacognosy Department Faculty of PharmacyOctober University for Modern Sciences and ArtsGizaEgypt Pharmacology and Toxicology Department Faculty of PharmacyCairo UniversityCairo 11562Egypt Pharmacology and Biochemistry Department Faculty of PharmacyThe British University in EgyptCairoEgypt

Objective:To evaluate the effect of hydroxysafflor yellow A(HSYA)on thioacetamide-induced liver ***:Thioacetamide was administered to rats intraperitoneally in doses of 200 mg/kg twice a week for 12 ***-intoxicated rats were given silymarin(50 mg/kg)or HSYA(5 mg/kg)orally every day for 8 *** enzymes,fibrosis markers,histological changes as well as immunohistochemistry of TNF-α,IL-6,p21,α-SmA,and caspase-3 were *** effect of HSYA on HSC-T6 activation/proliferation and apoptosis was also determined in ***:HSYA decreased liver enzymes,TNF-α,IL-6,and p21 expressions,hepatic PDGF-B,TImP-1,TGF-β1,and hydroxyproline levels,as well as fibrosis score(S2 vs.S4)compared to the thioacetamide *** also downregulatedα-SmA while increasing caspase-3 ***,at 500μg/mL,HSYA had only a slightly suppressive effect on HSC proliferation,with a 9.5%***,it significantly reduced TGF-β1,inhibitedα-SmA expression,induced caspase-3 expression,and promoted cell ***:HSYA may be a potential therapeutic agent for delaying and reversing the progression of liver *** research on HSYA at higher doses and for a longer period is warranted.

关键词： Hydroxysafflor yellow A Thioacetamide Hepatic stellate cells Inflammatory markers Liver fibrosis p21 α-SmA Apoptosis

Rosmarinic acid attenuates hepatic fibrogenesis via suppression of hepatic stellate cell activation/proliferation and induction of apoptosis

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Asian Pacific Journal of Tropical medicine 2017年第5期10卷 423-432页

作者： naglaa m.el-lakkany Walaa H.el-maadawy Sayed H.Seif el-Din Olfat A.Hammam Salwa H.mohamed Shahira m.Ezzat marwa m.Safar Samira Saleh Department of Pharmacology Theodor Bilharz Research InstituteWarak El-HadarImbaba P.O.Box 30Giza 12411Egypt Department of Pathology Theodor Bilharz Research InstituteWarak El-HadarImbaba P.O.Box 30Giza 12411Egypt Department of Immunology Theodor Bilharz Research InstituteWarak El-HadarImbaba P.O.Box 30Giza 12411Egypt Department of Pharmacognosy Faculty of PharmacyCairo UniversityCairo 11562Egypt Department of Pharmacology and Toxicology Faculty of PharmacyCairo UniversityCairo 11562Egypt

Objective:To investigate the antifibrotic role of rosmarinic acid(RA),a natural polyphenolic compound,on HSCs activation/proliferation and apoptosis in vitro and in vivo. methods:The impact of RA on stellate cell line(HSC-T6) proliferation,activation and apoptosis was assessed along with its safety on primary hepatocytes. In vivo,rats were divided into:(i) normal;(ii) thioacetamide(TAA)-intoxicated rats for 12 weeks;(iii) TAA+silymarin or(iv) TAA+RA. At the end of experiment,liver functions,oxidative stress,inflammatory and profibrogenic markers,tissue inhibitor metalloproteinases type-1(TImP-1) and hydroxyproline(HP) levels were evaluated. Additionally,liver histopathology and immunohistochemical examinations of alpha-smooth muscle actin(α-SmA),caspase-3 and proliferation cellular nuclear antigen(PCNA) were determined. Results:RA exhibited anti-proliferative effects on cultured HSCs in a time and concentration dependent manner showing an IC50 of 276 μg/mL and 171 μg/mL for 24 h and 48 h,respectively,with morphological reversion of activated stellate cell morphology to quiescent form. It significantly improved ALT,AST,oxidative stress markers and reduced TImP-1,HP levels,inflammatory markers and fibrosis score(S1 vs S4). Furthermore,reduction in α-SmA plus elevation in caspase-3 expressions of HSCs in vitro and in vivo associated with an inhibition in proliferation of damaged hepatocytes were recorded. Conclusions:RA impeded the progression of liver fibrosis through inhibition of HSCs activation/proliferation and induction of apoptosis with preservation of hepatic architecture.

关键词： Hepatic fibrosis Hepatic stellate cells Rosmarinic acid Apoptosis Proliferation Profibrogenic markers

Evaluation of phosphorus bioavailability in el mex Bay and Lake mariut sediments

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International Journal of Sediment Research 2017年第3期32卷 432-441页

作者： naglaa F.Soliman Gehan m.el Zokm mohamed A.Okbah Department of Environmental Studies Institute of Graduate Studies and Research University of Alexandria National Institute of Oceanography and Fisheries

Phosphorus(P) fractions and their bioavailability in the sediments from.el mex Bay and Lake mariut in Egypt were investigated using different chemical extraction methods. Sodium bicarbonate(NaHC03)extractable P(Olsen-P) was the largest fraction(14.42%), followed by algal available P(AAP)(3.56%),water soluble P(WSP)(0.79%), and readily desorbable P(RDP)(0.06%) for el mex Bay. While AAP contributed 9.94% to total P in sediments from Lake mariut, Olsen-P 8.53%, WSP 4.11%, and RDP 0.92%.Summation of the bioavailable P fractions didn’t exceed the sediment quality guidelines, and, therefore, P doesn’t represent a danger to marine organisms. Correlation coefficients showed that no apparent relations between total P(TP) and iron(Fe), aluminum(Al), and calcium(Ca) in the sediments. Furthermore, Fe:P ratio was less than 15 indicting that there was not enough Fe in surface sediments to bind to P at most of the sampling sites. The positive correlation between TP and organic matter(Om) for Lake mariut and el mex Bay sediments indicated that the organic matter content of the sediment was a useful predictor of the total phosphorus content. Data from this study constitute a baseline of phosphorus bioavailability in sediments from.el mex Bay and Lake mariut and could be used as a reference for future studies on the changes of bioavailable and residual phosphorus fractions over time.

关键词： Phosphorus bioavailability Sediments el mex Bay Lake mariut

An Efficient GCD-Based Cancelable Biometric Algorithm for Single and multiple Biometrics

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Computers, materials & Continua 2021年第11期69卷 1571-1595页

作者： naglaa F.Soliman Abeer D.Algarni Walid el-Shafai Fathi E.Abd el-Samie Ghada m.el Banby Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt Department of electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Industrial electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

Cancelable biometrics are required in most remote access applications that need an authentication stage such as the cloud and Internet of Things(IoT)*** objective of using cancelable biometrics is to save the original ones from hacking attempts.A generalized algorithm to generate cancelable templates that is applicable on both single and multiple biometrics is proposed in this paper to be considered for cloud and IoT *** original biometric is blurred with two co-prime ***,it can be recovered as the Greatest Common Divisor(GCD)between its two blurred *** changes if induced in the biometric image prior to processing with co-prime operators prevents the recovery of the original biometric image through a GCD ***,the ability to change cancelable templates is guaranteed,since the owner of the biometric can pre-determine and manage the minimal change induced in the biometric ***,we test the utility of the proposed algorithm in the single-and multi-biometric *** multi-biometric scenario depends on compressing face,fingerprint,iris,and palm print images,simultaneously,to generate the cancelable *** metrics such as Equal Error Rate(EER)and Area and Receiver Operator Characteristic curve(AROC)are *** results on single-and multi-biometric scenarios show high AROC values up to 99.59%,and low EER values down to 0.04%.

关键词： Cloud IoT cancelable biometrics GCD single-and multi-biometrics security applications

An Efficient CNN-Based Hybrid Classification and Segmentation Approach for COVID-19 Detection

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Computers, materials & Continua 2022年第3期70卷 4393-4410页

作者： Abeer D.Algarni Walid el-Shafai Ghada m.el Banby Fathi E.Abd el-Samie naglaa F.Soliman Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh 84428Saudi Arabia Department of electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf 32952Egypt Department of Industrial electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf 32952Egypt Department of electronics and Communications Engineering Faculty of EngineeringZagazig UniversityZagazigSharqia 44519Egypt

COVID-19 remains to proliferate precipitously in the *** has significantly influenced public health,the world economy,and the persons’***,there is a need to speed up the diagnosis and precautions to deal with COVID-19 *** this explosion of this pandemic,there is a need for automated diagnosis tools to help specialists based onmedical *** paper presents a hybrid Convolutional Neural Network(CNN)-based classification and segmentation approach for COVID-19 detection from Computed Tomography(CT)*** proposed approach is employed to classify and segment the COVID-19,pneumonia,and normal CT *** classification stage is firstly applied to detect and classify the input medical CT ***,the segmentation stage is performed to distinguish between pneumonia and COVID-19 CT *** classification stage is implemented based on a simple and efficient CNN deep learning *** model comprises four Rectified Linear Units(RelUs),four batch normalization layers,and four convolutional(Conv)*** layer depends on filters with sizes of 64,32,16,and 8.A2×2windowand a stride of 2 are employed in the utilized four max-pooling layers.A soft-max activation function and a Fully-Connected(FC)layer are utilized in the classification stage to perform the detection *** the segmentation process,the Simplified Pulse Coupled Neural Network(SPCNN)is utilized in the proposed hybrid *** proposed segmentation approach is based on salient object detection to localize the COVID-19 or pneumonia region,*** summarize the contributions of the paper,we can say that the classification process with a CNN model can be the first stage a highly-effective automated diagnosis *** the images are accepted by the system,it is possible to perform further processing through a segmentation process to isolate the regions of interest in the *** region of interest can be assesses both automatically and through ***

关键词： COVID-19 segmentation classification CNN SPCNN CT images

Automated COVID-19 Detection Based on Single-Image Super-Resolution and CNN models

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Computers, materials & Continua 2022年第1期70卷 1141-1157页

作者： Walid el-Shafai Anas m.Ali el-Sayed m.el-Rabaie naglaa F.Soliman Abeer D.Algarni Fathi E.Abd el-Samie Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Alexandria Higher Institute of Engineering&Technology(AIET) AlexandriaEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

In developing countries,medical diagnosis is expensive and time ***,automatic diagnosis can be a good cheap *** task can be performed with artificial intelligence tools such as deep Convolutional Neural Networks(CNNs).These tools can be used on medical images to speed up the diagnosis process and save the efforts of *** deep CNNs allow direct learning from the medical ***,the accessibility of classified data is still the largest challenge,particularly in the field of medical *** learning can deliver an effective and promising solution by transferring knowledge from universal object detection CNNs to medical image ***,because of the inhomogeneity and enormous overlap in intensity between medical images in terms of features in the diagnosis of Pneumonia and COVID-19,transfer learning is not usually a robust ***-Image Super-Resolution(SISR)can facilitate learning to enhance computer vision functions,apart from enhancing perceptual image ***,it helps in showing the main features of *** by the challenging dilemma of Pneumonia and COVID-19 diagnosis,this paper introduces a hybrid CNN model,namely SIGTra,to generate super-resolution versions of X-ray and CT *** depends on aGenerative Adversarial Network(GAN)for the super-resolution reconstruction ***,Transfer learning with CNN(TCNN)is adopted for the classification of *** different categories of chest X-ray and CT images can be classified with the proposed model.A comparison study is presented between the proposed SIGTra model and the other relatedCNNmodels for COVID-19 detection in terms of precision,sensitivity,and accuracy.

关键词： medical images SIGTra GAN CT and X-ray images SISR TCNN

Gauss Gradient and SURF Features for Landmine Detection from GPR Images

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Computers, materials & Continua 2022年第6期71卷 4457-4486页

作者： Fatma m.el-Ghamry Walid el-Shafai mahmouad I.Abdalla Ghada m.el-Banby Abeer D.Algarni moawad I.Dessouky Adel S.elfishawy Fathi E.Abd el-Samie naglaa F.Soliman Department of electronics and Communications Engineering Faculty of EngineeringZagazig UniversityZagazigSharqia44519Egypt Department of electronics and electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufia32952Egypt Department of Industrial electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

Recently,ground-penetrating radar(GPR)has been extended as a well-known area to investigate the subsurface ***,its output has a low resolution,and it needs more processing for more *** paper presents two algorithms for landmine detection from GPR *** first algorithm depends on a multi-scale technique.A Gaussian kernel with a particular scale is convolved with the image,and after that,two gradients are estimated;horizontal and vertical ***,histogram and cumulative histogram are estimated for the overall gradient *** bin values on the cumulative histogram are used for discrimination between images with and without ***,a neural classifier is used to classify images with cumulative histograms as feature *** second algorithm is based on scale-space analysis with the number of speeded-up robust feature(SURF)points as the key parameter for *** addition,this paper presents a framework for size reduction of GPR images based on decimation for efficient *** further classification steps can be performed on images after *** sensitivity of classification accuracy to the interpolation process is studied in detail.

关键词： GPR images cumulative histogram gradient image neural classifier SURF

An Efficient CNN-Based Automated Diagnosis Framework from COVID-19 CT Images

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Computers, materials & Continua 2021年第10期69卷 1323-1341页

作者： Walid el-Shafai Noha A.el-Hag Ghada m.el-Banby Ashraf A.m.Khalaf naglaa F.Soliman Abeer D.Algarni Fathi E.Abd el-Samie Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of electronics and electrical Communications Faculty of EngineeringMinia UniversityEgypt Department of Industrial electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Corona Virus Disease-2019(COVID-19)continues to spread rapidly in the *** has dramatically affected daily lives,public health,and the world *** paper presents a segmentation and classification framework of COVID-19 images based on deep ***,the classification process is employed to discriminate between COVID-19,non-COVID,and pneumonia by Convolutional Neural Network(CNN).Then,the segmentation process is applied for COVID-19 and pneumonia CT ***,the resulting segmented images are used to identify the infected region,whether COVID-19 or *** proposed CNN consists of four Convolutional(Conv)layers,four batch normalization layers,and four Rectified Linear Units(RelUs).The sizes of Conv layer used filters are 8,16,32,and *** maxpooling layers are employed with a stride of 2 and a 2×2 *** classification layer comprises a Fully-Connected(FC)layer and a soft-max activation function used to take the classification decision.A novel saliencybased region detection algorithm and an active contour segmentation strategy are applied to segment COVID-19 and pneumonia CT *** acquired findings substantiate the efficacy of the proposed framework for helping the specialists in automated diagnosis applications.

关键词： Classification segmentation COVID-19 CNN deep learning diagnosis applications

Efficient Deep Learning modalities for Object Detection from Infrared Images

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Computers, materials & Continua 2022年第8期72卷 2545-2563页

作者： naglaa F.Soliman E.A.Alabdulkreem Abeer D.Algarni Ghada m.el Banby Fathi E.Abd el-Samie Ahmed Sedik Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Industrial electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of the Robotics and Intelligent machines Faculty of Artificial IntelligenceKafrelSheikh UniversityKafr el-sheikhEgypt

For military warfare purposes,it is necessary to identify the type of a certain weapon through video stream tracking based on infrared(IR)video *** vision is a visual search trend that is used to identify objects in images or video *** military applications,drones take a main role in surveillance tasks,but they cannot be confident for longtime ***,there is a need for such a system,which provides a continuous surveillance task to support the drone *** a system can be called a Hybrid Surveillance System(HSS).This system is based on a distributed network of wireless sensors for continuous *** addition,it includes one or more drones to make short-time missions,if the sensors detect a suspicious *** paper presents a digital solution to identify certain types of concealed weapons in surveillance applications based on Convolutional Neural Networks(CNNs)and Convolutional Long Short-Term memory(ConvLSTm).Based on initial results,the importance of video frame enhancement is obvious to improve the visibility of objects in video *** accuracy of the proposed methods reach 99%,which reflects the effectiveness of the presented *** addition,the experimental results prove that the proposed methods provide superior performance compared to traditional ones.

关键词： Deep learning object detection military applications OFDm SPIHT IoT