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Strategies to overcome drug resistance using SHP2 inhibitors

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Acta Pharmaceutica Sinica B 2021年第12期11卷 3908-3924页

作者： meng Liu Shan Gao reham m.elhassan Xuben Hou Hao Fang School of Pharmaceutical Sciences Cheeloo College of MedicineShandong UniversityJinan 250012China

Encoded by PTPN11,the SHP2(Src homology-2 domain-containing protein tyrosine phosphatase-2)is widely recognized as a carcinogenic phosphatase.As a promising anti-cancer drug target,SHP2 regulates many signaling pathways such as RAS-RAF-ERK,PI3 K-AKT and JAK-STAT.meanwhile,SHP2 plays a significant role in regulating immune cell function in the tumor microenvironment.Heretofore,five SHP2 allosteric inhibitors have been recruited in clinical studies for the treatment of cancer.most recently,studies have proved the therapeutic potential of SHP2 inhibitor in overcoming drug resistance of kinase inhibitors and programmed cell death-1(PD-1)blockade.Herein,we review the structure,function and small molecular inhibitors of SHP2,and highlight recent progress in overcoming drug resistance using SHP2 inhibitor.We hope this review would facilitate the future clinical development of SHP2 inhibitors.

关键词： SHP2 inhibitor Allosteric inhibitor Anti-cancer Drug resistance

The Protective Effect of moringa oleifera Leaves Extract on Paracetamol Hepatotoxicity in male Rats

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Journal of Biomedical Science and Engineering 2024年第3期17卷 72-82页

作者： reham m. Al-Sultan Noorah Saleh Al-Sowayan Department of Biology College of Science Qassim University Buraydah Saudi Arabia

In recent years, there has been an increase in concern regarding the effects of paracetamol poisoning on liver tissues, particularly when consumed in large amounts. Some studies have estimated that paracetamol is involved in 56% of acute liver diseases, whereas 0.4% of paracetamol overdose cases result in fatal-ity. In this study, the effects of moringa oleifera on paracetamol toxicity in the liver were explored. It has been demonstrated that moringa oleifera is highly nu-tritious, contains bioactive molecules, and is therapeutically beneficial. many studies have shown that moringa oleifera leaves possess a wide range of biologi-cal properties, including antioxidant, tissue protection, analgesic, antihyperten-sive, and immunomodulatory activities. This study highlights the protective role of moringa oleifera on handling possible paracetamol hepatotoxicity in male rats. .

关键词： moringa oleifera Paracetamol Hepatotoxicity Oxidative Stress

Discovery of Novel ALDH2 modulators:an Integrative in Silico and in Vitro Approach

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Discovery of Novel ALDH2 Modulators:an Integrative in Silico...

作者： Reham.elhassan 山东大学

学位级别：硕士

ALDHs superfamily represents a group of enzymes that metabolize toxic aldehyde-induced ROS generation.ALDHs superfamily,therefore,is one of the ROS scavenger’s enzyme that plays a crucial protective role.It is not surprising that aberrant ALDHs activity via mutations has been associated with development of many human diseases,including Sj?gren-Larsson syndrome（SLS）,cardiovascular disease,neurodegenerative diseases,diabetes,acute lung injury and cancer.In human genome,there are a set of 19 Aldehyde dehydrogenase（ALDHs）genes with a diverse tissue distribution and substrate specificity.Of those,mitochondrial Aldehyde Dehydrogenase 2（ALDH2）emerges as a master detoxifier particularly in the metabolism of acetaldehyde-induce ROS generation.At the interface of the three domains,there is a hydrophobic funnel-shaped tunnel with an opening leading to the catalytic pocket located 12 ? from the surface of the enzyme and opposite to the cofactor binding site.ALDH2*2 allele,also known as Glu504Lys（E487K）,holds a single nucleotide polymorphism,resulting in a reduced enzyme ability to oxidize acetaldehyde compared with wild-type ALDH2 homozygotes.According to the epidemiological studies,ALDH2*2 allele,is the most common ALDH2 variant in nearly 50%of East Asians（i.e.,Chinese,Japanese and,Korean）.With the marked prevalence of ALDH2*2 in world population（～560 million）,ALDH2*2 is regarded to be the most common human enzyme deficiency disorder among other human enzymopathies.It is widely known that ALDH2 is regarded as endogenous cardio-protective factor in myocardial injury.However,several compelling evidences suggest that ALDH2*2 can either benefit or harm the cardiovascular system.moreover,the current clinical management of cardiomyopathies is mainly achieved through surgical intervention with little effective pharmaco-therapeutic regimen.Given the marked prevalence of cardiomyopathies in most developed countries and the emerging cardio-protective role of ALDH2 along with the considerable number of reported ALDH2 modulators to dat

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Galectins dysregulation: A way for cancer cells to invade and pervade

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Oncology Research 2022年第3期30卷 129-135页

作者： mAHmOUD m.ABDELFATTAH reham HELWA molecular Cancer Biology Group Zoology DepartmentFaculty of ScienceAin Shams UniversityCairoEgypt Faculty of Basic Science King Salman International UniversitySouth SinaiEgypt

Galectins are sticky molecules that bind toβ-galactoside.Their interactions render them essential players in many cellular processes.The imbalance of galectin expression was reported in many diseases.In cancer,galectins interact with the extracellular matrix,evade the immune system,and potentially have broad interactions with blood components.In the last ten years,since 2010,we did focus on galectin research in different cancer types.Ourﬁndings showed an interaction between cancer cells and erythrocytes via galectin-4.moreover,we found that upregulation of galectins was associated with lymph node metastasis in ovarian cancers.Hence,with this,we shortly review some important aspects of galectins and their potential importance in more profound understanding of cancer progression and theﬁeld of cancer biomarkers.

关键词： Galectins Cancer metastasis Erythrocytes Invasion

A New Hybrid model for Segmentation of the Skin Lesion Based on Residual Attention U-Net

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Computers, materials & Continua 2023年第6期75卷 5177-5192页

作者： Saleh Naif Almuayqil reham Arnous Noha Sakr magdy m.Fadel Department of Information Systems College of Computer and Information SciencesJouf UniversitySakakaSaudi Arabia Department of Communications and Electronics Delta Higher Institute for Engineering and Technology(DHIET)MansouraEgypt Computers Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansouraEgypt

Skin segmentation participates significantly in various biomedical applications,such as skin cancer identification and skin lesion detection.This paper presents a novel framework for segmenting the skin.The framework contains two main stages:The first stage is for removing different types of noises from the dermoscopic images,such as hair,speckle,and impulse noise,and the second stage is for segmentation of the dermoscopic images using an attention residual U-shaped Network(U-Net).The framework uses variational Autoencoders(VAEs)for removing the hair noises,the Generative Adversarial Denoising Network(DGAN-Net),the Denoising U-shaped U-Net(D-U-NET),and Batch Renormalization U-Net(Br-U-NET)for remov-ing the speckle noise,and the Laplacian Vector median Filter(mLVmF)for removing the impulse noise.In the second main stage,the residual attention u-net was used for segmentation.The framework achieves(35.11,31.26,27.01,and 26.16),(36.34,33.23,31.32,and 28.65),and(36.33,32.21,28.54,and 27.11)for removing hair,speckle,and impulse noise,respectively,based on Peak Signal Noise Ratio(PSNR)at the level of(0.1,0.25,0.5,and 0.75)of noise.The framework also achieves an accuracy of nearly 94.26 in the dice score in the process of segmentation before removing noise and 95.22 after removing different types of noise.The experiments have shown the efficiency of the used model in removing noise according to the structural similarity index measure(SSIm)and PSNR and in the segmentation process as well.

关键词： Skin tumor speckle noise impulse noise hair noise deep learning segmentation

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 2019.Discovering the infected people is the most important factor in the fight against the disease.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 results.Examining Computed Tomography(CT)images to diagnose patients infected with COVID-19 has become an urgent necessity.In this study,we propose a residual attention deep support vector data description SVDD(RADSVDD)approach to diagnose COVID-19.It is a novel approach combining residual attention with deep support vector data description(DSVDD)to classify the CT images.To the best of our knowledge,we are the first to combine residual attention with DSVDD in general,and specifically in the diagnosis of COVID-19.Combining attention with DSVDD naively may cause model collapse.Attention in the proposed RADSVDD guides the network during training and enables quick learning,residual connectivity prevents vanishing gradients.Our approach consists of three models,each model is devoted to recognizing one certain disease and classifying other diseases as anomalies.These models learn in an end-to-end fashion.The proposed approach attained high performance in classifying CT images into intact,COVID-19,and non-COVID-19 pneumonia.To evaluate the proposed approach,we created a dataset from published datasets and had it assessed by an experienced radiologist.The 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

The Impact of Inoculum Preparation media on Pollutant Removal through Phycoremediation of Agricultural Drainage Water by Desmodesmus sp.

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国际实验植物学杂志(英文) 2023年第10期92卷 2875-2890页

作者： Asmaa Salah Hoda Sany Abo El-Khair B.El-Sayed reham m.El-Bahbohy Heba I.mohamed Ayman Amin Plant Physiology Division Department of Agricultural BotanyFaculty of AgricultureCairo UniversityGizaP.O.Box 12613Egypt Algal Biotechnology Unit National Research CentreDokkiGiza12622Egypt Biological and Geological Science Department Faculty of EducationAin Shams UniversityCairo11341Egypt

Water is the most essential natural resource for the future development.Agriculture production is extensively water-dependent and a significant polluter of water resources.So,this work investigated the effect of two different preparation media[Bold’s Basal medium(BBm)and Domiati cheese whey(DCW)]for agricultural drainage water(ADW)remediation.All treatments were incubated for 6 days.According to the results of biomass productivity,specific growth rate,photosynthetic pigments,and biochemical composition,Desmodesmus sp.can grow in drainage water without dilution.The two treatments significantly reduced the concentration of nitrate,phosphate,chemical oxygen demand,and sodium in ADW.Finally,using cheese whey with BBm as inoculum preparation media enhanced the lipid accumulation in the algal biomass(25.4%w/w)and gave the best biodiesel properties among treatments.Therefore,combining remediation of drainage water with microalgae mass production can achieve the sustainability of agriculture.

关键词： Desmodesmus sp. drainage water nutrients recycle photosynthetic pigments phycoremediation water scarcity

Functional outcome of the low vision aids for visual impairment secondary to central nervous system tumors in children

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International Journal of Ophthalmology(English edition) 2019年第10期12卷 1643-1648页

作者： Rania GE Zaki reham F.Elshinawy Karim m.Naguib Department of Ophthalmology Faculty of Medicine Ain Shams University

To assess functional outcomes of optical low vision aids(LVAs) for pediatric visual impairment due to central nervous system(CNS) tumors. A prospective case study was conducted on 15 children with history of CNS tumors with mean age of 10.47±1.85 y. Lighthouse distance, near visual acuity tests, cycloplegic refraction, reading speed measurement and visual field examination were done. Prescription of far and near LVAs followed by training sessions. LVPrasad-functional vision questionnaire was done to evaluate performance. Visual impairment was moderate(13.3%), severe(73.3%), profound(6.7%) and near blindness in 6.7%. Telescopes prescribed in 33.4%, video magnifier in 46.7%. Questionnaire scores were significantly improved for distant rather than near tasks(P≤0.05) after training. LVAs rehabilitation is an effective method of improving vision in pediatric visual defects secondary to CNS tumors.

关键词： visual impairment low vision aids central nervous system tumors

Adaptive Dynamic Dipper Throated Optimization for Feature Selection in medical Data

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Computers, materials & Continua 2023年第4期75卷 1883-1900页

作者： Ghada Atteia El-Sayed m.El-kenawy Nagwan Abdel Samee mona m.Jamjoom Abdelhameed Ibrahim Abdelaziz A.Abdelhamid Ahmad Taher Azar Nima Khodadadi reham A.Ghanem mahmoud Y.Shams Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Faculty of Computers and Artificial Intelligence Benha UniversityBenha13518Egypt College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Civil Engineering University of Science and TechnologyMiami33101USA Department of Civil and Environmental Engineering Florida International UniversityMiamiUSA Oral Biology Department Faculty of Oral and Dental MedicineDelta University for Science and TechnologyGamasaEgypt Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33511Egypt

The rapid population growth results in a crucial problem in the early detection of diseases inmedical research.Among all the cancers unveiled,breast cancer is considered the second most severe cancer.Consequently,an exponential rising in death cases incurred by breast cancer is expected due to the rapid population growth and the lack of resources required for performing medical diagnoses.Utilizing recent advances in machine learning could help medical staff in diagnosing diseases as they offer effective,reliable,and rapid responses,which could help in decreasing the death risk.In this paper,we propose a new algorithm for feature selection based on a hybrid between powerful and recently emerged optimizers,namely,guided whale and dipper throated optimizers.The proposed algorithm is evaluated using four publicly available breast cancer datasets.The evaluation results show the effectiveness of the proposed approach from the accuracy and speed perspectives.To prove the superiority of the proposed algorithm,a set of competing feature selection algorithms were incorporated into the conducted experiments.In addition,a group of statistical analysis experiments was conducted to emphasize the superiority and stability of the proposed algorithm.The best-achieved breast cancer prediction average accuracy based on the proposed algorithm is 99.453%.This result is achieved in an average time of 3.6725 s,the best result among all the competing approaches utilized in the experiments.

关键词： medical dataset breast cancer guided whale optimizer dipper throated optimizer feature selection meta-heuristics