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Low testing rates and high BRCA prevalence: Poly (ADP-ribose) polymerase inhibitor use in Middle East BRCA/homologous recombination deficiency-positive cancer patients

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World Journal of Clinical Oncology 2024年第7期15卷 848-858页

作者： Naveed Syed Ashish Vittalrao Chintakuntlawar Deepti Vilasini aisha mohamed al salami Riad al Hasan Imrana Afrooz Kanishka Uttam Chandani Ashok Uttam Chandani Aref Chehal Department of Hematology and Oncology Sheikh Shakbout Medical CityAbu Dhabi 11001United Arab Emirates Department of Oncology Mayo ClinicRochesterNY 790339United States Department of Oncology Sheikh Shakbout Medical CityAbu Dhabi 11001United Arab Emirates Clinical Research Sheikh Shakbout Medical CityAbu Dhabi 11001United Arab Emirates Department of Internal Medicine Landmark Medical CenterRhode IslandRI 02895United States

BACKGROUND Poly(ADP-ribose)polymerase inhibitors(PARPis)are approved as first-line therapies for breast cancer gene(BRCA)-positive,human epidermal growth factor receptor 2-negative locally advanced or metastatic breast *** are also effective for new and recurrent ovarian cancers that are BRCA-or homologous recombination deficiency(HRD)-***,data on these mutations and PARPi use in the Middle East are *** To assess BRCA/HRD prevalence and PARPi use in patients in the Middle East with breast/ovarian *** This was a single-center retrospective study of 57 of 472 breast cancer patients tested for BRCA mutations,and 25 of 65 ovarian cancer patients tested for *** adult patients participated in at least four visits to the oncology service at our center between August 2021 and May *** were summarized using descriptive statistics and compared using counts and *** to treatment was assessed using Response Evaluation Criteria in Solid Tumors *** Among the 472 breast cancer patients,12.1%underwent BRCA testing,and 38.5%of 65 ovarian cancer patients received HRD *** mutations were found in 25.6%of the tested patients:26.3%breast cancers had germline BRCA(gBRCA)mutations and 24.0%ovarian cancers showed ***,40.0%of gBRCA-positive breast cancers and 66.0%of HRD-positive ovarian cancers were Middle Eastern and Asian patients,*** treatment was used in 5(33.3%)gBRCA-positive breast cancer patients as first-line therapy(n=1;7-months progression-free),for maintenance(n=2;>15-months progression-free),or at later stages due to compliance issues(n=2).Four patients(66.6%)with HRD-positive ovarian cancer received PARPi and all remained *** Lower testing rates but higher BRCA mutations in breast cancer were *** reflected United Arab Emirates demographics,with breast cancer in Middle Eastern and ovarian cancer in Asian patients.

关键词： Homologous recombination repair BRCA1 BRCA2 Homologous recombination deficiency Ovarian cancer Breast cancer Poly(ADP-ribose)polymerase inhibitors Olaparib DNA double-strand breaks

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Enhancing Patient Safety in the Operating Room: A Comprehensive Guide from a Nurse’s Perspective

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Open Journal of Nursing 2024年第6期14卷 252-266页

作者： aisha mohamed Hussein Operating Room Nurse Dr. Sulaiman Al-Habib Medical Group Bone Joint and Spine Hospital Riyadh Saudi Arabia

Ensuring patient safety within the operating room is a paramount concern in contemporary healthcare, and this guide aims to provide an in-depth exploration of this crucial aspect from the perspective of nurses. Nurses play a pivotal role in supporting surgeons and maintaining a safe environment for patients undergoing various medical procedures.

关键词： Operating Room Patient Safety Nurses

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Occupational health risks among healthcare workers during the COVID-19 pandemic in Saudi Arabia: preparing for the future pandemics

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Nursing Communications 2024年第2期8卷 1-5页

作者： Reham Suliman al Kharyef aisha ali al Harbi Mohammed Abdelhamied Genedy mohamed K.M.Khalil Suliman mohamed al Eidi Ministry of Health Riyadh 13352Saudi Arabia Consultant Public Health and Research Development.Cairo 11728 Egypt

Background:This study aimed to assess the occupational risks encountered by Healthcare Workers(HCWs)in Saudi Arabia during the COVID-19 ***:A cross-sectional survey was carried out from May to October *** a multi-stage stratified random sampling technique,an online questionnaire was sent to the recruited HCWs,across Saudi ***:Of the 768 HCWs recruited,702 participated in the survey.A significant majority(over 80%)reported working beyond 8 hours ***-19 infection,confirmed via PCR,was identified in 25%of the ***,infection was significantly correlated with direct or close contact(p=0.0007).Psychological distress was reported by 81%,with anxiety being the most prevalent(33%),followed by stress(19%),depression(17%),and insomnia(12%).Around 20%experienced headaches post-PPE use,while 14%reported adverse skin reactions,predominantly allergy and dermatitis.A concerning one-third of respondents reported exposure to ***:High infection rate,physical and psychological risks among HCWs especially those in direct contact with patients,reflect the need for enhancing the entirety of outbreak preparedness and response,specifically *** surveillance system,is crucial to adequately monitor and support HCWs during pandemic scenarios.

关键词： COVID-19 pandemic healthcare worker risk Saudi Arabia

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The impacts of altitude and seed pretreatments on seedling emergence of Syrian juniper (Juniperus drupacea (Labill.) Ant. et Kotschy)

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Ecological Processes 2021年第1期10卷 112-117页

作者： Cengiz Yucedag Mehmet Cetin Halil Baris Ozel Adel Easa Saad Abo aisha Osama B.Muragaa alrabiti Akram mohamed Omar al.JAMA Faculty of Engineering-Architecture Department of Landscape ArchitectureBurdur Mehmet Akif Ersoy UniversityBurdurTurkey. Faculty of Engineering and Architecture Department of Landscape ArchitectureKastamonu UniversityKuzeykent Campus37150 KastamonuTurkey Faculty of Forestry Department of Forest EngineeringBartin UniversityBartinTurkey Institute of Science and Technology Graduate Programs of Material Science and EngineeringKastamonu UniversityKastamonuTurkey.

Background:Syrian juniper is an economically important species and in danger of *** these reasons,the best seedling production methods of the species should be determined and its plantations should be *** aim of the study is to examine the impacts of altitude and different pretreatment combinations of cold and warm stratifications,citric acid,shaking seeds in bottles with crushed glass,and different stimulating agents including Baikal EM1,Biohumus,Polystimulin A6 and K hormones(PS-A6 and PS-K)on seed germination of Syrian *** conduct the study,the cones of the Syrian junipers were collected from three different altitudes(1000,1200,and 1400 m a.s.l.)within the boundaries of Forest Management Directorate of Bozyazı,Mersin in *** seeds were subjected to three replicates per one treatment(altitude in interaction with pretreatment).There were 100 seeds per ***:Two-way ANOVA revealed significant effects of altitude,pretreatment,and their interaction on seedling emergence of Syrian *** from higher altitudes had higher germination rates in all *** highest percent emergence(85%)was recorded in the combination consisting of shaking with crushed glass,both cold and warm stratification,and successive application of stimulators PS-A6 and *** the treatments with most germinating seeds encompassed shaking in crushed glass or soaking in citric acid,both warm and cold stratifications,and application of stimulating ***:The use of seeds from higher altitudes should be considered for seedling production of Syrian juniper due to their higher germination *** altitudinal differences,specific pretreatments can rise germination potential more than twofold.

关键词： Auxin Citric acid Cytokine Germination Stratification

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Malicious URL Classification Using Artificial Fish Swarm Optimization and Deep Learning

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Computers, Materials & Continua 2023年第1期74卷 607-621页

作者： Anwer Mustafa Hilal aisha Hassan Abdalla Hashim Heba G.mohamed mohamed K.Nour Mashael M.Asiri ali M.al-Sharafi Mahmoud Othman Abdelwahed Motwakel Department of Electrical and Computer Engineering International Islamic University Malaysia 53100 Kuala LumpurMalaysia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Electrical Engineering College of EngineeringPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Computer Science College of Computers and Information TechnologyUniversity of BishaSaudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt

Cybersecurity-related solutions have become familiar since it ensures security and privacy against cyberattacks in this digital *** Uniform Resource Locators(URLs)can be embedded in email or Twitter and used to lure vulnerable internet users to implement malicious data in their *** may result in compromised security of the systems,scams,and other such *** attacks hijack huge quantities of the available data,incurring heavy financial *** the same time,Machine Learning(ML)and Deep Learning(DL)models paved the way for designing models that can detect malicious URLs accurately and classify *** this motivation,the current article develops an Artificial Fish Swarm algorithm(AFSA)with Deep Learning Enabled Malicious URL Detection and Classification(AFSADL-MURLC)*** presented AFSADL-MURLC model intends to differentiate the malicious URLs from genuine *** attain this,AFSADL-MURLC model initially carries out data preprocessing and makes use of glove-based word embedding *** addition,the created vector model is then passed onto Gated Recurrent Unit(GRU)classification to recognize the malicious ***,AFSA is applied to the proposed model to enhance the efficiency of GRU *** proposed AFSADL-MURLC technique was experimentally validated using benchmark dataset sourced from Kaggle *** simulation results confirmed the supremacy of the proposed AFSADL-MURLC model over recent approaches under distinct measures.

关键词： Malicious URL cybersecurity deep learning machine learning metaheuristics gated recurrent unit

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Water Wave Optimization with Deep Learning Driven Smart Grid Stability Prediction

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Computers, Materials & Continua 2022年第12期73卷 6019-6035页

作者： Anwer Mustafa Hilal aisha Hassan Abdalla Hashim Heba G.mohamed Mohammad alamgeer mohamed K.Nour Anas Abdelrahman Abdelwahed Motwakel Department of Electrical and Computer Engineering International Islamic University MalaysiaKuala Lumpur53100Malaysia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam Bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Electrical Engineering College of EngineeringPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Computer Science and Bioinformatics Singhania UniversityPacheri BariJhnujhunuRajasthanIndia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Mechanical Engineering Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11835Egypt

Smart Grid(SG)technologies enable the acquisition of huge volumes of high dimension and multi-class data related to electric power grid operations through the integration of advanced metering infrastructures,control systems,and communication *** SGs,user demand data is gathered and examined over the present supply criteria whereas the expenses are then informed to the clients so that they can decide about electricity *** the entire procedure is valued on the basis of time,it is essential to perform adaptive estimation of the SG’s *** advancements inMachine Learning(ML)andDeep Learning(DL)models enable the designing of effective stability prediction models in *** this background,the current study introduces a novel Water Wave Optimization with Optimal Deep Learning Driven Smart Grid Stability Prediction(WWOODL-SGSP)*** aim of the presented WWOODL-SGSP model is to predict the stability level of SGs in a proficient *** attain this,the proposed WWOODL-SGSP model initially applies normalization process to scale the data to a uniform ***,WWO algorithm is applied to choose an optimal subset of features from the pre-processed ***,Deep Belief Network(DBN)model is followed to predict the stability level of ***,Slime Mold algorithm(SMA)is exploited to fine tune the hyperparameters involved in DBN *** order to validate the enhanced performance of the proposedWWOODL-SGSP model,a wide range of experimental analyses was *** simulation results confirmthe enhanced predictive results of WWOODL-SGSP model over other recent approaches.

关键词： Smart grid stability prediction deep learning energy systems machine learning metaheursitics

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Spotted Hyena Optimizer with Deep Learning Driven Cybersecurity for Social Networks

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Computer Systems Science & Engineering 2023年第5期45卷 2033-2047页

作者： Anwer Mustafa Hilal aisha Hassan Abdalla Hashim Heba G.mohamed Lubna A.alharbi mohamed K.Nour Abdullah mohamed Ahmed S.almasoud Abdelwahed Motwakel Department of Electrical and Computer Engineering International Islamic University MalaysiaKuala Lumpur53100Malaysia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Electrical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTabuk UniversityTabuk47512Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversityMecca24382Saudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Information Systems College of Computer and Information SciencesPrince Sultan UniversityRiyadh12435Saudi Arabia

Recent developments on Internet and social networking have led to the growth of aggressive language and hate *** provocation,abuses,and attacks are widely termed cyberbullying(CB).The massive quantity of user generated content makes it difficult to recognize *** advancements in machine learning(ML),deep learning(DL),and natural language processing(NLP)tools enable to detect and classify CB in social *** this view,this study introduces a spotted hyena optimizer with deep learning driven cybersecurity(SHODLCS)model for *** presented SHODLCS model intends to accomplish cybersecurity from the identification of CB in the *** achieving this,the SHODLCS model involves data pre-processing and TF-IDF based feature *** addition,the cascaded recurrent neural network(CRNN)model is applied for the identification and classification of ***,the SHO algorithm is exploited to optimally tune the hyperparameters involved in the CRNN model and thereby results in enhanced classifier *** experimental validation of the SHODLCS model on the benchmark dataset portrayed the better outcomes of the SHODLCS model over the recent approaches.

关键词： Cybersecurity cyberbullying online social network deep learning spotted hyena optimizer

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Hyperparameter Tuned Deep Learning Enabled Intrusion Detection on Internet of Everything Environment

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Computers, Materials & Continua 2022年第12期73卷 6579-6594页

作者： Manar Ahmed Hamza aisha Hassan Abdalla Hashim Heba G.mohamed Saud S.alotaibi Hany Mahgoub Amal S.Mehanna Abdelwahed Motwakel Department of Electrical and Computer Engineering International Islamic University MalaysiaKuala Lumpur53100Malaysia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Electrical Engineering College of EngineeringPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Faculty of Computers and Information Computer Science DepartmentMenoufia UniversityEgypt Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11845Egypt

Internet of Everything(IoE),the recent technological advancement,represents an interconnected network of people,processes,data,and *** recent times,IoE gained significant attention among entrepreneurs,individuals,and communities owing to its realization of intense values from the connected *** the other hand,the massive increase in data generation from IoE applications enables the transmission of big data,from contextawaremachines,into useful *** and privacy pose serious challenges in designing IoE environment which can be addressed by developing effective Intrusion Detection Systems(IDS).In this background,the current study develops Intelligent Multiverse Optimization with Deep Learning Enabled Intrusion Detection System(IMVO-DLIDS)for IoT *** presented IMVO-DLIDS model focuses on identification and classification of intrusions in IoT *** proposed IMVO-DLIDS model follows a three-stage *** first,data pre-processing is performed to convert the actual data into useful *** addition,Chaotic Local Search Whale Optimization algorithm-based Feature Selection(CLSWOA-FS)technique is employed to choose the optimal feature ***,MVO algorithm is exploited with Bidirectional Gated Recurrent Unit(BiGRU)model for ***,the novelty of the work is the application of MVO algorithm in fine-turning the hyperparameters involved in BiGRU *** experimental validation was conducted for the proposed IMVO-DLIDS model on benchmark datasets and the results were assessed under distinct *** extensive comparative study was conducted and the results confirmed the promising outcomes of IMVO-DLIDS approach compared to other approaches.

关键词： Internet of everything deep learning feature selection classification intrusion detection cybersecurity

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Utility of 2-Methyl-quinazolin-4(3H)-one in the Synthesis of Heterocyclic Compounds with Anticancer Activity

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Open Journal of Medicinal Chemistry 2014年第1期4卷 12-37页

作者： aisha Youssif Hassan Helali Marwa Taha Mostafa Sarg Makarem mohamed Said Koraa Mona Said Fathy El-Zoghbi Department of Chemistry Faculty of Science (Girls) Al-Azhar University Cairo Egypt Department of Organic Chemistry Faculty of Pharmacy (Girls) Al-Azhar University Cairo Egypt Department of Organic Chemistry Faculty of Pharmacy Cairo University Giza Egypt

Quinolino[2,1-b]quinazolines 3 and 4, pyrrolo[2,1-b]quinazoline 5 and various substituted 2-(4-chlorostyryl)quinazoline derivatives including: 4-amino derivative 8, 4-hydrazino derivative 9, thiourea derivative 10, thiosemicarbazide derivative 19, 4-benzylidene hydrazinyl derivative 21, 4-amino thiazolidene derivatives 11, 12, 13, 22, imidazoquinazolines 15, 16, quinazolinium chloride 14, triazino[4,3-c]quinazolines 17, 18, tetrazino[1,6-c]quinazoline 20, 4-amino azetidinyl derivative 23, triazolo[4,3-c]quinazoline 24, 4-amino substituted quinazolines 25, 26, 27, 29 and quinazolino quinazoline 28 were synthesized through different chemical reactions. The obtained compounds were evaluated for their in vitro antitumor activity against HEPG2 and MCF-7 cell lines compared to the reference drug (doxorubicin). Compounds 18, 19, 20, 23 and 24 were found to be the most active against both cell lines exhibiting IC50 values ranging from 10.82 - 29.46 μM/L and 7.09 - 31.85 μM/L against Hep-G2 and MCF-7 cell lines, respectively, in addition to docking study of these five compounds against thymidylate synthase and dihydrofolate reductase enzymes active sites.

关键词： Quinazoline Anticancer DHFR TS

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