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Opposite Modulatory Effects of Crataegus aronia Aqueous Extract on Platelet Aggregation in Rats

Chinese Journal of Integrative Medicine 2021年第9期27卷 696-704页

作者： Abdullah S.Shatoor ali Shati S.al Humayed Sultan al-Qahtani mahmoud alkhateeb Department of Medicine Cardiology SectionCollege of MedicineKing Khalid UniversityAbha(64121)Saudi Arabia Department of Biology College of ScienceCollege of MedicineKing Khalid UniversityAbha(64121)Saudi Arabia Department of Physiology College of MedicineKing Saud bin Abdulaziz University for Health SciencesRiyadh(11481)Saudi Arabia

Objectives:To reveal the mechanisms behind the dual effects of Crataegus aronia(***)aqueous extract on platelet aggregation by focusing on function,regulation,expression,and signaling of platelets P_(2)Y_(12)***:Adult male Wistar rats(120±10 g)were classified as control received the vehicle,***(200 mg/kg),and ***(2,000 mg/kg)-treated *** treatments for consecutive 7 days,hematological and molecular experiments were conducted to detect alterations in platelet aggregation,thromboxane B2(THXB2)and intracellular reactive oxygen species(ROS)content;protein levels of P_(2)Y_(12),p-Akt,cyclic adenosine monophosphate(c AMP),phosphorylated vasodilator-stimulated-phosphoprotein(p-VASP),nuclear factorκB(NF-κB),P-selectin,*** platelets were determined by Western blot;m RNA expressions of P_(2)Y_(12)and some inflammatory markers were determined by real-time polymerase chain ***:At a concentration of 200 mg/kg,*** inhibited platelet aggregation through multiple interconnected mechanisms including downregulation P_(2)Y_(12)synthesis and expression,stimulating intracellular cAMP levels and protein levels of p-VASP,inhibiting platelets THXB2 release and protein levels of ***,it inhibited platelets level of ROS and of NF-κB,a major signaling pathway that stimulates the expression of P_(2)Y_(12)and THXA2 *** findings were seen in platelets of rats received *** at a concentration of 2,000 mg/***,co-administration of N-acetylcysteine prevented all hematological and molecular alterations exerted by the high dose of the extract and inhibited platelet ***:Oral administration of *** at low dose inhibits platelet aggregation by reducing THXB2 release,expression of P-selectin and activating c AMP and Akt signaling through two major mechanisms including downregulation of P_(2)Y_(12)and inhibition of ROS-induced activation of NF-κB,an effect that is observed to be in the

关键词： Crataegus aronia platelets aggregation P_(2)Y_(12) Intracellular cyclic adenosine monophosphate reactive oxygen species nuclear factorκB

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Enhanced Artificial Intelligence-based Cybersecurity Intrusion Detection for Higher Education Institutions

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Computers, Materials & Continua 2022年第8期72卷 2895-2907页

作者： Abdullah S.al-Malaise al-Ghamdi mahmoud Ragab Maha Farouk S.Sabir Information Systems Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Centre of Artificial Intelligence for Precision Medicines King Abdulaziz UniversityJeddah21589Saudi Arabia Mathematics Department Faculty of ScienceAl-Azhar UniversityNaser City11884CairoEgypt

As higher education institutions(HEIs)go online,several benefits are attained,and also it is vulnerable to several kinds of *** accomplish security,this paper presents artificial intelligence based cybersecurity intrusion detection models to accomplish *** incorporation of the strategies into business is a tendency among several distinct industries,comprising education,have recognized as game ***,the HEIs are highly related to the requirement and knowledge of the learner,making the education procedure highly ***,artificial intelligence(AI)and machine learning(ML)models have shown significant interest in *** study designs a novel Artificial Intelligence based Cybersecurity Intrusion Detection Model for Higher Education Institutions named AICIDHEI *** goal of the AICID-HEI technique is to determine the occurrence of distinct kinds of intrusions in higher education *** AICID-HEI technique encompassesmin-max normalization approach to preprocess the ***,the AICID-HEI technique involves the design of improved differential evolution algorithm based feature selection(IDEA-FS)technique is applied to choose the feature ***,the bidirectional long short-term memory(BiLSTM)model is utilized for the detection and classification of intrusions in the ***,the Adam optimizer is applied for hyperparameter tuning to properly adjust the hyperparameters in higher educational *** order to validate the experimental results of the proposed AICID-HEI technique,the simulation results of the AICIDHEI technique take place by the use of benchmark *** experimental results reported the betterment of the AICID-HEI technique over the other methods interms of different measures.

关键词： Higher education institutions deep learning machine learning cybersecurity intrusion detection

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Cyclooxygenase-2 expression as a predictor of outcome in colorectal carcinoma

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World Journal of Gastroenterology 2012年第15期18卷 1793-1799页

作者： Jaudah al-Maghrabi Abdelbaset Buhmeida Eman Emam Kari Syrjnen Abdulrahman Sibiany Mohmmad al-Qahtani mahmoud al-Ahwal Department of Pathology King Abdulaziz UniversityJeddah 21589Saudi Arabia Center of Excellence in Genomic Medicine Research King Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Oncology and Radiotherapy Turku University HospitalT-Hospital(Administration)FIN20521 TurkuFinland Department of Surgery King Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Medicine Scientific Chair for Colorectal CancerKing Abdulaziz UniversityJeddah 21589Saudi Arabia

AIM:To correlate cyclooxygenase-2(COX-2)expression profile with clinical and pathological variables to assess their prognostic/predictive value in colorectal carcinoma(CRC).METHODS:Archival tumor samples were analyzed using immunohistochemistry for COX-2 expression in 94 patients with *** were diagnosed and treatedat the Departments of Surgery and Oncology,King Abdulaziz University Hospital,Saudi ***:Fifty-six percent of the tumors showed positive cytoplasmic COX-2 expression,whereas 44%of cases were completely *** were no significant correlations between COX-2 expression and sex,age,grade or tumor ***,COX-2 expression revealed a significant correlation with tumor stage(P=0.01)and distant metastasis(P=0.02),and a borderline association with lymph node involvement(P =0.07).Tumors with high COX-2 expression showed a higher recurrence rate than tumors with no expression(Pal analysis,there was a significant(P=0.026)difference in disease-free survival between COX-2-positive and negative tumors in favor of the ***-2 expression did not significantly predict disease-specific survival,which was much shorter for COX-2-positive *** multivariate(COX)models,COX-2 did not appear among the independent predictors of disease-free survival or disease-specific ***:COX-2 expression seems to provide useful prognostic information in CRC,while predicting the patients at high risk for recurrent disease.

关键词： Colorectal carcinoma Cyclooxygenase-2 Immunohistochemistry Disease outcome Adjuvant therapy

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Influence of non-uniform electric field distribution on the atmospheric pressure air dielectric barrier discharge

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Plasma Science and Technology 2021年第7期23卷 78-84页

作者： Weisheng CUI Shuai ZHAO Zhengfang QIAN Yiling SUN mahmoud al-SalIHI Xiangquan DENG Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhen 518060People’s Republic of China Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094People’s Republic of China

The dielectric barrier discharge(DBD)in air at atmospheric pressure is not suitable for industrial applications due to its randomly distributed discharge *** this paper,the influence of the electric field distribution on the uniformity of DBD is theoretically analyzed and experimentally *** is found that a certain degree of uneven electric field distributions can control the development of electron avalanches and regulate their transition to streamers in the *** discharge phenomena and electrical characteristics prove that an enhanced Townsend discharge can be formed in atmospheric-pressure air with a curved-plate *** spectral analysis further confirms that the gas temperature of the plasma produced by the curved-plate electrode is close to room temperature,which is beneficial for industrial *** paper presents the relationship between the electron avalanche transition and the formation of a uniform DBD,which can provide some references for the development and applications of the DBD in the future.

关键词： dielectric barrier discharge electric field distribution electron avalanche Townsend discharge

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Deep Learning Approach for COVID-19 Detection in Computed Tomography Images

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Computers, Materials & Continua 2021年第5期67卷 2093-2110页

作者： Mohamad mahmoud al Rahhal Yakoub Bazi Rami M.Jomaa Mansour Zuair Naif al Ajlan Department of Applied Computer Science College of Applied Computer EngineeringKing Saud UniversityRiyadh11362Saudi Arabia Department of Computer Engineering College of Computer and Information ScienceKing Saud UniversityRiyadh11362Saudi Arabia Department of Computer Science College of Computer and Information ScienceKing Saud UniversityRiyadh11362Saudi Arabia

With the rapid spread of the coronavirus disease 2019(COVID-19)worldwide,the establishment of an accurate and fast process to diagnose the disease is *** routine real-time reverse transcription-polymerase chain reaction(rRT-PCR)test that is currently used does not provide such high accuracy or speed in the screening *** the good choices for an accurate and fast test to screen COVID-19 are deep learning *** this study,a new convolutional neural network(CNN)framework for COVID-19 detection using computed tomography(CT)images is *** EfficientNet architecture is applied as the backbone structure of the proposed network,in which feature maps with different scales are extracted from the input CT scan *** addition,atrous convolution at different rates is applied to these multi-scale feature maps to generate denser features,which facilitates in obtaining COVID-19 findings in CT scan *** proposed framework is also evaluated in this study using a public CT dataset containing 2482 CT scan images from patients of both classes(i.e.,COVID-19 and non-COVID-19).To augment the dataset using additional training examples,adversarial examples generation is *** proposed system validates its superiority over the state-of-the-art methods with values exceeding 99.10%in terms of several metrics,such as accuracy,precision,recall,and *** proposed system also exhibits good robustness,when it is trained using a small portion of data(20%),with an accuracy of 96.16%.

关键词： COVID-19 deep learning computed tomography multi-scale features atrous convolution adversarial examples

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Decoding molecular mechanisms:brain aging and alzheimer's disease

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Neural Regeneration Research 2025年第8期20卷 2279-2299页

作者： Mahnoor Hayat Rafay ali Syed Hammad Qaiser Mohammad Uzair Khalid al-Regaiey Roaa Khallaf Lubna Abdullah Mohammed albassam Imdad Kaleem Xueyi Wang Ran Wang Mehwish SBhatti Shahid Bashir Atta-ur-Rahman School of Applied Biosciences(ASAB) National University of Sciences and Technology(NUST)IslamabadPakistan Department of Biotechnology Quaid-i-Azam UniversityIslamabadPakistan Department of Biological Sciences Faculty of Basic&Applied SciencesInternational Islamic University Islamabad(IIUI)IslamabadPakistan Department of Bioengineering King Fahd University of Petroleum and MineralsDhahranSaudi Arabia Department of Physiology College of MedicineKing Saud UniversityRiyadhSaudi Arabia Department of Neurology Neuroscience CenterKing Fahad Specialist HospitalDammamSaudi Arabia Department of Mental Health Neuroscience CenterKing Fahad Specialist HospitalDammamSaudi Arabia Department of Biosciences Commission on Science and Technology for Sustainable Development in the South(COMSATS University)IslamabadPakistan Department of Psychiatry The First Hospital of Hebei Medical UniversityShijiazhuangHebei ProvinceChina Mental Health Institute of Hebei Medical University ShijiazhuangHebei ProvinceChina Department of Neurobiology and Behavior University of CaliforniaIrvineCAUSA Neuroscience Center King Fahad Specialist Hospital DammamDammamSaudi Arabia

The complex morphological,anatomical,physiological,and chemical mechanisms within the aging brain have been the hot topic of research for *** aging process alters the brain structure that affects functions and cognitions,but the worsening of such processes contributes to the pathogenesis of neurodegenerative disorders,such as alzheimer's *** these observable,mild morphological shifts,significant functional modifications in neurotransmission and neuronal activity critically influence the aging *** these changes is important for maintaining cognitive health,especially given the increasing prevalence of age-related conditions that affect *** review aims to explore the age-induced changes in brain plasticity and molecular processes,differentiating normal aging from the pathogenesis of alzheimer's disease,thereby providing insights into predicting the risk of dementia,particularly alzheimer's disease.

关键词： alzheimer’s disease brain aging cognitive health dementia molecular mechanisms neuronal activity neuroplasticity neurotransmission

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Optimal Logistics Activities Based Deep Learning Enabled Traffic Flow Prediction Model

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Computers, Materials & Continua 2022年第12期73卷 5269-5282页

作者： Basim aljabhan mahmoud Ragab Sultanah M.alshammari Abdullah S.al-Malaise al-Ghamdi Ports and Maritime Transportation Department Faculty of Maritime StudiesKing Abdulaziz UniversityJeddah21589Saudi Arabia Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Mathematics Faculty of ScienceAl-Azhar UniversityNaser City11884CairoEgypt Center of Excellence in Smart Environment Research King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Information Systems Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia S 7Information Systems Department HECI SchoolDar Alhekma UniversityJeddahSaudi Arabia

Traffic flow prediction becomes an essential process for intelligent transportation systems(ITS).Though traffic sensor devices are manually controllable,traffic flow data with distinct length,uneven sampling,and missing data finds challenging for effective *** traffic data has been considerably increased in recent times which cannot be handled by traditional mathematical *** recent developments of statistic and deep learning(DL)models pave a way for the effectual design of traffic flow prediction(TFP)*** this view,this study designs optimal attentionbased deep learning with statistical analysis for TFP(OADLSA-TFP)*** presentedOADLSA-TFP model intends to effectually forecast the level of traffic in the *** attain this,the OADLSA-TFP model employs attention-based bidirectional long short-term memory(ABLSTM)model for predicting traffic *** order to enhance the performance of the ABLSTM model,the hyperparameter optimization process is performed using artificial fish swarm algorithm(AFSA).A wide-ranging experimental analysis is carried out on benchmark dataset and the obtained values reported the enhancements of the OADLSA-TFP model over the recent approaches mean square error(MSE),root mean square error(RMSE),and mean absolute percentage error(MAPE)of 120.342%,10.970%,and 8.146%respectively.

关键词： Traffic flow prediction deep learning artificial fish swarm algorithm mass gatherings statistical analysis logistics

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Investigation into the effect of silica nanoparticles on the rheological characteristics of water-in-heavy oil emulsions

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Petroleum Science 2019年第6期16卷 1374-1386页

作者： O.S.alade D.A.al Shehri M.mahmoud Department of Petroleum Engineering College of Petroleum and GeosciencesKing Fahd University of Minerals and PetroleumDhahranSaudi Arabia

The effect of silica nanoparticles on the rheological characteristics of water-in-heavy oil emulsions has been *** oil recovery methods for heavy oil production(most especially,thermal fluid injection)usually result in the formation of water-in-oil(W/O)*** reality,the emulsion produced also contains some fine solid mineral particles such as silica,which,depending on its quantity,may alter the viscosity and/or rheological properties of the fluid.A series of binary-component emulsions were separately prepared by dispersing silica nanoparticles[phase fraction,βs,=0.5%–5.75%(wt/v)]in heavy oil(S/O suspension)and by dispersing water[water cut,θw=10%–53%(v/v)]in heavy oil(W/O emulsion).Ternary-component emulsions comprising heavy oil,water droplets and suspended silica nanoparticles(S/W/O)were also prepared with similar ranges ofθw andβ*** viscosity was measured at different shear rates(5.1–1021.4 s-1)and temperatures(30–70°C).Both binary-component and ternary-component emulsion systems were observed to exhibit nonNewtonian shear thinning *** viscosity of the heavy oil and W/O emulsions increased in the presence of silica *** effect was,however,less signifi cant belowβs=2%(wt/v).Moreover,a generalized correlation has been proposed to predict the viscosity of both binary-component and ternary-component emulsions.

关键词： Heavy oil emulsions Heavy oil–silica nanoparticle suspension Viscosity functions Rheological model Complex fluid

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Detecting Man-in-the-Middle Attack in Fog Computing for Social Media

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Computers, Materials & Continua 2021年第10期69卷 1159-1181页

作者： Farouq aliyu Tarek Sheltami Ashraf mahmoud Louai al-Awami Ansar Yasar King Fahd University of Petroleum and Minerals Dhahran31261Saudi Arabia Transportation Research Institute(IMOB) Hasselt UniversityHasselt3500Belgium

Fog computing(FC)is a networking paradigm where wireless devices known as fog nodes are placed at the edge of the network(close to the Internet of Things(IoT)devices).Fog nodes provide services in lieu of the ***,improving the performance of the network and making it attractive to social media-based *** issues are one of the most challenges encountered in *** this paper,we propose an anomalybased Intrusion Detection and Prevention System(IDPS)against Man-in-theMiddle(MITM)attack in the fog *** system uses special nodes known as Intrusion Detection System(IDS)nodes to detect intrusion in the *** periodically monitor the behavior of the fog nodes in the *** deviation from normal network activity is categorized as malicious,and the suspected node is *** Moving Average(EWMA)is added to the system to smooth out the noise that is typically found in social media *** results(with 95%confidence)show that the accuracy of the proposed system increases from 80%to 95%after EWMA is ***,with EWMA,the proposed system can detect the intrusion from 0.25–0.5 s seconds faster than that without ***,it affects the latency of services provided by the fog nodes by at least 0.75–1.3 ***,EWMA has not increased the energy overhead of the system,due to its lightweight.

关键词： Fog computing man-in-the-middle attack intrusion detection system and prevention system network security social media

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Prediction of COVID-19 Confirmed Cases Using Gradient Boosting Regression Method

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Computers, Materials & Continua 2021年第1期66卷 315-329页

作者： Abdu Gumaei Mabrook al-Rakhami Mohamad mahmoud al Rahhal Fahad Raddah H.albogamy Eslam al Maghayreh Hussain alSalman College of Computer and Information Sciences King Saud UniversityRiyadh11362Saudi Arabia Computer Science Department Faculty of Applied ScienceTaiz UniversityTaizYemen College of Applied Computer Sciences King Saud UniversityRiyadh11362Saudi Arabia

The fast spread of coronavirus disease(COVID-19)caused by SARSCoV-2 has become a pandemic and a serious threat to the *** of May 30,2020,this disease had infected more than 6 million people globally,with hundreds of thousands of ***,there is an urgent need to predict confirmed cases so as to analyze the impact of COVID-19 and practice readiness in healthcare *** study uses gradient boosting regression(GBR)to build a trained model to predict the daily total confirmed cases of *** GBR method can minimize the loss function of the training process and create a single strong learner from weak *** are conducted on a dataset of daily confirmed COVID-19 cases from January 22,2020,to May 30,*** results are evaluated on a set of evaluation performance measures using 10-fold cross-validation to demonstrate the effectiveness of the GBR *** results reveal that the GBR model achieves 0.00686 root mean square error,the lowest among several comparative models.

关键词： COVID-19 coronavirus disease SARS-CoV-2 machine learning gradient boosting regression(GBR)method

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