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A comparative in vitro study on the effect of SGLT2 inhibitors on chemosensitivity to doxorubicin in MCF-7 breast cancer cells

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Oncology Research 2024年第5期32卷 817-830页

作者： SHAHID KARIM ALANOUD NAHER ALGHANMI MAHA JAMAL HUDA ALKREATHY ALAM JAMAL HIND A.ALKHATABI MOHAMMED BAZUHAIR AFTAB AHMAD Department of Clinical Pharmacology Faculty of MedicineKing Abdulaziz UniversityJeddahSaudi Arabia Department of Biochemistry Faculty of ScienceKing Abdulaziz UniversityJeddahSaudi Arabia Department of Biochemistry College of ScienceUniversity of JeddahJeddah21959Saudi Arabia Health Information Technology Department The Applied CollegeKing Abdulaziz UniversityJeddahSaudi Arabia Pharmacovigilance and Medication Safety Unit Center of Research Excellence for Drug Research and Pharmaceutical IndustriesKing Abdulaziz UniversityJeddahSaudi Arabia

Cancer frequently develops resistance to the majority of chemotherapy *** study aimed to examine the synergistic cytotoxic and antitumor effects of SGLT2 inhibitors,specifically Canagliflozin(CAN),Dapagliflozin(DAP),Empagliflozin(EMP),and Doxorubicin(DOX),using in vitro *** precise combination of CAN+DOX has been found to greatly enhance the cytotoxic effects of doxorubicin(DOX)in MCF-7 ***,it was shown that cancer cells exhibit an increased demand for glucose and ATP in order to support their ***,when these medications were combined with DOX,there was a considerable inhibition of glucose consumption,as well as reductions in intracellular ATP and lactate ***,this effect was found to be dependent on the dosages of the *** addition to effectively inhibiting the cell cycle,the combination of CAN+DOX induces substantial modifications in both cell cycle and apoptotic gene *** work represents the initial report on the beneficial impact of SGLT2 inhibitor medications,namely CAN,DAP,and EMP,on the responsiveness to the anticancer properties of *** underlying molecular mechanisms potentially involve the suppression of the function of SGLT2.

关键词： SGLT2 Cancer Cytotoxicity ATP Cell cycle

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Static Analysis Techniques for Fixing Software Defects in MPI-Based Parallel Programs

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Computers, Materials & Continua 2024年第5期79卷 3139-3173页

作者： Norah Abdullah Al-Johany Sanaa Abdullah Sharaf Fathy Elbouraey Eassa Reem Abdulaziz Alnanih Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Software Engineering and Distributed System Research Group King Abdulaziz UniversityJeddah21589Saudi Arabia

The Message Passing Interface (MPI) is a widely accepted standard for parallel computing on distributed ***, MPI implementations can contain defects that impact the reliability and performance of parallelapplications. Detecting and correcting these defects is crucial, yet there is a lack of published models specificallydesigned for correctingMPI defects. To address this, we propose a model for detecting and correcting MPI defects(DC_MPI), which aims to detect and correct defects in various types of MPI communication, including blockingpoint-to-point (BPTP), nonblocking point-to-point (NBPTP), and collective communication (CC). The defectsaddressed by the DC_MPI model include illegal MPI calls, deadlocks (DL), race conditions (RC), and messagemismatches (MM). To assess the effectiveness of the DC_MPI model, we performed experiments on a datasetconsisting of 40 MPI codes. The results indicate that the model achieved a detection rate of 37 out of 40 codes,resulting in an overall detection accuracy of 92.5%. Additionally, the execution duration of the DC_MPI modelranged from 0.81 to 1.36 s. These findings show that the DC_MPI model is useful in detecting and correctingdefects in MPI implementations, thereby enhancing the reliability and performance of parallel applications. TheDC_MPImodel fills an important research gap and provides a valuable tool for improving the quality ofMPI-basedparallel computing systems.

关键词： High-performance computing parallel computing software engineering software defect message passing interface deadlock

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Agmatine ameliorates diabetes type 2-induced nephropathy in rats

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Asian Pacific Journal of Tropical Biomedicine 2024年第1期14卷 8-16页

作者： Fatemah O.Kamel Ohoud Shagroud Mai AAlim A.Sattar Ahmad Gamal S Abd El-Aziz Abdulhadi S.Burzangi Duaa Bakhshwin Maha Jamal Shahid Karim Department of Clinical Pharmacology Faculty of MedicineKing Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Anatomy Faculty of MedicineKing Abdulaziz UniversityJeddah 21589Saudi Arabia

Objective:To assess the nephroprotective potential of agmatine in a rat model of streptozotocin-induced diabetic ***:A single dose of streptozotocin(40 mg/kg)coupled with a fructose diet induced diabetes in Wistar ***(40 and 80 mg/kg)was administered to rats for 12 *** body weight and fasting blood glucose were measured *** level,urine output,total protein,albumin,blood urea nitrogen,creatinine,and cystatin-C were also determined at the end of the ***,superoxide dismutase,glutathione,interleukin-1β,interleukin-6,and tumor necrosis factor-alpha were evaluated in kidney *** study was also performed using hematoxylin and eosin ***:Agmatine at both doses significantly increased final body weight,and lowered fasting blood glucose,urine output,insulin,total protein,albumin,blood urea nitrogen,creatinine,and cystatin-C levels compared with the diabetic group(P<0.05).Inflammatory markers and antioxidant effect were significantly improved in agmatine-treated ***,the histopathological changes in renal structure were ameliorated by agmatine ***:Agmatine alleviates diabetic nephropathy by improving renal functions and reducing inflammation and oxidative *** molecular mechanisms of its nephroprotective actions need to be investigated in future study.

关键词： Agmatine Type 2 diabetes Nephropathy Oxidative stress Nephroprotection

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Neuroprotective effect of liraglutide and memantine in a rat model of Alzheimer’s disease

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Asian Pacific Journal of Tropical Biomedicine 2024年第5期14卷 207-214页

作者： Duaa M.Bakhshwin Foziya W.Alhalabi Mohamad Omar Barasheed Ahmed M.Bakhshwin Maha H.Jamal Mohammed A.Bazuhair Fatemah O.Kamel Rania M.Magadmi Zoheir A Damanhouri Samar M.Alsaggaf Department of Clinical Pharmacology Faculty of MedicineKing Abdulaziz UniversityJeddahSaudi Arabia Hera General Hospital MakkahSaudi Arabia Department of Pathology Faculty of MedicineKing Abdulaziz UniversityJeddahSaudi Arabia Department of Clinical Anatomy Faculty of MedicineKing Abdulaziz UniversityJeddahSaudi Arabia

Objective:To assess the effect of memantine combined with liraglutide on aluminum chloride(AlCl_(3))and D-galactose(D-GAL)-induced neurotoxicity in ***:Male Wistar rats were divided into 5 groups of 5 animals each:the positive control,the negative control,the memantine-treated group,the liraglutide-treated group,and the combination group treated with memantine and ***_(3)and D-GAL were used to induce *** tests,brain beta-amyloid protein,and oxidative stress biomarkers were ***:The Morris water maze test indicated an enhanced memory in the combination ***,the combination treatment of liraglutide and memantine resulted in a remarkable reduction in the beta-amyloid protein level in the brain *** inflammation and oxidative stress biomarkers were significantly reduced,and the levels of antioxidant parameters were ***:The combination of liraglutide and memantine exerts neuroprotective effects and enhances memory and cognitive functions in rats with Alzheimer’s disease.

关键词： Alzheimer’s disease Cognitive function Glucagonlike peptide-1 Liraglutide Memantine

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THAPE: A Tunable Hybrid Associative Predictive Engine Approach for Enhancing Rule Interpretability in Association Rule Learning for the Retail Sector

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Computers, Materials & Continua 2024年第6期79卷 4995-5015页

作者： Monerah Alawadh Ahmed Barnawi Information Technology Department King Abdulaziz UniversityJeddah21589Saudi Arabia

Association rule learning(ARL)is a widely used technique for discovering relationships within ***,it often generates excessive irrelevant or ambiguous ***,post-processing is crucial not only for removing irrelevant or redundant rules but also for uncovering hidden associations that impact other ***,several post-processing methods have been proposed,each with its own strengths and *** this paper,we propose THAPE(Tunable Hybrid Associative Predictive Engine),which combines descriptive and predictive *** leveraging both techniques,our aim is to enhance the quality of analyzing generated *** includes removing irrelevant or redundant rules,uncovering interesting and useful rules,exploring hidden association rules that may affect other factors,and providing backtracking ability for a given *** proposed approach offers a tailored method that suits specific goals for retailers,enabling them to gain a better understanding of customer behavior based on factual transactions in the target *** applied THAPE to a real dataset as a case study in this paper to demonstrate its *** this application,we successfully mined a concise set of highly interesting and useful association *** of the 11,265 rules generated,we identified 125 rules that are particularly relevant to the business *** identified rules significantly improve the interpretability and usefulness of association rules for decision-making purposes.

关键词： Association rule learning post-processing predictive machine learning rule interpretability

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The interplay mechanism between IDH mutation, MGMT-promoter methylation, and PRMT5 activity in the progression of grade 4 astrocytoma: unraveling the complex triad theory

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Oncology Research 2024年第6期32卷 1037-1045页

作者： MAHER KURDI ALAA ALKHOTANI ABDULRAHMAN SABBAGH EYAD FAIZO AHMED I.LARY AHMED K.BAMAGA MAJID ALMANSOURI BADR HAFIZ THAMER ALSHARIF SALEH BAEESA Department of Pathology Faculty of MedicineKing Abdulaziz UniversityRabighSaudi Arabia Department of Pathology College of MedicineUmm Al-Qura UniversityMakkahSaudi Arabia Department of Surgery Faculty of MedicineKing Abdulaziz UniversityJeddahSaudi Arabia Department of Surgery Faculty of MedicineUniversity of TabukTabukSaudi Arabia Section of Neurosurgery Department of SurgeryKing Abdulaziz Medical CityJeddahSaudi Arabia Department of Pediatrics Faculty of MedicineKing Abdulaziz UniversityJeddahSaudi Arabia Department of Clinical Biochemistry Faculty of MedicineKing Abdulaziz UniversityJeddahSaudi Arabia Department of Neurosciences King Faisal Specialist Hospital and Research CenterJeddahSaudi Arabia Department of Surgery King Abdulaziz Specialist HospitalTaifSaudi Arabia

Background:The dysregulation of Isocitrate dehydrogenase(IDH)and the subsequent production of 2-Hydroxyglutrate(2HG)may alter the expression of epigenetic proteins in Grade 4 *** interplay mechanism between IDH,O-6-methylguanine-DNA methyltransferase(MGMT)-promoter methylation,and protein methyltransferase proteins-5(PRMT5)activity,with tumor progression has never been ***:A retrospective cohort of 34 patients with G4 astrocytoma is classified into IDH-mutant and IDH-wildtype *** groups were tested for MGMT-promoter methylation and PRMT5 through methylation-specific and gene expression PCR ***-cohort statistical significance was ***:Both IDH-mutant WHO grade 4 astrocytomas(n=22,64.7%)and IDH-wildtype glioblastomas(n=12,35.3%)had upregulated PRMT5 gene expression except in one *** of the 22 IDH-mutant tumors,10(45.5%)tumors showed MGMT-promoter methylation and 12(54.5%)tumors had unmethylated *** IDH-wildtype tumors had unmethylated *** was a statistically significant relationship between MGMT-promoter methylation and IDH in G4 astrocytoma(p-value=0.006).Statistically significant differences in progression-free survival(PFS)were also observed among all G4 astrocytomas that expressed PRMT5 and received either temozolomide(TMZ)or TMZ plus other chemotherapies,regardless of their IDH or MGMT-methylation status(p-value=0.0014).Specifically,IDH-mutant tumors that had upregulated PRMT5 activity and MGMT-promoter methylation,who received only TMZ,have exhibited longer ***:The relationship between PRMT5,MGMT-promoter,and IDH is not ***,accumulation of D2-hydroxyglutarate(2-HG),which partially activates 2-OG-dependent deoxygenase,may not affect their *** IDH-wildtype glioblastomas,the 2HG-2OG pathway is typically inactive,leading to PRMT5 *** alone,compared to TMZ-plus,can increase PFS in upregulated PRMT5 ***,using a PRMT5 inhibitor in G4

关键词： Grade 4 astrocytoma Glioblastoma Isocitrate dehydrogenase(IDH) O-6-methylguanine-DNA methyltransferase(MGMT) Protein methyltransferase proteins-5(PRMT5) Progression-free survival(PFS)

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Enhancing PDF Malware Detection through Logistic Model Trees

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Computers, Materials & Continua 2024年第3期78卷 3645-3663页

作者： Muhammad Binsawad Department of Information Systems King Abdulaziz UniversityP.O.Box 80217Jeddah21589Saudi Arabia

Malware is an ever-present and dynamic threat to networks and computer systems in cybersecurity,and because of its complexity and evasiveness,it is challenging to identify using traditional signature-based detection *** study article discusses the growing danger to cybersecurity that malware hidden in PDF files poses,highlighting the shortcomings of conventional detection techniques and the difficulties presented by adversarial *** article presents a new method that improves PDF virus detection by using document analysis and a Logistic Model *** a dataset from the Canadian Institute for Cybersecurity,a comparative analysis is carried out with well-known machine learning models,such as Credal Decision Tree,Naïve Bayes,Average One Dependency Estimator,Locally Weighted Learning,and Stochastic Gradient *** traditional structural and JavaScript-centric PDF analysis,the research makes a substantial contribution to the area by boosting precision and resilience in malware *** use of Logistic Model Tree,a thorough feature selection approach,and increased focus on PDF file attributes all contribute to the efficiency of PDF virus *** paper emphasizes Logistic Model Tree’s critical role in tackling increasing cybersecurity threats and proposes a viable answer to practical issues in the *** results reveal that the Logistic Model Tree is superior,with improved accuracy of 97.46%when compared to benchmark models,demonstrating its usefulness in addressing the ever-changing threat landscape.

关键词： Malware detection PDF files logistic model tree feature selection cybersecurity

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Enhancing Ulcerative Colitis Diagnosis:A Multi-Level Classification Approach with Deep Learning

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 1129-1142页

作者： Hasan J.Alyamani Department of Information Systems Faculty of Computing and Information Technology in RabighKing Abdulaziz UniversityJeddah21589Saudi Arabia

The evaluation of disease severity through endoscopy is pivotal in managing patients with ulcerative colitis,a condition with significant clinical ***,endoscopic assessment is susceptible to inherent variations,both within and between observers,compromising the reliability of individual *** study addresses this challenge by harnessing deep learning to develop a robust model capable of discerning discrete levels of endoscopic disease *** initiate this endeavor,a multi-faceted approach is embarked *** dataset is meticulously preprocessed,enhancing the quality and discriminative features of the images through contrast limited adaptive histogram equalization(CLAHE).A diverse array of data augmentation techniques,encompassing various geometric transformations,is leveraged to fortify the dataset’s diversity and facilitate effective feature extraction.A fundamental aspect of the approach involves the strategic incorporation of transfer learning principles,harnessing a modified ResNet-50 *** augmentation,informed by domain expertise,contributed significantly to enhancing the model’s classification *** outcome of this research endeavor yielded a highly promising model,demonstrating an accuracy rate of 86.85%,coupled with a recall rate of 82.11%and a precision rate of 89.23%.

关键词： Ulcerative colitis deep learning CLAHE transfer learning geometric transformations

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Gradient Optimizer Algorithm with Hybrid Deep Learning Based Failure Detection and Classification in the Industrial Environment

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1341-1364页

作者： Mohamed Zarouan Ibrahim M.Mehedi Shaikh Abdul Latif Md.Masud Rana Department of Electrical and Computer Engineering(ECE) King Abdulaziz UniversityJeddah21589Saudi Arabia Center of Excellence in Intelligent Engineering Systems(CEIES) King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Nuclear Engineering King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical and Electronic Engineering Rajshahi University of Engineering and TechnologyRajshahiBangladesh

Failure detection is an essential task in industrial systems for preventing costly downtime and ensuring the seamlessoperation of the system. Current industrial processes are getting smarter with the emergence of Industry ***, various modernized industrial processes have been equipped with quite a few sensors to collectprocess-based data to find faults arising or prevailing in processes along with monitoring the status of *** diagnosis of rotating machines serves a main role in the engineering field and industrial production. Dueto the disadvantages of existing fault, diagnosis approaches, which greatly depend on professional experienceand human knowledge, intellectual fault diagnosis based on deep learning (DL) has attracted the researcher’sinterest. DL reaches the desired fault classification and automatic feature learning. Therefore, this article designs a Gradient Optimizer Algorithm with Hybrid Deep Learning-based Failure Detection and Classification (GOAHDLFDC)in the industrial environment. The presented GOAHDL-FDC technique initially applies continuous wavelettransform (CWT) for preprocessing the actual vibrational signals of the rotating machinery. Next, the residualnetwork (ResNet18) model was exploited for the extraction of features from the vibration signals which are thenfed into theHDLmodel for automated fault detection. Finally, theGOA-based hyperparameter tuning is performedtoadjust the parameter valuesof theHDLmodel *** experimental result analysis of the GOAHDL-FD Calgorithm takes place using a series of simulations and the experimentation outcomes highlight the better resultsof the GOAHDL-FDC technique under different aspects.

关键词： Fault detection Industry 4.0 gradient optimizer algorithm deep learning rotating machineries artificial intelligence

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A Deep Learning Approach for Landmines Detection Based on Airborne Magnetometry Imaging and Edge Computing

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 2117-2137页

作者： Ahmed Barnawi Krishan Kumar Neeraj Kumar Bander Alzahrani Amal Almansour Faculty of Computing and Information Technology King Abdulaziz UniversityJeddahSaudi Arabia Department of Computer Science and Engineering Thapar Institute of Engineering and TechnologyDeemed to be UniversityPatialaIndia

Landmines continue to pose an ongoing threat in various regions around the world,with countless buried landmines affecting numerous human *** detonation of these landmines results in thousands of casualties reported worldwide ***,there is a pressing need to employ diverse landmine detection techniques for their *** effective approach for landmine detection is UAV(Unmanned Aerial Vehicle)based AirborneMagnetometry,which identifies magnetic anomalies in the local terrestrial magnetic *** can generate a contour plot or heat map that visually represents the magnetic field *** the effectiveness of this approach,landmine removal remains a challenging and resource-intensive task,fraughtwith *** computing,on the other hand,can play a crucial role in critical drone monitoring applications like landmine *** processing data locally on a nearby edge server,edge computing can reduce communication latency and bandwidth requirements,allowing real-time analysis of magnetic field *** enables faster decision-making and more efficient landmine detection,potentially saving lives and minimizing the risks involved in the ***,edge computing can provide enhanced security and privacy by keeping sensitive data close to the source,reducing the chances of data exposure during *** paper introduces the MAGnetometry Imaging based Classification System(MAGICS),a fully automated UAV-based system designed for landmine and buried object detection and *** have developed an efficient deep learning-based strategy for automatic image classification using magnetometry dataset *** simulating the proposal in various network scenarios,we have successfully detected landmine signatures present in themagnetometry *** trained models exhibit significant performance improvements,achieving a maximum mean average precision value of 97.8%.

关键词： CNN deep learning landmine detection magnetometer mean average precision UAV

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