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High-throughput computational screening and in vitro evaluation identifies 5-(4-oxo-4H-3,1-benzoxazin-2-yl)-2-[3-(4-oxo-4H-3,1-benzoxazin-2-yl)phenyl]-1H-isoindole-1,3(2H)-dione(C3),as a novel EGFR—HER2 dual inhibitor in gastric tumors

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Oncology Research 2024年第2期32卷 251-259页

作者： MESFER AL SHAHRANI REEM GAHTANI mohammad ABOHASSAN mohammad alshahrani YASSER ALRAEY AYED DERA mohammad RAJEH ASIRI PRASANNA RAJAGOPALAN Department of Clinical Laboratory Sciences College of Applied Medical SciencesKing Khalid UniversityAbhaSaudi Arabia

Gastric cancers are caused primarily due to the activation and amplification of the EGFR or HER2 kinases resulting in cell proliferation,adhesion,angiogenesis,and *** therapies are ineffective due to the intra-tumoral heterogeneity and concomitant genetic ***,dual inhibition strategies are recommended to increase potency and reduce *** this study,we have conducted computational high-throughput screening of the ChemBridge library followed by in vitro assays and identified novel selective inhibitors that have a dual impediment of EGFR/HER2 kinase ***-based High-throughput Virtual Screening(D-HTVS)was used to screen the whole ChemBridge small molecular library against EGFR and *** atomistic molecular dynamic simulation was conducted to understand the dynamics and stability of the protein-ligand ***/HER2 kinase enzymes,KATOIII,and Snu-5 cells were used for in vitro *** atomistic Molecular Dynamics simulations followed by solvent-based Gibbs binding free energy calculation of top molecules,identified compound C3(5-(4-oxo-4H-3,1-benzoxazin-2-yl)-2-[3-(4-oxo-4H-3,1-benzoxazin-2-yl)phenyl]-1H-isoindole-1,3(2H)-dione)to have a good affinity for both EGFR and *** predicted compound,C3,was promising with better binding energy,good binding pose,and optimum interactions with the EGFR and HER2 residues.C3 inhibited EGFR and HER2 kinases with IC50 values of 37.24 and 45.83 nM,*** GI50 values of C3 to inhibit KATOIII and Snu-5 cells were 84.76 and 48.26 nM,*** on these findings,we conclude that the identified compound C3 showed a conceivable dual inhibitory activity on EGFR/HER2 kinase,and therefore can be considered as a plausible lead-like molecule for treating gastric cancers with minimal side effects,though testing in higher models with pharmacokinetic approach is required.

关键词： Dual inhibitor Drug discovery EGFR/HER2 kinase Gastric cancer High-throughput screening

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Social Media-Based Surveillance Systems for Health Informatics Using Machine and Deep Learning Techniques:A Comprehensive Review and Open Challenges

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1167-1202页

作者： Samina Amin Muhammad Ali Zeb Hani alshahrani Mohammed Hamdi mohammad Alsulami Asadullah Shaikh Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan Department of Computer Science College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Information System College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia

Social media(SM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic *** review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their ***,every year,a large amount of data related to epidemic outbreaks,particularly Twitter data is generated by *** paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM,along with the ML and DL techniques that have been configured for the detection of epidemic *** has emerged as a promising ML technique that adaptsmultiple layers of representations or features of the data and yields state-of-the-art extrapolation *** recent years,along with the success of ML and DL in many other application domains,both ML and DL are also popularly used in SM *** paper aims to provide an overview of epidemic outbreaks in SM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in SM ***,this review serves the purpose of offering suggestions,ideas,and proposals,along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed.

关键词： Social media epidemic machine learning deep learning health informatics pandemic

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Anticancer efficacy of 3-(4-isopropyl)benzylidene-8-ethoxy,6-methyl,chroman-4-one(SBL-060),a novel,dual,estrogen receptor-Akt kinase inhibitor in acute myeloid leukemia cells

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Oncology Research 2021年第3期29卷 149-157页

作者： MESFER AL SHAHRANI PRASANNA RAJAGOPALAN mohammad ABOHASSAN mohammad alshahrani YASSER ALRAEY REEM MGAHTANI SURESH RADHAKRISHNAN KHLOOD DAGREERY Department of Clinical Laboratory Sciences College of Applied Medical SciencesKing Khalid UniversityAbhaSaudi Arabia Central Research Laboratory College of Applied Medical SciencesKing Khalid UniversityAbhaSaudi Arabia PG and Research Department of Chemistry Presidency CollegeChennaiTamil NaduIndia Regional Laboratory and Central Blood Bank JazanSaudi Arabia

Estrogen receptor(ER)αis expressed in a subset of patient-derived acute myeloid leukemia(AML)cells,whereas Akt is predominantly expressed in most types of *** AML with dual inhibitors is a novel approach to combat the ***,we examined a novel small molecule,3-(4-isopropyl)benzylidene-8-ethoxy,6-methyl,chroman-4-one(SBL-060),capable of targeting AML cells by inhibiting ERαand Akt *** chemical properties of SBL-060 were identified by proton nuclear magnetic resonance(^(1)H-NMR),^(13)C-NMR,and mass *** silico docking was performed using an automated protocol with ***-1 and HL-60 cell lines were differentiated using phorbol 12-myristate ***αinhibition was assessed using *** MTT assay assessed cell *** cytometry was performed for cell cycle,apoptosis,and p-Akt *** analysis identified the compound as 3-(4-isopropyl)benzylidene-8-ethoxy,6-methyl,chroman-4-one,which showed high binding efficacy toward ER,with aΔG_(binding) score of−7.4 kcal/***-060 inhibited ERα,exhibiting IC50 values of 448 and 374.3 nM in THP-1 and HL-60 cells,*** inhibited cell proliferation,GI50 values of SBL-060 were 244.1 and 189.9 nM for THP-1 and HL-60 cells,*** addition,a dose-dependent increase in sub G_(0)/G_(1) phase cell cycle arrest and total apoptosis was observed after treatment with SBL-060 in both cell ***-060 also dose-dependently increased the p-Akt-positive populations in both THP-1 and HL-60 *** results indicate that SBL-060 has excellent efficacy against differentiated AML cell types by inhibiting ER and Akt kinase,warranting further preclinical evaluations.

关键词： Akt kinase AML THP-1 HL-60 Estrogen receptor Benzylidene compounds

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A Deep Learning Model to Analyse Social-Cyber Psychological Problems in Youth

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Computer Systems Science & Engineering 2023年第7期46卷 551-562页

作者： Ali Alqazzaz mohammad Tabrez Quasim Mohammed Mujib alshahrani Ibrahim Alrashdi mohammad Ayoub Khan College of Computing and Information Technology University of Bisha67714BishaSaudi Arabia Department of Computer Science College of Computer and Information SciencesJouf UniversitySakakaAljouf72388Saudi Arabia

Facebook,Twitter,Instagram,and other social media have emerged as excellent platforms for interacting with friends and expressing thoughts,posts,comments,images,and videos that express moods,sentiments,and *** this,it has become possible to examine user thoughts and feelings in social network data to better understand their perspectives and ***,the analysis of depression based on social media has gained widespread acceptance worldwide,other verticals still have yet to be *** depression analysis uses Twitter data from a publicly available web source in this *** assess the accuracy of depression detection,long-short-term memory(LSTM)and convolution neural network(CNN)techniques were *** method is both efficient and *** simulation results have shown an accuracy of 86.23%,which is reasonable compared to existing methods.

关键词： Emotions depression social media

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Improved Fruitfly Optimization with Stacked Residual Deep Learning Based Email Classification

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Intelligent Automation & Soft Computing 2023年第6期36卷 3139-3155页

作者： Hala J.alshahrani Khaled Tarmissi Ayman Yafoz Abdullah Mohamed Abdelwahed Motwakel Ishfaq Yaseen Amgad Atta Abdelmageed mohammad Mahzari Department of Applied Linguistics College of LanguagesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversityMakkah24211Saudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah22230Saudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharj16242Saudi Arabia Department of English College of Science&HumanitiesPrince Sattam bin Abdulaziz UniversityAlKharj16242Saudi Arabia

Applied linguistics means a wide range of actions which include addressing a few language-based problems or solving some language-based *** stay in the leading positions for business as well as personal *** popularity grabs the interest of individuals with malevolent inten-tions—phishing and spam email *** filtering mechanisms were developed incessantly to follow unwanted,malicious content advancement to protect the *** prevailing solutions were focused on phishing email filtering and spam and whereas email labelling and analysis were not fully ***,this study provides a solution related to email message body text automatic classification into phishing and email *** paper presents an Improved Fruitfly Optimization with Stacked Residual Recurrent Neural Network(IFFO-SRRNN)based on Applied Linguistics for Email *** presented IFFO-SRRNN technique examines the intrinsic features of email for the identification of spam *** the preliminary level,the IFFO-SRRNN model follows the email pre-processing stage to make it compatible with further ***,the SRRNN method can be useful in recognizing and classifying spam *** hyperparameters of the SRRNN model need to be effectually tuned,the IFFO algorithm can be utilized as a hyperparameter *** investigate the effectual email classification results of the IFFO-SRDL technique,a series of simulations were taken placed on public datasets,and the comparison outcomes highlight the enhancements of the IFFO-SRDL method over other recent approaches with an accuracy of 98.86%.

关键词： Email classification applied linguistics improved fruitfly optimization deep learning recurrent neural network

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Applied Linguistics with Mixed Leader Optimizer Based English Text Summarization Model

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Intelligent Automation & Soft Computing 2023年第6期36卷 3203-3219页

作者： Hala J.alshahrani Khaled Tarmissi Ayman Yafoz Abdullah Mohamed Manar Ahmed Hamza Ishfaq Yaseen Abu Sarwar Zamani mohammad Mahzari Department of Applied Linguistics College of LanguagesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of English College of Science&HumanitiesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The term‘executed linguistics’corresponds to an interdisciplinary domain in which the solutions are identified and provided for real-time language-related *** exponential generation of text data on the Internet must be leveraged to gain knowledgeable *** extraction of meaningful insights from text data is crucial since it can provide value-added solutions for business organizations and *** Automatic Text Summarization(ATS)process reduces the primary size of the text without losing any basic components of the *** current study introduces an Applied Linguistics-based English Text Summarization using a Mixed Leader-Based Optimizer with Deep Learning(ALTS-MLODL)*** presented ALTS-MLODL technique aims to summarize the text documents in the English *** accomplish this objective,the proposed ALTS-MLODL technique pre-processes the input documents and primarily extracts a set of ***,the MLO algorithm is used for the effectual selection of the extracted *** the text summarization process,the Cascaded Recurrent Neural Network(CRNN)model is exploited whereas the Whale Optimization Algorithm(WOA)is used as a hyperparameter *** exploitation of the MLO-based feature selection and the WOA-based hyper-parameter tuning enhanced the summarization *** validate the perfor-mance of the ALTS-MLODL technique,numerous simulation analyses were *** experimental results signify the superiority of the proposed ALTS-MLODL technique over other approaches.

关键词： Text summarization deep learning hyperparameter tuning applied linguistics multi-leader optimizer

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Sine Cosine Optimization with Deep Learning-Based Applied Linguistics for Sentiment Analysis on COVID-19 Tweets

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Computers, Materials & Continua 2023年第6期75卷 4767-4783页

作者： Abdelwahed Motwakel Hala J.alshahrani Abdulkhaleq Q.A.Hassan Khaled Tarmissi Amal S.Mehanna Ishfaq Yaseen Amgad Atta Abdelmageed mohammad Mahzari Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Applied Linguistics College of LanguagesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of English College of Science and Arts at MahayilKing Khalid UniversityMuhayil63763Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversityMakkah24211Saudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11845Egypt Department of English College of Science&HumanitiesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Applied linguistics is an interdisciplinary domain which identifies,investigates,and offers solutions to language-related real-life *** new coronavirus disease,otherwise known as Coronavirus disease(COVID-19),has severely affected the everyday life of people all over the ***,since there is insufficient access to vaccines and no straight or reliable treatment for coronavirus infection,the country has initiated the appropriate preventive measures(like lockdown,physical separation,and masking)for combating this extremely transmittable ***,individuals spent more time on online social media platforms(i.e.,Twitter,Facebook,Instagram,LinkedIn,and Reddit)and expressed their thoughts and feelings about coronavirus *** has become one of the popular social media platforms and allows anyone to post *** study proposes a sine cosine optimization with bidirectional gated recurrent unit-based senti-ment analysis(SCOBGRU-SA)on COVID-19 *** SCOBGRU-SA technique aimed to detect and classify the various sentiments in Twitter data during the COVID-19 *** SCOBGRU-SA technique follows data pre-processing and the Fast-Text word embedding process to accomplish ***,the BGRU model is utilized to recognise and classify sen-timents present in the ***,the SCO algorithm is exploited for tuning the BGRU method’s hyperparameter,which helps attain improved classification *** experimental validation of the SCOBGRU-SA technique takes place using a benchmark dataset,and the results signify its promising performance compared to other DL models.

关键词： Applied linguistics deep learning sentiment analysis COVID-19 pandemic sine cosine optimization twitter

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Quantitative risk of positive family history in developing colorectal cancer: A meta-analysis

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World Journal of Gastroenterology 2019年第30期25卷 4278-4291页

作者： Parsa Mehraban Far Abdulaziz alshahrani mohammad Yaghoobi Division of Medicine Queen’s UniversityKingstonON K7L 3N6Canada Division of Gastroenterology McMaster UniversityHamiltonON L8S 4K1Canada The Farncombe Family Digestive Health Research Institute McMaster UniversityHamiltonON L8S 4K1Canada

BACKGROUND Positive family history is a risk factor for development of colorectal *** numerous studies on the topic,the absolute risk in patients with a positive family history remains unclear and therefore studies are lacking to validate non-invasive screening methods in individuals with positive family *** To quantify the risk of colorectal cancer in individuals with a positive family *** A comprehensive electronic literature search was performed using PubMed from January 1955 until November 2017,EMBASE from 1947 until 2018,and Cochrane Library without date *** independent reviewers conducted study selection,data extraction and quality assessment.A meta-analysis of Mantel-Haenzel relative risks was performed using the random effects ***-Ottawa scale was used to score the quality of selected *** plot and Egger’s regression test was performed to detect publication *** analysis was performed comparing Asian and non-Asian *** analyses were performed to rule out the effect of the timing of the study,overall quality,the main outcome and the effect of each individual study in overall *** Forty-six out of 3390 studies,including 906981 patients were included in the final analysis.41 of the included studies were case-control and 5 were cohort.A positive family history of colorectal cancer in first-degree relatives was associated with significantly increased risk of colorectal cancer with a relative risk of 1.87(95%CI:1.68-2.09;P<0.00001).Cochrane Q test was significant(P<0.00001,I2=90%).Egger’s regression test showed asymmetry in the funnel plot and therefore the Trim and Fill method was used which confirmed the validity of the *** was no difference between Asian versus non-Asian *** remained robust in sensitivity *** Individuals with a positive family history of colorectal cancer are 1.87 times more likely to develop colorectal cancer

关键词： Colorectal cancer Risk Family history

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Improved Attentive Recurrent Network for Applied Linguistics-Based Offensive Speech Detection

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Computer Systems Science & Engineering 2023年第11期47卷 1691-1707页

作者： Manar Ahmed Hamza Hala J.alshahrani Khaled Tarmissi Ayman Yafoz Amira Sayed A.Aziz mohammad Mahzari Abu Sarwar Zamani Ishfaq Yaseen Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Applied Linguistics College of LanguagesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversityMakkahSaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of English College of Science&HumanitiesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Applied linguistics is one of the fields in the linguistics domain and deals with the practical applications of the language studies such as speech processing,language teaching,translation and speech *** ever-growing Online Social Networks(OSNs)experience a vital issue to confront,i.e.,hate *** the OSN-oriented security problems,the usage of offensive language is the most important threat that is prevalently found across the *** on the group targeted,the offensive language varies in terms of adult content,hate speech,racism,cyberbullying,abuse,trolling and *** these,hate speech is the most intimidating form of using offensive language in which the targeted groups or individuals are intimidated with the intent of creating harm,social chaos or *** Learning(ML)techniques have recently been applied to recognize hate speech-related *** current research article introduces a Grasshopper Optimization with an Attentive Recurrent Network for Offensive Speech Detection(GOARN-OSD)model for social *** GOARNOSD technique integrates the concepts of DL and metaheuristic algorithms for detecting hate *** the presented GOARN-OSD technique,the primary stage involves the data pre-processing and word embedding ***,this study utilizes the Attentive Recurrent Network(ARN)model for hate speech recognition and *** last,the Grasshopper Optimization Algorithm(GOA)is exploited as a hyperparameter optimizer to boost the performance of the hate speech recognition *** depict the promising performance of the proposed GOARN-OSD method,a widespread experimental analysis was *** comparison study outcomes demonstrate the superior performance of the proposed GOARN-OSD model over other state-of-the-art approaches.

关键词： Applied linguistics hate speech offensive language natural language processing deep learning grasshopper optimization algorithm

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Prevalence of Infectious Complications in Children with Cancer

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Journal of Cancer Therapy 2019年第12期10卷 938-947页

作者： Zaheer Ullah Khan Nagi Amin Gaafar Ahmed Mustafa mohammad Sanad Tarmoom mohammad Yousef AlGhar Anwaar Saud Aldahir Dayel alshahrani Department of Paediatric Haematology and Oncology King Fahad Medical City Riyadh Kingdom of Saudi Arabia Department of Infectious Diseases King Fahad Medical City Riyadh Kingdom of Saudi Arabia Department of General Paediatric King Fahad Medical City Riyadh Kingdom of Saudi Arabia

Background:?Infections are the most common complications during chemotherapy. The trends have been changing over time due to use of multi-agent intensive chemotherapy.?Procedure:?We looked?over?our data to see what complications we get in our patients. The data was collected on patients treated in King Fahad Medical City from July 2009 to Dec 2015.?Results:?We?found that 86 patients had one episode only while 92 had 2 or more episodes reaching up to 11 episodes in 1 patient. We found positive cultures in 17.3% of episodes with staphylococcus as common gram positive and Klebsiella pneumoniae as common gram negative bacteria, respiratory viral infections in 13.8% and GI infections in 9%. We found Candida albicans as the most common fungus while other yeasts followed. Acute lymphoblastic leukaemia was the most common diagnosis. The episodes were associated with neutropenia of 7 days in 1st?episode and 56.8% in cases with repeated episodes. We had 2 deaths one from recurrent infections with CNS (Central Nervous System) damage and one from Pulmonary infections causing pulmonary haemorrhage. We had one with persistent neurological sequele from prolonged fungal infection.?Conclusions:Neutropenia of 7 days came out to be significant risk factors for infection across all diseases. We have an acceptable level of morbidity and mortality due to good supportive services.?We need prospective studies to get an up-to-date picture of our practice.?We need prophylactic antibiotics and antifungals for high-risk patients like AML.

关键词： Infections Cancer Children

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