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| 1 | Helicobacter pylori may be an initiating factor in newly diagnosed ulcerative colitis patients: A pilot study显示文摘AIM To directly visualize Helicobacter pylori(H. pylori) by the highly sensitive and specific technique of immunohistochemical staining in colonic tissue from patients newly diagnosed with ulcerative colitis(UC).METHODS Colonoscopic biopsies from thirty patients with newly diagnosed UC and thirty controls were stained with Giemsa stain and immunohistochemical stain for detection of H. pylori in the colonic tissue. Results were confirmed by testing H. pylori Ag in the stool then infected patients were randomized to receive either anti H. pylori treatment or placebo.RESULTS Twelve/30(40%) of the UC patients were positive for H. pylori by Giemsa, and 17/30(56.6%) by immunohistochemistry stain. Among the control group 4/30(13.3%) and 6/30(20 %) were positive for H. pylori by Giemsa and immunohistochemistry staining respectively. H. pylori was significantly higher in UC than in controls(P = 0.04 and 0.007). All Giemsa positive patients and controls were positive by immunohistochemical stain. Four cases of the control group positive for H. pylori also showed microscopic features consistent with early UC.CONCLUSION H. pylori can be detected in colonic mucosa of patients with UC and patients with histological superficial ulcerations and mild infiltration consistent with early UC. There seems to be an association between UC and presence of H. pylori in the colonic tissue. Whether this is a causal relationship or not remains to be discovered. | Loai Mansour Ferial El-Kalla Abdelrahman Kobtan Sherief Abd-Elsalam Mohamed Yousef Samah Soliman Lobna Abo Ali Walaa Elkhalawany Ibrahim Amer Heba Harras Maha M Hagras Mohamed Elhendawy | 2018 | World Journal of Clinical Cases2018，6，13： | 4 |
| 2 | Decoration of vertically aligned TiO2 nanotube arrays with WO3 particles for hydrogen fuel production显示文摘 | Heba ALI N. ISMAIL M. S. AMIN Mohamed MEKEWI | 2018 | Frontiers in Energy2018，12，2： | 2 |
| 3 | Hepatic Steatosis in Genotype 4 Chronic Hepatitis C Patients: Implication for Therapy显示文摘 | Mahmoud Aboelneen Khattab Mohammed Emad Abdel-fattah Mohammed Eslam Asharf Abdelaleem Rabab Atef Abdelaleem Mohammed Shatat Ahmed Ali Lamia Hamdy Heba Tawfek | 2010 | Journal of Clinical Gastroenterology2010，，10： | 1 |
| 4 | Brassinolide alleviates salt stress and increases antioxidant activityofcowpeaplants(Vigna sinensis)显示文摘 | Ali Abdel Aziz El-Mashad Heba Ibrahim Mohamed | 2012 | Protoplasma2012，249，： | 1 |
| 5 | Role of endoscopic ultrasound and cyst fluid tumor markers in diagnosis of pancreatic cystic lesions显示文摘BACKGROUND Pancreatic cystic lesions(PCLs) are common in clinical practice. The accurate classification and diagnosis of these lesions are crucial to avoid unnecessary treatment of benign lesions and missed opportunities for early treatment of potentially malignant lesions.AIM To evaluate the role of cyst fluid analysis of different tumor markers such as cancer antigens [e.g., cancer antigen(CA)19-9, CA72-4], carcinoembryonic antigen(CEA), serine protease inhibitor Kazal-type 1(SPINK1), interleukin 1 beta(IL1-β), vascular endothelial growth factor A(VEGF-A), and prostaglandin E2(PGE2)], amylase, and mucin stain in diagnosing pancreatic cysts and differentiating malignant from benign lesions.METHODS This study included 76 patients diagnosed with PCLs using different imaging modalities. All patients underwent endoscopic ultrasound(EUS) and EUS-fine needle aspiration(EUS-FNA) for characterization and sampling of different PCLs.RESULTS The mean age of studied patients was 47.4 ± 11.4 years, with a slight female predominance(59.2%). Mucin stain showed high statistical significance in predicting malignancy with a sensitivity of 87.1% and specificity of 95.56%. It also showed a positive predictive value and negative predictive value of 93.1% and 91.49%, respectively(P < 0.001). We found that positive mucin stain, cyst fluid glucose, SPINK1, amylase, and CEA levels had high statistical significance(P < 0.0001). In contrast, IL-1β, CA 72-4, VEGF-A, VEGFR2, and PGE2 did not show any statistical significance. Univariate regression analysis for prediction of malignancy in PCLs showed a statistically significant positive correlation with mural nodules, lymph nodes, cyst diameter, mucin stain, and cyst fluid CEA. Meanwhile, logistic multivariable regression analysis proved that mural nodules, mucin stain, and SPINK1 were independent predictors of malignancy in cystic pancreatic lesions.CONCLUSION EUS examination of cyst morphology with cytopathological analysis and cyst fluid analysis could improve the differentiation between malignant and benign pancreatic cysts. Also, CEA, glucose, and SPINK1 could be used as promising markers to predict malignant pancreatic cysts. | Hussein Hassan Okasha Abeer Abdellatef Shaimaa Elkholy Mohamad-Sherif Mogawer Ayman Yosry Magdy Elserafy Eman Medhat Hanaa Khalaf Magdy Fouad Tamer Elbaz Ahmed Ramadan Mervat E Behiry Kerolis Y William Ghada Habib Mona Kaddah Haitham Abdel-Hamid Amr Abou-Elmagd Ahmed Galal Wael A Abbas Ahmed Youssef Altonbary Mahmoud El-Ansary Aml E Abdou Hani Haggag Tarek Ali Abdellah Mohamed A Elfeki Heba Ahmed Faheem Hani M Khattab Mervat El-Ansary Safia Beshir Mohamed El-Nady | 2022 | World Journal of Gastrointestinal Endoscopy2022，14，6： | 1 |
| 6 | Malicious URL Classification Using Artificial Fish Swarm Optimization and Deep Learning显示文摘Cybersecurity-related solutions have become familiar since it ensures security and privacy against cyberattacks in this digital era.Malicious Uniform Resource Locators(URLs)can be embedded in email or Twitter and used to lure vulnerable internet users to implement malicious data in their systems.This may result in compromised security of the systems,scams,and other such cyberattacks.These attacks hijack huge quantities of the available data,incurring heavy financial loss.At 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 them.With this motivation,the current article develops an Artificial Fish Swarm Algorithm(AFSA)with Deep Learning Enabled Malicious URL Detection and Classification(AFSADL-MURLC)model.The presented AFSADL-MURLC model intends to differentiate the malicious URLs from genuine URLs.To attain this,AFSADL-MURLC model initially carries out data preprocessing and makes use of glove-based word embedding technique.In addition,the created vector model is then passed onto Gated Recurrent Unit(GRU)classification to recognize the malicious URLs.Finally,AFSA is applied to the proposed model to enhance the efficiency of GRU model.The proposed AFSADL-MURLC technique was experimentally validated using benchmark dataset sourced from Kaggle repository.The simulation results confirmed the supremacy of the proposed AFSADL-MURLC model over recent approaches under distinct measures. | Anwer Mustafa Hilal Aisha Hassan Abdalla Hashim Heba G.Mohamed Mohamed K.Nour Mashael M.Asiri Ali M.Al-Sharafi Mahmoud Othman Abdelwahed Motwakel | 2023 | Computers, Materials & Continua2023，，1： | 0 |
| 7 | Exendin-4 inhibits the survival and invasiveness of two colorectal cancer cell lines via suppressing GS3Kβ/β-catenin/NF-κB axis through activating SIRT1显示文摘This study examined if the anti-tumorigenesis effect of Exendin-4 in HT29 and HCT116 colorectal cancer(CRC)involves modulation of SIRT1 and Akt/GSR3K/β-catenin/NF-κB axis.HT29 and HCT116 cells were treated either with increasing levels of Exendin-4(0.0-200μM)or with Exendin-4(at its IC50)in the presence or absence of EX-527(10μM/a selective SIRT1 inhibitor)or Exendin-4(9-39)amide(E(9-39)A)(1μM/an Exendin-4 antagonist).In a dose-dependent manner,Exendin-4 inhibited cell survival,but enhanced levels of lactate dehydrogenase(LDH)and single-stranded DNA(ssDNA)in both HT29 and HCT116.In both cell lines and at it has an IC50(45μM for HT29 and 35μM for HCT1165),Exendin-4 also significantly reduced cell survival,migration,and invasion of both cell types,with no effect on the expression GLP-1 receptors(GLPRs)nor of the activity of Akt.At these doses,Exendin-4 also increased the expression of SIRT1 but reduced the acetylation of NF-κB and the expression of Bax and cleaved caspase-3 and in both cell lines.Concomitantly,protein levels of p-GS3Kβ(Ser9),total and acetylatedβ-catenin,and Anix2 were significantly decreased,but levels of p-GS3Kβ(Ser9)and p-β-catenin(Ser33/37/Thr41)were significantly increased in both HT29 and HCT116-exendin-4 treated cells.All the effects exerted by Exendin-4 were completely prevented by Ex527 or E(9-39)A.In conclusion,Exendin-4 suppresses the tumorigenesis of HT29 and HCT116 CRC cell activation of GS3Kβ-induced inhibition ofβ-catenin and NF-κβin a SIRT1-dependent mechanism. | ATTALLA F.EL-KOTT AYMAN E.EL-KENAWY EMAN R.ELBEALY ALI S.ALSHEHRI HEBA S.KHALIFA MASHAEL MOHAMMED BIN-MEFERIJ EHAB E.MASSOUD AMIRA M.ALRAMLAWY | 2021 | BIOCELL2021，45，5： | 0 |
| 8 | Computational Linguistics with Optimal Deep Belief Network Based Irony Detection in Social Media显示文摘Computational linguistics refers to an interdisciplinary field associated with the computational modelling of natural language and studying appropriate computational methods for linguistic questions.The number of social media users has been increasing over the last few years,which have allured researchers’interest in scrutinizing the new kind of creative language utilized on the Internet to explore communication and human opinions in a betterway.Irony and sarcasm detection is a complex task inNatural Language Processing(NLP).Irony detection has inferences in advertising,sentiment analysis(SA),and opinion mining.For the last few years,irony-aware SA has gained significant computational treatment owing to the prevalence of irony in web content.Therefore,this study develops Computational Linguistics with Optimal Deep Belief Network based Irony Detection and Classification(CLODBN-IRC)model on social media.The presented CLODBN-IRC model mainly focuses on the identification and classification of irony that exists in social media.To attain this,the presented CLODBN-IRC model performs different stages of pre-processing and TF-IDF feature extraction.For irony detection and classification,the DBN model is exploited in this work.At last,the hyperparameters of the DBN model are optimally modified by improved artificial bee colony optimization(IABC)algorithm.The experimental validation of the presentedCLODBN-IRCmethod can be tested by making use of benchmark dataset.The simulation outcomes highlight the superior outcomes of the presented CLODBN-IRC model over other approaches. | Manar Ahmed Hamza Hala J.Alshahrani Abdulkhaleq Q.A.Hassan Abdulbaset Gaddah Nasser Allheeib Suleiman Ali Alsaif Badriyya B.Al-onazi Heba Mohsen | 2023 | Computers, Materials & Continua2023，，5： | 0 |
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