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Role of endoscopic ultrasound and cyst fluid tumor markers in diagnosis of pancreatic cystic lesions

World Journal of Gastrointestinal Endoscopy 2022年第6期14卷 402-415页

作者： 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 Department of Internal Medicine and Hepatogastroenterology Kasr Al-Aini HospitalsCairo UniversityKasr Al-Aini HospitalsCairo UniversityCairo 11451Egypt Department of Endemic Diseases Cairo UniversityCairo 11451Egypt Department of Tropical Medicine and Gastroenterology Minia UniversityMinia 61511Egypt Department of Internal Medicine Kasr Al-Aini HospitalsCairo UniversityCairo 11562Egypt Department of Gastroenterology Armed forces College of MedicineCairo 11451Egypt Endoscopy and Internal Medicine Consultant at Dr/Ahmed Galal Endoscopy Center Alexandria 35516Egypt Department of Internal Medicine Faculty of MedicineAssuit UniversityAssuit 71111Egypt Department of Gastroenterology and Hepatology Mansoura UniversityMansoura 35511Egypt Department of Gastroenterology and Hepatology Theodor Bilharz Research InstituteCairo 11451Egypt Department of Microbiology and Immunology Faculty of Medicine for girls Al-Azhar UniversityCairo 11451Egypt Department of Internal Medicine Faculty of MedicineAin shams UniversityCairo 11451Egypt Department of Internal Medicine Bani-suef UniversityBani-suefBani-suef 62511Egypt Department of Pathology Faculty of MedicineCairo UniversityCairo 11451Egypt Department of Clinical Pathology Faculty of MedicineCairo UniversityCairo 11451Egypt Department of Environmental Medicine&Clinical Pathology National Research CentreCairo 11451Egypt

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 *** 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 *** 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 *** 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 alignancy 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 *** EUS examination of cyst morphology with cytopathological analysis and cyst fluid ana

关键词： Pancreatic cystic neoplasm Mucinous cystic neoplasm Intraductal papillary mucinous neoplasm Mucin stain Amylase

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Automatic segmentation of Colon Cancer Cells Based on Active Contour Method： A New Approach

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Journal of Life Sciences 2013年第2期7卷 105-109页

作者： Jamal Charara Alaa Hilal ali Al Houseini Walid Hassan mohamad Nassreddine Department of Physics and Electronics Faculty of Sciences I Lebanese University Beirut Lebanon

Automatic interpretation of the images of colon cell biopsies requires automatic segmentation of these cells in the image obtained. The active contour method for image segmentation is a well known method for automatic detection of the cell contour. However, the application of this method on colon cell images was not effective. In this paper, the authors have proposed a new technique to reduce the analysis time needed to detect cells in a given image. This technique is based on the active contour method but now using a progressive division of the dimensions of the image to achieve convergence. The model proposed succeeded in detecting cells whose boundaries are not necessarily defined by a gradient. The initial curve can be anywhere in the image, and interior contours can be automatically detected. The developed algorithm was successfully applied on textured multispectral images of three types of cells, including benign hyperplasia (BH), intraepithelial neoplasia (IN), and carcinoma (Ca) cells.

关键词：主动轮廓法癌细胞自动分割结肠图像分割方法自动检测方法多光谱图像自动判读

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Automated Classification of Segmented Cancerous Cells in Multispectral Images

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Journal of Life Sciences 2013年第4期7卷 358-362页

作者： Alaa Hilal Jamal Charara ali Al Houseini Walid Hassan mohamad Nassreddine Signal and Image Processing Lab Faculty of Sciences I Lebanese University Beirut Lebanon

Automatic reading procedures in colon cells biopsies allow a faster and precise reading of microscopic biopsies. These procedures implement automatic image segmentation in order to classify cell types as cancerous or noncancerous. The authors have developed a new approach aiming to detect colon cancer cells derived from the "Snake" method but using a progressive division of the dimensions of the image to achieve rapid segmentation. The aim of the present paper was to classify different cancerous cell types based on nine morphological parameters and on probabilistic neural network. Three types of cells were used to assess the efficiency of our classifications models, including BH (Benign Hyperplasia), IN (Intraepithelial Neoplasia) that is a precursor state for cancer, and Ca (Carcinoma) that corresponds to abnormal tissue proliferation (cancer). Results showed that among the nine parameters used to classify cells, only three morphologic parameters (area, Xor convex and solidity) were found to be effective in distinguishing the three types of cells. In addition, classification of unknown cells was possible using this method.

关键词：多光谱图像自动分类癌细胞形态学参数细胞类型分段概率神经网络图像分割

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Discovery of Simple Sequence Repeat Markers through Transcriptome Analysis of Baccaurea motleyana

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Journal of Food Science and Engineering 2020年第2期10卷 33-46页

作者： Khairun Hisam Nasir Muhammad Fairuz Mohd Yusof Mohd Shahril Firdaus Abdul Razak Siti NorsaidahIbrahim Mira Farzana mohamad Moktar Khadijah Awang Mohd Shukri Mat ali Centre for Molecular Marker Discovery and Validation(CMDV) Agri-Omic dan BioinformaticsBiotechnology and Nanotechnology Research CentreMalaysian Agricultural Research and Development Institute(MARDI)Serdang 43400SelangorMalaysia Industrial Crop Research Centre Malaysian Agricultural Research and Development Institute(MARDI)Serdang 43400SelangorMalaysia Horticulture Research Centre Malaysian Agricultural Research and Development Institute(MARDI)Serdang 43400SelangorMalaysia

Baccaurea motleyana(rambai)is underutilized fruits that are native to Malaysia,Indonesia and *** this study,a total of 54,779 unigenes identified from rambai transcriptome were used for simple sequence repeat(SSR)analysis by MIcroSAtellite(MISA).A total of 20,420 SSRs were found to be distributed within 37.27%of the total number of *** repeats represented the main type,accounting for 64.04%,followed by trinucleotide repeats(20.28%)and dinucleotide repeats(19.94%).Gene annotation to seven databases has a success ratio of 68.53%(National Center for Biotechnology Information(NCBI)protein sequences),53.68%(NCBI nucleotide sequences),27.43%(Kyoto Encyclopedia of Genes and Genome Ortholog),56.0%(SwissProt),52.44%(Protein family),53.99%(Gene Ontology)and 26.44%(Kluster of Orthologous Group).Further rambai SSRs were randomly selected and validated to ***(rambai),***(tampoi),***(jentik-jentik),***(pupor)and ***(setambun).

关键词： Baccaurea SSR transcriptome gene annotation and SSR validation

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