Search

Your search keyword '"Khan, Faiza"' showing total 474 results
Start Over Author "Khan, Faiza"
474 results on '"Khan, Faiza"'

53. Volume outcome relationship in post-esophagectomy leak: A systematic review and meta-analysis

Author

Rahouma, Mohamed, primary, Baudo, Massimo, additional, Mynard, Nathan, additional, Kamel, Mohamed, additional, Khan, Faiza M., additional, Shmushkevich, Shon, additional, Mehta, Kritika, additional, Hosny, Mohamed, additional, Dabsha, Anas, additional, Khairallah, Sherif, additional, Demetres, Michelle, additional, Saad, Reda, additional, Mohamed, Abdelrahaman, additional, Port, Jeffrey L., additional, Altorki, Nasser K., additional, and Gaudino, Mario, additional

Published
2023
Full Text
View/download PDF

62. Effect of Inorganic Selenium Supplementation on Thyroid Hormone and Redox Status in Broiler under Dexamethasone Induced Stress

Author

Afshan, Afshan, primary, Ullah, Asad, additional, Khan, Imad, additional, Ullah, Rafiq, additional, Tayyab, Tahira, additional, Syed, Fatima, additional, Taj, Raheela, additional, Gul, Shumaila, additional, Khan, Faiza, additional, Jan, Ibad Ullah, additional, Ali, Syed Weqas, additional, and Ullah, Assad, additional

Published
2023
Full Text
View/download PDF

68. Palmitoylation of the Alternative Amino Terminus of the BTK-C Isoform Controls Subcellular Distribution and Signaling

Author

KOKABEE, MOSTAFA, WANG, XIANHUI, VOORAND, ELENA, ALIN, EDEN, KOKABEE, LEILA, KHAN, FAIZA, DESROSIERS, SOPHIA, and CONKLIN, DOUGLAS S.

Subjects
Cancer Research, Lipoylation, Breast Neoplasms, Biochemistry, Phosphatidylinositol 3-Kinases, Glucose, Agammaglobulinaemia Tyrosine Kinase, Genetics, Humans, Protein Isoforms, Female, Neoplasms, Glandular and Epithelial, Molecular Biology, Research Article
Abstract

Background: The alternative transcriptional isoform of Bruton’s tyrosine kinase, BTK-C, is expressed in a wide variety of epithelial tumor types where it impacts apoptosis resistance, therapeutic escape, and glucose uptake. The initial exon in BTK-C encodes a 34 amino acid extension of the amino terminus of the canonical BTK-A isoform. Its function is unknown. Materials and Methods: Site-directed mutagenesis, acylation assays and expression studies in cancer cell lines were used to determine the effects that the BTK-C first exon sequence has on kinase activity, subcellular localization and cell physiology. Analysis of BTK-C expression in tumors was conducted using genomic databases. Results: BTK-C is palmitoylated on two cysteine residues. BTK-C localization at the plasma membrane is dependent upon phosphatidylinositol 3,4,5-triphosphate (PIP(3)) levels as well as palmitoylation. In epithelial cancer cells, both BTK-A and BTK-C isoforms are recruited to the plasma membrane; however, BTK-A also localizes to the nucleus whereas BTK-C has a primarily perinuclear distribution. Transcription of the BTK-C isoform is inversely correlated with expression of commonly activated breast cancer signaling receptors in breast tumors. In MDA-MB-231 cells, BTK-C expression confers modest increases in proliferation and glucose uptake rates compared to BTK-A. Conclusion: Palmitoylation affects localization and regulation of BTK-C in epithelial tumor cells where it functions as an important survival factor. Expression of either palmitoylated or non-palmitoylated kinase isoforms that function in PI3K signaling may be a common regulatory feature as nine other soluble kinases in the human genome possess similarly encoded alternative N-termini (ANT).

Published
2022

73. sj-docx-1-smo-10.1177_20503121231181267 – Supplemental material for Treatment of eculizumab refractory paroxysmal nocturnal hemoglobinuria: A systematic review about current treatment options and future direction

Author

Syed, Saad, Khan, Reda, Khurram, Fahmida, Khan, Faiza Humayun, Safi, Danish, and Safi, Salah Ud Din

Subjects
FOS: Veterinary sciences, 111199 Nutrition and Dietetics not elsewhere classified, Cardiology, 170199 Psychology not elsewhere classified, 111799 Public Health and Health Services not elsewhere classified, 110604 Sports Medicine, FOS: Health sciences, 110306 Endocrinology, 110308 Geriatrics and Gerontology, 111099 Nursing not elsewhere classified, 111708 Health and Community Services, 160807 Sociological Methodology and Research Methods, 111702 Aged Health Care, 111403 Paediatrics, 110904 Neurology and Neuromuscular Diseases, 110203 Respiratory Diseases, 110315 Otorhinolaryngology, 70706 Veterinary Medicine, FOS: Clinical medicine, 110319 Psychiatry (incl. Psychotherapy), FOS: Sociology, FOS: Psychology, 110599 Dentistry not elsewhere classified, 110323 Surgery, 110305 Emergency Medicine, 111599 Pharmacology and Pharmaceutical Sciences not elsewhere classified, 111299 Oncology and Carcinogenesis not elsewhere classified, 110314 Orthopaedics
Abstract

Supplemental material, sj-docx-1-smo-10.1177_20503121231181267 for Treatment of eculizumab refractory paroxysmal nocturnal hemoglobinuria: A systematic review about current treatment options and future direction by Saad Syed, Reda Khan, Fahmida Khurram, Faiza Humayun Khan, Danish Safi and Salah Ud Din Safi in SAGE Open Medicine

Published
2023
Full Text
View/download PDF

90. COVID‐opt‐aiNet: A clinical decision support system for COVID‐19 detection

Author

Kanwal, Summrina, Khan, Faiza, Alamri, Sultan, Dashtipur, Kia, and Gogate, Mandar

Subjects
bidirectional long-short-term memory, clinical decision support system, convolution neural network, COVID-19, deep learning neural network, feature selection, optimized artificial immune network, support vector machine
Abstract

Coronavirus disease (COVID-19) has had a major and sometimes lethal effect on global public health. COVID-19 detection is a difficult task that necessitates the use of intelligent diagnosis algorithms. Numerous studies have suggested the use of artificial intelligence (AI) and machine learning (ML) techniques to detect COVID-19 infection in patients through chest X-ray image analysis. The use of medical imaging with different modalities for COVID-19 detection has become an important means of containing the spread of this disease. However, medical images are not sufficiently adequate for routine clinical use; there is, therefore, an increasing need for AI to be applied to improve the diagnostic performance of medical image analysis. Regrettably, due to the evolving nature of the COVID-19 global epidemic, the systematic collection of a large data set for deep neural network (DNN)/ML training is problematic. Inspired by these studies, and to aid in the medical diagnosis and control of this contagious disease, we suggest a novel approach that ensembles the feature selection capability of the optimized artificial immune networks (opt-aiNet) algorithm with deep learning (DL) and ML techniques for better prediction of the disease. In this article, we experimented with a DNN, a convolutional neural network (CNN), bidirectional long-short-term memory, a support vector machine (SVM), and logistic regression for the effective detection of COVID-19 in patients. We illustrate the effectiveness of this proposed technique by using COVID-19 image datasets with a variety of modalities. An empirical study using the COVID-19 image dataset demonstrates that the proposed hybrid approaches, named COVID-opt-aiNet, improve classification accuracy by up to 98%–99% for SVM, 96%–97% for DNN, and 70.85%–71% for CNN, to name a few examples. Furthermore, statistical analysis ensures the validity of our proposed algorithms. The source code can be downloaded from Github: https://github.com/faizakhan1925/COVID-opt-aiNet.

Published
2022

91. Cognitive-inspired Post-processing of optical character recognition for Swedish addresses

Author

Andersson, Moa, Kanwal, Summrina, Khan, Faiza, Andersson, Moa, Kanwal, Summrina, and Khan, Faiza

Abstract

Optical character recognition (OCR) has many ap-plications, such as digitizing historical documents, automating processes, and helping visually impaired people read. However, extracting text from images into a digital format is not an easy problem to solve, and the outputs from the OCR frameworks often include errors. The complexity comes from the many variations in (digital) fonts, handwriting, lighting, etc. To tackle this problem, this thesis investigates two different methods for correcting the errors in OCR output. The used dataset consists of Swedish addresses. The methods are therefore applied to postal automation to investigate the usage of these methods for further automating postal work by automatically reading addresses on parcels using OCR. The first method, the lexical implementation, uses a dataset of Swedish addresses so that any valid address should be in this dataset (hence there is a known and limited vocabulary), and misspelled addresses are corrected to the address in the lexicon with the smallest Levenshtein distance. The second approach uses the same dataset, but with artificial errors, or artificial noise, added. The addresses with this artificial noise are then used together with their correct spelling to train a machine learning model based on Neural machine translation (NMT) to automatically correct errors in OCR read addresses. The results from this study could contribute by defining in what direction future work connected to OCR and postal addresses should go. The results were that the lexical implementation outperformed the NMT model. However, more experiments including real data would be required to draw definitive conclusions as to how the methods would work in real-life applications., Part of ISBN 9781665490849QC 20230801

Published
2022
Full Text
View/download PDF

92. Risk Factors for Bronchiolitis in Infants of Hazara Division - A Cross Sectional Study

Author

Shah, Syed Sajid Hussain, Khan, Naima, Khan, Mohsin, Khan, Faiza, Shah, Syed Sajid Hussain, Khan, Naima, Khan, Mohsin, and Khan, Faiza

Abstract

OBJECTIVES Bronchiolitis is one of the major causes of hospitalization in the infants. Higher rate of hospitalization and mortality can be reduced by recognizing and control of risk factors for bronchiolitis. The objective of this study is to ascertain risk factors of bronchiolitis in infants, in local population of Hazara Division. METHODOLOGY This cross-sectional study was done in Ayub teaching hospital form January, 2020 till June 2020. Infants of both gender from age of 3 months to 12 months were included with diagnosis of bronchiolitis. Patients with croup, pneumonia, cystic fibrosis and bronchomalasia are excluded. Demographic variables, clinical characteristics and risk factors of bronchiolitis related to infant, mother and family were documented on specific proforma. The data was analyzed by SPSS 21. RESULTS There were 101 infants. Mean age was 5±3.5 months. Male to female ratio was 2.8. 77.2% infant had de livery through surgical procedure and 82% are term. 45% infants were exclusively breast fed. 34% patients room were carpeted, 35% exposed to molds and 81% had history of contact with infected person.28% infants are exposed to passive smoke, 49% had history of allergies and 60% mothers uses perfume to their child’s. 31% infants have more than 10 family members and are living in 2 rooms (p=0.000). Infant weaned at 6month have late onset of bronchiolitis as compare to infants weaned before 6 months (p=0.000). CONCLUSION Perfume/powder use, family history of allergies, history of contact with respiratory infection, delivery with surgical procedure as major new risk factors. Carpets, mold, passive smoking, overcrowding, are also contributing risk factors.

Published
2022

93. Role of Multi detector computed Tomography in the evaluation of colorectal lesions with histopathological correlation.

Author

Mohammad Farid Khan, Khan Mohammad Faraz, Dayma, Chandrasen, Chouhan, Priyal, Khan, Faiza Fareed, and Khan, Fouzia Fareed

Subjects
DETECTORS, CONTRAST media, HISTOPATHOLOGY, SUPINE position, COLON (Anatomy)
Abstract

Background & Method: The aim of present study is to study the role of Multi detector computed Tomography in the evaluation of colorectal lesions with histopathological correlation. In this study, patients with wall thickening involving the colon and rectum on CT were included. CT was performed using Idohexol contrast medium. All patients were placed in the supine position on the CT table, and a rectal tube was inserted. Room air was gently insufflated into the colon get adequate colonic distension. CT acquisitions were performed in the arterial phase (start delay of 25-35 seconds) and in the portal venous phase (start delay of 50- 70 seconds) with a section width of 5 mm. when wall thickening is identified, it is characterized using the following criteria. Result: Of the 50 patients with colorectal lesions on CT, 40 lesions (80%) were diagnosed as malignant and 10 lesions (20%) were diagnosed as benign on histopathology. Of the 50 patients with colorectal lesions on CT, 40 lesions (80%) were diagnosed as malignant and 10 lesions (20%) were diagnosed as benign on histopathology. Conclusion: MDCT is an excellent modality in the diagnosis and differentiation of benign and malignant lesions of the colon and rectum, since it has the advantage of providing thinner sections, faster acquisition and multi planar reformatted images. MDCT is also useful in the staging of malignant lesions which helps in proper planning of surgery and further management of the patient. [ABSTRACT FROM AUTHOR]

Published
2023

Catalog

Books, media, physical & digital resources
See catalog results