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The Prevalence of UGT1A1*93 and ABCC5 Polymorphisms in Cancer Patients Receiving Irinotecan-Based Chemotherapy at Al-Najaf Al-Ashraf
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Irinotecan (CPT-11) is a semisynthetic derivative of the antineoplastic agent camptothecin used in a wide range as an anti-cancer agent in many solid tumors because of its cytotoxic effect through the interaction with the topoisomerase I enzyme. The major limiting factors for irinotecan treatment are its association with potentially life-threatening toxicities including neutropenia and acute or delayed-type diarrhea, results from distinct interindividual and interethnic variability due to gene polymorphism.

This is a cross sectional pharmacogentics study was conducted on 25 cancer patients to estimate the prevalence of UGT1A1*93 and ABCC5 allele single nucleotide polymorphism (SNP) in Iraqi cancer patients treated with irinotecan-based therapy at Middle Euphrates Cancer Center. Four drops of venous blood was drawn for each patient and was applied onto the FTA classic card to perform a genotyping assay for the 2 SNPs. After DNA isolation and purification, real time PCR was performed to detect the SNPs of each gene.

Results of this study showed the prevalence of one allele variant (heterozygous mutation) of UGT1A1*93 was 64% compared to 36% of patients were wild type to this SNP. No patient (0%) could be detected with homozygous polymorphism of the UGT1A1*93. For the ABCC5 polymorphism, results revealed that 32% of patients have one polymorphic allele (heterozygous), while 28% of them have two polymorphic alleles (homozygous mutation). Wild type ABCC5 gene constitutes 40% of patients.   As a conclusion, high prevalence of UGT1A1*93 and ABCC5 polymorphic alleles were detected in patients at Middle Euphrates Cancer Center which may explain the high toxicity features associated with irinotecan therapy. 

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Publication Date
Wed Sep 26 2018
Journal Name
Communications In Computer And Information Science
A New RGB Image Encryption Based on DNA Encoding and Multi-chaotic Maps
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Publication Date
Thu Jan 20 2022
Journal Name
Webology
Hybrid Intrusion Detection System based on DNA Encoding, Teiresias Algorithm and Clustering Method
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Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
Mobile-based Telemedicine Application using SVD and F-XoR Watermarking for Medical Images
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A medical- service platform is a mobile application through which patients are provided with doctor’s diagnoses based on information gleaned from medical images. The content of these diagnostic results must not be illegitimately altered during transmission and must be returned to the correct patient. In this paper, we present a solution to these problems using blind, reversible, and fragile watermarking based on authentication of the host image. In our proposed algorithm, the binary version of the Bose_Chaudhuri_Hocquengham (BCH) code for patient medical report (PMR) and binary patient medical image (PMI) after fuzzy exclusive or (F-XoR) are used to produce the patient's unique mark using secret sharing schema (SSS). The patient’s un

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Coronavirus Disease Diagnosis, Care and Prevention (COVID-19) Based on Decision Support System
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              Automated clinical decision support system (CDSS) acts as new paradigm in medical services today. CDSSs are utilized to increment specialists (doctors) in their perplexing decision-making. Along these lines, a reasonable decision support system is built up dependent on doctors' knowledge and data mining derivation framework so as to help with the interest the board in the medical care gracefully to control the Corona Virus Disease (COVID-19) virus pandemic and, generally, to determine the class of infection and to provide a suitable protocol treatment depending on the symptoms of patient. Firstly, it needs to determine the three early symptoms of COVID-19 pandemic criteria (fever, tiredness, dry cough and breat

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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Topology-Based Modularity and Modularity Density for Detecting Protein Complexes: A Comparative Study
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     Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin

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Publication Date
Wed Aug 28 2024
Journal Name
Mesopotamian Journal Of Cybersecurity
A Novel Anomaly Intrusion Detection Method based on RNA Encoding and ResNet50 Model
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Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

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Publication Date
Wed Jan 01 2020
Journal Name
Iraqi Journal Of Science
Paper based glucose biosensor depending on SPCE modified with hemoglobin and silver nanoparticles
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The direct electron transfer behavior of hemoglobin that is immobilized onto screen-printed carbon electrode (SPCE) modified with silver nanoparticles (AgNPs) and chitosan (CS) was studied in this work. Cyclic voltametry and spectrophotometry were used to characterize the hemoglobin (Hb) bioconjunction with AgNPs and CS. Results of the modified electrode showed quasi-reversible redox peaks with a formal potential of (-0.245 V) versus Ag/AgCl in 0.1 M phosphate buffer solution (PBS), pH7, at a scan rate of 0.1 Vs-1. The charge transfer coefficient (α) was 0.48 and the apparent electron transfer rate constant (Ks) was 0.47 s-1. The electrode was used as a hydrogen peroxide biosensor with a linear response over 3 to 240 µM and a detection li

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Publication Date
Wed Aug 28 2024
Journal Name
Mesopotamian Journal Of Cybersecurity
A Novel Anomaly Intrusion Detection Method based on RNA Encoding and ResNet50 Model
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Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

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Publication Date
Mon Jan 01 2024
Journal Name
Fifth International Conference On Applied Sciences: Icas2023
Facial deepfake performance evaluation based on three detection tools: MTCNN, Dlib, and MediaPipe
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Publication Date
Mon Oct 28 2019
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
Heuristic Initialization And Similarity Integration Based Model for Improving Extractive Multi-Document Summarization
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