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Molecular Genetics Innovations in Diagnosis of Metabolic Disorders: Integration with Multi-Omics and Computational Approaches (Review Article)
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Inherited metabolic disorders (IMDs) are a diverse group of hereditary abnormalities that leads to a defect in metabolic pathway. Its diagnosis has been transformed by the innovations of molecular genetics and computational biology. Conventionally, diagnosis of IMDs is dependent on clinical findings and biochemical tests. Yet, these methods are limited due to a heterogeneity of such disorders and a large number of genes involved. The main objective of this review is to highlight the role of next-generation sequencing (NGS), including targeted gene panels, whole-exome sequencing (WES), and whole-genome sequencing (WGS), in the diagnosis of IMDs and providing reliable information in identifying genetic causes, and to explore the integrated analysis of several molecular layers such as genomics, transcriptomics, proteomics, metabolomics, and epigenetics. Targeted mass spectrometry and untargeted metabolomics methods are essential approaches for screening and identifying the metabolic patterns that act as a diagnosis biomarker to confirm the biochemical phenotypes associated with IMDs. Moreover, a new diagnostic model has been developed from the combination data of transcriptomics and proteomics to determine whether a gene mutation leads to a protein's dysfunction or not. The review concludes that the IMDs diagnosis should be lied in a fully integrated between molecular genetics techniques with multi-omics pipeline enhanced by artificial intelligence (AI) and machine learning (ML), which will provide a more rapid, accurate, and accessible path to diagnosis and, ultimately, more effective treatment.

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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Assessment of Some Physiological, Immunological and Molecular Biomarkers in Sample of Iraqi Women Undergoing Caesarean Section and Normal Delivery
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     Pregnancy and delivery are physiological conditions that are marked by abrupt alterations to hormones, immunological and molecular characters. The current study aimed to evaluate oxytocin (OT), prolactin (PRL), cortisol and insulin growth factor-2 (IGF-2) levels as physiological biomarkers; programmed cell death protein-1 (PD-1), programmed cell death ligand-1 (PD-L1),interleukin-6 (IL-6) as immunological biomarkers, and single nucleotide polymorphisms (SNPs; rs53576 and rs2254298) of oxytocin receptor gene OXTR as molecular factors in samples of Iraqi women undergoing caesarean section (CS) and normal delivery (ND). Blood samples were collected from 96 pregnant women at term with ages ranging between 16-43 years. Regarding

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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Access
Patient Monitoring System Based on Internet of Things: A Review and Related Challenges With Open Research Issues
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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials & Continua
Submarine Hunter: Efficient and Secure Multi-Type Unmanned Vehicles
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Publication Date
Wed Mar 01 2017
Journal Name
Ieee Transactions On Cognitive Communications And Networking
Multi-Channel Distributed DSA Networks: Connectivity and Rendezvous Tradeoffs
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In this paper, we investigate and characterize the effects of multi-channel and rendezvous protocols on the connectivity of dynamic spectrum access networks using percolation theory. In particular, we focus on the scenario where the secondary nodes have plenty of vacant channels to choose from a phenomenon which we define as channel abundance. To cope with the existence of multi-channel, we use two types of rendezvous protocols: naive ones which do not guarantee a common channel and advanced ones which do. We show that, with more channel abundance, even with the use of either type of rendezvous protocols, it becomes difficult for two nodes to agree on a common channel, thereby, potentially remaining invisible to each other. We model this in

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Publication Date
Sun Dec 01 2024
Journal Name
The Medical Journal Of Tikrit University
ChemiluminescenceMicroparticle Immunoassay in the Diagnosis of Hepatitis C Virus among Patients on Hemodialysis: A Comparative Study
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Browse Iraqi academic journals and research papers

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Publication Date
Sun Apr 13 2025
Journal Name
Scientific Reports
Optimized image segmentation using an improved reptile search algorithm with Gbest operator for multi-level thresholding
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Abstract<p>Image segmentation using bi-level thresholds works well for straightforward scenarios; however, dealing with complex images that contain multiple objects or colors presents considerable computational difficulties. Multi-level thresholding is crucial for these situations, but it also introduces a challenging optimization problem. This paper presents an improved Reptile Search Algorithm (RSA) that includes a Gbest operator to enhance its performance. The proposed method determines optimal threshold values for both grayscale and color images, utilizing entropy-based objective functions derived from the Otsu and Kapur techniques. Experiments were carried out on 16 benchmark images, which inclu</p> ... Show More
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Publication Date
Fri Jan 01 2021
Journal Name
Research Journal Of Pharmacy And Technology
Bacteriological and molecular study on S. Aureus bacteria Atala, M.L.
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Publication Date
Tue Mar 19 2019
Journal Name
Tikrit Journal For Agricultural Sciences
Dependence and Phenotypic and Molecular Labels in Estimations of Genetic of Variance of Some Genotypes of Corn (Zea mays L.)
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Afield experiment was conducted in the college of Agriculture labs Sulaimanya University in 2014 to estimate the genetic variance between 12 genotypes of maize. (SSR) technology was used depending on (PCR) technology. Twenty primers were used for the genetic variance analysis between the studied genotypes and 15 primers showed polymorphic results in repeated experiment caused to experinse 52 alleles which gave 307 bands of range 3.1 by different molecular sizes ranged between 80-1000 pair base the value of PIC reached to phi069 gave high value (0.8785), the range of genetic diversity for studied genotypes reached to (0.625) gave primers pairs phi069 hig value for genetic diversity (0.888). The value of total allele replication ranged at pri

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Publication Date
Thu Jul 28 2016
Journal Name
Journal Of Advanced Nursing
Cardiovascular medication adherence among patients with cardiac disease: a systematic review
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Abstract<sec><title>Aims

The aim of this study was to critically appraise and synthesize the best available evidence on the effectiveness of interventions suitable for delivery by nurses, designed to enhance cardiac patients' adherence to their prescribed medications.

Background

Cardiac medications have statistically significant health benefits for patients with heart disease, but patients' adherence to prescribed medications remains suboptimal.

Design

A systematic quantitative review of intervention effects.

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