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3 articles for “B-cell acute lymphoblastic leukemia”
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An Evaluative Comparison of CD123 and CD66c as Biomarkers to Detect Minimal Residual Disease in B-Cell Acute Lymphoblastic Leukemia
Abstract: Background: B-cell Acute Lymphoblastic Leukemia (B-ALL) often shows lineage heterogeneity with lymphoid cells expressing myeloid markers. Minimal Residual Disease (MRD) refers to the small number of cancer cells that may remain in a patient's body after treatment and that are undetectable by standard diagnostic methods. In diseases like B-cell Acute Lymphoblastic Leukemia (B-ALL), MRD is a critical prognostic indicator, as its presence can signal a higher risk of relapse. In …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 · pp. 7–12 Read article
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Exploring the Potential of Allium sativum Phytocompounds as B-Cell Leukemia 2 Inhibitors in Acute Lymphoblastic Leukemia: Molecular Docking Study
Abstract: Objective: Acute lymphoblastic leukemia (ALL) is a lymphoid progenitor cell malignancy that could be treated with plant-based drugs, thus alleviating the off-target effects caused by conventional chemotherapy. Since ancient days, Allium sativum has been an integral part of traditional medicine and an excellent antimicrobial, antioxidant, and antiproliferative agent. Hence, this study aims to assess the anti-leukemic potential of A. sativum phytoconstituents as the B-cell leukemia 2 protein (Bcl-2) natural inhibitor …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 2, 2024 · pp. 53–80 Read article
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A Systematic Review on Leukemia Detection and Classification Techniques Using Gene Expression
Abstract: Early diagnosis of genetic diseases is crucial for effective treatment, especially in the case of Leukemia, a type of blood cancer characterized by abnormal proliferation of white blood cells. This paper presents a systematic review of recent computational techniques for the detection and classification of Leukemia using gene expression data obtained from DNA microarray analysis. The study explores diverse methodologies including machine learning (ML), deep learning (DL), and bio-inspired algorithms …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 2, 2025 Read article