Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal International Journal of Applied Mathematics, Sciences, and Technology for National Defense
Milasari, Azizah Eka
Unknown Affiliation
Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Mathematics Physics

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Insights into latent tuberculosis biomarkers from differential gene expression analysis in CD8 memory cells using secondary data Insilico approach Atmadi, Atmadi; Rahayu, Tiara; Wardani, Indah Kusuma; Elsadi, Reihana Marsha Cahyani; Milasari, Azizah Eka; Witadi, M. Ridwan Amarullah
International Journal of Applied Mathematics, Sciences, and Technology for National Defense Vol 2, No 3 (2024): International Journal of Applied Mathematics, Sciences, and Technology for Natio
Publisher : FoundAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/app.sci.def..v2i3.362

Abstract

Tuberculosis (TB) remains a global health challenge, significantly impacting infectious disease mortality and morbidity. In the quest for effective diagnostic tools and precise treatment strategies, differential gene expression (DEG)-based biomarkers offer a promising avenue. These biomarkers provide specific insights into disease states and treatment responses by deciphering gene alterations within body cells. In this study, we aimed to identify immunological signatures associated with latent Mycobacterium tuberculosis infection in memory T cells. Leveraging transcriptomic analysis, we examined memory CD8 T cells from individuals with latent TB (NCBI-GEO GSM2643205) and healthy controls (NCBI-GEO GSM2643198). Our findings highlight candidate biomarker genes—LDB1, ZNF121, and STAT6—whose differential expression could significantly enhance our understanding of CD8 T cell genetic regulation during latent TB infection. These results hold promise for the development of more accurate biomarkers for diagnosing latent tuberculosis.
Co-Authors Atmadi, Atmadi Elsadi, Reihana Marsha Cahyani Rahayu, Tiara Wardani, Indah Kusuma Witadi, M. Ridwan Amarullah