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Genetic variation among dengue virus that possibly correlate with pathogenesis Raekiansyah, Muhareva; Sudiro, T. M.
Medical Journal of Indonesia Vol 13, No 3 (2004): July-September
Publisher : Faculty of Medicine Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (211.165 KB) | DOI: 10.13181/mji.v13i3.151

Abstract

Dengue disease are reemerging disease and major health concern in tropical and subtropical regions because of the increasing number of patients, expanding endemic areas and increased occurrence of severe clinical manifestation (DHF/DSS) in the last two decades. Despite extensive studies, it is not fully elucidated mechanism by which dengue infection progress to DHF/DSS. Information obtained so far indicates that both host-related factor and virus virulence are involved. Recent studies have shown several structural differences of dengue virus genome between those associated with DF only and those with the potential to cause DHF. That genome differences might be correlated with pathogenesis. (Med J Indones 2004; 13: 190-4) Keywords: dengue virus, virulence factor, pathogenesis
SARS-CoV-2: Virology and Drug Repurposing Approaches Rahmasari, Ratika; Setiawan, Heri; Syahdi, Rezi Riadhi; Arifianti, Ayun; Irianti, Marina Ika; Sauriasari, Rani; Makau, Juliann Nzembi; Raekiansyah, Muhareva
Pharmaceutical Sciences and Research Vol. 7, No. 4
Publisher : UI Scholars Hub

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Abstract

An emerging coronavirus, SARS-CoV-2, is the causative agent for the ongoing pandemic of coronavirus disease 2019 (COVID-19), which has caused a worldwide social and economic disruption. Currently, no antiviral drugs with proven clinical efficacy, or vaccines for its prevention. Therefore, to combat the pandemic of this novel coronavirus, new effective treatments are urgently needed. In the process of traditional drug development, developing new drugs from scratch is a time- consuming process, requires high-investment, and is a high-risk process, which is impractical to face the immediate global challenge of the SARS-CoV-2 pandemic. Drug repurposing strategy is one of the effective ways to quickly find a therapeutic agent for COVID-19 Existing medicines, which already have been tested and proven safe in humans might work for COVID-19 offering a potentially faster approach for the disease management. Here, we review h the latest research progress in epidemiology, viral genome, and life cycles of SARS-CoV-2. Further, we describe and discuss some promising drugs repurposed to target SARS-CoV-2 that are being evaluated in clinical trials.
The Influence of CYP2C19 Gene Polymorphism on Selective Serotonin Reuptake Inhibitors In Patients with Major Depressive Disorder: A Pharmacogenetic Prospecting Approach Urbaningrum, Lestari Mahardika; Hermosaningtyas, Anastasia Aliesa; Kasasiah, Ahsanal; Rahmasari, Ratika; Raekiansyah, Muhareva; Hartanto, Adrian; Malau, Jekmal
Journal of Biomedicine and Translational Research Vol 10, No 1 (2024): April 2024
Publisher : Faculty of Medicine, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jbtr.v10i1.20338

Abstract

Major Depressive Disorder (MDD) is a chronic disorder characterized by at least a two-week-long major depressive episode. Selective Serotonin Reuptake Inhibitors (SSRIs) remain the primary prescribed antidepressants to treat MDD. However, SSRIs themselves are found to be ineffective in some individuals or may even lead to adverse side effects. These variable responses have been linked to the drug being metabolized by CYP2C19, which exhibited various polymorphisms. Understanding how gene polymorphism affects drug metabolism is essential since these insights can revolutionize clinical practice, allowing for more precise and personalized treatment approaches that optimize efficacy while minimizing side effects. This issue is particularly pertinent in Indonesia, where research in this area lags behind the pressing need for such studies. In this review, the impact of CYP2C19 polymorphism on the effectiveness of SSRI class drugs, namely citalopram, escitalopram, and sertraline, are explored. Nine relevant articles related to the topic have been studied in Japan, China, Turkey, Russia, Scandinavia, and Australia. The results concluded that CYP2C19 polymorphism can influence the metabolism of SSRIs (citalopram, escitalopram, and sertraline) due to its variability in enzyme activities, which includes both loss-of-function (*2, *3) and gain-of-function (*17) polymorphisms. Consequently, these genetic variations can lead to significant changes in drug efficacy and safety changes within individual patients. This review sheds light on the importance of considering genetic factors when prescribing SSRIs for MDD in the future treatment strategies.
In Silico Analysis of Actin Gene as a Candidate for DNA Non-Halal Detection Base on Real-Time PCR Waluyo, Seagames; Malau, Jekmal; Raekiansyah, Muhareva; Yulian, Edwin; Hardiman, Imam
Indonesian Journal of Halal Research Vol. 3 No. 2 (2021): August
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/ijhar.v3i2.12123

Abstract

Actin genes are genes that are common in organisms, and their expression is constitutive. These genes are used for gene normalization and internal control of DNA extraction, but the actin gene is not widely used for halal certification tests. Bioinformatic studies help to analyze the experiment through in silico more deeply before the experiment is carried out in laboratory, making it more efficient and time effective. uMelt is an analysis to predict the melting curve of target amplification in real-time PCR. Real-time PCR has been widely used for screening and detection of pork content in a product. This research aimed to explore actin gene as a candidate for testing pork using qPCR. The study was carried out in two main stages, namely alignment of the DNA sequence and analysis of the melting curve using the uMelt approach. The results showed a set of actin genes containing conserved regions that can be used as degenerate primers with different family-type coverages. Melting curve prediction with uMelt shows differences in tm peaks so as the types of samples can be easily identified. The use of bioinformatic applications such as uMelt helps in the simulation of predicting the melting curve to increase the precision of the analysis.