Coronavirus disease‐19 (COVID‐19) is correlated to a severe condition caused by a cytokine storm during which numerous proinflammatory cytokines, including interleukin‐6 (IL‐6) are released. IL‐6 is a critical driver in the COVID‐19 inflammatory state, and the inhibition is considered a potential treatment approach to prevent serious complications. Meanwhile, Melaleuca cajuputi is a plant with antibacterial, antiviral, anti‐inflammatory, and antioxidant activities. Therefore, this aimed to investigate the anti‐inflammatory potential of M. cajuputi in silico. Extraction of leaves was conducted by using 96% ethanol, followed by fractionation to obtain active compounds. Subsequently, LC/MS and GC/MS analyses were performed to obtain active compound profiling. Protein‐protein interaction (PPI), as well as molecular docking and dynamic analyses, were performed to examine interaction of active compounds of M. cajuputi with IL‐6. The results showed that 30 protein nodes played a significant role in COVID‐19 cytokine storm and eight active compounds had interactions with IL‐6. Among the active compounds, pinostrobin chalcone had the best delta G interaction with IL‐6. In conclusion, M. cajuputi has potential activity as an anti‐inflammatory agent against COVID‐19.

Background: Since the beginning of the coronavirus disease 2019 (COVID-19) outbreak, dynamic mutations in the receptor-binding domain (RBD) in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein have altered the pathogenicity of the variants of the virus circulating in Indonesia. This research analyzes the mutation trend in various RBD samples from Indonesia published in the Global Initiative on Sharing All Influenza Data (GISAID) database using genomic profiling. Method: Patients in Indonesia infected with SARS-CoV-2, whose samples have been published in genomic databases, were selected for this research. The collected data were processed for analysis following several bioinformatics protocols: visualization into phylogenetic trees, 3D rendering, and the assessment of mutational impact. Results: In Indonesia, there are 25 unique SARS-CoV-2 clades and 318 unique SARS-CoV-2 RBD mutations from the earliest COVID-19 sample to samples collected in 2022, with T478K being the most prevalent RBD mutation and 22B being the most abundant clade. The Omicron variant has a lower docking score, higher protein destabilization, and higher K_D than the Delta variant and the original virus. Conclusions: The study findings reveal a decreasing trend in virus pathogenicity as a potential trade-off to increase transmissibility via mutations in RBD over the years.

Most breast cancer cases are luminal subtypes which are estrogen receptor-sensitive or progesterone receptor-sensitive. Common treatments include surgery and adjuvant endocrine therapy by prescribing selective estrogen receptor degraders (SERD). SERD is a type of medication that inhibits estrogen receptor (ER) activity by degrading it, and as a result, downregulating it. The current FDA-approved SERD can only be administered through intramuscular injection. The aim of this study is to find orally non-toxic and bioavailable herbal alternatives of SERDs in Indonesian Herbal Database by doing virtual screening using LigandScout. The hit compounds were further analyzed using a molecular docking tool, AutoDock. Three compounds that gave the best results in molecular docking, namely kuwanon T, mulberrin, and curcumin, were analyzed in terms of their toxicity and drug-likeness. Based on toxicity and drug-likeness study, curcumin is considered to be the best candidates for SERD alternatives. This result is further supported by molecular dynamic simulation outcome in which curcumin is the most stable while binding with estrogen receptors.

This study explores the molecular landscape of cervical cancer through the identification and analysis of differentially expressed genes (DEGs) from the GSE63514 dataset. A high-confidence protein–protein interaction (PPI) network was constructed using the STRING database (v11.5) and visualized via Cytoscape, identifying 178 nodes and 1,052 edges. Using the CytoHubba plugin, the top 10 hub genes—TOP2A, MKI67, CDK1, BUB1, CCNB1, CCNA2, AURKA, CDC20, PLK1, and RFC4—were highlighted based on degree centrality. These genes are predominantly associated with cell cycle regulation, DNA replication, and mitotic division, and are potentially valuable as biomarkers or therapeutic targets for cervical cancer. Functional enrichment using DAVID and Enrichr tools revealed significant involvement of DEGs in ATP binding, spindle microtubule formation, and protein kinase activity, particularly within the chromosome centromeric region and nucleoplasm. KEGG pathway analysis identified key associations with the cell cycle, DNA replication, p53 signaling, and complement and coagulation cascades. Further heatmap analysis of treatment responders versus non-responders demonstrated distinct gene expression profiles, particularly of immune-related genes like C1QA, C3, and SERPING1, and proliferative markers such as TOP2A and MKI67. These findings underscore the dual role of immune and proliferative pathways in cervical cancer progression and suggest their utility in developing predictive biomarkers and personalized treatment strategies.

Background: Antimicrobial-resistant Escherichia coli and Klebsiella pneumoniae represent an increasing challenge in community-acquired pediatric diarrheal infections. Understanding the genomic basis and dissemination of resistance in outpatient settings is essential for guiding antimicrobial use. Methods: Eighteen Gram-negative isolates obtained from pediatric outpatients with acute diarrhea were analyzed using selective culture methods, antimicrobial susceptibility testing, and whole-genome sequencing. Multilocus sequence typing, serotyping, virulence profiling, antimicrobial resistance gene detection, plasmid replicon typing, mobile genetic element analysis, and core genome-based phylogenetic analysis were performed. Phenotypic resistance profiles were correlated with genomic resistance determinants. Results: Klebsiella pneumoniae (55.56%) and Escherichia coli (44.44%) were identified, with all isolates exhibiting putative multidrug resistance-associated genomic profiles. Extended-spectrum β-lactamase genes, particularly blaCTX-M variants, were strongly associated with resistance to third-generation cephalosporins. In contrast, fluoroquinolone resistance correlated with gyrA and parC mutations and plasmid-mediated qnr genes. Phylogenetic analysis revealed diverse lineages harboring resistance determinants. In silico plasmid analysis revealed that key resistance genes co-occurred with IncF-type plasmids and mobile genetic elements, including ISEcp1, IS26, and class 1 integrons, suggesting putative plasmid association rather than confirmed localization. Conclusions: These findings highlight the small scale of plasmid-mediated antimicrobial resistance among E. coli and K. pneumoniae causing pediatric community-acquired diarrhea. The integration of phenotypic and genomic analyses underscores the need for continuous resistance surveillance to support rational antibiotic use in outpatient settings.

Background/Objectives: Population-specific genomic data are essential for understanding hepatocellular carcinoma (HCC) biology, particularly in underrepresented regions. This study aimed to perform exploratory single-nucleotide polymorphism (SNP)-array-based profiling of HCC tumor samples from Indonesian patients and to prioritize candidate functional variants using a systematic in silico framework. Methods: This retrospective cross-sectional study included 15 resected HCC cases with available formalin-fixed paraffin-embedded (FFPE) tumor tissue. Genome-wide SNP genotyping was performed using the Illumina Asian Screening Array. Following quality control and filtering, variants were annotated using the Ensembl Variant Effect Predictor. A case-only functional prioritization approach incorporating multiple in silico prediction tools was applied, followed by gene-level burden aggregation. Results: After multistep filtering, 11 samples and 104 prioritized variants were retained for analysis. Variants consisted predominantly of splice-region, missense, and regulatory changes. Gene-level burden analysis identified Nuclear Autoantigenic Sperm Protein (NASP, rs775916096) as the highest-ranked candidate gene, while G protein-coupled receptor 78 (GPR78, rs558447540) emerged as a secondary candidate with predicted functional annotations but currently limited biological evidence in HCC. Given the tumor-only design without matched normal tissue, the prioritized variants cannot be distinguished from rare germline variants. Conclusions: This exploratory SNP-array study provides a hypothesis-generating framework for functional variant prioritization in Indonesian HCC. NASP and GPR78 represent preliminary candidates that require validation in larger cohorts with matched normal tissue and sequencing-based confirmation.