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All Journal Sriwijaya Journal of Forensic and Medicolegal Sriwijaya Journal of Internal Medicine Sriwijaya Journal of Otorhinolaryngology
Bjorka Alma
Department of Molecular Medicine, Ordubad State Hospital, Ordubad, Azerbaijan
Biochemistry, Genetics & Molecular Biology Health Professions Immunology & microbiology Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Neuroscience Nursing Public Health

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Cross-Cohort Transcriptomic Analysis Identifies an ECM–CAF Stromal Program but Does Not Validate a Seven-Gene Prognostic Score in Head and Neck Squamous Cell Carcinoma Reisha Notonegoro; Bjorka Alma; Patricia Wulandari; Muhammad Yoshandi
Sriwijaya Journal of Otorhinolaryngology Vol. 3 No. 2 (2025): Sriwijaya Journal of Otorhinolaryngology
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjorl.v3i2.307

Abstract

Background: Head and neck squamous cell carcinoma (HNSCC) is biologically heterogeneous, and many public-data gene signatures lack cross-platform replication and unbiased evaluation. Objective: We sought reproducible tumor–normal expression programs and tested the transportability of a derived seven-gene score. Methods: TCGA-HNSC RNA-sequencing defined differentially expressed genes (DEGs) between 520 tumors and 44 normal tissues using TMM normalization and voom–limma, with paired sensitivity analysis. Concordant genes were replicated in 22 GSE6631 matched pairs and analyzed for GO and KEGG enrichment. A seven-gene overall-survival score was developed in event-stratified TCGA training data (n=361), evaluated in held-out TCGA (n=156), repeated nested resampling, and examined in GSE65858 (n=253). ESTIMATE and marker scores characterized tumor-microenvironment features. Results: Among 5,657 TCGA and 168 GSE6631 DEGs, 151 replicated. Upregulated genes were enriched for extracellular-matrix organization, ECM–receptor interaction, integrin signaling, focal adhesion, and PI3K–Akt signaling. The score was associated with survival in training (HR per SD=1.68; C-index=0.642) but not held-out TCGA (HR=1.02; C-index=0.546) or unadjusted GSE65858 (HR=1.15; C-index=0.548). Median nested C-index was 0.564. HPV adjustment attenuated the GSE65858 association. The score correlated with CAF/fibroblast (ρ=0.269) and stromal scores (ρ=0.228). Conclusion: Replicated expression changes support an ECM–CAF program, but the seven-gene score did not generalize and is not a validated prognostic model.
Cardiovascular Risk Stratification in Pregnant Women with Gestational Diabetes: A Comparative Analysis of Predictive Models in Padang, Indonesia Cinthya Callathea; Vania Delma; Muhammad Rusli; Bjorka Alma; Rinna Azrida
Sriwijaya Journal of Internal Medicine Vol. 3 No. 1 (2025): Sriwijaya Journal of Internal Medicine
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjim.v2i2.177

Abstract

Introduction: Gestational diabetes mellitus (GDM) significantly increases the risk of both short-term and long-term cardiovascular disease (CVD) in women. Effective risk stratification during pregnancy is crucial for targeted interventions. This study aimed to compare the performance of established cardiovascular risk prediction models in a cohort of pregnant women with GDM in Padang, Indonesia. Methods: A prospective cohort study was conducted involving 350 pregnant women diagnosed with GDM at two major hospitals in Padang, Indonesia, between January 2022 and June 2023. Baseline demographic, clinical, and laboratory data were collected. Three established CVD risk prediction models – the Framingham Risk Score (FRS), the American College of Cardiology/American Heart Association (ACC/AHA) Pooled Cohort Equations (PCE), and a modified version of the PCE adapted for GDM (PCE-GDM) – were applied to calculate individual 10-year CVD risk scores. The primary outcome was the development of any major adverse cardiovascular event (MACE), defined as myocardial infarction, stroke, or cardiovascular death, or new-onset hypertension requiring medication, within one year postpartum. Model performance was assessed using discrimination (c-statistic) and calibration (Hosmer-Lemeshow goodness-of-fit test). Results: The mean age of participants was 32.4 ± 5.1 years. The prevalence of pre-existing hypertension was 8.6%, and the mean pre-pregnancy BMI was 28.5 ± 4.7 kg/m². During the one-year follow-up, 25 (7.1%) women experienced a MACE. The PCE-GDM model demonstrated the best discrimination (c-statistic = 0.82, 95% CI 0.76-0.88), followed by the PCE (c-statistic = 0.75, 95% CI 0.68-0.82), and the FRS (c-statistic = 0.68, 95% CI 0.60-0.76). The PCE-GDM also showed good calibration (χ² = 8.3, p = 0.41), while the FRS and PCE tended to underestimate risk (χ² = 18.5, p = 0.02 and χ² = 15.2, p = 0.06, respectively). Conclusion: The PCE-GDM model, specifically adapted for GDM, showed superior performance in predicting short-term cardiovascular risk compared to traditional models in this Indonesian cohort. These findings highlight the need for GDM-specific risk stratification tools to improve cardiovascular risk management in this vulnerable population.
Forensic DNA Phenotyping of Externally Visible Characteristics and Biogeographic Ancestry in Indonesian Populations: A Cross-Sectional Validation Study Rinna Azrida; Febria Suryani; Bjorka Alma; Sony Sanjaya; Khairiel Anwar
Sriwijaya Journal of Forensic and Medicolegal Vol. 2 No. 2 (2024): Sriwijaya Journal of Forensic and Medicolegal
Publisher : Phlox Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjfm.v2i2.366

Abstract

Background. Forensic DNA phenotyping (FDP) infers externally visible characteristics (EVCs) and biogeographic ancestry (BGA) from DNA when no reference profile is available. How well it performs in Indonesian populations has been little characterised. Objective. To evaluate how accurately a single nucleotide polymorphism (SNP) panel predicts skin, iris and hair colour and broad regional ancestry in Indonesian adults. Methods. In this cross-sectional study, 1,000 unrelated adults from eight named ethnic groups and a composite group were genotyped at 20 pigmentation SNPs and 26 ancestry-informative markers by multiplex single-base extension. Colour categories were predicted with a multinomial logistic model calibrated to HIrisPlex-S, and ancestry zones (Western, Central/other, Eastern) with a random forest. Accuracy was compared with the no-information rate, the accuracy of always predicting the commonest class. Results. Skin colour was predicted correctly in 89.2% of participants (no-information rate 45.0%), iris colour in 82.0% (88.0%) and hair colour in 80.0% (72.0%). The area under the curve was 0.96 for dark skin, 0.88 for brown irises and 0.87 for black hair; sensitivity for non-brown irises was 52.5%. Overall, 83.7% of participants were assigned to their expected ancestry zone (no-information rate 66.5%); sensitivity for the Eastern zone was 80.0% (95% CI 60.9–91.1; n = 25). Conclusion. In this cohort, skin colour prediction clearly exceeded the baseline, whereas iris and hair colour prediction improved little on it. The panel may support investigative leads, but independent test samples are needed before casework use.
Co-Authors Cinthya Callathea Febria Suryani Khairiel Anwar Muhammad Rusli Muhammad Yoshandi Patricia Wulandari Reisha Notonegoro Rinna Azrida Sony Sanjaya Vania Delma