Citrawati Dyah Kencono Wungu

Genetic variations are involved in determining heart failure (HF) phenotypes. While variants within the BAG3 gene have been associated with HF in European populations, the impact of specific single nucleotide polymorphisms (SNPs) within the BAG3 gene in determining phenotypes of HF with preserved ejection fraction (HFpEF) in Southeast Asian populations is unknown. Therefore, in this study, we identified BAG3 SNPs and investigated their biological and clinical relevance in determining HFpEF phenotypes among an Indonesian HFpEF cohort. We conducted a study involving 36 patients with HFpEF and 30 healthy individuals. We detected the presence of rs196326 and rs2240777 SNPs in our cohort. However, the rs2234962 polymorphism, which has been associated with HF and cardiomyopathy in Western populations, was absent in our Indonesian cohort. We found that the rs196326 SNP was significantly associated with relative wall thickness (RWT), with patients carrying the CG genotype displayed significantly lower RWT. Additionally, the rs196326 CG/GG genotypes were correlated with higher serum N-terminal pro B-type natriuretic peptide (NT-proBNP) and lower Caspase-3 levels. Our study showed that the BAG3 rs196326 polymorphism was significantly associated with HFpEF phenotypes in the Indonesian population. This highlights the importance of identifying population-specific as genetic markers of disease severity.

Background: Ductal carcinoma in situ (DCIS) may be upstaged to invasive carcinoma after surgical excision. Predicting upstaging before surgery may help guide treatment planning. Artificial intelligence (AI)-based imaging has been investigated for this purpose, but its overall performance remains unclear. Objective: To evaluate the diagnostic accuracy of AI-based systems for predicting DCIS upstaging to invasive carcinoma. Materials and Methods: A systematic review and meta-analysis was conducted following PRISMA 2020 and registered in PROSPERO (CRD420261516994). PubMed, Scopus, EBSCOhost, ProQuest, and Web of Science were searched from inception to September 2026. Studies evaluating AI-based imaging models for DCIS upstaging were included. Pooled sensitivity and specificity were calculated using a bivariate random-effects model. Risk of bias was assessed using QUADAS-2. Results: Six studies involving 701 participants were included. Pooled sensitivity was 0.77 (95% CI, 0.57–0.89) and specificity was 0.78 (95% CI, 0.64–0.87), with substantial heterogeneity (I² = 84.0% and 90.6%, respectively). The pooled log diagnostic odds ratio (DOR) was 2.15 (95% CI, 1.64–2.65). The SROC analysis showed moderate overall discriminative performance. No significant differences were observed across imaging modalities, while AI model type significantly affected specificity but not sensitivity. Deeks’ funnel plot suggested possible publication bias (p = 0.046). Conclusion: AI-based imaging showed moderate accuracy for predicting DCIS upstaging. However, substantial heterogeneity and methodological limitations limit confidence in these findings. Further prospective studies with external validation are needed.

Background: Hypertension is a condition characterized by elevated blood pressure, posing a risk factor for various cardiovascular diseases (CVDs) with increasing prevalence worldwide. One risk factor for hypertension includes single nucleotide polymorphism (SNP) A1166C (rs5186) in angiotensin II type 1 receptor (AT1R) gene. Through a mechanism of structural changes and microRNA (miRNA) expression, A1166C SNP is associated with an increased risk of hypertension. Objective: This study aimed to explore the effect of AT1R A1166C SNP on blood pressure in hypertensive patients. Methods: The analytical cross-sectional observational study was carried out using primary data from 52 stored biological samples (peripheral blood mononuclear cells - PBMC) obtained from hypertensive patients. The variables measured were the presence of AT1R SNP and patients’ blood pressure. AT1R SNP was detected using polymerase chain reaction (PCR), followed by gene sequencing. Data analysis was conducted using T-test and Mann-Whitney tests for systolic blood pressure (SBP) and diastolic blood pressure (DBP). Result: There was no statistically significant difference in SBP and DBP among patients between AT1R A1166C SNP and wild type (WT) group (p > 0.05). However, a clinically meaningful difference in SBP was observed in AT1R A1166C SNP group (158±26) compared to WT group (144±22). Conclusion: AT1R A1166C SNP was not associated with increased blood pressure in this population. Keyword : A1166C SNP; Angiotensin II Type 1 Receptor; Hypertension; rs5186.

Intake of flavonoid-rich foods improves flow-mediated dilation in healthy adults, while effects on arterial stiffness and blood pressure remain inconsistent.

Background: Automated insulin delivery (AID) has revolutionized care for people with type 1 diabetes. However, its efficacy and safety in older adults (≥60 years) and high-risk populations, including those with impaired awareness of hypoglycemia, or cognitive or functional impairment, have not been systematically evaluated. Materials and methods: CENTRAL, PubMed, Web of Science, Scopus, and ClinicalTrials.gov from inception to March 10, 2026. Studies on automated insulin delivery in older and high-risk individuals with type 1 diabetes were included. The primary outcome was time in range (3.9-10.0 mmol/L [70-180 mg/dL]). Secondary outcomes included time above range, time below range, psychosocial well-being (Gold, Clarke, and Hypoglycemia Fear Survey score), and serious adverse events. Pooled effect sizes were estimated with random-effects models (PROSPERO, CRD420251273526). Results: Twenty-three studies involving 967 participants (11 randomized controlled trials, 3 single-arm, and 9 cohort studies) were included. Automated insulin delivery increased time in range by 11.38% (95% CI: 8.07-14.70; I2 = 70%; P < .0001; very low certainty; equivalent to 2.7 hours/day). Time in range improvement was observed during the day (8.70%; 95% CI 5.18-12.22%) and overnight (13.35%; 95% CI 11.07-15.62%). Favorable improvement was also comparable among commercial and noncommercial systems. Automated insulin delivery reduced the time spent in hyperglycemia (−7.89%) and hypoglycemia (−1.16%). No significant differences in psychosocial well-being were observed. Diabetic ketoacidosis and severe hypoglycemia events were not significant. Conclusion: Automated insulin delivery exhibits favorable glycemic outcomes and safety profiles in older and high-risk individuals with type 1 diabetes, suggesting potential benefits for populations traditionally considered vulnerable, although no significant improvements were observed in psychosocial outcomes.

This study evaluates the association between sleep duration, sleep quality, and metabolic markers among construction workers in Sidoarjo Regency, Indonesia. This cross-sectional study enrolled 47 construction workers via consecutive sampling. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI); blood glucose and uric acid were measured using EasyTouch GCU, while blood pressure was measured separately. Because most continuous variables were non-normally distributed, we assessed associations using Spearman's rank correlation. Sleep duration was negatively correlated with blood glucose (p=0.028) and positively correlated with uric acid (p=0.015). Supplementary quadratic regression showed no evidence of curvature in the sleep duration–uric acid relationship, and categorical sensitivity analyses (hyperuricemia-based) found consistent but non-significant directions in the Mann-Whitney U test (p=0.072) and logistic regression (p=0.174). Sleep quality was not significantly associated with any metabolic marker (all p>0.05). Sleep duration was consistently associated with metabolic markers in this sample. Sleep duration showed a significant positive correlation with uric acid that was not corroborated by categorical and regression-based sensitivity analyses, and should therefore warrant larger, multi-site samples in future studies.

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition arising from interactions between genetic susceptibility and environmental factors, including vitamin D status. This study investigated the associations of serum vitamin D levels and vitamin D receptor (VDR) gene variants with ASD in Indonesian children. This exploratory case–control study included 80 children aged 24–59 months from Surabaya, Indonesia, comprising 40 children with ASD and 40 typically developing controls. Serum 25-hydroxyvitamin D3 (25[OH]D3) concentrations were measured using an enzyme-linked immunosorbent assay, while the VDR region containing rs731236 was amplified by polymerase chain reaction and analyzed using bidirectional Sanger sequencing. Sequencing additionally identified rs11574113, rs7975232, and the rare missense variant rs1338135647 (p.Gly375Asp). Children with ASD had lower serum 25(OH)D3 concentrations than controls (median, 46.13 vs 69.27 ng/mL; p = 0.027), and the difference remained significant after adjustment for age and sex (adjusted median difference, −24.86 ng/mL; 95% confidence interval [CI], −42.42 to −7.30; p = 0.007). The rs1338135647 AG genotype was more frequent in children with ASD than in controls (22.5% vs 2.5%) and remained associated with ASD after adjustment for age and sex using Firth penalized logistic regression (odds ratio, 6.44; 95% CI, 1.21–67.64; p = 0.028). No significant associations were observed for the other VDR variants. Lower vitamin D levels and the rare rs1338135647 variant may independently co-occur with ASD in Indonesian children; however, these hypothesis-generating findings require replication and functional validation in larger independent cohorts.

BACKGROUND: Transforming growth factor β1 (TGF-β1) is a major mediator of myocardial fibrosis and cardiac remodeling in hypertension. TGFB1 (rs1800470) and MTHFR (rs1801133) are known for their roles in TGF-β1 regulation and cardiovascular remodeling, with MTHFR rs1801133 potentially influencing TGF-β1–mediated fibrosis through homocysteine metabolism. However, genetic determinants and relationship of these polymorphism with left ventricular (LV) structure remain unclear in the Indonesian population. Clarifying these associations may improve risk stratification and precision care. Therefore, this study was conducted to assess the associations of these polymorphisms and TGF-β1 levels with LV remodeling in essential hypertension.METHODS: Sixty-four adults subjects with essential hypertension were included in this cross-sectional study, and their blood samples were taken. Genotyping of the MTHFR and TGFB1 genes was performed using polymerase chain reaction (PCR), followed by sequencing. Serum TGF-β1 was measured by enzyme-linked immunosorbent assay (ELISA), while LV mass index (LVMI) and relative wall thickness (RWT) were assessed by echocardiography.RESULTS: TGFB1 rs1800470 was significantly associated with higher TGF-β1 levels (p=0.013). In the recessive model, TT homozygotes had higher TGF-β1 than CC+CT carriers (β=1.444; standardized β=0.353; p=0.004). TGF-β1 correlated with LDL cholesterol and diastolic blood pressure (r=0.302; p=0.015 and r=0.277; p=0.027). The TT genotype was associated with higher RWT under recessive and overdominant models (p=0.021 and p=0.028).CONCLUSION: TGFB1 rs1800470 is associated with circulating TGF-β1 concentrations in essential hypertension, suggesting a potential role in hypertensive cardiac remodeling.KEYWORDS: hypertension, TGFB1 polymorphism, TGF-β1, cardiac remodeling, left ventricular geometry, myocardial fibrosis.

Background: Elevated microvesicle (MV) levels are potential biomarkers of coronavirus disease 2019 (COVID-19). We compared different types of microvesicles (total microvesicles, TMVs), platelet-derived microvesicles (PMVs), endothelium-derived microvesicles (EMVs), and tissue factor-bearing microvesicles (TF-MVs). Objectives: We investigated the correlations between microvesicles and D-dimers, as well as between microvesicles and COVID-19 severity. Materials and methods: A systematic literature search was conducted in PubMed, Web of Science, Scopus, and ScienceDirect to identify relevant studies comparing microvesicle types between patients with COVID-19 and healthy controls. Pooled estimates of the standardized mean difference (SMD) for each MV type were calculated using RevMan 5.4, along with the corresponding 95% confidence intervals (CIs). Results: This meta-analysis included six studies comprising 183 COVID-19 patients and 135 healthy controls for quantitative analysis. Compared with controls, COVID-19 patients presented significantly higher levels of circulating TMVs, PMVs, EMVs, and TF-MVs (TMVs: SMD=4.27, 95% CI 2.18-6.36, p<0.0001; PMVs: SMD=2.07, 95% CI 0.99-3.15, p=0.0002; EMVs: SMD=1.20, 95% CI 0.56-1.84, p=0.0002; and TF-MVs: SMD=2.56, 95% CI 1.98-3.15, p<0.00001). D-dimer levels were correlated with MV levels (N=82, r=0.430, 95% CI 0.227-0.592, p<0.0001). In general, MVs were correlated with COVID-19 severity (N=168; r=0.942; 95% CI, 0.558-0.993; p=0.002). Conclusion: Patients with severe COVID-19 had elevated levels of TMVs, PMVs, EMVs, and TF-MVs. Therefore, MVs may contribute to the procoagulant effects associated with prognostic and severity biomarkers of COVID-19.