Narra J最新文献

At the onset of the coronavirus disease 2019 (COVID-19) pandemic in Indonesia, surveillance focused on finding and treating symptomatic cases. However, emerging evidence indicated that asymptomatic and pre-symptomatic individuals significantly contributed to viral transmission. This highlights the need for comprehensive surveillance to understand better the actual spread of SARS-CoV-2. Therefore, the aim of this study was to determine the seroprevalence of SARS-CoV-2 antibodies in the general population across Indonesia and identify risk factors associated with infection at the beginning of the pandemic. A cross-sectional survey was conducted across 17 provinces, 69 districts/cities, and 1,020 villages in Indonesia from December 22, 2020, to February 15, 2021. A multistage random sampling technique was employed. Serological testing using enzyme-linked immunosorbent assay (ELISA) was performed to detect anti-SARS-CoV-2. Complex sample analysis, adjusted for weights, was utilized to estimate the national seroprevalence and a generalized linear model with a binomial distribution was applied to identify risk factors. A total of 10,161 individuals were included in the final analysis, with the national seroprevalence being 14.8% (95% confidence interval (CI): 14.2-18.5). The prevalence was higher in females (16.8%; 95%CI: 12.5-22.3), individuals aged 46-59 years (18.6%; 95%CI: 14.2-24.0), and in urban areas (20.1%; 95%CI: 15.0-26.2). The highest prevalence was observed in North Maluku (35.6%; 95%CI: 29.3-42.5). Notably, 54.2% of seropositive individuals were asymptomatic, while 7.5% reported hypertension as a comorbidity. Factors associated with higher seroprevalence were being married (adjusted prevalence ratio (aPR): 1.47; 95%CI: 1.02-2.12), widow (aPR: 1.74; 95%CI: 1.01-3.00), and close contact with confirmed cases (aPR: 2.04; 95%CI: 1.52-2.73). This study revealed a COVID-19 prevalence significantly higher than official estimate in Indonesia, underscoring the need for improved surveillance system to more accurately track disease spread and to inform timely public health responses in the future.

The p53 signaling pathway plays a critical role in regulating the cell cycle, apoptosis, and senescence, making it a key target in cancer research. The aim of this study was to investigate the effects of an ethanol extract from the stem of Ziziphus nummularia on the proliferation and expression of genes involved in the p53 pathway in MCF-7 breast cancer cells. To achieve this, real-time quantitative PCR (RT-qPCR) was used to evaluate the mRNA expression of downstream genes linked to cell cycle and senescence, including CycE or CCNEl, RBLl, and E2F1. Molecular docking simulations using Molegro Virtual Docker (MVD) were also performed to assess the potential inhibitory activity of metabolite compounds from Z. nummularia stem against p53-regulating kinase (TP53RK). The results showed that the IC50 value of Z. nummularia stem ethanol extract against MCF-7 cells was 38.27 ± 0.72 μg/mL. The results also revealed a reduction in the expression of downstream genes linked to cell senescence and the cell cycle: CycE or CCNE1 (p = 0.011), RBL1 (p = 0.008), and E2F1 (p = 0.005), which was observed through RT-qPCR analysis of mRNA expression. This fact indicated that the inhibitory effects on proliferation by the ethanol extract of Z. nummularia stem might occur via pathways associated with cell senescence and cell cycle arrest. Molecular docking results of metabolite compounds from Z. nummularia stem suggested that squalene (Rerank score -112.70 kJ/mol), and nummularine B (Rerank score -110.68 kJ/mol) had potential as TP53RK inhibitors. These Rerank scores were smaller compared to the Rerank score of adenyl-imidodiphosphate (AMP-PNP), which was the native ligand of TP53RK, as confirmed by molecular dynamics analysis. These in silico results were confirmed by the decrease in p21 (CDKN1A) mRNA expression. In conclusion, the anti-proliferative effects of the ethanol extract from Z. nummularia stem on breast cancer cells occurred by affecting cell cycle-related genes and inhibiting apoptosis protection mediated by overexpression of p21 (CDKN1A) through p53 activity.

The rising incidence of multidrug-resistant (MDR) Acinetobacter baumannii infections underscores the urgent need for novel antimicrobial strategies. The aim of this study was to investigate the synergistic effects between a polyphenol-rich extract from Phyllanthus emblica fruit and tetracycline against MDR A. baumannii strains. The extraction process was optimized using the Box-Behnken design approach to maximize the total phenolic content (TPC) of the P. emblica extract. Key variables, including ethanol concentration, extraction time, and solid-to-liquid ratio (w/v), were determined through single-factor experiments. The antimicrobial activity of the extract, both alone and in combination with tetracycline, was evaluated against A. baumannii. Mechanistic studies focusing on bacterial lysis and efflux pump inhibition were conducted to assess the extract's effects and its combined potential with tetracycline. The Box-Behnken design successfully optimized the extraction conditions, yielding the highest TPC at 68.92% ethanol concentration, 1.85 days of extraction time, and a 1:9.58 w/v ratio. The predicted and experimentally verified TPC values of the extract were 129.19 and 130.76 ± 2.46 mg GAE/g samples, respectively, with no significant difference (p > 0.05). The extract contained several phenolic compounds identified using liquid chromatography-high-resolution mass spectrometry (LC-HRMS). It exhibited antimicrobial activity against MDR Acinetobacter baumannii, either alone or in combination with tetracycline. The combination demonstrated a synergistic effect against MDR A. baumannii, with a fractional inhibitory concentration index (FICI) of 0.37. Moreover, the combination showed superior bacteriolytic effects against MDR A. baumannii cells, as evidenced by increased release of nucleic acid components and membrane destabilization, compared to the extract or tetracycline alone (p < 0.0001 for all comparisons). Additionally, the combination significantly enhanced the efflux pump inhibition effect compared to the extract or tetracycline alone (p < 0.05 for both). These findings support the potential use of polyphenol-rich P. emblica extracts as adjuncts to conventional antibiotics in treating drug-resistant bacterial infections.

The escalating prevalence of diabetes represents a critical challenge to global health and quality of life. Indonesia, particularly the Sulawesi region, is home to a diverse array of endemic plants with potential as sources of novel antidiabetic compounds. However, traditional preclinical models for evaluating these candidates are limited by high costs and lengthy timelines. The aim of this study was to explore the antidiabetic potential of Cordia myxa and Syzygium malaccense extracts using Drosophila melanogaster as a novel, cost- effective and efficient in vivo model. Hyperglycemia was induced in D. melanogaster larvae through a high-sugar diet, and the plant extracts were incorporated into the larval diets at concentrations ranging from 0.3125% to 2.5%. Phenotypic parameters, including body size, body weight, crawling activity, and hemolymph glucose levels, were evaluated, and the expression of metabolism-related genes (dilp2, dilp5, and srl) was analyzed using RT-qPCR. This study found that C. myxa and S. malaccense extracts improved crawling activity and body size in hyperglycemic larvae. Notably, C. myxa extract significantly reduced hemolymph glucose levels (p < 0.01), increased body weight (p < 0.01), and upregulated the expression of metabolic genes such as dilp2 (p < 0.001), dilp5 (p < 0.001), and srl (p < 0.0001). In contrast, S. malaccense extract showed less pronounced effects, highlighting the efficacy of C. myxa extract in alleviating hyperglycemia and restoring metabolic homeostasis. The study highlights that C. myxa extract demonstrated promising antidiabetic properties in the Drosophila model, underscoring the utility of this model for early-stage antidiabetic drug screening and supporting further preclinical investigation into the therapeutic potential of C. myxa for managing hyperglycemia.

Interprofessional collaboration is crucial for addressing the complexity of health problems, requiring contributions from various professions to enhance healthcare quality, improve patient satisfaction, and achieve better clinical outcomes. The aim of this study was to develop and validate the physicians and pharmacists collaborative practice instrument, known as KOMPAK (Kolaborasi Medis Persepsi Apoteker dan Dokter/Medical Collaboration: Perceptions of Pharmacists and Physicians) for use in Indonesia. A cross-sectional study was conducted across the western, central, and eastern rigors of Indonesia, targeting physicians and pharmacists. The study included translation (forward and backward), cross-cultural adaptation (with 30 participants), and validation using confirmatory factor analysis (CFA) among 315 physicians and 315 pharmacists. The present study found no significant changes emerged during the translation and adaptation phases. In the validation phase, the CFA results for the physician instrument indicated a Comparative Fit Index (CFI) of 0.94 (>0.92), Tucker-Lewis Index (TLI) of 0.93 (>0.92), Root Mean Squared Error of Approximation (RMSEA) of 0.055 (<0.07), Standardized Root Mean Residual (SRMR) of 0.07 (<0.08), and Cronbach's Alpha reliability of 0.88. The pharmacist instrument yielded similar results with a CFI of 0.94 (>0.92), TLI of 0.93 (>0.92), RMSEA of 0.06 (<0.07), SRMR of 0.05 (<0.08), and Cronbach's Alpha reliability of 0.83. The final instrument consists of 24 items. In conclusion, the KOMPAK instrument demonstrated validity and reliability, supporting its use for measuring interprofessional collaboration between physicians and pharmacists in Indonesia.

Research related to the development of diagnostic biomarkers in lung adenocarcinoma in various countries is important. Research on microRNA as a biomarker in lung adenocarcinoma varies depending on the population, specimen, and technology used for profiling and validation. The aim of this study was to map and analyze bibliometric data of publications related to the topic of microRNA as a candidate biomarker in lung adenocarcinoma and to determine any potential research gaps. A total of 8,506 articles were collected from Crossref, Google Scholar, Semantic Scholar, PubMed, and Scopus databases using Harzing's Publish or Perish platform. A systematic search was conducted using four keywords: "profiling," "validating," "microRNA," and "lung adenocarcinoma," and synonyms of these keywords based on the MeSH on NCBI. The data extraction process followed the chart from PRISMA-P. The article's elimination was conducted using Mendeley Desktop and then was analyzed based on the authors' keywords using VOSviewer and Biblioshiny. A bibliometric analysis of 692 relevant articles identified four primary research clusters: (1) microRNA (19 keywords), which highlights its potential as a biomarker for early detection and diagnosis; (2) lung adenocarcinoma (18 keywords), reflecting advancements in lung cancer research; (3) liquid biopsy (19 keywords), emphasizing the growing interest in non-invasive diagnostic methods; and (4) bioinformatics (nine keywords), underscoring the role of computational approaches in transcriptomic analysis. As a primary topic, microRNAs have become a focal point of research for diagnosing lung cancer across various stages and as biomarkers for cancer cell proliferation, invasion, migration, and metastasis. Numerous studies have demonstrated the successful application of microRNAs in lung cancer diagnosis in the last decade, although the reported types of microRNAs are inconsistent. Therefore, further research on this topic should be continuously conducted, particularly to validate the types of microRNAs and the types of environments that influence them.

Diabetes mellitus (DM) requires constant self-management and self-efficiency, which affects the quality of life among patients. It is important to understand the complex interplay between these factors to improve the results of treatment. The aim of this study was to explore the relationship between self-management, self-efficacy, and quality of life among diabetes mellitus patients. A cross-sectional study of 363 diabetes patients from three public hospitals in Cao Lanh City, Vietnam, was conducted. Self-management, self-efficacy, and quality of life were assessed using the 35-item Diabetes Self-Management Instrument (DSMI), the 6-item Self-Efficacy for Managing Chronic Disease Scale (SECD6), and the 5-item European Quality of Life 5 Dimensions 5 Level Version (EQ-5D-5L), respectively. Network analysis was performed to visually describe the relationship between self-management (which includes five domains of self-integration, self-regulation, interaction with health professionals and other significant people, self-monitoring, and medication adherence), self-efficacy, and quality of life. The network analysis showed that self-monitoring had the highest centrality. Two subscales of self-management, adherence and self-integration, were directly and positively correlated with quality of life, while the interaction was directly and negatively correlated with quality of life. Self-efficacy was positively correlated with self-regulation and self-monitoring, while it was negatively correlated with adherence. A direct positive correlation was also found between self-efficacy and quality of life. In conclusion, these findings highlight the pivotal role of self-management and self-efficacy in enhancing quality of life. Future studies should focus on patient education interventions to enhance adherence and self-efficacy, ultimately improving the quality of life in people with diabetes.

Stunting remains a critical public health issue in East Nusa Tenggara (ENT), Indonesia, with prevalence rates among the highest in the country despite national efforts to reduce its occurrence. The aim of this study was to project the impact of the 2018-2024 National Strategy to Accelerate Stunting Prevention on children under five years old in ENT, using the Lives Saved Tool. A cross-sectional approach was employed, integrating data from various sources, including the 2020 Census of Indonesia, the Global Data Lab-Area Database, the Central Bureau of Statistics Republic Indonesia, the National Socioeconomic Survey, the 2017 Indonesia Demographic and Health Survey, the 2018 Basic Health Research, and the 2021 Indonesia Nutrition Status Survey. The analysis considered three scenarios: (1) a baseline scenario reflecting ENT's 2017 coverage, maintained through 2028; (2) a scenario assuming Indonesia achieves the Health Plan Action Stunting targets; and (3) a projection of stunting rates based on ENT-specific coverage. Under scenarios 1 and 2, the prevalence of stunting was projected to decrease from 40.04% in 2018 to 39.82% and 39.78%, respectively, by 2028, with scenario 3 reflecting a similar trend. The findings revealed a sharp increase in the number of stunting cases averted among children under five years old between 2017 and 2021, followed by a more gradual decline, culminating in the 2028 projections: 2,249 children (scenario 2), 2,130 children (scenario 3), and 1,966 children (scenario 1). Breastfeeding promotion emerged as the most impactful intervention, accounting for over half of the total stunting cases averted under both Indonesia-wide and ENT-specific coverage scenarios. This was followed by interventions such as multiple micronutrient supplementation and vitamin A supplementation. The study highlights that reducing the prevalence of stunting among children requires a comprehensive prioritization of intervention strategies. The implementation of breastfeeding promotion, combined with appropriate complementary feeding practices, is expected to contribute significantly to achieving the sustainable development goal targets.

The Global Registry of Acute Coronary Events (GRACE) score is acknowledged for its ability to predict in-hospital mortality among patients with acute coronary syndrome (ACS). However, intensive care physicians often employ general prognostic scores such as Acute Physiologic and Chronic Health Evaluation II (APACHE-II) and Simplified Acute Physiology Score II (SAPS-II) to predict the mortality of ACS patients. However, their predictive values are not well-determined in predicting mortality in ACS treated in the cardiovascular care unit (CVCU). The aim of this study was to evaluate the performance of APACHE-II and SAPS-II scores in comparison with GRACE scores in predicting the CVCU mortality and in-hospital mortality of ACS patients admitted to CVCU. A multicenter retrospective cohort study was conducted using data from a registry of patients admitted to 10 hospitals in Indonesia between August 2021 and July 2023. This study evaluated the APACHE-II, SAPS-II, and GRACE scores for patients with ACS upon admission to CVCU. The area under the curve (AUC) of the receiver operating characteristic (ROC) was utilized to assess the discriminative ability for predicting mortality. Among the 12,950 admitted patients, 9,040 were diagnosed with ACS, and 6,490 patients were included in the final analysis. All three scoring systems had relatively good discriminative ability to predict CVCU mortality with APACHE-II having better results (AUC: 0.771; sensitivity: 63.9%; specificity: 78.7%) compared to GRACE (AUC: 0.726; sensitivity: 61.7%; specificity: 73.2%) and SAPS-II (AUC: 0.655; sensitivity: 38.9%; specificity: 85.2%). To predict in-hospital mortality, APACHE-II had better results (AUC: 815; sensitivity: 68.7%; specificity: 80.4%) compared to GRACE (AUC: 0.769; sensitivity: 64.6%; specificity: 77.5%) and SAPS-II (AUC: 0.683; sensitivity: 41.8%; specificity: 86.2%). APACHE-II had the best single risk factor for CVCU mortality (odds ratio (OR): 1.198; 95% confidence interval (CI): 1.181-1.214) and in-hospital mortality (OR: 1.259; 95%CI: 1.240-1.279). In conclusion, APACHE-II, SAPS-II, and GRACE scores moderately predict CVCU and in-hospital mortalities, with the APACHE-II score exhibiting the highest predictive capability in ACS patients admitted to CVCU.

The rapid evolution of generative artificial intelligence (genAI) has ushered in a new era of digital medical consultations, with patients turning to AI-driven tools for guidance. The emergence of Chinese-developed genAI models such as DeepSeek-R1 and Qwen-2.5 presented a challenge to the dominance of OpenAI's ChatGPT. The aim of this study was to benchmark the performance of Chinese genAI models against ChatGPT-40 and to assess disparities in performance across English and Arabic. Following the METRICS checklist for genAI evaluation, Qwen-2.5, DeepSeek-R1, and ChatGPT-40 were assessed for completeness, accuracy, and relevance using the CLEAR tool in common patient ophthalmology queries. In English, Qwen-2.5 demonstrated the highest overall performance (CLEAR score: 4.43 ± 0.28), outperforming both DeepSeek-R1 (4.3 ± 0.43) and ChatGPT-40 (4.14 ± 0.41), with p = 0.002. A similar hierarchy emerged in Arabic, with Qwen-2.5 again leading (4.40 ± 0.29), followed by DeepSeek-R1 (4.20 ± 0.49) and ChatGPT-40 (4.14 ± 0.41), with p = 0.007. Each tested genAI model exhibited near-identical performance across the two languages, with ChatGPT-40 demonstrating the most balanced linguistic capabilities (p = 0.957), while Qwen-2.5 and DeepSeek-R1 showed a marginal superiority for English. An in-depth examination of genAI performance across key CLEAR components revealed that Qwen-2.5 consistently excelled in content completeness, factual accuracy, and relevance in both English and Arabic, setting a new benchmark for genAI in medical inquiries. Despite minor linguistic disparities, all three models exhibited robust multilingual capabilities, challenging the long-held assumption that genAI is inherently biased toward English. These findings highlight the evolving nature of AI-driven medical assistance, with Chinese genAI models being able to rival or even surpass ChatGPT-40 in ophthalmology-related queries.