Safety and Efficacy of Antihypertensive Deprescribing in Frail Geriatric Patients: A Narrative Review of Contemporary Clinical Trial Evidence

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Polypharmacy with antihypertensive agents in frail older adults presents a clinical dilemma: continuing therapy may preserve cardiovascular protection, yet it simultaneously increases the risk of orthostatic hypotension, falls, and drug-related adverse events. This narrative review synthesizes contemporary clinical evidence on the safety and efficacy of antihypertensive deprescribing (gradual withdrawal or dose reduction) in frail geriatric populations, particularly those residing in long-term care facilities. Literature searches were conducted in PubMed/MEDLINE, Cochrane Library, and Google Scholar (2011–2025).

Key findings include: the OPTIMISE randomized trial, which demonstrated that withdrawing one antihypertensive agent in patients aged ≥80 years was non-inferior to usual care for systolic blood pressure control over 12 weeks, with 66% sustaining the reduction. The DANTE trial found no cognitive benefit from discontinuation in older adults with mild cognitive impairment. Observational data from the PARTAGE study revealed that low systolic blood pressure combined with ≥2 antihypertensives was associated with increased two-year mortality in frail nursing home residents, supporting the rationale for deprescribing in this subgroup. A Cochrane systematic review (2020, updated 2023) encompassing six trials (1,073 participants) found no significant association between antihypertensive withdrawal and mortality, myocardial infarction, stroke, or hospitalization, though evidence on falls and quality of life remains limited.

Overall, current evidence supports selective, closely monitored deprescribing in frail geriatric patients. However, long-term outcomes and data specific to Asian populations, including Indonesia, remain scarce, underscoring the need for further research.

The Role of Crisis Communication Channels on Student Engagement During Lecturers’ Industrial Strikes: Evidence from the University of Nairobi

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Effective crisis communication is essential for sustaining stakeholder engagement during periods of institutional disruption such as lecturers’ industrial strikes. However, despite the recurring nature of industrial strikes in Kenyan public universities and the associated crisis communication shortcomings, limited empirical research has examined how crisis communication channels influence student engagement during such crises. This study sought to establish the influence of crisis communication channels on student engagement during lecturers’ industrial strikes at the University of Nairobi. The study was guided by the Situational Crisis Communication Theory (SCCT) and adopted an explanatory mixed-methods research design. Quantitative data were collected from 391 undergraduate students using structured questionnaires, while qualitative data were obtained through interviews with 12 key informants comprising student leaders, academic staff, and non-academic staff. Quantitative data were analysed using Statistical Package for the Social Sciences (SPSS), while qualitative data were analysed thematically. The findings established that crisis communication channels have a positive and statistically significant influence on student engagement. Communication channels emerged as a key determinant of students’ willingness to remain informed, participate in university processes, and maintain confidence in the institution during industrial strikes. The study concludes that effective crisis communication depends not merely on disseminating information but on providing communication channels that are timely, accessible, interactive, transparent, and responsive to students’ informational needs during industrial disputes. The study recommends that public universities strengthen student-centred communication by institutionalising intercative, two-way communication channels that keep students informed through the crisis cycle, maintain trust, and allow them to seek clarifications and relay feedback.

The Therapeutic Promise of Citrus limon: A Review of its In-Vitro Antioxidant and Anti-Inflammatory Effects

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Citrus plants, members of the Family Rutaceae have long been utilized in Traditional Indian medicine for the treatment of scurvy, Rheumatism , stomach ailments, diarrhea ,and  liver disorders. In addition to their therapeutic applications, Citrus plants are well known for their potent antioxidant properties, underscoring their significance in both Ethnomedicine and modern pharmacological research. Citrus essential oils are fascinating because they sit at the intersection of botany, chemistry and human health. the Rutaceae family, with its rich diversity has given us plants whose oils are aromatic and also pharmacologically active.  What makes citrus oils particularly valuables is their complex  Phytochemical composition-mainly Terpenes {like limonene, Aldehydes ,Alcohols, Esters, Flavonoids } these mixture of compounds are known for both the Organoleptic properties { Flavour, fragrance} and the bioactivities like Antibacterial, anticancer, anti-inflammatory, antioxidant properties.  The study has an objective to investigate the  composition of phytochemicals in citrus limon leaf powder and evaluate their potential pharmacological activities  majorly antioxidant  and anti-inflammatory activity by evaluating their chemical constituents and carrying out testing procedures in various applications, the review highlights the importance of citrus limon leaves as a sustainable source of natural bioactive compounds. Citrus Genus are the most cultivated fruit crops ,rich in carotenoids,  Flavonoids , and many other bioactive compounds of nutritional and nutraceutical values.

A Correlational Study of Peer Social Support and Student Engagement Among Junior High School Students

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Student engagement is widely regarded as a key determinant of successful learning, yet preliminary observations at a state Islamic junior high school (Madrasah Tsanawiyah) in South Sumatra indicated that students’ affective, behavioral, and cognitive engagement had not yet developed optimally. One contextual factor thought to contribute to this pattern is peer social support, given that friendship relationships become increasingly important during early adolescence for meeting the psychological needs of belonging and relatedness. This study aimed to empirically examine the relationship between peer social support and student engagement among seventh- and eighth-grade students. A quantitative correlational design was employed, involving 205 students drawn from a population of 500 through simple random sampling based on the Isaac and Michael table at a 95% confidence level. Data were collected using two five-point Likert scales: a Student Engagement Scale developed from the affective, behavioral, and cognitive engagement dimensions proposed by Lam et al. (2014), and a Peer Social Support Scale based on the appraisal, tangible, belonging, and self-esteem support dimensions proposed by Cohen and Wills (as cited in Schonfeld, 1991). Data were analyzed using simple linear regression with SPSS version 27. The results revealed a positive and highly significant relationship between peer social support and student engagement (r = 0.329; R Square = 0.108; p = 0.000), with peer support accounting for 10.8% of the variance in engagement. These findings indicate that greater peer social support is associated with higher student engagement, although most of the variance in engagement is explained by factors beyond peer support alone.

The Application of a Problem-Based Learning Model Using The Experimental Method on The Learning Outcomes and Scientific Reasoning Skills of Elementary School Students in Science Education

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Science learning in elementary schools requires students to understand concepts through observation, investigation, and reasoning processes. However, students’ learning outcomes and inference skills are still relatively low because learning activities are often dominated by teacher explanations and have not fully involved students in scientific inquiry activities. This study aims to analyze the effect of the Discovery Learning model assisted by Live Worksheet on students’ learning outcomes and inference skills in science learning on the topic of changes in states of matter.

This study employed a quantitative approach with a quasi-experimental method using a Nonequivalent Control Group Design. The research subjects were fourth-grade students of SD Negeri Antirogo 01 and SD Negeri Antirogo 04, Jember Regency, consisting of 62 students. The experimental class received treatment through Discovery Learning assisted by Live Worksheet, while the control class received conventional learning. Data collection techniques used learning outcome tests and inference skill instruments. Data analysis was performed through prerequisite tests and hypothesis testing using inferential statistics.

The results showed that the Discovery Learning model assisted by Live Worksheet had a significant effect on students’ learning outcomes and inference skills. The learning process encouraged students to actively observe, collect information, process data, verify findings, and formulate conclusions based on evidence. The integration of interactive digital worksheets strengthened students’ involvement and supported meaningful learning experiences. Therefore, Discovery Learning assisted by Live Worksheet can be an effective alternative strategy to improve cognitive achievement and scientific thinking skills among elementary school students.

Transition From Free Bags to Eco-Friendly Alternatives: Economics, Greenwashing and Consumer Behavior in Veracruz, Mexico

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The replacement of free plastic bags with alternatives marketed as eco-friendly has transformed the economic and environmental relationships between businesses and consumers; however, charging for bags does not necessarily imply an effective reduction in their consumption and can encourage greenwashing strategies when environmental claims lack verifiable support. The objective of this research was to analyze the economic and environmental implications of changing from free bags to paid bags with an eco-label in businesses in Veracruz–Boca del Río. A descriptive-exploratory study was conducted through direct observation in 16 businesses in the Veracruz–Boca del Río metropolitan area, Veracruz, Mexico, during January and February 2024. The type of material, price, dimensions, delivery conditions, and observed consumer behavior were recorded. The information was systematized through a qualitative-interpretive analysis. Significant differences were identified in prices and marketing methods, noting that conventional bags ranged in price from $1.00 to $17.50 MXN, while those labeled as eco-friendly or reusable ranged from $3.00 to $25.00 MXN. Replacing free bags with paid alternatives eliminated an operating cost and generated a new potential revenue stream. Furthermore, commercial practices based on environmental attributes were observed without sufficient information on reuse or environmental performance. It is concluded that the analyzed transition presents a relevant economic dimension and characteristics consistent with greenwashing; therefore, the environmental effectiveness of these policies should be evaluated using verifiable indicators of reduced consumption and increased bag reuse.

Generative AI Empowering Chinese Language Teaching in Vietnam: Current Applications, Empirical Investigations, and Practical Pathways

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The iterative upgrading of generative artificial intelligence (AI) has profoundly reshaped the pedagogical forms and developmental models of international Chinese language education. As a core country for Chinese learning in Southeast Asia, Vietnam witnesses robust and growing demands for Chinese language education, yet it has long confronted structural dilemmas including insufficient teacher supply, inadequate localized teaching resources, and difficulties in implementing personalized instruction. To explore the adaptability and practical value of AI technology in Vietnamese Chinese teaching, this study adopts a mixed‑method research design. Based on questionnaires, semi‑structured interviews, and an eight‑week classroom action research involving 221 teachers and learners from universities, primary and secondary schools, and training institutions in Hanoi and Ho Chi Minh City, this paper systematically examines the application scenarios, practical effects, and localized challenges of generative AI in local Chinese pedagogy. The results indicate that generative AI functions as an effective digital pedagogical scaffold, alleviating shortages of teaching resources and professional teachers, reducing learners’ foreign language anxiety, and improving the efficiency of basic linguistic training. Nevertheless, current applications are constrained by insufficient Vietnamese‑Chinese bilingual corpus adaptation, inadequate teachers’ AI pedagogical literacy, learners’ technological dependence, and prominent regional digital divides. Grounded on the Technology Acceptance Model (TAM) and sociocultural constructivist theory, this study constructs a teacher‑led and AI‑assisted collaborative teaching paradigm and proposes targeted optimization pathways from four dimensions: localized resource development, teacher competency cultivation, classroom procedure reconstruction, and learner media literacy enhancement. This research fills the empirical research gap regarding intelligent Chinese language education in Vietnam and provides practical implications for the digital transformation of Chinese language education in ASEAN countries.

Business Analytics Capability and Organizational Cyber Resilience: The Roles of Data-Driven Risk Detection and Cybersecurity Governance

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This study examines the relationships among business analytics capability, data driven risk detection, and organizational cyber resilience while evaluating the moderating influence of cybersecurity governance maturity. Drawing on Dynamic Capabilities Theory and Organizational Information Processing Theory, it conceptualizes organizational cyber resilience as the outcome of organizational capabilities that transform integrated analytical resources and cyber risk information into timely, coordinated, and adaptive responses. Cybersecurity governance maturity serves as a boundary condition that determines whether analytical insights can be translated into stronger resilience outcomes. A quantitative cross-sectional design gathered responses through a five point Likert scale questionnaire from 385 Vietnamese professionals knowledgeable about business analytics, cybersecurity, information technology, risk management, digital operations, organizational governance, or business continuity. IBM SPSS version 26 supported reliability assessment, exploratory factor analysis, and multiple linear regression, while Hayes’ Process Macro Model 1 examined the moderating effect. The findings show that business analytics capability (β = 0.573) and data driven risk detection (β = 0.638) significantly improve organizational cyber resilience. Data driven risk detection produces the stronger direct effect, emphasizing the importance of continuous monitoring, anomaly identification, and actionable cyber risk warnings. Cybersecurity governance maturity further strengthens the positive relationship between business analytics capability and organizational cyber resilience through a significant interaction coefficient of 0.407. The results demonstrate that analytical technologies alone cannot guarantee cyber resilience. Organizations must combine integrated analytical resources and timely risk detection with clear accountability, formal escalation procedures, structured oversight, continuous governance improvement, and sufficient authority to coordinate responses.

Enhancing E-Commerce Customer Satisfaction: A Multi-Method Approach Using Sentiment Analysis, IPA, and PGCV

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The advancement of information technology has enabled rapid expansion in e-commerce, establishing one of the platforms as a leading company in Indonesia. Subsequently, the authors name the e-commerce platform as XZ to preserve the anonymity of the research subject. This research intends to evaluate consumer sentiment regarding XZ’s e-service quality utilizing opinion mining based in the Support Vector Machine (SVM) method, while also determining enhancement priorities through Importance Performance Analysis (IPA) and Potential Gain in Customer Value (PGCV). The dataset comprises 50,000 data from the Google Play Store, categorized into positive and negative comments. The findings reveal that factors including the promptness in addressing customer complaints, the effectiveness of refund procedures, and XZ’s reliability in delivering promotional commitments, including shipping discount vouchers, are primary customer concerns. The IPA technique indicated that key service components should be emphasized to improve customer satisfaction, particularly attributes such as P4, P13, and P14. The PGCV methodology strengthened these results by determining the enhancement opportunities that would most significantly elevate service value, particularly attribute P4 associated with the promptness of addressing customer complaints. Also, P13 regarding the effectiveness of refund procedures for incorrectly shipped or defective products, and lastly P14 pertaining to XZ’s reliability in delivering on promotional commitments such as shipping discount vouchers. The results of this study have the potential to provide a benchmark for the businesses in formulating more efficient service enhancement plans and assist in advancing the field of quality management within the e-commerce industry.

A Comparative Analysis of Advanced Nuclear Fuel and structural Design in Advanced Fission Reactor

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The rapid transition toward low-carbon energy systems and increasing global energy demand have renewed interest in advanced nuclear fission technologies, particularly Generation IV reactors and Small Modular Reactors. This study aims to comparatively evaluate advanced nuclear fuels and structural materials based on their thermal, neutronic, mechanical, chemical, irradiation, and safety performance. An analytical review of scientific and technical literature from academic databases and authoritative nuclear organizations was conducted. The literature was qualitatively synthesized according to fuel type, structural material, reactor concept, coolant, and neutron spectrum. The findings indicate that uranium nitride, uranium silicide, and tri-structural isotropic fuels provide important advantages over conventional uranium dioxide fuel, including higher thermal conductivity, greater fuel density, improved high-temperature performance, and enhanced fission-product retention. Among structural materials, iron-chromium-aluminum alloys, silicon carbide composites, and high-entropy alloys demonstrate promising oxidation resistance, thermal stability, mechanical strength, and irradiation tolerance. However, their performance is strongly dependent on reactor type, neutron spectrum, coolant chemistry, operating temperature, and irradiation conditions. The review further shows that integrating advanced fuels and structural materials with passive safety systems and modular reactor architectures can improve safety, thermal efficiency, sustainability, and economic potential. Major challenges remain in irradiation qualification, corrosion, manufacturing, regulatory approval, economic feasibility, and spent-fuel management. Overall, coordinated development of advanced fuels and structural materials represents a promising pathway toward safer, more efficient, sustainable, and economically viable nuclear energy systems.