Maintaining oral health is essential for preventing dental plaque, and toothpaste is a primary tool for supporting oral hygiene. Herbal-based toothpaste is considered a safer alternative due to its natural bioactive compounds, which have antimicrobial and antioxidant properties. This study was conducted to assess the antioxidant and antimicrobial activities of a toothpaste formulation containing royal jelly, black cumin, ginger, and cinnamon extracts. Antioxidant activity was assessed using DPPH, ABTS, H2O2, and NO scavenging assays, while antimicrobial activity was evaluated by the disk diffusion method against Porphyromonas gingivalis, Streptococcus mutans, and Candida albicans. The polyherbal toothpaste mix exhibited the highest scavenging activity in the DPPH (50.89%), ABTS (15.71%), NO (33.97%), and H2O2 (23.04%) assays, and showed significant antimicrobial activity against three representative oral pathogens at 100% concentration. The polyherbal toothpaste mix demonstrated significant antioxidant and antimicrobial properties, supporting its potential application as a natural dental care product.
This study examines the influence of audit committees, audit opinion, audit tenure, and auditor industry specialization on audit report lag in property and real estate companies listed on the Indonesia Stock Exchange during the 2023–2025 period. The study is motivated by the persistent delays in financial statement submissions, with the property and real estate sector consistently recording the highest number of late submissions over the past two years, despite regulatory mandates requiring audited financial statements to be published within 90 days. The sample consists of 201 firm-year observations obtained from 67 property and real estate companies selected using purposive sampling. Multiple linear regression analysis was employed to test the proposed hypotheses. The results indicate that audit opinion has a significant negative effect on audit report lag, suggesting that companies receiving unqualified opinions tend to have shorter audit completion times. Audit tenure also has a significant negative effect on audit report lag, indicating that longer auditor-client relationships facilitate more efficient audit execution through accumulated knowledge and familiarity. In contrast, audit committees and auditor industry specialization do not significantly influence audit report lag, implying that oversight roles focus on accuracy rather than speed, and that professional standards and company-specific complexity may outweigh the benefits of industry specialization. The model explains 17.1% of the variation in audit report lag. These findings suggest that maintaining high-quality financial reporting to obtain unqualified opinions and considering continuity with audit firms within regulatory limits are effective strategies for minimizing audit report lag in the property and real estate sector.
Intermittent fasting (IF) has gained increasing attention as a lifestyle intervention potentially influencing metabolic health and aging, partly through modulation of oxidative stress. This narrative review synthesizes current evidence on the effects of IF on oxidative pathways at molecular, cellular, and clinical levels. Mechanistically, IF induces metabolic switching from glucose to fatty acid and ketone utilization, activating interconnected nutrient-sensing pathways such as AMPK, SIRT1, and NRF2, as well as autophagy, which collectively contribute to improved mitochondrial function, enhanced antioxidant defenses, and reduced reactive oxygen species production. Preclinical studies consistently demonstrate that IF can reduce oxidative damage, upregulate endogenous antioxidant systems, and improve cellular stress resilience. However, much of this mechanistic evidence is derived from animal and experimental models, and its direct translation to humans remains uncertain. Human studies, including Ramadan cohorts and small interventional trials, report modest changes in commonly used oxidative stress biomarkers such as malondialdehyde (MDA) and F₂-isoprostanes. Nevertheless, these markers are non-specific, subject to methodological variability, and do not fully reflect tissue-level redox dynamics or clinically meaningful outcomes. Overall, human evidence remains limited, heterogeneous, and largely based on short-term studies, with a lack of long-term randomized controlled trials evaluating clinically relevant endpoints. While IF shows biologically plausible effects on oxidative stress, its clinical significance remains uncertain. Further well-designed, long-duration trials with standardized and comprehensive redox assessments are required to clarify its translational relevance.
Purpose Corporate sustainability development has become a concern for various parties around the world, including investors. In our study, we investigate the relationship between investor attention and sustainable performance in emerging economies.Design/methodology/approach Our study focuses on banking listing companies in ASEAN countries for the period 2015-2024 and applies ordinary least squares regression to test the models.Findings Our study shows that investor attention is positively associated with sustainability performance. In the view of the limited attention theory, investors focus on firms with better ESG implementation due to their limited time and energy. After addressing the endogeneity problems using the Generalized Method of Moment and lagged variable tests, the main results remain consistent and robust.Research limitations/implications We provide compelling evidence that investor attention serves as a powerful market-based mechanism for driving ESG improvements, suggesting that regulators and practitioners should proactively invest in and communicate sustainability initiatives to attract investors.Originality/value We highlight the importance of sustainability development for investors in bank industry in ASEAN.
In engineering education, Generative Artificial Intelligence (GenAI) might be misused to complete assessments with limited understanding. On courses that allow the use of GenAI, students might also forget to acknowledge its assistance. There is a need to identify such assistance. We present an automated detector with over-uniqueness and sample matching. GenAI-assisted submissions are identified based on their uniqueness and their similarity to a GenAI sample. Unique to our GenAI detector, it requires no training data and/or dedicated rules for each programming/scripting language. Further, the method can be integrated into any existing similarity detectors to identify plagiarism. The detector covers five similarity measurements, two similarity modes, and eight programming/scripting languages. Our evaluation of four data sets with thousands of submissions shows that our detector is effective (71
