Oral health is a critical yet often overlooked component of global health, with low- and middle-income countries and marginalized communities facing the greatest disparities in access and outcomes of oral health care. This narrative review synthesizes evidence from policy frameworks, program evaluations, and peer-reviewed literature from 2014 onward to explore effective strategies for bridging the global oral health gap. A narrative review was conducted for articles published between 2014 and 2025. Evidence was drawn from global initiatives, policy frameworks, and documented interventions addressing oral health, with a focus on sustainable and community-centered approaches. Global initiatives have advanced oral health policies, but top-down approaches alone are insufficient. Lasting improvement depends on community-centered, context-specific interventions, including evidence-based strategies like school programs, mid-level providers, and digital health tools. Integrating oral health into primary care and universal health coverage is essential, yet challenges such as funding gaps, service fragmentation, inequities, and weak political commitment remain. Public–private and intersectoral partnerships are key to overcoming these barriers and scaling effective solutions. This review emphasizes the need for robust monitoring systems, workforce development, and localized policy implementation guided by strong governance and advocacy. Future directions include leveraging artificial intelligence and tele-dentistry, addressing social determinants, and integrating oral health into broader health and development agendas. Achieving equitable global oral health requires a coordinated, evidence-driven, and community-engaged strategy supported by inclusive governance and sustained investment.
Alzheimer's disease (AD) is the most common cause of dementia and cognitive impairment; yet, there is currently no treatment. A buildup of Aβ, tau protein phosphorylation, oxidative stress, and inflammation in AD is pathogenic. The accumulation of amyloid-beta (Aβ) peptides in these neurocognitive areas is a significant characteristic of the disease. Therefore, inhibiting Aβ peptide aggregation has been proposed as the critical therapeutic approach for AD treatment. Resveratrol has been demonstrated in multiple studies to have a neuroprotective, anti-inflammatory, and antioxidant characteristic and the ability to minimize Aβ peptides aggregation and toxicity in the hippocampus of Alzheimer's patients, stimulating neurogenesis and inhibiting hippocampal degeneration. Furthermore, resveratrol's antioxidant effect promotes neuronal development by activating the silent information regulator-1 (SIRT1), which can protect against the detrimental effects of oxidative stress. Resveratrol-induced SIRT1 activation is becoming more crucial in developing novel therapeutic options for AD and other diseases that have neurodegenerative characteristics. This review highlighted a better knowledge of resveratrol's mechanism of action and its promising therapeutic efficacy in treating AD. We also highlighted the therapeutic potential of resveratrol as an AD therapeutic agent, which is effective against neurodegenerative disorders.
Despite numerous milestones in Alzheimer's disease (AD) research, the disease remains incurable, with a high prevalence and significant financial burdens. As a result, researchers are keen to look for new medications that can help manage or prevent the disease. The effects of long-term exposures to tirzepatide, a novel dual GIP/GLP-1 receptor agonist, on neurotoxicity and behavioral changes in the D-galactose/aluminium chloride (D-gal/AlCl3)-induced rats' AD-like pathological model were evaluated. Additionally, we investigated the underlying mechanism for tirzepatide's protective effects against neurotoxicity caused by D-gal/AlCl3. The present findings show that long-term administration of tirzepatide effectively reduced D-gal/AlCl3-induced AD-like neuronal and behavioral deficits and improved rats' learning, spatial memory, and locomotor activity. Tirzepatide restored the aberrant levels of acetylcholine, Aβ1-42, and pTau proteins, major AD hallmarks. Tirzepatide can alleviate behavioral impairments in D-gal/AlCl3-exposed rats by lowering acetylcholinesterase activation and inflammatory markers COX-2, IL-6, and TNF-α levels. This suggests that tirzepatide may alleviate inflammation, leading to restoring the level of acetylcholine and increasing the expression of the neurotrophin BDNF to reduce Aβ-induced neurodegeneration and apoptosis in rats exposed to D-gal/AlCl3. The neuroprotective effect of tirzepatide was also confirmed by lowering the histopathological alterations generated by D-gal/AlCl3 administration, highlighting the possibility of using tirzepatide as a therapeutic candidate to treat AD.
The pursuit of human-level artificial intelligence (AI) has significantly advanced the development of autonomous agents and Large Language Models (LLMs). LLMs are now widely utilized as decision-making agents for their ability to interpret instructions, manage sequential tasks, and adapt through feedback. This review examines recent developments in employing LLMs as autonomous agents and tool users and comprises seven research questions. We only used the papers published between 2023 and 2025 in conferences of the A* and A-ranked and Q1 journals. A structured analysis of the LLM agents’ architectural design principles, dividing their applications into single-agent and multi-agent systems, and strategies for integrating external tools is presented. In addition, the cognitive mechanisms of LLMs, including reasoning, planning, and memory, and the impact of prompting methods and fine-tuning procedures on agent performance are also investigated. Furthermore, we have evaluated current benchmarks and assessment protocols and provided an analysis of 68 publicly available datasets to assess the performance of LLM-based agents in various tasks. In conducting this review, we have identified critical findings on verifiable reasoning of LLMs, the capacity for self-improvement, and the personalization of LLM-based agents. Finally, we have discussed ten future research directions to overcome these gaps.
Tobacco use poses significant global public health risks, especially during infectious disease outbreaks. While tobacco use is typically examined as a predictor of COVID-19 outcomes, limited research has assessed how tobacco users differ in their preventive behaviors and treatment experiences, particularly in low- and middle-income countries. This study explored the associations between tobacco use and COVID-19 severity, treatment experiences, and preventive health behaviors in an urban LMIC context. Using multi-stage simple random sampling, a cross-sectional study was conducted among 659 COVID-19-positive patients who did and did not use tobacco products. Tobacco use was defined as current use of smoked or smokeless tobacco within the past 30 days prior to COVID-19 diagnosis. Data were collected through face-to-face interviews. Tobacco use was treated as a focal health behavior examined alongside sociodemographic, clinical, and COVID-19 preventive characteristics, including mask-wearing, respiratory hygiene, and avoiding large gatherings as co-occurring preventive health behaviors. Pearson’s Chi-square or Fisher’s exact test assessed the association between tobacco use and sociodemographic and clinical variables. Bivariate and multivariable logistic regression models estimated adjusted associations, adjusted logistic regression models were used to estimate associations between tobacco use, preventive behaviors, and treatment patterns. Patients requiring immediate ICU admission or invasive ventilation were excluded due to recruitment limitations. In our sample, 14
