Biological Profile of Ferulic Acid-Based Thiazolidin-4-One Derivatives: Toxicity, Inflammation, and Oxidative Stress Biomarkers.

India is undergoing accelerated population aging, with a substantial rise in the proportion of individuals aged over 65 years []. This demographic transition is accompanied by a rise in the prevalence of chronic non-communicable diseases (NCDs), posing a major threat to the health of the adult and geriatric population. Chronic diseases are estimated to cost the nation up to 4.3 trillion in terms of productivity and health care costs [,]. Among the spectrum of existing NCDs, dementia stands out as one of the most prevalent in older adults. Given its size and population diversity, India contributes significantly to this growing epidemic, with estimates of up to 7.5 million cases by 2040 [,]. The onset of dementia results from an interplay between genetic factors and environmental influences, including nutrition []. While an individual’s genetic predisposition is largely not amenable to modification, several modifiable risk factors, such as physical inactivity, diabetes mellitus, and elevated blood pressure, play important roles in its pathogenesis and can be addressed through changes in diet and lifestyle [,]. Mild cognitive impairment (MCI) represents a transitional state between normal cognitive ageing and dementia. It is characterised by impairments in cognitive domains such as language, visual perception, conceptual thinking, memory, and attention []. Recently, we reported higher micronutrient deficiencies in individuals with higher risk of dementia []. Given the widespread micronutrient deficiencies in India [,], and increasing dementia burden in the country, there is a critical need for early disease detection through the assessment of MCI []. Although MCI is not diagnostic of dementia, it is regarded as a reliable predictor of its future development, with studies estimating that 10–15% of individuals with MCI eventually progress to dementia [,]. Several tools have been developed to detect MCI, among which the Montreal Cognitive Assessment (MoCA) tool is one of the most widely used. MoCA evaluates multiple cognitive domains, including visuospatial ability, executive function, attention, concentration, language, memory, abstraction, and orientation. It demonstrates a high (90%) sensitivity for detecting MCI, attributable to its longer recall period and fewer learning trials compared with other cognitive screening tests [].