Aging involves progressive changes in sensory perception, appetite regulation, and metabolic flexibility, which together affect dietary intake, nutrient adequacy, and health-related outcomes. Meanwhile, current wearable technologies allow continuous, minimally invasive monitoring of physiological and behavioral markers relevant to metabolic health, such as physical activity, sleep, heart rate variability, glycemic patterns, and so forth. However, digital nutrition approaches have largely focused on physiological signals while underutilizing the sensory dimensions of eating-taste, smell, texture, and hedonic response-that strongly drive dietary intake and adherence. This narrative review synthesizes evidence on the following: (1) age-related sensory changes and their nutritional consequences, (2) metabolic adaptation and markers of resilience in older adults, and (3) current and emerging wearable technologies applicable to nutritional personalization. Following this, we propose an integrative framework linking subjective (implicit) sensory perception and objective (explicit) wearable-derived physiological responses into adaptive feedback loops to support personalized dietary strategies for healthy aging. In this light, we discuss practical applications, technological and methodological challenges, ethical considerations, and research priorities to validate and implement sensory-physiological integrated models. Merging together sensory science and wearable monitoring has the potential to enhance adherence, preserve nutritional status, and bolster metabolic resilience in aging populations, moving nutrition from one-size-fits-all prescriptions toward dynamic, person-centered, sensory-aware interventions.

Wine represents one of the most complex food matrices from a sensory perspective, as its appreciation emerges from the interaction between chemical composition, perceptual mechanisms, and contextual influences. Contemporary research in oenology and sensory science increasingly recognizes wine evaluation as an integrated perceptual event shaped by cognition, memory, and affect, rather than a simple response to aroma or flavor cues. Live music is widely used in hospitality settings to enhance consumer experience; however, its specific influence on wine appreciation and emotional responses remains insufficiently explored, particularly in real-world contexts. This study investigates how two contrasting musical atmospheres—melancholic/relaxing and upbeat/motivational—modulate hedonic evaluations and emotional profiles during public wine tastings, compared with a no-music condition. Data were collected across five live tasting events (5 Wednesdays of Emotions) using structured questionnaires that included hedonic ratings and multidimensional emotional measures. Statistical analyses were conducted using non-parametric tests, meta-analytic p-value combination, and cumulative link mixed models for ordinal data. The presence of music significantly enhanced overall wine appreciation compared to the silent condition, although the magnitude and direction of the effect varied across individuals and musical styles. Upbeat/motivational music generally produced stronger and more consistent increases in liking than melancholic/relaxing music. Emotional responses—particularly positive surprise—emerged as key mediators of hedonic improvement and showed strong associations with overall liking. Preference profiling revealed distinct response patterns, indicating that auditory modulation of wine perception is not uniform across consumers. These findings support a crossmodal interpretation in which music shapes wine appreciation primarily through emotion-based and expectancy-related mechanisms rather than through direct sensory enhancement. By demonstrating these effects in ecologically valid tasting environments, the study highlights the role of auditory context as a meaningful component of multisensory wine experiences.

Background This Review integrates evidence from neuroscience, psychology, and clinical research to outline a multisensory, food-based neurosensory framework as a promising non-pharmacological approach to neurological rehabilitation. Moving beyond a traditional focus on flavour perception, we discuss how food-evoked multisensory stimulation, integrating visual, olfactory, gustatory, auditory, and somatosensory cues, can engage neural circuits within the orbitofrontal cortex, hippocampus, amygdala, and related limbic networks. Scope and approach We examine how carefully designed culinary experiences, including colour–aroma congruency, sensory-rich presentation, and culturally meaningful flavours, may promote experience-dependent neuroplastic changes in individuals with neurological vulnerability. Although current evidence derives primarily from preclinical models of environmental enrichment, mechanistic studies, and small-scale pilot interventions, further clinical trials are required to confirm this potential.This review integrates existing evidence, identified through a systematic search of PubMed, Scopus, and Web of Science, according to clearly defined inclusion criteria, into a coherent neurosensory framework applicable to brain health and disease. Key findings and conclusion While the evidence base remains largely preliminary and predominantly derived from narrative synthesis, pilot studies, and mechanistic reasoning rather than randomised controlled trials, the convergence of findings across neuroscience, sensory science, and clinical rehabilitation supports the plausibility of food-based multisensory enrichment as a complementary non-pharmacological approach. By reframing food-related experience as an active, structured form of sensory-cognitive engagement, this review identifies promising directions for translational research. However, clinical recommendations will require rigorous experimental validation, integration of cultural and personal factors into intervention design, development of standardised protocols, and disease-specific adaptations.

Ischemic heart disease (IHD) is a chronic and progressive condition characterized by reduced blood flow, mainly due to atherosclerosis. It is currently the leading cause of mortality among cardiovascular diseases. In recent years, per- and polyfluoroalkyl substances (PFAS), a group of ubiquitous and highly persistent environmental contaminants, have emerged as potential risk factors for IHD. PFAS are well-established endocrine disruptors and have been associated with hypercholesterolemia, hypertriglyceridemia, and insulin resistance. Despite the limited number of epidemiological studies and inconsistent findings from occupational settings, accumulating evidence suggests that elevated exposure to certain PFAS compounds may increase the risk of IHD and vascular dysfunction, including processes related to atherosclerosis development, sometimes with dose-response relationships and sex-specific patterns. Mechanistic evidence supports this link, indicating that PFAS exposure induces molecular and cellular alterations relevant to cardiovascular pathophysiology, including increased oxidative stress and vascular inflammation, and disruption of lipid metabolism. In addition, PFAS may affect epigenetic regulation, telomere length, and mitochondrial DNA copy number, which are emerging biomarkers associated with atherosclerosis and IHD and may indicate early cardiovascular vulnerability. Future research integrating innovative approaches and advanced analytical techniques may help address current knowledge gaps and clarify the mechanistic pathways linking PFAS exposure to clinical cardiovascular outcomes.

Ischemic heart disease (IHD), a chronic and progressive condition marked by restricted blood flow predominantly arising from atherosclerosis, is currently the leading cause of mortality within cardiovascular disease. In recent years, per and polyfluoroalkyl substances (PFAS), ubiquitous, highly persistent environmental contaminants and wellestablished endocrine disruptors, have emerged as potential risk factors for IHD, given their documented associations with hypercholesterolemia, hypertriglyceridemia, and insulin resistance. Despite the still limited number of epidemiological studies and the inconsistent findings from investigations conducted in occupational settings, there is growing evidence that elevated exposure to certain PFAS compounds may increase the risk of IHD and vascular dysfunction, in some cases displaying doseresponse relationships and sexspecific patterns. Mechanistic studies support these epidemiological signals. Dysregulation of peroxisome proliferator-activated receptors alpha promotes vascular inflammation and oxidative stress, thereby contributing to endothelial dysfunction and the establishment of a prothrombotic milieu. Epigenetic modifications, together with telomere shortening, and alterations in mitochondrial DNA copy number, provide additional pathways linking PFAS exposure to atherogenesis. Future opportunities offered by novel approaches and intelligent techniques might revolutionize the research in this field attempting to address the existing knowledge gaps and to clarify the mechanistic relationships linking PFAS exposures with clinical cardiovascular outcomes.

Despite decades of interventions targeting modifiable risk factors to reduce the burden of cardiovascular disease, ischemic heart disease (IHD) remains the leading cause of mortality and the second leading cause of disability-adjusted life-years worldwide. Growing evidence suggests that phthalates–plasticizers widely used in consumer products, cosmetics, and medical devices, and therefore ubiquitous across environmental media, may contribute to IHD development. Epidemiological studies have reported associations between phthalate exposure and multiple markers of atherosclerosis, the pathological hallmark of IHD, with or without mediation by traditional cardiovascular risk factors. Experimental models support these findings, showing that phthalates can induce oxidative stress, mitochondrial dysfunction, apoptosis, lipid accumulation, and epigenetic alterations, all of which promote endothelial damage and atherogenesis. In this review, we synthesize current epidemiological findings linking phthalate exposure to IHD, describe the main cellular and molecular mechanisms involved, and outline research gaps and regulatory perspectives. We also discuss how novel analytical frameworks—including artificial intelligence—may enhance the integration of environmental, clinical, and molecular data to advance risk prediction and prevention strategies.

Virtual reality (VR) offers immersive, controllable environments that can simulate real-life contexts for studying consumer behavior. Nutrition is a key determinant of healthy aging, yet older adults often exhibit inadequate dietary patterns. Understanding their food preferences in realistic settings is therefore essential. This study presents an integrated system combining VR home-like with wearable physiological sensors to explore food preferences in elderly individuals. Twelve participants aged 65–85 years interacted with a virtual kitchen using a head-mounted display and handheld controllers. The environment included a variety of healthy and unhealthy foods that participants could freely select and manipulate. Simultaneously, electrocardiogram (ECG) and galvanic skin response (GSR) were recorded using wearable sensors. Results indicated a preference for sugar foods and coffee in the groups of subjects. Physiological analysis revealed an increase in sympathetic activity during VR interaction for certain foods, suggesting heightened engagement with food stimuli. The proposed approach provides a controlled yet realistic framework for investigating dietary preferences and emotional responses, with potential applications in nutrition research, intervention design, and the promotion of healthy aging.

Congenital heart disease (CHD) represents the major cause of infant mortality related to congenital anomalies globally. The etiology of CHD is mostly multifactorial, with environmental determinants, including maternal exposure to ambient air pollutants, assumed to contribute to CHD development. While particulate matter (PM) is responsible for millions of premature deaths every year, overall ambient air pollutants (PM, nitrogen and sulfur dioxide, ozone, and carbon monoxide) are known to increase the risk of adverse pregnancy outcomes. In this literature review, we provide an overview regarding the updated evidence related to the association between maternal exposure to outdoor air pollutants and CHD occurrence, also exploring the underlying biological mechanisms from human and experimental studies. With the exception of PM, for which there is currently moderate evidence of its positive association with overall CHD risk following exposure during the periconception and throughout pregnancy, and for ozone which shows a signal of association with increased risk of pooled CHD and certain CHD subtypes in the periconceptional period, for the other pollutants, the data are inconsistent, and no conclusion can be drawn about their role in CHD onset. Future epidemiological cohort studies in countries with different degree of air pollution and experimental research on animal models are warranted to gain a comprehensive picture of the possible involvement of ambient air pollutants in CHD etiopathogenesis. While on the one hand this information could also be useful for timely intervention to reduce the risk of CHD, on the other hand, it is mandatory to scale up the use of technologies for pollutant monitoring, as well as the use of Artificial Intelligence for data analysis to identify the non-linear relationships that will eventually exist between environmental and clinical variables.

Background: Ischemic heart disease is a major global health problem with significant morbidity and mortality. Several cardiometabolic variables play a key role in the incidence of adverse cardiovascular outcomes. Objectives: The aim of the present study was to apply a machine learning approach to investigate factors that can predict acute coronary syndrome in patients with a previous episode. Methods: We recruited 652 patients, admitted to the hospital for acute coronary syndrome, eligible if undergoing immediate coronary revascularization procedures for ST-segment-elevation myocardial infarction or coronary revascularization procedures within 24 h. Results: Baseline pulse wave velocity appears to be the most predictive variable overall, followed by the occurrence of left ventricular hypertrophy and left ventricular end-diastolic diameters. We found that the potential of machine learning to predict life-threatening events is significant. Conclusions: Machine learning algorithms can be used to create models to identify patients at risk for acute myocardial infarction. However, great care must be taken with data quality and ethical use of these algorithms.

Type 2 diabetes (T2D) represents a public health problem globally, with the highest prevalence reported among older adults. While an interplay of various determinants including genetic, epigenetic, environmental factors and unhealthy lifestyle, particularly diet, has been established to contribute to T2D development, emerging evidence supports the role of interactions between nutrients or dietary patterns and genes in the pathogenesis of this metabolic disorder. The amount, and especially the type of carbohydrates, in particular, have been correlated with the risk of non-communicable chronic disease and mortality. This narrative review aims to discuss the updated data on the complex and not fully elucidated relationship between carbohydrate–gene interactions and incidence of T2D, identifying the most susceptible genes able to modulate the dual association between carbohydrate intake and risk of developing T2D. The identification of genetic polymorphisms in response to this macronutrient represents a potentially powerful target to estimate individual risk and prevent the development of T2D in the context of personalized medicine. The postulation around novel foods potentially tailored to minimize the risks of developing T2D will pave the way for a new era into food research in relation to the safeguarding of well-being status in patients affected by, or at risk for, T2D.

Inflammatory bowel disease (IBD) is a multifactorial and complex condition of the gastrointestinal tract shaped by host genetics, immune dysregulation, gut microbiota and environmental determinants, with a steadily rising global prevalence. Although the etiology of IBD remains incompletely understood, chronic inflammation accompanied by oxidative stress, immune dysregulation, and gut dysbiosis is widely recognized as a hallmark of the condition. Given the frequent occurrence of undernutrition in IBD patients, the role of vitamins and micronutrients in modulating disease activity has been recently explored. Selenium (Se) is universally recognized as an essential trace element due to its diverse physiological functions, including potent antioxidant activity, anti-inflammatory effects, immunomodulatory properties, and the ability to influence gut microbial composition and diversity. This comprehensive review examines current evidence on the relationship between Se status and IBD, integrating epidemiological and experimental findings, elucidating the underlying biological mechanisms, and introducing Se nanoparticles, a viable therapeutic option using Se in IBD management.

In the wine industry, one of the main challenges is represented by environmental sustainability, not only limited to the preservation of the surrounding environment but also relying on good practices to make the working environment safe and sustainable for the employees. In such a framework, Industry 5.0 comes into help, leveraging Information and Communication Technology to enable the design and development of safe, secure workplaces, minimizing risks for the employees for both accidents and fatalities, and long-term consequences of exposure to pollutants. The present work encompasses this topic, by proposing an IoT-based solution, relying on a commercial device, Airthings View 2960, to continuously monitor the pollutants present at the cellar level within the winemaking industry. The paper revolves around a proposal for Internet-of-Things-based architecture, allowing a seamless data exchange between the device and a control center remotely placed, with a description of the use case scenario and potential room for future improvements and refinements.

Nowadays, society is becoming increasingly committed to traveling by plane for work, tourism, and leisure in general. However, either due to internal, specific factors or to external determinants, like terrorism and climate changes, a growing number of travelers have experienced the so-called fear of flying, a persistent, irrational fear of flight-related situations for which a clear, efficacious therapy does not yet exist. Based on the usual interaction with the surrounding environment, conducted by means of the five human senses, and particularly on the neurophysiological pathway followed by the chemical senses, in this study, we revise the findings in the related literature on the topic, proposing an alternative way to alleviate the anxiety related to the fear of flight. This is based on chemosensory stimulation being applied directly during a flight and is possibly concerned with the consumption of meals, an usual activity performed onboard. After an introductory section aimed at understanding the problem, we present some studies related to chemosensory perception during the flight, highlighting the specificities of the scenarios, followed by a description of findings related to the meals proposed by flight companies in this context, and finally wrapping up the possible alternative approaches that could be conducted by such providers to alleviate the fear of flying condition through chemosensory stimulation vehiculated by meals, and enhance the quality of flight experience related to food consumption onboard.

From an evolutionary perspective, smell and taste are the oldest human senses. Despite this, other than chemical senses—particularly vision—are commonly regarded as the most powerful tools for interacting with our environment. Within such a frame, it has become a common belief that blind individuals, especially those who are congenitally blind, develop a compensatory sensory pattern, enhancing the power of their sense of smell. However, the literature results are unclear, mainly due to the heterogeneity of the study population and of the investigation methods. Emotional reactions to olfactory stimuli in blind individuals remain underexplored, primarily due to challenges in delivering stimuli in a standardized and unbiased manner suitable for quantitative assessment. In such a framework, the present pilot study sought to indirectly discover the emotional responses of blind individuals to a specific class of sensory stimuli through the application of wearable sensors for capturing electrocardiographic (ECG) signals and galvanic skin response (GSR). Tonic GSR varied in blind individuals (p < 0.001), but not in controls. Notably, variations were observed between Baseline and Odor 1 (p = 0.002), Odors 1 and 2 (p = 0.003), Odors 2 and 3 (p = 0.003), and on the GSR phasic peak between Baseline and Odor 1 (p = 0.001). No differences were observed for ECG; however, blind individuals’ heart rate correlated with reported pleasantness (r = 0.436, p = 0.005). In light of the different patterns retrieved across stimulus responses, particularly in the GSR signal features, the comparison with a group of non-visually impaired peers shed light on the peculiarities in the psychophysiological responses of blind individuals, with potential use for tailored treatments for the improvement of well-being or, in some cases, for practical applications fostering social inclusion for affected subjects.

Wine is a cultural product that can evoke strong emotions. Understanding how these emotions shape consumer preferences and influence purchasing behavior has become an increasingly relevant focus in sensory and consumer research. However, the complexity of emotions makes them difficult to measure accurately, and a comprehensive understanding of emotional reaction to sensory stimuli, particularly in the context of wine tasting, remains limited. This study aims to assess the emotional impact of tasting red wines through a multidisciplinary framework. This approach integrates sensory analysis by trained panelists, explicit emotion measurements, and chemical analysis of the wines. The study focused on various red wines, characterized by high polyphenol content, rich texture, distinctive mouthfeel, and aging potential. The findings revealed a clear correlation between the emotional responses and the sensory attributes, both quantitative and hedonic, identified through traditional sensory analysis. Overall, assessors showed a preference for the international commercial style of full-bodied wines; however, further studies are required, taking into account different wine typologies and integrating chemical, sensory and emotional analysis methods. Moreover, applying this multidisciplinary approach in consumer studies, including those involving individuals with limited wine expertise, would be essential for validating the applicability of these initial findings.

Recent scientific evidence highlight the negative effects that air pollution and climate change have on human health. In the present review contribution, it will be shown how by means of Artificial Intelligence it is possible to correlate climate change, air pollution and chronic inflammatory diseases through cause-effect relationships. From the present study it clearly emerges that the implementation of machine learning algorithms, together with the development of specific models, may constitute a very powerful tool in early diagnosis, monitoring and treatment of chronic inflammatory disease and, hence, in assisting governments in adopting the best practices for pollutants reduction strategies.

The proliferation of consumer-grade wearable devices has revolutionized personal health monitoring,enabling real-time tracking of biometric signals including heart rate,physical activity,and stress,with a minimum obtrusiveness for the end-users.However,despite their widespread adoption,questions remain regarding the reliability and agreement of measurements across different devices.In this study,we conduct a quantitative validation of biometric data collected simultaneously from two commercially available wearable devices,the first one being a wearable ECG sensor attached to a chest strap,previously validated against gold standard holter,and the second one represented by a smartband,focusing on their consistency and measurement bias.Using a dataset acquired during a structured session of sensory analysis,comprising paired measurements from both devices on the same population and at the same time points,we apply multiple agreement metrics including Pearson’s correlation coefficient,Lin’s concordance correlation coefficient (CCC),Bland-Altman analysis,and Deming regression.Results show good agreement between the two methods $(C C C=0.79)$,nevertheless with constant bias and a slight heart rate overestimation by the smartband.This work provides practical insights into the use of consumer wearables for clinical and research purposes,highlighting the importance of rigorous data validation in the digital health ecosystem.

Spices and aromatic herbs are important components of everyday nutrition in several countries and cultures, thanks to their capability to enhance the flavor of many dishes and convey significant emotional contributions by themselves. Indeed, spices as well as aromatic herbs are to be considered not only for their important values of antimicrobial agents or flavor enhancers everybody knows, but also, thanks to their olfactory and gustatory spectrum, as drivers to stimulate the consumers’ memories and, in a stronger way, emotions. Considering these unique characteristics, spices and aromatic herbs have caught the attention of consumer scientists and experts in sensory analysis for their evaluation using semi-quantitative approaches, with interesting evidence. In this pilot study as a first step, each studied botanical, belonging to Piperaceae or aromatic herbs, has been subjected to headspace solid phase micro-extraction (HS-SPME) coupled with gas-chromatography mass spectrometry (GC-MS) analysis to assess their spontaneous volatile emission, representing the complex chemical pattern, which encounters the consumers’ olfactory perception. Furthermore, the present investigation, performed on 12 individuals, outlines the administration of a pilot study, merging the typical sensory analysis with emotional data collection and the innovative contribution related to the study around the Autonomic and Central Nervous System activation in consumers, performed using wearable technologies and related signal processing. The results obtained by our study, beyond demonstrating the feasibility of the approach, confirmed, both in terms of emotional responses and biomedical signals, the significant emotional potential of spices and aromatic herbs, most of which featuring an overall positive valence, yet with inter-subjects’ variations. Future investigations should aim to increase the number of volunteers evaluated with such an approach to draw more stable conclusions and attempting a customization of product preferences based on both implicit and explicit sensory responses.

In the last years, Virtual Reality (VR) has become a valuable tool to explore foods' preferences in a controlled and measurable environment. In addition, the integration with physiological signals can allow to measure the emotional response to the foods with which the subject interacts. Thus, the purpose of this study is to present a system that integrates a virtual environment, presented with a headset, with wearables sensors for measuring electrocardiogram (ECG) and galvanic skin response (GSR). The virtual environment resembles a kitchen, enabling the subject to interact with a comfortable scenario. Different foods were placed on the virtual table to allow the user freely exploring them. Physiological signals are continuously monitored during the interaction. The analysis of the data allowed to quantify how many times and how long the subject interacts with each food. Preliminarily, an increase of the arousal for certain foods was detected. The data collected with this system could allow to explore food preferences in particular in elderly subjects.

Cardiovascular diseases are currently the major causes of death globally. Among the strategies to prevent cardiovascular issues, the automated classification of heart sound abnormalities is an efficient way to detect early signs of cardiac conditions leading to heart failure or other, even asymptomatic, complications, quite effective for timely interventions. Despite the significant improvements in this field, there are still limitations due to the lack of solutions, available data-sets and poor (mainly binary - normal vs abnormal) classification models and algorithms. This paper presents a Medical Cyber-Physical System (MCPS) for the automatic classification of heart valve diseases onsite, in a timely manner. The proposed MCPS, indeed, can be deployed into personal and mobile devices, addressing the limitations of existing solutions for patients, healthcare practitioners, and researchers, through an efficient and easy accessible tool. It combines different neural network models trained on a new Italian dataset of 132 adult patients covering 9 heart sound categories (1 normal and 8 abnormal), also validated against two main open-access (Physionet/CinC Challenge 2016 and Korean) datasets. The overall MCPS performance (time, processing and energy resource utilization) and the high accuracy of the models (up to 98%) demonstrated the feasibility of the proposed solution, even with few data. The dataset supporting the findings of this paper is available upon request to the authors.