This paper arises from an ONRR project on “New technologies and methodologies for traceability, quality, safety, measurements and certifications to enhance the value and protect the typical traits in agrifood chains”. It has a first aim of performing an exhaustive review pertaining to the construction of indicators of the quality and safety of agrifood products, creating information systems dashboards of unidimensional and multidimensional indicators and applying such indicators, in the context of consumer choices and decisions of policy-makers and firms. Since it has been found that the literature offers no single proposal linking all such aspects, a second central and innovative aim is to propose an original step-by-step procedure for integrating information systems of statistical indicators for citizens, institutions and policy-makers with a specific focus on new technologies and methods for traceability, quality and safety of agrifood systems. The final output is a smart and user-friendly online database that is an absolute innovation on the topic.

Background: The aging evolution of Taurasi, an Aglianico-based DOCG wine from southern Italy, has been comprehensively characterized here for the first time. Known for its high levels of bioactive metabolites with potential health benefits, this variety was analyzed using an integrated analytical and computational approach to explore the evolution of its composition during bottle aging. Methods: The analytical framework encompassed physicochemical profiling (density, pH, °Brix) and targeted spectrophotometric analyses for polyphenols (Folin–Ciocâlteu), antioxidant capacity (DPPH, ABTS), and anthocyanins (TAC). The phenolic and volatile fractions were analyzed in detail qualitatively and quantitatively using HPLC-UV-DAD and HS-SPME-GC/MS, respectively. Results: The aging process was characterized by a profound phenolic reorganization, with a significant decrease in monomeric phenols and an accumulation of key phenolic acids and stilbenes. The net result of these opposing trends was an overall increase in antioxidant capacity, a significant decrease in total anthocyanins, and an aromatic shift from primary fruity esters to a complex tertiary bouquet. Additionally, machine learning techniques were employed to predict aging-related variations in antioxidant activity and chemical parameters, establishing links between compositional shifts and potential bioactivity. Conclusions: This study marks the first-ever investigation of Taurasi Aglianico wine aging, offering a novel multidisciplinary approach that provides comprehensive insights into the wine’s chemical evolution. The findings emphasize the potential of Taurasi Aglianico in both enological and health-related contexts, highlighting its unique aging dynamics and bioactive potential.

Chronic kidney disease (CKD) is a progressive condition associated with metabolic disturbances, systemic inflammation, and the accumulation of gut-derived uremic toxins. Increasing evidence highlights the role of gut microbiota dysbiosis in the progression of CKD through the gut–kidney axis. Consequently, microbiome-targeted nutritional strategies, including probiotics, prebiotics, and synbiotics, have emerged as promising complementary approaches to modulate intestinal microbial composition and metabolic functions. This review summarizes and critically evaluates the current clinical evidence regarding the use of these interventions in CKD patients. Clinical studies indicate that supplementation with probiotics, prebiotics, and synbiotic formulations may promote beneficial shifts in the composition of the gut microbiota, enhance saccharolytic fermentation, and increase the production of short-chain fatty acids (SCFAs). These changes have been associated with reduced circulating levels of gut-derived uremic toxins such as indoxyl sulfate and p-cresyl sulfate, as well as with the attenuation of systemic inflammation and oxidative stress. However, available trials remain heterogeneous in terms of study design, probiotic strains, prebiotic substrates, dosing regimens, and patient populations, and are frequently limited by small sample sizes and short intervention durations. As a result, evidence for improvements in renal function and long-term clinical outcomes remains inconclusive. While synbiotics may offer theoretical advantages by combining microbial supplementation with targeted substrates that support microbial growth and metabolic activity, current evidence does not consistently demonstrate superior clinical efficacy. Overall, these interventions often improve surrogate biomarkers, but their effects on renal function and hard clinical outcomes remain uncertain. Larger, longer-duration multicenter randomized controlled trials with standardized formulations are needed to establish their clinical utility and to better elucidate microbiota–host interactions in CKD. Advancing this field may support the development of personalized microbiome-based therapeutic strategies aimed at modulating the gut–kidney axis and ultimately improving clinical outcomes in CKD patients.

Optimizing surgical decisions in breast cancer is critical. Choosing between mastectomy and breast-conserving surgery (BCS) is complex due to heterogeneous pre-operative clinical factors. We developed BrCaM ( Br east Ca ncer M odel), a machine learning–based Clinical Prediction Model designed to analyze pre-operative surgical decision patterns. A dataset of 5100 patients (age range: 18–96 years) treated at a Breast Unit with standardized protocols was used. Surgeon-guided feature selection and an end-to-end machine learning pipeline were implemented. Multiple algorithms were evaluated; AdaBoost performed best using 10-fold cross-validation. BrCaM achieved an overall accuracy of 95% in distinguishing BCS from mastectomy. Feature selection identified clinically meaningful predictors that reflect established criteria influencing surgical decisions. In this retrospective setting, BrCaM captures real-world surgical decision patterns based on clinical factors. These findings support the consistency of current clinical practice and provide a foundation for future prospective validation as a clinical decision-support adjunct.