Integrating Artificial Intelligence (AI) into Precision Medicine (PM) is redefining healthcare, enabling personalized treatments tailored to individual patients based on their genetic code, environment, and lifestyle. AI’s ability to analyze vast and complex datasets, including genomics and medical records, facilitates the identification of hidden patterns and correlations, which are critical for developing personalized treatment plans. Unsupervised Learning (UL) is particularly valuable in PM as it can analyze unstructured and unlabeled data to uncover novel disease subtypes, biomarkers, and patient stratifications. By revealing patterns that are not explicitly labeled, unsupervised algorithms enable the discovery of new insights into disease mechanisms and patient variability, advancing our understanding of individual responses to treatment. However, the integration of AI into PM presents some challenges, including concerns about data privacy and the rigorous validation of AI models in clinical practice. Despite these challenges, AI holds immense potential to revolutionize PM, offering a more personalized, efficient, and effective approach to healthcare. Collaboration among AI developers and clinicians is essential to fully realize this potential and ensure ethical and reliable implementation in medical practice. This review will explore the latest emerging UL technologies in the biomedical field with a particular focus on PM applications and their impact on human health and well-being.

Lignin, the most abundant renewable aromatic biopolymer on Earth, is rapidly emerging as a powerful enabler of next-generation sustainable technologies. This review shifts the focus to the latest industrial breakthroughs that exploit lignin’s multifunctional properties across energy, agriculture, healthcare, and environmental sectors. Lignin-derived carbon materials are offering scalable, low-cost alternatives to critical raw materials in batteries and supercapacitors. In agriculture, lignin-based biostimulants and controlled-release fertilizers support resilient, low-impact food systems. Cosmetic and pharmaceutical industries are leveraging lignin’s antioxidant, UV-protective, and antimicrobial properties to create bio-based, clean-label products. In water purification, lignin-based adsorbents are enabling efficient and biodegradable solutions for persistent pollutants. These technological leaps are not merely incremental, they represent a paradigm shift toward a materials economy powered by renewable carbon. Backed by global sustainability roadmaps like the European Green Deal and China’s 14th Five-Year Plan, lignin is moving from industrial residue to strategic asset, driven by unprecedented investment and cross-sector collaboration. Breakthroughs in lignin upgrading, smart formulation, and application-driven design are dismantling long-standing barriers to scale, performance, and standardization. As showcased in this review, lignin is no longer just a promising biopolymer, it is a catalytic force accelerating the global transition toward circularity, climate resilience, and green industrial transformation. The future of sustainable innovation is lignin-enabled.

Computational methods have transformed target and drug discovery, significantly accelerating the identification of biological targets and lead compounds. Despite its limitations, in silico molecular docking represents a foundational tool. Molecular Dynamics (MD) simulations, employing accurate force fields, provide near-realistic insights into a compound’s behavior within a biological target. However, docking and MD predictions may be unreliable without precise knowledge of the target binding site. Through MD simulations, we investigated 100 co-crystal structures of biological targets complexed with active compounds, identifying key structural and energy dynamic features that govern target–ligand interactions. Our analysis provides a detailed quantitative description of these parameters, offering critical validation for improving the predictive reliability of docking and MD simulations. This work provides a robust framework for refining early-stage drug discovery and target identification.

Utilizing plant-based resources, particularly their by-products, aligns with sustainability principles and circular bioeconomy, contributing to environmental preservation. The therapeutic potential of plant extracts is garnering increasing interest, and this study aimed to demonstrate promising outcomes from an extract obtained from an underutilized plant waste. Chaetomorpha linum, an invasive macroalga found in the Orbetello Lagoon, thrives in eutrophic conditions, forming persistent mats covering approximately 400 hectares since 2005. The biomass of C. linum undergoes mechanical harvesting and is treated as waste, requiring significant human efforts and economic resources—A critical concern for municipalities. Despite posing challenges to local ecosystems, the study identified C. linum as a natural source of bioactive metabolites. Phytochemical characterization revealed lipids, amino acids, and other compounds with potential anti-inflammatory activity in C. linum extract. In vitro assays with LPS-stimulated RAW 264.7 and TNF-α/IFN-γ-stimulated HaCaT cells showed the extract inhibited reactive oxygen species (ROS), nitric oxide (NO), and prostaglandin E2 (PGE2) productions, and reduced inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) expressions via NF-κB nuclear translocation, in RAW 264.7 cells. It also reduced chemokines (TARC/CCL17, RANTES/CCL5, MCP-1/CCL2, and IL-8) and the cytokine IL-1β production in HaCaT cells, suggesting potential as a therapeutic candidate for chronic diseases like atopic dermatitis. Finally, in silico studies indicated palmitic acid as a significant contributor to the observed effect. This research not only uncovered the untapped potential of C. linum but also laid the foundation for its integration into the circular bioeconomy, promoting sustainable practices, and innovative applications across various industries.

Repurposing saffron (Crocus sativus) waste presents a sustainable strategy for generating high-value products within the bioeconomy framework. Typically, flower components are discarded after stigma harvest, resulting in significant waste—350 kg of tepals per kilogram of stigmas. This research employed a comprehensive approach, integrating bioactivity studies (in vitro and in silico) with Life Cycle Assessment (LCA) evaluations, to extract and assess bioactive compounds from C. sativus tepals sourced in Tuscany, Italy. Phytochemical characterization using UPLC-MS/MS revealed a high abundance and variety of flavonoids in the hydro-ethanolic extract (CST). The antioxidant capacity was validated through various assays, and the ability to mitigate H₂O₂-induced oxidative stress and enhance fermentation was demonstrated in Saccharomyces cerevisiae. This study reports that C. sativus tepals extract reduces oxidative stress and boosts ethanol fermentation in yeast, paving the way for applications in the food and biofuels sectors. Further validation in RAW 264.7 macrophages confirmed CST’s significant anti-inflammatory effects, indicating its potential for pharmaceutical, cosmeceutical, and nutraceutical applications. In silico studies identified potential targets involved in antioxidant and anti-inflammatory processes, shedding light on possible interaction mechanisms with Kaempferol 3-O-sophoroside (KOS-3), the predominant compound in the extract. The integration of LCA studies highlighted the environmental benefits of this approach. Overall, this research underscores the value of using waste-derived extracts through “green” methodologies, offering a model that may provide significant advantages for further evaluations compared to traditional methodologies and supporting the circular bioeconomy.

Sesquiterpenes such as leucodin and the labdane-type diterpene manool are natural compounds endowed with remarkably in vitro vasorelaxant and in vivo hypotensive activities. Given their structural similarity with the sesquiterpene lactone (+)-sclareolide, this molecule was selected as a scaffold to develop novel vasoactive agents. Functional, electrophysiology, and molecular dynamics studies were performed. The opening of the five-member lactone ring in the (+)-sclareolide provided a series of labdane-based small molecules, promoting a significant in vitro vasorelaxant effect. Electrophysiology data identified 7 as a Ca_V1.2 channel blocker and a K_Ca1.1 channel stimulator. These activities were also confirmed in the intact vascular tissue. The significant antagonism caused by the Ca_V1.2 channel agonist Bay K 8644 suggested that 7 might interact with the dihydropyridine binding site. Docking and molecular dynamic simulations provided the molecular basis of the Ca_V1.2 channel blockade and K_Ca1.1 channel stimulation produced by 7. Finally, 7 reduced coronary perfusion pressure and heart rate, while prolonging conduction and refractoriness of the atrioventricular node, likely because of its Ca²⁺ antagonism. Taken together, these data indicate that the labdane scaffold represents a valuable starting point for the development of new vasorelaxant agents endowed with negative chronotropic properties and targeting key pathways involved in the pathophysiology of hypertension and ischemic cardiomyopathy.