Skin aging reflects both intrinsic biological decline and extrinsic influences collectively known as the skin exposome, including ultraviolet (UV) radiation, air pollution, psychosocial stress, fatigue, sleep disruption, and suboptimal lifestyle behaviors. These factors contribute to cumulative molecular and structural damage, positioning the skin as both a visible marker of whole-body aging and a target for longevity strategies. This review examines the validity of an integrative “In and Out” approach, combining topical treatments, such as retinoids, peptides, antioxidants, and exosome-based formulations, with internal nutraceuticals including NAD+ precursors, collagen peptides, polyphenols, and microbiome modulators. By targeting key hallmarks of aging, oxidative stress, inflammation, and epigenetic changes, this dual-modality model has the potential to promote skin regeneration, enhance aesthetic and functional outcomes, and contribute to broader health span optimization. Emerging tools such as skin aging clocks, biomarker-driven personalization, and artificial intelligence (AI)-guided interventions further strengthen this paradigm, establishing a scientifically grounded, preventive, and personalized framework that redefines the role of dermatology in the context of longevity. Personalized strategies that integrate diagnostic tools, lifestyle coaching, and tracking technologies allow for adaptive, dynamic strategies both internally and externally.
Touch moderates how we interact with objects, others, and ourselves, where self-touch is particularly important in self-care, although fewer studies have investigated its perception, especially with age. Here, women aged 20-28 and 65-75 years rated how self-applied creams felt on the cheek and forearm, using sensory and emotional descriptors in the Touch Perception Task. Factor analyses uncovered higher tactile dimensions, including Texture, Moisture, Positive Affect, and Negative Affect. Sensory dimensions were more intense in the young group, whereas Positive Affect was stronger in the older group. We then used network and clustering analyses to map how the descriptors interacted. Young participants showed significantly higher connectivity between descriptors, whereas older participants displayed fewer connections, but many became mixed sensory-emotional pairings. Clustering analyses revealed further changes in the tactile groupings with age. We conclude that aging reshapes touch into an emotionally-rich experience, which impacts how interact with ourselves and others.
Concerns regarding the environmental risks of UV-filters used in suncare products have grown in recent years. Much of this concern has been driven by their use in products by consumers engaged in outdoor recreational activities, such as swimming, which can facilitate their direct emissions into aquatic systems. Uncertainties in estimating the amount of a UV-filter that might be directly emitted to water, however, represent a continuing challenge, and include the need to quantify the number of users of suncare products, the skin area covered, the concentration of the UV-filter in the product and the extent to which the UV-filter is 'washed-off'. This study aims to address this gap, which includes the development and application of screening-level exposure Models to Evaluate the direct Release of Cosmetic Ingredients (MERCI). The tier 1 and 2 MERCI models-SUNscreen and multi-SUNscreen-are described, with application to octocrylene, a well-studied UV-filter used in suncare products. Model results suggest that both tools provide reasonable estimates of environmental exposure. Specifically, the tier 1 SUNscreen model, estimates an environmental concentration of 422 ng·L-1 in freshwater and range from 191-428 ng·L-1 in marine water capturing differences between low-moderate tidal dilution rates, whereas sediment concentrations are estimated to be 206 ng·g-1 dw (freshwater) and 94-210 ng·g-1 dw (marine). The tier 2 multi-SUNscreen model, on the other hand, estimates freshwater concentrations of 81 ng·L-1 in water and 0.5 ng·g-1 dw in sediment, results that are observed to be within an order of magnitude of monitoring data. Overall, both models support a conservative, screening-level approach for estimating environmental exposure to UV-filters, and thus represent tools that can be readily utilized to support both risk assessment and research prioritization.
Biodegradability is a key parameter in the environmental assessment of chemical substances, requiring robust and reproducible methods to predict their fate. Among strategies aiming to improve the repeatability of biodegradation tests, the design of an artificial inoculum offers several advantages, such as ease of supply, control over its performance, and improved reproducibility. In this study, a panel of 44 microorganisms representative of activated sludge from domestic wastewater treatment plants and available from various strain collections was collected to: (1) evaluate its ability to assess the biodegradability of chemical substances, and (2) classify them into three categories: readily biodegradable, intrinsically biodegradable, and non-biodegradable to persistent. Each strain was individually tested against 30 chemicals with known biodegradability profiles (12 readily biodegradable, 10 inherently biodegradable, 8 non-biodegradable), yielding 3,960 independent 28-day oxygen consumption assays. Strain-level activity was used to derive a classification tool. This approach correctly identified 75
Analytical chemistry plays a central role in research and innovation, yet its environmental impacts remain insufficiently represented in sustainability assessments. Current score-based “greenness” indicators—defined as the compliance to the 12 green analytical chemistry principles—often overlook upstream and downstream processes, such as instrument manufacturing and data management. This study applies life cycle assessment (LCA) to characterize the environmental performance of four representative workflows in a cosmetic industry R I setting: an untargeted UPLC-PDA/HRMS analysis of natural extracts and three phenoxyethanol quantification methods (GC–MS, HPLC–UV, UPLC-UV). Inventories were structured to distinguish sample preparation, instrumental analysis, and data processing from supporting flows like consumables and energy. The results reveal distinct environmental hotspots for each protocol. The UPLC-PDA/HRMS workflow exhibited a climate change impact of 4.30 kg CO₂eq, driven by the amortization of the devices and the sample transport. In contrast, the GC–MS workflow (3.82 kg CO₂eq) was heavily influenced by dichloromethane production, while the HPLC–UV protocol reached 6.84 kg CO₂eq due to consumable-related flows and longer run times. These findings demonstrate that environmental burdens are highly workflow-specific and that commonly cited factors, such as solvent use, are not always the primary drivers. The study concludes that the normalization factors from the product environmental footprint (PEF) method are inadequate for analytical laboratory contexts and suggests that quantitative LCA provides a necessary complement to score-based metrics like the analytical greenness metric (AGREE) for supporting robust eco-design and corporate sustainability initiatives.
