Piaggio Aerospace (Italy)

A real-time structural health monitoring (SHM) system of an airplane composite wing with adjustable damage is reported, where testing under realistic flight conditions is carried out in the controllable and repeatable environment of an industrial wind tunnel. An FBG-based sensing array monitors a debonded region, whose compromised structural strength is regained by a set of lockable fasteners. Damage tunability is achieved by loosening some of or all these fasteners. Real-time analysis of the data collected involves Principal Component Analysis, followed by Hotelling’s T-squared and Q measures. With previously set criteria, real-time data collection and processing software can declare the structural health status as normal or abnormal. During testing, the system using the Q measure successfully identified the initiation of the damage and its extent, while the T-squared one returned limited outcomes.

This study explores the role of forensic toxicology in detecting the consumption of psychoactive substances and its impact on human organism and traffic safety, with a particular focus on alcohol use in Brazil. By analyzing statistical data, it aims to assess the effectiveness of Brazil’s “Lei Seca” (Dry Law), highlighting its positive influence in reducing accident rates while acknowledging ongoing challenges, including cultural normalization of drunk driving. The findings reinforce that toxicological studies are not only crucial for identifying legal violations but also serve as essential tools for quantitative and qualitative analyses of the relationship between alcohol consumption and driving risks. Overall, the study highlights the importance of integrating enforcement and education measures, which are essential for developing effective preventive polices to enhance public safety.

The growing availability of protein structural data from experimental methods and accurate predictive models provides the opportunity to investigate the molecular origins of rare diseases (RDs) reviewed in the Orpha.net database. In this study, we analyzed the topology of 5728 missense mutation sites involved in Mendelian RDs (MRDs), forming the basis of our structural bioinformatics investigation. Each mutation site was characterized by side-chain position within the overall 3D protein structure and side-chain orientation. Atom depth quantitation, achieved by using SADIC v2.0, allowed the classification of all the mutation sites listed in our database. Particular attention was given to mutations where smaller amino acids replaced bulky, outward-oriented residues in the outer structural layers. Our findings reveal that structural features that could lead to the formation of void spaces in the outer protein region are very frequent. Notably, we identified 722 cases where MRD-associated mutations could generate new surface pockets with the potential to accommodate pharmaceutical ligands. Molecular dynamics (MD) simulations further supported the prevalence of cryptic pocket formation in a subset of drug-binding protein candidates, underscoring their potential for structure-based drug discovery in RDs.

In 2023, the Italian healthcare system launched HCV screening targeting subjects born in 1968–1989. However, subjects > 50 yrs also need screening. In addition, existence of gender gaps in HCV diagnosis and treatment has been suggested. Our aim was to identify undiagnosed individuals outside the age groups to whom the screening is offered and to gather data about gender gaps. This is a prospective, opportunistic micro-elimination initiative based on a network between 24 Apulian pharmacies and our center. Between 01/07/2022 and 01/03/2024, subjects aged 55 to 85, accessing pharmacies were offered HCVOraQuick tests (F/M 1:1) and administered ad-hoc questionnaires. In total, 13,042 screening were carried out. Mean age was 64.9 (± 7.6), 51.1% females. Overall, 1.1% were anti-HCV positive: mean age 68.3 (± 10.3), 44.9% females. Seroprevalence was higher in males (p < 0.00001), elderly (p < 0.00001) and unknown transmission route (p = 0.0009). HCV-RNA was detectable in 67.4% of seropositive. They were 67.5 (± 10.7) yrs old, mainly males (55.1%). HCV-RNA prevalence was 0.8%, higher in elderly (p = 0.0003) and unknown transmission route (p = 0.0007). Overall, 90% were linked-to-treatment. Differences in patients profiles should be considered to guide policy and more inclusive treatment approaches. Gender differences in screening response and rates of active infections underscore the need for gender-targeted intervention.

The high biocompatibility and the key role of collagen in bone extracellular matrix make it useful for tissue engineering. However, the high demand, costs, and challenges of extracting good-quality collagen have led to the use of collagen derivatives and search for non-human alternatives. This study investigates fish and bovine collagen peptides (Collf and Collb, respectively) as sustainable sources for 3D-printed bone scaffolds by developing and characterizing peptide-incorporated alginate/hydroxyapatite-based bioinks. The chemical analysis revealed structural similarities between the peptides, while rheological tests showed a slightly higher viscosity of Collf-based inks, which improved shape fidelity during the printing process. Upon oscillating rheological tests, both the Collf and Collb-based ink formulations demonstrated a solid-like behavior at frequencies higher than 0.4 Hz, which is crucial for maintaining the printed structure integrity during extrusion. Although Collb-based inks exhibited better pore printability, Collf-based inks achieved superior resolution and geometry retention. Macro-porous structures printed from both inks showed good accuracy, with minimal shrinkage attributed to hydroxyapatite. Both the produced inks had a high gel fraction and swelling behavior, with Collb-based outperforming Collf-based inks. Finally, both ink formulations resulted to be cytocompatibile with human dermal fibroblasts. These findings position Collf- and Collb-based inks as promising alternatives for bone tissue scaffolds, offering a sustainable balance between performance and structural stability in 3D printing applications.

Green chemistry principles are pivotal in driving sustainable and innovative solutions to global health challenges. This study explores a hydroalcoholic extract from Castanea sativa (chestnut) burrs, an underutilized natural resource, as a potent source of antimicrobial compounds against Helicobacter pylori (H. pylori). The extract demonstrated significant bactericidal activity, synergizing effectively with clarithromycin and showing additive effects with metronidazole. Remarkably, combining the extract with clarithromycin and sub-inhibitory concentrations of pantoprazole reduced clarithromycin's Minimum Bactericidal Concentration (MBC) to just 1.56% of its original value. Mechanistic studies suggest that the extract's polyphenolic compounds compromise bacterial membrane integrity, enhancing antibiotic uptake, while pantoprazole disrupts bacterial ATPase activity. This research highlights the critical role of natural product extraction within the framework of green chemistry, offering a sustainable and environmentally friendly alternative to synthetic antimicrobials. By harnessing bioactive compounds from plant sources, this approach addresses the pressing issue of antibiotic resistance while promoting the responsible use of natural resources. The findings underscore the transformative potential of green chemistry in developing effective, eco-conscious antimicrobial therapies that align with global sustainability goals.

The sustainable utilization of biomass-derived bioactives addresses the growing demand for natural health products and supports sustainable development goals by reducing reliance on synthetic chemicals in healthcare. Cannabis sativa biomass, in particular, has emerged as a valuable resource within this context. This study focuses on the hydroethanolic extract of C. sativa leaves (CSE), which exhibited significant levels of phenolic compounds contributing to robust antioxidant activity. Evaluation using potassium ferricyanide, ABTS, and DPPH methods revealed potent radical scavenging activity comparable to the Trolox standard. UPLC-MS/MS profiling identified cannabinoids as the predominant secondary metabolites in CSE, with flavonoids also present in substantial quantities. This study investigated the anti-inflammatory potential of CSE on RAW 264.7 macrophages and IL-1β-stimulated C-20/A4 immortalized human chondrocytes, demonstrating protective effects without cytotoxic or mutagenic effects. Mechanistically, CSE reduced inflammation by inhibiting the MAPK and NF-κB signaling pathways. In silico approaches showed the ability of CSE’s main metabolites to bind and influence MAPK and NF-κB activity, confirming in vitro evidence. Incorporating C. sativa leaf extract into a hyaluronic acid-based formulation showed biotechnological promise for treating joint inflammation. Future research should aim to elucidate the molecular mechanisms underlying these effects and explore the potential of CSE-derived compounds in mitigating osteoarthritis progression. This approach highlights the significance of utilizing annually increasing biomass waste for sustainable bioactivity and environmental impact reduction.

Abstract Liquid Crystal Elastomers (LCEs) are responsive materials that undergo significant, reversible deformations when exposed to external stimulisuch as light, heat, and humidity. Light actuation, in particular, offers versatile control over LCE properties, enabling complex deformations. A notable phenomenon in LCEs is self-oscillation under constant illumination. Understanding the physics underlying this dynamic response, and especially the role of interactions with a surrounding fluid medium, is still crucial for optimizing the performance of LCEs. In this study, we have developed a multi-physics fluid-structure interaction model to explore the self-oscillation phenomenon of immersed LCE beams exposed to light. We consider a beam clamped at one end, originally vertical, and exposed to horizontal light rays of constant intensity focused near the fixed edge. Illumination causes the beam to bend towards the light due to a temperature gradient. As the free end of the beam surpasses the horizontal line through the clamp, self-shadowing induces cooling, initiating the self-oscillation phenomenon. The negative feedback resulting from self-shadowing injects energy into the system, with sustained self-oscillations in spite of the energy dissipation in the surrounding fluid. Our investigation involves parametric studies exploring the impact of beam length and light intensity on the amplitude, frequency, and mode of oscillation. Our findings indicate that the self-oscillation initiates above a certain critical light intensity, which is length-dependent. Also, shorter lengths induce oscillations in the beam with the first mode of vibration, while increasing the length changes the elasticity property of the beam and triggers the second mode. Additionally, applying higher light intensity may trigger composite complex modes, while the frequency of oscillation increases with the intensity of the light if the modeof oscillation remains constant.

Currently, one-third of global food production, accounting for 1.3 billions tons, goes wasted due to major humanitarian and environmental challenges. In such a scenario, the circular bioeconomy model stands as an innovative solution by promoting sustainable production, utilizing agri-food waste, and converting non-renewable products into valuable resources. Here, the circular bioeconomy concept was applied on a previously obtained chestnut burr extract (agri-food waste) composed of gallic acid, quinic acid, protocatechuic acid, brevifolin carboxylic acid, and ellagic acid to evaluate its antimicrobial activity against four bacterial opportunistic pathogens (Enterococcus faecalis, Staphylococcus aureus, Pseudomonas aeruginosa, and Escherichia coli). Our results evidenced a modest but measurable antibacterial activity against Enterococcus faecalis, with a minimum inhibitory concentration (MIC) of 64 μg/mL. In silico studies allowed for identifying the potential molecular target, supporting the underlying antibacterial activity of the active principle and providing useful molecular findings regarding their interaction. In this study, we show a robust and comprehensive in vitro and in silico pipeline aimed at the identification of novel antibacterial scaffolds taking advantage of agri-food waste.

This study applies an effective methodology based on Reinforcement Learning to a control system. Using the Pound–Drever–Hall locking scheme, we match the wavelength of a controlled laser to the length of a Fabry-Pérot cavity such that the cavity length is an exact integer multiple of the laser wavelength. Typically, long-term drift of the cavity length and laser wavelength exceeds the dynamic range of this control if only the laser’s piezoelectric transducer is actuated, so the same error signal also controls the temperature of the laser crystal. In this work, we instead implement this feedback control grounded on Q-Learning. Our system learns in real-time, eschewing reliance on historical data, and exhibits adaptability to system variations post-training. This adaptive quality ensures continuous updates to the learning agent. This innovative approach maintains lock for eight days on average.