Torino e-district

ABSTRACT Background Evolocumab promotes coronary plaque regression in patients with coronary artery disease, but little is known regarding carotid plaques (CP). This study aimed to evaluate the impact of evolocumab on top of lipid-lowering therapy (ELLT) on carotid morphological stabilization (MS) and plaque regression (PR) compared to lipid-lowering therapy (LLT) alone. Methods Asymptomatic patients with internal carotid stenosis≥50% and LDL-C≥100 mg/dL were randomized to ELLT or LLT and monitored by serial duplex ultrasound. The primary endpoint was a composite of 6-month-MS (i.e., switch from morphologic types I-II to III-IV) and/or 12-month-PR (i.e., reduction of carotid stenosis by at least 5% compared to baseline). The secondary endpoint was LDL-C change at 12 months. Major adverse vascular events (MAVE, i.e., cardiac death, stroke, myocardial infarction, carotid or coronary or peripheral revascularization) were recorded. Results A total of 170 patients were randomized. Mean carotid stenosis was 57%. At 6 months, MS occurred in the ELLT group (10.3%) only (p=0.29). At 12 months, PR was numerically more frequent in the ELLT group, without reaching statistical significance (43% versus 35.1%, p=0.42). The primary endpoint was met in 44.3% versus 35.1% (p=0.26). As compared to baseline, 6 and 12-month shifts from low to high-risk types were significantly higher in the LLT group (p=0.03). The 12-month LDL-C percentage reduction was -73.5% with ELLT, and -48.3% with LLT (p=0.0001). At 1 year, MAVE were significantly more frequent with LLT (14.6% versus 2.4%, p=0.005), and the absence of evolocumab was the only predictor (OR 7, p=0.014). Conclusions In patients with CP≥50% and LDL-C≥100 mg/dL, ELLT compared to LLT was associated with numerically but not statistically higher 6-month MS and/or 12-month PR. In the LLT group, 6- and 12-month changes from low to high-risk types, LDL-C, and MAVE were significantly higher. According to these results, evolocumab should be considered standard treatment for patients with CP≥50%. The study was registered at www.clinicaltrials.gov ( NCT04730973 ) and Eudract (2020-005663-31). SHORT ABSTRACT Patients with carotid stenosis≥50% and LDL-C≥100 mg/dL were randomized to evolocumab on top of optimal lipid-lowering therapy (ELLT) or optimal lipid-lowering therapy (LLT) alone to assess the impact of ELLT on carotid plaque morphological stabilization (MS) and plaque regression (PR). At 6 and 12 months, MS and PR occurred in both groups, but were numerically higher in the ELLT group, without reaching statistical significance. In the LLT group, 6- and 12-month changes from low to high-risk types were significantly higher, and the rate of adverse vascular events was sevenfold higher. Evolocumab might become the standard treatment for patients with carotid artery stenosis ≥50%. CLINICAL PERSPECTIVE What is new? The CARUSO is the largest randomized trial evaluating the impact of evolocumab on top of lipid-lowering therapy (ELLT) on carotid morphological stabilization (MS) and plaque regression (PR) monitored by serial duplex ultrasound. The primary endpoint was a composite of 6-month-MS (i.e., switch from morphologic types I-II to III-IV) and/or 12-month-PR (i.e., reduction of carotid stenosis by at least 5% compared to baseline) and was numerically higher in the ELLT group compared to lipid-lowering therapy (LLT) alone, without reaching statistical significance. The 1-year rate of major adverse vascular events (MAVE) was sevenfold higher in the LLT group. What are the clinical implications? Carotid plaque morphology is a dynamic event, and 6 and 12-month shifts from low to high-risk morphological types were significantly higher in the LLT group, thus suggesting that evolocumab added to LLT may prevent morphological deterioration. The absence of evolocumab was the only independent predictor of MAVE; according to our results, ELLT might become the standard treatment for patients with carotid plaques ≥50% and LDL-C not at target. Future larger studies are warranted to validate our findings, assess long-term adherence to therapy, and identify subgroups with higher probability of achieving MS and PR.

This work presents a systematic methodology for the preliminary design and optimization of electromechanical actuators, aimed at minimizing overall mass and rotational inertia while satisfying torque and speed requirements. The proposed approach integrates dimensionless scaling relationships, derived and corrected from catalog data, with a genetic algorithm that performs multi-parameter optimization across different actuator architectures. The algorithm enables the exploration of non-linear and multi-modal design spaces, allowing the identification of balanced solutions between mechanical efficiency and dynamic performance, employing custom functions for individual generation, constraint handling, and compatibility verification to ensure feasible and consistent architecture designs throughout the optimization process. A case study on the steering system of an aircraft nose landing gear illustrates the method’s ability to define optimal design parameters in real mechanical systems. Linear and non-linear dynamic analyses confirmed the compliance of the optimized design with control and stability requirements. The study demonstrates how the developed custom constrained genetic optimization approach can effectively support the early design phase, reducing the computational effort required in further stages and improving the overall consistency of electromechanical actuator development.

Digital twins (DTs) are increasingly adopted to enhance the monitoring, management, and planning of urban infrastructure. While DT development for buildings is well established, applications to urban road networks remain limited, particularly in integrating heterogeneous geospatial datasets into semantically rich, multi-scale representations. This study presents a methodology for developing a BIM-based DT of urban roads by integrating geospatial data from Mobile Mapping System (MMS) surveys with semantic information from municipal geodatabases. The approach follows a multi-modal (point clouds, imagery, vector data), multi-scale and multi-level framework, where ‘multi-level’ refers to modeling at different scopes—from a city-wide level, offering a generalized representation of the entire road network, to asset-level detail, capturing parametric BIM elements for individual road segments or specific components such as road sign and road marker, lamp posts and traffic light. MMS-derived LiDAR point clouds allow accurate 3D reconstruction of road surfaces, curbs, and ancillary infrastructure, while municipal geodatabases enrich the model with thematic layers including pavement condition, road classification, and street furniture. The resulting DT framework supports multi-scale visualization, asset management, and predictive maintenance. By combining geometric precision with semantic richness, the proposed methodology delivers an interoperable and scalable framework for sustainable urban road management, providing a foundation for AI-ready applications such as automated defect detection, traffic simulation, and predictive maintenance planning. The resulting DT achieved a geometric accuracy of ±3 cm and integrated more than 45 km of urban road network, enabling multi-scale analyses and AI-ready data fusion.

In vitro multi-electrode array (MEA) recordings are essential tools for neuroscience research, drug screening, and closed-loop neuromodulation. Yet, conventional MEA recording rely on continuous high-speed sampling, generating high data volumes that complicate processing, increase cost, and limit scalability. This work introduces a low-cost, low-data-rate, eventdriven neural acquisition platform that detects neural spikes directly in hardware, encoding them as discrete digital events, retaining only their spatiotemporal information. This architecture removes the need for high-resolution digitization and postprocessing, achieving over 99% data-rate reduction compared to continuous acquisition at 10 kS/s. Under controlled stress-test validation with synthetic signals across 15 simultaneous channels, the event-driven system reached F1-scores above 0.98 at 10 dB signal-to-noise ratio and remained stable up to 300 Hz firing rates, while maintaining sub-millisecond temporal accuracy. The platform can also be reprogrammed for conventional raw waveform acquisition, offering dual-use flexibility. Its modular design allows for straightforward scalability up to 60 channels, front-end upgrades or reconfiguration for other electrochemical measurements without a full hardware redesign. While the event-driven mode is not intended for experiments where spike morphology is critical, it provides an accessible and scalable solution for applications where spatio-temporal spike patterns are the key information, including network synchronization studies, burst detection, pharmacological assays, and long-term closed-loop protocols. By combining affordability, real-time performance, and high data reduction, this system establishes a practical and effective alternative to conventional electrophysiology systems for next-generation neuroscience research.

Abstract. We present a novel approach based on leveraging a network-wide parameterisation to derive snow water equivalent (SWE) with cosmic ray neutron sensing (CRNS) probes. The network comprises 26 sites (1422–2901 m asl) in the Italian Alps. The parameterisation was defined by fitting neutron counts to 35 SWE measurements taken at 6 sites in the first half of the 2023–2024 snow season and validated with 111 SWE data from 2023–2024 and 2024–2025 at 13 sites. Our analysis shows that this approach retains good representativeness of the snowpack, which can be extended to unmonitored sites if they have monitored counterparts at similar elevation. This finding overcomes the need for year-round accessibility and increases the number of potential sites for continuous SWE retrieval.

ObjectivesConspiracy thinking has played a significant role in shaping public responses to the COVID‐19 pandemic and has influenced citizens' adherence to government protocols, including reluctance to receive vaccination and adherence to public health measures. However, little attention has been paid to how contextual factors, such as the severity of the pandemic, interact with these beliefs. This study examines how the prevalence of the pandemic, defined as the ratio between the number of cases and swabs each day, moderated the relationship between conspiracy thinking and adherence to public health norms.MethodsWe conducted a secondary analysis of the ResPOnsE COVID‐19 project, a rolling cross‐section two‐wave survey of Italian adults (N = 5421) conducted between March and December 2021. Using a multilevel modelling approach, with data nested by day of data collection, we analysed the association between conspiracy beliefs, reluctance to receive a COVID‐19 vaccination and resistance to restrict personal freedoms, interacting conspiracy beliefs with daily variations in pandemic prevalence.ResultsConspiracy beliefs were positively associated with reluctance to receive the COVID‐19 vaccination and resistance to restrictions. The prevalence of the pandemic moderated these relationships: As the pandemic prevalence increased, conspiracy believers became more reluctant to get vaccinated but more accepting of restrictions on freedom.ConclusionsOur results emphasize the context‐dependent nature of the consequences of conspiracy beliefs. Rather than uniformly rejecting all public health measures, conspiracist citizens adjust their responses depending on contextual factors. These findings challenge simplistic representations of their attitudes and emphasize the need for dynamic public health communication strategies.

Arbuscular mycorrhizal fungi (AMF) are widespread plant symbionts that enhance nutrient acquisition and influence ecosystem productivity. Previous chromosome-level assemblies of a model species revealed a two-compartment genome architecture (active A and repressed B chromatin compartments), yet its conservation across evolutionarily distant AMF lineages remains unresolved. Here, we present a chromosome-scale and 3D genome assembly of Gigaspora margarita isolate BEG34, the largest and most repeat-rich AMF genome to date, alongside that of its obligate endobacterium, Candidatus Glomerobacter gigasporarum (CaGg), using PacBio HiFi and Hi-C sequencing. The G. margarita genome comprises 43 chromosomes (792 Mb) organized into stable A/B compartments and Topologically Associating Domains structures, irrespective of the presence of endobacteria. We uncover 21 divergent rDNA operons distributed across six chromosomes and show that these physically interact, suggesting conserved nucleolar organization. We also reveal that the CaGg genome is tripartite and mobilome-rich, encoding prophages, an orphan CRISPR array, and complete pathways for many novel and essential cofactors, including heme, which may enhance host bioenergetics. We also find that the endobacterium's presence regulates transposable elements in G. margarita. These findings reveal conserved principles of chromatin architecture in AMF symbionts and highlight the tight molecular interplay between fungal hosts and their endosymbionts, offering new insights into genome evolution and symbiotic adaptation.

ABSTRACT Aims Mires are important habitats that provide fundamental ecosystem services. Although they have traditionally been considered stable ecosystems, exhibiting little to no change in floristic composition over several decades to millennia, the effect of contemporary climate change is largely unknown. This study aimed to assess (i) how the vegetation of Sphagnum ‐dominated mires changed over the last two decades in the Western Alps, where mires are fragmented and at the southern edge of their European distribution, and (ii) whether climate change was a primary driver of these changes. Location Western Alps, Italy. Methods We resurveyed 139 plots across 14 sites, comparing historical vegetation data from 1998 and 2011 with new surveys conducted in 2023, including vascular plants and bryophytes. We analysed the shifts in species composition and the changes in community diversity and ecological indicators. We also evaluated climate trends over the past three decades and their relationship with vegetation dynamics. Results Climate data analyses confirmed increasing air temperatures, decreasing precipitation and increasing evaporation across the study sites. Both short‐term and long‐term resurveys showed an increase in species diversity, in particular woody and non‐specialist vascular plants, and a decrease in or local extinction of mire specialists, including Sphagnum species. These results suggest a lowering of the water table and a consequent drying. Longer term resurveys revealed signs of acidification and eutrophication, likely due to increased mineralisation. Attribution to climate change was supported by the higher increase in species richness in mires with a stronger decrease in precipitation. Conclusion Our results revealed significant vegetation changes under the pressure of climate change, with mires at the southern edge of their European distribution exhibiting more rapid and pronounced vegetation dynamics than previous studies conducted at higher latitudes. Urgent conservation measures, including rewetting, are essential to preserve these mires and their ecosystem services.