Azienda-Unita' Sanitaria Locale Di Cesena

• Enable patient digital twin deployment via a knowledge-driven, modular framework • Provide clinical data access and simulation through a FHIR-compliant API • Publish MIMO ontology to standardize and increase transparency of AI model interfaces • Automate AI model integration using a manifest-based binding protocol • Benchmark stroke risk models with real-time, time-aware clinical data streams Background: The healthcare sector faces diverse challenges, including poor interoperability and a lack of personalized approaches, which limit patient outcomes. Ineffective data exchange and one-size-fits-all treatments fail to meet individual needs. Emerging technologies like digital twins (DTs), the semantic web, and AI show promise in tackling these obstacles. For this reason, we introduced CONNECTED, a conceptual multi-level framework that combines these techniques to deploy general-purpose patient DTs. Objective: This study assesses CONNECTED’s comprehensiveness, applicability, and utility for developing intelligent, personalized healthcare applications. Specifically, we deliver a preliminary version of the framework to predict future patient states and demonstrate its automation benefits in deploying semantically enriched, AI-powered patient DTs. Methods: We enhanced the CONNECTED architecture by providing a formal definition of DT and modularizing its core functionalities into microservices—Properties, State, Capabilities, and Manifest. The Manifest service facilitates AI model integration through the Model Interface Manifest Ontology (MIMO), enabling automatic data-to-model binding via a reasoner. Using the HeartBeatKG quality assessment tool, we validated MIMO and tested the internal logic by integrating a well-established stroke-risk model. Results: Our implementation comprehends: (1) deploying a FHIR-compliant, patient-centric API for clinical history access, real-time monitoring, and predictive simulation; (2) publishing MIMO; (3) establishing the Manifest protocol for seamless, general-purpose AI model integration tailored to individual patient profiles; and (4) a proof-of-concept benchmarking application comparing multiple stroke risk classifiers. Conclusion: CONNECTED establishes a flexible, scalable foundation for interoperable semantic patient DTs. Automation reduces technical overhead and enables users to focus on delivering personalized, insight-driven care.

Background and Objectives: Pulmonary and mediastinal masses are diagnostic challenges for digestive endosonographers, and patients with these conditions are usually managed in thoracic or pulmonology units. EUS with tissue acquisition can result in adequate samples for histological examination and molecular analysis. Its spread among digestive endosonographers is limited; thus, we aimed to investigate the current management practices among the EUS Italian centers for those patients with mediastinal or pulmonary lesions to identify the principal areas of disagreement and help guide future research towards useful standardization. Methods: A 44‑question survey was sent during a temporal trend of 3 months to the endosonographers in Italian centers performing EUS. The survey includes questions with either a single answer choice or with multiple options exploring different aspects of the EUS done for the evaluation of thoracic lesions. The questions were grouped into specific sections: expertise of the center, periprocedural management, procedural aspects, and future perspectives. Results: Thirty-nine centers completed the survey, 27 (69.2%) from the north of Italy. Only 2 centers among the responders did not perform any mediastinal EUS (5.13%). The majority of centers (22, 59.5%) performed between 0 and 30 mediastinal EUS yearly, and only 3 centers did more than 100 mediastinal EUS per year. Responders were mainly gastroenterologists (34, 87.2%) versus surgeons (5, 12.8%). Only 5 centers performed mediastinal EUS in a shared room with bronchoscopy and endobronchial ultrasound (13.5%). The procedure was considered simple for 20 (54.1%) responders, complex for 5 (13.5%), and needed to be performed in a tertiary thoracic center for 12 (32.4%). Franseen and Fork tips were the most used tips (67.6% and 27%, respectively), and the most common needle diameter was 22 gauge (86.5%). Fifteen centers (40.5%) preferred deep sedation with an anesthesiologist without endotracheal intubation. The main growing indications appear to be local EUS-guided treatments (tumors or collections). Conclusions: This is the first survey assessing an evaluation on mediastinal/pulmonary EUS, which is well represented in Italy. Nonetheless, centers largely have low volumes of these procedures. Our results show heterogeneity in the management of patients affected with mediastinal/pulmonary lesions needing tissue acquisition. More studies also involving pulmonologists, thoracic surgeons, and oncologists are needed to increase data and understanding regarding this procedure.

Effective response inhibition is crucial for daily functioning. Behavioural inhibition can be assessed using the Stop Signal Task (SST), which requires coordinated activation across a complex network of brain regions, ultimately modulating corticospinal excitability (CSE). Importantly, CSE is not only modulated by excitatory drive but also by intracortical inhibitory processes such as short intracortical inhibition (SICI), which reflects the inhibitory activity of the GABAA receptors within the primary motor cortex. This review examines a series of studies exploring CSE changes, measured through Transcranial Magnetic Stimulation (TMS) applied online, i.e., during SST performance. We mainly focused on the temporal dynamics of CSE and SICI during the SST across healthy and clinical populations, highlighting differences between task-related and unrelated muscles, examining both global and selective modulations in proactive and reactive versions of the SST. Our discussion addresses the methodological and theoretical considerations involved in recording CSE online and questions the SST's effectiveness in accurately capturing inhibitory processes. Additionally, we analyse findings from motor-related disorders in clinical populations to identify specific abnormalities in CSE modulation and their underlying neural mechanisms. By summarizing the existing literature, we aim to offer a comprehensive view of the temporal dynamics of CSE, identifying key factors and methodologies that influence CSE modulation. This review seeks to prompt future directions in cognitive neuroscience research and potential clinical applications.

Gastrointestinal nematode infections significantly impact equine health and welfare, with rising anthelmintic resistance demanding alternative control strategies. Emerging evidence suggests that parasitic nematodes harbour distinct microbiomes, potentially influencing host-parasite dynamics and parasite survival. This study aimed to characterize and compare the microbiomes of equine gastrointestinal nematodes and their hosts, focusing on differences in composition, diversity, and core microbiota structure across different intestinal sites, nematode subfamilies, and sexes. Faecal and nematode samples were collected from equids (Equus caballus and Equus asinus) at slaughterhouses. DNA was extracted, and the V3-V4 regions of the 16S rRNA gene were amplified and sequenced using the Illumina iSeq 100 platform. Bioinformatic analyses were performed with QIIME2 and MicrobiomeAnalyst, and statistical comparisons employed PERMANOVA, LEfSe, and alpha and beta diversity metrics. Nematodes exhibited a distinct microbiome dominated by Firmicutes, Proteobacteria, Bacteroidota, Verrucomicrobiota, and Actinobacteriota, differing significantly from the faecal microbiota. Alpha diversity analyses revealed lower richness in nematodes, while beta diversity indicated distinct community structures (p = 0.007). Microbial composition varied by gastrointestinal site, nematode subfamily, and sex. Proteobacteria were consistently enriched in nematodes, particularly in the caecum. Core microbiome analysis identified exclusive nematode-associated taxa such as Fusobacterium, Mesorhizobium, and Mycoplasma. Equine gastrointestinal nematodes harbour independent and structured microbiomes, distinct from those of their hosts. These findings underscore the ecological specialization of nematodes and highlight the potential of targeting parasite-associated microbiota for novel control strategies.

Italy harbors one of the richest grapevine biodiversities worldwide, yet the sensory identity of wines from many native cultivars remains poorly defined despite their relevance on the market at regional, national, or international levels. This study provides a systematic sensory characterization of 18 Italian monovarietal white wines, analyzed across 246 commercial samples, including wines never investigated before by sensory analysis. Analysis of variance, hierarchical cluster analysis, and principal component analysis were applied to Rate-All-That-Apply (RATA) data performed by trained panelists to define a lexicon and identify the sensory attributes characterizing and discriminating the 18 wine types. A statistically based lexicon comprising 29 olfactory and seven taste/mouthfeel descriptors was defined. Multivariate statistics showed that the 18 monovarietal wine types belong to four main olfactory dimensions, labeled as fruity-balsamic, thiolic-mineral, floral-sweet, and toasty-dried. A three-dimensional space was defined along the four olfactory directions. Müller Thurgau, Gewürztraminer, Albana, and Falanghina emerged as the most representative wines in these directions, outlining the vertices of a spatial framework within and around which the other wines are distributed. Sensory wheels representing structured visual synthesis of the most relevant attributes (odor, taste, mouthfeel) were developed as 'identity models', providing systematic tools for defining wines' varietal typicality. Results are relevant for enologists and wine sellers as standardized reference sensory models for production and communication, as benchmarks for PDO/PGI quality control and disciplinary improvement, for researchers to advance modeling of wine sensory quality through sensometabolomic wine studies. Results also support the international recognition and valorization of Italian grapevine biodiversity according to Agenda 2030 sustainable development goals. © 2026 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Wetware Network-Based Artificial Intelligence (WNAI) introduces a new approach to robotic cognition and artificial intelligence: autonomous cognitive agents built from synthetic chemical networks. Rooted in Wetware Neuromorphic Engineering, WNAI shifts the focus of this emerging field from disembodied computation and biological mimicry to reticular chemical self-organization as a substrate for cognition. At the theoretical level, WNAI integrates insights from network cybernetics, autopoietic theory and enaction to frame cognition as a materially grounded, emergent phenomenon. At the heuristic level, WNAI defines its role as complementary to existing leading approaches. On the one hand, it complements embodied AI and xenobotics by expanding the design space of artificial embodied cognition into fully synthetic domains. On the other hand, it engages in mutual exchange with neural network architectures, advancing cross-substrate principles of network-based cognition. At the technological level, WNAI offers a roadmap for implementing chemical neural networks and protocellular agents, with potential applications in robotic systems requiring minimal, adaptive, and substrate-sensitive intelligence. By situating wetware neuromorphic engineering within the broader landscape of robotics and AI, this article outlines a programmatic framework that highlights its potential to expand artificial cognition beyond silicon and biohybrid systems.

The paper presents the design, simulation, and fabrication of a rectenna operating in the UHF band (868 MHz), optimized for energy harvesting in IoT applications. The system consists of a patch antenna fabricated on an FR4 substrate and excited via a coaxial pin, connected to a distributed impedance matching network implemented on the back side of the structure using a Rogers substrate to maximize power transfer to a nonlinear rectifier. The FR4 and Rogers substrates are separated by a ground plane, which serves as a shield between the antenna and the rectifier, ensuring that the rectenna's operation remains independent of the mounting surface. Measurement results show good impedance matching and an effective RF-to-DC conversion suitable for low-power, long-range (up to 20 meters) applications. An input power of at least <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{- 1 9} \mathbf{~ d B m}$</tex> is required for the cold-start of the DC-DC converter connected to the rectenna, and with this system, the suitability for ultra-low-power energy harvesting scenarios is demonstrated.

COVID-19 severity is uneven between genders. A role for sex hormones is possible and has been postulated. Considering this idea, we hypothesized hormonal therapies might influence the severity of COVID-19 in breast cancer (BC) patients. We mined the Emilia-Romagna region (Italy) registries to compare the rates of hospitalization and mortality by COVID-19 in 2020 amongst 22,987 BC patients treated with tamoxifen, aromatase inhibitors (AIs), fulvestrant, and anti-HER2 therapies (trastuzumab and pertuzumab) in 2020, the latter used as reference group. The hospitalization rate observed in 4719 tamoxifen-treated BC patients was the lowest (0.61%, OR, 0.38; 90% CI, 0.20–0.76; p = 0.03) among hormonal therapies. Importantly, only one COVID-19 fatality was observed in tamoxifen-treated BC patients, who showed a striking 0.02% COVID-19 death frequency as compared to 0.24% observed for the whole BC patients population. In addition, tamoxifen emerged in the sex and age adjusted analysis as the only agent significantly decreasing the standard mortality rate (SMR) by COVID-19 as compared to the regional population consisting of 2,296,559 female residents from the Emilia Romagna region in 2020. Our results show that BC patients are at increased risk of COVID-19 hospitalization and that COVID-19 mortality is hindered by SERM-based therapies like tamoxifen. These findings are relevant to choose adequate treatments in order to protect cancer patients from concomitant SARS-CoV-2 contagion and related symptoms and contribute to the idea that SERMs could be used as prophylactic agents and therapeutics to prevent the progression of severity of COVID-19.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-22463-8.