Polo d’Innovazione di Genomica

Aim: Kinesiophobia, which is essentially a consequence of the fear-avoidance model, is more common in geriatric individuals due to the fragility experienced in old age. The presence of urinary incontinence can exacerbate kinesiophobia by triggering avoidance behaviors. In this study, we investigated the effects of the presence of urinary incontinence on kinesiophobia in older adults with chronic pain. Materials and Methods: This study included 114 consecutive participants aged 65 years and older who were examined for chronic pain in the physical medicine and rehabilitation clinic, 55 with urinary incontinence, and 49 controls. After collecting sociodemographic data using a standardized form by a physiatrist, kinesiophobia was evaluated with the Tampa Kinesiophobia Scale. The participants’ moods and quality of life were assessed using the Hospital Anxiety and Depression Scale (HADS) and the 12-item Short Form Survey (SF-12), respectively. Incontinence severity was evaluated with the International Consultation on Incontinence Questionnaire-Short Form (ICIQ-SF), and the effects of incontinence on quality of life were assessed via the Incontinence Quality of Life Scale (I-QOL). Results: The sociodemographic characteristics of the 2 groups were similar. The HADS-A, HADS-D, SF-12 physical, and SF-12 mental scores were also similar between the groups ( P = .44, P = .33, P = .97, and P = .96, respectively), although the participants with incontinence registered higher Tampa Kinesiophobia Scale scores ( P = .018). The Tampa scores were positively correlated with the ICIQ-SF scores ( r = 0.70; P < 001) but negatively correlated with the I-QOL scores ( r = −0.40; P = .02). Conclusion: The kinesiophobia levels were higher in the participants with urinary incontinence, and an association was found between the severity of urinary incontinence and kinesiophobia. The presence of incontinence should be considered in the management of older adults with kinesiophobia.

The emergence of the Industrial Internet of Things (IIoT) is transforming traditional industrial maintenance into a predictive, data-driven process. This paper presents a comprehensive architecture for an IIoT-enabled monitoring and maintenance system focused on industrial machine tools. Leveraging proximity sensors to capture rotation speed, axial movement, and tool position, the system integrates sensor data with microprocessors such as Arduino STM32 and PID controllers to ensure real-time control and analysis. The architecture utilizes both local processing through Arduino IDE and centralized visualization via Node-RED, enabling efficient data transmission to cloud services through an Internet gateway. Key technologies such as 5G communication, big data analytics, and digital twins are incorporated to enhance predictive maintenance capabilities, reduce downtime, and improve overall equipment effectiveness (OEE). Despite the promise of IIoT integration, challenges such as interoperability, cybersecurity, and legacy system adaptation remain significant. This study proposes a scalable and intelligent CPS framework to overcome these obstacles and highlights the potential of Machine Tool 4.0 in achieving smarter, more autonomous, and sustainable manufacturing ecosystems.

This contribution presents new data on the distribution of Annex I Habitats in Italy. A total of 10 records are reported, including 6 within Natura 2000 sites and the addition of 15 new cells to the EEA 10 km × 10 km reference grid. The new records refer to the administrative regions of Apulia, Marche, Piedmont, Sardinia, Sicily, Tuscany and Veneto.

The rapid integration of generative AI (GenAI) into core organizational infrastructure requires a rethinking oftraditional governance models. This paper explores how organizations can effectively govern GenAI at scale whilemaintaining strategic, ethical, and societal alignment. By synthesizing key theoretical frameworks, including institutionaltheory and dynamic capabilities, we propose a conceptual framework organized around three interconnected domains:Model Stewardship, Operational Alignment, and Strategic Guardrails. We contend that scalable governance must evolvefrom static compliance to a dynamic, adaptable organizational capability. The paper concludes with the introduction of theGenAI Governance Maturity Model (GAI-GMM), a research-based tool for institutional alignment.

Extensive benchmarks and reviews of time-dependent density functional theory (TDDFT) have been published, covering at least 50 functionals. Here, we do not use one of the (meta)GGA or hybrid functionals but highlight the particular TDDFT method that does not use the Kohn-Sham (KS) potential of some exchange-correlation functional, but uses the exact Kohn-Sham potential or a close approximation to it in the SCF calculations. Such KS-potential-based TDDFT results have been proven to yield excellent results. For routine application, it is required that a computationally simple approximation (as a density functional) to the exact KS potential is available. In this paper, we benchmark TDDFT calculations with a recently developed model KS potential and compare them to advanced quantum chemical methods and experimental data. The target systems here are medium-sized molecules. These TDDFT calculations based on good KS potentials prove to be competitive in accuracy with sophisticated ab initio methods. An advantage is the possibility to use large basis sets (also for large molecules), enabling a description of valence excitations and Rydberg (or mixed valence-Rydberg) excitations on the same footing. This is necessary for high accuracy; a sophisticated but expensive method that cannot handle large basis sets cannot achieve high accuracy. An advantage of the use of a (close to) exact Kohn-Sham potential is the realistic nature (shape and energy) of both the occupied and the virtual KS orbitals, affording an interpretation of excitations in terms of one or a few single orbital-to-orbital transitions. This obviates the need for extensive optimization of the virtual orbitals for the purpose of interpreting excitations. To highlight the importance of the realistic nature of the KS virtuals, including the Rydberg orbitals, we discuss and reassess the nature of the 21 Ag state of s-trans-1,3-butadiene, which has been widely considered as a prototype excitation with large double excitation character. Charge-transfer and true double excitations cannot be handled by the simple ALDA kernel used here.

Abstract This article addresses symbolic communication in food labelling, with a particular emphasis on territorial references of a visual nature that do not correspond to the product’s actual origin. The European landscape will be examined, and the link between verbal and non-verbal labelling elements will be addressed. Secondly, consideration will be given to the most recent developments in US law in order to bring the focus back to comparing EU and US systems. Finally, summary reflections will include the divergence of positions among EU States as well as the possibility/availability of a convergence between European and US models.

Abstract Introduction Immune checkpoint inhibitors (ICIs), including PD-1/PD-L1 and CTLA-4 inhibitors, have significantly improved cancer treatment outcomes. Over the past decade, these therapies have demonstrated remarkable efficacy; however, their use is associated with immune-related cardiovascular adverse events (irCVEs), ranging from mild biomarker alterations to severe conditions such as arrhythmias, myocarditis, pericarditis, left ventricular dysfunction, heart failure, and acute coronary syndrome. Moreover, specific risk factors for irCVEs development remain unknown. Purpose This study aims to identify risk factors for irCVEs in cancer patients receiving ICI. Methods A total of 125 patients undergoing immunotherapy were assessed. From July 2022, each patient underwent baseline and on-treatment evaluations, including physical examination, electrocardiography, echocardiography, and measurement of high-sensitivity troponin I and NT-proBNP. Data were collected from medical records and diagnostic assessments. Logistic regression analysis was performed to identify independent risk factors, excluding imbalanced variables. Initial analysis using the Generalised Linear Model (GLM) in R found no significant predictors, leading to the application of a regularised GLM to enhance prediction accuracy and prevent overfitting. The dataset was divided into a training set (87 patients) and a test set (38 patients). Model optimisation involved hyperparameter tuning (penalty: 0.0000000001, mixture: 0), with validation based on key performance metrics (accuracy: 68%, precision: 83%, sensitivity: 77%, specificity: 29%, F-measure: 0.80, Cohen’s Kappa: 0.05). Results Our study identified 17 events, including 6 cases of asymptomatic cardiac biomarker elevation, 3 cases of myocarditis, 1 case of pericarditis, 3 cases of heart failure, 1 case of atrial fibrillation, and 3 cases of acute coronary syndrome, most of which occurred after the first ICI administration. Pre-existing diabetes, dyslipidaemia, atrial fibrillation, and prior treatment with a potentially cardiotoxic regimen emerged as independent predictors of irCVEs development. Additionally, our evaluation proved to be a reliable predictor of irCVEs development in medium- and high-risk patients according to ESC Guidelines 2022. No irCVEs-related deaths were reported. Conclusion Immunotherapy represents a major advancement in cancer care, yet early identification and risk stratification of irCVEs are crucial to minimising complications and optimising patient outcomes. Our findings underscore the need for proactive strategies to improve early irCVEs detection and risk assessment. This study provides real-world insights into irCVEs; however, our findings should be interpreted cautiously due to the limited sample size and low event incidence. Further ongoing research aims to expand patient cohorts and refine predictive models to support standardised prevention strategies.