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Background and Aim: Artificial intelligence (AI) is among the most promising innovations for transforming nursing education, making it more interactive, personalized, and competency-based. However, its integration also raises significant ethical and practical concerns. This scoping review aims to analyze and summarize key studies on the application of AI in university-level nursing education, focusing on its benefits, challenges, and future prospects. Methods: A scoping review was conducted using the Population, Concept, and Context (PCC) framework, targeting nursing students and educators in academic settings. A comprehensive search was carried out across the PubMed, Scopus, and Web of Science databases. Only peer-reviewed original studies published in English were included. Two researchers independently screened the studies, resolving any disagreements through team discussion. Data were synthesized narratively. Results: Of the 569 articles initially identified, 11 original studies met the inclusion criteria. The findings indicate that AI-based tools—such as virtual simulators and ChatGPT—can enhance students’ learning experiences, communication skills, and clinical preparedness. Nonetheless, several challenges were identified, including increased simulation-related anxiety, potential misuse, and ethical concerns related to data quality, privacy, and academic integrity. Conclusions: AI offers significant opportunities to enhance nursing education; however, its implementation must be approached with critical awareness and responsibility. It is essential that students develop both digital competencies and ethical sensitivity to fully leverage AI’s potential while ensuring high-quality education and responsible nursing practice.

Breast cancer (BC) is one of the most common malignancies among women worldwide. Despite advances in early detection and treatment, prognosis remains highly variable. Molecular biomarkers, such as microRNAs (miRNAs), have emerged as promising tools to refine prognostic assessment. Among them, miR-21 is consistently overexpressed in solid tumors and implicated in key oncogenic pathways. This systematic review and meta-analysis aimed to clarify the prognostic significance of miR-21 in BC and explore its molecular mechanisms through bioinformatic analyses. A systematic search of PubMed, Scopus, and Web of Science up to April 2025 identified 18 eligible observational studies. Pooled analyses showed that high miR-21 expression was significantly associated with poorer overall survival (OS) (HR = 2.37, 95% CI: 1.42–3.98) and recurrence-related outcomes (DFS/RFS) (HR = 2.10, 95% CI: 1.32–3.34). Subgroup analyses confirmed robust associations across different cut-off definitions and revealed particularly strong effects in triple-negative BC (HR = 5.69) and mixed subtypes (HR = 2.55), but no significant association in HER2-positive BC. Bioinformatic analysis identified target genes such as PTEN, BCL2, STAT3, and MYC, involved in apoptosis regulation, proliferation, NF-κB signaling, and immune modulation. These findings provide consistent evidence that miR-21 is a promising minimally invasive prognostic biomarker in BC, particularly in aggressive subtypes, and support its integration into future multimodal prognostic models.

Backgorund. Multiple sclerosis (MS) profoundly affects the lives of patients and their families. The experience of the disease is shaped not only by its progression and specific characteristics but also by the quality of medical and caregiving support received. The diagnosis of MS represents a transformative event that may lead to job loss, the need for continuous care, and a significant reorganization of family roles. In Italy, more than 140,000 people are affected by MS (AISM data, 2024). The impact of the disease is multifaceted and complex, involving various aspects of the patient’s life. Dependence on external assistance often becomes an unavoidable necessity, highlighting the importance of exploring the quality of life of people with MS in the Italian context. The main objective is to assess the quality of life of individuals affected by MS, both before diagnosis and during the course of the disease. A secondary aim is to identify related psycho-physical consequences, including care-related needs. Methods: An online survey was conducted through various associations operating across Italy, involving a sample of 99 individuals diagnosed with MS. Results: The results show a predominance of female participants, with a mean age of 41 years. The disease was reported to be at an early stage in 66.7% of cases and advanced in 33.3%, with none of the respondents being in a terminal phase. The most frequent clinical form was relapsing–remitting MS (RRMS), which accounted for 78.8% of the cases. In terms of employment and daily activities, more than half of the participants reported underperforming (59.6%) or limiting specific tasks (51.5%) due to disability caused by the disease. Emotional distress had even more pronounced effects, with 63.6% reporting a decline in performance and 62.6% experiencing concentration difficulties. Quality of life was significantly affected, particularly in the physical and emotional domains. Vitality, physical pain, perceived health, and psychological well-being emerged as compromised dimensions, pointing to the need for a multidimensional care model that integrates therapeutic, rehabilitative, and psychosocial interventions. Individuals in the early stages of MS tended to maintain better work relationships and demonstrated higher levels of professional engagement. Conclusions: The findings underscore the importance of a continuous and personalized care approach, addressing not only clinical treatment but also psychological and social support. These aspects are crucial for monitoring patients’ needs, promoting quality of life, facilitating disease acceptance, and mitigating psychological distress.

Background: Extracorporeal membrane oxygenation (ECMO) is commonly used for temporary support in patients with severe cardiogenic shock and may serve as a bridge to heart transplantation. In recent years, outcomes have improved with better timing, patient management and advances in ECMO technology. Case presentation: We describe the case of a 61-year-old man who developed refractory cardiogenic shock after an extensive acute myocardial infarction complicated by recurrent ventricular arrhythmias. After an initial period of stabilization following complex percutaneous coronary intervention, the patient suddenly deteriorated with acute pulmonary edema and severe hypoxemia. A peripheral femoro-femoral veno-arterial ECMO with distal limb perfusion was promptly implanted using the ECMOLIFE system and the Landing Advance system (Eurosets s.r.l., Medolla, MO, Italy) to stabilize the patient and enable continuous monitoring. Due to severe left ventricular distension, surgical left ventricular venting was performed through a minimally invasive approach. ECMO support allowed rapid hemodynamic stabilization without major complications. During ECMO support, the patient remained stable and after less than 48 h a suitable donor heart became available. The patient was safely transferred to a transplant center while on ECMO and successfully underwent heart transplantation. Conclusions: This case shows that early ECMO implantation, combined with appropriate ventricular unloading and careful management with an advanced monitoring system, can be an optimal support as a bridge to heart transplantation. Limiting the duration of ECMO support and ensuring timely referral to a transplant center may improve outcomes in patients with refractory cardiogenic shock.

Background: Artificial intelligence (AI) has emerged as a transformative tool in healthcare, particularly in drug and biomarker discovery, where it can enhance precision, streamline discovery processes, and optimize treatment strategies. Despite its potential, the application of AI in glioblastoma (GB) research, especially in identifying novel biomarkers and therapeutic targets, remains underexplored. The aim of this review is to map the existing literature on AI-driven approaches for biomarker and drug discovery in GB, highlighting key trends and gaps in current research. Design: Following a PRISMA methodology, this scoping review examined studies published between 2012 and 2024. Searches were conducted across multiple databases, including MEDLINE (PubMed), Scopus, the Cochrane Library, and Web of Science (WOS). Eligible studies were screened, and relevant data were extracted and synthesized to provide a comprehensive overview of AI applications in GB research. Results: A total of 224 records were identified, including 210 from PubMed, 104 from Scopus, 4 from WOS, and 6 from the Cochrane Library. After screening and applying eligibility criteria, 33 studies were included in the final review. These studies showcased diverse AI methodologies applied to both drug discovery and biomarker identification, focusing on various aspects of GB biology and treatment. Conclusions: This scoping review reveals an increasing interest in AI-driven strategies for biomarker and drug discovery in GB, with promising initial results. However, further large-scale, rigorous studies are needed to validate real-world applications of AI and the development of standardized protocols to enhance reproducibility and clinical translation.

The use of green compost is a suitable technology to recycle organic waste into environmentally friendly soil improvement mitigating the pressure on landfills and contributing to sustainability. Among the major nutrients, phosphorus (P) stands at a significant position for seed and fruit quality, photosynthesis, and metabolic function in plants. This work evaluates the effects of different doses of mineral/organic fertilizers on two durum wheat cultivars: Anco Marzio and Vespucci. The fertilization trials compared one unfertilized control test and six treatments performed with different types of fertilizers (four minerals and two organics, based on green compost). Grain yield, compared with the unfertilized control, increased with the mineral fertilization by 125.5% for Anco Marzio and 136.42% for Vespucci, while organic fertilization alone determined an increase of 25.52% and 30.92% for Anco Marzio and Vespucci, respectively. The contribution of a higher dose of phosphorus (140 kg ha−1), combined with nitrogen and potassium, favored a further increase in grain production (+9.34%), compared with 100 kg ha−1. The content of chlorophylls and carotenoids was highly increased (5%) in both the cultivars by all kinds of phosphate fertilization, whereas an increase in the phosphate content of caryopses resulted in Anco Marzio across the two years but not in Vespucci. Among the two cultivars of durum wheat, Vespucci produced a greater quantity of grains but with a less vitreous consistency and poorer in proteins than Anco Marzio. The fertilization management also influenced the wheat behavior to stripe yellow rust attack by showing the highest index severity with the compost-based fertilization. The best management of fertilizers associated with the use of more phosphorus-use-efficient genotypes, are essential for improving quality and for the development of a sustainable agriculture.