Lupus Nephritis (LN) still represents one of the most severe complications of Systemic Lupus Erythematosus (SLE) and a major risk factor for morbidity and mortality. However, over the last few years, several studies have paved the way for a deeper understanding of its pathogenetic mechanisms and more targeted treatments. This review aims to provide a comprehensive update on progress on several key aspects in this setting: pathogenetic mechanisms of LN, including new insight into the role of autoantibodies, complement, vitamin D deficiency, and interaction between infiltrating immune cells and kidney resident ones; the evolving role of renal biopsy and biomarkers, which may integrate information from renal histology; newly approved drugs such as voclosporin (VOC) and belimumab (BEL), allowing a more articulate strategy for induction therapy, and other promising phase III-immunosuppressive (IS) agents in the pipeline. Several adjunctive treatments aimed at reducing cardiovascular risk and progression of chronic renal damage, such as antiproteinuric agents, represent an important complement to IS therapy. Furthermore, non-pharmacological measures concerning general lifestyle and diet should also be adopted when managing LN. Integrating these therapeutic areas requires an effort towards a holistic and multidisciplinary approach. At the same time, the availability of an increasingly wider armamentarium may translate into improvements in patient’s renal outcomes over the next decades.

Critically ill patients are at risk of skin wounds, which reduce their quality of life, complicate their pharmacological regimens, and prolong their hospital stays in intensive care units (ICUs), while also increasing overall mortality and morbidity rates. Cold atmospheric plasma (CAP) has been proposed as a viable option for many biological and medical applications, given its capacity to reduce wound bacterial contamination and promote wound healing. The aim of this narrative review is to describe how CAP works and its operating mechanisms, as well as reporting its possible applications in critical care settings. The success of CAP in the treatment of wounds, in particular, bedsores or pressure sores, presents an innovative path in the prevention of nosocomial infections and an opportunity of reducing the negative implications of these diseases for the NHS. This narrative review of the literature was conducted following the ‘Scale for the Assessment of Narrative Review Articles’ (SANRA) methodology. Previous literature highlights three biological effects of plasma: inactivation of a wide range of microorganisms, including those that are multi-drug-resistant; increased cell proliferation and angiogenesis with a shorter period of plasma treatment; and apoptosis stimulation with a longer and more intensive treatment. CAP is effective in many areas of the medical field, with no significant adverse effects on healthy cells. However, its use can produce potentially serious side effects and should, therefore, be used under expert supervision and in appropriate doses.

Artificial Intelligence (AI) is rapidly transforming medical education by enabling adaptive tutoring, interactive simulation, diagnostic enhancement, and competency-based assessment. This narrative review explores how AI has influenced learning processes in undergraduate and postgraduate medical training, focusing on methodological rigor, educational impact, and implementation challenges. The literature reveals promising results: large language models can generate didactic content and foster academic writing; AI-driven simulations enhance decision-making, procedural skills, and interprofessional communication; and deep learning systems improve diagnostic accuracy in visually intensive tasks such as radiology and histology. Despite promising findings, the existing literature is methodologically heterogeneous. A minority of studies use controlled designs, while the majority focus on short-term effects or are confined to small, simulated cohorts. Critical limitations include algorithmic opacity, generalizability concerns, ethical risks (e.g., GDPR compliance, data bias), and infrastructural barriers, especially in low-resource contexts. Additionally, the unregulated use of AI may undermine critical thinking, foster cognitive outsourcing, and compromise pedagogical depth if not properly supervised. In conclusion, AI holds substantial potential to enhance medical education, but its integration requires methodological robustness, human oversight, and ethical safeguards. Future research should prioritize multicenter validation, longitudinal evaluation, and AI literacy for learners and educators to ensure responsible and sustainable adoption.

Introduction. The clinical course of Coronavirus Disease 2019 (COVID-19) is highly heterogenous, ranging from asymptomatic to fatal forms. The identification of clinical and laboratory predictors of poor prognosis may assist clinicians in monitoring strategies and therapeutic decisions. Materials and Methods. In this study, we retrospectively assessed the prognostic value of a simple tool, the complete blood count, on a cohort of 664 patients ( 260; 39%, median age 70 (56-81) years) hospitalized for COVID-19 in Northern Italy. We collected demographic data along with complete blood cell count; moreover, the outcome of the hospital in-stay was recorded. Results. At data cut-off, 221/664 patients (33.3%) had died and 453/664 (66.7%) had been discharged. Red cell distribution width (RDW) ( 10.4; ), neutrophil-to-lymphocyte (NL) ratio ( 7.6; ), and platelet count ( 5.39; ), along with age ( 87.6; ) and gender ( 17.3; ), accurately predicted in-hospital mortality. Hemoglobin levels were not associated with mortality. We also identified the best cut-off for mortality prediction: a was characterized by an odds ratio for in-hospital (2.40-4.82), while the OR for a