Acta Orientalia Vilnensia
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Prefazione Eutopia Messina
No full textIl breve testo inquadra la cornice filosofica nella quale si iscrive il progetto della Fondazione Messina per la realizzazione di una "eutopia", cioè non un sogno bellissimo ma irrealizzabile (utopia), né il delinearsi di un futuro triste e foriero di disagi per l'umanità (distopia), ma la concreta costruzione di un luogo di bellezza e giustizia nel nostro territori
Hyperparameter Optimized SVR Model Based on Particle Swarm Algorithm for RF Power Transistors
No full textA novel approach for optimizing the hyperparameters of a support vector regression (SVR) model is presented for radio frequency (RF) power transistors. In standard SVR models, hyperparameters are enhanced using grid search optimization (GSO), which can be inefficient. In this study, particle swarm optimization (PSO) is introduced as a method for optimizing hyperparameters in a SVR model that increases the model optimization efficiency significantly in comparison with GSO while maintaining a high level of performance. To verify the accuracy and effectiveness of the model, a 10-W GaN power transistor produced by Wolfspeed is used. In comparison to the existing GSO-SVR model, the proposed PSO-SVR model demonstrates superior performance and efficiency
Clinical Course of COVID-19 in Children With Adrenal Insufficiency: Results From National Data
No full textContext There has been concern about a potential increase in the incidence or severity of coronavirus disease 2019 (COVID-19) in individuals with adrenal insufficiency (AI). Data on the course of SARS-CoV-2 infection in AI children are lacking. Objective Evaluate whether children with AI are more susceptible to the infection or are at risk of severe COVID-19. Methods In this multicenter, retrospective study among 1143 children with AI, 148 contracted SARS-CoV-2 (112 with primary, 36 with secondary AI) and were evaluated for severity and outcomes of infection, along with 74 control subjects with normal adrenal function. Results The prevalence of COVID-19 in the AI cohort was 12.9%, not increased compared to pediatric Italian population in the same period. The severity was not increased in AI subjects and was classified as follows in patients vs controls: asymptomatic in 14.9% vs 10.8%; paucisymptomatic in 33.8% vs 37.8%; mild in 45.3% vs 45.9%; severe in 3.4% vs 2.7%; critical in 2.7% vs 2.7%. Among those with severe COVID, 4 patients with AI (2.7%) and 3 controls (4%) developed pneumonia while 3 patients with PAI (2%) and 2 controls (2.7%) developed multisystem inflammatory syndrome (P not statistically significant). Only 5 patients (3.4%) experienced an adrenal crisis during a severe COVID-19. The hospitalization rate was the same in patients vs controls (9.5%). All subjects completely recovered, and no COVID-related deaths were documented. Conclusion Our findings do not indicate that AI is associated with increased susceptibility to SARS-CoV-2 infection or higher risk for severe COVID-19 in children
Are biopesticides really safe? Impacts on gut microbiota and intestinal health in freshwater fish
No full textThe growing use of biopesticides as eco-friendly alternatives to chemical pesticides is reshaping pest control in agriculture and aquaculture. However, their potential effects on non-target aquatic species, particularly freshwater fish, remain underexplored. This review investigates how different biopesticides, such as microbial agents, biochemical compounds, and plant-incorporated protectants, affect the gut microbiota and intestinal health of freshwater fish. The gut microbiome plays a vital role in digestion, nutrient absorption, immunity, and overall fish health. Biopesticide exposure may disrupt microbial balance, leading to reduced diversity, changes in community composition, inflammation, and dysbiosis. These alterations can impair digestive efficiency, immune function, growth, and reproduction. Promising mitigation strategies include the use of probiotics, prebiotics, symbiotics, insect-based feeds and other non-bacterial dietary interventions to restore gut homeostasis and improve fish resilience. In addition, advanced techniques like metagenomics and metabolomics are enhancing our understanding of host–microbiome interactions under biopesticide exposure. This review emphasizes the importance of including gut microbiota health in environmental risk assessments for biopesticide use in aquaculture. Future studies should adopt a multidisciplinary approach combining toxicology, microbiology, nutrition, and environmental science to develop species-specific, long-term strategies that safeguard fish health in increasingly pesticide-influenced aquatic environments
Effectiveness and safety of opioid-free anesthesia compared to opioid-based anesthesia: a systematic review and network meta-analysis
No full textBackground: Opioid-free anesthesia (OFA) is an innovative approach to anesthesia management aimed at enhancing both the safety and the quality of perioperative outcomes. The efficacy and safety of these approaches are uncertain. The aim of our work was to compare the effectiveness and safety of different OFA regimens to opioid-based anesthesia (OBA). Study design and methods: We conducted a systematic review and frequentist random-effects network meta-analysis of randomized controlled trials (RCTs). The primary outcome measure was the intensity of postoperative pain at 24 h, expressed in terms of numerical rating scale (NRS), visual analogue scale (VAS), or verbal rating scale (VRS) scores. The SUCRA was used to determine the likelihood that an intervention was ranked as the best. The certainty of the evidence was assessed according to the GRADE methodology for Network Meta-analysis (NMA). Results: A total of 42 RCTs were included, for a total of 4666 patients. We have addressed the variety of available interventions. The random-effects network meta-analysis comparing OBA and different OFA regimens showed no difference in the pain intensity at 24 h. We performed the GRADE assessment for each comparison between each OFA regimen and OBA as a comparator. The certainty of evidence for the primary outcome ranges from moderate to very low among the different comparisons. Conclusions: We have identified a significant heterogeneity in OFA regimens evaluated and a moderate to high risk of bias in over 70% of studies reporting the primary outcome. No OFA regimens showed a statistically significant effect over OBA in reducing postoperative pain within the first 24 h following surgery. Current evidence does not support the superiority of the analgesic efficacy of OFA in the immediate postoperative period compared to the use of opioids. Trial registration: This study is registered in PROSPERO with the registration number CRD42024529236 (May 3, 2024)
Real-World Efficacy and Safety of Inclisiran: A Single-Country, Multicenter, Observational Study (CHOLINET Registry)
No full textTargeting Proteins Involved in Neurodegenerative Diseases and Cancer: From Traditional Structure-Based Approach to Artificial Intelligence Models
No full textComputer-aided drug design (CADD) and machine learning (ML) techniques are transforming drug discovery, enabling the efficient identification of small molecules with therapeutic potential. Neurological conditions, which affect 43% of the global population and represent the leading cause of ill health and disability worldwide, alongside cancer, with over 2 million new cases and 611,720 deaths expected in the USA in 2024, underscore the urgent need for effective treatments. [1, 2] This dissertation addresses such a challenge by applying CADD and ML methodologies to the discovery of ligands targeting proteins implicated in neurological disorders and tumors: Sigma receptors (SRs) and Tyrosinase (TYR). The Introduction section provides detailed insights into the methodologies employed throughout the study.
In Case study 1: targeting Tyrosinase enzyme, a therapeutic target associated with melanoma and Parkinson's disease, efforts were focused on the identication of new inhibitors targeting two distinct forms of tyrosinase: Agaricus Bisporus (AbTYR) and human Tyrosinase (hTYR). CADD techniques, spaning from docking studies, MM-GBSA calculations and molecular dynamics simulations, were employed in retro-analyses to rationalize experimental data. These approaches offered valuable insights into ligand-receptor interactions and revealed key structural determinants of binding, advancing our understanding of tyrosinase modulation.
In Case study 2: targeting Sigma Receptors, Sigma Receptors (SRs) are investigated as versatile targets in drug discovery, since the several implications in tumor and neurological conditions. The study encompassess a range of methodologies, including molecular docking and dynamics for retrospective analyses, as well as an in-depth structure-based approach to create a pharmacophore model for Sigma 1 receptor (S1R) compounds. This work, conducted during my 10-month industry internship at Net4Science, led to the identification of promising therapeutic candidates. Furthermore, during a six-month exchange program at the University of Vienna, a machine learning (ML) approach was utilized to predict active and selective compounds targeting SRs, enhancing the potential for precision in drug discovery. ML algorithms, trained on structural and physicochemical data, achieved high accuracy in identifying SRs compounds. The findings presented in this research highlight the effective contribution of CADD and ML in modern drug discovery, offering novel methodologies and insights into the design and optimization of compounds targeting SRs and TYRs