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The blood-brain barrier (BBB) plays a key role for brain homeostasis, but at the same time it represents a major obstacle to the development of efficacious treatment for brain diseases. The application of nanomedicine to neurological disorders is one of the most promising strategies to improve the current therapies [1]. Liposomes (LPs) have been widely studied as therapeutic tools for the delivery of drugs to the central nervous system, demonstrating their ability to cross the BBB and to target specific brain sites. Some approaches for BBB crossing involve the surface modification of LPs with biologically active ligands and, among them, Apolipoprotein E-modified peptide (mApoE) has been used for the functionalization of several liposome-based nanovectors under investigation [2-3]. In this study, we propose a biophotonic technique, Surface Plasmon Resonance imaging (SPRi), for the characterization of dual--targeting-peptides LPs to be tested for the control of neuroinflammation and associated microglial dysfunctions in Glioblastoma and Alzheimer’s disease. Indeed, LPs loaded with selected drugs were functionalized with mApoE to enable the BBB crossing and with a metallo-protease sensitive peptide to guarantee the localized release of the encapsulated drugs in diseased areas. SPRi is an optical detection technique used to monitor and analyze biomolecular interactions between an analyte in solution and ligands immobilized on a gold chip. Here, the SPRi analysis was performed in order to evaluate the binding affinity and kinetics between LPs and the receptors. In particular, mApoE targets were immobilized on a SPRi gold chip to verify and monitor the LP binding. The spotting procedure for ligands immobilization on the chip was carried out using a microspotter, and parameters like ligand concentration, buffer and spot diameter were optimized in order to obtain the most reproducible results. We analyzed mApoE LPs and not functionalized LPs finding that mApoE LPs generated

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Background: Older age is a well-known risk factor for recurrent and severe Clostridioides difficile infection (CDI). Fecal microbiota transplantation (FMT) is widely recognized as an effective and safe therapeutic option for the treatment of recurrent CDI (rCDI). However, the efficacy and safety of FMT for rCDI in very old patients are uncertain. This study evaluated the efficacy and safety of FMT in a group of very old subjects with rCDI, and the reliability of overall comorbidity and frailty assessment for identifying patients at higher risk of worse clinical outcomes. Methods: This is a retrospective single-center study including patients ≥85 years undergoing FMT for rCDI between 2014 and 2022. Primary outcomes included efficacy of FMT, defined as cure of CDI at 8 week-follow-up, and safety evaluation. At baseline, comorbidity was measured with the Charlson Comorbidity Index (CCI). Frailty was measured with the Clinical Frailty Scale (CFS). Results: Overall, 43 patients with a median age of 88 years underwent FMT by colonoscopy in the study period. The rate of first FMT success was 77%. Five of the 10 patients who failed the first FMT infusion were cured after repeat FMT, with an overall efficacy of 88%. In patients with successful treatment, the CFS was significantly lower compared to those who failed the FMT or underwent repeat FMT (p < 0.01 for both). Mild adverse events occurred in 11 patients (25%). One death, not related to FMT or rCDI, occurred within 7 days from the first procedure. Conclusions: FMT is effective and safe in very old patients. Frailty and high comorbidity do not limit use of FMT in these patients. Frailty assessment has potential to better identify patients at higher risk of worse outcomes or for repeat treatment with FMT.

The long-term impact of COVID-19 disease is becoming a major global concern. In this retrospective monocentric analysis, we included consecutive subjects admitted to our COVID-19 Post-Acute Care Service for a SARS-CoV-2 infection that occurred between three and twelve months before. A home medication list relative to the period before SARS-CoV-2 infection (baseline) was recorded and compared with that one relative to the time of outpatient visit (follow-up). Drugs were coded according to the Anatomical Therapeutic Chemical Classification (ATC) System. In a total of 2007 subjects, at follow-up, a significant increase with respect to baseline was reported in the total median number of chronic medications (two [0–4] vs. one [0–3]) and in specific ATC-group drugs involving the alimentary, blood, cardiovascular, genitourinary, muscle–skeletal, nervous and respiratory systems. In a multivariate analysis, COVID-19 disease severity and age > 65 years resulted in the best predictors for an increase in the number of medications, while anti-SARS-CoV-2 vaccination played a significant protective role. The long-term care of patients infected by COVID-19 may be more complex than reported so far. Multidisciplinary and integrated care pathways should be encouraged, mainly in older and frailer subjects and for patients experiencing a more severe disease. Vaccination may also represent a fundamental protection against long-term sequelae.

We adopt and extend the new Zenga inequality curve to study the degree of progressivity as well as the redistributive and re-ranking effects of a personal income tax system. Moreover, we also establish the social welfare implications of these new inequality measures and compare them with the classical approach based on the Lorenz curve and the Gini coefficient. The Zenga methodology is based on comparing the mean income of the poorest income earners with the mean income of the remaining richest part of the population. To the best of our knowledge, this approach has never been applied to study the effects produced by a personal income tax. To fill this gap in the literature, we prove that the elasticity of the Zenga uniformity curve with respect to the Lorenz curve is always greater than 1, thus recasting—within the new paradigm—the most important curves and the corresponding tax indices, such as the Reynolds–Smolensky, the Kakwani, and the Atkinson–Plotnick–Kakwani indices. We then derive three important inequalities for the newly developed measures, inspired by the well-known properties of the classical approach. Finally, we show how some information, which could remain unnoticed by the cumulative approach inherent to the Lorenz curve, is instead highlighted by the new methodology. The advantages of complementing the classic indices with the new ones are discussed through an application to the Italian tax system.

The empirical exercise conducted in this chapter is the first attempt towards an understanding of the relationship between the rulings of the Courts of Human Rights and voter turnout. Participation of voters is essential for democracy, and the judgments of the Courts of Human Rights, both in Europe and Latin America, guarantee a legal framework for free and democratic elections. Our empirical analysis, based on an original dataset including information on voter turnout for all countries under the jurisdiction of the ECHR and the IACHR and all the judgments of the two Courts, provides evidence of a positive correlation between judgments and turnout for European countries, albeit it turns negative when considering countries which were formerly part of Yugoslavia and countries belonging to the former Warsaw Pact. The general conclusion is that decisions might be a sign of substantial violations of voting rights in these countries, which in turn reduces the incentive to participate for voters. On the contrary, for most Western countries, ECHR decisions might be a sign of a strong interest by voters in participation. The Latin American experience appear to be different, military dictatorships seem to matter; but the small number of judgments suggest caution when interpreting correlation results. Future research should address these issues further in order to understand what mechanisms drive the correlations we have just begun to uncover.