A new procedure to analyze RNA non-branching structures

RNA structure prediction and structural motifs analysis are challenging tasks in the investigation of RNA function. We propose a novel procedure to detect structural motifs shared between two RNAs (a reference and a target). In particular, we developed two core modules: (i) nbRSSP_extractor, to assign a unique structure to the reference RNA encoded by a set of non-branching structures; (ii) SSD_finder, to detect structural motifs that the target RNA shares with the reference, by means of a new score function that rewards the relative distance of the target non-branching structures compared to the reference ones. We integrated these algorithms with already existing software to reach a coherent pipeline able to perform the following two main tasks: prediction of RNA structures (integration of RNALfold and nbRSSP_extractor) and search for chains of matches (integration of Structator and SSD_finder)

Linking CGE and Microsimulation Models: A Comparison of Different Approaches

In the paper we describe in detail how to build linked CGE-microsimulation models (using fictitious data) following three main approaches: one in accordance with the fully integrated approach and the other two according to the layered approach – the so-called Top-Down and Top-Down/Bottom-Up approaches. After this, we implement the same policy reform in each of the three models. Results show that all three approaches yield different results especially in terms of income distribution and poverty, although analysed within the same economy and under the same policy simulation. We then analyse in more detail the TD/BU approach as developed by Savard (2003) and, in order to avoid possible deviations due to data inconsistencies, we propose an alternative way of taking into account feedback effects from the micro level of analysis into the CGE model. --CGE models,microsimulation,income distribution

SWIM: A computational tool to unveiling crucial nodes in complex biological networks

SWItchMiner (SWIM) is a wizard-like software implementation of a procedure, previously described, able to extract information contained in complex networks. Specifically, SWIM allows unearthing the existence of a new class of hubs, called "fight-club hubs", characterized by a marked negative correlation with their first nearest neighbors. Among them, a special subset of genes, called "switch genes", appears to be characterized by an unusual pattern of intra- and inter-module connections that confers them a crucial topological role, interestingly mirrored by the evidence of their clinic-biological relevance. Here, we applied SWIM to a large panel of cancer datasets from The Cancer Genome Atlas, in order to highlight switch genes that could be critically associated with the drastic changes in the physiological state of cells or tissues induced by the cancer development. We discovered that switch genes are found in all cancers we studied and they encompass protein coding genes and non-coding RNAs, recovering many known key cancer players but also many new potential biomarkers not yet characterized in cancer context. Furthermore, SWIM is amenable to detect switch genes in different organisms and cell conditions, with the potential to uncover important players in biologically relevant scenarios, including but not limited to human cancer

Linking CGE and Microsimulation Models : a Comparison of Different Approaches

In the paper we describe in detail how to build linked CGE-microsimulation models (using fictitious data) following three main approaches: one in accordance with the fully integrated approach and the other two according to the layered approach – the so-called Top-Down and Top-Down/Bottom-Up approaches. After this, we implement the same policy reform in each of the three models. Results show that all three approaches yield different results especially in terms of income distribution and poverty, although analysed within the same economy and under the same policy simulation. We then analyse in more detail the TD/BU approach as developed by Savard (2003) and, in order to avoid possible deviations due to data inconsistencies, we propose an alternative way of taking into account feedback effects from the micro level of analysis into the CGE model

LINKING CGE AND MICROSIMULATION MODELS: METHODOLOGICAL AND APPLIED ISSUES

Questa tesi offre una descrizione dettagliata di come i modelli di equilibrio generale computazionale (CGE) ed i modelli di microsimulazione possano essere utilizzati congiuntamente, partendo dalla letteratura piú recente sull'argomento, e focalizzando l'attenzione in particolare sulla letteratura riguardante i paesi in via di sviluppo. La ragione principale per la quale questi modelli vengono utilizzati congiuntamente risiede nel fatto che il ricercatore vuole essere in grado di studiare contemporaneamente l'eterogeneità degli agenti economici e la complessità della distribuzione del reddito, ed allo stesso tempo di valutare gli effetti macroeconomici delle riforme. Nell'ultimo capitolo costruiamo un modello CGE-microsimulazione per l'economia del Nicaragua. Esso si rivela particolarmente adatto alla riforma di politica economica che vogliamo simulare: l'accordo di libero scambio commerciale tra i paesi dell'America Centrale e gli Stati Uniti è infatti una riforma di tipo macroeconomico, la quale potrebbe tuttavia avere effetti significativi sulla distribuzione del reddito. Con questo modello analizzeremo quindi gli effetti dell'accordo commerciale con gli Stati Uniti sulla distribuzione del reddito in Nicaragua. I risultati dell'analisi registrano soltanto piccole variazioni sia nelle principali variabili macroeconomiche che nella distribuzione del reddito e negli indici di povertà.This thesis wants to give an assessment and a detailed description of how Computable General Equilibrium (CGE) and microsimulation models can be linked together, taking inspiration from the current literature, with a special focus concerning the literature on developing countries. The main reason why these models are linked together is that the modeller wants to be able to take into account full agents' heterogeneity and the complexity of income distribution, and at the same time to analyse the macroeconomic effects of the policy reforms. In the last chapter, we build a CGE-microsimulation model for the economy of Nicaragua. This model appears to be particularly suited to the policy reform we are willing to simulate with the model: the Free Trade Agreement of Central American countries with USA is mainly a macroeconomic reform, which on the other hand can have important effects on the distribution of income and on poverty. With such a model we will study the possible changes in the distribution of income in Nicaragua deriving from the Free Trade Agreement with USA. Our analysis finds only small changes both in the main macroeconomic variables and in the distribution of income and poverty indices

Targeting tumor angiogenesis with TSP-1-based compounds: rational design of antiangiogenic mimetics of endogenous inhibitors

Inhibitors of angiogenesis are an important addition to conventional chemotherapy. Among different “druggable” angiogenic factors, fibroblast growth factor-2 (FGF-2) is an attractive target for novel therapies because of its intricated involvement in tumor neovascularization, tumor cell proliferation and migration, and the acquisition of resistance to antiangiogenic therapies. FGF-2 bioavailability and activity is affected by several natural ligands, including the endogenous inhibitor of angiogenesis thrombospondin-1 (TSP-1). We hypothesized that the FGF-2-binding sequence of TSP-1 might serve as a template for the development of non-peptide inhibitors of angiogenesis. Computational biology and nuclear magnetic resonance spectroscopy approaches, major investigative tools in the characterizations of protein-protein interaction (PPI), were used to map the residues at the TSP-1/FGF-2 interface. The translation of this three-dimensional information into a pharmacophore model allowed screening a small molecule databases, identifying three FGF-2-binding, antiangiogenic small molecules, mimetic of TSP-1. Pharmacophore-based approaches are thus feasible tools to exploit naturally occurring PPI, by generating a set of lead compounds mimetic of endogenous proteins, as a starting point for the development of novel therapeutic agents

Investigating dynamic and energetic determinants of protein nucleic acid recognition: analysis of the zinc finger zif268-DNA complexes

<p>Abstract</p> <p>Background</p> <p>Protein-DNA recognition underlies fundamental biological processes ranging from transcription to replication and modification. Herein, we present a computational study of the sequence modulation of internal dynamic properties and of intraprotein networks of aminoacid interactions that determine the stability and specificity of protein-DNA complexes.</p> <p>Results</p> <p>To this aim, we apply novel theoretical approaches to analyze the dynamics and energetics of biological systems starting from MD trajectories. As model system, we chose different sequences of Zinc Fingers (ZF) of the Zif268 family bound with different sequences of DNA. The complexes differ for their experimental stability properties, but share the same overall 3 D structure and do not undergo structural modifications during the simulations. The results of our analysis suggest that the energy landscape for DNA binding may be populated by dynamically different states, even in the absence of major conformational changes. Energetic couplings between residues change in response to protein and/or DNA sequence variations thus modulating the selectivity of recognition and the relative importance of different regions for binding.</p> <p>Conclusions</p> <p>The results show differences in the organization of the intra-protein energy-networks responsible for the stabilization of the protein conformations recognizing and binding DNA. These, in turn, are reflected into different modulation of the ZF's internal dynamics. The results also show a correlation between energetic and dynamic properties of the different proteins and their specificity/selectivity for DNA sequences. Finally, a dynamic and energetic model for the recognition of DNA by Zinc Fingers is proposed.</p

Challenge your Brain. Blogging during the COVID Lockdown as a Way to Enhance Well-Being and Cognitive Reserve in an Older Population

Background: The lockdown linked with COVID-19 restrictions has been reported to have severe consequences at an emotional and cognitive level, this was especially true for vulnerable populations, such as the older adults. This study aims at exploring the effect of a blog-based intervention implemented during COVID lockdown to increase the perceived well-being and cognitive reserve (CR) of a sample of American older adults. Methods: Forty-one participants (63% female), age range from 64 to 83, participated in a blog-based 5-week intervention. Their level of well-being as well as cognitive reserve were assessed before and after the intervention with specific scales. Participants were matched by age, gender and education level to a quasi-equivalent control group living in the same area who was tested on the same variables. Results: Results showed a significant increase in both perceived well-being and CR in the intervention group. A significant difference was also found when comparing the intervention group to the matched controls.publishedVersio

dose administration maneuvers and patient care in tobramycin dry powder inhalation therapy

Abstract The purpose of this work was to study a new dry powder inhaler (DPI) of tobramycin capable to simplify the dose administration maneuvers to maximize the cystic fibrosis (CF) patient care in antibiotic inhalation therapy. For the purpose, tobramycin/sodium stearate powder (TobraPS) having a high drug content, was produced by spray drying, characterized and the aerodynamic behavior was investigated in vitro using different RS01 DPI inhalers. The aerosols produced with 28, 56 or 112 mg of tobramycin in TobraPS powder using capsules size #3, #2 or #0 showed that there was quasi linear relationship between the amount loaded in the device and the FPD. An in vivo study in healthy human volunteers showed that 3–6 inhalation acts were requested by the volunteers to inhale 120 mg of TobraPS powder loaded in a size #0 capsule aerosolized with a prototype RS01 device, according to their capability to inhale. The amount of powder emitted at 4 kPa pressure drop at constant air flow well correlated with the in vivo emission at dynamic flow, when the same volume of air passed through the device. The novel approach for the administration of 112 mg of tobramycin in one capsule could improve the convenience and adherence of the CF patient to the antibiotic therapy