Nanostructured substrates to control the Embryonic Stem cells differentiation into neuronal lineage

2010/2011The objective of this project was to develop new nanotechnology-based strategies to increase embryonic stem cells (ESCs) differentiation into neuronal lineage. In particular it was chosen to investigate a nanostructured physical support for in vitro stem cell culture in which both the nanometrical topography and mechanical properties are well controlled and characterized. Nanopatterned substrates were designed to have physical properties as close as possible to the in vivo microenvironment where stem cells normally grow and differentiate based on the assumption that mimicking the natural niche equilibrium is of fundamental importance for stem cell fate. First, an original nanotechnological approach to fabricate the substrates for in vitro neuronal precursors culture was developed. Secondly the substrate geometrical and mechanical parameters were optimized in order to achieve the maximum differentiation yield of ESCs-derived neuronal precursors (NPs). It was reached a neuronal yield of 74±7% at 48 hours after NPs differentiation induction, which represents the highest yield ever published using nanopatterned substrates with controlled and highthroughput reproducible nanometrical features for cell culture. Moreover it was demonstrated that the mechanical properties of the substrate play a major role with respect to other parameters, such as substrate composition and geometry. A time-dependent analysis showed that the first hours after cell seeding are crucial in the determination of the final differentiation yield. A further control of ESCs differentiation by manipulating the substrates physical parameters, required a deep understanding of the cell-substrate interaction, therefore it was studied the behavior of neuronal precursors when placed and grown on different artificial substrates using atomic force microscope, scanning electron microscope, and single cell force spectroscopy measurements. The latter lead to a quantification of the forces that develop between neuronal precursors and substrate and provided a clear relationship between adhesion forces and differentiation. My results suggested the importance of the physical parameter involved in the regulation of the neuronal differentiation and to new guidelines for future applications in regenerative medicine.XXIV Ciclo198

Practical guide to characterize biomolecule adsorption on solid surfaces (Review)

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Tracking Data Provenance of Archaeological Temporal Information in Presence of Uncertainty

The interpretation process is one of the main tasks performed by archaeologists who, starting from ground data about evidences and findings, incrementally derive knowledge about ancient objects or events. Very often more than one archaeologist contributes in different time instants to discover details about the same finding and thus, it is important to keep track of history and provenance of the overall knowledge discovery process. To this aim, we propose a model and a set of derivation rules for tracking and refining data provenance during the archaeological interpretation process. In particular, among all the possible interpretation activities, we concentrate on the one concerning the dating that archaeologists perform to assign one or more time intervals to a finding to define its lifespan on the temporal axis. In this context, we propose a framework to represent and derive updated provenance data about temporal information after the mentioned derivation process. Archaeological data, and in particular their temporal dimension, are typically vague, since many different interpretations can coexist, thus, we will use Fuzzy Logic to assign a degree of confidence to values and Fuzzy Temporal Constraint Networks to model relationships between dating of different findings represented as a graph-based dataset. The derivation rules used to infer more precise temporal intervals are enriched to manage also provenance information and their following updates after a derivation step. A MapReduce version of the path consistency algorithm is also proposed to improve the efficiency of the refining process on big graph-based datasets

Tracking social provenance in chains of retweets

In the era of massive sharing of information, the term social provenance is used to denote the ownership, source or origin of a piece of information which has been propagated through social media. Tracking the provenance of information is becoming increasingly important as social platforms acquire more relevance as source of news. In this scenario, Twitter is considered one of the most important social networks for information sharing and dissemination which can be accelerated through the use of retweets and quotes. However, the Twitter API does not provide a complete tracking of the retweet chains, since only the connection between a retweet and the original post is stored, while all the intermediate connections are lost. This can limit the ability to track the diffusion of information as well as the estimation of the importance of specific users, who can rapidly become influencers, in the news dissemination. This paper proposes an innovative approach for rebuilding the possible chains of retweets and also providing an estimation of the contributions given by each user in the information spread. For this purpose, we define the concept of Provenance Constraint Network and a modified version of the Path Consistency Algorithm. An application of the proposed technique to a real-world dataset is presented at the end of the paper

CoPart: a context-based partitioning technique for big data

The MapReduce programming paradigm is frequently used in order to process and analyse a huge amount of data. This paradigm relies on the ability to apply the same operation in parallel on independent chunks of data. The consequence is that the overall performances greatly depend on the way data are partitioned among the various computation nodes. The default partitioning technique, provided by systems like Hadoop or Spark, basically performs a random subdivision of the input records, without considering the nature and correlation between them. Even if such approach can be appropriate in the simplest case where all the input records have to be always analyzed, it becomes a limit for sophisticated analyses, in which correlations between records can be exploited to preliminarily prune unnecessary computations. In this paper we design a context-based multi-dimensional partitioning technique, called COPART, which takes care of data correlation in order to determine how records are subdivided between splits (i.e., units of work assigned to a computation node). More specifically, it considers not only the correlation of data w.r.t. contextual attributes, but also the distribution of each contextual dimension in the dataset. We experimentally compare our approach with existing ones, considering both quality criteria and the query execution times

A Context-Aware Recommendation System with a Crowding Forecaster

Recommendation systems (RSs) are increasing their popularity in recent years. Many big IT companies like Google, Amazon and Netflix, have a RS at the core of their business. In this paper, we propose a modular platform for enhancing a RS for the tourism domain with a crowding forecaster, which is able to produce an estimation about the current and future occupation of different Points of Interest (PoIs) by taking into consideration also contextual aspects. The main advantage of the proposed system is its modularity and the ability to be easily tailored to different application domains. Moreover, the use of standard and pluggable components allows the system to be integrated in different application scenarios

Enhanced Biological Activity of BMP‐2 Bound to Surface‐Grafted Heparan Sulfate

Over the last decade, there has been a growing interest in the development of new materials to improve bone morphogenetic protein‐2 (BMP‐2) delivery for tissue regeneration. This study reports the development and application of model surfaces that present BMP‐2 via heparan sulfate (HS), a ubiquitous component of the extracellular matrix (ECM). On these surfaces, HS is grafted by its reducing end, to mimic the natural arrangement of HS proteoglycans in the ECM. The binding of each component on these biomimetic surfaces is highly controlled, in terms of stoichiometry of molecules and BMP‐2/grafted‐HS affinity, as determined by surface‐sensitive techniques. For comparison, this study also uses surfaces presenting immobilized BMP‐2 alone. Functional validations of the surfaces are performed using a murine myoblast cell line (C2C12) and primary human mesenchymal stromal cells. In both cell types, HS‐bound BMP‐2 and surface‐immobilized BMP‐2 significantly prolong SMAD 1/5 phosphorylation, compared to BMP‐2 added to the culture media. Moreover, HS‐bound BMP‐2 enhances p‐SMAD 1/5 levels in C2C12 cells and reduces noggin antagonistic activity. Thus, grafted HS positively affects BMP‐2 cellular activity. This innovative surface design, which mimics natural interactions of growth factors with ECM components, constitutes a promising candidate for future regenerative medicine applications

Attenuated inflammatory response of monocyte-derived macrophage from patients with BD : a preliminary report

Background: Innate immune system dysfunction has been recognized as an important element in the pathophysiology of bipolar disorder (BD). We aimed to investigate whether there are differences in the response of macrophages derived from patients in the early stages and late stages of BD and healthy subjects. Methods: Human monocytes purified from peripheral blood mononuclear cells (PBMCs) of patients with BD type I (n = 18)—further classified into early- and late stage BD patients according to their functioning- and from healthy individuals (n = 10) were differentiated into macrophages in vitro. Monocyte-derived macrophages (M) were exposed to IFNγ plus LPS-M(IFNγ + LPS)- or IL-4-M(IL-4)—to induce their polarization into the classical (also called M1) or alternative (also called M2) activation phenotypes, respectively; or either Mψ were not exposed to any stimuli characterizing the resting state (denominated M0). In vitro secretion of cytokines, such as IL-1β, IL-6, IL-10, and TNF-α, was used as an index of macrophage activity. Results: M(IFNγ + LPS) from late-stage BD patients produced less amount of IL-1β, IL-6, and IL-10 when compared to early-stage BD patients and healthy controls. Following alternative activation, M(IL-4) derived from late-stage patients secreted less IL-6 compared to the other groups. TNFα was less secreted by all macrophage phenotypes derived from late-stage patients when compared to healthy controls only (p < 0.005). Mψ from late-stage patients exhibited lower production of IL-1β and IL-10 compared to macrophages from healthy subjects and early-stage patients respectively. Interestingly, cytokines secretion from M(IFNγ + LPS), M(IL-4) and Mψ were similar between early-stage patients and healthy controls. Conclusion: Our results suggest a progressive dysfunction in the response of peripheral innate immune cells of BD patients in the late stages of the illness. This failure in the regulation of the immune system function may be implicated in the multisystemic progression of BD