The impact of carbon based materials on hippocampal cells: from neurons to networks.

Tissue engineering and regenerative medicine require the constant development of synthetic materials to manufacture scaffolds thatbetter integrate into the target tissues (O\u2019Brien, 2011; Ku et al, 2013; Harrison et al, 2014). In this framework, newly synthesized nanomaterials made of pure carbon, in particular Carbon Nanotubes (Ijima, 1991) and Graphene (Novoselov et al, 2004) applications to biology received particular attention due to their outstanding physicochemical properties (Hirsch, 2010). Our team has performed pioneer works during the last decade, about the interactions of neural cells with carbon nanotubes (Lovat et al, 2005; Mazzatenta et al, 2007; Cellot et al, 2009; Cellot et al, 2011; Fabbro et al, 2012; Bosi et al, 2015), and with graphene (Fabbro et al, 2015; Rauti et al, 2016) or, more in general, with synthetic substrates (Cellot et al, 2016). The major aim of my work has been to use traditional and novel physiology tools to investigate further these \u201cneuro-hybrid systems\u201d, and to understand how far Carbon Nanotubes and Graphene can be pushed in neuroscience applications. With this aim, in the first part of my PhD I further elucidated the behavior of newly formed synapses in primary dissociated neurons when interfaced to bi-dimensional substrates of Multi-walled Carbon Nanotubes. I then addressed the homeostasis of invitro neural networks interfaced to pure graphene and I characterized for the first time the changes induced by this material in neurons. As last step, I set up a more complex biological in-vitro model, consisting of lesioned organotypic Entorhinal-Hippocampal cultures (Perederiy and Westbrook, 2013) and we described the regenerative features of Carbon Nanotubes in this lesion model. During my PhD I was also involved in two side projects: in the first one, in collaboration with Sebastian Reinhartz and Matthew Diamond (SISSA), we refine the possible approaches of the optogenetic technique, by manipulating neuronal responses with different light waveforms (Reinhartz et al, MS in preparation, in the appendix). In the second one, in collaboration with the group of Manus Biggs, from the National University of Galway, Ireland, we tested the biocompatibility and addressed the neural behavior of primary neural cells interfaced with Indium Tin Oxide (ITO) substrates with different roughness, thickness and conducting profiles (Vallejo-Giraldo et al, 2017)

Advances in Nano Neuroscience: From Nanomaterials to Nanotools

During the last decades, neuroscientists have increasingly exploited a variety of artificial, de-novo synthesized materials with controlled nano-sized features. For instance, a renewed interest in the development of prostheses or neural interfaces was driven by the availability of novel nanomaterials that enabled the fabrication of implantable bioelectronics interfaces with reduced side effects and increased integration with the target biological tissue. The peculiar physical-chemical properties of nanomaterials have also contributed to the engineering of novel imaging devices toward sophisticated experimental settings, to smart fabricated scaffolds and microelectrodes, or other tools ultimately aimed at a better understanding of neural tissue functions. In this review, we focus on nanomaterials and specifically on carbon-based nanomaterials, such as carbon nanotubes (CNTs) and graphene. While these materials raise potential safety concerns, they represent a tremendous technological opportunity for the restoration of neuronal functions. We then describe nanotools such as nanowires and nano-modified MEA for high-performance electrophysiological recording and stimulation of neuronal electrical activity. We finally focus on the fabrication of three-dimensional synthetic nanostructures, used as substrates to interface biological cells and tissues in vitro and in vivo

Study of the snow melt–freeze cycle using multi-sensor data and snow modelling

The melt cycle of snow is investigated by combining ground-based microwave radiometric measurements with conventional and meteorological data and by using a hydrological snow model. Measurements at 2000 m a.s.l in the basin of the Cordevole river in the eastern Italian Alps confirm the high sensitivity of microwave emission at 19 and 37 GHz to the snow melt–freeze cycle, while the brightness at 6.8 GHz is mostly related to underlying soil. Simulations of snowpack changes performed by means of hydrological and electromagnetic models, driven with meteorological and snow data, provide additional insight into these processes and contribute to the interpretation of the experimental data

Exploiting the ANN Potential in Estimating Snow Depth and Snow Water Equivalent From the Airborne SnowSAR Data at X- and Ku-Bands

Within the framework of European Space Agency (ESA) activities, several campaigns were carried out in the last decade with the purpose of exploiting the capabilities of multifrequency synthetic aperture radar (SAR) data to retrieve snow information. This article presents the results obtained from the ESA SnowSAR airborne campaigns, carried out between 2011 and 2013 on boreal forest, tundra and alpine environments, selected as representative of different snow regimes. The aim of this study was to assess the capability of X- and Ku-bands SAR in retrieving the snow parameters, namely snow depth (SD) and snow water equivalent (SWE). The retrieval was based on machine learning (ML) techniques and, in particular, of artificial neural networks (ANNs). ANNs have been selected among other ML approaches since they are capable to offer a good compromise between retrieval accuracy and computational cost. Two approaches were evaluated, the first based on the experimental data (data driven) and the second based on data simulated by the dense medium radiative transfer (DMRT). The data driven algorithm was trained on half of the SnowSAR dataset and validated on the remaining half. The validation resulted in a correlation coefficient R ≃ 0.77 between estimated and target SD, a root-mean-square error (RMSE) ≃ 13 cm, and bias = 0.03 cm. ANN algorithms specific for each test site were also implemented, obtaining more accurate results, and the robustness of the data driven approach was evaluated over time and space. The algorithm trained with DMRT simulations and tested on the experimental dataset was able to estimate the target parameter (SWE in this case) with R = 0.74, RMSE = 34.8 mm, and bias = 1.8 mm. The model driven approach had the twofold advantage of reducing the amount of in situ data required for training the algorithm and of extending the algorithm exportability to other test sites

Single-layer graphene modulates neuronal communication and augments membrane ion currents

The use of graphenebased materials to engineer sophisticated biosensing interfaces that can adapt to the central nervous system requires a detailed understanding of how such materials behave in a biological context. Graphene's peculiar properties can cause various cellular changes, but the underlying mechanisms remain unclear. Here, we show that singlelayer graphene increases neuronal firing by altering membraneassociated functions in cultured cells. Graphene tunes the distribution of extracellular ions at the interface with neurons, a key regulator of neuronal excitability. The resulting biophysical changes in the membrane include stronger potassium ion currents, with a shift in the fraction of neuronal firing phenotypes from adapting to tonically firing. By using experimental and theoretical approaches, we hypothesize that the graphene\u2013ion interactions that are maximized when singlelayer graphene is deposited on electrically insulating substrates are crucial to these effects

A New Computational Tool for the Phenomenological Analysis of Multipassage Tumor Growth Curves

Multipassage experiments are performed by subcutaneous implantation in lab animals (usually mice) of a small number of cells from selected human lines. Tumor cells are then passaged from one mouse to another by harvesting them from a growing tumor and implanting them into other healthy animals. This procedure may be extremely useful to investigate the various mechanisms involved in the long term evolution of tumoral growth. It has been observed by several researchers that, contrary to what happens in in vitro experiments, there is a significant growth acceleration at each new passage. This result is explained by a new method of analysis, based on the Phenomenological Universalities approach. It is found that, by means of a simple rescaling of time, it is possible to collapse all the growth curves, corresponding to the successive passages, into a single curve, belonging to the Universality Class U2. Possible applications are proposed and the need of further experimental evidence is discussed

Microwave radiometry in monitoring and emergency mapping of water seepage and dangerously high groundwaters, Journal of Telecommunications and Information Technology, 2007, nr 1

Detailed and geo-referenced maps identifying the locations of saturated and dry levees can be produced using microwave radiometric measurements from a light aircraft or helicopter, and integrated with GPS for positioning and orientation. The development of synergetic remote sensing technology for raised groundwater and seepage detection by the joint use of microwave and optical data along with GIS databases is an effective and most contemporary way of supporting risk assessment and facilitating disaster prevention and management. In this paper we present a remote sensing microwave technology for monitoring and detection of areas of water seepage through irrigation constructions, levees and dykes as well as for revealing areas with dangerously high groundwater level. The possibility for emergency response mapping, integrated with GPS and GIS data, facilitates the risk assessment and management services. The passive microwave radiometry (PMR) is based on spectral measurements in the millimetre to decimetre range of wavelengths. Compared to other remote sensing techniques, such as colour and infrared photography, thermal images and lidar, PMR is the only technology taking measurements under the earth’s surface and therefore is very well suited for water seepage and underground water monitoring in a fast and reliable way

La restauración del Retrato Trivulzio de Antonello da Messina

El artículo presenta la intervención llevada a cabo en 2006 sobre el Retrato de hombre de Antonello da Messina, que pertenece a las colecciones del Museo Cívico de Arte Antiguo del Palacio Madame. The article presents the intervention carried out in 2006 about the Portrait of a man of Antonello da Messina, which belongs to the collections of the Civic Museum of Ancient Art of the Madame Palace.El artículo presenta la intervención llevada a cabo en 2006 sobre el Retrato de hombre de Antonello da Messina, que pertenece a las colecciones del Museo Cívico de Arte Antiguo del Palacio Madame.&nbsp

Proposal for the Global Boundary Stratotype Section and Point (GSSP) for the Priabonian Stage (Eocene) at the Alano section (Italy)

The base of the Priabonian Stage is one of two stage boundaries in the Paleogene that remains to be formalized. The Alano section (NE Italy) was elected by consensus as a suitable candidate for the base of the Priabonian during the Priabonian Working Group meeting held in Alano di Piave in June 2012. Further detailed research on the section is now followed by a formal proposal, which identifies the base of a prominent crystal tuff layer, the Tiziano bed, at meter 63.57 of the Alano section, as a suitable candidate for the Priabonian Stage. The choice of the Tiziano bed is appropriate from the historical point of view and several bio-magnetostratigraphic events are available to approximate this chronostratigraphic boundary and guarantee a high degree of correlatability over wide geographic areas. Events which approximate the base of the Priabonian Stage in the Alano section are the successive extinction of large acarininids and Morozovelloides (planktonic foraminifera), the Base of common and continuous Cribrocentrum erbae and the Top of Chiasmolithus grandis (nannofossils), as well as the Base of Subchron C17n.2n and the Base of Chron C17n (magnetostratigraphy). Cyclostratigraphic analysis of the Bartonian-Priabonian transition of the Alano section as well as radioisotopic data of the Tiziano tuff layer provide an absolute age (37.710 – 37.762 Ma, respectively) of this bed and, consequently, of the base of the Priabonian Stage

Radiometric Microwave Indices for Remote Sensing of Land Surfaces

This work presents an overview of the potential of microwave indices obtained from multi-frequency/polarization radiometry in detecting the characteristics of land surfaces, in particular soil covered by vegetation or snow and agricultural bare soils. Experimental results obtained with ground-based radiometers on different types of natural surfaces by the Microwave Remote Sensing Group of IFAC-CNR starting from ‘80s, are summarized and interpreted by means of theoretical models. It has been pointed out that, with respect to single frequency/polarization observations, microwave indices revealed a higher sensitivity to some significant parameters, which characterize the hydrological cycle, namely: soil moisture, vegetation biomass and snow depth or snow water equivalent. Electromagnetic models have then been used for simulating brightness temperature and microwave indices from land surfaces. As per vegetation covered soils, the well-known tau-omega (τ-ω) model based on the radiative transfer theory has been used, whereas terrestrial snow cover has been simulated using a multi-layer dense-medium radiative transfer model (DMRT). On the basis of these results, operational inversion algorithms for the retrieval of those hydrological quantities have been successfully implemented using multi-channel data from the microwave radiometric sensors operating from satellite