Dispersion Behaviour of Silica Nanoparticles in Biological Media and Its Influence on Cellular Uptake

Given the increasing variety of manufactured nanomaterials, suitable, robust, standardized in vitro screening methods are needed to study the mechanisms by which they can interact with biological systems. The in vitro evaluation of interactions of nanoparticles (NPs) with living cells is challenging due to the complex behaviour of NPs, which may involve dissolution, aggregation, sedimentation and formation of a protein corona. These variable parameters have an influence on the surface properties and the stability of NPs in the biological environment and therefore also on the interaction of NPs with cells. We present here a study using 30 nm and 80 nm fluorescently-labelled silicon dioxide NPs (Rubipy-SiO2 NPs) to evaluate the NPs dispersion behaviour up to 48 hours in two different cellular media either supplemented with 10% of serum or in serum-free conditions. Size-dependent differences in dispersion behaviour were observed and the influence of the living cells on NPs stability and deposition was determined. Using flow cytometry and fluorescence microscopy techniques we studied the kinetics of the cellular uptake of Rubipy-SiO2 NPs by A549 and CaCo-2 cells and we found a correlation between the NPs characteristics in cell media and the amount of cellular uptake. Our results emphasize how relevant and important it is to evaluate and to monitor the size and agglomeration state of nanoparticles in the biological medium, in order to interpret correctly the results of the in vitro toxicological assays.JRC.I.4-Nanobioscience

Modulation of surface bio-functionality by using gold nanostructures on protein repellent surfaces

The integration of gold nanoparticles (Au NPs) or nanostructures with special optical properties on solid surfaces has become a major research topic in the field of nanobiotechnology in particular for the development of new generation of multifunctional bioanalytical platforms. This has led to considerable research efforts for developing quick and direct nanofabrication methods capable of producing well-ordered 2D nanostructured arrays with tunable morphological, chemical and optical properties. In this paper, we propose a simple and fast nanofabrication method enabling the creation of Au NPs patterns on a non-adhesive and cell repellent plasma-deposited poly(ethyleneoxide) (PEO-like) coating. The immobilization of Au NPs on PEO-like coatings does not require any prior chemical modifications and is achieved by a straightforward and stable self-assembly technique. By varying the size and the concentration of the Au NPs it is possible to control the Au NPs density and spatial distribution on the PEO-like coated surface with direct effects on the bio-functionality of the surface. These nanostructured surfaces have been tested for protein bio-recognition analysis and as a cell culture platform. The developed nanostructured platform has many potential applications in the field of protein-nanoparticle and cell-nanoparticle interaction studies, nanotoxicology and bioengineering.JRC.I.4-Nanobioscience

Joint Super-Resolved Compressive Sensing and Encryption for Earth Observation Applications

Session 4A-Magli-Joint Super-Resolved Compressive Sensing and Encryption for Earth Observation Application

DeepSUM++: Non-local Deep Neural Network for Super-Resolution of Unregistered Multitemporal Images

Deep learning methods for super-resolution of a remote sensing scene from multiple unregistered low-resolution images have recently gained attention thanks to a challenge proposed by the European Space Agency. This paper presents an evolution of the winner of the challenge, showing how incorporating non-local information in a convolutional neural network allows to exploit self-similar patterns that provide enhanced regularization of the super-resolution problem. Experiments on the dataset of the challenge show improved performance over the state-of-the-art, which does not exploit non-local information.Comment: arXiv admin note: text overlap with arXiv:1907.0649

Towards Deep Unsupervised SAR Despeckling with Blind-Spot Convolutional Neural Networks

SAR despeckling is a problem of paramount importance in remote sensing, since it represents the first step of many scene analysis algorithms. Recently, deep learning techniques have outperformed classical model-based despeckling algorithms. However, such methods require clean ground truth images for training, thus resorting to synthetically speckled optical images since clean SAR images cannot be acquired. In this paper, inspired by recent works on blind-spot denoising networks, we propose a self-supervised Bayesian despeckling method. The proposed method is trained employing only noisy images and can therefore learn features of real SAR images rather than synthetic data. We show that the performance of the proposed network is very close to the supervised training approach on synthetic data and competitive on real data

Raman spectroscopy of gallium ion irradiated graphene

The successful integration of graphene in future technologies, such as filtration and nanoelectronics, depends on the ability to introduce controlled nanostructured defects in graphene. In this work, Raman spectroscopy is used to investigate the induction of disorder in graphene via gallium ion beam bombardment. Two configurations of CVD-grown graphene samples are used: (i) graphene supported on a Si/SiO2 substrate, and (ii) graphene suspended on porous TEM grids. It is observed that the supported graphene experiences more damage in response to lower beam doses than suspended graphene. This phenomenon is attributed to the behaviour of the energetic ions impinging the sample. In suspended graphene, the ions pass through the graphene membrane once and disperse to the atmosphere, while in supported graphene, the ions embed themselves in the substrate causing swelling and backscattering events, hence increasing the induced disorder. In supported graphene, the ratio between the Gaussian D and G peaks attributed to amorphous carbon, and the Lorentzian D and G peaks attributed to graphene, (IDG/IDL) and (IGG/IGL), are suggested to be used to quantify the degree of amorphization. The results are relevant to the development of nanostructured graphene-based filtration or desalination membranes, as well as for graphene-based nanoelectronics.JRC.F.2-Consumer Products Safet

Onboard Processing Capabilities of an Earth Observation Compressive Sensing Payload

In this paper, we explore the onboard processing capabilities of an optical Earth observation instrument operating under the principles of compressed sensing, currently under preliminary study. In particular, we focus on two main aspects for onboard operations: i) how to process measurements in a computationally-efficient way to obtain previews of the reconstructed image that can be easily used by downstream inference algorithms; ii) the possibility of having simultaneous compression and encryption by proper management of the pseudorandom patterns used for the sensing matrix and measurements