Time filter

Source Type

Wiersma D.S.,University of Florence | Wiersma D.S.,CNR Institute of Neuroscience
Nature Photonics | Year: 2013

What do lotus flowers have in common with human bones, liquid crystals with colloidal suspensions, and white beetles with the beautiful stones of the Taj Mahal? The answer is they all feature disordered structures that strongly scatter light, in which light waves entering the material are scattered several times before exiting in random directions. These randomly distributed rays interfere with each other, leading to interesting, and sometimes unexpected, physical phenomena. This Review describes the physics behind the optical properties of disordered structures and how knowledge of multiple light scattering can be used to develop new applications. The field of disordered photonics has grown immensely over the past decade, ranging from investigations into fundamental topics such as Anderson localization and other transport phenomena, to applications in imaging, random lasing and solar energy. Copyright © 2013 Macmillan Publishers Limited. Source

Tozzini V.,CNR Institute of Neuroscience
Accounts of Chemical Research | Year: 2010

(Figure Presented) The activity within a living cell is based on a complex network of interactions among biomolecules, exchanging information and energy through biochemical processes. These events occur on different scales, from the nano- to the macroscale, spanning about 10 orders of magnitude in the space domain and 15 orders of magnitude in the time domain. Consequently, many different modeling techniques, each proper for a particular time or space scale, are commonly used. In addition, a single process often spans more than a single time or space scale. Thus, the necessity arises for combining the modeling techniques in multiscale approaches. In this Account, I first review the different modeling methods for bio-systems, from quantum mechanics to the coarsegrained and continuum-like descriptions, passing through the atomistic force field simulations. Special attention is devoted to their combination in different possible multiscale approaches and to the questions and problems related to their coherent matching in the space and time domains. These aspects are often considered secondary, but in fact, they have primary relevance when the aim is the coherent and complete description of bioprocesses. Subsequently, applications are illustrated by means of two paradigmatic examples: (i) the green fluorescent protein (GFP) family and (ii) the proteins involved in the human immunodeficency virus (HIV) replication cycle. The GFPs are currently one of the most frequently used markers for monitoring protein trafficking within living cells; nanobiotechnology and cell biology strongly rely on their use in fluorescence microscopy techniques. A detailed knowledge of the actions of the virusspecific enzymes of HIV (specifically HIV protease and integrase) is necessary to study novel therapeutic strategies against this disease. Thus, the insight accumulated over years of intense study is an excellent framework for this Account. The foremost relevance of these two biomolecular systems was recently confirmed by the assignment of two of the Nobel prizes in 2008: in chemistry for the discovery of GFP and in medicine for the discovery of HIV. Accordingly, these proteins were studied with essentially all of the available modeling techniques, making them ideal examples for studying the details of multiscale approaches in protein modeling. © 2010 American Chemical Society. Source

Tozzini V.,CNR Institute of Neuroscience
Quarterly Reviews of Biophysics | Year: 2010

The last decade has witnessed a renewed interest in the coarse-grained (CG) models for biopolymers, also stimulated by the needs of modern molecular biology, dealing with nano- to micro-sized bio-molecular systems and larger than microsecond timescale. This combination of size and timescale is, in fact, hard to access by atomic-based simulations. Coarse graining the system is a route to be followed to overcome these limits, but the ways of practically implementing it are many and different, making the landscape of CG models very vast and complex. In this paper, the CG models are reviewed and their features, applications and performances compared. This analysis, restricted to proteins, focuses on the minimalist models, namely those reducing at minimum the number of degrees of freedom without losing the possibility of explicitly describing the secondary structures. This class includes models using a single or a few interacting centers (beads) for each amino acid. From this analysis several issues emerge. The difficulty in building these models resides in the need for combining transferability/predictive power with the capability of accurately reproducing the structures. It is shown that these aspects could be optimized by accurately choosing the force field (FF) terms and functional forms, and combining different parameterization procedures. In addition, in spite of the variety of the minimalist models, regularities can be found in the parameters values and in FF terms. These are outlined and schematically presented with the aid of a generic phase diagram of the polypeptide in the parameter space and, hopefully, could serve as guidelines for the development of minimalist models incorporating the maximum possible level of predictive power and structural accuracy. © 2010 Cambridge University Press. Source

MicroRNAs (miRNAs) control cell cycle progression by targeting the transcripts encoding for cyclins, CDKs and CDK inhibitors, such as p27KIP1 (p27). p27 expression is controlled by multiple transcriptional and posttranscriptional mechanisms, including translational inhibition by miR-221/222 and posttranslational regulation by the SCFSKP2 complex. The oncosuppressor activity of miR-340 has been recently characterized in breast, colorectal and osteosarcoma tumor cells. However, the mechanisms underlying miR-340-induced cell growth arrest have not been elucidated. Here, we describe miR-340 as a novel tumor suppressor in non-small cell lung cancer (NSCLC). Starting from the observation that the growth-inhibitory and proapoptotic effects of miR-340 correlate with the accumulation of p27 in lung adenocarcinoma and glioblastoma cells, we have analyzed the functional relationship between miR-340 and p27 expression. miR-340 targets three key negative regulators of p27. The miR-340-mediated inhibition of both Pumilio family RNA-binding proteins (PUM1 and PUM2), required for the miR-221/222 interaction with the p27 3′-UTR, antagonizes the miRNA-dependent downregulation of p27. At the same time, miR-340 induces the stabilization of p27 by targeting SKP2, the key posttranslational regulator of p27. Therefore, miR-340 controls p27 at both translational and posttranslational levels. Accordingly, the inhibition of either PUM1 or SKP2 partially recapitulates the miR-340 effect on cell proliferation and apoptosis. In addition to the effect on tumor cell proliferation, miR-340 also inhibits intercellular adhesion and motility in lung cancer cells. These changes correlate with the miR-340-mediated inhibition of previously validated (MET and ROCK1) and potentially novel (RHOA and CDH1) miR-340 target transcripts. Finally, we show that in a small cohort of NSCLC patients (n=23), representative of all four stages of lung cancer, miR-340 expression inversely correlates with clinical staging, thus suggesting that miR-340 downregulation contributes to the disease progression.Oncogene advance online publication, 25 August 2014; doi:10.1038/onc.2014.267. Source

CNR Institute of Neuroscience | Date: 2013-03-27

A video-confocal microscopy method for creating an image of an optical section () of a sample (

Discover hidden collaborations