Construction of 3D in vitro models by bioprinting human pluripotent stem cells: Challenges and opportunities

Three-dimensional (3D) printing of biological material, or 3D bioprinting, is a rapidly expanding field with interesting applications in tissue engineering and regenerative medicine. Bioprinters use cells and biocompatible materials as an ink (bioink) to build 3D structures representative of organs and tissues, in a controlled manner and with micrometric resolution. Human embryonic (hESCs) and induced (hiPSCs) pluripotent stem cells are ideally able to provide all cell types found in the human body. A limited, but growing, number of recent reports suggest that cells derived by differentiation of hESCs and hiPSCs can be used as building blocks in bioprinted human 3D models, reproducing the cellular variety and cytoarchitecture of real tissues. In this review we will illustrate these examples, which include hepatic, cardiac, vascular, corneal and cartilage tissues, and discuss challenges and opportunities of bioprinting more demanding cell types, such as neurons, obtained from human pluripotent stem cells

Condensation and equilibration in an urn model

After reviewing the general scaling properties of aging systems, we present a numerical study of the slow evolution induced in the zeta urn model by a quench from a high temperature to a lower one where a condensed equilibrium phase exists. By considering both one-time and two-time quantities we show that the features of the model fit into the general framework of aging systems. In particular, its behavior can be interpreted in terms of the simultaneous existence of equilibrated and aging degrees with different scaling properties.Comment: 13 pages, 4 figures, Proceedings of the International Conference on Statistical Physics SigmaPhi, Rhodes 2014. v2: a footnote and one reference added, few typos correcte

Topological regulation of activation barriers on fractal substrates

We study phase-ordering dynamics of a ferromagnetic system with a scalar order-parameter on fractal graphs. We propose a scaling approach, inspired by renormalization group ideas, where a crossover between distinct dynamical behaviors is induced by the presence of a length $\lambda$ associated to the topological properties of the graph. The transition between the early and the asymptotic stage is observed when the typical size $L(t)$ of the growing ordered domains reaches the crossover length $\lambda$. We consider two classes of inhomogeneous substrates, with different activated processes, where the effects of the free energy barriers can be analytically controlled during the evolution. On finitely ramified graphs the free energy barriers encountered by domains walls grow logarithmically with $L(t)$ while they increase as a power-law on all the other structures. This produces different asymptotic growth laws (power-laws vs logarithmic) and different dependence of the crossover length $\lambda$ on the model parameters. Our theoretical picture agrees very well with extensive numerical simulations.Comment: 13 pages, 4 figure

Evidence of radius inflation in stars approaching the slow-rotator sequence

Average stellar radii in open clusters can be estimated from rotation periods and projected rotational velocities under the assumption of random orientation of the spin axis. Such estimates are independent of distance, interstellar absorption, and models, but their validity can be limited by missing data (truncation) or data that only represent upper/lower limits (censoring). We present a new statistical analysis method to estimate average stellar radii in the presence of censoring and truncation. We use theoretical distribution functions of the projected stellar radius $R \sin i$ to define a likelihood function in the presence of censoring and truncation. Average stellar radii in magnitude bins are then obtained by a maximum likelihood parametric estimation procedure. This method is capable of recovering the average stellar radius within a few percent with as few as $\approx$ 10 measurements. Here it is applied for the first time to the dataset available for the Pleiades. We find an agreement better than $\approx$ 10 percent between the observed $R$ vs $M_K$ relationship and current standard stellar models for 1.2 $\ge M/M_{\odot} \ge$ 0.85 with no evident bias. Evidence of a systematic deviation at $2\sigma$ level are found for stars with 0.8 $\ge M/M_{\odot} \ge$ 0.6 approaching the slow-rotator sequence. Fast-rotators ($P$ < 2 d) agree with standard models within 15 percent with no systematic deviations in the whole 1.2 $\ge M/M_{\odot} \ge$ 0.5 range. The evidence found of a possible radius inflation just below the lower mass limit of the slow-rotator sequence indicates a possible connection with the transition from the fast to the slow-rotator sequence.Comment: Accepted by Astronomy and Astrophysics, 11 pages, 6 figure

Focal Firms as Technological Gatakeepers within Industrial Districts Knowledge Creation and Dissemination in the Italian Packaging Machinery Industry

Despite the diffusion of communication tools and boundary spanning technologies, knowledge flows in innovation processes retain a distinct localized nature in many industries and geographical clusters emerge as critical areas to foster technological diffusion. In this paper we focus on the role of focal firms in industrial clusters as “gatekeepers” introducing external technological novelties in the cluster and enacting new useful knowledge production locally, thus enhancing international competitive capabilities of all firms in the cluster. We analyze a longitudinal dataset of 720 patents 1 Corresponding Author www.druid.dk granted by USPTO between 1990 and 2003 to firms in the automatic packaging machinery industrial district of Emilia-Romagna in Northern Italy, and a matched-sample to control for the uneven geographical distribution of R&D and patenting activities. Our results show that firms within the cluster use local knowledge to a greater extent and more rapidly than knowledge from the outside than it would be expected given the geographic distribution of innovative activity in the industry. Moreover, focal firms use external knowledge to a greater extent than other firms operating in the cluster, and other (non focal) firms within the cluster use knowledge from focal firms to a greater extent than would be expected given the geographic distribution of innovative activity in the industry. Implications for research on the geographical distribution of innovation activities are discussed.Innovation processes, Knowledge flows, Geographical clusters

Fluctuation-dissipation relations and field-free algorithms for the computation of response functions

We discuss the relation between the fluctuation-dissipation relation derived by Chatelain and Ricci-Tersenghi [C.Chatelain, J.Phys. A {\bf 36}, 10739 (2003); F. Ricci-Tersenghi, Phys.Rev.E 68, 065104(R) (2003)] and that by Lippiello-Corberi-Zannetti [E. Lippiello, F. Corberi and M. Zannetti Phys. Rev. E {\bf 72}, 056103 (2005)]. In order to do that, we re-derive the fluctuation-dissipation relation for systems of discrete variables evolving in discrete time via a stochastic non-equilibrium Markov process. The calculation is carried out in a general formalism comprising the Chatelain, Ricci-Tersenghi result and that by Lippiello-Corberi-Zannetti as special cases. The applicability, generality, and experimental feasibility of the two approaches is thoroughly discussed. Extending the analytical calculation to the variance of the response function we show the vantage of field-free numerical methods with respect to the standard method where the perturbation is applied. We also show that the signal to noise ratio is better (by a factor $\sqrt 2$) in the algorithm of Lippiello-Corberi-Zannetti with respect to that of Chatelain-Ricci Tersenghi.Comment: 17 pages, 5 figures. To appear in Phys. Rev.

A Mathematical Model of Flavescence Dor\'ee Epidemiology

Flavescence dor\'ee (FD) is a disease of grapevine transmitted by an insect vector, $Scaphoideus$ $titanus$ Ball. At present, no prophylaxis exists, so mandatory control procedures (e.g. removal of infected plants, and insecticidal sprays to avoid transmission) are in place in Italy and other European countries. We propose a model of the epidemiology of FD by taking into account the different aspects involved into the transmission process (acquisition of the disease, latency and expression of symptoms, recovery rate, removal and replacement of infected plants, insecticidal treatments, and the effect of hotbeds). The model was constructed as a system of first order nonlinear ODEs in four compartment variables. We perform a bifurcation analysis of the equilibria of the model using the severity of the hotbeds as the control parameter. Depending on the non-dimensional grapevine density of the vineyard we find either a single family of equilibria in which the health of the vineyard gradually deteriorates for progressively more severe hotbeds, or multiple equilibria that give rise to sudden transitions from a nearly healthy vineyard to a severely deteriorated one when the severity of the hotbeds crosses a critical value. These results suggest some lines of intervention for limiting the spread of the disease