Cell bioprinting: The 3D-bioplotter™ case

The classic cell culture involves the use of support in two dimensions, such as a well plate or a Petri dish, that allows the culture of different types of cells. However, this technique does not mimic the natural microenvironment where the cells are exposed to. To solve that, three-dimensional bioprinting techniques were implemented, which involves the use of biopolymers and/or synthetic materials and cells. Because of a lack of information between data sources, the objective of this review paper is, to sum up, all the available information on the topic of bioprinting and to help researchers with the problematics with 3D bioprinters, such as the 3D-Bioplotter™. The 3D-Bioplotter™ has been used in the pre-clinical field since 2000 and could allow the printing of more than one material at the same time, and therefore to increase the complexity of the 3D structure manufactured. It is also very precise with maximum flexibility and a user-friendly and stable software that allows the optimization of the bioprinting process on the technological point of view. Different applications have resulted from the research on this field, mainly focused on regenerative medicine, but the lack of information and/or the possible misunderstandings between papers makes the reproducibility of the tests dicult. Nowadays, the 3D Bioprinting is evolving into another technology called 4D Bioprinting, which promises to be the next step in the bioprinting field and might promote great applications in the future

Enhancement of Tc in the Superconductor-Insulator Phase Transition on Scale-Free Networks

A road map to understand the relation between the onset of the superconducting state with the particular optimum heterogeneity in granular superconductors is to study a Random Tranverse Ising Model on complex networks with a scale-free degree distribution regularized by and exponential cutoff p(k) \propto k^{-\gamma}\exp[-k/\xi]. In this paper we characterize in detail the phase diagram of this model and its critical indices both on annealed and quenched networks. To uncover the phase diagram of the model we use the tools of heterogeneous mean-field calculations for the annealed networks and the most advanced techniques of quantum cavity methods for the quenched networks. The phase diagram of the dynamical process depends on the temperature T, the coupling constant J and on the value of the branching ratio / where k is the degree of the nodes in the network. For fixed value of the coupling the critical temperature increases linearly with the branching ration which diverges with the increasing cutoff value \xi or value of the \gamma exponent \gamma< 3. This result suggests that the fractal disorder of the superconducting material can be responsible for an enhancement of the superconducting critical temperature. At low temperature and low couplings T<<1 and J<<1, instead, we observe a different behavior for annealed and quenched networks. In the annealed networks there is no phase transition at zero temperature while on quenched network we observe a Griffith phase dominated by extremely rare events and a phase transition at zero temperature. The Griffiths critical region, nevertheless, is decreasing in size with increasing value of the cutoff \xi of the degree distribution for values of the \gamma exponents \gamma< 3.Comment: (17 pages, 3 figures

Entropy measures for complex networks: Toward an information theory of complex topologies

The quantification of the complexity of networks is, today, a fundamental problem in the physics of complex systems. A possible roadmap to solve the problem is via extending key concepts of information theory to networks. In this paper we propose how to define the Shannon entropy of a network ensemble and how it relates to the Gibbs and von Neumann entropies of network ensembles. The quantities we introduce here will play a crucial role for the formulation of null models of networks through maximum-entropy arguments and will contribute to inference problems emerging in the field of complex networks.Comment: (4 pages, 1 figure

micro structuring of titanium collectors by laser ablation technique a promising approach to produce micro patterned scaffolds for tissue engineering applications

Abstract Multi-scale micro-structured scaffolds can sustain attachment and orientation of different cells phenotypes. An innovative use of laser ablation technique to build micro-structured titanium surfaces to be used as collectors in both electrophoretic deposition and electrospinning processes was investigated. To produce micro-patterned scaffolds, a negative replica patterning was exploited by designing specific patterns to be laser ablated on titanium plates. This method allows the deposition of the scaffolds on the mold, thus reproducing the micro-features on the scaffold surface. The titanium surface morphology depending on ablation parameters was studied and the capability of the process in replicating the micro-pattern was characterized

Number of loops of size h in growing scale-free networks

The hierarchical structure of scale-free networks has been investigated focusing on the scaling of the number $N_h(t)$ of loops of size h as a function of the system size. In particular we have found the analytic expression for the scaling of $N_h(t)$ in the Barab\'asi-Albert (BA) scale-free network. We have performed numerical simulations on the scaling law for $N_h(t)$ in the BA network and in other growing scale free networks, such as the bosonic network (BN) and the aging nodes (AN) network. We show that in the bosonic network and in the aging node network the phase transitions in the topology of the network are accompained by a change in the scaling of the number of loops with the system size.Comment: 4 pages, 3 figure

Critical fluctuations in spatial complex networks

An anomalous mean-field solution is known to capture the non trivial phase diagram of the Ising model in annealed complex networks. Nevertheless the critical fluctuations in random complex networks remain mean-field. Here we show that a break-down of this scenario can be obtained when complex networks are embedded in geometrical spaces. Through the analysis of the Ising model on annealed spatial networks, we reveal in particular the spectral properties of networks responsible for critical fluctuations and we generalize the Ginsburg criterion to complex topologies.Comment: (4 pages, 2 figures

An experimental study on micro-milling of a medical grade Co-Cr-Mo alloy produced by selective laser melting

Cobalt-chromium-molybdenum (Co-Cr-Mo) alloys are very promising materials, in particular, in the biomedical field where their unique properties of biocompatibility and wear resistance can be exploited for surgery applications, prostheses, and many other medical devices. While Additive Manufacturing is a key technology in this field, micro-milling can be used for the creation of micro-scale details on the printed parts, not obtainable with Additive Manufacturing techniques. In particular, there is a lack of scientific research in the field of the fundamental material removal mechanisms involving micro-milling of Co-Cr-Mo alloys. Therefore, this paper presents a micro-milling characterization of Co-Cr-Mo samples produced by Additive Manufacturing with the Selective Laser Melting (SLM) technique. In particular, microchannels with different depths were made in order to evaluate the material behavior, including the chip formation mechanism, in micro-milling. In addition, the resulting surface roughness (Ra and Sa) and hardness were analyzed. Finally, the cutting forces were acquired and analyzed in order to ascertain the minimum uncut chip thickness for the material. The results of the characterization studies can be used as a basis for the identification of a machining window for micro-milling of biomedical grade cobalt-chromium-molybdenum (Co-Cr-Mo) alloys

Dynamical and bursty interactions in social networks

We present a modeling framework for dynamical and bursty contact networks made of agents in social interaction. We consider agents' behavior at short time scales, in which the contact network is formed by disconnected cliques of different sizes. At each time a random agent can make a transition from being isolated to being part of a group, or vice-versa. Different distributions of contact times and inter-contact times between individuals are obtained by considering transition probabilities with memory effects, i.e. the transition probabilities for each agent depend both on its state (isolated or interacting) and on the time elapsed since the last change of state. The model lends itself to analytical and numerical investigations. The modeling framework can be easily extended, and paves the way for systematic investigations of dynamical processes occurring on rapidly evolving dynamical networks, such as the propagation of an information, or spreading of diseases

Supercondutor-Insulator Transition on Annealed Complex Networks

Cuprates show multiphase complexity that has hindered physicists search for the mechanism of high T_c for many years. A fingerprint of electronic scale invariance has been reported recently by Fratini et al. by detecting the structural scale invariance of dopants using scanning micro x-ray diffraction. In order to shed light on critical phenomena on these materials, here we propose a stylized model capturing the essential characteristics of the superconducting-isulator transition of a highly dynamical, heterogenous granular material: the Disordered Quantum Tranverse Ising Model (DQTIM) on Annealed Complex Network. We show that when the networks encode for high heterogeneity of the expected degrees described by a power law distribution, the critical temperature for the onset of the supercoducting phase diverges to infinity as the power-law exponent \gamma of the expected degree distribution is less than 3, i.e. \gamma<3. Moreover we investigate the case in which the critical state of the electronic background is triggered by an external parameter g that determines an exponential cutoff in the power law expected degree distribution characterized by an exponent \gamma. We find that for g=g_c the critical temperature for the superconduting-insulator transition has a maximum is \gamma>3 and diverges if \gamma<3.Comment: 4 pages, 2 figure

Phase diagram of the Bose-Hubbard Model on Complex Networks

Critical phenomena can show unusual phase diagrams when defined in complex network topologies. The case of classical phase transitions such as the classical Ising model and the percolation transition has been studied extensively in the last decade. Here we show that the phase diagram of the Bose-Hubbard model, an exclusively quantum mechanical phase transition, also changes significantly when defined on random scale-free networks. We present a mean-field calculation of the model in annealed networks and we show that when the second moment of the average degree diverges the Mott-insulator phase disappears in the thermodynamic limit. Moreover we study the model on quenched networks and we show that the Mott-insulator phase disappears in the thermodynamic limit as long as the maximal eigenvalue of the adjacency matrix diverges. Finally we study the phase diagram of the model on Apollonian scale-free networks that can be embedded in 2 dimensions showing the extension of the results also to this case.Comment: (6 pages, 4 figures