The role of elasticity on adhesion and clustering of neurons on soft surfaces

The question of whether material stiffness enhances cell adhesion and clustering is still open to debate. Results from the literature are seemingly contradictory, with some reports illustrating that adhesion increases with surface stiffness and others suggesting that the performance of a system of cells is curbed by high values of elasticity. To address the role of elasticity as a regulator in neuronal cell adhesion and clustering, we investigated the topological characteristics of networks of neurons on polydimethylsiloxane (PDMS) surfaces - with values of elasticity (E) varying in the 0.55-2.65 MPa range. Results illustrate that, as elasticity increases, the number of neurons adhering on the surface decreases. Notably, the small-world coefficient - a topological measure of networks - also decreases. Numerical simulations and functional multi-calcium imaging experiments further indicated that the activity of neuronal cells on soft surfaces improves for decreasing E. Experimental findings are supported by a mathematical model, that explains adhesion and clustering of cells on soft materials as a function of few parameters - including the Young's modulus and roughness of the material. Overall, results indicate that - in the considered elasticity interval - increasing the compliance of a material improves adhesion, improves clustering, and enhances communication of neurons.

Connecting the dots: Exploring brain connectivity during responsibility recognition in construction contract negotiations

Despite recent advancements in monitoring brain activity, causal relationships within the brain during responsibility identification in construction contracts remain unexplored. We aimed to understand the neural mechanisms involved in the cognitive components and their interactions related to contract text reading by delving into the brain mechanisms of contract responsibility identification. This study investigated students' brain connectivity using electroencephalography (EEG) data during a text-based contract responsibility-identification task. It employed an adaptive directed transfer function based on Granger causality to simulate directed and time-varying information flow in observed brain activity. We evaluated the EEG records of 18 participants under two reading conditions (involving or not involving contractor responsibility). During responsibility identification, the most substantial information exchange occurs in the somatosensory area of the brain. The results revealed a "top-down" cortical mechanism for responsibility identification, with the left parietal-occipital area (PO3) as the central hub promoting connectivity structures. These findings indicate that the perceptual processing of contract responsibility texts is associated with higher visual learning and memory quality. Contracts without contractor-responsibility clauses resulted in more substantial information flow output in the frontal cortex and consumed more cognitive resources. Our findings advance the understanding of cognitive processes involved in contract responsibility identification, providing a framework for investigating causal relationships within the brain and novel insights into cortical mechanisms. By identifying the neural basis of responsibility identification, stakeholders can develop effective training programs for negotiators and enhance their ability to interpret and implement construction contracts.

Bioinspired micro- and nano-structured neural interfaces

The development of a functional nervous system requires neurons to interact with and promptly respond to a wealth of biochemical, mechanical and topographical cues found in the neural extracellular matrix (ECM). Among these, ECM topographical cues have been found to strongly influence neuronal function and behavior. Here, we discuss how the blueprint of the architectural organization of the brain ECM has been tremendously useful as a source of inspiration to design biomimetic substrates to enhance neural interfaces and dictate neuronal behavior at the cell-material interface. In particular, we focus on different strategies to recapitulate cell-ECM and cell-cell interactions. In order to mimic cell-ECM interactions, we introduce roughness as a first approach to provide informative topographical biomimetic cues to neurons. We then examine 3D scaffolds and hydrogels, as softer 3D platforms for neural interfaces. Moreover, we will discuss how anisotropic features such as grooves and fibers, recapitulating both ECM fibrils and axonal tracts, may provide recognizable paths and tracks that neuron can follow as they develop and establish functional connections. Finally, we show how isotropic topographical cues, recapitulating shapes, and geometries of filopodia- and mushroom-like dendritic spines, have been instrumental to better reproduce neuron-neuron interactions for applications in bioelectronics and neural repair strategies. The high complexity of the brain architecture makes the quest for the fabrication of create more biologically relevant biomimetic architectures in continuous and fast development. Here, we discuss how recent advancements in two-photon polymerization and remotely reconfigurable dynamic interfaces are paving the way towards to a new class of smart biointerfaces forin vitroapplications spanning from neural tissue engineering as well as neural repair strategies.

The small world coefficient 4.8 ± 1 optimizes information processing in 2D neuronal networks

Small world networks have recently attracted much attention because of their unique properties. Mounting evidence suggests that communication is optimized in networks with a small world topology. However, despite the relevance of the argument, little is known about the effective enhancement of information in similar graphs. Here, we provide a quantitative estimate of the efficiency of small world networks. We used a model of the brain in which neurons are described as agents that integrate the signals from other neurons and generate an output that spreads in the system. 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Moreover, we found that the information processing capacity of a system steadily increases with \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\rm{SW}}$$\end{document}SW until the value \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\rm{SW}}=4.8\pm 1$$\end{document}SW=4.8±1, independently on \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\triangle t$$\end{document}∆t and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$f$$\end{document}f. After this threshold, the performance degrades with \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\rm{SW}}$$\end{document}SW and there is no convenience in increasing indefinitely the number of active links in the system. Supported by the findings of the work and in analogy with the exergy in thermodynamics, we introduce the concept of exordic systems: a system is exordic if it is topologically biased to transmit information efficiently.

Optimization of High-Density Fe-Au Nano-Arrays for Surface-Enhanced Raman Spectroscopy of Biological Samples

The method of realizing nanostructures using porous alumina templates has attracted interest due to the precise geometry and cheap cost of nanofabrication. In this work, nanoporous alumina membranes were utilized to realize a forest of nanowires, providing a bottom-up nanofabrication method suitable for surface-enhanced Raman spectroscopy (SERS). Gold and iron were electroplated through the straight channels of the membrane. The resulting nanowires are, indeed, made of an active element for plasmonic resonance and SERS as the hexagonal distribution of the nanowires and the extreme high density of the nanowires allows to excite the plasmon and detect the Raman signal. The method to reduce the distance between pores and, consequently, the distance of the nanowires after electrodeposition is optimized here. Indeed, it has been predicted that the light intensity enhancement factor is up to 10¹² when the gap is small than 10 nm. Measurements of Raman signal of thiol groups drying on the gold nanowires show that the performance of the device is improved. As the thiol group can be linked to proteins, the device has the potential of a biosensor for the detection of a few biomolecules. To assess the performance of the device and demonstrate its ability to analyze biological solutions, we used it as SERS substrates to examine solutions of IgG in low abundance ranges. The results of the test indicate that the sensor can convincingly detect biomolecules in physiologically relevant ranges.

Oscillatory Copper Deposition on Conical Iron Electrodes in a Nonuniform Magnetic Field

We report the effect of a magnetic field on the deposition of copper ions on a conically shaped iron probe. In our setup, the magnetic forces and buoyancy are the key factors influencing the electrolyte flow and the mass transfer. Without external current, a spontaneous reduction of copper on the iron cone occurs, known as electroless deposition. Mach–Zehnder and differential interferometry indicate a variation in the concentration of copper ions near the cone. After an initial transient of about 60 s, temporal oscillations in the copper concentration are found under the effect of a magnetic field. In galvanostatic conditions, a similar oscillatory behavior of the concentration of the electrolyte is observed. Numerical simulations show that the oscillations are caused by the magnetic gradient, Lorentz force, and buoyancy force counteracting one another, and the oscillation frequency is estimated analytically based on this mechanism. Furthermore, we present a study on the oscillation frequency for both electroless and galvanostatic conditions with different current densities. The results of this study may stimulate future research aimed at the local control of the deposition rate and the realization of miniaturized, regularly structured deposits using magnetic fields.

Size-Exclusion Particle Separation Driven by Micro-Flows in a Quasi-Spherical Droplet: Modelling and Experimental Results

Aqueous solution droplets are supported quasi contact-free by superhydrophobic surfaces. The convective flow in evaporating droplets allows the manipulation and control of biological molecules in solution. In previous works, super-hydrophobic drops on nano-patterned substrates have been used to analyze otherwise undetectable species in extremely low concentration ranges. Here, we used particle image velocimetry (PIV) for studying the flow field in water droplets containing polystyrene particles on a pillared silicon super-hydrophobic chip. The particles describe vortex-like motions around the droplet center as long as the evaporating droplet maintains a spherical shape. Simulations by a Finite Element Method (FEM) suggest that the recirculating flow is due to the temperature gradient along the droplet rim, generating a shear stress. Notably, the characteristics of the internal flow can be modulated by varying the intensity of the temperature gradient along the drop. We then used the flow-field determined by experiments and an approximate form of the Langevin equation to examine how particles are transported in the drop as a function of particle size. We found that larger particles with an average size of 36 μm are preferentially transported toward the center of the substrate, differently from smaller particles with a 10-fold lower size that are distributed more uniformly in the drop. Results suggest that solutions of spherical particles on a super-hydrophobic chip can be used to separate soft matter and biological molecules based on their size, similarly to the working principle of a time-of-flight (ToF) mass analyzer, except that the separation takes place in a micro-sphere, with less space, less time, and less solution required for the separation compared to conventional ToF systems.

Cell aggregation on nanorough surfaces

The ability to control adhesion and the spatial organization of cells over nanoscale surfaces is essential in tissue engineering, regenerative medicine, the growth of organoids and spheroids as an in-vitro-model of human development and disease. Nonetheless, despite the several different works that have explored the influence of nanotopography on cell adhesion and clustering, little is known about how the forces arising from membrane conformational change developing during cell adaptation to a nanorough surface, and the cell-cell adhesion forces, interact to guide cell assembly. Here, starting from the works of Decuzzi and Ferrari, who examined how the energy of a cell varies while adhering to a nanoscale surface, and of Armstrong and collaborators, who developed a continuous model of cell-cell adhesion and morphogenesis, we provide a description of how nanotopography can modulate cellular clustering. In simulations where the parameters of the model were varied over large intervals, we found that nanoroughness may induce cell aggregation from a homogenous, uniform state, also for weak cell-cell adhesion. Results of the model are relevant in bio-engineering and biomedical nanotechnology, and may be of interest for those involved in the design and fabrication of biomaterials and scaffolds for tissue formation and repair.

Cell Theranostics on Mesoporous Silicon Substrates

The adhesion, proliferation, and migration of cells over nanomaterials is regulated by a cascade of biochemical signals that originate at the interface of a cell with a substrate and propagate through the cytoplasm to the nucleus. The topography of the substrate plays a major role in this process. Cell adhesion molecules (CAMs) have a characteristic size of some nanometers and a range of action of some tens of nanometers. Controlling details of a surface at the nanoscale-the same dimensional over which CAMs operate-offers ways to govern the behavior of cells and create organoids or tissues with heretofore unattainable precision. Here, using electrochemical procedures, we generated mesoporous silicon surfaces with different values of pore size (PS≈11 nm and PS≈21 nm), roughness (Ra≈7 nm and Ra≈13 nm), and fractal dimension (Df≈2.48 and Df≈2.15). Using electroless deposition, we deposited over these substrates thin layers of gold nanoparticles. Resulting devices feature (i) nanoscale details for the stimulation and control of cell assembly, (ii) arrays of pores for drug loading/release, (iii) layers of nanostructured gold for the enhancement of the electromagnetic signal in Raman spectroscopy (SERS). We then used these devices as cell culturing substrates. Upon loading with the anti-tumor drug PtCl (O,O'-acac)(DMSO) we examined the rate of adhesion and growth of breast cancer MCF-7 cells under the coincidental effects of surface geometry and drug release. Using confocal imaging and SERS spectroscopy we determined the relative importance of nano-topography and delivery of therapeutics on cell growth-and how an unbalance between these competing agents can accelerate the development of tumor cells.

Small-world networks of neuroblastoma cells cultured in three-dimensional polymeric scaffolds featuring multi-scale roughness

Understanding the mechanisms underlying cell-surface interaction is of fundamental importance for the rational design of scaffolds aiming at tissue engineering, tissue repair and neural regeneration applications. Here, we examined patterns of neuroblastoma cells cultured in three-dimensional polymeric scaffolds obtained by two-photon lithography. Because of the intrinsic resolution of the technique, the micrometric cylinders composing the scaffold have a lateral step size of ~200 nm, a surface roughness of around 20 nm, and large values of fractal dimension approaching 2.7. We found that cells in the scaffold assemble into separate groups with many elements per group. After cell wiring, we found that resulting networks exhibit high clustering, small path lengths, and small-world characteristics. These values of the topological characteristics of the network can potentially enhance the quality, quantity and density of information transported in the network compared to equivalent random graphs of the same size. This is one of the first direct observations of cells developing into 3D small-world networks in an artificial matrix.

Kinetic Rate Constants of Gold Nanoparticle Deposition on Silicon

We fabricated gold nanoparticles on nanoporous silicon microparticles using electroless deposition in a hydrofluoric acid solution containing gold chloride. The reaction was followed by UV spectrometer analysis of the absorbance of the solution (proportional to the nanoparticle concentration) for two temperatures (20 and 50 °C). The results indicate that the process is autocatalytic, described by a pseudo-first-order reaction, the apparent rate constant k_obs of which was determined by utilizing UV spectrometer data. We found that the reaction rate constant at 20 °C is 7 × 10^-3 s^-1 and that at 50 °C is 2.9 × 10^-2 s^-1. Scanning electron microscope (SEM) analysis of samples and diffusion-limited aggregation (DLA) simulations were used to validate the results. This study aims to resolve the kinetics of the electroless deposition of gold on silicon at the nanoscale, in the present state of art missing a quantitative characterization, for certain conditions of growth and given values of temperature and concentration of the reagents. Results may have applications to the synthesis of gold nanoparticles and their use as nanosensors, drug delivery systems, or metal nanometamaterials with advanced optical properties.

Cortical-like mini-columns of neuronal cells on zinc oxide nanowire surfaces

A long-standing goal of neuroscience is a theory that explains the formation of the minicolumns in the cerebral cortex. Minicolumns are the elementary computational units of the mature neocortex. Here, we use zinc oxide nanowires with controlled topography as substrates for neural-cell growth. We observe that neuronal cells form networks where the networks characteristics exhibit a high sensitivity to the topography of the nanowires. For certain values of nanowires density and fractal dimension, neuronal networks express small world attributes, with enhanced information flows. We observe that neurons in these networks congregate in superclusters of approximately 200 neurons. We demonstrate that this number is not coincidental: the maximum number of cells in a supercluster is limited by the competition between the binding energy between cells, adhesion to the substrate, and the kinetic energy of the system. Since cortical minicolumns have similar size, similar anatomical and topological characteristics of neuronal superclusters on nanowires surfaces, we conjecture that the formation of cortical minicolumns is likewise guided by the interplay between energy minimization, information optimization and topology. For the first time, we provide a clear account of the mechanisms of formation of the minicolumns in the brain.

Relating the rate of growth of metal nanoparticles to cluster size distribution in electroless deposition

Electroless deposition on patterned silicon substrates enables the formation of metal nanomaterials with tight control over their size and shape. In the technique, metal ions are transported by diffusion from a solution to the active sites of an autocatalytic substrate where they are reduced as metals upon contact. Here, using diffusion limited aggregation models and numerical simulations, we derived relationships that correlate the cluster size distribution to the total mass of deposited particles. We found that the ratio ξ between the rates of growth of two different metals depends on the ratio γ between the rates of growth of clusters formed by those metals through the linearity law ξ = 14(γ - 1). We then validated the model using experiments. Different from other methods, the model derives k using as input the geometry of metal nanoparticle clusters, decoded by SEM or AFM images of samples, and a known reference.

The effect of connectivity on information in neural networks

We present a mathematical model that quantifies the amount of information exchanged in bi-dimensional networks of nerve cells as a function of network connectivity Q. Upon varying Q over a significant range, we found that, from a certain cell density onwards, 90% of the maximal information transferred I(Q) in a random neuronal network is already reached with just 40% of the total possible connections Q among the cells. As a consequence, the system would not benefit from additional connections in terms of the amount of I(Q), in agreement with the tendency of brains to minimize Q because of its energetic costs. The model may reveal the circuits responsible for neurodegenerative disorders in that neurodegeneration can be regarded as a connective failure affecting information.

Laser-Generated Proton Beams for High-Precision Ultra-Fast Crystal Synthesis

We present a method for the synthesis of micro-crystals and micro-structured surfaces using laser-accelerated protons. In this method, a solid surface material having a low melting temperature is irradiated with very-short laser-generated protons, provoking in the ablation process thermodynamic conditions that are between the boiling and the critical point. The intense and very quick proton energy deposition (in the ns range) induces an explosive boiling and produces microcrystals that nucleate in a plasma plume composed by ions and atoms detached from the laser-irradiated surface. The synthesized particles in the plasma plume are then deposited onto a cold neighboring, non-irradiated, solid secondary surface. We experimentally verify the synthesizing methods by depositing low-melting-material microcrystals - such as gold - onto nearby silver surfaces and modeling the proton/matter interaction via a Monte Carlo code, confirming that we are in the above described thermodynamic conditions. Morphological and crystallinity measurements indicate the formation of gold octahedral crystals with dimensions around 1.2 μm, uniformly distributed onto a silver surface with dimensions in the tens of mm2. This laser-accelerated particle based synthesis method paves the way for the development of new material synthesis using ultrashort laser-accelerated particle beams.

Nano-topography Enhances Communication in Neural Cells Networks

Neural cells are the smallest building blocks of the central and peripheral nervous systems. Information in neural networks and cell-substrate interactions have been heretofore studied separately. Understanding whether surface nano-topography can direct nerve cells assembly into computational efficient networks may provide new tools and criteria for tissue engineering and regenerative medicine. In this work, we used information theory approaches and functional multi calcium imaging (fMCI) techniques to examine how information flows in neural networks cultured on surfaces with controlled topography. We found that substrate roughness S a affects networks topology. In the low nano-meter range, S a  = 0-30 nm, information increases with S a . Moreover, we found that energy density of a network of cells correlates to the topology of that network. This reinforces the view that information, energy and surface nano-topography are tightly inter-connected and should not be neglected when studying cell-cell interaction in neural tissue repair and regeneration.

Information in a Network of Neuronal Cells: Effect of Cell Density and Short-Term Depression

Neurons are specialized, electrically excitable cells which use electrical to chemical signals to transmit and elaborate information. Understanding how the cooperation of a great many of neurons in a grid may modify and perhaps improve the information quality, in contrast to few neurons in isolation, is critical for the rational design of cell-materials interfaces for applications in regenerative medicine, tissue engineering, and personalized lab-on-a-chips. In the present paper, we couple an integrate-and-fire model with information theory variables to analyse the extent of information in a network of nerve cells. We provide an estimate of the information in the network in bits as a function of cell density and short-term depression time. In the model, neurons are connected through a Delaunay triangulation of not-intersecting edges; in doing so, the number of connecting synapses per neuron is approximately constant to reproduce the early time of network development in planar neural cell cultures. In simulations where the number of nodes is varied, we observe an optimal value of cell density for which information in the grid is maximized. In simulations in which the posttransmission latency time is varied, we observe that information increases as the latency time decreases and, for specific configurations of the grid, it is largely enhanced in a resonance effect.

Patterned porous silicon photonic crystals with modular surface chemistry for spatial control of neural stem cell differentiation

We present a strategy to spatially define regions of gold and nanostructured silicon photonics, each with materials-specific surface chemistry, for azide-alkyne cycloaddition of different bioactive peptides. Neural stem cells are spatially directed to undergo neurogenesis and astrogenesis as a function of both surface properties and peptide identity.