Aligned Network Research Articles

Extracellular Matrix Expression and Production in Fibroblast-Collagen Gels: Towards an In Vitro Model for Ligament Wound Healing.

Ligament wound healing involves the proliferation of a dense and disorganized fibrous matrix that slowly remodels into scar tissue at the injury site. This remodeling process does not fully restore the highly aligned collagen network that exists in native tissue, and consequently repaired ligament has decreased strength and durability. In order to identify treatments that stimulate collagen alignment and strengthen ligament repair, there is a need to develop in vitro models to study fibroblast activation during ligament wound healing. The objective of this study was to measure gene expression and matrix protein accumulation in fibroblast-collagen gels that were subjected to different static stress conditions (stress-free, biaxial stress, and uniaxial stress) for three time points (1, 2 or 3weeks). By comparing our in vitro results to prior in vivo studies, we found that stress-free gels had time-dependent changes in gene expression (col3a1, TnC) corresponding to early scar formation, and biaxial stress gels had protein levels (collagen type III, decorin) corresponding to early scar formation. This is the first study to conduct a targeted evaluation of ligament healing biomarkers in fibroblast-collagen gels, and the results suggest that biomimetic in-vitromodels of early scar formation should be initially cultured under biaxial stress conditions.

Curviness of nanowires is shown to affect their resistivity in random and aligned networks

Monte Carlo simulations show that the resistivity of networks made up of 1-D metal nanowires depends on their curvature, where the degree of nanowire alignment changes the optimal curvature.

Effect of nitridation temperature on formation and properties of GaN nanowall networks on sapphire (0 0 0 1) grown by laser MBE

Vertical aligned GaN nanowall networks (NWN) have been grown on sapphire (0 0 0 1) substrates using laser assisted molecular beam epitaxy (LMBE) by tuning the sapphire pre-nitridation temperature (200–600 °C). Field emission scanning electron microscopy studies showed the formation of hexagonal shaped vertical GaN NWN with wall width of 8–20 nm on high temperature (600 °C) nitridated sapphire whereas flower shape granular GaN structure with grain size of 50–240 nm was obtained on low temperature (200 °C) nitridated sapphire. The crystalline properties of the GaN NWN have been studied using high resolution X-ray diffraction (HR-XRD). The results show that the full width at half maximum of the GaN(0 0 0 2) X-ray rocking curve has a relatively low value compared to previous reports of hetero-epitaxial grown GaN NWN on sapphire and other substrates. Raman spectroscopy measurements revealed the presence of compressive stress in film whereas tensile stress in GaN NWN structures which is also complimented by HR-XRD analysis. The room temperature photoluminescence spectroscopy measurement for NWN having tip width 8–20 nm showed a 94 meV blue-shift in near band edge emission, even though NWN experienced with tensile stress, which confirm the observation of quantum size effect. The hetero-epitaxial growth of porous GaN NWN with high crystalline quality holds promise for applications in field of nitride based sensors and the enhancement of light extraction efficiency in optoelectronics devices.

Textural Insights Into the Evolving Lava Dome Cycles at Santiaguito Lava Dome, Guatemala

The structures and textures preserved in lava domes reflect underlying magmatic and eruptive processes, and may provide evidence of how eruptions initiate and evolve. This study explores the remarkable cycles in lava extrusion style produced between 1922 and 2012 at the Santiaguito lava dome complex, Guatemala. By combining an examination of eruptive lava morphologies and textures with a review of historical records, we aim to constrain the processes responsible for the range of erupted lava type and morphologies. The Santiaguito lava dome complex is divided into four domes (El Caliente, La Mitad, El Monje, El Brujo), containing a range of proximal structures (e.g. spines) from which a series of structurally contrasting lava flows originate. Vesicular lava flows (with a’a like, yet non-brecciated flow top) have the highest porosity with interconnected spheroidal pores and may transition into blocky lava flows. Blocky lava flows are high volume and texturally variable with dense zones of small tubular aligned pore networks and more porous zones of spheroidal shaped pores. Spines are dense and low volume and contain small skeletal shaped pores, and subvertical zones of sigmoidal pores. We attribute the observed differences in pore shapes to reflect shallow inflation, deflation, flattening or shearing of the pore fraction. Effusion rate and duration of the eruption define the amount of time available for heating or cooling, degassing and outgassing prior to and during extrusion, driving changes in pore textures and lava type. Our new textural data when reviewed with all the other published data allows cyclic models to be developed. The cyclic eruption models are influenced by viscosity changes resulting from (1) initial magmatic composition and temperature, and (2) effusion rate which in turn affects degassing, outgassing and cooling time in the conduit. Each lava type presents a unique set of hazards and understanding the morphologies and dome progression is useful in hazard forecasting.

Microstructure evolution and self-assembling of CNT networks during mechanical stretching and mechanical properties of highly aligned CNT composites

Using a floating catalyst synthesis process, carbon nanotubes (CNTs) can be produced to form randomly oriented networks. However, to realize their potential high structural performance, the nanotubes must be aligned and closely packed to eliminate molecular and microscale defects, which would be similar to carbon fiber microstructures. This paper describes a mechanical stretching technique using bismaleimide (BMI) resin to transform the randomly oriented networks into aligned networks. The BMI resin acts as a lubricant to decrease the friction between the nanotube bundles within the network during the stretching process. The unique flattening and self-assembling behaviors and the resultant graphitic crystal packing of CNTs were observed. The nanotubes' degree of alignment, measured by Raman and X-ray scattering drastically increased at approximately 40% stretch strain, plateaued at a 60% stretch strain, and achieved a maximum of 0.92 degree of alignment with noticeable graphitic crystal packing at 80% stretch strain. Both TEM and SEM observations indicate that as the stretch strain increased, the CNTs started to align along the stretched direction and self-assembled into large bundles. Additionally, high-resolution TEM analysis indicated that the CNTs exhibited flattening and polygonization self-assembling to form graphitic crystal packing. Tensile testing on the stretched CNT/BMI composite samples revealed an increase in Young's modulus, with a maximum of 252 GPa at 80% stretch strain, while an ultimate tensile strength of 1.58 GPa was reached at 70% stretch strain. The high degree of alignment and polygonization packing resulted in a better load transfer among CNTs, and thus a higher mechanical performance in the resultant CNT composites. Furthermore, this stretching process is scalable and has the potential to realize greater performance for applications using CNTs.

Photodriven Shape-Stabilized Phase Change Materials with Optimized Thermal Conductivity by Tailoring the Microstructure of Hierarchically Ordered Hybrid Porous Scaffolds

Graphene oxide (GO)/boron nitride (BN) hybrid porous scaffolds (HPSs) with the optimally three-dimensional (3D) aligned network structure are fabricated using an unidirectional ice-templated strategy. A variety of HPSs with multilayer structure are obtained due to the various temperature gradients generated by tuning freezing temperature, in which GO and BN are expelled from the ice growth front to assemble between the oriented ice crystals. We demonstrate that the obtained HPSs have a significant influence on the properties of the resulting composite phase change materials (PCMs), including thermal conductivity and shape-stability. Various thermally conductive pathways are formed by tuning freezing temperature, which contributes to further understanding the relationship between thermal conductivity of composites and their internal network structure. Upon increasing the freezing temperature from −120 to −30 °C, the thermal conductivity of the composite PCMs increases and reaches a maximum value at −50 °C ...

Effect of electric field induced alignment and dispersion of functionalized carbon nanotubes on properties of natural rubber

Abstract The original equipment and method for orienting multi-walled carbon nanotubes (MWCNTs) in natural rubber (NR) by alternating current (AC) electric field were reported in the present study. MWCNTs with various volume fractions were dispersed in the mixture latex which composed of natural rubber, additives and methylbenzene. The application of AC electric field during nanocomposites curing process was used to induce the formation of aligned conductive nanotube networks between the electrodes. The aligned MWCNTs in the composites have a better orientation performance and dispersion quality than these of random MWCNTs by analyzing TEM and SEM images. The effects of MWCNTs anisotropy on thermal conductivity, dielectric properties, and dynamic mechanical properties of NR were studied. The mean value of thermal conductivity of composites loading with aligned MWCNTs was 8.67% higher than that of composites with random MWCNTs due to the anisotropy of aligned MWCNTs. The compounds with aligned MWCNTs possessed low dielectric constant, loss tangents and conductivity, namely a good insulativity. The compounds loading with aligned MWCNTs had lower loss modulus and better dynamic mechanical properties than those with random MWCNTs. This method can make full use of the high thermal conductivity of MWCNTs axis, and expand the application areas of natural rubber like conducting heat in a certain direction with a high efficiency.

Inferring Anchor Links Based on Social Network Structure

Nowadays, people usually participate in multiple social networks simultaneously, e.g., Facebook and Twitter. Formally, the correspondences of the accounts that belong to the same user are defined as anchor links, and the networks aligned by anchor links can be denoted as aligned networks. In this paper, we study the problem of anchor link prediction (ALP) across a pair of aligned networks based on social network structure. First, three similarity metrics (CPS, CCS, and CPS+) are proposed. Different from the previous works, we focus on the theoretical guarantees of our metrics. We prove mathematically that the node pair with the maximum CPS or CPS+ should be an anchor link with high probability and a correctly predicted anchor link must have a high value of CCS. Second, using the CPS+ and CCS, we present a two-stage iterative algorithm CPCC to solve the problem of the ALP. More specifically, we present an early termination strategy to make a tradeoff between precision and recall. At last, a series of experiments are conducted on both synthetic and real-world social networks to demonstrate the effectiveness of the CPCC.

Aligned flexible conductive fibrous networks for highly sensitive, ultrastretchable and wearable strain sensors

A high performance strain sensor based on an aligned conductive fibrous network was prepared with large responsivity, broad sensing range and remarkable stability, demonstrating the applications for detections of both vigorous and subtle human motions.

Transfer of assembled collagen fibrils to flexible substrates for mechanically tunable contact guidance cues.

Contact guidance or bidirectional migration along aligned fibers modulates many physiological and pathological processes such as wound healing and cancer invasion. Aligned 2D collagen fibrils epitaxially grown on mica substrates replicate many features of contact guidance seen in aligned 3D collagen fiber networks. However, these 2D collagen self-assembled substrates are difficult to image through, do not have known or tunable mechanical properties and cells degrade and mechanically detach collagen fibrils from the surface, leading to an inability to assess contact guidance over long times. Here, we describe the transfer of aligned collagen fibrils from mica substrates to three different functionalized target substrates: glass, polydimethylsiloxane (PDMS) and polyacrylamide (PA). Aligned collagen fibrils can be efficiently transferred to all three substrates. This transfer resulted in substrates that were to varying degrees resistant to cell-mediated collagen fibril deformation that resulted in detachment of the collagen fibril field, allowing for contact guidance to be observed over longer time periods. On these transferred substrates, cell speed is lowest on softer contact guidance cues for both MDA-MB-231 and MTLn3 cells. Intermediate stiffness resulted in the fastest migration. MTLn3 cell directionality was low on soft contact guidance cues, whereas MDA-MB-231 cell directionality marginally increased. It appears that the stiffness of the contact guidance cue regulates contact guidance differently between cell types. The development of this collagen fibril transfer method allows for the attachment of aligned collagen fibrils on substrates, particularly flexible substrates, that do not normally promote aligned collagen fibril growth, increasing the utility of this collagen self-assembly system for the fundamental examination of mechanical regulation of contact guidance.

Modeling the effect of collagen fibril alignment on ligament mechanical behavior.

Ligament mechanical behavior is primarily regulated by fibrous networks of type I collagen. Although these fibrous networks are typically highly aligned, healthy and injured ligament can also exhibit disorganized collagen architecture. The objective of this study was to determine whether variations in the collagen fibril network between neighboring ligaments can predict observed differences in mechanical behavior. Ligament specimens from two regions of bovine fetlock joints, which either exhibited highly aligned or disorganized collagen fibril networks, were mechanically tested in uniaxial tension. Confocal microscopy and FiberFit software were used to quantify the collagen fibril dispersion and mean fibril orientation in the mechanically tested specimens. These two structural parameters served as inputs into an established hyperelastic constitutive model that accounts for a continuous distribution of planar fibril orientations. The ability of the model to predict differences in the mechanical behavior between neighboring ligaments was tested by (1) curve fitting the model parameters to the stress response of the ligament with highly aligned fibrils and then (2) using this model to predict the stress response of the ligament with disorganized fibrils by only changing the parameter values for fibril dispersion and mean fibril orientation. This study found that when using parameter values for fibril dispersion and mean fibril orientation based on confocal imaging data, the model strongly predicted the average stress response of ligaments with disorganized fibrils ([Formula: see text]); however, the model only successfully predicted the individual stress response of ligaments with disorganized fibrils in half the specimens tested. Model predictions became worse when parameters for fibril dispersion and mean fibril orientation were not based on confocal imaging data. These findings emphasize the importance of collagen fibril alignment in ligament mechanics and help advance a mechanistic understanding of fibrillar networks in healthy and injured ligament.

Largely enhanced thermal conductivity of graphene/copper composites with highly aligned graphene network

Graphene has an ultra-high thermal conductivity (TC) along its basin plane. However, the TC of graphene/metal composites is still far below the expectation due primarily to the lack of sufficient graphene alignment in the metal matrix. Herein, we reported an efficient route to prepare the graphene nanoplatelet (GNP)/Cu composites with highly aligned GNPs by a vacuum filtration method followed by spark plasma sintering. Impressively, when the GNP fraction reached 35 vol%, a long-range and highly aligned GNP network was established within the Cu matrix, leading to a surprisingly high in-plane TC of 525 W/mK, which was 50% higher than that of Cu matrix and among the highest value ever reported for bulk graphene/metal composites. These results demonstrated that our strategy to construct a highly aligned graphene network could indeed achieve the remarkable in-plane TC enhancement in graphene/metal composites, and resulting composites may find application in electronic packaging that requires efficient directional heat transfer.

Fast charge rate supercapacitors based on nitrogen-doped aligned carbon nanosheet networks

Achieving high electrochemical energy density while retaining high power density still remains a great challenge for porous carbons as the electrodes for supercapacitors. We report a facile and scalable synthesis of N-doped aligned carbon nanosheet network (N-ACN10) with high surface area and efficient 3D ion and electron transport pathways. Moreover, 3D interconnected nanochannels parallel to the graphene planes are beneficial for the increased ion accessible surface area and fast ion diffusion. Benefiting from fast ion and electron transport kinetics, the N-ACN10 electrode exhibits excellent frequency response with a scan rate up to 5Vs−1, high capacitance of 331Fg−1 at 2mVs−1 and superior rate capability (203Fg−1 at 5Vs−1), as well as excellent cycling stability (98% of capacitance retention after 10,000 cycles) in 6M KOH. More importantly, the assembled N-ACN10//N-ACN10 supercapacitors exhibit outstanding electrochemical performances in 1M Na2SO4 and EMIMBF4 electrolytes with maximum energy densities of 20.6 and 120.4Whkg−1 based on the mass of total active material, respectively.

Multiple Network Alignment via MultiMAGNA+.

Network alignment (NA) aims to find a node mapping that identifies topologically or functionally similar network regions between molecular networks of different species. Analogous to genomic sequence alignment, NA can be used to transfer biological knowledge from well- to poorly-studied species between aligned network regions. Pairwise NA (PNA) finds similar regions between two networks while multiple NA (MNA) can align more than two networks. We focus on MNA. Existing MNA methods aim to maximize total similarity over all aligned nodes (node conservation). Then, they evaluate alignment quality by measuring the amount of conserved edges, but only after the alignment is constructed. Directly optimizing edge conservation during alignment construction in addition to node conservation may result in superior alignments. Thus, we present a novel MNA method called multiMAGNA++ that can achieve this. Indeed, multiMAGNA++ outperforms or is on par with existing MNA methods, while often completing faster than existing methods. That is, multiMAGNA++ scales well to larger network data and can be parallelized effectively. During method evaluation, we also introduce new MNA quality measures to allow for more fair MNA method comparison compared to the existing alignment quality measures. The multiMAGNA++ code is available on the method's web page at http://nd.edu/~cone/multiMAGNA++/.

Alignment of dynamic networks.

MotivationNetwork alignment (NA) aims to find a node mapping that conserves similar regions between compared networks. NA is applicable to many fields, including computational biology, where NA can guide the transfer of biological knowledge from well- to poorly-studied species across aligned network regions. Existing NA methods can only align static networks. However, most complex real-world systems evolve over time and should thus be modeled as dynamic networks. We hypothesize that aligning dynamic network representations of evolving systems will produce superior alignments compared to aligning the systems’ static network representations, as is currently done.ResultsFor this purpose, we introduce the first ever dynamic NA method, DynaMAGNA ++. This proof-of-concept dynamic NA method is an extension of a state-of-the-art static NA method, MAGNA++. Even though both MAGNA++ and DynaMAGNA++ optimize edge as well as node conservation across the aligned networks, MAGNA++ conserves static edges and similarity between static node neighborhoods, while DynaMAGNA++ conserves dynamic edges (events) and similarity between evolving node neighborhoods. For this purpose, we introduce the first ever measure of dynamic edge conservation and rely on our recent measure of dynamic node conservation. Importantly, the two dynamic conservation measures can be optimized with any state-of-the-art NA method and not just MAGNA++. We confirm our hypothesis that dynamic NA is superior to static NA, on synthetic and real-world networks, in computational biology and social domains. DynaMAGNA++ is parallelized and has a user-friendly graphical interface.Availability and implementation http://nd.edu/∼cone/DynaMAGNA++/.Supplementary information Supplementary data are available at Bioinformatics online.

The intricate anatomy of the periodontal ligament and its development: Lessons for periodontal regeneration

The periodontal ligament (PDL) connects the tooth root and alveolar bone. It is an aligned fibrous network that is interposed between, and anchored to, both mineralized surfaces. Periodontal disease is common and reduces the ability of the PDL to act as a shock absorber, a barrier for pathogens and a sensor of mastication. Although disease progression can be stopped, current therapies do not primarily focus on tissue regeneration. Functional regeneration of PDL may be achieved using innovative techniques, such as tissue engineering. However, the complex fibrillar architecture of the PDL, essential to withstand high forces, makes PDL tissue engineering very challenging. This challenge may be met by studying PDL anatomy and development. Understanding PDL anatomy, development and maintenance provides clues regarding the specific events that need to be mimicked for the formation of this intricate tissue. Owing to the specific composition of the PDL, which develops by self-organization, a different approach than the typical combination of biomaterials, growth factors and regenerative cells is necessary for functional PDL engineering. Most specifically, the architecture of the new PDL to be formed does not need to be dictated by textured biomaterials but can emerge from the local mechanical loading conditions. Elastic hydrogels are optimal to fill the space properly between tooth and bone, may house cells and growth factors to enhance regeneration and allow self-optimization by the alignment to local stresses. We suggest that cells and materials should be placed in a proper mechanical environment to initiate a process of self-organization resulting in a functional architecture of the PDL.

Interwoven Aligned Conductive Nanofiber Yarn/Hydrogel Composite Scaffolds for Engineered 3D Cardiac Anisotropy.

Mimicking the anisotropic cardiac structure and guiding 3D cellular orientation play a critical role in designing scaffolds for cardiac tissue regeneration. Significant advances have been achieved to control cellular alignment and elongation, but it remains an ongoing challenge for engineering 3D cardiac anisotropy using these approaches. Here, we present a 3D hybrid scaffold based on aligned conductive nanofiber yarns network (NFYs-NET, composition: polycaprolactone, silk fibroin, and carbon nanotubes) within a hydrogel shell for mimicking the native cardiac tissue structure, and further demonstrate their great potential for engineering 3D cardiac anisotropy for cardiac tissue engineering. The NFYs-NET structures are shown to control cellular orientation and enhance cardiomyocytes (CMs) maturation. 3D hybrid scaffolds were then fabricated by encapsulating NFYs-NET layers within hydrogel shell, and these 3D scaffolds performed the ability to promote aligned and elongated CMs maturation on each layer and individually control cellular orientation on different layers in a 3D environment. Furthermore, endothelialized myocardium was constructed by using this hybrid strategy via the coculture of CMs on NFYs-NET layer and endothelial cells within hydrogel shell. Therefore, these 3D hybrid scaffolds, containing NFYs-NET layer inducing cellular orientation, maturation, and anisotropy and hydrogel shell providing a suitable 3D environment for endothelialization, has great potential in engineering 3D cardiac anisotropy.

Anisotropically conductive polypropylene/nickel coated glass fiber composite via magnetic field inducement

In this work, we have reported a facile strategy to prepare an anisotropic conductive polypropylene/nickel coated glass fiber (PP/NCGF) composite with aligned NCGF network, through magnetic-assistant compression molding method. Owing to the high aspect ratio and particular magnetism, the conductive NCGF exhibits significant responsivity to the magnetic field during the molding process and thus aligns automatically in the PP matrix. The resultant PP/NCGF composite shows obvious anisotropy in electrical and electromagnetic interference (EMI) shielding performance. The electrical conductivity parallel to the magnetic field direction (1.46 S/m) is 18 times higher than that of perpendicular direction (8.06 × 10−2 S/m), and the EMI shielding effectiveness shows 8 dB disparity (15 dB in parallel direction and 23 dB in perpendicular direction). The anisotropic PP/NCGF composite would be considered as promising EMI shielding material where discrepant shielding level is required in orthogonal directions.

A Signal-Space Aligned Network Coding Approach to Distributed MIMO

This paper studies an uplink distributed MIMO (DMIMO) system that consists of $K$ users and $K^{\prime }$ distributed base stations (BSs), where the BSs are connected to a central unit (CU) via independent rate-constrained backhaul (BH) links. We propose a new signal-space aligned network coding scheme. First, a network coding generator matrix is selected subject to certain structural properties. Next, distributed linear precoding is employed by the users to create aligned signal-spaces at the BSs, according to the pattern determined by the network coding generator matrix. For each aligned signal-space at a BS, physical-layer network coding is utilized to compute the corresponding network-coded (NC) messages, where the actual number of NC messages forwarded to the CU is determined by the BH rate-constraint. We derive an achievable rate of the proposed scheme based on the existence of the NC generator matrix and signal-space alignment precoding matrices. For DMIMO with two and three BSs, the achievable rates and degrees of freedom (DoF) are evaluated and shown to outperform existing schemes. For example, for DMIMO with two BSs where each user and BS have $N$ and $N^{\prime }$ antennas, respectively, the proposed scheme achieves a DoF of $2\min \left(N,N^{\prime }\right) -1$ , if the BH capacity scales like $\left(2\min \left(N,N^{\prime }\right) -1\right) \log\;{SNR}$ . This leads to greater DoF compared to that utilizes the strategy for interference channel, whose DoF is $\min \left(N,N^{\prime }\right)$ . Numerical results demonstrate the performance advantage of the proposed scheme.

A study of electric field-induced conductive aligned network formation in high structure carbon black/silicone oil fluids

An electric field-induced alignment characteristics of high structure carbon black (HSCB) nanoparticles in silicone oil base fluids with different viscosities were investigated in this work. Resistivity change versus time of HSCB/silicone oil fluids with different concentrations of HSCB filler and different silicone oil viscosities was determined at different electric field strengths. Measurement results were analyzed using percolation theory by calculating critical concentration at which rapid increase of conductivity appears. An analytic model based on tunneling percolation theory was developed and successfully applied to explain the experimental results. The obtained results potentially can be used in the development of polymer composites with aligned nanoparticle structure.