Polymer-mediated synthesis of γ-Fe2O3 nano-particles

Nano-particles of γ-Fe2O3 were synthesized by reacting polyethylene oxide–FeCl3 complex with NH4OH. These were characterized by X-ray diffraction (XRD), scanning electron miscroscopy (SEM), selected area electron diffraction (SAED) and transmision electron microscopy (TEM). The average particle size was found to be 10 nm, as determined from the line broadening of the main XRD peak. The crystalline phase was a spinel-type tetragonal structure, which was confirmed from the electron diffraction pattern. The zero field cooled magnetization of samples with varying γ-Fe2O3 content as a function of temperature was measured using a vibrating sample magnetometer. The magnetization curves show a peak at low temperature (15 K) corresponding to the blocking temperature TB. The value of TB was found to decrease with decreasing particle size. The magnetization measurements with respect to field at 5 and 170 K confirmed the transition from superparamagnetic to spin-glass state at TB, as evidenced from the remanence and hysteresis. These results can be explained on the basis of Néel's theory of superparamagnetism as applied to nano-particles.

Energetic and thermal properties of tilt grain boundaries in graphene/hexagonal boron nitride heterostructures

Graphene/hexagonal boron nitride (G/h-BN) heterostructure has attracted tremendous research efforts owing to its great potential for applications in nano-scale electronic devices. In such hybrid materials, tilt grain boundaries (GBs) between graphene and h-BN grains may have unique physical properties, which have not been well understood. Here we have conducted non-equilibrium molecular dynamics simulations to study the energetic and thermal properties of tilt GBs in G/h-BN heterostructures. The effect of misorientation angles of tilt GBs on both GB energy and interfacial thermal conductance are investigated.

Nanoscale texture on glass and titanium substrates by physical vapor deposition process

The aim of the paper is to give a feasibility study on the material deposition of Nanoscale textured morphology of titanium and titanium oxide layers on titanium and glass substrates. As a recent development in nanoscale deposition, Physical Vapor Deposition (PVD) based DC magnetron sputtering has been the choice for the deposition process. The nanoscale morphology and surface roughness of the samples have been characterized using Atomic Force Microscope (AFM). The surface roughnesses obtained from AFM have been compared using surface profiler. From the results we can say that the roughness values are dependent on the surface roughness of the substrate. The glass substrate was relatively smoother than the titanium plate and hence lower layer roughness was obtained. From AFM a unique nano-pattern of a boomerang shaped titanium oxide layer on glass substrate have been obtained. The boomerang shaped nano-scale pattern was found to be smaller when the layer was deposited at higher sputtering power. This indicated that the morphology of the deposited titanium oxide layer has been influenced by the sputtering power.

Jet and flash imprint defectivity - Assessment and reduction for semiconductor applications

Defectivity has been historically identified as a leading technical roadblock to the implementation of nanoimprint lithography for semiconductor high volume manufacturing. The lack of confidence in nanoimprint's ability to meet defect requirements originates in part from the industry's past experiences with 1 × lithography and the shortage in enduser generated defect data. SEMATECH has therefore initiated a defect assessment aimed at addressing these concerns. The goal is to determine whether nanoimprint, specifically Jet and Flash Imprint Lithography from Molecular Imprints, is capable of meeting semiconductor industry defect requirements. At this time, several cycles of learning have been completed in SEMATECH's defect assessment, with promising results. J-FIL process random defectivity of < 0.1 def/cm2 has been demonstrated using a 120nm half-pitch template, providing proof of concept that a low defect nanoimprint process is possible. Template defectivity has also improved significantly as shown by a pre-production grade template at 80nm pitch. Cycles of learning continue on feature sizes down to 22nm. © 2011 SPIE.

Bacterial adherence and biofilm formation on medical implants : a review

Biofilms are a complex group of microbial cells that adhere to the exopolysaccharide matrix present on the surface of medical devices. Biofilm-associated infections in the medical devices pose a serious problem to the public health and adversely affect the function of the device. Medical implants used in oral and orthopedic surgery are fabricated using alloys such as stainless steel and titanium. The biological behavior, such as osseointegration and its antibacterial activity, essentially depends on both the chemical composition and the morphology of the surface of the device. Surface treatment of medical implants by various physical and chemical techniques are attempted in order to improve their surface properties so as to facilitate bio-integration and prevent bacterial adhesion. The potential source of infection of the surrounding tissue and antimicrobial strategies are from bacteria adherent to or in a biofilm on the implant which should prevent both biofilm formation and tissue colonization. This article provides an overview of bacterial biofilm formation and methods adopted for the inhibition of bacterial adhesion on medical implants

The BAD project: data mining, database and prediction of protein adsorption on surfaces

Protein adsorption at solid-liquid interfaces is critical to many applications, including biomaterials, protein microarrays and lab-on-a-chip devices. Despite this general interest, and a large amount of research in the last half a century, protein adsorption cannot be predicted with an engineering level, design-orientated accuracy. Here we describe a Biomolecular Adsorption Database (BAD), freely available online, which archives the published protein adsorption data. Piecewise linear regression with breakpoint applied to the data in the BAD suggests that the input variables to protein adsorption, i.e., protein concentration in solution; protein descriptors derived from primary structure (number of residues, global protein hydrophobicity and range of amino acid hydrophobicity, isoelectric point); surface descriptors (contact angle); and fluid environment descriptors (pH, ionic strength), correlate well with the output variable-the protein concentration on the surface. Furthermore, neural network analysis revealed that the size of the BAD makes it sufficiently representative, with a neural network-based predictive error of 5% or less. Interestingly, a consistently better fit is obtained if the BAD is divided in two separate sub-sets representing protein adsorption on hydrophilic and hydrophobic surfaces, respectively. Based on these findings, selected entries from the BAD have been used to construct neural network-based estimation routines, which predict the amount of adsorbed protein, the thickness of the adsorbed layer and the surface tension of the protein-covered surface. While the BAD is of general interest, the prediction of the thickness and the surface tension of the protein-covered layers are of particular relevance to the design of microfluidics devices.

Single-cell force spectroscopy, an emerging tool to quantify cell adhesion to biomaterials

Cell adhesion receptors play a central role in sensing and integrating signals provided by the cellular environment. Thus, understanding adhesive interactions at the cell-biomaterial interface is essential to improve the design of implants that should emulate certain characteristics of the cell's natural environment. Numerous cell adhesion assays have been developed; among these, atomic force microscopy-based single-cell force spectroscopy (AFM-SCFS) provides a versatile tool to quantify cell adhesion at physiological conditions. Here we discuss how AFM-SCFS can be used to quantify the adhesion of living cells to biomaterials and give examples of using AFM-SCFS in tissue engineering and regenerative medicine. We anticipate that in the near future, AFM-SCFS will be established in the biomaterial field as an important technique to quantify cell-biomaterial interactions and thereby will contribute to the optimization of implants, scaffolds, and medical devices.

Stimulation of osteogenesis and angiogenesis of hBMSCs by delivering Si ions and functional drug from mesoporous silica nanospheres

Multifunctional bioactive materials with the ability to stimulate osteogenesis and angiogenesis of stem cells play an important role in the regeneration of bone defects. However, how to develop such biomaterials remains a significant challenge. In this study, we prepared mesoporous silica nanospheres (MSNs) with uniform sphere size (∼90 nm) and mesopores (∼2.7 nm), which could release silicon ions (Si) to stimulate the osteogenic differentiation of human bone marrow stromal cells (hBMSCs) via activating their ALP activity, bone-related gene and protein (OCN, RUNX2 and OPN) expression. Hypoxia-inducing therapeutic drug, dimethyloxaloylglycine (DMOG), was effectively loaded in the mesopores of MSNs (D-MSNs). The sustained release of DMOG from D-MSNs could stabilize HIF-1α and further stimulated the angiogenic differentiation of hBMSCs as indicated by the enhanced VEGF secretion and protein expression. Our study revealed that D-MSNs could combine the stimulatory effect on both osteogenic and angiogenic activity of hBMSCs. The potential mechanism of D-MSN-stimulated osteogenesis and angiogenesis was further elucidated by the supplementation of cell culture medium with pure Si ions and DMOG. Considering the easy handling characteristics of nanospheres, the prepared D-MSNs may be applied in the forms of injectable spheres for minimally invasive surgery, or MSNs/polymer composite scaffolds for bone defect repair. The concept of delivering both stimulatory ions and functional drugs may offer a new strategy to construct a multifunctional biomaterial system for bone tissue regeneration.

Excitation of bound plasmons along nanoscale stripe waveguides: A comparison of end and grating coupling techniques

In this paper we excite bound long range stripe plasmon modes with a highly focused laser beam. We demonstrate highly confined plasmons propagating along a 50 μm long silver stripe 750 nm wide and 30 nm thick. Two excitation techniques were studied: focusing the laser spot onto the waveguide end and focusing the laser spot onto a silver grating. By comparing the intensity of the out-coupling photons at the end of the stripe for both grating and end excitation we are able to show that gratings provide an increase of a factor of two in the output intensity and thus out-coupling of plasmons excited by this technique are easier to detect. Authors expect that the outcome of this paper will prove beneficial for the development of passive nano-optical devices based on stripe waveguides, by providing insight into the different excitation techniques available and the advantages of each technique.

Graphene-oxide-modified β-tricalcium phosphate bioceramics stimulate in vitro and in vivo osteogenesis

Graphene oxide (GO) has attracted much interest for applications in bone tissue engineering; however, until now the interaction between GO and stem cells, and the in vivo bone-forming ability of GO has not been explored. The aim of this study was to produce a GO-modified β-tricalcium phosphate (β-TCP-GRA) biceramics and then explore the material’s osteogenic capacity in vitro and in vivo, as well as unravel some of the molecular mechanisms behind this. β-TCP-GRA disks and scaffolds were successfully prepared by a simple GO/water suspension soaking method in combination with heat treatment. These scaffolds were found to significantly enhance the proliferation, alkaline phosphatase activity and osteogenic gene expression of human bone marrow stromal cells (hBMSCs), when compared to β-TCP without GO modification (controls). Activation of the Wnt/β-catenin signaling pathway in hBMSCs appears to be the mechanism behind this osteogenic induction by β-TCP-GRA. β-TCP-GRA scaffolds led to an increased rate of in vivo new bone formation compared to β-TCP controls, indicative of the stimulatory effect of GO on in vivo osteogenesis, making GO modification of β-TCP a very promising method for applications in bone tissue engineering, in particular for the regeneration of large bone defects.

A new registration method based on Log-Euclidean tensor metrics and its application to genetic studies

In structural brain MRI, group differences or changes in brain structures can be detected using Tensor-Based Morphometry (TBM). This method consists of two steps: (1) a non-linear registration step, that aligns all of the images to a common template, and (2) a subsequent statistical analysis. The numerous registration methods that have recently been developed differ in their detection sensitivity when used for TBM, and detection power is paramount in epidemological studies or drug trials. We therefore developed a new fluid registration method that computes the mappings and performs statistics on them in a consistent way, providing a bridge between TBM registration and statistics. We used the Log-Euclidean framework to define a new regularizer that is a fluid extension of the Riemannian elasticity, which assures diffeomorphic transformations. This regularizer constrains the symmetrized Jacobian matrix, also called the deformation tensor. We applied our method to an MRI dataset from 40 fraternal and identical twins, to revealed voxelwise measures of average volumetric differences in brain structure for subjects with different degrees of genetic resemblance.

Quantitative genetic modeling of lateral ventricular shape and volume using multi-atlas fluid image alignment in twins

Despite substantial progress in measuring the 3D profile of anatomical variations in the human brain, their genetic and environmental causes remain enigmatic. We developed an automated system to identify and map genetic and environmental effects on brain structure in large brain MRI databases . We applied our multi-template segmentation approach ("Multi-Atlas Fluid Image Alignment") to fluidly propagate hand-labeled parameterized surface meshes into 116 scans of twins (60 identical, 56 fraternal), labeling the lateral ventricles. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps revealed 3D heritability patterns, and their significance, with and without adjustments for global brain scale. These maps visualized detailed profiles of environmental versus genetic influences on the brain, extending genetic models to spatially detailed, automatically computed, 3D maps.

Changes in anatomical brain connectivity between ages 12 and 30: A HARDI study of 467 adolescents and adults

Graph theory can be applied to matrices that represent the brain's anatomical connections, to better understand global properties of anatomical networks, such as their clustering, efficiency and "small-world" topology. Network analysis is popular in adult studies of connectivity, but only one study - in just 30 subjects - has examined how network measures change as the brain develops over this period. Here we assessed the developmental trajectory of graph theory metrics of structural brain connectivity in a cross-sectional study of 467 subjects, aged 12 to 30. We computed network measures from 70×70 connectivity matrices of fiber density generated using whole-brain tractography in 4-Tesla 105-gradient high angular resolution diffusion images (HARDI). We assessed global efficiency and modularity, and both age and age 2 effects were identified. HARDI-based connectivity maps are sensitive to the remodeling and refinement of structural brain connections as the human brain develops.