A Study on the Dependence of Water Tree Permittivity with Time

During the growth of water trees in the insulation of a cable the distribution of the electric field is modified because of the local change of the dielectric properties of the material. It results a local enhancement of the electric field which could increase the risk of breakdown. The key factor is the permittivity of the water tree and the aim of the work is to determine its possible values and, particularly, the law of its increase with time during the of the trees. The paper presents permittivity measurements in uniform field in MV and powe

Fingering Instabilities in Dewetting Nanofluids

The growth of fingering patterns in dewetting nanofluids (colloidal solutions of thiol-passivated gold nanoparticles) has been followed in real time using contrast-enhanced video microscopy. The fingering instability on which we focus here arises from evaporatively-driven nucleation and growth a nanoscopically thin "precursor" solvent film behind the macroscopic contact line. We find that well-developed isotropic fingering structures only form for a narrow range of experimental parameters. Numerical simulations, based on a modification of the Monte Carlo approach introduced by Rabani et al. [Nature 426, 271 (2003)], reproduce the patterns we observe experimentally

A study of Docetaxel-induced effects in MCF-7 cells by means of Raman microspectroscopy

Chemotherapies feature a low success rate of about 25%, and therefore, the choice of the most effective cytostatic drug for the individual patient and monitoring the efficiency of an ongoing chemotherapy are important steps towards personalized therapy. Thereby, an objective method able to differentiate between treated and untreated cancer cells would be essential. In this study, we provide molecular insights into Docetaxel-induced effects in MCF-7 cells, as a model system for adenocarcinoma, by means of Raman microspectroscopy combined with powerful chemometric methods. The analysis of the Raman data is divided into two steps. In the first part, the morphology of cell organelles, e.g. the cell nucleus has been visualized by analysing the Raman spectra with k-means cluster analysis and artificial neural networks and compared to the histopathologic gold standard method hematoxylin and eosin staining. This comparison showed that Raman microscopy is capable of displaying the cell morphology; however, this is in contrast to hematoxylin and eosin staining label free and can therefore be applied potentially in vivo. Because Docetaxel is a drug acting within the cell nucleus, Raman spectra originating from the cell nucleus region were further investigated in a next step. Thereby we were able to differentiate treated from untreated MCF-7 cells and to quantify the cell–drug response by utilizing linear discriminant analysis models

Raman spectroscopy and advanced mathematical modelling in the discrimination of human thyroid cell lines

Raman spectroscopy could offer non-invasive, rapid and an objective nature to cancer diagnostics. However, much work in this field has focused on resolving differences between cancerous and non-cancerous tissues, and lacks the reproducibility and interpretation to be put into clinical practice. Much work is needed on basic cellular differences between malignancy and normal. This would allow the establishment of a clinically relevant cellular based model to translate to tissue classification. Raman spectroscopy provides a very detailed biochemical analysis of the target material and to 'unlock' this potential requires sophisticated mathematical modelling such as neural networks as an adjunct to data interpretation. Commercially obtained cancerous and non-cancerous cells, cultured in the laboratory were used in Raman spectral measurements. Data trends were visualised through PCA and then subjected to neural network analysis based on self-organising maps; consisting of m maps, where m is the number of classes to be recognised. Each map approximates the statistical distribution of a given class. The neural network analysis provided a 95% accuracy for identification of the cancerous cell line and 92% accuracy for normal cell line. In this preliminay study we have demonstrated th ability to distinguish between "normal" and cancerous commercial cell lines. This encourages future work to establish the reasons underpinning these spectral differences and to move forward to more complex systems involving tissues. We have also shown that the use of sophisticated mathematical modelling allows a high degree of discrimination of 'raw' spectral data

Rapid production of human liver scaffolds for functional tissue engineering by high shear stress oscillation-decellularization

The development of human liver scaffolds retaining their 3-dimensional structure and extra-cellular matrix (ECM) composition is essential for the advancement of liver tissue engineering. We report the design and validation of a new methodology for the rapid and accurate production of human acellular liver tissue cubes (ALTCs) using normal liver tissue unsuitable for transplantation. The application of high shear stress is a key methodological determinant accelerating the process of tissue decellularization while maintaining ECM protein composition, 3D-architecture and physico-chemical properties of the native tissue. ALTCs were engineered with human parenchymal and non-parenchymal liver cell lines (HepG2 and LX2 cells, respectively), human umbilical vein endothelial cells (HUVEC), as well as primary human hepatocytes and hepatic stellate cells. Both parenchymal and non-parenchymal liver cells grown in ALTCs exhibited markedly different gene expression when compared to standard 2D cell cultures. Remarkably, HUVEC cells naturally migrated in the ECM scaffold and spontaneously repopulated the lining of decellularized vessels. The metabolic function and protein synthesis of engineered liver scaffolds with human primary hepatocytes reseeded under dynamic conditions were maintained. These results provide a solid basis for the establishment of effective protocols aimed at recreating human liver tissue in vitro

Intracellular SERS nanoprobes for distinction of different neuronal cell types.

Distinction between closely related and morphologically similar cells is difficult by conventional methods especially without labeling. Using nuclear-targeted gold nanoparticles (AuNPs) as intracellular probes we demonstrate the ability to distinguish between progenitor and differentiated cell types in a human neuroblastoma cell line using surface-enhanced Raman spectroscopy (SERS). SERS spectra from the whole cell area as well as only the nucleus were analyzed using principal component analysis that allowed unambiguous distinction of the different cell types. SERS spectra from the nuclear region showed the developments during cellular differentiation by identifying an increase in DNA/RNA ratio and proteins transcribed. Our approach using nuclear-targeted AuNPs and SERS imaging provides label-free and noninvasive characterization that can play a vital role in identifying cell types in biomedical stem cell research

Gold Nanoparticle-Based Surface-Enhanced Raman Scattering for Noninvasive Molecular Probing of Embryonic Stem Cell Differentiation

This study reports the use of gold nanoparticle-based surface-enhanced Raman scattering (SERS) for probing the differentiation of mouse embryonic stem (mES) cells, including undifferentiated single cells, embryoid bodies (EBs), and terminally differentiated cardiomyocytes. Gold nanoparticles (GNPs) were successfully delivered into all 3 mES cell differentiation stages without affecting cell viability or proliferation. Transmission electron microscopy (TEM) confirmed the localization of GNPs inside the following cell organelles: mitochondria, secondary lysosome, and endoplasmic reticulum. Using bright- and dark-field imaging, the bright scattering of GNPs and nanoaggregates in all 3 ES cell differentiation stages could be visualized. EB (an early differentiation stage) and terminally differentiated cardiomyocytes both showed SERS peaks specific to metabolic activity in the mitochondria and to protein translation (amide I, amide II, and amide III peaks). These peaks have been rarely identified in undifferentiated single ES cells. Spatiotemporal changes observed in the SERS spectra from terminally differentiated cardiomyocyte tissues revealed local and dynamic molecular interactions as well as transformations during ES cell differentiation

Surface-enhanced Raman spectroscopy study of 4-ATP on gold nanoparticles for basal cell carcinoma fingerprint detection

The surface-enhanced Raman signals of 4-aminothiophenol (4-ATP) attached to the surface of colloidal gold nanoparticles with size distribution of 2 to 5 nm were used as a labeling agent to detect basal cell carcinoma (BCC) of the skin. The enhanced Raman band at 1075 cm-1 corresponding to the C-S stretching vibration in 4-ATP was observed during attachment to the surface of the gold nanoparticles. The frequency and intensity of this band did not change when the colloids were conjugated with BerEP4 antibody, which specifically binds to BCC. We show the feasibility of imaging BCC by surface-enhanced Raman spectroscopy, scanning the 1075 cm-1 band to detect the distribution of 4ATP-coated gold nanoparticles attached to skin tissue ex vivo

Analysis of Intracellular State Based on Controlled 3D Nanostructures Mediated Surface Enhanced Raman Scattering

Near-infrared surface-enhanced Raman spectroscopy (SERS) is a powerful technique for analyzing the chemical composition within a single living cell at unprecedented resolution. However, current SERS methods employing uncontrollable colloidal metal particles or non-uniformly distributed metal particles on a substrate as SERS-active sites show relatively low reliability and reproducibility. Here, we report a highly-ordered SERS-active surface that is provided by a gold nano-dots array based on thermal evaporation of gold onto an ITO surface through a nanoporous alumina mask. This new combined technique showed a broader distribution of hot spots and a higher signal-to-noise ratio than current SERS techniques due to the highly reproducible and uniform geometrical structures over a large area. This SERS-active surface was applied as cell culture system to study living cells in situ within their culture environment without any external preparation processes. We applied this newly developed method to cell-based research to differentiate cell lines, cells at different cell cycle stages, and live/dead cells. The enhanced Raman signals achieved from each cell, which represent the changes in biochemical compositions, enabled differentiation of each state and the conditions of the cells. This SERS technique employing a tightly controlled nanostructure array can potentially be applied to single cell analysis, early cancer diagnosis and cell physiology research