Synthesis and Photoluminescence Properties of Porous Silicon Nanowire Arrays

Herein, we prepare vertical and single crystalline porous silicon nanowires (SiNWs) via a two-step metal-assisted electroless etching method. The porosity of the nanowires is restricted by etchant concentration, etching time and doping lever of the silicon wafer. The diffusion of silver ions could lead to the nucleation of silver nanoparticles on the nanowires and open new etching ways. Like porous silicon (PS), these porous nanowires also show excellent photoluminescence (PL) properties. The PL intensity increases with porosity, with an enhancement of about 100 times observed in our condition experiments. A “red-shift” of the PL peak is also found. Further studies prove that the PL spectrum should be decomposed into two elementary PL bands. The peak at 850 nm is the emission of the localized excitation in the nanoporous structure, while the 750-nm peak should be attributed to the surface-oxidized nanostructure. It could be confirmed from the Fourier transform infrared spectroscopy analyses. These porous SiNW arrays may be useful as the nanoscale optoelectronic devices

Routine Modeling with Time Series Metric Learning

version éditeur : https://rd.springer.com/chapter/10.1007/978-3-030-30484-3_47International audienceTraditionally, the automatic recognition of human activities is performed with supervised learning algorithms on limited sets of specific activities. This work proposes to recognize recurrent activity patterns, called routines, instead of precisely defined activities. The modeling of routines is defined as a metric learning problem, and an architecture, called SS2S, based on sequence-to-sequence models is proposed to learn a distance between time series. This approach only relies on inertial data and is thus non intrusive and preserves privacy. Experimental results show that a clustering algorithm provided with the learned distance is able to recover daily routines

Efficient Colonization and Therapy of Human Hepatocellular Carcinoma (HCC) Using the Oncolytic Vaccinia Virus Strain GLV-1h68

Virotherapy using oncolytic vaccinia virus strains is one of the most promising new strategies for cancer therapy. In this study, we analyzed for the first time the therapeutic efficacy of the oncolytic vaccinia virus GLV-1h68 in two human hepatocellular carcinoma cell lines HuH7 and PLC/PRF/5 (PLC) in cell culture and in tumor xenograft models. By viral proliferation assays and cell survival tests, we demonstrated that GLV-1h68 efficiently colonized, replicated in, and did lyse these cancer cells in culture. Experiments with HuH7 and PLC xenografts have revealed that a single intravenous injection (i.v.) of mice with GLV-1h68 resulted in a significant reduction of primary tumor sizes compared to uninjected controls. In addition, replication of GLV-1h68 in tumor cells led to strong inflammatory and oncolytic effects resulting in intense infiltration of MHC class II-positive cells like neutrophils, macrophages, B cells and dendritic cells and in up-regulation of 13 pro-inflammatory cytokines. Furthermore, GLV-1h68 infection of PLC tumors inhibited the formation of hemorrhagic structures which occur naturally in PLC tumors. Interestingly, we found a strongly reduced vascular density in infected PLC tumors only, but not in the non-hemorrhagic HuH7 tumor model. These data demonstrate that the GLV-1h68 vaccinia virus may have an enormous potential for treatment of human hepatocellular carcinoma in man

Nuclear envelope structural defects cause chromosomal numerical instability and aneuploidy in ovarian cancer

<p>Abstract</p> <p>Background</p> <p>Despite our substantial understanding of molecular mechanisms and gene mutations involved in cancer, the technical approaches for diagnosis and prognosis of cancer are limited. In routine clinical diagnosis of cancer, the procedure is very basic: nuclear morphology is used as a common assessment of the degree of malignancy, and hence acts as a prognostic and predictive indicator of the disease. Furthermore, though the atypical nuclear morphology of cancer cells is believed to be a consequence of oncogenic signaling, the molecular basis remains unclear. Another common characteristic of human cancer is aneuploidy, but the causes and its role in carcinogenesis are not well established.</p> <p>Methods</p> <p>We investigated the expression of the nuclear envelope proteins lamin A/C in ovarian cancer by immunohistochemistry and studied the consequence of lamin A/C suppression using siRNA in primary human ovarian surface epithelial cells in culture. We used immunofluorescence microscopy to analyze nuclear morphology, flow cytometry to analyze cellular DNA content, and fluorescence <it>in situ </it>hybridization to examine cell ploidy of the lamin A/C-suppressed cells.</p> <p>Results</p> <p>We found that nuclear lamina proteins lamin A/C are often absent (47%) in ovarian cancer cells and tissues. Even in lamin A/C-positive ovarian cancer, the expression is heterogeneous within the population of tumor cells. In most cancer cell lines, a significant fraction of the lamin A/C-negative population was observed to intermix with the lamin A/C-positive cells. Down regulation of lamin A/C in non-cancerous primary ovarian surface epithelial cells led to morphological deformation and development of aneuploidy. The aneuploid cells became growth retarded due to a p53-dependent induction of the cell cycle inhibitor p21.</p> <p>Conclusions</p> <p>We conclude that the loss of nuclear envelope structural proteins, such as lamin A/C, may underlie two of the hallmarks of cancer - aberrations in nuclear morphology and aneuploidy.</p

Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes

Comparative study of unsupervised dimension reduction techniques for the visualization of microarray gene expression data

<p>Abstract</p> <p>Background</p> <p>Visualization of DNA microarray data in two or three dimensional spaces is an important exploratory analysis step in order to detect quality issues or to generate new hypotheses. Principal Component Analysis (PCA) is a widely used linear method to define the mapping between the high-dimensional data and its low-dimensional representation. During the last decade, many new nonlinear methods for dimension reduction have been proposed, but it is still unclear how well these methods capture the underlying structure of microarray gene expression data. In this study, we assessed the performance of the PCA approach and of six nonlinear dimension reduction methods, namely Kernel PCA, Locally Linear Embedding, Isomap, Diffusion Maps, Laplacian Eigenmaps and Maximum Variance Unfolding, in terms of visualization of microarray data.</p> <p>Results</p> <p>A systematic benchmark, consisting of Support Vector Machine classification, cluster validation and noise evaluations was applied to ten microarray and several simulated datasets. Significant differences between PCA and most of the nonlinear methods were observed in two and three dimensional target spaces. With an increasing number of dimensions and an increasing number of differentially expressed genes, all methods showed similar performance. PCA and Diffusion Maps responded less sensitive to noise than the other nonlinear methods.</p> <p>Conclusions</p> <p>Locally Linear Embedding and Isomap showed a superior performance on all datasets. In very low-dimensional representations and with few differentially expressed genes, these two methods preserve more of the underlying structure of the data than PCA, and thus are favorable alternatives for the visualization of microarray data.</p

c-Abl downregulates the slow phase of double-strand break repair

c-Abl tyrosine kinase is activated by agents that induce double-strand DNA breaks (DSBs) and interacts with key components of the DNA damage response and of the DSB repair machinery. However, the functional significance of c-Abl in these processes, remained unclear. In this study, we demonstrate, using comet assay and pulsed-field gel electrophoresis, that c-Abl inhibited the repair of DSBs induced by ionizing radiation, particularly during the second and slow phase of DSB repair. Pharmacological inhibition of c-Abl and c-Abl depletion by siRNA-mediated knockdown resulted in higher DSB rejoining. c-Abl null MEFs exhibited higher DSB rejoining compared with cells reconstituted for c-Abl expression. Abrogation of c-Abl kinase activation resulted in higher H2AX phosphorylation levels and higher numbers of post-irradiation γH2AX foci, consistent with a role of c-Abl in DSB repair regulation. In conjunction with these findings, transient abrogation of c-Abl activity resulted in increased cellular radioresistance. Our findings suggest a novel function for c-Abl in inhibition of the slow phase of DSB repair

A facile chemical conversion synthesis of Sb2S3 nanotubes and the visible light-driven photocatalytic activities

We report a simple chemical conversion and cation exchange technique to realize the synthesis of Sb2S3 nanotubes at a low temperature of 90°C. The successful chemical conversion from ZnS nanotubes to Sb2S3 ones benefits from the large difference in solubility between ZnS and Sb2S3. The as-grown Sb2S3 nanotubes have been transformed from a weak crystallization to a polycrystalline structure via successive annealing. In addition to the detailed structural, morphological, and optical investigation of the yielded Sb2S3 nanotubes before and after annealing, we have shown high photocatalytic activities of Sb2S3 nanotubes for methyl orange degradation under visible light irradiation. This approach offers an effective control of the composition and structure of Sb2S3 nanomaterials, facilitates the production at a relatively low reaction temperature without the need of organics, templates, or crystal seeds, and can be extended to the synthesis of hollow structures with various compositions and shapes for unique properties

Alterations of the extracellular matrix in ovarian cancer studied by Second Harmonic Generation imaging microscopy

<p>Abstract</p> <p>Background</p> <p>Remodeling of the extracellular matrix (ECM) has been implicated in ovarian cancer, and we hypothesize that these alterations may provide a better optical marker of early disease than currently available imaging/screening methods and that understanding their physical manifestations will provide insight into invasion.</p> <p>Methods</p> <p>For this investigation we use Second Harmonic Generation (SHG) imaging microcopy to study changes in the structure of the ovarian ECM in human normal and malignant ex vivo biopsies. This method directly visualizes the type I collagen in the ECM and provides quantitative metrics of the fibrillar assembly. To quantify these changes in collagen morphology we utilized an integrated approach combining 3D SHG imaging measurements and bulk optical parameter measurements in conjunction with Monte Carlo simulations of the experimental data to extract tissue structural properties.</p> <p>Results</p> <p>We find the SHG emission attributes (directionality and relative intensity) and bulk optical parameters, both of which are related to the tissue structure, are significantly different in the tumors in a manner that is consistent with the change in collagen assembly. The normal and malignant tissues have highly different collagen fiber assemblies, where collectively, our findings show that the malignant ovaries are characterized by lower cell density, denser collagen, as well as higher regularity at both the fibril and fiber levels. This further suggests that the assembly in cancer may be comprised of newly synthesized collagen as opposed to modification of existing collagen.</p> <p>Conclusions</p> <p>Due to the large structural changes in tissue assembly and the SHG sensitivity to these collagen alterations, quantitative discrimination is achieved using small patient data sets. Ultimately these measurements may be developed as intrinsic biomarkers for use in clinical applications.</p