Thermally reduced Graphene Oxide: a well promising way to transparent flexible electrodes.

L'elaborato tratta dell'ottimizzazione del processo di riduzione termica dell'ossido di grafene in termini di conduttività e trasmittanza ottica. Definiti gli standard di deposizione tramite spin-coating e riduzione termica, i film prodotti vengono caratterizzati tramite XPS, AFM, UPS, TGA, ne vengono testate la conducibilità, con e senza effetto di gate, e la trasmittanza ottica, ne si misura l'elasticità tramite spettroscopia di forza, tutto al fine di comprendere l'evoluzione del processo termico di riduzione e di individuare i parametri migliori al fine di progredire verso la produzione di elettrodi flessibili e trasparenti a base di grafen ossido ridotto.

Mining tissue microarray data to uncover combinations of biomarker expression patterns that improve intermediate staging and grading of clear cell renal cell cancer

PURPOSE: Tumor stage and nuclear grade are the most important prognostic parameters of clear cell renal cell carcinoma (ccRCC). The progression risk of ccRCC remains difficult to predict particularly for tumors with organ-confined stage and intermediate differentiation grade. Elucidating molecular pathways deregulated in ccRCC may point to novel prognostic parameters that facilitate planning of therapeutic approaches. EXPERIMENTAL DESIGN: Using tissue microarrays, expression patterns of 15 different proteins were evaluated in over 800 ccRCC patients to analyze pathways reported to be physiologically controlled by the tumor suppressors von Hippel-Lindau protein and phosphatase and tensin homologue (PTEN). Tumor staging and grading were improved by performing variable selection using Cox regression and a recursive bootstrap elimination scheme. RESULTS: Patients with pT2 and pT3 tumors that were p27 and CAIX positive had a better outcome than those with all remaining marker combinations. A prolonged survival among patients with intermediate grade (grade 2) correlated with both nuclear p27 and cytoplasmic PTEN expression, as well as with inactive, nonphosphorylated ribosomal protein S6. By applying graphical log-linear modeling for over 700 ccRCC for which the molecular parameters were available, only a weak conditional dependence existed between the expression of p27, PTEN, CAIX, and p-S6, suggesting that the dysregulation of several independent pathways are crucial for tumor progression. CONCLUSIONS: The use of recursive bootstrap elimination, as well as graphical log-linear modeling for comprehensive tissue microarray (TMA) data analysis allows the unraveling of complex molecular contexts and may improve predictive evaluations for patients with advanced renal cancer.

Prognostic significance of apoptotic cell death in bladder cancer: a tissue microarray study on 179 urothelial carcinomas from cystectomy specimens

To assess the prognostic significance of apoptosis related markers in bladder cancer.

Cross-reactions vs co-sensitization evaluated by in silico motifs and in vitro IgE microarray testing

Using an in silico allergen clustering method, we have recently shown that allergen extracts are highly cross-reactive. Here we used serological data from a multi-array IgE test based on recombinant or highly purified natural allergens to evaluate whether co-reactions are true cross-reactions or co-sensitizations by allergens with the same motifs.

A Model to Predict Percolation Threshold and Effective Conductivity of Infiltrated Electrodes for Solid Oxide Fuel Cells

We present a mechanistic modeling methodology to predict both the percolation threshold and effective conductivity of infiltrated Solid Oxide Fuel Cell (SOFC) electrodes. The model has been developed to mirror each step of the experimental fabrication process. The primary model output is the infiltrated electrode effective conductivity which provides results over a range of infiltrate loadings that are independent of the chosen electronically conducting material. The percolation threshold is utilized as a valuable output data point directly related to the effective conductivity to compare a wide range of input value choices. The predictive capability of the model is demonstrated by favorable comparison to two separate published experimental studies, one using strontium molybdate and one using La0.8Sr0.2FeO3-δ as infiltrate materials. Effective conductivities and percolation thresholds are shown for varied infiltrate particle size, pore size, and porosity with the infiltrate particle size having the largest impact on the results.

A Model to Predict Percolation Threshold and Effective Conductivity of Infiltrated Electrodes for Solid Oxide Fuel Cells

We present a mechanistic modeling methodology to predict both the percolation threshold and effective conductivity of infiltrated Solid Oxide Fuel Cell (SOFC) electrodes. The model has been developed to mirror each step of the experimental fabrication process. The primary model output is the infiltrated electrode effective conductivity which provides results over a range of infiltrate loadings that are independent of the chosen electronically conducting material. The percolation threshold is utilized as a valuable output data point directly related to the effective conductivity to compare a wide range of input value choices. The predictive capability of the model is demonstrated by favorable comparison to two separate published experimental studies, one using strontium molybdate and one using La0.8Sr0.2FeO3-delta as infiltrate materials. Effective conductivities and percolation thresholds are shown for varied infiltrate particle size, pore size, and porosity with the infiltrate particle size having the largest impact on the results. (C) 2013 The Electrochemical Society. All rights reserved.

Redox-Switching in a Viologen-type Adlayer: An Electrochemical Shell-Isolated Nanoparticle Enhanced Raman Spectroscopy Study on Au(111)-(1 x 1) Single Crystal Electrodes

We reported the first application of in situ shell-isolated nanoparticle enhanced Raman spectroscopy (SHINERS) to an interfacial redox reaction under electrochemical conditions. We construct gap-mode sandwich structures composed of a thiol-terminated HS-6V6H viologen adlayer immobilized on a single crystal Au(111)-(1x1) electrode and covered by Au(60 nm)@SlO(2) core shell nanoparticles acting as plasmonic antennas. We observed high-quality, potential-dependent Raman spectra of the three viologen species V(2+),V(+center dot) and V(0) on a well-defined Au(111) substrate surface and could map their potential-dependent evolution. Comparison with experiments on powder samples revealed an enhancement factor of the nonresonant Raman modes of similar to 3 x 10(5), and up to 9 x 10(7) for the resonance modes. The study illustrates the unique capability of SHINERS and its potential in the entire field of electrochemical surface science to explore structures and reaction pathways on well-defined substrate surfaces, such as single crystals, for molecular, (electro-)- catalytic, bioelectrochemical systems up to fundamental double layer studies at electrified solid/liquid interfaces.

Human epidermal growth factor receptor-2 gene amplification in gastric cancer using tissue microarray technology

To assess human epidermal growth factor receptor-2 (HER2)-status in gastric cancer and matched lymph node metastases by immunohistochemistry (IHC) and chromogenic in situ hybridization (CISH).

Serodiagnosis of Echinococcus spp. infection: explorative selection of diagnostic antigens by peptide microarray

BACKGROUND: Production of native antigens for serodiagnosis of helminthic infections is laborious and hampered by batch-to-batch variation. For serodiagnosis of echinococcosis, especially cystic disease, most screening tests rely on crude or purified Echinococcus granulosus hydatid cyst fluid. To resolve limitations associated with native antigens in serological tests, the use of standardized and highly pure antigens produced by chemical synthesis offers considerable advantages, provided appropriate diagnostic sensitivity and specificity is achieved. METHODOLOGY/PRINCIPAL FINDINGS: Making use of the growing collection of genomic and proteomic data, we applied a set of bioinformatic selection criteria to a collection of protein sequences including conceptually translated nucleotide sequence data of two related tapeworms, Echinococcus multilocularis and Echinococcus granulosus. Our approach targeted alpha-helical coiled-coils and intrinsically unstructured regions of parasite proteins potentially exposed to the host immune system. From 6 proteins of E. multilocularis and 5 proteins of E. granulosus, 45 peptides between 24 and 30 amino acids in length were designed. These peptides were chemically synthesized, spotted on microarrays and screened for reactivity with sera from infected humans. Peptides reacting above the cut-off were validated in enzyme-linked immunosorbent assays (ELISA). Peptides identified failed to differentiate between E. multilocularis and E. granulosus infection. The peptide performing best reached 57% sensitivity and 94% specificity. This candidate derived from Echinococcus multilocularis antigen B8/1 and showed strong reactivity to sera from patients infected either with E. multilocularis or E. granulosus. CONCLUSIONS/SIGNIFICANCE: This study provides proof of principle for the discovery of diagnostically relevant peptides by bioinformatic selection complemented with screening on a high-throughput microarray platform. Our data showed that a single peptide cannot provide sufficient diagnostic sensitivity whereas pooling several peptide antigens improved sensitivity; thus combinations of several peptides may lead the way to new diagnostic tests that replace, or at least complement conventional immunodiagnosis of echinococcosis. Our strategy could prove useful for diagnostic developments in other pathogens.

Development of Solid Oxide Fuel Cell Electrodes with High Conductivity and Enhanced Redox Stability

The intent of this study was the development of new ceramic SOFC anode materials which possess electrical conductivity as well as redox stability.

The Effect of Various Electrode Microstructure Parameters on the Effective Conductivity and Three-Phase Boundary Density of Infiltrated SOFC Electrodes

Solid oxide fuel cell (SOFC) technology has the potential to be a significant player in our future energy technology repertoire based on its ability to convert chemical energy into electrical energy. Infiltrated SOFCs, in particular, have demonstrated improved performance and at lower cost than traditional SOFCs. An infiltrated electrode comprises porous ceramic scaffolding (typically constructed from the oxygen ion conducting material) that is infiltrated with electron conducting and catalytic particles. Two important SOFC electrode properties are effective conductivity and three phase boundary density (TPB). Researchers study these electrode properties separately, and fail to recognize them as competing properties. This thesis aims to (1) develop a method to model the TPB density and use it to determine the effect of porosity, scaffolding particle size, and pore former size on TPB density as well as to (2) compare the effect of porosity, scaffolding particle size, and pore former size on TPB density and effective conductivity to determine a desired set of parameters for infiltrated SOFC electrode performance. A computational model was used to study the effect of microstructure parameters on the effective conductivity and TPB density of the infiltrated SOFC electrode. From this study, effective conductivity and TPB density are determined to be competing properties of SOFC electrodes. Increased porosity, scaffolding particle size, and pore former particle size increase the effective conductivity for a given infiltrate loading above percolation threshold. Increased scaffolding particle size and pore former size ratio, however, decreases the TPB density. The maximum TPB density is achievable between porosities of 45% and 60%. The effect of microstructure parameters are more prominent at low loading with scaffolding particle size being the most significant factor and pore former size ratio being the least significant factor.