Microwave sintering of yttria-containing tetragonal zirconia polycrystal (Y-TZP) ceramics

Sintering of yttria-containing tetragonal zirconia polycrystal (Y-TZP) ceramics was performed in a single-mode cylindrical cavity applicator CMPR-250 operating at 2·45 GHz in the TM012 mode. High heating rates at low power levels were achieved. Rapid heating and cooling resulted in a fine-grain microstructure. High-purity submicron Y-TZP powders were sintered from an initial green density of 60% to final sintered density close to the theoretical density. Microwave sintering offers potential for improving microstructural properties through controlled development of uniform microstructure. © 1994 the Indian Academy of Sciences

Processing and properties of zirconia-toughened alumina ceramics

Al2O3:ZrO2 ceramics have been prepared from physically mixed pure oxide powders. The results indicate that careful processing of the starting powders and a two-stage sintering process can avoid expensive processing methods like hot pressing/hot isostatic pressing used for achieving high densification. The mechanical properties were measured and the resultant microstructure studied to explain the toughening behaviour of this material. © 1994 the Indian Academy of Sciences

Investigation on some ceramic materials for electrochemical device applications

The recent developments in the field of high temperature technology demand materials with tailor-made electrical properties. These conductors play an important role in many practical applications. Energy conversion devices like fuel cells require solid electrolyte materials with ionic conductivity and electrodes with electronic conductivity. Mixed conductors are useful for high- temperature electrolysis of water vapor resulting in substantial energy savings in comparison with conventional electrolysis techniques. Because of their stability and reasonably high conductivity the cubic fluorite oxides of zirconia-ceria and chromite-based perovskites have received considerable attention for such applications. Ceramics based on tetragonal zirconia polycrystal (TZP) are being projected as potential fuel cell electrolyte materials. Microwave processing of these materials is a promising approach for the future development of ceramic devices for various electrochemical applications. As a part of the program designed to develop suitable materials for some of these applications, this paper will cover the method of preparation and electrical conductivity study performed on (ZrO2)0.85(CeO2)0.12(Y2O3)0.03 and doped chromites A1-xSrxCrO3 (A = La, Y). We have also successfully sintered the Y-TZP ceramics to density close to the theoretical by using microwave energy and a single mode applicator. Some of the results will be presented in this paper. © 1992

A scalable, open-source implementation of a large-scale mechanistic model for single cell proliferation and death signaling

Abstract Mechanistic models of how single cells respond to different perturbations can help integrate disparate big data sets or predict response to varied drug combinations. However, the construction and simulation of such models have proved challenging. Here, we developed a python-based model creation and simulation pipeline that converts a few structured text files into an SBML standard and is high-performance- and cloud-computing ready. We applied this pipeline to our large-scale, mechanistic pan-cancer signaling model (named SPARCED) and demonstrate it by adding an IFNγ pathway submodel. We then investigated whether a putative crosstalk mechanism could be consistent with experimental observations from the LINCS MCF10A Data Cube that IFNγ acts as an anti-proliferative factor. The analyses suggested this observation can be explained by IFNγ-induced SOCS1 sequestering activated EGF receptors. This work forms a foundational recipe for increased mechanistic model-based data integration on a single-cell level, an important building block for clinically-predictive mechanistic models.</p

A scalable, open-source implementation of a large-scale mechanistic model for single cell proliferation and death signaling

AbstractMechanistic models of how single cells respond to different perturbations can help integrate disparate big data sets or predict response to varied drug combinations. However, the construction and simulation of such models have proved challenging. Here, we developed a python-based model creation and simulation pipeline that converts a few structured text files into an SBML standard and is high-performance- and cloud-computing ready. We applied this pipeline to our large-scale, mechanistic pan-cancer signaling model (named SPARCED) and demonstrate it by adding an IFNγ pathway submodel. We then investigated whether a putative crosstalk mechanism could be consistent with experimental observations from the LINCS MCF10A Data Cube that IFNγ acts as an anti-proliferative factor. The analyses suggested this observation can be explained by IFNγ-induced SOCS1 sequestering activated EGF receptors. This work forms a foundational recipe for increased mechanistic model-based data integration on a single-cell level, an important building block for clinically-predictive mechanistic models.</jats:p

A Scalable, Open-Source Implementation of a Large-Scale Mechanistic Model for Single Cell Proliferation and Death Signaling

ABSTRACTMechanistic models of how single cells respond to different perturbagens can help integrate disparate big data sets or predict response to varied drug combinations. However, the construction and simulation of such models have proved challenging. Our lab previously constructed one of the largest mechanistic models for single mammalian cell regulation of proliferation and death (774 species, 141 genes, 8 ligands, 2400 reactions). However, this, as many other large-scale models, was written using licensed software (MATLAB) with intricate programming structure, impeding alteration, expansion, and sharing. Here, we generated a new foundation for this model, which includes a python-based creation and simulation pipeline converting a few structured text files into an SBML-compatible format. This new open-source model (named SPARCED) is high-performance- and cloud-computing compatible and enables the study of virtual cell population responses at the single-cell level. We applied this new model to a subset of the LINCS MCF10A Data Cube, which observed that IFNγ acts as an anti-proliferative factor, but the reasons why were unknown. After expanding the SPARCED model with an IFNγ signaling module (to 950 species, 150 genes, 9 ligands, 2500 reactions), we ran stochastic single-cell simulations for two different putative crosstalk mechanisms and looked at the number of cycling cells in each case. Our model-based analysis suggested, and experiments support that these observations are better explained by IFNγ-induced SOCS1 expression sequestering activated EGF receptors, thereby downregulating AKT activity, as opposed to direct IFNγ-induced upregulation of p21 expression. This work forms a foundation for increased mechanistic model-based data integration on a single-cell level, an important building block for clinically predictive mechanistic models.</jats:p