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Temperature dependence of optical and transport properties in VO₂ with high temperature anomalies
Angus Gentle,Abbas Maaroof,Geoff Smith 한국물리학회 2008 Current Applied Physics Vol.8 No.3,4
Thermochromic VO₂ is of interest for energy ecient glazing, and for fast telecommunications because it optically switches in the nearIR. Despite extensive study several aspects of its apparently diverse behaviour have not been explained satisfactorily. The visibleNIRpermittivity and dc electrical conductivity of high quality thin lms of VO₂, across the metalinsulator phase transition and well into themetallic phase to temperatures up to 100℃ above Tc are studied as a function of temperature and grain size. Experimental behaviour ispartly explained with eective medium models, existing band structures and classical transport theory. Anomalies however include:unphysically fast relaxation rate, counter-intuitive and signicant dierences between optical and dc, and bulk and thin lm parameters;and residual ‘‘non-metallic’’ features above the transition in highly oriented lms. Residual, but transient high temperature d-electronsinglet pairing on V dimers, which is sensitive to nanostructure, is examined as a source of some anomalies.
Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation
Malta, Tathiane M.,Sokolov, Artem,Gentles, Andrew J.,Burzykowski, Tomasz,Poisson, Laila,Weinstein, John N.,Kamiń,ska, Boż,ena,Huelsken, Joerg,Omberg, Larsson,Gevaert, Olivier,Colaprico, Anto Elsevier 2018 Cell Vol.173 No.2
<P><B>Summary</B></P> <P>Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation.</P> <P><B>Video Abstract</B></P> <P>Display Omitted</P> <P><B>Highlights</B></P> <P> <UL> <LI> Epigenetic and expression-based stemness indices measure oncogenic dedifferentiation </LI> <LI> Immune microenvironment content and PD-L1 levels associate with stemness indices </LI> <LI> Stemness index is increased in metastatic tumors and reveals intratumor heterogeneity </LI> <LI> Applying stemness indices reveals potential drug targets for anti-cancer therapies </LI> </UL> </P> <P><B>Graphical Abstract</B></P> <P>[DISPLAY OMISSION]</P>