Periodic Anderson model with correlated conduction electrons

We investigate a periodic Anderson model with interacting conduction electrons which are described by a Hubbard-type interaction of strength U_c. Within dynamical mean-field theory the total Hamiltonian is mapped onto an impurity model, which is solved by an extended non-crossing approximation. We consider the particle-hole symmetric case at half-filling. Similar to the case U_c=0, the low-energy behavior of the conduction electrons at high temperatures is essentially unaffected by the f-electrons and for small U_c a quasiparticle peak corresponding to the Hubbard model evolves first. These quasiparticles screen the f-moments when the temperature is reduced further, and the system turns into an insulator with a tiny gap and flat bands. The formation of the quasiparticle peak is impeded by increasing either U_c or the c-f hybridization. Nevertheless almost dispersionless bands emerge at low temperature with an increased gap, even in the case of initially insulating host electrons. The size of the gap in the one-particle spectral density at low temperatures provides an estimate for the low-energy scale and increases as U_c increases.Comment: 11 pages RevTeX with 13 ps figures, accepted by PR

Dynamic Susceptibility and Phonon Anomalies in the Bilayer tt-JJ Model

We consider a bilayer version of the extended $t$-$J$ model, with a view to computing the form of certain experimentally observable properties. Using the slave-boson decomposition, we show at the mean-field level that in the bilayer system the existence of in-plane $d$-wave singlet pairing excludes any interplane singlet order for reasonable values of the interplane superexchange parameter. Restricting the analysis to the regime of no interplane singlet pairing, we deduce parameter sets reproducing the Fermi surfaces of YBCO- and BSCCO-like bilayer systems. From these we calculate the form of the dynamic susceptibility $\chi( {\bf q}, \omega )$ in both systems, and of the anomalies in frequency and linewidth of selected phonon modes in YBCO. We compare the results with experiment, and discuss the features which differ from the single-layer case.Comment: 24 pages. 12 figures on 6 pages, available only by fax or s-mail; send request by fax to -(81)-3-5800-6791 or by e-mail to normand%[email protected]

Biologically inspired simulation of livor mortis

We present a biologically motivated livor mortis simulation that is capable of modelling the colouration changes in skin caused by blood pooling after death. Our approach consists of a simulation of post mortem blood dynamics and a layered skin shader that is controlled by the haemoglobin and oxygen levels in blood. The object is represented by a layered data structure made of a triangle mesh for the skin and a tetrahedral mesh on which the blood dynamics are simulated. This allows us to simulate the skin discolouration caused by livor mortis, including early patchy appearance, fixation of hypostasis and pressure induced blanching. We demonstrate our approach on two different models and scenarios and compare the results to real world livor mortis photographic examples

A Kinematic Approach for Efficient and Robust Simulation of the Cardiac Beating Motion

Computer simulation techniques for cardiac beating motions potentially have many applications and a broad audience. However, most existing methods require enormous computational costs and often show unstable behavior for extreme parameter sets, which interrupts smooth simulation study and make it difficult to apply them to interactive applications. To address this issue, we present an efficient and robust framework for simulating the cardiac beating motion. The global cardiac motion is generated by the accumulation of local myocardial fiber contractions. We compute such local-to-global deformations using a kinematic approach; we divide a heart mesh model into overlapping local regions, contract them independently according to fiber orientation, and compute a global shape that satisfies contracted shapes of all local regions as much as possible. A comparison between our method and a physics-based method showed that our method can generate motion very close to that of a physics-based simulation. Our kinematic method has high controllability; the simulated ventricle-wall-contraction speed can be easily adjusted to that of a real heart by controlling local contraction timing. We demonstrate that our method achieves a highly realistic beating motion of a whole heart in real time on a consumer-level computer. Our method provides an important step to bridge a gap between cardiac simulations and interactive applications

How to detect fluctuating order in the high-temperature superconductors

We discuss fluctuating order in a quantum disordered phase proximate to a quantum critical point, with particular emphasis on fluctuating stripe order. Optimal strategies for extracting information concerning such local order from experiments are derived with emphasis on neutron scattering and scanning tunneling microscopy. These ideas are tested by application to two model systems - the exactly solvable one dimensional electron gas with an impurity, and a weakly-interacting 2D electron gas. We extensively review experiments on the cuprate high-temperature superconductors which can be analyzed using these strategies. We adduce evidence that stripe correlations are widespread in the cuprates. Finally, we compare and contrast the advantages of two limiting perspectives on the high-temperature superconductor: weak coupling, in which correlation effects are treated as a perturbation on an underlying metallic (although renormalized) Fermi liquid state, and strong coupling, in which the magnetism is associated with well defined localized spins, and stripes are viewed as a form of micro-phase separation. We present quantitative indicators that the latter view better accounts for the observed stripe phenomena in the cuprates.Comment: 43 pages, 11 figures, submitted to RMP; extensively revised and greatly improved text; one new figure, one new section, two new appendices and more reference

Mast cell lineage diversion of T lineage precursors by the essential T cell transcription factor GATA-3

GATA-3 is essential for T cell development from the earliest stages. However, abundant GATA-3 can drive T lineage precursors to a non–T cell fate, depending on Notch signaling and developmental stage. Here, overexpression of GATA-3 blocked the survival of pro–T cells when Notch-Delta signals were present but enhanced viability in their absence. In fetal thymocytes at the double-negative 1 (DN1) stage and DN2 stage but not those at the DN3 stage, overexpression of GATA-3 rapidly induced respecification to the mast cell lineage with high frequency by direct transcriptional 'reprogramming'. Normal DN2 thymocytes also showed mast cell potential when interleukin 3 and stem cell factor were added in the absence of Notch signaling. Our results suggest a close relationship between the pro–T cell and mast cell programs and a previously unknown function for Notch in T lineage fidelity

Applying unmixing to gene expression data for tumor phylogeny inference

<p>Abstract</p> <p>Background</p> <p>While in principle a seemingly infinite variety of combinations of mutations could result in tumor development, in practice it appears that most human cancers fall into a relatively small number of "sub-types," each characterized a roughly equivalent sequence of mutations by which it progresses in different patients. There is currently great interest in identifying the common sub-types and applying them to the development of diagnostics or therapeutics. Phylogenetic methods have shown great promise for inferring common patterns of tumor progression, but suffer from limits of the technologies available for assaying differences between and within tumors. One approach to tumor phylogenetics uses differences between single cells within tumors, gaining valuable information about intra-tumor heterogeneity but allowing only a few markers per cell. An alternative approach uses tissue-wide measures of whole tumors to provide a detailed picture of averaged tumor state but at the cost of losing information about intra-tumor heterogeneity.</p> <p>Results</p> <p>The present work applies "unmixing" methods, which separate complex data sets into combinations of simpler components, to attempt to gain advantages of both tissue-wide and single-cell approaches to cancer phylogenetics. We develop an unmixing method to infer recurring cell states from microarray measurements of tumor populations and use the inferred mixtures of states in individual tumors to identify possible evolutionary relationships among tumor cells. Validation on simulated data shows the method can accurately separate small numbers of cell states and infer phylogenetic relationships among them. Application to a lung cancer dataset shows that the method can identify cell states corresponding to common lung tumor types and suggest possible evolutionary relationships among them that show good correspondence with our current understanding of lung tumor development.</p> <p>Conclusions</p> <p>Unmixing methods provide a way to make use of both intra-tumor heterogeneity and large probe sets for tumor phylogeny inference, establishing a new avenue towards the construction of detailed, accurate portraits of common tumor sub-types and the mechanisms by which they develop. These reconstructions are likely to have future value in discovering and diagnosing novel cancer sub-types and in identifying targets for therapeutic development.</p

When Cytokinin, a Plant Hormone, Meets the Adenosine A2A Receptor: A Novel Neuroprotectant and Lead for Treating Neurodegenerative Disorders?

It is well known that cytokinins are a class of phytohormones that promote cell division in plant roots and shoots. However, their targets, biological functions, and implications in mammalian systems have rarely been examined. In this study, we show that one cytokinin, zeatin riboside, can prevent pheochromocytoma (PC12) cells from serum deprivation-induced apoptosis by acting on the adenosine A2A receptor (A2A-R), which was blocked by an A2A-R antagonist and a protein kinase A (PKA) inhibitor, demonstrating the functional ability of zeatin riboside by mediating through A2A-R signaling event. Since the A2A-R was implicated as a therapeutic target in treating Huntington’s disease (HD), a cellular model of HD was applied by transfecting mutant huntingtin in PC12 cells. By using filter retardation assay and confocal microscopy we found that zeatin riboside reversed mutant huntingtin (Htt)-induced protein aggregations and proteasome deactivation through A2A-R signaling. PKA inhibitor blocked zeatin riboside-induced suppression of mutant Htt aggregations. In addition, PKA activated proteasome activity and reduced mutant Htt protein aggregations. However, a proteasome inhibitor blocked both zeatin riboside-and PKA activator-mediated suppression of mutant Htt aggregations, confirming mediation of the A2A-R/PKA/proteasome pathway. Taken together, zeatin riboside might have therapeutic potential as a novel neuroprotectant and a lead for treating neurodegenerative disorders

Brain Arachidonic Acid Incorporation and Turnover are not Altered in the Flinders Sensitive Line Rat Model of Human Depression

Brain serotonergic signaling is coupled to arachidonic acid (AA)-releasing calcium-dependent phospholipase A2. Increased brain serotonin concentrations and disturbed serotonergic neurotransmission have been reported in the Flinders Sensitive Line (FSL) rat model of depression, suggesting that brain AA metabolism may be elevated. To test this hypothesis, (14)C-AA was intravenously infused to steady-state levels into control and FSL rats derived from the same Sprague-Dawley background strain, and labeled and unlabeled brain phospholipid and plasma fatty acid concentrations were measured to determine the rate of brain AA incorporation and turnover. Brain AA incorporation and turnover did not differ significantly between controls and FSL rats. Compared to controls, plasma unesterified docosahexaenoic acid was increased, and brain phosphatidylinositol AA and total lipid linoleic acid and n-3 and n-6 docosapentaenoic acid were significantly decreased in FSL rats. Several plasma esterified fatty acids differed significantly from controls. In summary, brain AA metabolism did not change in FSL rats despite reported increased levels of serotonin concentrations, suggesting possible post-synaptic dampening of serotonergic neurotransmission involving AA