Dynamical Mean-Field Theory

The dynamical mean-field theory (DMFT) is a widely applicable approximation scheme for the investigation of correlated quantum many-particle systems on a lattice, e.g., electrons in solids and cold atoms in optical lattices. In particular, the combination of the DMFT with conventional methods for the calculation of electronic band structures has led to a powerful numerical approach which allows one to explore the properties of correlated materials. In this introductory article we discuss the foundations of the DMFT, derive the underlying self-consistency equations, and present several applications which have provided important insights into the properties of correlated matter.Comment: Chapter in "Theoretical Methods for Strongly Correlated Systems", edited by A. Avella and F. Mancini, Springer (2011), 31 pages, 5 figure

Delayed Rectifier and A-Type Potassium Channels Associated with Kv 2.1 and Kv 4.3 Expression in Embryonic Rat Neural Progenitor Cells

BACKGROUND: Because of the importance of voltage-activated K(+) channels during embryonic development and in cell proliferation, we present here the first description of these channels in E15 rat embryonic neural progenitor cells derived from the subventricular zone (SVZ). Activation, inactivation, and single-channel conductance properties of recorded progenitor cells were compared with those obtained by others when these Kv gene products were expressed in oocytes. METHODOLOGY/PRINCIPAL FINDINGS: Neural progenitor cells derived from the subventricular zone of E15 embryonic rats were cultured under conditions that did not promote differentiation. Immunocytochemical and Western blot assays for nestin expression indicated that almost all of the cells available for recording expressed this intermediate filament protein, which is generally accepted as a marker for uncommitted embryonic neural progenitor cells. However, a very small numbers of the cells expressed GFAP, a marker for astrocytes, O4, a marker for immature oligodendrocytes, and betaIII-tubulin, a marker for neurons. Using immunocytochemistry and Western blots, we detected consistently the expression of Kv2.1, and 4.3. In whole-cell mode, we recorded two outward currents, a delayed rectifier and an A-type current. CONCLUSIONS/SIGNIFICANCE: We conclude that Kv2.1, and 4.3 are expressed in E15 SVZ neural progenitor cells, and we propose that they may be associated with the delayed-rectifier and the A-type currents, respectively, that we recorded. These results demonstrate the early expression of delayed rectifier and A-type K(+) currents and channels in embryonic neural progenitor cells prior to the differentiation of these cells

Why do physicians prescribe dialysis? A prospective questionnaire study

Funding Information: This study was supported by an unrestricted grant 14CECPDEU1001 from Baxter Healthcare International. Baxter Novum is the result of a grant from Baxter Healthcare Corporation to Division of Renal Medicine and Baxter Novum, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, to support research activities at Karolinska Institutet to promote the understanding and treatment of renal disease. Bengt Lindholm is employed by Baxter Healthcare Corporation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. This does not alter our adherence to PLOS ONE policies on sharing data and materials. Publisher Copyright: © 2017 Heaf et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Copyright: Copyright 2018 Elsevier B.V., All rights reserved.Introduction.The incidence of unplanned dialysis initiation (DI) with consequent increased comorbidity, mortality and reduced modality choice remains high, but the optimal timing of dialysis initiation (DI) remains controversial, and there is a lack of studies of specific reasons for DI. We investigated why and when physicians prescribe dialysis and hypothesized that physician motivation for DI is an independent factor which may have clinical consequences. Methods In the Peridialysis study, an ongoing multicenter prospective study assessing the causes and timing of DI and consequences of unplanned dialysis, physicians in 11 hospitals were asked to describe their primary, secondary and further reasons for prescribing DI. The stated reasons for DI were analyzed in relation to clinical and biochemical data at DI, and characteristics of physicians. Results In 446 patients (median age 67 years; 38% females; diabetes 25.6%), DI was prescribed by 84 doctors who stated 23 different primary reasons for DI. The primary indication was clinical in 63% and biochemical in 37%; 23% started for life-threatening conditions. Reduced renal function accounted for only 19% of primary reasons for DI but was a primary or contributing reason in 69%. The eGFR at DI was 7.2 ±3.4 ml/min/1.73 m2, but varied according to comorbidity and cause of DI. Patients with cachexia, anorexia and pulmonary stasis (34% with heart failure) had the highest eGFR (8.2–9.8 ml/min/1.73 m2), and those with edema, “low GFR”, and acidosis, the lowest (4.6–6.1 ml/min/1.73 m2). Patients with multiple comorbidity including diabetes started at a high eGFR (8.7 ml/min/1.73 m2). Physician experience played a role in dialysis prescription. Non-specialists were more likely to prescribe dialysis for life-threatening conditions, while older and more experienced physicians were more likely to start dialysis for clinical reasons, and at a lower eGFR. Female doctors started dialysis at a higher eGFR than males (8.0 vs. 7.1 ml/min/1.73 m2). Conclusions DI was prescribed mainly based on clinical reasons in accordance with current recommendations while low renal function accounted for only 19% of primary reasons for DI. There are considerable differences in physicians´ stated motivations for DI, related to their age, clinical experience and interpretation of biochemical variables. These differences may be an independent factor in the clinical treatment of patients, with consequences for the risk of unplanned DI.publishersversionPeer reviewe

An empirical examination of the factor structure of compassion

Compassion has long been regarded as a core part of our humanity by contemplative traditions, and in recent years, it has received growing research interest. Following a recent review of existing conceptualisations, compassion has been defined as consisting of the following five elements: 1) recognising suffering, 2) understanding the universality of suffering in human experience, 3) feeling moved by the person suffering and emotionally connecting with their distress, 4) tolerating uncomfortable feelings aroused (e.g., fear, distress) so that we remain open to and accepting of the person suffering, and 5) acting or being motivated to act to alleviate suffering. As a prerequisite to developing a high quality compassion measure and furthering research in this field, the current study empirically investigated the factor structure of the five-element definition using a combination of existing and newly generated self-report items. This study consisted of three stages: a systematic consultation with experts to review items from existing self-report measures of compassion and generate additional items (Stage 1), exploratory factor analysis of items gathered from Stage 1 to identify the underlying structure of compassion (Stage 2), and confirmatory factor analysis to validate the identified factor structure (Stage 3). Findings showed preliminary empirical support for a five-factor structure of compassion consistent with the five-element definition. However, findings indicated that the ‘tolerating’ factor may be problematic and not a core aspect of compassion. This possibility requires further empirical testing. Limitations with items from included measures lead us to recommend against using these items collectively to assess compassion. Instead, we call for the development of a new self-report measure of compassion, using the five-element definition to guide item generation. We recommend including newly generated ‘tolerating’ items in the initial item pool, to determine whether or not factor-level issues are resolved once item-level issues are addressed

A Cross-Study Transcriptional Analysis of Parkinson's Disease

The study of Parkinson's disease (PD), like other complex neurodegenerative disorders, is limited by access to brain tissue from patients with a confirmed diagnosis. Alternatively the study of peripheral tissues may offer some insight into the molecular basis of disease susceptibility and progression, but this approach still relies on brain tissue to benchmark relevant molecular changes against. Several studies have reported whole-genome expression profiling in post-mortem brain but reported concordance between these analyses is lacking. Here we apply a standardised pathway analysis to seven independent case-control studies, and demonstrate increased concordance between data sets. Moreover data convergence increased when the analysis was limited to the five substantia nigra (SN) data sets; this highlighted the down regulation of dopamine receptor signaling and insulin-like growth factor 1 (IGF1) signaling pathways. We also show that case-control comparisons of affected post mortem brain tissue are more likely to reflect terminal cytoarchitectural differences rather than primary pathogenic mechanisms. The implementation of a correction factor for dopaminergic neuronal loss predictably resulted in the loss of significance of the dopamine signaling pathway while axon guidance pathways increased in significance. Interestingly the IGF1 signaling pathway was also over-represented when data from non-SN areas, unaffected or only terminally affected in PD, were considered. Our findings suggest that there is greater concordance in PD whole-genome expression profiling when standardised pathway membership rather than ranked gene list is used for comparison

Finding the “Dark Matter” in Human and Yeast Protein Network Prediction and Modelling

Accurate modelling of biological systems requires a deeper and more complete knowledge about the molecular components and their functional associations than we currently have. Traditionally, new knowledge on protein associations generated by experiments has played a central role in systems modelling, in contrast to generally less trusted bio-computational predictions. However, we will not achieve realistic modelling of complex molecular systems if the current experimental designs lead to biased screenings of real protein networks and leave large, functionally important areas poorly characterised. To assess the likelihood of this, we have built comprehensive network models of the yeast and human proteomes by using a meta-statistical integration of diverse computationally predicted protein association datasets. We have compared these predicted networks against combined experimental datasets from seven biological resources at different level of statistical significance. These eukaryotic predicted networks resemble all the topological and noise features of the experimentally inferred networks in both species, and we also show that this observation is not due to random behaviour. In addition, the topology of the predicted networks contains information on true protein associations, beyond the constitutive first order binary predictions. We also observe that most of the reliable predicted protein associations are experimentally uncharacterised in our models, constituting the hidden or “dark matter” of networks by analogy to astronomical systems. Some of this dark matter shows enrichment of particular functions and contains key functional elements of protein networks, such as hubs associated with important functional areas like the regulation of Ras protein signal transduction in human cells. Thus, characterising this large and functionally important dark matter, elusive to established experimental designs, may be crucial for modelling biological systems. In any case, these predictions provide a valuable guide to these experimentally elusive regions

The NRF2-mediated oxidative stress response pathway is associated with tumor cell resistance to arsenic trioxide across the NCI-60 panel

<p>Abstract</p> <p>Background</p> <p>Drinking water contaminated with inorganic arsenic is associated with increased risk for different types of cancer. Paradoxically, arsenic trioxide can also be used to induce remission in patients with acute promyelocytic leukemia (APL) with a success rate of approximately 80%. A comprehensive study examining the mechanisms and potential signaling pathways contributing to the anti-tumor properties of arsenic trioxide has not been carried out.</p> <p>Methods</p> <p>Here we applied a systems biology approach to identify gene biomarkers that underlie tumor cell responses to arsenic-induced cytotoxicity. The baseline gene expression levels of 14,500 well characterized human genes were associated with the GI₅₀ data of the NCI-60 tumor cell line panel from the developmental therapeutics program (DTP) database. Selected biomarkers were tested <it>in vitro</it> for the ability to influence tumor susceptibility to arsenic trioxide.</p> <p>Results</p> <p>A significant association was found between the baseline expression levels of 209 human genes and the sensitivity of the tumor cell line panel upon exposure to arsenic trioxide. These genes were overlayed onto protein-protein network maps to identify transcriptional networks that modulate tumor cell responses to arsenic trioxide. The analysis revealed a significant enrichment for the oxidative stress response pathway mediated by nuclear factor erythroid 2-related factor 2 (NRF2) with high expression in arsenic resistant tumor cell lines. The role of the NRF2 pathway in protecting cells against arsenic-induced cell killing was validated in tumor cells using shRNA-mediated knock-down.</p> <p>Conclusions</p> <p>In this study, we show that the expression level of genes in the NRF2 pathway serve as potential gene biomarkers of tumor cell responses to arsenic trioxide. Importantly, we demonstrate that tumor cells that are deficient for NRF2 display increased sensitivity to arsenic trioxide. The results of our study will be useful in understanding the mechanism of arsenic-induced cytotoxicity in cells, as well as the increased applicability of arsenic trioxide as a chemotherapeutic agent in cancer treatment.</p

Palmitoylation Regulates Epidermal Homeostasis and Hair Follicle Differentiation

Palmitoylation is a key post-translational modification mediated by a family of DHHC-containing palmitoyl acyl-transferases (PATs). Unlike other lipid modifications, palmitoylation is reversible and thus often regulates dynamic protein interactions. We find that the mouse hair loss mutant, depilated, (dep) is due to a single amino acid deletion in the PAT, Zdhhc21, resulting in protein mislocalization and loss of palmitoylation activity. We examined expression of Zdhhc21 protein in skin and find it restricted to specific hair lineages. Loss of Zdhhc21 function results in delayed hair shaft differentiation, at the site of expression of the gene, but also leads to hyperplasia of the interfollicular epidermis (IFE) and sebaceous glands, distant from the expression site. The specific delay in follicle differentiation is associated with attenuated anagen propagation and is reflected by decreased levels of Lef1, nuclear β-catenin, and Foxn1 in hair shaft progenitors. In the thickened basal compartment of mutant IFE, phospho-ERK and cell proliferation are increased, suggesting increased signaling through EGFR or integrin-related receptors, with a parallel reduction in expression of the key differentiation factor Gata3. We show that the Src-family kinase, Fyn, involved in keratinocyte differentiation, is a direct palmitoylation target of Zdhhc21 and is mislocalized in mutant follicles. This study is the first to demonstrate a key role for palmitoylation in regulating developmental signals in mammalian tissue homeostasis