Thermodynamics of Strongly Correlated One-Dimensional Bose Gases

We investigate the thermodynamics of one-dimensional Bose gases in the strongly correlated regime. To this end, we prepare ensembles of independent 1D Bose gases in a two-dimensional optical lattice and perform high-resolution in situ imaging of the column-integrated density distribution. Using an inverse Abel transformation we derive effective one-dimensional line-density profiles and compare them to exact theoretical models. The high resolution allows for a direct thermometry of the trapped ensembles. The knowledge about the temperature enables us to extract thermodynamic equations of state such as the phase-space density, the entropy per particle and the local pair correlation function.Comment: 4 pages, 5 figure

Construction of a Pig Physical Interactome Using Sequence Homology and a Comprehensive Reference Human Interactome

The analysis of interaction networks is crucial for understanding molecular function and has an essential impact for genomewide studies. However, the interactomes of most species are largely incomplete and computational strategies that take into account sequence homology can help compensating for this lack of information using cross-species analysis. In this work we report the construction of a porcine interactome resource. We applied sequence homology matching and carried out bi-directional BLASTp searches for the currently available protein sequence collections of human and pig. Using this homology we were able to recover, on average, 71% of the proteins annotated for human pathways for the pig. Porcine protein-protein interactions were deduced from homologous proteins with known interactions in human. The result of this work is a resource comprising 204,699 predicted porcine interactions that can be used in genome analyses in order to enhance functional interpretation of data. The data can be visualized and downloaded from http://cpdb.molgen.mpg.de/pig

Erectile Dysfunction Caused by Cavernous Leakage

Erectile dysfunction (ED) is a big issue in various populations with up to 30% of young men suffering from this condition. Unfortunately, treatment schemes are currently mainly focused on elderly patients with chronic disorders. In younger patients, ED is more a vascular problem, which affects the storage capacity of the penis. The impact of penile blood supply on erectile function was recognized some 500 years ago. At the turn of the twentieth century, the first results of penile venous ligation were published. Simple isolated ligation of the deep dorsal vein in humans for ED due to venous leak is currently not recommended, due to some reported low long-term success rates. This was, as shown in several literature reports, obviously due to insufficient technical possibilities. Technical development in imaging and vascular and endovascular treatment have dramatically evolved our understanding of this underlying condition in the past 20 years and turned this disease into a long-term treatable condition. The current state-of-the-art work-up of the underlying condition, using the newest imaging technologies with color Doppler ultrasound and CT scan with additional three-dimensional reconstruction, is to show the surgeon exactly the points to focus on. Additionally, a so-called corporo-venous insufficiency can be recognized as a mainly combined condition, affecting peripheral and more proximal drainage pathways at the same time

Meta-Analysis Approach identifies Candidate Genes and associated Molecular Networks for Type-2 Diabetes Mellitus

Background Multiple functional genomics data for complex human diseases have been published and made available by researchers worldwide. The main goal of these studies is the detailed analysis of a particular aspect of the disease. Complementary, meta-analysis approaches try to extract supersets of disease genes and interaction networks by integrating and combining these individual studies using statistical approaches. Results Here we report on a meta-analysis approach that integrates data of heterogeneous origin in the domain of type-2 diabetes mellitus (T2DM). Different data sources such as DNA microarrays and, complementing, qualitative data covering several human and mouse tissues are integrated and analyzed with a Bootstrap scoring approach in order to extract disease relevance of the genes. The purpose of the meta-analysis is two-fold: on the one hand it identifies a group of genes with overall disease relevance indicating common, tissue-independent processes related to the disease; on the other hand it identifies genes showing specific alterations with respect to a single study. Using a random sampling approach we computed a core set of 213 T2DM genes across multiple tissues in human and mouse, including well-known genes such as Pdk4, Adipoq, Scd, Pik3r1, Socs2 that monitor important hallmarks of T2DM, for example the strong relationship between obesity and insulin resistance, as well as a large fraction (128) of yet barely characterized novel candidate genes. Furthermore, we explored functional information and identified cellular networks associated with this core set of genes such as pathway information, protein-protein interactions and gene regulatory networks. Additionally, we set up a web interface in order to allow users to screen T2DM relevance for any – yet non-associated – gene. Conclusion In our paper we have identified a core set of 213 T2DM candidate genes by a meta-analysis of existing data sources. We have explored the relation of these genes to disease relevant information and – using enrichment analysis – we have identified biological networks on different layers of cellular information such as signaling and metabolic pathways, gene regulatory networks and protein-protein interactions. The web interface is accessible via http://t2dm-geneminer.molgen.mpg.de webcite

Network and Pathway Analysis of Toxicogenomics Data

Toxicogenomics is the study of the molecular effects of chemical, biological and physical agents in biological systems, with the aim of elucidating toxicological mechanisms, building predictive models and improving diagnostics. The vast majority of toxicogenomics data has been generated at the transcriptome level, including RNA-seq and microarrays, and large quantities of drug-treatment data have been made publicly available through databases and repositories. Besides the identification of differentially expressed genes (DEGs) from case-control studies or drug treatment time series studies, bioinformatics methods have emerged that infer gene expression data at the molecular network and pathway level in order to reveal mechanistic information. In this work we describe different resources and tools that have been developed by us and others that relate gene expression measurements with known pathway information such as over-representation and gene set enrichment analyses. Furthermore, we highlight approaches that integrate gene expression data with molecular interaction networks in order to derive network modules related to drug toxicity. We describe the two main parts of the approach, i.e., the construction of a suitable molecular interaction network as well as the conduction of network propagation of the experimental data through the interaction network. In all cases we apply methods and tools to publicly available rat in vivo data on anthracyclines, an important class of anti-cancer drugs that are known to induce severe cardiotoxicity in patients. We report the results and functional implications achieved for four anthracyclines (doxorubicin, epirubicin, idarubicin, and daunorubicin) and compare the information content inherent in the different computational approaches

Negative differential conductivity in an interacting quantum gas

Negative differential conductivity (NDC) is a widely exploited effect in modern electronic components. Here, a proof-of-principle is given for the observation of NDC in a quantum transport device for neutral atoms employing a multi-mode tunneling junction. The transport of the many-body quantum system is governed by the interplay between the tunnel coupling, the interaction energy and the thermodynamics of intrinsic collisions, which turn the coherent coupling into a hopping process. The resulting current voltage characteristics exhibit NDC, for which we identify a new microscopic physical mechanism. Our study opens new ways for the future implementation and control of complex neutral atom quantum circuits

Cross-dimensional phase transition from an array of 1D Luttinger liquids to a 3D Bose-Einstein condensate

We study the thermodynamic properties of a 2D array of coupled one-dimensional Bose gases. The system is realized with ultracold bosonic atoms loaded in the potential tubes of a two-dimensional optical lattice. For negligible coupling strength, each tube is an independent weakly interacting 1D Bose gas featuring Tomonaga Luttinger liquid behavior. By decreasing the lattice depth, we increase the coupling strength between the 1D gases and allow for the phase transition into a 3D condensate. We extract the phase diagram for such a system and compare our results with theoretical predictions. Due to the high effective mass across the periodic potential and the increased 1D interaction strength, the phase transition is shifted to large positive values of the chemical potential. Our results are prototypical to a variety of low-dimensional systems, where the coupling between the subsystems is realized in a higher spatial dimension such as coupled spin chains in magnetic insulators.Comment: 5 pages, 5 pictures, final version, Phys. Rev. Lett. in print (2014