Regression of murine lung tumors by the let-7 microRNA.

MicroRNAs (miRNAs) have recently emerged as an important new class of cellular regulators that control various cellular processes and are implicated in human diseases, including cancer. Here, we show that loss of let-7 function enhances lung tumor formation in vivo, strongly supporting the hypothesis that let-7 is a tumor suppressor. Moreover, we report that exogenous delivery of let-7 to established tumors in mouse models of non-small-cell lung cancer (NSCLC) significantly reduces the tumor burden. These results demonstrate the therapeutic potential of let-7 in NSCLC and point to miRNA replacement therapy as a promising approach in cancer treatment

Yap and Taz regulate retinal pigment epithelial cell fate

The optic vesicle comprises a pool of bi-potential progenitor cells from which the retinal pigment epithelium (RPE) and neural retina fates segregate during ocular morphogenesis. Several transcription factors and signaling pathways have been shown to be important for RPE maintenance and differentiation, but an understanding of the initial fate specification and determination of this ocular cell type is lacking. We show that Yap/Taz-Tead activity is necessary and sufficient for optic vesicle progenitors to adopt RPE identity in zebrafish. A Tead-responsive transgene is expressed within the domain of the optic cup from which RPE arises, and Yap immunoreactivity localizes to the nuclei of prospective RPE cells. yap (yap1) mutants lack a subset of RPE cells and/or exhibit coloboma. Loss of RPE in yap mutants is exacerbated in combination with taz (wwtr1) mutant alleles such that, when Yap and Taz are both absent, optic vesicle progenitor cells completely lose their ability to form RPE. The mechanism of Yap-dependent RPE cell type determination is reliant on both nuclear localization of Yap and interaction with a Tead co-factor. In contrast to loss of Yap and Taz, overexpression of either protein within optic vesicle progenitors leads to ectopic pigmentation in a dosage-dependent manner. Overall, this study identifies Yap and Taz as key early regulators of RPE genesis and provides a mechanistic framework for understanding the congenital ocular defects of Sveinsson's chorioretinal atrophy and congenital retinal coloboma

Network Archaeology: Uncovering Ancient Networks from Present-day Interactions

Often questions arise about old or extinct networks. What proteins interacted in a long-extinct ancestor species of yeast? Who were the central players in the Last.fm social network 3 years ago? Our ability to answer such questions has been limited by the unavailability of past versions of networks. To overcome these limitations, we propose several algorithms for reconstructing a network's history of growth given only the network as it exists today and a generative model by which the network is believed to have evolved. Our likelihood-based method finds a probable previous state of the network by reversing the forward growth model. This approach retains node identities so that the history of individual nodes can be tracked. We apply these algorithms to uncover older, non-extant biological and social networks believed to have grown via several models, including duplication-mutation with complementarity, forest fire, and preferential attachment. Through experiments on both synthetic and real-world data, we find that our algorithms can estimate node arrival times, identify anchor nodes from which new nodes copy links, and can reveal significant features of networks that have long since disappeared.Comment: 16 pages, 10 figure

Bilayer manganites: polarons in the midst of a metallic breakdown

The exact nature of the low temperature electronic phase of the manganite materials family, and hence the origin of their colossal magnetoresistant (CMR) effect, is still under heavy debate. By combining new photoemission and tunneling data, we show that in La{2-2x}Sr{1+2x}Mn2O7 the polaronic degrees of freedom win out across the CMR region of the phase diagram. This means that the generic ground state is that of a system in which strong electron-lattice interactions result in vanishing coherent quasi-particle spectral weight at the Fermi level for all locations in k-space. The incoherence of the charge carriers offers a unifying explanation for the anomalous charge-carrier dynamics seen in transport, optics and electron spectroscopic data. The stacking number N is the key factor for true metallic behavior, as an intergrowth-driven breakdown of the polaronic domination to give a metal possessing a traditional Fermi surface is seen in the bilayer system.Comment: 7 pages, 2 figures, includes supplementary informatio

Calculation of molecular thermochemical data and their availability in databases

Thermodynamic properties of molecules can be obtained by experiment, by statistical mechanics in conjunction with electronic structure theory and by empirical rules like group additivity. The latter two methods are briefly re-viewed in this chapter. The overview of electronic structure methods is intended for readers less experienced in electronic structure theory and focuses on concepts without going into mathematical details. This is followed by a brief description of group additivity schemes; finally, an overview of databases listing reliable thermochemical data is given

Building cooperation through health initiatives: an Arab and Israeli case study

<p>Abstract</p> <p>Background</p> <p>Ongoing conflict in the Middle East poses a major threat to health and security. A project screening Arab and Israeli newborns for hearing loss provided an opportunity to evaluate ways for building cooperation. The aims of this study were to: a) examine what attracted Israeli, Jordanian and Palestinian participants to the project, b) describe challenges they faced, and c) draw lessons learned for guiding cross-border health initiatives.</p> <p>Methods</p> <p>A case study method was used involving 12 key informants stratified by country (3 Israeli, 3 Jordanian, 3 Palestinian, 3 Canadian). In-depth interviews were tape-recorded, transcribed and analyzed using an inductive qualitative approach to derive key themes.</p> <p>Results</p> <p>Major reasons for getting involved included: concern over an important health problem, curiosity about neighbors and opportunities for professional advancement. Participants were attracted to prospects for opening the dialogue, building relationships and facilitating cooperation in the region. The political situation was a major challenge that delayed implementation of the project and placed participants under social pressure. Among lessons learned, fostering personal relationships was viewed as critical for success of this initiative.</p> <p>Conclusion</p> <p>Arab and Israeli health professionals were prepared to get involved for two types of reasons: a) Project Level: opportunity to address a significant health issue (e.g. congenital hearing loss) while enhancing their professional careers, and b) Meta Level: concern about taking positive steps for building cooperation in the region. We invite discussion about roles that health professionals can play in building "cooperation networks" for underpinning health security, conflict resolution and global health promotion.</p

Jerarca: Efficient Analysis of Complex Networks Using Hierarchical Clustering

Background: How to extract useful information from complex biological networks is a major goal in many fields, especially in genomics and proteomics. We have shown in several works that iterative hierarchical clustering, as implemented in the UVCluster program, is a powerful tool to analyze many of those networks. However, the amount of computation time required to perform UVCluster analyses imposed significant limitations to its use. Methodology/Principal Findings: We describe the suite Jerarca, designed to efficiently convert networks of interacting units into dendrograms by means of iterative hierarchical clustering. Jerarca is divided into three main sections. First, weighted distances among units are computed using up to three different approaches: a more efficient version of UVCluster and two new, related algorithms called RCluster and SCluster. Second, Jerarca builds dendrograms based on those distances, using well-known phylogenetic algorithms, such as UPGMA or Neighbor-Joining. Finally, Jerarca provides optimal partitions of the trees using statistical criteria based on the distribution of intra- and intercluster connections. Outputs compatible with the phylogenetic software MEGA and the Cytoscape package are generated, allowing the results to be easily visualized. Conclusions/Significance: The four main advantages of Jerarca in respect to UVCluster are: 1) Improved speed of a novel UVCluster algorithm; 2) Additional, alternative strategies to perform iterative hierarchical clustering; 3) Automatic evaluatio

High order structure preserving explicit methods for solving linear-quadratic optimal control problems

[EN] We consider the numerical integration of linear-quadratic optimal control problems. This problem requires the solution of a boundary value problem: a non-autonomous matrix Riccati differential equation (RDE) with final conditions coupled with the state vector equation with initial conditions. The RDE has positive definite matrix solution and to numerically preserve this qualitative property we propose first to integrate this equation backward in time with a sufficiently accurate scheme. Then, this problem turns into an initial value problem, and we analyse splitting and Magnus integrators for the forward time integration which preserve the positive definite matrix solutions for the RDE. Duplicating the time as two new coordinates and using appropriate splitting methods, high order methods preserving the desired property can be obtained. The schemes make sequential computations and do not require the storrage of intermediate results, so the storage requirements are minimal. The proposed methods are also adapted for solving linear-quadratic N-player differential games. The performance of the splitting methods can be considerably improved if the system is a perturbation of an exactly solvable problem and the system is properly split. Some numerical examples illustrate the performance of the proposed methods.The author wishes to thank the University of California San Diego for its hospitality where part of this work was done. He also acknowledges the support of the Ministerio de Ciencia e Innovacion (Spain) under the coordinated project MTM2010-18246-C03. The author also acknowledges the suggestions by the referees to improve the presentation of this work.Blanes Zamora, S. (2015). High order structure preserving explicit methods for solving linear-quadratic optimal control problems. 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Improving Cancer Classification Accuracy Using Gene Pairs

Recent studies suggest that the deregulation of pathways, rather than individual genes, may be critical in triggering carcinogenesis. The pathway deregulation is often caused by the simultaneous deregulation of more than one gene in the pathway. This suggests that robust gene pair combinations may exploit the underlying bio-molecular reactions that are relevant to the pathway deregulation and thus they could provide better biomarkers for cancer, as compared to individual genes. In order to validate this hypothesis, in this paper, we used gene pair combinations, called doublets, as input to the cancer classification algorithms, instead of the original expression values, and we showed that the classification accuracy was consistently improved across different datasets and classification algorithms. We validated the proposed approach using nine cancer datasets and five classification algorithms including Prediction Analysis for Microarrays (PAM), C4.5 Decision Trees (DT), Naive Bayesian (NB), Support Vector Machine (SVM), and k-Nearest Neighbor (k-NN)

Protein Function Assignment through Mining Cross-Species Protein-Protein Interactions

Background: As we move into the post genome-sequencing era, an immediate challenge is how to make best use of the large amount of high-throughput experimental data to assign functions to currently uncharacterized proteins. We here describe CSIDOP, a new method for protein function assignment based on shared interacting domain patterns extracted from cross-species protein-protein interaction data. Methodology/Principal Findings: The proposed method is assessed both biologically and statistically over the genome of H. sapiens. The CSIDOP method is capable of making protein function prediction with accuracy of 95.42 % using 2,972 gene ontology (GO) functional categories. In addition, we are able to assign novel functional annotations for 181 previously uncharacterized proteins in H. sapiens. Furthermore, we demonstrate that for proteins that are characterized by GO, the CSIDOP may predict extra functions. This is attractive as a protein normally executes a variety of functions in different processes and its current GO annotation may be incomplete. Conclusions/Significance: It can be shown through experimental results that the CSIDOP method is reliable and practical in use. The method will continue to improve as more high quality interaction data becomes available and is readily scalable t