Structure factor and dynamics of the helix-coil transition

Thermodynamical properties of the helix-coil transition were successfully described in the past by the model of Lifson, Poland and Sheraga. Here we compute the corresponding structure factor and show that it possesses a universal scaling behavior near the transition point, even when the transition is of first order. Moreover, we introduce a dynamical version of this model, that we solve numerically. A Langevin equation is also proposed to describe the dynamics of the density of hydrogen bonds. Analytical solution of this equation shows dynamical scaling near the critical temperature and predicts a gelation phenomenon above the critical temperature. In the case when comparison of the two dynamical approaches is possible, the predictions of our phenomenological theory agree with the results of the Monte Carlo simulations.Comment: 11 pages, 7 figure

Single Top Production as a Window to Physics Beyond the Standard Model

Production of single top quarks at a high energy hadron collider is studied as a means to identify physics beyond the standard model related to the electroweak symmetry breaking. The sensitivity of the $s$-channel $W^*$ mode, the $t$-channel $W$-gluon fusion mode, and the \tw mode to various possible forms of new physics is assessed, and it is found that the three modes are sensitive to different forms of new physics, indicating that they provide complimentary information about the properties of the top quark. Polarization observables are also considered, and found to provide potentially useful information about the structure of the interactions of top.Comment: References added and minor discussion improvements; results unchanged; Version to be published in PR

Behavioral Modernity and the Cultural Transmission of Structured Information: The Semantic Axelrod Model

Cultural transmission models are coming to the fore in explaining increases in the Paleolithic toolkit richness and diversity. During the later Paleolithic, technologies increase not only in terms of diversity but also in their complexity and interdependence. As Mesoudi and O'Brien (2008) have shown, selection broadly favors social learning of information that is hierarchical and structured, and multiple studies have demonstrated that teaching within a social learning environment can increase fitness. We believe that teaching also provides the scaffolding for transmission of more complex cultural traits. Here, we introduce an extension of the Axelrod (1997} model of cultural differentiation in which traits have prerequisite relationships, and where social learning is dependent upon the ordering of those prerequisites. We examine the resulting structure of cultural repertoires as learning environments range from largely unstructured imitation, to structured teaching of necessary prerequisites, and we find that in combination with individual learning and innovation, high probabilities of teaching prerequisites leads to richer cultural repertoires. Our results point to ways in which we can build more comprehensive explanations of the archaeological record of the Paleolithic as well as other cases of technological change.Comment: 24 pages, 7 figures. Submitted to "Learning Strategies and Cultural Evolution during the Paleolithic", edited by Kenichi Aoki and Alex Mesoudi, and presented at the 79th Annual Meeting of the Society for American Archaeology, Austin TX. Revised 5/14/1

Your space or mine? : Mapping self in time

Peer reviewedPublisher PD

Conflict transformation and history teaching: social psychological theory and its contributions

The aim of this introductory chapter is to render intelligible how history teaching can be enriched with knowledge of social psychological theories that deal with the issue of conflict transformation and partcularly the notions of prejudice reduction and reconciliation. A major aim of history teaching is to engage students with historical texts, establish historical significance, identify continuity and change, analyse cause and consequence, take historical perspectives and understand the ethical dimensions of historical interpretations. Such teaching, enriched with social psychological theory, will enlarge the notion of historical literacy into a study of historical culture and historical consciousness in the classroom so that students become reflective of the role of collective memory and history teaching in processes of conflict transformation and understand the ways in which various forms of historical consciousness relate the past, present and future. This is what the editors of this volume call an interdisciplinary paradigm of transformative history teachin

Biclustering via optimal re-ordering of data matrices in systems biology: rigorous methods and comparative studies

<p>Abstract</p> <p>Background</p> <p>The analysis of large-scale data sets via clustering techniques is utilized in a number of applications. Biclustering in particular has emerged as an important problem in the analysis of gene expression data since genes may only jointly respond over a subset of conditions. Biclustering algorithms also have important applications in sample classification where, for instance, tissue samples can be classified as cancerous or normal. Many of the methods for biclustering, and clustering algorithms in general, utilize simplified models or heuristic strategies for identifying the "best" grouping of elements according to some metric and cluster definition and thus result in suboptimal clusters.</p> <p>Results</p> <p>In this article, we present a rigorous approach to biclustering, OREO, which is based on the Optimal RE-Ordering of the rows and columns of a data matrix so as to globally minimize the dissimilarity metric. The physical permutations of the rows and columns of the data matrix can be modeled as either a network flow problem or a traveling salesman problem. Cluster boundaries in one dimension are used to partition and re-order the other dimensions of the corresponding submatrices to generate biclusters. The performance of OREO is tested on (a) metabolite concentration data, (b) an image reconstruction matrix, (c) synthetic data with implanted biclusters, and gene expression data for (d) colon cancer data, (e) breast cancer data, as well as (f) yeast segregant data to validate the ability of the proposed method and compare it to existing biclustering and clustering methods.</p> <p>Conclusion</p> <p>We demonstrate that this rigorous global optimization method for biclustering produces clusters with more insightful groupings of similar entities, such as genes or metabolites sharing common functions, than other clustering and biclustering algorithms and can reconstruct underlying fundamental patterns in the data for several distinct sets of data matrices arising in important biological applications.</p

A critical assessment of Mus musculus gene function prediction using integrated genomic evidence

Background: Several years after sequencing the human genome and the mouse genome, much remains to be discovered about the functions of most human and mouse genes. Computational prediction of gene function promises to help focus limited experimental resources on the most likely hypotheses. Several algorithms using diverse genomic data have been applied to this task in model organisms; however, the performance of such approaches in mammals has not yet been evaluated. Results: In this study, a standardized collection of mouse functional genomic data was assembled; nine bioinformatics teams used this data set to independently train classifiers and generate predictions of function, as defined by Gene Ontology (GO) terms, for 21,603 mouse genes; and the best performing submissions were combined in a single set of predictions. We identified strengths and weaknesses of current functional genomic data sets and compared the performance of function prediction algorithms. This analysis inferred functions for 76% of mouse genes, including 5,000 currently uncharacterized genes. At a recall rate of 20%, a unified set of predictions averaged 41% precision, with 26% of GO terms achieving a precision better than 90%. Conclusion: We performed a systematic evaluation of diverse, independently developed computational approaches for predicting gene function from heterogeneous data sources in mammals. The results show that currently available data for mammals allows predictions with both breadth and accuracy. Importantly, many highly novel predictions emerge for the 38% of mouse genes that remain uncharacterized

ENDOR Spectroscopy and DFT Calculations: Evidence for the Hydrogen-Bond Network Within α2 in the PCET of E. coli Ribonucleotide Reductase

Escherichia coli class I ribonucleotide reductase (RNR) catalyzes the conversion of nucleotides to deoxynucleotides and is composed of two subunits: α2 and β2. β2 contains a stable di-iron tyrosyl radical (Y[subscript 122]•) cofactor required to generate a thiyl radical (C[subscript 439]•) in α2 over a distance of 35 Å, which in turn initiates the chemistry of the reduction process. The radical transfer process is proposed to occur by proton-coupled electron transfer (PCET) via a specific pathway: Y[subscript 122] ⇆ W[subscript 48][?] ⇆ Y[subscript 356] in β2, across the subunit interface to Y[subscript 731] ⇆ Y[subscript 730] ⇆ C[subscript 439] in α2. Within α2 a colinear PCET model has been proposed. To obtain evidence for this model, 3-amino tyrosine (NH2Y) replaced Y[subscript 730] in α2, and this mutant was incubated with β2, cytidine 5′-diphosphate, and adenosine 5′-triphosphate to generate a NH2Y730• in D2O. [[superscript 2]H]-Electron–nuclear double resonance (ENDOR) spectra at 94 GHz of this intermediate were obtained, and together with DFT models of α2 and quantum chemical calculations allowed assignment of the prominent ENDOR features to two hydrogen bonds likely associated with C[subscript 439] and Y[subscript 731]. A third proton was assigned to a water molecule in close proximity (2.2 Å O–H···O distance) to residue 730. The calculations also suggest that the unusual g-values measured for NH[subscript 2]Y[subscript 730]• are consistent with the combined effect of the hydrogen bonds to Cys[subscript 439] and Tyr[subscript 731], both nearly perpendicular to the ring plane of NH[subscript 2]Y[subscript 730]. The results provide the first experimental evidence for the hydrogen-bond network between the pathway residues in α2 of the active RNR complex, for which no structural data are available.National Institutes of Health (U.S.) (NIH GM29595

Skeletal Muscle Phenotypically Converts and Selectively Inhibits Metastatic Cells in Mice

Skeletal muscle is rarely a site of malignant metastasis; the molecular and cellular basis for this rarity is not understood. We report that myogenic cells exert pronounced effects upon co-culture with metastatic melanoma (B16-F10) or carcinoma (LLC1) cells including conversion to the myogenic lineage in vitro and in vivo, as well as inhibition of melanin production in melanoma cells coupled with cytotoxic and cytostatic effects. No effect is seen with non-tumorigenic cells. Tumor suppression assays reveal that the muscle-mediated tumor suppressor effects do not generate resistant clones but function through the down-regulation of the transcription factor MiTF, a master regulator of melanocyte development and a melanoma oncogene. Our findings point to skeletal muscle as a source of therapeutic agents in the treatment of metastatic cancers

Comprehensive in vivo Mapping of the Human Basal Ganglia and Thalamic Connectome in Individuals Using 7T MRI

Basal ganglia circuits are affected in neurological disorders such as Parkinson's disease (PD), essential tremor, dystonia and Tourette syndrome. Understanding the structural and functional connectivity of these circuits is critical for elucidating the mechanisms of the movement and neuropsychiatric disorders, and is vital for developing new therapeutic strategies such as deep brain stimulation (DBS). Knowledge about the connectivity of the human basal ganglia and thalamus has rapidly evolved over recent years through non-invasive imaging techniques, but has remained incomplete because of insufficient resolution and sensitivity of these techniques. Here, we present an imaging and computational protocol designed to generate a comprehensive in vivo and subject-specific, three-dimensional model of the structure and connections of the human basal ganglia. High-resolution structural and functional magnetic resonance images were acquired with a 7-Tesla magnet. Capitalizing on the enhanced signal-to-noise ratio (SNR) and enriched contrast obtained at high-field MRI, detailed structural and connectivity representations of the human basal ganglia and thalamus were achieved. This unique combination of multiple imaging modalities enabled the in-vivo visualization of the individual human basal ganglia and thalamic nuclei, the reconstruction of seven white-matter pathways and their connectivity probability that, to date, have only been reported in animal studies, histologically, or group-averaged MRI population studies. Also described are subject-specific parcellations of the basal ganglia and thalamus into sub-territories based on their distinct connectivity patterns. These anatomical connectivity findings are supported by functional connectivity data derived from resting-state functional MRI (R-fMRI). This work demonstrates new capabilities for studying basal ganglia circuitry, and opens new avenues of investigation into the movement and neuropsychiatric disorders, in individual human subjects