Master equation approach to DNA-breathing in heteropolymer DNA

After crossing an initial barrier to break the first base-pair (bp) in double-stranded DNA, the disruption of further bps is characterized by free energies between less than one to a few kT. This causes the opening of intermittent single-stranded bubbles. Their unzipping and zipping dynamics can be monitored by single molecule fluorescence or NMR methods. We here establish a dynamic description of this DNA-breathing in a heteropolymer DNA in terms of a master equation that governs the time evolution of the joint probability distribution for the bubble size and position along the sequence. The transfer coefficients are based on the Poland-Scheraga free energy model. We derive the autocorrelation function for the bubble dynamics and the associated relaxation time spectrum. In particular, we show how one can obtain the probability densities of individual bubble lifetimes and of the waiting times between successive bubble events from the master equation. A comparison to results of a stochastic Gillespie simulation shows excellent agreement.Comment: 12 pages, 8 figure

Directed motion emerging from two coupled random processes: Translocation of a chain through a membrane nanopore driven by binding proteins

We investigate the translocation of a stiff polymer consisting of M monomers through a nanopore in a membrane, in the presence of binding particles (chaperones) that bind onto the polymer, and partially prevent backsliding of the polymer through the pore. The process is characterized by the rates: k for the polymer to make a diffusive jump through the pore, q for unbinding of a chaperone, and the rate q kappa for binding (with a binding strength kappa); except for the case of no binding kappa=0 the presence of the chaperones give rise to an effective force that drives the translocation process. Based on a (2+1) variate master equation, we study in detail the coupled dynamics of diffusive translocation and (partial) rectification by the binding proteins. In particular, we calculate the mean translocation time as a function of the various physical parameters.Comment: 22 pages, 5 figures, IOP styl

Perspective on Coarse-Graining, Cognitive Load, and Materials Simulation

The predictive capabilities of computational materials science today derive from overlapping advances in simulation tools, modeling techniques, and best practices. We outline this ecosystem of molecular simulations by explaining how important contributions in each of these areas have fed into each other. The combined output of these tools, techniques, and practices is the ability for researchers to advance understanding by efficiently combining simple models with powerful software. As specific examples, we show how the prediction of organic photovoltaic morphologies have improved by orders of magnitude over the last decade, and how the processing of reacting epoxy thermosets can now be investigated with million-particle models. We discuss these two materials systems and the training of materials simulators through the lens of cognitive load theory. For students, the broad view of ecosystem components should facilitate understanding how the key parts relate to each other first, followed by targeted exploration. In this way, the paper is organized in loose analogy to a coarse-grained model: The main components provide basic framing and accelerated sampling from which deeper research is better contextualized. For mentors, this paper is organized to provide a snapshot in time of the current simulation ecosystem and an on-ramp for simulation experts into the literature on pedagogical practice

First aid in acute stroke: Introducing a concept of first action to laypersons

OBJECTIVE: First aid training is well established to teach the public how to recognize a medical emergency and take appropriate action. Though it is now handled as a high priority emergency stroke is not among the main topics of first aid. We investigated if first aid training may be useful for enhancing stroke awareness. METHODS: We developed a 15–20 minute teaching session about stroke as an emergency including signs and symptoms and first hands-on measures. The session was integrated in standard first aid training of the St John Ambulance of Germany and participants were asked to fill out a questionnaire regarding their knowledge about stroke. Subjects were questioned before the stroke lesson and again at the end of the training. RESULTS: 532 participants of the training responded to the questionnaire (mean age 28.6 years, 53.6% male). There was a significant increase in proportion of subjects correctly defining what stroke is (28.4% vs. 69.9%, p < 0,001) and in the mean number of stroke symptoms listed (1.52 vs. 3.35, p < 0,001) by the participants. The number of participants unable to list at least 1 symptom decreased significantly (12.8 vs. 3.6%, p<0.001). CONCLUSIONS: In our study a teaching lesson integrated in first aid training was effective in improving stroke knowledge of participants. First aid training should be used for stroke information complementary to other activities like mass media campaigns as it is effective, could reach younger people that are not primarily interested in stroke and provides connections to other health topics

Long-Term Survivors of Metastatic Colorectal Cancer Treated with Systemic Chemotherapy Alone: A North Central Cancer Treatment Group Review of 3811 Patients, N0144

Although systemic chemotherapy in patients with unresectable metastatic colorectal cancer (mCRC) is palliative in nature, some patients experience long-term remission beyond 5 years consequent to treatment with chemotherapy alone

Microbial nitrogen limitation in the mammalian large intestine

Resource limitation is a fundamental factor governing the composition and function of ecological communities. However, the role of resource supply in structuring the intestinal microbiome has not been established and represents a challenge for mammals that rely on microbial symbionts for digestion: too little supply might starve the microbiome while too much might starve the host. We present evidence that microbiota occupy a habitat that is limited in total nitrogen supply within the large intestines of 30 mammal species. Lowering dietary protein levels in mice reduced their faecal concentrations of bacteria. A gradient of stoichiometry along the length of the gut was consistent with the hypothesis that intestinal nitrogen limitation results from host absorption of dietary nutrients. Nitrogen availability is also likely to be shaped by host-microbe interactions: levels of host-secreted nitrogen were altered in germ-free mice and when bacterial loads were reduced via experimental antibiotic treatment. Single-cell spectrometry revealed that members of the phylum Bacteroidetes consumed nitrogen in the large intestine more readily than other commensal taxa did. Our findings support a model where nitrogen limitation arises from preferential host use of dietary nutrients. We speculate that this resource limitation could enable hosts to regulate microbial communities in the large intestine. Commensal microbiota may have adapted to nitrogen-limited settings, suggesting one reason why excess dietary protein has been associated with degraded gut-microbial ecosystems

PCI-SS: MISO dynamic nonlinear protein secondary structure prediction

<p>Abstract</p> <p>Background</p> <p>Since the function of a protein is largely dictated by its three dimensional configuration, determining a protein's structure is of fundamental importance to biology. Here we report on a novel approach to determining the one dimensional secondary structure of proteins (distinguishing α-helices, β-strands, and non-regular structures) from primary sequence data which makes use of Parallel Cascade Identification (PCI), a powerful technique from the field of nonlinear system identification.</p> <p>Results</p> <p>Using PSI-BLAST divergent evolutionary profiles as input data, dynamic nonlinear systems are built through a black-box approach to model the process of protein folding. Genetic algorithms (GAs) are applied in order to optimize the architectural parameters of the PCI models. The three-state prediction problem is broken down into a combination of three binary sub-problems and protein structure classifiers are built using 2 layers of PCI classifiers. Careful construction of the optimization, training, and test datasets ensures that no homology exists between any training and testing data. A detailed comparison between PCI and 9 contemporary methods is provided over a set of 125 new protein chains guaranteed to be dissimilar to all training data. Unlike other secondary structure prediction methods, here a web service is developed to provide both human- and machine-readable interfaces to PCI-based protein secondary structure prediction. This server, called PCI-SS, is available at <url>http://bioinf.sce.carleton.ca/PCISS</url>. In addition to a dynamic PHP-generated web interface for humans, a Simple Object Access Protocol (SOAP) interface is added to permit invocation of the PCI-SS service remotely. This machine-readable interface facilitates incorporation of PCI-SS into multi-faceted systems biology analysis pipelines requiring protein secondary structure information, and greatly simplifies high-throughput analyses. XML is used to represent the input protein sequence data and also to encode the resulting structure prediction in a machine-readable format. To our knowledge, this represents the only publicly available SOAP-interface for a protein secondary structure prediction service with published WSDL interface definition.</p> <p>Conclusion</p> <p>Relative to the 9 contemporary methods included in the comparison cascaded PCI classifiers perform well, however PCI finds greatest application as a consensus classifier. When PCI is used to combine a sequence-to-structure PCI-based classifier with the current leading ANN-based method, PSIPRED, the overall error rate (Q3) is maintained while the rate of occurrence of a particularly detrimental error is reduced by up to 25%. This improvement in BAD score, combined with the machine-readable SOAP web service interface makes PCI-SS particularly useful for inclusion in a tertiary structure prediction pipeline.</p

Regulatory Hotspots in the Malaria Parasite Genome Dictate Transcriptional Variation

The determinants of transcriptional regulation in malaria parasites remain elusive. The presence of a well-characterized gene expression cascade shared by different Plasmodium falciparum strains could imply that transcriptional regulation and its natural variation do not contribute significantly to the evolution of parasite drug resistance. To clarify the role of transcriptional variation as a source of stain-specific diversity in the most deadly malaria species and to find genetic loci that dictate variations in gene expression, we examined genome-wide expression level polymorphisms (ELPs) in a genetic cross between phenotypically distinct parasite clones. Significant variation in gene expression is observed through direct co-hybridizations of RNA from different P. falciparum clones. Nearly 18% of genes were regulated by a significant expression quantitative trait locus. The genetic determinants of most of these ELPs resided in hotspots that are physically distant from their targets. The most prominent regulatory locus, influencing 269 transcripts, coincided with a Chromosome 5 amplification event carrying the drug resistance gene, pfmdr1, and 13 other genes. Drug selection pressure in the Dd2 parental clone lineage led not only to a copy number change in the pfmdr1 gene but also to an increased copy number of putative neighboring regulatory factors that, in turn, broadly influence the transcriptional network. Previously unrecognized transcriptional variation, controlled by polymorphic regulatory genes and possibly master regulators within large copy number variants, contributes to sweeping phenotypic evolution in drug-resistant malaria parasites

Fibroblasts Express Immune Relevant Genes and Are Important Sentinel Cells during Tissue Damage in Rainbow Trout (Oncorhynchus mykiss)

Fibroblasts have shown to be an immune competent cell type in mammals. However, little is known about the immunological functions of this cell-type in lower vertebrates. A rainbow trout hypodermal fibroblast cell-line (RTHDF) was shown to be responsive to PAMPs and DAMPs after stimulation with LPS from E. coli, supernatant and debris from sonicated RTHDF cells. LPS was overall the strongest inducer of IL-1β, IL-8, IL-10, TLR-3 and TLR-9. IL-1β and IL-8 were already highly up regulated after 1 hour of LPS stimulation. Supernatant stimuli significantly increased the expression of IL-1β, TLR-3 and TLR-9, whereas the debris stimuli only increased expression of IL-1β. Consequently, an in vivo experiment was further set up. By mechanically damaging the muscle tissue of rainbow trout, it was shown that fibroblasts in the muscle tissue of rainbow trout contribute to electing a highly local inflammatory response following tissue injury. The damaged muscle tissue showed a strong increase in the expression of the immune genes IL-1β, IL-8 and TGF-β already 4 hours post injury at the site of injury while the expression in non-damaged muscle tissue was not influenced. A weaker, but significant response was also seen for TLR-9 and TLR-22. Rainbow trout fibroblasts were found to be highly immune competent with a significant ability to express cytokines and immune receptors. Thus fish fibroblasts are believed to contribute significantly to local inflammatory reactions in concert with the traditional immune cells