1,712 research outputs found

    Evolutionary dynamics of adult stem cells: Comparison of random and immortal strand segregation mechanisms

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    This paper develops a point-mutation model describing the evolutionary dynamics of a population of adult stem cells. Such a model may prove useful for quantitative studies of tissue aging and the emergence of cancer. We consider two modes of chromosome segregation: (1) Random segregation, where the daughter chromosomes of a given parent chromosome segregate randomly into the stem cell and its differentiating sister cell. (2) ``Immortal DNA strand'' co-segregation, for which the stem cell retains the daughter chromosomes with the oldest parent strands. Immortal strand co-segregation is a mechanism, originally proposed by Cairns (J. Cairns, {\it Nature} {\bf 255}, 197 (1975)), by which stem cells preserve the integrity of their genomes. For random segregation, we develop an ordered strand pair formulation of the dynamics, analogous to the ordered strand pair formalism developed for quasispecies dynamics involving semiconservative replication with imperfect lesion repair (in this context, lesion repair is taken to mean repair of postreplication base-pair mismatches). Interestingly, a similar formulation is possible with immortal strand co-segregation, despite the fact that this segregation mechanism is age-dependent. From our model we are able to mathematically show that, when lesion repair is imperfect, then immortal strand co-segregation leads to better preservation of the stem cell lineage than random chromosome segregation. Furthermore, our model allows us to estimate the optimal lesion repair efficiency for preserving an adult stem cell population for a given period of time. For human stem cells, we obtain that mispaired bases still present after replication and cell division should be left untouched, to avoid potentially fixing a mutation in both DNA strands.Comment: 9 pages, 3 figure

    Impact of foods with health logo on ssaturated fat, sodium and sugar intake of young Dutch adults

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    Objective Health logos are introduced to distinguish foods with ‘healthier’ nutrient composition from regular foods. In the present study, we evaluated the effects of changed food compositions according to health logo criteria on the intake of saturated fat, sugar and sodium in a Dutch population of young adults. Design Foods in the Dutch food composition table were evaluated against nutrient criteria for logo eligibility. Three replacement scenarios were compared with the nutrient intake ‘as measured’ in the Dutch consumption survey. The foods not complying with health logo criteria were replaced either by ‘virtual’ foods exactly complying with the health logo criteria, with real 2007 market shares (scenario I) and 100 % market shares (scenario II), or by existing similar foods with a composition that already complied with the health logo criteria (scenario III). Results The percentage reduction in nutrient intake with the current 2007 market shares of ‘health logo foods’ was -2·5 % for SFA, 0 % for sodium and -1 % for sugar. With a 100 % market share these reductions would be -10 % for SFA, -4 % for sodium and -6 % for sugar. This may lead to a reduction of -40 % for SFA, -23 % for sodium and -36 % for sugar in the most optimal replacement scenario. Conclusions With ‘health logo foods’, available in 2007 and current consumption patterns, small reductions can be achieved for SFA and sugar. For additional reductions, lowering the fat/sodium content of meat (products) towards health logo criteria and drinks without sugar towards limits far below health logo criteria would be the most effective reformulation strategy

    Ab initio study of alanine polypeptide chains twisting

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    We have investigated the potential energy surfaces for alanine chains consisting of three and six amino acids. For these molecules we have calculated potential energy surfaces as a function of the Ramachandran angles Phi and Psi, which are widely used for the characterization of the polypeptide chains. These particular degrees of freedom are essential for the characterization of proteins folding process. Calculations have been carried out within ab initio theoretical framework based on the density functional theory and accounting for all the electrons in the system. We have determined stable conformations and calculated the energy barriers for transitions between them. Using a thermodynamic approach, we have estimated the times of characteristic transitions between these conformations. The results of our calculations have been compared with those obtained by other theoretical methods and with the available experimental data extracted from the Protein Data Base. This comparison demonstrates a reasonable correspondence of the most prominent minima on the calculated potential energy surfaces to the experimentally measured angles Phi and Psi for alanine chains appearing in native proteins. We have also investigated the influence of the secondary structure of polypeptide chains on the formation of the potential energy landscape. This analysis has been performed for the sheet and the helix conformations of chains of six amino acids.Comment: 24 pages, 10 figure

    Unzipping and binding of small interfering RNA with single walled Carbon Nanotube: a platform for small interfering RNA delivery

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    In an effort to design efficient platform for siRNA delivery, we combine all atom classical and quantum simulations to study the binding of small interfering RNA (siRNA) by pristine single wall carbon nanotube (SWCNT). Our results show that siRNA strongly binds to SWCNT surface via unzipping its base-pairs and the propensity of unzipping increases with the increase in the diameter of the SWCNTs. The unzipping and subsequent wrapping events are initiated and driven by van der Waals interactions between the aromatic rings of siRNA nucleobases and the SWCNT surface. However, MD simulations of double strand DNA (dsDNA) of the same sequence show that the dsDNA undergoes much less unzipping and wrapping on the SWCNT in the simulation time scale of 70 ns. This interesting difference is due to smaller interaction energy of thymidine of dsDNA with the SWCNT compared to that of uridine of siRNA, as calculated by dispersion corrected density functional theory (DFT) methods. After the optimal binding of siRNA to SWCNT, the complex is very stable which serves as one of the major mechanisms of siRNA delivery for biomedical applications. Since siRNA has to undergo unwinding process with the effect of RNA- induced silencing complex, our proposed delivery mechanism by SWCNT possesses potential advantages in achieving RNA interference (RNAi).Comment: 28 pages, 7 figures, 4 table

    Southeast of What? Reflections on SEALS\u27 Success

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    In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model

    Single-Cell RNA-Sequencing Reveals a Continuous Spectrum of Differentiation in Hematopoietic Cells.

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    The transcriptional programs that govern hematopoiesis have been investigated primarily by population-level analysis of hematopoietic stem and progenitor cells, which cannot reveal the continuous nature of the differentiation process. Here we applied single-cell RNA-sequencing to a population of hematopoietic cells in zebrafish as they undergo thrombocyte lineage commitment. By reconstructing their developmental chronology computationally, we were able to place each cell along a continuum from stem cell to mature cell, refining the traditional lineage tree. The progression of cells along this continuum is characterized by a highly coordinated transcriptional program, displaying simultaneous suppression of genes involved in cell proliferation and ribosomal biogenesis as the expression of lineage specific genes increases. Within this program, there is substantial heterogeneity in the expression of the key lineage regulators. Overall, the total number of genes expressed, as well as the total mRNA content of the cell, decreases as the cells undergo lineage commitment.The study was supported by Cancer Research UK grant number C45041/A14953 to A.C., C.L. and L.F and a core support grant from the Wellcome Trust and MRC to the Wellcome Trust–Medical Research Council Cambridge Stem Cell Institute. S.T would like to acknowledge the Lister Research Prize from the Lister Institute. The authors declare no competing financial interestsThis is the final version of the article. It first appeared from Cell Press via http://dx.doi.org/10.1016/j.celrep.2015.12.08

    Mean-field cooperativity in chemical kinetics

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    We consider cooperative reactions and we study the effects of the interaction strength among the system components on the reaction rate, hence realizing a connection between microscopic and macroscopic observables. Our approach is based on statistical mechanics models and it is developed analytically via mean-field techniques. First of all, we show that, when the coupling strength is set positive, the model is able to consistently recover all the various cooperative measures previously introduced, hence obtaining a single unifying framework. Furthermore, we introduce a criterion to discriminate between weak and strong cooperativity, based on a measure of "susceptibility". We also properly extend the model in order to account for multiple attachments phenomena: this is realized by incorporating within the model pp-body interactions, whose non-trivial cooperative capability is investigated too.Comment: 25 pages, 4 figure
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