Prediction of biopore- and matrix-dominated flow from X-ray CT-derived macropore network characteristics

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Macropore flow at the field scale: predictive performance of empirical models and X-ray CT analyzed macropore characteristics

Predictions of macropore flow is important for maintaining both soil and water quality as it governs key related soil processes e.g. soil erosion and subsurface transport of pollutants. However, macropore flow currently cannot be reliably predicted at the field scale because of inherently large spatial variability. The aim of this study was to perform field scale characterization of macropore flow and investigate the predictive performance of (1) current empirical models for both water and air flow, and (2) X-ray CT derived macropore network characteristics. For this purpose, 65 cylindrical soil columns (6 cm diameter and 3.5 cm height) were extracted from the topsoil (5 to 8.5 cm depth) in a 15 m × 15 m grid from an agricultural loamy field located in Silstrup, Denmark. All soil columns were scanned with an industrial CT scanner (129 μm resolution) and later used for measurements of saturated water permeability, air permeability and gas diffusivity at -30 and -100 cm matric potentials. Distribution maps for both water and air permeabilities and gas diffusivity reflected no spatial correlation irrespective of the soil texture and organic matter maps. Empirical predictive models for both water and air permeabilities showed poor performance as they were not able to realistically capture macropore flow because of poor correlations with soil texture and bulk density. The tested empirical model predicted well gas diffusivity at -100 cm matric potential, but relatively failed at -30 cm matric potential particularly for samples with biopore flow. Image segmentation output of the four employed methods was nearly the same, and matched well with measured air-filled porosity at -30 cm matric potential. Many of the CT derived macropore network characteristics were strongly interrelated. Most of the macropore network characteristics were also strongly correlated with saturated water permeability, air permeability, and gas diffusivity. The correlations between macropore network characteristics and macropore flow parameters were further improved on dividing soil samples into samples with biopore and matrix flow. Observed strong correlations between macropore network characteristics and macropore flow highlighted the need of further research on numerical simulations of macropore flow based on X-ray CT images. This could pave the way for the digital soil physics laboratory in the future

Efficient algorithms for reconstructing gene content by co-evolution

<p>Abstract</p> <p>Background</p> <p>In a previous study we demonstrated that co-evolutionary information can be utilized for improving the accuracy of ancestral gene content reconstruction. To this end, we defined a new computational problem, the Ancestral Co-Evolutionary (ACE) problem, and developed algorithms for solving it.</p> <p>Results</p> <p>In the current paper we generalize our previous study in various ways. First, we describe new efficient computational approaches for solving the ACE problem. The new approaches are based on reductions to classical methods such as linear programming relaxation, quadratic programming, and min-cut. Second, we report new computational hardness results related to the ACE, including practical cases where it can be solved in polynomial time.</p> <p>Third, we generalize the ACE problem and demonstrate how our approach can be used for inferring parts of the genomes of <it>non-ancestral</it> organisms. To this end, we describe a heuristic for finding the portion of the genome ('dominant set’) that can be used to reconstruct the rest of the genome with the lowest error rate. This heuristic utilizes both evolutionary information and co-evolutionary information.</p> <p>We implemented these algorithms on a large input of the ACE problem (95 unicellular organisms, 4,873 protein families, and 10, 576 of co-evolutionary relations), demonstrating that some of these algorithms can outperform the algorithm used in our previous study. In addition, we show that based on our approach a ’dominant set’ cab be used reconstruct a major fraction of a genome (up to 79%) with relatively low error-rate (<it>e.g.</it> 0.11). We find that the ’dominant set’ tends to include metabolic and regulatory genes, with high evolutionary rate, and low protein abundance and number of protein-protein interactions.</p> <p>Conclusions</p> <p>The <it>ACE</it> problem can be efficiently extended for inferring the genomes of organisms that exist today. In addition, it may be solved in polynomial time in many practical cases. Metabolic and regulatory genes were found to be the most important groups of genes necessary for reconstructing gene content of an organism based on other related genomes.</p

Quantitative principles of cis-translational control by general mRNA sequence features in eukaryotes.

BackgroundGeneral translational cis-elements are present in the mRNAs of all genes and affect the recruitment, assembly, and progress of preinitiation complexes and the ribosome under many physiological states. These elements include mRNA folding, upstream open reading frames, specific nucleotides flanking the initiating AUG codon, protein coding sequence length, and codon usage. The quantitative contributions of these sequence features and how and why they coordinate to control translation rates are not well understood.ResultsHere, we show that these sequence features specify 42-81% of the variance in translation rates in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, Mus musculus, and Homo sapiens. We establish that control by RNA secondary structure is chiefly mediated by highly folded 25-60 nucleotide segments within mRNA 5' regions, that changes in tri-nucleotide frequencies between highly and poorly translated 5' regions are correlated between all species, and that control by distinct biochemical processes is extensively correlated as is regulation by a single process acting in different parts of the same mRNA.ConclusionsOur work shows that general features control a much larger fraction of the variance in translation rates than previously realized. We provide a more detailed and accurate understanding of the aspects of RNA structure that directs translation in diverse eukaryotes. In addition, we note that the strongly correlated regulation between and within cis-control features will cause more even densities of translational complexes along each mRNA and therefore more efficient use of the translation machinery by the cell

Rational manipulation of mRNA folding free energy allows rheostat control of pneumolysin production by Streptococcus pneumoniae

Rational manipulation of mRNA folding free energy allows rheostat control of pneumolysin production by Streptococcus pneumoniaeThe contribution of specific factors to bacterial virulence is generally investigated through creation of genetic "knockouts" that are then compared to wild-type strains or complemented mutants. This paradigm is useful to understand the effect of presence vs. absence of a specific gene product but cannot account for concentration-dependent effects, such as may occur with some bacterial toxins. In order to assess threshold and dose-response effects of virulence factors, robust systems for tunable expression are required. Recent evidence suggests that the folding free energy (?G) of the 5' end of mRNA transcripts can have a significant effect on translation efficiency and overall protein abundance. Here we demonstrate that rational alteration of 5' mRNA folding free energy by introduction of synonymous mutations allows for predictable changes in pneumolysin (PLY) expression by Streptococcus pneumoniae without the need for chemical inducers or heterologous promoters. We created a panel of isogenic S. pneumoniae strains, differing only in synonymous (silent) mutations at the 5' end of the PLY mRNA that are predicted to alter ?G. Such manipulation allows rheostat-like control of PLY production and alters the cytotoxicity of whole S. pneumoniae on primary and immortalized human cells. These studies provide proof-of-principle for further investigation of mRNA ?G manipulation as a tool in studies of bacterial pathogenesis.National Institutes of Health (www.nih.gov) (R01 AI092743 and R21 AI111020 to A.J.R.). F.E.A. was supported by the Portuguese Foundation for Science and Technology (www.fct.pt) SFRH/BD/33901/2009 and the Luso-American Development Foundation (www.flad.pt). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Small Polarons in Transition Metal Oxides

The formation of polarons is a pervasive phenomenon in transition metal oxide compounds, with a strong impact on the physical properties and functionalities of the hosting materials. In its original formulation the polaron problem considers a single charge carrier in a polar crystal interacting with its surrounding lattice. Depending on the spatial extension of the polaron quasiparticle, originating from the coupling between the excess charge and the phonon field, one speaks of small or large polarons. This chapter discusses the modeling of small polarons in real materials, with a particular focus on the archetypal polaron material TiO2. After an introductory part, surveying the fundamental theoretical and experimental aspects of the physics of polarons, the chapter examines how to model small polarons using first principles schemes in order to predict, understand and interpret a variety of polaron properties in bulk phases and surfaces. Following the spirit of this handbook, different types of computational procedures and prescriptions are presented with specific instructions on the setup required to model polaron effects.Comment: 36 pages, 12 figure

Combining visible near-infrared spectroscopy and water vapor sorption for soil specific surface area estimation

Abstract The soil specific surface area (SSA) is a fundamental property governing a range of soil processes relevant to engineering, environmental, and agricultural applications. A method for SSA determination based on a combination of visible near‐infrared spectroscopy (vis‐NIRS) and vapor sorption isotherm measurements was proposed. Two models for water vapor sorption isotherms (WSIs) were used: the Tuller–Or (TO) and the Guggenheim–Anderson–de Boer (GAB) model. They were parameterized with sorption isotherm measurements and applied for SSA estimation for a wide range of soils (N = 270) from 27 countries. The generated vis‐NIRS models were compared with models where the SSA was determined with the ethylene glycol monoethyl ether (EGME) method. Different regression techniques were tested and included partial least squares (PLS), support vector machines (SVM), and artificial neural networks (ANN). The effect of dataset subdivision based on EGME values on model performance was also tested. Successful calibration models for SSATO and SSAGAB were generated and were nearly identical to that of SSAEGME. The performance of models was dependent on the range and variation in SSA values. However, the comparison using selected validation samples indicated no significant differences in the estimated SSATO, SSAGAB, and SSAEGME, with an average standardized RMSE (SRMSE = RMSE/range) of 0.07, 0.06 and 0.07, respectively. Small differences among the regression techniques were found, yet SVM performed best. The results of this study indicate that the combination of vis‐NIRS with the WSI as a reference technique for vis‐NIRS models provides SSA estimations akin to the EGME method

Genome-Scale Analysis of Translation Elongation with a Ribosome Flow Model

We describe the first large scale analysis of gene translation that is based on a model that takes into account the physical and dynamical nature of this process. The Ribosomal Flow Model (RFM) predicts fundamental features of the translation process, including translation rates, protein abundance levels, ribosomal densities and the relation between all these variables, better than alternative (‘non-physical’) approaches. In addition, we show that the RFM can be used for accurate inference of various other quantities including genes' initiation rates and translation costs. These quantities could not be inferred by previous predictors. We find that increasing the number of available ribosomes (or equivalently the initiation rate) increases the genomic translation rate and the mean ribosome density only up to a certain point, beyond which both saturate. Strikingly, assuming that the translation system is tuned to work at the pre-saturation point maximizes the predictive power of the model with respect to experimental data. This result suggests that in all organisms that were analyzed (from bacteria to Human), the global initiation rate is optimized to attain the pre-saturation point. The fact that similar results were not observed for heterologous genes indicates that this feature is under selection. Remarkably, the gap between the performance of the RFM and alternative predictors is strikingly large in the case of heterologous genes, testifying to the model's promising biotechnological value in predicting the abundance of heterologous proteins before expressing them in the desired host

Professionalism, Golf Coaching and a Master of Science Degree: A commentary

As a point of reference I congratulate Simon Jenkins on tackling the issue of professionalism in coaching. As he points out coaching is not a profession, but this does not mean that coaching would not benefit from going through a professionalization process. As things stand I find that the stimulus article unpacks some critically important issues of professionalism, broadly within the context of golf coaching. However, I am not sure enough is made of understanding what professional (golf) coaching actually is nor how the development of a professional golf coach can be facilitated by a Master of Science Degree (M.Sc.). I will focus my commentary on these two issues