A new approach for estimating the efficiencies of the nucleotide substitution models

In this article, a new approach is presented for estimating the efficiencies of the nucleotide substitution models in a four-taxon case and then this approach is used to estimate the relative efficiencies of six substitution models under a wide variety of conditions. In this approach, efficiencies of the models are estimated by using a simple probability distribution theory. To assess the accuracy of the new approach, efficiencies of the models are also estimated by using the direct estimation method. Simulation results from the direct estimation method confirmed that the new approach is highly accurate. The success of the new approach opens a unique opportunity to develop analytical methods for estimating the relative efficiencies of the substitution models in a straightforward way.     

Estimation of true growth and product yields in aerobic cultures

In the microbial production of useful products, it is important to understand the allocation of substrate energy for maintanance, growth, and product formation. Methods are presented to obtain point and 95% confidence interval estimates for the true growth yield parameter, true product yield parameter, and the maintenance parameter. Methods are presented which allow all data to be used simultaneously for those cases where more than the minimum number of measurements are made at each specific growth rate (or dilution rate). Three estimation methods and two forms of the energy allocation equations are investigated. Point estimates are similar for the three methods, but interval estimates are considerably larger for one of the three methods. The results depend on the form of the equations.     

A new approach for estimating fine root production in forests: a combination of ingrowth core and scanner

Key message

A method of combination of ingrowth core and scanner provides better estimation of fine root production.

Abstract

Estimating fine root (diameter ≤2 mm) production has been difficult. The best method remains unknown because each method has potential biases associated with the estimation methods and field techniques applied, leading to over- or underestimation. In this study, a new method combining ingrowth core and scanner named as “combined method” was described, and it was applied to a Quercus serrata plantation in Tsukuba, Japan. Comparing accuracy of estimation of fine root production by decision matrix and continuous inflow method using ingrowth core with that by “combined method” was conducted. Closed-box protected scanners and ingrowth cores were buried in a field on December 6, 2012, and fine root images were nondestructively scanned biweekly for growth measurement. In addition, thermometers were used to record temperature automatically at 1 m from the ground and at a depth of 10 cm in soil at 12 a.m. daily to evaluate the effect of temperature on fine root production. The results indicated that the combined method gave 19 and 16 % higher estimation of fine root production than decision matrix and continuous inflow method, respectively. In the combined method, using scanned images at different time intervals gave different estimates. Generally, longer time-interval images gave lower estimates: biweekly-interval images yielded an estimate that was 16 % higher than that yielded using 2-month-interval images. A 1-month time lag relationship (R ² = 0.84, p < 0.01) between soil temperature and fine root production was found at the study site. This relationship implied that higher fine root production occurred in summer. It was concluded that the combined method gave a more accurate estimation of fine root production in forests among the three methods compared.

     

A new approach for estimating the crosslink density of covalently crosslinked ionic polysaccharide gels

For an ideal polysaccharide gel with a known total polymer chain contour length, crosslinks all of the same functionality and elastic chains all with the same contour length and stiffness, the gel crosslink density can readily be determined from measurements of the maximum volume of the swollen gel (Moe et al., (1991) Food Hydrocolloids, 5, (1/2), 119–123. In the case of randomly crosslinked polysaccharide gels, where the chain contour length between two adjacent crosslinks may vary greatly, it is often much more difficult to determine the crosslink density. This paper reports on an attempt to extend the use of maximum gel volume measurements to estimate crosslink density for the latter type of gel. This is done by calculating the maximum swelling volume for polymer networks with four-functional crosslinks, known elastic chain mean contour length and standard deviation. The numerical analysis involves the calculation of the equilibrium force at each crosslink as the network expands. This allows a detailed study of how the distribution of individual polymer chain contour lengths affects the maximum swelling volume. The computer simulation results are compared with the results from experimental measurements of the maximum volume of swollen covalently crosslinked sodium alginate gels.     

Accounting for imperfect observation and estimating true species distributions in modelling biological invasions

The documentation of biological invasions is often incomplete with records lagging behind the species’ actual spread to a spatio‐temporally heterogeneous extent. Such imperfect observation bears the risk of underestimating the already realised distribution of the invading species, misguiding management efforts and misjudging potential future impacts. In this paper, we develop a hierarchical modelling framework which disentangles the determinants of the invasion and observation processes, models spatio‐temporal heterogeneity in detection patterns, and infers the actual, yet partly undocumented distribution of the species at any particular time. We illustrate the model with a case study application to the invasion of common ragweed Ambrosia artemisiifolia in Austria. The invasion part of the model reconstructs the historical spread of this species across a grid of ～ 6 × 6 km² cells as driven by spatio‐temporal variation in physical site conditions, propagule production, dispersal, and ‘background’ introductions from unknown sources. The observation part models the detection of the species’ occurrences based on heterogeneous sampling efforts, human population density, and estimated local invasion level. We fitted the hierarchical model using a Bayesian inference approach with parameters estimated by Markov chain Monte Carlo (MCMC). The actual spread of A. artemisiifolia concentrated on the climatically well‐suited lowlands and was mainly driven by spatio‐temporal propagule pressure from source cells with long‐distance dispersal occurring rather frequently. Annual detection probabilities were estimated to vary between about 1 and up to 28%, depending mainly on sampling intensity. The model suggested that by 2005 about half of the actual distribution of the species was not yet documented. Our hierarchical model offers a flexible means to account for imperfect observation and spatio‐temporal variability in detection efficiency. Inferences can be used to disentangle aspects of the invasion dynamics itself from patterns of data collection, develop improved future surveying schemes, and design more efficient invasion management strategies.     

Models for longitudinal data: a generalized estimating equation approach

This article discusses extensions of generalized linear models for the analysis of longitudinal data. Two approaches are considered: subject-specific (SS) models in which heterogeneity in regression parameters is explicitly modelled; and population-averaged (PA) models in which the aggregate response for the population is the focus. We use a generalized estimating equation approach to fit both classes of models for discrete and continuous outcomes. When the subject-specific parameters are assumed to follow a Gaussian distribution, simple relationships between the PA and SS parameters are available. The methods are illustrated with an analysis of data on mother's smoking and children's respiratory disease.     

Evaluation of true kinetic parameters for reversible immobilized enzyme reactions

For a reversible one-substrate reaction system that follows the Haldane reaction mechanism, a new and effective method has been proposed to extract true or intrinsic kinetic parameters of immobilized enzymes from diffusion limited rate data. The method utilizes the effectiveness factors correlated in terms of the general modulus defined by Aris and Bischoff, and a new modulus defined in the present study. It requires a trial-and-error calculation, but only a few data points. Furthermore, it provides a saving of materials such as substrates and enzymes, and takes less time for experiments compared to the initial rate methods. The usefulness of the method is demonstrated by determining the kinetic parameters for membrane bound fumarase which catalyzes the reaction of the conversion of fumarate to L-malate, for which the equilibrium constant is ca. 4.     

Balanced biochemical reactions: a new approach to unify chemical and biochemical thermodynamics

A novel procedure is presented which, by balancing elements and electric charge of biochemical reactions which occur at constant pH and pMg, allows assessing the thermodynamics properties of reaction Δ_rG ^′0, Δ_rH ^′0, Δ_rS ^′0 and the change in binding of hydrogen and magnesium ions of these reactions. This procedure of general applicability avoids the complex calculations required by the use of the Legendre transformed thermodynamic properties of formation Δ_fG ^′0, Δ_fH ^′0 and Δ_fS ^′0 hitherto considered an obligatory prerequisite to deal with the thermodynamics of biochemical reactions. As a consequence, the term “conditional” is proposed in substitution of “Legendre transformed” to indicate these thermodynamics properties. It is also shown that the thermodynamic potential G is fully adequate to give a criterion of spontaneous chemical change for all biochemical reactions and then that the use of the Legendre transformed G′ is unnecessary. The procedure proposed can be applied to any biochemical reaction, making possible to re-unify the two worlds of chemical and biochemical thermodynamics, which so far have been treated separately.     

A new approach to estimating the significance of identification of deletion inserts in pairwise alignment

Within the framework of the unique method of estimating the significance of pairwise alignment of nucleotide sequences, developed by the authors, a new approach to the analysis of deletion inserts in pairwise alignment has been realized. It was shown that the decrease in the average integral length of deletion inserts in alignments obtained using the modern algorithms, as compared with true alignments, is related to a decrease in the number of some deletion inserts rather than a decrease in their average length.     

Shotgun isotope array for rapid, substrate-specific detection of microorganisms in a microbial community

The shotgun isotope array method has been proposed to be an effective new tool for use in substrate-specific microbe exploration without any prior knowledge of the community composition. Proof of concept was demonstrated by detection of acetate-degrading microorganisms in activated sludge and further verified by independent stable isotope probing (SIP).     

Changing the landscape: a new strategy for estimating large phylogenies

In this paper we describe a new heuristic strategy designed to find optimal (parsimonious) trees for data sets with large numbers of taxa and characters. This new strategy uses an iterative searching process of branch swapping with equally weighted characters, followed by swapping with reweighted characters. This process increases the efficiency of the search because, after each round of swapping with reweighted characters, the subsequent swapping with equal weights will start from a different group (island) of trees that are only slightly, if at all, less optimal. In contrast, conventional heuristic searching with constant equal weighting can become trapped on islands of suboptimal trees. We test the new strategy against a conventional strategy and a modified conventional strategy and show that, within a given time, the new strategy finds trees that are markedly more parsimonious. We also compare our new strategy with a recent, independently developed strategy known as the Parsimony Ratchet.     

A probabilistic approach for estimating water permeability in pressure-driven membranes

A probabilistic approach is proposed to estimate water permeability in a cellulose triacetate (CTA) membrane. Water transport across the membrane is simulated in reverse osmosis mode by means of non-equilibrium molecular dynamics (MD) simulations. Different membrane configurations obtained by an annealing MD simulation are considered and simulation results are analyzed by using a hierarchical Bayesian model to obtain the permeability of the different membranes. The estimated membrane permeability is used to predict full-scale water flux by means of a process-level Monte Carlo simulation. Based on the results, the parameters of the model are observed to converge within 5-ns total simulation time. The results also indicate that the use of unique structural configurations in MD simulations is essential to capture realistic membrane properties at the molecular scale. Furthermore, the predicted full-scale water flux based on the estimated permeability is within the same order of magnitude of bench-scale experimental measurement of 1.72×10^?5 m/s.     

Segmented Bayesian calibration approach for estimating age in forensic science

Forensic age estimation is receiving growing attention from researchers in the last few years. Accurate estimates of age are needed both for identifying real age in individuals without any identity document and assessing it for human remains. The methods applied in such context are mostly based on radiological analysis of some anatomical districts and entail the use of a regression model. However, estimating chronological age by regression models leads to overestimated ages in younger subjects and underestimated ages in older ones. We introduced a full Bayesian calibration method combined with a segmented function for age estimation that relied on a Normal distribution as a density model to mitigate this bias. In this way, we were also able to model the decreasing growth rate in juveniles. We compared our new Bayesian‐segmented model with other existing approaches. The proposed method helped producing more robust and precise forecasts of age than compared models while exhibited comparable accuracy in terms of forecasting measures. Our method seemed to overcome the estimation bias also when applied to a real data set of South‐African juvenile subjects.     

What's new and what's true of what's new in dermatology

Within the past few years it has been noted that abnormal types of hemoglobin found in certain persons are associated with definite clinical disorders. At least four different varieties of sickle cell anemia are now recognized, three of them being heterozygous and one homozygous. When the gene for sickling is represented once, the person is asymptomatic and is said to have "sickle cell trait." However, when the sickle cell trait is present in combination with certain other hemoglobin abnormalities such as hemoglobin C or D or with thalassemia trait, symptomatic clinical disease results. The homozygous condition, in which two genes for hemoglobin C are present in the same person, has been observed in a few instances. A similar condition as regards hemoglobin D has not as yet been recognized.     

A multicriteria decision making approach for estimating the number of clusters in a data set

Determining the number of clusters in a data set is an essential yet difficult step in cluster analysis. Since this task involves more than one criterion, it can be modeled as a multiple criteria decision making (MCDM) problem. This paper proposes a multiple criteria decision making (MCDM)-based approach to estimate the number of clusters for a given data set. In this approach, MCDM methods consider different numbers of clusters as alternatives and the outputs of any clustering algorithm on validity measures as criteria. The proposed method is examined by an experimental study using three MCDM methods, the well-known clustering algorithm-k-means, ten relative measures, and fifteen public-domain UCI machine learning data sets. The results show that MCDM methods work fairly well in estimating the number of clusters in the data and outperform the ten relative measures considered in the study.     

Microbial energetics and stoichiometry for biodegradation of aromatic compounds involving oxygenation reactions

Oxygenation reactions significantly alter the energy and electron flows and, consequently, the overall stoichiometry for the microbial utilization of aromatic compounds. Oxygenation reactions do not yield a net release of electrons, but require an input of electrons to reduce oxygen molecules. The biodegradation pathway of phenanthrene as a model compound was analyzed to determine the impact of oxygenation reactions on overall stoichiometry using the half-reaction method. For individual oxygenation reactions, the half-reaction method for analyzing the electron and energy flows must be modified, because the reactions do not release electrons for synthesis or energy generation. Coupling the oxygenation reaction to subsequent reaction steps provides a net electron release for the coupled reactions. Modeling results indicate that oxygenation reactions increase the oxygen requirement and reduce the cell yield, compared to the conventional mineralization represented by hydroxylation reactions in place of oxygenations. The computed yields considering oxygenation reactions conform better to empirical yields reported in the literature than do yields computed by the hydroxylation single-step methods. The coupled-reaction model also is consistent with information about the ways in which micro-organisms that degrade aromatics accumulate intermediates, regulate degradation genes, and organize enzyme clusters.