The hydrodynamic resistance of hyaluronic acid: estimates from sedimentation studies

The problem of estimating the permeability of hyaluronic acid as a function of concentration has been examined. A previously known method of obtaining permeability from sedimentation studies has been employed, and the results have been compared to those obtained from convection studies, in which solvent is forced through the hyaluronic acid. The two sets of results were seen to be at variance, which could be explained by a flow-induced polarization of the hyaluronic acid in the convection studies. The polarization phenomenon was described in terms of a convection-associated compaction balancing the hyaluronic acid's intrinsic resistance to compression. Based on these results and other arguments, it was suggested that data from sedimentation studies provide a more accurate estimate of hyaluronic acid permeability than do convection experiments. The implications of this finding in a physiological context were briefly discussed.     

The distribution of genetic parameter estimates and confidence intervals from small disconnected diallels

The distributions of genetic variance components and their ratios (heritability and type-B genetic correlation) from 105 pairs of six-parent disconnected half-diallels of a breeding population of loblolly pine (Pinus taeda L.) were examined. A series of simulations based on these estimates were carried out to study the coverage accuracy of confidence intervals based on the usual t-method and several other alternative methods. Genetic variance estimates fluctuated greatly from one experiment to another. Both general combining ability variance (²_g) and specific combining ability variance (²_s) had a large positive skewness. For ²_g and ²_s, a skewness-adjusted t-method proposed by Boos and Hughes-Oliver (Am Stat 54:121–128, 2000) provided better upper endpoint confidence intervals than t-intervals, whereas they were similar for the lower endpoint. Bootstrap BCa-intervals (Efron and Tibshirani, An introduction to the bootstrap. Chapman & Hall, London 436 p, 1993) and Halls transformation methods (Zhou and Gao, Am Stat 54:100–104, 2000) had poor coverages. Coverage accuracy of Fiellers interval endpoint(J R Stat Soc Ser B 16:175–185, 1954) and t-interval endpoint were similar for both h² and r_B for sample sizes n10, but for n=30 the Fiellers method is much better.     

Minimum significant ratio of selectivity ratios (MSRSR) and confidence in ratio of selectivity ratios (CRSR): quantitative measures for selectivity ratios obtained by screening assays

Development of inhibitor compounds selective against undesirable targets is critical in drug discovery. Selectivity ratios for candidate compounds are evaluated by dividing potencies from two assays assessing the off-target and target. Because all potency measurements have underlying uncertainty, understanding error propagation is essential to interpreting selectivity data. Assay noise introduces ambiguity in the statistical significance of selectivity ratios, particularly at low replicate numbers when compounds are often prioritized for subsequent testing. The ability to differentiate potency results for any pair of compounds in one assay is evaluated using a metric called minimum significant ratio (MSR). Potency results of one compound tested in a pair of assays can be differentiated by the minimum significant selectivity ratio (MSSR). To differentiate selectivity ratios for any pair of compounds, we extend this concept by proposing two new parameters called the minimum significant ratio of selectivity ratios (MSRSR) and confidence in ratio of selectivity ratios (CRSR). Importantly, these tools can be used after a single selectivity measurement. We describe these methods and illustrate their usefulness using structure-activity relationship data from a Janus kinase inhibitor project, in which these tools informed a cogent retesting strategy and enabled rapid and objective decision making.     

MUSA: a parameter free algorithm for the identification of biologically significant motifs

MOTIVATION: The ability to identify complex motifs, i.e. non-contiguous nucleotide sequences, is a key feature of modern motif finders. Addressing this problem is extremely important, not only because these motifs can accurately model biological phenomena but because its extraction is highly dependent upon the appropriate selection of numerous search parameters. Currently available combinatorial algorithms have proved to be highly efficient in exhaustively enumerating motifs (including complex motifs), which fulfill certain extraction criteria. However, one major problem with these methods is the large number of parameters that need to be specified. RESULTS: We propose a new algorithm, MUSA (Motif finding using an UnSupervised Approach), that can be used either to autonomously find over-represented complex motifs or to estimate search parameters for modern motif finders. This method relies on a biclustering algorithm that operates on a matrix of co-occurrences of small motifs. The performance of this method is independent of the composite structure of the motifs being sought, making few assumptions about their characteristics. The MUSA algorithm was applied to two datasets involving the bacterium Pseudomonas putida KT2440. The first one was composed of 70 sigma(54)-dependent promoter sequences and the second dataset included 54 promoter sequences of up-regulated genes in response to phenol, as suggested by quantitative proteomics. The results obtained indicate that this approach is very effective at identifying complex motifs of biological significance. AVAILABILITY: The MUSA algorithm is available upon request from the authors, and will be made available via a Web based interface.     

The use of continuous assays to characterize the oxidative cyclase that synthesizes the chlorophyll isocyclic ring.

A continuous spectroscopic assay has been developed for magnesium protoporphyrin monomethyl ester oxidative cyclase, which records either the dark formation of both free and protein-bound magnesium phaeoporphyrin or, following flash illumination, its corresponding chlorin. The properties of the enzyme were studied in wheat etioplasts. When plastids were pre-illuminated in the presence of NADPH all endogenous protochlorophyllide was converted into chlorophyllide and the product of dark incubation with magnesium protoporphyrin monomethyl ester was protein-bound magnesium 2-vinyl phaeoporphyrin a5 monomethyl ester with either a vinyl or an ethyl group at position 4 of the macrocycle alone. Rates of chlorin production from magnesium protoporphyrin monomethyl ester (up to 1240 pmol/h per mg of protein) were adequate to support known rates of plant chlorophyll synthesis. The enzyme required NADPH and O2 and had an approximate Km of 0.5 microM for magnesium protoporphyrin IX monomethyl ester. Lipid-soluble metal-complexing agents inhibited enzyme activity: hydrophilic agents were ineffective. The strong inhibition of mycobactin suggested the involvement of iron ions. Zinc protoporphyrin monomethyl ester, but not copper or nickel or metal-free protoporphyrin monomethyl esters, was a substrate; magnesium protoporphyrin dimethyl ester was inhibitory. The activity of the enzyme was unchanged by prior greening of the plants. The activity in isolated etioplasts was very dependent upon intactness of the plastid structure.     

Urea hydrolysis by immobilized urease in a fixed-bed reactor: analysis and kinetic parameter estimation

Urea hydrolysis by urease immobilized onto ion exchange resins in a fixed-bed reactor has been studied. A modified Michaelis-Menten rate expression is used to describe the pH-dependent, substrate- and product-inhibited kinetics. Ionic equilibria of product and buffer species are included to account for pH changes generated by reaction. An isothermal, heterogeneous plug-flow reactor model has been developed. An effectiveness factor is used to describe the reaction-diffusion process within the particle phase. The procedure for covalent immobilization of urease onto macroporous cation exchangers is described. Urea conversion data are used to estimate kinetic parameters by a simplex optimization method. The best-fitted parameters are then used to predict the outlet conversions and pH values for systems with various inlet pH values, inlet urea and ammonia concentrations, buffers, particle sizes, and spacetimes. Very good agreement is obtained between experimental data and model predictions. This immobilized urease system exhibits quite different kinetic behavior from soluble urease because the pH near the enzyme active sites is different from that of the pore fluid. This effect results in a shift of the optimal pH value of the V(max) (pH) curve from 6.6 (soluble urease) to ca. 7.6 in dialysate solution, and ca. pH 8.0 in 20mM phosphate buffer. The reactor model is especially useful for estimating intrinsic kinetic parameters of immobilized enzymes and for designing urea removal columns.     

A statistical evaluation of the reproducibility of micronucleus, sister-chromatid exchange, thioguanine-resistance and ouabain-resistance assays in V79 cells exposed to ethyl methanesulfonate and 7,12-dimethylbenz[a]anthracene

In contrast to the "validation" of short-term in vitro genotoxicity assays by concordance with the rodent cancer bioassay, the present report describes the multiple replication of 4 short-term tests with V79 cells (micronucleus assay, MN; sister-chromatid exchange, SCE; ouabain resistance. OUR; and thioguanine resistance, TGR) within the same assay system following exposure to each of two genotoxins, ethyl methanesulfonate (direct acting) and 7,12-dimethylbenz[a]anthracene (indirect acting). Reproducibility, proportion of genotoxins correctly identified, and proportion of non-genotoxins correctly identified by each test were each determined statistically. Decision rules were formulated to declare a positive response in each assay, and overall accuracy of each was determined. Statistical analysis of the data, obtained under standardized test conditions, showed that for these two chemicals SCE identified 100% of genotoxins and 86% of non-genotoxins, with overall accuracy of prediction of 93%; TGR identified 98% of genotoxins and 74% of non-genotoxins, with overall accuracy of 86%; MN identified 78% of genotoxins and 84% of non-genotoxins, with overall accuracy of 81%; while OUR indicated 100% of genotoxins, but only 50% of non-genotoxins, and only 76% overall accuracy. The results suggested that the best overall accuracy of classification with the V79 assay system could be achieved by measurement of SCE in combination with thioguanine resistance.     

The accuracy of statistical methods for estimation of haplotype frequencies: an example from the CD4 locus

Haplotype analysis has become increasingly important for the study of human disease as well as for reconstruction of human population histories. Computer programs have been developed to estimate haplotype frequencies statistically from marker phenotypes in unrelated individuals. However, there currently are few empirical reports on the accuracy of statistical estimates that must infer linkage phase. We have analyzed haplotypes at the CD4 locus on chromosome 12 that consist of a short tandem-repeat polymorphism and an Alu insertion/deletion polymorphism located 9.8 kb apart, in 398 individuals from 10 geographically diverse sub-Saharan African populations. Haplotype frequency estimates obtained using gene counting based on molecularly haplotyped (phase-known) data were compared with haplotype frequency estimates obtained using the expectation-maximization algorithm. We show that the estimated frequencies of common haplotypes do not differ significantly with the use of phase-known versus phase-unknown data. However, rare haplotypes are occasionally miscalled when their presence/absence must be inferred. Thus, for those research questions for which the common haplotypes are most important, frequency estimates based on the phase-unknown marker-typing results from unrelated individuals will be sufficient. However, in cases where knowledge of rare haplotypes is critical, molecular haplotyping will be necessary to determine linkage phase unambiguously.     

Frequency response of the chest: modeling and parameter estimation.

The frequency response of the respiratory system was studied in the range from 3 to 70 Hz in 15 normal subjects by applying sinusoidal pressure variations around the chest and measuring gas flow at the mouth. The observed input-output relationships were systematically compared to those predicted on the basis of linear differential equations of increasing order. From 3 to 20 Hz the behavior of the system was best described by a 3rd-order equation, and from 3 to 50 Hz by a 4th-order one. A mechanistic model of the 4th order, featuring tissue compliance (Ct), resistance (Rt) and inertance (It), alveolar gas compressibility (Cg) and airway resistance (Raw), and inertance (Iaw) was developed. Using that model, the following mean values were found: Ct = 2.08-10(-2)1-hPa-1 (1 hPa congruent to 1 cm of water); Rt = 1.10-hPa-1(-1)-s; It = 0.21-10(-2)hPa-1(-1)-s2; Raw = 1.35-hPa-1(-1)-s; Iaw = 2.55-10(-2)hPa-1(-1)-s2. Additional experiments devised to validate the model were reasonably successful, suggesting that the physical meaning attributed to the coefficients was correct. The validity of the assumptions and the physiological meaning of the coefficients are discussed.     

Evaluating the performance of a successive-approximations approach to parameter optimization in maximum-likelihood phylogeny estimation

Almost all studies that estimate phylogenies from DNA sequencedata under the maximum-likelihood (ML) criterion employ an approximateapproach. Most commonly, model parameters are estimated on someinitial phylogenetic estimate derived using a rapid method (neighbor-joiningor parsimony). Parameters are then held constant during a treesearch, and ideally, the procedure is repeated until convergenceis achieved. However, the effectiveness of this approximationhas not been formally assessed, in part because doing so requirescomputationally intensive, full-optimization analyses. Here,we report both indirect and direct evaluations of the effectivenessof successive approximations. We obtained an indirect evaluationby comparing the results of replicate runs on real data thatuse random trees to provide initial parameter estimates. Forsix real data sets taken from the literature, all replicateiterative searches converged to the same joint estimates oftopology and model parameters, suggesting that the approximationis not starting-point dependent, as long as the heuristic searchesof tree space are rigorous. We conducted a more direct assessmentusing simulations in which we compared the accuracy of phylogeniesestimated using full optimization of all model parameters oneach tree evaluated to the accuracy of trees estimated via successiveapproximations. There is no significant difference between theaccuracy of the approximation searches relative to full-optimizationsearches. Our results demonstrate that successive approximationis reliable and provide reassurance that this much faster approachis safe to use for ML estimation of topology.