Efficient multipoint mapping: making use of dominant repulsion-phase markers

The paper is devoted to the problem of multipoint gene ordering with a particular focus on "dominance" complication that acts differently in conditions of coupling-phase and repulsion-phase markers. To solve the problem we split the dataset into two complementary subsets each containing shared codominant markers and dominant markers in the coupling-phase only. Multilocus ordering in the proposed algorithm is based on pairwise recombination frequencies and using the well-known travelling salesman problem (TSP) formalization. To obtain accurate results, we developed a multiphase algorithm that includes synchronized-marker ordering of two subsets assisted by re-sampling-based map verification, combining the resulting maps into an integrated map followed by verification of the integrated map. A new synchronized Evolution-Strategy discrete optimization algorithm was developed here for the proposed multilocus ordering approach in which common codominant markers facilitate stabilization of the marker order of the two complementary maps. High performance of the employed algorithm allows systematic treatment for the problem of verification of the obtained multilocus orders, based on computing-intensive bootstrap and jackknife technologies for detection and removing unreliable marker scores. The efficiency of the proposed algorithm was demonstrated on simulated and real data.Communicated by J.W. Snape     

Development and operation of a trickling biofilter system for continuous treatment of gas-phase trichloroethylene

A parallel trickling biofilter (TBF) system that consists of two TBFs units in parallel, one for biodegradation of trichloroethylene (TCE) and the other for reactivation of an inactivated biofilm, was developed and operated for continuous treatment of gas-phase TCE by Burkholderia cepacia G4. For inlet loadings below 8.6 mg TCE l^–1 d^–1, complete removal of TCE was achieved. The maximal TCE elimination capacity was 17 mg l^–1 d^–1.     

Ginseng increases intestinal elimination of albendazole sulfoxide in the rat

Herbal products show potential drug interactions, some of them with adverse effects. The main aim of this work was to study the effect of Panax ginseng on the intestinal elimination of the benzimidazole derivative albendazole sulfoxide (ABZSO). An upper small intestine segment was isolated and perfused in situ with saline, while ABZSO solution (10 mg/kg i.v.) was administered intravenously. Blood samples and intestinal secretion were collected over 60 min and analysed by HPLC. The intestinal clearance of ABZSO was 0.106+/-0.010 ml/min. Systemic co-administration of ginseng (10 mg/kg i.v.) increased significantly (P<0.05) the clearance of ABZSO (0.132+/-0.005 ml/min). The increase in ABZSO elimination could be the result of the effect of ginseng on metabolic pathways. These results highlight the interactions between herbal products (sometimes dietary constituents) and drugs such as benzimidazoles, since ginseng modifies the luminal clearance of this anthelminthic drug and could potentially interfere with drugs that undergo the same intestinal processes.     

Stereoselective pharmacokinetics and metabolism of flobufen in guinea pigs

Stereoselective aspects of pharmacokinetics and metabolism of a chiral nonsteroidal antiinflammatory drug, flobufen, 4-(2', 4'-difluorobiphenyl-4-yl)-2-methyl-4-oxobutanoic acid, were studied in male guinea pigs after p.o. administration of racemic flobufen (rac-flobufen) at a dose of 10 mg/kg. Blood samples were collected at intervals over 16 h after the administration of rac-flobufen for the quantification of flobufen enantiomers and their respective metabolites in plasma by chiral high-performance liquid chromatography (HPLC). Compartmental pharmacokinetic analysis was used to determine pharmacokinetic parameters of R- and S-flobufen. The plasma concentrations of the S- and R-enantiomers differed significantly during the experimental period. The S/R-enantiomeric ratio in 7plasma reached a maximum value of 10.1 at 240 min postdose. The oral clearance value of R-flobufen was five times higher than S-flobufen. The other pharmacokinetic parameters (K(e), T(1/2), V(SS)/F, MRT) of the enantiomers also differed substantially. All four stereoisomers of the dihydrometabolite of flobufen were detected in plasma with varying concentrations. Metabolite 17203 [4-(2,4-difluorophenyl)-phenylacetic acid] exhibited a relatively longer residence time compared to that noted for the enantiomers of the parent compound. Pharmacokinetics of the flobufen enantiomers were stereoselective in guinea pigs. The metabolism of flobufen was complex. However, metabolite 17203 seemed to be the main metabolite of flobufen that may be responsible for its relatively long-lasting antiphlogistic and immunomodulatory effects.     

Structure-based prediction of binding peptides to MHC class I molecules: application to a broad range of MHC alleles

Specific binding of antigenic peptides to major histocompatibility complex (MHC) class I molecules is a prerequisite for their recognition by cytotoxic T-cells. Prediction of MHC-binding peptides must therefore be incorporated in any predictive algorithm attempting to identify immunodominant T-cell epitopes, based on the amino acid sequence of the protein antigen. Development of predictive algorithms based on experimental binding data requires experimental testing of a very large number of peptides. A complementary approach relies on the structural conservation observed in crystallographically solved peptide-MHC complexes. By this approach, the peptide structure in the MHC groove is used as a template upon which peptide candidates are threaded, and their compatibility to bind is evaluated by statistical pairwise potentials. Our original algorithm based on this approach used the pairwise potential table of Miyazawa and Jernigan (Miyazawa S, Jernigan RL, 1996, J Mol Biol 256:623-644) and succeeded to correctly identify good binders only for MHC molecules with hydrophobic binding pockets, probably because of the high emphasis of hydrophobic interactions in this table. A recently developed pairwise potential table by Betancourt and Thirumalai (Betancourt MR, Thirumalai D, 1999, Protein Sci 8:361-369) that is based on the Miyazawa and Jernigan table describes the hydrophilic interactions more appropriately. In this paper, we demonstrate how the use of this table, together with a new definition of MHC contact residues by which only residues that contribute exclusively to sequence specific binding are included, allows the development of an improved algorithm that can be applied to a wide range of MHC class I alleles.     

Prediction of amino acid sequence from structure

We have developed a method for the prediction of an amino acid sequence that is compatible with a three-dimensional backbone structure. Using only a backbone structure of a protein as input, the algorithm is capable of designing sequences that closely resemble natural members of the protein family to which the template structure belongs. In general, the predicted sequences are shown to have multiple sequence profile scores that are dramatically higher than those of random sequences, and sometimes better than some of the natural sequences that make up the superfamily. As anticipated, highly conserved but poorly predicted residues are often those that contribute to the functional rather than structural properties of the protein. Overall, our analysis suggests that statistical profile scores of designed sequences are a novel and valuable figure of merit for assessing and improving protein design algorithms.     

Semiparametric regression analysis of interval-censored data

We propose a semiparametric approach to the proportional hazards regression analysis of interval-censored data. An EM algorithm based on an approximate likelihood leads to an M-step that involves maximizing a standard Cox partial likelihood to estimate regression coefficients and then using the Breslow estimator for the unknown baseline hazards. The E-step takes a particularly simple form because all incomplete data appear as linear terms in the complete-data log likelihood. The algorithm of Turnbull (1976, Journal of the Royal Statistical Society, Series B 38, 290-295) is used to determine times at which the hazard can take positive mass. We found multiple imputation to yield an easily computed variance estimate that appears to be more reliable than asymptotic methods with small to moderately sized data sets. In the right-censored survival setting, the approach reduces to the standard Cox proportional hazards analysis, while the algorithm reduces to the one suggested by Clayton and Cuzick (1985, Applied Statistics 34, 148-156). The method is illustrated on data from the breast cancer cosmetics trial, previously analyzed by Finkelstein (1986, Biometrics 42, 845-854) and several subsequent authors.     

Estimation in a Cox proportional hazards cure model

Some failure time data come from a population that consists of some subjects who are susceptible to and others who are nonsusceptible to the event of interest. The data typically have heavy censoring at the end of the follow-up period, and a standard survival analysis would not always be appropriate. In such situations where there is good scientific or empirical evidence of a nonsusceptible population, the mixture or cure model can be used (Farewell, 1982, Biometrics 38, 1041-1046). It assumes a binary distribution to model the incidence probability and a parametric failure time distribution to model the latency. Kuk and Chen (1992, Biometrika 79, 531-541) extended the model by using Cox's proportional hazards regression for the latency. We develop maximum likelihood techniques for the joint estimation of the incidence and latency regression parameters in this model using the nonparametric form of the likelihood and an EM algorithm. A zero-tail constraint is used to reduce the near nonidentifiability of the problem. The inverse of the observed information matrix is used to compute the standard errors. A simulation study shows that the methods are competitive to the parametric methods under ideal conditions and are generally better when censoring from loss to follow-up is heavy. The methods are applied to a data set of tonsil cancer patients treated with radiation therapy.     

Minimax D-optimal designs for the logistic model

We propose an algorithm for constructing minimax D-optimal designs for the logistic model when only the ranges of the values for both parameters are assumed known. Properties of these designs are studied and compared with optimal Bayesian designs and Sitter's (1992, Biometrics, 48, 1145-1155) minimax D-optimal kk-designs. Examples of minimax D-optimal designs are presented for the logistic and power logistic models, including a dose-response design for rheumatoid arthritis patients.     

A linear mixed-effects model for multivariate censored data

We apply a linear mixed-effects model to multivariate failure time data. Computation of the regression parameters involves the Buckley-James method in an iterated Monte Carlo expectation-maximization algorithm, wherein the Monte Carlo E-step is implemented using the Metropolis-Hastings algorithm. From simulation studies, this approach compares favorably with the marginal independence approach, especially when there is a strong within-cluster correlation.