Comparing Two Samples of Response Curves by Nonparamètric Tests of Predicted Order

Starting from MOSTELLER'S (1955) one-sample test of predicted order, some two-sample versions are proposed for comparing nonparametrically a treatment group (m response curves) with a control group (n response curves) as to a predicted shape represented by a specified rank order. The tests are applied to two groups of learning curves.     

A Bayesian analysis of the effect of selection for growth rate on growth curves in rabbits

Gompertz growth curves were fitted to the data of 137 rabbits from control (C) and selected (S) lines. The animals came from a synthetic rabbit line selected for an increased growth rate. The embryos from generations 3 and 4 were frozen and thawed to be contemporary of rabbits born in generation 10. Group C was the offspring of generations 3 and 4, and group S was the contemporary offspring of generation 10. The animals were weighed individually twice a week during the first four weeks of life, and once a week thereafter, until 20 weeks of age. Subsequently, the males were weighed weekly until 40 weeks of age. The random samples of the posterior distributions of the growth curve parameters were drawn by using Markov Chain Monte Carlo (MCMC) methods. As a consequence of selection, the selected animals were heavier than the C animals throughout the entire growth curve. Adult body weight, estimated as a parameter of the Gompertz curve, was 7% higher in the selected line. The other parameters of the Gompertz curve were scarcely affected by selection. When selected and control growth curves are represented in a metabolic scale, all differences disappear.     

A Comparison between the LEHMACHER & WALL Rank Tests and Pyhel's Permutation Test for the Analysis of r Independent Samples of Response Curves

LEHMACHER & WALL'S (1978) example of the application of a rank test for the comparison of two independent samples of response curves is reanalyzed by PYHEL'S (1980) permutation test for the hypothesis of parallelism of response curves. This permutation test is part of a complete evaluation of effects for a split-plot design using the permutation test based procedure by WILLMES & PYHEL (1981). Differences in test decisions are discussed.     

Statistical analysis of optimal culture conditions for Gluconacetobacter hansenii cellulose production

AIM: The purpose of this study was to analyse the effects of different culture parameters on Gluconacetobacter hansenii (ATCC 10821) to determine which conditions provided optimum cellulose growth. METHODS AND RESULTS: Five culture factors were investigated: carbon source, addition of ethanol, inoculation ratio, pH and temperature. jmp Software (SAS, Cary, NC, USA) was used to design this experiment using a fractional factorial design. After 22 days of static culture, the cellulose produced by the bacteria was harvested, purified and dried to compare the cellulose yields. The results were analysed by fitting the data to a first-order model with two-factor interactions. CONCLUSIONS: The study confirmed that carbon source, addition of ethanol, and temperature were significant factors in the production of cellulose of this G. hansenii strain. While pH alone does not significantly affect average cellulose production, cellulose yields are affected by pH interaction with the carbon source. Culturing the bacteria on glucose at pH 6.5 produces more cellulose than at pH 5.5, while using mannitol at pH 5.5 produces more cellulose than at pH 6.5. The bacteria produced the most cellulose when cultured on mannitol, at pH 5.5, without ethanol, at 20 degrees C. Inoculation ratio was not found to be a significant factor or involved in any significant two-factor interaction. SIGNIFICANCE AND IMPACT OF THE STUDY: These findings give insight into the conditions necessary to maximize cellulose production from this G. hansenii strain. In addition, this work demonstrates how the fractional factorial design can be used to test a large number of factors using an abbreviated set of experiments. Fitting a statistical model determined the significant factors as well as the significant two-factor interactions.     

Analysis of the effect of design parameters and their interactions on the strength of dental restorations with endodontic posts,using finite element models and statistical analysis

Many previous studies, both in vitro and with model simulations, have been conducted in an attempt to reach a full understanding of how the different design parameters of an endodontically restored tooth affect its mechanical strength. However, differences in the experimental set-up or modelling conditions and the limited number of parameters studied in each case prevent us from obtaining clear conclusions about the real significance of each parameter. In this work, a new approach is proposed for this purpose based on the combination of a validated three-dimensional parametric biomechanical model of the restored tooth and statistical analysis using full factorial analysis of variance. A two-step approach with two virtual tests (with, respectively, 128 and 81 finite element models) was used in the present work to study the effect of several design parameters on the strength of a restored incisor, using full factorial designs. Within the limitations of this study, and for cases where the parameters are within the ranges that were tested, the conclusions indicate that the material of the post is the most significant factor as far as its strength is concerned, the use of a low Young's modulus being preferable for this component. Once the post material has been chosen, the geometry of the post is of less importance than the Young's modulus selected for the core or, especially, for the crown.     

基于全细胞催化合成NADP重组细胞复合通透剂的筛选

本文以重组大肠杆菌E. coli BL21(DE3) p ET30α(+)-Nmnat为研究对象,考察化学通透剂处理重组菌对其催化合成NADP的影响。实验显示,在单因素筛选实验中,四种通透剂曲拉通X-100、吐温80、二甲基亚砜和十六烷基三甲基溴化铵(CTAB)对细胞进行通透化处理均可提高全细胞催化产率,且提高幅度差距并不显著。进一步采用析因设计考察四种通透剂的复合效应,除了曲拉通X-100与吐温80和曲拉通X-100与CTAB交互作用的P大于0. 05为不显著,其余所有交互作用项P值均小于0. 05,呈现显著性,且复合通透剂中,仅单一增加CTAB量,复合体系的协同作用将减少,制约作用增加,不适宜用于复合配方。最后采用中心组合设计进一步对复配效果进行优化,通过拟合得到最佳通透剂配比为曲拉通X-100(1. 64%),吐温80(2. 53%)以及二甲基亚砜(1. 06%),此时NADP预测产率达到77. 46%,与实际验证产率均值77. 05%相差甚微,说明实验优化模型具有良好预测性,优化结果与未添加通透剂相比提升近47%,表明优化复合通透剂配方更有利于提高重组菌催化合成NADP。     

A convenient analysis of Michaelis enzyme kinetic progress curves based on second derivatives

A simple method is described for the estimation of the Michaelis parameters, K_m and V_m, from a single progress curve at a single substrate concentration without the need to follow the reaction to completion. By measuring the substrate concentration and the time when the second derivative is at a minimum, K_m and V_m can be easily obtained.     

An analysis of interspecific relationships ofSaguinus based on cranial measurements

The interspecific relationships of the following nine forms ofSaguinus were analyzed applying the multivariate analysis to the cranial measurements;S. oedipus, S. geoffroyi, S. leucopus, S. nigricollis, S. fuscicollis, S. labiatus, S. mystax, S. midas midas, andS. midas niger. Penrose's size distance was used to express the size factor among the nine forms; and for the shape factor, Q-mode correlation coefficients were utilized. The shape distance betweenS. oedipus andS. geoffroyi was almost equal to that betweenS. nigricollis andS. fuscicollis which are recognized as different species based on biogeographical evidence. Furthermore, the Penrose's size distance betweenS. oedipus andS. geoffroyi was quite large. Therefore, the results of this study support the hypothesis thatS. oedipus andS. geoffroyi are valid species. The analysis of the phylogenetic relationships among the nine forms was based on the shape factor only. The forms were divided into two main clusters: (1)S. oedipus, S. geoffroyi, andS. leucopus; (2)S. nigricollis, S. fuscicollis, S. labiatus, S. mystax, S. midas midas, andS. midas niger. In the former cluster,S. oedipus was more closely related toS. geoffroyi than either was toS. leucopus. The latter cluster was subdivided in two subclusters based on the degree of their affinity: (2a)S. nigricollis, S. fuscicollis, S. labiatus, andS. mystax; and (2b)S. midas midas andS. midas niger. In the former subcluster, [S. nigricollis, S. fuscicollis] and [S. labiatus, S. mystax] were classified into clusters, respectively. The ancestor of theS. nigricollis group differentiated intoS. oedipus, S. geoffroyi, andS. leucopus with the narrowing of the maxilla in the facial region, andS. midas midas andS. midas niger with the downward movement of rhinion.     

Comparison of culture methods on exopolysaccharide production in the submerged culture of Cordyceps militaris and process optimization

Aims: To improve exopolysaccharides (EPS) production of Cordyceps militaris (C. militaris), effects of different culture method on mycelial biomass and EPS production in the submerged culture of C. militaris were investigated. Methods and Results: A new two‐stage fermentation process for EPS production of C. militaris was designed in this work. Central composite design (CCD) was utilized to optimize the two‐stage fermentation process. The results showed that the two‐stage fermentation process for EPS production was superior to other culture method (conventional static culture and shake culture). CCD revealed that the optimum values of the test variables for EPS production were shaken for 140 h followed by 130‐h static culture. The maximum EPS production reached 3·2 g l^?1 under optimized two‐stage culture and was about 2·3‐fold and 1·6‐fold in comparison with those of original static culture and shake culture. Conclusions: It was indicated that a new two‐stage culture method obtained in this work possessed a high potential for the industrial production for EPS of C. militaris. Significance and Impact of the Study: The fundamental information obtained in this work is complementary to those of previous investigations on the submerged culture of C. militaris for the production of bioactive metabolites.     

Assessment of gene set analysis methods based on microarray data

Gene set analysis (GSA) incorporates biological information into statistical knowledge to identify gene sets differently expressed between two or more phenotypes. It allows us to gain an insight into the functional working mechanism of cells beyond the detection of differently expressed gene sets. In order to evaluate the competence of GSA approaches, three self-contained GSA approaches with different statistical methods were chosen; Category, Globaltest and Hotelling's T² together with their assayed power to identify the differences expressed via simulation and real microarray data. The Category does not take care of the correlation structure, while the other two deal with correlations.     

A general kinetic analysis of transport Tests of the carrier model based on predicted relations among experimental parameters

The analysis of transport kinetics has lacked both a unified treatment in which general rate equations are written entirely in terms of experimental parameters, and a convention by which these parameters may be designated in a concise yet immediately recognizable manner. Such a treatment is presented here in an easily accessible form, and a simple system of nomenclature is proposed resembling that in use in enzyme kinetics. The treatment is independent of assumptions about rate-limiting steps in transport, and applies to both active and facilitated systems, including obligatory exchange. A single substrate is characterized by twelve different parameters, only five of which are required in theory to calculate the others. If a second substrate is present on the trans side of the membrane there are six more parameters. All eighteen parameters are linked by multiple relationships which provide a complete set of rejection criteria for the generalized form of the mobile carrier. Relationships among parameters are also defined that give information on the rate-limiting steps in transport. Equations governing any individual experiment, involving only experimental parameters, are easily written out from the general expressions, for example under conditions of zero trans and infinite trans flux, equilibrium exchange, or competitive inhibition.     

Multi-scale parametric spectral analysis for exon detection in DNA sequences based on forward-backward linear prediction and singular value decomposition of the double-base curves

This paper presents a new method for exon detection in DNA sequences based on multi-scale parametric spectral analysis. A forward-backward linear prediction (FBLP) with the singular value decomposition (SVD) algorithm FBLP-SVD is applied to the double-base curves (DB-curves) of a DNA sequence using a variable moving window sizes to estimate the signal spectrum at multiple scales. Simulations are done on short human genes in the range of 11bp to 2032bp and the results show that our proposed method out-performs the classical Fourier transform method. The multi-scale approach is shown to be more effective than using a single scale with a fixed window size. In addition, our method is flexible as it requires no training data.     

A score test for linkage analysis of ordinal traits based on IBD sharing

Statistical methods for linkage analysis are well established for both binary and quantitative traits. However, numerous diseases including cancer and psychiatric disorders are rated on discrete ordinal scales. To analyze pedigree data with ordinal traits, we recently proposed a latent variable model which has higher power to detect linkage using ordinal traits than methods using the dichotomized traits. The challenge with the latent variable model is that the likelihood is usually very complicated, and as a result, the computation of the likelihood ratio statistic is too intensive for large pedigrees. In this paper, we derive a computationally efficient score statistic based on the identity-by-decent sharing information between relatives. Using simulation studies, we examined the asymptotic distribution of the test statistic and the power of our proposed test under various levels of heritability. We compared the computing time as well as power of the score test with the likelihood ratio test. We then applied our method for the Collaborative Study on the Genetics of Alcoholism and performed a genome scan to map susceptibility genes for alcohol dependence. We found a strong linkage signal on chromosome 4.     

Optimization of a protective medium for enhancing the viability of freeze-dried Lactobacillus delbrueckii subsp. bulgaricus based on response surface methodology

Response surface methodology (RSM) was used to optimize a protective medium for enhancing the cell viability of Lactobacillus delbrueckii subsp. bulgaricus LB14 during freeze-drying. Using a previous Plackett–Burman design, it was found that sucrose, glycerol, sorbitol and skim milk were the most effective freeze-drying protective agents for L. bulgaricus LB14. A full factorial central composite design was applied to determine the optimum levels of these four protective agents. The experimental data allowed the development of an empirical model (P<0.0001) describing the inter-relationships between the independent and dependent variables. By solving the regression equation, and analyzing the response surface contour and surface plots, the optimal concentrations of the agents were determined as: sucrose 66.40 g/L, glycerol 101.20 g/L, sorbitol 113.00 g/L, and skim milk 130.00 g/L. L. bulgaricus LB14 freeze-dried in this medium obtained a cell viability of up to 86.53%.     

Development of an isotope dilution mass spectrometry assay for HbA1c based on enzyme-cleaved peptide analysis

The hydrophobic contributions of 17 individual peptides, fused to the N-terminal of Bacillus stearothermophilus lactate dehydrogenase (LDH) were studied by hydrophobic interaction chromatography (HIC) and aqueous two-phase system (ATPS). The constructs were sequenced from a protein library designed with a five-amino acid randomised region in the N-terminal of an LDH protein. The 17 LDH variants and an LDH control lacking the randomised region were expressed in Escherichia coli. HIC and ATPS behaviour of the proteins indicated significant differences in protein hydrophobicity, even though the modifications caused only 1% increase in protein molecular weight and 2% variation in isoelectric points. HIC and ATPS results correlated well (R(2) = 0.89). Protein expression was clearly affected by N-terminal modification, but there was no evidence that the modification affected protein activity. A GluAsnAlaAspVal modification resulted in increased protein expression. In most cases, HIC and ATPS results compared favourably with those predicted on the basis of 34 amino acid residue hydrophobicity scales; assuming exposure of tag residues to solution. Exceptions included LeuAlaGlyValIle and LeuTyrGlyCysIle modifications, which were predicted, assuming full solution exposure, to be more hydrophobic than observed.     

Feasibility of methods based on nucleic acid amplification techniques to fulfil the requirements for microbiological analysis of water quality

Molecular methods based on nucleic acid recognition and amplification are valuable tools to complement and support water management decisions. At present, these decisions are mostly supported by the principle of end‐point monitoring for indicators and a small number of selected measured by traditional methods. Nucleic acid methods show enormous potential for identifying isolates from conventional culture methods, providing data on cultivable and noncultivable micro‐organisms, informing on the presence of pathogens in waters, determining the causes of waterborne outbreaks, and, in some cases, detecting emerging pathogens. However, some features of water microbiology affect the performance of nucleic acid‐based molecular techniques and thus challenge their suitability for routine water quality control. These features include the variable composition of target water samples, the generally low numbers of target micro‐organisms, the variable water quality required for different uses and the physiological status or condition of such micro‐organisms. The standardization of these molecular techniques is also an important challenge for its routine use in terms of accuracy (trueness and precision) and robustness (reproducibility and reliability during normal usage). Most of national and international water regulations recommend the application of standard methods, and any new technique must be validated respect to established methods and procedures. Moreover, molecular methods show a high cost‐effectiveness value that limits its practicability on some microbial water analyses. However, new molecular techniques could contribute with new information or at least to supplement the limitation of traditional culture‐based methods. Undoubtedly, challenges for these nucleic acid‐based methods need to be identified and solved to improve their feasibility for routine microbial water monitoring.     

Amperometric mediated carbon paste biosensor based on D-fructose dehydrogenase for the determination of fructose in food analysis

A new mediated amperometric biosensor for fructose is described. The sensor is based on a commercially available D-fructose dehydrogenase. The enzyme is incorporated in a carbon paste matrix containing Os(bpy)₂Cl₂ as redox mediator that achieves electron transfer at 0·1 V (versus Ag/AgCl) with maximum apparent current densities of 1·2 mA/cm². The dependence of the steady-state current on the loading of the mediator and the enzyme, other electrode construction parameters, the operating potential, the pH and the temperature was studied. In the steady-state mode the response current was directly proportional to D-fructose concentration from 0·2 to 20mM with a detection limit of 35 μM (signal-to-noise ratio, S/N, 3). In the flow injection analysis mode the response current was directly proportional to D-fructose concentration from 0·5 to 15 M with a detection limit of 115 μM (S/N 3). The sensor was used for the determination of fructose in food samples in a flow injection system and validated with a commercial enzyme kit.     

A new geometric biclustering algorithm based on the Hough transform for analysis of large-scale microarray data

Biclustering is an important tool in microarray analysis when only a subset of genes co-regulates in a subset of conditions. Different from standard clustering analyses, biclustering performs simultaneous classification in both gene and condition directions in a microarray data matrix. However, the biclustering problem is inherently intractable and computationally complex. In this paper, we present a new biclustering algorithm based on the geometrical viewpoint of coherent gene expression profiles. In this method, we perform pattern identification based on the Hough transform in a column-pair space. The algorithm is especially suitable for the biclustering analysis of large-scale microarray data. Our studies show that the approach can discover significant biclusters with respect to the increased noise level and regulatory complexity. Furthermore, we also test the ability of our method to locate biologically verifiable biclusters within an annotated set of genes.     

Experimental design for optimal parameter estimation of an enzyme kinetic process based on the analysis of the Fisher information matrix

The investigation of enzyme kinetics is increasingly important, especially for finding active substances and understanding intracellular behaviors. Therefore, the determination of an enzyme's kinetic parameters is crucial. For this a systematic experimental design procedure is necessary to avoid wasting time and resources. The parameter estimation error of a Michaelis-Menten enzyme kinetic process is analysed analytically to reduce the search area as well as numerically to specify the optimum for parameter estimation. From analytical analysis of the Fisher information matrix the fact is obtained, that an enzyme feed will not improve the estimation process, but substrate feeding is favorable with small volume flow. Unconstrained and constrained process conditions are considered. If substrate fed-batch process design is used instead of pure batch experiments the improvements of the Cramer-Rao lower bound of the variance of parameter estimation error reduces to 82% for mu(max) and to 60% for K(m) of the batch values in average.