Gene clustering for time-series microarray with production outputs

The identification of coexpressed genes from microarray data is a challenging problem in bioinformatics and computational biology. The objective of this study is to obtain knowledge about the most important genes and clusters related to production outputs of real-world time-series microarray data in the industrial microbiology area. Each sample in the microarray data experiment is complemented with the measurement of the corresponding production and growth values. A novel aspect of this research refers to considering the relation of coexpression patterns with the measured outputs to guide the biological interpretation of results. Shape-based clustering models are developed using the pattern of gene expression values over time and further incorporating knowledge about the correlation between the change in the gene expression level and the output value. Experiments are performed for time-series microarray of bacteria, and an analysis from a biological perspective is carried out. The obtained results confirm the existence of relationships between output variables and gene expressions. Moreover, the shape-based clustering methods show promising results, being able to guide metabolic engineering actions with the identification of potential targets.     

Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models.     

Homocamptothecins: synthesis and antitumor activity of novel E-ring-modified camptothecin analogues

Homocamptothecin (hCPT), a camptothecin (CPT) analogue with a seven membered beta-hydroxylactone which combines enhanced plasma stability and potent topoisomerase I (Topo I)-mediated activity, is an attractive template for the elaboration of new anticancer agents. Like CPT, hCPT carries an asymmetric tertiary alcohol and displays stereoselective inhibition of Topo I. The preparation and biological screening of racemic hCPT analogues are described. The 10 hCPTs tested were better Topo I inhibitors than CPT. Fluorinated hCPTs 23c, d,f,g were found to have potent cytotoxic activity on A427 and PC-3 tumor cell lines. Their cytotoxicity remained high on the K562adr and MCF7mdr cell lines, which overexpress a functionally active P-glycoprotein. Fluorinated hCPTs were more efficacious in vivo than CPT on HT-29 xenografts. In this model, a tumor growth delay of 25 days was reached with hCPT 23g at a daily dose of 0.32 mg/kg, compared to 4 days with CPT at 0.625 mg/kg. Thus difluorinated hCPT 23g warrants further investigation as a novel Topo I inhibitor with high cytotoxicity toward tumor cells and promising in vivo efficacy.     

The extent of knowledge of Quick Response Manufacturing principles: an exploratory transnational study

The main goal of this research is to identify whether companies that have implemented the Quick Response Manufacturing (QRM) approach have full knowledge of the QRM principles or have merely applied the elements (principles and tools) that have a close relationship with Lean Manufacturing. Based on a review of the literature regarding the QRM principles, an exploratory survey was conducted for over 20 manufacturing companies from Brazil, Europe and the USA that operate in an Engineer or Make to Order environment system and explicitly have conducted QRM journeys. The results of the present study show that (i) the surveyed companies have difficulty knowing and applying some of the exclusive elements of this approach, even if they started implementing QRM several years ago; (ii) the surveyed companies’ knowledge degree over QRM exclusive elements is apparently higher among US-based companies due to better trained employees and better dissemination and awareness of the QRM exclusive elements; and (iii) a mentality based on productivity, low costs and due date delivery was identified as the main barrier for companies to achieve a higher knowledge degree regarding QRM.     

Semiparametric additive models under symmetric distributions

In this paper we discuss estimation and diagnostic procedures in semiparametric additive models with symmetric errors in order to permit distributions with heavier and lighter tails than the normal ones, such as Student-t, Pearson VII, power exponential, logistics I and II, and contaminated normal, among others. Such models belong to the general class of statistical models GAMLSS proposed by Rigby and Stasinopoulos (Appl. Stat. 54:507–554, 2005). A back-fitting algorithm to attain the maximum penalized likelihood estimates (MPLEs) by using natural cubic smoothing splines is presented. In particular, the score functions and Fisher information matrices for the parameters of interest are expressed in a similar notation of that used in parametric symmetric models. Sufficient conditions on the existence of the MPLEs are presented as well as some inferential results and discussions on degrees of freedom and smoothing parameter estimation. Diagnostic quantities such as leverage, standardized residual and normal curvatures of local influence under two perturbation schemes are derived. A real data set previously analyzed under normal linear models is reanalyzed under semiparametric additive models with symmetric errors.     

Identification of an equivalent electrical model to a natural circulation BWR core model

In this work the developing of an electrical model of the natural circulation BWR (NCBWR) from analogies between coolant pressures drops, mass flow rates, and electrical voltages and currents, is presented. The electrical model allows estimating the coolant flows in the core, which is complex in NCBWR. The core processes (nuclear-thermo-hydraulics) are modeled with the reduced model where the reactor power is calculated from a point kinetics model with one group of delay neutrons. The reactivity due to Doppler effect, void fraction and control rod was considered. The predictions in steady state were compared with behavior of the power as a function of an ESBWR core flow, showing excellent agreement. The transient behavior considers positive reactivity due to extraction of the control rods.     

Application of linear-extended neutron diffusion equation in a semi-infinite homogeneous medium

The linear-extended neutron diffusion equation (LENDE) is the volume-averaged neutron diffusion equation (VANDE) which includes two correction terms: the first correction is related with the absorption process of the neutron and the second is a contribution to the neutron diffusion, both parameters are related to neutron effects on the interface of a heterogeneous configuration. In this work an analysis of a plane source in a semi-infinite homogeneous medium was considered to study the effects of the correction terms and the results obtained with the linear-extended neutron diffusion equation were compared against a semi-analytical benchmark for the same case. The comparison of the results demonstrate the excellent approach between the linear-extended diffusion theory and the selected benchmark, which means that the correction terms of the VANDE are physically acceptable.     

One-sided tests in generalized linear dose–response models

This paper discusses the asymptotic null distribution of three asymptotically equivalent one-sided tests in generalized linear models with separate lines. Simple forms for the correlation coefficients, which appear in the weights of the asymptotic null distribution, that is a mixture of chi-squared distributions, are given. A particular structure is proposed for the experiments in order to simplify the correlations and consequently to allow the use of several approximations developed for the weights. It is showed that the hypothesis of synergism or antagonism between two compounds may be assessed, under parallelism, by one-sided tests. Finally, as illustration, the efficiency of a standard preparation is compared with the efficiency of four test preparations under a gamma log-linear model.     

Phage Therapy for Crops: Concepts,Experimental and Bioinformatics Approaches to Direct Its Application

Phage therapy consists of applying bacteriophages, whose natural function is to kill specific bacteria. Bacteriophages are safe, evolve together with their host, and are environmentally friendly. At present, the indiscriminate use of antibiotics and salt minerals (Zn²⁺ or Cu²⁺) has caused the emergence of resistant strains that infect crops, causing difficulties and loss of food production. Phage therapy is an alternative that has shown positive results and can improve the treatments available for agriculture. However, the success of phage therapy depends on finding effective bacteriophages. This review focused on describing the potential, up to now, of applying phage therapy as an alternative treatment against bacterial diseases, with sustainable improvement in food production. We described the current isolation techniques, characterization, detection, and selection of lytic phages, highlighting the importance of complementary studies using genome analysis of the phage and its host. Finally, among these studies, we concentrated on the most relevant bacteriophages used for biocontrol of Pseudomonas spp., Xanthomonas spp., Pectobacterium spp., Ralstonia spp., Burkholderia spp., Dickeya spp., Clavibacter michiganensis, and Agrobacterium tumefaciens as agents that cause damage to crops, and affect food production around the world.