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. (C) 2010 Elsevier B.V. All rights reserved.

General results for the beta-modified Weibull distribution

We study in detail the so-called beta-modified Weibull distribution, motivated by the wide use of the Weibull distribution in practice, and also for the fact that the generalization provides a continuous crossover towards cases with different shapes. The new distribution is important since it contains as special sub-models some widely-known distributions, such as the generalized modified Weibull, beta Weibull, exponentiated Weibull, beta exponential, modified Weibull and Weibull distributions, among several others. It also provides more flexibility to analyse complex real data. Various mathematical properties of this distribution are derived, including its moments and moment generating function. We examine the asymptotic distributions of the extreme values. Explicit expressions are also derived for the chf, mean deviations, Bonferroni and Lorenz curves, reliability and entropies. The estimation of parameters is approached by two methods: moments and maximum likelihood. We compare by simulation the performances of the estimates from these methods. We obtain the expected information matrix. Two applications are presented to illustrate the proposed distribution.

The exponentiated generalized gamma distribution with application to lifetime data

A four-parameter extension of the generalized gamma distribution capable of modelling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone and non-monotone failure rate functions, which are quite common in lifetime data analysis and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the exponentiated Weibull, exponentiated generalized half-normal, exponentiated gamma and generalized Rayleigh, among others. We derive two infinite sum representations for its moments. We calculate the density of the order statistics and two expansions for their moments. The method of maximum likelihood is used for estimating the model parameters and the observed information matrix is obtained. Finally, a real data set from the medical area is analysed.

3D-Pharmacophore mapping of thymidine-based inhibitors of TMPK as potential antituberculosis agents

Tuberculosis (TB) is the primary cause of mortality among infectious diseases. Mycobacterium tuberculosis monophosphate kinase (TMPKmt) is essential to DNA replication. Thus, this enzyme represents a promising target for developing new drugs against TB. In the present study, the receptor-independent, RI, 4D-QSAR method has been used to develop QSAR models and corresponding 3D-pharmacophores for a set of 81 thymidine analogues, and two corresponding subsets, reported as inhibitors of TMPKmt. The resulting optimized models are not only statistically significant with r (2) ranging from 0.83 to 0.92 and q (2) from 0.78 to 0.88, but also are robustly predictive based on test set predictions. The most and the least potent inhibitors in their respective postulated active conformations, derived from each of the models, were docked in the active site of the TMPKmt crystal structure. There is a solid consistency between the 3D-pharmacophore sites defined by the QSAR models and interactions with binding site residues. Moreover, the QSAR models provide insights regarding a probable mechanism of action of the analogues.

Rational Design and 3D-Pharmacophore Mapping of 5 `-Thiourea-Substituted alpha-Thymidine Analogues as Mycobacterial TMPK Inhibitors

Thymidine monophosphate kinase (TMPK) has emerged as an attractive target for developing inhibitors of Mycobacterium tuberculosis growth. In this study the receptor-independent (RI) 4D-QSAR formalism has been used to develop QSAR models and corresponding 3D-pharmacophores for a set of 5`-thiourea-substituted alpha-thymidine inhibitors. Models were developed for the entire training set and for a subset of the training set consisting of the most potent inhibitors. The optimized (RI) 4D-QSAR models are statistically significant (r(2) = 0.90, q(2) = 0.83 entire set, r(2) = 0.86, q(2) = 0.80 high potency subset) and also possess good predictivity based on test set predictions. The most and least potent inhibitors, in their respective postulated active conformations derived from the models, were docked in the active site of the TMPK crystallographic structure. There is a solid consistency between the 3D-pharmacophore sites defined by the QSAR models and interactions with binding site residues. This model identifies new regions of the inhibitors that contain pharmacophore sites, such as the sugar-pyrimidine ring structure and the region of the 5`-arylthiourea moiety. These new regions of the ligands can be further explored and possibly exploited to identify new, novel, and, perhaps, better antituberculosis inhibitors of TMPKmt. Furthermore, the 3D-pharmacophores defined by these models can be used as a starting point for future receptor-dependent antituberculosis drug design as well as to elucidate candidate sites for substituent addition to optimize ADMET properties of analog inhibitors.

Molecular modeling and QSAR studies of a set of indole and benzimidazole derivatives as H(4) receptor antagonists

Histamine is an important biogenic amine, which acts with a group of four G-protein coupled receptors (GPCRs), namely H(1) to H(4) (H(1)R - H(4)R) receptors. The actions of histamine at H(4)R are related to immunological and inflammatory processes, particularly in pathophysiology of asthma, and H(4)R ligands having antagonistic properties could be helpful as antiinflammatory agents. In this work, molecular modeling and QSAR studies of a set of 30 compounds, indole and benzimidazole derivatives, as H(4)R antagonists were performed. The QSAR models were built and optimized using a genetic algorithm function and partial least squares regression (WOLF 5.5 program). The best QSAR model constructed with training set (N = 25) presented the following statistical measures: r (2) = 0.76, q (2) = 0.62, LOF = 0.15, and LSE = 0.07, and was validated using the LNO and y-randomization techniques. Four of five compounds of test set were well predicted by the selected QSAR model, which presented an external prediction power of 80%. These findings can be quite useful to aid the designing of new anti-H(4) compounds with improved biological response.

Generation and Analysis of Interaction Energy Maps of p-Substituted Benzoic Acid [(5-Nitro-thiophen-2-yl)-methylene]-Hydrazides Active against MRSA

In this preliminary study eighteen p-substituted benzoic acid [(5-nitro-thiophen-2-yl)-methylene]-hydrazides with antimicrobial activity were evaluated against multidrug-resistant Staphylococcus aureus, correlating the three-dimensional characteristics of the ligands with their respective bioactivities. The computer programs Sybyl and CORINA were used, respectively, for the design and three-dimensional conversion of the ligands. Molecular interaction fields were calculated using GRID program. Calculations using Volsurf resulted in a statistically consistent model with 48 structural descriptors showing that hydrophobicity is a fundamental property in the analyzed biological response.

Multilabeled classification approach to find a plaint source for terpenoids

Recently, we have built a classification model that is capable of assigning a given sesquiterpene lactone (STL) into exactly one tribe of the plant family Asteraceae from which the STL has been isolated. Although many plant species are able to biosynthesize a set of peculiar compounds, the occurrence of the same secondary metabolites in more than one tribe of Asteraceae is frequent. Building on our previous work, in this paper, we explore the possibility of assigning an STL to more than one tribe (class) simultaneously. When an object may belong to more than one class simultaneously, it is called multilabeled. In this work, we present a general overview of the techniques available to examine multilabeled data. The problem of evaluating the performance of a multilabeled classifier is discussed. Two particular multilabeled classification methods-cross-training with support vector machines (ct-SVM) and multilabeled k-nearest neighbors (M-L-kNN)were applied to the classification of the STLs into seven tribes from the plant family Asteraceae. The results are compared to a single-label classification and are analyzed from a chemotaxonomic point of view. The multilabeled approach allowed us to (1) model the reality as closely as possible, (2) improve our understanding of the relationship between the secondary metabolite profiles of different Asteraceae tribes, and (3) significantly decrease the number of plant sources to be considered for finding a certain STL. The presented classification models are useful for the targeted collection of plants with the objective of finding plant sources of natural compounds that are biologically active or possess other specific properties of interest.

Computer-aided drug design and ADMET predictions for identification and evaluation of novel potential farnesyltransferase inhibitors in cancer therapy

We have used various computational methodologies including molecular dynamics, density functional theory, virtual screening, ADMET predictions and molecular interaction field studies to design and analyze four novel potential inhibitors of farnesyltransferase (FTase). Evaluation of two proposals regarding their drug potential as well as lead compounds have indicated them as novel promising FTase inhibitors, with theoretically interesting pharmacotherapeutic profiles, when Compared to the very active and most cited FTase inhibitors that have activity data reported, which are launched drugs or compounds in clinical tests. One of our two proposals appears to be a more promising drug candidate and FTase inhibitor, but both derivative molecules indicate potentially very good pharmacotherapeutic profiles in comparison with Tipifarnib and Lonafarnib, two reference pharmaceuticals. Two other proposals have been selected with virtual screening approaches and investigated by LIS, which suggest novel and alternatives scaffolds to design future potential FTase inhibitors. Such compounds can be explored as promising molecules to initiate a research protocol in order to discover novel anticancer drug candidates targeting farnesyltransferase, in the fight against cancer. (C) 2009 Elsevier Inc. All rights reserved.

Quantum-chemical, NMR and X-ray diffraction studies on (+/-)-1-[3,4-(methylenedioxy)phenyl]-2-methylaminopropane

Time-averaged conformations of (+/-)-1-[3,4-(methylenedioxy)phenyl]-2-methylaminopropane hydrochloride (MDMA, ""ecstasy"") in D(2)O, and of its free base and trifluoroacetate in CDCl(3), were deduced from their (1)H NMR spectra and used to calculate their conformer distribution. Their rotational potential energy surface (PES) was calculated at the RHF/6-31G(d,p), 133LYP/6-31G(d,p), B3LYP/cc-pVDZ and AM1 levels. Solvent effects were evaluated using the polarizable continuum model. The NMR and theoretical studies showed that, in the free base, the N-methyl group and the ring are preferentially trans. This preference is stronger in the salts and corresponds to the X-ray structure of the hydrochloride. However, the energy barriers separating these forms are very low. The X-ray diffraction crystal structures of the anhydrous salt and its monohydrate differed mainly in the trans or cis relationship of the N-methyl group to the a-methyl, although these two forms interconvert freely in solution. (C) 2007 Elsevier Inc. All rights reserved.

Brazil

Brazil has led development of collective rights in Ibero-American states and has developed from consumer origins a general procedure on ""public civil actions"" largely brought by the attorney general. These have a two-stage process, involving a declaration on general liability followed by individuals bringing personal compensation claims.

Thermal Cycling Stability of Silica Membranes for Gas Separation

Hydrogen is being seen as an alternative energy carrier to conventional hydrocarbons to reduce greenhouse gas emissions. High efficiency separation technologies to remove hydrogen from the greenhouse gas, carbon dioxide, are therefore in growing demand. Traditional thermodynamic separation systems utilise distillation, absorption and adsorption, but are limited in efficiency at compact scales. Molecular sieve silica (MSS) membranes can perform this separation as they have high permselectivity of hydrogen to carbon dioxide, but their stability under thermal cycling is not well reported. In this work we exposed a standard MSS membrane and a carbonised template MSS (CTMSS) membrane to thermal cycling from 100 to 450°C. The standard MSS and carbonised template CTMSS membranes both showed permselectivity of helium to nitrogen dropping from around 10 to 6 in the first set of cycles, remaining stable until the last test. The permselectivity drop was due to small micropore collapse, which occurred via structure movement during cycling. Simulating single stage membrane separation with a 50:50 molar feed of H2:CO2, H2 exiting the permeate stream would start at 79% and stabilise at 67%. Higher selectivity membranes showed less of a purity drop, indicating the margin at which to design a stable membrane separation unit for CO2 capture.

Functionalisation of nanoparticles as electrolytes in fuel cells

Inorganic metal oxide materials are generally poor proton conductors as conductivities are lower than 10-5-10-6 S.cm-1. However, by functionalising Silica, Zirconia or Titania, proton conduction increases by up to 5 orders of magnitude. Hence, functionalised nanomaterials are becoming very competitive against conventional electrolyte materials such as Nafion. In this work, sol-gel processes are employed to produce silica phosphate, zirconia phosphate and titania phosphate functionalised nanoparticles. Furthermore, conductivities at hydrate conditions are investigated, and nanoparticle formation and functionalisation effects on proton conductivity are discussed. Results show conductivities up to 10-1 S.cm-1 (95% RH). Proton conduction increases with the functionalisation content, however heat treatment of nanoparticles locks the functionality in the crystal phase, thus inhibiting proton conduction. Controlling the mesopore phase allows for high proton conduction at hydrated conditions, clearly indicating facilitated ion transport through the pore channels.

Nanocomposite Nafion-Silica membranes for direct methanol fuel cells

Commercially available proton exchange membranes such as Nafion do not meet the requirements for high power density direct methanol fuel cells, partly due to their high methanol permeability. The aim of this work is to develop a new class of high-proton conductivity membranes, with thermal and mechanical stability similar to Nafion and reduced methanol permeability. Nanocomposite membranes were produced by the in-situ sol-gel synthesis of silicon dioxide particles in preformed Nafion membranes. Microstructural modification of Nafion membranes with silica nanoparticles was shown in this work to reduce methanol crossover from 7.48x10-6 cm2s^-1 for pure Nafion® to 2.86 x10-6 cm2s^-1 for nanocomposite nafion membranes (Methanol 50% (v/v) solution, 75 degrees C). Best results were achieved with a silica composition of 2.6% (w/w). We propose that silica inhibits the conduction of methanol through Nafion by blocking sites necessary for methanol diffusion through the polymer electrolyte membrane. Effects of surface chemistry, nanoparticle formation and interactions with Nafion matrix are further addressed.

Air Entrainment Processes in a Full-Scale Rectangular Dropshaft at Large Flows

Rectangular dropshafts, commonly used in sewers and storm water systems, are characterised by significant flow aeration. New detailed air-water flow measurements were conducted in a near-full-scale dropshaft at large discharges. In the shaft pool and outflow channel, the results demonstrated the complexity of different competitive air entrainment mechanisms. Bubble size measurements showed a broad range of entrained bubble sizes. Analysis of streamwise distributions of bubbles suggested further some clustering process in the bubbly flow although, in the outflow channel, bubble chords were in average smaller than in the shaft pool. A robust hydrophone was tested to measure bubble acoustic spectra and to assess its field application potential. The acoustic results characterised accurately the order of magnitude of entrained bubble sizes, but the transformation from acoustic frequencies to bubble radii did not predict correctly the probability distribution functions of bubble sizes.