Generalized linear models with random effects; salamander mating revisited.

In recent years much effort has been devoted to extending regression methodology to non-Gaussian data, where responses are not independent. These methods for dependent responses are suitable for data from longitudinal studies or nested designs. However, use of these methods for crossed designs seems to have serious limitations due to the intensive computations involved because of the intractable nature of the joint distribution. In this paper, we cast the problem in a Bayesian framework and use a Monte Carlo method, the Gibbs sampler, to avoid current computational limitations. The flexibility of this approach is illustrated by analyzing the interesting salamander mating data reported by McCullagh and Nelder (1989, Generalized Linear Models, 2nd edition, London: Chapman and Hall).     

Prosimian juvenile mortality in zoos and primate centers

I review literature on juvenile mortality of captive prosimians in order to evaluate the available information on captive breeding. Juvenile mortality includes abortion, premature mortality, stillbirth, and death of the unweaned young. Prosimian juvenile mortality ranges between 25 and 45% in captive populations. It is generally lower in the Lemuroidea, particularly the Cheirogaleidae, than in the Lorisoidea. Mortality is particularly high in the Lorisinae. Most mortality, including a high stillbirth rate, occurs on the first day and during the first 10 days thereafter. Stress, maternal neglect and traumatic insults, not infrequently linked to each other, are the most frequently reported causes of death. The percentage of congenital malformations tends to be high in some colonies. Sex of the infant and parity seem to be important risk factors for juvenile mortality, whereas litter size does not appear to be important. Based on few data, wild- caught females appear to have higher breeding success than those born in captivity. Synchronized births in lemuroids and isolated births in Galagoare more likely to result in successfully weaned infants.     

Virus evolution reveals an exclusive role for LEDGF/p75 in chromosomal tethering of HIV

Retroviruses by definition insert their viral genome into the host cell chromosome. Although the key player of retroviral integration is viral integrase, a role for cellular cofactors has been proposed. Lentiviral integrases use the cellular protein LEDGF/p75 to tether the preintegration complex to the chromosome, although the existence of alternative host proteins substituting for the function of LEDGF/p75 in integration has been proposed. Truncation mutants of LEDGF/p75 lacking the chromosome attachment site strongly inhibit HIV replication by competition for the interaction with integrase. In an attempt to select HIV strains that can overcome the inhibition, we now have used T-cell lines that stably express a C-terminal fragment of LEDGF/p75. Despite resistance development, the affinity of integrase for LEDGF/p75 is reduced and replication kinetics in human primary T cells is impaired. Detection of the integrase mutations A128T and E170G at key positions in the LEDGF/p75-integrase interface provides in vivo evidence for previously reported crystallographic data. Moreover, the complementary inhibition by LEDGF/p75 knockdown and mutagenesis at the integrase-LEDGF/p75 interface points to the incapability of HIV to circumvent LEDGF/p75 function during proviral integration. Altogether, the data provide a striking example of the power of viral molecular evolution. The results underline the importance of the LEDGF/p75 HIV-1 interplay as target for innovative antiviral therapy. Moreover, the role of LEDGF/p75 in targeting integration will stimulate research on strategies to direct gene therapy vectors into safe landing sites.     

Functional proteome analysis of the banana plant (Musa spp.) using de novo sequence analysis of derivatized peptides

We report the use of chemical derivatization with MALDI-MS/MS analysis for de novo sequence analysis. Using three frequently used homology-based search algorithms, we were able to identify more than 40 proteins from banana, a nonmodel plant with unsequenced genome. Furthermore, this approach allowed the identification of different isoforms. We also observed that the identification score obtained varied according to the position of the peptide sequences in the query using the MS-Blast algorithm.     

Development of resistance against diketo derivatives of human immunodeficiency virus type 1 by progressive accumulation of integrase mutations

The diketo acid L-708,906 has been reported to be a selective inhibitor of the strand transfer step of the human immunodeficiency virus type 1 (HIV-1) integration process (D. Hazuda, P. Felock, M. Witmer, A. Wolfe, K. Stillmock, J. A. Grobler, A. Espeseth, L. Gabryelski, W. Schleif, C. Blau, and M. D. Miller, Science 287:646-650, 2000). We have now studied the development of antiviral resistance to L-708,906 by growing HIV-1 strains in the presence of increasing concentrations of the compound. The mutations T66I, L74M, and S230R emerged successively in the integrase gene. The virus with three mutations (T66I L74M S230R) was 10-fold less susceptible to L-708,906, while displaying the sensitivity of the wild-type virus to inhibitors of the RT or PRO or viral entry process. Chimeric HIV-1 strains containing the mutant integrase genes displayed the same resistance profile as the in vitro-selected strains, corroborating the impact of the reported mutations on the resistance phenotype. Phenotypic cross-resistance to S-1360, a diketo analogue in clinical trials, was observed for all strains. Interestingly, the diketo acid-resistant strain remained fully sensitive to V-165, a novel integrase inhibitor (C. Pannecouque, W. Pluymers, B. Van Maele, V. Tetz, P. Cherepanov, E. De Clercq, M. Witvrouw, and Z. Debyser, Curr. Biol. 12:1169-1177, 2002). Antiviral resistance was also studied at the level of recombinant integrase. Single mutations did not appear to impair specific enzymatic activity. However, 3' processing and strand transfer activities of the recombinant integrases with two (T66I L74M) and three (T66I L74M S230R) mutations were notably lower than those of the wild-type integrase. Although the virus with three mutations was resistant to inhibition by diketo acids, the sensitivity of the corresponding enzyme to L-708,906 or S-1360 was reduced only two- to threefold. As to the replication kinetics of the selected strains, the replication fitness for all strains was lower than that of the wild-type HIV-1 strain.     

HIV-1 integrase forms stable tetramers and associates with LEDGF/p75 protein in human cells

We studied human immunodeficiency virus, type 1 (HIV-1) integrase (IN) complexes derived from nuclei of human cells stably expressing the viral protein from a synthetic gene. We show that in the nuclear extracts IN exists as part of a large distinct complex with an apparent Stokes radius of 61 A, which dissociates upon dilution yielding a core molecule of 41 A. We isolated the IN complexes from cells expressing FLAG-tagged IN and demonstrated that the 41 A core is a tetramer of IN, whereas 61 A molecules are composed of IN tetramers associated with a cellular protein with an apparent molecular mass of 76 kDa. This novel integrase interacting protein was found to be identical to lens epithelium-derived growth factor (LEDGF/p75), a protein implicated in regulation of gene expression and cellular stress response. HIV-1 IN and LEDGF co-localized in the nuclei of human cells stably expressing IN. Furthermore, recombinant LEDGF robustly enhanced strand transfer activity of HIV-1 IN in vitro. Our findings indicate that the minimal IN molecule in human cells is a homotetramer, suggesting that at least an octamer of IN is required to accomplish coordinated integration of both retroviral long terminal repeats and that LEDGF is a cellular factor involved in this process.     

Local mean normalization of microarray element signal intensities across an array surface: quality control and correction of spatially systematic artifacts

Here we present a methodology for the normalization of element signal intensities to a mean intensity calculated locally across the surface of a DNA microarray. These methods allow the detection and/or correction of spatially systematic artifacts in microarray data. These include artifacts that can be introduced during the robotic printing, hybridization, washing, or imaging of microarrays. Using array element signal intensities alone, this local mean normalization process can correct for such artifacts because they vary across the surface of the array. The local mean normalization can be usedfor quality control and data correction purposes in the analysis of microarray data. These algorithms assume that array elements are not spatially ordered with regard to sequence or biological function and require that this spatial mapping is identical between the two sets of intensities to be compared. The tool described in this report was developed in the R statistical language and is freely available on the Internet as part of a larger gene expression analysis package. This Web implementation is interactive and user-friendly and allows the easy use of the local mean normalization tool described here, without programming expertise or downloading of additional software.     

Latent class model diagnosis

In many areas of medical research, such as psychiatry and gerontology, latent class variables are used to classify individuals into disease categories, often with the intention of hierarchical modeling. Problems arise when it is not clear how many disease classes are appropriate, creating a need for model selection and diagnostic techniques. Previous work has shown that the Pearson chi 2 statistic and the log-likelihood ratio G2 statistic are not valid test statistics for evaluating latent class models. Other methods, such as information criteria, provide decision rules without providing explicit information about where discrepancies occur between a model and the data. Identifiability issues further complicate these problems. This paper develops procedures for assessing Markov chain Monte Carlo convergence and model diagnosis and for selecting the number of categories for the latent variable based on evidence in the data using Markov chain Monte Carlo techniques. Simulations and a psychiatric example are presented to demonstrate the effective use of these methods.