Double generalized linear model for tissue culture proportion data: a Bayesian perspective

Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.

The influence of environmental variables on capybara (Hydrochoerus hydrochaeris: Rodentia, Hydrochoeridae) detectability in anthropogenic environments of southeastern Brazil

Capybaras were monitored weekly from 1998 to 2006 by counting individuals in three anthropogenic environments (mixed agricultural fields, forest and open areas) of southeastern Brazil in order to examine the possible influence of environmental variables (temperature, humidity, wind speed, precipitation and global radiation) on the detectability of this species. There was consistent seasonality in the number of capybaras in the study area, with a specific seasonal pattern in each area. Log-linear models were fitted to the sample counts of adult capybaras separately for each sampled area, with an allowance for monthly effects, time trends and the effects of environmental variables. Log-linear models containing effects for the months of the year and a quartic time trend were highly significant. The effects of environmental variables on sample counts were different in each type of environment. As environmental variables affect capybara detectability, they should be considered in future species survey/monitoring programs.

Effects of dietary supplementation of rumen-protected conjugated linoleic acid to grazing cows in early lactation

Conjugated linoleic acids (CLA) are potent anticarcinogens in animal and in vitro models as well as inhibitors of fatty acid synthesis in mammary gland, liver, and adipose tissue. Our objective was to evaluate long-term CLA supplementation of lactating dairy cows in tropical pasture on milk production and composition and residual effects posttreatment. Thirty crossbred cows grazing stargrass (Cynodon nlemfuensis Vanderyst var. nlemfuensis) were blocked by parity and received 150 g/d of a dietary fat supplement of either Ca-salts of palm oil fatty acids (control) or a mixture of Ca-salts of CLA (CLA treatment). Supplements of fatty acids were mixed with 4 kg/d of concentrate. Grazing plus supplements were estimated to provide 115% of the estimated metabolizable protein requirements from 28 to 84 d in milk (treatment period). The CLA supplement provided 15 g/d of cis-9, trans-11 and 22 g of cis-10, trans-12. Residual effects were evaluated from 85 to 112 d in milk (residual period) when cows were fed an 18% crude protein concentrate without added fat. The CLA treatment increased milk production but reduced milk fat concentration from 2.90 to 2.14% and fat production from 437 to 348 g/d. Milk protein concentration increased by 11.5% (2.79 to 3.11%) and production by 19% (422 to 504 g/d) in the cows fed CLA. The CLA treatment decreased milk energy concentration and increased milk volume, resulting in unchanged energy output. Milk production and protein concentration and production were also greater during the residual period for the CLA-treated cows. The CLA treatment reduced production of fatty acids (FA) of all chain lengths, but the larger effect was on short-chain FA, causing a shift toward a greater content of longer chain FA. The CLA treatment increased total milk CLA content by 30% and content of the trans-10, cis-12 CLA isomer by 88%. The CLA treatment tended to decrease the number of days open, suggesting a possible effect on reproduction. Under tropical grazing conditions, in a nutritionally challenging environment, CLA-treated cows decreased milk fat content and secreted the same amount of milk energy by increasing milk volume and milk protein production.

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models

The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.

Random regression models to estimate test-day milk yield genetic parameters Holstein cows in Southeastern Brazil

A total of 152,145 weekly test-day milk yield records from 7317 first lactations of Holstein cows distributed in 93 herds in southeastern Brazil were analyzed. Test-day milk yields were classified into 44 weekly classes of DIM. The contemporary groups were defined as herd-year-week of test-day. The model included direct additive genetic, permanent environmental and residual effects as random and fixed effects of contemporary group and age of cow at calving as covariable, linear and quadratic effects. Mean trends were modeled by a cubic regression on orthogonal polynomials of DIM. Additive genetic and permanent environmental random effects were estimated by random regression on orthogonal Legendre polynomials. Residual variances were modeled using third to seventh-order variance functions or a step function with 1, 6,13,17 and 44 variance classes. Results from Akaike`s and Schwarz`s Bayesian information criterion suggested that a model considering a 7th-order Legendre polynomial for additive effect, a 12th-order polynomial for permanent environment effect and a step function with 6 classes for residual variances, fitted best. However, a parsimonious model, with a 6th-order Legendre polynomial for additive effects and a 7th-order polynomial for permanent environmental effects, yielded very similar genetic parameter estimates. (C) 2008 Elsevier B.V. All rights reserved.

Anti-inflammatory and antinociceptive effects of Baccharis dracunculifolia DC (Asteraceae) in different experimental models

Aim of the study: The aerial parts of Baccharis dracunculifolia D.C., popularly known as ""alecrim do campo"" are used in folk medicine as anti-inflammatory. The aim of the present study was to evaluate the anti-inflammatory and antinociceptive activities of the crude hydroalcoholic extract obtained from leaves of Baccharis dracunculifolia (BdE), which have not been reported. Matetials and methods: BdE was analyzed by HPLC and in vivo evaluated (doses ranging from 50 to 400 mg/kg, p.o.) by using the acetic acid-induced abdominal constrictions, paw oedema induced by carrageenan or histamine, overt nociception models using capsaicin, glutamate or phorbol myristate acetate (PMA), formalin-induced nociception and mechanical hypernociception induced by carrageenan or complete Freund adjuvant (CFA). As positive controls it was used paracetamol in both acetic acid and formalin tests; dipyrone in capsaicin, glutamate and PMA-induced nociception; indomethacin in CFA and carrageenan-induced hypernociception models. In addition, the in vitro effects of BdE on COX-2 activity and on the activation of NF-kappa B were also evaluated. Results: BdE (50-400 mg/kg, p.o.) significantly diminished the abdominal constrictions induced by acetic acid, glutamate and CFA. Furthermore, BdE also inhibited the nociceptive responses in both phases of formalin-induced nociception. BdE, administered orally, also produced a long-lasting anti-hypernociceptive effect in the acute model of inflammatory pain induced by carrageenan. It was also observed the inhibition of COX-2 activity by BdE. Conclusion: In summary, the data reported in this work confirmed the traditional anti-inflammatory indications of Baccharis dracunculifolia leaves and provided biological evidences that Baccharis dracunculifolia, like Brazilian green propolis, possess antinociceptive and anti-inflammatory activities. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

Effects of immunosuppressants on hepatocyte cell mitosis during liver regeneration in growing animal models of partial hepatectomy

Objective. We sought to evaluate the effects of immunosuppressant drugs (corticosteroid, cyclosporine [CsA], and tacrolimus [Tac]) on liver regeneration in growing animals submitted to 70% hepatectomy. Materials and Methods. Newborn and weaning rats were submitted to 70% hepatectomy receiving separately methylprednisolone, CsA, or Tac. All animals were sacrificed 24 hours after the procedure. The remnant liver lobes were subjected to histomorphometric analyses with determination of hepatocyte mitotic index. Results., Administration of immunosuppressants did not change the mitotic index of the regenerating liver in newborn animals. In weaning rats, methylprednisolone reduced the mitotic index (P = .01) and Tac caused a greater increase in this rate (P = .001). CsA had no effect on mitotic index. The number of hepatocyte mitoses in newborn animal livers was greater than that in weaning animal livers (P = .001). Conclusion. In situations in which intense, fast processes of liver regeneration are crucial, the advantages of the use of Tac must be considered, such as in pediatric transplant patients.

EFFECTS OF A POTENT PEROXYNITRITE DECOMPOSITION CATALYST IN MURINE MODELS OF ENDOTOXEMIA AND SEPSIS

Excessive free-radical production due to various bacterial components released during bacterial infection has been linked to cell death and tissue injury. Peroxynitrite is a highly reactive oxidant produced by the combination of nitric oxide (NO) and superoxide anion, which has been implicated in cell death and tissue injury in various forms of critical illness. Pharmacological decomposition of peroxynitrite may represent a potential therapeutic approach in diseases associated with the overproduction of NO and superoxide. In the present study, we tested the effect of a potent peroxynitrite decomposition catalyst in murine models of endotoxemia and sepsis. Mice were injected i.p. with LPS 40 mg/kg with or without FP15 [Fe(III) tetrakis-2-(N-triethylene glycol monomethyl ether) pyridyl porphyrin] (0.1, 0.3, 1, 3, or 10 mg/kg per hour). Mice were killed 12 h later, followed by the harvesting of samples from the lung, liver, and gut for malondialdehyde and myeloperoxidase measurements. In other subsets of animals, blood samples were obtained by cardiac puncture at 1.5, 4, and 8 h after LPS administration for cytokine (TNF-alpha, IL-1 beta, and IL-10), nitrite/nitrate, alanine aminotransferase, and blood urea nitrogen measurements. Endotoxemic animals showed an increase in survival from 25% to 80% at the FP15 doses of 0.3 and 1 mg/kg per hour. The same dose of FP15 had no effect on plasma levels of nitrite/nitrate. There was a reduction in liver and lung malondialdehyde in the endotoxemic animals pretreated with FP15, as well as in hepatic myeloperoxidase and biochemical markers of liver and kidney damage (alanine aminotransferase and blood urea nitrogen). In a bacterial model of sepsis induced by cecal ligation and puncture, FP15 treatment (0.3 mg/kg per day) significantly protected against mortality. The current data support the view that peroxynitrite is a critical factor mediating liver, gut, and lung injury in endotoxemia and septic shock: its pharmacological neutralization may be of therapeutic benefit.

Anti-aversive effects of the atypical antipsychotic, aripiprazole, in animal models of anxiety

Aripiprazole is a unique antipsychotic that seems to act as a partial agonist at dopamine D2-receptors, contrasting with other drugs in this class, which are silent antagonists. Aripiprazole may also bind to serotonin receptors. Both neurotransmitters may play major roles in aversion-, anxiety-and panic-related behaviours. Thus, the present work tested the hypothesis that this antipsychotic could also have anti-aversive properties. Male Wistar rats received injections of aripiprazole (0.1-10 mg/kg) and were tested in the open field, in the elevated plus and T mazes (EPM and ETM, respectively) and in a contextual fear conditioning paradigm. Aripiprazole (1mg/kg) increased the percentage of entries onto the open arms of the EPM and attenuated escape responses in the ETM. In the latter model, the dose of 0.1 mg/kg also decreased the latency to leave the enclosed arm, suggesting anxiolytic- and panicolytic-like properties. This dose also decreased the time spent in freezing in a contextual fear conditioning. No significant motor effects were observed at these doses. The present data support the hypothesis that aripiprazole could inhibit anxiety-related responses. Acting as a partial agonist at dopamine receptors, this drug could effectively treat schizophrenia and, in contrast with most antipsychotic drugs, alleviate aversive states.

Nitric oxide-mediated anxiolytic-like and antidepressant-like effects in animal models of anxiety and depression

The effects of microinjection of the nitric oxide (NO) precursor L-arginine (L-Arg), the NO synthase (NOS) inhibitors N-methyl-L-arginine (L-NAME) and 7-nitroindazole (7-NI), and the cyclic guanosine 3`,5`-monophosphate (cGMP) analog 8-Br-cGMP into the dorsal raphe nucleus (DRN) were assessed in rats using the elevated plus maze (EPM) and the forced swim test (FST). L-Arg (100 and 200 nmol) produced an anxiolytic-like effect in the EPM. 8-Br-cGMP (25 and 50 nmol) dose-dependently increased locomotor activity. In the FST, antidepressant-like effects were produced by L-Arg (50 and 100 nmol) and 8-Br-cGMP (12.5 and 25 nmol). Dual effects were observed with NOS inhibitors L-NAME and 7-NI in both the EPM and FST. While low doses of L-NAME (25 nmol) or 7-NI (1 nmol) induced a selective increase in EPM open arm exploration and a decrease in immobility time in the FST, high doses (L-NAME 400 nmol, 7-NI 10 nmol) decreased locomotor activity. These results show that interference with NO-mediated neurotransmission in the DRN induced significant and complex motor and emotional effects. Further studies are needed to elucidate the mechanisms involved in these effects. (C) 2007 Elsevier Inc. All rights reserved.

Long-term effects of rapid maxillary expansion on nasal area and nasal airway resistance

Background: Rapid maxillary expansion (RME) may improve the nasal respiratory pattern This study was performed to evaluate the effect of RME on the nasal cavity by acoustic rhinometry and computed rhinomanometry and to determine nasal and maxillary width by posteroanterior cephalometric radiography, up to 30 months after the orthodontic procedure Methods: Twenty-seven children with oral breathing, ranging in age from 7 to 70 years, and with mixed dentition were selected The children had unior bilateral posterior crossbite involving deciduous canines and the first permanent molars All subjects were submitted to nasofibroscopy, acoustic rhinometry, and computed rhinomanometry and posteroanterior cephalometric radiography at four different tunes, i e, before expansion, immediately, 90 days and 30 months after expansion Results: The mean linear left-to-right nasal cavity lateral prominence and left-to-right jugal ponds cephalometric measures increased considerably after expansion and this increase was maintained throughout the period of evaluation There was an immediate significant decrease in nasal resistance, up to 90 days after RME, but the nasal resistance increased 30 months after the procedure The acoustic rhinometry results did not show any difference in values throughout time Conclusion: RME significantly increased nasal and maxillary width as measured by frontal cephalometry, but the nasal mucosal effects were more subtle Also, the influence of RME on nasal resistance was not stable, and nasal resistance values returned to close to the initial ones after 30 months (Am J Rhinol Allergy 24, 161-165, 2010, doi 10.2500/ajra.2010.24.3440)

THE ROLE OF DIFFUSIVITY QUENCHING IN FLUX-TRANSPORT DYNAMO MODELS

In the nonlinear phase of a dynamo process, the back-reaction of the magnetic field upon the turbulent motion results in a decrease of the turbulence level and therefore in a suppression of both the magnetic field amplification (the alpha-quenching effect) and the turbulent magnetic diffusivity (the eta-quenching effect). While the former has been widely explored, the effects of eta-quenching in the magnetic field evolution have rarely been considered. In this work, we investigate the role of the suppression of diffusivity in a flux-transport solar dynamo model that also includes a nonlinear alpha-quenching term. Our results indicate that, although for alpha-quenching the dependence of the magnetic field amplification with the quenching factor is nearly linear, the magnetic field response to eta-quenching is nonlinear and spatially nonuniform. We have found that the magnetic field can be locally amplified in this case, forming long-lived structures whose maximum amplitude can be up to similar to 2.5 times larger at the tachocline and up to similar to 2 times larger at the center of the convection zone than in models without quenching. However, this amplification leads to unobservable effects and to a worse distribution of the magnetic field in the butterfly diagram. Since the dynamo cycle period increases when the efficiency of the quenching increases, we have also explored whether the eta-quenching can cause a diffusion-dominated model to drift into an advection-dominated regime. We have found that models undergoing a large suppression in eta produce a strong segregation of magnetic fields that may lead to unsteady dynamo-oscillations. On the other hand, an initially diffusion-dominated model undergoing a small suppression in eta remains in the diffusion-dominated regime.

Mitochondrial sequence data and Dipsacales phylogeny: Mixed models, partitioned Bayesian analyses, and model selection

Phylogenetic analyses of chloroplast DNA sequences, morphology, and combined data have provided consistent support for many of the major branches within the angiosperm, clade Dipsacales. Here we use sequences from three mitochondrial loci to test the existing broad scale phylogeny and in an attempt to resolve several relationships that have remained uncertain. Parsimony, maximum likelihood, and Bayesian analyses of a combined mitochondrial data set recover trees broadly consistent with previous studies, although resolution and support are lower than in the largest chloroplast analyses. Combining chloroplast and mitochondrial data results in a generally well-resolved and very strongly supported topology but the previously recognized problem areas remain. To investigate why these relationships have been difficult to resolve we conducted a series of experiments using different data partitions and heterogeneous substitution models. Usually more complex modeling schemes are favored regardless of the partitions recognized but model choice had little effect on topology or support values. In contrast there are consistent but weakly supported differences in the topologies recovered from coding and non-coding matrices. These conflicts directly correspond to relationships that were poorly resolved in analyses of the full combined chloroplast-mitochondrial data set. We suggest incongruent signal has contributed to our inability to confidently resolve these problem areas. (c) 2007 Elsevier Inc. All rights reserved.

Transformed generalized linear models

The estimation of data transformation is very useful to yield response variables satisfying closely a normal linear model, Generalized linear models enable the fitting of models to a wide range of data types. These models are based on exponential dispersion models. We propose a new class of transformed generalized linear models to extend the Box and Cox models and the generalized linear models. We use the generalized linear model framework to fit these models and discuss maximum likelihood estimation and inference. We give a simple formula to estimate the parameter that index the transformation of the response variable for a subclass of models. We also give a simple formula to estimate the rth moment of the original dependent variable. We explore the possibility of using these models to time series data to extend the generalized autoregressive moving average models discussed by Benjamin er al. [Generalized autoregressive moving average models. J. Amer. Statist. Assoc. 98, 214-223]. The usefulness of these models is illustrated in a Simulation study and in applications to three real data sets. (C) 2009 Elsevier B.V. All rights reserved.

Improved score tests in symmetric linear regression models

The class of symmetric linear regression models has the normal linear regression model as a special case and includes several models that assume that the errors follow a symmetric distribution with longer-than-normal tails. An important member of this class is the t linear regression model, which is commonly used as an alternative to the usual normal regression model when the data contain extreme or outlying observations. In this article, we develop second-order asymptotic theory for score tests in this class of models. We obtain Bartlett-corrected score statistics for testing hypotheses on the regression and the dispersion parameters. The corrected statistics have chi-squared distributions with errors of order O(n(-3/2)), n being the sample size. The corrections represent an improvement over the corresponding original Rao`s score statistics, which are chi-squared distributed up to errors of order O(n(-1)). Simulation results show that the corrected score tests perform much better than their uncorrected counterparts in samples of small or moderate size.