Effects of uremic solutes on reactive oxygen species in vitro model systems as a possibility of support the renal function management

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The use of artificial neural networks in analysing the nutritional ecology of Chrysomya megacephala (F.) (Diptera: Calliphoridae), compared with a statistical model

Artificial neural networks (ANNs) have been widely applied to the resolution of complex biological problems. An important feature of neural models is that their implementation is not precluded by the theoretical distribution shape of the data used. Frequently, the performance of ANNs over linear or non-linear regression-based statistical methods is deemed to be significantly superior if suitable sample sizes are provided, especially in multidimensional and non-linear processes. The current work was aimed at utilising three well-known neural network methods in order to evaluate whether these models would be able to provide more accurate outcomes in relation to a conventional regression method in pupal weight predictions of Chrysomya megacephala, a species of blowfly (Diptera: Calliphoridae), using larval density (i.e. the initial number of larvae), amount of available food and pupal size as input data. It was possible to notice that the neural networks yielded more accurate performances in comparison with the statistical model (multiple regression). Assessing the three types of networks utilised (Multi-layer Perceptron, Radial Basis Function and Generalised Regression Neural Network), no considerable differences between these models were detected. The superiority of these neural models over a classical statistical method represents an important fact, because more accurate models may clarify several intricate aspects concerning the nutritional ecology of blowflies.

Study of using marker assisted selection on a beef cattle breeding program by model comparison

A data set of a commercial Nellore beef cattle selection program was used to compare breeding models that assumed or not markers effects to estimate the breeding values, when a reduced number of animals have phenotypic, genotypic and pedigree information available. This herd complete data set was composed of 83,404 animals measured for weaning weight (WW), post-weaning gain (PWG), scrotal circumference (SC) and muscle score (MS), corresponding to 116,652 animals in the relationship matrix. Single trait analyses were performed by MTDFREML software to estimate fixed and random effects solutions using this complete data. The additive effects estimated were assumed as the reference breeding values for those animals. The individual observed phenotype of each trait was adjusted for fixed and random effects solutions, except for direct additive effects. The adjusted phenotype composed of the additive and residual parts of observed phenotype was used as dependent variable for models' comparison. Among all measured animals of this herd, only 3160 animals were genotyped for 106 SNP markers. Three models were compared in terms of changes on animals' rank, global fit and predictive ability. Model 1 included only polygenic effects, model 2 included only markers effects and model 3 included both polygenic and markers effects. Bayesian inference via Markov chain Monte Carlo methods performed by TM software was used to analyze the data for model comparison. Two different priors were adopted for markers effects in models 2 and 3, the first prior assumed was a uniform distribution (U) and, as a second prior, was assumed that markers effects were distributed as normal (N). Higher rank correlation coefficients were observed for models 3_U and 3_N, indicating a greater similarity of these models animals' rank and the rank based on the reference breeding values. Model 3_N presented a better global fit, as demonstrated by its low DIC. The best models in terms of predictive ability were models 1 and 3_N. Differences due prior assumed to markers effects in models 2 and 3 could be attributed to the better ability of normal prior in handle with collinear effects. The models 2_U and 2_N presented the worst performance, indicating that this small set of markers should not be used to genetically evaluate animals with no data, since its predictive ability is restricted. In conclusion, model 3_N presented a slight superiority when a reduce number of animals have phenotypic, genotypic and pedigree information. It could be attributed to the variation retained by markers and polygenic effects assumed together and the normal prior assumed to markers effects, that deals better with the collinearity between markers. (C) 2012 Elsevier B.V. All rights reserved.

Estimation methods of non-additive effects for characteristics of weight and scrotal circumference in crossbred beef cattle

The objective of this study was to investigate, in a population of crossbred cattle, the obtainment of the non-additive genetic effects for the characteristics weight at 205 and 390 days and scrotal circumference, and to evaluate the consideration of these effects in the prediction of breeding values of sires using different estimation methodologies. In method 1, the data were pre-adjusted for the non-additive effects obtained by least squares means method in a model that considered the direct additive, maternal and non-additive fixed genetic effects, the direct and total maternal heterozygosities, and epistasis. In method 2, the non-additive effects were considered covariates in genetic model. Genetic values for adjusted and non-adjusted data were predicted considering additive direct and maternal effects, and for weight at 205 days, also the permanent environmental effect, as random effects in the model. The breeding values of the categories of sires considered for the weight characteristic at 205 days were organized in files, in order to verify alterations in the magnitude of the predictions and ranking of animals in the two methods of correction data for the non-additives effects. The non-additive effects were not similar in magnitude and direction in the two estimation methods used, nor for the characteristics evaluated. Pearson and Spearman correlations between breeding values were higher than 0.94, and the use of different methods does not imply changes in the selection of animals.

Thermodynamics of Ising model with infinite-range interactions by generalized canonical ensemble

In this work we present the idea of how generalized ensembles can be used to simplify the operational study of non-additive physical systems. As alternative of the usual methods of direct integration or mean-field theory, we show how the solution of the Ising model with infinite-range interactions is obtained by using a generalized canonical ensemble. We describe how the thermodynamical properties of this model in the presence of an external magnetic field are founded by simple parametric equations. Without impairing the usual interpretation, we obtain an identical critical behaviour as observed in traditional approaches.

Are Multiple Cryoprobes Additive or Synergistic in Renal Cryotherapy?

OBJECTIVE To investigate the relationship between multiple cryoprobes was investigated to determine whether they work in an additive or synergistic fashion in an in vivo animal model because 1.47 mm (17-gauge) cryoprobes have been introduced to the armamentarium for renal cryotherapy. METHODS Laparoscopic-guided percutaneous cryoablation was performed in both renal poles of 3 pigs using 3 IceRod cryoprobes. These 12 cryolesions were compared with 12 cryolesions using a single IceRod cryoprobe. Each cycle consisted of two 10-minute freeze cycles separated by a 5-minute thaw. The iceball volume was measured using intraoperative ultrasonography. The kidneys were harvested, and cryolesion surface area was calculated. The lesions were fixed and excised to obtain a volume measurement. Statistical analysis was used to compare the single probe results multiplied by 3 to the multiple probe group for iceball volume, cryolesion surface area, and cryolesion volume. RESULTS The iceball volume for the first freeze cycle for the single cryoprobe multiplied by 3 was 8.55 cm(3) compared with 9.79 cm(3) for the multiple cryoprobe group (P = .44) and 10.01 cm(3) versus 16.58 cm(3) for the second freeze (P = .03). The cryolesion volume for the single cryoprobe multiplied by 3 was 11.29 cm(3) versus 14.75 cm(3) for the multiple cyroprobe group (P = .06). The gross cryolesion surface area for the single cryoprobe multiplied by 3 was 13.14 cm(2) versus 13.89 cm(2) for the multiple probe group (P = .52). CONCLUSION The cryolesion created by 3 simultaneously activated 1.47-mm probes appears to be larger than that of an additive effect. The lesions were significantly larger as measured by ultrasonography and nearly so (P = .06) as measured by the gross cryolesion volume. UROLOGY 79: 484.e1-484.e6, 2012. (c) 2012 Elsevier Inc. All rights reserved.

Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

The objective of this paper is to model variations in test-day milk yields of first lactations of Holstein cows by RR using B-spline functions and Bayesian inference in order to fit adequate and parsimonious models for the estimation of genetic parameters. They used 152,145 test day milk yield records from 7317 first lactations of Holstein cows. The model established in this study was additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. Authors modeled the average lactation curve of the population with a fourth-order orthogonal Legendre polynomial. They concluded that a cubic B-spline with seven random regression coefficients for both the additive genetic and permanent environment effects was to be the best according to residual mean square and residual variance estimates. Moreover they urged a lower order model (quadratic B-spline with seven random regression coefficients for both random effects) could be adopted because it yielded practically the same genetic parameter estimates with parsimony. (C) 2012 Elsevier B.V. All rights reserved.

Random regression analyses using B-spline functions to model growth of Nellore cattle

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

Degree of multicollinearity and variables involved in linear dependence in additive-dominant models

The objective of this work was to assess the degree of multicollinearity and to identify the variables involved in linear dependence relations in additive-dominant models. Data of birth weight (n=141,567), yearling weight (n=58,124), and scrotal circumference (n=20,371) of Montana Tropical composite cattle were used. Diagnosis of multicollinearity was based on the variance inflation factor (VIF) and on the evaluation of the condition indexes and eigenvalues from the correlation matrix among explanatory variables. The first model studied (RM) included the fixed effect of dam age class at calving and the covariates associated to the direct and maternal additive and non-additive effects. The second model (R) included all the effects of the RM model except the maternal additive effects. Multicollinearity was detected in both models for all traits considered, with VIF values of 1.03 - 70.20 for RM and 1.03 - 60.70 for R. Collinearity increased with the increase of variables in the model and the decrease in the number of observations, and it was classified as weak, with condition index values between 10.00 and 26.77. In general, the variables associated with additive and non-additive effects were involved in multicollinearity, partially due to the natural connection between these covariables as fractions of the biological types in breed composition.

Intermittent spike-wave dynamics in a heterogeneous, spatially extended neural mass model

Generalised epileptic seizures are frequently accompanied by sudden, reversible transitions from low amplitude, irregular background activity to high amplitude, regular spike-wave discharges (SWD) in the EEG. The underlying mechanisms responsible for SWD generation and for the apparently spontaneous transitions to SWD and back again are still not fully understood. Specifically, the role of spatial cortico-cortical interactions in ictogenesis is not well studied. We present a macroscopic, neural mass model of a cortical column which includes two distinct time scales of inhibition. This model can produce both an oscillatory background and a pathological SWD rhythm. We demonstrate that coupling two of these cortical columns can lead to a bistability between out-of-phase, low amplitude background dynamics and in-phase, high amplitude SWD activity. Stimuli can cause state-dependent transitions from background into SWD. In an extended local area of cortex, spatial heterogeneities in a model parameter can lead to spontaneous reversible transitions from a desynchronised background to synchronous SWD due to intermittency. The deterministic model is therefore capable of producing absence seizure-like events without any time dependent adjustment of model parameters. The emergence of such mechanisms due to spatial coupling demonstrates the importance of spatial interactions in modelling ictal dynamics, and in the study of ictogenesis.

Everolimus augments the effects of sorafenib in a syngeneic orthotopic model of hepatocellular carcinoma

Sorafenib targets the Raf/mitogen-activated protein kinase, VEGF, and platelet-derived growth factor pathways and prolongs survival patients in advanced hepatocellular carcinoma (HCC). Everolimus inhibits the mammalian target of rapamycin, a kinase overactive in HCC. To investigate whether the antitumor effects of these agents are additive, we compared a combined and sequential treatment regimen of everolimus and sorafenib with monotherapy. After hepatic implantation of Morris Hepatoma (MH) cells, rats were randomly allocated to everolimus (5 mg/kg, 2×/week), sorafenib (7.5 mg/kg/d), combined everolimus and sorafenib, sequential sorafenib (2 weeks) then everolimus (3 weeks), or control groups. MRI quantified tumor volumes. Erk1/2, 4E-BP1, and their phosphorylated forms were quantified by immunoblotting. Angiogenesis was assessed in vitro by aortic ring and tube formation assays, and in vivo with Vegf-a mRNA and vascular casts. After 35 days, tumor volumes were reduced by 60%, 85%, and 55%, relative to controls, in everolimus, the combination, and sequential groups, respectively (P < 0.01). Survival was longest in the combination group (P < 0.001). Phosphorylation of 4E-BP1 and Erk1/2 decreased after everolimus and sorafenib, respectively. Angiogenesis decreased after all treatments (P < 0.05), although sorafenib increased Vegf-a mRNA in liver tumors. Vessel sprouting was abundant in control tumors, lower after sorafenib, and absent after the combination. Intussusceptive angiogenic transluminal pillars failed to coalesce after the combination. Combined treatment with everolimus and sorafenib exerts a stronger antitumoral effect on MH tumors than monotherapy. Everolimus retains antitumoral properties when administered sequentially after sorafenib. This supports the clinical use of everolimus in HCC, both in combination with sorafenib or after sorafenib.

Interleukin-6 is an efficacious marker of axonal transport disruption during experimental glaucoma and stimulates neuritogenesis in cultured retinal ganglion cells

It is increasingly recognised that chronically activated glia contribute to the pathology of various neurodegenerative diseases, including glaucoma. One means by which this can occur is through the release of neurotoxic, proinflammatory factors. In the current study, we therefore investigated the spatio-temporal patterns of expression of three such cytokines, IL-1β, TNFα and IL-6, in a validated rat model of experimental glaucoma. First, only weak evidence was found for increased expression of IL-1β and TNFα following induction of ocular hypertension. Second, and much more striking, was that robust evidence was uncovered showing IL-6 to be synthesised by injured retinal ganglion cells following elevation of intraocular pressure and transported in an orthograde fashion along the nerve, accumulating at sites of axonal disruption in the optic nerve head. Verification that IL-6 represents a novel marker of disrupted axonal transport in this model was obtained by performing double labelling immunofluorescence with recognised markers of fast axonal transport. The stimulus for IL-6 synthesis and axonal transport during experimental glaucoma arose from axonal injury rather than ocular hypertension, as the response was identical after optic nerve crush and bilateral occlusion of the carotid arteries, each of which is independent of elevated intraocular pressure. Moreover, the response of IL-6 was not a generalised feature of the gp130 family of cytokines, as it was not mimicked by another family member, ciliary neurotrophic factor. Finally, further study suggested that IL-6 may be an early part of the endogenous regenerative response as the cytokine colocalised with growth-associated membrane phosphoprotein-43 in some putative regenerating axons, and potently stimulated neuritogenesis in retinal ganglion cells in culture, an effect that was additive to that of ciliary neurotrophic factor. These data comprise clear evidence that IL-6 is actively involved in the attempt of injured retinal ganglion cells to regenerate their axons.

Additive Hazards Models with Latent Treatment Effectiveness Lag Time

In many clinical trials to evaluate treatment efficacy, it is believed that there may exist latent treatment effectiveness lag times after which medical procedure or chemical compound would be in full effect. In this article, semiparametric regression models are proposed and studied to estimate the treatment effect accounting for such latent lag times. The new models take advantage of the invariance property of the additive hazards model in marginalizing over random effects, so parameters in the models are easy to be estimated and interpreted, while the flexibility without specifying baseline hazard function is kept. Monte Carlo simulation studies demonstrate the appropriateness of the proposed semiparametric estimation procedure. Data collected in the actual randomized clinical trial, which evaluates the effectiveness of biodegradable carmustine polymers for treatment of recurrent brain tumors, are analyzed.

Inhibition of mTOR in combination with doxorubicin in an experimental model of hepatocellular carcinoma

BACKGROUND/AIMS: Hepatocellular carcinoma (HCC) is resistant to chemotherapy. We reported that sirolimus, an mTOR inhibitor, has antiangiogenic properties in HCC. Since antiangiogenic therapy may enhance chemotherapy effects, we tested the antitumorigenic properties of sirolimus combined with doxorubicin in experimental HCC. METHODS: Morris Hepatoma (MH) cells were implanted into livers of syngeneic rats. Animals were assigned to sirolimus, pegylated liposomal doxorubicin, both combined or control groups. Tumoral growth was followed by MRI. Antiangiogenic effects were assessed by CD31 immunostaining and capillary tube formation assays. Cell proliferation was monitored in vitro by thymidine incorporation. Expression of p21 and phosphorylated MAPKAP kinase-2 was quantified by immunoblotting. RESULTS: Animals treated with the combination developed smaller tumors with decreased tumor microvessel density compared to animals that received monotherapies. In vitro, inhibition of mTOR further impaired capillary formation in the presence of doxorubicin. Doxorubicin reduced endothelial cell proliferation; inhibition of mTOR accentuated this effect. Doxorubicin stimulated p21 expression and the phosphorylation of MAPKAP kinase-2 in endothelial cells. Addition of mTOR inhibitor down-regulated p21, but did not decrease MAPKAP kinase-2 phosphorylation. CONCLUSIONS: Sirolimus has additive antitumoral and antiangiogenic effects when administered with doxorubicin. These findings offer a rationale for combining mTOR inhibitors with chemotherapy in HCC treatment.