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.

Bayesian analysis of weak gravitational lensing and Sunyaev-Zel'dovich data for six galaxy clusters

We present an analysis of observations made with the Arcminute Microkelvin Imager (AMI) and the CanadaFranceHawaii Telescope (CFHT) of six galaxy clusters in a redshift range of 0.160.41. The cluster gas is modelled using the SunyaevZeldovich (SZ) data provided by AMI, while the total mass is modelled using the lensing data from the CFHT. In this paper, we (i) find very good agreement between SZ measurements (assuming large-scale virialization and a gas-fraction prior) and lensing measurements of the total cluster masses out to r200; (ii) perform the first multiple-component weak-lensing analysis of A115; (iii) confirm the unusual separation between the gas and mass components in A1914 and (iv) jointly analyse the SZ and lensing data for the relaxed cluster A611, confirming our use of a simulation-derived masstemperature relation for parametrizing measurements of the SZ effect.

A multiple time scale survival model with a cure fraction

Many recent survival studies propose modeling data with a cure fraction, i.e., data in which part of the population is not susceptible to the event of interest. This event may occur more than once for the same individual (recurrent event). We then have a scenario of recurrent event data in the presence of a cure fraction, which may appear in various areas such as oncology, finance, industries, among others. This paper proposes a multiple time scale survival model to analyze recurrent events using a cure fraction. The objective is analyzing the efficiency of certain interventions so that the studied event will not happen again in terms of covariates and censoring. All estimates were obtained using a sampling-based approach, which allows information to be input beforehand with lower computational effort. Simulations were done based on a clinical scenario in order to observe some frequentist properties of the estimation procedure in the presence of small and moderate sample sizes. An application of a well-known set of real mammary tumor data is provided.

Framing the difficulties resulting from implementing a Participatory Management Model in a public hospital

Objective: This study aims to address difficulties reported by the nursing team during the process of changing the management model in a public hospital in Brazil. Methods: This qualitative study used thematic content analysis as proposed by Bardin, and data were analyzed using the theoretical framework of Bolman and Deal. Results: The vertical implementation of Participatory Management contradicted its underlying philosophy and thereby negatively influenced employee acceptance of the change. The decentralized structure of the Participatory Management Model was implemented but shared decision-making was only partially utilized. Despite facilitation of the communication process within the unit, more significant difficulties arose from lack of communication inter-unit. Values and principals need to be shared by teams, however, that will happens only if managers restructure accountabilities changing job descriptions of all team members. Conclusion: Innovative management models that depart from the premise of decentralized decision-making and increased communication encourage accountability, increased motivation and satisfaction, and contribute to improving the quality of care. The contribution of the study is that it describes the complexity of implementing an innovative management model, examines dissent and intentionally acknowledges the difficulties faced by employees in the organization.

Methionine-induced hyperhomocysteinemia reverts fibrinolytic pathway activation in a murine model of acute promyelocytic leukemia

Increased fibrinolysis is an important component of acute promyelocytic leukemia (APL) bleeding diathesis. APL blasts overexpress annexin II (ANXII), a receptor for tissue plasminogen activator (tPA), and plasminogen, thereby increasing plasmin generation. Previous studies suggested that ANXII plays a pivotal role in APL coagulopathy. ANXII binding to tPA can be inhibited by homocysteine and hyperhomocysteinemia can be induced by L-methionine supplementation. In the present study, we used an APL mouse model to study ANXII function and the effects of hyperhomocysteinemia in vivo. Leukemic cells expressed higher ANXII and tPA plasma levels (11.95 ng/mL in leukemic vs 10.74 ng/mL in wild-type; P = .004). In leukemic mice, administration of L-methionine significantly increased homocysteine levels (49.0 mu mol/mL and < 6.0 mu mol/mL in the treated and nontreated groups, respectively) and reduced tPA levels to baseline concentrations. The latter were also decreased after infusion of the LCKLSL peptide, a competitor for the ANXII tPA-binding site (11.07 ng/mL; P = .001). We also expressed and purified the p36 component of ANXII in Pichia methanolica. The infusion of p36 in wild-type mice increased tPA and thrombin-antithrombin levels, and the latter was reversed by L-methionine administration. The results of the present study demonstrate the relevance of ANXII in vivo and suggest that methionine-induced hyperhomocysteinemia may reverse hyperfibrinolysis in APL. (Blood. 2012;120(1):207-213)

Forced Desynchronization of Activity Rhythms in a Model of Chronic Jet Lag in Mice

We studied locomotor activity rhythms of C57/Bl6 mice under a chronic jet lag (CJL) protocol (ChrA(6/2)), which consisted of 6-hour phase advances of the light-dark schedule (LD) every 2 days. Through periodogram analysis, we found 2 components of the activity rhythm: a short-period component (21.01 +/- 0.04 h) that was entrained by the LD schedule and a long-period component (24.68 +/- 0.26 h). We developed a mathematical model comprising 2 coupled circadian oscillators that was tested experimentally with different CJL schedules. Our simulations suggested that under CJL, the system behaves as if it were under a zeitgeber with a period determined by (24 -[phase shift size/days between shifts]). Desynchronization within the system arises according to whether this effective zeitgeber is inside or outside the range of entrainment of the oscillators. In this sense, ChrA(6/2) is interpreted as a (24 - 6/2 = 21 h) zeitgeber, and simulations predicted the behavior of mice under other CJL schedules with an effective 21-hour zeitgeber. Animals studied under an asymmetric T = 21 h zeitgeber (carried out by a 3-hour shortening of every dark phase) showed 2 activity components as observed under ChrA(6/2): an entrained short-period (21.01 +/- 0.03 h) and a long-period component (23.93 +/- 0.31 h). Internal desynchronization was lost when mice were subjected to 9-hour advances every 3 days, a possibility also contemplated by the simulations. Simulations also predicted that desynchronization should be less prevalent under delaying than under advancing CJL. Indeed, most mice subjected to 6-hour delay shifts every 2 days (an effective 27-hour zeitgeber) displayed a single entrained activity component (26.92 +/- 0.11 h). Our results demonstrate that the disruption provoked by CJL schedules is not dependent on the phase-shift magnitude or the frequency of the shifts separately but on the combination of both, through its ratio and additionally on their absolute values. In this study, we present a novel model of forced desynchronization in mice under a specific CJL schedule; in addition, our model provides theoretical tools for the evaluation of circadian disruption under CJL conditions that are currently used in circadian research.

Spatio-temporal patterns of tuberculosis incidence in Ribeirao Preto, State of Sao Paulo, southeast Brazil, and their relationship with social vulnerability: a Bayesian analysis

Introduction: The purpose of this ecological study was to evaluate the urban spatial and temporal distribution of tuberculosis (TB) in Ribeirao Preto, State of Sao Paulo, southeast Brazil, between 2006 and 2009 and to evaluate its relationship with factors of social vulnerability such as income and education level. Methods: We evaluated data from TBWeb, an electronic notification system for TB cases. Measures of social vulnerability were obtained from the SEADE Foundation, and information about the number of inhabitants, education and income of the households were obtained from Brazilian Institute of Geography and Statistics. Statistical analyses were conducted by a Bayesian regression model assuming a Poisson distribution for the observed new cases of TB in each area. A conditional autoregressive structure was used for the spatial covariance structure. Results: The Bayesian model confirmed the spatial heterogeneity of TB distribution in Ribeirao Preto, identifying areas with elevated risk and the effects of social vulnerability on the disease. We demonstrated that the rate of TB was correlated with the measures of income, education and social vulnerability. However, we observed areas with low vulnerability and high education and income, but with high estimated TB rates. Conclusions: The study identified areas with different risks for TB, given that the public health system deals with the characteristics of each region individually and prioritizes those that present a higher propensity to risk of TB. Complex relationships may exist between TB incidence and a wide range of environmental and intrinsic factors, which need to be studied in future research.

Motion-based wave estimation: Small-scale tests with a crane-barge model

This paper provides additional validation to the problem of estimating wave spectra based on the first-order motions of a moored vessel. Prior investigations conducted by the authors have attested that even a large-volume ship, such as an FPSO unit, could be adopted for on-board estimation of the wave field. The obvious limitation of the methodology concerns filtering of high-frequency wave components, for which the vessel has no significant response. As a result, the estimation range is directly dependent on the characteristics of the vessel response. In order to extend this analysis, further small-scale tests were performed with a model of a pipe-laying crane-barge. When compared to the FPSO case, the results attest that a broader range of typical sea states can be accurately estimated, including crossed-sea states with low peak periods. (C) 2012 Elsevier Ltd. All rights reserved.

Bayesian Analysis for Errors in Variables with Changepoint Models

Changepoint regression models have originally been developed in connection with applications in quality control, where a change from the in-control to the out-of-control state has to be detected based on the avaliable random observations. Up to now various changepoint models have been suggested for differents applications like reliability, econometrics or medicine. In many practical situations the covariate cannot be measured precisely and an alternative model are the errors in variable regression models. In this paper we study the regression model with errors in variables with changepoint from a Bayesian approach. From the simulation study we found that the proposed procedure produces estimates suitable for the changepoint and all other model parameters.

Sympathetic overactivity precedes metabolic dysfunction in a fructose model of glucose intolerance in mice

De Angelis K, Senador DD, Mostarda C, Irigoyen MC, Morris M. Sympathetic overactivity precedes metabolic dysfunction in a fructose model of glucose intolerance in mice. Am J Physiol Regul Integr Comp Physiol 302: R950-R957, 2012. First published February 8, 2012; doi: 10.1152/ajpregu.00450.2011.-Consumption of high levels of fructose in humans and animals leads to metabolic and cardiovascular dysfunction. There are questions as to the role of the autonomic changes in the time course of fructose-induced dysfunction. C57/BL male mice were given tap water or fructose water (100 g/l) to drink for up to 2 mo. Groups were control (C), 15-day fructose (F15), and 60-day fructose (F60). Light-dark patterns of arterial pressure (AP) and heart rate (HR), and their respective variabilities were measured. Plasma glucose, lipids, insulin, leptin, resistin, adiponectin, and glucose tolerance were quantified. Fructose increased systolic AP (SAP) at 15 and 60 days during both light (F15: 123 +/- 2 and F60: 118 +/- 2 mmHg) and dark periods (F15: 136 +/- 4 and F60: 136 +/- 5 mmHg) compared with controls (light: 111 +/- 2 and dark: 117 +/- 2 mmHg). SAP variance (VAR) and the low-frequency component (LF) were increased in F15 (>60% and >80%) and F60 (>170% and >140%) compared with C. Cardiac sympatho-vagal balance was enhanced, while baroreflex function was attenuated in fructose groups. Metabolic parameters were unchanged in F15. However, F60 showed significant increases in plasma glucose (26%), cholesterol (44%), triglycerides (22%), insulin (95%), and leptin (63%), as well as glucose intolerance. LF of SAP was positively correlated with SAP. Plasma leptin was correlated with triglycerides, insulin, and glucose tolerance. Results show that increased sympathetic modulation of vessels and heart preceded metabolic dysfunction in fructose-consuming mice. Data suggest that changes in autonomic modulation may be an initiating mechanism underlying the cluster of symptoms associated with cardiometabolic disease.

Dynamical (super)symmetry vacuum properties of the supersymmetric Chern-Simons-matter model

By computing the two-loop effective potential of the D=3 N=1 supersymmetric Chern-Simons model minimally coupled to a massless self-interacting matter superfield, it is shown that supersymmetry is preserved, while the internal U(1) and the scale symmetries are broken at two-loop order, dynamically generating masses both for the gauge superfield and for the real component of the matter superfield.

Cointegration: Bayesian Significance Test

To estimate causal relationships, time series econometricians must be aware of spurious correlation, a problem first mentioned by Yule (1926). To deal with this problem, one can work either with differenced series or multivariate models: VAR (VEC or VECM) models. These models usually include at least one cointegration relation. Although the Bayesian literature on VAR/VEC is quite advanced, Bauwens et al. (1999) highlighted that "the topic of selecting the cointegrating rank has not yet given very useful and convincing results". The present article applies the Full Bayesian Significance Test (FBST), especially designed to deal with sharp hypotheses, to cointegration rank selection tests in VECM time series models. It shows the FBST implementation using both simulated and available (in the literature) data sets. As illustration, standard non informative priors are used.

Discrimination of Basal Cell Carcinoma and Melanoma from Normal Skin Biopsies in Vitro Through Raman Spectroscopy and Principal Component Analysis

Objective: Raman spectroscopy has been employed to discriminate between malignant (basal cell carcinoma [BCC] and melanoma [MEL]) and normal (N) skin tissues in vitro, aimed at developing a method for cancer diagnosis. Background data: Raman spectroscopy is an analytical tool that could be used to diagnose skin cancer rapidly and noninvasively. Methods: Skin biopsy fragments of similar to 2 mm(2) from excisional surgeries were scanned through a Raman spectrometer (830 nm excitation wavelength, 50 to 200 mW of power, and 20 sec exposure time) coupled to a fiber optic Raman probe. Principal component analysis (PCA) and Euclidean distance were employed to develop a discrimination model to classify samples according to histopathology. In this model, we used a set of 145 spectra from N (30 spectra), BCC (96 spectra), and MEL (19 spectra) skin tissues. Results: We demonstrated that principal components (PCs) 1 to 4 accounted for 95.4% of all spectral variation. These PCs have been spectrally correlated to the biochemicals present in tissues, such as proteins, lipids, and melanin. The scores of PC2 and PC3 revealed statistically significant differences among N, BCC, and MEL (ANOVA, p < 0.05) and were used in the discrimination model. A total of 28 out of 30 spectra were correctly diagnosed as N, 93 out of 96 as BCC, and 13 out of 19 as MEL, with an overall accuracy of 92.4%. Conclusions: This discrimination model based on PCA and Euclidean distance could differentiate N from malignant (BCC and MEL) with high sensitivity and specificity.

Targeting the Transposase Domain of the DNA Repair Component Metnase to Enhance Chemotherapy

Previous studies have shown that the DNA repair component Metnase (SETMAR) mediates resistance to DNA damaging cancer chemotherapy. Metnase has a nuclease domain that shares homology with the Transposase family. We therefore virtually screened the tertiary Metnase structure against the 550,000 compound ChemDiv library to identify small molecules that might dock in the active site of the transposase nuclease domain of Metnase. We identified eight compounds as possible Metnase inhibitors. Interestingly, among these candidate inhibitors were quinolone antibiotics and HIV integrase inhibitors, which share common structural features. Previous reports have described possible activity of quinolones as antineoplastic agents. Therefore, we chose the quinolone ciprofloxacin for further study, based on its wide clinical availability and low toxicity. We found that ciprofloxacin inhibits the ability of Metnase to cleave DNA and inhibits Metnase-dependent DNA repair. Ciprofloxacin on its own did not induce DNA damage, but it did reduce repair of chemotherapy-induced DNA damage. Ciprofloxacin increased the sensitivity of cancer cell lines and a xenograft tumor model to clinically relevant chemotherapy. These studies provide a mechanism for the previously postulated antineoplastic activity of quinolones, and suggest that ciprofloxacin might be a simple yet effective adjunct to cancer chemotherapy. Cancer Res; 72(23); 6200-8. (C) 2012 AACR.

Structure and Ionic Conductivity in the Mixed-Network Former Chalcogenide Glass System [Na2S](2/3)[(B2S3)(x)(P2S5)(1-x)](1/3)

Glasses in the system [Na2S](2/3)[(B2S3)(x)(P2S5)(1-x)](1/3) (0.0 <= x <= 1.0) were prepared by the melt quenching technique, and their properties were characterized by thermal analysis and impedance spectroscopy. Their atomic-level structures were comprehensively characterized by Raman spectroscopy and B-11, P-31, and Na-23 high resolution solid state magic-angle spinning (MAS) NMR techniques. P-31 MAS NMR peak assignments were made by the presence or absence of homonuclear indirect P-31-P-31 spin-spin interactions as detected using homonuclear J-resolved and refocused INADEQUATE techniques. The extent of B-S-P connectivity in the glassy network was quantified by P-31{B-11} and B-11{P-31} rotational echo double resonance spectroscopy. The results clearly illustrate that the network modifier alkali sulfide, Na2S, is not proportionally shared between the two network former components, B and P. Rather, the thiophosphate (P) component tends to attract a larger concentration of network modifier species than predicted by the bulk composition, and this results in the conversion of P2S74-, pyrothiophosphate, Na/P = 2:1, units into PS43-, orthothiophosphate, Na/P = 3:1, groups. Charge balance is maintained by increasing the net degree of polymerization of the thioborate (B) units through the formation of covalent bridging sulfur (BS) units, B S B. Detailed inspection of the B-11 MAS NMR spectra reveals that multiple thioborate units are formed, ranging from neutral BS3/2 groups all the way to the fully depolymerized orthothioborate (BS33-) species. On the basis of these results, a comprehensive and quantitative structural model is developed for these glasses, on the basis of which the compositional trends in the glass transition temperatures (T-g) and ionic conductivities can be rationalized. Up to x = 0.4, the dominant process can be described in a simplified way by the net reaction equation P-1 + B-1 reversible arrow P-0 + B-4, where the superscripts denote the number of BS atoms for the respective network former species. Above x = 0.4, all of the thiophosphate units are of the P-0 type and both pyro-(B-1) and orthothioborate (B-0) species make increasing contributions to the network structure with increasing x. In sharp contrast to the situation in sodium borophosphate glasses, four-coordinated thioborate species are generally less abundant and heteroatomic B-S-P linkages appear to not exist. On the basis of this structural information, compositional trends in the ionic conductivities are discussed in relation to the nature of the charge-compensating anionic species and the spatial distribution of the charge carriers.