Bayesian analysis of skew-t multivariate null intercept measurement error model

The multivariate skew-t distribution (J Multivar Anal 79:93-113, 2001; J R Stat Soc, Ser B 65:367-389, 2003; Statistics 37:359-363, 2003) includes the Student t, skew-Cauchy and Cauchy distributions as special cases and the normal and skew-normal ones as limiting cases. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis of repeated measures, pretest/post-test data, under multivariate null intercept measurement error model (J Biopharm Stat 13(4):763-771, 2003) where the random errors and the unobserved value of the covariate (latent variable) follows a Student t and skew-t distribution, respectively. The results and methods are numerically illustrated with an example in the field of dentistry.

Bayesian analysis for a skew extension of the multivariate null intercept measurement error model

Skew-normal distribution is a class of distributions that includes the normal distributions as a special case. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis in a multivariate, null intercept, measurement error model [R. Aoki, H. Bolfarine, J.A. Achcar, and D. Leao Pinto Jr, Bayesian analysis of a multivariate null intercept error-in -variables regression model, J. Biopharm. Stat. 13(4) (2003b), pp. 763-771] where the unobserved value of the covariate (latent variable) follows a skew-normal distribution. The results and methods are applied to a real dental clinical trial presented in [A. Hadgu and G. Koch, Application of generalized estimating equations to a dental randomized clinical trial, J. Biopharm. Stat. 9 (1999), pp. 161-178].

Inference and local influence assessment in skew-normal null intercept measurement error model

In this article, we discuss inferential aspects of the measurement error regression models with null intercepts when the unknown quantity x (latent variable) follows a skew normal distribution. We examine first the maximum-likelihood approach to estimation via the EM algorithm by exploring statistical properties of the model considered. Then, the marginal likelihood, the score function and the observed information matrix of the observed quantities are presented allowing direct inference implementation. In order to discuss some diagnostics techniques in this type of models, we derive the appropriate matrices to assessing the local influence on the parameter estimates under different perturbation schemes. The results and methods developed in this paper are illustrated considering part of a real data set used by Hadgu and Koch [1999, Application of generalized estimating equations to a dental randomized clinical trial. Journal of Biopharmaceutical Statistics, 9, 161-178].

UPLC-MS-based urine metabolomics reveals indole-3-lactic acid and phenyllactic acid as conserved biomarkers for alcohol-induced liver disease in the Ppara-null mouse model

Since the development and prognosis of alcohol-induced liver disease (ALD) vary significantly with genetic background, identification of a genetic background-independent noninvasive ALD biomarker would significantly improve screening and diagnosis. This study explored the effect of genetic background on the ALD-associated urinary metabolome using the Ppara-null mouse model on two different backgrounds, C57BL/6 (B6) and 129/SvJ (129S), along with their wild-type counterparts. Reversed-phase gradient UPLC-ESI-QTOF-MS analysis revealed that urinary excretion of a number of metabolites, such as ethylsulfate, 4-hydroxyphenylacetic acid, 4-hydroxyphenylacetic acid sulfate, adipic acid, pimelic acid, xanthurenic acid, and taurine, were background-dependent. Elevation of ethyl-β-d-glucuronide and N-acetylglycine was found to be a common signature of the metabolomic response to alcohol exposure in wild-type as well as in Ppara-null mice of both strains. However, increased excretion of indole-3-lactic acid and phenyllactic acid was found to be a conserved feature exclusively associated with the alcohol-treated Ppara-null mouse on both backgrounds that develop liver pathologies similar to the early stages of human ALD. These markers reflected the biochemical events associated with early stages of ALD pathogenesis. The results suggest that indole-3-lactic acid and phenyllactic acid are potential candidates for conserved and pathology-specific high-throughput noninvasive biomarkers for early stages of ALD.

Identification of noninvasive biomarkers for alcohol-induced liver disease using urinary metabolomics and the Ppara-null mouse

Alcohol-induced liver disease (ALD) is a leading cause of nonaccident-related deaths in the United States. Although liver damage caused by ALD is reversible when discovered at the earlier stages, current risk assessment tools are relatively nonspecific. Identification of an early specific signature of ALD would aid in therapeutic intervention and recovery. In this study, the metabolic changes associated with ALD were examined using alcohol-fed male Ppara-null mouse as a model of ALD. Principal components analysis of the mass spectrometry-based urinary metabolic profile showed that alcohol-treated wild-type and Ppara-null mice could be distinguished from control animals without information on history of alcohol consumption. The urinary excretion of ethyl-sulfate, ethyl-beta-d-glucuronide, 4-hydroxyphenylacetic acid, and 4-hydroxyphenylacetic acid sulfate was elevated and that of the 2-hydroxyphenylacetic acid, adipic acid, and pimelic acid was depleted during alcohol treatment in both wild-type and the Ppara-null mice albeit to different extents. However, indole-3-lactic acid was exclusively elevated by alcohol exposure in Ppara-null mice. The elevation of indole-3-lactic acid is mechanistically related to the molecular events associated with development of ALD in alcohol-treated Ppara-null mice. This study demonstrated the ability of a metabolomics approach to identify early, noninvasive biomarkers of ALD pathogenesis in Ppara-null mouse model.

I. Identification and characterisation of epigenetically altered tumor supressor genes by proteomic and genomic approches / II. Studies of genes regualted by MeCP2 union to its promoter regions by proteomic and genmomic approches

DNA methylation has an important impact on normal cell physiology, thus any defects in this mechanism may be related to the development of various diseases In this project we are interested in identifying epigeneticaliy modified genes, in general controlled by processes related to the DNA methylation, by means of a new strategy combining protomic and genomic analyses. First, the two Dimensional-Difference Gel Electrophoresis (2-DIGE) protein analyses of extracts obtained from HCT-116 wt and double knockout for DNMT1 and DNMT3b (DKO) cells revealed 34 proteins overexpressed in the condition of DNMTs depletion. From five genes with higher transcript lavels in DKO cells, comparing with HCT-116 wt. oniy AKR1B1, UCHLl and VIM are melhylated in HCT-116. As expected. the DNA methvlation 1s lost in DKO cells. The rneth,vl ation of VIM and UCHLl promoters in some cancer samples has already been repaired, thus further studies has been focused on AKRlBI. AKR1B1 expression due lo DNA methyiaton of promoter region seems to occur specilfically in the colon cancer cell Iines. which was confirmed in the DNA rnethylation status and expression analyses. performed on 32 different cancer cell lines (including colon, breast, lymphoma, leukemia, neuroblastoma, glioma and lung cancer cell Iines) as well as normal colon and normal lymphocytes samples. AKRIBI expression after treatments with DNA demethvlating agent (AZA) was rescued in 5 coloncancer cell lines (including genetic regulation of the candidate gene. The methylation status of the rest of the genes identified in proteomic analysis was checked by methylation specific PCR (MSP) experiment and all appeared to be unmethylated. The similar research has been done also bv means of Mecp2-null mouse model For 14 selected candidate genes the analyses of expression leveis, methylation Status and MeCP2 interaction with promoters are currently being performed.

Modeling spatial distribution of cancer incidence in Cordoba, Argentina

Background: Cancer is the second leading cause of death in Argentina, and there is little knowledge about its incidence. The first study based on population-based cancer registry described spatial incidence and indicated that there existed at least county-level aggregation. The aim of the present work is to model the incidence patterns for the most incidence cancer in Córdoba Province, Argentina, using information from the Córdoba Cancer Registry by performing multilevel mixed model approach to deal with dependence and unobserved heterogeneity coming from the geo-reference cancer occurrence. Methods: Standardized incidence rates (world standard population) (SIR) by sex based on 5-year age groups were calculated for 109 districts nested on 26 counties for the most incidence cancers in Cordoba using 2004 database. A Poisson twolevel random effect model representing unobserved heterogeneity between first level-districts and second level-counties was fitted to assess the spatial distribution of the overall and site specific cancer incidence rates. Results: SIR cancer at Córdoba province shown an average of 263.53±138.34 and 200.45±98.30 for men and women, respectively. Considering the ratio site specific mean SIR to the total mean, breast cancer ratio was 0.25±0.19, prostate cancer ratio was 0.12±0.10 and lower values for lung and colon cancer for both sexes. The Poisson two-level random intercepts model fitted for SIR data distributed with overdispersion shown significant hierarchical structure for the cancer incidence distribution. Conclusions: a strong spatial-nested effect for the cancer incidence in Córdoba was observed and will help to begin the study of the factors associated with it.

In vitro generation and characterization of acute myeloid leukemia-reactive CD8 + cytotoxic T-lymphocyte clones from healthy donors

Donor-derived CD8+ cytotoxic T lymphocytes (CTLs) eliminating host leukemic cells mediate curative graft-versus-leukemia (GVL) reactions after allogeneic hematopoietic stem cell transplantation (HSCT). The leukemia-reactive CTLs recognize hematopoiesis-restricted or broadly expressed minor histocompatibility and leukemia-associated peptide antigens that are presented by human leukocyte antigen (HLA) class I molecules on recipient cells. The development of allogeneic CTL therapy in acute myeloid leukemia (AML) is hampered by the poor efficiency of current techniques for generating leukemia-reactive CTLs from unprimed healthy donors in vitro. In this work, a novel allogeneic mini-mixed lymphocyte/leukemia culture (mini-MLLC) approach was established by stimulating CD8+ T cells isolated from peripheral blood of healthy donors at comparably low numbers (i.e. 10e4/well) with HLA class I-matched primary AML blasts in 96-well microtiter plates. Before culture, CD8+ T cells were immunomagnetically separated into CD62L(high)+ and CD62L(low)+/neg subsets enriched for naive/central memory and effector memory cells, respectively. The application of 96-well microtiter plates aimed at creating multiple different responder-stimulator cell compositions in order to provide for the growth of leukemia-reactive CTLs optimized culture conditions by chance. The culture medium was supplemented with interleukin (IL)-7, IL-12, and IL-15. On day 14, IL-12 was replaced by IL-2. In eight different related and unrelated donor/AML pairs with complete HLA class I match, numerous CTL populations were isolated that specifically lysed myeloid leukemias in association with various HLA-A, -B, or -C alleles. These CTLs recognized neither lymphoblastoid B cell lines of donor and patient origin nor primary B cell leukemias expressing the corresponding HLA restriction element. CTLs expressed T cell receptors of single V-beta chain families, indicating their clonality. The vast majority of CTL clones were obtained from mini-MLLCs initiated with CD8+ CD62L(high)+ cells. Using antigen-specific stimulation, multiple CTL populations were amplified to 10e8-10e10 cells within six to eight weeks. The capability of mini-MLLC derived AML-reactive CTL clones to inhibit the engraftment of human primary AML blasts was investigated in the immunodeficient nonobese diabetic/severe combined immune deficient IL-2 receptor common γ-chain deficient (NOD/SCID IL2Rγnull) mouse model. The leukemic engraftment in NOD/SCID IL2Rγnull was specifically prevented if inoculated AML blasts had been pre-incubated in vitro with AML-reactive CTLs, but not with anti-melanoma control CTLs. These results demonstrate that myeloid leukemia-specific CTL clones capable of preventing AML engraftment in mice can be rapidly isolated from CD8+ CD62L(high)+ T cells of healthy donors in vitro. The efficient generation and expansion of these CTLs by the newly established mini-MLLC approach opens the door for several potential applications. First, CTLs can be used within T cell-driven antigen identification strategies to extend the panel of molecularly defined AML antigens that are recognizable by T cells of healthy donors. Second, because these CTLs can be isolated from the stem cell donor by mini-MLLC prior to transplantation, they could be infused into AML patients as a part of the stem cell allograft, or early after transplantation when the leukemia burden is low. The capability of these T cells to expand and function in vivo might require the simultaneous administration of AML-reactive CD4+ T cells generated by a similar in vitro strategy or, less complex, the co-transfer of CD8-depleted donor lymphocytes. To prepare clinical testing, the mini-MLLC approach should now be translated into a protocol that is compatible with good manufacturing practice guidelines.

Dislocated Tongue Muscle Attachment and Cleft Palate Formation

In Pierre Robin sequence, a retracted tongue due to micrognathia is thought to physically obstruct palatal shelf elevation and thereby cause cleft palate. However, micrognathia is not always associated with palatal clefting. Here, by using the Bmp7-null mouse model presenting with cleft palate and severe micrognathia, we provide the first causative mechanism linking the two. In wild-type embryos, the genioglossus muscle, which mediates tongue protrusion, originates from the rostral process of Meckel's cartilage and later from the mandibular symphysis, with 2 tendons positive for Scleraxis messenger RNA. In E13.5 Bmp7-null embryos, a rostral process failed to form, and a mandibular symphysis was absent at E17.5. Consequently, the genioglossus muscle fibers were diverted toward the lingual surface of Meckel's cartilage and mandibles, where they attached in an aponeurosis that ectopically expressed Scleraxis. The deflection of genioglossus fibers from the anterior-posterior toward the medial-lateral axis alters their direction of contraction and necessarily compromises tongue protrusion. Since this muscle abnormality precedes palatal shelf elevation, it is likely to contribute to clefting. In contrast, embryos with a cranial mesenchyme-specific deletion of Bmp7 (Bmp7:Wnt1-Cre) exhibited some degree of micrognathia but no cleft palate. In these embryos, a rostral process was present, indicating that mesenchyme-derived Bmp7 is dispensable for its formation. Moreover, the genioglossus appeared normal in Bmp7:Wnt1-Cre embryos, further supporting a role of aberrant tongue muscle attachment in palatal clefting. We thus propose that in Pierre Robin sequence, palatal shelf elevation is not impaired simply by physical obstruction by the tongue but by a specific developmental defect that leads to functional changes in tongue movements.

Analysis of the role of the transcription factor C/EBPβ in controlling uterine functions during early pregnancy

Embryo implantation into the endometrium is a complex biological process involving the integration of steroid hormone signaling, endometrial tissue remodeling and maternal- fetal communications. A successful pregnancy is the outcome of the timely integration of these events during the early stages of implantation. The involvement of ovarian steroid hormones, estrogen (E) and progesterone (P), acting through their cognate receptors, is essential for uterine functions during pregnancy. The molecular mechanisms that control the process of implantation are undergoing active exploration. Through our recent efforts, we identified the transcription factor, CCAAT Enhancer Binding Protein Beta (C/EBPb) as a prominent target of estrogen and progesterone signaling in the uterus. The development of a C/EBPb-null mouse model, which is infertile, presented us with an opportunity to analyze the role of this molecule in uterine function. We discovered that C/EBPb functions in two distinct manners: (i) by acting as a mediator of E-induced proliferation of the uterine epithelium and (ii) by controlling uterine stromal cell differentiation, a process known as decidualization, during pregnancy. My studies have delineated important mechanisms by which E regulates C/EBPb expression to induce DNA replication and prevent apoptosis of uterine epithelial cells during E-induced epithelial growth. In subsequent studies, I analyzed the role of C/EBPb in decidualization and uncovered a unique mechanism by which C/EBPb regulates the synthesis of a unique laminin-containing extracellular matrix (ECM) that supports stromal cell differentiation and embryo invasion. In order to better define the role of laminin in implantation, we developed a laminin gamma 1-conditional knockout mouse model. This is currently an area of ongoing investigation. The information gained from our analysis of C/EBPb function in the uterus provides new insights into the mechanisms of steroid hormone action during early pregnancy. Ultimately, our findings may aid in the understanding of dysregulation of hormone-controlled pathways that underlie early pregnancy loss and infertility in women.

A musculoskeletal shoulder model based on pseudo-inverse and null-space optimization.

The goal of the present work was assess the feasibility of using a pseudo-inverse and null-space optimization approach in the modeling of the shoulder biomechanics. The method was applied to a simplified musculoskeletal shoulder model. The mechanical system consisted in the arm, and the external forces were the arm weight, 6 scapulo-humeral muscles and the reaction at the glenohumeral joint, which was considered as a spherical joint. The muscle wrapping was considered around the humeral head assumed spherical. The dynamical equations were solved in a Lagrangian approach. The mathematical redundancy of the mechanical system was solved in two steps: a pseudo-inverse optimization to minimize the square of the muscle stress and a null-space optimization to restrict the muscle force to physiological limits. Several movements were simulated. The mathematical and numerical aspects of the constrained redundancy problem were efficiently solved by the proposed method. The prediction of muscle moment arms was consistent with cadaveric measurements and the joint reaction force was consistent with in vivo measurements. This preliminary work demonstrated that the developed algorithm has a great potential for more complex musculoskeletal modeling of the shoulder joint. In particular it could be further applied to a non-spherical joint model, allowing for the natural translation of the humeral head in the glenoid fossa.

Hypotheses Testing on a Multivariate Null Intercept Errors-in-Variables Model

Considering the Wald, score, and likelihood ratio asymptotic test statistics, we analyze a multivariate null intercept errors-in-variables regression model, where the explanatory and the response variables are subject to measurement errors, and a possible structure of dependency between the measurements taken within the same individual are incorporated, representing a longitudinal structure. This model was proposed by Aoki et al. (2003b) and analyzed under the bayesian approach. In this article, considering the classical approach, we analyze asymptotic test statistics and present a simulation study to compare the behavior of the three test statistics for different sample sizes, parameter values and nominal levels of the test. Also, closed form expressions for the score function and the Fisher information matrix are presented. We consider two real numerical illustrations, the odontological data set from Hadgu and Koch (1999), and a quality control data set.

A robust Bayesian approach to null intercept measurement error model with application to dental data

Measurement error models often arise in epidemiological and clinical research. Usually, in this set up it is assumed that the latent variable has a normal distribution. However, the normality assumption may not be always correct. Skew-normal/independent distribution is a class of asymmetric thick-tailed distributions which includes the Skew-normal distribution as a special case. In this paper, we explore the use of skew-normal/independent distribution as a robust alternative to null intercept measurement error model under a Bayesian paradigm. We assume that the random errors and the unobserved value of the covariate (latent variable) follows jointly a skew-normal/independent distribution, providing an appealing robust alternative to the routine use of symmetric normal distribution in this type of model. Specific distributions examined include univariate and multivariate versions of the skew-normal distribution, the skew-t distributions, the skew-slash distributions and the skew contaminated normal distributions. The methods developed is illustrated using a real data set from a dental clinical trial. (C) 2008 Elsevier B.V. All rights reserved.

The Schwinger model on the null-plane

We study the Schwinger Model on the null-plane using the Dirac method for constrained systems. The fermion field is analyzed using the natural null-plane projections coming from the γ-algebra and it is shown that the fermionic sector of the Schwinger Model has only second class constraints. However, the first class constraints are exclusively of the bosonic sector. Finally, we establish the graded Lie algebra between the dynamical variables, via generalized Dirac bracket in the null-plane gauge, which is consistent with every constraint of the theory. © World Scientific Publishing Company.

Strategy and model building in the fourth dimension: a null model for genotype × age interaction as a Gaussian stationary stochastic process

Abstract Background Using univariate and multivariate variance components linkage analysis methods, we studied possible genotype × age interaction in cardiovascular phenotypes related to the aging process from the Framingham Heart Study. Results We found evidence for genotype × age interaction for fasting glucose and systolic blood pressure. Conclusions There is polygenic genotype × age interaction for fasting glucose and systolic blood pressure and quantitative trait locus × age interaction for a linkage signal for systolic blood pressure phenotypes located on chromosome 17 at 67 cM.