Modeling absolute differences in life expectancy with a censored skew-normal regression approach.

Parameter estimates from commonly used multivariable parametric survival regression models do not directly quantify differences in years of life expectancy. Gaussian linear regression models give results in terms of absolute mean differences, but are not appropriate in modeling life expectancy, because in many situations time to death has a negative skewed distribution. A regression approach using a skew-normal distribution would be an alternative to parametric survival models in the modeling of life expectancy, because parameter estimates can be interpreted in terms of survival time differences while allowing for skewness of the distribution. In this paper we show how to use the skew-normal regression so that censored and left-truncated observations are accounted for. With this we model differences in life expectancy using data from the Swiss National Cohort Study and from official life expectancy estimates and compare the results with those derived from commonly used survival regression models. We conclude that a censored skew-normal survival regression approach for left-truncated observations can be used to model differences in life expectancy across covariates of interest.

RNase E is required for the maturation of ssrA RNA and normal ssrA RNA peptide-tagging activity

During recent studies of ribonucleolytic “degradosome” complexes of Escherichia coli, we found that degradosomes contain certain RNAs as well as RNase E and other protein components. One of these RNAs is ssrA (for small stable RNA) RNA (also known as tm RNA or 10Sa RNA), which functions as both a tRNA and mRNA to tag the C-terminal ends of truncated proteins with a short peptide and target them for degradation. Here, we show that mature 363-nt ssrA RNA is generated by RNase E cleavage at the CCA-3′ terminus of a 457-nt ssrA RNA precursor and that interference with this cleavage in vivo leads to accumulation of the precursor and blockage of SsrA-mediated proteolysis. These results demonstrate that RNase E is required to produce mature ssrA RNA and for normal ssrA RNA peptide-tagging activity. Our findings indicate that RNase E, an enzyme already known to have a central role in RNA processing and decay in E. coli, also has the previously unsuspected ability to affect protein degradation through its role in maturation of the 3′ end of ssrA RNA.

Movements of truncated kinesin fragments with a short or an artificial flexible neck

To investigate the role of the neck domain of kinesin, we used optical trapping nanometry to perform high-resolution measurements of the movements and forces produced by recombinant kinesin fragments in which the neck domains were shortened or replaced by an artificial random coil. Truncated kinesin fragments (K351) that contain a motor domain consisting of ≈340 aa and a short neck domain consisting of ≈11 aa showed fast movement (800 nm/s) and 8-nm steps. Such behavior was similar to that of recombinant fragments containing the full-length neck domain (K411) and to that of native kinesin. Kinesin fragments lacking the short neck domain (K340), however, showed very slow movement (<50 nm/s), as previously reported. Joining an artificial 11-aa sequence that was expected to form a flexible random chain to the motor domain (K340–chain) produced normal fast (≈700 nm/s) and stepwise movement. The results suggest that the neck domain does not act as a rigid lever arm to magnify the structural change at the catalytic domain as has been believed for myosin, but it does act as a flexible joint to guarantee the mobility of the motor domain.

RacF1, a Novel Member of the Rho Protein Family in Dictyostelium discoideum, Associates Transiently with Cell Contact Areas, Macropinosomes, and Phagosomes

Using a PCR approach we have isolated racF1, a novel member of the Rho family in Dictyostelium. The racF1 gene encodes a protein of 193 amino acids and is constitutively expressed throughout the Dictyostelium life cycle. Highest identity (94%) was found to a RacF2 isoform, to Dictyostelium Rac1A, Rac1B, and Rac1C (70%), and to Rac proteins of animal species (64–69%). To investigate the role of RacF1 in cytoskeleton-dependent processes, we have fused it at its amino-terminus with green fluorescent protein (GFP) and studied the dynamics of subcellular redistribution using a confocal laser scanning microscope and a double-view microscope system. GFP–RacF1 was homogeneously distributed in the cytosol and accumulated at the plasma membrane, especially at regions of transient intercellular contacts. GFP–RacF1 also localized transiently to macropinosomes and phagocytic cups and was gradually released within <1 min after formation of the endocytic vesicle or the phagosome, respectively. On stimulation with cAMP, no enrichment of GFP–RacF1 was observed in leading fronts, from which it was found to be initially excluded. Cell lines were obtained using homologous recombination that expressed a truncated racF1 gene lacking sequences encoding the carboxyl-terminal region responsible for membrane targeting. These cells displayed normal phagocytosis, endocytosis, and exocytosis rates. Our results suggest that RacF1 associates with dynamic structures that are formed during pinocytosis and phagocytosis. Although RacF1 appears not to be essential, it might act in concert and/or share functions with other members of the Rho family in the regulation of a subset of cytoskeletal rearrangements that are required for these processes.

Proliferation of multipotent hematopoietic cells controlled by a truncated erythropoietin receptor transgene.

The long-term efficacy of gene therapy using bone marrow transplantation requires the engraftment of genetically altered totipotent hematopoietic stem cells (THSCs). Ex vivo expansion of corrected THSCs is one way to increase the efficiency of the procedure. Similarly, selective in vivo expansion of the therapeutic THSCs rather than the endogenous THSCs could favor the transplant. To test whether a conferred proliferative advantage gene can facilitate the in vitro and in vivo expansion of hematopoietic stem cells, we have generated transgenic mice expressing a truncated receptor for the growth factor erythropoietin. These mice are phenotypically normal, but when treated in vivo with exogenous erythropoietin they exhibit a marked increase in multipotent, clonogenic hematopoietic cells [colony-forming units in the spleen (CFU-S) and CFUs that give rise to granulocytes, erythroid cells, macrophages, and megakaryocytes within the same colony (CFU-GEMM)] in comparison with the wild-type mice. In addition, long-term in vitro culture of tEpoR transgenic bone marrow in the presence of erythropoietin induces exponential expansion of trilineage hematopoietic stem cells not seen with wild-type bone marrow. Thus, the truncated erythropoietin receptor gene shows promise as a means for obtaining cytokine-inducible hematopoietic stem cell proliferation to facilitate the direct targeting of THSCs and to provide a competitive repopulation advantage for transplanted therapeutic stem cells.

Modulation of retinoblastoma gene in normal adult hematopoiesis: peak expression and functional role in advanced erythroid differentiation.

The retinoblastoma (RB) gene specifies a nuclear phosphoprotein (pRb 105), which is a prototype tumor suppressor inactivated in a variety of human tumors. Recent studies suggest that RB is also involved in embryonic development of murine central nervous and hematopoietic systems. We have investigated RB expression and function in human adult hematopoiesis--i.e., in liquid suspension culture of purified quiescent hematopoietic progenitor cells (HPCs) induced by growth factor stimulus to proliferation and unilinage differentiation/maturation through the erythroid or granulocytic lineage. In the initial HPC differentiation stages, the RB gene is gradually induced at the mRNA and protein level in both erythroid and granulopoietic cultures. In late HPC differentiation and then precursor maturation, RB gene expression is sustained in the erythroid lineage, whereas it is sharply downmodulated in the granulocytic series. Functional studies were performed by treatment of HPC differentiation culture with phosphorothioate antisense oligomer targeting Rb mRNA; coherent with the expression pattern, oligomer treatment of late HPCs causes a dose-dependent and selective inhibition of erythroid colony formation. These observations suggest that the RB gene plays an erythroid- and stage-specific functional role in normal adult hematopoiesis, particularly at the level of late erythroid HPCs.

Loss of Apc heterozygosity and abnormal tissue building in nascent intestinal polyps in mice carrying a truncated Apc gene.

Mutations in the APC (adenomatous polyposis coli) gene appear to be responsible for not only familial adenomatous polyposis but also many sporadic cases of gastrointestinal cancers. Using homologous recombination in mouse embryonic stem cells, we constructed mice that contained a mutant gene encoding a product truncated at a 716 (Apc delta 716). Mendelian transmission of the gene caused most homozygous mice to die in utero before day 8 of gestation. The heterozygotes developed multiple polyps throughout the intestinal tract, mostly in the small intestine. The earliest polyps arose multifocally during the third week after birth, and new polyps continued to appear thereafter. Surprisingly, every nascent polyp consisted of a microadenoma covered with a layer of the normal villous epithelium. These microadenomas originated from single crypts by forming abnormal outpockets into the inner (lacteal) side of the neighboring villi. We carefully dissected such microadenomas from nascent polyps by peeling off the normal epithelium and determined their genotype by PCR: all microadenomas had already lost the wild-type Apc allele, whereas the mutant allele remained unchanged. These results indicate that loss of heterozygosity followed by formation of intravillous microadenomas is responsible for polyposis in Apc delta 716 intestinal mucosa. It is therefore unlikely that the truncated product interacts directly with the wild-type protein and causes the microadenomas by a dominant negative mechanism.

A nova família de distribuições odd log-logística: teoria e aplicações

Neste trabalho, foi proposta uma nova família de distribuições, a qual permite modelar dados de sobrevivência quando a função de risco tem formas unimodal e U (banheira). Ainda, foram consideradas as modificações das distribuições Weibull, Fréchet, half-normal generalizada, log-logística e lognormal. Tomando dados não-censurados e censurados, considerou-se os estimadores de máxima verossimilhança para o modelo proposto, a fim de verificar a flexibilidade da nova família. Além disso, um modelo de regressão locação-escala foi utilizado para verificar a influência de covariáveis nos tempos de sobrevida. Adicionalmente, conduziu-se uma análise de resíduos baseada nos resíduos deviance modificada. Estudos de simulação, utilizando-se de diferentes atribuições dos parâmetros, porcentagens de censura e tamanhos amostrais, foram conduzidos com o objetivo de verificar a distribuição empírica dos resíduos tipo martingale e deviance modificada. Para detectar observações influentes, foram utilizadas medidas de influência local, que são medidas de diagnóstico baseadas em pequenas perturbações nos dados ou no modelo proposto. Podem ocorrer situações em que a suposição de independência entre os tempos de falha e censura não seja válida. Assim, outro objetivo desse trabalho é considerar o mecanismo de censura informativa, baseado na verossimilhança marginal, considerando a distribuição log-odd log-logística Weibull na modelagem. Por fim, as metodologias descritas são aplicadas a conjuntos de dados reais.

Pattern integration in the normal and abnormal human visual system

The processing conducted by the visual system requires the combination of signals that are detected at different locations in the visual field. The processes by which these signals are combined are explored here using psychophysical experiments and computer modelling. Most of the work presented in this thesis is concerned with the summation of contrast over space at detection threshold. Previous investigations of this sort have been confounded by the inhomogeneity in contrast sensitivity across the visual field. Experiments performed in this thesis find that the decline in log contrast sensitivity with eccentricity is bilinear, with an initial steep fall-off followed by a shallower decline. This decline is scale-invariant for spatial frequencies of 0.7 to 4 c/deg. A detailed map of the inhomogeneity is developed, and applied to area summation experiments both by incorporating it into models of the visual system and by using it to compensate stimuli in order to factor out the effects of the inhomogeneity. The results of these area summation experiments show that the summation of contrast over area is spatially extensive (occurring over 33 stimulus carrier cycles), and that summation behaviour is the same in the fovea, parafovea, and periphery. Summation occurs according to a fourth-root summation rule, consistent with a “noisy energy” model. This work is extended to investigate the visual deficit in amblyopia, finding that area summation is normal in amblyopic observers. Finally, the methods used to study the summation of threshold contrast over area are adapted to investigate the integration of coherent orientation signals in a texture. The results of this study are described by a two-stage model, with a mandatory local combination stage followed by flexible global pooling of these local outputs. In each study, the results suggest a more extensive combination of signals in vision than has been previously understood.

Bayesian Inference in Large-scale Problems

Many modern applications fall into the category of "large-scale" statistical problems, in which both the number of observations n and the number of features or parameters p may be large. Many existing methods focus on point estimation, despite the continued relevance of uncertainty quantification in the sciences, where the number of parameters to estimate often exceeds the sample size, despite huge increases in the value of n typically seen in many fields. Thus, the tendency in some areas of industry to dispense with traditional statistical analysis on the basis that "n=all" is of little relevance outside of certain narrow applications. The main result of the Big Data revolution in most fields has instead been to make computation much harder without reducing the importance of uncertainty quantification. Bayesian methods excel at uncertainty quantification, but often scale poorly relative to alternatives. This conflict between the statistical advantages of Bayesian procedures and their substantial computational disadvantages is perhaps the greatest challenge facing modern Bayesian statistics, and is the primary motivation for the work presented here.

Two general strategies for scaling Bayesian inference are considered. The first is the development of methods that lend themselves to faster computation, and the second is design and characterization of computational algorithms that scale better in n or p. In the first instance, the focus is on joint inference outside of the standard problem of multivariate continuous data that has been a major focus of previous theoretical work in this area. In the second area, we pursue strategies for improving the speed of Markov chain Monte Carlo algorithms, and characterizing their performance in large-scale settings. Throughout, the focus is on rigorous theoretical evaluation combined with empirical demonstrations of performance and concordance with the theory.

One topic we consider is modeling the joint distribution of multivariate categorical data, often summarized in a contingency table. Contingency table analysis routinely relies on log-linear models, with latent structure analysis providing a common alternative. Latent structure models lead to a reduced rank tensor factorization of the probability mass function for multivariate categorical data, while log-linear models achieve dimensionality reduction through sparsity. Little is known about the relationship between these notions of dimensionality reduction in the two paradigms. In Chapter 2, we derive several results relating the support of a log-linear model to nonnegative ranks of the associated probability tensor. Motivated by these findings, we propose a new collapsed Tucker class of tensor decompositions, which bridge existing PARAFAC and Tucker decompositions, providing a more flexible framework for parsimoniously characterizing multivariate categorical data. Taking a Bayesian approach to inference, we illustrate empirical advantages of the new decompositions.

Latent class models for the joint distribution of multivariate categorical, such as the PARAFAC decomposition, data play an important role in the analysis of population structure. In this context, the number of latent classes is interpreted as the number of genetically distinct subpopulations of an organism, an important factor in the analysis of evolutionary processes and conservation status. Existing methods focus on point estimates of the number of subpopulations, and lack robust uncertainty quantification. Moreover, whether the number of latent classes in these models is even an identified parameter is an open question. In Chapter 3, we show that when the model is properly specified, the correct number of subpopulations can be recovered almost surely. We then propose an alternative method for estimating the number of latent subpopulations that provides good quantification of uncertainty, and provide a simple procedure for verifying that the proposed method is consistent for the number of subpopulations. The performance of the model in estimating the number of subpopulations and other common population structure inference problems is assessed in simulations and a real data application.

In contingency table analysis, sparse data is frequently encountered for even modest numbers of variables, resulting in non-existence of maximum likelihood estimates. A common solution is to obtain regularized estimates of the parameters of a log-linear model. Bayesian methods provide a coherent approach to regularization, but are often computationally intensive. Conjugate priors ease computational demands, but the conjugate Diaconis--Ylvisaker priors for the parameters of log-linear models do not give rise to closed form credible regions, complicating posterior inference. In Chapter 4 we derive the optimal Gaussian approximation to the posterior for log-linear models with Diaconis--Ylvisaker priors, and provide convergence rate and finite-sample bounds for the Kullback-Leibler divergence between the exact posterior and the optimal Gaussian approximation. We demonstrate empirically in simulations and a real data application that the approximation is highly accurate, even in relatively small samples. The proposed approximation provides a computationally scalable and principled approach to regularized estimation and approximate Bayesian inference for log-linear models.

Another challenging and somewhat non-standard joint modeling problem is inference on tail dependence in stochastic processes. In applications where extreme dependence is of interest, data are almost always time-indexed. Existing methods for inference and modeling in this setting often cluster extreme events or choose window sizes with the goal of preserving temporal information. In Chapter 5, we propose an alternative paradigm for inference on tail dependence in stochastic processes with arbitrary temporal dependence structure in the extremes, based on the idea that the information on strength of tail dependence and the temporal structure in this dependence are both encoded in waiting times between exceedances of high thresholds. We construct a class of time-indexed stochastic processes with tail dependence obtained by endowing the support points in de Haan's spectral representation of max-stable processes with velocities and lifetimes. We extend Smith's model to these max-stable velocity processes and obtain the distribution of waiting times between extreme events at multiple locations. Motivated by this result, a new definition of tail dependence is proposed that is a function of the distribution of waiting times between threshold exceedances, and an inferential framework is constructed for estimating the strength of extremal dependence and quantifying uncertainty in this paradigm. The method is applied to climatological, financial, and electrophysiology data.

The remainder of this thesis focuses on posterior computation by Markov chain Monte Carlo. The Markov Chain Monte Carlo method is the dominant paradigm for posterior computation in Bayesian analysis. It has long been common to control computation time by making approximations to the Markov transition kernel. Comparatively little attention has been paid to convergence and estimation error in these approximating Markov Chains. In Chapter 6, we propose a framework for assessing when to use approximations in MCMC algorithms, and how much error in the transition kernel should be tolerated to obtain optimal estimation performance with respect to a specified loss function and computational budget. The results require only ergodicity of the exact kernel and control of the kernel approximation accuracy. The theoretical framework is applied to approximations based on random subsets of data, low-rank approximations of Gaussian processes, and a novel approximating Markov chain for discrete mixture models.

Data augmentation Gibbs samplers are arguably the most popular class of algorithm for approximately sampling from the posterior distribution for the parameters of generalized linear models. The truncated Normal and Polya-Gamma data augmentation samplers are standard examples for probit and logit links, respectively. Motivated by an important problem in quantitative advertising, in Chapter 7 we consider the application of these algorithms to modeling rare events. We show that when the sample size is large but the observed number of successes is small, these data augmentation samplers mix very slowly, with a spectral gap that converges to zero at a rate at least proportional to the reciprocal of the square root of the sample size up to a log factor. In simulation studies, moderate sample sizes result in high autocorrelations and small effective sample sizes. Similar empirical results are observed for related data augmentation samplers for multinomial logit and probit models. When applied to a real quantitative advertising dataset, the data augmentation samplers mix very poorly. Conversely, Hamiltonian Monte Carlo and a type of independence chain Metropolis algorithm show good mixing on the same dataset.

TRIB2 in normal and malignant hematopoiesis - a transcription factor network

Hematopoiesis is the tightly controlled and complex process in which the entire blood system is formed and maintained by a rare pool of hematopoietic stem cells (HSCs), and its dysregulation results in the formation of leukaemia. TRIB2, a member of the Tribbles family of serine/threonine pseudokinases, has been implicated in a variety of cancers and is a potent murine oncogene that induces acute myeloid leukaemia (AML) in vivo via modulation of the essential myeloid transcription factor CCAAT-enhancer binding protein α (C/EBPα). C/EBPα, which is crucial for myeloid cell differentiation, is commonly dysregulated in a variety of cancers, including AML. Two isoforms of C/EBPα exist - the full-length p42 isoform, and the truncated oncogenic p30 isoform. TRIB2 has been shown to selectively degrade the p42 isoform of C/EBPα and induce p30 expression in AML. In this study, overexpression of the p30 isoform in a bone marrow transplant (BMT) leads to perturbation of myelopoiesis, and in the presence of physiological levels of p42, this oncogene exhibited weak transformative ability. It was also shown by BMT that despite their degradative relationship, expression of C/EBPα was essential for TRIB2 mediated leukaemia. A conditional mouse model was used to demonstrate that oncogenic p30 cooperates with TRIB2 to reduce disease latency, only in the presence of p42. At the molecular level, a ubiquitination assay was used to show that TRIB2 degrades p42 by K48-mediated proteasomal ubiquitination and was unable to ubiquitinate p30. Mutation of a critical lysine residue in the C-terminus of C/EBPα abrogated TRIB2 mediated C/EBPα ubiquitination suggesting that this site, which is frequently mutated in AML, is the site at which TRIB2 mediates its degradative effects. The TRIB2-C/EBPα axis was effectively targeted by proteasome inhibition. AML is a very difficult disease to target therapeutically due to the extensive array of chromosomal translocations and genetic aberrations that contribute to the disease. The cell from which a specific leukaemia arises, or leukaemia initiating cell (LIC), can affect the phenotype and chemotherapeutic response of the resultant disease. The LIC has been elucidated for some common oncogenes but it is unknown for TRIB2. The data presented in this thesis investigate the ability of the oncogene TRIB2 to transform hematopoietic stem and progenitor cells in vitro and in vivo. TRIB2 overexpression conferred in vitro serially replating ability to all stem and progenitor cells studied. Upon transplantation, only TRIB2 overexpressing HSCs and granulocyte/macrophage progenitors (GMPs) resulted in the generation of leukaemia in vivo. TRIB2 induced a mature myeloid leukaemia from the GMP, and a mixed lineage leukaemia from the HSC. As such the role of TRIB2 in steady state hematopoiesis was also explored using a Trib2-/- mouse and it was determined that loss of Trib2 had no effect on lineage distribution in the hematopoietic compartment under steady-state conditions. The process of hematopoiesis is controlled by a host of lineage restricted transcription factors. Recently members of the Nuclear Factor 1 family of transcription factors (NFIA, NFIB, NFIC and NFIX) have been implicated in hematopoiesis. Little is known about the role of NFIX in lineage determination. Here we describe a novel role for NFIX in lineage fate determination. In human and murine datasets the expression of Nfix was shown to decrease as cells differentiated along the lymphoid pathway. NFIX overexpression resulted in enhanced myelopoiesis in vivo and in vitro and a block in B cell development at the pre-pro-B cell stage. Loss of NFIX resulted in disruption of myeloid and lymphoid differentiation in vivo. These effects on stem and progenitor cell fate correlated with changes in the expression levels of key transcription factors involved in hematopoietic differentiation including a 15-fold increase in Cebpa expression in Nfix overexpressing cells. The data presented support a role for NFIX as an important transcription factor influencing hematopoietic lineage specification. The identification of NFIX as a novel transcription factor influencing lineage determination will lead to further study of its role in hematopoiesis, and contribute to a better understanding of the process of differentiation. Elucidating the relationship between TRIB2 and C/EBPα not only impacts on our understanding of the pathophysiology of AML but is also relevant in other cancer types including lung and liver cancer. Thus in summary, the data presented in this thesis provide important insights into key areas which will facilitate the development of future therapeutic approaches in cancer treatment.

Angiogenic Effects Of Cryosurgery With Liquid Nitrogen On The Normal Skin Of Rats, Through Morphometric Study.

Cryosurgery is an efficient therapeutic technique used to treat benign and malignant cutaneous diseases. The primary active mechanism of cryosurgery is related to vascular effects on treated tissue. After a cryosurgical procedure, exuberant granulation tissue is formed at the injection site, probably as a result of angiogenic stimulation of the cryogen and inflammatory response, particularly in endothelial cells. To evaluate the angiogenic effects of freezing, as part of the phenomenon of healing rat skin subjected to previous injury. Two incisions were made in each of the twenty rats, which were divided randomly into two groups of ten. After 3 days, cryosurgery with liquid nitrogen was performed in one of incisions. The rats' samples were then collected, cut and stained to conduct histopathological examination, to assess the local angiogenesis in differing moments and situations. It was possible to demonstrate that cryosurgery, in spite of promoting cell death and accentuated local inflammation soon after its application, induces quicker cell proliferation in the affected tissue and maintenance of this rate in a second phase, than in tissue healing without this procedure. These findings, together with the knowledge that there is a direct relationship between mononuclear cells and neovascularization (the development of a rich system of new vessels in injury caused by cold), suggest that cryosurgery possesses angiogenic stimulus, even though complete healing takes longer to occur. The significance level for statistical tests was 5% (p<0,05).

Kinesiographic Study Of Masticatory Movements In Denture Wearers With Normal And Resorbed Denture-bearing Areas.

An unfavorable denture-bearing area could compromise denture retention and stability, limit mastication, and possibly alter masticatory motion. The purpose of this study was to evaluate the masticatory movements of denture wearers with normal and resorbed denture-bearing areas. Completely edentulous participants who received new complete dentures were selected and divided into 2 groups (n=15) according to the condition of their denture-bearing areas as classified by the Kapur method: a normal group (control) (mean age, 65.9 ± 7.8 years) and a resorbed group (mean age, 70.2 ± 7.6 years). Masticatory motion was recorded and analyzed with a kinesiographic device. The patients masticated peanuts and Optocal. The masticatory movements evaluated were the durations of opening, closing, and occlusion; duration of the masticatory cycle; maximum velocities and angles of opening and closing; total masticatory area; and amplitudes of the masticatory cycle. The data were analyzed by 2-way ANOVA and the Tukey honestly significant difference post hoc test (α=.05). The group with a resorbed denture-bearing area had a smaller total masticatory area in the frontal plane and shorter horizontal masticatory amplitude than the group with normal denture-bearing area (P<.05). Denture wearers with resorbed denture-bearing areas showed reduced jaw motion during mastication.

Censored Linear Regression Models For Irregularly Observed Longitudinal Data Using The Multivariate-t Distribution.

In acquired immunodeficiency syndrome (AIDS) studies it is quite common to observe viral load measurements collected irregularly over time. Moreover, these measurements can be subjected to some upper and/or lower detection limits depending on the quantification assays. A complication arises when these continuous repeated measures have a heavy-tailed behavior. For such data structures, we propose a robust structure for a censored linear model based on the multivariate Student's t-distribution. To compensate for the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is employed. An efficient expectation maximization type algorithm is developed for computing the maximum likelihood estimates, obtaining as a by-product the standard errors of the fixed effects and the log-likelihood function. The proposed algorithm uses closed-form expressions at the E-step that rely on formulas for the mean and variance of a truncated multivariate Student's t-distribution. The methodology is illustrated through an application to an Human Immunodeficiency Virus-AIDS (HIV-AIDS) study and several simulation studies.

Tubular Variant Of Basal Cell Adenoma Shares Immunophenotypical Features With Normal Intercalated Ducts And Is Closely Related To Intercalated Duct Lesions Of Salivary Gland.

The morphological criteria for identification of intercalated duct lesions (IDLs) of salivary glands have been defined recently. It has been hypothesised that IDL could be a precursor of basal cell adenoma (BCA). BCAs show a variety of histological patterns, and the tubular variant is the one that presents the strongest resemblance with IDLs. The aim of this study was to analyse the morphological and immunohistochemical profiles of IDLs and BCAs classified into tubular and non-tubular subtypes, to determine whether or not IDL and tubular BCA represent distinct entities. Eight IDLs, nine tubular BCAs and 19 non-tubular BCAs were studied. All tubular BCAs contained IDL-like areas, which represented 20-70% of the tumour. In non-tubular BCA, IDL-like areas were occasional and small (<5%). One patient presented IDLs, tubular BCAs and IDL/tubular BCA combined lesions. Luminal ductal cells of IDLs and tubular BCAs exhibited positivity for CK7, lysozyme, S100 and DOG1. In the non-tubular BCA group, few luminal cells exhibited such an immunoprofile; they were mainly CK14-positive. Basal/myoepithelial cells of IDLs, tubular BCAs and non-tubular BCAs were positive for CK14, calponin, α-SMA and p63; they were more numerous in BCA lesions. IDL, tubular BCA and non-tubular BCA form a continuum of lesions in which IDLs are related closely to tubular BCA. In both, the immunoprofile of luminal and myoepithelial cells recapitulates the normal intercalated duct. The difference between the adenoma-like subset of IDLs and tubular BCA rests mainly on the larger numbers of myoepithelial cells in the latter. Our findings indicate that at least some BCAs can arise via IDLs.