Diet alters age-related remodeling of aortic collagen in mice susceptible to atherosclerosis.

Vascular cells restructure extracellular matrix in response to aging or changes in mechanical loading. Here, we characterized collagen architecture during age-related aortic remodeling in atherosclerosis-prone mice. We hypothesized that changes in collagen fiber orientation reflect an altered balance between passive and active forces acting on the arterial wall. We examined two factors that can alter this balance, endothelial dysfunction and reduced smooth muscle cell (SMC) contractility. Collagen fiber organization was visualized by second-harmonic generation microscopy in aortic adventitia of apolipoprotein E (apoE) knockout (KO) mice at 6 wk and 6 mo of age on a chow diet and at 7.5 mo of age on a Western diet (WD), using image analysis to yield mean fiber orientation. Adventitial collagen fibers became significantly more longitudinally oriented with aging in apoE knockout mice on chow diet. Conversely, fibers became more circumferentially oriented with aging in mice on WD. Total collagen content increased significantly with age in mice fed WD. We compared expression of endothelial nitric oxide synthase and acetylcholine-mediated nitric oxide release but found no evidence of endothelial dysfunction in older mice. Time-averaged volumetric blood flow in all groups showed no significant changes. Wire myography of aortic rings revealed decreases in active stress generation with age that were significantly exacerbated in WD mice. We conclude that the aorta displays a distinct remodeling response to atherogenic stimuli, indicated by altered collagen organization. Collagen reorganization can occur in the absence of altered hemodynamics and may represent an adaptive response to reduced active stress generation by vascular SMCs.NEW & NOTEWORTHY The following major observations were made in this study: 1) aortic adventitial collagen fibers become more longitudinally oriented with aging in apolipoprotein E knockout mice fed a chow diet; 2) conversely, adventitial collagen fibers become more circumferentially oriented with aging in apoE knockout mice fed a high-fat diet; 3) adventitial collagen content increases significantly with age in mice on a high-fat diet; 4) these alterations in collagen organization occur largely in the absence of hemodynamic changes; and 5) circumferential reorientation of collagen is associated with decreased active force generation (contractility) in aged mice on a high-fat diet.

Transforming Growth Factor Beta3 is Required for Cardiovascular Development.

Transforming growth factor beta3 (TGFB3) gene mutations in patients of arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVD1) and Loeys-Dietz syndrome-5 (LDS5)/Rienhoff syndrome are associated with cardiomyopathy, cardiac arrhythmia, cardiac fibrosis, cleft palate, aortic aneurysms, and valvular heart disease. Although the developing heart of embryos express Tgfb3, its overarching role remains unclear in cardiovascular development and disease. We used histological, immunohistochemical, and molecular analyses of Tgfb3-/- fetuses and compared them to wildtype littermate controls. The cardiovascular phenotypes were diverse with approximately two thirds of the Tgfb3-/- fetuses having one or more cardiovascular malformations, including abnormal ventricular myocardium (particularly of the right ventricle), outflow tract septal and alignment defects, abnormal aortic and pulmonary trunk walls, and thickening of semilunar and/or atrioventricular valves. Ventricular septal defects (VSD) including the perimembranous VSDs were observed in Tgfb3-/- fetuses with myocardial defects often accompanied by the muscular type VSD. In vitro studies using TGFß3-deficient fibroblasts in 3-D collagen lattice formation assays indicated that TGFß3 was required for collagen matrix reorganization. Biochemical studies indicated the 'paradoxically' increased activation of canonical (SMAD-dependent) and noncanonical (MAP kinase-dependent) pathways. TGFß3 is required for cardiovascular development to maintain a balance of canonical and noncanonical TGFß signaling pathways.

Both diet and Helicobacter pylori infection contribute to atherosclerosis in pre- and postmenopausal cynomolgus monkeys.

A number of viruses and bacterial species have been implicated as contributors to atherosclerosis, potentially providing novel pathways for prevention. Epidemiological studies examining the association between Helicobacter pylori and cardiovascular disease have yielded variable results and no studies have been conducted in nonhuman primates. In this investigation, we examined the relationship between H. pylori infection and atherosclerosis development in socially housed, pre- and postmenopausal cynomolgus macaques consuming human-like diets. Ninety-four premenopausal cynomolgus monkeys (Macaca fascicularis) were fed for 36 months an atherogenic diet deriving its protein from either casein lactalbumin(CL) or high isoflavone soy (SOY). Animals were then ovariectomized and fed either the same or the alternate diet for an additional 36 months. Iliac artery biopsies were obtained at the time of ovariectomy and iliac and coronary artery sections were examined at the end of the study. Evidence of H. pylori infection was found in 64% of the monkeys and 46% of animals had live H. pylori within coronary atheromas as determined by mRNA-specific in situ hybridization. There was a significant linear relationship between the densities of gastric and atheroma organisms. Helicobactor pylori infection correlated with increased intimal plaque area and thickness at both the premenopausal and postmenopausal time points and regardless of diet (p< 0.01), although animals consuming the SOY diet throughout had the least amount of atherosclerosis. Additionally, plasma lipid profiles, intimal collagen accumulation, ICAM-1, and plaque macrophage densities were adversely affected by H. pylori infection among animals consuming the CL diet, while the SOY diet had the opposite effect. Plaque measurements were more highly associated with the densities of cagA-positive H. pylori within coronary atheromas than with the densities of gastric organisms, whereas plasma lipid changes were associated with H. pylori infection, but not cagA status. This study provides strong evidence that live H. pylori infects atheromas, exacerbates atherosclerotic plaque development, and alters plasma lipid profiles independently of diet or hormonal status. Finally, socially subordinate animals relative to their dominant counterparts had a greater prevalence of H. pylori, suggesting a stress effect. The results indicate that early H. pylori eradication could prevent or delay development of cardiovascular disease.

Loss of Function of Phosphodiesterase 11A4 Shows that Recent and Remote Long-Term Memories Can Be Uncoupled.

Systems consolidation is a process by which memories initially require the hippocampus for recent long-term memory (LTM) but then become increasingly independent of the hippocampus and more dependent on the cortex for remote LTM. Here, we study the role of phosphodiesterase 11A4 (PDE11A4) in systems consolidation. PDE11A4, which degrades cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP), is preferentially expressed in neurons of CA1, the subiculum, and the adjacently connected amygdalohippocampal region. In male and female mice, deletion of PDE11A enhances remote LTM for social odor recognition and social transmission of food preference (STFP) despite eliminating or silencing recent LTM for those same social events. Measurement of a surrogate marker of neuronal activation (i.e., Arc mRNA) suggests the recent LTM deficits observed in Pde11 knockout mice correspond with decreased activation of ventral CA1 relative to wild-type littermates. In contrast, the enhanced remote LTM observed in Pde11a knockout mice corresponds with increased activation and altered functional connectivity of anterior cingulate cortex, frontal association cortex, parasubiculum, and the superficial layer of medial entorhinal cortex. The apparent increased neural activation observed in prefrontal cortex of Pde11a knockout mice during remote LTM retrieval may be related to an upregulation of the N-methyl-D-aspartate receptor subunits NR1 and NR2A. Viral restoration of PDE11A4 to vCA1 alone is sufficient to rescue both the LTM phenotypes and upregulation of NR1 exhibited by Pde11a knockout mice. Together, our findings suggest remote LTM can be decoupled from recent LTM, which may have relevance for cognitive deficits associated with aging, temporal lobe epilepsy, or transient global amnesia.

Treatment effect on ordinal functional outcome using piecewise multistate Markov model with unobservable baseline: an application to the modified Rankin scale.

In clinical trials, longitudinally assessed ordinal outcomes are commonly dichotomized and only the final measure is used for primary analysis, partly for ease of clinical interpretation. Dichotomization of the ordinal scale and failure to utilize the repeated measures can reduce statistical power. Additionally, in certain emergent settings, the same measure cannot be assessed at baseline prior to treatment. For such a data set, a piecewise-constant multistate Markov model that incorporates a latent model for the unobserved baseline measure is proposed. These models can be useful in analyzing disease history data and are advantageous in clinical applications where a disease process naturally moves through increasing stages of severity. Two examples are provided using acute stroke clinical trials data. Conclusions drawn in this article are consistent with those from the primary analysis for treatment effect in both of the motivating examples. Use of these models allows for a more refined examination of treatment effect and describes the movement between health states from baseline to follow-up visits which may provide more clinical insight into the treatment effect.

Axonal G3BP1 stress granule protein limits axonal mRNA translation and nerve regeneration.

Critical functions of intra-axonally synthesized proteins are thought to depend on regulated recruitment of mRNA from storage depots in axons. Here we show that axotomy of mammalian neurons induces translation of stored axonal mRNAs via regulation of the stress granule protein G3BP1, to support regeneration of peripheral nerves. G3BP1 aggregates within peripheral nerve axons in stress granule-like structures that decrease during regeneration, with a commensurate increase in phosphorylated G3BP1. Colocalization of G3BP1 with axonal mRNAs is also correlated with the growth state of the neuron. Disrupting G3BP functions by overexpressing a dominant-negative protein activates intra-axonal mRNA translation, increases axon growth in cultured neurons, disassembles axonal stress granule-like structures, and accelerates rat nerve regeneration in vivo.

Assessing type I error and power of multistate Markov models for panel data-A simulation study.

Ordinal outcomes collected at multiple follow-up visits are common in clinical trials. Sometimes, one visit is chosen for the primary analysis and the scale is dichotomized amounting to loss of information. Multistate Markov models describe how a process moves between states over time. Here, simulation studies are performed to investigate the type I error and power characteristics of multistate Markov models for panel data with limited non-adjacent state transitions. The results suggest that the multistate Markov models preserve the type I error and adequate power is achieved with modest sample sizes for panel data with limited non-adjacent state transitions.

Comparison of multistate Markov modeling with contemporary outcomes in a reanalysis of the NINDS tissue plasminogen activator for acute ischemic stroke treatment trial.

Historically, ordinal measures of functional outcome have been dichotomized for the primary analysis in acute stroke therapy trials. A number of alternative methods to analyze the ordinal scales have been proposed, with an emphasis on maintaining the ordinal structure as much as possible. In addition, despite the availability of longitudinal outcome data in many trials, the primary analysis consists of a single endpoint. Inclusion of information about the course of disease progression allows for a more complete understanding of the treatment effect. Multistate Markov modeling, which allows for the full ordinal scale to be analyzed longitudinally, is compared with previously suggested analytic techniques for the ordinal modified Rankin Scale (dichotomous-logistic regression; continuous-linear regression; ordinal- shift analysis, proportional odds model, partial proportional odds model, adjacent categories logit model; sliding dichotomy; utility weights; repeated measures). In addition, a multistate Markov model utilizing an estimate of the unobservable baseline outcome derived from principal component analysis is compared Each of the methods is used to re-analyze the National Institute of Neurological Diseases and Stroke tissue plasminogen activator study which showed a consistently significant effect of tissue plasminogen activator using a global test of four dichotomized outcomes in the analysis of the primary outcome at 90 days post-stroke in the primary analysis. All methods detected a statistically significant treatment effect except the multistate Markov model without predicted baseline (p = 0.053). This provides support for the use of the estimated baseline in the multistate Markov model since the treatment effect is able to be detected with its inclusion. Multistate Markov modeling allows for a more refined examination of treatment effect and describes the movement between modified Rankin Scale states over time which may provide more clinical insight into the treatment effect. Multistate Markov models are feasible and desirable in describing treatment effect in acute stroke therapy trials.

Model Selection and Estimation with Quantal-Response Data in Benchmark Risk Assessment.

This article describes several approaches for estimating the benchmark dose (BMD) in a risk assessment study with quantal dose-response data and when there are competing model classes for the dose-response function. Strategies involving a two-step approach, a model-averaging approach, a focused-inference approach, and a nonparametric approach based on a PAVA-based estimator of the dose-response function are described and compared. Attention is raised to the perils involved in data "double-dipping" and the need to adjust for the model-selection stage in the estimation procedure. Simulation results are presented comparing the performance of five model selectors and eight BMD estimators. An illustration using a real quantal-response data set from a carcinogenecity study is provided.

Multinomial probit Bayesian additive regression trees.

This article proposes multinomial probit Bayesian additive regression trees (MPBART) as a multinomial probit extension of BART - Bayesian additive regression trees. MPBART is flexible to allow inclusion of predictors that describe the observed units as well as the available choice alternatives. Through two simulation studies and four real data examples, we show that MPBART exhibits very good predictive performance in comparison to other discrete choice and multiclass classification methods. To implement MPBART, the R package mpbart is freely available from CRAN repositories.

Comparison of Aortic Collagen Fiber Angle Distribution in Mouse Models of Atherosclerosis Using Second-Harmonic Generation (SHG) Microscopy.

Characterization of collagen fiber angle distribution throughout the blood vessel wall provides insight into the mechanical behavior of healthy and diseased arteries and their capacity to remodel. Atherosclerotic plaque contributes to the overall mechanical behavior, yet little is known experimentally about how collagen fiber orientation is influenced by atherogenesis. We hypothesized that atherosclerotic lesion development, and the factors contributing to lesion development, leads to a shift in collagen fiber angles within the aorta. Second-harmonic generation microscopy was used to visualize the three-dimensional organization of collagen throughout the aortic wall and to examine structural differences in mice maintained on high-fat Western diet versus age-matched chow diet mice in a model of atherosclerosis. Image analysis was performed on thoracic and abdominal sections of the aorta from each mouse to determine fiber orientation, with the circumferential (0°) and blood flow directions (axial ±90°) as the two reference points. All measurements were used in a multiple regression analysis to determine the factors having a significant influence on mean collagen fiber angle. We found that mean absolute angle of collagen fibers is 43° lower in Western diet mice compared with chow diet mice. Mice on a chow diet have a mean collagen fiber angle of ±63°, whereas mice on a Western diet have a more circumferential fiber orientation (~20°). This apparent shift in absolute angle coincides with the development of extensive aortic atherosclerosis, suggesting that atherosclerotic factors contribute to collagen fiber angle orientation.

Sojourning with the Homogeneous Poisson Process.

In this pedagogical article, distributional properties, some surprising, pertaining to the homogeneous Poisson process (HPP), when observed over a possibly random window, are presented. Properties of the gap-time that covered the termination time and the correlations among gap-times of the observed events are obtained. Inference procedures, such as estimation and model validation, based on event occurrence data over the observation window, are also presented. We envision that through the results in this paper, a better appreciation of the subtleties involved in the modeling and analysis of recurrent events data will ensue, since the HPP is arguably one of the simplest among recurrent event models. In addition, the use of the theorem of total probability, Bayes theorem, the iterated rules of expectation, variance and covariance, and the renewal equation could be illustrative when teaching distribution theory, mathematical statistics, and stochastic processes at both the undergraduate and graduate levels. This article is targeted towards both instructors and students.

Asymptotics for a Class of Dynamic Recurrent Event Models.

Asymptotic properties, both consistency and weak convergence, of estimators arising in a general class of dynamic recurrent event models are presented. The class of models take into account the impact of interventions after each event occurrence, the impact of accumulating event occurrences, the induced informative and dependent right-censoring mechanism due to the data-accrual scheme, and the effect of covariate processes on the recurrent event occurrences. The class of models subsumes as special cases many of the recurrent event models that have been considered in biostatistics, reliability, and in the social sciences. The asymptotic properties presented have the potential of being useful in developing goodness-of-fit and model validation procedures, confidence intervals and confidence bands constructions, and hypothesis testing procedures for the finite- and infinite-dimensional parameters of a general class of dynamic recurrent event models, albeit the models without frailties.

Classes of Multiple Decision Functions Strongly Controlling FWER and FDR.

Two general classes of multiple decision functions, where each member of the first class strongly controls the family-wise error rate (FWER), while each member of the second class strongly controls the false discovery rate (FDR), are described. These classes offer the possibility that optimal multiple decision functions with respect to a pre-specified Type II error criterion, such as the missed discovery rate (MDR), could be found which control the FWER or FDR Type I error rates. The gain in MDR of the associated FDR-controlling procedure relative to the well-known Benjamini-Hochberg (BH) procedure is demonstrated via a modest simulation study with gamma-distributed component data. Such multiple decision functions may have the potential of being utilized in multiple testing, specifically in the analysis of high-dimensional data sets.

Compound p-value statistics for multiple testing procedures.

Many multiple testing procedures make use of the p-values from the individual pairs of hypothesis tests, and are valid if the p-value statistics are independent and uniformly distributed under the null hypotheses. However, it has recently been shown that these types of multiple testing procedures are inefficient since such p-values do not depend upon all of the available data. This paper provides tools for constructing compound p-value statistics, which are those that depend upon all of the available data, but still satisfy the conditions of independence and uniformity under the null hypotheses. Several examples are provided, including a class of compound p-value statistics for testing location shifts. It is demonstrated, both analytically and through simulations, that multiple testing procedures tend to reject more false null hypotheses when applied to these compound p-values rather than the usual p-values, and at the same time still guarantee the desired type I error rate control. The compound p-values are used to analyze a real microarray data set and allow for more rejected null hypotheses.

Nonparametric estimation with recurrent competing risks data.

Nonparametric estimators of component and system life distributions are developed and presented for situations where recurrent competing risks data from series systems are available. The use of recurrences of components' failures leads to improved efficiencies in statistical inference, thereby leading to resource-efficient experimental or study designs or improved inferences about the distributions governing the event times. Finite and asymptotic properties of the estimators are obtained through simulation studies and analytically. The detrimental impact of parametric model misspecification is also vividly demonstrated, lending credence to the virtue of adopting nonparametric or semiparametric models, especially in biomedical settings. The estimators are illustrated by applying them to a data set pertaining to car repairs for vehicles that were under warranty.

Information-theoretic model-averaged benchmark dose analysis in environmental risk assessment.

An important objective in environmental risk assessment is estimation of minimum exposure levels, called Benchmark Doses (BMDs), that induce a pre-specified Benchmark Response (BMR) in a dose-response experiment. In such settings, representations of the risk are traditionally based on a specified parametric model. It is a well-known concern, however, that existing parametric estimation techniques are sensitive to the form employed for modeling the dose response. If the chosen parametric model is in fact misspecified, this can lead to inaccurate low-dose inferences. Indeed, avoiding the impact of model selection was one early motivating issue behind development of the BMD technology. Here, we apply a frequentist model averaging approach for estimating benchmark doses, based on information-theoretic weights. We explore how the strategy can be used to build one-sided lower confidence limits on the BMD, and we study the confidence limits' small-sample properties via a simulation study. An example from environmental carcinogenicity testing illustrates the calculations. It is seen that application of this information-theoretic, model averaging methodology to benchmark analysis can improve environmental health planning and risk regulation when dealing with low-level exposures to hazardous agents.

Parametric Estimation in a Recurrent Competing Risks Model.

A resource-efficient approach to making inferences about the distributional properties of the failure times in a competing risks setting is presented. Efficiency is gained by observing recurrences of the competing risks over a random monitoring period. The resulting model is called the recurrent competing risks model (RCRM) and is coupled with two repair strategies whenever the system fails. Maximum likelihood estimators of the parameters of the marginal distribution functions associated with each of the competing risks and also of the system lifetime distribution function are presented. Estimators are derived under perfect and partial repair strategies. Consistency and asymptotic properties of the estimators are obtained. The estimation methods are applied to a data set of failures for cars under warranty. Simulation studies are used to ascertain the small sample properties and the efficiency gains of the resulting estimators.

Bayes multiple decision functions.

This paper deals with the problem of simultaneously making many (M) binary decisions based on one realization of a random data matrix X. M is typically large and X will usually have M rows associated with each of the M decisions to make, but for each row the data may be low dimensional. Such problems arise in many practical areas such as the biological and medical sciences, where the available dataset is from microarrays or other high-throughput technology and with the goal being to decide which among of many genes are relevant with respect to some phenotype of interest; in the engineering and reliability sciences; in astronomy; in education; and in business. A Bayesian decision-theoretic approach to this problem is implemented with the overall loss function being a cost-weighted linear combination of Type I and Type II loss functions. The class of loss functions considered allows for use of the false discovery rate (FDR), false nondiscovery rate (FNR), and missed discovery rate (MDR) in assessing the quality of decision. Through this Bayesian paradigm, the Bayes multiple decision function (BMDF) is derived and an efficient algorithm to obtain the optimal Bayes action is described. In contrast to many works in the literature where the rows of the matrix X are assumed to be stochastically independent, we allow a dependent data structure with the associations obtained through a class of frailty-induced Archimedean copulas. In particular, non-Gaussian dependent data structure, which is typical with failure-time data, can be entertained. The numerical implementation of the determination of the Bayes optimal action is facilitated through sequential Monte Carlo techniques. The theory developed could also be extended to the problem of multiple hypotheses testing, multiple classification and prediction, and high-dimensional variable selection. The proposed procedure is illustrated for the simple versus simple hypotheses setting and for the composite hypotheses setting through simulation studies. The procedure is also applied to a subset of a microarray data set from a colon cancer study.

Characterization of the bipartite degron that regulates ubiquitin-independent degradation of thymidylate synthase.

TS (thymidylate synthase) is a key enzyme in the de novo biosynthesis of dTMP, and is indispensable for DNA replication. Previous studies have shown that intracellular degradation of the human enzyme [hTS (human thymidylate synthase)] is mediated by the 26S proteasome, and occurs in a ubiquitin-independent manner. Degradation of hTS is governed by a degron that is located at the polypeptide's N-terminus that is capable of promoting the destabilization of heterologous proteins to which it is attached. The hTS degron is bipartite, consisting of two subdomains: an IDR (intrinsically disordered region) that is highly divergent among mammalian species, followed by a conserved amphipathic α-helix (designated hA). In the present report, we have characterized the structure and function of the hTS degron in more detail. We have conducted a bioinformatic analysis of interspecies sequence variation exhibited by the IDR, and find that its hypervariability is not due to diversifying (or positive) selection; rather, it has been subjected to purifying (or negative) selection, although the intensity of such selection is relaxed or weakened compared with that exerted on the rest of the molecule. In addition, we have verified that both subdomains of the hTS degron are required for full activity. Furthermore, their co-operation does not necessitate that they are juxtaposed, but is maintained when they are physically separated. Finally, we have identified a 'cryptic' degron at the C-terminus of hTS, which is activated by the N-terminal degron and appears to function only under certain circumstances; its role in TS metabolism is not known.