A stochastic spatially structured epidemic model with diffusive processes

We developed a stochastic lattice model to describe the vector-borne disease (like yellow fever or dengue). The model is spatially structured and its dynamical rules take into account the diffusion of vectors. We consider a bipartite lattice, forming a sub-lattice of human and another occupied by mosquitoes. At each site of lattice we associate a stochastic variable that describes the occupation and the health state of a single individual (mosquito or human). The process of disease transmission in the human population follows a similar dynamic of the Susceptible-Infected-Recovered model (SIR), while the disease transmission in the mosquito population has an analogous dynamic of the Susceptible-Infected-Susceptible model (SIS) with mosquitos diffusion. The occurrence of an epidemic is directly related to the conditional probability of occurrence of infected mosquitoes (human) in the presence of susceptible human (mosquitoes) on neighborhood. The probability of diffusion of mosquitoes can facilitate the formation of pairs Susceptible-Infected enabling an increase in the size of the epidemic. Using an asynchronous dynamic update, we study the disease transmission in a population initially formed by susceptible individuals due to the introduction of a single mosquito (human) infected. We find that this model exhibits a continuous phase transition related to the existence or non-existence of an epidemic. By means of mean field approximations and Monte Carlo simulations we investigate the epidemic threshold and the phase diagram in terms of the diffusion probability and the infection probability.

Conditional and transgenic mouse models as tools to study the role of TGFbeta, BMP signaling in skeletal development

Die TGFbeta/BMP Signaltransduktionskaskade ist wichtig für viele Entwicklungsprozesse fast aller embryonaler sowie extraembryonaler Gewebe und sie ist ebenso essentiell bei der Aufrechterhaltung der Homöostase im adulten Organismus. In vielen Mausmodellen und Zellkulturversuchen wurde gezeigt, dass Liganden dieses Signalweges in verschiedene Stadien der Knorpel- und Knochenentwicklung involviert sind. BMPs sind beispielsweise maßgeblich an der frühen Kondensation und Bildung des Knorpels und später an Proliferation und Hypertrophie der Chondrozyten beteiligt. BMPs können ektopisch Knochenbildung auslösen und das Expressionsmuster der Liganden und spezifischen Rezeptoren in der Wachstumsfuge lässt auf eine wichtige Rolle der BMPs in der Wachstumsfuge schließen. Der gezielte knock out der BMP-Rezeptoren Bmpr1a und Bmpr1b in proliferierenden Chondrozyten führt zur Ausbildung einer generellen Chondrodysplasie. Smad1, Smad5 und Smad8 sind die Mediatoren der BMP-Signalkaskade. Im Rahmen der vorliegenden Arbeit sollte die Rolle und Funktion der Smad1- und Smad5-Proteine in der Wachstumsfuge untersucht werden. Hierzu wurden konditionale Smad1-knock out-Mäuse mit einer transgenen Mauslinie gekreuzt, die die Cre-Rekombinase spezifisch in proliferierenden Chondrozyten exprimiert. Diese Mäuse wurden mit und ohne heterozygotem Smad5-Hintergrund charakterisiert. Bei einem knock out von Smad1 allein konnte ein leichte Verkürzung der Wachstumsfuge beobachtet werden, wobei prähypertrophe und hypertrophe Zone gleichermaßen betroffen waren. Dieser Phänotyp war verstärkt in Mäusen mit zusätzlichem heterozygotem Smad5-Hintergrund. Eine Verringerung der Proliferationsrate konnte zusammen mit einer verminderten Ihh-Expression nachgewiesen werden. Zusätzlich konnte anhand von Röntgenaufnahmen eine Dysorganisation der nasalen Region und ein fehlendes nasales Septum beobachtet werden. Produktion und Mineralisation der extrazellulären Matrix waren nicht beeinträchtigt. Um die Rolle der BMP- und TGFbeta-Signalkaskaden während der endochondralen Ossifikation zu vergleichen, wurden transgene Mäuse generiert, in denen die TGFbeta-Signalkaskade spezifisch in proliferierenden Chondrozyten gestört war. Zwei Mauslinien, die ähnliche Phänotypen zeigten, wurden untersucht. Esl1 ist ein TGFbeta-bindendes Protein, von dem man annimmt, dass es die TGFbeta-Signalkaskade inhibieren kann. Esl1-knock out-Mäuse sind kleiner als Wildtypmäuse und die Überexpression von Esl1 in proliferierenden Chondrozyten führt zu einer Verlängerung der Wachstumsfuge und einer verstärkten Proliferationsrate. Knorpelmarker, wie Col2a1 und Sox9 sind in diesen Mäusen herunterreguliert, während Col10a1 und Ihh als Marker für die hypertrophe und prähypertrophe Zone herunterreguliert waren. Dies führt zu der Annahme, dass mehr Zellen in die terminale Differenzierung eintreten. Bei transgenen Mäusen, in denen ein dominant-negativer (dn) TGFbeta-Rezeptor in proliferierenden Chondrozyten überexprimiert wurde, konnte eine verlängerte prähypertrophe Zone, eine erhöhte Ihh-Expression, sowie eine verstärkte Proliferationsrate beobachtet werden. Zusätzlich konnte in homozygoten Tieren ein craniofacialer Phänotyp beschrieben werden, der zu Problemen bei der Nahrungsaufnahme und damit zu einer starken Wachstumsbeeinträchtigung führte. Die BMP- und TGFbeta-Signalkaskaden haben möglicherweise antagonistische Effekte in der Wachstumsfuge. Während der Ausfall von BMP in proliferierenden Chondrozyten aufgrund einer gesunkenen Proliferationsrate zu einer Verkürzung der Wachstumsfuge führte, kann man in Mäusen mit einer Störung der TGFbeta-Signalkaskade eine verstärkte Proliferation in einer daher verlängerten Wachstumsfuge beobachten. Ein weiteres Ziel dieser Arbeit war die Generation einer transgenen Mauslinie, die die Cre-Rekombinase spezifisch in hypertrophen Chondrozyten exprimiert. Promoterstudien mit transgenen Mäusen weisen darauf hin, dass ein putatives AP1-Element, etwa 4 kb vor dem ersten Exon des Col10a1 gelegen, wichtig für die spezifische Expression in hypertrophen Chondrozyten ist. Ein Konstrukt, dass vier Kopien dieses Elements und den basalen Promoter enthält, wurde benutzt, um die Cre-Rekombinase spezifisch zu exprimieren. Diese Mauslinie befindet sich in der Testphase und erste Daten deuten auf eine spezifische Expression der Cre-Rekombinase in hypertrophen Chondrozyten hin.

Effect of loss of CDKL5 on brain development in a new Cdkl5 knockout mouse model

Rett's Syndrome (RTT) is a severe neurodevelopmental disorder, characterized by cognitive disability that appears in the first months/years of life. Recently, mutations in the X-linked cyclin-dependent kinase-like 5 (CDKL5) gene have been detected in RTT patients characterized by early-onset seizures. CDKL5 is highly expressed in the brain starting from early postnatal stages to adulthood, suggesting the importance of this kinase for proper brain maturation and function. However, the role/s of CDKL5 in brain development and the molecular mechanisms whereby CDKL5 exerts its effects are still largely unknown. In order to characterize the role of CDKL5 on brain development, we created a mice carrying a targeted conditional knockout allele of Cdkl5. A first behavioral characterization shows that Cdkl5 knockout mice recapitulate several features that mimic the clinical features described in CDKL5 patients and are a useful tool to investigate phenotypic and functional aspects of Cdkl5 loss. We used the Cdkl5 knockout mouse model to dissect the role of CDKL5 on hippocampal development and to establish the mechanism/s underlying its actions. We found that Cdkl5 knockout mice showed increased precursor cell proliferation in the hippocampal dentate gyrus. Interestingly, this region was also characterized by an increased rate of apoptotic cell death that caused a reduction in the final neuron number in spite of the proliferation increase. Moreover, loss of Cdkl5 led to decreased dendritic development of new generated granule cells. Finally, we identified the Akt/GSK3-beta signaling as a target of Cdkl5 in the regulation of neuronal precursor proliferation, survival and maturation. Overall our findings highlight a critical role of CDKL5/AKT/GSK3-beta signaling in the control of neuron proliferation, survival and differentiation and suggest that CDKL5-related alterations of these processes during brain development underlie the neurological symptoms of the CDKL5 variant of RTT.

Gene therapy for a novel mouse model of Canavan disease

Canavan disease (CD) is a rare leukodystrophy caused by loss-of-function mutations in the gene encoding aspartoacylase (ASPA), an oligodendrocyte-enriched enzyme. It is characterised by the accumulation of the ASPA substrate N-acetylaspartate (NAA) in brain, blood and urine, leading to a spongiform vacuolisation of the brain, severe motoric and cognitive impairments and premature death. To date, no therapy is available due to the lack of a gene-transfer system allowing transgene expression in oligodendrocytes (OLs) and the restoration of the missing enzyme. Hence, the aim of this study was to establish a novel gene-transfer system and its preclinical evaluation in a CD animal model.rnIn the first part of this thesis, a novel ASPA mouse mutant was generated. A βgeo cassette (including the genes encoding β-galactosidase and neomycin) flanked by frt sites was inserted into intron 1 of the intact aspa gene. Additionally, exon 2 was flanked by loxP sites for optional conditional deletion of the targeted locus. The resulting ASPA-deficient aspalacZ/lacZ-mouse was found to be an accurate model of CD and an important tool to identify novel aspects of its complex pathology. Homozygous mutants showed a CD-like histopathology, neurological impairment, behavioural deficits as well as a reduced body weight. Additionally, MRI data revealed changes in brain metabolite composition. rnRecombinant adeno-associated viral (rAAV) vectors have become a versatile tool for gene transfer to the central nervous system because they are efficient, non-toxic and replication-deficient. Based on the natural neurotropism of AAV vectors, AAV-based gene delivery has entered the clinics for the treatment of neurodegenerative diseases. However, the lack of AAV vectors with oligodendroglial tropism has precluded gene therapy for leukodystrophies. In the second part of this work, it was shown that the transduction profile of established AAV serotypes can be targeted towards OLs in a transcriptional approach, using the oligodendrocyte-specific myelin basic protein (MBP) promoter to drive transgene expression in OLs.rnIn the last part of this work, the therapeutic efficacy of AAV-mediated aspa gene transfer to OLs of juvenile aspalacZ/lacZ mice was evaluated. AAV-aspa injections into multiple sites of the brain parenchyma resulted in transduction of OLs in the grey and white matter throughout the brain. Histological abnormalities in the brain of ASPA-deficient mice were ameliorated and accompanied by a reduction of NAA levels. Furthermore, the treatment resulted in normalisation of body weight, motor function and nest-building behaviour. These data provide a proof-of-concept for a successful gene therapy of Canavan disease. This might pave the way towards translation into clinical application and serve as the basis for the genetic treatment of other leukodystrophies.

A Cox Model for Biostatistics of the Future

Professor Sir David R. Cox (DRC) is widely acknowledged as among the most important scientists of the second half of the twentieth century. He inherited the mantle of statistical science from Pearson and Fisher, advanced their ideas, and translated statistical theory into practice so as to forever change the application of statistics in many fields, but especially biology and medicine. The logistic and proportional hazards models he substantially developed, are arguably among the most influential biostatistical methods in current practice. This paper looks forward over the period from DRC's 80th to 90th birthdays, to speculate about the future of biostatistics, drawing lessons from DRC's contributions along the way. We consider "Cox's model" of biostatistics, an approach to statistical science that: formulates scientific questions or quantities in terms of parameters gamma in probability models f(y; gamma) that represent in a parsimonious fashion, the underlying scientific mechanisms (Cox, 1997); partition the parameters gamma = theta, eta into a subset of interest theta and other "nuisance parameters" eta necessary to complete the probability distribution (Cox and Hinkley, 1974); develops methods of inference about the scientific quantities that depend as little as possible upon the nuisance parameters (Barndorff-Nielsen and Cox, 1989); and thinks critically about the appropriate conditional distribution on which to base infrences. We briefly review exciting biomedical and public health challenges that are capable of driving statistical developments in the next decade. We discuss the statistical models and model-based inferences central to the CM approach, contrasting them with computationally-intensive strategies for prediction and inference advocated by Breiman and others (e.g. Breiman, 2001) and to more traditional design-based methods of inference (Fisher, 1935). We discuss the hierarchical (multi-level) model as an example of the future challanges and opportunities for model-based inference. We then consider the role of conditional inference, a second key element of the CM. Recent examples from genetics are used to illustrate these ideas. Finally, the paper examines causal inference and statistical computing, two other topics we believe will be central to biostatistics research and practice in the coming decade. Throughout the paper, we attempt to indicate how DRC's work and the "Cox Model" have set a standard of excellence to which all can aspire in the future.

A Diagnostic Test for the Mixing Distribution in a Generalised Linear Mixed Model

We introduce a diagnostic test for the mixing distribution in a generalised linear mixed model. The test is based on the difference between the marginal maximum likelihood and conditional maximum likelihood estimates of a subset of the fixed effects in the model. We derive the asymptotic variance of this difference, and propose a test statistic that has a limiting chi-square distribution under the null hypothesis that the mixing distribution is correctly specified. For the important special case of the logistic regression model with random intercepts, we evaluate via simulation the power of the test in finite samples under several alternative distributional forms for the mixing distribution. We illustrate the method by applying it to data from a clinical trial investigating the effects of hormonal contraceptives in women.

On the Behaviour of Marginal and Conditional Akaike Information Criteria in Linear Mixed Models

In linear mixed models, model selection frequently includes the selection of random effects. Two versions of the Akaike information criterion (AIC) have been used, based either on the marginal or on the conditional distribution. We show that the marginal AIC is no longer an asymptotically unbiased estimator of the Akaike information, and in fact favours smaller models without random effects. For the conditional AIC, we show that ignoring estimation uncertainty in the random effects covariance matrix, as is common practice, induces a bias that leads to the selection of any random effect not predicted to be exactly zero. We derive an analytic representation of a corrected version of the conditional AIC, which avoids the high computational cost and imprecision of available numerical approximations. An implementation in an R package is provided. All theoretical results are illustrated in simulation studies, and their impact in practice is investigated in an analysis of childhood malnutrition in Zambia.

Nonparametric Estimation of the Bivariate Recurrence Time Distribution

This paper considers statistical models in which two different types of events, such as the diagnosis of a disease and the remission of the disease, occur alternately over time and are observed subject to right censoring. We propose nonparametric estimators for the joint distribution of bivariate recurrence times and the marginal distribution of the first recurrence time. In general, the marginal distribution of the second recurrence time cannot be estimated due to an identifiability problem, but a conditional distribution of the second recurrence time can be estimated non-parametrically. In literature, statistical methods have been developed to estimate the joint distribution of bivariate recurrence times based on data of the first pair of censored bivariate recurrence times. These methods are efficient in the current model because recurrence times of higher orders are not used. Asymptotic properties of the estimators are established. Numerical studies demonstrate the estimator performs well with practical sample sizes. We apply the proposed method to a Denmark psychiatric case register data set for illustration of the methods and theory.

Transgenic system for conditional induction and rescue of chronic myocardial hibernation provides insights into genomic programs of hibernation

A key energy-saving adaptation to chronic hypoxia that enables cardiomyocytes to withstand severe ischemic insults is hibernation, i.e., a reversible arrest of contractile function. Whereas hibernating cardiomyocytes represent the critical reserve of dysfunctional cells that can be potentially rescued, a lack of a suitable animal model has hampered insights on this medically important condition. We developed a transgenic mouse system for conditional induction of long-term hibernation and a system to rescue hibernating cardiomyocytes at will. Via myocardium-specific induction (and, in turn, deinduction) of a VEGF-sequestering soluble receptor, we show that VEGF is indispensable for adjusting the coronary vasculature to match increased oxygen consumption and exploit this finding to generate a hypoperfused heart. Importantly, ensuing ischemia is tunable to a level at which large cohorts of cardiomyocytes are driven to enter a hibernation mode, without cardiac cell death. Relieving the VEGF blockade even months later resulted in rapid revascularization and full recovery of contractile function. Furthermore, we show that left ventricular remodeling associated with hibernation is also fully reversible. The unique opportunity to uncouple hibernation from other ischemic heart phenotypes (e.g., infarction) was used to determine the genetic program of hibernation; uncovering hypoxia-inducible factor target genes associated with metabolic adjustments and induced expression of several cardioprotective genes. Autophagy, specifically self-digestion of mitochondria, was identified as a key prosurvival mechanism in hibernating cardiomyocytes. This system may lend itself for examining the potential utility of treatments to rescue dysfunctional cardiomyocytes and reverse maladaptive remodeling.

Multivariate modelling of responses to conditional items: New possibilities for latent class analysis

Questionnaire data may contain missing values because certain questions do not apply to all respondents. For instance, questions addressing particular attributes of a symptom, such as frequency, triggers or seasonality, are only applicable to those who have experienced the symptom, while for those who have not, responses to these items will be missing. This missing information does not fall into the category 'missing by design', rather the features of interest do not exist and cannot be measured regardless of survey design. Analysis of responses to such conditional items is therefore typically restricted to the subpopulation in which they apply. This article is concerned with joint multivariate modelling of responses to both unconditional and conditional items without restricting the analysis to this subpopulation. Such an approach is of interest when the distributions of both types of responses are thought to be determined by common parameters affecting the whole population. By integrating the conditional item structure into the model, inference can be based both on unconditional data from the entire population and on conditional data from subjects for whom they exist. This approach opens new possibilities for multivariate analysis of such data. We apply this approach to latent class modelling and provide an example using data on respiratory symptoms (wheeze and cough) in children. Conditional data structures such as that considered here are common in medical research settings and, although our focus is on latent class models, the approach can be applied to other multivariate models.

Frailty and risk for heart failure in older adults: the health, aging, and body composition study

OBJECTIVE The aim of this study was to assess the association between frailty and risk for heart failure (HF) in older adults. BACKGROUND Frailty is common in the elderly and is associated with adverse health outcomes. Impact of frailty on HF risk is not known. METHODS We assessed the association between frailty, using the Health ABC Short Physical Performance Battery (HABC Battery) and the Gill index, and incident HF in 2825 participants aged 70 to 79 years. RESULTS Mean age of participants was 74 ± 3 years; 48% were men and 59% were white. During a median follow up of 11.4 (7.1-11.7) years, 466 participants developed HF. Compared to non-frail participants, moderate (HR 1.36, 95% CI 1.08-1.71) and severe frailty (HR 1.88, 95% CI 1.02-3.47) by Gill index was associated with a higher risk for HF. HABC Battery score was linearly associated with HF risk after adjusting for the Health ABC HF Model (HR 1.24, 95% CI 1.13-1.36 per SD decrease in score) and remained significant when controlled for death as a competing risk (HR 1.30; 95% CI 1.00-1.55). Results were comparable across age, sex, and race, and in sub-groups based on diabetes mellitus or cardiovascular disease at baseline. Addition of HABC Battery scores to the Health ABC HF Risk Model improved discrimination (change in C-index, 0.014; 95% CI 0.018-0.010) and appropriately reclassified 13.4% (net-reclassification-improvement 0.073, 95% CI 0.021-0.125; P = .006) of participants (8.3% who developed HF and 5.1% who did not). CONCLUSIONS Frailty is independently associated with risk of HF in older adults.

Detection and sequence analysis of a nickel-induced mutation in a retroviral model system

We have developed a novel way to assess the mutagenicity of environmentally important metal carcinogens, such as nickel, by creating a positive selection system based upon the conditional expression of a retroviral transforming gene. The target gene is the v-mos gene in MuSVts110, a murine retrovirus possessing a growth temperature dependent defect in expression of the transforming gene due to viral RNA splicing. In normal rat kidney cells infected with MuSVts110 (6m2 cells), splicing of the MuSVts110 RNA to form the mRNA from which the transforming protein, p85$\sp{\rm gag-mos}$, is translated is growth-temperature dependent, occurring at 33 C and below but not at 39 C and above. This splicing "defect" is mediated by cis-acting viral sequences. Nickel chloride treatment of 6m2 cells followed by growth at 39 C, allowed the selection of "revertant" cells which constitutively express p85$\sp{\rm gag-mos}$ due to stable changes in the viral RNA splicing phenotype, suggesting that nickel, a carcinogen whose mutagenicity has not been well established, could induce mutations in mammalian genes. We also show by direct sequencing of PCR-amplified integrated MuSVts110 DNA from a 6m2 nickel-revertant cell line that the nickel-induced mutation affecting the splicing phenotype is a cis-acting 70-base duplication of a region of the viral DNA surrounding the 3$\sp\prime$ splice site. These findings provide the first example of the molecular basis for a nickel-induced DNA lesion and establish the mutagenicity of this potent carcinogen. ^

Callings and work engagement: Moderated mediation model of work meaningfulness, occupational identity, and occupational self-efficacy

Scholarly interest in callings is growing, but our understanding of how and when callings relate to career outcomes is incomplete. The present study investigated the possibility that the relationship of calling to work engagement is mediated by work meaningfulness, occupational identity, and occupational self-efficacy – and that this mediation depends on the degree of perceived person-job fit. I examined a highly educated sample of German employees (N=529) in diverse occupations and found support for two of the three hypothesized mediators – work meaningfulness and occupational identity – after controlling for the relation of core self-evaluations to work engagement. Contrary to expectations, the mediated relations of callings to work engagement were not conditional upon the degree of person-job fit. The findings are considered in terms of the pathways through which callings may relate to work engagement and other career development outcomes.

Empirical Analysis of Credit Risk Regime Switching and Temporal Conditional Default Correlation in Credit Default Swap Valuation: The Market liquidity effect

In this paper, we extend the debate concerning Credit Default Swap valuation to include time varying correlation and co-variances. Traditional multi-variate techniques treat the correlations between covariates as constant over time; however, this view is not supported by the data. Secondly, since financial data does not follow a normal distribution because of its heavy tails, modeling the data using a Generalized Linear model (GLM) incorporating copulas emerge as a more robust technique over traditional approaches. This paper also includes an empirical analysis of the regime switching dynamics of credit risk in the presence of liquidity by following the general practice of assuming that credit and market risk follow a Markov process. The study was based on Credit Default Swap data obtained from Bloomberg that spanned the period January 1st 2004 to August 08th 2006. The empirical examination of the regime switching tendencies provided quantitative support to the anecdotal view that liquidity decreases as credit quality deteriorates. The analysis also examined the joint probability distribution of the credit risk determinants across credit quality through the use of a copula function which disaggregates the behavior embedded in the marginal gamma distributions, so as to isolate the level of dependence which is captured in the copula function. The results suggest that the time varying joint correlation matrix performed far superior as compared to the constant correlation matrix; the centerpiece of linear regression models.