Inactive Matrix Gla-Protein is associated with arterial stiffness in an adult population-based study

Increased pulse wave velocity (PWV) is a marker of aortic stiffness and an independent predictor of mortality. Matrix Gla-protein (MGP) is a vascular calcification inhibitor that needs vitamin K to be activated. Inactive MGP, known as desphospho-uncarboxylated MGP (dp-ucMGP), can be measured in plasma and has been associated with various cardiovascular markers, cardiovascular outcomes, and mortality. In this study, we hypothesized that high levels of dp-ucMGP are associated with increased PWV. We recruited participants via a multicenter family-based cross-sectional study in Switzerland. Dp-ucMGP was quantified in plasma by sandwich ELISA. Aortic PWV was determined by applanation tonometry using carotid and femoral pulse waveforms. Multiple regression analysis was performed to estimate associations between PWV and dp-ucMGP adjusting for age, renal function, and other cardiovascular risk factors. We included 1001 participants in our analyses (475 men and 526 women). Mean values were 7.87±2.10 m/s for PWV and 0.43±0.20 nmol/L for dp-ucMGP. PWV was positively associated with dp-ucMGP both before and after adjustment for sex, age, body mass index, height, systolic and diastolic blood pressure (BP), heart rate, renal function, low- and high-density lipoprotein, glucose, smoking status, diabetes mellitus, BP and cholesterol lowering drugs, and history of cardiovascular disease (P≤0.01). In conclusion, high levels of dp-ucMGP are independently and positively associated with arterial stiffness after adjustment for common cardiovascular risk factors, renal function, and age. Experimental studies are needed to determine whether vitamin K supplementation slows arterial stiffening by increasing MGP carboxylation.

Inactive matrix gla-protein is associated with arterial atiffness in an adult population-based study

La vitesse de l'onde de pouls (VOP) est la méthode pour mesurer la rigidité artérielle la plus répandue et la plus validée. C'est aussi un prédicteur indépendant de la mortalité. La Matrix Gla- protein (MGP) est une protein qui inhibe les calcifications vasculaires. MGP nécessite une enzyme dérivée de la vitamine K pour être activée, à l'instar de certains facteurs de coagulation. La forme inactive de MGP, connue sous le terme de « desphospho-uncarboxylated MGP » (dp-ucMGP), peut-être mesurée dans le plasma. Plus les apports de vitamine K sont importants plus les taux de dp-ucMGP diminue. Les taux de dp-ucMGP ont déjà été étudiés et associés à différents marqueurs cardiovasculaires (CV), aux événements CV et à la mortalité. Dans notre travail de recherche nous avons émis l'hypothèse que des taux élevés de dp-ucMGP seraient associés à une VOP élevée. Nous avons recruté les participants à travers une étude multicentrique suisse (SKIPOGH). Le processus de recrutement ciblait des familles dans lesquelles plusieurs membres étaient d'accord de participer. Nous avons mesuré la dp-ucMGP plasmatique grâce à la méthode immuno-enzymatique « ELISA ». Concernant la VOP, nous avons mesuré les ondes de pression au niveau carotidien et fémorale grâce à un tonomètre et calculer la vitesse de leurs propagations. Par la suite nous avons utilisé un modèle de régression linéaire multiple afin de déterminer le lien entre la VOP et dp- ucMGP. Le modèle était ajusté pour l'âge, la fonction rénale et les risques CV classiques. Nous avons inclut 1001 participants dans les analyses (475 hommes et 526 femmes). La valeur moyenne de la VOP était de 7.87 ± 2.10 (m/s) et celle de dp-ucMGP de 0.43 ± 0.20 (nmol/L). La VOP était positivement et significativement associée à dp-ucMGP avant comme après ajustement pour le sexe, l'âge, l'indice de masse corporel, la taille, la pression artérielle systolique et diastolique, la fréquence cardiaque, la fonction rénale, les taux de cholestérol (LDL, HDL), la glycémie, la consommation de tabac, la présence d'un diabète, l'utilisation de médicaments antihypertenseurs ou hypolipémiants et la présence d'antécédents CV (P<0.01). En conclusion, des taux élevés de dp-ucMGP sont positivement et indépendamment associés à la rigidité artérielle après ajustement pour les facteurs de risques CV traditionnels, la fonction rénale et l'âge. Des études expérimentales sont nécessaires afin de déterminer si une supplémentation en vitamine K permet de ralentir l'avancement de la rigidité artérielle grâce à son activation de la MGP.

Stellar population synthesis: the effect of improved Asymptotic Giant Branch models and of interstellar dust on mass-to-light–color relations

Teoreettisen populaatiosynteesin avulla voidaan mallintaa tähtijoukkojen ja galaksien fotometrisiä ominaisuuksia yhdistämällä yksittäisten tähtien tuottama säteily, joka saadaan teoreettisista tähtien kehitysmalleista. Valitsemalla sopiva massajakauma syntyville tähdille voidaan muodostaa yksinkertainen tähtipopulaatio, joka koostuu saman ikäisistä ja kemialliselta koostumukseltaan yhtenäisistä tähdistä. Monimutkaisempia tähtipopulaatioita voidaan muodostaa konvoloimalla yksinkertaisten tähtipopulaatioiden luminositeetti jonkin valitun tähtienmuodostushistorian kanssa sekä yhdistämällä näin muodostettuja populaatioita. Tässä työssä tarkastellaan asymptoottisen jättiläishaaran (AGB) tähtien uusien, tarkentuneiden evoluutiomallien vaikutusta populaatiosynteesin tuloksiin niin yksinkertaisten tähtipopulaatioiden kuin galaksien mallinnukseen soveltuvien monimutkaisempien tähtipopulaatioiden kohdalla. Työn päätarkoitus on tuottaa uudistuneisiin malleihin perustuvat populaation massa-luminositeetti -suhteen ja värin väliset relaatiot (MLC-relaatiot). MLC-relaatioita voidaan käyttää populaation massan määrittämiseen sen fotometristen ominaisuuksien (väri, luminositeetti) perusteella. Lisäksi tutkitaan tähtienvälisen pölyn vaikutusta yksinkertaisen spiraaligalaksimallin MLC-relaatioihin. Työssä käytetyt tähtien kehitysmallit perustuvat julkaisuun Marigo et al. (Astronomy & Astrophysics 482, 2008). Havaitaan, että AGB-tähtien vaikutus populaation integroituun luminositeettiin on pieni näkyvillä aallonpituuksilla, mutta merkittävä lähi-infrapuna-alueella. Vaikutus MLC-relaatioihin on vastaavasti merkittävä tarkkailtaessa luminositeettia lähi-infrapunassa sekä käytettäessä värejä, joissa yhdistetään optisia ja lähi-infrapunan kaistoja. Todetaan, että MLC-relaatioiden käyttö lähi-infrapunassa edellyttää tarkentuneen AGB-vaiheen sisällyttämistä populaatiosynteesin malleihin. Tähtienvälisen pölyn vaikutus MLC-relaatioihin todetaan riippuvan käytetystä kaistasta ja väristä, mutta vaikutuksen havaitaan olevan suurin optisen ja lähi-infrapunan väriyhdistelmillä.

Effect of race, genetic population structure, and genetic models in two-locus association studies: clustering of functional renin-angiotensin system gene variants in hypertension association studies

Previous genetic association studies have overlooked the potential for biased results when analyzing different population structures in ethnically diverse populations. The purpose of the present study was to quantify this bias in two-locus association studies conducted on an admixtured urban population. We studied the genetic structure distribution of angiotensin-converting enzyme insertion/deletion (ACE I/D) and angiotensinogen methionine/threonine (M/T) polymorphisms in 382 subjects from three subgroups in a highly admixtured urban population. Group I included 150 white subjects; group II, 142 mulatto subjects, and group III, 90 black subjects. We conducted sample size simulation studies using these data in different genetic models of gene action and interaction and used genetic distance calculation algorithms to help determine the population structure for the studied loci. Our results showed a statistically different population structure distribution of both ACE I/D (P = 0.02, OR = 1.56, 95% CI = 1.05-2.33 for the D allele, white versus black subgroup) and angiotensinogen M/T polymorphism (P = 0.007, OR = 1.71, 95% CI = 1.14-2.58 for the T allele, white versus black subgroup). Different sample sizes are predicted to be determinant of the power to detect a given genotypic association with a particular phenotype when conducting two-locus association studies in admixtured populations. In addition, the postulated genetic model is also a major determinant of the power to detect any association in a given sample size. The present simulation study helped to demonstrate the complex interrelation among ethnicity, power of the association, and the postulated genetic model of action of a particular allele in the context of clustering studies. This information is essential for the correct planning and interpretation of future association studies conducted on this population.

Development and applications of density matrix functional theory of generalized Hubbard Models

In dieser Doktorarbeit wird eine akkurate Methode zur Bestimmung von Grundzustandseigenschaften stark korrelierter Elektronen im Rahmen von Gittermodellen entwickelt und angewandt. In der Dichtematrix-Funktional-Theorie (LDFT, vom englischen lattice density functional theory) ist die Ein-Teilchen-Dichtematrix γ die fundamentale Variable. Auf der Basis eines verallgemeinerten Hohenberg-Kohn-Theorems ergibt sich die Grundzustandsenergie Egs[γgs] = min° E[γ] durch die Minimierung des Energiefunktionals E[γ] bezüglich aller physikalischer bzw. repräsentativer γ. Das Energiefunktional kann in zwei Beiträge aufgeteilt werden: Das Funktional der kinetischen Energie T[γ], dessen lineare Abhängigkeit von γ genau bekannt ist, und das Funktional der Korrelationsenergie W[γ], dessen Abhängigkeit von γ nicht explizit bekannt ist. Das Auffinden präziser Näherungen für W[γ] stellt die tatsächliche Herausforderung dieser These dar. Einem Teil dieser Arbeit liegen vorausgegangene Studien zu Grunde, in denen eine Näherung des Funktionals W[γ] für das Hubbardmodell, basierend auf Skalierungshypothesen und exakten analytischen Ergebnissen für das Dimer, hergeleitet wird. Jedoch ist dieser Ansatz begrenzt auf spin-unabhängige und homogene Systeme. Um den Anwendungsbereich von LDFT zu erweitern, entwickeln wir drei verschiedene Ansätze zur Herleitung von W[γ], die das Studium von Systemen mit gebrochener Symmetrie ermöglichen. Zuerst wird das bisherige Skalierungsfunktional erweitert auf Systeme mit Ladungstransfer. Eine systematische Untersuchung der Abhängigkeit des Funktionals W[γ] von der Ladungsverteilung ergibt ähnliche Skalierungseigenschaften wie für den homogenen Fall. Daraufhin wird eine Erweiterung auf das Hubbardmodell auf bipartiten Gittern hergeleitet und an sowohl endlichen als auch unendlichen Systemen mit repulsiver und attraktiver Wechselwirkung angewandt. Die hohe Genauigkeit dieses Funktionals wird aufgezeigt. Es erweist sich jedoch als schwierig, diesen Ansatz auf komplexere Systeme zu übertragen, da bei der Berechnung von W[γ] das System als ganzes betrachtet wird. Um dieses Problem zu bewältigen, leiten wir eine weitere Näherung basierend auf lokalen Skalierungseigenschaften her. Dieses Funktional ist lokal bezüglich der Gitterplätze formuliert und ist daher anwendbar auf jede Art von geordneten oder ungeordneten Hamiltonoperatoren mit lokalen Wechselwirkungen. Als Anwendungen untersuchen wir den Metall-Isolator-Übergang sowohl im ionischen Hubbardmodell in einer und zwei Dimensionen als auch in eindimensionalen Hubbardketten mit nächsten und übernächsten Nachbarn. Schließlich entwickeln wir ein numerisches Verfahren zur Berechnung von W[γ], basierend auf exakten Diagonalisierungen eines effektiven Vielteilchen-Hamilton-Operators, welcher einen von einem effektiven Medium umgebenen Cluster beschreibt. Dieser effektive Hamiltonoperator hängt von der Dichtematrix γ ab und erlaubt die Herleitung von Näherungen an W[γ], dessen Qualität sich systematisch mit steigender Clustergröße verbessert. Die Formulierung ist spinabhängig und ermöglicht eine direkte Verallgemeinerung auf korrelierte Systeme mit mehreren Orbitalen, wie zum Beispiel auf den spd-Hamilton-Operator. Darüber hinaus berücksichtigt sie die Effekte kurzreichweitiger Ladungs- und Spinfluktuationen in dem Funktional. Für das Hubbardmodell wird die Genauigkeit der Methode durch Vergleich mit Bethe-Ansatz-Resultaten (1D) und Quanten-Monte-Carlo-Simulationen (2D) veranschaulicht. Zum Abschluss wird ein Ausblick auf relevante zukünftige Entwicklungen dieser Theorie gegeben.

Front spreading in population dynamic models. Theory and application to the Neolithic transition

This thesis presents population dynamics models that can be applied to predict the rate of spread of the Neolithic transition (change from hunter-gathering to farming economics) across the European continent, which took place about 9000 to 5000 years ago. The first models in this thesis provide predictions at a continental scale. We develop population dynamics models with explicit kernels and apply realistic data. We also derive a new time-delayed reaction-diffusion equation which yields speeds about a 10% slower than previous models. We also deal with a regional variability: the slowdown of the Neolithic front when reaching the North of Europe. We develop simple reaction-diffusion models that can predict the measured speeds in terms of the non-homogeneous distribution of pre-Neolithic (Mesolithic) population in Europe, which were present in higher densities at the North of the continent. Such models can explain the observed speeds.

Lesser Scaup Population Dynamics: What Can Be Learned from Available Data?

Populations of Lesser Scaup (Aythya affinis) have declined markedly in North America since the early 1980s. When considering alternatives for achieving population recovery, it would be useful to understand how the rate of population growth is functionally related to the underlying vital rates and which vital rates affect population growth rate the most if changed (which need not be those that influenced historical population declines). To establish a more quantitative basis for learning about life history and population dynamics of Lesser Scaup, we summarized published and unpublished estimates of vital rates recorded between 1934 and 2005, and developed matrix life-cycle models with these data for females breeding in the boreal forest, prairie-parklands, and both regions combined. We then used perturbation analysis to evaluate the effect of changes in a variety of vital-rate statistics on finite population growth rate and abundance. Similar to Greater Scaup (Aythya marila), our modeled population growth rate for Lesser Scaup was most sensitive to unit and proportional change in adult female survival during the breeding and non-breeding seasons, but much less so to changes in fecundity parameters. Interestingly, population growth rate was also highly sensitive to unit and proportional changes in the mean of nesting success, duckling survival, and juvenile survival. Given the small samples of data for key aspects of the Lesser Scaup life cycle, we recommend additional research on vital rates that demonstrate a strong effect on population growth and size (e.g., adult survival probabilities). Our life-cycle models should be tested and regularly updated in the future to simultaneously guide science and management of Lesser Scaup populations in an adaptive context.

Impact of Resolution on the Tropical Pacific Circulation in a Matrix of Coupled Models

Results are presented from a matrix of coupled model integrations, using atmosphere resolutions of 135 and 90 km, and ocean resolutions of 1° and 1/3°, to study the impact of resolution on simulated climate. The mean state of the tropical Pacific is found to be improved in the models with a higher ocean resolution. Such an improved mean state arises from the development of tropical instability waves, which are poorly resolved at low resolution; these waves reduce the equatorial cold tongue bias. The improved ocean state also allows for a better simulation of the atmospheric Walker circulation. Several sensitivity studies have been performed to further understand the processes involved in the different component models. Significantly decreasing the horizontal momentum dissipation in the coupled model with the lower-resolution ocean has benefits for the mean tropical Pacific climate, but decreases model stability. Increasing the momentum dissipation in the coupled model with the higher-resolution ocean degrades the simulation toward that of the lower-resolution ocean. These results suggest that enhanced ocean model resolution can have important benefits for the climatology of both the atmosphere and ocean components of the coupled model, and that some of these benefits may be achievable at lower ocean resolution, if the model formulation allows.

Population genetic models can be used to study the evolution of the interacting behaviours of parents and their progeny

An example of the evolution of the interacting behaviours of parents and progeny is studied using iterative equations linking the frequencies of the gametes produced by the progeny to the frequencies of the gametes in the parental generation. This population genetics approach shows that a model in which both behaviours are determined by a single locus can lead to a stable equilibrium in which the two behaviours continue to segregate. A model in which the behaviours are determined by genes at two separate loci leads eventually to fixation of the alleles at both loci but this can take many generations of selection. Models of the type described in this paper will be needed to understand the evolution of complex behaviour when genomic or experimental information is available about the genetic determinants of behaviour and the selective values of different genomes. (c) 2007 Elsevier Inc. All rights reserved.

Highly accurate detection of ovarian cancer using CA125 but limited improvement with serum matrix-assisted laser desorption/ionization time-of-flight mass spectrometry profiling

Objectives: Our objective was to test the performance of CA125 in classifying serum samples from a cohort of malignant and benign ovarian cancers and age-matched healthy controls and to assess whether combining information from matrix-assisted laser desorption/ionization (MALDI) time-of-flight profiling could improve diagnostic performance. Materials and Methods: Serum samples from women with ovarian neoplasms and healthy volunteers were subjected to CA125 assay and MALDI time-of-flight mass spectrometry (MS) profiling. Models were built from training data sets using discriminatory MALDI MS peaks in combination with CA125 values and tested their ability to classify blinded test samples. These were compared with models using CA125 threshold levels from 193 patients with ovarian cancer, 290 with benign neoplasm, and 2236 postmenopausal healthy controls. Results: Using a CA125 cutoff of 30 U/mL, an overall sensitivity of 94.8% (96.6% specificity) was obtained when comparing malignancies versus healthy postmenopausal controls, whereas a cutoff of 65 U/mL provided a sensitivity of 83.9% (99.6% specificity). High classification accuracies were obtained for early-stage cancers (93.5% sensitivity). Reasons for high accuracies include recruitment bias, restriction to postmenopausal women, and inclusion of only primary invasive epithelial ovarian cancer cases. The combination of MS profiling information with CA125 did not significantly improve the specificity/accuracy compared with classifications on the basis of CA125 alone. Conclusions: We report unexpectedly good performance of serum CA125 using threshold classification in discriminating healthy controls and women with benign masses from those with invasive ovarian cancer. This highlights the dependence of diagnostic tests on the characteristics of the study population and the crucial need for authors to provide sufficient relevant details to allow comparison. Our study also shows that MS profiling information adds little to diagnostic accuracy. This finding is in contrast with other reports and shows the limitations of serum MS profiling for biomarker discovery and as a diagnostic tool

Importance of oceanic resolution and mean state on the extra-tropical response to El Niño in a matrix of coupled models

The extra-tropical response to El Niño in configurations of a coupled model with increased horizontal resolution in the oceanic component is shown to be more realistic than in configurations with a low resolution oceanic component. This general conclusion is independent of the atmospheric resolution. Resolving small-scale processes in the ocean produces a more realistic oceanic mean state, with a reduced cold tongue bias, which in turn allows the atmospheric model component to be forced more realistically. A realistic atmospheric basic state is critical in order to represent Rossby wave propagation in response to El Niño, and hence the extra-tropical response to El Niño. Through the use of high and low resolution configurations of the forced atmospheric-only model component we show that, in isolation, atmospheric resolution does not significantly affect the simulation of the extra-tropical response to El Niño. It is demonstrated, through perturbations to the SST forcing of the atmospheric model component, that biases in the climatological SST field typical of coupled model configurations with low oceanic resolution can account for the erroneous atmospheric basic state seen in these coupled model configurations. These results highlight the importance of resolving small-scale oceanic processes in producing a realistic large-scale mean climate in coupled models, and suggest that it might may be possible to “squeeze out” valuable extra performance from coupled models through increases to oceanic resolution alone.

Population based models of cortical drug response: insights from anaesthesia

A great explanatory gap lies between the molecular pharmacology of psychoactive agents and the neurophysiological changes they induce, as recorded by neuroimaging modalities. Causally relating the cellular actions of psychoactive compounds to their influence on population activity is experimentally challenging. Recent developments in the dynamical modelling of neural tissue have attempted to span this explanatory gap between microscopic targets and their macroscopic neurophysiological effects via a range of biologically plausible dynamical models of cortical tissue. Such theoretical models allow exploration of neural dynamics, in particular their modification by drug action. The ability to theoretically bridge scales is due to a biologically plausible averaging of cortical tissue properties. In the resulting macroscopic neural field, individual neurons need not be explicitly represented (as in neural networks). The following paper aims to provide a non-technical introduction to the mean field population modelling of drug action and its recent successes in modelling anaesthesia.

Importance of estimating matrix quality for modeling species distribution in complex tropical landscapes: a test with Atlantic forest small mammals

Information to guide decision making is especially urgent in human dominated landscapes in the tropics, where urban and agricultural frontiers are still expanding in an unplanned manner. Nevertheless, most studies that have investigated the influence of landscape structure on species distribution have not considered the heterogeneity of altered habitats of the matrix, which is usually high in human dominated landscapes. Using the distribution of small mammals in forest remnants and in the four main altered habitats in an Atlantic forest landscape, we investigated 1) how explanatory power of models describing species distribution in forest remnants varies between landscape structure variables that do or do not incorporate matrix quality and 2) the importance of spatial scale for analyzing the influence of landscape structure. We used standardized sampling in remnants and altered habitats to generate two indices of habitat quality, corresponding to the abundance and to the occurrence of small mammals. For each remnant, we calculated habitat quantity and connectivity in different spatial scales, considering or not the quality of surrounding habitats. The incorporation of matrix quality increased model explanatory power across all spatial scales for half the species that occurred in the matrix, but only when taking into account the distance between habitat patches (connectivity). These connectivity models were also less affected by spatial scale than habitat quantity models. The few consistent responses to the variation in spatial scales indicate that despite their small size, small mammals perceive landscape features at large spatial scales. Matrix quality index corresponding to species occurrence presented a better or similar performance compared to that of species abundance. Results indicate the importance of the matrix for the dynamics of fragmented landscapes and suggest that relatively simple indices can improve our understanding of species distribution, and could be applied in modeling, monitoring and managing complex tropical landscapes.

Covariance matrix formula for Birnbaum-Saunders regression models

The Birnbaum-Saunders regression model is commonly used in reliability studies. We derive a simple matrix formula for second-order covariances of maximum-likelihood estimators in this class of models. The formula is quite suitable for computer implementation, since it involves only simple operations on matrices and vectors. Some simulation results show that the second-order covariances can be quite pronounced in small to moderate sample sizes. We also present empirical applications.

Estimation of Parameters in Random Effect Models with Incidence Matrix Uncertainty

Random effect models have been widely applied in many fields of research. However, models with uncertain design matrices for random effects have been little investigated before. In some applications with such problems, an expectation method has been used for simplicity. This method does not include the extra information of uncertainty in the design matrix is not included. The closed solution for this problem is generally difficult to attain. We therefore propose an two-step algorithm for estimating the parameters, especially the variance components in the model. The implementation is based on Monte Carlo approximation and a Newton-Raphson-based EM algorithm. As an example, a simulated genetics dataset was analyzed. The results showed that the proportion of the total variance explained by the random effects was accurately estimated, which was highly underestimated by the expectation method. By introducing heuristic search and optimization methods, the algorithm can possibly be developed to infer the 'model-based' best design matrix and the corresponding best estimates.