Association between Functional Variables and Heart Failure after Myocardial Infarction in Rats

Background: Heart failure prediction after acute myocardial infarction may have important clinical implications. Objective: To analyze the functional echocardiographic variables associated with heart failure in an infarction model in rats. Methods: The animals were divided into two groups: control and infarction. Subsequently, the infarcted animals were divided into groups: with and without heart failure. The predictive values were assessed by logistic regression. The cutoff values predictive of heart failure were determined using ROC curves. Results: Six months after surgery, 88 infarcted animals and 43 control animals were included in the study. Myocardial infarction increased left cavity diameters and the mass and wall thickness of the left ventricle. Additionally, myocardial infarction resulted in systolic and diastolic dysfunction, characterized by lower area variation fraction values, posterior wall shortening velocity, E-wave deceleration time, associated with higher values of E / A ratio and isovolumic relaxation time adjusted by heart rate. Among the infarcted animals, 54 (61%) developed heart failure. Rats with heart failure have higher left cavity mass index and diameter, associated with worsening of functional variables. The area variation fraction, the E/A ratio, E-wave deceleration time and isovolumic relaxation time adjusted by heart rate were functional variables predictors of heart failure. The cutoff values of functional variables associated with heart failure were: area variation fraction < 31.18%; E / A > 3.077; E-wave deceleration time < 42.11 and isovolumic relaxation time adjusted by heart rate < 69.08. Conclusion: In rats followed for 6 months after myocardial infarction, the area variation fraction, E/A ratio, E-wave deceleration time and isovolumic relaxation time adjusted by heart rate are predictors of heart failure onset.

Cost Factors in Digital Projects: A Model Useful in Other Applications

Description of a costing model developed by digital production librarian to determine the cost to put an item into the Claremont Colleges Digital Library at the Claremont University Consortium. This case study includes variables such as material types and funding sources, data collection methods, and formulas and calculations for analysis. This model is useful for grant applications, cost allocations, and budgeting for digital project coordinators and digital library projects.

MB-MDR: Model-Based Multifactor Dimensionality Reduction for detecting interactions in high-dimensional genomic data

L’anàlisi de l’efecte dels gens i els factors ambientals en el desenvolupament de malalties complexes és un gran repte estadístic i computacional. Entre les diverses metodologies de mineria de dades que s’han proposat per a l’anàlisi d’interaccions una de les més populars és el mètode Multifactor Dimensionality Reduction, MDR, (Ritchie i al. 2001). L’estratègia d’aquest mètode és reduir la dimensió multifactorial a u mitjançant l’agrupació dels diferents genotips en dos grups de risc: alt i baix. Tot i la seva utilitat demostrada, el mètode MDR té alguns inconvenients entre els quals l’agrupació excessiva de genotips pot fer que algunes interaccions importants no siguin detectades i que no permet ajustar per efectes principals ni per variables confusores. En aquest article il•lustrem les limitacions de l’estratègia MDR i d’altres aproximacions no paramètriques i demostrem la conveniència d’utilitzar metodologies parametriques per analitzar interaccions en estudis cas-control on es requereix l’ajust per variables confusores i per efectes principals. Proposem una nova metodologia, una versió paramètrica del mètode MDR, que anomenem Model-Based Multifactor Dimensionality Reduction (MB-MDR). La metodologia proposada té com a objectiu la identificació de genotips específics que estiguin associats a la malaltia i permet ajustar per efectes marginals i variables confusores. La nova metodologia s’il•lustra amb dades de l’Estudi Espanyol de Cancer de Bufeta.

Functional and histopathological identification of the respiratory failure in a DMSXL transgenic mouse model of myotonic dystrophy.

Acute and chronic respiratory failure is one of the major and potentially life-threatening features in individuals with myotonic dystrophy type 1 (DM1). Despite several clinical demonstrations showing respiratory problems in DM1 patients, the mechanisms are still not completely understood. This study was designed to investigate whether the DMSXL transgenic mouse model for DM1 exhibits respiratory disorders and, if so, to identify the pathological changes underlying these respiratory problems. Using pressure plethysmography, we assessed the breathing function in control mice and DMSXL mice generated after large expansions of the CTG repeat in successive generations of DM1 transgenic mice. Statistical analysis of breathing function measurements revealed a significant decrease in the most relevant respiratory parameters in DMSXL mice, indicating impaired respiratory function. Histological and morphometric analysis showed pathological changes in diaphragmatic muscle of DMSXL mice, characterized by an increase in the percentage of type I muscle fibers, the presence of central nuclei, partial denervation of end-plates (EPs) and a significant reduction in their size, shape complexity and density of acetylcholine receptors, all of which reflect a possible breakdown in communication between the diaphragmatic muscles fibers and the nerve terminals. Diaphragm muscle abnormalities were accompanied by an accumulation of mutant DMPK RNA foci in muscle fiber nuclei. Moreover, in DMSXL mice, the unmyelinated phrenic afferents are significantly lower. Also in these mice, significant neuronopathy was not detected in either cervical phrenic motor neurons or brainstem respiratory neurons. Because EPs are involved in the transmission of action potentials and the unmyelinated phrenic afferents exert a modulating influence on the respiratory drive, the pathological alterations affecting these structures might underlie the respiratory impairment detected in DMSXL mice. Understanding mechanisms of respiratory deficiency should guide pharmaceutical and clinical research towards better therapy for the respiratory deficits associated with DM1.

Aggregating Brain Cell Cultures as a Model to Study Ischaemia-induced Neurodegeneration.

Rotation-mediated aggregating brain cell cultures at two different maturational stages (DIV 11 and DIV 20) were subjected for 1 or 2 hours to ischaemic conditions by transient immobilization (arrest of media circulation). During recovery, cell damage was evaluated by measuring changes in cell type-specific enzyme activities and total protein content. It was found that in immature cultures (DIV 11), immobilization for 1 or 2 hours did not affect the parameters measured. By contrast, at DIV 20, ischaemic conditions for 1 hour caused a pronounced decrease in the activities of glutamic acid decarboxylase and choline acetyltransferase. A significant decrease in these neuron-specific enzyme activities was found at post-ischaemic days 1-14, indicating immediate and irreversible neuronal damage. The activity of the astrocyte-specific enzyme, glutamine synthetase, was significantly increased at 4 days post-treatment; equal to control values at 6 days; and significantly decreased at 14 days after the ischaemic insult. Immobilization of DIV 20 cultures for 2 hours caused a drastic reduction in all the parameters measured at post-ischaemic day 6. Generally, the ischaemic conditions appeared to be more detrimental to neurons than to astrocytes, and GABAergic neurons were more affected than cholinergic neurons.

Structural analysis of Turtle mountain (Alberta) using digital elevation model: Toward a progressive failure

In 1903, the eastern slope of Turtle Mountain (Alberta) was affected by a 30 M m3-rockslide named Frank Slide that resulted in more than 70 casualties. Assuming that the main discontinuity sets, including bedding, control part of the slope morphology, the structural features of Turtle Mountain were investigated using a digital elevation model (DEM). Using new landscape analysis techniques, we have identified three main joint and fault sets. These results are in agreement with those sets identified through field observations. Landscape analysis techniques, using a DEM, confirm and refine the most recent geology model of the Frank Slide. The rockslide was initiated along bedding and a fault at the base of the slope and propagated up slope by a regressive process following a surface composed of pre-existing discontinuities. The DEM analysis also permits the identification of important geological structures along the 1903 slide scar. Based on the so called Sloping Local Base Level (SLBL) an estimation was made of the present unstable volumes in the main scar delimited by the cracks, and around the south area of the scar (South Peak). The SLBL is a method permitting a geometric interpretation of the failure surface based on a DEM. Finally we propose a failure mechanism permitting the progressive failure of the rock mass that considers gentle dipping wedges (30°). The prisms or wedges defined by two discontinuity sets permit the creation of a failure surface by progressive failure. Such structures are more commonly observed in recent rockslides. This method is efficient and is recommended as a preliminary analysis prior to field investigation.

Model based fault diagnosis with application to an automotive engine

Report for the scientific sojourn at the University of Linköping between April to July 2007. Monitoring of the air intake system of an automotive engine is important to meet emission related legislative diagnosis requirements. During the research the problem of fault detection in the air intake system was stated as a constraint satisfaction problem over continuous domains with a big number of variables and constraints. This problem was solved using Interval-based Consistency Techniques. Interval-based consistency techniques are shown to be particularly efficient for checking the consistency of the Analytical Redundancy Relations (ARRs), dealing with uncertain measurements and parameters, and using experimental data. All experiments were performed on a four-cylinder turbo-charged spark-ignited SAAB engine located in the research laboratory at Vehicular System Group - University of Linköping.

Climbing to the top? Foreign Direct Investment and Property Rights.

This paper operates at the interface of the literature on the impact of foreign direct investment (FDI) on host countries, and the literature on the determinants of institutional quality. We argue that FDI contributes to economic development by improving institutional quality in the host country and we attempt to test this proposition using a large panel data set of 70 developing countries during the period 1981 and 2005, and we show that FDI inflows have a positive and highly significant impact on property rights. The result appears to be very robust and is and not affected by model specification, different control variables, or a particular estimation technique. As far as we are aware this is the first paper to empirically test the FDI – property rights linkage.

Sex biased spatial strategies relying on the integration of multimodal cues in a rat model of schizophrenia: impairment in predicting future context?

Male and female Wistar rats were treated postnatally (PND 5-16) with BSO (l-buthionine-(S,R)-sulfoximine) to provide a rat model of schizophrenia based on transient glutathione deficit. In the watermaze, BSO-treated male rats perform very efficiently in conditions where a diversity of visual information is continuously available during orientation trajectories [1]. Our hypothesis is that the treatment impairs proactive strategies anticipating future sensory information, while supporting a tight visual adjustment on memorized snapshots, i.e. compensatory reactive strategies. To test this hypothesis, BSO rats' performance was assessed in two conditions using an 8-arm radial maze task: a semi-transparent maze with no available view on the environment from maze centre [2], and a modified 2-parallel maze known to induce a neglect of the parallel pair in normal rats [3-5]. Male rats, but not females, were affected by the BSO treatment. In the semi-transparent maze, BSO males expressed a higher error rate, especially in completing the maze after an interruption. In the 2-parallel maze shape, BSO males, unlike controls, expressed no neglect of the parallel arms. This second result was in accord with a reactive strategy using accurate memory images of the contextual environment instead of a representation based on integrating relative directions. These results are coherent with a treatment-induced deficit in proactive decision strategy based on multimodal cognitive maps, compensated by accurate reactive adaptations based on the memory of local configurations. Control females did not express an efficient proactive capacity in the semi-transparent maze, neither did they show the significant neglect of the parallel arms, which might have masked the BSO induced effect. Their reduced sensitivity to BSO treatment is discussed with regard to a sex biased basal cognitive style.

Fear of model misspecifcation and the robustness premium

Robust decision making implies welfare costs or robustness premia when the approximating model is the true data generating process. To examine the importance of these premia at the aggregate level we employ a simple two-sector dynamic general equilibrium model with human capital and introduce an additional form of precautionary behavior. The latter arises from the robust decision maker s ability to reduce the effects of model misspecification through allocating time and existing human capital to this end. We find that the extent of the robustness premia critically depends on the productivity of time relative to that of human capital. When the relative efficiency of time is low, despite transitory welfare costs, there are gains from following robust policies in the long-run. In contrast, high relative productivity of time implies misallocation costs that remain even in the long-run. Finally, depending on the technology used to reduce model uncertainty, we fi nd that while increasing the fear of model misspecfi cation leads to a net increase in precautionary behavior, investment and output can fall.

Accurate performance of a rat model of schizophrenia in the water maze depends on visual cue availability and stability: a distortion in cognitive mapping abilities?

Rats were treated postnatally (PND 5-16) with BSO (l-buthionine-(S,R)-sulfoximine) in an animal model of schizophrenia based on transient glutathione deficit. The BSO treated rats were impaired in patrolling a maze or a homing table when adult, yet demonstrated preserved escape learning, place discrimination and reversal in a water maze task [37]. In the present work, BSO rats' performance in the water maze was assessed in conditions controlling for the available visual cues. First, in a completely curtained environment with two salient controlled cues, BSO rats showed little accuracy compared to control rats. Secondly, pre-trained BSO rats were impaired in reaching the familiar spatial position when curtains partially occluded different portions of the room environment in successive sessions. The apparently preserved place learning in a classical water maze task thus appears to require the stability and the richness of visual landmarks from the surrounding environment. In other words, the accuracy of BSO rats in place and reversal learning is impaired in a minimal cue condition or when the visual panorama changes between trials. However, if the panorama remains rich and stable between trials, BSO rats are equally efficient in reaching a familiar position or in learning a new one. This suggests that the BSO accurate performance in the water maze does not satisfy all the criteria for a cognitive map based navigation on the integration of polymodal cues. It supports the general hypothesis of a binding deficit in BSO rats.

Imperfect Credibility and Robust Monetary Policy

This paper studies the behavior of a central bank that seeks to conduct policy optimally while having imperfect credibility and harboring doubts about its model. Taking the Smets-Wouters model as the central bank.s approximating model, the paper's main findings are as follows. First, a central bank.s credibility can have large consequences for how policy responds to shocks. Second, central banks that have low credibility can bene.t from a desire for robustness because this desire motivates the central bank to follow through on policy announcements that would otherwise not be time-consistent. Third, even relatively small departures from perfect credibility can produce important declines in policy performance. Finally, as a technical contribution, the paper develops a numerical procedure to solve the decision-problem facing an imperfectly credible policymaker that seeks robustness.

A control flow prototype for a dose recommending device for chronic myeloid leukemia patients

In this paper we present a prototype of a control flow for an a posteriori drug dose adaptation for Chronic Myelogenous Leukemia (CML) patients. The control flow is modeled using Timed Automata extended with Tasks (TAT) model. The feedback loop of the control flow includes the decision-making process for drug dose adaptation. This is based on the outputs of the body response model represented by the Support Vector Machine (SVM) algorithm for drug concentration prediction. The decision is further checked for conformity with the dose level rules of a medical guideline. We also have developed an automatic code synthesizer for the icycom platform as an extension of the TIMES tool.

Term Structure Dynamics, Macro-Finance Factors and Model Uncertainty

This paper extends the Nelson-Siegel linear factor model by developing a flexible macro-finance framework for modeling and forecasting the term structure of US interest rates. Our approach is robust to parameter uncertainty and structural change, as we consider instabilities in parameters and volatilities, and our model averaging method allows for investors' model uncertainty over time. Our time-varying parameter Nelson-Siegel Dynamic Model Averaging (NS-DMA) predicts yields better than standard benchmarks and successfully captures plausible time-varying term premia in real time. The proposed model has significant in-sample and out-of-sample predictability for excess bond returns, and the predictability is of economic value.

Quantile forecasts of inflation under model uncertainty

Bayesian model averaging (BMA) methods are regularly used to deal with model uncertainty in regression models. This paper shows how to introduce Bayesian model averaging methods in quantile regressions, and allow for different predictors to affect different quantiles of the dependent variable. I show that quantile regression BMA methods can help reduce uncertainty regarding outcomes of future inflation by providing superior predictive densities compared to mean regression models with and without BMA.