An in vivo ultrahigh field 14.1 T (1) H-MRS study on 6-OHDA and α-synuclein-based rat models of Parkinson's disease: GABA as an early disease marker.

The detection of Parkinson's disease (PD) in its preclinical stages prior to outright neurodegeneration is essential to the development of neuroprotective therapies and could reduce the number of misdiagnosed patients. However, early diagnosis is currently hampered by lack of reliable biomarkers. (1) H magnetic resonance spectroscopy (MRS) offers a noninvasive measure of brain metabolite levels that allows the identification of such potential biomarkers. This study aimed at using MRS on an ultrahigh field 14.1 T magnet to explore the striatal metabolic changes occurring in two different rat models of the disease. Rats lesioned by the injection of 6-hydroxydopamine (6-OHDA) in the medial-forebrain bundle were used to model a complete nigrostriatal lesion while a genetic model based on the nigral injection of an adeno-associated viral (AAV) vector coding for the human α-synuclein was used to model a progressive neurodegeneration and dopaminergic neuron dysfunction, thereby replicating conditions closer to early pathological stages of PD. MRS measurements in the striatum of the 6-OHDA rats revealed significant decreases in glutamate and N-acetyl-aspartate levels and a significant increase in GABA level in the ipsilateral hemisphere compared with the contralateral one, while the αSyn overexpressing rats showed a significant increase in the GABA striatal level only. Therefore, we conclude that MRS measurements of striatal GABA levels could allow for the detection of early nigrostriatal defects prior to outright neurodegeneration and, as such, offers great potential as a sensitive biomarker of presymptomatic PD.

Downregulation of cannabinoid receptor 1 from neuropeptide Y interneurons in the basal ganglia of patients with Huntington's disease and mouse models.

Cannabinoid receptor 1 (CB(1) receptor) controls several neuronal functions, including neurotransmitter release, synaptic plasticity, gene expression and neuronal viability. Downregulation of CB(1) expression in the basal ganglia of patients with Huntington's disease (HD) and animal models represents one of the earliest molecular events induced by mutant huntingtin (mHtt). This early disruption of neuronal CB(1) signaling is thought to contribute to HD symptoms and neurodegeneration. Here we determined whether CB(1) downregulation measured in patients with HD and mouse models was ubiquitous or restricted to specific striatal neuronal subpopulations. Using unbiased semi-quantitative immunohistochemistry, we confirmed previous studies showing that CB(1) expression is downregulated in medium spiny neurons of the indirect pathway, and found that CB(1) is also downregulated in neuropeptide Y (NPY)/neuronal nitric oxide synthase (nNOS)-expressing interneurons while remaining unchanged in parvalbumin- and calretinin-expressing interneurons. CB(1) downregulation in striatal NPY/nNOS-expressing interneurons occurs in R6/2 mice, Hdh(Q150/Q150) mice and the caudate nucleus of patients with HD. In R6/2 mice, CB(1) downregulation in NPY/nNOS-expressing interneurons correlates with diffuse expression of mHtt in the soma. This downregulation also occludes the ability of cannabinoid agonists to activate the pro-survival signaling molecule cAMP response element-binding protein in NPY/nNOS-expressing interneurons. Loss of CB(1) signaling in NPY/nNOS-expressing interneurons could contribute to the impairment of basal ganglia functions linked to HD.

A test of the predictive validity of non-linear QALY models using time trade-off utilities

This paper presents a test of the predictive validity of various classes ofQALY models (i.e., linear, power and exponential models). We first estimatedTTO utilities for 43 EQ-5D chronic health states and next these states wereembedded in health profiles. The chronic TTO utilities were then used topredict the responses to TTO questions with health profiles. We find that thepower QALY model clearly outperforms linear and exponential QALY models.Optimal power coefficient is 0.65. Our results suggest that TTO-based QALYcalculations may be biased. This bias can be avoided using a power QALY model.

Ecological niche models and patterns of richness and endemism of the southern Andean genus Eurymetopum (Coleoptera, Cleridae)

Eurymetopum is an Andean clerid genus with 22 species. We modeled the ecological niches of 19 species with Maxent and used them as potential distributional maps to identify patterns of richness and endemicity. All modeled species maps were overlapped in a single map in order to determine richness. We performed an optimality analysis with NDM/VNDM in a grid of 1º latitude-longitude in order to identify endemism. We found a highly rich area, located between 32º and 41º south latitude, where the richest pixels have 16 species. One area of endemism was identified, located in the Maule and Valdivian Forest biogeographic provinces, which extends also to the Santiago province of the Central Chilean subregion, and contains four endemic species (E. parallelum, E. prasinum, E. proteus, and E. viride), as well as 16 non-endemic species. The sympatry of these phylogenetically unrelated species might indicate ancient vicariance processes, followed by episodes of dispersal. Based on our results, we suggest a close relationship between these provinces, with the Maule representing a complex area.

Business cycles, unemployment insurance and the calibration of matching models

This paper theoretically and empirically documents a puzzle that arises when an RBC economy with a job matching function is used to model unemployment. The standard model can generate sufficiently large cyclical fluctuations in unemployment, or a sufficiently small response of unemployment to labor market policies, but it cannot do both. Variable search and separation, finite UI benefit duration, efficiency wages, and capital all fail to resolve this puzzle. However, either sticky wages or match-specific productivity shocks can improve the model's performance by making the firm's flow of surplus more procyclical, which makes hiring more procyclical too.

Forecasting with missing data: Application to a real case

This paper presents a comparative analysis of linear and mixed modelsfor short term forecasting of a real data series with a high percentage of missing data. Data are the series of significant wave heights registered at regular periods of three hours by a buoy placed in the Bay of Biscay.The series is interpolated with a linear predictor which minimizes theforecast mean square error. The linear models are seasonal ARIMA models and themixed models have a linear component and a non linear seasonal component.The non linear component is estimated by a non parametric regression of dataversus time. Short term forecasts, no more than two days ahead, are of interestbecause they can be used by the port authorities to notice the fleet.Several models are fitted and compared by their forecasting behavior.

Nonlinear models and small sample performance of the generalized method of moments

In this paper I explore the issue of nonlinearity (both in the datageneration process and in the functional form that establishes therelationship between the parameters and the data) regarding the poorperformance of the Generalized Method of Moments (GMM) in small samples.To this purpose I build a sequence of models starting with a simple linearmodel and enlarging it progressively until I approximate a standard (nonlinear)neoclassical growth model. I then use simulation techniques to find the smallsample distribution of the GMM estimators in each of the models.

Solving heterogeneous-agent models by projection and perturbation

The paper proposes a numerical solution method for general equilibrium models with a continuum of heterogeneous agents, which combines elements of projection and of perturbation methods. The basic idea is to solve first for the stationary solutionof the model, without aggregate shocks but with fully specified idiosyncratic shocks. Afterwards one computes a first-order perturbation of the solution in the aggregate shocks. This approach allows to include a high-dimensional representation of the cross-sectional distribution in the state vector. The method is applied to a model of household saving with uninsurable income risk and liquidity constraints. The model includes not only productivity shocks, but also shocks to redistributive taxation, which cause substantial short-run variation in the cross-sectional distribution of wealth. If those shocks are operative, it is shown that a solution method based on very few statistics of the distribution is not suitable, while the proposed method can solve the model with high accuracy, at least for the case of small aggregate shocks. Techniques are discussed to reduce the dimension of the state space such that higher order perturbations are feasible.Matlab programs to solve the model can be downloaded.

Differentiation of focal liver lesions: usefulness of parametric imaging with contrast-enhanced US.

Purpose: To evaluate whether parametric imaging with contrast material-enhanced ultrasonography (US) is superior to visual assessment for the differential diagnosis of focal liver lesions (FLLs). Materials and Methods: This study had institutional review board approval, and verbal patient informed consent was obtained. Between August 2005 and October 2008, 146 FLLs in 145 patients (63 women, 82 men; mean age, 62.5 years; age range, 22-89 years) were imaged with real-time low-mechanical-index contrast-enhanced US after a bolus injection of 2.4 mL of a second-generation contrast agent. Clips showing contrast agent uptake kinetics (including arterial, portal, and late phases) were recorded and subsequently analyzed off-line with dedicated image processing software. Analysis of the dynamic vascular patterns (DVPs) of lesions with respect to adjacent parenchyma allowed mapping DVP signatures on a single parametric image. Cine loops of contrast-enhanced US and results from parametric imaging of DVP were assessed separately by three independent off-site readers who classified each lesion as benign, malignant, or indeterminate. Sensitivity, specificity, accuracy, and positive and negative predictive values were calculated for both techniques. Interobserver agreement (κ statistics) was determined. Results: Sensitivities for visual interpretation of cine loops for the three readers were 85.0%, 77.9%, and 87.6%, which improved significantly to 96.5%, 97.3%, and 96.5% for parametric imaging, respectively (P < .05, McNemar test), while retaining high specificity (90.9% for all three readers). Accuracy scores of parametric imaging were higher than those of conventional contrast-enhanced US for all three readers (P < .001, McNemar test). Interobserver agreement increased with DVP parametric imaging compared with conventional contrast-enhanced US (change of κ from 0.54 to 0.99). Conclusion: Parametric imaging of DVP improves diagnostic performance of contrast-enhanced US in the differentiation between malignant and benign FLLs; it also provides excellent interobserver agreement.

Consumer choice in competitive location models: Formulations and heuristics

A new direction of research in Competitive Location theory incorporatestheories of Consumer Choice Behavior in its models. Following thisdirection, this paper studies the importance of consumer behavior withrespect to distance or transportation costs in the optimality oflocations obtained by traditional Competitive Location models. To dothis, it considers different ways of defining a key parameter in thebasic Maximum Capture model (MAXCAP). This parameter will reflectvarious ways of taking into account distance based on several ConsumerChoice Behavior theories. The optimal locations and the deviation indemand captured when the optimal locations of the other models are usedinstead of the true ones, are computed for each model. A metaheuristicbased on GRASP and Tabu search procedure is presented to solve all themodels. Computational experience and an application to 55-node networkare also presented.

Money and prices in models of bounded rationality in high inflation economies

This paper studies the short run correlation of inflation and money growth. We study whether a model of learning can do better than a model of rational expectations, we focus our study on countries of high inflation. We take the money process as an exogenous variable, estimated from the data through a switching regime process. We findthat the rational expectations model and the model of learning both offer very good explanations for the joint behavior of money and prices.

The three phases of the ensemble forecasting of niche models: geographic range and shifts in climatically suitable areas of Utetheisa ornatrix (Lepidoptera, Arctiidae)

Species' geographic ranges are usually considered as basic units in macroecology and biogeography, yet it is still difficult to measure them accurately for many reasons. About 20 years ago, researchers started using local data on species' occurrences to estimate broad scale ranges, thereby establishing the niche modeling approach. However, there are still many problems in model evaluation and application, and one of the solutions is to find a consensus solution among models derived from different mathematical and statistical models for niche modeling, climatic projections and variable combination, all of which are sources of uncertainty during niche modeling. In this paper, we discuss this approach of ensemble forecasting and propose that it can be divided into three phases with increasing levels of complexity. Phase I is the simple combination of maps to achieve a consensual and hopefully conservative solution. In Phase II, differences among the maps used are described by multivariate analyses, and Phase III consists of the quantitative evaluation of the relative magnitude of uncertainties from different sources and their mapping. To illustrate these developments, we analyzed the occurrence data of the tiger moth, Utetheisa ornatrix (Lepidoptera, Arctiidae), a Neotropical moth species, and modeled its geographic range in current and future climates.

Evolution in heterogeneous populations: from migration models to fixation probabilities.

Although dispersal is recognized as a key issue in several fields of population biology (such as behavioral ecology, population genetics, metapopulation dynamics or evolutionary modeling), these disciplines focus on different aspects of the concept and often make different implicit assumptions regarding migration models. Using simulations, we investigate how such assumptions translate into effective gene flow and fixation probability of selected alleles. Assumptions regarding migration type (e.g. source-sink, resident pre-emption, or balanced dispersal) and patterns (e.g. stepping-stone versus island dispersal) have large impacts when demes differ in sizes or selective pressures. The effects of fragmentation, as well as the spatial localization of newly arising mutations, also strongly depend on migration type and patterns. Migration rate also matters: depending on the migration type, fixation probabilities at an intermediate migration rate may lie outside the range defined by the low- and high-migration limits when demes differ in sizes. Given the extreme sensitivity of fixation probability to characteristics of dispersal, we underline the importance of making explicit (and documenting empirically) the crucial ecological/ behavioral assumptions underlying migration models.

Obesity-related phenotypes are associated to parental longevity in a Swiss population-based study

PURPOSE. Longevity has been attributed to decreased cardiovascular mortality. Subjects with long-lived parents may represent a valuable group to study cardiovascular risk factors (CVRF) associated with longevity, possibly leading to new ways of preventing cardiovascular disease. Purpose: Longevity has been attributed to decreased cardiovascular mortality. Subjects with long-lived parents may represent a valuable group to study cardiovascular risk factors (CVRF) associated with longevity, possibly leading to new ways of preventing cardiovascular disease. Methods: We analyzed data from a population-based sample of 2561 participants (1163 men and 1398 women) aged 55--75 years from the city of Lausanne, Switzerland (CoLaus study). Participants were stratified by the number of parents (0, 1, 2) who survived to 85 years or more. Trend across these strata was assessed using a non-parametric kmean test. The associations of parental age (independent covariate used as a proxy for longevity) with fasting blood glucose, blood pressures, blood lipids, body mass index (BMI), weight, height or liver enzymes (continuous dependent variables) were analyzed using multiple linear regressions. Models were adjusted for age, sex, alcohol consumption, smoking and educational level, and BMI for liver enzymes. Results: For subjects with 0 (N=1298), 1 (N=991) and 2 (N=272) long-lived parents, median BMI (interquartile range) was 25.4 (6.5), 24.9 (6.1) and 23.7 (4.8) kg/m2 in women (P<0.001), and 27.3 (4.8), 27.0 (4.5) and 25.9 (4.9) kg/m2 in men (P=0.04), respectively; median weight was 66.5 (16.1), 65.0 (16.4) and 63.4 (13.7) kg in women (P=0.003), and 81.5 (17.0), 81.4 (16.4) and 80.3 (17.1) kg in men (P=0.36). Median height was 161 (8), 162 (9) and 163 (8) cm in women (P=0.005), and 173 (9), 174 (9) and 174 (11) cm in men (P=0.09). The corresponding medians for AST (Aspartate Aminotransferase) were 31 (13), 29 (11) and 28 (10) U/L (P=0.002), and 28 (17), 27 (14) and 26 (19) U/L for ALT (Alanin Aminotransferase, P=0.053) in men. In multivariable analyses, greater parental longevity was associated with lower BMI, lower weight and taller stature in women (P<0.01) and lower AST in men (P=0.011). No significant associations were observed for the other variables analyzed. Sensitivity analyses restricted to subjects whose parents were dead (N=1844) led to similar results, with even stronger associations of parental longevity with liver enzymes in men. Conclusion: In women, increased parental longevity was associated with smaller BMI, attributable to lower weight and taller stature. In men, the association of increased parental longevity with lower liver enzymes, independently of BMI, suggests that parental longevity may be associated with decreased nonalcoholic fatty liver disease.