Manganese-enhanced magnetic resonance imaging detects mossy fiber sprouting in the pilocarpine model of epilepsy

Purpose: Mossy fiber sprouting (MFS) is a frequent finding following status epilepticus (SE). The present study aimed to test the feasibility of using manganese-enhanced magnetic resonance imaging (MEMRI) to detect MFS in the chronic phase of the well-established pilocarpine (Pilo) rat model of temporal lobe epilepsy (TLE). Methods: To modulate MFS, cycloheximide (CHX), a protein synthesis inhibitor, was coadministered with Pilo in a subgroup of animals. In vivo MEMRI was performed 3 months after induction of SE and compared to the neo-Timm histologic labeling of zinc mossy fiber terminals in the dentate gyrus (DG). Key Findings: Chronically epileptic rats displaying MFS as detected by neo-Timm histology had a hyperintense MEMRI signal in the DG, whereas chronically epileptic animals that did not display MFS had minimal MEMRI signal enhancement compared to nonepileptic control animals. A strong correlation (r = 0.81, p < 0.001) was found between MEMRI signal enhancement and MFS. Significance: This study shows that MEMRI is an attractive noninvasive method for detection of mossy fiber sprouting in vivo and can be used as an evaluation tool in testing therapeutic approaches to manage chronic epilepsy.

Biogeographic and diversification patterns of Neotropical Troidini butterflies (Papilionidae) support a museum model of diversity dynamics for Amazonia

Background: The temporal and geographical diversification of Neotropical insects remains poorly understood because of the complex changes in geological and climatic conditions that occurred during the Cenozoic. To better understand extant patterns in Neotropical biodiversity, we investigated the evolutionary history of three Neotropical swallowtail Troidini genera (Papilionidae). First, DNA-based species delimitation analyses were conducted to assess species boundaries within Neotropical Troidini using an enlarged fragment of the standard barcode gene. Molecularly delineated species were then used to infer a time-calibrated species-level phylogeny based on a three-gene dataset and Bayesian dating analyses. The corresponding chronogram was used to explore their temporal and geographical diversification through distinct likelihood-based methods. Results: The phylogeny for Neotropical Troidini was well resolved and strongly supported. Molecular dating and biogeographic analyses indicate that the extant lineages of Neotropical Troidini have a late Eocene (33-42 Ma) origin in North America. Two independent lineages (Battus and Euryades + Parides) reached South America via the GAARlandia temporary connection, and later became extinct in North America. They only began substantive diversification during the early Miocene in Amazonia. Macroevolutionary analysis supports the "museum model" of diversification, rather than Pleistocene refugia, as the best explanation for the diversification of these lineages. Conclusions: This study demonstrates that: (i) current Neotropical biodiversity may have originated ex situ; (ii) the GAARlandia bridge was important in facilitating invasions of South America; (iii) colonization of Amazonia initiated the crown diversification of these swallowtails; and (iv) Amazonia is not only a species-rich region but also acted as a sanctuary for the dynamics of this diversity. In particular, Amazonia probably allowed the persistence of old lineages and contributed to the steady accumulation of diversity over time with constant net diversification rates, a result that contrasts with previous studies on other South American butterflies.

Spatio-temporal patterns of tuberculosis incidence in Ribeirão Preto, State of São Paulo, southeast Brazil, and their relationship with social vulnerability: a Bayesian analysis

INTRODUCTION: The purpose of this ecological study was to evaluate the urban spatial and temporal distribution of tuberculosis (TB) in Ribeirão Preto, State of São Paulo, southeast Brazil, between 2006 and 2009 and to evaluate its relationship with factors of social vulnerability such as income and education level. METHODS: We evaluated data from TBWeb, an electronic notification system for TB cases. Measures of social vulnerability were obtained from the SEADE Foundation, and information about the number of inhabitants, education and income of the households were obtained from Brazilian Institute of Geography and Statistics. Statistical analyses were conducted by a Bayesian regression model assuming a Poisson distribution for the observed new cases of TB in each area. A conditional autoregressive structure was used for the spatial covariance structure. RESULTS: The Bayesian model confirmed the spatial heterogeneity of TB distribution in Ribeirão Preto, identifying areas with elevated risk and the effects of social vulnerability on the disease. We demonstrated that the rate of TB was correlated with the measures of income, education and social vulnerability. However, we observed areas with low vulnerability and high education and income, but with high estimated TB rates. CONCLUSIONS: The study identified areas with different risks for TB, given that the public health system deals with the characteristics of each region individually and prioritizes those that present a higher propensity to risk of TB. Complex relationships may exist between TB incidence and a wide range of environmental and intrinsic factors, which need to be studied in future research.

Spatio-temporal variability of sugarcane yield efficiency in the state of São Paulo, Brazil

The objective of this work was to assess the spatial and temporal variability of sugarcane yield efficiency and yield gap in the state of São Paulo, Brazil, throughout 16 growing seasons, considering climate and soil as main effects, and socioeconomic factors as complementary. An empirical model was used to assess potential and attainable yields, using climate data series from 37 weather stations. Soil effects were analyzed using the concept of production environments associated with a soil aptitude map for sugarcane. Crop yield efficiency increased from 0.42 to 0.58 in the analyzed period (1990/1991 to 2005/2006 crop seasons), and yield gap consequently decreased from 58 to 42%. Climatic factors explained 43% of the variability of sugarcane yield efficiency, in the following order of importance: solar radiation, water deficit, maximum air temperature, precipitation, and minimum air temperature. Soil explained 15% of the variability, considering the average of all seasons. There was a change in the correlation pattern of climate and soil with yield efficiency after the 2001/2002 season, probably due to the crop expansion to the west of the state during the subsequent period. Socioeconomic, biotic and crop management factors together explain 42% of sugarcane yield efficiency in the state of São Paulo.

Psychiatric comorbidities in temporal lobe epilepsy: possible relationships between psychotic disorders and involvement of limbic circuits

OBJECTIVE: Mounting evidence suggests that the limbic system is pathologically involved in cases of psychiatric comorbidities in temporal lobe epilepsy (TLE) patients. Our objective was to develop a conceptual framework describing how neuropathological and connectivity changes might contribute to the development of psychosis and to the potential neurobiological mechanisms that cause schizophrenia-like psychosis in TLE patients. METHODS: In this review, clinical and neuropathological findings, especially brain circuitry of the limbic system, were examined together to enhance our understanding of the association between TLE and psychosis. Finally, the importance of animal models in epilepsy and psychiatric disorders was discussed. CONCLUSIONS: TLE and psychiatric symptoms coexist more frequently than chance would predict. Damage and deregulation among critical anatomical regions, such as the hippocampus, amygdala, thalamus, and the temporal, frontal and cingulate cortices, might predispose TLE brains to psychosis. Studies of the effects of kindling and injection of neuroactive substances on behavior and electrophysiological patterns may offer a model of how limbic seizures in humans increase the vulnerability of TLE patients to psychiatric symptoms.

Classification of the severity of diabetic neuropathy: a new approach taking uncertainties into account using fuzzy logic

OBJECTIVE: This study proposes a new approach that considers uncertainty in predicting and quantifying the presence and severity of diabetic peripheral neuropathy. METHODS: A rule-based fuzzy expert system was designed by four experts in diabetic neuropathy. The model variables were used to classify neuropathy in diabetic patients, defining it as mild, moderate, or severe. System performance was evaluated by means of the Kappa agreement measure, comparing the results of the model with those generated by the experts in an assessment of 50 patients. Accuracy was evaluated by an ROC curve analysis obtained based on 50 other cases; the results of those clinical assessments were considered to be the gold standard. RESULTS: According to the Kappa analysis, the model was in moderate agreement with expert opinions. The ROC analysis (evaluation of accuracy) determined an area under the curve equal to 0.91, demonstrating very good consistency in classifying patients with diabetic neuropathy. CONCLUSION: The model efficiently classified diabetic patients with different degrees of neuropathy severity. In addition, the model provides a way to quantify diabetic neuropathy severity and allows a more accurate patient condition assessment.

Evolução temporal da proliferação neointimal após implante de dois tipos de stent farmacológico com polímeros biodegradáveis em modelo porcino: avaliação qualitativa por tomografia de coerência óptica sequencial

INTRODUÇÃO: Baseados na hipótese de que a neoíntima encontrada em stents farmacológicos (SFs) com polímeros biodegradáveis aos 28 dias não é a neoíntima definitiva e de que a tomografia de coerência óptica (TCO) é um método eficaz para a avaliação sequencial da neoíntima, objetivamos, neste estudo experimental, comparar os achados da TCO aos 28 dias e aos 90 dias em dois tipos de SF com polímeros biodegradáveis: o stent liberador de sirolimus (Inspiron®, Scitech) e o stent liberador de biolimus A9 (Biomatrix®, Biosensors International). MÉTODOS: No total, 6 porcos não-ateroscleróticos foram submetidos a implante de 6 stents Inspiron® e de 6 stents Biomatrix®. Cada porco recebeu os dois tipos de stent, um em cada artéria coronária (descendente anterior e circunflexa) e após 28 dias e 90 dias foram realizadas avaliações qualitativas intrastent a cada milímetro com TCO. RESULTADOS: A avaliação qualitativa, feita por pareamento milímetro a milímetro intrastent, evidenciou neoíntima heterogênea em 39% aos 28 dias e em 0% aos 90 dias, presença de tecido intraluminal em 18% aos 28 dias e em 0% aos 90 dias, irregularidade luminal em 62% aos 28 dias e em 2% aos 90 dias (P < 0,005). Não houve diferença entre os grupos quanto à qualidade da neoíntima ao longo do tempo (P > 0,05). CONCLUSÕES: Os achados à TCO corroboram a hipótese de que a neoíntima encontrada em SFs com polímeros biodegradáveis aos 28 dias não é a neoíntima definitiva. A evidência experimental mais significativa é a mudança das características da neoíntima observada à TCO sequencial.

Temporal changes of CB1 cannabinoid receptor in the basal ganglia as a possible structure-specific plasticity process in 6-OHDA lesioned rats

The endocannabinoid system has been implicated in several neurobiological processes, including neurodegeneration, neuroprotection and neuronal plasticity. The CB1 cannabinoid receptors are abundantly expressed in the basal ganglia, the circuitry that is mostly affected in Parkinson’s Disease (PD). Some studies show variation of CB1 expression in basal ganglia in different animal models of PD, however the results are quite controversial, due to the differences in the procedures employed to induce the parkinsonism and the periods analyzed after the lesion. The present study evaluated the CB1 expression in four basal ganglia structures, namely striatum, external globus pallidus (EGP), internal globus pallidus (IGP) and substantia nigra pars reticulata (SNpr) of rats 1, 5, 10, 20, and 60 days after unilateral intrastriatal 6-hydroxydopamine injections, that causes retrograde dopaminergic degeneration. We also investigated tyrosine hydroxylase (TH), parvalbumin, calbindin and glutamic acid decarboxylase (GAD) expression to verify the status of dopaminergic and GABAergic systems. We observed a structure-specific modulation of CB1 expression at different periods after lesions. In general, there were no changes in the striatum, decreased CB1 in IGP and SNpr and increased CB1 in EGP, but this increase was not sustained over time. No changes in GAD and parvalbumin expression were observed in basal ganglia, whereas TH levels were decreased and the calbindin increased in striatum in short periods after lesion. We believe that the structure-specific variation of CB1 in basal ganglia in the 6-hydroxydopamine PD model could be related to a compensatory process involving the GABAergic transmission, which is impaired due to the lack of dopamine. Our data, therefore, suggest that the changes of CB1 and calbindin expression may represent a plasticity process in this PD model

Optical flow estimation with consistent spatio-temporal coherence models

[EN] In this work we propose a new variational model for the consistent estimation of motion fields. The aim of this work is to develop appropriate spatio-temporal coherence models. In this sense, we propose two main contributions: a nonlinear flow constancy assumption, similar in spirit to the nonlinear brightness constancy assumption, which conveniently relates flow fields at different time instants; and a nonlinear temporal regularization scheme, which complements the spatial regularization and can cope with piecewise continuous motion fields. These contributions pose a congruent variational model since all the energy terms, except the spatial regularization, are based on nonlinear warpings of the flow field. This model is more general than its spatial counterpart, provides more accurate solutions and preserves the continuity of optical flows in time. In the experimental results, we show that the method attains better results and, in particular, it considerably improves the accuracy in the presence of large displacements.

Temporal constraints in large optical flow estimation

[EN] The aim of this work is to propose a model for computing the optical flow in a sequence of images. We introduce a new temporal regularizer that is suitable for large displacements. We propose to decouple the spatial and temporal regularizations to avoid an incongruous formulation. For the spatial regularization we use the Nagel-Enkelmann operator and a newly designed temporal regularization. Our model is based on an energy functional that yields a partial differential equation (PDE). This PDE is embedded into a multipyramidal strategy to recover large displacements. A gradient descent technique is applied at each scale to reach the minimum.

Assimilation of Meteosat Second Generation (MSG) satellite data in a regional numerical weather prediction model using a one-dimensional variational approach

The quality of temperature and humidity retrievals from the infrared SEVIRI sensors on the geostationary Meteosat Second Generation (MSG) satellites is assessed by means of a one dimensional variational algorithm. The study is performed with the aim of improving the spatial and temporal resolution of available observations to feed analysis systems designed for high resolution regional scale numerical weather prediction (NWP) models. The non-hydrostatic forecast model COSMO (COnsortium for Small scale MOdelling) in the ARPA-SIM operational configuration is used to provide background fields. Only clear sky observations over sea are processed. An optimised 1D–VAR set-up comprising of the two water vapour and the three window channels is selected. It maximises the reduction of errors in the model backgrounds while ensuring ease of operational implementation through accurate bias correction procedures and correct radiative transfer simulations. The 1D–VAR retrieval quality is firstly quantified in relative terms employing statistics to estimate the reduction in the background model errors. Additionally the absolute retrieval accuracy is assessed comparing the analysis with independent radiosonde and satellite observations. The inclusion of satellite data brings a substantial reduction in the warm and dry biases present in the forecast model. Moreover it is shown that the retrieval profiles generated by the 1D–VAR are well correlated with the radiosonde measurements. Subsequently the 1D–VAR technique is applied to two three–dimensional case–studies: a false alarm case–study occurred in Friuli–Venezia–Giulia on the 8th of July 2004 and a heavy precipitation case occurred in Emilia–Romagna region between 9th and 12th of April 2005. The impact of satellite data for these two events is evaluated in terms of increments in the integrated water vapour and saturation water vapour over the column, in the 2 meters temperature and specific humidity and in the surface temperature. To improve the 1D–VAR technique a method to calculate flow–dependent model error covariance matrices is also assessed. The approach employs members from an ensemble forecast system generated by perturbing physical parameterisation schemes inside the model. The improved set–up applied to the case of 8th of July 2004 shows a substantial neutral impact.

Multitemporal analysis of satellite imagery: implementation of a land evolution model in ALCS (ATSR LAND CLASSIFICATION SYSTEM)

In this report it was designed an innovative satellite-based monitoring approach applied on the Iraqi Marshlands to survey the extent and distribution of marshland re-flooding and assess the development of wetland vegetation cover. The study, conducted in collaboration with MEEO Srl , makes use of images collected from the sensor (A)ATSR onboard ESA ENVISAT Satellite to collect data at multi-temporal scales and an analysis was adopted to observe the evolution of marshland re-flooding. The methodology uses a multi-temporal pixel-based approach based on classification maps produced by the classification tool SOIL MAPPER ®. The catalogue of the classification maps is available as web service through the Service Support Environment Portal (SSE, supported by ESA). The inundation of the Iraqi marshlands, which has been continuous since April 2003, is characterized by a high degree of variability, ad-hoc interventions and uncertainty. Given the security constraints and vastness of the Iraqi marshlands, as well as cost-effectiveness considerations, satellite remote sensing was the only viable tool to observe the changes taking place on a continuous basis. The proposed system (ALCS – AATSR LAND CLASSIFICATION SYSTEM) avoids the direct use of the (A)ATSR images and foresees the application of LULCC evolution models directly to „stock‟ of classified maps. This approach is made possible by the availability of a 13 year classified image database, conceived and implemented in the CARD project (http://earth.esa.int/rtd/Projects/#CARD).The approach here presented evolves toward an innovative, efficient and fast method to exploit the potentiality of multi-temporal LULCC analysis of (A)ATSR images. The two main objectives of this work are both linked to a sort of assessment: the first is to assessing the ability of modeling with the web-application ALCS using image-based AATSR classified with SOIL MAPPER ® and the second is to evaluate the magnitude, the character and the extension of wetland rehabilitation.

Local scale air quality model with several pollutant sources

[EN]This paper shows a finite element method for pollutant transport with several pollutant sources. An Eulerian convection–diffusion–reaction model to simulate the pollutant dispersion is used. The discretization of the different sources allows to impose the emissions as boundary conditions. The Eulerian description can deal with the coupling of several plumes. An adaptive stabilized finite element formulation, specifically Least-Squares, with a Crank-Nicolson temporal integration is proposed to solve the problem. An splitting scheme has been used to treat separately the transport and the reaction. A mass-consistent model has been used to compute the wind field of the problem…

Specification and Verification of Declarative Open Interaction Models - A Logic-based framework

The advent of distributed and heterogeneous systems has laid the foundation for the birth of new architectural paradigms, in which many separated and autonomous entities collaborate and interact to the aim of achieving complex strategic goals, impossible to be accomplished on their own. A non exhaustive list of systems targeted by such paradigms includes Business Process Management, Clinical Guidelines and Careflow Protocols, Service-Oriented and Multi-Agent Systems. It is largely recognized that engineering these systems requires novel modeling techniques. In particular, many authors are claiming that an open, declarative perspective is needed to complement the closed, procedural nature of the state of the art specification languages. For example, the ConDec language has been recently proposed to target the declarative and open specification of Business Processes, overcoming the over-specification and over-constraining issues of classical procedural approaches. On the one hand, the success of such novel modeling languages strongly depends on their usability by non-IT savvy: they must provide an appealing, intuitive graphical front-end. On the other hand, they must be prone to verification, in order to guarantee the trustworthiness and reliability of the developed model, as well as to ensure that the actual executions of the system effectively comply with it. In this dissertation, we claim that Computational Logic is a suitable framework for dealing with the specification, verification, execution, monitoring and analysis of these systems. We propose to adopt an extended version of the ConDec language for specifying interaction models with a declarative, open flavor. We show how all the (extended) ConDec constructs can be automatically translated to the CLIMB Computational Logic-based language, and illustrate how its corresponding reasoning techniques can be successfully exploited to provide support and verification capabilities along the whole life cycle of the targeted systems.

Implementation of a non ground meta interpreter for defeasible logic

Human reasoning is a fascinating and complex cognitive process that can be applied in different research areas such as philosophy, psychology, laws and financial. Unfortunately, developing supporting software (to those different areas) able to cope such as complex reasoning it’s difficult and requires a suitable logic abstract formalism. In this thesis we aim to develop a program, that has the job to evaluate a theory (a set of rules) w.r.t. a Goal, and provide some results such as “The Goal is derivable from the KB5 (of the theory)”. In order to achieve this goal we need to analyse different logics and choose the one that best meets our needs. In logic, usually, we try to determine if a given conclusion is logically implied by a set of assumptions T (theory). However, when we deal with programming logic we need an efficient algorithm in order to find such implications. In this work we use a logic rather similar to human logic. Indeed, human reasoning requires an extension of the first order logic able to reach a conclusion depending on not definitely true6 premises belonging to a incomplete set of knowledge. Thus, we implemented a defeasible logic7 framework able to manipulate defeasible rules. Defeasible logic is a non-monotonic logic designed for efficient defeasible reasoning by Nute (see Chapter 2). Those kind of applications are useful in laws area especially if they offer an implementation of an argumentation framework that provides a formal modelling of game. Roughly speaking, let the theory is the set of laws, a keyclaim is the conclusion that one of the party wants to prove (and the other one wants to defeat) and adding dynamic assertion of rules, namely, facts putted forward by the parties, then, we can play an argumentative challenge between two players and decide if the conclusion is provable or not depending on the different strategies performed by the players. Implementing a game model requires one more meta-interpreter able to evaluate the defeasible logic framework; indeed, according to Göedel theorem (see on page 127), we cannot evaluate the meaning of a language using the tools provided by the language itself, but we need a meta-language able to manipulate the object language8. Thus, rather than a simple meta-interpreter, we propose a Meta-level containing different Meta-evaluators. The former has been explained above, the second one is needed to perform the game model, and the last one will be used to change game execution and tree derivation strategies.