Role of eosinophilic airway inflammation in models of asthma

Eosinophils play a central role in the establishment and outcome of bronchial inflammation in asthma. Animal models of allergy are useful to answer questions related to mechanisms of allergic inflammation. We have used models of sensitized and boosted guinea pigs to investigate the nature of bronchial inflammation in allergic conditions. These animals develop marked bronchial infiltration composed mainly of CD4+ T-lymphocytes and eosinophils. Further provocation with antigen leads to degranulation of eosinophils and ulceration of the bronchial mucosa. Eosinophils are the first cells to increase in numbers in the mucosa after antigen challenge and depend on the expression of alpha 4 integrin to adhere to the vascular endothelium and transmigrate to the mucosa. Blockage of alpha4 integrin expression with specific antibody prevents not only the transmigration of eosinophils but also the development of bronchial hyperresponsiveness (BHR) to agonists in sensitized and challenged animals, clearly suggesting a role for this cell type in this altered functional state. Moreover, introduction of antibody against Major Basic Protein into the airways also prevents the development of BHR in similar model. BHR can also be suppressed by the use of FK506, an immunosuppressor that reduces in almost 100% the infiltration of eosinophils into the bronchi of allergic animals. These data support the concept that eosinophil is the most important pro-inflammatory factor in bronchial inflammation associated with allergy.

Stochastic time-concentration activity models for cytotoxicity in 3D brain cell cultures.

BACKGROUND: In vitro aggregating brain cell cultures containing all types of brain cells have been shown to be useful for neurotoxicological investigations. The cultures are used for the detection of nervous system-specific effects of compounds by measuring multiple endpoints, including changes in enzyme activities. Concentration-dependent neurotoxicity is determined at several time points. METHODS: A Markov model was set up to describe the dynamics of brain cell populations exposed to potentially neurotoxic compounds. Brain cells were assumed to be either in a healthy or stressed state, with only stressed cells being susceptible to cell death. Cells may have switched between these states or died with concentration-dependent transition rates. Since cell numbers were not directly measurable, intracellular lactate dehydrogenase (LDH) activity was used as a surrogate. Assuming that changes in cell numbers are proportional to changes in intracellular LDH activity, stochastic enzyme activity models were derived. Maximum likelihood and least squares regression techniques were applied for estimation of the transition rates. Likelihood ratio tests were performed to test hypotheses about the transition rates. Simulation studies were used to investigate the performance of the transition rate estimators and to analyze the error rates of the likelihood ratio tests. The stochastic time-concentration activity model was applied to intracellular LDH activity measurements after 7 and 14 days of continuous exposure to propofol. The model describes transitions from healthy to stressed cells and from stressed cells to death. RESULTS: The model predicted that propofol would affect stressed cells more than healthy cells. Increasing propofol concentration from 10 to 100 μM reduced the mean waiting time for transition to the stressed state by 50%, from 14 to 7 days, whereas the mean duration to cellular death reduced more dramatically from 2.7 days to 6.5 hours. CONCLUSION: The proposed stochastic modeling approach can be used to discriminate between different biological hypotheses regarding the effect of a compound on the transition rates. The effects of different compounds on the transition rate estimates can be quantitatively compared. Data can be extrapolated at late measurement time points to investigate whether costs and time-consuming long-term experiments could possibly be eliminated.

Sensitivity of predictive species distribution models to change in grain size

Predictive species distribution modelling (SDM) has become an essential tool in biodiversity conservation and management. The choice of grain size (resolution) of environmental layers used in modelling is one important factor that may affect predictions. We applied 10 distinct modelling techniques to presence-only data for 50 species in five different regions, to test whether: (1) a 10-fold coarsening of resolution affects predictive performance of SDMs, and (2) any observed effects are dependent on the type of region, modelling technique, or species considered. Results show that a 10 times change in grain size does not severely affect predictions from species distribution models. The overall trend is towards degradation of model performance, but improvement can also be observed. Changing grain size does not equally affect models across regions, techniques, and species types. The strongest effect is on regions and species types, with tree species in the data sets (regions) with highest locational accuracy being most affected. Changing grain size had little influence on the ranking of techniques: boosted regression trees remain best at both resolutions. The number of occurrences used for model training had an important effect, with larger sample sizes resulting in better models, which tended to be more sensitive to grain. Effect of grain change was only noticeable for models reaching sufficient performance and/or with initial data that have an intrinsic error smaller than the coarser grain size.

Hierarchical conditional random fields for parts based models matching

A parts based model is a parametrization of an object class using a collection of landmarks following the object structure. The matching of parts based models is one of the problems where pairwise Conditional Random Fields have been successfully applied. The main reason of their effectiveness is tractable inference and learning due to the simplicity of involved graphs, usually trees. However, these models do not consider possible patterns of statistics among sets of landmarks, and thus they sufffer from using too myopic information. To overcome this limitation, we propoese a novel structure based on a hierarchical Conditional Random Fields, which we explain in the first part of this memory. We build a hierarchy of combinations of landmarks, where matching is performed taking into account the whole hierarchy. To preserve tractable inference we effectively sample the label set. We test our method on facial feature selection and human pose estimation on two challenging datasets: Buffy and MultiPIE. In the second part of this memory, we present a novel approach to multiple kernel combination that relies on stacked classification. This method can be used to evaluate the landmarks of the parts-based model approach. Our method is based on combining responses of a set of independent classifiers for each individual kernel. Unlike earlier approaches that linearly combine kernel responses, our approach uses them as inputs to another set of classifiers. We will show that we outperform state-of-the-art methods on most of the standard benchmark datasets.

Factors associated with schistosomiasis mansoni in a population from the municipality of Jaboticatubas, State of Minas Gerais, Brazil

Jaboticatubas is a municipality in the metropolitan region of Belo Horizonte which has been a target of a wide media release as "the capital of schistosomiasis" since the 1960's. In order to give support to a work based on an integrated control, we sought to identify the disease determinants at the site. A transversal study was carried out aimed at identifying prevalence rates of the disease and factors associated with the infection in the district of São José de Almeida, and two close localities, Cipó Velho and São José da Serra, all of them located in the municipality of Jaboticatubas. A parasitological survey was performed, applying the Kato-Katz method with two slides per sample in 1186 schoolchildren which represents 77% of all registered pupils in four public schools in 2001. Among these schoolchildren a number of 101 (8.6%) prooved positive for Schistosoma mansoni eggs in their stool samples. A total of 64 families, whose schoolchildren had shown to be positive for schistosomiasis, also undertook examinations. As negative control, a random sample was collected from the 206 families, whose children had proven negative for schistosomiasis. The prevalence among 270 families (1304 people) was 12%. To assess those who continued to have contact with possibly contaminated water, 1061 (81.4%) people of the 270 families were interviewed. A multivariate analysis identified the following factors associated with the infection: time of residence in the area (short period), garbage disposal (use of deserted areas), gender (male), age (from 10 to 29 years), and water contact (daily and weekly). Further analysis of these factors revealed a close correlation between water contact and the disease, with a positive significant frequency concerning almost all those items. Depending on gender and age significant variations of water contact patterns associated with leisure and professional activities were found. A malacological survey on water collections in the area identified snails of the species Biomphalaria straminea and B. glabrata. The latter showed 17 (0.6%) specimens positive for S. mansoni. Qualitative studies have complemented such evidences, which allowed us to design a reference picture and specific indicators of the disease for the local population. Those data provided the essential information to continue the development of an already ongoing educative process, as well as projects on environmental improvements.

Beclin 1 mitigates motor and neuropathological deficits in genetic mouse models of Machado-Joseph disease.

Machado-Joseph disease or spinocerebellar ataxia type 3, the most common dominantly-inherited spinocerebellar ataxia, results from translation of the polyglutamine-expanded and aggregation prone ataxin 3 protein. Clinical manifestations include cerebellar ataxia and pyramidal signs and there is no therapy to delay disease progression. Beclin 1, an autophagy-related protein and essential gene for cell survival, is decreased in several neurodegenerative disorders. This study aimed at evaluating if lentiviral-mediated beclin 1 overexpression would rescue motor and neuropathological impairments when administered to pre- and post-symptomatic lentiviral-based and transgenic mouse models of Machado-Joseph disease. Beclin 1-mediated significant improvements in motor coordination, balance and gait with beclin 1-treated mice equilibrating longer periods in the Rotarod and presenting longer and narrower footprints. Furthermore, in agreement with the improvements observed in motor function beclin 1 overexpression prevented neuronal dysfunction and neurodegeneration, decreasing formation of polyglutamine-expanded aggregates, preserving Purkinje cell arborization and immunoreactivity for neuronal markers. These data show that overexpression of beclin 1 in the mouse cerebellum is able to rescue and hinder the progression of motor deficits when administered to pre- and post-symptomatic stages of the disease.

Estat de la qüestió de l'estudi de l'aspecte lèxic : una proposta cognitiva de classficació d'esdeveniments

Peer-reviewed

Statistical modeling on coordinates

This paper is a first draft of the principle of statistical modelling on coordinates. Several causes —which would be long to detail—have led to this situation close to the deadline for submitting papers to CODAWORK’03. The main of them is the fast development of the approach along thelast months, which let appear previous drafts as obsolete. The present paper contains the essential parts of the state of the art of this approach from my point of view. I would like to acknowledge many clarifying discussions with the group of people working in this field in Girona, Barcelona, Carrick Castle, Firenze, Berlin, G¨ottingen, and Freiberg. They have given a lot of suggestions and ideas. Nevertheless, there might be still errors or unclear aspects which are exclusively my fault. I hope this contribution serves as a basis for further discussions and new developments

Accuracy profile validation of a new method for carbon monoxide measurement in the human blood using headspace-gas chromatography-mass spectrometry (HS-GC-MS).

The aim of our study was to provide an innovative headspace-gas chromatography-mass spectrometry (HS-GC-MS) method applicable for the routine determination of blood CO concentration in forensic toxicology laboratories. The main drawback of the GC/MS methods discussed in literature for CO measurement is the absence of a specific CO internal standard necessary for performing quantification. Even if stable isotope of CO is commercially available in the gaseous state, it is essential to develop a safer method to limit the manipulation of gaseous CO and to precisely control the injected amount of CO for spiking and calibration. To avoid the manipulation of a stable isotope-labeled gas, we have chosen to generate in a vial in situ, an internal labeled standard gas ((13)CO) formed by the reaction of labeled formic acid formic acid (H(13)COOH) with sulfuric acid. As sulfuric acid can also be employed to liberate the CO reagent from whole blood, the procedure allows for the liberation of CO simultaneously with the generation of (13)CO. This method allows for precise measurement of blood CO concentrations from a small amount of blood (10 μL). Finally, this method was applied to measure the CO concentration of intoxicated human blood samples from autopsies.

A geoprocessing approach for studying and controlling schistosomiasis in the state of Minas Gerais, Brazil

Geographical information systems (GIS) are tools that have been recently tested for improving our understanding of the spatial distribution of disease. The objective of this paper was to further develop the GIS technology to model and control schistosomiasis using environmental, social, biological and remote-sensing variables. A final regression model (R² = 0.39) was established, after a variable selection phase, with a set of spatial variables including the presence or absence of Biomphalaria glabrata, winter enhanced vegetation index, summer minimum temperature and percentage of houses with water coming from a spring or well. A regional model was also developed by splitting the state of Minas Gerais (MG) into four regions and establishing a linear regression model for each of the four regions: 1 (R² = 0.97), 2 (R² = 0.60), 3 (R² = 0.63) and 4 (R² = 0.76). Based on these models, a schistosomiasis risk map was built for MG. In this paper, geostatistics was also used to make inferences about the presence of Biomphalaria spp. The result was a map of species and risk areas. The obtained risk map permits the association of uncertainties, which can be used to qualify the inferences and it can be thought of as an auxiliary tool for public health strategies.

Biological, biochemical and molecular features of Trypanosoma cruzi strains isolated from patients infected through oral transmission during a 2005 outbreak in the state of Santa Catarina, Brazil: its correspondence with the new T. cruzi Taxonomy Consensus (2009)

We examined strains of Trypanosoma cruzi isolated from patients with acute Chagas disease that had been acquired by oral transmission in the state of Santa Catarina, Brazil (2005) and two isolates that had been obtained from a marsupial (Didelphis aurita) and a vector (Triatoma tibiamaculata). These strains were characterised through their biological behaviour and isoenzymic profiles and genotyped according to the new Taxonomy Consensus (2009) based on the discrete typing unities, that is, T. cruzi genotypes I-VI. All strains exhibited the biological behaviour of biodeme type II. In six isolates, late peaks of parasitaemia, beyond the 20th day, suggested a double infection with biodemes II + III. Isoenzymes revealed Z2 or mixed Z1 and Z2 profiles. Genotyping was performed using three polymorphic genes (cytochrome oxidase II, spliced leader intergenic region and 24Sα rRNA) and the restriction fragment length polymorphism of the kDNA minicircles. Based on these markers, all but four isolates were characterised as T. cruzi II genotypes. Four mixed populations were identified: SC90, SC93 and SC97 (T. cruzi I + T. cruzi II) and SC95 (T. cruzi I + T. cruzi VI). Comparison of the results obtained by different methods was essential for the correct identification of the mixed populations and major lineages involved indicating that characterisation by different methods can provide new insights into the relationship between phenotypic and genotypic aspects of parasite behaviour.

Predicting the geographic distribution of Lutzomyia longipalpis (Diptera: Psychodidae) and visceral leishmaniasis in the state of Mato Grosso do Sul, Brazil

To understand the geographic distribution of visceral leishmaniasis (VL) in the state of Mato Grosso do Sul (MS), Brazil, both the climatic niches of Lutzomyia longipalpis and VL cases were analysed. Distributional data were obtained from 55 of the 79 counties of MS between 2003-2012. Ecological niche models (ENM) of Lu. longipalpis and VL cases were produced using the maximum entropy algorithm based on eight climatic variables. Lu. longipalpis showed a wide distribution in MS. The highest climatic suitability for Lu. longipalpis was observed in southern MS. Temperature seasonality and annual mean precipitation were the variables that most influenced these models. Two areas of high climatic suitability for the occurrence of VL cases were predicted: one near Aquidauana and another encompassing several municipalities in the southeast region of MS. As expected, a large overlap between the models for Lu. longipalpis and VL cases was detected. Northern and northwestern areas of MS were suitable for the occurrence of cases, but did not show high climatic suitability for Lu. longipalpis . ENM of vectors and human cases provided a greater understanding of the geographic distribution of VL in MS, which can be applied to the development of future surveillance strategies.

State-of-the-art treatment of hypertension: established and new drugs.

The treatment of essential hypertension is based essentially on the prescription of four major classes of antihypertensive drugs, i.e. blockers of the renin-angiotensin system, calcium channel blockers, diuretics and beta-blockers. In recent years, very few new drug therapies of hypertension have become available. Therefore, it is crucial for physicians to optimize their antihypertensive therapies with the drugs available on the market. In each of the classes of antihypertensive drugs, questions have recently been raised: are angiotensin-converting enzyme (ACE) inhibitors superior to angiotensin II receptor blockers (ARB)? Is it possible to reduce the incidence of peripheral oedema with calcium antagonists? Is hydrochlorothiazide really the good diuretic to use in combination therapies? The purpose of this review is to discuss these various questions in the light of the most recent clinical studies and meta-analyses. These latter suggest that ACE inhibitors and ARB are equivalent except for a better tolerability profile of ARB. Third generation calcium channel blockers enable to reduce the incidence of peripheral oedema and chlorthalidone is certainly more effective than hydrochlorothiazide in preventing cardiovascular events in hypertension. At last, studies suggest that drug adherence and long-term persistence under therapy is one of the major issues in the actual management of essential hypertension.

Modelling world investment markets using threshold conditional correlation models

In this paper we propose a parsimonious regime-switching approach to model the correlations between assets, the threshold conditional correlation (TCC) model. This method allows the dynamics of the correlations to change from one state (or regime) to another as a function of observable transition variables. Our model is similar in spirit to Silvennoinen and Teräsvirta (2009) and Pelletier (2006) but with the appealing feature that it does not suffer from the course of dimensionality. In particular, estimation of the parameters of the TCC involves a simple grid search procedure. In addition, it is easy to guarantee a positive definite correlation matrix because the TCC estimator is given by the sample correlation matrix, which is positive definite by construction. The methodology is illustrated by evaluating the behaviour of international equities, govenrment bonds and major exchange rates, first separately and then jointly. We also test and allow for different parts in the correlation matrix to be governed by different transition variables. For this, we estimate a multi-threshold TCC specification. Further, we evaluate the economic performance of the TCC model against a constant conditional correlation (CCC) estimator using a Diebold-Mariano type test. We conclude that threshold correlation modelling gives rise to a significant reduction in portfolio´s variance.

A public health risk assessment for yellow fever vaccination: a model exemplified by an outbreak in the state of São Paulo, Brazil

We propose a method to analyse the 2009 outbreak in the region of Botucatu in the state of São Paulo (SP), Brazil, when 28 yellow fever (YF) cases were confirmed, including 11 deaths. At the time of the outbreak, the Secretary of Health of the State of São Paulo vaccinated one million people, causing the death of five individuals, an unprecedented number of YF vaccine-induced fatalities. We apply a mathematical model described previously to optimise the proportion of people who should be vaccinated to minimise the total number of deaths. The model was used to calculate the optimum proportion that should be vaccinated in the remaining, vaccine-free regions of SP, considering the risk of vaccine-induced fatalities and the risk of YF outbreaks in these regions.