Estratificação vertical de formigas em cerrado strictu sensu no Parque Estadual da Serra de Caldas Novas, Goiás, Brasil

Formicidae é um grupo abundante no solo e também largamente distribuído em todos os estratos da vegetação, constituindo-se em um bom modelo biológico para estudos de estratificação vertical. O objetivo geral do trabalho foi determinar os padrões de estratificação da assembléia de formigas em três estratos verticais (solo, estrato arbustivo e estrato arbóreo). Os dados foram coletados no Parque Estadual da Serra de Caldas Novas, em uma área de cerrado strictu sensu. A coleta de formigas foi realizada utilizando-se armadilhas do tipo pitfall. Foram instaladas 11 armadilhas no solo, 17 em plantas do estrato arbustivo e 23 em plantas do estrato arbóreo (uma armadilha por planta). Foi coletado um total de 49 espécies de formigas, pertencentes a 15 gêneros e cinco subfamílias. Através de curvas de acumulação de espécies, pôde-se verificar que existem 37,5% a mais de espécies no solo do que nas árvores e 35% a mais de espécies nas árvores do que nos arbustos. Uma análise de agrupamento indicou uma similaridade mediana entre as espécies de formigas do solo e vegetação (estrato arbustivo e arbóreo). Uma análise de aninhamento demonstrou que as espécies presentes no solo são um subconjunto das espécies presentes nos dois estratos de vegetação. Mesmo sem uma estratificação vertical muito clara, a alta diversidade de formigas encontrada no cerrado pode ser explicada em parte pelo fato de algumas espécies serem especializadas em forragear e/ou nidificar no solo e outras na vegetação.

Particulate formulations for the delivery of poly(I:C) as vaccine adjuvant.

Current research and development of antigens for vaccination often center on purified recombinant proteins, viral subunits, synthetic oligopeptides or oligosaccharides, most of them suffering from being poorly immunogenic and subject to degradation. Hence, they call for efficient delivery systems and potent immunostimulants, jointly denoted as adjuvants. Particulate delivery systems like emulsions, liposomes, nanoparticles and microspheres may provide protection from degradation and facilitate the co-formulation of both the antigen and the immunostimulant. Synthetic double-stranded (ds) RNA, such as polyriboinosinic acid-polyribocytidylic acid, poly(I:C), is a mimic of viral dsRNA and, as such, a promising immunostimulant candidate for vaccines directed against intracellular pathogens. Poly(I:C) signaling is primarily dependent on Toll-like receptor 3 (TLR3), and on melanoma differentiation-associated gene-5 (MDA-5), and strongly drives cell-mediated immunity and a potent type I interferon response. However, stability and toxicity issues so far prevented the clinical application of dsRNAs as they undergo rapid enzymatic degradation and bear the potential to trigger undue immune stimulation as well as autoimmune disorders. This review addresses these concerns and suggests strategies to improve the safety and efficacy of immunostimulatory dsRNA formulations. The focus is on technological means required to lower the necessary dosage of poly(I:C), to target surface-modified microspheres passively or actively to antigen-presenting cells (APCs), to control their interaction with non-professional phagocytes and to modulate the resulting cytokine secretion profile.

A two-compartment mathematical model of neuroglial metabolism using [1-(11)C] acetate.

The purpose of this study was to develop a two-compartment metabolic model of brain metabolism to assess oxidative metabolism from [1-(11)C] acetate radiotracer experiments, using an approach previously applied in (13)C magnetic resonance spectroscopy (MRS), and compared with an one-tissue compartment model previously used in brain [1-(11)C] acetate studies. Compared with (13)C MRS studies, (11)C radiotracer measurements provide a single uptake curve representing the sum of all labeled metabolites, without chemical differentiation, but with higher temporal resolution. The reliability of the adjusted metabolic fluxes was analyzed with Monte-Carlo simulations using synthetic (11)C uptake curves, based on a typical arterial input function and previously published values of the neuroglial fluxes V(tca)(g), V(x), V(nt), and V(tca)(n) measured in dynamic (13)C MRS experiments. Assuming V(x)(g)=10 × V(tca)(g) and V(x)(n)=V(tca)(n), it was possible to assess the composite glial tricarboxylic acid (TCA) cycle flux V(gt)(g) (V(gt)(g)=V(x)(g) × V(tca)(g)/(V(x)(g)+V(tca)(g))) and the neurotransmission flux V(nt) from (11)C tissue-activity curves obtained within 30 minutes in the rat cortex with a beta-probe after a bolus infusion of [1-(11)C] acetate (n=9), resulting in V(gt)(g)=0.136±0.042 and V(nt)=0.170±0.103 μmol/g per minute (mean±s.d. of the group), in good agreement with (13)C MRS measurements.

The generator problem for Z-stable C*-algebras

The generator problem was posed by Kadison in 1967, and it remains open until today. We provide a solution for the class of C*-algebras absorbing the Jiang-Su algebra Z tensorially. More precisely, we show that every unital, separable, Z-stable C*-algebra A is singly generated, which means that there exists an element x є A that is not contained in any proper sub-C*- algebra of A. To give applications of our result, we observe that Z can be embedded into the reduced group C*-algebra of a discrete group that contains a non-cyclic, free subgroup. It follows that certain tensor products with reduced group C*-algebras are singly generated. In particular, C*r (F ∞) ⨂ C*r (F ∞) is singly generated.

Cloning and characterization of a V-ATPase subunit C from the American visceral leishmaniasis vector Lutzomyia longipalpis modulated during development and blood ingestion

Visceral leishmaniasis (VL) is a serious tropical disease that affects approximately 500 thousand people worldwide every year. In the Americas, VL is caused by the parasite Leishmania (Leishmania) infantum chagasi mainly transmitted by the bite of the sand fly vector Lutzomyia longipalpis. Despite recent advances in the study of interaction between Leishmania and sand flies, very little is known about sand fly protein expression profiles. Understanding how the expression of proteins may be affected by blood feeding and/or presence of parasite in the vector's midgut might allow us to devise new strategies for controlling the spread of leishmaniasis. In this work, we report the characterization of a vacuolar ATPase subunit C from L. longipalpis by screening of a midgut cDNA library with a 220 bp fragment identified by means of differential display reverse transcriptase-polymerase chain reaction analysis. The expression of the gene varies along insect development and is upregulated in males and bloodfed L. longipalpis, compared to unfed flies.

Assessment of adipose tissue metabolism by means of subcutaneous microdialysis in patients with sepsis or circulatory failure.

To evaluate the role of adipose tissue in the metabolic stress response of critically ill patients, the release of glycerol and lactate by subcutaneous adipose tissue was assessed by means of microdialysis in patients with sepsis or circulatory failure and in healthy subjects. Patients with sepsis had lower plasma free fatty acid concentrations and non-significant elevations of plasma glycerol concentrations, but higher adipose-systemic glycerol concentrations gradients than healthy subjects or patients with circulatory failure, indicating a stimulation of subcutaneous adipose lipolysis. They also had a higher lipid oxidation. Lipid metabolism (adipose-systemic glycerol gradients, lipid oxidation) was not altered in patients with circulatory failure. These observations highlight major differences in lipolysis and lipid utilization between patients with sepsis and circulatory failure. Hyperlactataemia was present in both groups of patients, but the adipose-systemic lactate concentration gradient was not increased, indicating that lactate production by adipose tissue was not involved. This speaks against a role of adipose tissue in the development of hyperlactataemia in critically ill patients.

A Homogeneous Set-Theoretical Frame for Clustering Fuzzy Relational Data

Our purpose is to provide a set-theoretical frame to clustering fuzzy relational data basically based on cardinality of the fuzzy subsets that represent objects and their complementaries, without applying any crisp property. From this perspective we define a family of fuzzy similarity indexes which includes a set of fuzzy indexes introduced by Tolias et al, and we analyze under which conditions it is defined a fuzzy proximity relation. Following an original idea due to S. Miyamoto we evaluate the similarity between objects and features by means the same mathematical procedure. Joining these concepts and methods we establish an algorithm to clustering fuzzy relational data. Finally, we present an example to make clear all the process

Effective diagnosis of Alzheimer's disease by means of large margin-based methodology.

BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).

Prospective comparison of MR enteroclysis with multidetector spiral-CT enteroclysis: interobserver agreement and sensitivity by means of "sign-by-sign" correlation.

Our objective was a prospective comparison of MR enteroclysis (MRE) with multidetector spiral-CT enteroclysis (MSCTE). Fifty patients with various suspected small bowel diseases were investigated by MSCTE and MRE. The MSCTE was performed using slices of 2.5 mm, immediately followed by MRE, obtaining T1- and T2-weighted sequences, including gadolinium-enhanced acquisition with fat saturation. Three radiologists independently evaluated MSCTE and MRE searching for 12 pathological signs. Interobserver agreement was calculated. Sensitivities and specificities resulted from comparison with pathological results ( n=29) and patient's clinical evolution ( n=21). Most pathological signs, such as bowel wall thickening (BWT), bowel wall enhancement (BWE) and lymphadenopathy (ADP), showed better interobserver agreement on MSCTE than on MRE (BWT: 0.65 vs 0.48; BWE: 0.51 vs 0.37; ADP: 0.52 vs 0.15). Sensitivity of MSCTE was higher than that of MRE in detecting BWT (88.9 vs 60%), BWE (78.6 vs 55.5%) and ADP (63.8 vs 14.3%). Wilcoxon signed-rank test revealed significantly better sensitivity of MSCTE than that of MRE for each observer ( p=0.028, p=0.046, p=0.028, respectively). Taking the given study design into account, MSCTE provides better sensitivity in detecting lesions of the small bowel than MRE, with higher interobserver agreement.

Discovering similarities in the time use patterns of the Spanish Autonomous Communities by Fuzzy techniques

In 2000 the European Statistical Office published the guidelines for developing theHarmonized European Time Use Surveys system. Under such a unified framework,the first Time Use Survey of national scope was conducted in Spain during 2002–03. The aim of these surveys is to understand human behavior and the lifestyle ofpeople. Time allocation data are of compositional nature in origin, that is, they aresubject to non-negativity and constant-sum constraints. Thus, standard multivariatetechniques cannot be directly applied to analyze them. The goal of this work is toidentify homogeneous Spanish Autonomous Communities with regard to the typicalactivity pattern of their respective populations. To this end, fuzzy clustering approachis followed. Rather than the hard partitioning of classical clustering, where objects areallocated to only a single group, fuzzy method identify overlapping groups of objectsby allowing them to belong to more than one group. Concretely, the probabilistic fuzzyc-means algorithm is conveniently adapted to deal with the Spanish Time Use Surveymicrodata. As a result, a map distinguishing Autonomous Communities with similaractivity pattern is drawn.Key words: Time use data, Fuzzy clustering; FCM; simplex space; Aitchison distance

Ciclo de vida organizacional pautado no modelo de Lester, Parnell e Carraher (2003) e na lógica fuzzy: classificação de empresas de um segmento industrial de Santa Catarina

Neste estudo, objetiva-se identificar os estágios do ciclo de vida organizacional pautados no modelo de Lester, Parnell e Carraher (2003) das empresas do segmento industrial de máquinas, aparelhos e materiais elétricos do estado de Santa Catarina. Pesquisa descritiva, com abordagem quantitativa, foi realizada por meio de levantamento com aplicação de questionário aos gestores das empresas. A população constituiu-se das 264 empresas desse segmento econômico, listadas na Secretaria da Fazenda do Estado de Santa Catarina, e a amostra não aleatória das 40 empresas que responderam a pesquisa. As variáveis de identificação dos estágios de ciclo de vida utilizadas no questionário foram extraídas de Lester, Parnell e Carraher (2003). Os dados da pesquisa foram submetidos à técnica estatística denominada lógica fuzzy. Os resultados da pesquisa demonstraram que 57,5% das empresas foram classificadas no estágio do nascimento, 15% do, 7,5% da Maturidade, 10% do rejuvenescimento e 10% do declínio. Concluiu-se que determinados estágios do ciclo de vida organizacional estão próximos uns dos outros e que não se pode perceber claramente uma progressão determinista nas fases do ciclo de vida, como uma sequência única, definitiva e irreversível, no sentido tradicional biológico.

Spatial relationship between the atmospheric circulation and the precipitation measured in the western Swiss Alps by means of the analogue method

An adaptation technique based on the synoptic atmospheric circulation to forecast local precipitation, namely the analogue method, has been implemented for the western Swiss Alps. During the calibration procedure, relevance maps were established for the geopotential height data. These maps highlight the locations were the synoptic circulation was found of interest for the precipitation forecasting at two rain gauge stations (Binn and Les Marécottes) that are located both in the alpine Rhône catchment, at a distance of about 100 km from each other. These two stations are sensitive to different atmospheric circulations. We have observed that the most relevant data for the analogue method can be found where specific atmospheric circulation patterns appear concomitantly with heavy precipitation events. Those skilled regions are coherent with the atmospheric flows illustrated, for example, by means of the back trajectories of air masses. Indeed, the circulation recurrently diverges from the climatology during days with strong precipitation on the southern part of the alpine Rhône catchment. We have found that for over 152 days with precipitation amount above 50 mm at the Binn station, only 3 did not show a trajectory of a southerly flow, meaning that such a circulation was present for 98% of the events. Time evolution of the relevance maps confirms that the atmospheric circulation variables have significantly better forecasting skills close to the precipitation period, and that it seems pointless for the analogue method to consider circulation information days before a precipitation event as a primary predictor. Even though the occurrence of some critical circulation patterns leading to heavy precipitation events can be detected by precursors at remote locations and 1 week ahead (Grazzini, 2007; Martius et al., 2008), time extrapolation by the analogue method seems to be rather poor. This would suggest, in accordance with previous studies (Obled et al., 2002; Bontron and Obled, 2005), that time extrapolation should be done by the Global Circulation Model, which can process atmospheric variables that can be used by the adaptation method.

Discourse Type Clustering using POS n-gram Profiles and High-Dimensional Embeddings

Abstract: To cluster textual sequence types (discourse types/modes) in French texts, K-means algorithm with high-dimensional embeddings and fuzzy clustering algorithm were applied on clauses whose POS (part-ofspeech) n-gram profiles were previously extracted. Uni-, bi- and trigrams were used on four 19th century French short stories by Maupassant. For high-dimensional embeddings, power transformations on the chi-squared distances between clauses were explored. Preliminary results show that highdimensional embeddings improve the quality of clustering, contrasting the use of bi and trigrams whose performance is disappointing, possibly because of feature space sparsity.