Intermolecular interactions and characterization of the novel factor Xa exosite involved in macromolecular recognition and inhibition: Crystal structure of human Gla-domainless factor Xa complexed with the anticoagulant protein NAPc2 from the hematophagous nematode Ancylostoma caninum

NAPc2, an anticoagulant protein from the hematophagous nematode Ancylostoma caninum evaluated in phase-II/IIa clinical trials, inhibits the extrinsic blood coagulation pathway by a two step mechanism, initially interacting with the hitherto uncharacterized factor Xa exosite involved in macromolecular recognition and subsequently inhibiting factor VIIa (K-i = 8.4 pM) of the factor VIIa/tissue factor complex. NAPc2 is highly flexible, becoming partially ordered and undergoing significant structural changes in the C terminus upon binding to the factor Xa exosite. In the crystal structure of the ternary factor Xa/NAPc2/selectide complex, the binding interface consists of an intermolecular antiparallel beta-sheet formed by the segment of the polypeptide chain consisting of residues 74-80 of NAPc2 with the residues 86-93 of factor Xa that is additional maintained by contacts between the short helical segment (residues 67-73) and a turn (residues 26-29) of NAPc2 with the short C-terminal helix of factor Xa (residues 233-243). This exosite is physiologically highly relevant for the recognition and inhibition of factor X/Xa by macromolecular substrates and provides a structural motif for the development of a new class of inhibitors for the treatment of deep vein thrombosis and angioplasty. (c) 2006 Elsevier Ltd. All rights reserved.

Recognition and distribution of Leptodactylus mystaceus (Anura; Leptodactylidae) in the State of São Paulo, Southeastern Brazil

Leptodactylus mystaceus, uma espécie com ampla distribuição geográfica pela América do Sul, é diagnosticada com base em exemplares do Estado de São Paulo, seu limite meridional de distribuição geográfica. Apresentamos aqui o primeiro registro da espécie para o Sudeste do Brasil, ampliando sua distribuição conhecida em cerca de 1.300 km ao sudeste. Também incluímos a descrição da vocalização de anúncio, informações sobre história natural, fotografia em vida e desenhos de caracteres morfológicos que auxiliam na identificação desta espécie.

Computer-assisted analysis of p53 and PCNA expression in oral lesions infected with human papillomavirus

OBJECTIVE: To carry out a retrospective study to determine whether human papillomavirus (HPV) infection and immunohistochemical expression of p53 and proliferating cell nuclear antigen (PCNA) are related to the risk of oral cancer. STUDY DESIGN: Fifty-seven oral biopsies, consisting of 30 oral squamous papillomas (OSPs) and 27 oral squamous cell carcinomas (OSCCs) were tested for the presence of HPV 6/11 and 16/18 by in situ hybridization using catalyzed signal amplification and in situ hybridization. p53 And PCNA expression was analyzed by immunohistochemistry and evaluated quantitatively by image analysis. RESULTS: Nineteen of the 57 oral lesions (33.3%) were positive for HPV. HPV 6/11 was found in 6 of 30 (20%) OSPs and 1 of 27 (3.7%) OSCCs. HPV 16/18 was found in 10 of 27 (37%) OSCCs and 2 of 30 (6.7%) OSPs. Sixteen of the 19 HPV-positive cases (84.2%) were p53 negative; 5 (9%) were HPV 6/11 and 11 (19%) HPV 16/18, with an inverse correlation between the presence of HPV DNA and p53 expression (P=.017, P < .05). PCNA expression appeared in 18 (94.7%) of HPV positive cases, showing that HPV 16/18 was associated with intensity of PCNA expression and with OSCCs (P=.037, P < .05). CONCLUSION: Quantitative evaluation of p53 by image analysis showed an inverse correlation between p53 expression and HPV presence, suggesting protein degradation. Image analysis also demonstrated that PCNA expression was more intense in HPV DNA 16/18 OSCCs. These findings suggest involvement of high-risk HPV types in oral carcinogenesis.

Automated extraction of road network from medium-and high-resolution images

This paper presents an automatic methodology for road network extraction from medium-and high-resolution aerial images. It is based on two steps. In the first step, the road seeds (i.e., road segments) are extracted using a set of four road objects and another set of connection rules among road objects. Each road object is a local representation of an approximately straight road fragment and its construction is based on a combination of polygons describing all relevant image edges, according to some rules embodying road knowledge. Each road seed is composed by a sequence of connected road objects in which each sequence of this type can be geometrically structured as a chain of contiguous quadrilaterals. In the second step, two strategies for road completion are applied in order to generate the complete road network. The first strategy is based on two basic perceptual grouping rules, i.e., proximity and collinearity rules, which allow the sequential reconstruction of gaps between every pair of disconnected road segments. This strategy does not allow the reconstruction of road crossings, but it allows the extraction of road centerlines from the contiguous quadrilaterals representing connected road segments. The second strategy for road completion aims at reconstructing road crossings. Firstly, the road centerlines are used to find reference points for road crossings, which are their approximate positions. Then these points are used to extract polygons representing the contours of road crossings. This paper presents the proposed methodology and experimental results. © Pleiades Publishing, Inc. 2006.

An intelligent system to detect drilling problems through drilled cuttings return analysis

Cuttings return analysis is an important tool to detect and prevent problems during the petroleum well drilling process. Several measurements and tools have been developed for drilling problems detection, including mud logging, PWD and downhole torque information. Cuttings flow meters were developed in the past to provide information regarding cuttings return at the shale shakers. Their use, however, significantly impact the operation including rig space issues, interferences in geological analysis besides, additional personel required. This article proposes a non intrusive system to analyze the cuttings concentration at the shale shakers, which can indicate problems during drilling process, such as landslide, the collapse of the well borehole walls. Cuttings images are acquired by a high definition camera installed above the shakers and sent to a computer coupled with a data analysis system which aims the quantification and closure of a cuttings material balance in the well surface system domain. No additional people at the rigsite are required to operate the system. Modern Artificial intelligence techniques are used for pattern recognition and data analysis. Techniques include the Optimum-Path Forest (OPF), Artificial Neural Network using Multilayer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC). Field test results conducted on offshore floating vessels are presented. Results show the robustness of the proposed system, which can be also integrated with other data to improve the efficiency of drilling problems detection. Copyright 2010, IADC/SPE Drilling Conference and Exhibition.

Attitude of Brazilian veterinarians in the recognition and treatment of pain in horses and cattle

Objective: The objective of this study was to assess the use of analgesics, describe the attitudes of Brazilian veterinarians towards pain relief in horses and cattle and evaluate the differences due to gender, year of graduation and type of practice. Study design: Prospective survey. Methods: Questionnaires were sent to 1000 large animal veterinarians by mail, internet and delivered in person during national meetings. The survey investigated the attitudes of Brazilian veterinarians to the recognition and treatment of pain in large animals and consisted of sections asking about demographic data, use of analgesic drugs, attitudes to pain relief and to the assessment of pain. Descriptive statistics were used to analyze frequencies. Simple post hoc comparisons were performed using the chi-square test. Results: Eight hundred questionnaires were collected, but 87 were discarded because they were incomplete or blank. The opioid of choice for use in large animals was butorphanol (43.4%) followed by tramadol (39%). Flunixin (83.2%) and ketoprofen (67.6%) were the most frequently used NSAIDs by Brazilian veterinarians. Respondents indicated that horses received preoperative analgesics for laparotomy more frequently (72.9%) than cattle (58.5%). The most frequently administered preoperative drugs for laparotomy in horses were flunixin (38.4%) and xylazine (23.6%), whereas the preoperative drugs for the same surgical procedure in cattle were xylazine (31.8%) and the local administration of lidocaine (48%). Fracture repair was considered the most painful surgical procedure for both species. Most veterinarians (84.1%) believed that their knowledge in this area was not adequate. Conclusions and clinical relevance: Although these Brazilian veterinarians thought that their knowledge on recognition and treatment of pain was not adequate, the use of analgesic in large animals was similar in Brazil to that reported in other countries. © 2013 Association of Veterinary Anaesthetists and the American College of Veterinary Anesthesia and Analgesia.

Padrões fractais: contribuições ao processo de generalização de conteúdos matemáticos

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Scanning Electron Microscopy of Male Terminalia and Its Application to Species Recognition and Phylogenetic Reconstruction in the Drosophila saltans Group

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Physiological and pathophysiological interactions between the respiratory central pattern generator and the sympathetic nervous system

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

HOW FAR do WE GET USING MACHINE LEARNING BLACK-BOXES?

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Structural FRF acquisition via electric impedance measurement applied to damage location

Continuing development of new materials makes systems lighter and stronger permitting more complex systems to provide more functionality and flexibility that demands a more effective evaluation of their structural health. Smart material technology has become an area of increasing interest in this field. The combination of smart materials and artificial neural networks can be used as an excellent tool for pattern recognition, turning their application adequate for monitoring and fault classification of equipment and structures. In order to identify the fault, the neural network must be trained using a set of solutions to its corresponding forward Variational problem. After the training process, the net can successfully solve the inverse variational problem in the context of monitoring and fault detection because of their pattern recognition and interpolation capabilities. The use of structural frequency response function is a fundamental portion of structural dynamic analysis, and it can be extracted from measured electric impedance through the electromechanical interaction of a piezoceramic and a structure. In this paper we use the FRF obtained by a mathematical model (FEM) in order to generate the training data for the neural networks, and the identification of damage can be done by measuring electric impedance, since suitable data normalization correlates FRF and electrical impedance.

The Canny detector with edge region focusing using an anisotropic diffusion process

This paper proposes a methodology for edge detection in digital images using the Canny detector, but associated with a priori edge structure focusing by a nonlinear anisotropic diffusion via the partial differential equation (PDE). This strategy aims at minimizing the effect of the well-known duality of the Canny detector, under which is not possible to simultaneously enhance the insensitivity to image noise and the localization precision of detected edges. The process of anisotropic diffusion via thePDE is used to a priori focus the edge structure due to its notable characteristic in selectively smoothing the image, leaving the homogeneous regions strongly smoothed and mainly preserving the physical edges, i.e., those that are actually related to objects presented in the image. The solution for the mentioned duality consists in applying the Canny detector to a fine gaussian scale but only along the edge regions focused by the process of anisotropic diffusion via the PDE. The results have shown that the method is appropriate for applications involving automatic feature extraction, since it allowed the high-precision localization of thinned edges, which are usually related to objects present in the image. © Nauka/Interperiodica 2006.

Construction of perfect space-time codes

In this work, we propose an innovative methodology to extend the construction of minimum and non-minimum delay perfect codes as a subset of cyclic division algebras over ℚ(ζ3), where the signal constellations are isomorphic to the hexagonal An 2 -rotated lattice, for any channel of any dimension n such that gcd{n, 3) = 1.

Análise e extração de características de imagens termográficas utilizando componentes principais

Pós-graduação em Engenharia Mecânica - FEIS