INCREASED SARCOLEMMAL PERMEABILITY AS AN EARLY EVENT IN EXPERIMENTAL SEPTIC CARDIOMYOPATHY: A POTENTIAL ROLE FOR OXIDATIVE DAMAGE TO LIPIDS AND PROTEINS

This study describes increased sarcolemmal permeability and myofilamentar damage that occur together with lipid peroxidation and protein nitration in the myocardium in severe sepsis induced by cecal ligation and puncture. Male C57BL/6 mice were submitted to moderate and severe septic injury and sham operation. Using light and laser confocal microscopy, diffuse foci of myocytolysis associated with focal disruption of the actin/myosin contractile apparatus could be seen in hearts with severe septic injury. The myocardial expressions of the sarcomeric proteins myosin and actin were downregulated by both severe and moderate injuries. The detection of albumin staining in the cytoplasm of myocytes to evaluate sarcolemmal permeability provided evidence of severe and mild injury of the plasma membrane in hearts with severe and moderate septic injury, respectively. The administration of a superoxide scavenger caused marked reduction of sarcolemmal permeability, indicating the involvement of free radicals in its genesis. On electron microscopy, these changes were seen to correspond to spread blocks of a few myocytes with fragmentation and dissolution of myofibrils, intracellular edema, and, occasionally, rupture of the sarcolemma. In addition, oxidative damage to lipids, using anti-4-hydroxynonenal, an indicator of oxidative stress and disruption of plasma membrane lipids, and to proteins, using antinitrotyrosine, a stable biomarker of peroxynitrite-mediated protein nitration, was demonstrated. These findings make plausible the hypothesis that increased sarcolemmal permeability might be a primary event in myocardial injury in severe sepsis possibly due to oxidative damage to lipids and proteins that could precede phenotypic changes that characterize a septic cardiomyopathy.

Detection of Auditory Cortex Activity by fMRI Using a Dependent Component Analysis

Functional MRI (fMRI) data often have low signal-to-noise-ratio (SNR) and are contaminated by strong interference from other physiological sources. A promising tool for extracting signals, even under low SNR conditions, is blind source separation (BSS), or independent component analysis (ICA). BSS is based on the assumption that the detected signals are a mixture of a number of independent source signals that are linearly combined via an unknown mixing matrix. BSS seeks to determine the mixing matrix to recover the source signals based on principles of statistical independence. In most cases, extraction of all sources is unnecessary; instead, a priori information can be applied to extract only the signal of interest. Herein we propose an algorithm based on a variation of ICA, called Dependent Component Analysis (DCA), where the signal of interest is extracted using a time delay obtained from an autocorrelation analysis. We applied such method to inspect functional Magnetic Resonance Imaging (fMRI) data, aiming to find the hemodynamic response that follows neuronal activation from an auditory stimulation, in human subjects. The method localized a significant signal modulation in cortical regions corresponding to the primary auditory cortex. The results obtained by DCA were also compared to those of the General Linear Model (GLM), which is the most widely used method to analyze fMRI datasets.

The SARS algorithm: detrending CoRoT light curves with Sysrem using simultaneous external parameters

Surveys for exoplanetary transits are usually limited not by photon noise but rather by the amount of red noise in their data. In particular, although the CoRoT space-based survey data are being carefully scrutinized, significant new sources of systematic noises are still being discovered. Recently, a magnitude-dependant systematic effect was discovered in the CoRoT data by Mazeh et al. and a phenomenological correction was proposed. Here we tie the observed effect to a particular type of effect, and in the process generalize the popular Sysrem algorithm to include external parameters in a simultaneous solution with the unknown effects. We show that a post-processing scheme based on this algorithm performs well and indeed allows for the detection of new transit-like signals that were not previously detected.

A Parallel Hardware Architecture for Scale and Rotation Invariant Feature Detection

This paper proposes a parallel hardware architecture for image feature detection based on the Scale Invariant Feature Transform algorithm and applied to the Simultaneous Localization And Mapping problem. The work also proposes specific hardware optimizations considered fundamental to embed such a robotic control system on-a-chip. The proposed architecture is completely stand-alone; it reads the input data directly from a CMOS image sensor and provides the results via a field-programmable gate array coupled to an embedded processor. The results may either be used directly in an on-chip application or accessed through an Ethernet connection. The system is able to detect features up to 30 frames per second (320 x 240 pixels) and has accuracy similar to a PC-based implementation. The achieved system performance is at least one order of magnitude better than a PC-based solution, a result achieved by investigating the impact of several hardware-orientated optimizations oil performance, area and accuracy.

Objective Detection and Delineation of Oral Neoplasia Using Autofluorescence Imaging

Although the oral cavity is easily accessible to inspection, patients with oral cancer most often present at a late stage, leading to high morbidity and mortality. Autofluorescence imaging has emerged as a promising technology to aid clinicians in screening for oral neoplasia and as an aid to resection, but current approaches rely on subjective interpretation. We present a new method to objectively delineate neoplastic oral mucosa using autofluorescence imaging. Autofluorescence images were obtained from 56 patients with oral lesions and 11 normal volunteers. From these images, 276 measurements from 159 unique regions of interest (ROI) sites corresponding to normal and confirmed neoplastic areas were identified. Data from ROIs in the first 46 subjects were used to develop a simple classification algorithm based on the ratio of red-to-green fluorescence; performance of this algorithm was then validated using data from the ROIs in the last 21 subjects. This algorithm was applied to patient images to create visual disease probability maps across the field of view. Histologic sections of resected tissue were used to validate the disease probability maps. The best discrimination between neoplastic and nonneoplastic areas was obtained at 405 nm excitation; normal tissue could be discriminated from dysplasia and invasive cancer with a 95.9% sensitivity and 96.2% specificity in the training set, and with a 100% sensitivity and 91.4% specificity in the validation set. Disease probability maps qualitatively agreed with both clinical impression and histology. Autofluorescence imaging coupled with objective image analysis provided a sensitive and noninvasive tool for the detection of oral neoplasia.

Multiple camera people detection and tracking using support integration

This paper proposes a method to locate and track people by combining evidence from multiple cameras using the homography constraint. The proposed method use foreground pixels from simple background subtraction to compute evidence of the location of people on a reference ground plane. The algorithm computes the amount of support that basically corresponds to the ""foreground mass"" above each pixel. Therefore, pixels that correspond to ground points have more support. The support is normalized to compensate for perspective effects and accumulated on the reference plane for all camera views. The detection of people on the reference plane becomes a search for regions of local maxima in the accumulator. Many false positives are filtered by checking the visibility consistency of the detected candidates against all camera views. The remaining candidates are tracked using Kalman filters and appearance models. Experimental results using challenging data from PETS`06 show good performance of the method in the presence of severe occlusion. Ground truth data also confirms the robustness of the method. (C) 2010 Elsevier B.V. All rights reserved.

Detection of human cytomegalovirus and Epstein-Barr virus in coronary atherosclerotic tissue

Previous studies indicated that patients with atherosclerosis are predominantly infected by human cytomegalovirus (HCMV), but rarely infected by type 1 Epstein-Barr virus (EBV-1). In this study, atheromas of 30 patients who underwent aortocoronary bypass surgery with coronary endartherectomy were tested for the presence of these two viruses. HCMV occurred in 93.3% of the samples and EBV-1 was present in 50% of them. Concurrent presence of both pathogens was detected in 43.3% of the samples.

Validity and reliability of methods for the detection of secondary caries around amalgam restorations in primary teeth

Secondary caries has been reported as the main reason for restoration replacement. The aim of this in vitro study was to evaluate the performance of different methods - visual inspection, laser fluorescence (DIAGNOdent), radiography and tactile examination - for secondary caries detection in primary molars restored with amalgam. Fifty-four primary molars were photographed and 73 suspect sites adjacent to amalgam restorations were selected. Two examiners evaluated independently these sites using all methods. Agreement between examiners was assessed by the Kappa test. To validate the methods, a caries-detector dye was used after restoration removal. The best cut-off points for the sample were found by a Receiver Operator Characteristic (ROC) analysis, and the area under the ROC curve (Az), and the sensitivity, specificity and accuracy of the methods were calculated for enamel (D2) and dentine (D3) thresholds. These parameters were found for each method and then compared by the McNemar test. The tactile examination and visual inspection presented the highest inter-examiner agreement for the D2 and D3 thresholds, respectively. The visual inspection also showed better performance than the other methods for both thresholds (Az = 0.861 and Az = 0.841, respectively). In conclusion, the visual inspection presented the best performance for detecting enamel and dentin secondary caries in primary teeth restored with amalgam.

Spatial pattern detection modeling of thrips (Thrips tabaci) on onion fields

Onion (Allium cepa) is one of the most cultivated and consumed vegetables in Brazil and its importance is due to the large laborforce involved. One of the main pests that affect this crop is the Onion Thrips (Thrips tabaci), but the spatial distribution of this insect, although important, has not been considered in crop management recommendations, experimental planning or sampling procedures. Our purpose here is to consider statistical tools to detect and model spatial patterns of the occurrence of the onion thrips. In order to characterize the spatial distribution pattern of the Onion Thrips a survey was carried out to record the number of insects in each development phase on onion plant leaves, on different dates and sample locations, in four rural properties with neighboring farms under different infestation levels and planting methods. The Mantel randomization test proved to be a useful tool to test for spatial correlation which, when detected, was described by a mixed spatial Poisson model with a geostatistical random component and parameters allowing for a characterization of the spatial pattern, as well as the production of prediction maps of susceptibility to levels of infestation throughout the area.

Detection of Brucella ovis in ovine from Paraíba State, in the Northeast region of Brazil

To determine the presence of Brucella ovis in ovine from Paraíba State, in the Northeast region of Brazil, 80 animals slaughtered in the public slaughterhouse of Patos city were used. Before slaughter, blood samples were collected by jugular venopuncture from each animal, and after slaughter, testicles, epidydimus and uterus were aseptically collected. For the serological diagnosis of B. ovis and B. abortus infections, the agar gel immunodiffusion (AGID) and Rose Bengal (RBT) tests were carried out, respectively. In addition, microbiological culture and polymerase chain reaction (PCR) were performed on testicle, epidydimus and uterus samples. Six animals (7.5%) tested positive for the presence of B. ovis antibodies and all animals tested negative for the presence of B. abortus antibodies. One AGID-positive animal tested positive at uterine swab culture. PCR was able to amplify DNA of Brucella spp. from the pool of testicle, epidydimus and uterus samples from AGID-positive animals. This is the first report of isolation and detection of B. ovis DNA by PCR in ovine from the Northeast region of Brazil.

Evaluation of DNA extraction protocols for Brucella abortus pcr detection in aborted fetuses or calves born from cows experimentally infected with strain 2308

The objective of the present study was to improve the detection of B. abortus by PCR in organs of aborted fetuses from infected cows, an important mechanism to find infected herds on the eradication phase of the program. So, different DNA extraction protocols were compared, focusing the PCR detection of B. abortus in clinical samples collected from aborted fetuses or calves born from cows challenged with the 2308 B. abortus strain. Therefore, two gold standard groups were built based on classical bacteriology, formed from: 32 lungs (17 positives), 26 spleens (11 positives), 23 livers (8 positives) and 22 bronchial lymph nodes (7 positives). All samples were submitted to three DNA extraction protocols, followed by the same amplification process with the primers B4 and B5. From the accumulated results for organ, the proportion of positives for the lungs was higher than the livers (p=0.04) or bronchial lymph nodes (p=0.004) and equal to the spleens (p=0.18). From the accumulated results for DNA extraction protocol, the proportion of positives for the Boom protocol was bigger than the PK (p<0.0001) and GT (p=0.0004). There was no difference between the PK and GT protocols (p=0.5). Some positive samples from the classical bacteriology were negative to the PCR and viceversa. Therefore, the best strategy for B. abortus detection in the organs of aborted fetuses or calves born from infected cows is the use, in parallel, of isolation by classical bacteriology and the PCR, with the DNA extraction performed by the Boom protocol.

The mitochondrial genome of the stingless bee Melipona bicolor (Hymenoptera, Apidae, Meliponini): sequence, gene organization and a unique tRNA translocation event conserved across the tribe Meliponini

At present a complete mtDNA sequence has been reported for only two hymenopterans, the Old World honey bee, Apis mellifera and the sawfly Perga condei. Among the bee group, the tribe Meliponini (stingless bees) has some distinction due to its Pantropical distribution, great number of species and large importance as main pollinators in several ecosystems, including the Brazilian rain forest. However few molecular studies have been conducted on this group of bees and few sequence data from mitochondrial genomes have been described. In this project, we PCR amplified and sequenced 78% of the mitochondrial genome of the stingless bee Melipona bicolor (Apidae, Meliponini). The sequenced region contains all of the 13 mitochondrial protein-coding genes, 18 of 22 tRNA genes, and both rRNA genes (one of them was partially sequenced). We also report the genome organization (gene content and order), gene translation, genetic code, and other molecular features, such as base frequencies, codon usage, gene initiation and termination. We compare these characteristics of M. bicolor to those of the mitochondrial genome of A. mellifera and other insects. A highly biased A+T content is a typical characteristic of the A. mellifera mitochondrial genome and it was even more extreme in that of M. bicolor. Length and compositional differences between M. bicolor and A. mellifera genes were detected and the gene order was compared. Eleven tRNA gene translocations were observed between these two species. This latter finding was surprising, considering the taxonomic proximity of these two bee tribes. The tRNA Lys gene translocation was investigated within Meliponini and showed high conservation across the Pantropical range of the tribe.

A closer look at multiple-clone Plasmodium vivax infections: detection methods, prevalence and consequences

The naturally occurring clonal diversity among field isolates of the major human malaria parasite Plasmodium vivax remained unexplored until the early 1990s, when improved molecular methods allowed the use of blood samples obtained directly from patients, without prior in vitro culture, for genotyping purposes. Here we briefly review the molecular strategies currently used to detect genetically distinct clones in patient-derived P. vivax samples, present evidence that multiple-clone P. vivax infections are commonly detected in areas with different levels of malaria transmission and discuss possible evolutionary and epidemiological consequences of the competition between genetically distinct clones in natural human infections. We suggest that, when two or more genetically distinct clones are present in the same host, intra-host competition for limited resources may select for P. vivax traits that represent major public health challenges, such as increased virulence, increased transmissibility and antimalarial drug resistance.

Pre-processing for noise detection in gene expression classification data

Due to the imprecise nature of biological experiments, biological data is often characterized by the presence of redundant and noisy data. This may be due to errors that occurred during data collection, such as contaminations in laboratorial samples. It is the case of gene expression data, where the equipments and tools currently used frequently produce noisy biological data. Machine Learning algorithms have been successfully used in gene expression data analysis. Although many Machine Learning algorithms can deal with noise, detecting and removing noisy instances from the training data set can help the induction of the target hypothesis. This paper evaluates the use of distance-based pre-processing techniques for noise detection in gene expression data classification problems. This evaluation analyzes the effectiveness of the techniques investigated in removing noisy data, measured by the accuracy obtained by different Machine Learning classifiers over the pre-processed data.

Development of instrumentation for amperometric and coulometric detection using ultramicroelectrodes

In this work it is presented the development of a simple, portable and inexpensive instrumentation for amperometric and coulometric detection in different analytical instrumentation systems utilizing ultramicroelectrodes. The software, developed in LabVIEW 7.1TM, is capable to carry out three main detection techniques (amperometric, pulsed amperometric and coulometric detection) and a voltammetric technique (cyclic voltammetry). The instrumentation was successfully evaluated using the following systems: cyclic voltammograms of metallic electrodes in alkaline solutions, flow electrochemical detection of glucose and glycine and direct determination of herbicide glyphosate (electrochemical detection coupled to HPLC).