Ssr-based Genetic Diversity And Structure Of Garlic Accessions From Brazil.

Garlic is a spice and a medicinal plant; hence, there is an increasing interest in 'developing' new varieties with different culinary properties or with high content of nutraceutical compounds. Phenotypic traits and dominant molecular markers are predominantly used to evaluate the genetic diversity of garlic clones. However, 24 SSR markers (codominant) specific for garlic are available in the literature, fostering germplasm researches. In this study, we genotyped 130 garlic accessions from Brazil and abroad using 17 polymorphic SSR markers to assess the genetic diversity and structure. This is the first attempt to evaluate a large set of accessions maintained by Brazilian institutions. A high level of redundancy was detected in the collection (50 % of the accessions represented eight haplotypes). However, non-redundant accessions presented high genetic diversity. We detected on average five alleles per locus, Shannon index of 1.2, HO of 0.5, and HE of 0.6. A core collection was set with 17 accessions, covering 100 % of the alleles with minimum redundancy. Overall FST and D values indicate a strong genetic structure within accessions. Two major groups identified by both model-based (Bayesian approach) and hierarchical clustering (UPGMA dendrogram) techniques were coherent with the classification of accessions according to maturity time (growth cycle): early-late and midseason accessions. Assessing genetic diversity and structure of garlic collections is the first step towards an efficient management and conservation of accessions in genebanks, as well as to advance future genetic studies and improvement of garlic worldwide.

Ten Years Of Proteomics In Multiple Sclerosis.

Multiple sclerosis, which is the most common cause of chronic neurological disability in young adults, is an inflammatory, demyelinating, and neurodegenerative disease of the CNS, which leads to the formation of multiple foci of demyelinated lesions in the white matter. The diagnosis is based currently on magnetic resonance image and evidence of dissemination in time and space. However, this could be facilitated if biomarkers were available to rule out other disorders with similar symptoms as well as to avoid cerebrospinal fluid analysis, which requires an invasive collection. Additionally, the molecular mechanisms of the disease are not completely elucidated, especially those related to the neurodegenerative aspects of the disease. The identification of biomarker candidates and molecular mechanisms of multiple sclerosis may be approached by proteomics. In the last 10 years, proteomic techniques have been applied in different biological samples (CNS tissue, cerebrospinal fluid, and blood) from multiple sclerosis patients and in its experimental model. In this review, we summarize these data, presenting their value to the current knowledge of the disease mechanisms, as well as their importance in identifying biomarkers or treatment targets.

Microfluidic Paper-based Devices For Bioanalytical Applications.

Paper has become increasingly recognized as a very interesting substrate for the construction of microfluidic devices, with potential application in a variety of areas, including health diagnosis, environmental monitoring, immunoassays and food safety. The aim of this review is to present a short history of analytical systems constructed from paper, summarize the main advantages and disadvantages of fabrication techniques, exploit alternative methods of detection such as colorimetric, electrochemical, photoelectrochemical, chemiluminescence and electrochemiluminescence, as well as to take a closer look at the novel achievements in the field of bioanalysis published during the last 2 years. Finally, the future trends for production of such devices are discussed.

Authenticity study of Phyllanthus species by NMR and FT-IR Techniques coupled with chemometric methods

The importance of medicinal plants and their use in industrial applications is increasing worldwide, especially in Brazil. Phyllanthus species, popularly known as quebra-pedras in Brazil, are used in folk medicine for treating urinary infections and renal calculus. This paper reports an authenticity study, based on herbal drugs from Phyllanthus species, involving commercial and authentic samples using spectroscopic techniques: FT-IR, ¹H HR-MAS NMR and ¹H NMR in solution, combined with chemometric analysis. The spectroscopic techniques evaluated, coupled with chemometric methods, have great potential in the investigation of complex matrices. Furthermore, several metabolites were identified by the NMR techniques.

Study of mural paintings by Fulvio Pennacchi in São Paulo City by mineralogical techniques

The present research deals with two mural paintings made in 1947 with the fresco technique by Fulvio Pennacchi in the Catholic Chapel of the Hospital das Clínicas (São Paulo City, Brazil), namely the Virgin Annunciation and the Supper at Emmaus. This study regards the materials and painting techniques used by the artist, based on historical research,on in situ observations and laboratory analytical techniques (stereomicroscopy,scanning electron microscopy with an energy dispersive spectrometer, X-ray diffractometry, electron microprobe, images obtained with UV-light), aiming to improve the methods of characterization of objects of our cultural heritage, and to enhance its preservation accordingly. The results lead to the identification of the plaster components and of distinct layers in the frescoes, besides further information on grain size, impurities and textures, composition of pigments, and features of deterioration, such as efflorescences. The degree of degradation of the murals painting was assessed by this way. Our data suggest that a single layer of plaster was used by Pennacchi, as a common mortar with fine- and medium-grained aggregates. Differences in texture were obtained by adding gypsum to the plaster.

Computational adjustment technique for digital mammographic images based on the digitizer characteristic curve

We evaluated the performance of a novel procedure for segmenting mammograms and detecting clustered microcalcifications in two types of image sets obtained from digitization of mammograms using either a laser scanner, or a conventional ""optical"" scanner. Specific regions forming the digital mammograms were identified and selected, in which clustered microcalcifications appeared or not. A remarkable increase in image intensity was noticed in the images from the optical scanner compared with the original mammograms. A procedure based on a polynomial correction was developed to compensate the changes in the characteristic curves from the scanners, relative to the curves from the films. The processing scheme was applied to both sets, before and after the polynomial correction. The results indicated clearly the influence of the mammogram digitization on the performance of processing schemes intended to detect microcalcifications. The image processing techniques applied to mammograms digitized by both scanners, without the polynomial intensity correction, resulted in a better sensibility in detecting microcalcifications in the images from the laser scanner. However, when the polynomial correction was applied to the images from the optical scanner, no differences in performance were observed for both types of images. (C) 2008 SPIE and IS&T [DOI: 10.1117/1.3013544]

FILTERING TECHNIQUES APPLIED ON RAW CARRIER PHASE FOR GPS DETECTING SMALL DYNAMIC DISPLACEMENTS

This work is part of a research under construction since 2000, in which the main objective is to measure small dynamic displacements by using L1 GPS receivers. A very sensible way to detect millimetric periodic displacements is based on the Phase Residual Method (PRM). This method is based on the frequency domain analysis of the phase residuals resulted from the L1 double difference static data processing of two satellites in almost orthogonal elevation angle. In this article, it is proposed to obtain the phase residuals directly from the raw phase observable collected in a short baseline during a limited time span, in lieu of obtaining the residual data file from regular GPS processing programs which not always allow the choice of the aimed satellites. In order to improve the ability to detect millimetric oscillations, two filtering techniques are introduced. One is auto-correlation which reduces the phase noise with random time behavior. The other is the running mean to separate low frequency from the high frequency phase sources. Two trials have been carried out to verify the proposed method and filtering techniques. One simulates a 2.5 millimeter vertical antenna displacement and the second uses the GPS data collected during a bridge load test. The results have shown a good consistency to detect millimetric oscillations.

A reliable measure of similarity based on dependency for short time series: an application to gene expression networks

Background: Microarray techniques have become an important tool to the investigation of genetic relationships and the assignment of different phenotypes. Since microarrays are still very expensive, most of the experiments are performed with small samples. This paper introduces a method to quantify dependency between data series composed of few sample points. The method is used to construct gene co-expression subnetworks of highly significant edges. Results: The results shown here are for an adapted subset of a Saccharomyces cerevisiae gene expression data set with low temporal resolution and poor statistics. The method reveals common transcription factors with a high confidence level and allows the construction of subnetworks with high biological relevance that reveals characteristic features of the processes driving the organism adaptations to specific environmental conditions. Conclusion: Our method allows a reliable and sophisticated analysis of microarray data even under severe constraints. The utilization of systems biology improves the biologists ability to elucidate the mechanisms underlying celular processes and to formulate new hypotheses.

A score system for quality evaluation of RNA sequence tags: an improvement for gene expression profiling

Background: High-throughput molecular approaches for gene expression profiling, such as Serial Analysis of Gene Expression (SAGE), Massively Parallel Signature Sequencing (MPSS) or Sequencing-by-Synthesis (SBS) represent powerful techniques that provide global transcription profiles of different cell types through sequencing of short fragments of transcripts, denominated sequence tags. These techniques have improved our understanding about the relationships between these expression profiles and cellular phenotypes. Despite this, more reliable datasets are still necessary. In this work, we present a web-based tool named S3T: Score System for Sequence Tags, to index sequenced tags in accordance with their reliability. This is made through a series of evaluations based on a defined rule set. S3T allows the identification/selection of tags, considered more reliable for further gene expression analysis. Results: This methodology was applied to a public SAGE dataset. In order to compare data before and after filtering, a hierarchical clustering analysis was performed in samples from the same type of tissue, in distinct biological conditions, using these two datasets. Our results provide evidences suggesting that it is possible to find more congruous clusters after using S3T scoring system. Conclusion: These results substantiate the proposed application to generate more reliable data. This is a significant contribution for determination of global gene expression profiles. The library analysis with S3T is freely available at http://gdm.fmrp.usp.br/s3t/.S3T source code and datasets can also be downloaded from the aforementioned website.

The pulsations of the B5IVe star HD 181231 observed with CoRoT and ground-based spectroscopy

Context. HD 181231 is a B5IVe star, which has been observed with the CoRoT satellite during similar to 5 consecutive months and simultaneously from the ground in spectroscopy and spectropolarimetry. Aims. By analysing these data, we aim to detect and characterize as many pulsation frequencies as possible, to search for the presence of beating effects possibly at the origin of the Be phenomenon. Our results will also provide a basis for seismic modelling. Methods. The fundamental parameters of the star are determined from spectral fitting and from the study of the circumstellar emission. The CoRoT photometric data and ground-based spectroscopy are analysed using several Fourier techniques: CLEAN-NG, PASPER, and TISAFT, as well as a time-frequency technique. A search for a magnetic field is performed by applying the LSD technique to the spectropolarimetric data. Results. We find that HD 181231 is a B5IVe star seen with an inclination of similar to 45 degrees. No magnetic field is detected in its photosphere. We detect at least 10 independent significant frequencies of variations among the 54 detected frequencies, interpreted in terms of non-radial pulsation modes and rotation. Two longer-term variations are also detected: one at similar to 14 days resulting from a beating effect between the two main frequencies of short-term variations, the other at similar to 116 days due either to a beating of frequencies or to a zonal pulsation mode. Conclusions. Our analysis of the CoRoT light curve and ground-based spectroscopic data of HD 181231 has led to the determination of the fundamental and pulsational parameters of the star, including beating effects. This will allow a precise seismic modelling of this star.

Comparative analysis of two sampling techniques for pollen gathered by Nannotrigona testaceicornis Lepeletier (Apidae, Meliponini)

Pollen counts from samples taken from storage pots throughout one year (from October to September) were adjusted by Tasei's volumetric correction coefficient for the determination of pollen sources exploited by two colonies of Nannotrigona testaceicornis in Sao Paulo, Brazil. The results obtained by this sampling technique for seven months (December to June) were compared with those from corbicula load samples taken within the same period. This species visited a large variety of plant species, but few of them were frequently used. As a rule, pollen sources that appeared at frequencies greater than 1% were found with both sampling methods and significant positive correlations (Spearman correlation coefficient) were found between their values. The pollen load sample data showed that N. testaceicornis gathered pollen throughout the external activity period.

Designing real nanotube-based gas sensors

Using a combination of density functional theory and recursive Green's functions techniques, we present a full description of a large scale sensor, accounting for disorder and different coverages. Here, we use this method to demonstrate the functionality of nitrogen-rich carbon nanotubes as ammonia sensors as an example. We show how the molecules one wishes to detect bind to the most relevant defects on the nanotube, describe how these interactions lead to changes in the electronic transport properties of each isolated defect, and demonstrate that there are significative resistance changes even in the presence of disorder, elucidating how a realistic nanosensor works.

DISTRIBUTION OF CAPYBARAS IN AN AGROECOSYSTEM, SOUTHEASTERN BRAZIL, BASED ON ECOLOGICAL NICHE MODELING

Southeastern Brazil has seen dramatic landscape modifications in recent decades, due to expansion of agriculture and urban areas; these changes have influenced the distribution and abundance of vertebrates. We developed predictive models of ecological and spatial distributions of capybaras (Hydrochoerus hydrochaeris) using ecological niche modeling. Most Occurrences of capybaras were in flat areas with water bodies Surrounded by sugarcane and pasture. More than 75% of the Piracicaba River basin was estimated as potentially habitable by capybara. The models had low omission error (2.3-3.4%), but higher commission error (91.0-98.5%); these ""model failures"" seem to be more related to local habitat characteristics than to spatial ones. The potential distribution of capybaras in the basin is associated with anthropogenic habitats, particularly with intensive land use for agriculture.

An alternative to the Pythagorean rule? Reevaluating Problem 1 of cuneiform tablet BM 34 568

The first problem of the Seleucid mathematical cuneiform tablet BM 34 568 calculates the diagonal of a rectangle from its sides without resorting to the Pythagorean rule. For this reason, it has been a source of discussion among specialists ever since its first publication. but so far no consensus in relation to its mathematical meaning has been attained. This paper presents two new interpretations of the scribe`s procedure. based on the assumption that he was able to reduce the problem to a standard Mesopotamian question about reciprocal numbers. These new interpretations are then linked to interpretations of the Old Babylonian tablet Plimpton 322 and to the presence of Pythagorean triples in the contexts of Old Babylonian and Hellenistic mathematics. (C) 2007 Elsevier Inc. All rights reserved.

Using Bayesian networks with rule extraction to infer the risk of weed infestation in a corn-crop

This paper describes the modeling of a weed infestation risk inference system that implements a collaborative inference scheme based on rules extracted from two Bayesian network classifiers. The first Bayesian classifier infers a categorical variable value for the weed-crop competitiveness using as input categorical variables for the total density of weeds and corresponding proportions of narrow and broad-leaved weeds. The inferred categorical variable values for the weed-crop competitiveness along with three other categorical variables extracted from estimated maps for the weed seed production and weed coverage are then used as input for a second Bayesian network classifier to infer categorical variables values for the risk of infestation. Weed biomass and yield loss data samples are used to learn the probability relationship among the nodes of the first and second Bayesian classifiers in a supervised fashion, respectively. For comparison purposes, two types of Bayesian network structures are considered, namely an expert-based Bayesian classifier and a naive Bayes classifier. The inference system focused on the knowledge interpretation by translating a Bayesian classifier into a set of classification rules. The results obtained for the risk inference in a corn-crop field are presented and discussed. (C) 2009 Elsevier Ltd. All rights reserved.