967 resultados para multivariate morphometry


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Eutetranychus banksi (McGregor, 1914) is a phytophagous, polyphagous and cosmopolitan species recorded on 23 plant families in 24 countries in North, Central and South Americas, Europe, Asia, and Africa. Specimens of E. banksi present morphological variability among individuals of the same population and also among populations from different host species, being commonly referred to as a polytypic species, despite the fact that studies based on meristic comparisons of these populations are lacking. Also, there is no data available in the literature on the biological life tables of E. banksi on different hosts. Specimens collected in Brazil, Guadeloupe, Martinique, Mexico, and Paraguay were investigated in order to recognize morphological patterns among populations from different localities and hosts. A redescription of the species is provided based on data both from literature and new observations. Also, the biological cycle on three hosts, experiments of hosts exchange and the possibility of interbreeding in individuals originating from different populations were evaluated. Significant differences in the morphology of the females of different populations were detected when comparing the different hosts. The length of the dorsal pairs of setae v2, sc2, c1, c3, e1 and h1 differentiated the specimens of the populations collected from Citrus sp. from those of Hevea brasiliensis Muell. Arg. and Pachira aquatica Aubl.. Herein we observed significant variation among the life cycle of this species on the three hosts studied. When a substrate different from the one where the mites were collected was used for the biological cycle essay, significant variation was observed in several parameters such as average oviposition rate, events of arrenothoky, and sex ratio. Interbreeding with populations collected from Citrus sinensis and P. aquatica resulted in no descendants, although mating was observed.

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Background: Obsessive-compulsive disorder (OCD) is a clinically heterogenous disorder characterized by temporally stable symptom dimensions. Past inconsistent results from structural neuroimaging studies of OCD may have resulted from the effects of these specific symptom dimensions as well as other socio-demographic and clinical variables upon gray matter (GM) volume. Methods: GM volume was measured in 25 adult OCD patients and 20 adult healthy controls using voxel-based morphometry (VBM), controlling for age and total brain GM volume. Univariate and multivariate regression analyses were carried out between regions of GM difference and age, age of onset, medication load, OCD severity, depression severity, and separate symptom dimension scores. Results: Significant GM volumetric differences in OCD patients relative to controls were found in dorsal cortical regions, including bilateral BA6, BA46, BA9 and right BA8 (controls > patients), and bilateral midbrain (patients > controls). Stepwise regression analyses revealed highly significant relationships between greater total OCD symptom severity and smaller GM volumes in dorsal cortical regions and larger GM volumes in bilateral midbrain. Greater age was independently associated with smaller GM volumes in right BA6, left BA9, left BA46 and larger GM volumes in right midbrain. Greater washing symptom severity was independently associated with smaller GM volume in right BA6, while there was a trend association between greater hoarding symptom severity and lower GM volume in left BA6. Limitations: The sample was relatively small to examine the relationship between symptom scores and GM volumes. Multiple patients were taking medication and had comorbid disorders. Conclusions: These analyses suggest dorsal prefrontal cortical and bilateral midbrain GM abnormalities in OCD that appear to be primarily driven by the effects of total OCD symptom severity. The results regarding the relationship between GM volumes and symptom dimension scores require examination in larger samples. (C) 2008 Elsevier B.V. All rights reserved.

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The human brainstem is a densely packed, complex but highly organised structure. It not only serves as a conduit for long projecting axons conveying motor and sensory information, but also is the location of multiple primary nuclei that control or modulate a vast array of functions, including homeostasis, consciousness, locomotion, and reflexive and emotive behaviours. Despite its importance, both in understanding normal brain function as well as neurodegenerative processes, it remains a sparsely studied structure in the neuroimaging literature. In part, this is due to the difficulties in imaging the internal architecture of the brainstem in vivo in a reliable and repeatable fashion. A modified multivariate mixture of Gaussians (mmMoG) was applied to the problem of multichannel tissue segmentation. By using quantitative magnetisation transfer and proton density maps acquired at 3 T with 0.8 mm isotropic resolution, tissue probability maps for four distinct tissue classes within the human brainstem were created. These were compared against an ex vivo fixated human brain, imaged at 0.5 mm, with excellent anatomical correspondence. These probability maps were used within SPM8 to create accurate individual subject segmentations, which were then used for further quantitative analysis. As an example, brainstem asymmetries were assessed across 34 right-handed individuals using voxel based morphometry (VBM) and tensor based morphometry (TBM), demonstrating highly significant differences within localised regions that corresponded to motor and vocalisation networks. This method may have important implications for future research into MRI biomarkers of pre-clinical neurodegenerative diseases such as Parkinson's disease.

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This paper presents a GIS-based multicriteria flood risk assessment and mapping approach applied to coastal drainage basins where hydrological data are not available. It involves risk to different types of possible processes: coastal inundation (storm surge), river, estuarine and flash flood, either at urban or natural areas, and fords. Based on the causes of these processes, several environmental indicators were taken to build-up the risk assessment. Geoindicators include geological-geomorphologic proprieties of Quaternary sedimentary units, water table, drainage basin morphometry, coastal dynamics, beach morphodynamics and microclimatic characteristics. Bioindicators involve coastal plain and low slope native vegetation categories and two alteration states. Anthropogenic indicators encompass land use categories properties such as: type, occupation density, urban structure type and occupation consolidation degree. The selected indicators were stored within an expert Geoenvironmental Information System developed for the State of Sao Paulo Coastal Zone (SIIGAL), which attributes were mathematically classified through deterministic approaches, in order to estimate natural susceptibilities (Sn), human-induced susceptibilities (Sa), return period of rain events (Ri), potential damages (Dp) and the risk classification (R), according to the equation R=(Sn.Sa.Ri).Dp. Thematic maps were automatically processed within the SIIGAL, in which automata cells (""geoenvironmental management units"") aggregating geological-geomorphologic and land use/native vegetation categories were the units of classification. The method has been applied to the Northern Littoral of the State of Sao Paulo (Brazil) in 32 small drainage basins, demonstrating to be very useful for coastal zone public politics, civil defense programs and flood management.

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The morphometric study of the midgut in Diatraea saccharalis (Lepidoptera) larvae parasitized by the Cotesia flavipes (Hymenoptera) showed that there was significant increase in the columnar, goblet and regenerative cells and their nuclei; the midgut lumen diameter and the epithelial height were also increased in the parasitized larvae. The multivariate analysis showed that parasitism affected the columnar cell only in the posterior region, and the goblet cells along the midgut length (anterior and posterior regions). (c) 2006 Elsevier B.V. All rights reserved.

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

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Although a large amount of data have been published in past years on the taxonomic status of the Anastrepha fraterculus (Wiedemann) species complex, there is still a need to know how many species this complex comprises, the distribution of each one, and their distinguishing features. In this study, we assessed the morphometric variability of 32 populations from the A. fraterculus complex, located in major biogeographical areas from the Neotropics. Multivariate techniques for analysis were applied to the measurements of 21 variables referring to the mesonotum, aculeus, and wing. For the first time, our results identified the presence of seven distinct morphotypes within this species complex. According to the biogeographical areas, populations occurring in the Mesoamerican dominion (Mexico, Guatemala, and Panama) were clustered within a single natural entity labeled as the "Mexican" morphotype; whereas in the northwestern South American dominion, samples fell into three distinct groups: the "Venezuelan" morphotype with a single population from the Caribbean lowlands of Venezuela, the "Andean" morphotype from the highlands of Venezuela and Colombia, and the third group or "Peruvian" morphotype comprised the samples from the Pacific coastal lowlands of Ecuador and Peru. Three additional groups were identified from the Chacoan and Paranaense sub-regions: the morphotype "Brazilian-1" was recognized as including the Argentinean samples with most pertaining to Brazil, and widely distributed in these biogeographical areas; the morphotype "Brazilian-2" was recognized as including two samples from the state of Sao Paulo (Ilha-Bela and Sao Sebastiao); whereas the morphotype "Brazilian-3" included a single population from Botucatu (state of Sao Paulo). Based on data published by previous authors showing genetic and karyotypic differentiation, as well as reproductive isolation, we have concluded that such morphotypes indeed represent natural groups and distinct taxonomic entities.

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In acquired immunodeficiency syndrome (AIDS) studies it is quite common to observe viral load measurements collected irregularly over time. Moreover, these measurements can be subjected to some upper and/or lower detection limits depending on the quantification assays. A complication arises when these continuous repeated measures have a heavy-tailed behavior. For such data structures, we propose a robust structure for a censored linear model based on the multivariate Student's t-distribution. To compensate for the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is employed. An efficient expectation maximization type algorithm is developed for computing the maximum likelihood estimates, obtaining as a by-product the standard errors of the fixed effects and the log-likelihood function. The proposed algorithm uses closed-form expressions at the E-step that rely on formulas for the mean and variance of a truncated multivariate Student's t-distribution. The methodology is illustrated through an application to an Human Immunodeficiency Virus-AIDS (HIV-AIDS) study and several simulation studies.

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Conventional reflectance spectroscopy (NIRS) and hyperspectral imaging (HI) in the near-infrared region (1000-2500 nm) are evaluated and compared, using, as the case study, the determination of relevant properties related to the quality of natural rubber. Mooney viscosity (MV) and plasticity indices (PI) (PI0 - original plasticity, PI30 - plasticity after accelerated aging, and PRI - the plasticity retention index after accelerated aging) of rubber were determined using multivariate regression models. Two hundred and eighty six samples of rubber were measured using conventional and hyperspectral near-infrared imaging reflectance instruments in the range of 1000-2500 nm. The sample set was split into regression (n = 191) and external validation (n = 95) sub-sets. Three instruments were employed for data acquisition: a line scanning hyperspectral camera and two conventional FT-NIR spectrometers. Sample heterogeneity was evaluated using hyperspectral images obtained with a resolution of 150 × 150 μm and principal component analysis. The probed sample area (5 cm(2); 24,000 pixels) to achieve representativeness was found to be equivalent to the average of 6 spectra for a 1 cm diameter probing circular window of one FT-NIR instrument. The other spectrophotometer can probe the whole sample in only one measurement. The results show that the rubber properties can be determined with very similar accuracy and precision by Partial Least Square (PLS) regression models regardless of whether HI-NIR or conventional FT-NIR produce the spectral datasets. The best Root Mean Square Errors of Prediction (RMSEPs) of external validation for MV, PI0, PI30, and PRI were 4.3, 1.8, 3.4, and 5.3%, respectively. Though the quantitative results provided by the three instruments can be considered equivalent, the hyperspectral imaging instrument presents a number of advantages, being about 6 times faster than conventional bulk spectrometers, producing robust spectral data by ensuring sample representativeness, and minimizing the effect of the presence of contaminants.

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The aim of the present study was to evaluate the effect of soil characteristics (pH, macro- and micro-nutrients), environmental factors (temperature, humidity, period of the year and time of day of collection) and meteorological conditions (rain, sun, cloud and cloud/rain) on the flavonoid content of leaves of Passiflora incarnata L., Passifloraceae. The total flavonoid contents of leaf samples harvested from plants cultivated or collected under different conditions were quantified by high-performance liquid chromatography with ultraviolet detection (HPLC-UV/PAD). Chemometric treatment of the data by principal component (PCA) and hierarchic cluster analyses (HCA) showed that the samples did not present a specific classification in relation to the environmental and soil variables studied, and that the environmental variables were not significant in describing the data set. However, the levels of the elements Fe, B and Cu present in the soil showed an inverse correlation with the total flavonoid contents of the leaves of P. incarnata.

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The occipital dysplasia has been characterized by a dorsal enlargement of the foramen magnum which can vary in size and shape. Clinical signs may be present or not in animals with occipital dysplasia. The purpose of this study was to radiographically analyze the morphology and morphometry of the foramen magnum of thirty healthy dogs. This study chose to use fifteen Yorkshire terrier dogs and fifteen Toy Poodle dogs in order to characterize the radiographic aspects of the foramen magnum and contribute to the diagnosis and critical analysis of the occipital dysplasia importance. According to the foramen magnum morphology and tracings, it was possible to classify the radiographic aspects into different shapes varing from oval and quadrangular. Out of 26 (86.7%) animals had a dorsal enlargement and 4 (13.3%) showed normal foramen magnum. Animals without any clinical signs that are radiographically classified as dysplastic dogs may simply represent an anatomic variation of the foramen magnum.

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Twenty-nine canine cutaneous mast cell tumors (MCTs) were morphometrically analyzed with regard to mean nuclear area (MNA) using cytopathology smears. The results showed a correlation between MNA and survival. When graded into 2 morphometrically different groups, there were statistically significant differences among high- and low-grade MCTs, regarding both Romanowsky-type stain and hematoxylin and eosin. Cytomorphometry could also separate histologic grade II tumors with better prognosis from the more aggressive MCTs. The results indicated that nuclear morphometry on cytopathology preparations can predict the biological behavior of cutaneous MCTs in dogs in an independent manner, yielding a rapid and reproducible diagnosis, which renders the method useful for veterinary oncology.

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The application of laser induced breakdown spectrometry (LIBS) aiming the direct analysis of plant materials is a great challenge that still needs efforts for its development and validation. In this way, a series of experimental approaches has been carried out in order to show that LIBS can be used as an alternative method to wet acid digestions based methods for analysis of agricultural and environmental samples. The large amount of information provided by LIBS spectra for these complex samples increases the difficulties for selecting the most appropriated wavelengths for each analyte. Some applications have suggested that improvements in both accuracy and precision can be achieved by the application of multivariate calibration in LIBS data when compared to the univariate regression developed with line emission intensities. In the present work, the performance of univariate and multivariate calibration, based on partial least squares regression (PLSR), was compared for analysis of pellets of plant materials made from an appropriate mixture of cryogenically ground samples with cellulose as the binding agent. The development of a specific PLSR model for each analyte and the selection of spectral regions containing only lines of the analyte of interest were the best conditions for the analysis. In this particular application, these models showed a similar performance. but PLSR seemed to be more robust due to a lower occurrence of outliers in comparison to the univariate method. Data suggests that efforts dealing with sample presentation and fitness of standards for LIBS analysis must be done in order to fulfill the boundary conditions for matrix independent development and validation. (C) 2009 Elsevier B.V. All rights reserved.

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The Random Parameter model was proposed to explain the structure of the covariance matrix in problems where most, but not all, of the eigenvalues of the covariance matrix can be explained by Random Matrix Theory. In this article, we explore the scaling properties of the model, as observed in the multifractal structure of the simulated time series. We use the Wavelet Transform Modulus Maxima technique to obtain the multifractal spectrum dependence with the parameters of the model. The model shows a scaling structure compatible with the stylized facts for a reasonable choice of the parameter values. (C) 2009 Elsevier B.V. All rights reserved.