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1.
Biomed Eng Online ; 20(1): 72, 2021 Jul 29.
Artigo em Inglês | MEDLINE | ID: mdl-34325693

RESUMO

BACKGROUND: The visualization and analysis of brain data such as white matter diffusion tractography and magnetic resonance imaging (MRI) volumes is commonly used by neuro-specialist and researchers to help the understanding of brain structure, functionality and connectivity. As mobile devices are widely used among users and their technology shows a continuous improvement in performance, different types of applications have been designed to help users in different work areas. RESULTS: We present, ABrainVis, an Android mobile tool that allows users to visualize different types of brain images, such as white matter diffusion tractographies, represented as fibers in 3D, segmented fiber bundles, MRI 3D images as rendered volumes and slices, and meshes. The tool enables users to choose and combine different types of brain imaging data to provide visual anatomical context for specific visualization needs. ABrainVis provides high performance over a wide range of Android devices, including tablets and cell phones using medium and large tractography datasets. Interesting visualizations including brain tumors and arteries, along with fiber, are given as examples of case studies using ABrainVis. CONCLUSIONS: The functionality, flexibility and performance of ABrainVis tool introduce an improvement in user experience enabling neurophysicians and neuroscientists fast visualization of large tractography datasets, as well as the ability to incorporate other brain imaging data such as MRI volumes and meshes, adding anatomical contextual information.


Assuntos
Imagem de Tensor de Difusão , Substância Branca , Encéfalo/diagnóstico por imagem , Processamento de Imagem Assistida por Computador , Imageamento Tridimensional , Imageamento por Ressonância Magnética , Substância Branca/diagnóstico por imagem
2.
Front Neurosci ; 18: 1333243, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38529266

RESUMO

We present a Python library (Phybers) for analyzing brain tractography data. Tractography datasets contain streamlines (also called fibers) composed of 3D points representing the main white matter pathways. Several algorithms have been proposed to analyze this data, including clustering, segmentation, and visualization methods. The manipulation of tractography data is not straightforward due to the geometrical complexity of the streamlines, the file format, and the size of the datasets, which may contain millions of fibers. Hence, we collected and structured state-of-the-art methods for the analysis of tractography and packed them into a Python library, to integrate and share tools for tractography analysis. Due to the high computational requirements, the most demanding modules were implemented in C/C++. Available functions include brain Bundle Segmentation (FiberSeg), Hierarchical Fiber Clustering (HClust), Fast Fiber Clustering (FFClust), normalization to a reference coordinate system, fiber sampling, calculation of intersection between sets of brain fibers, tools for cluster filtering, calculation of measures from clusters, and fiber visualization. The library tools were structured into four principal modules: Segmentation, Clustering, Utils, and Visualization (Fibervis). Phybers is freely available on a GitHub repository under the GNU public license for non-commercial use and open-source development, which provides sample data and extensive documentation. In addition, the library can be easily installed on both Windows and Ubuntu operating systems through the pip library.

3.
Am J Clin Pathol ; 154(1): 70-77, 2020 06 08.
Artigo em Inglês | MEDLINE | ID: mdl-32270177

RESUMO

OBJECTIVES: Since hematologic values vary with age in children, we evaluated the agreement between the "traditional" reticulocyte production index (RPI) and an RPI by age (RPI/A)-adjusted normal values. METHODS: A retrospective, observational, and analytical study was performed on CBCs of children with anemia younger than 18 years. The agreement and clinical repercussions of the RPI values were analyzed with an RPI/A developed with theoretical values for different ages. RESULTS: A total of 5,503 tests were analyzed and no systematic error between the two indices was found; however, there were significant proportional differences at higher values that resulted in lower RPI/A in children younger than 15 days and higher RPI/A in children aged 15 days and older. No agreement was observed at any age. The proportion of arregenerative anemia diagnosed using RPI/A was higher in children younger than 15 days and lower in those 15 days and older. CONCLUSIONS: RPI is not an adequate tool for evaluating the erythropoietic capacity of bone marrow in the pediatric population. The disagreement between the results can be explained by the difference in normal hematologic values between children and adults.


Assuntos
Contagem de Reticulócitos/normas , Reticulócitos , Adolescente , Criança , Pré-Escolar , Feminino , Humanos , Lactente , Recém-Nascido , Masculino , Valores de Referência , Estudos Retrospectivos
4.
Ecol Evol ; 7(14): 5343-5351, 2017 07.
Artigo em Inglês | MEDLINE | ID: mdl-28770072

RESUMO

The common vampire bat, Desmodus rotundus, ranges from South America into northern Mexico in North America. This sanguivorous species of bat feeds primarily on medium to large-sized mammals and is known to rely on livestock as primary prey. Each year, there are hotspot areas of D. rotundus-specific rabies virus outbreaks that lead to the deaths of livestock and economic losses. Based on incidental captures in our study area, which is an area of high cattle mortality from D. rotundus transmitted rabies, it appears that D. rotundus are being caught regularly in areas and elevations where they previously were thought to be uncommon. Our goal was to investigate demographic processes and genetic diversity at the north eastern edge of the range of D. rotundus in Mexico. We generated control region sequences (441 bp) and 12-locus microsatellite genotypes for 602 individuals of D. rotundus. These data were analyzed using network analyses, Bayesian clustering approaches, and standard population genetic statistical analyses. Our results demonstrate panmixia across our sampling area with low genetic diversity, low population differentiation, loss of intermediate frequency alleles at microsatellite loci, and very low mtDNA haplotype diversity with all haplotypes being very closely related. Our study also revealed strong signals of population expansion. These results follow predictions from the leading-edge model of expanding populations and supports conclusions from another study that climate change may allow this species to find suitable habitat within the U.S. border.

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