122 resultados para Cranial Anatomy
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The ability to function in a nocturnal and ground-dwelling niche requires a unique set of sensory specializations. The New Zealand kiwi has shifted away from vision, instead relying on auditory and tactile stimuli to function in its environment and locate prey. Behavioral evidence suggests that kiwi also rely on their sense of smell, using olfactory cues in foraging and possibly also in communication and social interactions. Anatomical studies appear to support these observations: the olfactory bulbs and tubercles have been suggested to be large in the kiwi relative to other birds, although the extent of this enlargement is poorly understood. In this study, we examine the size of the olfactory bulbs in kiwi and compare them with 55 other bird species, including emus, ostriches, rheas, tinamous, and 2 extinct species of moa (Dinornithiformes). We also examine the cytoarchitecture of the olfactory bulbs and olfactory epithelium to determine if any neural specializations beyond size are present that would increase olfactory acuity. Kiwi were a clear outlier in our analysis, with olfactory bulbs that are proportionately larger than those of any other bird in this study. Emus, close relatives of the kiwi, also had a relative enlargement of the olfactory bulbs, possibly supporting a phylogenetic link to well-developed olfaction. The olfactory bulbs in kiwi are almost in direct contact with the olfactory epithelium, which is indeed well developed and complex, with olfactory receptor cells occupying a large percentage of the epithelium. The anatomy of the kiwi olfactory system supports an enhancement for olfactory sensitivities, which is undoubtedly associated with their unique nocturnal niche.
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Background Definitive cisplatin-based is increasingly delivered as the treatment of choice for patients with head and neck cancer. Sensorineural hearing loss is a significant long term side effect of cisplatin-based chemoradiation and is associated with potential major quality of life issues for patients. Purpose The purpose of this manuscript was to review the mechanism behind sensorineural hearing loss in patients treated with cisplatin-based chemoradiation, including incidence, the contributions of radiotherapy and cisplatin to sensorineural hearing loss and the impact of the toxicity on patient quality of life. Methods Database searches were conducted through PubMed (National Centre for Biotechnology Information) and OvidSP Medline via the Queensland University of Technology Library website. General article searches were conducted through the online search engine Google Scholar. Articles were excluded if the full-text was unavailable, they were not in English or if they were published prior to 1990. Keywords included hearing loss, ototoxicity, cancer, quality of life, cisplatin and radiotherapy. Results/Discussion The total number of journal articles accessed was 290. Due to exclusion criteria, 129 articles were deemed appropriated for review. Findings indicated that sensorineural hearing loss is a significant, long term complication for patients treated with cisplatin-based chemoradiation. Current literature recognises the ototoxic effects of cisplatin and cranial irradiation as separate entities, however the impact of combined modality therapy on sensorineural hearing loss is seldom reported. Multiple risk factors for hearing loss are described, however there are contradictory opinions on incidence and severity and the exact radiation dose threshold responsible for inducing hearing loss in patients receiving combined modality therapy. Sensorineural hearing loss creates a subset of complexities for patients with head and neck cancer and that these patients face significant quality of life impairment. Conclusion The literature review identified that sensorineural hearing loss is a major quality of life issue for patients treated with cisplatin-based chemoradiation for head and neck cancer. Further investigation evaluating the contribution of cisplatin-based chemoradiation to sensorineural hearing loss and the subsequent effect on patient quality of life is warranted.
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The development of whole-body imaging at single-cell resolution enables system-level approaches to studying cellular circuits in organisms. Previous clearing methods focused on homogenizing mismatched refractive indices of individual tissues, enabling reductions in opacity but falling short of achieving transparency. Here, we show that an aminoalcohol decolorizes blood by efficiently eluting the heme chromophore from hemoglobin. Direct transcardial perfusion of an aminoalcohol-containing cocktail that we previously termed CUBIC coupled with a 10 day to 2 week clearing protocol decolorized and rendered nearly transparent almost all organs of adult mice as well as the entire body of infant and adult mice. This CUBIC-perfusion protocol enables rapid whole-body and whole-organ imaging at single-cell resolution by using light-sheet fluorescent microscopy. The CUBIC protocol is also applicable to 3D pathology, anatomy, and immunohistochemistry of various organs. These results suggest that whole-body imaging of colorless tissues at high resolution will contribute to organism-level systems biology.
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Given the ever increasing importance of legislation to the resolution of legal disputes, there is a concomitant need for law students to be well trained in the anatomy, identification, interpretation and application of laws made by or under parliament. This article discusses a blended learning project called Indigo’s Folly, implemented at the Queensland University of Technology Law School in 2014. Indigo’s Folly was created to increase law student competency with respect to statutory interpretation. Just as importantly, it was designed to make the teaching of statutory interpretation more interesting – to “bring the sexy” to the student statutory interpretation experience. Quantitative and qualitative empirical data will be presented as evidence to show that statutory interpretation can be taught in a way that law students find engaging.
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This thesis provides new knowledge on an understudied group of grasses, some of which are resurrection grasses (i.e. able to withstand extreme drought). The sole Australian species (Tripogon loliiformis) is morphologically diverse and could be more than one species. This study sought to determine how many species of Tripogon occur in Australia, their relationships to other species in the genus and to two other genera of resurrection grasses (Eragrostiella and Oropetium). Results of the research indicate there is not enough evidence, from DNA sequence data, to warrant splitting up T. loliiformis into multiple species. The extensive morphological diversity seems to be influenced by environmental conditions. The three genera are so closely related that they could be grouped into a single genus. This new knowledge opens up pathways for future investigations, including studying genes responsible for desiccation tolerance and the conservation of native grasses that occur in rocky habitats.
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Myceugenia rufa is a rare and endemic species from the coast of central Chile. There are no published studies describing flower, fruit or seed anatomy. Forty-two accessions were collected from across the geographic range of the species. Reproductive structures were fixed, dehydrated, embedded in paraffin, sectioned and stained with Safranin O and Fast green. Anatomy of floral buds, mature flowers, fruits and seeds was described. Reproductive anatomy matches that of other Myrtaceae, such as presence of druses, internal phloem and schizogenous secretory cavities in buds, flowers, fruits and seeds. The anatomy and development of reproductive structures of M. rufa might enhance the understanding for future studies regarding natural reproduction and conservation programs.
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We defined a new statistical fluid registration method with Lagrangian mechanics. Although several authors have suggested that empirical statistics on brain variation should be incorporated into the registration problem, few algorithms have included this information and instead use regularizers that guarantee diffeomorphic mappings. Here we combine the advantages of a large-deformation fluid matching approach with empirical statistics on population variability in anatomy. We reformulated the Riemannian fluid algorithmdeveloped in [4], and used a Lagrangian framework to incorporate 0 th and 1st order statistics in the regularization process. 92 2D midline corpus callosum traces from a twin MRI database were fluidly registered using the non-statistical version of the algorithm (algorithm 0), giving initial vector fields and deformation tensors. Covariance matrices were computed for both distributions and incorporated either separately (algorithm 1 and algorithm 2) or together (algorithm 3) in the registration. We computed heritability maps and two vector and tensorbased distances to compare the power and the robustness of the algorithms.
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Genetic and environmental factors influence brain structure and function profoundly. The search for heritable anatomical features and their influencing genes would be accelerated with detailed 3D maps showing the degree to which brain morphometry is genetically determined. As part of an MRI study that will scan 1150 twins, we applied Tensor-Based Morphometry to compute morphometric differences in 23 pairs of identical twins and 23 pairs of same-sex fraternal twins (mean age: 23.8 ± 1.8 SD years). All 92 twins' 3D brain MRI scans were nonlinearly registered to a common space using a Riemannian fluid-based warping approach to compute volumetric differences across subjects. A multi-template method was used to improve volume quantification. Vector fields driving each subject's anatomy onto the common template were analyzed to create maps of local volumetric excesses and deficits relative to the standard template. Using a new structural equation modeling method, we computed the voxelwise proportion of variance in volumes attributable to additive (A) or dominant (D) genetic factors versus shared environmental (C) or unique environmental factors (E). The method was also applied to various anatomical regions of interest (ROIs). As hypothesized, the overall volumes of the brain, basal ganglia, thalamus, and each lobe were under strong genetic control; local white matter volumes were mostly controlled by common environment. After adjusting for individual differences in overall brain scale, genetic influences were still relatively high in the corpus callosum and in early-maturing brain regions such as the occipital lobes, while environmental influences were greater in frontal brain regions that have a more protracted maturational time-course.
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Imaging genetics aims to discover how variants in the human genome influence brain measures derived from images. Genome-wide association scans (GWAS) can screen the genome for common differences in our DNA that relate to brain measures. In small samples, GWAS has low power as individual gene effects are weak and one must also correct for multiple comparisons across the genome and the image. Here we extend recent work on genetic clustering of images, to analyze surface-based models of anatomy using GWAS. We performed spherical harmonic analysis of hippocampal surfaces, automatically extracted from brain MRI scans of 1254 subjects. We clustered hippocampal surface regions with common genetic influences by examining genetic correlations (r(g)) between the normalized deformation values at all pairs of surface points. Using genetic correlations to cluster surface measures, we were able to boost effect sizes for genetic associations, compared to clustering with traditional phenotypic correlations using Pearson's r.
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Cortical connectivity is associated with cognitive and behavioral traits that are thought to vary between sexes. Using high-angular resolution diffusion imaging at 4 Tesla, we scanned 234 young adult twins and siblings (mean age: 23.4 2.0 SD years) with 94 diffusion-encoding directions. We applied a novel Hough transform method to extract fiber tracts throughout the entire brain, based on fields of constant solid angle orientation distribution functions (ODFs). Cortical surfaces were generated from each subject's 3D T1-weighted structural MRI scan, and tracts were aligned to the anatomy. Network analysis revealed the proportions of fibers interconnecting 5 key subregions of the frontal cortex, including connections between hemispheres. We found significant sex differences (147 women/87 men) in the proportions of fibers connecting contralateral superior frontal cortices. Interhemispheric connectivity was greater in women, in line with long-standing theories of hemispheric specialization. These findings may be relevant for ongoing studies of the human connectome.
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To understand factors that affect brain connectivity and integrity, it is beneficial to automatically cluster white matter (WM) fibers into anatomically recognizable tracts. Whole brain tractography, based on diffusion-weighted MRI, generates vast sets of fibers throughout the brain; clustering them into consistent and recognizable bundles can be difficult as there are wide individual variations in the trajectory and shape of WM pathways. Here we introduce a novel automated tract clustering algorithm based on label fusion - a concept from traditional intensity-based segmentation. Streamline tractography generates many incorrect fibers, so our top-down approach extracts tracts consistent with known anatomy, by mapping multiple hand-labeled atlases into a new dataset. We fuse clustering results from different atlases, using a mean distance fusion scheme. We reliably extracted the major tracts from 105-gradient high angular resolution diffusion images (HARDI) of 198 young normal twins. To compute population statistics, we use a pointwise correspondence method to match, compare, and average WM tracts across subjects. We illustrate our method in a genetic study of white matter tract heritability in twins.
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Automatic labeling of white matter fibres in diffusion-weighted brain MRI is vital for comparing brain integrity and connectivity across populations, but is challenging. Whole brain tractography generates a vast set of fibres throughout the brain, but it is hard to cluster them into anatomically meaningful tracts, due to wide individual variations in the trajectory and shape of white matter pathways. We propose a novel automatic tract labeling algorithm that fuses information from tractography and multiple hand-labeled fibre tract atlases. As streamline tractography can generate a large number of false positive fibres, we developed a top-down approach to extract tracts consistent with known anatomy, based on a distance metric to multiple hand-labeled atlases. Clustering results from different atlases were fused, using a multi-stage fusion scheme. Our "label fusion" method reliably extracted the major tracts from 105-gradient HARDI scans of 100 young normal adults. © 2012 Springer-Verlag.
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Imaging genetics is a new field of neuroscience that blends methods from computational anatomy and quantitative genetics to identify genetic influences on brain structure and function. Here we analyzed brain MRI data from 372 young adult twins to identify cortical regions in which gray matter volume is influenced by genetic differences across subjects. Thickness maps, reconstructed from surface models of the cortical gray/white and gray/CSF interfaces, were smoothed with a 25 mm FWHM kernel and automatically parcellated into 34 regions of interest per hemisphere. In structural equation models fitted to volume values at each surface vertex, we computed components of variance due to additive genetic (A), shared (C) and unique (E) environmental factors, and tested their significance. Cortical regions in the vicinity of the perisylvian language cortex, and at the frontal and temporal poles, showed significant additive genetic variance, suggesting that volume measures from these regions may provide quantitative phenotypes to narrow the search for quantitative trait loci that influence brain structure.
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We present a new algorithm to compute the voxel-wise genetic contribution to brain fiber microstructure using diffusion tensor imaging (DTI) in a dataset of 25 monozygotic (MZ) twins and 25 dizygotic (DZ) twin pairs (100 subjects total). First, the structural and DT scans were linearly co-registered. Structural MR scans were nonlinearly mapped via a 3D fluid transformation to a geometrically centered mean template, and the deformation fields were applied to the DTI volumes. After tensor re-orientation to realign them to the anatomy, we computed several scalar and multivariate DT-derived measures including the geodesic anisotropy (GA), the tensor eigenvalues and the full diffusion tensors. A covariance-weighted distance was measured between twins in the Log-Euclidean framework [2], and used as input to a maximum-likelihood based algorithm to compute the contributions from genetics (A), common environmental factors (C) and unique environmental ones (E) to fiber architecture. Quanititative genetic studies can take advantage of the full information in the diffusion tensor, using covariance weighted distances and statistics on the tensor manifold.
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3D registration of brain MRI data is vital for many medical imaging applications. However, purely intensitybased approaches for inter-subject matching of brain structure are generally inaccurate in cortical regions, due to the highly complex network of sulci and gyri, which vary widely across subjects. Here we combine a surfacebased cortical registration with a 3D fluid one for the first time, enabling precise matching of cortical folds, but allowing large deformations in the enclosed brain volume, which guarantee diffeomorphisms. This greatly improves the matching of anatomy in cortical areas. The cortices are segmented and registered with the software Freesurfer. The deformation field is initially extended to the full 3D brain volume using a 3D harmonic mapping that preserves the matching between cortical surfaces. Finally, these deformation fields are used to initialize a 3D Riemannian fluid registration algorithm, that improves the alignment of subcortical brain regions. We validate this method on an MRI dataset from 92 healthy adult twins. Results are compared to those based on volumetric registration without surface constraints; the resulting mean templates resolve consistent anatomical features both subcortically and at the cortex, suggesting that the approach is well-suited for cross-subject integration of functional and anatomic data.