Concept: Procrustes analysis
Adequate normalization minimizes the effects of systematic technical variations and is a prerequisite for getting meaningful biological changes. However, there is inconsistency about miRNA normalization performances and recommendations. Thus, we investigated the impact of seven different normalization methods (reference gene index, global geometric mean, quantile, invariant selection, loess, loessM, and generalized procrustes analysis) on intra- and inter-platform performance of two distinct and commonly used miRNA profiling platforms.
BACKGROUND: Anopheles (Kerteszia) cruzii is a primary vector of Plasmodium parasites in Brazil’s Atlantic Forest. Adult females of An. cruzii and An. homunculus, which is a secondary malaria vector, are morphologically similar and difficult to distinguish when using external morphological characteristics only. These two species may occur syntopically with An. bellator, which is also a potential vector of Plasmodium species and is morphologically similar to An. cruzii and An. homunculus. Identification of these species based on female specimens is often jeopardised by polymorphisms, overlapping morphological characteristics and damage caused to specimens during collection. Wing geometric morphometrics has been used to distinguish several insect species; however, this economical and powerful tool has not been applied to Kerteszia species. Our objective was to assess wing geometry to distinguish An. cruzii, An. homunculus and An. bellator. METHODS: Specimens were collected in an area in the Serra do Mar hotspot biodiversity corridor of the Atlantic Forest biome (Cananeia municipality, State of Sao Paulo, Brazil). The right wings of females of An. cruzii (n= 40), An. homunculus (n= 50) and An. bellator (n= 27) were photographed. For each individual, 18 wing landmarks were subjected to standard geometric morphometrics. Discriminant analysis of Procrustean coordinates was performed to quantify wing shape variation. RESULTS: Individuals clustered into three distinct groups according to species with a slight overlap between representatives of An. cruzii and An. homunculus. The Mahalanobis distance between An. cruzii and An. homunculus was consistently lower (3.50) than that between An. cruzii and An. bellator (4.58) or An. homunculus and An. bellator (4.32). Pairwise cross-validated reclassification showed that geometric morphometrics is an effective analytical method to distinguish between An. bellator, An. cruzii and An. homunculus with a reliability rate varying between 78-88%. Shape analysis revealed that the wings of An. homunculus are narrower than those of An. cruzii and that An. bellator is different from both of the congeneric species. CONCLUSION: It is possible to distinguish among the vectors An. cruzii, An. homunculus and An. bellator based on female wing characteristics.
- The Journal of neuroscience : the official journal of the Society for Neuroscience
- Published over 5 years ago
Recent research has suggested that marijuana use is associated with volumetric and shape differences in subcortical structures, including the nucleus accumbens and amygdala, in a dose-dependent fashion. Replication of such results in well controlled studies is essential to clarify the effects of marijuana. To that end, this retrospective study examined brain morphology in a sample of adult daily marijuana users (n = 29) versus nonusers (n = 29) and a sample of adolescent daily users (n = 50) versus nonusers (n = 50). Groups were matched on a critical confounding variable, alcohol use, to a far greater degree than in previously published studies. We acquired high-resolution MRI scans, and investigated group differences in gray matter using voxel-based morphometry, surface-based morphometry, and shape analysis in structures suggested to be associated with marijuana use, as follows: the nucleus accumbens, amygdala, hippocampus, and cerebellum. No statistically significant differences were found between daily users and nonusers on volume or shape in the regions of interest. Effect sizes suggest that the failure to find differences was not due to a lack of statistical power, but rather was due to the lack of even a modest effect. In sum, the results indicate that, when carefully controlling for alcohol use, gender, age, and other variables, there is no association between marijuana use and standard volumetric or shape measurements of subcortical structures.
Whole brain MRI registration has many useful applications in group analysis and morphometry yet accurate registration across different neuropathological groups remains challenging. Structure-specific information, or anatomical guidance, can be used to initialize and constrain registration to improve accuracy and robustness. We describe here a multi-structure diffeomorphic registration approach that uses concurrent subcortical and cortical shape matching to guide the overall registration. Validation experiments carried out on openly-available datasets demonstrate comparable or improved alignment of subcortical and cortical brain structures over leading brain registration algorithms. We also demonstrate that a group-wise average atlas built with multi-structure registration accounts for greater inter-subject variability and provides more sensitive tensor-based morphometry measurements.
A general morphometric method for describing shape variation in a sample consisting of landmarks and multiple outline shapes is developed in this article. A distance metric is developed for such data and is used to embed the data in a low-dimensional Euclidean space. The Euclidean space is used to generate summary statistics such as mean and principal shape variation which are implicitly represented in the original space using elements of the sample. A new distance metric for outline shapes is proposed based on Procrustes distance that does not require the extraction of discrete points along the curve. The outline distance metric can be naturally combined with distances between landmarks. A method for aligning outlines and multiple outlines is developed that minimizes the distance metric. The method is compared with semilandmarks on synthetic data and 2 real data sets. Outline methods produce useful and valid results when suitably constrained by landmarks and are useful visualization aids, but questions remain about their suitability for answering biological questions until appropriate distance metrics can be biologically validated. [Morphometrics; outline analysis; semilandmark.].
We studied sexually dimorphic differences in the ilium using geometric morphometric analysis of 10 osteometric landmarks recorded by multislice computed tomography, based on three-dimensional reconstructions of 188 children (95 boys, 93 girls) of mixed origins living in the area of Toulouse, southern France, and ranging in age from 1 to 18 years. We used geometric morphometrics methodology first to test sexual dimorphism in size (centroid size) and shape (Procrustes residuals) and second to examine patterns of shape change with age (development) and size change with age (growth). On the basis of statistical significance testing, the ilium shape became sexually dimorphic at 11 years of age, although visible shape differences were observed as early as 1 year of age. There was no statistically significant difference in size between sexes. Trajectories of shape (development) and size (growth) differed throughout ontogeny and between sexes.
An anatomic and morphometric analysis of splenic variability using 3D reconstruction and spatial orientation from computed tomography
- Annals of anatomy = Anatomischer Anzeiger : official organ of the Anatomische Gesellschaft
- Published about 5 years ago
In terms of frequency, the spleen is the first organ affected in abdominal trauma, resulting even today in a high rate of mortality (10%). Nevertheless, very few studies have investigated splenic quantitative morphometry as to shape and spatial orientation. Therefore, we analysed healthy spleen variability in order to integrate it in its environment and to correlate its morphometric parameters to anthropometric characteristics.
Evaluating phenotypic plasticity in attachment organs of parasites can provide information on the capacity to colonize new hosts and illuminate evolutionary processes driving host specificity. We analysed the variability in shape and size of the dorsal and ventral anchors of Ligophorus cephali from Mugil cephalus by means of geometric morphometrics and multivariate statistics. We also assessed the morphological integration between anchors and between the roots and points in order to gain insight into their functional morphology. Dorsal and ventral anchors showed a similar gradient of overall shape variation, but the amount of localized changes was much higher in the former. Statistical models describing variations in shape and size revealed clear differences between anchors. The dorsal anchor/bar complex seems more mobile than the ventral one in Ligophorus, and these differences may reflect different functional roles in attachment to the gills. The lower residual variation associated with the ventral anchor models suggests a tighter control of their shape and size, perhaps because these anchors seem to be responsible for firmer attachment and their size and shape would allow more effective responses to characteristics of the microenvironment within the individual host. Despite these putative functional differences, the high level of morphological integration indicates a concerted action between anchors. In addition, we found a slight, although significant, morphological integration between roots and points in both anchors, which suggests that a large fraction of the observed phenotypic variation does not compromise the functional role of anchors as levers. Given the low level of genetic variation in our sample, it is likely that much of the morphological variation reflects host-driven plastic responses. This supports the hypothesis of monogenean specificity through host-switching and rapid speciation. The present study demonstrates the potential of geometric morphometrics to provide new and previously unexplored insights into the functional morphology of attachment and evolutionary processes of host-parasite coevolution.
Chitosan interaction with chitosanase was examined through analysis of spectral line shapes in the NMR HSQC titration experiments. We established that the substrate, chitosan hexamer, binds to the enzyme through the three-state induced-fit mechanism with fast formation of the encounter complex followed by slow isomerization of the bound-state into the final conformation. Mapping of the chemical shift perturbations in two sequential steps of the mechanism highlighted involvement of the substrate-binding subsites and the hinge region in the binding reaction. Equilibrium parameters of the three-state model agreed with the overall thermodynamic dissociation constant determined by ITC. This study presented the first kinetic evidence of the induced-fit mechanism in the glycoside hydrolases.
Mindboggle (http://mindboggle.info) is an open source brain morphometry platform that takes in preprocessed T1-weighted MRI data and outputs volume, surface, and tabular data containing label, feature, and shape information for further analysis. In this article, we document the software and demonstrate its use in studies of shape variation in healthy and diseased humans. The number of different shape measures and the size of the populations make this the largest and most detailed shape analysis of human brains ever conducted. Brain image morphometry shows great potential for providing much-needed biological markers for diagnosing, tracking, and predicting progression of mental health disorders. Very few software algorithms provide more than measures of volume and cortical thickness, while more subtle shape measures may provide more sensitive and specific biomarkers. Mindboggle computes a variety of (primarily surface-based) shapes: area, volume, thickness, curvature, depth, Laplace-Beltrami spectra, Zernike moments, etc. We evaluate Mindboggle’s algorithms using the largest set of manually labeled, publicly available brain images in the world and compare them against state-of-the-art algorithms where they exist. All data, code, and results of these evaluations are publicly available.