Effects of sex chromosome dosage on corpus callosum morphology in supernumerary sex chromosome aneuploidies.

BackgroundSupernumerary sex chromosome aneuploidies (sSCA) are characterized by the presence of one or more additional sex chromosomes in an individual's karyotype; they affect around 1 in 400 individuals. Although there is high variability, each sSCA subtype has a characteristic set of cognitive and physical phenotypes. Here, we investigated the differences in the morphometry of the human corpus callosum (CC) between sex-matched controls 46,XY (N =99), 46,XX (N =93), and six unique sSCA karyotypes: 47,XYY (N =29), 47,XXY (N =58), 48,XXYY (N =20), 47,XXX (N =30), 48,XXXY (N =5), and 49,XXXXY (N =6).MethodsWe investigated CC morphometry using local and global area, local curvature of the CC boundary, and between-landmark distance analysis (BLDA). We hypothesized that CC morphometry would vary differentially along a proposed spectrum of Y:X chromosome ratio with supernumerary Y karyotypes having the largest CC areas and supernumerary X karyotypes having significantly smaller CC areas. To investigate this, we defined an sSCA spectrum based on a descending Y:X karyotype ratio: 47,XYY, 46,XY, 48,XXYY, 47,XXY, 48,XXXY, 49,XXXXY, 46,XX, 47,XXX. We similarly explored the effects of both X and Y chromosome numbers within sex. Results of shape-based metrics were analyzed using permutation tests consisting of 5,000 iterations.ResultsSeveral subregional areas, local curvature, and BLDs differed between groups. Moderate associations were found between area and curvature in relation to the spectrum and X and Y chromosome counts. BLD was strongly associated with X chromosome count in both male and female groups.ConclusionsOur results suggest that X- and Y-linked genes have differential effects on CC morphometry. To our knowledge, this is the first study to compare CC morphometry across these extremely rare groups

Postulates on electromagnetic activity in biological systems and cancer

A framework of postulates is formulated to define the existence, nature, and function of a coherent state far from thermodynamic equilibrium in biological systems as an essential condition for the existence of life. This state is excited and sustained by energy supply. Mitochondria producing small packets of energy in the form of adenosine and guanosine triphosphate and strong static electric field around them form boundary elements between biochemical-genetic and physical processes. The transformation mechanism of chemical energy into useful work for biological needs and the excitation of the coherent state far from thermodynamic equilibrium are fundamental problems. The exceptional electrical polarity of biological objects and long-range interactions suggest a basic role of the endogenous electromagnetic field generated by living cells. The formulated postulates encompass generation, properties and function of the electromagnetic field connected with biological activity and its pathological deviations. Excited longitudinal polar oscillations in microtubules in eukaryotic cells generate the endogenous electromagnetic field. The metabolic activity of mitochondria connected with water ordering forms conditions for excitation. The electrodynamic field plays an important role in the establishment of coherence, directional transport, organization of morphological structures, interactions, information transfer, and brain activity. An overview of experimental results and physical models supporting the postulates is included. The existence of the endogenous biological electromagnetic field, its generation by microtubules and supporting effects produced by mitochondria have a reasonable experimental foundation. Cancer transformation is a pathological reduction of the coherent energy state far from thermodynamic equilibrium. Malignancy, i.e. local invasion and metastasis, is a direct consequence of mitochondrial dysfunction, disturbed microtubule polar oscillations and the generated electromagnetic field

Learning a morphological system without a default: the Polish genitive

The acquisition of the English past tense inflection is the paradigm example of rule learning in the child language literature and has become something of a test case for theories of language development. This is unfortunate, as the idiosyncratic properties of the English system of marking tense make it a rather unrepresentative example of morphological development. In this paper, I contrast this familiar inflection with a much more complex morphological subsystem, the Polish genitive. The genitive case has three different markers, each restricted to a different subset of nouns, in both the singular and the plural. Analysis of the spontanous speech of three children between the ages of 1;4 and 4;11 showed that they generalized, and overgeneralized, all three singular endings. However, error rates were extremely low and there is no evidence that they treated any one ending as the ‘default’. The genitive plural, on the other hand, showed a strikingly different pattern of acquisition, similar to that seen in English-speaking children learning the past tense. It is argued that in the latter two cases, the default-like character of one of the affixes is attributable to the properties of the relevant inflectional subsystems, not to the predispositions that children bring to the language-learning task

Application of spectral and spatial indices for specific class identification in Airborne Prism EXperiment (APEX) imaging spectrometer data for improved land cover classification

Hyperspectral remote sensing's ability to capture spectral information of targets in very narrow bandwidths gives rise to many intrinsic applications. However, the major limiting disadvantage to its applicability is its dimensionality, known as the Hughes Phenomenon. Traditional classification and image processing approaches fail to process data along many contiguous bands due to inadequate training samples. Another challenge of successful classification is to deal with the real world scenario of mixed pixels i.e. presence of more than one class within a single pixel. An attempt has been made to deal with the problems of dimensionality and mixed pixels, with an objective to improve the accuracy of class identification. In this paper, we discuss the application of indices to cope with the disadvantage of the dimensionality of the Airborne Prism EXperiment (APEX) hyperspectral Open Science Dataset (OSD) and to improve the classification accuracy using the Possibilistic c–Means (PCM) algorithm. This was used for the formulation of spectral and spatial indices to describe the information in the dataset in a lesser dimensionality. This reduced dimensionality is used for classification, attempting to improve the accuracy of determination of specific classes. Spectral indices are compiled from the spectral signatures of the target and spatial indices have been defined using texture analysis over defined neighbourhoods. The classification of 20 classes of varying spatial distributions was considered in order to evaluate the applicability of spectral and spatial indices in the extraction of specific class information. The classification of the dataset was performed in two stages; spectral and a combination of spectral and spatial indices individually as input for the PCM classifier. In addition to the reduction of entropy, while considering a spectral-spatial indices approach, an overall classification accuracy of 80.50% was achieved, against 65% (spectral indices only) and 59.50% (optimally determined principal component

Mapping lung cancer epithelial-mesenchymal transition states and trajectories with single-cell resolution.

Elucidating the spectrum of epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET) states in clinical samples promises insights on cancer progression and drug resistance. Using mass cytometry time-course analysis, we resolve lung cancer EMT states through TGFβ-treatment and identify, through TGFβ-withdrawal, a distinct MET state. We demonstrate significant differences between EMT and MET trajectories using a computational tool (TRACER) for reconstructing trajectories between cell states. In addition, we construct a lung cancer reference map of EMT and MET states referred to as the EMT-MET PHENOtypic STAte MaP (PHENOSTAMP). Using a neural net algorithm, we project clinical samples onto the EMT-MET PHENOSTAMP to characterize their phenotypic profile with single-cell resolution in terms of our in vitro EMT-MET analysis. In summary, we provide a framework to phenotypically characterize clinical samples in the context of in vitro EMT-MET findings which could help assess clinical relevance of EMT in cancer in future studies

Vector ordering and multispectral morphological image processing

International audienceThis chapter illustrates the suitability of recent multivariate ordering approaches to morphological analysis of colour and multispectral images working on their vector representation. On the one hand, supervised ordering renders machine learning no-tions and image processing techniques, through a learning stage to provide a total ordering in the colour/multispectral vector space. On the other hand, anomaly-based ordering, automatically detects spectral diversity over a majority background, al-lowing an adaptive processing of salient parts of a colour/multispectral image. These two multivariate ordering paradigms allow the definition of morphological operators for multivariate images, from algebraic dilation and erosion to more advanced techniques as morphological simplification, decomposition and segmentation. A number of applications are reviewed and implementation issues are discussed in detail

Spatio-temporal expression patterns of Arabidopsis thaliana and Medicago truncatula defensin-like genes

Plant genomes contain several hundred defensin-like (DEFL) genes that encode short cysteine-rich proteins resembling defensins, which are well known antimicrobial polypeptides. Little is known about the expression patterns or functions of many DEFLs because most were discovered recently and hence are not well represented on standard microarrays. We designed a custom Affymetrix chip consisting of probe sets for 317 and 684 DEFLs from Arabidopsis thaliana and Medicago truncatula, respectively for cataloging DEFL expression in a variety of plant organs at different developmental stages and during symbiotic and pathogenic associations. The microarray analysis provided evidence for the transcription of 71% and 90% of the DEFLs identified in Arabidopsis and Medicago, respectively, including many of the recently annotated DEFL genes that previously lacked expression information. Both model plants contain a subset of DEFLs specifically expressed in seeds or fruits. A few DEFLs, including some plant defensins, were significantly up-regulated in Arabidopsis leaves inoculated with Alternaria brassicicola or Pseudomonas syringae pathogens. Among these, some were dependent on jasmonic acid signaling or were associated with specific types of immune responses. There were notable differences in DEFL gene expression patterns between Arabidopsis and Medicago, as the majority of Arabidopsis DEFLs were expressed in inflorescences, while only a few exhibited root-enhanced expression. By contrast, Medicago DEFLs were most prominently expressed in nitrogen-fixing root nodules. Thus, our data document salient differences in DEFL temporal and spatial expression between Arabidopsis and Medicago, suggesting distinct signaling routes and distinct roles for these proteins in the two plant species