Childhood medulloblastoma: novel approaches to the classification of a heterogeneous disease

Hybridization and polyploidization are important processes for plant evolution. However, classification of hybrid or polyploid species has been notoriously difficult because of the complexity of processes and different evolutionary scenarios that do not fit with classical species concepts. Polyploid complexes are formed via combinations of allopolyploidy, autopolyploidy and homoploid hybridization with persisting sexual reproduction, resulting in many discrete lineages that have been classified as species. Polyploid complexes with facultative apomixis result in complicated net-work like clusters, or rarely in agamospecies. Various case studies illustrate the problems that apply to traditional species concepts to hybrids and polyploids. Conceptual progress can be made if lineage formation is accepted as an inevitable consequence of meiotic sex, which is established already in the first eukaryotes as a DNA restoration tool. The turnaround of the viewpoint that sex forms species as lineages helps to overcome traditional thinking of species as “units”. Lineage formation and self-sustainability is the prerequisite for speciation and can also be applied to hybrids and polyploids. Species delimitation is aided by the improved recognition of lineages via various novel -omics methods, by understanding meiosis functions, and by recognizing functional phenotypes by considering morphological-physiological-ecological adaptations.

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Classification of Childhood Medulloblastoma and its subtypes using Transfer Learning features - A Comparative Study of Deep Convolutional Neural Networks

2020 International Conference on Computer, Electrical & Communication Engineering (ICCECE) ◽

10.1109/iccece48148.2020.9223104 ◽

2020 ◽

Author(s):

Daisy Das ◽

Lipi B. Mahanta ◽

Basanta K Baishya ◽

Shabnam Ahmed

Keyword(s):

Neural Networks ◽

Comparative Study ◽

Transfer Learning ◽

Convolutional Neural Networks ◽

Deep Convolutional Neural Networks ◽

Childhood Medulloblastoma

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Novel approaches for the molecular classification of prostate cancer

Asian Journal of Andrology ◽

10.1038/aja.2010.95 ◽

2010 ◽

Vol 12 (5) ◽

pp. 620-622 ◽

Cited By ~ 2

Author(s):

Robert H. Getzenberg

Keyword(s):

Prostate Cancer ◽

Molecular Classification ◽

Novel Approaches

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Note on the spectral classification of carbon stars in the photographic infrared region

Symposium - International Astronomical Union ◽

10.1017/s0074180900053080 ◽

1966 ◽

Vol 24 ◽

pp. 21-23

Author(s):

Y. Fujita

Keyword(s):

Infrared Region ◽

Spectral Classification ◽

Carbon Stars

We have investigated the spectrograms (dispersion: 8Å/mm) in the photographic infrared region fromλ7500 toλ9000 of some carbon stars obtained by the coudé spectrograph of the 74-inch reflector attached to the Okayama Astrophysical Observatory. The names of the stars investigated are listed in Table 1.

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Diagnostic Value of Electron Microscopy in Soft Tissue Tumors

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100068096 ◽

1970 ◽

Vol 28 ◽

pp. 220-221

Author(s):

Gerald Fine ◽

Azorides R. Morales

Keyword(s):

Cardiac Myxoma ◽

Osteogenic Sarcoma ◽

Diagnostic Value ◽

Soft Tissue Tumors ◽

Amelanotic Melanoma ◽

Growth Patterns ◽

Light Microscopic Level ◽

Mesenchymal Tumors ◽

Good Agreement

For years the separation of carcinoma and sarcoma and the subclassification of sarcomas has been based on the appearance of the tumor cells and their microscopic growth pattern and information derived from certain histochemical and special stains. Although this method of study has produced good agreement among pathologists in the separation of carcinoma from sarcoma, it has given less uniform results in the subclassification of sarcomas. There remain examples of neoplasms of different histogenesis, the classification of which is questionable because of similar cytologic and growth patterns at the light microscopic level; i.e. amelanotic melanoma versus carcinoma and occasionally sarcoma, sarcomas with an epithelial pattern of growth simulating carcinoma, histologically similar mesenchymal tumors of different histogenesis (histiocytoma versus rhabdomyosarcoma, lytic osteogenic sarcoma versus rhabdomyosarcoma), and myxomatous mesenchymal tumors of diverse histogenesis (myxoid rhabdo and liposarcomas, cardiac myxoma, myxoid neurofibroma, etc.)

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Ultrastructure of mesotheliomas

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100110775 ◽

1984 ◽

Vol 42 ◽

pp. 98-101

Author(s):

Irving Dardick

Keyword(s):

Electron Microscopy ◽

Latent Period ◽

Spindle Cell ◽

Spindle Cell Sarcoma ◽

Metastatic Adenocarcinoma ◽

Cell Sarcoma ◽

Cytological Features ◽

Industrial Use ◽

Degree Of Differentiation

With the extensive industrial use of asbestos in this century and the long latent period (20-50 years) between exposure and tumor presentation, the incidence of malignant mesothelioma is now increasing. Thus, surgical pathologists are more frequently faced with the dilemma of differentiating mesothelioma from metastatic adenocarcinoma and spindle-cell sarcoma involving serosal surfaces. Electron microscopy is amodality useful in clarifying this problem.In utilizing ultrastructural features in the diagnosis of mesothelioma, it is essential to appreciate that the classification of this tumor reflects a variety of morphologic forms of differing biologic behavior (Table 1). Furthermore, with the variable histology and degree of differentiation in mesotheliomas it might be expected that the ultrastructure of such tumors also reflects a range of cytological features. Such is the case.

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Interpreting HVEM of muscle-cell impulse networks

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s042482010012103x ◽

1992 ◽

Vol 50 (1) ◽

pp. 126-127

Author(s):

Paul DeCosta ◽

Kyugon Cho ◽

Stephen Shemlon ◽

Heesung Jun ◽

Stanley M. Dunn

Keyword(s):

Structural Analysis ◽

Muscle Cell ◽

Electron Micrographs ◽

Relative Size ◽

Automatic Classification ◽

Nerve Fibers ◽

Analysis Algorithm ◽

Structural Networks

Introduction: The analysis and interpretation of electron micrographs of cells and tissues, often requires the accurate extraction of structural networks, which either provide immediate 2D or 3D information, or from which the desired information can be inferred. The images of these structures contain lines and/or curves whose orientation, lengths, and intersections characterize the overall network.Some examples exist of studies that have been done in the analysis of networks of natural structures. In, Sebok and Roemer determine the complexity of nerve structures in an EM formed slide. Here the number of nodes that exist in the image describes how dense nerve fibers are in a particular region of the skin. Hildith proposes a network structural analysis algorithm for the automatic classification of chromosome spreads (type, relative size and orientation).

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