scholarly journals Morphology of Juniperus Cone and Its Implications on Cone Evolution

2020 ◽  
Author(s):  
Xin Wang ◽  
Xiuping Xu
Keyword(s):  
Spatial Arrangement ◽  
External Morphology ◽  
Axillary Shoot ◽  
Micro Ct ◽  
Juniperus Oxycedrus

Abstract Background The basic cone unit in Pinaceae is called bract-scale-seed complex (BSSC), in which the scale is supposed to be equivalent to an axillary shoot bearing ovules in Cordaitales. This correlation established by Florin provides a rational foundation on which an interpretation for the origin of cones in at least most Coniferales is built, and may be called Florin model for convenience. Cupressaceae is a family in Coniferales, in which the ovule-scale and its subtending bract are thought fully fused and hard to distinguish by external morphology. Results Different from Pinaceae and other typical conifers, Juniperus (Cupressaceae) appears not following Florin’s model closely. For example, the cone of Juniperus oxycedrus has only three rather than more BSSCs in a whorl, and its fleshy fructification appears more like a berry rather than a typical coniferalean cone. In this paper morphology and anatomy of Juniperus oxycedrus fructifications are documented using Micro CT. New observation demonstrates clearly that three seeds alternate the three surrounding bracts in J. oxycedrus. Conclusions Such spatial arrangement is quite different from that in typical BSSCs, in which the ovules should be aligned with their subtending bract. Together with other unexpected features in other cupressaceous cones, Juniperus my help to expand the avenue through which we can interpret the origin and homology of cones in Cupressaceae and other conifers or gymnosperms in general.

Internal and external morphology of mandibular molars: An original micro-CT study and meta-analysis with review of implications for endodontic therapy

2018 ◽  
Vol 31 (6) ◽  
pp. 797-811 ◽  
Author(s):  
Iwona M. Tomaszewska ◽  
Bendik Skinningsrud ◽  
Anna Jarzębska ◽  
Jakub R. Pękala ◽  
Jacek Tarasiuk ◽  
...  
Keyword(s):  
Meta Analysis ◽  
External Morphology ◽  
Micro Ct ◽  
Mandibular Molars

scholarly journals Tamilokus mabinia, a new, anatomically divergent genus and species of wood-boring bivalve from the Philippines

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6256 ◽  
Author(s):  
J. Reuben Shipway ◽  
Marvin A. Altamia ◽  
Gary Rosenberg ◽  
Gisela P. Concepcion ◽  
Margo G. Haygood ◽  
...  
Keyword(s):  
Spatial Arrangement ◽  
Adductor Muscle ◽  
The Philippines ◽  
Rrna Gene ◽  
Micro Ct ◽  
Micro Computed Tomography ◽  
New Genus And Species ◽  
The Family ◽  
Well Differentiated ◽  
Wood Boring

Here we describe an anatomically divergent wood-boring bivalve belonging to the family Teredinidae. Specimens were collected off the coast of Mabini, Batangas, Philippines, in February 2018, from sunken driftwood at a depth of less than 2 m. A combination of characteristics differentiates these specimens from members of previously named teredinid genera and species. Most notable among these include: an enlarged cephalic hood which extends across the posterior slope of the shell valves and integrates into the posterior adductor muscle; a unique structure, which we term the ‘cephalic collar’, formed by protruding folds of the mantle immediately ventral to the foot and extending past the posterior margin of the valves; a large globular stomach located entirely posterior to the posterior adductor muscle and extending substantially beyond the posterior gape of the valves; an elongate crystalline style and style sac extending from the base of the foot, past the posterior adductor muscle, to the posteriorly located stomach; calcareous pallets distinct from those of described genera; a prominently flared mantle collar which extends midway along the stalk of the pallets; and, separated siphons that bear a pigmented pinstripe pattern with highly elaborate compound papillae on the incurrent siphon aperture. We used Micro-Computed Tomography (Micro-CT) to build a virtual 3D anatomical model of this organism, confirming the spatial arrangement of the structures described above. Phylogenetic analysis of the small (18S) and large (28S) nuclear rRNA gene sequences, place this bivalve within the Teredindae on a branch well differentiated from previously named genera and species. We propose the new genus and species Tamilokus mabinia to accommodate these organisms, raising the total number of genera in this economically and environmentally important family to 17. This study demonstrates the efficacy of Micro-CT for anatomical description of a systematically challenging group of bivalves whose highly derived body plans are differentiated predominantly by soft tissue adaptations rather than features of calcareous hard-parts.

Conformation of Ribosomes from Escherichia Coli

1974 ◽  
Vol 32 ◽  
pp. 210-211
Author(s):  
M. Boublik ◽  
W. Hellmann ◽  
F. Jenkins
Keyword(s):  
Binding Sites ◽  
Ribosomal Proteins ◽  
Fluorescent Dyes ◽  
Protein Biosynthesis ◽  
Three Dimensional ◽  
Spatial Arrangement ◽  
Dimensional Structure ◽  
Complete Understanding ◽  
And Function

The present knowledge of the three-dimensional structure of ribosomes is far too limited to enable a complete understanding of the various roles which ribosomes play in protein biosynthesis. The spatial arrangement of proteins and ribonuclec acids in ribosomes can be analysed in many ways. Determination of binding sites for individual proteins on ribonuclec acid and locations of the mutual positions of proteins on the ribosome using labeling with fluorescent dyes, cross-linking reagents, neutron-diffraction or antibodies against ribosomal proteins seem to be most successful approaches. Structure and function of ribosomes can be correlated be depleting the complete ribosomes of some proteins to the functionally inactive core and by subsequent partial reconstitution in order to regain active ribosomal particles.

Structural organization of escherichia coli ribosomes as determined by immuno electron microscopy

1978 ◽  
Vol 36 (2) ◽  
pp. 166-167 ◽  
Author(s):  
G. Stöffler ◽  
R.W. Bald ◽  
J. Dieckhoff ◽  
H. Eckhard ◽  
R. Lührmann ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Escherichia Coli ◽  
Ribosomal Proteins ◽  
Structural Organization ◽  
Three Dimensional ◽  
Ribosomal Subunit ◽  
Spatial Arrangement ◽  
Small Subunit ◽  
Antibody Binding ◽  
Immuno Electron Microscopy

A central step towards an understanding of the structure and function of the Escherichia coli ribosome, a large multicomponent assembly, is the elucidation of the spatial arrangement of its 54 proteins and its three rRNA molecules. The structural organization of ribosomal components has been investigated by a number of experimental approaches. Specific antibodies directed against each of the 54 ribosomal proteins of Escherichia coli have been performed to examine antibody-subunit complexes by electron microscopy. The position of the bound antibody, specific for a particular protein, can be determined; it indicates the location of the corresponding protein on the ribosomal surface.The three-dimensional distribution of each of the 21 small subunit proteins on the ribosomal surface has been determined by immuno electron microscopy: the 21 proteins have been found exposed with altogether 43 antibody binding sites. Each one of 12 proteins showed antibody binding at remote positions on the subunit surface, indicating highly extended conformations of the proteins concerned within the 30S ribosomal subunit; the remaining proteins are, however, not necessarily globular in shape (Fig. 1).

Colloidal systems in soils

1994 ◽  
Vol 52 ◽  
pp. 64-65
Author(s):  
J. Thieme ◽  
J. Niemeyer ◽  
P. Guttman
Keyword(s):  
Clay Minerals ◽  
Polymeric Materials ◽  
Spatial Arrangement ◽  
High Specific Surface Area ◽  
Turnover Rates ◽  
Colloidal Systems ◽  
Chemical Conditions ◽  
Aggregation Phenomena ◽  
Iron And Manganese ◽  
Soil Colloids

In soil science the fraction of colloids in soils is understood as particles with diameters smaller than 2μm. Clay minerals, aquoxides of iron and manganese, humic substances, and other polymeric materials are found in this fraction. The spatial arrangement (microstructure) is controlled by the substantial structure of the colloids, by the chemical composition of the soil solution, and by thesoil biota. This microstructure determines among other things the diffusive mass flow within the soils and as a result the availability of substances for chemical and microbiological reactions. The turnover of nutrients, the adsorption of toxicants and the weathering of soil clay minerals are examples of these surface mediated reactions. Due to their high specific surface area, the soil colloids are the most reactive species in this respect. Under the chemical conditions in soils, these minerals are associated in larger aggregates. The accessibility of reactive sites for these reactions on the surface of the colloids is reduced by this aggregation. To determine the turnover rates of chemicals within these aggregates it is highly desirable to visualize directly these aggregation phenomena.

Computational Micrograph Registration with Sieve Processes

1996 ◽  
Vol 54 ◽  
pp. 440-441
Author(s):  
P.J. Phillips ◽  
J. Huang ◽  
S. M. Dunn
Keyword(s):  
Planar Graph ◽  
Efficient Algorithm ◽  
Spatial Organization ◽  
Spatial Arrangement ◽  
Stereo Image ◽  
Image Model ◽  
Geometric Invariants ◽  
Point Set

In this paper we present an efficient algorithm for automatically finding the correspondence between pairs of stereo micrographs, the key step in forming a stereo image. The computation burden in this problem is solving for the optimal mapping and transformation between the two micrographs. In this paper, we present a sieve algorithm for efficiently estimating the transformation and correspondence.In a sieve algorithm, a sequence of stages gradually reduce the number of transformations and correspondences that need to be examined, i.e., the analogy of sieving through the set of mappings with gradually finer meshes until the answer is found. The set of sieves is derived from an image model, here a planar graph that encodes the spatial organization of the features. In the sieve algorithm, the graph represents the spatial arrangement of objects in the image. The algorithm for finding the correspondence restricts its attention to the graph, with the correspondence being found by a combination of graph matchings, point set matching and geometric invariants.

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