The insulin signaling pathway in honey bee (Apis mellifera) caste development - differential expression of insulin-like peptides and insulin receptors in queen and worker larvae

The insulin/insulin-like signaling (IIS) pathway is an evolutionarily conserved module in the control of body size and correlated organ growth in metazoans. In the highly eusocial bees, the caste phenotypes differ not only in size and several structural features but also in individual fitness and life history. We investigated the developmental expression profiles of genes encoding the two insulin-like peptides (AmILP-1 and AmILP-2) and the two insulin receptors (AmInR-1 and AmInR-2) predicted in the honey bee genome. Quantitative PCR analysis for queen and worker larvae in critical stages of caste development showed that AmILP-2 is the predominantly transcribed ILP in both castes, with higher expression in workers than in queens. Expression of both InR genes sharply declined in fourth instar queen larvae, but showed little modulation in workers. On first sight, these findings are non-intuitive, considering the higher growth rates of queens, but they can be interpreted as possibly antagonistic crosstalk between the IIS module and juvenile hormone. Analyzing AmInR-1 and AmInR-2 expression in ovaries of queen and worker larvae revealed low transcript levels in queens and a sharp drop in AmInR-2 expression in fifth instar worker larvae, indicating relative independence in tissue-specific versus overall IIS pathway activity. (C) 2008 Elsevier Ltd. All rights reserved.

Differential expression of hypoxia pathway genes in honey bee (Apis mellifera L.) caste development

Diphenism in social bees is essentially contingent on nutrient-induced cellular and systemic physiological responses resulting in divergent gene expression patterns. Analyses of juvenile hormone (JH) titers and functional genomics assays of the insulin-insulin-like signaling (IIS) pathway and its associated branch, target-of-rapamycin (TOR), revealed systemic responses underlying honey bee (Apis mellifera) caste development. Nevertheless, little attention has been paid to cellular metabolic responses. Following up earlier investigations showing major caste differences in oxidative metabolism and mitochondrial physiology, we herein identified honey bee homologs of hypoxia signaling factors, HIF alpha/Sima, HIF beta/Tango and PHD/Fatiga and we investigated their transcript levels throughout critical stages of larval development. Amsima, Amtango and Amfatiga showed correlated transcriptional activity, with two peaks of occurring in both queens and workers, the first one shortly after the last larval molt and the second during the cocoon-spinning phase. Transcript levels for the three genes were consistently higher in workers. As there is no evidence for major microenvironmental differences in oxygen levels within the brood nest area, this appears to be an inherent caste character. Quantitative PCR analyses on worker brain, ovary, and leg imaginal discs showed that these tissues differ in transcript levels. Being a highly conserved pathway and linked to IIS/TOR, the hypoxia gene expression pattern seen in honey bee larvae denotes that the hypoxia pathway has undergone a transformation, at least during larval development, from a response to environmental oxygen concentrations to an endogenous regulatory factor in the diphenic development of honey bee larvae. (C) 2010 Elsevier Ltd. All rights reserved.

Template-based quadrilateral meshing

Generating quadrilateral meshes is a highly non-trivial task, as design decisions are frequently driven by specific application demands. Automatic techniques can optimize objective quality metrics, such as mesh regularity, orthogonality, alignment and adaptivity; however, they cannot make subjective design decisions. There are a few quad meshing approaches that offer some mechanisms to include the user in the mesh generation process; however, these techniques either require a large amount of user interaction or do not provide necessary or easy to use inputs. Here, we propose a template-based approach for generating quad-only meshes from triangle surfaces. Our approach offers a flexible mechanism to allow external input, through the definition of alignment features that are respected during the mesh generation process. While allowing user inputs to support subjective design decisions, our approach also takes into account objective quality metrics to produce semi-regular, quad-only meshes that align well to desired surface features. Published by Elsevier Ltd.

PedVis: A Structured, Space-Efficient Technique for Pedigree Visualization

Public genealogical databases are becoming increasingly populated with historical data and records of the current population`s ancestors. As this increasing amount of available information is used to link individuals to their ancestors, the resulting trees become deeper and more dense, which justifies the need for using organized, space-efficient layouts to display the data. Existing layouts are often only able to show a small subset of the data at a time. As a result, it is easy to become lost when navigating through the data or to lose sight of the overall tree structure. On the contrary, leaving space for unknown ancestors allows one to better understand the tree`s structure, but leaving this space becomes expensive and allows fewer generations to be displayed at a time. In this work, we propose that the H-tree based layout be used in genealogical software to display ancestral trees. We will show that this layout presents an increase in the number of displayable generations, provides a nicely arranged, symmetrical, intuitive and organized fractal structure, increases the user`s ability to understand and navigate through the data, and accounts for the visualization requirements necessary for displaying such trees. Finally, user-study results indicate potential for user acceptance of the new layout.

Interactive Vector Field Feature Identification

We introduce a flexible technique for interactive exploration of vector field data through classification derived from user-specified feature templates. Our method is founded on the observation that, while similar features within the vector field may be spatially disparate, they share similar neighborhood characteristics. Users generate feature-based visualizations by interactively highlighting well-accepted and domain specific representative feature points. Feature exploration begins with the computation of attributes that describe the neighborhood of each sample within the input vector field. Compilation of these attributes forms a representation of the vector field samples in the attribute space. We project the attribute points onto the canonical 2D plane to enable interactive exploration of the vector field using a painting interface. The projection encodes the similarities between vector field points within the distances computed between their associated attribute points. The proposed method is performed at interactive rates for enhanced user experience and is completely flexible as showcased by the simultaneous identification of diverse feature types.

Fiedler trees for multiscale surface analysis

In this work we introduce a new hierarchical surface decomposition method for multiscale analysis of surface meshes. In contrast to other multiresolution methods, our approach relies on spectral properties of the surface to build a binary hierarchical decomposition. Namely, we utilize the first nontrivial eigenfunction of the Laplace-Beltrami operator to recursively decompose the surface. For this reason we coin our surface decomposition the Fiedler tree. Using the Fiedler tree ensures a number of attractive properties, including: mesh-independent decomposition, well-formed and nearly equi-areal surface patches, and noise robustness. We show how the evenly distributed patches can be exploited for generating multiresolution high quality uniform meshes. Additionally, our decomposition permits a natural means for carrying out wavelet methods, resulting in an intuitive method for producing feature-sensitive meshes at multiple scales. Published by Elsevier Ltd.