Behavioral suites mediate group-level foraging dynamics in communities of tropical stingless bees

Competition for floral resources is a key force shaping pollinator communities, particularly among social bees. The ability of social bees to recruit nestmates for group foraging is hypothesized to be a major factor in their ability to dominate rich resources such as mass-flowering trees. We tested the role of group foraging in attaining dominance by stingless bees, eusocial tropical pollinators that exhibit high diversity in foraging strategies. We provide the first experimental evidence that meliponine group foraging strategies, large colony sizes and aggressive behavior form a suite of traits that enable colonies to improve dominance of rich resources. Using a diverse assemblage of Brazilian stingless bee species and an array of artificial ""flowers"" that provided a sucrose reward, we compared species` dominance and visitation under unrestricted foraging conditions and with experimental removal of group-foraging species. Dominance does not vary with individual body size, but rather with foraging group size. Species that recruit larger numbers of nestmates (Scaptotrigona aff. depilis, Trigona hyalinata, Trigona spinipes) dominated both numerically (high local abundance) and behaviorally (controlling feeders). Removal of group-foraging species increased feeding opportunities for solitary foragers (Frieseomelitta varia, Melipona quadrifasciata and Nannotrigona testaceicornis). Trigona hyalinata always dominated under unrestricted conditions. When this species was removed, T. spinipes or S. aff. depilis controlled feeders and limited visitation by solitary-foraging species. Because bee foraging patterns determine plant pollination success, understanding the forces that shape these patterns is crucial to ensuring pollination of both crops and natural areas in the face of current pollinator declines.

Design issues for knowledge artifacts

The notion of knowledge artifact has rapidly gained popularity in the fields of general knowledge management and more recently knowledge-based systems. The main goal on this paper is to propose and discuss a methodology for the design and implementation of knowledge-based systems founded on knowledge artifacts. We advocate that the systems built according to this methodology can be effective to convey the flow of knowledge between different communities of practice. Our methodology has been developed from the ground up, i.e. we have built some concrete systems based on the abstract notion of knowledge artifact and synthesized our methodology based on reflections upon our experiences building these systems. In this paper, we also describe the most relevant systems we have built and how they have guided us to the synthesis of our proposed methodology. (C) 2008 Elsevier B.V. All rights reserved.

Integration of Ligand- and Target-Based Virtual Screening for the Discovery of Cruzain Inhibitors

A myriad of methods are available for virtual screening of small organic compound databases. In this study we have successfully applied a quantitative model of consensus measurements, using a combination of 3D similarity searches (ROCS and EON), Hologram Quantitative Structure Activity Relationships (HQSAR) and docking (FRED, FlexX, Glide and AutoDock Vina), to retrieve cruzain inhibitors from collected databases. All methods were assessed individually and then combined in a Ligand-Based Virtual Screening (LBVS) and Target-Based Virtual Screening (TBVS) consensus scoring, using Receiving Operating Characteristic (ROC) curves to evaluate their performance. Three consensus strategies were used: scaled-rank-by-number, rank-by-rank and rank-by-vote, with the most thriving the scaled-rank-by-number strategy, considering that the stiff ROC curve appeared to be satisfactory in every way to indicate a higher enrichment power at early retrieval of active compounds from the database. The ligand-based method provided access to a robust and predictive HQSAR model that was developed to show superior discrimination between active and inactive compounds, which was also better than ROCS and EON procedures. Overall, the integration of fast computational techniques based on ligand and target structures resulted in a more efficient retrieval of cruzain inhibitors with desired pharmacological profiles that may be useful to advance the discovery of new trypanocidal agents.