Mechanical Analysis of Feeding Behavior in the Extinct “Terror Bird” Andalgalornis steulleti (Gruiformes: Phorusrhacidae)

The South American phorusrhacid bird radiation comprised at least 18 species of small to gigantic terrestrial predators for which there are no close modern analogs. Here we perform functional analyses of the skull of the medium-sized (∼40 kg) patagornithine phorusrhacid Andalgalornis steulleti (upper Miocene–lower Pliocene, Andalgalá Formation, Catamarca, Argentina) to assess its mechanical performance in a comparative context. Based on computed tomographic (CT) scanning and morphological analysis, the skull of Andalgalornis steulleti is interpreted as showing features reflecting loss of intracranial immobility. Discrete anatomical attributes permitting such cranial kinesis are widespread phorusrhacids outgroups, but this is the first clear evidence of loss of cranial kinesis in a gruiform bird and may be among the best documented cases among all birds. This apomorphic loss is interpreted as an adaptation for enhanced craniofacial rigidity, particularly with regard to sagittal loading. We apply a Finite Element approach to a three-dimensional (3D) model of the skull. Based on regression analysis we estimate the bite force of Andalgalornis at the bill tip to be 133 N. Relative to results obtained from Finite Element Analysis of one of its closest living relatives (seriema) and a large predatory bird (eagle), the phorusrhacid's skull shows relatively high stress under lateral loadings, but low stress where force is applied dorsoventrally (sagittally) and in “pullback” simulations. Given the relative weakness of the skull mediolaterally, it seems unlikely that Andalgalornis engaged in potentially risky behaviors that involved subduing large, struggling prey with its beak. We suggest that it either consumed smaller prey that could be killed and consumed more safely (e.g., swallowed whole) or that it used multiple well-targeted sagittal strikes with the beak in a repetitive attack-and-retreat strategy

Structuring and extracting knowledge for the support of hypothesis generation in molecular biology

Background: Hypothesis generation in molecular and cellular biology is an empirical process in which knowledge derived from prior experiments is distilled into a comprehensible model. The requirement of automated support is exemplified by the difficulty of considering all relevant facts that are contained in the millions of documents available from PubMed. Semantic Web provides tools for sharing prior knowledge, while information retrieval and information extraction techniques enable its extraction from literature. Their combination makes prior knowledge available for computational analysis and inference. While some tools provide complete solutions that limit the control over the modeling and extraction processes, we seek a methodology that supports control by the experimenter over these critical processes. Results: We describe progress towards automated support for the generation of biomolecular hypotheses. Semantic Web technologies are used to structure and store knowledge, while a workflow extracts knowledge from text. We designed minimal proto-ontologies in OWL for capturing different aspects of a text mining experiment: the biological hypothesis, text and documents, text mining, and workflow provenance. The models fit a methodology that allows focus on the requirements of a single experiment while supporting reuse and posterior analysis of extracted knowledge from multiple experiments. Our workflow is composed of services from the 'Adaptive Information Disclosure Application' (AIDA) toolkit as well as a few others. The output is a semantic model with putative biological relations, with each relation linked to the corresponding evidence. Conclusion: We demonstrated a 'do-it-yourself' approach for structuring and extracting knowledge in the context of experimental research on biomolecular mechanisms. The methodology can be used to bootstrap the construction of semantically rich biological models using the results of knowledge extraction processes. Models specific to particular experiments can be constructed that, in turn, link with other semantic models, creating a web of knowledge that spans experiments. Mapping mechanisms can link to other knowledge resources such as OBO ontologies or SKOS vocabularies. AIDA Web Services can be used to design personalized knowledge extraction procedures. In our example experiment, we found three proteins (NF-Kappa B, p21, and Bax) potentially playing a role in the interplay between nutrients and epigenetic gene regulation