Overcompensation and population cycles in an ungulate.

Although theoretical studies show that overcompensatory density-dependent mechanisms can potentially generate regular or chaotic fluctuations in animal numbers, the majority of realistic single-species models of invertebrate populations are not overcompensatory enough to cause sustained population cycles. The possibility that overcompensation may generate cycles or chaos in vertebrate populations has seldom been considered. Here we show that highly overcompensatng density-dependent mortality can generate recurrent population crashes consistent with those observed in a naturally limited population of Soay sheep. The observed interval of three or more years between crashes points to sharp 'focusing' of mortality over a narrow range of population density.     

On the limitations of comparing mean square forecast errors

Linear models are invariant under non-singular, scale-preserving linear transformations, whereas mean square forecast errors (MSFEs) are not. Different rankings may result across models or methods from choosing alternative yet isomorphic representations of a process. One approach can dominate others for comparisons in levels, yet lose to another for differences, to a second for cointegrating vectors and to a third for combinations of variables. The potential for switches in ranking is related to criticisms of the inadequacy of MSFE against encompassing criteria, which are invariant under linear transforms and entail MSFE dominance. An invariant evaluation criterion which avoids misleading outcomes is examined in a Monte Carlo study of forecasting methods.     

DNA fingerprinting transforms the art of cell authentication.

The increasing diversity of new cell cultures is seriously stretching the capabilities of traditional methods of identification. DNA fingerprinting is set to play an important role in increasing confidence in the authenticity of cultures in research and industry.     

Prediction of the structure of a receptor-protein complex using a binary docking method.

To validate procedures of rational drug design, it is important to develop computational methods that predict binding sites between a protein and a ligand molecule. Many small molecules have been tested using such programs, but examination of protein-protein and peptide-protein interactions has been sparse. We were able to test such applications once the structures of both the maltose-binding protein (MBP) and the ligand-binding domain of the aspartate receptor, which binds MBP, became available. Here we predict the binding site of MBP to its receptor using a 'binary docking' technique in which two MBP octapeptide sequences containing mutations that eliminate maltose chemotaxis are independently docked to the receptor. The peptides in the docked solutions superimpose on their original positions in the structure of MBP and allow the formation of an MBP-receptor complex. The consistency of the computational and biological results supports this approach for predicting protein-protein and peptide-protein interactions.     

Targeted disruption of the mouse transforming growth factor-beta 1 gene results in multifocal inflammatory disease.

Transforming growth factor-beta 1 (TGF-beta 1) is a multifunctional growth factor that has profound regulatory effects on many developmental and physiological processes. Disruption of the TGF-beta 1 gene by homologous recombination in murine embryonic stem cells enables mice to be generated that carry the disrupted allele. Animals homozygous for the mutated TGF-beta 1 allele show no gross developmental abnormalities, but about 20 days after birth they succumb to a wasting syndrome accompanied by a multifocal, mixed inflammatory cell response and tissue necrosis, leading to organ failure and death. TGF-beta 1-deficient mice may be valuable models for human immune and inflammatory disorders, including autoimmune diseases, transplant rejection and graft versus host reactions.