Data-Based Analysis of Winner-Loser Models of Hierarchy Formation in Animals

We review winner-loser models, the currently popular explanation for the occurrence of linear dominance hierarchies, via a three-part approach. (1) We isolate the two most significant components of the mathematical formulation of three of the most widely-cited models and rigorously evaluate the components’ predictions against data collected on hierarchy formation in groups of hens. (2) We evaluate the experimental support in the literature for the basic assumptions contained in winner-loser models. (3) We apply new techniques to the hen data to uncover several behavioral dynamics of hierarchy formation not previously described. The mathematical formulations of these models do not show satisfactory agreement with the hen data, and key model assumptions have either little or no conclusive support from experimental findings in the literature. In agreement with the latest experimental results concerning social cognition, the new behavioral dynamics of hierarchy formation discovered in the hen data suggest that members of groups are intensely aware both of their own interactions as well as interactions occurring among other members of their group. We suggest that more adequate models of hierarchy formation should be based upon behavioral dynamics that reflect more sophisticated levels of social cognition.     

Concentrating Toxoplasma gondii and Cyclospora cayetanensis from surface water and drinking water by continuous separation channel centrifugation

Aims:  To evaluate the effectiveness of continuous separation channel centrifugation for concentrating Toxoplasma gondii and Cyclospora cayetanensis from drinking water and environmental waters.
Methods and Results:  Ready-to-seed vials with known quantities of T. gondii and C. cayetanensis oocysts were prepared by flow cytometry. Oocysts were seeded at densities ranging from 1 to 1000 oocysts l⁻¹ into 10 to 100 l test volumes of finished drinking water, water with manipulated turbidity, and the source waters from nine drinking water utilities. Oocysts were recovered using continuous separation channel centrifugation and counted on membrane filters using epifluorescent microscopy. Recovery efficiencies of both parasites were ≥84% in 10 l volumes of drinking water. In source waters, recoveries ranged from 64% to 100%, with the lowest recoveries in the most turbid waters. Method precision was between 10% and 20% coefficient of variation.
Conclusion:  Toxoplasma gondii and C. cayetanensis are effectively concentrated from various water matrices by continuous separation channel centrifugation.
Significance and Impact of the Study:  Waterborne transmission of T. gondii and C. cayetanensis presents another challenge in producing clean drinking water and protecting public health. Detection of these parasites relies on effectively concentrating oocysts from ambient water, otherwise false negatives may result. Validation data specific to T. gondii and C. cayetanensis concentration methods are limited. Continuous separation channel centrifugation recovers oocysts with high efficiency and precision, the method attributes required to accurately assess the risk of waterborne transmission.     

Land crabs as key drivers in tropical coastal forest recruitment

Plant populations are regulated by a diverse assortment of abiotic and biotic factors that influence seed dispersal and viability, and seedling establishment and growth at the microsite. Rarely does one animal guild exert as significant an influence on different plant assemblages as land crabs. We review three tropical coastal ecosystems–mangroves, island maritime forests, and mainland coastal terrestrial forests–where land crabs directly influence forest composition by limiting tree establishment and recruitment. Land crabs differentially prey on seeds, propagules and seedlings along nutrient, chemical and physical environmental gradients. In all of these ecosystems, but especially mangroves, abiotic gradients are well studied, strong and influence plant species distributions. However, we suggest that crab predation has primacy over many of these environmental factors by acting as the first limiting factor of tropical tree recruitment to drive the potential structural and compositional organisation of coastal forests. We show that the influence of crabs varies relative to tidal gradient, shoreline distance, canopy position, time, season, tree species and fruiting periodicity. Crabs also facilitate forest growth and development through such activities as excavation of burrows, creation of soil mounds, aeration of soils, removal of leaf litter into burrows and creation of carbon-rich soil microhabitats. For all three systems, land crabs influence the distribution, density and size-class structure of tree populations. Indeed, crabs are among the major drivers of tree recruitment in tropical coastal forest ecosystems, and their conservation should be included in management plans of these forests.     

Surface plasmon resonance for high-throughput ligand screening of membrane-bound proteins

Technologies based on surface plasmon resonance (SPR) have allowed rapid, label-free characterization of protein-protein and protein-small molecule interactions. SPR has become the gold standard in industrial and academic settings, in which the interaction between a pair of soluble binding partners is characterized in detail or a library of molecules is screened for binding against a single soluble protein. In spite of these successes, SPR is only beginning to be adapted to the needs of membrane-bound proteins which are difficult to study in situ but represent promising targets for drug and biomarker development. Existing technologies, such as BIAcoreTM, have been adapted for membrane protein analysis by building supported lipid layers or capturing lipid vesicles on existing chips. Newer technologies, still in development, will allow membrane proteins to be presented in native or near-native formats. These include SPR nanopore arrays, in which lipid bilayers containing membrane proteins stably span small pores that are addressable from both sides of the bilayer. Here, we discuss current SPR instrumentation and the potential for SPR nanopore arrays to enable quantitative, high-throughput screening of G protein coupled receptor ligands and applications in basic cellular biology.     

Context dependent neuroprotective properties of prion protein (PrP)

Although it has been known for more than twenty years that an aberrant conformation of the prion protein (PrP) is the causative agent in prion diseases, the role of PrP in normal biology is undetermined. Numerous studies have suggested a protective function for PrP, including protection from ischemic and excitotoxic lesions and several apoptotic insults. On the other hand, many observations have suggested the contrary, linking changes in PrP localization or domain structure—independent of infectious prion conformation—to severe neuronal damage. Surprisingly, a recent report suggests that PrP is a receptor for toxic oligomeric species of a-β, a pathogenic fragment of the amyloid precursor protein, and likely contributes to disease pathogenesis of Alzheimer disease. We sought to access the role of PrP in diverse neurological disorders. First, we confirmed that PrP confers protection against ischemic damage using an acute stroke model, a well characterized association. After ischemic insult, PrP knockouts had dramatically increased infarct volumes and decreased behavioral performance compared to controls. To examine the potential of PrP''s neuroprotective or neurotoxic properties in the context of other pathologies, we deleted PrP from several transgenic models of neurodegenerative disease. Deletion of PrP did not substantially alter the disease phenotypes of mouse models of Parkinson disease or tauopathy. Deletion of PrP in one of two Huntington disease models tested, R6/2, modestly slowed motor deterioration as measured on an accelerating rotarod but otherwise did not alter other major features of the disease. Finally, transgenic overexpression of PrP did not exacerbate the Huntington motor phenotype. These results suggest that PrP has a context-dependent neuroprotective function and does not broadly contribute to the disease models tested herein.Key words: neurodegeneration, protein misfolding, PrP, home cage, stroke     

Effective degree network disease models

An effective degree approach to modeling the spread of infectious diseases on a network is introduced and applied to a disease that confers no immunity (a Susceptible-Infectious-Susceptible model, abbreviated as SIS) and to a disease that confers permanent immunity (a Susceptible-Infectious-Recovered model, abbreviated as SIR). Each model is formulated as a large system of ordinary differential equations that keeps track of the number of susceptible and infectious neighbors of an individual. From numerical simulations, these effective degree models are found to be in excellent agreement with the corresponding stochastic processes of the network on a random graph, in that they capture the initial exponential growth rates, the endemic equilibrium of an invading disease for the SIS model, and the epidemic peak for the SIR model. For each of these effective degree models, a formula for the disease threshold condition is derived. The threshold parameter for the SIS model is shown to be larger than that derived from percolation theory for a model with the same disease and network parameters, and consequently a disease may be able to invade with lower transmission than predicted by percolation theory. For the SIR model, the threshold condition is equal to that predicted by percolation theory. Thus unlike the classical homogeneous mixing disease models, the SIS and SIR effective degree models have different disease threshold conditions.     

Isocitrate dehydrogenase 1 R132C mutation occurs exclusively in microsatellite stable colorectal cancers with the CpG island methylator phenotype

The CpG Island Methylator Phenotype (CIMP) is fundamental to an important subset of colorectal cancer; however, its cause is unknown. CIMP is associated with microsatellite instability but is also found in BRAF mutant microsatellite stable cancers that are associated with poor prognosis. The isocitrate dehydrogenase 1 (IDH1) gene causes CIMP in glioma due to an activating mutation that produces the 2-hydroxyglutarate oncometabolite. We therefore examined IDH1 alteration as a potential cause of CIMP in colorectal cancer. The IDH1 mutational hotspot was screened in 86 CIMP-positive and 80 CIMP-negative cancers. The entire coding sequence was examined in 81 CIMP-positive colorectal cancers. Forty-seven cancers varying by CIMP-status and IDH1 mutation status were examined using Illumina 450K DNA methylation microarrays. The R132C IDH1 mutation was detected in 4/166 cancers. All IDH1 mutations were in CIMP cancers that were BRAF mutant and microsatellite stable (4/45, 8.9%). Unsupervised hierarchical cluster analysis identified an IDH1 mutation-like methylation signature in approximately half of the CIMP-positive cancers. IDH1 mutation appears to cause CIMP in a small proportion of BRAF mutant, microsatellite stable colorectal cancers. This study provides a precedent that a single gene mutation may cause CIMP in colorectal cancer, and that this will be associated with a specific epigenetic signature and clinicopathological features.     

Mathematical and computational modeling in biology at multiple scales

A variety of topics are reviewed in the area of mathematical and computational modeling in biology, covering the range of scales from populations of organisms to electrons in atoms. The use of maximum entropy as an inference tool in the fields of biology and drug discovery is discussed. Mathematical and computational methods and models in the areas of epidemiology, cell physiology and cancer are surveyed. The technique of molecular dynamics is covered, with special attention to force fields for protein simulations and methods for the calculation of solvation free energies. The utility of quantum mechanical methods in biophysical and biochemical modeling is explored. The field of computational enzymology is examined.