Understanding tissue morphology: model repurposing using the CoSMoS process

We present CoSMoS as a way of structuring thinking on how to reuse parts of an existing model and simulation in a new model and its implementation. CoSMoS provides a lens through which to consider, post-implementation, the assumptions made during the design and implementation of a software simulation of physical interactions in the formation of vascular structures from endothelial cells. We show how the abstract physical model and its software implementation can be adapted for a different problem: the growth of cancer cells under varying environmental perturbations. We identify the changes that must be made to adapt the model to its new context, along with the gaps in our knowledge of the domain that must be filled by wet-lab experimentation when recalibrating the model. Through parameter exploration, we identify the parameters that are critical to the dynamic physical structure of the modelled tissue, and we calibrate these parameters using a series of in vitro experiments. Drawing inspiration from the CoSMoS project structure, we maintain confidence in the repurposed model, and achieve a satisfactory degree of model reuse within our in silico experimental system

Disease effects on reproduction can cause population cycles in seasonal environments

Recent studies of rodent populations have demonstrated that certain parasites can cause juveniles to delay maturation until the next reproductive season. Furthermore, a variety of parasites may share the same host, and evidence is beginning to accumulate showing nonindependent effects of different infections.We investigated the consequences for host population dynamics of a disease-induced period of no reproduction, and a chronic reduction in fecundity following recovery from infection (such as may be induced by secondary infections) using a modified SIR (susceptible, infected, recovered) model. We also included a seasonally varying birth rate as recent studies have demonstrated that seasonally varying parameters can have important effects on long-term host–parasite dynamics. We investigated the model predictions using parameters derived from five different cyclic rodent populations.Delayed and reduced fecundity following recovery from infection have no effect on the ability of the disease to regulate the host population in the model as they have no effect on the basic reproductive rate. However, these factors can influence the long-term dynamics including whether or not they exhibit multiyear cycles.The model predicts disease-induced multiyear cycles for a wide range of realistic parameter values. Host populations that recover relatively slowly following a disease-induced population crash are more likely to show multiyear cycles. Diseases for which the period of infection is brief, but full recovery of reproductive function is relatively slow, could generate large amplitude multiyear cycles of several years in length. Chronically reduced fecundity following recovery can also induce multiyear cycles, in support of previous theoretical studies.When parameterized for cowpox virus in the cyclic field vole populations (Microtus agrestis) of Kielder Forest (northern England), the model predicts that the disease must chronically reduce host fecundity by more than 70%, following recovery from infection, for it to induce multiyear cycles. When the model predicts quasi-periodic multiyear cycles it also predicts that seroprevalence and the effective date of onset of the reproductive season are delayed density-dependent, two phenomena that have been recorded in the field

Calcareous nannofossils across the Eocene-Oligocene transition: Preservation signals and biostratigraphic remarks from ODP Site 1209 (NW Pacific, Shatsky Rise) and IODP Hole U1411B (NW Atlantic Ocean, Newfoundland Ridge)

This work provides a detailed biostratigraphic correlation through the Eocene-Oligocene Transition (EOT), based on an integrated stratigraphic approach and the study of calcareous nannofossils, between two disparate sites, one in the NW Atlantic (IODP Hole U1411B) and one in the NW Pacific (ODP Site 1209). The precise site-to-site correlation provided by these data allows for a comparison of carbonate preservation across the EOT including identification of the main post-depositional processes that impact the calcareous nannofossil ooze at Site 1209. The main aim of this work is to understand the extent to which the bulk δ18O and δ13C records and their sources (mainly calcareous nannofossils) are altered by diagenesis. Our detailed SEM study highlights some differences before, during and after the EOT, suggesting local diagenetic dynamics. At Site 1209, a distinctive change, both in nannofossil assemblage composition and preservation state, is observed from the pre-EOT phase to the Late Eocene Event (LEE), with a shift in the dominant process from dissolution to recrystallisation. Surprisingly, despite the overall poor preservation, only the interval between 141 and 142.4 (adj. rmcd) was compromised in term of isotopic values and assemblage diversity and abundance. This interval, recorded in the upper Eocene, was characterized by severe dissolution, concomitant with deposition of secondary calcite on solution-resistant forms. Diagenetic processes have strongly biased the δ18O isotopic signal, resulting in a positive oxygen isotope anomaly through the upper Eocene that is difficult to reconcile with other published trends. For the remaining time intervals, diagenesis seems not to have altered the bulk δ18O profile, which closely resembles that of other sites across the world, and is particularly consistent with other data from the Pacific Ocean. In summary, the impact of diagenesis on nannofossil preservation even if clearly visible both in SEM and optical microscope observations does not always cause a pervasive alteration of the primary isotopic signal and can instead provide important clues on local depositional dynamics

Engineering simulations for cancer systems biology

Computer simulation can be used to inform in vivo and in vitro experimentation, enabling rapid, low-cost hypothesis generation and directing experimental design in order to test those hypotheses. In this way, in silico models become a scientific instrument for investigation, and so should be developed to high standards, be carefully calibrated and their findings presented in such that they may be reproduced. Here, we outline a framework that supports developing simulations as scientific instruments, and we select cancer systems biology as an exemplar domain, with a particular focus on cellular signalling models. We consider the challenges of lack of data, incomplete knowledge and modelling in the context of a rapidly changing knowledge base. Our framework comprises a process to clearly separate scientific and engineering concerns in model and simulation development, and an argumentation approach to documenting models for rigorous way of recording assumptions and knowledge gaps. We propose interactive, dynamic visualisation tools to enable the biological community to interact with cellular signalling models directly for experimental design. There is a mismatch in scale between these cellular models and tissue structures that are affected by tumours, and bridging this gap requires substantial computational resource. We present concurrent programming as a technology to link scales without losing important details through model simplification. We discuss the value of combining this technology, interactive visualisation, argumentation and model separation to support development of multi-scale models that represent biologically plausible cells arranged in biologically plausible structures that model cell behaviour, interactions and response to therapeutic interventions

Creative Experiments Using a System for Learning High-level Performance Structure in Ableton Live

(Abstract to follow

Modelling fungal colonies and communities:challenges and opportunities

This contribution, based on a Special Interest Group session held during IMC9, focuses on physiological based models of filamentous fungal colony growth and interactions. Fungi are known to be an important component of ecosystems, in terms of colony dynamics and interactions within and between trophic levels. We outline some of the essential components necessary to develop a fungal ecology: a mechanistic model of fungal colony growth and interactions, where observed behaviour can be linked to underlying function; a model of how fungi can cooperate at larger scales; and novel techniques for both exploring quantitatively the scales at which fungi operate; and addressing the computational challenges arising from this highly detailed quantification. We also propose a novel application area for fungi which may provide alternate routes for supporting scientific study of colony behaviour. This synthesis offers new potential to explore fungal community dynamics and the impact on ecosystem functioning

Robot narratives

There is evidence that humans understand how the world goes through narrative. We discuss what it might mean for embodied robots to understand the world, and communicate that understanding, in a similar manner. We suggest an architecture for adding narrative to robot cognition, and an experimental scenario for investigating the narrative hypothesis in a combination of physical and simulated robots

Mimoperadectes, A New Marsupial, and Worlandia, A New Dermopteran, from the Lower Part of the Willwood Formation (Early Eocene), Bighorn Basin, Wyoming

89-104http://deepblue.lib.umich.edu/bitstream/2027.42/48494/2/ID345.pd