Monday, June 14 at 7:45pm (PDT)
Tuesday, June 15 at 03:45am (BST)
Tuesday, June 15 11:45am (KST)


Diverse quantitative approaches integrating data and modelling in development and medicine

Organized by: Adriana Dawes (Ohio State University, USA), Sungrim Seirin-Lee (Hiroshima University, Japan)
Note: this minisymposia has multiple sessions. The second session is MS03-CDEV.

  • Adriana Dawes (Ohio State University, USA)
    "The causes and consequences of centrosome asymmetry during development"
  • Asymmetric cell division, where daughter cells inherit unequal amounts of specific factors, is critical for development and cell fate specification, and is implicated in disease processes such as tumour growth. In polarized cells, where specific factors are segregated to opposite ends of the cell as seen in early embryos of the nematode worm C. elegans, asymmetric cell division occurs as a result of dynein-mediated centrosome positioning along the polarity axis. Using a combination of stochastic and continuum models with experimental validation, we show that centrosome asymmetry is critical for centrosome positioning in the early C. elegans embryo, and that this asymmetry arises from differential recruitment of proteins to centrosomes during their maturation process.
  • Susanne Rafelski (Allen Institute for Cell Science, USA)
    "Decoding the variance in intracellular organization of human stem cells"
  • The Allen Institute for Cell Science aims to understand the principles by which human induced pluripotent stem cells (hiPSCs) establish and maintain robust dynamic localization of subcellular structures. Initial steps aim to determine the full range of natural variation in intracellular organization in hiPSCs under normal, unperturbed conditions. We used 25 of the endogenous fluorescently tagged hiPSC lines in the Allen Cell Collection (, each expressing a monoallelic EGFP-tagged protein labeling a particular organelle or structure. We imaged thousands of cells at high resolution in 3D for each structure and developed segmentation algorithms and workflows for quantitative analyses. To measure variation in cell and nuclear shapes, we fit 3D segmented masks using spherical harmonic functions, and then performed a principal component analysis of the spherical harmonic coefficients. We found that the largest axes of shape variation corresponds to 1) cell height, due to differences in cell packing colonies, and 2) cell volume, representing cell growth through the cell cycle. We performed a survey analysis of size scaling and found that structures differ in the strength of their scaling with cell size and nuclear size. To explore variation in intracellular organization, we parameterized the cytoplasm and nucleoplasm via spherical harmonics to generate maps for each structure in each cell in 3D. Analysis of these maps allowed us to quantify and rank how stereotyped the locations for each of these structures are and further to cluster structures via correlations in their location relative to each other over different spatial scales. This systematic approach has enabled us to quantify how subcellular organelle organization varies with changes in cell shape in an integrated fashion across 25 EGFP-tagged subcellular structures.
  • Naoki Honda (, Japan)
    "Data-driven hierarchical modeling of collective cell migration"
  • Collective cell migration is a fundamental process of development. It has been known that cell migration within an epithelial sheet is oriented by traveling waves of ERK activation. However, its mechanism has remained elusive. To extract control roles in the epithelial sheet dynamics, we first developed mathematical models at the different hierarchical levels of individual cells and continuum, which can be seamlessly linked. Based on this hierarchical modeling, we mathematically predicted that migration velocity is directed by several mechano-chemical signals: cellular density, ERK activity, velocity field and their temporal and/or spatial derivatives. To test this model prediction, we live-imaged ERK activity during the collective cell migration with FRET-based biosensor. From the live imaging data, we quantified the time-series data corresponding to variables in the model. We then analyzed the time-series data with help of machine learning and then obtained a reverse-engineered model, which describes how the cells intracellularly process these mechano-chemical signals. We also confirmed that this model has an ability to forecast cell migration, hence showing validity of the model. By interpreting the reverse-engineered continuum model at the individual cellular level, we elucidated intercellular mechanical interaction is up-regulated by temporal derivative of ERK signal. Therefore, our data-driven hierarchical modeling approach is powerful to understand multicellular dynamics.
  • Hiroshi Suito (Tohoku University, Japan)
    "Patient-specific approaches to cardiovascular diseases"
  • In blood vessels with congenital heart diseases, characteristic flow structures are formed, in which pulsating flows affect strongly on wall shear stresses and energy dissipation patterns. In this talk, we present computational analyses for blood flows in patient-specific cases, through which we aim at understanding the relationships between differences in geometries and in energy dissipations. Our present targets include an aortic coarctation case and a Norwood surgery for hypoplastic left heart syndrome. These analyses yield deeper understandings in clinical medicine.

Collaboration and calibration: modelling with experimental and clinical data

Organized by: Adriana Zanca (The University of Melbourne, Australia), Jennifer Flegg (The University of Melbourne, Australia), Helen Byrne (University of Oxford, UK)
Note: this minisymposia has multiple sessions. The second session is MS03-IMMU.

  • Wafaa Mansoor (Murdoch University, Australia)
    "Modelling hydrogen clearance in the retina"
  • Two simple mathematical models of advection and diffusion of hydrogen within the retina are discussed to assist in interpretation of the ’hydrogen clearance technique’ that is used to estimate blood flow. The first model assumes the retina consists of three, well-mixed layers with different thickness, two-dimensional model consisting of three regions that represent the layers in the retina. Diffusion between the layers and leakage through the outer edges are considered. Solutions to the governing equations are obtained by employing Fourier series and finite difference methods for the two models, respectively. The effect of important parameters on the hydrogen concentration is examined and discussed. The results contribute to understanding the dispersal of hydrogen in the retina and in particular the effect of flow in the vascular retina. It is shown that the predominant features of the process are captured by the simpler model.
  • Vijayalakshmi Srinivasan (Auckland Bioengineering Institute, New Zealand)
    "3D analysis of Human placental cotyledon: a step ahead to understand feto-placental vasculature"
  • The human placenta has extensive branching villus structure, which contains a branching network of fetal blood vessels that are essential for efficient exchange of nutrients from mother to fetus. Reduced vascular density and branching have been linked to functional placental impairments, such as fetal growth restriction (FGR) where the baby’s growth rate becomes dangerously reduced. Currently, we lack clear understanding of origins of FGR for early diagnosis and treatment. Computational models that mimic the structure and function of the feto-placental vasculature have proved useful in predicting the consequences of perturbations to these structures in FGR. However, they have been limited in their anatomical fidelity at the meso-scale (the primary site of resistance), due to challenges in imaging the placenta. Here, we present our approach to simulating feto-placental vascular function in the placenta as a whole, which aims to accurately incorporate structural detail regarding branching properties of the complex vascular tree. We then present new data regarding the complexity of the feto-placental vasculature at the cotyledon (functional unit) scale, and show how mathematical models representing the cotyledon as a branching network of vessels can be used to interrogate function across spatial scales relevant to the key sites of feto-placental vascular resistance.
  • Yuhuang Wu (Kirby Institute, Australia)
    "Predicting the composition of the HIV / SIV Reservoir and Rebounding Virus"
  • Human Immunodeficiency Virus (HIV) attacks human immune cells and new free virus is produced via infected cells. Even with a successful treatment of HIV, the population of infected cells does not go extinct. Instead, a number of infected cells stay in an inactive state and once treatment is stopped, reactivation of infected cells may produce virus again. To date, it is still unclear when and how these inactive infected cells (reservoir) are formed. In this work, we try to distinguish whether different virus produced throughout the course of infection contributes equally to the formation of reservoir, or virus strains produced over a certain time period are more important to reservoir formation. Furthermore, we explore how the composition of replicating virus relates to the composition of the reservoir. Additionally, we look at if the reservoir composition determines the production of virus when the treatment is stopped. In this talk, we use both mathematical modelling and statistical analysis, applied to experimental data from an animal study, to show the relationship between the early viral dynamics and the reservoir composition as well as the recrudescent virus. We find dominant viral strains present prior to treatment are more likely to reactivate after cessation of treatment.
  • Claire Miller (University of Amsterdam, Netherlands)
    "In silico clinical trials for acute ischemic stroke"
  • The concept of in silico trials is gaining increasing attention in medical research. The end goal of these trials is to refine, reduce the cost of, and partially replace in vivo animal studies and human clinical trials. In our project, INSIST, we are developing in silico trials for acute ischemic stroke (AIS): the occlusion of an artery in the brain. The current standard of care for AIS is thrombolysis (drug) and/or thrombectomy (surgical) intervention. Modelling AIS requires the modelling of the stroke onset, treatment, and resulting injury. This is done by linking models for blood flow through the arteries, blood perfusion in the brain, the two treatment approaches, and tissue injury. It is also necessary to be able to produce large numbers of patients to run these models on; provide trial outcomes that are clinically relevant; and a trial framework that can be practically compared to current traditional clinical trials. In this talk I will discuss the setup of the INSIST in silico trials, how we connect the different models to predict treatment and patient outcome, and the methods we have used to generate populations of virtual patients using clinical data. Additionally I will discuss how the approaches used facilitate the translation of the trial outcomes to a clinical setting.

Mathematical Modelling that Supported Australia and New Zealand’s COVID-19 Responses

Organized by: James Walker (The University of Melbourne, Australia)

  • Rebecca Chisholm (La Trobe University, Australia)
    "Modelling response strategies for potential COVID-19 outbreaks in remote Australian Aboriginal communities"
  • Remote Australian Aboriginal and Torres Strait Islander communities have potential to be severely impacted by COVID-19. Accordingly, the Aboriginal and Torres Strait Islander Advisory Group on COVID-19, co-chaired by the Australian Government Department of Health and the National Aboriginal Community Controlled Health Organisation led the development of specific guidance to support initial response to identified infections in these settings, and commissioned modelling to help inform this advice. We developed an individual-based model to represent remote communities of different sizes to consider alternative public health responses following the silent introduction of infection. The model included data-informed representation of extended family connections spanning multiple, often crowded dwellings, which are a key driver of infection spread. A range of strategies for case finding, quarantining of contacts, testing, and lockdown were examined. Our model suggests a SARS-CoV-2 outbreak will develop and spread rapidly in remote communities if an undetected infection is introduced. Prompt case detection with quarantining of extended-household contacts and a 14-day lockdown for all other residents, combined with exit testing for all, is the strategy most likely to achieve definitive initial containment.
  • Emily Harvey (ME Research & Te Pūnaha Matatini, Aotearoa New Zealand)
    "Modelling COVID-19 in Aotearoa NZ on a bipartite contact network of 5 million individuals"
  • Many of the models used for rapid policy advice during the COVID-19 pandemic have relied on simplifying assumptions about the homogeneity of individuals, however we know that risk factors for exposure, transmission, and poor outcomes are not evenly distributed across society. We have built a stochastic model of infection dynamics that runs on an empirically derived bipartite contact network of the ~5 million people in Aotearoa New Zealand. The contact network includes spatial information, and individual demographic information, along with distinct ‘transmission contexts’ including dwellings, workplaces, and schools, built from linked data in the Statistics NZ Integrated Data Infrastructure. This network is the underlying structure on which we run a stochastic contagion process to model the spread of COVID 19, which includes explicit representation of the testing and contact tracing processes. We have used this model to estimate the probable outcomes of COVID outbreaks in Aotearoa and to evaluate the effect of non-pharmaceutical interventions including 'Alert Level' changes. In particular, we find that this heterogeneity (network structure) means that the effect of different interventions does not combine linearly.
  • Michael Plank (University of Canterbury, Aotearoa New Zealand)
    "Modelling the risk of re-introduction of COVID-19 from border arrivals"
  • In an attempt to maintain the elimination of COVID-19 in New Zealand, all international arrivals are required to spend 14 days in government-managed quarantine and to return a negative test result before being released. We model the testing, isolation and transmission of COVID-19 within quarantine facilities to estimate the risk of community outbreaks being seeded at the border. We use a simple branching process model for COVID-19 transmission that includes a time-dependent probability of a false-negative test result. We show that the combination of 14-day quarantine with two tests is highly effective in preventing an infectious case entering the community, provided there is no transmission within quarantine facilities. Shorter quarantine periods, or reliance on testing only with no quarantine, substantially increases the risk of an infectious case being released. We calculate the fraction of cases detected in the second week of their two-week stay and show that this may be a useful indicator of the likelihood of transmission occurring within quarantine facilities. Frontline staff working at the border risk exposure to infected individuals and this has the potential to lead to a community outbreak. We use the model to test surveillance strategies and evaluate the likely size of the outbreak at the time it is first detected. We conclude with some recommendations for managing the risk of potential future outbreaks originating from the border.
  • Freya Shearer (The University of Melbourne, Australia)
    "Supporting the Australian response to COVID-19 through model-based situational assessment"
  • A key element of epidemic decision-making is situational awareness — that is, knowing the current and potential future status of the epidemic. Outputs from mathematical and statistical models have provided enhanced situational awareness to the Australian government throughout the course of the COVID-19 pandemic. Our response to COVID-19 required the rapid development of new methodologies and data streams for situational assessment, particularly with respect to monitoring changes in population behaviour and estimating transmission risk in the absence of cases. In this talk, I will describe Australia’s situational awareness modelling program for COVID-19. I will provide an overview of the modelling outputs reported to key government decision-making committees on a weekly basis (at least) since April 2020. Further, I will describe how our methods and the structure of our reporting has evolved over time, in response to changing epidemiology and response priorities.

Hibernation and circadian rhythms: the differences and the possible interactions

Organized by: Shingo Gibo (RIKEN, Japan) and Gen Kurosawa (RIKEN, Japan)

  • Elena Gracheva (Yale School of Medicine, United States of America)
    "Neurophysiological adaptations to the unique lifestyle in mammalian hibernators"
  • Mammalian hibernation is fascinating. During a short period of time, hibernating animals undergo dramatic adaptive changes, including a reduction in heart and respiration rate and a decrease in core body temperature from 37°C (98.6°F) to 4°C (39°F), yet they do not experience cold-induced pain, and their organs continue to function despite being cold and deprived of oxygen for 8 month out of the year! Moreover, since these animals do not eat or drink during hibernation, they must rely solely on the management and utilization of their internal resources for long-term survival. How hibernators achieve such a remarkable physiological adaptation, remains unknown. We use hibernating 13-lined Ground squirrels (an obligatory hibernator) and Syrian hamsters (a non-obligatory hibernator), to tackle fundamental biological questions from perspectives unachievable using the standard animal models alone. Specifically, we are interested in studying molecular evolution of mammalian hibernation and cellular adaptations that these animals evolve in order to survive prolonged periods of hypothermia, water deprivation and starvation. We are also trying to pinpoint the molecular and physiological basis of hibernation induction. Comparative analysis of three rodent species—such as ground squirrels, hamsters and mice (non-hibernator)—at the behavioral, cellular and molecular levels, will help us to delineate the multitude of adaptations that hibernators evolved in order to survive harsh environment and as a result came to inhabit a wide geographical range.
  • Tanya Leise (Amherst College, United States of America)
    "Analysis of the Circadian Rhythms of Brown Bears During Winter Dormancy"
  • Applications of wavelet transforms and other methods will be demonstrated in the context of activity and body temperature records of brown bears under different entrained and free-running conditions, including during winter dormancy. Wavelet-based methods can be useful in quantifying properties of circadian rhythms, including period, phase, amplitude, quality of rhythms, and coherence between simultaneously recorded rhythms. I will also highlight the quite distinct types of information provided by discrete versus continuous wavelet transforms methods. In particular, the analysis indicates that the circadian system is functional in torpid bears even when housed in constant darkness and it continues to be responsive to phase-shifting effects of light.
  • Hsin-tzu Wang (The University of Tokyo, Japan)
    "Cold Ca2+ signaling for temperature compensation of circadian rhythms"
  • Reaction rates of almost all biochemical processes change with temperature. On the other hand, oscillation speed of the circadian clock remains nearly unchanged in a physiological range of temperatures, and this feature common to the circadian clocks is termed temperature compensation. In chemical biological screening, we found that inhibitor of Na+/Ca2+ exchanger (NCX) or Ca2+/calmodulin dependent protein kinase II (CaMKII) remarkably increased Q10 value of the period length of gene expression rhythms in mammalian fibroblasts. In response to temperature decrease, NCX elevates intracellular Ca2+ and activates CaMKII. Activated CaMKII accelerates transcriptional oscillations of clock genes, so that the period of circadian clock remains stable. Moreover, Ca2+ signal is also important for high-amplitude oscillation of the circadian rhythms, and CaMKII alleviates amplitude reduction by temperature decrease to prevent loss of cellular rhythmicity at low temperature. In mouse spontaneous behavioral rhythms, disruption of CaMKII activity caused significant decrease of the rhythmicity. Therefore, we propose that cold NCX-Ca2+-CaMKII signaling is a crucial regulator of the amplitude and the period length of the temperature-compensated circadian rhythms.
  • Shingo Gibo (RIKEN iTHEMS, Japan)
    "Waveform analysis reveals the mechanisms for circadian rhythms and hibernation"
  • Organisms have evolved many oscillatory systems such as circadian rhythms and hibernation. The waveforms of the biological oscillations are of various shapes. This may indicate that the various waveforms contain the important information for understanding the biological systems. In this talk, by analyzing waveform pattern, we theoretically consider (i) circadian clocks and (ii) hibernation. First, we study the robustness of circadian period to temperature. The circadian clocks consist of complex biochemical networks. Although most biochemical reactions accelerate with increasing temperature, the period of circadian clocks is stable to temperature changes. This phenomenon is called as “temperature compensation,” and the mechanism has been unclear. To understand the condition of temperature compensation, we analyzed a mathematical model for circadian clocks. Then, we found that the waveforms of gene-activity rhythms should become more non-sinusoidal when reactions become faster and simultaneously, the circadian period becomes longer or remains unchanged. From this result, we predict that the waveforms should be more distorted at higher temperature in order to achieve temperature compensated period. Next, we analyzed the temporal pattern of hibernation. Under cold and short photoperiodic conditions, Syrian hamsters enter hibernation spontaneously. During hibernation, their body temperature shows fluctuation between euthermia and hypothermia with a certain period of several days. It is called 'torpor-arousal cycle'. In this study, we analyzed the time-series of body temperature during hibernation by using generalized harmonic analysis. Then, we found that the period of torpor-arousal cycle gradually changes at hundred-days scale.