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  • 06 Nov 2024 8:27 PM | Publications Team (Administrator)

    …where we talk about a paper studying who and when we should vaccinate.

    After completing a DPhil in Statistics from the University of Oxford, focussing in epidemiology and phylogenetics, Matt now works as a data scientist for Italian football club Como 1907.

    Matt was awarded the Lee A. Segel Prize for Best Student Paper published inThe Bulletin of Mathematical Biology for his paper Asymptotic Analysis of Optimal Vaccination Policies.

    Join us to learn more about how this paper can help health professionals better assess the best way to distribute vaccines.

    Find out more about Matt and his work on Linkedin:
    linkedin.com/in/matthew-penn-732551232/



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  • 30 Oct 2024 2:18 PM | Publications Team (Administrator)

    …where we talk parasites, motorbikes, and digital twins.

    Professor Reinhard Laubenbacher is: the Director of Laboratory for Systems Medicine at the University of Florida, an AAAS fellow (American Association for the Advancement of Science), and a scientist interested in using math to understand human disease and more specifically fungal infections in the lungs. When not at work, Reinhard and his wife enjoy motorbiking everywhere from the swamps of Florida, to the plains of Patagonia.

    Find out more about Reinhard’s work on the following websites:

    https://systemsmedicine.pulmonary.medicine.ufl.edu/

    https://systemsmedicine.pulmonary.medicine.ufl.edu/profile/laubenbacher-reinhard/




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  • 23 Oct 2024 5:49 PM | Publications Team (Administrator)

    Harnessing flex point symmetry to estimate logistic tumor population growth

    by Stefano Pasetto, Isha Harshe, Renee Brady-Nicholls, Robert A. Gatenby, Heiko Enderling

    Read the paper

    Tumor growth dynamics are well-described mathematically by the S-shaped logistic function. Initially exponential growth decelerates as the tumor approaches its carrying capacity – the maximum tumor burden that can be sustained by the local and systemic (micro-)environment. The volume-to-carrying capacity ratio is a major determinant of response to (radio-)therapy; therefore, it is of high importance to estimate the carrying capacity from limited tumor volume measurements. The symmetry around the logistic growth flex point can be used to introduce ghost points symmetric to observed data points to double the available data to calibrate model parameters for an individual patient. With this approach, fewer data points are necessary to identify patient-specific carrying capacities, thereby potentiating shorter times to treatment decisions.





  • 18 Oct 2024 3:53 PM | Publications Team (Administrator)

    Relational Persistent Homology for Multispecies Data with Application to the Tumor Microenvironment

    by Bernadette J. Stolz, Jagdeep Dhesi, Joshua A. Bull, Heather A. Harrington, Helen M. Byrne, Iris H. R. Yoon

    Read the paper

    State-of-the-art data is exquisite in detail, often containing information on multiple species, e.g. cell types in imaging data. However, there are very few techniques equipped to analyse and quantify relations in such data. The paper by Stolz, Dhesi et al. proposes two topological approaches for multispecies data that can encode relations in spatial data. The authors showcase the methods on synthetic data of the tumour microenvironment which models the behaviour and interactions between tumour cells, macrophage subtypes, necrotic cells, and blood vessels. They demonstrate that relational topological features can extract biological insight, including dominant immune cell phenotype and parameter regimes of the data-generating model.


    Relational persistent homology encodes spatial relations in multispecies data. We use synthetic images of the tumour microenvironment generated by an agent-based model as input to two different topological methods for encoding relations: Dowker persistent homology (top row) and multispecies witness persistent homology (bottom row). The topological features that we extract can classify the synthetic images according to dominant immune cell type and cluster qualitative behaviours of the model.


  • 09 Oct 2024 3:13 PM | Publications Team (Administrator)

    Assessing the Role of Patient Generation Techniques in Virtual Clinical Trial Outcomes

    by Jana L. Gevertz and Joanna R. Wares

    Read the paper

    Virtual clinical trials (VCTs) are a tool for understanding heterogeneous treatment responses. A number of techniques have been proposed to determine the set of model parametrizations ("virtual patients") that get included in a VCT. There is, however, no standard way to set the parameter prior distributions and to choose the criteria for including or excluding a parametrization sampled from the priors in the plausible population. In this work, we rigorously quantify the impact that VCT design choices have in a controlled setting using simulated patient data and a toy mathematical model. Our study provides a foundational understanding of how these choices influence the heterogeneity of virtual populations, and the predictions of a VCT.


    Schematic of two methods for the generation of plausible patients for a virtual clinical trial.


  • 01 Oct 2024 11:21 AM | Publications Team (Administrator)

    ...where we talk about infectious diseases, mentorship and mathematical tattoos.

    Professor Stacey Smith? is an infectious disease modeler who appreciates the real world impacts that math biology can have. She leads educational and mentorship programming at the SMB and apparently never says no to anything SMB related. We caught Stacey at SMB 2024 in South Korea to talk about her research, life-changing transitions, and being a Whovian. 

    Check out Stacey’s website for science, articles and Sci-Fi nerdiness: mysite.science.uottawa.ca/rsmith43/

    And for those curious about the tattoo, read more about the Mandlebrot set: wikipedia.org/wiki/Mandelbrot_set



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  • 26 Sep 2024 11:28 AM | Publications Team (Administrator)

    …where we talk all things math bio at the annual meeting.

    Science isn’t complete until it’s communicated, and what better place to do this than a scientific conference. This year, more than a thousand scientists were lucky enough to attend the SMB meeting in Seoul in Korea. This special episode gives a brief preview of some of the exciting research being done, as well as the people doing the work. Join us to hear from: 

    • Fred Adler - Professor at the University of Utah, Utah, US 
    • Kit Gallagher - Doctoral student at the University of Oxford, US & Moffitt Cancer Center, Florida, US
    • Megan Greischer - Assistant Professor at Cornell University, New York, US
    • Jona Kayser - Group leader at the Max Planck Institute for Physics and Medicine, Erlangen, Germany
    • Bo-Moon Kim - Doctoral student at Kyoto University, Kyoto, Japan
    • Breanne Sparta - Postdoctoral Researcher at UCLA, Los Angeles, US
    • Rossana Vermiglio - Full professor at the University of Udine, Udine, Italy.

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  • 19 Sep 2024 5:00 AM | Publications Team (Administrator)

    Statistical Mobility of Multicellular Colonies of Flagellated Swimming Cells

    by Yonatan Ashenafi and Peter R. Kramer

    Read the paper

    Eukaryotic cells, such as protozoa and sperm, use flagella—whip-like structures—for movement, helping them navigate, find food, interact, and evade predators. Researchers study flagellar propulsion through fluid dynamics and cellular responses. Recently, attention has shifted to multicellular colonies, where each cell has its own flagellum. In these colonies, misaligned flagella can cause unique movements, like rotating or spiraling. This paper presents a mathematical model to predict how flagellar behavior and colony structure affect movement, offering insights into the emergence of functional multicellularity.


    Time-lapse composite schematic of a circular colony's planar motion. The colony consists of a dozen flagellated cells.


  • 12 Sep 2024 10:20 AM | Publications Team (Administrator)

    Relaxation and Noise-Driven Oscillations in a Model of Mitotic Spindle Dynamics

    by Dionn Hargreaves, Sarah Woolner, and Oliver E. Jensen

    Read the paper

    Cell division orientation is controlled by the mitotic spindle, which dynamically positions itself to segregate chromosomes. Often, spindle positioning shows noisy, non-linear oscillations, observed here in dividing embryonic epithelial cells. These oscillations are thought to result from molecular motors that randomly attach, walk along, and detach from spindle microtubules. Prior models predict 1D spindle oscillations, but the effects of noise and nonlinearity remain underexplored. We demonstrate that relaxation oscillations emerge when pulling dominates restoring forces provided by flexible microtubules. Stochastic simulations and analysis reveal noise-induced oscillations, offering new insights into oscillation mechanisms.


    Force generators (molecular motors) attach, walk along, and detach from microtubules to dynamically position the spindle pole, to give rise to noise-induced oscillations.

  • 05 Sep 2024 10:11 AM | Publications Team (Administrator)

    Sara Loo (Johns Hopkins University), Burcu Gürbüz (Johannes Gutenberg-University Mainz), Thomas Woolley (Cardiff University), and Olivia Chu (Bryn Mawr College).

    1. News - updates from: 

    2. People - Interview with new editor Olivia Chu.
    3. Editorial - After a productive summer - About the SMB and ECMTB Conferences

    4. Featured Figures - SMB Poster prize winners

    To see the articles in this issue, click the links at the above items.

    Contributing content

    Issues of the newsletter are released four times per year in Spring, Summer, Autumn, and Winter. The newsletter serves the SMB community with news and updates, so please share it with your colleagues and contribute content to future issues.

    We welcome your submissions to expand the content of the newsletter.  The next issue will be released in late October, so if you would like to contribute, please send an email to the editors by the start of October 2023 to discuss how your content can be included. This could include summaries of relevant conferences that you have attended, suggestions for interviews, professional development opportunities etc. Please note that job advertisements should be sent to the SMB digest rather than to the newsletter.

    If you have any suggestions on how to improve the newsletter and would like to become more involved and/or contribute, please contact us at any time. We appreciate and welcome feedback and ideas from the community. The editors can be reached at newsletter@smb.org.

    We hope you enjoy this issue of the newsletter!

    Sara, Burcu, Thomas and Olivia

    Editors, SMB Newsletter

    Featured Figures

    By Olivia Chu

    In this issue, we feature the work of Luke Heirene, a graduate student at the University of Oxford, and Yuan Yin, a graduate student at the University of Oxford, who were both poster prize winners at this year’s SMB Annual Meeting. 

    We asked Luke to tell us a bit more about his work here:

    Immunotherapies have seen success in a variety of diseases, including cancer. An important class of immunotherapy are monoclonal antibodies (mAbs). Mabs can induce their anti-tumour effects in a variety of ways. For example, they can inhibit a tumour cell’s ability to downregulate the immune response against it as well as target and stimulate immune effector cells to kill the tumour cell. Regardless of a mAbs mechanism of action, core to their effect are their interactions with target antigens. Processes that alter the ability of a mAb to bind its target antigen, such as differences in binding affinity or antigen expression, will directly impact the resulting therapeutic effect.

    In our work, we use an ODE model of bivalent antibody-antigen binding to establish the key parameters that drive mAb potency and efficacy. We utilise a global parameter sensitivity analysis to establish the parameters that most affect antigen occupancy and bound antibody number, key drivers of mAb potency and efficacy, finding that the most important parameters change with antibody dose. Another key mAb-antigen interaction is the observed increase in binding affinity due to a mAb binding multiple antigens, termed the avidity effect. We use our model to predict antibody binding affinities and antigen expression numbers which result in a large avidity effect. Our results can be used to identify key parameters and interactions that can assist in the preclinical development of mAb therapeutics.



    Figure caption:

    (A) Schematic of model for bivalent mAb-antigen binding (Created with https://www.biorender.com)

    (B) Total order Sobol sensitivity analysis for antigen occupancy as antibody concentration varies on the x-axis.

    (C) Heatmaps displaying the avidity effect as measured by a change in the EC50 between a monovalent and bivalent antibody for different receptor expressions (r_tot) and binding affinities (K_D). The EC50 was calculated as the concentration at which half of the maximum bound antibody number was achieved.

    We asked Yuan to tell us a bit more about her work here:

    ‘Accurate stochastic simulation algorithm for multiscale models of infectious diseases’ by Yuan Yin (University of Oxford), Jennifer A. Flegg (University of Melbourne), Mark B. Flegg (Monash University)

    In the infectious disease literature, significant effort has been devoted to studying dynamics at a single scale. For example, compartmental models describing population-level dynamics are often formulated using differential equations. In cases where small numbers or noise play a crucial role, these differential equations are replaced with memoryless Markovian models, where discrete individuals can be members of a compartment and transition stochastically. Classic stochastic simulation algorithms, such as Gillespie's algorithm and the next reaction method, can be employed to simulate from these Markovian models exactly. The intricate coupling between models at different scales underscores the importance of multiscale modelling in infectious diseases.

    However, several computational challenges arise when the multiscale model becomes non-Markovian. In this study, we address these challenges by developing a novel exact stochastic simulation algorithm. We apply it to a showcase multiscale system where all individuals share the same deterministic within-host model while the population-level dynamics are governed by a stochastic formulation. We demonstrate that as long as the within-host information is simulated at a reasonable resolution, the novel algorithm we develop will always be accurate. Moreover, the novel algorithm we develop is general and can be easily applied to other multiscale models in (or outside) the realm of infectious diseases.

    Figure Caption:

    (a). Sample numerical solution of the within-host CC*V (target cell-limited) model. (b). Viral dynamics for 5 individuals with different calendar infection dates. (c). Propensity of infection per susceptible. (d). Population-level dynamics. Our algorithm (Algo. 2) is compared with an approximate time-driven algorithm (Algo. 1) and a golden-standard exact algorithm (GS). (e). Accuracy comparison between Algo. 1 and Algo. 2 given different population sizes. The markers denote the maximum time resolution where the relative errors are below 5%.


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