This week in MathOnco 188

Radiotherapy, physics-based modeling, resource competition, positive selection in healthy tissue, and more

“This week in Mathematical Oncology” — Nov. 18, 2021
> mathematical-oncology.org
From the editor:

This week’s edition includes topics radiotherapy, physics-based modeling, resource competition, positive selection in healthy tissue, and more.

Enjoy!

Jeffrey West
jeffrey.west@moffitt.org

  1. Dynamics-Adapted Radiotherapy Dose (DARD) for Head and Neck Cancer Radiotherapy Dose Personalization
    Mohammad U. Zahid, Abdallah S. R. Mohamed, Jimmy J. Caudell, Louis B. Harrison, Clifton D. Fuller, Eduardo G. Moros, Heiko Enderling

  2. The imperative of physics-based modeling and inverse theory in computational science
    Karen E. Willcox, Omar Ghattas & Patrick Heimbach

  3. Synonymous mutations reveal genome-wide levels of positive selection in healthy tissues
    Gladys Poon, Caroline Watson, Daniel Fisher, Jamie Blundell

  4. Positive interactions are common among culturable bacteria
    Jared Kehe, Anthony Ortiz, Anthony Kulesa, Jeff Gore, Paul Blainey, Jonathan Friedman

  5. The physics of higher-order interactions in complex systems
    Federico Battiston, Enrico Amico, Alain Barrat, Ginestra Bianconi, …, Micah M. Murray, Tiago P. Peixoto, Francesco Vaccarino, Giovanni Petri

  6. Effective Resource Competition Model for Species Coexistence
    Deepak Gupta, Stefano Garlaschi, Samir Suweis, Sandro Azaele, Amos Maritan

  7. Mathematical Modeling of Pancreatic Cancer Treatment with Cancer Stem Cells
    Tugba Akman Yildiz, Emek Kose, Samantha L. Elliott

  1. BayesDeBulk: A Flexible Bayesian Algorithm for the Deconvolution of Bulk Tumor Data
    Francesca Petralia, Anna P Calinawan, Song Feng, Sara JC Gosline, Pietro Pugliese, Michele Ceccarelli, Pei Wang

  2. Exploiting convergent evolution to derive a pan-cancer cisplatin sensitivity gene expression signature
    Jessica A. Scarborough, Steven A. Eschrich, Javier Torres-Roca, Andrew Dhawan, Jacob G. Scott

  3. Gattaca: Base pair resolution mutation tracking for somatic evolution studies using agent-based models
    Ryan O Schenck, Gabriel Brosula, Jeffrey West, Simon Leedham, Darryl Shibata, Alexander RA Anderson

  4. Mutational landscapes of normal breast during age and pregnancy determine cancer risk
    Biancastella Cereser, Neha Tabassum, Lisa Del Bel Belluz, Angela Yiu, Sladjana Zagorac, Cristian Miere, Benjamin Werner, Nina Moderau, Alicia Rose Jeffries-Jones, Justin Stebbing

  5. Non-reciprocal interactions promote diversity
    Riccardo Muolo, Timoteo Carletti

  1. The secret lives of cells — as never seen before
    Nature News Feature
    Diana Kwon: “Cutting-edge microscopy techniques are allowing researchers to spy on the innards of cells in all their crowded glory.”

  2. Aspiring to greater intellectual humility in science
    Nature Human Behavior
    Rink Hoekstra & Simine Vazire: “A less often mentioned aspect of credibility is the need for intellectual humility or being transparent about and owning the limitations of our work. Although intellectual humility is presented as a widely accepted scientific norm, we argue that current research practice does not incentivize intellectual humility. We provide a set of recommendations on how to increase intellectual humility in research articles and highlight the central role peer reviewers can play in incentivizing authors to foreground the flaws and uncertainty in their work, thus enabling full and transparent evaluation of the validity of research.

The newsletter now has a dedicated homepage where we post the cover artwork for each issue. We encourage submissions that coincide with the release of a recent paper from your group.

Caption: Changes in head and neck cancer tumor volumes, derived from weekly CT images, are used to inform patient-specific tumor volume forecasts in our newly published methodology for estimating personalized radiotherapy (RT) dose. The patient-to-patient variance is shown with the 8 representative forecasts (arranged in increasing order of radiosensitivity, going clockwise around the CT image, starting at the 12 o’clock position), where the white dots are weekly tumor volume measurements from weeks 0-4 of RT and the yellow curves are the individual tumor volume forecast trajectories used to estimate personalized dose. Check out the paper for more details!

Created by: Mohammad Zahid

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