This week in MathOnco 276

Fractional calculus, intrinsic drug resistance, senescence, and an agent-based modeling guide.

Jeffrey West

Maximilian Strobl

Franco Pradelli

, and 2 others

Nov 16, 2023

`> mathematical-oncology.org`

`From the editor:`

This week’s interesting collection of papers includes topics such as fractional calculus, intrinsic drug resistance, senescence, and an agent-based modeling guide.

Enjoy,

Jeffrey West jeffrey.west@moffitt.org

Investigating tumor-host response dynamics in preclinical immunotherapy experiments using a stepwise mathematical modeling strategy
Angela M. Jarrett, Patrick N. Song, Kirsten Reeves, Ernesto A.B.F. Lima, Benjamin Larimer, Thomas E. Yankeelov, Anna G. Sorace
Mathematical Model of Intrinsic Drug Resistance in Lung Cancer
Emilia Kozłowska, Andrzej Swierniak
Mathematical modeling identifies optimum palbociclib-fulvestrant dose administration schedules for the treatment of estrogen receptor-positive breast cancer patients
Yu-Chen Cheng, Shayna Stein, Agostina Nardone, Weihan Liu, Wen Ma, Gabriella Cohen, Cristina Guarducci, Thomas O McDonald, Rinath M. Jeselsohn, Franziska Michor
Simulating tumor volume dynamics in response to radiotherapy: Implications of model selection
Nuverah Mohsin, Heiko Enderling, Renee Brady-Nicholls, Mohammad U. Zahid
Fractional calculus in mathematical oncology
Tudor Alinei-Poiana, Eva-H. Dulf, Levente Kovacs
Optimal intercellular competition in senescence and cancer
Thomas C. T. Michaels and L. Mahadevan
Modeling tumor growth using fractal calculus: Insights into tumor dynamics
Amirreza Khalili Golmankhaneh, Sümeyye Tunç, Agnieszka Matylda Schlichtinger, Dachel Martinez Asanza, Alireza Khalili Golmankhaneh

A seven-step guide to spatial, agent-based modelling of tumour evolution
Blair Colyer, Maciej Bak, David Basanta, Robert Noble
Mutation of NOTCH1 is selected within normal esophageal tissues, yet leads to selective epistasis suppressive of further evolution into cancer
Kira A. Glasmacher, Vincent L. Cannataro, Jeffrey D. Mandell, Mia Jackson, J. Nic Fisk, Jeffrey P. Townsend

HIP IMO Applications now open
Moffitt’s Highschool Internship Program, HIP IMO, is an integrated mathematical oncology-centric internship program that delivers interdisciplinary team science research experiences for high school students ages 16 or older by the time of the internship. This mentored summer training program is designed for motivated aspiring scientists to help prepare them for interdisciplinary cancer research careers. Working under the direction and guidance of faculty/scientist mentors in the Integrated Mathematical Oncology (IMO) department, interns are involved in activities designed to foster the development of life-long research skills. Students will be assigned individual research projects appropriate to their interests and abilities.

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. This week’s artwork:

Based on the paper: Eigenvalue Experiment

Artist: Simone Conradi (@S_Conradi)

Caption: These plots represent an exploration of the eigenvalues of matrices constructed through the random selection of elements from a finite set of values. The central question is: what is the distribution of eigenvalues in the complex plane when two elements in such matrices are designated as real parameters, denoted as t₁ and t₂, and allowed to vary, while the remaining values remain fixed?

Each subplot illustrates the eigenvalues in ℂ for a family of 7 by 7 matrices. To generate a family, we first designate two entries t₁ and t₂ which we will vary, and then draw all other elements from the set {0, -i, i, 1, 0.5, 0.3}. These then remain fixed, while we sample 2,000,000 values t₁ and t₂, ranging from -20 to 20, compute that matrix’s eigenvalues, plot them in the complex plane, and repeat. To generate your own, you can find the code here.

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