“This week in Mathematical Oncology” — February 22, 2024
> mathematical-oncology.org
From the editor:
This week’s list includes topics like subclonal evolution, collective motion, and spatial interactions.
You’ll also find a preprint from my own group, where we attempt to use methods originally developed for Artificial Life (not to be confused with Artificial Intelligence) to address questions on spatial structure in tumors.
Enjoy,
Jeffrey West
jeffrey.west@moffitt.org
A novel multiscale framework for delineating cancer evolution from subclonal compositions
Zhihao Yao, Suoqin Jin, Fuling Zhou, Junbai Wang, Kai Wang, Xiufen ZouBridging scales: A hybrid model to simulate vascular tumor growth and treatment response
Tobias Duswald, Ernesto A.B.F. Lima, J. Tinsley Oden, Barbara WohlmuthQuantifying collective motion patterns in mesenchymal cell populations using topological data analysis and agent-based modeling
Kyle C. Nguyen, Carter D. Jameson, Scott A. Baldwin, John T. Nardini, Ralph C. Smith, Jason M. Haugh, Kevin B. FloresDynamics of T-helper cell differentiation and plasticity: How have computational models improved our understanding?
Pradyumna Harlapur, Atchuta Srinivas Duddu, Mohit Kumar JollySelection of prostate cancer therapy strategy under early androgen suppression treatment
Miaoran Yao, Yongxin Zhang, Wendi WangMitigating non-genetic resistance to checkpoint inhibition based on multiple states of immune exhaustion
Irina Kareva & Jana L. GevertzForum on immune digital twins: a meeting report
Reinhard Laubenbacher, Fred Adler, Gary An, Filippo Castiglione, …, Amber Smith, Isabel Voigt, Thomas E. Yankeelov & Tjalf ZiemssenCalibration of agent based models for monophasic and biphasic tumour growth using approximate Bayesian computation
Xiaoyu Wang, Adrianne L. Jenner, Robert Salomone, David J. Warne & Christopher Drovandi
Spatial interactions modulate tumor growth and immune infiltration
Sadegh Marzban, Sonal Srivastava, Sharon Kartika, Rafael Bravo, …, Alexander R. A. Anderson, Christine H Chung, Antonio L Amelio, Jeffrey WestMultistability and predominant double-positive states in a four node mutually repressive network: a case study of Th1/Th2/Th17/T-reg differentiation
Atchuta Srinivas Duddu, Elizabeth Andreas, BV Harshavardhan, Kaushal Grover, …, Siddharth Jhunjhunwala, Breschine Cummins, Tomas Gedeon, Mohit Kumar JollySpatially Fractionated GRID radiation potentiates immune-mediated tumor control
Rebecca A. Bekker, Nina Obertopp, Gage Redler, José Penagaricano, Jimmy J. Caudell, Kosj Yamoah, Shari Pilon-Thomas, Eduardo G. Moros, Heiko Enderling
Google Scholar is manipulatable
ArXiv: Hazem Ibrahim, Fengyuan Liu, Yasir Zaki, Talal Rahwan
”Citations are widely considered in scientists' evaluation. As such, scientists may be incentivized to inflate their citation counts. While previous literature has examined self-citations and citation cartels, it remains unclear whether scientists can purchase citations. Here, we compile a dataset of ~1.6 million profiles on Google Scholar to examine instances of citation fraud on the platform. We survey faculty at highly-ranked universities, and confirm that Google Scholar is widely used when evaluating scientists. Intrigued by a citation-boosting service that we unravelled during our investigation, we contacted the service while undercover as a fictional author, and managed to purchase 50 citations. These findings provide conclusive evidence that citations can be bought in bulk, and highlight the need to look beyond citation counts.”
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: Synergistic Drug Combinations Promote the Development of Resistance in Acute Myeloid Leukemia published in Blood Cancer Discovery
Artist: Amy Pomeroy (@AmyEPomeroy)
Caption: A drug combination that works better than expected from the efficacy of the individual drugs seems like it should be all upside and no downside, and indeed, this combinational synergy has been the motivation for many drug combinations. However, recent computational and experimental work on combination therapies in Acute Myeloid Leukemia, demonstrated that this synergy has an unintended consequence – increased development of resistance. A commentary of this work likens synergy to siren songs from Greek mythology, luring us towards seemingly promising combinations that result in increased resistance. A theoretical model, supported by extensive experimental evidence, demonstrates that synergy increases the impact of resistance to one drug since both the effect of that drug and the added benefit of synergistic interaction are lost. This result suggests that, when designing combinations, the lure of the siren song of synergy should be resisted to avoid increased drug resistance.
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