It doesn’t always pay to be fit: success landscapes

Wang, Gao; Tuan, Khanh Dang; Kevrekidis, Ioannis G.; Amend, Sarah R.; Hammarlund, Emma U.; Brown, Joel S.; Liu, Liyu; Austin, Robert H.

doi:10.1007/s10867-021-09589-2

Cited by 6 publications

(8 citation statements)

References 18 publications

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“…in which Ω is the maximum possible angular-velocity of a single isolated spinners plays a similar role to that of the carrying capacity in growth dynamics [16]. This model turns out to be in great agreement with how a single isolated aerial spinner accelerates its rotational motion (see Fig.…”

Section: B the Emergence Of Collective Spin-pumpingsupporting

confidence: 69%

“…2D). Based on this, we can create an inertial-dominated toy-model which allows us to write down the equation of rotational motion for each spinners, as we show in SM Section III [12][13][14][15][16]. After time-averaging many collisions for all spinners in each species, we arrive at the estimation for the average spinning velocity ω ± from the population number N ± :…”

mentioning

confidence: 99%

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Inertial Spinner Swarm Experiments: Spin Pumping, Entropy Oscillations and Spin Frustration

Li¹,

Wang²,

Khuri³

et al. 2023

Preprint

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We present here an inertial active spinning swarm consisting of mixtures of opposite handedness torque driven spinners floating on an air bed with low damping. Depending on the relative spin sign, spinners can act as their own anti-particles and annihilate their spins. Rotational energy can become highly focused, with minority fraction spinners pumped to very high levels of spin angular momentum. Spinner handedness also matters at high spinner densities but not low densities: oscillations in the mixing spatial entropy of spinners over time emerge if there is a net spin imbalance from collective rotations. Geometrically confined spinners can lock themselves into frustrated spin states.

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Section: B the Emergence Of Collective Spin-pumpingsupporting

confidence: 69%

mentioning

confidence: 99%

Inertial Spinner Swarm Experiments: Spin Pumping, Entropy Oscillations and Spin Frustration

Li¹,

Wang²,

Khuri³

et al. 2023

Preprint

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“…Such data directs us to investigate the role of the TME in providing selective pressures for adaptation that may explain poor response to therapies and the acquisition of resistance. This concept can be further expanded, considering the TME as a fitness landscape ( Phan et al, 2021 ) with features of microniches that drive the selection of plastic phenotypes for tumor progression. As proposed by Pienta and others, we suggest that tumor therapies consider multimodal mechanisms of drug action, or sequential regimens that limit tumor evolvability in early stages of the disease, exploiting the concept of inducing an extinction event and preventing the reconstitution of the tumor ( Pienta et al, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

Delineating intra-tumoral heterogeneity and tumor evolution in breast cancer using precision-based approaches

Xulu,

Nweke,

Augustine

2023

Front. Genet.

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The burden of breast cancer continues to increase worldwide as it remains the most diagnosed tumor in females and the second leading cause of cancer-related deaths. Breast cancer is a heterogeneous disease characterized by different subtypes which are driven by aberrations in key genes such as BRCA1 and BRCA2, and hormone receptors. However, even within each subtype, heterogeneity that is driven by underlying evolutionary mechanisms is suggested to underlie poor response to therapy, variance in disease progression, recurrence, and relapse. Intratumoral heterogeneity highlights that the evolvability of tumor cells depends on interactions with cells of the tumor microenvironment. The complexity of the tumor microenvironment is being unraveled by recent advances in screening technologies such as high throughput sequencing; however, there remain challenges that impede the practical use of these approaches, considering the underlying biology of the tumor microenvironment and the impact of selective pressures on the evolvability of tumor cells. In this review, we will highlight the advances made thus far in defining the molecular heterogeneity in breast cancer and the implications thereof in diagnosis, the design and application of targeted therapies for improved clinical outcomes. We describe the different precision-based approaches to diagnosis and treatment and their prospects. We further propose that effective cancer diagnosis and treatment are dependent on unpacking the tumor microenvironment and its role in driving intratumoral heterogeneity. Underwriting such heterogeneity are Darwinian concepts of natural selection that we suggest need to be taken into account to ensure evolutionarily informed therapeutic decisions.

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“…Therefore, only when the genes and traits of the robot match the type and amount of environmental resources can the individual survive for a long time. [35] Figure 2(e) shows the relationship between the robot mutation rate and the resource intensity. In short, when the environment is less suitable for the individual to survive, the individual's survival pressure will increase, and the possibility of gene mutation will be higher.…”

Section: Definition Of Biological Evolution Characteristics Of Robotsmentioning

confidence: 99%

Bio-inspired environmental adaptability of swarm active matter

et al. 2023

Self Cite

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How biologically active matters survive adaptively in complex and changeable environments is a common concern of scientists. Genetics, evolution and natural selection are vital factors in the process of biological evolution and are also the key to survival in harsh environments. However, it is challenging to intuitively and accurately reproduce such long-term adaptive survival processes in the laboratory. Although simulation experiments are intuitive and efficient, they lack fidelity. Therefore, we propose to use swarm robots to study the adaptive process of active matter swarms to complex and changeable environments. Based on a self-built virtual environmental platform and a robot swarm that can interact with the environment, we introduce the concept of genes into the robot system, giving each robot unique digital genes, and design robot breeding methods and rules for gene mutations. Our previous work[1] has demonstrated the effectiveness of this system. In this work, by analyzing the relationship between the genetic traits of the population and the characteristics of environmental resources, and comparing different experimental conditions, we verified in both robot experiments and corresponding simulation experiments that agents with genetic inheritance can survive for a long time under the action of natural selection in periodically changing environments. We also confirmed that in the robot system, both breeding and mutation are essential factors. These findings can help answer the practical scientific question of how individuals and swarms can successfully adapt to complex, dynamic, and unpredictable actual environments.

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It doesn’t always pay to be fit: success landscapes

Cited by 6 publications

References 18 publications

Inertial Spinner Swarm Experiments: Spin Pumping, Entropy Oscillations and Spin Frustration

Inertial Spinner Swarm Experiments: Spin Pumping, Entropy Oscillations and Spin Frustration

Delineating intra-tumoral heterogeneity and tumor evolution in breast cancer using precision-based approaches

Bio-inspired environmental adaptability of swarm active matter

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