| 研究領域 | 情報物理学でひもとく生命の秩序と設計原理 |
|---|
| 研究課題/領域番号 |
22H04841
|
|---|
| 研究機関 | 東京大学 |
|---|
研究代表者 |
Schnyder Simon 東京大学, 生産技術研究所, 特任助教 (50812616)
|
|---|
| 研究期間 (年度) |
2022-04-01 – 2024-03-31
|
| キーワード | active matter / cell cycle / control theory / collective behavior / simulations |
|---|
| 研究実績の概要 |
In accordance with the plans I set out in the beginning, I surveyed theoretical and computational approaches with the aim was to extend a mechanical tissue model with signal processing and decision making.
In accordance with this, we extended the model to include programmed cell death (apoptosis) and coupled it to the cell cycle of each cell, which represents the internal signal processing of the cell. With this we were able to investigate how cell competition between two types of cells is affected by different parameters of apoptosis and the cell cycle regulation. We studied how cells compete in 2D by using both a mean field theory and particle-based simulations. We employ a mechanical model that incorporates a stylized form of cell cycle regulation to control cell division events.Analytic predictions for the invasion speed and the coexistence line were in agreement with simulations. We also studied the invasion or elimination of small (pre)cancerous colonies. We showed how a Laplace pressure at the colony interface, controlled by differential cell adhesion, shifted the coexistence line; there are cell types that can invade when starting from a large colony but will be eliminated if the colony is small.
In order to understand how to apply control theory in a highly collective setting, I found it necessary to first study the control theoretic aspects of the project in isolation. This has led to a series of results for optimal behavior of individuals in populations. We are in the process of readying these works for publication. (Further details in “Current Status”)
|
| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
The completion of the first study is a promising first step. The extension of the model is still ongoing. In particular, I am beginning to implement control theoretic approaches, with the goal of studying optimal behavior of collective cellular tissues.
In order to understand how to apply control theory in a highly collective setting, I found it necessary to first study the control theoretic aspects of the project in isolation. This has led to a series of results for optimal behavior of individuals in populations. In particular, we investigated how collective social behavior can arise in a self organized way in a population of individuals. For a representative individual, one can write down a utility function that the individual will seek to optimise, while incorporating information about the population in a mean field sense. If all individuals are identical, all will react in the same way to the state of the population, giving rise to a Nash equilibrium. In addition, we understood how a planner who is looking to maximize a separate objective function, can design external control fields to affect this Nash equilibrium to achieve this goal. We found it sensible to first apply this framework to the situation of self-organized social distancing in an epidemic, with the government acting as the planner designing incentive structures to maximize the public health outcome. We are in the process of readying these works for publication.
|
| 今後の研究の推進方策 |
We hope to be able to publish our work on optimal behavior of individuals in populations in the coming year. I will then continue to extend the cell model with cell motility, working towards the study of wound closure. Ideally, I would be able to then synthesize our work on control theory and our work on cellular behavior to generate new insights into optimal wound healing. For instance, I believe that the control theoretic framework we developed and which is outlined in the “Current Status”, can be applied to tissues in which cells are making decisions and in which for instance drugs might be used by the planner to obtain optimal outcomes.
I believe this project would have higher impact if the scope of the research target were broadened. We believe the developed approach to be applicable to other range of biological collective decision making processes, for instance swarming. In addition, I hope to continue work on extending the control theoretic framework to be able to represent not only the population and a representative individual, but also intermediate structures. In particular, even for a purely self-interested organism or person, it can be important to optimize not only for one’s own goals but for the intermediate structures goals as well. In the epidemic context, this might represent one’s family; in the biological context, this might represent a clonal sub colony or a group of a particular differentiated cell type in a greater colony.
|
