Gildas Carlin, Ian Manifacier, Dang Khoa Cao, Laurent Pieuchot, Valeriy Luchnikov, Jean-Louis Milan
{"title":"各向异性持续随机游走模型模拟t细胞在弯曲地形上的迁移。","authors":"Gildas Carlin, Ian Manifacier, Dang Khoa Cao, Laurent Pieuchot, Valeriy Luchnikov, Jean-Louis Milan","doi":"10.1038/s41598-025-02804-3","DOIUrl":null,"url":null,"abstract":"<p><p>Cell migration is an important cellular process to study, as it plays a fundamental role in tissue structuring and development, while abnormal cell migration may be the cause of certain diseases. Among the known factors influencing cell migration, substrate curvature is one, with cells naturally moving towards concave areas while avoiding convex ones. The underlying causes of migration guidance by curvature remain unclear, and in particular, the way in which cell persistence is affected is still not well understood. We introduce an anisotropic persistent random walk model which includes cell heterogeneity to simulate T-cell migration across various corrugate landscapes. We compared the trajectories generated by the model with in vitro T-cells trajectories over the same topographies. The model accurately captures key features of cell trajectories on flat surfaces as well as on curved surfaces, such as a directional bias toward concave regions. The model also reveals a superdiffusive behavior on curvature, demonstrating more efficient movement compared to flat surfaces. The anisotropic randomness incorporated in the model appears as a critical feature which shapes T-cells persistence mechanisms by increasing cellular activity in the axis of concave valleys and promoting migration towards concave areas.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"19629"},"PeriodicalIF":3.9000,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12137650/pdf/","citationCount":"0","resultStr":"{\"title\":\"Anisotropic persistent random walk model simulates T-cells migration over curved landscapes.\",\"authors\":\"Gildas Carlin, Ian Manifacier, Dang Khoa Cao, Laurent Pieuchot, Valeriy Luchnikov, Jean-Louis Milan\",\"doi\":\"10.1038/s41598-025-02804-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Cell migration is an important cellular process to study, as it plays a fundamental role in tissue structuring and development, while abnormal cell migration may be the cause of certain diseases. Among the known factors influencing cell migration, substrate curvature is one, with cells naturally moving towards concave areas while avoiding convex ones. The underlying causes of migration guidance by curvature remain unclear, and in particular, the way in which cell persistence is affected is still not well understood. We introduce an anisotropic persistent random walk model which includes cell heterogeneity to simulate T-cell migration across various corrugate landscapes. We compared the trajectories generated by the model with in vitro T-cells trajectories over the same topographies. The model accurately captures key features of cell trajectories on flat surfaces as well as on curved surfaces, such as a directional bias toward concave regions. The model also reveals a superdiffusive behavior on curvature, demonstrating more efficient movement compared to flat surfaces. The anisotropic randomness incorporated in the model appears as a critical feature which shapes T-cells persistence mechanisms by increasing cellular activity in the axis of concave valleys and promoting migration towards concave areas.</p>\",\"PeriodicalId\":21811,\"journal\":{\"name\":\"Scientific Reports\",\"volume\":\"15 1\",\"pages\":\"19629\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2025-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12137650/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific Reports\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1038/s41598-025-02804-3\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Reports","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41598-025-02804-3","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Anisotropic persistent random walk model simulates T-cells migration over curved landscapes.
Cell migration is an important cellular process to study, as it plays a fundamental role in tissue structuring and development, while abnormal cell migration may be the cause of certain diseases. Among the known factors influencing cell migration, substrate curvature is one, with cells naturally moving towards concave areas while avoiding convex ones. The underlying causes of migration guidance by curvature remain unclear, and in particular, the way in which cell persistence is affected is still not well understood. We introduce an anisotropic persistent random walk model which includes cell heterogeneity to simulate T-cell migration across various corrugate landscapes. We compared the trajectories generated by the model with in vitro T-cells trajectories over the same topographies. The model accurately captures key features of cell trajectories on flat surfaces as well as on curved surfaces, such as a directional bias toward concave regions. The model also reveals a superdiffusive behavior on curvature, demonstrating more efficient movement compared to flat surfaces. The anisotropic randomness incorporated in the model appears as a critical feature which shapes T-cells persistence mechanisms by increasing cellular activity in the axis of concave valleys and promoting migration towards concave areas.
期刊介绍:
We publish original research from all areas of the natural sciences, psychology, medicine and engineering. You can learn more about what we publish by browsing our specific scientific subject areas below or explore Scientific Reports by browsing all articles and collections.
Scientific Reports has a 2-year impact factor: 4.380 (2021), and is the 6th most-cited journal in the world, with more than 540,000 citations in 2020 (Clarivate Analytics, 2021).
•Engineering
Engineering covers all aspects of engineering, technology, and applied science. It plays a crucial role in the development of technologies to address some of the world''s biggest challenges, helping to save lives and improve the way we live.
•Physical sciences
Physical sciences are those academic disciplines that aim to uncover the underlying laws of nature — often written in the language of mathematics. It is a collective term for areas of study including astronomy, chemistry, materials science and physics.
•Earth and environmental sciences
Earth and environmental sciences cover all aspects of Earth and planetary science and broadly encompass solid Earth processes, surface and atmospheric dynamics, Earth system history, climate and climate change, marine and freshwater systems, and ecology. It also considers the interactions between humans and these systems.
•Biological sciences
Biological sciences encompass all the divisions of natural sciences examining various aspects of vital processes. The concept includes anatomy, physiology, cell biology, biochemistry and biophysics, and covers all organisms from microorganisms, animals to plants.
•Health sciences
The health sciences study health, disease and healthcare. This field of study aims to develop knowledge, interventions and technology for use in healthcare to improve the treatment of patients.