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Related Concept Videos

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Embryonic and induced pluripotent stem cells are excellent models for disease research because of their ability to self-renew and differentiate into most cell types. Somatic cells from a patient are isolated and reprogrammed into induced pluripotent stem cells or iPSCs. These iPSCs are later differentiated into the desired cell type, which mirrors the diseased cell of the patient. In this way, disease models have been created for investigating diseases such as Down syndrome, type I diabetes,...
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Embryonic stem (ES) cells were first discovered in mice in 1981 by Martin Evans. In 1998, James Thomson identified a method to isolate embryonic stem cells from humans. Human embryonic stem cells (hESCs) are obtained from 3-5 day old embryos that remain unused after an in vitro fertilization procedure.
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Related Experiment Video

Updated: Dec 7, 2025

Patterning the Geometry of Human Embryonic Stem Cell Colonies on Compliant Substrates to Control Tissue-Level Mechanics
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Predicting pattern formation in embryonic stem cells using a minimalist, agent-based probabilistic model.

Minhong Wang1, Athanasios Tsanas2, Guillaume Blin3

  • 1Usher Institute, Edinburgh Medical School, The University of Edinburgh, Edinburgh, EH16 4UX, UK. Minhong.Wang@ed.ac.uk.

Scientific Reports
|October 2, 2020
PubMed
Summary
This summary is machine-generated.

Embryonic stem cells spontaneously form spatial patterns when confined. Differential cell motility, modeled using an agent-based approach, sufficiently explains this emergent phenomenon, reducing the need for extensive experiments.

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Area of Science:

  • Developmental Biology
  • Computational Biology
  • Stem Cell Biology

Background:

  • Embryonic development involves complex pattern formation, the mechanisms of which are not fully understood.
  • Embryonic stem cells in culture self-organize into spatial patterns of gene expression under geometrical confinement.
  • Patterning is recognized as an emergent phenomenon arising from numerous cell-cell interactions.

Purpose of the Study:

  • To identify plausible biological rules governing meso-scale interactions within stem cell collectives that explain spontaneous patterning.
  • To utilize an agent-based modeling approach to simulate and analyze stem cell behavior.
  • To develop and apply a novel metric, stem cell aggregate pattern distance (SCAPD), for assessing model-data fitness.

Main Methods:

  • Agent-based modeling was employed to simulate stem cell collectives.
  • Models explored differential motile behaviors, with and without neighbor interaction biases.
  • The stem cell aggregate pattern distance (SCAPD) metric was introduced to quantitatively compare model predictions with empirical data.

Main Results:

  • The best-performing models demonstrated significant improvements in fitness compared to random models (70% for discoidal confinement, 77% for ellipsoidal confinement).
  • A parsimonious mechanism involving differential cell motility was found sufficient to explain spontaneous patterning.
  • The study defined a specific parameter space compatible with observed stem cell patterning.

Conclusions:

  • Differential cell motility is a key factor driving spontaneous spatial patterning in confined embryonic stem cell collectives.
  • Agent-based modeling provides a powerful tool for understanding emergent biological phenomena.
  • This approach can potentially reduce the reliance on costly and time-consuming experimental studies in developmental biology.