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Related Concept Videos

Lineage Commitment01:21

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Commitment is the  process whereby stem cells:
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The cells of the blastocyst inner cell mass only remain pluripotent for a short time. This state of pluripotency and self-renewal can be maintained in embryonic stem (ES) cell culture by adding specific chemicals or growth factors to ensure the cells can continue dividing and later differentiate into different cell types. In some cases, the cells are grown on a feeder layer of differentiated cells, which provides the growth factors and extracellular matrix components necessary for stem cell...
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Stem cell research aims to find ways to use stem cells to regenerate and repair cellular damage. Over time, most adult cells undergo the wear and tear of aging and lose their ability to divide and repair themselves. Stem cells do not display a particular morphology or function. Adult stem cells, which exist as a small subset of cells in most tissues, keep dividing and can differentiate into a number of specialized cells generally formed by that tissue. These cells enable the body to renew and...
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Determination01:51

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During embryogenesis, cells become progressively committed to different fates through a two-step process: specification followed by determination. Specification is demonstrated by removing a segment of an early embryo, “neutrally” culturing the tissue in vitro—for example, in a petri dish with simple medium—and then observing the derivatives. If the cultured region gives rise to cell types that it would normally generate in the embryo, this means that it is specified. In...
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Stem Cell Niche01:26

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The stem cell niche is the dynamic microenvironment where stem cells reside. Inside these niches, the cells may remain undifferentiated, undergo high self-renewal, or become lineage-specific progenitors. Stem cells coexist with other niche cells, such as stromal cells. They also interact closely with the ECM. Cell-cell and cell-matrix communication occur via adhesion molecules or soluble factors that signal the stem cells and determine their fate. Stromal cells also provide survival signals to...
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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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Related Experiment Video

Updated: Nov 22, 2025

Blastomere Explants to Test for Cell Fate Commitment During Embryonic Development
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Stem Cell Fate Decision Making: Modeling Approaches.

Alexander A Spector1,2, Warren L Grayson3,4

  • 1Department of Biomedical Engineering and ‡Translational Tissue Engineering Center, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, United States.

ACS Biomaterials Science & Engineering
|January 9, 2021
PubMed
Summary
This summary is machine-generated.

Computational modeling offers key insights into cell-fate decisions across various stem cell types. This review explores diverse modeling approaches, highlighting their effectiveness in understanding differentiation and disease.

Keywords:
cell differentiationdynamical systemmechanobiologystochastic methods

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Area of Science:

  • Computational biology
  • Stem cell biology
  • Mathematical modeling

Background:

  • Cell-fate decisions are complex processes crucial for development and disease.
  • Mathematical modeling provides a powerful framework to understand these intricate mechanisms.
  • Various stem cell types, including embryonic, hematopoietic, and neural stem cells, undergo differentiation.

Purpose of the Study:

  • To review major mathematical modeling approaches for stem cell differentiation.
  • To discuss the application of these models in understanding cell-fate decisions.
  • To highlight the role of modeling in improving differentiation platforms and analyzing pathological conditions.

Main Methods:

  • Population dynamics models
  • Bifurcating dynamical systems (bistability, oscillations)
  • Spatiotemporal models (continuum, agent-based, rule-based)
  • Mechanotransduction and extracellular matrix modeling
  • Stochastic models incorporating molecular noise

Main Results:

  • Differentiation models effectively capture cell-fate choices.
  • Modeling reveals insights into embryonic, hematopoietic, adipose-derived, cancer, and neural stem cell differentiation.
  • Mechanical factors and molecular noise significantly influence differentiation pathways.
  • Computational models aid in developing improved differentiation platforms and analyzing disease.

Conclusions:

  • Mathematical modeling is essential for deciphering cell differentiation processes.
  • Diverse modeling strategies offer complementary perspectives on cell-fate decisions.
  • These approaches have significant implications for regenerative medicine and disease understanding.