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Stem Cell Culture01:17

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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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Forced Transdifferentiation01:28

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Transdifferentiation, also known as lineage reprogramming, was first discovered by Selman and Kafatos in 1974 in silkmoths. They observed that the moths’ cuticle-producing cells transformed into salt-producing cells. Many such cases of natural transdifferentiation occur in organisms. In humans, pancreatic alpha cells can become beta cells. In newts, the loss of the eye’s lens causes the pigmented epithelial cells to transdifferentiate into the lens cells.
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Stem Cell Niche01:26

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Stem Cell Differentiation as a Non-Markov Stochastic Process.

Patrick S Stumpf1, Rosanna C G Smith1, Michael Lenz2

  • 1Centre for Human Development, Stem Cells and Regeneration, Faculty of Medicine, University of Southampton, Southampton SO17 1BJ, UK; Institute for Life Sciences, University of Southampton, Southampton SO17 1BJ, UK.

Cell Systems
|September 29, 2017
PubMed
Summary
This summary is machine-generated.

Stem cell differentiation involves unobserved molecular states, creating a cellular memory. This study models stem cell differentiation as a non-Markov process, revealing hidden steps in neuronal lineage progression.

Keywords:
lineage commitmentnon-Markov processsingle-cell biologystatistical mechanicsstem cellsstochastic process

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Area of Science:

  • Developmental Biology
  • Stem Cell Biology
  • Computational Biology

Background:

  • Pluripotent stem cells possess self-renewal and differentiation capabilities.
  • The molecular mechanisms underlying stem cell differentiation are not fully understood.

Purpose of the Study:

  • To investigate the differentiation trajectory of mouse embryonic stem cells along the neuronal lineage.
  • To elucidate the hidden molecular states governing stem cell differentiation.

Main Methods:

  • Profiling individual mouse embryonic stem cells during neuronal differentiation.
  • Utilizing hidden Markov models to analyze cell state transitions.
  • Applying statistical mechanics for interpretation.

Main Results:

  • Identified an intermediate epiblast-like state during neuronal differentiation.
  • Revealed a chain of unobserved molecular states influencing differentiation.
  • Demonstrated that cells encode their position on the differentiation trajectory, suggesting cellular memory.

Conclusions:

  • Stem cell differentiation proceeds through a sequence of hidden molecular states.
  • A non-Markov stochastic process model explains stem cell differentiation.
  • Distinguishes between cellular "macrostates" and molecular "microstates".