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Related Concept Videos

Diversity in Cell Signaling Responses01:22

Diversity in Cell Signaling Responses

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The physiological function of a cell and cellular communication are outcomes of a range of extrinsic signals, intracellular signaling pathways, and cellular responses. No two cell types express the same repertoire of signaling components. Receptors are highly selective for their cognate ligands, but once activated, they can alter multiple cellular processes such as DNA transcription, protein synthesis, and metabolic activity. 
Graded and Abrupt Responses
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Interactions Between Signaling Pathways01:19

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Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
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Overview of Cell Signaling01:23

Overview of Cell Signaling

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Despite the protective membrane that separates a cell from the environment, cells need the ability to detect and respond to environmental changes. Additionally, cells often need to communicate with one another. Unicellular and multicellular organisms use a variety of cell signaling mechanisms to communicate with the environment.
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What is Cell Signaling?02:03

What is Cell Signaling?

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Despite the protective membrane that separates a cell from the environment, cells need the ability to detect and respond to environmental changes. Additionally, cells often need to communicate with one another. Unicellular and multicellular organisms use a variety of cell signaling mechanisms to communicate to respond to the environment.
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Notch Signaling Pathway03:14

Notch Signaling Pathway

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The Notch signaling pathway is a major intracellular signaling pathway that is highly conserved over a broad spectrum of metazoan species. It stands unique from other intracellular signaling mechanisms in animals because notch protein itself acts as the receptor as well as the primary signaling molecule.
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Hedgehog Signaling Pathway02:33

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The Hedgehog gene (Hh) was first discovered due to its control of the growth of disorganized, hair-like bristles phenotype in Drosophila, much like hedgehog spines. Hh plays a crucial role in the development of organs and the maintenance of homeostasis in both invertebrates and vertebrates. However, while Drosophila has only one Hh protein, mammals have multiple functional Hedgehog proteins - Sonic (Shh), Desert (Dhh), and Indian Hedgehog (Ihh). All of these homologous proteins have adapted to...
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Updated: Jun 17, 2025

The Power of Simplicity: Sea Urchin Embryos as in Vivo Developmental Models for Studying Complex Cell-to-cell Signaling Network Interactions
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The Power of Simplicity: Sea Urchin Embryos as in Vivo Developmental Models for Studying Complex Cell-to-cell Signaling Network Interactions

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Correspondence between multiple signaling and developmental cellular patterns: a computational perspective.

Zahra Eidi1, Najme Khorasani1, Mehdi Sadeghi2

  • 1School of Biological Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.

Frontiers in Cell and Developmental Biology
|August 14, 2024
PubMed
Summary
This summary is machine-generated.

This study models how chemical signals guide stem cell differentiation and tissue self-organization. It shows a link between signaling patterns and resulting cell structures, aiding in predicting or identifying developmental influences.

Keywords:
Turing dynamicscell tissuedevelopmental patternregenerative therapyself-organizationsignaling

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Area of Science:

  • Developmental Biology
  • Systems Biology
  • Computational Biology

Background:

  • Stem cell division and spatial arrangement of phenotypes are key to tissue self-organization.
  • Diffusible chemical signals and intracellular/intercellular events influence cellular pattern formation.
  • Cells interpret external signals to designate cell fate and modify production rates.

Purpose of the Study:

  • To investigate the spatial distribution of differentiating cells using distinct signaling patterns as cues.
  • To establish a correspondence between multiple signaling patterns and developmental cellular patterns.
  • To develop a model for predicting cellular structures and identifying influencing signaling patterns.

Main Methods:

  • Utilized Turing systems to generate distinct signaling patterns.
  • Proposed a computational map to analyze spatial distribution of differentiating cells.
  • Investigated the relationship between signaling cues and cell fate determination.

Main Results:

  • Demonstrated a correspondence between multiple signaling patterns and developmental cellular patterns.
  • Showed the model can predict the final structure of differentiated cells in complex environments.
  • Developed an algorithm to partially identify signaling patterns from known cellular structures.

Conclusions:

  • The computational model accurately predicts cellular structures based on signaling patterns.
  • The findings offer insights into how cells self-organize and differentiate in response to chemical cues.
  • The algorithm aids in understanding the influence of signaling dynamics on tissue development.