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Related Concept Videos

Cluster Sampling Method01:20

Cluster Sampling Method

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Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
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After budding out from the ER membrane, some COPII vesicles lose their coat and fuse with one another to form larger vesicles and interconnected tubules called vesicular tubular clusters or VTCs. These clusters constitute a compartment at the ER-Golgi interface known as ERGIC (Endoplasmic Reticulum Golgi Intermediate Compartment). The ERGIC is a mobile membrane-bound cargo transport system that sorts proteins secreted from ER and delivers them to the Golgi.
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Contact-dependent Signaling

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Contact-dependent signaling, as the name suggests, requires that communicating cells be in direct contact with each other. This is achieved either through receptor-ligand interactions or by specialized cytoplasmic channels that allow the flow of small molecules between cells. In animal cells, channels called gap junctions facilitate contact-dependent signaling in certain tissues, whereas, plasmodesmata perform a similar function in plants.
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ATP-driven pumps, also known as transport ATPases, are integral membrane proteins. They have binding sites for ATP located on the membrane's cytosolic side and the ion-conducting domain in the transmembrane region. These pumps use the free energy released from ATP hydrolysis to move the solutes across cell membranes against an electrochemical gradient.
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Endocrine cells produce hormones to communicate with remote target cells found in other organs. The hormone reaches these distant areas using the circulatory system. This exposes the whole organism to the hormone but only those cells expressing hormone receptors or target cells are affected. Thus, endocrine signaling induces slow responses from its target cells but these effects also last longer.
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Bacterial signaling can occur within bacteria (intracellular) or between bacteria (intercellular). At times, a group of bacteria behaves like a community. To achieve this, they engage in quorum sensing, the perception of higher cell density that causes changes in gene expression. Quorum sensing involves both extracellular and intracellular signaling. The signaling cascade starts with a molecule called an autoinducer (AI). Individual bacteria produce AIs that move out of the bacterial cell...
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Related Experiment Video

Updated: Feb 13, 2026

Rapid Genetic Analysis of Epithelial-Mesenchymal Signaling During Hair Regeneration
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Phenotype-driven identification of epithelial signalling clusters.

Elsa Marques1, Tomi Peltola2, Samuel Kaski2

  • 1Cancer Cell Circuitry Laboratory, Research Programs Unit/Translational Cancer Biology & Medicum, University of Helsinki, P.O Box 63 (street address: Haartmaninkatu 8), 00014 University of Helsinki, Helsinki, Finland.

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Summary
This summary is machine-generated.

Researchers identified new gene regulators of epithelial architecture using 3D cell cultures and a genetic screen. This approach reveals how gene function depends on cellular context, aiding cancer research.

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Area of Science:

  • Cell Biology
  • Genetics
  • Biophysics

Background:

  • Epithelial architecture is crucial for cell responses to signals, including cancer development.
  • Three-dimensional (3D) epithelial cultures model context-dependent gene functions.
  • Genetic screens are vital for discovering new determinants of cellular phenotypes.

Purpose of the Study:

  • To identify novel genetic determinants of epithelial architecture in 3D mammary epithelial cultures.
  • To develop and validate a method for analyzing population distribution changes in 3D structures.
  • To integrate morphometric and interaction data for pathway discovery.

Main Methods:

  • Arrayed genetic shRNA screen in 3D mammary epithelial cultures.
  • Analysis of population distribution patterns using Maximum Mean Discrepancy.
  • Integration of morphometric data with protein-protein interaction networks.

Main Results:

  • Identified shRNAs that significantly alter population distribution, not just averages.
  • Demonstrated the feasibility of using Maximum Mean Discrepancy for 3D structure analysis.
  • Generated hypotheses for novel pathways involved in 3D epithelial phenotype alterations.

Conclusions:

  • A new strategy for 3D phenotype-driven pathway analysis was established.
  • This approach accelerates the discovery of context-dependent gene functions.
  • Findings are applicable to understanding epithelial biology and tumorigenesis.