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Related Experiment Video

Updated: Apr 15, 2026

Accurate Follicle Enumeration in Adult Mouse Ovaries
07:27

Accurate Follicle Enumeration in Adult Mouse Ovaries

Published on: October 16, 2020

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Computer-generated ovaries to assist follicle counting experiments.

Angelos Skodras1, Gianluca Marcelli2

  • 1German Centre for Neurodegenerative Diseases (DZNE), Tübingen, Germany.

Plos One
|March 27, 2015
PubMed
Summary

Estimating ovarian follicle numbers in mice is crucial for reproductive biology and toxicology studies. This research introduces a novel computer simulation to optimize experimental design, reducing animal use and improving accuracy.

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Area of Science:

  • Reproductive Biology
  • Developmental Biology
  • Toxicology

Background:

  • Accurate ovarian follicle counting is vital for understanding reproductive development and assessing environmental/therapeutic impacts.
  • Estimates are influenced by sampling methods and inherent biological variability within animal populations.
  • Neonatal mouse ovaries are a key model for studying these factors.

Purpose of the Study:

  • To assess the impact of sampling methods and biological variability on ovarian follicle number estimation in neonatal mice.
  • To develop and validate a computational tool for optimizing experimental design in reproductive studies.
  • To enhance the accuracy and efficiency of follicle counting methodologies.

Main Methods:

  • Development of computer algorithms to generate simulated neonatal mouse ovaries based on published data.

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Last Updated: Apr 15, 2026

Accurate Follicle Enumeration in Adult Mouse Ovaries
07:27

Accurate Follicle Enumeration in Adult Mouse Ovaries

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Ovarian Tissue Culture to Visualize Phenomena in Mouse Ovary
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  • In-silico counting experiments utilizing unbiased stereological techniques on simulated ovaries.
  • Modeling of biological variability and sampling strategies to predict experimental outcomes.
  • Main Results:

    • The developed computer algorithms successfully model neonatal mouse ovaries with realistic characteristics.
    • In-silico experiments demonstrate the utility of simulated ovaries for optimizing sampling frequency and animal numbers.
    • The approach provides data-driven recommendations for achieving desired accuracy in follicle count estimations.

    Conclusions:

    • Simulated ovaries offer a versatile and novel tool for the planning phase of reproductive biology experiments.
    • This in-silico approach aids in estimating required animal numbers and workload, ensuring adequate statistical power.
    • The simulated ovary concept holds potential for application to other organs with numerous functional units.