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Related Experiment Video

Updated: Nov 11, 2025

Visualization and Quantification of Brown and Beige Adipose Tissues in Mice using [18F]FDG Micro-PET/MR Imaging
08:31

Visualization and Quantification of Brown and Beige Adipose Tissues in Mice using [18F]FDG Micro-PET/MR Imaging

Published on: July 1, 2021

3.3K

Beige Adipose Tissue Identification and Marker Specificity-Overview.

Anna-Claire Pilkington1, Henry A Paz1,2, Umesh D Wankhade1,2

  • 1Arkansas Children's Nutrition Center, University of Arkansas for Medical Sciences, Little Rock, AR, United States.

Frontiers in Endocrinology
|March 29, 2021
PubMed
Summary

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Identifying beige adipose tissue (BeAT) is challenging due to similarities with brown adipose tissue (BAT). This review explores transcript markers for distinguishing BeAT, BAT, and white adipose tissue (WAT) to improve metabolic health understanding.

Area of Science:

  • Cell Biology
  • Metabolic Health
  • Adipose Tissue Biology

Background:

  • Adipose tissue (AT) comprises white (WAT), brown (BAT), and beige (BeAT) types, each with distinct characteristics.
  • Differentiating BeAT from BAT is difficult due to overlapping molecular and visual features.
  • Accurate classification of AT subtypes is crucial for understanding metabolic health.

Purpose of the Study:

  • To review current advances in identifying BeAT, BAT, and WAT using transcript markers.
  • To highlight challenges in current AT identification methods.
  • To propose new perspectives for transcript-specific BeAT identification.

Main Methods:

  • Literature review of transcript markers for AT identification.
  • Analysis of challenges associated with differentiating AT subtypes.
Keywords:
beige adipose tissuebrown adipose tissueobesitythermogenesiswhite adipose tissue

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  • Exploration of novel strategies for BeAT classification.
  • Main Results:

    • Current transcript markers present difficulties in definitively distinguishing between BeAT and BAT.
    • Similarities in appearance and gene expression profiles complicate classification.
    • New perspectives for transcript-specific BeAT identification are proposed.

    Conclusions:

    • Precise identification of BeAT is essential for advancing AT biology.
    • Improved AT classification strategies can aid in tracking interventions for metabolic health.
    • Further research into transcript-specific markers will enhance our understanding of AT diversity.