Over the past decade, great progress has been made in understanding the complexity of adipose tissue biology and its role in metabolism. This includes new insights into the multiple layers of adipose tissue heterogeneity, not only differences between white and brown adipocytes, but also differences in white adipose tissue at the depot level and even heterogeneity of white adipocytes within a single depot. These inter- and intra-depot differences in adipocytes are developmentally programmed and contribute to the wide range of effects observed in disorders with fat excess (overweight/obesity) or fat loss (lipodystrophy). Recent studies also highlight the underappreciated dynamic nature of adipose tissue, including potential to undergo rapid turnover and dedifferentiation and as a source of stem cells. Finally, we explore the rapidly expanding field of adipose tissue as an endocrine organ, and how adipose tissue communicates with other tissues to regulate systemic metabolism both centrally and peripherally through secretion of adipocyte-derived peptide hormones, inflammatory mediators, signaling lipids, and miRNAs packaged in exosomes. Together these attributes and complexities create a robust, multidimensional signaling network that is central to metabolic homeostasis.
C. Ronald Kahn, Guoxiao Wang, Kevin Y. Lee
Usage data is cumulative from April 2024 through April 2025.
Usage | JCI | PMC |
---|---|---|
Text version | 4,500 | 1,411 |
547 | 413 | |
Figure | 692 | 17 |
Citation downloads | 119 | 0 |
Totals | 5,858 | 1,841 |
Total Views | 7,699 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.