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Cited by 440

The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.

Transport of Protein-Bound Hormones into Tissues in Vivo*

PARDRIDGE, WILLIAM M.·1981·Endocrine Reviews

Abstract

THE STEROID and thyroid hormones circulate in the plasma tightly bound by albumin and by specific plasma globulins (1, 2). Consequently, hormones exist in two states at equilibrium in vitro, i.e. free (dialyzable) and protein-bound. A widely held hypothesis in endocrinology is that the fraction of hormone that is free in vitro is equivalent to the fraction of hormone that is free and available for transport into tissues in vivo. Therefore, in vitro measurements of free hormones may be commonly used as reliable indices of the free hormone in vivo for a variety of clinical states. The purpose of this review is to advance the concept that the large protein-bound moiety of plasma hormone is available for transport into tissues. Consequently, the fraction of plasma hormone that is available for transport in vivo may deviate greatly from the free fraction in vitro. Under some conditions, changes in the free hormone fraction in vitro and in the fraction of plasma hormone that is available for transport in vivo will be proportional.

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Crossref · 10.1210/edrv-2-1-103

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Metadata

Authors
PARDRIDGE, W. M.
Venue
Endocrine Reviews
Published
1981-01
Volume
2
Issue
1
Pages
103-123
ISSN
  • 0163-769X (ISSN-L)
  • 1945-7189
OpenAlex
W1995993817
Cited by
440
References
54
FWCI
8.80
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Transport of Protein-Bound Hormones into Tissues in Vivo*. https://app.cochat.ai/papers/10.1210/edrv-2-1-103
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PARDRIDGE, W. M. (1981). Transport of Protein-Bound Hormones into Tissues in Vivo*. Endocrine Reviews. https://doi.org/10.1210/edrv-2-1-103

Data sources

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.