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Effects of Neuropeptides and TSH on Thyroid Blood Flow and Hormone Secretion

  • George A. Hedge
  • Linda Huffman
  • John M. Connors

Abstract

The thyroid gland of the rat is now known to receive nerve fibers containing a variety of neuropeptides (NP’s) including vasoactive intestinal peptide (VIP) (1), peptide HI (PHI) (2), neuropeptide Y (NPY) (3), and substance P (SP) (4). There is also evidence to indicate that some of these NP’s can affect thyroid hormone secretion, particularly TSH-induced secretion. For example, VIP enhances thyroid colloid droplet formation and cyclic AMP production in vitro (1,5,6), and it increases the release of radioactive iodine from the thyroid in vivo (1). Using the latter index, NPY has been shown to modulate thyroid responsiveness to TSH (3). In contrast, SP is reported to increase thyroid hormone release in vitro (7), but apparently has no effect in vivo (4). Since the nerve fibers containing these NP’s are distributed to both follicles and blood vessels (2), we have initiated some studies of the effects of NP’s on thyroid blood flow and on plasma thyroid hormone concentrations in the presence and the absence of exogenous TSH. In our preliminary communications (8,9), we have reported increases in total thyroidal blood flow in response to some of these NP’s. However, since flow is a function of both pressure and resistance (either of which may vary), we were not able to determine with certainty whether the NP’s had a direct effect on the vascular smooth muscle of the thyroid vessels. We address this issue in the present communication, and we also consider the route by which the NP-containing fibers might reach the thyroid by measuring blood flow and hormone secretion in superior cervical ganglionectomized (SCGX) rats.

Keywords

Thyroid Hormone Vasoactive Intestinal Peptide Superior Cervical Ganglion Plasma Thyroid Hormone Thyroid Hormone Secretion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Springer Science+Business Media New York 1986

Authors and Affiliations

  • George A. Hedge
    • 1
  • Linda Huffman
    • 1
  • John M. Connors
    • 1
  1. 1.Department of PhysiologyWest Virginia University Medical CenterMorgantownUSA

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