The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Central Mechanisms for Thermoregulation
Abstract
Maintenance of a homeostatic body core temperature is a critical brain function accomplished by a central neural network. This orchestrates a complex behavioral and autonomic repertoire in response to environmental temperature challenges or declining energy homeostasis and in support of immune responses and many behavioral states. This review summarizes the anatomical, neurotransmitter, and functional relationships within the central neural network that controls the principal thermoeffectors: cutaneous vasoconstriction regulating heat loss and shivering and brown adipose tissue for heat production. The core thermoregulatory network regulating these thermoeffectors consists of parallel but distinct central efferent pathways that share a common peripheral thermal sensory input. Delineating the neural circuit mechanism underlying central thermoregulation provides a useful platform for exploring its functional organization, elucidating the molecular underpinnings of its neuronal interactions, and discovering novel therapeutic approaches to modulating body temperature and energy homeostasis.
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Cites
How do you feel? Interoception: The sense of the physiological condition of the body
Craig, A. D. (2002) · Nature Reviews Neuroscience · doi:10.1038/nrn894 · Cited by 6,006
Thermoregulation: some concepts have changed. Functional architecture of the thermoregulatory system
Romanovsky, A. A. (2007) · American Journal of Physiology-Regulatory, Integrative and Comparative Physiology · doi:10.1152/ajpregu.00668.2006 · Cited by 786
Impaired febrile response in mice lacking the prostaglandin E receptor subtype EP3
Ushikubi, F., Segi, E., Sugimoto, Y., Murata, T., Matsuoka, T., Kobayashi, T., Hizaki, H., Tuboi, K., Katsuyama, M., Ichikawa, A., et al. (1998) · Nature · doi:10.1038/26233 · Cited by 677
Central circuitries for body temperature regulation and fever
Nakamura, K. (2011) · American Journal of Physiology-Regulatory, Integrative and Comparative Physiology · doi:10.1152/ajpregu.00109.2011 · Cited by 543
Self-citationWarm-Sensitive Neurons that Control Body Temperature
Tan, C. L., Cooke, E. K., Leib, D. E., Lin, Y.-C., Daly, G. E., Zimmerman, C. A., & Knight, Z. A. (2016) · Cell · doi:10.1016/j.cell.2016.08.028 · Cited by 402
Romanovsky, A. A., Ivanov, A. I., & Shimansky, Y. P. (2002) · Journal of Applied Physiology · doi:10.1152/japplphysiol.01173.2001 · Cited by 351
Tupone, D., Madden, C. J., Cano, G., & Morrison, S. F. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.3909-11.2011 · Cited by 228
Human Brown Adipose Tissue: What We Have Learned So Far
Betz, M. J., & Enerbäck, S. (2015) · Diabetes · doi:10.2337/db15-0146 · Cited by 223
Zaretskaia, M. V., Zaretsky, D. V., Shekhar, A., & DiMicco, J. A. (2002) · Brain Research · doi:10.1016/s0006-8993(01)03369-8 · Cited by 173
Parallel preoptic pathways for thermoregulation
Yoshida, K., Li, X., Cano, G., Lazarus, M., & Saper, C. B. (2009) · The Journal of Neuroscience · doi:10.1523/jneurosci.2643-09.2009 · Cited by 160
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Baker, F. C., Siboza, F., & Fuller, A. (2020) · Temperature · doi:10.1080/23328940.2020.1735927 · Cited by 262
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Chen, A., Sun, Y., Lei, Y., Li, C., Liao, S., Meng, J., Bai, Y., Liu, Z., Liang, Z., Zhu, Z., et al. (2023) · Cell · doi:10.1016/j.cell.2023.06.009 · Cited by 232
Hypothalamic control of energy expenditure and thermogenesis
Tran, L. T., Park, S., Kim, S. K., Lee, J. S., Kim, K. W., & Kwon, O. (2022) · Experimental & Molecular Medicine · doi:10.1038/s12276-022-00741-z · Cited by 208
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Tan, M., Xu, Y., Gao, Z., Yuan, T., Liu, Q., Yang, R., Zhang, B., & Peng, L. (2022) · Advanced Materials · doi:10.1002/adma.202108491 · Cited by 187
The physiological control of eating: signals, neurons, and networks
Watts, A. G., Kanoski, S. E., Sanchez-Watts, G., & Langhans, W. (2022) · Physiological Reviews · doi:10.1152/physrev.00028.2020 · Cited by 168
Nguyen, T., Wen, S., Gong, M., Yuan, X., Xu, D., Wang, C., Jin, J., & Zhou, L. (2020) · Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy · doi:10.2147/dmso.s258593 · Cited by 97
Diurnal rhythms of wrist temperature are associated with future disease risk in the UK Biobank
Brooks, T. G., Lahens, N. F., Grant, G. R., Sheline, Y. I., FitzGerald, G. A., & Skarke, C. (2023) · Nature Communications · doi:10.1038/s41467-023-40977-5 · Cited by 57
microRNA-33 maintains adaptive thermogenesis via enhanced sympathetic nerve activity
Horie, T., Nakao, T., Miyasaka, Y., Nishino, T., Matsumura, S., Nakazeki, F., Ide, Y., Kimura, M., Tsuji, S., Rodriguez, R. R., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-21107-5 · Cited by 49
Self-citationAn mPOA-ARCAgRP pathway modulates cold-evoked eating behavior
Yang, S., Tan, Y. L., Wu, X., Wang, J., Sun, J., Liu, A., Gan, L., Shen, B., Zhang, X., Fu, Y., et al. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109502 · Cited by 44
Pharmacological hypotheses: Is acetaminophen selective in its cyclooxygenase inhibition?
Esh, C. J., Chrismas, B. C. R., Mauger, A. R., & Taylor, L. (2021) · Pharmacology Research & Perspectives · doi:10.1002/prp2.835 · Cited by 38
Wei, H.-H., Yuan, X.-S., Chen, Z.-K., Chen, P.-P., Xiang, Z., Qu, W.-M., Li, R.-X., Zhou, G.-M., & Huang, Z.-L. (2021) · Experimental Neurology · doi:10.1016/j.expneurol.2021.113784 · Cited by 29
Metadata
- Authors
- Morrison, S. F., & Nakamura, K.
- Venue
- Annual Review of Physiology
- Publisher
- Annual Reviews
- Published
- 2019-02-10
- Volume
- 81
- Issue
- 1
- Pages
- 285-308
- ISSN
- 0066-4278 (ISSN-L)
- 1545-1585
- OpenAlex
- W2893551963
- Cited by
- 573
- References
- 11
- FWCI
- 5.47
- Type
- journal article
- Language
- en
- Open access
- closed
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