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Cited by 237

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

SUSPENDED ANIMATION-LIKE STATE PROTECTS MICE FROM LETHAL HYPOXIA

Blackstone, Eric, Roth, Mark B.·2007·Shock

Abstract

Joseph Priestley observed the high burn rate of candles in pure oxygen and wondered if people would "live out too fast" if we were in the same environment. We hypothesize that sulfide, a natural reducer of oxygen that is made in many cell types, acts as a buffer to prevent unrestricted oxygen consumption. To test this, we administered sulfide in the form of hydrogen sulfide (H2S) to mice (Mus musculus). As we have previously shown, H2S decreases the metabolic rate of mice by approximately 90% and induces a suspended animation-like state. Mice cannot survive for longer than 20 min when exposed to 5% oxygen. However, if mice are first put into a suspended animation-like state by a 20-min pretreatment with H2S and then are exposed to low oxygen, they can survive for more than 6.5 h in 5% oxygen with no apparent detrimental effects. In addition, if mice are exposed to a 20-min pretreatment with H2S followed by 1 h at 5% oxygen, they can then survive for several hours at oxygen tensions as low as 3%. We hypothesize that prior exposure to H2S reduces oxygen demand, therefore making it possible for the mice to survive with low oxygen supply. These results suggest that H2S may be useful to prevent damage associated with hypoxia.

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Metadata

Authors
Blackstone, E., & Roth, M. B.
Venue
Shock
Published
2007-04
Volume
27
Issue
4
Pages
370-372
ISSN
1073-2322 (ISSN-L)
OpenAlex
W2079498607
Cited by
237
References
2
FWCI
9.67
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: SUSPENDED ANIMATION-LIKE STATE PROTECTS MICE FROM LETHAL HYPOXIA. https://app.cochat.ai/papers/10.1097/shk.0b013e31802e27a0
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Blackstone, E., & Roth, M. B. (2007). SUSPENDED ANIMATION-LIKE STATE PROTECTS MICE FROM LETHAL HYPOXIA. Shock. https://doi.org/10.1097/shk.0b013e31802e27a0

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