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Record W3030139701 · doi:10.3390/ani10060950

Aversion to Desflurane and Isoflurane in Sprague-Dawley Rats (Rattus norvegicus)

2020· article· en· W3030139701 on OpenAlexafffund
Katrina Frost, Maaria Shah, Vivian SY Leung, Daniel Pang

Bibliographic record

VenueAnimals · 2020
Typearticle
Languageen
FieldVeterinary
TopicAnimal testing and alternatives
Canadian institutionsUniversité de MontréalUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDesfluraneIsofluraneAnesthesiaIntoxicative inhalantAnestheticMedicineSalineToxicologyBiology

Abstract

fetched live from OpenAlex

Carbon dioxide and isoflurane are widely used for killing rats, yet may not truly achieve “euthanasia”, because they elicit aversion. The inhalant anesthetic desflurane is faster acting than isoflurane, representing a potential refinement. Using an aversion-avoidance paradigm, 24 rats were exposed to isoflurane or desflurane (n = 12 per group) at initial exposure. Fourteen rats were then re-exposed to isoflurane or desflurane (n = 7 per group), after a 7 days washout period. Initial exposure: time to recumbency was faster for desflurane than isoflurane (p = 0.0008, 95% CI [-12.9 to 32.6 s]), with 9/12 and 6/12 rats becoming recumbent, respectively. At initial exposure, there was no difference between groups in time to withdrawal (p = 0.714). At re-exposure, all rats withdrew and no rats became recumbent. Time to withdrawal at re-exposure did not differ between treatment groups (p = 0.083). Compared to initial exposure, time to withdrawal during re-exposure was similar for isoflurane (p = 0.228) and faster with desflurane (p = 0.012, 95% CI [19.1 to 49.5 s]). Isoflurane and desflurane are similarly aversive, with aversion increasing at re-exposure. The shorter time from exposure to recumbency with desflurane indicates that any distress is of a shorter duration when compared with isoflurane.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.215
GPT teacher head0.389
Teacher spread0.174 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2020
Admission routes2
Has abstractyes

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